MTA3 regulates CGB5 and Snail genes in trophoblast

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Ying; Miyazaki, Jun; Division of Molecular Genetics, Institute for Comprehensive Medical Science, Fujita Health University, Toyoake

Highlights: •Impaired MTA3, raised CGB5 and Snail expression are associated with preeclampsia. •Knock-down of MTA3 causes up-regulation of CGB5 and Snail genes in BeWo cells. •MTA3 occupies CGB5 and Snail gene promoters in BeWo cells. -- Abstract: Secreted by the placental trophoblast, human chorionic gonadotropin (hCG) is an important hormone during pregnancy and is required for the maintenance of pregnancy. Previous studies have shown that dys-regulation of hCG expression is associated with preeclampsia. However, the exact relationship between altered hCG levels and development of preeclampsia is unknown. Metastasis associated protein 3 (MTA3), a chromatin remodeling protein, is abundantly expressed inmore » the placental trophoblasts, but its function is unknown. In breast cancer, MTA3 has been shown to repress the expression of Snail and cell migration. However, whether MTA3 acts similarly in the trophoblast has not been investigated. In the present study, we examined the role of MTA3 in regulating the hCG β-subunit gene (gene name: CGB5) and Snail expression in the trophoblast cell line, BeWo, as well as its relevance to the high hCG expression levels seen in preeclampsia. First, we investigated MTA3 expression in preeclamptic placenta as compared to normal control placenta via gene expression microarray and qRT-PCR and found that MTA3 was significantly down-regulated, whereas both CGB5 and Snail were up-regulated in preeclamptic placenta. Secondly, we knocked down MTA3 gene in trophoblast cell line BeWo and found Snail and hCG were both up-regulated, suggesting that MTA3 represses Snail and hCG gene expression in trophoblasts. Next, we cloned the CGB5 and Snail promoters into the pGL3-basic vector individually and found that silencing of MTA3 by siRNA resulted in an increase of both CGB5 and Snail promoter activities. To confirm that this MTA3 inhibition is a direct effect, we performed a chromatin immune-precipitation (ChIP) assay and found that MTA3 occupied the proximal promoter regions of both Snail and hCG within BeWo cells. Furthermore, we examined MTA3 expression in placental trophoblast by immunohistochemistry and found that MTA3 expression was higher in villous cytotrophoblasts versus syncytiotrophoblasts, which supports an inverse association of MTA3 with hCG expression. Lastly, using the well-characterized trophoblast fusion model, we examined MTA3 and hCG levels in forskolin-treated BeWo cells and found that MTA3 down-regulation was accompanied by an up-regulation of hCG. These data further suggest that MTA3 is repressing placental hCG expression. In summary, MTA3 plays a critical role in repressing hCG and Snail in placenta trophoblast and its deregulation is associated with preeclampsia.« less

Effects of phytoestrogens on the trophoblast tumour cell lines BeWo and Jeg3.

PubMed

Plessow, D; Waldschläger, J; Richter, D U; Jeschke, U; Bruer, G; Briese, V; Friese, K

2003-01-01

Phytoestrogens are a diverse group of nonsteroidal plant compounds that occur naturally in many plants. Because they possess a ring system similar to estrogens they are able to bind to estrogen receptors in humans. With this study we tested the effects of the phytoestrogens genistein and daidzein in cell proliferation and the production of progesterone and hCG in trophoblast tumour cells of the cell lines BeWo and Jeg3. The phytoestrogens genistein and daidzein were incubated in different concentrations with trophoblast tumour cells. Untreated cells were used as controls. At designated times, aliquots were removed and tested for progesterone and hCG. In addition we tested the effects of phytoestrogens on cell proliferation. Different concentrations of genistein and daidzein were cultivated with trophoblast tumour cells. After designated times, 1 microCi thymidin-(methyl-3H) was added. Methyl-3H thymidin incorporation was tested and compared to incorporation results of untreated cells. With this study we could show that the production of the steroid hormone progesterone and the protein hormone hCG is influenced by the phytoestrogens genistein and daidzein in trophoblast tumour cells of the cell lines BeWo and Jeg3. We found a correlation between the effects on the proliferation and the production of progesterone and hCG at high concentrations of genistein and daidzein in the cell lines tested. With low concentrations of genistein and daidzein we observed a stimulation of the production of hCG and a weak inhibition of proliferation in both cell lines BeWo and Jeg3. The results obtained with this study suggest that only high doses of phytoestrogens (> 1 mumol/ml) can reduce the proliferation of trophoblast tumour cells significantly. Low doses of phytoestrogens induced a higher hCG production in both cell lines tested. Although high hCG production did not lead to a higher proliferation rate of the tumour cells tested, hCG is able to induce neovascularisation in tumour cells. In summary, with this in vitro study we showed that high doses of phytoestrogens inhibit proliferation and progesterone production in trophoblast tumour cells. High doses of phytoestrogens could be useful candidates for special diet programs for prevention and surgery for patients with this type of disease. In addition we found a useful cell culture model for the testing of new types of phytoestrogens.

Placental Sequestration of Plasmodium falciparum Malaria Parasites Is Mediated by the Interaction Between VAR2CSA and Chondroitin Sulfate A on Syndecan-1

PubMed Central

Mao, Yang; Resende, Mafalda; Daugaard, Mads; Riis Kristensen, Anders; Damm, Peter; G. Theander, Thor; R. Hansson, Stefan; Salanti, Ali

2016-01-01

During placental malaria, Plasmodium falciparum infected erythrocytes sequester in the placenta, causing health problems for both the mother and fetus. The specific adherence is mediated by the VAR2CSA protein, which binds to placental chondroitin sulfate (CS) on chondroitin sulfate proteoglycans (CSPGs) in the placental syncytium. However, the identity of the CSPG core protein and the cellular impact of the interaction have remain elusive. In this study we identified the specific CSPG core protein to which the CS is attached, and characterized its exact placental location. VAR2CSA pull-down experiments using placental extracts from whole placenta or syncytiotrophoblast microvillous cell membranes showed three distinct CSPGs available for VAR2CSA adherence. Further examination of these three CSPGs by immunofluorescence and proximity ligation assays showed that syndecan-1 is the main receptor for VAR2CSA mediated placental adherence. We further show that the commonly used placental choriocarcinoma cell line, BeWo, express a different set of proteoglycans than those present on placental syncytiotrophoblast and may not be the most biologically relevant model to study placental malaria. Syncytial fusion of the BeWo cells, triggered by forskolin treatment, caused an increased expression of placental CS-modified syndecan-1. In line with this, we show that rVAR2 binding to placental CS impairs syndecan-1-related Src signaling in forskolin treated BeWo cells, but not in untreated cells. PMID:27556547

Progesterone Inhibits Leptin-Induced Invasiveness of BeWo Cells.

PubMed

Jo, Yun Sung; Lee, Gui Se Ra; Nam, Sun Young; Kim, Sa Jin

2015-01-01

This study investigated the roles of progesterone and leptin in placenta invasion, which is closely related to pregnancy prognosis. We examined the effects of leptin and progesterone on the invasion of BeWo cells, a human trophoblastic cell line, and the effect of concurrent treatment. Cells were treated with leptin (0, 5, 50, or 500 ng/mL) or progesterone (0, 2, 20, or 200 µM) and cultured in an invasion assay. Cells treated with 500 ng/mL leptin were also treated with progesterone (0, 2, 20, or 200 µM) in the invasion assay for 48 h. The number of cells that invaded the lower surface was counted in five randomly chosen fields using a light microscope with a 200× objective. The mRNA expression levels of MMP-9, TIMP1, TIMP2, and E-cadherin were detected by semi-quantitative PCR. Invasion of BeWo cells was promoted by leptin and influenced by both leptin concentration and treatment duration. Invasion was most effective at 500 ng/mL leptin and 48 h culture. Leptin-induced invasiveness was suppressed by progesterone in a dose-dependent manner. Leptin significantly decreased the expression levels of TIMP1 and E-cadherin, whereas progesterone significantly decreased expression of MMP-9 and significantly increased levels of TIMP1, TIMP2, and E-cadherin. Leptin promotes invasion of BeWo cells, and progesterone suppresses leptin-induced invasion by regulating the expressions of MMP-9, TIMP1, TIMP2, and E-cadherin. The balance between leptin and progesterone may play an important role in human placenta formation during early pregnancy.

TAAR1 induces a disturbed GSK3β phosphorylation in recurrent miscarriages through the ODC

PubMed Central

Stavrou, Stavroula; Gratz, Michael; Tremmel, Eileen; Kuhn, Christina; Hofmann, Simone; Heidegger, Helene; Peryanova, Mina; Hermelink, Kerstin; Hutter, Stefan; Toth, Bettina; Mayr, Doris; Mahner, Sven; Jeschke, Udo; Vattai, Aurelia

2018-01-01

Objectives Thyroid hormones play an important role in the maintenance of pregnancy. Their derivates, endogenous amines, act via binding to the trace amine-associated receptor (TAAR1). The aim of our study was to analyse the regulation of TAAR1, serine/threonine kinase (pGSK3β) and ornithine decarboxylase (ODC) in placentas of healthy pregnancies, spontaneous (SM) and recurrent miscarriages (RM) and to investigate the influence of thyroid hormone derivates on TAAR1 expression in trophoblast model cells in vitro. Methods Patients with SM (n = 15) and RM (n = 15) were compared with patients with healthy pregnancies (n = 15) (pregnancy weeks 7–13 each). Immunohistochemistry was applied to analyse placental TAAR1, pGSK3β and ODC expression. Protein expression of the receptors after stimulation with T3, T1AM and RO5203548 in BeWo trophoblast model cells was determined via Western blot. Double-immunofluorescence was used to determine placental expression of TAAR1 and ODC. Results Levels of TAAR1, pGSK3β and ODC were higher in placentas of RM in comparison to healthy controls. Stimulation of BeWo cells with T3, T1AM and RO5203548 significantly increased TAAR1 expression. ODC expression in BeWo cells was upregulated through T3. Via double-immunofluorescence, TAAR1 and ODC-positive EVT could be detected. Conclusions Upregulation of placental TAAR1 may indicate an increased decarboxylation of thyroid hormones in miscarriages. Patients with RM may have a lack of T3 through an enhanced transformation of T3 into T1AM induced by the ODC. Future investigations could be carried out to analyse what role a prophylactic T3 substitution plays for patients. PMID:29472377

Genetic and Dietary Regulation of Glyburide Efflux by the Human Placental Breast Cancer Resistance Protein Transporter

PubMed Central

Bircsak, Kristin M.; Gupta, Vivek; Yuen, Poi Yu Sofia; Gorczyca, Ludwik; Weinberger, Barry I.; Vetrano, Anna M.

2016-01-01

Glyburide is frequently used to treat gestational diabetes owing to its low fetal accumulation resulting from placental efflux by the breast cancer resistance protein (BCRP)/ABCG2 transporter. Here we sought to determine how exposure to the dietary phytoestrogen genistein and expression of a loss-of-function polymorphism in the ABCG2 gene (C421A) impacted the transport of glyburide by BCRP using stably transfected human embryonic kidney 293 (HEK) cells, human placental choriocarcinoma BeWo cells, and human placental explants. Genistein competitively inhibited the BCRP-mediated transport of 3H-glyburide in both wild-type (WT) and C421A-BCRP HEK-expressing cells, with greater accumulation of 3H-glyburide in cells expressing the C421A variant. In BeWo cells, exposure to genistein for 60 minutes increased the accumulation of 3H-glyburide 30%–70% at concentrations relevant to dietary exposure (IC50 ∼180 nM). Continuous exposure of BeWo cells to genistein for 48 hours reduced the expression of BCRP mRNA and protein by up to 40%, which impaired BCRP transport activity. Pharmacologic antagonism of the estrogen receptor attenuated the genistein-mediated downregulation of BCRP expression, suggesting that phytoestrogens may reduce BCRP levels through this hormone receptor pathway in BeWo cells. Interestingly, genistein treatment for 48 hours did not alter BCRP protein expression in explants dissected from healthy term placentas. These data suggest that whereas genistein can act as a competitive inhibitor of BCRP-mediated transport, its ability to downregulate placental BCRP expression may only occur in choriocarcinoma cells. Overall, this research provides important mechanistic data regarding how the environment (dietary genistein) and a frequent genetic variant (ABCG2, C421A) may alter the maternal-fetal disposition of glyburide. PMID:26850786

Uptake mechanism of valproic acid in human placental choriocarcinoma cell line (BeWo).

PubMed

Ushigome, F; Takanaga, H; Matsuo, H; Tsukimori, K; Nakano, H; Ohtani, H; Sawada, Y

2001-04-13

Valproic acid is an anticonvulsant widely used for the treatment of epilepsy. However, valproic acid is known to show fetal toxicity, including teratogenicity. In the present study, to elucidate the mechanisms of valproic acid transport across the blood-placental barrier, we carried out transcellular transport and uptake experiments with human placental choriocarcinoma epithelial cells (BeWo cells) in culture. The permeability coefficient of [3H]valproic acid in BeWo cells for the apical-to-basolateral flux was greater than that for the opposite flux, suggesting a higher unidirectional transport in the fetal direction. The uptake of [3H]valproic acid from the apical side was temperature-dependent and enhanced under acidic pH. In the presence of 50 microM carbonyl cyanide p-trifluoromethoxylhydrazone, the uptake of [3H]valproic acid was significantly reduced. A metabolic inhibitor, 10 mM sodium azide, also significantly reduced the uptake of [3H]valproic acid. Therefore, valproic acid is actively transported in a pH-dependent manner on the brush-border membrane of BeWo cells. Kinetic analysis of valproic acid uptake revealed the involvement of a non-saturable component and a saturable component. The Michaelis constant for the saturable transport (K(t)) was smaller under acidic pH, suggesting a proton-linked active transport mechanism for valproic acid in BeWo cells. In the inhibitory experiments, some short-chain fatty acids, such as acetic acid, lactic acid, propanoic acid and butyric acid, and medium-chain fatty acids, such as hexanoic acid and octanoic acid, inhibited the uptake of [3H]valproic acid. The uptake of [3H]valproic acid was also significantly decreased in the presence of 4,4'-diisothiocyanatostilbene-2,2'-disulfonic acid, salicylic acid and furosemide, which are well-known inhibitors of the anion exchange system. Moreover, p-aminohippuric acid significantly reduced the uptake of [3H]valproic acid. These results suggest that an active transport mechanism for valproic acid exists on the brush-border membrane of placental trophoblast cells and operates in a proton-linked manner.

The human leukocyte antigen G promotes trophoblast fusion and β-hCG production through the Erk1/2 pathway in human choriocarcinoma cell lines

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Ji-meng; State Key Laboratory of Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101; Zhao, Hong-xi

2013-05-10

Highlights: •HLA-G expression promotes BeWo cells fusion and fusogenic gene expression. •HLA-G is capable of inducing β-hCG production in human choriocarcinoma cell lines. •Up-regulation of β-hCG production by HLA-G is mediated via the Erk1/2 pathway. -- Abstract: The human leukocyte antigen G (HLA-G) is expressed on the fetal–maternal interface and plays a role in protecting fetal-derived trophoblasts from the maternal immune response, allowing trophoblasts to invade the uterus. However, HLA-G also possesses immune suppressing-independent functions. We found that HLA-G expressing BeWo choriocarcinoma cells increased cell–cell fusion compared to control BeWo cells under forskolin treatment. Regardless of forskolin treatment, the expressionmore » of fusogenic gene mRNAs, including syncytin-1, the transcription factor glial cell missing 1 (Gcm1), and beta human chorionic gonadotropin (β-hCG) were elevated. HLA-G up-regulates β-hCG production in human choriocarcinoma cells because HLA-G knockdown in JEG-3 cells induces a dramatic decrease in β-hCG compared with control cells. The defect in β-hCG production in HLA-G knocked-down cells could not be completely overcome by stimulating hCG production through increasing intracellular cAMP levels. HLA-G expressing cells have increased phosphorylation levels for extracellular signal-regulated kinase1/2 (Erk1/2) in BeWo cells. The Erk1/2 pathway is inactivated after the inhibition of HLA-G expression in JEG-3 cells. Finally, Erk1/2 inhibition was able to suppress the increased hCG production induced by HLA-G expression. Together, these data suggest novel roles for HLA-G in regulating β-hCG production via the modulation of the Erk1/2 pathway and by inducing trophoblast cell fusion.« less

Long-term forskolin stimulation induces AMPK activation and thereby enhances tight junction formation in human placental trophoblast BeWo cells.

PubMed

Egawa, M; Kamata, H; Kushiyama, A; Sakoda, H; Fujishiro, M; Horike, N; Yoneda, M; Nakatsu, Y; Ying, Guo; Jun, Zhang; Tsuchiya, Y; Takata, K; Kurihara, H; Asano, T

2008-12-01

BeWo cells, derived from human choriocarcinoma, have been known to respond to forskolin or cAMP analogues by differentiating into multinucleated cells- like syncytiotrophoblasts on the surfaces of chorionic villi of the human placenta. In this study, we demonstrated that long-term treatment with forskolin enhances the tight junction (TJ) formation in human placental BeWo cells. Interestingly, AMPK activation and phosphorylation of acetyl-CoA carboxylase (ACC), a molecule downstream from AMPK, were induced by long-term incubation (>12h) with forskolin, despite not being induced by acute stimulation with forskolin. In addition, co-incubation with an AMPK inhibitor, compound C, as well as overexpression of an AMPK dominant negative mutant inhibited forskolin-induced TJ formation. Thus, although the molecular mechanism underlying AMPK activation via the forskolin stimulation is unclear, the TJ formation induced by forskolin is likely to be mediated by the AMPK pathway. Taking into consideration that TJs are present in the normal human placenta, this mechanism may be important for forming the placental barrier system between the fetal and maternal circulations.

Role of microRNA-130b in placental PGC-1α/TFAM mitochondrial biogenesis pathway

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jiang, Shaoning; Teague, April M.; Tryggestad, Jeanie B.

Diabetes during pregnancy is associated with abnormal placenta mitochondrial function and increased oxidative stress, which affect fetal development and offspring long-term health. Peroxisome proliferator-activated receptor-γ coactivator-1α (PGC-1α) is a master regulator of mitochondrial biogenesis and energy metabolism. The molecular mechanisms underlying the regulation of PGC-1α in placenta in the context of diabetes remain unclear. The present study examined the role of microRNA 130b (miR-130b-3p) in regulating PGC-1α expression and oxidative stress in a placental trophoblastic cell line (BeWo). Prolonged exposure of BeWo cells to high glucose mimicking hyperglycemia resulted in decreased protein abundance of PGC-1α and its downstream factor, mitochondrialmore » transcription factor A (TFAM). High glucose treatment increased the expression of miR-130b-3p in BeWo cells, as well as exosomal secretion of miR-130b-3p. Transfection of BeWo cells with miR-130b-3p mimic reduced the abundance of PGC-1α, whereas inhibition of miR-130b-3p increased PGC-1α expression in response to high glucose, suggesting a role for miR-130b-3p in mediating high glucose-induced down regulation of PGC-1α expression. In addition, miR-130b-3p anti-sense inhibitor increased TFAM expression and reduced 4-hydroxynonenal (4-HNE)-induced production of reactive oxygen species (ROS). Taken together, these findings reveal that miR-130b-3p down-regulates PGC-1α expression in placental trophoblasts, and inhibition of miR-130b-3p appears to improve mitochondrial biogenesis signaling and protect placental trophoblast cells from oxidative stress. - Highlights: • High glucose reduces PGC-1α and TFAM proteins in trophoblast BeWo cells. • miR-130b-3p mediates high glucose-induced decrease in PGC-1α abundance. • Inhibition of miR-130b-3p improves mitochondrial biogenesis signaling. • Inhibition of miR-130b-3p protects trophoblasts against oxidative stress.« less

Human parvovirus B19 antibodies induce altered membrane protein expression and apoptosis of BeWo trophoblasts.

PubMed

Tzang, Bor-Show; Chiang, Szu-Yi; Chan, Hsu-Chin; Liu, Chung-Hsien; Hsu, Tsai-Ching

2016-11-01

Human parvovirus B19 (B19) is harmful during pregnancy since it can be vertically transmitted to the developing fetus. In addition, the anti‑B19 antibodies induced by B19 infection are believed to have a cytopathic role in B19 transmission; however, knowledge regarding the effects of anti‑B19 antibodies during pregnancy is limited. To investigate the possible roles of anti‑B19 antibodies during pregnancy, the present study examined the effects of anti‑B19‑VP1 unique region (VP1u), anti‑B19‑VP2 and anti‑B19‑nonstructural protein 1 (NS1) immunoglobulin G (IgG) antibodies on BeWo trophoblasts. Briefly, BeWo trophoblasts were incubated with purified IgG against B19‑VP1u, B19‑VP2 and B19‑NS1. Subsequently, the expression of surface proteins and apoptotic molecules were assessed in BeWo trophoblasts using flow cytometry, ELISA and western blotting. The expression levels of human leukocyte antigen (HLA)‑G were significantly increased on BeWo trophoblasts treated with rabbit anti‑B19‑VP1u IgG, and were unchanged in those treated with rabbit anti‑B19‑NS1 and anti‑B19‑VP2 IgG, as compared with the control group. Furthermore, the expression levels of globoside (P blood group antigen) and cluster of differentiation (CD)29 (β1 integrin) were significantly increased in BeWo trophoblasts treated with rabbit anti‑B19‑NS1 and anti‑B19‑VP2 IgG, whereas only CD29 was also significantly increased in cells treated with anti‑B19‑VP1u IgG. In addition, the number of cells at sub‑G1 phase; caspase‑3 activity; and the expression of intrinsic and extrinsic apoptotic molecules, including Fas‑associated death domain protein, activated caspase‑8, activated caspase‑3, B‑cell lymphoma 2‑associated X protein, cytochrome c, apoptotic peptidase activating factor 1 and activated caspase‑9, were significantly increased in BeWo trophoblasts treated with anti‑B19‑VP1u and anti‑B19‑NS1 IgG. In conclusion, the present study demonstrated that antibodies against B19 may have a crucial role in pathological processes during pregnancy. These findings may help to elucidate the mechanisms underlying transmission of the B19 virus during pregnancy.

Bisphenol A increases BeWo trophoblast survival in stress-induced paradigms through regulation of oxidative stress and apoptosis.

PubMed

Ponniah, Muralitharan; Billett, E Ellen; De Girolamo, Luigi A

2015-09-21

Bisphenol A (BPA) is ubiquitous in the environment and is reported to be present at high concentrations in placental tissue, where its presence raises concerns over its potential to disrupt placental function. This report investigates how BPA interferes with the survival of human choriocarcinoma BeWo cells (a model of placental trophoblasts) under stress-induced paradigms reminiscent of pathways activated in placental development. These include conditions that promote oxidative stress (glutathione depletion) and apoptosis (serum withdrawal) or mimic hypoxia (HIF-1α accumulation via dimethyloxalylglycine treatment). Treatment of BeWo cells with BPA during stress-induced paradigms led to a consistent and significant increase in cell viability, with a concomitant increase in glutathione levels and a reduction in apoptosis. Assessment of the antioxidant capacity of BPA revealed its ability to quench reactive oxygen species and reduce the levels generated during glutathione and serum depletion. BPA was also able to reduce the activation of the antioxidant response element (ARE) through mediation of its activators, nuclear factor erythroid related factor family members (Nrf's). Indeed, the expression and nuclear translocation of Nrf2 (an important ARE activator) were impaired by BPA, while Nrf1 and Nrf3 expression levels were increased. Furthermore, BPA increased the levels of the anti-apoptotic proteins (Bcl-2 and Hsp70) and decreased HIF-1α levels during stress-induced conditions. Together, these results indicate that BPA inhibits trophoblast cell death under conditions of cellular stress. This could have implications on placental trophoblasts during development.

Genetic and Dietary Regulation of Glyburide Efflux by the Human Placental Breast Cancer Resistance Protein Transporter.

PubMed

Bircsak, Kristin M; Gupta, Vivek; Yuen, Poi Yu Sofia; Gorczyca, Ludwik; Weinberger, Barry I; Vetrano, Anna M; Aleksunes, Lauren M

2016-04-01

Glyburide is frequently used to treat gestational diabetes owing to its low fetal accumulation resulting from placental efflux by the breast cancer resistance protein (BCRP)/ABCG2 transporter. Here we sought to determine how exposure to the dietary phytoestrogen genistein and expression of a loss-of-function polymorphism in the ABCG2 gene (C421A) impacted the transport of glyburide by BCRP using stably transfected human embryonic kidney 293 (HEK) cells, human placental choriocarcinoma BeWo cells, and human placental explants. Genistein competitively inhibited the BCRP-mediated transport of (3)H-glyburide in both wild-type (WT) and C421A-BCRP HEK-expressing cells, with greater accumulation of (3)H-glyburide in cells expressing the C421A variant. In BeWo cells, exposure to genistein for 60 minutes increased the accumulation of (3)H-glyburide 30%-70% at concentrations relevant to dietary exposure (IC50 ∼180 nM). Continuous exposure of BeWo cells to genistein for 48 hours reduced the expression of BCRP mRNA and protein by up to 40%, which impaired BCRP transport activity. Pharmacologic antagonism of the estrogen receptor attenuated the genistein-mediated downregulation of BCRP expression, suggesting that phytoestrogens may reduce BCRP levels through this hormone receptor pathway in BeWo cells. Interestingly, genistein treatment for 48 hours did not alter BCRP protein expression in explants dissected from healthy term placentas. These data suggest that whereas genistein can act as a competitive inhibitor of BCRP-mediated transport, its ability to downregulate placental BCRP expression may only occur in choriocarcinoma cells. Overall, this research provides important mechanistic data regarding how the environment (dietary genistein) and a frequent genetic variant (ABCG2, C421A) may alter the maternal-fetal disposition of glyburide. Copyright © 2016 by The American Society for Pharmacology and Experimental Therapeutics.

Effects of Phytoestrogen Extracts Isolated from Elder Flower on Hormone Production and Receptor Expression of Trophoblast Tumor Cells JEG-3 and BeWo, as well as MCF7 Breast Cancer Cells

PubMed Central

Schröder, Lennard; Richter, Dagmar Ulrike; Piechulla, Birgit; Chrobak, Mareike; Kuhn, Christina; Schulze, Sandra; Abarzua, Sybille; Jeschke, Udo; Weissenbacher, Tobias

2016-01-01

Herein we investigated the effect of elderflower extracts (EFE) and of enterolactone/enterodiol on hormone production and proliferation of trophoblast tumor cell lines JEG-3 and BeWo, as well as MCF7 breast cancer cells. The EFE was analyzed by mass spectrometry. Cells were incubated with various concentrations of EFE. Untreated cells served as controls. Supernatants were tested for estradiol production with an ELISA method. Furthermore, the effect of the EFE on ERα/ERβ/PR expression was assessed by immunocytochemistry. EFE contains a substantial amount of lignans. Estradiol production was inhibited in all cells in a concentration-dependent manner. EFE upregulated ERα in JEG-3 cell lines. In MCF7 cells, a significant ERα downregulation and PR upregulation were observed. The control substances enterolactone and enterodiol in contrast inhibited the expression of both ER and of PR in MCF7 cells. In addition, the production of estradiol was upregulated in BeWo and MCF7 cells in a concentration dependent manner. The downregulating effect of EFE on ERα expression and the upregulation of the PR expression in MFC-7 cells are promising results. Therefore, additional unknown substances might be responsible for ERα downregulation and PR upregulation. These findings suggest potential use of EFE in breast cancer prevention and/or treatment and warrant further investigation. PMID:27740591

Nanoparticle-induced neuronal toxicity across placental barriers is mediated by autophagy and dependent on astrocytes.

PubMed

Hawkins, Simon J; Crompton, Lucy A; Sood, Aman; Saunders, Margaret; Boyle, Noreen T; Buckley, Amy; Minogue, Aedín M; McComish, Sarah F; Jiménez-Moreno, Natalia; Cordero-Llana, Oscar; Stathakos, Petros; Gilmore, Catherine E; Kelly, Stephen; Lane, Jon D; Case, C Patrick; Caldwell, Maeve A

2018-05-01

The potential for maternal nanoparticle (NP) exposures to cause developmental toxicity in the fetus without the direct passage of NPs has previously been shown, but the mechanism remained elusive. We now demonstrate that exposure of cobalt and chromium NPs to BeWo cell barriers, an in vitro model of the human placenta, triggers impairment of the autophagic flux and release of interleukin-6. This contributes to the altered differentiation of human neural progenitor cells and DNA damage in the derived neurons and astrocytes. Crucially, neuronal DNA damage is mediated by astrocytes. Inhibiting the autophagic degradation in the BeWo barrier by overexpression of the dominant-negative human ATG4B C74A significantly reduces the levels of DNA damage in astrocytes. In vivo, indirect NP toxicity in mice results in neurodevelopmental abnormalities with reactive astrogliosis and increased DNA damage in the fetal hippocampus. Our results demonstrate the potential importance of autophagy to elicit NP toxicity and the risk of indirect developmental neurotoxicity after maternal NP exposure.

Nanoparticle-induced neuronal toxicity across placental barriers is mediated by autophagy and dependent on astrocytes

NASA Astrophysics Data System (ADS)

Hawkins, Simon J.; Crompton, Lucy A.; Sood, Aman; Saunders, Margaret; Boyle, Noreen T.; Buckley, Amy; Minogue, Aedín M.; McComish, Sarah F.; Jiménez-Moreno, Natalia; Cordero-Llana, Oscar; Stathakos, Petros; Gilmore, Catherine E.; Kelly, Stephen; Lane, Jon D.; Case, C. Patrick; Caldwell, Maeve A.

2018-05-01

The potential for maternal nanoparticle (NP) exposures to cause developmental toxicity in the fetus without the direct passage of NPs has previously been shown, but the mechanism remained elusive. We now demonstrate that exposure of cobalt and chromium NPs to BeWo cell barriers, an in vitro model of the human placenta, triggers impairment of the autophagic flux and release of interleukin-6. This contributes to the altered differentiation of human neural progenitor cells and DNA damage in the derived neurons and astrocytes. Crucially, neuronal DNA damage is mediated by astrocytes. Inhibiting the autophagic degradation in the BeWo barrier by overexpression of the dominant-negative human ATG4BC74A significantly reduces the levels of DNA damage in astrocytes. In vivo, indirect NP toxicity in mice results in neurodevelopmental abnormalities with reactive astrogliosis and increased DNA damage in the fetal hippocampus. Our results demonstrate the potential importance of autophagy to elicit NP toxicity and the risk of indirect developmental neurotoxicity after maternal NP exposure.

Trypanosoma cruzi infectivity assessment in "in vitro" culture systems by automated cell counting.

PubMed

Liempi, Ana; Castillo, Christian; Cerda, Mauricio; Droguett, Daniel; Duaso, Juan; Barahona, Katherine; Hernández, Ariane; Díaz-Luján, Cintia; Fretes, Ricardo; Härtel, Steffen; Kemmerling, Ulrike

2015-03-01

Chagas disease is an endemic, neglected tropical disease in Latin America that is caused by the protozoan parasite Trypanosoma cruzi. In vitro models constitute the first experimental approach to study the physiopathology of the disease and to assay potential new trypanocidal agents. Here, we report and describe clearly the use of commercial software (MATLAB(®)) to quantify T. cruzi amastigotes and infected mammalian cells (BeWo) and compared this analysis with the manual one. There was no statistically significant difference between the manual and the automatic quantification of the parasite; the two methods showed a correlation analysis r(2) value of 0.9159. The most significant advantage of the automatic quantification was the efficiency of the analysis. The drawback of this automated cell counting method was that some parasites were assigned to the wrong BeWo cell, however this data did not exceed 5% when adequate experimental conditions were chosen. We conclude that this quantification method constitutes an excellent tool for evaluating the parasite load in cells and therefore constitutes an easy and reliable ways to study parasite infectivity. Copyright © 2014 Elsevier B.V. All rights reserved.

Human trophoblast-derived hydrogen sulfide stimulates placental artery endothelial cell angiogenesis.

PubMed

Chen, Dong-Bao; Feng, Lin; Hodges, Jennifer K; Lechuga, Thomas J; Zhang, Honghai

2017-09-01

Endogenous hydrogen sulfide (H2S), mainly synthesized by cystathionine β-synthase (CBS) and cystathionine γ-lyase (CTH), has been implicated in regulating placental angiogenesis; however, the underlying mechanisms are unknown. This study was to test a hypothesis that trophoblasts synthesize H2S to promote placental angiogenesis. Human choriocarcinoma-derived BeWo cells expressed both CBS and CTH proteins, while the first trimester villous trophoblast-originated HTR-8/SVneo cells expressed CTH protein only. The H2S producing ability of BeWo cells was significantly inhibited by either inhibitors of CBS (carboxymethyl hydroxylamine hemihydrochloride, CHH) or CTH (β-cyano-L-alanine, BCA) and that in HTR-8/SVneo cells was inhibited by CHH only. H2S donors stimulated cell proliferation, migration, and tube formation in ovine placental artery endothelial cells (oFPAECs) as effectively as vascular endothelial growth factor. Co-culture with BeWo and HTR-8/SVneo cells stimulated oFPAEC migration, which was inhibited by CHH or BCA in BeWo but CHH only in HTR-8/SVneo cells. Primary human villous trophoblasts (HVT) were more potent than trophoblast cell lines in stimulating oFPAEC migration that was inhibited by CHH and CHH/BCA combination in accordance with its H2S synthesizing activity linked to CBS and CTH expression patterns. H2S donors activated endothelial nitric oxide synthase (NOS3), v-AKT murine thymoma viral oncogene homolog 1 (AKT1), and extracellular signal-activated kinase 1/2 (mitogen-activated protein kinase 3/1, MAPK3/1) in oFPAECs. H2S donor-induced NOS3 activation was blocked by AKT1 but not MAPK3/1 inhibition. In keeping with our previous studies showing a crucial role of AKT1, MAPK3/1, and NOS3/NO in placental angiogenesis, these data show that trophoblast-derived endogenous H2S stimulates placental angiogenesis, involving activation of AKT1, NOS3/NO, and MAPK3/1. © The Authors 2017. Published by Oxford University Press on behalf of Society for the Study of Reproduction. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Progranulin shows cytoprotective effects on trophoblast cells in vitro but does not antagonize TNF-α-induced apoptosis.

PubMed

Stubert, Johannes; Waldmann, Kathrin; Dieterich, Max; Richter, Dagmar-Ulrike; Briese, Volker

2014-11-01

The glycoprotein progranulin directly binds to TNF-receptors and thereby can antagonize the inflammatory effects of TNF-α. Here we analyzed the impact of both cytokines on cytotoxicity and viability of trophoblast cells. Isolated villous first trimester human trophoblast cells and the human choriocarcinoma cell line BeWo were treated with recombinant human progranulin and TNF-α. Analyses were performed by LDH- and MTT-assay and measurement of caspase-8-activity. Progranulin treatment showed some cytoprotective effects on isolated trophoblast cells. However, TNF-α-induced apoptosis was not antagonized by addition of progranulin. Effects were similar, but more pronounced in BeWo cells. The cytoprotective activity of progranulin on trophoblast cells in vitro was only weak and of doubtful biologic relevance. It was not able to antagonize TNF-α. Future studies should focus on possible paracrine activities of progranulin.

The inhibitory effects of fluoroquinolones on L-carnitine transport in placental cell line BeWo.

PubMed

Hirano, Takeshi; Yasuda, Satoru; Osaka, Yuki; Asari, Masaru; Kobayashi, Masaki; Itagaki, Shirou; Iseki, Ken

2008-03-03

L-Carnitine plays an important role in lipid metabolism by facilitating the transport of long-chain fatty acids across the mitochondrial inner membrane followed by fatty acid beta-oxidation. It is known that members of the OCTN family play an important role in L-carnitine transport in the placenta. Investigation of drug-drug or drug-nutrient interaction in the placenta is important for establishment of safety drug medication during pregnancy. The aim of this study was to determine the effects of fluoroquinolones, inhibitors of OCTN2, on L-carnitine transport in the placenta which is known to have a high expression level of OCTN2. We investigated the inhibitory effect of five fluoroquinolones, ciprofloxacin (CPFX), gatifloxacin (GFLX), ofloxacin (OFLX), levofloxacin (LVFX) and grepafloxacin (GPFX), on L-carnitine transport mediated by OCTN2 in placental cell line BeWo cells. We found that all of the fluoroquinolones inhibited L-carnitine transport, GPFX being the strongest inhibitor. We also found that the inhibitory effects of LVFX and GPFX depended on their existence ratio of zwitterionic forms as, we reported previously. Furthermore, we elucidated the LVFX transport mechanism in BeWo cells. LVFX was transported actively by transporters. However, we found that LVFX transport was Na+-independent and l-carnitine had no inhibitory effect on LVFX transport, suggesting that LVFX acts as inhibitor of OCTN2, not as a substrate for OCTN2.

Glucose transporter 3 (GLUT3) protein expression in human placenta across gestation

PubMed Central

Brown, Kelecia; Heller, Debra S.; Zamudio, Stacy; Illsley, Nicholas P.

2012-01-01

Conflicting information regarding expression of GLUT3 protein in the human placenta has been reported and the localization and pattern of expression of GLUT3 protein across gestation has not been clearly defined. The objective of this study was characterization of syncytial GLUT3 protein expression across gestation. We hypothesized that GLUT3 protein is present in the syncytial microvillous membrane and that its expression decreases over gestation. GLUT3 protein was measured in samples from a range of gestational ages (first to third trimester), with human brain and human bowel used as a positive and negative control respectively. As an additional measure of specificity, we transfected BeWo choriocarcinoma cells, a trophoblast cell line expressing GLUT3, with siRNA directed against GLUT3 and analyzed expression by Western blotting. GLUT3 was detected in the syncytiotrophoblast at all gestational ages by immunohistochemistry. Using Western blotting GLUT3 was detected as an integral membrane protein at a molecular weight of ~50kDa in microvillous membranes from all trimesters but not in syncytial basal membranes. The identity of the primary antibody target was confirmed by demonstrating that expression of the immunoblotting signal in GLUT3 siRNA-treated BeWo was decreased to 18 ± 6% (mean ± SEM) of that seen in cells transfected with a non-targeting siRNA. GLUT3 expression in microvillous membranes detected by Western blot decreased through the trimesters such that expression in the second trimester (wks 14–26) was 48 ± 7% of that in the first trimester and by the third trimester (wks 31–40) only 34 ± 10% of first trimester expression. In addition, glucose uptake into BeWo cells treated with GLUT3 siRNA was reduced to 60% of that measured in cells treated with the non-targeting siRNA. This suggests that GLUT3-mediated uptake comprises approximately 50% of glucose uptake into BeWo cells. These results confirm the hypothesis that GLUT3 is present in the syncytial microvillous membrane early in gestation and decreases thereafter, supporting the idea that GLUT3 is of greater importance for glucose uptake early in gestation. PMID:22000473

In Vitro Screening of Environmental Chemicals Identifies Zearalenone as a Novel Substrate of the Placental BCRP/ABCG2 Transporter

PubMed Central

Xiao, Jingcheng; Wang, Qi; Bircsak, Kristin M.; Wen, Xia; Aleksunes, Lauren M.

2015-01-01

The BCRP (ABCG2) transporter is responsible for the efflux of chemicals from the placenta to the maternal circulation. Inhibition of BCRP activity could enhance exposure of offspring to environmental chemicals leading to altered reproductive, endocrine, and metabolic development. The purpose of this study was to characterize environmental chemicals as potential substrates and inhibitors of the human placental BCRP transporter. The interaction of BCRP with a panel of environmental chemicals was assessed using the ATPase and inverted plasma membrane vesicle assays as well as a cell-based fluorescent substrate competition assay. Human HEK cells transfected with wild-type BCRP or the Q141K genetic variant, as well as BeWo placental cells that endogenously express BCRP were used to further test inhibitor and substrate interactions. To varying degrees, the eleven chemicals inhibited BCRP activity in activated ATPase membranes and inverted membrane vesicles. Further, genistein, zearalenone, and tributyltin increased the retention of the fluorescent BCRP substrate, Hoechst 33342, between 50–100% in BeWo cells. Additional experiments characterized the mycotoxin and environmental estrogen, zearalenone, as a novel substrate and inhibitor of BCRP in WT-BCRP and BeWo cells. Interestingly, the BCRP genetic variant Q141K exhibited reduced efflux of zearalenone compared to the wild-type protein. Taken together, screening assays and direct quantification experiments identified zearalenone as a novel human BCRP substrate. Additional in vivo studies are needed to directly determine whether placental BCRP prevents fetal exposure to zearalenone. PMID:26052432

Identification of CD147 (basigin) as a mediator of trophoblast functions.

PubMed

Lee, Cheuk-Lun; Lam, Maggie P Y; Lam, Kevin K W; Leung, Carmen O N; Pang, Ronald T K; Chu, Ivan K; Wan, Tiffany H L; Chai, Joyce; Yeung, William S B; Chiu, Philip C N

2013-11-01

Does CD147 regulate trophoblast functions in vitro? CD147 exists as a receptor complex on human trophoblast and regulates the implantation, invasion and differentiation of trophoblast. CD147 is a membrane protein implicated in a variety of physiological and pathological conditions due to its regulation of cell-cell recognition, cell differentiation and tissue remodeling. Reduced placental CD147 expression is associated with pre-eclampsia, but the mechanism of actions remains unclear. A loss of function approach or functional blocking antibody was used to study the function of CD147 in primary human cytotrophoblasts isolated from first trimester termination of pregnancy and/or in the BeWo cell line, which possesses characteristics of human cytotrophoblasts. CD147 expression was analyzed by immunofluorescence staining and western blotting. CD147-associated protein complex on plasma membrane were separated by blue native gel electrophoresis and identified by reversed-phase liquid chromatography coupled with quadrupole time-of-flight hybrid mass spectrometer. Cell proliferation and invasion were determined by fluorometric cell proliferation assays and transwell invasion assays, respectively. Matrix metalloproteinases (MMPs) and urokinase plasminogen activator (uPA) activities were measured by gelatin gel zymography and uPA assay kits, respectively. Cell migration was determined by wound-healing assays. Cell fusion was analyzed by immunocytochemistry staining of E-cadherin and 4',6-diamidino-2-phenylindole. The transcripts of matrix proteinases and trophoblast lineage markers were measured by quantitative PCR. Extracellular signal-regulated kinase (ERK) activation was analyzed by western blot using antibodies against ERKs. CD147 exists as protein complexes on the plasma membrane of primary human cytotrophoblasts and BeWo cells. Several known CD147-interacting partners, including integrin β1 and monocarboxylate transporter-1, were identified. Suppression of CD147 by siRNA significantly (P < 0.05) reduced trophoblast-endometrial cell interaction, cell invasion, syncytialization, differentiation and ERK activation of BeWo cells. Consistently, anti-CD147 functional blocking antibody suppressed the invasiveness of primary human cytotrophoblasts. The reduced invasiveness was probably due to the restrained (P < 0.05) enzyme activities of MMP-2, MMP-9 and uPA. Most of the above findings are based on BeWo cell lines. These results need to be confirmed with human first trimester primary cytotrophoblast. This is the first study on the role of CD147 in trophoblast function. Further investigation on the function of CD147 and its associated protein complexes will enhance our understanding on human placentation. This work was supported in part by the University of Hong Kong Grant 201011159200. The authors have no competing interests to declare.

Live cell imaging of in vitro human trophoblast syncytialization.

PubMed

Wang, Rui; Dang, Yan-Li; Zheng, Ru; Li, Yue; Li, Weiwei; Lu, Xiaoyin; Wang, Li-Juan; Zhu, Cheng; Lin, Hai-Yan; Wang, Hongmei

2014-06-01

Human trophoblast syncytialization, a process of cell-cell fusion, is one of the most important yet least understood events during placental development. Investigating the fusion process in a placenta in vivo is very challenging given the complexity of this process. Application of primary cultured cytotrophoblast cells isolated from term placentas and BeWo cells derived from human choriocarcinoma formulates a biphasic strategy to achieve the mechanism of trophoblast cell fusion, as the former can spontaneously fuse to form the multinucleated syncytium and the latter is capable of fusing under the treatment of forskolin (FSK). Live-cell imaging is a powerful tool that is widely used to investigate many physiological or pathological processes in various animal models or humans; however, to our knowledge, the mechanism of trophoblast cell fusion has not been reported using a live- cell imaging manner. In this study, a live-cell imaging system was used to delineate the fusion process of primary term cytotrophoblast cells and BeWo cells. By using live staining with Hoechst 33342 or cytoplasmic dyes or by stably transfecting enhanced green fluorescent protein (EGFP) and DsRed2-Nuc reporter plasmids, we observed finger-like protrusions on the cell membranes of fusion partners before fusion and the exchange of cytoplasmic contents during fusion. In summary, this study provides the first video recording of the process of trophoblast syncytialization. Furthermore, the various live-cell imaging systems used in this study will help to yield molecular insights into the syncytialization process during placental development. © 2014 by the Society for the Study of Reproduction, Inc.

Exposure to ethanol and nicotine induces stress responses in human placental BeWo cells.

PubMed

Repo, Jenni K; Pesonen, Maija; Mannelli, Chiara; Vähäkangas, Kirsi; Loikkanen, Jarkko

2014-01-13

Human placental trophoblastic cancer BeWo cells can be used as a model of placental trophoblasts. We found that combined exposure to relevant exposure concentrations of ethanol (2‰) and nicotine (15 μM) induces an increase in the amount of reactive oxygen species (ROS). Neither ethanol or nicotine alone, nor their combination affected cell viability. However, nicotine decreased cell proliferation, both alone and combined with ethanol. Nicotine increased the expression of the endoplasmic reticulum (ER)-stress related protein GRP78/BiP, but not another marker of ER-stress, IRE1α. We also studied the effects of nicotine and/or ethanol on phosphorylation and expression of three mitogen-activated protein kinases (MAPKs), i.e. JNK, p38 and ERK1/2. Nicotine decreased the phosphorylation of JNK and also had similar effect on total amount of this protein. Phosphorylation and expression of p38 were increased 1.7- and 1.6-fold, respectively, by nicotine alone, and 1.9- and 2.1-fold by the combined treatment. Some increase (1.8-fold) was also seen in the phosphorylation of ERK2 at 48 h, in cells exposed to both ethanol and nicotine. This study shows that ethanol and nicotine, which harm the development of fetus may induce both oxidative and ER stress responses in human placental trophoblastic cells, implicating these mechanisms in their fetotoxic effects. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Impact of graphene oxide on human placental trophoblast viability, functionality and barrier integrity

NASA Astrophysics Data System (ADS)

Kucki, Melanie; Aengenheister, Leonie; Diener, Liliane; Rippl, Alexandra V.; Vranic, Sandra; Newman, Leon; Vazquez, Ester; Kostarelos, Kostas; Wick, Peter; Buerki-Thurnherr, Tina

2018-07-01

Graphene oxide (GO) is considered a promising 2D material for biomedical applications. However, the biological health effects of GO are not yet fully understood, in particular for highly sensitive populations such as pregnant women and their unborn children. Especially the potential impact of GO on the human placenta, a transient and multifunctional organ that enables successful pregnancy, has not been investigated yet. Here we performed a mechanistic in vitro study on the placental uptake and biological effects of four non-labelled GO with varying physicochemical properties using the human trophoblast cell line BeWo. No overt cytotoxicity was observed for all GO materials after 48 h of exposure at concentrations up to 40 µg ml‑1. However, exposure to GO materials induced a slight decrease in mitochondrial activity and human choriogonadotropin secretion. In addition, GO induced a transient opening of the trophoblast barrier as evidenced by a temporary increase in the translocation of sodium fluorescein, a marker molecule for passive transport. Evidence for cellular uptake of GO was found by transmission electron microscopy analysis, revealing uptake of even large micro-sized GO by BeWo cells. Although GO did not elicit major acute adverse effects on BeWo trophoblast cells, the pronounced cellular internalization as well as the potential adverse effects on hormone release and barrier integrity warrants further studies on the long-term consequences of GO on placental functionality in order to understand potential embryo-fetotoxic risks.

Reduced syncytin-1 expression in chriocarcinoma BeWo cells activates the calpain1-AIF-mediated apoptosis, implication for preeclampsia

PubMed Central

Huang, Qiang; Chen, Haibin; Wang, Fengchao; Brost, Brian C.; Li, Jinping; Gao, Yu; Li, Zongfang; Gao, Ya; Jiang, Shi-Wen

2015-01-01

Placentas associated with preeclampsia are characterized by extensive apoptosis in trophoblast lineages. Syncytin-1 (HERVWE1) mediates the fusion of cytotrophoblasts to form syncytiotrophoblasts, which assume the placental barrier, fetal-maternal exchange and endocrine functions. While decreased syncytin-1 expression has been observed in preeclamptic placentas, it is not clear if this alteration is involved in trophoblast apoptosis. In the current study we found that siRNA-mediated knockdown of syncytin-1 led to apoptosis in choriocarcinoma BeWo, a cell line of trophoblastic origin. Characterization of the apoptotic pathways indicated that this effect does not rely on the activation of caspases. Rather, decreased syncytin-1 levels activated the AIF apoptotic pathway by inducing the expression, cleavage, and nuclear translocation of AIF. Moreover, calpain1, the cysteine protease capable of cleaving AIF, was upregulated by syncytin-1 knockdown. Furthermore, treatment with calpain1 inhibitor MDL28170 effectively reversed AIF cleavage, AIF nuclear translocation, and cell apoptosis triggered by syncytin-1 downregulation, verifying the specific action of calpain1-AIF pathway in trophoblast apoptosis. We confirmed that preeclamptic placentas express lower levels of syncytin-1 than normal placentas, and observed an inverse correlation between syncytin-1 and AIF/calpain1 mRNA levels, a result consistent with the in vitro findings. Immunohistochemistry analyses indicated decreased syncytin-1, increased AIF and calpain1 protein levels in apoptotic cells of preeclamptic placentas. These findings have for the first time revealed that decreased levels of syncytin-1 can trigger the AIF-mediated apoptosis pathway in BeWo cells. This novel mechanism may contribute to the structural and functional deficiencies of syncytium frequently observed in preeclamptic placentas. PMID:24413738

Expression of NADPH Oxidase Isoform 1 (Nox1) in Human Placenta: Involvement in Preeclampsia

PubMed Central

Cui, X.-L.; Brockman, D.; Campos, B.; Myatt, L.

2010-01-01

Increased oxidative stress in the placenta has been associated with preeclampsia (PE), a clinical syndrome involving placental pathology. The enzymatic sources of reactive oxygen species in the human placenta are as yet unidentified. We hypothesized that NADPH oxidase is a main source of reactive oxygen species in the placenta and its expression may change in PE. Employing RTPCR, we have amplified a novel NADPH oxidase isoform Nox1 from human choriocarcinoma BeWo cells. Using polyclonal anti-peptide antiserum recognizing unique Nox1 peptide sequences, we identified by immunohistochemistry and cell fractionation that Nox1 protein localizes in the BeWo cell membrane structures. Immunohistochemistry of normal placental tissues showed that Nox1 was localized in syncytiotrophoblasts, in villous vascular endothelium, and in some stromal cells. At the immunohistochemical level Nox1 expression was significantly increased in syncytiotrophoblast and endothelial cells in placentas from patients with preeclampsia as compared to gestational age-matched controls. Western blot analysis of whole placental homogenate confirmed this increase. Our data suggests that increased Nox1 expression is associated with the increased oxidative stress found in these placentas. PMID:15993942

Anti-proliferative and angio-suppressive effect of Stoechospermum marginatum (C. Agardh) Kutzing extract using various experimental models

PubMed Central

Puttananjaiah, Shilpa; Chatterji, Anil; Salimath, Bharati

2014-01-01

BACKGROUND/OBJECTIVES Abundant consumption of seaweeds in the diet is epidemiologically linked to the reduction in risk of developing cancer. In larger cases, however, identification of particular seaweeds that are accountable for these effects is still lacking, hindering the recognition of competent dietary-based chemo preventive approaches. The aim of this research was to establish the antiproliferative potency and angiosuppressive mode of action of Stoechospermum marginatum seaweed methanolic extract using various experimental models. MATERIALS/METHODS Among the 15 seaweeds screened for antiproliferative activity against Ehrlich ascites tumor (EAT) cell line, Stoechospermum marginatum extract (SME) was found to be the most promising. Therefore, it was further investigated for its anti-proliferative activity in-vitro against choriocarcinoma (BeWo) and non-transformed Human embryonic kidney (HEK 293) cells, and for its anti-migratory/tube formation activity against HUVEC cells in-vitro. Subsequently, the angiosuppressive activity of S. marginatum was established by inhibition of angiogenesis in in-vivo (peritoneal angiogenesis and chorioallantoic membrane assay) and ex-vivo (rat cornea assay) models. RESULTS Most brown seaweed extracts inhibited the proliferation of EAT cells, while green and red seaweed extracts were much less effective. According to the results, SME selectively inhibited proliferation of BeWo cells in-vitro in a dose-dependent manner, but had a lesser effect on HEK 293 cells. SME also suppressed the migration and tube formation of HUVEC cells in-vitro. In addition, SME was able to suppress VEGF-induced angiogenesis in the chorio allantoic membrane, rat cornea, and tumor induced angiogenesis in the peritoneum of EAT bearing mice. A decrease in the microvessel density count and CD31 antigen staining of treated mice peritoneum provided further evidence of its angiosuppressive activity. CONCLUSIONS Altogether, the data underline that VEGF mediated angiogenesis is the target for the angiosuppressive action of SME and could potentially be useful in cancer prevention or treatment involving stimulated angiogenesis. PMID:25110556

Disruption of thyroid hormone sulfotransferase activity by brominated flame retardant chemicals in the human choriocarcinoma placenta cell line, BeWo.

PubMed

Leonetti, Christopher P; Butt, Craig M; Stapleton, Heather M

2018-04-01

Brominated flame retardants (BFRs) have been shown to disrupt thyroid hormone (TH) homeostasis through multiple mechanisms, including inhibition of enzymes that regulate intracellular levels of THs, such as sulfotransferases (SULTs). The placenta plays a critical role in helping to maintain TH levels during fetal development and expresses SULTs. This is concerning given that disruption of TH regulation within the placenta could potentially harm the developing fetus. In this study, we investigated the effects of two polybrominated diphenyl ethers (PBDEs), two hydroxylated PBDEs, and 2,4,6-tribromophenol (2,4,6-TBP) on TH SULT activity in a choriocarcinoma placenta cell line (BeWo). BeWo cells were exposed to BFR concentrations up to 1 μM for 1-24 h to investigate changes in basal SULT activity and in mRNA expression of several TH regulating genes. 2,4,6-TBP was the most potent inhibitor of basal 3,3'-T2 SULT activity at all exposure durations, decreasing activity by as much as 86% after 24 h of exposure. BDE-99, 3-OH BDE-47, and 6-OH BDE-47 also decreased 3,3'-T2 SULT activity by 23-42% at concentrations of 0.5 μM and 1.0 μM following 24 h exposures. BDE-47 had no effect on SULT activity, and there was no observed effect of any BFR exposure on expression of SULT1A1, or thyroid nuclear receptors alpha or beta. This research demonstrates that total TH SULT activity in placental cells are sensitive to BFR exposure; however, the mechanisms and consequences have yet to be fully elucidated. Copyright © 2017 Elsevier Ltd. All rights reserved.

Resistin modulates glucose uptake and glucose transporter-1 (GLUT-1) expression in trophoblast cells.

PubMed

Di Simone, Nicoletta; Di Nicuolo, Fiorella; Marzioni, Daniela; Castellucci, Mario; Sanguinetti, Maurizio; D'lppolito, Silvia; Caruso, Alessandro

2009-02-01

The adipocytokine resistin impairs glucose tolerance and insulin sensitivity. Here, we examine the effect of resistin on glucose uptake in human trophoblast cells and we demonstrate that transplacental glucose transport is mediated by glucose transporter (GLUT)-1. Furthermore, we evaluate the type of signal transduction induced by resistin in GLUT-1 regulation. BeWo choriocarcinoma cells and primary cytotrophoblast cells were cultured with increasing resistin concentrations for 24 hrs. The main outcome measures include glucose transport assay using [(3)H]-2-deoxy glucose, GLUT-1 protein expression by Western blot analysis and GLUT-1 mRNA detection by quantitative real-time RT-PCR. Quantitative determination of phospho(p)-ERK1/2 in cell lysates was performed by an Enzyme Immunometric Assay and Western blot analysis. Our data demonstrate a direct effect of resistin on normal cytotrophoblastic and on BeWo cells: resistin modulates glucose uptake, GLUT-1 messenger ribonucleic acid (mRNA) and protein expression in placental cells. We suggest that ERK1/2 phosphorylation is involved in the GLUT-1 regulation induced by resistin. In conclusion, resistin causes activation of both the ERK1 and 2 pathway in trophoblast cells. ERK1 and 2 activation stimulated GLUT-1 synthesis and resulted in increase of placental glucose uptake. High resistin levels (50-100 ng/ml) seem able to affect glucose-uptake, presumably by decreasing the cell surface glucose transporter.

Cell-to-Cell Contact Results in a Selective Translocation of Maternal Human Immunodeficiency Virus Type 1 Quasispecies across a Trophoblastic Barrier by both Transcytosis and Infection

PubMed Central

Lagaye, S.; Derrien, M.; Menu, E.; Coïto, C.; Tresoldi, E.; Mauclère, P.; Scarlatti, G.; Chaouat, G.; Barré-Sinoussi, F.; Bomsel, M.

2001-01-01

Mother-to-child transmission can occur in utero, mainly intrapartum and postpartum in case of breastfeeding. In utero transmission is highly restricted and results in selection of viral variant from the mother to the child. We have developed an in vitro system that mimics the interaction between viruses, infected cells present in maternal blood, and the trophoblast, the first barrier protecting the fetus. Trophoblastic BeWo cells were grown as a tight polarized monolayer in a two-chamber system. Cell-free virions applied to the apical pole neither crossed the barrier nor productively infected BeWo cells. In contrast, apical contact with human immunodeficiency virus (HIV)-infected peripheral blood mononuclear cells (PBMCs) resulted in transcytosis of infectious virus across the trophoblastic monolayer and in productive infection correlating with the fusion of HIV-infected PBMCs with trophoblasts. We showed that viral variants are selected during these two steps and that in one case of in utero transmission, the predominant maternal viral variant characterized after transcytosis was phylogenetically indistinguishable from the predominant child's virus. Hence, the first steps of transmission of HIV-1 in utero appear to involve the interaction between HIV type 1-infected cells and the trophoblastic layer, resulting in the passage of infectious HIV by transcytosis and by fusion/infection, both leading to a selection of virus quasispecies. PMID:11312350

Dopamine synthesis and dopamine receptor expression are disturbed in recurrent miscarriages

PubMed Central

Gratz, Michael J; Stavrou, Stavroula; Kuhn, Christina; Hofmann, Simone; Hermelink, Kerstin; Heidegger, Helene; Hutter, Stefan; Mayr, Doris; Mahner, Sven; Jeschke, Udo; Vattai, Aurelia

2018-01-01

Objectives l-dopa decarboxylase (DDC) is responsible for the synthesis of dopamine. Dopamine, which binds to the D2-dopamine receptor (D2R), plays an important role in the maintenance of pregnancy. Aim of our study was the analysis of DDC and D2R expression in placentas of spontaneous miscarriages (SMs) and recurrent miscarriages (RMs) in comparison to healthy controls. Methods Patients with SM (n = 15) and RM (n = 15) were compared with patients from healthy pregnancies (n = 15) (pregnancy weeks 7–13 each). Placental tissue has been collected from SMs and RMs from the first trimester (Department of Gynaecology and Obstetrics, LMU Munich) and from abruptions (private practice, Munich). Placental cell lines, BeWo- and JEG-3 cells, were stimulated with the trace amines T0AM and T1AM in vitro. Results Levels of DDC and D2R in trophoblasts and the decidua were lower in RMs in comparison to healthy controls. Stimulation of BeWo cells with T1AM significantly reduced DDC mRNA and protein levels. Via double-immunofluorescence, a DDC-positive cell type beneath decidual stromal cells and foetal EVT in the decidua could be detected. Conclusions Downregulation of DDC and D2R in trophoblasts of RMs reflects a reduced signal cascade of catecholamines on the foetal side. PMID:29686031

Dopamine synthesis and dopamine receptor expression are disturbed in recurrent miscarriages.

PubMed

Gratz, Michael J; Stavrou, Stavroula; Kuhn, Christina; Hofmann, Simone; Hermelink, Kerstin; Heidegger, Helene; Hutter, Stefan; Mayr, Doris; Mahner, Sven; Jeschke, Udo; Vattai, Aurelia

2018-05-01

l-dopa decarboxylase (DDC) is responsible for the synthesis of dopamine. Dopamine, which binds to the D 2 -dopamine receptor (D2R), plays an important role in the maintenance of pregnancy. Aim of our study was the analysis of DDC and D2R expression in placentas of spontaneous miscarriages (SMs) and recurrent miscarriages (RMs) in comparison to healthy controls. Patients with SM (n = 15) and RM (n = 15) were compared with patients from healthy pregnancies (n = 15) (pregnancy weeks 7-13 each). Placental tissue has been collected from SMs and RMs from the first trimester (Department of Gynaecology and Obstetrics, LMU Munich) and from abruptions (private practice, Munich). Placental cell lines, BeWo- and JEG-3 cells, were stimulated with the trace amines T 0 AM and T 1 AM in vitro . Levels of DDC and D2R in trophoblasts and the decidua were lower in RMs in comparison to healthy controls. Stimulation of BeWo cells with T 1 AM significantly reduced DDC mRNA and protein levels. Via double-immunofluorescence, a DDC-positive cell type beneath decidual stromal cells and foetal EVT in the decidua could be detected. Downregulation of DDC and D2R in trophoblasts of RMs reflects a reduced signal cascade of catecholamines on the foetal side. © 2018 The authors.

Molecular hydrogen ameliorates several characteristics of preeclampsia in the Reduced Uterine Perfusion Pressure (RUPP) rat model.

PubMed

Ushida, Takafumi; Kotani, Tomomi; Tsuda, Hiroyuki; Imai, Kenji; Nakano, Tomoko; Hirako, Shima; Ito, Yumiko; Li, Hua; Mano, Yukio; Wang, Jingwen; Miki, Rika; Yamamoto, Eiko; Iwase, Akira; Bando, Yasuko K; Hirayama, Masaaki; Ohno, Kinji; Toyokuni, Shinya; Kikkawa, Fumitaka

2016-12-01

Oxidative stress plays an important role in the pathogenesis of preeclampsia. Recently, molecular hydrogen (H 2 ) has been shown to have therapeutic potential in various oxidative stress-related diseases. The aim of this study is to investigate the effect of H 2 on preeclampsia. We used the reduced utero-placental perfusion pressure (RUPP) rat model, which has been widely used as a model of preeclampsia. H 2 water (HW) was administered orally ad libitum in RUPP rats from gestational day (GD) 12-19, starting 2 days before RUPP procedure. On GD19, mean arterial pressure (MAP) was measured, and samples were collected. Maternal administration of HW significantly decreased MAP, and increased fetal and placental weight in RUPP rats. The increased levels of soluble fms-like tyrosine kinase-1 (sFlt-1) and diacron reactive oxygen metabolites as a biomarker of reactive oxygen species in maternal blood were decreased by HW administration. However, vascular endothelial growth factor level in maternal blood was increased by HW administration. Proteinuria, and histological findings in kidney were improved by HW administration. In addition, the effects of H 2 on placental villi were examined by using a trophoblast cell line (BeWo) and villous explants from the placental tissue of women with or without preeclampsia. H 2 significantly attenuated hydrogen peroxide-induced sFlt-1 expression, but could not reduce the expression induced by hypoxia in BeWo cells. H 2 significantly attenuated sFlt-1 expression in villous explants from women with preeclampsia, but not affected them from normotensive pregnancy. The prophylactic administration of H 2 attenuated placental ischemia-induced hypertension, angiogenic imbalance, and oxidative stress. These results support the theory that H 2 has a potential benefit in the prevention of preeclampsia. Copyright © 2016 Elsevier Inc. All rights reserved.

Development and characterization of a monoclonal antibody to human embryonal carcinoma

DOE Office of Scientific and Technical Information (OSTI.GOV)

Khazaeli, M.B.; Beierwaltes, W.H.; Pitt, G.S.

1987-06-01

A monoclonal anti-testicular carcinoma antibody was obtained via the somatic cell fusion technique by immunization of BALB/c mice with freshly prepared single cell suspension from a patient with testicular embryonal carcinoma with choriocarcinoma components. The hybridoma supernates were screened against the testicular carcinoma cells used in the immunization as well as normal mononuclear white blood cells isolated from the same patient. An antibody (5F9) was selected which bound to fresh tumor cells from two patients with embryonal testicular carcinoma and failed to bind to fresh tumor cells from 24 patients (2 seminoma, 2 melanoma, 3 neck, 2 esophageal, 1 ovarian,more » 3 colon, 1 prostate, 2 breast, 1 liposarcoma, 3 endometrial, 1 kidney, 1 adrenal, 1 larynx and 1 bladder tumors) or cell suspensions prepared from normal liver, lung, spleen, ovary, testes, kidney, red blood cells or white blood cells. The antibody was tested for its binding to several well established cancer cell lines, and was found to bind to the BeWo human choriocarcinoma and two human embryonal carcinoma cell lines. The antibody did not react with 22 other cell lines or with hCG. The antibody was labeled with /sup 131/I and injected into nude mice bearing BeWo tumors and evaluated for tumor localization by performing whole body scans with a gamma camera 5 days later. Six mice injected with the antibody showed positive tumor localization without the need for background subtraction while six mice injected with MOPC-21, a murine myeloma immunoglobulin, demonstrated much less tumor localization. Tissue distribution studies performed after scanning showed specific tumor localization (8:1 tumor: muscle) for the monoclonal antibody and no specific localization for MOPC-21.« less

Buprenorphine, Norbuprenorphine, R-Methadone, and S-Methadone Upregulate BCRP/ABCG2 Expression by Activating Aryl Hydrocarbon Receptor in Human Placental Trophoblasts

PubMed Central

Neradugomma, Naveen K.; Liao, Michael Z.

2017-01-01

Opioid dependence during pregnancy is a rising concern. Maintaining addicted pregnant women on long-acting opioid receptor agonist is the most common strategy to manage drug abuse in pregnant women. Methadone (MET) and buprenorphine (BUP) are widely prescribed for opiate maintenance therapy. Norbuprenorphine (NBUP) is the primary active metabolite of BUP. These medications can cross the placenta to the fetus, leading to postpartum neonatal abstinence syndrome. Despite their use during pregnancy, little is known about the cellular changes in the placenta brought about by these drugs. In this study, we showed that BUP, NBUP, and MET at clinically relevant plasma concentrations significantly induced BCRP mRNA up to 10-fold in human model placental JEG3 and BeWo cells and in primary human villous trophoblasts, and this induction was abrogated by CH223191, an aryl hydrocarbon receptor (AhR)-specific antagonist. These drugs increased AhR recruitment onto the AhR-response elements and significantly induced breast cancer resistance protein (BCRP) gene transcription. AhR overexpression further increased BCRP mRNA and protein expression. Knockdown of AhR by shRNA decreased BCRP expression, and this decrease was reversed by rescuing AhR expression. Finally, induction of BCRP expression in JEG3 and BeWo cells was accompanied by an increase in its efflux activity. Collectively, we have demonstrated, for the first time, that BUP, NBUP, and MET are potent AhR agonists and can induce BCRP in human placental trophoblasts by activating AhR. Given the critical role of BCRP in limiting fetal exposure to drugs and xenobiotics, long-term use of these medications may affect fetal drug exposure by altering BCRP expression in human placenta. PMID:27974484

Genome-wide high-resolution aCGH analysis of gestational choriocarcinomas.

PubMed

Poaty, Henriette; Coullin, Philippe; Peko, Jean Félix; Dessen, Philippe; Diatta, Ange Lucien; Valent, Alexander; Leguern, Eric; Prévot, Sophie; Gombé-Mbalawa, Charles; Candelier, Jean-Jacques; Picard, Jean-Yves; Bernheim, Alain

2012-01-01

Eleven samples of DNA from choriocarcinomas were studied by high resolution CGH-array 244 K. They were studied after histopathological confirmation of the diagnosis, of the androgenic etiology and after a microsatellite marker analysis confirming the absence of contamination of tumor DNA from maternal DNA. Three cell lines, BeWo, JAR, JEG were also studied by this high resolution pangenomic technique. According to aCGH analysis, the de novo choriocarcinomas exhibited simple chromosomal rearrangements or normal profiles. The cell lines showed various and complex chromosomal aberrations. 23 Minimal Critical Regions were defined that allowed us to list the genes that were potentially implicated. Among them, unusually high numbers of microRNA clusters and imprinted genes were observed.

Preparation, characterization, and transport of dexamethasone-loaded polymeric nanoparticles across a human placental in vitro model

PubMed Central

Ali, Hazem; Kalashnikova, Irina; White, Mark Andrew; Sherman, Michael; Rytting, Erik

2013-01-01

The purpose of this study was to prepare dexamethasone-loaded polymeric nanoparticles and evaluate their potential for transport across human placenta. Statistical modeling and factorial design was applied to investigate the influence of process parameters on the following nanoparticle characteristics: particle size, polydispersity index, zeta potential, and drug encapsulation efficiency. Dexamethasone and nanoparticle transport was subsequently investigated using the BeWo b30 cell line, an in vitro model of human placental trophoblast cells, which represent the rate-limiting barrier for maternal-fetal transfer. Encapsulation efficiency and drug transport were determined using a validated high performance liquid chromatography method. Nanoparticle morphology and drug encapsulation were further characterized by cryo-transmission electron microscopy and X-ray diffraction, respectively. Nanoparticles prepared from poly(lactic-co-glycolic acid) were spherical, with particle sizes ranging from 140–298 nm, and encapsulation efficiency ranging from 52–89%. Nanoencapsulation enhanced the apparent permeability of dexamethasone from the maternal compartment to the fetal compartment more than 10-fold in this model. Particle size was shown to be inversely correlated with drug and nanoparticle permeability, as confirmed with fluorescently-labeled nanoparticles. These results highlight the feasibility of designing nanoparticles capable of delivering medication to the fetus, in particular, potential dexamethasone therapy for the prenatal treatment of congenital adrenal hyperplasia. PMID:23850397

Changes of placental syndecan-1 expression in preeclampsia and HELLP syndrome

PubMed Central

Szabo, Szilvia; Xu, Yi; Romero, Roberto; Fule, Tibor; Karaszi, Katalin; Bhatti, Gaurav; Varkonyi, Tibor; Varkonyi, Ildiko; Krenacs, Tibor; Dong, Zhong; Tarca, Adi L.; Chaiworapongsa, Tinnakorn; Hassan, Sonia S.; Papp, Zoltan; Kovalszky, Ilona; Than, Nandor Gabor

2014-01-01

Introduction Preeclampsia is characterized by maternal systemic anti-angiogenic and pro-inflammatory states. Syndecan-1 is a cell surface proteoglycan expressed by the syncytiotrophoblast, which plays an important role in angiogenesis and resolution of inflammation. Our aim was to examine placental syndecan-1 expression in preeclampsia with or without HELLP syndrome. Methods Placentas were obtained from women in the following groups: (1) late-onset preeclampsia (n=8); (2) early-onset preeclampsia without (n=7) and (3) with HELLP syndrome (n=8); (4) preterm controls (n=5); and (5) term controls (n=9). Tissue microarrays (TMAs) were constructed from paraffin-embedded placentas. TMA slides were immunostained for syndecan-1 and evaluated using microscopy, virtual microscopy, and semi-automated image analysis. Maternal sera from patients with preeclampsia (n=49) and controls (n=32) were immunoassayed for syndecan-1. BeWo cells were treated with Forskolin or Latrunculin-B, or kept in ischemic conditions. SDC1 expression and syndecan-1 production were investigated with qRT-PCR, confocal microscopy, and immunoassays. Results Syndecan-1 was localized to the syncytiotrophoblast apical membrane in normal placentas. Syndecan-1 immunoscores were higher in late-onset preeclampsia (p=0.0001) and early-onset preeclampsia with or without HELLP syndrome (p=0.02 for both) than in controls. Maternal serum syndecan-1 concentration was lower in preeclampsia (median: 673ng/ml, interquartile range: 459-1161ng/ml) than in controls (1158ng/ml, 622-1480ng/ml). SDC1 expression and syndecan-1 immunostainings in BeWo cells and syndecan-1 concentrations in supernatants increased during cell differentiation. Disruption of the actin cytoskeleton with Latrunculin-B decreased syndecan-1 release, while ischemic conditions increased it. Conclusions Syncytiotrophoblastic syndecan-1 expression depends on the differentiation of villous trophoblasts, and trophoblastic syndecan-1 release is decreased in preeclampsia and HELLP syndrome. This phenomenon may be related to the disturbed syncytiotrophoblastic cortical actin cytoskeleton, and associated with maternal anti-angiogenic and pro-inflammatory states in these syndromes. PMID:23807541

Oxcarbazepine-loaded polymeric nanoparticles: development and permeability studies across in vitro models of the blood–brain barrier and human placental trophoblast

PubMed Central

Lopalco, Antonio; Ali, Hazem; Denora, Nunzio; Rytting, Erik

2015-01-01

Encapsulation of antiepileptic drugs (AEDs) into nanoparticles may offer promise for treating pregnant women with epilepsy by improving brain delivery and limiting the transplacental permeability of AEDs to avoid fetal exposure and its consequent undesirable adverse effects. Oxcarbazepine-loaded nanoparticles were prepared by a modified solvent displacement method from biocompatible polymers (poly(lactic-co-glycolic acid) [PLGA] with or without surfactant and PEGylated PLGA [Resomer® RGPd5055]). The physical properties of the developed nanoparticles were determined with subsequent evaluation of their permeability across in vitro models of the blood–brain barrier (hCMEC/D3 cells) and human placental trophoblast cells (BeWo b30 cells). Oxcarbazepine-loaded nanoparticles with encapsulation efficiency above 69% were prepared with sizes ranging from 140–170 nm, polydispersity indices below 0.3, and zeta potential values below -34 mV. Differential scanning calorimetry and X-ray diffraction studies confirmed the amorphous state of the nanoencapsulated drug. The apparent permeability (Pe) values of the free and nanoencapsulated oxcarbazepine were comparable across both cell types, likely due to rapid drug release kinetics. Transport studies using fluorescently-labeled nanoparticles (loaded with coumarin-6) demonstrated increased permeability of surfactant-coated nanoparticles. Future developments in enzyme-prodrug therapy and targeted delivery are expected to provide improved options for pregnant patients with epilepsy. PMID:25792832

Oxcarbazepine-loaded polymeric nanoparticles: development and permeability studies across in vitro models of the blood-brain barrier and human placental trophoblast.

PubMed

Lopalco, Antonio; Ali, Hazem; Denora, Nunzio; Rytting, Erik

2015-01-01

Encapsulation of antiepileptic drugs (AEDs) into nanoparticles may offer promise for treating pregnant women with epilepsy by improving brain delivery and limiting the transplacental permeability of AEDs to avoid fetal exposure and its consequent undesirable adverse effects. Oxcarbazepine-loaded nanoparticles were prepared by a modified solvent displacement method from biocompatible polymers (poly(lactic-co-glycolic acid) [PLGA] with or without surfactant and PEGylated PLGA [Resomer(®) RGPd5055]). The physical properties of the developed nanoparticles were determined with subsequent evaluation of their permeability across in vitro models of the blood-brain barrier (hCMEC/D3 cells) and human placental trophoblast cells (BeWo b30 cells). Oxcarbazepine-loaded nanoparticles with encapsulation efficiency above 69% were prepared with sizes ranging from 140-170 nm, polydispersity indices below 0.3, and zeta potential values below -34 mV. Differential scanning calorimetry and X-ray diffraction studies confirmed the amorphous state of the nanoencapsulated drug. The apparent permeability (Pe ) values of the free and nanoencapsulated oxcarbazepine were comparable across both cell types, likely due to rapid drug release kinetics. Transport studies using fluorescently-labeled nanoparticles (loaded with coumarin-6) demonstrated increased permeability of surfactant-coated nanoparticles. Future developments in enzyme-prodrug therapy and targeted delivery are expected to provide improved options for pregnant patients with epilepsy.

Genome-Wide High-Resolution aCGH Analysis of Gestational Choriocarcinomas

PubMed Central

Poaty, Henriette; Coullin, Philippe; Peko, Jean Félix; Dessen, Philippe; Diatta, Ange Lucien; Valent, Alexander; Leguern, Eric; Prévot, Sophie; Gombé-Mbalawa, Charles; Candelier, Jean-Jacques; Picard, Jean-Yves; Bernheim, Alain

2012-01-01

Eleven samples of DNA from choriocarcinomas were studied by high resolution CGH-array 244 K. They were studied after histopathological confirmation of the diagnosis, of the androgenic etiology and after a microsatellite marker analysis confirming the absence of contamination of tumor DNA from maternal DNA. Three cell lines, BeWo, JAR, JEG were also studied by this high resolution pangenomic technique. According to aCGH analysis, the de novo choriocarcinomas exhibited simple chromosomal rearrangements or normal profiles. The cell lines showed various and complex chromosomal aberrations. 23 Minimal Critical Regions were defined that allowed us to list the genes that were potentially implicated. Among them, unusually high numbers of microRNA clusters and imprinted genes were observed. PMID:22253721

DNA methylation of amino acid transporter genes in the human placenta.

PubMed

Simner, C; Novakovic, B; Lillycrop, K A; Bell, C G; Harvey, N C; Cooper, C; Saffery, R; Lewis, R M; Cleal, J K

2017-12-01

Placental transfer of amino acids via amino acid transporters is essential for fetal growth. Little is known about the epigenetic regulation of amino acid transporters in placenta. This study investigates the DNA methylation status of amino acid transporters and their expression across gestation in human placenta. BeWo cells were treated with 5-aza-2'-deoxycytidine to inhibit methylation and assess the effects on amino acid transporter gene expression. The DNA methylation levels of amino acid transporter genes in human placenta were determined across gestation using DNA methylation array data. Placental amino acid transporter gene expression across gestation was also analysed using data from publically available Gene Expression Omnibus data sets. The expression levels of these transporters at term were established using RNA sequencing data. Inhibition of DNA methylation in BeWo cells demonstrated that expression of specific amino acid transporters can be inversely associated with DNA methylation. Amino acid transporters expressed in term placenta generally showed low levels of promoter DNA methylation. Transporters with little or no expression in term placenta tended to be more highly methylated at gene promoter regions. The transporter genes SLC1A2, SLC1A3, SLC1A4, SLC7A5, SLC7A11 and SLC7A10 had significant changes in enhancer DNA methylation across gestation, as well as gene expression changes across gestation. This study implicates DNA methylation in the regulation of amino acid transporter gene expression. However, in human placenta, DNA methylation of these genes remains low across gestation and does not always play an obvious role in regulating gene expression, despite clear evidence for differential expression as gestation proceeds. Copyright © 2017. Published by Elsevier Ltd.

The regulation of oxytocin and oxytocin receptor in human placenta according to gestational age.

PubMed

Kim, Seung-Chul; Lee, Jae-Eon; Kang, Seong Soo; Yang, Hoe-Saeng; Kim, Sun Suk; An, Beum-Soo

2017-10-01

Oxytocin (OXT) is a peptide hormone that plays a central role in the regulation of parturition and lactation. OXT signaling is mediated by OXT receptor (OXTR), which shows species- and tissue-specific expressions and gene regulation. In the present study, we examined the synthesis of OXT and OXTR in human placenta tissue according to gestational age. A total of 48 placentas were divided into early preterm, late preterm and term groups depending on gestational age, and expression of OXT and OXTR was evaluated. First, OXT and OXTR mRNA and protein were detected in normal placenta tissue via Q-PCR, Dot-blot and Western blot assay. Both OXT and OXTR levels in normal placenta increased gradually in the late stage of pregnancy, suggesting that local OXT may play a critical role in the function of the placenta. To determine the regulatory mechanism of OXT, placental BeWo cells were administrated estrogen (E2) or progesterone (P 4 ), and expression of OXT and OXTR was tested. The mRNA and protein levels of OXT and OXTR were upregulated by E2 but blocked by co-treatment with P 4 In order to confirm the estrogen receptor (ESR)-mediated signaling, we administrated ESR antagonists together with E2 to BeWo cells. As a result, both OXT and OXTR were significantly altered by ESR1 antagonist (MPP) while moderately regulated by ESR2 antagonist (PHTPP). These results suggest that OXT and OXTR are controlled mainly by E2 in the placenta via ESR1 and thus may play physiological functions in the human placenta during the late stage of pregnancy. © 2017 Society for Endocrinology.

Differential expression of the metastasis suppressor KAI1 in decidual cells and trophoblast giant cells at the feto-maternal interface.

PubMed

Koo, Tae Bon; Han, Min-Su; Tadashi, Yamashita; Seong, Won Joon; Choi, Je-Yong

2013-10-01

Invasion of trophoblasts into maternal uterine tissue is essential for establishing mature feto-maternal circulation. The trophoblast invasion associated with placentation is similar to tumor invasion. In this study, we investigated the role of KAI1, an antimetastasis factor, at the maternal-fetal interface during placentation. Mouse embryos were obtained from gestational days 5.5 (E5.5) to E13.5. Immunohistochemical analysis revealed that KAI1 was expressed on decidual cells around the track made when a fertilized ovum invaded the endometrium, at days E5.5 and E7.5, and on trophoblast giant cells, along the central maternal artery of the placenta at E9.5. KAI1 in trophoblast giant cells was increased at E11.5, and then decreased at E13.5. Furthermore, KAI1 was upregulated during the forskolin-mediated trophoblastic differentiation of BeWo cells. Collectively, these results indicate that KAI1 is differentially expressed in decidual cells and trophoblasts at the maternal-fetal interface, suggesting that KAI1 prevents trophoblast invasion during placentation.

The use of a unique co-culture model of fetoplacental steroidogenesis as a screening tool for endocrine disruptors: The effects of neonicotinoids on aromatase activity and hormone production.

PubMed

Caron-Beaudoin, Elyse; Viau, Rachel; Hudon-Thibeault, Andrée-Anne; Vaillancourt, Cathy; Sanderson, J Thomas

2017-10-01

Estrogen biosynthesis during pregnancy is dependent on the collaboration between the fetus producing the androgen precursors, and the placenta expressing the enzyme aromatase (CYP19). Disruption of estrogen production by contaminants may result in serious pregnancy outcomes. We used our recently developed in vitro co-culture model of fetoplacental steroidogenesis to screen the effects of three neonicotinoid insecticides on the catalytic activity of aromatase and the production of steroid hormones. A co-culture of H295R human adrenocortical carcinoma cells with fetal characteristics and BeWo human choriocarcinoma cells which display characteristics of the villous cytotrophoblast was exposed for 24h to various concentrations of three neonicotinoids: thiacloprid, thiamethoxam and imidacloprid. Aromatase catalytic activity was determined in both cell lines using the tritiated water-release assay. Hormone production was measured by ELISA. The three neonicotinoids induced aromatase activity in our fetoplacental co-culture and concordingly, estradiol and estrone production were increased. In contrast, estriol production was strongly inhibited by the neonicotinoids. All three pesticides induced the expression of CYP3A7 in H295R cells, and this induction was reversed by co-treatment of H295R cells with exogenous estriol. CYP3A7 is normally expressed in fetal liver and is a key enzyme involved in estriol synthesis. We suggest that neonicotinoids are metabolized by CYP3A7, thus impeding the 16α-hydroxylation of fetal DHEA(-sulfate), which is normally converted to estriol by placental aromatase. We successfully used the fetoplacental co-culture as a physiologically relevant tool to highlight the potential effects of neonicotinoids on estrogen production, aromatase activity and CYP3A7 expression during pregnancy. Copyright © 2017 Elsevier Inc. All rights reserved.

Online combination of reversed-phase/reversed-phase and porous graphitic carbon liquid chromatography for multicomponent separation of proteomics and glycoproteomics samples.

PubMed

Lam, Maggie P Y; Lau, Edward; Siu, S O; Ng, Dominic C M; Kong, Ricky P W; Chiu, Philip C N; Yeung, William S B; Lo, Clive; Chu, Ivan K

2011-11-01

In this paper, we describe an online combination of reversed-phase/reversed-phase (RP-RP) and porous graphitic carbon (PGC) liquid chromatography (LC) for multicomponent analysis of proteomics and glycoproteomics samples. The online RP-RP portion of this system provides comprehensive 2-D peptide separation based on sequence hydrophobicity at pH 2 and 10. Hydrophilic components (e.g. glycans, glycopeptides) that are not retained by RP are automatically diverted downstream to a PGC column for further trapping and separation. Furthermore, the RP-RP/PGC system can provide simultaneous extension of the hydropathy range and peak capacity for analysis. Using an 11-protein mixture, we found that the system could efficiently separate native peptides and released N-glycans from a single sample. We evaluated the applicability of the system to the analysis of complex biological samples using 25 μg of the lysate of a human choriocarcinoma cell line (BeWo), confidently identifying a total of 1449 proteins from a single experiment and up to 1909 distinct proteins from technical triplicates. The PGC fraction increased the sequence coverage through the inclusion of additional hydrophilic sequences that accounted for up to 6.9% of the total identified peptides from the BeWo lysate, with apparent preference for the detection of hydrophilic motifs and proteins. In addition, RP-RP/PGC is applicable to the analysis of complex glycomics samples, as demonstrated by our analysis of a concanavalin A-extracted glycoproteome from human serum; in total, 134 potentially N-glycosylated serum proteins, 151 possible N-glycosylation sites, and more than 40 possible N-glycan structures recognized by concanavalin A were simultaneously detected. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Inhibition of placental 11beta-hydroxysteroid dehydrogenase type 2 by lead.

PubMed

St-Pierre, Joey; Fraser, Marc; Vaillancourt, Cathy

2016-10-01

Lead interferes with cortisol blood concentration, increases the risk of obstetrical complications, and could alter fetal development. The placenta controls maternal cortisol transfer to the fetus by the activity of the type 2 11β-hydroxysteroid dehydrogenase (11β-HSD2), which converts cortisol into inactive cortisone. This study determines the effect of lead on the expression and activity of the placental 11β-HSD2 in human trophoblast-like BeWo cells. Cells were treated with increasing concentration (0-1000nM) of PbCl2 for 24h. 11β-HSD2 protein expression was reduced by 45% at 1000nM of PbCl 2 compared to untreated cells, while the activity was significantly reduced by PbCl 2 at 10, 100 and 1000nM. This study shows the direct inhibitory action of lead on placental 11β-HSD2 activity and suggests that this heavy metal reduces the efficiency of the placental protection against the adverse effects of high cortisol level during fetal development. Copyright © 2016 Elsevier Inc. All rights reserved.

Sorcin is involved during embryo implantation via activating VEGF/PI3K/Akt pathway in mice.

PubMed

Gupta, Kanchan; Sirohi, Vijay Kumar; Kumari, Suparna; Shukla, Vinay; Manohar, Murli; Popli, Pooja; Dwivedi, Anila

2018-02-01

Our earlier studies have demonstrated the cyclic variation and also the altered expression of sorcin in endometrium during early-to-mid-secretory phase transition in women with unexplained infertility. The current study was undertaken to establish the functional role of sorcin in endometrial receptivity in mice. Results indicated that sorcin was highly expressed during the window of implantation in mice and functional blockage of sorcin caused significant reduction in number of implanted blastocyst. The receptivity markers (i.e.Integrin β3, HBEGF, IGFBP1, WNT4 and Cyclin E)) were found to be downregulated in sorcin knocked down uterine horn on day 5 as compared to untreated horn. The reduced attachment and expansion of BeWo spheroids on RL95-2 endometrial cells with sorcin knock down, in in vitro model of endometrium-trophoblast interaction further supported these findings. Uterine sorcin expression pattern during estrous cycle and in delayed implantation mice model suggested the upregulation of sorcin by estrogen. The functional blockade of sorcin induced the intracellular Ca +2 levels in endometrial epithelial cells (EECs), which indicated that altered Ca +2 homeostasis might be responsible for implantation failure. Sorcin silencing led to significant reduction in the expression of angiogenic factor VEGF and its downstream effector molecules i.e. PI3K, Akt and NOS. The migratory and invasive properties of HUVECs were abrogated by anti-VEGF or by adding culture media from sorcin blocked EECs, which indicated that sorcin might mediate angiogenesis during implantation. Taken together, sorcin is involved in the regulation of Ca +2 -mediated angiogenesis via VEGF/PI3K/Akt pathway in endometrial cells and plays a crucial role in preparing the endometrium for implantation. © 2018 Society for Endocrinology.

Expression of a fms-related oncogene in carcinogen-induced neoplastic epithelial cells

DOE Office of Scientific and Technical Information (OSTI.GOV)

Walker, C.; Nettesheim, P.; Barrett, J.C.

1987-04-01

Following carcinogen exposure in vitro, normal rat tracheal epithelial cells are transformed in a multistage process in which the cultured cells become immortal and ultimately, neoplastic. Five cell lines derived from tumors produced by neoplastically transformed rat tracheal epithelial cells were examined for the expression of 11 cellular oncogenes previously implicated in pulmonary or epithelial carcinogenesis. RNA homologous to fms was expressed at a level 5-19 times higher than normal tracheal epithelial cells in three of five of the tumor-derived lines. All three lines expressing high levels of fms-related RNA gave rise to invasive tumors of epithelial origin when injectedmore » into nude mice. Increased expression of the fms-related mRNA was not due to gene amplification, and no gene rearrangement was detected by Southern analyses. RNA blot analysis using a 3' v-fms probe detected a 9.5-kilobase message in the three tumor-derived lines, whereas both normal rat aveolar macrophages and the human choriocarcinoma line BeWo expressed a fms transcript of approx. = 4 kilobases. The authors conclude from these data that the gene expressed as a 9.5-kilobase transcript in these neoplastic epithelial cells is a member of a fms-related gene family but may be distinct from the gene that encodes the macrophage colony-stimulating factor (CSF-1) receptor.« less

Investigations on clonazepam-loaded polymeric micelle-like nanoparticles for safe drug administration during pregnancy.

PubMed

Sezgin-Bayindir, Zerrin; Elcin, Ayse Eser; Parmaksiz, Mahmut; Elcin, Yasar Murat; Yuksel, Nilufer

2018-03-01

Medication during pregnancy is often a necessity for women to treat their acute or chronic diseases. The goal of this study is to evaluate the potential of micelle-like nanoparticles (MNP) for providing safe drug usage in pregnancy and protect both foetus and mother from medication side effects. Clonazepam-loaded MNP were prepared from copolymers [polystyrene-poly(acrylic acid) (PS-PAA), poly(ethylene glycol)-b-poly(lactic acid) (PEG-PLA) and distearyl-sn-glycero-3-phosphoethanolamine-N-[methoxy-poly(ethylene glycol) (PEG-DSPE)] with varying monomer ratios and their drug-loading efficiency, drug release ratio, particle size, surface charge and morphology were characterised. The cellular transport and cytotoxicity experiments were conducted on clonazepam and MNP formulations using placenta-choriocarcinoma-BeWo and brain-endothelial-bEnd3 cells. Clonazepam-loaded PEG 5000 -PLA 4500 MNP reduced the drug transport through BeWo cells demonstrating that MNP may lower foetal drug exposure, thus reduce the drug side effects. However, lipofectamine modified MNP improved the transport of clonazepam and found to be promising for brain and in-utero-specific drug treatment.

Hypericum caprifoliatum and Hypericum connatum affect human trophoblast-like cells differentiation and Ca2+ influx

PubMed Central

da Conceição, Aline O.; von Poser, Gilsane Lino; Barbeau, Benoit; Lafond, Julie

2014-01-01

Objective To study the effect of crude methanol and n-hexane extracts of Hypericum connatum (H. connatum) and Hypericum caprifoliatum on trophoblast-like cells. Methods BeWo and JEG-3 trophoblast-like cells were submitted to different extract concentrations (1, 5, 10 and 15 µg/mL) and evaluated in relation to cell viability and in vitro trophoblast differentiation and function. Cell viability was evaluated using WST-1 reagent. Differentiation was measured by luciferase production, hCG production/release, and mitogen-activated protein kinase signaling pathway activation. The function of the trophoblast-like cells was measured by 45Ca2+ influx evaluation. Results The results showed a decrease in cell viability/proliferation. Both plants and different extracts induced a significant decrease in hCG production/release and luciferase production. H. connatum did not cause mitogen-activated protein kinase signaling pathway disturbance; however, Hypericum caprifoliatum n-hexane extract at 15 µg/mL inhibited extracellular signal-regulated kinase 1/2 activation. The significant increase in Ca2+ influx by JEG-3 cells was seen after short and long incubation times with H. connatum methanolic extract at 15 µg/mL. Conclusions The results indicated that these two Hypericum species extracts can interfere on trophoblast differentiation and Ca2+ influx, according to their molecular diversity. Although in vivo experiments are necessary to establish their action on placental formation and function, this study suggests that attention must be paid to the potential toxic effect of these plants. PMID:25182721

Transcriptional and functional studies of Human Endogenous Retrovirus envelope EnvP(b) and EnvV genes in human trophoblasts

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vargas, Amandine, E-mail: amandine.vargas@voila.fr; Thiery, Maxime, E-mail: thiery.maxime@courrier.uqam.ca; Lafond, Julie, E-mail: lafond.julie@uqam.ca

2012-03-30

HERV (Human Endogenous Retrovirus)-encoded envelope proteins are implicated in the development of the placenta. Indeed, Syncytin-1 and -2 play a crucial role in the fusion of human trophoblasts, a key step in placentation. Other studies have identified two other HERV env proteins, namely EnvP(b) and EnvV, both expressed in the placenta. In this study, we have fully characterized both env transcripts and their expression pattern and have assessed their implication in trophoblast fusion. Through RACE analyses, standard spliced transcripts were detected, while EnvV transcripts demonstrated alternative splicing at its 3 Prime end. Promoter activity and expression of both genes weremore » induced in forskolin-stimulated BeWo cells and in primary trophoblasts. Although we have confirmed the fusogenic activity of EnvP(b), overexpression or silencing experiments revealed no impact of this protein on trophoblast fusion. Our results demonstrate that both env genes are expressed in human trophoblasts but are not required for syncytialization.« less

ABCG2/BCRP decreases the transfer of a food-born chemical carcinogen, 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP) in perfused term human placenta.

PubMed

Myllynen, Päivi; Kummu, Maria; Kangas, Tiina; Ilves, Mika; Immonen, Elina; Rysä, Jaana; Pirilä, Rauna; Lastumäki, Anni; Vähäkangas, Kirsi H

2008-10-15

We have studied the role of ATP binding cassette (ABC) transporters in fetal exposure to carcinogens using 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP) a known substrate for ABC transporters as a model compound. In perfusion of human term placenta, transfer of (14)C-PhIP (2 microM) through the placenta resulted in fetal-to-maternal concentration ratio (FM ratio) of 0.72+/-0.09 at 6 h. The specific ABCG2 inhibitor KO143 increased the transfer of (14)C-PhIP from maternal to fetal circulation (FM ratio 0.90+/-0.08 at 6 h, p<0.05) while the ABCC1/ABCC2 inhibitor probenecid had no effect (FM ratio at 6 h 0.75+/-0.10, p=0.84). There was a negative correlation between the expression of ABCG2 protein in perfused tissue and the FM ratio of (14)C-PhIP (R=-0.81, p<0.01) at the end of the perfusion. The expression of ABCC2 protein did not correlate with FM ratio of PhIP (R: -0.11, p=0.76). In addition, PhIP induced the expression of ABC transporters in BeWo cells at mRNA level. In conclusion, our data indicates that ABCG2 decreases placental transfer of (14)C-PhIP in perfused human placenta. Also, PhIP may modify ABC transporter expression in choriocarcinoma cells.

ABCG2/BCRP decreases the transfer of a food-born chemical carcinogen, 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP) in perfused term human placenta

DOE Office of Scientific and Technical Information (OSTI.GOV)

Myllynen, Paeivi; Kummu, Maria; Kangas, Tiina

2008-10-15

We have studied the role of ATP binding cassette (ABC) transporters in fetal exposure to carcinogens using 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP) a known substrate for ABC transporters as a model compound. In perfusion of human term placenta, transfer of {sup 14}C-PhIP (2 {mu}M) through the placenta resulted in fetal-to-maternal concentration ratio (FM ratio) of 0.72 {+-} 0.09 at 6 h. The specific ABCG2 inhibitor KO143 increased the transfer of {sup 14}C-PhIP from maternal to fetal circulation (FM ratio 0.90 {+-} 0.08 at 6 h, p < 0.05) while the ABCC1/ABCC2 inhibitor probenecid had no effect (FM ratio at 6 h 0.75 {+-}more » 0.10, p = 0.84). There was a negative correlation between the expression of ABCG2 protein in perfused tissue and the FM ratio of {sup 14}C-PhIP (R = - 0.81, p < 0.01) at the end of the perfusion. The expression of ABCC2 protein did not correlate with FM ratio of PhIP (R: - 0.11, p = 0.76). In addition, PhIP induced the expression of ABC transporters in BeWo cells at mRNA level. In conclusion, our data indicates that ABCG2 decreases placental transfer of {sup 14}C-PhIP in perfused human placenta. Also, PhIP may modify ABC transporter expression in choriocarinoma cells.« less

[Aromatase activities of endometrial carcinomas and both basic and clinical analyses of endometrial hyperplasia as a premalignant disease].

PubMed

Sasaki, H

1993-08-01

Paraffin-embedded materials obtained from 117 cases of endometrial hyperplasia and 84 cases of carcinoma were used for measurement of both ki-ras and p53 gene mutation and aromatase (ARO) and TGF-alpha immunostaining. The overall incidence of ki-ras mutations in the hyperplasia specimens (16%) was similar to the incidence detected in carcinomas (18%). None of 117 endometrial hyperplasias were found to have mutations in the p53 gene, whereas mutations were seen in 3 (13.3%) endometrial carcinomas. The intensity of both ARO and TGF-alpha immunostaining was increased in glands of both hyperplasia and carcinoma, and also in the interstitium of carcinoma. The positive sites of both ARO and TGF-alpha were almost the same, with an incidence below 40% in both hyperplasias and carcinomas. The cultured cells of endometrial carcinoma showed aromatase activity below MCF-7 cells, because testosterone was converted to estradiol (E2). TGF-alpha induced cell growth with at an optimal concentration. In HEC-59 cells, TGF-alpha increased both ARO-activity and mRNA. Some promoters on ARO-exon 1 in HEC-59 cells were different from those in BeWo cells. Progesterone inhibited the E2-induced excretion of pre TGF-alpha in endometrial carcinoma cells. These findings suggest that endometrial hyperplasia can be a premalignant condition of carcinoma, and can be initiated by both ki-ras codon 12 mutation and abnormal activity of ARO induced by TGF-alpha. In addition, HEC-59 cells may possess autocrine/paracrine properties involving ARO, E2 and TGF-alpha.

Rab11 family expression in the human placenta: Localization at the maternal-fetal interface

PubMed Central

Artemiuk, Patrycja A.; Hanscom, Sara R.; Lindsay, Andrew J.; Wuebbolt, Danielle; Breathnach, Fionnuala M.; Tully, Elizabeth C.; Khan, Amir R.; McCaffrey, Mary W.

2017-01-01

Rab proteins are a family of small GTPases involved in a variety of cellular processes. The Rab11 subfamily in particular directs key steps of intracellular functions involving vesicle trafficking of the endosomal recycling pathway. This Rab subfamily works through a series of effector proteins including the Rab11-FIPs (Rab11 Family-Interacting Proteins). While the Rab11 subfamily has been well characterized at the cellular level, its function within human organ systems is still being explored. In an effort to further study these proteins, we conducted a preliminary investigation of a subgroup of endosomal Rab proteins in a range of human cell lines by Western blotting. The results from this analysis indicated that Rab11a, Rab11c(Rab25) and Rab14 were expressed in a wide range of cell lines, including the human placental trophoblastic BeWo cell line. These findings encouraged us to further analyse the localization of these Rabs and their common effector protein, the Rab Coupling Protein (RCP), by immunofluorescence microscopy and to extend this work to normal human placental tissue. The placenta is a highly active exchange interface, facilitating transfer between mother and fetus during pregnancy. As Rab11 proteins are closely involved in transcytosis we hypothesized that the placenta would be an interesting human tissue model system for Rab investigation. By immunofluorescence microscopy, Rab11a, Rab11c(Rab25), Rab14 as well as their common FIP effector RCP showed prominent expression in the placental cell lines. We also identified the expression of these proteins in human placental lysates by Western blot analysis. Further, via fluorescent immunohistochemistry, we noted abundant localization of these proteins within key functional areas of primary human placental tissues, namely the outer syncytial layer of placental villous tissue and the endothelia of fetal blood vessels. Overall these findings highlight the expression of the Rab11 family within the human placenta, with novel localization at the maternal-fetal interface. PMID:28922401

Ascorbic acid transported by sodium-dependent vitamin C transporter 2 stimulates steroidogenesis in human choriocarcinoma cells.

PubMed

Wu, Ximei; Iguchi, Takuma; Itoh, Norio; Okamoto, Kousuke; Takagi, Tatsuya; Tanaka, Keiichi; Nakanishi, Tsuyoshi

2008-01-01

Reduced vitamin C [ascorbic acid (AA)], which is taken up into cells by sodium-dependent vitamin C transporter (SVCT) 1 and 2, is believed to be important for hormone synthesis, but its role in generating placental steroids needed to maintain pregnancy and fetal development is not clear. To determine the steroidogenic effect of AA and the role of SVCT2 in AA-induced steroidogenesis, we tested the effects of AA treatment and SVCT2 knockdown on steroidogenesis in human choriocarcinoma cell lines. AA treatment of JEG-3, BeWo, and JAR cells for 48-h dose dependently increased progesterone and estradiol levels. In JEG-3 cells, AA increased the mRNA expression of P450 cholesterol side-chain cleavage enzyme, 3beta-hydroxysteroid dehydrogenase type 1, and aromatase, key enzymes for steroidogenesis. Stable knockdown of SVCT2 in JEG-3 cells by retrovirally mediated RNA interference decreased the maximal velocity of AA uptake by approximately 50%, but apparent affinity values were not affected. SVCT2 knockdown in JEG-3 cells significantly suppressed the AA-induced mRNA expression of placental P450 cholesterol side-chain cleavage enzyme, 3beta-hydroxysteroid dehydrogenase type 1, and aromatase. This suppression of the AA-induced mRNA expression of steroidogenic enzymes subsequently decreased progesterone and estradiol production. In addition, inhibition of MAPK kinase-ERK signaling, which is a major pathway for AA-regulated gene expression, failed to affect AA-induced steroidogenesis. Our observations indicate that SVCT2-mediated AA uptake into cells is necessary for AA-induced steroidogenesis in human choriocarcinoma cell, but MAPK kinase-ERK signaling is not involved in AA-induced steroidogenesis.

Changes in trophoblasts gene expression in response to perchlorate exposition.

PubMed

la Peña Sol, De; Isela, Santiago-Roque; Zendy, Olivo-Vidal; Mónica, Navarro-Meza; Irene, Xochihua-Rosas; Omar, Arroyo-Helguera

2018-04-17

Contaminated water with chlorates is a public health problem associated with iodine deficiency. Epidemiological evidence shows that iodine deficiency is a risk factor for preeclampsia (PE). In this study we use human BeWo trophoblast cells exposed to perchlorate (KClO 4 ) and changes in gene expression were analyzed by microarrays, quantitative RT-PCR (qRT-PCR) and immunoblot. The microarray analysis identified 48 transcripts up-regulated and 112 down-regulated in comparison with non-exposed trophoblast. The qRT-PCR analysis confirmed changes in GAS7, PKP2, Emilin, Dynatic 3, protocadherins 11, 15, gamma A12, EGFR, SAFB1, ACE2, ANXA2, Apoliprotein E, SREBF1, and C/EBP-β. KClO 4 exposition decreased the mRNA and protein of C/EBP-β and GPX4. Also, we observed a nuclear translocation of HIF1α protein, and increase in both Snail and ACE2 protein by immunoblot. These effects were accompanied by an increases in ROS and nitric oxide. In conclusion, our results show that exposure to KClO 4 alters genes involved in migration, adhesion, differentiation, and correlate with the increase of oxidative stress and nitric oxide production in trophoblast cells. It is possible that iodine deficiency is associated with these processes. However, further studies are required to corroborate the role of iodine in trophoblast cells. Copyright © 2018 Elsevier Ltd. All rights reserved.

In vitro toxicological effects of estrogenic mycotoxins on human placental cells: Structure activity relationships

DOE Office of Scientific and Technical Information (OSTI.GOV)

Prouillac, Caroline, E-mail: c.prouillac@vetagro-sup.fr; Koraichi, Farah; Videmann, Bernadette

2012-03-15

Zearalenone (ZEN) is a non-steroid estrogen mycotoxin produced by numerous strains of Fusarium which commonly contaminate cereals. After oral administration, ZEN is reduced via intestinal and hepatic metabolism to α- and β-zearalenol (αZEL and βZEL). These reduced metabolites possess estrogenic properties, αZEL showing the highest affinity for ERs. ZEN and reduced metabolites cause hormonal effects in animals, such as abnormalities in the development of the reproductive tract and mammary gland in female offspring, suggesting a fetal exposure to these contaminants. In our previous work, we have suggested the potential impact of ZEN on placental cells considering this organ as amore » potential target of xenobiotics. In this work, we first compared the in vitro effects of αZEL and βΖΕL on cell differentiation to their parental molecule on human trophoblast (BeWo cells). Secondly, we investigated their molecular mechanisms of action by investigating the expression of main differentiation biomarkers and the implication of nuclear receptor by docking prediction. Conversely to ZEN, reduced metabolites did not induce trophoblast differentiation. They also induced significant changes in ABC transporter expression by potential interaction with nuclear receptors (LXR, PXR, PR) that could modify the transport function of placental cells. Finally, the mechanism of ZEN differentiation induction seemed not to involve nuclear receptor commonly involved in the differentiation process (PPARγ). Our results demonstrated that in spite of structure similarities between ZEN, αZEL and βZEL, toxicological effects and toxicity mechanisms were significantly different for the three molecules. -- Highlights: ► ZEN and metabolites have differential effect on trophoblast differentiation. ► ZEN and metabolites have differential effect on ABC transporter expression. ► ZEN and metabolites effects involved nuclear receptors interaction.« less

The transforming growth factor-ss superfamily cytokine macrophage inhibitory cytokine-1 is present in high concentrations in the serum of pregnant women.

PubMed

Moore, A G; Brown, D A; Fairlie, W D; Bauskin, A R; Brown, P K; Munier, M L; Russell, P K; Salamonsen, L A; Wallace, E M; Breit, S N

2000-12-01

Macrophage inhibitory cytokine-1 (MIC-1) is a recently described divergent member of the transforming growth factor-ss superfamily. MIC-1 transcription up-regulation is associated with macrophage activation, and this observation led to its cloning. Northern blots indicate that MIC-1 is also present in human placenta. A sensitive sandwich enzyme-linked immunosorbent assay for the quantification of MIC-1 was developed and used to examine the role of this cytokine in pregnancy. High levels of MIC-1 are present in the sera of pregnant women. The level rises substantially with progress of gestation. MIC-1 can also be detected, in large amounts, in amniotic fluid and placental extracts. In addition, the BeWo placental trophoblastic cell line was found to constitutively express the MIC-1 transcript and secrete large amounts of MIC-1. These findings suggest that the placental trophoblast is a major source of the MIC-1 present in maternal serum and amniotic fluid. We suggest that MIC-1 may promote fetal survival by suppressing the production of maternally derived proinflammatory cytokines within the uterus.

Overexpression of Endogenous Anti-Oxidants with Selenium Supplementation Protects Trophoblast Cells from Reactive Oxygen Species-Induced Apoptosis in a Bcl-2-Dependent Manner.

PubMed

Khera, Alisha; Vanderlelie, Jessica J; Holland, Olivia; Perkins, Anthony V

2017-06-01

The human placenta provides life support for the developing foetus, and a healthy placenta is a prerequisite to a healthy start to life. Placental tissue is subject to oxidative stress which can lead to pathological conditions of pregnancy such as preeclampsia, preterm labour and intrauterine growth restriction. Up-regulation of endogenous anti-oxidants may alleviate placental oxidative stress and provide a therapy for these complications of pregnancy. In this study, selenium supplementation, as inorganic sodium selenite (NaSel) or organic selenomethionine (SeMet), was used to increase the protein production and cellular activity of the important redox active proteins glutathione peroxidase (GPx) and thioredoxin reductase (Thx-Red). Placental trophoblast cell lines, BeWo, JEG-3 and Swan-71, were cultured in various concentrations of NaSel or SeMet for 24 h and cell extracts prepared for western blots and enzyme assays. Rotenone and antimycin were used to stimulate mitochondrial reactive oxygen species (ROS) production and induce apoptosis. Trophoblast cells supplemented with 100 nM NaSel and 500 nM SeMet exhibited significantly enhanced expression and activity of both GPx and Thx-Red. Antimycin and rotenone were found to generate ROS when measured by 2',7'-dichlorofluorescein diacetate (DCFDA) assay, and selenium supplementation was shown to reduce ROS production in a dose-dependent manner. Rotenone, 100 μM treatment for 4 h, caused trophoblast cell apoptosis as evidenced by increased Annexin V binding and decreased expression of Bcl-2. In both assays of apoptosis, selenium supplementation was able to prevent apoptosis, preserve Bcl-2 expression and protect trophoblast cells from mitochondrial oxidative stress. This data suggests that selenoproteins such as GPx and Thx-Red have an important role in protecting trophoblast cells from mitochondrial oxidative stress and that selenium supplementation may be important in treating some placental pathologies.

The effect of acetaminophen on the expression of BCRP in trophoblast cells impairs the placental barrier to bile acids during maternal cholestasis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Blazquez, Alba G., E-mail: albamgb@usal.es; CIBERehd, Instituto de Salud Carlos III, Madrid; Briz, Oscar, E-mail: obriz@usal.es

Acetaminophen is used as first-choice drug for pain relief during pregnancy. Here we have investigated the effect of acetaminophen at subtoxic doses on the expression of ABC export pumps in trophoblast cells and its functional repercussion on the placental barrier during maternal cholestasis. The incubation of human choriocarcinoma cells (JAr, JEG-3 and BeWo) with acetaminophen for 48 h resulted in no significant changes in the expression and/or activity of MDR1 and MRPs. In contrast, in JEG-3 cells, BCRP mRNA, protein, and transport activity were reduced. In rat placenta, collected at term, acetaminophen administration for the last three days of pregnancymore » resulted in enhanced mRNA, but not protein, levels of Mrp1 and Bcrp. In fact, a decrease in Bcrp protein was found. Using in situ perfused rat placenta, a reduction in the Bcrp-dependent fetal-to-maternal bile acid transport after treating the dams with acetaminophen was found. Complete biliary obstruction in pregnant rats induced a significant bile acid accumulation in fetal serum and tissues, which was further enhanced when the mothers were treated with acetaminophen. This drug induced increased ROS production in JEG-3 cells and decreased the total glutathione content in rat placenta. Moreover, the NRF2 pathway was activated in JEG-3 cells as shown by an increase in nuclear NRF2 levels and an up-regulation of NRF2 target genes, NQO1 and HMOX-1, which was not observed in rat placenta. In conclusion, acetaminophen induces in placenta oxidative stress and a down-regulation of BCRP/Bcrp, which may impair the placental barrier to bile acids during maternal cholestasis. - Highlights: • Acetaminophen induces changes in placental BCRP expression in vitro. • This drug reduces the ability of placental cells to export BCRP substrates. • Acetaminophen induces changes in Bcrp expression in rat placenta. • Placental barrier to bile acids is impaired in rats treated with this drug.« less

Expression of the vascular endothelial growth factor receptor neuropilin-1 at the human embryo-maternal interface.

PubMed

Baston-Buest, Dunja M; Porn, Anne C; Schanz, Andrea; Kruessel, Jan-S; Janni, Wolfgang; Hess, Alexandra P

2011-02-01

Angiogenesis is required for successful implantation of the invading blastocyst. Vascular endothelial growth factor (VEGF) is an important key player in angiogenesis and vascular remodeling during the implantation process. Besides its well-characterized receptors VEGFR1 and VEGFR2, neuropilin-1 (NRP-1) has been shown to play an additional role in the signaling process of angiogenesis in human endometrium during the menstrual cycle, as a co-receptor of VEGF. These findings led to the hypothesis that NRP-1 might play a role in the vascular remodeling process during embryo implantation and the establishment of a pregnancy. NRP-1 mRNA transcript and protein expression were investigated in human choriocarcinoma cell lines (JEG-3, Jar and BeWo) aiming to evaluate the expression of NRP-1 in vitro, as well as in human decidua of all three trimesters of pregnancy, by western blot analysis (three samples of each trimester of pregnancy). The localization of NRP-1 in human decidua of all three trimesters of pregnancy was analyzed by immunohistochemistry (five samples of each trimester of pregnancy). NRP-1 transcript and protein were expressed in all cell lines examined. Corresponding to the analysis of human tissue by western blot and the localization by immunohistochemistry, NRP-1 protein higher expressed in samples of early pregnancy in comparison to the end of pregnancy. NRP-1 was expressed in the decidua, villi and invading cytotrophoblast of all samples investigated. This is the first study clearly showing the expression of NRP-1 in human decidua and trophoblast, suggesting an important role for the VEGF co-receptor NRP-1 besides the established receptor VEGFR2 at the embryo-maternal interface during embryonic implantation and placentation. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

[Cytogenomic studies of hydatiform moles and gestational choriocarcinoma].

PubMed

Poaty, Henriette; Coullin, Philippe; Leguern, Eric; Dessen, Philippe; Valent, Alexandre; Afoutou, José-Marie; Peko, Jean-Félix; Candelier, Jean-Jacques; Gombé-Mbalawa, Charles; Picard, Jean-Yves; Bernheim, Alain

2012-09-01

The complete hydatidiform mole (CHM), a gestational trophoblastic disease, is usually caused by the development of an androgenic egg whose genome is exclusively paternal. Due to parental imprinting, only trophoblasts develop in the absence of a fetus. CHM are diploid and no abnormal karyotype is observed. It is 46,XX in most cases and less frequently 46,XY. The major complication of this disease is gestational choriocarcinoma, a metastasizing tumor and a true allografted malignancy. This complication is infrequent in developed countries, but is more common in the developing countries and is then worsened by delayed care. The malignancies are often accompanied by acquired, possibly etiological genomic abnormalities. We investigated the presence of recurrent cytogenetic abnormalities in CHM and post-molar choriocarcinoma using metaphasic CGH (mCGH) and high-resolution 244K aCGH techniques. The 10 CHM studied by mCGH showed no chromosomal gains or losses. For post-molar choriocarcinoma, 11 tumors, whose diagnosis was verified by histopathology, were investigated by aCGH. Their androgenic nature and the absence of tumor DNA contamination by maternal DNA were verified by the analysis of microsatellite markers. Three choriocarcinoma cell lines (BeWo, JAR and JEG) were also analyzed by aCGH. The results allowed us to observe some chromosomal rearrangements in primary tumors, and more in the cell lines. Chromosomal abnormalities were confirmed by FISH and functional effect by immunohistochemical analysis of gene expression. Forty minimum critical regions (MCR) were defined on chromosomes. Candidate genes implicated in choriocarcinoma oncogenesis were selected. The presence in the MCR of many miRNA clusters whose expression is modulated by parental imprinting has been observed, for example in 14q32 or in 19q13.4. This suggests that, in gestational choriocarcinoma, the consequences of gene abnormalities directly linked to acquired chromosomal abnormalities are superimposed upon those of imprinted genes altered at fertilization.

The Alternative Epac/cAMP Pathway and the MAPK Pathway Mediate hCG Induction of Leptin in Placental Cells

PubMed Central

Maymó, Julieta Lorena; Pérez Pérez, Antonio; Maskin, Bernardo; Dueñas, José Luis; Calvo, Juan Carlos; Sánchez Margalet, Víctor; Varone, Cecilia Laura

2012-01-01

Pleiotropic effects of leptin have been identified in reproduction and pregnancy, particularly in the placenta, where it works as an autocrine hormone. In this work, we demonstrated that human chorionic gonadotropin (hCG) added to JEG-3 cell line or to placental explants induces endogenous leptin expression. We also found that hCG increased cAMP intracellular levels in BeWo cells in a dose-dependent manner, stimulated cAMP response element (CRE) activity and the cotransfection with an expression plasmid of a dominant negative mutant of CREB caused a significant inhibition of hCG stimulation of leptin promoter activity. These results demonstrate that hCG indeed activates cAMP/PKA pathway, and that this pathway is involved in leptin expression. Nevertheless, we found leptin induction by hCG is dependent on cAMP levels. Treatment with (Bu)2cAMP in combination with low and non stimulatory hCG concentrations led to an increase in leptin expression, whereas stimulatory concentrations showed the opposite effect. We found that specific PKA inhibition by H89 caused a significant increase of hCG leptin induction, suggesting that probably high cAMP levels might inhibit hCG effect. It was found that hCG enhancement of leptin mRNA expression involved the MAPK pathway. In this work, we demonstrated that hCG leptin induction through the MAPK signaling pathway is inhibited by PKA. We observed that ERK1/2 phosphorylation increased when hCG treatment was combined with H89. In view of these results, the involvement of the alternative cAMP/Epac signaling pathway was studied. We observed that a cAMP analogue that specifically activates Epac (CPT-OMe) stimulated leptin expression by hCG. In addition, the overexpression of Epac and Rap1 proteins increased leptin promoter activity and enhanced hCG. In conclusion, we provide evidence suggesting that hCG induction of leptin gene expression in placenta is mediated not only by activation of the MAPK signaling pathway but also by the alternative cAMP/Epac signaling pathway. PMID:23056265

HYDROXYCHLOROQUINE REDUCES BINDING OF ANTIPHOSPHOLIPID ANTIBODIES TO SYNCYTIOTROPHOBLASTS AND RESTORES ANNEXIN A5 EXPRESSION

PubMed Central

Wu, Xiao-Xuan; Guller, Seth; Rand, Jacob H.

2011-01-01

Objectives Antibody-mediated disruption of the annexin A5 (AnxA5) anticoagulant shield has been posited to be a thrombogenic mechanism in the antiphospholipid syndrome. We recently showed that the antimalarial drug, hydroxychloroquine, dissociates antiphospholipid immune complexes and restores AnxA5 binding to planar phospholipid bilayer. Using quantitative immunoassays, we demonstrated similar effects on BeWo trophoblasts. We therefore investigated the effects of the drug on localization of AnxA5 in primary cultures of human placental syncytiotrophoblasts (SCTs). Study Laser confocal microscopy with computer-based morphometric analysis was used to localize AnxA5 and antiphospholipid antibodies on SCTs exposed to polyclonal and monoclonal antiphospholipid and control IgGs. Results Hydroxychloroquine reversed the effects of the antiphospholipid antibodies on the SCTs by markedly reducing IgG binding and restoring AnxA5 expression. Conclusions These results provide the first morphologic evidence for this effect of hydroxychloroquine on human placental SCTs and support the possibility of novel treatments that target antiphospholipid antibody binding. PMID:21871597

An EG-VEGF-dependent decrease in homeobox gene NKX3.1 contributes to cytotrophoblast dysfunction: a possible mechanism in human fetal growth restriction.

PubMed

Murthi, P; Brouillet, S; Pratt, A; Borg, Aj; Kalionis, B; Goffin, F; Tsatsaris, V; Munaut, C; Feige, Jj; Benharouga, M; Fournier, T; Alfaidy, N

2015-07-21

Idiopathic fetal growth restriction (FGR) is frequently associated with placental insufficiency. Previous reports have provided evidence that EG-VEGF (endocrine gland derived-vascular endothelial growth factor), a placental secreted protein, is expressed during the first trimester of pregnancy, controls both trophoblast proliferation and invasion, and its increased expression is associated with human FGR. In this study, we hypothesise that EG-VEGF-dependent change in placental homeobox gene expressions contribute to trophoblast dysfunction in idiopathic FGR. The changes in EG-VEGF-dependent homeobox gene expressions were determined using a Homeobox gene cDNA array on placental explants of 8-12 weeks' gestation after stimulation with EG-VEGF in vitro for 24 hours. The Homeobox gene array identified a >5-fold increase in HOXA9, HOXC8, HOXC10, HOXD1, HOXD8, HOXD9 and HOXD11, while NKX 3.1 showed a >2 fold-decrease in mRNA expression compared to untreated controls. Homeobox gene NKX3.1 was selected as a candidate because it is a downstream target of EG-VEGF and its expression and functional role are largely unknown in control and idiopathic FGR-affected placentae. Real-time PCR and immunoblotting showed a significant decrease in NKX3.1 mRNA and protein levels, respectively, in placentae from FGR compared to control pregnancies. Gene inactivation in vitro using short-interference RNA specific for NKX3.1 demonstrated an increase in BeWo cell differentiation and a decrease in HTR8-SVneo proliferation. We conclude that the decreased expression of homeobox gene NKX3.1 down-stream of EG-VEGF may contribute to the trophoblast dysfunction associated with idiopathic FGR pregnancies.

Aldo-keto Reductase 1B15 (AKR1B15)

PubMed Central

Weber, Susanne; Salabei, Joshua K.; Möller, Gabriele; Kremmer, Elisabeth; Bhatnagar, Aruni; Adamski, Jerzy; Barski, Oleg A.

2015-01-01

Aldo-keto reductases (AKRs) comprise a superfamily of proteins involved in the reduction and oxidation of biogenic and xenobiotic carbonyls. In humans, at least 15 AKR superfamily members have been identified so far. One of these is a newly identified gene locus, AKR1B15, which clusters on chromosome 7 with the other human AKR1B subfamily members (i.e. AKR1B1 and AKR1B10). We show that alternative splicing of the AKR1B15 gene transcript gives rise to two protein isoforms with different N termini: AKR1B15.1 is a 316-amino acid protein with 91% amino acid identity to AKR1B10; AKR1B15.2 has a prolonged N terminus and consists of 344 amino acid residues. The two gene products differ in their expression level, subcellular localization, and activity. In contrast with other AKR enzymes, which are mostly cytosolic, AKR1B15.1 co-localizes with the mitochondria. Kinetic studies show that AKR1B15.1 is predominantly a reductive enzyme that catalyzes the reduction of androgens and estrogens with high positional selectivity (17β-hydroxysteroid dehydrogenase activity) as well as 3-keto-acyl-CoA conjugates and exhibits strong cofactor selectivity toward NADP(H). In accordance with its substrate spectrum, the enzyme is expressed at the highest levels in steroid-sensitive tissues, namely placenta, testis, and adipose tissue. Placental and adipose expression could be reproduced in the BeWo and SGBS cell lines, respectively. In contrast, AKR1B15.2 localizes to the cytosol and displays no enzymatic activity with the substrates tested. Collectively, these results demonstrate the existence of a novel catalytically active AKR, which is associated with mitochondria and expressed mainly in steroid-sensitive tissues. PMID:25577493

Preeclampsia Is Associated with Alterations in the p53-Pathway in Villous Trophoblast

PubMed Central

Sharp, Andrew N.; Heazell, Alexander E. P.; Baczyk, Dora; Dunk, Caroline E.; Lacey, Helen A.; Jones, Carolyn J. P.; Perkins, Jonathan E.; Kingdom, John C. P.; Baker, Philip N.; Crocker, Ian P.

2014-01-01

Background Preeclampsia (PE) is characterized by exaggerated apoptosis of the villous trophoblast of placental villi. Since p53 is a critical regulator of apoptosis we hypothesized that excessive apoptosis in PE is mediated by abnormal expression of proteins participating in the p53 pathway and that modulation of the p53 pathway alters trophoblast apoptosis in vitro. Methods Fresh placental villous tissue was collected from normal pregnancies and pregnancies complicated by PE; Western blotting and real-time PCR were performed on tissue lysate for protein and mRNA expression of p53 and downstream effector proteins, p21, Bax and caspases 3 and 8. To further assess the ability of p53 to modulate apoptosis within trophoblast, BeWo cells and placental villous tissue were exposed to the p53-activator, Nutlin-3, alone or in combination with the p53-inhibitor, Pifithrin-α (PFT- α). Equally, Mdm2 was knocked-down with siRNA. Results Protein expression of p53, p21 and Bax was significantly increased in pregnancies complicated by PE. Conversely, Mdm2 protein levels were significantly depleted in PE; immunohistochemistry showed these changes to be confined to trophoblast. Reduction in the negative feedback of p53 by Mdm2, using siRNA and Nutlin-3, caused an imbalance between p53 and Mdm2 that triggered apoptosis in term villous explants. In the case of Nutlin, this was attenuated by Pifithrin-α. Conclusions These data illustrate the potential for an imbalance in p53 and Mdm2 expression to promote excessive apoptosis in villous trophoblast. The upstream regulation of p53 and Mdm2, with regard to exaggerated apoptosis and autophagy in PE, merits further investigation. PMID:24498154

Preeclampsia is associated with alterations in the p53-pathway in villous trophoblast.

PubMed

Sharp, Andrew N; Heazell, Alexander E P; Baczyk, Dora; Dunk, Caroline E; Lacey, Helen A; Jones, Carolyn J P; Perkins, Jonathan E; Kingdom, John C P; Baker, Philip N; Crocker, Ian P

2014-01-01

Preeclampsia (PE) is characterized by exaggerated apoptosis of the villous trophoblast of placental villi. Since p53 is a critical regulator of apoptosis we hypothesized that excessive apoptosis in PE is mediated by abnormal expression of proteins participating in the p53 pathway and that modulation of the p53 pathway alters trophoblast apoptosis in vitro. Fresh placental villous tissue was collected from normal pregnancies and pregnancies complicated by PE; Western blotting and real-time PCR were performed on tissue lysate for protein and mRNA expression of p53 and downstream effector proteins, p21, Bax and caspases 3 and 8. To further assess the ability of p53 to modulate apoptosis within trophoblast, BeWo cells and placental villous tissue were exposed to the p53-activator, Nutlin-3, alone or in combination with the p53-inhibitor, Pifithrin-α (PFT-α). Equally, Mdm2 was knocked-down with siRNA. Protein expression of p53, p21 and Bax was significantly increased in pregnancies complicated by PE. Conversely, Mdm2 protein levels were significantly depleted in PE; immunohistochemistry showed these changes to be confined to trophoblast. Reduction in the negative feedback of p53 by Mdm2, using siRNA and Nutlin-3, caused an imbalance between p53 and Mdm2 that triggered apoptosis in term villous explants. In the case of Nutlin, this was attenuated by Pifithrin-α. These data illustrate the potential for an imbalance in p53 and Mdm2 expression to promote excessive apoptosis in villous trophoblast. The upstream regulation of p53 and Mdm2, with regard to exaggerated apoptosis and autophagy in PE, merits further investigation.

Prenatal caffeine exposure induced a lower level of fetal blood leptin mainly via placental mechanism

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, Yi-meng; Luo, Han-wen; Kou, Hao

It's known that blood leptin level is reduced in intrauterine growth retardation (IUGR) fetus, and placental leptin is the major source of fetal blood leptin. This study aimed to investigate the decreased fetal blood leptin level by prenatal caffeine exposure (PCE) and its underlying placental mechanisms. Pregnant Wistar rats were intragastrically administered caffeine (30–120 mg/kg day) from gestational day 9 to 20. The level of fetal serum leptin and the expression of placental leptin-related genes were analyzed. Furthermore, we investigated the molecular mechanism of the reduced placental leptin's expression by treatment with caffeine (0.8–20 μM) in the BeWo cells. Inmore » vivo, PCE significantly decreased fetal serum leptin level in caffeine dose-dependent manner. Meanwhile, placental mRNA expression of adenosine A2a receptor (Adora2a), cAMP-response element binding protein (CREB), a short-type leptin receptor (Ob-Ra) and leptin was reduced in the PCE groups. In vitro, caffeine significantly decreased the mRNA expression of leptin, CREB and ADORA2A in concentration and time-dependent manners. The addition of ADORA2A agonist or adenylyl cyclase (AC) agonist reversed the inhibition of leptin expression induced by caffeine. PCE induced a lower level of fetal blood leptin, which the primary mechanism is that caffeine inhibited antagonized Adora2a and AC activities to decreased cAMP synthesis, thus inhibited the expression of the transcription factor CREB and target gene leptin in the placenta. Meantime, the reduced transportation of maternal leptin by placental Ob-Ra also contributed to the reduced fetal blood leptin. Together, PCE decreased fetal blood leptin mainly via reducing the expression and transportation of leptin in the placenta. - Highlights: • Caffeine reduced fetal blood leptin level. • Caffeine inhibited placental leptin production and transport. • Caffeine down-regulated placental leptin expression via antagonizing ADORA2. • Caffeine inhibited placental leptin transport via decreased OB-Ra expression.« less

nAChRs-ERK1/2-Egr-1 signaling participates in the developmental toxicity of nicotine by epigenetically down-regulating placental 11β-HSD2.

PubMed

Zhou, Jin; Liu, Fulin; Yu, Luting; Xu, Dan; Li, Bin; Zhang, Guohui; Huang, Wen; Li, Lu; Zhang, Yuanzhen; Zhang, Wei; Wang, Hui

2018-04-01

Impaired placental 11β-hydroxysteroid dehydrogenase type 2 (11β-HSD2) activity which inactivates maternal glucocorticoids is associated with poor fetal growth and a higher risk of chronic diseases in adulthood. This study aimed to elucidate the epigenetically regulatory mechanism of nicotine on placental 11β-HSD2 expression. Pregnant Wistar rats were administered 1.0 mg/kg nicotine subcutaneously twice a day from gestational day 9 to 20. The results showed that prenatal nicotine exposure increased corticosterone levels in the placenta and fetal serum, disrupted placental morphology and endocrine function, and reduced fetal bodyweight. Meanwhile, histone modification abnormalities (decreased acetylation and increased di-methylation of histone 3 Lysine 9) on the HSD11B2 promoter and lower-expression of 11β-HSD2 were observed. Furthermore, the expression of nicotinic acetylcholine receptor (nAChR) α4/β2, the phosphorylation of extracellular regulated kinase 1/2 (ERK1/2) and Ets-like protein-1 (Elk-1), and the expression of early growth response-1 (Egr-1) were increased in the nicotine groups. In human BeWo cells, nicotine decreased 11β-HSD2 expression, increased nAChRα9 expression, and activated ERK1/2/Elk-1/Egr-1 signaling in the concentration (0.1-10 μM)-dependent manner. Antagonism of nAChRs, inhibition of ERK1/2 and Egr-1 knockdown by siRNA were able to block/abrogate the effects of nicotine on histone modification and expression of 11β-HSD2. Taken together, nicotine can impair placental structure and function, and induce fetal developmental toxicity. The underlying mechanism involves histone modifications and down-regulation of 11β-HSD2 through nAChRs/ERK1/2/Elk-1/Egr-1 signaling, which increases active glucocorticoids levels in the placenta and fetus, and eventually inhibits the fetal development. Copyright © 2018 Elsevier Inc. All rights reserved.

Modeling keratinocyte wound healing dynamics: Cell-cell adhesion promotes sustained collective migration.

PubMed

Nardini, John T; Chapnick, Douglas A; Liu, Xuedong; Bortz, David M

2016-07-07

The in vitro migration of keratinocyte cell sheets displays behavioral and biochemical similarities to the in vivo wound healing response of keratinocytes in animal model systems. In both cases, ligand-dependent Epidermal Growth Factor Receptor (EGFR) activation is sufficient to elicit collective cell migration into the wound. Previous mathematical modeling studies of in vitro wound healing assays assume that physical connections between cells have a hindering effect on cell migration, but biological literature suggests a more complicated story. By combining mathematical modeling and experimental observations of collectively migrating sheets of keratinocytes, we investigate the role of cell-cell adhesion during in vitro keratinocyte wound healing assays. We develop and compare two nonlinear diffusion models of the wound healing process in which cell-cell adhesion either hinders or promotes migration. Both models can accurately fit the leading edge propagation of cell sheets during wound healing when using a time-dependent rate of cell-cell adhesion strength. The model that assumes a positive role of cell-cell adhesion on migration, however, is robust to changes in the leading edge definition and yields a qualitatively accurate density profile. Using RNAi for the critical adherens junction protein, α-catenin, we demonstrate that cell sheets with wild type cell-cell adhesion expression maintain migration into the wound longer than cell sheets with decreased cell-cell adhesion expression, which fails to exhibit collective migration. Our modeling and experimental data thus suggest that cell-cell adhesion promotes sustained migration as cells pull neighboring cells into the wound during wound healing. Copyright © 2016 Elsevier Ltd. All rights reserved.

Power-Law Modeling of Cancer Cell Fates Driven by Signaling Data to Reveal Drug Effects

PubMed Central

Zhang, Fan; Wu, Min; Kwoh, Chee Keong; Zheng, Jie

2016-01-01

Extracellular signals are captured and transmitted by signaling proteins inside a cell. An important type of cellular responses to the signals is the cell fate decision, e.g., apoptosis. However, the underlying mechanisms of cell fate regulation are still unclear, thus comprehensive and detailed kinetic models are not yet available. Alternatively, data-driven models are promising to bridge signaling data with the phenotypic measurements of cell fates. The traditional linear model for data-driven modeling of signaling pathways has its limitations because it assumes that the a cell fate is proportional to the activities of signaling proteins, which is unlikely in the complex biological systems. Therefore, we propose a power-law model to relate the activities of all the measured signaling proteins to the probabilities of cell fates. In our experiments, we compared our nonlinear power-law model with the linear model on three cancer datasets with phosphoproteomics and cell fate measurements, which demonstrated that the nonlinear model has superior performance on cell fates prediction. By in silico simulation of virtual protein knock-down, the proposed model is able to reveal drug effects which can complement traditional approaches such as binding affinity analysis. Moreover, our model is able to capture cell line specific information to distinguish one cell line from another in cell fate prediction. Our results show that the power-law data-driven model is able to perform better in cell fate prediction and provide more insights into the signaling pathways for cancer cell fates than the linear model. PMID:27764199

Computer support for physiological cell modelling using an ontology on cell physiology.

PubMed

Takao, Shimayoshi; Kazuhiro, Komurasaki; Akira, Amano; Takeshi, Iwashita; Masanori, Kanazawa; Tetsuya, Matsuda

2006-01-01

The development of electrophysiological whole cell models to support the understanding of biological mechanisms is increasing rapidly. Due to the complexity of biological systems, comprehensive cell models, which are composed of many imported sub-models of functional elements, can get quite complicated as well, making computer modification difficult. Here, we propose a computer support to enhance structural changes of cell models, employing the markup languages CellML and our original PMSML (physiological model structure markup language), in addition to a new ontology for cell physiological modelling. In particular, a method to make references from CellML files to the ontology and a method to assist manipulation of model structures using markup languages together with the ontology are reported. Using these methods three software utilities, including a graphical model editor, are implemented. Experimental results proved that these methods are effective for the modification of electrophysiological models.

Developing global regression models for metabolite concentration prediction regardless of cell line.

PubMed

André, Silvère; Lagresle, Sylvain; Da Sliva, Anthony; Heimendinger, Pierre; Hannas, Zahia; Calvosa, Éric; Duponchel, Ludovic

2017-11-01

Following the Process Analytical Technology (PAT) of the Food and Drug Administration (FDA), drug manufacturers are encouraged to develop innovative techniques in order to monitor and understand their processes in a better way. Within this framework, it has been demonstrated that Raman spectroscopy coupled with chemometric tools allow to predict critical parameters of mammalian cell cultures in-line and in real time. However, the development of robust and predictive regression models clearly requires many batches in order to take into account inter-batch variability and enhance models accuracy. Nevertheless, this heavy procedure has to be repeated for every new line of cell culture involving many resources. This is why we propose in this paper to develop global regression models taking into account different cell lines. Such models are finally transferred to any culture of the cells involved. This article first demonstrates the feasibility of developing regression models, not only for mammalian cell lines (CHO and HeLa cell cultures), but also for insect cell lines (Sf9 cell cultures). Then global regression models are generated, based on CHO cells, HeLa cells, and Sf9 cells. Finally, these models are evaluated considering a fourth cell line(HEK cells). In addition to suitable predictions of glucose and lactate concentration of HEK cell cultures, we expose that by adding a single HEK-cell culture to the calibration set, the predictive ability of the regression models are substantially increased. In this way, we demonstrate that using global models, it is not necessary to consider many cultures of a new cell line in order to obtain accurate models. Biotechnol. Bioeng. 2017;114: 2550-2559. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Stochastic cellular automata model of cell migration, proliferation and differentiation: validation with in vitro cultures of muscle satellite cells.

PubMed

Garijo, N; Manzano, R; Osta, R; Perez, M A

2012-12-07

Cell migration and proliferation has been modelled in the literature as a process similar to diffusion. However, using diffusion models to simulate the proliferation and migration of cells tends to create a homogeneous distribution in the cell density that does not correlate to empirical observations. In fact, the mechanism of cell dispersal is not diffusion. Cells disperse by crawling or proliferation, or are transported in a moving fluid. The use of cellular automata, particle models or cell-based models can overcome this limitation. This paper presents a stochastic cellular automata model to simulate the proliferation, migration and differentiation of cells. These processes are considered as completely stochastic as well as discrete. The model developed was applied to predict the behaviour of in vitro cell cultures performed with adult muscle satellite cells. Moreover, non homogeneous distribution of cells has been observed inside the culture well and, using the above mentioned stochastic cellular automata model, we have been able to predict this heterogeneous cell distribution and compute accurate quantitative results. Differentiation was also incorporated into the computational simulation. The results predicted the myotube formation that typically occurs with adult muscle satellite cells. In conclusion, we have shown how a stochastic cellular automata model can be implemented and is capable of reproducing the in vitro behaviour of adult muscle satellite cells. Copyright © 2012 Elsevier Ltd. All rights reserved.

Modelling cell population growth with applications to cancer therapy in human tumour cell lines.

PubMed

Basse, Britta; Baguley, Bruce C; Marshall, Elaine S; Wake, Graeme C; Wall, David J N

2004-01-01

In this paper we present an overview of the work undertaken to model a population of cells and the effects of cancer therapy. We began with a theoretical one compartment size structured cell population model and investigated its asymptotic steady size distributions (SSDs) (On a cell growth model for plankton, MMB JIMA 21 (2004) 49). However these size distributions are not similar to the DNA (size) distributions obtained experimentally via the flow cytometric analysis of human tumour cell lines (data obtained from the Auckland Cancer Society Research Centre, New Zealand). In our one compartment model, size was a generic term, but in order to obtain realistic steady size distributions we chose size to be DNA content and devised a multi-compartment mathematical model for the cell division cycle where each compartment corresponds to a distinct phase of the cell cycle (J. Math. Biol. 47 (2003) 295). We then incorporated another compartment describing the possible induction of apoptosis (cell death) from mitosis phase (Modelling cell death in human tumour cell lines exposed to anticancer drug paclitaxel, J. Math. Biol. 2004, in press). This enabled us to compare our model to flow cytometric data of a melanoma cell line where the anticancer drug, paclitaxel, had been added. The model gives a dynamic picture of the effects of paclitaxel on the cell cycle. We hope to use the model to describe the effects of other cancer therapies on a number of different cell lines. Copyright 2004 Elsevier Ltd.

Rule-Based Simulation of Multi-Cellular Biological Systems—A Review of Modeling Techniques

PubMed Central

Hwang, Minki; Garbey, Marc; Berceli, Scott A.; Tran-Son-Tay, Roger

2011-01-01

Emergent behaviors of multi-cellular biological systems (MCBS) result from the behaviors of each individual cells and their interactions with other cells and with the environment. Modeling MCBS requires incorporating these complex interactions among the individual cells and the environment. Modeling approaches for MCBS can be grouped into two categories: continuum models and cell-based models. Continuum models usually take the form of partial differential equations, and the model equations provide insight into the relationship among the components in the system. Cell-based models simulate each individual cell behavior and interactions among them enabling the observation of the emergent system behavior. This review focuses on the cell-based models of MCBS, and especially, the technical aspect of the rule-based simulation method for MCBS is reviewed. How to implement the cell behaviors and the interactions with other cells and with the environment into the computational domain is discussed. The cell behaviors reviewed in this paper are division, migration, apoptosis/necrosis, and differentiation. The environmental factors such as extracellular matrix, chemicals, microvasculature, and forces are also discussed. Application examples of these cell behaviors and interactions are presented. PMID:21369345

Assessment of Cell Line Models of Primary Human Cells by Raman Spectral Phenotyping

PubMed Central

Swain, Robin J.; Kemp, Sarah J.; Goldstraw, Peter; Tetley, Teresa D.; Stevens, Molly M.

2010-01-01

Abstract Researchers have previously questioned the suitability of cell lines as models for primary cells. In this study, we used Raman microspectroscopy to characterize live A549 cells from a unique molecular biochemical perspective to shed light on their suitability as a model for primary human pulmonary alveolar type II (ATII) cells. We also investigated a recently developed transduced type I (TT1) cell line as a model for alveolar type I (ATI) cells. Single-cell Raman spectra provide unique biomolecular fingerprints that can be used to characterize cellular phenotypes. A multivariate statistical analysis of Raman spectra indicated that the spectra of A549 and TT1 cells are characterized by significantly lower phospholipid content compared to ATII and ATI spectra because their cytoplasm contains fewer surfactant lamellar bodies. Furthermore, we found that A549 spectra are statistically more similar to ATI spectra than to ATII spectra. The spectral variation permitted phenotypic classification of cells based on Raman spectral signatures with >99% accuracy. These results suggest that A549 cells are not a good model for ATII cells, but TT1 cells do provide a reasonable model for ATI cells. The findings have far-reaching implications for the assessment of cell lines as suitable primary cellular models in live cultures. PMID:20409492

Comparison of a Rat Primary Cell-Based Blood-Brain Barrier Model With Epithelial and Brain Endothelial Cell Lines: Gene Expression and Drug Transport.

PubMed

Veszelka, Szilvia; Tóth, András; Walter, Fruzsina R; Tóth, Andrea E; Gróf, Ilona; Mészáros, Mária; Bocsik, Alexandra; Hellinger, Éva; Vastag, Monika; Rákhely, Gábor; Deli, Mária A

2018-01-01

Cell culture-based blood-brain barrier (BBB) models are useful tools for screening of CNS drug candidates. Cell sources for BBB models include primary brain endothelial cells or immortalized brain endothelial cell lines. Despite their well-known differences, epithelial cell lines are also used as surrogate models for testing neuropharmaceuticals. The aim of the present study was to compare the expression of selected BBB related genes including tight junction proteins, solute carriers (SLC), ABC transporters, metabolic enzymes and to describe the paracellular properties of nine different culture models. To establish a primary BBB model rat brain capillary endothelial cells were co-cultured with rat pericytes and astrocytes (EPA). As other BBB and surrogate models four brain endothelial cells lines, rat GP8 and RBE4 cells, and human hCMEC/D3 cells with or without lithium treatment (D3 and D3L), and four epithelial cell lines, native human intestinal Caco-2 and high P-glycoprotein expressing vinblastine-selected VB-Caco-2 cells, native MDCK and MDR1 transfected MDCK canine kidney cells were used. To test transporter functionality, the permeability of 12 molecules, glucopyranose, valproate, baclofen, gabapentin, probenecid, salicylate, rosuvastatin, pravastatin, atorvastatin, tacrine, donepezil, was also measured in the EPA and epithelial models. Among the junctional protein genes, the expression level of occludin was high in all models except the GP8 and RBE4 cells, and each model expressed a unique claudin pattern. Major BBB efflux (P-glycoprotein or ABCB1) and influx transporters (GLUT-1, LAT-1) were present in all models at mRNA levels. The transcript of BCRP (ABCG2) was not expressed in MDCK, GP8 and RBE4 cells. The absence of gene expression of important BBB efflux and influx transporters BCRP, MRP6, -9, MCT6, -8, PHT2, OATPs in one or both types of epithelial models suggests that Caco-2 or MDCK models are not suitable to test drug candidates which are substrates of these transporters. Brain endothelial cell lines GP8, RBE4, D3 and D3L did not form a restrictive paracellular barrier necessary for screening small molecular weight pharmacons. Therefore, among the tested culture models, the primary cell-based EPA model is suitable for the functional analysis of the BBB.

Regulatory T cell effects in antitumor laser immunotherapy: a mathematical model and analysis

NASA Astrophysics Data System (ADS)

Dawkins, Bryan A.; Laverty, Sean M.

2016-03-01

Regulatory T cells (Tregs) have tremendous influence on treatment outcomes in patients receiving immunotherapy for cancerous tumors. We present a mathematical model incorporating the primary cellular and molecular components of antitumor laser immunotherapy. We explicitly model developmental classes of dendritic cells (DCs), cytotoxic T cells (CTLs), primary and metastatic tumor cells, and tumor antigen. Regulatory T cells have been shown to kill antigen presenting cells, to influence dendritic cell maturation and migration, to kill activated killer CTLs in the tumor microenvironment, and to influence CTL proliferation. Since Tregs affect explicitly modeled cells, but we do not explicitly model dynamics of Treg themselves, we use model parameters to analyze effects of Treg immunosuppressive activity. We will outline a systematic method for assigning clinical outcomes to model simulations and use this condition to associate simulated patient treatment outcome with Treg activity.

Continuum-level modelling of cellular adhesion and matrix production in aggregates.

PubMed

Geris, Liesbet; Ashbourn, Joanna M A; Clarke, Tim

2011-05-01

Key regulators in tissue-engineering processes such as cell culture and cellular organisation are the cell-cell and cell-matrix interactions. As mathematical models are increasingly applied to investigate biological phenomena in the biomedical field, it is important, for some applications, that these models incorporate an adequate description of cell adhesion. This study describes the development of a continuum model that represents a cell-in-gel culture system used in bone-tissue engineering, namely that of a cell aggregate embedded in a hydrogel. Cell adhesion is modelled through the use of non-local (integral) terms in the partial differential equations. The simulation results demonstrate that the effects of cell-cell and cell-matrix adhesion are particularly important for the survival and growth of the cell population and the production of extracellular matrix by the cells, concurring with experimental observations in the literature.

The statistical geometry of transcriptome divergence in cell-type evolution and cancer.

PubMed

Liang, Cong; Forrest, Alistair R R; Wagner, Günter P

2015-01-14

In evolution, body plan complexity increases due to an increase in the number of individualized cell types. Yet, there is very little understanding of the mechanisms that produce this form of organismal complexity. One model for the origin of novel cell types is the sister cell-type model. According to this model, each cell type arises together with a sister cell type through specialization from an ancestral cell type. A key prediction of the sister cell-type model is that gene expression profiles of cell types exhibit tree structure. Here we present a statistical model for detecting tree structure in transcriptomic data and apply it to transcriptomes from ENCODE and FANTOM5. We show that transcriptomes of normal cells harbour substantial amounts of hierarchical structure. In contrast, cancer cell lines have less tree structure, suggesting that the emergence of cancer cells follows different principles from that of evolutionary cell-type origination.

Physical models of collective cell motility: from cell to tissue

NASA Astrophysics Data System (ADS)

Camley, B. A.; Rappel, W.-J.

2017-03-01

In this article, we review physics-based models of collective cell motility. We discuss a range of techniques at different scales, ranging from models that represent cells as simple self-propelled particles to phase field models that can represent a cell’s shape and dynamics in great detail. We also extensively review the ways in which cells within a tissue choose their direction, the statistics of cell motion, and some simple examples of how cell-cell signaling can interact with collective cell motility. This review also covers in more detail selected recent works on collective cell motion of small numbers of cells on micropatterns, in wound healing, and the chemotaxis of clusters of cells.

CellML metadata standards, associated tools and repositories

PubMed Central

Beard, Daniel A.; Britten, Randall; Cooling, Mike T.; Garny, Alan; Halstead, Matt D.B.; Hunter, Peter J.; Lawson, James; Lloyd, Catherine M.; Marsh, Justin; Miller, Andrew; Nickerson, David P.; Nielsen, Poul M.F.; Nomura, Taishin; Subramanium, Shankar; Wimalaratne, Sarala M.; Yu, Tommy

2009-01-01

The development of standards for encoding mathematical models is an important component of model building and model sharing among scientists interested in understanding multi-scale physiological processes. CellML provides such a standard, particularly for models based on biophysical mechanisms, and a substantial number of models are now available in the CellML Model Repository. However, there is an urgent need to extend the current CellML metadata standard to provide biological and biophysical annotation of the models in order to facilitate model sharing, automated model reduction and connection to biological databases. This paper gives a broad overview of a number of new developments on CellML metadata and provides links to further methodological details available from the CellML website. PMID:19380315

Summary of the DREAM8 Parameter Estimation Challenge: Toward Parameter Identification for Whole-Cell Models.

PubMed

Karr, Jonathan R; Williams, Alex H; Zucker, Jeremy D; Raue, Andreas; Steiert, Bernhard; Timmer, Jens; Kreutz, Clemens; Wilkinson, Simon; Allgood, Brandon A; Bot, Brian M; Hoff, Bruce R; Kellen, Michael R; Covert, Markus W; Stolovitzky, Gustavo A; Meyer, Pablo

2015-05-01

Whole-cell models that explicitly represent all cellular components at the molecular level have the potential to predict phenotype from genotype. However, even for simple bacteria, whole-cell models will contain thousands of parameters, many of which are poorly characterized or unknown. New algorithms are needed to estimate these parameters and enable researchers to build increasingly comprehensive models. We organized the Dialogue for Reverse Engineering Assessments and Methods (DREAM) 8 Whole-Cell Parameter Estimation Challenge to develop new parameter estimation algorithms for whole-cell models. We asked participants to identify a subset of parameters of a whole-cell model given the model's structure and in silico "experimental" data. Here we describe the challenge, the best performing methods, and new insights into the identifiability of whole-cell models. We also describe several valuable lessons we learned toward improving future challenges. Going forward, we believe that collaborative efforts supported by inexpensive cloud computing have the potential to solve whole-cell model parameter estimation.

Model of Oxygen and Glucose Deprivation in PC12 Cells and Detection of HSP70 Protein

NASA Astrophysics Data System (ADS)

He, Jinting; Yang, Le; Shao, Yankun

2018-01-01

Objective: PC12 cell was used to set up a ischemia model by OGD and detected HSP70 protein. Methods: Use of PC12 cells induced by NGF stimulation into nerve cells, oxygen and glucose deprivation to build the nerve cells of oxygen and glucose deprivation model; using Western blot analysis of PC12 cells into neuron-like cells and oxygen-glucose deprivation model established. Results: The application of a final concentration of 50 ng / ml of NGF in DMEM complete mediumPC12 cells showed a typical neuronal morphology with the increase in cell culture time. NGF culture time showed a positive correlation, the establishment of oxygen and glucose deprivation (OGD) training environment, the OGD after nerve element appears different degrees of damage, OGD can effectively induce the expression of HSP70. Conclusion: PC12 cell transformed into cells by NGF; the cell model of OGD was established.

Interactions between airway epithelial cells and dendritic cells during viral infections using an in vitro co-culture model

EPA Science Inventory

Rationale: Historically, single cell culture models have been limited in pathological and physiological relevance. A co-culture model of dendritic cells (DCs) and differentiated human airway epithelial cells was developed to examine potential interactions between these two cell t...

An Off-Lattice Hybrid Discrete-Continuum Model of Tumor Growth and Invasion

PubMed Central

Jeon, Junhwan; Quaranta, Vito; Cummings, Peter T.

2010-01-01

Abstract We have developed an off-lattice hybrid discrete-continuum (OLHDC) model of tumor growth and invasion. The continuum part of the OLHDC model describes microenvironmental components such as matrix-degrading enzymes, nutrients or oxygen, and extracellular matrix (ECM) concentrations, whereas the discrete portion represents individual cell behavior such as cell cycle, cell-cell, and cell-ECM interactions and cell motility by the often-used persistent random walk, which can be depicted by the Langevin equation. Using this framework of the OLHDC model, we develop a phenomenologically realistic and bio/physically relevant model that encompasses the experimentally observed superdiffusive behavior (at short times) of mammalian cells. When systemic simulations based on the OLHDC model are performed, tumor growth and its morphology are found to be strongly affected by cell-cell adhesion and haptotaxis. There is a combination of the strength of cell-cell adhesion and haptotaxis in which fingerlike shapes, characteristic of invasive tumor, are observed. PMID:20074513

Dynamical crossover in a stochastic model of cell fate decision

NASA Astrophysics Data System (ADS)

Yamaguchi, Hiroki; Kawaguchi, Kyogo; Sagawa, Takahiro

2017-07-01

We study the asymptotic behaviors of stochastic cell fate decision between proliferation and differentiation. We propose a model of a self-replicating Langevin system, where cells choose their fate (i.e., proliferation or differentiation) depending on local cell density. Based on this model, we propose a scenario for multicellular organisms to maintain the density of cells (i.e., homeostasis) through finite-ranged cell-cell interactions. Furthermore, we numerically show that the distribution of the number of descendant cells changes over time, thus unifying the previously proposed two models regarding homeostasis: the critical birth death process and the voter model. Our results provide a general platform for the study of stochastic cell fate decision in terms of nonequilibrium statistical mechanics.

Temperature-dependent rate models of vascular cambium cell mortality

Treesearch

Matthew B. Dickinson; Edward A. Johnson

2004-01-01

We use two rate-process models to describe cell mortality at elevated temperatures as a means of understanding vascular cambium cell death during surface fires. In the models, cell death is caused by irreversible damage to cellular molecules that occurs at rates that increase exponentially with temperature. The models differ in whether cells show cumulative effects of...

A Micromechanics Finite Element Model for Studying the Mechanical Behavior of Spray-On Foam Insulation (SOFI)

NASA Technical Reports Server (NTRS)

Ghosn, Louis J.; Sullivan, Roy M.; Lerch, Bradley A.

2006-01-01

A micromechanics model has been constructed to study the mechanical behavior of spray-on foam insulation (SOFI) for the external tank. The model was constructed using finite elements representing the fundamental repeating unit of the SOFI microstructure. The details of the micromechanics model were based on cell observations and measured average cell dimensions discerned from photomicrographs. The unit cell model is an elongated Kelvin model (fourteen-sided polyhedron with 8 hexagonal and six quadrilateral faces), which will pack to a 100% density. The cell faces and cell edges are modeled using three-dimensional 20-node brick elements. Only one-eighth of the cell is modeled due to symmetry. By exercising the model and correlating the results with the macro-mechanical foam behavior obtained through material characterization testing, the intrinsic stiffness and Poisson s Ratio of the polymeric cell walls and edges are determined as a function of temperature. The model is then exercised to study the unique and complex temperature-dependent mechanical behavior as well as the fracture initiation and propagation at the microscopic unit cell level.

Simple rules for a "simple" nervous system? Molecular and biomathematical approaches to enteric nervous system formation and malformation.

PubMed

Newgreen, Donald F; Dufour, Sylvie; Howard, Marthe J; Landman, Kerry A

2013-10-01

We review morphogenesis of the enteric nervous system from migratory neural crest cells, and defects of this process such as Hirschsprung disease, centering on cell motility and assembly, and cell adhesion and extracellular matrix molecules, along with cell proliferation and growth factors. We then review continuum and agent-based (cellular automata) models with rules of cell movement and logistical proliferation. Both movement and proliferation at the individual cell level are modeled with stochastic components from which stereotyped outcomes emerge at the population level. These models reproduced the wave-like colonization of the intestine by enteric neural crest cells, and several new properties emerged, such as colonization by frontal expansion, which were later confirmed biologically. These models predict a surprising level of clonal heterogeneity both in terms of number and distribution of daughter cells. Biologically, migrating cells form stable chains made up of unstable cells, but this is not seen in the initial model. We outline additional rules for cell differentiation into neurons, axon extension, cell-axon and cell-cell adhesions, chemotaxis and repulsion which can reproduce chain migration. After the migration stage, the cells re-arrange as a network of ganglia. Changes in cell adhesion molecules parallel this, and we describe additional rules based on Steinberg's Differential Adhesion Hypothesis, reflecting changing levels of adhesion in neural crest cells and neurons. This was able to reproduce enteric ganglionation in a model. Mouse mutants with disturbances of enteric nervous system morphogenesis are discussed, and these suggest future refinement of the models. The modeling suggests a relatively simple set of cell behavioral rules could account for complex patterns of morphogenesis. The model has allowed the proposal that Hirschsprung disease is mostly an enteric neural crest cell proliferation defect, not a defect of cell migration. In addition, the model suggests an explanations for zonal and skip segment variants of Hirschsprung disease, and also gives a novel stochastic explanation for the observed discordancy of Hirschsprung disease in identical twins. © 2013 Elsevier Inc. All rights reserved.

Spatial Pattern of Cell Damage in Tissue from Heavy Ions

NASA Technical Reports Server (NTRS)

Ponomarev, Artem L.; Huff, Janice L.; Cucinotta, Francis A.

2007-01-01

A new Monte Carlo algorithm was developed that can model passage of heavy ions in a tissue, and their action on the cellular matrix for 2- or 3-dimensional cases. The build-up of secondaries such as projectile fragments, target fragments, other light fragments, and delta-rays was simulated. Cells were modeled as a cell culture monolayer in one example, where the data were taken directly from microscopy (2-d cell matrix). A simple model of tissue was given as abstract spheres with close approximation to real cell geometries (3-d cell matrix), as well as a realistic model of tissue was proposed based on microscopy images. Image segmentation was used to identify cells in an irradiated cell culture monolayer, or slices of tissue. The cells were then inserted into the model box pixel by pixel. In the case of cell monolayers (2-d), the image size may exceed the modeled box size. Such image was is moved with respect to the box in order to sample as many cells as possible. In the case of the simple tissue (3-d), the tissue box is modeled with periodic boundary conditions, which extrapolate the technique to macroscopic volumes of tissue. For real tissue, specific spatial patterns for cell apoptosis and necrosis are expected. The cell patterns were modeled based on action cross sections for apoptosis and necrosis estimated based on BNL data, and other experimental data.

An efficient current-based logic cell model for crosstalk delay analysis

NASA Astrophysics Data System (ADS)

Nazarian, Shahin; Das, Debasish

2013-04-01

Logic cell modelling is an important component in the analysis and design of CMOS integrated circuits, mostly due to nonlinear behaviour of CMOS cells with respect to the voltage signal at their input and output pins. A current-based model for CMOS logic cells is presented, which can be used for effective crosstalk noise and delta delay analysis in CMOS VLSI circuits. Existing current source models are expensive and need a new set of Spice-based characterisation, which is not compatible with typical EDA tools. In this article we present Imodel, a simple nonlinear logic cell model that can be derived from the typical cell libraries such as NLDM, with accuracy much higher than NLDM-based cell delay models. In fact, our experiments show an average error of 3% compared to Spice. This level of accuracy comes with a maximum runtime penalty of 19% compared to NLDM-based cell delay models on medium-sized industrial designs.

cellPACK: A Virtual Mesoscope to Model and Visualize Structural Systems Biology

PubMed Central

Johnson, Graham T.; Autin, Ludovic; Al-Alusi, Mostafa; Goodsell, David S.; Sanner, Michel F.; Olson, Arthur J.

2014-01-01

cellPACK assembles computational models of the biological mesoscale, an intermediate scale (10−7–10−8m) between molecular and cellular biology. cellPACK’s modular architecture unites existing and novel packing algorithms to generate, visualize and analyze comprehensive 3D models of complex biological environments that integrate data from multiple experimental systems biology and structural biology sources. cellPACK is currently available as open source code, with tools for validation of models and with recipes and models for five biological systems: blood plasma, cytoplasm, synaptic vesicles, HIV and a mycoplasma cell. We have applied cellPACK to model distributions of HIV envelope protein to test several hypotheses for consistency with experimental observations. Biologists, educators, and outreach specialists can interact with cellPACK models, develop new recipes and perform packing experiments through scripting and graphical user interfaces at http://cellPACK.org. PMID:25437435

Optimizing eukaryotic cell hosts for protein production through systems biotechnology and genome-scale modeling.

PubMed

Gutierrez, Jahir M; Lewis, Nathan E

2015-07-01

Eukaryotic cell lines, including Chinese hamster ovary cells, yeast, and insect cells, are invaluable hosts for the production of many recombinant proteins. With the advent of genomic resources, one can now leverage genome-scale computational modeling of cellular pathways to rationally engineer eukaryotic host cells. Genome-scale models of metabolism include all known biochemical reactions occurring in a specific cell. By describing these mathematically and using tools such as flux balance analysis, the models can simulate cell physiology and provide targets for cell engineering that could lead to enhanced cell viability, titer, and productivity. Here we review examples in which metabolic models in eukaryotic cell cultures have been used to rationally select targets for genetic modification, improve cellular metabolic capabilities, design media supplementation, and interpret high-throughput omics data. As more comprehensive models of metabolism and other cellular processes are developed for eukaryotic cell culture, these will enable further exciting developments in cell line engineering, thus accelerating recombinant protein production and biotechnology in the years to come. Copyright © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Implementation of a Smeared Crack Band Model in a Micromechanics Framework

NASA Technical Reports Server (NTRS)

Pineda, Evan J.; Bednarcyk, Brett A.; Waas, Anthony M.; Arnold, Steven M.

2012-01-01

The smeared crack band theory is implemented within the generalized method of cells and high-fidelity generalized method of cells micromechanics models to capture progressive failure within the constituents of a composite material while retaining objectivity with respect to the size of the discretization elements used in the model. An repeating unit cell containing 13 randomly arranged fibers is modeled and subjected to a combination of transverse tension/compression and transverse shear loading. The implementation is verified against experimental data (where available), and an equivalent finite element model utilizing the same implementation of the crack band theory. To evaluate the performance of the crack band theory within a repeating unit cell that is more amenable to a multiscale implementation, a single fiber is modeled with generalized method of cells and high-fidelity generalized method of cells using a relatively coarse subcell mesh which is subjected to the same loading scenarios as the multiple fiber repeating unit cell. The generalized method of cells and high-fidelity generalized method of cells models are validated against a very refined finite element model.

Modelling the Immune Response to Cancer: An Individual-Based Approach Accounting for the Difference in Movement Between Inactive and Activated T Cells.

PubMed

Macfarlane, Fiona R; Lorenzi, Tommaso; Chaplain, Mark A J

2018-06-01

A growing body of experimental evidence indicates that immune cells move in an unrestricted search pattern if they are in the pre-activated state, whilst they tend to stay within a more restricted area upon activation induced by the presence of tumour antigens. This change in movement is not often considered in the existing mathematical models of the interactions between immune cells and cancer cells. With the aim to fill such a gap in the existing literature, in this work we present a spatially structured individual-based model of tumour-immune competition that takes explicitly into account the difference in movement between inactive and activated immune cells. In our model, a Lévy walk is used to capture the movement of inactive immune cells, whereas Brownian motion is used to describe the movement of antigen-activated immune cells. The effects of activation of immune cells, the proliferation of cancer cells and the immune destruction of cancer cells are also modelled. We illustrate the ability of our model to reproduce qualitatively the spatial trajectories of immune cells observed in experimental data of single-cell tracking. Computational simulations of our model further clarify the conditions for the onset of a successful immune action against cancer cells and may suggest possible targets to improve the efficacy of cancer immunotherapy. Overall, our theoretical work highlights the importance of taking into account spatial interactions when modelling the immune response to cancer cells.

Summary of the DREAM8 Parameter Estimation Challenge: Toward Parameter Identification for Whole-Cell Models

PubMed Central

Karr, Jonathan R.; Williams, Alex H.; Zucker, Jeremy D.; Raue, Andreas; Steiert, Bernhard; Timmer, Jens; Kreutz, Clemens; Wilkinson, Simon; Allgood, Brandon A.; Bot, Brian M.; Hoff, Bruce R.; Kellen, Michael R.; Covert, Markus W.; Stolovitzky, Gustavo A.; Meyer, Pablo

2015-01-01

Whole-cell models that explicitly represent all cellular components at the molecular level have the potential to predict phenotype from genotype. However, even for simple bacteria, whole-cell models will contain thousands of parameters, many of which are poorly characterized or unknown. New algorithms are needed to estimate these parameters and enable researchers to build increasingly comprehensive models. We organized the Dialogue for Reverse Engineering Assessments and Methods (DREAM) 8 Whole-Cell Parameter Estimation Challenge to develop new parameter estimation algorithms for whole-cell models. We asked participants to identify a subset of parameters of a whole-cell model given the model’s structure and in silico “experimental” data. Here we describe the challenge, the best performing methods, and new insights into the identifiability of whole-cell models. We also describe several valuable lessons we learned toward improving future challenges. Going forward, we believe that collaborative efforts supported by inexpensive cloud computing have the potential to solve whole-cell model parameter estimation. PMID:26020786

Impedance analysis of cultured cells: a mean-field electrical response model for electric cell-substrate impedance sensing technique.

PubMed

Urdapilleta, E; Bellotti, M; Bonetto, F J

2006-10-01

In this paper we present a model to describe the electrical properties of a confluent cell monolayer cultured on gold microelectrodes to be used with electric cell-substrate impedance sensing technique. This model was developed from microscopic considerations (distributed effects), and by assuming that the monolayer is an element with mean electrical characteristics (specific lumped parameters). No assumptions were made about cell morphology. The model has only three adjustable parameters. This model and other models currently used for data analysis are compared with data we obtained from electrical measurements of confluent monolayers of Madin-Darby Canine Kidney cells. One important parameter is the cell-substrate height and we found that estimates of this magnitude strongly differ depending on the model used for the analysis. We analyze the origin of the discrepancies, concluding that the estimates from the different models can be considered as limits for the true value of the cell-substrate height.

Progressive Failure of a Unidirectional Fiber-Reinforced Composite Using the Method of Cells: Discretization Objective Computational Results

NASA Technical Reports Server (NTRS)

Pineda, Evan J.; Bednarcyk, Brett A.; Waas, Anthony M.; Arnold, Steven M.

2012-01-01

The smeared crack band theory is implemented within the generalized method of cells and high-fidelity generalized method of cells micromechanics models to capture progressive failure within the constituents of a composite material while retaining objectivity with respect to the size of the discretization elements used in the model. An repeating unit cell containing 13 randomly arranged fibers is modeled and subjected to a combination of transverse tension/compression and transverse shear loading. The implementation is verified against experimental data (where available), and an equivalent finite element model utilizing the same implementation of the crack band theory. To evaluate the performance of the crack band theory within a repeating unit cell that is more amenable to a multiscale implementation, a single fiber is modeled with generalized method of cells and high-fidelity generalized method of cells using a relatively coarse subcell mesh which is subjected to the same loading scenarios as the multiple fiber repeating unit cell. The generalized method of cells and high-fidelity generalized method of cells models are validated against a very refined finite element model.

Low-high junction theory applied to solar cells

NASA Technical Reports Server (NTRS)

Godlewski, M. P.; Baraona, C. R.; Brandhorst, H. W., Jr.

1973-01-01

Recent use of alloying techniques for rear contact formation has yielded a new kind of silicon solar cell, the back surface field (BSF) cell, with abnormally high open circuit voltage and improved radiation resistance. Several analytical models for open circuit voltage based on the reverse saturation current are formulated to explain these observations. The zero SRV case of the conventional cell model, the drift field model, and the low-high junction (LHJ) model can predict the experimental trends. The LHJ model applies the theory of the low-high junction and is considered to reflect a more realistic view of cell fabrication. This model can predict the experimental trends observed for BSF cells. Detailed descriptions and derivations for the models are included. The correspondences between them are discussed. This modeling suggests that the meaning of minority carrier diffusion length measured in BSF cells be reexamined.

Probing eukaryotic cell mechanics via mesoscopic simulations

NASA Astrophysics Data System (ADS)

Pivkin, Igor V.; Lykov, Kirill; Nematbakhsh, Yasaman; Shang, Menglin; Lim, Chwee Teck

2017-11-01

We developed a new mesoscopic particle based eukaryotic cell model which takes into account cell membrane, cytoskeleton and nucleus. The breast epithelial cells were used in our studies. To estimate the viscoelastic properties of cells and to calibrate the computational model, we performed micropipette aspiration experiments. The model was then validated using data from microfluidic experiments. Using the validated model, we probed contributions of sub-cellular components to whole cell mechanics in micropipette aspiration and microfluidics experiments. We believe that the new model will allow to study in silico numerous problems in the context of cell biomechanics in flows in complex domains, such as capillary networks and microfluidic devices.

RCCS bioreactor-based modelled microgravity induces significant changes on in vitro 3D neuroglial cell cultures.

PubMed

Morabito, Caterina; Steimberg, Nathalie; Mazzoleni, Giovanna; Guarnieri, Simone; Fanò-Illic, Giorgio; Mariggiò, Maria A

2015-01-01

We propose a human-derived neuro-/glial cell three-dimensional in vitro model to investigate the effects of microgravity on cell-cell interactions. A rotary cell-culture system (RCCS) bioreactor was used to generate a modelled microgravity environment, and morphofunctional features of glial-like GL15 and neuronal-like SH-SY5Y cells in three-dimensional individual cultures (monotypic aggregates) and cocultures (heterotypic aggregates) were analysed. Cell survival was maintained within all cell aggregates over 2 weeks of culture. Moreover, compared to cells as traditional static monolayers, cell aggregates cultured under modelled microgravity showed increased expression of specific differentiation markers (e.g., GL15 cells: GFAP, S100B; SH-SY5Y cells: GAP43) and modulation of functional cell-cell interactions (e.g., N-CAM and Cx43 expression and localisation). In conclusion, this culture model opens a wide range of specific investigations at the molecular, biochemical, and morphological levels, and it represents an important tool for in vitro studies into dynamic interactions and responses of nervous system cell components to microgravity environmental conditions.

RCCS Bioreactor-Based Modelled Microgravity Induces Significant Changes on In Vitro 3D Neuroglial Cell Cultures

PubMed Central

Mazzoleni, Giovanna; Fanò-Illic, Giorgio; Mariggiò, Maria A.

2015-01-01

We propose a human-derived neuro-/glial cell three-dimensional in vitro model to investigate the effects of microgravity on cell-cell interactions. A rotary cell-culture system (RCCS) bioreactor was used to generate a modelled microgravity environment, and morphofunctional features of glial-like GL15 and neuronal-like SH-SY5Y cells in three-dimensional individual cultures (monotypic aggregates) and cocultures (heterotypic aggregates) were analysed. Cell survival was maintained within all cell aggregates over 2 weeks of culture. Moreover, compared to cells as traditional static monolayers, cell aggregates cultured under modelled microgravity showed increased expression of specific differentiation markers (e.g., GL15 cells: GFAP, S100B; SH-SY5Y cells: GAP43) and modulation of functional cell-cell interactions (e.g., N-CAM and Cx43 expression and localisation). In conclusion, this culture model opens a wide range of specific investigations at the molecular, biochemical, and morphological levels, and it represents an important tool for in vitro studies into dynamic interactions and responses of nervous system cell components to microgravity environmental conditions. PMID:25654124

From single cells to tissue architecture-a bottom-up approach to modelling the spatio-temporal organisation of complex multi-cellular systems.

PubMed

Galle, J; Hoffmann, M; Aust, G

2009-01-01

Collective phenomena in multi-cellular assemblies can be approached on different levels of complexity. Here, we discuss a number of mathematical models which consider the dynamics of each individual cell, so-called agent-based or individual-based models (IBMs). As a special feature, these models allow to account for intracellular decision processes which are triggered by biomechanical cell-cell or cell-matrix interactions. We discuss their impact on the growth and homeostasis of multi-cellular systems as simulated by lattice-free models. Our results demonstrate that cell polarisation subsequent to cell-cell contact formation can be a source of stability in epithelial monolayers. Stroma contact-dependent regulation of tumour cell proliferation and migration is shown to result in invasion dynamics in accordance with the migrating cancer stem cell hypothesis. However, we demonstrate that different regulation mechanisms can equally well comply with present experimental results. Thus, we suggest a panel of experimental studies for the in-depth validation of the model assumptions.

Optimal Charging of Nickel-Hydrogen Batteries for Life Extension

NASA Technical Reports Server (NTRS)

Hartley, Tom T.; Lorenzo, Carl F.

2002-01-01

We are exploring the possibility of extending the cycle life of battery systems by using a charging profile that minimizes cell damage. Only nickel-hydrogen cells are discussed at this time, but applications to lithium-ion cells are being considered. The process first requires the development of a fractional calculus based nonlinear dynamic model of the specific cells being used. The parameters of this model are determined from the cell transient responses. To extend cell cycle life, an instantaneous damage rate model is developed. The model is based on cycle life data and is highly dependent on cell voltage. Once both the cell dynamic model and the instantaneous damage rate model have been determined, the charging profile for a specific cell is determined by numerical optimization. Results concerning the percentage life extension for different charging strategies are presented. The overall procedure is readily adaptable to real-time implementations where the charging profile can maintain its minimum damage nature as the specific cell ages.

A three-dimensional in vitro ovarian cancer coculture model using a high-throughput cell patterning platform

PubMed Central

Rizvi, Imran; Moon, Sangjun; Hasan, Tayyaba; Demirci, Utkan

2013-01-01

In vitro 3D cancer models that provide a more accurate representation of disease in vivo are urgently needed to improve our understanding of cancer pathology and to develop better cancer therapies. However, development of 3D models that are based on manual ejection of cells from micropipettes suffer from inherent limitations such as poor control over cell density, limited repeatability, low throughput, and, in the case of coculture models, lack of reproducible control over spatial distance between cell types (e.g., cancer and stromal cells). In this study, we build on a recently introduced 3D model in which human ovarian cancer (OVCAR-5) cells overlaid on Matrigel™ spontaneously form multicellular acini. We introduce a high-throughput automated cell printing system to bioprint a 3D coculture model using cancer cells and normal fibroblasts micropatterned on Matrigel™. Two cell types were patterned within a spatially controlled microenvironment (e.g., cell density, cell-cell distance) in a high-throughput and reproducible manner; both cell types remained viable during printing and continued to proliferate following patterning. This approach enables the miniaturization of an established macro-scale 3D culture model and would allow systematic investigation into the multiple unknown regulatory feedback mechanisms between tumor and stromal cells and provide a tool for high-throughput drug screening. PMID:21298805

Active unjamming of confluent cell layers

NASA Astrophysics Data System (ADS)

Marchetti, M. Cristina

Cell motion inside dense tissues governs many biological processes, including embryonic development and cancer metastasis, and recent experiments suggest that these tissues exhibit collective glassy behavior. Motivated by these observations, we have studied a model of dense tissues that combines self-propelled particle models and vertex models of confluent cell layers. In this model, referred to as self-propelled Voronoi (SPV), cells are described as polygons in a Voronoi tessellation with directed noisy cell motility and interactions governed by a shape energy that incorporates the effects of cell volume incompressibility, contractility and cell-cell adhesion. Using this model, we have demonstrated a new density-independent solid-liquid transition in confluent tissues controlled by cell motility and a cell-shape parameter measuring the interplay of cortical tension and cell-cell adhesion. An important insight of this work is that the rigidity and dynamics of cell layers depends sensitively on cell shape. We have also used the SPV model to test a new method developed by our group to determine cellular forces and tissue stresses from experimentally accessible cell shapes and traction forces, hence providing the spatio-temporal distribution of stresses in motile dense tissues. This work was done with Dapeng Bi, Lisa Manning and Xingbo Yang. MCM was supported by NSF-DMR-1305184 and by the Simons Foundation.

AlgiMatrix™-Based 3D Cell Culture System as an In Vitro Tumor Model: An Important Tool in Cancer Research.

PubMed

Godugu, Chandraiah; Singh, Mandip

2016-01-01

Routinely used two-dimensional cell culture-based models often fail while translating the observations into in vivo models. This setback is more common in cancer research, due to several reasons. The extracellular matrix and cell-to-cell interactions are not present in two-dimensional (2D) cell culture models. Diffusion of drug molecules into cancer cells is hindered by barriers of extracellular components in in vivo conditions, these barriers are absent in 2D cell culture models. To better mimic or simulate the in vivo conditions present in tumors, the current study used the alginate based three-dimensional cell culture (AlgiMatrix™) model, which resembles close to the in vivo tumor models. The current study explains the detailed protocols involved in AlgiMatrix™ based in vitro non-small-cell lung cancer (NSCLC) models. The suitability of this model was studied by evaluating, cytotoxicity, apoptosis, and penetration of nanoparticles into the in vitro tumor spheroids. This study also demonstrated the effect of EphA2 receptor targeted docetaxel-loaded nanoparticles on MDA-MB-468 TNBC cell lines. The methods section is subdivided into three subsections such as (1) preparation of AlgiMatrix™-based 3D in vitro tumor models and cytotoxicity assays, (2) free drug and nanoparticle uptake into spheroid studies, and (3) western blot, IHC, and RT-PCR studies.

Modeling the mechanics of cells in the cell-spreading process driven by traction forces

NASA Astrophysics Data System (ADS)

Fang, Yuqiang; Lai, King W. C.

2016-04-01

Mechanical properties of cells and their mechanical interaction with the extracellular environments are main factors influencing cellular function, thus indicating the progression of cells in different disease states. By considering the mechanical interactions between cell adhesion molecules and the extracellular environment, we developed a cell mechanical model that can characterize the mechanical changes in cells during cell spreading. A cell model was established that consisted of various main subcellular components, including cortical cytoskeleton, nuclear envelope, actin filaments, intermediate filaments, and microtubules. We demonstrated the structural changes in subcellular components and the changes in spreading areas during cell spreading driven by traction forces. The simulation of nanoindentation tests was conducted by integrating the indenting force to the cell model. The force-indentation curve of the cells at different spreading states was simulated, and the results showed that cell stiffness increased with increasing traction forces, which were consistent with the experimental results. The proposed cell mechanical model provides a strategy to investigate the mechanical interactions of cells with the extracellular environments through the adhesion molecules and to reveal the cell mechanical properties at the subcellular level as cells shift from the suspended state to the adherent state.

Modeling the mechanics of cells in the cell-spreading process driven by traction forces.

PubMed

Fang, Yuqiang; Lai, King W C

2016-04-01

Mechanical properties of cells and their mechanical interaction with the extracellular environments are main factors influencing cellular function, thus indicating the progression of cells in different disease states. By considering the mechanical interactions between cell adhesion molecules and the extracellular environment, we developed a cell mechanical model that can characterize the mechanical changes in cells during cell spreading. A cell model was established that consisted of various main subcellular components, including cortical cytoskeleton, nuclear envelope, actin filaments, intermediate filaments, and microtubules. We demonstrated the structural changes in subcellular components and the changes in spreading areas during cell spreading driven by traction forces. The simulation of nanoindentation tests was conducted by integrating the indenting force to the cell model. The force-indentation curve of the cells at different spreading states was simulated, and the results showed that cell stiffness increased with increasing traction forces, which were consistent with the experimental results. The proposed cell mechanical model provides a strategy to investigate the mechanical interactions of cells with the extracellular environments through the adhesion molecules and to reveal the cell mechanical properties at the subcellular level as cells shift from the suspended state to the adherent state.

Emergence of collective propulsion through cell-cell adhesion.

PubMed

Matsushita, Katsuyoshi

2018-04-01

The mechanisms driving the collective movement of cells remain poorly understood. To contribute toward resolving this mystery, a model was formulated to theoretically explore the possible functions of polarized cell-cell adhesion in collective cell migration. The model consists of an amoeba cell with polarized cell-cell adhesion, which is controlled by positive feedback with cell motion. This model cell has no persistent propulsion and therefore exhibits a simple random walk when in isolation. However, at high density, these cells acquire collective propulsion and form ordered movement. This result suggests that cell-cell adhesion has a potential function, which induces collective propulsion with persistence.

Emergence of collective propulsion through cell-cell adhesion

NASA Astrophysics Data System (ADS)

Matsushita, Katsuyoshi

2018-04-01

The mechanisms driving the collective movement of cells remain poorly understood. To contribute toward resolving this mystery, a model was formulated to theoretically explore the possible functions of polarized cell-cell adhesion in collective cell migration. The model consists of an amoeba cell with polarized cell-cell adhesion, which is controlled by positive feedback with cell motion. This model cell has no persistent propulsion and therefore exhibits a simple random walk when in isolation. However, at high density, these cells acquire collective propulsion and form ordered movement. This result suggests that cell-cell adhesion has a potential function, which induces collective propulsion with persistence.

Cell population modelling of yeast glycolytic oscillations.

PubMed Central

Henson, Michael A; Müller, Dirk; Reuss, Matthias

2002-01-01

We investigated a cell-population modelling technique in which the population is constructed from an ensemble of individual cell models. The average value or the number distribution of any intracellular property captured by the individual cell model can be calculated by simulation of a sufficient number of individual cells. The proposed method is applied to a simple model of yeast glycolytic oscillations where synchronization of the cell population is mediated by the action of an excreted metabolite. We show that smooth one-dimensional distributions can be obtained with ensembles comprising 1000 individual cells. Random variations in the state and/or structure of individual cells are shown to produce complex dynamic behaviours which cannot be adequately captured by small ensembles. PMID:12206713

Cell differentiation modeled via a coupled two-switch regulatory network

NASA Astrophysics Data System (ADS)

Schittler, D.; Hasenauer, J.; Allgöwer, F.; Waldherr, S.

2010-12-01

Mesenchymal stem cells can give rise to bone and other tissue cells, but their differentiation still escapes full control. In this paper we address this issue by mathematical modeling. We present a model for a genetic switch determining the cell fate of progenitor cells which can differentiate into osteoblasts (bone cells) or chondrocytes (cartilage cells). The model consists of two switch mechanisms and reproduces the experimentally observed three stable equilibrium states: a progenitor, an osteogenic, and a chondrogenic state. Conventionally, the loss of an intermediate (progenitor) state and the entailed attraction to one of two opposite (differentiated) states is modeled as a result of changing parameters. In our model in contrast, we achieve this by distributing the differentiation process to two functional switch parts acting in concert: one triggering differentiation and the other determining cell fate. Via stability and bifurcation analysis, we investigate the effects of biochemical stimuli associated with different system inputs. We employ our model to generate differentiation scenarios on the single cell as well as on the cell population level. The single cell scenarios allow to reconstruct the switching upon extrinsic signals, whereas the cell population scenarios provide a framework to identify the impact of intrinsic properties and the limiting factors for successful differentiation.

A model for the kinetics of homotypic cellular aggregation under static conditions

NASA Technical Reports Server (NTRS)

Neelamegham, S.; Munn, L. L.; Zygourakis, K.; McIntire, L. V. (Principal Investigator)

1997-01-01

We present the formulation and testing of a mathematical model for the kinetics of homotypic cellular aggregation. The model considers cellular aggregation under no-flow conditions as a two-step process. Individual cells and cell aggregates 1) move on the tissue culture surface and 2) collide with other cells (or aggregates). These collisions lead to the formation of intercellular bonds. The aggregation kinetics are described by a system of coupled, nonlinear ordinary differential equations, and the collision frequency kernel is derived by extending Smoluchowski's colloidal flocculation theory to cell migration and aggregation on a two-dimensional surface. Our results indicate that aggregation rates strongly depend upon the motility of cells and cell aggregates, the frequency of cell-cell collisions, and the strength of intercellular bonds. Model predictions agree well with data from homotypic lymphocyte aggregation experiments using Jurkat cells activated by 33B6, an antibody to the beta 1 integrin. Since cell migration speeds and all the other model parameters can be independently measured, the aggregation model provides a quantitative methodology by which we can accurately evaluate the adhesivity and aggregation behavior of cells.

Optimization of cell seeding in a 2D bio-scaffold system using computational models.

PubMed

Ho, Nicholas; Chua, Matthew; Chui, Chee-Kong

2017-05-01

The cell expansion process is a crucial part of generating cells on a large-scale level in a bioreactor system. Hence, it is important to set operating conditions (e.g. initial cell seeding distribution, culture medium flow rate) to an optimal level. Often, the initial cell seeding distribution factor is neglected and/or overlooked in the design of a bioreactor using conventional seeding distribution methods. This paper proposes a novel seeding distribution method that aims to maximize cell growth and minimize production time/cost. The proposed method utilizes two computational models; the first model represents cell growth patterns whereas the second model determines optimal initial cell seeding positions for adherent cell expansions. Cell growth simulation from the first model demonstrates that the model can be a representation of various cell types with known probabilities. The second model involves a combination of combinatorial optimization, Monte Carlo and concepts of the first model, and is used to design a multi-layer 2D bio-scaffold system that increases cell production efficiency in bioreactor applications. Simulation results have shown that the recommended input configurations obtained from the proposed optimization method are the most optimal configurations. The results have also illustrated the effectiveness of the proposed optimization method. The potential of the proposed seeding distribution method as a useful tool to optimize the cell expansion process in modern bioreactor system applications is highlighted. Copyright © 2017 Elsevier Ltd. All rights reserved.

Cell sources for in vitro human liver cell culture models.

PubMed

Zeilinger, Katrin; Freyer, Nora; Damm, Georg; Seehofer, Daniel; Knöspel, Fanny

2016-09-01

In vitro liver cell culture models are gaining increasing importance in pharmacological and toxicological research. The source of cells used is critical for the relevance and the predictive value of such models. Primary human hepatocytes (PHH) are currently considered to be the gold standard for hepatic in vitro culture models, since they directly reflect the specific metabolism and functionality of the human liver; however, the scarcity and difficult logistics of PHH have driven researchers to explore alternative cell sources, including liver cell lines and pluripotent stem cells. Liver cell lines generated from hepatomas or by genetic manipulation are widely used due to their good availability, but they are generally altered in certain metabolic functions. For the past few years, adult and pluripotent stem cells have been attracting increasing attention, due their ability to proliferate and to differentiate into hepatocyte-like cells in vitro However, controlling the differentiation of these cells is still a challenge. This review gives an overview of the major human cell sources under investigation for in vitro liver cell culture models, including primary human liver cells, liver cell lines, and stem cells. The promises and challenges of different cell types are discussed with a focus on the complex 2D and 3D culture approaches under investigation for improving liver cell functionality in vitro Finally, the specific application options of individual cell sources in pharmacological research or disease modeling are described. © 2016 by the Society for Experimental Biology and Medicine.

Cell sources for in vitro human liver cell culture models

PubMed Central

Freyer, Nora; Damm, Georg; Seehofer, Daniel; Knöspel, Fanny

2016-01-01

In vitro liver cell culture models are gaining increasing importance in pharmacological and toxicological research. The source of cells used is critical for the relevance and the predictive value of such models. Primary human hepatocytes (PHH) are currently considered to be the gold standard for hepatic in vitro culture models, since they directly reflect the specific metabolism and functionality of the human liver; however, the scarcity and difficult logistics of PHH have driven researchers to explore alternative cell sources, including liver cell lines and pluripotent stem cells. Liver cell lines generated from hepatomas or by genetic manipulation are widely used due to their good availability, but they are generally altered in certain metabolic functions. For the past few years, adult and pluripotent stem cells have been attracting increasing attention, due their ability to proliferate and to differentiate into hepatocyte-like cells in vitro. However, controlling the differentiation of these cells is still a challenge. This review gives an overview of the major human cell sources under investigation for in vitro liver cell culture models, including primary human liver cells, liver cell lines, and stem cells. The promises and challenges of different cell types are discussed with a focus on the complex 2D and 3D culture approaches under investigation for improving liver cell functionality in vitro. Finally, the specific application options of individual cell sources in pharmacological research or disease modeling are described. PMID:27385595

Nonlinear empirical model of gas humidity-related voltage dynamics of a polymer-electrolyte-membrane fuel cell stack

NASA Astrophysics Data System (ADS)

Meiler, M.; Andre, D.; Schmid, O.; Hofer, E. P.

Intelligent energy management is a cost-effective key path to realize efficient automotive drive trains [R. O'Hayre, S.W. Cha, W. Colella, F.B. Prinz. Fuel Cell Fundamentals, John Wiley & Sons, Hoboken, 2006]. To develop operating strategy in fuel cell drive trains, precise and computational efficient models of all system components, especially the fuel cell stack, are needed. Should these models further be used in diagnostic or control applications, then some major requirements must be fulfilled. First, the model must predict the mean fuel cell voltage very precisely in all possible operating conditions, even during transients. The model output should be as smooth as possible to support best efficient optimization strategies of the complete system. At least, the model must be computational efficient. For most applications, a difference between real fuel cell voltage and model output of less than 10 mV and 1000 calculations per second will be sufficient. In general, empirical models based on system identification offer a better accuracy and consume less calculation resources than detailed models derived from theoretical considerations [J. Larminie, A. Dicks. Fuel Cell Systems Explained, John Wiley & Sons, West Sussex, 2003]. In this contribution, the dynamic behaviour of the mean cell voltage of a polymer-electrolyte-membrane fuel cell (PEMFC) stack due to variations in humidity of cell's reactant gases is investigated. The validity of the overall model structure, a so-called general Hammerstein model (or Uryson model), was introduced recently in [M. Meiler, O. Schmid, M. Schudy, E.P. Hofer. Dynamic fuel cell stack model for real-time simulation based on system identification, J. Power Sources 176 (2007) 523-528]. Fuel cell mean voltage is calculated as the sum of a stationary and a dynamic voltage component. The stationary component of cell voltage is represented by a lookup-table and the dynamic voltage by a parallel placed, nonlinear transfer function. A suitable experimental setup to apply fast variations of gas humidity is introduced and is used to investigate a 10 cell PEMFC stack under various operation conditions. Using methods like stepwise multiple-regression a good mathematical description with reduced free parameters is achieved.

Relation Between the Cell Volume and the Cell Cycle Dynamics in Mammalian cell

NASA Astrophysics Data System (ADS)

Magno, A. C. G.; Oliveira, I. L.; Hauck, J. V. S.

2016-08-01

The main goal of this work is to add and analyze an equation that represents the volume in a dynamical model of the mammalian cell cycle proposed by Gérard and Goldbeter (2011) [1]. The cell division occurs when the cyclinB/Cdkl complex is totally degraded (Tyson and Novak, 2011)[2] and it reaches a minimum value. At this point, the cell is divided into two newborn daughter cells and each one will contain the half of the cytoplasmic content of the mother cell. The equations of our base model are only valid if the cell volume, where the reactions occur, is constant. Whether the cell volume is not constant, that is, the rate of change of its volume with respect to time is explicitly taken into account in the mathematical model, then the equations of the original model are no longer valid. Therefore, every equations were modified from the mass conservation principle for considering a volume that changes with time. Through this approach, the cell volume affects all model variables. Two different dynamic simulation methods were accomplished: deterministic and stochastic. In the stochastic simulation, the volume affects every model's parameters which have molar unit, whereas in the deterministic one, it is incorporated into the differential equations. In deterministic simulation, the biochemical species may be in concentration units, while in stochastic simulation such species must be converted to number of molecules which are directly proportional to the cell volume. In an effort to understand the influence of the new equation a stability analysis was performed. This elucidates how the growth factor impacts the stability of the model's limit cycles. In conclusion, a more precise model, in comparison to the base model, was created for the cell cycle as it now takes into consideration the cell volume variation

A novel microfluidic model can mimic organ-specific metastasis of circulating tumor cells.

PubMed

Kong, Jing; Luo, Yong; Jin, Dong; An, Fan; Zhang, Wenyuan; Liu, Lilu; Li, Jiao; Fang, Shimeng; Li, Xiaojie; Yang, Xuesong; Lin, Bingcheng; Liu, Tingjiao

2016-11-29

A biomimetic microsystem might compensate costly and time-consuming animal metastatic models. Herein we developed a biomimetic microfluidic model to study cancer metastasis. Primary cells isolated from different organs were cultured on the microlfuidic model to represent individual organs. Breast and salivary gland cancer cells were driven to flow over primary cell culture chambers, mimicking dynamic adhesion of circulating tumor cells (CTCs) to endothelium in vivo. These flowing artificial CTCs showed different metastatic potentials to lung on the microfluidic model. The traditional nude mouse model of lung metastasis was performed to investigate the physiological similarity of the microfluidic model to animal models. It was found that the metastatic potential of different cancer cells assessed by the microfluidic model was in agreement with that assessed by the nude mouse model. Furthermore, it was demonstrated that the metastatic inhibitor AMD3100 inhibited lung metastasis effectively in both the microfluidic model and the nude mouse model. Then the microfluidic model was used to mimick liver and bone metastasis of CTCs and confirm the potential for research of multiple-organ metastasis. Thus, the metastasis of CTCs to different organs was reconstituted on the microfluidic model. It may expand the capabilities of traditional cell culture models, providing a low-cost, time-saving, and rapid alternative to animal models.

Impact of implementation choices on quantitative predictions of cell-based computational models

NASA Astrophysics Data System (ADS)

Kursawe, Jochen; Baker, Ruth E.; Fletcher, Alexander G.

2017-09-01

'Cell-based' models provide a powerful computational tool for studying the mechanisms underlying the growth and dynamics of biological tissues in health and disease. An increasing amount of quantitative data with cellular resolution has paved the way for the quantitative parameterisation and validation of such models. However, the numerical implementation of cell-based models remains challenging, and little work has been done to understand to what extent implementation choices may influence model predictions. Here, we consider the numerical implementation of a popular class of cell-based models called vertex models, which are often used to study epithelial tissues. In two-dimensional vertex models, a tissue is approximated as a tessellation of polygons and the vertices of these polygons move due to mechanical forces originating from the cells. Such models have been used extensively to study the mechanical regulation of tissue topology in the literature. Here, we analyse how the model predictions may be affected by numerical parameters, such as the size of the time step, and non-physical model parameters, such as length thresholds for cell rearrangement. We find that vertex positions and summary statistics are sensitive to several of these implementation parameters. For example, the predicted tissue size decreases with decreasing cell cycle durations, and cell rearrangement may be suppressed by large time steps. These findings are counter-intuitive and illustrate that model predictions need to be thoroughly analysed and implementation details carefully considered when applying cell-based computational models in a quantitative setting.

Model of Fission Yeast Cell Shape Driven by Membrane-Bound Growth Factors and the Cytoskeleton

PubMed Central

Drake, Tyler; Vavylonis, Dimitrios

2013-01-01

Fission yeast serves as a model for how cellular polarization machinery consisting of signaling molecules and the actin and microtubule cytoskeleton regulates cell shape. In this work, we develop mathematical models to investigate how these cells maintain a tubular shape of approximately constant diameter. Many studies identify active Cdc42, found in a cap at the inner membrane of growing cell tips, as an important regulator of local cell wall remodeling, likely through control of exocyst tethering and the targeting of other polarity-enhancing structures. First, we show that a computational model with Cdc42-dependent local cell wall remodeling under turgor pressure predicts a relationship between spatial extent of growth signal and cell diameter that is in agreement with prior experiments. Second, we model the consequences of feedback between cell shape and distribution of Cdc42 growth signal at cell tips. We show that stability of cell diameter over successive cell divisions places restrictions on their mutual dependence. We argue that simple models where the spatial extent of the tip growth signal relies solely on geometrical alignment of confined microtubules might lead to unstable width regulation. Third, we study a computational model that combines a growth signal distributed over a characteristic length scale (as, for example, by a reaction-diffusion mechanism) with an axis-sensing microtubules system that places landmarks at positions where microtubule tips touch the cortex. A two-dimensional implementation of this model leads to stable cell diameter for a wide range of parameters. Changes to the parameters of this model reproduce straight, bent, and bulged cell shapes, and we discuss how this model is consistent with other observed cell shapes in mutants. Our work provides an initial quantitative framework for understanding the regulation of cell shape in fission yeast, and a scaffold for understanding this process on a more molecular level in the future. PMID:24146607

Systems, methods and computer-readable media for modeling cell performance fade of rechargeable electrochemical devices

DOEpatents

Gering, Kevin L

2013-08-27

A system includes an electrochemical cell, monitoring hardware, and a computing system. The monitoring hardware periodically samples performance characteristics of the electrochemical cell. The computing system determines cell information from the performance characteristics of the electrochemical cell. The computing system also develops a mechanistic level model of the electrochemical cell to determine performance fade characteristics of the electrochemical cell and analyzing the mechanistic level model to estimate performance fade characteristics over aging of a similar electrochemical cell. The mechanistic level model uses first constant-current pulses applied to the electrochemical cell at a first aging period and at three or more current values bracketing a first exchange current density. The mechanistic level model also is based on second constant-current pulses applied to the electrochemical cell at a second aging period and at three or more current values bracketing the second exchange current density.

A minimal spatial cell lineage model of epithelium: tissue stratification and multi-stability

NASA Astrophysics Data System (ADS)

Yeh, Wei-Ting; Chen, Hsuan-Yi

2018-05-01

A minimal model which includes spatial and cell lineage dynamics for stratified epithelia is presented. The dependence of tissue steady state on cell differentiation models, cell proliferation rate, cell differentiation rate, and other parameters are studied numerically and analytically. Our minimal model shows some important features. First, we find that morphogen or mechanical stress mediated interaction is necessary to maintain a healthy stratified epithelium. Furthermore, comparing with tissues in which cell differentiation can take place only during cell division, tissues in which cell division and cell differentiation are decoupled can achieve relatively higher degree of stratification. Finally, our model also shows that in the presence of short-range interactions, it is possible for a tissue to have multiple steady states. The relation between our results and tissue morphogenesis or lesion is discussed.

Low-high junction theory applied to solar cells

NASA Technical Reports Server (NTRS)

Godlewski, M. P.; Baraona, C. R.; Brandhorst, H. W., Jr.

1974-01-01

Recent use of alloying techniques for rear contact formation has yielded a new kind of silicon solar cell, the back surface field (BSF) cell, with abnormally high open-circuit voltage and improved radiation resistance. Several analytical models for open-circuit voltage based on the reverse saturation current are formulated to explain these observations. The zero surface recombination velocity (SRV) case of the conventional cell model, the drift field model, and the low-high junction (LHJ) model can predict the experimental trends. The LHJ model applies the theory of the low-high junction and is considered to reflect a more realistic view of cell fabrication. This model can predict the experimental trends observed for BSF cells.

A hybrid computational model to explore the topological characteristics of epithelial tissues.

PubMed

González-Valverde, Ismael; García-Aznar, José Manuel

2017-11-01

Epithelial tissues show a particular topology where cells resemble a polygon-like shape, but some biological processes can alter this tissue topology. During cell proliferation, mitotic cell dilation deforms the tissue and modifies the tissue topology. Additionally, cells are reorganized in the epithelial layer and these rearrangements also alter the polygon distribution. We present here a computer-based hybrid framework focused on the simulation of epithelial layer dynamics that combines discrete and continuum numerical models. In this framework, we consider topological and mechanical aspects of the epithelial tissue. Individual cells in the tissue are simulated by an off-lattice agent-based model, which keeps the information of each cell. In addition, we model the cell-cell interaction forces and the cell cycle. Otherwise, we simulate the passive mechanical behaviour of the cell monolayer using a material that approximates the mechanical properties of the cell. This continuum approach is solved by the finite element method, which uses a dynamic mesh generated by the triangulation of cell polygons. Forces generated by cell-cell interaction in the agent-based model are also applied on the finite element mesh. Cell movement in the agent-based model is driven by the displacements obtained from the deformed finite element mesh of the continuum mechanical approach. We successfully compare the results of our simulations with some experiments about the topology of proliferating epithelial tissues in Drosophila. Our framework is able to model the emergent behaviour of the cell monolayer that is due to local cell-cell interactions, which have a direct influence on the dynamics of the epithelial tissue. Copyright © 2017 John Wiley & Sons, Ltd.

Time-lapse microscopy and image processing for stem cell research: modeling cell migration

NASA Astrophysics Data System (ADS)

Gustavsson, Tomas; Althoff, Karin; Degerman, Johan; Olsson, Torsten; Thoreson, Ann-Catrin; Thorlin, Thorleif; Eriksson, Peter

2003-05-01

This paper presents hardware and software procedures for automated cell tracking and migration modeling. A time-lapse microscopy system equipped with a computer controllable motorized stage was developed. The performance of this stage was improved by incorporating software algorithms for stage motion displacement compensation and auto focus. The microscope is suitable for in-vitro stem cell studies and allows for multiple cell culture image sequence acquisition. This enables comparative studies concerning rate of cell splits, average cell motion velocity, cell motion as a function of cell sample density and many more. Several cell segmentation procedures are described as well as a cell tracking algorithm. Statistical methods for describing cell migration patterns are presented. In particular, the Hidden Markov Model (HMM) was investigated. Results indicate that if the cell motion can be described as a non-stationary stochastic process, then the HMM can adequately model aspects of its dynamic behavior.

3D multicellular model of shock wave-cell interaction.

PubMed

Li, Dongli; Hallack, Andre; Cleveland, Robin O; Jérusalem, Antoine

2018-05-01

Understanding the interaction between shock waves and tissue is critical for ad- vancing the use of shock waves for medical applications, such as cancer therapy. This work aims to study shock wave-cell interaction in a more realistic environment, relevant to in vitro and in vivo studies, by using 3D computational models of healthy and cancerous cells. The results indicate that for a single cell embedded in an extracellular environment, the cellular geometry does not influence significantly the membrane strain but does influence the von Mises stress. On the contrary, the presence of neighbouring cells has a strong effect on the cell response, by increasing fourfold both quantities. The membrane strain response of a cell converges with more than three neighbouring cell layers, indicating that a cluster of four layers of cells is sufficient to model the membrane strain in a large domain of tissue. However, a full 3D tissue model is needed if the stress evaluation is of main interest. A tumour mimicking multicellular spheroid model is also proposed to study mutual interaction between healthy and cancer cells and shows that cancer cells can be specifically targeted in an early stage tumour-mimicking environment. This work presents 3D computational models of shock-wave/cell interaction in a biophysically realistic environment using real cell morphology in tissue-mimicking phantom and multicellular spheroid. Results show that cell morphology does not strongly influence the membrane strain but influences the von Mises stress. While the presence of neighbouring cells significantly increases the cell response, four cell layers are enough to capture the membrane strain change in tissue. However, a full tissue model is necessary if accurate stress analysis is needed. The work also shows that cancer cells can be specifically targetted in early stage tumourmimicking environment. This work is a step towards realistic modelling of shock-wave/cell interactions in tissues and provides insight on the use of 3D models for different scenarios. Copyright © 2018 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Integrating Intracellular Dynamics Using CompuCell3D and Bionetsolver: Applications to Multiscale Modelling of Cancer Cell Growth and Invasion

PubMed Central

Andasari, Vivi; Roper, Ryan T.; Swat, Maciej H.; Chaplain, Mark A. J.

2012-01-01

In this paper we present a multiscale, individual-based simulation environment that integrates CompuCell3D for lattice-based modelling on the cellular level and Bionetsolver for intracellular modelling. CompuCell3D or CC3D provides an implementation of the lattice-based Cellular Potts Model or CPM (also known as the Glazier-Graner-Hogeweg or GGH model) and a Monte Carlo method based on the metropolis algorithm for system evolution. The integration of CC3D for cellular systems with Bionetsolver for subcellular systems enables us to develop a multiscale mathematical model and to study the evolution of cell behaviour due to the dynamics inside of the cells, capturing aspects of cell behaviour and interaction that is not possible using continuum approaches. We then apply this multiscale modelling technique to a model of cancer growth and invasion, based on a previously published model of Ramis-Conde et al. (2008) where individual cell behaviour is driven by a molecular network describing the dynamics of E-cadherin and -catenin. In this model, which we refer to as the centre-based model, an alternative individual-based modelling technique was used, namely, a lattice-free approach. In many respects, the GGH or CPM methodology and the approach of the centre-based model have the same overall goal, that is to mimic behaviours and interactions of biological cells. Although the mathematical foundations and computational implementations of the two approaches are very different, the results of the presented simulations are compatible with each other, suggesting that by using individual-based approaches we can formulate a natural way of describing complex multi-cell, multiscale models. The ability to easily reproduce results of one modelling approach using an alternative approach is also essential from a model cross-validation standpoint and also helps to identify any modelling artefacts specific to a given computational approach. PMID:22461894

Emergent Stratification in Solid Tumors Selects for Reduced Cohesion of Tumor Cells: A Multi-Cell, Virtual-Tissue Model of Tumor Evolution Using CompuCell3D.

PubMed

Swat, Maciej H; Thomas, Gilberto L; Shirinifard, Abbas; Clendenon, Sherry G; Glazier, James A

2015-01-01

Tumor cells and structure both evolve due to heritable variation of cell behaviors and selection over periods of weeks to years (somatic evolution). Micro-environmental factors exert selection pressures on tumor-cell behaviors, which influence both the rate and direction of evolution of specific behaviors, especially the development of tumor-cell aggression and resistance to chemotherapies. In this paper, we present, step-by-step, the development of a multi-cell, virtual-tissue model of tumor somatic evolution, simulated using the open-source CompuCell3D modeling environment. Our model includes essential cell behaviors, microenvironmental components and their interactions. Our model provides a platform for exploring selection pressures leading to the evolution of tumor-cell aggression, showing that emergent stratification into regions with different cell survival rates drives the evolution of less cohesive cells with lower levels of cadherins and higher levels of integrins. Such reduced cohesivity is a key hallmark in the progression of many types of solid tumors.

Emergent Stratification in Solid Tumors Selects for Reduced Cohesion of Tumor Cells: A Multi-Cell, Virtual-Tissue Model of Tumor Evolution Using CompuCell3D

PubMed Central

Swat, Maciej H.; Thomas, Gilberto L.; Shirinifard, Abbas; Clendenon, Sherry G.; Glazier, James A.

2015-01-01

Tumor cells and structure both evolve due to heritable variation of cell behaviors and selection over periods of weeks to years (somatic evolution). Micro-environmental factors exert selection pressures on tumor-cell behaviors, which influence both the rate and direction of evolution of specific behaviors, especially the development of tumor-cell aggression and resistance to chemotherapies. In this paper, we present, step-by-step, the development of a multi-cell, virtual-tissue model of tumor somatic evolution, simulated using the open-source CompuCell3D modeling environment. Our model includes essential cell behaviors, microenvironmental components and their interactions. Our model provides a platform for exploring selection pressures leading to the evolution of tumor-cell aggression, showing that emergent stratification into regions with different cell survival rates drives the evolution of less cohesive cells with lower levels of cadherins and higher levels of integrins. Such reduced cohesivity is a key hallmark in the progression of many types of solid tumors. PMID:26083246

Preface of the "Symposium on Mathematical Models and Methods to investigate Heterogeneity in Cell and Cell Population Biology"

NASA Astrophysics Data System (ADS)

Clairambault, Jean

2016-06-01

This session investigates hot topics related to mathematical representations of cell and cell population dynamics in biology and medicine, in particular, but not only, with applications to cancer. Methods in mathematical modelling and analysis, and in statistical inference using single-cell and cell population data, should contribute to focus this session on heterogeneity in cell populations. Among other methods are proposed: a) Intracellular protein dynamics and gene regulatory networks using ordinary/partial/delay differential equations (ODEs, PDEs, DDEs); b) Representation of cell population dynamics using agent-based models (ABMs) and/or PDEs; c) Hybrid models and multiscale models to integrate single-cell dynamics into cell population behaviour; d) Structured cell population dynamics and asymptotic evolution w.r.t. relevant traits; e) Heterogeneity in cancer cell populations: origin, evolution, phylogeny and methods of reconstruction; f) Drug resistance as an evolutionary phenotype: predicting and overcoming it in therapeutics; g) Theoretical therapeutic optimisation of combined drug treatments in cancer cell populations and in populations of other organisms, such as bacteria.

A 3D Monte Carlo model of radiation affecting cells, and its application to neuronal cells and GCR irradiation

NASA Astrophysics Data System (ADS)

Ponomarev, Artem; Sundaresan, Alamelu; Kim, Angela; Vazquez, Marcelo E.; Guida, Peter; Kim, Myung-Hee; Cucinotta, Francis A.

A 3D Monte Carlo model of radiation transport in matter is applied to study the effect of heavy ion radiation on human neuronal cells. Central nervous system effects, including cognitive impairment, are suspected from the heavy ion component of galactic cosmic radiation (GCR) during space missions. The model can count, for instance, the number of direct hits from ions, which will have the most affect on the cells. For comparison, the remote hits, which are received through δ-rays from the projectile traversing space outside the volume of the cell, are also simulated and their contribution is estimated. To simulate tissue effects from irradiation, cellular matrices of neuronal cells, which were derived from confocal microscopy, were simulated in our model. To produce this realistic model of the brain tissue, image segmentation was used to identify cells in the images of cells cultures. The segmented cells were inserted pixel by pixel into the modeled physical space, which represents a volume of interacting cells with periodic boundary conditions (PBCs). PBCs were used to extrapolate the model results to the macroscopic tissue structures. Specific spatial patterns for cell apoptosis are expected from GCR, as heavy ions produce concentrated damage along their trajectories. The apoptotic cell patterns were modeled based on the action cross sections for apoptosis, which were estimated from the available experimental data. The cell patterns were characterized with an autocorrelation function, which values are higher for non-random cell patterns, and the values of the autocorrelation function were compared for X rays and Fe ion irradiations. The autocorrelation function indicates the directionality effects present in apoptotic neuronal cells from GCR.

Kinetic models in industrial biotechnology - Improving cell factory performance.

PubMed

Almquist, Joachim; Cvijovic, Marija; Hatzimanikatis, Vassily; Nielsen, Jens; Jirstrand, Mats

2014-07-01

An increasing number of industrial bioprocesses capitalize on living cells by using them as cell factories that convert sugars into chemicals. These processes range from the production of bulk chemicals in yeasts and bacteria to the synthesis of therapeutic proteins in mammalian cell lines. One of the tools in the continuous search for improved performance of such production systems is the development and application of mathematical models. To be of value for industrial biotechnology, mathematical models should be able to assist in the rational design of cell factory properties or in the production processes in which they are utilized. Kinetic models are particularly suitable towards this end because they are capable of representing the complex biochemistry of cells in a more complete way compared to most other types of models. They can, at least in principle, be used to in detail understand, predict, and evaluate the effects of adding, removing, or modifying molecular components of a cell factory and for supporting the design of the bioreactor or fermentation process. However, several challenges still remain before kinetic modeling will reach the degree of maturity required for routine application in industry. Here we review the current status of kinetic cell factory modeling. Emphasis is on modeling methodology concepts, including model network structure, kinetic rate expressions, parameter estimation, optimization methods, identifiability analysis, model reduction, and model validation, but several applications of kinetic models for the improvement of cell factories are also discussed. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Advanced Cell Culture Techniques for Cancer Drug Discovery

PubMed Central

Lovitt, Carrie J.; Shelper, Todd B.; Avery, Vicky M.

2014-01-01

Human cancer cell lines are an integral part of drug discovery practices. However, modeling the complexity of cancer utilizing these cell lines on standard plastic substrata, does not accurately represent the tumor microenvironment. Research into developing advanced tumor cell culture models in a three-dimensional (3D) architecture that more prescisely characterizes the disease state have been undertaken by a number of laboratories around the world. These 3D cell culture models are particularly beneficial for investigating mechanistic processes and drug resistance in tumor cells. In addition, a range of molecular mechanisms deconstructed by studying cancer cells in 3D models suggest that tumor cells cultured in two-dimensional monolayer conditions do not respond to cancer therapeutics/compounds in a similar manner. Recent studies have demonstrated the potential of utilizing 3D cell culture models in drug discovery programs; however, it is evident that further research is required for the development of more complex models that incorporate the majority of the cellular and physical properties of a tumor. PMID:24887773

Advanced cell culture techniques for cancer drug discovery.

PubMed

Lovitt, Carrie J; Shelper, Todd B; Avery, Vicky M

2014-05-30

Human cancer cell lines are an integral part of drug discovery practices. However, modeling the complexity of cancer utilizing these cell lines on standard plastic substrata, does not accurately represent the tumor microenvironment. Research into developing advanced tumor cell culture models in a three-dimensional (3D) architecture that more prescisely characterizes the disease state have been undertaken by a number of laboratories around the world. These 3D cell culture models are particularly beneficial for investigating mechanistic processes and drug resistance in tumor cells. In addition, a range of molecular mechanisms deconstructed by studying cancer cells in 3D models suggest that tumor cells cultured in two-dimensional monolayer conditions do not respond to cancer therapeutics/compounds in a similar manner. Recent studies have demonstrated the potential of utilizing 3D cell culture models in drug discovery programs; however, it is evident that further research is required for the development of more complex models that incorporate the majority of the cellular and physical properties of a tumor.

Chimeric animal models in human stem cell biology.

PubMed

Glover, Joel C; Boulland, Jean-Luc; Halasi, Gabor; Kasumacic, Nedim

2009-01-01

The clinical use of stem cells for regenerative medicine is critically dependent on preclinical studies in animal models. In this review we examine some of the key issues and challenges in the use of animal models to study human stem cell biology-experimental standardization, body size, immunological barriers, cell survival factors, fusion of host and donor cells, and in vivo imaging and tracking. We focus particular attention on the various imaging modalities that can be used to track cells in living animals, comparing their strengths and weaknesses and describing technical developments that are likely to lead to new opportunities for the dynamic assessment of stem cell behavior in vivo. We then provide an overview of some of the most commonly used animal models, their advantages and disadvantages, and examples of their use for xenotypic transplantation of human stem cells, with separate reviews of models involving rodents, ungulates, nonhuman primates, and the chicken embryo. As the use of human somatic, embryonic, and induced pluripotent stem cells increases, so too will the range of applications for these animal models. It is likely that increasingly sophisticated uses of human/animal chimeric models will be developed through advances in genetic manipulation, cell delivery, and in vivo imaging.

A Model of Yeast Cell-Cycle Regulation Based on a Standard Component Modeling Strategy for Protein Regulatory Networks.

PubMed

Laomettachit, Teeraphan; Chen, Katherine C; Baumann, William T; Tyson, John J

2016-01-01

To understand the molecular mechanisms that regulate cell cycle progression in eukaryotes, a variety of mathematical modeling approaches have been employed, ranging from Boolean networks and differential equations to stochastic simulations. Each approach has its own characteristic strengths and weaknesses. In this paper, we propose a "standard component" modeling strategy that combines advantageous features of Boolean networks, differential equations and stochastic simulations in a framework that acknowledges the typical sorts of reactions found in protein regulatory networks. Applying this strategy to a comprehensive mechanism of the budding yeast cell cycle, we illustrate the potential value of standard component modeling. The deterministic version of our model reproduces the phenotypic properties of wild-type cells and of 125 mutant strains. The stochastic version of our model reproduces the cell-to-cell variability of wild-type cells and the partial viability of the CLB2-dbΔ clb5Δ mutant strain. Our simulations show that mathematical modeling with "standard components" can capture in quantitative detail many essential properties of cell cycle control in budding yeast.

A Model of Yeast Cell-Cycle Regulation Based on a Standard Component Modeling Strategy for Protein Regulatory Networks

PubMed Central

Laomettachit, Teeraphan; Chen, Katherine C.; Baumann, William T.

2016-01-01

To understand the molecular mechanisms that regulate cell cycle progression in eukaryotes, a variety of mathematical modeling approaches have been employed, ranging from Boolean networks and differential equations to stochastic simulations. Each approach has its own characteristic strengths and weaknesses. In this paper, we propose a “standard component” modeling strategy that combines advantageous features of Boolean networks, differential equations and stochastic simulations in a framework that acknowledges the typical sorts of reactions found in protein regulatory networks. Applying this strategy to a comprehensive mechanism of the budding yeast cell cycle, we illustrate the potential value of standard component modeling. The deterministic version of our model reproduces the phenotypic properties of wild-type cells and of 125 mutant strains. The stochastic version of our model reproduces the cell-to-cell variability of wild-type cells and the partial viability of the CLB2-dbΔ clb5Δ mutant strain. Our simulations show that mathematical modeling with “standard components” can capture in quantitative detail many essential properties of cell cycle control in budding yeast. PMID:27187804

A two-scale model for correlation between B cell VDJ usage in zebrafish

NASA Astrophysics Data System (ADS)

Pan, Keyao; Deem, Michael

2011-03-01

The zebrafish (Danio rerio) is one of the model animals for study of immunology. The dynamics of the adaptive immune system in zebrafish is similar to that in higher animals. In this work, we built a two-scale model to simulate the dynamics of B cells in primary and secondary immune reactions in zebrafish and to explain the reported correlation between VDJ usage of B cell repertoires in distinct zebrafish. The first scale of the model consists of a generalized NK model to simulate the B cell maturation process in the 10-day primary immune response. The second scale uses a delay ordinary differential equation system to model the immune responses in the 6-month lifespan of zebrafish. The generalized NK model shows that mature B cells specific to one antigen mostly possess a single VDJ recombination. The probability that mature B cells in two zebrafish have the same VDJ recombination increases with the B cell population size or the B cell selection intensity and decreases with the B cell hypermutation rate. The ODE model shows a distribution of correlation in the VDJ usage of the B cell repertoires in two six-month-old zebrafish that is highly similar to that from experiment. This work presents a simple theory to explain the experimentally observed correlation in VDJ usage of distinct zebrafish B cell repertoires after an immune response.

Multiscale mechanisms of cell migration during development: theory and experiment.

PubMed

McLennan, Rebecca; Dyson, Louise; Prather, Katherine W; Morrison, Jason A; Baker, Ruth E; Maini, Philip K; Kulesa, Paul M

2012-08-01

Long-distance cell migration is an important feature of embryonic development, adult morphogenesis and cancer, yet the mechanisms that drive subpopulations of cells to distinct targets are poorly understood. Here, we use the embryonic neural crest (NC) in tandem with theoretical studies to evaluate model mechanisms of long-distance cell migration. We find that a simple chemotaxis model is insufficient to explain our experimental data. Instead, model simulations predict that NC cell migration requires leading cells to respond to long-range guidance signals and trailing cells to short-range cues in order to maintain a directed, multicellular stream. Experiments confirm differences in leading versus trailing NC cell subpopulations, manifested in unique cell orientation and gene expression patterns that respond to non-linear tissue growth of the migratory domain. Ablation experiments that delete the trailing NC cell subpopulation reveal that leading NC cells distribute all along the migratory pathway and develop a leading/trailing cellular orientation and gene expression profile that is predicted by model simulations. Transplantation experiments and model predictions that move trailing NC cells to the migratory front, or vice versa, reveal that cells adopt a gene expression profile and cell behaviors corresponding to the new position within the migratory stream. These results offer a mechanistic model in which leading cells create and respond to a cell-induced chemotactic gradient and transmit guidance information to trailing cells that use short-range signals to move in a directional manner.

A Prestressed Cable Network Model of the Adherent Cell Cytoskeleton

PubMed Central

Coughlin, Mark F.; Stamenović, Dimitrije

2003-01-01

A prestressed cable network is used to model the deformability of the adherent cell actin cytoskeleton. The overall and microstructural model geometries and cable mechanical properties were assigned values based on observations from living cells and mechanical measurements on isolated actin filaments, respectively. The models were deformed to mimic cell poking (CP), magnetic twisting cytometry (MTC) and magnetic bead microrheometry (MBM) measurements on living adherent cells. The models qualitatively and quantitatively captured the fibroblast cell response to the deformation imposed by CP while exhibiting only some qualitative features of the cell response to MTC and MBM. The model for CP revealed that the tensed peripheral actin filaments provide the key resistance to indentation. The actin filament tension that provides mechanical integrity to the network was estimated at ∼158 pN, and the nonlinear mechanical response during CP originates from filament kinematics. The MTC and MBM simulations revealed that the model is incomplete, however, these simulations show cable tension as a key determinant of the model response. PMID:12547813

A prestressed cable network model of the adherent cell cytoskeleton.

PubMed

Coughlin, Mark F; Stamenović, Dimitrije

2003-02-01

A prestressed cable network is used to model the deformability of the adherent cell actin cytoskeleton. The overall and microstructural model geometries and cable mechanical properties were assigned values based on observations from living cells and mechanical measurements on isolated actin filaments, respectively. The models were deformed to mimic cell poking (CP), magnetic twisting cytometry (MTC) and magnetic bead microrheometry (MBM) measurements on living adherent cells. The models qualitatively and quantitatively captured the fibroblast cell response to the deformation imposed by CP while exhibiting only some qualitative features of the cell response to MTC and MBM. The model for CP revealed that the tensed peripheral actin filaments provide the key resistance to indentation. The actin filament tension that provides mechanical integrity to the network was estimated at approximately 158 pN, and the nonlinear mechanical response during CP originates from filament kinematics. The MTC and MBM simulations revealed that the model is incomplete, however, these simulations show cable tension as a key determinant of the model response.

Of mice and men: how animal models advance our understanding of T-cell function in RA.

PubMed

Kobezda, Tamás; Ghassemi-Nejad, Sheida; Mikecz, Katalin; Glant, Tibor T; Szekanecz, Zoltán

2014-03-01

The involvement of autoreactive T cells in the pathogenesis of rheumatoid arthritis (RA) as well as in autoimmune animal models of arthritis has been well established; however, unanswered questions, such as the role of joint-homing T cells, remain. Animal models of arthritis are superb experimental tools in demonstrating how T cells trigger joint inflammation, and thus can help to further our knowledge of disease mechanisms and potential therapies. In this Review, we discuss the similarities and differences in T-cell subsets and functions between RA and mouse arthritis models. For example, various T-cell subsets are involved in both human and mouse arthritis, but differences might exist in the cytokine regulation and plasticity of these cells. With regard to joint-homing T cells, an abundance of synovial T cells is present in humans compared with mice. On the other hand, local expansion of type 17 T-helper (TH17) cells is observed in some animal models, but not in RA. Finally, whereas T-cell depletion therapy essentially failed in RA, antibody targeting of T cells can work, at least preventatively, in most arthritis models. Clearly, additional human and animal studies are needed to fill the gap in our understanding of the specific contribution of T-cell subsets to arthritis in mice and men.

An Îto stochastic differential equations model for the dynamics of the MCF-7 breast cancer cell line treated by radiotherapy.

PubMed

Oroji, Amin; Omar, Mohd; Yarahmadian, Shantia

2016-10-21

In this paper, a new mathematical model is proposed for studying the population dynamics of breast cancer cells treated by radiotherapy by using a system of stochastic differential equations. The novelty of the model is essentially in capturing the concept of the cell cycle in the modeling to be able to evaluate the tumor lifespan. According to the cell cycle, each cell belongs to one of three subpopulations G, S, or M, representing gap, synthesis and mitosis subpopulations. Cells in the M subpopulation are highly radio-sensitive, whereas cells in the S subpopulation are highly radio-resistant. Therefore, in the process of radiotherapy, cell death rates of different subpopulations are not equal. In addition, since flow cytometry is unable to detect apoptotic cells accurately, the small changes in cell death rate in each subpopulation during treatment are considered. Subsequently, the proposed model is calibrated using experimental data from previous experiments involving the MCF-7 breast cancer cell line. Consequently, the proposed model is able to predict tumor lifespan based on the number of initial carcinoma cells. The results show the effectiveness of the radiation under the condition of stability, which describes the decreasing trend of the tumor cells population. Copyright © 2016 Elsevier Ltd. All rights reserved.

Cetuximab intensifies the ADCC activity of adoptive NK cells in a nude mouse colorectal cancer xenograft model.

PubMed

Chen, Shanshan; Li, Xuechun; Chen, Rongming; Yin, Mingang; Zheng, Qiuhong

2016-09-01

Natural killer (NK) cells, discovered ~40 years ago, are believed to be the most effective cytotoxic lymphocytes to counteract cancer; however, adoptive NK cell therapy in vivo has encountered certain limitations, including a lack of specificity. The drug cetuximab can mediate antibody dependent cell mediated cytotoxicity (ADCC) activity through NK cells in vivo , and has been approved for the first-line treatment of epidermal growth factor receptor (EGFR)-positive metastatic colorectal cancer (CRC). However, the ADCC activity of adoptive NK cells, induced by cetuximab in a nude mouse CRC xenograft model, has not been previously reported. The aim of the present study was to explore the ADCC activity of cetuximab combined with adoptive NK cells in CRC xenograft models with various EGFR expressions. The nude mouse xenograft models were established by subcutaneously injecting LOVO or SW620 cells. The mice were then randomly divided into 6 groups: Phosphate-buffered saline, cetuximab, human immunoglobulin G (hIgG), NK cells, hIgG plus NK cells and cetuximab plus NK cells. The ADCC antitumor activity was evaluated in these CRC models. The results indicated that the cetuximab plus NK cells group showed the greatest tumor inhibition effect compared with the NK cells group in LOVO xenograft tumor models with positive EGFR expression. However, the combination of cetuximab and NK cells did not show a stronger tumor inhibitory effect against the SW620 xenograft tumor models compared with the efficiency of NK cells. In conclusion, cetuximab could intensify the ADCC antitumor activity of adoptive NK cells towards CRC with an increased EGFR expression. The combination of cetuximab and NK cells may be a potential immunotherapy for metastatic CRC patients with positive EGFR expression.

Fluctuation-Noise Model for PEM Fuel Cell

NASA Astrophysics Data System (ADS)

Denisov, E. S.; Salakhova, A. Sh.; Adiutantov, N. A.; Evdokimov, Yu. K.

2017-08-01

The fluctuation-noise model is presented. This model allows to describe the power spectral density of PEM fuel cell electrical fluctuation. The proposed model can be used for diagnostics of PEM fuel cell state of health.

A model with competition between the cell lines in leukemia under treatment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Halanay, A.; Cândea, D.; Rădulescu, R.

2014-12-10

The evolution of leukemia is modeled with a delay differential equation model of four cell populations: two populations (healthy and leukemic) ) of stem-like cells involving a larger category consisting of proliferating stem and progenitor cells with self-renew capacity and two populations (healthy and leukemic) of mature cells, considering the competition of healthy vs. leukemic cell populations and three types of division that a stem-like cell can exhibit: self-renew, asymmetric division and differentiation. In the model it is assumed that the treatment acts on the proliferation rate of the leukemic stem cells and on the apoptosis of stem and maturemore » cells. The emphasis in this model is on establishing relevant parameters for chronic and acute manifestations of leukemia. Stability of equilibria is investigated and sufficient conditions for local asymptotic stability will be given using a Lyapunov-Krasovskii functional.« less

3D molecular models of whole HIV-1 virions generated with cellPACK

PubMed Central

Goodsell, David S.; Autin, Ludovic; Forli, Stefano; Sanner, Michel F.; Olson, Arthur J.

2014-01-01

As knowledge of individual biological processes grows, it becomes increasingly useful to frame new findings within their larger biological contexts in order to generate new systems-scale hypotheses. This report highlights two major iterations of a whole virus model of HIV-1, generated with the cellPACK software. cellPACK integrates structural and systems biology data with packing algorithms to assemble comprehensive 3D models of cell-scale structures in molecular detail. This report describes the biological data, modeling parameters and cellPACK methods used to specify and construct editable models for HIV-1. Anticipating that cellPACK interfaces under development will enable researchers from diverse backgrounds to critique and improve the biological models, we discuss how cellPACK can be used as a framework to unify different types of data across all scales of biology. PMID:25253262

Agent-Based Deterministic Modeling of the Bone Marrow Homeostasis.

PubMed

Kurhekar, Manish; Deshpande, Umesh

2016-01-01

Modeling of stem cells not only describes but also predicts how a stem cell's environment can control its fate. The first stem cell populations discovered were hematopoietic stem cells (HSCs). In this paper, we present a deterministic model of bone marrow (that hosts HSCs) that is consistent with several of the qualitative biological observations. This model incorporates stem cell death (apoptosis) after a certain number of cell divisions and also demonstrates that a single HSC can potentially populate the entire bone marrow. It also demonstrates that there is a production of sufficient number of differentiated cells (RBCs, WBCs, etc.). We prove that our model of bone marrow is biologically consistent and it overcomes the biological feasibility limitations of previously reported models. The major contribution of our model is the flexibility it allows in choosing model parameters which permits several different simulations to be carried out in silico without affecting the homeostatic properties of the model. We have also performed agent-based simulation of the model of bone marrow system proposed in this paper. We have also included parameter details and the results obtained from the simulation. The program of the agent-based simulation of the proposed model is made available on a publicly accessible website.

Stem cells and cancer of the stomach and intestine.

PubMed

Vries, Robert G J; Huch, Meritxell; Clevers, Hans

2010-10-01

Cancer in the 21st century has become the number one cause of death in developed countries. Although much progress has been made in improving patient survival, tumour relapse is one of the important causes of cancer treatment failure. An early observation in the study of cancer was the heterogeneity of tumours. Traditionally, this was explained by a combination of genomic instability of tumours and micro environmental factors leading to diverse phenotypical characteristics. It was assumed that cells in a tumour have an equal capacity to propagate the cancer. This model is currently known as the stochastic model. Recently, the Cancer stem cell model has been proposed to explain the heterogeneity of a tumour and its progression. According to this model, the heterogeneity of tumours is the result of aberrant differentiation of tumour cells into the cells of the tissue the tumour originated from. Tumours were suggested to contain stem cell-like cells, the cancer stem cells or tumour-initiating cells, which are uniquely capable of propagating a tumour much like normal stem cells fuel proliferation and differentiation in normal tissue. In this review we discuss the normal stem cell biology of the stomach and intestine followed by both the stochastic and cancer stem cell models in light of recent findings in the gastric and intestinal systems. The molecular pathways underlying normal and tumourigenic growth have been well studied, and recently the stem cells of the stomach and intestine have been identified. Furthermore, intestinal stem cells were identified as the cells-of-origin of colon cancer upon loss of the tumour suppressor APC. Lastly, several studies have proposed the positive identification of a cancer stem cell of human colon cancer. At the end we compare the cancer stem cell model and the stochastic model. We conclude that clonal evolution of tumour cells resulting from genetic mutations underlies tumour initiation and progression in both cancer models. This implies that at any point during tumour development any tumour cell can revert to a cancer stem cell after having gained a clonal advantage over the original cancer stem cell. Therefore, these models represent two sides of the same coin. Copyright © 2010 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Spiking Neurons in a Hierarchical Self-Organizing Map Model Can Learn to Develop Spatial and Temporal Properties of Entorhinal Grid Cells and Hippocampal Place Cells

PubMed Central

Pilly, Praveen K.; Grossberg, Stephen

2013-01-01

Medial entorhinal grid cells and hippocampal place cells provide neural correlates of spatial representation in the brain. A place cell typically fires whenever an animal is present in one or more spatial regions, or places, of an environment. A grid cell typically fires in multiple spatial regions that form a regular hexagonal grid structure extending throughout the environment. Different grid and place cells prefer spatially offset regions, with their firing fields increasing in size along the dorsoventral axes of the medial entorhinal cortex and hippocampus. The spacing between neighboring fields for a grid cell also increases along the dorsoventral axis. This article presents a neural model whose spiking neurons operate in a hierarchy of self-organizing maps, each obeying the same laws. This spiking GridPlaceMap model simulates how grid cells and place cells may develop. It responds to realistic rat navigational trajectories by learning grid cells with hexagonal grid firing fields of multiple spatial scales and place cells with one or more firing fields that match neurophysiological data about these cells and their development in juvenile rats. The place cells represent much larger spaces than the grid cells, which enable them to support navigational behaviors. Both self-organizing maps amplify and learn to categorize the most frequent and energetic co-occurrences of their inputs. The current results build upon a previous rate-based model of grid and place cell learning, and thus illustrate a general method for converting rate-based adaptive neural models, without the loss of any of their analog properties, into models whose cells obey spiking dynamics. New properties of the spiking GridPlaceMap model include the appearance of theta band modulation. The spiking model also opens a path for implementation in brain-emulating nanochips comprised of networks of noisy spiking neurons with multiple-level adaptive weights for controlling autonomous adaptive robots capable of spatial navigation. PMID:23577130

Dynamics of human T-cell lymphotropic virus I (HTLV-I) infection of CD4+ T-cells.

PubMed

Katri, Patricia; Ruan, Shigui

2004-11-01

Stilianakis and Seydel (Bull. Math. Biol., 1999) proposed an ODE model that describes the T-cell dynamics of human T-cell lymphotropic virus I (HTLV-I) infection and the development of adult T-cell leukemia (ATL). Their model consists of four components: uninfected healthy CD4+ T-cells, latently infected CD4+ T-cells, actively infected CD4+ T-cells, and ATL cells. Mathematical analysis that completely determines the global dynamics of this model has been done by Wang et al. (Math. Biosci., 2002). In this note, we first modify the parameters of the model to distinguish between contact and infectivity rates. Then we introduce a discrete time delay to the model to describe the time between emission of contagious particles by active CD4+ T-cells and infection of pure cells. Using the results in Culshaw and Ruan (Math. Biosci., 2000) in the analysis of time delay with respect to cell-free viral spread of HIV, we study the effect of time delay on the stability of the endemically infected equilibrium. Numerical simulations are presented to illustrate the results.

Reprogramming of human cancer cells to pluripotency for models of cancer progression

PubMed Central

Kim, Jungsun; Zaret, Kenneth S

2015-01-01

The ability to study live cells as they progress through the stages of cancer provides the opportunity to discover dynamic networks underlying pathology, markers of early stages, and ways to assess therapeutics. Genetically engineered animal models of cancer, where it is possible to study the consequences of temporal-specific induction of oncogenes or deletion of tumor suppressors, have yielded major insights into cancer progression. Yet differences exist between animal and human cancers, such as in markers of progression and response to therapeutics. Thus, there is a need for human cell models of cancer progression. Most human cell models of cancer are based on tumor cell lines and xenografts of primary tumor cells that resemble the advanced tumor state, from which the cells were derived, and thus do not recapitulate disease progression. Yet a subset of cancer types have been reprogrammed to pluripotency or near-pluripotency by blastocyst injection, by somatic cell nuclear transfer and by induced pluripotent stem cell (iPS) technology. The reprogrammed cancer cells show that pluripotency can transiently dominate over the cancer phenotype. Diverse studies show that reprogrammed cancer cells can, in some cases, exhibit early-stage phenotypes reflective of only partial expression of the cancer genome. In one case, reprogrammed human pancreatic cancer cells have been shown to recapitulate stages of cancer progression, from early to late stages, thus providing a model for studying pancreatic cancer development in human cells where previously such could only be discerned from mouse models. We discuss these findings, the challenges in developing such models and their current limitations, and ways that iPS reprogramming may be enhanced to develop human cell models of cancer progression. PMID:25712212

Allometric Scaling and Cell Ratios in Multi-Organ in vitro Models of Human Metabolism.

PubMed

Ucciferri, Nadia; Sbrana, Tommaso; Ahluwalia, Arti

2014-01-01

Intelligent in vitro models able to recapitulate the physiological interactions between tissues in the body have enormous potential as they enable detailed studies on specific two-way or higher order tissue communication. These models are the first step toward building an integrated picture of systemic metabolism and signaling in physiological or pathological conditions. However, the rational design of in vitro models of cell-cell or cell-tissue interaction is difficult as quite often cell culture experiments are driven by the device used, rather than by design considerations. Indeed, very little research has been carried out on in vitro models of metabolism connecting different cell or tissue types in a physiologically and metabolically relevant manner. Here, we analyze the physiological relationship between cells, cell metabolism, and exchange in the human body using allometric rules, downscaling them to an organ-on-a-plate device. In particular, in order to establish appropriate cell ratios in the system in a rational manner, two different allometric scaling models (cell number scaling model and metabolic and surface scaling model) are proposed and applied to a two compartment model of hepatic-vascular metabolic cross-talk. The theoretical scaling studies illustrate that the design and hence relevance of multi-organ models is principally determined by experimental constraints. Two experimentally feasible model configurations are then implemented in a multi-compartment organ-on-a-plate device. An analysis of the metabolic response of the two configurations demonstrates that their glucose and lipid balance is quite different, with only one of the two models recapitulating physiological-like homeostasis. In conclusion, not only do cross-talk and physical stimuli play an important role in in vitro models, but the numeric relationship between cells is also crucial to recreate in vitro interactions, which can be extrapolated to the in vivo reality.

Comparison of Multiscale Method of Cells-Based Models for Predicting Elastic Properties of Filament Wound C/C-SiC

NASA Technical Reports Server (NTRS)

Pineda, Evan J.; Fassin, Marek; Bednarcyk, Brett A.; Reese, Stefanie; Simon, Jaan-Willem

2017-01-01

Three different multiscale models, based on the method of cells (generalized and high fidelity) micromechanics models were developed and used to predict the elastic properties of C/C-SiC composites. In particular, the following multiscale modeling strategies were employed: Concurrent multiscale modeling of all phases using the generalized method of cells, synergistic (two-way coupling in space) multiscale modeling with the generalized method of cells, and hierarchical (one-way coupling in space) multiscale modeling with the high fidelity generalized method of cells. The three models are validated against data from a hierarchical multiscale finite element model in the literature for a repeating unit cell of C/C-SiC. Furthermore, the multiscale models are used in conjunction with classical lamination theory to predict the stiffness of C/C-SiC plates manufactured via a wet filament winding and liquid silicon infiltration process recently developed by the German Aerospace Institute.

Modeling Cell Size Regulation: From Single-Cell-Level Statistics to Molecular Mechanisms and Population-Level Effects.

PubMed

Ho, Po-Yi; Lin, Jie; Amir, Ariel

2018-05-20

Most microorganisms regulate their cell size. In this article, we review some of the mathematical formulations of the problem of cell size regulation. We focus on coarse-grained stochastic models and the statistics that they generate. We review the biologically relevant insights obtained from these models. We then describe cell cycle regulation and its molecular implementations, protein number regulation, and population growth, all in relation to size regulation. Finally, we discuss several future directions for developing understanding beyond phenomenological models of cell size regulation.

Vertex Models of Epithelial Morphogenesis

PubMed Central

Fletcher, Alexander G.; Osterfield, Miriam; Baker, Ruth E.; Shvartsman, Stanislav Y.

2014-01-01

The dynamic behavior of epithelial cell sheets plays a central role during numerous developmental processes. Genetic and imaging studies of epithelial morphogenesis in a wide range of organisms have led to increasingly detailed mechanisms of cell sheet dynamics. Computational models offer a useful means by which to investigate and test these mechanisms, and have played a key role in the study of cell-cell interactions. A variety of modeling approaches can be used to simulate the balance of forces within an epithelial sheet. Vertex models are a class of such models that consider cells as individual objects, approximated by two-dimensional polygons representing cellular interfaces, in which each vertex moves in response to forces due to growth, interfacial tension, and pressure within each cell. Vertex models are used to study cellular processes within epithelia, including cell motility, adhesion, mitosis, and delamination. This review summarizes how vertex models have been used to provide insight into developmental processes and highlights current challenges in this area, including progressing these models from two to three dimensions and developing new tools for model validation. PMID:24896108

Towards Predicting the Response of a Solid Tumour to Chemotherapy and Radiotherapy Treatments: Clinical Insights from a Computational Model

PubMed Central

Powathil, Gibin G.; Adamson, Douglas J. A.; Chaplain, Mark A. J.

2013-01-01

In this paper we use a hybrid multiscale mathematical model that incorporates both individual cell behaviour through the cell-cycle and the effects of the changing microenvironment through oxygen dynamics to study the multiple effects of radiation therapy. The oxygenation status of the cells is considered as one of the important prognostic markers for determining radiation therapy, as hypoxic cells are less radiosensitive. Another factor that critically affects radiation sensitivity is cell-cycle regulation. The effects of radiation therapy are included in the model using a modified linear quadratic model for the radiation damage, incorporating the effects of hypoxia and cell-cycle in determining the cell-cycle phase-specific radiosensitivity. Furthermore, after irradiation, an individual cell's cell-cycle dynamics are intrinsically modified through the activation of pathways responsible for repair mechanisms, often resulting in a delay/arrest in the cell-cycle. The model is then used to study various combinations of multiple doses of cell-cycle dependent chemotherapies and radiation therapy, as radiation may work better by the partial synchronisation of cells in the most radiosensitive phase of the cell-cycle. Moreover, using this multi-scale model, we investigate the optimum sequencing and scheduling of these multi-modality treatments, and the impact of internal and external heterogeneity on the spatio-temporal patterning of the distribution of tumour cells and their response to different treatment schedules. PMID:23874170

Stem Cell Models: A Guide to Understand and Mitigate Aging?

PubMed

Brunauer, Regina; Alavez, Silvestre; Kennedy, Brian K

2017-01-01

Aging is studied either on a systemic level using life span and health span of animal models, or on the cellular level using replicative life span of yeast or mammalian cells. While useful in identifying general and conserved pathways of aging, both approaches provide only limited information about cell-type specific causes and mechanisms of aging. Stem cells are the regenerative units of multicellular life, and stem cell aging might be a major cause for organismal aging. Using the examples of hematopoietic stem cell aging and human pluripotent stem cell models, we propose that stem cell models of aging are valuable for studying tissue-specific causes and mechanisms of aging and can provide unique insights into the mammalian aging process that may be inaccessible in simple model organisms. © 2016 S. Karger AG, Basel.

Probing eukaryotic cell mechanics via mesoscopic simulations

PubMed Central

Shang, Menglin; Lim, Chwee Teck

2017-01-01

Cell mechanics has proven to be important in many biological processes. Although there is a number of experimental techniques which allow us to study mechanical properties of cell, there is still a lack of understanding of the role each sub-cellular component plays during cell deformations. We present a new mesoscopic particle-based eukaryotic cell model which explicitly describes cell membrane, nucleus and cytoskeleton. We employ Dissipative Particle Dynamics (DPD) method that provides us with the unified framework for modeling of a cell and its interactions in the flow. Data from micropipette aspiration experiments were used to define model parameters. The model was validated using data from microfluidic experiments. The validated model was then applied to study the impact of the sub-cellular components on the cell viscoelastic response in micropipette aspiration and microfluidic experiments. PMID:28922399

"Mouse Clone Model" for evaluating the immunogenicity and tumorigenicity of pluripotent stem cells.

PubMed

Zhang, Gang; Zhang, Yi

2015-12-18

To investigate the immune-rejection and tumor-formation potentials of induced pluripotent stem cells and other stem cells, we devised a model-designated the "Mouse Clone Model"-which combined the theory of somatic animal cloning, tetraploid complementation, and induced pluripotent stem cells to demonstrate the applicability of stem cells for transplantation therapy.

SU-E-T-751: Three-Component Kinetic Model of Tumor Growth and Radiation Response for Stereotactic Radiosurgery

DOE Office of Scientific and Technical Information (OSTI.GOV)

Watanabe, Y; Dahlman, E; Leder, K

Purpose: To develop and study a kinetic model of tumor growth and its response to stereotactic radiosurgery (SRS) by assuming that the cells in irradiated tumor volume were made of three types. Methods: A set of ordinary differential equations (ODEs) were derived for three types of cells and a tumor growth rate. It is assumed that the cells were composed of actively proliferating cells, lethally damaged-dividing cells, and non-dividing cells. We modeled the tumor volume growth with a time-dependent growth rate to simulate the saturation of growth. After SRS, the proliferating cells were permanently damaged and converted to the lethallymore » damaged cells. The amount of damaged cells were estimated by the LQ-model. The damaged cells gradually stopped dividing/proliferating and died with a constant rate. The dead cells were cleared from their original location with a constant rate. The total tumor volume was the sum of the three components. The ODEs were numerically solved with appropriate initial conditions for a given dosage. The proposed model was used to model an animal experiment, for which the temporal change of a rhabdomyosarcoma tumor volume grown in a rat was measured with time resolution sufficient to test the model. Results: To fit the model to the experimental data, the following characteristics were needed with the model parameters. The α-value in the LQ-model was smaller than the commonly used value; furthermore, it decreased with increasing dose. At the same time, the tumor growth rate after SRS had to increase. Conclusions: The new 3-component model of tumor could simulate the experimental data very well. The current study suggested that the radiation sensitivity and the growth rate of the proliferating tumor cells may change after irradiation and it depended on the dosage used for SRS. These preliminary observations must be confirmed by future animal experiments.« less

Models of collective cell spreading with variable cell aspect ratio: a motivation for degenerate diffusion models.

PubMed

Simpson, Matthew J; Baker, Ruth E; McCue, Scott W

2011-02-01

Continuum diffusion models are often used to represent the collective motion of cell populations. Most previous studies have simply used linear diffusion to represent collective cell spreading, while others found that degenerate nonlinear diffusion provides a better match to experimental cell density profiles. In the cell modeling literature there is no guidance available with regard to which approach is more appropriate for representing the spreading of cell populations. Furthermore, there is no knowledge of particular experimental measurements that can be made to distinguish between situations where these two models are appropriate. Here we provide a link between individual-based and continuum models using a multiscale approach in which we analyze the collective motion of a population of interacting agents in a generalized lattice-based exclusion process. For round agents that occupy a single lattice site, we find that the relevant continuum description of the system is a linear diffusion equation, whereas for elongated rod-shaped agents that occupy L adjacent lattice sites we find that the relevant continuum description is connected to the porous media equation (PME). The exponent in the nonlinear diffusivity function is related to the aspect ratio of the agents. Our work provides a physical connection between modeling collective cell spreading and the use of either the linear diffusion equation or the PME to represent cell density profiles. Results suggest that when using continuum models to represent cell population spreading, we should take care to account for variations in the cell aspect ratio because different aspect ratios lead to different continuum models.

Preclinical mouse model to monitor live Muc5b-producing conjunctival goblet cell density under pharmacological treatments.

PubMed

Portal, Céline; Gouyer, Valérie; Gottrand, Frédéric; Desseyn, Jean-Luc

2017-01-01

Modification of mucous cell density and gel-forming mucin production are established hallmarks of mucosal diseases. Our aim was to develop and validate a mouse model to study live goblet cell density in pathological situations and under pharmacological treatments. We created a reporter mouse for the gel-forming mucin gene Muc5b. Muc5b-positive goblet cells were studied in the eye conjunctiva by immunohistochemistry and probe-based confocal laser endomicroscopy (pCLE) in living mice. Dry eye syndrome (DES) model was induced by topical application of benzalkonium chloride (BAK) and recombinant interleukine (rIL) 13 was administered to reverse the goblet cell loss in the DES model. Almost 50% of the total of conjunctival goblet cells are Muc5b+ in unchallenged mice. The decrease density of Muc5b+ conjunctival goblet cell population in the DES model reflects the whole conjunctival goblet cell loss. Ten days of BAK in one eye followed by 4 days without any treatment induced a -18.3% decrease in conjunctival goblet cell density. A four days of rIL13 application in the DES model restored the normal goblet cell density. Muc5b is a biological marker of DES mouse models. We bring the proof of concept that our model is unique and allows a better understanding of the mechanisms that regulate gel-forming mucin production/secretion and mucous cell differentiation in the conjunctiva of living mice and can be used to test treatment compounds in mucosal disease models.

Selection of a Relevant In Vitro Blood-Brain Barrier Model to Investigate Pro-Metastatic Features of Human Breast Cancer Cell Lines.

PubMed

Drolez, Aurore; Vandenhaute, Elodie; Julien, Sylvain; Gosselet, Fabien; Burchell, Joy; Cecchelli, Roméo; Delannoy, Philippe; Dehouck, Marie-Pierre; Mysiorek, Caroline

2016-01-01

Around 7-17% of metastatic breast cancer patients will develop brain metastases, associated with a poor prognosis. To reach the brain parenchyma, cancer cells need to cross the highly restrictive endothelium of the Blood-Brain Barrier (BBB). As treatments for brain metastases are mostly inefficient, preventing cancer cells to reach the brain could provide a relevant and important strategy. For that purpose an in vitro approach is required to identify cellular and molecular interaction mechanisms between breast cancer cells and BBB endothelium, notably at the early steps of the interaction. However, while numerous studies are performed with in vitro models, the heterogeneity and the quality of BBB models used is a limitation to the extrapolation of the obtained results to in vivo context, showing that the choice of a model that fulfills the biological BBB characteristics is essential. Therefore, we compared pre-established and currently used in vitro models from different origins (bovine, mice, human) in order to define the most appropriate tool to study interactions between breast cancer cells and the BBB. On each model, the BBB properties and the adhesion capacities of breast cancer cell lines were evaluated. As endothelial cells represent the physical restriction site of the BBB, all the models consisted of endothelial cells from animal or human origins. Among these models, only the in vitro BBB model derived from human stem cells both displayed BBB properties and allowed measurement of meaningful different interaction capacities of the cancer cell lines. Importantly, the measured adhesion and transmigration were found to be in accordance with the cancer cell lines molecular subtypes. In addition, at a molecular level, the inhibition of ganglioside biosynthesis highlights the potential role of glycosylation in breast cancer cells adhesion capacities.

Parameter estimation for an immortal model of colonic stem cell division using approximate Bayesian computation.

PubMed

Walters, Kevin

2012-08-07

In this paper we use approximate Bayesian computation to estimate the parameters in an immortal model of colonic stem cell division. We base the inferences on the observed DNA methylation patterns of cells sampled from the human colon. Utilising DNA methylation patterns as a form of molecular clock is an emerging area of research and has been used in several studies investigating colonic stem cell turnover. There is much debate concerning the two competing models of stem cell turnover: the symmetric (immortal) and asymmetric models. Early simulation studies concluded that the observed methylation data were not consistent with the immortal model. A later modified version of the immortal model that included preferential strand segregation was subsequently shown to be consistent with the same methylation data. Most of this earlier work assumes site independent methylation models that do not take account of the known processivity of methyltransferases whilst other work does not take into account the methylation errors that occur in differentiated cells. This paper addresses both of these issues for the immortal model and demonstrates that approximate Bayesian computation provides accurate estimates of the parameters in this neighbour-dependent model of methylation error rates. The results indicate that if colonic stem cells divide asymmetrically then colon stem cell niches are maintained by more than 8 stem cells. Results also indicate the possibility of preferential strand segregation and provide clear evidence against a site-independent model for methylation errors. In addition, algebraic expressions for some of the summary statistics used in the approximate Bayesian computation (that allow for the additional variation arising from cell division in differentiated cells) are derived and their utility discussed. Copyright © 2012 Elsevier Ltd. All rights reserved.

A simplified solar cell array modelling program

NASA Technical Reports Server (NTRS)

Hughes, R. D.

1982-01-01

As part of the energy conversion/self sufficiency efforts of DSN engineering, it was necessary to have a simplified computer model of a solar photovoltaic (PV) system. This article describes the analysis and simplifications employed in the development of a PV cell array computer model. The analysis of the incident solar radiation, steady state cell temperature and the current-voltage characteristics of a cell array are discussed. A sample cell array was modelled and the results are presented.

Freezing Transition Studies Through Constrained Cell Model Simulation

NASA Astrophysics Data System (ADS)

Nayhouse, Michael; Kwon, Joseph Sang-Il; Heng, Vincent R.; Amlani, Ankur M.; Orkoulas, G.

2014-10-01

In the present work, a simulation method based on cell models is used to deduce the fluid-solid transition of a system of particles that interact via a pair potential, , which is of the form with . The simulations are implemented under constant-pressure conditions on a generalized version of the constrained cell model. The constrained cell model is constructed by dividing the volume into Wigner-Seitz cells and confining each particle in a single cell. This model is a special case of a more general cell model which is formed by introducing an additional field variable that controls the number of particles per cell and, thus, the relative stability of the solid against the fluid phase. High field values force configurations with one particle per cell and thus favor the solid phase. Fluid-solid coexistence on the isotherm that corresponds to a reduced temperature of 2 is determined from constant-pressure simulations of the generalized cell model using tempering and histogram reweighting techniques. The entire fluid-solid phase boundary is determined through a thermodynamic integration technique based on histogram reweighting, using the previous coexistence point as a reference point. The vapor-liquid phase diagram is obtained from constant-pressure simulations of the unconstrained system using tempering and histogram reweighting. The phase diagram of the system is found to contain a stable critical point and a triple point. The phase diagram of the corresponding constrained cell model is also found to contain both a stable critical point and a triple point.

A multiphase model for chemically- and mechanically- induced cell differentiation in a hollow fibre membrane bioreactor: minimising growth factor consumption.

PubMed

Pearson, Natalie C; Oliver, James M; Shipley, Rebecca J; Waters, Sarah L

2016-06-01

We present a simplified two-dimensional model of fluid flow, solute transport, and cell distribution in a hollow fibre membrane bioreactor. We consider two cell populations, one undifferentiated and one differentiated, with differentiation stimulated either by growth factor alone, or by both growth factor and fluid shear stress. Two experimental configurations are considered, a 3-layer model in which the cells are seeded in a scaffold throughout the extracapillary space (ECS), and a 4-layer model in which the cell-scaffold construct occupies a layer surrounding the outside of the hollow fibre, only partially filling the ECS. Above this is a region of free-flowing fluid, referred to as the upper fluid layer. Following previous models by the authors (Pearson et al. in Math Med Biol, 2013, Biomech Model Mechanbiol 1-16, 2014a, we employ porous mixture theory to model the dynamics of, and interactions between, the cells, scaffold, and fluid in the cell-scaffold construct. We use this model to determine operating conditions (experiment end time, growth factor inlet concentration, and inlet fluid fluxes) which result in a required percentage of differentiated cells, as well as maximising the differentiated cell yield and minimising the consumption of expensive growth factor.

Highly Adaptable Triple-Negative Breast Cancer Cells as a Functional Model for Testing Anticancer Agents

PubMed Central

Singh, Balraj; Shamsnia, Anna; Raythatha, Milan R.; Milligan, Ryan D.; Cady, Amanda M.; Madan, Simran; Lucci, Anthony

2014-01-01

A major obstacle in developing effective therapies against solid tumors stems from an inability to adequately model the rare subpopulation of panresistant cancer cells that may often drive the disease. We describe a strategy for optimally modeling highly abnormal and highly adaptable human triple-negative breast cancer cells, and evaluating therapies for their ability to eradicate such cells. To overcome the shortcomings often associated with cell culture models, we incorporated several features in our model including a selection of highly adaptable cancer cells based on their ability to survive a metabolic challenge. We have previously shown that metabolically adaptable cancer cells efficiently metastasize to multiple organs in nude mice. Here we show that the cancer cells modeled in our system feature an embryo-like gene expression and amplification of the fat mass and obesity associated gene FTO. We also provide evidence of upregulation of ZEB1 and downregulation of GRHL2 indicating increased epithelial to mesenchymal transition in metabolically adaptable cancer cells. Our results obtained with a variety of anticancer agents support the validity of the model of realistic panresistance and suggest that it could be used for developing anticancer agents that would overcome panresistance. PMID:25279830

Modelling Spread of Oncolytic Viruses in Heterogeneous Cell Populations

NASA Astrophysics Data System (ADS)

Ellis, Michael; Dobrovolny, Hana

2014-03-01

One of the most promising areas in current cancer research and treatment is the use of viruses to attack cancer cells. A number of oncolytic viruses have been identified to date that possess the ability to destroy or neutralize cancer cells while inflicting minimal damage upon healthy cells. Formulation of predictive models that correctly describe the evolution of infected tumor systems is critical to the successful application of oncolytic virus therapy. A number of different models have been proposed for analysis of the oncolytic virus-infected tumor system, with approaches ranging from traditional coupled differential equations such as the Lotka-Volterra predator-prey models, to contemporary modeling frameworks based on neural networks and cellular automata. Existing models are focused on tumor cells and the effects of virus infection, and offer the potential for improvement by including effects upon normal cells. We have recently extended the traditional framework to a 2-cell model addressing the full cellular system including tumor cells, normal cells, and the impacts of viral infection upon both populations. Analysis of the new framework reveals complex interaction between the populations and potential inability to simultaneously eliminate the virus and tumor populations.

Highly adaptable triple-negative breast cancer cells as a functional model for testing anticancer agents.

PubMed

Singh, Balraj; Shamsnia, Anna; Raythatha, Milan R; Milligan, Ryan D; Cady, Amanda M; Madan, Simran; Lucci, Anthony

2014-01-01

A major obstacle in developing effective therapies against solid tumors stems from an inability to adequately model the rare subpopulation of panresistant cancer cells that may often drive the disease. We describe a strategy for optimally modeling highly abnormal and highly adaptable human triple-negative breast cancer cells, and evaluating therapies for their ability to eradicate such cells. To overcome the shortcomings often associated with cell culture models, we incorporated several features in our model including a selection of highly adaptable cancer cells based on their ability to survive a metabolic challenge. We have previously shown that metabolically adaptable cancer cells efficiently metastasize to multiple organs in nude mice. Here we show that the cancer cells modeled in our system feature an embryo-like gene expression and amplification of the fat mass and obesity associated gene FTO. We also provide evidence of upregulation of ZEB1 and downregulation of GRHL2 indicating increased epithelial to mesenchymal transition in metabolically adaptable cancer cells. Our results obtained with a variety of anticancer agents support the validity of the model of realistic panresistance and suggest that it could be used for developing anticancer agents that would overcome panresistance.

Three-dimensional printing of Hela cells for cervical tumor model in vitro.

PubMed

Zhao, Yu; Yao, Rui; Ouyang, Liliang; Ding, Hongxu; Zhang, Ting; Zhang, Kaitai; Cheng, Shujun; Sun, Wei

2014-09-01

Advances in three-dimensional (3D) printing have enabled the direct assembly of cells and extracellular matrix materials to form in vitro cellular models for 3D biology, the study of disease pathogenesis and new drug discovery. In this study, we report a method of 3D printing for Hela cells and gelatin/alginate/fibrinogen hydrogels to construct in vitro cervical tumor models. Cell proliferation, matrix metalloproteinase (MMP) protein expression and chemoresistance were measured in the printed 3D cervical tumor models and compared with conventional 2D planar culture models. Over 90% cell viability was observed using the defined printing process. Comparisons of 3D and 2D results revealed that Hela cells showed a higher proliferation rate in the printed 3D environment and tended to form cellular spheroids, but formed monolayer cell sheets in 2D culture. Hela cells in 3D printed models also showed higher MMP protein expression and higher chemoresistance than those in 2D culture. These new biological characteristics from the printed 3D tumor models in vitro as well as the novel 3D cell printing technology may help the evolution of 3D cancer study.

Multi-Node Thermal System Model for Lithium-Ion Battery Packs: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shi, Ying; Smith, Kandler; Wood, Eric

Temperature is one of the main factors that controls the degradation in lithium ion batteries. Accurate knowledge and control of cell temperatures in a pack helps the battery management system (BMS) to maximize cell utilization and ensure pack safety and service life. In a pack with arrays of cells, a cells temperature is not only affected by its own thermal characteristics but also by its neighbors, the cooling system and pack configuration, which increase the noise level and the complexity of cell temperatures prediction. This work proposes to model lithium ion packs thermal behavior using a multi-node thermal network model,more » which predicts the cell temperatures by zones. The model was parametrized and validated using commercial lithium-ion battery packs. neighbors, the cooling system and pack configuration, which increase the noise level and the complexity of cell temperatures prediction. This work proposes to model lithium ion packs thermal behavior using a multi-node thermal network model, which predicts the cell temperatures by zones. The model was parametrized and validated using commercial lithium-ion battery packs.« less

Computational analysis of the human sinus node action potential: model development and effects of mutations

PubMed Central

Fabbri, Alan; Fantini, Matteo; Wilders, Ronald

2017-01-01

Key points We constructed a comprehensive mathematical model of the spontaneous electrical activity of a human sinoatrial node (SAN) pacemaker cell, starting from the recent Severi–DiFrancesco model of rabbit SAN cells.Our model is based on electrophysiological data from isolated human SAN pacemaker cells and closely matches the action potentials and calcium transient that were recorded experimentally.Simulated ion channelopathies explain the clinically observed changes in heart rate in corresponding mutation carriers, providing an independent qualitative validation of the model.The model shows that the modulatory role of the ‘funny current’ (I f) in the pacing rate of human SAN pacemaker cells is highly similar to that of rabbit SAN cells, despite its considerably lower amplitude.The model may prove useful in the design of experiments and the development of heart‐rate modulating drugs. Abstract The sinoatrial node (SAN) is the normal pacemaker of the mammalian heart.  Over several decades, a large amount of data on the ionic mechanisms underlying the spontaneous electrical activity of SAN pacemaker cells has been obtained, mostly in experiments on single cells isolated from rabbit SAN. This wealth of data has allowed the development of mathematical models of the electrical activity of rabbit SAN pacemaker cells. The present study aimed to construct a comprehensive model of the electrical activity of a human SAN pacemaker cell using recently obtained electrophysiological data from human SAN pacemaker cells.  We based our model on the recent Severi–DiFrancesco model of a rabbit SAN pacemaker cell. The action potential and calcium transient of the resulting model are close to the experimentally recorded values. The model has a much smaller ‘funny current’ (I f) than do rabbit cells, although its modulatory role is highly similar. Changes in pacing rate upon the implementation of mutations associated with sinus node dysfunction agree with the clinical observations. This agreement holds for both loss‐of‐function and gain‐of‐function mutations in the HCN4, SCN5A and KCNQ1 genes, underlying ion channelopathies in I f, fast sodium current and slow delayed rectifier potassium current, respectively. We conclude that our human SAN cell model can be a useful tool in the design of experiments and the development of drugs that aim to modulate heart rate. PMID:28185290

Stem cells in genetically-engineered mouse models of prostate cancer

PubMed Central

Shibata, Maho; Shen, Michael M.

2015-01-01

The cancer stem cell model proposes that tumors have a hierarchical organization in which tumorigenic cells give rise to non-tumorigenic cells, with only a subset of stem-like cells able to propagate the tumor. In the case of prostate cancer, recent analyses of genetically engineered mouse (GEM) models have provided evidence supporting the existence of cancer stem cells in vivo. These studies suggest that cancer stem cells capable of tumor propagation exist at various stages of tumor progression from prostatic intraepithelial neoplasia (PIN) to advanced metastatic and castration-resistant disease. However, studies of stem cells in prostate cancer have been limited by available approaches for evaluating their functional properties in cell culture and transplantation assays. Given the role of the tumor microenvironment and the putative cancer stem cell niche, future studies using GEM models to analyze cancer stem cells in their native tissue microenvironment are likely to be highly informative. PMID:26341780

Multiple scale model for cell migration in monolayers: Elastic mismatch between cells enhances motility

NASA Astrophysics Data System (ADS)

Palmieri, Benoit; Bresler, Yony; Wirtz, Denis; Grant, Martin

2015-07-01

We propose a multiscale model for monolayer of motile cells that comprise normal and cancer cells. In the model, the two types of cells have identical properties except for their elasticity; cancer cells are softer and normal cells are stiffer. The goal is to isolate the role of elasticity mismatch on the migration potential of cancer cells in the absence of other contributions that are present in real cells. The methodology is based on a phase-field description where each cell is modeled as a highly-deformable self-propelled droplet. We simulated two types of nearly confluent monolayers. One contains a single cancer cell in a layer of normal cells and the other contains normal cells only. The simulation results demonstrate that elasticity mismatch alone is sufficient to increase the motility of the cancer cell significantly. Further, the trajectory of the cancer cell is decorated by several speed “bursts” where the cancer cell quickly relaxes from a largely deformed shape and consequently increases its translational motion. The increased motility and the amplitude and frequency of the bursts are in qualitative agreement with recent experiments.

Pharmacodynamic Modeling of Cell Cycle Effects for Gemcitabine and Trabectedin Combinations in Pancreatic Cancer Cells

PubMed Central

Miao, Xin; Koch, Gilbert; Ait-Oudhia, Sihem; Straubinger, Robert M.; Jusko, William J.

2016-01-01

Combinations of gemcitabine and trabectedin exert modest synergistic cytotoxic effects on two pancreatic cancer cell lines. Here, systems pharmacodynamic (PD) models that integrate cellular response data and extend a prototype model framework were developed to characterize dynamic changes in cell cycle phases of cancer cell subpopulations in response to gemcitabine and trabectedin as single agents and in combination. Extensive experimental data were obtained for two pancreatic cancer cell lines (MiaPaCa-2 and BxPC-3), including cell proliferation rates over 0–120 h of drug exposure, and the fraction of cells in different cell cycle phases or apoptosis. Cell cycle analysis demonstrated that gemcitabine induced cell cycle arrest in S phase, and trabectedin induced transient cell cycle arrest in S phase that progressed to G2/M phase. Over time, cells in the control group accumulated in G0/G1 phase. Systems cell cycle models were developed based on observed mechanisms and were used to characterize both cell proliferation and cell numbers in the sub G1, G0/G1, S, and G2/M phases in the control and drug-treated groups. The proposed mathematical models captured well both single and joint effects of gemcitabine and trabectedin. Interaction parameters were applied to quantify unexplainable drug-drug interaction effects on cell cycle arrest in S phase and in inducing apoptosis. The developed models were able to identify and quantify the different underlying interactions between gemcitabine and trabectedin, and captured well our large datasets in the dimensions of time, drug concentrations, and cellular subpopulations. PMID:27895579

A multi-scale model for correlation in B cell VDJ usage of zebrafish

NASA Astrophysics Data System (ADS)

Pan, Keyao; Deem, Michael W.

2011-10-01

The zebrafish (Danio rerio) is one of the model animals used for the study of immunology because the dynamics in the adaptive immune system of zebrafish are similar to that in higher animals. In this work, we built a multi-scale model to simulate the dynamics of B cells in the primary and secondary immune responses of zebrafish. We use this model to explain the reported correlation between VDJ usage of B cell repertoires in individual zebrafish. We use a delay ordinary differential equation (ODE) system to model the immune responses in the 6-month lifespan of a zebrafish. This mean field theory gives the number of high-affinity B cells as a function of time during an infection. The sequences of those B cells are then taken from a distribution calculated by a 'microscopic' random energy model. This generalized NK model shows that mature B cells specific to one antigen largely possess a single VDJ recombination. The model allows first-principle calculation of the probability, p, that two zebrafish responding to the same antigen will select the same VDJ recombination. This probability p increases with the B cell population size and the B cell selection intensity. The probability p decreases with the B cell hypermutation rate. The multi-scale model predicts correlations in the immune system of the zebrafish that are highly similar to that from experiment.

Mammalian cell models to advance our understanding of wound healing: a review.

PubMed

Vidmar, Jerneja; Chingwaru, Constance; Chingwaru, Walter

2017-04-01

Rapid and efficient healing of damaged tissue is critical for the restoration of tissue function and avoidance of tissue defects. Many in vitro cell models have been described for wound healing studies; however, the mechanisms that underlie the process, especially in chronic or complicated wounds, are not fully understood. The identification of cell culture systems that closely simulate the physiology of damaged tissue in vivo is necessary. We describe the cell culture models that have enhanced our understanding, this far, of the wound healing process or have been used in drug discovery. Cell cultures derived from the epithelium, including corneal, renal, intestinal (IEC-8 cells and IEC-6), skin epithelial cells (keratinocytes, fibroblasts, and multipotent mesenchymal stem cells), and the endothelium (human umbilical vein endothelial cells, primary mouse endothelial cells, endodermal stem cells, human mesenchymal stem cells, and corneal endothelial cells) have played a pivotal role toward our understanding of the mechanisms of wound healing. More studies are necessary to develop co-culture cell models which closely simulate the environment of a wound in vivo. Cell culture models are invaluable tools to promote our understanding of the mechanisms that regulate the wound healing process and provide a platform for drug discovery. Copyright © 2016 Elsevier Inc. All rights reserved.

Comparison of Perturbed Pathways in Two Different Cell Models for Parkinson's Disease with Structural Equation Model.

PubMed

Pepe, Daniele; Do, Jin Hwan

2015-12-16

Increasing evidence indicates that different morphological types of cell death coexist in the brain of patients with Parkinson's disease (PD), but the molecular explanation for this is still under investigation. In this study, we identified perturbed pathways in two different cell models for PD through the following procedures: (1) enrichment pathway analysis with differentially expressed genes and the Reactome pathway database, and (2) construction of the shortest path model for the enriched pathway and detection of significant shortest path model with fitting time-course microarray data of each PD cell model to structural equation model. Two PD cell models constructed by the same neurotoxin showed different perturbed pathways. That is, one showed perturbation of three Reactome pathways, including cellular senescence, chromatin modifying enzymes, and chromatin organization, while six modules within metabolism pathway represented perturbation in the other. This suggests that the activation of common upstream cell death pathways in PD may result in various down-stream processes, which might be associated with different morphological types of cell death. In addition, our results might provide molecular clues for coexistence of different morphological types of cell death in PD patients.

Cell-type-specific modelling of intracellular calcium signalling: a urothelial cell model.

PubMed

Appleby, Peter A; Shabir, Saqib; Southgate, Jennifer; Walker, Dawn

2013-09-06

Calcium signalling plays a central role in regulating a wide variety of cell processes. A number of calcium signalling models exist in the literature that are capable of reproducing a variety of experimentally observed calcium transients. These models have been used to examine in more detail the mechanisms underlying calcium transients, but very rarely has a model been directly linked to a particular cell type and experimentally verified. It is important to show that this can be achieved within the general theoretical framework adopted by these models. Here, we develop a framework designed specifically for modelling cytosolic calcium transients in urothelial cells. Where possible, we draw upon existing calcium signalling models, integrating descriptions of components known to be important in this cell type from a number of studies in the literature. We then add descriptions of several additional pathways that play a specific role in urothelial cell signalling, including an explicit ionic influx term and an active pumping mechanism that drives the cytosolic calcium concentration to a target equilibrium. The resulting one-pool model of endoplasmic reticulum (ER)-dependent calcium signalling relates the cytosolic, extracellular and ER calcium concentrations and can generate a wide range of calcium transients, including spikes, bursts, oscillations and sustained elevations in the cytosolic calcium concentration. Using single-variate robustness and multivariate sensitivity analyses, we quantify how varying each of the parameters of the model leads to changes in key features of the calcium transient, such as initial peak amplitude and the frequency of bursting or spiking, and in the transitions between bursting- and plateau-dominated modes. We also show that, novel to our urothelial cell model, the ionic and purinergic P2Y pathways make distinct contributions to the calcium transient. We then validate the model using human bladder epithelial cells grown in monolayer cell culture and show that the model robustly captures the key features of the experimental data in a way that is not possible using more generic calcium models from the literature.

Modeling the Chagas’ disease after stem cell transplantation

NASA Astrophysics Data System (ADS)

Galvão, Viviane; Miranda, José Garcia Vivas

2009-04-01

A recent model for Chagas’ disease after stem cell transplantation is extended for a three-dimensional multi-agent-based model. The computational model includes six different types of autonomous agents: inflammatory cell, fibrosis, cardiomyocyte, proinflammatory cytokine tumor necrosis factor- α, Trypanosoma cruzi, and bone marrow stem cell. Only fibrosis is fixed and the other types of agents can move randomly through the empty spaces using the three-dimensional Moore neighborhood. Bone marrow stem cells can promote apoptosis in inflammatory cells, fibrosis regression and can differentiate in cardiomyocyte. T. cruzi can increase the number of inflammatory cells. Inflammatory cells and tumor necrosis factor- α can increase the quantity of fibrosis. Our results were compared with experimental data giving a fairly fit and they suggest that the inflammatory cells are important for the development of fibrosis.

Random-Walk Model of Diffusion in Three Dimensions in Brain Extracellular Space: Comparison with Microfiberoptic Photobleaching Measurements

PubMed Central

Jin, Songwan; Zador, Zsolt; Verkman, A. S.

2008-01-01

Diffusion through the extracellular space (ECS) in brain is important in drug delivery, intercellular communication, and extracellular ionic buffering. The ECS comprises ∼20% of brain parenchymal volume and contains cell-cell gaps ∼50 nm. We developed a random-walk model to simulate macromolecule diffusion in brain ECS in three dimensions using realistic ECS dimensions. Model inputs included ECS volume fraction (α), cell size, cell-cell gap geometry, intercellular lake (expanded regions of brain ECS) dimensions, and molecular size of the diffusing solute. Model output was relative solute diffusion in water versus brain ECS (Do/D). Experimental Do/D for comparison with model predictions was measured using a microfiberoptic fluorescence photobleaching method involving stereotaxic insertion of a micron-size optical fiber into mouse brain. Do/D for the small solute calcein in different regions of brain was in the range 3.0–4.1, and increased with brain cell swelling after water intoxication. Do/D also increased with increasing size of the diffusing solute, particularly in deep brain nuclei. Simulations of measured Do/D using realistic α, cell size and cell-cell gap required the presence of intercellular lakes at multicell contact points, and the contact length of cell-cell gaps to be least 50-fold smaller than cell size. The model accurately predicted Do/D for different solute sizes. Also, the modeling showed unanticipated effects on Do/D of changing ECS and cell dimensions that implicated solute trapping by lakes. Our model establishes the geometric constraints to account quantitatively for the relatively modest slowing of solute and macromolecule diffusion in brain ECS. PMID:18469079

Random-walk model of diffusion in three dimensions in brain extracellular space: comparison with microfiberoptic photobleaching measurements.

PubMed

Jin, Songwan; Zador, Zsolt; Verkman, A S

2008-08-01

Diffusion through the extracellular space (ECS) in brain is important in drug delivery, intercellular communication, and extracellular ionic buffering. The ECS comprises approximately 20% of brain parenchymal volume and contains cell-cell gaps approximately 50 nm. We developed a random-walk model to simulate macromolecule diffusion in brain ECS in three dimensions using realistic ECS dimensions. Model inputs included ECS volume fraction (alpha), cell size, cell-cell gap geometry, intercellular lake (expanded regions of brain ECS) dimensions, and molecular size of the diffusing solute. Model output was relative solute diffusion in water versus brain ECS (D(o)/D). Experimental D(o)/D for comparison with model predictions was measured using a microfiberoptic fluorescence photobleaching method involving stereotaxic insertion of a micron-size optical fiber into mouse brain. D(o)/D for the small solute calcein in different regions of brain was in the range 3.0-4.1, and increased with brain cell swelling after water intoxication. D(o)/D also increased with increasing size of the diffusing solute, particularly in deep brain nuclei. Simulations of measured D(o)/D using realistic alpha, cell size and cell-cell gap required the presence of intercellular lakes at multicell contact points, and the contact length of cell-cell gaps to be least 50-fold smaller than cell size. The model accurately predicted D(o)/D for different solute sizes. Also, the modeling showed unanticipated effects on D(o)/D of changing ECS and cell dimensions that implicated solute trapping by lakes. Our model establishes the geometric constraints to account quantitatively for the relatively modest slowing of solute and macromolecule diffusion in brain ECS.

Comparing ESC and iPSC-Based Models for Human Genetic Disorders.

PubMed

Halevy, Tomer; Urbach, Achia

2014-10-24

Traditionally, human disorders were studied using animal models or somatic cells taken from patients. Such studies enabled the analysis of the molecular mechanisms of numerous disorders, and led to the discovery of new treatments. Yet, these systems are limited or even irrelevant in modeling multiple genetic diseases. The isolation of human embryonic stem cells (ESCs) from diseased blastocysts, the derivation of induced pluripotent stem cells (iPSCs) from patients' somatic cells, and the new technologies for genome editing of pluripotent stem cells have opened a new window of opportunities in the field of disease modeling, and enabled studying diseases that couldn't be modeled in the past. Importantly, despite the high similarity between ESCs and iPSCs, there are several fundamental differences between these cells, which have important implications regarding disease modeling. In this review we compare ESC-based models to iPSC-based models, and highlight the advantages and disadvantages of each system. We further suggest a roadmap for how to choose the optimal strategy to model each specific disorder.

An Improved Model for Nucleation-Limited Ice Formation in Living Cells during Freezing

PubMed Central

Zhao, Gang; He, Xiaoming

2014-01-01

Ice formation in living cells is a lethal event during freezing and its characterization is important to the development of optimal protocols for not only cryopreservation but also cryotherapy applications. Although the model for probability of ice formation (PIF) in cells developed by Toner et al. has been widely used to predict nucleation-limited intracellular ice formation (IIF), our data of freezing Hela cells suggest that this model could give misleading prediction of PIF when the maximum PIF in cells during freezing is less than 1 (PIF ranges from 0 to 1). We introduce a new model to overcome this problem by incorporating a critical cell volume to modify the Toner's original model. We further reveal that this critical cell volume is dependent on the mechanisms of ice nucleation in cells during freezing, i.e., surface-catalyzed nucleation (SCN) and volume-catalyzed nucleation (VCN). Taken together, the improved PIF model may be valuable for better understanding of the mechanisms of ice nucleation in cells during freezing and more accurate prediction of PIF for cryopreservation and cryotherapy applications. PMID:24852166

A medaka model of cancer allowing direct observation of transplanted tumor cells in vivo at a cellular-level resolution.

PubMed

Hasegawa, Sumitaka; Maruyama, Kouichi; Takenaka, Hikaru; Furukawa, Takako; Saga, Tsuneo

2009-08-18

The recent success with small fish as an animal model of cancer with the aid of fluorescence technique has attracted cancer modelers' attention because it would be possible to directly visualize tumor cells in vivo in real time. Here, we report a medaka model capable of allowing the observation of various cell behaviors of transplanted tumor cells, such as cell proliferation and metastasis, which were visualized easily in vivo. We established medaka melanoma (MM) cells stably expressing GFP and transplanted them into nonirradiated and irradiated medaka. The tumor cells were grown at the injection sites in medaka, and the spatiotemporal changes were visualized under a fluorescence stereoscopic microscope at a cellular-level resolution, and even at a single-cell level. Tumor dormancy and metastasis were also observed. Interestingly, in irradiated medaka, accelerated tumor growth and metastasis of the transplanted tumor cells were directly visualized. Our medaka model provides an opportunity to visualize in vivo tumor cells "as seen in a culture dish" and would be useful for in vivo tumor cell biology.

Modelling in conventional electroporation for model cell with organelles using COMSOL Multiphysics

NASA Astrophysics Data System (ADS)

Sulaeman, M. Y.; Widita, R.

2016-03-01

Conventional electroporation is a formation of pores in the membrane cell due to the external electric field applied to the cell. The purpose of creating pores in the cell using conventional electroporation are to increase the effectiveness of chemotherapy (electrochemotherapy) and to kill cancer tissue using irreversible electroporation. Modeling of electroporation phenomenon on a model cell had been done by using software COMSOL Multiphysics 4.3b with the applied external electric field with intensity at 1.1 kV/cm to find transmembrane voltage and pore density. It can be concluded from the results of potential distribution and transmembrane voltage, it show that pores formation only occurs in the membrane cells and it could not penetrate into inside the model cell so there is not pores formation in its organells.

simBio: a Java package for the development of detailed cell models.

PubMed

Sarai, Nobuaki; Matsuoka, Satoshi; Noma, Akinori

2006-01-01

Quantitative dynamic computer models, which integrate a variety of molecular functions into a cell model, provide a powerful tool to create and test working hypotheses. We have developed a new modeling tool, the simBio package (freely available from ), which can be used for constructing cell models, such as cardiac cells (the Kyoto model from Matsuoka et al., 2003, 2004 a, b, the LRd model from Faber and Rudy, 2000, and the Noble 98 model from Noble et al., 1998), epithelial cells (Strieter et al., 1990) and pancreatic beta cells (Magnus and Keizer, 1998). The simBio package is written in Java, uses XML and can solve ordinary differential equations. In an attempt to mimic biological functional structures, a cell model is, in simBio, composed of independent functional modules called Reactors, such as ion channels and the sarcoplasmic reticulum, and dynamic variables called Nodes, such as ion concentrations. The interactions between Reactors and Nodes are described by the graph theory and the resulting graph represents a blueprint of an intricate cellular system. Reactors are prepared in a hierarchical order, in analogy to the biological classification. Each Reactor can be composed or improved independently, and can easily be reused for different models. This way of building models, through the combination of various modules, is enabled through the use of object-oriented programming concepts. Thus, simBio is a straightforward system for the creation of a variety of cell models on a common database of functional modules.

Three-dimensional Model of Tissue and Heavy Ions Effects

NASA Technical Reports Server (NTRS)

Ponomarev, Artem L.; Sundaresan, Alamelu; Huff, Janice L.; Cucinotta, Francis A.

2007-01-01

A three-dimensional tissue model was incorporated into a new Monte Carlo algorithm that simulates passage of heavy ions in a tissue box . The tissue box was given as a realistic model of tissue based on confocal microscopy images. The action of heavy ions on the cellular matrix for 2- or 3-dimensional cases was simulated. Cells were modeled as a cell culture monolayer in one example, where the data were taken directly from microscopy (2-d cell matrix), and as a multi-layer obtained from confocal microscopy (3-d case). Image segmentation was used to identify cells with precise areas/volumes in an irradiated cell culture monolayer, and slices of tissue with many cell layers. The cells were then inserted into the model box of the simulated physical space pixel by pixel. In the case of modeled tissues (3-d), the tissue box had periodic boundary conditions imposed, which extrapolates the technique to macroscopic volumes of tissue. For the real tissue (3-d), specific spatial patterns for cell apoptosis and necrosis are expected. The cell patterns were modeled based on action cross sections for apoptosis and necrosis estimated from current experimental data. A spatial correlation function indicating a higher spatial concentration of damaged cells from heavy ions relative to the low-LET radiation cell damage pattern is presented. The spatial correlation effects among necrotic cells can help studying microlesions in organs, and probable effects of directionality of heavy ion radiation on epithelium and endothelium.

A multiphase model for tissue construct growth in a perfusion bioreactor.

PubMed

O'Dea, R D; Waters, S L; Byrne, H M

2010-06-01

The growth of a cell population within a rigid porous scaffold in a perfusion bioreactor is studied, using a three-phase continuum model of the type presented by Lemon et al. (2006, Multiphase modelling of tissue growth using the theory of mixtures. J. Math. Biol., 52, 571-594) to represent the cell population (and attendant extracellular matrix), culture medium and porous scaffold. The bioreactor system is modelled as a 2D channel containing the cell-seeded rigid porous scaffold (tissue construct) which is perfused with culture medium. The study concentrates on (i) the cell-cell and cell-scaffold interactions and (ii) the impact of mechanotransduction mechanisms on construct composition. A numerical and analytical analysis of the model equations is presented and, depending upon the relative importance of cell aggregation and repulsion, markedly different cell movement is revealed. Additionally, mechanotransduction effects due to cell density, pressure and shear stress-mediated tissue growth are shown to generate qualitative differences in the composition of the resulting construct. The results of our simulations indicate that this model formulation (in conjunction with appropriate experimental data) has the potential to provide a means of identifying the dominant regulatory stimuli in a cell population.

Dynamic self-organisation of haematopoiesis and (a)symmetric cell division.

PubMed

Måløy, Marthe; Måløy, Frode; Jakobsen, Per; Olav Brandsdal, Bjørn

2017-02-07

A model of haematopoiesis that links self-organisation with symmetric and asymmetric cell division is presented in this paper. It is assumed that all cell divisions are completely random events, and that the daughter cells resulting from symmetric and asymmetric stem cell divisions are, in general, phenotypically identical, and still, the haematopoietic system has the flexibility to self-renew, produce mature cells by differentiation, and regenerate undifferentiated and differentiated cells when necessary, due to self-organisation. As far as we know, no previous model implements symmetric and asymmetric division as the result of self-organisation. The model presented in this paper is inspired by experiments on the Drosophila germline stem cell, which imply that under normal conditions, the stem cells typically divide asymmetrically, whereas during regeneration, the rate of symmetric division increases. Moreover, the model can reproduce several of the results from experiments on female Safari cats. In particular, the model can explain why significant fluctuation in the phenotypes of haematopoietic cells was observed in some cats, when the haematopoietic system had reached normal population level after regeneration. To our knowledge, no previous model of haematopoiesis in Safari cats has captured this phenomenon. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Modelling cell motility and chemotaxis with evolving surface finite elements

PubMed Central

Elliott, Charles M.; Stinner, Björn; Venkataraman, Chandrasekhar

2012-01-01

We present a mathematical and a computational framework for the modelling of cell motility. The cell membrane is represented by an evolving surface, with the movement of the cell determined by the interaction of various forces that act normal to the surface. We consider external forces such as those that may arise owing to inhomogeneities in the medium and a pressure that constrains the enclosed volume, as well as internal forces that arise from the reaction of the cells' surface to stretching and bending. We also consider a protrusive force associated with a reaction–diffusion system (RDS) posed on the cell membrane, with cell polarization modelled by this surface RDS. The computational method is based on an evolving surface finite-element method. The general method can account for the large deformations that arise in cell motility and allows the simulation of cell migration in three dimensions. We illustrate applications of the proposed modelling framework and numerical method by reporting on numerical simulations of a model for eukaryotic chemotaxis and a model for the persistent movement of keratocytes in two and three space dimensions. Movies of the simulated cells can be obtained from http://homepages.warwick.ac.uk/∼maskae/CV_Warwick/Chemotaxis.html. PMID:22675164

Mechano-logical model of C. elegans germ line suggests feedback on the cell cycle

PubMed Central

Atwell, Kathryn; Qin, Zhao; Gavaghan, David; Kugler, Hillel; Hubbard, E. Jane Albert; Osborne, James M.

2015-01-01

The Caenorhabditis elegans germ line is an outstanding model system in which to study the control of cell division and differentiation. Although many of the molecules that regulate germ cell proliferation and fate decisions have been identified, how these signals interact with cellular dynamics and physical forces within the gonad remains poorly understood. We therefore developed a dynamic, 3D in silico model of the C. elegans germ line, incorporating both the mechanical interactions between cells and the decision-making processes within cells. Our model successfully reproduces key features of the germ line during development and adulthood, including a reasonable ovulation rate, correct sperm count, and appropriate organization of the germ line into stably maintained zones. The model highlights a previously overlooked way in which germ cell pressure may influence gonadogenesis, and also predicts that adult germ cells might be subject to mechanical feedback on the cell cycle akin to contact inhibition. We provide experimental data consistent with the latter hypothesis. Finally, we present cell trajectories and ancestry recorded over the course of a simulation. The novel approaches and software described here link mechanics and cellular decision-making, and are applicable to modeling other developmental and stem cell systems. PMID:26428008

Feathers and fins: non-mammalian models for hair cell regeneration.

PubMed

Brignull, Heather R; Raible, David W; Stone, Jennifer S

2009-06-24

Death of mechanosensory cells in the inner ear results in two profound disabilities: hearing loss and balance disorders. Although mammals lack the capacity to regenerate hair cells, recent studies in mice and other rodents have offered valuable insight into strategies for stimulating hair cell regeneration in mammals. Investigations of model organisms that retain the ability to form new hair cells after embryogenesis, such as fish and birds, are equally important and have provided clues as to the cellular and molecular mechanisms that may block hair cell regeneration in mammals. Here, we summarize studies on hair cell regeneration in the chicken and the zebrafish, discuss specific advantages of each model, and propose future directions for the use of non-mammalian models in understanding hair cell regeneration.

Human induced pluripotent stem cells: A disruptive innovation.

PubMed

De Vos, J; Bouckenheimer, J; Sansac, C; Lemaître, J-M; Assou, S

2016-01-01

This year (2016) will mark the 10th anniversary of the discovery of induced pluripotent stem cells (iPSCs). The finding that the transient expression of four transcription factors can radically remodel the epigenome, transcriptome and metabolome of differentiated cells and reprogram them into pluripotent stem cells has been a major and groundbreaking technological innovation. In this review, we discuss the major applications of this technology that we have grouped in nine categories: a model to study cell fate control; a model to study pluripotency; a model to study human development; a model to study human tissue and organ physiology; a model to study genetic diseases in a dish; a tool for cell rejuvenation; a source of cells for drug screening; a source of cells for regenerative medicine; a tool for the production of human organs in animals. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Surface tension and modeling of cellular intercalation during zebrafish gastrulation.

PubMed

Calmelet, Colette; Sepich, Diane

2010-04-01

In this paper we discuss a model of zebrafish embryo notochord development based on the effect of surface tension of cells at the boundaries. We study the process of interaction of mesodermal cells at the boundaries due to adhesion and cortical tension, resulting in cellular intercalation. From in vivo experiments, we obtain cell outlines of time-lapse images of cell movements during zebrafish embryo development. Using Cellular Potts Model, we calculate the total surface energy of the system of cells at different time intervals at cell contacts. We analyze the variations of total energy depending on nature of cell contacts. We demonstrate that our model can be viable by calculating the total surface energy value for experimentally observed configurations of cells and showing that in our model these configurations correspond to a decrease in total energy values in both two and three dimensions.

A stochastic spatiotemporal model of a response-regulator network in the Caulobacter crescentus cell cycle

NASA Astrophysics Data System (ADS)

Li, Fei; Subramanian, Kartik; Chen, Minghan; Tyson, John J.; Cao, Yang

2016-06-01

The asymmetric cell division cycle in Caulobacter crescentus is controlled by an elaborate molecular mechanism governing the production, activation and spatial localization of a host of interacting proteins. In previous work, we proposed a deterministic mathematical model for the spatiotemporal dynamics of six major regulatory proteins. In this paper, we study a stochastic version of the model, which takes into account molecular fluctuations of these regulatory proteins in space and time during early stages of the cell cycle of wild-type Caulobacter cells. We test the stochastic model with regard to experimental observations of increased variability of cycle time in cells depleted of the divJ gene product. The deterministic model predicts that overexpression of the divK gene blocks cell cycle progression in the stalked stage; however, stochastic simulations suggest that a small fraction of the mutants cells do complete the cell cycle normally.

Electrolytic hydrogen production: An analysis and review

NASA Technical Reports Server (NTRS)

Evangelista, J.; Phillips, B.; Gordon, L.

1975-01-01

The thermodynamics of water electrolysis cells is presented, followed by a review of current and future technology of commercial cells. The irreversibilities involved are analyzed and the resulting equations assembled into a computer simulation model of electrolysis cell efficiency. The model is tested by comparing predictions based on the model to actual commercial cell performance, and a parametric investigation of operating conditions is performed. Finally, the simulation model is applied to a study of electrolysis cell dynamics through consideration of an ideal pulsed electrolyzer.

Communication—indentation of Li-ion pouch cell: Effect of material homogenization on prediction of internal short circuit

DOE PAGES

Kumar, A.; Kalnaus, Sergiy; Simunovic, Srdjan; ...

2016-09-12

We performed finite element simulations of spherical indentation of Li-ion pouch cells. Our model fully resolves different layers in the cell. The results of the layer resolved models were compared to the models available in the literature that treat the cell as an equivalent homogenized continuum material. Simulations were carried out for different sizes of the spherical indenter. Here, we show that calibration of a failure criterion for the cell in the homogenized model depends on the indenter size, whereas in the layer-resoled model, such dependency is greatly diminished.

Compression simulations of plant tissue in 3D using a mass-spring system approach and discrete element method.

PubMed

Pieczywek, Piotr M; Zdunek, Artur

2017-10-18

A hybrid model based on a mass-spring system methodology coupled with the discrete element method (DEM) was implemented to simulate the deformation of cellular structures in 3D. Models of individual cells were constructed using the particles which cover the surfaces of cell walls and are interconnected in a triangle mesh network by viscoelastic springs. The spatial arrangement of the cells required to construct a virtual tissue was obtained using Poisson-disc sampling and Voronoi tessellation in 3D space. Three structural features were included in the model: viscoelastic material of cell walls, linearly elastic interior of the cells (simulating compressible liquid) and a gas phase in the intercellular spaces. The response of the models to an external load was demonstrated during quasi-static compression simulations. The sensitivity of the model was investigated at fixed compression parameters with variable tissue porosity, cell size and cell wall properties, such as thickness and Young's modulus, and a stiffness of the cell interior that simulated turgor pressure. The extent of the agreement between the simulation results and other models published is discussed. The model demonstrated the significant influence of tissue structure on micromechanical properties and allowed for the interpretation of the compression test results with respect to changes occurring in the structure of the virtual tissue. During compression virtual structures composed of smaller cells produced higher reaction forces and therefore they were stiffer than structures with large cells. The increase in the number of intercellular spaces (porosity) resulted in a decrease in reaction forces. The numerical model was capable of simulating the quasi-static compression experiment and reproducing the strain stiffening observed in experiment. Stress accumulation at the edges of the cell walls where three cells meet suggests that cell-to-cell debonding and crack propagation through the contact edge of neighboring cells is one of the most prevalent ways for tissue to rupture.

A model for proton-irradiated GaAs solar cells

NASA Technical Reports Server (NTRS)

Wilson, J. W.; Walker, G. H.; Outlaw, R. A.; Stock, L. V.

1982-01-01

A simple model for proton radiation damage in GaAs heteroface solar cells is developed. The model includes the effects of spatial nonuniformity of low energy proton damage. Agreement between the model and experimental proton damage data for GaAs heteroface solar cells is satisfactory. An extension of the model to include angular isotropy, as is appropriate for protons in space, is shown to result in significantly less cell damage than for normal proton incidence.

Characterization of biomechanical properties of cells through dielectrophoresis-based cell stretching and actin cytoskeleton modeling.

PubMed

Bai, Guohua; Li, Ying; Chu, Henry K; Wang, Kaiqun; Tan, Qiulin; Xiong, Jijun; Sun, Dong

2017-04-04

Cytoskeleton is a highly dynamic network that helps to maintain the rigidity of a cell, and the mechanical properties of a cell are closely related to many cellular functions. This paper presents a new method to probe and characterize cell mechanical properties through dielectrophoresis (DEP)-based cell stretching manipulation and actin cytoskeleton modeling. Leukemia NB4 cells were used as cell line, and changes in their biological properties were examined after chemotherapy treatment with doxorubicin (DOX). DEP-integrated microfluidic chip was utilized as a low-cost and efficient tool to study the deformability of cells. DEP forces used in cell stretching were first evaluated through computer simulation, and the results were compared with modeling equations and with the results of optical stretching (OT) experiments. Structural parameters were then extracted by fitting the experimental data into the actin cytoskeleton model, and the underlying mechanical properties of the cells were subsequently characterized. The DEP forces generated under different voltage inputs were calculated and the results from different approaches demonstrate good approximations to the force estimation. Both DEP and OT stretching experiments confirmed that DOX-treated NB4 cells were stiffer than the untreated cells. The structural parameters extracted from the model and the confocal images indicated significant change in actin network after DOX treatment. The proposed DEP method combined with actin cytoskeleton modeling is a simple engineering tool to characterize the mechanical properties of cells.

Determination of morphological parameters of biological cells by analysis of scattered-light distributions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Burger, D.E.

1979-11-01

The extraction of morphological parameters from biological cells by analysis of light-scatter patterns is described. A light-scattering measurement system has been designed and constructed that allows one to visually examine and photographically record biological cells or cell models and measure the light-scatter pattern of an individual cell or cell model. Using a laser or conventional illumination, the imaging system consists of a modified microscope with a 35 mm camera attached to record the cell image or light-scatter pattern. Models of biological cells were fabricated. The dynamic range and angular distributions of light scattered from these models was compared to calculatedmore » distributions. Spectrum analysis techniques applied on the light-scatter data give the sought after morphological cell parameters. These results compared favorably to shape parameters of the fabricated cell models confirming the mathematical model procedure. For nucleated biological material, correct nuclear and cell eccentricity as well as the nuclear and cytoplasmic diameters were determined. A method for comparing the flow equivalent of nuclear and cytoplasmic size to the actual dimensions is shown. This light-scattering experiment provides baseline information for automated cytology. In its present application, it involves correlating average size as measured in flow cytology to the actual dimensions determined from this technique. (ERB)« less

Two-stage model of radon-induced malignant lung tumors in rats: effects of cell killing

NASA Technical Reports Server (NTRS)

Luebeck, E. G.; Curtis, S. B.; Cross, F. T.; Moolgavkar, S. H.

1996-01-01

A two-stage stochastic model of carcinogenesis is used to analyze lung tumor incidence in 3750 rats exposed to varying regimens of radon carried on a constant-concentration uranium ore dust aerosol. New to this analysis is the parameterization of the model such that cell killing by the alpha particles could be included. The model contains parameters characterizing the rate of the first mutation, the net proliferation rate of initiated cells, the ratio of the rates of cell loss (cell killing plus differentiation) and cell division, and the lag time between the appearance of the first malignant cell and the tumor. Data analysis was by standard maximum likelihood estimation techniques. Results indicate that the rate of the first mutation is dependent on radon and consistent with in vitro rates measured experimentally, and that the rate of the second mutation is not dependent on radon. An initial sharp rise in the net proliferation rate of initiated cell was found with increasing exposure rate (denoted model I), which leads to an unrealistically high cell-killing coefficient. A second model (model II) was studied, in which the initial rise was attributed to promotion via a step function, implying that it is due not to radon but to the uranium ore dust. This model resulted in values for the cell-killing coefficient consistent with those found for in vitro cells. An "inverse dose-rate" effect is seen, i.e. an increase in the lifetime probability of tumor with a decrease in exposure rate. This is attributed in large part to promotion of intermediate lesions. Since model II is preferable on biological grounds (it yields a plausible cell-killing coefficient), such as uranium ore dust. This analysis presents evidence that a two-stage model describes the data adequately and generates hypotheses regarding the mechanism of radon-induced carcinogenesis.

A hybrid mathematical model of solid tumour invasion: the importance of cell adhesion.

PubMed

Anderson, Alexander R A

2005-06-01

In this paper we present a hybrid mathematical model of the invasion of healthy tissue by a solid tumour. In particular we consider early vascular growth, just after angiogenesis has occurred. We examine how the geometry of the growing tumour is affected by tumour cell heterogeneity caused by genetic mutations. As the tumour grows, mutations occur leading to a heterogeneous tumour cell population with some cells having a greater ability to migrate, proliferate or degrade the surrounding tissue. All of these cell properties are closely controlled by cell-cell and cell-matrix interactions and as such the physical geometry of the whole tumour will be dependent on these individual cell interactions. The hybrid model we develop focuses on four key variables implicated in the invasion process: tumour cells, host tissue (extracellular matrix), matrix-degradative enzymes and oxygen. The model is considered to be hybrid since the latter three variables are continuous (i.e. concentrations) and the tumour cells are discrete (i.e. individuals). With this hybrid model we examine how individual-based cell interactions (with one another and the matrix) can affect the tumour shape and discuss which of these interactions is perhaps most crucial in influencing the tumour's final structure.

Flocking Transition in Confluent Tissues

NASA Astrophysics Data System (ADS)

Paoluzzi, Matteo; Giavazzi, Fabio; Macchi, Marta; Scita, Giorgio; Cerbino, Roberto; Manning, Lisa; Marchetti, Cristina

The emerging of collective migration in biological tissues plays a pivotal role in embryonic morphogenesis, wound healing and cancer invasion. While many aspects of single cell movements are well established, the mechanisms leading to coherent displacements of cohesive cell groups are still poorly understood. Some of us recently proposed a Self-Propelled Voronoi (SPV) model of dense tissues that combines self-propelled particle models and vertex models of confluent cell layers and exhibits a liquid-solid transition as a function of cell shape and cell motility. We now examine the role of cell polarization on collective cell dynamics by introducing an orientation mechanism that aligns cell polarization with local cell motility. The model predicts a density-independent flocking transition tuned by the strength of the aligning interaction, with both solid and liquid flocking states existing in different regions of parameter space. MP and MCM were supported by the Simons Foundation Targeted Grant in the Mathematical Modeling of Living Systems Number: 342354 and by the Syracuse Soft Matter Program.

Electrical coupling in ensembles of nonexcitable cells: modeling the spatial map of single cell potentials.

PubMed

Cervera, Javier; Manzanares, Jose Antonio; Mafe, Salvador

2015-02-19

We analyze the coupling of model nonexcitable (non-neural) cells assuming that the cell membrane potential is the basic individual property. We obtain this potential on the basis of the inward and outward rectifying voltage-gated channels characteristic of cell membranes. We concentrate on the electrical coupling of a cell ensemble rather than on the biochemical and mechanical characteristics of the individual cells, obtain the map of single cell potentials using simple assumptions, and suggest procedures to collectively modify this spatial map. The response of the cell ensemble to an external perturbation and the consequences of cell isolation, heterogeneity, and ensemble size are also analyzed. The results suggest that simple coupling mechanisms can be significant for the biophysical chemistry of model biomolecular ensembles. In particular, the spatiotemporal map of single cell potentials should be relevant for the uptake and distribution of charged nanoparticles over model cell ensembles and the collective properties of droplet networks incorporating protein ion channels inserted in lipid bilayers.

Three-dimensional Myoblast Aggregates--Effects of Modeled Microgravity

NASA Technical Reports Server (NTRS)

Byerly, Diane; Sognier, M. A.; Marquette, M. L.

2006-01-01

The overall objective of these studies is to elucidate the molecular and cellular alterations that contribute to muscle atrophy in astronauts caused by exposure to microgravity conditions in space. To accomplish this, a three-dimensional model test system was developed using mouse myoblast cells (C2C12). Myoblast cells were grown as three-dimensional aggregates (without scaffolding or other solid support structures) in both modeled microgravity (Rotary Cell Culture System, Synthecon, Inc.) and at unit gravity in coated Petri dishes. Evaluation of H&E stained thin sections of the aggregates revealed the absence of any necrosis. Confocal microscopy evaluations of cells stained with the Live/Dead assay (Molecular Probes) confirmed that viable cells were present throughout the aggregates with an average of only three dead cells observed per aggregate. Preliminary results from gene array analysis (Affymetrix chip U74Av2) showed that approximately 14% of the genes were down regulated (decreased more than 3 fold) and 4% were upregulated in cells exposed to modeled microgravity for 12 hours compared to unit gravity controls. Additional studies using fluorescent phallacidin revealed a decrease in F-actin in the cells exposed to modeled microgravity compared to unit gravity. Myoblast cells grown as aggregates in modeled microgravity exhibited spontaneous differentiation into syncitia while no differentiation was seen in the unit gravity controls. These studies show that 1)the model test system developed is suitable for assessing cellular and molecular alterations in myoblasts; 2) gene expression alterations occur rapidly (within 12 hours) following exposure to modeled microgravity; and 3) modeled microgravity conditions stimulated myoblast cell differentiation. Achieving a greater understanding of the molecular alterations leading to muscle atrophy will eventually enable the development of cell-based countermeasures, which may be valuable for treatment of muscle diseases on Earth and future space explorations.

A polynomial based model for cell fate prediction in human diseases.

PubMed

Ma, Lichun; Zheng, Jie

2017-12-21

Cell fate regulation directly affects tissue homeostasis and human health. Research on cell fate decision sheds light on key regulators, facilitates understanding the mechanisms, and suggests novel strategies to treat human diseases that are related to abnormal cell development. In this study, we proposed a polynomial based model to predict cell fate. This model was derived from Taylor series. As a case study, gene expression data of pancreatic cells were adopted to test and verify the model. As numerous features (genes) are available, we employed two kinds of feature selection methods, i.e. correlation based and apoptosis pathway based. Then polynomials of different degrees were used to refine the cell fate prediction function. 10-fold cross-validation was carried out to evaluate the performance of our model. In addition, we analyzed the stability of the resultant cell fate prediction model by evaluating the ranges of the parameters, as well as assessing the variances of the predicted values at randomly selected points. Results show that, within both the two considered gene selection methods, the prediction accuracies of polynomials of different degrees show little differences. Interestingly, the linear polynomial (degree 1 polynomial) is more stable than others. When comparing the linear polynomials based on the two gene selection methods, it shows that although the accuracy of the linear polynomial that uses correlation analysis outcomes is a little higher (achieves 86.62%), the one within genes of the apoptosis pathway is much more stable. Considering both the prediction accuracy and the stability of polynomial models of different degrees, the linear model is a preferred choice for cell fate prediction with gene expression data of pancreatic cells. The presented cell fate prediction model can be extended to other cells, which may be important for basic research as well as clinical study of cell development related diseases.

Systems Modelling and the Development of Coherent Understanding of Cell Biology

ERIC Educational Resources Information Center

Verhoeff, Roald P.; Waarlo, Arend Jan; Boersma, Kerst Th.

2008-01-01

This article reports on educational design research concerning a learning and teaching strategy for cell biology in upper-secondary education introducing "systems modelling" as a key competence. The strategy consists of four modelling phases in which students subsequently develop models of free-living cells, a general two-dimensional model of…

Applying the cell-based coagulation model in the management of critical bleeding.

PubMed

Ho, K M; Pavey, W

2017-03-01

The cell-based coagulation model was proposed 15 years ago, yet has not been applied commonly in the management of critical bleeding. Nevertheless, this alternative model may better explain the physiological basis of current coagulation management during critical bleeding. In this article we describe the limitations of the traditional coagulation protein cascade and standard coagulation tests, and explain the potential advantages of applying the cell-based model in current coagulation management strategies. The cell-based coagulation model builds on the traditional coagulation model and explains many recent clinical observations and research findings related to critical bleeding unexplained by the traditional model, including the encouraging results of using empirical 1:1:1 fresh frozen plasma:platelets:red blood cells transfusion strategy, and the use of viscoelastic and platelet function tests in patients with critical bleeding. From a practical perspective, applying the cell-based coagulation model also explains why new direct oral anticoagulants are effective systemic anticoagulants even without affecting activated partial thromboplastin time or the International Normalized Ratio in a dose-related fashion. The cell-based coagulation model represents the most cohesive scientific framework on which we can understand and manage coagulation during critical bleeding.

Metabolic design of macroscopic bioreaction models: application to Chinese hamster ovary cells.

PubMed

Provost, A; Bastin, G; Agathos, S N; Schneider, Y-J

2006-12-01

The aim of this paper is to present a systematic methodology to design macroscopic bioreaction models for cell cultures based upon metabolic networks. The cell culture is seen as a succession of phases. During each phase, a metabolic network represents the set of reactions occurring in the cell. Then, through the use of the elementary flux modes, these metabolic networks are used to derive macroscopic bioreactions linking the extracellular substrates and products. On this basis, as many separate models are obtained as there are phases. Then, a complete model is obtained by smoothly switching from model to model. This is illustrated with batch cultures of Chinese hamster ovary cells.

Development of a statistical model for cervical cancer cell death with irreversible electroporation in vitro.

PubMed

Yang, Yongji; Moser, Michael A J; Zhang, Edwin; Zhang, Wenjun; Zhang, Bing

2018-01-01

The aim of this study was to develop a statistical model for cell death by irreversible electroporation (IRE) and to show that the statistic model is more accurate than the electric field threshold model in the literature using cervical cancer cells in vitro. HeLa cell line was cultured and treated with different IRE protocols in order to obtain data for modeling the statistical relationship between the cell death and pulse-setting parameters. In total, 340 in vitro experiments were performed with a commercial IRE pulse system, including a pulse generator and an electric cuvette. Trypan blue staining technique was used to evaluate cell death after 4 hours of incubation following IRE treatment. Peleg-Fermi model was used in the study to build the statistical relationship using the cell viability data obtained from the in vitro experiments. A finite element model of IRE for the electric field distribution was also built. Comparison of ablation zones between the statistical model and electric threshold model (drawn from the finite element model) was used to show the accuracy of the proposed statistical model in the description of the ablation zone and its applicability in different pulse-setting parameters. The statistical models describing the relationships between HeLa cell death and pulse length and the number of pulses, respectively, were built. The values of the curve fitting parameters were obtained using the Peleg-Fermi model for the treatment of cervical cancer with IRE. The difference in the ablation zone between the statistical model and the electric threshold model was also illustrated to show the accuracy of the proposed statistical model in the representation of ablation zone in IRE. This study concluded that: (1) the proposed statistical model accurately described the ablation zone of IRE with cervical cancer cells, and was more accurate compared with the electric field model; (2) the proposed statistical model was able to estimate the value of electric field threshold for the computer simulation of IRE in the treatment of cervical cancer; and (3) the proposed statistical model was able to express the change in ablation zone with the change in pulse-setting parameters.

Beta-Poisson model for single-cell RNA-seq data analyses.

PubMed

Vu, Trung Nghia; Wills, Quin F; Kalari, Krishna R; Niu, Nifang; Wang, Liewei; Rantalainen, Mattias; Pawitan, Yudi

2016-07-15

Single-cell RNA-sequencing technology allows detection of gene expression at the single-cell level. One typical feature of the data is a bimodality in the cellular distribution even for highly expressed genes, primarily caused by a proportion of non-expressing cells. The standard and the over-dispersed gamma-Poisson models that are commonly used in bulk-cell RNA-sequencing are not able to capture this property. We introduce a beta-Poisson mixture model that can capture the bimodality of the single-cell gene expression distribution. We further integrate the model into the generalized linear model framework in order to perform differential expression analyses. The whole analytical procedure is called BPSC. The results from several real single-cell RNA-seq datasets indicate that ∼90% of the transcripts are well characterized by the beta-Poisson model; the model-fit from BPSC is better than the fit of the standard gamma-Poisson model in > 80% of the transcripts. Moreover, in differential expression analyses of simulated and real datasets, BPSC performs well against edgeR, a conventional method widely used in bulk-cell RNA-sequencing data, and against scde and MAST, two recent methods specifically designed for single-cell RNA-seq data. An R package BPSC for model fitting and differential expression analyses of single-cell RNA-seq data is available under GPL-3 license at https://github.com/nghiavtr/BPSC CONTACT: yudi.pawitan@ki.se or mattias.rantalainen@ki.se Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

UML as a cell and biochemistry modeling language.

PubMed

Webb, Ken; White, Tony

2005-06-01

The systems biology community is building increasingly complex models and simulations of cells and other biological entities, and are beginning to look at alternatives to traditional representations such as those provided by ordinary differential equations (ODE). The lessons learned over the years by the software development community in designing and building increasingly complex telecommunication and other commercial real-time reactive systems, can be advantageously applied to the problems of modeling in the biology domain. Making use of the object-oriented (OO) paradigm, the unified modeling language (UML) and Real-Time Object-Oriented Modeling (ROOM) visual formalisms, and the Rational Rose RealTime (RRT) visual modeling tool, we describe a multi-step process we have used to construct top-down models of cells and cell aggregates. The simple example model described in this paper includes membranes with lipid bilayers, multiple compartments including a variable number of mitochondria, substrate molecules, enzymes with reaction rules, and metabolic pathways. We demonstrate the relevance of abstraction, reuse, objects, classes, component and inheritance hierarchies, multiplicity, visual modeling, and other current software development best practices. We show how it is possible to start with a direct diagrammatic representation of a biological structure such as a cell, using terminology familiar to biologists, and by following a process of gradually adding more and more detail, arrive at a system with structure and behavior of arbitrary complexity that can run and be observed on a computer. We discuss our CellAK (Cell Assembly Kit) approach in terms of features found in SBML, CellML, E-CELL, Gepasi, Jarnac, StochSim, Virtual Cell, and membrane computing systems.

Statistical Modeling of Single Target Cell Encapsulation

PubMed Central

Moon, SangJun; Ceyhan, Elvan; Gurkan, Umut Atakan; Demirci, Utkan

2011-01-01

High throughput drop-on-demand systems for separation and encapsulation of individual target cells from heterogeneous mixtures of multiple cell types is an emerging method in biotechnology that has broad applications in tissue engineering and regenerative medicine, genomics, and cryobiology. However, cell encapsulation in droplets is a random process that is hard to control. Statistical models can provide an understanding of the underlying processes and estimation of the relevant parameters, and enable reliable and repeatable control over the encapsulation of cells in droplets during the isolation process with high confidence level. We have modeled and experimentally verified a microdroplet-based cell encapsulation process for various combinations of cell loading and target cell concentrations. Here, we explain theoretically and validate experimentally a model to isolate and pattern single target cells from heterogeneous mixtures without using complex peripheral systems. PMID:21814548

Predicting the impact of combined therapies on myeloma cell growth using a hybrid multi-scale agent-based model.

PubMed

Ji, Zhiwei; Su, Jing; Wu, Dan; Peng, Huiming; Zhao, Weiling; Nlong Zhao, Brian; Zhou, Xiaobo

2017-01-31

Multiple myeloma is a malignant still incurable plasma cell disorder. This is due to refractory disease relapse, immune impairment, and development of multi-drug resistance. The growth of malignant plasma cells is dependent on the bone marrow (BM) microenvironment and evasion of the host's anti-tumor immune response. Hence, we hypothesized that targeting tumor-stromal cell interaction and endogenous immune system in BM will potentially improve the response of multiple myeloma (MM). Therefore, we proposed a computational simulation of the myeloma development in the complicated microenvironment which includes immune cell components and bone marrow stromal cells and predicted the effects of combined treatment with multi-drugs on myeloma cell growth. We constructed a hybrid multi-scale agent-based model (HABM) that combines an ODE system and Agent-based model (ABM). The ODEs was used for modeling the dynamic changes of intracellular signal transductions and ABM for modeling the cell-cell interactions between stromal cells, tumor, and immune components in the BM. This model simulated myeloma growth in the bone marrow microenvironment and revealed the important role of immune system in this process. The predicted outcomes were consistent with the experimental observations from previous studies. Moreover, we applied this model to predict the treatment effects of three key therapeutic drugs used for MM, and found that the combination of these three drugs potentially suppress the growth of myeloma cells and reactivate the immune response. In summary, the proposed model may serve as a novel computational platform for simulating the formation of MM and evaluating the treatment response of MM to multiple drugs.

A mechanistic model for bromodeoxyuridine dilution naturally explains labelling data of self-renewing T cell populations

PubMed Central

Ganusov, Vitaly V.; De Boer, Rob J.

2013-01-01

Bromodeoxyuridine (BrdU) is widely used in immunology to detect cell division, and several mathematical models have been proposed to estimate proliferation and death rates of lymphocytes from BrdU labelling and de-labelling curves. One problem in interpreting BrdU data is explaining the de-labelling curves. Because shortly after label withdrawal, BrdU+ cells are expected to divide into BrdU+ daughter cells, one would expect a flat down-slope. As for many cell types, the fraction of BrdU+ cells decreases during de-labelling, previous mathematical models had to make debatable assumptions to be able to account for the data. We develop a mechanistic model tracking the number of divisions that each cell has undergone in the presence and absence of BrdU, and allow cells to accumulate and dilute their BrdU content. From the same mechanistic model, one can naturally derive expressions for the mean BrdU content (MBC) of all cells, or the MBC of the BrdU+ subset, which is related to the mean fluorescence intensity of BrdU that can be measured in experiments. The model is extended to include subpopulations with different rates of division and death (i.e. kinetic heterogeneity). We fit the extended model to previously published BrdU data from memory T lymphocytes in simian immunodeficiency virus-infected and uninfected macaques, and find that the model describes the data with at least the same quality as previous models. Because the same model predicts a modest decline in the MBC of BrdU+ cells, which is consistent with experimental observations, BrdU dilution seems a natural explanation for the observed down-slopes in self-renewing populations. PMID:23034350

Biological Effects of Protracted Exposure to Ionizing Radiation: Review, Analysis, and Model Development

DTIC Science & Technology

1991-11-01

dynamics, physiological changes, morphologi- cal changes, cell/tissue damage and recovery mechanisms, and existing radiobiological injury and recovery...humans and the ferret. The gut injury model (GIM) is a three-compartment hierarchial- type tissue model to simulate radiation-induced changes in the...Prodromal Symptoms Diarrhea Gastrointestinal Symptoms Dose Rate Cell Survival Intestinal Injury Fatigability Cell Damage Cell Repair Cell Proliferation

A Theoretical Model of Jigsaw-Puzzle Pattern Formation by Plant Leaf Epidermal Cells.

PubMed

Higaki, Takumi; Kutsuna, Natsumaro; Akita, Kae; Takigawa-Imamura, Hisako; Yoshimura, Kenji; Miura, Takashi

2016-04-01

Plant leaf epidermal cells exhibit a jigsaw puzzle-like pattern that is generated by interdigitation of the cell wall during leaf development. The contribution of two ROP GTPases, ROP2 and ROP6, to the cytoskeletal dynamics that regulate epidermal cell wall interdigitation has already been examined; however, how interactions between these molecules result in pattern formation remains to be elucidated. Here, we propose a simple interface equation model that incorporates both the cell wall remodeling activity of ROP GTPases and the diffusible signaling molecules by which they are regulated. This model successfully reproduces pattern formation observed in vivo, and explains the counterintuitive experimental results of decreased cellulose production and increased thickness. Our model also reproduces the dynamics of three-way cell wall junctions. Therefore, this model provides a possible mechanism for cell wall interdigitation formation in vivo.

Dental pulp stem cells promote regeneration of damaged neuron cells on the cellular model of Alzheimer's disease.

PubMed

Wang, Feixiang; Jia, Yali; Liu, Jiajing; Zhai, Jinglei; Cao, Ning; Yue, Wen; He, Huixia; Pei, Xuetao

2017-06-01

Alzheimer's disease (AD) is an incurable neurodegenerative disease and many types of stem cells have been used in AD therapy with some favorable effects. In this study, we investigated the potential therapeutical effects of human dental pulp stem cells (hDPSCs) on AD cellular model which established by okadaic acid (OA)-induced damage to human neuroblastoma cell line, SH-SY5Y, in vitro for 24 h. After confirmed the AD cellular model, the cells were co-culture with hDPSCs by transwell co-culture system till 24 h for treatment. Then the cytomorphology of the hDPSCs-treated cells were found to restore gradually with re-elongation of retracted dendrites. Meanwhile, Cell Counting Kit-8 assay and Hoechst 33258 staining showed that hDPSCs caused significant increase in the viability and decrease in apoptosis of the model cells, respectively. Observation of DiI labeling also exhibited the prolongation dendrites in hDPSCs-treated cells which were obviously different from the retraction dendrites in AD model cells. Furthermore, specific staining of α-tubulin and F-actin demonstrated that the hDPSCs-treated cells had the morphology of restored neurons, with elongated dendrites, densely arranged microfilaments, and thickened microtubular fibrils. In addition, results from western blotting revealed that phosphorylation at Ser 396 of Tau protein was significantly suppressed by adding of hDPSCs. These results indicate that hDPSCs may promote regeneration of damaged neuron cells in vitro model of AD and may serve as a useful cell source for treatment of AD. © 2017 International Federation for Cell Biology.

Spin glass model for dynamics of cell reprogramming

NASA Astrophysics Data System (ADS)

Pusuluri, Sai Teja; Lang, Alex H.; Mehta, Pankaj; Castillo, Horacio E.

2015-03-01

Recent experiments show that differentiated cells can be reprogrammed to become pluripotent stem cells. The possible cell fates can be modeled as attractors in a dynamical system, the ``epigenetic landscape.'' Both cellular differentiation and reprogramming can be described in the landscape picture as motion from one attractor to another attractor. We perform Monte Carlo simulations in a simple model of the landscape. This model is based on spin glass theory and it can be used to construct a simulated epigenetic landscape starting from the experimental genomic data. We re-analyse data from several cell reprogramming experiments and compare with our simulation results. We find that the model can reproduce some of the main features of the dynamics of cell reprogramming.

A model for compression-weakening materials and the elastic fields due to contractile cells

NASA Astrophysics Data System (ADS)

Rosakis, Phoebus; Notbohm, Jacob; Ravichandran, Guruswami

2015-12-01

We construct a homogeneous, nonlinear elastic constitutive law that models aspects of the mechanical behavior of inhomogeneous fibrin networks. Fibers in such networks buckle when in compression. We model this as a loss of stiffness in compression in the stress-strain relations of the homogeneous constitutive model. Problems that model a contracting biological cell in a finite matrix are solved. It is found that matrix displacements and stresses induced by cell contraction decay slower (with distance from the cell) in a compression weakening material than linear elasticity would predict. This points toward a mechanism for long-range cell mechanosensing. In contrast, an expanding cell would induce displacements that decay faster than in a linear elastic matrix.

A mathematical model of a lithium/thionyl chloride primary cell

NASA Technical Reports Server (NTRS)

Evans, T. I.; Nguyen, T. V.; White, R. E.

1987-01-01

A 1-D mathematical model for the lithium/thionyl chloride primary cell was developed to investigate methods of improving its performance and safety. The model includes many of the components of a typical lithium/thionyl chloride cell such as the porous lithium chloride film which forms on the lithium anode surface. The governing equations are formulated from fundamental conservation laws using porous electrode theory and concentrated solution theory. The model is used to predict 1-D, time dependent profiles of concentration, porosity, current, and potential as well as cell temperature and voltage. When a certain discharge rate is required, the model can be used to determine the design criteria and operating variables which yield high cell capacities. Model predictions can be used to establish operational and design limits within which the thermal runaway problem, inherent in these cells, can be avoided.

Simulation analysis of receptive-field size of retinal horizontal cells by ionic current model.

PubMed

Aoyama, Toshihiro; Kamiyama, Yoshimi; Usui, Shiro

2005-01-01

The size of the receptive field of retinal horizontal cells changes with the state of dark/light adaptation. We have used a mathematical model to determine how changes in the membrane conductance affect the receptive-field properties of horizontal cells. We first modeled the nonlinear membrane properties of horizontal cells based on ionic current mechanisms. The dissociated horizontal cell model reproduced the voltage-current (V-I) relationships for various extracellular glutamate concentrations measured in electrophysiological studies. Second, a network horizontal cell model was also described, and it reproduced the V-I relationship observed in vivo. The network model showed a bell-shaped relationship between the receptive-field size and constant glutamate concentration. The simulated results suggest that the calcium current is a candidate for the bell-shaped length constant relationship.

Stromal–epithelial cell interactions and alteration of branching morphogenesis in macromastic mammary glands

PubMed Central

Zhong, Aimei; Wang, Guohua; Yang, Jie; Xu, Qijun; Yuan, Quan; Yang, Yanqing; Xia, Yun; Guo, Ke; Horch, Raymund E; Sun, Jiaming

2014-01-01

True macromastia is a rare but disabling condition characterized by massive breast growth. The aetiology and pathogenic mechanisms for this disorder remain largely unexplored because of the lack of in vivo or in vitro models. Previous studies suggested that regulation of epithelial cell growth and development by oestrogen was dependent on paracrine growth factors from the stroma. In this study, a co-culture model containing epithelial and stromal cells was used to investigate the interactions of these cells in macromastia. Epithelial cell proliferation and branching morphogenesis were measured to assess the effect of macromastic stromal cells on epithelial cells. We analysed the cytokines secreted by stromal cells and identified molecules that were critical for effects on epithelial cells. Our results indicated a significant increase in cell proliferation and branching morphogenesis of macromastic and non-macromastic epithelial cells when co-cultured with macromastic stromal cells or in conditioned medium from macromastic stromal cells. Hepatocyte growth factor (HGF) is a key factor in epithelial–stromal interactions of macromastia-derived cell cultures. Blockade of HGF with neutralizing antibodies dramatically attenuated epithelial cell proliferation in conditioned medium from macromastic stromal cells. The epithelial–stromal cell co-culture model demonstrated reliability for studying interactions of mammary stromal and epithelial cells in macromastia. In this model, HGF secreted by macromastic stromal cells was found to play an important role in modifying the behaviour of co-cultured epithelial cells. This model allows further studies to investigate basic cellular and molecular mechanisms in tissue from patients with true breast hypertrophy. PMID:24720804

Approaches for Analyzing the Roles of Mast Cells and Their Proteases In Vivo

PubMed Central

Galli, Stephen J.; Tsai, Mindy; Marichal, Thomas; Tchougounova, Elena; Reber, Laurent L.; Pejler, Gunnar

2016-01-01

The roles of mast cells in health and disease remain incompletely understood. While the evidence that mast cells are critical effector cells in IgE-dependent anaphylaxis and other acute IgE-mediated allergic reactions seems unassailable, studies employing various mice deficient in mast cells or mast cell-associated proteases have yielded divergent conclusions about the roles of mast cells or their proteases in certain other immunological responses. Such “controversial” results call into question the relative utility of various older versus newer approaches to ascertain the roles of mast cells and mast cell proteases in vivo. This review discusses how both older and more recent mouse models have been used to investigate the functions of mast cells and their proteases in health and disease. We particularly focus on settings in which divergent conclusions about the importance of mast cells and their proteases have been supported by studies that employed different models of mast cell or mast cell protease deficiency. We think that two major conclusions can be drawn from such findings: (1) no matter which models of mast cell or mast cell protease deficiency one employs, the conclusions drawn from the experiments always should take into account the potential limitations of the models (particularly abnormalities affecting cell types other than mast cells) and (2) even when analyzing a biological response using a single model of mast cell or mast cell protease deficiency, details of experimental design are critical in efforts to define those conditions under which important contributions of mast cells or their proteases can be identified. PMID:25727288

Bubbly vertex dynamics: A dynamical and geometrical model for epithelial tissues with curved cell shapes

NASA Astrophysics Data System (ADS)

Ishimoto, Yukitaka; Morishita, Yoshihiro

2014-11-01

In order to describe two-dimensionally packed cells in epithelial tissues both mathematically and physically, there have been developed several sorts of geometrical models, such as the vertex model, the finite element model, the cell-centered model, and the cellular Potts model. So far, in any case, pressures have not neatly been dealt with and the curvatures of the cell boundaries have been even omitted through their approximations. We focus on these quantities and formulate them in the vertex model. Thus, a model with the curvatures is constructed, and its algorithm for simulation is provided. The possible extensions and applications of this model are also discussed.

A coupled diffusion-fluid pressure model to predict cell density distribution for cells encapsulated in a porous hydrogel scaffold under mechanical loading.

PubMed

Zhao, Feihu; Vaughan, Ted J; Mc Garrigle, Myles J; McNamara, Laoise M

2017-10-01

Tissue formation within tissue engineering (TE) scaffolds is preceded by growth of the cells throughout the scaffold volume and attachment of cells to the scaffold substrate. It is known that mechanical stimulation, in the form of fluid perfusion or mechanical strain, enhances cell differentiation and overall tissue formation. However, due to the complex multi-physics environment of cells within TE scaffolds, cell transport under mechanical stimulation is not fully understood. Therefore, in this study, we have developed a coupled multiphysics model to predict cell density distribution in a TE scaffold. In this model, cell transport is modelled as a thermal conduction process, which is driven by the pore fluid pressure under applied loading. As a case study, the model is investigated to predict the cell density patterns of pre-osteoblasts MC3T3-e1 cells under a range of different loading regimes, to obtain an understanding of desirable mechanical stimulation that will enhance cell density distribution within TE scaffolds. The results of this study have demonstrated that fluid perfusion can result in a higher cell density in the scaffold region closed to the outlet, while cell density distribution under mechanical compression was similar with static condition. More importantly, the study provides a novel computational approach to predict cell distribution in TE scaffolds under mechanical loading. Copyright © 2017 Elsevier Ltd. All rights reserved.

Simulation of Cardiac Arrhythmias Using a 2D Heterogeneous Whole Heart Model

PubMed Central

Balakrishnan, Minimol; Chakravarthy, V. Srinivasa; Guhathakurta, Soma

2015-01-01

Simulation studies of cardiac arrhythmias at the whole heart level with electrocardiogram (ECG) gives an understanding of how the underlying cell and tissue level changes manifest as rhythm disturbances in the ECG. We present a 2D whole heart model (WHM2D) which can accommodate variations at the cellular level and can generate the ECG waveform. It is shown that, by varying cellular-level parameters like the gap junction conductance (GJC), excitability, action potential duration (APD) and frequency of oscillations of the auto-rhythmic cell in WHM2D a large variety of cardiac arrhythmias can be generated including sinus tachycardia, sinus bradycardia, sinus arrhythmia, sinus pause, junctional rhythm, Wolf Parkinson White syndrome and all types of AV conduction blocks. WHM2D includes key components of the electrical conduction system of the heart like the SA (Sino atrial) node cells, fast conducting intranodal pathways, slow conducting atriovenctricular (AV) node, bundle of His cells, Purkinje network, atrial, and ventricular myocardial cells. SA nodal cells, AV nodal cells, bundle of His cells, and Purkinje cells are represented by the Fitzhugh-Nagumo (FN) model which is a reduced model of the Hodgkin-Huxley neuron model. The atrial and ventricular myocardial cells are modeled by the Aliev-Panfilov (AP) two-variable model proposed for cardiac excitation. WHM2D can prove to be a valuable clinical tool for understanding cardiac arrhythmias. PMID:26733873

The nexin link and B-tubule glutamylation maintain the alignment of outer doublets in the ciliary axoneme.

PubMed

Alford, Lea M; Stoddard, Daniel; Li, Jennifer H; Hunter, Emily L; Tritschler, Douglas; Bower, Raqual; Nicastro, Daniela; Porter, Mary E; Sale, Winfield S

2016-06-01

We developed quantitative assays to test the hypothesis that the N-DRC is required for integrity of the ciliary axoneme. We examined reactivated motility of demembranated drc cells, commonly termed "reactivated cell models." ATP-induced reactivation of wild-type cells resulted in the forward swimming of ∼90% of cell models. ATP-induced reactivation failed in a subset of drc cell models, despite forward motility in live drc cells. Dark-field light microscopic observations of drc cell models revealed various degrees of axonemal splaying. In contrast, >98% of axonemes from wild-type reactivated cell models remained intact. The sup-pf4 and drc3 mutants, unlike other drc mutants, retain most of the N-DRC linker that interconnects outer doublet microtubules. Reactivated sup-pf4 and drc3 cell models displayed nearly wild-type levels of forward motility. Thus, the N-DRC linker is required for axonemal integrity. We also examined reactivated motility and axoneme integrity in mutants defective in tubulin polyglutamylation. ATP-induced reactivation resulted in forward swimming of >75% of tpg cell models. Analysis of double mutants defective in tubulin polyglutamylation and different regions of the N-DRC indicate B-tubule polyglutamylation and the distal lobe of the linker region are both important for axonemal integrity and normal N-DRC function. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

A rigorous multiple independent binding site model for determining cell-based equilibrium dissociation constants.

PubMed

Drake, Andrew W; Klakamp, Scott L

2007-01-10

A new 4-parameter nonlinear equation based on the standard multiple independent binding site model (MIBS) is presented for fitting cell-based ligand titration data in order to calculate the ligand/cell receptor equilibrium dissociation constant and the number of receptors/cell. The most commonly used linear (Scatchard Plot) or nonlinear 2-parameter model (a single binding site model found in commercial programs like Prism(R)) used for analysis of ligand/receptor binding data assumes only the K(D) influences the shape of the titration curve. We demonstrate using simulated data sets that, depending upon the cell surface receptor expression level, the number of cells titrated, and the magnitude of the K(D) being measured, this assumption of always being under K(D)-controlled conditions can be erroneous and can lead to unreliable estimates for the binding parameters. We also compare and contrast the fitting of simulated data sets to the commonly used cell-based binding equation versus our more rigorous 4-parameter nonlinear MIBS model. It is shown through these simulations that the new 4-parameter MIBS model, when used for cell-based titrations under optimal conditions, yields highly accurate estimates of all binding parameters and hence should be the preferred model to fit cell-based experimental nonlinear titration data.

Modeling the Effects of Solar Cell Distribution on Optical Cross Section for Solar Panel Simulation

DTIC Science & Technology

2012-09-01

cell material. The solar panel was created as a CAD model and simulated with the imaging facility parameters with TASAT. TASAT uses a BRDF to apply...1 MODELING THE EFFECTS OF SOLAR CELL DISTRIBUTION ON OPTICAL CROSS SECTION FOR SOLAR PANEL SIMULATION Kelly Feirstine Meiling Klein... model of a solar panel with various solar cell tip and tilt distribution statistics. Modeling a solar panel as a single sheet of “solar cell” material

GEM System: automatic prototyping of cell-wide metabolic pathway models from genomes.

PubMed

Arakawa, Kazuharu; Yamada, Yohei; Shinoda, Kosaku; Nakayama, Yoichi; Tomita, Masaru

2006-03-23

Successful realization of a "systems biology" approach to analyzing cells is a grand challenge for our understanding of life. However, current modeling approaches to cell simulation are labor-intensive, manual affairs, and therefore constitute a major bottleneck in the evolution of computational cell biology. We developed the Genome-based Modeling (GEM) System for the purpose of automatically prototyping simulation models of cell-wide metabolic pathways from genome sequences and other public biological information. Models generated by the GEM System include an entire Escherichia coli metabolism model comprising 968 reactions of 1195 metabolites, achieving 100% coverage when compared with the KEGG database, 92.38% with the EcoCyc database, and 95.06% with iJR904 genome-scale model. The GEM System prototypes qualitative models to reduce the labor-intensive tasks required for systems biology research. Models of over 90 bacterial genomes are available at our web site.

Finding your inner modeler: An NSF-sponsored workshop to introduce cell biologists to modeling/computational approaches.

PubMed

Stone, David E; Haswell, Elizabeth S; Sztul, Elizabeth

2017-01-01

In classical Cell Biology, fundamental cellular processes are revealed empirically, one experiment at a time. While this approach has been enormously fruitful, our understanding of cells is far from complete. In fact, the more we know, the more keenly we perceive our ignorance of the profoundly complex and dynamic molecular systems that underlie cell structure and function. Thus, it has become apparent to many cell biologists that experimentation alone is unlikely to yield major new paradigms, and that empiricism must be combined with theory and computational approaches to yield major new discoveries. To facilitate those discoveries, three workshops will convene annually for one day in three successive summers (2017-2019) to promote the use of computational modeling by cell biologists currently unconvinced of its utility or unsure how to apply it. The first of these workshops was held at the University of Illinois, Chicago in July 2017. Organized to facilitate interactions between traditional cell biologists and computational modelers, it provided a unique educational opportunity: a primer on how cell biologists with little or no relevant experience can incorporate computational modeling into their research. Here, we report on the workshop and describe how it addressed key issues that cell biologists face when considering modeling including: (1) Is my project appropriate for modeling? (2) What kind of data do I need to model my process? (3) How do I find a modeler to help me in integrating modeling approaches into my work? And, perhaps most importantly, (4) why should I bother?

Clonal tracing of Sox9+ liver progenitors in oval cell injury

PubMed Central

Tarlow, Branden D.; Finegold, Milton J.; Grompe, Markus

2014-01-01

Proliferating ducts, termed “oval cells”, have long thought to be bipotential, i.e. produce both biliary ducts and hepatocytes during chronic liver injury. The precursor to oval cells is considered to be a facultative liver stem cell (LSC). Recent lineage tracing experiments indicated that the LSC is Sox9+ and can replace the bulk of hepatocyte mass in several settings. However, no clonal relationship between Sox9+ cells and the two epithelial liver lineages was established. We labeled Sox9+ mouse liver cells at low density with a multicolor fluorescent confetti reporter. Organoid formation validated the progenitor activity of the labeled population. Sox9+ cells were traced in multiple oval cell injury models using both histology and FACS. Surprisingly, only rare clones containing both hepatocytes and oval cells were found in any experiment. Quantitative analysis showed that Sox9+ cells contributed only minimally (<1%) to the hepatocyte pool, even in classic oval cell injury models. In contrast, clonally marked mature hepatocytes demonstrated the ability to self-renew in all classic mouse oval cell activation injuries. A hepatocyte chimera model to trace hepatocytes and non-parenchymal cells also demonstrated the prevalence of hepatocyte-driven regeneration in mouse oval cell injury models. Conclusion Sox9+ ductal progenitor cells give rise to clonal oval cell proliferation and bipotential organoids but rarely produce hepatocytes in vivo. Hepatocytes themselves are the predominant source of new parenchyma cells in prototypical mouse models of oval cell activation. PMID:24700457

Hepatitis C Virus Cell-Cell Transmission and Resistance to Direct-Acting Antiviral Agents

PubMed Central

Heydmann, Laura; Barth, Heidi; Soulier, Eric; Habersetzer, François; Doffoël, Michel; Bukh, Jens; Patel, Arvind H.; Zeisel, Mirjam B.; Baumert, Thomas F.

2014-01-01

Hepatitis C virus (HCV) is transmitted between hepatocytes via classical cell entry but also uses direct cell-cell transfer to infect neighboring hepatocytes. Viral cell-cell transmission has been shown to play an important role in viral persistence allowing evasion from neutralizing antibodies. In contrast, the role of HCV cell-cell transmission for antiviral resistance is unknown. Aiming to address this question we investigated the phenotype of HCV strains exhibiting resistance to direct-acting antivirals (DAAs) in state-of-the-art model systems for cell-cell transmission and spread. Using HCV genotype 2 as a model virus, we show that cell-cell transmission is the main route of viral spread of DAA-resistant HCV. Cell-cell transmission of DAA-resistant viruses results in viral persistence and thus hampers viral eradication. We also show that blocking cell-cell transmission using host-targeting entry inhibitors (HTEIs) was highly effective in inhibiting viral dissemination of resistant genotype 2 viruses. Combining HTEIs with DAAs prevented antiviral resistance and led to rapid elimination of the virus in cell culture model. In conclusion, our work provides evidence that cell-cell transmission plays an important role in dissemination and maintenance of resistant variants in cell culture models. Blocking virus cell-cell transmission prevents emergence of drug resistance in persistent viral infection including resistance to HCV DAAs. PMID:24830295

Cellular Models: HD Patient-Derived Pluripotent Stem Cells.

PubMed

Geater, Charlene; Hernandez, Sarah; Thompson, Leslie; Mattis, Virginia B

2018-01-01

Huntington's disease (HD) is an autosomal dominant neurodegenerative disorder caused by expanded polyglutamine (polyQ)-encoding repeats in the Huntingtin (HTT) gene. Traditionally, HD cellular models consisted of either patient cells not affected by disease or rodent neurons expressing expanded polyQ repeats in HTT. As these models can be limited in their disease manifestation or proper genetic context, respectively, human HD pluripotent stem cells (PSCs) are currently under investigation as a way to model disease in patient-derived neurons and other neural cell types. This chapter reviews embryonic stem cell (ESC) and induced pluripotent stem cell (iPSC) models of disease, including published differentiation paradigms for neurons and their associated phenotypes, as well as current challenges to the field such as validation of the PSCs and PSC-derived cells. Highlighted are potential future technical advances to HD PSC modeling, including transdifferentiation, complex in vitro multiorgan/system reconstruction, and personalized medicine. Using a human HD patient model of the central nervous system, hopefully one day researchers can tease out the consequences of mutant HTT (mHTT) expression on specific cell types within the brain in order to identify and test novel therapies for disease.

A simple and accurate rule-based modeling framework for simulation of autocrine/paracrine stimulation of glioblastoma cell motility and proliferation by L1CAM in 2-D culture.

PubMed

Caccavale, Justin; Fiumara, David; Stapf, Michael; Sweitzer, Liedeke; Anderson, Hannah J; Gorky, Jonathan; Dhurjati, Prasad; Galileo, Deni S

2017-12-11

Glioblastoma multiforme (GBM) is a devastating brain cancer for which there is no known cure. Its malignancy is due to rapid cell division along with high motility and invasiveness of cells into the brain tissue. Simple 2-dimensional laboratory assays (e.g., a scratch assay) commonly are used to measure the effects of various experimental perturbations, such as treatment with chemical inhibitors. Several mathematical models have been developed to aid the understanding of the motile behavior and proliferation of GBM cells. However, many are mathematically complicated, look at multiple interdependent phenomena, and/or use modeling software not freely available to the research community. These attributes make the adoption of models and simulations of even simple 2-dimensional cell behavior an uncommon practice by cancer cell biologists. Herein, we developed an accurate, yet simple, rule-based modeling framework to describe the in vitro behavior of GBM cells that are stimulated by the L1CAM protein using freely available NetLogo software. In our model L1CAM is released by cells to act through two cell surface receptors and a point of signaling convergence to increase cell motility and proliferation. A simple graphical interface is provided so that changes can be made easily to several parameters controlling cell behavior, and behavior of the cells is viewed both pictorially and with dedicated graphs. We fully describe the hierarchical rule-based modeling framework, show simulation results under several settings, describe the accuracy compared to experimental data, and discuss the potential usefulness for predicting future experimental outcomes and for use as a teaching tool for cell biology students. It is concluded that this simple modeling framework and its simulations accurately reflect much of the GBM cell motility behavior observed experimentally in vitro in the laboratory. Our framework can be modified easily to suit the needs of investigators interested in other similar intrinsic or extrinsic stimuli that influence cancer or other cell behavior. This modeling framework of a commonly used experimental motility assay (scratch assay) should be useful to both researchers of cell motility and students in a cell biology teaching laboratory.

Track structure model of cell damage in space flight

NASA Technical Reports Server (NTRS)

Katz, Robert; Cucinotta, Francis A.; Wilson, John W.; Shinn, Judy L.; Ngo, Duc M.

1992-01-01

The phenomenological track-structure model of cell damage is discussed. A description of the application of the track-structure model with the NASA Langley transport code for laboratory and space radiation is given. Comparisons to experimental results for cell survival during exposure to monoenergetic, heavy-ion beams are made. The model is also applied to predict cell damage rates and relative biological effectiveness for deep-space exposures.

Single-cell-based computer simulation of the oxygen-dependent tumour response to irradiation

NASA Astrophysics Data System (ADS)

Harting, Christine; Peschke, Peter; Borkenstein, Klaus; Karger, Christian P.

2007-08-01

Optimization of treatment plans in radiotherapy requires the knowledge of tumour control probability (TCP) and normal tissue complication probability (NTCP). Mathematical models may help to obtain quantitative estimates of TCP and NTCP. A single-cell-based computer simulation model is presented, which simulates tumour growth and radiation response on the basis of the response of the constituting cells. The model contains oxic, hypoxic and necrotic tumour cells as well as capillary cells which are considered as sources of a radial oxygen profile. Survival of tumour cells is calculated by the linear quadratic model including the modified response due to the local oxygen concentration. The model additionally includes cell proliferation, hypoxia-induced angiogenesis, apoptosis and resorption of inactivated tumour cells. By selecting different degrees of angiogenesis, the model allows the simulation of oxic as well as hypoxic tumours having distinctly different oxygen distributions. The simulation model showed that poorly oxygenated tumours exhibit an increased radiation tolerance. Inter-tumoural variation of radiosensitivity flattens the dose response curve. This effect is enhanced by proliferation between fractions. Intra-tumoural radiosensitivity variation does not play a significant role. The model may contribute to the mechanistic understanding of the influence of biological tumour parameters on TCP. It can in principle be validated in radiation experiments with experimental tumours.

Immortalized endothelial cell lines for in vitro blood-brain barrier models: A systematic review.

PubMed

Rahman, Nurul Adhwa; Rasil, Alifah Nur'ain Haji Mat; Meyding-Lamade, Uta; Craemer, Eva Maria; Diah, Suwarni; Tuah, Ani Afiqah; Muharram, Siti Hanna

2016-07-01

Endothelial cells play the most important role in construction of the blood-brain barrier. Many studies have opted to use commercially available, easily transfected or immortalized endothelial cell lines as in vitro blood-brain barrier models. Numerous endothelial cell lines are available, but we do not currently have strong evidence for which cell lines are optimal for establishment of such models. This review aimed to investigate the application of immortalized endothelial cell lines as in vitro blood-brain barrier models. The databases used for this review were PubMed, OVID MEDLINE, ProQuest, ScienceDirect, and SpringerLink. A narrative systematic review was conducted and identified 155 studies. As a result, 36 immortalized endothelial cell lines of human, mouse, rat, porcine and bovine origins were found for the establishment of in vitro blood-brain barrier and brain endothelium models. This review provides a summary of immortalized endothelial cell lines as a guideline for future studies and improvements in the establishment of in vitro blood-brain barrier models. It is important to establish a good and reproducible model that has the potential for multiple applications, in particular a model of such a complex compartment such as the blood-brain barrier. Copyright © 2016 Elsevier B.V. All rights reserved.

Three-dimensional cell culture models for investigating human viruses.

PubMed

He, Bing; Chen, Guomin; Zeng, Yi

2016-10-01

Three-dimensional (3D) culture models are physiologically relevant, as they provide reproducible results, experimental flexibility and can be adapted for high-throughput experiments. Moreover, these models bridge the gap between traditional two-dimensional (2D) monolayer cultures and animal models. 3D culture systems have significantly advanced basic cell science and tissue engineering, especially in the fields of cell biology and physiology, stem cell research, regenerative medicine, cancer research, drug discovery, and gene and protein expression studies. In addition, 3D models can provide unique insight into bacteriology, virology, parasitology and host-pathogen interactions. This review summarizes and analyzes recent progress in human virological research with 3D cell culture models. We discuss viral growth, replication, proliferation, infection, virus-host interactions and antiviral drugs in 3D culture models.

A hybrid model of cell cycle in mammals.

PubMed

Behaegel, Jonathan; Comet, Jean-Paul; Bernot, Gilles; Cornillon, Emilien; Delaunay, Franck

2016-02-01

Time plays an essential role in many biological systems, especially in cell cycle. Many models of biological systems rely on differential equations, but parameter identification is an obstacle to use differential frameworks. In this paper, we present a new hybrid modeling framework that extends René Thomas' discrete modeling. The core idea is to associate with each qualitative state "celerities" allowing us to compute the time spent in each state. This hybrid framework is illustrated by building a 5-variable model of the mammalian cell cycle. Its parameters are determined by applying formal methods on the underlying discrete model and by constraining parameters using timing observations on the cell cycle. This first hybrid model presents the most important known behaviors of the cell cycle, including quiescent phase and endoreplication.

Characterization of thyroid cancer cell lines in murine orthotopic and intracardiac metastasis models.

PubMed

Morrison, Jennifer A; Pike, Laura A; Lund, Greg; Zhou, Qiong; Kessler, Brittelle E; Bauerle, Kevin T; Sams, Sharon B; Haugen, Bryan R; Schweppe, Rebecca E

2015-06-01

Thyroid cancer incidence has been increasing over time, and it is estimated that ∼1950 advanced thyroid cancer patients will die of their disease in 2015. To combat this disease, an enhanced understanding of thyroid cancer development and progression as well as the development of efficacious, targeted therapies are needed. In vitro and in vivo studies utilizing thyroid cancer cell lines and animal models are critically important to these research efforts. In this report, we detail our studies with a panel of authenticated human anaplastic and papillary thyroid cancer (ATC and PTC) cell lines engineered to express firefly luciferase in two in vivo murine cancer models-an orthotopic thyroid cancer model as well as an intracardiac injection metastasis model. In these models, primary tumor growth in the orthotopic model and the establishment and growth of metastases in the intracardiac injection model are followed in vivo using an IVIS imaging system. In the orthotopic model, the ATC cell lines 8505C and T238 and the PTC cell lines K1/GLAG-66 and BCPAP had take rates >90 % with final tumor volumes ranging 84-214 mm(3) over 4-5 weeks. In the intracardiac model, metastasis establishment was successful in the ATC cell lines HTh74, HTh7, 8505C, THJ-16T, and Cal62 with take rates ≥70 %. Only one of the PTC cell lines tested (BCPAP) was successful in the intracardiac model with a take rate of 30 %. These data will be beneficial to inform the choice of cell line and model system for the design of future thyroid cancer studies.

Computational modelling of the scaffold-free chondrocyte regeneration: a two-way coupling between the cell growth and local fluid flow and nutrient concentration.

PubMed

Hossain, Md Shakhawath; Bergstrom, D J; Chen, X B

2015-11-01

The in vitro chondrocyte cell culture process in a perfusion bioreactor provides enhanced nutrient supply as well as the flow-induced shear stress that may have a positive influence on the cell growth. Mathematical and computational modelling of such a culture process, by solving the coupled flow, mass transfer and cell growth equations simultaneously, can provide important insight into the biomechanical environment of a bioreactor and the related cell growth process. To do this, a two-way coupling between the local flow field and cell growth is required. Notably, most of the computational and mathematical models to date have not taken into account the influence of the cell growth on the local flow field and nutrient concentration. The present research aimed at developing a mathematical model and performing a numerical simulation using the lattice Boltzmann method to predict the chondrocyte cell growth without a scaffold on a flat plate placed inside a perfusion bioreactor. The model considers the two-way coupling between the cell growth and local flow field, and the simulation has been performed for 174 culture days. To incorporate the cell growth into the model, a control-volume-based surface growth modelling approach has been adopted. The simulation results show the variation of local fluid velocity, shear stress and concentration distribution during the culture period due to the growth of the cell phase and also illustrate that the shear stress can increase the cell volume fraction to a certain extent.

Computational model, method, and system for kinetically-tailoring multi-drug chemotherapy for individuals

DOEpatents

Gardner, Shea Nicole

2007-10-23

A method and system for tailoring treatment regimens to individual patients with diseased cells exhibiting evolution of resistance to such treatments. A mathematical model is provided which models rates of population change of proliferating and quiescent diseased cells using cell kinetics and evolution of resistance of the diseased cells, and pharmacokinetic and pharmacodynamic models. Cell kinetic parameters are obtained from an individual patient and applied to the mathematical model to solve for a plurality of treatment regimens, each having a quantitative efficacy value associated therewith. A treatment regimen may then be selected from the plurlaity of treatment options based on the efficacy value.

Use of the HepaRG Cell Line to Assess Potential Human Hepatotoxicity of ToxCast™ Chemicals

EPA Science Inventory

The HepaRG cell line is a promising model system for predicting human hepatotoxicity in part because of the greater capacity to metabolize chemicals than other cell models. We hypothesized that this cell line would be a relevant model for toxicity testing of industrial chemicals....

Evaluating cell lines as tumour models by comparison of genomic profiles

PubMed Central

Domcke, Silvia; Sinha, Rileen; Levine, Douglas A.; Sander, Chris; Schultz, Nikolaus

2013-01-01

Cancer cell lines are frequently used as in vitro tumour models. Recent molecular profiles of hundreds of cell lines from The Cancer Cell Line Encyclopedia and thousands of tumour samples from the Cancer Genome Atlas now allow a systematic genomic comparison of cell lines and tumours. Here we analyse a panel of 47 ovarian cancer cell lines and identify those that have the highest genetic similarity to ovarian tumours. Our comparison of copy-number changes, mutations and mRNA expression profiles reveals pronounced differences in molecular profiles between commonly used ovarian cancer cell lines and high-grade serous ovarian cancer tumour samples. We identify several rarely used cell lines that more closely resemble cognate tumour profiles than commonly used cell lines, and we propose these lines as the most suitable models of ovarian cancer. Our results indicate that the gap between cell lines and tumours can be bridged by genomically informed choices of cell line models for all tumour types. PMID:23839242

Effects of stiffness and volume on the transit time of an erythrocyte through a slit.

PubMed

Salehyar, Sara; Zhu, Qiang

2017-06-01

By using a fully coupled fluid-cell interaction model, we numerically simulate the dynamic process of a red blood cell passing through a slit driven by an incoming flow. The model is achieved by combining a multiscale model of the composite cell membrane with a boundary element fluid dynamics model based on the Stokes flow assumption. Our concentration is on the correlation between the transit time (the time it takes to finish the whole translocation process) and different conditions (flow speed, cell orientation, cell stiffness, cell volume, etc.) that are involved. According to the numerical prediction (with some exceptions), the transit time rises as the cell is stiffened. It is also highly sensitive to volume increase inside the cell. In general, even slightly swollen cells (i.e., the internal volume is increased while the surface area of the cell kept unchanged) travel dramatically slower through the slit. For these cells, there is also an increased chance of blockage.

Modeling to Optimize Terminal Stem Cell Differentiation

PubMed Central

Gallicano, G. Ian

2013-01-01

Embryonic stem cell (ESC), iPCs, and adult stem cells (ASCs) all are among the most promising potential treatments for heart failure, spinal cord injury, neurodegenerative diseases, and diabetes. However, considerable uncertainty in the production of ESC-derived terminally differentiated cell types has limited the efficiency of their development. To address this uncertainty, we and other investigators have begun to employ a comprehensive statistical model of ESC differentiation for determining the role of intracellular pathways (e.g., STAT3) in ESC differentiation and determination of germ layer fate. The approach discussed here applies the Baysian statistical model to cell/developmental biology combining traditional flow cytometry methodology and specific morphological observations with advanced statistical and probabilistic modeling and experimental design. The final result of this study is a unique tool and model that enhances the understanding of how and when specific cell fates are determined during differentiation. This model provides a guideline for increasing the production efficiency of therapeutically viable ESCs/iPSCs/ASC derived neurons or any other cell type and will eventually lead to advances in stem cell therapy. PMID:24278782

Multiscale Modeling of Cell Interaction in Angiogenesis: From the Micro- to Macro-scale

NASA Astrophysics Data System (ADS)

Pillay, Samara; Maini, Philip; Byrne, Helen

Solid tumors require a supply of nutrients to grow in size. To this end, tumors induce the growth of new blood vessels from existing vasculature through the process of angiogenesis. In this work, we use a discrete agent-based approach to model the behavior of individual endothelial cells during angiogenesis. We incorporate crowding effects through volume exclusion, motility of cells through biased random walks, and include birth and death processes. We use the transition probabilities associated with the discrete models to determine collective cell behavior, in terms of partial differential equations, using a Markov chain and master equation framework. We find that the cell-level dynamics gives rise to a migrating cell front in the form of a traveling wave on the macro-scale. The behavior of this front depends on the cell interactions that are included and the extent to which volume exclusion is taken into account in the discrete micro-scale model. We also find that well-established continuum models of angiogenesis cannot distinguish between certain types of cell behavior on the micro-scale. This may impact drug development strategies based on these models.

Cancer drug discovery: recent innovative approaches to tumor modeling.

PubMed

Lovitt, Carrie J; Shelper, Todd B; Avery, Vicky M

2016-09-01

Cell culture models have been at the heart of anti-cancer drug discovery programs for over half a century. Advancements in cell culture techniques have seen the rapid evolution of more complex in vitro cell culture models investigated for use in drug discovery. Three-dimensional (3D) cell culture research has become a strong focal point, as this technique permits the recapitulation of the tumor microenvironment. Biologically relevant 3D cellular models have demonstrated significant promise in advancing cancer drug discovery, and will continue to play an increasing role in the future. In this review, recent advances in 3D cell culture techniques and their application in tumor modeling and anti-cancer drug discovery programs are discussed. The topics include selection of cancer cells, 3D cell culture assays (associated endpoint measurements and analysis), 3D microfluidic systems and 3D bio-printing. Although advanced cancer cell culture models and techniques are becoming commonplace in many research groups, the use of these approaches has yet to be fully embraced in anti-cancer drug applications. Furthermore, limitations associated with analyzing information-rich biological data remain unaddressed.

Architecture and inherent robustness of a bacterial cell-cycle control system.

PubMed

Shen, Xiling; Collier, Justine; Dill, David; Shapiro, Lucy; Horowitz, Mark; McAdams, Harley H

2008-08-12

A closed-loop control system drives progression of the coupled stalked and swarmer cell cycles of the bacterium Caulobacter crescentus in a near-mechanical step-like fashion. The cell-cycle control has a cyclical genetic circuit composed of four regulatory proteins with tight coupling to processive chromosome replication and cell division subsystems. We report a hybrid simulation of the coupled cell-cycle control system, including asymmetric cell division and responses to external starvation signals, that replicates mRNA and protein concentration patterns and is consistent with observed mutant phenotypes. An asynchronous sequential digital circuit model equivalent to the validated simulation model was created. Formal model-checking analysis of the digital circuit showed that the cell-cycle control is robust to intrinsic stochastic variations in reaction rates and nutrient supply, and that it reliably stops and restarts to accommodate nutrient starvation. Model checking also showed that mechanisms involving methylation-state changes in regulatory promoter regions during DNA replication increase the robustness of the cell-cycle control. The hybrid cell-cycle simulation implementation is inherently extensible and provides a promising approach for development of whole-cell behavioral models that can replicate the observed functionality of the cell and its responses to changing environmental conditions.

Modelling the balance between quiescence and cell death in normal and tumour cell populations.

PubMed

Spinelli, Lorenzo; Torricelli, Alessandro; Ubezio, Paolo; Basse, Britta

2006-08-01

When considering either human adult tissues (in vivo) or cell cultures (in vitro), cell number is regulated by the relationship between quiescent cells, proliferating cells, cell death and other controls of cell cycle duration. By formulating a mathematical description we see that even small alterations of this relationship may cause a non-growing population to start growing with doubling times characteristic of human tumours. Our model consists of two age structured partial differential equations for the proliferating and quiescent cell compartments. Model parameters are death rates from and transition rates between these compartments. The partial differential equations can be solved for the steady-age distributions, giving the distribution of the cells through the cell cycle, dependent on specific model parameter values. Appropriate formulas can then be derived for various population characteristic quantities such as labelling index, proliferation fraction, doubling time and potential doubling time of the cell population. Such characteristic quantities can be estimated experimentally, although with decreasing precision from in vitro, to in vivo experimental systems and to the clinic. The model can be used to investigate the effects of a single alteration of either quiescence or cell death control on the growth of the whole population and the non-trivial dependence of the doubling time and other observable quantities on particular underlying cell cycle scenarios of death and quiescence. The model indicates that tumour evolution in vivo is a sequence of steady-states, each characterised by particular death and quiescence rate functions. We suggest that a key passage of carcinogenesis is a loss of the communication between quiescence, death and cell cycle machineries, causing a defect in their precise, cell cycle dependent relationship.

Modeling the Morphogenesis of Epidermal Tissues on the Surface of a 3D Last

NASA Astrophysics Data System (ADS)

McCleery, W. Tyler; Crews, Sarah M.; Mashburn, David N.; Veldhuis, Jim; Brodland, G. Wayne; Hutson, M. Shane

2014-03-01

Embryogenesis in the fruit fly Drosophila melanogaster is coordinated by the interaction of cells in adjacent tissues. For some events of embryogenesis, e.g., dorsal closure, two-dimensional models have been sufficient to elucidate the relevant cell and tissue mechanics. Here, we describe a new three-dimensional cell-level finite element model for investigating germ band retraction - a morphogenetic event where one epidermal tissue, the germ band, initially wraps around the posterior end of the ellipsoidal embryo. This tissue then retracts with a mechanical assist from contraction of cells in a second epidermal tissue, the amnioserosa. To speed simulation run times and focus on the relevant tissues, we only model epidermal tissue interactions. Epidermal cells are defined as polygons constrained to lie on the surface of the ellipsoidal last, but have adjustable parameters such as edge tensions and cell pressures. Tissue movements are simulated by balancing these dynamic cell-level forces with viscous resistance and allowing cells to exchange neighbors. Our choice of modeling parameters is informed by in vivo measurements of cell-level forces using laser microsurgery. We use this model to investigate the multicellular stress fields in normal and aberrant development.

Emergence of tissue mechanics from cellular processes: shaping a fly wing

NASA Astrophysics Data System (ADS)

Merkel, Matthias; Etournay, Raphael; Popovic, Marko; Nandi, Amitabha; Brandl, Holger; Salbreux, Guillaume; Eaton, Suzanne; Jülicher, Frank

Nowadays, biologistsare able to image biological tissueswith up to 10,000 cells in vivowhere the behavior of each individual cell can be followed in detail.However, how precisely large-scale tissue deformation and stresses emerge from cellular behavior remains elusive. Here, we study this question in the developing wing of the fruit fly. To this end, we first establish a geometrical framework that exactly decomposes tissue deformation into contributions by different kinds of cellular processes. These processes comprise cell shape changes, cell neighbor exchanges, cell divisions, and cell extrusions. As the key idea, we introduce a tiling of the cellular network into triangles. This approach also reveals that tissue deformation can also be created by correlated cellular motion. Based on quantifications using these concepts, we developed a novel continuum mechanical model for the fly wing. In particular, our model includes active anisotropic stresses and a delay in the response of cell rearrangements to material stresses. A different approach to study the emergence of tissue mechanics from cellular behavior are cell-based models. We characterize the properties of a cell-based model for 3D tissues that is a hybrid between single particle models and the so-called vertex models.

Agent-Based Modeling of Cancer Stem Cell Driven Solid Tumor Growth.

PubMed

Poleszczuk, Jan; Macklin, Paul; Enderling, Heiko

2016-01-01

Computational modeling of tumor growth has become an invaluable tool to simulate complex cell-cell interactions and emerging population-level dynamics. Agent-based models are commonly used to describe the behavior and interaction of individual cells in different environments. Behavioral rules can be informed and calibrated by in vitro assays, and emerging population-level dynamics may be validated with both in vitro and in vivo experiments. Here, we describe the design and implementation of a lattice-based agent-based model of cancer stem cell driven tumor growth.

Computational analysis of integrated biosensing and shear flow in a microfluidic vascular model

NASA Astrophysics Data System (ADS)

Wong, Jeremy F.; Young, Edmond W. K.; Simmons, Craig A.

2017-11-01

Fluid flow and flow-induced shear stress are critical components of the vascular microenvironment commonly studied using microfluidic cell culture models. Microfluidic vascular models mimicking the physiological microenvironment also offer great potential for incorporating on-chip biomolecular detection. In spite of this potential, however, there are few examples of such functionality. Detection of biomolecules released by cells under flow-induced shear stress is a significant challenge due to severe sample dilution caused by the fluid flow used to generate the shear stress, frequently to the extent where the analyte is no longer detectable. In this work, we developed a computational model of a vascular microfluidic cell culture model that integrates physiological shear flow and on-chip monitoring of cell-secreted factors. Applicable to multilayer device configurations, the computational model was applied to a bilayer configuration, which has been used in numerous cell culture applications including vascular models. Guidelines were established that allow cells to be subjected to a wide range of physiological shear stress while ensuring optimal rapid transport of analyte to the biosensor surface and minimized biosensor response times. These guidelines therefore enable the development of microfluidic vascular models that integrate cell-secreted factor detection while addressing flow constraints imposed by physiological shear stress. Ultimately, this work will result in the addition of valuable functionality to microfluidic cell culture models that further fulfill their potential as labs-on-chips.

Advances and challenges in logical modeling of cell cycle regulation: perspective for multi-scale, integrative yeast cell models

PubMed Central

Todd, Robert G.; van der Zee, Lucas

2016-01-01

Abstract The eukaryotic cell cycle is robustly designed, with interacting molecules organized within a definite topology that ensures temporal precision of its phase transitions. Its underlying dynamics are regulated by molecular switches, for which remarkable insights have been provided by genetic and molecular biology efforts. In a number of cases, this information has been made predictive, through computational models. These models have allowed for the identification of novel molecular mechanisms, later validated experimentally. Logical modeling represents one of the youngest approaches to address cell cycle regulation. We summarize the advances that this type of modeling has achieved to reproduce and predict cell cycle dynamics. Furthermore, we present the challenge that this type of modeling is now ready to tackle: its integration with intracellular networks, and its formalisms, to understand crosstalks underlying systems level properties, ultimate aim of multi-scale models. Specifically, we discuss and illustrate how such an integration may be realized, by integrating a minimal logical model of the cell cycle with a metabolic network. PMID:27993914

Use of upscaled elevation and surface roughness data in two-dimensional surface water models

USGS Publications Warehouse

Hughes, J.D.; Decker, J.D.; Langevin, C.D.

2011-01-01

In this paper, we present an approach that uses a combination of cell-block- and cell-face-averaging of high-resolution cell elevation and roughness data to upscale hydraulic parameters and accurately simulate surface water flow in relatively low-resolution numerical models. The method developed allows channelized features that preferentially connect large-scale grid cells at cell interfaces to be represented in models where these features are significantly smaller than the selected grid size. The developed upscaling approach has been implemented in a two-dimensional finite difference model that solves a diffusive wave approximation of the depth-integrated shallow surface water equations using preconditioned Newton–Krylov methods. Computational results are presented to show the effectiveness of the mixed cell-block and cell-face averaging upscaling approach in maintaining model accuracy, reducing model run-times, and how decreased grid resolution affects errors. Application examples demonstrate that sub-grid roughness coefficient variations have a larger effect on simulated error than sub-grid elevation variations.

Programmatic access to logical models in the Cell Collective modeling environment via a REST API.

PubMed

Kowal, Bryan M; Schreier, Travis R; Dauer, Joseph T; Helikar, Tomáš

2016-01-01

Cell Collective (www.cellcollective.org) is a web-based interactive environment for constructing, simulating and analyzing logical models of biological systems. Herein, we present a Web service to access models, annotations, and simulation data in the Cell Collective platform through the Representational State Transfer (REST) Application Programming Interface (API). The REST API provides a convenient method for obtaining Cell Collective data through almost any programming language. To ensure easy processing of the retrieved data, the request output from the API is available in a standard JSON format. The Cell Collective REST API is freely available at http://thecellcollective.org/tccapi. All public models in Cell Collective are available through the REST API. For users interested in creating and accessing their own models through the REST API first need to create an account in Cell Collective (http://thecellcollective.org). thelikar2@unl.edu. Technical user documentation: https://goo.gl/U52GWo. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Relating cell shape and mechanical stress in a spatially disordered epithelium using a vertex-based model

PubMed Central

Nestor-Bergmann, Alexander; Goddard, Georgina; Woolner, Sarah; Jensen, Oliver E

2018-01-01

Abstract Using a popular vertex-based model to describe a spatially disordered planar epithelial monolayer, we examine the relationship between cell shape and mechanical stress at the cell and tissue level. Deriving expressions for stress tensors starting from an energetic formulation of the model, we show that the principal axes of stress for an individual cell align with the principal axes of shape, and we determine the bulk effective tissue pressure when the monolayer is isotropic at the tissue level. Using simulations for a monolayer that is not under peripheral stress, we fit parameters of the model to experimental data for Xenopus embryonic tissue. The model predicts that mechanical interactions can generate mesoscopic patterns within the monolayer that exhibit long-range correlations in cell shape. The model also suggests that the orientation of mechanical and geometric cues for processes such as cell division are likely to be strongly correlated in real epithelia. Some limitations of the model in capturing geometric features of Xenopus epithelial cells are highlighted. PMID:28992197

Intelligent data analysis to model and understand live cell time-lapse sequences.

PubMed

Paterson, Allan; Ashtari, M; Ribé, D; Stenbeck, G; Tucker, A

2012-01-01

One important aspect of cellular function, which is at the basis of tissue homeostasis, is the delivery of proteins to their correct destinations. Significant advances in live cell microscopy have allowed tracking of these pathways by following the dynamics of fluorescently labelled proteins in living cells. This paper explores intelligent data analysis techniques to model the dynamic behavior of proteins in living cells as well as to classify different experimental conditions. We use a combination of decision tree classification and hidden Markov models. In particular, we introduce a novel approach to "align" hidden Markov models so that hidden states from different models can be cross-compared. Our models capture the dynamics of two experimental conditions accurately with a stable hidden state for control data and multiple (less stable) states for the experimental data recapitulating the behaviour of particle trajectories within live cell time-lapse data. In addition to having successfully developed an automated framework for the classification of protein transport dynamics from live cell time-lapse data our model allows us to understand the dynamics of a complex trafficking pathway in living cells in culture.

Simulations of Living Cell Origins Using a Cellular Automata Model

NASA Astrophysics Data System (ADS)

Ishida, Takeshi

2014-04-01

Understanding the generalized mechanisms of cell self-assembly is fundamental for applications in various fields, such as mass producing molecular machines in nanotechnology. Thus, the details of real cellular reaction networks and the necessary conditions for self-organized cells must be elucidated. We constructed a 2-dimensional cellular automata model to investigate the emergence of biological cell formation, which incorporated a looped membrane and a membrane-bound information system (akin to a genetic code and gene expression system). In particular, with an artificial reaction system coupled with a thermal system, the simultaneous formation of a looped membrane and an inner reaction process resulted in a more stable structure. These double structures inspired the primitive biological cell formation process from chemical evolution stage. With a model to simulate cellular self-organization in a 2-dimensional cellular automata model, 3 phenomena could be realized: (1) an inner reaction system developed as an information carrier precursor (akin to DNA); (2) a cell border emerged (akin to a cell membrane); and (3) these cell structures could divide into 2. This double-structured cell was considered to be a primary biological cell. The outer loop evolved toward a lipid bilayer membrane, and inner polymeric particles evolved toward precursor information carriers (evolved toward DNA). This model did not completely clarify all the necessary and sufficient conditions for biological cell self-organization. Further, our virtual cells remained unstable and fragile. However, the "garbage bag model" of Dyson proposed that the first living cells were deficient; thus, it would be reasonable that the earliest cells were more unstable and fragile than the simplest current unicellular organisms.

Simulations of living cell origins using a cellular automata model.

PubMed

Ishida, Takeshi

2014-04-01

Understanding the generalized mechanisms of cell self-assembly is fundamental for applications in various fields, such as mass producing molecular machines in nanotechnology. Thus, the details of real cellular reaction networks and the necessary conditions for self-organized cells must be elucidated. We constructed a 2-dimensional cellular automata model to investigate the emergence of biological cell formation, which incorporated a looped membrane and a membrane-bound information system (akin to a genetic code and gene expression system). In particular, with an artificial reaction system coupled with a thermal system, the simultaneous formation of a looped membrane and an inner reaction process resulted in a more stable structure. These double structures inspired the primitive biological cell formation process from chemical evolution stage. With a model to simulate cellular self-organization in a 2-dimensional cellular automata model, 3 phenomena could be realized: (1) an inner reaction system developed as an information carrier precursor (akin to DNA); (2) a cell border emerged (akin to a cell membrane); and (3) these cell structures could divide into 2. This double-structured cell was considered to be a primary biological cell. The outer loop evolved toward a lipid bilayer membrane, and inner polymeric particles evolved toward precursor information carriers (evolved toward DNA). This model did not completely clarify all the necessary and sufficient conditions for biological cell self-organization. Further, our virtual cells remained unstable and fragile. However, the "garbage bag model" of Dyson proposed that the first living cells were deficient; thus, it would be reasonable that the earliest cells were more unstable and fragile than the simplest current unicellular organisms.

Deep Reinforcement Learning of Cell Movement in the Early Stage of C. elegans Embryogenesis.

PubMed

Wang, Zi; Wang, Dali; Li, Chengcheng; Xu, Yichi; Li, Husheng; Bao, Zhirong

2018-04-25

Cell movement in the early phase of C. elegans development is regulated by a highly complex process in which a set of rules and connections are formulated at distinct scales. Previous efforts have demonstrated that agent-based, multi-scale modeling systems can integrate physical and biological rules and provide new avenues to study developmental systems. However, the application of these systems to model cell movement is still challenging and requires a comprehensive understanding of regulatory networks at the right scales. Recent developments in deep learning and reinforcement learning provide an unprecedented opportunity to explore cell movement using 3D time-lapse microscopy images. We present a deep reinforcement learning approach within an agent-based modeling system to characterize cell movement in the embryonic development of C. elegans. Our modeling system captures the complexity of cell movement patterns in the embryo and overcomes the local optimization problem encountered by traditional rule-based, agent-based modeling that uses greedy algorithms. We tested our model with two real developmental processes: the anterior movement of the Cpaaa cell via intercalation and the rearrangement of the superficial left-right asymmetry. In the first case, the model results suggested that Cpaaa's intercalation is an active directional cell movement caused by the continuous effects from a longer distance (farther than the length of two adjacent cells), as opposed to a passive movement caused by neighbor cell movements. In the second case, a leader-follower mechanism well explained the collective cell movement pattern in the asymmetry rearrangement. These results showed that our approach to introduce deep reinforcement learning into agent-based modeling can test regulatory mechanisms by exploring cell migration paths in a reverse engineering perspective. This model opens new doors to explore the large datasets generated by live imaging. Source code is available at https://github.com/zwang84/drl4cellmovement. dwang7@utk.edu, baoz@mskcc.org. Supplementary data are available at Bioinformatics online.

A drift-diffusion checkpoint model predicts a highly variable and growth-factor-sensitive portion of the cell cycle G1 phase.

PubMed

Jones, Zack W; Leander, Rachel; Quaranta, Vito; Harris, Leonard A; Tyson, Darren R

2018-01-01

Even among isogenic cells, the time to progress through the cell cycle, or the intermitotic time (IMT), is highly variable. This variability has been a topic of research for several decades and numerous mathematical models have been proposed to explain it. Previously, we developed a top-down, stochastic drift-diffusion+threshold (DDT) model of a cell cycle checkpoint and showed that it can accurately describe experimentally-derived IMT distributions [Leander R, Allen EJ, Garbett SP, Tyson DR, Quaranta V. Derivation and experimental comparison of cell-division probability densities. J. Theor. Biol. 2014;358:129-135]. Here, we use the DDT modeling approach for both descriptive and predictive data analysis. We develop a custom numerical method for the reliable maximum likelihood estimation of model parameters in the absence of a priori knowledge about the number of detectable checkpoints. We employ this method to fit different variants of the DDT model (with one, two, and three checkpoints) to IMT data from multiple cell lines under different growth conditions and drug treatments. We find that a two-checkpoint model best describes the data, consistent with the notion that the cell cycle can be broadly separated into two steps: the commitment to divide and the process of cell division. The model predicts one part of the cell cycle to be highly variable and growth factor sensitive while the other is less variable and relatively refractory to growth factor signaling. Using experimental data that separates IMT into G1 vs. S, G2, and M phases, we show that the model-predicted growth-factor-sensitive part of the cell cycle corresponds to a portion of G1, consistent with previous studies suggesting that the commitment step is the primary source of IMT variability. These results demonstrate that a simple stochastic model, with just a handful of parameters, can provide fundamental insights into the biological underpinnings of cell cycle progression.

A redefinition of the representation of mammary cells and enzyme activities in a lactating dairy cow model.

PubMed

Hanigan, M D; Rius, A G; Kolver, E S; Palliser, C C

2007-08-01

The Molly model predicts various aspects of digestion and metabolism in the cow, including nutrient partitioning between milk and body stores. It has been observed previously that the model underpredicts milk component yield responses to nutrition and consequently overpredicts body energy store responses. In Molly, mammary enzyme activity is represented as an aggregate of mammary cell numbers and activity per cell with minimal endocrine regulation. Work by others suggests that mammary cells can cycle between active and quiescent states in response to various stimuli. Simple models of milk production have demonstrated the utility of this representation when using the model to simulate variable milking and nutrient restriction. It was hypothesized that replacing the current representation of mammary cells and enzyme activity in Molly with a representation of active and quiescent cells and improving the representation of endocrine control of cell activity would improve predictions of milk component yield. The static representation of cell numbers was replaced with a representation of cell growth during gestation and early lactation periods and first-order cell death. Enzyme capacity for fat and protein synthesis was assumed to be proportional to cell numbers. Enzyme capacity for lactose synthesis was represented with the same equation form as for cell numbers. Data used for parameter estimation were collected as part of an extended lactation trial. Cows with North American or New Zealand genotypes were fed 0, 3, or 6 kg of concentrate dry matter daily during a 600-d lactation. The original model had root mean square prediction errors of 17.7, 22.3, and 19.8% for lactose, protein, and fat yield, respectively, as compared with values of 8.3, 9.4, and 11.7% for the revised model, respectively. The original model predicted body weight with an error of 19.7% vs. 5.7% for the revised model. Based on these observations, it was concluded that representing mammary synthetic capacity as a function of active cell numbers and revisions to endocrine control of cell activity was meritorious.

A numerical model for charge transport and energy conversion of perovskite solar cells.

PubMed

Zhou, Yecheng; Gray-Weale, Angus

2016-02-14

Based on the continuity equations and Poisson's equation, we developed a numerical model for perovskite solar cells. Due to different working mechanisms, the model for perovskite solar cells differs from that of silicon solar cells and Dye Sensitized Solar Cells. The output voltage and current are calculated differently, and in a manner suited in particular to perovskite organohalides. We report a test of our equations against experiment with good agreement. Using this numerical model, it was found that performances of solar cells increase with charge carrier's lifetimes, mobilities and diffusion lengths. The open circuit voltage (Voc) of a solar cell is dependent on light intensities, and charge carrier lifetimes. Diffusion length and light intensity determine the saturated current (Jsc). Additionally, three possible guidelines for the design and fabrication of perovskite solar cells are suggested by our calculations. Lastly, we argue that concentrator perovskite solar cells are promising.

The mathematical cell model reconstructed from interference microscopy data

NASA Astrophysics Data System (ADS)

Rogotnev, A. A.; Nikitiuk, A. S.; Naimark, O. B.; Nebogatikov, V. O.; Grishko, V. V.

2017-09-01

The mathematical model of cell dynamics is developed to link the dynamics of the phase cell thickness with the signs of the oncological pathology. The measurements of irregular oscillations of cancer cells phase thickness were made with laser interference microscope MIM-340 in order to substantiate this model. These data related to the dynamics of phase thickness for different cross-sections of cells (nuclei, nucleolus, and cytoplasm) allow the reconstruction of the attractor of dynamic system. The attractor can be associated with specific types of collective modes of phase thickness responsible for the normal and cancerous cell dynamics. Specific type of evolution operator was determined using an algorithm of designing of the mathematical cell model and temporal phase thickness data for cancerous and normal cells. Qualitative correspondence of attractor types to the cell states was analyzed in terms of morphological signs associated with maximum value of mean square irregular oscillations of phase thickness dynamics.

Mathematical model of macrophage-facilitated breast cancer cells invasion.

PubMed

Knútsdóttir, Hildur; Pálsson, Eirikur; Edelstein-Keshet, Leah

2014-09-21

Mortality from breast cancer stems from its tendency to invade into surrounding tissues and organs. Experiments have shown that this metastatic process is facilitated by macrophages in a short-ranged chemical signalling loop. Macrophages secrete epidermal growth factor, EGF, and respond to the colony stimulating factor 1, CSF-1. Tumor cells secrete CSF-1 and respond to EGF. In this way, the cells coordinate aggregation and cooperative migration. Here we investigate this process in a model for in vitro interactions using two distinct but related mathematical approaches. In the first, we analyze and simulate a set of partial differential equations to determine conditions for aggregation. In the second, we use a cell-based discrete 3D simulation to follow the fates and motion of individual cells during aggregation. Linear stability analysis of the PDE model reveals that decreasing the chemical secretion, chemotaxis coefficients or density of cells or increasing the chemical degradation in the model could eliminate the spontaneous aggregation of cells. Simulations with the discrete model show that the ratio between tumor cells and macrophages in aggregates increases when the EGF secretion parameter is increased. The results also show how CSF-1/CSF-1R autocrine signalling in tumor cells affects the ratio between the two cell types. Comparing the continuum results with simulations of a discrete cell-based model, we find good qualitative agreement. Copyright © 2014 Elsevier Ltd. All rights reserved.

Inheritance of Cell-Cycle Duration in the Presence of Periodic Forcing

NASA Astrophysics Data System (ADS)

Mosheiff, Noga; Martins, Bruno M. C.; Pearl-Mizrahi, Sivan; Grünberger, Alexander; Helfrich, Stefan; Mihalcescu, Irina; Kohlheyer, Dietrich; Locke, James C. W.; Glass, Leon; Balaban, Nathalie Q.

2018-04-01

Periodic forcing of nonlinear oscillators leads to a large number of dynamic behaviors. The coupling of the cell cycle to the circadian clock provides a biological realization of such forcing. A previous model of forcing leads to nontrivial relations between correlations along cell lineages. Here, we present a simplified two-dimensional nonlinear map for the periodic forcing of the cell cycle. Using high-throughput single-cell microscopy, we have studied the correlations between cell-cycle duration in discrete lineages of several different organisms, including those with known coupling to a circadian clock and those without known coupling to a circadian clock. The model reproduces the paradoxical correlations and predicts new features that can be compared with the experimental data. By fitting the model to the data, we extract the important parameters that govern the dynamics. Interestingly, the model reproduces bimodal distributions for cell-cycle duration, as well as the gating of cell division by the phase of the clock, without having been explicitly fed into the model. In addition, the model predicts that circadian coupling may increase cell-to-cell variability in a clonal population of cells. In agreement with this prediction, deletion of the circadian clock reduces variability. Our results show that simple correlations can identify systems under periodic forcing and that studies of nonlinear coupling of biological oscillators provide insight into basic cellular processes of growth.

[Effects of electromagnetic pulse exposure on the permeability of inner blood-retinal barrier model in vitro].

PubMed

Li, Hai-juan; Yang, Long-long; Tian, Wei; Liu, Jun-ju; Xie, Xue-jun; Guo, Guo-zhen

2012-03-01

To establish the inner blood-retinal barrier (BRB) model in vitro by co-culturing RF/6A cells and C6 cells and to investigate the effects of EMP (200 kV/m, 200 pulses) exposure on the permeability of the inner BRB model in vitro. RF/6A cells and C6 cells were co-cultured on transwell, and the characteristic of the inner BRB model was assessed by detecting transendothelial electrical resistance (TEER) and the permeability of horseradish peroxidase (HRP). The co-cultured model was exposed or sham exposed to the EMP (200 kV/m 200 pulses) for 0.5, 3, 6, 12, 24 h in vitro, then TEER and the permeability of HRP were measured for studying the effects of EMP on the permeability of inner BRB model in vitro. TEER value (145 Ωcm(2)) of the co-culturing inner BRB model significantly increased, as compared to that of RF/6A cells alone model (P < 0.05) on the 6th day after inoculation. There was significant difference of permeability of HRP between the co-culturing inner BRB model and RF/6A cells alone model (P < 0.05). The ability of inhibiting large molecular materials in the co-culturing inner BRB model enhanced. The TEER value decreased and the permeability of HRP increased as compared to the sham group at 0.5, 3, 6 h after the exposure. The inner BRB model by co-culturing RF/6A cells and C6 cells in vitro is efficient and suitable to study the alterations of the restricted permeability function of the inner BRB. EMP (200 kV/m for 200 pulses) could induce the enhanced permeability of the inner BRB model in vitro.

Numerical modelling of CIGS/CdS solar cell

NASA Astrophysics Data System (ADS)

Devi, Nisha; Aziz, Anver; Datta, Shouvik

2018-05-01

In this work, we design and analyze the Cu(In,Ga)Se2 (CIGS) solar cell using simulation software "Solar Cell Capacitance Simulator in One Dimension (SCAPS-1D)". The conventional CIGS solar cell uses various layers, like intrinsic ZnO/Aluminium doped ZnO as transparent oxide, antireflection layer MgF2, and electron back reflection (EBR) layer at CIGS/Mo interface for good power conversion efficiency. We replace this conventional model by a simple model which is easy to fabricate and also reduces the cost of this cell because of use of lesser materials. The new designed model of CIGS solar cell is ITO/CIGS/OVC/CdS/Metal contact, where OVC is ordered vacancy compound. From this simple structure, even at very low illumination we are getting good results. We simulate this CIGS solar cell model by varying various physical parameters of CIGS like thickness, carrier density, band gap and temperature.

A Theoretical Model of Jigsaw-Puzzle Pattern Formation by Plant Leaf Epidermal Cells

PubMed Central

Higaki, Takumi; Kutsuna, Natsumaro; Akita, Kae; Takigawa-Imamura, Hisako; Yoshimura, Kenji; Miura, Takashi

2016-01-01

Plant leaf epidermal cells exhibit a jigsaw puzzle–like pattern that is generated by interdigitation of the cell wall during leaf development. The contribution of two ROP GTPases, ROP2 and ROP6, to the cytoskeletal dynamics that regulate epidermal cell wall interdigitation has already been examined; however, how interactions between these molecules result in pattern formation remains to be elucidated. Here, we propose a simple interface equation model that incorporates both the cell wall remodeling activity of ROP GTPases and the diffusible signaling molecules by which they are regulated. This model successfully reproduces pattern formation observed in vivo, and explains the counterintuitive experimental results of decreased cellulose production and increased thickness. Our model also reproduces the dynamics of three-way cell wall junctions. Therefore, this model provides a possible mechanism for cell wall interdigitation formation in vivo. PMID:27054467

Rheological behavior of mammalian cells.

PubMed

Stamenović, D

2008-11-01

Rheological properties of living cells determine how cells interact with their mechanical microenvironment and influence their physiological functions. Numerous experimental studies have show that mechanical contractile stress borne by the cytoskeleton and weak power-law viscoelasticity are governing principles of cell rheology, and that the controlling physics is at the level of integrative cytoskeletal lattice properties. Based on these observations, two concepts have emerged as leading models of cytoskeletal mechanics. One is the tensegrity model, which explains the role of the contractile stress in cytoskeletal mechanics, and the other is the soft glass rheology model, which explains the weak power-law viscoelasticity of cells. While these two models are conceptually disparate, the phenomena that they describe are often closely associated in living cells for reasons that are largely unknown. In this review, we discuss current understanding of cell rheology by emphasizing the underlying biophysical mechanism and critically evaluating the existing rheological models.

Modeling intrinsic electrophysiology of AII amacrine cells: preliminary results.

PubMed

Apollo, Nick; Grayden, David B; Burkitt, Anthony N; Meffin, Hamish; Kameneva, Tatiana

2013-01-01

In patients who have lost their photoreceptors due to retinal degenerative diseases, it is possible to restore rudimentary vision by electrically stimulating surviving neurons. AII amacrine cells, which reside in the inner plexiform layer, split the signal from rod bipolar cells into ON and OFF cone pathways. As a result, it is of interest to develop a computational model to aid in the understanding of how these cells respond to the electrical stimulation delivered by a prosthetic implant. The aim of this work is to develop and constrain parameters in a single-compartment model of an AII amacrine cell using data from whole-cell patch clamp recordings. This model will be used to explore responses of AII amacrine cells to electrical stimulation. Single-compartment Hodgkin-Huxley-type neural models are simulated in the NEURON environment. Simulations showed successful reproduction of the potassium currentvoltage relationship and some of the spiking properties observed in vitro.

Modelling collective cell migration of neural crest

PubMed Central

Szabó, András; Mayor, Roberto

2016-01-01

Collective cell migration has emerged in the recent decade as an important phenomenon in cell and developmental biology and can be defined as the coordinated and cooperative movement of groups of cells. Most studies concentrate on tightly connected epithelial tissues, even though collective migration does not require a constant physical contact. Movement of mesenchymal cells is more independent, making their emergent collective behaviour less intuitive and therefore lending importance to computational modelling. Here we focus on such modelling efforts that aim to understand the collective migration of neural crest cells, a mesenchymal embryonic population that migrates large distances as a group during early vertebrate development. By comparing different models of neural crest migration, we emphasize the similarity and complementary nature of these approaches and suggest a future direction for the field. The principles derived from neural crest modelling could aid understanding the collective migration of other mesenchymal cell types. PMID:27085004

Modelling collective cell migration of neural crest.

PubMed

Szabó, András; Mayor, Roberto

2016-10-01

Collective cell migration has emerged in the recent decade as an important phenomenon in cell and developmental biology and can be defined as the coordinated and cooperative movement of groups of cells. Most studies concentrate on tightly connected epithelial tissues, even though collective migration does not require a constant physical contact. Movement of mesenchymal cells is more independent, making their emergent collective behaviour less intuitive and therefore lending importance to computational modelling. Here we focus on such modelling efforts that aim to understand the collective migration of neural crest cells, a mesenchymal embryonic population that migrates large distances as a group during early vertebrate development. By comparing different models of neural crest migration, we emphasize the similarity and complementary nature of these approaches and suggest a future direction for the field. The principles derived from neural crest modelling could aid understanding the collective migration of other mesenchymal cell types. Copyright © 2016 Elsevier Ltd. All rights reserved.

A particle-based model to simulate the micromechanics of single-plant parenchyma cells and aggregates

NASA Astrophysics Data System (ADS)

Van Liedekerke, P.; Ghysels, P.; Tijskens, E.; Samaey, G.; Smeedts, B.; Roose, D.; Ramon, H.

2010-06-01

This paper is concerned with addressing how plant tissue mechanics is related to the micromechanics of cells. To this end, we propose a mesh-free particle method to simulate the mechanics of both individual plant cells (parenchyma) and cell aggregates in response to external stresses. The model considers two important features in the plant cell: (1) the cell protoplasm, the interior liquid phase inducing hydrodynamic phenomena, and (2) the cell wall material, a viscoelastic solid material that contains the protoplasm. In this particle framework, the cell fluid is modeled by smoothed particle hydrodynamics (SPH), a mesh-free method typically used to address problems with gas and fluid dynamics. In the solid phase (cell wall) on the other hand, the particles are connected by pairwise interactions holding them together and preventing the fluid to penetrate the cell wall. The cell wall hydraulic conductivity (permeability) is built in as well through the SPH formulation. Although this model is also meant to be able to deal with dynamic and even violent situations (leading to cell wall rupture or cell-cell debonding), we have concentrated on quasi-static conditions. The results of single-cell compression simulations show that the conclusions found by analytical models and experiments can be reproduced at least qualitatively. Relaxation tests revealed that plant cells have short relaxation times (1 µs-10 µs) compared to mammalian cells. Simulations performed on cell aggregates indicated an influence of the cellular organization to the tissue response, as was also observed in experiments done on tissues with a similar structure.

Cellular volume regulation and substrate stiffness modulate the detachment dynamics of adherent cells

NASA Astrophysics Data System (ADS)

Yang, Yuehua; Jiang, Hongyuan

2018-03-01

Quantitative characterizations of cell detachment are vital for understanding the fundamental mechanisms of cell adhesion. Experiments have found that cell detachment shows strong rate dependence, which is mostly attributed to the binding-unbinding kinetics of receptor-ligand bond. However, our recent study showed that the cellular volume regulation can significantly regulate the dynamics of adherent cell and cell detachment. How this cellular volume regulation contributes to the rate dependence of cell detachment remains elusive. Here, we systematically study the role of cellular volume regulation in the rate dependence of cell detachment by investigating the cell detachments of nonspecific adhesion and specific adhesion. We find that the cellular volume regulation and the bond kinetics dominate the rate dependence of cell detachment at different time scales. We further test the validity of the traditional Johnson-Kendall-Roberts (JKR) contact model and the detachment model developed by Wyart and Gennes et al (W-G model). When the cell volume is changeable, the JKR model is not appropriate for both the detachments of convex cells and concave cells. The W-G model is valid for the detachment of convex cells but is no longer applicable for the detachment of concave cells. Finally, we show that the rupture force of adherent cells is also highly sensitive to substrate stiffness, since an increase in substrate stiffness will lead to more associated bonds. These findings can provide insight into the critical role of cell volume in cell detachment and might have profound implications for other adhesion-related physiological processes.

Examining a scaled dynamical system of telomere shortening

NASA Astrophysics Data System (ADS)

Cyrenne, Benoit M.; Gooding, Robert J.

2015-02-01

A model of telomere dynamics is proposed and examined. Our model, which extends a previously introduced model that incorporates stem cells as progenitors of new cells, imposes the Hayflick limit, the maximum number of cell divisions that are possible. This new model leads to cell populations for which the average telomere length is not necessarily a monotonically decreasing function of time, in contrast to previously published models. We provide a phase diagram indicating where such results would be expected via the introduction of scaled populations, rate constants and time. The application of this model to available leukocyte baboon data is discussed.

Modeling in conventional and supra electroporation for model cell with organelles

NASA Astrophysics Data System (ADS)

Sulaeman, Muhammad Yangki; Widita, Rena

2015-09-01

Electroporation is a formation of pores in the membrane cell due to the external electric field applied to the cell. There are two types of electroporation, conventional and supra-electroporation. The purpose of creating pores in the cell using conventional electroporation are to increase the effectiveness of chemotherapy (electrochemotherapy) and to kill cancer tissue using irreversible electroporation. Supra-electroporation shows that it can induce electroporation in the organell inside the cell, so it can kill the cell by apoptosis mechanism. Modeling of electroporation phenomenon on a model cell had been done by using software COMSOL Multiphysics 4.3b with the applied external electric field used are 1.1 kV/cm for conventional electroporation and 60 kV/cm for supra-electroporation to find the difference between transmembrane voltage and pore density for both electroporation. It can be concluded from the results that there is a big difference between transmembrane voltage and pores density on conventional and supra electroporation on model cell.

Model-Based Phenotypic Signatures Governing the Dynamics of the Stem and Semi-differentiated Cell Populations in Dysplastic Colonic Crypts.

PubMed

Nikolov, Svetoslav; Santos, Guido; Wolkenhauer, Olaf; Vera, Julio

2018-02-01

Mathematical modeling of cell differentiated in colonic crypts can contribute to a better understanding of basic mechanisms underlying colonic tissue organization, but also its deregulation during carcinogenesis and tumor progression. Here, we combined bifurcation analysis to assess the effect that time delay has in the complex interplay of stem cells and semi-differentiated cells at the niche of colonic crypts, and systematic model perturbation and simulation to find model-based phenotypes linked to cancer progression. The models suggest that stem cell and semi-differentiated cell population dynamics in colonic crypts can display chaotic behavior. In addition, we found that clinical profiling of colorectal cancer correlates with the in silico phenotypes proposed by the mathematical model. Further, potential therapeutic targets for chemotherapy resistant phenotypes are proposed, which in any case will require experimental validation.

Theoretical analysis of insulin-dependent glucose uptake heterogeneity in 3D bioreactor cell culture.

PubMed

Magrofuoco, Enrico; Elvassore, Nicola; Doyle, Francis J

2012-01-01

Three-dimensional (3D) cell cultures in bioreactors are becoming relevant as models for biological and physiological in vitro studies. In such systems, mathematical models can assist the experiment design that links the macroscopic properties to single-cell responses. We investigated the relationship between biochemical stimuli and cell response within a 3D cell culture in scaffold with heterogeneous porosity. Specifically, we studied the effect of insulin on the local glucose metabolism as a function of 3D pore size distribution. The multiscale mathematical model combines the mass transport within a 3D scaffold and a signaling pathways model. It considers the scaffold heterogeneity, and it describes spatiotemporal concentration of metabolites, biochemical stimuli, and cell density. The signaling model was integrated into this model, linking the local insulin concentration at cell membrane to the glucose uptake rate through glucose transporter type 4 (GLUT4) translocation from the cytosol to the cell membrane. The integrated model determines the cell response heterogeneities in a single channel, hence the biological response distribution in a 3D system. It also provides macroscopic outcomes to evaluate the feasibility of an experimental measurement of the system response. From our analysis, it became apparent that the flow rate is the most important operative variable, and that an optimum value ensures a fast and detectable cell response. This model on insulin-dependent glucose consumption rate offers insight into the cell metabolism physiology, which is a fundamental requirement for the study metabolic disorder such as Type 2 diabetes mellitus, in which the physiological insulin-dependent glucose metabolism is impaired. Copyright © 2012 American Institute of Chemical Engineers (AIChE).

Modeling an Excitable Biosynthetic Tissue with Inherent Variability for Paired Computational-Experimental Studies.

PubMed

Gokhale, Tanmay A; Kim, Jong M; Kirkton, Robert D; Bursac, Nenad; Henriquez, Craig S

2017-01-01

To understand how excitable tissues give rise to arrhythmias, it is crucially necessary to understand the electrical dynamics of cells in the context of their environment. Multicellular monolayer cultures have proven useful for investigating arrhythmias and other conduction anomalies, and because of their relatively simple structure, these constructs lend themselves to paired computational studies that often help elucidate mechanisms of the observed behavior. However, tissue cultures of cardiomyocyte monolayers currently require the use of neonatal cells with ionic properties that change rapidly during development and have thus been poorly characterized and modeled to date. Recently, Kirkton and Bursac demonstrated the ability to create biosynthetic excitable tissues from genetically engineered and immortalized HEK293 cells with well-characterized electrical properties and the ability to propagate action potentials. In this study, we developed and validated a computational model of these excitable HEK293 cells (called "Ex293" cells) using existing electrophysiological data and a genetic search algorithm. In order to reproduce not only the mean but also the variability of experimental observations, we examined what sources of variation were required in the computational model. Random cell-to-cell and inter-monolayer variation in both ionic conductances and tissue conductivity was necessary to explain the experimentally observed variability in action potential shape and macroscopic conduction, and the spatial organization of cell-to-cell conductance variation was found to not impact macroscopic behavior; the resulting model accurately reproduces both normal and drug-modified conduction behavior. The development of a computational Ex293 cell and tissue model provides a novel framework to perform paired computational-experimental studies to study normal and abnormal conduction in multidimensional excitable tissue, and the methodology of modeling variation can be applied to models of any excitable cell.

Modeling Bi-modality Improves Characterization of Cell Cycle on Gene Expression in Single Cells

PubMed Central

Danaher, Patrick; Finak, Greg; Krouse, Michael; Wang, Alice; Webster, Philippa; Beechem, Joseph; Gottardo, Raphael

2014-01-01

Advances in high-throughput, single cell gene expression are allowing interrogation of cell heterogeneity. However, there is concern that the cell cycle phase of a cell might bias characterizations of gene expression at the single-cell level. We assess the effect of cell cycle phase on gene expression in single cells by measuring 333 genes in 930 cells across three phases and three cell lines. We determine each cell's phase non-invasively without chemical arrest and use it as a covariate in tests of differential expression. We observe bi-modal gene expression, a previously-described phenomenon, wherein the expression of otherwise abundant genes is either strongly positive, or undetectable within individual cells. This bi-modality is likely both biologically and technically driven. Irrespective of its source, we show that it should be modeled to draw accurate inferences from single cell expression experiments. To this end, we propose a semi-continuous modeling framework based on the generalized linear model, and use it to characterize genes with consistent cell cycle effects across three cell lines. Our new computational framework improves the detection of previously characterized cell-cycle genes compared to approaches that do not account for the bi-modality of single-cell data. We use our semi-continuous modelling framework to estimate single cell gene co-expression networks. These networks suggest that in addition to having phase-dependent shifts in expression (when averaged over many cells), some, but not all, canonical cell cycle genes tend to be co-expressed in groups in single cells. We estimate the amount of single cell expression variability attributable to the cell cycle. We find that the cell cycle explains only 5%–17% of expression variability, suggesting that the cell cycle will not tend to be a large nuisance factor in analysis of the single cell transcriptome. PMID:25032992

Accounting for Space—Quantification of Cell-To-Cell Transmission Kinetics Using Virus Dynamics Models.

PubMed

Kumberger, Peter; Durso-Cain, Karina; Uprichard, Susan L; Dahari, Harel; Graw, Frederik

2018-04-17

Mathematical models based on ordinary differential equations (ODE) that describe the population dynamics of viruses and infected cells have been an essential tool to characterize and quantify viral infection dynamics. Although an important aspect of viral infection is the dynamics of viral spread, which includes transmission by cell-free virions and direct cell-to-cell transmission, models used so far ignored cell-to-cell transmission completely, or accounted for this process by simple mass-action kinetics between infected and uninfected cells. In this study, we show that the simple mass-action approach falls short when describing viral spread in a spatially-defined environment. Using simulated data, we present a model extension that allows correct quantification of cell-to-cell transmission dynamics within a monolayer of cells. By considering the decreasing proportion of cells that can contribute to cell-to-cell spread with progressing infection, our extension accounts for the transmission dynamics on a single cell level while still remaining applicable to standard population-based experimental measurements. While the ability to infer the proportion of cells infected by either of the transmission modes depends on the viral diffusion rate, the improved estimates obtained using our novel approach emphasize the need to correctly account for spatial aspects when analyzing viral spread.

Emergent cell and tissue dynamics from subcellular modeling of active biomechanical processes

NASA Astrophysics Data System (ADS)

Sandersius, S. A.; Weijer, C. J.; Newman, T. J.

2011-08-01

Cells and the tissues they form are not passive material bodies. Cells change their behavior in response to external biochemical and biomechanical cues. Behavioral changes, such as morphological deformation, proliferation and migration, are striking in many multicellular processes such as morphogenesis, wound healing and cancer progression. Cell-based modeling of these phenomena requires algorithms that can capture active cell behavior and their emergent tissue-level phenotypes. In this paper, we report on extensions of the subcellular element model to model active biomechanical subcellular processes. These processes lead to emergent cell and tissue level phenotypes at larger scales, including (i) adaptive shape deformations in cells responding to slow stretching, (ii) viscous flow of embryonic tissues, and (iii) streaming patterns of chemotactic cells in epithelial-like sheets. In each case, we connect our simulation results to recent experiments.

Modeling Surface Growth of Escherichia coli on Agar Plates

PubMed Central

Fujikawa, Hiroshi; Morozumi, Satoshi

2005-01-01

Surface growth of Escherichia coli cells on a membrane filter placed on a nutrient agar plate under various conditions was studied with a mathematical model. The surface growth of bacterial cells showed a sigmoidal curve with time on a semilogarithmic plot. To describe it, a new logistic model that we presented earlier (H. Fujikawa et al., Food Microbiol. 21:501-509, 2004) was modified. Growth curves at various constant temperatures (10 to 34°C) were successfully described with the modified model (model III). Model III gave better predictions of the rate constant of growth and the lag period than a modified Gompertz model and the Baranyi model. Using the parameter values of model III at the constant temperatures, surface growth at various temperatures was successfully predicted. Surface growth curves at various initial cell numbers were also sigmoidal and converged to the same maximum cell numbers at the stationary phase. Surface growth curves at various nutrient levels were also sigmoidal. The maximum cell number and the rate of growth were lower as the nutrient level decreased. The surface growth curve was the same as that in a liquid, except for the large curvature at the deceleration period. These curves were also well described with model III. The pattern of increase in the ATP content of cells grown on a surface was sigmoidal, similar to that for cell growth. We discovered several characteristics of the surface growth of bacterial cells under various growth conditions and examined the applicability of our model to describe these growth curves. PMID:16332768

The effect of solution nonideality on modeling transmembrane water transport and diffusion-limited intracellular ice formation during cryopreservation

NASA Astrophysics Data System (ADS)

Zhao, Gang; Takamatsu, Hiroshi; He, Xiaoming

2014-04-01

A new model was developed to predict transmembrane water transport and diffusion-limited ice formation in cells during freezing without the ideal-solution assumption that has been used in previous models. The model was applied to predict cell dehydration and intracellular ice formation (IIF) during cryopreservation of mouse oocytes and bovine carotid artery endothelial cells in aqueous sodium chloride (NaCl) solution with glycerol as the cryoprotectant or cryoprotective agent. A comparison of the predictions between the present model and the previously reported models indicated that the ideal-solution assumption results in under-prediction of the amount of intracellular ice at slow cooling rates (<50 K/min). In addition, the lower critical cooling rates for IIF that is lethal to cells predicted by the present model were much lower than those estimated with the ideal-solution assumption. This study represents the first investigation on how accounting for solution nonideality in modeling water transport across the cell membrane could affect the prediction of diffusion-limited ice formation in biological cells during freezing. Future studies are warranted to look at other assumptions alongside nonideality to further develop the model as a useful tool for optimizing the protocol of cell cryopreservation for practical applications.

The effect of solution nonideality on modeling transmembrane water transport and diffusion-limited intracellular ice formation during cryopreservation.

PubMed

Zhao, Gang; Takamatsu, Hiroshi; He, Xiaoming

2014-04-14

A new model was developed to predict transmembrane water transport and diffusion-limited ice formation in cells during freezing without the ideal-solution assumption that has been used in previous models. The model was applied to predict cell dehydration and intracellular ice formation (IIF) during cryopreservation of mouse oocytes and bovine carotid artery endothelial cells in aqueous sodium chloride (NaCl) solution with glycerol as the cryoprotectant or cryoprotective agent. A comparison of the predictions between the present model and the previously reported models indicated that the ideal-solution assumption results in under-prediction of the amount of intracellular ice at slow cooling rates (<50 K/min). In addition, the lower critical cooling rates for IIF that is lethal to cells predicted by the present model were much lower than those estimated with the ideal-solution assumption. This study represents the first investigation on how accounting for solution nonideality in modeling water transport across the cell membrane could affect the prediction of diffusion-limited ice formation in biological cells during freezing. Future studies are warranted to look at other assumptions alongside nonideality to further develop the model as a useful tool for optimizing the protocol of cell cryopreservation for practical applications.

A Nonlinear Mixed Effects Approach for Modeling the Cell-To-Cell Variability of Mig1 Dynamics in Yeast

PubMed Central

Almquist, Joachim; Bendrioua, Loubna; Adiels, Caroline Beck; Goksör, Mattias; Hohmann, Stefan; Jirstrand, Mats

2015-01-01

The last decade has seen a rapid development of experimental techniques that allow data collection from individual cells. These techniques have enabled the discovery and characterization of variability within a population of genetically identical cells. Nonlinear mixed effects (NLME) modeling is an established framework for studying variability between individuals in a population, frequently used in pharmacokinetics and pharmacodynamics, but its potential for studies of cell-to-cell variability in molecular cell biology is yet to be exploited. Here we take advantage of this novel application of NLME modeling to study cell-to-cell variability in the dynamic behavior of the yeast transcription repressor Mig1. In particular, we investigate a recently discovered phenomenon where Mig1 during a short and transient period exits the nucleus when cells experience a shift from high to intermediate levels of extracellular glucose. A phenomenological model based on ordinary differential equations describing the transient dynamics of nuclear Mig1 is introduced, and according to the NLME methodology the parameters of this model are in turn modeled by a multivariate probability distribution. Using time-lapse microscopy data from nearly 200 cells, we estimate this parameter distribution according to the approach of maximizing the population likelihood. Based on the estimated distribution, parameter values for individual cells are furthermore characterized and the resulting Mig1 dynamics are compared to the single cell times-series data. The proposed NLME framework is also compared to the intuitive but limited standard two-stage (STS) approach. We demonstrate that the latter may overestimate variabilities by up to almost five fold. Finally, Monte Carlo simulations of the inferred population model are used to predict the distribution of key characteristics of the Mig1 transient response. We find that with decreasing levels of post-shift glucose, the transient response of Mig1 tend to be faster, more extended, and displays an increased cell-to-cell variability. PMID:25893847

Allometric Scaling and Cell Ratios in Multi-Organ in vitro Models of Human Metabolism

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ucciferri, Nadia; Interdepartmental Research Center “E. Piaggio”, University of Pisa, Pisa; Sbrana, Tommaso

2014-12-17

Intelligent in vitro models able to recapitulate the physiological interactions between tissues in the body have enormous potential as they enable detailed studies on specific two-way or higher order tissue communication. These models are the first step toward building an integrated picture of systemic metabolism and signaling in physiological or pathological conditions. However, the rational design of in vitro models of cell–cell or cell–tissue interaction is difficult as quite often cell culture experiments are driven by the device used, rather than by design considerations. Indeed, very little research has been carried out on in vitro models of metabolism connecting differentmore » cell or tissue types in a physiologically and metabolically relevant manner. Here, we analyze the physiological relationship between cells, cell metabolism, and exchange in the human body using allometric rules, downscaling them to an organ-on-a-plate device. In particular, in order to establish appropriate cell ratios in the system in a rational manner, two different allometric scaling models (cell number scaling model and metabolic and surface scaling model) are proposed and applied to a two compartment model of hepatic-vascular metabolic cross-talk. The theoretical scaling studies illustrate that the design and hence relevance of multi-organ models is principally determined by experimental constraints. Two experimentally feasible model configurations are then implemented in a multi-compartment organ-on-a-plate device. An analysis of the metabolic response of the two configurations demonstrates that their glucose and lipid balance is quite different, with only one of the two models recapitulating physiological-like homeostasis. In conclusion, not only do cross-talk and physical stimuli play an important role in in vitro models, but the numeric relationship between cells is also crucial to recreate in vitro interactions, which can be extrapolated to the in vivo reality.« less

A biologically based model of growth and senescence of Syrian hamster embryo (SHE) cells after exposure to arsenic.

PubMed Central

Liao, K H; Gustafson, D L; Fox, M H; Chubb, L S; Reardon, K F; Yang, R S

2001-01-01

We modified the two-stage Moolgavkar-Venzon-Knudson (MVK) model for use with Syrian hamster embryo (SHE) cell neoplastic progression. Five phenotypic stages are proposed in this model: Normal cells can either become senescent or mutate into immortal cells followed by anchorage-independent growth and tumorigenic stages. The growth of normal SHE cells was controlled by their division, death, and senescence rates, and all senescent cells were converted from normal cells. In this report, we tested the modeling of cell kinetics of the first two phenotypic stages against experimental data evaluating the effects of arsenic on SHE cells. We assessed cell division and death rates using flow cytometry and correlated cell division rates to the degree of confluence of cell cultures. The mean cell death rate was approximately equal to 1% of the average division rate. Arsenic did not induce immortalization or further mutations of SHE cells at concentrations of 2 microM and below, and chromium (3.6 microM) and lead (100 microM) had similar negative results. However, the growth of SHE cells was inhibited by 5.4 microM arsenic after a 2-day exposure, with cells becoming senescent after only 16 population doublings. In contrast, normal cells and cells exposed to lower arsenic concentrations grew normally for at least 30 population doublings. The biologically based model successfully predicted the growth of normal and arsenic-treated cells, as well as the senescence rates. Mechanisms responsible for inducing cellular senescence in SHE cells exposed to arsenic may help explain the apparent inability of arsenic to induce neoplasia in experimental animals. PMID:11748027

Quantification of Hepatitis C Virus Cell-to-Cell Spread Using a Stochastic Modeling Approach

PubMed Central

Martin, Danyelle N.; Perelson, Alan S.; Dahari, Harel

2015-01-01

ABSTRACT It has been proposed that viral cell-to-cell transmission plays a role in establishing and maintaining chronic infections. Thus, understanding the mechanisms and kinetics of cell-to-cell spread is fundamental to elucidating the dynamics of infection and may provide insight into factors that determine chronicity. Because hepatitis C virus (HCV) spreads from cell to cell and has a chronicity rate of up to 80% in exposed individuals, we examined the dynamics of HCV cell-to-cell spread in vitro and quantified the effect of inhibiting individual host factors. Using a multidisciplinary approach, we performed HCV spread assays and assessed the appropriateness of different stochastic models for describing HCV focus expansion. To evaluate the effect of blocking specific host cell factors on HCV cell-to-cell transmission, assays were performed in the presence of blocking antibodies and/or small-molecule inhibitors targeting different cellular HCV entry factors. In all experiments, HCV-positive cells were identified by immunohistochemical staining and the number of HCV-positive cells per focus was assessed to determine focus size. We found that HCV focus expansion can best be explained by mathematical models assuming focus size-dependent growth. Consistent with previous reports suggesting that some factors impact HCV cell-to-cell spread to different extents, modeling results estimate a hierarchy of efficacies for blocking HCV cell-to-cell spread when targeting different host factors (e.g., CLDN1 > NPC1L1 > TfR1). This approach can be adapted to describe focus expansion dynamics under a variety of experimental conditions as a means to quantify cell-to-cell transmission and assess the impact of cellular factors, viral factors, and antivirals. IMPORTANCE The ability of viruses to efficiently spread by direct cell-to-cell transmission is thought to play an important role in the establishment and maintenance of viral persistence. As such, elucidating the dynamics of cell-to-cell spread and quantifying the effect of blocking the factors involved has important implications for the design of potent antiviral strategies and controlling viral escape. Mathematical modeling has been widely used to understand HCV infection dynamics and treatment response; however, these models typically assume only cell-free virus infection mechanisms. Here, we used stochastic models describing focus expansion as a means to understand and quantify the dynamics of HCV cell-to-cell spread in vitro and determined the degree to which cell-to-cell spread is reduced when individual HCV entry factors are blocked. The results demonstrate the ability of this approach to recapitulate and quantify cell-to-cell transmission, as well as the impact of specific factors and potential antivirals. PMID:25833046

Modeling Human Natural Killer Cell Development in the Era of Innate Lymphoid Cells

PubMed Central

Scoville, Steven D.; Freud, Aharon G.; Caligiuri, Michael A.

2017-01-01

Decades after the discovery of natural killer (NK) cells, their developmental pathways in mice and humans have not yet been completely deciphered. Accumulating evidence indicates that NK cells can develop in multiple tissues throughout the body. Moreover, detailed and comprehensive models of NK cell development were proposed soon after the turn of the century. However, with the recent identification and characterization of other subtypes of innate lymphoid cells (ILCs), which show some overlapping functional and phenotypic features with NK cell developmental intermediates, the distinct stages through which human NK cells develop from early hematopoietic progenitor cells remain unclear. Thus, there is a need to reassess and refine older models of NK cell development in the context of new data and in the era of ILCs. Our group has focused on elucidating the developmental pathway of human NK cells in secondary lymphoid tissues (SLTs), including tonsils and lymph nodes. Here, we provide an update of recent progress that has been made with regard to human NK cell development in SLTs, and we discuss these new findings in the context of contemporary models of ILC development. PMID:28396671

Modeling Human Natural Killer Cell Development in the Era of Innate Lymphoid Cells.

PubMed

Scoville, Steven D; Freud, Aharon G; Caligiuri, Michael A

2017-01-01

Decades after the discovery of natural killer (NK) cells, their developmental pathways in mice and humans have not yet been completely deciphered. Accumulating evidence indicates that NK cells can develop in multiple tissues throughout the body. Moreover, detailed and comprehensive models of NK cell development were proposed soon after the turn of the century. However, with the recent identification and characterization of other subtypes of innate lymphoid cells (ILCs), which show some overlapping functional and phenotypic features with NK cell developmental intermediates, the distinct stages through which human NK cells develop from early hematopoietic progenitor cells remain unclear. Thus, there is a need to reassess and refine older models of NK cell development in the context of new data and in the era of ILCs. Our group has focused on elucidating the developmental pathway of human NK cells in secondary lymphoid tissues (SLTs), including tonsils and lymph nodes. Here, we provide an update of recent progress that has been made with regard to human NK cell development in SLTs, and we discuss these new findings in the context of contemporary models of ILC development.

Rate-equation modelling and ensemble approach to extraction of parameters for viral infection-induced cell apoptosis and necrosis

NASA Astrophysics Data System (ADS)

Domanskyi, Sergii; Schilling, Joshua E.; Gorshkov, Vyacheslav; Libert, Sergiy; Privman, Vladimir

2016-09-01

We develop a theoretical approach that uses physiochemical kinetics modelling to describe cell population dynamics upon progression of viral infection in cell culture, which results in cell apoptosis (programmed cell death) and necrosis (direct cell death). Several model parameters necessary for computer simulation were determined by reviewing and analyzing available published experimental data. By comparing experimental data to computer modelling results, we identify the parameters that are the most sensitive to the measured system properties and allow for the best data fitting. Our model allows extraction of parameters from experimental data and also has predictive power. Using the model we describe interesting time-dependent quantities that were not directly measured in the experiment and identify correlations among the fitted parameter values. Numerical simulation of viral infection progression is done by a rate-equation approach resulting in a system of "stiff" equations, which are solved by using a novel variant of the stochastic ensemble modelling approach. The latter was originally developed for coupled chemical reactions.

Rate-equation modelling and ensemble approach to extraction of parameters for viral infection-induced cell apoptosis and necrosis

NASA Astrophysics Data System (ADS)

Domanskyi, Sergii; Schilling, Joshua; Gorshkov, Vyacheslav; Libert, Sergiy; Privman, Vladimir

We develop a theoretical approach that uses physiochemical kinetics modelling to describe cell population dynamics upon progression of viral infection in cell culture, which results in cell apoptosis (programmed cell death) and necrosis (direct cell death). Several model parameters necessary for computer simulation were determined by reviewing and analyzing available published experimental data. By comparing experimental data to computer modelling results, we identify the parameters that are the most sensitive to the measured system properties and allow for the best data fitting. Our model allows extraction of parameters from experimental data and also has predictive power. Using the model we describe interesting time-dependent quantities that were not directly measured in the experiment and identify correlations among the fitted parameter values. Numerical simulation of viral infection progression is done by a rate-equation approach resulting in a system of ``stiff'' equations, which are solved by using a novel variant of the stochastic ensemble modelling approach. The latter was originally developed for coupled chemical reactions.

Selective destruction of mouse islet beta cells by human T lymphocytes in a newly-established humanized type 1 diabetic model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhao, Yong, E-mail: yongzhao@uic.edu; Guo, Chengshan; Hwang, David

2010-09-03

Research highlights: {yields} Establish a human immune-mediated type 1 diabetic model in NOD-scid IL2r{gamma}{sup null} mice. {yields} Using the irradiated diabetic NOD mouse spleen mononuclear cells as trigger. {yields} The islet {beta} cells were selectively destroyed by infiltrated human T cells. {yields} The model can facilitate translational research to find a cure for type 1 diabetes. -- Abstract: Type 1 diabetes (T1D) is caused by a T cell-mediated autoimmune response that leads to the loss of insulin-producing {beta} cells. The optimal preclinical testing of promising therapies would be aided by a humanized immune-mediated T1D model. We develop this model inmore » NOD-scid IL2r{gamma}{sup null} mice. The selective destruction of pancreatic islet {beta} cells was mediated by human T lymphocytes after an initial trigger was supplied by the injection of irradiated spleen mononuclear cells (SMC) from diabetic nonobese diabetic (NOD) mice. This resulted in severe insulitis, a marked loss of total {beta}-cell mass, and other related phenotypes of T1D. The migration of human T cells to pancreatic islets was controlled by the {beta} cell-produced highly conserved chemokine stromal cell-derived factor 1 (SDF-1) and its receptor C-X-C chemokine receptor (CXCR) 4, as demonstrated by in vivo blocking experiments using antibody to CXCR4. The specificity of humanized T cell-mediated immune responses against islet {beta} cells was generated by the local inflammatory microenvironment in pancreatic islets including human CD4{sup +} T cell infiltration and clonal expansion, and the mouse islet {beta}-cell-derived CD1d-mediated human iNKT activation. The selective destruction of mouse islet {beta} cells by a human T cell-mediated immune response in this humanized T1D model can mimic those observed in T1D patients. This model can provide a valuable tool for translational research into T1D.« less

Stability and bifurcation in a model for the dynamics of stem-like cells in leukemia under treatment

NASA Astrophysics Data System (ADS)

Rǎdulescu, I. R.; Cândea, D.; Halanay, A.

2012-11-01

A mathematical model for the dynamics of leukemic cells during treatment is introduced. Delay differential equations are used to model cells' evolution and are based on the Mackey-Glass approach, incorporating Goldie-Coldman law. Since resistance is propagated by cells that have the capacity of self-renewal, a population of stem-like cells is studied. Equilibrium points are calculated and their stability properties are investigated.

Developing Novel Therapeutic Approaches in Small Cell Lung Carcinoma Using Genetically Engineered Mouse Models and Human Circulating Tumor Cells

DTIC Science & Technology

2014-10-01

AD_________________ Award Number: W81XWH-13-1-0325 TITLE: Developing Novel Therapeutic Approaches in Small Cell Lung Carcinoma Using ...Genetically Engineered Mouse Models and Human Circulating Tumor Cells PRINCIPAL INVESTIGATOR: Jeffrey Engelman MD PhD CONTRACTING ORGANIZATION ...Novel Therapeutic Approaches in Small Cell Lung 5a. CONTRACT NUMBER W81XWH-13-1-0325 Carcinoma Using Genetically Engineered Mouse Models and 5b

An Elongated Tetrakaidecahedron Model for Open-Celled Foams

NASA Technical Reports Server (NTRS)

Sullivan, Roy M.; Ghosn, Louis J.; Lerch, Bradley A.

2007-01-01

A micro-mechanics model for non-isotropic, open-celled foams is developed using an elongated tetrakaidecahedron (Kelvin model) as the repeating unit cell. The micro-mechanics model employs an elongated Kelvin model geometry which is more general than that employed by previous authors. Assuming the cell edges possess axial and bending rigidity, the mechanics of deformation of the elongated tetrakaidecahedron lead to a set of equations for the Young's modulus, Poisson's ratio and strength of the foam in the principal material directions. These equations are written as a function of the cell edge lengths and cross-section properties, the inclination angle and the strength and stiffness of the solid material. The model is applied to predict the strength and stiffness of several polymeric foams. Good agreement is observed between the model results and the experimental measurements.

The Dynamics of HPV Infection and Cervical Cancer Cells.

PubMed

Asih, Tri Sri Noor; Lenhart, Suzanne; Wise, Steven; Aryati, Lina; Adi-Kusumo, F; Hardianti, Mardiah S; Forde, Jonathan

2016-01-01

The development of cervical cells from normal cells infected by human papillomavirus into invasive cancer cells can be modeled using population dynamics of the cells and free virus. The cell populations are separated into four compartments: susceptible cells, infected cells, precancerous cells and cancer cells. The model system of differential equations also has a free virus compartment in the system, which infect normal cells. We analyze the local stability of the equilibrium points of the model and investigate the parameters, which play an important role in the progression toward invasive cancer. By simulation, we investigate the boundary between initial conditions of solutions, which tend to stable equilibrium point, representing controlled infection, and those which tend to unbounded growth of the cancer cell population. Parameters affected by drug treatment are varied, and their effect on the risk of cancer progression is explored.

A calibrated agent-based computer model of stochastic cell dynamics in normal human colon crypts useful for in silico experiments.

PubMed

Bravo, Rafael; Axelrod, David E

2013-11-18

Normal colon crypts consist of stem cells, proliferating cells, and differentiated cells. Abnormal rates of proliferation and differentiation can initiate colon cancer. We have measured the variation in the number of each of these cell types in multiple crypts in normal human biopsy specimens. This has provided the opportunity to produce a calibrated computational model that simulates cell dynamics in normal human crypts, and by changing model parameter values, to simulate the initiation and treatment of colon cancer. An agent-based model of stochastic cell dynamics in human colon crypts was developed in the multi-platform open-source application NetLogo. It was assumed that each cell's probability of proliferation and probability of death is determined by its position in two gradients along the crypt axis, a divide gradient and in a die gradient. A cell's type is not intrinsic, but rather is determined by its position in the divide gradient. Cell types are dynamic, plastic, and inter-convertible. Parameter values were determined for the shape of each of the gradients, and for a cell's response to the gradients. This was done by parameter sweeps that indicated the values that reproduced the measured number and variation of each cell type, and produced quasi-stationary stochastic dynamics. The behavior of the model was verified by its ability to reproduce the experimentally observed monocolonal conversion by neutral drift, the formation of adenomas resulting from mutations either at the top or bottom of the crypt, and by the robust ability of crypts to recover from perturbation by cytotoxic agents. One use of the virtual crypt model was demonstrated by evaluating different cancer chemotherapy and radiation scheduling protocols. A virtual crypt has been developed that simulates the quasi-stationary stochastic cell dynamics of normal human colon crypts. It is unique in that it has been calibrated with measurements of human biopsy specimens, and it can simulate the variation of cell types in addition to the average number of each cell type. The utility of the model was demonstrated with in silico experiments that evaluated cancer therapy protocols. The model is available for others to conduct additional experiments.

Incorporating pushing in exclusion-process models of cell migration.

PubMed

Yates, Christian A; Parker, Andrew; Baker, Ruth E

2015-05-01

The macroscale movement behavior of a wide range of isolated migrating cells has been well characterized experimentally. Recently, attention has turned to understanding the behavior of cells in crowded environments. In such scenarios it is possible for cells to interact, inducing neighboring cells to move in order to make room for their own movements or progeny. Although the behavior of interacting cells has been modeled extensively through volume-exclusion processes, few models, thus far, have explicitly accounted for the ability of cells to actively displace each other in order to create space for themselves. In this work we consider both on- and off-lattice volume-exclusion position-jump processes in which cells are explicitly allowed to induce movements in their near neighbors in order to create space for themselves to move or proliferate into. We refer to this behavior as pushing. From these simple individual-level representations we derive continuum partial differential equations for the average occupancy of the domain. We find that, for limited amounts of pushing, comparison between the averaged individual-level simulations and the population-level model is nearly as good as in the scenario without pushing. Interestingly, we find that, in the on-lattice case, the diffusion coefficient of the population-level model is increased by pushing, whereas, for the particular off-lattice model that we investigate, the diffusion coefficient is reduced. We conclude, therefore, that it is important to consider carefully the appropriate individual-level model to use when representing complex cell-cell interactions such as pushing.

Establishment and Characterization of a Tumor Stem Cell-Based Glioblastoma Invasion Model.

PubMed

Jensen, Stine Skov; Meyer, Morten; Petterson, Stine Asferg; Halle, Bo; Rosager, Ann Mari; Aaberg-Jessen, Charlotte; Thomassen, Mads; Burton, Mark; Kruse, Torben A; Kristensen, Bjarne Winther

2016-01-01

Glioblastoma is the most frequent and malignant brain tumor. Recurrence is inevitable and most likely connected to tumor invasion and presence of therapy resistant stem-like tumor cells. The aim was therefore to establish and characterize a three-dimensional in vivo-like in vitro model taking invasion and tumor stemness into account. Glioblastoma stem cell-like containing spheroid (GSS) cultures derived from three different patients were established and characterized. The spheroids were implanted in vitro into rat brain slice cultures grown in stem cell medium and in vivo into brains of immuno-compromised mice. Invasion was followed in the slice cultures by confocal time-lapse microscopy. Using immunohistochemistry, we compared tumor cell invasion as well as expression of proliferation and stem cell markers between the models. We observed a pronounced invasion into brain slice cultures both by confocal time-lapse microscopy and immunohistochemistry. This invasion closely resembled the invasion in vivo. The Ki-67 proliferation indexes in spheroids implanted into brain slices were lower than in free-floating spheroids. The expression of stem cell markers varied between free-floating spheroids, spheroids implanted into brain slices and tumors in vivo. The established invasion model kept in stem cell medium closely mimics tumor cell invasion into the brain in vivo preserving also to some extent the expression of stem cell markers. The model is feasible and robust and we suggest the model as an in vivo-like model with a great potential in glioma studies and drug discovery.

Rapid acquisition and model-based analysis of cell-free transcription–translation reactions from nonmodel bacteria

PubMed Central

Wienecke, Sarah; Ishwarbhai, Alka; Tsipa, Argyro; Aw, Rochelle; Kylilis, Nicolas; Bell, David J.; McClymont, David W.; Jensen, Kirsten; Biedendieck, Rebekka

2018-01-01

Native cell-free transcription–translation systems offer a rapid route to characterize the regulatory elements (promoters, transcription factors) for gene expression from nonmodel microbial hosts, which can be difficult to assess through traditional in vivo approaches. One such host, Bacillus megaterium, is a giant Gram-positive bacterium with potential biotechnology applications, although many of its regulatory elements remain uncharacterized. Here, we have developed a rapid automated platform for measuring and modeling in vitro cell-free reactions and have applied this to B. megaterium to quantify a range of ribosome binding site variants and previously uncharacterized endogenous constitutive and inducible promoters. To provide quantitative models for cell-free systems, we have also applied a Bayesian approach to infer ordinary differential equation model parameters by simultaneously using time-course data from multiple experimental conditions. Using this modeling framework, we were able to infer previously unknown transcription factor binding affinities and quantify the sharing of cell-free transcription–translation resources (energy, ribosomes, RNA polymerases, nucleotides, and amino acids) using a promoter competition experiment. This allows insights into resource limiting-factors in batch cell-free synthesis mode. Our combined automated and modeling platform allows for the rapid acquisition and model-based analysis of cell-free transcription–translation data from uncharacterized microbial cell hosts, as well as resource competition within cell-free systems, which potentially can be applied to a range of cell-free synthetic biology and biotechnology applications. PMID:29666238

Point process models for localization and interdependence of punctate cellular structures.

PubMed

Li, Ying; Majarian, Timothy D; Naik, Armaghan W; Johnson, Gregory R; Murphy, Robert F

2016-07-01

Accurate representations of cellular organization for multiple eukaryotic cell types are required for creating predictive models of dynamic cellular function. To this end, we have previously developed the CellOrganizer platform, an open source system for generative modeling of cellular components from microscopy images. CellOrganizer models capture the inherent heterogeneity in the spatial distribution, size, and quantity of different components among a cell population. Furthermore, CellOrganizer can generate quantitatively realistic synthetic images that reflect the underlying cell population. A current focus of the project is to model the complex, interdependent nature of organelle localization. We built upon previous work on developing multiple non-parametric models of organelles or structures that show punctate patterns. The previous models described the relationships between the subcellular localization of puncta and the positions of cell and nuclear membranes and microtubules. We extend these models to consider the relationship to the endoplasmic reticulum (ER), and to consider the relationship between the positions of different puncta of the same type. Our results do not suggest that the punctate patterns we examined are dependent on ER position or inter- and intra-class proximity. With these results, we built classifiers to update previous assignments of proteins to one of 11 patterns in three distinct cell lines. Our generative models demonstrate the ability to construct statistically accurate representations of puncta localization from simple cellular markers in distinct cell types, capturing the complex phenomena of cellular structure interaction with little human input. This protocol represents a novel approach to vesicular protein annotation, a field that is often neglected in high-throughput microscopy. These results suggest that spatial point process models provide useful insight with respect to the spatial dependence between cellular structures. © 2016 International Society for Advancement of Cytometry. © 2016 International Society for Advancement of Cytometry.

Model-based analysis of Arabidopsis leaf epidermal cells reveals distinct division and expansion patterns for pavement and guard cells.

PubMed

Asl, Leila Kheibarshekan; Dhondt, Stijn; Boudolf, Véronique; Beemster, Gerrit T S; Beeckman, Tom; Inzé, Dirk; Govaerts, Willy; De Veylder, Lieven

2011-08-01

To efficiently capture sunlight for photosynthesis, leaves typically develop into a flat and thin structure. This development is driven by cell division and expansion, but the individual contribution of these processes is currently unknown, mainly because of the experimental difficulties to disentangle them in a developing organ, due to their tight interconnection. To circumvent this problem, we built a mathematic model that describes the possible division patterns and expansion rates for individual epidermal cells. This model was used to fit experimental data on cell numbers and sizes obtained over time intervals of 1 d throughout the development of the first leaf pair of Arabidopsis (Arabidopsis thaliana). The parameters were obtained by a derivative-free optimization method that minimizes the differences between the predicted and experimentally observed cell size distributions. The model allowed us to calculate probabilities for a cell to divide into guard or pavement cells, the maximum size at which it can divide, and its average cell division and expansion rates at each point during the leaf developmental process. Surprisingly, average cell cycle duration remained constant throughout leaf development, whereas no evidence for a maximum cell size threshold for cell division of pavement cells was found. Furthermore, the model predicted that neighboring cells of different sizes within the epidermis expand at distinctly different relative rates, which could be verified by direct observations. We conclude that cell division seems to occur independently from the status of cell expansion, whereas the cell cycle might act as a timer rather than as a size-regulated machinery.

Model-Based Analysis of Arabidopsis Leaf Epidermal Cells Reveals Distinct Division and Expansion Patterns for Pavement and Guard Cells1[W][OA

PubMed Central

Asl, Leila Kheibarshekan; Dhondt, Stijn; Boudolf, Véronique; Beemster, Gerrit T.S.; Beeckman, Tom; Inzé, Dirk; Govaerts, Willy; De Veylder, Lieven

2011-01-01

To efficiently capture sunlight for photosynthesis, leaves typically develop into a flat and thin structure. This development is driven by cell division and expansion, but the individual contribution of these processes is currently unknown, mainly because of the experimental difficulties to disentangle them in a developing organ, due to their tight interconnection. To circumvent this problem, we built a mathematic model that describes the possible division patterns and expansion rates for individual epidermal cells. This model was used to fit experimental data on cell numbers and sizes obtained over time intervals of 1 d throughout the development of the first leaf pair of Arabidopsis (Arabidopsis thaliana). The parameters were obtained by a derivative-free optimization method that minimizes the differences between the predicted and experimentally observed cell size distributions. The model allowed us to calculate probabilities for a cell to divide into guard or pavement cells, the maximum size at which it can divide, and its average cell division and expansion rates at each point during the leaf developmental process. Surprisingly, average cell cycle duration remained constant throughout leaf development, whereas no evidence for a maximum cell size threshold for cell division of pavement cells was found. Furthermore, the model predicted that neighboring cells of different sizes within the epidermis expand at distinctly different relative rates, which could be verified by direct observations. We conclude that cell division seems to occur independently from the status of cell expansion, whereas the cell cycle might act as a timer rather than as a size-regulated machinery. PMID:21693673

A three-dimensional neural spheroid model for capillary-like network formation.

PubMed

Boutin, Molly E; Kramer, Liana L; Livi, Liane L; Brown, Tyler; Moore, Christopher; Hoffman-Kim, Diane

2018-04-01

In vitro three-dimensional neural spheroid models have an in vivo-like cell density, and have the potential to reduce animal usage and increase experimental throughput. The aim of this study was to establish a spheroid model to study the formation of capillary-like networks in a three-dimensional environment that incorporates both neuronal and glial cell types, and does not require exogenous vasculogenic growth factors. We created self-assembled, scaffold-free cellular spheroids using primary-derived postnatal rodent cortex as a cell source. The interactions between relevant neural cell types, basement membrane proteins, and endothelial cells were characterized by immunohistochemistry. Transmission electron microscopy was used to determine if endothelial network structures had lumens. Endothelial cells within cortical spheroids assembled into capillary-like networks with lumens. Networks were surrounded by basement membrane proteins, including laminin, fibronectin and collagen IV, as well as key neurovascular cell types. Existing in vitro models of the cortical neurovascular environment study monolayers of endothelial cells, either on transwell inserts or coating cellular spheroids. These models are not well suited to study vasculogenesis, a process hallmarked by endothelial cell cord formation and subsequent lumenization. The neural spheroid is a new model to study the formation of endothelial cell capillary-like structures in vitro within a high cell density three-dimensional environment that contains both neuronal and glial populations. This model can be applied to investigate vascular assembly in healthy or disease states, such as stroke, traumatic brain injury, or neurodegenerative disorders. Copyright © 2017 Elsevier B.V. All rights reserved.

Cell Death Pathways in Mutant Rhodopsin Rat Models Identifies Genotype-Specific Targets Controlling Retinal Degeneration.

PubMed

Viringipurampeer, Ishaq A; Gregory-Evans, Cheryl Y; Metcalfe, Andrew L; Bashar, Emran; Moritz, Orson L; Gregory-Evans, Kevin

2018-06-18

Retinitis pigmentosa (RP) is a group of inherited neurological disorders characterized by rod photoreceptor cell death, followed by secondary cone cell death leading to progressive blindness. Currently, there are no viable treatment options for RP. Due to incomplete knowledge of the molecular signaling pathways associated with RP pathogenesis, designing therapeutic strategies remains a challenge. In particular, preventing secondary cone photoreceptor cell loss is a key goal in designing potential therapies. In this study, we identified the main drivers of rod cell death and secondary cone loss in the transgenic S334ter rhodopsin rat model, tested the efficacy of specific cell death inhibitors on retinal function, and compared the effect of combining drugs to target multiple pathways in the S334ter and P23H rhodopsin rat models. The primary driver of early rod cell death in the S334ter model was a caspase-dependent process, whereas cone cell death occurred though RIP3-dependent necroptosis. In comparison, rod cell death in the P23H model was via necroptotic signaling, whereas cone cell loss occurred through inflammasome activation. Combination therapy of four drugs worked better than the individual drugs in the P23H model but not in the S334ter model. These differences imply that treatment modalities need to be tailored for each genotype. Taken together, our data demonstrate that rationally designed genotype-specific drug combinations will be an important requisite to effectively target primary rod cell loss and more importantly secondary cone survival.

Agent-Based Computational Modeling of Cell Culture ...

EPA Pesticide Factsheets

Quantitative characterization of cellular dose in vitro is needed for alignment of doses in vitro and in vivo. We used the agent-based software, CompuCell3D (CC3D), to provide a stochastic description of cell growth in culture. The model was configured so that isolated cells assumed a “fried egg shape” but became increasingly cuboidal with increasing confluency. The surface area presented by each cell to the overlying medium varies from cell-to-cell and is a determinant of diffusional flux of toxicant from the medium into the cell. Thus, dose varies among cells for a given concentration of toxicant in the medium. Computer code describing diffusion of H2O2 from medium into each cell and clearance of H2O2 was calibrated against H2O2 time-course data (25, 50, or 75 uM H2O2 for 60 min) obtained with the Amplex Red assay for the medium and the H2O2-sensitive fluorescent reporter, HyPer, for cytosol. Cellular H2O2 concentrations peaked at about 5 min and were near baseline by 10 min. The model predicted a skewed distribution of surface areas, with between cell variation usually 2 fold or less. Predicted variability in cellular dose was in rough agreement with the variation in the HyPer data. These results are preliminary, as the model was not calibrated to the morphology of a specific cell type. Future work will involve morphology model calibration against human bronchial epithelial (BEAS-2B) cells. Our results show, however, the potential of agent-based modeling

Induced Pluripotent Stem Cell Models to Enable In Vitro Models for Screening in the Central Nervous System.

PubMed

Hunsberger, Joshua G; Efthymiou, Anastasia G; Malik, Nasir; Behl, Mamta; Mead, Ivy L; Zeng, Xianmin; Simeonov, Anton; Rao, Mahendra

2015-08-15

There is great need to develop more predictive drug discovery tools to identify new therapies to treat diseases of the central nervous system (CNS). Current nonpluripotent stem cell-based models often utilize non-CNS immortalized cell lines and do not enable the development of personalized models of disease. In this review, we discuss why in vitro models are necessary for translational research and outline the unique advantages of induced pluripotent stem cell (iPSC)-based models over those of current systems. We suggest that iPSC-based models can be patient specific and isogenic lines can be differentiated into many neural cell types for detailed comparisons. iPSC-derived cells can be combined to form small organoids, or large panels of lines can be developed that enable new forms of analysis. iPSC and embryonic stem cell-derived cells can be readily engineered to develop reporters for lineage studies or mechanism of action experiments further extending the utility of iPSC-based systems. We conclude by describing novel technologies that include strategies for the development of diversity panels, novel genomic engineering tools, new three-dimensional organoid systems, and modified high-content screens that may bring toxicology into the 21st century. The strategic integration of these technologies with the advantages of iPSC-derived cell technology, we believe, will be a paradigm shift for toxicology and drug discovery efforts.

Multi-scale modeling of the CD8 immune response

NASA Astrophysics Data System (ADS)

Barbarroux, Loic; Michel, Philippe; Adimy, Mostafa; Crauste, Fabien

2016-06-01

During the primary CD8 T-Cell immune response to an intracellular pathogen, CD8 T-Cells undergo exponential proliferation and continuous differentiation, acquiring cytotoxic capabilities to address the infection and memorize the corresponding antigen. After cleaning the organism, the only CD8 T-Cells left are antigen-specific memory cells whose role is to respond stronger and faster in case they are presented this very same antigen again. That is how vaccines work: a small quantity of a weakened pathogen is introduced in the organism to trigger the primary response, generating corresponding memory cells in the process, giving the organism a way to defend himself in case it encounters the same pathogen again. To investigate this process, we propose a non linear, multi-scale mathematical model of the CD8 T-Cells immune response due to vaccination using a maturity structured partial differential equation. At the intracellular scale, the level of expression of key proteins is modeled by a delay differential equation system, which gives the speeds of maturation for each cell. The population of cells is modeled by a maturity structured equation whose speeds are given by the intracellular model. We focus here on building the model, as well as its asymptotic study. Finally, we display numerical simulations showing the model can reproduce the biological dynamics of the cell population for both the primary response and the secondary responses.

Critical analysis of open circuit voltage and its effect on estimation of irreversible heat for Li-ion pouch cells

NASA Astrophysics Data System (ADS)

Arora, Shashank; Shen, Weixiang; Kapoor, Ajay

2017-05-01

Battery polarisation is not only responsible for reducing battery available capacity but also for controlling heat generation characteristics of batteries. This phenomenon was therefore carefully studied and modelled by Newman, Tiedemann and Gu (NTG). The NTG model is now widely used for simulating battery thermal behaviour and has even been adopted by CD-adapco for their proprietary battery modelling software - Battery Design Studio. The model however revolves around an idealised battery cell. It may thus not be applicable to commercial battery cells. This paper scrutinises the effect of open circuit voltage (OCV), a key parameter in the NTG model, on the irreversible heat generation of a commercial cell under a controlled environment by differentiating the OCV recorded immediately after the current stops flowing through the cell and the OCV corresponding to the equilibrium state of the cell. It is noticed that the NTG model underestimates the irreversible heat generation rates for a 20 Ah Li-ion pouch cell by approximately 0.15 W and 0.22 W for discharge currents at 0.33C and 0.5C at an operating temperature of 27 °C, respectively. It is also observed that the accuracy of the NTG model is significantly improved in simulating thermal behaviour of commercial battery cells when the OCV is representative of the cell equilibrium voltage.

The Effect of Primary Cancer Cell Culture Models on the Results of Drug Chemosensitivity Assays: The Application of Perfusion Microbioreactor System as Cell Culture Vessel

PubMed Central

Chen, Yi-Dao; Huang, Shiang-Fu; Wang, Hung-Ming

2015-01-01

To precisely and faithfully perform cell-based drug chemosensitivity assays, a well-defined and biologically relevant culture condition is required. For the former, a perfusion microbioreactor system capable of providing a stable culture condition was adopted. For the latter, however, little is known about the impact of culture models on the physiology and chemosensitivity assay results of primary oral cavity cancer cells. To address the issues, experiments were performed. Results showed that minor environmental pH change could significantly affect the metabolic activity of cells, demonstrating the importance of stable culture condition for such assays. Moreover, the culture models could also significantly influence the metabolic activity and proliferation of cells. Furthermore, the choice of culture models might lead to different outcomes of chemosensitivity assays. Compared with the similar test based on tumor-level assays, the spheroid model could overestimate the drug resistance of cells to cisplatin, whereas the 2D and 3D culture models might overestimate the chemosensitivity of cells to such anticancer drug. In this study, the 3D culture models with same cell density as that in tumor samples showed comparable chemosensitivity assay results as the tumor-level assays. Overall, this study has provided some fundamental information for establishing a precise and faithful drug chemosensitivity assay. PMID:25654105

Multi-scale modeling of the CD8 immune response

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barbarroux, Loic, E-mail: loic.barbarroux@doctorant.ec-lyon.fr; Ecole Centrale de Lyon, 36 avenue Guy de Collongue, 69134 Ecully; Michel, Philippe, E-mail: philippe.michel@ec-lyon.fr

During the primary CD8 T-Cell immune response to an intracellular pathogen, CD8 T-Cells undergo exponential proliferation and continuous differentiation, acquiring cytotoxic capabilities to address the infection and memorize the corresponding antigen. After cleaning the organism, the only CD8 T-Cells left are antigen-specific memory cells whose role is to respond stronger and faster in case they are presented this very same antigen again. That is how vaccines work: a small quantity of a weakened pathogen is introduced in the organism to trigger the primary response, generating corresponding memory cells in the process, giving the organism a way to defend himself inmore » case it encounters the same pathogen again. To investigate this process, we propose a non linear, multi-scale mathematical model of the CD8 T-Cells immune response due to vaccination using a maturity structured partial differential equation. At the intracellular scale, the level of expression of key proteins is modeled by a delay differential equation system, which gives the speeds of maturation for each cell. The population of cells is modeled by a maturity structured equation whose speeds are given by the intracellular model. We focus here on building the model, as well as its asymptotic study. Finally, we display numerical simulations showing the model can reproduce the biological dynamics of the cell population for both the primary response and the secondary responses.« less

Predicting electroporation of cells in an inhomogeneous electric field based on mathematical modeling and experimental CHO-cell permeabilization to propidium iodide determination.

PubMed

Dermol, Janja; Miklavčič, Damijan

2014-12-01

High voltage electric pulses cause electroporation of the cell membrane. Consequently, flow of the molecules across the membrane increases. In our study we investigated possibility to predict the percentage of the electroporated cells in an inhomogeneous electric field on the basis of the experimental results obtained when cells were exposed to a homogeneous electric field. We compared and evaluated different mathematical models previously suggested by other authors for interpolation of the results (symmetric sigmoid, asymmetric sigmoid, hyperbolic tangent and Gompertz curve). We investigated the density of the cells and observed that it has the most significant effect on the electroporation of the cells while all four of the mathematical models yielded similar results. We were able to predict electroporation of cells exposed to an inhomogeneous electric field based on mathematical modeling and using mathematical formulations of electroporation probability obtained experimentally using exposure to the homogeneous field of the same density of cells. Models describing cell electroporation probability can be useful for development and presentation of treatment planning for electrochemotherapy and non-thermal irreversible electroporation. Copyright © 2014 Elsevier B.V. All rights reserved.

Modeling collective cell migration in geometric confinement

NASA Astrophysics Data System (ADS)

Tarle, Victoria; Gauquelin, Estelle; Vedula, S. R. K.; D'Alessandro, Joseph; Lim, C. T.; Ladoux, Benoit; Gov, Nir S.

2017-06-01

Monolayer expansion has generated great interest as a model system to study collective cell migration. During such an expansion the culture front often develops ‘fingers’, which we have recently modeled using a proposed feedback between the curvature of the monolayer’s leading edge and the outward motility of the edge cells. We show that this model is able to explain the puzzling observed increase of collective cellular migration speed of a monolayer expanding into thin stripes, as well as describe the behavior within different confining geometries that were recently observed in experiments. These comparisons give support to the model and emphasize the role played by the edge cells and the edge shape during collective cell motion.

Modeling collective cell migration in geometric confinement.

PubMed

Tarle, Victoria; Gauquelin, Estelle; Vedula, S R K; D'Alessandro, Joseph; Lim, C T; Ladoux, Benoit; Gov, Nir S

2017-05-03

Monolayer expansion has generated great interest as a model system to study collective cell migration. During such an expansion the culture front often develops 'fingers', which we have recently modeled using a proposed feedback between the curvature of the monolayer's leading edge and the outward motility of the edge cells. We show that this model is able to explain the puzzling observed increase of collective cellular migration speed of a monolayer expanding into thin stripes, as well as describe the behavior within different confining geometries that were recently observed in experiments. These comparisons give support to the model and emphasize the role played by the edge cells and the edge shape during collective cell motion.

Modeling Dynamics of Cell-to-Cell Variability in TRAIL-Induced Apoptosis Explains Fractional Killing and Predicts Reversible Resistance

PubMed Central

Bertaux, François; Stoma, Szymon; Drasdo, Dirk; Batt, Gregory

2014-01-01

Isogenic cells sensing identical external signals can take markedly different decisions. Such decisions often correlate with pre-existing cell-to-cell differences in protein levels. When not neglected in signal transduction models, these differences are accounted for in a static manner, by assuming randomly distributed initial protein levels. However, this approach ignores the a priori non-trivial interplay between signal transduction and the source of this cell-to-cell variability: temporal fluctuations of protein levels in individual cells, driven by noisy synthesis and degradation. Thus, modeling protein fluctuations, rather than their consequences on the initial population heterogeneity, would set the quantitative analysis of signal transduction on firmer grounds. Adopting this dynamical view on cell-to-cell differences amounts to recast extrinsic variability into intrinsic noise. Here, we propose a generic approach to merge, in a systematic and principled manner, signal transduction models with stochastic protein turnover models. When applied to an established kinetic model of TRAIL-induced apoptosis, our approach markedly increased model prediction capabilities. One obtains a mechanistic explanation of yet-unexplained observations on fractional killing and non-trivial robust predictions of the temporal evolution of cell resistance to TRAIL in HeLa cells. Our results provide an alternative explanation to survival via induction of survival pathways since no TRAIL-induced regulations are needed and suggest that short-lived anti-apoptotic protein Mcl1 exhibit large and rare fluctuations. More generally, our results highlight the importance of accounting for stochastic protein turnover to quantitatively understand signal transduction over extended durations, and imply that fluctuations of short-lived proteins deserve particular attention. PMID:25340343

Mucosal-associated invariant T cells from induced pluripotent stem cells: A novel approach for modeling human diseases

PubMed Central

Sugimoto, Chie; Fujita, Hiroyoshi; Wakao, Hiroshi

2016-01-01

Mice have frequently been used to model human diseases involving immune dysregulation such as autoimmune and inflammatory diseases. These models help elucidate the mechanisms underlying the disease and in the development of novel therapies. However, if mice are deficient in certain cells and/or effectors associated with human diseases, how can their functions be investigated in this species? Mucosal-associated invariant T (MAIT) cells, a novel innate-like T cell family member, are a good example. MAIT cells are abundant in humans but scarce in laboratory mice. MAIT cells harbor an invariant T cell receptor and recognize nonpeptidic antigens vitamin B2 metabolites from bacteria and yeasts. Recent studies have shown that MAIT cells play a pivotal role in human diseases such as bacterial infections and autoimmune and inflammatory diseases. MAIT cells possess granulysin, a human-specific effector molecule, but granulysin and its homologue are absent in mice. Furthermore, MAIT cells show poor proliferation in vitro. To overcome these problems and further our knowledge of MAIT cells, we have established a method to expand MAIT cells via induced pluripotent stem cells (iPSCs). In this review, we describe recent advances in the field of MAIT cell research and our approach for human disease modeling with iPSC-derived MAIT cells. PMID:27114747

Mechanism of cell alignment in groups of Myxococcus xanthus bacteria

NASA Astrophysics Data System (ADS)

Balgam, Rajesh; Igoshin, Oleg

2015-03-01

Myxococcus xanthus is a model for studying self-organization in bacteria. These flexible cylindrical bacteria move along. In groups, M. xanthus cells align themselves into dynamic cell clusters but the mechanism underlying their formation is unknown. It has been shown that steric interactions can cause alignment in self-propelled hard rods but it is not clear how flexibility and reversals affect the alignment and cluster formation. We have investigated cell alignment process using our biophysical model of M. xanthus cell in an agent-based simulation framework under realistic cell flexibility values. We observed that flexible model cells can form aligned cell clusters when reversals are suppressed but these clusters disappeared when reversals frequency becomes similar to the observed value. However, M. xanthus cells follow slime (polysaccharide gel like material) trails left by other cells and we show that implementing this into our model rescues cell clustering for reversing cells. Our results show that slime following along with periodic cell reversals act as positive feedback to reinforce existing slime trails and recruit more cells. Furthermore, we have observed that mechanical cell alignment combined with slime following is sufficient to explain the distinct clustering patterns of reversing and non-reversing cells as observed in recent experiments. This work is supported by NSF MCB 0845919 and 1411780.

Enhancing dendritic cell immunotherapy for melanoma using a simple mathematical model.

PubMed

Castillo-Montiel, E; Chimal-Eguía, J C; Tello, J Ignacio; Piñon-Zaráte, G; Herrera-Enríquez, M; Castell-Rodríguez, A E

2015-06-09

The immunotherapy using dendritic cells (DCs) against different varieties of cancer is an approach that has been previously explored which induces a specific immune response. This work presents a mathematical model of DCs immunotherapy for melanoma in mice based on work by Experimental Immunotherapy Laboratory of the Medicine Faculty in the Universidad Autonoma de Mexico (UNAM). The model is a five delay differential equation (DDEs) which represents a simplified view of the immunotherapy mechanisms. The mathematical model takes into account the interactions between tumor cells, dendritic cells, naive cytotoxic T lymphocytes cells (inactivated cytotoxic cells), effector cells (cytotoxic T activated cytotoxic cells) and transforming growth factor β cytokine (T G F-β). The model is validated comparing the computer simulation results with biological trial results of the immunotherapy developed by the research group of UNAM. The results of the growth of tumor cells obtained by the control immunotherapy simulation show a similar amount of tumor cell population than the biological data of the control immunotherapy. Moreover, comparing the increase of tumor cells obtained from the immunotherapy simulation and the biological data of the immunotherapy applied by the UNAM researchers obtained errors of approximately 10 %. This allowed us to use the model as a framework to test hypothetical treatments. The numerical simulations suggest that by using more doses of DCs and changing the infusion time, the tumor growth decays compared with the current immunotherapy. In addition, a local sensitivity analysis is performed; the results show that the delay in time " τ", the maximal growth rate of tumor "r" and the maximal efficiency of tumor cytotoxic cells rate "aT" are the most sensitive model parameters. By using this mathematical model it is possible to simulate the growth of the tumor cells with or without immunotherapy using the infusion protocol of the UNAM researchers, to obtain a good approximation of the biological trials data. It is worth mentioning that by manipulating the different parameters of the model the effectiveness of the immunotherapy may increase. This last suggests that different protocols could be implemented by the Immunotherapy Laboratory of UNAM in order to improve their results.

Combinations of chromosome transfer and genome editing for the development of cell/animal models of human disease and humanized animal models.

PubMed

Uno, Narumi; Abe, Satoshi; Oshimura, Mitsuo; Kazuki, Yasuhiro

2018-02-01

Chromosome transfer technology, including chromosome modification, enables the introduction of Mb-sized or multiple genes to desired cells or animals. This technology has allowed innovative developments to be made for models of human disease and humanized animals, including Down syndrome model mice and humanized transchromosomic (Tc) immunoglobulin mice. Genome editing techniques are developing rapidly, and permit modifications such as gene knockout and knockin to be performed in various cell lines and animals. This review summarizes chromosome transfer-related technologies and the combined technologies of chromosome transfer and genome editing mainly for the production of cell/animal models of human disease and humanized animal models. Specifically, these include: (1) chromosome modification with genome editing in Chinese hamster ovary cells and mouse A9 cells for efficient transfer to desired cell types; (2) single-nucleotide polymorphism modification in humanized Tc mice with genome editing; and (3) generation of a disease model of Down syndrome-associated hematopoiesis abnormalities by the transfer of human chromosome 21 to normal human embryonic stem cells and the induction of mutation(s) in the endogenous gene(s) with genome editing. These combinations of chromosome transfer and genome editing open up new avenues for drug development and therapy as well as for basic research.

Myxobacteria Fruiting Body Formation

NASA Astrophysics Data System (ADS)

Jiang, Yi

2006-03-01

Myxobacteria are social bacteria that swarm and glide on surfaces, and feed cooperatively. When starved, tens of thousands of cells change their movement pattern from outward spreading to inward concentration; they form aggregates that become fruiting bodies, inside which cells differentiate into nonmotile, environmentally resistant spores. Traditionally, cell aggregation has been considered to imply chemotaxis, a long-range cell interaction mediated by diffusing chemicals. However, myxobacteria aggregation is the consequence of direct cell-contact interactions. I will review our recent efforts in modeling the fruiting body formation of Myxobacteria, using lattice gas cellular automata models that are based on local cell-cell contact signaling. These models have reproduced the individual phases in Myxobacteria development such as the rippling, streaming, early aggregation and the final sporulation; the models can be unified to simulate the whole developmental process of Myxobacteria.

In vitro cell and tissue models for studying host-microbe interactions: a review.

PubMed

Bermudez-Brito, Miriam; Plaza-Díaz, Julio; Fontana, Luis; Muñoz-Quezada, Sergio; Gil, Angel

2013-01-01

Ideally, cell models should resemble the in vivo conditions; however, in most in vitro experimental models, epithelial cells are cultivated as monolayers, in which the establishment of functional epithelial features is not achieved. To overcome this problem, co-culture experiments with probiotics, dendritic cells and intestinal epithelial cells and three-dimensional models attempt to reconcile the complex and dynamic interactions that exist in vivo between the intestinal epithelium and bacteria on the luminal side and between the epithelium and the underlying immune system on the basolateral side. Additional models include tissue explants, bioreactors and organoids. The present review details the in vitro models used to study host-microbe interactions and explores the new tools that may help in understanding the molecular mechanisms of these interactions.

Modeling the Soft Geometry of Biological Membranes

NASA Astrophysics Data System (ADS)

Daly, K.

This dissertation presents work done applying the techniques of physics to biological systems. The difference in length scales of the thickness of the phospolipid bilayer and overall size of a biological cell allows bilayer to be modeled elastically as a thin sheet. The Helfrich free energy is extended applied to models representing various biological systems, in order to find quasi-equilibrium states as well as transitions between states. Morphologies are approximated as axially sym-metric. Stable morphologies are de-termined analytically and through the use of computer simulation. The simple morphologies examined analytically give a model for the pearling transition seen in growing biological cells. An analytic model of celluar bulging in gram-negative bacteria predicts a critical pore radius for bulging of 20 nanometers. This model is extended to the membrane dynamics of human red blood cells, predicting three morphologic phases which are seen in vivo. A computer simulation was developed to study more complex morphologies with models representing different bilayer compositions. Single and multi-component bilayer models reproduce morphologies previously predicted by Seifert. A mean field model representing the intrinsic curvature of proteins coupling to membrane curvature is used to explore the stability of the particular morphology of rod outer segment cells. The process of pore formation and expansion in cell-cell fusion is not well understood. Simulation of the pore created in cell-cell fusion led to the finding of a minimal pore radius required for pore expansion, suggesting pores formed in nature are formed with a minimum size.

Myeloma Cell Dynamics in Response to Treatment Supports a Model of Hierarchical Differentiation and Clonal Evolution.

PubMed

Tang, Min; Zhao, Rui; van de Velde, Helgi; Tross, Jennifer G; Mitsiades, Constantine; Viselli, Suzanne; Neuwirth, Rachel; Esseltine, Dixie-Lee; Anderson, Kenneth; Ghobrial, Irene M; San Miguel, Jesús F; Richardson, Paul G; Tomasson, Michael H; Michor, Franziska

2016-08-15

Since the pioneering work of Salmon and Durie, quantitative measures of tumor burden in multiple myeloma have been used to make clinical predictions and model tumor growth. However, such quantitative analyses have not yet been performed on large datasets from trials using modern chemotherapy regimens. We analyzed a large set of tumor response data from three randomized controlled trials of bortezomib-based chemotherapy regimens (total sample size n = 1,469 patients) to establish and validate a novel mathematical model of multiple myeloma cell dynamics. Treatment dynamics in newly diagnosed patients were most consistent with a model postulating two tumor cell subpopulations, "progenitor cells" and "differentiated cells." Differential treatment responses were observed with significant tumoricidal effects on differentiated cells and less clear effects on progenitor cells. We validated this model using a second trial of newly diagnosed patients and a third trial of refractory patients. When applying our model to data of relapsed patients, we found that a hybrid model incorporating both a differentiation hierarchy and clonal evolution best explains the response patterns. The clinical data, together with mathematical modeling, suggest that bortezomib-based therapy exerts a selection pressure on myeloma cells that can shape the disease phenotype, thereby generating further inter-patient variability. This model may be a useful tool for improving our understanding of disease biology and the response to chemotherapy regimens. Clin Cancer Res; 22(16); 4206-14. ©2016 AACR. ©2016 American Association for Cancer Research.

The Activation and Inactivation of Mature CD4 T cells: A Case for Peripheral Self–Nonself Discrimination

PubMed Central

Bretscher, P A

2014-01-01

The establishment of central tolerance to most self-antigens results in a repertoire of mature peripheral lymphocytes specific for foreign and peripheral self-antigens. The framework that single, mature lymphocytes are inactivated by antigen, whereas their activation requires lymphocyte cooperation, accounts for diverse observations and incorporates a mechanism of peripheral tolerance. This framework accounts for the generalizations that the sustained activation by antigen of most B cells and CD8 T cells requires CD4 T helper cells; in the absence of CD4 T cells, antigen can inactivate these B cells and CD8 T cells. In this sense, CD4 T cells are the guardians of the fate of most B cells and CD8 T cells when they encounter antigen. I argue here that the single-lymphocyte/multiple-lymphocyte framework for the inactivation/activation of lymphocytes also applies to CD4 T cells. I consider within this framework a model for the activation/inactivation of CD4 T cells that is consistent with the large majority of contemporary observations, including significant clinical observations. I outline the grounds why I feel this model is more plausible than the contemporary and predominant pathogen-associated molecular pattern (PAMP) and Danger Models for CD4 T cell activation. These models are based upon what I consider the radical premise that self–nonself discrimination does not exist at the level of mature CD4 T cells. I explain why I feel this feature renders the PAMP and Danger Models somewhat implausible. The model I propose, in contrast, is conservative in that it embodies such a process of self–nonself discrimination. PMID:24684567

A network model for the specification of vulval precursor cells and cell fusion control in Caenorhabditis elegans

PubMed Central

Weinstein, Nathan; Mendoza, Luis

2013-01-01

The vulva of Caenorhabditis elegans has been long used as an experimental model of cell differentiation and organogenesis. While it is known that the signaling cascades of Wnt, Ras/MAPK, and NOTCH interact to form a molecular network, there is no consensus regarding its precise topology and dynamical properties. We inferred the molecular network, and developed a multivalued synchronous discrete dynamic model to study its behavior. The model reproduces the patterns of activation reported for the following types of cell: vulval precursor, first fate, second fate, second fate with reversed polarity, third fate, and fusion fate. We simulated the fusion of cells, the determination of the first, second, and third fates, as well as the transition from the second to the first fate. We also used the model to simulate all possible single loss- and gain-of-function mutants, as well as some relevant double and triple mutants. Importantly, we associated most of these simulated mutants to multivulva, vulvaless, egg-laying defective, or defective polarity phenotypes. The model shows that it is necessary for RAL-1 to activate NOTCH signaling, since the repression of LIN-45 by RAL-1 would not suffice for a proper second fate determination in an environment lacking DSL ligands. We also found that the model requires the complex formed by LAG-1, LIN-12, and SEL-8 to inhibit the transcription of eff-1 in second fate cells. Our model is the largest reconstruction to date of the molecular network controlling the specification of vulval precursor cells and cell fusion control in C. elegans. According to our model, the process of fate determination in the vulval precursor cells is reversible, at least until either the cells fuse with the ventral hypoderm or divide, and therefore the cell fates must be maintained by the presence of extracellular signals. PMID:23785384

Establishment of a translational endothelial cell model using directed differentiation of induced pluripotent stem cells from Cynomolgus monkey.

PubMed

Thoma, Eva C; Heckel, Tobias; Keller, David; Giroud, Nicolas; Leonard, Brian; Christensen, Klaus; Roth, Adrian; Bertinetti-Lapatki, Cristina; Graf, Martin; Patsch, Christoph

2016-10-25

Due to their broad differentiation potential, pluripotent stem cells (PSCs) offer a promising approach for generating relevant cellular models for various applications. While human PSC-based cellular models are already advanced, similar systems for non-human primates (NHPs) are still lacking. However, as NHPs are the most appropriate animals for evaluating the safety of many novel pharmaceuticals, the availability of in vitro systems would be extremely useful to bridge the gap between cellular and animal models. Here, we present a NHP in vitro endothelial cell system using induced pluripotent stem cells (IPSCs) from Cynomolgus monkey (Macaca fascicularis). Based on an adapted protocol for human IPSCs, we directly differentiated macaque IPSCs into endothelial cells under chemically defined conditions. The resulting endothelial cells can be enriched using immuno-magnetic cell sorting and display endothelial marker expression and function. RNA sequencing revealed that the differentiation process closely resembled vasculogenesis. Moreover, we showed that endothelial cells derived from macaque and human IPSCs are highly similar with respect to gene expression patterns and key endothelial functions, such as inflammatory responses. These data demonstrate the power of IPSC differentiation technology to generate defined cell types for use as translational in vitro models to compare cell type-specific responses across species.

Pluripotent stem cell derived hepatocyte like cells and their potential in toxicity screening.

PubMed

Greenhough, Sebastian; Medine, Claire N; Hay, David C

2010-12-30

Despite considerable progress in modelling human liver toxicity, the requirement still exists for efficient, predictive and cost effective in vitro models to reduce attrition during drug development. Thousands of compounds fail in this process, with hepatotoxicity being one of the significant causes of failure. The cost of clinical studies is substantial, therefore it is essential that toxicological screening is performed early on in the drug development process. Human hepatocytes represent the gold standard model for evaluating drug toxicity, but are a limited resource. Current alternative models are based on immortalised cell lines and animal tissue, but these are limited by poor function, exhibit species variability and show instability in culture. Pluripotent stem cells are an attractive alternative as they are capable of self-renewal and differentiation to all three germ layers, and thereby represent a potentially inexhaustible source of somatic cells. The differentiation of human embryonic stem cells and induced pluripotent stem cells to functional hepatocyte like cells has recently been reported. Further development of this technology could lead to the scalable production of hepatocyte like cells for liver toxicity screening and clinical therapies. Additionally, induced pluripotent stem cell derived hepatocyte like cells may permit in vitro modelling of gene polymorphisms and genetic diseases. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Coordinated learning of grid cell and place cell spatial and temporal properties: multiple scales, attention and oscillations.

PubMed

Grossberg, Stephen; Pilly, Praveen K

2014-02-05

A neural model proposes how entorhinal grid cells and hippocampal place cells may develop as spatial categories in a hierarchy of self-organizing maps (SOMs). The model responds to realistic rat navigational trajectories by learning both grid cells with hexagonal grid firing fields of multiple spatial scales, and place cells with one or more firing fields, that match neurophysiological data about their development in juvenile rats. Both grid and place cells can develop by detecting, learning and remembering the most frequent and energetic co-occurrences of their inputs. The model's parsimonious properties include: similar ring attractor mechanisms process linear and angular path integration inputs that drive map learning; the same SOM mechanisms can learn grid cell and place cell receptive fields; and the learning of the dorsoventral organization of multiple spatial scale modules through medial entorhinal cortex to hippocampus (HC) may use mechanisms homologous to those for temporal learning through lateral entorhinal cortex to HC ('neural relativity'). The model clarifies how top-down HC-to-entorhinal attentional mechanisms may stabilize map learning, simulates how hippocampal inactivation may disrupt grid cells, and explains data about theta, beta and gamma oscillations. The article also compares the three main types of grid cell models in the light of recent data.

Three dimensional CFD modeling and experimental validation of a single chamber solid oxide fuel cell fed by methane

NASA Astrophysics Data System (ADS)

Nguyen, H. T.; Le, M. V.; Nguyen, T. A.; Nguyen, T. A. N.

2017-06-01

The solid oxide fuel cell is one of the promising technologies for future energy demand. Solid oxide fuel cell operated in the single-chamber mode exhibits several advantages over conventional single oxide fuel cell due to the simplified, compact, sealing-free cell structure. There are some studies on simulating the behavior of this type of fuel cell but they mainly focus on the 2D model. In the present study, a three-dimensional numerical model of a single chamber solid oxide fuel cell (SOFC) is reported and solved using COMSOL Multiphysics software. Experiments of a planar button solid oxide fuel cell were used to verify the simulation results. The system is fed by methane and oxygen and operated at 700°C. The cathode is LSCF6482, the anode is GDC-Ni, the electrolyte is LDM and the operating pressure is 1 atm. There was a good agreement between the cell temperature and current voltage estimated from the model and measured from the experiment. The results indicate that the model is applicable for the single chamber solid oxide fuel cell and it can provide a basic for the design, scale up of single chamber solid oxide fuel cell system.

Groundwater management under uncertainty using a stochastic multi-cell model

NASA Astrophysics Data System (ADS)

Joodavi, Ata; Zare, Mohammad; Ziaei, Ali Naghi; Ferré, Ty P. A.

2017-08-01

The optimization of spatially complex groundwater management models over long time horizons requires the use of computationally efficient groundwater flow models. This paper presents a new stochastic multi-cell lumped-parameter aquifer model that explicitly considers uncertainty in groundwater recharge. To achieve this, the multi-cell model is combined with the constrained-state formulation method. In this method, the lower and upper bounds of groundwater heads are incorporated into the mass balance equation using indicator functions. This provides expressions for the means, variances and covariances of the groundwater heads, which can be included in the constraint set in an optimization model. This method was used to formulate two separate stochastic models: (i) groundwater flow in a two-cell aquifer model with normal and non-normal distributions of groundwater recharge; and (ii) groundwater management in a multiple cell aquifer in which the differences between groundwater abstractions and water demands are minimized. The comparison between the results obtained from the proposed modeling technique with those from Monte Carlo simulation demonstrates the capability of the proposed models to approximate the means, variances and covariances. Significantly, considering covariances between the heads of adjacent cells allows a more accurate estimate of the variances of the groundwater heads. Moreover, this modeling technique requires no discretization of state variables, thus offering an efficient alternative to computationally demanding methods.

Exploring the benefits of antibody immune response in HIV-1 infection using a discrete model.

PubMed

Showa, S P; Nyabadza, F; Hove-Musekwa, S D; Magombedze, G

2016-06-01

The role of antibodies in HIV-1 infection is investigated using a discrete-time mathematical model that considers cell-free and cell-associated transmission of the virus. Model analysis shows that the effect of each type of antibody is dependent on the stage of the infection. Neutralizing antibodies are efficient in controlling the viral levels in the early days after seroconversion and antibodies that coat HIV-1-infected cells and recruit effector cells to either kill the HIV-1-infected cells or inhibit viral replication are efficient when the infection becomes established. Model simulations show that antibodies that inhibit viral replication are more effective in controlling the infection than those that recruit Natural Killer T cells after infection establishment. The model was fitted to subjects of the Tsedimoso study conducted in Botswana and conclusions similar to elasticity analysis results were obtained. Model fitting results predicted that neutralizing antibodies are more efficient in controlling the viral levels than antibodies that coat HIV-1-infected cells and recruit effector cells to either kill the HIV-1-infected cells or inhibit viral replication in the early days after seroconversion. © The Authors 2015. Published by Oxford University Press on behalf of the Institute of Mathematics and its Applications. All rights reserved.

Effect of Grain Boundaries on the Performance of Thin-Film-Based Polycrystalline Silicon Solar Cells: A Numerical Modeling

NASA Astrophysics Data System (ADS)

Chhetri, Nikita; Chatterjee, Somenath

2018-01-01

Solar cells/photovoltaic, a renewable energy source, is appraised to be the most effective alternative to the conventional electrical energy generator. A cost-effective alternative of crystalline wafer-based solar cell is thin-film polycrystalline-based solar cell. This paper reports the numerical analysis of dependency of the solar cell parameters (i.e., efficiency, fill factor, open-circuit voltage and short-circuit current density) on grain size for thin-film-based polycrystalline silicon (Si) solar cells. A minority carrier lifetime model is proposed to do a correlation between the grains, grain boundaries and lifetime for thin-film-based polycrystalline Si solar cells in MATLAB environment. As observed, the increment in the grain size diameter results in increase in minority carrier lifetime in polycrystalline Si thin film. A non-equivalent series resistance double-diode model is used to find the dark as well as light (AM1.5) current-voltage (I-V) characteristics for thin-film-based polycrystalline Si solar cells. To optimize the effectiveness of the proposed model, a successive approximation method is used and the corresponding fitting parameters are obtained. The model is validated with the experimentally obtained results reported elsewhere. The experimentally reported solar cell parameters can be found using the proposed model described here.

Corrigendum to "Microstructural Characterization of Metal Foams: An Examination of the Applicability of the Theoretical Models for Modeling Foams"

NASA Technical Reports Server (NTRS)

Raj. Sai V.

2011-01-01

Establishing the geometry of foam cells is useful in developing microstructure-based acoustic and structural models. Since experimental data on the geometry of the foam cells are limited, most modeling efforts use an idealized three-dimensional, space-filling Kelvin tetrakaidecahedron. The validity of this assumption is investigated in the present paper. Several FeCrAlY foams with relative densities varying between 3 and 15% and cells per mm (c.p.mm.) varying between 0.2 and 3.9 c.p.mm. were microstructurally evaluated. The number of edges per face for each foam specimen was counted by approximating the cell faces by regular polygons, where the number of cell faces measured varied between 207 and 745. The present observations revealed that 50-57% of the cell faces were pentagonal while 24-28% were quadrilateral and 15-22% were hexagonal. The present measurements are shown to be in excellent agreement with literature data. It is demonstrated that the Kelvin model, as well as other proposed theoretical models, cannot accurately describe the FeCrAlY foam cell structure. Instead, it is suggested that the ideal foam cell geometry consists of 11 faces with 3 quadrilateral, 6 pentagonal faces and 2 hexagonal faces consistent with the 3-6-2 Matzke cell

A biochemically semi-detailed model of auxin-mediated vein formation in plant leaves.

PubMed

Roussel, Marc R; Slingerland, Martin J

2012-09-01

We present here a model intended to capture the biochemistry of vein formation in plant leaves. The model consists of three modules. Two of these modules, those describing auxin signaling and transport in plant cells, are biochemically detailed. We couple these modules to a simple model for PIN (auxin efflux carrier) protein localization based on an extracellular auxin sensor. We study the single-cell responses of this combined model in order to verify proper functioning of the modeled biochemical network. We then assemble a multicellular model from the single-cell building blocks. We find that the model can, under some conditions, generate files of polarized cells, but not true veins. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Cellular automata model for human articular chondrocytes migration, proliferation and cell death: An in vitro validation.

PubMed

Vaca-González, J J; Gutiérrez, M L; Guevara, J M; Garzón-Alvarado, D A

2017-01-01

Articular cartilage is characterized by low cell density of only one cell type, chondrocytes, and has limited self-healing properties. When articular cartilage is affected by traumatic injuries, a therapeutic strategy such as autologous chondrocyte implantation is usually proposed for its treatment. This approach requires in vitro chondrocyte expansion to yield high cell number for cell transplantation. To improve the efficiency of this procedure, it is necessary to assess cell dynamics such as migration, proliferation and cell death during culture. Computational models such as cellular automata can be used to simulate cell dynamics in order to enhance the result of cell culture procedures. This methodology has been implemented for several cell types; however, an experimental validation is required for each one. For this reason, in this research a cellular automata model, based on random-walk theory, was devised in order to predict articular chondrocyte behavior in monolayer culture during cell expansion. Results demonstrated that the cellular automata model corresponded to cell dynamics and computed-accurate quantitative results. Moreover, it was possible to observe that cell dynamics depend on weighted probabilities derived from experimental data and cell behavior varies according to the cell culture period. Thus, depending on whether cells were just seeded or proliferated exponentially, culture time probabilities differed in percentages in the CA model. Furthermore, in the experimental assessment a decreased chondrocyte proliferation was observed along with increased passage number. This approach is expected to having other uses as in enhancing articular cartilage therapies based on tissue engineering and regenerative medicine.

Investigation of polymer electrolyte membrane fuel cell internal behaviour during long term operation and its use in prognostics

NASA Astrophysics Data System (ADS)

Mao, Lei; Jackson, Lisa; Jackson, Tom

2017-09-01

This paper investigates the polymer electrolyte membrane (PEM) fuel cell internal behaviour variation at different operating condition, with characterization test data taken at predefined inspection times, and uses the determined internal behaviour evolution to predict the future PEM fuel cell performance. For this purpose, a PEM fuel cell behaviour model is used, which can be related to various fuel cell losses. By matching the model to the collected polarization curves from the PEM fuel cell system, the variation of fuel cell internal behaviour can be obtained through the determined model parameters. From the results, the source of PEM fuel cell degradation during its lifetime at different conditions can be better understood. Moreover, with determined fuel cell internal behaviour, the future fuel cell performance can be obtained by predicting the future model parameters. By comparing with prognostic results using adaptive neuro fuzzy inference system (ANFIS), the proposed prognostic analysis can provide better predictions for PEM fuel cell performance at dynamic condition, and with the understanding of variation in PEM fuel cell internal behaviour, mitigation strategies can be designed to extend the fuel cell performance.

Chaos in an Eulerian Based Model of Sickle Cell Blood Flow

NASA Astrophysics Data System (ADS)

Apori, Akwasi; Harris, Wesley

2001-11-01

A novel Eulerian model describing the manifestation of sickle cell blood flow in the capillaries has been formulated to study the apparently chaotic onset of sickle cell crises. This Eulerian model was based on extending previous models of sickle cell blood flow which were limited due to their Lagrangian formulation. Oxygen concentration, red blood cell velocity, cell stiffness, and plasma viscosity were modeled as system state variables. The governing equations of the system were expressed in canonical form. The non-linear coupling of velocity-viscosity and viscosity- stiffness proved to be the origin of chaos in the system. The system was solved with respect to a control parameter representing the unique rheology of the sickle cell erythrocytes. Results of chaos tests proved positive for various ranges of the control parameter. The results included con-tinuous patterns found in the Poincare section, spectral broadening of the Fourier power spectrum, and positive Lyapunov exponent values. The onset of chaos predicted by this sickle cell flow model as the control parameter was varied appeared to coincide with the change from a healthy state to a crisis state in a sickle cell patient. This finding that sickle cell crises may be caused from the well understood change of a solution from a steady state to chaotic could point to new ways in preventing and treating crises and should be validated in clinical trials.

Development of small scale cell culture models for screening poloxamer 188 lot-to-lot variation.

PubMed

Peng, Haofan; Hall, Kaitlyn M; Clayton, Blake; Wiltberger, Kelly; Hu, Weiwei; Hughes, Erik; Kane, John; Ney, Rachel; Ryll, Thomas

2014-01-01

Shear protectants such as poloxamer 188 play a critical role in protecting cells during cell culture bioprocessing. Lot-to-lot variation of poloxamer 188 was experienced during a routine technology transfer across sites of similar scale and equipment. Cell culture medium containing a specific poloxamer 188 lot resulted in an unusual drop in cell growth, viability, and titer during manufacturing runs. After switching poloxamer lots, culture performance returned to the expected level. In order to control the quality of poloxamer 188 and thus maintain better consistency in manufacturing, multiple small scale screening models were developed. Initially, a 5L bioreactor model was established to evaluate cell damage by high sparge rates with different poloxamer 188 lots. Subsequently, a more robust, simple, and efficient baffled shake flask model was developed. The baffled shake flask model can be performed in a high throughput manner to investigate the cell damage in a bubbling environment. The main cause of the poor performance was the loss of protection, rather than toxicity. It was also suggested that suspicious lots can be identified using different cell line and media. The screening methods provide easy, yet remarkable models for understanding and controlling cell damage due to raw material lot variation as well as studying the interaction between poloxamer 188 and cells. © 2014 American Institute of Chemical Engineers.

Modeling universal dynamics of cell spreading on elastic substrates.

PubMed

Fan, Houfu; Li, Shaofan

2015-11-01

A three-dimensional (3D) multiscale moving contact line model is combined with a soft matter cell model to study the universal dynamics of cell spreading over elastic substrates. We have studied both the early stage and the late stage cell spreading by taking into account the actin tension effect. In this work, the cell is modeled as an active nematic droplet, and the substrate is modeled as a St. Venant Kirchhoff elastic medium. A complete 3D simulation of cell spreading has been carried out. The simulation results show that the spreading area versus spreading time at different stages obeys specific power laws, which is in good agreement with experimental data and theoretical prediction reported in the literature. Moreover, the simulation results show that the substrate elasticity may affect force dipole distribution inside the cell. The advantage of this approach is that it combines the hydrodynamics of actin retrograde flow with moving contact line model so that it can naturally include actin tension effect resulting from actin polymerization and actomyosin contraction, and thus it might be capable of simulating complex cellular scale phenomenon, such as cell spreading or even crawling.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, G. H.; Pesaran, A.; Spotnitz, R.

To understand further the thermal abuse behavior of large format Li-ion batteries for automotive applications, the one-dimensional modeling approach formulated by Hatchard et al. was reproduced. Then it was extended to three dimensions so we could consider the geometrical features, which are critical in large cells for automotive applications. The three-dimensional model captures the shapes and dimensions of cell components and the spatial distributions of materials and temperatures, and is used to simulate oven tests, and to determine how a local hot spot can propagate through the cell. In simulations of oven abuse testing of cells with cobalt oxide cathodemore » and graphite anode with standard LiPF6 electrolyte, the three-dimensional model predicts that thermal runaway will occur sooner or later than the lumped model, depending on the size of the cell. The model results showed that smaller cells reject heat faster than larger cells; this may prevent them from going into thermal runaway under identical abuse conditions. In simulations of local hot spots inside a large cylindrical cell, the three-dimensional model predicts that the reactions initially propagate in the azimuthal and longitudinal directions to form a hollow cylinder-shaped reaction zone.« less

A simplified model for dynamics of cell rolling and cell-surface adhesion

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cimrák, Ivan, E-mail: ivan.cimrak@fri.uniza.sk

2015-03-10

We propose a three dimensional model for the adhesion and rolling of biological cells on surfaces. We study cells moving in shear flow above a wall to which they can adhere via specific receptor-ligand bonds based on receptors from selectin as well as integrin family. The computational fluid dynamics are governed by the lattice-Boltzmann method. The movement and the deformation of the cells is described by the immersed boundary method. Both methods are fully coupled by implementing a two-way fluid-structure interaction. The adhesion mechanism is modelled by adhesive bonds including stochastic rules for their creation and rupture. We explore amore » simplified model with dissociation rate independent of the length of the bonds. We demonstrate that this model is able to resemble the mesoscopic properties, such as velocity of rolling cells.« less

An non-uniformity voltage model for proton exchange membrane fuel cell

NASA Astrophysics Data System (ADS)

Li, Kelei; Li, Yankun; Liu, Jiawei; Guo, Ai

2017-01-01

The fuel cell used in transportation has environmental protection, high efficiency and no line traction power system which can greatly reduce line construction investment. That makes it a huge potential. The voltage uniformity is one of the most important factors affecting the operation life of proton exchange membrane fuel cell (PEMFC). On the basis of principle and classical model of the PEMFC, single cell voltage is calculated and the location coefficients are introduced so as to establish a non-uniformity voltage model. These coefficients are estimated with the experimental datum at stack current 50 A. The model is validated respectively with datum at 60 A and 100 A. The results show that the model reflects the basic characteristics of voltage non-uniformity and provides the beneficial reference for fuel cell control and single cell voltage detection.

A mathematical model for mesenchymal and chemosensitive cell dynamics.

PubMed

Häcker, Anita

2012-01-01

The structure of an underlying tissue network has a strong impact on cell dynamics. If, in addition, cells alter the network by mechanical and chemical interactions, their movement is called mesenchymal. Important examples for mesenchymal movement include fibroblasts in wound healing and metastatic tumour cells. This paper is focused on the latter. Based on the anisotropic biphasic theory of Barocas and Tranquillo, which models a fibre network and interstitial solution as two-component fluid, a mathematical model for the interactions of cells with a fibre network is developed. A new description for fibre reorientation is given and orientation-dependent proteolysis is added to the model. With respect to cell dynamics, the equation, based on anisotropic diffusion, is extended by haptotaxis and chemotaxis. The chemoattractants are the solute network fragments, emerging from proteolysis, and the epidermal growth factor which may guide the cells to a blood vessel. Moreover the cell migration is impeded at either high or low network density. This new model enables us to study chemotactic cell migration in a complex fibre network and the consequential network deformation. Numerical simulations for the cell migration and network deformation are carried out in two space dimensions. Simulations of cell migration in underlying tissue networks visualise the impact of the network structure on cell dynamics. In a scenario for fibre reorientation between cell clusters good qualitative agreement with experimental results is achieved. The invasion speeds of cells in an aligned and an isotropic fibre network are compared. © Springer-Verlag 2011

ODE constrained mixture modelling: a method for unraveling subpopulation structures and dynamics.

PubMed

Hasenauer, Jan; Hasenauer, Christine; Hucho, Tim; Theis, Fabian J

2014-07-01

Functional cell-to-cell variability is ubiquitous in multicellular organisms as well as bacterial populations. Even genetically identical cells of the same cell type can respond differently to identical stimuli. Methods have been developed to analyse heterogeneous populations, e.g., mixture models and stochastic population models. The available methods are, however, either incapable of simultaneously analysing different experimental conditions or are computationally demanding and difficult to apply. Furthermore, they do not account for biological information available in the literature. To overcome disadvantages of existing methods, we combine mixture models and ordinary differential equation (ODE) models. The ODE models provide a mechanistic description of the underlying processes while mixture models provide an easy way to capture variability. In a simulation study, we show that the class of ODE constrained mixture models can unravel the subpopulation structure and determine the sources of cell-to-cell variability. In addition, the method provides reliable estimates for kinetic rates and subpopulation characteristics. We use ODE constrained mixture modelling to study NGF-induced Erk1/2 phosphorylation in primary sensory neurones, a process relevant in inflammatory and neuropathic pain. We propose a mechanistic pathway model for this process and reconstructed static and dynamical subpopulation characteristics across experimental conditions. We validate the model predictions experimentally, which verifies the capabilities of ODE constrained mixture models. These results illustrate that ODE constrained mixture models can reveal novel mechanistic insights and possess a high sensitivity.

Mechanical behavior in living cells consistent with the tensegrity model

NASA Technical Reports Server (NTRS)

Wang, N.; Naruse, K.; Stamenovic, D.; Fredberg, J. J.; Mijailovich, S. M.; Tolic-Norrelykke, I. M.; Polte, T.; Mannix, R.; Ingber, D. E.

2001-01-01

Alternative models of cell mechanics depict the living cell as a simple mechanical continuum, porous filament gel, tensed cortical membrane, or tensegrity network that maintains a stabilizing prestress through incorporation of discrete structural elements that bear compression. Real-time microscopic analysis of cells containing GFP-labeled microtubules and associated mitochondria revealed that living cells behave like discrete structures composed of an interconnected network of actin microfilaments and microtubules when mechanical stresses are applied to cell surface integrin receptors. Quantitation of cell tractional forces and cellular prestress by using traction force microscopy confirmed that microtubules bear compression and are responsible for a significant portion of the cytoskeletal prestress that determines cell shape stability under conditions in which myosin light chain phosphorylation and intracellular calcium remained unchanged. Quantitative measurements of both static and dynamic mechanical behaviors in cells also were consistent with specific a priori predictions of the tensegrity model. These findings suggest that tensegrity represents a unified model of cell mechanics that may help to explain how mechanical behaviors emerge through collective interactions among different cytoskeletal filaments and extracellular adhesions in living cells.

Simulation study of GaAsP/Si tandem cells including the impact of threading dislocations on the luminescent coupling between the cells

NASA Astrophysics Data System (ADS)

Onno, Arthur; Harder, Nils-Peter; Oberbeck, Lars; Liu, Huiyun

2016-03-01

A model, derived from the detailed balance model from Shockley and Queisser, has been adapted to monolithically grown GaAsP/Si tandem dual junction solar cells. In this architecture, due to the difference of lattice parameters between the silicon bottom cell - acting as the substrate - and the GaAsP top cell, threading dislocations (TDs) arise at the IIIV/ Si interface and propagate in the top cell. These TDs act as non-radiative recombination centers, degrading the performances of the tandem cell. Our model takes into account the impact of TDs by integrating the NTT model developed by Yamaguchi et. al.. Two surface geometries have been investigated: flat and ideally textured. Finally the model considers the luminescent coupling (LC) between the cells due to reemitted photons from the top cell cascading to the bottom cell. Without dislocations, LC allows a greater flexibility in the cell design by rebalancing the currents between the two cells when the top cell presents a higher short-circuit current. However we show that, as the TD density (TDD) increases, nonradiative recombinations take over radiative recombinations in the top cell and the LC is quenched. As a result, nonoptimized tandem cells with higher short-circuit current in the top cell experience a very fast degradation of efficiency for TDDs over 104cm-2. On the other hand optimized cells with matching currents only experience a small efficiency drop for TDDs up to 105cm-2. High TDD cells therefore need to be current-matched for optimal performances as the flexibility due to LC is lost.

A model of the effects of cancer cell motility and cellular adhesion properties on tumour-immune dynamics.

PubMed

Frascoli, Federico; Flood, Emelie; Kim, Peter S

2017-06-01

We present a three-dimensional model simulating the dynamics of an anti-cancer T-cell response against a small, avascular, early-stage tumour. Interactions at the tumour site are accounted for using an agent-based model (ABM), while immune cell dynamics in the lymph node are modelled as a system of delay differential equations (DDEs). We combine these separate approaches into a two-compartment hybrid ABM-DDE system to capture the T-cell response against the tumour. In the ABM at the tumour site, movement of tumour cells is modelled using effective physical forces with a specific focus on cell-to-cell adhesion properties and varying levels of tumour cell motility, thus taking into account the ability of cancer cells to spread and form clusters. We consider the effectiveness of the immune response over a range of parameters pertaining to tumour cell motility, cell-to-cell adhesion strength and growth rate. We also investigate the dependence of outcomes on the distribution of tumour cells. Low tumour cell motility is generally a good indicator for successful tumour eradication before relapse, while high motility leads, almost invariably, to relapse and tumour escape. In general, the effect of cell-to-cell adhesion on prognosis is dependent on the level of tumour cell motility, with an often unpredictable cross influence between adhesion and motility, which can lead to counterintuitive effects. In terms of overall tumour shape and structure, the spatial distribution of cancer cells in clusters of various sizes has shown to be strongly related to the likelihood of extinction. © The authors 2016. Published by Oxford University Press on behalf of the Institute of Mathematics and its Applications. All rights reserved.

Rapid high-throughput characterisation, classification and selection of recombinant mammalian cell line phenotypes using intact cell MALDI-ToF mass spectrometry fingerprinting and PLS-DA modelling.

PubMed

Povey, Jane F; O'Malley, Christopher J; Root, Tracy; Martin, Elaine B; Montague, Gary A; Feary, Marc; Trim, Carol; Lang, Dietmar A; Alldread, Richard; Racher, Andrew J; Smales, C Mark

2014-08-20

Despite many advances in the generation of high producing recombinant mammalian cell lines over the last few decades, cell line selection and development is often slowed by the inability to predict a cell line's phenotypic characteristics (e.g. growth or recombinant protein productivity) at larger scale (large volume bioreactors) using data from early cell line construction at small culture scale. Here we describe the development of an intact cell MALDI-ToF mass spectrometry fingerprinting method for mammalian cells early in the cell line construction process whereby the resulting mass spectrometry data are used to predict the phenotype of mammalian cell lines at larger culture scale using a Partial Least Squares Discriminant Analysis (PLS-DA) model. Using MALDI-ToF mass spectrometry, a library of mass spectrometry fingerprints was generated for individual cell lines at the 96 deep well plate stage of cell line development. The growth and productivity of these cell lines were evaluated in a 10L bioreactor model of Lonza's large-scale (up to 20,000L) fed-batch cell culture processes. Using the mass spectrometry information at the 96 deep well plate stage and phenotype information at the 10L bioreactor scale a PLS-DA model was developed to predict the productivity of unknown cell lines at the 10L scale based upon their MALDI-ToF fingerprint at the 96 deep well plate scale. This approach provides the basis for the very early prediction of cell lines' performance in cGMP manufacturing-scale bioreactors and the foundation for methods and models for predicting other mammalian cell phenotypes from rapid, intact-cell mass spectrometry based measurements. Copyright © 2014 Elsevier B.V. All rights reserved.

A Comprehensive Fluid Dynamic-Diffusion Model of Blood Microcirculation with Focus on Sickle Cell Disease

NASA Astrophysics Data System (ADS)

Le Floch, Francois; Harris, Wesley L.

2009-11-01

A novel methodology has been developed to address sickle cell disease, based on highly descriptive mathematical models for blood flow in the capillaries. Our investigations focus on the coupling between oxygen delivery and red blood cell dynamics, which is crucial to understanding sickle cell crises and is unique to this blood disease. The main part of our work is an extensive study of blood dynamics through simulations of red cells deforming within the capillary vessels, and relies on the use of a large mathematical system of equations describing oxygen transfer, blood plasma dynamics and red cell membrane mechanics. This model is expected to lead to the development of new research strategies for sickle cell disease. Our simulation model could be used not only to assess current researched remedies, but also to spur innovative research initiatives, based on our study of the physical properties coupled in sickle cell disease.

[The implementation of computer model in research of dynamics of proliferation of cells of thyroid gland follicle].

PubMed

Abduvaliev, A A; Gil'dieva, M S; Khidirov, B N; Saĭdalieva, M; Khasanov, A A; Musaeva, Sh N; Saatov, T S

2012-04-01

The article deals with the results of computational experiments in research of dynamics of proliferation of cells of thyroid gland follicle in normal condition and in the case of malignant neoplasm. The model studies demonstrated that the chronic increase of parameter of proliferation of cells of thyroid gland follicle results in abnormal behavior of numbers of cell cenosis of thyroid gland follicle. The stationary state interrupts, the auto-oscillations occur with transition to irregular oscillations with unpredictable cell proliferation and further to the "black hole" effect. It is demonstrated that the present medical biologic experimental data and theory propositions concerning the structural functional organization of thyroid gland on cell level permit to develop mathematical models for quantitative analysis of numbers of cell cenosis of thyroid gland follicle in normal conditions. The technique of modeling of regulative mechanisms of living systems and equations of cell cenosis regulations was used

Random blebbing motion: A simple model linking cell structural properties to migration characteristics.

PubMed

Woolley, Thomas E; Gaffney, Eamonn A; Goriely, Alain

2017-07-01

If the plasma membrane of a cell is able to delaminate locally from its actin cortex, a cellular bleb can be produced. Blebs are pressure-driven protrusions, which are noteworthy for their ability to produce cellular motion. Starting from a general continuum mechanics description, we restrict ourselves to considering cell and bleb shapes that maintain approximately spherical forms. From this assumption, we obtain a tractable algebraic system for bleb formation. By including cell-substrate adhesions, we can model blebbing cell motility. Further, by considering mechanically isolated blebbing events, which are randomly distributed over the cell, we can derive equations linking the macroscopic migration characteristics to the microscopic structural parameters of the cell. This multiscale modeling framework is then used to provide parameter estimates, which are in agreement with current experimental data. In summary, the construction of the mathematical model provides testable relationships between the bleb size and cell motility.

A comprehensive model of the spatio-temporal stem cell and tissue organisation in the intestinal crypt.

PubMed

Buske, Peter; Galle, Jörg; Barker, Nick; Aust, Gabriela; Clevers, Hans; Loeffler, Markus

2011-01-06

We introduce a novel dynamic model of stem cell and tissue organisation in murine intestinal crypts. Integrating the molecular, cellular and tissue level of description, this model links a broad spectrum of experimental observations encompassing spatially confined cell proliferation, directed cell migration, multiple cell lineage decisions and clonal competition.Using computational simulations we demonstrate that the model is capable of quantitatively describing and predicting the dynamic behaviour of the intestinal tissue during steady state as well as after cell damage and following selective gain or loss of gene function manipulations affecting Wnt- and Notch-signalling. Our simulation results suggest that reversibility and flexibility of cellular decisions are key elements of robust tissue organisation of the intestine. We predict that the tissue should be able to fully recover after complete elimination of cellular subpopulations including subpopulations deemed to be functional stem cells. This challenges current views of tissue stem cell organisation.

Development of suspension cell culture model to mimic circulating tumor cells

PubMed Central

Park, Ji Young; Jeong, Ae Lee; Joo, Hyun Jeong; Han, Sora; Kim, So-Hyun; Kim, Hye-Youn; Lim, Jong-Seok; Lee, Myeong-Sok; Choi, Hyung-Kyoon; Yang, Young

2018-01-01

Circulating tumor cells (CTCs) are essential for the establishment of distant metastasis. Numerous studies have characterized CTCs as metastatic precursors; however, the molecular nature of CTCs has not been completely revealed yet due to the low number of CTCs in the blood stream. As an alternative approach, we developed a long-term suspension cell culture model using human breast cancer cell lines to mimic CTCs. We found that more than 40 passaged suspension cells acquired the ability to enhance metastasis like cancer stem cells. To identify molecular changes acquired during the suspension cell culture, we analyzed metabolic and lipidomic profiles as well as transcriptome in MDA-MB-468 suspension cells. Glutamate and leucine levels increased in suspension cells, and cholesterol synthesis pathway was altered. The inhibition of glutamate metabolic pathway decreased the proliferation of suspension cells compared to that of adherent cells. In the lipidomic profile, PC species containing long chain and polyunsaturated fatty acids increased in suspension cells and these species could be authentic and specific biomarkers for highly metastatic cancers. As this CTC-mimicking suspension cell culture model may easily apply to various types of cancer, we suggest this model as a great tool to develop therapeutic targets and drugs to eradicate metastatic cancer cells. PMID:29416640

A multi scale multi-dimensional thermo electrochemical modelling of high capacity lithium-ion cells

NASA Astrophysics Data System (ADS)

Tourani, Abbas; White, Peter; Ivey, Paul

2014-06-01

Lithium iron phosphate (LFP) and lithium manganese oxide (LMO) are competitive and complementary to each other as cathode materials for lithium-ion batteries, especially for use in electric vehicles. A multi scale multi-dimensional physic-based model is proposed in this paper to study the thermal behaviour of the two lithium-ion chemistries. The model consists of two sub models, a one dimensional (1D) electrochemical sub model and a two dimensional (2D) thermo-electric sub model, which are coupled and solved concurrently. The 1D model predicts the heat generation rate (Qh) and voltage (V) of the battery cell through different load cycles. The 2D model of the battery cell accounts for temperature distribution and current distribution across the surface of the battery cell. The two cells are examined experimentally through 90 h load cycles including high/low charge/discharge rates. The experimental results are compared with the model results and they are in good agreement. The presented results in this paper verify the cells temperature behaviour at different operating conditions which will lead to the design of a cost effective thermal management system for the battery pack.

Identifying mechanisms for superdiffusive dynamics in cell trajectories

NASA Astrophysics Data System (ADS)

Passucci, Giuseppe; Brasch, Megan; Henderson, James; Manning, M. Lisa

Self-propelled particle (SPP) models have been used to explore features of active matter such as motility-induced phase separation, jamming, and flocking, and are often used to model biological cells. However, many cells exhibit super-diffusive trajectories, where displacements scale faster than t 1 / 2 in all directions, and these are not captured by traditional SPP models. We extract cell trajectories from image stacks of mouse fibroblast cells moving on 2D substrates and find super-diffusive mean-squared displacements in all directions across varying densities. Two SPP model modifications have been proposed to capture super-diffusive dynamics: Levy walks and heterogeneous motility parameters. In mouse fibroblast cells displacement probability distributions collapse when time is rescaled by a power greater than 1/2, which is consistent with Levy walks. We show that a simple SPP model with heterogeneous rotational noise can also generate a similar collapse. Furthermore, a close examination of statistics extracted directly from cell trajectories is consistent with a heterogeneous mobility SPP model and inconsistent with a Levy walk model. Our work demonstrates that a simple set of analyses can distinguish between mechanisms for anomalous diffusion in active matter.

Cellular modelling of secondary radial growth in conifer trees: application to Pinus radiata (D. Don).

PubMed

Forest, Loïc; Demongeot, Jacques; Demongeota, Jacques

2006-05-01

The radial growth of conifer trees proceeds from the dynamics of a merismatic tissue called vascular cambium or cambium. Cambium is a thin layer of active proliferating cells. The purpose of this paper was to model the main characteristics of cambial activity and its consecutive radial growth. Cell growth is under the control of the auxin hormone indole-3-acetic. The model is composed of a discrete part, which accounts for cellular proliferation, and a continuous part involving the transport of auxin. Cambium is modeled in a two-dimensional cross-section by a cellular automaton that describes the set of all its constitutive cells. Proliferation is defined as growth and division of cambial cells under neighbouring constraints, which can eliminate some cells from the cambium. The cell-growth rate is determined from auxin concentration, calculated with the continuous model. We studied the integration of each elementary cambial cell activity into the global coherent movement of macroscopic morphogenesis. Cases of normal and abnormal growth of Pinus radiata (D. Don) are modelled. Abnormal growth includes deformed trees where gravity influences auxin transport, producing heterogeneous radial growth. Cross-sectional microscopic views are also provided to validate the model's hypothesis and results.

An "age"-structured model of hematopoietic stem cell organization with application to chronic myeloid leukemia.

PubMed

Roeder, Ingo; Herberg, Maria; Horn, Matthias

2009-04-01

Previously, we have modeled hematopoietic stem cell organization by a stochastic, single cell-based approach. Applications to different experimental systems demonstrated that this model consistently explains a broad variety of in vivo and in vitro data. A major advantage of the agent-based model (ABM) is the representation of heterogeneity within the hematopoietic stem cell population. However, this advantage comes at the price of time-consuming simulations if the systems become large. One example in this respect is the modeling of disease and treatment dynamics in patients with chronic myeloid leukemia (CML), where the realistic number of individual cells to be considered exceeds 10(6). To overcome this deficiency, without losing the representation of the inherent heterogeneity of the stem cell population, we here propose to approximate the ABM by a system of partial differential equations (PDEs). The major benefit of such an approach is its independence from the size of the system. Although this mean field approach includes a number of simplifying assumptions compared to the ABM, it retains the key structure of the model including the "age"-structure of stem cells. We show that the PDE model qualitatively and quantitatively reproduces the results of the agent-based approach.

The Cell Collective: Toward an open and collaborative approach to systems biology

PubMed Central

2012-01-01

Background Despite decades of new discoveries in biomedical research, the overwhelming complexity of cells has been a significant barrier to a fundamental understanding of how cells work as a whole. As such, the holistic study of biochemical pathways requires computer modeling. Due to the complexity of cells, it is not feasible for one person or group to model the cell in its entirety. Results The Cell Collective is a platform that allows the world-wide scientific community to create these models collectively. Its interface enables users to build and use models without specifying any mathematical equations or computer code - addressing one of the major hurdles with computational research. In addition, this platform allows scientists to simulate and analyze the models in real-time on the web, including the ability to simulate loss/gain of function and test what-if scenarios in real time. Conclusions The Cell Collective is a web-based platform that enables laboratory scientists from across the globe to collaboratively build large-scale models of various biological processes, and simulate/analyze them in real time. In this manuscript, we show examples of its application to a large-scale model of signal transduction. PMID:22871178

Mechanical Model of Geometric Cell and Topological Algorithm for Cell Dynamics from Single-Cell to Formation of Monolayered Tissues with Pattern

PubMed Central

Kachalo, Sëma; Naveed, Hammad; Cao, Youfang; Zhao, Jieling; Liang, Jie

2015-01-01

Geometric and mechanical properties of individual cells and interactions among neighboring cells are the basis of formation of tissue patterns. Understanding the complex interplay of cells is essential for gaining insight into embryogenesis, tissue development, and other emerging behavior. Here we describe a cell model and an efficient geometric algorithm for studying the dynamic process of tissue formation in 2D (e.g. epithelial tissues). Our approach improves upon previous methods by incorporating properties of individual cells as well as detailed description of the dynamic growth process, with all topological changes accounted for. Cell size, shape, and division plane orientation are modeled realistically. In addition, cell birth, cell growth, cell shrinkage, cell death, cell division, cell collision, and cell rearrangements are now fully accounted for. Different models of cell-cell interactions, such as lateral inhibition during the process of growth, can be studied in detail. Cellular pattern formation for monolayered tissues from arbitrary initial conditions, including that of a single cell, can also be studied in detail. Computational efficiency is achieved through the employment of a special data structure that ensures access to neighboring cells in constant time, without additional space requirement. We have successfully generated tissues consisting of more than 20,000 cells starting from 2 cells within 1 hour. We show that our model can be used to study embryogenesis, tissue fusion, and cell apoptosis. We give detailed study of the classical developmental process of bristle formation on the epidermis of D. melanogaster and the fundamental problem of homeostatic size control in epithelial tissues. Simulation results reveal significant roles of solubility of secreted factors in both the bristle formation and the homeostatic control of tissue size. Our method can be used to study broad problems in monolayered tissue formation. Our software is publicly available. PMID:25974182

In vitro models of the blood–brain barrier: An overview of commonly used brain endothelial cell culture models and guidelines for their use

PubMed Central

Helms, Hans C; Abbott, N Joan; Burek, Malgorzata; Cecchelli, Romeo; Couraud, Pierre-Olivier; Deli, Maria A; Förster, Carola; Galla, Hans J; Romero, Ignacio A; Shusta, Eric V; Stebbins, Matthew J; Vandenhaute, Elodie; Weksler, Babette

2016-01-01

The endothelial cells lining the brain capillaries separate the blood from the brain parenchyma. The endothelial monolayer of the brain capillaries serves both as a crucial interface for exchange of nutrients, gases, and metabolites between blood and brain, and as a barrier for neurotoxic components of plasma and xenobiotics. This “blood-brain barrier” function is a major hindrance for drug uptake into the brain parenchyma. Cell culture models, based on either primary cells or immortalized brain endothelial cell lines, have been developed, in order to facilitate in vitro studies of drug transport to the brain and studies of endothelial cell biology and pathophysiology. In this review, we aim to give an overview of established in vitro blood–brain barrier models with a focus on their validation regarding a set of well-established blood–brain barrier characteristics. As an ideal cell culture model of the blood–brain barrier is yet to be developed, we also aim to give an overview of the advantages and drawbacks of the different models described. PMID:26868179

Current State-of-the-Art 3D Tissue Models and Their Compatibility with Live Cell Imaging.

PubMed

Bardsley, Katie; Deegan, Anthony J; El Haj, Alicia; Yang, Ying

2017-01-01

Mammalian cells grow within a complex three-dimensional (3D) microenvironment where multiple cells are organized and surrounded by extracellular matrix (ECM). The quantity and types of ECM components, alongside cell-to-cell and cell-to-matrix interactions dictate cellular differentiation, proliferation and function in vivo. To mimic natural cellular activities, various 3D tissue culture models have been established to replace conventional two dimensional (2D) culture environments. Allowing for both characterization and visualization of cellular activities within possibly bulky 3D tissue models presents considerable challenges due to the increased thickness and subsequent light scattering features of such 3D models. In this chapter, state-of-the-art methodologies used to establish 3D tissue models are discussed, first with a focus on both scaffold-free and scaffold-based 3D tissue model formation. Following on, multiple 3D live cell imaging systems, mainly optical imaging modalities, are introduced. Their advantages and disadvantages are discussed, with the aim of stimulating more research in this highly demanding research area.

Tailoring Mathematical Models to Stem-Cell Derived Cardiomyocyte Lines Can Improve Predictions of Drug-Induced Changes to Their Electrophysiology.

PubMed

Lei, Chon Lok; Wang, Ken; Clerx, Michael; Johnstone, Ross H; Hortigon-Vinagre, Maria P; Zamora, Victor; Allan, Andrew; Smith, Godfrey L; Gavaghan, David J; Mirams, Gary R; Polonchuk, Liudmila

2017-01-01

Human induced pluripotent stem cell derived cardiomyocytes (iPSC-CMs) have applications in disease modeling, cell therapy, drug screening and personalized medicine. Computational models can be used to interpret experimental findings in iPSC-CMs, provide mechanistic insights, and translate these findings to adult cardiomyocyte (CM) electrophysiology. However, different cell lines display different expression of ion channels, pumps and receptors, and show differences in electrophysiology. In this exploratory study, we use a mathematical model based on iPSC-CMs from Cellular Dynamic International (CDI, iCell), and compare its predictions to novel experimental recordings made with the Axiogenesis Cor.4U line. We show that tailoring this model to the specific cell line, even using limited data and a relatively simple approach, leads to improved predictions of baseline behavior and response to drugs. This demonstrates the need and the feasibility to tailor models to individual cell lines, although a more refined approach will be needed to characterize individual currents, address differences in ion current kinetics, and further improve these results.

A novel 3D mesenchymal stem cell model of the multiple myeloma bone marrow niche: biologic and clinical applications

PubMed Central

Jakubikova, Jana; Cholujova, Danka; Hideshima, Teru; Gronesova, Paulina; Soltysova, Andrea; Harada, Takeshi; Joo, Jungnam; Kong, Sun-Young; Szalat, Raphael E.; Richardson, Paul G.; Munshi, Nikhil C.; Dorfman, David M.; Anderson, Kenneth C.

2016-01-01

Specific niches within the tumor bone marrow (BM) microenvironment afford a sanctuary for multiple myeloma (MM) clones due to stromal cell-tumor cell interactions, which confer survival advantage and drug resistance. Defining the sequelae of tumor cell interactions within the MM niches on an individualized basis may provide the rationale for personalized therapies. To mimic the MM niche, we here describe a new 3D co-culture ex-vivo model in which primary MM patient BM cells are co-cultured with mesenchymal stem cells (MSC) in a hydrogel 3D system. In the 3D model, MSC with conserved phenotype (CD73+CD90+CD105+) formed compact clusters with active fibrous connections, and retained lineage differentiation capacity. Extracellular matrix molecules, integrins, and niche related molecules including N-cadherin and CXCL12 are expressed in 3D MSC model. Furthermore, activation of osteogenesis (MMP13, SPP1, ADAMTS4, and MGP genes) and osteoblastogenic differentiation was confirmed in 3D MSC model. Co-culture of patient-derived BM mononuclear cells with either autologous or allogeneic MSC in 3D model increased proliferation of MM cells, CXCR4 expression, and SP cells. We carried out immune profiling to show that distribution of immune cell subsets was similar in 3D and 2D MSC model systems. Importantly, resistance to novel agents (IMiDs, bortezomib, carfilzomib) and conventional agents (doxorubicin, dexamethasone, melphalan) was observed in 3D MSC system, reflective of clinical resistance. This 3D MSC model may therefore allow for studies of MM pathogenesis and drug resistance within the BM niche. Importantly, ongoing prospective trials are evaluating its utility to inform personalized targeted and immune therapy in MM. PMID:27764795

Models of germ cell development and their application for toxicity studies

PubMed Central

Ferreira, Daniel W.; Allard, Patrick

2015-01-01

Germ cells are unique in their ability to transfer genetic information and traits from generation to generation. As such, the proper development of germ cells and the integrity of their genome are paramount to the health of organisms and the survival of species. Germ cells are also exquisitely sensitive to environmental influences although the testing of germ cell toxicity, especially in females, has proven particularly challenging. In this review, we first describe the remarkable odyssey of germ cells in mammals, with an emphasis on the female germline, from their initial specification during embryogenesis to the generation of mature gametes in adults. We also describe the current methods used in germ cell toxicity testing and their limitations in examining the complex features of mammalian germ cell development. To bypass these challenges, we propose the use of alternative model systems such as Saccharomyces cerevisiae, Drosophila melanogaster, Caenorhabditis elegans and in vitro germ cell methods that have distinct advantages over traditional toxicity models. We discuss the benefits and limitations of each approach, their application to germ cell toxicity studies, and the need for computational approaches to maximize the usefulness of these models. Together, the inclusion of these alternative germ cell toxicity models will be invaluable for the examination of stages not easily accessible in mammals as well as the large scale, high-throughput investigation of germ cell toxicity. PMID:25821157

Hybrid multiscale modeling and prediction of cancer cell behavior

PubMed Central

Habibi, Jafar

2017-01-01

Background Understanding cancer development crossing several spatial-temporal scales is of great practical significance to better understand and treat cancers. It is difficult to tackle this challenge with pure biological means. Moreover, hybrid modeling techniques have been proposed that combine the advantages of the continuum and the discrete methods to model multiscale problems. Methods In light of these problems, we have proposed a new hybrid vascular model to facilitate the multiscale modeling and simulation of cancer development with respect to the agent-based, cellular automata and machine learning methods. The purpose of this simulation is to create a dataset that can be used for prediction of cell phenotypes. By using a proposed Q-learning based on SVR-NSGA-II method, the cells have the capability to predict their phenotypes autonomously that is, to act on its own without external direction in response to situations it encounters. Results Computational simulations of the model were performed in order to analyze its performance. The most striking feature of our results is that each cell can select its phenotype at each time step according to its condition. We provide evidence that the prediction of cell phenotypes is reliable. Conclusion Our proposed model, which we term a hybrid multiscale modeling of cancer cell behavior, has the potential to combine the best features of both continuum and discrete models. The in silico results indicate that the 3D model can represent key features of cancer growth, angiogenesis, and its related micro-environment and show that the findings are in good agreement with biological tumor behavior. To the best of our knowledge, this paper is the first hybrid vascular multiscale modeling of cancer cell behavior that has the capability to predict cell phenotypes individually by a self-generated dataset. PMID:28846712

Hybrid multiscale modeling and prediction of cancer cell behavior.

PubMed

Zangooei, Mohammad Hossein; Habibi, Jafar

2017-01-01

Understanding cancer development crossing several spatial-temporal scales is of great practical significance to better understand and treat cancers. It is difficult to tackle this challenge with pure biological means. Moreover, hybrid modeling techniques have been proposed that combine the advantages of the continuum and the discrete methods to model multiscale problems. In light of these problems, we have proposed a new hybrid vascular model to facilitate the multiscale modeling and simulation of cancer development with respect to the agent-based, cellular automata and machine learning methods. The purpose of this simulation is to create a dataset that can be used for prediction of cell phenotypes. By using a proposed Q-learning based on SVR-NSGA-II method, the cells have the capability to predict their phenotypes autonomously that is, to act on its own without external direction in response to situations it encounters. Computational simulations of the model were performed in order to analyze its performance. The most striking feature of our results is that each cell can select its phenotype at each time step according to its condition. We provide evidence that the prediction of cell phenotypes is reliable. Our proposed model, which we term a hybrid multiscale modeling of cancer cell behavior, has the potential to combine the best features of both continuum and discrete models. The in silico results indicate that the 3D model can represent key features of cancer growth, angiogenesis, and its related micro-environment and show that the findings are in good agreement with biological tumor behavior. To the best of our knowledge, this paper is the first hybrid vascular multiscale modeling of cancer cell behavior that has the capability to predict cell phenotypes individually by a self-generated dataset.

Intracellular Fluid Mechanics: Coupling Cytoplasmic Flow with Active Cytoskeletal Gel

NASA Astrophysics Data System (ADS)

Mogilner, Alex; Manhart, Angelika

2018-01-01

The cell is a mechanical machine, and continuum mechanics of the fluid cytoplasm and the viscoelastic deforming cytoskeleton play key roles in cell physiology. We review mathematical models of intracellular fluid mechanics, from cytoplasmic fluid flows, to the flow of a viscous active cytoskeletal gel, to models of two-phase poroviscous flows, to poroelastic models. We discuss application of these models to cell biological phenomena, such as organelle positioning, blebbing, and cell motility. We also discuss challenges of understanding fluid mechanics on the cellular scale.

Field-aligned currents and magnetospheric convection - A comparison between MHD simulations and observations

NASA Technical Reports Server (NTRS)

Walker, Raymond J.; Ogino, Tatsuki

1988-01-01

A time-dependent three-dimensional MHD model was used to investigate the magnetospheric configuration as a function of the interplanetary magnetic field direction when it was in the y-z plane in geocentric solar magnetospheric coordinates. The model results show large global convection cells, tail lobe cells, high-latitude polarcap cells, and low latitude cells. The field-aligned currents generated in the model magnetosphere and the model convection system are compared with observations from low-altitude polar orbiting satellites.

Temporally structured replay of neural activity in a model of entorhinal cortex, hippocampus and postsubiculum

PubMed Central

Hasselmo, Michael E.

2008-01-01

The spiking activity of hippocampal neurons during REM sleep exhibits temporally structured replay of spiking occurring during previously experienced trajectories (Louie and Wilson, 2001). Here, temporally structured replay of place cell activity during REM sleep is modeled in a large-scale network simulation of grid cells, place cells and head direction cells. During simulated waking behavior, the movement of the simulated rat drives activity of a population of head direction cells that updates the activity of a population of entorhinal grid cells. The population of grid cells drives the activity of place cells coding individual locations. Associations between location and movement direction are encoded by modification of excitatory synaptic connections from place cells to speed modulated head direction cells. During simulated REM sleep, the population of place cells coding an experienced location activates the head direction cells coding the associated movement direction. Spiking of head direction cells then causes frequency shifts within the population of entorhinal grid cells to update a phase representation of location. Spiking grid cells then activate new place cells that drive new head direction activity. In contrast to models that perform temporally compressed sequence retrieval similar to sharp wave activity, this model can simulate data on temporally structured replay of hippocampal place cell activity during REM sleep at time scales similar to those observed during waking. These mechanisms could be important for episodic memory of trajectories. PMID:18973557

Exposure of Microcystis aeruginosa to hydrogen peroxide and titanium dioxide under visible light conditions: Modeling the impact of hydrogen peroxide and hydroxyl radical on cell rupture and microcystin degradation.

PubMed

Chang, Che-Wei; Huo, Xiangchen; Lin, Tsair-Fuh

2018-05-14

The aims of this study are to evaluate, under visible light conditions, the ability of H 2 O 2 and TiO 2 to produce OH, their quantitative impacts on the cell integrity of Microcystis, and the subsequent release and degradation of microcystins (MCs). A sequential reaction model was developed, including one sub-model to simulate the rupture kinetics for cell integrity of Microcystis, and another to describe the release and degradation of MCs. For cell rupture, the dual-oxidant Delayed Chick-Watson model (DCWM) and dual-oxidant Hom model (HM) were first proposed and developed, giving excellent simulation results of cell rupture kinetics. Kinetic rate constants between Microcystis cells and H 2 O 2 [Formula: see text] as well as OH (k •OH, Cell ) under visible light successfully separated the individual effects of H 2 O 2 and OH on Microcystis. The dual-oxidant models were further validated with additional experiments, making the models more convincing. Finally, the dual-oxidant cell rupture models were integrated with the MC degradation model and well predicted the observed MCs concentrations in the experimental systems. The results of this study not only demonstrate the potential application of H 2 O 2 and TiO 2 for the control of cyanobacteria and metabolites in natural water bodies, but also provide a new methodology to differentiate the individual contributions of the two oxidants, H 2 O 2 and OH, on cell rupture, thus giving a novel way to more precisely determine the effective doses of applied oxidants for cyanobacteria control. Copyright © 2018 Elsevier Ltd. All rights reserved.

Analytical determination of critical crack size in solar cells

NASA Technical Reports Server (NTRS)

Chen, C. P.

1988-01-01

Although solar cells usually have chips and cracks, no material specifications concerning the allowable crack size on solar cells are available for quality assurance and engineering design usage. Any material specifications that the cell manufacturers use were developed for cosmetic reasons that have no technical basis. Therefore, the Applied Solar Energy Corporation (ASEC) has sponsored a continuing program for the fracture mechanics evaluation of GaAs. Fracture mechanics concepts were utilized to develop an analytical model that can predict the critical crack size of solar cells. This model indicates that the edge cracks of a solar cell are more critical than its surface cracks. In addition, the model suggests that the material specifications on the allowable crack size used for Si solar cells should not be applied to GaAs solar cells. The analytical model was applied to Si and GaAs solar cells, but it would also be applicable to the semiconductor wafers of other materials, such as a GaAs thin film on a Ge substrate, using appropriate input data.

Roles and regulations of Hippo signaling during preimplantation mouse development.

PubMed

Sasaki, Hiroshi

2017-01-01

During preimplantation development, mouse embryos form two types of cells, the trophoectoderm (TE) and inner cell mass (ICM), by the early blastocyst stage. This process does not require maternal factors localized in the zygotes, and embryos self-organize at the blastocyst stage through intercellular communications. In terms of the mechanisms of cell fate specification, three historical models have been proposed: the positional model, and the original and newer versions of the polarity model. Recent studies have revealed that the intercellular Hippo signaling pathway plays a central role in the specification of the first cell fates. Hippo signaling is active in the inner cells but inactive in the outer cells. The Hippo-active inner and Hippo-inactive outer cells take the fates of the ICM and the TE, respectively. At the 32-cell stage, E-cadherin-mediated cell-cell adhesion and cell polarization by the Par-aPKC system activates and inactivates the Hippo pathway, respectively. Both mechanisms involve regulation of angiomotin, and cooperation of these mechanisms establishes cell position-dependent activation of Hippo signaling. At the 16-cell stage, however, asymmetric cell division produces the initial differences in Hippo signaling. At this stage, cell polarity is controlled by both Par-aPKC-dependent and -independent mechanisms. All three historical models are explained by the different regulations and roles of Hippo signaling. Based on these findings, I would like to propose the model by which the differences in Hippo signaling among blastomeres is first produced by asymmetric cell division and then enhanced and stabilized by cell position-dependent mechanisms until their fates are fixed. © 2016 Japanese Society of Developmental Biologists.

Modeling Huntington׳s disease with patient-derived neurons.

PubMed

Mattis, Virginia B; Svendsen, Clive N

2017-02-01

Huntington׳s Disease (HD) is a fatal neurodegenerative disorder caused by expanded polyglutamine repeats in the Huntingtin (HTT) gene. While the gene was identified over two decades ago, it remains poorly understood why mutant HTT (mtHTT) is initially toxic to striatal medium spiny neurons (MSNs). Models of HD using non-neuronal human patient cells and rodents exhibit some characteristic HD phenotypes. While these current models have contributed to the field, they are limited in disease manifestation and may vary in their response to treatments. As such, human HD patient MSNs for disease modeling could greatly expand the current understanding of HD and facilitate the search for a successful treatment. It is now possible to use pluripotent stem cells, which can generate any tissue type in the body, to study and potentially treat HD. This review covers disease modeling in vitro and, via chimeric animal generation, in vivo using human HD patient MSNs differentiated from embryonic stem cells or induced pluripotent stem cells. This includes an overview of the differentiation of pluripotent cells into MSNs, the established phenotypes found in cell-based models and transplantation studies using these cells. This review not only outlines the advancements in the rapidly progressing field of HD modeling using neurons derived from human pluripotent cells, but also it highlights several remaining controversial issues such as the 'ideal' series of pluripotent lines, the optimal cell types to use and the study of a primarily adult-onset disease in a developmental model. This article is part of a Special Issue entitled SI: Exploiting human neurons. Copyright © 2015 Elsevier B.V. All rights reserved.

Continuum modeling of neuronal cell under blast loading

PubMed Central

Jérusalem, Antoine; Dao, Ming

2012-01-01

Traumatic brain injuries have recently been put under the spotlight as one of the most important causes of accidental brain dysfunctions. Significant experimental and modeling efforts are thus ongoing to study the associated biological, mechanical and physical mechanisms. In the field of cell mechanics, progresses are also being made at the experimental and modeling levels to better characterize many of the cell functions such as differentiation, growth, migration and death, among others. The work presented here aims at bridging both efforts by proposing a continuum model of neuronal cell submitted to blast loading. In this approach, cytoplasm, nucleus and membrane (plus cortex) are differentiated in a representative cell geometry, and different material constitutive models are adequately chosen for each one. The material parameters are calibrated against published experimental work of cell nanoindentation at multiple rates. The final cell model is ultimately subjected to blast loading within a complete fluid-structure interaction computational framework. The results are compared to the nanoindentation simulation and the specific effects of the blast wave on the pressure and shear levels at the interfaces are identified. As a conclusion, the presented model successfully captures some of the intrinsic intracellular phenomena occurring during its deformation under blast loading and potentially leading to cell damage. It suggests more particularly the localization of damage at the nucleus membrane similarly to what has already been observed at the overall cell membrane. This degree of damage is additionally predicted to be worsened by a longer blast positive phase duration. As a conclusion, the proposed model ultimately provides a new three dimensional computational tool to evaluate intracellular damage during blast loading. PMID:22562014

Three-dimensional finite element modeling of pericellular matrix and cell mechanics in the nucleus pulposus of the intervertebral disk based on in situ morphology.

PubMed

Cao, Li; Guilak, Farshid; Setton, Lori A

2011-02-01

Nucleus pulposus (NP) cells of the intervertebral disk (IVD) have unique morphological characteristics and biologic responses to mechanical stimuli that may regulate maintenance and health of the IVD. NP cells reside as single cell, paired or multiple cells in a contiguous pericellular matrix (PCM), whose structure and properties may significantly influence cell and extracellular matrix mechanics. In this study, a computational model was developed to predict the stress-strain, fluid pressure and flow fields for cells and their surrounding PCM in the NP using three-dimensional (3D) finite element models based on the in situ morphology of cell-PCM regions of the mature rat NP, measured using confocal microscopy. Three-dimensional geometries of the extracellular matrix and representative cell-matrix units were used to construct 3D finite element models of the structures as isotropic and biphasic materials. In response to compressive strain of the extracellular matrix, NP cells and PCM regions were predicted to experience volumetric strains that were 1.9-3.7 and 1.4-2.1 times greater than the extracellular matrix, respectively. Volumetric and deviatoric strain concentrations were generally found at the cell/PCM interface, while von Mises stress concentrations were associated with the PCM/extracellular matrix interface. Cell-matrix units containing greater cell numbers were associated with higher peak cell strains and lower rates of fluid pressurization upon loading. These studies provide new model predictions for micromechanics of NP cells that can contribute to an understanding of mechanotransduction in the IVD and its changes with aging and degeneration.

Mechanical positioning of multiple nuclei in muscle cells.

PubMed

Manhart, Angelika; Windner, Stefanie; Baylies, Mary; Mogilner, Alex

2018-06-01

Many types of large cells have multiple nuclei. In skeletal muscle fibers, the nuclei are distributed along the cell to maximize their internuclear distances. This myonuclear positioning is crucial for cell function. Although microtubules, microtubule associated proteins, and motors have been implicated, mechanisms responsible for myonuclear positioning remain unclear. We used a combination of rough interacting particle and detailed agent-based modeling to examine computationally the hypothesis that a force balance generated by microtubules positions the muscle nuclei. Rather than assuming the nature and identity of the forces, we simulated various types of forces between the pairs of nuclei and between the nuclei and cell boundary to position the myonuclei according to the laws of mechanics. We started with a large number of potential interacting particle models and computationally screened these models for their ability to fit biological data on nuclear positions in hundreds of Drosophila larval muscle cells. This reverse engineering approach resulted in a small number of feasible models, the one with the best fit suggests that the nuclei repel each other and the cell boundary with forces that decrease with distance. The model makes nontrivial predictions about the increased nuclear density near the cell poles, the zigzag patterns of the nuclear positions in wider cells, and about correlations between the cell width and elongated nuclear shapes, all of which we confirm by image analysis of the biological data. We support the predictions of the interacting particle model with simulations of an agent-based mechanical model. Taken together, our data suggest that microtubules growing from nuclear envelopes push on the neighboring nuclei and the cell boundaries, which is sufficient to establish the nearly-uniform nuclear spreading observed in muscle fibers.

Development of an in silico stochastic 4D model of tumor growth with angiogenesis.

PubMed

Forster, Jake C; Douglass, Michael J J; Harriss-Phillips, Wendy M; Bezak, Eva

2017-04-01

A stochastic computer model of tumour growth with spatial and temporal components that includes tumour angiogenesis was developed. In the current work it was used to simulate head and neck tumour growth. The model also provides the foundation for a 4D cellular radiotherapy simulation tool. The model, developed in Matlab, contains cell positions randomised in 3D space without overlap. Blood vessels are represented by strings of blood vessel units which branch outwards to achieve the desired tumour relative vascular volume. Hypoxic cells have an increased cell cycle time and become quiescent at oxygen tensions less than 1 mmHg. Necrotic cells are resorbed. A hierarchy of stem cells, transit cells and differentiated cells is considered along with differentiated cell loss. Model parameters include the relative vascular volume (2-10%), blood oxygenation (20-100 mmHg), distance from vessels to the onset of necrosis (80-300 μm) and probability for stem cells to undergo symmetric division (2%). Simulations were performed to observe the effects of hypoxia on tumour growth rate for head and neck cancers. Simulations were run on a supercomputer with eligible parts running in parallel on 12 cores. Using biologically plausible model parameters for head and neck cancers, the tumour volume doubling time varied from 45 ± 5 days (n = 3) for well oxygenated tumours to 87 ± 5 days (n = 3) for severely hypoxic tumours. The main achievements of the current model were randomised cell positions and the connected vasculature structure between the cells. These developments will also be beneficial when irradiating the simulated tumours using Monte Carlo track structure methods. © 2017 American Association of Physicists in Medicine.

Modeling dynamics of HIV infected cells using stochastic cellular automaton

NASA Astrophysics Data System (ADS)

Precharattana, Monamorn; Triampo, Wannapong

2014-08-01

Ever since HIV was first diagnosed in human, a great number of scientific works have been undertaken to explore the biological mechanisms involved in the infection and progression of the disease. Several cellular automata (CA) models have been introduced to gain insights into the dynamics of the disease progression but none of them has taken into account effects of certain immune cells such as the dendritic cells (DCs) and the CD8+ T lymphocytes (CD8+ T cells). In this work, we present a CA model, which incorporates effects of the HIV specific immune response focusing on the cell-mediated immunities, and investigate the interaction between the host immune response and the HIV infected cells in the lymph nodes. The aim of our work is to propose a model more realistic than the one in Precharattana et al. (2010) [10], by incorporating roles of the DCs, the CD4+ T cells, and the CD8+ T cells into the model so that it would reproduce the HIV infection dynamics during the primary phase of HIV infection.

A mathematical model of cancer stem cell driven tumor initiation: implications of niche size and loss of homeostatic regulatory mechanisms.

PubMed

Gentry, Sara N; Jackson, Trachette L

2013-01-01

Hierarchical organized tissue structures, with stem cell driven cell differentiation, are critical to the homeostatic maintenance of most tissues, and this underlying cellular architecture is potentially a critical player in the development of a many cancers. Here, we develop a mathematical model of mutation acquisition to investigate how deregulation of the mechanisms preserving stem cell homeostasis contributes to tumor initiation. A novel feature of the model is the inclusion of both extrinsic and intrinsic chemical signaling and interaction with the niche to control stem cell self-renewal. We use the model to simulate the effects of a variety of types and sequences of mutations and then compare and contrast all mutation pathways in order to determine which ones generate cancer cells fastest. The model predicts that the sequence in which mutations occur significantly affects the pace of tumorigenesis. In addition, tumor composition varies for different mutation pathways, so that some sequences generate tumors that are dominated by cancerous cells with all possible mutations, while others are primarily comprised of cells that more closely resemble normal cells with only one or two mutations. We are also able to show that, under certain circumstances, healthy stem cells diminish due to the displacement by mutated cells that have a competitive advantage in the niche. Finally, in the event that all homeostatic regulation is lost, exponential growth of the cancer population occurs in addition to the depletion of normal cells. This model helps to advance our understanding of how mutation acquisition affects mechanisms that influence cell-fate decisions and leads to the initiation of cancers.

A new level set model for cell image segmentation

NASA Astrophysics Data System (ADS)

Ma, Jing-Feng; Hou, Kai; Bao, Shang-Lian; Chen, Chun

2011-02-01

In this paper we first determine three phases of cell images: background, cytoplasm and nucleolus according to the general physical characteristics of cell images, and then develop a variational model, based on these characteristics, to segment nucleolus and cytoplasm from their relatively complicated backgrounds. In the meantime, the preprocessing obtained information of cell images using the OTSU algorithm is used to initialize the level set function in the model, which can speed up the segmentation and present satisfactory results in cell image processing.

Mathematical model for HIV dynamics in HIV-specific helper cells

NASA Astrophysics Data System (ADS)

Pinto, Carla M. A.; Carvalho, Ana

2014-03-01

In this paper we study a delay mathematical model for the dynamics of HIV in HIV-specific CD4 + T helper cells. We modify the model presented by Roy and Wodarz in 2012, where the HIV dynamics is studied, considering a single CD4 + T cell population. Non-specific helper cells are included as alternative target cell population, to account for macrophages and dendritic cells. In this paper, we include two types of delay: (1) a latent period between the time target cells are contacted by the virus particles and the time the virions enter the cells and; (2) virus production period for new virions to be produced within and released from the infected cells. We compute the reproduction number of the model, R0, and the local stability of the disease free equilibrium and of the endemic equilibrium. We find that for values of R0<1, the model approaches asymptotically the disease free equilibrium. For values of R0>1, the model approximates asymptotically the endemic equilibrium. We observe numerically the phenomenon of backward bifurcation for values of R0⪅1. This statement will be proved in future work. We also vary the values of the latent period and the production period of infected cells and free virus. We conclude that increasing these values translates in a decrease of the reproduction number. Thus, a good strategy to control the HIV virus should focus on drugs to prolong the latent period and/or slow down the virus production. These results suggest that the model is mathematically and epidemiologically well-posed.

Concise Review: Stem Cell Trials Using Companion Animal Disease Models.

PubMed

Hoffman, Andrew M; Dow, Steven W

2016-07-01

Studies to evaluate the therapeutic potential of stem cells in humans would benefit from more realistic animal models. In veterinary medicine, companion animals naturally develop many diseases that resemble human conditions, therefore, representing a novel source of preclinical models. To understand how companion animal disease models are being studied for this purpose, we reviewed the literature between 2008 and 2015 for reports on stem cell therapies in dogs and cats, excluding laboratory animals, induced disease models, cancer, and case reports. Disease models included osteoarthritis, intervertebral disc degeneration, dilated cardiomyopathy, inflammatory bowel diseases, Crohn's fistulas, meningoencephalomyelitis (multiple sclerosis-like), keratoconjunctivitis sicca (Sjogren's syndrome-like), atopic dermatitis, and chronic (end-stage) kidney disease. Stem cells evaluated in these studies included mesenchymal stem-stromal cells (MSC, 17/19 trials), olfactory ensheathing cells (OEC, 1 trial), or neural lineage cells derived from bone marrow MSC (1 trial), and 16/19 studies were performed in dogs. The MSC studies (13/17) used adipose tissue-derived MSC from either allogeneic (8/13) or autologous (5/13) sources. The majority of studies were open label, uncontrolled studies. Endpoints and protocols were feasible, and the stem cell therapies were reportedly safe and elicited beneficial patient responses in all but two of the trials. In conclusion, companion animals with naturally occurring diseases analogous to human conditions can be recruited into clinical trials and provide realistic insight into feasibility, safety, and biologic activity of novel stem cell therapies. However, improvements in the rigor of manufacturing, study design, and regulatory compliance will be needed to better utilize these models. Stem Cells 2016;34:1709-1729. © 2016 AlphaMed Press.

Cell Protrusion and Retraction Driven by Fluctuations in Actin Polymerization: A Two-Dimensional Model

PubMed Central

Ryan, Gillian L.; Holz, Danielle; Yamashiro, Sawako; Taniguchi, Daisuke; Watanabe, Naoki; Vavylonis, Dimitrios

2017-01-01

Animal cells that spread onto a surface often rely on actin-rich lamellipodial extensions to execute protrusion. Many cell types recently adhered on a two-dimensional substrate exhibit protrusion and retraction of their lamellipodia, even though the cell is not translating. Traveling waves of protrusion have also been observed, similar to those observed in crawling cells. These regular patterns of protrusion and retraction allow quantitative analysis for comparison to mathematical models. The periodic fluctuations in leading edge position of XTC cells have been linked to excitable actin dynamics using a one-dimensional model of actin dynamics, as a function of arc-length along the cell. In this work we extend this earlier model of actin dynamics into two dimensions (along the arc-length and radial directions of the cell) and include a model membrane that protrudes and retracts in response to the changing number of free barbed ends of actin filaments near the membrane. We show that if the polymerization rate at the barbed ends changes in response to changes in their local concentration at the leading edge and/or the opposing force from the cell membrane, the model can reproduce the patterns of membrane protrusion and retraction seen in experiment. We investigate both Brownian ratchet and switch-like force-velocity relationships between the membrane load forces and actin polymerization rate. The switch-like polymerization dynamics recover the observed patterns of protrusion and retraction as well as the fluctuations in F-actin concentration profiles. The model generates predictions for the behavior of cells after local membrane tension perturbations. PMID:28752950

Microstructural Characterization of Metal Foams: An Examination of the Applicability of the Theoretical Models for Modeling Foams. Revision 1

NASA Technical Reports Server (NTRS)

Raj, S. V.

2011-01-01

Establishing the geometry of foam cells is useful in developing microstructure-based acoustic and structural models. Since experimental data on the geometry of the foam cells are limited, most modeling efforts use an idealized three-dimensional, space-filling Kelvin tetrakaidecahedron. The validity of this assumption is investigated in the present paper. Several FeCrAlY foams with relative densities varying between 3 and 15 percent and cells per mm (c.p.mm.) varying between 0.2 and 3.9 c.p.mm. were microstructurally evaluated. The number of edges per face for each foam specimen was counted by approximating the cell faces by regular polygons, where the number of cell faces measured varied between 207 and 745. The present observations revealed that 50 to 57 percent of the cell faces were pentagonal while 24 to 28 percent were quadrilateral and 15 to 22 percent were hexagonal. The present measurements are shown to be in excellent agreement with literature data. It is demonstrated that the Kelvin model, as well as other proposed theoretical models, cannot accurately describe the FeCrAlY foam cell structure. Instead, it is suggested that the ideal foam cell geometry consists of 11 faces with three quadrilateral, six pentagonal faces and two hexagonal faces consistent with the 3-6-2 Matzke cell. A compilation of 90 years of experimental data reveals that the average number of cell faces decreases linearly with the increasing ratio of quadrilateral to pentagonal faces. It is concluded that the Kelvin model is not supported by these experimental data.

Use of genome editing tools in human stem cell-based disease modeling and precision medicine.

PubMed

Wei, Yu-da; Li, Shuang; Liu, Gai-gai; Zhang, Yong-xian; Ding, Qiu-rong

2015-10-01

Precision medicine emerges as a new approach that takes into account individual variability. The successful conduct of precision medicine requires the use of precise disease models. Human pluripotent stem cells (hPSCs), as well as adult stem cells, can be differentiated into a variety of human somatic cell types that can be used for research and drug screening. The development of genome editing technology over the past few years, especially the CRISPR/Cas system, has made it feasible to precisely and efficiently edit the genetic background. Therefore, disease modeling by using a combination of human stem cells and genome editing technology has offered a new platform to generate " personalized " disease models, which allow the study of the contribution of individual genetic variabilities to disease progression and the development of precise treatments. In this review, recent advances in the use of genome editing in human stem cells and the generation of stem cell models for rare diseases and cancers are discussed.

Therapeutic effects of autologous lymphocytes activated with trastuzumab for xenograft mouse models of human breast cancer.

PubMed

Nakagawa, Shinichiro; Matsuoka, Yusuke; Ichihara, Hideaki; Yoshida, Hitoji; Yoshida, Kenshi; Ueoka, Ryuichi

2013-01-01

Trastuzumab (TTZ) is molecular targeted drug used for metastatic breast cancer patients overexpressing human epidermal growth factor receptor 2 (HER2). Therapeutic effects of lymphocytes activated with TTZ (TTZ-LAK) using xenograft mouse models of human breast cancer (MDA-MB-453) cells were examined in vivo. Remarkable reduction of tumor volume in a xenograft mouse models intravenously treated with TTZ-LAK cells after the subcutaneously inoculated of MDA-MB-453 cells was verified in vivo. The migration of TTZ-LAK cells in tumor of mouse models subcutaneously inoculated MDA-MB-453 cells was observed on the basis of histological analysis using immunostaining with CD-3. Induction of apoptosis in tumor of xenograft mice treated with TTZ-LAK cells was observed in micrographs using terminal deoxynucleotidyl transferase-mediated deoxyuridine triphosphate nick-end labeling (TUNEL) method. It was noteworthy that the therapeutic effects of TTZ-LAK cells along with apoptosis were obtained for xenograft mouse models of human breast tumor in vivo.

Modeling oscillations and spiral waves in Dictyostelium populations

NASA Astrophysics Data System (ADS)

Noorbakhsh, Javad; Schwab, David J.; Sgro, Allyson E.; Gregor, Thomas; Mehta, Pankaj

2015-06-01

Unicellular organisms exhibit elaborate collective behaviors in response to environmental cues. These behaviors are controlled by complex biochemical networks within individual cells and coordinated through cell-to-cell communication. Describing these behaviors requires new mathematical models that can bridge scales—from biochemical networks within individual cells to spatially structured cellular populations. Here we present a family of "multiscale" models for the emergence of spiral waves in the social amoeba Dictyostelium discoideum. Our models exploit new experimental advances that allow for the direct measurement and manipulation of the small signaling molecule cyclic adenosine monophosphate (cAMP) used by Dictyostelium cells to coordinate behavior in cellular populations. Inspired by recent experiments, we model the Dictyostelium signaling network as an excitable system coupled to various preprocessing modules. We use this family of models to study spatially unstructured populations of "fixed" cells by constructing phase diagrams that relate the properties of population-level oscillations to parameters in the underlying biochemical network. We then briefly discuss an extension of our model that includes spatial structure and show how this naturally gives rise to spiral waves. Our models exhibit a wide range of novel phenomena. including a density-dependent frequency change, bistability, and dynamic death due to slow cAMP dynamics. Our modeling approach provides a powerful tool for bridging scales in modeling of Dictyostelium populations.

Hybrid Modeling of Cell Signaling and Transcriptional Reprogramming and Its Application in C. elegans Development.

PubMed

Fertig, Elana J; Danilova, Ludmila V; Favorov, Alexander V; Ochs, Michael F

2011-01-01

Modeling of signal driven transcriptional reprogramming is critical for understanding of organism development, human disease, and cell biology. Many current modeling techniques discount key features of the biological sub-systems when modeling multiscale, organism-level processes. We present a mechanistic hybrid model, GESSA, which integrates a novel pooled probabilistic Boolean network model of cell signaling and a stochastic simulation of transcription and translation responding to a diffusion model of extracellular signals. We apply the model to simulate the well studied cell fate decision process of the vulval precursor cells (VPCs) in C. elegans, using experimentally derived rate constants wherever possible and shared parameters to avoid overfitting. We demonstrate that GESSA recovers (1) the effects of varying scaffold protein concentration on signal strength, (2) amplification of signals in expression, (3) the relative external ligand concentration in a known geometry, and (4) feedback in biochemical networks. We demonstrate that setting model parameters based on wild-type and LIN-12 loss-of-function mutants in C. elegans leads to correct prediction of a wide variety of mutants including partial penetrance of phenotypes. Moreover, the model is relatively insensitive to parameters, retaining the wild-type phenotype for a wide range of cell signaling rate parameters.

Intratubular transplantation as a strategy for establishing animal models of testicular germ cell tumours

PubMed Central

Li, Yunmin; Kido, Tatsuo; Luo, Jinping; Fukuda, Michiko; Dobrinski, Ina; Lau, Yun-Fai Chris

2008-01-01

Testicular germ cell tumours (TGCTs) are prevalent cancers among young men. Currently, there is no reliable animal model for TGCTs. To establish such animal models, we have explored the possibility of intratubular testicular transplantation as means to deliver tumour cells into the seminiferous tubules of host animals. Our results demonstrated that transplanted cells could effectively populate the testis of a recipient mouse and develop into TGCTs. In addition, the donor cells could be transfected with a specific transgene before transplantation, thereby providing an approach to evaluate the specific effects of gene functions in the oncogenic processes. Hence, depending on selection of specific donor cells or mixtures of donor cells, transplantation models of TGCTs could be significant for studies on the pathogenesis, diagnosis and therapies of such a prevalent and important cancer in men. PMID:18808526

Running and rotating: modelling the dynamics of migrating cell clusters

NASA Astrophysics Data System (ADS)

Copenhagen, Katherine; Gov, Nir; Gopinathan, Ajay

Collective motion of cells is a common occurrence in many biological systems, including tissue development and repair, and tumor formation. Recent experiments have shown cells form clusters in a chemical gradient, which display three different phases of motion: translational, rotational, and random. We present a model for cell clusters based loosely on other models seen in the literature that involves a Vicsek-like alignment as well as physical collisions and adhesions between cells. With this model we show that a mechanism for driving rotational motion in this kind of system is an increased motility of rim cells. Further, we examine the details of the relationship between rim and core cells, and find that the phases of the cluster as a whole are correlated with the creation and annihilation of topological defects in the tangential component of the velocity field.

Edge Detection Based On the Characteristic of Primary Visual Cortex Cells

NASA Astrophysics Data System (ADS)

Zhu, M. M.; Xu, Y. L.; Ma, H. Q.

2018-01-01

Aiming at the problem that it is difficult to balance the accuracy of edge detection and anti-noise performance, and referring to the dynamic and static perceptions of the primary visual cortex (V1) cells, a V1 cell model is established to perform edge detection. A spatiotemporal filter is adopted to simulate the receptive field of V1 simple cells, the model V1 cell is obtained after integrating the responses of simple cells by half-wave rectification and normalization, Then the natural image edge is detected by using static perception of V1 cells. The simulation results show that, the V1 model can basically fit the biological data and has the universality of biology. What’s more, compared with other edge detection operators, the proposed model is more effective and has better robustness

Derivation of rigorous conditions for high cell-type diversity by algebraic approach.

PubMed

Yoshida, Hiroshi; Anai, Hirokazu; Horimoto, Katsuhisa

2007-01-01

The development of a multicellular organism is a dynamic process. Starting with one or a few cells, the organism develops into different types of cells with distinct functions. We have constructed a simple model by considering the cell number increase and the cell-type order conservation, and have assessed conditions for cell-type diversity. This model is based on a stochastic Lindenmayer system with cell-to-cell interactions for three types of cells. In the present model, we have successfully derived complex but rigorous algebraic relations between the proliferation and transition rates for cell-type diversity by using a symbolic method: quantifier elimination (QE). Surprisingly, three modes for the proliferation and transition rates have emerged for large ratios of the initial cells to the developed cells. The three modes have revealed that the equality between the development rates for the highest cell-type diversity is reduced during the development process of multicellular organisms. Furthermore, we have found that the highest cell-type diversity originates from order conservation.

On the relationship between cell cycle analysis with ergodic principles and age-structured cell population models.

PubMed

Kuritz, K; Stöhr, D; Pollak, N; Allgöwer, F

2017-02-07

Cyclic processes, in particular the cell cycle, are of great importance in cell biology. Continued improvement in cell population analysis methods like fluorescence microscopy, flow cytometry, CyTOF or single-cell omics made mathematical methods based on ergodic principles a powerful tool in studying these processes. In this paper, we establish the relationship between cell cycle analysis with ergodic principles and age structured population models. To this end, we describe the progression of a single cell through the cell cycle by a stochastic differential equation on a one dimensional manifold in the high dimensional dataspace of cell cycle markers. Given the assumption that the cell population is in a steady state, we derive transformation rules which transform the number density on the manifold to the steady state number density of age structured population models. Our theory facilitates the study of cell cycle dependent processes including local molecular events, cell death and cell division from high dimensional "snapshot" data. Ergodic analysis can in general be applied to every process that exhibits a steady state distribution. By combining ergodic analysis with age structured population models we furthermore provide the theoretic basis for extensions of ergodic principles to distribution that deviate from their steady state. Copyright © 2016 Elsevier Ltd. All rights reserved.

The role of backward cell migration in two-hit mutants' production in the stem cell niche.

PubMed

Bollas, Audrey; Shahriyari, Leili

2017-01-01

It has been discovered that there are two stem cell groups in the intestinal crypts: central stem cells (CeSCs), which are at the very bottom of the crypt, and border stem cells (BSCs), which are located between CeSCs and transit amplifying cells (TAs). Moreover, backward cell migration from BSCs to CeSCs has been observed. Recently, a bi-compartmental stochastic model, which includes CeSCs and BSCs, has been developed to investigate the probability of two-hit mutant production in the stem cell niche. In this project, we improve this stochastic model by adding the probability of backward cell migration to the model. The model suggests that the probability of two-hit mutant production increases when the frequency of backward cell migration increases. Furthermore, a small non-zero probability of backward cell migration leads to the largest range of optimal values for the frequency of symmetric divisions and the portion of divisions at each stem cell compartment in terms of delaying 2-hit mutant production. Moreover, the probability of two-hit mutant production is more sensitive to the probability of symmetric divisions than to the rate of backward cell migrations. The highest probability of two-hit mutant production corresponds to the case when all stem cell's divisions are asymmetric.

Time series modeling of live-cell shape dynamics for image-based phenotypic profiling.

PubMed

Gordonov, Simon; Hwang, Mun Kyung; Wells, Alan; Gertler, Frank B; Lauffenburger, Douglas A; Bathe, Mark

2016-01-01

Live-cell imaging can be used to capture spatio-temporal aspects of cellular responses that are not accessible to fixed-cell imaging. As the use of live-cell imaging continues to increase, new computational procedures are needed to characterize and classify the temporal dynamics of individual cells. For this purpose, here we present the general experimental-computational framework SAPHIRE (Stochastic Annotation of Phenotypic Individual-cell Responses) to characterize phenotypic cellular responses from time series imaging datasets. Hidden Markov modeling is used to infer and annotate morphological state and state-switching properties from image-derived cell shape measurements. Time series modeling is performed on each cell individually, making the approach broadly useful for analyzing asynchronous cell populations. Two-color fluorescent cells simultaneously expressing actin and nuclear reporters enabled us to profile temporal changes in cell shape following pharmacological inhibition of cytoskeleton-regulatory signaling pathways. Results are compared with existing approaches conventionally applied to fixed-cell imaging datasets, and indicate that time series modeling captures heterogeneous dynamic cellular responses that can improve drug classification and offer additional important insight into mechanisms of drug action. The software is available at http://saphire-hcs.org.

WholeCellSimDB: a hybrid relational/HDF database for whole-cell model predictions

PubMed Central

Karr, Jonathan R.; Phillips, Nolan C.; Covert, Markus W.

2014-01-01

Mechanistic ‘whole-cell’ models are needed to develop a complete understanding of cell physiology. However, extracting biological insights from whole-cell models requires running and analyzing large numbers of simulations. We developed WholeCellSimDB, a database for organizing whole-cell simulations. WholeCellSimDB was designed to enable researchers to search simulation metadata to identify simulations for further analysis, and quickly slice and aggregate simulation results data. In addition, WholeCellSimDB enables users to share simulations with the broader research community. The database uses a hybrid relational/hierarchical data format architecture to efficiently store and retrieve both simulation setup metadata and results data. WholeCellSimDB provides a graphical Web-based interface to search, browse, plot and export simulations; a JavaScript Object Notation (JSON) Web service to retrieve data for Web-based visualizations; a command-line interface to deposit simulations; and a Python API to retrieve data for advanced analysis. Overall, we believe WholeCellSimDB will help researchers use whole-cell models to advance basic biological science and bioengineering. Database URL: http://www.wholecellsimdb.org Source code repository URL: http://github.com/CovertLab/WholeCellSimDB PMID:25231498

Role of streams in myxobacteria aggregate formation

NASA Astrophysics Data System (ADS)

Kiskowski, Maria A.; Jiang, Yi; Alber, Mark S.

2004-10-01

Cell contact, movement and directionality are important factors in biological development (morphogenesis), and myxobacteria are a model system for studying cell-cell interaction and cell organization preceding differentiation. When starved, thousands of myxobacteria cells align, stream and form aggregates which later develop into round, non-motile spores. Canonically, cell aggregation has been attributed to attractive chemotaxis, a long range interaction, but there is growing evidence that myxobacteria organization depends on contact-mediated cell-cell communication. We present a discrete stochastic model based on contact-mediated signaling that suggests an explanation for the initialization of early aggregates, aggregation dynamics and final aggregate distribution. Our model qualitatively reproduces the unique structures of myxobacteria aggregates and detailed stages which occur during myxobacteria aggregation: first, aggregates initialize in random positions and cells join aggregates by random walk; second, cells redistribute by moving within transient streams connecting aggregates. Streams play a critical role in final aggregate size distribution by redistributing cells among fewer, larger aggregates. The mechanism by which streams redistribute cells depends on aggregate sizes and is enhanced by noise. Our model predicts that with increased internal noise, more streams would form and streams would last longer. Simulation results suggest a series of new experiments.

Comprehensive silicon solar-cell computer modeling

NASA Technical Reports Server (NTRS)

Lamorte, M. F.

1984-01-01

A comprehensive silicon solar cell computer modeling scheme was developed to perform the following tasks: (1) model and analysis of the net charge distribution in quasineutral regions; (2) experimentally determined temperature behavior of Spire Corp. n+pp+ solar cells where n+-emitter is formed by ion implantation of 75As or 31P; and (3) initial validation results of computer simulation program using Spire Corp. n+pp+ cells.

Modeling mammary organogenesis from biological first principles: Cells and their physical constraints.

PubMed

Montévil, Maël; Speroni, Lucia; Sonnenschein, Carlos; Soto, Ana M

2016-10-01

In multicellular organisms, relations among parts and between parts and the whole are contextual and interdependent. These organisms and their cells are ontogenetically linked: an organism starts as a cell that divides producing non-identical cells, which organize in tri-dimensional patterns. These association patterns and cells types change as tissues and organs are formed. This contextuality and circularity makes it difficult to establish detailed cause and effect relationships. Here we propose an approach to overcome these intrinsic difficulties by combining the use of two models; 1) an experimental one that employs 3D culture technology to obtain the structures of the mammary gland, namely, ducts and acini, and 2) a mathematical model based on biological principles. The typical approach for mathematical modeling in biology is to apply mathematical tools and concepts developed originally in physics or computer sciences. Instead, we propose to construct a mathematical model based on proper biological principles. Specifically, we use principles identified as fundamental for the elaboration of a theory of organisms, namely i) the default state of cell proliferation with variation and motility and ii) the principle of organization by closure of constraints. This model has a biological component, the cells, and a physical component, a matrix which contains collagen fibers. Cells display agency and move and proliferate unless constrained; they exert mechanical forces that i) act on collagen fibers and ii) on other cells. As fibers organize, they constrain the cells on their ability to move and to proliferate. The model exhibits a circularity that can be interpreted in terms of closure of constraints. Implementing the mathematical model shows that constraints to the default state are sufficient to explain ductal and acinar formation, and points to a target of future research, namely, to inhibitors of cell proliferation and motility generated by the epithelial cells. The success of this model suggests a step-wise approach whereby additional constraints imposed by the tissue and the organism could be examined in silico and rigorously tested by in vitro and in vivo experiments, in accordance with the organicist perspective we embrace. Copyright © 2016. Published by Elsevier Ltd.

Modeling mammary organogenesis from biological first principles: Cells and their physical constraints

PubMed Central

Montévil, Maël; Speroni, Lucia; Sonnenschein, Carlos; Soto, Ana M.

2017-01-01

In multicellular organisms, relations among parts and between parts and the whole are contextual and interdependent. These organisms and their cells are ontogenetically linked: an organism starts as a cell that divides producing non-identical cells, which organize in tri-dimensional patterns. These association patterns and cells types change as tissues and organs are formed. This contextuality and circularity makes it difficult to establish detailed cause and effect relationships. Here we propose an approach to overcome these intrinsic difficulties by combining the use of two models; 1) an experimental one that employs 3D culture technology to obtain the structures of the mammary gland, namely, ducts and acini, and 2) a mathematical model based on biological principles. The typical approach for mathematical modeling in biology is to apply mathematical tools and concepts developed originally in physics or computer sciences. Instead, we propose to construct a mathematical model based on proper biological principles. Specifically, we use principles identified as fundamental for the elaboration of a theory of organisms, namely i) the default state of cell proliferation with variation and motility and ii) the principle of organization by closure of constraints. This model has a biological component, the cells, and a physical component, a matrix which contains collagen fibers. Cells display agency and move and proliferate unless constrained; they exert mechanical forces that i) act on collagen fibers and ii) on other cells. As fibers organize, they constrain the cells on their ability to move and to proliferate. The model exhibits a circularity that can be interpreted in terms of closure of constraints. Implementing the mathematical model shows that constraints to the default state are sufficient to explain ductal and acinar formation, and points to a target of future research, namely, to inhibitors of cell proliferation and motility generated by the epithelial cells. The success of this model suggests a step-wise approach whereby additional constraints imposed by the tissue and the organism could be examined in silico and rigorously tested by in vitro and in vivo experiments, in accordance with the organicist perspective we embrace. PMID:27544910

The Use of Modelling for Improving Pupils' Learning about Cells.

ERIC Educational Resources Information Center

Tregidgo, David; Ratcliffe, Mary

2000-01-01

Outlines the use of modeling in science teaching. Describes a study in which two parallel groups of year seven pupils modeled concepts of cell structure and function as they produced two- or three-dimensional representations of plant and animal cells. (Author/CCM)

Modelling and fabrication of high-efficiency silicon solar cells

NASA Astrophysics Data System (ADS)

Rohatgi, A.; Smith, A. W.; Salami, J.

1991-10-01

This report covers the research conducted on modelling and development of high efficiency silicon solar cells during the period May 1989 to August 1990. First, considerable effort was devoted toward developing a ray tracing program for the photovoltaic community to quantify and optimize surface texturing for solar cells. Second, attempts were made to develop a hydrodynamic model for device simulation. Such a model is somewhat slower than drift-diffusion type models like PC-1D, but it can account for more physical phenomena in the device, such as hot carrier effects, temperature gradients, thermal diffusion, and lattice heat flow. In addition, Fermi-Dirac statistics have been incorporated into the model to deal with heavy doping effects more accurately. The third and final component of the research includes development of silicon cell fabrication capabilities and fabrication of high efficiency silicon cells.

Weakly coupled map lattice models for multicellular patterning and collective normalization of abnormal single-cell states

NASA Astrophysics Data System (ADS)

García-Morales, Vladimir; Manzanares, José A.; Mafe, Salvador

2017-04-01

We present a weakly coupled map lattice model for patterning that explores the effects exerted by weakening the local dynamic rules on model biological and artificial networks composed of two-state building blocks (cells). To this end, we use two cellular automata models based on (i) a smooth majority rule (model I) and (ii) a set of rules similar to those of Conway's Game of Life (model II). The normal and abnormal cell states evolve according to local rules that are modulated by a parameter κ . This parameter quantifies the effective weakening of the prescribed rules due to the limited coupling of each cell to its neighborhood and can be experimentally controlled by appropriate external agents. The emergent spatiotemporal maps of single-cell states should be of significance for positional information processes as well as for intercellular communication in tumorigenesis, where the collective normalization of abnormal single-cell states by a predominantly normal neighborhood may be crucial.

Matrix viscoplasticity and its shielding by active mechanics in microtissue models: experiments and mathematical modeling

NASA Astrophysics Data System (ADS)

Liu, Alan S.; Wang, Hailong; Copeland, Craig R.; Chen, Christopher S.; Shenoy, Vivek B.; Reich, Daniel H.

2016-09-01

The biomechanical behavior of tissues under mechanical stimulation is critically important to physiological function. We report a combined experimental and modeling study of bioengineered 3D smooth muscle microtissues that reveals a previously unappreciated interaction between active cell mechanics and the viscoplastic properties of the extracellular matrix. The microtissues’ response to stretch/unstretch actuations, as probed by microcantilever force sensors, was dominated by cellular actomyosin dynamics. However, cell lysis revealed a viscoplastic response of the underlying model collagen/fibrin matrix. A model coupling Hill-type actomyosin dynamics with a plastic perfectly viscoplastic description of the matrix quantitatively accounts for the microtissue dynamics, including notably the cells’ shielding of the matrix plasticity. Stretch measurements of single cells confirmed the active cell dynamics, and were well described by a single-cell version of our model. These results reveal the need for new focus on matrix plasticity and its interactions with active cell mechanics in describing tissue dynamics.

From in vitro to in vivo: Integration of the virtual cell based assay with physiologically based kinetic modelling.

PubMed

Paini, Alicia; Sala Benito, Jose Vicente; Bessems, Jos; Worth, Andrew P

2017-12-01

Physiologically based kinetic (PBK) models and the virtual cell based assay can be linked to form so called physiologically based dynamic (PBD) models. This study illustrates the development and application of a PBK model for prediction of estragole-induced DNA adduct formation and hepatotoxicity in humans. To address the hepatotoxicity, HepaRG cells were used as a surrogate for liver cells, with cell viability being used as the in vitro toxicological endpoint. Information on DNA adduct formation was taken from the literature. Since estragole induced cell damage is not directly caused by the parent compound, but by a reactive metabolite, information on the metabolic pathway was incorporated into the model. In addition, a user-friendly tool was developed by implementing the PBK/D model into a KNIME workflow. This workflow can be used to perform in vitro to in vivo extrapolation and forward as backward dosimetry in support of chemical risk assessment. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Cell-oriented modeling of angiogenesis.

PubMed

Guidolin, Diego; Rebuffat, Piera; Albertin, Giovanna

2011-01-01

Due to its significant involvement in various physiological and pathological conditions, angiogenesis (the development of new blood vessels from an existing vasculature) represents an important area of the actual biological research and a field in which mathematical modeling proved particularly useful in supporting the experimental work. In this paper, we focus on a specific modeling strategy, known as "cell-centered" approach. This type of mathematical models work at a "mesoscopic scale," assuming the cell as the natural level of abstraction for computational modeling of development. They treat cells phenomenologically, considering their essential behaviors to study how tissue structure and organization emerge from the collective dynamics of multiple cells. The main contributions of the cell-oriented approach to the study of the angiogenic process will be described. From one side, they have generated "basic science understanding" about the process of capillary assembly during development, growth, and pathology. On the other side, models were also developed supporting "applied biomedical research" for the purpose of identifying new therapeutic targets and clinically relevant approaches for either inhibiting or stimulating angiogenesis.

Matrix viscoplasticity and its shielding by active mechanics in microtissue models: experiments and mathematical modeling

PubMed Central

Liu, Alan S.; Wang, Hailong; Copeland, Craig R.; Chen, Christopher S.; Shenoy, Vivek B.; Reich, Daniel H.

2016-01-01

The biomechanical behavior of tissues under mechanical stimulation is critically important to physiological function. We report a combined experimental and modeling study of bioengineered 3D smooth muscle microtissues that reveals a previously unappreciated interaction between active cell mechanics and the viscoplastic properties of the extracellular matrix. The microtissues’ response to stretch/unstretch actuations, as probed by microcantilever force sensors, was dominated by cellular actomyosin dynamics. However, cell lysis revealed a viscoplastic response of the underlying model collagen/fibrin matrix. A model coupling Hill-type actomyosin dynamics with a plastic perfectly viscoplastic description of the matrix quantitatively accounts for the microtissue dynamics, including notably the cells’ shielding of the matrix plasticity. Stretch measurements of single cells confirmed the active cell dynamics, and were well described by a single-cell version of our model. These results reveal the need for new focus on matrix plasticity and its interactions with active cell mechanics in describing tissue dynamics. PMID:27671239

Weakly coupled map lattice models for multicellular patterning and collective normalization of abnormal single-cell states.

PubMed

García-Morales, Vladimir; Manzanares, José A; Mafe, Salvador

2017-04-01

We present a weakly coupled map lattice model for patterning that explores the effects exerted by weakening the local dynamic rules on model biological and artificial networks composed of two-state building blocks (cells). To this end, we use two cellular automata models based on (i) a smooth majority rule (model I) and (ii) a set of rules similar to those of Conway's Game of Life (model II). The normal and abnormal cell states evolve according to local rules that are modulated by a parameter κ. This parameter quantifies the effective weakening of the prescribed rules due to the limited coupling of each cell to its neighborhood and can be experimentally controlled by appropriate external agents. The emergent spatiotemporal maps of single-cell states should be of significance for positional information processes as well as for intercellular communication in tumorigenesis, where the collective normalization of abnormal single-cell states by a predominantly normal neighborhood may be crucial.

A Model for the Epigenetic Switch Linking Inflammation to Cell Transformation: Deterministic and Stochastic Approaches

PubMed Central

Gérard, Claude; Gonze, Didier; Lemaigre, Frédéric; Novák, Béla

2014-01-01

Recently, a molecular pathway linking inflammation to cell transformation has been discovered. This molecular pathway rests on a positive inflammatory feedback loop between NF-κB, Lin28, Let-7 microRNA and IL6, which leads to an epigenetic switch allowing cell transformation. A transient activation of an inflammatory signal, mediated by the oncoprotein Src, activates NF-κB, which elicits the expression of Lin28. Lin28 decreases the expression of Let-7 microRNA, which results in higher level of IL6 than achieved directly by NF-κB. In turn, IL6 can promote NF-κB activation. Finally, IL6 also elicits the synthesis of STAT3, which is a crucial activator for cell transformation. Here, we propose a computational model to account for the dynamical behavior of this positive inflammatory feedback loop. By means of a deterministic model, we show that an irreversible bistable switch between a transformed and a non-transformed state of the cell is at the core of the dynamical behavior of the positive feedback loop linking inflammation to cell transformation. The model indicates that inhibitors (tumor suppressors) or activators (oncogenes) of this positive feedback loop regulate the occurrence of the epigenetic switch by modulating the threshold of inflammatory signal (Src) needed to promote cell transformation. Both stochastic simulations and deterministic simulations of a heterogeneous cell population suggest that random fluctuations (due to molecular noise or cell-to-cell variability) are able to trigger cell transformation. Moreover, the model predicts that oncogenes/tumor suppressors respectively decrease/increase the robustness of the non-transformed state of the cell towards random fluctuations. Finally, the model accounts for the potential effect of competing endogenous RNAs, ceRNAs, on the dynamics of the epigenetic switch. Depending on their microRNA targets, the model predicts that ceRNAs could act as oncogenes or tumor suppressors by regulating the occurrence of cell transformation. PMID:24499937

Modeling extracellular fields for a three-dimensional network of cells using NEURON.

PubMed

Appukuttan, Shailesh; Brain, Keith L; Manchanda, Rohit

2017-10-01

Computational modeling of biological cells usually ignores their extracellular fields, assuming them to be inconsequential. Though such an assumption might be justified in certain cases, it is debatable for networks of tightly packed cells, such as in the central nervous system and the syncytial tissues of cardiac and smooth muscle. In the present work, we demonstrate a technique to couple the extracellular fields of individual cells within the NEURON simulation environment. The existing features of the simulator are extended by explicitly defining current balance equations, resulting in the coupling of the extracellular fields of adjacent cells. With this technique, we achieved continuity of extracellular space for a network model, thereby allowing the exploration of extracellular interactions computationally. Using a three-dimensional network model, passive and active electrical properties were evaluated under varying levels of extracellular volumes. Simultaneous intracellular and extracellular recordings for synaptic and action potentials were analyzed, and the potential of ephaptic transmission towards functional coupling of cells was explored. We have implemented a true bi-domain representation of a network of cells, with the extracellular domain being continuous throughout the entire model. This has hitherto not been achieved using NEURON, or other compartmental modeling platforms. We have demonstrated the coupling of the extracellular field of every cell in a three-dimensional model to obtain a continuous uniform extracellular space. This technique provides a framework for the investigation of interactions in tightly packed networks of cells via their extracellular fields. Copyright © 2017 Elsevier B.V. All rights reserved.

The re-incarnation, re-interpretation and re-demise of the transition probability model.

PubMed

Koch, A L

1999-05-28

There are two classes of models for the cell cycle that have both a deterministic and a stochastic part; they are the transition probability (TP) models and sloppy size control (SSC) models. The hallmark of the basic TP model are two graphs: the alpha and beta plots. The former is the semi-logarithmic plot of the percentage of cell divisions yet to occur, this results in a horizontal line segment at 100% corresponding to the deterministic phase and a straight line sloping tail corresponding to the stochastic part. The beta plot concerns the differences of the age-at-division of sisters (the beta curve) and gives a straight line parallel to the tail of the alpha curve. For the SC models the deterministic part is the time needed for the cell to accumulate a critical amount of some substance(s). The variable part differs in the various variants of the general model, but they do not give alpha and beta curves with linear tails as postulated by the TP model. This paper argues against TP and for an elaboration of SSC type of model. The main argument against TP is that it assumes that the probability of the transition from the stochastic phase is time invariant even though it is certain that the cells are growing and metabolizing throughout the cell cycle; a fact that should make the transition probability be variable. The SSC models presume that cell division is triggered by the cell's success in growing and not simply the result of elapsed time. The extended model proposed here to accommodate the predictions of the SSC to the straight tailed parts of the alpha and beta plots depends on the existence of a few percent of the cell in a growing culture that are not growing normally, these are growing much slower or are temporarily quiescent. The bulk of the cells, however, grow nearly exponentially. Evidence for a slow growing component comes from experimental analyses of population size distributions for a variety of cell types by the Collins-Richmond technique. These subpopulations existence is consistent with the new concept that there are a large class of rapidly reversible mutations occurring in many organisms and at many loci serving a large range of purposes to enable the cell to survive environmental challenges. These mutations yield special subpopulations of cells within a population. The reversible mutational changes, relevant to the elaboration of SSC models, produce slow-growing cells that are either very large or very small in size; these later revert to normal growth and division. The subpopulations, however, distort the population distribution in such a way as to fit better the exponential tails of the alpha and beta curves of the TP model.

Thermofluid Modeling of Fuel Cells

NASA Astrophysics Data System (ADS)

Young, John B.

2007-01-01

Fuel cells offer the prospect of silent electrical power generation at high efficiency with near-zero pollutant emission. Many materials and fabrication problems have now been solved and attention has shifted toward system modeling, including the fluid flows that supply the cells with hydrogen and oxygen. This review describes the current thermofluid modeling capabilities for proton exchange membrane fuel cells (PEMFCs) and solid oxide fuel cells (SOFCs), the most promising candidates for commercial exploitation. Topics covered include basic operating principles and stack design, convective-diffusive flow in porous solids, special modeling issues for PEMFCs and SOFCs, and the use of computational fluid dynamics (CFD) methods.

Human mammary microenvironment better regulates the biology of human breast cancer in humanized mouse model.

PubMed

Zheng, Ming-Jie; Wang, Jue; Xu, Lu; Zha, Xiao-Ming; Zhao, Yi; Ling, Li-Jun; Wang, Shui

2015-02-01

During the past decades, many efforts have been made in mimicking the clinical progress of human cancer in mouse models. Previously, we developed a human breast tissue-derived (HB) mouse model. Theoretically, it may mimic the interactions between "species-specific" mammary microenvironment of human origin and human breast cancer cells. However, detailed evidences are absent. The present study (in vivo, cellular, and molecular experiments) was designed to explore the regulatory role of human mammary microenvironment in the progress of human breast cancer cells. Subcutaneous (SUB), mammary fat pad (MFP), and HB mouse models were developed for in vivo comparisons. Then, the orthotopic tumor masses from three different mouse models were collected for primary culture. Finally, the biology of primary cultured human breast cancer cells was compared by cellular and molecular experiments. Results of in vivo mouse models indicated that human breast cancer cells grew better in human mammary microenvironment. Cellular and molecular experiments confirmed that primary cultured human breast cancer cells from HB mouse model showed a better proliferative and anti-apoptotic biology than those from SUB to MFP mouse models. Meanwhile, primary cultured human breast cancer cells from HB mouse model also obtained the migratory and invasive biology for "species-specific" tissue metastasis to human tissues. Comprehensive analyses suggest that "species-specific" mammary microenvironment of human origin better regulates the biology of human breast cancer cells in our humanized mouse model of breast cancer, which is more consistent with the clinical progress of human breast cancer.

Cell survival fraction estimation based on the probability densities of domain and cell nucleus specific energies using improved microdosimetric kinetic models.

PubMed

Sato, Tatsuhiko; Furusawa, Yoshiya

2012-10-01

Estimation of the survival fractions of cells irradiated with various particles over a wide linear energy transfer (LET) range is of great importance in the treatment planning of charged-particle therapy. Two computational models were developed for estimating survival fractions based on the concept of the microdosimetric kinetic model. They were designated as the double-stochastic microdosimetric kinetic and stochastic microdosimetric kinetic models. The former model takes into account the stochastic natures of both domain and cell nucleus specific energies, whereas the latter model represents the stochastic nature of domain specific energy by its approximated mean value and variance to reduce the computational time. The probability densities of the domain and cell nucleus specific energies are the fundamental quantities for expressing survival fractions in these models. These densities are calculated using the microdosimetric and LET-estimator functions implemented in the Particle and Heavy Ion Transport code System (PHITS) in combination with the convolution or database method. Both the double-stochastic microdosimetric kinetic and stochastic microdosimetric kinetic models can reproduce the measured survival fractions for high-LET and high-dose irradiations, whereas a previously proposed microdosimetric kinetic model predicts lower values for these fractions, mainly due to intrinsic ignorance of the stochastic nature of cell nucleus specific energies in the calculation. The models we developed should contribute to a better understanding of the mechanism of cell inactivation, as well as improve the accuracy of treatment planning of charged-particle therapy.

Rate-equation modelling and ensemble approach to extraction of parameters for viral infection-induced cell apoptosis and necrosis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Domanskyi, Sergii; Schilling, Joshua E.; Privman, Vladimir, E-mail: privman@clarkson.edu

We develop a theoretical approach that uses physiochemical kinetics modelling to describe cell population dynamics upon progression of viral infection in cell culture, which results in cell apoptosis (programmed cell death) and necrosis (direct cell death). Several model parameters necessary for computer simulation were determined by reviewing and analyzing available published experimental data. By comparing experimental data to computer modelling results, we identify the parameters that are the most sensitive to the measured system properties and allow for the best data fitting. Our model allows extraction of parameters from experimental data and also has predictive power. Using the model wemore » describe interesting time-dependent quantities that were not directly measured in the experiment and identify correlations among the fitted parameter values. Numerical simulation of viral infection progression is done by a rate-equation approach resulting in a system of “stiff” equations, which are solved by using a novel variant of the stochastic ensemble modelling approach. The latter was originally developed for coupled chemical reactions.« less

The impact of cell regeneration on the dynamics of viral coinfection

NASA Astrophysics Data System (ADS)

Pinky, Lubna; Dobrovolny, Hana M.

2017-06-01

Many mathematical models of respiratory viral infections do not include regeneration of cells within the respiratory tract, arguing that the infection is resolved before there is significant cellular regeneration. However, recent studies have found that ˜40% of patients hospitalized with influenza-like illness are infected with at least two different viruses, which could potentially lead to longer-lasting infections. In these longer infections, cell regeneration might affect the infection dynamics, in particular, allowing for the possibility of chronic coinfections. Several mathematical models have been used to describe cell regeneration in infection models, though the effect of model choice on the predicted time course of viral coinfections is not clear. We investigate four mathematical models incorporating different mechanisms of cell regeneration during respiratory viral coinfection to determine the effect of cell regeneration on infection dynamics. We perform linear stability analysis for each of the models and find the steady states analytically. The analysis suggests that chronic illness is possible but only with one viral species; chronic coexistence of two different viral species is not possible with the regeneration models considered here.

Crypt dynamics and colorectal cancer: advances in mathematical modelling.

PubMed

van Leeuwen, I M M; Byrne, H M; Jensen, O E; King, J R

2006-06-01

Mathematical modelling forms a key component of systems biology, offering insights that complement and stimulate experimental studies. In this review, we illustrate the role of theoretical models in elucidating the mechanisms involved in normal intestinal crypt dynamics and colorectal cancer. We discuss a range of modelling approaches, including models that describe cell proliferation, migration, differentiation, crypt fission, genetic instability, APC inactivation and tumour heterogeneity. We focus on the model assumptions, limitations and applications, rather than on the technical details. We also present a new stochastic model for stem-cell dynamics, which predicts that, on average, APC inactivation occurs more quickly in the stem-cell pool in the absence of symmetric cell division. This suggests that natural niche succession may protect stem cells against malignant transformation in the gut. Finally, we explain how we aim to gain further understanding of the crypt system and of colorectal carcinogenesis with the aid of multiscale models that cover all levels of organization from the molecular to the whole organ.

A Lattice Boltzmann Fictitious Domain Method for Modeling Red Blood Cell Deformation and Multiple-Cell Hydrodynamic Interactions in Flow

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shi, Xing; Lin, Guang; Zou, Jianfeng

To model red blood cell (RBC) deformation in flow, the recently developed LBM-DLM/FD method ([Shi and Lim, 2007)29], derived from the lattice Boltzmann method and the distributed Lagrange multiplier/fictitious domain methodthe fictitious domain method, is extended to employ the mesoscopic network model for simulations of red blood cell deformation. The flow is simulated by the lattice Boltzmann method with an external force, while the network model is used for modeling red blood cell deformation and the fluid-RBC interaction is enforced by the Lagrange multiplier. To validate parameters of the RBC network model, sThe stretching numerical tests on both coarse andmore » fine meshes are performed and compared with the corresponding experimental data to validate the parameters of the RBC network model. In addition, RBC deformation in pipe flow and in shear flow is simulated, revealing the capacity of the current method for modeling RBC deformation in various flows.« less

Estimation of Cell Proliferation Dynamics Using CFSE Data

PubMed Central

Banks, H.T.; Sutton, Karyn L.; Thompson, W. Clayton; Bocharov, Gennady; Roose, Dirk; Schenkel, Tim; Meyerhans, Andreas

2010-01-01

Advances in fluorescent labeling of cells as measured by flow cytometry have allowed for quantitative studies of proliferating populations of cells. The investigations (Luzyanina et al. in J. Math. Biol. 54:57–89, 2007; J. Math. Biol., 2009; Theor. Biol. Med. Model. 4:1–26, 2007) contain a mathematical model with fluorescence intensity as a structure variable to describe the evolution in time of proliferating cells labeled by carboxyfluorescein succinimidyl ester (CFSE). Here, this model and several extensions/modifications are discussed. Suggestions for improvements are presented and analyzed with respect to statistical significance for better agreement between model solutions and experimental data. These investigations suggest that the new decay/label loss and time dependent effective proliferation and death rates do indeed provide improved fits of the model to data. Statistical models for the observed variability/noise in the data are discussed with implications for uncertainty quantification. The resulting new cell dynamics model should prove useful in proliferation assay tracking and modeling, with numerous applications in the biomedical sciences. PMID:20195910

Three-dimensional simulation of pseudopod-driven swimming of amoeboid cells

NASA Astrophysics Data System (ADS)

Campbell, Eric; Bagchi, Prosenjit

2016-11-01

Pseudopod-driven locomotion is common in eukaryotic cells, such as amoeba, neutrophils, and cancer cells. Pseudopods are protrusions of the cell body that grow, bifurcate, and retract. Due to the dynamic nature of pseudopods, the shape of a motile cell constantly changes. The actin-myosin protein dynamics is a likely mechanism for pseudopod growth. Existing theoretical models often focus on the acto-myosin dynamics, and not the whole cell shape dynamics. Here we present a full 3D simulation of pseudopod-driven motility by coupling a surface-bound reaction-diffusion (RD) model for the acto-myosin dynamics, a continuum model for the cell membrane deformation, and flow of the cytoplasmic and extracellular fluids. The whole cell is represented as a viscous fluid surrounded by a membrane. A finite-element method is used to solve the membrane deformation, and the RD model on the deforming membrane, while a finite-difference/spectral method is used to solve the flow fields inside and outside the cell. The fluid flow and cell deformation are coupled by the immersed-boundary method. The model predicts pseudopod growth, bifurcation, and retraction as observed for a swimming amoeba. The work provides insights on the role of membrane stiffness and cytoplasmic viscosity on amoeboid swimming. Funded by NSF CBET 1438255.

The effect of differentiation agents on inflammatory and oxidative responses of the human neuroblastoma cell line SK-N-SH.

PubMed

Niewiarowska-Sendo, Anna; Patrzalek, Katarzyna; Kozik, Andrzej; Guevara-Lora, Ibeth

2015-01-01

Obtaining a suitable experimental cellular model is a major problem for neuroscience studies. Neuroblastoma cell lines have been often applied in studies related to pathological disorders of nervous system. However, in the search for an ideal model, these cells must be differentiated to cancel their tumor character. The subsequent reactions that are caused by differentiation are not always indifferent to the same model. We evaluated the effect of two well known substances, used for SH-N-SK cell line differentiation, retinoic acid (RA) and phorbol-12-myristate-13-acetate (PMA), on the induction of pro-inflammatory and pro-oxidative reactions in these cells. Cells differentiated with PMA were able to produce significantly higher amounts of pro-inflammatory cytokines whereas the release of nitric oxide radicals was similar to that in undifferentiated cells. On the contrary, in RA-differentiated cells no significant changes in cytokine production were observed and the nitric oxide release was decreased. Additionally, the RA-differentiated neuronal model was more sensible to lipopolysaccharide stimulation, producing pro-inflammatory cytokines abundantly. These results suggest that RA-differentiated SH-N-SK cells provide a more suitable experimental model for the study of molecular and cellular mechanisms of the inflammation and oxidative stress in neuronal cells.

A Stochastic Model of the Yeast Cell Cycle Reveals Roles for Feedback Regulation in Limiting Cellular Variability.

PubMed

Barik, Debashis; Ball, David A; Peccoud, Jean; Tyson, John J

2016-12-01

The cell division cycle of eukaryotes is governed by a complex network of cyclin-dependent protein kinases (CDKs) and auxiliary proteins that govern CDK activities. The control system must function reliably in the context of molecular noise that is inevitable in tiny yeast cells, because mistakes in sequencing cell cycle events are detrimental or fatal to the cell or its progeny. To assess the effects of noise on cell cycle progression requires not only extensive, quantitative, experimental measurements of cellular heterogeneity but also comprehensive, accurate, mathematical models of stochastic fluctuations in the CDK control system. In this paper we provide a stochastic model of the budding yeast cell cycle that accurately accounts for the variable phenotypes of wild-type cells and more than 20 mutant yeast strains simulated in different growth conditions. We specifically tested the role of feedback regulations mediated by G1- and SG2M-phase cyclins to minimize the noise in cell cycle progression. Details of the model are informed and tested by quantitative measurements (by fluorescence in situ hybridization) of the joint distributions of mRNA populations in yeast cells. We use the model to predict the phenotypes of ~30 mutant yeast strains that have not yet been characterized experimentally.

A Stochastic Model of the Yeast Cell Cycle Reveals Roles for Feedback Regulation in Limiting Cellular Variability

PubMed Central

Ball, David A.

2016-01-01

The cell division cycle of eukaryotes is governed by a complex network of cyclin-dependent protein kinases (CDKs) and auxiliary proteins that govern CDK activities. The control system must function reliably in the context of molecular noise that is inevitable in tiny yeast cells, because mistakes in sequencing cell cycle events are detrimental or fatal to the cell or its progeny. To assess the effects of noise on cell cycle progression requires not only extensive, quantitative, experimental measurements of cellular heterogeneity but also comprehensive, accurate, mathematical models of stochastic fluctuations in the CDK control system. In this paper we provide a stochastic model of the budding yeast cell cycle that accurately accounts for the variable phenotypes of wild-type cells and more than 20 mutant yeast strains simulated in different growth conditions. We specifically tested the role of feedback regulations mediated by G1- and SG2M-phase cyclins to minimize the noise in cell cycle progression. Details of the model are informed and tested by quantitative measurements (by fluorescence in situ hybridization) of the joint distributions of mRNA populations in yeast cells. We use the model to predict the phenotypes of ~30 mutant yeast strains that have not yet been characterized experimentally. PMID:27935947

Plasmonic Light Trapping in Thin-Film Solar Cells: Impact of Modeling on Performance Prediction

PubMed Central

Micco, Alberto; Pisco, Marco; Ricciardi, Armando; Mercaldo, Lucia V.; Usatii, Iurie; La Ferrara, Vera; Delli Veneri, Paola; Cutolo, Antonello; Cusano, Andrea

2015-01-01

We present a comparative study on numerical models used to predict the absorption enhancement in thin-film solar cells due to the presence of structured back-reflectors exciting, at specific wavelengths, hybrid plasmonic-photonic resonances. To evaluate the effectiveness of the analyzed models, they have been applied in a case study: starting from a U-shaped textured glass thin-film, µc-Si:H solar cells have been successfully fabricated. The fabricated cells, with different intrinsic layer thicknesses, have been morphologically, optically and electrically characterized. The experimental results have been successively compared with the numerical predictions. We have found that, in contrast to basic models based on the underlying schematics of the cell, numerical models taking into account the real morphology of the fabricated device, are able to effectively predict the cells performances in terms of both optical absorption and short-circuit current values.

Alzheimer’s in 3D culture: Challenges and perspectives

PubMed Central

D'Avanzo, Carla; Aronson, Jenna; Kim, Young Hye; Choi, Se Hoon; Tanzi, Rudolph E.; Kim, Doo Yeon

2015-01-01

Summary Alzheimer’s disease (AD) is the most common cause of dementia, and there is currently no cure. The “β-amyloid cascade hypothesis” of AD is the basis of current understanding of AD pathogenesis and drug discovery. However, no AD models have fully validated this hypothesis. We recently developed a human stem cell culture model of AD by cultivating genetically modified human neural stem cells in a three-dimensional (3D) cell culture system. These cells were able to recapitulate key events of AD pathology including β-amyloid plaques and neurofibrillary tangles. In this review, we will discuss the progress and current limitations of AD mouse models and human stem cell models as well as explore the breakthroughs of 3D cell culture systems. We will also share our perspective on the potential of dish models of neurodegenerative diseases for studying pathogenic cascades and therapeutic drug discovery. PMID:26252541

INFLUENCE OF DIFFERENT INCUBATOR MODELS ON MAGNETIC FIELD-INDUCED CHANGES IN NEURITE OUTGROWTH IN PC-12 CELLS

EPA Science Inventory

OBJECTIVE: Devise a method to standardize responses of cells to MF-exposure in different incubator environments. METHODS: We compared the cell responses to generated MF in a standard cell-culture incubator (Forma, model #3158) with cell responses to the same exposure when a mu-m...

A primary cell model of HIV-1 latency that uses activation through the T cell receptor and return to quiescence to establish latent infection

PubMed Central

Kim, Michelle; Hosmane, Nina N.; Bullen, C. Korin; Capoferri, Adam; Yang, Hung-Chih; Siliciano, Janet D.; Siliciano, Robert F.

2015-01-01

A mechanistic understanding of HIV-1 latency depends upon a model system that recapitulates the in vivo condition of latently infected, resting CD4+ T lymphocytes. Latency appears to be established after activated CD4+ T cells, the principal targets of HIV-1 infection, become productively infected and survive long enough to return to a resting memory state in which viral expression is inhibited by changes in the cellular environment. This protocol describes an ex vivo primary cell system that is generated under conditions that reflect the in vivo establishment of latency. Creation of these latency model cells takes 12 weeks and, once established, the cells can be maintained and used for several months. The resulting cell population contains both uninfected and latently infected cells. This primary cell model can be used to perform drug screens, study CTL responses to HIV-1, compare viral alleles, or to expand the ex vivo lifespan of cells from HIV-1 infected individuals for extended study. PMID:25375990

Multidisciplinary approaches to understanding collective cell migration in developmental biology.

PubMed

Schumacher, Linus J; Kulesa, Paul M; McLennan, Rebecca; Baker, Ruth E; Maini, Philip K

2016-06-01

Mathematical models are becoming increasingly integrated with experimental efforts in the study of biological systems. Collective cell migration in developmental biology is a particularly fruitful application area for the development of theoretical models to predict the behaviour of complex multicellular systems with many interacting parts. In this context, mathematical models provide a tool to assess the consistency of experimental observations with testable mechanistic hypotheses. In this review, we showcase examples from recent years of multidisciplinary investigations of neural crest cell migration. The neural crest model system has been used to study how collective migration of cell populations is shaped by cell-cell interactions, cell-environmental interactions and heterogeneity between cells. The wide range of emergent behaviours exhibited by neural crest cells in different embryonal locations and in different organisms helps us chart out the spectrum of collective cell migration. At the same time, this diversity in migratory characteristics highlights the need to reconcile or unify the array of currently hypothesized mechanisms through the next generation of experimental data and generalized theoretical descriptions. © 2016 The Authors.

Ancestral trees for modeling stem cell lineages genetically rather than functionally: understanding mutation accumulation and distinguishing the restrictive cancer stem cell propagation theory and the unrestricted cell propagation theory of human tumorigenesis.

PubMed

Shibata, Darryl K; Kern, Scott E

2008-01-01

Cancer stem cells either could be rare or common in tumors, constituting the major distinction between the two fundamentally opposed theoretical models of tumor progression: A newer and restrictive stem cell propagation model, in which the stem cells are a small and special minority of the tumor cells, and a standard older model, an unrestricted cell proliferation theory, in which many or most tumor cells are capable of indefinite generations of cell division. Stem cells of tumors are difficult to quantitate using functional assays, and the validity of the most common assays is seriously questioned. Nonetheless, stem cells are an essential component of any tumorigenesis model. Alternative approaches to studying tumor stem cells should be explored. Cell populations can be conceived of as having a genealogy, a relationship of cells to their ancestral lineage, from the zygote to the adult cells or neoplasms. Models using ancestral trees thus offer an anatomic and genetic means to "observe" stem cells independent of artificial conditions. Ancestral trees broaden our attention backward along a lineage, to the zygote stage, and thereby add insight into how the mutations of tumors accumulate. It is possible that a large fraction of mutations in a tumor originate from normal, endogenous, replication errors (nearly all being passenger mutations) occurring prior to the emergence of the first transformed cell. Trees can be constructed from experimental measurements - molecular clocks - of real human tissues and tumors. Detailed analysis of single-cell methylation patterns, heritable yet slightly plastic, now can provide this information in the necessary depth. Trees based on observations of molecular clocks may help us to distinguish between competing theories regarding the proliferative properties among cells of actual human tumors, to observe subtle and difficult phenomena such as the extinction of stem lineages, and to address the origins and rates of mutations in various normal, hormone-stimulated, aging, or neoplastic tissues. The simple concept that cancers arise from the transformation of a normal stem cell, the stem cell origination theory, is sometimes superficially and confusingly referred to as "the stem cell theory". This concept is compatible with but not a requisite assumption for both of the major competing theories of tumor progression, and plays essentially no role in clarifying the nature of tumor progression.

A Rapid Embryonic Stem Cell-Based Mouse Model for B-cell Lymphomas Driven by Epstein-Barr Virus Protein LMP1.

PubMed

Ba, Zhaoqing; Meng, Fei-Long; Gostissa, Monica; Huang, Pei-Yi; Ke, Qiang; Wang, Zhe; Dao, Mai N; Fujiwara, Yuko; Rajewsky, Klaus; Zhang, Baochun; Alt, Frederick W

2015-06-01

The Epstein-Barr virus (EBV) latent membrane protein 1 (LMP1) contributes to oncogenic human B-cell transformation. Mouse B cells conditionally expressing LMP1 are not predisposed to B-cell malignancies, as LMP1-expressing B cells are eliminated by T cells. However, mice with conditional B-cell LMP1 expression and genetic elimination of α/β and γ/δ T cells ("CLT" mice) die early in association with B-cell lymphoproliferation and lymphomagenesis. Generation of CLT mice involves in-breeding multiple independently segregating alleles. Thus, although introduction of additional activating or knockout mutations into the CLT model is desirable for further B-cell expansion and immunosurveillance studies, doing such experiments by germline breeding is time-consuming, expensive, and sometimes unfeasible. To generate a more tractable model, we generated clonal CLT embryonic stem (ES) cells from CLT embryos and injected them into RAG2-deficient blastocysts to generate chimeric mice, which, like germline CLT mice, harbor splenic CLT B cells and lack T cells. CLT chimeric mice generated by this RAG2-deficient blastocyst complementation ("RDBC") approach die rapidly in association with B-cell lymphoproliferation and lymphoma. Because CLT lymphomas routinely express the activation-induced cytidine deaminase (AID) antibody diversifier, we tested potential AID roles by eliminating the AID gene in CLT ES cells and testing them via RDBC. We found that CLT and AID-deficient CLT ES chimeras had indistinguishable phenotypes, showing that AID is not essential for LMP1-induced lymphomagenesis. Beyond expanding accessibility and utility of CLT mice as a cancer immunotherapy model, our studies provide a new approach for facilitating generation of genetically complex mouse cancer models. ©2015 American Association for Cancer Research.

A Rapid Embryonic Stem Cell-Based Mouse Model for B-cell Lymphomas Driven by Epstein-Barr Virus Protein LMP1

PubMed Central

Ba, Zhaoqing; Meng, Fei-Long; Gostissa, Monica; Huang, Pei-Yi; Ke, Qiang; Wang, Zhe; Dao, Mai N.; Fujiwara, Yuko; Rajewsky, Klaus; Baochun, Zhang; Alt, Frederick W.

2015-01-01

The Epstein-Barr virus (EBV) latent membrane protein 1 (LMP1) contributes to oncogenic human B-cell transformation. Mouse B cells conditionally expressing LMP1 are not predisposed to B-cell malignancies, as LMP1-expressing B cells are eliminated by T cells. However, mice with conditional B-cell LMP1 expression and genetic elimination of α/β and γ/δ T cells (“CLT” mice) die early in association with B-cell lymphoproliferation and lymphomagenesis. Generation of CLT mice involves in-breeding multiple independently segregating alleles. Thus, while introduction of additional activating or knock-out mutations into the CLT model is desirable for further B-cell expansion and immunosurveillance studies, doing such experiments by germline breeding is time-consuming, expensive and sometimes unfeasible. To generate a more tractable model, we generated clonal CLT ES cells from CLT embryos and injected them into RAG2-deficient blastocysts to generate chimeric mice, which like germline CLT mice harbor splenic CLT B cells and lack T cells. CLT chimeric mice generated by this RAG2-deficient blastocyst complementation (“RDBC”) approach die rapidly in association with B-cell lymphoproliferation and lymphoma. As CLT lymphomas routinely express the Activation-Induced Cytidine Deaminase (AID) antibody diversifier, we tested potential AID roles by eliminating the AID gene in CLT ES cells and testing them via RDBC. We found that CLT and AID-deficient CLT ES chimeras had indistinguishable phenotypes, showing that AID is not essential for LMP1-induced lymphomagenesis. Beyond expanding accessibility and utility of CLT mice as a cancer immunotherapy model, our studies provide a new approach for facilitating generation of genetically complex mouse cancer models. PMID:25934172

Colonic stem cell data are consistent with the immortal model of stem cell division under non-random strand segregation.

PubMed

Walters, K

2009-06-01

Colonic stem cells are thought to reside towards the base of crypts of the colon, but their numbers and proliferation mechanisms are not well characterized. A defining property of stem cells is that they are able to divide asymmetrically, but it is not known whether they always divide asymmetrically (immortal model) or whether there are occasional symmetrical divisions (stochastic model). By measuring diversity of methylation patterns in colon crypt samples, a recent study found evidence in favour of the stochastic model, assuming random segregation of stem cell DNA strands during cell division. Here, the effect of preferential segregation of the template strand is considered to be consistent with the 'immortal strand hypothesis', and explore the effect on conclusions of previously published results. For a sample of crypts, it is shown how, under the immortal model, to calculate mean and variance of the number of unique methylation patterns allowing for non-random strand segregation and compare them with those observed. The calculated mean and variance are consistent with an immortal model that incorporates non-random strand segregation for a range of stem cell numbers and levels of preferential strand segregation. Allowing for preferential strand segregation considerably alters previously published conclusions relating to stem cell numbers and turnover mechanisms. Evidence in favour of the stochastic model may not be as strong as previously thought.

Using induced pluripotent stem cells derived neurons to model brain diseases.

PubMed

McKinney, Cindy E

2017-07-01

The ability to use induced pluripotent stem cells (iPSC) to model brain diseases is a powerful tool for unraveling mechanistic alterations in these disorders. Rodent models of brain diseases have spurred understanding of pathology but the concern arises that they may not recapitulate the full spectrum of neuron disruptions associated with human neuropathology. iPSC derived neurons, or other neural cell types, provide the ability to access pathology in cells derived directly from a patient's blood sample or skin biopsy where availability of brain tissue is limiting. Thus, utilization of iPSC to study brain diseases provides an unlimited resource for disease modelling but may also be used for drug screening for effective therapies and may potentially be used to regenerate aged or damaged cells in the future. Many brain diseases across the spectrum of neurodevelopment, neurodegenerative and neuropsychiatric are being approached by iPSC models. The goal of an iPSC based disease model is to identify a cellular phenotype that discriminates the disease-bearing cells from the control cells. In this mini-review, the importance of iPSC cell models validated for pluripotency, germline competency and function assessments is discussed. Selected examples for the variety of brain diseases that are being approached by iPSC technology to discover or establish the molecular basis of the neuropathology are discussed.

An Improved Model of Nonuniform Coleochaete Cell Division.

PubMed

Wang, Yuandi; Cong, Jinyu

2016-08-01

Cell division is a key biological process in which cells divide forming new daughter cells. In the present study, we investigate continuously how a Coleochaete cell divides by introducing a modified differential equation model in parametric equation form. We discuss both the influence of "dead" cells and the effects of various end-points on the formation of the new cells' boundaries. We find that the boundary condition on the free end-point is different from that on the fixed end-point; the former has a direction perpendicular to the surface. It is also shown that the outer boundaries of new cells are arc-shaped. The numerical experiments and theoretical analyses for this model to construct the outer boundary are given.

A carbon dioxide stripping model for mammalian cell culture in manufacturing scale bioreactors.

PubMed

Xing, Zizhuo; Lewis, Amanda M; Borys, Michael C; Li, Zheng Jian

2017-06-01

Control of carbon dioxide within the optimum range is important in mammalian bioprocesses at the manufacturing scale in order to ensure robust cell growth, high protein yields, and consistent quality attributes. The majority of bioprocess development work is done in laboratory bioreactors, in which carbon dioxide levels are more easily controlled. Some challenges in carbon dioxide control can present themselves when cell culture processes are scaled up, because carbon dioxide accumulation is a common feature due to longer gas-residence time of mammalian cell culture in large scale bioreactors. A carbon dioxide stripping model can be used to better understand and optimize parameters that are critical to cell culture processes at the manufacturing scale. The prevailing carbon dioxide stripping models in literature depend on mass transfer coefficients and were applicable to cell culture processes with low cell density or at stationary/cell death phase. However, it was reported that gas bubbles are saturated with carbon dioxide before leaving the culture, which makes carbon dioxide stripping no longer depend on a mass transfer coefficient in the new generation cell culture processes characterized by longer exponential growth phase, higher peak viable cell densities, and higher specific production rate. Here, we present a new carbon dioxide stripping model for manufacturing scale bioreactors, which is independent of carbon dioxide mass transfer coefficient, but takes into account the gas-residence time and gas CO 2 saturation time. The model was verified by CHO cell culture processes with different peak viable cell densities (7 to 12 × 10 6  cells mL -1 ) for two products in 5,000-L and 25,000-L bioreactors. The model was also applied to a next generation cell culture process to optimize cell culture conditions and reduce carbon dioxide levels at manufacturing scale. The model provides a useful tool to understand and better control cell culture carbon dioxide profiles for process development, scale up, and characterization. Biotechnol. Bioeng. 2017;114: 1184-1194. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

The Danger Model Approach to the Pathogenesis of the Rheumatic Diseases

PubMed Central

Pacheco-Tena, César; González-Chávez, Susana Aideé

2015-01-01

The danger model was proposed by Polly Matzinger as complement to the traditional self-non-self- (SNS-) model to explain the immunoreactivity. The danger model proposes a central role of the tissular cells' discomfort as an element to prime the immune response processes in opposition to the traditional SNS-model where foreignness is a prerequisite. However recent insights in the proteomics of diverse tissular cells have revealed that under stressful conditions they have a significant potential to initiate, coordinate, and perpetuate autoimmune processes, in many cases, ruling over the adaptive immune response cells; this ruling potential can also be confirmed by observations in several genetically manipulated animal models. Here, we review the pathogenesis of rheumatic diseases such as systemic lupus erythematous, rheumatoid arthritis, spondyloarthritis including ankylosing spondylitis, psoriasis, and Crohn's disease and provide realistic approaches based on the logic of the danger model. We assume that tissular dysfunction is a prerequisite for chronic autoimmunity and propose two genetically conferred hypothetical roles for the tissular cells causing the disease: (A) the Impaired cell and (B) the paranoid cell. Both roles are not mutually exclusive. Some examples in human disease and in animal models are provided based on current evidence. PMID:25973436

Follow-the-leader cell migration requires biased cell-cell contact and local microenvironmental signals

NASA Astrophysics Data System (ADS)

Wynn, Michelle L.; Rupp, Paul; Trainor, Paul A.; Schnell, Santiago; Kulesa, Paul M.

2013-06-01

Directed cell migration often involves at least two types of cell motility that include multicellular streaming and chain migration. However, what is unclear is how cell contact dynamics and the distinct microenvironments through which cells travel influence the selection of one migratory mode or the other. The embryonic and highly invasive neural crest (NC) are an excellent model system to study this question since NC cells have been observed in vivo to display both of these types of cell motility. Here, we present data from tissue transplantation experiments in chick and in silico modeling that test our hypothesis that cell contact dynamics with each other and the microenvironment promote and sustain either multicellular stream or chain migration. We show that when premigratory cranial NC cells (at the pre-otic level) are transplanted into a more caudal region in the head (at the post-otic level), cells alter their characteristic stream behavior and migrate in chains. Similarly, post-otic NC cells migrate in streams after transplantation into the pre-otic hindbrain, suggesting that local microenvironmental signals dictate the mode of NC cell migration. Simulations of an agent-based model (ABM) that integrates the NC cell behavioral data predict that chain migration critically depends on the interplay of biased cell-cell contact and local microenvironment signals. Together, this integrated modeling and experimental approach suggests new experiments and offers a powerful tool to examine mechanisms that underlie complex cell migration patterns.

Simulation of Cell Patterning Triggered by Cell Death and Differential Adhesion in Drosophila Wing.

PubMed

Nagai, Tatsuzo; Honda, Hisao; Takemura, Masahiko

2018-02-27

The Drosophila wing exhibits a well-ordered cell pattern, especially along the posterior margin, where hair cells are arranged in a zigzag pattern in the lateral view. Based on an experimental result observed during metamorphosis of Drosophila, we considered that a pattern of initial cells autonomously develops to the zigzag pattern through cell differentiation, intercellular communication, and cell death (apoptosis) and performed computer simulations of a cell-based model of vertex dynamics for tissues. The model describes the epithelial tissue as a monolayer cell sheet of polyhedral cells. Their vertices move according to equations of motion, minimizing the sum total of the interfacial and elastic energies of cells. The interfacial energy densities between cells are introduced consistently with an ideal zigzag cell pattern, extracted from the experimental result. The apoptosis of cells is modeled by gradually reducing their equilibrium volume to zero and by assuming that the hair cells prohibit neighboring cells from undergoing apoptosis. Based on experimental observations, we also assumed wing elongation along the proximal-distal axis. Starting with an initial cell pattern similar to the micrograph experimentally obtained just before apoptosis, we carried out the simulations according to the model mentioned above and successfully reproduced the ideal zigzag cell pattern. This elucidates a physical mechanism of patterning triggered by cell apoptosis theoretically and exemplifies, to our knowledge, a new framework to study apoptosis-induced patterning. We conclude that the zigzag cell pattern is formed by an autonomous communicative process among the participant cells. Copyright © 2018 Biophysical Society. All rights reserved.

Modeling the lung: Design and development of tissue engineered macro- and micro-physiologic lung models for research use.

PubMed

Nichols, Joan E; Niles, Jean A; Vega, Stephanie P; Argueta, Lissenya B; Eastaway, Adriene; Cortiella, Joaquin

2014-09-01

Respiratory tract specific cell populations, or tissue engineered in vitro grown human lung, have the potential to be used as research tools to mimic physiology, toxicology, pathology, as well as infectious diseases responses of cells or tissues. Studies related to respiratory tract pathogenesis or drug toxicity testing in the past made use of basic systems where single cell populations were exposed to test agents followed by evaluations of simple cellular responses. Although these simple single-cell-type systems provided good basic information related to cellular responses, much more can be learned from cells grown in fabricated microenvironments which mimic in vivo conditions in specialized microfabricated chambers or by human tissue engineered three-dimensional (3D) models which allow for more natural interactions between cells. Recent advances in microengineering technology, microfluidics, and tissue engineering have provided a new approach to the development of 2D and 3D cell culture models which enable production of more robust human in vitro respiratory tract models. Complex models containing multiple cell phenotypes also provide a more reasonable approximation of what occurs in vivo without the confounding elements in the dynamic in vivo environment. The goal of engineering good 3D human models is the formation of physiologically functional respiratory tissue surrogates which can be used as pathogenesis models or in the case of 2D screening systems for drug therapy evaluation as well as human toxicity testing. We hope that this manuscript will serve as a guide for development of future respiratory tract model systems as well as a review of conventional models. © 2014 by the Society for Experimental Biology and Medicine.

Accurate path integration in continuous attractor network models of grid cells.

PubMed

Burak, Yoram; Fiete, Ila R

2009-02-01

Grid cells in the rat entorhinal cortex display strikingly regular firing responses to the animal's position in 2-D space and have been hypothesized to form the neural substrate for dead-reckoning. However, errors accumulate rapidly when velocity inputs are integrated in existing models of grid cell activity. To produce grid-cell-like responses, these models would require frequent resets triggered by external sensory cues. Such inadequacies, shared by various models, cast doubt on the dead-reckoning potential of the grid cell system. Here we focus on the question of accurate path integration, specifically in continuous attractor models of grid cell activity. We show, in contrast to previous models, that continuous attractor models can generate regular triangular grid responses, based on inputs that encode only the rat's velocity and heading direction. We consider the role of the network boundary in the integration performance of the network and show that both periodic and aperiodic networks are capable of accurate path integration, despite important differences in their attractor manifolds. We quantify the rate at which errors in the velocity integration accumulate as a function of network size and intrinsic noise within the network. With a plausible range of parameters and the inclusion of spike variability, our model networks can accurately integrate velocity inputs over a maximum of approximately 10-100 meters and approximately 1-10 minutes. These findings form a proof-of-concept that continuous attractor dynamics may underlie velocity integration in the dorsolateral medial entorhinal cortex. The simulations also generate pertinent upper bounds on the accuracy of integration that may be achieved by continuous attractor dynamics in the grid cell network. We suggest experiments to test the continuous attractor model and differentiate it from models in which single cells establish their responses independently of each other.

A transplantable TH-MYCN transgenic tumor model in C57Bl/6 mice for preclinical immunological studies in neuroblastoma.

PubMed

Kroesen, Michiel; Nierkens, Stefan; Ansems, Marleen; Wassink, Melissa; Orentas, Rimas J; Boon, Louis; den Brok, Martijn H; Hoogerbrugge, Peter M; Adema, Gosse J

2014-03-15

Current multimodal treatments for patients with neuroblastoma (NBL), including anti-disialoganglioside (GD2) monoclonal antibody (mAb) based immunotherapy, result in a favorable outcome in around only half of the patients with advanced disease. To improve this, novel immunocombinational strategies need to be developed and tested in autologous preclinical NBL models. A genetically well-explored autologous mouse model for NBL is the TH-MYCN model. However, the immunobiology of the TH-MYCN model remains largely unexplored. We developed a mouse model using a transplantable TH-MYCN cell line in syngeneic C57Bl/6 mice and characterized the immunobiology of this model. In this report, we show the relevance and opportunities of this model to study immunotherapy for human NBL. Similar to human NBL cells, syngeneic TH-MYCN-derived 9464D cells endogenously express the tumor antigen GD2 and low levels of MHC Class I. The presence of the adaptive immune system had little or no influence on tumor growth, showing the low immunogenicity of the NBL cells. In contrast, depletion of NK1.1+ cells resulted in enhanced tumor outgrowth in both wild-type and Rag1(-/-) mice, showing an important role for NK cells in the natural anti-NBL immune response. Analysis of the tumor infiltrating leukocytes ex vivo revealed the presence of both tumor associated myeloid cells and T regulatory cells, thus mimicking human NBL tumors. Finally, anti-GD2 mAb mediated NBL therapy resulted in ADCC in vitro and delayed tumor outgrowth in vivo. We conclude that the transplantable TH-MYCN model represents a relevant model for the development of novel immunocombinatorial approaches for NBL patients. © 2013 UICC.

Development & experimental validation of a SINDA/FLUINT thermal/fluid/electrical model of a multi-tube AMTEC cell

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hendricks, T.J.; Borkowski, C.A.; Huang, C.

1998-01-01

AMTEC (Alkali Metal Thermal-to-Electric Conversion) cell development has received increased attention and funding in the space power community because of several desirable performance characteristics compared to current radioisotope thermoelectric generation and solar photovoltaic (PV) power generation. AMTEC cell development is critically dependent upon the ability to predict thermal, fluid dynamic and electrical performance of an AMTEC cell which has many complex thermal, fluid dynamic and electrical processes and interactions occurring simultaneously. Development of predictive capability is critical to understanding the complex processes and interactions within the AMTEC cell, and thereby creating the ability to design high-performance, cost-effective AMTEC cells. Amore » flexible, sophisticated thermal/fluid/electrical model of an operating AMTEC cell has been developed using the SINDA/FLUINT analysis software. This model can accurately simulate AMTEC cell performance at any hot side and cold side temperature combination desired, for any voltage and current conditions, and for a broad range of cell design parameters involving the cell dimensions, current collector and electrode design, electrode performance parameters, and cell wall and thermal shield emissivity. The model simulates the thermal radiation network within the AMTEC cell using RadCAD thermal radiation analysis; hot side, cold side and cell wall conductive and radiative coupling; BASE (Beta Alumina Solid Electrode) tube electrochemistry, including electrode over-potentials; the fluid dynamics of the low-pressure sodium vapor flow to the condenser and liquid sodium flow in the wick; sodium condensation at the condenser; and high-temperature sodium evaporation in the wick. The model predicts the temperature profiles within the AMTEC cell walls, the BASE tube temperature profiles, the sodium temperature profile in the artery return, temperature profiles in the evaporator, thermal energy flows throughout the AMTEC cell, all sodium pressure drops from hot BASE tubes to the condenser, the current, voltage, and power output from the cell, and the cell efficiency. This AMTEC cell model is so powerful and flexible that it is used in radioisotope AMTEC power system design, solar AMTEC power system design, and combustion-driven power system design on several projects at Advanced Modular Power Systems, Inc. (AMPS). The model has been successfully validated against actual cell experimental data and its performance predictions agree very well with experimental data on PX-5B cells and other test cells at AMPS. {copyright} {ital 1998 American Institute of Physics.}« less

Development of Maps of Simple and Complex Cells in the Primary Visual Cortex

PubMed Central

Antolík, Ján; Bednar, James A.

2011-01-01

Hubel and Wiesel (1962) classified primary visual cortex (V1) neurons as either simple, with responses modulated by the spatial phase of a sine grating, or complex, i.e., largely phase invariant. Much progress has been made in understanding how simple-cells develop, and there are now detailed computational models establishing how they can form topographic maps ordered by orientation preference. There are also models of how complex cells can develop using outputs from simple cells with different phase preferences, but no model of how a topographic orientation map of complex cells could be formed based on the actual connectivity patterns found in V1. Addressing this question is important, because the majority of existing developmental models of simple-cell maps group neurons selective to similar spatial phases together, which is contrary to experimental evidence, and makes it difficult to construct complex cells. Overcoming this limitation is not trivial, because mechanisms responsible for map development drive receptive fields (RF) of nearby neurons to be highly correlated, while co-oriented RFs of opposite phases are anti-correlated. In this work, we model V1 as two topographically organized sheets representing cortical layer 4 and 2/3. Only layer 4 receives direct thalamic input. Both sheets are connected with narrow feed-forward and feedback connectivity. Only layer 2/3 contains strong long-range lateral connectivity, in line with current anatomical findings. Initially all weights in the model are random, and each is modified via a Hebbian learning rule. The model develops smooth, matching, orientation preference maps in both sheets. Layer 4 units become simple cells, with phase preference arranged randomly, while those in layer 2/3 are primarily complex cells. To our knowledge this model is the first explaining how simple cells can develop with random phase preference, and how maps of complex cells can develop, using only realistic patterns of connectivity. PMID:21559067

Stable Regulation of Cell Cycle Events in Mycobacteria: Insights From Inherently Heterogeneous Bacterial Populations.

PubMed

Logsdon, Michelle M; Aldridge, Bree B

2018-01-01

Model bacteria, such as E. coli and B. subtilis , tightly regulate cell cycle progression to achieve consistent cell size distributions and replication dynamics. Many of the hallmark features of these model bacteria, including lateral cell wall elongation and symmetric growth and division, do not occur in mycobacteria. Instead, mycobacterial growth is characterized by asymmetric polar growth and division. This innate asymmetry creates unequal birth sizes and growth rates for daughter cells with each division, generating a phenotypically heterogeneous population. Although the asymmetric growth patterns of mycobacteria lead to a larger variation in birth size than typically seen in model bacterial populations, the cell size distribution is stable over time. Here, we review the cellular mechanisms of growth, division, and cell cycle progression in mycobacteria in the face of asymmetry and inherent heterogeneity. These processes coalesce to control cell size. Although Mycobacterium smegmatis and Mycobacterium bovis Bacillus Calmette-Guérin (BCG) utilize a novel model of cell size control, they are similar to previously studied bacteria in that initiation of DNA replication is a key checkpoint for cell division. We compare the regulation of DNA replication initiation and strategies used for cell size homeostasis in mycobacteria and model bacteria. Finally, we review the importance of cellular organization and chromosome segregation relating to the physiology of mycobacteria and consider how new frameworks could be applied across the wide spectrum of bacterial diversity.

Stochastic Petri Net extension of a yeast cell cycle model.

PubMed

Mura, Ivan; Csikász-Nagy, Attila

2008-10-21

This paper presents the definition, solution and validation of a stochastic model of the budding yeast cell cycle, based on Stochastic Petri Nets (SPN). A specific family of SPNs is selected for building a stochastic version of a well-established deterministic model. We describe the procedure followed in defining the SPN model from the deterministic ODE model, a procedure that can be largely automated. The validation of the SPN model is conducted with respect to both the results provided by the deterministic one and the experimental results available from literature. The SPN model catches the behavior of the wild type budding yeast cells and a variety of mutants. We show that the stochastic model matches some characteristics of budding yeast cells that cannot be found with the deterministic model. The SPN model fine-tunes the simulation results, enriching the breadth and the quality of its outcome.

A theory of germinal center B cell selection, division, and exit.

PubMed

Meyer-Hermann, Michael; Mohr, Elodie; Pelletier, Nadége; Zhang, Yang; Victora, Gabriel D; Toellner, Kai-Michael

2012-07-26

High-affinity antibodies are generated in germinal centers in a process involving mutation and selection of B cells. Information processing in germinal center reactions has been investigated in a number of recent experiments. These have revealed cell migration patterns, asymmetric cell divisions, and cell-cell interaction characteristics, used here to develop a theory of germinal center B cell selection, division, and exit (the LEDA model). According to this model, B cells selected by T follicular helper cells on the basis of successful antigen processing always return to the dark zone for asymmetric division, and acquired antigen is inherited by one daughter cell only. Antigen-retaining B cells differentiate to plasma cells and leave the germinal center through the dark zone. This theory has implications for the functioning of germinal centers because compared to previous models, high-affinity antibodies appear one day earlier and the amount of derived plasma cells is considerably larger. Copyright © 2012 The Authors. Published by Elsevier Inc. All rights reserved.

Induced Pluripotent Stem Cells for Disease Modeling and Evaluation of Therapeutics for Niemann-Pick Disease Type A.

PubMed

Long, Yan; Xu, Miao; Li, Rong; Dai, Sheng; Beers, Jeanette; Chen, Guokai; Soheilian, Ferri; Baxa, Ulrich; Wang, Mengqiao; Marugan, Juan J; Muro, Silvia; Li, Zhiyuan; Brady, Roscoe; Zheng, Wei

2016-12-01

: Niemann-Pick disease type A (NPA) is a lysosomal storage disease caused by mutations in the SMPD1 gene that encodes acid sphingomyelinase (ASM). Deficiency in ASM function results in lysosomal accumulation of sphingomyelin and neurodegeneration. Currently, there is no effective treatment for NPA. To accelerate drug discovery for treatment of NPA, we generated induced pluripotent stem cells from two patient dermal fibroblast lines and differentiated them into neural stem cells. The NPA neural stem cells exhibit a disease phenotype of lysosomal sphingomyelin accumulation and enlarged lysosomes. By using this disease model, we also evaluated three compounds that reportedly reduced lysosomal lipid accumulation in Niemann-Pick disease type C as well as enzyme replacement therapy with ASM. We found that α-tocopherol, δ-tocopherol, hydroxypropyl-β-cyclodextrin, and ASM reduced sphingomyelin accumulation and enlarged lysosomes in NPA neural stem cells. Therefore, the NPA neural stem cells possess the characteristic NPA disease phenotype that can be ameliorated by tocopherols, cyclodextrin, and ASM. Our results demonstrate the efficacies of cyclodextrin and tocopherols in the NPA cell-based model. Our data also indicate that the NPA neural stem cells can be used as a new cell-based disease model for further study of disease pathophysiology and for high-throughput screening to identify new lead compounds for drug development. Currently, there is no effective treatment for Niemann-Pick disease type A (NPA). To accelerate drug discovery for treatment of NPA, NPA-induced pluripotent stem cells were generated from patient dermal fibroblasts and differentiated into neural stem cells. By using the differentiated NPA neuronal cells as a cell-based disease model system, α-tocopherol, δ-tocopherol, and hydroxypropyl-β-cyclodextrin significantly reduced sphingomyelin accumulation in these NPA neuronal cells. Therefore, this cell-based NPA model can be used for further study of disease pathophysiology and for high-throughput screening of compound libraries to identify lead compounds for drug development. ©AlphaMed Press.

Establishment of mouse neuron and microglial cell co-cultured models and its action mechanism.

PubMed

Zhang, Bo; Yang, Yunfeng; Tang, Jun; Tao, Yihao; Jiang, Bing; Chen, Zhi; Feng, Hua; Yang, Liming; Zhu, Gang

2017-06-27

The objective of this study is to establish a co-culture model of mouse neurons and microglial cells, and to analyze the mechanism of action of oxygen glucose deprivation (OGD) and transient oxygen glucose deprivation (tOGD) preconditioning cell models. Mouse primary neurons and BV2 microglial cells were successfully cultured, and the OGD and tOGD models were also established. In the co-culture of mouse primary neurons and microglial cells, the cell number of tOGD mouse neurons and microglial cells was larger than the OGD cell number, observed by a microscope. CCK-8 assay result showed that at 1h after treatment, the OD value in the control group is lower compared to all the other three groups (P < 0.05). The treatment group exhibited the highest OD value among the four groups. The results observed at 5h were consistent with the results at 1 h. Flow cytometry results showed that at 1h after treatment the apoptosis percentages is higher in the control group compared to other three groups (P < 0.05). Mouse brain tissues were collected and primary neurons cells were cultured. In the meantime mouse BV2 microglia cells were cultured. Two types of cells were co-cultured, and OGD and tOGD cell models were established. There were four groups in the experiment: control group (OGD), treatment group (tOGD+OGD), placebo group (tOGD+OGD+saline) and minocycline intervention group (tOGD+OGD+minocycline). CCK-8 kit was used to detect cell viability and flow cytometry was used to detect apoptosis. In this study, mouse primary neurons and microglial cells were co-cultured. The OGD and tOGD models were established successfully. tOGD was able to effectively protect neurons and microglial cells from damage, and inhibit the apoptosis caused by oxygen glucose deprivation.

How and why does the immunological synapse form? Physical chemistry meets cell biology.

PubMed

Chakraborty, Arup K

2002-03-05

During T lymphocyte (T cell) recognition of an antigen, a highly organized and specific pattern of membrane proteins forms in the junction between the T cell and the antigen-presenting cell (APC). This specialized cell-cell junction is called the immunological synapse. It is several micrometers large and forms over many minutes. A plethora of experiments are being performed to study the mechanisms that underlie synapse formation and the way in which information transfer occurs across the synapse. The wealth of experimental data that is beginning to emerge must be understood within a mechanistic framework if it is to prove useful in developing modalities to control the immune response. Quantitative models can complement experiments in the quest for such a mechanistic understanding by suggesting experimentally testable hypotheses. Here, a quantitative synapse assembly model is described. The model uses concepts developed in physical chemistry and cell biology and is able to predict the spatiotemporal evolution of cell shape and receptor protein patterns observed during synapse formation. Attention is directed to how the juxtaposition of model predictions and experimental data has led to intriguing hypotheses regarding the role of null and self peptides during synapse assembly, as well as correlations between T cell effector functions and the robustness of synapse assembly. We remark on some ways in which synergistic experiments and modeling studies can improve current models, and we take steps toward a better understanding of information transfer across the T cell-APC junction.

Microstructure based hygromechanical modelling of deformation of fruit tissue

NASA Astrophysics Data System (ADS)

Abera, M. K.; Wang, Z.; Verboven, P.; Nicolai, B.

2017-10-01

Quality parameters such as firmness and susceptibility to mechanical damage are affected by the mechanical properties of fruit tissue. Fruit tissue is composed of turgid cells that keep cell walls under tension, and intercellular gas spaces where cell walls of neighboring cells have separated. How the structure and properties of these complex microstructures are affecting tissue mechanics is difficult to unravel experimentally. In this contribution, a modelling methodology is presented to calculate the deformation of apple fruit tissue affected by differences in structure and properties of cells and cell walls. The model can be used to perform compression experiments in silico using a hygromechanical model that computes the stress development and water loss during tissue deformation, much like in an actual compression test. The advantage of the model is that properties and structure can be changed to test the influence on the mechanical deformation process. The effect of microstructure, turgor pressure, cell membrane permeability, wall thickness and damping) on the compressibility of the tissue was simulated. Increasing the turgor pressure and thickness of the cell walls results in increased compression resistance of apple tissue increases, as do decreasing cell size and porosity. Geometric variability of the microstructure of tissues plays a major role, affecting results more than other model parameters. Different fruit cultivars were compared, and it was demonstrated, that microstructure variations within a cultivar are so large that interpretation of cultivar-specific effects is difficult.

Microstructural Characterization of Metal Foams: An Examination of the Applicability of the Theoretical Models for Modeling Foams

NASA Technical Reports Server (NTRS)

Raj, S. V.

2010-01-01

Establishing the geometry of foam cells is useful in developing microstructure-based acoustic and structural models. Since experimental data on the geometry of the foam cells are limited, most modeling efforts use the three-dimensional, space-filling Kelvin tetrakaidecahedron. The validity of this assumption is investigated in the present paper. Several FeCrAlY foams with relative densities varying between 3 and 15 percent and cells per mm (c.p.mm.) varying between 0.2 and 3.9 c.p.mm. were microstructurally evaluated. The number of edges per face for each foam specimen was counted by approximating the cell faces by regular polygons, where the number of cell faces measured varied between 207 and 745. The present observations revealed that 50 to 57 percent of the cell faces were pentagonal while 24 to 28 percent were quadrilateral and 15 to 22 percent were hexagonal. The present measurements are shown to be in excellent agreement with literature data. It is demonstrated that the Kelvin model, as well as other proposed theoretical models, cannot accurately describe the FeCrAlY foam cell structure. Instead, it is suggested that the ideal foam cell geometry consists of 11 faces with 3 quadrilateral, 6 pentagonal faces and 2 hexagonal faces consistent with the 3-6-2 cell.

Quantifying T Lymphocyte Turnover

PubMed Central

De Boer, Rob J.; Perelson, Alan S.

2013-01-01

Peripheral T cell populations are maintained by production of naive T cells in the thymus, clonal expansion of activated cells, cellular self-renewal (or homeostatic proliferation), and density dependent cell life spans. A variety of experimental techniques have been employed to quantify the relative contributions of these processes. In modern studies lymphocytes are typically labeled with 5-bromo-2′-deoxyuridine (BrdU), deuterium, or the fluorescent dye carboxy-fluorescein diacetate succinimidyl ester (CFSE), their division history has been studied by monitoring telomere shortening and the dilution of T cell receptor excision circles (TRECs) or the dye CFSE, and clonal expansion has been documented by recording changes in the population densities of antigen specific cells. Proper interpretation of such data in terms of the underlying rates of T cell production, division, and death has proven to be notoriously difficult and involves mathematical modeling. We review the various models that have been developed for each of these techniques, discuss which models seem most appropriate for what type of data, reveal open problems that require better models, and pinpoint how the assumptions underlying a mathematical model may influence the interpretation of data. Elaborating various successful cases where modeling has delivered new insights in T cell population dynamics, this review provides quantitative estimates of several processes involved in the maintenance of naive and memory, CD4+ and CD8+ T cell pools in mice and men. PMID:23313150

ODE Constrained Mixture Modelling: A Method for Unraveling Subpopulation Structures and Dynamics

PubMed Central

Hasenauer, Jan; Hasenauer, Christine; Hucho, Tim; Theis, Fabian J.

2014-01-01

Functional cell-to-cell variability is ubiquitous in multicellular organisms as well as bacterial populations. Even genetically identical cells of the same cell type can respond differently to identical stimuli. Methods have been developed to analyse heterogeneous populations, e.g., mixture models and stochastic population models. The available methods are, however, either incapable of simultaneously analysing different experimental conditions or are computationally demanding and difficult to apply. Furthermore, they do not account for biological information available in the literature. To overcome disadvantages of existing methods, we combine mixture models and ordinary differential equation (ODE) models. The ODE models provide a mechanistic description of the underlying processes while mixture models provide an easy way to capture variability. In a simulation study, we show that the class of ODE constrained mixture models can unravel the subpopulation structure and determine the sources of cell-to-cell variability. In addition, the method provides reliable estimates for kinetic rates and subpopulation characteristics. We use ODE constrained mixture modelling to study NGF-induced Erk1/2 phosphorylation in primary sensory neurones, a process relevant in inflammatory and neuropathic pain. We propose a mechanistic pathway model for this process and reconstructed static and dynamical subpopulation characteristics across experimental conditions. We validate the model predictions experimentally, which verifies the capabilities of ODE constrained mixture models. These results illustrate that ODE constrained mixture models can reveal novel mechanistic insights and possess a high sensitivity. PMID:24992156

Quantitative comparison of the spreading and invasion of radial growth phase and metastatic melanoma cells in a three-dimensional human skin equivalent model.

PubMed

Haridas, Parvathi; McGovern, Jacqui A; McElwain, Sean D L; Simpson, Matthew J

2017-01-01

Standard two-dimensional (2D) cell migration assays do not provide information about vertical invasion processes, which are critical for melanoma progression. We provide information about three-dimensional (3D) melanoma cell migration, proliferation and invasion in a 3D melanoma skin equivalent (MSE) model. In particular, we pay careful attention to compare the structure of the tissues in the MSE with similarly-prepared 3D human skin equivalent (HSE) models. The HSE model is identically prepared to the MSE model except that melanoma cells are omitted. Using the MSE model, we examine melanoma migration, proliferation and invasion from two different human melanoma cell lines. One cell line, WM35, is associated with the early phase of the disease where spreading is thought to be confined to the epidermis. The other cell line, SK-MEL-28, is associated with the later phase of the disease where spreading into the dermis is expected. 3D MSE and HSE models are constructed using human de-epidermised dermis (DED) prepared from skin tissue. Primary fibroblasts and primary keratinocytes are used in the MSE and HSE models to ensure the formation of a stratified epidermis, with a well-defined basement membrane. Radial spreading of cells across the surface of the HSE and MSE models is observed. Vertical invasion of melanoma cells downward through the skin is observed and measured using immunohistochemistry. All measurements of invasion are made at day 0, 9, 15 and 20, providing detailed time course data. Both HSE and MSE models are similar to native skin in vivo , with a well-defined stratification of the epidermis that is separated from the dermis by a basement membrane. In the HSE and MSE we find fibroblast cells confined to the dermis, and differentiated keratinocytes in the epidermis. In the MSE, melanoma cells form colonies in the epidermis during the early part of the experiment. In the later stage of the experiment, the melanoma cells in the MSE invade deeper into the tissues. Interestingly, both the WM35 and SK-MEL-28 melanoma cells lead to a breakdown of the basement membrane and eventually enter the dermis. However, these two cell lines invade at different rates, with the SK-MEL-28 melanoma cells invading faster than the WM35 cells. The MSE and HSE models are a reliable platform for studying melanoma invasion in a 3D tissue that is similar to native human skin. Interestingly, we find that the WM35 cell line, that is thought to be associated with radial spreading only, is able to invade into the dermis. The vertical invasion of melanoma cells into the dermal region appears to be associated with a localised disruption of the basement membrane. Presenting our results in terms of time course data, along with images and quantitative measurements of the depth of invasion extends previous 3D work that has often been reported without these details.

Quantitative comparison of the spreading and invasion of radial growth phase and metastatic melanoma cells in a three-dimensional human skin equivalent model

PubMed Central

Haridas, Parvathi; McGovern, Jacqui A.; McElwain, Sean D.L.

2017-01-01

Background Standard two-dimensional (2D) cell migration assays do not provide information about vertical invasion processes, which are critical for melanoma progression. We provide information about three-dimensional (3D) melanoma cell migration, proliferation and invasion in a 3D melanoma skin equivalent (MSE) model. In particular, we pay careful attention to compare the structure of the tissues in the MSE with similarly-prepared 3D human skin equivalent (HSE) models. The HSE model is identically prepared to the MSE model except that melanoma cells are omitted. Using the MSE model, we examine melanoma migration, proliferation and invasion from two different human melanoma cell lines. One cell line, WM35, is associated with the early phase of the disease where spreading is thought to be confined to the epidermis. The other cell line, SK-MEL-28, is associated with the later phase of the disease where spreading into the dermis is expected. Methods 3D MSE and HSE models are constructed using human de-epidermised dermis (DED) prepared from skin tissue. Primary fibroblasts and primary keratinocytes are used in the MSE and HSE models to ensure the formation of a stratified epidermis, with a well-defined basement membrane. Radial spreading of cells across the surface of the HSE and MSE models is observed. Vertical invasion of melanoma cells downward through the skin is observed and measured using immunohistochemistry. All measurements of invasion are made at day 0, 9, 15 and 20, providing detailed time course data. Results Both HSE and MSE models are similar to native skin in vivo, with a well-defined stratification of the epidermis that is separated from the dermis by a basement membrane. In the HSE and MSE we find fibroblast cells confined to the dermis, and differentiated keratinocytes in the epidermis. In the MSE, melanoma cells form colonies in the epidermis during the early part of the experiment. In the later stage of the experiment, the melanoma cells in the MSE invade deeper into the tissues. Interestingly, both the WM35 and SK-MEL-28 melanoma cells lead to a breakdown of the basement membrane and eventually enter the dermis. However, these two cell lines invade at different rates, with the SK-MEL-28 melanoma cells invading faster than the WM35 cells. Discussion The MSE and HSE models are a reliable platform for studying melanoma invasion in a 3D tissue that is similar to native human skin. Interestingly, we find that the WM35 cell line, that is thought to be associated with radial spreading only, is able to invade into the dermis. The vertical invasion of melanoma cells into the dermal region appears to be associated with a localised disruption of the basement membrane. Presenting our results in terms of time course data, along with images and quantitative measurements of the depth of invasion extends previous 3D work that has often been reported without these details. PMID:28890854

WholeCellSimDB: a hybrid relational/HDF database for whole-cell model predictions.

PubMed

Karr, Jonathan R; Phillips, Nolan C; Covert, Markus W

2014-01-01

Mechanistic 'whole-cell' models are needed to develop a complete understanding of cell physiology. However, extracting biological insights from whole-cell models requires running and analyzing large numbers of simulations. We developed WholeCellSimDB, a database for organizing whole-cell simulations. WholeCellSimDB was designed to enable researchers to search simulation metadata to identify simulations for further analysis, and quickly slice and aggregate simulation results data. In addition, WholeCellSimDB enables users to share simulations with the broader research community. The database uses a hybrid relational/hierarchical data format architecture to efficiently store and retrieve both simulation setup metadata and results data. WholeCellSimDB provides a graphical Web-based interface to search, browse, plot and export simulations; a JavaScript Object Notation (JSON) Web service to retrieve data for Web-based visualizations; a command-line interface to deposit simulations; and a Python API to retrieve data for advanced analysis. Overall, we believe WholeCellSimDB will help researchers use whole-cell models to advance basic biological science and bioengineering. http://www.wholecellsimdb.org SOURCE CODE REPOSITORY: URL: http://github.com/CovertLab/WholeCellSimDB. © The Author(s) 2014. Published by Oxford University Press.

Mechanism for Collective Cell Alignment in Myxococcus xanthus Bacteria

PubMed Central

Balagam, Rajesh; Igoshin, Oleg A.

2015-01-01

Myxococcus xanthus cells self-organize into aligned groups, clusters, at various stages of their lifecycle. Formation of these clusters is crucial for the complex dynamic multi-cellular behavior of these bacteria. However, the mechanism underlying the cell alignment and clustering is not fully understood. Motivated by studies of clustering in self-propelled rods, we hypothesized that M. xanthus cells can align and form clusters through pure mechanical interactions among cells and between cells and substrate. We test this hypothesis using an agent-based simulation framework in which each agent is based on the biophysical model of an individual M. xanthus cell. We show that model agents, under realistic cell flexibility values, can align and form cell clusters but only when periodic reversals of cell directions are suppressed. However, by extending our model to introduce the observed ability of cells to deposit and follow slime trails, we show that effective trail-following leads to clusters in reversing cells. Furthermore, we conclude that mechanical cell alignment combined with slime-trail-following is sufficient to explain the distinct clustering behaviors observed for wild-type and non-reversing M. xanthus mutants in recent experiments. Our results are robust to variation in model parameters, match the experimentally observed trends and can be applied to understand surface motility patterns of other bacterial species. PMID:26308508

The role of backward cell migration in two-hit mutants’ production in the stem cell niche

PubMed Central

Bollas, Audrey

2017-01-01

It has been discovered that there are two stem cell groups in the intestinal crypts: central stem cells (CeSCs), which are at the very bottom of the crypt, and border stem cells (BSCs), which are located between CeSCs and transit amplifying cells (TAs). Moreover, backward cell migration from BSCs to CeSCs has been observed. Recently, a bi-compartmental stochastic model, which includes CeSCs and BSCs, has been developed to investigate the probability of two-hit mutant production in the stem cell niche. In this project, we improve this stochastic model by adding the probability of backward cell migration to the model. The model suggests that the probability of two-hit mutant production increases when the frequency of backward cell migration increases. Furthermore, a small non-zero probability of backward cell migration leads to the largest range of optimal values for the frequency of symmetric divisions and the portion of divisions at each stem cell compartment in terms of delaying 2-hit mutant production. Moreover, the probability of two-hit mutant production is more sensitive to the probability of symmetric divisions than to the rate of backward cell migrations. The highest probability of two-hit mutant production corresponds to the case when all stem cell’s divisions are asymmetric. PMID:28931019

Culture in embryonic kidney serum and xeno-free media as renal cell carcinoma and renal cell carcinoma cancer stem cells research model.

PubMed

Krawczyk, Krzysztof M; Matak, Damian; Szymanski, Lukasz; Szczylik, Cezary; Porta, Camillo; Czarnecka, Anna M

2018-04-01

The use of fetal bovine serum hinders obtaining reproducible experimental results and should also be removed in hormone and growth factor studies. In particular hormones found in FBS act globally on cancer cell physiology and influence transcriptome and metabolome. The aim of our study was to develop a renal carcinoma serum free culture model optimized for (embryonal) renal cells in order to select the best study model for downstream auto-, para- or endocrine research. Secondary aim was to verify renal carcinoma stem cell culture for this application. In the study, we have cultured renal cell carcinoma primary tumour cell line (786-0) as well as human kidney cancer stem cells in standard 2D monolayer cultures in Roswell Park Memorial Institute Medium or Dulbecco's Modified Eagle's Medium and Complete Human Kidney Cancer Stem Cell Medium, respectively. Serum-free, animal-component free Human Embryonic Kidney 293 media were tested. Our results revealed that xeno-free embryonal renal cells optimized culture media provide a useful tool in RCC cancer biology research and at the same time enable effective growth of RCC. We propose bio-mimic RCC cell culture model with specific serum-free and xeno-free medium that promote RCC cell viability.

Microfluidic devices for modeling cell-cell and particle-cell interactions in the microvasculature

PubMed Central

Prabhakarpandian, Balabhaskar; Shen, Ming-Che; Pant, Kapil; Kiani, Mohammad F.

2011-01-01

Cell-fluid and cell-cell interactions are critical components of many physiological and pathological conditions in the microvasculature. Similarly, particle-cell interactions play an important role in targeted delivery of therapeutics to tissue. Development of in vitro fluidic devices to mimic these microcirculatory processes has been a critical step forward in our understanding of the inflammatory process, development of nano-particulate drug carriers, and developing realistic in vitro models of the microvasculature and its surrounding tissue. However, widely used parallel plate flow based devices and assays have a number of important limitations for studying the physiological conditions in vivo. In addition, these devices are resource hungry and time consuming for performing various assays. Recently developed, more realistic, microfluidic based devices have been able to overcome many of these limitations. In this review, an overview of the fluidic devices and their use in studying the effects of shear forces on cell-cell and cell-particle interactions is presented. In addition, use of mathematical models and Computational Fluid Dynamics (CFD) based models for interpreting the complex flow patterns in the microvasculature are highlighted. Finally, the potential of 3D microfluidic devices and imaging for better representing in vivo conditions under which cell-cell and cell-particle interactions take place are discussed. PMID:21763328