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Sample records for proinflammatory profile predicts

  1. VIP impairs acquisition of the macrophage proinflammatory polarization profile.

    PubMed

    Carrión, Mar; Pérez-García, Selene; Martínez, Carmen; Juarranz, Yasmina; Estrada-Capetillo, Lizbeth; Puig-Kröger, Amaya; Gomariz, Rosa P; Gutiérrez-Cañas, Irene

    2016-12-01

    This study tested the hypothesis that vasoactive intestinal peptide (VIP) is able to modify the macrophage inflammatory profile, thus supporting its therapeutic role in autoimmune diseases. Macrophages are innate immune cells that display a variety of functions and inflammatory profiles in response to the environment that critically controls their polarization. Deregulation between the pro- and anti-inflammatory phenotypes has been involved in different pathologies. Rheumatoid arthritis (RA) is an autoimmune disease, in which macrophages are considered central effectors of synovial inflammation, displaying a proinflammatory profile. VIP is a pleiotropic neuropeptide with proven anti-inflammatory actions. As modulation of the macrophage phenotype has been implicated in the resolution of inflammatory diseases, we evaluated whether VIP is able to modulate human macrophage polarization. In vitro-polarized macrophages by GM-CSF (GM-MØ), with a proinflammatory profile, expressed higher levels of VIP receptors, vasoactive intestinal polypeptide receptors 1 and 2 (VPAC1 and VPAC2, respectively), than macrophages polarized by M-CSF (M-MØ) with anti-inflammatory activities. RA synovial macrophages, according to their GM-CSF-like polarization state, expressed both VPAC1 and VPAC2. In vitro-generated GM-MØ exposed to VIP exhibited an up-regulation of M-MØ gene marker expression, whereas their proinflammatory cytokine profile was reduced in favor of an anti-inflammatory function. Likewise, in GM-MØ, generated in the presence of VIP, VIP somehow changes the macrophages physiology profile to a less-damaging phenotype. Therefore, these results add new value to VIP as an immunomodulatory agent on inflammatory diseases. © Society for Leukocyte Biology.

  2. Identification of informative features for predicting proinflammatory potentials of engine exhausts.

    PubMed

    Wang, Chia-Chi; Lin, Ying-Chi; Lin, Yuan-Chung; Jhang, Syu-Ruei; Tung, Chun-Wei

    2017-08-18

    The immunotoxicity of engine exhausts is of high concern to human health due to the increasing prevalence of immune-related diseases. However, the evaluation of immunotoxicity of engine exhausts is currently based on expensive and time-consuming experiments. It is desirable to develop efficient methods for immunotoxicity assessment. To accelerate the development of safe alternative fuels, this study proposed a computational method for identifying informative features for predicting proinflammatory potentials of engine exhausts. A principal component regression (PCR) algorithm was applied to develop prediction models. The informative features were identified by a sequential backward feature elimination (SBFE) algorithm. A total of 19 informative chemical and biological features were successfully identified by SBFE algorithm. The informative features were utilized to develop a computational method named FS-CBM for predicting proinflammatory potentials of engine exhausts. FS-CBM model achieved a high performance with correlation coefficient values of 0.997 and 0.943 obtained from training and independent test sets, respectively. The FS-CBM model was developed for predicting proinflammatory potentials of engine exhausts with a large improvement on prediction performance compared with our previous CBM model. The proposed method could be further applied to construct models for bioactivities of mixtures.

  3. Adherent Human Alveolar Macrophages Exhibit a Transient Pro-Inflammatory Profile That Confounds Responses to Innate Immune Stimulation

    PubMed Central

    Tomlinson, Gillian S.; Booth, Helen; Petit, Sarah J.; Potton, Elspeth; Towers, Greg J.; Miller, Robert F.; Chain, Benjamin M.; Noursadeghi, Mahdad

    2012-01-01

    Alveolar macrophages (AM) are thought to have a key role in the immunopathogenesis of respiratory diseases. We sought to test the hypothesis that human AM exhibit an anti-inflammatory bias by making genome-wide comparisons with monocyte derived macrophages (MDM). Adherent AM obtained by bronchoalveolar lavage of patients under investigation for haemoptysis, but found to have no respiratory pathology, were compared to MDM from healthy volunteers by whole genome transcriptional profiling before and after innate immune stimulation. We found that freshly isolated AM exhibited a marked pro-inflammatory transcriptional signature. High levels of basal pro-inflammatory gene expression gave the impression of attenuated responses to lipopolysaccharide (LPS) and the RNA analogue, poly IC, but in rested cells pro-inflammatory gene expression declined and transcriptional responsiveness to these stimuli was restored. In comparison to MDM, both freshly isolated and rested AM showed upregulation of MHC class II molecules. In most experimental paradigms ex vivo adherent AM are used immediately after isolation. Therefore, the confounding effects of their pro-inflammatory profile at baseline need careful consideration. Moreover, despite the prevailing view that AM have an anti-inflammatory bias, our data clearly show that they can adopt a striking pro-inflammatory phenotype, and may have greater capacity for presentation of exogenous antigens than MDM. PMID:22768282

  4. Pro-inflammatory fatty acid profile and colorectal cancer risk: A Mendelian randomisation analysis.

    PubMed

    May-Wilson, Sebastian; Sud, Amit; Law, Philip J; Palin, Kimmo; Tuupanen, Sari; Gylfe, Alexandra; Hänninen, Ulrika A; Cajuso, Tatiana; Tanskanen, Tomas; Kondelin, Johanna; Kaasinen, Eevi; Sarin, Antti-Pekka; Eriksson, Johan G; Rissanen, Harri; Knekt, Paul; Pukkala, Eero; Jousilahti, Pekka; Salomaa, Veikko; Ripatti, Samuli; Palotie, Aarno; Renkonen-Sinisalo, Laura; Lepistö, Anna; Böhm, Jan; Mecklin, Jukka-Pekka; Al-Tassan, Nada A; Palles, Claire; Farrington, Susan M; Timofeeva, Maria N; Meyer, Brian F; Wakil, Salma M; Campbell, Harry; Smith, Christopher G; Idziaszczyk, Shelley; Maughan, Timothy S; Fisher, David; Kerr, Rachel; Kerr, David; Passarelli, Michael N; Figueiredo, Jane C; Buchanan, Daniel D; Win, Aung K; Hopper, John L; Jenkins, Mark A; Lindor, Noralane M; Newcomb, Polly A; Gallinger, Steven; Conti, David; Schumacher, Fred; Casey, Graham; Aaltonen, Lauri A; Cheadle, Jeremy P; Tomlinson, Ian P; Dunlop, Malcolm G; Houlston, Richard S

    2017-10-01

    While dietary fat has been established as a risk factor for colorectal cancer (CRC), associations between fatty acids (FAs) and CRC have been inconsistent. Using Mendelian randomisation (MR), we sought to evaluate associations between polyunsaturated (PUFA), monounsaturated (MUFA) and saturated FAs (SFAs) and CRC risk. We analysed genotype data on 9254 CRC cases and 18,386 controls of European ancestry. Externally weighted polygenic risk scores were generated and used to evaluate associations with CRC per one standard deviation increase in genetically defined plasma FA levels. Risk reduction was observed for oleic and palmitoleic MUFAs (OR OA  = 0.77, 95% CI: 0.65-0.92, P = 3.9 × 10 -3 ; OR POA  = 0.36, 95% CI: 0.15-0.84, P = 0.018). PUFAs linoleic and arachidonic acid had negative and positive associations with CRC respectively (OR LA  = 0.95, 95% CI: 0.93-0.98, P = 3.7 × 10 -4 ; OR AA  = 1.05, 95% CI: 1.02-1.07, P = 1.7 × 10 -4 ). The SFA stearic acid was associated with increased CRC risk (OR SA  = 1.17, 95% CI: 1.01-1.35, P = 0.041). Results from our analysis are broadly consistent with a pro-inflammatory FA profile having a detrimental effect in terms of CRC risk. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

  5. Systemic and intraperitoneal proinflammatory cytokines profiles in patients on chronic peritoneal dialysis.

    PubMed

    Maksić, Doko; Colić, Miodrag; Stanković-Popović, Verica; Radojević, Milorad; Bokonjić, Dubravko

    2007-01-01

    Cytokines are essential mediators of immune response and inflammatory reactions. Patients with chronic renal failure and on Continuous Ambulatory Peritoneal Dialysis commonly present abnormalities of immune function related to impaired kidney function, accumulation of uremic toxins and bioincompatibility of peritoneal dialysis solutions. Aim of this study was to examine effects of the CAPD solutions (standard v.s. biocompatible), as well as dialysis duration upon the local and systemic profile of the pro-inflammatory cytokines (IL-1, TNF and IL-6) in patients on CAPD. The cross-sectional study included 44 CAPD patients (27 M and 17 F, average mean age 57.12+/-16.66), of whom 21 patients were on the standard solutions (A.N.D.Y.Disc) for peritoneal dialysis and 23 on the biocompatible solutions (Gambrosol bio trio, Stay Safe balance). The average dialysis treatment period was 3.59+/-2.67 years. In all CAPD patients dialysed longer than 6 months, levels of IL-1. TNF and IL-6 in the serum and dialysis effluent were analysed in the phase without acute infection-related complications (CAPD peritonitis, infection of the catheter exit-site, other acute infections). The control group included 20 patients with the CRF (stage IV and V) whose serum levels of the examined cytokines were also determined. Levels of the inflammatory cytokines were measured by commercial specific ELISA kits (BioSource, Camarillo, California, USA). Statistical analysis of the obtained results was performed by commercial statistics PC software (Stat for Windows, R.4.5. SAD). The serum IL-1 and IL-6 levels were not statistically significantly different in patients on CAPD, irrespective of the type of the used dialysis solutions and in the control group of patients with CRF. The serum TNF levels, unlike IL-1 and IL-6, were statistically significantly higher in patients on CAPD in comparison with the control group of patients (13.203.23 v.s. 5.594.54, p< 0.001, Mann Whitney test). The serum and effluent

  6. Long-Term Dietary Sodium Restriction Increases Adiponectin Expression and Ameliorates the Proinflammatory Adipokine Profile in Obesity

    PubMed Central

    Baudrand, R; Lian, CG; Lian, BQ; Ricchiuti, V; Yao, TM; Li, J; Williams, GH; Adler, GK

    2015-01-01

    Background/Aim Obesity is associated with changes in adiponectin and pro-inflammatory adipokines. Sodium intake can affect adipokine secretion suggesting a role in cardiovascular dysfunction. We tested if long-term dietary sodium restriction modifies the expression of adiponectin and ameliorates the pro-inflammatory profile of obese, diabetic Methods/Results Db/db mice were randomized to high sodium (HS 1.6% Na+, n=6) or low sodium (LS 0.03% Na+, n=8) diet for 16 weeks and compared with lean, db/+ mice on HS diet (n=8). Insulin levels were 50% lower in the db/db mice on LS diet when compared with HS db/db (p <0.05). LS diet increased cardiac adiponectin mRNA levels in db/db mice by 5-fold when compared with db/db mice on HS diet and by 2-fold when compared with HS lean mice (both p < 0.01). LS diet increased adiponectin in adipose tissue compared with db/db mice on HS diet, achieving levels similar to those of lean mice. MCP-1, IL-6 and TNF-α expression were reduced more than 50% in adipose tissue of db/db mice on LS diet when compared with HS db/db mice (all p < 0.05), to levels observed in the HS lean mice. Further, LS db/db mice had significantly reduced circulating MCP-1 and IL-6 levels when compared with HS db/db mice (both p < 0.01). Conclusion In obese-diabetic mice, long-term LS diet increases adiponectin in heart and adipose tissue and reduces pro-inflammatory factors in adipose tissue and plasma. These additive mechanisms may contribute to the potential cardioprotective benefits of LS diet in obesity-related metabolic disorders. PMID:24418377

  7. DNA Methylation Profiles of Selected Pro-Inflammatory Cytokines in Alzheimer Disease.

    PubMed

    Nicolia, Vincenzina; Cavallaro, Rosaria A; López-González, Irene; Maccarrone, Mauro; Scarpa, Sigfrido; Ferrer, Isidre; Fuso, Andrea

    2017-01-01

    By means of functional genomics analysis, we recently described the mRNA expression profiles of various genes involved in the neuroinflammatory response in the brains of subjects with late-onset Alzheimer Disease (LOAD). Some of these genes, namely interleukin (IL)-1β and IL-6, showed distinct expression profiles with peak expression during the first stages of the disease and control-like levels at later stages. IL-1β and IL-6 genes are modulated by DNA methylation in different chronic and degenerative diseases; it is also well known that LOAD may have an epigenetic basis. Indeed, we and others have previously reported gene-specific DNA methylation alterations in LOAD and in related animal models. Based on these data, we studied the DNA methylation profiles, at single cytosine resolution, of IL-1β and IL-6 5'-flanking region by bisulphite modification in the cortex of healthy controls and LOAD patients at 2 different disease stages: Braak I-II/A and Braak V-VI/C. Our analysis provides evidence that neuroinflammation in LOAD is associated with (and possibly mediated by) epigenetic modifications. © 2017 American Association of Neuropathologists, Inc. All rights reserved.

  8. Lack of pro-inflammatory cytokine mobilization predicts poor prognosis in patients with acute heart failure.

    PubMed

    Vistnes, M; Høiseth, A D; Røsjø, H; Nygård, S; Pettersen, E; Søyseth, V; Hurlen, P; Christensen, G; Omland, T

    2013-03-01

    The aim of this study was to gain insight in the inflammatory response in acute heart failure (AHF) by assessing (1) plasma cytokine profiles and (2) prognostic value of circulating cytokines in AHF patients. Plasma levels of 26 cytokines were quantified by multiplex protein arrays in 36 patients with congestive AHF, characterized by echocardiographic, radiologic, and clinical examinations on admission, during hospitalization and at discharge. Recurrent AHF leading to death or readmission constituted the combined end point, and all patients were followed for 120 days after discharge. Levels of 15 of the measured cytokines were higher in AHF than in healthy subjects (n=22) on admission. Low levels of MCP-1, IL-1β and a low IL-1β/IL-1ra ratio predicted fatal and non-fatal AHF within 120 days. Patients with low circulating levels of IL-1β had lower left ventricular ejection fraction and higher levels of N-terminal pro-B-type natriuretic peptide, while patients with low levels of MCP-1 had higher E/E' and inferior caval vein diameter, than patients with high levels. Immune activation, reflected in increased cytokine levels, is present in AHF patients. Interestingly, failure to increase secretion of IL-1β and MCP-1 during AHF is associated with poor outcome. Copyright © 2013 Elsevier Ltd. All rights reserved.

  9. Procalcitonin and proinflammatory parameters in diabetic foot infection as new predictive factor

    NASA Astrophysics Data System (ADS)

    Raheem, Shler Gh.; Al-Barzinji, Ruqaya M.; Mansoor, Husham Y.; Al-Dabbagh, Ali A.

    2017-09-01

    Diabetic foot is a common complication of diabetes due to changes in blood vessels and nerves, often leads to ulceration and subsequent limb amputation if not treated early. A new diagnostic marker of bacterial infections is procalcitonin. C-reactive protein, Interleukin1β, Interleukin-6 and tumor necrosis factor-α as proinflammatory parameters increased in Diabetic foot infection. We evaluated above parameters in patients with diabetic foot infections in different grades. A total of 130 diabetic patients were enrolled in this case control study between June 2011 and March 2012 in Rizgary, Emergency and Hawler Teaching Hospitals, 90 of them with diabetic foot lesion as a patient group. 40 without foot lesion, as a patient control and 20 individuals as healthy control. Assessment of above parameters in sera of study groups and also bacteriological tests (bacterial isolation and identification) were done. Serum procalcitonin levels significantly increased in patients with diabetic foot with higher Wagner grades (III, IV and V) (0.28 ± 0.04, 0.30 ± 0.07 and 0.60 ± 0.11) respectively (P<0.01), indication for amputation (0.45 ± 0.06) (P<0.01), and polymicrobial infection (0.345 ± 0.043) (P<0.05). The severity of foot ulcer based on Wagner classification system was also associated with circulating levels of C-reactive protein, Interleukin1β, Interleukin-6 and tumor necrosis factor-α (G III, IV and V) (5.36 ± 0.70, 6.38 ± 0.65, and 9.13 ± 0.88), (1.21 ± 0.08, 1.56 ± 0.16 and 2.02 ± 0.07), (23.02 ± 2.98, 36.32 ± 5.75 and 43.36 ± 6.16), and (215.39 ± 16.8, 259.21 ± 40.7 and 398.45 ± 33.4) respectively (P<0.01). A new useful diagnostic parameter in infected diabetic foot patients may be a procalcitonin especially in those with higher Wagner grades and with polymicrobial infection.

  10. Pro-inflammatory cytokines and oxidative stress/antioxidant parameters characterize the bio-humoral profile of early cachexia in lung cancer patients.

    PubMed

    Fortunati, Nicoletta; Manti, Roberta; Birocco, Nadia; Pugliese, Mariateresa; Brignardello, Enrico; Ciuffreda, Libero; Catalano, Maria G; Aragno, Manuela; Boccuzzi, Giuseppe

    2007-12-01

    Cancer-related cachexia, that is present in about 50% of cancer patients and accounts for 20% of all cancer deaths, is clinically characterized by progressive weight loss, anorexia, metabolic alterations, asthenia, depletion of lipid stores and severe loss of skeletal muscle proteins. The main biochemical and molecular alterations that are responsible for the syndrome are prematurely present in the progress of the disease and the identification of the early stages of cachexia can be useful in targetting patients who will benefit from early treatment. The aim of the present study was to delineate the bio-humoral profile of a group of lung cancer patients either non-cachectic or cachectic by evaluating serum pro-inflammatory cytokines and oxidative stress/antioxidant parameters (both recognized to be involved in cachexia pathogenesis) and pro-inflammatory cytokine gene expression in PBMC (Peripheral blood mononuclear cells) of cancer patients. All serum pro-inflammatory cytokines and oxidative stress/antioxidant parameters significantly increased in neoplastic patients, but only TNF-alpha, ROS, GSH and vitamin E showed a significantly greater increase in cachectic patients. Pro-inflammatory cytokine gene expression mirrored serum level behaviour except for IL-6 that was increased in serum but not as gene expression, suggesting its provenience from tumour tissue. Our data support that the simultaneous determination of ROS, GSH, vitamin E, together with TNF-alpha allows the identification of a lung cancer patient developing cancer-related cachexia. This bio-humoral profile should be used for the early diagnosis and follow-up of the syndrome. Moreover, the evaluation of gene expression in patient PBMC was helpful in differentiating tumour vs host factors, therefore being useful in the study of pathogenetic mechanisms in neoplastic cachectic patients.

  11. Nanostructured TiO2 surfaces promote polarized activation of microglia, but not astrocytes, toward a proinflammatory profile

    NASA Astrophysics Data System (ADS)

    de Astis, Silvia; Corradini, Irene; Morini, Raffaella; Rodighiero, Simona; Tomasoni, Romana; Lenardi, Cristina; Verderio, Claudia; Milani, Paolo; Matteoli, Michela

    2013-10-01

    Activation of glial cells, including astrocytes and microglia, has been implicated in the inflammatory responses underlying brain injury and neurodegenerative diseases including Alzheimer's and Parkinson's diseases. The classic activation state (M1) is characterized by high capacity to present antigens, high production of nitric oxide (NO) and reactive oxygen species (ROS) and proinflammatory cytokines. Classically activated cells act as potent effectors that drive the inflammatory response and may mediate detrimental effects on neural cells. The second phenotype (M2) is an alternative, apparently beneficial, activation state, more related to a fine tuning of inflammation, scavenging of debris, promotion of angiogenesis, tissue remodeling and repair. Specific environmental chemical signals are able to induce these different polarization states. We provide here evidence that nanostructured substrates are able, exclusively in virtue of their physical properties, to push microglia toward the proinflammatory activation phenotype, with an efficacy which reflects the graded nanoscale rugosity. The acquisition of a proinflammatory phenotype appears specific for microglia and not astrocytes, indicating that these two cell types, although sharing common innate immune responses, respond differently to external physical stimuli.

  12. Predominance of Th17 over regulatory T-cells in pleural effusions of patients with lung cancer implicates a proinflammatory profile.

    PubMed

    Prado-Garcia, Heriberto; Romero-Garcia, Susana; Rumbo-Nava, Uriel; Lopez-Gonzalez, Jose Sullivan

    2015-03-01

    Regulatory T-(Treg) and pro-inflammatory T-helper 17 (Th17) cells have been reported to be involved in the pathogenesis of pleural effusions caused by lung cancer. However, the presence of these subsets might not be a consequence of tumor pathogenesis, but rather a result of the pleural effusion itself, irrespective of its origin. In the present study, we analyzed the balance between these CD4+ T-cell subsets and compared them with those in non-malignant pleural effusions. We detected the frequencies of Treg and Th17 cells, identified as cluster of differentiation (CD)3+CD4+CD25+CD127low/- and CD3+CD4+ retinoid-related orphan receptor γt (RORγt)+ cells respectively, and proportions of interleukin (IL)17A-producing CD4+ cells in pleural effusions of patients with lung cancer, tuberculous and non-chronic pathologies by flow cytometry. The cytokine profile of stimulated CD4+ T-cells from tuberculosis and cancer groups was compared. The proportion of Th17 cells were increased whereas Tregs were decreased in both tuberculosis and cancer, but not in non-chronic pathologies. Nevertheless, CD4+ T-cells from lung cancer effusions secreted interferon (IFN)γ, IL6 and IL17A, whereas CD4+ T-cells from tuberculous effusions secreted IL10 and low levels of IFNγ. Although effusions from patients with chronic pathologies presented higher proportions of Th17 cells in comparison to those with non-chronic pathologies, only Th17 cells from malignant effusions maintained their proinflammatory profile after stimulation. Thus, in the pleural compartment of patients with lung cancer, a proinflammatory environment might be favored and possibly maintained by Th17 response. Copyright© 2015 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

  13. Profiles of neurological outcome prediction among intensivists.

    PubMed

    Racine, Eric; Dion, Marie-Josée; Wijman, Christine A C; Illes, Judy; Lansberg, Maarten G

    2009-12-01

    Advances in intensive care medicine have increased survival rates of patients with critical neurological conditions. The focus of prognostication for such patients is therefore shifting from predicting chances of survival to meaningful neurological recovery. This study assessed the variability in long-term outcome predictions among physicians and aimed to identify factors that may account for this variability. Based on a clinical vignette describing a comatose patient suffering from post-anoxic brain injury intensivists were asked in a semi-structured interview about the patient's specific neurological prognosis and about prognostication in general. Qualitative research methods were used to identify areas of variability in prognostication and to classify physicians according to specific prognostication profiles. Quantitative statistics were used to assess for associations between prognostication profiles and physicians' demographic and practice characteristics. Eighteen intensivists participated. Functional outcome predictions varied along an evaluative dimension (fair/good-poor) and a confidence dimension (certain-uncertain). More experienced physicians tended to be more pessimistic about the patient's functional outcome and more certain of their prognosis. Attitudes toward quality of life varied along an evaluative dimension (good-poor) and a "style" dimension (objective-subjective). Older and more experienced physicians were more likely to express objective judgments of quality of life and to predict a worse quality of life for the patient than their younger and less experienced counterparts. Various prognostication profiles exist among intensivists. These may be dictated by factors such as physicians' age and clinical experience. Awareness of these associations may be a first step to more uniform prognostication.

  14. Collective hormonal profiles predict group performance.

    PubMed

    Akinola, Modupe; Page-Gould, Elizabeth; Mehta, Pranjal H; Lu, Jackson G

    2016-08-30

    Prior research has shown that an individual's hormonal profile can influence the individual's social standing within a group. We introduce a different construct-a collective hormonal profile-which describes a group's hormonal make-up. We test whether a group's collective hormonal profile is related to its performance. Analysis of 370 individuals randomly assigned to work in 74 groups of three to six individuals revealed that group-level concentrations of testosterone and cortisol interact to predict a group's standing across groups. Groups with a collective hormonal profile characterized by high testosterone and low cortisol exhibited the highest performance. These collective hormonal level results remained reliable when controlling for personality traits and group-level variability in hormones. These findings support the hypothesis that groups with a biological propensity toward status pursuit (high testosterone) coupled with reduced stress-axis activity (low cortisol) engage in profit-maximizing decision-making. The current work extends the dual-hormone hypothesis to the collective level and provides a neurobiological perspective on the factors that determine who rises to the top across, not just within, social hierarchies.

  15. Divergent pro-inflammatory profile of human dendritic cells in response to commensal and pathogenic bacteria associated with the airway microbiota.

    PubMed

    Larsen, Jeppe Madura; Steen-Jensen, Daniel Bisgaard; Laursen, Janne Marie; Søndergaard, Jonas Nørskov; Musavian, Hanieh Sadat; Butt, Tariq Mahmood; Brix, Susanne

    2012-01-01

    Recent studies using culture-independent methods have characterized the human airway microbiota and report microbial communities distinct from other body sites. Changes in these airway bacterial communities appear to be associated with inflammatory lung disease, yet the pro-inflammatory properties of individual bacterial species are unknown. In this study, we compared the immune stimulatory capacity on human monocyte-derived dendritic cells (DCs) of selected airway commensal and pathogenic bacteria predominantly associated with lungs of asthma or COPD patients (pathogenic Haemophillus spp. and Moraxella spp.), healthy lungs (commensal Prevotella spp.) or both (commensal Veillonella spp. and Actinomyces spp.). All bacteria were found to induce activation of DCs as demonstrated by similar induction of CD83, CD40 and CD86 surface expression. However, asthma and COPD-associated pathogenic bacteria provoked a 3-5 fold higher production of IL-23, IL-12p70 and IL-10 cytokines compared to the commensal bacteria. Based on the differential cytokine production profiles, the studied airway bacteria could be segregated into three groups (Haemophilus spp. and Moraxella spp. vs. Prevotella spp. and Veillonella spp. vs. Actinomyces spp.) reflecting their pro-inflammatory effects on DCs. Co-culture experiments found that Prevotella spp. were able to reduce Haemophillus influenzae-induced IL-12p70 in DCs, whereas no effect was observed on IL-23 and IL-10 production. This study demonstrates intrinsic differences in DC stimulating properties of bacteria associated with the airway microbiota.

  16. Divergent Pro-Inflammatory Profile of Human Dendritic Cells in Response to Commensal and Pathogenic Bacteria Associated with the Airway Microbiota

    PubMed Central

    Larsen, Jeppe Madura; Steen-Jensen, Daniel Bisgaard; Laursen, Janne Marie; Søndergaard, Jonas Nørskov; Musavian, Hanieh Sadat; Butt, Tariq Mahmood; Brix, Susanne

    2012-01-01

    Recent studies using culture-independent methods have characterized the human airway microbiota and report microbial communities distinct from other body sites. Changes in these airway bacterial communities appear to be associated with inflammatory lung disease, yet the pro-inflammatory properties of individual bacterial species are unknown. In this study, we compared the immune stimulatory capacity on human monocyte-derived dendritic cells (DCs) of selected airway commensal and pathogenic bacteria predominantly associated with lungs of asthma or COPD patients (pathogenic Haemophillus spp. and Moraxella spp.), healthy lungs (commensal Prevotella spp.) or both (commensal Veillonella spp. and Actinomyces spp.). All bacteria were found to induce activation of DCs as demonstrated by similar induction of CD83, CD40 and CD86 surface expression. However, asthma and COPD-associated pathogenic bacteria provoked a 3–5 fold higher production of IL-23, IL-12p70 and IL-10 cytokines compared to the commensal bacteria. Based on the differential cytokine production profiles, the studied airway bacteria could be segregated into three groups (Haemophilus spp. and Moraxella spp. vs. Prevotella spp. and Veillonella spp. vs. Actinomyces spp.) reflecting their pro-inflammatory effects on DCs. Co-culture experiments found that Prevotella spp. were able to reduce Haemophillus influenzae-induced IL-12p70 in DCs, whereas no effect was observed on IL-23 and IL-10 production. This study demonstrates intrinsic differences in DC stimulating properties of bacteria associated with the airway microbiota. PMID:22363778

  17. Collective hormonal profiles predict group performance

    PubMed Central

    Akinola, Modupe; Page-Gould, Elizabeth; Mehta, Pranjal H.; Lu, Jackson G.

    2016-01-01

    Prior research has shown that an individual’s hormonal profile can influence the individual’s social standing within a group. We introduce a different construct—a collective hormonal profile—which describes a group’s hormonal make-up. We test whether a group’s collective hormonal profile is related to its performance. Analysis of 370 individuals randomly assigned to work in 74 groups of three to six individuals revealed that group-level concentrations of testosterone and cortisol interact to predict a group’s standing across groups. Groups with a collective hormonal profile characterized by high testosterone and low cortisol exhibited the highest performance. These collective hormonal level results remained reliable when controlling for personality traits and group-level variability in hormones. These findings support the hypothesis that groups with a biological propensity toward status pursuit (high testosterone) coupled with reduced stress-axis activity (low cortisol) engage in profit-maximizing decision-making. The current work extends the dual-hormone hypothesis to the collective level and provides a neurobiological perspective on the factors that determine who rises to the top across, not just within, social hierarchies. PMID:27528679

  18. Vernonia cinerea L. scavenges free radicals and regulates nitric oxide and proinflammatory cytokines profile in carrageenan induced paw edema model.

    PubMed

    Kumar, P Pratheesh; Kuttan, Girija

    2009-01-01

    In this study, we evaluated the anti-oxidant and anti-inflammatory activities of the medicinal plant, Vernonia cinerea L (Asteraceae) using in vitro as well as in vivo models. Methanolic extract of Vernonia cinerea was found to scavenge the hydroxyl radical generated by Fenton reaction (IC(50)130 microg/ml), Superoxide generated by photo reduction of riboflavin (IC(50)190 microg/ml) and inhibited lipid peroxidation significantly (IC(50)130.5 microg/ml). The drug also scavenged nitric oxide (IC(50)210 microg/ml). Intraperitoneal administration of Vernonia cinerea was found to inhibit the PMA induced Superoxide generation in mice peritoneal macrophages. The administration of Vernonia cinerea to mice significantly increased the levels of catalase, superoxide dismutase, glutathione, glutathione peroxidase and glutathione-S transferase in blood and liver, whereas lipid peroxidation activity was significantly decreased. It was also found that Vernonia cinerea extract significantly inhibited carrageenan induced inflammation, compared with control models. Down regulation of pro-inflammatory cytokine level and gene expression were also support the above result.

  19. Adaptive method for electron bunch profile prediction

    DOE PAGES

    Scheinker, Alexander; Gessner, Spencer

    2015-10-15

    We report on an experiment performed at the Facility for Advanced Accelerator Experimental Tests (FACET) at SLAC National Accelerator Laboratory, in which a new adaptive control algorithm, one with known, bounded update rates, despite operating on analytically unknown cost functions, was utilized in order to provide quasi-real-time bunch property estimates of the electron beam. Multiple parameters, such as arbitrary rf phase settings and other time-varying accelerator properties, were simultaneously tuned in order to match a simulated bunch energy spectrum with a measured energy spectrum. Thus, the simple adaptive scheme was digitally implemented using matlab and the experimental physics and industrialmore » control system. Finally, the main result is a nonintrusive, nondestructive, real-time diagnostic scheme for prediction of bunch profiles, as well as other beam parameters, the precise control of which are important for the plasma wakefield acceleration experiments being explored at FACET.« less

  20. Adaptive method for electron bunch profile prediction

    SciTech Connect

    Scheinker, Alexander; Gessner, Spencer

    2015-10-01

    We report on an experiment performed at the Facility for Advanced Accelerator Experimental Tests (FACET) at SLAC National Accelerator Laboratory, in which a new adaptive control algorithm, one with known, bounded update rates, despite operating on analytically unknown cost functions, was utilized in order to provide quasi-real-time bunch property estimates of the electron beam. Multiple parameters, such as arbitrary rf phase settings and other time-varying accelerator properties, were simultaneously tuned in order to match a simulated bunch energy spectrum with a measured energy spectrum. The simple adaptive scheme was digitally implemented using matlab and the experimental physics and industrial controlmore » system. The main result is a nonintrusive, nondestructive, real-time diagnostic scheme for prediction of bunch profiles, as well as other beam parameters, the precise control of which are important for the plasma wakefield acceleration experiments being explored at FACET. © 2015 authors. Published by the American Physical Society.« less

  1. Predictive genomics DNA profiling for athletic performance.

    PubMed

    Kambouris, Marios; Ntalouka, Foteini; Ziogas, Georgios; Maffulli, Nicola

    2012-12-01

    Genes control biological processes such as muscle, cartilage and bone formation, muscle energy production and metabolism (mitochondriogenesis, lactic acid removal), blood and tissue oxygenation (erythropoiesis, angiogenesis, vasodilatation), all essential in sport and athletic performance. DNA sequence variations in such genes confer genetic advantages that can be exploited, or genetic 'barriers' that could be overcome to achieve optimal athletic performance. Predictive Genomic DNA Profiling for athletic performance reveals genetic variations that may be associated with better suitability for endurance, strength and speed sports, vulnerability to sports-related injuries and individualized nutritional requirements. Knowledge of genetic 'suitability' in respect to endurance capacity or strength and speed would lead to appropriate sport and athletic activity selection. Knowledge of genetic advantages and barriers would 'direct' an individualized training program, nutritional plan and nutritional supplementation to achieving optimal performance, overcoming 'barriers' that results from intense exercise and pressure under competition with minimum waste of time and energy and avoidance of health risks (hypertension, cardiovascular disease, inflammation, and musculoskeletal injuries) related to exercise, training and competition. Predictive Genomics DNA profiling for Athletics and Sports performance is developing into a tool for athletic activity and sport selection and for the formulation of individualized and personalized training and nutritional programs to optimize health and performance for the athlete. Human DNA sequences are patentable in some countries, while in others DNA testing methodologies [unless proprietary], are non patentable. On the other hand, gene and variant selection, genotype interpretation and the risk and suitability assigning algorithms based on the specific Genomic variants used are amenable to patent protection.

  2. Red wine intake but not other alcoholic beverages increases total antioxidant capacity and improves pro-inflammatory profile after an oral fat diet in healthy volunteers.

    PubMed

    Torres, A; Cachofeiro, V; Millán, J; Lahera, V; Nieto, M L; Martín, R; Bello, E; Alvarez-Sala, L A

    2015-12-01

    Different alcoholic beverages exert different effects on inflammation and oxidative stress but these results are controversial and scanty in some aspects. We analyze the effect of different alcoholic beverages after a fat-enriched diet on lipid profile, inflammatory factors and oxidative stress in healthy people in a controlled environment. We have performed a cross-over design in five different weeks. Sixteen healthy volunteers have received the same oral fat-enriched diet (1486kcal/m(2)) and a daily total amount of 16g/m(2) of alcohol, of different beverages (red wine, vodka, brandy or rum) and equivalent caloric intakes as sugar with water in the control group. We have measured the levels of serum lipids, high sensitivity C-reactive protein (hsCRP), tumor necrosis factor α (TNFα), interleukin 6 (IL-6), soluble phospholipase A2 (sPLA2), lipid peroxidation (LPO) and total antioxidant capacity (TAC). Red wine intake was associated with decreased of mean concentrations of hsCRP, TNFα and IL-6 induced by fat-enriched diet (p<0.05); nevertheless, sPLA2 concentrations were not significantly modified. After a fat-enriched diet added with red wine, TAC increased as compared to the same diet supplemented with rum, brandy, vodka or the control (water with sugar) (p<0.05). Moderate red wine intake, but not other alcoholic beverages, decreased pro-inflammatory factors and increased total antioxidant capacity despite a fat-enriched diet intake in healthy young volunteers. Copyright © 2015 Elsevier España, S.L.U. y Sociedad Española de Medicina Interna (SEMI). All rights reserved.

  3. Increased plasma DPP4 activities predict new-onset atherosclerosis in association with its proinflammatory effects in Chinese over a four year period: A prospective study.

    PubMed

    Zheng, T P; Yang, F; Gao, Y; Baskota, A; Chen, T; Tian, H M; Ran, X W

    2014-08-01

    DPP4, a novel proinflammatory cytokine, is involved in the inflammatory process through its interaction with IGF-II/M6P receptor. We aimed to investigate whether it could predict new-onset atherosclerosis in Chinese. A prospective study was conducted of 590 adults (213 men and 377 women) aged 18-70 years without atherosclerosis examined in 2007(baseline) and 2011(follow-up). Circulating DPP4 activity, inflammatory markers, IGF-II/M6P receptor and common carotid artery Intima-Media Thickness (C-IMT) were measured at baseline and four years later. At baseline, individuals in the highest quartile of DPP4 activity had higher age, WHR, BMI, SBP, fasting insulin, 2h-PG, TG, LDL-C, IL-6, hs-CRP, IGF-II/M6P-R, C-IMT and lower HDL-C compared with individuals in the lowest quartile. After a 4-year follow-up, 71 individuals developed atherosclerosis. In multiple linear regression analysis, baseline DPP4 activity was an independent predictor of an increase in inflammatory markers, IGF-II/M6P receptor, and C-IMT over a 4-year period (all P < 0.01). In multivariable-adjusted models, the odds ratio (OR) for incident atherosclerosis comparing the highest with the lowest quartiles of DPP4 activity was 3.17 (95%CI 1.33-7.58) after adjustment for confounding risk factors (P = 0.009). The incidence of atherosclerosis owing to DPP4 activity increased by 12.41%. DPP4 activity is an important predictor of the onset of inflammation and atherosclerosis in apparently healthy Chinese. This finding may have important implications for understanding the proinflammatory role of DPP-4 in the pathogenesis of atherosclerosis. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  4. Predicting Academic Success Using Admission Profiles

    ERIC Educational Resources Information Center

    Davidovitch, Nitza; Soen, Dan

    2015-01-01

    This study, conducted at a tertiary education institution in Israel, following two previous studies, was designed to deal again with a question that is a topic of debate in Israel and worldwide: Is there justification for the approach that considers restrictive university admission policies an efficient tool for predicting students' success at the…

  5. Gene Expression Profiling Predicts the Development of Oral Cancer

    PubMed Central

    Saintigny, Pierre; Zhang, Li; Fan, You-Hong; El-Naggar, Adel K.; Papadimitrakopoulou, Vali; Feng, Lei; Lee, J. Jack; Kim, Edward S.; Hong, Waun Ki; Mao, Li

    2011-01-01

    Patients with oral preneoplastic lesion (OPL) have high risk of developing oral cancer. Although certain risk factors such as smoking status and histology are known, our ability to predict oral cancer risk remains poor. The study objective was to determine the value of gene expression profiling in predicting oral cancer development. Gene expression profile was measured in 86 of 162 OPL patients who were enrolled in a clinical chemoprevention trial that used the incidence of oral cancer development as a prespecified endpoint. The median follow-up time was 6.08 years and 35 of the 86 patients developed oral cancer over the course. Gene expression profiles were associated with oral cancer-free survival and used to develope multivariate predictive models for oral cancer prediction. We developed a 29-transcript predictive model which showed marked improvement in terms of prediction accuracy (with 8% predicting error rate) over the models using previously known clinico-pathological risk factors. Based on the gene expression profile data, we also identified 2182 transcripts significantly associated with oral cancer risk associated genes (P-value<0.01, single variate Cox proportional hazards model). Functional pathway analysis revealed proteasome machinery, MYC, and ribosomes components as the top gene sets associated with oral cancer risk. In multiple independent datasets, the expression profiles of the genes can differentiate head and neck cancer from normal mucosa. Our results show that gene expression profiles may improve the prediction of oral cancer risk in OPL patients and the significant genes identified may serve as potential targets for oral cancer chemoprevention. PMID:21292635

  6. Effect of Roller Profile on Cylindrical Roller Bearing Life Prediction

    NASA Technical Reports Server (NTRS)

    Poplawski, Joseph V.; Zaretsky, Erwin V.; Peters, Steven M.

    2000-01-01

    Four roller profiles used in cylindrical roller bearing design and manufacture were analyzed using both a closed form solution and finite element analysis (FEA) for stress and life. The roller profiles analyzed were flat, tapered end, aerospace, and fully crowned loaded against a flat raceway. Four rolling-element bearing life models were chosen for this analysis and compared. These were those of Weibull, Lundberg and Palmgren, Ioannides and Harris, and Zaretsky. The flat roller profile without edge loading has the longest predicted life. However, edge loading can reduce life by as much as 98 percent. The end tapered profile produced the highest lives but not significantly different than the aerospace profile. The fully crowned profile produces the lowest lives. The resultant predicted life at each stress condition not only depends on the life equation used but also on the Weibull slope assumed. For Weibull slopes of 1.5 and 2, both Lundberg-Palmgren and Iaonnides-Harris equations predict lower lives than the ANSI/ABMAJISO standards. Based upon the Hertz stresses for line contact, the accepted load-life exponent of 10/3 results in a maximum Hertz stress-life exponent equal to 6.6. This value is inconsistent with that experienced in the field.

  7. Metabolic Profiles Predict Adverse Events Following Coronary Artery Bypass Grafting

    PubMed Central

    Shah, Asad A.; Craig, Damian M.; Sebek, Jacqueline K.; Haynes, Carol; Stevens, Robert C.; Muehlbauer, Michael J.; Granger, Christopher B.; Hauser, Elizabeth R.; Newby, L. Kristin; Newgard, Christopher B.; Kraus, William E.; Hughes, G. Chad; Shah, Svati H.

    2012-01-01

    Objectives Clinical models incompletely predict outcomes following coronary artery bypass grafting. Novel molecular technologies may identify biomarkers to improve risk stratification. We examined whether metabolic profiles can predict adverse events in patients undergoing coronary artery bypass grafting. Methods The study population comprised 478 subjects from the CATHGEN biorepository of patients referred for cardiac catheterization who underwent coronary artery bypass grafting after enrollment. Targeted mass spectrometry-based profiling of 69 metabolites was performed in frozen, fasting plasma samples collected prior to surgery. Principal-components analysis and Cox proportional hazards regression modeling were used to assess the relation between metabolite factor levels and a composite outcome of post-coronary artery bypass grafting myocardial infarction, need for percutaneous coronary intervention, repeat coronary artery bypass grafting, or death. Results Over a mean follow-up of 4.3 ± 2.4 years, 126 subjects (26.4%) suffered an adverse event. Three principal-components analysis-derived factors were significantly associated with adverse outcome in univariable analysis: short-chain dicarboxylacylcarnitines (factor 2, P=0.001); ketone-related metabolites (factor 5, P=0.02); and short-chain acylcarnitines (factor 6, P=0.004). These three factors remained independently predictive of adverse outcome after multivariable adjustment: factor 2 (adjusted hazard ratio 1.23; 95% confidence interval [1.10-1.38]; P<0.001), factor 5 (1.17 [1.01-1.37], P=0.04), and factor 6 (1.14 [1.02-1.27], P=0.03). Conclusions Metabolic profiles are independently associated with adverse outcomes following coronary artery bypass grafting. These profiles may represent novel biomarkers of risk that augment existing tools for risk stratification of coronary artery bypass grafting patients and may elucidate novel biochemical pathways that mediate risk. PMID:22306227

  8. Predicting Node Degree Centrality with the Node Prominence Profile

    PubMed Central

    Yang, Yang; Dong, Yuxiao; Chawla, Nitesh V.

    2014-01-01

    Centrality of a node measures its relative importance within a network. There are a number of applications of centrality, including inferring the influence or success of an individual in a social network, and the resulting social network dynamics. While we can compute the centrality of any node in a given network snapshot, a number of applications are also interested in knowing the potential importance of an individual in the future. However, current centrality is not necessarily an effective predictor of future centrality. While there are different measures of centrality, we focus on degree centrality in this paper. We develop a method that reconciles preferential attachment and triadic closure to capture a node's prominence profile. We show that the proposed node prominence profile method is an effective predictor of degree centrality. Notably, our analysis reveals that individuals in the early stage of evolution display a distinctive and robust signature in degree centrality trend, adequately predicted by their prominence profile. We evaluate our work across four real-world social networks. Our findings have important implications for the applications that require prediction of a node's future degree centrality, as well as the study of social network dynamics. PMID:25429797

  9. Purinergic signalling links mechanical breath profile and alveolar mechanics with the pro-inflammatory innate immune response causing ventilation-induced lung injury.

    PubMed

    Hasan, Djo; Blankman, Paul; Nieman, Gary F

    2017-09-01

    Severe pulmonary infection or vigorous cyclic deformation of the alveolar epithelial type I (AT I) cells by mechanical ventilation leads to massive extracellular ATP release. High levels of extracellular ATP saturate the ATP hydrolysis enzymes CD39 and CD73 resulting in persistent high ATP levels despite the conversion to adenosine. Above a certain level, extracellular ATP molecules act as danger-associated molecular patterns (DAMPs) and activate the pro-inflammatory response of the innate immunity through purinergic receptors on the surface of the immune cells. This results in lung tissue inflammation, capillary leakage, interstitial and alveolar oedema and lung injury reducing the production of surfactant by the damaged AT II cells and deactivating the surfactant function by the concomitant extravasated serum proteins through capillary leakage followed by a substantial increase in alveolar surface tension and alveolar collapse. The resulting inhomogeneous ventilation of the lungs is an important mechanism in the development of ventilation-induced lung injury. The high levels of extracellular ATP and the upregulation of ecto-enzymes and soluble enzymes that hydrolyse ATP to adenosine (CD39 and CD73) increase the extracellular adenosine levels that inhibit the innate and adaptive immune responses rendering the host susceptible to infection by invading microorganisms. Moreover, high levels of extracellular adenosine increase the expression, the production and the activation of pro-fibrotic proteins (such as TGF-β, α-SMA, etc.) followed by the establishment of lung fibrosis.

  10. Modulation of immune response by Vernonia cinerea L. inhibits the proinflammatory cytokine profile, iNOS, and COX-2 expression in LPS-stimulated macrophages.

    PubMed

    Pratheeshkumar, P; Kuttan, Girija

    2011-03-01

    The effect of methanolic extract of Vernonia cinerea L. on the immune system was studied using BALB/c mice. Intraperitoneal (i.p.) administration of five doses of the extract (20 mg/kg body weight) was found to enhance the total white blood cell (WBC) count (13,700 ± 463 cells/mm(3)) on 6th day, bone marrow cellularity (27.9 ± 2.1 × 10(6) cells/femur) and number of α-esterase positive cells (1184 ± 56.29/4000 cells). Treatment with V. cinerea along with the antigen, sheep red blood cells (SRBC), produced an enhancement in the circulating antibody titre and the number of plaque forming cells (PFC) in the spleen. Maximum number of PFC (304.16 ± 12.4) was obtained on the 6th day. It also enhanced the proliferation of splenocytes, thymocytes and bone marrow cells both in the presence and absence of specific mitogens in vitro and in vivo. Administration of V. cinerea significantly reduced the lipopolysaccharide (LPS) induced elevated levels of nitric oxide (NO) and proinflammatory cytokines such as tumor necrosis factor-α, interleukin-1 (IL-1β), and IL-6 in mice. Treatment of V. cinerea methanolic extract also showed an enhancement in the phagocytic activity of peritoneal macrophages. Moreover The extract downregulated the inducible NO synthase and cyclooxygenase-2 (COX-2) mRNA expression in LPS-stimulated macrophages. These results indicate the immunomodulatory activity of V. cinerea.

  11. Acylcarnitines profile best predicts survival in horses with atypical myopathy

    PubMed Central

    Detilleux, Johann; Cello, Christophe; Amory, Hélène; Marcillaud-Pitel, Christel; Richard, Eric; van Galen, Gaby; van Loon, Gunther; Lefère, Laurence; Votion, Dominique-Marie

    2017-01-01

    Equine atypical myopathy (AM) is caused by hypoglycin A intoxication and is characterized by a high fatality rate. Predictive estimation of survival in AM horses is necessary to prevent unnecessary suffering of animals that are unlikely to survive and to focus supportive therapy on horses with a possible favourable prognosis of survival. We hypothesized that outcome may be predicted early in the course of disease based on the assumption that the acylcarnitine profile reflects the derangement of muscle energetics. We developed a statistical model to prognosticate the risk of death of diseased animals and found that estimation of outcome may be drawn from three acylcarnitines (C2, C10:2 and C18 -carnitines) with a high sensitivity and specificity. The calculation of the prognosis of survival makes it possible to distinguish the horses that will survive from those that will die despite severe signs of acute rhabdomyolysis in both groups. PMID:28846683

  12. Metabolomic profiling in the prediction of gestational diabetes mellitus.

    PubMed

    Bentley-Lewis, Rhonda; Huynh, Jennifer; Xiong, Grace; Lee, Hang; Wenger, Julia; Clish, Clary; Nathan, David; Thadhani, Ravi; Gerszten, Robert

    2015-06-01

    Metabolomic profiling in populations with impaired glucose tolerance has revealed that branched chain and aromatic amino acids (BCAAs) are predictive of type 2 diabetes. Because gestational diabetes mellitus (GDM) shares pathophysiological similarities with type 2 diabetes, the metabolite profile predictive of type 2 diabetes could potentially identify women who will develop GDM. We conducted a nested case-control study of 18- to 40-year-old women who participated in the Massachusetts General Hospital Obstetrical Maternal Study between 1998 and 2007. Participants were enrolled during their first trimester of a singleton pregnancy and fasting serum samples were collected. The women were followed throughout pregnancy and identified as having GDM or normal glucose tolerance (NGT) in the third trimester. Women with GDM (n = 96) were matched to women with NGT (n = 96) by age, BMI, gravidity and parity. Liquid chromatography-mass spectrometry was used to measure the levels of 91 metabolites. Data analyses revealed the following characteristics (mean ± SD): age 32.8 ± 4.4 years, BMI 28.3 ± 5.6 kg/m(2), gravidity 2 ± 1 and parity 1 ± 1. Six metabolites (anthranilic acid, alanine, glutamate, creatinine, allantoin and serine) were identified as having significantly different levels between the two groups in conditional logistic regression analyses (p < 0.05). The levels of the BCAAs did not differ significantly between GDM and NGT. Metabolic markers identified as being predictive of type 2 diabetes may not have the same predictive power for GDM. However, further study in a racially/ethnically diverse population-based cohort is necessary.

  13. Metabolomic profiling in the prediction of gestational diabetes mellitus

    PubMed Central

    Huynh, Jennifer; Xiong, Grace; Lee, Hang; Wenger, Julia; Clish, Clary; Nathan, David; Thadhani, Ravi; Gerszten, Robert

    2015-01-01

    Aims/hypothesis Metabolomic profiling in populations with impaired glucose tolerance has revealed that branched chain and aromatic amino acids (BCAAs) are predictive of type 2 diabetes. Because gestational diabetes mellitus (GDM) shares pathophysiological similarities with type 2 diabetes, the metabolite profile predictive of type 2 diabetes could potentially identify women who will develop GDM. Methods We conducted a nested case–control study of 18- to 40-year-old women who participated in the Massachusetts General Hospital Obstetrical Maternal Study between 1998 and 2007. Participants were enrolled during their first trimester of a singleton pregnancy and fasting serum samples were collected. The women were followed throughout pregnancy and identified as having GDM or normal glucose tolerance (NGT) in the third trimester. Women with GDM (n=96) were matched to women with NGT (n=96) by age, BMI, gravidity and parity. Liquid chromatography–mass spectrometry was used to measure the levels of 91 metabolites. Results Data analyses revealed the following characteristics (mean±SD): age 32.8±4.4 years, BMI 28.3±5.6 kg/m2, gravidity 2±1 and parity 1±1. Six metabolites (anthranilic acid, alanine, glutamate, creatinine, allantoin and serine) were identified as having significantly different levels between the two groups in conditional logistic regression analyses (p<0.05). The levels of the BCAAs did not differ significantly between GDM and NGT. Conclusions/interpretation Metabolic markers identified as being predictive of type 2 diabetes may not have the same predictive power for GDM. However, further study in a racially/ethnically diverse population-based cohort is necessary. PMID:25748329

  14. Periodontal profile classes predict periodontal disease progression and tooth loss.

    PubMed

    Morelli, Thiago; Moss, Kevin L; Preisser, John S; Beck, James D; Divaris, Kimon; Wu, Di; Offenbacher, Steven

    2018-02-01

    Current periodontal disease taxonomies have limited utility for predicting disease progression and tooth loss; in fact, tooth loss itself can undermine precise person-level periodontal disease classifications. To overcome this limitation, the current group recently introduced a novel patient stratification system using latent class analyses of clinical parameters, including patterns of missing teeth. This investigation sought to determine the clinical utility of the Periodontal Profile Classes and Tooth Profile Classes (PPC/TPC) taxonomy for risk assessment, specifically for predicting periodontal disease progression and incident tooth loss. The analytic sample comprised 4,682 adult participants of two prospective cohort studies (Dental Atherosclerosis Risk in Communities Study and Piedmont Dental Study) with information on periodontal disease progression and incident tooth loss. The PPC/TPC taxonomy includes seven distinct PPCs (person-level disease pattern and severity) and seven TPCs (tooth-level disease). Logistic regression modeling was used to estimate relative risks (RR) and 95% confidence intervals (CI) for the association of these latent classes with disease progression and incident tooth loss, adjusting for examination center, race, sex, age, diabetes, and smoking. To obtain personalized outcome propensities, risk estimates associated with each participant's PPC and TPC were combined into person-level composite risk scores (Index of Periodontal Risk [IPR]). Individuals in two PPCs (PPC-G: Severe Disease and PPC-D: Tooth Loss) had the highest tooth loss risk (RR = 3.6; 95% CI = 2.6 to 5.0 and RR = 3.8; 95% CI = 2.9 to 5.1, respectively). PPC-G also had the highest risk for periodontitis progression (RR = 5.7; 95% CI = 2.2 to 14.7). Personalized IPR scores were positively associated with both periodontitis progression and tooth loss. These findings, upon additional validation, suggest that the periodontal/tooth profile classes and the derived

  15. Prediction of fracture profile using digital image correlation

    NASA Astrophysics Data System (ADS)

    Chaitanya, G. M. S. K.; Sasi, B.; Kumar, Anish; Babu Rao, C.; Purnachandra Rao, B.; Jayakumar, T.

    2015-04-01

    Digital Image Correlation (DIC) based full field strain mapping methodology is used for mapping strain on an aluminum sample subjected to tensile deformation. The local strains on the surface of the specimen are calculated at different strain intervals. Early localization of strain is observed at a total strain of 0.050ɛ; itself, whereas a visually apparent localization of strain is observed at a total strain of 0.088ɛ;. Orientation of the line of fracture (12.0°) is very close to the orientation of locus of strain maxima (11.6°) computed from the strain mapping at 0.063ɛ itself. These results show the efficacy of the DIC based method to predict the location as well as the profile of the fracture, at an early stage.

  16. Predictive Rotation Profile Control for the DIII-D Tokamak

    NASA Astrophysics Data System (ADS)

    Wehner, W. P.; Schuster, E.; Boyer, M. D.; Walker, M. L.; Humphreys, D. A.

    2017-10-01

    Control-oriented modeling and model-based control of the rotation profile are employed to build a suitable control capability for aiding rotation-related physics studies at DIII-D. To obtain a control-oriented model, a simplified version of the momentum balance equation is combined with empirical representations of the momentum sources. The control approach is rooted in a Model Predictive Control (MPC) framework to regulate the rotation profile while satisfying constraints associated with the desired plasma stored energy and/or βN limit. Simple modifications allow for alternative control objectives, such as maximizing the plasma rotation while maintaining a specified input torque. Because the MPC approach can explicitly incorporate various types of constraints, this approach is well suited to a variety of control objectives, and therefore serves as a valuable tool for experimental physics studies. Closed-loop TRANSP simulations are presented to demonstrate the effectiveness of the control approach. Supported by the US DOE under DE-SC0010661 and DE-FC02-04ER54698.

  17. Behavioral Profile Predicts Dominance Status in Mountain Chickadees.

    PubMed

    Fox, Rebecca A; Ladage, Lara D; Roth, Timothy C; Pravosudov, Vladimir V

    2009-06-01

    Individual variation in stable behavioral traits may explain variation in ecologically-relevant behaviors such as foraging, dispersal, anti-predator behavior, and dominance. We investigated behavioral variation in mountain chickadees (Poecile gambeli), a North American parid that lives in dominance-structured winter flocks, using two common measures of behavioral profile: exploration of a novel room and novel object exploration. We related those behavioral traits to dominance status in male chickadees following brief, pair-wise encounters. Low-exploring birds (birds that visited less than four locations in the novel room) were significantly more likely to become dominant in brief, pairwise encounters with high-exploring birds (i.e., birds that visited all perching locations within a novel room). On the other hand, there was no relationship between novel object exploration and dominance. Interestingly, novel room exploration was also not correlated with novel object exploration. These results suggest that behavioral profile may predict the social status of group-living individuals. Moreover, our results contradict the idea that novel object exploration and novel room exploration are always interchangeable measures of individuals' sensitivity to environmental novelty.

  18. Predicting fiber refractive index from a measured preform index profile

    NASA Astrophysics Data System (ADS)

    Kiiveri, P.; Koponen, J.; Harra, J.; Novotny, S.; Husu, H.; Ihalainen, H.; Kokki, T.; Aallos, V.; Kimmelma, O.; Paul, J.

    2018-02-01

    When producing fiber lasers and amplifiers, silica glass compositions consisting of three to six different materials are needed. Due to the varying needs of different applications, substantial number of different glass compositions are used in the active fiber structures. Often it is not possible to find material parameters for theoretical models to estimate thermal and mechanical properties of those glass compositions. This makes it challenging to predict accurately fiber core refractive index values, even if the preform index profile is measured. Usually the desired fiber refractive index value is achieved experimentally, which is expensive. To overcome this problem, we analyzed statistically the changes between the measured preform and fiber index values. We searched for correlations that would help to predict the Δn-value change from preform to fiber in a situation where we don't know the values of the glass material parameters that define the change. Our index change models were built using the data collected from preforms and fibers made by the Direct Nanoparticle Deposition (DND) technology.

  19. The Reliability and Predictive Validity of the Stalking Risk Profile.

    PubMed

    McEwan, Troy E; Shea, Daniel E; Daffern, Michael; MacKenzie, Rachel D; Ogloff, James R P; Mullen, Paul E

    2018-03-01

    This study assessed the reliability and validity of the Stalking Risk Profile (SRP), a structured measure for assessing stalking risks. The SRP was administered at the point of assessment or retrospectively from file review for 241 adult stalkers (91% male) referred to a community-based forensic mental health service. Interrater reliability was high for stalker type, and moderate-to-substantial for risk judgments and domain scores. Evidence for predictive validity and discrimination between stalking recidivists and nonrecidivists for risk judgments depended on follow-up duration. Discrimination was moderate (area under the curve = 0.66-0.68) and positive and negative predictive values good over the full follow-up period ( Mdn = 170.43 weeks). At 6 months, discrimination was better than chance only for judgments related to stalking of new victims (area under the curve = 0.75); however, high-risk stalkers still reoffended against their original victim(s) 2 to 4 times as often as low-risk stalkers. Implications for the clinical utility and refinement of the SRP are discussed.

  20. Predicting ozone profile shape from satellite UV spectra

    NASA Astrophysics Data System (ADS)

    Xu, Jian; Loyola, Diego; Romahn, Fabian; Doicu, Adrian

    2017-04-01

    Identifying ozone profile shape is a critical yet challenging job for the accurate reconstruction of vertical distributions of atmospheric ozone that is relevant to climate change and air quality. Motivated by the need to develop an approach to reliably and efficiently estimate vertical information of ozone and inspired by the success of machine learning techniques, this work proposes a new algorithm for deriving ozone profile shapes from ultraviolet (UV) absorption spectra that are recorded by satellite instruments, e.g. GOME series and the future Sentinel missions. The proposed algorithm formulates this particular inverse problem in a classification framework rather than a conventional inversion one and places an emphasis on effectively characterizing various profile shapes based on machine learning techniques. Furthermore, a comparison of the ozone profiles from real GOME-2 data estimated by our algorithm and the classical retrieval algorithm (Optimal Estimation Method) is performed.

  1. A Gene Expression Profile of BRCAness That Predicts for Responsiveness to Platinum and PARP Inhibitors

    DTIC Science & Technology

    2015-10-01

    1 Award Number: W81XWH-10-1-0585 TITLE: A Gene Expression Profile of BRCAness That Predicts for Responsiveness to Platinum and PARP Inhibitors...TITLE AND SUBTITLE A Gene Expression Profile of BRCAness That Predicts for Responsiveness to Platinum and PARP Inhibitors 5a. CONTRACT NUMBER W81XWH...BRCAlike, i.e. not HR deficient and are resistant to PARPis but are sensitive to platinum . These tumors exhibit alterations in another DNA repair

  2. Prediction of individualized therapeutic vulnerabilities in cancer from genomic profiles

    PubMed Central

    Aksoy, Bülent Arman; Demir, Emek; Babur, Özgün; Wang, Weiqing; Jing, Xiaohong; Schultz, Nikolaus; Sander, Chris

    2014-01-01

    Motivation: Somatic homozygous deletions of chromosomal regions in cancer, while not necessarily oncogenic, may lead to therapeutic vulnerabilities specific to cancer cells compared with normal cells. A recently reported example is the loss of one of the two isoenzymes in glioblastoma cancer cells such that the use of a specific inhibitor selectively inhibited growth of the cancer cells, which had become fully dependent on the second isoenzyme. We have now made use of the unprecedented conjunction of large-scale cancer genomics profiling of tumor samples in The Cancer Genome Atlas (TCGA) and of tumor-derived cell lines in the Cancer Cell Line Encyclopedia, as well as the availability of integrated pathway information systems, such as Pathway Commons, to systematically search for a comprehensive set of such epistatic vulnerabilities. Results: Based on homozygous deletions affecting metabolic enzymes in 16 TCGA cancer studies and 972 cancer cell lines, we identified 4104 candidate metabolic vulnerabilities present in 1019 tumor samples and 482 cell lines. Up to 44% of these vulnerabilities can be targeted with at least one Food and Drug Administration-approved drug. We suggest focused experiments to test these vulnerabilities and clinical trials based on personalized genomic profiles of those that pass preclinical filters. We conclude that genomic profiling will in the future provide a promising basis for network pharmacology of epistatic vulnerabilities as a promising therapeutic strategy. Availability and implementation: A web-based tool for exploring all vulnerabilities and their details is available at http://cbio.mskcc.org/cancergenomics/statius/ along with supplemental data files. Contact: statius@cbio.mskcc.org Supplementary information: Supplementary data are available at Bioinformatics online. PMID:24665131

  3. Geometrical theory to predict eccentric photorefraction intensity profiles in the human eye

    NASA Astrophysics Data System (ADS)

    Roorda, Austin; Campbell, Melanie C. W.; Bobier, W. R.

    1995-08-01

    In eccentric photorefraction, light returning from the retina of the eye is photographed by a camera focused on the eye's pupil. We use a geometrical model of eccentric photorefraction to generate intensity profiles across the pupil image. The intensity profiles for three different monochromatic aberration functions induced in a single eye are predicted and show good agreement with the measured eccentric photorefraction intensity profiles. A directional reflection from the retina is incorporated into the calculation. Intensity profiles for symmetric and asymmetric aberrations are generated and measured. The latter profile shows a dependency on the source position and the meridian. The magnitude of the effect of thresholding on measured pattern extents is predicted. Monochromatic aberrations in human eyes will cause deviations in the eccentric photorefraction measurements from traditional crescents caused by defocus and may cause misdiagnoses of ametropia or anisometropia. Our results suggest that measuring refraction along the vertical meridian is preferred for screening studies with the eccentric photorefractor.

  4. Comparisons of Crosswind Velocity Profile Estimates Used in Fast-Time Wake Vortex Prediction Models

    NASA Technical Reports Server (NTRS)

    Pruis, Mathew J.; Delisi, Donald P.; Ahmad, Nashat N.

    2011-01-01

    Five methods for estimating crosswind profiles used in fast-time wake vortex prediction models are compared in this study. Previous investigations have shown that temporal and spatial variations in the crosswind vertical profile have a large impact on the transport and time evolution of the trailing vortex pair. The most important crosswind parameters are the magnitude of the crosswind and the gradient in the crosswind shear. It is known that pulsed and continuous wave lidar measurements can provide good estimates of the wind profile in the vicinity of airports. In this study comparisons are made between estimates of the crosswind profiles from a priori information on the trajectory of the vortex pair as well as crosswind profiles derived from different sensors and a regional numerical weather prediction model.

  5. Cell-specific prediction and application of drug-induced gene expression profiles.

    PubMed

    Hodos, Rachel; Zhang, Ping; Lee, Hao-Chih; Duan, Qiaonan; Wang, Zichen; Clark, Neil R; Ma'ayan, Avi; Wang, Fei; Kidd, Brian; Hu, Jianying; Sontag, David; Dudley, Joel

    2018-01-01

    Gene expression profiling of in vitro drug perturbations is useful for many biomedical discovery applications including drug repurposing and elucidation of drug mechanisms. However, limited data availability across cell types has hindered our capacity to leverage or explore the cell-specificity of these perturbations. While recent efforts have generated a large number of drug perturbation profiles across a variety of human cell types, many gaps remain in this combinatorial drug-cell space. Hence, we asked whether it is possible to fill these gaps by predicting cell-specific drug perturbation profiles using available expression data from related conditions--i.e. from other drugs and cell types. We developed a computational framework that first arranges existing profiles into a three-dimensional array (or tensor) indexed by drugs, genes, and cell types, and then uses either local (nearest-neighbors) or global (tensor completion) information to predict unmeasured profiles. We evaluate prediction accuracy using a variety of metrics, and find that the two methods have complementary performance, each superior in different regions in the drug-cell space. Predictions achieve correlations of 0.68 with true values, and maintain accurate differentially expressed genes (AUC 0.81). Finally, we demonstrate that the predicted profiles add value for making downstream associations with drug targets and therapeutic classes.

  6. Cell-specific prediction and application of drug-induced gene expression profiles

    PubMed Central

    Hodos, Rachel; Zhang, Ping; Lee, Hao-Chih; Duan, Qiaonan; Wang, Zichen; Clark, Neil R.; Ma'ayan, Avi; Wang, Fei; Kidd, Brian; Hu, Jianying; Sontag, David

    2017-01-01

    Gene expression profiling of in vitro drug perturbations is useful for many biomedical discovery applications including drug repurposing and elucidation of drug mechanisms. However, limited data availability across cell types has hindered our capacity to leverage or explore the cell-specificity of these perturbations. While recent efforts have generated a large number of drug perturbation profiles across a variety of human cell types, many gaps remain in this combinatorial drug-cell space. Hence, we asked whether it is possible to fill these gaps by predicting cell-specific drug perturbation profiles using available expression data from related conditions--i.e. from other drugs and cell types. We developed a computational framework that first arranges existing profiles into a three-dimensional array (or tensor) indexed by drugs, genes, and cell types, and then uses either local (nearest-neighbors) or global (tensor completion) information to predict unmeasured profiles. We evaluate prediction accuracy using a variety of metrics, and find that the two methods have complementary performance, each superior in different regions in the drug-cell space. Predictions achieve correlations of 0.68 with true values, and maintain accurate differentially expressed genes (AUC 0.81). Finally, we demonstrate that the predicted profiles add value for making downstream associations with drug targets and therapeutic classes. PMID:29218867

  7. NICU Network Neurobehavioral Profiles Predict Developmental Outcomes in a Low Risk Sample

    PubMed Central

    Sucharew, Heidi; Khoury, Jane C.; Xu, Yingying; Succop, Paul; Yolton, Kimberly

    2012-01-01

    Summary Latent profile analysis (LPA) has been used previously to classify neurobehavioral responses of infants prenatally exposed to cocaine and other drugs of abuse. The objective of this study was to define NICU Network Neurobehavioral Scale (NNNS) profile response patterns in a cohort of infants with no known cocaine exposure or other risks for neurobehavior deficits, and determine whether these profiles predict neurobehavioral outcomes in these low-risk infants. NNNS exams were performed on 355 low-risk infants at approximately 5 weeks after birth. LPA was used to define discrete profiles based on the standard NNNS summary scales. Associations between the infant profiles and neurobehavioral outcomes at one to three years of age were examined. Twelve of the 13 summary scales were used and three discrete NNNS profiles identified: social/easy going infants (44%), hypotonic infants (24%), and high arousal/difficult infants (32%). Statistically significant associations between NNNS profiles and later neurobehavioral outcomes were found for psychomotor development and externalizing behaviors. Hypotonic infants had both lower psychomotor development and lower externalizing scores compared to the other two profiles. In conclusion, three distinct profiles of the NNNS summary scores were identifiable using LPA among infants with no known cocaine exposure. These profile patterns were associated with early childhood neurobehavioral outcome, similar to findings reported in a study of infants with substantial cocaine exposure, demonstrating the utility of this profiling technique in both exposed and unexposed populations. PMID:22686386

  8. Effects of DTM resolution on slope steepness and soil loss prediction on hillslope profiles

    Treesearch

    Eder Paulo Moreira; William J. Elliot; Andrew T. Hudak

    2011-01-01

    Topographic attributes play a critical role in predicting erosion in models such as the Water Erosion Prediction Project (WEPP). The effects of four different high resolution hillslope profiles were studied using four different DTM resolutions: 1-m, 3-m, 5-m and 10-m. The WEPP model used a common scenario encountered in the forest environment and the selected hillslope...

  9. A Prognostic Gene Expression Profile That Predicts Circulating Tumor Cell Presence in Breast Cancer Patients

    PubMed Central

    Molloy, Timothy J.; Roepman, Paul; Naume, Bjørn; van't Veer, Laura J.

    2012-01-01

    The detection of circulating tumor cells (CTCs) in the peripheral blood and microarray gene expression profiling of the primary tumor are two promising new technologies able to provide valuable prognostic data for patients with breast cancer. Meta-analyses of several established prognostic breast cancer gene expression profiles in large patient cohorts have demonstrated that despite sharing few genes, their delineation of patients into “good prognosis” or “poor prognosis” are frequently very highly correlated, and combining prognostic profiles does not increase prognostic power. In the current study, we aimed to develop a novel profile which provided independent prognostic data by building a signature predictive of CTC status rather than outcome. Microarray gene expression data from an initial training cohort of 72 breast cancer patients for which CTC status had been determined in a previous study using a multimarker QPCR-based assay was used to develop a CTC-predictive profile. The generated profile was validated in two independent datasets of 49 and 123 patients and confirmed to be both predictive of CTC status, and independently prognostic. Importantly, the “CTC profile” also provided prognostic information independent of the well-established and powerful ‘70-gene’ prognostic breast cancer signature. This profile therefore has the potential to not only add prognostic information to currently-available microarray tests but in some circumstances even replace blood-based prognostic CTC tests at time of diagnosis for those patients already undergoing testing by multigene assays. PMID:22384245

  10. Understanding and predicting profile structure and parametric scaling of intrinsic rotation

    SciTech Connect

    Wang, W. X.; Grierson, B. A.; Ethier, S.

    2017-08-10

    This study reports on a recent advance in developing physical understanding and a first-principles-based model for predicting intrinsic rotation profiles in magnetic fusion experiments. It is shown for the first time that turbulent fluctuation-driven residual stress (a non-diffusive component of momentum flux) along with diffusive momentum flux can account for both the shape and magnitude of the observed intrinsic toroidal rotation profile. Both the turbulence intensity gradient and zonal flow E×B shear are identified as major contributors to the generation of the k ∥-asymmetry needed for the residual stress generation. The model predictions of core rotation based on global gyrokineticmore » simulations agree well with the experimental measurements of main ion toroidal rotation for a set of DIII-D ECH discharges. The validated model is further used to investigate the characteristic dependence of residual stress and intrinsic rotation profile structure on the multi-dimensional parametric space covering the turbulence type, q-profile structure, and up-down asymmetry in magnetic geometry with the goal of developing the physics understanding needed for rotation profile control and optimization. It is shown that in the flat-q profile regime, intrinsic rotations driven by ITG and TEM turbulence are in the opposite direction (i.e., intrinsic rotation reverses). The predictive model also produces reversed intrinsic rotation for plasmas with weak and normal shear q-profiles.« less

  11. Accurate and predictive antibody repertoire profiling by molecular amplification fingerprinting

    PubMed Central

    Khan, Tarik A.; Friedensohn, Simon; de Vries, Arthur R. Gorter; Straszewski, Jakub; Ruscheweyh, Hans-Joachim; Reddy, Sai T.

    2016-01-01

    High-throughput antibody repertoire sequencing (Ig-seq) provides quantitative molecular information on humoral immunity. However, Ig-seq is compromised by biases and errors introduced during library preparation and sequencing. By using synthetic antibody spike-in genes, we determined that primer bias from multiplex polymerase chain reaction (PCR) library preparation resulted in antibody frequencies with only 42 to 62% accuracy. Additionally, Ig-seq errors resulted in antibody diversity measurements being overestimated by up to 5000-fold. To rectify this, we developed molecular amplification fingerprinting (MAF), which uses unique molecular identifier (UID) tagging before and during multiplex PCR amplification, which enabled tagging of transcripts while accounting for PCR efficiency. Combined with a bioinformatic pipeline, MAF bias correction led to measurements of antibody frequencies with up to 99% accuracy. We also used MAF to correct PCR and sequencing errors, resulting in enhanced accuracy of full-length antibody diversity measurements, achieving 98 to 100% error correction. Using murine MAF-corrected data, we established a quantitative metric of recent clonal expansion—the intraclonal diversity index—which measures the number of unique transcripts associated with an antibody clone. We used this intraclonal diversity index along with antibody frequencies and somatic hypermutation to build a logistic regression model for prediction of the immunological status of clones. The model was able to predict clonal status with high confidence but only when using MAF error and bias corrected Ig-seq data. Improved accuracy by MAF provides the potential to greatly advance Ig-seq and its utility in immunology and biotechnology. PMID:26998518

  12. Accurate and predictive antibody repertoire profiling by molecular amplification fingerprinting.

    PubMed

    Khan, Tarik A; Friedensohn, Simon; Gorter de Vries, Arthur R; Straszewski, Jakub; Ruscheweyh, Hans-Joachim; Reddy, Sai T

    2016-03-01

    High-throughput antibody repertoire sequencing (Ig-seq) provides quantitative molecular information on humoral immunity. However, Ig-seq is compromised by biases and errors introduced during library preparation and sequencing. By using synthetic antibody spike-in genes, we determined that primer bias from multiplex polymerase chain reaction (PCR) library preparation resulted in antibody frequencies with only 42 to 62% accuracy. Additionally, Ig-seq errors resulted in antibody diversity measurements being overestimated by up to 5000-fold. To rectify this, we developed molecular amplification fingerprinting (MAF), which uses unique molecular identifier (UID) tagging before and during multiplex PCR amplification, which enabled tagging of transcripts while accounting for PCR efficiency. Combined with a bioinformatic pipeline, MAF bias correction led to measurements of antibody frequencies with up to 99% accuracy. We also used MAF to correct PCR and sequencing errors, resulting in enhanced accuracy of full-length antibody diversity measurements, achieving 98 to 100% error correction. Using murine MAF-corrected data, we established a quantitative metric of recent clonal expansion-the intraclonal diversity index-which measures the number of unique transcripts associated with an antibody clone. We used this intraclonal diversity index along with antibody frequencies and somatic hypermutation to build a logistic regression model for prediction of the immunological status of clones. The model was able to predict clonal status with high confidence but only when using MAF error and bias corrected Ig-seq data. Improved accuracy by MAF provides the potential to greatly advance Ig-seq and its utility in immunology and biotechnology.

  13. Validity of a Manual Soft Tissue Profile Prediction Method Following Mandibular Setback Osteotomy

    PubMed Central

    Kolokitha, Olga-Elpis

    2007-01-01

    Objectives The aim of this study was to determine the validity of a manual cephalometric method used for predicting the post-operative soft tissue profiles of patients who underwent mandibular setback surgery and compare it to a computerized cephalometric prediction method (Dentofacial Planner). Lateral cephalograms of 18 adults with mandibular prognathism taken at the end of pre-surgical orthodontics and approximately one year after surgery were used. Methods To test the validity of the manual method the prediction tracings were compared to the actual post-operative tracings. The Dentofacial Planner software was used to develop the computerized post-surgical prediction tracings. Both manual and computerized prediction printouts were analyzed by using the cephalometric system PORDIOS. Statistical analysis was performed by means of t-test. Results Comparison between manual prediction tracings and the actual post-operative profile showed that the manual method results in more convex soft tissue profiles; the upper lip was found in a more prominent position, upper lip thickness was increased and, the mandible and lower lip were found in a less posterior position than that of the actual profiles. Comparison between computerized and manual prediction methods showed that in the manual method upper lip thickness was increased, the upper lip was found in a more anterior position and the lower anterior facial height was increased as compared to the computerized prediction method. Conclusions Cephalometric simulation of post-operative soft tissue profile following orthodontic-surgical management of mandibular prognathism imposes certain limitations related to the methods implied. However, both manual and computerized prediction methods remain a useful tool for patient communication. PMID:19212468

  14. Validity of a manual soft tissue profile prediction method following mandibular setback osteotomy.

    PubMed

    Kolokitha, Olga-Elpis

    2007-10-01

    The aim of this study was to determine the validity of a manual cephalometric method used for predicting the post-operative soft tissue profiles of patients who underwent mandibular setback surgery and compare it to a computerized cephalometric prediction method (Dentofacial Planner). Lateral cephalograms of 18 adults with mandibular prognathism taken at the end of pre-surgical orthodontics and approximately one year after surgery were used. To test the validity of the manual method the prediction tracings were compared to the actual post-operative tracings. The Dentofacial Planner software was used to develop the computerized post-surgical prediction tracings. Both manual and computerized prediction printouts were analyzed by using the cephalometric system PORDIOS. Statistical analysis was performed by means of t-test. Comparison between manual prediction tracings and the actual post-operative profile showed that the manual method results in more convex soft tissue profiles; the upper lip was found in a more prominent position, upper lip thickness was increased and, the mandible and lower lip were found in a less posterior position than that of the actual profiles. Comparison between computerized and manual prediction methods showed that in the manual method upper lip thickness was increased, the upper lip was found in a more anterior position and the lower anterior facial height was increased as compared to the computerized prediction method. Cephalometric simulation of post-operative soft tissue profile following orthodontic-surgical management of mandibular prognathism imposes certain limitations related to the methods implied. However, both manual and computerized prediction methods remain a useful tool for patient communication.

  15. Perceived Partner Responsiveness Predicts Diurnal Cortisol Profiles 10 Years Later.

    PubMed

    Slatcher, Richard B; Selcuk, Emre; Ong, Anthony D

    2015-07-01

    Several decades of research have demonstrated that marital relationships have a powerful influence on physical health. However, surprisingly little is known about how marriage affects health--both in terms of psychological processes and biological ones. Over a 10-year period, we investigated the associations between perceived partner responsiveness--the extent to which people feel understood, cared for, and appreciated by their romantic partners--and diurnal cortisol in a large sample of married and cohabitating couples in the United States. Partner responsiveness predicted higher cortisol values at awakening and steeper (i.e., healthier) cortisol slopes at the 10-year follow-up. These associations remained strong after we controlled for demographic factors, depressive symptoms, agreeableness, and other positive and negative relationship factors. Furthermore, declines in negative affect over the 10-year period mediated the prospective association between responsiveness and cortisol slope. These findings suggest that diurnal cortisol may be a key biological pathway through which social relationships affect long-term health. © The Author(s) 2015.

  16. Within treatment therapeutic alliance ratings profiles predict posttreatment frequency of alcohol use

    PubMed Central

    Prince, Mark A.; Connors, Gerard J.; Maisto, Stephen A.; Dearing, Ronda L.

    2016-01-01

    While past research has demonstrated a positive relationship between the therapeutic alliance (TA) and improved drinking outcomes, specific aspects of the alliance have received less attention. In this study, we examined the association between alliance characteristics during treatment and 4-month follow-up drinking reports. 65 treatment-seeking alcohol dependent clients who participated in 12 weeks of individual outpatient treatment provided weekly TA ratings during treatment and reported on pre-treatment, during treatment, and post-treatment alcohol use. Latent profile analysis was conducted to discern distinct profiles of client and therapist ratings of therapeutic alliance with similar alliance characteristics. TA profiles were based on clients’ and therapists’ mean alliance rating, minimum alliance rating, maximum alliance rating, the range of alliance ratings, and the difference in session number between maximum and minimum alliance ratings. 1- through 4- class models were fit to the data. Model fit was judged by comparative fit indices, substantive interpretability, and parsimony. Wald tests of mean equality determined whether classes differed on follow-up percentage of days abstinent (PDA) at 4 months posttreatment. 3-profile solutions provided the best fit for both client and therapist ratings of the therapeutic alliance. Client alliance rating profiles predicted drinking in the follow-up period, but therapist rating profiles did not. These results suggest that distinct profiles of the therapeutic alliance can be identified and that client alliance rating profiles are associated with frequency of alcohol use following outpatient treatment. PMID:26999350

  17. Technical player profiles related to the physical fitness of young female volleyball players predict team performance.

    PubMed

    Dávila-Romero, C; Hernández-Mocholí, M A; García-Hermoso, A

    2015-03-01

    This study is divided into three sequential stages: identification of fitness and game performance profiles (individual player performance), an assessment of the relationship between these profiles, and an assessment of the relationship between individual player profiles and team performance during play (in championship performance). The overall study sample comprised 525 (19 teams) female volleyball players aged 12-16 years and a subsample (N.=43) used to examine study aims one and two was selected from overall sample. Anthropometric, fitness and individual player performance (actual game) data were collected in the subsample. These data were analyzed through clustering methods, ANOVA and independence chi-square test. Then, we investigated whether the proportion of players with the highest individual player performance profile might predict a team's results in the championship. Cluster analysis identified three volleyball fitness profiles (high, medium, and low) and two individual player performance profiles (high and low). The results showed a relationship between both types of profile (fitness and individual player performance). Then, linear regression revealed a moderate relationship between the number of players with a high volleyball fitness profile and a team's results in the championship (R2=0.23). The current study findings may enable coaches and trainers to manage training programs more efficiently in order to obtain tailor-made training, identify volleyball-specific physical fitness training requirements and reach better results during competitions.

  18. Modeling and life prediction methodology for Titanium Matrix Composites subjected to mission profiles

    NASA Technical Reports Server (NTRS)

    Mirdamadi, M.; Johnson, W. S.

    1994-01-01

    Titanium matrix composites (TMC) are being evaluated as structural materials for elevated temperature applications in future generation hypersonic vehicles. In such applications, TMC components are subjected to complex thermomechanical loading profiles at various elevated temperatures. Therefore, thermomechanical fatigue (TMF) testing, using a simulated mission profile, is essential for evaluation and development of life prediction methodologies. The objective of the research presented in this paper was to evaluate the TMF response of the (0/90)2s SCS-6/Timetal-21S subjected to a generic hypersonic flight profile and its portions with a temperature ranging from -130 C to 816 C. It was found that the composite modulus, prior to rapid degradation, had consistent values for all the profiles tested. A micromechanics based analysis was used to predict the stress-strain response of the laminate and of the constituents in each ply during thermomechanical loading conditions by using only constituent properties as input. The fiber was modeled as elastic with transverse orthotropic and temperature dependent properties. The matrix was modeled using a thermoviscoplastic constitutive relation. In the analysis, the composite modulus degradation was assumed to result from matrix cracking and was modeled by reducing the matrix modulus. Fatigue lives of the composite subjected to the complex generic hypersonic flight profile were well correlated using the predicted stress in 0 degree fibers.

  19. Prediction of Human Pharmacokinetic Profile After Transdermal Drug Application Using Excised Human Skin.

    PubMed

    Yamamoto, Syunsuke; Karashima, Masatoshi; Arai, Yuta; Tohyama, Kimio; Amano, Nobuyuki

    2017-09-01

    Although several mathematical models have been reported for the estimation of human plasma concentration profiles of drug substances after dermal application, the successful cases that can predict human pharmacokinetic profiles are limited. Therefore, the aim of this study is to investigate the prediction of human plasma concentrations after dermal application using in vitro permeation parameters obtained from excised human skin. The in vitro skin permeability of 7 marketed drug products was evaluated. The plasma concentration-time profiles of the drug substances in humans after their dermal application were simulated using compartment models and the clinical pharmacokinetic parameters. The transdermal process was simulated using the in vitro skin permeation rate and lag time assuming a zero-order absorption. These simulated plasma concentration profiles were compared with the clinical data. The result revealed that the steady-state plasma concentration of diclofenac and the maximum concentrations of nicotine, bisoprolol, rivastigmine, and lidocaine after topical application were within 2-fold of the clinical data. Furthermore, the simulated concentration profiles of bisoprolol, nicotine, and rivastigmine reproduced the decrease in absorption due to drug depletion from the formulation. In conclusion, this simple compartment model using in vitro human skin permeation parameters as zero-order absorption predicted the human plasma concentrations accurately. Copyright © 2017 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

  20. A Gene Expression Profile of BRCAness that Predicts for Responsiveness to Platinum and PARP Inhibitors

    DTIC Science & Technology

    2013-08-01

    like ( NBL ) corresponding to tumors predicted to have a BRCAness phenotype (BL tumors) or not ( NBL tumors). In the previous years we performed a...TCGA EOC project that have been characterized as BL or NBL by our profile to identify 3 candidate miRNAs (let-7f-2*, miR-744*, miR-342-5p) that may be

  1. Model predictions of wind and turbulence profiles associated with an ensemble of aircraft accidents

    NASA Technical Reports Server (NTRS)

    Williamson, G. G.; Lewellen, W. S.; Teske, M. E.

    1977-01-01

    The feasibility of predicting conditions under which wind/turbulence environments hazardous to aviation operations exist is studied by examining a number of different accidents in detail. A model of turbulent flow in the atmospheric boundary layer is used to reconstruct wind and turbulence profiles which may have existed at low altitudes at the time of the accidents. The predictions are consistent with available flight recorder data, but neither the input boundary conditions nor the flight recorder observations are sufficiently precise for these studies to be interpreted as verification tests of the model predictions.

  2. Profiles of observed infant anger predict preschool behavior problems: Moderation by life stress

    PubMed Central

    Brooker, Rebecca J.; Buss, Kristin A.; Lemery-Chalfant, Kathryn; Aksan, Nazan; Davidson, Richard J.; Goldsmith, H. Hill

    2014-01-01

    Using both traditional composites and novel profiles of anger, we examined associations between infant anger and preschool behavior problems in a large, longitudinal data set (N = 966). We also tested the role of life stress as a moderator of the link between early anger and the development of behavior problems. Although traditional measures of anger were largely unrelated to later behavior problems, profiles of anger that dissociated typical from atypical development predicted behavior problems during preschool. Moreover, the relation between infant anger profiles and preschool behavior problems was moderated such that, when early life stress was low, infants with atypical profiles of early anger showed more preschool behavior problems than did infants with normative anger profiles. However, when early life stress was high, infants with atypical and normative profiles of infant anger did not differ in preschool behavior problems. We conclude that a discrete emotions approach including latent profile analysis is useful for elucidating biological and environmental developmental pathways to early problem behaviors. PMID:25151247

  3. Prediction of polypharmacological profiles of drugs by the integration of chemical, side effect, and therapeutic space.

    PubMed

    Cheng, Feixiong; Li, Weihua; Wu, Zengrui; Wang, Xichuan; Zhang, Chen; Li, Jie; Liu, Guixia; Tang, Yun

    2013-04-22

    Prediction of polypharmacological profiles of drugs enables us to investigate drug side effects and further find their new indications, i.e. drug repositioning, which could reduce the costs while increase the productivity of drug discovery. Here we describe a new computational framework to predict polypharmacological profiles of drugs by the integration of chemical, side effect, and therapeutic space. On the basis of our previous developed drug side effects database, named MetaADEDB, a drug side effect similarity inference (DSESI) method was developed for drug-target interaction (DTI) prediction on a known DTI network connecting 621 approved drugs and 893 target proteins. The area under the receiver operating characteristic curve was 0.882 ± 0.011 averaged from 100 simulated tests of 10-fold cross-validation for the DSESI method, which is comparative with drug structural similarity inference and drug therapeutic similarity inference methods. Seven new predicted candidate target proteins for seven approved drugs were confirmed by published experiments, with the successful hit rate more than 15.9%. Moreover, network visualization of drug-target interactions and off-target side effect associations provide new mechanism-of-action of three approved antipsychotic drugs in a case study. The results indicated that the proposed methods could be helpful for prediction of polypharmacological profiles of drugs.

  4. Modeling and prediction of extraction profile for microwave-assisted extraction based on absorbed microwave energy.

    PubMed

    Chan, Chung-Hung; Yusoff, Rozita; Ngoh, Gek-Cheng

    2013-09-01

    A modeling technique based on absorbed microwave energy was proposed to model microwave-assisted extraction (MAE) of antioxidant compounds from cocoa (Theobroma cacao L.) leaves. By adapting suitable extraction model at the basis of microwave energy absorbed during extraction, the model can be developed to predict extraction profile of MAE at various microwave irradiation power (100-600 W) and solvent loading (100-300 ml). Verification with experimental data confirmed that the prediction was accurate in capturing the extraction profile of MAE (R-square value greater than 0.87). Besides, the predicted yields from the model showed good agreement with the experimental results with less than 10% deviation observed. Furthermore, suitable extraction times to ensure high extraction yield at various MAE conditions can be estimated based on absorbed microwave energy. The estimation is feasible as more than 85% of active compounds can be extracted when compared with the conventional extraction technique. Copyright © 2013 Elsevier Ltd. All rights reserved.

  5. Predicting domain-domain interaction based on domain profiles with feature selection and support vector machines

    PubMed Central

    2010-01-01

    Background Protein-protein interaction (PPI) plays essential roles in cellular functions. The cost, time and other limitations associated with the current experimental methods have motivated the development of computational methods for predicting PPIs. As protein interactions generally occur via domains instead of the whole molecules, predicting domain-domain interaction (DDI) is an important step toward PPI prediction. Computational methods developed so far have utilized information from various sources at different levels, from primary sequences, to molecular structures, to evolutionary profiles. Results In this paper, we propose a computational method to predict DDI using support vector machines (SVMs), based on domains represented as interaction profile hidden Markov models (ipHMM) where interacting residues in domains are explicitly modeled according to the three dimensional structural information available at the Protein Data Bank (PDB). Features about the domains are extracted first as the Fisher scores derived from the ipHMM and then selected using singular value decomposition (SVD). Domain pairs are represented by concatenating their selected feature vectors, and classified by a support vector machine trained on these feature vectors. The method is tested by leave-one-out cross validation experiments with a set of interacting protein pairs adopted from the 3DID database. The prediction accuracy has shown significant improvement as compared to InterPreTS (Interaction Prediction through Tertiary Structure), an existing method for PPI prediction that also uses the sequences and complexes of known 3D structure. Conclusions We show that domain-domain interaction prediction can be significantly enhanced by exploiting information inherent in the domain profiles via feature selection based on Fisher scores, singular value decomposition and supervised learning based on support vector machines. Datasets and source code are freely available on the web at http

  6. Understanding and Predicting Profile Structure and Parametric Scaling of Intrinsic Rotation

    NASA Astrophysics Data System (ADS)

    Wang, Weixing

    2016-10-01

    It is shown for the first time that turbulence-driven residual Reynolds stress can account for both the shape and magnitude of the observed intrinsic toroidal rotation profile. Nonlinear, global gyrokinetic simulations using GTS of DIII-D ECH plasmas indicate a substantial ITG fluctuation-induced non-diffusive momentum flux generated around a mid-radius-peaked intrinsic toroidal rotation profile. The non-diffusive momentum flux is dominated by the residual stress with a negligible contribution from the momentum pinch. The residual stress profile shows a robust anti-gradient, dipole structure in a set of ECH discharges with varying ECH power. Such interesting features of non-diffusive momentum fluxes, in connection with edge momentum sources and sinks, are found to be critical to drive the non-monotonic core rotation profiles in the experiments. Both turbulence intensity gradient and zonal flow ExB shear are identified as major contributors to the generation of the k∥-asymmetry needed for the residual stress generation. By balancing the residual stress and the momentum diffusion, a self-organized, steady-state rotation profile is calculated. The predicted core rotation profiles agree well with the experimentally measured main-ion toroidal rotation. The validated model is further used to investigate the characteristic dependence of global rotation profile structure in the multi-dimensional parametric space covering turbulence type, q-profile structure and collisionality with the goal of developing physics understanding needed for rotation profile control and optimization. Interesting results obtained include intrinsic rotation reversal induced by ITG-TEM transition in flat-q profile regime and by change in q-profile from weak to normal shear.. Fluctuation-generated poloidal Reynolds stress is also shown to significantly modify the neoclassical poloidal rotation in a way consistent with experimental observations. Finally, the first-principles-based model is applied

  7. Longitudinal prediction and concurrent functioning of adolescent girls demonstrating various profiles of dating violence and victimization.

    PubMed

    Chiodo, Debbie; Crooks, Claire V; Wolfe, David A; McIsaac, Caroline; Hughes, Ray; Jaffe, Peter G

    2012-08-01

    Adolescent girls are involved in physical dating violence as both perpetrators and victims, and there are negative consequences associated with each of these behaviors. This article used a prospective design with 519 girls dating in grade 9 to predict profiles of dating violence in grade 11 based on relationships with families of origin (child maltreatment experiences, harsh parenting), and peers (harassment, delinquency, relational aggression). In addition, dating violence profiles were compared on numerous indices of adjustment (school connectedness, grades, self-efficacy and community connectedness) and maladjustment (suicide attempts, distress, delinquency, sexual behavior) for descriptive purposes. The most common profile was no dating violence (n = 367) followed by mutual violence (n = 81). Smaller numbers of girls reported victimization or perpetration only (ns = 39 and 32, respectively). Predicting grade 11 dating violence profile membership from grade 9 relationships was limited, although delinquency, parental rejection, and sexual harassment perpetration predicted membership to the mutually violent group, and delinquency predicted the perpetrator-only group. Compared to the non-violent group, the mutually violent girls in grade 11 had lower grades, poorer self-efficacy, and lower school connectedness and community involvement. Furthermore, they had higher rates of peer aggression and delinquency, were less likely to use condoms and were much more likely to have considered suicide. There were fewer differences among the profiles for girls involved with dating violence. In addition, the victims-only group reported higher rates of sexual intercourse, comparable to the mutually violent group and those involved in nonviolent relationships. Implications for prevention and intervention are highlighted.

  8. A Serum Protein Profile Predictive of the Resistance to Neoadjuvant Chemotherapy in Advanced Breast Cancers*

    PubMed Central

    Hyung, Seok-Won; Lee, Min Young; Yu, Jong-Han; Shin, Byunghee; Jung, Hee-Jung; Park, Jong-Moon; Han, Wonshik; Lee, Kyung-Min; Moon, Hyeong-Gon; Zhang, Hui; Aebersold, Ruedi; Hwang, Daehee; Lee, Sang-Won; Yu, Myeong-Hee; Noh, Dong-Young

    2011-01-01

    Prediction of the responses to neoadjuvant chemotherapy (NACT) can improve the treatment of patients with advanced breast cancer. Genes and proteins predictive of chemoresistance have been extensively studied in breast cancer tissues. However, noninvasive serum biomarkers capable of such prediction have been rarely exploited. Here, we performed profiling of N-glycosylated proteins in serum from fifteen advanced breast cancer patients (ten patients sensitive to and five patients resistant to NACT) to discover serum biomarkers of chemoresistance using a label-free liquid chromatography-tandem MS method. By performing a series of statistical analyses of the proteomic data, we selected thirteen biomarker candidates and tested their differential serum levels by Western blotting in 13 independent samples (eight patients sensitive to and five patients resistant to NACT). Among the candidates, we then selected the final set of six potential serum biomarkers (AHSG, APOB, C3, C9, CP, and ORM1) whose differential expression was confirmed in the independent samples. Finally, we demonstrated that a multivariate classification model using the six proteins could predict responses to NACT and further predict relapse-free survival of patients. In summary, global N-glycoproteome profile in serum revealed a protein pattern predictive of the responses to NACT, which can be further validated in large clinical studies. PMID:21799047

  9. Predicting survival times for neuroblastoma patients using RNA-seq expression profiles.

    PubMed

    Grimes, Tyler; Walker, Alejandro R; Datta, Susmita; Datta, Somnath

    2018-05-30

    Neuroblastoma is the most common tumor of early childhood and is notorious for its high variability in clinical presentation. Accurate prognosis has remained a challenge for many patients. In this study, expression profiles from RNA-sequencing are used to predict survival times directly. Several models are investigated using various annotation levels of expression profiles (genes, transcripts, and introns), and an ensemble predictor is proposed as a heuristic for combining these different profiles. The use of RNA-seq data is shown to improve accuracy in comparison to using clinical data alone for predicting overall survival times. Furthermore, clinically high-risk patients can be subclassified based on their predicted overall survival times. In this effort, the best performing model was the elastic net using both transcripts and introns together. This model separated patients into two groups with 2-year overall survival rates of 0.40±0.11 (n=22) versus 0.80±0.05 (n=68). The ensemble approach gave similar results, with groups 0.42±0.10 (n=25) versus 0.82±0.05 (n=65). This suggests that the ensemble is able to effectively combine the individual RNA-seq datasets. Using predicted survival times based on RNA-seq data can provide improved prognosis by subclassifying clinically high-risk neuroblastoma patients. This article was reviewed by Subharup Guha and Isabel Nepomuceno.

  10. Profile analysis and prediction of tissue-specific CpG island methylation classes

    PubMed Central

    2009-01-01

    Background The computational prediction of DNA methylation has become an important topic in the recent years due to its role in the epigenetic control of normal and cancer-related processes. While previous prediction approaches focused merely on differences between methylated and unmethylated DNA sequences, recent experimental results have shown the presence of much more complex patterns of methylation across tissues and time in the human genome. These patterns are only partially described by a binary model of DNA methylation. In this work we propose a novel approach, based on profile analysis of tissue-specific methylation that uncovers significant differences in the sequences of CpG islands (CGIs) that predispose them to a tissue- specific methylation pattern. Results We defined CGI methylation profiles that separate not only between constitutively methylated and unmethylated CGIs, but also identify CGIs showing a differential degree of methylation across tissues and cell-types or a lack of methylation exclusively in sperm. These profiles are clearly distinguished by a number of CGI attributes including their evolutionary conservation, their significance, as well as the evolutionary evidence of prior methylation. Additionally, we assess profile functionality with respect to the different compartments of protein coding genes and their possible use in the prediction of DNA methylation. Conclusion Our approach provides new insights into the biological features that determine if a CGI has a functional role in the epigenetic control of gene expression and the features associated with CGI methylation susceptibility. Moreover, we show that the ability to predict CGI methylation is based primarily on the quality of the biological information used and the relationships uncovered between different sources of knowledge. The strategy presented here is able to predict, besides the constitutively methylated and unmethylated classes, two more tissue specific methylation classes

  11. PrePhyloPro: phylogenetic profile-based prediction of whole proteome linkages

    PubMed Central

    Niu, Yulong; Liu, Chengcheng; Moghimyfiroozabad, Shayan; Yang, Yi

    2017-01-01

    Direct and indirect functional links between proteins as well as their interactions as part of larger protein complexes or common signaling pathways may be predicted by analyzing the correlation of their evolutionary patterns. Based on phylogenetic profiling, here we present a highly scalable and time-efficient computational framework for predicting linkages within the whole human proteome. We have validated this method through analysis of 3,697 human pathways and molecular complexes and a comparison of our results with the prediction outcomes of previously published co-occurrency model-based and normalization methods. Here we also introduce PrePhyloPro, a web-based software that uses our method for accurately predicting proteome-wide linkages. We present data on interactions of human mitochondrial proteins, verifying the performance of this software. PrePhyloPro is freely available at http://prephylopro.org/phyloprofile/. PMID:28875072

  12. HMMBinder: DNA-Binding Protein Prediction Using HMM Profile Based Features.

    PubMed

    Zaman, Rianon; Chowdhury, Shahana Yasmin; Rashid, Mahmood A; Sharma, Alok; Dehzangi, Abdollah; Shatabda, Swakkhar

    2017-01-01

    DNA-binding proteins often play important role in various processes within the cell. Over the last decade, a wide range of classification algorithms and feature extraction techniques have been used to solve this problem. In this paper, we propose a novel DNA-binding protein prediction method called HMMBinder. HMMBinder uses monogram and bigram features extracted from the HMM profiles of the protein sequences. To the best of our knowledge, this is the first application of HMM profile based features for the DNA-binding protein prediction problem. We applied Support Vector Machines (SVM) as a classification technique in HMMBinder. Our method was tested on standard benchmark datasets. We experimentally show that our method outperforms the state-of-the-art methods found in the literature.

  13. Prediction of Response to Preoperative Chemoradiotherapy in Rectal Cancer by Multiplex Kinase Activity Profiling

    SciTech Connect

    Folkvord, Sigurd; Flatmark, Kjersti; Department of Cancer and Surgery, Norwegian Radium Hospital, Oslo University Hospital

    2010-10-01

    Purpose: Tumor response of rectal cancer to preoperative chemoradiotherapy (CRT) varies considerably. In experimental tumor models and clinical radiotherapy, activity of particular subsets of kinase signaling pathways seems to predict radiation response. This study aimed to determine whether tumor kinase activity profiles might predict tumor response to preoperative CRT in locally advanced rectal cancer (LARC). Methods and Materials: Sixty-seven LARC patients were treated with a CRT regimen consisting of radiotherapy, fluorouracil, and, where possible, oxaliplatin. Pretreatment tumor biopsy specimens were analyzed using microarrays with kinase substrates, and the resulting substrate phosphorylation patterns were correlated with tumor response to preoperative treatmentmore » as assessed by histomorphologic tumor regression grade (TRG). A predictive model for TRG scores from phosphosubstrate signatures was obtained by partial-least-squares discriminant analysis. Prediction performance was evaluated by leave-one-out cross-validation and use of an independent test set. Results: In the patient population, 73% and 15% were scored as good responders (TRG 1-2) or intermediate responders (TRG 3), whereas 12% were assessed as poor responders (TRG 4-5). In a subset of 7 poor responders and 12 good responders, treatment outcome was correctly predicted for 95%. Application of the prediction model on the remaining patient samples resulted in correct prediction for 85%. Phosphosubstrate signatures generated by poor-responding tumors indicated high kinase activity, which was inhibited by the kinase inhibitor sunitinib, and several discriminating phosphosubstrates represented proteins derived from signaling pathways implicated in radioresistance. Conclusions: Multiplex kinase activity profiling may identify functional biomarkers predictive of tumor response to preoperative CRT in LARC.« less

  14. Ozone Mapping and Profiler Suite: using mission performance data to refine predictive contamination modeling

    NASA Astrophysics Data System (ADS)

    Devaud, Genevieve; Jaross, Glen

    2014-09-01

    On October 28, 2011, the Suomi National Polar-orbiting Partnership (Suomi NPP) satellite launched at Vandenberg Air Force base aboard a United Launch Alliance Delta II rocket. Included among the five instruments was the Ozone Mapping and Profiler Suite (OMPS), an advanced suite of three hyperspectral instruments built by Ball Aerospace and Technologies Corporation (BATC) for the NASA Goddard Space Flight Center. Molecular transport modeling is used to predict optical throughput changes due to contaminant accumulation to ensure performance margin to End Of Life. The OMPS Nadir Profiler, operating at the lowest wavelengths of 250 - 310 nm, is most sensitive to contaminant accumulation. Geometry, thermal profile and material properties must be accurately modeled in order to have confidence in the results, yet it is well known that the complex chemistry and process dependent variability of aerospace materials presents a substantial challenge to the modeler. Assumptions about the absorption coefficients, desorption and diffusion kinetics of outgassing species from polymeric materials dramatically affect the model predictions, yet it is rare indeed that on-mission data is analyzed at a later date as a means to compare with modeling results. Optical throughput measurements for the Ozone and Mapping Profiler Suite on the Suomi NPP Satellite indicate that optical throughput degradation between day 145 and day 858 is less than 0.5%. We will show how assumptions about outgassing rates and desorption energies, in particular, dramatically affect the modeled optical throughput and what assumptions represent the on-orbit data.

  15. Value of genetic profiling for the prediction of coronary heart disease.

    PubMed

    van der Net, Jeroen B; Janssens, A Cecile J W; Sijbrands, Eric J G; Steyerberg, Ewout W

    2009-07-01

    Advances in high-throughput genomics facilitate the identification of novel genetic susceptibility variants for coronary heart disease (CHD). This may improve CHD risk prediction. The aim of the present simulation study was to investigate to what degree CHD risk can be predicted by testing multiple genetic variants (genetic profiling). We simulated genetic profiles for a population of 100,000 individuals with a 10-year CHD incidence of 10%. For each combination of model parameters (number of variants, genotype frequency and odds ratio [OR]), we calculated the area under the receiver operating characteristic curve (AUC) to indicate the discrimination between individuals who will and will not develop CHD. The AUC of genetic profiles could rise to 0.90 when 100 hypothetical variants with ORs of 1.5 and genotype frequencies of 50% were simulated. The AUC of a genetic profile consisting of 10 established variants, with ORs ranging from 1.13 to 1.42, was 0.59. When 2, 5, and 10 times as many identical variants would be identified, the AUCs were 0.63, 0.69, and 0.76. To obtain AUCs similar to those of conventional CHD risk predictors, a considerable number of additional common genetic variants need to be identified with preferably strong effects.

  16. Combining guilt-by-association and guilt-by-profiling to predict Saccharomyces cerevisiae gene function

    PubMed Central

    Tian, Weidong; Zhang, Lan V; Taşan, Murat; Gibbons, Francis D; King, Oliver D; Park, Julie; Wunderlich, Zeba; Cherry, J Michael; Roth, Frederick P

    2008-01-01

    Background: Learning the function of genes is a major goal of computational genomics. Methods for inferring gene function have typically fallen into two categories: 'guilt-by-profiling', which exploits correlation between function and other gene characteristics; and 'guilt-by-association', which transfers function from one gene to another via biological relationships. Results: We have developed a strategy ('Funckenstein') that performs guilt-by-profiling and guilt-by-association and combines the results. Using a benchmark set of functional categories and input data for protein-coding genes in Saccharomyces cerevisiae, Funckenstein was compared with a previous combined strategy. Subsequently, we applied Funckenstein to 2,455 Gene Ontology terms. In the process, we developed 2,455 guilt-by-profiling classifiers based on 8,848 gene characteristics and 12 functional linkage graphs based on 23 biological relationships. Conclusion: Funckenstein outperforms a previous combined strategy using a common benchmark dataset. The combination of 'guilt-by-profiling' and 'guilt-by-association' gave significant improvement over the component classifiers, showing the greatest synergy for the most specific functions. Performance was evaluated by cross-validation and by literature examination of the top-scoring novel predictions. These quantitative predictions should help prioritize experimental study of yeast gene functions. PMID:18613951

  17. Development of New Military Applicant Profile (MAP) Autobiographical Questionnaires for Use in Predicting Early Army Attrition

    DTIC Science & Technology

    1985-01-01

    y’. - " Research Note 85-11 in .. Development of New Military Applicant Profile (MAP) Autobiographical Questionnaires for Use in Predicting Early...Manpower and Personnel Research Laboratory Joyce L. Shields, Director Si- V T c ,-wt h>b- ’fl ~P Toved U. S. Army , Research Institute for the...Behavioral and Social Sciences January 1985 v5 1 (-1 ,,o -4. U. S. ARMY RESEARCH INSTITUTE FOR THE BEHAVIORAL AND SOCIAL SCIENCES A Field Operating Agency

  18. A Gene Expression Profile of BRCAness That Predicts for Responsiveness to Platinum and PARP Inhibitors

    DTIC Science & Technology

    2017-02-01

    To) 15 July 2010 – 2 Nov.2016 4 . TITLE AND SUBTITLE A Gene Expression Profile of BRCAness That Predicts for Responsiveness to Platinum and PARP...resistance in vitro, and to investigate the mechanism for this effect. The major goal for Aim 4 was to determine the reproducibility of the BRCAness...we used the epithelial ovarian cancer (EOC) dataset from The Cancer Genome Atlas (TCGA) ( 4 ). The TCGA dataset is a unique tool for these studies as

  19. Biochemistry of proinflammatory macrophage activation.

    PubMed

    Nonnenmacher, Yannic; Hiller, Karsten

    2018-06-01

    In the last decade, metabolism has been recognized as a major determinant of immunological processes. During an inflammatory response, macrophages undergo striking changes in their metabolism. This metabolic reprogramming is governed by a complex interplay between metabolic enzymes and metabolites of different pathways and represents the basis for proper macrophage function. It is now evident that these changes go far beyond the well-known Warburg effect and the perturbation of metabolic targets is being investigated as a means to treat infections and auto-immune diseases. In the present review, we will aim to provide an overview of the metabolic responses during proinflammatory macrophage activation and show how these changes modulate the immune response.

  20. Body composition indices and predicted cardiovascular disease risk profile among urban dwellers in Malaysia.

    PubMed

    Su, Tin Tin; Amiri, Mohammadreza; Mohd Hairi, Farizah; Thangiah, Nithiah; Dahlui, Maznah; Majid, Hazreen Abdul

    2015-01-01

    This study aims to compare various body composition indices and their association with a predicted cardiovascular disease (CVD) risk profile in an urban population in Kuala Lumpur, Malaysia. A cross-sectional survey was conducted in metropolitan Kuala Lumpur, Malaysia, in 2012. Households were selected using a simple random-sampling method, and adult members were invited for medical screening. The Framingham Risk Scoring algorithm was used to predict CVD risk, which was then analyzed in association with body composition measurements, including waist circumference, waist-hip ratio, waist-height ratio, body fat percentage, and body mass index. Altogether, 882 individuals were included in our analyses. Indices that included waist-related measurements had the strongest association with CVD risk in both genders. After adjusting for demographic and socioeconomic variables, waist-related measurements retained the strongest correlations with predicted CVD risk in males. However, body mass index, waist-height ratio, and waist circumference had the strongest correlation with CVD risk in females. The waist-related indicators of abdominal obesity are important components of CVD risk profiles. As waist-related parameters can quickly and easily be measured, they should be routinely obtained in primary care settings and population health screens in order to assess future CVD risk profiles and design appropriate interventions.

  1. Body Composition Indices and Predicted Cardiovascular Disease Risk Profile among Urban Dwellers in Malaysia

    PubMed Central

    Su, Tin Tin; Amiri, Mohammadreza; Mohd Hairi, Farizah; Thangiah, Nithiah; Dahlui, Maznah; Majid, Hazreen Abdul

    2015-01-01

    Objectives. This study aims to compare various body composition indices and their association with a predicted cardiovascular disease (CVD) risk profile in an urban population in Kuala Lumpur, Malaysia. Methods. A cross-sectional survey was conducted in metropolitan Kuala Lumpur, Malaysia, in 2012. Households were selected using a simple random-sampling method, and adult members were invited for medical screening. The Framingham Risk Scoring algorithm was used to predict CVD risk, which was then analyzed in association with body composition measurements, including waist circumference, waist-hip ratio, waist-height ratio, body fat percentage, and body mass index. Results. Altogether, 882 individuals were included in our analyses. Indices that included waist-related measurements had the strongest association with CVD risk in both genders. After adjusting for demographic and socioeconomic variables, waist-related measurements retained the strongest correlations with predicted CVD risk in males. However, body mass index, waist-height ratio, and waist circumference had the strongest correlation with CVD risk in females. Conclusions. The waist-related indicators of abdominal obesity are important components of CVD risk profiles. As waist-related parameters can quickly and easily be measured, they should be routinely obtained in primary care settings and population health screens in order to assess future CVD risk profiles and design appropriate interventions. PMID:25710002

  2. Latent profiles of nonresidential father engagement six years after divorce predict long-term offspring outcomes.

    PubMed

    Modecki, Kathryn Lynn; Hagan, Melissa J; Sandler, Irwin; Wolchik, Sharlene A

    2015-01-01

    This study examined profiles of nonresidential father engagement (i.e., support to the adolescent, contact frequency, remarriage, relocation, and interparental conflict) with their adolescent children (N = 156) 6 to 8 years following divorce and the prospective relation between these profiles and the psychosocial functioning of their offspring, 9 years later. Parental divorce occurred during late childhood to early adolescence; indicators of nonresidential father engagement were assessed during adolescence, and mental health problems and academic achievement of offspring were assessed 9 years later in young adulthood. Three profiles of father engagement were identified in our sample of mainly White, non-Hispanic divorced fathers: Moderate Involvement/Low Conflict, Low Involvement/Moderate Conflict, and High Involvement/High Conflict. Profiles differentially predicted offspring outcomes 9 years later when they were young adults, controlling for quality of the mother-adolescent relationship, mother's remarriage, mother's income, and gender, age, and offspring mental health problems in adolescence. Offspring of fathers characterized as Moderate Involvement/Low Conflict had the highest academic achievement and the lowest number of externalizing problems 9 years later compared to offspring whose fathers had profiles indicating either the highest or lowest levels of involvement but higher levels of conflict. Results indicate that greater paternal psychosocial support and more frequent father-adolescent contact do not outweigh the negative impact of interparental conflict on youth outcomes in the long term. Implications of findings for policy and intervention are discussed.

  3. Theoretical and experimental study of a new method for prediction of profile drag of airfoil sections

    NASA Technical Reports Server (NTRS)

    Goradia, S. H.; Lilley, D. E.

    1975-01-01

    Theoretical and experimental studies are described which were conducted for the purpose of developing a new generalized method for the prediction of profile drag of single component airfoil sections with sharp trailing edges. This method aims at solution for the flow in the wake from the airfoil trailing edge to the large distance in the downstream direction; the profile drag of the given airfoil section can then easily be obtained from the momentum balance once the shape of velocity profile at a large distance from the airfoil trailing edge has been computed. Computer program subroutines have been developed for the computation of the profile drag and flow in the airfoil wake on CDC6600 computer. The required inputs to the computer program consist of free stream conditions and the characteristics of the boundary layers at the airfoil trailing edge or at the point of incipient separation in the neighborhood of airfoil trailing edge. The method described is quite generalized and hence can be extended to the solution of the profile drag for multi-component airfoil sections.

  4. [Factors predicting sensory profile of 4 to 18 month old infants].

    PubMed

    Pedrosa, Carina; Caçola, Priscila; Carvalhal, Maria Isabel Martins Mourão

    2015-01-01

    To identify environment factors predicting sensory profile of infants between 4 and 18 months old. This cross-sectional study evaluated 97 infants (40 females e 57 males), with a mean age of 1.05±0.32 years with the Test of Sensory Functions in Infants (TSFI) and also asked 97 parents and 11 kindergarten teachers of seven daycare centers to answer the Affordances in the Home Environment for Motor Development- Infant Scale (AHEMD-IS). The AHEMD-IS is a questionnaire that characterizes the opportunities in the home environment for infants between 3 and 18 months of age. We tested the association between affordances and the sensory profile of infants. Significant variables were entered into a regression model to determine predictors of sensory profile. The majority of infants (66%) had a normal sensory profile and 34% were at risk or deficit. Affordances in the home were classified as adequate and they were good in the studied daycare centers. The results of the regression revealed that only daily hours in daycare center and daycare outside space influenced the sensory profile of infants, in particular the Ocular-Motor Control component. The sensory profile of infants was between normal and at risk. While the family home offered adequate affordances for motor development, the daycare centers of the infants involved demonstrated a good quantity and quality of affordances. Overall, we conclude that daily hours in the daycare center and daycare outside space were predictors of the sensory profile, particular on Ocular-Motor Control component. Copyright © 2015 Associação de Pediatria de São Paulo. Publicado por Elsevier Editora Ltda. All rights reserved.

  5. Circulating cytokine/inhibitor profiles reshape the understanding of the SIRS/CARS continuum in sepsis and predict mortality.

    PubMed

    Osuchowski, Marcin F; Welch, Kathy; Siddiqui, Javed; Remick, Daniel G

    2006-08-01

    Mortality in sepsis remains unacceptably high and attempts to modulate the inflammatory response failed to improve survival. Previous reports postulated that the sepsis-triggered immunological cascade is multimodal: initial systemic inflammatory response syndrome (SIRS; excessive pro-, but no/low anti-inflammatory plasma mediators), intermediate homeostasis with a mixed anti-inflammatory response syndrome (MARS; both pro- and anti-inflammatory mediators) and final compensatory anti-inflammatory response syndrome (CARS; excessive anti-, but no/low proinflammatory mediators). To verify this, we examined the evolution of the inflammatory response during the early phase of murine sepsis by repetitive blood sampling of septic animals. Increased plasma concentrations of proinflammatory (IL-6, TNF, IL-1beta, KC, MIP-2, MCP-1, and eotaxin) and anti-inflammatory (TNF soluble receptors, IL-10, IL-1 receptor antagonist) cytokines were observed in early deaths (days 1-5). These elevations occurred simultaneously for both the pro- and anti-inflammatory mediators. Plasma levels of IL-6 (26 ng/ml), TNF-alpha (12 ng/ml), KC (33 ng/ml), MIP-2 (14 ng/ml), IL-1 receptor antagonist (65 ng/ml), TNF soluble receptor I (3 ng/ml), and TNF soluble receptor II (14 ng/ml) accurately predicted mortality within 24 h. In contrast, these parameters were not elevated in either the late-deaths (day 6-28) or survivors. Surprisingly, either pro- or anti-inflammatory cytokines were also reliable in predicting mortality up to 48 h before outcome. These data demonstrate that the initial inflammatory response directly correlates to early but not late sepsis mortality. This multifaceted response questions the use of a simple proinflammatory cytokine measurement for classifying the inflammatory status during sepsis.

  6. Biomarkers are used to predict quantitative metabolite concentration profiles in human red blood cells

    DOE PAGES

    Yurkovich, James T.; Yang, Laurence; Palsson, Bernhard O.; ...

    2017-03-06

    Deep-coverage metabolomic profiling has revealed a well-defined development of metabolic decay in human red blood cells (RBCs) under cold storage conditions. A set of extracellular biomarkers has been recently identified that reliably defines the qualitative state of the metabolic network throughout this metabolic decay process. Here, we extend the utility of these biomarkers by using them to quantitatively predict the concentrations of other metabolites in the red blood cell. We are able to accurately predict the concentration profile of 84 of the 91 (92%) measured metabolites ( p < 0.05) in RBC metabolism using only measurements of these five biomarkers.more » The median of prediction errors (symmetric mean absolute percent error) across all metabolites was 13%. Furthermore, the ability to predict numerous metabolite concentrations from a simple set of biomarkers offers the potential for the development of a powerful workflow that could be used to evaluate the metabolic state of a biological system using a minimal set of measurements.« less

  7. Biomarkers are used to predict quantitative metabolite concentration profiles in human red blood cells

    SciTech Connect

    Yurkovich, James T.; Yang, Laurence; Palsson, Bernhard O.

    Deep-coverage metabolomic profiling has revealed a well-defined development of metabolic decay in human red blood cells (RBCs) under cold storage conditions. A set of extracellular biomarkers has been recently identified that reliably defines the qualitative state of the metabolic network throughout this metabolic decay process. Here, we extend the utility of these biomarkers by using them to quantitatively predict the concentrations of other metabolites in the red blood cell. We are able to accurately predict the concentration profile of 84 of the 91 (92%) measured metabolites ( p < 0.05) in RBC metabolism using only measurements of these five biomarkers.more » The median of prediction errors (symmetric mean absolute percent error) across all metabolites was 13%. Furthermore, the ability to predict numerous metabolite concentrations from a simple set of biomarkers offers the potential for the development of a powerful workflow that could be used to evaluate the metabolic state of a biological system using a minimal set of measurements.« less

  8. Classification of Phylogenetic Profiles for Protein Function Prediction: An SVM Approach

    NASA Astrophysics Data System (ADS)

    Kotaru, Appala Raju; Joshi, Ramesh C.

    Predicting the function of an uncharacterized protein is a major challenge in post-genomic era due to problems complexity and scale. Having knowledge of protein function is a crucial link in the development of new drugs, better crops, and even the development of biochemicals such as biofuels. Recently numerous high-throughput experimental procedures have been invented to investigate the mechanisms leading to the accomplishment of a protein’s function and Phylogenetic profile is one of them. Phylogenetic profile is a way of representing a protein which encodes evolutionary history of proteins. In this paper we proposed a method for classification of phylogenetic profiles using supervised machine learning method, support vector machine classification along with radial basis function as kernel for identifying functionally linked proteins. We experimentally evaluated the performance of the classifier with the linear kernel, polynomial kernel and compared the results with the existing tree kernel. In our study we have used proteins of the budding yeast saccharomyces cerevisiae genome. We generated the phylogenetic profiles of 2465 yeast genes and for our study we used the functional annotations that are available in the MIPS database. Our experiments show that the performance of the radial basis kernel is similar to polynomial kernel is some functional classes together are better than linear, tree kernel and over all radial basis kernel outperformed the polynomial kernel, linear kernel and tree kernel. In analyzing these results we show that it will be feasible to make use of SVM classifier with radial basis function as kernel to predict the gene functionality using phylogenetic profiles.

  9. Mindfulness-Based Stress Reduction training reduces loneliness and pro-inflammatory gene expression in older adults: a small randomized controlled trial.

    PubMed

    Creswell, J David; Irwin, Michael R; Burklund, Lisa J; Lieberman, Matthew D; Arevalo, Jesusa M G; Ma, Jeffrey; Breen, Elizabeth Crabb; Cole, Steven W

    2012-10-01

    Lonely older adults have increased expression of pro-inflammatory genes as well as increased risk for morbidity and mortality. Previous behavioral treatments have attempted to reduce loneliness and its concomitant health risks, but have had limited success. The present study tested whether the 8-week Mindfulness-Based Stress Reduction (MBSR) program (compared to a Wait-List control group) reduces loneliness and downregulates loneliness-related pro-inflammatory gene expression in older adults (N = 40). Consistent with study predictions, mixed effect linear models indicated that the MBSR program reduced loneliness, compared to small increases in loneliness in the control group (treatment condition × time interaction: F(1,35) = 7.86, p = .008). Moreover, at baseline, there was an association between reported loneliness and upregulated pro-inflammatory NF-κB-related gene expression in circulating leukocytes, and MBSR downregulated this NF-κB-associated gene expression profile at post-treatment. Finally, there was a trend for MBSR to reduce C Reactive Protein (treatment condition × time interaction: (F(1,33) = 3.39, p = .075). This work provides an initial indication that MBSR may be a novel treatment approach for reducing loneliness and related pro-inflammatory gene expression in older adults. Copyright © 2012 Elsevier Inc. All rights reserved.

  10. Mindfulness-Based Stress Reduction Training Reduces Loneliness and Pro-Inflammatory Gene Expression in Older Adults: A Small Randomized Controlled Trial

    PubMed Central

    Creswell, J. David; Irwin, Michael R.; Burklund, Lisa J.; Lieberman, Matthew D.; Arevalo, Jesusa M. G.; Ma, Jeffrey; Breen, Elizabeth Crabb; Cole, Steven W.

    2013-01-01

    Lonely older adults have increased expression of pro-inflammatory genes as well as increased risk for morbidity and mortality. Previous behavioral treatments have attempted to reduce loneliness and its concomitant health risks, but have had limited success. The present study tested whether the 8-week Mindfulness-Based Stress Reduction (MBSR) program (compared to a Wait-List control group) reduces loneliness and downregulates loneliness-related pro-inflammatory gene expression in older adults (N=40). Consistent with study predictions, mixed effect linear models indicated that the MBSR program reduced loneliness, compared to small increases in loneliness in the control group (treatment condition × time interaction: F(1,35)=7.86, p=.008). Moreover, at baseline, there was an association between reported loneliness and upregulated pro-inflammatory NF-κB-related gene expression in circulating leukocytes, and MBSR downregulated this NF-κB-associated gene expression profile at post-treatment. Finally, there was a trend for MBSR to reduce C Reactive Protein (treatment condition × time interaction: (F(1,33)=3.39, p=.075). This work provides an initial indication that MBSR may be a novel treatment approach for reducing loneliness and related pro-inflammatory gene expression in older adults. PMID:22820409

  11. Insights into an original pocket-ligand pair classification: a promising tool for ligand profile prediction.

    PubMed

    Pérot, Stéphanie; Regad, Leslie; Reynès, Christelle; Spérandio, Olivier; Miteva, Maria A; Villoutreix, Bruno O; Camproux, Anne-Claude

    2013-01-01

    Pockets are today at the cornerstones of modern drug discovery projects and at the crossroad of several research fields, from structural biology to mathematical modeling. Being able to predict if a small molecule could bind to one or more protein targets or if a protein could bind to some given ligands is very useful for drug discovery endeavors, anticipation of binding to off- and anti-targets. To date, several studies explore such questions from chemogenomic approach to reverse docking methods. Most of these studies have been performed either from the viewpoint of ligands or targets. However it seems valuable to use information from both ligands and target binding pockets. Hence, we present a multivariate approach relating ligand properties with protein pocket properties from the analysis of known ligand-protein interactions. We explored and optimized the pocket-ligand pair space by combining pocket and ligand descriptors using Principal Component Analysis and developed a classification engine on this paired space, revealing five main clusters of pocket-ligand pairs sharing specific and similar structural or physico-chemical properties. These pocket-ligand pair clusters highlight correspondences between pocket and ligand topological and physico-chemical properties and capture relevant information with respect to protein-ligand interactions. Based on these pocket-ligand correspondences, a protocol of prediction of clusters sharing similarity in terms of recognition characteristics is developed for a given pocket-ligand complex and gives high performances. It is then extended to cluster prediction for a given pocket in order to acquire knowledge about its expected ligand profile or to cluster prediction for a given ligand in order to acquire knowledge about its expected pocket profile. This prediction approach shows promising results and could contribute to predict some ligand properties critical for binding to a given pocket, and conversely, some key pocket

  12. Insights into an Original Pocket-Ligand Pair Classification: A Promising Tool for Ligand Profile Prediction

    PubMed Central

    Reynès, Christelle; Spérandio, Olivier; Miteva, Maria A.; Villoutreix, Bruno O.; Camproux, Anne-Claude

    2013-01-01

    Pockets are today at the cornerstones of modern drug discovery projects and at the crossroad of several research fields, from structural biology to mathematical modeling. Being able to predict if a small molecule could bind to one or more protein targets or if a protein could bind to some given ligands is very useful for drug discovery endeavors, anticipation of binding to off- and anti-targets. To date, several studies explore such questions from chemogenomic approach to reverse docking methods. Most of these studies have been performed either from the viewpoint of ligands or targets. However it seems valuable to use information from both ligands and target binding pockets. Hence, we present a multivariate approach relating ligand properties with protein pocket properties from the analysis of known ligand-protein interactions. We explored and optimized the pocket-ligand pair space by combining pocket and ligand descriptors using Principal Component Analysis and developed a classification engine on this paired space, revealing five main clusters of pocket-ligand pairs sharing specific and similar structural or physico-chemical properties. These pocket-ligand pair clusters highlight correspondences between pocket and ligand topological and physico-chemical properties and capture relevant information with respect to protein-ligand interactions. Based on these pocket-ligand correspondences, a protocol of prediction of clusters sharing similarity in terms of recognition characteristics is developed for a given pocket-ligand complex and gives high performances. It is then extended to cluster prediction for a given pocket in order to acquire knowledge about its expected ligand profile or to cluster prediction for a given ligand in order to acquire knowledge about its expected pocket profile. This prediction approach shows promising results and could contribute to predict some ligand properties critical for binding to a given pocket, and conversely, some key pocket

  13. Predictive Properties of Plasma Amino Acid Profile for Cardiovascular Disease in Patients with Type 2 Diabetes

    PubMed Central

    Kume, Shinji; Araki, Shin-ichi; Ono, Nobukazu; Shinhara, Atsuko; Muramatsu, Takahiko; Araki, Hisazumi; Isshiki, Keiji; Nakamura, Kazuki; Miyano, Hiroshi; Koya, Daisuke; Haneda, Masakazu; Ugi, Satoshi; Kawai, Hiromichi; Kashiwagi, Atsunori; Uzu, Takashi; Maegawa, Hiroshi

    2014-01-01

    Prevention of cardiovascular disease (CVD) is an important therapeutic object of diabetes care. This study assessed whether an index based on plasma free amino acid (PFAA) profiles could predict the onset of CVD in diabetic patients. The baseline concentrations of 31 PFAAs were measured with high-performance liquid chromatography-electrospray ionization-mass spectrometry in 385 Japanese patients with type 2 diabetes registered in 2001 for our prospective observational follow-up study. During 10 years of follow-up, 63 patients developed cardiovascular composite endpoints (myocardial infarction, angina pectoris, worsening of heart failure and stroke). Using the PFAA profiles and clinical information, an index (CVD-AI) consisting of six amino acids to predict the onset of any endpoints was retrospectively constructed. CVD-AI levels were significantly higher in patients who did than did not develop CVD. The area under the receiver-operator characteristic curve of CVD-AI (0.72 [95% confidence interval (CI): 0.64–0.79]) showed equal or slightly better discriminatory capacity than urinary albumin excretion rate (0.69 [95% CI: 0.62–0.77]) on predicting endpoints. A multivariate Cox proportional hazards regression analysis showed that the high level of CVD-AI was identified as an independent risk factor for CVD (adjusted hazard ratio: 2.86 [95% CI: 1.57–5.19]). This predictive effect of CVD-AI was observed even in patients with normoalbuminuria, as well as those with albuminuria. In conclusion, these results suggest that CVD-AI based on PFAA profiles is useful for identifying diabetic patients at risk for CVD regardless of the degree of albuminuria, or for improving the discriminative capability by combining it with albuminuria. PMID:24971671

  14. SVM-PB-Pred: SVM based protein block prediction method using sequence profiles and secondary structures.

    PubMed

    Suresh, V; Parthasarathy, S

    2014-01-01

    We developed a support vector machine based web server called SVM-PB-Pred, to predict the Protein Block for any given amino acid sequence. The input features of SVM-PB-Pred include i) sequence profiles (PSSM) and ii) actual secondary structures (SS) from DSSP method or predicted secondary structures from NPS@ and GOR4 methods. There were three combined input features PSSM+SS(DSSP), PSSM+SS(NPS@) and PSSM+SS(GOR4) used to test and train the SVM models. Similarly, four datasets RS90, DB433, LI1264 and SP1577 were used to develop the SVM models. These four SVM models developed were tested using three different benchmarking tests namely; (i) self consistency, (ii) seven fold cross validation test and (iii) independent case test. The maximum possible prediction accuracy of ~70% was observed in self consistency test for the SVM models of both LI1264 and SP1577 datasets, where PSSM+SS(DSSP) input features was used to test. The prediction accuracies were reduced to ~53% for PSSM+SS(NPS@) and ~43% for PSSM+SS(GOR4) in independent case test, for the SVM models of above two same datasets. Using our method, it is possible to predict the protein block letters for any query protein sequence with ~53% accuracy, when the SP1577 dataset and predicted secondary structure from NPS@ server were used. The SVM-PB-Pred server can be freely accessed through http://bioinfo.bdu.ac.in/~svmpbpred.

  15. A new metric of inclusive fitness predicts the human mortality profile.

    PubMed

    Newman, Saul J; Easteal, Simon

    2015-01-01

    Biological species have evolved characteristic patterns of age-specific mortality across their life spans. If these mortality profiles are shaped by natural selection they should reflect underlying variation in the fitness effect of mortality with age. Direct fitness models, however, do not accurately predict the mortality profiles of many species. For several species, including humans, mortality rates vary considerably before and after reproductive ages, during life-stages when no variation in direct fitness is possible. Variation in mortality rates at these ages may reflect indirect effects of natural selection acting through kin. To test this possibility we developed a new two-variable measure of inclusive fitness, which we term the extended genomic output or EGO. Using EGO, we estimate the inclusive fitness effect of mortality at different ages in a small hunter-gatherer population with a typical human mortality profile. EGO in this population predicts 90% of the variation in age-specific mortality. This result represents the first empirical measurement of inclusive fitness of a trait in any species. It shows that the pattern of human survival can largely be explained by variation in the inclusive fitness cost of mortality at different ages. More generally, our approach can be used to estimate the inclusive fitness of any trait or genotype from population data on birth dates and relatedness.

  16. Model Predictive Control of the Current Profile and the Internal Energy of DIII-D Plasmas

    NASA Astrophysics Data System (ADS)

    Lauret, M.; Wehner, W.; Schuster, E.

    2015-11-01

    For efficient and stable operation of tokamak plasmas it is important that the current density profile and the internal energy are jointly controlled by using the available heating and current-drive (H&CD) sources. The proposed approach is a version of nonlinear model predictive control in which the input set is restricted in size by the possible combinations of the H&CD on/off states. The controller uses real-time predictions over a receding-time horizon of both the current density profile (nonlinear partial differential equation) and the internal energy (nonlinear ordinary differential equation) evolutions. At every time instant the effect of every possible combination of H&CD sources on the current profile and internal energy is evaluated over the chosen time horizon. The combination that leads to the best result, which is assessed by a user-defined cost function, is then applied up until the next time instant. Simulations results based on a control-oriented transport code illustrate the effectiveness of the proposed control method. Supported by the US DOE under DE-FC02-04ER54698 & DE-SC0010661.

  17. Activated sludge pilot plant: comparison between experimental and predicted concentration profiles using three different modelling approaches.

    PubMed

    Le Moullec, Y; Potier, O; Gentric, C; Leclerc, J P

    2011-05-01

    This paper presents an experimental and numerical study of an activated sludge channel pilot plant. Concentration profiles of oxygen, COD, NO(3) and NH(4) have been measured for several operating conditions. These profiles have been compared to the simulated ones with three different modelling approaches, namely a systemic approach, CFD and compartmental modelling. For these three approaches, the kinetics model was the ASM-1 model (Henze et al., 2001). The three approaches allowed a reasonable simulation of all the concentration profiles except for ammonium for which the simulations results were far from the experimental ones. The analysis of the results showed that the role of the kinetics model is of primary importance for the prediction of activated sludge reactors performance. The fact that existing kinetics parameters in the literature have been determined by parametric optimisation using a systemic model limits the reliability of the prediction of local concentrations and of the local design of activated sludge reactors. Copyright © 2011 Elsevier Ltd. All rights reserved.

  18. Elderly fall risk prediction based on a physiological profile approach using artificial neural networks.

    PubMed

    Razmara, Jafar; Zaboli, Mohammad Hassan; Hassankhani, Hadi

    2016-11-01

    Falls play a critical role in older people's life as it is an important source of morbidity and mortality in elders. In this article, elders fall risk is predicted based on a physiological profile approach using a multilayer neural network with back-propagation learning algorithm. The personal physiological profile of 200 elders was collected through a questionnaire and used as the experimental data for learning and testing the neural network. The profile contains a series of simple factors putting elders at risk for falls such as vision abilities, muscle forces, and some other daily activities and grouped into two sets: psychological factors and public factors. The experimental data were investigated to select factors with high impact using principal component analysis. The experimental results show an accuracy of ≈90 percent and ≈87.5 percent for fall prediction among the psychological and public factors, respectively. Furthermore, combining these two datasets yield an accuracy of ≈91 percent that is better than the accuracy of single datasets. The proposed method suggests a set of valid and reliable measurements that can be employed in a range of health care systems and physical therapy to distinguish people who are at risk for falls.

  19. ORION: a web server for protein fold recognition and structure prediction using evolutionary hybrid profiles

    PubMed Central

    Ghouzam, Yassine; Postic, Guillaume; Guerin, Pierre-Edouard; de Brevern, Alexandre G.; Gelly, Jean-Christophe

    2016-01-01

    Protein structure prediction based on comparative modeling is the most efficient way to produce structural models when it can be performed. ORION is a dedicated webserver based on a new strategy that performs this task. The identification by ORION of suitable templates is performed using an original profile-profile approach that combines sequence and structure evolution information. Structure evolution information is encoded into profiles using structural features, such as solvent accessibility and local conformation —with Protein Blocks—, which give an accurate description of the local protein structure. ORION has recently been improved, increasing by 5% the quality of its results. The ORION web server accepts a single protein sequence as input and searches homologous protein structures within minutes. Various databases such as PDB, SCOP and HOMSTRAD can be mined to find an appropriate structural template. For the modeling step, a protein 3D structure can be directly obtained from the selected template by MODELLER and displayed with global and local quality model estimation measures. The sequence and the predicted structure of 4 examples from the CAMEO server and a recent CASP11 target from the ‘Hard’ category (T0818-D1) are shown as pertinent examples. Our web server is accessible at http://www.dsimb.inserm.fr/ORION/. PMID:27319297

  20. ORION: a web server for protein fold recognition and structure prediction using evolutionary hybrid profiles.

    PubMed

    Ghouzam, Yassine; Postic, Guillaume; Guerin, Pierre-Edouard; de Brevern, Alexandre G; Gelly, Jean-Christophe

    2016-06-20

    Protein structure prediction based on comparative modeling is the most efficient way to produce structural models when it can be performed. ORION is a dedicated webserver based on a new strategy that performs this task. The identification by ORION of suitable templates is performed using an original profile-profile approach that combines sequence and structure evolution information. Structure evolution information is encoded into profiles using structural features, such as solvent accessibility and local conformation -with Protein Blocks-, which give an accurate description of the local protein structure. ORION has recently been improved, increasing by 5% the quality of its results. The ORION web server accepts a single protein sequence as input and searches homologous protein structures within minutes. Various databases such as PDB, SCOP and HOMSTRAD can be mined to find an appropriate structural template. For the modeling step, a protein 3D structure can be directly obtained from the selected template by MODELLER and displayed with global and local quality model estimation measures. The sequence and the predicted structure of 4 examples from the CAMEO server and a recent CASP11 target from the 'Hard' category (T0818-D1) are shown as pertinent examples. Our web server is accessible at http://www.dsimb.inserm.fr/ORION/.

  1. Profile control simulations and experiments on TCV: a controller test environment and results using a model-based predictive controller

    NASA Astrophysics Data System (ADS)

    Maljaars, E.; Felici, F.; Blanken, T. C.; Galperti, C.; Sauter, O.; de Baar, M. R.; Carpanese, F.; Goodman, T. P.; Kim, D.; Kim, S. H.; Kong, M.; Mavkov, B.; Merle, A.; Moret, J. M.; Nouailletas, R.; Scheffer, M.; Teplukhina, A. A.; Vu, N. M. T.; The EUROfusion MST1-team; The TCV-team

    2017-12-01

    The successful performance of a model predictive profile controller is demonstrated in simulations and experiments on the TCV tokamak, employing a profile controller test environment. Stable high-performance tokamak operation in hybrid and advanced plasma scenarios requires control over the safety factor profile (q-profile) and kinetic plasma parameters such as the plasma beta. This demands to establish reliable profile control routines in presently operational tokamaks. We present a model predictive profile controller that controls the q-profile and plasma beta using power requests to two clusters of gyrotrons and the plasma current request. The performance of the controller is analyzed in both simulation and TCV L-mode discharges where successful tracking of the estimated inverse q-profile as well as plasma beta is demonstrated under uncertain plasma conditions and the presence of disturbances. The controller exploits the knowledge of the time-varying actuator limits in the actuator input calculation itself such that fast transitions between targets are achieved without overshoot. A software environment is employed to prepare and test this and three other profile controllers in parallel in simulations and experiments on TCV. This set of tools includes the rapid plasma transport simulator RAPTOR and various algorithms to reconstruct the plasma equilibrium and plasma profiles by merging the available measurements with model-based predictions. In this work the estimated q-profile is merely based on RAPTOR model predictions due to the absence of internal current density measurements in TCV. These results encourage to further exploit model predictive profile control in experiments on TCV and other (future) tokamaks.

  2. Alcoholism: A systemic proinflammatory condition

    PubMed Central

    González-Reimers, Emilio; Santolaria-Fernández, Francisco; Martín-González, María Candelaria; Fernández-Rodríguez, Camino María; Quintero-Platt, Geraldine

    2014-01-01

    Excessive ethanol consumption affects virtually any organ, both by indirect and direct mechanisms. Considerable research in the last two decades has widened the knowledge about the paramount importance of proinflammatory cytokines and oxidative damage in the pathogenesis of many of the systemic manifestations of alcoholism. These cytokines derive primarily from activated Kupffer cells exposed to Gram-negative intestinal bacteria, which reach the liver in supra-physiological amounts due to ethanol-mediated increased gut permeability. Reactive oxygen species (ROS) that enhance the inflammatory response are generated both by activation of Kupffer cells and by the direct metabolic effects of ethanol. The effects of this increased cytokine secretion and ROS generation lie far beyond liver damage. In addition to the classic consequences of endotoxemia associated with liver cirrhosis that were described several decades ago, important research in the last ten years has shown that cytokines may also induce damage in remote organs such as brain, bone, muscle, heart, lung, gonads, peripheral nerve, and pancreas. These effects are even seen in alcoholics without significant liver disease. Therefore, alcoholism can be viewed as an inflammatory condition, a concept which opens the possibility of using new therapeutic weapons to treat some of the complications of this devastating and frequent disease. In this review we examine some of the most outstanding consequences of the altered cytokine regulation that occurs in alcoholics in organs other than the liver. PMID:25356029

  3. Alcoholism: a systemic proinflammatory condition.

    PubMed

    González-Reimers, Emilio; Santolaria-Fernández, Francisco; Martín-González, María Candelaria; Fernández-Rodríguez, Camino María; Quintero-Platt, Geraldine

    2014-10-28

    Excessive ethanol consumption affects virtually any organ, both by indirect and direct mechanisms. Considerable research in the last two decades has widened the knowledge about the paramount importance of proinflammatory cytokines and oxidative damage in the pathogenesis of many of the systemic manifestations of alcoholism. These cytokines derive primarily from activated Kupffer cells exposed to Gram-negative intestinal bacteria, which reach the liver in supra-physiological amounts due to ethanol-mediated increased gut permeability. Reactive oxygen species (ROS) that enhance the inflammatory response are generated both by activation of Kupffer cells and by the direct metabolic effects of ethanol. The effects of this increased cytokine secretion and ROS generation lie far beyond liver damage. In addition to the classic consequences of endotoxemia associated with liver cirrhosis that were described several decades ago, important research in the last ten years has shown that cytokines may also induce damage in remote organs such as brain, bone, muscle, heart, lung, gonads, peripheral nerve, and pancreas. These effects are even seen in alcoholics without significant liver disease. Therefore, alcoholism can be viewed as an inflammatory condition, a concept which opens the possibility of using new therapeutic weapons to treat some of the complications of this devastating and frequent disease. In this review we examine some of the most outstanding consequences of the altered cytokine regulation that occurs in alcoholics in organs other than the liver.

  4. Integrated analysis of drug-induced gene expression profiles predicts novel hERG inhibitors.

    PubMed

    Babcock, Joseph J; Du, Fang; Xu, Kaiping; Wheelan, Sarah J; Li, Min

    2013-01-01

    Growing evidence suggests that drugs interact with diverse molecular targets mediating both therapeutic and toxic effects. Prediction of these complex interactions from chemical structures alone remains challenging, as compounds with different structures may possess similar toxicity profiles. In contrast, predictions based on systems-level measurements of drug effect may reveal pharmacologic similarities not evident from structure or known therapeutic indications. Here we utilized drug-induced transcriptional responses in the Connectivity Map (CMap) to discover such similarities among diverse antagonists of the human ether-à-go-go related (hERG) potassium channel, a common target of promiscuous inhibition by small molecules. Analysis of transcriptional profiles generated in three independent cell lines revealed clusters enriched for hERG inhibitors annotated using a database of experimental measurements (hERGcentral) and clinical indications. As a validation, we experimentally identified novel hERG inhibitors among the unannotated drugs in these enriched clusters, suggesting transcriptional responses may serve as predictive surrogates of cardiotoxicity complementing existing functional assays.

  5. Cytokine Profiles during Invasive Nontyphoidal Salmonella Disease Predict Outcome in African Children.

    PubMed

    Gilchrist, James J; Heath, Jennifer N; Msefula, Chisomo L; Gondwe, Esther N; Naranbhai, Vivek; Mandala, Wilson; MacLennan, Jenny M; Molyneux, Elizabeth M; Graham, Stephen M; Drayson, Mark T; Molyneux, Malcolm E; MacLennan, Calman A

    2016-07-01

    Nontyphoidal Salmonella is a leading cause of sepsis in African children. Cytokine responses are central to the pathophysiology of sepsis and predict sepsis outcome in other settings. In this study, we investigated cytokine responses to invasive nontyphoidal Salmonella (iNTS) disease in Malawian children. We determined serum concentrations of 48 cytokines with multiplexed immunoassays in Malawian children during acute iNTS disease (n = 111) and in convalescence (n = 77). Principal component analysis and logistic regression were used to identify cytokine signatures of acute iNTS disease. We further investigated whether these responses are altered by HIV coinfection or severe malnutrition and whether cytokine responses predict inpatient mortality. Cytokine changes in acute iNTS disease were associated with two distinct cytokine signatures. The first is characterized by increased concentrations of mediators known to be associated with macrophage function, and the second is characterized by raised pro- and anti-inflammatory cytokines typical of responses reported in sepsis secondary to diverse pathogens. These cytokine responses were largely unaltered by either severe malnutrition or HIV coinfection. Children with fatal disease had a distinctive cytokine profile, characterized by raised mediators known to be associated with neutrophil function. In conclusion, cytokine responses to acute iNTS infection in Malawian children are reflective of both the cytokine storm typical of sepsis secondary to diverse pathogens and the intramacrophage replicative niche of NTS. The cytokine profile predictive of fatal disease supports a key role of neutrophils in the pathogenesis of NTS sepsis. Copyright © 2016 Gilchrist et al.

  6. Hyperspectral scattering profiles for prediction of the microbial spoilage of beef

    NASA Astrophysics Data System (ADS)

    Peng, Yankun; Zhang, Jing; Wu, Jianhu; Hang, Hui

    2009-05-01

    Spoilage in beef is the result of decomposition and the formation of metabolites caused by the growth and enzymatic activity of microorganisms. There is still no technology for the rapid, accurate and non-destructive detection of bacterially spoiled or contaminated beef. In this study, hyperspectral imaging technique was exploited to measure biochemical changes within the fresh beef. Fresh beef rump steaks were purchased from a commercial plant, and left to spoil in refrigerator at 8°C. Every 12 hours, hyperspectral scattering profiles over the spectral region between 400 nm and 1100 nm were collected directly from the sample surface in reflection pattern in order to develop an optimal model for prediction of the beef spoilage, in parallel the total viable count (TVC) per gram of beef were obtained by classical microbiological plating methods. The spectral scattering profiles at individual wavelengths were fitted accurately by a two-parameter Lorentzian distribution function. TVC prediction models were developed, using multi-linear regression, on relating individual Lorentzian parameters and their combinations at different wavelengths to log10(TVC) value. The best predictions were obtained with r2= 0.96 and SEP = 0.23 for log10(TVC). The research demonstrated that hyperspectral imaging technique is a valid tool for real-time and non-destructive detection of bacterial spoilage in beef.

  7. Integrated Analysis of Drug-Induced Gene Expression Profiles Predicts Novel hERG Inhibitors

    PubMed Central

    Babcock, Joseph J.; Du, Fang; Xu, Kaiping; Wheelan, Sarah J.; Li, Min

    2013-01-01

    Growing evidence suggests that drugs interact with diverse molecular targets mediating both therapeutic and toxic effects. Prediction of these complex interactions from chemical structures alone remains challenging, as compounds with different structures may possess similar toxicity profiles. In contrast, predictions based on systems-level measurements of drug effect may reveal pharmacologic similarities not evident from structure or known therapeutic indications. Here we utilized drug-induced transcriptional responses in the Connectivity Map (CMap) to discover such similarities among diverse antagonists of the human ether-à-go-go related (hERG) potassium channel, a common target of promiscuous inhibition by small molecules. Analysis of transcriptional profiles generated in three independent cell lines revealed clusters enriched for hERG inhibitors annotated using a database of experimental measurements (hERGcentral) and clinical indications. As a validation, we experimentally identified novel hERG inhibitors among the unannotated drugs in these enriched clusters, suggesting transcriptional responses may serve as predictive surrogates of cardiotoxicity complementing existing functional assays. PMID:23936032

  8. Non-invasively predicting differentiation of pancreatic cancer through comparative serum metabonomic profiling.

    PubMed

    Wen, Shi; Zhan, Bohan; Feng, Jianghua; Hu, Weize; Lin, Xianchao; Bai, Jianxi; Huang, Heguang

    2017-11-02

    The differentiation of pancreatic ductal adenocarcinoma (PDAC) could be associated with prognosis and may influence the choices of clinical management. No applicable methods could reliably predict the tumor differentiation preoperatively. Thus, the aim of this study was to compare the metabonomic profiling of pancreatic ductal adenocarcinoma with different differentiations and assess the feasibility of predicting tumor differentiations through metabonomic strategy based on nuclear magnetic resonance spectroscopy. By implanting pancreatic cancer cell strains Panc-1, Bxpc-3 and SW1990 in nude mice in situ, we successfully established the orthotopic xenograft models of PDAC with different differentiations. The metabonomic profiling of serum from different PDAC was achieved and analyzed by using 1 H nuclear magnetic resonance (NMR) spectroscopy combined with the multivariate statistical analysis. Then, the differential metabolites acquired were used for enrichment analysis of metabolic pathways to get a deep insight. An obvious metabonomic difference was demonstrated between all groups and the pattern recognition models were established successfully. The higher concentrations of amino acids, glycolytic and glutaminolytic participators in SW1990 and choline-contain metabolites in Panc-1 relative to other PDAC cells were demonstrated, which may be served as potential indicators for tumor differentiation. The metabolic pathways and differential metabolites identified in current study may be associated with specific pathways such as serine-glycine-one-carbon and glutaminolytic pathways, which can regulate tumorous proliferation and epigenetic regulation. The NMR-based metabonomic strategy may be served as a non-invasive detection method for predicting tumor differentiation preoperatively.

  9. Predicting Drug Concentration‐Time Profiles in Multiple CNS Compartments Using a Comprehensive Physiologically‐Based Pharmacokinetic Model

    PubMed Central

    Yamamoto, Yumi; Välitalo, Pyry A.; Huntjens, Dymphy R.; Proost, Johannes H.; Vermeulen, An; Krauwinkel, Walter; Beukers, Margot W.; van den Berg, Dirk‐Jan; Hartman, Robin; Wong, Yin Cheong; Danhof, Meindert; van Hasselt, John G. C.

    2017-01-01

    Drug development targeting the central nervous system (CNS) is challenging due to poor predictability of drug concentrations in various CNS compartments. We developed a generic physiologically based pharmacokinetic (PBPK) model for prediction of drug concentrations in physiologically relevant CNS compartments. System‐specific and drug‐specific model parameters were derived from literature and in silico predictions. The model was validated using detailed concentration‐time profiles from 10 drugs in rat plasma, brain extracellular fluid, 2 cerebrospinal fluid sites, and total brain tissue. These drugs, all small molecules, were selected to cover a wide range of physicochemical properties. The concentration‐time profiles for these drugs were adequately predicted across the CNS compartments (symmetric mean absolute percentage error for the model prediction was <91%). In conclusion, the developed PBPK model can be used to predict temporal concentration profiles of drugs in multiple relevant CNS compartments, which we consider valuable information for efficient CNS drug development. PMID:28891201

  10. Predicting protein-binding regions in RNA using nucleotide profiles and compositions.

    PubMed

    Choi, Daesik; Park, Byungkyu; Chae, Hanju; Lee, Wook; Han, Kyungsook

    2017-03-14

    Motivated by the increased amount of data on protein-RNA interactions and the availability of complete genome sequences of several organisms, many computational methods have been proposed to predict binding sites in protein-RNA interactions. However, most computational methods are limited to finding RNA-binding sites in proteins instead of protein-binding sites in RNAs. Predicting protein-binding sites in RNA is more challenging than predicting RNA-binding sites in proteins. Recent computational methods for finding protein-binding sites in RNAs have several drawbacks for practical use. We developed a new support vector machine (SVM) model for predicting protein-binding regions in mRNA sequences. The model uses sequence profiles constructed from log-odds scores of mono- and di-nucleotides and nucleotide compositions. The model was evaluated by standard 10-fold cross validation, leave-one-protein-out (LOPO) cross validation and independent testing. Since actual mRNA sequences have more non-binding regions than protein-binding regions, we tested the model on several datasets with different ratios of protein-binding regions to non-binding regions. The best performance of the model was obtained in a balanced dataset of positive and negative instances. 10-fold cross validation with a balanced dataset achieved a sensitivity of 91.6%, a specificity of 92.4%, an accuracy of 92.0%, a positive predictive value (PPV) of 91.7%, a negative predictive value (NPV) of 92.3% and a Matthews correlation coefficient (MCC) of 0.840. LOPO cross validation showed a lower performance than the 10-fold cross validation, but the performance remains high (87.6% accuracy and 0.752 MCC). In testing the model on independent datasets, it achieved an accuracy of 82.2% and an MCC of 0.656. Testing of our model and other state-of-the-art methods on a same dataset showed that our model is better than the others. Sequence profiles of log-odds scores of mono- and di-nucleotides were much more powerful

  11. Predictive value of dysregulation profile trajectories in childhood for symptoms of ADHD, anxiety and depression in late adolescence.

    PubMed

    Wang, B; Brueni, L G; Isensee, C; Meyer, T; Bock, N; Ravens-Sieberer, U; Klasen, F; Schlack, R; Becker, A; Rothenberger, A

    2018-06-01

    We examined whether there are certain dysregulation profile trajectories in childhood that may predict an elevated risk for mental disorders in later adolescence. Participants (N = 554) were drawn from a representative community sample of German children, 7-11 years old, who were followed over four measurement points (baseline, 1, 2 and 6 years later). Dysregulation profile, derived from the parent report of the Strengths and Difficulties Questionnaire, was measured at the first three measurement points, while symptoms of attention deficit hyperactivity disorder (ADHD), anxiety and depression were assessed at the fourth measurement point. We used latent class growth analysis to investigate developmental trajectories in the development of the dysregulation profile. The predictive value of dysregulation profile trajectories for later ADHD, anxiety and depression was examined by linear regression. For descriptive comparison, the predictive value of a single measurement (baseline) was calculated. Dysregulation profile was a stable trait during childhood. Boys and girls had similar levels of dysregulation profile over time. Two developmental subgroups were identified, namely the low dysregulation profile and the high dysregulation profile trajectory. The group membership in the high dysregulation profile trajectory (n = 102) was best predictive of later ADHD, regardless of an individual's gender and age. It explained 11% of the behavioural variance. For anxiety this was 8.7% and for depression 5.6%, including some gender effects. The single-point measurement was less predictive. An enduring high dysregulation profile in childhood showed some predictive value for psychological functioning 4 years later. Hence, it might be helpful in the preventive monitoring of children at risk.

  12. A Gene Expression Profile of BRCAness that Predicts for Responsiveness to Platinum and PARP Inhibitors

    DTIC Science & Technology

    2011-08-01

    tumors as BRCA-like (BL) or non-BRCA-like ( NBL ) corresponding to tumors predicted to have a BRCAness phenotype (BL tumors) or not ( NBL tumors). In...of six specimens with ATM knock down had the BL signature and six of six control specimens had the NBL signature (Fisher’s exact two sided p=0.002...control specimens had the NBL signature (Fisher’s exact two sided p=0.067). Figure 2. BRCAness profile distinguishes between BRCA1 knock down

  13. Chemical genomic profiling via barcode sequencing to predict compound mode of action

    PubMed Central

    Piotrowski, Jeff S.; Simpkins, Scott W.; Li, Sheena C.; Deshpande, Raamesh; McIlwain, Sean; Ong, Irene; Myers, Chad L.; Boone, Charlie; Andersen, Raymond J.

    2015-01-01

    Summary Chemical genomics is an unbiased, whole-cell approach to characterizing novel compounds to determine mode of action and cellular target. Our version of this technique is built upon barcoded deletion mutants of Saccharomyces cerevisiae and has been adapted to a high-throughput methodology using next-generation sequencing. Here we describe the steps to generate a chemical genomic profile from a compound of interest, and how to use this information to predict molecular mechanism and targets of bioactive compounds. PMID:25618354

  14. Genome-wide mutant profiling predicts the mechanism of a Lipid II binding antibiotic.

    PubMed

    Santiago, Marina; Lee, Wonsik; Fayad, Antoine Abou; Coe, Kathryn A; Rajagopal, Mithila; Do, Truc; Hennessen, Fabienne; Srisuknimit, Veerasak; Müller, Rolf; Meredith, Timothy C; Walker, Suzanne

    2018-06-01

    Identifying targets of antibacterial compounds remains a challenging step in the development of antibiotics. We have developed a two-pronged functional genomics approach to predict mechanism of action that uses mutant fitness data from antibiotic-treated transposon libraries containing both upregulation and inactivation mutants. We treated a Staphylococcus aureus transposon library containing 690,000 unique insertions with 32 antibiotics. Upregulation signatures identified from directional biases in insertions revealed known molecular targets and resistance mechanisms for the majority of these. Because single-gene upregulation does not always confer resistance, we used a complementary machine-learning approach to predict the mechanism from inactivation mutant fitness profiles. This approach suggested the cell wall precursor Lipid II as the molecular target of the lysocins, a mechanism we have confirmed. We conclude that docking to membrane-anchored Lipid II precedes the selective bacteriolysis that distinguishes these lytic natural products, showing the utility of our approach for nominating the antibiotic mechanism of action.

  15. Reduced model prediction of electron temperature profiles in microtearing-dominated NSTX plasmas

    NASA Astrophysics Data System (ADS)

    Kaye, S. M.; Guttenfelder, W.; Bell, R.; Gerhardt, S.; Leblanc, B.; Maingi, R.

    2014-10-01

    A representative H-mode discharge from the National Spherical Torus Experiment (NSTX) is studied in detail as a basis for a time-evolving prediction of the electron temperature profile using an appropriate reduced transport model. The time evolution of characteristic plasma variables such as βe, νe*, the MHD α parameter and the gradient scale lengths of Te, Ti and ne were examined prior to performing linear gyrokinetic calculations to determine the fastest growing microinstability at various times and locations throughout the discharge. The inferences from the parameter evolutions and the linear stability calculations were consistent. Early in the discharge, when βe and νe* were relatively low, ballooning parity modes were dominant. As both βe and νe* increased with time, microtearing became the dominant low-kθmode, especially in the outer half of the plasma. There are instances in time and radius where other modes, at higher-kθ, may be important for driving electron transport. The Rebut-Lallia-Watkins (RLW) electron thermal diffusivity model, which is based on microtearing-induced transport, was used to predict the time-evolving electron temperature across most of the profile. The results indicate that RLW does a good job of predicting Te for times and locations where microtearing was determined to be important, but not as well when microtearing was predicted to be stable or subdominant. This work has been supported by U.S. Dept of Energy contracts DE-AC02-09CH11466.

  16. Hierarchical Status Predicts Behavioral Vulnerability and Nucleus Accumbens Metabolic Profile Following Chronic Social Defeat Stress.

    PubMed

    Larrieu, Thomas; Cherix, Antoine; Duque, Aranzazu; Rodrigues, João; Lei, Hongxia; Gruetter, Rolf; Sandi, Carmen

    2017-07-24

    Extensive data highlight the existence of major differences in individuals' susceptibility to stress [1-4]. While genetic factors [5, 6] and exposure to early life stress [7, 8] are key components for such neurobehavioral diversity, intriguing observations revealed individual differences in response to stress in inbred mice [9-12]. This raised the possibility that other factors might be critical in stress vulnerability. A key challenge in the field is to identify non-invasively risk factors for vulnerability to stress. Here, we investigated whether behavioral factors, emerging from preexisting dominance hierarchies, could predict vulnerability to chronic stress [9, 13-16]. We applied a chronic social defeat stress (CSDS) model of depression in C57BL/6J mice to investigate the predictive power of hierarchical status to pinpoint which individuals will exhibit susceptibility to CSDS. Given that the high social status of dominant mice would be the one particularly challenged by CSDS, we predicted and found that dominant individuals were the ones showing a strong susceptibility profile as indicated by strong social avoidance following CSDS, while subordinate mice were not affected. Data from 1 H-NMR spectroscopy revealed that the metabolic profile in the nucleus accumbens (NAc) relates to social status and vulnerability to stress. Under basal conditions, subordinates show lower levels of energy-related metabolites compared to dominants. In subordinates, but not dominants, levels of these metabolites were increased after exposure to CSDS. To the best of our knowledge, this is the first study that identifies non-invasively the origin of behavioral risk factors predictive of stress-induced depression-like behaviors associated with metabolic changes. Copyright © 2017 Elsevier Ltd. All rights reserved.

  17. Prediction of mitochondrial proteins of malaria parasite using split amino acid composition and PSSM profile.

    PubMed

    Verma, Ruchi; Varshney, Grish C; Raghava, G P S

    2010-06-01

    The rate of human death due to malaria is increasing day-by-day. Thus the malaria causing parasite Plasmodium falciparum (PF) remains the cause of concern. With the wealth of data now available, it is imperative to understand protein localization in order to gain deeper insight into their functional roles. In this manuscript, an attempt has been made to develop prediction method for the localization of mitochondrial proteins. In this study, we describe a method for predicting mitochondrial proteins of malaria parasite using machine-learning technique. All models were trained and tested on 175 proteins (40 mitochondrial and 135 non-mitochondrial proteins) and evaluated using five-fold cross validation. We developed a Support Vector Machine (SVM) model for predicting mitochondrial proteins of P. falciparum, using amino acids and dipeptides composition and achieved maximum MCC 0.38 and 0.51, respectively. In this study, split amino acid composition (SAAC) is used where composition of N-termini, C-termini, and rest of protein is computed separately. The performance of SVM model improved significantly from MCC 0.38 to 0.73 when SAAC instead of simple amino acid composition was used as input. In addition, SVM model has been developed using composition of PSSM profile with MCC 0.75 and accuracy 91.38%. We achieved maximum MCC 0.81 with accuracy 92% using a hybrid model, which combines PSSM profile and SAAC. When evaluated on an independent dataset our method performs better than existing methods. A web server PFMpred has been developed for predicting mitochondrial proteins of malaria parasites ( http://www.imtech.res.in/raghava/pfmpred/).

  18. Development of Castration Resistant Prostate Cancer can be Predicted by a DNA Hypermethylation Profile.

    PubMed

    Angulo, Javier C; Andrés, Guillermo; Ashour, Nadia; Sánchez-Chapado, Manuel; López, Jose I; Ropero, Santiago

    2016-03-01

    Detection of DNA hypermethylation has emerged as a novel molecular biomarker for prostate cancer diagnosis and evaluation of prognosis. We sought to define whether a hypermethylation profile of patients with prostate cancer on androgen deprivation would predict castrate resistant prostate cancer. Genome-wide methylation analysis was performed using a methylation cancer panel in 10 normal prostates and 45 tumor samples from patients placed on androgen deprivation who were followed until castrate resistant disease developed. Castrate resistant disease was defined according to EAU (European Association of Urology) guideline criteria. Two pathologists reviewed the Gleason score, Ki-67 index and neuroendocrine differentiation. Hierarchical clustering analysis was performed and relationships with outcome were investigated by Cox regression and log rank analysis. We found 61 genes that were significantly hypermethylated in greater than 20% of tumors analyzed. Three clusters of patients were characterized by a DNA methylation profile, including 1 at risk for earlier castrate resistant disease (log rank p = 0.019) and specific mortality (log rank p = 0.002). Hypermethylation of ETV1 (HR 3.75) and ZNF215 (HR 2.89) predicted disease progression despite androgen deprivation. Hypermethylation of IRAK3 (HR 13.72), ZNF215 (HR 4.81) and SEPT9 (HR 7.64) were independent markers of prognosis. Prostate specific antigen greater than 25 ng/ml, Gleason pattern 5, Ki-67 index greater than 12% and metastasis at diagnosis also predicted a negative response to androgen deprivation. Study limitations included the retrospective design and limited number of cases. Epigenetic silencing of the mentioned genes could be novel molecular markers for the prognosis of advanced prostate cancer. It might predict castrate resistance during hormone deprivation and, thus, disease specific mortality. Gene hypermethylation is associated with disease progression in patients who receive hormone therapy. It

  19. Profiling persistent tubercule bacilli from patient sputa during therapy predicts early drug efficacy.

    PubMed

    Honeyborne, Isobella; McHugh, Timothy D; Kuittinen, Iitu; Cichonska, Anna; Evangelopoulos, Dimitrios; Ronacher, Katharina; van Helden, Paul D; Gillespie, Stephen H; Fernandez-Reyes, Delmiro; Walzl, Gerhard; Rousu, Juho; Butcher, Philip D; Waddell, Simon J

    2016-04-07

    New treatment options are needed to maintain and improve therapy for tuberculosis, which caused the death of 1.5 million people in 2013 despite potential for an 86 % treatment success rate. A greater understanding of Mycobacterium tuberculosis (M.tb) bacilli that persist through drug therapy will aid drug development programs. Predictive biomarkers for treatment efficacy are also a research priority. Genome-wide transcriptional profiling was used to map the mRNA signatures of M.tb from the sputa of 15 patients before and 3, 7 and 14 days after the start of standard regimen drug treatment. The mRNA profiles of bacilli through the first 2 weeks of therapy reflected drug activity at 3 days with transcriptional signatures at days 7 and 14 consistent with reduced M.tb metabolic activity similar to the profile of pre-chemotherapy bacilli. These results suggest that a pre-existing drug-tolerant M.tb population dominates sputum before and after early drug treatment, and that the mRNA signature at day 3 marks the killing of a drug-sensitive sub-population of bacilli. Modelling patient indices of disease severity with bacterial gene expression patterns demonstrated that both microbiological and clinical parameters were reflected in the divergent M.tb responses and provided evidence that factors such as bacterial load and disease pathology influence the host-pathogen interplay and the phenotypic state of bacilli. Transcriptional signatures were also defined that predicted measures of early treatment success (rate of decline in bacterial load over 3 days, TB test positivity at 2 months, and bacterial load at 2 months). This study defines the transcriptional signature of M.tb bacilli that have been expectorated in sputum after two weeks of drug therapy, characterizing the phenotypic state of bacilli that persist through treatment. We demonstrate that variability in clinical manifestations of disease are detectable in bacterial sputa signatures, and that the changing M.tb m

  20. Anthropometric profile of elite acrobatic gymnasts and prediction of role performance.

    PubMed

    Taboada-Iglesias, Yaiza; Gutiérrez-Sánchez, Águeda; Vernetta Santana, Mercedes

    2016-04-01

    This study is aimed at determining the anthropometric profile of acrobatic gymnasts, differentiating on the basis of their role. The sample consisted of 150 gymnasts (129 women and 21 men) from throughout Spain. The anthropometric measurements were taken according to the International Society for the Advancement of Kinanthropometry (ISAK) procedures. Morphological measurements, proportionality and somatotype were analyzed in both groups. A comparative analysis between groups and a prediction model were used to analyze the specific profile of each role. All morphological measurements showed significant differences (P<0.05) between tops and bases, the latter presenting higher values. The endomorphic element of the bases presented higher values than the tops, for whom the ectomorphy scores were higher. Bases have an endo-mesomorphic somatotype and tops present a balanced mesomorphic. There are no mesomorphy differences between the tops and bases. BMI was significantly higher in the bases (BMI=20.28 kg/m2). Proportionality differences between roles are shown. Both roles present negatives values for almost all variables studied except for the trochlear condyle of the humerus, the bicondyle of the femur and the wrist bistyloid breadth in tops and the wrist bistyloid breadth, the upper arm relaxed girths and maximum calf in bases. The best prediction model included thigh girth as the best explanatory covariate of role performance. Here are differences between both roles, bases being gymnasts of larger size than tops. However, they present no differences in the muscular component, as it might be expected.

  1. How good are publicly available web services that predict bioactivity profiles for drug repurposing?

    PubMed

    Murtazalieva, K A; Druzhilovskiy, D S; Goel, R K; Sastry, G N; Poroikov, V V

    2017-10-01

    Drug repurposing provides a non-laborious and less expensive way for finding new human medicines. Computational assessment of bioactivity profiles shed light on the hidden pharmacological potential of the launched drugs. Currently, several freely available computational tools are available via the Internet, which predict multitarget profiles of drug-like compounds. They are based on chemical similarity assessment (ChemProt, SuperPred, SEA, SwissTargetPrediction and TargetHunter) or machine learning methods (ChemProt and PASS). To compare their performance, this study has created two evaluation sets, consisting of (1) 50 well-known repositioned drugs and (2) 12 drugs recently patented for new indications. In the first set, sensitivity values varied from 0.64 (TarPred) to 1.00 (PASS Online) for the initial indications and from 0.64 (TarPred) to 0.98 (PASS Online) for the repurposed indications. In the second set, sensitivity values varied from 0.08 (SuperPred) to 1.00 (PASS Online) for the initial indications and from 0.00 (SuperPred) to 1.00 (PASS Online) for the repurposed indications. Thus, this analysis demonstrated that the performance of machine learning methods surpassed those of chemical similarity assessments, particularly in the case of novel repurposed indications.

  2. Enniatin and Beauvericin Biosynthesis in Fusarium Species: Production Profiles and Structural Determinant Prediction.

    PubMed

    Liuzzi, Vania C; Mirabelli, Valentina; Cimmarusti, Maria Teresa; Haidukowski, Miriam; Leslie, John F; Logrieco, Antonio F; Caliandro, Rocco; Fanelli, Francesca; Mulè, Giuseppina

    2017-01-25

    Members of the fungal genus Fusarium can produce numerous secondary metabolites, including the nonribosomal mycotoxins beauvericin (BEA) and enniatins (ENNs). Both mycotoxins are synthesized by the multifunctional enzyme enniatin synthetase (ESYN1) that contains both peptide synthetase and S-adenosyl-l-methionine-dependent N -methyltransferase activities. Several Fusarium species can produce ENNs, BEA or both, but the mechanism(s) enabling these differential metabolic profiles is unknown. In this study, we analyzed the primary structure of ESYN1 by sequencing esyn1 transcripts from different Fusarium species. We measured ENNs and BEA production by ultra-performance liquid chromatography coupled with photodiode array and Acquity QDa mass detector (UPLC-PDA-QDa) analyses. We predicted protein structures, compared the predictions by multivariate analysis methods and found a striking correlation between BEA/ENN-producing profiles and ESYN1 three-dimensional structures. Structural differences in the β strand's Asn789-Ala793 and His797-Asp802 portions of the amino acid adenylation domain can be used to distinguish BEA/ENN-producing Fusarium isolates from those that produce only ENN.

  3. Profiles of verbal working memory growth predict speech and language development in children with cochlear implants.

    PubMed

    Kronenberger, William G; Pisoni, David B; Harris, Michael S; Hoen, Helena M; Xu, Huiping; Miyamoto, Richard T

    2013-06-01

    Verbal short-term memory (STM) and working memory (WM) skills predict speech and language outcomes in children with cochlear implants (CIs) even after conventional demographic, device, and medical factors are taken into account. However, prior research has focused on single end point outcomes as opposed to the longitudinal process of development of verbal STM/WM and speech-language skills. In this study, the authors investigated relations between profiles of verbal STM/WM development and speech-language development over time. Profiles of verbal STM/WM development were identified through the use of group-based trajectory analysis of repeated digit span measures over at least a 2-year time period in a sample of 66 children (ages 6-16 years) with CIs. Subjects also completed repeated assessments of speech and language skills during the same time period. Clusters representing different patterns of development of verbal STM (digit span forward scores) were related to the growth rate of vocabulary and language comprehension skills over time. Clusters representing different patterns of development of verbal WM (digit span backward scores) were related to the growth rate of vocabulary and spoken word recognition skills over time. Different patterns of development of verbal STM/WM capacity predict the dynamic process of development of speech and language skills in this clinical population.

  4. Predicting Mental Imagery-Based BCI Performance from Personality, Cognitive Profile and Neurophysiological Patterns.

    PubMed

    Jeunet, Camille; N'Kaoua, Bernard; Subramanian, Sriram; Hachet, Martin; Lotte, Fabien

    2015-01-01

    Mental-Imagery based Brain-Computer Interfaces (MI-BCIs) allow their users to send commands to a computer using their brain-activity alone (typically measured by ElectroEncephaloGraphy-EEG), which is processed while they perform specific mental tasks. While very promising, MI-BCIs remain barely used outside laboratories because of the difficulty encountered by users to control them. Indeed, although some users obtain good control performances after training, a substantial proportion remains unable to reliably control an MI-BCI. This huge variability in user-performance led the community to look for predictors of MI-BCI control ability. However, these predictors were only explored for motor-imagery based BCIs, and mostly for a single training session per subject. In this study, 18 participants were instructed to learn to control an EEG-based MI-BCI by performing 3 MI-tasks, 2 of which were non-motor tasks, across 6 training sessions, on 6 different days. Relationships between the participants' BCI control performances and their personality, cognitive profile and neurophysiological markers were explored. While no relevant relationships with neurophysiological markers were found, strong correlations between MI-BCI performances and mental-rotation scores (reflecting spatial abilities) were revealed. Also, a predictive model of MI-BCI performance based on psychometric questionnaire scores was proposed. A leave-one-subject-out cross validation process revealed the stability and reliability of this model: it enabled to predict participants' performance with a mean error of less than 3 points. This study determined how users' profiles impact their MI-BCI control ability and thus clears the way for designing novel MI-BCI training protocols, adapted to the profile of each user.

  5. Predicting Mental Imagery-Based BCI Performance from Personality, Cognitive Profile and Neurophysiological Patterns

    PubMed Central

    Jeunet, Camille; N’Kaoua, Bernard; Subramanian, Sriram; Hachet, Martin; Lotte, Fabien

    2015-01-01

    Mental-Imagery based Brain-Computer Interfaces (MI-BCIs) allow their users to send commands to a computer using their brain-activity alone (typically measured by ElectroEncephaloGraphy—EEG), which is processed while they perform specific mental tasks. While very promising, MI-BCIs remain barely used outside laboratories because of the difficulty encountered by users to control them. Indeed, although some users obtain good control performances after training, a substantial proportion remains unable to reliably control an MI-BCI. This huge variability in user-performance led the community to look for predictors of MI-BCI control ability. However, these predictors were only explored for motor-imagery based BCIs, and mostly for a single training session per subject. In this study, 18 participants were instructed to learn to control an EEG-based MI-BCI by performing 3 MI-tasks, 2 of which were non-motor tasks, across 6 training sessions, on 6 different days. Relationships between the participants’ BCI control performances and their personality, cognitive profile and neurophysiological markers were explored. While no relevant relationships with neurophysiological markers were found, strong correlations between MI-BCI performances and mental-rotation scores (reflecting spatial abilities) were revealed. Also, a predictive model of MI-BCI performance based on psychometric questionnaire scores was proposed. A leave-one-subject-out cross validation process revealed the stability and reliability of this model: it enabled to predict participants’ performance with a mean error of less than 3 points. This study determined how users’ profiles impact their MI-BCI control ability and thus clears the way for designing novel MI-BCI training protocols, adapted to the profile of each user. PMID:26625261

  6. Gas chromatography/mass spectrometry based component profiling and quality prediction for Japanese sake.

    PubMed

    Mimura, Natsuki; Isogai, Atsuko; Iwashita, Kazuhiro; Bamba, Takeshi; Fukusaki, Eiichiro

    2014-10-01

    Sake is a Japanese traditional alcoholic beverage, which is produced by simultaneous saccharification and alcohol fermentation of polished and steamed rice by Aspergillus oryzae and Saccharomyces cerevisiae. About 300 compounds have been identified in sake, and the contribution of individual components to the sake flavor has been examined at the same time. However, only a few compounds could explain the characteristics alone and most of the attributes still remain unclear. The purpose of this study was to examine the relationship between the component profile and the attributes of sake. Gas chromatography coupled with mass spectrometry (GC/MS)-based non-targeted analysis was employed to obtain the low molecular weight component profile of Japanese sake including both nonvolatile and volatile compounds. Sake attributes and overall quality were assessed by analytical descriptive sensory test and the prediction model of the sensory score from the component profile was constructed by means of orthogonal projections to latent structures (OPLS) regression analysis. Our results showed that 12 sake attributes [ginjo-ka (aroma of premium ginjo sake), grassy/aldehydic odor, sweet aroma/caramel/burnt odor, sulfury odor, sour taste, umami, bitter taste, body, amakara (dryness), aftertaste, pungent/smoothness and appearance] and overall quality were accurately explained by component profiles. In addition, we were able to select statistically significant components according to variable importance on projection (VIP). Our methodology clarified the correlation between sake attribute and 200 low molecular components and presented the importance of each component thus, providing new insights to the flavor study of sake. Copyright © 2014 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

  7. Electromyographic Patterns during Golf Swing: Activation Sequence Profiling and Prediction of Shot Effectiveness

    PubMed Central

    Verikas, Antanas; Vaiciukynas, Evaldas; Gelzinis, Adas; Parker, James; Olsson, M. Charlotte

    2016-01-01

    This study analyzes muscle activity, recorded in an eight-channel electromyographic (EMG) signal stream, during the golf swing using a 7-iron club and exploits information extracted from EMG dynamics to predict the success of the resulting shot. Muscles of the arm and shoulder on both the left and right sides, namely flexor carpi radialis, extensor digitorum communis, rhomboideus and trapezius, are considered for 15 golf players (∼5 shots each). The method using Gaussian filtering is outlined for EMG onset time estimation in each channel and activation sequence profiling. Shots of each player revealed a persistent pattern of muscle activation. Profiles were plotted and insights with respect to player effectiveness were provided. Inspection of EMG dynamics revealed a pair of highest peaks in each channel as the hallmark of golf swing, and a custom application of peak detection for automatic extraction of swing segment was introduced. Various EMG features, encompassing 22 feature sets, were constructed. Feature sets were used individually and also in decision-level fusion for the prediction of shot effectiveness. The prediction of the target attribute, such as club head speed or ball carry distance, was investigated using random forest as the learner in detection and regression tasks. Detection evaluates the personal effectiveness of a shot with respect to the player-specific average, whereas regression estimates the value of target attribute, using EMG features as predictors. Fusion after decision optimization provided the best results: the equal error rate in detection was 24.3% for the speed and 31.7% for the distance; the mean absolute percentage error in regression was 3.2% for the speed and 6.4% for the distance. Proposed EMG feature sets were found to be useful, especially when used in combination. Rankings of feature sets indicated statistics for muscle activity in both the left and right body sides, correlation-based analysis of EMG dynamics and features

  8. Electromyographic Patterns during Golf Swing: Activation Sequence Profiling and Prediction of Shot Effectiveness.

    PubMed

    Verikas, Antanas; Vaiciukynas, Evaldas; Gelzinis, Adas; Parker, James; Olsson, M Charlotte

    2016-04-23

    This study analyzes muscle activity, recorded in an eight-channel electromyographic (EMG) signal stream, during the golf swing using a 7-iron club and exploits information extracted from EMG dynamics to predict the success of the resulting shot. Muscles of the arm and shoulder on both the left and right sides, namely flexor carpi radialis, extensor digitorum communis, rhomboideus and trapezius, are considered for 15 golf players (∼5 shots each). The method using Gaussian filtering is outlined for EMG onset time estimation in each channel and activation sequence profiling. Shots of each player revealed a persistent pattern of muscle activation. Profiles were plotted and insights with respect to player effectiveness were provided. Inspection of EMG dynamics revealed a pair of highest peaks in each channel as the hallmark of golf swing, and a custom application of peak detection for automatic extraction of swing segment was introduced. Various EMG features, encompassing 22 feature sets, were constructed. Feature sets were used individually and also in decision-level fusion for the prediction of shot effectiveness. The prediction of the target attribute, such as club head speed or ball carry distance, was investigated using random forest as the learner in detection and regression tasks. Detection evaluates the personal effectiveness of a shot with respect to the player-specific average, whereas regression estimates the value of target attribute, using EMG features as predictors. Fusion after decision optimization provided the best results: the equal error rate in detection was 24.3% for the speed and 31.7% for the distance; the mean absolute percentage error in regression was 3.2% for the speed and 6.4% for the distance. Proposed EMG feature sets were found to be useful, especially when used in combination. Rankings of feature sets indicated statistics for muscle activity in both the left and right body sides, correlation-based analysis of EMG dynamics and features

  9. Immune Profiles to Predict Response to Desensitization Therapy in Highly HLA-Sensitized Kidney Transplant Candidates

    PubMed Central

    Yabu, Julie M.; Siebert, Janet C.; Maecker, Holden T.

    2016-01-01

    Background Kidney transplantation is the most effective treatment for end-stage kidney disease. Sensitization, the formation of human leukocyte antigen (HLA) antibodies, remains a major barrier to successful kidney transplantation. Despite the implementation of desensitization strategies, many candidates fail to respond. Current progress is hindered by the lack of biomarkers to predict response and to guide therapy. Our objective was to determine whether differences in immune and gene profiles may help identify which candidates will respond to desensitization therapy. Methods and Findings Single-cell mass cytometry by time-of-flight (CyTOF) phenotyping, gene arrays, and phosphoepitope flow cytometry were performed in a study of 20 highly sensitized kidney transplant candidates undergoing desensitization therapy. Responders to desensitization therapy were defined as 5% or greater decrease in cumulative calculated panel reactive antibody (cPRA) levels, and non-responders had 0% decrease in cPRA. Using a decision tree analysis, we found that a combination of transitional B cell and regulatory T cell (Treg) frequencies at baseline before initiation of desensitization therapy could distinguish responders from non-responders. Using a support vector machine (SVM) and longitudinal data, TRAF3IP3 transcripts and HLA-DR-CD38+CD4+ T cells could also distinguish responders from non-responders. Combining all assays in a multivariate analysis and elastic net regression model with 72 analytes, we identified seven that were highly interrelated and eleven that predicted response to desensitization therapy. Conclusions Measuring baseline and longitudinal immune and gene profiles could provide a useful strategy to distinguish responders from non-responders to desensitization therapy. This study presents the integration of novel translational studies including CyTOF immunophenotyping in a multivariate analysis model that has potential applications to predict response to

  10. Immune Profiles to Predict Response to Desensitization Therapy in Highly HLA-Sensitized Kidney Transplant Candidates.

    PubMed

    Yabu, Julie M; Siebert, Janet C; Maecker, Holden T

    2016-01-01

    Kidney transplantation is the most effective treatment for end-stage kidney disease. Sensitization, the formation of human leukocyte antigen (HLA) antibodies, remains a major barrier to successful kidney transplantation. Despite the implementation of desensitization strategies, many candidates fail to respond. Current progress is hindered by the lack of biomarkers to predict response and to guide therapy. Our objective was to determine whether differences in immune and gene profiles may help identify which candidates will respond to desensitization therapy. Single-cell mass cytometry by time-of-flight (CyTOF) phenotyping, gene arrays, and phosphoepitope flow cytometry were performed in a study of 20 highly sensitized kidney transplant candidates undergoing desensitization therapy. Responders to desensitization therapy were defined as 5% or greater decrease in cumulative calculated panel reactive antibody (cPRA) levels, and non-responders had 0% decrease in cPRA. Using a decision tree analysis, we found that a combination of transitional B cell and regulatory T cell (Treg) frequencies at baseline before initiation of desensitization therapy could distinguish responders from non-responders. Using a support vector machine (SVM) and longitudinal data, TRAF3IP3 transcripts and HLA-DR-CD38+CD4+ T cells could also distinguish responders from non-responders. Combining all assays in a multivariate analysis and elastic net regression model with 72 analytes, we identified seven that were highly interrelated and eleven that predicted response to desensitization therapy. Measuring baseline and longitudinal immune and gene profiles could provide a useful strategy to distinguish responders from non-responders to desensitization therapy. This study presents the integration of novel translational studies including CyTOF immunophenotyping in a multivariate analysis model that has potential applications to predict response to desensitization, select candidates, and personalize

  11. TargetNet: a web service for predicting potential drug-target interaction profiling via multi-target SAR models.

    PubMed

    Yao, Zhi-Jiang; Dong, Jie; Che, Yu-Jing; Zhu, Min-Feng; Wen, Ming; Wang, Ning-Ning; Wang, Shan; Lu, Ai-Ping; Cao, Dong-Sheng

    2016-05-01

    Drug-target interactions (DTIs) are central to current drug discovery processes and public health fields. Analyzing the DTI profiling of the drugs helps to infer drug indications, adverse drug reactions, drug-drug interactions, and drug mode of actions. Therefore, it is of high importance to reliably and fast predict DTI profiling of the drugs on a genome-scale level. Here, we develop the TargetNet server, which can make real-time DTI predictions based only on molecular structures, following the spirit of multi-target SAR methodology. Naïve Bayes models together with various molecular fingerprints were employed to construct prediction models. Ensemble learning from these fingerprints was also provided to improve the prediction ability. When the user submits a molecule, the server will predict the activity of the user's molecule across 623 human proteins by the established high quality SAR model, thus generating a DTI profiling that can be used as a feature vector of chemicals for wide applications. The 623 SAR models related to 623 human proteins were strictly evaluated and validated by several model validation strategies, resulting in the AUC scores of 75-100 %. We applied the generated DTI profiling to successfully predict potential targets, toxicity classification, drug-drug interactions, and drug mode of action, which sufficiently demonstrated the wide application value of the potential DTI profiling. The TargetNet webserver is designed based on the Django framework in Python, and is freely accessible at http://targetnet.scbdd.com .

  12. TargetNet: a web service for predicting potential drug-target interaction profiling via multi-target SAR models

    NASA Astrophysics Data System (ADS)

    Yao, Zhi-Jiang; Dong, Jie; Che, Yu-Jing; Zhu, Min-Feng; Wen, Ming; Wang, Ning-Ning; Wang, Shan; Lu, Ai-Ping; Cao, Dong-Sheng

    2016-05-01

    Drug-target interactions (DTIs) are central to current drug discovery processes and public health fields. Analyzing the DTI profiling of the drugs helps to infer drug indications, adverse drug reactions, drug-drug interactions, and drug mode of actions. Therefore, it is of high importance to reliably and fast predict DTI profiling of the drugs on a genome-scale level. Here, we develop the TargetNet server, which can make real-time DTI predictions based only on molecular structures, following the spirit of multi-target SAR methodology. Naïve Bayes models together with various molecular fingerprints were employed to construct prediction models. Ensemble learning from these fingerprints was also provided to improve the prediction ability. When the user submits a molecule, the server will predict the activity of the user's molecule across 623 human proteins by the established high quality SAR model, thus generating a DTI profiling that can be used as a feature vector of chemicals for wide applications. The 623 SAR models related to 623 human proteins were strictly evaluated and validated by several model validation strategies, resulting in the AUC scores of 75-100 %. We applied the generated DTI profiling to successfully predict potential targets, toxicity classification, drug-drug interactions, and drug mode of action, which sufficiently demonstrated the wide application value of the potential DTI profiling. The TargetNet webserver is designed based on the Django framework in Python, and is freely accessible at http://targetnet.scbdd.com.

  13. Cannabis use in children with individualized risk profiles: Predicting the effect of universal prevention intervention.

    PubMed

    Miovský, Michal; Vonkova, Hana; Čablová, Lenka; Gabrhelík, Roman

    2015-11-01

    To study the effect of a universal prevention intervention targeting cannabis use in individual children with different risk profiles. A school-based randomized controlled prevention trial was conducted over a period of 33 months (n=1874 sixth-graders, baseline mean age 11.82). We used a two-level random intercept logistic model for panel data to predict the probabilities of cannabis use for each child. Specifically, we used eight risk/protective factors to characterize each child and then predicted two probabilities of cannabis use for each child if the child had the intervention or not. Using the two probabilities, we calculated the absolute and relative effect of the intervention for each child. According to the two probabilities, we also divided the sample into a low-risk group (the quarter of the children with the lowest probabilities), a moderate-risk group, and a high-risk group (the quarter of the children with the highest probabilities) and showed the average effect of the intervention on these groups. The differences between the intervention group and the control group were statistically significant in each risk group. The average predicted probabilities of cannabis use for a child from the low-risk group were 4.3% if the child had the intervention and 6.53% if no intervention was provided. The corresponding probabilities for a child from the moderate-risk group were 10.91% and 15.34% and for a child from the high-risk group 25.51% and 32.61%. School grades, thoughts of hurting oneself, and breaking the rules were the three most important factors distinguishing high-risk and low-risk children. We predicted the effect of the intervention on individual children, characterized by their risk/protective factors. The predicted absolute effect and relative effect of any intervention for any selected risk/protective profile of a given child may be utilized in both prevention practice and research. Copyright © 2015 Elsevier Ltd. All rights reserved.

  14. Quantitative prediction of shrimp disease incidence via the profiles of gut eukaryotic microbiota.

    PubMed

    Xiong, Jinbo; Yu, Weina; Dai, Wenfang; Zhang, Jinjie; Qiu, Qiongfen; Ou, Changrong

    2018-04-01

    One common notion is emerging that gut eukaryotes are commensal or beneficial, rather than detrimental. To date, however, surprisingly few studies have been taken to discern the factors that govern the assembly of gut eukaryotes, despite growing interest in the dysbiosis of gut microbiota-disease relationship. Herein, we firstly explored how the gut eukaryotic microbiotas were assembled over shrimp postlarval to adult stages and a disease progression. The gut eukaryotic communities changed markedly as healthy shrimp aged, and converged toward an adult-microbiota configuration. However, the adult-like stability was distorted by disease exacerbation. A null model untangled that the deterministic processes that governed the gut eukaryotic assembly tended to be more important over healthy shrimp development, whereas this trend was inverted as the disease progressed. After ruling out the baseline of gut eukaryotes over shrimp ages, we identified disease-discriminatory taxa (species level afforded the highest accuracy of prediction) that characteristic of shrimp health status. The profiles of these taxa contributed an overall 92.4% accuracy in predicting shrimp health status. Notably, this model can accurately diagnose the onset of shrimp disease. Interspecies interaction analysis depicted how the disease-discriminatory taxa interacted with one another in sustaining shrimp health. Taken together, our findings offer novel insights into the underlying ecological processes that govern the assembly of gut eukaryotes over shrimp postlarval to adult stages and a disease progression. Intriguingly, the established model can quantitatively and accurately predict the incidences of shrimp disease.

  15. Prediction of dissolved oxygen and carbon dioxide concentration profiles in tubular photobioreactors for microalgal culture

    PubMed

    Rubio; Fernandez; Perez; Camacho; Grima

    1999-01-05

    A model is developed for prediction of axial concentration profiles of dissolved oxygen and carbon dioxide in tubular photobioreactors used for culturing microalgae. Experimental data are used to verify the model for continuous outdoor culture of Porphyridium cruentum grown in a 200-L reactor with 100-m long tubular solar receiver. The culture was carried out at a dilution rate of 0.05 h-1 applied only during a 10-h daylight period. The quasi-steady state biomass concentration achieved was 3.0 g. L-1, corresponding to a biomass productivity of 1.5 g. L-1. d-1. The model could predict the dissolved oxygen level in both gas disengagement zone of the reactor and at the end of the loop, the exhaust gas composition, the amount of carbon dioxide injected, and the pH of the culture at each hour. In predicting the various parameters, the model took into account the length of the solar receiver tube, the rate of photosynthesis, the velocity of flow, the degree of mixing, and gas-liquid mass transfer. Because the model simulated the system behavior as a function of tube length and operational variables (superficial gas velocity in the riser, composition of carbon dioxide in the gas injected in the solar receiver and its injection rate), it could potentially be applied to rational design and scale-up of photobioreactors. Copyright 1999 John Wiley & Sons, Inc.

  16. Predicting lysine glycation sites using bi-profile bayes feature extraction.

    PubMed

    Ju, Zhe; Sun, Juhe; Li, Yanjie; Wang, Li

    2017-12-01

    Glycation is a nonenzymatic post-translational modification which has been found to be involved in various biological processes and closely associated with many metabolic diseases. The accurate identification of glycation sites is important to understand the underlying molecular mechanisms of glycation. As the traditional experimental methods are often labor-intensive and time-consuming, it is desired to develop computational methods to predict glycation sites. In this study, a novel predictor named BPB_GlySite is proposed to predict lysine glycation sites by using bi-profile bayes feature extraction and support vector machine algorithm. As illustrated by 10-fold cross-validation, BPB_GlySite achieves a satisfactory performance with a Sensitivity of 63.68%, a Specificity of 72.60%, an Accuracy of 69.63% and a Matthew's correlation coefficient of 0.3499. Experimental results also indicate that BPB_GlySite significantly outperforms three existing glycation sites predictors: NetGlycate, PreGly and Gly-PseAAC. Therefore, BPB_GlySite can be a useful bioinformatics tool for the prediction of glycation sites. A user-friendly web-server for BPB_GlySite is established at 123.206.31.171/BPB_GlySite/. Copyright © 2017 Elsevier Ltd. All rights reserved.

  17. Profiling healthy eaters. Determining factors that predict healthy eating practices among Dutch adults.

    PubMed

    Swan, Emily; Bouwman, Laura; Hiddink, Gerrit Jan; Aarts, Noelle; Koelen, Maria

    2015-06-01

    Research has identified multiple factors that predict unhealthy eating practices. However what remains poorly understood are factors that promote healthy eating practices. This study aimed to determine a set of factors that represent a profile of healthy eaters. This research applied Antonovsky's salutogenic framework for health development to examine a set of factors that predict healthy eating in a cross-sectional study of Dutch adults. Data were analyzed from participants (n = 703) who completed the study's survey in January 2013. Logistic regression analysis was performed to test the association of survey factors on the outcome variable high dietary score. In the multivariate logistic regression model, five factors contributed significantly (p < .05) to the predictive ability of the overall model: being female; living with a partner; a strong sense of coherence (construct from the salutogenic framework), flexible restraint of eating, and self-efficacy for healthy eating. Findings complement what is already known of the factors that relate to poor eating practices. This can provide nutrition promotion with a more comprehensive picture of the factors that both support and hinder healthy eating practices. Future research should explore these factors to better understand their origins and mechanisms in relation to healthy eating practices. Copyright © 2015 Elsevier Ltd. All rights reserved.

  18. An empirical model for inverted-velocity-profile jet noise prediction

    NASA Technical Reports Server (NTRS)

    Stone, J. R.

    1977-01-01

    An empirical model for predicting the noise from inverted-velocity-profile coaxial or coannular jets is presented and compared with small-scale static and simulated flight data. The model considered the combined contributions of as many as four uncorrelated constituent sources: the premerged-jet/ambient mixing region, the merged-jet/ambient mixing region, outer-stream shock/turbulence interaction, and inner-stream shock/turbulence interaction. The noise from the merged region occurs at relatively low frequency and is modeled as the contribution of a circular jet at merged conditions and total exhaust area, with the high frequencies attenuated. The noise from the premerged region occurs at high frequency and is modeled as the contribution of an equivalent plug nozzle at outer stream conditions, with the low frequencies attenuated.

  19. Plasma metabolomic profiles predict near-term death among individuals with lower extremity peripheral arterial disease.

    PubMed

    Huang, Chiang-Ching; McDermott, Mary M; Liu, Kiang; Kuo, Ching-Hua; Wang, San-Yuan; Tao, Huimin; Tseng, Yufeng Jane

    2013-10-01

    Individuals with peripheral arterial disease (PAD) have a nearly two-fold increased risk of all-cause and cardiovascular disease mortality compared to those without PAD. This pilot study determined whether metabolomic profiling can accurately identify patients with PAD who are at increased risk of near-term mortality. We completed a case-control study using (1)H NMR metabolomic profiling of plasma from 20 decedents with PAD, without critical limb ischemia, who had blood drawn within 8 months prior to death (index blood draw) and within 10 to 28 months prior to death (preindex blood draw). Twenty-one PAD participants who survived more than 30 months after their index blood draw served as a control population. Results showed distinct metabolomic patterns between preindex decedent, index decedent, and survivor samples. The major chemical signals contributing to the differential pattern (between survivors and decedents) arose from the fatty acyl chain protons of lipoproteins and the choline head group protons of phospholipids. Using the top 40 chemical signals for which the intensity was most distinct between survivor and preindex decedent samples, classification models predicted near-term all-cause death with overall accuracy of 78% (32/41), a sensitivity of 85% (17/20), and a specificity of 71% (15/21). When comparing survivor with index decedent samples, the overall classification accuracy was optimal at 83% (34/41) with a sensitivity of 80% (16/20) and a specificity of 86% (18/21), using as few as the top 10 to 20 chemical signals. Our results suggest that metabolomic profiling of plasma may be useful for identifying PAD patients at increased risk for near-term death. Larger studies using more sensitive metabolomic techniques are needed to identify specific metabolic pathways associated with increased risk of near-term all-cause mortality among PAD patients. Copyright © 2013 Society for Vascular Surgery. Published by Mosby, Inc. All rights reserved.

  20. Prediction of future risk of insulin resistance and metabolic syndrome based on Korean boy's metabolite profiling.

    PubMed

    Lee, AeJin; Jang, Han Byul; Ra, Moonjin; Choi, Youngshim; Lee, Hye-Ja; Park, Ju Yeon; Kang, Jae Heon; Park, Kyung-Hee; Park, Sang Ick; Song, Jihyun

    2015-01-01

    Childhood obesity is strongly related to future insulin resistance and metabolic syndrome. Thus, identifying early biomarkers of obesity-related diseases based on metabolic profiling is useful to control future metabolic disorders. We compared metabolic profiles between obese and normal-weight children and investigated specific biomarkers of future insulin resistance and metabolic syndrome. In all, 186 plasma metabolites were analysed at baseline and after 2 years in 109 Korean boys (age 10.5±0.4 years) from the Korean Child Obesity Cohort Study using the AbsoluteIDQ™ p180 Kit. We observed that levels of 41 metabolites at baseline and 40 metabolites at follow-up were significantly altered in obese children (p<0.05). Obese children showed significantly higher levels of branched-chain amino acids (BCAAs) and several acylcarnitines and lower levels of acyl-alkyl phosphatidylcholines. Also, baseline BCAAs were significantly positively correlated with both homeostasis model assessment for insulin resistance (HOMA-IR) and continuous metabolic risk score at the 2-year follow-up. In logistic regression analyses with adjustments for degree of obesity at baseline, baseline BCAA concentration, greater than the median value, was identified as a predictor of future risk of insulin resistance and metabolic syndrome. High BCAA concentration could be "early" biomarkers for predicting future metabolic diseases. Copyright © 2014 Asian Oceanian Association for the Study of Obesity. Published by Elsevier Ltd. All rights reserved.

  1. Muscle Protein Profiles Used for Prediction of Texture of Farmed Salmon (Salmo salar L.).

    PubMed

    Ørnholt-Johansson, Gine; Frosch, Stina; Gudjónsdóttir, María; Wulff, Tune; Jessen, Flemming

    2017-04-26

    A soft texture is undesired in Atlantic salmon as it leads to downgrading and reduced yield, yet it is a factor for which the cause is not fully understood. This lack of understanding highlights the need for identifying the cause of the soft texture and developing solutions by which the processing industry can improve the yield. Changes in muscle protein profiles can occur both pre- and postharvest and constitute an overall characterization of the muscle properties including texture. The aim of this study was to investigate this relationship between specific muscle proteins and the texture of the salmon fillet. Samples for 2D-gel-based proteomics were taken from the fillet above the lateral line at the same position as where the texture had been measured. The resulting protein profiles were analyzed using multivariate data analysis. Sixteen proteins were found to correlate to the measured texture, showing that it is possible to predict peak force based on a small subset of proteins. Additionally, eight of the 16 proteins were identified by tandem mass spectrometry including serum albumin, dipeptidyl peptidase 3, heat shock protein 70, annexins, and a protein presumed to be a titin fragment. It is contemplated that the identification of these proteins and their significance for the measured texture will contribute to further understanding of the Atlantic salmon muscle texture.

  2. Classification and prediction of toxicity of chemicals using an automated phenotypic profiling of Caenorhabditis elegans.

    PubMed

    Gao, Shan; Chen, Weiyang; Zeng, Yingxin; Jing, Haiming; Zhang, Nan; Flavel, Matthew; Jois, Markandeya; Han, Jing-Dong J; Xian, Bo; Li, Guojun

    2018-04-18

    Traditional toxicological studies have relied heavily on various animal models to understand the effect of various compounds in a biological context. Considering the great cost, complexity and time involved in experiments using higher order organisms. Researchers have been exploring alternative models that avoid these disadvantages. One example of such a model is the nematode Caenorhabditis elegans. There are some advantages of C. elegans, such as small size, short life cycle, well defined genome, ease of maintenance and efficient reproduction. As these benefits allow large scale studies to be initiated with relative ease, the problem of how to efficiently capture, organize and analyze the resulting large volumes of data must be addressed. We have developed a new method for quantitative screening of chemicals using C. elegans. 33 features were identified for each chemical treatment. The compounds with different toxicities were shown to alter the phenotypes of C. elegans in distinct and detectable patterns. We found that phenotypic profiling revealed conserved functions to classify and predict the toxicity of different chemicals. Our results demonstrate the power of phenotypic profiling in C. elegans under different chemical environments.

  3. Higher schizotypy predicts better metabolic profile in unaffected siblings of patients with schizophrenia.

    PubMed

    Atbasoglu, E Cem; Gumus-Akay, Guvem; Guloksuz, Sinan; Saka, Meram Can; Ucok, Alp; Alptekin, Koksal; Gullu, Sevim; van Os, Jim

    2018-04-01

    Type 2 diabetes (T2D) is more frequent in schizophrenia (Sz) than in the general population. This association is partly accounted for by shared susceptibility genetic variants. We tested the hypotheses that a genetic predisposition to Sz would be associated with higher likelihood of insulin resistance (IR), and that IR would be predicted by subthreshold psychosis phenotypes. Unaffected siblings of Sz patients (n = 101) were compared with a nonclinical sample (n = 305) in terms of IR, schizotypy (SzTy), and a behavioural experiment of "jumping to conclusions". The measures, respectively, were the Homeostatic Model Assessment of Insulin Resistance (HOMA-IR), Structured Interview for Schizotypy-Revised (SIS-R), and the Beads Task (BT). The likelihood of IR was examined in multiple regression models that included sociodemographic, metabolic, and cognitive parameters alongside group status, SIS-R scores, and BT performance. Insulin resistance was less frequent in siblings (31.7%) compared to controls (43.3%) (p < 0.05), and negatively associated with SzTy, as compared among the tertile groups for the latter (p < 0.001). The regression model that examined all relevant parameters included the tSzTy tertiles, TG and HDL-C levels, and BMI, as significant predictors of IR. Lack of IR was predicted by the highest as compared to the lowest SzTy tertile [OR (95%CI): 0.43 (0.21-0.85), p = 0.015]. Higher dopaminergic activity may contribute to both schizotypal features and a favourable metabolic profile in the same individual. This is compatible with dopamine's regulatory role in glucose metabolism via indirect central actions and a direct action on pancreatic insulin secretion. The relationship between dopaminergic activity and metabolic profile in Sz must be examined in longitudinal studies with younger unaffected siblings.

  4. Biochemical profiling in silico--predicting substrate specificities of large enzyme families.

    PubMed

    Tyagi, Sadhna; Pleiss, Juergen

    2006-06-25

    A general high-throughput method for in silico biochemical profiling of enzyme families has been developed based on covalent docking of potential substrates into the binding sites of target enzymes. The method has been tested by systematically docking transition state--analogous intermediates of 12 substrates into the binding sites of 20 alpha/beta hydrolases from 15 homologous families. To evaluate the effect of side chain orientations to the docking results, 137 crystal structures were included in the analysis. A good substrate must fulfil two criteria: it must bind in a productive geometry with four hydrogen bonds between the substrate and the catalytic histidine and the oxyanion hole, and a high affinity of the enzyme-substrate complex as predicted by a high docking score. The modelling results in general reproduce experimental data on substrate specificity and stereoselectivity: the differences in substrate specificity of cholinesterases toward acetyl- and butyrylcholine, the changes of activity of lipases and esterases upon the size of the acid moieties, activity of lipases and esterases toward tertiary alcohols, and the stereopreference of lipases and esterases toward chiral secondary alcohols. Rigidity of the docking procedure was the major reason for false positive and false negative predictions, as the geometry of the complex and docking score may sensitively depend on the orientation of individual side chains. Therefore, appropriate structures have to be identified. In silico biochemical profiling provides a time efficient and cost saving protocol for virtual screening to identify the potential substrates of the members of large enzyme family from a library of molecules.

  5. Theoretical prediction of pullout strengths for dental and orthopaedic screws with conical profile and buttress threads.

    PubMed

    Shih, Kao-Shang; Hou, Sheng-Mou; Lin, Shang-Chih

    2017-12-01

    The pullout strength of a screw is an indicator of how secure bone fragments are being held in place. Such bone-purchasing ability is sensitive to bone quality, thread design, and the pilot hole, and is often evaluated by experimental and numerical methods. Historically, there are some mathematical formulae to simulate the screw withdrawal from the synthetic bone. There are great variations in screw specifications. However, extensive investigation of the correlation between experimental and analytical results has not been reported in literature. Referring to the literature formulae, this study aims to evaluate the differences in the calculated pullout strengths. The pullout tests of the surgical screws are measured and the sawbone is used as the testing block. The absolute errors and correlation coefficients of the experimental and analytical results are calculated as the comparison baselines of the formulae. The absolute error of the dental, traumatic, and spinal groups are 21.7%, 95.5%, and 37.0%, respectively. For the screws with a conical profile and/or tiny threads, the calculated and measured results are not well correlated. The formulae are not accurate indicators of the pullout strengths of the screws where the design parameters are slightly varied. However, the experimental and numerical results are highly correlated for the cylindrical screws. The pullout strength of a conical screw is higher than that of its counterpart, but all formulae consistently predict the opposite results. In general, the bony purchase of the buttress threads is securer than that of the symmetric thread. An absolute error of up to 51.4% indicates the theoretical results cannot predict the actual value of the pullout strength. Only thread diameter, pitch, and depth are considered in the investigated formulae. The thread profile and shape should be formulated to modify the slippage mechanism at the bone-screw interfaces and simulate the strength change in the squeezed bones

  6. Assimilation of temperature and salinity profile data in the Norwegian Climate Prediction Model

    NASA Astrophysics Data System (ADS)

    Wang, Yiguo; Counillon, Francois; Bertino, Laurent; Bethke, Ingo; Keenlyside, Noel

    2016-04-01

    Assimilating temperature and salinity profile data is promising to constrain the ocean component of Earth system models for the purpose of seasonal-to-dedacal climate predictions. However, assimilating temperature and salinity profiles that are measured in standard depth coordinate (z-coordinate) into isopycnic coordinate ocean models that are discretised by water densities is challenging. Prior studies (Thacker and Esenkov, 2002; Xie and Zhu, 2010) suggested that converting observations to the model coordinate (i.e. innovations in isopycnic coordinate) performs better than interpolating model state to observation coordinate (i.e. innovations in z-coordinate). This problem is revisited here with the Norwegian Climate Prediction Model, which applies the ensemble Kalman filter (EnKF) into the ocean isopycnic model (MICOM) of the Norwegian Earth System Model. We perform Observing System Simulation Experiments (OSSEs) to compare two schemes (the EnKF-z and EnKF-ρ). In OSSEs, the truth is set to the EN4 objective analyses and observations are perturbations of the truth with white noises. Unlike in previous studies, it is found that EnKF-z outperforms EnKF-ρ for different observed vertical resolution, inhomogeneous sampling (e.g. upper 1000 meter observations only), or lack of salinity measurements. That is mostly because the operator converting observations into isopycnic coordinate is strongly non-linear. We also study the horizontal localisation radius at certain arbitrary grid points. Finally, we perform the EnKF-z with the chosen localisation radius in a realistic framework with NorCPM over a 5-year analysis period. The analysis is validated by different independent datasets.

  7. Identifying and Predicting Profiles of Medical Noncompliance: Pediatric Caregivers' Antibiotic Stewardship.

    PubMed

    Smith, Rachel A; Kim, Youllee; M'Ikanatha, Nkuchia M

    2018-05-14

    Sometimes compliance with medical recommendations is problematic. We investigated pediatric caregivers' (N = 606) patterns of noncompliance with antibiotic stewardship based on the obstacle hypothesis. We tested predictors of noncompliance framed by the obstacle hypothesis, dissonance theory, and psychological reactance. The results revealed four profiles of caregivers' stewardship: one marked by compliance (Stewards) and three marked by types of noncompliance (Stockers, Persuaders, and Dissenters). The covariate analysis showed that, although psychological reactance predicted being noncompliant, it was types of obstacles and discrepant experiences that predicted caregivers' patterns of noncompliance with antibiotic stewardship. Campaign planning often focuses on identifying the belief most associated with the targeted outcome, such as compliance. Noncompliance research, however, points out that persuaders may be successful to the extent to which they anticipate obstacles to compliance and address them in their influence attempts. A shift from medical noncompliance to patient engagement also affords an opportunity to consider how some recommendations create obstacles for others and to find positive ways to embrace conflicting needs, tensions, and reasons for refusal in order to promote collective goals.

  8. Predicting the response of the injured lung to the mechanical breath profile

    PubMed Central

    Smith, Bradford J.; Lundblad, Lennart K. A.; Kollisch-Singule, Michaela; Satalin, Joshua; Nieman, Gary; Habashi, Nader

    2015-01-01

    Mechanical ventilation is a crucial component of the supportive care provided to patients with acute respiratory distress syndrome. Current practice stipulates the use of a low tidal volume (Vt) of 6 ml/kg ideal body weight, the presumptive notion being that this limits overdistension of the tissues and thus reduces volutrauma. We have recently found, however, that airway pressure release ventilation (APRV) is efficacious at preventing ventilator-induced lung injury, yet APRV has a very different mechanical breath profile compared with conventional low-Vt ventilation. To gain insight into the relative merits of these two ventilation modes, we measured lung mechanics and derecruitability in rats before and following Tween lavage. We fit to these lung mechanics measurements a computational model of the lung that accounts for both the degree of tissue distension of the open lung and the amount of lung derecruitment that takes place as a function of time. Using this model, we predicted how tissue distension, open lung fraction, and intratidal recruitment vary as a function of ventilator settings both for conventional low-Vt ventilation and for APRV. Our predictions indicate that APRV is more effective at recruiting the lung than low-Vt ventilation, but without causing more overdistension of the tissues. On the other hand, low-Vt ventilation generally produces less intratidal recruitment than APRV. Predictions such as these may be useful for deciding on the relative benefits of different ventilation modes and thus may serve as a means for determining how to ventilate a given lung in the least injurious fashion. PMID:25635004

  9. Predicted thermal response of a cryogenic fuel tank exposed to simulated aerodynamic heating profiles with different cryogens and fill levels

    NASA Technical Reports Server (NTRS)

    Hanna, Gregory J.; Stephens, Craig A.

    1991-01-01

    A two dimensional finite difference thermal model was developed to predict the effects of heating profile, fill level, and cryogen type prior to experimental testing the Generic Research Cryogenic Tank (GRCT). These numerical predictions will assist in defining test scenarios, sensor locations, and venting requirements for the GRCT experimental tests. Boiloff rates, tank-wall and fluid temperatures, and wall heat fluxes were determined for 20 computational test cases. The test cases spanned three discrete fill levels and three heating profiles for hydrogen and nitrogen.

  10. Global proteomics profiling improves drug sensitivity prediction: results from a multi-omics, pan-cancer modeling approach.

    PubMed

    Ali, Mehreen; Khan, Suleiman A; Wennerberg, Krister; Aittokallio, Tero

    2018-04-15

    Proteomics profiling is increasingly being used for molecular stratification of cancer patients and cell-line panels. However, systematic assessment of the predictive power of large-scale proteomic technologies across various drug classes and cancer types is currently lacking. To that end, we carried out the first pan-cancer, multi-omics comparative analysis of the relative performance of two proteomic technologies, targeted reverse phase protein array (RPPA) and global mass spectrometry (MS), in terms of their accuracy for predicting the sensitivity of cancer cells to both cytotoxic chemotherapeutics and molecularly targeted anticancer compounds. Our results in two cell-line panels demonstrate how MS profiling improves drug response predictions beyond that of the RPPA or the other omics profiles when used alone. However, frequent missing MS data values complicate its use in predictive modeling and required additional filtering, such as focusing on completely measured or known oncoproteins, to obtain maximal predictive performance. Rather strikingly, the two proteomics profiles provided complementary predictive signal both for the cytotoxic and targeted compounds. Further, information about the cellular-abundance of primary target proteins was found critical for predicting the response of targeted compounds, although the non-target features also contributed significantly to the predictive power. The clinical relevance of the selected protein markers was confirmed in cancer patient data. These results provide novel insights into the relative performance and optimal use of the widely applied proteomic technologies, MS and RPPA, which should prove useful in translational applications, such as defining the best combination of omics technologies and marker panels for understanding and predicting drug sensitivities in cancer patients. Processed datasets, R as well as Matlab implementations of the methods are available at https://github.com/mehr-een/bemkl-rbps. mehreen

  11. Computational Models for Prediction of Yeast Strain Potential for Winemaking from Phenotypic Profiles

    PubMed Central

    Umek, Lan; Fonseca, Elza; Drumonde-Neves, João; Dequin, Sylvie; Zupan, Blaz; Schuller, Dorit

    2013-01-01

    Saccharomyces cerevisiae strains from diverse natural habitats harbour a vast amount of phenotypic diversity, driven by interactions between yeast and the respective environment. In grape juice fermentations, strains are exposed to a wide array of biotic and abiotic stressors, which may lead to strain selection and generate naturally arising strain diversity. Certain phenotypes are of particular interest for the winemaking industry and could be identified by screening of large number of different strains. The objective of the present work was to use data mining approaches to identify those phenotypic tests that are most useful to predict a strain's potential for winemaking. We have constituted a S. cerevisiae collection comprising 172 strains of worldwide geographical origins or technological applications. Their phenotype was screened by considering 30 physiological traits that are important from an oenological point of view. Growth in the presence of potassium bisulphite, growth at 40°C, and resistance to ethanol were mostly contributing to strain variability, as shown by the principal component analysis. In the hierarchical clustering of phenotypic profiles the strains isolated from the same wines and vineyards were scattered throughout all clusters, whereas commercial winemaking strains tended to co-cluster. Mann-Whitney test revealed significant associations between phenotypic results and strain's technological application or origin. Naïve Bayesian classifier identified 3 of the 30 phenotypic tests of growth in iprodion (0.05 mg/mL), cycloheximide (0.1 µg/mL) and potassium bisulphite (150 mg/mL) that provided most information for the assignment of a strain to the group of commercial strains. The probability of a strain to be assigned to this group was 27% using the entire phenotypic profile and increased to 95%, when only results from the three tests were considered. Results show the usefulness of computational approaches to simplify strain selection

  12. Melancholic depression prediction by identifying representative features in metabolic and microarray profiles with missing values.

    PubMed

    Nie, Zhi; Yang, Tao; Liu, Yashu; Li, Qingyang; Narayan, Vaibhav A; Wittenberg, Gayle; Ye, Jieping

    2015-01-01

    Recent studies have revealed that melancholic depression, one major subtype of depression, is closely associated with the concentration of some metabolites and biological functions of certain genes and pathways. Meanwhile, recent advances in biotechnologies have allowed us to collect a large amount of genomic data, e.g., metabolites and microarray gene expression. With such a huge amount of information available, one approach that can give us new insights into the understanding of the fundamental biology underlying melancholic depression is to build disease status prediction models using classification or regression methods. However, the existence of strong empirical correlations, e.g., those exhibited by genes sharing the same biological pathway in microarray profiles, tremendously limits the performance of these methods. Furthermore, the occurrence of missing values which are ubiquitous in biomedical applications further complicates the problem. In this paper, we hypothesize that the problem of missing values might in some way benefit from the correlation between the variables and propose a method to learn a compressed set of representative features through an adapted version of sparse coding which is capable of identifying correlated variables and addressing the issue of missing values simultaneously. An efficient algorithm is also developed to solve the proposed formulation. We apply the proposed method on metabolic and microarray profiles collected from a group of subjects consisting of both patients with melancholic depression and healthy controls. Results show that the proposed method can not only produce meaningful clusters of variables but also generate a set of representative features that achieve superior classification performance over those generated by traditional clustering and data imputation techniques. In particular, on both datasets, we found that in comparison with the competing algorithms, the representative features learned by the proposed

  13. Livestock abundance predicts vampire bat demography, immune profiles and bacterial infection risk

    PubMed Central

    Czirják, Gábor Á.; Volokhov, Dmitriy V.; Carrera, Jorge E.; Camus, Melinda S.; Navara, Kristen J.; Chizhikov, Vladimir E.; Fenton, M. Brock; Simmons, Nancy B.; Recuenco, Sergio E.; Gilbert, Amy T.

    2018-01-01

    Human activities create novel food resources that can alter wildlife–pathogen interactions. If resources amplify or dampen, pathogen transmission probably depends on both host ecology and pathogen biology, but studies that measure responses to provisioning across both scales are rare. We tested these relationships with a 4-year study of 369 common vampire bats across 10 sites in Peru and Belize that differ in the abundance of livestock, an important anthropogenic food source. We quantified innate and adaptive immunity from bats and assessed infection with two common bacteria. We predicted that abundant livestock could reduce starvation and foraging effort, allowing for greater investments in immunity. Bats from high-livestock sites had higher microbicidal activity and proportions of neutrophils but lower immunoglobulin G and proportions of lymphocytes, suggesting more investment in innate relative to adaptive immunity and either greater chronic stress or pathogen exposure. This relationship was most pronounced in reproductive bats, which were also more common in high-livestock sites, suggesting feedbacks between demographic correlates of provisioning and immunity. Infection with both Bartonella and haemoplasmas were correlated with similar immune profiles, and both pathogens tended to be less prevalent in high-livestock sites, although effects were weaker for haemoplasmas. These differing responses to provisioning might therefore reflect distinct transmission processes. Predicting how provisioning alters host–pathogen interactions requires considering how both within-host processes and transmission modes respond to resource shifts. This article is part of the theme issue ‘Anthropogenic resource subsidies and host–parasite dynamics in wildlife’. PMID:29531144

  14. Predicting and comparing long-term measles antibody profiles of different immunization policies.

    PubMed

    Lee, M S; Nokes, D J

    2001-01-01

    Measles outbreaks are infrequent and localized in areas with high coverage of measles vaccine. The need is to assess long-term effectiveness of coverage. Since 1991, no measles epidemic affecting the whole island has occurred in Taiwan, China. Epidemiological models are developed to predict the long-term measles antibody profiles and compare the merits of different immunization policies on the island. The current measles immunization policy in Taiwan, China, is 1 dose of measles vaccine at 9 months of age and 1 dose of measles, mumps and rubella (MMR) vaccine at 15 months of age, plus a 'mop-up' of MMR-unvaccinated schoolchildren at 6 years of age. Refinements involve a change to a two-dose strategy. Five scenarios based on different vaccination strategies are compared. The models are analysed using Microsoft Excel. First, making the assumption that measles vaccine-induced immunity will not wane, the predicted measles IgG seroprevalences in preschool children range from 81% (lower bound) to 94% (upper bound) and in schoolchildren reach 97-98% in all strategy scenarios. Results are dependent on the association of vaccine coverage between the first and second dose of vaccine. Second, if it is assumed that vaccine-induced antibody titres decay, the long-term measles seroprevalence will depend on the initial titres post vaccination, decay rates of antibody titres and cut-off of seropositivity. If MMR coverage at 12 months of age can reach > 90%, it would be worth changing the current policy to 2 doses at 12 months and 6 years of age to induce higher antibody titres. These epidemiological models could be applied wherever a similar stage of measles elimination has been reached.

  15. Circulating metabolomic profile can predict dyslipidemia in HIV patients undergoing antiretroviral therapy.

    PubMed

    Rodríguez-Gallego, Esther; Gómez, Josep; Domingo, Pere; Ferrando-Martínez, Sara; Peraire, Joaquim; Viladés, Consuelo; Veloso, Sergi; López-Dupla, Miguel; Beltrán-Debón, Raúl; Alba, Verónica; Vargas, Montserrat; Castellano, Alfonso J; Leal, Manuel; Pacheco, Yolanda María; Ruiz-Mateos, Ezequiel; Gutiérrez, Félix; Vidal, Francesc; Rull, Anna

    2018-06-01

    Dyslipidemia in HIV-infected patients is unique and pathophysiologically associated with host factors, HIV itself and the use of antiretroviral therapy (ART). The use of nuclear magnetic resonance spectroscopy (NMR) provides additional data to conventional lipid measurements concerning the number of lipoprotein subclasses and particle sizes. To investigate the ability of lipoprotein profile, we used a circulating metabolomic approach in a cohort of 103 ART-naive HIV-infected patients, who were initiating non-nucleoside analogue transcriptase inhibitor (NNRTI)-based ART, and we subsequently followed up these patients for 36 months. Univariate and multivariate analyses were performed to evaluate the predictive power of NMR spectroscopy. VLDL-metabolism (including VLDL lipid concentrations, sizes, and particle numbers), total triglycerides and lactate levels resulted in good classifiers of dyslipidemia (AUC 0.903). Total particles/HDL-P ratio was significantly higher in ART-associated dyslipidemia compared to ART-normolipidemia (p = 0.001). Large VLDL-Ps were positively associated with both LDL-triglycerides (ρ 0.682, p < 0.001) and lactate concentrations (ρ 0.416, p < 0.001), the last one a marker of mitochondrial low oxidative capacity. Our data suggest that circulating metabolites have better predictive values for HIV/ART-related dyslipidemia onset than do the biochemical markers associated with conventional lipid measurements. NMR identifies changes in VLDL-P, lactate and LDL-TG as potential clinical markers of baseline HIV-dyslipidemia predisposition. Differences in circulating metabolomics, especially differences in particle size, are indicators of important derangements of mitochondrial function that are linked to ART-related dyslipidemia. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

  16. Does Enjoying Friendship Help or Impede Academic Achievement? Academic and Social Intrinsic Value Profiles Predict Academic Achievement

    ERIC Educational Resources Information Center

    Seo, Eunjin; Lee, You-kyung

    2018-01-01

    We examine the intrinsic value students placed on schoolwork (i.e. academic intrinsic value) and social relationships (i.e. social intrinsic value). We then look at how these values predict middle and high school achievement. To do this, we came up with four profiles based on cluster analyses of 6,562 South Korean middle school students. The four…

  17. EvoCor: a platform for predicting functionally related genes using phylogenetic and expression profiles.

    PubMed

    Dittmar, W James; McIver, Lauren; Michalak, Pawel; Garner, Harold R; Valdez, Gregorio

    2014-07-01

    The wealth of publicly available gene expression and genomic data provides unique opportunities for computational inference to discover groups of genes that function to control specific cellular processes. Such genes are likely to have co-evolved and be expressed in the same tissues and cells. Unfortunately, the expertise and computational resources required to compare tens of genomes and gene expression data sets make this type of analysis difficult for the average end-user. Here, we describe the implementation of a web server that predicts genes involved in affecting specific cellular processes together with a gene of interest. We termed the server 'EvoCor', to denote that it detects functional relationships among genes through evolutionary analysis and gene expression correlation. This web server integrates profiles of sequence divergence derived by a Hidden Markov Model (HMM) and tissue-wide gene expression patterns to determine putative functional linkages between pairs of genes. This server is easy to use and freely available at http://pilot-hmm.vbi.vt.edu/. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

  18. Latent Profile Analysis and Conversion to Psychosis: Characterizing Subgroups to Enhance Risk Prediction.

    PubMed

    Healey, Kristin M; Penn, David L; Perkins, Diana; Woods, Scott W; Keefe, Richard S E; Addington, Jean

    2018-02-15

    Groups at clinical high risk (CHR) of developing psychosis are heterogeneous, composed of individuals with different clusters of symptoms. It is likely that there exist subgroups, each associated with different symptom constellations and probabilities of conversion. Present study used latent profile analysis (LPA) to ascertain subgroups in a combined sample of CHR (n = 171) and help-seeking controls (HSCs; n = 100; PREDICT study). Indicators in the LPA model included baseline Scale of Prodromal Symptoms (SOPS), Calgary Depression Scale for Schizophrenia (CDSS), and neurocognitive performance as measured by multiple instruments, including category instances (CAT). Subgroups were further characterized using covariates measuring demographic and clinical features. Three classes emerged: class 1 (mild, transition rate 5.6%), lowest SOPS and depression scores, intact neurocognitive performance; class 2 (paranoid-affective, transition rate 14.2%), highest suspiciousness, mild negative symptoms, moderate depression; and class 3 (negative-neurocognitive, transition rate 29.3%), highest negative symptoms, neurocognitive impairment, social cognitive impairment. Classes 2 and 3 evidenced poor social functioning. Results support a subgroup approach to research, assessment, and treatment of help-seeking individuals. Class 3 may be an early risk stage of developing schizophrenia.

  19. [Clinical heterogeneity of Alzheimer's disease. Different clinical profiles can predict the progression rate].

    PubMed

    Mangone, C A

    Alzheimer's disease (AD) is a degenerative dementia that may disclose different cognitive, behavioral, psychiatric and functional symptoms since onset. These distinct cognitive profiles support the conception of clinical heterogeneity and account for AD's highly variable rate of progression. In spite of strict diagnostic criteria NINCS ADRDA's and DSM IV the clinical certainty is only about 85%. Mayeux define 4 subtypes: a). Benign: mild cognitive and functional impairment without focal signs and late onset behavioral signs, slow progression; b). Myoclonic: usually of presenile onset with severe cognitive deterioration, mutism and early onset myoclonus; c). Extrapyramidal: early onset akineto rigid signs with severe cognitive, behavioral and psychiatric involvement; d). Typical: gradual and progressive cognitive, behavioral and functional impairment. The differentiation of these subtypes will allow us to define discrete patterns of progression, to define prognostic subgroups, and to homogenize them for clinical research and drug trials. We examined 1000 charts of probable AD patients from the Santojanni Center. We found 42% extrapyramidal, 35% typical, 15% benign and 8% myoclonic. The early onset of parkinsonism and myoclonus predict a rapidly evolving cognitive impairment and a more severe rate of progression with psychiatric disorders and dependency in activities of daily living. (DADL) Patients with low level of education, low cognitive performance at entry as well as those with rapid rate of cognitive deterioration had a faster rate of progression to DADL. Delusions, low level of education, extrapyramidal signs and motor hyperactivity but not hallucinations, and anosognosia were the best non cognitive predictors of DADL.

  20. The child behavior checklist dysregulation profile predicts adolescent DSM-5 pathological personality traits 4 years later.

    PubMed

    De Caluwé, Elien; Decuyper, Mieke; De Clercq, Barbara

    2013-07-01

    Emotional dysregulation in childhood has been associated with various forms of later psychopathology, although no studies have investigated the personality related adolescent outcomes associated with early emotional dysregulation. The present study uses a typological approach to examine how the child behavior checklist-dysregulation profile (CBCL-DP) predicts DSM-5 pathological personality traits (as measured with the personality inventory for the diagnostic and statistical manual of mental disorders 5 or PID-5 by Krueger et al. (Psychol Med 2012)) across a time span of 4 years in a sample of 243 children aged 8-14 years (57.2 % girls). The results showed that children assigned to the CBCL-DP class are at risk for elevated scores on a wide range of DSM-5 personality pathology features, including higher scores on hostility, risk taking, deceitfulness, callousness, grandiosity, irresponsibility, impulsivity and manipulativeness. These results are discussed in the context of identifying early manifestations of persistent regulation problems, because of their enduring impact on a child's personality development.

  1. Ability of prospective assessment of personality profiles to predict the practice specialty of medical students

    PubMed Central

    Maron, Bradley A.; Fein, Steven; Hillel, Alexander T.; El Baghdadi, Mariam M.; Rodenhauser, Paul

    2007-01-01

    Medical practice encompasses a diverse spectrum of specialties. Factors that impact selection of clinical disciplines by young physicians may have recently evolved associated with changes in medical school demographics. We assessed whether physicians gravitate to certain practice specialties due to preexisting personality traits. The Neuroticism-Extraversion-Openness Personality Inventory Revised Test was administered prospectively to 130 first-year students the week before they began medical school. Scores for five traits (neuroticism, extraversion, openness, agreeableness, conscientiousness) were compared with the selection among nine medical residencies at the conclusion of medical school. Personality scores for medical students selecting psychiatry residencies showed greater degrees of neuroticism (P < 0.01) and openness (P < 0.03). Students electing family practice also deviated from other specialties, showing a lower degree of neuroticism (P < 0.03). Unexpectedly, personality traits in prospective surgical residents did not differ from those of students choosing nonsurgical residencies. Personality profiles present before medical school appear to predict the selection of some residencies and clinical specialties but not others. PMID:17256038

  2. pH-dependent solubility and permeability profiles: A useful tool for prediction of oral bioavailability.

    PubMed

    Sieger, P; Cui, Y; Scheuerer, S

    2017-07-15

    pH-dependent solubility - permeability profiles offer a simple way to predict bioavailability after oral application, if bioavailability is only solubility and permeability driven. Combining both pH-dependent solubility and pH-dependent permeability in one diagram provides a pH-window (=ΔpH sol-perm ) from which the conditions for optimal oral bioavailability can be taken. The size of this window is directly proportional to the observed oral bioavailability. A set of 21 compounds, with known absolute human oral bioavailability, was used to establish this correlation. Compounds with ΔpH sol-perm <2 exhibit poor oral bioavailability (<25%). An increase of ΔpH sol-perm by one pH-unit increases oral bioavailability typically by approximately 25%. For compounds where ΔpH sol-perm ≥3 but still showing poor bioavailability, most probably other pharmacokinetic aspects (e.g. high clearance), are limiting exposure. Interestingly, the location of this pH-window seems to have a negligible influence on the observed oral bioavailability. In scenarios, where the bioavailability is impaired by certain factors, like for example proton pump inhibitor co-medication or food intake, the exact position of this pH-window might be beneficial for understanding the root cause. Copyright © 2017 Elsevier B.V. All rights reserved.

  3. Prediction of incidence and stability of alcohol use disorders by latent internalizing psychopathology risk profiles in adolescence and young adulthood.

    PubMed

    Behrendt, Silke; Bühringer, Gerhard; Höfler, Michael; Lieb, Roselind; Beesdo-Baum, Katja

    2017-10-01

    Comorbid internalizing mental disorders in alcohol use disorders (AUD) can be understood as putative independent risk factors for AUD or as expressions of underlying shared psychopathology vulnerabilities. However, it remains unclear whether: 1) specific latent internalizing psychopathology risk-profiles predict AUD-incidence and 2) specific latent internalizing comorbidity-profiles in AUD predict AUD-stability. To investigate baseline latent internalizing psychopathology risk profiles as predictors of subsequent AUD-incidence and -stability in adolescents and young adults. Data from the prospective-longitudinal EDSP study (baseline age 14-24 years) were used. The study-design included up to three follow-up assessments in up to ten years. DSM-IV mental disorders were assessed with the DIA-X/M-CIDI. To investigate risk-profiles and their associations with AUD-outcomes, latent class analysis with auxiliary outcome variables was applied. AUD-incidence: a 4-class model (N=1683) was identified (classes: normative-male [45.9%], normative-female [44.2%], internalizing [5.3%], nicotine dependence [4.5%]). Compared to the normative-female class, all other classes were associated with a higher risk of subsequent incident alcohol dependence (p<0.05). AUD-stability: a 3-class model (N=1940) was identified with only one class (11.6%) with high probabilities for baseline AUD. This class was further characterized by elevated substance use disorder (SUD) probabilities and predicted any subsequent AUD (OR 8.5, 95% CI 5.4-13.3). An internalizing vulnerability may constitute a pathway to AUD incidence in adolescence and young adulthood. In contrast, no indication for a role of internalizing comorbidity profiles in AUD-stability was found, which may indicate a limited importance of such profiles - in contrast to SUD-related profiles - in AUD stability. Copyright © 2017 Elsevier B.V. All rights reserved.

  4. Metataxonomic profiling and prediction of functional behaviour of wheat straw degrading microbial consortia

    PubMed Central

    2014-01-01

    Background Mixed microbial cultures, in which bacteria and fungi interact, have been proposed as an efficient way to deconstruct plant waste. The characterization of specific microbial consortia could be the starting point for novel biotechnological applications related to the efficient conversion of lignocellulose to cello-oligosaccharides, plastics and/or biofuels. Here, the diversity, composition and predicted functional profiles of novel bacterial-fungal consortia are reported, on the basis of replicated aerobic wheat straw enrichment cultures. Results In order to set up biodegradative microcosms, microbial communities were retrieved from a forest soil and introduced into a mineral salt medium containing 1% of (un)treated wheat straw. Following each incubation step, sequential transfers were carried out using 1 to 1,000 dilutions. The microbial source next to three sequential batch cultures (transfers 1, 3 and 10) were analyzed by bacterial 16S rRNA gene and fungal ITS1 pyrosequencing. Faith’s phylogenetic diversity values became progressively smaller from the inoculum to the sequential batch cultures. Moreover, increases in the relative abundances of Enterobacteriales, Pseudomonadales, Flavobacteriales and Sphingobacteriales were noted along the enrichment process. Operational taxonomic units affiliated with Acinetobacter johnsonii, Pseudomonas putida and Sphingobacterium faecium were abundant and the underlying strains were successfully isolated. Interestingly, Klebsiella variicola (OTU1062) was found to dominate in both consortia, whereas K. variicola-affiliated strains retrieved from untreated wheat straw consortia showed endoglucanase/xylanase activities. Among the fungal players with high biotechnological relevance, we recovered members of the genera Penicillium, Acremonium, Coniochaeta and Trichosporon. Remarkably, the presence of peroxidases, alpha-L-fucosidases, beta-xylosidases, beta-mannases and beta-glucosidases, involved in lignocellulose

  5. Predicting the spatial distribution of soil profile in Adapazari/Turkey by artificial neural networks using CPT data

    NASA Astrophysics Data System (ADS)

    Arel, Ersin

    2012-06-01

    The infamous soils of Adapazari, Turkey, that failed extensively during the 46-s long magnitude 7.4 earthquake in 1999 have since been the subject of a research program. Boreholes, piezocone soundings and voluminous laboratory testing have enabled researchers to apply sophisticated methods to determine the soil profiles in the city using the existing database. This paper describes the use of the artificial neural network (ANN) model to predict the complex soil profiles of Adapazari, based on cone penetration test (CPT) results. More than 3236 field CPT readings have been collected from 117 soundings spread over an area of 26 km2. An attempt has been made to develop the ANN model using multilayer perceptrons trained with a feed-forward back-propagation algorithm. The results show that the ANN model is fairly accurate in predicting complex soil profiles. Soil identification using CPT test results has principally been based on the Robertson charts. Applying neural network systems using the chart offers a powerful and rapid route to reliable prediction of the soil profiles.

  6. Quantifying and Predicting Three-Dimensional Heterogeneity in Transient Storage Using Roving Profiling

    NASA Astrophysics Data System (ADS)

    Kaplan, D. A.; Reaver, N.; Hensley, R. T.; Cohen, M. J.

    2017-12-01

    Hydraulic transport is an important component of nutrient spiraling in streams. Quantifying conservative solute transport is a prerequisite for understanding the cycling and fate of reactive solutes, such as nutrients. Numerous studies have modeled solute transport within streams using the one-dimensional advection, dispersion and storage (ADS) equation calibrated to experimental data from tracer experiments. However, there are limitations to the information about in-stream transient storage that can be derived from calibrated ADS model parameters. Transient storage (TS) in the ADS model is most often modeled as a single process, and calibrated model parameters are "lumped" values that are the best-fit representation of multiple real-world TS processes. In this study, we developed a roving profiling method to assess and predict spatial heterogeneity of in-stream TS. We performed five tracer experiments on three spring-fed rivers in Florida (USA) using Rhodamine WT. During each tracer release, stationary fluorometers were deployed to measure breakthrough curves for multiple reaches within the river. Teams of roving samplers moved along the rivers measuring tracer concentrations at various locations and depths within the reaches. A Bayesian statistical method was used to calibrate the ADS model to the stationary breakthrough curves, resulting in probability distributions for both the advective and TS zone as a function of river distance and time. Rover samples were then assigned a probability of being from either the advective or TS zone by comparing measured concentrations to the probability distributions of concentrations in the ADS advective and TS zones. A regression model was used to predict the probability of any in-stream position being located within the advective versus TS zone based on spatiotemporal predictors (time, river position, depth, and distance from bank) and eco-geomorphological feature (eddies, woody debris, benthic depressions, and aquatic

  7. Predicting the Effect of Mutations on Protein-Protein Binding Interactions through Structure-Based Interface Profiles

    PubMed Central

    Brender, Jeffrey R.; Zhang, Yang

    2015-01-01

    The formation of protein-protein complexes is essential for proteins to perform their physiological functions in the cell. Mutations that prevent the proper formation of the correct complexes can have serious consequences for the associated cellular processes. Since experimental determination of protein-protein binding affinity remains difficult when performed on a large scale, computational methods for predicting the consequences of mutations on binding affinity are highly desirable. We show that a scoring function based on interface structure profiles collected from analogous protein-protein interactions in the PDB is a powerful predictor of protein binding affinity changes upon mutation. As a standalone feature, the differences between the interface profile score of the mutant and wild-type proteins has an accuracy equivalent to the best all-atom potentials, despite being two orders of magnitude faster once the profile has been constructed. Due to its unique sensitivity in collecting the evolutionary profiles of analogous binding interactions and the high speed of calculation, the interface profile score has additional advantages as a complementary feature to combine with physics-based potentials for improving the accuracy of composite scoring approaches. By incorporating the sequence-derived and residue-level coarse-grained potentials with the interface structure profile score, a composite model was constructed through the random forest training, which generates a Pearson correlation coefficient >0.8 between the predicted and observed binding free-energy changes upon mutation. This accuracy is comparable to, or outperforms in most cases, the current best methods, but does not require high-resolution full-atomic models of the mutant structures. The binding interface profiling approach should find useful application in human-disease mutation recognition and protein interface design studies. PMID:26506533

  8. Predicting nicotine dependence profiles among adolescent smokers: the roles of personal and social-environmental factors in a longitudinal framework

    PubMed Central

    2012-01-01

    Background Although several studies have reported that symptoms of nicotine dependence can occur after limited exposure to smoking, the majority of research on nicotine dependence has focused on adult smokers. Insufficient knowledge exists regarding the epidemiology and aetiology of nicotine dependence among adolescent smokers. The objective of the present study is to identify the effects of theoretically driven social and individual predictors of nicotine dependence symptom profiles in a population-based sample of adolescent smokers. Method A longitudinal study among 6,783 adolescents (12 to 14 years old at baseline) was conducted. In the first and second year of secondary education, personality traits and exposure to smoking in the social environment were assessed. Two and a half years later, adolescents' smoking status and nicotine dependence symptom profiles were assessed. A total of 796 adolescents were identified as smokers and included in the analyses. Results At follow-up, four distinct dependence symptom profiles were identified: low cravings only, high cravings and withdrawal, high cravings and behavioural dependence, and overall highly dependent. Personality traits of neuroticism and extraversion did not independently predict nicotine dependence profiles, whereas exposure to smoking in the social environment posed a risk for the initial development of nicotine dependence symptoms. However, in combination with environmental exposure to smoking, extraversion and neuroticism increased the risk of developing more severe dependence symptom profiles. Conclusions Nicotine dependence profiles are predicted by interactions between personal and environmental factors. These insights offer important directions for tailoring interventions to prevent the onset and escalation of nicotine dependence. Opportunities for intervention programs that target individuals with a high risk of developing more severe dependence symptom profiles are discussed. PMID:22424115

  9. Modeling for influenza vaccines and adjuvants profile for safety prediction system using gene expression profiling and statistical tools

    PubMed Central

    Sasaki, Eita; Momose, Haruka; Hiradate, Yuki; Furuhata, Keiko; Takai, Mamiko; Asanuma, Hideki; Ishii, Ken J.

    2018-01-01

    Historically, vaccine safety assessments have been conducted by animal testing (e.g., quality control tests and adjuvant development). However, classical evaluation methods do not provide sufficient information to make treatment decisions. We previously identified biomarker genes as novel safety markers. Here, we developed a practical safety assessment system used to evaluate the intramuscular, intraperitoneal, and nasal inoculation routes to provide robust and comprehensive safety data. Influenza vaccines were used as model vaccines. A toxicity reference vaccine (RE) and poly I:C-adjuvanted hemagglutinin split vaccine were used as toxicity controls, while a non-adjuvanted hemagglutinin split vaccine and AddaVax (squalene-based oil-in-water nano-emulsion with a formulation similar to MF59)-adjuvanted hemagglutinin split vaccine were used as safety controls. Body weight changes, number of white blood cells, and lung biomarker gene expression profiles were determined in mice. In addition, vaccines were inoculated into mice by three different administration routes. Logistic regression analyses were carried out to determine the expression changes of each biomarker. The results showed that the regression equations clearly classified each vaccine according to its toxic potential and inoculation amount by biomarker expression levels. Interestingly, lung biomarker expression was nearly equivalent for the various inoculation routes. The results of the present safety evaluation were confirmed by the approximation rate for the toxicity control. This method may contribute to toxicity evaluation such as quality control tests and adjuvant development. PMID:29408882

  10. Prediction of subcellular localization of eukaryotic proteins using position-specific profiles and neural network with weighted inputs.

    PubMed

    Zou, Lingyun; Wang, Zhengzhi; Huang, Jiaomin

    2007-12-01

    Subcellular location is one of the key biological characteristics of proteins. Position-specific profiles (PSP) have been introduced as important characteristics of proteins in this article. In this study, to obtain position-specific profiles, the Position Specific Iterative-Basic Local Alignment Search Tool (PSI-BLAST) has been used to search for protein sequences in a database. Position-specific scoring matrices are extracted from the profiles as one class of characteristics. Four-part amino acid compositions and 1st-7th order dipeptide compositions have also been calculated as the other two classes of characteristics. Therefore, twelve characteristic vectors are extracted from each of the protein sequences. Next, the characteristic vectors are weighed by a simple weighing function and inputted into a BP neural network predictor named PSP-Weighted Neural Network (PSP-WNN). The Levenberg-Marquardt algorithm is employed to adjust the weight matrices and thresholds during the network training instead of the error back propagation algorithm. With a jackknife test on the RH2427 dataset, PSP-WNN has achieved a higher overall prediction accuracy of 88.4% rather than the prediction results by the general BP neural network, Markov model, and fuzzy k-nearest neighbors algorithm on this dataset. In addition, the prediction performance of PSP-WNN has been evaluated with a five-fold cross validation test on the PK7579 dataset and the prediction results have been consistently better than those of the previous method on the basis of several support vector machines, using compositions of both amino acids and amino acid pairs. These results indicate that PSP-WNN is a powerful tool for subcellular localization prediction. At the end of the article, influences on prediction accuracy using different weighting proportions among three characteristic vector categories have been discussed. An appropriate proportion is considered by increasing the prediction accuracy.

  11. Prediction of Process-Induced Distortions in L-Shaped Composite Profiles Using Path-Dependent Constitutive Law

    NASA Astrophysics Data System (ADS)

    Ding, Anxin; Li, Shuxin; Wang, Jihui; Ni, Aiqing; Sun, Liangliang; Chang, Lei

    2016-10-01

    In this paper, the corner spring-in angles of AS4/8552 L-shaped composite profiles with different thicknesses are predicted using path-dependent constitutive law with the consideration of material properties variation due to phase change during curing. The prediction accuracy mainly depends on the properties in the rubbery and glassy states obtained by homogenization method rather than experimental measurements. Both analytical and finite element (FE) homogenization methods are applied to predict the overall properties of AS4/8552 composite. The effect of fiber volume fraction on the properties is investigated for both rubbery and glassy states using both methods. And the predicted results are compared with experimental measurements for the glassy state. Good agreement is achieved between the predicted results and available experimental data, showing the reliability of the homogenization method. Furthermore, the corner spring-in angles of L-shaped composite profiles are measured experimentally and the reliability of path-dependent constitutive law is validated as well as the properties prediction by FE homogenization method.

  12. Prediction of protein long-range contacts using an ensemble of genetic algorithm classifiers with sequence profile centers.

    PubMed

    Chen, Peng; Li, Jinyan

    2010-05-17

    Prediction of long-range inter-residue contacts is an important topic in bioinformatics research. It is helpful for determining protein structures, understanding protein foldings, and therefore advancing the annotation of protein functions. In this paper, we propose a novel ensemble of genetic algorithm classifiers (GaCs) to address the long-range contact prediction problem. Our method is based on the key idea called sequence profile centers (SPCs). Each SPC is the average sequence profiles of residue pairs belonging to the same contact class or non-contact class. GaCs train on multiple but different pairs of long-range contact data (positive data) and long-range non-contact data (negative data). The negative data sets, having roughly the same sizes as the positive ones, are constructed by random sampling over the original imbalanced negative data. As a result, about 21.5% long-range contacts are correctly predicted. We also found that the ensemble of GaCs indeed makes an accuracy improvement by around 5.6% over the single GaC. Classifiers with the use of sequence profile centers may advance the long-range contact prediction. In line with this approach, key structural features in proteins would be determined with high efficiency and accuracy.

  13. Kozeny-Carman permeability relationship with disintegration process predicted from early dissolution profiles of immediate release tablets.

    PubMed

    Kumari, Parveen; Rathi, Pooja; Kumar, Virender; Lal, Jatin; Kaur, Harmeet; Singh, Jasbir

    2017-07-01

    This study was oriented toward the disintegration profiling of the diclofenac sodium (DS) immediate-release (IR) tablets and development of its relationship with medium permeability k perm based on Kozeny-Carman equation. Batches (L1-L9) of DS IR tablets with different porosities and specific surface area were prepared at different compression forces and evaluated for porosity, in vitro dissolution and particle-size analysis of the disintegrated mass. The k perm was calculated from porosities and specific surface area, and disintegration profiles were predicted from the dissolution profiles of IR tablets by stripping/residual method. The disintegration profiles were subjected to exponential regression to find out the respective disintegration equations and rate constants k d . Batches L1 and L2 showed the fastest disintegration rates as evident from their bi-exponential equations while the rest of the batches L3-L9 exhibited the first order or mono-exponential disintegration kinetics. The 95% confidence interval (CI 95% ) revealed significant differences between k d values of different batches except L4 and L6. Similar results were also spotted for dissolution profiles of IR tablets by similarity (f 2 ) test. The final relationship between k d and k perm was found to be hyperbolic, signifying the initial effect of k perm on the disintegration rate. The results showed that disintegration profiling is possible because a relationship exists between k d and k perm . The later being relatable with porosity and specific surface area can be determined by nondestructive tests.

  14. CYTOKINE PROFILES DO NOT PREDICT ANTIBODY RESPONSES AND RESPIRATORY HYPERRESPONSIVENESS FOLLOWING DERMAL EXPOSURE TO ISOCYANATES

    EPA Science Inventory

    Rationale: Cytokine profiling of local lymph node responses following dermal exposure has been proposed as a test to identify chemicals that pose a risk of occupational asthma. The present study tested the hypothesis that relative differences in cytokine profiles for dini...

  15. Urinary Metabolite Profiles May be Predictive of Cognitive Performance Under Conditions of Acute Sleep Deprivation

    DTIC Science & Technology

    2016-01-01

    temporal changes in urinary metabolite profiles mirrored cognitive performance during continuous wakefulness. Additionally , subjects identified by...profiles mirrored cognitive performance during continuous wakefulness. Additionally , subjects identified by cognitive assessments as having a high...field studies and would have little useful application in occupational or military operational environments. Addition - ally, their usefulness is

  16. Using Early Literacy Profiles of Hispanic English Language Learners to Predict Later Reading Achievement

    ERIC Educational Resources Information Center

    Huang, Francis; Ford, Karen; Invernizzi, Marcia

    2011-01-01

    Following a cohort of students from fall of kindergarten to spring of first grade, the authors investigated whether the general cluster profiles identified in Burrow et al.'s (2010) study remained consistent over time. If cluster profiles in the fall of kindergarten held, their goal was to investigate the differences between clusters in terms of…

  17. Fuzzy Neural Network Applied to Gene Expression Profiling for Predicting the Prognosis of Diffuse Large B‐cell Lymphoma

    PubMed Central

    Ando, Tatsuya; Suguro, Miyuki; Hanai, Taizo; Kobayashi, Takeshi; Seto, Masao

    2002-01-01

    Diffuse large B‐cell lymphoma (DLBCL) is the largest category of aggressive lymphomas. Less than 50% of patients can be cured by combination chemotherapy. Microarray technologies have recently shown that the response to chemotherapy reflects the molecular heterogeneity in DLBCL. On the basis of published microarray data, we attempted to develop a long‐overdue method for the precise and simple prediction of survival of DLBCL patients. We developed a fuzzy neural network (FNN) model to analyze gene expression profiling data for DLBCL. From data on 5857 genes, this model identified four genes (CD10, AA807551, AA805611 and IRF‐4) that could be used to predict prognosis with 93% accuracy. FNNs are powerful tools for extracting significant biological markers affecting prognosis, and are applicable to various kinds of expression profiling data for any malignancy. PMID:12460461

  18. Monoamine transporter and receptor interaction profiles in vitro predict reported human doses of novel psychoactive stimulants and psychedelics.

    PubMed

    Luethi, Dino; Liechti, Matthias E

    2018-05-29

    Pharmacological profiles of new psychoactive substances (NPSs) can be established rapidly in vitro and provide information on potential psychoactive effects in humans. The present study investigated whether specific in vitro monoamine transporter and receptor interactions can predict effective psychoactive doses in humans. We correlated previously assessed in vitro data of stimulants and psychedelics with human doses that are reported on the Internet and in books. For stimulants, dopamine and norepinephrine transporter inhibition potency was positively correlated with human doses, whereas serotonin transporter inhibition potency was inversely correlated with human doses. Serotonin 5-hydroxytryptamine-2A (5-HT2A) and 5-HT2C receptor affinity was significantly correlated with psychedelic doses, but 5-HT1A receptor affinity and 5-HT2A and 5-HT2B receptor activation potency were not. The rapid assessment of in vitro pharmacological profiles of NPSs can help to predict psychoactive doses and effects in humans and facilitate the appropriate scheduling of NPSs.

  19. Injury Profile SIMulator, a Qualitative Aggregative Modelling Framework to Predict Crop Injury Profile as a Function of Cropping Practices, and the Abiotic and Biotic Environment. I. Conceptual Bases

    PubMed Central

    Aubertot, Jean-Noël; Robin, Marie-Hélène

    2013-01-01

    The limitation of damage caused by pests (plant pathogens, weeds, and animal pests) in any agricultural crop requires integrated management strategies. Although significant efforts have been made to i) develop, and to a lesser extent ii) combine genetic, biological, cultural, physical and chemical control methods in Integrated Pest Management (IPM) strategies (vertical integration), there is a need for tools to help manage Injury Profiles (horizontal integration). Farmers design cropping systems according to their goals, knowledge, cognition and perception of socio-economic and technological drivers as well as their physical, biological, and chemical environment. In return, a given cropping system, in a given production situation will exhibit a unique injury profile, defined as a dynamic vector of the main injuries affecting the crop. This simple description of agroecosystems has been used to develop IPSIM (Injury Profile SIMulator), a modelling framework to predict injury profiles as a function of cropping practices, abiotic and biotic environment. Due to the tremendous complexity of agroecosystems, a simple holistic aggregative approach was chosen instead of attempting to couple detailed models. This paper describes the conceptual bases of IPSIM, an aggregative hierarchical framework and a method to help specify IPSIM for a given crop. A companion paper presents a proof of concept of the proposed approach for a single disease of a major crop (eyespot on wheat). In the future, IPSIM could be used as a tool to help design ex-ante IPM strategies at the field scale if coupled with a damage sub-model, and a multicriteria sub-model that assesses the social, environmental, and economic performances of simulated agroecosystems. In addition, IPSIM could also be used to help make diagnoses on commercial fields. It is important to point out that the presented concepts are not crop- or pest-specific and that IPSIM can be used on any crop. PMID:24019908

  20. Injury Profile SIMulator, a qualitative aggregative modelling framework to predict crop injury profile as a function of cropping practices, and the abiotic and biotic environment. I. Conceptual bases.

    PubMed

    Aubertot, Jean-Noël; Robin, Marie-Hélène

    2013-01-01

    The limitation of damage caused by pests (plant pathogens, weeds, and animal pests) in any agricultural crop requires integrated management strategies. Although significant efforts have been made to i) develop, and to a lesser extent ii) combine genetic, biological, cultural, physical and chemical control methods in Integrated Pest Management (IPM) strategies (vertical integration), there is a need for tools to help manage Injury Profiles (horizontal integration). Farmers design cropping systems according to their goals, knowledge, cognition and perception of socio-economic and technological drivers as well as their physical, biological, and chemical environment. In return, a given cropping system, in a given production situation will exhibit a unique injury profile, defined as a dynamic vector of the main injuries affecting the crop. This simple description of agroecosystems has been used to develop IPSIM (Injury Profile SIMulator), a modelling framework to predict injury profiles as a function of cropping practices, abiotic and biotic environment. Due to the tremendous complexity of agroecosystems, a simple holistic aggregative approach was chosen instead of attempting to couple detailed models. This paper describes the conceptual bases of IPSIM, an aggregative hierarchical framework and a method to help specify IPSIM for a given crop. A companion paper presents a proof of concept of the proposed approach for a single disease of a major crop (eyespot on wheat). In the future, IPSIM could be used as a tool to help design ex-ante IPM strategies at the field scale if coupled with a damage sub-model, and a multicriteria sub-model that assesses the social, environmental, and economic performances of simulated agroecosystems. In addition, IPSIM could also be used to help make diagnoses on commercial fields. It is important to point out that the presented concepts are not crop- or pest-specific and that IPSIM can be used on any crop.

  1. Through-Thickness Residual Stress Profiles in Austenitic Stainless Steel Welds: A Combined Experimental and Prediction Study

    NASA Astrophysics Data System (ADS)

    Mathew, J.; Moat, R. J.; Paddea, S.; Francis, J. A.; Fitzpatrick, M. E.; Bouchard, P. J.

    2017-12-01

    Economic and safe management of nuclear plant components relies on accurate prediction of welding-induced residual stresses. In this study, the distribution of residual stress through the thickness of austenitic stainless steel welds has been measured using neutron diffraction and the contour method. The measured data are used to validate residual stress profiles predicted by an artificial neural network approach (ANN) as a function of welding heat input and geometry. Maximum tensile stresses with magnitude close to the yield strength of the material were observed near the weld cap in both axial and hoop direction of the welds. Significant scatter of more than 200 MPa was found within the residual stress measurements at the weld center line and are associated with the geometry and welding conditions of individual weld passes. The ANN prediction is developed in an attempt to effectively quantify this phenomenon of `innate scatter' and to learn the non-linear patterns in the weld residual stress profiles. Furthermore, the efficacy of the ANN method for defining through-thickness residual stress profiles in welds for application in structural integrity assessments is evaluated.

  2. Hierarchical kernel mixture models for the prediction of AIDS disease progression using HIV structural gp120 profiles

    PubMed Central

    2010-01-01

    Changes to the glycosylation profile on HIV gp120 can influence viral pathogenesis and alter AIDS disease progression. The characterization of glycosylation differences at the sequence level is inadequate as the placement of carbohydrates is structurally complex. However, no structural framework is available to date for the study of HIV disease progression. In this study, we propose a novel machine-learning based framework for the prediction of AIDS disease progression in three stages (RP, SP, and LTNP) using the HIV structural gp120 profile. This new intelligent framework proves to be accurate and provides an important benchmark for predicting AIDS disease progression computationally. The model is trained using a novel HIV gp120 glycosylation structural profile to detect possible stages of AIDS disease progression for the target sequences of HIV+ individuals. The performance of the proposed model was compared to seven existing different machine-learning models on newly proposed gp120-Benchmark_1 dataset in terms of error-rate (MSE), accuracy (CCI), stability (STD), and complexity (TBM). The novel framework showed better predictive performance with 67.82% CCI, 30.21 MSE, 0.8 STD, and 2.62 TBM on the three stages of AIDS disease progression of 50 HIV+ individuals. This framework is an invaluable bioinformatics tool that will be useful to the clinical assessment of viral pathogenesis. PMID:21143806

  3. Latent profiles of non-residential father engagement six years after divorce predict long term offspring outcomes

    PubMed Central

    Modecki, Kathryn Lynn; Hagan, Melissa; Sandler, Irwin; Wolchik, Sharlene

    2014-01-01

    This study examined profiles of non-residential father engagement (i.e., support to the adolescent, contact frequency, remarriage, relocation, and interparental conflict) with their adolescent children (N = 156) six to eight years following divorce and the prospective relation between these profiles and the psychosocial functioning of their offspring, nine years later. Parental divorce occurred during late childhood to early adolescence; indicators of non-residential father engagement were assessed during adolescence, and mental health problems and academic achievement of offspring were assessed nine years later in young adulthood. Three profiles of father engagement were identified in our sample of mainly White, non-Hispanic divorced fathers: Moderate Involvement/Low Conflict, Low Involvement/Moderate Conflict, and High Involvement/High Conflict. Profiles differentially predicted offspring outcomes nine years later when they were young adults, controlling for quality of the mother-adolescent relationship, mother’s remarriage, mother’s income, and gender, age and offspring mental health problems in adolescence. Offspring of fathers characterized as Moderate Involvement/Low Conflict had the highest academic achievement and the lowest number of externalizing problems nine years later compared to offspring whose fathers had profiles indicating either the highest or lowest levels of involvement but higher levels of conflict. Results indicate that greater paternal psychosocial support and more frequent father-adolescent contact do not outweigh the negative impact of interparental conflict on youth outcomes in the long-term. Implications of findings for policy and intervention are discussed. PMID:24484456

  4. Integrating Milk Metabolite Profile Information for the Prediction of Traditional Milk Traits Based on SNP Information for Holstein Cows

    PubMed Central

    Melzer, Nina; Wittenburg, Dörte; Repsilber, Dirk

    2013-01-01

    In this study the benefit of metabolome level analysis for the prediction of genetic value of three traditional milk traits was investigated. Our proposed approach consists of three steps: First, milk metabolite profiles are used to predict three traditional milk traits of 1,305 Holstein cows. Two regression methods, both enabling variable selection, are applied to identify important milk metabolites in this step. Second, the prediction of these important milk metabolite from single nucleotide polymorphisms (SNPs) enables the detection of SNPs with significant genetic effects. Finally, these SNPs are used to predict milk traits. The observed precision of predicted genetic values was compared to the results observed for the classical genotype-phenotype prediction using all SNPs or a reduced SNP subset (reduced classical approach). To enable a comparison between SNP subsets, a special invariable evaluation design was implemented. SNPs close to or within known quantitative trait loci (QTL) were determined. This enabled us to determine if detected important SNP subsets were enriched in these regions. The results show that our approach can lead to genetic value prediction, but requires less than 1% of the total amount of (40,317) SNPs., significantly more important SNPs in known QTL regions were detected using our approach compared to the reduced classical approach. Concluding, our approach allows a deeper insight into the associations between the different levels of the genotype-phenotype map (genotype-metabolome, metabolome-phenotype, genotype-phenotype). PMID:23990900

  5. Applying geographic profiling used in the field of criminology for predicting the nest locations of bumble bees.

    PubMed

    Suzuki-Ohno, Yukari; Inoue, Maki N; Ohno, Kazunori

    2010-07-21

    We tested whether geographic profiling (GP) can predict multiple nest locations of bumble bees. GP was originally developed in the field of criminology for predicting the area where an offender most likely resides on the basis of the actual crime sites and the predefined probability of crime interaction. The predefined probability of crime interaction in the GP model depends on the distance of a site from an offender's residence. We applied GP for predicting nest locations, assuming that foraging and nest sites were the crime sites and the offenders' residences, respectively. We identified the foraging and nest sites of the invasive species Bombus terrestris in 2004, 2005, and 2006. We fitted GP model coefficients to the field data of the foraging and nest sites, and used GP with the fitting coefficients. GP succeeded in predicting about 10-30% of actual nests. Sensitivity analysis showed that the predictability of the GP model mainly depended on the coefficient value of buffer zone, the distance at the mode of the foraging probability. GP will be able to predict the nest locations of bumble bees in other area by using the fitting coefficient values measured in this study. It will be possible to further improve the predictability of the GP model by considering food site preference and nest density. (c) 2010 Elsevier Ltd. All rights reserved.

  6. Prediction of Microbial Infection of Cultured Cells Using DNA Microarray Gene-Expression Profiles of Host Responses

    PubMed Central

    Park, Yu Rang; Chung, Tae Su; Lee, Young Joo; Song, Yeong Wook; Lee, Eun Young; Sohn, Yeo Won; Song, Sukgil; Park, Woong Yang

    2012-01-01

    Infection by microorganisms may cause fatally erroneous interpretations in the biologic researches based on cell culture. The contamination by microorganism in the cell culture is quite frequent (5% to 35%). However, current approaches to identify the presence of contamination have many limitations such as high cost of time and labor, and difficulty in interpreting the result. In this paper, we propose a model to predict cell infection, using a microarray technique which gives an overview of the whole genome profile. By analysis of 62 microarray expression profiles under various experimental conditions altering cell type, source of infection and collection time, we discovered 5 marker genes, NM_005298, NM_016408, NM_014588, S76389, and NM_001853. In addition, we discovered two of these genes, S76389, and NM_001853, are involved in a Mycolplasma-specific infection process. We also suggest models to predict the source of infection, cell type or time after infection. We implemented a web based prediction tool in microarray data, named Prediction of Microbial Infection (http://www.snubi.org/software/PMI). PMID:23091307

  7. Proinflammatory Cytokines as Regulators of Vaginal Microbiota.

    PubMed

    Kremleva, E A; Sgibnev, A V

    2016-11-01

    It was shown that IL-1β, IL-8, and IL-6 in concentrations similar to those in the vagina of healthy women stimulated the growth of normal microflora (Lactobacillus spp.) and suppressed the growth and biofilm production by S. aureus and E. coli. On the contrary, these cytokines in higher concentrations typical of vaginal dysbiosis suppressed normal microflora and stimulated the growth of opportunistic microorganisms. TGF-β1 in both doses produced a stimulating effects on study vaginal microsymbionts. It is hypothesized that pro-inflammatory cytokines serve as the molecules of interspecies communication coordinating the interactions of all components of the vaginal symbiotic system.

  8. Mycobacterium tuberculosis Hip1 Dampens Macrophage Proinflammatory Responses by Limiting Toll-Like Receptor 2 Activation▿

    PubMed Central

    Madan-Lala, Ranjna; Peixoto, Katia Vitorello; Re, Fabio; Rengarajan, Jyothi

    2011-01-01

    Mycobacterium tuberculosis is a highly successful human pathogen that evades host innate immunity by interfering with macrophage functions. In addition to avoiding macrophage microbicidal activities, M. tuberculosis triggers secretion of proinflammatory cytokines and chemokines in macrophages. The levels of proinflammatory cytokines induced by clinical M. tuberculosis isolates are thought to play an important role in determining tuberculosis disease progression and severity, but the mechanisms by which M. tuberculosis modulates the magnitude of inflammatory responses remain unclear. Here we show that M. tuberculosis restricts robust macrophage activation and dampens proinflammatory responses through the cell envelope-associated serine hydrolase Hip1 (hydrolase important for pathogenesis 1). By transcriptionally profiling macrophages infected with either wild-type or hip1 mutant bacteria, we found that the hip1 mutant induced earlier and significantly higher levels of several proinflammatory cytokines and chemokines. We show that increased activation of Toll-like receptor 2 (TLR2)- and MyD88-dependent signaling pathways mediates the enhanced cytokine secretion induced by the hip1 mutant. Thus, Hip1 restricts the onset and magnitude of proinflammatory cytokines by limiting TLR2-dependent activation. We also show that Hip1 dampens TLR2-independent activation of the inflammasome and limits secretion of interleukin-18 (IL-18). Dampening of TLR2 signaling does not require viable M. tuberculosis or phagocytosis but does require Hip1 catalytic activity. We propose that M. tuberculosis restricts proinflammatory responses by masking cell surface interactions between TLR2 agonists on M. tuberculosis and TLR2 on macrophages. This strategy may allow M. tuberculosis to evade early detection by host immunity, delay the onset of adaptive immune responses, and accelerate disease progression. PMID:21947769

  9. Mycobacterium tuberculosis Hip1 dampens macrophage proinflammatory responses by limiting toll-like receptor 2 activation.

    PubMed

    Madan-Lala, Ranjna; Peixoto, Katia Vitorello; Re, Fabio; Rengarajan, Jyothi

    2011-12-01

    Mycobacterium tuberculosis is a highly successful human pathogen that evades host innate immunity by interfering with macrophage functions. In addition to avoiding macrophage microbicidal activities, M. tuberculosis triggers secretion of proinflammatory cytokines and chemokines in macrophages. The levels of proinflammatory cytokines induced by clinical M. tuberculosis isolates are thought to play an important role in determining tuberculosis disease progression and severity, but the mechanisms by which M. tuberculosis modulates the magnitude of inflammatory responses remain unclear. Here we show that M. tuberculosis restricts robust macrophage activation and dampens proinflammatory responses through the cell envelope-associated serine hydrolase Hip1 (hydrolase important for pathogenesis 1). By transcriptionally profiling macrophages infected with either wild-type or hip1 mutant bacteria, we found that the hip1 mutant induced earlier and significantly higher levels of several proinflammatory cytokines and chemokines. We show that increased activation of Toll-like receptor 2 (TLR2)- and MyD88-dependent signaling pathways mediates the enhanced cytokine secretion induced by the hip1 mutant. Thus, Hip1 restricts the onset and magnitude of proinflammatory cytokines by limiting TLR2-dependent activation. We also show that Hip1 dampens TLR2-independent activation of the inflammasome and limits secretion of interleukin-18 (IL-18). Dampening of TLR2 signaling does not require viable M. tuberculosis or phagocytosis but does require Hip1 catalytic activity. We propose that M. tuberculosis restricts proinflammatory responses by masking cell surface interactions between TLR2 agonists on M. tuberculosis and TLR2 on macrophages. This strategy may allow M. tuberculosis to evade early detection by host immunity, delay the onset of adaptive immune responses, and accelerate disease progression.

  10. Vertical temperature profile and mesospheric winds retrieval on Mars from CO ;millimeter observations. Comparison with general circulation model predictions

    NASA Astrophysics Data System (ADS)

    Cavalié, T.; Billebaud, F.; Encrenaz, T.; Dobrijevic, M.; Brillet, J.; Forget, F.; Lellouch, E.

    2008-10-01

    Aims: We have recorded high spectral resolution spectra and derived precise atmospheric temperature profiles and wind velocities in the atmosphere of Mars. We have compared observations of the planetary mean thermal profile and mesospheric wind velocities on the disk, obtained with our millimetric observations of CO rotational lines, to predictions from the Laboratoire de Météorologie Dynamique (LMD) Mars General Circulation Model, as provided through the Mars Climate Database (MCD) numerical tool. Methods: We observed the atmosphere of Mars at CO(1-0) and CO(2-1) wavelengths with the IRAM 30-m antenna in June 2001 and November 2005. We retrieved the mean thermal profile of the planet from high and low spectral resolution data with an inversion method detailed here. High spectral resolution spectra were used to derive mesospheric wind velocities on the planetary disk. We also report here the use of 13CO(2-1) line core shifts to measure wind velocities at 40 km. Results: Neither the Mars Year 24 (MY24) nor the Dust Storm scenario from the Mars Climate Database (MCD) provides satisfactory fits to the 2001 and 2005 data when retrieving the thermal profiles. The Warm scenario only provides good fits for altitudes lower than 30 km. The atmosphere is warmer than predicted up to 60 km and then becomes colder. Dust loading could be the reason for this mismatch. The MCD MY24 scenario predicts a thermal inversion layer between 40 and 60 km, which is not retrieved from the high spectral resolution data. Our results are generally in agreement with other observations from 10 to 40 km in altitude, but our results obtained from the high spectral resolution spectra differ in the 40-70 km layer, where the instruments are the most sensitive. The wind velocities we retrieve from our 12CO observations confirm MCD predictions for 2001 and 2005. Velocities obtained from 13CO observations are consistent with MCD predictions in 2001, but are lower than predicted in 2005.

  11. Prediction of tolerance in children with IgE mediated cow's milk allergy by microarray profiling and chemometric approach.

    PubMed

    Wulfert, F; Sanyasi, G; Tongen, L; Watanabe, L A; Wang, X; Renault, N K; Falcone, F H; Jacob, C M A; Alcocer, M J C

    2012-08-31

    The sera of a retrospective cohort (n=41) composed of children with well characterized cow's milk allergy collected from multiple visits were analyzed using a protein microarray system measuring four classes of immunoglobulins. The frequency of the visits, age and gender distribution reflected real situation faced by the clinicians at a pediatric reference center for food allergy in São Paulo, Brazil. The profiling array results have shown that total IgG and IgA share similar specificity whilst IgM and in particular IgE are distantly related. The correlation of specificity of IgE and IgA is variable amongst the patients and this relationship cannot be used to predict atopy or the onset of tolerance to milk. The array profiling technique has corroborated the clinical selection criteria for this cohort albeit it clearly suggested that 4 out of the 41 patients might have allergies other than milk origin. There was also a good correlation between the array data and ImmunoCAP results, casein in particular. By using qualitative and quantitative multivariate analysis routines it was possible to produce validated statistical models to predict with reasonable accuracy the onset of tolerance to milk proteins. If expanded to larger study groups, the array profiling in combination with the multivariate techniques show potential to improve the prognostic of milk allergic patients. Copyright © 2012 Elsevier B.V. All rights reserved.

  12. Development of Integrated Magnetic and Kinetic Control-oriented Transport Model for q-profile Response Prediction in EAST Discharges

    NASA Astrophysics Data System (ADS)

    Wang, Hexiang; Schuster, Eugenio; Rafiq, Tariq; Kritz, Arnold; Ding, Siye

    2016-10-01

    Extensive research has been conducted to find high-performance operating scenarios characterized by high fusion gain, good confinement, plasma stability and possible steady-state operation. A key plasma property that is related to both the stability and performance of these advanced plasma scenarios is the safety factor profile. A key component of the EAST research program is the exploration of non-inductively driven steady-state plasmas with the recently upgraded heating and current drive capabilities that include lower hybrid current drive and neutral beam injection. Anticipating the need for tight regulation of the safety factor profile in these plasma scenarios, a first-principles-driven (FPD)control-oriented model is proposed to describe the safety factor profile evolution in EAST in response to the different actuators. The TRANSP simulation code is employed to tailor the FPD model to the EAST tokamak geometry and to convert it into a form suitable for control design. The FPD control-oriented model's prediction capabilities are demonstrated by comparing predictions with experimental data from EAST. Supported by the US DOE under DE-SC0010537,DE-FG02-92ER54141 and DE-SC0013977.

  13. Computational Analysis of Epidermal Growth Factor Receptor Mutations Predicts Differential Drug Sensitivity Profiles toward Kinase Inhibitors.

    PubMed

    Akula, Sravani; Kamasani, Swapna; Sivan, Sree Kanth; Manga, Vijjulatha; Vudem, Dashavantha Reddy; Kancha, Rama Krishna

    2018-05-01

    A significant proportion of patients with lung cancer carry mutations in the EGFR kinase domain. The presence of a deletion mutation in exon 19 or L858R point mutation in the EGFR kinase domain has been shown to cause enhanced efficacy of inhibitor treatment in patients with NSCLC. Several less frequent (uncommon) mutations in the EGFR kinase domain with potential implications in treatment response have also been reported. The role of a limited number of uncommon mutations in drug sensitivity was experimentally verified. However, a huge number of these mutations remain uncharacterized for inhibitor sensitivity or resistance. A large-scale computational analysis of clinically reported 298 point mutants of EGFR kinase domain has been performed, and drug sensitivity profiles for each mutant toward seven kinase inhibitors has been determined by molecular docking. In addition, the relative inhibitor binding affinity toward each drug as compared with that of adenosine triphosphate was calculated for each mutant. The inhibitor sensitivity profiles predicted in this study for a set of previously characterized mutants correlated well with the published clinical, experimental, and computational data. Both the single and compound mutations displayed differential inhibitor sensitivity toward first- and next-generation kinase inhibitors. The present study provides predicted drug sensitivity profiles for a large panel of uncommon EGFR mutations toward multiple inhibitors, which may help clinicians in deciding mutant-specific treatment strategies. Copyright © 2018 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved.

  14. Proinflammatory cytokines, sickness behavior, and Alzheimer disease.

    PubMed

    Holmes, C; Cunningham, C; Zotova, E; Culliford, D; Perry, V H

    2011-07-19

    In Alzheimer disease (AD), systemic inflammation is known to give rise to a delirium. However, systemic inflammation also gives rise to other centrally mediated symptoms in the absence of a delirium, a concept known as sickness behavior. Systemic inflammation is characterized by the systemic production of the proinflammatory cytokines tumor necrosis factor-α (TNFα) and interleukin-6 (IL-6) that mediate immune to brain communication and the development of sickness behavior. To determine if raised serum TNFα or IL-6 are associated with the presence of sickness behavior symptoms, independent of the development of delirium, in a prospective cohort study of subjects with AD. A total of 300 subjects with mild to severe AD were cognitively assessed at baseline and a blood sample taken for inflammatory markers. Cognitive assessments, including assessments to detect the development of a delirium, and blood samples were repeated at 2, 4, and 6 months. The development of neuropsychiatric symptoms in the subject with AD over the 6-month follow-up period was assessed independently by carer interview at 2, 4, and 6 months. Raised serum TNFα and IL-6, but not CRP, were associated with an approximately 2-fold increased frequency of neuropsychiatric symptoms characteristic of sickness behavior. These relationships are independent of the development of delirium. Increased serum proinflammatory cytokines are associated with the presence of symptoms characteristic of sickness behavior, which are common neuropsychiatric features found in AD. This association was independent of the presence of delirium.

  15. Proinflammatory cytokines, sickness behavior, and Alzheimer disease

    PubMed Central

    Cunningham, C.; Zotova, E.; Culliford, D.; Perry, V.H.

    2011-01-01

    Background: In Alzheimer disease (AD), systemic inflammation is known to give rise to a delirium. However, systemic inflammation also gives rise to other centrally mediated symptoms in the absence of a delirium, a concept known as sickness behavior. Systemic inflammation is characterized by the systemic production of the proinflammatory cytokines tumor necrosis factor–α (TNFα) and interleukin-6 (IL-6) that mediate immune to brain communication and the development of sickness behavior. Objective: To determine if raised serum TNFα or IL-6 are associated with the presence of sickness behavior symptoms, independent of the development of delirium, in a prospective cohort study of subjects with AD. Methods: A total of 300 subjects with mild to severe AD were cognitively assessed at baseline and a blood sample taken for inflammatory markers. Cognitive assessments, including assessments to detect the development of a delirium, and blood samples were repeated at 2, 4, and 6 months. The development of neuropsychiatric symptoms in the subject with AD over the 6-month follow-up period was assessed independently by carer interview at 2, 4, and 6 months. Results: Raised serum TNFα and IL-6, but not CRP, were associated with an approximately 2-fold increased frequency of neuropsychiatric symptoms characteristic of sickness behavior. These relationships are independent of the development of delirium. Conclusions: Increased serum proinflammatory cytokines are associated with the presence of symptoms characteristic of sickness behavior, which are common neuropsychiatric features found in AD. This association was independent of the presence of delirium. PMID:21753171

  16. Early Childhood Profiles of Sleep Problems and Self-Regulation Predict Later School Adjustment

    ERIC Educational Resources Information Center

    Williams, Kate E.; Nicholson, Jan M.; Walker, Sue; Berthelsen, Donna

    2016-01-01

    Background: Children's sleep problems and self-regulation problems have been independently associated with poorer adjustment to school, but there has been limited exploration of longitudinal early childhood profiles that include both indicators. Aims: This study explores the normative developmental pathway for sleep problems and self-regulation…

  17. Predicting Educational Outcomes and Psychological Well-Being in Adolescents Using Time Attitude Profiles

    ERIC Educational Resources Information Center

    Andretta, James R.; Worrell, Frank C.; Mello, Zena R.

    2014-01-01

    Using cluster analysis of Adolescent Time Attitude Scale (ATAS) scores in a sample of 300 adolescents ("M" age = 16 years; "SD" = 1.25; 60% male; 41% European American; 25.3% Asian American; 11% African American; 10.3% Latino), the authors identified five time attitude profiles based on positive and negative attitudes toward…

  18. The Validity of the Musical Aptitude Profile for Predicting Grades in Freshman Music Theory.

    ERIC Educational Resources Information Center

    Harrison, Carole S.

    1987-01-01

    This study investigated the criterion-related validity of the Musical Aptitude Profile in relation to achievement in freshman music theory as determined by semester grades in the courses and by grades in three course components (paperwork, sight-singing and ear-training). (Author/BS)

  19. Predictive Validity of Career Decision-Making Profiles over Time among Chinese College Students

    ERIC Educational Resources Information Center

    Tian, Lin; Guan, Yanjun; Chen, Sylvia Xiaohua; Levin, Nimrod; Cai, Zijun; Chen, Pei; Zhu, Chengfeng; Fu, Ruchunyi; Wang, Yang; Zhang, Shu

    2014-01-01

    Two studies were conducted to validate the Chinese version of the Career Decision-Making Profiles (CDMP) questionnaire, a multidimensional measure of the way individuals make career decisions. Results of Study 1 showed that after dropping 1 item from the original CDMP scale, the 11-factor structure was supported among Chinese college students (N =…

  20. Profiles of Observed Infant Anger Predict Preschool Behavior Problems: Moderation by Life Stress

    ERIC Educational Resources Information Center

    Brooker, Rebecca J.; Buss, Kristin A.; Lemery-Chalfant, Kathryn; Aksan, Nazan; Davidson, Richard J.; Goldsmith, H. Hill

    2014-01-01

    Using both traditional composites and novel profiles of anger, we examined associations between infant anger and preschool behavior problems in a large, longitudinal data set (N = 966). We also tested the role of life stress as a moderator of the link between early anger and the development of behavior problems. Although traditional measures of…

  1. Distinct neurohumoral biomarker profiles in children with hemodynamically defined orthostatic intolerance may predict treatment options

    PubMed Central

    Wagoner, Ashley L.; Shaltout, Hossam A.; Fortunato, John E.

    2015-01-01

    Studies of adults with orthostatic intolerance (OI) have revealed altered neurohumoral responses to orthostasis, which provide mechanistic insights into the dysregulation of blood pressure control. Similar studies in children with OI providing a thorough neurohumoral profile are lacking. The objective of the present study was to determine the cardiovascular and neurohumoral profile in adolescent subjects presenting with OI. Subjects at 10–18 yr of age were prospectively recruited if they exhibited two or more traditional OI symptoms and were referred for head-up tilt (HUT) testing. Circulating catecholamines, vasopressin, aldosterone, renin, and angiotensins were measured in the supine position and after 15 min of 70° tilt. Heart rate and blood pressure were continuously measured. Of the 48 patients, 30 patients had an abnormal tilt. Subjects with an abnormal tilt had lower systolic, diastolic, and mean arterial blood pressures during tilt, significantly higher levels of vasopressin during HUT, and relatively higher catecholamines and ANG II during HUT than subjects with a normal tilt. Distinct neurohumoral profiles were observed when OI subjects were placed into the following groups defined by the hemodynamic response: postural orthostatic tachycardia syndrome (POTS), orthostatic hypotension (OH), syncope, and POTS/syncope. Key characteristics included higher HUT-induced norepinephrine in POTS subjects, higher vasopressin in OH and syncope subjects, and higher supine and HUT aldosterone in OH subjects. In conclusion, children with OI and an abnormal response to tilt exhibit distinct neurohumoral profiles associated with the type of the hemodynamic response during orthostatic challenge. Elevated arginine vasopressin levels in syncope and OH groups are likely an exaggerated response to decreased blood flow not compensated by higher norepinephrine levels, as observed in POTS subjects. These different compensatory mechanisms support the role of measuring

  2. Use of the maximum entropy method to retrieve the vertical atmospheric ozone profile and predict atmospheric ozone content

    NASA Technical Reports Server (NTRS)

    Turner, B. Curtis

    1992-01-01

    A method is developed for prediction of ozone levels in planetary atmospheres. This method is formulated in terms of error covariance matrices, and is associated with both direct measurements, a priori first guess profiles, and a weighting function matrix. This is described by the following linearized equation: y = A(matrix) x X + eta, where A is the weighting matrix and eta is noise. The problems to this approach are: (1) the A matrix is near singularity; (2) the number of unknowns in the profile exceeds the number of data points, therefore, the solution may not be unique; and (3) even if a unique solution exists, eta may cause the solution to be ill conditioned.

  3. Predicting fatty acid profiles in blood based on food intake and the FADS1 rs174546 SNP.

    PubMed

    Hallmann, Jacqueline; Kolossa, Silvia; Gedrich, Kurt; Celis-Morales, Carlos; Forster, Hannah; O'Donovan, Clare B; Woolhead, Clara; Macready, Anna L; Fallaize, Rosalind; Marsaux, Cyril F M; Lambrinou, Christina-Paulina; Mavrogianni, Christina; Moschonis, George; Navas-Carretero, Santiago; San-Cristobal, Rodrigo; Godlewska, Magdalena; Surwiłło, Agnieszka; Mathers, John C; Gibney, Eileen R; Brennan, Lorraine; Walsh, Marianne C; Lovegrove, Julie A; Saris, Wim H M; Manios, Yannis; Martinez, Jose Alfredo; Traczyk, Iwona; Gibney, Michael J; Daniel, Hannelore

    2015-12-01

    A high intake of n-3 PUFA provides health benefits via changes in the n-6/n-3 ratio in blood. In addition to such dietary PUFAs, variants in the fatty acid desaturase 1 (FADS1) gene are also associated with altered PUFA profiles. We used mathematical modeling to predict levels of PUFA in whole blood, based on multiple hypothesis testing and bootstrapped LASSO selected food items, anthropometric and lifestyle factors, and the rs174546 genotypes in FADS1 from 1607 participants (Food4Me Study). The models were developed using data from the first reported time point (training set) and their predictive power was evaluated using data from the last reported time point (test set). Among other food items, fish, pizza, chicken, and cereals were identified as being associated with the PUFA profiles. Using these food items and the rs174546 genotypes as predictors, models explained 26-43% of the variability in PUFA concentrations in the training set and 22-33% in the test set. Selecting food items using multiple hypothesis testing is a valuable contribution to determine predictors, as our models' predictive power is higher compared to analogue studies. As unique feature, we additionally confirmed our models' power based on a test set. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  4. Multiple fuzzy neural network system for outcome prediction and classification of 220 lymphoma patients on the basis of molecular profiling.

    PubMed

    Ando, Tatsuya; Suguro, Miyuki; Kobayashi, Takeshi; Seto, Masao; Honda, Hiroyuki

    2003-10-01

    A fuzzy neural network (FNN) using gene expression profile data can select combinations of genes from thousands of genes, and is applicable to predict outcome for cancer patients after chemotherapy. However, wide clinical heterogeneity reduces the accuracy of prediction. To overcome this problem, we have proposed an FNN system based on majoritarian decision using multiple noninferior models. We used transcriptional profiling data, which were obtained from "Lymphochip" DNA microarrays (http://llmpp.nih.gov/DLBCL), reported by Rosenwald (N Engl J Med 2002; 346: 1937-47). When the data were analyzed by our FNN system, accuracy (73.4%) of outcome prediction using only 1 FNN model with 4 genes was higher than that (68.5%) of the Cox model using 17 genes. Higher accuracy (91%) was obtained when an FNN system with 9 noninferior models, consisting of 35 independent genes, was used. The genes selected by the system included genes that are informative in the prognosis of Diffuse large B-cell lymphoma (DLBCL), such as genes showing an expression pattern similar to that of CD10 and BCL-6 or similar to that of IRF-4 and BCL-4. We classified 220 DLBCL patients into 5 groups using the prediction results of 9 FNN models. These groups may correspond to DLBCL subtypes. In group A containing half of the 220 patients, patients with poor outcome were found to satisfy 2 rules, i.e., high expression of MAX dimerization with high expression of unknown A (LC_26146), or high expression of MAX dimerization with low expression of unknown B (LC_33144). The present paper is the first to describe the multiple noninferior FNN modeling system. This system is a powerful tool for predicting outcome and classifying patients, and is applicable to other heterogeneous diseases.

  5. Prediction of cis/trans isomerization in proteins using PSI-BLAST profiles and secondary structure information.

    PubMed

    Song, Jiangning; Burrage, Kevin; Yuan, Zheng; Huber, Thomas

    2006-03-09

    The majority of peptide bonds in proteins are found to occur in the trans conformation. However, for proline residues, a considerable fraction of Prolyl peptide bonds adopt the cis form. Proline cis/trans isomerization is known to play a critical role in protein folding, splicing, cell signaling and transmembrane active transport. Accurate prediction of proline cis/trans isomerization in proteins would have many important applications towards the understanding of protein structure and function. In this paper, we propose a new approach to predict the proline cis/trans isomerization in proteins using support vector machine (SVM). The preliminary results indicated that using Radial Basis Function (RBF) kernels could lead to better prediction performance than that of polynomial and linear kernel functions. We used single sequence information of different local window sizes, amino acid compositions of different local sequences, multiple sequence alignment obtained from PSI-BLAST and the secondary structure information predicted by PSIPRED. We explored these different sequence encoding schemes in order to investigate their effects on the prediction performance. The training and testing of this approach was performed on a newly enlarged dataset of 2424 non-homologous proteins determined by X-Ray diffraction method using 5-fold cross-validation. Selecting the window size 11 provided the best performance for determining the proline cis/trans isomerization based on the single amino acid sequence. It was found that using multiple sequence alignments in the form of PSI-BLAST profiles could significantly improve the prediction performance, the prediction accuracy increased from 62.8% with single sequence to 69.8% and Matthews Correlation Coefficient (MCC) improved from 0.26 with single local sequence to 0.40. Furthermore, if coupled with the predicted secondary structure information by PSIPRED, our method yielded a prediction accuracy of 71.5% and MCC of 0.43, 9% and 0

  6. Predicting drug side-effect profiles: a chemical fragment-based approach

    PubMed Central

    2011-01-01

    Background Drug side-effects, or adverse drug reactions, have become a major public health concern. It is one of the main causes of failure in the process of drug development, and of drug withdrawal once they have reached the market. Therefore, in silico prediction of potential side-effects early in the drug discovery process, before reaching the clinical stages, is of great interest to improve this long and expensive process and to provide new efficient and safe therapies for patients. Results In the present work, we propose a new method to predict potential side-effects of drug candidate molecules based on their chemical structures, applicable on large molecular databanks. A unique feature of the proposed method is its ability to extract correlated sets of chemical substructures (or chemical fragments) and side-effects. This is made possible using sparse canonical correlation analysis (SCCA). In the results, we show the usefulness of the proposed method by predicting 1385 side-effects in the SIDER database from the chemical structures of 888 approved drugs. These predictions are performed with simultaneous extraction of correlated ensembles formed by a set of chemical substructures shared by drugs that are likely to have a set of side-effects. We also conduct a comprehensive side-effect prediction for many uncharacterized drug molecules stored in DrugBank, and were able to confirm interesting predictions using independent source of information. Conclusions The proposed method is expected to be useful in various stages of the drug development process. PMID:21586169

  7. Prediction of pi-turns in proteins using PSI-BLAST profiles and secondary structure information.

    PubMed

    Wang, Yan; Xue, Zhi-Dong; Shi, Xiao-Hong; Xu, Jin

    2006-09-01

    Due to the structural and functional importance of tight turns, some methods have been proposed to predict gamma-turns, beta-turns, and alpha-turns in proteins. In the past, studies of pi-turns were made, but not a single prediction approach has been developed so far. It will be useful to develop a method for identifying pi-turns in a protein sequence. In this paper, the support vector machine (SVM) method has been introduced to predict pi-turns from the amino acid sequence. The training and testing of this approach is performed with a newly collected data set of 640 non-homologous protein chains containing 1931 pi-turns. Different sequence encoding schemes have been explored in order to investigate their effects on the prediction performance. With multiple sequence alignment and predicted secondary structure, the final SVM model yields a Matthews correlation coefficient (MCC) of 0.556 by a 7-fold cross-validation. A web server implementing the prediction method is available at the following URL: http://210.42.106.80/piturn/.

  8. Concomitant prediction of function and fold at the domain level with GO-based profiles.

    PubMed

    Lopez, Daniel; Pazos, Florencio

    2013-01-01

    Predicting the function of newly sequenced proteins is crucial due to the pace at which these raw sequences are being obtained. Almost all resources for predicting protein function assign functional terms to whole chains, and do not distinguish which particular domain is responsible for the allocated function. This is not a limitation of the methodologies themselves but it is due to the fact that in the databases of functional annotations these methods use for transferring functional terms to new proteins, these annotations are done on a whole-chain basis. Nevertheless, domains are the basic evolutionary and often functional units of proteins. In many cases, the domains of a protein chain have distinct molecular functions, independent from each other. For that reason resources with functional annotations at the domain level, as well as methodologies for predicting function for individual domains adapted to these resources are required.We present a methodology for predicting the molecular function of individual domains, based on a previously developed database of functional annotations at the domain level. The approach, which we show outperforms a standard method based on sequence searches in assigning function, concomitantly predicts the structural fold of the domains and can give hints on the functionally important residues associated to the predicted function.

  9. Coconut oil predicts a beneficial lipid profile in pre-menopausal women in the Philippines

    PubMed Central

    Feranil, Alan B.; Duazo, Paulita L.; Kuzawa, Christopher W.; Adair, Linda S.

    2011-01-01

    Coconut oil is a common edible oil in many countries, and there is mixed evidence for its effects on lipid profiles and cardiovascular disease risk. Here we examine the association between coconut oil consumption and lipid profiles in a cohort of 1,839 Filipino women (age 35–69 years) participating in the Cebu Longitudinal Health and Nutrition Survey, a community based study in Metropolitan Cebu City. Coconut oil intake was measured as individual coconut oil intake calculated using two 24-hour dietary recalls (9.54 ± 8.92 grams). Cholesterol profiles were measured in plasma samples collected after an overnight fast. Mean lipid values in this sample were total cholesterol (TC) (186.52 ± 38.86 mg/dL), high density lipoprotein cholesterol (HDL-c) (40.85 ± 10.30 mg/dL), low density lipoprotein cholesterol (LDL-c) (119.42 ± 33.21 mg/dL), triglycerides (130.75 ± 85.29 mg/dL) and the TC/HDL ratio (4.80 ± 1.41). Linear regression models were used to estimate the association between coconut oil intake and each plasma lipid outcome after adjusting for total energy intake, age, body mass index (BMI), number of pregnancies, education, menopausal status, household assets and urban residency. Dietary coconut oil intake was positively associated with HDL-c levels. PMID:21669587

  10. Early pharmaceutical profiling to predict oral drug absorption: current status and unmet needs.

    PubMed

    Bergström, Christel A S; Holm, René; Jørgensen, Søren Astrup; Andersson, Sara B E; Artursson, Per; Beato, Stefania; Borde, Anders; Box, Karl; Brewster, Marcus; Dressman, Jennifer; Feng, Kung-I; Halbert, Gavin; Kostewicz, Edmund; McAllister, Mark; Muenster, Uwe; Thinnes, Julian; Taylor, Robert; Mullertz, Anette

    2014-06-16

    Preformulation measurements are used to estimate the fraction absorbed in vivo for orally administered compounds and thereby allow an early evaluation of the need for enabling formulations. As part of the Oral Biopharmaceutical Tools (OrBiTo) project, this review provides a summary of the pharmaceutical profiling methods available, with focus on in silico and in vitro models typically used to forecast active pharmaceutical ingredient's (APIs) in vivo performance after oral administration. An overview of the composition of human, animal and simulated gastrointestinal (GI) fluids is provided and state-of-the art methodologies to study API properties impacting on oral absorption are reviewed. Assays performed during early development, i.e. physicochemical characterization, dissolution profiles under physiological conditions, permeability assays and the impact of excipients on these properties are discussed in detail and future demands on pharmaceutical profiling are identified. It is expected that innovative computational and experimental methods that better describe molecular processes involved in vivo during dissolution and absorption of APIs will be developed in the OrBiTo. These methods will provide early insights into successful pathways (medicinal chemistry or formulation strategy) and are anticipated to increase the number of new APIs with good oral absorption being discovered. Copyright © 2013 Elsevier B.V. All rights reserved.

  11. Taxonomic and predicted metabolic profiles of the human gut microbiome in pre-Columbian mummies.

    PubMed

    Santiago-Rodriguez, Tasha M; Fornaciari, Gino; Luciani, Stefania; Dowd, Scot E; Toranzos, Gary A; Marota, Isolina; Cano, Raul J

    2016-11-01

    Characterization of naturally mummified human gut remains could potentially provide insights into the preservation and evolution of commensal and pathogenic microorganisms, and metabolic profiles. We characterized the gut microbiome of two pre-Columbian Andean mummies dating to the 10-15th centuries using 16S rRNA gene high-throughput sequencing and metagenomics, and compared them to a previously characterized gut microbiome of an 11th century AD pre-Columbian Andean mummy. Our previous study showed that the Clostridiales represented the majority of the bacterial communities in the mummified gut remains, but that other microbial communities were also preserved during the process of natural mummification, as shown with the metagenomics analyses. The gut microbiome of the other two mummies were mainly comprised by Clostridiales or Bacillales, as demonstrated with 16S rRNA gene amplicon sequencing, many of which are facultative anaerobes, possibly consistent with the process of natural mummification requiring low oxygen levels. Metagenome analyses showed the presence of other microbial groups that were positively or negatively correlated with specific metabolic profiles. The presence of sequences similar to both Trypanosoma cruzi and Leishmania donovani could suggest that these pathogens were prevalent in pre-Columbian individuals. Taxonomic and functional profiling of mummified human gut remains will aid in the understanding of the microbial ecology of the process of natural mummification. © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  12. Proinflammatory Stem Cell Signaling in Cardiac Ischemia

    PubMed Central

    Herrmann, Jeremy L.; Markel, Troy A.; Abarbanell, Aaron M.; Weil, Brent R.; Wang, Meijing; Wang, Yue; Tan, Jiangning

    2009-01-01

    Abstract Cardiovascular disease remains a leading cause of mortality in developed nations, despite continued advancement in modern therapy. Progenitor and stem cell–based therapy is a novel treatment for cardiovascular disease, and modest benefits in cardiac recovery have been achieved in small clinical trials. This therapeutic modality remains challenged by limitations of low donor-cell survival rates, transient recovery of cardiac function, and the technical difficulty of applying directed cell therapy. Understanding the signaling mechanisms involved in the stem cell response to ischemia has revealed opportunities to modify directly aspects of these pathways to improve their cardioprotective abilities. This review highlights general considerations of stem cell therapy for cardiac disease, reviews the major proinflammatory signaling pathways of mesenchymal stem cells, and reviews ex vivo modifications of stem cells based on these pathways. Antioxid. Redox Signal. 11, 1883–1896. PMID:19187005

  13. Effect of proinflammatory cytokines on PIGA- hematopoiesis.

    PubMed

    Kulkarni, Shashikant; Bessler, Monica

    2003-09-01

    Blood cells from patients with paroxysmal nocturnal hemoglobinuria lack glycosyl phosphatidylinositol (GPI)-linked proteins, due to a somatic mutation in the X-linked PIGA gene. It is believed that clonal expansion of PIGA- blood cells is due to a survival advantage in the hostile marrow environment of aplastic anemia. Here we investigated the effects of inhibitory cytokines in mice genetically engineered to have blood cells deficient in GPI-linked proteins. The effect of inhibitory cytokines (tumor necrosis factor-alpha [TNF-alpha], interferon-gamma [IFN-gamma], macrophage inflammatory protein-1 alpha [MIP-1alpha], and transforming growth factor-beta1 [TGF-beta1]) was investigated, using clonogenic assays, competitive repopulation, and in vivo induction of proinflammatory cytokines by double-stranded RNA. The expression of Fas on progenitor cells and its up-regulation by inhibitory cytokines were analyzed by flow cytometry. TNF-alpha, IFN-gamma, MIP-1alpha, and TGF-beta1 suppressed colony formation in a dose-dependent fashion that was similar for PIGA+ and PIGA- blood bone marrow cells. Competitive repopulation of bone marrow cells cultured in IFN-gamma and TNF-alpha resulted in a comparable ability of PIGA+ and PIGA- hematopoietic stem cells to reconstitute hematopoiesis. Fas expression was minimal on PIGA+ and PIGA- progenitor cells and was up-regulated to the same extent in response to IFN-gamma and TNF-alpha as assessed by Fas antibody-mediated apoptosis. Similarly, in vivo induction of proinflammatory cytokines by double-stranded RNA had no effect on the proportion of circulating PIGA- blood cells. These results indicate that PIGA+ and PIGA- hematopoietic progenitor cells respond similarly to inhibitory cytokines, suggesting that other factors are responsible for the clonal expansion of paroxysmal nocturnal hemoglobinuria cells.

  14. The Application of Gene Expression Profiling in Predictions of Occult Lymph Node Metastasis in Colorectal Cancer Patients

    PubMed Central

    Peyravian, Noshad; Larki, Pegah; Gharib, Ehsan; Nazemalhosseini-Mojarad, Ehsan; Anaraki, Fakhrosadate; Young, Chris; McClellan, James; Ashrafian Bonab, Maziar; Asadzadeh-Aghdaei, Hamid; Zali, Mohammad Reza

    2018-01-01

    A key factor in determining the likely outcome for a patient with colorectal cancer is whether or not the tumour has metastasised to the lymph nodes—information which is also important in assessing any possibilities of lymph node resection so as to improve survival. In this review we perform a wide-range assessment of literature relating to recent developments in gene expression profiling (GEP) of the primary tumour, to determine their utility in assessing node status. A set of characteristic genes seems to be involved in the prediction of lymph node metastasis (LNM) in colorectal patients. Hence, GEP is applicable in personalised/individualised/tailored therapies and provides insights into developing novel therapeutic targets. Not only is GEP useful in prediction of LNM, but it also allows classification based on differences such as sample size, target gene expression, and examination method. PMID:29498671

  15. MicroRNA Profile Predicts Recurrence after Resection in Patients with Hepatocellular Carcinoma within the Milan Criteria

    PubMed Central

    Sato, Fumiaki; Hatano, Etsuro; Kitamura, Koji; Myomoto, Akira; Fujiwara, Takeshi; Takizawa, Satoko; Tsuchiya, Soken; Tsujimoto, Gozoh; Uemoto, Shinji; Shimizu, Kazuharu

    2011-01-01

    Objective Hepatocellular carcinoma (HCC) is difficult to manage due to the high frequency of post-surgical recurrence. Early detection of the HCC recurrence after liver resection is important in making further therapeutic options, such as salvage liver transplantation. In this study, we utilized microRNA expression profiling to assess the risk of HCC recurrence after liver resection. Methods We examined microRNA expression profiling in paired tumor and non-tumor liver tissues from 73 HCC patients who satisfied the Milan Criteria. We constructed prediction models of recurrence-free survival using the Cox proportional hazard model and principal component analysis. The prediction efficiency was assessed by the leave-one-out cross-validation method, and the time-averaged area under the ROC curve (ta-AUROC). Results The univariate Cox analysis identified 13 and 56 recurrence-related microRNAs in the tumor and non-tumor tissues, such as miR-96. The number of recurrence-related microRNAs was significantly larger in the non-tumor-derived microRNAs (N-miRs) than in the tumor-derived microRNAs (T-miRs, P<0.0001). The best ta-AUROC using the whole dataset, T-miRs, N-miRs, and clinicopathological dataset were 0.8281, 0.7530, 0.7152, and 0.6835, respectively. The recurrence-free survival curve of the low-risk group stratified by the best model was significantly better than that of the high-risk group (Log-rank: P = 0.00029). The T-miRs tend to predict early recurrence better than late recurrence, whereas N-miRs tend to predict late recurrence better (P<0.0001). This finding supports the concept of early recurrence by the dissemination of primary tumor cells and multicentric late recurrence by the ‘field effect’. Conclusion microRNA profiling can predict HCC recurrence in Milan criteria cases. PMID:21298008

  16. Reduced model prediction of electron temperature profiles in microtearing-dominated National Spherical Torus eXperiment plasmas

    NASA Astrophysics Data System (ADS)

    Kaye, S. M.; Guttenfelder, W.; Bell, R. E.; Gerhardt, S. P.; LeBlanc, B. P.; Maingi, R.

    2014-08-01

    A representative H-mode discharge from the National Spherical Torus eXperiment is studied in detail to utilize it as a basis for a time-evolving prediction of the electron temperature profile using an appropriate reduced transport model. The time evolution of characteristic plasma variables such as β e , νe ∗ , the MHD α parameter, and the gradient scale lengths of Te, Ti, and ne were examined as a prelude to performing linear gyrokinetic calculations to determine the fastest growing micro instability at various times and locations throughout the discharge. The inferences from the parameter evolutions and the linear stability calculations were consistent. Early in the discharge, when βe and νe ∗ were relatively low, ballooning parity modes were dominant. As time progressed and both βe and νe ∗ increased, microtearing became the dominant low-kθ mode, especially in the outer half of the plasma. There are instances in time and radius, however, where other modes, at higher-kθ, may, in addition to microtearing, be important for driving electron transport. Given these results, the Rebut-Lallia-Watkins (RLW) electron thermal diffusivity model, which is based on microtearing-induced transport, was used to predict the time-evolving electron temperature across most of the profile. The results indicate that RLW does a good job of predicting Te for times and locations where microtearing was determined to be important, but not as well when microtearing was predicted to be stable or subdominant.

  17. Reduced model prediction of electron temperature profiles in microtearing-dominated National Spherical Torus eXperiment plasmas

    SciTech Connect

    Kaye, S. M.; Guttenfelder, W.; Bell, R. E.

    A representative H-mode discharge from the National Spherical Torus eXperiment is studied in detail to utilize it as a basis for a time-evolving prediction of the electron temperature profile using an appropriate reduced transport model. The time evolution of characteristic plasma variables such as βe, ν*e, the MHD α parameter, and the gradient scale lengths of Te, Ti, and ne were examined as a prelude to performing linear gyrokinetic calculations to determine the fastest growing micro instability at various times and locations throughout the discharge. The inferences from the parameter evolutions and the linear stability calculations were consistent. Early inmore » the discharge, when βe and ν*e were relatively low, ballooning parity modes were dominant. As time progressed and both βe and ν*e increased, microtearing became the dominant low-κθ mode, especially in the outer half of the plasma. There are instances in time and radius, however, where other modes, at higher-κθ, may, in addition to microtearing, be important for driving electron transport. Given these results, the Rebut-Lallia-Watkins (RLW) electron thermal diffusivity model, which is based on microtearing-induced transport, was used to predict the time-evolving electron temperature across most of the profile. The results indicate that RLW does a good job of predicting Te for times and locations where microtearing was determined to be important, but not as well when microtearing was predicted to be stable or subdominant.« less

  18. Reduced model prediction of electron temperature profiles in microtearing-dominated National Spherical Torus eXperiment plasmas

    SciTech Connect

    Kaye, S. M., E-mail: skaye@pppl.gov; Guttenfelder, W.; Bell, R. E.

    A representative H-mode discharge from the National Spherical Torus eXperiment is studied in detail to utilize it as a basis for a time-evolving prediction of the electron temperature profile using an appropriate reduced transport model. The time evolution of characteristic plasma variables such as β{sub e}, ν{sub e}{sup ∗}, the MHD α parameter, and the gradient scale lengths of T{sub e}, T{sub i}, and n{sub e} were examined as a prelude to performing linear gyrokinetic calculations to determine the fastest growing micro instability at various times and locations throughout the discharge. The inferences from the parameter evolutions and the linear stabilitymore » calculations were consistent. Early in the discharge, when β{sub e} and ν{sub e}{sup ∗} were relatively low, ballooning parity modes were dominant. As time progressed and both β{sub e} and ν{sub e}{sup ∗} increased, microtearing became the dominant low-k{sub θ} mode, especially in the outer half of the plasma. There are instances in time and radius, however, where other modes, at higher-k{sub θ}, may, in addition to microtearing, be important for driving electron transport. Given these results, the Rebut-Lallia-Watkins (RLW) electron thermal diffusivity model, which is based on microtearing-induced transport, was used to predict the time-evolving electron temperature across most of the profile. The results indicate that RLW does a good job of predicting T{sub e} for times and locations where microtearing was determined to be important, but not as well when microtearing was predicted to be stable or subdominant.« less

  19. Ovary transcriptome profiling via artificial intelligence reveals a transcriptomic fingerprint predicting egg quality in striped bass, Morone saxatilis.

    PubMed

    Chapman, Robert W; Reading, Benjamin J; Sullivan, Craig V

    2014-01-01

    Inherited gene transcripts deposited in oocytes direct early embryonic development in all vertebrates, but transcript profiles indicative of embryo developmental competence have not previously been identified. We employed artificial intelligence to model profiles of maternal ovary gene expression and their relationship to egg quality, evaluated as production of viable mid-blastula stage embryos, in the striped bass (Morone saxatilis), a farmed species with serious egg quality problems. In models developed using artificial neural networks (ANNs) and supervised machine learning, collective changes in the expression of a limited suite of genes (233) representing <2% of the queried ovary transcriptome explained >90% of the eventual variance in embryo survival. Egg quality related to minor changes in gene expression (<0.2-fold), with most individual transcripts making a small contribution (<1%) to the overall prediction of egg quality. These findings indicate that the predictive power of the transcriptome as regards egg quality resides not in levels of individual genes, but rather in the collective, coordinated expression of a suite of transcripts constituting a transcriptomic "fingerprint". Correlation analyses of the corresponding candidate genes indicated that dysfunction of the ubiquitin-26S proteasome, COP9 signalosome, and subsequent control of the cell cycle engenders embryonic developmental incompetence. The affected gene networks are centrally involved in regulation of early development in all vertebrates, including humans. By assessing collective levels of the relevant ovarian transcripts via ANNs we were able, for the first time in any vertebrate, to accurately predict the subsequent embryo developmental potential of eggs from individual females. Our results show that the transcriptomic fingerprint evidencing developmental dysfunction is highly predictive of, and therefore likely to regulate, egg quality, a biologically complex trait crucial to reproductive

  20. A long non-coding RNA expression profile can predict early recurrence in hepatocellular carcinoma after curative resection.

    PubMed

    Lv, Yufeng; Wei, Wenhao; Huang, Zhong; Chen, Zhichao; Fang, Yuan; Pan, Lili; Han, Xueqiong; Xu, Zihai

    2018-06-20

    The aim of this study was to develop a novel long non-coding RNA (lncRNA) expression signature to accurately predict early recurrence for patients with hepatocellular carcinoma (HCC) after curative resection. Using expression profiles downloaded from The Cancer Genome Atlas database, we identified multiple lncRNAs with differential expression between early recurrence (ER) group and non-early recurrence (non-ER) group of HCC. Least absolute shrinkage and selection operator (LASSO) for logistic regression models were used to develop a lncRNA-based classifier for predicting ER in the training set. An independent test set was used to validated the predictive value of this classifier. Futhermore, a co-expression network based on these lncRNAs and its highly related genes was constructed and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses of genes in the network were performed. We identified 10 differentially expressed lncRNAs, including 3 that were upregulated and 7 that were downregulated in ER group. The lncRNA-based classifier was constructed based on 7 lncRNAs (AL035661.1, PART1, AC011632.1, AC109588.1, AL365361.1, LINC00861 and LINC02084), and its accuracy was 0.83 in training set, 0.87 in test set and 0.84 in total set. And ROC curve analysis showed the AUROC was 0.741 in training set, 0.824 in the test set and 0.765 in total set. A functional enrichment analysis suggested that the genes of which is highly related to 4 lncRNAs were involved in immune system. This 7-lncRNA expression profile can effectively predict the early recurrence after surgical resection for HCC. This article is protected by copyright. All rights reserved.

  1. Gene expression profile predicting the response to anti-TNF treatment in patients with rheumatoid arthritis; analysis of GEO datasets.

    PubMed

    Kim, Tae-Hwan; Choi, Sung Jae; Lee, Young Ho; Song, Gwan Gyu; Ji, Jong Dae

    2014-07-01

    Anti-tumor necrosis factor (TNF) therapy is the treatment of choice for rheumatoid arthritis (RA) patients in whom standard disease-modifying anti-rheumatic drugs are ineffective. However, a substantial proportion of RA patients treated with anti-TNF agents do not show a significant clinical response. Therefore, biomarkers predicting response to anti-TNF agents are needed. Recently, gene expression profiling has been applied in research for developing such biomarkers. We compared gene expression profiles reported by previous studies dealing with the responsiveness of anti-TNF therapy in RA patients and attempted to identify differentially expressed genes (DEGs) that discriminated between responders and non-responders to anti-TNF therapy. We used microarray datasets available at the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO). This analysis included 6 studies and 5 sets of microarray data that used peripheral blood samples for identification of DEGs predicting response to anti-TNF therapy. We found little overlap in the DEGs that were highly ranked in each study. Three DEGs including IL2RB, SH2D2A and G0S2 appeared in more than 1 study. In addition, a meta-analysis designed to increase statistical power found one DEG, G0S2 by the Fisher's method. Our finding suggests the possibility that G0S2 plays as a biomarker to predict response to anti-TNF therapy in patients with rheumatoid arthritis. Further investigations based on larger studies are therefore needed to confirm the significance of G0S2 in predicting response to anti-TNF therapy. Copyright © 2014 Société française de rhumatologie. Published by Elsevier SAS. All rights reserved.

  2. Ovary Transcriptome Profiling via Artificial Intelligence Reveals a Transcriptomic Fingerprint Predicting Egg Quality in Striped Bass, Morone saxatilis

    PubMed Central

    2014-01-01

    Inherited gene transcripts deposited in oocytes direct early embryonic development in all vertebrates, but transcript profiles indicative of embryo developmental competence have not previously been identified. We employed artificial intelligence to model profiles of maternal ovary gene expression and their relationship to egg quality, evaluated as production of viable mid-blastula stage embryos, in the striped bass (Morone saxatilis), a farmed species with serious egg quality problems. In models developed using artificial neural networks (ANNs) and supervised machine learning, collective changes in the expression of a limited suite of genes (233) representing <2% of the queried ovary transcriptome explained >90% of the eventual variance in embryo survival. Egg quality related to minor changes in gene expression (<0.2-fold), with most individual transcripts making a small contribution (<1%) to the overall prediction of egg quality. These findings indicate that the predictive power of the transcriptome as regards egg quality resides not in levels of individual genes, but rather in the collective, coordinated expression of a suite of transcripts constituting a transcriptomic “fingerprint”. Correlation analyses of the corresponding candidate genes indicated that dysfunction of the ubiquitin-26S proteasome, COP9 signalosome, and subsequent control of the cell cycle engenders embryonic developmental incompetence. The affected gene networks are centrally involved in regulation of early development in all vertebrates, including humans. By assessing collective levels of the relevant ovarian transcripts via ANNs we were able, for the first time in any vertebrate, to accurately predict the subsequent embryo developmental potential of eggs from individual females. Our results show that the transcriptomic fingerprint evidencing developmental dysfunction is highly predictive of, and therefore likely to regulate, egg quality, a biologically complex trait crucial to

  3. Prediction du profil de durete de l'acier AISI 4340 traite thermiquement au laser

    NASA Astrophysics Data System (ADS)

    Maamri, Ilyes

    Les traitements thermiques de surfaces sont des procedes qui visent a conferer au coeur et a la surface des pieces mecaniques des proprietes differentes. Ils permettent d'ameliorer la resistance a l'usure et a la fatigue en durcissant les zones critiques superficielles par des apports thermiques courts et localises. Parmi les procedes qui se distinguent par leur capacite en terme de puissance surfacique, le traitement thermique de surface au laser offre des cycles thermiques rapides, localises et precis tout en limitant les risques de deformations indesirables. Les proprietes mecaniques de la zone durcie obtenue par ce procede dependent des proprietes physicochimiques du materiau a traiter et de plusieurs parametres du procede. Pour etre en mesure d'exploiter adequatement les ressources qu'offre ce procede, il est necessaire de developper des strategies permettant de controler et regler les parametres de maniere a produire avec precision les caracteristiques desirees pour la surface durcie sans recourir au classique long et couteux processus essai-erreur. L'objectif du projet consiste donc a developper des modeles pour predire le profil de durete dans le cas de traitement thermique de pieces en acier AISI 4340. Pour comprendre le comportement du procede et evaluer les effets des differents parametres sur la qualite du traitement, une etude de sensibilite a ete menee en se basant sur une planification experimentale structuree combinee a des techniques d'analyse statistiques eprouvees. Les resultats de cette etude ont permis l'identification des variables les plus pertinentes a exploiter pour la modelisation. Suite a cette analyse et dans le but d'elaborer un premier modele, deux techniques de modelisation ont ete considerees, soient la regression multiple et les reseaux de neurones. Les deux techniques ont conduit a des modeles de qualite acceptable avec une precision d'environ 90%. Pour ameliorer les performances des modeles a base de reseaux de neurones, deux

  4. Profiles of Verbal Working Memory Growth Predict Speech and Language Development in Children with Cochlear Implants

    ERIC Educational Resources Information Center

    Kronenberger, William G.; Pisoni, David B.; Harris, Michael S.; Hoen, Helena M.; Xu, Huiping; Miyamoto, Richard T.

    2013-01-01

    Purpose: Verbal short-term memory (STM) and working memory (WM) skills predict speech and language outcomes in children with cochlear implants (CIs) even after conventional demographic, device, and medical factors are taken into account. However, prior research has focused on single end point outcomes as opposed to the longitudinal process of…

  5. Persistent Hypogonadotropic Hypogonadism in Men After Severe Traumatic Brain Injury: Temporal Hormone Profiles and Outcome Prediction.

    PubMed

    Barton, David J; Kumar, Raj G; McCullough, Emily H; Galang, Gary; Arenth, Patricia M; Berga, Sarah L; Wagner, Amy K

    2016-01-01

    To (1) examine relationships between persistent hypogonadotropic hypogonadism (PHH) and long-term outcomes after severe traumatic brain injury (TBI); and (2) determine whether subacute testosterone levels can predict PHH. Level 1 trauma center at a university hospital. Consecutive sample of men with severe TBI between 2004 and 2009. Prospective cohort study. Post-TBI blood samples were collected during week 1, every 2 weeks until 26 weeks, and at 52 weeks. Serum hormone levels were measured, and individuals were designated as having PHH if 50% or more of samples met criteria for hypogonadotropic hypogonadism. At 6 and 12 months postinjury, we assessed global outcome, disability, functional cognition, depression, and quality of life. We recruited 78 men; median (interquartile range) age was 28.5 (22-42) years. Thirty-four patients (44%) had PHH during the first year postinjury. Multivariable regression, controlling for age, demonstrated PHH status predicted worse global outcome scores, more disability, and reduced functional cognition at 6 and 12 months post-TBI. Two-step testosterone screening for PHH at 12 to 16 weeks postinjury yielded a sensitivity of 79% and specificity of 100%. PHH status in men predicts poor outcome after severe TBI, and PHH can accurately be predicted at 12 to 16 weeks.

  6. Amazon forest carbon dynamics predicted by profiles of canopy leaf area and light environment

    Treesearch

    S. C. Stark; V. Leitold; J. L. Wu; M. O. Hunter; C. V. de Castilho; F. R. C. Costa; S. M. McMahon; G. G. Parker; M. Takako Shimabukuro; M. A. Lefsky; M. Keller; L. F. Alves; J. Schietti; Y. E. Shimabukuro; D. O. Brandao; T. K. Woodcock; N. Higuchi; P. B de Camargo; R. C. de Oliveira; S. R. Saleska

    2012-01-01

    Tropical forest structural variation across heterogeneous landscapes may control above-ground carbon dynamics. We tested the hypothesis that canopy structure (leaf area and light availability) – remotely estimated from LiDAR – control variation in above-ground coarse wood production (biomass growth). Using a statistical model, these factors predicted biomass growth...

  7. Describing and Predicting Developmental Profiles of Externalizing Problems from Childhood to Adulthood

    PubMed Central

    Petersen, Isaac T.; Bates, John E.; Dodge, Kenneth A.; Lansford, Jennifer E.; Pettit, Gregory S.

    2014-01-01

    This longitudinal study considers externalizing behavior problems from ages 5 to 27 (N = 585). Externalizing problem ratings by mothers, fathers, teachers, peers, and self-report were modeled with growth curves. Risk and protective factors across many different domains and time frames were included as predictors of the trajectories. A major contribution of the study is in demonstrating how heterotypic continuity and changing measures can be handled in modeling changes in externalizing behavior over long developmental periods. On average, externalizing problems decreased from early childhood to preadolescence, increased during adolescence, and decreased from late adolescence to adulthood. There was strong nonlinear continuity in externalizing problems over time. Family process, peer process, stress, and individual characteristics predicted externalizing problems beyond the strong continuity of externalizing problems. The model accounted for 70% of the variability in the development of externalizing problems. The model’s predicted values showed moderate sensitivity and specificity in prediction of arrests, illegal drug use, and drunk driving. Overall, the study showed that by using changing, developmentally-relevant measures and simultaneously taking into account numerous characteristics of children and their living situations, research can model lengthy spans of development and improve predictions of the development of later, severe externalizing problems. PMID:25166430

  8. Predictive Signatures of Developmental Toxicity Modeled with HTS Data from ToxCast™ Bioactivity Profiles

    EPA Science Inventory

    The EPA ToxCast™ research program uses a high-throughput screening (HTS) approach for predicting the toxicity of large numbers of chemicals. Phase-I contains 309 well-characterized chemicals which are mostly pesticides tested in over 600 assays of different molecular targets, cel...

  9. Persistent hypogonadotropic hypogonadism in men after severe traumatic brain injury: temporal hormone profiles and outcome prediction

    PubMed Central

    Barton, David J.; Kumar, Raj G.; McCullough, Emily H.; Galang, Gary; Arenth, Patricia M.; Berga, Sarah L.; Wagner, Amy K.

    2015-01-01

    Objective (1) Examine relationships between persistent hypogonadotropic hypogonadism (PHH) and long-term outcomes after severe traumatic brain injury (TBI); (2) determine if sub-acute testosterone levels can predict PHH. Setting Level 1 trauma center at a university hospital. Participants Consecutive sample of men with severe TBI between 2004 and 2009. Design Prospective cohort study. Main Measures Post-TBI blood samples were collected during week 1, every 2 weeks until 26 weeks, and at 52 weeks. Serum hormone levels were measured, and individuals were designated as having PHH if ≥50% of samples met criteria for hypogonadotropic hypogonadism. At 6 and 12 months post-injury, we assessed global outcome, disability, functional cognition, depression, and quality-of-life. Results We recruited 78 men; median (IQR) age was 28.5 (22–42) years. 34 patients (44%) had PHH during the first year post-injury. Multivariable regression, controlling for age, demonstrated PHH status predicted worse global outcome scores, more disability, and reduced functional cognition at 6 and 12 months post-TBI. Two-step testosterone screening for PHH at 12–16 weeks post-injury yielded a sensitivity of 79% and specificity of 100%. Conclusion PHH status in men predicts poor outcome after severe TBI, and PHH can accurately be predicted at 12–16 weeks. PMID:26360007

  10. Modelling the Tox21 10 K chemical profiles for in vivo toxicity prediction and mechanism characterization

    PubMed Central

    Huang, Ruili; Xia, Menghang; Sakamuru, Srilatha; Zhao, Jinghua; Shahane, Sampada A.; Attene-Ramos, Matias; Zhao, Tongan; Austin, Christopher P.; Simeonov, Anton

    2016-01-01

    Target-specific, mechanism-oriented in vitro assays post a promising alternative to traditional animal toxicology studies. Here we report the first comprehensive analysis of the Tox21 effort, a large-scale in vitro toxicity screening of chemicals. We test ∼10,000 chemicals in triplicates at 15 concentrations against a panel of nuclear receptor and stress response pathway assays, producing more than 50 million data points. Compound clustering by structure similarity and activity profile similarity across the assays reveals structure–activity relationships that are useful for the generation of mechanistic hypotheses. We apply structural information and activity data to build predictive models for 72 in vivo toxicity end points using a cluster-based approach. Models based on in vitro assay data perform better in predicting human toxicity end points than animal toxicity, while a combination of structural and activity data results in better models than using structure or activity data alone. Our results suggest that in vitro activity profiles can be applied as signatures of compound mechanism of toxicity and used in prioritization for more in-depth toxicological testing. PMID:26811972

  11. Magnetic resonance spectroscopy metabolite profiles predict survival in paediatric brain tumours.

    PubMed

    Wilson, Martin; Cummins, Carole L; Macpherson, Lesley; Sun, Yu; Natarajan, Kal; Grundy, Richard G; Arvanitis, Theodoros N; Kauppinen, Risto A; Peet, Andrew C

    2013-01-01

    Brain tumours cause the highest mortality and morbidity rate of all childhood tumour groups and new methods are required to improve clinical management. (1)H magnetic resonance spectroscopy (MRS) allows non-invasive concentration measurements of small molecules present in tumour tissue, providing clinically useful imaging biomarkers. The primary aim of this study was to investigate whether MRS detectable molecules can predict the survival of paediatric brain tumour patients. Short echo time (30ms) single voxel (1)H MRS was performed on children attending Birmingham Children's Hospital with a suspected brain tumour and 115 patients were included in the survival analysis. Patients were followed-up for a median period of 35 months and Cox-Regression was used to establish the prognostic value of individual MRS detectable molecules. A multivariate model of survival was also investigated to improve prognostic power. Lipids and scyllo-inositol predicted poor survival whilst glutamine and N-acetyl aspartate predicted improved survival (p<0.05). A multivariate model of survival based on three MRS biomarkers predicted survival with a similar accuracy to histologic grading (p<5e-5). A negative correlation between lipids and glutamine was found, suggesting a functional link between these molecules. MRS detectable biomolecules have been identified that predict survival of paediatric brain tumour patients across a range of tumour types. The evaluation of these biomarkers in large prospective studies of specific tumour types should be undertaken. The correlation between lipids and glutamine provides new insight into paediatric brain tumour metabolism that may present novel targets for therapy. Copyright © 2012 Elsevier Ltd. All rights reserved.

  12. Accurate prediction of bacterial type IV secreted effectors using amino acid composition and PSSM profiles.

    PubMed

    Zou, Lingyun; Nan, Chonghan; Hu, Fuquan

    2013-12-15

    Various human pathogens secret effector proteins into hosts cells via the type IV secretion system (T4SS). These proteins play important roles in the interaction between bacteria and hosts. Computational methods for T4SS effector prediction have been developed for screening experimental targets in several isolated bacterial species; however, widely applicable prediction approaches are still unavailable In this work, four types of distinctive features, namely, amino acid composition, dipeptide composition, .position-specific scoring matrix composition and auto covariance transformation of position-specific scoring matrix, were calculated from primary sequences. A classifier, T4EffPred, was developed using the support vector machine with these features and their different combinations for effector prediction. Various theoretical tests were performed in a newly established dataset, and the results were measured with four indexes. We demonstrated that T4EffPred can discriminate IVA and IVB effectors in benchmark datasets with positive rates of 76.7% and 89.7%, respectively. The overall accuracy of 95.9% shows that the present method is accurate for distinguishing the T4SS effector in unidentified sequences. A classifier ensemble was designed to synthesize all single classifiers. Notable performance improvement was observed using this ensemble system in benchmark tests. To demonstrate the model's application, a genome-scale prediction of effectors was performed in Bartonella henselae, an important zoonotic pathogen. A number of putative candidates were distinguished. A web server implementing the prediction method and the source code are both available at http://bioinfo.tmmu.edu.cn/T4EffPred.

  13. Multivariate modelling of faecal bacterial profiles of patients with IBS predicts responsiveness to a diet low in FODMAPs.

    PubMed

    Bennet, Sean M P; Böhn, Lena; Störsrud, Stine; Liljebo, Therese; Collin, Lena; Lindfors, Perjohan; Törnblom, Hans; Öhman, Lena; Simrén, Magnus

    2018-05-01

    The effects of dietary interventions on gut bacteria are ambiguous. Following a previous intervention study, we aimed to determine how differing diets impact gut bacteria and if bacterial profiles predict intervention response. Sixty-seven patients with IBS were randomised to traditional IBS (n=34) or low fermentable oligosaccharides, disaccharides, monosaccharides and polyols (FODMAPs) (n=33) diets for 4 weeks. Food intake was recorded for 4 days during screening and intervention. Faecal samples and IBS Symptom Severity Score (IBS-SSS) reports were collected before (baseline) and after intervention. A faecal microbiota dysbiosis test (GA-map Dysbiosis Test) evaluated bacterial composition. Per protocol analysis was performed on 61 patients from whom microbiome data were available. Responders (reduced IBS-SSS by ≥50) to low FODMAP, but not traditional, dietary intervention were discriminated from non-responders before and after intervention based on faecal bacterial profiles. Bacterial abundance tended to be higher in non-responders to a low FODMAP diet compared with responders before and after intervention. A low FODMAP intervention was associated with an increase in Dysbiosis Index (DI) scores in 42% of patients; while decreased DI scores were recorded in 33% of patients following a traditional IBS diet. Non-responders to a low FODMAP diet, but not a traditional IBS diet had higher DI scores than responders at baseline. Finally, while a traditional IBS diet was not associated with significant reduction of investigated bacteria, a low FODMAP diet was associated with reduced Bifidobacterium and Actinobacteria in patients, correlating with lactose consumption. A low FODMAP, but not a traditional IBS diet may have significant impact on faecal bacteria. Responsiveness to a low FODMAP diet intervention may be predicted by faecal bacterial profiles. NCT02107625. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a

  14. A method for predicting the noise levels of coannular jets with inverted velocity profiles

    NASA Technical Reports Server (NTRS)

    Russell, J. W.

    1979-01-01

    A coannular jet was equated with a single stream equivalent jet with the same mass flow, energy, and thrust. The acoustic characteristics of the coannular jet were then related to the acoustic characteristics of the single jet. Forward flight effects were included by incorporating a forward exponent, a Doppler amplification factor, and a Strouhal frequency shift. Model test data, including 48 static cases and 22 wind tunnel cases, were used to evaluate the prediction method. For the static cases and the low forward velocity wind tunnel cases, the spectral mean square pressure correlation coefficients were generally greater than 90 percent, and the spectral sound pressure level standard deviation were generally less than 3 decibels. The correlation coefficient and the standard deviation were not affected by changes in equivalent jet velocity. Limitations of the prediction method are also presented.

  15. Genomic profiling of human penile carcinoma predicts worse prognosis and survival.

    PubMed

    Busso-Lopes, Ariane F; Marchi, Fábio A; Kuasne, Hellen; Scapulatempo-Neto, Cristovam; Trindade-Filho, José Carlos S; de Jesus, Carlos Márcio N; Lopes, Ademar; Guimarães, Gustavo C; Rogatto, Silvia R

    2015-02-01

    The molecular mechanisms underlying penile carcinoma are still poorly understood, and the detection of genetic markers would be of great benefit for these patients. In this study, we assessed the genomic profile aiming at identifying potential prognostic biomarkers in penile carcinoma. Globally, 46 penile carcinoma samples were considered to evaluate DNA copy-number alterations via array comparative genomic hybridization (aCGH) combined with human papillomavirus (HPV) genotyping. Specific genes were investigated by using qPCR, FISH, and RT-qPCR. Genomic alterations mapped at 3p and 8p were related to worse prognostic features, including advanced T and clinical stage, recurrence and death from the disease. Losses of 3p21.1-p14.3 and gains of 3q25.31-q29 were associated with reduced cancer-specific and disease-free survival. Genomic alterations detected for chromosome 3 (LAMP3, PPARG, TNFSF10 genes) and 8 (DLC1) were evaluated by qPCR. DLC1 and PPARG losses were associated with poor prognosis characteristics. Losses of DLC1 were an independent risk factor for recurrence on multivariate analysis. The gene-expression analysis showed downexpression of DLC1 and PPARG and overexpression of LAMP3 and TNFSF10 genes. Chromosome Y losses and MYC gene (8q24) gains were confirmed by FISH. HPV infection was detected in 34.8% of the samples, and 19 differential genomic regions were obtained related to viral status. At first time, we described recurrent copy-number alterations and its potential prognostic value in penile carcinomas. We also showed a specific genomic profile according to HPV infection, supporting the hypothesis that penile tumors present distinct etiologies according to virus status. ©2014 American Association for Cancer Research.

  16. Assessment of leisure-time physical activity for the prediction of inflammatory status and cardiometabolic profile.

    PubMed

    Pires, Milena Monfort; Salvador, Emanuel P; Siqueira-Catania, Antonela; Folchetti, Luciana D; Cezaretto, Adriana; Ferreira, Sandra Roberta G

    2012-11-01

    Associations of leisure-time physical activity (LTPA), commuting and total physical activity with inflammatory markers, insulin resistance and metabolic profile in individuals at high cardiometabolic risk were investigated. This was a cross-sectional study. A total of 193 prediabetic adults were compared according to physical activity levels measured by the international physical activity questionnaire; p for trend and logistic regression was employed. The most active subset showed lower BMI and abdominal circumference, reaching significance only for LTPA (p for trend=0.02). Lipid profile improved with increased physical activity levels. Interleukin-6 decreased with increased total physical activity and LTPA (p for trend=0.02 and 0.03, respectively), while adiponectin increased in more active subsets for LTPA (p for trend=0.03). Elevation in adjusted OR for hypercholesterolemia was significant for lower LTPA durations (p for trend=0.04). High apolipoprotein B/apolipoprotein A ratio was inversely associated with LTPA, commuting and total physical activity. Increase in adjusted OR for insulin resistance was found from the highest to the lowest category of LTPA (p for trend=0.04) but significance disappeared after adjustments for BMI and energy intake. No association of increased C-reactive protein with physical activity domains was observed. In general, the associations of LTPA, but not commuting or total physical activity, with markers of cardiometabolic risk reinforces the importance of initiatives to increase this domain in programs for the prevention of lifestyle-related diseases. Copyright © 2012 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

  17. Late-Onset Alzheimer's Disease Polygenic Risk Profile Score Predicts Hippocampal Function.

    PubMed

    Xiao, Ena; Chen, Qiang; Goldman, Aaron L; Tan, Hao Yang; Healy, Kaitlin; Zoltick, Brad; Das, Saumitra; Kolachana, Bhaskar; Callicott, Joseph H; Dickinson, Dwight; Berman, Karen F; Weinberger, Daniel R; Mattay, Venkata S

    2017-11-01

    We explored the cumulative effect of several late-onset Alzheimer's disease (LOAD) risk loci using a polygenic risk profile score (RPS) approach on measures of hippocampal function, cognition, and brain morphometry. In a sample of 231 healthy control subjects (19-55 years of age), we used an RPS to study the effect of several LOAD risk loci reported in a recent meta-analysis on hippocampal function (determined by its engagement with blood oxygen level-dependent functional magnetic resonance imaging during episodic memory) and several cognitive metrics. We also studied effects on brain morphometry in an overlapping sample of 280 subjects. There was almost no significant association of LOAD-RPS with cognitive or morphometric measures. However, there was a significant negative relationship between LOAD-RPS and hippocampal function (familywise error [small volume correction-hippocampal region of interest] p < .05). There were also similar associations for risk score based on APOE haplotype, and for a combined LOAD-RPS + APOE haplotype risk profile score (p < .05 familywise error [small volume correction-hippocampal region of interest]). Of the 29 individual single nucleotide polymorphisms used in calculating LOAD-RPS, variants in CLU, PICALM, BCL3, PVRL2, and RELB showed strong effects (p < .05 familywise error [small volume correction-hippocampal region of interest]) on hippocampal function, though none survived further correction for the number of single nucleotide polymorphisms tested. There is a cumulative deleterious effect of LOAD risk genes on hippocampal function even in healthy volunteers. The effect of LOAD-RPS on hippocampal function in the relative absence of any effect on cognitive and morphometric measures is consistent with the reported temporal characteristics of LOAD biomarkers with the earlier manifestation of synaptic dysfunction before morphometric and cognitive changes. Copyright © 2017 Society of Biological Psychiatry. All rights reserved.

  18. Insights on wood combustion generated proinflammatory ultrafine particles (UFP).

    PubMed

    Corsini, Emanuela; Ozgen, Senem; Papale, Angela; Galbiati, Valentina; Lonati, Giovanni; Fermo, Paola; Corbella, Lorenza; Valli, Gianluigi; Bernardoni, Vera; Dell'Acqua, Manuela; Becagli, Silvia; Caruso, Donatella; Vecchi, Roberta; Galli, Corrado L; Marinovich, Marina

    2017-01-15

    This study aimed to collect, characterize ultrafine particles (UFP) generated from the combustion of wood pellets and logs (softwood and hardwood) and to evaluate their pro-inflammatory effects in THP-1 and A549 cells. Both cell lines responded to UFP producing interleukin-8 (IL-8), with wood log UFP being more active compared to pellet UFP. With the exception of higher effect observed with beech wood log UFP in THP-1, the ability of soft or hard woods to induce IL-8 release was similar. In addition, on weight mass, IL-8 release was similar or lower compared to diesel exhaust particles (DEP), arguing against higher biological activity of smaller size particles. UFP-induced IL-8 could be reduced by SB203580, indicating a role of p38MAPK activation in IL-8 production. The higher activity of beech wood log UFP in THP-1 was not due to higher uptake or endotoxin contamination. Qualitatively different protein adsorption profiles were observed, with less proteins bound to beech UFP compared to conifer UFP or DEP, which may provide higher intracellular availability of bioactive components, i.e. levoglucosan and galactosan, toward which THP-1 were more responsive compared to A549 cells. These results contribute to our understanding of particles emitted by domestic appliances and their biological effects. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  19. High-Throughput Gene Expression Profiles to Define Drug Similarity and Predict Compound Activity.

    PubMed

    De Wolf, Hans; Cougnaud, Laure; Van Hoorde, Kirsten; De Bondt, An; Wegner, Joerg K; Ceulemans, Hugo; Göhlmann, Hinrich

    2018-04-01

    By adding biological information, beyond the chemical properties and desired effect of a compound, uncharted compound areas and connections can be explored. In this study, we add transcriptional information for 31K compounds of Janssen's primary screening deck, using the HT L1000 platform and assess (a) the transcriptional connection score for generating compound similarities, (b) machine learning algorithms for generating target activity predictions, and (c) the scaffold hopping potential of the resulting hits. We demonstrate that the transcriptional connection score is best computed from the significant genes only and should be interpreted within its confidence interval for which we provide the stats. These guidelines help to reduce noise, increase reproducibility, and enable the separation of specific and promiscuous compounds. The added value of machine learning is demonstrated for the NR3C1 and HSP90 targets. Support Vector Machine models yielded balanced accuracy values ≥80% when the expression values from DDIT4 & SERPINE1 and TMEM97 & SPR were used to predict the NR3C1 and HSP90 activity, respectively. Combining both models resulted in 22 new and confirmed HSP90-independent NR3C1 inhibitors, providing two scaffolds (i.e., pyrimidine and pyrazolo-pyrimidine), which could potentially be of interest in the treatment of depression (i.e., inhibiting the glucocorticoid receptor (i.e., NR3C1), while leaving its chaperone, HSP90, unaffected). As such, the initial hit rate increased by a factor 300, as less, but more specific chemistry could be screened, based on the upfront computed activity predictions.

  20. Vertical Ozone Concentration Profiles in the Middle East: WRF-Chem Predictions vs. Balloon Measurements

    NASA Astrophysics Data System (ADS)

    Fountoukis, C.; Ayoub, M.; Ackermann, L.; Gladich, I.; Hoehn, R.

    2017-12-01

    The greater Middle Eastern area is made up by more than 20 countries with over 400 million inhabitants. Due to extensive land conversion, intense industrialization and rapid urban population growth in recent years, the region's air quality is changing. High ozone levels affected by free tropospheric subsidence, long range transport and local production in large metropolitan areas of the region are of major concern. In this study we analyze data from i) continuously (24/7) operated ground monitoring stations, and ii) an ozonesonde station, operated in Doha by the Qatar Environment and Energy Research Institute coupled with simulations using a three-dimensional regional air quality model (WRF-Chem). Ozonesondes were launched at 1300 LT (1000 UTC) weekly during a summertime month (August 2015) representative of extremely hot and humid atmospheric conditions and a wintertime period (January/February 2016) of cool and dry conditions in the area. This is the first application of WRF-Chem in the Middle East focusing on vertical ozone concentrations on the lower troposphere (0 - 6 km) combined with high frequency vertical measurement (balloon) data. A triple nested model configuration has been selected with high spatial resolution over the domain of interest (2 × 2 km2). We examine different meteorological regimes and test the sensitivity of model predictions to planetary boundary layer parameterizations. Comparison of model predictions against observations show high correlation coefficients and encouragingly low biases in all meteorological variables. During wintertime, ozone is overall well predicted (Fractional Bias = -0.1) while the summertime comparison is more challenging. We suggest that the YSU scheme is more representative of the region and should be the scheme of choice in future WRF-Chem applications in the Middle East. Furthermore, we highlight the importance of revising the available anthropogenic emission inventory to account rapidly-changing urban

  1. Therapeutic profile of single-fraction radiosurgery of vestibular schwannoma: unrelated malignancy predicts tumor control

    PubMed Central

    Wowra, Berndt; Muacevic, Alexander; Fürweger, Christoph; Schichor, Christian; Tonn, Jörg-Christian

    2012-01-01

    Radiosurgery has become an accepted treatment option for vestibular schwannomas. Nevertheless, predictors of tumor control and treatment toxicity in current radiosurgery of vestibular schwannomas are not well understood. To generate new information on predictors of tumor control and cranial nerve toxicity of single-fraction radiosurgery of vestibular schwannomas, we conducted a single-institution long-term observational study of radiosurgery for sporadic vestibular schwannomas. Minimum follow-up was 3 years. Investigated as potential predictors of tumor control and cranial nerve toxicity were treatment technology; tumor resection preceding radiosurgery; tumor size; gender; patient age; history of cancer, vascular disease, or metabolic disease; tumor volume; radiosurgical prescription dose; and isodose line. Three hundred eighty-six patients met inclusion criteria. Treatment failure was observed in 27 patients. History of unrelated cancer (strongest predictor) and prescription dose significantly predicted tumor control. The cumulative incidence of treatment failure was 30% after 6.5 years in patients with unrelated malignancy and 10% after ≥15 years in patients without such cancer (P < .02). Tumor volume was the only predictor of trigeminal neuropathy (observed in 6 patients). No predictor of facial nerve toxicity was found. On the House and Brackmann scale, 1 patient had a permanent one-level drop and 7 a transient drop of 1 to 3 levels. Serviceable hearing was preserved in 75.1%. Tumor hearing before radiosurgery, recurrence, and prescription isodose predicted ototoxicity. Unrelated malignancy is a strong predictor of tumor control. Tumor recurrence predominantly predicts ototoxicity. These findings potentially will aid future clinical decision making in ambiguous cases. PMID:22561798

  2. Proinflammatory cytokines oppose opioid induced acute and chronic analgesia

    PubMed Central

    Hutchinson, Mark R.; Coats, Benjamen D.; Lewis, Susannah S.; Zhang, Yingning; Sprunger, David B.; Rezvani, Niloofar; Baker, Eric M.; Jekich, Brian M.; Wieseler, Julie L.; Somogyi, Andrew A.; Martin, David; Poole, Stephen; Judd, Charles M.; Maier, Steven F.; Watkins, Linda R.

    2008-01-01

    Spinal proinflammatory cytokines are powerful pain-enhancing signals that contribute to pain following peripheral nerve injury (neuropathic pain). Recently, one proinflammatory cytokine, interleukin-1, was also implicated in the loss of analgesia upon repeated morphine exposure (tolerance). In contrast to prior literature, we demonstrate that the action of several spinal proinflammatory cytokines oppose systemic and intrathecal opioid analgesia, causing reduced pain suppression. In vitro morphine exposure of lumbar dorsal spinal cord caused significant increases in proinflammatory cytokine and chemokine release. Opposition of analgesia by proinflammatory cytokines is rapid, occurring ≤5 minutes after intrathecal (perispinal) opioid administration. We document that opposition of analgesia by proinflammatory cytokines cannot be accounted for by an alteration in spinal morphine concentrations. The acute anti-analgesic effects of proinflammatory cytokines occur in a p38 mitogen-activated protein kinase and nitric oxide dependent fashion. Chronic intrathecal morphine or methadone significantly increased spinal glial activation (toll-like receptor 4 mRNA and protein) and the expression of multiple chemokines and cytokines, combined with development of analgesic tolerance and pain enhancement (hyperalgesia, allodynia). Statistical analysis demonstrated that a cluster of cytokines and chemokines was linked with pain-related behavioral changes. Moreover, blockade of spinal proinflammatory cytokines during a stringent morphine regimen previously associated with altered neuronal function also attenuated enhanced pain, supportive that proinflammatory cytokines are importantly involved in tolerance induced by such regimens. These data implicate multiple opioid-induced spinal proinflammatory cytokines in opposing both acute and chronic opioid analgesia, and provide a novel mechanism for the opposition of acute opioid analgesia. PMID:18599265

  3. Volatile profile analysis and quality prediction of Longjing tea (Camellia sinensis) by HS-SPME/GC-MS

    PubMed Central

    Lin, Jie; Dai, Yi; Guo, Ya-nan; Xu, Hai-rong; Wang, Xiao-chang

    2012-01-01

    This study aimed to analyze the volatile chemical profile of Longjing tea, and further develop a prediction model for aroma quality of Longjing tea based on potent odorants. A total of 21 Longjing samples were analyzed by headspace solid phase microextraction (HS-SPME) coupled with gas chromatography-mass spectrometry (GC-MS). Pearson’s linear correlation analysis and partial least square (PLS) regression were applied to investigate the relationship between sensory aroma scores and the volatile compounds. Results showed that 60 volatile compounds could be commonly detected in this famous green tea. Terpenes and esters were two major groups characterized, representing 33.89% and 15.53% of the total peak area respectively. Ten compounds were determined to contribute significantly to the perceived aroma quality of Longjing tea, especially linalool (0.701), nonanal (0.738), (Z)-3-hexenyl hexanoate (−0.785), and β-ionone (−0.763). On the basis of these 10 compounds, a model (correlation coefficient of 89.4% and cross-validated correlation coefficient of 80.4%) was constructed to predict the aroma quality of Longjing tea. Summarily, this study has provided a novel option for quality prediction of green tea based on HS-SPME/GC-MS technique. PMID:23225852

  4. Transcriptome profiles in sarcoidosis and their potential role in disease prediction.

    PubMed

    Schupp, Jonas C; Vukmirovic, Milica; Kaminski, Naftali; Prasse, Antje

    2017-09-01

    Sarcoidosis is a systemic disease defined by the presence of nonnecrotizing granuloma in the absence of any known cause. Although the heterogeneity of sarcoidosis is well characterized clinically, the transcriptome of sarcoidosis and underlying molecular mechanisms are not. The signal of all transcripts, small and long noncoding RNAs, can be detected using microarrays or RNA-Sequencing. Analyzing the transcriptome of tissues that are directly affected by granulomas is of great importance to understand biology of the disease and may be predictive of disease and treatment outcome. Multiple genome wide expression studies performed on sarcoidosis affected tissues were published in the last 11 years. Published studies focused on differences in gene expression between sarcoidosis vs. control tissues, stable vs. progressive sarcoidosis, as well as sarcoidosis vs. other diseases. Strikingly, all these transcriptomics data confirm the key role of TH1 immune response in sarcoidosis and particularly of interferon-γ (IFN-γ) and type I IFN-driven signaling pathways. The steps toward transcriptomics of sarcoidosis in precision medicine highlight the potentials of this approach. Large prospective follow-up studies are required to identify signatures predictive of disease progression and outcome.

  5. Religious Participation Predicts Diurnal Cortisol Profiles 10 Years Later via Lower Levels of Religious Struggle

    PubMed Central

    Tobin, Erin T.; Slatcher, Richard B.

    2016-01-01

    Objective Multiple aspects of religion have been linked with a variety of physical health outcomes; however, rarely have investigators attempted to empirically test the mechanisms through which religiosity impacts health. The links between religious participation, religious coping, and diurnal cortisol patterns over a 10-year period in a national sample of adults in the United States were investigated. Method Participants included 1,470 respondents from the Midlife in the United States (MIDUS) study who provided reports on religious participation, religious coping, and diurnal cortisol. Results Religious participation predicted steeper (“healthier”) cortisol slopes at the 10-year follow-up, controlling for potential confounds. Further, religious struggle (religious coping marked by tension and strain about religious and spiritual issues) mediated the prospective association between religious participation and cortisol slope, such that greater religious attendance predicted lower levels of religious struggle 10 years later, which in turn was linked with a steeper cortisol slope; this effect remained strong when controlling for general emotional coping and social support. Positive religious coping was unrelated to diurnal cortisol patterns. Conclusion These findings identify religious struggle as a mechanism through which religious participation impacts diurnal cortisol levels and suggest that diurnal cortisol is a plausible pathway through which aspects of religion influence long-term physical health. PMID:27280366

  6. Prediction of conversion from mild cognitive impairment to dementia with neuronally derived blood exosome protein profile.

    PubMed

    Winston, Charisse N; Goetzl, Edward J; Akers, Johnny C; Carter, Bob S; Rockenstein, Edward M; Galasko, Douglas; Masliah, Eliezer; Rissman, Robert A

    2016-01-01

    Levels of Alzheimer's disease (AD)-related proteins in plasma neuronal derived exosomes (NDEs) were quantified to identify biomarkers for prediction and staging of mild cognitive impairment (MCI) and AD. Plasma exosomes were extracted, precipitated, and enriched for neuronal source by anti-L1CAM antibody absorption. NDEs were characterized by size (Nanosight) and shape (TEM) and extracted NDE protein biomarkers were quantified by ELISAs. Plasma NDE cargo was injected into normal mice, and results were characterized by immunohistochemistry to determine pathogenic potential. Plasma NDE levels of P-T181-tau, P-S396-tau, and Aβ1-42 were significantly higher, whereas those of neurogranin (NRGN) and the repressor element 1-silencing transcription factor (REST) were significantly lower in AD and MCI converting to AD (ADC) patients compared to cognitively normal controls (CNC) subjects and stable MCI patients. Mice injected with plasma NDEs from ADC patients displayed increased P-tau (PHF-1 antibody)-positive cells in the CA1 region of the hippocampus compared to plasma NDEs from CNC and stable MCI patients. Abnormal plasma NDE levels of P-tau, Aβ1-42, NRGN, and REST accurately predict conversion of MCI to AD dementia. Plasma NDEs from demented patients seeded tau aggregation and induced AD-like neuropathology in normal mouse CNS.

  7. Predicting Drug-Target Interactions for New Drug Compounds Using a Weighted Nearest Neighbor Profile.

    PubMed

    van Laarhoven, Twan; Marchiori, Elena

    2013-01-01

    In silico discovery of interactions between drug compounds and target proteins is of core importance for improving the efficiency of the laborious and costly experimental determination of drug-target interaction. Drug-target interaction data are available for many classes of pharmaceutically useful target proteins including enzymes, ion channels, GPCRs and nuclear receptors. However, current drug-target interaction databases contain a small number of drug-target pairs which are experimentally validated interactions. In particular, for some drug compounds (or targets) there is no available interaction. This motivates the need for developing methods that predict interacting pairs with high accuracy also for these 'new' drug compounds (or targets). We show that a simple weighted nearest neighbor procedure is highly effective for this task. We integrate this procedure into a recent machine learning method for drug-target interaction we developed in previous work. Results of experiments indicate that the resulting method predicts true interactions with high accuracy also for new drug compounds and achieves results comparable or better than those of recent state-of-the-art algorithms. Software is publicly available at http://cs.ru.nl/~tvanlaarhoven/drugtarget2013/.

  8. White matter maturation profiles through early childhood predict general cognitive ability.

    PubMed

    Deoni, Sean C L; O'Muircheartaigh, Jonathan; Elison, Jed T; Walker, Lindsay; Doernberg, Ellen; Waskiewicz, Nicole; Dirks, Holly; Piryatinsky, Irene; Dean, Doug C; Jumbe, N L

    2016-03-01

    Infancy and early childhood are periods of rapid brain development, during which brain structure and function mature alongside evolving cognitive ability. An important neurodevelopmental process during this postnatal period is the maturation of the myelinated white matter, which facilitates rapid communication across neural systems and networks. Though prior brain imaging studies in children (4 years of age and above), adolescents, and adults have consistently linked white matter development with cognitive maturation and intelligence, few studies have examined how these processes are related throughout early development (birth to 4 years of age). Here, we show that the profile of white matter myelination across the first 5 years of life is strongly and specifically related to cognitive ability. Using a longitudinal design, coupled with advanced magnetic resonance imaging, we demonstrate that children with above-average ability show differential trajectories of myelin development compared to average and below average ability children, even when controlling for socioeconomic status, gestation, and birth weight. Specifically, higher ability children exhibit slower but more prolonged early development, resulting in overall increased myelin measures by ~3 years of age. These results provide new insight into the early neuroanatomical correlates of cognitive ability, and suggest an early period of prolonged maturation with associated protracted white matter plasticity may result in strengthened neural networks that can better support later development. Further, these results reinforce the necessity of a longitudinal perspective in investigating typical or suspected atypical cognitive maturation.

  9. Use of life course work-family profiles to predict mortality risk among US women.

    PubMed

    Sabbath, Erika L; Guevara, Ivan Mejía; Glymour, M Maria; Berkman, Lisa F

    2015-04-01

    We examined relationships between US women's exposure to midlife work-family demands and subsequent mortality risk. We used data from women born 1935 to 1956 in the Health and Retirement Study to calculate employment, marital, and parenthood statuses for each age between 16 and 50 years. We used sequence analysis to identify 7 prototypical work-family trajectories. We calculated age-standardized mortality rates and hazard ratios (HRs) for mortality associated with work-family sequences, with adjustment for covariates and potentially explanatory later-life factors. Married women staying home with children briefly before reentering the workforce had the lowest mortality rates. In comparison, after adjustment for age, race/ethnicity, and education, HRs for mortality were 2.14 (95% confidence interval [CI] = 1.58, 2.90) among single nonworking mothers, 1.48 (95% CI = 1.06, 1.98) among single working mothers, and 1.36 (95% CI = 1.02, 1.80) among married nonworking mothers. Adjustment for later-life behavioral and economic factors partially attenuated risks. Sequence analysis is a promising exposure assessment tool for life course research. This method permitted identification of certain lifetime work-family profiles associated with mortality risk before age 75 years.

  10. Use of Life Course Work–Family Profiles to Predict Mortality Risk Among US Women

    PubMed Central

    Guevara, Ivan Mejía; Glymour, M. Maria; Berkman, Lisa F.

    2015-01-01

    Objectives. We examined relationships between US women’s exposure to midlife work–family demands and subsequent mortality risk. Methods. We used data from women born 1935 to 1956 in the Health and Retirement Study to calculate employment, marital, and parenthood statuses for each age between 16 and 50 years. We used sequence analysis to identify 7 prototypical work–family trajectories. We calculated age-standardized mortality rates and hazard ratios (HRs) for mortality associated with work–family sequences, with adjustment for covariates and potentially explanatory later-life factors. Results. Married women staying home with children briefly before reentering the workforce had the lowest mortality rates. In comparison, after adjustment for age, race/ethnicity, and education, HRs for mortality were 2.14 (95% confidence interval [CI] = 1.58, 2.90) among single nonworking mothers, 1.48 (95% CI = 1.06, 1.98) among single working mothers, and 1.36 (95% CI = 1.02, 1.80) among married nonworking mothers. Adjustment for later-life behavioral and economic factors partially attenuated risks. Conclusions. Sequence analysis is a promising exposure assessment tool for life course research. This method permitted identification of certain lifetime work–family profiles associated with mortality risk before age 75 years. PMID:25713976

  11. Predicting the oral pharmacokinetic profiles of multiple-unit (pellet) dosage forms using a modeling and simulation approach coupled with biorelevant dissolution testing: case example diclofenac sodium.

    PubMed

    Kambayashi, Atsushi; Blume, Henning; Dressman, Jennifer B

    2014-07-01

    The objective of this research was to characterize the dissolution profile of a poorly soluble drug, diclofenac, from a commercially available multiple-unit enteric coated dosage form, Diclo-Puren® capsules, and to develop a predictive model for its oral pharmacokinetic profile. The paddle method was used to obtain the dissolution profiles of this dosage form in biorelevant media, with the exposure to simulated gastric conditions being varied in order to simulate the gastric emptying behavior of pellets. A modified Noyes-Whitney theory was subsequently fitted to the dissolution data. A physiologically-based pharmacokinetic (PBPK) model for multiple-unit dosage forms was designed using STELLA® software and coupled with the biorelevant dissolution profiles in order to simulate the plasma concentration profiles of diclofenac from Diclo-Puren® capsule in both the fasted and fed state in humans. Gastric emptying kinetics relevant to multiple-units pellets were incorporated into the PBPK model by setting up a virtual patient population to account for physiological variations in emptying kinetics. Using in vitro biorelevant dissolution coupled with in silico PBPK modeling and simulation it was possible to predict the plasma profile of this multiple-unit formulation of diclofenac after oral administration in both the fasted and fed state. This approach might be useful to predict variability in the plasma profiles for other drugs housed in multiple-unit dosage forms. Copyright © 2014 Elsevier B.V. All rights reserved.

  12. Microbial forensics: predicting phenotypic characteristics and environmental conditions from large-scale gene expression profiles.

    PubMed

    Kim, Minseung; Zorraquino, Violeta; Tagkopoulos, Ilias

    2015-03-01

    A tantalizing question in cellular physiology is whether the cellular state and environmental conditions can be inferred by the expression signature of an organism. To investigate this relationship, we created an extensive normalized gene expression compendium for the bacterium Escherichia coli that was further enriched with meta-information through an iterative learning procedure. We then constructed an ensemble method to predict environmental and cellular state, including strain, growth phase, medium, oxygen level, antibiotic and carbon source presence. Results show that gene expression is an excellent predictor of environmental structure, with multi-class ensemble models achieving balanced accuracy between 70.0% (±3.5%) to 98.3% (±2.3%) for the various characteristics. Interestingly, this performance can be significantly boosted when environmental and strain characteristics are simultaneously considered, as a composite classifier that captures the inter-dependencies of three characteristics (medium, phase and strain) achieved 10.6% (±1.0%) higher performance than any individual models. Contrary to expectations, only 59% of the top informative genes were also identified as differentially expressed under the respective conditions. Functional analysis of the respective genetic signatures implicates a wide spectrum of Gene Ontology terms and KEGG pathways with condition-specific information content, including iron transport, transferases, and enterobactin synthesis. Further experimental phenotypic-to-genotypic mapping that we conducted for knock-out mutants argues for the information content of top-ranked genes. This work demonstrates the degree at which genome-scale transcriptional information can be predictive of latent, heterogeneous and seemingly disparate phenotypic and environmental characteristics, with far-reaching applications.

  13. Maternal cytokine profiles during pregnancy predict asthma in children of nonasthmatic mothers.

    PubMed

    Rothers, Janet; Stern, Debra A; Lohman, I Carla; Spangenberg, Amber; Wright, Anne L; DeVries, Avery; Vercelli, Donata; Halonen, Marilyn

    2018-06-04

    Little is known about whether maternal immune status during pregnancy influences asthma development in the child. We measured cytokine production in supernatants from mitogen-stimulated peripheral blood immune cells collected during and after pregnancy from the mothers of children enrolled in the Tucson Infant Immune Study, a non-selected birth cohort. Physician-diagnosed active asthma in children through age 9 and a history of asthma in their mothers were assessed through questionnaires. Maternal production of each of the cytokines IL-13, IL-4, IL-5, IFN-γ, IL-10, and IL-17 during pregnancy was unrelated to childhood asthma. However, IFN-γ/IL-13 and IFN-γ/IL-4 ratios during pregnancy were associated with decreased in risk of childhood asthma (N=381; OR=0.33; 95%CI=0.17-0.66, p=0.002 and N=368; OR=0.36; 95%CI=0.18-0.71, p=0.003, respectively). The inverse relations of these two ratios with childhood asthma were only evident in nonasthmatic mothers ( N=309; OR=0.18; 95% CI=0.08-0.42, p=0.00007 and N=299; OR=0.17; 95% CI=0.07-0.39, p=0.00003, respectively) and not in asthmatic mother (N=72 and 69, respectively; p for interaction by maternal asthma=0.036 and 0.002, respectively). Paternal cytokine ratios were unrelated to childhood asthma. Maternal cytokine ratios in nonasthmatic mothers were unrelated to the child's skin test reactivity, total IgE, physician-confirmed allergic rhinitis at age 5, or eczema in infancy. To our knowledge this study provides the first evidence that cytokine profiles in pregnant nonasthmatic mothers relate to risk for childhood asthma but not allergy and suggests a process of asthma development that begins in utero and is independent of allergy.

  14. Analysis and Prediction of the Billet Butt and Transverse Weld in the Continuous Extrusion Process of a Hollow Aluminum Profile

    NASA Astrophysics Data System (ADS)

    Lou, Shumei; Wang, Yongxiao; Liu, Chuanxi; Lu, Shuai; Liu, Sujun; Su, Chunjian

    2017-08-01

    In continuous extrusions of aluminum profiles, the thickness of the billet butt and the length of the discarded extrudate containing the transverse weld play key roles in reducing material loss and improving product quality. The formation and final distribution of the billet butt and transverse weld depend entirely on the flow behavior of the billet skin material. This study examined the flow behavior of the billet skin material as well as the formation and evolution of the billet butt and the transverse weld in detail through numerical simulation and a series of experiments. In practical extrusions, even if the billet skin is removed by lathe turning shortly before extrusion, billet skin impurities are still distributed around the transverse weld and in the billet butt. The thickness of the scrap billet butt and the length of the discarded extrudate containing the transverse weld can be exactly predicted via simulation.

  15. Lyα Profile, Dust, and Prediction of Lyα Escape Fraction in Green Pea Galaxies

    NASA Astrophysics Data System (ADS)

    Yang, Huan; Malhotra, Sangeeta; Gronke, Max; Rhoads, James E.; Leitherer, Claus; Wofford, Aida; Jiang, Tianxing; Dijkstra, Mark; Tilvi, V.; Wang, Junxian

    2017-08-01

    We studied Lyman-α (Lyα) escape in a statistical sample of 43 Green Peas with HST/COS Lyα spectra. Green Peas are nearby star-forming galaxies with strong [O III]λ5007 emission lines. Our sample is four times larger than the previous sample and covers a much more complete range of Green Pea properties. We found that about two-thirds of Green Peas are strong Lyα line emitters with rest-frame Lyα equivalent width > 20 \\mathringA . The Lyα profiles of Green Peas are diverse. The Lyα escape fraction, defined as the ratio of observed Lyα flux to intrinsic Lyα flux, shows anti-correlations with a few Lyα kinematic features—both the blue peak and red peak velocities, the peak separations, and the FWHM of the red portion of the Lyα profile. Using properties measured from Sloan Digital Sky Survey optical spectra, we found many correlations—the Lyα escape fraction generally increases at lower dust reddening, lower metallicity, lower stellar mass, and higher [O III]/[O II] ratio. We fit their Lyα profiles with the H I shell radiative transfer model and found that the Lyα escape fraction is anti-correlated with the best-fit N H I . Finally, we fit an empirical linear relation to predict {f}{esc}{Lyα } from the dust extinction and Lyα red peak velocity. The standard deviation of this relation is about 0.3 dex. This relation can be used to isolate the effect of intergalactic medium (IGM) scatterings from Lyα escape and to probe the IGM optical depth along the line of sight of each z> 7 Lyα emission-line galaxy in the James Webb Space Telescope era.

  16. PROSPECT improves cis-acting regulatory element prediction by integrating expression profile data with consensus pattern searches

    PubMed Central

    Fujibuchi, Wataru; Anderson, John S. J.; Landsman, David

    2001-01-01

    Consensus pattern and matrix-based searches designed to predict cis-acting transcriptional regulatory sequences have historically been subject to large numbers of false positives. We sought to decrease false positives by incorporating expression profile data into a consensus pattern-based search method. We have systematically analyzed the expression phenotypes of over 6000 yeast genes, across 121 expression profile experiments, and correlated them with the distribution of 14 known regulatory elements over sequences upstream of the genes. Our method is based on a metric we term probabilistic element assessment (PEA), which is a ranking of potential sites based on sequence similarity in the upstream regions of genes with similar expression phenotypes. For eight of the 14 known elements that we examined, our method had a much higher selectivity than a naïve consensus pattern search. Based on our analysis, we have developed a web-based tool called PROSPECT, which allows consensus pattern-based searching of gene clusters obtained from microarray data. PMID:11574681

  17. Aerodynamic and acoustic investigation of inverted velocity profile coannular exhaust nozzle models and development of aerodynamic and acoustic prediction procedures

    NASA Technical Reports Server (NTRS)

    Larson, R. S.; Nelson, D. P.; Stevens, B. S.

    1979-01-01

    Five co-annular nozzle models, covering a systematic variation of nozzle geometry, were tested statically over a range of exhaust conditions including inverted velocity profile (IVP) (fan to primary stream velocity ratio 1) and non IVP profiles. Fan nozzle pressure ratio (FNPR) was varied from 1.3 to 4.1 at primary nozzle pressure ratios (PNPR) of 1.53 and 2.0. Fan stream temperatures of 700 K (1260 deg R) and 1089 K(1960 deg R) were tested with primary stream temperatures of 700 K (1260 deg R), 811 K (1460 deg R), and 1089 K (1960 deg R). At fan and primary stream velocities of 610 and 427 m/sec (2000 and 1400 ft/sec), respectively, increasing fan radius ratio from 0.69 to 0.83 reduced peak perceived noise level (PNL) 3 dB, and an increase in primary radius ratio from 0 to 0.81 (fan radius ratio constant at 0.83) reduced peak PNL an additional 1.0 dB. There were no noise reductions at a fan stream velocity of 853 m/sec (2800 ft/sec). Increasing fan radius ratio from 0.69 to 0.83 reduced nozzle thrust coefficient 1.2 to 1.5% at a PNPR of 1.53, and 1.7 to 2.0% at a PNPR of 2.0. The developed acoustic prediction procedure collapsed the existing data with standard deviation varying from + or - 8 dB to + or - 7 dB. The aerodynamic performance prediction procedure collapsed thrust coefficient measurements to within + or - .004 at a FNPR of 4.0 and a PNPR of 2.0.

  18. Genetic risk profiling and gene signature modeling to predict risk of complications after IPAA.

    PubMed

    Sehgal, Rishabh; Berg, Arthur; Polinski, Joseph I; Hegarty, John P; Lin, Zhenwu; McKenna, Kevin J; Stewart, David B; Poritz, Lisa S; Koltun, Walter A

    2012-03-01

    Severe pouchitis and Crohn's disease-like complications are 2 adverse postoperative complications that confound the success of the IPAA in patients with ulcerative colitis. To date, approximately 83 single nucleotide polymorphisms within 55 genes have been associated with IBD. The aim of this study was to identify single-nucleotide polymorphisms that correlate with complications after IPAA that could be utilized in a gene signature fashion to predict postoperative complications and aid in preoperative surgical decision making. One hundred forty-two IPAA patients were retrospectively classified as "asymptomatic" (n = 104, defined as no Crohn's disease-like complications or severe pouchitis for at least 2 years after IPAA) and compared with a "severe pouchitis" group (n = 12, ≥ 4 episodes pouchitis per year for 2 years including the need for long-term therapy to maintain remission) and a "Crohn's disease-like" group (n = 26, presence of fistulae, pouch inlet stricture, proximal small-bowel disease, or pouch granulomata, occurring at least 6 months after surgery). Genotyping for 83 single-nucleotide polymorphisms previously associated with Crohn's disease and/or ulcerative colitis was performed on a customized Illumina genotyping platform. The top 2 single-nucleotide polymorphisms statistically identified as being independently associated with each of Crohn's disease-like and severe pouchitis were used in a multivariate logistic regression model. These single-nucleotide polymorphisms were then used to create probability equations to predict overall chance of a positive or negative outcome for that complication. The top 2 single-nucleotide polymorphisms for Crohn's disease-like complications were in the 10q21 locus and the gene for PTGER4 (p = 0.006 and 0.007), whereas for severe pouchitis it was NOD2 and TNFSF15 (p = 0.003 and 0.011). Probability equations suggested that the risk of these 2 complications greatly increased with increasing number of risk alleles

  19. Principal components derived from CSF inflammatory profiles predict outcome in survivors after severe traumatic brain injury.

    PubMed

    Kumar, Raj G; Rubin, Jonathan E; Berger, Rachel P; Kochanek, Patrick M; Wagner, Amy K

    2016-03-01

    Studies have characterized absolute levels of multiple inflammatory markers as significant risk factors for poor outcomes after traumatic brain injury (TBI). However, inflammatory marker concentrations are highly inter-related, and production of one may result in the production or regulation of another. Therefore, a more comprehensive characterization of the inflammatory response post-TBI should consider relative levels of markers in the inflammatory pathway. We used principal component analysis (PCA) as a dimension-reduction technique to characterize the sets of markers that contribute independently to variability in cerebrospinal (CSF) inflammatory profiles after TBI. Using PCA results, we defined groups (or clusters) of individuals (n=111) with similar patterns of acute CSF inflammation that were then evaluated in the context of outcome and other relevant CSF and serum biomarkers collected days 0-3 and 4-5 post-injury. We identified four significant principal components (PC1-PC4) for CSF inflammation from days 0-3, and PC1 accounted for the greatest (31%) percentage of variance. PC1 was characterized by relatively higher CSF sICAM-1, sFAS, IL-10, IL-6, sVCAM-1, IL-5, and IL-8 levels. Cluster analysis then defined two distinct clusters, such that individuals in cluster 1 had highly positive PC1 scores and relatively higher levels of CSF cortisol, progesterone, estradiol, testosterone, brain derived neurotrophic factor (BDNF), and S100b; this group also had higher serum cortisol and lower serum BDNF. Multinomial logistic regression analyses showed that individuals in cluster 1 had a 10.9 times increased likelihood of GOS scores of 2/3 vs. 4/5 at 6 months compared to cluster 2, after controlling for covariates. Cluster group did not discriminate between mortality compared to GOS scores of 4/5 after controlling for age and other covariates. Cluster groupings also did not discriminate mortality or 12 month outcomes in multivariate models. PCA and cluster analysis

  20. Comparison of ring-focus image profile with predictions for the AXAF VETA-I test

    NASA Technical Reports Server (NTRS)

    Zissa, David E.

    1993-01-01

    The X-ray test of the largest pair of nearly cylindrical mirrors for the Advanced X-ray Astrophysics Facility (AXAF) was completed in October 1991 at Marshall Space Flight Center. The test assembly was named the Verification Engineering Test Article I (VETA-I). The ring-focus portion of the test measured the imaging quality of azimuthal sections of VETA-I. This gives information about the core of the on-orbit image. The finite source distance, VETA-I mirror spacing, and VETA-I structural deformation caused the core of the image to be spread over a diameter of nearly 4 arc seconds at the VETA-I overall focus. The results of a preliminary analysis of the ring-focus data and the implications for the on-orbit image of the telescope are discussed. An upper limit for the on-orbit encircled-energy fraction at 1 arc second diameter was determined to be 0.82 at 0.277 keV X-ray energy. This assumes that the bottoms of the mirrors in the VETA-I arrangement are representative of the mirror surfaces and that the on-orbit system would be aligned using a combination of preliminary measurements and predictions for the mirror surface shapes.

  1. Molecular profiling of prostate cancer derived exosomes may reveal a predictive signature for response to docetaxel

    PubMed Central

    Kharaziha, Pedram; Chioureas, Dimitris; Rutishauser, Dorothea; Baltatzis, George; Lennartsson, Lena; Fonseca, Pedro; Azimi, Alireza; Hultenby, Kjell; Zubarev, Roman; Ullén, Anders; Yachnin, Jeffrey; Nilsson, Sten; Panaretakis, Theocharis

    2015-01-01

    Docetaxel is a cornerstone treatment for metastatic, castration resistant prostate cancer (CRPC) which remains a leading cause of cancer-related deaths, worldwide. The clinical usage of docetaxel has resulted in modest gains in survival, primarily due to the development of resistance. There are currently no clinical biomarkers available that predict whether a CRPC patient will respond or acquire resistance to this therapy. Comparative proteomics analysis of exosomes secreted from DU145 prostate cancer cells that are sensitive (DU145 Tax-Sen) or have acquired resistance (DU145 Tax-Res) to docetaxel, demonstrated significant differences in the amount of exosomes secreted and in their molecular composition. A panel of proteins was identified by proteomics to be differentially enriched in DU145 Tax-Res compared to DU145 Tax-Sen exosomes and was validated by western blotting. Importantly, we identified MDR-1, MDR-3, Endophilin-A2 and PABP4 that were enriched only in DU145 Tax-Res exosomes. We validated the presence of these proteins in the serum of a small cohort of patients. DU145 cells that have uptaken DU145 Tax-Res exosomes show properties of increased matrix degradation. In summary, exosomes derived from DU145 Tax-Res cells may be a valuable source of biomarkers for response to therapy. PMID:25844599

  2. Predicting clinical concussion measures at baseline based on motivation and academic profile.

    PubMed

    Trinidad, Katrina J; Schmidt, Julianne D; Register-Mihalik, Johna K; Groff, Diane; Goto, Shiho; Guskiewicz, Kevin M

    2013-11-01

    The purpose of this study was to predict baseline neurocognitive and postural control performance using a measure of motivation, high school grade point average (hsGPA), and Scholastic Aptitude Test (SAT) score. Cross-sectional. Clinical research center. Eighty-eight National Collegiate Athletic Association Division I incoming student-athletes (freshman and transfers). Participants completed baseline clinical concussion measures, including a neurocognitive test battery (CNS Vital Signs), a balance assessment [Sensory Organization Test (SOT)], and motivation testing (Rey Dot Counting). Participants granted permission to access hsGPA and SAT total score. Standard scores for each CNS Vital Signs domain and SOT composite score. Baseline motivation, hsGPA, and SAT explained a small percentage of the variance of complex attention (11%), processing speed (12%), and composite SOT score (20%). Motivation, hsGPA, and total SAT score do not explain a significant amount of the variance in neurocognitive and postural control measures but may still be valuable to consider when interpreting neurocognitive and postural control measures.

  3. Molecular profiling of prostate cancer derived exosomes may reveal a predictive signature for response to docetaxel.

    PubMed

    Kharaziha, Pedram; Chioureas, Dimitris; Rutishauser, Dorothea; Baltatzis, George; Lennartsson, Lena; Fonseca, Pedro; Azimi, Alireza; Hultenby, Kjell; Zubarev, Roman; Ullén, Anders; Yachnin, Jeffrey; Nilsson, Sten; Panaretakis, Theocharis

    2015-08-28

    Docetaxel is a cornerstone treatment for metastatic, castration resistant prostate cancer (CRPC) which remains a leading cause of cancer-related deaths, worldwide. The clinical usage of docetaxel has resulted in modest gains in survival, primarily due to the development of resistance. There are currently no clinical biomarkers available that predict whether a CRPC patient will respond or acquire resistance to this therapy. Comparative proteomics analysis of exosomes secreted from DU145 prostate cancer cells that are sensitive (DU145 Tax-Sen) or have acquired resistance (DU145 Tax-Res) to docetaxel, demonstrated significant differences in the amount of exosomes secreted and in their molecular composition. A panel of proteins was identified by proteomics to be differentially enriched in DU145 Tax-Res compared to DU145 Tax-Sen exosomes and was validated by western blotting. Importantly, we identified MDR-1, MDR-3, Endophilin-A2 and PABP4 that were enriched only in DU145 Tax-Res exosomes. We validated the presence of these proteins in the serum of a small cohort of patients. DU145 cells that have uptaken DU145 Tax-Res exosomes show properties of increased matrix degradation. In summary, exosomes derived from DU145 Tax-Res cells may be a valuable source of biomarkers for response to therapy.

  4. Dopamine Gene Profiling to Predict Impulse Control and Effects of Dopamine Agonist Ropinirole.

    PubMed

    MacDonald, Hayley J; Stinear, Cathy M; Ren, April; Coxon, James P; Kao, Justin; Macdonald, Lorraine; Snow, Barry; Cramer, Steven C; Byblow, Winston D

    2016-07-01

    Dopamine agonists can impair inhibitory control and cause impulse control disorders for those with Parkinson disease (PD), although mechanistically this is not well understood. In this study, we hypothesized that the extent of such drug effects on impulse control is related to specific dopamine gene polymorphisms. This double-blind, placebo-controlled study aimed to examine the effect of single doses of 0.5 and 1.0 mg of the dopamine agonist ropinirole on impulse control in healthy adults of typical age for PD onset. Impulse control was measured by stop signal RT on a response inhibition task and by an index of impulsive decision-making on the Balloon Analogue Risk Task. A dopamine genetic risk score quantified basal dopamine neurotransmission from the influence of five genes: catechol-O-methyltransferase, dopamine transporter, and those encoding receptors D1, D2, and D3. With placebo, impulse control was better for the high versus low genetic risk score groups. Ropinirole modulated impulse control in a manner dependent on genetic risk score. For the lower score group, both doses improved response inhibition (decreased stop signal RT) whereas the lower dose reduced impulsiveness in decision-making. Conversely, the higher score group showed a trend for worsened response inhibition on the lower dose whereas both doses increased impulsiveness in decision-making. The implications of the present findings are that genotyping can be used to predict impulse control and whether it will improve or worsen with the administration of dopamine agonists.

  5. Expression profiles of loneliness-associated genes for survival prediction in cancer patients.

    PubMed

    You, Liang-Fu; Yeh, Jia-Rong; Su, Mu-Chun

    2014-01-01

    Influence of loneliness on human survival has been established epidemiologically, but genomic research remains undeveloped. We identified 34 loneliness-associated genes which were statistically significant for high- lonely and low-lonely individuals. With the univariate Cox proportional hazards regression model, we obtained corresponding regression coefficients for loneliness-associated genes fo individual cancer patients. Furthermore, risk scores could be generated with the combination of gene expression level multiplied by corresponding regression coefficients of loneliness-associated genes. We verified that high-risk score cancer patients had shorter mean survival time than their low-risk score counterparts. Then we validated the loneliness-associated gene signature in three independent brain cancer cohorts with Kaplan-Meier survival curves (n=77, 85 and 191), significantly separable by log-rank test with hazard ratios (HR) >1 and p-values <0.0001 (HR=2.94, 3.82, and 1.78). Moreover, we validated the loneliness-associated gene signature in bone cancer (HR=5.10, p-value=4.69e-3), lung cancer (HR=2.86, p-value=4.71e-5), ovarian cancer (HR=1.97, p-value=3.11e-5), and leukemia (HR=2.06, p-value=1.79e-4) cohorts. The last lymphoma cohort proved to have an HR=3.50, p-value=1.15e-7. Loneliness- associated genes had good survival prediction for cancer patients, especially bone cancer patients. Our study provided the first indication that expression of loneliness-associated genes are related to survival time of cancer patients.

  6. Integrating Circadian Activity and Gene Expression Profiles to Predict Chronotoxicity of Drosophila suzukii Response to Insecticides

    PubMed Central

    Hamby, Kelly A.; Kwok, Rosanna S.; Zalom, Frank G.; Chiu, Joanna C.

    2013-01-01

    Native to Southeast Asia, Drosophila suzukii (Matsumura) is a recent invader that infests intact ripe and ripening fruit, leading to significant crop losses in the U.S., Canada, and Europe. Since current D. suzukii management strategies rely heavily on insecticide usage and insecticide detoxification gene expression is under circadian regulation in the closely related Drosophila melanogaster, we set out to determine if integrative analysis of daily activity patterns and detoxification gene expression can predict chronotoxicity of D. suzukii to insecticides. Locomotor assays were performed under conditions that approximate a typical summer or winter day in Watsonville, California, where D. suzukii was first detected in North America. As expected, daily activity patterns of D. suzukii appeared quite different between ‘summer’ and ‘winter’ conditions due to differences in photoperiod and temperature. In the ‘summer’, D. suzukii assumed a more bimodal activity pattern, with maximum activity occurring at dawn and dusk. In the ‘winter’, activity was unimodal and restricted to the warmest part of the circadian cycle. Expression analysis of six detoxification genes and acute contact bioassays were performed at multiple circadian times, but only in conditions approximating Watsonville summer, the cropping season, when most insecticide applications occur. Five of the genes tested exhibited rhythmic expression, with the majority showing peak expression at dawn (ZT0, 6am). We observed significant differences in the chronotoxicity of D. suzukii towards malathion, with highest susceptibility at ZT0 (6am), corresponding to peak expression of cytochrome P450s that may be involved in bioactivation of malathion. High activity levels were not found to correlate with high insecticide susceptibility as initially hypothesized. Chronobiology and chronotoxicity of D. suzukii provide valuable insights for monitoring and control efforts, because insect activity as well as

  7. Prediction of protein-protein interaction sites using electrostatic desolvation profiles.

    PubMed

    Fiorucci, Sébastien; Zacharias, Martin

    2010-05-19

    Protein-protein complex formation involves removal of water from the interface region. Surface regions with a small free energy penalty for water removal or desolvation may correspond to preferred interaction sites. A method to calculate the electrostatic free energy of placing a neutral low-dielectric probe at various protein surface positions has been designed and applied to characterize putative interaction sites. Based on solutions of the finite-difference Poisson equation, this method also includes long-range electrostatic contributions and the protein solvent boundary shape in contrast to accessible-surface-area-based solvation energies. Calculations on a large set of proteins indicate that in many cases (>90%), the known binding site overlaps with one of the six regions of lowest electrostatic desolvation penalty (overlap with the lowest desolvation region for 48% of proteins). Since the onset of electrostatic desolvation occurs even before direct protein-protein contact formation, it may help guide proteins toward the binding region in the final stage of complex formation. It is interesting that the probe desolvation properties associated with residue types were found to depend to some degree on whether the residue was outside of or part of a binding site. The probe desolvation penalty was on average smaller if the residue was part of a binding site compared to other surface locations. Applications to several antigen-antibody complexes demonstrated that the approach might be useful not only to predict protein interaction sites in general but to map potential antigenic epitopes on protein surfaces. Copyright (c) 2010 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  8. Prediction of Protein-Protein Interaction Sites Using Electrostatic Desolvation Profiles

    PubMed Central

    Fiorucci, Sébastien; Zacharias, Martin

    2010-01-01

    Abstract Protein-protein complex formation involves removal of water from the interface region. Surface regions with a small free energy penalty for water removal or desolvation may correspond to preferred interaction sites. A method to calculate the electrostatic free energy of placing a neutral low-dielectric probe at various protein surface positions has been designed and applied to characterize putative interaction sites. Based on solutions of the finite-difference Poisson equation, this method also includes long-range electrostatic contributions and the protein solvent boundary shape in contrast to accessible-surface-area-based solvation energies. Calculations on a large set of proteins indicate that in many cases (>90%), the known binding site overlaps with one of the six regions of lowest electrostatic desolvation penalty (overlap with the lowest desolvation region for 48% of proteins). Since the onset of electrostatic desolvation occurs even before direct protein-protein contact formation, it may help guide proteins toward the binding region in the final stage of complex formation. It is interesting that the probe desolvation properties associated with residue types were found to depend to some degree on whether the residue was outside of or part of a binding site. The probe desolvation penalty was on average smaller if the residue was part of a binding site compared to other surface locations. Applications to several antigen-antibody complexes demonstrated that the approach might be useful not only to predict protein interaction sites in general but to map potential antigenic epitopes on protein surfaces. PMID:20441756

  9. Validating predictive models for fast ion profile relaxation in burning plasmas

    NASA Astrophysics Data System (ADS)

    Gorelenkov, N. N.; Heidbrink, W. W.; Kramer, G. J.; Lestz, J. B.; Podesta, M.; Van Zeeland, M. A.; White, R. B.

    2016-11-01

    The redistribution and potential loss of energetic particles due to MHD modes can limit the performance of fusion plasmas by reducing the plasma heating rate. In this work, we present validation studies of the 1.5D critical gradient model (CGM) for Alfvén eigenmode (AE) induced EP transport in NSTX and DIII-D neutral beam heated plasmas. In previous comparisons with a single DIII-D L-mode case, the CGM model was found to be responsible for 75% of measured AE induced neutron deficit [1]. A fully kinetic HINST is used to compute mode stability for the non-perturbative version of CGM (or nCGM). We have found that AEs show strong local instability drive up to γ /ω ∼ 20% violating assumptions of perturbative approaches used in NOVA-K code. We demonstrate that both models agree with each other and both underestimate the neutron deficit measured in DIII-D shot by approximately a factor of 2. On the other hand in NSTX the application of CGM shows good agreement for the measured flux deficit predictions. We attempt to understand these results with the help of the so-called kick model which is based on the guiding center code ORBIT. The kick model comparison gives important insight into the underlying velocity space dependence of the AE induced EP transport as well as it allows the estimate of the neutron deficit in the presence of the low frequency Alfvénic modes. Within the limitations of used models we infer that there are missing modes in the analysis which could improve the agreement with the experiments.

  10. Integrating circadian activity and gene expression profiles to predict chronotoxicity of Drosophila suzukii response to insecticides.

    PubMed

    Hamby, Kelly A; Kwok, Rosanna S; Zalom, Frank G; Chiu, Joanna C

    2013-01-01

    Native to Southeast Asia, Drosophila suzukii (Matsumura) is a recent invader that infests intact ripe and ripening fruit, leading to significant crop losses in the U.S., Canada, and Europe. Since current D. suzukii management strategies rely heavily on insecticide usage and insecticide detoxification gene expression is under circadian regulation in the closely related Drosophila melanogaster, we set out to determine if integrative analysis of daily activity patterns and detoxification gene expression can predict chronotoxicity of D. suzukii to insecticides. Locomotor assays were performed under conditions that approximate a typical summer or winter day in Watsonville, California, where D. suzukii was first detected in North America. As expected, daily activity patterns of D. suzukii appeared quite different between 'summer' and 'winter' conditions due to differences in photoperiod and temperature. In the 'summer', D. suzukii assumed a more bimodal activity pattern, with maximum activity occurring at dawn and dusk. In the 'winter', activity was unimodal and restricted to the warmest part of the circadian cycle. Expression analysis of six detoxification genes and acute contact bioassays were performed at multiple circadian times, but only in conditions approximating Watsonville summer, the cropping season, when most insecticide applications occur. Five of the genes tested exhibited rhythmic expression, with the majority showing peak expression at dawn (ZT0, 6am). We observed significant differences in the chronotoxicity of D. suzukii towards malathion, with highest susceptibility at ZT0 (6am), corresponding to peak expression of cytochrome P450s that may be involved in bioactivation of malathion. High activity levels were not found to correlate with high insecticide susceptibility as initially hypothesized. Chronobiology and chronotoxicity of D. suzukii provide valuable insights for monitoring and control efforts, because insect activity as well as insecticide timing

  11. Sleep-wake profiles predict longitudinal changes in manic symptoms and memory in young people with mood disorders.

    PubMed

    Robillard, Rébecca; Hermens, Daniel F; Lee, Rico S C; Jones, Andrew; Carpenter, Joanne S; White, Django; Naismith, Sharon L; Southan, James; Whitwell, Bradley; Scott, Elizabeth M; Hickie, Ian B

    2016-10-01

    Mood disorders are characterized by disabling symptoms and cognitive difficulties which may vary in intensity throughout the course of the illness. Sleep-wake cycles and circadian rhythms influence emotional regulation and cognitive functions. However, the relationships between the sleep-wake disturbances experienced commonly by people with mood disorders and the longitudinal changes in their clinical and cognitive profile are not well characterized. This study investigated associations between initial sleep-wake patterns and longitudinal changes in mood symptoms and cognitive functions in 50 young people (aged 13-33 years) with depression or bipolar disorder. Data were based on actigraphy monitoring conducted over approximately 2 weeks and clinical and neuropsychological assessment. As part of a longitudinal cohort study, these assessments were repeated after a mean follow-up interval of 18.9 months. No significant differences in longitudinal clinical changes were found between the participants with depression and those with bipolar disorder. Lower sleep efficiency was predictive of longitudinal worsening in manic symptoms (P = 0.007). Shorter total sleep time (P = 0.043) and poorer circadian rhythmicity (P = 0.045) were predictive of worsening in verbal memory. These findings suggest that some sleep-wake and circadian disturbances in young people with mood disorders may be associated with less favourable longitudinal outcomes, notably for subsequent manic symptoms and memory difficulties. © 2016 European Sleep Research Society.

  12. Evidence that specific executive functions predict symptom variance among schizophrenia patients with a predominantly negative symptom profile.

    PubMed

    Donohoe, Gary; Corvin, Aiden; Robertson, Ian H

    2006-01-01

    Although deficits in executive functioning in schizophrenia have been consistently reported, their precise relationship to symptomatology remains unclear. Recent approaches to executive functioning in nonschizophrenia studies have aimed to "fractionate" the individual cognitive processes involved. In this study, we hypothesised that if these processes are fractionable, then particular symptom syndromes may be selectively related to executive deficits. In particular, it was hoped that this approach could clarify whether negative and positive symptoms of schizophrenia are differentially related to particular aspects of executive/attentional functions. A total of 32 patients with schizophrenia and 16 matched controls were assessed on a series of tasks designed to tap the theoretically derived executive functions of Inhibition, Shifting set, Working memory, and Sustained attention. Negative symptoms were significantly predicted by performance on an "Inhibition" task (Stroop), and not by performance on any other task. Furthermore, for a subgroup of patients with predominantly negative symptoms variance in positive symptoms was only significantly predicted by performance on a set-shifting task (Visual Elevator), and not by performance on other tasks, including inhibition. Our results support the contention that negative symptoms can, at least partly, be conceived of as cognitive behaviours expressing specific executive deficits. Specifically, we discuss the possibility that negative symptoms may, in part, express a failure in response monitoring. We further suggest that the disordered metacognition resulting in positive symptoms may be mediated by cognitive flexibility in patients with a predominantly negative symptom profile.

  13. Profiling crop pollinators: life history traits predict habitat use and crop visitation by Mediterranean wild bees.

    PubMed

    Pisanty, Gideon; Mandelik, Yael

    2015-04-01

    Wild pollinators, bees in particular, may greatly contribute to crop pollination and provide a safety net against declines in commercial pollinators. However, the identity, life history traits, and environmental sensitivities of main crop pollinator species.have received limited attention. These are crucial for predicting pollination services of different communities and for developing management practices that enhance crop pollinators. We sampled wild bees in three crop systems (almond, confection sunflower, and seed watermelon) in a mosaic Israeli Mediterranean landscape. Bees were sampled in field/orchard edges and interiors, and in seminatural scrub surrounding the fields/orchards. We also analyzed land cover at 50-2500 m radii around fields/orchards. We used this data to distinguish crop from non-crop pollinators based on a set of life history traits (nesting, lecty, sociality, body size) linked to habitat preference and crop visitation. Bee abundance and species richness decreased from the surrounding seminatural habitat to the field/orchard interior, especially across the seminatural habitat-field edge ecotone. Thus, although rich bee communities were found near fields, only small fractions crossed the ecotone and visited crop flowers in substantial numbers. The bee assemblage in agricultural fields/orchards and on crop flowers was dominated by ground-nesting bees of the tribe Halictini, which tend to nest within fields. Bees' habitat preferences were determined mainly by nesting guild, whereas crop visitation was determined mainly by sociality. Lecty and body size also affected both measures. The percentage of surrounding seminatural habitat at 250-2500 m radii had a positive effect on wild bee diversity in field edges, for all bee guilds, while at 50-100 m radii, only aboveground nesters were positively affected. In sum, we found that crop and non-crop pollinators are distinguished by behavioral and morphological traits. Hence, analysis of life

  14. Pro-inflammatory capacity of classically activated monocytes relates positively to muscle mass and strength.

    PubMed

    Beenakker, Karel G M; Westendorp, Rudi G J; de Craen, Anton J M; Slagboom, Pieternella E; van Heemst, Diana; Maier, Andrea B

    2013-08-01

    In mice, monocytes that exhibit a pro-inflammatory profile enter muscle tissue after muscle injury and are crucial for clearance of necrotic tissue and stimulation of muscle progenitor cell proliferation and differentiation. The aim of this study was to test if pro-inflammatory capacity of classically activated (M1) monocytes relates to muscle mass and strength in humans. This study included 191 male and 195 female subjects (mean age 64.2 years (SD 6.4) and 61.9 ± 6.4, respectively) of the Leiden Longevity Study. Pro-inflammatory capacity of M1 monocytes was assessed by ex vivo stimulation of whole blood with Toll-like receptor (TLR) 4 agonist lipopolysaccharide (LPS) and TLR-2/1 agonist tripalmitoyl-S-glycerylcysteine (Pam₃Cys-SK₄), both M1 phenotype activators. Cytokines that stimulate M1 monocyte response (IFN-γ and GM-CSF) as well as cytokines that are secreted by M1 monocytes (IL-6, TNF-α, IL-12, and IL-1β) were measured. Analyses were adjusted for age, height, and body fat mass. Upon stimulation with LPS, the cytokine production capacity of INF-γ, GM-CSF, and TNF-α was significantly positively associated with lean body mass, appendicular lean mass and handgrip strength in men, but not in women. Upon stimulation with Pam₃Cys-SK₄, IL-6; TNF-α; and Il-1β were significantly positively associated with lean body mass and appendicular lean in women, but not in men. Taken together, this study shows that higher pro-inflammatory capacity of M1 monocytes upon stimulation is associated with muscle characteristics and sex dependent. © 2013 John Wiley & Sons Ltd and the Anatomical Society.

  15. Genetic analysis of predicted fatty acid profiles of milk from Danish Holstein and Danish Jersey cattle populations.

    PubMed

    Hein, L; Sørensen, L P; Kargo, M; Buitenhuis, A J

    2018-03-01

    The objective of this study was to assess the genetic variability of the detailed fatty acid (FA) profiles of Danish Holstein (DH) and Danish Jersey (DJ) cattle populations. We estimated genetic parameters for 11 FA or groups of FA in milk samples from the Danish milk control system between May 2015 and October 2016. Concentrations of different FA and FA groups in milk samples were measured by mid-infrared spectroscopy. Data used for parameter estimation were from 132,732 first-parity DH cows and 21,966 first-parity DJ cows. We found the highest heritabilities for test day measurements in both populations for short-chain FA (DH = 0.16; DJ = 0.16) and C16:0 (DH = 0.14; DJ = 0.16). In DH, the highest heritabilities were also found for saturated FA and monounsaturated FA (both populations: 0.15). Genetic correlations between the fatty acid traits showed large differences between DH and DJ for especially short-chain FA with the other FA traits measured. Furthermore, genetic correlations of total fat with monounsaturated FA, polyunsaturated FA, short-chain FA, and C16:0 differed markedly between DH and DJ populations. In conclusion, we found genetic variation in the mid-infrared spectroscopy-predicted FA and FA groups of the DH and DJ cattle populations. This finding opens the possibility of using genetic selection to change the FA profiles of dairy cattle. The Authors. Published by FASS Inc. and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).

  16. COSIM: A Finite-Difference Computer Model to Predict Ternary Concentration Profiles Associated With Oxidation and Interdiffusion of Overlay-Coated Substrates

    NASA Technical Reports Server (NTRS)

    Nesbitt, James A.

    2001-01-01

    A finite-difference computer program (COSIM) has been written which models the one-dimensional, diffusional transport associated with high-temperature oxidation and interdiffusion of overlay-coated substrates. The program predicts concentration profiles for up to three elements in the coating and substrate after various oxidation exposures. Surface recession due to solute loss is also predicted. Ternary cross terms and concentration-dependent diffusion coefficients are taken into account. The program also incorporates a previously-developed oxide growth and spalling model to simulate either isothermal or cyclic oxidation exposures. In addition to predicting concentration profiles after various oxidation exposures, the program can also be used to predict coating life based on a concentration dependent failure criterion (e.g., surface solute content drops to 2%). The computer code is written in FORTRAN and employs numerous subroutines to make the program flexible and easily modifiable to other coating oxidation problems.

  17. COSIM: A Finite-Difference Computer Model to Predict Ternary Concentration Profiles Associated with Oxidation and Interdiffusion of Overlay-Coated Substrates

    NASA Technical Reports Server (NTRS)

    Nesbitt, James A.

    2000-01-01

    A finite-difference computer program (COSIM) has been written which models the one-dimensional, diffusional transport associated with high-temperature oxidation and interdiffusion of overlay-coated substrates. The program predicts concentration profiles for up to three elements in the coating and substrate after various oxidation exposures. Surface recession due to solute loss is also predicted. Ternary cross terms and concentration-dependent diffusion coefficients are taken into account. The program also incorporates a previously-developed oxide growth and spalling model to simulate either isothermal or cyclic oxidation exposures. In addition to predicting concentration profiles after various oxidation exposures, the program can also be used to predict coating fife based on a concentration dependent failure criterion (e.g., surface solute content drops to two percent). The computer code, written in an extension of FORTRAN 77, employs numerous subroutines to make the program flexible and easily modifiable to other coating oxidation problems.

  18. Whole Blood Gene Expression Profiling Predicts Severe Morbidity and Mortality in Cystic Fibrosis: A 5-Year Follow-Up Study.

    PubMed

    Saavedra, Milene T; Quon, Bradley S; Faino, Anna; Caceres, Silvia M; Poch, Katie R; Sanders, Linda A; Malcolm, Kenneth C; Nichols, David P; Sagel, Scott D; Taylor-Cousar, Jennifer L; Leach, Sonia M; Strand, Matthew; Nick, Jerry A

    2018-05-01

    appropriately in terms of clinical characteristics, and short- and long-term clinical outcomes, remained consistent, even when adding in a secondary population with significantly different clinical outcomes. Whole blood gene expression profiling allows molecular classification of acute pulmonary exacerbations, beyond standard clinical measures, providing a predictive tool for identifying subjects at increased risk for mortality and disease progression.

  19. Prediction of pH-Dependent Hydrophobic Profiles of Small Molecules from Miertus-Scrocco-Tomasi Continuum Solvation Calculations.

    PubMed

    Zamora, William J; Curutchet, Carles; Campanera, Josep M; Luque, F Javier

    2017-10-26

    Hydrophobicity is a key physicochemical descriptor used to understand the biological profile of (bio)organic compounds as well as a broad variety of biochemical, pharmacological, and toxicological processes. This property is estimated from the partition coefficient between aqueous and nonaqueous environments for neutral compounds (P N ) and corrected for the pH-dependence of ionizable compounds as the distribution coefficient (D). Here, we have extended the parametrization of the Miertus-Scrocco-Tomasi continuum solvation model in n-octanol to nitrogen-containing heterocyclic compounds, as they are present in many biologically relevant molecules (e.g., purines and pyrimidines bases, amino acids, and drugs), to obtain accurate log P N values for these molecules. This refinement also includes solvation calculations for ionic species in n-octanol with the aim of reproducing the experimental partition of ionic compounds (P I ). Finally, the suitability of different formalisms to estimate the distribution coefficient for a wide range of pH values has been examined for a set of small acidic and basic compounds. The results indicate that in general the simple pH-dependence model of the ionizable compound in water suffices to predict the partitioning at or around physiological pH. However, at extreme pH values, where ionic species are predominant, more elaborate models provide a better prediction of the n-octanol/water distribution coefficient, especially for amino acid analogues. Finally, the results also show that these formalisms are better suited to reproduce the experimental pH-dependent distribution curves of log D for both acidic and basic compounds as well as for amino acid analogues.

  20. Serum Amino Acid Profiles in Childhood Predict Triglyceride Level in Adulthood: A 7-Year Longitudinal Study in Girls.

    PubMed

    Wiklund, Petri; Zhang, Xiaobo; Tan, Xiao; Keinänen-Kiukaanniemi, Sirkka; Alen, Markku; Cheng, Sulin

    2016-05-01

    Branched-chain and aromatic amino acids are associated with high risk of developing dyslipidemia and type II diabetes in adults. This study aimed to examine whether serum amino acid profiles associate with triglyceride concentrations during pubertal growth and predict hypertriglyceridemia in early adulthood. This was a 7.5-year longitudinal study. The study was conducted at the Health Science Laboratory, University of Jyväskylä. A total of 396 nondiabetic Finnish girls aged 11.2 ± 0.8 years at the baseline participated in the study. Body composition was assessed by dual-energy x-ray absorptiometry; serum concentrations of glucose, insulin, and triglyceride by enzymatic photometric methods; and amino acids by nuclear magnetic resonance spectroscopy. Serum leucine and isoleucine correlated significantly with future triglyceride, independent of baseline triglyceride level (P < .05 for all). In early adulthood (at the age of 18 years), these amino acids were significantly associated with hypertriglyceridemia, whereas fat mass and homeostasis model assessment of insulin resistance were not. Leucine was the strongest determinant discriminating subjects with hypertriglyceridemia from those with normal triglyceride level (area under the curve, 0.822; 95% confidence interval, 0.740-0.903; P = .000001). Serum leucine and isoleucine were associated with future serum triglyceride levels in girls during pubertal growth and predicted hypertriglyceridemia in early adulthood. Therefore, these amino acid indices may serve as biomarkers to identify individuals at high risk for developing hypertriglyceridemia and cardiovascular disease later in life. Further studies are needed to elucidate the role these amino acids play in the lipid metabolism.

  1. Vascular biology: cellular and molecular profiling.

    PubMed

    Baird, Alison E; Wright, Violet L

    2006-02-01

    Our understanding of the mechanisms underlying cerebrovascular atherosclerosis has improved in recent years, but significant gaps remain. New insights into the vascular biological processes that result in ischemic stroke may come from cellular and molecular profiling studies of the peripheral blood. In recent cellular profiling studies, increased levels of a proinflammatory T-cell subset (CD4 (+)CD28 (-)) have been associated with stroke recurrence and death. Expansion of this T-cell subset may occur after ischemic stroke and be a pathogenic mechanism leading to recurrent stroke and death. Increases in certain phenotypes of endothelial cell microparticles have been found in stroke patients relative to controls, possibly indicating a state of increased vascular risk. Molecular profiling approaches include gene expression profiling and proteomic methods that permit large-scale analyses of the transcriptome and the proteome, respectively. Ultimately panels of genes and proteins may be identified that are predictive of stroke risk. Cellular and molecular profiling studies of the peripheral blood and of atherosclerotic plaques may also pave the way for the development of therapeutic agents for primary and secondary stroke prevention.

  2. A review of the relationship between proinflammatory cytokines and major depressive disorder.

    PubMed

    Young, Juan Joseph; Bruno, Davide; Pomara, Nunzio

    2014-12-01

    Determining etiological factors and reviewing advances in diagnostic modalities sensitive and specific to Major Depressive Disorder (MDD) is of importance in its evaluation and treatment. The inflammatory hypothesis is one of the most prevalent topics concerning MDD and may provide insight into the pathogenesis of depression, development of biomarkers, and ultimately production of more effective depression therapies. We reviewed several studies to evaluate contemporary concepts concerning proinflammatory cytokines and their relationship to various depressive disorders, the use of anti-inflammatory therapies in MDD treatment, and the application of neuroimaging in conjunction with cytokine profiles from both plasma and CSF as possible diagnostic tools. Proinflammatory cytokines in both plasma and CSF have been found to influence the progression and severity of depressive disorders in different populations. Studies have shown elevated serum levels of IL-1, IL-6, TNF-α, CRP, and MCP-1 in depressed patients, but have presented mixed results with IL-8 serum levels, and with IL-6 and MCP-1 CSF levels. Anti-inflammatory treatment of MDD may have adjuvant properties with current depression medications. MRI and NIRS neuroimaging confirm neurological abnormalities in the presence of elevated proinflammatory cytokines in depressed or stressed patients. Heterogeneity of MDD and limited CSF cytokine research complicate the study of MDD pathogenesis. There is significant evidence that inflammatory processes influence the development and progression of MDD. Future studies with larger arrays of cytokine profiles aided by neuroimaging may provide more sensitive and specific modes of diagnostics in determining MDD etiology and provide guidance in individual therapies. Copyright © 2014 Elsevier B.V. All rights reserved.

  3. Mutant alpha-synuclein overexpression mediates early proinflammatory activity.

    PubMed

    Su, Xiaomin; Federoff, Howard J; Maguire-Zeiss, Kathleen A

    2009-10-01

    Microglia provide immune surveillance for the brain through both the removal of cellular debris and protection against infection by microorganisms and "foreign" molecules. Upon activation, microglia display an altered morphology and increased expression of proinflammatory molecules. Increased numbers of activated microglia have been identified in a number of neurodegenerative diseases including Parkinson's disease (PD). What remains to be determined is whether activated microglia result from ongoing cell death or are involved in disease initiation and progression. To address this question we utilized a transgenic mouse model that expresses a mutated form of a key protein involved in Parkinson's disease, alpha-synuclein. Herein, we report an increase in activated microglia and proinflammatory molecules in 1-month-old transgenic mice well before cell death occurs in this model. Frank microglial activation is resolved by 6 months of age while a subset of proinflammatory molecules remain elevated for 12 months. Both tyrosine hydroxylase mRNA expression and alpha-synuclein protein are decreased in the striatum of older animals evidence of dystrophic neuritic projections. To determine whether mutated alpha-synuclein could directly activate microglia primary microglia-enriched cell cultures were treated with exogenous mutated alpha-synuclein. The data reveal an increase in activated microglia and proinflammatory molecules due to direct interaction with mutated alpha-synuclein. Together, these data demonstrate that mutated alpha-synuclein mediates a proinflammatory response in microglia and this activity may participate in PD pathogenesis.

  4. Differential Pro-Inflammatory Responses of Astrocytes and Microglia Involve STAT3 Activation in Response to 1800 MHz Radiofrequency Fields

    PubMed Central

    Lu, Yonghui; He, Mindi; Zhang, Yang; Xu, Shangcheng; Zhang, Lei; He, Yue; Chen, Chunhai; Liu, Chuan; Pi, Huifeng; Yu, Zhengping; Zhou, Zhou

    2014-01-01

    Microglia and astrocytes play important role in maintaining the homeostasis of central nervous system (CNS). Several CNS impacts have been postulated to be associated with radiofrequency (RF) electromagnetic fields exposure. Given the important role of inflammation in neural physiopathologic processes, we investigated the pro-inflammatory responses of microglia and astrocytes and the involved mechanism in response to RF fields. Microglial N9 and astroglial C8-D1A cells were exposed to 1800 MHz RF for different time with or without pretreatment with STAT3 inhibitor. Microglia and astrocytes were activated by RF exposure indicated by up-regulated CD11b and glial fibrillary acidic protein (GFAP). However, RF exposure induced differential pro-inflammatory responses in astrocytes and microglia, characterized by different expression and release profiles of IL-1β, TNF-α, IL-6, PGE2, nitric oxide (NO), inducible nitric oxide synthase (iNOS) and cyclooxygenase 2 (COX2). Moreover, the RF exposure activated STAT3 in microglia but not in astrocytes. Furthermore, the STAT3 inhibitor Stattic ameliorated the RF-induced release of pro-inflammatory cytokines in microglia but not in astrocytes. Our results demonstrated that RF exposure differentially induced pro-inflammatory responses in microglia and astrocytes, which involved differential activation of STAT3 in microglia and astrocytes. Our data provide novel insights into the potential mechanisms of the reported CNS impacts associated with mobile phone use and present STAT3 as a promising target to protect humans against increasing RF exposure. PMID:25275372

  5. Morphogen and proinflammatory cytokine release kinetics from PRGF-Endoret fibrin scaffolds: evaluation of the effect of leukocyte inclusion.

    PubMed

    Anitua, E; Zalduendo, M M; Prado, R; Alkhraisat, M H; Orive, G

    2015-03-01

    The potential influence of leukocyte incorporation in the kinetic release of growth factors from platelet-rich plasma (PRP) may explain the conflicting efficiency of leukocyte platelet-rich plasma (L-PRP) scaffolds in tissue regeneration. To assess this hypothesis, leukocyte-free (PRGF-Endoret) and L-PRP fibrin scaffolds were prepared, and both morphogen and proinflammatory cytokine release kinetics were analyzed. Clots were incubated with culture medium to monitor protein release over 8 days. Furthermore, the different fibrin scaffolds were morphologically characterized. Results show that leukocyte-free fibrin matrices were homogenous while leukocyte-containing ones were heterogeneous, loose and cellular. Leukocyte incorporation produced a significant increase in the contents of proinflammatory cytokines interleukin (IL)-1β and IL-16 but not in the platelet-derived growth factors release (<1.5-fold). Surprisingly, the availability of vascular endothelial growth factor suffered an important decrease after 3 days of incubation in the case of L-PRP matrices. While the release of proinflammatory cytokines was almost absent or very low from PRGF-Endoret, the inclusion of leukocytes induced a major increase in these cytokines, which was characterized by the presence of a latent period. The PRGF-Endoret matrices were stable during the 8 days of incubation. The inclusion of leukocytes alters the growth factors release profile and also increased the dose of proinflammatory cytokines. © 2014 Wiley Periodicals, Inc.

  6. Differential pro-inflammatory responses of astrocytes and microglia involve STAT3 activation in response to 1800 MHz radiofrequency fields.

    PubMed

    Lu, Yonghui; He, Mindi; Zhang, Yang; Xu, Shangcheng; Zhang, Lei; He, Yue; Chen, Chunhai; Liu, Chuan; Pi, Huifeng; Yu, Zhengping; Zhou, Zhou

    2014-01-01

    Microglia and astrocytes play important role in maintaining the homeostasis of central nervous system (CNS). Several CNS impacts have been postulated to be associated with radiofrequency (RF) electromagnetic fields exposure. Given the important role of inflammation in neural physiopathologic processes, we investigated the pro-inflammatory responses of microglia and astrocytes and the involved mechanism in response to RF fields. Microglial N9 and astroglial C8-D1A cells were exposed to 1800 MHz RF for different time with or without pretreatment with STAT3 inhibitor. Microglia and astrocytes were activated by RF exposure indicated by up-regulated CD11b and glial fibrillary acidic protein (GFAP). However, RF exposure induced differential pro-inflammatory responses in astrocytes and microglia, characterized by different expression and release profiles of IL-1β, TNF-α, IL-6, PGE2, nitric oxide (NO), inducible nitric oxide synthase (iNOS) and cyclooxygenase 2 (COX2). Moreover, the RF exposure activated STAT3 in microglia but not in astrocytes. Furthermore, the STAT3 inhibitor Stattic ameliorated the RF-induced release of pro-inflammatory cytokines in microglia but not in astrocytes. Our results demonstrated that RF exposure differentially induced pro-inflammatory responses in microglia and astrocytes, which involved differential activation of STAT3 in microglia and astrocytes. Our data provide novel insights into the potential mechanisms of the reported CNS impacts associated with mobile phone use and present STAT3 as a promising target to protect humans against increasing RF exposure.

  7. Predicting Ga and Cu Profiles in Co-Evaporated Cu(In,Ga)Se 2 Using Modified Diffusion Equations and a Spreadsheet

    DOE PAGES

    Repins, Ingrid L.; Harvey, Steve; Bowers, Karen; ...

    2017-05-15

    Cu(In,Ga)Se 2(CIGS) photovoltaic absorbers frequently develop Ga gradients during growth. These gradients vary as a function of growth recipe, and are important to device performance. Prediction of Ga profiles using classic diffusion equations is not possible because In and Ga atoms occupy the same lattice sites and thus diffuse interdependently, and there is not yet a detailed experimental knowledge of the chemical potential as a function of composition that describes this interaction. Here, we show how diffusion equations can be modified to account for site sharing between In and Ga atoms. The analysis has been implemented in an Excel spreadsheet,more » and outputs predicted Cu, In, and Ga profiles for entered deposition recipes. A single set of diffusion coefficients and activation energies are chosen, such that simulated elemental profiles track with published data and those from this study. Extent and limits of agreement between elemental profiles predicted from the growth recipes and the spreadsheet tool are demonstrated.« less

  8. Predicting Ga and Cu Profiles in Co-Evaporated Cu(In,Ga)Se 2 Using Modified Diffusion Equations and a Spreadsheet

    SciTech Connect

    Repins, Ingrid L.; Harvey, Steve; Bowers, Karen

    Cu(In,Ga)Se 2(CIGS) photovoltaic absorbers frequently develop Ga gradients during growth. These gradients vary as a function of growth recipe, and are important to device performance. Prediction of Ga profiles using classic diffusion equations is not possible because In and Ga atoms occupy the same lattice sites and thus diffuse interdependently, and there is not yet a detailed experimental knowledge of the chemical potential as a function of composition that describes this interaction. Here, we show how diffusion equations can be modified to account for site sharing between In and Ga atoms. The analysis has been implemented in an Excel spreadsheet,more » and outputs predicted Cu, In, and Ga profiles for entered deposition recipes. A single set of diffusion coefficients and activation energies are chosen, such that simulated elemental profiles track with published data and those from this study. Extent and limits of agreement between elemental profiles predicted from the growth recipes and the spreadsheet tool are demonstrated.« less

  9. Proinflammatory cytokine levels in patients with conversion disorder.

    PubMed

    Tiyekli, Utkan; Calıyurt, Okan; Tiyekli, Nimet Dilek

    2013-06-01

    It was aimed to evaluate the relationship between proinflammatory cytokine levels and conversion disorder both commonly known as stress regulated. Baseline proinflammatory cytokine levels-[Tumour necrosis factor alpha (TNF-α), Interleukin-1 beta (IL-1β), Interleukin-6 (IL-6)]-were evaluated with enzyme-linked immunosorbent assay in 35 conversion disorder patients and 30 healthy controls. Possible changes in proinflammatory cytokine levels were evaluated again, after their acute phase in conversion disorder patients. Statistically significant decreased serum TNF-α levels were obtained in acute phase of conversion disorder. Those levels increased after acute conversion phase. There were no statistically significant difference observed between groups in serum IL-1β and (IL-6) levels. Stress associated with conversion disorder may suppress immune function in acute conversion phase and may have diagnostic and therapeutic value.

  10. PREDICTS

    NASA Technical Reports Server (NTRS)

    Zhou, Hanying

    2007-01-01

    PREDICTS is a computer program that predicts the frequencies, as functions of time, of signals to be received by a radio science receiver in this case, a special-purpose digital receiver dedicated to analysis of signals received by an antenna in NASA s Deep Space Network (DSN). Unlike other software used in the DSN, PREDICTS does not use interpolation early in the calculations; as a consequence, PREDICTS is more precise and more stable. The precision afforded by the other DSN software is sufficient for telemetry; the greater precision afforded by PREDICTS is needed for radio-science experiments. In addition to frequencies as a function of time, PREDICTS yields the rates of change and interpolation coefficients for the frequencies and the beginning and ending times of reception, transmission, and occultation. PREDICTS is applicable to S-, X-, and Ka-band signals and can accommodate the following link configurations: (1) one-way (spacecraft to ground), (2) two-way (from a ground station to a spacecraft to the same ground station), and (3) three-way (from a ground transmitting station to a spacecraft to a different ground receiving station).

  11. Cancer as a Proinflammatory Environment: Metastasis and Cachexia

    PubMed Central

    Inácio Pinto, Nelson; Carnier, June; Oyama, Lila M.; Otoch, Jose Pinhata; Alcântara, Paulo Sergio; Tokeshi, Flavio; Nascimento, Claudia M.

    2015-01-01

    The development of the syndrome of cancer cachexia and that of metastasis are related with a poor prognostic for cancer patients. They are considered multifactorial processes associated with a proinflammatory environment, to which tumour microenvironment and other tissues from the tumour bearing individuals contribute. The aim of the present review is to address the role of ghrelin, myostatin, leptin, HIF, IL-6, TNF-α, and ANGPTL-4 in the regulation of energy balance, tumour development, and tumoural cell invasion. Hypoxia induced factor plays a prominent role in tumour macro- and microenvironment, by modulating the release of proinflammatory cytokines. PMID:26508818

  12. Injury profile SIMulator, a Qualitative aggregative modelling framework to predict injury profile as a function of cropping practices, and abiotic and biotic environment. II. Proof of concept: design of IPSIM-wheat-eyespot.

    PubMed

    Robin, Marie-Hélène; Colbach, Nathalie; Lucas, Philippe; Montfort, Françoise; Cholez, Célia; Debaeke, Philippe; Aubertot, Jean-Noël

    2013-01-01

    IPSIM (Injury Profile SIMulator) is a generic modelling framework presented in a companion paper. It aims at predicting a crop injury profile as a function of cropping practices and abiotic and biotic environment. IPSIM's modelling approach consists of designing a model with an aggregative hierarchical tree of attributes. In order to provide a proof of concept, a model, named IPSIM-Wheat-Eyespot, has been developed with the software DEXi according to the conceptual framework of IPSIM to represent final incidence of eyespot on wheat. This paper briefly presents the pathosystem, the method used to develop IPSIM-Wheat-Eyespot using IPSIM's modelling framework, simulation examples, an evaluation of the predictive quality of the model with a large dataset (526 observed site-years) and a discussion on the benefits and limitations of the approach. IPSIM-Wheat-Eyespot proved to successfully represent the annual variability of the disease, as well as the effects of cropping practices (Efficiency = 0.51, Root Mean Square Error of Prediction = 24%; bias = 5.0%). IPSIM-Wheat-Eyespot does not aim to precisely predict the incidence of eyespot on wheat. It rather aims to rank cropping systems with regard to the risk of eyespot on wheat in a given production situation through ex ante evaluations. IPSIM-Wheat-Eyespot can also help perform diagnoses of commercial fields. Its structure is simple and permits to combine available knowledge in the scientific literature (data, models) and expertise. IPSIM-Wheat-Eyespot is now available to help design cropping systems with a low risk of eyespot on wheat in a wide range of production situations, and can help perform diagnoses of commercial fields. In addition, it provides a proof of concept with regard to the modelling approach of IPSIM. IPSIM-Wheat-Eyespot will be a sub-model of IPSIM-Wheat, a model that will predict injury profile on wheat as a function of cropping practices and the production situation.

  13. The Child Behavior Checklist-Dysregulation Profile Predicts Substance Use, Suicidality, and Functional Impairment: A Longitudinal Analysis

    ERIC Educational Resources Information Center

    Holtmann, Martin; Buchmann, Arlette F.; Esser, Guenter; Schmidt, Martin H.; Banaschewski, Tobias; Laucht, Manfred

    2011-01-01

    Background: Recent studies have identified a Child Behavior Checklist profile that characterizes children with severe affective and behavioral dysregulation (CBCL-dysregulation profile, CBCL-DP). In two recent longitudinal studies the CBCL-DP in childhood was associated with heightened rates of comorbid psychiatric disorders, among them bipolar…

  14. Mars Ozone Absorption Line Shapes from Infrared Heterodyne Spectra Applied to GCM-Predicted Ozone Profiles and to MEX/SPICAM Column Retrievals

    NASA Technical Reports Server (NTRS)

    Fast, Kelly E.; Kostiuk, T.; Annen, J.; Hewagama, T.; Delgado, J.; Livengood, T. A.; Lefevre, F.

    2008-01-01

    We present the application of infrared heterodyne line shapes of ozone on Mars to those produced by radiative transfer modeling of ozone profiles predicted by general circulation models (GCM), and to contemporaneous column abundances measured by Mars Express SPICAM. Ozone is an important tracer of photochemistry Mars' atmosphere, serving as an observable with which to test predictions of photochemistry-coupled GCMs. Infrared heterodyne spectroscopy at 9.5 microns with spectral resolving power >1,000,000 is the only technique that can directly measure fully-resolved line shapes of Martian ozone features from the surface of the Earth. Measurements were made with Goddard Space Flight Center's Heterodyne instrument for Planetary Wind And Composition (HIPWAC) at the NASA Infrared Telescope Facility (IRTF) on Mauna Kea, Hawaii on February 21-24 2008 UT at Ls=35deg on or near the MEX orbital path. The HIPWAC observations were used to test GCM predictions. For example, a GCM-generated ozone profile for 60degN 112degW was scaled so that a radiative transfer calculation of its absorption line shape matched an observed HIPWAC absorption feature at the same areographic position, local time, and season. The RMS deviation of the model from the data was slightly smaller for the GCM-generated profile than for a line shape produced by a constant-with-height profile, even though the total column abundances were the same, showing potential for testing and constraining GCM ozone-profiles. The resulting ozone column abundance from matching the model to the HIPWAC line shape was 60% higher than that observed by SPICAM at the same areographic position one day earlier and 2.5 hours earlier in local time. This could be due to day-to-day, diurnal, or north polar region variability, or to measurement sensitivity to the ozone column and its distribution, and these possibilities will be explored. This work was supported by NASA's Planetary Astronomy Program.

  15. NFAT5-Regulated Macrophage Polarization Supports the Proinflammatory Function of Macrophages and T Lymphocytes.

    PubMed

    Tellechea, Mónica; Buxadé, Maria; Tejedor, Sonia; Aramburu, Jose; López-Rodríguez, Cristina

    2018-01-01

    Macrophages are exquisite sensors of tissue homeostasis that can rapidly switch between pro- and anti-inflammatory or regulatory modes to respond to perturbations in their microenvironment. This functional plasticity involves a precise orchestration of gene expression patterns whose transcriptional regulators have not been fully characterized. We had previously identified the transcription factor NFAT5 as an activator of TLR-induced responses, and in this study we explore its contribution to macrophage functions in different polarization settings. We found that both in classically and alternatively polarized macrophages, NFAT5 enhanced functions associated with a proinflammatory profile such as bactericidal capacity and the ability to promote Th1 polarization over Th2 responses. In this regard, NFAT5 upregulated the Th1-stimulatory cytokine IL-12 in classically activated macrophages, whereas in alternatively polarized ones it enhanced the expression of the pro-Th1 mediators Fizz-1 and arginase 1, indicating that it could promote proinflammatory readiness by regulating independent genes in differently polarized macrophages. Finally, adoptive transfer assays in vivo revealed a reduced antitumor capacity in NFAT5-deficient macrophages against syngeneic Lewis lung carcinoma and ID8 ovarian carcinoma cells, a defect that in the ID8 model was associated with a reduced accumulation of effector CD8 T cells at the tumor site. Altogether, detailed analysis of the effect of NFAT5 in pro- and anti-inflammatory macrophages uncovered its ability to regulate distinct genes under both polarization modes and revealed its predominant role in promoting proinflammatory macrophage functions. Copyright © 2017 by The American Association of Immunologists, Inc.

  16. FUNCTIONAL SUBCLONE PROFILING FOR PREDICTION OF TREATMENT-INDUCED INTRA-TUMOR POPULATION SHIFTS AND DISCOVERY OF RATIONAL DRUG COMBINATIONS IN HUMAN GLIOBLASTOMA

    PubMed Central

    Reinartz, Roman; Wang, Shanshan; Kebir, Sied; Silver, Daniel J.; Wieland, Anja; Zheng, Tong; Küpper, Marius; Rauschenbach, Laurèl; Fimmers, Rolf; Shepherd, Timothy M.; Trageser, Daniel; Till, Andreas; Schäfer, Niklas; Glas, Martin; Hillmer, Axel M.; Cichon, Sven; Smith, Amy A.; Pietsch, Torsten; Liu, Ying; Reynolds, Brent A.; Yachnis, Anthony; Pincus, David W.; Simon, Matthias; Brüstle, Oliver; Steindler, Dennis A.; Scheffler, Björn

    2016-01-01

    Purpose Investigation of clonal heterogeneity may be key to understanding mechanisms of therapeutic failure in human cancer. However, little is known on the consequences of therapeutic intervention on the clonal composition of solid tumors. Experimental Design Here, we used 33 single cell-derived subclones generated from five clinical glioblastoma specimens for exploring intra- and inter-individual spectra of drug resistance profiles in vitro. In a personalized setting, we explored whether differences in pharmacological sensitivity among subclones could be employed to predict drug-dependent changes to the clonal composition of tumors. Results Subclones from individual tumors exhibited a remarkable heterogeneity of drug resistance to a library of potential anti-glioblastoma compounds. A more comprehensive intra-tumoral analysis revealed that stable genetic and phenotypic characteristics of co-existing subclones could be correlated with distinct drug sensitivity profiles. The data obtained from differential drug response analysis could be employed to predict clonal population shifts within the naïve parental tumor in vitro and in orthotopic xenografts. Furthermore, the value of pharmacological profiles could be shown for establishing rational strategies for individualized secondary lines of treatment. Conclusions Our data provide a previously unrecognized strategy for revealing functional consequences of intra-tumor heterogeneity by enabling predictive modeling of treatment-related subclone dynamics in human glioblastoma. PMID:27521447

  17. Plasma Free Amino Acid Profiles Predict Four-Year Risk of Developing Diabetes, Metabolic Syndrome, Dyslipidemia, and Hypertension in Japanese Population

    PubMed Central

    Yamakado, Minoru; Nagao, Kenji; Imaizumi, Akira; Tani, Mizuki; Toda, Akiko; Tanaka, Takayuki; Jinzu, Hiroko; Miyano, Hiroshi; Yamamoto, Hiroshi; Daimon, Takashi; Horimoto, Katsuhisa; Ishizaka, Yuko

    2015-01-01

    Plasma free amino acid (PFAA) profile is highlighted in its association with visceral obesity and hyperinsulinemia, and future diabetes. Indeed PFAA profiling potentially can evaluate individuals’ future risks of developing lifestyle-related diseases, in addition to diabetes. However, few studies have been performed especially in Asian populations, about the optimal combination of PFAAs for evaluating health risks. We quantified PFAA levels in 3,701 Japanese subjects, and determined visceral fat area (VFA) and two-hour post-challenge insulin (Ins120 min) values in 865 and 1,160 subjects, respectively. Then, models between PFAA levels and the VFA or Ins120 min values were constructed by multiple linear regression analysis with variable selection. Finally, a cohort study of 2,984 subjects to examine capabilities of the obtained models for predicting four-year risk of developing new-onset lifestyle-related diseases was conducted. The correlation coefficients of the obtained PFAA models against VFA or Ins120 min were higher than single PFAA level. Our models work well for future risk prediction. Even after adjusting for commonly accepted multiple risk factors, these models can predict future development of diabetes, metabolic syndrome, and dyslipidemia. PFAA profiles confer independent and differing contributions to increasing the lifestyle-related disease risks in addition to the currently known factors in a general Japanese population. PMID:26156880

  18. Predictive modelling of grain-size distributions from marine electromagnetic profiling data using end-member analysis and a radial basis function network

    NASA Astrophysics Data System (ADS)

    Baasch, B.; Müller, H.; von Dobeneck, T.

    2018-07-01

    In this work, we present a new methodology to predict grain-size distributions from geophysical data. Specifically, electric conductivity and magnetic susceptibility of seafloor sediments recovered from electromagnetic profiling data are used to predict grain-size distributions along shelf-wide survey lines. Field data from the NW Iberian shelf are investigated and reveal a strong relation between the electromagnetic properties and grain-size distribution. The here presented workflow combines unsupervised and supervised machine-learning techniques. Non-negative matrix factorization is used to determine grain-size end-members from sediment surface samples. Four end-members were found, which well represent the variety of sediments in the study area. A radial basis function network modified for prediction of compositional data is then used to estimate the abundances of these end-members from the electromagnetic properties. The end-members together with their predicted abundances are finally back transformed to grain-size distributions. A minimum spatial variation constraint is implemented in the training of the network to avoid overfitting and to respect the spatial distribution of sediment patterns. The predicted models are tested via leave-one-out cross-validation revealing high prediction accuracy with coefficients of determination (R2) between 0.76 and 0.89. The predicted grain-size distributions represent the well-known sediment facies and patterns on the NW Iberian shelf and provide new insights into their distribution, transition and dynamics. This study suggests that electromagnetic benthic profiling in combination with machine learning techniques is a powerful tool to estimate grain-size distribution of marine sediments.

  19. Predictive modelling of grain size distributions from marine electromagnetic profiling data using end-member analysis and a radial basis function network

    NASA Astrophysics Data System (ADS)

    Baasch, B.; M"uller, H.; von Dobeneck, T.

    2018-04-01

    In this work we present a new methodology to predict grain-size distributions from geophysical data. Specifically, electric conductivity and magnetic susceptibility of seafloor sediments recovered from electromagnetic profiling data are used to predict grain-size distributions along shelf-wide survey lines. Field data from the NW Iberian shelf are investigated and reveal a strong relation between the electromagnetic properties and grain-size distribution. The here presented workflow combines unsupervised and supervised machine learning techniques. Nonnegative matrix factorisation is used to determine grain-size end-members from sediment surface samples. Four end-members were found which well represent the variety of sediments in the study area. A radial-basis function network modified for prediction of compositional data is then used to estimate the abundances of these end-members from the electromagnetic properties. The end-members together with their predicted abundances are finally back transformed to grain-size distributions. A minimum spatial variation constraint is implemented in the training of the network to avoid overfitting and to respect the spatial distribution of sediment patterns. The predicted models are tested via leave-one-out cross-validation revealing high prediction accuracy with coefficients of determination (R2) between 0.76 and 0.89. The predicted grain-size distributions represent the well-known sediment facies and patterns on the NW Iberian shelf and provide new insights into their distribution, transition and dynamics. This study suggests that electromagnetic benthic profiling in combination with machine learning techniques is a powerful tool to estimate grain-size distribution of marine sediments.

  20. Repurposing mitochondria from ATP production to ROS generation drives a pro-inflammatory phenotype in macrophages that depends on succinate oxidation by complex II

    PubMed Central

    Logan, A; Costa, A. S. H.; Varma, M.; Bryant, C. E.; Tourlomousis, P.; Däbritz, J. H. M.; Gottlieb, E.; Latorre, I.; Corr, S.C.; McManus, G.; Ryan, D.; Jacobs, H.T.; Szibor, M.; Xavier, R. J.; Braun, T.; Frezza, C.; Murphy, M. P.; O’Neill, L. A.

    2018-01-01

    Activated macrophages undergo metabolic reprogramming which drives their pro-inflammatory phenotype, but the mechanistic basis for this remains obscure. Here we demonstrate that upon lipopolysaccharide (LPS) stimulation macrophages shift from producing ATP by oxidative phosphorylation to glycolysis, while also increasing succinate levels. We show that increased mitochondrial oxidation of succinate via succinate dehydrogenase (SDH) and an elevation of mitochondrial membrane potential combine to drive mitochondrial ROS production. RNA sequencing reveals that this combination induces a pro-inflammatory gene expression profile, while an inhibitor of succinate oxidation, dimethyl malonate (DMM), promotes an anti-inflammatory outcome. Blocking ROS production with rotenone, by uncoupling mitochondria, or by expressing the alternative oxidase (AOX) inhibits this inflammatory phenotype, with AOX protecting mice from LPS lethality. The metabolic alterations that occur upon activation of macrophages therefore repurpose mitochondria from ATP synthesis to ROS production in order to promote a pro-inflammatory state. PMID:27667687

  1. Prediction of Clinical Outcomes by Chemokine and Cytokine Profiling In CSF from Radiation Treated Breast Cancer Primary with Brain Metastases

    NASA Astrophysics Data System (ADS)

    Lok, Edwin

    Whole brain radiation is the standard treatment for patients with brain metastasis but unfortunately tumors can recover from radiation-induced damage with the help of the immune system. The hypothesis that differences in immunokines in the cerebrospinal fluid (CSF) pre- and post-irradiation could reveal tumor biology and correlate with outcome of patients with metastatic breast cancer to the brain is tested. Collected CSF samples were analyzed using Luminex's multiplexing assays to survey global immunokine levels while Enzyme-Linked Immunosorbent Assays were used to quantify each individual immunokines. Cluster analysis was performed to segregate patients based on their common immunokine profile and each cluster was correlated with survival and other clinical parameters. Breast cancer brain metastasis was found to have altered immunokine profiles in the CSF, and that Interleukin-1α expression was elevated after irradiation. Therefore, immunokine profiling in the CSF could enable cancer physicians to monitor the status of brain metastases.

  2. Waist circumference: a better index of fat location than WHR for predicting lipid profile in overweight/obese Iranian women.

    PubMed

    Shahraki, T; Shahraki, M; Roudbari, M

    2009-01-01

    We carried out a clinical cross-sectional study on 728 overweight and obese women aged 20-60 years during July 2005-May 2006 in Sistan and Baluchestan, Islamic Republic of Iran. Body mass index (BMI) and waist circumference (WC) showed significant correlation with total cholesterol (TC), triglycerides (TG) and low-density lipoprotein cholesterol. After adjustment for age and BMI, this was also true for WC with TC and TG. There was no such correlation between waist-to-hip ratio (WHR) and lipid profile. Hence, WC was a better anthropometric index of fat location than WHR to estimate lipid profile in overweight and obese adult women.

  3. Modeling the Zeeman effect in high altitude SSMIS channels for numerical weather prediction profiles: comparing a fast model and a line-by-line model

    NASA Astrophysics Data System (ADS)

    Larsson, R.; Milz, M.; Rayer, P.; Saunders, R.; Bell, W.; Booton, A.; Buehler, S. A.; Eriksson, P.; John, V.

    2015-10-01

    We present a comparison of a reference and a fast radiative transfer model using numerical weather prediction profiles for the Zeeman-affected high altitude Special Sensor Microwave Imager/Sounder channels 19-22. We find that the models agree well for channels 21 and 22 compared to the channels' system noise temperatures (1.9 and 1.3 K, respectively) and the expected profile errors at the affected altitudes (estimated to be around 5 K). For channel 22 there is a 0.5 K average difference between the models, with a standard deviation of 0.24 K for the full set of atmospheric profiles. Same channel, there is 1.2 K in average between the fast model and the sensor measurement, with 1.4 K standard deviation. For channel 21 there is a 0.9 K average difference between the models, with a standard deviation of 0.56 K. Same channel, there is 1.3 K in average between the fast model and the sensor measurement, with 2.4 K standard deviation. We consider the relatively small model differences as a validation of the fast Zeeman effect scheme for these channels. Both channels 19 and 20 have smaller average differences between the models (at below 0.2 K) and smaller standard deviations (at below 0.4 K) when both models use a two-dimensional magnetic field profile. However, when the reference model is switched to using a full three-dimensional magnetic field profile, the standard deviation to the fast model is increased to almost 2 K due to viewing geometry dependencies causing up to ± 7 K differences near the equator. The average differences between the two models remain small despite changing magnetic field configurations. We are unable to compare channels 19 and 20 to sensor measurements due to limited altitude range of the numerical weather prediction profiles. We recommended that numerical weather prediction software using the fast model takes the available fast Zeeman scheme into account for data assimilation of the affected sensor channels to better constrain the upper

  4. Modeling the Zeeman effect in high-altitude SSMIS channels for numerical weather prediction profiles: comparing a fast model and a line-by-line model

    NASA Astrophysics Data System (ADS)

    Larsson, Richard; Milz, Mathias; Rayer, Peter; Saunders, Roger; Bell, William; Booton, Anna; Buehler, Stefan A.; Eriksson, Patrick; John, Viju O.

    2016-03-01

    We present a comparison of a reference and a fast radiative transfer model using numerical weather prediction profiles for the Zeeman-affected high-altitude Special Sensor Microwave Imager/Sounder channels 19-22. We find that the models agree well for channels 21 and 22 compared to the channels' system noise temperatures (1.9 and 1.3 K, respectively) and the expected profile errors at the affected altitudes (estimated to be around 5 K). For channel 22 there is a 0.5 K average difference between the models, with a standard deviation of 0.24 K for the full set of atmospheric profiles. Concerning the same channel, there is 1.2 K on average between the fast model and the sensor measurement, with 1.4 K standard deviation. For channel 21 there is a 0.9 K average difference between the models, with a standard deviation of 0.56 K. Regarding the same channel, there is 1.3 K on average between the fast model and the sensor measurement, with 2.4 K standard deviation. We consider the relatively small model differences as a validation of the fast Zeeman effect scheme for these channels. Both channels 19 and 20 have smaller average differences between the models (at below 0.2 K) and smaller standard deviations (at below 0.4 K) when both models use a two-dimensional magnetic field profile. However, when the reference model is switched to using a full three-dimensional magnetic field profile, the standard deviation to the fast model is increased to almost 2 K due to viewing geometry dependencies, causing up to ±7 K differences near the equator. The average differences between the two models remain small despite changing magnetic field configurations. We are unable to compare channels 19 and 20 to sensor measurements due to limited altitude range of the numerical weather prediction profiles. We recommended that numerical weather prediction software using the fast model takes the available fast Zeeman scheme into account for data assimilation of the affected sensor channels to

  5. Interactions between pro-inflammatory cytokines and statins on depression in patients with acute coronary syndrome.

    PubMed

    Kim, Sung-Wan; Kang, Hee-Ju; Bae, Kyung-Yeol; Shin, Il-Seon; Hong, Young Joon; Ahn, Young-Keun; Jeong, Myung Ho; Berk, Michael; Yoon, Jin-Sang; Kim, Jae-Min

    2018-01-03

    Pro-inflammatory cytokines are associated with the development of depression and statins exert anti-inflammatory and antidepressant effects. The present study aimed to investigate associations between interleukin (IL)-6 and IL-18 and depression in patients with acute coronary syndrome (ACS) and potential interactions between statin use and pro-inflammatory cytokines on depression in this population. We used pooled datasets from 1-year follow-up data from a 24-week randomized double-blind placebo-controlled trial (RCT) of escitalopram for treatment of depressive disorder and data from a naturalistic, prospective, observational cohort study in patients with ACS. IL-6 and IL-18 levels were measured at baseline. Logistic regression models were used to investigate independent associations of IL-6/IL-18 levels with depressive disorder at baseline and at 1year. We repeated all analyses by reference to statin use to determine whether any significant association emerged. Of the 969 participants, 378 (39.0%) had major or minor depression at baseline. Of 711 patients followed-up at 1year, 183 (25.7%) had depression. Logistic regression analysis showed that higher IL-6 and IL-18 levels at baseline were significantly associated with baseline depression after adjusting for other variables (adjusted p-values=0.005 and 0.001, respectively). IL-6 and IL-18 levels were also significantly higher in patients with depression at the 1-year follow-up after adjusting for other variables amongst those not taking statins (adjusted p-values=0.040 and 0.004, respectively); but this was not the case in patients taking statins. Levels of pro-inflammatory cytokines appear to predict development of depression after ACS and statins attenuate the effects of cytokines on depression. Copyright © 2017 Elsevier Inc. All rights reserved.

  6. Predicting the educational performance of Isfahan University students of medical sciences based on their behaviour profile, mental health and demographic characteristic.

    PubMed

    Samouei, Rahele; Fooladvand, Maryam; Janghorban, Shahla; Khorvash, Fariba

    2015-01-01

    The issue of students' academic failure is one of the most important educational, economic, and social issues. Cognizance of the factors related to academic downfall is so efficient in its prevention and control and leads to protecting governmental assets and labor force. In order to achieve this goal, this study intends to determine the predictive factors of the students' academic performance in Isfahan University of Medical Sciences in terms of their personality profile, mental health, and their demographic characteristics. This study was a descriptive-correlation study on 771 students who entered Isfahan University of Medical Sciences between 2005 and 2007. The information was gathered through using the students' educational and clinical files (for measuring personality characteristics and mental health) and SAMA Software (To get the mean scores). Minnesota Multiphasic Personality Inventory short form and General Health Questionnaire were used for collecting clinical data. The data were analyzed using SPSS 15 (stepwise regression coefficient, variance analysis, Student's t-test, and Spearman correlation coefficient). The results showed that the aforementioned students obtained a normal average for their personality profile and mental health indicators. Of all the reviewed variables, education, age, gender, depression, and hypochondria were the predictive factors of the students' educational performance. It could be concluded that some of the personality features, mental health indicators, and personality profile play such a significant role in the students' educational life that the disorder in any of them affects the students' educational performance and academic failure.

  7. Prediction of Cytochrome P450 Profiles of Environmental Chemicals with QSAR Models Built from Drug-like Molecules

    EPA Science Inventory

    The human cytochrome P450 (CYP450) enzyme family is involved in the biotransformation of many environmental chemicals. As part of the U.S. Tox21 effort, we profiled the CYP450 activity of ~2800 chemicals predominantly of environmental concern against CYP1A2, CYP2C19, CYP2C9, CYP2...

  8. The affective profiles, psychological well-being, and harmony: environmental mastery and self-acceptance predict the sense of a harmonious life

    PubMed Central

    Al Nima, Ali; Kjell, Oscar N.E.

    2014-01-01

    the dimensions of psychological well-being within the four affective profiles. Specifically, harmony in life was significantly predicted by environmental mastery and self-acceptance across all affective profiles. However, for the low affective group high purpose in life predicted low levels of harmony in life. Conclusions. The results demonstrated that affective profiles systematically relate to psychological well-being and harmony in life. Notably, individuals categorised as self-fulfilling tended to report higher levels of both psychological well-being and harmony in life when compared with the other profiles. Meanwhile individuals in the self-destructive group reported the lowest levels of psychological well-being and harmony when compared with the three other profiles. It is proposed that self-acceptance and environmental acceptance might enable individuals to go from self-destructive to a self-fulfilling state that also involves harmony in life. PMID:24688843

  9. Effect of proinflammatory interleukins on jejunal nutrient transport

    PubMed Central

    Hardin, J; Kroeker, K; Chung, B; Gall, D

    2000-01-01

    AIM—We examined the effect of proinflammatory and anti-inflammatory interleukins on jejunal nutrient transport and expression of the sodium-glucose linked cotransporter (SGLT-1).
METHODS—3-O-methyl glucose and L-proline transport rates were examined in New Zealand White rabbit stripped, short circuited jejunal tissue. The effects of the proinflammatory cytokines interleukin (IL)-1α, IL-6, and IL-8, IL-1α plus the specific IL-1 antagonist, IL-1ra, and the anti-inflammatory cytokine IL-10 were investigated. In separate experiments, passive tissue permeability was assessed and brush border SGLT-1 expression was measured by western blot in tissues exposed to proinflammatory interleukins.
RESULTS—The proinflammatory interleukins IL-6, IL-1α, and IL-8 significantly increased glucose absorption compared with control levels. This increase in glucose absorption was due to an increase in mucosal to serosal flux. IL-1α and IL-8 also significantly increased L-proline absorption due to an increase in absorptive flux. The anti-inflammatory IL-10 had no effect on glucose transport. The receptor antagonist IL-1ra blocked the ability of IL-1α to stimulate glucose transport. IL-8 had no effect on passive tissue permeability. SGLT-1 content did not differ in brush border membrane vesicles (BBMV) from control or interleukin treated tissue.
CONCLUSIONS—These findings suggest that intestinal inflammation and release of inflammatory mediators such as interleukins increase nutrient absorption in the gut. The increase in glucose transport does not appear to be due to changes in BBMV SGLT-1 content.


Keywords: glucose transport; small intestine; intestinal inflammation; inflammation PMID:10896908

  10. Hostile marital interactions, proinflammatory cytokine production, and wound healing.

    PubMed

    Kiecolt-Glaser, Janice K; Loving, Timothy J; Stowell, Jeffrey R; Malarkey, William B; Lemeshow, Stanley; Dickinson, Stephanie L; Glaser, Ronald

    2005-12-01

    A growing epidemiological literature has suggested that marital discord is a risk factor for morbidity and mortality. In addition, depression and stress are associated with enhanced production of proinflammatory cytokines that influence a spectrum of conditions associated with aging. To assess how hostile marital behaviors modulate wound healing, as well as local and systemic proinflammatory cytokine production. Couples were admitted twice to a hospital research unit for 24 hours in a crossover trial. Wound healing was assessed daily following research unit discharge. Volunteer sample of 42 healthy married couples, aged 22 to 77 years (mean [SD], 37.04 [13.05]), married a mean (SD) of 12.55 (11.01) years. During the first research unit admission, couples had a structured social support interaction, and during the second admission, they discussed a marital disagreement. Couples' interpersonal behavior, wound healing, and local and systemic changes in proinflammatory cytokine production were assessed during each research unit admission. Couples' blister wounds healed more slowly and local cytokine production (IL-6, tumor necrosis factor alpha, and IL-1beta) was lower at wound sites following marital conflicts than after social support interactions. Couples who demonstrated consistently higher levels of hostile behaviors across both their interactions healed at 60% of the rate of low-hostile couples. High-hostile couples also produced relatively larger increases in plasma IL-6 and tumor necrosis factor alpha values the morning after a conflict than after a social support interaction compared with low-hostile couples. These data provide further mechanistic evidence of the sensitivity of wound healing to everyday stressors. Moreover, more frequent and amplified increases in proinflammatory cytokine levels could accelerate a range of age-related diseases. Thus, these data also provide a window on the pathways through which hostile or abrasive relationships affect

  11. The Pro-inflammatory Effects of Glucocorticoids in the Brain

    PubMed Central

    Duque, Erica de Almeida; Munhoz, Carolina Demarchi

    2016-01-01

    Glucocorticoids are a class of steroid hormones derived from cholesterol. Their actions are mediated by the glucocorticoid and mineralocorticoid receptors, members of the superfamily of nuclear receptors, which, once bound to their ligands, act as transcription factors that can directly modulate gene expression. Through protein–protein interactions with other transcription factors, they can also regulate the activity of many genes in a composite or tethering way. Rapid non-genomic signaling was also demonstrated since glucocorticoids can act through membrane receptors and activate signal transduction pathways, such as protein kinases cascades, to modulate other transcriptions factors and activate or repress various target genes. By all these different mechanisms, glucocorticoids regulate numerous important functions in a large variety of cells, not only in the peripheral organs but also in the central nervous system during development and adulthood. In general, glucocorticoids are considered anti-inflammatory and protective agents due to their ability to inhibit gene expression of pro-inflammatory mediators and other possible damaging molecules. Nonetheless, recent studies have uncovered situations in which these hormones can act as pro-inflammatory agents depending on the dose, chronicity of exposure, and the structure/organ analyzed. In this review, we will provide an overview of the conditions under which these phenomena occur, a discussion that will serve as a basis for exploring the mechanistic foundation of glucocorticoids pro-inflammatory gene regulation in the brain. PMID:27445981

  12. Proinflammatory cytokines: a link between chorioamnionitis and fetal brain injury.

    PubMed

    Patrick, Lindsay A; Smith, Graeme N

    2002-09-01

    To review the etiology of impaired fetal neurodevelopment - in particular, the relationship between chorioamnionitis, cytokines, and cerebral palsy. A MEDLINE search was performed for all clinical and basic science studies published in the English literature from 1966 to 2002. Key words or phrases used were chorioamnionitis, cerebral palsy, fetal brain damage, fetal CNS injury, infection in pregnancy, proinflammatory cytokines in pregnancy, proinflammatory cytokines in infection, and preterm labour or birth. All relevant human and animal studies were included. Fetal brain injury remains a major cause of lifelong morbidity, incurring significant societal and health care costs. It has been postulated that chorioamnionitis stimulates maternal/fetal proinflammatory cytokine release, which is damaging to the developing fetal nervous system. Elevated cytokine concentrations may interfere with glial cell development and proliferation in the late second trimester of pregnancy, when the central nervous system is most vulnerable. Increasing numbers of epidemiological and basic science studies found through MEDLINE searches support this hypothesis. Treatment options aimed at etiologic factors may lead to improved neurodevelopmental outcomes. Clearly, some relationship exists between chorioamnionitis, cytokines, and the development of cerebral palsy, but the severity and duration of exposure required to produce fetal damage remains unknown. Future research addressing these issues may aid in clinical decision-making. As well, the elucidation of mechanisms of cytokine action may aid in early treatment options to prevent or limit development of fetal brain injury.

  13. Biochemical Profile of Heritage and Modern Apple Cultivars and Application of Machine Learning Methods To Predict Usage, Age, and Harvest Season.

    PubMed

    Anastasiadi, Maria; Mohareb, Fady; Redfern, Sally P; Berry, Mark; Simmonds, Monique S J; Terry, Leon A

    2017-07-05

    The present study represents the first major attempt to characterize the biochemical profile in different tissues of a large selection of apple cultivars sourced from the United Kingdom's National Fruit Collection comprising dessert, ornamental, cider, and culinary apples. Furthermore, advanced machine learning methods were applied with the objective to identify whether the phenolic and sugar composition of an apple cultivar could be used as a biomarker fingerprint to differentiate between heritage and mainstream commercial cultivars as well as govern the separation among primary usage groups and harvest season. A prediction accuracy of >90% was achieved with the random forest method for all three models. The results highlighted the extraordinary phytochemical potency and unique profile of some heritage, cider, and ornamental apple cultivars, especially in comparison to more mainstream apple cultivars. Therefore, these findings could guide future cultivar selection on the basis of health-promoting phytochemical content.

  14. Blood autoantibody and cytokine profiles predict response to anti-tumor necrosis factor therapy in rheumatoid arthritis

    PubMed Central

    Hueber, Wolfgang; Tomooka, Beren H; Batliwalla, Franak; Li, Wentian; Monach, Paul A; Tibshirani, Robert J; Van Vollenhoven, Ronald F; Lampa, Jon; Saito, Kazuyoshi; Tanaka, Yoshiya; Genovese, Mark C; Klareskog, Lars; Gregersen, Peter K; Robinson, William H

    2009-01-01

    Introduction Anti-TNF therapies have revolutionized the treatment of rheumatoid arthritis (RA), a common systemic autoimmune disease involving destruction of the synovial joints. However, in the practice of rheumatology approximately one-third of patients demonstrate no clinical improvement in response to treatment with anti-TNF therapies, while another third demonstrate a partial response, and one-third an excellent and sustained response. Since no clinical or laboratory tests are available to predict response to anti-TNF therapies, great need exists for predictive biomarkers. Methods Here we present a multi-step proteomics approach using arthritis antigen arrays, a multiplex cytokine assay, and conventional ELISA, with the objective to identify a biomarker signature in three ethnically diverse cohorts of RA patients treated with the anti-TNF therapy etanercept. Results We identified a 24-biomarker signature that enabled prediction of a positive clinical response to etanercept in all three cohorts (positive predictive values 58 to 72%; negative predictive values 63 to 78%). Conclusions We identified a multi-parameter protein biomarker that enables pretreatment classification and prediction of etanercept responders, and tested this biomarker using three independent cohorts of RA patients. Although further validation in prospective and larger cohorts is needed, our observations demonstrate that multiplex characterization of autoantibodies and cytokines provides clinical utility for predicting response to the anti-TNF therapy etanercept in RA patients. PMID:19460157

  15. Diagnostic value of the flow profile in the distal descending aorta by phase-contrast magnetic resonance for predicting severe coarctation of the aorta.

    PubMed

    Muzzarelli, Stefano; Ordovas, Karen Gomes; Hope, Michael D; Meadows, Jeffery J; Higgins, Charles B; Meadows, Alison Knauth

    2011-06-01

    To compare aortic flow profiles at the level of the proximal descending (PDAo) and distal descending aorta (DDAo) in patients investigated for coarctation of the aorta (CoA), and compare their respective diagnostic value for predicting severe CoA. Diastolic flow decay in the PDAo predicts severe CoA, but flow measurements at this level are limited by flow turbulence, aliasing, and stent-related artifacts. We studied 49 patients evaluated for CoA with phase contrast magnetic resonance imaging (PC-MRI). Parameters of diastolic flow decay in the PDAo and DDAo were compared. Their respective diagnostic value was compared with the standard reference of transcatheter peak gradient ≥20 mmHg. Flow measurement in the PDAo required repeated acquisition with adjustment of encoding velocity or location of the imaging plane in 69% of patients; measurement in the DDAo was achieved in single acquisition in all cases. Parameters of diastolic flow decay in the PDAo and DDAo, including rate-corrected (RC) deceleration time and RC flow deceleration yielded a good correlation (r = 0.78; P < 0.01, and r = 0.92; P < 0.01), and a similar diagnostic value for predicting severe CoA. The highest diagnostic accuracy was achieved by RC deceleration time at DDAo (sensitivity 85%, specificity 85%). Characterization of aortic flow profiles at the DDAo offers a quick and reliable noninvasive means of assessing hemodynamically significant CoA. Copyright © 2011 Wiley-Liss, Inc.

  16. The Predictive Effects of Early Pregnancy Lipid Profiles and Fasting Glucose on the Risk of Gestational Diabetes Mellitus Stratified by Body Mass Index.

    PubMed

    Wang, Chen; Zhu, Weiwei; Wei, Yumei; Su, Rina; Feng, Hui; Lin, Li; Yang, Huixia

    2016-01-01

    This study aimed at evaluating the predictive effects of early pregnancy lipid profiles and fasting glucose on the risk of gestational diabetes mellitus (GDM) in patients stratified by prepregnancy body mass index (p-BMI) and to determine the optimal cut-off values of each indicator for different p-BMI ranges. A retrospective system cluster sampling survey was conducted in Beijing during 2013 and a total of 5,265 singleton pregnancies without prepregnancy diabetes were included. The information for each participant was collected individually using questionnaires and medical records. Logistic regression analysis and receiver operator characteristics analysis were used in the analysis. Outcomes showed that potential markers for the prediction of GDM include early pregnancy lipid profiles (cholesterol, triacylglycerols, low-density lipoprotein cholesterol/high-density lipoprotein cholesterol ratios [LDL-C/HDL-C], and triglyceride to high-density lipoprotein cholesterol ratios [TG/HDL-C]) and fasting glucose, of which fasting glucose level was the most accurate indicator. Furthermore, the predictive effects and cut-off values for these factors varied according to p-BMI. Thus, p-BMI should be a consideration for the risk assessment of pregnant patients for GDM development.

  17. Use of Artificial Intelligence and Machine Learning Algorithms with Gene Expression Profiling to Predict Recurrent Nonmuscle Invasive Urothelial Carcinoma of the Bladder.

    PubMed

    Bartsch, Georg; Mitra, Anirban P; Mitra, Sheetal A; Almal, Arpit A; Steven, Kenneth E; Skinner, Donald G; Fry, David W; Lenehan, Peter F; Worzel, William P; Cote, Richard J

    2016-02-01

    Due to the high recurrence risk of nonmuscle invasive urothelial carcinoma it is crucial to distinguish patients at high risk from those with indolent disease. In this study we used a machine learning algorithm to identify the genes in patients with nonmuscle invasive urothelial carcinoma at initial presentation that were most predictive of recurrence. We used the genes in a molecular signature to predict recurrence risk within 5 years after transurethral resection of bladder tumor. Whole genome profiling was performed on 112 frozen nonmuscle invasive urothelial carcinoma specimens obtained at first presentation on Human WG-6 BeadChips (Illumina®). A genetic programming algorithm was applied to evolve classifier mathematical models for outcome prediction. Cross-validation based resampling and gene use frequencies were used to identify the most prognostic genes, which were combined into rules used in a voting algorithm to predict the sample target class. Key genes were validated by quantitative polymerase chain reaction. The classifier set included 21 genes that predicted recurrence. Quantitative polymerase chain reaction was done for these genes in a subset of 100 patients. A 5-gene combined rule incorporating a voting algorithm yielded 77% sensitivity and 85% specificity to predict recurrence in the training set, and 69% and 62%, respectively, in the test set. A singular 3-gene rule was constructed that predicted recurrence with 80% sensitivity and 90% specificity in the training set, and 71% and 67%, respectively, in the test set. Using primary nonmuscle invasive urothelial carcinoma from initial occurrences genetic programming identified transcripts in reproducible fashion, which were predictive of recurrence. These findings could potentially impact nonmuscle invasive urothelial carcinoma management. Copyright © 2016 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

  18. A study of polarized spectra of magnetic CP stars: Predicted š. observed Stokes IQUV profiles for beta CrB and 53 Cam

    NASA Astrophysics Data System (ADS)

    Bagnulo, S.; Wade, G. A.; Donati, J.-F.; Landstreet, J. D.; Leone, F.; Monin, D. N.; Stift, M. J.

    2001-04-01

    We present a comparison of observed and calculated Stokes IQUV spectra of two well-known magnetic chemically peculiar stars, beta Coronae Borealis and 53 Camelopardalis. The observed Stokes spectra were recently described by Wade et al. (\\cite{wad00a}), and have been complemented with additional circularly polarized spectra obtained at the Special Astrophysical Observatory. The calculated spectra represent the predictions of new and previously published magnetic field models derived from the analysis of some surface averaged field estimates (e.g., longitudinal field, magnetic field modulus, etc.). We find that these magnetic models are not sufficient to account fully for the observed Stokes profiles - particularly remarkable is the disagreement between the predicted and observed Stokes Q and U profiles of 53 Cam. We suggest that this should be interpreted in terms of magnetic morphologies which are significantly more complex than the second-order multipolar expansions assumed in the models. However, it is clear that some of our inability to reproduce the detailed shapes of the Stokes IQUV profiles is unrelated to the magnetic models. For many metallic ions, for both stars, we found it impossible to account for the strengths and shapes of the observed spectral line profiles when we adopted a unique value for the individual ion abundance. We suggest that this results from strongly non-uniform distributions of these ions as a function of optical depth (i.e., chemical stratification), a hypothesis that is supported by comparison with simple chemically stratified models. Based on observations obtained with the 2 m Bernard Lyot telescope of the Pic-du-Midi Observatory, the 1 m telescope of the Special Astrophysical Observatory, and the 0.9 m telescope of the Osservatorio Astrofisico di Catania.

  19. A predictive model to evaluate the impact of the cooling profile on growth of psychrotrophic bacteria in raw milk from conventional and robotic milking.

    PubMed

    Christiansson, Anders

    2017-08-01

    This Research Communication explores the usefulness of predictive modelling to explain bacterial behaviour during cooling. A simple dynamic lag phase model was developed and validated. The model takes into account the effect of the cooling profile on the lag phase and growth in bulk tank milk. The time before the start of cooling was the most critical and should not exceed 1 h. The cooling rate between 30 and approximately 10 °C was the second most critical period. Cooling from 30 to 10 °C within 2 h ensured minimal growth of psychrotrophic bacteria in the milk. The cooling rate between 10 and 4 °C (the slowest phase of cooling) was of surprisingly little importance. Given a normal cooling profile to 10 °C, several hours of prolonged cooling time made practically no difference in psychrotrophic counts. This behaviour can be explained by the time/temperature dependence of the work needed by the bacteria to complete the lag phase at low temperature. For milk quality advisors, it is important to know that slow cooling below 10 °C does not result in high total counts of bacteria. In practice, slow cooling is occasionally found at farms with robotic milking. However, when comparing psychrotrophic growth in bulk milk tanks designed for robotic milking or conventional milking, the model predicted less growth for robotic milking for identical cooling profiles. It is proposed that due to the different rates of milk entering the tank, fewer bacteria will exit the lag phase during robotic milking and they will be more diluted than in conventional milking systems. At present, there is no international standard that specifies the cooling profile in robotic systems. The information on the insignificant effect of the cooling rate below 10 °C may be useful in the development of a standard.

  20. Serum protein profiling using an aptamer array predicts clinical outcomes of stage IIA colon cancer: A leave-one-out crossvalidation

    PubMed Central

    Huh, Jung Wook; Kim, Sung Chun; Sohn, Insuk; Jung, Sin-Ho; Kim, Hee Cheol

    2016-01-01

    Background In this study, we established and validated a model for predicting prognosis of stage IIA colon cancer patients based on expression profiles of aptamers in serum. Methods Bloods samples were collected from 227 consecutive patients with pathologic T3N0M0 (stage IIA) colon cancer. We incubated 1,149 serum molecule-binding aptamer pools of clinical significance with serum from patients to obtain aptamers bound to serum molecules, which were then amplified and marked. Oligonucleotide arrays were constructed with the base sequences of the 1,149 aptamers, and the marked products identified above were reacted with one another to produce profiles of the aptamers bound to serum molecules. These profiles were organized into low- and high-risk groups of colon cancer patients based on clinical information for the serum samples. Cox proportional hazards model and leave-one-out cross-validation (LOOCV) were used to evaluate predictive performance. Results During a median follow-up period of 5 years, 29 of the 227 patients (11.9%) experienced recurrence. There were 212 patients (93.4%) in the low-risk group and 15 patients (6.6%) in the high-risk group in our aptamer prognosis model. Postoperative recurrence significantly correlated with age and aptamer risk stratification (p = 0.046 and p = 0.001, respectively). In multivariate analysis, aptamer risk stratification (p < 0.001) was an independent predictor of recurrence. Disease-free survival curves calculated according to aptamer risk level predicted through a LOOCV procedure and age showed significant differences (p < 0.001 from permutations). Conclusion Aptamer risk stratification can be a valuable prognostic factor in stage II colon cancer patients. PMID:26908450

  1. Segmenting by Risk Perceptions: Predicting Young Adults’ Genetic-Belief Profiles with Health and Opinion-Leader Covariates

    PubMed Central

    Smith, Rachel A.; Greenberg, Marisa; Parrott, Roxanne L.

    2014-01-01

    With a growing interest in using genetic information to motivate young adults’ health behaviors, audience segmentation is needed for effective campaign design. Using latent class analysis, this study identifies segments based on young adults’ (N = 327) beliefs about genetic threats to their health and personal efficacy over genetic influences on their health. A four-class model was identified. The model indicators fit the risk perception attitude framework (Rimal & Real, 2003), but the covariates (e.g., current health behaviors) did not. In addition, opinion leader qualities covaried with one profile: those in this profile engaged in fewer preventative behaviors and more dangerous treatment options, and also liked to persuade others, making them a particularly salient group for campaign efforts. The implications for adult-onset disorders, like alpha-1 antitrypsin deficiency are discussed. PMID:24111749

  2. Injury Profile SIMulator, a Qualitative Aggregative Modelling Framework to Predict Injury Profile as a Function of Cropping Practices, and Abiotic and Biotic Environment. II. Proof of Concept: Design of IPSIM-Wheat-Eyespot

    PubMed Central

    Robin, Marie-Hélène; Colbach, Nathalie; Lucas, Philippe; Montfort, Françoise; Cholez, Célia; Debaeke, Philippe; Aubertot, Jean-Noël

    2013-01-01

    IPSIM (Injury Profile SIMulator) is a generic modelling framework presented in a companion paper. It aims at predicting a crop injury profile as a function of cropping practices and abiotic and biotic environment. IPSIM's modelling approach consists of designing a model with an aggregative hierarchical tree of attributes. In order to provide a proof of concept, a model, named IPSIM-Wheat-Eyespot, has been developed with the software DEXi according to the conceptual framework of IPSIM to represent final incidence of eyespot on wheat. This paper briefly presents the pathosystem, the method used to develop IPSIM-Wheat-Eyespot using IPSIM's modelling framework, simulation examples, an evaluation of the predictive quality of the model with a large dataset (526 observed site-years) and a discussion on the benefits and limitations of the approach. IPSIM-Wheat-Eyespot proved to successfully represent the annual variability of the disease, as well as the effects of cropping practices (Efficiency = 0.51, Root Mean Square Error of Prediction = 24%; bias = 5.0%). IPSIM-Wheat-Eyespot does not aim to precisely predict the incidence of eyespot on wheat. It rather aims to rank cropping systems with regard to the risk of eyespot on wheat in a given production situation through ex ante evaluations. IPSIM-Wheat-Eyespot can also help perform diagnoses of commercial fields. Its structure is simple and permits to combine available knowledge in the scientific literature (data, models) and expertise. IPSIM-Wheat-Eyespot is now available to help design cropping systems with a low risk of eyespot on wheat in a wide range of production situations, and can help perform diagnoses of commercial fields. In addition, it provides a proof of concept with regard to the modelling approach of IPSIM. IPSIM-Wheat-Eyespot will be a sub-model of IPSIM-Wheat, a model that will predict injury profile on wheat as a function of cropping practices and the production situation. PMID:24146783

  3. A model for prediction of profile and flatness of hot and cold rolled flat products in four-high mills

    NASA Astrophysics Data System (ADS)

    Overhagen, Christian; Mauk, Paul Josef

    2018-05-01

    For flat rolled products, the thickness profile in the transversal direction is one of the most important product properties. For further processing, a defined crown of the product is necessary. In the rolling process, several mechanical and thermal influences interact with each other to form the strip shape at the roll gap exit. In the present analysis, a process model for rolling of strip and sheet is presented. The core feature of the process model is a two-dimensional stress distribution model based on von Karman's differential equation. Sub models for the mechanical influences of work roll flattening as well as work and backup roll deflection and the thermal influence of work roll expansion have been developed or extended. The two-dimensional stress distribution serves as an input parameter for the roll deformation models. For work roll flattening, a three-dimensional model based on the Boussinesq problem is adopted, while the work and backup roll deflection, including contact flattening is calculated by means of finite beam elements. The thermal work roll crown is calculated with help of an axisymmetric numerical solution of the heat equation for the work roll, considering azimuthal averaging for the boundary conditions at the work roll surface. Results are presented for hot rolling of a strip in a seven-stand finishing train of a hot strip mill, showing the calculated evolution of the strip profile. A variation of the strip profile from the first to the 20th rolled strip is shown. This variation is addressed to the progressive increase of work roll temperature during the first 20 strips. It is shown that a CVC® system can lead to improvements in strip profile and therefore flatness.

  4. A Binomial Modeling Approach for Upscaling Colloid Transport Under Unfavorable Attachment Conditions: Emergent Prediction of Nonmonotonic Retention Profiles

    NASA Astrophysics Data System (ADS)

    Hilpert, Markus; Johnson, William P.

    2018-01-01

    We used a recently developed simple mathematical network model to upscale pore-scale colloid transport information determined under unfavorable attachment conditions. Classical log-linear and nonmonotonic retention profiles, both well-reported under favorable and unfavorable attachment conditions, respectively, emerged from our upscaling. The primary attribute of the network is colloid transfer between bulk pore fluid, the near-surface fluid domain (NSFD), and attachment (treated as irreversible). The network model accounts for colloid transfer to the NSFD of downgradient grains and for reentrainment to bulk pore fluid via diffusion or via expulsion at rear flow stagnation zones (RFSZs). The model describes colloid transport by a sequence of random trials in a one-dimensional (1-D) network of Happel cells, which contain a grain and a pore. Using combinatorial analysis that capitalizes on the binomial coefficient, we derived from the pore-scale information the theoretical residence time distribution of colloids in the network. The transition from log-linear to nonmonotonic retention profiles occurs when the conditions underlying classical filtration theory are not fulfilled, i.e., when an NSFD colloid population is maintained. Then, nonmonotonic retention profiles result potentially both for attached and NSFD colloids. The concentration maxima shift downgradient depending on specific parameter choice. The concentration maxima were also shown to shift downgradient temporally (with continued elution) under conditions where attachment is negligible, explaining experimentally observed downgradient transport of retained concentration maxima of adhesion-deficient bacteria. For the case of zero reentrainment, we develop closed-form, analytical expressions for the shape, and the maximum of the colloid retention profile.

  5. Proinflammatory cytokines and response to molds in mononuclear cells of patients with Meniere disease.

    PubMed

    Frejo, Lidia; Gallego-Martinez, Alvaro; Requena, Teresa; Martin-Sanz, Eduardo; Amor-Dorado, Juan Carlos; Soto-Varela, Andres; Santos-Perez, Sofia; Espinosa-Sanchez, Juan Manuel; Batuecas-Caletrio, Angel; Aran, Ismael; Fraile, Jesus; Rossi-Izquierdo, Marcos; Lopez-Escamez, Jose Antonio

    2018-04-13

    Epidemiological studies have found a higher prevalence of allergic symptoms and positive prick tests in patients with Meniere's disease (MD); however the effect of allergenic extracts in MD has not been established. Thus, this study aims to determine the effect of Aspergillus and Penicillium stimulation in cytokine release and gene expression profile in MD. Patients with MD showed higher basal levels of IL-1β, IL-1RA, IL-6 and TNF-α when compared to healthy controls. We observed that IL-1β levels had a bimodal distribution suggesting two different subgroups of patients, with low and high basal levels of cytokines. Gene expression profile in peripheral blood mononuclear cells (PBMC) showed significant differences in patients with high and low basal levels of IL-1β. We found that both mold extracts triggered a significant release of TNF-α in MD patients, which were not found in controls. Moreover, after mold stimulation, MD patients showed a different gene expression profile in PBMC, according to the basal levels of IL-1β. The results indicate that a subset of MD patients have higher basal levels of proinflammatory cytokines and the exposure to Aspergillus and Penicillium extracts may trigger additional TNF-α release and contribute to exacerbate inflammation.

  6. Diffusion profiling of tumor volumes using a histogram approach can predict proliferation and further microarchitectural features in medulloblastoma.

    PubMed

    Schob, Stefan; Beeskow, Anne; Dieckow, Julia; Meyer, Hans-Jonas; Krause, Matthias; Frydrychowicz, Clara; Hirsch, Franz-Wolfgang; Surov, Alexey

    2018-05-31

    Medulloblastomas are the most common central nervous system tumors in childhood. Treatment and prognosis strongly depend on histology and transcriptomic profiling. However, the proliferative potential also has prognostical value. Our study aimed to investigate correlations between histogram profiling of diffusion-weighted images and further microarchitectural features. Seven patients (age median 14.6 years, minimum 2 years, maximum 20 years; 5 male, 2 female) were included in this retrospective study. Using a Matlab-based analysis tool, histogram analysis of whole apparent diffusion coefficient (ADC) volumes was performed. ADC entropy revealed a strong inverse correlation with the expression of the proliferation marker Ki67 (r = - 0.962, p = 0.009) and with total nuclear area (r = - 0.888, p = 0.044). Furthermore, ADC percentiles, most of all ADCp90, showed significant correlations with Ki67 expression (r = 0.902, p = 0.036). Diffusion histogram profiling of medulloblastomas provides valuable in vivo information which potentially can be used for risk stratification and prognostication. First of all, entropy revealed to be the most promising imaging biomarker. However, further studies are warranted.

  7. Comparison of Models and Whole-Genome Profiling Approaches for Genomic-Enabled Prediction of Septoria Tritici Blotch, Stagonospora Nodorum Blotch, and Tan Spot Resistance in Wheat.

    PubMed

    Juliana, Philomin; Singh, Ravi P; Singh, Pawan K; Crossa, Jose; Rutkoski, Jessica E; Poland, Jesse A; Bergstrom, Gary C; Sorrells, Mark E

    2017-07-01

    The leaf spotting diseases in wheat that include Septoria tritici blotch (STB) caused by , Stagonospora nodorum blotch (SNB) caused by , and tan spot (TS) caused by pose challenges to breeding programs in selecting for resistance. A promising approach that could enable selection prior to phenotyping is genomic selection that uses genome-wide markers to estimate breeding values (BVs) for quantitative traits. To evaluate this approach for seedling and/or adult plant resistance (APR) to STB, SNB, and TS, we compared the predictive ability of least-squares (LS) approach with genomic-enabled prediction models including genomic best linear unbiased predictor (GBLUP), Bayesian ridge regression (BRR), Bayes A (BA), Bayes B (BB), Bayes Cπ (BC), Bayesian least absolute shrinkage and selection operator (BL), and reproducing kernel Hilbert spaces markers (RKHS-M), a pedigree-based model (RKHS-P) and RKHS markers and pedigree (RKHS-MP). We observed that LS gave the lowest prediction accuracies and RKHS-MP, the highest. The genomic-enabled prediction models and RKHS-P gave similar accuracies. The increase in accuracy using genomic prediction models over LS was 48%. The mean genomic prediction accuracies were 0.45 for STB (APR), 0.55 for SNB (seedling), 0.66 for TS (seedling) and 0.48 for TS (APR). We also compared markers from two whole-genome profiling approaches: genotyping by sequencing (GBS) and diversity arrays technology sequencing (DArTseq) for prediction. While, GBS markers performed slightly better than DArTseq, combining markers from the two approaches did not improve accuracies. We conclude that implementing GS in breeding for these diseases would help to achieve higher accuracies and rapid gains from selection. Copyright © 2017 Crop Science Society of America.

  8. Non-invasive metabolomic profiling of embryo culture media and morphology grading to predict implantation outcome in frozen-thawed embryo transfer cycles.

    PubMed

    Li, Xiong; Xu, Yan; Fu, Jing; Zhang, Wen-Bi; Liu, Su-Ying; Sun, Xiao-Xi

    2015-11-01

    Assessment of embryo viability is a crucial component of in vitro fertilization and currently relies largely on embryo morphology and cleavage rate. Because morphological assessment remains highly subjective, it can be unreliable in predicting embryo viability. This study investigated the metabolomic profiling of embryo culture media using near-infrared (NIR) spectroscopy for predicting the implantation potential of human embryos in frozen-thawed embryo transfer (FET) cycles. Spent embryo culture media was collected on day 4 after thawed embryo transfer (n = 621) and analysed using NIR spectroscopy. Viability scores were calculated using a predictive multivariate algorithm of fresh embryos with known pregnancy outcomes. The mean viability indices of embryos resulting in clinical pregnancy following FET were significantly higher than those of non-implanted embryos and differed between the 0, 50, and 100 % implantation groups. Notably, the 0 % group index was significantly lower than the 100 % implantation group index (-0.787 ± 0.382 vs. 1.064 ± 0.331, P < 0.01). To predict implantation outcomes, we examined the area under the ROC curve (AUCROC), which was significantly higher for the viability than for the morphology score (0.94 vs. 0.55; P < 0.01); however, the AUCROCs for the composite and viability scores did not differ significantly (0.92 vs. 0.94; P > 0.05). NIR metabolomic profiling of thawed embryo culture media is independent of morphology and correlates with embryo implantation potential in FET cycles. The viability score alone or in conjunction with morphologic grading is a more objective marker for implantation outcome in FET cycles than morphology alone.

  9. Genomic profiling is predictive of response to cisplatin treatment but not to PI3K inhibition in bladder cancer patient-derived xenografts

    PubMed Central

    Ramakrishnan, Swathi; Elbanna, May; Wang, Jianmin; Hu, Qiang; Glenn, Sean T.; Murakami, Mitsuko; Liu, Lu; Gomez, Eduardo Cortes; Sun, Yuchen; Conroy, Jacob; Miles, Kiersten Marie; Malathi, Kullappan; Ramaiah, Sudha; Anbarasu, Anand; Woloszynska-Read, Anna; Johnson, Candace S.; Conroy, Jeffrey; Liu, Song; Morrison, Carl D.; Pili, Roberto

    2016-01-01

    Purpose Effective systemic therapeutic options are limited for bladder cancer. In this preclinical study we tested whether bladder cancer gene alterations may be predictive of treatment response. Experimental design We performed genomic profiling of two bladder cancer patient derived tumor xenografts (PDX). We optimized the exome sequence analysis method to overcome the mouse genome interference. Results We identified a number of somatic mutations, mostly shared by the primary tumors and PDX. In particular, BLCAb001, which is less responsive to cisplatin than BLCAb002, carried non-sense mutations in several genes associated with cisplatin resistance, including MLH1, BRCA2, and CASP8. Furthermore, RNA-Seq analysis revealed the overexpression of cisplatin resistance associated genes such as SLC7A11, TLE4, and IL1A in BLCAb001. Two different PIK3CA mutations, E542K and E545K, were identified in BLCAb001 and BLCAb002, respectively. Thus, we tested whether the genomic profiling was predictive of response to a dual PI3K/mTOR targeting agent, LY3023414. Despite harboring similar PIK3CA mutations, BLCAb001 and BLCAb002 exhibited differential response, both in vitro and in vivo. Sustained target modulation was observed in the sensitive model BLCAb002 but not in BLCAb001, as well as decreased autophagy. Interestingly, computational modelling of mutant structures and affinity binding to PI3K revealed that E542K mutation was associated with weaker drug binding than E545K. Conclusions Our results suggest that the presence of activating PIK3CA mutations may not necessarily predict in vivo treatment response to PI3K targeted therapies, while specific gene alterations may be predictive for cisplatin response in bladder cancer models and, potentially, in patients as well. PMID:27823983

  10. Predicting multi-level drug response with gene expression profile in multiple myeloma using hierarchical ordinal regression.

    PubMed

    Zhang, Xinyan; Li, Bingzong; Han, Huiying; Song, Sha; Xu, Hongxia; Hong, Yating; Yi, Nengjun; Zhuang, Wenzhuo

    2018-05-10

    Multiple myeloma (MM), like other cancers, is caused by the accumulation of genetic abnormalities. Heterogeneity exists in the patients' response to treatments, for example, bortezomib. This urges efforts to identify biomarkers from numerous molecular features and build predictive models for identifying patients that can benefit from a certain treatment scheme. However, previous studies treated the multi-level ordinal drug response as a binary response where only responsive and non-responsive groups are considered. It is desirable to directly analyze the multi-level drug response, rather than combining the response to two groups. In this study, we present a novel method to identify significantly associated biomarkers and then develop ordinal genomic classifier using the hierarchical ordinal logistic model. The proposed hierarchical ordinal logistic model employs the heavy-tailed Cauchy prior on the coefficients and is fitted by an efficient quasi-Newton algorithm. We apply our hierarchical ordinal regression approach to analyze two publicly available datasets for MM with five-level drug response and numerous gene expression measures. Our results show that our method is able to identify genes associated with the multi-level drug response and to generate powerful predictive models for predicting the multi-level response. The proposed method allows us to jointly fit numerous correlated predictors and thus build efficient models for predicting the multi-level drug response. The predictive model for the multi-level drug response can be more informative than the previous approaches. Thus, the proposed approach provides a powerful tool for predicting multi-level drug response and has important impact on cancer studies.

  11. OH-PRED: prediction of protein hydroxylation sites by incorporating adapted normal distribution bi-profile Bayes feature extraction and physicochemical properties of amino acids.

    PubMed

    Jia, Cang-Zhi; He, Wen-Ying; Yao, Yu-Hua

    2017-03-01

    Hydroxylation of proline or lysine residues in proteins is a common post-translational modification event, and such modifications are found in many physiological and pathological processes. Nonetheless, the exact molecular mechanism of hydroxylation remains under investigation. Because experimental identification of hydroxylation is time-consuming and expensive, bioinformatics tools with high accuracy represent desirable alternatives for large-scale rapid identification of protein hydroxylation sites. In view of this, we developed a supporter vector machine-based tool, OH-PRED, for the prediction of protein hydroxylation sites using the adapted normal distribution bi-profile Bayes feature extraction in combination with the physicochemical property indexes of the amino acids. In a jackknife cross validation, OH-PRED yields an accuracy of 91.88% and a Matthew's correlation coefficient (MCC) of 0.838 for the prediction of hydroxyproline sites, and yields an accuracy of 97.42% and a MCC of 0.949 for the prediction of hydroxylysine sites. These results demonstrate that OH-PRED increased significantly the prediction accuracy of hydroxyproline and hydroxylysine sites by 7.37 and 14.09%, respectively, when compared with the latest predictor PredHydroxy. In independent tests, OH-PRED also outperforms previously published methods.

  12. Scalable and Cost-Effective Assignment of Mobile Crowdsensing Tasks Based on Profiling Trends and Prediction: The ParticipAct Living Lab Experience

    PubMed Central

    Bellavista, Paolo; Corradi, Antonio; Foschini, Luca; Ianniello, Raffaele

    2015-01-01

    Nowadays, sensor-rich smartphones potentially enable the harvesting of huge amounts of valuable sensing data in urban environments, by opportunistically involving citizens to play the role of mobile virtual sensors to cover Smart City areas of interest. This paper proposes an in-depth study of the challenging technical issues related to the efficient assignment of Mobile Crowd Sensing (MCS) data collection tasks to volunteers in a crowdsensing campaign. In particular, the paper originally describes how to increase the effectiveness of the proposed sensing campaigns through the inclusion of several new facilities, including accurate participant selection algorithms able to profile and predict user mobility patterns, gaming techniques, and timely geo-notification. The reported results show the feasibility of exploiting profiling trends/prediction techniques from volunteers’ behavior; moreover, they quantitatively compare different MCS task assignment strategies based on large-scale and real MCS data campaigns run in the ParticipAct living lab, an ongoing MCS real-world experiment that involved more than 170 students of the University of Bologna for more than one year. PMID:26263985

  13. Improving spatial prediction of Schistosoma haematobium prevalence in southern Ghana through new remote sensors and local water access profiles.

    PubMed

    Kulinkina, Alexandra V; Walz, Yvonne; Koch, Magaly; Biritwum, Nana-Kwadwo; Utzinger, Jürg; Naumova, Elena N

    2018-06-04

    Schistosomiasis is a water-related neglected tropical disease. In many endemic low- and middle-income countries, insufficient surveillance and reporting lead to poor characterization of the demographic and geographic distribution of schistosomiasis cases. Hence, modeling is relied upon to predict areas of high transmission and to inform control strategies. We hypothesized that utilizing remotely sensed (RS) environmental data in combination with water, sanitation, and hygiene (WASH) variables could improve on the current predictive modeling approaches. Schistosoma haematobium prevalence data, collected from 73 rural Ghanaian schools, were used in a random forest model to investigate the predictive capacity of 15 environmental variables derived from RS data (Landsat 8, Sentinel-2, and Global Digital Elevation Model) with fine spatial resolution (10-30 m). Five methods of variable extraction were tested to determine the spatial linkage between school-based prevalence and the environmental conditions of potential transmission sites, including applying the models to known human water contact locations. Lastly, measures of local water access and groundwater quality were incorporated into RS-based models to assess the relative importance of environmental and WASH variables. Predictive models based on environmental characterization of specific locations where people contact surface water bodies offered some improvement as compared to the traditional approach based on environmental characterization of locations where prevalence is measured. A water index (MNDWI) and topographic variables (elevation and slope) were important environmental risk factors, while overall, groundwater iron concentration predominated in the combined model that included WASH variables. The study helps to understand localized drivers of schistosomiasis transmission. Specifically, unsatisfactory water quality in boreholes perpetuates reliance of surface water bodies, indirectly increasing

  14. Intestinal alkaline phosphatase inhibits the proinflammatory nucleotide uridine diphosphate.

    PubMed

    Moss, Angela K; Hamarneh, Sulaiman R; Mohamed, Mussa M Rafat; Ramasamy, Sundaram; Yammine, Halim; Patel, Palak; Kaliannan, Kanakaraju; Alam, Sayeda N; Muhammad, Nur; Moaven, Omeed; Teshager, Abeba; Malo, Nondita S; Narisawa, Sonoko; Millán, José Luis; Warren, H Shaw; Hohmann, Elizabeth; Malo, Madhu S; Hodin, Richard A

    2013-03-15

    Uridine diphosphate (UDP) is a proinflammatory nucleotide implicated in inflammatory bowel disease. Intestinal alkaline phosphatase (IAP) is a gut mucosal defense factor capable of inhibiting intestinal inflammation. We used the malachite green assay to show that IAP dephosphorylates UDP. To study the anti-inflammatory effect of IAP, UDP or other proinflammatory ligands (LPS, flagellin, Pam3Cys, or TNF-α) in the presence or absence of IAP were applied to cell cultures, and IL-8 was measured. UDP caused dose-dependent increase in IL-8 release by immune cells and two gut epithelial cell lines, and IAP treatment abrogated IL-8 release. Costimulation with UDP and other inflammatory ligands resulted in a synergistic increase in IL-8 release, which was prevented by IAP treatment. In vivo, UDP in the presence or absence of IAP was instilled into a small intestinal loop model in wild-type and IAP-knockout mice. Luminal contents were applied to cell culture, and cytokine levels were measured in culture supernatant and intestinal tissue. UDP-treated luminal contents induced more inflammation on target cells, with a greater inflammatory response to contents from IAP-KO mice treated with UDP than from WT mice. Additionally, UDP treatment increased TNF-α levels in intestinal tissue of IAP-KO mice, and cotreatment with IAP reduced inflammation to control levels. Taken together, these studies show that IAP prevents inflammation caused by UDP alone and in combination with other ligands, and the anti-inflammatory effect of IAP against UDP persists in mouse small intestine. The benefits of IAP in intestinal disease may be partly due to inhibition of the proinflammatory activity of UDP.

  15. The molecular basis for development of proinflammatory autoantibodies to progranulin.

    PubMed

    Thurner, Lorenz; Fadle, Natalie; Regitz, Evi; Kemele, Maria; Klemm, Philipp; Zaks, Marina; Stöger, Elisabeth; Bette, Birgit; Carbon, Gabi; Zimmer, Vincent; Assmann, Gunter; Murawski, Niels; Kubuschok, Boris; Held, Gerhard; Preuss, Klaus-Dieter; Pfreundschuh, Michael

    2015-07-01

    Recently we identified in a wide spectrum of autoimmune diseases frequently occurring proinflammatory autoantibodies directed against progranulin, a direct inhibitor of TNFR1 & 2 and of DR3. In the present study we investigated the mechanisms for the breakdown of self-tolerance against progranulin. Isoelectric focusing identified a second, differentially electrically charged progranulin isoform exclusively present in progranulin-antibody-positive patients. Alkaline phosphatase treatment revealed this additional progranulin isoform to be hyperphosphorylated. Subsequently Ser81, which is located within the epitope region of progranulin-antibodies, was identified as hyperphosphorylated serine residue by site directed mutagenesis of candidate phosphorylation sites. Hyperphosphorylated progranulin was detected exclusively in progranulin-antibody-positive patients during the courses of their diseases. The occurrence of hyperphosphorylated progranulin preceded seroconversions of progranulin-antibodies, indicating adaptive immune response. Utilizing panels of kinase and phosphatase inhibitors, PKCβ1 was identified as the relevant kinase and PP1 as the relevant phosphatase for phosphorylation and dephosphorylation of Ser81. In contrast to normal progranulin, hyperphosphorylated progranulin interacted exclusively with inactivated (pThr320) PP1, suggesting inactivated PP1 to cause the detectable occurrence of phosphorylated Ser81 PGRN. Investigation of possible functional alterations of PGRN due to Ser81 phosphorylation revealed, that hyperphosphorylation prevents the interaction and thus direct inhibition of TNFR1, TNFR2 and DR3, representing an additional direct proinflammatory effect. Finally phosphorylation of Ser81 PGRN alters the conversion pattern of PGRN. In conclusion, inactivated PP1 induces hyperphosphorylation of progranulin in a wide spectrum of autoimmune diseases. This hyperphosphorylation prevents direct inhibition of TNFR1, TNFR2 and DR3 by PGRN, alters the

  16. Intestinal alkaline phosphatase inhibits the proinflammatory nucleotide uridine diphosphate

    PubMed Central

    Hamarneh, Sulaiman R.; Mohamed, Mussa M. Rafat; Ramasamy, Sundaram; Yammine, Halim; Patel, Palak; Kaliannan, Kanakaraju; Alam, Sayeda N.; Muhammad, Nur; Moaven, Omeed; Teshager, Abeba; Malo, Nondita S.; Narisawa, Sonoko; Millán, José Luis; Warren, H. Shaw; Hohmann, Elizabeth; Malo, Madhu S.; Hodin, Richard A.

    2013-01-01

    Uridine diphosphate (UDP) is a proinflammatory nucleotide implicated in inflammatory bowel disease. Intestinal alkaline phosphatase (IAP) is a gut mucosal defense factor capable of inhibiting intestinal inflammation. We used the malachite green assay to show that IAP dephosphorylates UDP. To study the anti-inflammatory effect of IAP, UDP or other proinflammatory ligands (LPS, flagellin, Pam3Cys, or TNF-α) in the presence or absence of IAP were applied to cell cultures, and IL-8 was measured. UDP caused dose-dependent increase in IL-8 release by immune cells and two gut epithelial cell lines, and IAP treatment abrogated IL-8 release. Costimulation with UDP and other inflammatory ligands resulted in a synergistic increase in IL-8 release, which was prevented by IAP treatment. In vivo, UDP in the presence or absence of IAP was instilled into a small intestinal loop model in wild-type and IAP-knockout mice. Luminal contents were applied to cell culture, and cytokine levels were measured in culture supernatant and intestinal tissue. UDP-treated luminal contents induced more inflammation on target cells, with a greater inflammatory response to contents from IAP-KO mice treated with UDP than from WT mice. Additionally, UDP treatment increased TNF-α levels in intestinal tissue of IAP-KO mice, and cotreatment with IAP reduced inflammation to control levels. Taken together, these studies show that IAP prevents inflammation caused by UDP alone and in combination with other ligands, and the anti-inflammatory effect of IAP against UDP persists in mouse small intestine. The benefits of IAP in intestinal disease may be partly due to inhibition of the proinflammatory activity of UDP. PMID:23306083

  17. Histogram Profiling of Postcontrast T1-Weighted MRI Gives Valuable Insights into Tumor Biology and Enables Prediction of Growth Kinetics and Prognosis in Meningiomas.

    PubMed

    Gihr, Georg Alexander; Horvath-Rizea, Diana; Kohlhof-Meinecke, Patricia; Ganslandt, Oliver; Henkes, Hans; Richter, Cindy; Hoffmann, Karl-Titus; Surov, Alexey; Schob, Stefan

    2018-06-14

    Meningiomas are the most frequently diagnosed intracranial masses, oftentimes requiring surgery. Especially procedure-related morbidity can be substantial, particularly in elderly patients. Hence, reliable imaging modalities enabling pretherapeutic prediction of tumor grade, growth kinetic, realistic prognosis, and-as a consequence-necessity of surgery are of great value. In this context, a promising diagnostic approach is advanced analysis of magnetic resonance imaging data. Therefore, our study investigated whether histogram profiling of routinely acquired postcontrast T1-weighted images is capable of separating low-grade from high-grade lesions and whether histogram parameters reflect Ki-67 expression in meningiomas. Pretreatment T1-weighted postcontrast volumes of 44 meningioma patients were used for signal intensity histogram profiling. WHO grade, tumor volume, and Ki-67 expression were evaluated. Comparative and correlative statistics investigating the association between histogram profile parameters and neuropathology were performed. None of the investigated histogram parameters revealed significant differences between low-grade and high-grade meningiomas. However, significant correlations were identified between Ki-67 and the histogram parameters skewness and entropy as well as between entropy and tumor volume. Contrary to previously reported findings, pretherapeutic postcontrast T1-weighted images can be used to predict growth kinetics in meningiomas if whole tumor histogram analysis is employed. However, no differences between distinct WHO grades were identifiable in out cohort. As a consequence, histogram analysis of postcontrast T1-weighted images is a promising approach to obtain quantitative in vivo biomarkers reflecting the proliferative potential in meningiomas. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

  18. Combining solvent thermodynamic profiles with functionality maps of the Hsp90 binding site to predict the displacement of water molecules.

    PubMed

    Haider, Kamran; Huggins, David J

    2013-10-28

    Intermolecular interactions in the aqueous phase must compete with the interactions between the two binding partners and their solvating water molecules. In biological systems, water molecules in protein binding sites cluster at well-defined hydration sites and can form strong hydrogen-bonding interactions with backbone and side-chain atoms. Displacement of such water molecules is only favorable when the ligand can form strong compensating hydrogen bonds. Conversely, water molecules in hydrophobic regions of protein binding sites make only weak interactions, and the requirements for favorable displacement are less stringent. The propensity of water molecules for displacement can be identified using inhomogeneous fluid solvation theory (IFST), a statistical mechanical method that decomposes the solvation free energy of a solute into the contributions from different spatial regions and identifies potential binding hotspots. In this study, we employed IFST to study the displacement of water molecules from the ATP binding site of Hsp90, using a test set of 103 ligands. The predicted contribution of a hydration site to the hydration free energy was found to correlate well with the observed displacement. Additionally, we investigated if this correlation could be improved by using the energetic scores of favorable probe groups binding at the location of hydration sites, derived from a multiple copy simultaneous search (MCSS) method. The probe binding scores were not highly predictive of the observed displacement and did not improve the predictivity when used in combination with IFST-based hydration free energies. The results show that IFST alone can be used to reliably predict the observed displacement of water molecules in Hsp90. However, MCSS can augment IFST calculations by suggesting which functional groups should be used to replace highly displaceable water molecules. Such an approach could be very useful in improving the hit-to-lead process for new drug targets.

  19. CpG island methylation profile in non-invasive oral rinse samples is predictive of oral and pharyngeal carcinoma.

    PubMed

    Langevin, Scott M; Eliot, Melissa; Butler, Rondi A; Cheong, Agnes; Zhang, Xiang; McClean, Michael D; Koestler, Devin C; Kelsey, Karl T

    2015-01-01

    There are currently no screening tests in routine use for oral and pharyngeal cancer beyond visual inspection and palpation, which are provided on an opportunistic basis, indicating a need for development of novel methods for early detection, particularly in high-risk populations. We sought to address this need through comprehensive interrogation of CpG island methylation in oral rinse samples. We used the Infinium HumanMethylation450 BeadArray to interrogate DNA methylation in oral rinse samples collected from 154 patients with incident oral or pharyngeal carcinoma prior to treatment and 72 cancer-free control subjects. Subjects were randomly allocated to either a training or a testing set. For each subject, average methylation was calculated for each CpG island represented on the array. We applied a semi-supervised recursively partitioned mixture model to the CpG island methylation data to identify a classifier for prediction of case status in the training set. We then applied the resultant classifier to the testing set for validation and to assess the predictive accuracy. We identified a methylation classifier comprised of 22 CpG islands, which predicted oral and pharyngeal carcinoma with a high degree of accuracy (AUC = 0.92, 95 % CI 0.86, 0.98). This novel methylation panel is a strong predictor of oral and pharyngeal carcinoma case status in oral rinse samples and may have utility in early detection and post-treatment follow-up.

  20. Immediate Postoperative Pain Scores Predict Neck Pain Profile up to 1 Year Following Anterior Cervical Discectomy and Fusion.

    PubMed

    Adogwa, Owoicho; Elsamadicy, Aladine A; Vuong, Victoria D; Mehta, Ankit I; Vasquez, Raul A; Cheng, Joseph; Bagley, Carlos A; Karikari, Isaac O

    2018-05-01

    Retrospective cohort review. To assess whether immediate postoperative neck pain scores accurately predict 12-month visual analog scale-neck pain (VAS-NP) outcomes following Anterior Cervical Discectomy and Fusion surgery (ACDF). This was a retrospective study of 82 patients undergoing elective ACDF surgery at a major academic medical center. Patient reported outcomes measures VAS-NP scores were recorded on the first postoperative day, then at 6-weeks, 3, 6, and 12-months after surgery. Multivariate correlation and logistic regression methods were utilized to determine whether immediate postoperative VAS-NP score accurately predicted 1-year patient reported VAS-NP Scores. Overall, 46.3% male, 25.6% were smokers, and the mean age and body mass index (BMI) were 53.7 years and 28.28 kg/m 2 , respectively. There were significant correlations between immediate postoperative pain scores and neck pain scores at 6 weeks VAS-NP ( P = .0015), 6 months VAS-NP ( P = .0333), and 12 months VAS-NP ( P = .0247) after surgery. Furthermore, immediate postoperative pain score is an independent predictor of 6 weeks, 6 months, and 1 year VAS-NP scores. Our study suggests that immediate postoperative patient reported neck pain scores accurately predicts and correlates with 12-month VAS-NP scores after an ACDF procedure. Patients with high neck pain scores after surgery are more likely to report persistent neck pain 12 months after index surgery.

  1. Prediction of outcome in newly diagnosed myeloma: a meta-analysis of the molecular profiles of 1905 trial patients

    PubMed Central

    Shah, V; Sherborne, A L; Walker, B A; Johnson, D C; Boyle, E M; Ellis, S; Begum, D B; Proszek, P Z; Jones, J R; Pawlyn, C; Savola, S; Jenner, M W; Drayson, M T; Owen, R G; Houlston, R S; Cairns, D A; Gregory, W M; Cook, G; Davies, F E; Jackson, G H; Morgan, G J; Kaiser, M F

    2018-01-01

    Robust establishment of survival in multiple myeloma (MM) and its relationship to recurrent genetic aberrations is required as outcomes are variable despite apparent similar staging. We assayed copy number alterations (CNA) and translocations in 1036 patients from the NCRI Myeloma XI trial and linked these to overall survival (OS) and progression-free survival. Through a meta-anlysis of these data with data from MRC Myeloma IX trial, totalling 1905 newly diagnosed MM patients (NDMM), we confirm the association of t(4;14), t(14;16), t(14;20), del(17p) and gain(1q21) with poor prognosis with hazard ratios (HRs) for OS of 1.60 (P=4.77 × 10−7), 1.74 (P=0.0005), 1.90 (P=0.0089), 2.10 (P=8.86 × 10−14) and 1.68 (P=2.18 × 10−14), respectively. Patients with ‘double-hit’ defined by co-occurrence of at least two adverse lesions have an especially poor prognosis with HRs for OS of 2.67 (P=8.13 × 10−27) for all patients and 3.19 (P=1.23 × 10−18) for intensively treated patients. Using comprehensive CNA and translocation profiling in Myeloma XI we also demonstrate a strong association between t(4;14) and BIRC2/BIRC3 deletion (P=8.7 × 10−15), including homozygous deletion. Finally, we define distinct sub-groups of hyperdiploid MM, with either gain(1q21) and CCND2 overexpression (P<0.0001) or gain(11q25) and CCND1 overexpression (P<0.0001). Profiling multiple genetic lesions can identify MM patients likely to relapse early allowing stratification of treatment. PMID:28584253

  2. Fatigue in primary Sjögren's syndrome is associated with lower levels of proinflammatory cytokines.

    PubMed

    Howard Tripp, Nadia; Tarn, Jessica; Natasari, Andini; Gillespie, Colin; Mitchell, Sheryl; Hackett, Katie L; Bowman, Simon J; Price, Elizabeth; Pease, Colin T; Emery, Paul; Lanyon, Peter; Hunter, John; Gupta, Monica; Bombardieri, Michele; Sutcliffe, Nurhan; Pitzalis, Costantino; McLaren, John; Cooper, Annie; Regan, Marian; Giles, Ian; Isenberg, David A; Saravanan, Vadivelu; Coady, David; Dasgupta, Bhaskar; McHugh, Neil; Young-Min, Steven; Moots, Robert; Gendi, Nagui; Akil, Mohammed; Griffiths, Bridget; Lendrem, Dennis W; Ng, Wan-Fai

    2016-01-01

    This article reports relationships between serum cytokine levels and patient-reported levels of fatigue, in the chronic immunological condition primary Sjögren's syndrome (pSS). Blood levels of 24 cytokines were measured in 159 patients with pSS from the United Kingdom Primary Sjögren's Syndrome Registry and 28 healthy non-fatigued controls. Differences between cytokines in cases and controls were evaluated using Wilcoxon test. Patient-reported scores for fatigue were evaluated, classified according to severity and compared with cytokine levels using analysis of variance. Logistic regression was used to determine the most important predictors of fatigue levels. 14 cytokines were significantly higher in patients with pSS (n=159) compared to non-fatigued healthy controls (n=28). While serum levels were elevated in patients with pSS compared to healthy controls, unexpectedly, the levels of 4 proinflammatory cytokines-interferon-γ-induced protein-10 (IP-10) (p=0.019), tumour necrosis factor-α (p=0.046), lymphotoxin-α (p=0.034) and interferon-γ (IFN-γ) (p=0.022)-were inversely related to patient-reported levels of fatigue. A regression model predicting fatigue levels in pSS based on cytokine levels, disease-specific and clinical parameters, as well as anxiety, pain and depression, revealed IP-10, IFN-γ (both inversely), pain and depression (both positively) as the most important predictors of fatigue. This model correctly predicts fatigue levels with reasonable (67%) accuracy. Cytokines, pain and depression appear to be the most powerful predictors of fatigue in pSS. Our data challenge the notion that proinflammatory cytokines directly mediate fatigue in chronic immunological conditions. Instead, we hypothesise that mechanisms regulating inflammatory responses may be important.

  3. Fatigue in primary Sjögren's syndrome is associated with lower levels of proinflammatory cytokines

    PubMed Central

    Howard Tripp, Nadia; Tarn, Jessica; Natasari, Andini; Gillespie, Colin; Mitchell, Sheryl; Hackett, Katie L; Bowman, Simon J; Price, Elizabeth; Pease, Colin T; Emery, Paul; Lanyon, Peter; Hunter, John; Gupta, Monica; Bombardieri, Michele; Sutcliffe, Nurhan; Pitzalis, Costantino; McLaren, John; Cooper, Annie; Regan, Marian; Giles, Ian; Isenberg, David A; Saravanan, Vadivelu; Coady, David; Dasgupta, Bhaskar; McHugh, Neil; Young-Min, Steven; Moots, Robert; Gendi, Nagui; Akil, Mohammed; Griffiths, Bridget; Lendrem, Dennis W; Ng, Wan-Fai

    2016-01-01

    Objectives This article reports relationships between serum cytokine levels and patient-reported levels of fatigue, in the chronic immunological condition primary Sjögren's syndrome (pSS). Methods Blood levels of 24 cytokines were measured in 159 patients with pSS from the United Kingdom Primary Sjögren's Syndrome Registry and 28 healthy non-fatigued controls. Differences between cytokines in cases and controls were evaluated using Wilcoxon test. Patient-reported scores for fatigue were evaluated, classified according to severity and compared with cytokine levels using analysis of variance. Logistic regression was used to determine the most important predictors of fatigue levels. Results 14 cytokines were significantly higher in patients with pSS (n=159) compared to non-fatigued healthy controls (n=28). While serum levels were elevated in patients with pSS compared to healthy controls, unexpectedly, the levels of 4 proinflammatory cytokines—interferon-γ-induced protein-10 (IP-10) (p=0.019), tumour necrosis factor-α (p=0.046), lymphotoxin-α (p=0.034) and interferon-γ (IFN-γ) (p=0.022)—were inversely related to patient-reported levels of fatigue. A regression model predicting fatigue levels in pSS based on cytokine levels, disease-specific and clinical parameters, as well as anxiety, pain and depression, revealed IP-10, IFN-γ (both inversely), pain and depression (both positively) as the most important predictors of fatigue. This model correctly predicts fatigue levels with reasonable (67%) accuracy. Conclusions Cytokines, pain and depression appear to be the most powerful predictors of fatigue in pSS. Our data challenge the notion that proinflammatory cytokines directly mediate fatigue in chronic immunological conditions. Instead, we hypothesise that mechanisms regulating inflammatory responses may be important. PMID:27493792

  4. Polycystic Ovary Syndrome as a Proinflammatory State: The Role of Adipokines.

    PubMed

    Dimitriadis, Georgios K; Kyrou, Ioannis; Randeva, Harpal S

    2016-01-01

    Polycystic Ovary Syndrome (PCOS) is a complex heterogeneous disorder and the most common endocrinopathy amongst women of reproductive age. It is characterized by androgen excess, chronic anovulation and an altered cardiometabolic profile. PCOS is linked to impaired adipose tissue (AT) physiology and women with this disorder present with greater risk for insulin resistance (IR), hyperinsulinemia, central adiposity, nonalcoholic fatty liver disease (NAFLD) and type 2 diabetes mellitus (T2DM) than matched for age and body mass index (BMI) women without PCOS. Hyperandrogenaemia appears to be driving adipocyte hypertrophy observed in PCOS under the influence of a hyperinsulinaemic state. Changes in the function of adipocytes have an impact on the secretion of adipokines, adipose tissue-derived proinflammatory factors promoting susceptibility to low grade inflammation. In this article, we review the existing knowledge on the interplay between hyperandrogenaemia, insulin resistance, impaired adipocyte biology, adipokines and chronic low-grade inflammation in PCOS. In PCOS, more than one mechanisms have been suggested in the development of a chronic low-grade inflammation state with the most prevalent being that of a direct effect of the immune system on adipose tissue functions as previously reported in obese women without PCOS. Despite the lack of conclusive evidence regarding a direct mechanism linking hyperandrogenaemia to pro-inflammation in PCOS, there have been recent findings indicating that hyperandrogenaemia might be involved in chronic inflammation by exerting an effect on adipocytes morphology and attributes. Increasing evidence suggests that there is an important connection and interaction between proinflammatory pathways, hyperinsulinemia, androgen excess and adipose tissue hypertrophy and, dysfunction in PCOS. While lifestyle changes and individualized prescription of insulin-sensitizing drugs are common in managing PCOS, further studies are warranted to

  5. GPER Deficiency in Male Mice Results in Insulin Resistance, Dyslipidemia, and a Proinflammatory State

    PubMed Central

    Sharma, Geetanjali; Hu, Chelin; Brigman, Jonathan L.; Zhu, Gang; Hathaway, Helen J.

    2013-01-01

    Estrogen is an important regulator of metabolic syndrome, a collection of abnormalities including obesity, insulin resistance/glucose intolerance, hypertension, dyslipidemia, and inflammation, which together lead to increased risk of cardiovascular disease and diabetes. The role of the G protein-coupled estrogen receptor (GPER/GPR30), particularly in males, in these pathologies remains unclear. We therefore sought to determine whether loss of GPER contributes to aspects of metabolic syndrome in male mice. Although 6-month-old male and female GPER knockout (KO) mice displayed increased body weight compared with wild-type littermates, only female GPER KO mice exhibited glucose intolerance at this age. Weight gain in male GPER KO mice was associated with increases in both visceral and sc fat. GPER KO mice, however, exhibited no differences in food intake or locomotor activity. One-year-old male GPER KO mice displayed an abnormal lipid profile with higher cholesterol and triglyceride levels. Fasting blood glucose levels remained normal, whereas insulin levels were elevated. Although insulin resistance was evident in GPER KO male mice from 6 months onward, glucose intolerance was pronounced only at 18 months of age. Furthermore, by 2 years of age, a proinflammatory phenotype was evident, with increases in the proinflammatory and immunomodulatory cytokines IL-1β, IL-6, IL-12, TNFα, monocyte chemotactic protein-1, interferon γ-induced protein 10, and monokine induced by interferon gamma and a concomitant decrease in the adipose-specific cytokine adiponectin. In conclusion, our study demonstrates for the first time that in male mice, GPER regulates metabolic parameters associated with obesity and diabetes. PMID:23970785

  6. GPER deficiency in male mice results in insulin resistance, dyslipidemia, and a proinflammatory state.

    PubMed

    Sharma, Geetanjali; Hu, Chelin; Brigman, Jonathan L; Zhu, Gang; Hathaway, Helen J; Prossnitz, Eric R

    2013-11-01

    Estrogen is an important regulator of metabolic syndrome, a collection of abnormalities including obesity, insulin resistance/glucose intolerance, hypertension, dyslipidemia, and inflammation, which together lead to increased risk of cardiovascular disease and diabetes. The role of the G protein-coupled estrogen receptor (GPER/GPR30), particularly in males, in these pathologies remains unclear. We therefore sought to determine whether loss of GPER contributes to aspects of metabolic syndrome in male mice. Although 6-month-old male and female GPER knockout (KO) mice displayed increased body weight compared with wild-type littermates, only female GPER KO mice exhibited glucose intolerance at this age. Weight gain in male GPER KO mice was associated with increases in both visceral and sc fat. GPER KO mice, however, exhibited no differences in food intake or locomotor activity. One-year-old male GPER KO mice displayed an abnormal lipid profile with higher cholesterol and triglyceride levels. Fasting blood glucose levels remained normal, whereas insulin levels were elevated. Although insulin resistance was evident in GPER KO male mice from 6 months onward, glucose intolerance was pronounced only at 18 months of age. Furthermore, by 2 years of age, a proinflammatory phenotype was evident, with increases in the proinflammatory and immunomodulatory cytokines IL-1β, IL-6, IL-12, TNFα, monocyte chemotactic protein-1, interferon γ-induced protein 10, and monokine induced by interferon gamma and a concomitant decrease in the adipose-specific cytokine adiponectin. In conclusion, our study demonstrates for the first time that in male mice, GPER regulates metabolic parameters associated with obesity and diabetes.

  7. Lack of Interferon and Proinflammatory Cyto/chemokines in Serologically Active Clinically Quiescent Systemic Lupus Erythematosus.

    PubMed

    Steiman, Amanda J; Gladman, Dafna D; Ibañez, Dominique; Noamani, Babak; Landolt-Marticorena, Carolina; Urowitz, Murray B; Wither, Joan E

    2015-12-01

    Serologically active clinically quiescent (SACQ) patients with systemic lupus erythematosus (SLE) remain clinically quiescent for prolonged periods despite anti-dsDNA antibodies and/or low complements, indicating the presence of immune complexes. The immune mechanisms leading to this quiescence are unknown. However, in addition to activating complement, immune complex uptake by various cells leads to the production of interferon (IFN)-α and other proinflammatory factors that are also involved in tissue damage. Here we investigate whether production of these factors is reduced in SACQ patients. The levels of 5 IFN-induced genes and 19 cyto/chemokines were measured in SACQ patients and were compared with those in serologically and clinically active (SACA) and serologically and clinically quiescent (SQCQ) patients. SACQ and SQCQ were defined as ≥ 2 years without clinical activity, with/without persistent serologic activity, respectively, and off corticosteroids/immunosuppressives. SACA was defined as disease activity compelling immunosuppression. Levels of OAS1, IFIT1, MX1, LY6E, and ISG15 were measured by quantitative real-time polymerase chain reaction (PCR) and a composite score (IFN-5) derived from this. Plasma cyto/chemokines were measured by Luminex assay. Nonparametric univariate and logistic regression analyses were conducted. There were no differences in gene expression or cyto/chemokine levels between SACQ and SQCQ patients. The SACQ IFN-5 score was significantly lower than that of SACA (p = 0.003) and was driven by SACQ status, not by autoantibody profile or disease duration. Levels of granulocyte-macrophage colony-stimulating factor, interleukin (IL) 6, IL-10, IFN-γ-inducible protein 10, monocyte chemoattractant protein 1, and tumor necrosis factor-α were significantly lower in SACQ than SACA. The levels of proinflammatory factors in SACQ mirror those of SQCQ patients, indicating reduced production of these factors despite the presence of immune

  8. Antimicrobial peptides and pro-inflammatory cytokines are differentially regulated across epidermal layers following bacterial stimuli.

    PubMed

    Percoco, Giuseppe; Merle, Chloé; Jaouen, Thomas; Ramdani, Yasmina; Bénard, Magalie; Hillion, Mélanie; Mijouin, Lily; Lati, Elian; Feuilloley, Marc; Lefeuvre, Luc; Driouich, Azeddine; Follet-Gueye, Marie-Laure

    2013-12-01

    The skin is a natural barrier between the body and the environment and is colonised by a large number of microorganisms. Here, we report a complete analysis of the response of human skin explants to microbial stimuli. Using this ex vivo model, we analysed at both the gene and protein level the response of epidermal cells to Staphylococcus epidermidis (S. epidermidis) and Pseudomonas fluorescens (P. fluorescens), which are present in the cutaneous microbiota. We showed that both bacterial species affect the structure of skin explants without penetrating the living epidermis. We showed by real-time quantitative polymerase chain reaction (qPCR) that S. epidermidis and P. fluorescens increased the levels of transcripts that encode antimicrobial peptides (AMPs), including human β defensin (hBD)2 and hBD3, and the pro-inflammatory cytokines interleukin (IL)-1α and (IL)-1-β, as well as IL-6. In addition, we analysed the effects of bacterial stimuli on the expression profiles of genes related to innate immunity and the inflammatory response across the epidermal layers, using laser capture microdissection (LCM) coupled to qPCR. We showed that AMP transcripts were principally upregulated in suprabasal keratinocytes. Conversely, the expression of pro-inflammatory cytokines was upregulated in the lower epidermis. These findings were confirmed by protein localisation using specific antibodies coupled to optical or electron microscopy. This work underscores the potential value of further studies that use LCM on human skin explants model to study the roles and effects of the epidermal microbiota on human skin physiology. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  9. Comparison of midlatitude ionospheric F region peak parameters and topside Ne profiles from IRI2012 model prediction with ground-based ionosonde and Alouette II observations

    NASA Astrophysics Data System (ADS)

    Gordiyenko, G. I.; Yakovets, A. F.

    2017-07-01

    The ionospheric F2 peak parameters recorded by a ground-based ionosonde at the midlatitude station Alma-Ata [43.25N, 76.92E] were compared with those obtained using the latest version of the IRI model (http://omniweb.gsfc.nasa.gov/vitmo/iri2012_vitmo.html). It was found that for the Alma-Ata (Kazakhstan) location, the IRI2012 model describes well the morphology of seasonal and diurnal variations of the ionospheric critical frequency (foF2) and peak density height (hmF2) monthly medians. The model errors in the median foF2 prediction (percentage deviations between the median foF2 values and their model predictions) were found to vary approximately in the range from about -20% to 34% and showed a stable overestimation in the median foF2 values for daytime in January and July and underestimation for day- and nighttime hours in the equinoctial months. The comparison between the ionosonde hmF2 and IRI results clearly showed that the IRI overestimates the nighttime hmF2 values for March and September months, and the difference is up to 30 km. The daytime Alma-Ata hmF2 data were found to be close to the IRI predictions (deviations are approximately ±10-15 km) in winter and equinoctial months, except in July when the observed hmF2 values were much more (from approximately 50-200 km). The comparison between the Alouette foF2 data and IRI predictions showed mixed results. In particular, the Alouette foF2 data showed a tendency to be overestimated for daytime in winter months similar to the ionosonde data; however, the overestimated foF2 values for nighttime in the autumn equinox were in disagreement with the ionosonde observations. There were large deviations between the observed hmF2 values and their model predictions. The largest deviations were found during winter and summer (up to -90 km). The comparison of the Alouette II electron density profiles with those predicted by the adapted IRI2012 model in the altitude range hmF2 of the satellite position showed a great

  10. Identification of predictive markers of cytarabine response in AML by integrative analysis of gene-expression profiles with multiple phenotypes

    PubMed Central

    Lamba, Jatinder K; Crews, Kristine R; Pounds, Stanley B; Cao, Xueyuan; Gandhi, Varsha; Plunkett, William; Razzouk, Bassem I; Lamba, Vishal; Baker, Sharyn D; Raimondi, Susana C; Campana, Dario; Pui, Ching-Hon; Downing, James R; Rubnitz, Jeffrey E; Ribeiro, Raul C

    2011-01-01

    Aim To identify gene-expression signatures predicting cytarabine response by an integrative analysis of multiple clinical and pharmacological end points in acute myeloid leukemia (AML) patients. Materials & methods We performed an integrated analysis to associate the gene expression of diagnostic bone marrow blasts from acute myeloid leukemia (AML) patients treated in the discovery set (AML97; n = 42) and in the independent validation set (AML02; n = 46) with multiple clinical and pharmacological end points. Based on prior biological knowledge, we defined a gene to show a therapeutically beneficial (detrimental) pattern of association of its expression positively (negatively) correlated with favorable phenotypes such as intracellular cytarabine 5´-triphosphate levels, morphological response and event-free survival, and negatively (positively) correlated with unfavorable end points such as post-cytarabine DNA synthesis levels, minimal residual disease and cytarabine LC50. Results We identified 240 probe sets predicting a therapeutically beneficial pattern and 97 predicting detrimental pattern (p ≤ 0.005) in the discovery set. Of these, 60 were confirmed in the independent validation set. The validated probe sets correspond to genes involved in PIK3/PTEN/AKT/mTOR signaling, G-protein-coupled receptor signaling and leukemogenesis. This suggests that targeting these pathways as potential pharmacogenomic and therapeutic candidates could be useful for improving treatment outcomes in AML. Conclusion This study illustrates the power of integrated data analysis of genomic data as well as multiple clinical and pharmacologic end points in the identification of genes and pathways of biological relevance. PMID:21449673

  11. Plasma Lipidomic Profiles Improve on Traditional Risk Factors for the Prediction of Cardiovascular Events in Type 2 Diabetes Mellitus.

    PubMed

    Alshehry, Zahir H; Mundra, Piyushkumar A; Barlow, Christopher K; Mellett, Natalie A; Wong, Gerard; McConville, Malcolm J; Simes, John; Tonkin, Andrew M; Sullivan, David R; Barnes, Elizabeth H; Nestel, Paul J; Kingwell, Bronwyn A; Marre, Michel; Neal, Bruce; Poulter, Neil R; Rodgers, Anthony; Williams, Bryan; Zoungas, Sophia; Hillis, Graham S; Chalmers, John; Woodward, Mark; Meikle, Peter J

    2016-11-22

    Clinical lipid measurements do not show the full complexity of the altered lipid metabolism associated with diabetes mellitus or cardiovascular disease. Lipidomics enables the assessment of hundreds of lipid species as potential markers for disease risk. Plasma lipid species (310) were measured by a targeted lipidomic analysis with liquid chromatography electrospray ionization-tandem mass spectrometry on a case-cohort (n=3779) subset from the ADVANCE trial (Action in Diabetes and Vascular Disease: Preterax and Diamicron-MR Controlled Evaluation). The case-cohort was 61% male with a mean age of 67 years. All participants had type 2 diabetes mellitus with ≥1 additional cardiovascular risk factors, and 35% had a history of macrovascular disease. Weighted Cox regression was used to identify lipid species associated with future cardiovascular events (nonfatal myocardial infarction, nonfatal stroke, and cardiovascular death) and cardiovascular death during a 5-year follow-up period. Multivariable models combining traditional risk factors with lipid species were optimized with the Akaike information criteria. C statistics and NRIs were calculated within a 5-fold cross-validation framework. Sphingolipids, phospholipids (including lyso- and ether- species), cholesteryl esters, and glycerolipids were associated with future cardiovascular events and cardiovascular death. The addition of 7 lipid species to a base model (14 traditional risk factors and medications) to predict cardiovascular events increased the C statistic from 0.680 (95% confidence interval [CI], 0.678-0.682) to 0.700 (95% CI, 0.698-0.702; P<0.0001) with a corresponding continuous NRI of 0.227 (95% CI, 0.219-0.235). The prediction of cardiovascular death was improved with the incorporation of 4 lipid species into the base model, showing an increase in the C statistic from 0.740 (95% CI, 0.738-0.742) to 0.760 (95% CI, 0.757-0.762; P<0.0001) and a continuous net reclassification index of 0.328 (95% CI, 0

  12. Qualitative and quantitative prediction of volatile compounds from initial amino acid profiles in Korean rice wine (makgeolli) model.

    PubMed

    Kang, Bo-Sik; Lee, Jang-Eun; Park, Hyun-Jin

    2014-06-01

    In Korean rice wine (makgeolli) model, we tried to develop a prediction model capable of eliciting a quantitative relationship between initial amino acids in makgeolli mash and major aromatic compounds, such as fusel alcohols, their acetate esters, and ethyl esters of fatty acids, in makgeolli brewed. Mass-spectrometry-based electronic nose (MS-EN) was used to qualitatively discriminate between makgeollis made from makgeolli mashes with different amino acid compositions. Following this measurement, headspace solid-phase microextraction coupled to gas chromatography-mass spectrometry (GC-MS) combined with partial least-squares regression (PLSR) method was employed to quantitatively correlate amino acid composition of makgeolli mash with major aromatic compounds evolved during makgeolli fermentation. In qualitative prediction with MS-EN analysis, the makgeollis were well discriminated according to the volatile compounds derived from amino acids of makgeolli mash. Twenty-seven ion fragments with mass-to-charge ratio (m/z) of 55 to 98 amu were responsible for the discrimination. In GC-MS combined with PLSR method, a quantitative approach between the initial amino acids of makgeolli mash and the fusel compounds of makgeolli demonstrated that coefficient of determination (R(2)) of most of the fusel compounds ranged from 0.77 to 0.94 in good correlation, except for 2-phenylethanol (R(2) = 0.21), whereas R(2) for ethyl esters of MCFAs including ethyl caproate, ethyl caprylate, and ethyl caprate was 0.17 to 0.40 in poor correlation. The amino acids have been known to affect the aroma in alcoholic beverages. In this study, we demonstrated that an electronic nose qualitatively differentiated Korean rice wines (makgeollis) by their volatile compounds evolved from amino acids with rapidity and reproducibility and successively, a quantitative correlation with acceptable R2 between amino acids and fusel compounds could be established via HS-SPME GC-MS combined with partial least

  13. Early Attachment-Figure Separation and Increased Risk for Later Depression: Potential Mediation by Proinflammatory Processes

    PubMed Central

    Hennessy, Michael B.; Deak, Terrence; Schiml-Webb, Patricia A.

    2009-01-01

    Early maternal separation and other disruptions of attachment relations are known to increase risk for the later onset of depressive illness in vulnerable individuals. It is suggested here that sensitization involving proinflammatory processes may contribute to this effect. This argument is based on: (1) current notions of the role of proinflammatory cytokines in depressive illness; (2) evidence that proinflammatory cytokines mediate depressive-like behavior during separation in a rodent model of infant attachment; and (3) comparisons of the effects of early proinflammatory activation versus maternal separation on later proinflammatory activity and biobehavioral processes related to depression. The possible interaction of proinflammatory processes and corticotropin-releasing factor in the sensitization process is discussed. PMID:20359585

  14. Physical fitness predicts technical-tactical and time-motion profile in simulated Judo and Brazilian Jiu-Jitsu matches

    PubMed Central

    Gentil, Paulo; Bueno, João C.A.; Follmer, Bruno; Marques, Vitor A.; Del Vecchio, Fabrício B.

    2018-01-01

    Background Among combat sports, Judo and Brazilian Jiu-Jitsu (BJJ) present elevated physical fitness demands from the high-intensity intermittent efforts. However, information regarding how metabolic and neuromuscular physical fitness is associated with technical-tactical performance in Judo and BJJ fights is not available. This study aimed to relate indicators of physical fitness with combat performance variables in Judo and BJJ. Methods The sample consisted of Judo (n = 16) and BJJ (n = 24) male athletes. At the first meeting, the physical tests were applied and, in the second, simulated fights were performed for later notational analysis. Results The main findings indicate: (i) high reproducibility of the proposed instrument and protocol used for notational analysis in a mobile device; (ii) differences in the technical-tactical and time-motion patterns between modalities; (iii) performance-related variables are different in Judo and BJJ; and (iv) regression models based on metabolic fitness variables may account for up to 53% of the variances in technical-tactical and/or time-motion variables in Judo and up to 31% in BJJ, whereas neuromuscular fitness models can reach values up to 44 and 73% of prediction in Judo and BJJ, respectively. When all components are combined, they can explain up to 90% of high intensity actions in Judo. Discussion In conclusion, performance prediction models in simulated combat indicate that anaerobic, aerobic and neuromuscular fitness variables contribute to explain time-motion variables associated with high intensity and technical-tactical variables in Judo and BJJ fights. PMID:29844991

  15. Profiling of histone H3 lysine 9 trimethylation levels predicts transcription factor activity and survival in acute myeloid leukemia.

    PubMed

    Müller-Tidow, Carsten; Klein, Hans-Ulrich; Hascher, Antje; Isken, Fabienne; Tickenbrock, Lara; Thoennissen, Nils; Agrawal-Singh, Shuchi; Tschanter, Petra; Disselhoff, Christine; Wang, Yipeng; Becker, Anke; Thiede, Christian; Ehninger, Gerhard; zur Stadt, Udo; Koschmieder, Steffen; Seidl, Matthias; Müller, Frank U; Schmitz, Wilhelm; Schlenke, Peter; McClelland, Michael; Berdel, Wolfgang E; Dugas, Martin; Serve, Hubert

    2010-11-04

    Acute myeloid leukemia (AML) is commonly associated with alterations in transcription factors because of altered expression or gene mutations. These changes might induce leukemia-specific patterns of histone modifications. We used chromatin-immunoprecipitation on microarray to analyze histone 3 lysine 9 trimethylation (H3K9me3) patterns in primary AML (n = 108), acute lymphoid leukemia (n = 28), CD34(+) cells (n = 21) and white blood cells (n = 15) specimens. Hundreds of promoter regions in AML showed significant alterations in H3K9me3 levels. H3K9me3 deregulation in AML occurred preferentially as a decrease in H3K9me3 levels at core promoter regions. The altered genomic regions showed an overrepresentation of cis-binding sites for ETS and cyclic adenosine monophosphate response elements (CREs) for transcription factors of the CREB/CREM/ATF1 family. The decrease in H3K9me3 levels at CREs was associated with increased CRE-driven promoter activity in AML blasts in vivo. AML-specific H3K9me3 patterns were not associated with known cytogenetic abnormalities. But a signature derived from H3K9me3 patterns predicted event-free survival in AML patients. When the H3K9me3 signature was combined with established clinical prognostic markers, it outperformed prognosis prediction based on clinical parameters alone. These findings demonstrate widespread changes of H3K9me3 levels at gene promoters in AML. Signatures of histone modification patterns are associated with patient prognosis in AML.

  16. Physical fitness predicts technical-tactical and time-motion profile in simulated Judo and Brazilian Jiu-Jitsu matches.

    PubMed

    Coswig, Victor S; Gentil, Paulo; Bueno, João C A; Follmer, Bruno; Marques, Vitor A; Del Vecchio, Fabrício B

    2018-01-01

    Among combat sports, Judo and Brazilian Jiu-Jitsu (BJJ) present elevated physical fitness demands from the high-intensity intermittent efforts. However, information regarding how metabolic and neuromuscular physical fitness is associated with technical-tactical performance in Judo and BJJ fights is not available. This study aimed to relate indicators of physical fitness with combat performance variables in Judo and BJJ. The sample consisted of Judo ( n  = 16) and BJJ ( n  = 24) male athletes. At the first meeting, the physical tests were applied and, in the second, simulated fights were performed for later notational analysis. The main findings indicate: (i) high reproducibility of the proposed instrument and protocol used for notational analysis in a mobile device; (ii) differences in the technical-tactical and time-motion patterns between modalities; (iii) performance-related variables are different in Judo and BJJ; and (iv) regression models based on metabolic fitness variables may account for up to 53% of the variances in technical-tactical and/or time-motion variables in Judo and up to 31% in BJJ, whereas neuromuscular fitness models can reach values up to 44 and 73% of prediction in Judo and BJJ, respectively. When all components are combined, they can explain up to 90% of high intensity actions in Judo. In conclusion, performance prediction models in simulated combat indicate that anaerobic, aerobic and neuromuscular fitness variables contribute to explain time-motion variables associated with high intensity and technical-tactical variables in Judo and BJJ fights.

  17. Profiling of histone H3 lysine 9 trimethylation levels predicts transcription factor activity and survival in acute myeloid leukemia

    PubMed Central

    Klein, Hans-Ulrich; Hascher, Antje; Isken, Fabienne; Tickenbrock, Lara; Thoennissen, Nils; Agrawal-Singh, Shuchi; Tschanter, Petra; Disselhoff, Christine; Wang, Yipeng; Becker, Anke; Thiede, Christian; Ehninger, Gerhard; zur Stadt, Udo; Koschmieder, Steffen; Seidl, Matthias; Müller, Frank U.; Schmitz, Wilhelm; Schlenke, Peter; McClelland, Michael; Berdel, Wolfgang E.; Dugas, Martin; Serve, Hubert

    2010-01-01

    Acute myeloid leukemia (AML) is commonly associated with alterations in transcription factors because of altered expression or gene mutations. These changes might induce leukemia-specific patterns of histone modifications. We used chromatin-immunoprecipitation on microarray to analyze histone 3 lysine 9 trimethylation (H3K9me3) patterns in primary AML (n = 108), acute lymphoid leukemia (n = 28), CD34+ cells (n = 21) and white blood cells (n = 15) specimens. Hundreds of promoter regions in AML showed significant alterations in H3K9me3 levels. H3K9me3 deregulation in AML occurred preferentially as a decrease in H3K9me3 levels at core promoter regions. The altered genomic regions showed an overrepresentation of cis-binding sites for ETS and cyclic adenosine monophosphate response elements (CREs) for transcription factors of the CREB/CREM/ATF1 family. The decrease in H3K9me3 levels at CREs was associated with increased CRE-driven promoter activity in AML blasts in vivo. AML-specific H3K9me3 patterns were not associated with known cytogenetic abnormalities. But a signature derived from H3K9me3 patterns predicted event-free survival in AML patients. When the H3K9me3 signature was combined with established clinical prognostic markers, it outperformed prognosis prediction based on clinical parameters alone. These findings demonstrate widespread changes of H3K9me3 levels at gene promoters in AML. Signatures of histone modification patterns are associated with patient prognosis in AML. PMID:20498303

  18. Sensitivity and specificity of a brief personality screening instrument in predicting future substance use, emotional, and behavioral problems: 18-month predictive validity of the Substance Use Risk Profile Scale.

    PubMed

    Castellanos-Ryan, Natalie; O'Leary-Barrett, Maeve; Sully, Laura; Conrod, Patricia

    2013-01-01

    This study assessed the validity, sensitivity, and specificity of the Substance Use Risk Profile Scale (SURPS), a measure of personality risk factors for substance use and other behavioral problems in adolescence. The concurrent and predictive validity of the SURPS was tested in a sample of 1,162 adolescents (mean age: 13.7 years) using linear and logistic regressions, while its sensitivity and specificity were examined using the receiver operating characteristics curve analyses. Concurrent and predictive validity tests showed that all 4 brief scales-hopelessness (H), anxiety sensitivity (AS), impulsivity (IMP), and sensation seeking (SS)-were related, in theoretically expected ways, to measures of substance use and other behavioral and emotional problems. Results also showed that when using the 4 SURPS subscales to identify adolescents "at risk," one can identify a high number of those who developed problems (high sensitivity scores ranging from 72 to 91%). And, as predicted, because each scale is related to specific substance and mental health problems, good specificity was obtained when using the individual personality subscales (e.g., most adolescents identified at high risk by the IMP scale developed conduct or drug use problems within the next 18 months [a high specificity score of 70 to 80%]). The SURPS is a valuable tool for identifying adolescents at high risk for substance misuse and other emotional and behavioral problems. Implications of findings for the use of this measure in future research and prevention interventions are discussed. Copyright © 2012 by the Research Society on Alcoholism.

  19. [Is stress cardiovascular magnetic resonance really useful to detect ischemia and predict events in patients with different cardiovascular risk profile?

    PubMed

    Esteban-Fernández, Alberto; Coma-Canella, Isabel; Bastarrika, Gorka; Barba-Cosials, Joaquín; Azcárate-Agüero, Pedro M

    The aim of this study was to evaluate the diagnostic and prognostic usefulness of stress cardiovascular magnetic resonance (stress CMR) in patients with different cardiovascular risk profile and to assess if the degree of hypoperfusion is important to guide clinical decisions. We included patients submitted to adenosine stress CMR to rule out myocardial ischemia. We evaluated its diagnostic accuracy with likelihood ratio (LR) and its prognostic value with survival curves and a Cox regression model. 295 patients were studied. The positive LR was 3.40 and the negative one 0.47. The maximal usefulness of the test was found in patients without previous ischemic cardiomyopathy (positive LR 4.85), patients with atypical chest pain (positive LR 8.56), patients with low or intermediate cardiovascular risk (positive LR 3.87) and those with moderate or severe hypoperfusion (positive LR 8.63). Sixty cardiovascular major events were registered. The best survival prognosis was found in patients with a negative result (p=0.001) or mild hypoperfusion (p=0.038). In the multivariate analysis, a moderate or severe hypoperfusion increased cardiovascular event probability (HR=2.2; IC 95% 1.26-3.92), with no differences between a mild positive and a negative result (HR=0.93; IC 95% 0.38-2.28). Stress CMR was specially useful in patients with low or intermediate cardiovascular risk, patients with atypical chest pain, patients without previous ischemic cardiomyopathy and those with moderate or severe hypoperfusion. Hypoperfusion degree was the main issue factor to guide clinical decisions. Copyright © 2016 Instituto Nacional de Cardiología Ignacio Chávez. Publicado por Masson Doyma México S.A. All rights reserved.

  20. The Hierarchy of Proinflammatory Cytokines in Ocular Inflammation.

    PubMed

    Da Cunha, A P; Zhang, Q; Prentiss, M; Wu, X Q; Kainz, V; Xu, Y Y; Vrouvlianis, J; Li, H; Rangaswamy, N; Leehy, B; McGee, T L; Bell, C L; Bigelow, C E; Kansara, V; Medley, Q; Huang, Q; Wu, H Y

    2018-04-01

    The concept of tissue-dependent cytokine hierarchy has been demonstrated in a number of diseases, but it has not been investigated in ophthalmic diseases. Here, we evaluated the functional hierarchy of interleukin-1β (IL-1β), IL-6, IL-17A, and tumor necrosis factor (TNF) in the induction of ocular inflammation. We delivered adeno-associated virus (AAV) vectors expressing IL-1β, IL-6, IL-17A, or TNF intravitreally in naïve C57/BL6 mice and compared and contrasted the inflammatory effects in the eye 5 weeks after AAV-mediated gene transfer. We also used an in vitro human system to test the effect of cytokines on barrier function. We found that IL-1β had the highest ability to initiate ocular inflammation. The continuous overexpression of IL-1β resulted in a significant upregulation of additional proinflammatory mediators in the eye. Using scanning laser ophthalmoscope and optical coherence tomography imaging techniques, we showed that a low dose of AAVIL-1β was sufficient and was as pathogenic as a high dose of TNF in inducing vascular leakage, retinal degeneration, and cellular infiltration. Furthermore, only a marginal increase in IL-1β was enough to cause cellular infiltration, thus confirming the highly pathogenic nature of IL-1β in the eye. Contrary to our expectation, IL-6 or IL-17A had minimal or no effect in the eye. To examine the clinical relevance of our findings, we used an impedance assay to show that IL-1β alone or TNF alone was able to cause primary human retinal endothelial cell barrier dysfunction in vitro. Again, IL-6 alone or IL-17A alone had no effect on barrier function; however, in the presence of IL-1β or TNF, IL-17A but not IL-6 may provide additive proinflammatory effects. Our studies demonstrate the existence of a functional hierarchy of proinflammatory cytokines in the eye, and we show that IL-1β is the most pathogenic when it is continuously expressed in the eye.

  1. Oxidized phospholipids are proinflammatory and proatherogenic in hypercholesterolaemic mice.

    PubMed

    Que, Xuchu; Hung, Ming-Yow; Yeang, Calvin; Gonen, Ayelet; Prohaska, Thomas A; Sun, Xiaoli; Diehl, Cody; Määttä, Antti; Gaddis, Dalia E; Bowden, Karen; Pattison, Jennifer; MacDonald, Jeffrey G; Ylä-Herttuala, Seppo; Mellon, Pamela L; Hedrick, Catherine C; Ley, Klaus; Miller, Yury I; Glass, Christopher K; Peterson, Kirk L; Binder, Christoph J; Tsimikas, Sotirios; Witztum, Joseph L

    2018-06-06

    Oxidized phospholipids (OxPL) are ubiquitous, are formed in many inflammatory tissues, including atherosclerotic lesions, and frequently mediate proinflammatory changes 1 . Because OxPL are mostly the products of non-enzymatic lipid peroxidation, mechanisms to specifically neutralize them are unavailable and their roles in vivo are largely unknown. We previously cloned the IgM natural antibody E06, which binds to the phosphocholine headgroup of OxPL, and blocks the uptake of oxidized low-density lipoprotein (OxLDL) by macrophages and inhibits the proinflammatory properties of OxPL 2-4 . Here, to determine the role of OxPL in vivo in the context of atherogenesis, we generated transgenic mice in the Ldlr -/- background that expressed a single-chain variable fragment of E06 (E06-scFv) using the Apoe promoter. E06-scFv was secreted into the plasma from the liver and macrophages, and achieved sufficient plasma levels to inhibit in vivo macrophage uptake of OxLDL and to prevent OxPL-induced inflammatory signalling. Compared to Ldlr -/- mice, Ldlr -/- E06-scFv mice had 57-28% less atherosclerosis after 4, 7 and even 12 months of 1% high-cholesterol diet. Echocardiographic and histologic evaluation of the aortic valves demonstrated that E06-scFv ameliorated the development of aortic valve gradients and decreased aortic valve calcification. Both cholesterol accumulation and in vivo uptake of OxLDL were decreased in peritoneal macrophages, and both peritoneal and aortic macrophages had a decreased inflammatory phenotype. Serum amyloid A was decreased by 32%, indicating decreased systemic inflammation, and hepatic steatosis and inflammation were also decreased. Finally, the E06-scFv prolonged life as measured over 15 months. Because the E06-scFv lacks the functional effects of an intact antibody other than the ability to bind OxPL and inhibit OxLDL uptake in macrophages, these data support a major proatherogenic role of OxLDL and demonstrate that OxPL are proinflammatory and

  2. TP53, STK11 and EGFR Mutations Predict Tumor Immune Profile and the Response to anti-PD-1 in Lung Adenocarcinoma.

    PubMed

    Biton, Jerome; Mansuet-Lupo, Audrey; Pécuchet, Nicolas; Alifano, Marco; Ouakrim, Hanane; Arrondeau, Jennifer; Boudou-Rouquette, Pascaline; Goldwasser, Francois; Leroy, Karen; Goc, Jeremy; Wislez, Marie; Germain, Claire; Laurent-Puig, Pierre; Dieu-Nosjean, Marie-Caroline; Cremer, Isabelle; Herbst, Ronald; Blons, Hélène F; Damotte, Diane

    2018-05-15

    By unlocking anti-tumor immunity, antibodies targeting programmed cell death 1 (PD-1) exhibit impressive clinical results in non-small cell lung cancer, underlining the strong interactions between tumor and immune cells. However, factors that can robustly predict long-lasting responses are still needed. We performed in depth immune profiling of lung adenocarcinoma using an integrative analysis based on immunohistochemistry, flow-cytometry and transcriptomic data. Tumor mutational status was investigated using next-generation sequencing. The response to PD-1 blockers was analyzed from a prospective cohort according to tumor mutational profiles and to PD-L1 expression, and a public clinical database was used to validate the results obtained. We showed that distinct combinations of STK11 , EGFR and TP53 mutations, were major determinants of the tumor immune profile (TIP) and of the expression of PD-L1 by malignant cells. Indeed, the presence of TP53 mutations without co-occurring STK11 or EGFR alterations ( TP53 -mut/ STK11 - EGFR -WT), independently of KRAS mutations, identified the group of tumors with the highest CD8 T cell density and PD-L1 expression. In this tumor subtype, pathways related to T cell chemotaxis, immune cell cytotoxicity, and antigen processing were up-regulated. Finally, a prolonged progression-free survival (PFS: HR=0.32; 95% CI, 0.16-0.63, p <0.001) was observed in anti-PD-1 treated patients harboring TP53 -mut/ STK11 - EGFR -WT tumors. This clinical benefit was even more remarkable in patients with associated strong PD-L1 expression. Our study reveals that different combinations of TP53 , EGFR and STK11 mutations , together with PD-L1 expression by tumor cells, represent robust parameters to identify best responders to PD-1 blockade. Copyright ©2018, American Association for Cancer Research.

  3. Prediction of the binding mode and resistance profile for a dual-target pyrrolyl diketo acid scaffold against HIV-1 integrase and reverse-transcriptase-associated ribonuclease H.

    PubMed

    Yang, Fengyuan; Zheng, Guoxun; Fu, Tingting; Li, Xiaofeng; Tu, Gao; Li, Ying Hong; Yao, Xiaojun; Xue, Weiwei; Zhu, Feng

    2018-06-27

    The rapid emergence of drug-resistant variants is one of the most common causes of highly active antiretroviral therapeutic (HAART) failure in patients infected with HIV-1. Compared with the existing HAART, the recently developed pyrrolyl diketo acid scaffold targeting both HIV-1 integrase (IN) and reverse transcriptase-associated ribonuclease H (RNase H) is an efficient approach to counteract the failure of anti-HIV treatment due to drug resistance. However, the binding mode and potential resistance profile of these inhibitors with important mechanistic principles remain poorly understood. To address this issue, an integrated computational method was employed to investigate the binding mode of inhibitor JMC6F with HIV-1 IN and RNase H. By using per-residue binding free energy decomposition analysis, the following residues: Asp64, Thr66, Leu68, Asp116, Tyr143, Gln148 and Glu152 in IN, Asp443, Glu478, Trp536, Lys541 and Asp549 in RNase H were identified as key residues for JMC6F binding. And then computational alanine scanning was carried to further verify the key residues. Moreover, the resistance profile of the currently known major mutations in HIV-1 IN and 2 mutations in RNase H against JMC6F was predicted by in silico mutagenesis studies. The results demonstrated that only three mutations in HIV-1 IN (Y143C, Q148R and N155H) and two mutations in HIV-1 RNase H (Y501R and Y501W) resulted in a reduction of JMC6F potency, thus indicating their potential role in providing resistance to JMC6F. These data provided important insights into the binding mode and resistance profile of the inhibitors with a pyrrolyl diketo acid scaffold in HIV-1 IN and RNase H, which would be helpful for the development of more effective dual HIV-1 IN and RNase H inhibitors.

  4. Simultaneous virtual prediction of anti-Escherichia coli activities and ADMET profiles: A chemoinformatic complementary approach for high-throughput screening.

    PubMed

    Speck-Planche, Alejandro; Cordeiro, M N D S

    2014-02-10

    Escherichia coli remains one of the principal pathogens that cause nosocomial infections, medical conditions that are increasingly common in healthcare facilities. E. coli is intrinsically resistant to many antibiotics, and multidrug-resistant strains have emerged recently. Chemoinformatics has been a great ally of experimental methodologies such as high-throughput screening, playing an important role in the discovery of effective antibacterial agents. However, there is no approach that can design safer anti-E. coli agents, because of the multifactorial nature and complexity of bacterial diseases and the lack of desirable ADMET (absorption, distribution, metabolism, elimination, and toxicity) profiles as a major cause of disapproval of drugs. In this work, we introduce the first multitasking model based on quantitative-structure biological effect relationships (mtk-QSBER) for simultaneous virtual prediction of anti-E. coli activities and ADMET properties of drugs and/or chemicals under many experimental conditions. The mtk-QSBER model was developed from a large and heterogeneous data set of more than 37800 cases, exhibiting overall accuracies of >95% in both training and prediction (validation) sets. The utility of our mtk-QSBER model was demonstrated by performing virtual prediction of properties for the investigational drug avarofloxacin (AVX) under 260 different experimental conditions. Results converged with the experimental evidence, confirming the remarkable anti-E. coli activities and safety of AVX. Predictions also showed that our mtk-QSBER model can be a promising computational tool for virtual screening of desirable anti-E. coli agents, and this chemoinformatic approach could be extended to the search for safer drugs with defined pharmacological activities.

  5. Moving Toward Integrating Gene Expression Profiling Into High-Throughput Testing: A Gene Expression Biomarker Accurately Predicts Estrogen Receptor α Modulation in a Microarray Compendium

    PubMed Central

    Ryan, Natalia; Chorley, Brian; Tice, Raymond R.; Judson, Richard; Corton, J. Christopher

    2016-01-01

    Microarray profiling of chemical-induced effects is being increasingly used in medium- and high-throughput formats. Computational methods are described here to identify molecular targets from whole-genome microarray data using as an example the estrogen receptor α (ERα), often modulated by potential endocrine disrupting chemicals. ERα biomarker genes were identified by their consistent expression after exposure to 7 structurally diverse ERα agonists and 3 ERα antagonists in ERα-positive MCF-7 cells. Most of the biomarker genes were shown to be directly regulated by ERα as determined by ESR1 gene knockdown using siRNA as well as through chromatin immunoprecipitation coupled with DNA sequencing analysis of ERα-DNA interactions. The biomarker was evaluated as a predictive tool using the fold-change rank-based Running Fisher algorithm by comparison to annotated gene expression datasets from experiments using MCF-7 cells, including those evaluating the transcriptional effects of hormones and chemicals. Using 141 comparisons from chemical- and hormone-treated cells, the biomarker gave a balanced accuracy for prediction of ERα activation or suppression of 94% and 93%, respectively. The biomarker was able to correctly classify 18 out of 21 (86%) ER reference chemicals including “very weak” agonists. Importantly, the biomarker predictions accurately replicated predictions based on 18 in vitro high-throughput screening assays that queried different steps in ERα signaling. For 114 chemicals, the balanced accuracies were 95% and 98% for activation or suppression, respectively. These results demonstrate that the ERα gene expression biomarker can accurately identify ERα modulators in large collections of microarray data derived from MCF-7 cells. PMID:26865669

  6. Moving Toward Integrating Gene Expression Profiling Into High-Throughput Testing: A Gene Expression Biomarker Accurately Predicts Estrogen Receptor α Modulation in a Microarray Compendium.

    PubMed

    Ryan, Natalia; Chorley, Brian; Tice, Raymond R; Judson, Richard; Corton, J Christopher

    2016-05-01

    Microarray profiling of chemical-induced effects is being increasingly used in medium- and high-throughput formats. Computational methods are described here to identify molecular targets from whole-genome microarray data using as an example the estrogen receptor α (ERα), often modulated by potential endocrine disrupting chemicals. ERα biomarker genes were identified by their consistent expression after exposure to 7 structurally diverse ERα agonists and 3 ERα antagonists in ERα-positive MCF-7 cells. Most of the biomarker genes were shown to be directly regulated by ERα as determined by ESR1 gene knockdown using siRNA as well as through chromatin immunoprecipitation coupled with DNA sequencing analysis of ERα-DNA interactions. The biomarker was evaluated as a predictive tool using the fold-change rank-based Running Fisher algorithm by comparison to annotated gene expression datasets from experiments using MCF-7 cells, including those evaluating the transcriptional effects of hormones and chemicals. Using 141 comparisons from chemical- and hormone-treated cells, the biomarker gave a balanced accuracy for prediction of ERα activation or suppression of 94% and 93%, respectively. The biomarker was able to correctly classify 18 out of 21 (86%) ER reference chemicals including "very weak" agonists. Importantly, the biomarker predictions accurately replicated predictions based on 18 in vitro high-throughput screening assays that queried different steps in ERα signaling. For 114 chemicals, the balanced accuracies were 95% and 98% for activation or suppression, respectively. These results demonstrate that the ERα gene expression biomarker can accurately identify ERα modulators in large collections of microarray data derived from MCF-7 cells. Published by Oxford University Press on behalf of the Society of Toxicology 2016. This work is written by US Government employees and is in the public domain in the US.

  7. A one-dimensional Fickian model to predict the Ga depth profiles in three-stage Cu(In,Ga)Se{sub 2}

    SciTech Connect

    Rodriguez-Alvarez, H., E-mail: humberto.rodriguez@helmholtz-berlin.de; Helmholtz-Zentrum Berlin, Hahn-Meitner Platz 1, 14109 Berlin; Mainz, R.

    2014-05-28

    We present a one-dimensional Fickian model that predicts the formation of a double Ga gradient during the fabrication of Cu(In,Ga)Se{sub 2} thin films by three-stage thermal co-evaporation. The model is based on chemical reaction equations, structural data, and effective Ga diffusivities. In the model, the Cu(In,Ga)Se{sub 2} surface is depleted from Ga during the deposition of Cu-Se in the second deposition stage, leading to an accumulation of Ga near the back contact. During the third deposition stage, where In-Ga-Se is deposited at the surface, the atomic fluxes within the growing layer are inverted. This results in the formation of amore » double Ga gradient within the Cu(In,Ga)Se{sub 2} layer and reproduces experimentally observed Ga distributions. The final shape of the Ga depth profile strongly depends on the temperatures, times and deposition rates used. The model is used to evaluate possible paths to flatten the marked Ga depth profile that is obtained when depositing at low substrate temperatures. We conclude that inserting Ga during the second deposition stage is an effective way to achieve this.« less

  8. Inflamm-aging does not simply reflect increases in pro-inflammatory markers.

    PubMed

    Morrisette-Thomas, Vincent; Cohen, Alan A; Fülöp, Tamàs; Riesco, Éléonor; Legault, Véronique; Li, Qing; Milot, Emmanuel; Dusseault-Bélanger, Françis; Ferrucci, Luigi

    2014-07-01

    Many biodemographic studies use biomarkers of inflammation to understand or predict chronic disease and aging. Inflamm-aging, i.e. chronic low-grade inflammation during aging, is commonly characterized by pro-inflammatory biomarkers. However, most studies use just one marker at a time, sometimes leading to conflicting results due to complex interactions among the markers. A multidimensional approach allows a more robust interpretation of the various relationships between the markers. We applied principal component analysis (PCA) to 19 inflammatory biomarkers from the InCHIANTI study. We identified a clear, stable structure among the markers, with the first axis explaining inflammatory activation (both pro- and anti-inflammatory markers loaded strongly and positively) and the second axis innate immune response. The first but not the second axis was strongly correlated with age (r=0.56, p<0.0001, r=0.08 p=0.053), and both were strongly predictive of mortality (hazard ratios per PCA unit (95% CI): 1.33 (1.16-1.53) and 0.87 (0.76-0.98) respectively) and multiple chronic diseases, but in opposite directions. Both axes were more predictive than any individual markers for baseline chronic diseases and mortality. These results show that PCA can uncover a novel biological structure in the relationships among inflammatory markers, and that key axes of this structure play important roles in chronic disease. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  9. [Interleukins network in rheumatoid arthritis pathophysiology: beyond proinflammatory cytokines].

    PubMed

    Sánchez-Ramón, Silvia; López-Longo, Francisco Javier; Carreño, Luis

    2011-03-01

    Rheumatoid arthritis (RA) is a systemic autoimmune disease characterized by synovitis and progressive destruction of the joint cartilage and underlying bone, together with diverse extra-articular manifestations. Cytokines act as soluble effector mediators of the inflammatory process. Therapeutic neutralization with monoclonal antibodies against the pro-inflammatory cytokines TNF-alpha and interleukin 1 (IL-1) has shown a clear efficacy on inflammation and clinical manifestations of RA, although a percentage of patients do not respond. This review covers new relevant cytokines in the RA physiopathology and potential biomarkers of inflammation. The current challenge is to develop biomarkers that enable an earlier diagnosis, as well as prognostic markers and new therapeutic candidates. Combined administration of several of these cytokines could eventually address a personalized treatment approach for each patient. Copyright © 2010 Elsevier España, S.L. All rights reserved.

  10. Proinflammatory effects of cookstove emissions on human bronchial epithelial cells.

    PubMed

    Hawley, B; Volckens, J

    2013-02-01

    Approximately half of the world's population uses biomass fuel for indoor cooking and heating. This form of combustion typically occurs in open fires or primitive stoves. Human exposure to emissions from indoor biomass combustion is a global health concern, causing an estimated 1.5 million premature deaths each year. Many 'improved' stoves have been developed to address this concern; however, studies that examine exposure-response with cleaner-burning, more efficient stoves are few. The objective of this research was to evaluate the effects of traditional and cleaner-burning stove emissions on an established model of the bronchial epithelium. We exposed well-differentiated, normal human bronchial epithelial cells to emissions from a single biomass combustion event using either a traditional three-stone fire or one of two energy-efficient stoves. Air-liquid interface cultures were exposed using a novel, aerosol-to-cell deposition system. Cellular expression of a panel of three pro-inflammatory markers was evaluated at 1 and 24 h following exposure. Cells exposed to emissions from the cleaner-burning stoves generated significantly fewer amounts of pro-inflammatory markers than cells exposed to emissions from a traditional three-stone fire. Particulate matter emissions from each cookstove were substantially different, with the three-stone fire producing the largest concentrations of particles (by both number and mass). This study supports emerging evidence that more efficient cookstoves have the potential to reduce respiratory inflammation in settings where solid fuel combustion is used to meet basic domestic needs. Emissions from more efficient, cleaner-burning cookstoves produced less inflammation in well-differentiated bronchial lung cells. The results support evidence that more efficient cookstoves can reduce the health burden associated with exposure to indoor pollution from the combustion of biomass. © 2012 John Wiley & Sons A/S.

  11. Proinflammatory and anti-inflammatory cytokine changes related to menopause

    PubMed Central

    Malutan, Andrei Mihai; Nicolae, Costin; Carmen, Mihu

    2014-01-01

    The aim of the study The aim of the study was to determine menopause-related changes in serum levels of main proinflammatory and anti-inflammatory cytokines. Material and methods The study included 175 women, who were divided into 5 study groups (group 1 – fertile women; group 2 – pre- and perimenopausal women; group 3 – postmenopausal women; group 4 – surgically induced menopausal women; group 5 – women with chronic inflammatory pathology). We evaluated the serum levels of interleukin (IL)-1α, IL-1β, IL-2, IL-4, IL-5, IL-6, IL-8, IL-10, IL-17, IL-20 and of the tumour necrosis factor (TNF)α with the use of two multiplex cytokine kits. We also determined the serum levels of follicle stimulating hormone (FSH), luteinizing hormone (LH), 17β-estradiol (17β-E2), progesterone (P), dehydroepiandrosterone (DHEA) and dehydroepiandrosterone sulfate (DHEAS) using sandwich ELISA. Results The serum level of IL-1β, IL-8 and TNF-α in women with natural menopause and in women with surgically induced menopause is significantly higher than in fertile women in the control group. In patients with surgically induced menopause and in women with natural menopause, IL-8 serum levels are similar to those seen in patients with chronic inflammatory diseases. There is a statistically significant decrease in serum levels of IL-20 in women with natural or surgical menopause than in fertile and premenopausal women. Conclusions Women in menopause have elevated levels of the key proinflammatory cytokines, i.e. IL-1β, IL-8 and TNF-α and low serum levels of IL-20 in comparison with fertile women. PMID:26327849

  12. Metabolic profiling and predicting the free radical scavenging activity of guava (Psidium guajava L.) leaves according to harvest time by 1H-nuclear magnetic resonance spectroscopy.

    PubMed

    Kim, So-Hyun; Cho, Somi K; Hyun, Sun-Hee; Park, Hae-Eun; Kim, Young-Suk; Choi, Hyung-Kyoon

    2011-01-01

    Guava leaves were classified and the free radical scavenging activity (FRSA) evaluated according to different harvest times by using the (1)H-NMR-based metabolomic technique. A principal component analysis (PCA) of (1)H-NMR data from the guava leaves provided clear clusters according to the harvesting time. A partial least squares (PLS) analysis indicated a correlation between the metabolic profile and FRSA. FRSA levels of the guava leaves harvested during May and August were high, and those leaves contained higher amounts of 3-hydroxybutyric acid, acetic acid, glutamic acid, asparagine, citric acid, malonic acid, trans-aconitic acid, ascorbic acid, maleic acid, cis-aconitic acid, epicatechin, protocatechuic acid, and xanthine than the leaves harvested during October and December. Epicatechin and protocatechuic acid among those compounds seem to have enhanced FRSA of the guava leaf samples harvested in May and August. A PLS regression model was established to predict guava leaf FRSA at different harvesting times by using a (1)H-NMR data set. The predictability of the PLS model was then tested by internal and external validation. The results of this study indicate that (1)H-NMR-based metabolomic data could usefully characterize guava leaves according to their time of harvesting.

  13. Genome-wide Expression Profiling, In Vivo DNA Binding Analysis, and Probabilistic Motif Prediction Reveal Novel Abf1 Target Genes during Fermentation, Respiration, and Sporulation in Yeast

    PubMed Central

    Schlecht, Ulrich; Erb, Ionas; Demougin, Philippe; Robine, Nicolas; Borde, Valérie; van Nimwegen, Erik; Nicolas, Alain

    2008-01-01

    The autonomously replicating sequence binding factor 1 (Abf1) was initially identified as an essential DNA replication factor and later shown to be a component of the regulatory network controlling mitotic and meiotic cell cycle progression in budding yeast. The protein is thought to exert its functions via specific interaction with its target site as part of distinct protein complexes, but its roles during mitotic growth and meiotic development are only partially understood. Here, we report a comprehensive approach aiming at the identification of direct Abf1-target genes expressed during fermentation, respiration, and sporulation. Computational prediction of the protein's target sites was integrated with a genome-wide DNA binding assay in growing and sporulating cells. The resulting data were combined with the output of expression profiling studies using wild-type versus temperature-sensitive alleles. This work identified 434 protein-coding loci as being transcriptionally dependent on Abf1. More than 60% of their putative promoter regions contained a computationally predicted Abf1 binding site and/or were bound by Abf1 in vivo, identifying them as direct targets. The present study revealed numerous loci previously unknown to be under Abf1 control, and it yielded evidence for the protein's variable DNA binding pattern during mitotic growth and meiotic development. PMID:18305101

  14. A Metagenomic and in Silico Functional Prediction of Gut Microbiota Profiles May Concur in Discovering New Cystic Fibrosis Patient-Targeted Probiotics.

    PubMed

    Vernocchi, Pamela; Del Chierico, Federica; Quagliariello, Andrea; Ercolini, Danilo; Lucidi, Vincenzina; Putignani, Lorenza

    2017-12-09

    Cystic fibrosis (CF) is a life-limiting hereditary disorder that results in aberrant mucosa in the lungs and digestive tract, chronic respiratory infections, chronic inflammation, and the need for repeated antibiotic treatments. Probiotics have been demonstrated to improve the quality of life of CF patients. We investigated the distribution of gut microbiota (GM) bacteria to identify new potential probiotics for CF patients on the basis of GM patterns. Fecal samples of 28 CF patients and 31 healthy controls (HC) were collected and analyzed by 16S rRNA-based pyrosequencing analysis of GM, to produce CF-HC paired maps of the distribution of operational taxonomic units (OTUs), and by Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) for Kyoto Encyclopedia of Genes and Genomes (KEGG) biomarker prediction. The maps were scanned to highlight the distribution of bacteria commonly claimed as probiotics, such as bifidobacteria and lactobacilli, and of butyrate-producing colon bacteria, such as Eubacterium spp. and Faecalibacterium prausnitzii. The analyses highlighted 24 OTUs eligible as putative probiotics. Eleven and nine species were prevalently associated with the GM of CF and HC subjects, respectively. Their KEGG prediction provided differential CF and HC pathways, indeed associated with health-promoting biochemical activities in the latter case. GM profiling and KEGG biomarkers concurred in the evaluation of nine bacterial species as novel putative probiotics that could be investigated for the nutritional management of CF patients.

  15. Adding anthropometric measures of regional adiposity to BMI improves prediction of cardiometabolic, inflammatory and adipokines profiles in youths: a cross-sectional study.

    PubMed

    Samouda, Hanen; de Beaufort, Carine; Stranges, Saverio; Guinhouya, Benjamin C; Gilson, Georges; Hirsch, Marco; Jacobs, Julien; Leite, Sonia; Vaillant, Michel; Dadoun, Frédéric

    2015-10-24

    Paediatric research analysing the relationship between the easy-to-use anthropometric measures for adiposity and cardiometabolic risk factors remains highly controversial in youth. Several studies suggest that only body mass index (BMI), a measure of relative weight, constitutes an accurate predictor, whereas others highlight the potential role of waist-to-hip ratio (WHR), waist circumference (Waist C), and waist-to-height ratio (WHtR). In this study, we examined the effectiveness of adding anthropometric measures of body fat distribution (Waist C Z Score, WHR Z Score and/or WHtR) to BMI Z Score to predict cardiometabolic risk factors in overweight and obese youth. We also examined the consistency of these associations with the "total fat mass + trunk/legs fat mass" and/or the "total fat mass + trunk fat mass" combinations, as assessed by dual energy X-ray absorptiometry (DXA), the gold standard measurement of body composition. Anthropometric and DXA measurements of total and regional adiposity, as well as a comprehensive assessment of cardiometabolic, inflammatory and adipokines profiles were performed in 203 overweight and obese 7-17 year-old youths from the Paediatrics Clinic, Centre Hospitalier de Luxembourg. Adding only one anthropometric surrogate of regional fat to BMI Z Score improved the prediction of insulin resistance (WHR Z Score, R(2): 45.9%. Waist C Z Score, R(2): 45.5%), HDL-cholesterol (WHR Z Score, R(2): 9.6%. Waist C Z Score, R(2): 10.8%. WHtR, R(2): 6.5%), triglycerides (WHR Z Score, R(2): 11.7%. Waist C Z Score, R(2): 12.2%), adiponectin (WHR Z Score, R(2): 14.3%. Waist C Z Score, R(2): 17.7%), CRP (WHR Z Score, R(2): 18.2%. WHtR, R(2): 23.3%), systolic (WHtR, R(2): 22.4%), diastolic blood pressure (WHtR, R(2): 20%) and fibrinogen (WHtR, R(2): 21.8%). Moreover, WHR Z Score, Waist C Z Score and/or WHtR showed an independent significant contribution according to these models. These results were in line with the DXA findings. Adding

  16. Accurate prediction of retention in hydrophilic interaction chromatography by back calculation of high pressure liquid chromatography gradient profiles.

    PubMed

    Wang, Nu; Boswell, Paul G

    2017-10-20

    Gradient retention times are difficult to project from the underlying retention factor (k) vs. solvent composition (φ) relationships. A major reason for this difficulty is that gradients produced by HPLC pumps are imperfect - gradient delay, gradient dispersion, and solvent mis-proportioning are all difficult to account for in calculations. However, we recently showed that a gradient "back-calculation" methodology can measure these imperfections and take them into account. In RPLC, when the back-calculation methodology was used, error in projected gradient retention times is as low as could be expected based on repeatability in the k vs. φ relationships. HILIC, however, presents a new challenge: the selectivity of HILIC columns drift strongly over time. Retention is repeatable in short time, but selectivity frequently drifts over the course of weeks. In this study, we set out to understand if the issue of selectivity drift can be avoid by doing our experiments quickly, and if there any other factors that make it difficult to predict gradient retention times from isocratic k vs. φ relationships when gradient imperfections are taken into account with the back-calculation methodology. While in past reports, the accuracy of retention projections was >5%, the back-calculation methodology brought our error down to ∼1%. This result was 6-43 times more accurate than projections made using ideal gradients and 3-5 times more accurate than the same retention projections made using offset gradients (i.e., gradients that only took gradient delay into account). Still, the error remained higher in our HILIC projections than in RPLC. Based on the shape of the back-calculated gradients, we suspect the higher error is a result of prominent gradient distortion caused by strong, preferential water uptake from the mobile phase into the stationary phase during the gradient - a factor our model did not properly take into account. It appears that, at least with the stationary phase

  17. Improvement of a predictive model in ovarian cancer patients submitted to platinum-based chemotherapy: implications of a GST activity profile.

    PubMed

    Pereira, Deolinda; Assis, Joana; Gomes, Mónica; Nogueira, Augusto; Medeiros, Rui

    2016-05-01

    The success of chemotherapy in ovarian cancer (OC) is directly associated with the broad variability in platinum response, with implications in patients survival. This heterogeneous response might result from inter-individual variations in the platinum-detoxification pathway due to the expression of glutathione-S-transferase (GST) enzymes. We hypothesized that GSTM1 and GSTT1 polymorphisms might have an impact as prognostic and predictive determinants for OC. We conducted a hospital-based study in a cohort of OC patients submitted to platinum-based chemotherapy. GSTM1 and GSTT1 genotypes were determined by multiplex PCR. GSTM1-null genotype patients presented a significantly longer 5-year survival and an improved time to progression when compared with GSTM1-wt genotype patients (log-rank test, P = 0.001 and P = 0.013, respectively). Multivariate Cox regression analysis indicates that the inclusion of genetic information regarding GSTM1 polymorphism increased the predictive ability of risk of death after OC platinum-based chemotherapy (c-index from 0.712 to 0.833). Namely, residual disease (HR, 4.90; P = 0.016) and GSTM1-wt genotype emerged as more important predictors of risk of death (HR, 2.29; P = 0.039; P = 0.036 after bootstrap). No similar effect on survival was observed regarding GSTT1 polymorphism, and there were no statistically significant differences between GSTM1 and GSTT1 genotypes and the assessed patients' clinical-pathological characteristics. GSTM1 polymorphism seems to have an impact in OC prognosis as it predicts a better response to platinum-based chemotherapy and hence an improved survival. The characterization of the GSTM1 genetic profile might be a useful molecular tool and a putative genetic marker for OC clinical outcome.

  18. All Our Babies Cohort Study: recruitment of a cohort to predict women at risk of preterm birth through the examination of gene expression profiles and the environment

    PubMed Central

    2010-01-01

    Background Preterm birth is the leading cause of perinatal morbidity and mortality. Risk factors for preterm birth include a personal or familial history of preterm delivery, ethnicity and low socioeconomic status yet the ability to predict preterm delivery before the onset of preterm labour evades clinical practice. Evidence suggests that genetics may play a role in the multi-factorial pathophysiology of preterm birth. The All Our Babies Study is an on-going community based longitudinal cohort study that was designed to establish a cohort of women to investigate how a women's genetics and environment contribute to the pathophysiology of preterm birth. Specifically this study will examine the predictive potential of maternal leukocytes for predicting preterm birth in non-labouring women through the examination of gene expression profiles and gene-environment interactions. Methods/Design Collaborations have been established between clinical lab services, the provincial health service provider and researchers to create an interdisciplinary study design for the All Our Babies Study. A birth cohort of 2000 women has been established to address this research question. Women provide informed consent for blood sample collection, linkage to medical records and complete questionnaires related to prenatal health, service utilization, social support, emotional and physical health, demographics, and breast and infant feeding. Maternal blood samples are collected in PAXgene™ RNA tubes between 18-22 and 28-32 weeks gestation for transcriptomic analyses. Discussion The All Our Babies Study is an example of how investment in clinical-academic-community partnerships can improve research efficiency and accelerate the recruitment and data collection phases of a study. Establishing these partnerships during the study design phase and maintaining these relationships through the duration of the study provides the unique opportunity to investigate the multi-causal factors of preterm

  19. An assessment of predictive value of the biophysical profile in women with preeclampsia using data from the fullPIERS database.

    PubMed

    Payne, Beth A; Kyle, Phillipa M; Lim, Kenneth; Lisonkova, Sarka; Magee, Laura A; Pullar, Barbra; Qu, Ziguang; von Dadelszen, Peter

    2013-07-01

    Pre-eclampsia is associated with increased risk to both the mother and fetus. Effective monitoring of the fetal condition is essential to the management of women with pre-eclampsia. The biophysical profile (BPP) is one monitoring tool available to clinicians. To compare the BPP test with cardiotocography/non-stress test (CTG/NST) alone for their ability to predict fetal acidemia at birth or a composite adverse perinatal outcome among women with preeclampsia and to estimate the effect of BPP assessment on mode of delivery and birth outcome. Secondary analysis of a prospective cohort of women with preeclampsia. The predictive ability of the tests was assessed based on sensitivity, specificity, positive and negative likelihood ratios (LR+, LR-). Women assessed with the BPP were compared with matched controls not assessed with the BPP to determine the odds of Cesarean delivery or adverse perinatal outcomes after adjustment for potential confounders. Five out of 89 women (5.6%) had an abnormal BPP; 18 out of 89 (20.2%) had an abnormal CTG/NST. Fetal acidemia was diagnosed in 13 fetuses (14.6%); composite adverse perinatal outcome in 68 fetuses/infants (76.4%). Both tests had relatively poor predictive performance for both outcomes (LR+ between 2.50 and 3.90 and LR- between 0.64 and 0.93). Assessment with the BPP was positively associated with fetal acidemia (adjusted OR 4.84; 95% CI 1.33-17.66). The BPP and CTG/NST alone were poor predictors of perinatal outcome in this cohort; multiple tests should be considered when assessing fetal risk in women with preeclampsia. Crown Copyright © 2013. Published by Elsevier B.V. All rights reserved.

  20. Formal Modelling of Toll like Receptor 4 and JAK/STAT Signalling Pathways: Insight into the Roles of SOCS-1, Interferon-β and Proinflammatory Cytokines in Sepsis

    PubMed Central

    Paracha, Rehan Zafar; Ahmad, Jamil; Ali, Amjad; Hussain, Riaz; Niazi, Umar; Tareen, Samar Hayat Khan; Aslam, Babar

    2014-01-01

    Sepsis is one of the major causes of human morbidity and results in a considerable number of deaths each year. Lipopolysaccharide-induced sepsis has been associated with TLR4 signalling pathway which in collaboration with the JAK/STAT signalling regulate endotoxemia and inflammation. However, during sepsis our immune system cannot maintain a balance of cytokine levels and results in multiple organ damage and eventual death. Different opinions have been made in previous studies about the expression patterns and the role of proinflammatory cytokines in sepsis that attracted our attention towards qualitative properties of TLR4 and JAK/STAT signalling pathways using computer-aided studies. René Thomas’ formalism was used to model septic and non-septic dynamics of TLR4 and JAK/STAT signalling. Comparisons among dynamics were made by intervening or removing the specific interactions among entities. Among our predictions, recurrent induction of proinflammatory cytokines with subsequent downregulation was found as the basic characteristic of septic model. This characteristic was found in agreement with previous experimental studies, which implicate that inflammation is followed by immunomodulation in septic patients. Moreover, intervention in downregulation of proinflammatory cytokines by SOCS-1 was found desirable to boost the immune responses. On the other hand, interventions either in TLR4 or transcriptional elements such as NFκB and STAT were found effective in the downregulation of immune responses. Whereas, IFN-β and SOCS-1 mediated downregulation at different levels of signalling were found to be associated with variations in the levels of proinflammatory cytokines. However, these predictions need to be further validated using wet laboratory experimental studies to further explore the roles of inhibitors such as SOCS-1 and IFN-β, which may alter the levels of proinflammatory cytokines at different stages of sepsis. PMID:25255432

  1. Better cognitive control of emotional information is associated with reduced pro-inflammatory cytokine reactivity to emotional stress.

    PubMed

    Shields, Grant S; Kuchenbecker, Shari Young; Pressman, Sarah D; Sumida, Ken D; Slavich, George M

    2016-01-01

    Stress is strongly associated with several mental and physical health problems that involve inflammation, including asthma, cardiovascular disease, certain types of cancer, and depression. It has been hypothesized that better cognitive control of emotional information may lead to reduced inflammatory reactivity to stress and thus better health, but to date no studies have examined whether differences in cognitive control predict pro-inflammatory cytokine responses to stress. To address this issue, we conducted a laboratory-based experimental study in which we randomly assigned healthy young-adult females to either an acute emotional stress (emotionally evocative video) or no-stress (control video) condition. Salivary levels of the key pro-inflammatory cytokines IL-1β, IL-6, and IL-8 were measured before and after the experimental manipulation, and following the last cytokine sample, we assessed participants' cognitive control of emotional information using an emotional Stroop task. We also assessed participants' cortisol levels before and after the manipulation to verify that documented effects were specific to cytokines and not simply due to increased nonwater salivary output. As hypothesized, the emotional stressor triggered significant increases in IL-1β, IL-6, and IL-8. Moreover, even in fully adjusted models, better cognitive control following the emotional (but not control) video predicted less pronounced cytokine responses to that stressor. In contrast, no effects were observed for cortisol. These data thus indicate that better cognitive control specifically following an emotional stressor is uniquely associated with less pronounced pro-inflammatory cytokine reactivity to such stress. These findings may therefore help explain why superior cognitive control portends better health over the lifespan.

  2. Suppression of Proinflammatory and Prosurvival Biomarkers in Oral Cancer Patients Consuming a Black Raspberry Phytochemical-Rich Troche.

    PubMed

    Knobloch, Thomas J; Uhrig, Lana K; Pearl, Dennis K; Casto, Bruce C; Warner, Blake M; Clinton, Steven K; Sardo-Molmenti, Christine L; Ferguson, Jeanette M; Daly, Brett T; Riedl, Kenneth; Schwartz, Steven J; Vodovotz, Yael; Buchta, Anthony J; Schuller, David E; Ozer, Enver; Agrawal, Amit; Weghorst, Christopher M

    2016-02-01

    Black raspberries (BRB) demonstrate potent inhibition of aerodigestive tract carcinogenesis in animal models. However, translational clinical trials evaluating the ability of BRB phytochemicals to impact molecular biomarkers in the oral mucosa remain limited. The present phase 0 study addresses a fundamental question for oral cancer food-based prevention: Do BRB phytochemicals successfully reach the targeted oral tissues and reduce proinflammatory and antiapoptotic gene expression profiles? Patients with biopsy-confirmed oral squamous cell carcinomas (OSCC) administered oral troches containing freeze-dried BRB powder from the time of enrollment to the date of curative intent surgery (13.9 ± 1.27 days). Transcriptional biomarkers were evaluated in patient-matched OSCCs and noninvolved high at-risk mucosa (HARM) for BRB-associated changes. Significant expression differences between baseline OSCC and HARM tissues were confirmed using a panel of genes commonly deregulated during oral carcinogenesis. Following BRB troche administration, the expression of prosurvival genes (AURKA, BIRC5, EGFR) and proinflammatory genes (NFKB1, PTGS2) were significantly reduced. There were no BRB-associated grade 3-4 toxicities or adverse events, and 79.2% (N = 30) of patients successfully completed the study with high levels of compliance (97.2%). The BRB phytochemicals cyanidin-3-rutinoside and cyanidin-3-xylosylrutinoside were detected in all OSCC tissues analyzed, demonstrating that bioactive components were successfully reaching targeted OSCC tissues. We confirmed that hallmark antiapoptotic and proinflammatory molecular biomarkers were overexpressed in OSCCs and that their gene expression was significantly reduced following BRB troche administration. As these molecular biomarkers are fundamental to oral carcinogenesis and are modifiable, they may represent emerging biomarkers of molecular efficacy for BRB-mediated oral cancer chemoprevention. ©2015 American Association for Cancer

  3. Monocyte NOTCH2 expression predicts IFN-β immunogenicity in multiple sclerosis patients.

    PubMed

    Adriani, Marsilio; Nytrova, Petra; Mbogning, Cyprien; Hässler, Signe; Medek, Karel; Jensen, Poul Erik H; Creeke, Paul; Warnke, Clemens; Ingenhoven, Kathleen; Hemmer, Bernhard; Sievers, Claudia; Lindberg Gasser, Raija Lp; Fissolo, Nicolas; Deisenhammer, Florian; Bocskei, Zsolt; Mikol, Vincent; Fogdell-Hahn, Anna; Kubala Havrdova, Eva; Broët, Philippe; Dönnes, Pierre; Mauri, Claudia; Jury, Elizabeth C

    2018-06-07

    Multiple sclerosis (MS) is an autoimmune disease characterized by CNS inflammation leading to demyelination and axonal damage. IFN-β is an established treatment for MS; however, up to 30% of IFN-β-treated MS patients develop neutralizing antidrug antibodies (nADA), leading to reduced drug bioactivity and efficacy. Mechanisms driving antidrug immunogenicity remain uncertain, and reliable biomarkers to predict immunogenicity development are lacking. Using high-throughput flow cytometry, NOTCH2 expression on CD14+ monocytes and increased frequency of proinflammatory monocyte subsets were identified as baseline predictors of nADA development in MS patients treated with IFN-β. The association of this monocyte profile with nADA development was validated in 2 independent cross-sectional MS patient cohorts and a prospective cohort followed before and after IFN-β administration. Reduced monocyte NOTCH2 expression in nADA+ MS patients was associated with NOTCH2 activation measured by increased expression of Notch-responsive genes, polarization of monocytes toward a nonclassical phenotype, and increased proinflammatory IL-6 production. NOTCH2 activation was T cell dependent and was only triggered in the presence of serum from nADA+ patients. Thus, nADA development was driven by a proinflammatory environment that triggered activation of the NOTCH2 signaling pathway prior to first IFN-β administration.

  4. Glucocorticoid sensitivity and proinflammatory cytokines pattern in pemphigus.

    PubMed

    Chriguer, Rosangela Soares; Roselino, Ana Maria; de Castro, Margaret

    2012-08-01

    Glucocorticoids (GC) represent the main treatment for pemphigus; however, some patients show GC resistance. GC sensitivity was evaluated in 19 pemphigus patients and 41 controls by the number of binding sites [B(max) (fmol/mg protein)] and the affinity of GC receptor [Kd (nM)] to dexamethasone (DEX) as well as by the pattern of cytokine by DEX-mediated inhibition of concanavalin-A (Con-A)-stimulated PBMC proliferation. The Kd (15.7 ± 2.8 vs.8.1 ± 1.3) and Bmax (6.5 ± 0.9 vs. 3.9 ± 0.3) were higher in pemphigus than controls (p = 0.002). Considering the values above the 95th percentile of normal group as a cut-off (K(d) > 24.9 nM and B(max) > 8.1 fmol/mg protein), elevated K(d) and B(max) were observed in 9.8% and 2.4% of controls and 15.8% and 36.8% of patients (p = 0.02). PBMC proliferation was stimulated by Con-A and inhibited by DEX (p < 0.001) in both pemphigus and control groups. IL-6 and TNFα (pg/mL) basal production were higher in patients than controls. There was an increment of these cytokines after Con-A stimulation, and they were inhibited by DEX (p = 0.002) in controls and remained elevated in pemphigus (p < 0.02). Patients and controls showed no difference in basal and stimulated production of IL-8 and IL-10. There is an alteration on GC sensitivity in pemphigus patients and a higher production of proinflammatory cytokines. Therefore, in pemphigus patients, proinflammatory cytokines might be involved in the mechanism of GC resistance and/or in its maintenance.

  5. Breastmilk from obese mothers has pro-inflammatory properties and decreased neuroprotective factors

    PubMed Central

    Panagos, PG; Vishwanathan, R; Penfield-Cyr, A; Matthan, NR; Shivappa, N; Wirth, MD; Hebert, JR; Sen, S

    2016-01-01

    OBJECTIVE To determine the impact of maternal obesity on breastmilk composition. STUDY DESIGN Breastmilk and food records from 21 lean and 21 obese women who delivered full-term infants were analyzed at 2 months post-partum. Infant growth and adiposity were measured at birth and 2 months of age. RESULT Breastmilk from obese mothers had higher omega-6 to omega-3 fatty acid ratio and lower concentrations of docosahexaenoic acid, eicosapentaenoic acid, docasapentaenoic acid and lutein compared with lean mothers (P < 0.05), which were strongly associated with maternal body mass index. Breastmilk saturated fatty acid and monounsaturated fatty acid concentrations were positively associated with maternal dietary inflammation, as measured by dietary inflammatory index. There were no differences in infant growth measurements. CONCLUSION Breastmilk from obese mothers has a pro-inflammatory fatty acid profile and decreased concentrations of fatty acids and carotenoids that have been shown to have a critical role in early visual and neurodevelopment. Studies are needed to determine the link between these early-life influences and subsequent cardiometabolic and neurodevelopmental outcomes. PMID:26741571

  6. Phagocytosis of Apoptotic Trophoblast Cells by Human Endometrial Endothelial Cells Induces Proinflammatory Cytokine Production

    PubMed Central

    Peng, Bing; Koga, Kaori; Cardenas, Ingrid; Aldo, Paulomi; Mor, Gil

    2011-01-01

    Problem Apoptosis is a normal constituent of trophoblast turnover in the placenta; however in some cases, this process is related to pregnancy complications such as preeclampsia. Recognition and engulfment of these apoptotic trophoblast cells is important for clearance of dying cells. The aim of this study was to show the cross talk between human endometrial endothelial cells (HEECs) and apoptotic trophoblast cells in an in vitro coculture model and its effect on cytokine production by HEECs. Method of study Fluorescent-labeled HEECs were cocultured with fluorescent-labeled apoptotic human trophoblast cells. Confocal microscopy and flowcytometry were used to show the interaction between these two types of cells. Cytokine profiles were determined using multiplex analysis. Results HEECs are capable to phagocytose apoptotic trophoblasts. This activity is inhibited by the phagocytosis inhibitor cytochalasin B. Phagocytosis of apoptotic trophoblast cells induced the secretion of the proinflammatory cytokines interleukin-6 and monocyte chemoattractant protein-1 by HEECs. Conclusion This study provides the first evidence that HEECs have an ability to phagocytose apoptotic trophoblasts. Furthermore, we demonstrated an inflammatory response of HEECs after phagocytosing the apoptotic trophoblast cells. This event may contribute to the inflammatory response in both normal pregnancy and pathologic pregnancy such as preeclampsia. PMID:20219062

  7. Epithelial cell pro-inflammatory cytokine response differs across dental plaque bacterial species.

    PubMed

    Stathopoulou, Panagiota G; Benakanakere, Manjunatha R; Galicia, Johnah C; Kinane, Denis F

    2010-01-01

    The dental plaque is comprised of numerous bacterial species, which may or may not be pathogenic. Human gingival epithelial cells (HGECs) respond to perturbation by various bacteria of the dental plaque by production of different levels of inflammatory cytokines, which is a putative reflection of their virulence. The aim of the current study was to determine responses in terms of interleukin (IL)-1beta, IL-6, IL-8 and IL-10 secretion induced by Porphyromonas gingivalis, Aggregatibacter actinomycetemcomitans, Fusobacterium nucleatum and Streptococcus gordonii in order to gauge their virulence potential. HGECs were challenged with the four bacterial species, live or heat killed, at various multiplicity of infections and the elicited IL-1beta, IL-6, IL-8 and IL-10 responses were assayed by enzyme-linked immunosorbent assay. Primary HGECs challenged with live P. gingivalis produced high levels of IL-1beta, while challenge with live A. actinomycetemcomitans gave high levels of IL-8. The opportunistic pathogen F. nucleatum induces the highest levels of pro-inflammatory cytokines, while the commensal S. gordonii is the least stimulatory. We conclude that various dental plaque biofilm bacteria induce different cytokine response profiles in primary HGECs that may reflect their individual virulence or commensal status.

  8. Anesthesiologists at work: an increase in pro-inflammatory and Th2 cytokine production, and alterations in proliferative immune responses.

    PubMed

    Beilin, B; Greenfeld, K; Abiri, N; Yardeni, I Z; Bessler, H; Ben-Eliyahu, S

    2006-11-01

    Anesthesiologists are a population at high risk of alcohol and drug abuse, depression, suicide, and psychiatric hospitalization. The impact of their working milieu on specific immune indices has scarcely been studied, and it is assumed that immune perturbations may contribute to some of the above risks. This study took advantage of an unplanned, 3-month long strike of anesthesiologists, and explored its relations to specific immune measures. We assessed induced cytokine production and lymphocytes proliferative responses in blood samples taken from 10 anesthesiologists just before the strike and at its end, after a long period of markedly reduced workload. The results indicated that the proliferative responses to phytohemagglutinin (PHA) and concanavalin A (Con A) were significantly lower at the end of the strike. At this time point, we observed a significant decrease in the production of interleukin-6 (IL-6), IL-10 and IL1ra levels, and a significant increase in IL-2 production. A strong trend towards a decline in tumor necrosis factor-alpha (TNF-alpha) levels was evident, while levels of IL-1beta were unchanged. These findings suggest that the working conditions of anesthesiologists are associated with specific immune alterations, including a shift towards a Th2 cytokines' dominance, and an elevated pro-inflammatory cytokine response. A reduced Th1 profile has been related to increased susceptibility to infections, and high pro-inflammatory cytokine levels were recently proposed as etiological factors in cardiovascular diseases and in depression.

  9. Pro-inflammatory effects of the mushroom Agaricus blazei and its consequences on atherosclerosis development.

    PubMed

    Gonçalves, Juliana L; Roma, Eric H; Gomes-Santos, Ana Cristina; Aguilar, Edenil C; Cisalpino, Daniel; Fernandes, Luciana R; Vieira, Angélica T; Oliveira, Dirce R; Cardoso, Valbert N; Teixeira, Mauro M; Alvarez-Leite, Jacqueline I

    2012-12-01

    Extracts of the mushroom Agaricus blazei (A. blazei) have been described as possessing immunomodulatory and potentially cancer-protective activities. However, these effects of A. blazei as a functional food have not been fully investigated in vivo. Using apolipoprotein E-deficient (ApoE(-/-)) mice, an experimental model of atherosclerosis, we evaluated the effects of 6 or 12 weeks of A. blazei supplementation on the activation of immune cells in the spleen and blood and on the development of atherosclerosis. Food intake, weight gain, blood lipid profile, and glycemia were similar between the groups. To evaluate leukocyte homing and activation, mice were injected with (99m)Tc-radiolabeled leukocytes, which showed enhanced leukocyte migration to the spleen and heart of A. blazei-supplemented animals. Analysis of the spleen showed higher levels of activation of neutrophils, NKT cells, and monocytes as well as increased production of TNF-α and IFN-γ. Circulating NKT cells and monocytes were also more activated in the supplemented group. Atherosclerotic lesion areas were larger in the aorta of supplemented mice and exhibited increased numbers of macrophages and neutrophils and a thinner fibrous cap. A. blazei-induced transcriptional upregulation of molecules linked to macrophage activation (CD36, TLR4), neutrophil chemotaxy (CXCL1), leukocyte adhesion (VCAM-1), and plaque vulnerability (MMP9) were seen after 12 weeks of supplementation. This is the first in vivo study showing that the immunostimulatory effect of A. blazei has proatherogenic repercussions. A. blazei enhances local and systemic inflammation, upregulating pro-inflammatory molecules, and enhancing leukocyte homing to atherosclerosis sites without affecting the lipoprotein profile.

  10. The Staphyloccous aureus Eap protein activates expression of proinflammatory cytokines.

    PubMed

    Scriba, Thomas J; Sierro, Sophie; Brown, Eric L; Phillips, Rodney E; Sewell, Andrew K; Massey, Ruth C

    2008-05-01

    The extracellular adhesion protein (Eap) secreted by the major human pathogen Staphylococcus aureus is known to have several effects on human immunity. We have recently added to knowledge of these roles by demonstrating that Eap enhances interactions between major histocompatibility complex molecules and human leukocytes. Several studies have indicated that Eap can induce cytokine production by human peripheral blood mononuclear cells (PBMCs). To date, there has been no rigorous attempt to identify the breadth of cytokines produced by Eap stimulation or to identify the cell subsets that respond. Here, we demonstrate that Eap induces the secretion of the proinflammatory cytokines interleukin 6 (IL-6) and tumor necrosis factor alpha (TNF-alpha) by CD14(+) leukocytes (monocytes and macrophages) within direct ex vivo PBMC populations (note that granulocytes are also CD14(+) but are largely depleted from PBMC preparations). Anti-intercellular adhesion molecule 1 (CD54) antibodies inhibited this induction and implicated a role for this known Eap binding protein in cellular activation. IL-6 and TNF-alpha secretion by murine cells exposed to Eap was also observed. The activation of CD14(+) cells by Eap suggests that it could play a significant role in both septic shock and fever, two of the major pathological features of S. aureus infections.

  11. Targeting sortilin in immune cells reduces proinflammatory cytokines and atherosclerosis

    PubMed Central

    Mortensen, Martin B.; Kjolby, Mads; Gunnersen, Stine; Larsen, Jakob V.; Palmfeldt, Johan; Falk, Erling; Nykjaer, Anders; Bentzon, Jacob F.

    2014-01-01

    Genome-wide association studies have identified a link between genetic variation at the human chromosomal locus 1p13.3 and coronary artery disease. The gene encoding sortilin (SORT1) has been implicated as the causative gene within the locus, as sortilin regulates hepatic lipoprotein metabolism. Here we demonstrated that sortilin also directly affects atherogenesis, independent of its regulatory role in lipoprotein metabolism. In a mouse model of atherosclerosis, deletion of Sort1 did not alter plasma cholesterol levels, but reduced the development of both early and late atherosclerotic lesions. We determined that sortilin is a high-affinity receptor for the proinflammatory cytokines IL-6 and IFN-γ. Moreover, macrophages and Th1 cells (both of which mediate atherosclerotic plaque formation) lacking sortilin had reduced secretion of IL-6 and IFN-γ, but not of other measured cytokines. Transfer of sortilin-deficient BM into irradiated atherosclerotic mice reduced atherosclerosis and systemic markers of inflammation. Together, these data demonstrate that sortilin influences cytokine secretion and that targeting sortilin in immune cells attenuates inflammation and reduces atherosclerosis. PMID:25401472

  12. Prediction of protein S-nitrosylation sites based on adapted normal distribution bi-profile Bayes and Chou's pseudo amino acid composition.

    PubMed

    Jia, Cangzhi; Lin, Xin; Wang, Zhiping

    2014-06-10

    Protein S-nitrosylation is a reversible post-translational modification by covalent modification on the thiol group of cysteine residues by nitric oxide. Growing evidence shows that protein S-nitrosylation plays an important role in normal cellular function as well as in various pathophysiologic conditions. Because of the inherent chemical instability of the S-NO bond and the low abundance of endogenous S-nitrosylated proteins, the unambiguous identification of S-nitrosylation sites by commonly used proteomic approaches remains challenging. Therefore, computational prediction of S-nitrosylation sites has been considered as a powerful auxiliary tool. In this work, we mainly adopted an adapted normal distribution bi-profile Bayes (ANBPB) feature extraction model to characterize the distinction of position-specific amino acids in 784 S-nitrosylated and 1568 non-S-nitrosylated peptide sequences. We developed a support vector machine prediction model, iSNO-ANBPB, by incorporating ANBPB with the Chou's pseudo amino acid composition. In jackknife cross-validation experiments, iSNO-ANBPB yielded an accuracy of 65.39% and a Matthew's correlation coefficient (MCC) of 0.3014. When tested on an independent dataset, iSNO-ANBPB achieved an accuracy of 63.41% and a MCC of 0.2984, which are much higher than the values achieved by the existing predictors SNOSite, iSNO-PseAAC, the Li et al. algorithm, and iSNO-AAPair. On another training dataset, iSNO-ANBPB also outperformed GPS-SNO and iSNO-PseAAC in the 10-fold crossvalidation test.

  13. Immunohistochemical expression profiles of mucin antigens in salivary gland mucoepidermoid carcinoma: MUC4- and MUC6-negative expression predicts a shortened survival in the early postoperative phase.

    PubMed

    Honjo, Kie; Hiraki, Tsubasa; Higashi, Michiyo; Noguchi, Hirotsugu; Nomoto, Mitsuharu; Yoshimura, Takuya; Batra, Surinder K; Yonezawa, Suguru; Semba, Ichiro; Nakamura, Norifumi; Tanimoto, Akihide; Yamada, Sohsuke

    2018-02-01

    In mucoepidermoid carcinoma (MEC), the most common salivary gland carcinoma, there is a lack of novel prognostic markers, but post-operative early recurrence strongly affects the clinical course and a poor outcome. It is critical to predict which MEC patients are prone to develop recurrence/metastases. Mucins play pivotal roles in influencing cancer biology, thus affecting cell differentiation, adhesion, carcinoma invasion, aggressiveness and/or metastatic potential. Our aim is to elucidate the significance of expression profiles for mucins, particularly MUC4 and MUC6, and their correlations with various clinicopathological features and recurrence in salivary gland MECs. We performed immunohistochemical analyses on patients with surgically resected primary MEC using antibodies against mucin core proteins MUC4/8G7 and MUC6/CLH5 in 73 paraffin-embedded samples. Recurrence was noted in 15 of 73 (20.5%) patients. MUC4 or MUC6 expression was considered to be negative when <30% or 0% of the MEC cells showed positive staining, respectively. MUC4- and/or MUC6-negative expression respectively and variably showed a significant relationship to pathological tumor high-grade, the presence of lymphovascular invasion, lymph node metastasis and/or tumor-related death. In addition, MUC4 showed significantly negative co-expression with MUC6. Kaplan-Meier analyses revealed that not only single MUC4/6-negative expression but also the combination of both predicted significantly shorter disease-free and disease-specific survivals in MECs, especially within the first two years postoperatively. Therefore, each mucin plays a pivotal role in the pathogenesis of MEC progression. The detection of MUC4 and/or MUC6 might be a powerful parameter in the clinical management of MECs in the early postsurgical phase.

  14. Anticipating the next meal using meal behavioral profiles: a hybrid model-based stochastic predictive control algorithm for T1DM.

    PubMed

    Hughes, C S; Patek, S D; Breton, M; Kovatchev, B P

    2011-05-01

    Automatic control of Type 1 Diabetes Mellitus (T1DM) with subcutaneous (SC) measurement of glucose concentration and subcutaneous (SC) insulin infusion is of great interest within the diabetes technology research community. The main challenge with the so-called "SC-SC" route to control is sensing and actuation delay, which tends to either destabilize the system or inhibit the aggressiveness of the controller in responding to meals and exercise. Model predictive control (MPC) is one strategy for mitigating delay, where optimal insulin infusions can be given in anticipation of future meal disturbances. Unfortunately, exact prior knowledge of meals can only be assured in a clinical environment and uncertainty about when and if meals will arrive could lead to catastrophic outcomes. As a follow-on to our recent paper in the IFAC symposium on Biological and Medical Systems (MCBMS 2009), we develop a control law that can anticipate meals given a probabilistic description of the patient's eating behavior in the form of a random meal (behavioral) profile. Preclinical in silico trials using the oral glucose meal model of Dalla Man et al. show that the control strategy provides a convenient means of accounting for uncertain prior knowledge of meals without compromising patient safety, even in the event that anticipated meals are skipped. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

  15. Fourier transform infrared spectroscopy for the prediction of fatty acid profiles in Mucor fungi grown in media with different carbon sources.

    PubMed

    Shapaval, Volha; Afseth, Nils Kristian; Vogt, Gjermund; Kohler, Achim

    2014-09-11

    Fungal production of polyunsaturated fatty acids (PUFAs) is a highly potential approach in biotechnology. Currently the main focus is directed towards screening of hundreds strains in order to select of few potential ones. Thus, a reliable method for screening a high number of strains within a short period of time is needed. Here, we present a novel method for screening of PUFA-producing fungi by high-throughput microcultivation and FTIR spectroscopy. In the study selected Mucor fungi were grown in media with different carbon sources and fatty acid profiles were predicted on the basis of the obtained spectral data. FTIR spectra were calibrated against fatty acid analysis by GC-FD. The calibration models were cross-validated and correlation coefficients (R2) from 0.71 to 0.78 with RMSECV (root mean squared error) from 2.86% to 6.96% (percentage of total fat) were obtained. The FTIR results show a strong correlation to the results obtained by GC analysis, where high total contents of unsaturated fatty acids (both PUFA and MUFA) were achieved for Mucor plumbeus VI02019 cultivated in canola, olive and sunflower oil and Mucor hiemalis VI01993 cultivated in canola and olive oil.

  16. Rapid profiling of polymeric phenolic acids in Salvia miltiorrhiza by hybrid data-dependent/targeted multistage mass spectrometry acquisition based on expected compounds prediction and fragment ion searching.

    PubMed

    Shen, Yao; Feng, Zijin; Yang, Min; Zhou, Zhe; Han, Sumei; Hou, Jinjun; Li, Zhenwei; Wu, Wanying; Guo, De-An

    2018-04-01

    Phenolic acids are the major water-soluble components in Salvia miltiorrhiza (>5%). According to previous studies, many of them contribute to the cardiovascular effects and antioxidant effects of S. miltiorrhiza. Polymeric phenolic acids can be considered as the tanshinol derived metabolites, e.g., dimmers, trimers, and tetramers. A strategy combined with tanshinol-based expected compounds prediction, total ion chromatogram filtering, fragment ion searching, and parent list-based multistage mass spectrometry acquisition by linear trap quadropole-orbitrap Velos mass spectrometry was proposed to rapid profile polymeric phenolic acids in S. miltiorrhiza. More than 480 potential polymeric phenolic acids could be screened out by this strategy. Based on the fragment information obtained by parent list-activated data dependent multistage mass spectrometry acquisition, 190 polymeric phenolic acids were characterized by comparing their mass information with literature data, and 18 of them were firstly detected from S. miltiorrhiza. Seven potential compounds were tentatively characterized as new polymeric phenolic acids from S. miltiorrhiza. This strategy facilitates identification of polymeric phenolic acids in complex matrix with both selectivity and sensitivity, which could be expanded for rapid discovery and identification of compounds from complex matrix. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  17. Geographic Profiling: Knowledge Through Prediction

    DTIC Science & Technology

    2014-06-01

    FTO Foreign Terrorist Organization GIS geographic information systems LE lawless elements MADM multi-attribute decision making MILF Moro Islamic...or her life. Anchor points can include the offender’s home , his or her workplace, a home of a friend of the offender, or even a bar or restaurant...more generally for the improvement of police patrols. In Memphis, TN, city officials have seen a decrease in crime with the help of operation Blue

  18. [The value of fasting plasma glucose and lipid profiles between 7 and 15 gestational weeks in the prediction of gestational diabetes mellitus].

    PubMed

    Zhao, M; Li, G H

    2016-11-25

    Objective: To explore the value of using fasting plasma glucose (FPG) and lipid profiles between 7 and 15 gestational weeks to predict gestational diabetes mellitus (GDM). Methods: The medical records of 2 138 pregnant women who had prenatal care in Beijing Obstetrics and Gynecology Hospital from August 2011 to February 2012 were analyzed retrospectively. According to results of the oral glucose tolerance tests, women were devided into the GDM group ( n =240) and the normal group ( n= 1 898). Maternal characteristics, FPG and lipid levels between 7 and 15 gestational weeks were compared between the two groups. Logistic regression analysis and receiver operator characteristics(ROC) curve were used in the analysis. Results: Potential markers for the prediction of GDM included total cholesterol, triglyceride (TG) , low-density lipoprotein cholesterol/high-density lipoprotein cholesterol ratios (LDL-C/HDL-C) , triglyceride to high-density lipoprotein cholesterol ratios (TG/HDL-C) and FPG. After adjustment of confounding factors, age ( OR= 1.046, 95% CI: 1.003-1.090), pre- pregnancy body mass index ( OR= 1.104, 95% CI: 1.049-1.161), gravidity>3 ( OR= 1.768, 95% CI: 1.071-2.920), FPG ( OR= 8.137, 95% CI: 5.412-12.236), TG ( OR= 1.460, 95% CI: 1.148-1.858) were independently associated with the risk of developing GDM. Equation, P GDM =1/{1+exp[-(-16.542+0.045×age+0.103×pre-pregnancy body mass index+0.551×gravidity>3+2.110×FPG+0.372×TG)]}, was constructed by the logistic regression analysis. Sensitivity (67.5%) and specificity (70.5%) were determined by the calculated risk score, with a cut-off value of 0.11 (area under the curve: 0.751, 95% CI: 0.718-0.783, P< 0.001). Conclusions: FPG and TG, together with clinical characteristics may have a better predictive value for the risk of GDM.

  19. The association between maternal cervicovaginal proinflammatory cytokines concentrations during pregnancy and subsequent early-onset neonatal infection.

    PubMed

    Kalinka, Jarosław; Krajewski, Paweł; Sobala, Wojciech; Wasiela, Małgorzata; Brzezińska-Błaszczyk, Ewa

    2006-01-01

    The aim of this study was to investigate the relationship between the concentration of selected proinflammatory cytokines (IL-1alpha, IL-1beta, IL-6 and IL-8) in cervicovaginal fluid, as measured in midgestation, and the risk of early-onset neonatal infection (EONI). Cervicovaginal fluids were obtained from a cohort of 114 pregnant women at 22 to 34 weeks' gestation. The samples were analyzed for the concentrations of selected proinflammatory cytokines using standard enzyme-linked immunosorbent assay technique (ELISA). Lower genital tract microbiology was diagnosed using Gram stain method according to Spiegel's criteria and by culture. Mean gestational age at the time of sampling was 29.0 weeks. Mean time between sampling and delivery was 9.3 (SD 4.7) weeks. Bacterial vaginosis (BV) was diagnosed in 27.2% of subjects and M. hominis and U. urealyticum in 22.8% and 26.3%, respectively. Out of 114 women examined, 20 (17.5%) delivered newborns with EONI. Median cervicovaginal concentrations of IL-1alpha, IL-1beta, IL-6 and IL-8 did not differ between women who delivered newborns with EONI as compared to women who delivered newborns without EONI. Women with pathological lower genital tract microflora and low IL-8 concentration (below 25(th) percentile) during pregnancy presented a significant risk of delivering newborns with EONI (OR=4.9; 95% CI, 1.1-22.8). Subjects with pathological lower genital tract microflora and a low concentration of more than one cytokine had the highest risk of delivering a newborn with EONI, OR=16.2, 95% CI, 1.1-234.0. Cytokine measurement in cervicovaginal fluid in early gestation could be useful for predicting subsequent EONI only among pregnant women with lower genital tract infection. Maternal genital tract immune hyporesponsiveness as represented by low concentrations of proinflammatory cytokines may create a permissive environment for ascending infection and may lead to subsequent EONI.

  20. Proinflammatory Cytokines, Enolase and S-100 as Early Biochemical Indicators of Hypoxic-Ischemic Encephalopathy Following Perinatal Asphyxia in Newborns.

    PubMed

    Chaparro-Huerta, Verónica; Flores-Soto, Mario Eduardo; Merin Sigala, Mario Ernesto; Barrera de León, Juan Carlos; Lemus-Varela, María de Lourdes; Torres-Mendoza, Blanca Miriam de Guadalupe; Beas-Zárate, Carlos

    2017-02-01

    Estimation of the neurological prognosis of infants suffering from perinatal asphyxia and signs of hypoxic-ischemic encephalopathy is of great clinical importance; however, it remains difficult to satisfactorily assess these signs with current standard medical practices. Prognoses are typically based on data obtained from clinical examinations and neurological tests, such as electroencephalography (EEG) and neuroimaging, but their sensitivities and specificities are far from optimal, and they do not always reliably predict future neurological sequelae. In an attempt to improve prognostic estimates, neurological research envisaged various biochemical markers detectable in the umbilical cord blood of newborns (NB). Few studies examining these biochemical factors in the whole blood of newborns exist. Thus, the aim of this study was to determine the expression and concentrations of proinflammatory cytokines (TNF-α, IL-1β and IL-6) and specific CNS enzymes (S-100 and enolase) in infants with perinatal asphyxia. These data were compared between the affected infants and controls and were related to the degree of HIE to determine their utilities as biochemical markers for early diagnosis and prognosis. The levels of the proinflammatory cytokines and enzymes were measured by enzyme-linked immunosorbent assay (ELISA) and Reverse Transcription polymerase chain reaction (RT-PCR). The expression and serum levels of the proinflammatory cytokines, enolase and S-100 were significantly increased in the children with asphyxia compared with the controls. The role of cytokines after hypoxic-ischemic insult has been determined in studies of transgenic mice that support the use of these molecules as candidate biomarkers. Similarly, S-100 and enolase are considered promising candidates because these markers have been correlated with tissue damage in different experimental models. Copyright © 2016. Published by Elsevier B.V.

  1. Mercury exposure induces proinflammatory enzymes in vascular fibroblasts.

    PubMed

    Millán Longo, Alberto; Montero Saiz, Óscar; Sarró Fuente, Claudia; Aguado Martínez, Andrea; Salaices Sánchez, Mercedes

    Previous studies show that mercury exposure increases cardiovascular risk, although the underlying cellular mechanisms have still not been fully studied. The aim of this project is to study, in vascular fibroblasts (VF), the effect of HgCl 2 exposure on the expression of enzymes involved in the synthesis of prostanoids and reactive oxygen species (ROS). These molecules have been shown to participate in the inflammatory response associated with cardiovascular diseases. Adventitial VF cultures of Sprague-Dawley rat aortas, shown to be α-actin negative by immunofluorescence, were exposed to HgCl 2 (0.05-5μg/mL) for 48h. mRNA and protein levels of cyclooxygenase-2 (COX-2), microsomal prostaglandin E synthase 1 (mPGES-1), thromboxane A 2 synthase (TXAS), NADPH oxidase 1 (NOX-1), and 4 (NOX-4) where analyzed using qRT-PCR and western blot, respectively. NOX activity was determined by chemiluminescence. HgCl 2 exposure increased COX-2, mPGES-1, TXAS, and NOX-1 expression and NOX activity, and decreased NOX-4 expression. The increase in NOX-1 and COX-2 expression was abolished by the treatment with inhibitors of COX-2 (10μM celecoxib) and NOX (300μM apocynin, 0.5μM ML-171). 1) HgCl 2 increases the expression of pro-inflammatory enzymes involved in ROS and prostanoid synthesis in VF. 2) There is a reciprocal regulation between COX-2 and NOX-1 pathways. 3) These effects can contribute to explain the increase in cardiovascular risk associated to mercury. Copyright © 2017 Sociedad Española de Arteriosclerosis. Publicado por Elsevier España, S.L.U. All rights reserved.

  2. Sites Inferred by Metabolic Background Assertion Labeling (SIMBAL): adapting the Partial Phylogenetic Profiling algorithm to scan sequences for signatures that predict protein function

    PubMed Central

    2010-01-01

    Background Comparative genomics methods such as phylogenetic profiling can mine powerful inferences from inherently noisy biological data sets. We introduce Sites Inferred by Metabolic Background Assertion Labeling (SIMBAL), a method that applies the Partial Phylogenetic Profiling (PPP) approach locally within a protein sequence to discover short sequence signatures associated with functional sites. The approach is based on the basic scoring mechanism employed by PPP, namely the use of binomial distribution statistics to optimize sequence similarity cutoffs during searches of partitioned training sets. Results Here we illustrate and validate the ability of the SIMBAL method to find functionally relevant short sequence signatures by application to two well-characterized protein families. In the first example, we partitioned a family of ABC permeases using a metabolic background property (urea utilization). Thus, the TRUE set for this family comprised members whose genome of origin encoded a urea utilization system. By moving a sliding window across the sequence of a permease, and searching each subsequence in turn against the full set of partitioned proteins, the method found which local sequence signatures best correlated with the urea utilization trait. Mapping of SIMBAL "hot spots" onto crystal structures of homologous permeases reveals that the significant sites are gating determinants on the cytosolic face rather than, say, docking sites for the substrate-binding protein on the extracellular face. In the second example, we partitioned a protein methyltransferase family using gene proximity as a criterion. In this case, the TRUE set comprised those methyltransferases encoded near the gene for the substrate RF-1. SIMBAL identifies sequence regions that map onto the substrate-binding interface while ignoring regions involved in the methyltransferase reaction mechanism in general. Neither method for training set construction requires any prior experimental

  3. Etiogenic factors present in the cerebrospinal fluid from amyotrophic lateral sclerosis patients induce predominantly pro-inflammatory responses in microglia.

    PubMed

    Mishra, Pooja-Shree; Vijayalakshmi, K; Nalini, A; Sathyaprabha, T N; Kramer, B W; Alladi, Phalguni Anand; Raju, T R

    2017-12-16

    Microglial cell-associated neuroinflammation is considered as a potential contributor to the pathophysiology of sporadic amyotrophic lateral sclerosis. However, the specific role of microglia in the disease pathogenesis remains to be elucidated. We studied the activation profiles of the microglial cultures exposed to the cerebrospinal fluid from these patients which recapitulates the neurodegeneration seen in sporadic amyotrophic lateral sclerosis. This was done by investigating the morphological and functional changes including the expression levels of prostaglandin E2 (PGE2), cyclooxygenase-2 (COX-2), TNF-α, IL-6, IFN-γ, IL-10, inducible nitric oxide synthase (iNOS), arginase, and trophic factors. We also studied the effect of chitotriosidase, the inflammatory protein found upregulated in the cerebrospinal fluid from amyotrophic lateral sclerosis patients, on these cultures. We report that the cerebrospinal fluid from amyotrophic lateral sclerosis patients could induce an early and potent response in the form of microglial activation, skewed primarily towards a pro-inflammatory profile. It was seen in the form of upregulation of the pro-inflammatory cytokines and factors including IL-6, TNF-α, iNOS, COX-2, and PGE2. Concomitantly, a downregulation of beneficial trophic factors and anti-inflammatory markers including VEGF, glial cell line-derived neurotrophic factor, and IFN-γ was seen. In addition, chitotriosidase-1 appeared to act specifically via the microglial cells. Our findings demonstrate that the cerebrospinal fluid from amyotrophic lateral sclerosis patients holds enough cues to induce microglial inflammatory processes as an early event, which may contribute to the neurodegeneration seen in the sporadic amyotrophic lateral sclerosis. These findings highlight the dynamic role of microglial cells in the pathogenesis of the disease, thus suggesting the need for a multidimensional and temporally guarded therapeutic approach targeting the inflammatory

  4. Development and validation of a gene profile predicting benefit of postmastectomy radiotherapy in patients with high-risk breast cancer: a study of gene expression in the DBCG82bc cohort.

    PubMed

    Tramm, Trine; Mohammed, Hayat; Myhre, Simen; Kyndi, Marianne; Alsner, Jan; Børresen-Dale, Anne-Lise; Sørlie, Therese; Frigessi, Arnoldo; Overgaard, Jens

    2014-10-15

    To identify genes predicting benefit of radiotherapy in patients with high-risk breast cancer treated with systemic therapy and randomized to receive or not receive postmastectomy radiotherapy (PMRT). The study was based on the Danish Breast Cancer Cooperative Group (DBCG82bc) cohort. Gene-expression analysis was performed in a training set of frozen tumor tissue from 191 patients. Genes were identified through the Lasso method with the endpoint being locoregional recurrence (LRR). A weighted gene-expression index (DBCG-RT profile) was calculated and transferred to quantitative real-time PCR (qRT-PCR) in corresponding formalin-fixed, paraffin-embedded (FFPE) samples, before validation in FFPE from 112 additional patients. Seven genes were identified, and the derived DBCG-RT profile divided the 191 patients into "high LRR risk" and "low LRR risk" groups. PMRT significantly reduced risk of LRR in "high LRR risk" patients, whereas "low LRR risk" patients showed no additional reduction in LRR rate. Technical transfer of the DBCG-RT profile to FFPE/qRT-PCR was successful, and the predictive impact was successfully validated in another 112 patients. A DBCG-RT gene profile was identified and validated, identifying patients with very low risk of LRR and no benefit from PMRT. The profile may provide a method to individualize treatment with PMRT. ©2014 American Association for Cancer Research.

  5. Prediction of functional profiles of gut microbiota from 16S rRNA metagenomic data provides a more robust evaluation of gut dysbiosis occurring in Japanese type 2 diabetic patients.

    PubMed

    Inoue, Ryo; Ohue-Kitano, Ryuji; Tsukahara, Takamitsu; Tanaka, Masashi; Masuda, Shinya; Inoue, Takayuki; Yamakage, Hajime; Kusakabe, Toru; Hasegawa, Koji; Shimatsu, Akira; Satoh-Asahara, Noriko

    2017-11-01

    We assessed whether gut microbial functional profiles predicted from 16S rRNA metagenomics differed in Japanese type 2 diabetic patients. A total of 22 Japanese subjects were recruited from our outpatient clinic in an observational study. Fecal samples were obtained from 12 control and 10 type 2 diabetic subjects. 16S rRNA metagenomic data were generated and functional profiles predicted using "Phylogenetic Investigation of Communities by Reconstruction of Unobserved States" software. We measured the parameters of glucose metabolism, gut bacterial taxonomy and functional profile, and examined the associations in a cross-sectional manner. Eleven of 288 "Kyoto Encyclopedia of Genes and Genomes" pathways were significantly enriched in diabetic patients compared with control subjects ( p <0.05, q<0.1). The relative abundance of almost all pathways, including the Insulin signaling pathway and Glycolysis/Gluconeogenesis , showed strong, positive correlations with hemoglobin A 1c (HbA 1c ) and fasting plasma glucose (FPG) levels. Bacterial taxonomic analysis showed that genus Blautia significantly differed between groups and had negative correlations with HbA 1c and FPG levels. Our findings suggest a novel pathophysiological relationship between gut microbial communities and diabetes, further highlighting the significance and utility of combining prediction of functional profiles with ordinal bacterial taxonomic analysis (UMIN Clinical Trails Registry number: UMIN000026592).

  6. A comparative analysis of cardiovascular disease risk profiles of five Pacific ethnic groups assessed in New Zealand primary care practice: PREDICT CVD-13.

    PubMed

    Grey, Corina; Wells, Sue; Riddell, Tania; Pylypchuk, Romana; Marshall, Roger; Drury, Paul; Elley, Raina; Ameratunga, Shanthi; Gentles, Dudley; Erick-Peletiy, Stephanie; Bell, Fionna; Kerr, Andrew; Jackson, Rod

    2010-11-05

    Data on the cardiovascular disease risk profiles of Pacific peoples in New Zealand is usually aggregated and treated as a single entity. Little is known about the comparability or otherwise of cardiovascular disease (CVD) risk between different Pacific groups. To compare CVD risk profiles for the main Pacific ethnic groups assessed in New Zealand primary care practice to determine if it is reasonable to aggregate these data, or if significant differences exist. A web-based clinical decision support system for CVD risk assessment and management (PREDICT) has been implemented in primary care practices in nine PHOs throughout Auckland and Northland since 2002, covering approximately 65% of the population of these regions. Between 2002 and January 2009, baseline CVD risk assessments were carried out on 11,642 patients aged 35-74 years identifying with one or more Pacific ethnic groups (4933 Samoans, 1724 Tongans, 1366 Cook Island Maori, 880 Niueans, 1341 Fijians and 1398 people identified as Other Pacific or Pacific Not Further Defined). Fijians were subsequently excluded from the analyses because of a probable misclassification error that appears to combine Fijian Indians with ethnic Fijians. Prevalences of smoking, diabetes and prior history of CVD, as well as mean total cholesterol/HDL ratio, systolic and diastolic blood pressures, and Framingham 5-year CVD risk were calculated for each Pacific group. Age-adjusted risk ratios and mean differences stratified by gender were calculated using Samoans as the reference group. Cook Island women were almost 60% more likely to smoke than Samoan women. While Tongan men had the highest proportion of smoking (29%) among Pacific men, Tongan women had the lowest smoking proportion (10%) among Pacific women. Tongan women and Niuean men and women had a higher burden of diabetes than other Pacific ethnic groups, which were 20-30% higher than their Samoan counterparts. Niuean men and women had lower blood pressure levels than all

  7. Proinflammatory isoforms of IL-32 as novel and robust biomarkers for control failure in HIV-infected slow progressors

    PubMed Central

    El-Far, Mohamed; Kouassi, Pascale; Sylla, Mohamed; Zhang, Yuwei; Fouda, Ahmed; Fabre, Thomas; Goulet, Jean-Philippe; van Grevenynghe, Julien; Lee, Terry; Singer, Joel; Harris, Marianne; Baril, Jean-Guy; Trottier, Benoit; Ancuta, Petronela; Routy, Jean-Pierre; Bernard, Nicole; Tremblay, Cécile L.; Angel, Jonathan; Conway, Brian; Côté, Pierre; Gill, John; Johnston, Lynn; Kovacs, Colin; Loutfy, Mona; Logue, Kenneth; Piché, Alain; Rachlis, Anita; Rouleau, Danielle; Thompson, Bill; Thomas, Réjean; Trottier, Sylvie; Walmsley, Sharon; Wobeser, Wendy

    2016-01-01

    HIV-infected slow progressors (SP) represent a heterogeneous group of subjects who spontaneously control HIV infection without treatment for several years while showing moderate signs of disease progression. Under conditions that remain poorly understood, a subgroup of these subjects experience failure of spontaneous immunological and virological control. Here we determined the frequency of SP subjects who showed loss of HIV control within our Canadian Cohort of HIV+ Slow Progressors and identified the proinflammatory cytokine IL-32 as a robust biomarker for control failure. Plasmatic levels of the proinflammatory isoforms of IL-32 (mainly β and γ) at earlier clinic visits positively correlated with the decline of CD4 T-cell counts, increased viral load, lower CD4/CD8 ratio and levels of inflammatory markers (sCD14 and IL-6) at later clinic visits. We present here a proof-of-concept for the use of IL-32 as a predictive biomarker for disease progression in SP subjects and identify IL-32 as a potential therapeutic target. PMID:26978598

  8. [PECULIARITIES OF THE ANALYSIS OF THE LEVEL OF PROINFLAMMATORY CYTOKINS IN THE COMMUNITY-ACQUIRED PNEUMONIA IN CHILDREN].

    PubMed

    Akhaeyva, A; Zhupenova, D; Kenzhetaeva, T; Kysabekova, A; Dzhabaeva, S

    2017-11-01

    The high specific gravity in the structure of morbidity in children of all age groups, complicated course, determines the urgency of studying the clinical and diagnostic aspects of community-acquired pneumonia. In recent years, interest has been growing in the study of the child's cytokine status. A number of studies indicate that cytokines regulate the severity and duration of the inflammatory process. In this regard, the study of the possibility of determining the level of proinflammatory cytokines (IL-6 , TNF-α) is of great practical importance for assessing the prognosis of community-acquired pneumonia in children. In a prospective cohort study, 90 children with community-acquired pneumonia aged between 5 and 14 years were treated under treatment in the department respiratory of the Children›s Hospital in Karaganda, of which 47% were girls (95% CI 31.51% - 56.33%) and boys 53% (CI 95% 34.91% - 59.88%). The control group included 20 healthy children. Analysis of the results of the study revealed an increase in the content of proinflammatory cytokines in the blood serum and urine on children with community-acquired pneumonia depending on the severity of the course. At the same time, the equivalence of the cytokine trends in serum and urine determines the possibility of noninvasive detection of cytokines, both for characterizing the inflammatory response of the organism as such and for predicting the development of community-acquired pneumonia, which is especially valuable in pediatric practice.

  9. Expression profiles analysis of long non-coding RNAs identified novel lncRNA biomarkers with predictive value in outcome of cutaneous melanoma.

    PubMed

    Ma, Xu; He, Zhijuan; Li, Ling; Yang, Daping; Liu, Guofeng

    2017-09-29

    Recent advancements in cancer biology have identified a large number of lncRNAs that are dysregulated expression in the development and tumorigenesis of cancers, highlighting the importance of lncRNAs as a key player for human cancers. However, the prognostic value of lncRNAs still remains unclear and needs to be further investigated. In the present study, we aim to assess the prognostic value of lncRNAs in cutaneous melanoma by integrated lncRNA expression profiles from TCGA database and matched clinical information from a large cohort of patients with cutaneous melanoma. We finally identified a set of six lncRNAs that are significantly associated with survival of patients with cutaneous melanoma. A linear combination of six lncRNAs ( LINC01260, HCP5, PIGBOS1, RP11-247L20.4, CTA-292E10.6 and CTB-113P19.5 ) was constructed as a six-lncRNA signature which classified patients of training cohort into the high-risk group and low-risk group with significantly different survival time. The prognostic value of the six-lncRNA signature was validated in both the validation cohort and entire TCGA cohort. Moreover, the six-lncRNA signature is independent of known clinic-pathological factors by multivariate Cox regression analysis and demonstrated good performance for predicting three- and five-year overall survival by time-dependent receiver operating characteristic (ROC) analysis. Our study provides novel insights into the molecular heterogeneity of cutaneous melanoma and also shows potentially important implications of lncRNAs for prognosis and therapy for cutaneous melanoma.

  10. Do proinflammatory cytokine levels predict serious complication risk of infection in pediatric cancer patients?

    PubMed

    Karakurt, Deniz Guven; Demirsoy, Ugur; Corapcioglu, Funda; Oncel, Selim; Karadogan, Meriban; Arisoy, Emin Sami

    2014-08-01

    Determination of risk of severe bacterial infection complication in children with cancer is important to diminish the cost of hospitalization and therapy. In this study, children with cancer (leukemia excluded) were evaluated for risk of severe infection complication, success of therapy and the relation between clinical and inflammatory parameters during neutropenic fever attacks. Children who fulfilled the criteria of neutropenic fever with cancer were enrolled in the study. During admission, together with clinical and laboratory parameters; interleukin-6, interleukin-8, soluble tumor necrosis factor receptor II, and soluble interleukin 2 reseptor ve procalcitonin levels were detected. Empirical therapy was started with piperacillin/tazobactam and relation between the inflammatory cytokine levels and therapy response parameters were evaluated. The study population included 31 children and 50 neutropenic attacks were studied. In 48% of the attacks, absolute neutrophile count was >100/mm(3) and infectious agents were shown microbiologically in 12% of the attacks. In the study group with piperacillin/tazobactam monotherapy, the success rate without modification was 58%. In the therapy modified group mean duration of fever, antibiotherapy and hospitalization were significantly longer than the group without modification. Inflammatory cytokines' levels during admission (interleukin-6, interleukin-8, soluble tumor necrosis factor reseptor II) were higher in patients with fever >3 days and in multiple regression analysis, it has been shown that they have a determinative role on fever control time. Other cytokines did not show any significant relationship with risk of severe bacterial infection complication and success of therapy.

  11. Basal gene expression predicts ozone-induced pro-inflammatory response in GSTM1-null individuals

    EPA Science Inventory

    Air pollution exposure causes increased cardiopulmonary morbidity and mortality and has been linked to the deaths of 7 million people every year by the World Health Organization. Approximately 40% of the population lack expression of the antioxidant enzyme glutathione S-transfer...

  12. EXTRINSIC COAGULATION BLOCKADE ATTENUATES LUNG INJURY AND PROINFLAMMATORY CYTOKINE RELEASE AFTER INTRATRACHEAL LIPOPOLYSACCHARIDE

    EPA Science Inventory

    Initiation of coagulation by tissue factor (TF) is a potentially powerful regulator of local inflammatory responses. We hypothesized that blockade of TF-factor VIIa (FVIIa) complex would decrease lung inflammation and proinflammatory cytokine release after tracheal instillation o...

  13. Age-associated Pro-inflammatory Remodeling and Functional Phenotype in the Heart and Large Arteries

    PubMed Central

    Wang, Mingyi; Shah, Ajay M

    2015-01-01

    The aging population is increasing dramatically. Aging–associated stress simultaneously drives proinflammatory remodeling, involving angiotensin II and other factors, in both the heart and large arteries. The structural remodeling and functional changes that occur with aging include cardiac and vascular wall stiffening, systolic hypertension and suboptimal ventricular-arterial coupling, features that are often clinically silent and thus termed a silent syndrome. These age-related effects are the result of responses initiated by cardiovascular proinflammatory cells. Local proinflammatory signals are coupled between the heart and arteries due to common mechanical and humoral messengers within a closed circulating system. Thus, targeting proinflammatory signaling molecules would be a promising approach to improve age-associated suboptimal ventricular-arterial coupling, a major predisposing factor for the pathogenesis of clinical cardiovascular events such as heart failure. PMID:25665458

  14. Pro-inflammatory cytokine single nucleotide polymorphisms in Kawasaki disease.

    PubMed

    Assari, Raheleh; Aghighi, Yahya; Ziaee, Vahid; Sadr, Maryam; Rahmani, Farzaneh; Rezaei, Arezou; Sadr, Zeinab; Moradinejad, Mohammad Hassan; Raeeskarami, Seyed Reza; Rezaei, Nima

    2016-07-25

    Kawasaki disease (KD) is a systemic vasculitis of children associated with cardiovascular sequelae. Proinflammatory cytokines play a major role in KD pathogenesis. However, their role is both influenced and modified by regulatory T-cells. IL-1 gene cluster, IL-6 and TNF-α polymorphisms have shown significant associations with some vasculitides. Herein we investigated their role in KD. Fifty-five patients with KD who were randomly selected from referrals to the main pediatric hospital were enrolled in this case-control study. Single nucleotide polymorphisms (SNPs) of the following genes were assessed in patients and 140 healthy subjects as control group: IL-1α at -889 (rs1800587), IL-1β at -511 (rs16944), IL-1β at +3962 (rs1143634), IL-1R at Pst-I 1970 (rs2234650), IL-1RN/A at Mspa-I 11100 (rs315952), TNF-α at -308 (rs1800629), TNF-α at -238, IL-6 at -174 (rs1800795) and IL-6 at +565. Twenty-one percent of the control group had A allele at TNF-α -238 while only 8% of KD patients had A allele at this position (P = 0.003, OR [95%CI] = 0.32 [0.14-0.71]). Consistently, TNF-α genotype GG at -238 had significant association with KD (OR [95% CI] = 4.31 [1.79-10.73]). Most controls carried the CG genotype at IL-6 -174 (n = 93 [66.9%]) while GG genotype was the most common genotype (n = 27 [49%]) among patients. Carriers of the GG haplotype at TNF-α (-308, -238) were significantly more prevalent among the KD group. No association was found between IL-1 gene cluster, allelic or haplotypic variants and KD. TNF-α GG genotype at -238 and GG haplotype at positions -308 and -238 were associated with KD in an Iranian population. © 2016 Asia Pacific League of Associations for Rheumatology and John Wiley & Sons Australia, Ltd.

  15. Extracorporeal Shock Wave Therapy Suppresses the Early Proinflammatory Immune Response to a Severe Cutaneous Burn Injury

    DTIC Science & Technology

    2009-02-01

    Burn wound model Mice were anaesthetised using isoflurane inha- lation. After shaving the dorsum, the exposed skin was washed gently with room...Extracorporeal shock wave therapy suppresses the early proinflammatory immune response to a severe cutaneous burn injury* Thomas A Davis, Alexander...S, Peoples GE, Tadaki D, Elster EA. Extracorporeal shock wave therapy suppresses the early proinflammatory immune response to a severe cutaneous burn

  16. Progression of symptomatic intracranial large artery atherosclerosis is associated with a proinflammatory state and impaired fibrinolysis.

    PubMed

    Arenillas, Juan F; Alvarez-Sabín, José; Molina, Carlos A; Chacón, Pilar; Fernández-Cadenas, Israel; Ribó, Marc; Delgado, Pilar; Rubiera, Marta; Penalba, Anna; Rovira, Alex; Montaner, Joan

    2008-05-01

    The molecular pathways involved in the progression of intracranial large artery atherosclerosis (ILA) are largely unknown. Our objective was to prospectively study the relationship between circulating levels of inflammatory markers and fibrinolysis inhibitors, and the risk of progression of symptomatic ILA. Seventy-five consecutive patients with first-ever symptomatic intracranial atherostenosis were studied. Blood levels of C-reactive protein (CRP), E-selectin, monocyte chemoattractant protein-1, intercellular adhesion molecule-1, matrix metalloproteinases 1, 2, 3, 8, 9, 10, and 13, plasminogen activator inhibitor-1 (PAI-1), and lipoprotein(a) were measured 3 months after the qualifying stroke or transient ischemic attack. Thereafter, patients underwent long-term transcranial Doppler follow-up to detect progression of ILA. During a median follow-up time of 23 months, 25 (33%) patients showed ILA progression. Multivariable adjusted Cox regression models and Kaplan-Meier curves showed that high baseline level of CRP, E-selectin, intercellular adhesion molecule-1, matrix metalloproteinase 9, PAI-1, and lipoprotein(a) predicted ILA progression independently of vascular risk factors. Of them, only CRP (CRP>5.5 mg/L; HR, 5.4 [2.3 to 12.7]; P=0.0001) and PAI-1 (PAI-1>23.1 ng/mL; HR, 2.4 [1.0 to 5.8]; P=0.05) predicted ILA progression also independently of the other studied molecules. Progression of symptomatic ILA is associated with a proinflammatory state, as reflected by high levels of inflammatory markers, and with defective fibrinolysis, as indicated by raised concentrations of endogenous fibrinolysis inhibitors.

  17. PhosphoLipid transfer protein (PLTP) exerts a direct pro-inflammatory effect on rheumatoid arthritis (RA) fibroblasts-like-synoviocytes (FLS) independently of its lipid transfer activity

    PubMed Central

    Deckert, Valérie; Daien, Claire I.; Che, Hélène; Elhmioui, Jamila; Lemaire, Stéphanie; Pais de Barros, Jean-Paul; Desrumaux, Catherine; Combe, Bernard; Hahne, Michael; Lagrost, Laurent; Morel, Jacques

    2018-01-01

    Rheumatoid arthritis (RA) is a chronic inflammatory rheumatic disease with modification of lipids profile and an increased risk of cardiovascular events related to inflammation. Plasma phospholipid transfer protein (PLTP) exerts a lipid transfer activity through its active form. PLTP can also bind to receptors such as ATP-binding cassette transporter A1 (ABCA1). In addition to its role in lipoprotein metabolism and atherosclerosis, the latest advances came in support of a complex role of PLTP in the regulation of the inflammatory response, both with pro-inflammatory or anti-inflammatory properties. The aim of the present study was to decipher the role of PLTP in joint inflammation and to assess its relevance in the context of RA. PLTP expression was examined by western-blot and by immunochemistry. ABCA1 expression was analyzed by flow cytometry. Lipid transfer activity of PLTP and pro-inflammatory cytokines were measured in sera and synovial fluid (SF) from RA patients and controls (healthy subjects or osteoarthritis patients [OA]). FLS were treated with both lipid-transfer active form and inactive form of recombinant human PLTP. IL-8, IL-6, VEGF and MMP3 produced by FLS were assessed by ELISA, and proliferation by measuring 3H-Thymidine incorporation. RA synovial tissues showed higher PLTP staining than OA and PLTP protein levels were also significantly higher in RA-FLS. In addition, RA, unlike OA patients, displayed elevated levels of PLTP activity in SF, which correlated with pro-inflammatory cytokines. Both lipid-transfer active and inactive forms of PLTP significantly increased the production of cytokines and proliferation of FLS. ABCA1 was expressed on RAFLS and PLTP activated STAT3 pathway. To conclude, PLTP is highly expressed in the joints of RA patients and may directly trigger inflammation and FLS proliferation, independently of its lipid transfer activity. These results suggest a pro-inflammatory role for PLTP in RA. PMID:29565987

  18. HLA-B27-Homodimer-Specific Antibody Modulates the Expansion of Pro-Inflammatory T-Cells in HLA-B27 Transgenic Rats.

    PubMed

    Marroquin Belaunzaran, Osiris; Kleber, Sascha; Schauer, Stefan; Hausmann, Martin; Nicholls, Flora; Van den Broek, Maries; Payeli, Sravan; Ciurea, Adrian; Milling, Simon; Stenner, Frank; Shaw, Jackie; Kollnberger, Simon; Bowness, Paul; Petrausch, Ulf; Renner, Christoph

    2015-01-01

    HLA-B27 is a common genetic risk factor for the development of Spondyloarthritides (SpA). HLA-B27 can misfold to form cell-surface heavy chain homodimers (B272) and induce pro-inflammatory responses that may lead to SpA pathogenesis. The presence of B272 can be detected on leukocytes of HLA-B27+ Ankylosing spondylitis (AS) patients and HLA-B27 transgenic rats. We characterized a novel B272-specific monoclonal antibody to study its therapeutic use in HLA-B27 associated disorders. The monoclonal HD5 antibody was selected from a phage library to target cell-surface B272 homodimers and characterized for affinity, specificity and ligand binding. The immune modulating effect of HD5 was tested in HLA-B27 transgenic rats. Onset and progression of disease profiles were monitored during therapy. Cell-surface B272 and expansion of pro-inflammatory cells from blood, spleen and draining lymph nodes were assessed by flow cytometry. HD5 bound B272 with high specificity and affinity (Kd = 0.32 nM). HD5 blocked cell-surface interaction of B272 with immune regulatory receptors KIR3DL2, LILRB2 and Pirb. In addition, HD5 modulated the production of TNF from CD4+ T-cells by limiting B272 interactions in vitro. In an HLA-B27 transgenic rat model repetitive dosing of HD5 reduced the expansion of pro-inflammatory CD4+ T-cells, and decreased the levels of soluble TNF and number of cell-surface B272 molecules. HD5 predominantly inhibits early TNF production and expansion of pro-inflammatory CD4+ T-cells in HLA-B27 transgenic rats. Monoclonal antibodies targeting cell-surface B272 propose a new concept for the modulation of inflammatory responses in HLA-B27 related disorders.

  19. HLA-B27-Homodimer-Specific Antibody Modulates the Expansion of Pro-Inflammatory T-Cells in HLA-B27 Transgenic Rats

    PubMed Central

    Marroquin Belaunzaran, Osiris; Kleber, Sascha; Schauer, Stefan; Hausmann, Martin; Nicholls, Flora; Van den Broek, Maries; Payeli, Sravan; Ciurea, Adrian; Milling, Simon; Stenner, Frank; Shaw, Jackie; Kollnberger, Simon; Bowness, Paul; Petrausch, Ulf; Renner, Christoph

    2015-01-01

    Objectives HLA-B27 is a common genetic risk factor for the development of Spondyloarthritides (SpA). HLA-B27 can misfold to form cell-surface heavy chain homodimers (B272) and induce pro-inflammatory responses that may lead to SpA pathogenesis. The presence of B272 can be detected on leukocytes of HLA-B27+ Ankylosing spondylitis (AS) patients and HLA-B27 transgenic rats. We characterized a novel B272–specific monoclonal antibody to study its therapeutic use in HLA-B27 associated disorders. Methods The monoclonal HD5 antibody was selected from a phage library to target cell-surface B272 homodimers and characterized for affinity, specificity and ligand binding. The immune modulating effect of HD5 was tested in HLA-B27 transgenic rats. Onset and progression of disease profiles were monitored during therapy. Cell-surface B272 and expansion of pro-inflammatory cells from blood, spleen and draining lymph nodes were assessed by flow cytometry. Results HD5 bound B272 with high specificity and affinity (Kd = 0.32 nM). HD5 blocked cell-surface interaction of B272 with immune regulatory receptors KIR3DL2, LILRB2 and Pirb. In addition, HD5 modulated the production of TNF from CD4+ T-cells by limiting B272 interactions in vitro. In an HLA-B27 transgenic rat model repetitive dosing of HD5 reduced the expansion of pro-inflammatory CD4+ T-cells, and decreased the levels of soluble TNF and number of cell-surface B272 molecules. Conclusion HD5 predominantly inhibits early TNF production and expansion of pro-inflammatory CD4+ T-cells in HLA-B27 transgenic rats. Monoclonal antibodies targeting cell-surface B272 propose a new concept for the modulation of inflammatory responses in HLA-B27 related disorders. PMID:26125554

  20. Vasculitic peripheral neuropathy induced by ischemia-reperfusion in the rat femoral artery involves activation of proinflammatory signaling pathway in the sciatic nerve.

    PubMed

    Chung, Chih-Yang; Chang, Yi-Wei; Huang, Chun-Jen; Wang, Po-Kai; Wan, Hung-Chieh; Lin, Yi-Ying; Kao, Ming-Chang

    2017-08-24

    Ischemia-reperfusion (IR) in the rat femoral artery has been proposed as an experimental model of vasculitic peripheral neuropathy (VPN) which presents neuropathic pain and peripheral nerve injury patterns observed clinically. This study investigates the involvement of the proinflammatory signaling pathway underlying the peripheral mechanisms of VPN. Male Sprague-Dawley rats were allocated to receive either a sham operation or IR. IR was induced by occluding the right femoral artery for 4h followed by reperfusion periods from 0 to 72h. The behavioral parameters were assessed at baseline as well as at days 1, 2 and 3 after reperfusion. The time-course analyses of proinflammatory mediators in the sciatic nerves were also performed on rats of the sham group or IR groups with reperfusion periods of 0, 2, 4, 24 and 72h, respectively. The behavioral data confirmed that this VPN model induced hindpaw mechano-allodynia and heat hyperalgesia as well as impaired hindpaw grip strength. The molecular data revealed that IR in the femoral artery activated the expression of nuclear factor-κB (NF-κB) in the sciatic nerve indicating a neuroinflammatory response. Moreover, IR in the femoral artery increased the expression of proinflammatory cytokines TNF-α and IL-1β in the sciatic nerve. This study elucidated the novel time-course expression profiles of NF-κB and proinflammatory cytokines in VPN induced by IR which may be involved in the development of neuropathic pain. Since NF-κB is a key element during neuroinflammation, strategies targeting the NF-κB signaling pathway may provide therapeutic potential against VPN induced by IR. Copyright © 2017 Elsevier B.V. All rights reserved.

  1. Proinflammatory and anti-inflammatory cytokine balance in gasoline exhaust induced pulmonary injury in mice.

    PubMed

    Sureshkumar, Veerapandian; Paul, Bholanath; Uthirappan, Mani; Pandey, Renu; Sahu, Anand Prakash; Lal, Kewal; Prasad, Arun Kumar; Srivastava, Suresh; Saxena, Ashok; Mathur, Neeraj; Gupta, Yogendra Kumar

    2005-03-01

    Proinflammatory and anti-inflammatory cytokine balance and associated changes in pulmonary bronchoalveolar lavage fluid (BALF) of unleaded gasoline exhaust (GE) exposed mice were investigated. Animals were exposed to GE (1 L/min of GE mixed with 14 L/min of compressed air) using a flow-past, nose-only, dynamic inhalation exposure chamber for different durations (7, 14, and 21 days). The particulate content of the GE was found to be 0.635, +/-0.10 mg PM/m3. Elevated levels of tumor necrosis factor-alpha (TNF-alpha) and interleukin-6 (IL-6) were observed in BALF of GE-exposed mice, but interleukin 1beta(IL-1beta) and the anti-inflammatory cytokine interleukin-10 (IL-10) remained unaffected. GE induced higher activities of alkaline phosphatase (ALP), gamma-glutamyl transferase (gammaGT), and lactate dehydrogenase (LDH) in the BALF, indicating Type II alveolar epithelial cell injury, Clara-cell injury, and general toxicity, respectively. Total protein in the BALF increased after 14 and 21 days of exposure, indicating enhanced alveolar-capillary permeability. However, the difference in the mean was found statistically insignificant in comparison to the compressed air control. Total cell count in the BALF of GE-exposed mice ranged between 0.898 and 0.813x10(6) cells/ml, whereas the compressed air control showed 0.65x10(6) cells/mL. The histopathological changes in GE-exposed lung includes perivascular, and peribronchiolar cuffing of mononuclear cells, migration of polymorphonuclear cells in the alveolar septa, alveolar thickening, and mild alveolar edematous changes indicating inflammation. The shift in pro- and anti-inflammatory cytokine balance and elevation of the pulmonary marker enzymes indicate toxic insult of GE. This study will help in our understanding of the mechanism of pulmonary injury by GE in the light of cytokine profiles, pulmonary marker enzymes, and lung architecture.

  2. Osteoarthritis and rheumatoid arthritis pannus have similar qualitative metabolic characteristics and pro-inflammatory cytokine response.

    PubMed

    Furuzawa-Carballeda, J; Macip-Rodríguez, P M; Cabral, A R

    2008-01-01

    Pannus in osteoarthritis (OA) has only recently been characterized. Little is known, however, regarding the behavior of OA pannus in vitro compared to rheumatoid arthritis (RA) pannus. The purpose of our study was to compare OA with RA pannus. Pannus and synovial tissue co-cultures from 5 patients with OA and 5 patients with RA obtained during arthroplasty were studied. Pannus was defined as the microscopic invasive granulation tissue covering the articular surface. Tissues were cultured for 7 days and stained with Alcian Blue technique. Interleukin-1beta (IL-1beta), IL-8, IL-10, IL-12, tumor necrosis factor-alpha (TNF-alpha), and interferon gamma (IFN-gamma) were also determined in supernatants by ELISA. Cartilage oligomeric matrix protein (COMP), type II collagen, TNF-alpha, IL-10 and Ki-67 expression were also detected by immunohistochemistry. All patients had vascular or fibrous pannus. Synovial proliferation, inflammatory infiltrates and a decrease of extracellular matrix proteins were observed in all tissue samples. Chondrocyte proliferation was lower in OA than RA cartilage. OA synovial tissue expressed lower levels of proteoglycans than RA synoyium. Type II collagen levels were lower in OA than in RA cartilage. Significantly higher levels of IL-1beta were found in the supernatants of RA pannus compared to OA pannus (p<0.05). High but similar levels of TNF-alpha, IL-8 and TIMP-1 were detected in OA and RA pannus supernatants. IL-10, IL-12 and IFN-gamma were undetectable. RA and OA pannus had similar pro-inflammatory and anti-inflammatory cytokine profile expression. OA cartilage, synovial tissue and pannus had lower production of proteoglycans, type II collagen and IL-1beta. It remains to be elucidated why OA pannus invades the cartilage surface but does not cause the marginal erosions typically seen in RA.

  3. Immune consequences of the spontaneous pro-inflammatory status in depressed elderly patients.

    PubMed

    Trzonkowski, Piotr; Myśliwska, Jolanta; Godlewska, Beata; Szmit, Ewa; Łukaszuk, Krzysztof; Wieckiewicz, Joanna; Brydak, Lidia; Machała, Magdalena; Landowski, Jerzy; Myśliwski, Andrzej

    2004-03-01

    The aim of the study was to describe the interrelationship between senescence, depression, and immunity. We assessed 10 elderly patients with depression and 10 age- and sex-matched controls: before, at one and at six month intervals after the anti-influenza vaccination. Levels of TNFalpha, IL6, ACTH, and cortisol, titres of anti-hemagglutinins and anti-neuraminidases, lymphocytes secreting IFNgamma, IL2, IL4, and IL10, cytotoxicity of NK and CD3+ CD8+ IFNgamma+ cells, anti-CMV a