Impact of age and vector construct on striatal and nigral transgene expression

PubMed Central

Polinski, Nicole K; Manfredsson, Fredric P; Benskey, Matthew J; Fischer, D Luke; Kemp, Christopher J; Steece-Collier, Kathy; Sandoval, Ivette M; Paumier, Katrina L; Sortwell, Caryl E

2016-01-01

Therapeutic protein delivery using viral vectors has shown promise in preclinical models of Parkinson’s disease (PD) but clinical trial success remains elusive. This may partially be due to a failure to include advanced age as a covariate despite aging being the primary risk factor for PD. We investigated transgene expression following intracerebral injections of recombinant adeno-associated virus pseudotypes 2/2 (rAAV2/2), 2/5 (rAAV2/5), 2/9 (rAAV2/9), and lentivirus (LV) expressing green fluorescent protein (GFP) in aged versus young adult rats. Both rAAV2/2 and rAAV2/5 yielded lower GFP expression following injection to either the aged substantia nigra or striatum. rAAV2/9-mediated GFP expression was deficient in the aged striatonigral system but displayed identical transgene expression between ages in the nigrostriatal system. Young and aged rats displayed equivalent GFP levels following LV injection to the striatonigral system but LV-delivered GFP was deficient in delivering GFP to the aged nigrostriatal system. Notably, age-related transgene expression deficiencies revealed by protein quantitation were poorly predicted by GFP-immunoreactive cell counts. Further, in situ hybridization for the viral CβA promoter revealed surprisingly limited tropism for astrocytes compared to neurons. Our results demonstrate that aging is a critical covariate to consider when designing gene therapy approaches for PD. PMID:27933309

Disruption of Microtubules Post-Virus Entry Enhances Adeno-Associated Virus Vector Transduction

PubMed Central

Xiao, Ping-Jie; Mitchell, Angela M.; Huang, Lu; Li, Chengwen; Samulski, R. Jude

2016-01-01

Perinuclear retention of viral particles is a poorly understood phenomenon observed during many virus infections. In this study, we investigated whether perinuclear accumulation acts as a barrier to limit recombinant adeno-associated virus (rAAV) transduction. After nocodazole treatment to disrupt microtubules at microtubule-organization center (MT-MTOC) after virus entry, we observed higher rAAV transduction. To elucidate the role of MT-MTOC in rAAV infection and study its underlying mechanisms, we demonstrated that rAAV's perinuclear localization was retained by MT-MTOC with fluorescent analysis, and enhanced rAAV transduction from MT-MTOC disruption was dependent on the rAAV capsid's nuclear import signals. Interestingly, after knocking down RhoA or inhibiting its downstream effectors (ROCK and Actin), MT-MTOC disruption failed to increase rAAV transduction or nuclear entry. These data suggest that enhancement of rAAV transduction is the result of increased trafficking to the nucleus via the RhoA-ROCK-Actin pathway. Ten-fold higher rAAV transduction was also observed by disrupting MT-MTOC in brain, liver, and tumor in vivo. In summary, this study indicates that virus perinuclear accumulation at MT-MTOC is a barrier-limiting parameter for effective rAAV transduction and defines a novel defense mechanism by which host cells restrain viral invasion. PMID:26942476

Sodium Chloride Enhances Recombinant Adeno-Associated Virus Production in a Serum-Free Suspension Manufacturing Platform Using the Herpes Simplex Virus System

PubMed Central

Adamson-Small, Laura; Potter, Mark; Byrne, Barry J.; Clément, Nathalie

2017-01-01

The increase in effective treatments using recombinant adeno-associated viral (rAAV) vectors has underscored the importance of scalable, high-yield manufacturing methods. Previous work from this group reported the use of recombinant herpes simplex virus type 1 (rHSV) vectors to produce rAAV in adherent HEK293 cells, demonstrating the capacity of this system and quality of the product generated. Here we report production and optimization of rAAV using the rHSV system in suspension HEK293 cells (Expi293F) grown in serum and animal component-free medium. Through adjustment of salt concentration in the medium and optimization of infection conditions, titers greater than 1 × 1014 vector genomes per liter (VG/liter) were observed in purified rAAV stocks produced in Expi293F cells. Furthermore, this system allowed for high-titer production of multiple rAAV serotypes (2, 5, and 9) as well as multiple transgenes (green fluorescent protein and acid α-glucosidase). A proportional increase in vector production was observed as this method was scaled, with a final 3-liter shaker flask production yielding an excess of 1 × 1015 VG in crude cell harvests and an average of 3.5 × 1014 total VG of purified rAAV9 material, resulting in greater than 1 × 105 VG/cell. These results support the use of this rHSV-based rAAV production method for large-scale preclinical and clinical vector production. PMID:28117600

Differential effects of two MRI contrast agents on the integrity and distribution of rAAV2 and rAAV5 in the rat striatum

PubMed Central

Osting, Sue; Bennett, Antonette; Power, Shelby; Wackett, Jordan; Hurley, Samuel A; Alexander, Andrew L; Agbandje-Mckena, Mavis; Burger, Corinna

2014-01-01

Intraoperative magnetic resonance imaging (MRI) has been proposed as a method to optimize intracerebral targeting and for tracking infusate distribution in gene therapy trials for nervous system disorders. We thus investigated possible effects of two MRI contrast agents, gadoteridol (Gd) and galbumin (Gab), on the distribution and levels of transgene expression in the rat striatum and their effect on integrity and stability of recombinant adeno-associated virus (rAAV) particles. MRI studies showed that contrast agent distribution did not predict rAAV distribution. However, green fluorescent protein (GFP) immunoreactivity revealed an increase in distribution of rAAV5-GFP, but not rAAV2-GFP, in the presence of Gd when compared with viral vector injected alone. In contrast, Gab increased the distribution of rAAV2-GFP not rAAV5-GFP. These observations pointed to a direct effect of infused contrast agent on the rAAV particles. Negative-stain electron microscopy (EM), DNAase treatment, and differential scanning calorimetry (DSC) were used to monitor rAAV2 and rAAV5 particle integrity and stability following contrast agent incubation. EMs of rAAV2-GFP and rAAV5-GFP particles pretreated with Gd appear morphologically similar to the untreated sample; however, Gab treatment resulted in surface morphology changes and aggregation. A compromise of particle integrity was suggested by sensitivity of the packaged genome to DNAase treatment following Gab incubation but not Gd for both vectors. However, neither agent significantly affected particle stability when analyzed by DSC. An increase in Tm was observed for AAV2 in lactated Ringer’s buffer. These results thus highlight potential interactions between MRI contrast agents and AAV that might affect vector distribution and stability, as well as the stabilizing effect of lactated Ringer’s solution on AAV2. PMID:26015943

Establishment of an AAV Reverse Infection-Based Array

PubMed Central

Wang, Gang; Dong, Zheyue; Shen, Wei; Zheng, Gang; Wu, Xiaobing; Xue, Jinglun; Wang, Yue; Chen, Jinzhong

2010-01-01

Background The development of a convenient high-throughput gene transduction approach is critical for biological screening. Adeno-associated virus (AAV) vectors are broadly used in gene therapy studies, yet their applications in in vitro high-throughput gene transduction are limited. Principal Findings We established an AAV reverse infection (RI)-based method in which cells were transduced by quantified recombinant AAVs (rAAVs) pre-coated onto 96-well plates. The number of pre-coated rAAV particles and number of cells loaded per well, as well as the temperature stability of the rAAVs on the plates, were evaluated. As the first application of this method, six serotypes or hybrid serotypes of rAAVs (AAV1, AAV2, AAV5/5, AAV8, AAV25 m, AAV28 m) were compared for their transduction efficiencies using various cell lines, including BHK21, HEK293, BEAS-2BS, HeLaS3, Huh7, Hepa1-6, and A549. AAV2 and AAV1 displayed high transduction efficiency; thus, they were deemed to be suitable candidate vectors for the RI-based array. We next evaluated the impact of sodium butyrate (NaB) treatment on rAAV vector-mediated reporter gene expression and found it was significantly enhanced, suggesting that our system reflected the biological response of target cells to specific treatments. Conclusions/Significance Our study provides a novel method for establishing a highly efficient gene transduction array that may be developed into a platform for cell biological assays. PMID:20976058

Synergistic cardioprotective effects of rAAV9-CyclinA2 combined with fibrin glue in rats after myocardial infarction.

PubMed

Cao, Wen; Chang, Ya-Fei; Zhao, Ai-Chao; Chen, Bang-Dang; Liu, Fen; Ma, Yi-Tong; Ma, Xiang

2017-08-01

The present study aimed to investigate the protective effects of rAAV9-CyclinA2 combined with fibrin glue (FG) in vivo in rats after myocardial infarction (MI). Ninety male Sprague-Dawley rats were randomized into 6 groups (15 in each group): sham, MI, rAAV9-green fluorescent protein (GFP) + MI, rAAV9-CyclinA2 + MI, FG + MI, and rAAV9-CyclinA2 + FG + MI. Packed virus (5 × 10 11 vg/ml) in 150 µl of normal saline or FG was injected into the infarcted myocardium at five locations in rAAV9-GFP + MI, rAAV9-CyclinA2 + MI, and rAAV9-CyclinA2 + FG + MI groups. The sham, MI, and FG + MI groups were injected with an equal volume of normal saline or FG at the same sites. Five weeks after injection, echocardiography was performed to evaluate the left ventricular function. The expressions of CyclinA2, proliferating cell nuclear antigen (PCNA), and phospho-histone-H3 (H3P), vascular density, and infarct area were assessed by Western blot, immunohistochemistry, immunofluorescence, and Masson staining. As a result, the combination of rAAV9-CyclinA2 and FG increased ejection fraction and fractional shortening compared with FG or rAAV9-CyclinA2 alone. The expression level of CyclinA2 was significantly higher in the rAAV9-CyclinA2 + FG + MI group compared with the rAAV9-CyclinA2 + MI and FG + MI groups (70.1 ± 1.86% vs. 14.74 ± 2.02%, P < 0.01; or vs. 50.13 ± 3.80%; P < 0.01). A higher expression level of PCNA and H3P was found in the rAAV9-CyclinA2 + FG + MI group compared with other groups. Comparing with other experiment groups, collagen deposition and the infarct size significantly decreased in rAAV9-CyclinA2 + Fibrin + MI group. The vascular density was much higher in the rAAV9-CyclinA2 + FG + MI group compared with the rAAV9-CyclinA2 + MI group. We concluded that fibrin glue combined with rAAV9-CyclinA2 was found to be effective in cardiac remodeling and improving myocardial protection.

Viral single-strand DNA induces p53-dependent apoptosis in human embryonic stem cells.

PubMed

Hirsch, Matthew L; Fagan, B Matthew; Dumitru, Raluca; Bower, Jacquelyn J; Yadav, Swati; Porteus, Matthew H; Pevny, Larysa H; Samulski, R Jude

2011-01-01

Human embryonic stem cells (hESCs) are primed for rapid apoptosis following mild forms of genotoxic stress. A natural form of such cellular stress occurs in response to recombinant adeno-associated virus (rAAV) single-strand DNA genomes, which exploit the host DNA damage response for replication and genome persistence. Herein, we discovered a unique DNA damage response induced by rAAV transduction specific to pluripotent hESCs. Within hours following rAAV transduction, host DNA damage signaling was elicited as measured by increased gamma-H2AX, ser15-p53 phosphorylation, and subsequent p53-dependent transcriptional activation. Nucleotide incorporation assays demonstrated that rAAV transduced cells accumulated in early S-phase followed by the induction of apoptosis. This lethal signaling sequalae required p53 in a manner independent of transcriptional induction of Puma, Bax and Bcl-2 and was not evident in cells differentiated towards a neural lineage. Consistent with a lethal DNA damage response induced upon rAAV transduction of hESCs, empty AAV protein capsids demonstrated no toxicity. In contrast, DNA microinjections demonstrated that the minimal AAV origin of replication and, in particular, a 40 nucleotide G-rich tetrad repeat sequence, was sufficient for hESC apoptosis. Our data support a model in which rAAV transduction of hESCs induces a p53-dependent lethal response that is elicited by a telomeric sequence within the AAV origin of replication.

Single residue AAV capsid mutation improves transduction of photoreceptors in the Abca4-/- mouse and bipolar cells in the rd1 mouse and human retina ex vivo.

PubMed

De Silva, Samantha R; Charbel Issa, Peter; Singh, Mandeep S; Lipinski, Daniel M; Barnea-Cramer, Alona O; Walker, Nathan J; Barnard, Alun R; Hankins, Mark W; MacLaren, Robert E

2016-11-01

Gene therapy using adeno-associated viral (AAV) vectors for the treatment of retinal degenerations has shown safety and efficacy in clinical trials. However, very high levels of vector expression may be necessary for the treatment of conditions such as Stargardt disease where a dual vector approach is potentially needed, or in optogenetic strategies for end-stage degeneration in order to achieve maximal light sensitivity. In this study, we assessed two vectors with single capsid mutations, rAAV2/2(Y444F) and rAAV2/8(Y733F) in their ability to transduce retina in the Abca4 -/- and rd1 mouse models of retinal degeneration. We noted significantly increased photoreceptor transduction using rAAV2/8(Y733F) in the Abca4 -/- mouse, in contrast to previous work where vectors tested in this model have shown low levels of photoreceptor transduction. Bipolar cell transduction was achieved following subretinal delivery of both vectors in the rd1 mouse, and via intravitreal delivery of rAAV2/2(Y444F). The successful use of rAAV2/8(Y733F) to target bipolar cells was further validated on human tissue using an ex vivo culture system of retinal explants. Capsid mutant AAV vectors transduce human retinal cells and may be particularly suited to treat retinal degenerations in which high levels of transgene expression are required.

The upstream enhancer elements of the G6PC promoter are critical for optimal G6PC expression in murine glycogen storage disease type Ia.

PubMed

Lee, Young Mok; Pan, Chi-Jiunn; Koeberl, Dwight D; Mansfield, Brian C; Chou, Janice Y

2013-11-01

Glycogen storage disease type-Ia (GSD-Ia) patients deficient in glucose-6-phosphatase-α (G6Pase-α or G6PC) manifest impaired glucose homeostasis characterized by fasting hypoglycemia, growth retardation, hepatomegaly, nephromegaly, hyperlipidemia, hyperuricemia, and lactic acidemia. Two efficacious recombinant adeno-associated virus pseudotype 2/8 (rAAV8) vectors expressing human G6Pase-α have been independently developed. One is a single-stranded vector containing a 2864-bp of the G6PC promoter/enhancer (rAAV8-GPE) and the other is a double-stranded vector containing a shorter 382-bp minimal G6PC promoter/enhancer (rAAV8-miGPE). To identify the best construct, a direct comparison of the rAAV8-GPE and the rAAV8-miGPE vectors was initiated to determine the best vector to take forward into clinical trials. We show that the rAAV8-GPE vector directed significantly higher levels of hepatic G6Pase-α expression, achieved greater reduction in hepatic glycogen accumulation, and led to a better toleration of fasting in GSD-Ia mice than the rAAV8-miGPE vector. Our results indicated that additional control elements in the rAAV8-GPE vector outweigh the gains from the double-stranded rAAV8-miGPE transduction efficiency, and that the rAAV8-GPE vector is the current choice for clinical translation in human GSD-Ia. © 2013.

Modeling correction of severe urea cycle defects in the growing murine liver using a hybrid recombinant adeno-associated virus/piggyBac transposase gene delivery system.

PubMed

Cunningham, Sharon C; Siew, Susan M; Hallwirth, Claus V; Bolitho, Christine; Sasaki, Natsuki; Garg, Gagan; Michael, Iacovos P; Hetherington, Nicola A; Carpenter, Kevin; de Alencastro, Gustavo; Nagy, Andras; Alexander, Ian E

2015-08-01

Liver-targeted gene therapy based on recombinant adeno-associated viral vectors (rAAV) shows promising therapeutic efficacy in animal models and adult-focused clinical trials. This promise, however, is not directly translatable to the growing liver, where high rates of hepatocellular proliferation are accompanied by loss of episomal rAAV genomes and subsequently a loss in therapeutic efficacy. We have developed a hybrid rAAV/piggyBac transposon vector system combining the highly efficient liver-targeting properties of rAAV with stable piggyBac-mediated transposition of the transgene into the hepatocyte genome. Transposition efficiency was first tested using an enhanced green fluorescent protein expression cassette following delivery to newborn wild-type mice, with a 20-fold increase in stably gene-modified hepatocytes observed 4 weeks posttreatment compared to traditional rAAV gene delivery. We next modeled the therapeutic potential of the system in the context of severe urea cycle defects. A single treatment in the perinatal period was sufficient to confer robust and stable phenotype correction in the ornithine transcarbamylase-deficient Spf(ash) mouse and the neonatal lethal argininosuccinate synthetase knockout mouse. Finally, transposon integration patterns were analyzed, revealing 127,386 unique integration sites which conformed to previously published piggyBac data. Using a hybrid rAAV/piggyBac transposon vector system, we achieved stable therapeutic protection in two urea cycle defect mouse models; a clinically conceivable early application of this technology in the management of severe urea cycle defects could be as a bridging therapy while awaiting liver transplantation; further improvement of the system will result from the development of highly human liver-tropic capsids, the use of alternative strategies to achieve transient transposase expression, and engineered refinements in the safety profile of piggyBac transposase-mediated integration. © 2015 by the American Association for the Study of Liver Diseases.

Gene Therapy Models of Alzheimer’s Disease and Other Dementias

PubMed Central

Combs, Benjamin; Kneynsberg, Andrew; Kanaan, Nicholas M.

2016-01-01

Dementias are among the most common neurological disorders, and Alzheimer’s disease (AD) is the most common cause of dementia worldwide. AD remains a looming health crisis despite great efforts to learn the mechanisms surrounding the neuron dysfunction and neurodegeneration that accompanies AD primarily in the medial temporal lobe. In addition to AD, a group of diseases known as frontotemporal dementias (FTDs) are degenerative diseases involving atrophy and degeneration in the frontal and temporal lobe regions. Importantly, AD and a number of FTDs are collectively known as tauopathies due to the abundant accumulation of pathological tau inclusions in the brain. The precise role tau plays in disease pathogenesis remains an area of strong research focus. A critical component to effectively study any human disease is the availability of models that recapitulate key features of the disease. Accordingly, a number of animal models are currently being pursued to fill the current gaps in our knowledge of the causes of dementias and to develop effective therapeutics. Recent developments in gene therapy-based approaches, particularly in recombinant adeno-associated viruses (rAAVs), have provided new tools to study AD and other related neurodegenerative disorders. Additionally, gene therapy approaches have emerged as an intriguing possibility for treating these diseases in humans. This chapter explores the current state of rAAV models of AD and other dementias, discuss recent efforts to improve these models, and describe current and future possibilities in the use of rAAVs and other viruses in treatments of disease. PMID:26611599

Recombinant adeno-associated virus targets passenger gene expression to cones in primate retina

NASA Astrophysics Data System (ADS)

Mancuso, Katherine; Hendrickson, Anita E.; Connor, Thomas B., Jr.; Mauck, Matthew C.; Kinsella, James J.; Hauswirth, William W.; Neitz, Jay; Neitz, Maureen

2007-05-01

Recombinant adeno-associated virus (rAAV) is a promising vector for gene therapy of photoreceptor-based diseases. Previous studies have demonstrated that rAAV serotypes 2 and 5 can transduce both rod and cone photoreceptors in rodents and dogs, and it can target rods, but not cones in primates. Here we report that using a human cone-specific enhancer and promoter to regulate expression of a green fluorescent protein (GFP) reporter gene in an rAAV-5 vector successfully targeted expression of the reporter gene to primate cones, and the time course of GFP expression was able to be monitored in a living animal using the RetCam II digital imaging system.

Correction of the enzymatic and functional deficits in a model of Pompe disease using adeno-associated virus vectors.

PubMed

Fraites, Thomas J; Schleissing, Mary R; Shanely, R Andrew; Walter, Glenn A; Cloutier, Denise A; Zolotukhin, Irene; Pauly, Daniel F; Raben, Nina; Plotz, Paul H; Powers, Scott K; Kessler, Paul D; Byrne, Barry J

2002-05-01

Pompe disease is a lysosomal storage disease caused by the absence of acid alpha-1,4 glucosidase (GAA). The pathophysiology of Pompe disease includes generalized myopathy of both cardiac and skeletal muscle. We sought to use recombinant adeno-associated virus (rAAV) vectors to deliver functional GAA genes in vitro and in vivo. Myotubes and fibroblasts from Pompe patients were transduced in vitro with rAAV2-GAA. At 14 days postinfection, GAA activities were at least fourfold higher than in their respective untransduced controls, with a 10-fold increase observed in GAA-deficient myotubes. BALB/c and Gaa(-/-) mice were also treated with rAAV vectors. Persistent expression of vector-derived human GAA was observed in BALB/c mice up to 6 months after treatment. In Gaa(-/-) mice, intramuscular and intramyocardial delivery of rAAV2-Gaa (carrying the mouse Gaa cDNA) resulted in near-normal enzyme activities. Skeletal muscle contractility was partially restored in the soleus muscles of treated Gaa(-/-) mice, indicating the potential for vector-mediated restoration of both enzymatic activity and muscle function. Furthermore, intramuscular treatment with a recombinant AAV serotype 1 vector (rAAV1-Gaa) led to nearly eight times normal enzymatic activity in Gaa(-/-) mice, with concomitant glycogen clearance as assessed in vitro and by proton magnetic resonance spectroscopy.

Production of recombinant adeno-associated vectors using two bioreactor configurations at different scales

PubMed Central

Negrete, Alejandro; Kotin, Robert M.

2007-01-01

The conventional methods for producing recombinant adeno-associated virus (rAAV) rely on transient transfection of adherent mammalian cells. To gain acceptance and achieve current good manufacturing process (cGMP) compliance, clinical grade rAAV production process should have the following qualities: simplicity, consistency, cost effectiveness, and scalability. Currently, the only viable method for producing rAAV in large-scale, e.g.≥1016 particles per production run, utilizes Baculovirus Expression Vectors (BEVs) and insect cells suspension cultures. The previously described rAAV production in 40 L culture using a stirred tank bioreactor requires special conditions for implementation and operation not available in all laboratories. Alternatives to producing rAAV in stirred-tank bioreactors are single-use, disposable bioreactors, e.g. Wave™. The disposable bags are purchased pre-sterilized thereby eliminating the need for end-user sterilization and also avoiding cleaning steps between production runs thus facilitating the production process. In this study, rAAV production in stirred tank and Wave™ bioreactors was compared. The working volumes were 10 L and 40 L for the stirred tank bioreactors and 5 L and 20 L for the Wave™ bioreactors. Comparable yields of rAAV, ~2e+13 particles per liter of cell culture were obtained in all volumes and configurations. These results demonstrate that producing rAAV in large scale using BEVs is reproducible, scalable, and independent of the bioreactor configuration. Keywords: adeno-associated vectors; large-scale production; stirred tank bioreactor; wave bioreactor; gene therapy. PMID:17606302

Assessment of tropism and effectiveness of new primate-derived hybrid recombinant AAV serotypes in the mouse and primate retina.

PubMed

Charbel Issa, Peter; De Silva, Samantha R; Lipinski, Daniel M; Singh, Mandeep S; Mouravlev, Alexandre; You, Qisheng; Barnard, Alun R; Hankins, Mark W; During, Matthew J; Maclaren, Robert E

2013-01-01

Adeno-associated viral vectors (AAV) have been shown to be safe in the treatment of retinal degenerations in clinical trials. Thus, improving the efficiency of viral gene delivery has become increasingly important to increase the success of clinical trials. In this study, structural domains of different rAAV serotypes isolated from primate brain were combined to create novel hybrid recombinant AAV serotypes, rAAV2/rec2 and rAAV2/rec3. The efficacy of these novel serotypes were assessed in wild type mice and in two models of retinal degeneration (the Abca4(-/-) mouse which is a model for Stargardt disease and in the Pde6b(rd1/rd1) mouse) in vivo, in primate tissue ex-vivo, and in the human-derived SH-SY5Y cell line, using an identical AAV2 expression cassette. We show that these novel hybrid serotypes can transduce retinal tissue in mice and primates efficiently, although no more than AAV2/2 and rAAV2/5 serotypes. Transduction efficiency appeared lower in the Abca4(-/-) mouse compared to wild type with all vectors tested, suggesting an effect of specific retinal diseases on the efficiency of gene delivery. Shuffling of AAV capsid domains may have clinical applications for patients who develop T-cell immune responses following AAV gene therapy, as specific peptide antigen sequences could be substituted using this technique prior to vector re-treatments.

Zinc-finger nuclease-mediated gene correction using single AAV vector transduction and enhancement by Food and Drug Administration-approved drugs

PubMed Central

Ellis, BL; Hirsch, ML; Porter, SN; Samulski, RJ; Porteus, MH

2016-01-01

An emerging strategy for the treatment of monogenic diseases uses genetic engineering to precisely correct the mutation(s) at the genome level. Recent advancements in this technology have demonstrated therapeutic levels of gene correction using a zinc-finger nuclease (ZFN)-induced DNA double-strand break in conjunction with an exogenous DNA donor substrate. This strategy requires efficient nucleic acid delivery and among viral vectors, recombinant adeno-associated virus (rAAV) has demonstrated clinical success without pathology. However, a major limitation of rAAV is the small DNA packaging capacity and to date, the use of rAAV for ZFN gene delivery has yet to be reported. Theoretically, an ideal situation is to deliver both ZFNs and the repair substrate in a single vector to avoid inefficient gene targeting and unwanted mutagenesis, both complications of a rAAV co-transduction strategy. Therefore, a rAAV format was generated in which a single polypeptide encodes the ZFN monomers connected by a ribosome skipping 2A peptide and furin cleavage sequence. On the basis of this arrangement, a DNA repair substrate of 750 nucleotides was also included in this vector. Efficient polypeptide processing to discrete ZFNs is demonstrated, as well as the ability of this single vector format to stimulate efficient gene targeting in a human cell line and mouse model derived fibroblasts. Additionally, we increased rAAV-mediated gene correction up to sixfold using a combination of Food and Drug Administration-approved drugs, which act at the level of AAV vector transduction. Collectively, these experiments demonstrate the ability to deliver ZFNs and a repair substrate by a single AAV vector and offer insights for the optimization of rAAV-mediated gene correction using drug therapy. PMID:22257934

Adeno-associated-virus-mediated transduction of the mammary gland enables sustained production of recombinant proteins in milk

PubMed Central

Wagner, Stefan; Thresher, Rosemary; Bland, Ross; Laible, Götz

2015-01-01

Biopharming for the production of recombinant pharmaceutical proteins in the mammary gland of transgenic animals is an attractive but laborious alternative compared to mammalian cell fermentation. The disadvantage of the lengthy process of genetically modifying an entire animal could be circumvented with somatic transduction of only the mammary epithelium with recombinant, replication-defective viruses. While other viral vectors offer very limited scope for this approach, vectors based on adeno-associated virus (AAV) appear to be ideal candidates because AAV is helper-dependent, does not induce a strong immune response and has no association with disease. Here, we sought to test the suitability of recombinant AAV (rAAV) for biopharming. Using reporter genes, we showed that injected rAAV efficiently transduced mouse mammary cells. When rAAV encoding human myelin basic protein (hMBP) was injected into the mammary glands of mice and rabbits, this resulted in the expression of readily detectable protein levels of up to 0.5 g/L in the milk. Furthermore we demonstrated that production of hMBP persisted over extended periods and that protein expression could be renewed in a subsequent lactation by re-injection of rAAV into a previously injected mouse gland. PMID:26463440

Longevity of rAAV vector and plasmid DNA in blood after intramuscular injection in nonhuman primates: implications for gene doping.

PubMed

Ni, W; Le Guiner, C; Gernoux, G; Penaud-Budloo, M; Moullier, P; Snyder, R O

2011-07-01

Legitimate uses of gene transfer technology can benefit from sensitive detection methods to determine vector biodistribution in pre-clinical studies and in human clinical trials, and similar methods can detect illegitimate gene transfer to provide sports-governing bodies with the ability to maintain fairness. Real-time PCR assays were developed to detect a performance-enhancing transgene (erythropoietin, EPO) and backbone sequences in the presence of endogenous cellular sequences. In addition to developing real-time PCR assays, the steps involved in DNA extraction, storage and transport were investigated. By real-time PCR, the vector transgene is distinguishable from the genomic DNA sequence because of the absence of introns, and the vector backbone can be identified by heterologous gene expression control elements. After performance of the assays was optimized, cynomolgus macaques received a single dose by intramuscular (IM) injection of plasmid DNA, a recombinant adeno-associated viral vector serotype 1 (rAAV1) or a rAAV8 vector expressing cynomolgus macaque EPO. Macaques received a high plasmid dose intended to achieve a significant, but not life-threatening, increase in hematocrit. rAAV vectors were used at low doses to achieve a small increase in hematocrit and to determine the limit of sensitivity for detecting rAAV sequences by single-step PCR. DNA extracted from white blood cells (WBCs) was tested to determine whether WBCs can be collaterally transfected by plasmid or transduced by rAAV vectors in this context, and can be used as a surrogate marker for gene doping. We demonstrate that IM injection of a conventional plasmid and rAAV vectors results in the presence of DNA that can be detected at high levels in blood before rapid elimination, and that rAAV genomes can persist for several months in WBCs.

rAAV Gene Therapy in a Canavan's Disease Mouse Model Reveals Immune Impairments and an Extended Pathology Beyond the Central Nervous System.

PubMed

Ahmed, Seemin Seher; Schattgen, Stefan A; Frakes, Ashley E; Sikoglu, Elif M; Su, Qin; Li, Jia; Hampton, Thomas G; Denninger, Andrew R; Kirschner, Daniel A; Kaspar, Brian; Matalon, Reuben; Gao, Guangping

2016-06-01

Aspartoacylase (AspA) gene mutations cause the pediatric lethal neurodegenerative Canavan disease (CD). There is emerging promise of successful gene therapy for CD using recombinant adeno-associated viruses (rAAVs). Here, we report an intracerebroventricularly delivered AspA gene therapy regime using three serotypes of rAAVs at a 20-fold reduced dose than previously described in AspA(-/-) mice, a bona-fide mouse model of CD. Interestingly, central nervous system (CNS)-restricted therapy prolonged survival over systemic therapy in CD mice but failed to sustain motor functions seen in systemically treated mice. Importantly, we reveal through histological and functional examination of untreated CD mice that AspA deficiency in peripheral tissues causes morphological and functional abnormalities in this heretofore CNS-defined disorder. We demonstrate for the first time that AspA deficiency, possibly through excessive N-acetyl aspartic acid accumulation, elicits both a peripheral and CNS immune response in CD mice. Our data establish a role for peripheral tissues in CD pathology and serve to aid the development of more efficacious and sustained gene therapy for this disease.

Pathology Associated with AAV Mediated Expression of Beta Amyloid or C100 in Adult Mouse Hippocampus and Cerebellum

PubMed Central

Drummond, Eleanor S.; Muhling, Jill; Martins, Ralph N.; Wijaya, Linda K.; Ehlert, Erich M.; Harvey, Alan R.

2013-01-01

Accumulation of beta amyloid (Aβ) in the brain is a primary feature of Alzheimer’s disease (AD) but the exact molecular mechanisms by which Aβ exerts its toxic actions are not yet entirely clear. We documented pathological changes 3 and 6 months after localised injection of recombinant, bi-cistronic adeno-associated viral vectors (rAAV2) expressing human Aβ40-GFP, Aβ42-GFP, C100-GFP or C100V717F-GFP into the hippocampus and cerebellum of 8 week old male mice. Injection of all rAAV2 vectors resulted in wide-spread transduction within the hippocampus and cerebellum, as shown by expression of transgene mRNA and GFP protein. Despite the lack of accumulation of Aβ protein after injection with AAV vectors, injection of rAAV2-Aβ42-GFP and rAAV2- C100V717F-GFP into the hippocampus resulted in significantly increased microgliosis and altered permeability of the blood brain barrier, the latter revealed by high levels of immunoglobulin G (IgG) around the injection site and the presence of IgG positive cells. In comparison, injection of rAAV2-Aβ40-GFP and rAAV2-C100-GFP into the hippocampus resulted in substantially less neuropathology. Injection of rAAV2 vectors into the cerebellum resulted in similar types of pathological changes, but to a lesser degree. The use of viral vectors to express different types of Aβ and C100 is a powerful technique with which to examine the direct in vivo consequences of Aβ expression in different regions of the mature nervous system and will allow experimentation and analysis of pathological AD-like changes in a broader range of species other than mouse. PMID:23516609

Widespread spinal cord transduction by intrathecal injection of rAAV delivers efficacious RNAi therapy for amyotrophic lateral sclerosis.

PubMed

Wang, Hongyan; Yang, Bin; Qiu, Linghua; Yang, Chunxing; Kramer, Joshua; Su, Qin; Guo, Yansu; Brown, Robert H; Gao, Guangping; Xu, Zuoshang

2014-02-01

Amyotrophic lateral sclerosis (ALS) causes motor neuron degeneration and paralysis. No treatment can significantly slow or arrest the disease progression. Mutations in the SOD1 gene cause a subset of familial ALS by a gain of toxicity. In principle, these cases could be treated with RNAi that destroys the mutant mRNA, thereby abolishing the toxic protein. However, no system is available to efficiently deliver the RNAi therapy. Recombinant adenoassociated virus (rAAV) is a promising vehicle due to its long-lasting gene expression and low toxicity. However, ALS afflicts broad areas of the central nervous system (CNS). A lack of practical means to spread rAAV broadly has hindered its application in treatment of ALS. To overcome this barrier, we injected several rAAV serotypes into the cerebrospinal fluid. We found that some rAAV serotypes such as rAAVrh10 and rAAV9 transduced cells throughout the length of the spinal cord following a single intrathecal injection and in the broad forebrain following a single injection into the third ventricle. Furthermore, a single intrathecal injection of rAAVrh10 robustly transduced motor neurons throughout the spinal cord in a non-human primate. These results suggested a therapeutic potential of this vector for ALS. To test this, we injected a rAAVrh10 vector that expressed an artificial miRNA targeting SOD1 into the SOD1G93A mice. This treatment knocked down the mutant SOD1 expression and slowed the disease progression. Our results demonstrate the potential of rAAVs for delivering gene therapy to treat ALS and other diseases that afflict broad areas of the CNS.

Gene Delivery to Adipose Tissue Using Transcriptionally Targeted rAAV8 Vectors

PubMed Central

Uhrig-Schmidt, Silke; Geiger, Matthias; Luippold, Gerd; Birk, Gerald; Mennerich, Detlev; Neubauer, Heike; Grimm, Dirk; Wolfrum, Christian; Kreuz, Sebastian

2014-01-01

In recent years, the increasing prevalence of obesity and obesity-related co-morbidities fostered intensive research in the field of adipose tissue biology. To further unravel molecular mechanisms of adipose tissue function, genetic tools enabling functional studies in vitro and in vivo are essential. While the use of transgenic animals is well established, attempts using viral and non-viral vectors to genetically modify adipocytes in vivo are rare. Therefore, we here characterized recombinant Adeno-associated virus (rAAV) vectors regarding their potency as gene transfer vehicles for adipose tissue. Our results demonstrate that a single dose of systemically applied rAAV8-CMV-eGFP can give rise to remarkable transgene expression in murine adipose tissues. Upon transcriptional targeting of the rAAV8 vector to adipocytes using a 2.2 kb fragment of the murine adiponectin (mAP2.2) promoter, eGFP expression was significantly decreased in off-target tissues while efficient transduction was maintained in subcutaneous and visceral fat depots. Moreover, rAAV8-mAP2.2-mediated expression of perilipin A – a lipid-droplet-associated protein – resulted in significant changes in metabolic parameters only three weeks post vector administration. Taken together, our findings indicate that rAAV vector technology is applicable as a flexible tool to genetically modify adipocytes for functional proof-of-concept studies and the assessment of putative therapeutic targets in vivo. PMID:25551639

Successful gene therapy in older Rpe65-deficient dogs following subretinal injection of an adeno-associated vector expressing RPE65.

PubMed

Annear, Matthew J; Mowat, Freya M; Bartoe, Joshua T; Querubin, Janice; Azam, Selina A; Basche, Mark; Curran, Paul G; Smith, Alexander J; Bainbridge, James W B; Ali, Robin R; Petersen-Jones, Simon M

2013-10-01

Young Rpe65-deficient dogs have been used as a model for human RPE65 Leber congenital amaurosis (RPE65-LCA) in proof-of-concept trials of recombinant adeno-associated virus (rAAV) gene therapy. However, there are relatively few reports of the outcome of rAAV gene therapy in Rpe65-deficient dogs older than 2 years of age. The purpose of this study was to investigate the success of this therapy in older Rpe65-deficient dogs. Thirteen eyes were treated in dogs between 2 and 6 years old. An rAAV2 vector expressing the human RPE65 cDNA driven by the human RPE65 promoter was delivered by subretinal injection. Twelve of the 13 eyes had improved retinal function as assessed by electroretinography, and all showed improvement in vision at low lighting intensities. Histologic examination of five of the eyes was performed but found no correlation between electroretinogram (ERG) rescue and numbers of remaining photoreceptors. We conclude that functional rescue is still possible in older dogs and that the use of older Rpe65-deficient dogs, rather than young Rpe65-deficient dogs that have very little loss of photoreceptors, more accurately models the situation when treating human RPE65-LCA patients.

Hyaluronic acid synthase-2 gene transfer into the joints of Beagles by use of recombinant adeno-associated viral vectors.

PubMed

Kyostio-Moore, Sirkka; Berthelette, Patricia; Cornell, Cathleen Sookdeo; Nambiar, Bindu; Figueiredo, Monica Dias

2018-05-01

OBJECTIVE To evaluate gene transfer of recombinant adeno-associated viral (rAAV) vectors with AAV2 or AAV5 capsid and encoding hyaluronic acid (HA) synthase-2 (HAS2) into joints of healthy dogs. ANIMALS 22 purpose-bred Beagles. PROCEDURES Plasmid expression cassettes encoding canine HAS2 (cHAS2) were assessed in vitro for concentration and molecular size of secreted HA. Thereafter, rAAV2-cHAS2 vectors at 3 concentrations and rAAV5-cHAS2 vectors at 1 concentration were each administered intra-articularly into the left stifle joint of 5 dogs; 2 dogs received PBS solution instead. Synovial fluid HA concentration and serum and synovial fluid titers of neutralizing antibodies against AAV capsids were measured at various points. Dogs were euthanized 28 days after treatment, and cartilage and synovium samples were collected for vector DNA and mRNA quantification and histologic examination. RESULTS Cell transfection with plasmids encoding cHAS2 resulted in an increase in production and secretion of HA in vitro. In vivo, the rAAV5-cHAS2 vector yielded uniform genome transfer and cHAS2 expression in collected synovium and cartilage samples. In contrast, rAAV2-cHAS2 vectors were detected inconsistently in synovium and cartilage samples and failed to produce clear dose-related responses. Histologic examination revealed minimal synovial inflammation in joints injected with rAAV vectors. Neutralizing antibodies against AAV capsids were detected in serum and synovial fluid samples from all vector-treated dogs. CONCLUSIONS AND CLINICAL RELEVANCE rAAV5-mediated transfer of the gene for cHAS2 into healthy joints of dogs by intra-articular injection appeared safe and resulted in vector-derived cHAS2 production by synoviocytes and chondrocytes. Whether this treatment may increase HA production by synoviocytes and chondrocytes in osteoarthritic joints remains to be determined.

Convection Enhanced Delivery of Recombinant Adeno-associated Virus into the Mouse Brain.

PubMed

Nash, Kevin R; Gordon, Marcia N

2016-01-01

Recombinant adeno-associated virus (rAAV) has become an extremely useful tool for the study of gene over expression or knockdown in the central nervous system of experimental animals. One disadvantage of intracranial injections of rAAV vectors into the brain parenchyma has been restricted distribution to relatively small volumes of the brain. Convection enhanced delivery (CED) is a method for delivery of clinically relevant amounts of therapeutic agents to large areas of the brain in a direct intracranial injection procedure. CED uses bulk flow to increase the hydrostatic pressure and thus improve volume distribution. The CED method has shown robust gene transfer and increased distribution within the CNS and can be successfully used for different serotypes of rAAV for increased transduction of the mouse CNS. This chapter details the surgical injection of rAAV by CED into a mouse brain.

Practical utilization of recombinant AAV vector reference standards: focus on vector genomes titration by free ITR qPCR.

PubMed

D'Costa, Susan; Blouin, Veronique; Broucque, Frederic; Penaud-Budloo, Magalie; François, Achille; Perez, Irene C; Le Bec, Christine; Moullier, Philippe; Snyder, Richard O; Ayuso, Eduard

2016-01-01

Clinical trials using recombinant adeno-associated virus (rAAV) vectors have demonstrated efficacy and a good safety profile. Although the field is advancing quickly, vector analytics and harmonization of dosage units are still a limitation for commercialization. AAV reference standard materials (RSMs) can help ensure product safety by controlling the consistency of assays used to characterize rAAV stocks. The most widely utilized unit of vector dosing is based on the encapsidated vector genome. Quantitative polymerase chain reaction (qPCR) is now the most common method to titer vector genomes (vg); however, significant inter- and intralaboratory variations have been documented using this technique. Here, RSMs and rAAV stocks were titered on the basis of an inverted terminal repeats (ITRs) sequence-specific qPCR and we found an artificial increase in vg titers using a widely utilized approach. The PCR error was introduced by using single-cut linearized plasmid as the standard curve. This bias was eliminated using plasmid standards linearized just outside the ITR region on each end to facilitate the melting of the palindromic ITR sequences during PCR. This new "Free-ITR" qPCR delivers vg titers that are consistent with titers obtained with transgene-specific qPCR and could be used to normalize in-house product-specific AAV vector standards and controls to the rAAV RSMs. The free-ITR method, including well-characterized controls, will help to calibrate doses to compare preclinical and clinical data in the field.

Co-overexpression of TGF-β and SOX9 via rAAV gene transfer modulates the metabolic and chondrogenic activities of human bone marrow-derived mesenchymal stem cells.

PubMed

Tao, Ke; Frisch, Janina; Rey-Rico, Ana; Venkatesan, Jagadeesh K; Schmitt, Gertrud; Madry, Henning; Lin, Jianhao; Cucchiarini, Magali

2016-02-01

Articular cartilage has a limited potential for self-healing. Transplantation of genetically modified progenitor cells like bone marrow-derived mesenchymal stem cells (MSCs) is an attractive strategy to improve the intrinsic repair capacities of damaged articular cartilage. In this study, we examined the potential benefits of co-overexpressing the pleiotropic transformation growth factor beta (TGF-β) with the cartilage-specific transcription factor SOX9 via gene transfer with recombinant adeno-associated virus (rAAV) vectors upon the biological activities of human MSCs (hMSCs). Freshly isolated hMSCs were transduced over time with separate rAAV vectors carrying either TGF-β or sox9 in chondrogenically-induced aggregate cultures to evaluate the efficacy and duration of transgene expression and to monitor the effects of rAAV-mediated genetic modification upon the cellular activities (proliferation, matrix synthesis) and chondrogenic differentiation potency compared with control conditions (lacZ treatment, sequential transductions). Significant, prolonged TGF-β/sox9 co-overexpression was achieved in chondrogenically-induced hMSCs upon co-transduction via rAAV for up to 21 days, leading to enhanced proliferative, biosynthetic, and chondrogenic activities relative to control treatments, especially when co-applying the candidate vectors at the highest vector doses tested. Optimal co-administration of TGF-β with sox9 also advantageously reduced hypertrophic differentiation of the cells in the conditions applied here. The present findings demonstrate the possibility of modifying MSCs by combined therapeutic gene transfer as potent future strategies for implantation in clinically relevant animal models of cartilage defects in vivo.

Induction of immunity to antigens expressed by recombinant adeno-associated virus depends on the route of administration.

PubMed

Brockstedt, D G; Podsakoff, G M; Fong, L; Kurtzman, G; Mueller-Ruchholtz, W; Engleman, E G

1999-07-01

Recombinant adeno-associated virus (rAAV) is a replication-defective parvovirus which is being explored as a vector for gene therapy because of its broad host range, excellent safety profile, and durable transgene expression in infected hosts. rAAV has also been reported by several groups to induce little or no immune response to its encoded transgene products. In this study we examined the immunogenicity of rAAV by studying the immune response of C57BL/6 mice to a single dose of rAAV-encoding ovalbumin (AAV-Ova) administered by a variety of routes. Mice injected with AAV-Ova intraperitoneally (ip), intravenously, or subcutaneously developed potent ovalbumin-specific cytotoxic T lymphocytes (CTL) as well as anti-ovalbumin antibodies and antibodies to AAV. In contrast, mice injected with AAV-Ova intramuscularly developed a humoral response to the virus and the transgene but minimal ovalbumin-specific CTLs. The induced CTL response after ip administration of AAV-Ova protected mice against a subsequent tumor challenge with an ovalbumin-transfected B16 melanoma cell line. Studies of the mechanism by which AAV-Ova induces CTL confirmed that the virus delivers the transgene product into the classical MHC class I pathway of antigen processing. Mice that previously had been exposed to rAAV vectors failed to develop ovalbumin-specific CTL following administration of AAV-Ova. Analysis of these mice revealed the presence of circulating anti-AAV antibodies that blocked rAAV transduction in vitro and inhibited CTL induction in vivo. These results suggest a possible role for rAAV in the immunotherapy of malignancies and viral infections, although induced antibody responses to AAV may limit its ability to be administered for repeated vaccinations. Copyright 1999 Academic Press.

Efficacy of a Combined Intracerebral and Systemic Gene Delivery Approach for the Treatment of a Severe Lysosomal Storage Disorder

PubMed Central

Spampanato, Carmine; De Leonibus, Elvira; Dama, Paola; Gargiulo, Annagiusi; Fraldi, Alessandro; Sorrentino, Nicolina Cristina; Russo, Fabio; Nusco, Edoardo; Auricchio, Alberto; Surace, Enrico M; Ballabio, Andrea

2011-01-01

Multiple sulfatase deficiency (MSD), a severe autosomal recessive disease is caused by mutations in the sulfatase modifying factor 1 gene (Sumf1). We have previously shown that in the Sumf1 knockout mouse model (Sumf1−/−) sulfatase activities are completely absent and, similarly to MSD patients, this mouse model displays growth retardation and early mortality. The severity of the phenotype makes MSD unsuitable to be treated by enzyme replacement or bone marrow transplantation, hence the importance of testing the efficacy of novel treatment strategies. Here we show that recombinant adeno-associated virus serotype 9 (rAAV9) vector injected into the cerebral ventricles of neonatal mice resulted in efficient and widespread transduction of the brain parenchyma. In addition, we compared a combined, intracerebral ventricles and systemic, administration of an rAAV9 vector encoding SUMF1 gene to the single administrations—either directly in brain, or systemic alone —in MSD mice. The combined treatment resulted in the global activation of sulfatases, near-complete clearance of glycosaminoglycans (GAGs) and decrease of inflammation in both the central nervous system (CNS) and visceral organs. Furthermore, behavioral abilities were improved by the combined treatment. These results underscore that the “combined” mode of rAAV9 vector administration is an efficient option for the treatment of severe whole-body disorders. PMID:21326216

New cell engineering approaches for cartilage regenerative medicine.

PubMed

Cucchiarini, Magali

2017-01-01

Articular cartilage injuries have an inadequate aptitude to reproduce the original structure and functions of this highly specialized tissue. As most of the currently available options also do not lead to the restoration of the original hyaline cartilage, novel treatments are critically needed to address this global problems in the clinics. Gene therapy combined with tissue engineering approaches offers effective tools capable of enhancing cartilage repair experimentally, especially those based on the controlled delivery of the highly effective, clinically adapted recombinant adeno-associated viral (rAAV) vectors. This work presents an overview of the most recent evidence showing the benefits of using rAAV vectors and biocompatible materials for the elaboration of adapted treatments against cartilage injuries.

Characteristics of Minimally Oversized Adeno-Associated Virus Vectors Encoding Human Factor VIII Generated Using Producer Cell Lines and Triple Transfection.

PubMed

Nambiar, Bindu; Cornell Sookdeo, Cathleen; Berthelette, Patricia; Jackson, Robert; Piraino, Susan; Burnham, Brenda; Nass, Shelley; Souza, David; O'Riordan, Catherine R; Vincent, Karen A; Cheng, Seng H; Armentano, Donna; Kyostio-Moore, Sirkka

2017-02-01

Several ongoing clinical studies are evaluating recombinant adeno-associated virus (rAAV) vectors as gene delivery vehicles for a variety of diseases. However, the production of vectors with genomes >4.7 kb is challenging, with vector preparations frequently containing truncated genomes. To determine whether the generation of oversized rAAVs can be improved using a producer cell-line (PCL) process, HeLaS3-cell lines harboring either a 5.1 or 5.4 kb rAAV vector genome encoding codon-optimized cDNA for human B-domain deleted Factor VIII (FVIII) were isolated. High-producing "masterwells" (MWs), defined as producing >50,000 vg/cell, were identified for each oversized vector. These MWs provided stable vector production for >20 passages. The quality and potency of the AAVrh8R/FVIII-5.1 and AAVrh8R/FVIII-5.4 vectors generated by the PCL method were then compared to those prepared via transient transfection (TXN). Southern and dot blot analyses demonstrated that both production methods resulted in packaging of heterogeneously sized genomes. However, the PCL-derived rAAV vector preparations contained some genomes >4.7 kb, whereas the majority of genomes generated by the TXN method were ≤4.7 kb. The PCL process reduced packaging of non-vector DNA for both the AAVrh8R/FVIII-5.1 and the AAVrh8R/FVIII-5.4 kb vector preparations. Furthermore, more DNA-containing viral particles were obtained for the AAVrh8R/FVIII-5.1 vector. In a mouse model of hemophilia A, animals administered a PCL-derived rAAV vector exhibited twofold higher plasma FVIII activity and increased levels of vector genomes in the liver than mice treated with vector produced via TXN did. Hence, the quality of oversized vectors prepared using the PCL method is greater than that of vectors generated using the TXN process, and importantly this improvement translates to enhanced performance in vivo.

Molecular design for recombinant adeno-associated virus (rAAV) vector production.

PubMed

Aponte-Ubillus, Juan Jose; Barajas, Daniel; Peltier, Joseph; Bardliving, Cameron; Shamlou, Parviz; Gold, Daniel

2018-02-01

Recombinant adeno-associated virus (rAAV) vectors are increasingly popular tools for gene therapy applications. Their non-pathogenic status, low inflammatory potential, availability of viral serotypes with different tissue tropisms, and prospective long-lasting gene expression are important attributes that make rAAVs safe and efficient therapeutic options. Over the last three decades, several groups have engineered recombinant AAV-producing platforms, yielding high titers of transducing vector particles. Current specific productivity yields from different platforms range from 10 3 to 10 5 vector genomes (vg) per cell, and there is an ongoing effort to improve vector yields in order to satisfy high product demands required for clinical trials and future commercialization.Crucial aspects of vector production include the molecular design of the rAAV-producing host cell line along with the design of AAV genes, promoters, and regulatory elements. Appropriately, configuring and balancing the expression of these elements not only contributes toward high productivity, it also improves process robustness and product quality. In this mini-review, the rational design of rAAV-producing expression systems is discussed, with special attention to molecular strategies that contribute to high-yielding, biomanufacturing-amenable rAAV production processes. Details on molecular optimization from four rAAV expression systems are covered: adenovirus, herpesvirus, and baculovirus complementation systems, as well as a recently explored yeast expression system.

The recombinant adeno-associated virus vector (rAAV2)-mediated apolipoprotein B mRNA-specific hammerhead ribozyme: a self-complementary AAV2 vector improves the gene expression

PubMed Central

Zhong, Shumei; Sun, Shihua; Teng, Ba-Bie

2004-01-01

Background In humans, overproduction of apolipoprotein B (apoB) is positively associated with premature coronary artery diseases. To reduce the levels of apoB mRNA, we have designed an apoB mRNA-specific hammerhead ribozyme targeted at nucleotide sequences GUA6679 (RB15) mediated by adenovirus, which efficiently cleaves and decreases apoB mRNA by 80% in mouse liver and attenuates the hyperlipidemic condition. In the current study, we used an adeno-associated virus vector, serotype 2 (AAV2) and a self-complementary AAV2 vector (scAAV2) to demonstrate the effect of long-term tissue-specific gene expression of RB15 on the regulation apoB mRNA in vivo. Methods We constructed a hammerhead ribozyme RB15 driven by a liver-specific transthyretin (TTR) promoter using an AAV2 vector (rAAV2-TTR-RB15). HepG2 cells and hyperlipidemic mice deficient in both the low density lipoprotein receptor and the apoB mRNA editing enzyme genes (LDLR-/-Apobec1-/-; LDb) were transduced with rAAV2-TTR-RB15 and a control vector rAAV-TTR-RB15-mutant (inactive ribozyme). The effects of ribozyme RB15 on apoB metabolism and atherosclerosis development were determined in LDb mice at 5-month after transduction. A self-complementary AAV2 vector expressing ribozyme RB15 (scAAV2-TTR-RB15) was also engineered and used to transduce HepG2 cells. Studies were designed to compare the gene expression efficiency between rAAV2-TTR-RB15 and scAAV2-TTR-RB15. Results The effect of ribozyme RB15 RNA on reducing apoB mRNA levels in HepG2 cells was observed only on day-7 after rAAV2-TTR-RB15 transduction. And, at 5-month after rAAV2-TTR-RB15 treatment, the apoB mRNA levels in LDb mice were significantly decreased by 43%, compared to LDb mice treated with control vector rAAV2-TTR-RB15-mutant. Moreover, both the rAAV2-TTR-RB15 viral DNA and ribozyme RB15 RNA were still detectable in mice livers at 5-month after treatment. However, this rAAV2-TTR-RB15 vector mediated a prolonged but low level of ribozyme RB15 gene expression in the mice livers, which did not produce the therapeutic effects on alteration the lipid levels or the inhibition of atherosclerosis development. In contrast, the ribozyme RB15 RNA mediated by scAAV2-TTR-RB15 vector was expressed immediately at day-1 after transduction in HepG2 cells. The apoB mRNA levels were decreased 47% (p = 0.001), compared to the control vector scAAV2-TTR-RB15-mutant. Conclusion This study provided evidence that the rAAV2 single-strand vector mediated a prolonged but not efficient transduction in mouse liver. However, the scAAV2 double-strand vector mediated a rapid and efficient gene expression in liver cells. This strategy using scAAV2 vectors represents a better approach to express small molecules such as ribozyme. PMID:15193153

Rational plasmid design and bioprocess optimization to enhance recombinant adeno-associated virus (AAV) productivity in mammalian cells.

PubMed

Emmerling, Verena V; Pegel, Antje; Milian, Ernest G; Venereo-Sanchez, Alina; Kunz, Marion; Wegele, Jessica; Kamen, Amine A; Kochanek, Stefan; Hoerer, Markus

2016-02-01

Viral vectors used for gene and oncolytic therapy belong to the most promising biological products for future therapeutics. Clinical success of recombinant adeno-associated virus (rAAV) based therapies raises considerable demand for viral vectors, which cannot be met by current manufacturing strategies. Addressing existing bottlenecks, we improved a plasmid system termed rep/cap split packaging and designed a minimal plasmid encoding adenoviral helper function. Plasmid modifications led to a 12-fold increase in rAAV vector titers compared to the widely used pDG standard system. Evaluation of different production approaches revealed superiority of processes based on anchorage- and serum-dependent HEK293T cells, exhibiting about 15-fold higher specific and volumetric productivity compared to well-established suspension cells cultivated in serum-free medium. As for most other viral vectors, classical stirred-tank bioreactor production is thus still not capable of providing drug product of sufficient amount. We show that manufacturing strategies employing classical surface-providing culture systems can be successfully transferred to the new fully-controlled, single-use bioreactor system Integrity(TM) iCELLis(TM) . In summary, we demonstrate substantial bioprocess optimizations leading to more efficient and scalable production processes suggesting a promising way for flexible large-scale rAAV manufacturing. Copyright © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Methods of treating Parkinson's disease using viral vectors

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

Bankiewicz, Krystof; Cunningham, Janet

Methods of delivering viral vectors, particularly recombinant adeno-associated virus (rAAV) virions, to the central nervous system (CNS) using convection enhanced delivery (CED) are provided. The rAAV virions include a nucleic acid sequence encoding a therapeutic polypeptide. The methods can be used for treating CNS disorders such as for treating Parkinson's Disease.

[Immune response induced by HIV DNA vaccine combined with recombinant adeno-associated virus].

PubMed

Liu, Yan-zheng; Zhou, Ling; Wang, Qi; Ye, Shu-qing; Li, Hong-xia; Zeng, Yi

2004-09-01

HIV-1 DNA vaccine and recombinant adeno-associated virus (rAAV) expressing gagV3 gene of HIV-1 subtype B were constructed and BALB/c mice were immunized by vaccination regimen consisting of consecutive priming with DNA vaccine and boosting with rAAV vaccine; the CTL and antibody response were detected and compared with those induced by DNA vaccine or rAAV vaccine separately. HIV-1 subtype B gagV3 gene was inserted into the polyclonal site of plasmid pCI-neo, DNA vaccine pCI-gagV3 was thereby constructed; pCI-gagV3 was transfected into p815 cells, G-418-resistant cells were obtained through screening transfected cells with G418, the expression of HIV-1 antigen in G-418-resistant cells was detected by EIA; BALB/c mice were immunized with pCI-gagV3 and the immune response was tested; BALB/c mouse immunized with pCI-gagV3 and combined with rAAV expressing the same gagV3 genes were tested for antibody level in sera by EIA method and cytotoxicity response by LDH method. pCI-gagV3 could express HIV-1 gene in p815 cells; pCI-gagV3 could induce HIV-1 specific humoral and cell-mediated immune response in BALB/c mice. The HIV-1 specific antibody level was 1/20; when the ratio of effector cells: target cells was 50:1, the average specific cytotoxicity was 41.7%; there was no evident increase in the antibody level induced by pCI-gagV3 combined with rAAV, but there was increase in CTL response, the average specific cytotoxicity was 61.3% when effector cells: target cells ratio was 50:1. HIV-1 specific cytotoxicity in BALB/c mice can be increased by immunization of BALB/c mice with DNA vaccine combined with rAAV vaccine.

Expressing Transgenes That Exceed the Packaging Capacity of Adeno-Associated Virus Capsids

PubMed Central

Chamberlain, Kyle; Riyad, Jalish Mahmud; Weber, Thomas

2016-01-01

Recombinant adeno-associated virus vectors (rAAV) are being explored as gene delivery vehicles for the treatment of various inherited and acquired disorders. rAAVs are attractive vectors for several reasons: wild-type AAVs are nonpathogenic, and rAAVs can trigger long-term transgene expression even in the absence of genome integration—at least in postmitotic tissues. Moreover, rAAVs have a low immunogenic profile, and the various AAV serotypes and variants display broad but distinct tropisms. One limitation of rAAVs is that their genome-packaging capacity is only ∼5 kb. For most applications this is not of major concern because the median human protein size is 375 amino acids. Excluding the ITRs, for a protein of typical length, this allows the incorporation of ∼3.5 kb of DNA for the promoter, polyadenylation sequence, and other regulatory elements into a single AAV vector. Nonetheless, for certain diseases the packaging limit of AAV does not allow the delivery of a full-length therapeutic protein by a single AAV vector. Hence, approaches to overcome this limitation have become an important area of research for AAV gene therapy. Among the most promising approaches to overcome the limitation imposed by the packaging capacity of AAV is the use of dual-vector approaches, whereby a transgene is split across two separate AAV vectors. Coinfection of a cell with these two rAAVs will then—through a variety of mechanisms—result in the transcription of an assembled mRNA that could not be encoded by a single AAV vector because of the DNA packaging limits of AAV. The main purpose of this review is to assess the current literature with respect to dual-AAV-vector design, to highlight the effectiveness of the different methodologies and to briefly discuss future areas of research to improve the efficiency of dual-AAV-vector transduction. PMID:26757051

Recombinant AAV-directed gene therapy for type I glycogen storage diseases

PubMed Central

Chou, JY; Mansfield, BC

2011-01-01

Introduction Glycogen storage disease (GSD) type Ia and Ib are disorders of impaired glucose homeostasis affecting the liver and kidney. GSD-Ib also affects neutrophils. Current dietary therapies cannot prevent long-term complications. In animal studies, recombinant adeno-associated virus (rAAV) vector-mediated gene therapy can correct or minimize multiple aspects of the disorders, offering hope for human gene therapy. Areas covered A summary of recent progress in rAAV-mediated gene therapy for GSD-I; strategies to improve rAAV-mediated gene delivery, transduction efficiency and immune avoidance; and vector refinements that improve expression. Expert opinion rAAV-mediated gene delivery to the liver can restore glucose homeostasis in preclinical models of GSD-I, but some long-term complications of the liver and kidney remain. Gene therapy for GSD-Ib is less advanced than for GSD-Ia and only transient correction of myeloid dysfunction has been achieved. A question remains whether a single rAAV vector can meet the expression efficiency and tropism required to treat all aspects of GSD-I, or if a multi-prong approach is needed. An understanding of the strengths and weaknesses of rAAV vectors in the context of strategies to achieve efficient transduction of the liver, kidney, and hematopoietic stem cells is required for treating GSD-I. PMID:21504389

Detection of exogenous gene doping of IGF-I by a real-time quantitative PCR assay.

PubMed

Zhang, Jin-Ju; Xu, Jing-Feng; Shen, Yong-Wei; Ma, Shi-Jiao; Zhang, Ting-Ting; Meng, Qing-Lin; Lan, Wen-Jun; Zhang, Chun; Liu, Xiao-Mei

2017-07-01

Gene doping can be easily concealed since its product is similar to endogenous protein, making its effective detection very challenging. In this study, we selected insulin-like growth factor I (IGF-I) exogenous gene for gene doping detection. First, the synthetic IGF-I gene was subcloned to recombinant adeno-associated virus (rAAV) plasmid to produce recombinant rAAV2/IGF-I-GFP vectors. Second, in an animal model, rAAV2/IGF-I-GFP vectors were injected into the thigh muscle tissue of mice, and then muscle and blood specimens were sampled at different time points for total DNA isolation. Finally, real-time quantitative PCR was employed to detect the exogenous gene doping of IGF-I. In view of the characteristics of endogenous IGF-I gene sequences, a TaqMan probe was designed at the junction of exons 2 and 3 of IGF-I gene to distinguish it from the exogenous IGF-I gene. In addition, an internal reference control plasmid and its probe were used in PCR to rule out false-positive results through comparison of their threshold cycle (Ct) values. Thus, an accurate exogenous IGF-I gene detection approach was developed in this study. © 2016 International Union of Biochemistry and Molecular Biology, Inc.

Transgene expression in target-defined neuron populations mediated by retrograde infection with adeno-associated viral vectors.

PubMed

Rothermel, Markus; Brunert, Daniela; Zabawa, Christine; Díaz-Quesada, Marta; Wachowiak, Matt

2013-09-18

Tools enabling the manipulation of well defined neuronal subpopulations are critical for probing complex neuronal networks. Cre recombinase (Cre) mouse driver lines in combination with the Cre-dependent expression of proteins using viral vectors--in particular, recombinant adeno-associated viral vectors (rAAVs)--have emerged as a widely used platform for achieving transgene expression in specified neural populations. However, the ability of rAAVs to further specify neuronal subsets on the basis of their anatomical connectivity has been reported as limited or inconsistent. Here, we systematically tested a variety of widely used neurotropic rAAVs for their ability to mediate retrograde gene transduction in the mouse brain. We tested pseudotyped rAAVs of several common serotypes (rAAV 2/1, 2/5, and 2/9) as well as constructs both with and without Cre-dependent expression switches. Many of the rAAVs tested--in particular, though not exclusively, Cre-dependent vectors--showed a robust capacity for retrograde infection and transgene expression. Retrograde expression was successful over distances as large as 6 mm and in multiple neuron types, including olfactory projection neurons, neocortical pyramidal cells projecting to distinct targets, and corticofugal and modulatory projection neurons. Retrograde infection using transgenes such as ChR2 allowed for optical control or optically assisted electrophysiological identification of neurons defined genetically as well as by their projection target. These results establish a widely accessible tool for achieving combinatorial specificity and stable, long-term transgene expression to isolate precisely defined neuron populations in the intact animal.

Transgene Expression in Target-Defined Neuron Populations Mediated by Retrograde Infection with Adeno-Associated Viral Vectors

PubMed Central

Rothermel, Markus; Brunert, Daniela; Zabawa, Christine; Díaz-Quesada, Marta

2013-01-01

Tools enabling the manipulation of well defined neuronal subpopulations are critical for probing complex neuronal networks. Cre recombinase (Cre) mouse driver lines in combination with the Cre-dependent expression of proteins using viral vectors—in particular, recombinant adeno-associated viral vectors (rAAVs)—have emerged as a widely used platform for achieving transgene expression in specified neural populations. However, the ability of rAAVs to further specify neuronal subsets on the basis of their anatomical connectivity has been reported as limited or inconsistent. Here, we systematically tested a variety of widely used neurotropic rAAVs for their ability to mediate retrograde gene transduction in the mouse brain. We tested pseudotyped rAAVs of several common serotypes (rAAV 2/1, 2/5, and 2/9) as well as constructs both with and without Cre-dependent expression switches. Many of the rAAVs tested—in particular, though not exclusively, Cre-dependent vectors—showed a robust capacity for retrograde infection and transgene expression. Retrograde expression was successful over distances as large as 6 mm and in multiple neuron types, including olfactory projection neurons, neocortical pyramidal cells projecting to distinct targets, and corticofugal and modulatory projection neurons. Retrograde infection using transgenes such as ChR2 allowed for optical control or optically assisted electrophysiological identification of neurons defined genetically as well as by their projection target. These results establish a widely accessible tool for achieving combinatorial specificity and stable, long-term transgene expression to isolate precisely defined neuron populations in the intact animal. PMID:24048849

Recombinant adeno-associated virus serotype 6 (rAAV2/6)-mediated gene transfer to nociceptive neurons through different routes of delivery

PubMed Central

Towne, Chris; Pertin, Marie; Beggah, Ahmed T; Aebischer, Patrick; Decosterd, Isabelle

2009-01-01

Background Gene transfer to nociceptive neurons of the dorsal root ganglia (DRG) is a promising approach to dissect mechanisms of pain in rodents and is a potential therapeutic strategy for the treatment of persistent pain disorders such as neuropathic pain. A number of studies have demonstrated transduction of DRG neurons using herpes simplex virus, adenovirus and more recently, adeno-associated virus (AAV). Recombinant AAV are currently the gene transfer vehicles of choice for the nervous system and have several advantages over other vectors, including stable and safe gene expression. We have explored the capacity of recombinant AAV serotype 6 (rAAV2/6) to deliver genes to DRG neurons and characterized the transduction of nociceptors through five different routes of administration in mice. Results Direct injection of rAAV2/6 expressing green fluorescent protein (eGFP) into the sciatic nerve resulted in transduction of up to 30% eGFP-positive cells of L4 DRG neurons in a dose dependant manner. More than 90% of transduced cells were small and medium sized neurons (< 700 μm2), predominantly colocalized with markers of nociceptive neurons, and had eGFP-positive central terminal fibers in the superficial lamina of the spinal cord dorsal horn. The efficiency and profile of transduction was independent of mouse genetic background. Intrathecal administration of rAAV2/6 gave the highest level of transduction (≈ 60%) and had a similar size profile and colocalization with nociceptive neurons. Intrathecal administration also transduced DRG neurons at cervical and thoracic levels and resulted in comparable levels of transduction in a mouse model for neuropathic pain. Subcutaneous and intramuscular delivery resulted in low levels of transduction in the L4 DRG. Likewise, delivery via tail vein injection resulted in relatively few eGFP-positive cells within the DRG, however, this transduction was observed at all vertebral levels and corresponded to large non-nociceptive cell types. Conclusion We have found that rAAV2/6 is an efficient vector to deliver transgenes to nociceptive neurons in mice. Furthermore, the characterization of the transduction profile may facilitate gene transfer studies to dissect mechanisms behind neuropathic pain. PMID:19737386

Elevated expression of activins promotes muscle wasting and cachexia.

PubMed

Chen, Justin L; Walton, Kelly L; Winbanks, Catherine E; Murphy, Kate T; Thomson, Rachel E; Makanji, Yogeshwar; Qian, Hongwei; Lynch, Gordon S; Harrison, Craig A; Gregorevic, Paul

2014-04-01

In models of cancer cachexia, inhibiting type IIB activin receptors (ActRIIBs) reverse muscle wasting and prolongs survival, even with continued tumor growth. ActRIIB mediates signaling of numerous TGF-β proteins; of these, we demonstrate that activins are the most potent negative regulators of muscle mass. To determine whether activin signaling in the absence of tumor-derived factors induces cachexia, we used recombinant serotype 6 adeno-associated virus (rAAV6) vectors to increase circulating activin A levels in C57BL/6 mice. While mice injected with control vector gained ~10% of their starting body mass (3.8±0.4 g) over 10 wk, mice injected with increasing doses of rAAV6:activin A exhibited weight loss in a dose-dependent manner, to a maximum of -12.4% (-4.2±1.1 g). These reductions in body mass in rAAV6:activin-injected mice correlated inversely with elevated serum activin A levels (7- to 24-fold). Mechanistically, we show that activin A reduces muscle mass and function by stimulating the ActRIIB pathway, leading to deleterious consequences, including increased transcription of atrophy-related ubiquitin ligases, decreased Akt/mTOR-mediated protein synthesis, and a profibrotic response. Critically, we demonstrate that the muscle wasting and fibrosis that ensues in response to excessive activin levels is fully reversible. These findings highlight the therapeutic potential of targeting activins in cachexia.

Promyelocytic Leukemia Protein Is a Cell-Intrinsic Factor Inhibiting Parvovirus DNA Replication

PubMed Central

Mitchell, Angela M.; Hirsch, Matthew L.; Li, Chengwen

2014-01-01

Tripartite motif proteins are important viral restriction factors and affect processes ranging from uncoating to transcription to immune signaling. Specifically, the promyelocytic leukemia protein (TRIM19; also called PML) is a viral restriction factor inhibiting processes from uncoating to transcription to cell survival. Here we investigated PML's effect on adeno-associated virus (AAV), a parvovirus used for gene delivery. Although dependovirus (AAV) and autonomous parvovirus (minute virus of mice) replication centers can colocalize with PML, PML's functional effect on parvoviruses is unknown. Using PML knockout mice, we determined that PML knockout enhances recombinant AAV2 (rAAV2) transduction at a range of vector doses in both male and female mice. In fact, male and female PML knockout mice exhibited up to 56-fold and 28-fold increases in transduction, respectively. PML inhibited several rAAV serotypes, suggesting a conserved mechanism, and organ specificity correlated with PML expression. Mechanistically, PML inhibited rAAV second-strand DNA synthesis, precluding inhibition of self-complementary rAAV, and did not affect the prior steps in transduction. Furthermore, we confirmed the effect of human PML on rAAV transduction through small interfering RNA (siRNA)-mediated knockdown in HuH7 cells and determined that the highest level of inhibition was due to effects of PML isoform II (PMLII). Overexpression of PMLII resulted in inhibition of second-strand synthesis, vector production, and genome replication. Moreover, wild-type AAV2 production and infectivity were also inhibited by PMLII, demonstrating a PML interaction with wild-type AAV. These data have important implications for AAV-mediated gene therapy. Additionally, PMLII inhibition of AAV second-strand synthesis and replication, which are processes necessary for all parvoviruses, suggests implications for replication of other parvoviruses. PMID:24198403

Promyelocytic leukemia protein is a cell-intrinsic factor inhibiting parvovirus DNA replication.

PubMed

Mitchell, Angela M; Hirsch, Matthew L; Li, Chengwen; Samulski, R Jude

2014-01-01

Tripartite motif proteins are important viral restriction factors and affect processes ranging from uncoating to transcription to immune signaling. Specifically, the promyelocytic leukemia protein (TRIM19; also called PML) is a viral restriction factor inhibiting processes from uncoating to transcription to cell survival. Here we investigated PML's effect on adeno-associated virus (AAV), a parvovirus used for gene delivery. Although dependovirus (AAV) and autonomous parvovirus (minute virus of mice) replication centers can colocalize with PML, PML's functional effect on parvoviruses is unknown. Using PML knockout mice, we determined that PML knockout enhances recombinant AAV2 (rAAV2) transduction at a range of vector doses in both male and female mice. In fact, male and female PML knockout mice exhibited up to 56-fold and 28-fold increases in transduction, respectively. PML inhibited several rAAV serotypes, suggesting a conserved mechanism, and organ specificity correlated with PML expression. Mechanistically, PML inhibited rAAV second-strand DNA synthesis, precluding inhibition of self-complementary rAAV, and did not affect the prior steps in transduction. Furthermore, we confirmed the effect of human PML on rAAV transduction through small interfering RNA (siRNA)-mediated knockdown in HuH7 cells and determined that the highest level of inhibition was due to effects of PML isoform II (PMLII). Overexpression of PMLII resulted in inhibition of second-strand synthesis, vector production, and genome replication. Moreover, wild-type AAV2 production and infectivity were also inhibited by PMLII, demonstrating a PML interaction with wild-type AAV. These data have important implications for AAV-mediated gene therapy. Additionally, PMLII inhibition of AAV second-strand synthesis and replication, which are processes necessary for all parvoviruses, suggests implications for replication of other parvoviruses.

[Construction of rAAV2-GPIIb/IIIa vector and test of its expression and function in vitro].

PubMed

Wang, Kai; Peng, Jian-Qiang; Chen, Fang-Ping; Wu, Xiao-Bin

2006-04-01

This study was aimed to explore the possibility of rAAV2 vector-mediating gene therapy for Glanzmann' s thrombasthenia. The rAAV2-GPIIb/IIIa vector was constructed. The GPIIb/IIIa gene expression in mammal cell were examined by different methods, such as: detection of mRNA expression in BHK-21 cells after 24 hours of infection (MOI = 1 x 10(5) v.g/cell) was performed by RT-PCR; the relation between MOI and quantity of GPII6/IIIa gene expression was detected by FACS after 48 hours of infection; GPIIb/IIIa protein expression in BHK-21 cells after 48 hours of infection (MOI = 10(5) v x g/cell) was assayed by Western blot, GPIIb/IIIa protein expression on cell surface was detected by immunofluorescence, and the biological function of expressing product was determined by PAC-1 conjunct experiments. The results showed that GPIIb/IIIa gene expression in mRNA level could be detected in BHK-21 cells after 24 hours of infection at MOI = 1 x 10(5) v x g/cell and the GPIIb/IIIa gene expression in protein level could be detected in BHK-21 cells after 48 hours of infection at MOI = 1 x 10(5) v x g/cell. In certain range, quantity of GPIIb/IIIa gene expression increased with MOI, but overdose of MOI decreased quantity of GPIIb/IIIa gene expression. Activated product of GPIIb/IIIa gene expression could combined with PAC-I, and possesed normal biological function. In conclusion, rAAV2 vactor can effectively mediate GPIIb and GPIIIa gene expressing in mammal cells, and the products of these genes exhibit biological function. This result may provide a basis for application of rAAV2 vector in Glanzmann's thrombasthenia gene therapy in furture.

Long-term outcomes of gene therapy for the treatment of Leber's hereditary optic neuropathy.

PubMed

Yang, Shuo; Ma, Si-Qi; Wan, Xing; He, Heng; Pei, Han; Zhao, Min-Jian; Chen, Chen; Wang, Dao-Wen; Dong, Xiao-Yan; Yuan, Jia-Jia; Li, Bin

2016-08-01

Leber's hereditary optic neuropathy (LHON) is a disease that leads to blindness. Gene therapy has been investigated with some success, and could lead to important advancements in treating LHON. This was a prospective, open-label trial involving 9 LHON patients at Tongji Hospital, Wuhan, China, from August 2011 to December 2015. The purpose of this study was to evaluate the long-term outcomes of gene therapy for LHON. Nine LHON patients voluntarily received an intravitreal injection of rAAV2-ND4. Systemic examinations and visual function tests were performed during the 36-month follow-up period to determine the safety and efficacy of this gene therapy. Based on successful experiments in an animal model of LHON, 1 subject also received an rAAV2-ND4 injection in the second eye 12months after gene therapy was administered in the first eye. Recovery of visual acuity was defined as the primary outcome of this study. Changes in the visual field, visual evoked potential (VEP), optical coherence tomography findings, liver and kidney function, and antibodies against AAV2 were defined as secondary endpoints. Eight patients (Patients 2-9) received unilateral gene therapy and visual function improvement was observed in both treated eyes (Patients 4, 6, 7, and 8) and untreated eyes (Patients 2, 3, 4, 6 and 8). Visual regression fluctuations, defined as changes in visual acuity greater than or equal to 0.3 logMAR, were observed in Patients 2 and 9. Age at disease onset, disease duration, and the amount of remaining optic nerve fibers did not have a significant effect on the visual function improvement. The visual field and pattern reversal VEP also improved. The patient (Patient 1) who received gene therapy in both eyes had improved visual acuity in the injected eye after the first treatment. Unfortunately, visual acuity in this eye decreased 3months after he received gene therapy in the second eye. Animal experiments suggested that ND4 expression remains stable in the contralateral eye after intravitreal injections. No serious safety problem was observed in the 3-year follow-up of the 9 participants enrolled in this virus-based gene therapy. Meanwhile, our results support the use of intravitreal rAAV2-ND4 as an aggressive maneuver in our clinical trial. Further study in additional patients and in these 9 subjects is needed to better understand the effects of rAAV2-ND4 gene therapy on LHON and to increase the applications of this technique. Copyright © 2016 The Ohio State University Wexner Medical Center. Published by Elsevier B.V. All rights reserved.

Catalytic immunoglobulin gene delivery in a mouse model of Alzheimer's disease: prophylactic and therapeutic applications.

PubMed

Kou, Jinghong; Yang, Junling; Lim, Jeong-Eun; Pattanayak, Abhinandan; Song, Min; Planque, Stephanie; Paul, Sudhir; Fukuchi, Ken-Ichiro

2015-02-01

Accumulation of amyloid beta-peptide (Aβ) in the brain is hypothesized to be a causal event leading to dementia in Alzheimer's disease (AD). Aβ vaccination removes Aβ deposits from the brain. Aβ immunotherapy, however, may cause T cell- and/or Fc-receptor-mediated brain inflammation and relocate parenchymal Aβ deposits to blood vessels leading to cerebral hemorrhages. Because catalytic antibodies do not form stable immune complexes and Aβ fragments produced by catalytic antibodies are less likely to form aggregates, Aβ-specific catalytic antibodies may have safer therapeutic profiles than reversibly-binding anti-Aβ antibodies. Additionally, catalytic antibodies may remove Aβ more efficiently than binding antibodies because a single catalytic antibody can hydrolyze thousands of Aβ molecules. We previously isolated Aβ-specific catalytic antibody, IgVL5D3, with strong Aβ-hydrolyzing activity. Here, we evaluated the prophylactic and therapeutic efficacy of brain-targeted IgVL5D3 gene delivery via recombinant adeno-associated virus serotype 9 (rAAV9) in an AD mouse model. One single injection of rAAV9-IgVL5D3 into the right ventricle of AD model mice yielded widespread, high expression of IgVL5D3 in the unilateral hemisphere. IgVL5D3 expression was readily detectable in the contralateral hemisphere but to a much lesser extent. IgVL5D3 expression was also confirmed in the cerebrospinal fluid. Prophylactic and therapeutic injection of rAAV9-IgVL5D3 reduced Aβ load in the ipsilateral hippocampus of AD model mice. No evidence of hemorrhages, increased vascular amyloid deposits, increased proinflammatory cytokines, or infiltrating T-cells in the brains was found in the experimental animals. AAV9-mediated anti-Aβ catalytic antibody brain delivery can be prophylactic and therapeutic options for AD.

Modular adeno-associated virus (rAAV) vectors used for cellular virus-directed enzyme prodrug therapy

PubMed Central

Hagen, Sven; Baumann, Tobias; Wagner, Hanna J.; Morath, Volker; Kaufmann, Beate; Fischer, Adrian; Bergmann, Stefan; Schindler, Patrick; Arndt, Katja M.; Müller, Kristian M.

2014-01-01

The pre-clinical and clinical development of viral vehicles for gene transfer increased in recent years, and a recombinant adeno-associated virus (rAAV) drug took center stage upon approval in the European Union. However, lack of standardization, inefficient purification methods and complicated retargeting limit general usability. We address these obstacles by fusing rAAV-2 capsids with two modular targeting molecules (DARPin or Affibody) specific for a cancer cell-surface marker (EGFR) while simultaneously including an affinity tag (His-tag) in a surface-exposed loop. Equipping these particles with genes coding for prodrug converting enzymes (thymidine kinase or cytosine deaminase) we demonstrate tumor marker specific transduction and prodrug-dependent apoptosis of cancer cells. Coding terminal and loop modifications in one gene enabled specific and scalable purification. Our genetic parts for viral production adhere to a standardized cloning strategy facilitating rapid prototyping of virus directed enzyme prodrug therapy (VDEPT). PMID:24457557

Striatal Pleiotrophin Overexpression Provides Functional and Morphological Neuroprotection in the 6-Hydroxydopamine Model

PubMed Central

Gombash, Sara E; Lipton, Jack W; Collier, Timothy J; Madhavan, Lalitha; Steece-Collier, Kathy; Cole-Strauss, Allyson; Terpstra, Brian T; Spieles-Engemann, Anne L; Daley, Brian F; Wohlgenant, Susan L; Thompson, Valerie B; Manfredsson, Fredric P; Mandel, Ronald J; Sortwell, Caryl E

2012-01-01

Neurotrophic factors are integrally involved in the development of the nigrostriatal system and in combination with gene therapy, possess great therapeutic potential for Parkinson's disease (PD). Pleiotrophin (PTN) is involved in the development, maintenance, and repair of the nigrostriatal dopamine (DA) system. The present study examined the ability of striatal PTN overexpression, delivered via psueudotyped recombinant adeno-associated virus type 2/1 (rAAV2/1), to provide neuroprotection and functional restoration from 6-hydroxydopamine (6-OHDA). Striatal PTN overexpression led to significant neuroprotection of tyrosine hydroxylase immunoreactive (THir) neurons in the substantia nigra pars compacta (SNpc) and THir neurite density in the striatum, with long-term PTN overexpression producing recovery from 6-OHDA-induced deficits in contralateral forelimb use. Transduced striatal PTN levels were increased threefold compared to adult striatal PTN expression and approximated peak endogenous developmental levels (P1). rAAV2/1 vector exclusively transduced neurons within the striatum and SNpc with approximately half the total striatal volume routinely transduced using our injection parameters. Our results indicate that striatal PTN overexpression can provide neuroprotection for the 6-OHDA lesioned nigrostriatal system based upon morphological and functional measures and that striatal PTN levels similar in magnitude to those expressed in the striatum during development are sufficient to provide neuroprotection from Parkinsonian insult. PMID:22008908

Long-term correction of very long-chain acyl-coA dehydrogenase deficiency in mice using AAV9 gene therapy.

PubMed

Keeler, Allison M; Conlon, Thomas; Walter, Glenn; Zeng, Huadong; Shaffer, Scott A; Dungtao, Fu; Erger, Kirsten; Cossette, Travis; Tang, Qiushi; Mueller, Christian; Flotte, Terence R

2012-06-01

Very long-chain acyl-coA dehydrogenase (VLCAD) is the rate-limiting step in mitochondrial fatty acid oxidation. VLCAD-deficient mice and patients clinical symptoms stem from not only an energy deficiency but also long-chain metabolite accumulations. VLCAD-deficient mice were treated systemically with 1 × 10(12) vector genomes of recombinant adeno-associated virus 9 (rAAV9)-VLCAD. Biochemical correction was observed in vector-treated mice beginning 2 weeks postinjection, as characterized by a significant drop in long-chain fatty acyl accumulates in whole blood after an overnight fast. Changes persisted through the termination point around 20 weeks postinjection. Magnetic resonance spectroscopy (MRS) and tandem mass spectrometry (MS/MS) revealed normalization of intramuscular lipids in treated animals. Correction was not observed in liver tissue extracts, but cardiac muscle extracts showed significant reduction of long-chain metabolites. Disease-specific phenotypes were characterized, including thermoregulation and maintenance of euglycemia after a fasting cold challenge. Internal body temperatures of untreated VLCAD(-/-) mice dropped below 20 °C and the mice became lethargic, requiring euthanasia. In contrast, all rAAV9-treated VLCAD(-/-) mice and the wild-type controls maintained body temperatures. rAAV9-treated VLCAD(-/-) mice maintained euglycemia, whereas untreated VLCAD(-/-) mice suffered hypoglycemia following a fasting cold challenge. These promising results suggest rAAV9 gene therapy as a potential treatment for VLCAD deficiency in humans.

Lack of Humoral Immune Response to the Tetracycline (Tet) Activator in Rats Injected Intracranially with Tet-off rAAV Vectors

PubMed Central

Han, Ye; Chang, Qin A.; Virag, Tamas; West, Neva C.; George, David; Castro, Maria G.; Bohn, Martha C.

2010-01-01

The ability to safely control transgene expression from viral vectors is a long-term goal in the gene therapy field. We have previously reported tight regulation of GFP expression in rat brain using a self-regulating tet-off rAAV vector. The immune responses against tet regulatory elements observed by other groups in nonhuman primates after intramuscular injection of tet-on encoding vectors raise concerns about the clinical value of tet-regulated vectors. However, previous studies have not examined immune responses following injection of AAV vectors into brain. Therefore, rat striatum was injected with tet-off rAAV harboring a therapeutic gene for Parkinson's disease, either hAADC or hGDNF. The expression of each gene was tightly controlled by the tet-off regulatory system. Using an ELISA developed with purified GST-tTA protein, no detectable immunogenicity against tTA was observed in sera of rats that received an intrastriatal injection of either vector. In contrast, sera from rats intradermally injected with an adenovirus containing either tTA or rtTA, as positive controls, had readily detectable antibodies. These observations suggest that tet-off rAAV vectors do not elicit an immune response when injected into rat brain and that these may offer safer vectors for Parkinson's disease than vectors with constitutive expression. PMID:20164859

Adeno-associated Virus Serotype 9 – Driven Expression of BAG3 Improves Left Ventricular Function in Murine Hearts with Left Ventricular Dysfunction Secondary to a Myocardial Infarction

PubMed Central

Knezevic, Tijana; Myers, Valerie D.; Su, Feifei; Wang, JuFang; Song, Jianliang; Zhang, Xue-Qian; Gao, Erhe; Gao, Guofeng; Muniswamy, Madesh; Gupta, Manish K.; Gordon, Jennifer; Weiner, Kristen N.; Rabinowitz, Joseph; Ramsey, Frederick V.; Tilley, Douglas G.; Khalili, Kamel; Cheung, Joseph Y.; Feldman, Arthur M.

2016-01-01

Objectives The present study was undertaken to test the hypothesis that gene delivery of BCL2-Associated Athanogene 3 (BAG3) to the heart of mice with left ventricular dysfunction secondary to a myocardial infarction could enhance cardiac performance. Background BAG3 is a 575 amino acid protein that has pleotropic functions in the cell including pro-autophagy and anti-apoptosis. Mutations in BAG3 have been associated with both skeletal muscle dysfunction and familial dilated cardiomyopathy and BAG3 levels are diminished in non-familial heart failure. Methods Eight-week-old C57/BL6 mice underwent ligation of the left coronary artery (MI) or sham surgery (Sham). Eight weeks later, mice in both groups were randomly assigned to receive either a retro-orbital injection of rAAV9-BAG3 (MI-BAG3 or Sham-BAG3) or rAAV9-GFP (MI-GFP or Sham GFP). Mice were sacrificed at 3 weeks post-injection and myocytes were isolated from the left ventricle. Results MI-BAG3 mice demonstrated a significantly (p < 0.0001) higher left ventricular ejection fraction (LVEF) 9 days after rAAV9-BAG3 injection with further improvement in LVEF, fractional shortening and stroke volume at 3 weeks post-injection without changes in LV mass or LV volume. Injection of rAAV9-BAG3 had no effect on LVEF in Sham mice. The salutary benefits of rAAV9-BAG3 were also observed in myocytes isolated from MI hearts including improved cell shortening (p<0.05), increased systolic [Ca2+]i, increased [Ca2+]i transient amplitudes and increased maximal ICa amplitude. Implications The results suggest that BAG3 gene therapy may provide a novel therapeutic option for the treatment of heart failure. PMID:28164169

Adeno-associated Virus Serotype 9 - Driven Expression of BAG3 Improves Left Ventricular Function in Murine Hearts with Left Ventricular Dysfunction Secondary to a Myocardial Infarction.

PubMed

Knezevic, Tijana; Myers, Valerie D; Su, Feifei; Wang, JuFang; Song, Jianliang; Zhang, Xue-Qian; Gao, Erhe; Gao, Guofeng; Muniswamy, Madesh; Gupta, Manish K; Gordon, Jennifer; Weiner, Kristen N; Rabinowitz, Joseph; Ramsey, Frederick V; Tilley, Douglas G; Khalili, Kamel; Cheung, Joseph Y; Feldman, Arthur M

2016-12-01

The present study was undertaken to test the hypothesis that gene delivery of BCL2-Associated Athanogene 3 (BAG3) to the heart of mice with left ventricular dysfunction secondary to a myocardial infarction could enhance cardiac performance. BAG3 is a 575 amino acid protein that has pleotropic functions in the cell including pro-autophagy and anti-apoptosis. Mutations in BAG3 have been associated with both skeletal muscle dysfunction and familial dilated cardiomyopathy and BAG3 levels are diminished in non-familial heart failure. Eight-week-old C57/BL6 mice underwent ligation of the left coronary artery (MI) or sham surgery (Sham). Eight weeks later, mice in both groups were randomly assigned to receive either a retro-orbital injection of rAAV9-BAG3 (MI-BAG3 or Sham-BAG3) or rAAV9-GFP (MI-GFP or Sham GFP). Mice were sacrificed at 3 weeks post-injection and myocytes were isolated from the left ventricle. MI-BAG3 mice demonstrated a significantly (p < 0.0001) higher left ventricular ejection fraction (LVEF) 9 days after rAAV9-BAG3 injection with further improvement in LVEF, fractional shortening and stroke volume at 3 weeks post-injection without changes in LV mass or LV volume. Injection of rAAV9-BAG3 had no effect on LVEF in Sham mice. The salutary benefits of rAAV9-BAG3 were also observed in myocytes isolated from MI hearts including improved cell shortening (p<0.05), increased systolic [Ca 2+ ] i , increased [Ca 2+ ] i transient amplitudes and increased maximal I Ca amplitude. The results suggest that BAG3 gene therapy may provide a novel therapeutic option for the treatment of heart failure.

Transduction of skeletal muscles with common reporter genes can promote muscle fiber degeneration and inflammation.

PubMed

Winbanks, Catherine E; Beyer, Claudia; Qian, Hongwei; Gregorevic, Paul

2012-01-01

Recombinant adeno-associated viral vectors (rAAV vectors) are promising tools for delivering transgenes to skeletal muscle, in order to study the mechanisms that control the muscle phenotype, and to ameliorate diseases that perturb muscle homeostasis. Many studies have employed rAAV vectors carrying reporter genes encoding for β-galactosidase (β-gal), human placental alkaline phosphatase (hPLAP), and green fluorescent protein (GFP) as experimental controls when studying the effects of manipulating other genes. However, it is not clear to what extent these reporter genes can influence signaling and gene expression signatures in skeletal muscle, which may confound the interpretation of results obtained in experimentally manipulated muscles. Herein, we report a strong pro-inflammatory effect of expressing reporter genes in skeletal muscle. Specifically, we show that the administration of rAAV6:hPLAP vectors to the hind limb muscles of mice is associated with dose- and time-dependent macrophage recruitment, and skeletal muscle damage. Dose-dependent expression of hPLAP also led to marked activity of established pro-inflammatory IL-6/Stat3, TNFα, IKKβ and JNK signaling in lysates obtained from homogenized muscles. These effects were independent of promoter type, as expression cassettes featuring hPLAP under the control of constitutive CMV and muscle-specific CK6 promoters both drove cellular responses when matched for vector dose. Importantly, the administration of rAAV6:GFP vectors did not induce muscle damage or inflammation except at the highest doses we examined, and administration of a transgene-null vector (rAAV6:MCS) did not cause damage or inflammation at any of the doses tested, demonstrating that GFP-expressing, or transgene-null vectors may be more suitable as experimental controls. The studies highlight the importance of considering the potential effects of reporter genes when designing experiments that examine gene manipulation in vivo.

Generation of insulin-producing human mesenchymal stem cells using recombinant adeno-associated virus.

PubMed

Kim, Jeong Hwan; Park, Si-Nae; Suh, Hwal

2007-02-28

The purpose of current experiment is the generation of insulin-producing human mesenchymal stem cells as therapeutic source for the cure of type 1 diabetes. Type 1 diabetes is generally caused by insulin deficiency accompanied by the destruction of islet beta-cells. In various trials for the treatment of type 1 diabetes, cell-based gene therapy using stem cells is considered as one of the most useful candidate for the treatment. In this experiment, human mesenchymal stem cells were transduced with AAV which is containing furin-cleavable human preproinsulin gene to generate insulin-producing cells as surrogate beta-cells for the type 1 diabetes therapy. In the rAAV production procedure, rAAV was generated by transfection of AD293 cells. Human mesenchymal stems cells were transduced using rAAV with a various multiplicity of infection. Transduction of recombinant AAV was also tested using beta-galactosidse expression. Cell viability was determined by using MTT assay to evaluate the toxicity of the transduction procedure. Expression and production of Insulin were tested using reverse transcriptase-polymerase chain reaction and immunocytochemistry. Secretion of human insulin and C-peptide from the cells was assayed using enzyme-linked immunosorbent assay. Production of insulin and C-peptide from the test group represented a higher increase compared to the control group. In this study, we examined generation of insulin-producing cells from mesenchymal stem cells by genetic engineering for diabetes therapy. This work might be valuable to the field of tissue engineering for diabetes treatment.

Efficient CRISPR-rAAV engineering of endogenous genes to study protein function by allele-specific RNAi.

PubMed

Kaulich, Manuel; Lee, Yeon J; Lönn, Peter; Springer, Aaron D; Meade, Bryan R; Dowdy, Steven F

2015-04-20

Gene knockout strategies, RNAi and rescue experiments are all employed to study mammalian gene function. However, the disadvantages of these approaches include: loss of function adaptation, reduced viability and gene overexpression that rarely matches endogenous levels. Here, we developed an endogenous gene knockdown/rescue strategy that combines RNAi selectivity with a highly efficient CRISPR directed recombinant Adeno-Associated Virus (rAAV) mediated gene targeting approach to introduce allele-specific mutations plus an allele-selective siRNA Sensitive (siSN) site that allows for studying gene mutations while maintaining endogenous expression and regulation of the gene of interest. CRISPR/Cas9 plus rAAV targeted gene-replacement and introduction of allele-specific RNAi sensitivity mutations in the CDK2 and CDK1 genes resulted in a >85% site-specific recombination of Neo-resistant clones versus ∼8% for rAAV alone. RNAi knockdown of wild type (WT) Cdk2 with siWT in heterozygotic knockin cells resulted in the mutant Cdk2 phenotype cell cycle arrest, whereas allele specific knockdown of mutant CDK2 with siSN resulted in a wild type phenotype. Together, these observations demonstrate the ability of CRISPR plus rAAV to efficiently recombine a genomic locus and tag it with a selective siRNA sequence that allows for allele-selective phenotypic assays of the gene of interest while it remains expressed and regulated under endogenous control mechanisms. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Adeno-Associated Virus Type 2 Wild-Type and Vector-Mediated Genomic Integration Profiles of Human Diploid Fibroblasts Analyzed by Third-Generation PacBio DNA Sequencing

PubMed Central

Hüser, Daniela; Gogol-Döring, Andreas; Chen, Wei

2014-01-01

ABSTRACT Genome-wide analysis of adeno-associated virus (AAV) type 2 integration in HeLa cells has shown that wild-type AAV integrates at numerous genomic sites, including AAVS1 on chromosome 19q13.42. Multiple GAGY/C repeats, resembling consensus AAV Rep-binding sites are preferred, whereas rep-deficient AAV vectors (rAAV) regularly show a random integration profile. This study is the first study to analyze wild-type AAV integration in diploid human fibroblasts. Applying high-throughput third-generation PacBio-based DNA sequencing, integration profiles of wild-type AAV and rAAV are compared side by side. Bioinformatic analysis reveals that both wild-type AAV and rAAV prefer open chromatin regions. Although genomic features of AAV integration largely reproduce previous findings, the pattern of integration hot spots differs from that described in HeLa cells before. DNase-Seq data for human fibroblasts and for HeLa cells reveal variant chromatin accessibility at preferred AAV integration hot spots that correlates with variant hot spot preferences. DNase-Seq patterns of these sites in human tissues, including liver, muscle, heart, brain, skin, and embryonic stem cells further underline variant chromatin accessibility. In summary, AAV integration is dependent on cell-type-specific, variant chromatin accessibility leading to random integration profiles for rAAV, whereas wild-type AAV integration sites cluster near GAGY/C repeats. IMPORTANCE Adeno-associated virus type 2 (AAV) is assumed to establish latency by chromosomal integration of its DNA. This is the first genome-wide analysis of wild-type AAV2 integration in diploid human cells and the first to compare wild-type to recombinant AAV vector integration side by side under identical experimental conditions. Major determinants of wild-type AAV integration represent open chromatin regions with accessible consensus AAV Rep-binding sites. The variant chromatin accessibility of different human tissues or cell types will have impact on vector targeting to be considered during gene therapy. PMID:25031342

Therapeutic Benefits and Adverse Effects of Combined Proangiogenic Gene Therapy in Mouse Critical Leg Ischemia.

PubMed

Lebas, Benoît; Galley, Julien; Renaud-Gabardos, Edith; Pujol, Françoise; Lenfant, Françoise; Garmy-Susini, Barbara; Chaufour, Xavier; Prats, Anne-Catherine

2017-04-01

Critical leg ischemia (CLI) represents the ultimate stage of peripheral arterial disease. Despite current surgery advances, patients with CLI have limited therapeutic options. Therapeutic angiogenesis thus appears as a powerful approach, aiming to stimulate vessel formation by angiogenic molecules administration. In this context, combined gene therapy has been proved to be the most efficient. The present study aims to compare, in a preclinical mouse model, the therapeutic benefit of a combination of 2 angiogenic factors fibroblast growth factor 2 (FGF2) and Cyr61 using plasmid and viral vectors, able to generate short- or long-term transgene expression in the leg, respectively. Two therapeutic genes, FGF2 and Cyr61, were introduced into internal ribosome entry site-based expression vectors (FGFiCyr) allowing co-expression of the 2 transgenes. The proangiogenic plasmid pC-FGFiCyr was assessed by intramuscular administration followed by electrotransfer into ischemic legs. To generate long-term transgene expression, the FGFiCyr bicistronic cassette was introduced into an adenoassociated virus-derived vector (rAAV). The rAAV treatment was performed either before or immediately after surgery. Therapeutic effects were analyzed by laser Doppler imaging, clinical score, and angiography. The plasmid pC-FGFiCyr improved revascularization, reperfusion, and clinical score. Surprisingly, when AAV-FGFiCyr was injected 21 or 28 days before surgery, the proangiogenic rAAV was drastically deleterious on all measured parameters. In contrast, when administrated shortly after surgery, AAV-FGFiCyr generated therapeutic benefits, with a significantly better clinical score than after treatment with the plasmid. Therapeutic effects of the angiogenic combination FGF2-Cyr61 is observed with short-term transgene expression, but the treatment is significantly more efficient when a long-term expression viral vector is used. However, the rAAV-FGFiCyr generated therapeutic benefit only when injected in an ischemic leg, whereas the same dose of rAAV exhibited deleterious effects when administrated to healthy animals. These data may contribute to the understanding of the moderate success of proangiogenic treatments in CLI gene therapy clinical assays. Copyright © 2016 Elsevier Inc. All rights reserved.

Recent tissue engineering-based advances for effective rAAV-mediated gene transfer in the musculoskeletal system.

PubMed

Rey-Rico, Ana; Cucchiarini, Magali

2016-04-01

Musculoskeletal tissues are diverse and significantly different in their ability to repair upon injury. Current treatments often fail to reproduce the natural functions of the native tissue, leading to an imperfect healing. Gene therapy might improve the repair of tissues by providing a temporarily and spatially defined expression of the therapeutic gene(s) at the site of the injury. Several gene transfer vehicles have been developed to modify various human cells and tissues from musculoskeletal system among which the non-pathogenic, effective, and relatively safe recombinant adeno-associated viral (rAAV) vectors that have emerged as the preferred gene delivery system to treat human disorders. Adapting tissue engineering platforms to gene transfer approaches mediated by rAAV vectors is an attractive tool to circumvent both the limitations of the current therapeutic options to promote an effective healing of the tissue and the natural obstacles from these clinically adapted vectors to achieve an efficient and durable gene expression of the therapeutic sequences within the lesions.

Effective genetic modification and differentiation of hMSCs upon controlled release of rAAV vectors using alginate/poloxamer composite systems.

PubMed

Díaz-Rodríguez, P; Rey-Rico, A; Madry, H; Landin, M; Cucchiarini, M

2015-12-30

Viral vectors are common tools in gene therapy to deliver foreign therapeutic sequences in a specific target population via their natural cellular entry mechanisms. Incorporating such vectors in implantable systems may provide strong alternatives to conventional gene transfer procedures. The goal of the present study was to generate different hydrogel structures based on alginate (AlgPH155) and poloxamer PF127 as new systems to encapsulate and release recombinant adeno-associated viral (rAAV) vectors. Inclusion of rAAV in such polymeric capsules revealed an influence of the hydrogel composition and crosslinking temperature upon the vector release profiles, with alginate (AlgPH155) structures showing the fastest release profiles early on while over time vector release was more effective from AlgPH155+PF127 [H] capsules crosslinked at a high temperature (50°C). Systems prepared at room temperature (AlgPH155+PF127 [C]) allowed instead to achieve a more controlled release profile. When tested for their ability to target human mesenchymal stem cells, the different systems led to high transduction efficiencies over time and to gene expression levels in the range of those achieved upon direct vector application, especially when using AlgPH155+PF127 [H]. No detrimental effects were reported on either cell viability or on the potential for chondrogenic differentiation. Inclusion of PF127 in the capsules was also capable of delaying undesirable hypertrophic cell differentiation. These findings are of promising value for the further development of viral vector controlled release strategies. Copyright © 2015 Elsevier B.V. All rights reserved.

Chronic Cardiac-Targeted RNA Interference for the Treatment of Heart Failure Restores Cardiac Function and Reduces Pathological Hypertrophy

PubMed Central

Suckau, Lennart; Fechner, Henry; Chemaly, Elie; Krohn, Stefanie; Hadri, Lahouaria; Kockskämper, Jens; Westermann, Dirk; Bisping, Egbert; Ly, Hung; Wang, Xiaomin; Kawase, Yoshiaki; Chen, Jiqiu; Liang, Lifan; Sipo, Isaac; Vetter, Roland; Weger, Stefan; Kurreck, Jens; Erdmann, Volker; Tschope, Carsten; Pieske, Burkert; Lebeche, Djamel; Schultheiss, Heinz-Peter; Hajjar, Roger J.; Poller, Wolfgang Ch.

2009-01-01

Background RNA interference (RNAi) has the potential to be a novel therapeutic strategy in diverse areas of medicine. We report on targeted RNAi for the treatment of heart failure (HF), an important disorder in humans resulting from multiple etiologies. Successful treatment of HF is demonstrated in a rat model of transaortic banding by RNAi targeting of phospholamban (PLB), a key regulator of cardiac Ca2+ homeostasis. Whereas gene therapy rests on recombinant protein expression as its basic principle, RNAi therapy employs regulatory RNAs to achieve its effect. Methods and Results We describe structural requirements to obtain high RNAi activity from adenoviral (AdV) and adeno-associated virus (AAV9) vectors and show that an AdV short hairpin RNA vector (AdV-shRNA) silenced PLB in cardiomyocytes (NRCMs) and improved hemodynamics in HF rats 1 month after aortic root injection. For simplified long-term therapy we developed a dimeric cardiotropic AAV vector (rAAV9-shPLB) delivering RNAi activity to the heart via intravenous injection. Cardiac PLB protein was reduced to 25% and SERCA2a suppression in the HF groups was rescued. In contrast to traditional vectors rAAV9 shows high affinity for myocardium, but low affinity for liver and other organs. rAAV9-shPLB therapy restored diastolic (LVEDP, dp/dtmin, Tau) and systolic (fractional shortening) functional parameters to normal range. The massive cardiac dilation was normalized and the cardiac hypertrophy, cardiomyocyte diameter and cardiac fibrosis significantly reduced. Importantly, there was no evidence of microRNA deregulation or hepatotoxicity during these RNAi therapies. Conclusion Our data show, for the first time, high efficacy of an RNAi therapeutic strategy in a cardiac disease. PMID:19237664

Preclinical Potency and Biodistribution Studies of an AAV 5 Vector Expressing Human Interferon-β (ART-I02) for Local Treatment of Patients with Rheumatoid Arthritis

PubMed Central

Aalbers, Caroline J.; Bevaart, Lisette; Loiler, Scott; de Cortie, Karin; Wright, J. Fraser; Mingozzi, Federico; Tak, Paul P.; Vervoordeldonk, Margriet J.

2015-01-01

Introduction Proof of concept for local gene therapy for the treatment of arthritis with immunomodulatory cytokine interferon beta (IFN-β) has shown promising results in animal models of rheumatoid arthritis (RA). For the treatment of RA patients, we engineered a recombinant adeno-associated serotype 5 vector (rAAV5) encoding human (h)IFN-β under control of a nuclear factor κB promoter (ART-I02). Methods The potency of ART-I02 in vitro as well as biodistribution in vivo in arthritic animals was evaluated to characterize the vector prior to clinical application. ART-I02 expression and bioactivity after transduction was evaluated in fibroblast-like synoviocytes (FLS) from different species. Biodistribution of the vector after local injection was assessed in a rat adjuvant arthritis model through qPCR analysis of vector DNA. In vivo imaging was used to investigate transgene expression and kinetics in a mouse collagen induced arthritis model. Results Transduction of RA FLS in vitro with ART-I02 resulted in high expression levels of bioactive hIFN-β. Transduction of FLS from rhesus monkeys, rodents and rabbits with ART-I02 showed high transgene expression, and hIFN-β proved bioactive in FLS from rhesus monkeys. Transgene expression and bioactivity in RA FLS were unaltered in the presence of methotrexate. In vivo, vector biodistribution analysis in rats after intra-articular injection of ART-I02 demonstrated that the majority of vector DNA remained in the joint (>93%). In vivo imaging in mice confirmed local expression of rAAV5 in the knee joint region and demonstrated rapid detectable and sustained expression up until 7 weeks. Conclusions These data show that hIFN-β produced by RA FLS transduced with ART-I02 is bioactive and that intra-articular delivery of rAAV5 drives expression of a therapeutic transgene in the joint, with only limited biodistribution of vector DNA to other tissues, supporting progress towards a phase 1 clinical trial for the local treatment of arthritis in patients with RA. PMID:26107769

Preclinical Potency and Biodistribution Studies of an AAV 5 Vector Expressing Human Interferon-β (ART-I02) for Local Treatment of Patients with Rheumatoid Arthritis.

PubMed

Aalbers, Caroline J; Bevaart, Lisette; Loiler, Scott; de Cortie, Karin; Wright, J Fraser; Mingozzi, Federico; Tak, Paul P; Vervoordeldonk, Margriet J

2015-01-01

Proof of concept for local gene therapy for the treatment of arthritis with immunomodulatory cytokine interferon beta (IFN-β) has shown promising results in animal models of rheumatoid arthritis (RA). For the treatment of RA patients, we engineered a recombinant adeno-associated serotype 5 vector (rAAV5) encoding human (h)IFN-β under control of a nuclear factor κB promoter (ART-I02). The potency of ART-I02 in vitro as well as biodistribution in vivo in arthritic animals was evaluated to characterize the vector prior to clinical application. ART-I02 expression and bioactivity after transduction was evaluated in fibroblast-like synoviocytes (FLS) from different species. Biodistribution of the vector after local injection was assessed in a rat adjuvant arthritis model through qPCR analysis of vector DNA. In vivo imaging was used to investigate transgene expression and kinetics in a mouse collagen induced arthritis model. Transduction of RA FLS in vitro with ART-I02 resulted in high expression levels of bioactive hIFN-β. Transduction of FLS from rhesus monkeys, rodents and rabbits with ART-I02 showed high transgene expression, and hIFN-β proved bioactive in FLS from rhesus monkeys. Transgene expression and bioactivity in RA FLS were unaltered in the presence of methotrexate. In vivo, vector biodistribution analysis in rats after intra-articular injection of ART-I02 demonstrated that the majority of vector DNA remained in the joint (>93%). In vivo imaging in mice confirmed local expression of rAAV5 in the knee joint region and demonstrated rapid detectable and sustained expression up until 7 weeks. These data show that hIFN-β produced by RA FLS transduced with ART-I02 is bioactive and that intra-articular delivery of rAAV5 drives expression of a therapeutic transgene in the joint, with only limited biodistribution of vector DNA to other tissues, supporting progress towards a phase 1 clinical trial for the local treatment of arthritis in patients with RA.

Hypothalamic IGF-I Gene Therapy Prolongs Estrous Cyclicity and Protects Ovarian Structure in Middle-Aged Female Rats

PubMed Central

Rodríguez, Silvia S.; Schwerdt, José I.; Barbeito, Claudio G.; Flamini, Mirta A.; Han, Ye; Bohn, Martha C.

2013-01-01

There is substantial evidence that age-related ovarian failure in rats is preceded by abnormal responsiveness of the neuroendocrine axis to estrogen positive feedback. Because IGF-I seems to act as a permissive factor for proper GnRH neuronal response to estrogen positive feedback and considering that the hypothalamic content of IGF-I declines in middle-aged (M-A) rats, we assessed the effectiveness of long-term IGF-I gene therapy in the mediobasal hypothalamus (MBH) of M-A female rats to extend regular cyclicity and preserve ovarian structure. We used 3 groups of M-A rats: 1 group of intact animals and 2 groups injected, at 36.2 weeks of age, in the MBH with either a bicistronic recombinant adeno-associated virus (rAAV) harboring the genes for IGF-I and the red fluorescent protein DsRed2, or a control rAAV expressing only DsRed2. Daily vaginal smears were taken throughout the study, which ended at 49.5 weeks of age. We measured serum levels of reproductive hormones and assessed ovarian histology at the end of the study. Although most of the rats injected with the IGF-I rAAV had, on the average, well-preserved estrous cyclicity as well as a generally normal ovarian histology, the intact and control rAAV groups showed a high percentage of acyclic rats at the end of the study and ovaries with numerous enlarged cysts and scarce corpora lutea. Serum LH was higher and hyperprolactinemia lower in the treated animals. These results suggest that overexpression of IGF-I in the MBH prolongs normal ovarian function in M-A female rats. PMID:23584855

The use of a viral 2A sequence for the simultaneous over-expression of both the vgf gene and enhanced green fluorescent protein (eGFP) in vitro and in vivo

PubMed Central

Lewis, Jo E.; Brameld, John M.; Hill, Phil; Barrett, Perry; Ebling, Francis J.P.; Jethwa, Preeti H.

2015-01-01

Introduction The viral 2A sequence has become an attractive alternative to the traditional internal ribosomal entry site (IRES) for simultaneous over-expression of two genes and in combination with recombinant adeno-associated viruses (rAAV) has been used to manipulate gene expression in vitro. New method To develop a rAAV construct in combination with the viral 2A sequence to allow long-term over-expression of the vgf gene and fluorescent marker gene for tracking of the transfected neurones in vivo. Results Transient transfection of the AAV plasmid containing the vgf gene, viral 2A sequence and eGFP into SH-SY5Y cells resulted in eGFP fluorescence comparable to a commercially available reporter construct. This increase in fluorescent cells was accompanied by an increase in VGF mRNA expression. Infusion of the rAAV vector containing the vgf gene, viral 2A sequence and eGFP resulted in eGFP fluorescence in the hypothalamus of both mice and Siberian hamsters, 32 weeks post infusion. In situ hybridisation confirmed that the location of VGF mRNA expression in the hypothalamus corresponded to the eGFP pattern of fluorescence. Comparison with old method The viral 2A sequence is much smaller than the traditional IRES and therefore allowed over-expression of the vgf gene with fluorescent tracking without compromising viral capacity. Conclusion The use of the viral 2A sequence in the AAV plasmid allowed the simultaneous expression of both genes in vitro. When used in combination with rAAV it resulted in long-term over-expression of both genes at equivalent locations in the hypothalamus of both Siberian hamsters and mice, without any adverse effects. PMID:26300182

Restoration of central nervous system alpha-N-acetylglucosaminidase activity and therapeutic benefits in mucopolysaccharidosis IIIB mice by a single intracisternal recombinant adeno-associated viral type 2 vector delivery.

PubMed

Fu, Haiyan; DiRosario, Julianne; Kang, Lu; Muenzer, Joseph; McCarty, Douglas M

2010-07-01

Finding efficient central nervous system (CNS) delivery approaches has been the major challenge facing therapeutic development for treating diseases with global neurological manifestation, such as mucopolysaccharidosis (MPS) IIIB, a lysosomal storage disease, caused by autosomal recessive defect of alpha-N-acetylglucosaminidase (NaGlu). Previously, we developed an approach, intracisternal (i.c.) injection, to deliver recombinant adeno-associated viral (rAAV) vector to the CNS of mice, leading to a widespread periventricular distribution of transduction. In the present study, we delivered rAAV2 vector expressing human NaGlu into the CNS of MPS IIIB mice by an i.c. injection approach, to test its therapeutic efficacy and feasibility for treating the neurological manifestation of the disease. We demonstrated significant functional neurological benefits of a single i.c. vector infusion in adult MPS IIIB mice. The treatment slowed the disease progression by mediating widespread recombinant NaGlu expression in the CNS, resulting in the reduction of brain lysosomal storage pathology, significantly improved cognitive function and prolonged survival. However, persisting motor function deficits suggested that pathology in areas outside the CNS contributes to the MPS IIIB behavioral phenotype. The therapeutic benefit of i.c. rAAV2 delivery was dose-dependent and could be attribute solely to the CNS transduction because the procedure did not lead to detectable transduction in somatic tissues. A single IC rAAV2 gene delivery is functionally beneficial for treating the CNS disease of MPS IIIB in mice. It is immediately clinically translatable, with the potential of improving the quality of life for patients with MPS IIIB.

Long-Term Correction of Sandhoff Disease Following Intravenous Delivery of rAAV9 to Mouse Neonates

PubMed Central

Walia, Jagdeep S; Altaleb, Naderah; Bello, Alexander; Kruck, Christa; LaFave, Matthew C; Varshney, Gaurav K; Burgess, Shawn M; Chowdhury, Biswajit; Hurlbut, David; Hemming, Richard; Kobinger, Gary P; Triggs-Raine, Barbara

2015-01-01

GM2 gangliosidoses are severe neurodegenerative disorders resulting from a deficiency in β-hexosaminidase A activity and lacking effective therapies. Using a Sandhoff disease (SD) mouse model (Hexb−/−) of the GM2 gangliosidoses, we tested the potential of systemically delivered adeno-associated virus 9 (AAV9) expressing Hexb cDNA to correct the neurological phenotype. Neonatal or adult SD and normal mice were intravenously injected with AAV9-HexB or –LacZ and monitored for serum β-hexosaminidase activity, motor function, and survival. Brain GM2 ganglioside, β-hexosaminidase activity, and inflammation were assessed at experimental week 43, or an earlier humane end point. SD mice injected with AAV9-LacZ died by 17 weeks of age, whereas all neonatal AAV9-HexB–treated SD mice survived until 43 weeks (P < 0.0001) with only three exhibiting neurological dysfunction. SD mice treated as adults with AAV9-HexB died between 17 and 35 weeks. Neonatal SD-HexB–treated mice had a significant increase in brain β-hexosaminidase activity, and a reduction in GM2 ganglioside storage and neuroinflammation compared to adult SD-HexB– and SD-LacZ–treated groups. However, at 43 weeks, 8 of 10 neonatal-HexB injected control and SD mice exhibited liver or lung tumors. This study demonstrates the potential for long-term correction of SD and other GM2 gangliosidoses through early rAAV9 based systemic gene therapy. PMID:25515709

Systemic AAV8-Mediated Gene Therapy Drives Whole-Body Correction of Myotubular Myopathy in Dogs.

PubMed

Mack, David L; Poulard, Karine; Goddard, Melissa A; Latournerie, Virginie; Snyder, Jessica M; Grange, Robert W; Elverman, Matthew R; Denard, Jérôme; Veron, Philippe; Buscara, Laurine; Le Bec, Christine; Hogrel, Jean-Yves; Brezovec, Annie G; Meng, Hui; Yang, Lin; Liu, Fujun; O'Callaghan, Michael; Gopal, Nikhil; Kelly, Valerie E; Smith, Barbara K; Strande, Jennifer L; Mavilio, Fulvio; Beggs, Alan H; Mingozzi, Federico; Lawlor, Michael W; Buj-Bello, Ana; Childers, Martin K

2017-04-05

X-linked myotubular myopathy (XLMTM) results from MTM1 gene mutations and myotubularin deficiency. Most XLMTM patients develop severe muscle weakness leading to respiratory failure and death, typically within 2 years of age. Our objective was to evaluate the efficacy and safety of systemic gene therapy in the p.N155K canine model of XLMTM by performing a dose escalation study. A recombinant adeno-associated virus serotype 8 (rAAV8) vector expressing canine myotubularin (cMTM1) under the muscle-specific desmin promoter (rAAV8-cMTM1) was administered by simple peripheral venous infusion in XLMTM dogs at 10 weeks of age, when signs of the disease are already present. A comprehensive analysis of survival, limb strength, gait, respiratory function, neurological assessment, histology, vector biodistribution, transgene expression, and immune response was performed over a 9-month study period. Results indicate that systemic gene therapy was well tolerated, prolonged lifespan, and corrected the skeletal musculature throughout the body in a dose-dependent manner, defining an efficacious dose in this large-animal model of the disease. These results support the development of gene therapy clinical trials for XLMTM. Copyright © 2017 The American Society of Gene and Cell Therapy. Published by Elsevier Inc. All rights reserved.

Generation of infectious recombinant Adeno-associated virus in Saccharomyces cerevisiae.

PubMed

Barajas, Daniel; Aponte-Ubillus, Juan Jose; Akeefe, Hassibullah; Cinek, Tomas; Peltier, Joseph; Gold, Daniel

2017-01-01

The yeast Saccharomyces cerevisiae has been successfully employed to establish model systems for a number of viruses. Such model systems are powerful tools to study the virus biology and in particular for the identification and characterization of host factors playing a role in the viral infection cycle. Adeno-associated viruses (AAV) are heavily studied due to their use as gene delivery vectors. AAV relies on other helper viruses for successful replication and on host factors for several aspects of the viral life cycle. However the role of host and helper viral factors is only partially known. Production of recombinant AAV (rAAV) vectors for gene delivery applications depends on knowledge of AAV biology and the limited understanding of host and helper viral factors may be precluding efficient production, particularly in heterologous systems. Model systems in simpler eukaryotes like the yeast S. cerevisiae would be useful tools to identify and study the role of host factors in AAV biology. Here we show that expression of AAV2 viral proteins VP1, VP2, VP3, AAP, Rep78, Rep52 and an ITR-flanked DNA in yeast leads to capsid formation, DNA replication and encapsidation, resulting in formation of infectious particles. Many of the AAV characteristics observed in yeast resemble those in other systems, making it a suitable model system. Future findings in the yeast system could be translatable to other AAV host systems and aid in more efficient production of rAAV vectors.

The gene therapy revolution in ophthalmology.

PubMed

Al-Saikhan, Fahad I

2013-04-01

The advances in gene therapy hold significant promise for the treatment of ophthalmic conditions. Several studies using animal models have been published. Animal models on retinitis pigmentosa, Leber's Congenital Amaurosis (LCA), and Stargardt disease have involved the use of adeno-associated virus (AAV) to deliver functional genes into mice and canines. Mice models have been used to show that a mutation in cGMP phosphodiesterase that results in retinitis pigmentosa can be corrected using rAAV vectors. Additionally, rAAV vectors have been successfully used to deliver ribozyme into mice with a subsequent improvement in autosomal dominant retinitis pigmentosa. By using dog models, researchers have made progress in studying X-linked retinitis pigmentosa which results from a RPGR gene mutation. Mouse and canine models have also been used in the study of LCA. The widely studied form of LCA is LCA2, resulting from a mutation in the gene RPE65. Mice and canines that were injected with normal copies of RPE65 gene showed signs such as improved retinal pigment epithelium transduction, visual acuity, and functional recovery. Studies on Stargardt disease have shown that mutations in the ABCA4 gene can be corrected with AAV vectors, or nanoparticles. Gene therapy for the treatment of red-green color blindness was successful in squirrel monkeys. Plans are at an advanced stage to begin clinical trials. Researchers have also proved that CD59 can be used with AMD. Gene therapy is also able to treat primary open angle glaucoma (POAG) in animal models, and studies show it is economically viable.

The gene therapy revolution in ophthalmology

PubMed Central

Al-Saikhan, Fahad I.

2013-01-01

The advances in gene therapy hold significant promise for the treatment of ophthalmic conditions. Several studies using animal models have been published. Animal models on retinitis pigmentosa, Leber’s Congenital Amaurosis (LCA), and Stargardt disease have involved the use of adeno-associated virus (AAV) to deliver functional genes into mice and canines. Mice models have been used to show that a mutation in cGMP phosphodiesterase that results in retinitis pigmentosa can be corrected using rAAV vectors. Additionally, rAAV vectors have been successfully used to deliver ribozyme into mice with a subsequent improvement in autosomal dominant retinitis pigmentosa. By using dog models, researchers have made progress in studying X-linked retinitis pigmentosa which results from a RPGR gene mutation. Mouse and canine models have also been used in the study of LCA. The widely studied form of LCA is LCA2, resulting from a mutation in the gene RPE65. Mice and canines that were injected with normal copies of RPE65 gene showed signs such as improved retinal pigment epithelium transduction, visual acuity, and functional recovery. Studies on Stargardt disease have shown that mutations in the ABCA4 gene can be corrected with AAV vectors, or nanoparticles. Gene therapy for the treatment of red–green color blindness was successful in squirrel monkeys. Plans are at an advanced stage to begin clinical trials. Researchers have also proved that CD59 can be used with AMD. Gene therapy is also able to treat primary open angle glaucoma (POAG) in animal models, and studies show it is economically viable. PMID:24227970

Delivery and evaluation of recombinant adeno-associated viral vectors in the equine distal extremity for the treatment of laminitis.

PubMed

Mason, J B; Gurda, B L; Van Wettere, A; Engiles, J B; Wilson, J M; Richardson, D W

2017-01-01

Our long-term aim is to develop a gene therapy approach for the prevention of laminitis in the contralateral foot of horses with major musculoskeletal injuries and non-weightbearing lameness. The goal of this study was to develop a practical method to efficiently deliver therapeutic proteins deep within the equine foot. Randomised in vivo experiment. We used recombinant adeno-associated viral vectors (rAAVs) to deliver marker genes using regional limb perfusion through the palmar digital artery of the horse. Vector serotypes rAAV2/1, 2/8 and 2/9 all successfully transduced equine foot tissues and displayed similar levels and patterns of transduction. The regional distribution of transduction within the foot decreased with decreasing vector dose. The highest transduction values were seen in the sole and coronary regions and the lowest transduction values were detected in the dorsal hoof-wall region. The use of a surfactant-enriched vector diluent increased regional distribution of the vector and improved the transduction in the hoof-wall region. The hoof-wall region of the foot, which exhibited the lowest levels of transduction using saline as the vector diluent, displayed a dramatic increase in transduction when surfactant was included in the vector diluent (9- to 81-fold increase). In transduced tissues, no significant difference was observed between promoters (chicken β-actin vs. cytomegalovirus) for gene expression. All horses tested for vector-neutralising antibodies were positive for serotype-specific neutralising antibodies to rAAV2/5. The current experiments demonstrate that transgenes can be successfully delivered to the equine distal extremity using rAAV vectors and that serotypes 2/8, 2/9 and 2/1 can successfully transduce tissues of the equine foot. When the vector was diluted with surfactant-containing saline, the level of transduction increased dramatically. The increased level of transduction due to the addition of surfactant also improved the distribution pattern of transduction. © 2015 EVJ Ltd.

The use of a viral 2A sequence for the simultaneous over-expression of both the vgf gene and enhanced green fluorescent protein (eGFP) in vitro and in vivo.

PubMed

Lewis, Jo E; Brameld, John M; Hill, Phil; Barrett, Perry; Ebling, Francis J P; Jethwa, Preeti H

2015-12-30

The viral 2A sequence has become an attractive alternative to the traditional internal ribosomal entry site (IRES) for simultaneous over-expression of two genes and in combination with recombinant adeno-associated viruses (rAAV) has been used to manipulate gene expression in vitro. To develop a rAAV construct in combination with the viral 2A sequence to allow long-term over-expression of the vgf gene and fluorescent marker gene for tracking of the transfected neurones in vivo. Transient transfection of the AAV plasmid containing the vgf gene, viral 2A sequence and eGFP into SH-SY5Y cells resulted in eGFP fluorescence comparable to a commercially available reporter construct. This increase in fluorescent cells was accompanied by an increase in VGF mRNA expression. Infusion of the rAAV vector containing the vgf gene, viral 2A sequence and eGFP resulted in eGFP fluorescence in the hypothalamus of both mice and Siberian hamsters, 32 weeks post infusion. In situ hybridisation confirmed that the location of VGF mRNA expression in the hypothalamus corresponded to the eGFP pattern of fluorescence. The viral 2A sequence is much smaller than the traditional IRES and therefore allowed over-expression of the vgf gene with fluorescent tracking without compromising viral capacity. The use of the viral 2A sequence in the AAV plasmid allowed the simultaneous expression of both genes in vitro. When used in combination with rAAV it resulted in long-term over-expression of both genes at equivalent locations in the hypothalamus of both Siberian hamsters and mice, without any adverse effects. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

Phase I/II Trial of Adeno-Associated Virus–Mediated Alpha-Glucosidase Gene Therapy to the Diaphragm for Chronic Respiratory Failure in Pompe Disease: Initial Safety and Ventilatory Outcomes

PubMed Central

Smith, Barbara K.; Collins, Shelley W.; Conlon, Thomas J.; Mah, Cathryn S.; Lawson, Lee Ann; Martin, Anatole D.; Fuller, David D.; Cleaver, Brian D.; Clément, Nathalie; Phillips, Dawn; Islam, Saleem; Dobjia, Nicole

2013-01-01

Abstract Pompe disease is an inherited neuromuscular disease caused by deficiency of lysosomal acid alpha-glucosidase (GAA) leading to glycogen accumulation in muscle and motoneurons. Cardiopulmonary failure in infancy leads to early mortality, and GAA enzyme replacement therapy (ERT) results in improved survival, reduction of cardiac hypertrophy, and developmental gains. However, many children have progressive ventilatory insufficiency and need additional support. Preclinical work shows that gene transfer restores phrenic neural activity and corrects ventilatory deficits. Here we present 180-day safety and ventilatory outcomes for five ventilator-dependent children in a phase I/II clinical trial of AAV-mediated GAA gene therapy (rAAV1-hGAA) following intradiaphragmatic delivery. We assessed whether rAAV1-hGAA results in acceptable safety outcomes and detectable functional changes, using general safety measures, immunological studies, and pulmonary functional testing. All subjects required chronic, full-time mechanical ventilation because of respiratory failure that was unresponsive to both ERT and preoperative muscle-conditioning exercises. After receiving a dose of either 1×1012 vg (n=3) or 5×1012 vg (n=2) of rAAV1-hGAA, the subjects' unassisted tidal volume was significantly larger (median [interquartile range] 28.8% increase [15.2–35.2], p<0.05). Further, most patients tolerated appreciably longer periods of unassisted breathing (425% increase [103–851], p=0.08). Gene transfer did not improve maximal inspiratory pressure. Expected levels of circulating antibodies and no T-cell-mediated immune responses to the vector (capsids) were observed. One subject demonstrated a slight increase in anti-GAA antibody that was not considered clinically significant. These results indicate that rAAV1-hGAA was safe and may lead to modest improvements in volitional ventilatory performance measures. Evaluation of the next five patients will determine whether earlier intervention can further enhance the functional benefit. PMID:23570273

Adeno Associated Viral-mediated intraosseus labeling of bone marrow derived cells for CNS tracking

PubMed Central

Selenica, Maj-Linda B.; Reid, Patrick; Pena, Gabriela; Alvarez, Jennifer; Hunt, Jerry B.; Nash, Kevin R.; Morgan, Dave; Gordon, Marcia N.; Lee, Daniel C.

2016-01-01

Inflammation, including microglial activation in the CNS, is an important hallmark in many neurodegenerative diseases. Microglial stimuli not only impact the brain microenvironment by production and release of cytokines and chemokines, but also influence the activity of bone marrow derived cells and blood born macrophage populations. In many diseases including brain disorders and spinal cord injury, researchers have tried to harbor the neuroprotective and repair properties of these subpopulations. Hematopoietic bone marrow derived cells (BMDCs) are of great interest, especially during gene therapy because certain hematopoietic cell subpopulations traffic to the sites of injury and inflammation. The aim of this study was to develop a method of labeling endogenous bone marrow derived cells through intraosseus impregnation of recombinant adeno-associated virus (rAAV) or lentivirus. We utilized rAAV serotype 9 (rAAV-9) or lentivirus for gene delivery of green florescence protein (GFP) to the mouse bone marrow cells. Flow cytometry showed that both viruses were able to efficiently transduce mouse bone marrow cells in vivo. However, the rAAV9–GFP viral construct transduced BMDCs more efficiently than the lentivirus (11.2% vs. 6.8%), as indicated by cellular GFP expression. We also demonstrate that GFP labeled cells correspond to bone marrow cells of myeloid origin using CD11b as a marker. Additionally, we characterized the ability of bone marrow derived, GFP labeled cells to extravasate into the brain parenchyma upon acute and subchronic neuroinflammatory stimuli in the mouse CNS. Viral mediated over expression of chemokine (C-C motif) ligand 2 (CCL2) or intracranial injection of lipopolysaccharide (LPS) recruited GFP labeled BMDCs from the periphery into the brain parenchyma compared to vehicle treated mice. Altogether our findings demonstrate a useful method of labeling endogenous BMDCs via viral transduction and the ability to track subpopulations throughout the body following insult or injury. Alternatively, this method might find utility in delivering therapeutic genes for neuroinflammatory conditions. PMID:26784524

Successful transduction of liver in hemophilia by AAV-Factor IX and limitations imposed by the host immune response.

PubMed

Manno, Catherine S; Pierce, Glenn F; Arruda, Valder R; Glader, Bertil; Ragni, Margaret; Rasko, John J; Rasko, John; Ozelo, Margareth C; Hoots, Keith; Blatt, Philip; Konkle, Barbara; Dake, Michael; Kaye, Robin; Razavi, Mahmood; Zajko, Albert; Zehnder, James; Rustagi, Pradip K; Nakai, Hiroyuki; Chew, Amy; Leonard, Debra; Wright, J Fraser; Lessard, Ruth R; Sommer, Jürg M; Tigges, Michael; Sabatino, Denise; Luk, Alvin; Jiang, Haiyan; Mingozzi, Federico; Couto, Linda; Ertl, Hildegund C; High, Katherine A; Kay, Mark A

2006-03-01

We have previously shown that a single portal vein infusion of a recombinant adeno-associated viral vector (rAAV) expressing canine Factor IX (F.IX) resulted in long-term expression of therapeutic levels of F.IX in dogs with severe hemophilia B. We carried out a phase 1/2 dose-escalation clinical study to extend this approach to humans with severe hemophilia B. rAAV-2 vector expressing human F.IX was infused through the hepatic artery into seven subjects. The data show that: (i) vector infusion at doses up to 2 x 10(12) vg/kg was not associated with acute or long-lasting toxicity; (ii) therapeutic levels of F.IX were achieved at the highest dose tested; (iii) duration of expression at therapeutic levels was limited to a period of approximately 8 weeks; (iv) a gradual decline in F.IX was accompanied by a transient asymptomatic elevation of liver transaminases that resolved without treatment. Further studies suggested that destruction of transduced hepatocytes by cell-mediated immunity targeting antigens of the AAV capsid caused both the decline in F.IX and the transient transaminitis. We conclude that rAAV-2 vectors can transduce human hepatocytes in vivo to result in therapeutically relevant levels of F.IX, but that future studies in humans may require immunomodulation to achieve long-term expression.

Bcl-2–associated athanogene 3 protects the heart from ischemia/reperfusion injury

PubMed Central

Su, Feifei; Myers, Valerie D.; Knezevic, Tijana; Wang, JuFang; Gao, Erhe; Madesh, Muniswamy; Tahrir, Farzaneh G.; Gupta, Manish K.; Gordon, Jennifer; Rabinowitz, Joseph; Tilley, Douglas G.; Khalili, Kamel; Cheung, Joseph Y.

2016-01-01

Bcl-2–associated athanogene 3 (BAG3) is an evolutionarily conserved protein expressed at high levels in the heart and the vasculature and in many cancers. While altered BAG3 expression has been associated with cardiac dysfunction, its role in ischemia/reperfusion (I/R) is unknown. To test the hypothesis that BAG3 protects the heart from reperfusion injury, in vivo cardiac function was measured in hearts infected with either recombinant adeno-associated virus serotype 9–expressing (rAAV9-expressing) BAG3 or GFP and subjected to I/R. To elucidate molecular mechanisms by which BAG3 protects against I/R injury, neonatal mouse ventricular cardiomyocytes (NMVCs) in which BAG3 levels were modified by adenovirus expressing (Ad-expressing) BAG3 or siBAG3 were exposed to hypoxia/reoxygenation (H/R). H/R significantly reduced NMVC BAG3 levels, which were associated with enhanced expression of apoptosis markers, decreased expression of autophagy markers, and reduced autophagy flux. The deleterious effects of H/R on apoptosis and autophagy were recapitulated by knockdown of BAG3 with Ad-siBAG3 and were rescued by Ad-BAG3. In vivo, treatment of mice with rAAV9-BAG3 prior to I/R significantly decreased infarct size and improved left ventricular function when compared with mice receiving rAAV9-GFP and improved markers of autophagy and apoptosis. These findings suggest that BAG3 may provide a therapeutic target in patients undergoing reperfusion after myocardial infarction. PMID:27882354

Formation of AAV Single Stranded DNA Genome from a Circular Plasmid in Saccharomyces cerevisiae

PubMed Central

Cervelli, Tiziana; Backovic, Ana; Galli, Alvaro

2011-01-01

Adeno-associated virus (AAV)-based vectors are promising tools for targeted transfer in gene therapy studies. Many efforts have been accomplished to improve production and purification methods. We thought to develop a simple eukaryotic system allowing AAV replication which could provide an excellent opportunity for studying AAV biology and, more importantly, for AAV vector production. It has been shown that yeast Saccharomyces cerevisiae is able to replicate and form the capsid of many viruses. We investigated the ability of the yeast Saccharomyces cerevisiae to carry out the replication of a recombinant AAV (rAAV). When a plasmid containing a rAAV genome in which the cap gene was replaced with the S. cerevisiae URA3 gene, was co-transformed in yeast with a plasmid expressing Rep68, a significant number of URA3+ clones were scored (more than 30-fold over controls). Molecular analysis of low molecular weight DNA by Southern blotting revealed that single stranded DNA is formed and that the plasmid is entirely replicated. The ssDNA contains the ITRs, URA3 gene and also vector sequences suggesting the presence of two distinct molecules. Its formation was dependent on Rep68 expression and ITR. These data indicate that DNA is not obtained by the canonical AAV replication pathway. PMID:21853137

Formation of AAV single stranded DNA genome from a circular plasmid in Saccharomyces cerevisiae.

PubMed

Cervelli, Tiziana; Backovic, Ana; Galli, Alvaro

2011-01-01

Adeno-associated virus (AAV)-based vectors are promising tools for targeted transfer in gene therapy studies. Many efforts have been accomplished to improve production and purification methods. We thought to develop a simple eukaryotic system allowing AAV replication which could provide an excellent opportunity for studying AAV biology and, more importantly, for AAV vector production. It has been shown that yeast Saccharomyces cerevisiae is able to replicate and form the capsid of many viruses. We investigated the ability of the yeast Saccharomyces cerevisiae to carry out the replication of a recombinant AAV (rAAV). When a plasmid containing a rAAV genome in which the cap gene was replaced with the S. cerevisiae URA3 gene, was co-transformed in yeast with a plasmid expressing Rep68, a significant number of URA3(+) clones were scored (more than 30-fold over controls). Molecular analysis of low molecular weight DNA by Southern blotting revealed that single stranded DNA is formed and that the plasmid is entirely replicated. The ssDNA contains the ITRs, URA3 gene and also vector sequences suggesting the presence of two distinct molecules. Its formation was dependent on Rep68 expression and ITR. These data indicate that DNA is not obtained by the canonical AAV replication pathway.

Recombinant adeno-associated virus mediates a high level of gene transfer but less efficient integration in the K562 human hematopoietic cell line.

PubMed Central

Malik, P; McQuiston, S A; Yu, X J; Pepper, K A; Krall, W J; Podsakoff, G M; Kurtzman, G J; Kohn, D B

1997-01-01

We tested the ability of a recombinant adeno-associated virus (rAAV) vector to express and integrate exogenous DNA into human hematopoietic cells in the absence of selection. We developed an rAAV vector, AAV-tNGFR, carrying a truncated rat nerve growth factor receptor (tNGFR) cDNA as a cell surface reporter under the control of the Moloney murine leukemia virus (MoMuLV) long terminal repeat. An analogous MoMuLV-based retroviral vector (L-tNGFR) was used in parallel, and gene transfer and expression in human hematopoietic cells were assessed by flow cytometry and DNA analyses. Following gene transfer into K562 cells with AAV-tNGFR at a multiplicity of infection (MOI) of 13 infectious units (IU), 26 to 38% of cells expressed tNGFR on the surface early after transduction, but the proportion of tNGFR expressing cells steadily declined to 3.0 to 3.5% over 1 month of culture. At an MOI of 130 IU, nearly all cells expressed tNGFR immediately posttransduction, but the proportion of cells expressing tNGFR declined to 62% over 2 months of culture. The decline in the proportion of AAV-tNGFR-expressing cells was associated with ongoing losses of vector genomes. In contrast, K562 cells transduced with the retroviral vector L-tNGFR expressed tNGFR in a constant fraction. Integration analyses on clones showed that integration occurred at different sites. Integration frequencies were estimated at about 49% at an MOI of 130 and 2% at an MOI of 1.3. Transduction of primary human CD34+ progenitor cells by AAV-tNGFR was less efficient than with K562 cells and showed a declining percentage of cells expressing tNGFR over 2 weeks of culture. Thus, purified rAAV caused very high gene transfer and expression in human hematopoietic cells early after transduction, which steadily declined during cell passage in the absence of selection. Although the efficiency of integration was low, overall integration was markedly improved at a high MOI. While prolonged episomal persistence may be adequate for gene therapy of nondividing cells, a very high MOI or improvements in basic aspects of AAV-based vectors may be necessary to improve integration frequency in the rapidly dividing hematopoietic cell population. PMID:9032306

Recombinant adeno-associated virus mediates a high level of gene transfer but less efficient integration in the K562 human hematopoietic cell line.

PubMed

Malik, P; McQuiston, S A; Yu, X J; Pepper, K A; Krall, W J; Podsakoff, G M; Kurtzman, G J; Kohn, D B

1997-03-01

We tested the ability of a recombinant adeno-associated virus (rAAV) vector to express and integrate exogenous DNA into human hematopoietic cells in the absence of selection. We developed an rAAV vector, AAV-tNGFR, carrying a truncated rat nerve growth factor receptor (tNGFR) cDNA as a cell surface reporter under the control of the Moloney murine leukemia virus (MoMuLV) long terminal repeat. An analogous MoMuLV-based retroviral vector (L-tNGFR) was used in parallel, and gene transfer and expression in human hematopoietic cells were assessed by flow cytometry and DNA analyses. Following gene transfer into K562 cells with AAV-tNGFR at a multiplicity of infection (MOI) of 13 infectious units (IU), 26 to 38% of cells expressed tNGFR on the surface early after transduction, but the proportion of tNGFR expressing cells steadily declined to 3.0 to 3.5% over 1 month of culture. At an MOI of 130 IU, nearly all cells expressed tNGFR immediately posttransduction, but the proportion of cells expressing tNGFR declined to 62% over 2 months of culture. The decline in the proportion of AAV-tNGFR-expressing cells was associated with ongoing losses of vector genomes. In contrast, K562 cells transduced with the retroviral vector L-tNGFR expressed tNGFR in a constant fraction. Integration analyses on clones showed that integration occurred at different sites. Integration frequencies were estimated at about 49% at an MOI of 130 and 2% at an MOI of 1.3. Transduction of primary human CD34+ progenitor cells by AAV-tNGFR was less efficient than with K562 cells and showed a declining percentage of cells expressing tNGFR over 2 weeks of culture. Thus, purified rAAV caused very high gene transfer and expression in human hematopoietic cells early after transduction, which steadily declined during cell passage in the absence of selection. Although the efficiency of integration was low, overall integration was markedly improved at a high MOI. While prolonged episomal persistence may be adequate for gene therapy of nondividing cells, a very high MOI or improvements in basic aspects of AAV-based vectors may be necessary to improve integration frequency in the rapidly dividing hematopoietic cell population.

Overexpression of cystatin C in synovium does not reduce synovitis or cartilage degradation in established osteoarthritis.

PubMed

Kyostio-Moore, Sirkka; Piraino, Susan; Berthelette, Patricia; Moran, Nance; Serriello, Joseph; Bendele, Alison; Sookdeo, Cathleen; Nambiar, Bindu; Ewing, Patty; Armentano, Donna; Matthews, Gloria L

2015-01-16

Cathepsin K (catK) expression is increased in cartilage, bone and synovium during osteoarthritis (OA). To study the role of catK expression and elevated cathepsin activity in the synovium on cartilage destruction in established OA, we overexpressed cystatin C (cysC), a natural cysteine protease inhibitor, in the synovium of rabbit OA joints. The ability of cysC to inhibit activity of cathepsins in rabbit OA synovium lysates was tested in vitro using protease activity assay. In vivo, the tissue localization of recombinant adeno-associated virus (rAAV) with LacZ gene after intra-articular injection was determined by β-galactosidase staining of rabbit joints 4 weeks later. To inhibit cathepsin activity in the synovium, a rAAV2-encoding cysC was delivered intra-articularly into rabbit joints 4 weeks after OA was induced by anterior cruciate ligament transection (ACLT). Seven weeks postinjection, endogenous catK and cysC levels as well as the vector-derived cysC expression in the synovium of normal and OA joints were examined by RNA quantification. Synovial cathepsin activity and catK, catB and catL protein levels were determined by activity and Western blot analyses, respectively. Synovitis and cartilage degradation were evaluated by histopathological scoring. In vitro, the ability of cysC to efficiently inhibit activity of purified catK and OA-induced cathepsins in rabbit synovial lysates was demonstrated. In vivo, the intra-articular delivery of rAAV2/LacZ showed transduction of mostly synovium. Induction of OA in rabbit joints resulted in fourfold increase in catK mRNA compared to sham controls while no change was detected in endogenous cysC mRNA levels in the synovium. Protein levels for catK, catB and catL were also increased in the synovium with a concomitant fourfold increase in cathepsin activity. Joints treated with rAAV2/cysC showed both detection of vector genomes and vector-derived cysC transcripts in the synovium. Production of functional cysC by the vector was demonstrated by complete block of cathepsin activity in the synovium. However, this did not decrease synovitis, bone sclerosis or progression of cartilage degradation. Increased production of natural cathepsin inhibitor, cysC, in OA synovium does not alleviate synovitis or cartilage pathology during a preexisting OA.

Strategies to optimize capsid protein expression and single-stranded DNA formation of adeno-associated virus in Saccharomyces cerevisiae.

PubMed

Galli, A; Della Latta, V; Bologna, C; Pucciarelli, D; Cipriani, F; Backovic, A; Cervelli, T

2017-08-01

Adeno-associated virus type 2 (AAV) is a nonpathogenic parvovirus that is a promising tool for gene therapy. We aimed to construct plasmids for optimal expression and assembly of capsid proteins and evaluate adenovirus (Ad) protein effect on AAV single-stranded DNA (ssDNA) formation in Saccharomyces cerevisiae. Yeast expression plasmids have been developed in which the transcription of AAV capsid proteins (VP1,2,3) is driven by the constitutive ADH1 promoter or galactose-inducible promoters. Optimal VP1,2,3 expression was obtained from GAL1/10 bidirectional promoter. Moreover, we demonstrated that AAP is expressed in yeast and virus-like particles (VLPs) assembled inside the cell. Finally, the expression of two Ad proteins, E4orf6 and E1b55k, had no effect on AAV ssDNA formation. This study confirms that yeast is able to form AAV VLPs; however, capsid assembly and ssDNA formation are less efficient in yeast than in human cells. Moreover, the expression of Ad proteins did not affect AAV ssDNA formation. New manufacturing strategies for AAV-based gene therapy vectors (rAAV) are needed to reduce costs and time of production. Our study explores the feasibility of yeast as alternative system for rAAV production. © 2017 The Society for Applied Microbiology.

Overexpression of suppressor of cytokine signaling 3 in the arcuate nucleus of juvenile Phodopus sungorus alters seasonal body weight changes.

PubMed

Ganjam, Goutham K; Benzler, Jonas; Pinkenburg, Olaf; Boucsein, Alisa; Stöhr, Sigrid; Steger, Juliane; Culmsee, Carsten; Barrett, Perry; Tups, Alexander

2013-12-01

The profound seasonal cycle in body weight exhibited by the Djungarian hamster (Phodopus sungorus) is associated with the development of hypothalamic leptin resistance during long day photoperiod (LD, 16:8 h light dark cycle), when body weight is elevated relative to short day photoperiod (SD, 8:16 h light dark cycle). We previously have shown that this seasonal change in physiology is associated with higher levels of mRNA for the potent inhibitor of leptin signaling, suppressor of cytokine signaling-3 (SOCS3), in the arcuate nucleus (ARC) of LD hamsters relative to hamsters in SD. The alteration in SOCS3 gene expression preceded the body weight change suggesting that SOCS3 might be the molecular switch of seasonal body weight changes. To functionally characterize the role of SOCS3 in seasonal body weight regulation, we injected SOCS3 expressing recombinant adeno-associated virus type-2 (rAAV2-SOCS3) constructs into the ARC of leptin sensitive SD hamsters immediately after weaning. Hamsters that received rAAV2 expressing enhanced green fluorescent protein (rAAV2-EGFP) served as controls. ARC-directed SOCS3 overexpression led to a significant increase in body weight over a period of 12 weeks without fully restoring the LD phenotype. This increase was partially due to elevated brown and white adipose tissue mass. Gene expression of pro-opiomelanocortin was increased while thyroid hormone converting enzyme DIO3 mRNA levels were reduced in SD hamsters with SOCS3 overexpression. In conclusion, our data suggest that ARC-directed SOCS3 overexpression partially overcomes the profound seasonal body weight cycle exhibited by the hamster which is associated with altered pro-opiomelanocortin and DIO3 gene expression.

Promise and problems associated with the use of recombinant AAV for the delivery of anti-HIV antibodies

PubMed Central

Fuchs, Sebastian P; Desrosiers, Ronald C

2016-01-01

Attempts to elicit antibodies with potent neutralizing activity against a broad range of human immunodeficiency virus (HIV) isolates have so far proven unsuccessful. Long-term delivery of monoclonal antibodies (mAbs) with such activity is a creative alternative that circumvents the need for an immune response and has the potential for creating a long-lasting sterilizing barrier against HIV. This approach is made possible by an incredible array of potent broadly neutralizing antibodies (bnAbs) that have been identified over the last several years. Recombinant adeno-associated virus (rAAV) vectors are ideally suited for long-term delivery for a variety of reasons. The only products made from rAAV are derived from the transgenes that are put into it; as long as those products are not viewed as foreign, expression from muscle tissue may continue for decades. Thus, use of rAAV to achieve long-term delivery of anti-HIV mAbs with potent neutralizing activity against a broad range of HIV-1 isolates is emerging as a promising concept for the prevention or treatment of HIV-1 infection in humans. Experiments in mice and monkeys that have demonstrated protective efficacy against AIDS virus infection have raised hopes for the promise of this approach. However, all published experiments in monkeys have encountered unwanted immune responses to the AAV-delivered antibody, and these immune responses appear to limit the levels of delivered antibody that can be achieved. In this review, we highlight the promise of rAAV-mediated antibody delivery for the prevention or treatment of HIV infection in humans, but we also discuss the obstacles that will need to be understood and solved in order for the promise of this approach to be realized. PMID:28197421

Gene Transfer of ZMapp Antibodies Mediated by Recombinant Adeno-Associated Virus Protects Against Ebola Infections.

PubMed

Robert, Marc-André; Nassoury, Nasha; Chahal, Parminder S; Venne, Marie-Hélène; Racine, Trina; Qiu, Xiangguo; Kobinger, Gary; Kamen, Amine; Gilbert, Rénald; Gaillet, Bruno

2018-04-01

Vectored delivery of the ZMapp antibody cocktail (c2G4, c4G7, and c13C6) by using recombinant adeno-associated viruses (rAAVs) could be useful for preventive immunization against Ebola virus infections because rAAVs can generate long-term antibody expression. Three rAAVs (serotype 9) encoding chimeric ZMapp antibodies were produced by triple-plasmid transfection up to 10 L-scale in WAVE bioreactors using HEK293 cells grown in suspension/serum-free conditions. Efficacy of AAV-c2G4 via intravenous (i.v.), intramuscular (i.m.), and intranasal (i.n.) routes of administration was evaluated in mice with two different doses of 2.7 × 10 10 and 13.0 × 10 10 vector genomes (vg). The best protective efficacies after Ebola challenge were obtained with the i.v. and i.m. routes. Serum concentrations of ZMapp antibodies positively correlated with survivability. Efficacy of the rAAV-ZMapp cocktail was then evaluated at a higher dose of 30.0 × 10 10 vg. It conferred a more robust protection (90% i.v. and 60% i.m.) than rAAV-c4G7 (30%) and rAAV-c13C6 (70%), both administered separately at the same dose. Delivery of rAAV-c2G4 alone achieved up to 100% protection (100% i.v. and 90% i.m.) at the same dose. In conclusion, the preventive treatment was effective in mice. However, no advantage was observed for using the rAAV-ZMapp cocktail in comparison to the utilization of the single rAAV-c2G4.

Characterization of a Recombinant Adeno-Associated Virus Type 2 Reference Standard Material

PubMed Central

Lock, Martin; McGorray, Susan; Auricchio, Alberto; Ayuso, Eduard; Beecham, E. Jeffrey; Blouin-Tavel, Véronique; Bosch, Fatima; Bose, Mahuya; Byrne, Barry J.; Caton, Tina; Chiorini, John A.; Chtarto, Abdelwahed; Clark, K. Reed; Conlon, Thomas; Darmon, Christophe; Doria, Monica; Douar, Anne; Flotte, Terence R.; Francis, Joyce D.; Francois, Achille; Giacca, Mauro; Korn, Michael T.; Korytov, Irina; Leon, Xavier; Leuchs, Barbara; Lux, Gabriele; Melas, Catherine; Mizukami, Hiroaki; Moullier, Philippe; Müller, Marcus; Ozawa, Keiya; Philipsberg, Tina; Poulard, Karine; Raupp, Christina; Rivière, Christel; Roosendaal, Sigrid D.; Samulski, R. Jude; Soltys, Steven M.; Surosky, Richard; Tenenbaum, Liliane; Thomas, Darby L.; van Montfort, Bart; Veres, Gabor; Wright, J. Fraser; Xu, Yili; Zelenaia, Olga; Zentilin, Lorena

2010-01-01

Abstract A recombinant adeno-associated virus serotype 2 Reference Standard Material (rAAV2 RSM) has been produced and characterized with the purpose of providing a reference standard for particle titer, vector genome titer, and infectious titer for AAV2 gene transfer vectors. Production and purification of the reference material were carried out by helper virus–free transient transfection and chromatographic purification. The purified bulk material was vialed, confirmed negative for microbial contamination, and then distributed for characterization along with standard assay protocols and assay reagents to 16 laboratories worldwide. Using statistical transformation and modeling of the raw data, mean titers and confidence intervals were determined for capsid particles ({X}, 9.18 × 1011 particles/ml; 95% confidence interval [CI], 7.89 × 1011 to 1.05 × 1012 particles/ml), vector genomes ({X}, 3.28 × 1010 vector genomes/ml; 95% CI, 2.70 × 1010 to 4.75 × 1010 vector genomes/ml), transducing units ({X}, 5.09 × 108 transducing units/ml; 95% CI, 2.00 × 108 to 9.60 × 108 transducing units/ml), and infectious units ({X}, 4.37 × 109 TCID50 IU/ml; 95% CI, 2.06 × 109 to 9.26 × 109 TCID50 IU/ml). Further analysis confirmed the identity of the reference material as AAV2 and the purity relative to nonvector proteins as greater than 94%. One obvious trend in the quantitative data was the degree of variation between institutions for each assay despite the relatively tight correlation of assay results within an institution. This relatively poor degree of interlaboratory precision and accuracy was apparent even though attempts were made to standardize the assays by providing detailed protocols and common reagents. This is the first time that such variation between laboratories has been thoroughly documented and the findings emphasize the need in the field for universal reference standards. The rAAV2 RSM has been deposited with the American Type Culture Collection and is available to the scientific community to calibrate laboratory-specific internal titer standards. Anticipated uses of the rAAV2 RSM are discussed. PMID:20486768

Production of Recombinant Adeno-associated Virus Vectors Using Suspension HEK293 Cells and Continuous Harvest of Vector From the Culture Media for GMP FIX and FLT1 Clinical Vector

PubMed Central

Grieger, Joshua C; Soltys, Stephen M; Samulski, Richard Jude

2016-01-01

Adeno-associated virus (AAV) has shown great promise as a gene therapy vector in multiple aspects of preclinical and clinical applications. Many developments including new serotypes as well as self-complementary vectors are now entering the clinic. With these ongoing vector developments, continued effort has been focused on scalable manufacturing processes that can efficiently generate high-titer, highly pure, and potent quantities of rAAV vectors. Utilizing the relatively simple and efficient transfection system of HEK293 cells as a starting point, we have successfully adapted an adherent HEK293 cell line from a qualified clinical master cell bank to grow in animal component-free suspension conditions in shaker flasks and WAVE bioreactors that allows for rapid and scalable rAAV production. Using the triple transfection method, the suspension HEK293 cell line generates greater than 1 × 105 vector genome containing particles (vg)/cell or greater than 1 × 1014 vg/l of cell culture when harvested 48 hours post-transfection. To achieve these yields, a number of variables were optimized such as selection of a compatible serum-free suspension media that supports both growth and transfection, selection of a transfection reagent, transfection conditions and cell density. A universal purification strategy, based on ion exchange chromatography methods, was also developed that results in high-purity vector preps of AAV serotypes 1–6, 8, 9 and various chimeric capsids tested. This user-friendly process can be completed within 1 week, results in high full to empty particle ratios (>90% full particles), provides postpurification yields (>1 × 1013 vg/l) and purity suitable for clinical applications and is universal with respect to all serotypes and chimeric particles. To date, this scalable manufacturing technology has been utilized to manufacture GMP phase 1 clinical AAV vectors for retinal neovascularization (AAV2), Hemophilia B (scAAV8), giant axonal neuropathy (scAAV9), and retinitis pigmentosa (AAV2), which have been administered into patients. In addition, we report a minimum of a fivefold increase in overall vector production by implementing a perfusion method that entails harvesting rAAV from the culture media at numerous time-points post-transfection. PMID:26437810

AAV-mediated RLBP1 gene therapy improves the rate of dark adaptation in Rlbp1 knockout mice

PubMed Central

Choi, Vivian W; Bigelow, Chad E; McGee, Terri L; Gujar, Akshata N; Li, Hui; Hanks, Shawn M; Vrouvlianis, Joanna; Maker, Michael; Leehy, Barrett; Zhang, Yiqin; Aranda, Jorge; Bounoutas, George; Demirs, John T; Yang, Junzheng; Ornberg, Richard; Wang, Yu; Martin, Wendy; Stout, Kelly R; Argentieri, Gregory; Grosenstein, Paul; Diaz, Danielle; Turner, Oliver; Jaffee, Bruce D; Police, Seshidhar R; Dryja, Thaddeus P

2015-01-01

Recessive mutations in RLBP1 cause a form of retinitis pigmentosa in which the retina, before its degeneration leads to blindness, abnormally slowly recovers sensitivity after exposure to light. To develop a potential gene therapy for this condition, we tested multiple recombinant adeno-associated vectors (rAAVs) composed of different promoters, capsid serotypes, and genome conformations. We generated rAAVs in which sequences from the promoters of the human RLBP1, RPE65, or BEST1 genes drove the expression of a reporter gene (green fluorescent protein). A promoter derived from the RLBP1 gene mediated expression in the retinal pigment epithelium and Müller cells (the intended target cell types) at qualitatively higher levels than in other retinal cell types in wild-type mice and monkeys. With this promoter upstream of the coding sequence of the human RLBP1 gene, we compared the potencies of vectors with an AAV2 versus an AAV8 capsid in transducing mouse retinas, and we compared vectors with a self-complementary versus a single-stranded genome. The optimal vector (scAAV8-pRLBP1-hRLBP1) had serotype 8 capsid and a self-complementary genome. Subretinal injection of scAAV8-pRLBP1-hRLBP1 in Rlbp1 nullizygous mice improved the rate of dark adaptation based on scotopic (rod-plus-cone) and photopic (cone) electroretinograms (ERGs). The effect was still present after 1 year. PMID:26199951

rAAV-compatible MiniPromoters for restricted expression in the brain and eye.

PubMed

de Leeuw, Charles N; Korecki, Andrea J; Berry, Garrett E; Hickmott, Jack W; Lam, Siu Ling; Lengyell, Tess C; Bonaguro, Russell J; Borretta, Lisa J; Chopra, Vikramjit; Chou, Alice Y; D'Souza, Cletus A; Kaspieva, Olga; Laprise, Stéphanie; McInerny, Simone C; Portales-Casamar, Elodie; Swanson-Newman, Magdalena I; Wong, Kaelan; Yang, George S; Zhou, Michelle; Jones, Steven J M; Holt, Robert A; Asokan, Aravind; Goldowitz, Daniel; Wasserman, Wyeth W; Simpson, Elizabeth M

2016-05-10

Small promoters that recapitulate endogenous gene expression patterns are important for basic, preclinical, and now clinical research. Recently, there has been a promising revival of gene therapy for diseases with unmet therapeutic needs. To date, most gene therapies have used viral-based ubiquitous promoters-however, promoters that restrict expression to target cells will minimize off-target side effects, broaden the palette of deliverable therapeutics, and thereby improve safety and efficacy. Here, we take steps towards filling the need for such promoters by developing a high-throughput pipeline that goes from genome-based bioinformatic design to rapid testing in vivo. For much of this work, therapeutically interesting Pleiades MiniPromoters (MiniPs; ~4 kb human DNA regulatory elements), previously tested in knock-in mice, were "cut down" to ~2.5 kb and tested in recombinant adeno-associated virus (rAAV), the virus of choice for gene therapy of the central nervous system. To evaluate our methods, we generated 29 experimental rAAV2/9 viruses carrying 19 different MiniPs, which were injected intravenously into neonatal mice to allow broad unbiased distribution, and characterized in neural tissues by X-gal immunohistochemistry for icre, or immunofluorescent detection of GFP. The data showed that 16 of the 19 (84 %) MiniPs recapitulated the expression pattern of their design source. This included expression of: Ple67 in brain raphe nuclei; Ple155 in Purkinje cells of the cerebellum, and retinal bipolar ON cells; Ple261 in endothelial cells of brain blood vessels; and Ple264 in retinal Müller glia. Overall, the methodology and MiniPs presented here represent important advances for basic and preclinical research, and may enable a paradigm shift in gene therapy.

High density recombinant AAV particles are competent vectors for in vivo transduction

USDA-ARS?s Scientific Manuscript database

Recombinant adeno-associated viral (rAAV) vectors have recently achieved clinical successes in human gene therapy. However, the commonly observed heavier particles found in AAV preparations have traditionally been ignored due to its low in vitro infectivity. In this study, we systemically compared t...

The effect of surface demineralization of cortical bone allograft on the properties of recombinant adeno-associated virus coatings.

PubMed

Yazici, Cemal; Yanoso, Laura; Xie, Chao; Reynolds, David G; Samulski, R Jude; Samulski, Jade; Yannariello-Brown, Judith; Gertzman, Arthur A; Zhang, Xinping; Awad, Hani A; Schwarz, Edward M

2008-10-01

Freeze-dried recombinant adeno-associated virus (rAAV) coated structural allografts have emerged as an approach to engender necrotic cortical bone with host factors that will persist for weeks following surgery to facilitate revascularization, osteointegration, and remodeling. However, one major limitation is the nonporous cortical surface that prohibits uniform distribution of the rAAV coating prior to freeze-drying. To overcome this we have developed a demineralization method to increase surface absorbance while retaining the structural integrity of the allograft. Demineralized bone wafers (DBW) made from human femoral allograft rings demonstrated a significant 21.1% (73.6+/-3.9% versus 52.5+/-2.6%; p<0.001) increase in percent surface area coating versus mineralized controls. Co-incubation of rAAV-luciferase (rAAV-Luc) coated DBW with a monolayer of C3H10T1/2 cells in culture led to peak luciferase levels that were not significantly different from soluble rAAV-Luc controls (p>0.05), although the peaks occurred at 60h and 12h, respectively. To assess the transduction efficiency of rAAV-Luc coated DBW in vivo, we first performed a dose response with allografts containing 10(7), 10(9) or 10(10) particles that were surgically implanted into the quadriceps of mice, and assayed by in vivo bioluminescence imaging (BLI) on days 1, 3, 5, 7, 10, 14, and 21. The results demonstrated a dose response in which the DBW coated with 10(10) rAAV-Luc particles achieved peak gene expression levels on day 3, which persisted until day 21, and was significantly greater than the 10(7) dose throughout this time period (p<0.01). A direct comparison of mineralized versus DBW coated with 10(10) rAAV-Luc particles failed to demonstrate any significant differences in transduction kinetics or efficiency in vivo. Thus, surface demineralization of human cortical bone allograft increases its absorbance for uniform rAAV coating, without affecting vector transduction efficiency.

Overexpression of the Steroidogenic Enzyme Cytochrome P450 Side Chain Cleavage in the Ventral Tegmental Area Increases 3α,5α-THP and Reduces Long-Term Operant Ethanol Self-Administration

PubMed Central

Cook, Jason B.; Werner, David F.; Maldonado-Devincci, Antoniette M.; Leonard, Maggie N.; Fisher, Kristen R.; O'Buckley, Todd K.; Porcu, Patrizia; McCown, Thomas J.; Besheer, Joyce; Hodge, Clyde W.

2014-01-01

Neuroactive steroids are endogenous neuromodulators capable of altering neuronal activity and behavior. In rodents, systemic administration of endogenous or synthetic neuroactive steroids reduces ethanol self-administration. We hypothesized this effect arises from actions within mesolimbic brain regions that we targeted by viral gene delivery. Cytochrome P450 side chain cleavage (P450scc) converts cholesterol to pregnenolone, the rate-limiting enzymatic reaction in neurosteroidogenesis. Therefore, we constructed a recombinant adeno-associated serotype 2 viral vector (rAAV2), which drives P450scc expression and neuroactive steroid synthesis. The P450scc-expressing vector (rAAV2-P450scc) or control GFP-expressing vector (rAAV2-GFP) were injected bilaterally into the ventral tegmental area (VTA) or nucleus accumbens (NAc) of alcohol preferring (P) rats trained to self-administer ethanol. P450scc overexpression in the VTA significantly reduced ethanol self-administration by 20% over the 3 week test period. P450scc overexpression in the NAc, however, did not alter ethanol self-administration. Locomotor activity was unaltered by vector administration to either region. P450scc overexpression produced a 36% increase in (3α,5α)-3-hydroxypregnan-20-one (3α,5α-THP, allopregnanolone)-positive cells in the VTA, but did not increase 3α,5α-THP immunoreactivity in NAc. These results suggest that P450scc overexpression and the resultant increase of 3α,5α-THP-positive cells in the VTA reduces ethanol reinforcement. 3α,5α-THP is localized to neurons in the VTA, including tyrosine hydroxylase neurons, but not astrocytes. Overall, the results demonstrate that using gene delivery to modulate neuroactive steroids shows promise for examining the neuronal mechanisms of moderate ethanol drinking, which could be extended to other behavioral paradigms and neuropsychiatric pathology. PMID:24760842

Overexpression of the steroidogenic enzyme cytochrome P450 side chain cleavage in the ventral tegmental area increases 3α,5α-THP and reduces long-term operant ethanol self-administration.

PubMed

Cook, Jason B; Werner, David F; Maldonado-Devincci, Antoniette M; Leonard, Maggie N; Fisher, Kristen R; O'Buckley, Todd K; Porcu, Patrizia; McCown, Thomas J; Besheer, Joyce; Hodge, Clyde W; Morrow, A Leslie

2014-04-23

Neuroactive steroids are endogenous neuromodulators capable of altering neuronal activity and behavior. In rodents, systemic administration of endogenous or synthetic neuroactive steroids reduces ethanol self-administration. We hypothesized this effect arises from actions within mesolimbic brain regions that we targeted by viral gene delivery. Cytochrome P450 side chain cleavage (P450scc) converts cholesterol to pregnenolone, the rate-limiting enzymatic reaction in neurosteroidogenesis. Therefore, we constructed a recombinant adeno-associated serotype 2 viral vector (rAAV2), which drives P450scc expression and neuroactive steroid synthesis. The P450scc-expressing vector (rAAV2-P450scc) or control GFP-expressing vector (rAAV2-GFP) were injected bilaterally into the ventral tegmental area (VTA) or nucleus accumbens (NAc) of alcohol preferring (P) rats trained to self-administer ethanol. P450scc overexpression in the VTA significantly reduced ethanol self-administration by 20% over the 3 week test period. P450scc overexpression in the NAc, however, did not alter ethanol self-administration. Locomotor activity was unaltered by vector administration to either region. P450scc overexpression produced a 36% increase in (3α,5α)-3-hydroxypregnan-20-one (3α,5α-THP, allopregnanolone)-positive cells in the VTA, but did not increase 3α,5α-THP immunoreactivity in NAc. These results suggest that P450scc overexpression and the resultant increase of 3α,5α-THP-positive cells in the VTA reduces ethanol reinforcement. 3α,5α-THP is localized to neurons in the VTA, including tyrosine hydroxylase neurons, but not astrocytes. Overall, the results demonstrate that using gene delivery to modulate neuroactive steroids shows promise for examining the neuronal mechanisms of moderate ethanol drinking, which could be extended to other behavioral paradigms and neuropsychiatric pathology.

Remodelling of human osteoarthritic cartilage by FGF-2, alone or combined with Sox9 via rAAV gene transfer.

PubMed

Cucchiarini, Magali; Terwilliger, Ernest F; Kohn, Dieter; Madry, Henning

2009-08-01

Compensating for the loss of extracellular cartilage matrix, as well as counteracting the alterations of the chondrocyte phenotype in osteoarthritis are of key importance to develop effective therapeutic strategies against this disorder. In the present study, we analysed the benefits of applying a potent gene combination to remodel human osteoarthritic (OA) cartilage. We employed the promising recombinant adeno-associated virus (rAAV) vector to deliver the mitogenic fibroblast growth factor 2 (FGF-2) factor, alone or simultaneously with the transcription factor Sox9 as a key activator of matrix synthesis, to human normal and OA articular chondrocytes. We evaluated the effects of single (FGF-2) or combined (FGF-2/SOX9) transgene expression upon the regenerative activities of chondrocytes in three dimensional cultures in vitro and in cartilage explants in situ. Single overexpression of FGF-2 enhanced the survival and proliferation of both normal and OA chondrocytes, without stimulating the matrix synthetic processes in the increased pools of cells. The mitogenic properties of FGF-2 were maintained when SOX9 was co-overexpressed and concomitant with an increase in the production of proteoglycans and type-II collagen, suggesting that the transcription factor was capable of counterbalancing the effects of FGF-2 on matrix accumulation. Also important, expression of type-X collagen, a marker of hypertrophy strongly decreased following treatment by the candidate vectors. Most remarkably, the levels of activities achieved in co-treated human OA cartilage were similar to or higher than those observed in normal cartilage. The present findings show that combined expression of candidate factors in OA cartilage can re-establish key features of normal cartilage and prevent the pathological shift of metabolic homeostasis. These data provide further motivation to develop coupled gene transfer approaches via rAAV for the treatment of human OA.

Development of recombinant adeno-associated virus vectors carrying small interfering RNA (shHec1)-mediated depletion of kinetochore Hec1 protein in tumor cells.

PubMed

Li, L; Yang, L; Scudiero, D A; Miller, S A; Yu, Z-X; Stukenberg, P T; Shoemaker, R H; Kotin, R M

2007-05-01

Transcript depletion using small interfering RNA (siRNA) technology represents a potentially valuable technique for the treatment of cancer. However, delivering therapeutic quantities of siRNA into solid tumors by chemical transfection is not feasible, whereas viral vectors efficiently transduce many human tumor cell lines. Yet producing sufficient quantities of viral vectors that elicit acute and selective cytotoxicity remains a major obstacle for preclinical and clinical trials. Using the invertebrate Spodoptera frugiperda (Sf9) cell line, we were able to produce high titer stocks of cytotoxic recombinant adeno-associated virus (rAAV) that express short hairpin RNA (shRNA) and that efficiently deplete Hec1 (highly expressed in cancer 1), or Kntc2 (kinetochore-associated protein 2), a kinetochore protein directly involved in kinetochore microtubule interactions, chromosome congression and spindle checkpoint signaling. Depletion of Hec1 protein results in persistent spindle checkpoint activation followed by cell death. Because Hec1 expression and activity are only present in mitotic cells, non-dividing cells were not affected by rAAV treatment. On the basis of the results of screening 56 human tumor cell lines with three different serotype vectors, we used a tumor xenograft model to test the effects in vivo. The effects of the shHec1 vector were evident in sectioned and stained tumors. The experiments with rAAV-shRNA vectors demonstrate the utility of producing vectors in invertebrate cells to obtain sufficient concentrations and quantities for solid tumor therapy. This addresses an important requirement for cancer gene therapy, to produce cytotoxic vectors in sufficient quantities and concentrations to enable quantitative transduction and selective killing of solid tumor cells.

Protein-Anchoring Therapy of Biglycan for Mdx Mouse Model of Duchenne Muscular Dystrophy.

PubMed

Ito, Mikako; Ehara, Yuka; Li, Jin; Inada, Kosuke; Ohno, Kinji

2017-05-01

Duchenne muscular dystrophy (DMD) is a devastating muscle disease caused by loss-of-function mutations in DMD encoding dystrophin. No rational therapy is currently available. Utrophin is a paralog of dystrophin and is highly expressed at the neuromuscular junction. In mdx mice, utrophin is naturally upregulated throughout the muscle fibers, which mitigates muscular dystrophy. Protein-anchoring therapy was previously reported, in which a recombinant extracellular matrix (ECM) protein is delivered to and anchored to a specific target using its proprietary binding domains. Being prompted by a report that intramuscular and intraperitoneal injection of an ECM protein, biglycan, upregulates expression of utrophin and ameliorates muscle pathology in mdx mice, protein-anchoring therapy was applied to mdx mice. Recombinant adeno-associated virus serotype 8 (rAAV8) carrying hBGN encoding human biglycan was intravenously injected into 5-week-old mdx mice. The rAAV8-hBGN treatment improved motor deficits and decreased plasma creatine kinase activities. In muscle sections of treated mice, the number of central myonuclei and the distribution of myofiber sizes were improved. The treated mice increased gene expressions of utrophin and β1-syntrophin, as well as protein expressions of biglycan, utrophin, γ-sarcoglycan, dystrobrevin, and α1-syntrophin. The expression of hBGN in the skeletal muscle of the treated mice was 1.34-fold higher than that of the native mouse Bgn (mBgn). The low transduction efficiency and improved motor functions suggest that biglycan expressed in a small number of muscle fibers was likely to have been secreted and anchored to the cell surface throughout the whole muscular fibers. It is proposed that the protein-anchoring strategy can be applied not only to deficiency of an ECM protein as previously reported, but also to augmentation of a naturally induced ECM protein.

Methods of treating Parkinson's disease using viral vectors

DOEpatents

Bankiewicz, Krys; Cunningham, Janet

2012-11-13

Methods of delivering viral vectors, particularly recombinant AAV virions, to the central nervous system (CNS) are provided for the treatment of CNS disorders, particularly those disorders which involve the neurotransmitter dopamine. The methods entail providing rAAV virions that comprise a transgene encoding aromatic amino acid decarboxylase (AADC) and administering the virions to the brain of a mammal using a non-manual pump.

Ribosomal DNA Integrating rAAV-rDNA Vectors Allow for Stable Transgene Expression

PubMed Central

Lisowski, Leszek; Lau, Ashley; Wang, Zhongya; Zhang, Yue; Zhang, Feijie; Grompe, Markus; Kay, Mark A

2012-01-01

Although recombinant adeno-associated virus (rAAV) vectors are proving to be efficacious in clinical trials, the episomal character of the delivered transgene restricts their effectiveness to use in quiescent tissues, and may not provide lifelong expression. In contrast, integrating vectors enhance the risk of insertional mutagenesis. In an attempt to overcome both of these limitations, we created new rAAV-rDNA vectors, with an expression cassette flanked by ribosomal DNA (rDNA) sequences capable of homologous recombination into genomic rDNA. We show that after in vivo delivery the rAAV-rDNA vectors integrated into the genomic rDNA locus 8–13 times more frequently than control vectors, providing an estimate that 23–39% of the integrations were specific to the rDNA locus. Moreover, a rAAV-rDNA vector containing a human factor IX (hFIX) expression cassette resulted in sustained therapeutic levels of serum hFIX even after repeated manipulations to induce liver regeneration. Because of the relative safety of integration in the rDNA locus, these vectors expand the usage of rAAV for therapeutics requiring long-term gene transfer into dividing cells. PMID:22990671

Combined antitumor gene therapy with herpes simplex virus-thymidine kinase and short hairpin RNA specific for mammalian target of rapamycin.

PubMed

Woo, Ha-Na; Lee, Won Il; Kim, Ji Hyun; Ahn, Jeonghyun; Han, Jeong Hee; Lim, Sue Yeon; Lee, Won Woo; Lee, Heuiran

2015-12-01

A proof-of-concept study is presented using dual gene therapy that employed a small hairpin RNA (shRNA) specific for mammalian target of rapamycin (mTOR) and a herpes simplex virus-thymidine kinase (HSV-TK) gene to inhibit the growth of tumors. Recombinant adeno-associated virus (rAAV) vectors containing a mutant TK gene (sc39TK) were transduced into HeLa cells, and the prodrug ganciclovir (GCV) was administered to establish a suicide gene-therapy strategy. Additionally, rAAV vectors expressing an mTOR-targeted shRNA were employed to suppress mTOR-dependent tumor growth. GCV selectively induced death in tumor cells expressing TK, and the mTOR-targeted shRNA altered the cell cycle to impair tumor growth. Combining the TK-GCV system with mTOR inhibition suppressed tumor growth to a greater extent than that achieved with either treatment alone. Furthermore, HSV-TK expression and mTOR inhibition did not mutually interfere with each other. In conclusion, gene therapy that combines the TK-GCV system and mTOR inhibition shows promise as a novel strategy for cancer therapy.

Gene delivery to skeletal muscle results in sustained expression and systemic delivery of a therapeutic protein.

PubMed

Kessler, P D; Podsakoff, G M; Chen, X; McQuiston, S A; Colosi, P C; Matelis, L A; Kurtzman, G J; Byrne, B J

1996-11-26

Somatic gene therapy has been proposed as a means to achieve systemic delivery of therapeutic proteins. However, there is limited evidence that current methods of gene delivery can practically achieve this goal. In this study, we demonstrate that, following a single intramuscular administration of a recombinant adeno-associated virus (rAAV) vector containing the beta-galactosidase (AAV-lacZ) gene into adult BALB/c mice, protein expression was detected in myofibers for at least 32 weeks. A single intramuscular administration of an AAV vector containing a gene for human erythropoietin (AAV-Epo) into mice resulted in dose-dependent secretion of erythropoietin and corresponding increases in red blood cell production that persisted for up to 40 weeks. Primary human myotubes transduced in vitro with the AAV-Epo vector also showed dose-dependent production of Epo. These results demonstrate that rAAV vectors are able to transduce skeletal muscle and are capable of achieving sustained expression and systemic delivery of a therapeutic protein following a single intramuscular administration. Gene therapy using AAV vectors may provide a practical strategy for the treatment of inherited and acquired protein deficiencies.

Gene delivery to skeletal muscle results in sustained expression and systemic delivery of a therapeutic protein

PubMed Central

Kessler, Paul D.; Podsakoff, Gregory M.; Chen, Xiaojuan; McQuiston, Susan A.; Colosi, Peter C.; Matelis, Laura A.; Kurtzman, Gary J.; Byrne, Barry J.

1996-01-01

Somatic gene therapy has been proposed as a means to achieve systemic delivery of therapeutic proteins. However, there is limited evidence that current methods of gene delivery can practically achieve this goal. In this study, we demonstrate that, following a single intramuscular administration of a recombinant adeno-associated virus (rAAV) vector containing the β-galactosidase (AAV-lacZ) gene into adult BALB/c mice, protein expression was detected in myofibers for at least 32 weeks. A single intramuscular administration of an AAV vector containing a gene for human erythropoietin (AAV-Epo) into mice resulted in dose-dependent secretion of erythropoietin and corresponding increases in red blood cell production that persisted for up to 40 weeks. Primary human myotubes transduced in vitro with the AAV-Epo vector also showed dose-dependent production of Epo. These results demonstrate that rAAV vectors are able to transduce skeletal muscle and are capable of achieving sustained expression and systemic delivery of a therapeutic protein following a single intramuscular administration. Gene therapy using AAV vectors may provide a practical strategy for the treatment of inherited and acquired protein deficiencies. PMID:8943064

[Anti-apoptosis and expression of microRNA-21 in rat myocardium during early ischemia-reperfusion injury].

PubMed

Yang, Qiong; Yang, Kan; Li, Anying; Tan, Wenpeng

2013-05-01

To observe the expression and anti-apoptosis of microRNA-21(miR-21) in rat myocardium during early ischemia-reperfusion injury (I/R). Sprague-Dawley rats were randomly divided into 5 groups: a control group (transfected with rAAV9-ZsGreen by coronary injection), a miR-21group (transfected rAAV9-ZsGreen-premiR- 21 by coronary injection), a sham group (open-chest only), an I/R group (I/R), and an I/ R+miR-21 (I/R after transfected rAAV9-ZsGreen-pre-miR-21 by coronary injection). Realtime PCR was used to assess the expression level of miR-21. Immunohistochemistry and Western blot were used to determine the expression of Bcl-2, Bax, caspase-3 and Bcl-2/Bax. MiR-21 was increased by 4.43 times in the miR-21 group (P<0.001). MiR-21 was downregulated in the ischemia zone after I/R compared with the sham group (P<0.05), but that in the non-ischemia zone was significantly increased compared with the sham group (P<0.01). MiR- 21 expression was decreased in the I/R group compared with that in the sham group at 1 h, 2 h and 6 h after I/R (P<0.05), and it was up-regulated in the I/R+miR-21 group at the same time point compared with the I/R group (P<0.01). The expression of Bcl-2, Bax, and caspase-3 was upregulated and Bcl-2/Bax was decreased in the ischemia zone in the I/R group and I/R+miR-21 group than the sham group(P<0.05). Compared with the I/R group, the expression of Bcl-2 and caspase-3 was down-regulated and Bcl-2/Bax was increased in the ischemia zone in the I/ R+miR-21 group (P<0.05). MiR-21 expression is down-regulated and cell apoptosis is increased in rat myocardium during early ischemia-reperfusion injury. Myocardial cell apoptosis may be alleviated by miR-21 over-expression.

Gene Transfer Corrects Acute GM2 Gangliosidosis—Potential Therapeutic Contribution of Perivascular Enzyme Flow

PubMed Central

Cachón-González, M Begoña; Wang, Susan Z; McNair, Rosamund; Bradley, Josephine; Lunn, David; Ziegler, Robin; Cheng, Seng H; Cox, Timothy M

2012-01-01

The GM2 gangliosidoses are fatal lysosomal storage diseases principally affecting the brain. Absence of β-hexosaminidase A and B activities in the Sandhoff mouse causes neurological dysfunction and recapitulates the acute Tay–Sachs (TSD) and Sandhoff diseases (SD) in infants. Intracranial coinjection of recombinant adeno-associated viral vectors (rAAV), serotype 2/1, expressing human β-hexosaminidase α (HEXA) and β (HEXB) subunits into 1-month-old Sandhoff mice gave unprecedented survival to 2 years and prevented disease throughout the brain and spinal cord. Classical manifestations of disease, including spasticity—as opposed to tremor-ataxia—were resolved by localized gene transfer to the striatum or cerebellum, respectively. Abundant biosynthesis of β-hexosaminidase isozymes and their global distribution via axonal, perivascular, and cerebrospinal fluid (CSF) spaces, as well as diffusion, account for the sustained phenotypic rescue—long-term protein expression by transduced brain parenchyma, choroid plexus epithelium, and dorsal root ganglia neurons supplies the corrective enzyme. Prolonged survival permitted expression of cryptic disease in organs not accessed by intracranial vector delivery. We contend that infusion of rAAV into CSF space and intraparenchymal administration by convection-enhanced delivery at a few strategic sites will optimally treat neurodegeneration in many diseases affecting the nervous system. PMID:22453766

Gene transfer corrects acute GM2 gangliosidosis--potential therapeutic contribution of perivascular enzyme flow.

PubMed

Cachón-González, M Begoña; Wang, Susan Z; McNair, Rosamund; Bradley, Josephine; Lunn, David; Ziegler, Robin; Cheng, Seng H; Cox, Timothy M

2012-08-01

The GM2 gangliosidoses are fatal lysosomal storage diseases principally affecting the brain. Absence of β-hexosaminidase A and B activities in the Sandhoff mouse causes neurological dysfunction and recapitulates the acute Tay-Sachs (TSD) and Sandhoff diseases (SD) in infants. Intracranial coinjection of recombinant adeno-associated viral vectors (rAAV), serotype 2/1, expressing human β-hexosaminidase α (HEXA) and β (HEXB) subunits into 1-month-old Sandhoff mice gave unprecedented survival to 2 years and prevented disease throughout the brain and spinal cord. Classical manifestations of disease, including spasticity-as opposed to tremor-ataxia-were resolved by localized gene transfer to the striatum or cerebellum, respectively. Abundant biosynthesis of β-hexosaminidase isozymes and their global distribution via axonal, perivascular, and cerebrospinal fluid (CSF) spaces, as well as diffusion, account for the sustained phenotypic rescue-long-term protein expression by transduced brain parenchyma, choroid plexus epithelium, and dorsal root ganglia neurons supplies the corrective enzyme. Prolonged survival permitted expression of cryptic disease in organs not accessed by intracranial vector delivery. We contend that infusion of rAAV into CSF space and intraparenchymal administration by convection-enhanced delivery at a few strategic sites will optimally treat neurodegeneration in many diseases affecting the nervous system.

Long-Term Effect of Gene Therapy on Leber’s Congenital Amaurosis

PubMed Central

Bainbridge, J.W.B.; Mehat, M.S.; Sundaram, V.; Robbie, S.J.; Barker, S.E.; Ripamonti, C.; Georgiadis, A.; Mowat, F.M.; Beattie, S.G.; Gardner, P.J.; Feathers, K.L.; Luong, V.A.; Yzer, S.; Balaggan, K.; Viswanathan, A.; de Ravel, T.J.L.; Casteels, I.; Holder, G.E.; Tyler, N.; Fitzke, F.W.; Weleber, R.G.; Nardini, M.; Moore, A.T.; Thompson, D.A.; Petersen-Jones, S.M.; Michaelides, M.; van den Born, L.I.; Stockman, A.; Smith, A.J.; Rubin, G.; Ali, R.R.

2015-01-01

BACKGROUND Mutations in RPE65 cause Leber’s congenital amaurosis, a progressive retinal degenerative disease that severely impairs sight in children. Gene therapy can result in modest improvements in night vision, but knowledge of its efficacy in humans is limited. METHODS We performed a phase 1–2 open-label trial involving 12 participants to evaluate the safety and efficacy of gene therapy with a recombinant adeno-associated virus 2/2 (rAAV2/2) vector carrying the RPE65 complementary DNA, and measured visual function over the course of 3 years. Four participants were administered a lower dose of the vector, and 8 were administered a higher dose. In a parallel study in dogs, we investigated the relationship among vector dose, visual function, and electroretinography (ERG) findings. RESULTS Improvements in retinal sensitivity were evident, to varying extents, in six participants for up to 3 years, peaking at 6 to 12 months after treatment and then declining. No associated improvement in retinal function was detected by means of ERG. Three participants had intraocular inflammation, and two had clinically significant deterioration of visual acuity. The reduction in central retinal thickness varied among participants. In dogs, RPE65 gene therapy with the same vector at lower doses improved vision-guided behavior, but only higher doses resulted in improvements in retinal function that were detectable with the use of ERG. CONCLUSIONS Gene therapy with rAAV2/2 RPE65 vector improved retinal sensitivity, albeit modestly and temporarily. Comparison with the results obtained in the dog model indicates that there is a species difference in the amount of RPE65 required to drive the visual cycle and that the demand for RPE65 in affected persons was not met to the extent required for a durable, robust effect. (Funded by the National Institute for Health Research and others; ClinicalTrials.gov number, NCT00643747.) PMID:25938638

Chondrogenic Differentiation Processes in Human Bone Marrow Aspirates Seeded in Three-Dimensional Woven Poly(ε-Caprolactone) Scaffolds Enhanced by rAAV-Mediated SOX9 Gene Transfer.

PubMed

Venkatesan, Jagadeesh Kumar; Moutos, Franklin T; Rey-Rico, Ana; Estes, Bradley T; Frisch, Janina; Schmitt, Gertrud; Madry, Henning; Guilak, Farshid; Cucchiarini, Magali

2018-05-02

Combining gene therapy approaches with tissue engineering procedures is an active area of translational research for the effective treatment of articular cartilage lesions, especially to target chondrogenic progenitor cells such as those derived from the bone marrow. Here, we evaluated the effect of genetically modifying concentrated human mesenchymal stem cells from bone marrow to induce chondrogenesis by recombinant adeno-associated viral (rAAV) vector gene transfer of the sex-determining region Y-type high-mobility group box 9 (SOX9) factor upon seeding in three-dimensional (3D) woven poly(ε-caprolactone) (PCL) scaffolds that provide mechanical properties mimicking those of native articular cartilage. Prolonged, effective SOX9 expression was reported in the constructs for at least 21 days, the longest time point evaluated, leading to enhanced metabolic and chondrogenic activities relative to the control conditions (reporter lacZ gene transfer or absence of vector treatment) but without affecting the proliferative activities in the samples. The application of the rAAV SOX9 vector also prevented undesirable hypertrophic and terminal differentiation in the seeded concentrates. As bone marrow is readily accessible during surgery, such findings reveal the therapeutic potential of providing rAAV-modified marrow concentrates within 3D woven PCL scaffolds for repair of focal cartilage lesions.

Developing protocols for recombinant adeno-associated virus-mediated gene therapy in space.

PubMed

Ohi, S

2000-07-01

With the advent of the era of International Space Station (ISS) and Mars exploration, it is important more than ever to develop means to cure genetic and acquired diseases, which include cancer and AIDS, for these diseases hamper human activities. Thus, our ultimate goal is to develop protocols for gene therapy, which are suitable to humans on the earth as well as in space. Specifically, we are trying to cure the hemoglobinopathies, beta-thalassemia (Cooley's anemia) and sickle cell anemia, by gene therapy. These well-characterized molecular diseases serve as models for developing ex vivo gene therapy, which would apply to other disorders as well. For example, the procedure may become directly relevant to treating astronauts for space-anemia, immune suppression and bone marrow derived tumors, e.g. leukemia. The adeno-associated virus serotype 2 (AAV2) is a non-pathogenic human parvovirus with broad host-range and tissue specificity. Exploiting these characteristics we have been developing protocols for recombinant AAV2 (rAAV)-based gene therapy. With the rAAV constructs and hematopoietic stem cell (HSC) culture systems in hand, we are currently attempting to cure the mouse model of beta-thalassemia [C57BL/6- Hbbth/Hbbth, Hb(d-minor)] by HSC transplantation (HST) as well as by gene therapy. This paper describes the current status of our rAAV-gene therapy research.

Virally delivered Channelrhodopsin-2 Safely and Effectively Restores Visual Function in Multiple Mouse Models of Blindness

PubMed Central

Doroudchi, M Mehdi; Greenberg, Kenneth P; Liu, Jianwen; Silka, Kimberly A; Boyden, Edward S; Lockridge, Jennifer A; Arman, A Cyrus; Janani, Ramesh; Boye, Shannon E; Boye, Sanford L; Gordon, Gabriel M; Matteo, Benjamin C; Sampath, Alapakkam P; Hauswirth, William W; Horsager, Alan

2011-01-01

Previous work established retinal expression of channelrhodopsin-2 (ChR2), an algal cation channel gated by light, restored physiological and behavioral visual responses in otherwise blind rd1 mice. However, a viable ChR2-based human therapy must meet several key criteria: (i) ChR2 expression must be targeted, robust, and long-term, (ii) ChR2 must provide long-term and continuous therapeutic efficacy, and (iii) both viral vector delivery and ChR2 expression must be safe. Here, we demonstrate the development of a clinically relevant therapy for late stage retinal degeneration using ChR2. We achieved specific and stable expression of ChR2 in ON bipolar cells using a recombinant adeno-associated viral vector (rAAV) packaged in a tyrosine-mutated capsid. Targeted expression led to ChR2-driven electrophysiological ON responses in postsynaptic retinal ganglion cells and significant improvement in visually guided behavior for multiple models of blindness up to 10 months postinjection. Light levels to elicit visually guided behavioral responses were within the physiological range of cone photoreceptors. Finally, chronic ChR2 expression was nontoxic, with transgene biodistribution limited to the eye. No measurable immune or inflammatory response was observed following intraocular vector administration. Together, these data indicate that virally delivered ChR2 can provide a viable and efficacious clinical therapy for photoreceptor disease-related blindness. PMID:21505421

MRI roadmap-guided transendocardial delivery of exon-skipping recombinant adeno-associated virus restores dystrophin expression in a canine model of Duchenne muscular dystrophy.

PubMed

Barbash, I M; Cecchini, S; Faranesh, A Z; Virag, T; Li, L; Yang, Y; Hoyt, R F; Kornegay, J N; Bogan, J R; Garcia, L; Lederman, R J; Kotin, R M

2013-03-01

Duchenne muscular dystrophy (DMD) cardiomyopathy patients currently have no therapeutic options. We evaluated catheter-based transendocardial delivery of a recombinant adeno-associated virus (rAAV) expressing a small nuclear U7 RNA (U7smOPT) complementary to specific cis-acting splicing signals. Eliminating specific exons restores the open reading frame resulting in translation of truncated dystrophin protein. To test this approach in a clinically relevant DMD model, golden retriever muscular dystrophy (GRMD) dogs received serotype 6 rAAV-U7smOPT via the intracoronary or transendocardial route. Transendocardial injections were administered with an injection-tipped catheter and fluoroscopic guidance using X-ray fused with magnetic resonance imaging (XFM) roadmaps. Three months after treatment, tissues were analyzed for DNA, RNA, dystrophin protein, and histology. Whereas intracoronary delivery did not result in effective transduction, transendocardial injections, XFM guidance, enabled 30±10 non-overlapping injections per animal. Vector DNA was detectable in all samples tested and ranged from <1 to >3000 vector genome copies per cell. RNA analysis, western blot analysis, and immunohistology demonstrated extensive expression of skipped RNA and dystrophin protein in the treated myocardium. Left ventricular function remained unchanged over a 3-month follow-up. These results demonstrated that effective transendocardial delivery of rAAV-U7smOPT was achieved using XFM. This approach restores an open reading frame for dystrophin in affected dogs and has potential clinical utility.

Humoral Immune Response After Intravitreal But Not After Subretinal AAV8 in Primates and Patients.

PubMed

Reichel, Felix F; Peters, Tobias; Wilhelm, Barbara; Biel, Martin; Ueffing, Marius; Wissinger, Bernd; Bartz-Schmidt, Karl U; Klein, Reinhild; Michalakis, Stylianos; Fischer, M Dominik

2018-04-01

To study longitudinal changes of anti-drug antibody (ADA) titers to recombinant adeno-associated virus serotype 8 (rAAV8) capsid epitopes in nonhuman primates (NHP) and patients. Three groups of six NHP each received subretinal injections (high dose: 1 × 1012 vector genomes [vg], low dose: 1 × 1011 vg, or vehicle only). Four additional animals received intravitreal injections of the high dose (1 × 1012 vg). Three patients received 1 × 1010 vg as subretinal injections. ELISA quantified ADA levels at baseline and 1, 2, 3, 7, 28, and 90 days after surgery in NHP and at baseline and 1, 3, and 6 months after surgery in patients. Two out of 22 animals lacked ADA titers at baseline and developed low ADA titers toward the end of the study. Titers in the low-dose group stayed constant, while two of six animals from the high-dose group developed titers that rose beyond the range of the assay. All animals from the intravitreal control group showed a rise in ADA titer by day 7 that peaked at day 28. Preliminary data from the clinical trial (NCT02610582) show no humoral immune response in patients following subretinal delivery of 1 × 1010 vg. No significant induction of ADA occurred in NHP when mimicking the clinical scenario of subretinal delivery with a clinical-grade rAAV8 and concomitant immunosuppression. Likewise, clinical data showed no humoral immune response in patients. In contrast, intravitreal delivery was associated with a substantial humoral immune response. Subretinal delivery might be superior to an intravitreal application regarding immunologic aspects.

Cre-dependent selection yields AAV variants for widespread gene transfer to the adult brain

PubMed Central

Deverman, Benjamin E.; Pravdo, Piers L.; Simpson, Bryan P.; Kumar, Sripriya Ravindra; Chan, Ken Y.; Banerjee, Abhik; Wu, Wei-Li; Yang, Bin; Huber, Nina; Pasca, Sergiu P.; Gradinaru, Viviana

2015-01-01

Recombinant adeno-associated viruses (rAAVs) are commonly used vehicles for in vivo gene transfer1-6. However, the tropism repertoire of naturally occurring AAVs is limited, prompting a search for novel AAV capsids with desired characteristics7-13. Here we describe a capsid selection method, called Cre-recombination-based AAV targeted evolution (CREATE), that enables the development of AAV capsids that more efficiently transduce defined Cre-expressing cell populations in vivo. We use CREATE to generate AAV variants that efficiently and widely transduce the adult mouse central nervous system (CNS) after intravenous injection. One variant, AAV-PHP.B, transfers genes throughout the CNS with an efficiency that is at least 40-fold greater than that of the current standard, AAV914-17, and transduces the majority of astrocytes and neurons across multiple CNS regions. In vitro, it transduces human neurons and astrocytes more efficiently than does AAV9, demonstrating the potential of CREATE to produce customized AAV vectors for biomedical applications. PMID:26829320

AAV-CRISPR/Cas9-Mediated Depletion of VEGFR2 Blocks Angiogenesis In Vitro.

PubMed

Wu, Wenyi; Duan, Yajian; Ma, Gaoen; Zhou, Guohong; Park-Windhol, Cindy; D'Amore, Patricia A; Lei, Hetian

2017-12-01

Pathologic angiogenesis is a component of many diseases, including neovascular age-related macular degeneration, proliferation diabetic retinopathy, as well as tumor growth and metastasis. The purpose of this project was to examine whether the system of adeno-associated viral (AAV)-mediated CRISPR (clustered regularly interspaced short palindromic repeats)-associated endonuclease (Cas)9 can be used to deplete expression of VEGF receptor 2 (VEGFR2) in human vascular endothelial cells in vitro and thus suppress its downstream signaling events. The dual AAV system of CRISPR/Cas9 from Streptococcus pyogenes (AAV-SpGuide and -SpCas9) was adapted to edit genomic VEGFR2 in primary human retinal microvascular endothelial cells (HRECs). In this system, the endothelial-specific promoter for intercellular adhesion molecule 2 (ICAM2) was cloned into the dual AAV vectors of SpGuide and SpCas9 for driving expression of green fluorescence protein (GFP) and SpCas9, respectively. These two AAV vectors were applied to production of recombinant AAV serotype 5 (rAAV5), which were used to infect HRECs for depletion of VEGFR2. Protein expression was determined by Western blot; and cell proliferation, migration, as well as tube formation were examined. AAV5 effectively infected vascular endothelial cells (ECs) and retinal pigment epithelial (RPE) cells; the ICAM2 promoter drove expression of GFP and SpCas9 in HRECs, but not in RPE cells. The results showed that the rAAV5-CRISPR/Cas9 depleted VEGFR2 by 80% and completely blocked VEGF-induced activation of Akt, and proliferation, migration as well as tube formation of HRECs. AAV-CRISRP/Cas9-mediated depletion of VEGFR2 is a potential therapeutic strategy for pathologic angiogenesis.

Subthalamic hGAD65 Gene Therapy and Striatum TH Gene Transfer in a Parkinson’s Disease Rat Model

PubMed Central

Zheng, Deyu; Jiang, Xiaohua; Zhao, Junpeng; Duan, Deyi; Zhao, Huanying; Xu, Qunyuan

2013-01-01

The aim of the present study is to detect a combination method to utilize gene therapy for the treatment of Parkinson’s disease (PD). Here, a PD rat model is used for the in vivo gene therapy of a recombinant adeno-associated virus (AAV2) containing a human glutamic acid decarboxylase 65 (rAAV2-hGAD65) gene delivered to the subthalamic nucleus (STN). This is combined with the ex vivo gene delivery of tyrosine hydroxylase (TH) by fibroblasts injected into the striatum. After the treatment, the rotation behavior was improved with the greatest efficacy in the combination group. The results of immunohistochemistry showed that hGAD65 gene delivery by AAV2 successfully led to phenotypic changes of neurons in STN. And the levels of glutamic acid and GABA in the internal segment of the globus pallidus (GPi) and substantia nigra pars reticulata (SNr) were obviously lower than the control groups. However, hGAD65 gene transfer did not effectively protect surviving dopaminergic neurons in the SNc and VTA. This study suggests that subthalamic hGAD65 gene therapy and combined with TH gene therapy can alleviate symptoms of the PD model rats, independent of the protection the DA neurons from death. PMID:23738148

RNAi-Based GluN3A Silencing Prevents and Reverses Disease Phenotypes Induced by Mutant huntingtin.

PubMed

Marco, Sonia; Murillo, Alvaro; Pérez-Otaño, Isabel

2018-06-15

Huntington's disease (HD) is a dominantly inherited neurodegenerative disease caused by expansion of a polyglutamine tract in the huntingtin protein. HD symptoms include severe motor, cognitive, and psychiatric impairments that result from dysfunction and later degeneration of medium-sized spiny neurons (MSNs) in the striatum. A key early pathogenic mechanism is dysregulated synaptic transmission due to enhanced surface expression of juvenile NMDA-type glutamate receptors containing GluN3A subunits, which trigger the aberrant pruning of synapses formed by cortical afferents onto MSNs. Here, we tested the therapeutic potential of silencing GluN3A expression in YAC128 mice, a well-established HD model. Recombinant adeno-associated viruses encoding a short-hairpin RNA against GluN3A (rAAV-shGluN3A) were generated, and the ability of different serotypes to transduce MSNs was compared. A single injection of rAAV9-shGluN3A into the striatum of 1-month-old mice drove potent (>90%) and long-lasting reductions of GluN3A expression in MSNs, prevented dendritic spine loss and improved motor performance in YAC128 mice. Later delivery, when spine pathology is already apparent, was also effective. Our data provide proof-of-concept for GluN3A silencing as a beneficial strategy to prevent or reverse corticostriatal disconnectivity and motor impairment in HD and support the use of RNAi-based or small-molecule approaches for harnessing this therapeutic potential. Copyright © 2018 The American Society of Gene and Cell Therapy. Published by Elsevier Inc. All rights reserved.

Comparative Effects of Diet-Induced Lipid Lowering Versus Lipid Lowering Along With Apo A-I Milano Gene Therapy on Regression of Atherosclerosis.

PubMed

Wang, Lai; Tian, Fang; Arias, Ana; Yang, Mingjie; Sharifi, Behrooz G; Shah, Prediman K

2016-05-01

Apolipoprotein A-1 (Apo A-I) Milano, a naturally occurring Arg173to Cys mutant of Apo A-1, has been shown to reduce atherosclerosis in animal models and in a small phase 2 human trial. We have shown the superior atheroprotective effects of Apo A-I Milano (Apo A-IM) gene compared to wild-type Apo A-I gene using transplantation of retrovirally transduced bone marrow in Apo A-I/Apo E null mice. In this study, we compared the effect of dietary lipid lowering versus lipid lowering plus Apo A-IM gene transfer using recombinant adeno-associated virus (rAAV) 8 as vectors on atherosclerosis regression in Apo A-I/Apo E null mice. All mice were fed a high-cholesterol diet from age of 6 weeks until week 20, and at 20 weeks, 10 mice were euthanized to determine the extent of atherosclerosis. After 20 weeks, an additional 20 mice were placed on either a low-cholesterol diet plus empty rAAV (n = 10) to serve as controls or low-cholesterol diet plus 1 single intravenous injection of 1.2 × 10(12)vector genomes of adeno-associated virus (AAV) 8 vectors expressing Apo A-IM (n = 10). At the 40 week time point, intravenous AAV8 Apo A-IM recipients showed a significant regression of atherosclerosis in the whole aorta (P< .01), aortic sinuses (P< .05), and brachiocephalic arteries (P< .05) compared to 20-week-old mice, whereas low-cholesterol diet plus empty vector control group showed no significant regression in lesion size. Immunostaining showed that compared to the 20-week-old mice, there was a significantly reduced macrophage content in the brachiocephalic (P< .05) and aortic sinus plaques (P< .05) of AAV8 Apo A-IM recipients. These data show that although dietary-mediated cholesterol lowering halts progression of atherosclerosis, it does not induce regression, whereas combination of low-cholesterol diet and AAV8 mediated Apo A-I Milano gene therapy induces rapid and significant regression of atherosclerosis in mice. These data provide support for the potential feasibility of this approach for atherosclerosis regression. © The Author(s) 2015.

Remission in models of type 1 diabetes by gene therapy using a single-chain insulin analogue

NASA Astrophysics Data System (ADS)

Lee, Hyun Chul; Kim, Su-Jin; Kim, Kyung-Sup; Shin, Hang-Cheol; Yoon, Ji-Won

2000-11-01

A cure for diabetes has long been sought using several different approaches, including islet transplantation, regeneration of β cells and insulin gene therapy. However, permanent remission of type 1 diabetes has not yet been satisfactorily achieved. The development of type 1 diabetes results from the almost total destruction of insulin-producing pancreatic β cells by autoimmune responses specific to β cells. Standard insulin therapy may not maintain blood glucose concentrations within the relatively narrow range that occurs in the presence of normal pancreatic β cells. We used a recombinant adeno-associated virus (rAAV) that expresses a single-chain insulin analogue (SIA), which possesses biologically active insulin activity without enzymatic conversion, under the control of hepatocyte-specific L-type pyruvate kinase (LPK) promoter, which regulates SIA expression in response to blood glucose levels. Here we show that SIA produced from the gene construct rAAV-LPK-SIA caused remission of diabetes in streptozotocin-induced diabetic rats and autoimmune diabetic mice for a prolonged time without any apparent side effects. This new SIA gene therapy may have potential therapeutic value for the cure of autoimmune diabetes in humans.

Effective relief of neuropathic pain by adeno-associated virus-mediated expression of a small hairpin RNA against GTP cyclohydrolase 1

PubMed Central

2009-01-01

Background Recent studies show that transcriptional activation of GTP cyclohydrolase I (GCH1) in dorsal root ganglia (DRG) is significantly involved in the development and persistency of pain symptoms. We thus hypothesize that neuropathic pain may be attenuated by down-regulation of GCH1 expression, and propose a gene silencing system for this purpose. Results To interrupt GCH1 synthesis, we designed a bidirectional recombinant adeno-associated virus encoding both a small hairpin RNA against GCH1 and a GFP reporter gene (rAAV-shGCH1). After rAAV-shGCH1 was introduced into the sciatic nerve prior to or following pain-inducing surgery, therapeutic efficacy and the underlying mechanisms were subsequently validated in animal models. The GFP expression data indicates that rAAV effectively delivered transgenes to DRG. Subsequently reduced GCH1 expression was evident from immunohistochemistry and western-blotting analysis. Along with the down-regulation of GCH1, the von Frey test correspondingly indicated a sharp decline in pain symptoms upon both pre- and post-treatment with rAAV-shGCH1. Interestingly, GCH1 down-regulation additionally led to decreased microglial activation in the dorsal horn, implying an association between pain attenuation and reduced inflammation. Conclusion Therefore, the data suggests that GCH1 levels can be reduced by introducing rAAV-shGCH1, leading to pain relief. Based on the results, we propose that GCH1 modulation may be developed as a clinically applicable gene therapy strategy to treat neuropathic pain. PMID:19922668

Targeted Modifications in Adeno-Associated Virus Serotype 8 Capsid Improves Its Hepatic Gene Transfer Efficiency In Vivo

PubMed Central

Sen, Dwaipayan; Gadkari, Rupali A; Sudha, Govindarajan; Gabriel, Nishanth; Kumar, Yesupatham Sathish; Selot, Ruchita; Samuel, Rekha; Rajalingam, Sumathi; Ramya, V.; Nair, Sukesh C.; Srinivasan, Narayanaswamy; Srivastava, Alok

2013-01-01

Abstract Recombinant adeno-associated virus vectors based on serotype 8 (AAV8) have shown significant promise for liver-directed gene therapy. However, to overcome the vector dose dependent immunotoxicity seen with AAV8 vectors, it is important to develop better AAV8 vectors that provide enhanced gene expression at significantly low vector doses. Since it is known that AAV vectors during intracellular trafficking are targeted for destruction in the cytoplasm by the host–cellular kinase/ubiquitination/proteasomal machinery, we modified specific serine/threonine kinase or ubiquitination targets on the AAV8 capsid to augment its transduction efficiency. Point mutations at specific serine (S)/threonine (T)/lysine (K) residues were introduced in the AAV8 capsid at the positions equivalent to that of the effective AAV2 mutants, generated successfully earlier. Extensive structure analysis was carried out subsequently to evaluate the structural equivalence between the two serotypes. scAAV8 vectors with the wild-type (WT) and each one of the S/T→Alanine (A) or K-Arginine (R) mutant capsids were evaluated for their liver transduction efficiency in C57BL/6 mice in vivo. Two of the AAV8-S→A mutants (S279A and S671A), and a K137R mutant vector, demonstrated significantly higher enhanced green fluorescent protein (EGFP) transcript levels (∼9- to 46-fold) in the liver compared to animals that received WT-AAV8 vectors alone. The best performing AAV8 mutant (K137R) vector also had significantly reduced ubiquitination of the viral capsid, reduced activation of markers of innate immune response, and a concomitant two-fold reduction in the levels of neutralizing antibody formation in comparison to WT-AAV8 vectors. Vector biodistribution studies revealed that the K137R mutant had a significantly higher and preferential transduction of the liver (106 vs. 7.7 vector copies/mouse diploid genome) when compared to WT-AAV8 vectors. To further study the utility of the K137R-AAV8 mutant in therapeutic gene transfer, we delivered human coagulation factor IX (h.FIX) under the control of liver-specific promoters (LP1 or hAAT) into C57BL/6 mice. The circulating levels of h.FIX:Ag were higher in all the K137R-AAV8 treated groups up to 8 weeks post-hepatic gene transfer. These studies demonstrate the feasibility of the use of this novel AAV8 vectors for potential gene therapy of hemophilia B. PMID:23442071

A Therapeutic Role for Survivin in Mitigating the Harmful Effects of Ionizing Radiation

PubMed Central

Carruthers, Katherine H.; Metzger, Gregory; Choi, Eugene; During, Matthew J.; Kocak, Ergun

2016-01-01

Background. Radiation therapy is a form of adjuvant care used in many oncological treatment protocols. However, nonmalignant neighboring tissues are harmed as a result of this treatment. Therefore, the goal of this study was to induce the production of survivin, an antiapoptotic protein, to determine if this protein could provide protection to noncancerous cells during radiation exposure. Methods. Using a murine model, a recombinant adenoassociated virus (rAAV) was used to deliver survivin to the treatment group and yellow fluorescence protein (YFP) to the control group. Both groups received targeted radiation. Visual inspection, gait analysis, and tissue histology were used to determine the extent of damage caused by the radiation. Results. The YFP group demonstrated ulceration of the irradiated area while the survivin treated mice exhibited only hair loss. Histology showed that the YFP treated mice experienced dermal thickening, as well as an increase in collagen that was not present in the survivin treated mice. Gait analysis demonstrated a difference between the two groups, with the YFP mice averaging a lower speed. Conclusions. The use of gene-modification to induce survivin expression in normal tissues allows for the protection of nontarget areas from the negative side effects normally associated with ionizing radiation. PMID:27190495

AAV-Mediated Gene Transfer to Dorsal Root Ganglion.

PubMed

Yu, Hongwei; Fischer, Gregory; Hogan, Quinn H

2016-01-01

Transferring genetic molecules into the peripheral sensory nervous system to manipulate nociceptive pathophysiology is a powerful approach for experimental modulation of sensory signaling and potentially for translation into therapy for chronic pain. This can be efficiently achieved by the use of recombinant adeno-associated virus (rAAV) in conjunction with nociceptor-specific regulatory transgene cassettes. Among different routes of delivery, direct injection into the dorsal root ganglia (DRGs) offers the most efficient AAV-mediated gene transfer selectively into the peripheral sensory nervous system. Here, we briefly discuss the advantages and applications of intraganglionic microinjection, and then provide a detailed approach for DRG injection, including a list of the necessary materials and description of a method for performing DRG microinjection experiments. We also discuss our experience with several adeno-associated virus (AAV) options for in vivo transgene expression in DRG neurons.

Long-term correction of obesity and diabetes in genetically obese mice by a single intramuscular injection of recombinant adeno-associated virus encoding mouse leptin

PubMed Central

Murphy, John E.; Zhou, Shangzhen; Giese, Klaus; Williams, Lewis T.; Escobedo, Jaime A.; Dwarki, Varavani J.

1997-01-01

The ob/ob mouse is genetically deficient in leptin and exhibits a phenotype that includes obesity and non-insulin-dependent diabetes melitus. This phenotype closely resembles the morbid obesity seen in humans. In this study, we demonstrate that a single intramuscular injection of a recombinant adeno-associated virus (AAV) vector encoding mouse leptin (rAAV-leptin) in ob/ob mice leads to prevention of obesity and diabetes. The treated animals show normalization of metabolic abnormalities including hyperglycemia, insulin resistance, impaired glucose tolerance, and lethargy. The effects of a single injection have lasted through the 6-month course of the study. At all time points measured the circulating levels of leptin in the serum were similar to age-matched control C57 mice. These results demonstrate that maintenance of normal levels of leptin (2–5 ng/ml) in the circulation can prevent both the onset of obesity and associated non-insulin-dependent diabetes. Thus a single injection of a rAAV vector expressing a therapeutic gene can lead to complete and long-term correction of a genetic disorder. Our study demonstrates the long-term correction of a disease caused by a genetic defect and proves the feasibility of using rAAV-based vectors for the treatment of chronic disorders like obesity. PMID:9391128

Gene therapy mediated seizure suppression in Genetic Generalised Epilepsy: Neuropeptide Y overexpression in a rat model.

PubMed

Powell, Kim L; Fitzgerald, Xavier; Shallue, Claire; Jovanovska, Valentina; Klugmann, Matthias; Von Jonquieres, Georg; O'Brien, Terence J; Morris, Margaret J

2018-05-01

Neuropeptide Y (NPY) is an important 36 amino acid peptide that is abundantly expressed in the mammalian CNS and is known to be an endogenous modulator of seizure activity, including in rat models of Genetic Generalised Epilepsy (GGE) with absence seizures. Studies have shown that viral-mediated "gene therapy" with overexpression of NPY in the hippocampus can suppress seizures in acquired epilepsy animal models. This study investigated whether NPY gene delivery to the thalamus or somatosensory cortex, using recombinant adeno-associated viral vector (rAAV), could produce sustained seizure suppression in the GAERS model of GGE with absence seizures. Three cohorts of GAERS were injected bilaterally into the thalamus (short term n = 14 and long term n = 8) or the somatosensory cortex (n = 26) with rAAV-NPY or rAAV-empty. EEG recordings were acquired weekly post-treatment and seizure expression was quantified. Anxiety levels were tested using elevated plus maze and open field test. NPY and NPY receptor mRNA and protein expression were evaluated using quantitative PCR, immunohistochemistry and immunofluorescence. Viral overexpression of human NPY in the thalamus and somatosensory cortex in GAERS significantly reduced the time spent in seizure activity and number of seizures, whereas seizure duration was only reduced after thalamic NPY overexpression. Human and rat NPY and rat Y2 receptor mRNA expression was significantly increased in the somatosensory cortex. NPY overexpression in the thalamus was observed in rAAV-NPY treated rats compared to controls in the long term cohort. No effect was observed on anxiety behaviour. We conclude that virally-mediated human NPY overexpression in the thalamus or somatosensory cortex produces sustained anti-epileptic effects in GAERS. NPY gene therapy may represent a novel approach for the treatment of patients with genetic generalised epilepsies. Copyright © 2018 Elsevier Inc. All rights reserved.

Long-term safety and efficacy of AAV gene therapy in the canine model of glycogen storage disease type Ia.

PubMed

Lee, Young Mok; Conlon, Thomas J; Specht, Andrew; Coleman, Kirsten E; Brown, Laurie M; Estrella, Ana M; Dambska, Monika; Dahlberg, Kathryn R; Weinstein, David A

2018-05-25

Viral mediated gene therapy has progressed after overcoming early failures, and gene therapy has now been approved for several conditions in Europe and the USA. Glycogen storage disease (GSD) type Ia, caused by a deficiency of glucose-6-phosphatase-α, has been viewed as an outstanding candidate for gene therapy. This follow-up report describes the long-term outcome for the naturally occurring GSD-Ia dogs treated with rAAV-GPE-hG6PC-mediated gene therapy. A total of seven dogs were treated with rAAV-GPE-hG6PC-mediated gene therapy. The first four dogs were treated at birth, and three dogs were treated between 2 and 6 months of age to assess the efficacy and safety in animals with mature livers. Blood and urine samples, radiographic studies, histological evaluation, and biodistribution were assessed. Gene therapy improved survival in the GSD-Ia dogs. With treatment, the biochemical studies normalized for the duration of the study (up to 7 years). None of the rAAV-GPE-hG6PC-treated dogs had focal hepatic lesions or renal abnormalities. Dogs treated at birth required a second dose of rAAV after 2-4 months; gene therapy after hepatic maturation resulted in improved efficacy after a single dose. rAAV-GPE-hG6PC treatment in GSD-Ia dogs was found to be safe and efficacious. GSD-Ia is an attractive target for human gene therapy since it is a monogenic disorder with limited tissue involvement. Blood glucose and lactate monitoring can be used to assess effectiveness and as a biomarker of success. GSD-Ia can also serve as a model for other hepatic monogenic disorders.

Pharmacological and rAAV Gene Therapy Rescue of Visual Functions in a Blind Mouse Model of Leber Congenital Amaurosis

PubMed Central

Batten, Matthew L; Imanishi, Yoshikazu; Tu, Daniel C; Doan, Thuy; Zhu, Li; Pang, Jijing; Glushakova, Lyudmila; Moise, Alexander R; Baehr, Wolfgang; Van Gelder, Russell N.; Hauswirth, William W; Rieke, Fred; Palczewski, Krzysztof

2005-01-01

Background Leber congenital amaurosis (LCA), a heterogeneous early-onset retinal dystrophy, accounts for ~15% of inherited congenital blindness. One cause of LCA is loss of the enzyme lecithin:retinol acyl transferase (LRAT), which is required for regeneration of the visual photopigment in the retina. Methods and Findings An animal model of LCA, the Lrat −/− mouse, recapitulates clinical features of the human disease. Here, we report that two interventions—intraocular gene therapy and oral pharmacologic treatment with novel retinoid compounds—each restore retinal function to Lrat −/− mice. Gene therapy using intraocular injection of recombinant adeno-associated virus carrying the Lrat gene successfully restored electroretinographic responses to ~50% of wild-type levels (p < 0.05 versus wild-type and knockout controls), and pupillary light responses (PLRs) of Lrat −/− mice increased ~2.5 log units (p < 0.05). Pharmacological intervention with orally administered pro-drugs 9-cis-retinyl acetate and 9-cis-retinyl succinate (which chemically bypass the LRAT-catalyzed step in chromophore regeneration) also caused long-lasting restoration of retinal function in LRAT-deficient mice and increased ERG response from ~5% of wild-type levels in Lrat −/− mice to ~50% of wild-type levels in treated Lrat −/− mice (p < 0.05 versus wild-type and knockout controls). The interventions produced markedly increased levels of visual pigment from undetectable levels to 600 pmoles per eye in retinoid treated mice, and ~1,000-fold improvements in PLR and electroretinogram sensitivity. The techniques were complementary when combined. Conclusion Intraocular gene therapy and pharmacologic bypass provide highly effective and complementary means for restoring retinal function in this animal model of human hereditary blindness. These complementary methods offer hope of developing treatment to restore vision in humans with certain forms of hereditary congenital blindness. PMID:16250670

The natural dietary genistein boosts bacteriophage-mediated cancer cell killing by improving phage-targeted tumor cell transduction.

PubMed

Tsafa, Effrosyni; Al-Bahrani, Mariam; Bentayebi, Kaoutar; Przystal, Justyna; Suwan, Keittisak; Hajitou, Amin

2016-08-09

Gene therapy has long been regarded as a promising treatment for cancer. However, cancer gene therapy is still facing the challenge of targeting gene delivery vectors specifically to tumors when administered via clinically acceptable non-invasive systemic routes (i.e. intravenous). The bacteria virus, bacteriophage (phage), represents a new generation of promising vectors in systemic gene delivery since their targeting can be achieved through phage capsid display ligands, which enable them to home to specific tumor receptors without the need to ablate any native eukaryotic tropism. We have previously reported a tumor specific bacteriophage vector named adeno-associated virus/phage, or AAVP, in which gene expression is under a recombinant human rAAV2 virus genome targeted to tumors via a ligand-directed phage capsid. However, cancer gene therapy with this tumor-targeted vector achieved variable outcomes ranging from tumor regression to no effect in both experimental and natural preclinical models. Herein, we hypothesized that combining the natural dietary genistein, with proven anticancer activity, would improve bacteriophage anticancer safe therapy. We show that combination treatment with genistein and AAVP increased targeted cancer cell killing by AAVP carrying the gene for Herpes simplex virus thymidine kinase (HSVtk) in 2D tissue cultures and 3D tumor spheroids. We found this increased tumor cell killing was associated with enhanced AAVP-mediated gene expression. Next, we established that genistein protects AAVP against proteasome degradation and enhances vector genome accumulation in the nucleus. Combination of genistein and phage-guided virotherapy is a safe and promising strategy that should be considered in anticancer therapy with AAVP.

Intra-Amniotic rAAV-Mediated Microdystrophin Gene Transfer Improves Canine X-Linked Muscular Dystrophy and May Induce Immune Tolerance

PubMed Central

Hayashita-Kinoh, Hiromi; Yugeta, Naoko; Okada, Hironori; Nitahara-Kasahara, Yuko; Chiyo, Tomoko; Okada, Takashi; Takeda, Shin'ichi

2015-01-01

Duchenne muscular dystrophy (DMD) is a severe congenital disease due to mutations in the dystrophin gene. Supplementation of dystrophin using recombinant adenoassociated virus vector has promise as a treatment of DMD, although therapeutic benefit of the truncated dystrophin still remains to be elucidated. Besides, host immune responses against the vector as well as transgene products have been denoted in the clinical gene therapy studies. Here, we transduced dystrophic dogs fetuses to investigate the therapeutic effects of an AAV vector expressing microdystrophin under conditions of immune tolerance. rAAV-CMV-microdystrophin and a rAAV-CAG-luciferase were injected into the amniotic fluid surrounding fetuses. We also reinjected rAAV9-CMV-microdystrophin into the jugular vein of an infant dystrophic dog to induce systemic expression of microdystrophin. Gait and cardiac function significantly improved in the rAAV-microdystrophin-injected dystrophic dog, suggesting that an adequate treatment of rAAV-microdystrophin with immune modulation induces successful long-term transgene expression to analyze improved dystrophic phenotype. PMID:25586688

Bcl-2, Bcl-xL, and p-AKT are involved in neuroprotective effects of transcription factor Brn3b in an ocular hypertension rat model of glaucoma

PubMed Central

Phatak, Nitasha R.; Stankowska, Dorota L.

2016-01-01

Purpose Brn3b is a class IV POU domain transcription factor that plays an important role in the development of retinal ganglion cells (RGCs), RGC survival, and particularly axon growth and pathfinding. Our previous study demonstrated that recombinant adenoassociated virus serotype 2 (rAAV-2)–mediated overexpression of Brn3b in RGCs promoted neuroprotection in a rodent model of glaucoma. However, the mechanisms underlying neuroprotection of RGCs in rats overexpressing Brn3b in animal models of glaucoma remain largely unknown. The goal of this study was to understand some of the mechanisms underlying the neuroprotection of RGCs overexpressing Brn3b during intraocular pressure (IOP) elevation in Brown Norway rats. Methods One eye of Brown Norway rats (Rattus norvegicus) was injected with an AAV construct encoding either green fluorescent protein (GFP; recombinant adenoassociated virus–green fluorescent protein, rAAV-hSyn-GFP) or Brn3b (rAAV-hSyn-Brn3b). Expression of antiapoptotic proteins, including B cell lymphoma/leukemia-2 (Bcl-2) family proteins (Bcl-2 and Bcl-xL), and p-AKT, was observed following immunostaining of rat retinas that overexpress Brn3b. In a different set of experiments, intraocular pressure was elevated in one eye of Brown Norway rats, which was followed by intravitreal injection with AAV constructs encoding either GFP (rAAV-CMV-GFP) or Brn3b (rAAV-CMV-Brn3b). Retinal sections were stained for prosurvival factors, including Bcl-2, Bcl-XL, and p-AKT. Results AAV-mediated expression of transcription factor Brn3b promoted statistically significant upregulation of the Bcl-2 protein and increased expression of p-AKT in RGCs of Brown Norway rats. In addition, following IOP elevation, AAV-mediated Brn3b expression also statistically significantly increased levels of Bcl-2 in the RGC layer in Brown Norway rats. Conclusions Adenoassociated virus–mediated Brn3b protein overexpression may promote neuroprotection by upregulating key antiapoptotic proteins, including Bcl-2, Bcl-xL, and p-AKT, in animal models of glaucoma. PMID:27587945

Evidence based knee injections for the management of arthritis

PubMed Central

Cheng, Olivia T.; Souzdalnitski, Dmitri; Vrooman, Bruce; Cheng, Jianguo

2012-01-01

Objective Arthritis of the knee affects 46 million Americans. We aimed to determine the level of evidence of intraarticular knee injections in the management of arthritic knee pain. Methods We systematically searched PUBMED/MEDLINE and the Cochrane databases for articles published on knee injections and evaluated their level of evidence and recommendations according to established criteria. Results The evidence supports the use of intraarticular corticosteroid injections for rheumatoid arthritis (1A+ level), osteoarthritis (1A+ level), and juvenile idiopathic arthritis (2C+ level). Pain relief and functional improvement are significant for months up to one year after the injection. Triamcinolone hexacetonide offers an advantage over triamcinolone acetonide and should be the intraarticular steroid of choice (2B+ level). Intraarticular injection of hyaluronate may provide longer pain relief than steroid injection in osteoarthritis (2B+ level). It can also be effective for rheumatoid arthritis knee pain (1A+ level). However, it is only recommended for patients with significant surgical risk factors and for patients with mild radiographic disease in whom conservative treatment has failed (2B± level). Botulinum toxin Type A injection is effective in reducing arthritic knee pain (2B+ level) and so is tropisetron (2B+ level) and tanezumab (2B+ level). The new agents, such as rAAV2-TNFR:Fc, SB-210396/CE 9.1, and various radioisotopes have provided various degrees of success, but their long-term safety and efficacy remains to be determined. Conclusions We conclude that strong evidence supports the use of intraarticular knee injection as a valuable intervention in the continuum of management of arthritis between conservative treatment and knee surgeries. PMID:22621287

The natural dietary genistein boosts bacteriophage-mediated cancer cell killing by improving phage-targeted tumor cell transduction

PubMed Central

Tsafa, Effrosyni; Al-Bahrani, Mariam; Bentayebi, Kaoutar; Przystal, Justyna; Suwan, Keittisak; Hajitou, Amin

2016-01-01

Gene therapy has long been regarded as a promising treatment for cancer. However, cancer gene therapy is still facing the challenge of targeting gene delivery vectors specifically to tumors when administered via clinically acceptable non-invasive systemic routes (i.e. intravenous). The bacteria virus, bacteriophage (phage), represents a new generation of promising vectors in systemic gene delivery since their targeting can be achieved through phage capsid display ligands, which enable them to home to specific tumor receptors without the need to ablate any native eukaryotic tropism. We have previously reported a tumor specific bacteriophage vector named adeno-associated virus/phage, or AAVP, in which gene expression is under a recombinant human rAAV2 virus genome targeted to tumors via a ligand-directed phage capsid. However, cancer gene therapy with this tumor-targeted vector achieved variable outcomes ranging from tumor regression to no effect in both experimental and natural preclinical models. Herein, we hypothesized that combining the natural dietary genistein, with proven anticancer activity, would improve bacteriophage anticancer safe therapy. We show that combination treatment with genistein and AAVP increased targeted cancer cell killing by AAVP carrying the gene for Herpes simplex virus thymidine kinase (HSVtk) in 2D tissue cultures and 3D tumor spheroids. We found this increased tumor cell killing was associated with enhanced AAVP-mediated gene expression. Next, we established that genistein protects AAVP against proteasome degradation and enhances vector genome accumulation in the nucleus. Combination of genistein and phage-guided virotherapy is a safe and promising strategy that should be considered in anticancer therapy with AAVP. PMID:27437775

Production and validation of recombinant adeno-associated virus for channelrhodopsin expression in neurons.

PubMed

Lin, John Y

2013-01-01

Recent discovery of the light-activated ion channel, channelrhodopsin (ChR), has provided researchers a powerful and convenient tool to manipulate the membrane potential of specific cells with light. With genetic targeting of these channels and illumination of light to a specific location, the experimenter can selectively activate the voltage-gated ion channels (VGICs) of ChR-expressing cells, initiating electrical signaling in temporally and spatially precise manners. In neuroscience research, this can be used to study electrical signal processing within one neuron at the cellular level, or the synaptic connectivity between neurons at the circuitry level. To conduct experiments with ChRs, these exogenous channels need to be introduced into the cells of interest, commonly through a viral approach. This chapter provides an overview of the design, production, and validation of recombinant adeno-associated virus (rAAV) for ChR expression that can be used in vitro or in vivo to infect neurons. The virus produced can be used to conduct "optogenetic" experiments in behaving animals, in vitro preparations and cultured cells, and can be used to study signal transduction and processing at a cellular or circuitry level.

Hybrid Adeno-Associated Viral Vectors Utilizing Transposase-Mediated Somatic Integration for Stable Transgene Expression in Human Cells

PubMed Central

Zhang, Wenli; Solanki, Manish; Müther, Nadine; Ebel, Melanie; Wang, Jichang; Sun, Chuanbo; Izsvak, Zsuzsanna; Ehrhardt, Anja

2013-01-01

Recombinant adeno-associated viral (AAV) vectors have been shown to be one of the most promising vectors for therapeutic gene delivery because they can induce efficient and long-term transduction in non-dividing cells with negligible side-effects. However, as AAV vectors mostly remain episomal, vector genomes and transgene expression are lost in dividing cells. Therefore, to stably transduce cells, we developed a novel AAV/transposase hybrid-vector. To facilitate SB-mediated transposition from the rAAV genome, we established a system in which one AAV vector contains the transposon with the gene of interest and the second vector delivers the hyperactive Sleeping Beauty (SB) transposase SB100X. Human cells were infected with the AAV-transposon vector and the transposase was provided in trans either by transient and stable plasmid transfection or by AAV vector transduction. We found that groups which received the hyperactive transposase SB100X showed significantly increased colony forming numbers indicating enhanced integration efficiencies. Furthermore, we found that transgene copy numbers in transduced cells were dose-dependent and that predominantly SB transposase-mediated transposition contributed to stabilization of the transgene. Based on a plasmid rescue strategy and a linear-amplification mediated PCR (LAM-PCR) protocol we analysed the SB100X-mediated integration profile after transposition from the AAV vector. A total of 1840 integration events were identified which revealed a close to random integration profile. In summary, we show for the first time that AAV vectors can serve as template for SB transposase mediated somatic integration. We developed the first prototype of this hybrid-vector system which with further improvements may be explored for treatment of diseases which originate from rapidly dividing cells. PMID:24116154

Molecular anthropology meets genetic medicine to treat blindness in the North African Jewish population: human gene therapy initiated in Israel.

PubMed

Banin, Eyal; Bandah-Rozenfeld, Dikla; Obolensky, Alexey; Cideciyan, Artur V; Aleman, Tomas S; Marks-Ohana, Devora; Sela, Malka; Boye, Sanford; Sumaroka, Alexander; Roman, Alejandro J; Schwartz, Sharon B; Hauswirth, William W; Jacobson, Samuel G; Hemo, Itzhak; Sharon, Dror

2010-12-01

The history of the North African Jewish community is ancient and complicated with a number of immigration waves and persecutions dramatically affecting its population size. A decade-long process in Israel of clinical-molecular screening of North African Jews with incurable autosomal recessive blindness led to the identification of a homozygous splicing mutation (c.95-2A > T; IVS2-2A > T) in RPE65, the gene encoding the isomerase that catalyzes a key step in the retinoid-visual cycle, in patients from 10 unrelated families. A total of 33 patients (four now deceased) had the severe childhood blindness known as Leber congenital amaurosis (LCA), making it the most common cause of retinal degeneration in this population. Haplotype analysis in seven of the patients revealed a shared homozygous region, indicating a population-specific founder mutation. The age of the RPE65 founder mutation was estimated to have emerged 100-230 (mean, 153) generations ago, suggesting it originated before the establishment of the Jewish community in North Africa. Individuals with this RPE65 mutation were characterized with retinal studies to determine if they were candidates for gene replacement, the recent and only therapy to date for this otherwise incurable blindness. The step from molecular anthropological studies to application of genetic medicine was then taken, and a representative of this patient subgroup was treated with subretinal rAAV2-RPE65 gene therapy. An increase in vision was present in the treated area as early as 15 days after the intervention. This process of genetically analyzing affected isolated populations as a screen for gene-based therapy suggests a new paradigm for disease diagnosis and treatment.

Tissue-Specific Expression of Herpes Simplex Virus Thymidine Kinase Gene Delivered by Adeno-Associated Virus Inhibits the Growth of Human Hepatocellular Carcinoma in Athymic Mice

NASA Astrophysics Data System (ADS)

Su, Hua; Lu, Ronghua; Chang, Judy C.; Kan, Yuet Wai

1997-12-01

About 70% of hepatocellular carcinomas are known to express α -fetoprotein, which is normally expressed in fetal but not in adult livers. To induce herpes simplex virus-thymidine kinase expression in these cancer cells, we constructed an adeno-associated viral vector containing the HSV-TK gene under the control of the α -fetoprotein enhancer and albumin promoter. We previously demonstrated in vitro that although this vector can transduce a variety of human cells, only transduced AFP and albumin-expressing hepatocellular carcinoma cell lines were sensitive to killing by ganciclovir (GCV). In the present study, we explored the effect of this vector on hepatocellular carcinoma cells in vivo. Subcutaneous tumors generated in nude mice by implanting hepatocellular carcinoma cells previously transduced with this vector shrank dramatically after treatment with GCV. Bystander effect was also observed on the tumors generated by mixing transduced and untransduced cells. To test whether the tumor cells can be transduced by the virus in vivo, we injected the recombinant adeno-associated virus into tumors generated by untransduced hepatocarcinoma cell line. Tumor growth were retarded after treatment with GCV. These experiments demonstrate the feasibility of in vivo transduction of tumor cell with rAAV.

Follistatin-mediated skeletal muscle hypertrophy is regulated by Smad3 and mTOR independently of myostatin

PubMed Central

Winbanks, Catherine E.; Weeks, Kate L.; Thomson, Rachel E.; Sepulveda, Patricio V.; Beyer, Claudia; Qian, Hongwei; Chen, Justin L.; Allen, James M.; Lancaster, Graeme I.; Febbraio, Mark A.; Harrison, Craig A.; McMullen, Julie R.; Chamberlain, Jeffrey S.

2012-01-01

Follistatin is essential for skeletal muscle development and growth, but the intracellular signaling networks that regulate follistatin-mediated effects are not well defined. We show here that the administration of an adeno-associated viral vector expressing follistatin-288aa (rAAV6:Fst-288) markedly increased muscle mass and force-producing capacity concomitant with increased protein synthesis and mammalian target of rapamycin (mTOR) activation. These effects were attenuated by inhibition of mTOR or deletion of S6K1/2. Furthermore, we identify Smad3 as the critical intracellular link that mediates the effects of follistatin on mTOR signaling. Expression of constitutively active Smad3 not only markedly prevented skeletal muscle growth induced by follistatin but also potently suppressed follistatin-induced Akt/mTOR/S6K signaling. Importantly, the regulation of Smad3- and mTOR-dependent events by follistatin occurred independently of overexpression or knockout of myostatin, a key repressor of muscle development that can regulate Smad3 and mTOR signaling and that is itself inhibited by follistatin. These findings identify a critical role of Smad3/Akt/mTOR/S6K/S6RP signaling in follistatin-mediated muscle growth that operates independently of myostatin-driven mechanisms. PMID:22711699

miR-206 represses hypertrophy of myogenic cells but not muscle fibers via inhibition of HDAC4.

PubMed

Winbanks, Catherine E; Beyer, Claudia; Hagg, Adam; Qian, Hongwei; Sepulveda, Patricio V; Gregorevic, Paul

2013-01-01

microRNAs regulate the development of myogenic progenitors, and the formation of skeletal muscle fibers. However, the role miRNAs play in controlling the growth and adaptation of post-mitotic musculature is less clear. Here, we show that inhibition of the established pro-myogenic regulator miR-206 can promote hypertrophy and increased protein synthesis in post-mitotic cells of the myogenic lineage. We have previously demonstrated that histone deacetylase 4 (HDAC4) is a target of miR-206 in the regulation of myogenic differentiation. We confirmed that inhibition of miR-206 de-repressed HDAC4 accumulation in cultured myotubes. Importantly, inhibition of HDAC4 activity by valproic acid or sodium butyrate prevented hypertrophy of myogenic cells otherwise induced by inhibition of miR-206. To test the significance of miRNA-206 as a regulator of skeletal muscle mass in vivo, we designed recombinant adeno-associated viral vectors (rAAV6 vectors) expressing miR-206, or a miR-206 "sponge," featuring repeats of a validated miR-206 target sequence. We observed that over-expression or inhibition of miR-206 in the muscles of mice decreased or increased endogenous HDAC4 levels respectively, but did not alter muscle mass or myofiber size. We subsequently manipulated miR-206 levels in muscles undergoing follistatin-induced hypertrophy or denervation-induced atrophy (models of muscle adaptation where endogenous miR-206 expression is altered). Vector-mediated manipulation of miR-206 activity in these models of cell growth and wasting did not alter gain or loss of muscle mass respectively. Our data demonstrate that although the miR-206/HDAC4 axis operates in skeletal muscle, the post-natal expression of miR-206 is not a key regulator of basal skeletal muscle mass or specific modes of muscle growth and wasting. These studies support a context-dependent role of miR-206 in regulating hypertrophy that may be dispensable for maintaining or modifying the adult skeletal muscle phenotype--an important consideration in relation to the development of therapeutics designed to manipulate microRNA activity in musculature.

miR-206 Represses Hypertrophy of Myogenic Cells but Not Muscle Fibers via Inhibition of HDAC4

PubMed Central

Winbanks, Catherine E.; Beyer, Claudia; Hagg, Adam; Qian, Hongwei; Sepulveda, Patricio V.; Gregorevic, Paul

2013-01-01

microRNAs regulate the development of myogenic progenitors, and the formation of skeletal muscle fibers. However, the role miRNAs play in controlling the growth and adaptation of post-mitotic musculature is less clear. Here, we show that inhibition of the established pro-myogenic regulator miR-206 can promote hypertrophy and increased protein synthesis in post-mitotic cells of the myogenic lineage. We have previously demonstrated that histone deacetylase 4 (HDAC4) is a target of miR-206 in the regulation of myogenic differentiation. We confirmed that inhibition of miR-206 de-repressed HDAC4 accumulation in cultured myotubes. Importantly, inhibition of HDAC4 activity by valproic acid or sodium butyrate prevented hypertrophy of myogenic cells otherwise induced by inhibition of miR-206. To test the significance of miRNA-206 as a regulator of skeletal muscle mass in vivo, we designed recombinant adeno-associated viral vectors (rAAV6 vectors) expressing miR-206, or a miR-206 “sponge,” featuring repeats of a validated miR-206 target sequence. We observed that over-expression or inhibition of miR-206 in the muscles of mice decreased or increased endogenous HDAC4 levels respectively, but did not alter muscle mass or myofiber size. We subsequently manipulated miR-206 levels in muscles undergoing follistatin-induced hypertrophy or denervation-induced atrophy (models of muscle adaptation where endogenous miR-206 expression is altered). Vector-mediated manipulation of miR-206 activity in these models of cell growth and wasting did not alter gain or loss of muscle mass respectively. Our data demonstrate that although the miR-206/HDAC4 axis operates in skeletal muscle, the post-natal expression of miR-206 is not a key regulator of basal skeletal muscle mass or specific modes of muscle growth and wasting. These studies support a context-dependent role of miR-206 in regulating hypertrophy that may be dispensable for maintaining or modifying the adult skeletal muscle phenotype – an important consideration in relation to the development of therapeutics designed to manipulate microRNA activity in musculature. PMID:24023888

Intracranial delivery of Interleukin-17A via adeno-associated virus fails to induce physical and learning disabilities and neuroinflammation in mice but improves glucose metabolism through AKT signaling pathway

PubMed Central

Yang, Junling; Kou, Jinghong; Lim, Jeong-Eun; Lalonde, Robert; Fukuchi, Ken-ichiro

2015-01-01

Interleukin-17A (IL-17A) is generally considered as one of the pathogenic factors involved in multiple sclerosis (MS). Indirect evidence for this is that IL-17A-producing T helper 17 (Th17) cells preferentially accumulate in lesions of MS and experimental autoimmune encephalomyelitis (EAE). However, a direct involvement of IL-17A in MS pathogenesis is still an open question. In this study, we overexpressed IL-17A in the brains of mice (IL-17A-in-Brain mice) via recombinant adeno-associated virus serotype 5 (rAAV5)-mediated gene delivery. In spite of high levels of IL-17A expression in the brain and blood, IL-17A-in-Brain mice exhibit no inflammatory responses and no abnormalities in motor coordination and spatial orientation. Unexpectedly, IL-17A-in-Brain mice show decreases in body weight and adipose tissue mass and an improvement in glucose tolerance and insulin sensitivity. IL-17A enhances glucose uptake in PC12 cells by activation of AKT. Our results provide direct evidence for the first time that IL-17A overexpression in the central nervous system does not cause physical and learning disabilities and neuroinflammation and suggest that IL-17A may regulate glucose metabolism through the AKT signaling pathway. PMID:26562537

CHIP, a carboxy terminus HSP-70 interacting protein, prevents cell death induced by endoplasmic reticulum stress in the central nervous system.

PubMed

Cabral Miranda, Felipe; Adão-Novaes, Juliana; Hauswirth, William W; Linden, Rafael; Petrs-Silva, Hilda; Chiarini, Luciana B

2014-01-01

Endoplasmic reticulum (ER) stress and protein misfolding are associated with various neurodegenerative diseases. ER stress activates unfolded protein response (UPR), an adaptative response. However, severe ER stress can induce cell death. Here we show that the E3 ubiquitin ligase and co-chaperone Carboxyl Terminus HSP70/90 Interacting Protein (CHIP) prevents neuron death in the hippocampus induced by severe ER stress. Organotypic hippocampal slice cultures (OHSCs) were exposed to Tunicamycin, a pharmacological ER stress inducer, to trigger cell death. Overexpression of CHIP was achieved with a recombinant adeno-associated viral vector (rAAV) and significantly diminished ER stress-induced cell death, as shown by analysis of propidium iodide (PI) uptake, condensed chromatin, TUNEL and cleaved caspase 3 in the CA1 region of OHSCs. In addition, overexpression of CHIP prevented upregulation of both CHOP and p53 both pro-apoptotic pathways induced by ER stress. We also detected an attenuation of eIF2a phosphorylation promoted by ER stress. However, CHIP did not prevent upregulation of BiP/GRP78 induced by UPR. These data indicate that overexpression of CHIP attenuates ER-stress death response while maintain ER stress adaptative response in the central nervous system. These results indicate a neuroprotective role for CHIP upon UPR signaling. CHIP emerge as a candidate for clinical intervention in neurodegenerative diseases associated with ER stress.

PAX6 MiniPromoters drive restricted expression from rAAV in the adult mouse retina

PubMed Central

Hickmott, Jack W; Chen, Chih-yu; Arenillas, David J; Korecki, Andrea J; Lam, Siu Ling; Molday, Laurie L; Bonaguro, Russell J; Zhou, Michelle; Chou, Alice Y; Mathelier, Anthony; Boye, Sanford L; Hauswirth, William W; Molday, Robert S; Wasserman, Wyeth W; Simpson, Elizabeth M

2016-01-01

Current gene therapies predominantly use small, strong, and readily available ubiquitous promoters. However, as the field matures, the availability of small, cell-specific promoters would be greatly beneficial. Here we design seven small promoters from the human paired box 6 (PAX6) gene and test them in the adult mouse retina using recombinant adeno-associated virus. We chose the retina due to previous successes in gene therapy for blindness, and the PAX6 gene since it is: well studied; known to be driven by discrete regulatory regions; expressed in therapeutically interesting retinal cell types; and mutated in the vision-loss disorder aniridia, which is in need of improved therapy. At the PAX6 locus, 31 regulatory regions were bioinformatically predicted, and nine regulatory regions were constructed into seven MiniPromoters. Driving Emerald GFP, these MiniPromoters were packaged into recombinant adeno-associated virus, and injected intravitreally into postnatal day 14 mice. Four MiniPromoters drove consistent retinal expression in the adult mouse, driving expression in combinations of cell-types that endogenously express Pax6: ganglion, amacrine, horizontal, and Müller glia. Two PAX6-MiniPromoters drive expression in three of the four cell types that express PAX6 in the adult mouse retina. Combined, they capture all four cell types, making them potential tools for research, and PAX6-gene therapy for aniridia. PMID:27556059

PAX6 MiniPromoters drive restricted expression from rAAV in the adult mouse retina.

PubMed

Hickmott, Jack W; Chen, Chih-Yu; Arenillas, David J; Korecki, Andrea J; Lam, Siu Ling; Molday, Laurie L; Bonaguro, Russell J; Zhou, Michelle; Chou, Alice Y; Mathelier, Anthony; Boye, Sanford L; Hauswirth, William W; Molday, Robert S; Wasserman, Wyeth W; Simpson, Elizabeth M

2016-01-01

Current gene therapies predominantly use small, strong, and readily available ubiquitous promoters. However, as the field matures, the availability of small, cell-specific promoters would be greatly beneficial. Here we design seven small promoters from the human paired box 6 (PAX6) gene and test them in the adult mouse retina using recombinant adeno-associated virus. We chose the retina due to previous successes in gene therapy for blindness, and the PAX6 gene since it is: well studied; known to be driven by discrete regulatory regions; expressed in therapeutically interesting retinal cell types; and mutated in the vision-loss disorder aniridia, which is in need of improved therapy. At the PAX6 locus, 31 regulatory regions were bioinformatically predicted, and nine regulatory regions were constructed into seven MiniPromoters. Driving Emerald GFP, these MiniPromoters were packaged into recombinant adeno-associated virus, and injected intravitreally into postnatal day 14 mice. Four MiniPromoters drove consistent retinal expression in the adult mouse, driving expression in combinations of cell-types that endogenously express Pax6: ganglion, amacrine, horizontal, and Müller glia. Two PAX6-MiniPromoters drive expression in three of the four cell types that express PAX6 in the adult mouse retina. Combined, they capture all four cell types, making them potential tools for research, and PAX6-gene therapy for aniridia.

Diabetes Mellitus-Induced Microvascular Destabilization in the Myocardium.

PubMed

Hinkel, Rabea; Howe, Andrea; Renner, Simone; Ng, Judy; Lee, Seungmin; Klett, Katharina; Kaczmarek, Veronika; Moretti, Alessandra; Laugwitz, Karl-Ludwig; Skroblin, Philipp; Mayr, Manuel; Milting, Hendrik; Dendorfer, Andreas; Reichart, Bruno; Wolf, Eckhard; Kupatt, Christian

2017-01-17

Diabetes mellitus causes microcirculatory rarefaction and may impair the responsiveness of ischemic myocardium to proangiogenic factors. This study sought to determine whether microvascular destabilization affects organ function and therapeutic neovascularization in diabetes mellitus. The authors obtained myocardial samples from patients with end-stage heart failure at time of transplant, with or without diabetes mellitus. Diabetic (db) and wild-type (wt) pigs were used to analyze myocardial vascularization and function. Chronic ischemia was induced percutaneously (day 0) in the circumflex artery. At day 28, recombinant adeno-associated virus (rAAV) (5 × 10 12 viral particles encoding vascular endothelial growth factor-A [VEGF-A] or thymosin beta 4 [Tβ4]) was applied regionally. CD31+ capillaries per high power field (c/hpf) and NG2+ pericyte coverage were analyzed. Global myocardial function (ejection fraction [EF] and left ventricular end-diastolic pressure) was assessed at days 28 and 56. Diabetic human myocardial explants revealed capillary rarefaction and pericyte loss compared to nondiabetic explants. Hyperglycemia in db pigs, even without ischemia, induced capillary rarefaction in the myocardium (163 ± 14 c/hpf in db vs. 234 ± 8 c/hpf in wt hearts; p < 0.005), concomitant with a distinct loss of EF (44.9% vs. 53.4% in nondiabetic controls; p < 0.05). Capillary density further decreased in chronic ischemic hearts, as did EF (both p < 0.05). Treatment with rAAV.Tβ4 enhanced capillary density and maturation in db hearts less efficiently than in wt hearts, similar to collateral growth. rAAV.VEGF-A, though stimulating angiogenesis, induced neither pericyte recruitment nor collateral growth. As a result, rAAV.Tβ4 but not rAAV.VEGF-A improved EF in db hearts (34.5 ± 1.4%), but less so than in wt hearts (44.8 ± 1.5%). Diabetes mellitus destabilized microvascular vessels of the heart, affecting the amplitude of therapeutic neovascularization via rAAV.Tβ4 in a translational large animal model of hibernating myocardium. Copyright © 2017 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Gamma-sarcoglycan is required for the response of archvillin to mechanical stimulation in skeletal muscle

PubMed Central

Spinazzola, Janelle M.; Smith, Tara C.; Liu, Min; Luna, Elizabeth J.; Barton, Elisabeth R.

2015-01-01

Loss of gamma-sarcoglycan (γ-SG) induces muscle degeneration and signaling defects in response to mechanical load, and its absence is common to both Duchenne and limb girdle muscular dystrophies. Growing evidence suggests that aberrant signaling contributes to the disease pathology; however, the mechanisms of γ-SG-mediated mechanical signaling are poorly understood. To uncover γ-SG signaling pathway components, we performed yeast two-hybrid screens and identified the muscle-specific protein archvillin as a γ-SG and dystrophin interacting protein. Archvillin protein and message levels were significantly upregulated at the sarcolemma of murine γ-SG-null (gsg−/−) muscle but delocalized in dystrophin-deficient mdx muscle. Similar elevation of archvillin protein was observed in human quadriceps muscle lacking γ-SG. Reintroduction of γ-SG in gsg−/− muscle by rAAV injection restored archvillin levels to that of control C57 muscle. In situ eccentric contraction of tibialis anterior (TA) muscles from C57 mice caused ERK1/2 phosphorylation, nuclear activation of P-ERK1/2 and stimulus-dependent archvillin association with P-ERK1/2. In contrast, TA muscles from gsg−/− and mdx mice exhibited heightened P-ERK1/2 and increased nuclear P-ERK1/2 localization following eccentric contractions, but the archvillin–P-ERK1/2 association was completely ablated. These results position archvillin as a mechanically sensitive component of the dystrophin complex and demonstrate that signaling defects caused by loss of γ-SG occur both at the sarcolemma and in the nucleus. PMID:25605665

X-linked juvenile retinoschisis: Clinical diagnosis, genetic analysis, and molecular mechanisms

PubMed Central

Molday, Robert S.; Kellner, Ulrich; Weber, Bernhard H.F.

2012-01-01

X-linked juvenile retinoschisis (XLRS, MIM 312700) is a common early onset macular degeneration in males characterized by mild to severe loss in visual acuity, splitting of retinal layers, and a reduction in the b-wave of the electroretinogram (ERG). The RS1 gene (MIM 300839) associated with the disease encodes retinoschisin, a 224 amino acid protein containing a discoidin domain as the major structural unit, an N-terminal cleavable signal sequence, and regions responsible for subunit oligomerization. Retinoschisin is secreted from retinal cells as a disulphide-linked homo-octameric complex which binds to the surface of photoreceptors and bipolar cells to help maintain the integrity of the retina. Over 190 disease-causing mutations in the RS1 gene are known with most mutations occurring as non-synonymous changes in the discoidin domain. Cell expression studies have shown that disease-associated missense mutations in the discoidin domain cause severe protein misfolding and retention in the endoplasmic reticulum, mutations in the signal sequence result in aberrant protein synthesis, and mutations in regions flanking the discoidin domain cause defective disulphide-linked subunit assembly, all of which produce a non-functional protein. Knockout mice deficient in retinoschisin have been generated and shown to display most of the characteristic features found in XLRS patients. Recombinant adeno-associated virus (rAAV) mediated delivery of the normal RS1 gene to the retina of young knockout mice result in long term retinoschisin expression and rescue of retinal structure and function providing a ‘proof of concept’ that gene therapy may be an effective treatment for XLRS. PMID:22245536

X-linked juvenile retinoschisis: clinical diagnosis, genetic analysis, and molecular mechanisms.

PubMed

Molday, Robert S; Kellner, Ulrich; Weber, Bernhard H F

2012-05-01

X-linked juvenile retinoschisis (XLRS, MIM 312700) is a common early onset macular degeneration in males characterized by mild to severe loss in visual acuity, splitting of retinal layers, and a reduction in the b-wave of the electroretinogram (ERG). The RS1 gene (MIM 300839) associated with the disease encodes retinoschisin, a 224 amino acid protein containing a discoidin domain as the major structural unit, an N-terminal cleavable signal sequence, and regions responsible for subunit oligomerization. Retinoschisin is secreted from retinal cells as a disulphide-linked homo-octameric complex which binds to the surface of photoreceptors and bipolar cells to help maintain the integrity of the retina. Over 190 disease-causing mutations in the RS1 gene are known with most mutations occurring as non-synonymous changes in the discoidin domain. Cell expression studies have shown that disease-associated missense mutations in the discoidin domain cause severe protein misfolding and retention in the endoplasmic reticulum, mutations in the signal sequence result in aberrant protein synthesis, and mutations in regions flanking the discoidin domain cause defective disulphide-linked subunit assembly, all of which produce a non-functional protein. Knockout mice deficient in retinoschisin have been generated and shown to display most of the characteristic features found in XLRS patients. Recombinant adeno-associated virus (rAAV) mediated delivery of the normal RS1 gene to the retina of young knockout mice result in long-term retinoschisin expression and rescue of retinal structure and function providing a 'proof of concept' that gene therapy may be an effective treatment for XLRS. Copyright © 2012 Elsevier Ltd. All rights reserved.

The Hematopoietic Stem Cell Therapy for Exploration of Space

NASA Astrophysics Data System (ADS)

Ohi, S.

Departments of Biochemistry &Molecular Biology, Genetics &Human Genetics, Pediatrics &Child Long-duration space missions require countermeasures against severe/invasive disorders in astronauts that are caused by space environments, such as hematological/cardiac abnormalities, bone/muscle losses, immunodeficiency, neurological disorders, and cancer. Some, if not all, of these disorders may be amenable to hematopoietic stem cell therapy and gene therapy. Growing evidence indicates that hematopoietic stem cells (HSCs) possess extraordinary plasticity to differentiate not only to all types of blood cells but also to various tissues, including bone, muscle, skin, liver and neuronal cells. Therefore, our working hypothesis is that the hematopoietic stem cell-based therapy, herein called as the hematopoietic stem cell therapy (HSCT), might provide countermeasure/prevention for hematological abnormalities, bone and muscle losses in space, thereby maintaining astronauts' homeostasis. Our expertise lies in recombinant adeno-associated virus (rAAV)-mediated gene therapy for the hemoglobinopathies, -thalassemia and sickle cell disease (Ohi S, Kim BC, J Pharm Sci 85: 274-281, 1996; Ohi S, et al. Grav Space Biol Bull 14: 43, 2000). As the requisite steps in this protocol, we established procedures for purification of HSCs from both mouse and human bone marrow in 1 G. Furthermore, we developed an easily harvestable, long-term liquid suspension culture system, which lasts more than one year, for growing/expanding HSCs without stromal cells. Human globin cDNAs/gene were efficiently expressed from the rAAVs in the mouse HSCs in culture. Additionally, the NASA Rotating Wall Vessel (RWV) culture system is being optimized for the HSC growth/expansion. Thus, using these technologies, the above hypothesis is being investigated by the ground-based experiments as follows: 1) -thalassemic mice (C57BL/6-Hbbth/Hbbth, Hbd-minor) are transplanted with normal isologous HSCs to correct the hematological abnormalities. To date, the - thalassemic mice have been successfully HSC-transplanted to produce chimerism of hemoglobin species (Ohi S, J Grav Physiol 7: 67-68, 2000); 2) Transgenic HSCs harboring green fluorescent protein (GFP) gene or -galactosidase gene are/will be transplanted to hindlimb suspended mice, and differentiation of HSCs to bone will be traced by the marker gene expression. Repair/prevention of bone loss by the HSCT will be investigated by analyzing physical/biochemical parameters; 3) Similarly, the efficacy of HSCT for muscle loss in the unloaded mouse is being studied. In addition, using the hindlimb suspension model, effects of exercise on the HSCT for bone and muscle losses are being investigated. Our long-term goal is to automate/robotize the HSCT protocols so that astronauts would be able to treat themselves during long-duration space missions. Such a program will be also beneficial to the earth people as a self-care health system. Upon optimization of the condition of HSC growth in the RWV culture system, it is in our plan to conduct the similar experiments as above in the International Space Station in future. (Supported in part by grant from NASA Institute for Advanced Concepts/USRA.

The influence of rAAV2-mediated SOX2 delivery into neonatal and adult human RPE cells; a comparative study.

PubMed

Ezati, Razie; Etemadzadeh, Azadeh; Soheili, Zahra-Soheila; Samiei, Shahram; Ranaei Pirmardan, Ehsan; Davari, Malihe; Najafabadi, Hoda Shams

2018-02-01

Cell replacement is a promising therapy for degenerative diseases like age-related macular degeneration (AMD). Since the human retina lacks regeneration capacity, much attention has been directed toward persuading for cells that can differentiate into retinal neurons. In this report, we have investigated reprogramming of the human RPE cells and concerned the effect of donor age on the cellular fate as a critical determinant in reprogramming competence. We evaluated the effect of SOX2 over-expression in human neonatal and adult RPE cells in cultures. The coding region of human SOX2 gene was cloned into adeno-associated virus (AAV2) and primary culture of human neonatal/adult RPE cells were infected by recombinant virus. De-differentiation of RPE to neural/retinal progenitor cells was investigated by quantitative real-time PCR and ICC for neural/retinal progenitor cells' markers. Gene expression analysis showed 80-fold and 12-fold over-expression for SOX2 gene in infected neonatal and adult hRPE cells, respectively. The fold of increase for Nestin in neonatal and adult hRPE cells was 3.8-fold and 2.5-fold, respectively. PAX6 expression was increased threefold and 2.5-fold in neonatal/adult treated cultures. Howbeit, we could not detect rhodopsin, and CHX10 expression in neonatal hRPE cultures and expression of rhodopsin in adult hRPE cells. Results showed SOX2 induced human neonatal/adult RPE cells to de-differentiate toward retinal progenitor cells. However, the increased number of PAX6, CHX10, Thy1, and rhodopsin positive cells in adult hRPE treated cultures clearly indicated the considerable generation of neuro-retinal terminally differentiated cells. © 2017 Wiley Periodicals, Inc.

Klotho gene delivery ameliorates renal hypertrophy and fibrosis in streptozotocin-induced diabetic rats by suppressing the Rho-associated coiled-coil kinase signaling pathway.

PubMed

Deng, Minghong; Luo, Yumei; Li, Yunkui; Yang, Qiuchen; Deng, Xiaoqin; Wu, Ping; Ma, Houxun

2015-07-01

The present study aimed to investigate whether klotho gene delivery attenuated renal hypertrophy and fibrosis in streptozotocin-induced diabetic rats. A recombinant adeno-associated virus (rAAV) carrying mouse klotho full-length cDNA (rAAV.mKL), was constructed for in vivo investigation of klotho expression. Diabetes was induced in rats by a single tail vein injection of 60 mg/kg streptozotocin. Subsequently, the diabetic rats received an intravenous injection of rAAV.mKL, rAAV.green fluorescent protein (GFP) or phosphate-buffered saline (PBS). The Sprague-Dawley rat group received PBS and served as the control group. After 12 weeks, all the rats were sacrificed and ELISA, immunohistochemical and histological analyses, fluorescence microscopy, semi-quantitative reverse transcription-polymerase chain reaction and western blottin were performed. A single dose of rAAV.mKL was found to prevent the progression of renal hypertrophy and fibrosis for at least 12 weeks (duration of study). Klotho expression was suppressed in the diabetic rats, but was increased by rAAV.mKL delivery. rAAV.mKL significantly suppressed diabetes-induced renal hypertrophy and histopathological changes, reduced renal collagen fiber generation and decreased kidney hypertrophy index. In addition, rAAV.mKL decreased the protein expression levels of fibronectin and vimentin, while it downregulated the mRNA expression and activity of Rho-associated coiled-coil kinase (ROCK)I in the kidneys of the diabetic rats. These results indicated that klotho gene delivery ameliorated renal hypertrophy and fibrosis in diabetic rats, possibly by suppressing the ROCK signaling pathway. This may offer a novel approach for the long-term control and renoprotection of diabetes.

Gene therapy strategy for long-term myocardial protection using adeno-associated virus-mediated delivery of heme oxygenase gene.

PubMed

Melo, Luis G; Agrawal, Reitu; Zhang, Lunan; Rezvani, Mojgan; Mangi, Abeel A; Ehsan, Afshin; Griese, Daniel P; Dell'Acqua, Giorgio; Mann, Michael J; Oyama, Junichi; Yet, Shaw-Fang; Layne, Matthew D; Perrella, Mark A; Dzau, Victor J

2002-02-05

Ischemia and oxidative stress are the leading mechanisms for tissue injury. An ideal strategy for preventive/protective therapy would be to develop an approach that could confer long-term transgene expression and, consequently, tissue protection from repeated ischemia/reperfusion injury with a single administration of a therapeutic gene. In the present study, we used recombinant adeno-associated virus (rAAV) as a vector for direct delivery of the cytoprotective gene heme oxygenase-1 (HO-1) into the rat myocardium, with the purpose of evaluating this strategy as a therapeutic approach for long-term protection from ischemia-induced myocardial injury. Human HO-1 gene (hHO-1) was delivered to normal rat hearts by intramyocardial injection. AAV-mediated transfer of the hHO-1 gene 8 weeks before acute coronary artery ligation and release led to a dramatic reduction (>75%) in left ventricular myocardial infarction. The reduction in infarct size was accompanied by decreases in myocardial lipid peroxidation and in proapoptotic Bax and proinflammatory interleukin-1beta protein abundance, concomitant with an increase in antiapoptotic Bcl-2 protein level. This suggested that the transgene exerts its cardioprotective effects in part by reducing oxidative stress and associated inflammation and apoptotic cell death. This study documents the beneficial therapeutic effect of rAAV-mediated transfer, before myocardial injury, of a cytoprotective gene that confers long-term myocardial protection from ischemia/reperfusion injury. Our data suggest that this novel "pre-event" gene transfer approach may provide sustained tissue protection from future repeated episodes of injury and may be beneficial as preventive therapy for patients with or at risk of developing coronary ischemic events.

Mosaic analysis of gene function in postnatal mouse brain development by using virus-based Cre recombination.

PubMed

Gibson, Daniel A; Ma, Le

2011-08-01

Normal brain function relies not only on embryonic development when major neuronal pathways are established, but also on postnatal development when neural circuits are matured and refined. Misregulation at this stage may lead to neurological and psychiatric disorders such as autism and schizophrenia. Many genes have been studied in the prenatal brain and found crucial to many developmental processes. However, their function in the postnatal brain is largely unknown, partly because their deletion in mice often leads to lethality during neonatal development, and partly because their requirement in early development hampers the postnatal analysis. To overcome these obstacles, floxed alleles of these genes are currently being generated in mice. When combined with transgenic alleles that express Cre recombinase in specific cell types, conditional deletion can be achieved to study gene function in the postnatal brain. However, this method requires additional alleles and extra time (3-6 months) to generate the mice with appropriate genotypes, thereby limiting the expansion of the genetic analysis to a large scale in the mouse brain. Here we demonstrate a complementary approach that uses virally-expressed Cre to study these floxed alleles rapidly and systematically in postnatal brain development. By injecting recombinant adeno-associated viruses (rAAVs) encoding Cre into the neonatal brain, we are able to delete the gene of interest in different regions of the brain. By controlling the viral titer and coexpressing a fluorescent protein marker, we can simultaneously achieve mosaic gene inactivation and sparse neuronal labeling. This method bypasses the requirement of many genes in early development, and allows us to study their cell autonomous function in many critical processes in postnatal brain development, including axonal and dendritic growth, branching, and tiling, as well as synapse formation and refinement. This method has been used successfully in our own lab (unpublished results) and others, and can be extended to other viruses, such as lentivirus, as well as to the expression of shRNA or dominant active proteins. Furthermore, by combining this technique with electrophysiology as well as recently-developed optical imaging tools, this method provides a new strategy to study how genetic pathways influence neural circuit development and function in mice and rats.

Downregulation of SIRT1 signaling underlies hepatic autophagy impairment in glycogen storage disease type Ia

PubMed Central

Cho, Jun-Ho; Pan, Chi-Jiunn; Anduaga, Javier

2017-01-01

A deficiency in glucose-6-phosphatase-α (G6Pase-α) in glycogen storage disease type Ia (GSD-Ia) leads to impaired glucose homeostasis and metabolic manifestations including hepatomegaly caused by increased glycogen and neutral fat accumulation. A recent report showed that G6Pase-α deficiency causes impairment in autophagy, a recycling process important for cellular metabolism. However, the molecular mechanism underlying defective autophagy is unclear. Here we show that in mice, liver-specific knockout of G6Pase-α (L-G6pc-/-) leads to downregulation of sirtuin 1 (SIRT1) signaling that activates autophagy via deacetylation of autophagy-related (ATG) proteins and forkhead box O (FoxO) family of transcriptional factors which transactivate autophagy genes. Consistently, defective autophagy in G6Pase-α-deficient liver is characterized by attenuated expressions of autophagy components, increased acetylation of ATG5 and ATG7, decreased conjugation of ATG5 and ATG12, and reduced autophagic flux. We further show that hepatic G6Pase-α deficiency results in activation of carbohydrate response element-binding protein, a lipogenic transcription factor, increased expression of peroxisome proliferator-activated receptor-γ (PPAR-γ), a lipid regulator, and suppressed expression of PPAR-α, a master regulator of fatty acid β-oxidation, all contributing to hepatic steatosis and downregulation of SIRT1 expression. An adenovirus vector-mediated increase in hepatic SIRT1 expression corrects autophagy defects but does not rectify metabolic abnormalities associated with G6Pase-α deficiency. Importantly, a recombinant adeno-associated virus (rAAV) vector-mediated restoration of hepatic G6Pase-α expression corrects metabolic abnormalities, restores SIRT1-FoxO signaling, and normalizes defective autophagy. Taken together, these data show that hepatic G6Pase-α deficiency-mediated down-regulation of SIRT1 signaling underlies defective hepatic autophagy in GSD-Ia. PMID:28558013

Insulin Therapy Improves Adeno-Associated Virus Transduction of Liver and Skeletal Muscle in Mice and Cultured Cells.

PubMed

Carrig, Sean; Bijjiga, Enoch; Wopat, Mitchell J; Martino, Ashley T

2016-11-01

Adeno-associated virus (AAV) gene transfer is a promising treatment for genetic abnormalities. Optimal AAV vectors are showing success in clinical trials. Gene transfer to skeletal muscle and liver is being explored as a potential therapy for some conditions, that is, α 1 -antitrypsin (AAT) disorder and hemophilia B. Exploring approaches that enhance transduction of liver and skeletal muscle, using these vectors, is beneficial for gene therapy. Regulating hormones as an approach to improve AAV transduction is largely unexplored. In this study we tested whether insulin therapy improves liver and skeletal muscle gene transfer. In vitro studies demonstrated that the temporary coadministration (2, 8, and 24 hr) of insulin significantly improves AAV2-CMV-LacZ transduction of cultured liver cells and differentiated myofibers, but not of lung cells. In addition, there was a dose response related to this improved transduction. Interestingly, when insulin was not coadministered with the virus but given 24 hr afterward, there was no increase in the transgene product. Insulin receptor gene (INSR) expression levels were increased 5- to 13-fold in cultured liver cells and differentiated myofibers when compared with lung cells. Similar INSR gene expression profiles occurred in mouse tissues. Insulin therapy was performed in mice, using a subcutaneously implanted insulin pellet or a high-carbohydrate diet. Insulin treatment began just before intramuscular delivery of AAV1-CMV-schFIX or liver-directed delivery of AAV8-CMV-schFIX and continued for 28 days. Both insulin augmentation therapies improved skeletal muscle- and liver-directed gene transduction in mice as seen by a 3.0- to 4.5-fold increase in human factor IX (hFIX) levels. The improvement was observed even after the insulin therapy ended. Monitoring insulin showed that insulin levels increased during the brief period of rAAV delivery and during the entire insulin augmentation period (28 days). This study demonstrates that AAV transduction of liver or skeletal muscle can be improved by insulin therapy.

AAV2 production with optimized N/P ratio and PEI-mediated transfection results in low toxicity and high titer for in vitro and in vivo applications.

PubMed

Huang, Xinping; Hartley, Antja-Voy; Yin, Yishi; Herskowitz, Jeremy H; Lah, James J; Ressler, Kerry J

2013-11-01

The adeno-associated virus (AAV) is one of the most useful viral vectors for gene delivery for both in vivo and in vitro applications. A variety of methods have been established to produce and characterize recombinant AAV (rAAV) vectors; however most methods are quite cumbersome and obtaining consistently high titer can be problematic. This protocol describes a triple-plasmid co-transfection approach with 25 kDa linear polyethylenimine (PEI) in 293 T cells for the production of AAV serotype 2. Seventy-two hours post-transfection, supernatant and cells were harvested and purified by a discontinuous iodixanol density gradient ultracentrifugation, then dialyzed and concentrated with an Amicon 15 100,000 MWCO concentration unit. To optimize the protocol for AAV2 production using PEI, various N/P ratios and DNA amounts were compared. We found that an N/P ratio of 40 coupled with 1.05 μg DNA per ml of media (21 μg DNA/15 cm dish) was found to produce the highest yields for viral replication and assembly measured multiple ways. The infectious units, as determined by serial dilution, were between 1×10(8) and 2×10(9) IU/ml. The genomic titer of the viral stock was determined by qPCR and ranged from 2×10(12) to 6×10(13) VG/ml. These viral vectors showed high expression both in vivo within the brain and in vitro in cell culture. The use of linear 25 kDa polyethylenamine PEI as a transfection reagent is a simple, more cost-effective, and stable means of high-throughput production of high-titer AAV serotype 2. The use of PEI also eliminates the need to change cell medium post-transfection, lowering cost and workload, while producing high-titer, efficacious AAV2 vectors for routine gene transfer. Copyright © 2013 Elsevier B.V. All rights reserved.

A demonstrative model of a lunar base simulation on a personal computer

NASA Technical Reports Server (NTRS)

1985-01-01

The initial demonstration model of a lunar base simulation is described. This initial model was developed on the personal computer level to demonstrate feasibility and technique before proceeding to a larger computer-based model. Lotus Symphony Version 1.1 software was used to base the demonstration model on an personal computer with an MS-DOS operating system. The personal computer-based model determined the applicability of lunar base modeling techniques developed at an LSPI/NASA workshop. In addition, the personnal computer-based demonstration model defined a modeling structure that could be employed on a larger, more comprehensive VAX-based lunar base simulation. Refinement of this personal computer model and the development of a VAX-based model is planned in the near future.

Model-based RSA of a femoral hip stem using surface and geometrical shape models.

PubMed

Kaptein, Bart L; Valstar, Edward R; Spoor, Cees W; Stoel, Berend C; Rozing, Piet M

2006-07-01

Roentgen stereophotogrammetry (RSA) is a highly accurate three-dimensional measuring technique for assessing micromotion of orthopaedic implants. A drawback is that markers have to be attached to the implant. Model-based techniques have been developed to prevent using special marked implants. We compared two model-based RSA methods with standard marker-based RSA techniques. The first model-based RSA method used surface models, and the second method used elementary geometrical shape (EGS) models. We used a commercially available stem to perform experiments with a phantom as well as reanalysis of patient RSA radiographs. The data from the phantom experiment indicated the accuracy and precision of the elementary geometrical shape model-based RSA method is equal to marker-based RSA. For model-based RSA using surface models, the accuracy is equal to the accuracy of marker-based RSA, but its precision is worse. We found no difference in accuracy and precision between the two model-based RSA techniques in clinical data. For this particular hip stem, EGS model-based RSA is a good alternative for marker-based RSA.

Regional climate model downscaling may improve the prediction of alien plant species distributions

NASA Astrophysics Data System (ADS)

Liu, Shuyan; Liang, Xin-Zhong; Gao, Wei; Stohlgren, Thomas J.

2014-12-01

Distributions of invasive species are commonly predicted with species distribution models that build upon the statistical relationships between observed species presence data and climate data. We used field observations, climate station data, and Maximum Entropy species distribution models for 13 invasive plant species in the United States, and then compared the models with inputs from a General Circulation Model (hereafter GCM-based models) and a downscaled Regional Climate Model (hereafter, RCM-based models).We also compared species distributions based on either GCM-based or RCM-based models for the present (1990-1999) to the future (2046-2055). RCM-based species distribution models replicated observed distributions remarkably better than GCM-based models for all invasive species under the current climate. This was shown for the presence locations of the species, and by using four common statistical metrics to compare modeled distributions. For two widespread invasive taxa ( Bromus tectorum or cheatgrass, and Tamarix spp. or tamarisk), GCM-based models failed miserably to reproduce observed species distributions. In contrast, RCM-based species distribution models closely matched observations. Future species distributions may be significantly affected by using GCM-based inputs. Because invasive plants species often show high resilience and low rates of local extinction, RCM-based species distribution models may perform better than GCM-based species distribution models for planning containment programs for invasive species.

Representing Micro-Macro Linkages by Actor-Based Dynamic Network Models

ERIC Educational Resources Information Center

Snijders, Tom A. B.; Steglich, Christian E. G.

2015-01-01

Stochastic actor-based models for network dynamics have the primary aim of statistical inference about processes of network change, but may be regarded as a kind of agent-based models. Similar to many other agent-based models, they are based on local rules for actor behavior. Different from many other agent-based models, by including elements of…

Ventral Tegmental Area Dopamine Cell Activation during Male Rat Sexual Behavior Regulates Neuroplasticity and d-Amphetamine Cross-Sensitization following Sex Abstinence.

PubMed

Beloate, Lauren N; Omrani, Azar; Adan, Roger A; Webb, Ian C; Coolen, Lique M

2016-09-21

Experience with sexual behavior causes cross-sensitization of amphetamine reward, an effect dependent on a period of sexual reward abstinence. We previously showed that ΔFosB in the nucleus accumbens (NAc) is a key mediator of this cross-sensitization, potentially via dopamine receptor activation. However, the role of mesolimbic dopamine for sexual behavior or cross-sensitization between natural and drug reward is unknown. This was tested using inhibitory designer receptors exclusively activated by designer drugs in ventral tegmental area (VTA) dopamine cells. rAAV5/hSvn-DIO-hm4D-mCherry was injected into the VTA of TH::Cre adult male rats. Males received clozapine N-oxide (CNO) or vehicle injections before each of 5 consecutive days of mating or handling. Following an abstinence period of 7 d, males were tested for amphetamine conditioned place preference (CPP). Next, males were injected with CNO or vehicle before mating or handling for analysis of mating-induced cFos, sex experience-induced ΔFosB, and reduction of VTA dopamine soma size. Results showed that CNO did not affect mating behavior. Instead, CNO prevented sexual experience-induced cross-sensitization of amphetamine CPP, ΔFosB in the NAc and medial prefrontal cortex, and decreases in VTA dopamine soma size. Expression of hm4D-mCherry was specific to VTA dopamine cells and CNO blocked excitation and mating-induced cFos expression in VTA dopamine cells. These findings provide direct evidence that VTA dopamine activation is not required for initiation or performance of sexual behavior. Instead, VTA dopamine directly contributes to increased vulnerability for drug use following loss of natural reward by causing neuroplasticity in the mesolimbic pathway during the natural reward experience. Drugs of abuse act on the neural pathways that mediate natural reward learning and memory. Exposure to natural reward behaviors can alter subsequent drug-related reward. Specifically, experience with sexual behavior, followed by a period of abstinence from sexual behavior, causes increased reward for amphetamine in male rats. This study demonstrates that activation of ventral tegmental area dopamine neurons during sexual experience regulates cross-sensitization of amphetamine reward. Finally, ventral tegmental area dopamine cell activation is essential for experience-induced neural adaptations in the nucleus accumbens, prefrontal cortex, and ventral tegmental area. These findings demonstrate a role of mesolimbic dopamine in the interaction between natural and drug rewards, and identify mesolimbic dopamine as a key mediator of changes in vulnerability for drug use after loss of natural reward. Copyright © 2016 the authors 0270-6474/16/369949-13$15.00/0.

Model-free and model-based reward prediction errors in EEG.

PubMed

Sambrook, Thomas D; Hardwick, Ben; Wills, Andy J; Goslin, Jeremy

2018-05-24

Learning theorists posit two reinforcement learning systems: model-free and model-based. Model-based learning incorporates knowledge about structure and contingencies in the world to assign candidate actions with an expected value. Model-free learning is ignorant of the world's structure; instead, actions hold a value based on prior reinforcement, with this value updated by expectancy violation in the form of a reward prediction error. Because they use such different learning mechanisms, it has been previously assumed that model-based and model-free learning are computationally dissociated in the brain. However, recent fMRI evidence suggests that the brain may compute reward prediction errors to both model-free and model-based estimates of value, signalling the possibility that these systems interact. Because of its poor temporal resolution, fMRI risks confounding reward prediction errors with other feedback-related neural activity. In the present study, EEG was used to show the presence of both model-based and model-free reward prediction errors and their place in a temporal sequence of events including state prediction errors and action value updates. This demonstration of model-based prediction errors questions a long-held assumption that model-free and model-based learning are dissociated in the brain. Copyright © 2018 Elsevier Inc. All rights reserved.

NED-IIS: An Intelligent Information System for Forest Ecosystem Management

Treesearch

W.D. Potter; S. Somasekar; R. Kommineni; H.M. Rauscher

1999-01-01

We view Intelligent Information System (IIS) as composed of a unified knowledge base, database, and model base. The model base includes decision support models, forecasting models, and cvsualization models for example. In addition, we feel that the model base should include domain specific porblems solving modules as well as decision support models. This, then,...

A hybrid agent-based approach for modeling microbiological systems.

PubMed

Guo, Zaiyi; Sloot, Peter M A; Tay, Joc Cing

2008-11-21

Models for systems biology commonly adopt Differential Equations or Agent-Based modeling approaches for simulating the processes as a whole. Models based on differential equations presuppose phenomenological intracellular behavioral mechanisms, while models based on Multi-Agent approach often use directly translated, and quantitatively less precise if-then logical rule constructs. We propose an extendible systems model based on a hybrid agent-based approach where biological cells are modeled as individuals (agents) while molecules are represented by quantities. This hybridization in entity representation entails a combined modeling strategy with agent-based behavioral rules and differential equations, thereby balancing the requirements of extendible model granularity with computational tractability. We demonstrate the efficacy of this approach with models of chemotaxis involving an assay of 10(3) cells and 1.2x10(6) molecules. The model produces cell migration patterns that are comparable to laboratory observations.

Cognitive components underpinning the development of model-based learning.

PubMed

Potter, Tracey C S; Bryce, Nessa V; Hartley, Catherine A

2017-06-01

Reinforcement learning theory distinguishes "model-free" learning, which fosters reflexive repetition of previously rewarded actions, from "model-based" learning, which recruits a mental model of the environment to flexibly select goal-directed actions. Whereas model-free learning is evident across development, recruitment of model-based learning appears to increase with age. However, the cognitive processes underlying the development of model-based learning remain poorly characterized. Here, we examined whether age-related differences in cognitive processes underlying the construction and flexible recruitment of mental models predict developmental increases in model-based choice. In a cohort of participants aged 9-25, we examined whether the abilities to infer sequential regularities in the environment ("statistical learning"), maintain information in an active state ("working memory") and integrate distant concepts to solve problems ("fluid reasoning") predicted age-related improvements in model-based choice. We found that age-related improvements in statistical learning performance did not mediate the relationship between age and model-based choice. Ceiling performance on our working memory assay prevented examination of its contribution to model-based learning. However, age-related improvements in fluid reasoning statistically mediated the developmental increase in the recruitment of a model-based strategy. These findings suggest that gradual development of fluid reasoning may be a critical component process underlying the emergence of model-based learning. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Agent-Based vs. Equation-based Epidemiological Models:A Model Selection Case Study

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

Sukumar, Sreenivas R; Nutaro, James J

This paper is motivated by the need to design model validation strategies for epidemiological disease-spread models. We consider both agent-based and equation-based models of pandemic disease spread and study the nuances and complexities one has to consider from the perspective of model validation. For this purpose, we instantiate an equation based model and an agent based model of the 1918 Spanish flu and we leverage data published in the literature for our case- study. We present our observations from the perspective of each implementation and discuss the application of model-selection criteria to compare the risk in choosing one modeling paradigmmore » to another. We conclude with a discussion of our experience and document future ideas for a model validation framework.« less

Construction of dynamic stochastic simulation models using knowledge-based techniques

NASA Technical Reports Server (NTRS)

Williams, M. Douglas; Shiva, Sajjan G.

1990-01-01

Over the past three decades, computer-based simulation models have proven themselves to be cost-effective alternatives to the more structured deterministic methods of systems analysis. During this time, many techniques, tools and languages for constructing computer-based simulation models have been developed. More recently, advances in knowledge-based system technology have led many researchers to note the similarities between knowledge-based programming and simulation technologies and to investigate the potential application of knowledge-based programming techniques to simulation modeling. The integration of conventional simulation techniques with knowledge-based programming techniques is discussed to provide a development environment for constructing knowledge-based simulation models. A comparison of the techniques used in the construction of dynamic stochastic simulation models and those used in the construction of knowledge-based systems provides the requirements for the environment. This leads to the design and implementation of a knowledge-based simulation development environment. These techniques were used in the construction of several knowledge-based simulation models including the Advanced Launch System Model (ALSYM).

Practical Application of Model-based Programming and State-based Architecture to Space Missions

NASA Technical Reports Server (NTRS)

Horvath, Gregory; Ingham, Michel; Chung, Seung; Martin, Oliver; Williams, Brian

2006-01-01

A viewgraph presentation to develop models from systems engineers that accomplish mission objectives and manage the health of the system is shown. The topics include: 1) Overview; 2) Motivation; 3) Objective/Vision; 4) Approach; 5) Background: The Mission Data System; 6) Background: State-based Control Architecture System; 7) Background: State Analysis; 8) Overview of State Analysis; 9) Background: MDS Software Frameworks; 10) Background: Model-based Programming; 10) Background: Titan Model-based Executive; 11) Model-based Execution Architecture; 12) Compatibility Analysis of MDS and Titan Architectures; 13) Integrating Model-based Programming and Execution into the Architecture; 14) State Analysis and Modeling; 15) IMU Subsystem State Effects Diagram; 16) Titan Subsystem Model: IMU Health; 17) Integrating Model-based Programming and Execution into the Software IMU; 18) Testing Program; 19) Computationally Tractable State Estimation & Fault Diagnosis; 20) Diagnostic Algorithm Performance; 21) Integration and Test Issues; 22) Demonstrated Benefits; and 23) Next Steps

Model-Based Reasoning in Humans Becomes Automatic with Training.

PubMed

Economides, Marcos; Kurth-Nelson, Zeb; Lübbert, Annika; Guitart-Masip, Marc; Dolan, Raymond J

2015-09-01

Model-based and model-free reinforcement learning (RL) have been suggested as algorithmic realizations of goal-directed and habitual action strategies. Model-based RL is more flexible than model-free but requires sophisticated calculations using a learnt model of the world. This has led model-based RL to be identified with slow, deliberative processing, and model-free RL with fast, automatic processing. In support of this distinction, it has recently been shown that model-based reasoning is impaired by placing subjects under cognitive load--a hallmark of non-automaticity. Here, using the same task, we show that cognitive load does not impair model-based reasoning if subjects receive prior training on the task. This finding is replicated across two studies and a variety of analysis methods. Thus, task familiarity permits use of model-based reasoning in parallel with other cognitive demands. The ability to deploy model-based reasoning in an automatic, parallelizable fashion has widespread theoretical implications, particularly for the learning and execution of complex behaviors. It also suggests a range of important failure modes in psychiatric disorders.

The LUE data model for representation of agents and fields

NASA Astrophysics Data System (ADS)

de Jong, Kor; Schmitz, Oliver; Karssenberg, Derek

2017-04-01

Traditionally, agents-based and field-based modelling environments use different data models to represent the state of information they manipulate. In agent-based modelling, involving the representation of phenomena as objects bounded in space and time, agents are often represented by classes, each of which represents a particular kind of agent and all its properties. Such classes can be used to represent entities like people, birds, cars and countries. In field-based modelling, involving the representation of the environment as continuous fields, fields are often represented by a discretization of space, using multidimensional arrays, each storing mostly a single attribute. Such arrays can be used to represent the elevation of the land-surface, the pH of the soil, or the population density in an area, for example. Representing a population of agents by class instances grouped in collections is an intuitive way of organizing information. A drawback, though, is that models in which class instances grouping properties are stored in collections are less efficient (execute slower) than models in which collections of properties are grouped. The field representation, on the other hand, is convenient for the efficient execution of models. Another drawback is that, because the data models used are so different, integrating agent-based and field-based models becomes difficult, since the model builder has to deal with multiple concepts, and often multiple modelling environments. With the development of the LUE data model [1] we aim at representing agents and fields within a single paradigm, by combining the advantages of the data models used in agent-based and field-based data modelling. This removes the barrier for writing integrated agent-based and field-based models. The resulting data model is intuitive to use and allows for efficient execution of models. LUE is both a high-level conceptual data model and a low-level physical data model. The LUE conceptual data model is a generalization of the data models used in agent-based and field-based modelling. The LUE physical data model [2] is an implementation of the LUE conceptual data model in HDF5. In our presentation we will provide details of our approach to organizing information about agents and fields. We will show examples of agent and field data represented by the conceptual and physical data model. References: [1] de Bakker, M.P., de Jong, K., Schmitz, O., Karssenberg, D., 2016. Design and demonstration of a data model to integrate agent-based and field-based modelling. Environmental Modelling and Software. http://dx.doi.org/10.1016/j.envsoft.2016.11.016 [2] de Jong, K., 2017. LUE source code. https://github.com/pcraster/lue

The Use of Modeling-Based Text to Improve Students' Modeling Competencies

ERIC Educational Resources Information Center

Jong, Jing-Ping; Chiu, Mei-Hung; Chung, Shiao-Lan

2015-01-01

This study investigated the effects of a modeling-based text on 10th graders' modeling competencies. Fifteen 10th graders read a researcher-developed modeling-based science text on the ideal gas law that included explicit descriptions and representations of modeling processes (i.e., model selection, model construction, model validation, model…

Building occupancy simulation and data assimilation using a graph-based agent-oriented model

NASA Astrophysics Data System (ADS)

Rai, Sanish; Hu, Xiaolin

2018-07-01

Building occupancy simulation and estimation simulates the dynamics of occupants and estimates their real-time spatial distribution in a building. It requires a simulation model and an algorithm for data assimilation that assimilates real-time sensor data into the simulation model. Existing building occupancy simulation models include agent-based models and graph-based models. The agent-based models suffer high computation cost for simulating large numbers of occupants, and graph-based models overlook the heterogeneity and detailed behaviors of individuals. Recognizing the limitations of existing models, this paper presents a new graph-based agent-oriented model which can efficiently simulate large numbers of occupants in various kinds of building structures. To support real-time occupancy dynamics estimation, a data assimilation framework based on Sequential Monte Carlo Methods is also developed and applied to the graph-based agent-oriented model to assimilate real-time sensor data. Experimental results show the effectiveness of the developed model and the data assimilation framework. The major contributions of this work are to provide an efficient model for building occupancy simulation that can accommodate large numbers of occupants and an effective data assimilation framework that can provide real-time estimations of building occupancy from sensor data.

Anthropometric measures in cardiovascular disease prediction: comparison of laboratory-based versus non-laboratory-based model.

PubMed

Dhana, Klodian; Ikram, M Arfan; Hofman, Albert; Franco, Oscar H; Kavousi, Maryam

2015-03-01

Body mass index (BMI) has been used to simplify cardiovascular risk prediction models by substituting total cholesterol and high-density lipoprotein cholesterol. In the elderly, the ability of BMI as a predictor of cardiovascular disease (CVD) declines. We aimed to find the most predictive anthropometric measure for CVD risk to construct a non-laboratory-based model and to compare it with the model including laboratory measurements. The study included 2675 women and 1902 men aged 55-79 years from the prospective population-based Rotterdam Study. We used Cox proportional hazard regression analysis to evaluate the association of BMI, waist circumference, waist-to-hip ratio and a body shape index (ABSI) with CVD, including coronary heart disease and stroke. The performance of the laboratory-based and non-laboratory-based models was evaluated by studying the discrimination, calibration, correlation and risk agreement. Among men, ABSI was the most informative measure associated with CVD, therefore ABSI was used to construct the non-laboratory-based model. Discrimination of the non-laboratory-based model was not different than laboratory-based model (c-statistic: 0.680-vs-0.683, p=0.71); both models were well calibrated (15.3% observed CVD risk vs 16.9% and 17.0% predicted CVD risks by the non-laboratory-based and laboratory-based models, respectively) and Spearman rank correlation and the agreement between non-laboratory-based and laboratory-based models were 0.89 and 91.7%, respectively. Among women, none of the anthropometric measures were independently associated with CVD. Among middle-aged and elderly where the ability of BMI to predict CVD declines, the non-laboratory-based model, based on ABSI, could predict CVD risk as accurately as the laboratory-based model among men. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

State-of-the-Art Review on Physiologically Based Pharmacokinetic Modeling in Pediatric Drug Development.

PubMed

Yellepeddi, Venkata; Rower, Joseph; Liu, Xiaoxi; Kumar, Shaun; Rashid, Jahidur; Sherwin, Catherine M T

2018-05-18

Physiologically based pharmacokinetic modeling and simulation is an important tool for predicting the pharmacokinetics, pharmacodynamics, and safety of drugs in pediatrics. Physiologically based pharmacokinetic modeling is applied in pediatric drug development for first-time-in-pediatric dose selection, simulation-based trial design, correlation with target organ toxicities, risk assessment by investigating possible drug-drug interactions, real-time assessment of pharmacokinetic-safety relationships, and assessment of non-systemic biodistribution targets. This review summarizes the details of a physiologically based pharmacokinetic modeling approach in pediatric drug research, emphasizing reports on pediatric physiologically based pharmacokinetic models of individual drugs. We also compare and contrast the strategies employed by various researchers in pediatric physiologically based pharmacokinetic modeling and provide a comprehensive overview of physiologically based pharmacokinetic modeling strategies and approaches in pediatrics. We discuss the impact of physiologically based pharmacokinetic models on regulatory reviews and product labels in the field of pediatric pharmacotherapy. Additionally, we examine in detail the current limitations and future directions of physiologically based pharmacokinetic modeling in pediatrics with regard to the ability to predict plasma concentrations and pharmacokinetic parameters. Despite the skepticism and concern in the pediatric community about the reliability of physiologically based pharmacokinetic models, there is substantial evidence that pediatric physiologically based pharmacokinetic models have been used successfully to predict differences in pharmacokinetics between adults and children for several drugs. It is obvious that the use of physiologically based pharmacokinetic modeling to support various stages of pediatric drug development is highly attractive and will rapidly increase, provided the robustness and reliability of these techniques are well established.

A physical data model for fields and agents

NASA Astrophysics Data System (ADS)

de Jong, Kor; de Bakker, Merijn; Karssenberg, Derek

2016-04-01

Two approaches exist in simulation modeling: agent-based and field-based modeling. In agent-based (or individual-based) simulation modeling, the entities representing the system's state are represented by objects, which are bounded in space and time. Individual objects, like an animal, a house, or a more abstract entity like a country's economy, have properties representing their state. In an agent-based model this state is manipulated. In field-based modeling, the entities representing the system's state are represented by fields. Fields capture the state of a continuous property within a spatial extent, examples of which are elevation, atmospheric pressure, and water flow velocity. With respect to the technology used to create these models, the domains of agent-based and field-based modeling have often been separate worlds. In environmental modeling, widely used logical data models include feature data models for point, line and polygon objects, and the raster data model for fields. Simulation models are often either agent-based or field-based, even though the modeled system might contain both entities that are better represented by individuals and entities that are better represented by fields. We think that the reason for this dichotomy in kinds of models might be that the traditional object and field data models underlying those models are relatively low level. We have developed a higher level conceptual data model for representing both non-spatial and spatial objects, and spatial fields (De Bakker et al. 2016). Based on this conceptual data model we designed a logical and physical data model for representing many kinds of data, including the kinds used in earth system modeling (e.g. hydrological and ecological models). The goal of this work is to be able to create high level code and tools for the creation of models in which entities are representable by both objects and fields. Our conceptual data model is capable of representing the traditional feature data models and the raster data model, among many other data models. Our physical data model is capable of storing a first set of kinds of data, like omnipresent scalars, mobile spatio-temporal points and property values, and spatio-temporal rasters. With our poster we will provide an overview of the physical data model expressed in HDF5 and show examples of how it can be used to capture both object- and field-based information. References De Bakker, M, K. de Jong, D. Karssenberg. 2016. A conceptual data model and language for fields and agents. European Geosciences Union, EGU General Assembly, 2016, Vienna.

Cognitive Components Underpinning the Development of Model-Based Learning

PubMed Central

Potter, Tracey C.S.; Bryce, Nessa V.; Hartley, Catherine A.

2016-01-01

Reinforcement learning theory distinguishes “model-free” learning, which fosters reflexive repetition of previously rewarded actions, from “model-based” learning, which recruits a mental model of the environment to flexibly select goal-directed actions. Whereas model-free learning is evident across development, recruitment of model-based learning appears to increase with age. However, the cognitive processes underlying the development of model-based learning remain poorly characterized. Here, we examined whether age-related differences in cognitive processes underlying the construction and flexible recruitment of mental models predict developmental increases in model-based choice. In a cohort of participants aged 9–25, we examined whether the abilities to infer sequential regularities in the environment (“statistical learning”), maintain information in an active state (“working memory”) and integrate distant concepts to solve problems (“fluid reasoning”) predicted age-related improvements in model-based choice. We found that age-related improvements in statistical learning performance did not mediate the relationship between age and model-based choice. Ceiling performance on our working memory assay prevented examination of its contribution to model-based learning. However, age-related improvements in fluid reasoning statistically mediated the developmental increase in the recruitment of a model-based strategy. These findings suggest that gradual development of fluid reasoning may be a critical component process underlying the emergence of model-based learning. PMID:27825732

The "proactive" model of learning: Integrative framework for model-free and model-based reinforcement learning utilizing the associative learning-based proactive brain concept.

PubMed

Zsuga, Judit; Biro, Klara; Papp, Csaba; Tajti, Gabor; Gesztelyi, Rudolf

2016-02-01

Reinforcement learning (RL) is a powerful concept underlying forms of associative learning governed by the use of a scalar reward signal, with learning taking place if expectations are violated. RL may be assessed using model-based and model-free approaches. Model-based reinforcement learning involves the amygdala, the hippocampus, and the orbitofrontal cortex (OFC). The model-free system involves the pedunculopontine-tegmental nucleus (PPTgN), the ventral tegmental area (VTA) and the ventral striatum (VS). Based on the functional connectivity of VS, model-free and model based RL systems center on the VS that by integrating model-free signals (received as reward prediction error) and model-based reward related input computes value. Using the concept of reinforcement learning agent we propose that the VS serves as the value function component of the RL agent. Regarding the model utilized for model-based computations we turned to the proactive brain concept, which offers an ubiquitous function for the default network based on its great functional overlap with contextual associative areas. Hence, by means of the default network the brain continuously organizes its environment into context frames enabling the formulation of analogy-based association that are turned into predictions of what to expect. The OFC integrates reward-related information into context frames upon computing reward expectation by compiling stimulus-reward and context-reward information offered by the amygdala and hippocampus, respectively. Furthermore we suggest that the integration of model-based expectations regarding reward into the value signal is further supported by the efferent of the OFC that reach structures canonical for model-free learning (e.g., the PPTgN, VTA, and VS). (c) 2016 APA, all rights reserved).

Two takes on the ecosystem impacts of climate change and fishing: Comparing a size-based and a species-based ecosystem model in the central North Pacific

NASA Astrophysics Data System (ADS)

Woodworth-Jefcoats, Phoebe A.; Polovina, Jeffrey J.; Howell, Evan A.; Blanchard, Julia L.

2015-11-01

We compare two ecosystem model projections of 21st century climate change and fishing impacts in the central North Pacific. Both a species-based and a size-based ecosystem modeling approach are examined. While both models project a decline in biomass across all sizes in response to climate change and a decline in large fish biomass in response to increased fishing mortality, the models vary significantly in their handling of climate and fishing scenarios. For example, based on the same climate forcing the species-based model projects a 15% decline in catch by the end of the century while the size-based model projects a 30% decline. Disparities in the models' output highlight the limitations of each approach by showing the influence model structure can have on model output. The aspects of bottom-up change to which each model is most sensitive appear linked to model structure, as does the propagation of interannual variability through the food web and the relative impact of combined top-down and bottom-up change. Incorporating integrated size- and species-based ecosystem modeling approaches into future ensemble studies may help separate the influence of model structure from robust projections of ecosystem change.

Model based design introduction: modeling game controllers to microprocessor architectures

NASA Astrophysics Data System (ADS)

Jungwirth, Patrick; Badawy, Abdel-Hameed

2017-04-01

We present an introduction to model based design. Model based design is a visual representation, generally a block diagram, to model and incrementally develop a complex system. Model based design is a commonly used design methodology for digital signal processing, control systems, and embedded systems. Model based design's philosophy is: to solve a problem - a step at a time. The approach can be compared to a series of steps to converge to a solution. A block diagram simulation tool allows a design to be simulated with real world measurement data. For example, if an analog control system is being upgraded to a digital control system, the analog sensor input signals can be recorded. The digital control algorithm can be simulated with the real world sensor data. The output from the simulated digital control system can then be compared to the old analog based control system. Model based design can compared to Agile software develop. The Agile software development goal is to develop working software in incremental steps. Progress is measured in completed and tested code units. Progress is measured in model based design by completed and tested blocks. We present a concept for a video game controller and then use model based design to iterate the design towards a working system. We will also describe a model based design effort to develop an OS Friendly Microprocessor Architecture based on the RISC-V.

Representing Micro-Macro Linkages by Actor-Based Dynamic Network Models

PubMed Central

Snijders, Tom A.B.; Steglich, Christian E.G.

2014-01-01

Stochastic actor-based models for network dynamics have the primary aim of statistical inference about processes of network change, but may be regarded as a kind of agent-based models. Similar to many other agent-based models, they are based on local rules for actor behavior. Different from many other agent-based models, by including elements of generalized linear statistical models they aim to be realistic detailed representations of network dynamics in empirical data sets. Statistical parallels to micro-macro considerations can be found in the estimation of parameters determining local actor behavior from empirical data, and the assessment of goodness of fit from the correspondence with network-level descriptives. This article studies several network-level consequences of dynamic actor-based models applied to represent cross-sectional network data. Two examples illustrate how network-level characteristics can be obtained as emergent features implied by micro-specifications of actor-based models. PMID:25960578

Model compilation: An approach to automated model derivation

NASA Technical Reports Server (NTRS)

Keller, Richard M.; Baudin, Catherine; Iwasaki, Yumi; Nayak, Pandurang; Tanaka, Kazuo

1990-01-01

An approach is introduced to automated model derivation for knowledge based systems. The approach, model compilation, involves procedurally generating the set of domain models used by a knowledge based system. With an implemented example, how this approach can be used to derive models of different precision and abstraction is illustrated, and models are tailored to different tasks, from a given set of base domain models. In particular, two implemented model compilers are described, each of which takes as input a base model that describes the structure and behavior of a simple electromechanical device, the Reaction Wheel Assembly of NASA's Hubble Space Telescope. The compilers transform this relatively general base model into simple task specific models for troubleshooting and redesign, respectively, by applying a sequence of model transformations. Each transformation in this sequence produces an increasingly more specialized model. The compilation approach lessens the burden of updating and maintaining consistency among models by enabling their automatic regeneration.

EPR-based material modelling of soils

NASA Astrophysics Data System (ADS)

Faramarzi, Asaad; Alani, Amir M.

2013-04-01

In the past few decades, as a result of the rapid developments in computational software and hardware, alternative computer aided pattern recognition approaches have been introduced to modelling many engineering problems, including constitutive modelling of materials. The main idea behind pattern recognition systems is that they learn adaptively from experience and extract various discriminants, each appropriate for its purpose. In this work an approach is presented for developing material models for soils based on evolutionary polynomial regression (EPR). EPR is a recently developed hybrid data mining technique that searches for structured mathematical equations (representing the behaviour of a system) using genetic algorithm and the least squares method. Stress-strain data from triaxial tests are used to train and develop EPR-based material models for soil. The developed models are compared with some of the well-known conventional material models and it is shown that EPR-based models can provide a better prediction for the behaviour of soils. The main benefits of using EPR-based material models are that it provides a unified approach to constitutive modelling of all materials (i.e., all aspects of material behaviour can be implemented within a unified environment of an EPR model); it does not require any arbitrary choice of constitutive (mathematical) models. In EPR-based material models there are no material parameters to be identified. As the model is trained directly from experimental data therefore, EPR-based material models are the shortest route from experimental research (data) to numerical modelling. Another advantage of EPR-based constitutive model is that as more experimental data become available, the quality of the EPR prediction can be improved by learning from the additional data, and therefore, the EPR model can become more effective and robust. The developed EPR-based material models can be incorporated in finite element (FE) analysis.

Marker-based or model-based RSA for evaluation of hip resurfacing arthroplasty? A clinical validation and 5-year follow-up.

PubMed

Lorenzen, Nina Dyrberg; Stilling, Maiken; Jakobsen, Stig Storgaard; Gustafson, Klas; Søballe, Kjeld; Baad-Hansen, Thomas

2013-11-01

The stability of implants is vital to ensure a long-term survival. RSA determines micro-motions of implants as a predictor of early implant failure. RSA can be performed as a marker- or model-based analysis. So far, CAD and RE model-based RSA have not been validated for use in hip resurfacing arthroplasty (HRA). A phantom study determined the precision of marker-based and CAD and RE model-based RSA on a HRA implant. In a clinical study, 19 patients were followed with stereoradiographs until 5 years after surgery. Analysis of double-examination migration results determined the clinical precision of marker-based and CAD model-based RSA, and at the 5-year follow-up, results of the total translation (TT) and the total rotation (TR) for marker- and CAD model-based RSA were compared. The phantom study showed that comparison of the precision (SDdiff) in marker-based RSA analysis was more precise than model-based RSA analysis in TT (p CAD < 0.001; p RE = 0.04) and TR (p CAD = 0.01; p RE < 0.001). The clinical precision (double examination in 8 patients) comparing the precision SDdiff was better evaluating the TT using the marker-based RSA analysis (p = 0.002), but showed no difference between the marker- and CAD model-based RSA analysis regarding the TR (p = 0.91). Comparing the mean signed values regarding the TT and the TR at the 5-year follow-up in 13 patients, the TT was lower (p = 0.03) and the TR higher (p = 0.04) in the marker-based RSA compared to CAD model-based RSA. The precision of marker-based RSA was significantly better than model-based RSA. However, problems with occluded markers lead to exclusion of many patients which was not a problem with model-based RSA. HRA were stable at the 5-year follow-up. The detection limit was 0.2 mm TT and 1° TR for marker-based and 0.5 mm TT and 1° TR for CAD model-based RSA for HRA.

Model Documentation of Base Case Data | Regional Energy Deployment System

Science.gov Websites

Model | Energy Analysis | NREL Documentation of Base Case Data Model Documentation of Base Case base case of the model. The base case was developed simply as a point of departure for other analyses Base Case derives many of its inputs from the Energy Information Administration's (EIA's) Annual Energy

Models-Based Practice: Great White Hope or White Elephant?

ERIC Educational Resources Information Center

Casey, Ashley

2014-01-01

Background: Many critical curriculum theorists in physical education have advocated a model- or models-based approach to teaching in the subject. This paper explores the literature base around models-based practice (MBP) and asks if this multi-models approach to curriculum planning has the potential to be the great white hope of pedagogical change…

Testing Strategies for Model-Based Development

NASA Technical Reports Server (NTRS)

Heimdahl, Mats P. E.; Whalen, Mike; Rajan, Ajitha; Miller, Steven P.

2006-01-01

This report presents an approach for testing artifacts generated in a model-based development process. This approach divides the traditional testing process into two parts: requirements-based testing (validation testing) which determines whether the model implements the high-level requirements and model-based testing (conformance testing) which determines whether the code generated from a model is behaviorally equivalent to the model. The goals of the two processes differ significantly and this report explores suitable testing metrics and automation strategies for each. To support requirements-based testing, we define novel objective requirements coverage metrics similar to existing specification and code coverage metrics. For model-based testing, we briefly describe automation strategies and examine the fault-finding capability of different structural coverage metrics using tests automatically generated from the model.

New approaches in agent-based modeling of complex financial systems

NASA Astrophysics Data System (ADS)

Chen, Ting-Ting; Zheng, Bo; Li, Yan; Jiang, Xiong-Fei

2017-12-01

Agent-based modeling is a powerful simulation technique to understand the collective behavior and microscopic interaction in complex financial systems. Recently, the concept for determining the key parameters of agent-based models from empirical data instead of setting them artificially was suggested. We first review several agent-based models and the new approaches to determine the key model parameters from historical market data. Based on the agents' behaviors with heterogeneous personal preferences and interactions, these models are successful in explaining the microscopic origination of the temporal and spatial correlations of financial markets. We then present a novel paradigm combining big-data analysis with agent-based modeling. Specifically, from internet query and stock market data, we extract the information driving forces and develop an agent-based model to simulate the dynamic behaviors of complex financial systems.

Global structure–activity relationship model for nonmutagenic carcinogens using virtual ligand-protein interactions as model descriptors

PubMed Central

Cunningham, Albert R.; Trent, John O.

2012-01-01

Structure–activity relationship (SAR) models are powerful tools to investigate the mechanisms of action of chemical carcinogens and to predict the potential carcinogenicity of untested compounds. We describe the use of a traditional fragment-based SAR approach along with a new virtual ligand-protein interaction-based approach for modeling of nonmutagenic carcinogens. The ligand-based SAR models used descriptors derived from computationally calculated ligand-binding affinities for learning set agents to 5495 proteins. Two learning sets were developed. One set was from the Carcinogenic Potency Database, where chemicals tested for rat carcinogenesis along with Salmonella mutagenicity data were provided. The second was from Malacarne et al. who developed a learning set of nonalerting compounds based on rodent cancer bioassay data and Ashby’s structural alerts. When the rat cancer models were categorized based on mutagenicity, the traditional fragment model outperformed the ligand-based model. However, when the learning sets were composed solely of nonmutagenic or nonalerting carcinogens and noncarcinogens, the fragment model demonstrated a concordance of near 50%, whereas the ligand-based models demonstrated a concordance of 71% for nonmutagenic carcinogens and 74% for nonalerting carcinogens. Overall, these findings suggest that expert system analysis of virtual chemical protein interactions may be useful for developing predictive SAR models for nonmutagenic carcinogens. Moreover, a more practical approach for developing SAR models for carcinogenesis may include fragment-based models for chemicals testing positive for mutagenicity and ligand-based models for chemicals devoid of DNA reactivity. PMID:22678118

Global structure-activity relationship model for nonmutagenic carcinogens using virtual ligand-protein interactions as model descriptors.

PubMed

Cunningham, Albert R; Carrasquer, C Alex; Qamar, Shahid; Maguire, Jon M; Cunningham, Suzanne L; Trent, John O

2012-10-01

Structure-activity relationship (SAR) models are powerful tools to investigate the mechanisms of action of chemical carcinogens and to predict the potential carcinogenicity of untested compounds. We describe the use of a traditional fragment-based SAR approach along with a new virtual ligand-protein interaction-based approach for modeling of nonmutagenic carcinogens. The ligand-based SAR models used descriptors derived from computationally calculated ligand-binding affinities for learning set agents to 5495 proteins. Two learning sets were developed. One set was from the Carcinogenic Potency Database, where chemicals tested for rat carcinogenesis along with Salmonella mutagenicity data were provided. The second was from Malacarne et al. who developed a learning set of nonalerting compounds based on rodent cancer bioassay data and Ashby's structural alerts. When the rat cancer models were categorized based on mutagenicity, the traditional fragment model outperformed the ligand-based model. However, when the learning sets were composed solely of nonmutagenic or nonalerting carcinogens and noncarcinogens, the fragment model demonstrated a concordance of near 50%, whereas the ligand-based models demonstrated a concordance of 71% for nonmutagenic carcinogens and 74% for nonalerting carcinogens. Overall, these findings suggest that expert system analysis of virtual chemical protein interactions may be useful for developing predictive SAR models for nonmutagenic carcinogens. Moreover, a more practical approach for developing SAR models for carcinogenesis may include fragment-based models for chemicals testing positive for mutagenicity and ligand-based models for chemicals devoid of DNA reactivity.

Predictive models for subtypes of autism spectrum disorder based on single-nucleotide polymorphisms and magnetic resonance imaging.

PubMed

Jiao, Y; Chen, R; Ke, X; Cheng, L; Chu, K; Lu, Z; Herskovits, E H

2011-01-01

Autism spectrum disorder (ASD) is a neurodevelopmental disorder, of which Asperger syndrome and high-functioning autism are subtypes. Our goal is: 1) to determine whether a diagnostic model based on single-nucleotide polymorphisms (SNPs), brain regional thickness measurements, or brain regional volume measurements can distinguish Asperger syndrome from high-functioning autism; and 2) to compare the SNP, thickness, and volume-based diagnostic models. Our study included 18 children with ASD: 13 subjects with high-functioning autism and 5 subjects with Asperger syndrome. For each child, we obtained 25 SNPs for 8 ASD-related genes; we also computed regional cortical thicknesses and volumes for 66 brain structures, based on structural magnetic resonance (MR) examination. To generate diagnostic models, we employed five machine-learning techniques: decision stump, alternating decision trees, multi-class alternating decision trees, logistic model trees, and support vector machines. For SNP-based classification, three decision-tree-based models performed better than the other two machine-learning models. The performance metrics for three decision-tree-based models were similar: decision stump was modestly better than the other two methods, with accuracy = 90%, sensitivity = 0.95 and specificity = 0.75. All thickness and volume-based diagnostic models performed poorly. The SNP-based diagnostic models were superior to those based on thickness and volume. For SNP-based classification, rs878960 in GABRB3 (gamma-aminobutyric acid A receptor, beta 3) was selected by all tree-based models. Our analysis demonstrated that SNP-based classification was more accurate than morphometry-based classification in ASD subtype classification. Also, we found that one SNP--rs878960 in GABRB3--distinguishes Asperger syndrome from high-functioning autism.

A Correlation-Based Transition Model using Local Variables. Part 1; Model Formation

NASA Technical Reports Server (NTRS)

Menter, F. R.; Langtry, R. B.; Likki, S. R.; Suzen, Y. B.; Huang, P. G.; Volker, S.

2006-01-01

A new correlation-based transition model has been developed, which is based strictly on local variables. As a result, the transition model is compatible with modern computational fluid dynamics (CFD) approaches, such as unstructured grids and massive parallel execution. The model is based on two transport equations, one for intermittency and one for the transition onset criteria in terms of momentum thickness Reynolds number. The proposed transport equations do not attempt to model the physics of the transition process (unlike, e.g., turbulence models) but from a framework for the implementation of correlation-based models into general-purpose CFD methods.

Guide to APA-Based Models

NASA Technical Reports Server (NTRS)

Robins, Robert E.; Delisi, Donald P.

2008-01-01

In Robins and Delisi (2008), a linear decay model, a new IGE model by Sarpkaya (2006), and a series of APA-Based models were scored using data from three airports. This report is a guide to the APA-based models.

Modeling of the radiation belt megnetosphere in decisional timeframes

DOEpatents

Koller, Josef; Reeves, Geoffrey D; Friedel, Reiner H.W.

2013-04-23

Systems and methods for calculating L* in the magnetosphere with essentially the same accuracy as with a physics based model at many times the speed by developing a surrogate trained to be a surrogate for the physics-based model. The trained model can then beneficially process input data falling within the training range of the surrogate model. The surrogate model can be a feedforward neural network and the physics-based model can be the TSK03 model. Operatively, the surrogate model can use parameters on which the physics-based model was based, and/or spatial data for the location where L* is to be calculated. Surrogate models should be provided for each of a plurality of pitch angles. Accordingly, a surrogate model having a closed drift shell can be used from the plurality of models. The feedforward neural network can have a plurality of input-layer units, there being at least one input-layer unit for each physics-based model parameter, a plurality of hidden layer units and at least one output unit for the value of L*.

A logical model of cooperating rule-based systems

NASA Technical Reports Server (NTRS)

Bailin, Sidney C.; Moore, John M.; Hilberg, Robert H.; Murphy, Elizabeth D.; Bahder, Shari A.

1989-01-01

A model is developed to assist in the planning, specification, development, and verification of space information systems involving distributed rule-based systems. The model is based on an analysis of possible uses of rule-based systems in control centers. This analysis is summarized as a data-flow model for a hypothetical intelligent control center. From this data-flow model, the logical model of cooperating rule-based systems is extracted. This model consists of four layers of increasing capability: (1) communicating agents, (2) belief-sharing knowledge sources, (3) goal-sharing interest areas, and (4) task-sharing job roles.

A new region-edge based level set model with applications to image segmentation

NASA Astrophysics Data System (ADS)

Zhi, Xuhao; Shen, Hong-Bin

2018-04-01

Level set model has advantages in handling complex shapes and topological changes, and is widely used in image processing tasks. The image segmentation oriented level set models can be grouped into region-based models and edge-based models, both of which have merits and drawbacks. Region-based level set model relies on fitting to color intensity of separated regions, but is not sensitive to edge information. Edge-based level set model evolves by fitting to local gradient information, but can get easily affected by noise. We propose a region-edge based level set model, which considers saliency information into energy function and fuses color intensity with local gradient information. The evolution of the proposed model is implemented by a hierarchical two-stage protocol, and the experimental results show flexible initialization, robust evolution and precise segmentation.

Rule-based simulation models

NASA Technical Reports Server (NTRS)

Nieten, Joseph L.; Seraphine, Kathleen M.

1991-01-01

Procedural modeling systems, rule based modeling systems, and a method for converting a procedural model to a rule based model are described. Simulation models are used to represent real time engineering systems. A real time system can be represented by a set of equations or functions connected so that they perform in the same manner as the actual system. Most modeling system languages are based on FORTRAN or some other procedural language. Therefore, they must be enhanced with a reaction capability. Rule based systems are reactive by definition. Once the engineering system has been decomposed into a set of calculations using only basic algebraic unary operations, a knowledge network of calculations and functions can be constructed. The knowledge network required by a rule based system can be generated by a knowledge acquisition tool or a source level compiler. The compiler would take an existing model source file, a syntax template, and a symbol table and generate the knowledge network. Thus, existing procedural models can be translated and executed by a rule based system. Neural models can be provide the high capacity data manipulation required by the most complex real time models.

How Accumulated Real Life Stress Experience and Cognitive Speed Interact on Decision-Making Processes

PubMed Central

Friedel, Eva; Sebold, Miriam; Kuitunen-Paul, Sören; Nebe, Stephan; Veer, Ilya M.; Zimmermann, Ulrich S.; Schlagenhauf, Florian; Smolka, Michael N.; Rapp, Michael; Walter, Henrik; Heinz, Andreas

2017-01-01

Rationale: Advances in neurocomputational modeling suggest that valuation systems for goal-directed (deliberative) on one side, and habitual (automatic) decision-making on the other side may rely on distinct computational strategies for reinforcement learning, namely model-free vs. model-based learning. As a key theoretical difference, the model-based system strongly demands cognitive functions to plan actions prospectively based on an internal cognitive model of the environment, whereas valuation in the model-free system relies on rather simple learning rules from operant conditioning to retrospectively associate actions with their outcomes and is thus cognitively less demanding. Acute stress reactivity is known to impair model-based but not model-free choice behavior, with higher working memory capacity protecting the model-based system from acute stress. However, it is not clear which impact accumulated real life stress has on model-free and model-based decision systems and how this influence interacts with cognitive abilities. Methods: We used a sequential decision-making task distinguishing relative contributions of both learning strategies to choice behavior, the Social Readjustment Rating Scale questionnaire to assess accumulated real life stress, and the Digit Symbol Substitution Test to test cognitive speed in 95 healthy subjects. Results: Individuals reporting high stress exposure who had low cognitive speed showed reduced model-based but increased model-free behavioral control. In contrast, subjects exposed to accumulated real life stress with high cognitive speed displayed increased model-based performance but reduced model-free control. Conclusion: These findings suggest that accumulated real life stress exposure can enhance reliance on cognitive speed for model-based computations, which may ultimately protect the model-based system from the detrimental influences of accumulated real life stress. The combination of accumulated real life stress exposure and slower information processing capacities, however, might favor model-free strategies. Thus, the valence and preference of either system strongly depends on stressful experiences and individual cognitive capacities. PMID:28642696

How Accumulated Real Life Stress Experience and Cognitive Speed Interact on Decision-Making Processes.

PubMed

Friedel, Eva; Sebold, Miriam; Kuitunen-Paul, Sören; Nebe, Stephan; Veer, Ilya M; Zimmermann, Ulrich S; Schlagenhauf, Florian; Smolka, Michael N; Rapp, Michael; Walter, Henrik; Heinz, Andreas

2017-01-01

Rationale: Advances in neurocomputational modeling suggest that valuation systems for goal-directed (deliberative) on one side, and habitual (automatic) decision-making on the other side may rely on distinct computational strategies for reinforcement learning, namely model-free vs. model-based learning. As a key theoretical difference, the model-based system strongly demands cognitive functions to plan actions prospectively based on an internal cognitive model of the environment, whereas valuation in the model-free system relies on rather simple learning rules from operant conditioning to retrospectively associate actions with their outcomes and is thus cognitively less demanding. Acute stress reactivity is known to impair model-based but not model-free choice behavior, with higher working memory capacity protecting the model-based system from acute stress. However, it is not clear which impact accumulated real life stress has on model-free and model-based decision systems and how this influence interacts with cognitive abilities. Methods: We used a sequential decision-making task distinguishing relative contributions of both learning strategies to choice behavior, the Social Readjustment Rating Scale questionnaire to assess accumulated real life stress, and the Digit Symbol Substitution Test to test cognitive speed in 95 healthy subjects. Results: Individuals reporting high stress exposure who had low cognitive speed showed reduced model-based but increased model-free behavioral control. In contrast, subjects exposed to accumulated real life stress with high cognitive speed displayed increased model-based performance but reduced model-free control. Conclusion: These findings suggest that accumulated real life stress exposure can enhance reliance on cognitive speed for model-based computations, which may ultimately protect the model-based system from the detrimental influences of accumulated real life stress. The combination of accumulated real life stress exposure and slower information processing capacities, however, might favor model-free strategies. Thus, the valence and preference of either system strongly depends on stressful experiences and individual cognitive capacities.

Annotation of rule-based models with formal semantics to enable creation, analysis, reuse and visualization.

PubMed

Misirli, Goksel; Cavaliere, Matteo; Waites, William; Pocock, Matthew; Madsen, Curtis; Gilfellon, Owen; Honorato-Zimmer, Ricardo; Zuliani, Paolo; Danos, Vincent; Wipat, Anil

2016-03-15

Biological systems are complex and challenging to model and therefore model reuse is highly desirable. To promote model reuse, models should include both information about the specifics of simulations and the underlying biology in the form of metadata. The availability of computationally tractable metadata is especially important for the effective automated interpretation and processing of models. Metadata are typically represented as machine-readable annotations which enhance programmatic access to information about models. Rule-based languages have emerged as a modelling framework to represent the complexity of biological systems. Annotation approaches have been widely used for reaction-based formalisms such as SBML. However, rule-based languages still lack a rich annotation framework to add semantic information, such as machine-readable descriptions, to the components of a model. We present an annotation framework and guidelines for annotating rule-based models, encoded in the commonly used Kappa and BioNetGen languages. We adapt widely adopted annotation approaches to rule-based models. We initially propose a syntax to store machine-readable annotations and describe a mapping between rule-based modelling entities, such as agents and rules, and their annotations. We then describe an ontology to both annotate these models and capture the information contained therein, and demonstrate annotating these models using examples. Finally, we present a proof of concept tool for extracting annotations from a model that can be queried and analyzed in a uniform way. The uniform representation of the annotations can be used to facilitate the creation, analysis, reuse and visualization of rule-based models. Although examples are given, using specific implementations the proposed techniques can be applied to rule-based models in general. The annotation ontology for rule-based models can be found at http://purl.org/rbm/rbmo The krdf tool and associated executable examples are available at http://purl.org/rbm/rbmo/krdf anil.wipat@newcastle.ac.uk or vdanos@inf.ed.ac.uk. © The Author 2015. Published by Oxford University Press.

Haplotype-Based Genome-Wide Prediction Models Exploit Local Epistatic Interactions Among Markers

PubMed Central

Jiang, Yong; Schmidt, Renate H.; Reif, Jochen C.

2018-01-01

Genome-wide prediction approaches represent versatile tools for the analysis and prediction of complex traits. Mostly they rely on marker-based information, but scenarios have been reported in which models capitalizing on closely-linked markers that were combined into haplotypes outperformed marker-based models. Detailed comparisons were undertaken to reveal under which circumstances haplotype-based genome-wide prediction models are superior to marker-based models. Specifically, it was of interest to analyze whether and how haplotype-based models may take local epistatic effects between markers into account. Assuming that populations consisted of fully homozygous individuals, a marker-based model in which local epistatic effects inside haplotype blocks were exploited (LEGBLUP) was linearly transformable into a haplotype-based model (HGBLUP). This theoretical derivation formally revealed that haplotype-based genome-wide prediction models capitalize on local epistatic effects among markers. Simulation studies corroborated this finding. Due to its computational efficiency the HGBLUP model promises to be an interesting tool for studies in which ultra-high-density SNP data sets are studied. Applying the HGBLUP model to empirical data sets revealed higher prediction accuracies than for marker-based models for both traits studied using a mouse panel. In contrast, only a small subset of the traits analyzed in crop populations showed such a benefit. Cases in which higher prediction accuracies are observed for HGBLUP than for marker-based models are expected to be of immediate relevance for breeders, due to the tight linkage a beneficial haplotype will be preserved for many generations. In this respect the inheritance of local epistatic effects very much resembles the one of additive effects. PMID:29549092

Haplotype-Based Genome-Wide Prediction Models Exploit Local Epistatic Interactions Among Markers.

PubMed

Jiang, Yong; Schmidt, Renate H; Reif, Jochen C

2018-05-04

Genome-wide prediction approaches represent versatile tools for the analysis and prediction of complex traits. Mostly they rely on marker-based information, but scenarios have been reported in which models capitalizing on closely-linked markers that were combined into haplotypes outperformed marker-based models. Detailed comparisons were undertaken to reveal under which circumstances haplotype-based genome-wide prediction models are superior to marker-based models. Specifically, it was of interest to analyze whether and how haplotype-based models may take local epistatic effects between markers into account. Assuming that populations consisted of fully homozygous individuals, a marker-based model in which local epistatic effects inside haplotype blocks were exploited (LEGBLUP) was linearly transformable into a haplotype-based model (HGBLUP). This theoretical derivation formally revealed that haplotype-based genome-wide prediction models capitalize on local epistatic effects among markers. Simulation studies corroborated this finding. Due to its computational efficiency the HGBLUP model promises to be an interesting tool for studies in which ultra-high-density SNP data sets are studied. Applying the HGBLUP model to empirical data sets revealed higher prediction accuracies than for marker-based models for both traits studied using a mouse panel. In contrast, only a small subset of the traits analyzed in crop populations showed such a benefit. Cases in which higher prediction accuracies are observed for HGBLUP than for marker-based models are expected to be of immediate relevance for breeders, due to the tight linkage a beneficial haplotype will be preserved for many generations. In this respect the inheritance of local epistatic effects very much resembles the one of additive effects. Copyright © 2018 Jiang et al.

Gaze data reveal distinct choice processes underlying model-based and model-free reinforcement learning

PubMed Central

Konovalov, Arkady; Krajbich, Ian

2016-01-01

Organisms appear to learn and make decisions using different strategies known as model-free and model-based learning; the former is mere reinforcement of previously rewarded actions and the latter is a forward-looking strategy that involves evaluation of action-state transition probabilities. Prior work has used neural data to argue that both model-based and model-free learners implement a value comparison process at trial onset, but model-based learners assign more weight to forward-looking computations. Here using eye-tracking, we report evidence for a different interpretation of prior results: model-based subjects make their choices prior to trial onset. In contrast, model-free subjects tend to ignore model-based aspects of the task and instead seem to treat the decision problem as a simple comparison process between two differentially valued items, consistent with previous work on sequential-sampling models of decision making. These findings illustrate a problem with assuming that experimental subjects make their decisions at the same prescribed time. PMID:27511383

Of goals and habits: age-related and individual differences in goal-directed decision-making.

PubMed

Eppinger, Ben; Walter, Maik; Heekeren, Hauke R; Li, Shu-Chen

2013-01-01

In this study we investigated age-related and individual differences in habitual (model-free) and goal-directed (model-based) decision-making. Specifically, we were interested in three questions. First, does age affect the balance between model-based and model-free decision mechanisms? Second, are these age-related changes due to age differences in working memory (WM) capacity? Third, can model-based behavior be affected by manipulating the distinctiveness of the reward value of choice options? To answer these questions we used a two-stage Markov decision task in in combination with computational modeling to dissociate model-based and model-free decision mechanisms. To affect model-based behavior in this task we manipulated the distinctiveness of reward probabilities of choice options. The results show age-related deficits in model-based decision-making, which are particularly pronounced if unexpected reward indicates the need for a shift in decision strategy. In this situation younger adults explore the task structure, whereas older adults show perseverative behavior. Consistent with previous findings, these results indicate that older adults have deficits in the representation and updating of expected reward value. We also observed substantial individual differences in model-based behavior. In younger adults high WM capacity is associated with greater model-based behavior and this effect is further elevated when reward probabilities are more distinct. However, in older adults we found no effect of WM capacity. Moreover, age differences in model-based behavior remained statistically significant, even after controlling for WM capacity. Thus, factors other than decline in WM, such as deficits in the in the integration of expected reward value into strategic decisions may contribute to the observed impairments in model-based behavior in older adults.

Of goals and habits: age-related and individual differences in goal-directed decision-making

PubMed Central

Eppinger, Ben; Walter, Maik; Heekeren, Hauke R.; Li, Shu-Chen

2013-01-01

In this study we investigated age-related and individual differences in habitual (model-free) and goal-directed (model-based) decision-making. Specifically, we were interested in three questions. First, does age affect the balance between model-based and model-free decision mechanisms? Second, are these age-related changes due to age differences in working memory (WM) capacity? Third, can model-based behavior be affected by manipulating the distinctiveness of the reward value of choice options? To answer these questions we used a two-stage Markov decision task in in combination with computational modeling to dissociate model-based and model-free decision mechanisms. To affect model-based behavior in this task we manipulated the distinctiveness of reward probabilities of choice options. The results show age-related deficits in model-based decision-making, which are particularly pronounced if unexpected reward indicates the need for a shift in decision strategy. In this situation younger adults explore the task structure, whereas older adults show perseverative behavior. Consistent with previous findings, these results indicate that older adults have deficits in the representation and updating of expected reward value. We also observed substantial individual differences in model-based behavior. In younger adults high WM capacity is associated with greater model-based behavior and this effect is further elevated when reward probabilities are more distinct. However, in older adults we found no effect of WM capacity. Moreover, age differences in model-based behavior remained statistically significant, even after controlling for WM capacity. Thus, factors other than decline in WM, such as deficits in the in the integration of expected reward value into strategic decisions may contribute to the observed impairments in model-based behavior in older adults. PMID:24399925

Using Data-Driven Model-Brain Mappings to Constrain Formal Models of Cognition

PubMed Central

Borst, Jelmer P.; Nijboer, Menno; Taatgen, Niels A.; van Rijn, Hedderik; Anderson, John R.

2015-01-01

In this paper we propose a method to create data-driven mappings from components of cognitive models to brain regions. Cognitive models are notoriously hard to evaluate, especially based on behavioral measures alone. Neuroimaging data can provide additional constraints, but this requires a mapping from model components to brain regions. Although such mappings can be based on the experience of the modeler or on a reading of the literature, a formal method is preferred to prevent researcher-based biases. In this paper we used model-based fMRI analysis to create a data-driven model-brain mapping for five modules of the ACT-R cognitive architecture. We then validated this mapping by applying it to two new datasets with associated models. The new mapping was at least as powerful as an existing mapping that was based on the literature, and indicated where the models were supported by the data and where they have to be improved. We conclude that data-driven model-brain mappings can provide strong constraints on cognitive models, and that model-based fMRI is a suitable way to create such mappings. PMID:25747601

Model-based learning and the contribution of the orbitofrontal cortex to the model-free world

PubMed Central

McDannald, Michael A.; Takahashi, Yuji K.; Lopatina, Nina; Pietras, Brad W.; Jones, Josh L.; Schoenbaum, Geoffrey

2012-01-01

Learning is proposed to occur when there is a discrepancy between reward prediction and reward receipt. At least two separate systems are thought to exist: one in which predictions are proposed to be based on model-free or cached values; and another in which predictions are model-based. A basic neural circuit for model-free reinforcement learning has already been described. In the model-free circuit the ventral striatum (VS) is thought to supply a common-currency reward prediction to midbrain dopamine neurons that compute prediction errors and drive learning. In a model-based system, predictions can include more information about an expected reward, such as its sensory attributes or current, unique value. This detailed prediction allows for both behavioral flexibility and learning driven by changes in sensory features of rewards alone. Recent evidence from animal learning and human imaging suggests that, in addition to model-free information, the VS also signals model-based information. Further, there is evidence that the orbitofrontal cortex (OFC) signals model-based information. Here we review these data and suggest that the OFC provides model-based information to this traditional model-free circuitry and offer possibilities as to how this interaction might occur. PMID:22487030

Model-based influences on humans’ choices and striatal prediction errors

PubMed Central

Daw, Nathaniel D.; Gershman, Samuel J.; Seymour, Ben; Dayan, Peter; Dolan, Raymond J.

2011-01-01

Summary The mesostriatal dopamine system is prominently implicated in model-free reinforcement learning, with fMRI BOLD signals in ventral striatum notably covarying with model-free prediction errors. However, latent learning and devaluation studies show that behavior also shows hallmarks of model-based planning, and the interaction between model-based and model-free values, prediction errors and preferences is underexplored. We designed a multistep decision task in which model-based and model-free influences on human choice behavior could be distinguished. By showing that choices reflected both influences we could then test the purity of the ventral striatal BOLD signal as a model-free report. Contrary to expectations, the signal reflected both model-free and model-based predictions in proportions matching those that best explained choice behavior. These results challenge the notion of a separate model-free learner and suggest a more integrated computational architecture for high-level human decision-making. PMID:21435563

Compartmental and Data-Based Modeling of Cerebral Hemodynamics: Linear Analysis.

PubMed

Henley, B C; Shin, D C; Zhang, R; Marmarelis, V Z

Compartmental and data-based modeling of cerebral hemodynamics are alternative approaches that utilize distinct model forms and have been employed in the quantitative study of cerebral hemodynamics. This paper examines the relation between a compartmental equivalent-circuit and a data-based input-output model of dynamic cerebral autoregulation (DCA) and CO2-vasomotor reactivity (DVR). The compartmental model is constructed as an equivalent-circuit utilizing putative first principles and previously proposed hypothesis-based models. The linear input-output dynamics of this compartmental model are compared with data-based estimates of the DCA-DVR process. This comparative study indicates that there are some qualitative similarities between the two-input compartmental model and experimental results.

A Logical Account of Diagnosis with Multiple Theories

NASA Technical Reports Server (NTRS)

Pandurang, P.; Lum, Henry Jr. (Technical Monitor)

1994-01-01

Model-based diagnosis is a powerful, first-principles approach to diagnosis. The primary drawback with model-based diagnosis is that it is based on a system model, and this model might be inappropriate. The inappropriateness of models usually stems from the fundamental tradeoff between completeness and efficiency. Recently, Struss has developed an elegant proposal for diagnosis with multiple models. Struss characterizes models as relations and develops a precise notion of abstraction. He defines relations between models and analyzes the effect of a model switch on the space of possible diagnoses. In this paper we extend Struss's proposal in three ways. First, our account of diagnosis with multiple models is based on representing models as more expressive first-order theories, rather than as relations. A key technical contribution is the use of a general notion of abstraction based on interpretations between theories. Second, Struss conflates component modes with models, requiring him to define models relations such as choices which result in non-relational models. We avoid this problem by differentiating component modes from models. Third, we present a more general account of simplifications that correctly handles situations where the simplification contradicts the base theory.

Agent-Based Modeling of Chronic Diseases: A Narrative Review and Future Research Directions

PubMed Central

Lawley, Mark A.; Siscovick, David S.; Zhang, Donglan; Pagán, José A.

2016-01-01

The United States is experiencing an epidemic of chronic disease. As the US population ages, health care providers and policy makers urgently need decision models that provide systematic, credible prediction regarding the prevention and treatment of chronic diseases to improve population health management and medical decision-making. Agent-based modeling is a promising systems science approach that can model complex interactions and processes related to chronic health conditions, such as adaptive behaviors, feedback loops, and contextual effects. This article introduces agent-based modeling by providing a narrative review of agent-based models of chronic disease and identifying the characteristics of various chronic health conditions that must be taken into account to build effective clinical- and policy-relevant models. We also identify barriers to adopting agent-based models to study chronic diseases. Finally, we discuss future research directions of agent-based modeling applied to problems related to specific chronic health conditions. PMID:27236380

Agent-Based Modeling of Chronic Diseases: A Narrative Review and Future Research Directions.

PubMed

Li, Yan; Lawley, Mark A; Siscovick, David S; Zhang, Donglan; Pagán, José A

2016-05-26

The United States is experiencing an epidemic of chronic disease. As the US population ages, health care providers and policy makers urgently need decision models that provide systematic, credible prediction regarding the prevention and treatment of chronic diseases to improve population health management and medical decision-making. Agent-based modeling is a promising systems science approach that can model complex interactions and processes related to chronic health conditions, such as adaptive behaviors, feedback loops, and contextual effects. This article introduces agent-based modeling by providing a narrative review of agent-based models of chronic disease and identifying the characteristics of various chronic health conditions that must be taken into account to build effective clinical- and policy-relevant models. We also identify barriers to adopting agent-based models to study chronic diseases. Finally, we discuss future research directions of agent-based modeling applied to problems related to specific chronic health conditions.

In defense of compilation: A response to Davis' form and content in model-based reasoning

NASA Technical Reports Server (NTRS)

Keller, Richard

1990-01-01

In a recent paper entitled 'Form and Content in Model Based Reasoning', Randy Davis argues that model based reasoning research aimed at compiling task specific rules from underlying device models is mislabeled, misguided, and diversionary. Some of Davis' claims are examined and his basic conclusions are challenged about the value of compilation research to the model based reasoning community. In particular, Davis' claim is refuted that model based reasoning is exempt from the efficiency benefits provided by knowledge compilation techniques. In addition, several misconceptions are clarified about the role of representational form in compilation. It is concluded that techniques have the potential to make a substantial contribution to solving tractability problems in model based reasoning.

Logic-Based Models for the Analysis of Cell Signaling Networks†

PubMed Central

2010-01-01

Computational models are increasingly used to analyze the operation of complex biochemical networks, including those involved in cell signaling networks. Here we review recent advances in applying logic-based modeling to mammalian cell biology. Logic-based models represent biomolecular networks in a simple and intuitive manner without describing the detailed biochemistry of each interaction. A brief description of several logic-based modeling methods is followed by six case studies that demonstrate biological questions recently addressed using logic-based models and point to potential advances in model formalisms and training procedures that promise to enhance the utility of logic-based methods for studying the relationship between environmental inputs and phenotypic or signaling state outputs of complex signaling networks. PMID:20225868

Evaluation of model-based versus non-parametric monaural noise-reduction approaches for hearing aids.

PubMed

Harlander, Niklas; Rosenkranz, Tobias; Hohmann, Volker

2012-08-01

Single channel noise reduction has been well investigated and seems to have reached its limits in terms of speech intelligibility improvement, however, the quality of such schemes can still be advanced. This study tests to what extent novel model-based processing schemes might improve performance in particular for non-stationary noise conditions. Two prototype model-based algorithms, a speech-model-based, and a auditory-model-based algorithm were compared to a state-of-the-art non-parametric minimum statistics algorithm. A speech intelligibility test, preference rating, and listening effort scaling were performed. Additionally, three objective quality measures for the signal, background, and overall distortions were applied. For a better comparison of all algorithms, particular attention was given to the usage of the similar Wiener-based gain rule. The perceptual investigation was performed with fourteen hearing-impaired subjects. The results revealed that the non-parametric algorithm and the auditory model-based algorithm did not affect speech intelligibility, whereas the speech-model-based algorithm slightly decreased intelligibility. In terms of subjective quality, both model-based algorithms perform better than the unprocessed condition and the reference in particular for highly non-stationary noise environments. Data support the hypothesis that model-based algorithms are promising for improving performance in non-stationary noise conditions.

Model-based Acceleration Control of Turbofan Engines with a Hammerstein-Wiener Representation

NASA Astrophysics Data System (ADS)

Wang, Jiqiang; Ye, Zhifeng; Hu, Zhongzhi; Wu, Xin; Dimirovsky, Georgi; Yue, Hong

2017-05-01

Acceleration control of turbofan engines is conventionally designed through either schedule-based or acceleration-based approach. With the widespread acceptance of model-based design in aviation industry, it becomes necessary to investigate the issues associated with model-based design for acceleration control. In this paper, the challenges for implementing model-based acceleration control are explained; a novel Hammerstein-Wiener representation of engine models is introduced; based on the Hammerstein-Wiener model, a nonlinear generalized minimum variance type of optimal control law is derived; the feature of the proposed approach is that it does not require the inversion operation that usually upsets those nonlinear control techniques. The effectiveness of the proposed control design method is validated through a detailed numerical study.

Not just the norm: exemplar-based models also predict face aftereffects.

PubMed

Ross, David A; Deroche, Mickael; Palmeri, Thomas J

2014-02-01

The face recognition literature has considered two competing accounts of how faces are represented within the visual system: Exemplar-based models assume that faces are represented via their similarity to exemplars of previously experienced faces, while norm-based models assume that faces are represented with respect to their deviation from an average face, or norm. Face identity aftereffects have been taken as compelling evidence in favor of a norm-based account over an exemplar-based account. After a relatively brief period of adaptation to an adaptor face, the perceived identity of a test face is shifted toward a face with attributes opposite to those of the adaptor, suggesting an explicit psychological representation of the norm. Surprisingly, despite near universal recognition that face identity aftereffects imply norm-based coding, there have been no published attempts to simulate the predictions of norm- and exemplar-based models in face adaptation paradigms. Here, we implemented and tested variations of norm and exemplar models. Contrary to common claims, our simulations revealed that both an exemplar-based model and a version of a two-pool norm-based model, but not a traditional norm-based model, predict face identity aftereffects following face adaptation.

Not Just the Norm: Exemplar-Based Models also Predict Face Aftereffects

PubMed Central

Ross, David A.; Deroche, Mickael; Palmeri, Thomas J.

2014-01-01

The face recognition literature has considered two competing accounts of how faces are represented within the visual system: Exemplar-based models assume that faces are represented via their similarity to exemplars of previously experienced faces, while norm-based models assume that faces are represented with respect to their deviation from an average face, or norm. Face identity aftereffects have been taken as compelling evidence in favor of a norm-based account over an exemplar-based account. After a relatively brief period of adaptation to an adaptor face, the perceived identity of a test face is shifted towards a face with opposite attributes to the adaptor, suggesting an explicit psychological representation of the norm. Surprisingly, despite near universal recognition that face identity aftereffects imply norm-based coding, there have been no published attempts to simulate the predictions of norm- and exemplar-based models in face adaptation paradigms. Here we implemented and tested variations of norm and exemplar models. Contrary to common claims, our simulations revealed that both an exemplar-based model and a version of a two-pool norm-based model, but not a traditional norm-based model, predict face identity aftereffects following face adaptation. PMID:23690282

Agent-based modeling of the spread of the 1918-1919 flu in three Canadian fur trading communities.

PubMed

O'Neil, Caroline A; Sattenspiel, Lisa

2010-01-01

Previous attempts to study the 1918-1919 flu in three small communities in central Manitoba have used both three-community population-based and single-community agent-based models. These studies identified critical factors influencing epidemic spread, but they also left important questions unanswered. The objective of this project was to design a more realistic agent-based model that would overcome limitations of earlier models and provide new insights into these outstanding questions. The new model extends the previous agent-based model to three communities so that results can be compared to those from the population-based model. Sensitivity testing was conducted, and the new model was used to investigate the influence of seasonal settlement and mobility patterns, the geographic heterogeneity of the observed 1918-1919 epidemic in Manitoba, and other questions addressed previously. Results confirm outcomes from the population-based model that suggest that (a) social organization and mobility strongly influence the timing and severity of epidemics and (b) the impact of the epidemic would have been greater if it had arrived in the summer rather than the winter. New insights from the model suggest that the observed heterogeneity among communities in epidemic impact was not unusual and would have been the expected outcome given settlement structure and levels of interaction among communities. Application of an agent-based computer simulation has helped to better explain observed patterns of spread of the 1918-1919 flu epidemic in central Manitoba. Contrasts between agent-based and population-based models illustrate the advantages of agent-based models for the study of small populations. © 2010 Wiley-Liss, Inc.

ALC: automated reduction of rule-based models

PubMed Central

Koschorreck, Markus; Gilles, Ernst Dieter

2008-01-01

Background Combinatorial complexity is a challenging problem for the modeling of cellular signal transduction since the association of a few proteins can give rise to an enormous amount of feasible protein complexes. The layer-based approach is an approximative, but accurate method for the mathematical modeling of signaling systems with inherent combinatorial complexity. The number of variables in the simulation equations is highly reduced and the resulting dynamic models show a pronounced modularity. Layer-based modeling allows for the modeling of systems not accessible previously. Results ALC (Automated Layer Construction) is a computer program that highly simplifies the building of reduced modular models, according to the layer-based approach. The model is defined using a simple but powerful rule-based syntax that supports the concepts of modularity and macrostates. ALC performs consistency checks on the model definition and provides the model output in different formats (C MEX, MATLAB, Mathematica and SBML) as ready-to-run simulation files. ALC also provides additional documentation files that simplify the publication or presentation of the models. The tool can be used offline or via a form on the ALC website. Conclusion ALC allows for a simple rule-based generation of layer-based reduced models. The model files are given in different formats as ready-to-run simulation files. PMID:18973705

Unifying Model-Based and Reactive Programming within a Model-Based Executive

NASA Technical Reports Server (NTRS)

Williams, Brian C.; Gupta, Vineet; Norvig, Peter (Technical Monitor)

1999-01-01

Real-time, model-based, deduction has recently emerged as a vital component in AI's tool box for developing highly autonomous reactive systems. Yet one of the current hurdles towards developing model-based reactive systems is the number of methods simultaneously employed, and their corresponding melange of programming and modeling languages. This paper offers an important step towards unification. We introduce RMPL, a rich modeling language that combines probabilistic, constraint-based modeling with reactive programming constructs, while offering a simple semantics in terms of hidden state Markov processes. We introduce probabilistic, hierarchical constraint automata (PHCA), which allow Markov processes to be expressed in a compact representation that preserves the modularity of RMPL programs. Finally, a model-based executive, called Reactive Burton is described that exploits this compact encoding to perform efficIent simulation, belief state update and control sequence generation.

Model-Based Learning: A Synthesis of Theory and Research

ERIC Educational Resources Information Center

Seel, Norbert M.

2017-01-01

This article provides a review of theoretical approaches to model-based learning and related research. In accordance with the definition of model-based learning as an acquisition and utilization of mental models by learners, the first section centers on mental model theory. In accordance with epistemology of modeling the issues of semantics,…

Research on light rail electric load forecasting based on ARMA model

NASA Astrophysics Data System (ADS)

Huang, Yifan

2018-04-01

The article compares a variety of time series models and combines the characteristics of power load forecasting. Then, a light load forecasting model based on ARMA model is established. Based on this model, a light rail system is forecasted. The prediction results show that the accuracy of the model prediction is high.

A Cyclic-Plasticity-Based Mechanistic Approach for Fatigue Evaluation of 316 Stainless Steel Under Arbitrary Loading

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

Barua, Bipul; Mohanty, Subhasish; Listwan, Joseph T.

In this paper, a cyclic-plasticity based fully mechanistic fatigue modeling approach is presented. This is based on time-dependent stress-strain evolution of the material over the entire fatigue life rather than just based on the end of live information typically used for empirical S~N curve based fatigue evaluation approaches. Previously we presented constant amplitude fatigue test based related material models for 316 SS base, 508 LAS base and 316 SS- 316 SS weld which are used in nuclear reactor components such as pressure vessels, nozzles, and surge line pipes. However, we found that constant amplitude fatigue data based models have limitationmore » in capturing the stress-strain evolution under arbitrary fatigue loading. To address the above mentioned limitation, in this paper, we present a more advanced approach that can be used for modeling the cyclic stress-strain evolution and fatigue life not only under constant amplitude but also under any arbitrary (random/variable) fatigue loading. The related material model and analytical model results are presented for 316 SS base metal. Two methodologies (either based on time/cycle or based on accumulated plastic strain energy) to track the material parameters at a given time/cycle are discussed and associated analytical model results are presented. From the material model and analytical cyclic plasticity model results, it is found that the proposed cyclic plasticity model can predict all the important stages of material behavior during the entire fatigue life of the specimens with more than 90% accuracy« less

A Cyclic-Plasticity-Based Mechanistic Approach for Fatigue Evaluation of 316 Stainless Steel Under Arbitrary Loading

DOE PAGES

Barua, Bipul; Mohanty, Subhasish; Listwan, Joseph T.; ...

2017-12-05

In this paper, a cyclic-plasticity based fully mechanistic fatigue modeling approach is presented. This is based on time-dependent stress-strain evolution of the material over the entire fatigue life rather than just based on the end of live information typically used for empirical S~N curve based fatigue evaluation approaches. Previously we presented constant amplitude fatigue test based related material models for 316 SS base, 508 LAS base and 316 SS- 316 SS weld which are used in nuclear reactor components such as pressure vessels, nozzles, and surge line pipes. However, we found that constant amplitude fatigue data based models have limitationmore » in capturing the stress-strain evolution under arbitrary fatigue loading. To address the above mentioned limitation, in this paper, we present a more advanced approach that can be used for modeling the cyclic stress-strain evolution and fatigue life not only under constant amplitude but also under any arbitrary (random/variable) fatigue loading. The related material model and analytical model results are presented for 316 SS base metal. Two methodologies (either based on time/cycle or based on accumulated plastic strain energy) to track the material parameters at a given time/cycle are discussed and associated analytical model results are presented. From the material model and analytical cyclic plasticity model results, it is found that the proposed cyclic plasticity model can predict all the important stages of material behavior during the entire fatigue life of the specimens with more than 90% accuracy« less

From creatures of habit to goal-directed learners: Tracking the developmental emergence of model-based reinforcement learning

PubMed Central

Decker, Johannes H.; Otto, A. Ross; Daw, Nathaniel D.; Hartley, Catherine A.

2016-01-01

Theoretical models distinguish two decision-making strategies that have been formalized in reinforcement-learning theory. A model-based strategy leverages a cognitive model of potential actions and their consequences to make goal-directed choices, whereas a model-free strategy evaluates actions based solely on their reward history. Research in adults has begun to elucidate the psychological mechanisms and neural substrates underlying these learning processes and factors that influence their relative recruitment. However, the developmental trajectory of these evaluative strategies has not been well characterized. In this study, children, adolescents, and adults, performed a sequential reinforcement-learning task that enables estimation of model-based and model-free contributions to choice. Whereas a model-free strategy was evident in choice behavior across all age groups, evidence of a model-based strategy only emerged during adolescence and continued to increase into adulthood. These results suggest that recruitment of model-based valuation systems represents a critical cognitive component underlying the gradual maturation of goal-directed behavior. PMID:27084852

Geodesy- and geology-based slip-rate models for the Western United States (excluding California) national seismic hazard maps

USGS Publications Warehouse

Petersen, Mark D.; Zeng, Yuehua; Haller, Kathleen M.; McCaffrey, Robert; Hammond, William C.; Bird, Peter; Moschetti, Morgan; Shen, Zhengkang; Bormann, Jayne; Thatcher, Wayne

2014-01-01

The 2014 National Seismic Hazard Maps for the conterminous United States incorporate additional uncertainty in fault slip-rate parameter that controls the earthquake-activity rates than was applied in previous versions of the hazard maps. This additional uncertainty is accounted for by new geodesy- and geology-based slip-rate models for the Western United States. Models that were considered include an updated geologic model based on expert opinion and four combined inversion models informed by both geologic and geodetic input. The two block models considered indicate significantly higher slip rates than the expert opinion and the two fault-based combined inversion models. For the hazard maps, we apply 20 percent weight with equal weighting for the two fault-based models. Off-fault geodetic-based models were not considered in this version of the maps. Resulting changes to the hazard maps are generally less than 0.05 g (acceleration of gravity). Future research will improve the maps and interpret differences between the new models.

Comparative evaluation of urban storm water quality models

NASA Astrophysics Data System (ADS)

Vaze, J.; Chiew, Francis H. S.

2003-10-01

The estimation of urban storm water pollutant loads is required for the development of mitigation and management strategies to minimize impacts to receiving environments. Event pollutant loads are typically estimated using either regression equations or "process-based" water quality models. The relative merit of using regression models compared to process-based models is not clear. A modeling study is carried out here to evaluate the comparative ability of the regression equations and process-based water quality models to estimate event diffuse pollutant loads from impervious surfaces. The results indicate that, once calibrated, both the regression equations and the process-based model can estimate event pollutant loads satisfactorily. In fact, the loads estimated using the regression equation as a function of rainfall intensity and runoff rate are better than the loads estimated using the process-based model. Therefore, if only estimates of event loads are required, regression models should be used because they are simpler and require less data compared to process-based models.

Hirabayashi, Satoshi; Kroll, Charles N.; Nowak, David J. 2011. Component-based development and sensitivity analyses of an air pollutant dry deposition model. Environmental Modelling & Software. 26(6): 804-816.

Treesearch

Satoshi Hirabayashi; Chuck Kroll; David Nowak

2011-01-01

The Urban Forest Effects-Deposition model (UFORE-D) was developed with a component-based modeling approach. Functions of the model were separated into components that are responsible for user interface, data input/output, and core model functions. Taking advantage of the component-based approach, three UFORE-D applications were developed: a base application to estimate...

Competition-Based Learning: A Model for the Integration of Competitions with Project-Based Learning Using Open Source LMS

ERIC Educational Resources Information Center

Issa, Ghassan; Hussain, Shakir M.; Al-Bahadili, Hussein

2014-01-01

In an effort to enhance the learning process in higher education, a new model for Competition-Based Learning (CBL) is presented. The new model utilizes two well-known learning models, namely, the Project-Based Learning (PBL) and competitions. The new model is also applied in a networked environment with emphasis on collective learning as well as…

Technical Note: Approximate Bayesian parameterization of a process-based tropical forest model

NASA Astrophysics Data System (ADS)

Hartig, F.; Dislich, C.; Wiegand, T.; Huth, A.

2014-02-01

Inverse parameter estimation of process-based models is a long-standing problem in many scientific disciplines. A key question for inverse parameter estimation is how to define the metric that quantifies how well model predictions fit to the data. This metric can be expressed by general cost or objective functions, but statistical inversion methods require a particular metric, the probability of observing the data given the model parameters, known as the likelihood. For technical and computational reasons, likelihoods for process-based stochastic models are usually based on general assumptions about variability in the observed data, and not on the stochasticity generated by the model. Only in recent years have new methods become available that allow the generation of likelihoods directly from stochastic simulations. Previous applications of these approximate Bayesian methods have concentrated on relatively simple models. Here, we report on the application of a simulation-based likelihood approximation for FORMIND, a parameter-rich individual-based model of tropical forest dynamics. We show that approximate Bayesian inference, based on a parametric likelihood approximation placed in a conventional Markov chain Monte Carlo (MCMC) sampler, performs well in retrieving known parameter values from virtual inventory data generated by the forest model. We analyze the results of the parameter estimation, examine its sensitivity to the choice and aggregation of model outputs and observed data (summary statistics), and demonstrate the application of this method by fitting the FORMIND model to field data from an Ecuadorian tropical forest. Finally, we discuss how this approach differs from approximate Bayesian computation (ABC), another method commonly used to generate simulation-based likelihood approximations. Our results demonstrate that simulation-based inference, which offers considerable conceptual advantages over more traditional methods for inverse parameter estimation, can be successfully applied to process-based models of high complexity. The methodology is particularly suitable for heterogeneous and complex data structures and can easily be adjusted to other model types, including most stochastic population and individual-based models. Our study therefore provides a blueprint for a fairly general approach to parameter estimation of stochastic process-based models.

Design of a component-based integrated environmental modeling framework

EPA Science Inventory

Integrated environmental modeling (IEM) includes interdependent science-based components (e.g., models, databases, viewers, assessment protocols) that comprise an appropriate software modeling system. The science-based components are responsible for consuming and producing inform...

A Collective Case Study of Secondary Students' Model-Based Inquiry on Natural Selection through Programming in an Agent-Based Modeling Environment

ERIC Educational Resources Information Center

Xiang, Lin

2011-01-01

This is a collective case study seeking to develop detailed descriptions of how programming an agent-based simulation influences a group of 8th grade students' model-based inquiry (MBI) by examining students' agent-based programmable modeling (ABPM) processes and the learning outcomes. The context of the present study was a biology unit on…

SPARK: A Framework for Multi-Scale Agent-Based Biomedical Modeling.

PubMed

Solovyev, Alexey; Mikheev, Maxim; Zhou, Leming; Dutta-Moscato, Joyeeta; Ziraldo, Cordelia; An, Gary; Vodovotz, Yoram; Mi, Qi

2010-01-01

Multi-scale modeling of complex biological systems remains a central challenge in the systems biology community. A method of dynamic knowledge representation known as agent-based modeling enables the study of higher level behavior emerging from discrete events performed by individual components. With the advancement of computer technology, agent-based modeling has emerged as an innovative technique to model the complexities of systems biology. In this work, the authors describe SPARK (Simple Platform for Agent-based Representation of Knowledge), a framework for agent-based modeling specifically designed for systems-level biomedical model development. SPARK is a stand-alone application written in Java. It provides a user-friendly interface, and a simple programming language for developing Agent-Based Models (ABMs). SPARK has the following features specialized for modeling biomedical systems: 1) continuous space that can simulate real physical space; 2) flexible agent size and shape that can represent the relative proportions of various cell types; 3) multiple spaces that can concurrently simulate and visualize multiple scales in biomedical models; 4) a convenient graphical user interface. Existing ABMs of diabetic foot ulcers and acute inflammation were implemented in SPARK. Models of identical complexity were run in both NetLogo and SPARK; the SPARK-based models ran two to three times faster.

Assessing College Students' Understanding of Acid Base Chemistry Concepts

ERIC Educational Resources Information Center

Wan, Yanjun Jean

2014-01-01

Typically most college curricula include three acid base models: Arrhenius', Bronsted-Lowry's, and Lewis'. Although Lewis' acid base model is generally thought to be the most sophisticated among these three models, and can be further applied in reaction mechanisms, most general chemistry curricula either do not include Lewis' acid base model, or…

An object-based storage model for distributed remote sensing images

NASA Astrophysics Data System (ADS)

Yu, Zhanwu; Li, Zhongmin; Zheng, Sheng

2006-10-01

It is very difficult to design an integrated storage solution for distributed remote sensing images to offer high performance network storage services and secure data sharing across platforms using current network storage models such as direct attached storage, network attached storage and storage area network. Object-based storage, as new generation network storage technology emerged recently, separates the data path, the control path and the management path, which solves the bottleneck problem of metadata existed in traditional storage models, and has the characteristics of parallel data access, data sharing across platforms, intelligence of storage devices and security of data access. We use the object-based storage in the storage management of remote sensing images to construct an object-based storage model for distributed remote sensing images. In the storage model, remote sensing images are organized as remote sensing objects stored in the object-based storage devices. According to the storage model, we present the architecture of a distributed remote sensing images application system based on object-based storage, and give some test results about the write performance comparison of traditional network storage model and object-based storage model.

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

PubMed Central

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

2012-01-01

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

Model-based surgical planning and simulation of cranial base surgery.

PubMed

Abe, M; Tabuchi, K; Goto, M; Uchino, A

1998-11-01

Plastic skull models of seven individual patients were fabricated by stereolithography from three-dimensional data based on computed tomography bone images. Skull models were utilized for neurosurgical planning and simulation in the seven patients with cranial base lesions that were difficult to remove. Surgical approaches and areas of craniotomy were evaluated using the fabricated skull models. In preoperative simulations, hand-made models of the tumors, major vessels and nerves were placed in the skull models. Step-by-step simulation of surgical procedures was performed using actual surgical tools. The advantages of using skull models to plan and simulate cranial base surgery include a better understanding of anatomic relationships, preoperative evaluation of the proposed procedure, increased understanding by the patient and family, and improved educational experiences for residents and other medical staff. The disadvantages of using skull models include the time and cost of making the models. The skull models provide a more realistic tool that is easier to handle than computer-graphic images. Surgical simulation using models facilitates difficult cranial base surgery and may help reduce surgical complications.

Modeling river total bed material load discharge using artificial intelligence approaches (based on conceptual inputs)

NASA Astrophysics Data System (ADS)

Roushangar, Kiyoumars; Mehrabani, Fatemeh Vojoudi; Shiri, Jalal

2014-06-01

This study presents Artificial Intelligence (AI)-based modeling of total bed material load through developing the accuracy level of the predictions of traditional models. Gene expression programming (GEP) and adaptive neuro-fuzzy inference system (ANFIS)-based models were developed and validated for estimations. Sediment data from Qotur River (Northwestern Iran) were used for developing and validation of the applied techniques. In order to assess the applied techniques in relation to traditional models, stream power-based and shear stress-based physical models were also applied in the studied case. The obtained results reveal that developed AI-based models using minimum number of dominant factors, give more accurate results than the other applied models. Nonetheless, it was revealed that k-fold test is a practical but high-cost technique for complete scanning of applied data and avoiding the over-fitting.

A Rigorous Temperature-Dependent Stochastic Modelling and Testing for MEMS-Based Inertial Sensor Errors.

PubMed

El-Diasty, Mohammed; Pagiatakis, Spiros

2009-01-01

In this paper, we examine the effect of changing the temperature points on MEMS-based inertial sensor random error. We collect static data under different temperature points using a MEMS-based inertial sensor mounted inside a thermal chamber. Rigorous stochastic models, namely Autoregressive-based Gauss-Markov (AR-based GM) models are developed to describe the random error behaviour. The proposed AR-based GM model is initially applied to short stationary inertial data to develop the stochastic model parameters (correlation times). It is shown that the stochastic model parameters of a MEMS-based inertial unit, namely the ADIS16364, are temperature dependent. In addition, field kinematic test data collected at about 17 °C are used to test the performance of the stochastic models at different temperature points in the filtering stage using Unscented Kalman Filter (UKF). It is shown that the stochastic model developed at 20 °C provides a more accurate inertial navigation solution than the ones obtained from the stochastic models developed at -40 °C, -20 °C, 0 °C, +40 °C, and +60 °C. The temperature dependence of the stochastic model is significant and should be considered at all times to obtain optimal navigation solution for MEMS-based INS/GPS integration.

Predictive representations can link model-based reinforcement learning to model-free mechanisms.

PubMed

Russek, Evan M; Momennejad, Ida; Botvinick, Matthew M; Gershman, Samuel J; Daw, Nathaniel D

2017-09-01

Humans and animals are capable of evaluating actions by considering their long-run future rewards through a process described using model-based reinforcement learning (RL) algorithms. The mechanisms by which neural circuits perform the computations prescribed by model-based RL remain largely unknown; however, multiple lines of evidence suggest that neural circuits supporting model-based behavior are structurally homologous to and overlapping with those thought to carry out model-free temporal difference (TD) learning. Here, we lay out a family of approaches by which model-based computation may be built upon a core of TD learning. The foundation of this framework is the successor representation, a predictive state representation that, when combined with TD learning of value predictions, can produce a subset of the behaviors associated with model-based learning, while requiring less decision-time computation than dynamic programming. Using simulations, we delineate the precise behavioral capabilities enabled by evaluating actions using this approach, and compare them to those demonstrated by biological organisms. We then introduce two new algorithms that build upon the successor representation while progressively mitigating its limitations. Because this framework can account for the full range of observed putatively model-based behaviors while still utilizing a core TD framework, we suggest that it represents a neurally plausible family of mechanisms for model-based evaluation.

Predictive representations can link model-based reinforcement learning to model-free mechanisms

PubMed Central

Botvinick, Matthew M.

2017-01-01

Humans and animals are capable of evaluating actions by considering their long-run future rewards through a process described using model-based reinforcement learning (RL) algorithms. The mechanisms by which neural circuits perform the computations prescribed by model-based RL remain largely unknown; however, multiple lines of evidence suggest that neural circuits supporting model-based behavior are structurally homologous to and overlapping with those thought to carry out model-free temporal difference (TD) learning. Here, we lay out a family of approaches by which model-based computation may be built upon a core of TD learning. The foundation of this framework is the successor representation, a predictive state representation that, when combined with TD learning of value predictions, can produce a subset of the behaviors associated with model-based learning, while requiring less decision-time computation than dynamic programming. Using simulations, we delineate the precise behavioral capabilities enabled by evaluating actions using this approach, and compare them to those demonstrated by biological organisms. We then introduce two new algorithms that build upon the successor representation while progressively mitigating its limitations. Because this framework can account for the full range of observed putatively model-based behaviors while still utilizing a core TD framework, we suggest that it represents a neurally plausible family of mechanisms for model-based evaluation. PMID:28945743

Stimulating Scientific Reasoning with Drawing-Based Modeling

ERIC Educational Resources Information Center

Heijnes, Dewi; van Joolingen, Wouter; Leenaars, Frank

2018-01-01

We investigate the way students' reasoning about evolution can be supported by drawing-based modeling. We modified the drawing-based modeling tool SimSketch to allow for modeling evolutionary processes. In three iterations of development and testing, students in lower secondary education worked on creating an evolutionary model. After each…

Video-Based Modeling: Differential Effects due to Treatment Protocol

ERIC Educational Resources Information Center

Mason, Rose A.; Ganz, Jennifer B.; Parker, Richard I.; Boles, Margot B.; Davis, Heather S.; Rispoli, Mandy J.

2013-01-01

Identifying evidence-based practices for individuals with disabilities requires specification of procedural implementation. Video-based modeling (VBM), consisting of both video self-modeling and video modeling with others as model (VMO), is one class of interventions that has frequently been explored in the literature. However, current information…

Learning of Chemical Equilibrium through Modelling-Based Teaching

ERIC Educational Resources Information Center

Maia, Poliana Flavia; Justi, Rosaria

2009-01-01

This paper presents and discusses students' learning process of chemical equilibrium from a modelling-based approach developed from the use of the "Model of Modelling" diagram. The investigation was conducted in a regular classroom (students 14-15 years old) and aimed at discussing how modelling-based teaching can contribute to students…

A 4DCT imaging-based breathing lung model with relative hysteresis

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

Miyawaki, Shinjiro; Choi, Sanghun; Hoffman, Eric A.

To reproduce realistic airway motion and airflow, the authors developed a deforming lung computational fluid dynamics (CFD) model based on four-dimensional (4D, space and time) dynamic computed tomography (CT) images. A total of 13 time points within controlled tidal volume respiration were used to account for realistic and irregular lung motion in human volunteers. Because of the irregular motion of 4DCT-based airways, we identified an optimal interpolation method for airway surface deformation during respiration, and implemented a computational solid mechanics-based moving mesh algorithm to produce smooth deforming airway mesh. In addition, we developed physiologically realistic airflow boundary conditions for bothmore » models based on multiple images and a single image. Furthermore, we examined simplified models based on one or two dynamic or static images. By comparing these simplified models with the model based on 13 dynamic images, we investigated the effects of relative hysteresis of lung structure with respect to lung volume, lung deformation, and imaging methods, i.e., dynamic vs. static scans, on CFD-predicted pressure drop. The effect of imaging method on pressure drop was 24 percentage points due to the differences in airflow distribution and airway geometry. - Highlights: • We developed a breathing human lung CFD model based on 4D-dynamic CT images. • The 4DCT-based breathing lung model is able to capture lung relative hysteresis. • A new boundary condition for lung model based on one static CT image was proposed. • The difference between lung models based on 4D and static CT images was quantified.« less

The impact of design-based modeling instruction on seventh graders' spatial abilities and model-based argumentation

NASA Astrophysics Data System (ADS)

McConnell, William J.

Due to the call of current science education reform for the integration of engineering practices within science classrooms, design-based instruction is receiving much attention in science education literature. Although some aspect of modeling is often included in well-known design-based instructional methods, it is not always a primary focus. The purpose of this study was to better understand how design-based instruction with an emphasis on scientific modeling might impact students' spatial abilities and their model-based argumentation abilities. In the following mixed-method multiple case study, seven seventh grade students attending a secular private school in the Mid-Atlantic region of the United States underwent an instructional intervention involving design-based instruction, modeling and argumentation. Through the course of a lesson involving students in exploring the interrelatedness of the environment and an animal's form and function, students created and used multiple forms of expressed models to assist them in model-based scientific argument. Pre/post data were collected through the use of The Purdue Spatial Visualization Test: Rotation, the Mental Rotation Test and interviews. Other data included a spatial activities survey, student artifacts in the form of models, notes, exit tickets, and video recordings of students throughout the intervention. Spatial abilities tests were analyzed using descriptive statistics while students' arguments were analyzed using the Instrument for the Analysis of Scientific Curricular Arguments and a behavior protocol. Models were analyzed using content analysis and interviews and all other data were coded and analyzed for emergent themes. Findings in the area of spatial abilities included increases in spatial reasoning for six out of seven participants, and an immense difference in the spatial challenges encountered by students when using CAD software instead of paper drawings to create models. Students perceived 3D printed models to better assist them in scientific argumentation over paper drawing models. In fact, when given a choice, students rarely used paper drawing to assist in argument. There was also a difference in model utility between the two different model types. Participants explicitly used 3D printed models to complete gestural modeling, while participants rarely looked at 2D models when involved in gestural modeling. This study's findings added to current theory dealing with the varied spatial challenges involved in different modes of expressed models. This study found that depth, symmetry and the manipulation of perspectives are typically spatial challenges students will attend to using CAD while they will typically ignore them when drawing using paper and pencil. This study also revealed a major difference in model-based argument in a design-based instruction context as opposed to model-based argument in a typical science classroom context. In the context of design-based instruction, data revealed that design process is an important part of model-based argument. Due to the importance of design process in model-based argumentation in this context, trusted methods of argument analysis, like the coding system of the IASCA, was found lacking in many respects. Limitations and recommendations for further research were also presented.

Multiscale Modeling of Angiogenesis and Predictive Capacity

NASA Astrophysics Data System (ADS)

Pillay, Samara; Byrne, Helen; Maini, Philip

Tumors induce the growth of new blood vessels from existing vasculature through angiogenesis. Using an agent-based approach, we model the behavior of individual endothelial cells during angiogenesis. We incorporate crowding effects through volume exclusion, motility of cells through biased random walks, and include birth and death-like processes. We use the transition probabilities associated with the discrete model and a discrete conservation equation for cell occupancy to determine collective cell behavior, in terms of partial differential equations (PDEs). We derive three PDE models incorporating single, multi-species and no volume exclusion. By fitting the parameters in our PDE models and other well-established continuum models to agent-based simulations during a specific time period, and then comparing the outputs from the PDE models and agent-based model at later times, we aim to determine how well the PDE models predict the future behavior of the agent-based model. We also determine whether predictions differ across PDE models and the significance of those differences. This may impact drug development strategies based on PDE models.

Model-based influences on humans' choices and striatal prediction errors.

PubMed

Daw, Nathaniel D; Gershman, Samuel J; Seymour, Ben; Dayan, Peter; Dolan, Raymond J

2011-03-24

The mesostriatal dopamine system is prominently implicated in model-free reinforcement learning, with fMRI BOLD signals in ventral striatum notably covarying with model-free prediction errors. However, latent learning and devaluation studies show that behavior also shows hallmarks of model-based planning, and the interaction between model-based and model-free values, prediction errors, and preferences is underexplored. We designed a multistep decision task in which model-based and model-free influences on human choice behavior could be distinguished. By showing that choices reflected both influences we could then test the purity of the ventral striatal BOLD signal as a model-free report. Contrary to expectations, the signal reflected both model-free and model-based predictions in proportions matching those that best explained choice behavior. These results challenge the notion of a separate model-free learner and suggest a more integrated computational architecture for high-level human decision-making. Copyright © 2011 Elsevier Inc. All rights reserved.

Introducing the fit-criteria assessment plot - A visualisation tool to assist class enumeration in group-based trajectory modelling.

PubMed

Klijn, Sven L; Weijenberg, Matty P; Lemmens, Paul; van den Brandt, Piet A; Lima Passos, Valéria

2017-10-01

Background and objective Group-based trajectory modelling is a model-based clustering technique applied for the identification of latent patterns of temporal changes. Despite its manifold applications in clinical and health sciences, potential problems of the model selection procedure are often overlooked. The choice of the number of latent trajectories (class-enumeration), for instance, is to a large degree based on statistical criteria that are not fail-safe. Moreover, the process as a whole is not transparent. To facilitate class enumeration, we introduce a graphical summary display of several fit and model adequacy criteria, the fit-criteria assessment plot. Methods An R-code that accepts universal data input is presented. The programme condenses relevant group-based trajectory modelling output information of model fit indices in automated graphical displays. Examples based on real and simulated data are provided to illustrate, assess and validate fit-criteria assessment plot's utility. Results Fit-criteria assessment plot provides an overview of fit criteria on a single page, placing users in an informed position to make a decision. Fit-criteria assessment plot does not automatically select the most appropriate model but eases the model assessment procedure. Conclusions Fit-criteria assessment plot is an exploratory, visualisation tool that can be employed to assist decisions in the initial and decisive phase of group-based trajectory modelling analysis. Considering group-based trajectory modelling's widespread resonance in medical and epidemiological sciences, a more comprehensive, easily interpretable and transparent display of the iterative process of class enumeration may foster group-based trajectory modelling's adequate use.

State-based versus reward-based motivation in younger and older adults.

PubMed

Worthy, Darrell A; Cooper, Jessica A; Byrne, Kaileigh A; Gorlick, Marissa A; Maddox, W Todd

2014-12-01

Recent decision-making work has focused on a distinction between a habitual, model-free neural system that is motivated toward actions that lead directly to reward and a more computationally demanding goal-directed, model-based system that is motivated toward actions that improve one's future state. In this article, we examine how aging affects motivation toward reward-based versus state-based decision making. Participants performed tasks in which one type of option provided larger immediate rewards but the alternative type of option led to larger rewards on future trials, or improvements in state. We predicted that older adults would show a reduced preference for choices that led to improvements in state and a greater preference for choices that maximized immediate reward. We also predicted that fits from a hybrid reinforcement-learning model would indicate greater model-based strategy use in younger than in older adults. In line with these predictions, older adults selected the options that maximized reward more often than did younger adults in three of the four tasks, and modeling results suggested reduced model-based strategy use. In the task where older adults showed similar behavior to younger adults, our model-fitting results suggested that this was due to the utilization of a win-stay-lose-shift heuristic rather than a more complex model-based strategy. Additionally, within older adults, we found that model-based strategy use was positively correlated with memory measures from our neuropsychological test battery. We suggest that this shift from state-based to reward-based motivation may be due to age related declines in the neural structures needed for more computationally demanding model-based decision making.

A Resource-Based Modelling Framework to Assess Habitat Suitability for Steppe Birds in Semiarid Mediterranean Agricultural Systems

PubMed Central

Cardador, Laura; De Cáceres, Miquel; Bota, Gerard; Giralt, David; Casas, Fabián; Arroyo, Beatriz; Mougeot, François; Cantero-Martínez, Carlos; Moncunill, Judit; Butler, Simon J.; Brotons, Lluís

2014-01-01

European agriculture is undergoing widespread changes that are likely to have profound impacts on farmland biodiversity. The development of tools that allow an assessment of the potential biodiversity effects of different land-use alternatives before changes occur is fundamental to guiding management decisions. In this study, we develop a resource-based model framework to estimate habitat suitability for target species, according to simple information on species’ key resource requirements (diet, foraging habitat and nesting site), and examine whether it can be used to link land-use and local species’ distribution. We take as a study case four steppe bird species in a lowland area of the north-eastern Iberian Peninsula. We also compare the performance of our resource-based approach to that obtained through habitat-based models relating species’ occurrence and land-cover variables. Further, we use our resource-based approach to predict the effects that change in farming systems can have on farmland bird habitat suitability and compare these predictions with those obtained using the habitat-based models. Habitat suitability estimates generated by our resource-based models performed similarly (and better for one study species) than habitat based-models when predicting current species distribution. Moderate prediction success was achieved for three out of four species considered by resource-based models and for two of four by habitat-based models. Although, there is potential for improving the performance of resource-based models, they provide a structure for using available knowledge of the functional links between agricultural practices, provision of key resources and the response of organisms to predict potential effects of changing land-uses in a variety of context or the impacts of changes such as altered management practices that are not easily incorporated into habitat-based models. PMID:24667825

What are the Starting Points? Evaluating Base-Year Assumptions in the Asian Modeling Exercise

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

Chaturvedi, Vaibhav; Waldhoff, Stephanie; Clarke, Leon E.

2012-12-01

A common feature of model inter-comparison efforts is that the base year numbers for important parameters such as population and GDP can differ substantially across models. This paper explores the sources and implications of this variation in Asian countries across the models participating in the Asian Modeling Exercise (AME). Because the models do not all have a common base year, each team was required to provide data for 2005 for comparison purposes. This paper compares the year 2005 information for different models, noting the degree of variation in important parameters, including population, GDP, primary energy, electricity, and CO2 emissions. Itmore » then explores the difference in these key parameters across different sources of base-year information. The analysis confirms that the sources provide different values for many key parameters. This variation across data sources and additional reasons why models might provide different base-year numbers, including differences in regional definitions, differences in model base year, and differences in GDP transformation methodologies, are then discussed in the context of the AME scenarios. Finally, the paper explores the implications of base-year variation on long-term model results.« less

Argumentation in Science Education: A Model-based Framework

NASA Astrophysics Data System (ADS)

Böttcher, Florian; Meisert, Anke

2011-02-01

The goal of this article is threefold: First, the theoretical background for a model-based framework of argumentation to describe and evaluate argumentative processes in science education is presented. Based on the general model-based perspective in cognitive science and the philosophy of science, it is proposed to understand arguments as reasons for the appropriateness of a theoretical model which explains a certain phenomenon. Argumentation is considered to be the process of the critical evaluation of such a model if necessary in relation to alternative models. Secondly, some methodological details are exemplified for the use of a model-based analysis in the concrete classroom context. Third, the application of the approach in comparison with other analytical models will be presented to demonstrate the explicatory power and depth of the model-based perspective. Primarily, the framework of Toulmin to structurally analyse arguments is contrasted with the approach presented here. It will be demonstrated how common methodological and theoretical problems in the context of Toulmin's framework can be overcome through a model-based perspective. Additionally, a second more complex argumentative sequence will also be analysed according to the invented analytical scheme to give a broader impression of its potential in practical use.

Simulating Cancer Growth with Multiscale Agent-Based Modeling

PubMed Central

Wang, Zhihui; Butner, Joseph D.; Kerketta, Romica; Cristini, Vittorio; Deisboeck, Thomas S.

2014-01-01

There have been many techniques developed in recent years to in silico model a variety of cancer behaviors. Agent-based modeling is a specific discrete-based hybrid modeling approach that allows simulating the role of diversity in cell populations as well as within each individual cell; it has therefore become a powerful modeling method widely used by computational cancer researchers. Many aspects of tumor morphology including phenotype-changing mutations, the adaptation to microenvironment, the process of angiogenesis, the influence of extracellular matrix, reactions to chemotherapy or surgical intervention, the effects of oxygen and nutrient availability, and metastasis and invasion of healthy tissues have been incorporated and investigated in agent-based models. In this review, we introduce some of the most recent agent-based models that have provided insight into the understanding of cancer growth and invasion, spanning multiple biological scales in time and space, and we further describe several experimentally testable hypotheses generated by those models. We also discuss some of the current challenges of multiscale agent-based cancer models. PMID:24793698

Model-Based Diagnosis in a Power Distribution Test-Bed

NASA Technical Reports Server (NTRS)

Scarl, E.; McCall, K.

1998-01-01

The Rodon model-based diagnosis shell was applied to a breadboard test-bed, modeling an automated power distribution system. The constraint-based modeling paradigm and diagnostic algorithm were found to adequately represent the selected set of test scenarios.

Comparison of land use regression models for NO2 based on routine and campaign monitoring data from an urban area of Japan.

PubMed

Kashima, Saori; Yorifuji, Takashi; Sawada, Norie; Nakaya, Tomoki; Eboshida, Akira

2018-08-01

Typically, land use regression (LUR) models have been developed using campaign monitoring data rather than routine monitoring data. However, the latter have advantages such as low cost and long-term coverage. Based on the idea that LUR models representing regional differences in air pollution and regional road structures are optimal, the objective of this study was to evaluate the validity of LUR models for nitrogen dioxide (NO 2 ) based on routine and campaign monitoring data obtained from an urban area. We selected the city of Suita in Osaka (Japan). We built a model based on routine monitoring data obtained from all sites (routine-LUR-All), and a model based on campaign monitoring data (campaign-LUR) within the city. Models based on routine monitoring data obtained from background sites (routine-LUR-BS) and based on data obtained from roadside sites (routine-LUR-RS) were also built. The routine LUR models were based on monitoring networks across two prefectures (i.e., Osaka and Hyogo prefectures). We calculated the predictability of the each model. We then compared the predicted NO 2 concentrations from each model with measured annual average NO 2 concentrations from evaluation sites. The routine-LUR-All and routine-LUR-BS models both predicted NO 2 concentrations well: adjusted R 2 =0.68 and 0.76, respectively, and root mean square error=3.4 and 2.1ppb, respectively. The predictions from the routine-LUR-All model were highly correlated with the measured NO 2 concentrations at evaluation sites. Although the predicted NO 2 concentrations from each model were correlated, the LUR models based on routine networks, and particularly those based on all monitoring sites, provided better visual representations of the local road conditions in the city. The present study demonstrated that LUR models based on routine data could estimate local traffic-related air pollution in an urban area. The importance and usefulness of data from routine monitoring networks should be acknowledged. Copyright © 2018 Elsevier B.V. All rights reserved.

Sequential optimization of a terrestrial biosphere model constrained by multiple satellite based products

NASA Astrophysics Data System (ADS)

Ichii, K.; Kondo, M.; Wang, W.; Hashimoto, H.; Nemani, R. R.

2012-12-01

Various satellite-based spatial products such as evapotranspiration (ET) and gross primary productivity (GPP) are now produced by integration of ground and satellite observations. Effective use of these multiple satellite-based products in terrestrial biosphere models is an important step toward better understanding of terrestrial carbon and water cycles. However, due to the complexity of terrestrial biosphere models with large number of model parameters, the application of these spatial data sets in terrestrial biosphere models is difficult. In this study, we established an effective but simple framework to refine a terrestrial biosphere model, Biome-BGC, using multiple satellite-based products as constraints. We tested the framework in the monsoon Asia region covered by AsiaFlux observations. The framework is based on the hierarchical analysis (Wang et al. 2009) with model parameter optimization constrained by satellite-based spatial data. The Biome-BGC model is separated into several tiers to minimize the freedom of model parameter selections and maximize the independency from the whole model. For example, the snow sub-model is first optimized using MODIS snow cover product, followed by soil water sub-model optimized by satellite-based ET (estimated by an empirical upscaling method; Support Vector Regression (SVR) method; Yang et al. 2007), photosynthesis model optimized by satellite-based GPP (based on SVR method), and respiration and residual carbon cycle models optimized by biomass data. As a result of initial assessment, we found that most of default sub-models (e.g. snow, water cycle and carbon cycle) showed large deviations from remote sensing observations. However, these biases were removed by applying the proposed framework. For example, gross primary productivities were initially underestimated in boreal and temperate forest and overestimated in tropical forests. However, the parameter optimization scheme successfully reduced these biases. Our analysis shows that terrestrial carbon and water cycle simulations in monsoon Asia were greatly improved, and the use of multiple satellite observations with this framework is an effective way for improving terrestrial biosphere models.

Bridging process-based and empirical approaches to modeling tree growth

Treesearch

Harry T. Valentine; Annikki Makela; Annikki Makela

2005-01-01

The gulf between process-based and empirical approaches to modeling tree growth may be bridged, in part, by the use of a common model. To this end, we have formulated a process-based model of tree growth that can be fitted and applied in an empirical mode. The growth model is grounded in pipe model theory and an optimal control model of crown development. Together, the...

EMPIRE and pyenda: Two ensemble-based data assimilation systems written in Fortran and Python

NASA Astrophysics Data System (ADS)

Geppert, Gernot; Browne, Phil; van Leeuwen, Peter Jan; Merker, Claire

2017-04-01

We present and compare the features of two ensemble-based data assimilation frameworks, EMPIRE and pyenda. Both frameworks allow to couple models to the assimilation codes using the Message Passing Interface (MPI), leading to extremely efficient and fast coupling between models and the data-assimilation codes. The Fortran-based system EMPIRE (Employing Message Passing Interface for Researching Ensembles) is optimized for parallel, high-performance computing. It currently includes a suite of data assimilation algorithms including variants of the ensemble Kalman and several the particle filters. EMPIRE is targeted at models of all kinds of complexity and has been coupled to several geoscience models, eg. the Lorenz-63 model, a barotropic vorticity model, the general circulation model HadCM3, the ocean model NEMO, and the land-surface model JULES. The Python-based system pyenda (Python Ensemble Data Assimilation) allows Fortran- and Python-based models to be used for data assimilation. Models can be coupled either using MPI or by using a Python interface. Using Python allows quick prototyping and pyenda is aimed at small to medium scale models. pyenda currently includes variants of the ensemble Kalman filter and has been coupled to the Lorenz-63 model, an advection-based precipitation nowcasting scheme, and the dynamic global vegetation model JSBACH.

Abstracting event-based control models for high autonomy systems

NASA Technical Reports Server (NTRS)

Luh, Cheng-Jye; Zeigler, Bernard P.

1993-01-01

A high autonomy system needs many models on which to base control, management, design, and other interventions. These models differ in level of abstraction and in formalism. Concepts and tools are needed to organize the models into a coherent whole. The paper deals with the abstraction processes for systematic derivation of related models for use in event-based control. The multifaceted modeling methodology is briefly reviewed. The morphism concepts needed for application to model abstraction are described. A theory for supporting the construction of DEVS models needed for event-based control is then presented. An implemented morphism on the basis of this theory is also described.

Model Based Analysis and Test Generation for Flight Software

NASA Technical Reports Server (NTRS)

Pasareanu, Corina S.; Schumann, Johann M.; Mehlitz, Peter C.; Lowry, Mike R.; Karsai, Gabor; Nine, Harmon; Neema, Sandeep

2009-01-01

We describe a framework for model-based analysis and test case generation in the context of a heterogeneous model-based development paradigm that uses and combines Math- Works and UML 2.0 models and the associated code generation tools. This paradigm poses novel challenges to analysis and test case generation that, to the best of our knowledge, have not been addressed before. The framework is based on a common intermediate representation for different modeling formalisms and leverages and extends model checking and symbolic execution tools for model analysis and test case generation, respectively. We discuss the application of our framework to software models for a NASA flight mission.

A Research on the Generative Learning Model Supported by Context-Based Learning

ERIC Educational Resources Information Center

Ulusoy, Fatma Merve; Onen, Aysem Seda

2014-01-01

This study is based on the generative learning model which involves context-based learning. Using the generative learning model, we taught the topic of Halogens. This topic is covered in the grade 10 chemistry curriculum using activities which are designed in accordance with the generative learning model supported by context-based learning. The…

When Does Model-Based Control Pay Off?

PubMed

Kool, Wouter; Cushman, Fiery A; Gershman, Samuel J

2016-08-01

Many accounts of decision making and reinforcement learning posit the existence of two distinct systems that control choice: a fast, automatic system and a slow, deliberative system. Recent research formalizes this distinction by mapping these systems to "model-free" and "model-based" strategies in reinforcement learning. Model-free strategies are computationally cheap, but sometimes inaccurate, because action values can be accessed by inspecting a look-up table constructed through trial-and-error. In contrast, model-based strategies compute action values through planning in a causal model of the environment, which is more accurate but also more cognitively demanding. It is assumed that this trade-off between accuracy and computational demand plays an important role in the arbitration between the two strategies, but we show that the hallmark task for dissociating model-free and model-based strategies, as well as several related variants, do not embody such a trade-off. We describe five factors that reduce the effectiveness of the model-based strategy on these tasks by reducing its accuracy in estimating reward outcomes and decreasing the importance of its choices. Based on these observations, we describe a version of the task that formally and empirically obtains an accuracy-demand trade-off between model-free and model-based strategies. Moreover, we show that human participants spontaneously increase their reliance on model-based control on this task, compared to the original paradigm. Our novel task and our computational analyses may prove important in subsequent empirical investigations of how humans balance accuracy and demand.

AGENT-BASED MODELS IN EMPIRICAL SOCIAL RESEARCH*

PubMed Central

Bruch, Elizabeth; Atwell, Jon

2014-01-01

Agent-based modeling has become increasingly popular in recent years, but there is still no codified set of recommendations or practices for how to use these models within a program of empirical research. This article provides ideas and practical guidelines drawn from sociology, biology, computer science, epidemiology, and statistics. We first discuss the motivations for using agent-based models in both basic science and policy-oriented social research. Next, we provide an overview of methods and strategies for incorporating data on behavior and populations into agent-based models, and review techniques for validating and testing the sensitivity of agent-based models. We close with suggested directions for future research. PMID:25983351

Models of Quantitative Estimations: Rule-Based and Exemplar-Based Processes Compared

ERIC Educational Resources Information Center

von Helversen, Bettina; Rieskamp, Jorg

2009-01-01

The cognitive processes underlying quantitative estimations vary. Past research has identified task-contingent changes between rule-based and exemplar-based processes (P. Juslin, L. Karlsson, & H. Olsson, 2008). B. von Helversen and J. Rieskamp (2008), however, proposed a simple rule-based model--the mapping model--that outperformed the…

Control algorithms and applications of the wavefront sensorless adaptive optics

NASA Astrophysics Data System (ADS)

Ma, Liang; Wang, Bin; Zhou, Yuanshen; Yang, Huizhen

2017-10-01

Compared with the conventional adaptive optics (AO) system, the wavefront sensorless (WFSless) AO system need not to measure the wavefront and reconstruct it. It is simpler than the conventional AO in system architecture and can be applied to the complex conditions. Based on the analysis of principle and system model of the WFSless AO system, wavefront correction methods of the WFSless AO system were divided into two categories: model-free-based and model-based control algorithms. The WFSless AO system based on model-free-based control algorithms commonly considers the performance metric as a function of the control parameters and then uses certain control algorithm to improve the performance metric. The model-based control algorithms include modal control algorithms, nonlinear control algorithms and control algorithms based on geometrical optics. Based on the brief description of above typical control algorithms, hybrid methods combining the model-free-based control algorithm with the model-based control algorithm were generalized. Additionally, characteristics of various control algorithms were compared and analyzed. We also discussed the extensive applications of WFSless AO system in free space optical communication (FSO), retinal imaging in the human eye, confocal microscope, coherent beam combination (CBC) techniques and extended objects.

Testing the Predictive Power of Coulomb Stress on Aftershock Sequences

NASA Astrophysics Data System (ADS)

Woessner, J.; Lombardi, A.; Werner, M. J.; Marzocchi, W.

2009-12-01

Empirical and statistical models of clustered seismicity are usually strongly stochastic and perceived to be uninformative in their forecasts, since only marginal distributions are used, such as the Omori-Utsu and Gutenberg-Richter laws. In contrast, so-called physics-based aftershock models, based on seismic rate changes calculated from Coulomb stress changes and rate-and-state friction, make more specific predictions: anisotropic stress shadows and multiplicative rate changes. We test the predictive power of models based on Coulomb stress changes against statistical models, including the popular Short Term Earthquake Probabilities and Epidemic-Type Aftershock Sequences models: We score and compare retrospective forecasts on the aftershock sequences of the 1992 Landers, USA, the 1997 Colfiorito, Italy, and the 2008 Selfoss, Iceland, earthquakes. To quantify predictability, we use likelihood-based metrics that test the consistency of the forecasts with the data, including modified and existing tests used in prospective forecast experiments within the Collaboratory for the Study of Earthquake Predictability (CSEP). Our results indicate that a statistical model performs best. Moreover, two Coulomb model classes seem unable to compete: Models based on deterministic Coulomb stress changes calculated from a given fault-slip model, and those based on fixed receiver faults. One model of Coulomb stress changes does perform well and sometimes outperforms the statistical models, but its predictive information is diluted, because of uncertainties included in the fault-slip model. Our results suggest that models based on Coulomb stress changes need to incorporate stochastic features that represent model and data uncertainty.

Evidence for Model-based Computations in the Human Amygdala during Pavlovian Conditioning

PubMed Central

Prévost, Charlotte; McNamee, Daniel; Jessup, Ryan K.; Bossaerts, Peter; O'Doherty, John P.

2013-01-01

Contemporary computational accounts of instrumental conditioning have emphasized a role for a model-based system in which values are computed with reference to a rich model of the structure of the world, and a model-free system in which values are updated without encoding such structure. Much less studied is the possibility of a similar distinction operating at the level of Pavlovian conditioning. In the present study, we scanned human participants while they participated in a Pavlovian conditioning task with a simple structure while measuring activity in the human amygdala using a high-resolution fMRI protocol. After fitting a model-based algorithm and a variety of model-free algorithms to the fMRI data, we found evidence for the superiority of a model-based algorithm in accounting for activity in the amygdala compared to the model-free counterparts. These findings support an important role for model-based algorithms in describing the processes underpinning Pavlovian conditioning, as well as providing evidence of a role for the human amygdala in model-based inference. PMID:23436990

From Creatures of Habit to Goal-Directed Learners: Tracking the Developmental Emergence of Model-Based Reinforcement Learning.

PubMed

Decker, Johannes H; Otto, A Ross; Daw, Nathaniel D; Hartley, Catherine A

2016-06-01

Theoretical models distinguish two decision-making strategies that have been formalized in reinforcement-learning theory. A model-based strategy leverages a cognitive model of potential actions and their consequences to make goal-directed choices, whereas a model-free strategy evaluates actions based solely on their reward history. Research in adults has begun to elucidate the psychological mechanisms and neural substrates underlying these learning processes and factors that influence their relative recruitment. However, the developmental trajectory of these evaluative strategies has not been well characterized. In this study, children, adolescents, and adults performed a sequential reinforcement-learning task that enabled estimation of model-based and model-free contributions to choice. Whereas a model-free strategy was apparent in choice behavior across all age groups, a model-based strategy was absent in children, became evident in adolescents, and strengthened in adults. These results suggest that recruitment of model-based valuation systems represents a critical cognitive component underlying the gradual maturation of goal-directed behavior. © The Author(s) 2016.

A web-based portfolio model as the students' final assignment: Dealing with the development of higher education trend

NASA Astrophysics Data System (ADS)

Utanto, Yuli; Widhanarto, Ghanis Putra; Maretta, Yoris Adi

2017-03-01

This study aims to develop a web-based portfolio model. The model developed in this study could reveal the effectiveness of the new model in experiments conducted at research respondents in the department of curriculum and educational technology FIP Unnes. In particular, the further research objectives to be achieved through this development of research, namely: (1) Describing the process of implementing a portfolio in a web-based model; (2) Assessing the effectiveness of web-based portfolio model for the final task, especially in Web-Based Learning courses. This type of research is the development of research Borg and Gall (2008: 589) says "educational research and development (R & D) is a process used to develop and validate educational production". The series of research and development carried out starting with exploration and conceptual studies, followed by testing and evaluation, and also implementation. For the data analysis, the technique used is simple descriptive analysis, analysis of learning completeness, which then followed by prerequisite test for normality and homogeneity to do T - test. Based on the data analysis, it was concluded that: (1) a web-based portfolio model can be applied to learning process in higher education; (2) The effectiveness of web-based portfolio model with field data from the respondents of large group trial participants (field trial), the number of respondents who reached mastery learning (a score of 60 and above) were 24 people (92.3%) in which it indicates that the web-based portfolio model is effective. The conclusion of this study is that a web-based portfolio model is effective. The implications of the research development of this model, the next researcher is expected to be able to use the guideline of the development model based on the research that has already been conducted to be developed on other subjects.

Ensuring congruency in multiscale modeling: towards linking agent based and continuum biomechanical models of arterial adaptation.

PubMed

Hayenga, Heather N; Thorne, Bryan C; Peirce, Shayn M; Humphrey, Jay D

2011-11-01

There is a need to develop multiscale models of vascular adaptations to understand tissue-level manifestations of cellular level mechanisms. Continuum-based biomechanical models are well suited for relating blood pressures and flows to stress-mediated changes in geometry and properties, but less so for describing underlying mechanobiological processes. Discrete stochastic agent-based models are well suited for representing biological processes at a cellular level, but not for describing tissue-level mechanical changes. We present here a conceptually new approach to facilitate the coupling of continuum and agent-based models. Because of ubiquitous limitations in both the tissue- and cell-level data from which one derives constitutive relations for continuum models and rule-sets for agent-based models, we suggest that model verification should enforce congruency across scales. That is, multiscale model parameters initially determined from data sets representing different scales should be refined, when possible, to ensure that common outputs are consistent. Potential advantages of this approach are illustrated by comparing simulated aortic responses to a sustained increase in blood pressure predicted by continuum and agent-based models both before and after instituting a genetic algorithm to refine 16 objectively bounded model parameters. We show that congruency-based parameter refinement not only yielded increased consistency across scales, it also yielded predictions that are closer to in vivo observations.

PRESS-based EFOR algorithm for the dynamic parametrical modeling of nonlinear MDOF systems

NASA Astrophysics Data System (ADS)

Liu, Haopeng; Zhu, Yunpeng; Luo, Zhong; Han, Qingkai

2017-09-01

In response to the identification problem concerning multi-degree of freedom (MDOF) nonlinear systems, this study presents the extended forward orthogonal regression (EFOR) based on predicted residual sums of squares (PRESS) to construct a nonlinear dynamic parametrical model. The proposed parametrical model is based on the non-linear autoregressive with exogenous inputs (NARX) model and aims to explicitly reveal the physical design parameters of the system. The PRESS-based EFOR algorithm is proposed to identify such a model for MDOF systems. By using the algorithm, we built a common-structured model based on the fundamental concept of evaluating its generalization capability through cross-validation. The resulting model aims to prevent over-fitting with poor generalization performance caused by the average error reduction ratio (AERR)-based EFOR algorithm. Then, a functional relationship is established between the coefficients of the terms and the design parameters of the unified model. Moreover, a 5-DOF nonlinear system is taken as a case to illustrate the modeling of the proposed algorithm. Finally, a dynamic parametrical model of a cantilever beam is constructed from experimental data. Results indicate that the dynamic parametrical model of nonlinear systems, which depends on the PRESS-based EFOR, can accurately predict the output response, thus providing a theoretical basis for the optimal design of modeling methods for MDOF nonlinear systems.

Model-based learning and the contribution of the orbitofrontal cortex to the model-free world.

PubMed

McDannald, Michael A; Takahashi, Yuji K; Lopatina, Nina; Pietras, Brad W; Jones, Josh L; Schoenbaum, Geoffrey

2012-04-01

Learning is proposed to occur when there is a discrepancy between reward prediction and reward receipt. At least two separate systems are thought to exist: one in which predictions are proposed to be based on model-free or cached values; and another in which predictions are model-based. A basic neural circuit for model-free reinforcement learning has already been described. In the model-free circuit the ventral striatum (VS) is thought to supply a common-currency reward prediction to midbrain dopamine neurons that compute prediction errors and drive learning. In a model-based system, predictions can include more information about an expected reward, such as its sensory attributes or current, unique value. This detailed prediction allows for both behavioral flexibility and learning driven by changes in sensory features of rewards alone. Recent evidence from animal learning and human imaging suggests that, in addition to model-free information, the VS also signals model-based information. Further, there is evidence that the orbitofrontal cortex (OFC) signals model-based information. Here we review these data and suggest that the OFC provides model-based information to this traditional model-free circuitry and offer possibilities as to how this interaction might occur. © 2012 The Authors. European Journal of Neuroscience © 2012 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

Fundamental Algorithms of the Goddard Battery Model

NASA Technical Reports Server (NTRS)

Jagielski, J. M.

1985-01-01

The Goddard Space Flight Center (GSFC) is currently producing a computer model to predict Nickel Cadmium (NiCd) performance in a Low Earth Orbit (LEO) cycling regime. The model proper is currently still in development, but the inherent, fundamental algorithms (or methodologies) of the model are defined. At present, the model is closely dependent on empirical data and the data base currently used is of questionable accuracy. Even so, very good correlations have been determined between model predictions and actual cycling data. A more accurate and encompassing data base has been generated to serve dual functions: show the limitations of the current data base, and be inbred in the model properly for more accurate predictions. The fundamental algorithms of the model, and the present data base and its limitations, are described and a brief preliminary analysis of the new data base and its verification of the model's methodology are presented.

Model-Driven Useware Engineering

NASA Astrophysics Data System (ADS)

Meixner, Gerrit; Seissler, Marc; Breiner, Kai

User-oriented hardware and software development relies on a systematic development process based on a comprehensive analysis focusing on the users' requirements and preferences. Such a development process calls for the integration of numerous disciplines, from psychology and ergonomics to computer sciences and mechanical engineering. Hence, a correspondingly interdisciplinary team must be equipped with suitable software tools to allow it to handle the complexity of a multimodal and multi-device user interface development approach. An abstract, model-based development approach seems to be adequate for handling this complexity. This approach comprises different levels of abstraction requiring adequate tool support. Thus, in this chapter, we present the current state of our model-based software tool chain. We introduce the use model as the core model of our model-based process, transformation processes, and a model-based architecture, and we present different software tools that provide support for creating and maintaining the models or performing the necessary model transformations.

Effects of linking a soil-water-balance model with a groundwater-flow model

USGS Publications Warehouse

Stanton, Jennifer S.; Ryter, Derek W.; Peterson, Steven M.

2013-01-01

A previously published regional groundwater-flow model in north-central Nebraska was sequentially linked with the recently developed soil-water-balance (SWB) model to analyze effects to groundwater-flow model parameters and calibration results. The linked models provided a more detailed spatial and temporal distribution of simulated recharge based on hydrologic processes, improvement of simulated groundwater-level changes and base flows at specific sites in agricultural areas, and a physically based assessment of the relative magnitude of recharge for grassland, nonirrigated cropland, and irrigated cropland areas. Root-mean-squared (RMS) differences between the simulated and estimated or measured target values for the previously published model and linked models were relatively similar and did not improve for all types of calibration targets. However, without any adjustment to the SWB-generated recharge, the RMS difference between simulated and estimated base-flow target values for the groundwater-flow model was slightly smaller than for the previously published model, possibly indicating that the volume of recharge simulated by the SWB code was closer to actual hydrogeologic conditions than the previously published model provided. Groundwater-level and base-flow hydrographs showed that temporal patterns of simulated groundwater levels and base flows were more accurate for the linked models than for the previously published model at several sites, particularly in agricultural areas.

Validating the ACE Model for Evaluating Student Performance Using a Teaching-Learning Process Based on Computational Modeling Systems

ERIC Educational Resources Information Center

Louzada, Alexandre Neves; Elia, Marcos da Fonseca; Sampaio, Fábio Ferrentini; Vidal, Andre Luiz Pestana

2014-01-01

The aim of this work is to adapt and test, in a Brazilian public school, the ACE model proposed by Borkulo for evaluating student performance as a teaching-learning process based on computational modeling systems. The ACE model is based on different types of reasoning involving three dimensions. In addition to adapting the model and introducing…

Promoting Evidence-Based Practice: Models and Mechanisms from Cross-Sector Review

ERIC Educational Resources Information Center

Nutley, Sandra; Walter, Isabel; Davies, Huw T. O.

2009-01-01

This article draws on both a cross-sector literature review of mechanisms to promote evidence-based practice and a specific review of ways of improving research use in social care. At the heart of the article is a discussion of three models of evidence-based practice: the research-based practitioner model, the embedded research model, and the…

A Model-based Approach to Reactive Self-Configuring Systems

NASA Technical Reports Server (NTRS)

Williams, Brian C.; Nayak, P. Pandurang

1996-01-01

This paper describes Livingstone, an implemented kernel for a self-reconfiguring autonomous system, that is reactive and uses component-based declarative models. The paper presents a formal characterization of the representation formalism used in Livingstone, and reports on our experience with the implementation in a variety of domains. Livingstone's representation formalism achieves broad coverage of hybrid software/hardware systems by coupling the concurrent transition system models underlying concurrent reactive languages with the discrete qualitative representations developed in model-based reasoning. We achieve a reactive system that performs significant deductions in the sense/response loop by drawing on our past experience at building fast prepositional conflict-based algorithms for model-based diagnosis, and by framing a model-based configuration manager as a prepositional, conflict-based feedback controller that generates focused, optimal responses. Livingstone automates all these tasks using a single model and a single core deductive engine, thus making significant progress towards achieving a central goal of model-based reasoning. Livingstone, together with the HSTS planning and scheduling engine and the RAPS executive, has been selected as the core autonomy architecture for Deep Space One, the first spacecraft for NASA's New Millennium program.

Comparison of an Agent-based Model of Disease Propagation with the Generalised SIR Epidemic Model

DTIC Science & Technology

2009-08-01

has become a practical method for conducting Epidemiological Modelling. In the agent- based approach the whole township can be modelled as a system of...SIR system was initially developed based on a very simplified model of social interaction. For instance an assumption of uniform population mixing was...simulating the progress of a disease within a host and of transmission between hosts is based upon Transportation Analysis and Simulation System

A method for diagnosing time dependent faults using model-based reasoning systems

NASA Technical Reports Server (NTRS)

Goodrich, Charles H.

1995-01-01

This paper explores techniques to apply model-based reasoning to equipment and systems which exhibit dynamic behavior (that which changes as a function of time). The model-based system of interest is KATE-C (Knowledge based Autonomous Test Engineer) which is a C++ based system designed to perform monitoring and diagnosis of Space Shuttle electro-mechanical systems. Methods of model-based monitoring and diagnosis are well known and have been thoroughly explored by others. A short example is given which illustrates the principle of model-based reasoning and reveals some limitations of static, non-time-dependent simulation. This example is then extended to demonstrate representation of time-dependent behavior and testing of fault hypotheses in that environment.

Revisiting node-based SIR models in complex networks with degree correlations

NASA Astrophysics Data System (ADS)

Wang, Yi; Cao, Jinde; Alofi, Abdulaziz; AL-Mazrooei, Abdullah; Elaiw, Ahmed

2015-11-01

In this paper, we consider two growing networks which will lead to the degree-degree correlations between two nearest neighbors in the network. When the network grows to some certain size, we introduce an SIR-like disease such as pandemic influenza H1N1/09 to the population. Due to its rapid spread, the population size changes slowly, and thus the disease spreads on correlated networks with approximately fixed size. To predict the disease evolution on correlated networks, we first review two node-based SIR models incorporating degree correlations and an edge-based SIR model without considering degree correlation, and then compare the predictions of these models with stochastic SIR simulations, respectively. We find that the edge-based model, even without considering degree correlations, agrees much better than the node-based models incorporating degree correlations with stochastic SIR simulations in many respects. Moreover, simulation results show that for networks with positive correlation, the edge-based model provides a better upper bound of the cumulative incidence than the node-based SIR models, whereas for networks with negative correlation, it provides a lower bound of the cumulative incidence.

Hydrological modelling in forested systems | Science ...

EPA Pesticide Factsheets

This chapter provides a brief overview of forest hydrology modelling approaches for answering important global research and management questions. Many hundreds of hydrological models have been applied globally across multiple decades to represent and predict forest hydrological processes. The focus of this chapter is on process-based models and approaches, specifically 'forest hydrology models'; that is, physically based simulation tools that quantify compartments of the forest hydrological cycle. Physically based models can be considered those that describe the conservation of mass, momentum and/or energy. The purpose of this chapter is to provide a brief overview of forest hydrology modeling approaches for answering important global research and management questions. The focus of this chapter is on process-based models and approaches, specifically “forest hydrology models”, i.e., physically-based simulation tools that quantify compartments of the forest hydrological cycle.

Understanding Elementary Astronomy by Making Drawing-Based Models

NASA Astrophysics Data System (ADS)

van Joolingen, W. R.; Aukes, Annika V. A.; Gijlers, H.; Bollen, L.

2015-04-01

Modeling is an important approach in the teaching and learning of science. In this study, we attempt to bring modeling within the reach of young children by creating the SimSketch modeling system, which is based on freehand drawings that can be turned into simulations. This system was used by 247 children (ages ranging from 7 to 15) to create a drawing-based model of the solar system. The results show that children in the target age group are capable of creating a drawing-based model of the solar system and can use it to show the situations in which eclipses occur. Structural equation modeling predicting post-test knowledge scores based on learners' pre-test knowledge scores, the quality of their drawings and motivational aspects yielded some evidence that such drawing contributes to learning. Consequences for using modeling with young children are considered.

Going beyond the unitary curve: incorporating richer cognition into agent-based water resources models

NASA Astrophysics Data System (ADS)

Kock, B. E.

2008-12-01

The increased availability and understanding of agent-based modeling technology and techniques provides a unique opportunity for water resources modelers, allowing them to go beyond traditional behavioral approaches from neoclassical economics, and add rich cognition to social-hydrological models. Agent-based models provide for an individual focus, and the easier and more realistic incorporation of learning, memory and other mechanisms for increased cognitive sophistication. We are in an age of global change impacting complex water resources systems, and social responses are increasingly recognized as fundamentally adaptive and emergent. In consideration of this, water resources models and modelers need to better address social dynamics in a manner beyond the capabilities of neoclassical economics theory and practice. However, going beyond the unitary curve requires unique levels of engagement with stakeholders, both to elicit the richer knowledge necessary for structuring and parameterizing agent-based models, but also to make sure such models are appropriately used. With the aim of encouraging epistemological and methodological convergence in the agent-based modeling of water resources, we have developed a water resources-specific cognitive model and an associated collaborative modeling process. Our cognitive model emphasizes efficiency in architecture and operation, and capacity to adapt to different application contexts. We describe a current application of this cognitive model and modeling process in the Arkansas Basin of Colorado. In particular, we highlight the potential benefits of, and challenges to, using more sophisticated cognitive models in agent-based water resources models.

Evaluating Emulation-based Models of Distributed Computing Systems

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

Jones, Stephen T.; Gabert, Kasimir G.; Tarman, Thomas D.

Emulation-based models of distributed computing systems are collections of virtual ma- chines, virtual networks, and other emulation components configured to stand in for oper- ational systems when performing experimental science, training, analysis of design alterna- tives, test and evaluation, or idea generation. As with any tool, we should carefully evaluate whether our uses of emulation-based models are appropriate and justified. Otherwise, we run the risk of using a model incorrectly and creating meaningless results. The variety of uses of emulation-based models each have their own goals and deserve thoughtful evaluation. In this paper, we enumerate some of these uses andmore » describe approaches that one can take to build an evidence-based case that a use of an emulation-based model is credible. Predictive uses of emulation-based models, where we expect a model to tell us something true about the real world, set the bar especially high and the principal evaluation method, called validation , is comensurately rigorous. We spend the majority of our time describing and demonstrating the validation of a simple predictive model using a well-established methodology inherited from decades of development in the compuational science and engineering community.« less

Derivation of Continuum Models from An Agent-based Cancer Model: Optimization and Sensitivity Analysis.

PubMed

Voulgarelis, Dimitrios; Velayudhan, Ajoy; Smith, Frank

2017-01-01

Agent-based models provide a formidable tool for exploring complex and emergent behaviour of biological systems as well as accurate results but with the drawback of needing a lot of computational power and time for subsequent analysis. On the other hand, equation-based models can more easily be used for complex analysis in a much shorter timescale. This paper formulates an ordinary differential equations and stochastic differential equations model to capture the behaviour of an existing agent-based model of tumour cell reprogramming and applies it to optimization of possible treatment as well as dosage sensitivity analysis. For certain values of the parameter space a close match between the equation-based and agent-based models is achieved. The need for division of labour between the two approaches is explored. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

A Novel Modeling Method for Aircraft Engine Using Nonlinear Autoregressive Exogenous (NARX) Models Based on Wavelet Neural Networks

NASA Astrophysics Data System (ADS)

Yu, Bing; Shu, Wenjun; Cao, Can

2018-05-01

A novel modeling method for aircraft engine using nonlinear autoregressive exogenous (NARX) models based on wavelet neural networks is proposed. The identification principle and process based on wavelet neural networks are studied, and the modeling scheme based on NARX is proposed. Then, the time series data sets from three types of aircraft engines are utilized to build the corresponding NARX models, and these NARX models are validated by the simulation. The results show that all the best NARX models can capture the original aircraft engine's dynamic characteristic well with the high accuracy. For every type of engine, the relative identification errors of its best NARX model and the component level model are no more than 3.5 % and most of them are within 1 %.

Mosquito population dynamics from cellular automata-based simulation

NASA Astrophysics Data System (ADS)

Syafarina, Inna; Sadikin, Rifki; Nuraini, Nuning

2016-02-01

In this paper we present an innovative model for simulating mosquito-vector population dynamics. The simulation consist of two stages: demography and dispersal dynamics. For demography simulation, we follow the existing model for modeling a mosquito life cycles. Moreover, we use cellular automata-based model for simulating dispersal of the vector. In simulation, each individual vector is able to move to other grid based on a random walk. Our model is also capable to represent immunity factor for each grid. We simulate the model to evaluate its correctness. Based on the simulations, we can conclude that our model is correct. However, our model need to be improved to find a realistic parameters to match real data.

A Systematic Review of Agent-Based Modelling and Simulation Applications in the Higher Education Domain

ERIC Educational Resources Information Center

Gu, X.; Blackmore, K. L.

2015-01-01

This paper presents the results of a systematic review of agent-based modelling and simulation (ABMS) applications in the higher education (HE) domain. Agent-based modelling is a "bottom-up" modelling paradigm in which system-level behaviour (macro) is modelled through the behaviour of individual local-level agent interactions (micro).…

Integrating Mathematical Modeling for Undergraduate Pre-Service Science Education Learning and Instruction in Middle School Classrooms

ERIC Educational Resources Information Center

Carrejo, David; Robertson, William H.

2011-01-01

Computer-based mathematical modeling in physics is a process of constructing models of concepts and the relationships between them in the scientific characteristics of work. In this manner, computer-based modeling integrates the interactions of natural phenomenon through the use of models, which provide structure for theories and a base for…

Extension of landscape-based population viability models to ecoregional scales for conservation planning

Treesearch

Thomas W. Bonnot; Frank R. III Thompson; Joshua Millspaugh

2011-01-01

Landscape-based population models are potentially valuable tools in facilitating conservation planning and actions at large scales. However, such models have rarely been applied at ecoregional scales. We extended landscape-based population models to ecoregional scales for three species of concern in the Central Hardwoods Bird Conservation Region and compared model...

Development and validation of deterioration models for concrete bridge decks - phase 2 : mechanics-based degradation models.

DOT National Transportation Integrated Search

2013-06-01

This report summarizes a research project aimed at developing degradation models for bridge decks in the state of Michigan based on durability mechanics. A probabilistic framework to implement local-level mechanistic-based models for predicting the c...

FRAMEWORK FOR EVALUATION OF PHYSIOLOGICALLY-BASED PHARMACOKINETIC MODELS FOR USE IN SAFETY OR RISK ASSESSMENT

EPA Science Inventory

ABSTRACT

Proposed applications of increasingly sophisticated biologically-based computational models, such as physiologically-based pharmacokinetic (PBPK) models, raise the issue of how to evaluate whether the models are adequate for proposed uses including safety or risk ...

Technical Note: Approximate Bayesian parameterization of a complex tropical forest model

NASA Astrophysics Data System (ADS)

Hartig, F.; Dislich, C.; Wiegand, T.; Huth, A.

2013-08-01

Inverse parameter estimation of process-based models is a long-standing problem in ecology and evolution. A key problem of inverse parameter estimation is to define a metric that quantifies how well model predictions fit to the data. Such a metric can be expressed by general cost or objective functions, but statistical inversion approaches are based on a particular metric, the probability of observing the data given the model, known as the likelihood. Deriving likelihoods for dynamic models requires making assumptions about the probability for observations to deviate from mean model predictions. For technical reasons, these assumptions are usually derived without explicit consideration of the processes in the simulation. Only in recent years have new methods become available that allow generating likelihoods directly from stochastic simulations. Previous applications of these approximate Bayesian methods have concentrated on relatively simple models. Here, we report on the application of a simulation-based likelihood approximation for FORMIND, a parameter-rich individual-based model of tropical forest dynamics. We show that approximate Bayesian inference, based on a parametric likelihood approximation placed in a conventional MCMC, performs well in retrieving known parameter values from virtual field data generated by the forest model. We analyze the results of the parameter estimation, examine the sensitivity towards the choice and aggregation of model outputs and observed data (summary statistics), and show results from using this method to fit the FORMIND model to field data from an Ecuadorian tropical forest. Finally, we discuss differences of this approach to Approximate Bayesian Computing (ABC), another commonly used method to generate simulation-based likelihood approximations. Our results demonstrate that simulation-based inference, which offers considerable conceptual advantages over more traditional methods for inverse parameter estimation, can successfully be applied to process-based models of high complexity. The methodology is particularly suited to heterogeneous and complex data structures and can easily be adjusted to other model types, including most stochastic population and individual-based models. Our study therefore provides a blueprint for a fairly general approach to parameter estimation of stochastic process-based models in ecology and evolution.

Inadequacy representation of flamelet-based RANS model for turbulent non-premixed flame

NASA Astrophysics Data System (ADS)

Lee, Myoungkyu; Oliver, Todd; Moser, Robert

2017-11-01

Stochastic representations for model inadequacy in RANS-based models of non-premixed jet flames are developed and explored. Flamelet-based RANS models are attractive for engineering applications relative to higher-fidelity methods because of their low computational costs. However, the various assumptions inherent in such models introduce errors that can significantly affect the accuracy of computed quantities of interest. In this work, we develop an approach to represent the model inadequacy of the flamelet-based RANS model. In particular, we pose a physics-based, stochastic PDE for the triple correlation of the mixture fraction. This additional uncertain state variable is then used to construct perturbations of the PDF for the instantaneous mixture fraction, which is used to obtain an uncertain perturbation of the flame temperature. A hydrogen-air non-premixed jet flame is used to demonstrate the representation of the inadequacy of the flamelet-based RANS model. This work was supported by DARPA-EQUiPS(Enabling Quantification of Uncertainty in Physical Systems) program.

A Model-Based Expert System for Space Power Distribution Diagnostics

NASA Technical Reports Server (NTRS)

Quinn, Todd M.; Schlegelmilch, Richard F.

1994-01-01

When engineers diagnose system failures, they often use models to confirm system operation. This concept has produced a class of advanced expert systems that perform model-based diagnosis. A model-based diagnostic expert system for the Space Station Freedom electrical power distribution test bed is currently being developed at the NASA Lewis Research Center. The objective of this expert system is to autonomously detect and isolate electrical fault conditions. Marple, a software package developed at TRW, provides a model-based environment utilizing constraint suspension. Originally, constraint suspension techniques were developed for digital systems. However, Marple provides the mechanisms for applying this approach to analog systems such as the test bed, as well. The expert system was developed using Marple and Lucid Common Lisp running on a Sun Sparc-2 workstation. The Marple modeling environment has proved to be a useful tool for investigating the various aspects of model-based diagnostics. This report describes work completed to date and lessons learned while employing model-based diagnostics using constraint suspension within an analog system.

A simple computational algorithm of model-based choice preference.

PubMed

Toyama, Asako; Katahira, Kentaro; Ohira, Hideki

2017-08-01

A broadly used computational framework posits that two learning systems operate in parallel during the learning of choice preferences-namely, the model-free and model-based reinforcement-learning systems. In this study, we examined another possibility, through which model-free learning is the basic system and model-based information is its modulator. Accordingly, we proposed several modified versions of a temporal-difference learning model to explain the choice-learning process. Using the two-stage decision task developed by Daw, Gershman, Seymour, Dayan, and Dolan (2011), we compared their original computational model, which assumes a parallel learning process, and our proposed models, which assume a sequential learning process. Choice data from 23 participants showed a better fit with the proposed models. More specifically, the proposed eligibility adjustment model, which assumes that the environmental model can weight the degree of the eligibility trace, can explain choices better under both model-free and model-based controls and has a simpler computational algorithm than the original model. In addition, the forgetting learning model and its variation, which assume changes in the values of unchosen actions, substantially improved the fits to the data. Overall, we show that a hybrid computational model best fits the data. The parameters used in this model succeed in capturing individual tendencies with respect to both model use in learning and exploration behavior. This computational model provides novel insights into learning with interacting model-free and model-based components.

Model-based Clustering of High-Dimensional Data in Astrophysics

NASA Astrophysics Data System (ADS)

Bouveyron, C.

2016-05-01

The nature of data in Astrophysics has changed, as in other scientific fields, in the past decades due to the increase of the measurement capabilities. As a consequence, data are nowadays frequently of high dimensionality and available in mass or stream. Model-based techniques for clustering are popular tools which are renowned for their probabilistic foundations and their flexibility. However, classical model-based techniques show a disappointing behavior in high-dimensional spaces which is mainly due to their dramatical over-parametrization. The recent developments in model-based classification overcome these drawbacks and allow to efficiently classify high-dimensional data, even in the "small n / large p" situation. This work presents a comprehensive review of these recent approaches, including regularization-based techniques, parsimonious modeling, subspace classification methods and classification methods based on variable selection. The use of these model-based methods is also illustrated on real-world classification problems in Astrophysics using R packages.

Model-based sensor-less wavefront aberration correction in optical coherence tomography.

PubMed

Verstraete, Hans R G W; Wahls, Sander; Kalkman, Jeroen; Verhaegen, Michel

2015-12-15

Several sensor-less wavefront aberration correction methods that correct nonlinear wavefront aberrations by maximizing the optical coherence tomography (OCT) signal are tested on an OCT setup. A conventional coordinate search method is compared to two model-based optimization methods. The first model-based method takes advantage of the well-known optimization algorithm (NEWUOA) and utilizes a quadratic model. The second model-based method (DONE) is new and utilizes a random multidimensional Fourier-basis expansion. The model-based algorithms achieve lower wavefront errors with up to ten times fewer measurements. Furthermore, the newly proposed DONE method outperforms the NEWUOA method significantly. The DONE algorithm is tested on OCT images and shows a significantly improved image quality.

Testing the Digital Thread in Support of Model-Based Manufacturing and Inspection

PubMed Central

Hedberg, Thomas; Lubell, Joshua; Fischer, Lyle; Maggiano, Larry; Feeney, Allison Barnard

2016-01-01

A number of manufacturing companies have reported anecdotal evidence describing the benefits of Model-Based Enterprise (MBE). Based on this evidence, major players in industry have embraced a vision to deploy MBE. In our view, the best chance of realizing this vision is the creation of a single “digital thread.” Under MBE, there exists a Model-Based Definition (MBD), created by the Engineering function, that downstream functions reuse to complete Model-Based Manufacturing and Model-Based Inspection activities. The ensemble of data that enables the combination of model-based definition, manufacturing, and inspection defines this digital thread. Such a digital thread would enable real-time design and analysis, collaborative process-flow development, automated artifact creation, and full-process traceability in a seamless real-time collaborative development among project participants. This paper documents the strengths and weaknesses in the current, industry strategies for implementing MBE. It also identifies gaps in the transition and/or exchange of data between various manufacturing processes. Lastly, this paper presents measured results from a study of model-based processes compared to drawing-based processes and provides evidence to support the anecdotal evidence and vision made by industry. PMID:27325911

Model-based choices involve prospective neural activity

PubMed Central

Doll, Bradley B.; Duncan, Katherine D.; Simon, Dylan A.; Shohamy, Daphna; Daw, Nathaniel D.

2015-01-01

Decisions may arise via “model-free” repetition of previously reinforced actions, or by “model-based” evaluation, which is widely thought to follow from prospective anticipation of action consequences using a learned map or model. While choices and neural correlates of decision variables sometimes reflect knowledge of their consequences, it remains unclear whether this actually arises from prospective evaluation. Using functional MRI and a sequential reward-learning task in which paths contained decodable object categories, we found that humans’ model-based choices were associated with neural signatures of future paths observed at decision time, suggesting a prospective mechanism for choice. Prospection also covaried with the degree of model-based influences on neural correlates of decision variables, and was inversely related to prediction error signals thought to underlie model-free learning. These results dissociate separate mechanisms underlying model-based and model-free evaluation and support the hypothesis that model-based influences on choices and neural decision variables result from prospection. PMID:25799041

A Correlation-Based Transition Model using Local Variables. Part 2; Test Cases and Industrial Applications

NASA Technical Reports Server (NTRS)

Langtry, R. B.; Menter, F. R.; Likki, S. R.; Suzen, Y. B.; Huang, P. G.; Volker, S.

2006-01-01

A new correlation-based transition model has been developed, which is built strictly on local variables. As a result, the transition model is compatible with modern computational fluid dynamics (CFD) methods using unstructured grids and massive parallel execution. The model is based on two transport equations, one for the intermittency and one for the transition onset criteria in terms of momentum thickness Reynolds number. The proposed transport equations do not attempt to model the physics of the transition process (unlike, e.g., turbulence models), but form a framework for the implementation of correlation-based models into general-purpose CFD methods.

Overcoming limitations of model-based diagnostic reasoning systems

NASA Technical Reports Server (NTRS)

Holtzblatt, Lester J.; Marcotte, Richard A.; Piazza, Richard L.

1989-01-01

The development of a model-based diagnostic system to overcome the limitations of model-based reasoning systems is discussed. It is noted that model-based reasoning techniques can be used to analyze the failure behavior and diagnosability of system and circuit designs as part of the system process itself. One goal of current research is the development of a diagnostic algorithm which can reason efficiently about large numbers of diagnostic suspects and can handle both combinational and sequential circuits. A second goal is to address the model-creation problem by developing an approach for using design models to construct the GMODS model in an automated fashion.

Model-assisted template extraction SRAF application to contact holes patterns in high-end flash memory device fabrication

NASA Astrophysics Data System (ADS)

Seoud, Ahmed; Kim, Juhwan; Ma, Yuansheng; Jayaram, Srividya; Hong, Le; Chae, Gyu-Yeol; Lee, Jeong-Woo; Park, Dae-Jin; Yune, Hyoung-Soon; Oh, Se-Young; Park, Chan-Ha

2018-03-01

Sub-resolution assist feature (SRAF) insertion techniques have been effectively used for a long time now to increase process latitude in the lithography patterning process. Rule-based SRAF and model-based SRAF are complementary solutions, and each has its own benefits, depending on the objectives of applications and the criticality of the impact on manufacturing yield, efficiency, and productivity. Rule-based SRAF provides superior geometric output consistency and faster runtime performance, but the associated recipe development time can be of concern. Model-based SRAF provides better coverage for more complicated pattern structures in terms of shapes and sizes, with considerably less time required for recipe development, although consistency and performance may be impacted. In this paper, we introduce a new model-assisted template extraction (MATE) SRAF solution, which employs decision tree learning in a model-based solution to provide the benefits of both rule-based and model-based SRAF insertion approaches. The MATE solution is designed to automate the creation of rules/templates for SRAF insertion, and is based on the SRAF placement predicted by model-based solutions. The MATE SRAF recipe provides optimum lithographic quality in relation to various manufacturing aspects in a very short time, compared to traditional methods of rule optimization. Experiments were done using memory device pattern layouts to compare the MATE solution to existing model-based SRAF and pixelated SRAF approaches, based on lithographic process window quality, runtime performance, and geometric output consistency.

Automated extraction of knowledge for model-based diagnostics

NASA Technical Reports Server (NTRS)

Gonzalez, Avelino J.; Myler, Harley R.; Towhidnejad, Massood; Mckenzie, Frederic D.; Kladke, Robin R.

1990-01-01

The concept of accessing computer aided design (CAD) design databases and extracting a process model automatically is investigated as a possible source for the generation of knowledge bases for model-based reasoning systems. The resulting system, referred to as automated knowledge generation (AKG), uses an object-oriented programming structure and constraint techniques as well as internal database of component descriptions to generate a frame-based structure that describes the model. The procedure has been designed to be general enough to be easily coupled to CAD systems that feature a database capable of providing label and connectivity data from the drawn system. The AKG system is capable of defining knowledge bases in formats required by various model-based reasoning tools.

A Model-Driven Architecture Approach for Modeling, Specifying and Deploying Policies in Autonomous and Autonomic Systems

NASA Technical Reports Server (NTRS)

Pena, Joaquin; Hinchey, Michael G.; Sterritt, Roy; Ruiz-Cortes, Antonio; Resinas, Manuel

2006-01-01

Autonomic Computing (AC), self-management based on high level guidance from humans, is increasingly gaining momentum as the way forward in designing reliable systems that hide complexity and conquer IT management costs. Effectively, AC may be viewed as Policy-Based Self-Management. The Model Driven Architecture (MDA) approach focuses on building models that can be transformed into code in an automatic manner. In this paper, we look at ways to implement Policy-Based Self-Management by means of models that can be converted to code using transformations that follow the MDA philosophy. We propose a set of UML-based models to specify autonomic and autonomous features along with the necessary procedures, based on modification and composition of models, to deploy a policy as an executing system.

A two-stage stochastic rule-based model to determine pre-assembly buffer content

NASA Astrophysics Data System (ADS)

Gunay, Elif Elcin; Kula, Ufuk

2018-01-01

This study considers instant decision-making needs of the automobile manufactures for resequencing vehicles before final assembly (FA). We propose a rule-based two-stage stochastic model to determine the number of spare vehicles that should be kept in the pre-assembly buffer to restore the altered sequence due to paint defects and upstream department constraints. First stage of the model decides the spare vehicle quantities, where the second stage model recovers the scrambled sequence respect to pre-defined rules. The problem is solved by sample average approximation (SAA) algorithm. We conduct a numerical study to compare the solutions of heuristic model with optimal ones and provide following insights: (i) as the mismatch between paint entrance and scheduled sequence decreases, the rule-based heuristic model recovers the scrambled sequence as good as the optimal resequencing model, (ii) the rule-based model is more sensitive to the mismatch between the paint entrance and scheduled sequences for recovering the scrambled sequence, (iii) as the defect rate increases, the difference in recovery effectiveness between rule-based heuristic and optimal solutions increases, (iv) as buffer capacity increases, the recovery effectiveness of the optimization model outperforms heuristic model, (v) as expected the rule-based model holds more inventory than the optimization model.

Comparing model-based and model-free analysis methods for QUASAR arterial spin labeling perfusion quantification.

PubMed

Chappell, Michael A; Woolrich, Mark W; Petersen, Esben T; Golay, Xavier; Payne, Stephen J

2013-05-01

Amongst the various implementations of arterial spin labeling MRI methods for quantifying cerebral perfusion, the QUASAR method is unique. By using a combination of labeling with and without flow suppression gradients, the QUASAR method offers the separation of macrovascular and tissue signals. This permits local arterial input functions to be defined and "model-free" analysis, using numerical deconvolution, to be used. However, it remains unclear whether arterial spin labeling data are best treated using model-free or model-based analysis. This work provides a critical comparison of these two approaches for QUASAR arterial spin labeling in the healthy brain. An existing two-component (arterial and tissue) model was extended to the mixed flow suppression scheme of QUASAR to provide an optimal model-based analysis. The model-based analysis was extended to incorporate dispersion of the labeled bolus, generally regarded as the major source of discrepancy between the two analysis approaches. Model-free and model-based analyses were compared for perfusion quantification including absolute measurements, uncertainty estimation, and spatial variation in cerebral blood flow estimates. Major sources of discrepancies between model-free and model-based analysis were attributed to the effects of dispersion and the degree to which the two methods can separate macrovascular and tissue signal. Copyright © 2012 Wiley Periodicals, Inc.

DFM flow by using combination between design based metrology system and model based verification at sub-50nm memory device

NASA Astrophysics Data System (ADS)

Kim, Cheol-kyun; Kim, Jungchan; Choi, Jaeseung; Yang, Hyunjo; Yim, Donggyu; Kim, Jinwoong

2007-03-01

As the minimum transistor length is getting smaller, the variation and uniformity of transistor length seriously effect device performance. So, the importance of optical proximity effects correction (OPC) and resolution enhancement technology (RET) cannot be overemphasized. However, OPC process is regarded by some as a necessary evil in device performance. In fact, every group which includes process and design, are interested in whole chip CD variation trend and CD uniformity, which represent real wafer. Recently, design based metrology systems are capable of detecting difference between data base to wafer SEM image. Design based metrology systems are able to extract information of whole chip CD variation. According to the results, OPC abnormality was identified and design feedback items are also disclosed. The other approaches are accomplished on EDA companies, like model based OPC verifications. Model based verification will be done for full chip area by using well-calibrated model. The object of model based verification is the prediction of potential weak point on wafer and fast feed back to OPC and design before reticle fabrication. In order to achieve robust design and sufficient device margin, appropriate combination between design based metrology system and model based verification tools is very important. Therefore, we evaluated design based metrology system and matched model based verification system for optimum combination between two systems. In our study, huge amount of data from wafer results are classified and analyzed by statistical method and classified by OPC feedback and design feedback items. Additionally, novel DFM flow would be proposed by using combination of design based metrology and model based verification tools.

Gaps Analysis of Integrating Product Design, Manufacturing, and Quality Data in The Supply Chain Using Model-Based Definition.

PubMed

Trainer, Asa; Hedberg, Thomas; Feeney, Allison Barnard; Fischer, Kevin; Rosche, Phil

2016-01-01

Advances in information technology triggered a digital revolution that holds promise of reduced costs, improved productivity, and higher quality. To ride this wave of innovation, manufacturing enterprises are changing how product definitions are communicated - from paper to models. To achieve industry's vision of the Model-Based Enterprise (MBE), the MBE strategy must include model-based data interoperability from design to manufacturing and quality in the supply chain. The Model-Based Definition (MBD) is created by the original equipment manufacturer (OEM) using Computer-Aided Design (CAD) tools. This information is then shared with the supplier so that they can manufacture and inspect the physical parts. Today, suppliers predominantly use Computer-Aided Manufacturing (CAM) and Coordinate Measuring Machine (CMM) models for these tasks. Traditionally, the OEM has provided design data to the supplier in the form of two-dimensional (2D) drawings, but may also include a three-dimensional (3D)-shape-geometry model, often in a standards-based format such as ISO 10303-203:2011 (STEP AP203). The supplier then creates the respective CAM and CMM models and machine programs to produce and inspect the parts. In the MBE vision for model-based data exchange, the CAD model must include product-and-manufacturing information (PMI) in addition to the shape geometry. Today's CAD tools can generate models with embedded PMI. And, with the emergence of STEP AP242, a standards-based model with embedded PMI can now be shared downstream. The on-going research detailed in this paper seeks to investigate three concepts. First, that the ability to utilize a STEP AP242 model with embedded PMI for CAD-to-CAM and CAD-to-CMM data exchange is possible and valuable to the overall goal of a more efficient process. Second, the research identifies gaps in tools, standards, and processes that inhibit industry's ability to cost-effectively achieve model-based-data interoperability in the pursuit of the MBE vision. Finally, it also seeks to explore the interaction between CAD and CMM processes and determine if the concept of feedback from CAM and CMM back to CAD is feasible. The main goal of our study is to test the hypothesis that model-based-data interoperability from CAD-to-CAM and CAD-to-CMM is feasible through standards-based integration. This paper presents several barriers to model-based-data interoperability. Overall, the project team demonstrated the exchange of product definition data between CAD, CAM, and CMM systems using standards-based methods. While gaps in standards coverage were identified, the gaps should not stop industry's progress toward MBE. The results of our study provide evidence in support of an open-standards method to model-based-data interoperability, which would provide maximum value and impact to industry.

Simulating cancer growth with multiscale agent-based modeling.

PubMed

Wang, Zhihui; Butner, Joseph D; Kerketta, Romica; Cristini, Vittorio; Deisboeck, Thomas S

2015-02-01

There have been many techniques developed in recent years to in silico model a variety of cancer behaviors. Agent-based modeling is a specific discrete-based hybrid modeling approach that allows simulating the role of diversity in cell populations as well as within each individual cell; it has therefore become a powerful modeling method widely used by computational cancer researchers. Many aspects of tumor morphology including phenotype-changing mutations, the adaptation to microenvironment, the process of angiogenesis, the influence of extracellular matrix, reactions to chemotherapy or surgical intervention, the effects of oxygen and nutrient availability, and metastasis and invasion of healthy tissues have been incorporated and investigated in agent-based models. In this review, we introduce some of the most recent agent-based models that have provided insight into the understanding of cancer growth and invasion, spanning multiple biological scales in time and space, and we further describe several experimentally testable hypotheses generated by those models. We also discuss some of the current challenges of multiscale agent-based cancer models. Copyright © 2014 Elsevier Ltd. All rights reserved.

Computational Modeling of Human Metabolism and Its Application to Systems Biomedicine.

PubMed

Aurich, Maike K; Thiele, Ines

2016-01-01

Modern high-throughput techniques offer immense opportunities to investigate whole-systems behavior, such as those underlying human diseases. However, the complexity of the data presents challenges in interpretation, and new avenues are needed to address the complexity of both diseases and data. Constraint-based modeling is one formalism applied in systems biology. It relies on a genome-scale reconstruction that captures extensive biochemical knowledge regarding an organism. The human genome-scale metabolic reconstruction is increasingly used to understand normal cellular and disease states because metabolism is an important factor in many human diseases. The application of human genome-scale reconstruction ranges from mere querying of the model as a knowledge base to studies that take advantage of the model's topology and, most notably, to functional predictions based on cell- and condition-specific metabolic models built based on omics data.An increasing number and diversity of biomedical questions are being addressed using constraint-based modeling and metabolic models. One of the most successful biomedical applications to date is cancer metabolism, but constraint-based modeling also holds great potential for inborn errors of metabolism or obesity. In addition, it offers great prospects for individualized approaches to diagnostics and the design of disease prevention and intervention strategies. Metabolic models support this endeavor by providing easy access to complex high-throughput datasets. Personalized metabolic models have been introduced. Finally, constraint-based modeling can be used to model whole-body metabolism, which will enable the elucidation of metabolic interactions between organs and disturbances of these interactions as either causes or consequence of metabolic diseases. This chapter introduces constraint-based modeling and describes some of its contributions to systems biomedicine.

Evaluation of six NEHRP B/C crustal amplification models proposed for use in western North America

USGS Publications Warehouse

Boore, David; Campbell, Kenneth W.

2016-01-01

We evaluate six crustal amplification models based on National Earthquake Hazards Reduction Program (NEHRP) B/C crustal profiles proposed for use in western North America (WNA) and often used in other active crustal regions where crustal properties are unknown. One of the models is based on an interpolation of generic rock velocity profiles previously proposed for WNA and central and eastern North America (CENA), in conjunction with material densities based on an updated velocity–density relationship. A second model is based on the velocity profile used to develop amplification factors for the Next Generation Attenuation (NGA)‐West2 project. A third model is based on a near‐surface velocity profile developed from the NGA‐West2 site database. A fourth model is based on velocity and density profiles originally proposed for use in CENA but recently used to represent crustal properties in California. We propose two alternatives to this latter model that more closely represent WNA crustal properties. We adopt a value of site attenuation (κ0) for each model that is either recommended by the author of the model or proposed by us. Stochastic simulation is used to evaluate the Fourier amplification factors and their impact on response spectra associated with each model. Based on this evaluation, we conclude that among the available models evaluated in this study the NEHRP B/C amplification model of Boore (2016) best represents median crustal amplification in WNA, although the amplification models based on the crustal profiles of Kamai et al. (2013, 2016, unpublished manuscript, see Data and Resources) and Yenier and Atkinson (2015), the latter adjusted to WNA crustal properties, can be used to represent epistemic uncertainty.

Temperature based daily incoming solar radiation modeling based on gene expression programming, neuro-fuzzy and neural network computing techniques.

NASA Astrophysics Data System (ADS)

Landeras, G.; López, J. J.; Kisi, O.; Shiri, J.

2012-04-01

The correct observation/estimation of surface incoming solar radiation (RS) is very important for many agricultural, meteorological and hydrological related applications. While most weather stations are provided with sensors for air temperature detection, the presence of sensors necessary for the detection of solar radiation is not so habitual and the data quality provided by them is sometimes poor. In these cases it is necessary to estimate this variable. Temperature based modeling procedures are reported in this study for estimating daily incoming solar radiation by using Gene Expression Programming (GEP) for the first time, and other artificial intelligence models such as Artificial Neural Networks (ANNs), and Adaptive Neuro-Fuzzy Inference System (ANFIS). Traditional temperature based solar radiation equations were also included in this study and compared with artificial intelligence based approaches. Root mean square error (RMSE), mean absolute error (MAE) RMSE-based skill score (SSRMSE), MAE-based skill score (SSMAE) and r2 criterion of Nash and Sutcliffe criteria were used to assess the models' performances. An ANN (a four-input multilayer perceptron with ten neurons in the hidden layer) presented the best performance among the studied models (2.93 MJ m-2 d-1 of RMSE). A four-input ANFIS model revealed as an interesting alternative to ANNs (3.14 MJ m-2 d-1 of RMSE). Very limited number of studies has been done on estimation of solar radiation based on ANFIS, and the present one demonstrated the ability of ANFIS to model solar radiation based on temperatures and extraterrestrial radiation. By the way this study demonstrated, for the first time, the ability of GEP models to model solar radiation based on daily atmospheric variables. Despite the accuracy of GEP models was slightly lower than the ANFIS and ANN models the genetic programming models (i.e., GEP) are superior to other artificial intelligence models in giving a simple explicit equation for the phenomenon which shows the relationship between the input and output parameters. This study provided new alternatives for solar radiation estimation based on temperatures.

Consequences of Base Time for Redundant Signals Experiments

PubMed Central

Townsend, James T.; Honey, Christopher

2007-01-01

We report analytical and computational investigations into the effects of base time on the diagnosticity of two popular theoretical tools in the redundant signals literature: (1) the race model inequality and (2) the capacity coefficient. We show analytically and without distributional assumptions that the presence of base time decreases the sensitivity of both of these measures to model violations. We further use simulations to investigate the statistical power model selection tools based on the race model inequality, both with and without base time. Base time decreases statistical power, and biases the race model test toward conservatism. The magnitude of this biasing effect increases as we increase the proportion of total reaction time variance contributed by base time. We marshal empirical evidence to suggest that the proportion of reaction time variance contributed by base time is relatively small, and that the effects of base time on the diagnosticity of our model-selection tools are therefore likely to be minor. However, uncertainty remains concerning the magnitude and even the definition of base time. Experimentalists should continue to be alert to situations in which base time may contribute a large proportion of the total reaction time variance. PMID:18670591

Understanding photoluminescence of metal nanostructures based on an oscillator model.

PubMed

Cheng, Yuqing; Zhang, Weidong; Zhao, Jingyi; Wen, Te; Hu, Aiqin; Gong, Qihuang; Lu, Guowei

2018-08-03

Scattering and absorption properties of metal nanostructures have been well understood based on the classic oscillator theory. Here, we demonstrate that photoluminescence of metal nanostructures can also be explained based on a classic model. The model shows that inelastic radiation of an oscillator resembles its resonance band after external excitation, and is related to the photoluminescence from metallic nanostructures. The understanding based on the classic oscillator model is in agreement with that predicted by a quantum electromagnetic cavity model. Moreover, by correlating a two-temperature model and the electron distributions, we demonstrate that both one-photon and two-photon luminescence of the metal nanostructures undergo the same mechanism. Furthermore, the model explains most of the emission characteristics of the metallic nanostructures, such as quantum yield, spectral shape, excitation polarization and power dependence. The model based on an oscillator provides an intuitive description of the photoluminescence process and may enable rapid optimization and exploration of the plasmonic properties.

Improving the FLORIS wind plant model for compatibility with gradient-based optimization

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

Thomas, Jared J.; Gebraad, Pieter MO; Ning, Andrew

The FLORIS (FLOw Redirection and Induction in Steady-state) model, a parametric wind turbine wake model that predicts steady-state wake characteristics based on wind turbine position and yaw angle, was developed for optimization of control settings and turbine locations. This article provides details on changes made to the FLORIS model to make the model more suitable for gradient-based optimization. Changes to the FLORIS model were made to remove discontinuities and add curvature to regions of non-physical zero gradient. Exact gradients for the FLORIS model were obtained using algorithmic differentiation. A set of three case studies demonstrate that using exact gradients withmore » gradient-based optimization reduces the number of function calls by several orders of magnitude. The case studies also show that adding curvature improves convergence behavior, allowing gradient-based optimization algorithms used with the FLORIS model to more reliably find better solutions to wind farm optimization problems.« less

Discovering the Power of Individual-Based Modelling in Teaching and Learning: The Study of a Predator-Prey System

ERIC Educational Resources Information Center

Ginovart, Marta

2014-01-01

The general aim is to promote the use of individual-based models (biological agent-based models) in teaching and learning contexts in life sciences and to make their progressive incorporation into academic curricula easier, complementing other existing modelling strategies more frequently used in the classroom. Modelling activities for the study…

When Does Model-Based Control Pay Off?

PubMed Central

2016-01-01

Many accounts of decision making and reinforcement learning posit the existence of two distinct systems that control choice: a fast, automatic system and a slow, deliberative system. Recent research formalizes this distinction by mapping these systems to “model-free” and “model-based” strategies in reinforcement learning. Model-free strategies are computationally cheap, but sometimes inaccurate, because action values can be accessed by inspecting a look-up table constructed through trial-and-error. In contrast, model-based strategies compute action values through planning in a causal model of the environment, which is more accurate but also more cognitively demanding. It is assumed that this trade-off between accuracy and computational demand plays an important role in the arbitration between the two strategies, but we show that the hallmark task for dissociating model-free and model-based strategies, as well as several related variants, do not embody such a trade-off. We describe five factors that reduce the effectiveness of the model-based strategy on these tasks by reducing its accuracy in estimating reward outcomes and decreasing the importance of its choices. Based on these observations, we describe a version of the task that formally and empirically obtains an accuracy-demand trade-off between model-free and model-based strategies. Moreover, we show that human participants spontaneously increase their reliance on model-based control on this task, compared to the original paradigm. Our novel task and our computational analyses may prove important in subsequent empirical investigations of how humans balance accuracy and demand. PMID:27564094

Learning-Based Just-Noticeable-Quantization- Distortion Modeling for Perceptual Video Coding.

PubMed

Ki, Sehwan; Bae, Sung-Ho; Kim, Munchurl; Ko, Hyunsuk

2018-07-01

Conventional predictive video coding-based approaches are reaching the limit of their potential coding efficiency improvements, because of severely increasing computation complexity. As an alternative approach, perceptual video coding (PVC) has attempted to achieve high coding efficiency by eliminating perceptual redundancy, using just-noticeable-distortion (JND) directed PVC. The previous JNDs were modeled by adding white Gaussian noise or specific signal patterns into the original images, which were not appropriate in finding JND thresholds due to distortion with energy reduction. In this paper, we present a novel discrete cosine transform-based energy-reduced JND model, called ERJND, that is more suitable for JND-based PVC schemes. Then, the proposed ERJND model is extended to two learning-based just-noticeable-quantization-distortion (JNQD) models as preprocessing that can be applied for perceptual video coding. The two JNQD models can automatically adjust JND levels based on given quantization step sizes. One of the two JNQD models, called LR-JNQD, is based on linear regression and determines the model parameter for JNQD based on extracted handcraft features. The other JNQD model is based on a convolution neural network (CNN), called CNN-JNQD. To our best knowledge, our paper is the first approach to automatically adjust JND levels according to quantization step sizes for preprocessing the input to video encoders. In experiments, both the LR-JNQD and CNN-JNQD models were applied to high efficiency video coding (HEVC) and yielded maximum (average) bitrate reductions of 38.51% (10.38%) and 67.88% (24.91%), respectively, with little subjective video quality degradation, compared with the input without preprocessing applied.

ASSESSMENT OF TWO PHYSICALLY BASED WATERSHED MODELS BASED ON THEIR PERFORMANCES OF SIMULATING SEDIMENT MOVEMENT OVER SMALL WATERSHEDS

EPA Science Inventory

Abstract: Two physically based and deterministic models, CASC2-D and KINEROS are evaluated and compared for their performances on modeling sediment movement on a small agricultural watershed over several events. Each model has different conceptualization of a watershed. CASC...

Some Statistics for Assessing Person-Fit Based on Continuous-Response Models

ERIC Educational Resources Information Center

Ferrando, Pere Joan

2010-01-01

This article proposes several statistics for assessing individual fit based on two unidimensional models for continuous responses: linear factor analysis and Samejima's continuous response model. Both models are approached using a common framework based on underlying response variables and are formulated at the individual level as fixed regression…

ASSESSMENT OF TWO PHYSICALLY-BASED WATERSHED MODELS BASED ON THEIR PERFORMANCES OF SIMULATING WATER AND SEDIMENT MOVEMENT

EPA Science Inventory

Two physically based watershed models, GSSHA and KINEROS-2 are evaluated and compared for their performances on modeling flow and sediment movement. Each model has a different watershed conceptualization. GSSHA divides the watershed into cells, and flow and sediments are routed t...

Using Video-Based Modeling to Promote Acquisition of Fundamental Motor Skills

ERIC Educational Resources Information Center

Obrusnikova, Iva; Rattigan, Peter J.

2016-01-01

Video-based modeling is becoming increasingly popular for teaching fundamental motor skills to children in physical education. Two frequently used video-based instructional strategies that incorporate modeling are video prompting (VP) and video modeling (VM). Both strategies have been used across multiple disciplines and populations to teach a…

Thermodynamics-based models of transcriptional regulation with gene sequence.

PubMed

Wang, Shuqiang; Shen, Yanyan; Hu, Jinxing

2015-12-01

Quantitative models of gene regulatory activity have the potential to improve our mechanistic understanding of transcriptional regulation. However, the few models available today have been based on simplistic assumptions about the sequences being modeled or heuristic approximations of the underlying regulatory mechanisms. In this work, we have developed a thermodynamics-based model to predict gene expression driven by any DNA sequence. The proposed model relies on a continuous time, differential equation description of transcriptional dynamics. The sequence features of the promoter are exploited to derive the binding affinity which is derived based on statistical molecular thermodynamics. Experimental results show that the proposed model can effectively identify the activity levels of transcription factors and the regulatory parameters. Comparing with the previous models, the proposed model can reveal more biological sense.

Quality prediction modeling for sintered ores based on mechanism models of sintering and extreme learning machine based error compensation

NASA Astrophysics Data System (ADS)

Tiebin, Wu; Yunlian, Liu; Xinjun, Li; Yi, Yu; Bin, Zhang

2018-06-01

Aiming at the difficulty in quality prediction of sintered ores, a hybrid prediction model is established based on mechanism models of sintering and time-weighted error compensation on the basis of the extreme learning machine (ELM). At first, mechanism models of drum index, total iron, and alkalinity are constructed according to the chemical reaction mechanism and conservation of matter in the sintering process. As the process is simplified in the mechanism models, these models are not able to describe high nonlinearity. Therefore, errors are inevitable. For this reason, the time-weighted ELM based error compensation model is established. Simulation results verify that the hybrid model has a high accuracy and can meet the requirement for industrial applications.

Stimulating Scientific Reasoning with Drawing-Based Modeling

NASA Astrophysics Data System (ADS)

Heijnes, Dewi; van Joolingen, Wouter; Leenaars, Frank

2018-02-01

We investigate the way students' reasoning about evolution can be supported by drawing-based modeling. We modified the drawing-based modeling tool SimSketch to allow for modeling evolutionary processes. In three iterations of development and testing, students in lower secondary education worked on creating an evolutionary model. After each iteration, the user interface and instructions were adjusted based on students' remarks and the teacher's observations. Students' conversations were analyzed on reasoning complexity as a measurement of efficacy of the modeling tool and the instructions. These findings were also used to compose a set of recommendations for teachers and curriculum designers for using and constructing models in the classroom. Our findings suggest that to stimulate scientific reasoning in students working with a drawing-based modeling, tool instruction about the tool and the domain should be integrated. In creating models, a sufficient level of scaffolding is necessary. Without appropriate scaffolds, students are not able to create the model. With scaffolding that is too high, students may show reasoning that incorrectly assigns external causes to behavior in the model.

A place for agent-based models. Comment on "Statistical physics of crime: A review" by M.R. D'Orsogna and M. Perc

NASA Astrophysics Data System (ADS)

Barbaro, Alethea

2015-03-01

Agent-based models have been widely applied in theoretical ecology to explain migrations and other collective animal movements [2,5,8]. As D'Orsogna and Perc have expertly highlighted in [6], the recent emergence of crime modeling has opened another interesting avenue for mathematical investigation. The area of crime modeling is particularly suited to agent-based models, because these models offer a great deal of flexibility within the model and also ease of communication among criminologist, law enforcement and modelers.

Urban stormwater inundation simulation based on SWMM and diffusive overland-flow model.

PubMed

Chen, Wenjie; Huang, Guoru; Zhang, Han

2017-12-01

With rapid urbanization, inundation-induced property losses have become more and more severe. Urban inundation modeling is an effective way to reduce these losses. This paper introduces a simplified urban stormwater inundation simulation model based on the United States Environmental Protection Agency Storm Water Management Model (SWMM) and a geographic information system (GIS)-based diffusive overland-flow model. SWMM is applied for computation of flows in storm sewer systems and flooding flows at junctions, while the GIS-based diffusive overland-flow model simulates surface runoff and inundation. One observed rainfall scenario on Haidian Island, Hainan Province, China was chosen to calibrate the model and the other two were used for validation. Comparisons of the model results with field-surveyed data and InfoWorks ICM (Integrated Catchment Modeling) modeled results indicated the inundation model in this paper can provide inundation extents and reasonable inundation depths even in a large study area.

Directivity models produced for the Next Generation Attenuation West 2 (NGA-West 2) project

USGS Publications Warehouse

Spudich, Paul A.; Watson-Lamprey, Jennie; Somerville, Paul G.; Bayless, Jeff; Shahi, Shrey; Baker, Jack W.; Rowshandel, Badie; Chiou, Brian

2012-01-01

Five new directivity models are being developed for the NGA-West 2 project. All are based on the NGA-West 2 data base, which is considerably expanded from the original NGA-West data base, containing about 3,000 more records from earthquakes having finite-fault rupture models. All of the new directivity models have parameters based on fault dimension in km, not normalized fault dimension. This feature removes a peculiarity of previous models which made them inappropriate for modeling large magnitude events on long strike-slip faults. Two models are explicitly, and one is implicitly, 'narrowband' models, in which the effect of directivity does not monotonically increase with spectral period but instead peaks at a specific period that is a function of earthquake magnitude. These narrowband models' functional forms are capable of simulating directivity over a wider range of earthquake magnitude than previous models. The functional forms of the five models are presented.

Model predictive control based on reduced order models applied to belt conveyor system.

PubMed

Chen, Wei; Li, Xin

2016-11-01

In the paper, a model predictive controller based on reduced order model is proposed to control belt conveyor system, which is an electro-mechanics complex system with long visco-elastic body. Firstly, in order to design low-degree controller, the balanced truncation method is used for belt conveyor model reduction. Secondly, MPC algorithm based on reduced order model for belt conveyor system is presented. Because of the error bound between the full-order model and reduced order model, two Kalman state estimators are applied in the control scheme to achieve better system performance. Finally, the simulation experiments are shown that balanced truncation method can significantly reduce the model order with high-accuracy and model predictive control based on reduced-model performs well in controlling the belt conveyor system. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

A Coupled Simulation Architecture for Agent-Based/Geohydrological Modelling

NASA Astrophysics Data System (ADS)

Jaxa-Rozen, M.

2016-12-01

The quantitative modelling of social-ecological systems can provide useful insights into the interplay between social and environmental processes, and their impact on emergent system dynamics. However, such models should acknowledge the complexity and uncertainty of both of the underlying subsystems. For instance, the agent-based models which are increasingly popular for groundwater management studies can be made more useful by directly accounting for the hydrological processes which drive environmental outcomes. Conversely, conventional environmental models can benefit from an agent-based depiction of the feedbacks and heuristics which influence the decisions of groundwater users. From this perspective, this work describes a Python-based software architecture which couples the popular NetLogo agent-based platform with the MODFLOW/SEAWAT geohydrological modelling environment. This approach enables users to implement agent-based models in NetLogo's user-friendly platform, while benefiting from the full capabilities of MODFLOW/SEAWAT packages or reusing existing geohydrological models. The software architecture is based on the pyNetLogo connector, which provides an interface between the NetLogo agent-based modelling software and the Python programming language. This functionality is then extended and combined with Python's object-oriented features, to design a simulation architecture which couples NetLogo with MODFLOW/SEAWAT through the FloPy library (Bakker et al., 2016). The Python programming language also provides access to a range of external packages which can be used for testing and analysing the coupled models, which is illustrated for an application of Aquifer Thermal Energy Storage (ATES).

Statistical shape model-based reconstruction of a scaled, patient-specific surface model of the pelvis from a single standard AP x-ray radiograph

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

Zheng Guoyan

2010-04-15

Purpose: The aim of this article is to investigate the feasibility of using a statistical shape model (SSM)-based reconstruction technique to derive a scaled, patient-specific surface model of the pelvis from a single standard anteroposterior (AP) x-ray radiograph and the feasibility of estimating the scale of the reconstructed surface model by performing a surface-based 3D/3D matching. Methods: Data sets of 14 pelvises (one plastic bone, 12 cadavers, and one patient) were used to validate the single-image based reconstruction technique. This reconstruction technique is based on a hybrid 2D/3D deformable registration process combining a landmark-to-ray registration with a SSM-based 2D/3D reconstruction.more » The landmark-to-ray registration was used to find an initial scale and an initial rigid transformation between the x-ray image and the SSM. The estimated scale and rigid transformation were used to initialize the SSM-based 2D/3D reconstruction. The optimal reconstruction was then achieved in three stages by iteratively matching the projections of the apparent contours extracted from a 3D model derived from the SSM to the image contours extracted from the x-ray radiograph: Iterative affine registration, statistical instantiation, and iterative regularized shape deformation. The image contours are first detected by using a semiautomatic segmentation tool based on the Livewire algorithm and then approximated by a set of sparse dominant points that are adaptively sampled from the detected contours. The unknown scales of the reconstructed models were estimated by performing a surface-based 3D/3D matching between the reconstructed models and the associated ground truth models that were derived from a CT-based reconstruction method. Such a matching also allowed for computing the errors between the reconstructed models and the associated ground truth models. Results: The technique could reconstruct the surface models of all 14 pelvises directly from the landmark-based initialization. Depending on the surface-based matching techniques, the reconstruction errors were slightly different. When a surface-based iterative affine registration was used, an average reconstruction error of 1.6 mm was observed. This error was increased to 1.9 mm, when a surface-based iterative scaled rigid registration was used. Conclusions: It is feasible to reconstruct a scaled, patient-specific surface model of the pelvis from single standard AP x-ray radiograph using the present approach. The unknown scale of the reconstructed model can be estimated by performing a surface-based 3D/3D matching.« less

Provision of hearing aids to children in Bangladesh: costs and cost-effectiveness of a community-based and a centre-based approach.

PubMed

Ekman, Björn; Borg, Johan

2017-08-01

The aim of this study is to provide evidence on the costs and health effects of two alternative hearing aid delivery models, a community-based and a centre-based approach. The study is set in Bangladesh and the study population is children between 12 and 18 years old. Data on resource use by participants and their caregivers were collected by a household survey. Follow-up data were collected after two months. Data on the costs to providers of the two approaches were collected by means of key informant interviews. The total cost per participant in the community-based model was BDT 6,333 (USD 79) compared with BDT 13,718 (USD 172) for the centre-based model. Both delivery models are found to be cost-effective with an estimated cost per DALY averted of BDT 17,611 (USD 220) for the community-based model and BDT 36,775 (USD 460) for the centre-based model. Using a community-based approach to deliver hearing aids to children in a resource constrained environment is a cost-effective alternative to the traditional centre-based approach. Further evidence is needed to draw conclusions for scale-up of approaches; rigorous analysis is possible using well-prepared data collection tools and working closely with sector professionals. Implications for Rehabilitation Delivery models vary by resources needed for their implementation. Community-based deliver models of hearing aids to children in low-income countries are a cost-effective alternative. The assessment of costs and effects of hearing aids delivery models in low-income countries is possible through planned collaboration between researchers and sector professionals.

RECURSIVE PROTEIN MODELING: A DIVIDE AND CONQUER STRATEGY FOR PROTEIN STRUCTURE PREDICTION AND ITS CASE STUDY IN CASP9

PubMed Central

CHENG, JIANLIN; EICKHOLT, JESSE; WANG, ZHENG; DENG, XIN

2013-01-01

After decades of research, protein structure prediction remains a very challenging problem. In order to address the different levels of complexity of structural modeling, two types of modeling techniques — template-based modeling and template-free modeling — have been developed. Template-based modeling can often generate a moderate- to high-resolution model when a similar, homologous template structure is found for a query protein but fails if no template or only incorrect templates are found. Template-free modeling, such as fragment-based assembly, may generate models of moderate resolution for small proteins of low topological complexity. Seldom have the two techniques been integrated together to improve protein modeling. Here we develop a recursive protein modeling approach to selectively and collaboratively apply template-based and template-free modeling methods to model template-covered (i.e. certain) and template-free (i.e. uncertain) regions of a protein. A preliminary implementation of the approach was tested on a number of hard modeling cases during the 9th Critical Assessment of Techniques for Protein Structure Prediction (CASP9) and successfully improved the quality of modeling in most of these cases. Recursive modeling can signicantly reduce the complexity of protein structure modeling and integrate template-based and template-free modeling to improve the quality and efficiency of protein structure prediction. PMID:22809379

Modeling potential Emerald Ash Borer spread through GIS/cell-based/gravity models with data bolstered by web-based inputs

Treesearch

Louis R. Iverson; Anantha M. Prasad; Davis Sydnor; Jonathan Bossenbroek; Mark W. Schwartz; Mark W. Schwartz

2006-01-01

We model the susceptibility and potential spread of the organism across the eastern United States and especially through Michigan and Ohio using Forest Inventory and Analysis (FIA) data. We are also developing a cell-based model for the potential spread of the organism. We have developed a web-based tool for public agencies and private individuals to enter the...

Background-Error Correlation Model Based on the Implicit Solution of a Diffusion Equation

DTIC Science & Technology

2010-01-01

1 Background- Error Correlation Model Based on the Implicit Solution of a Diffusion Equation Matthew J. Carrier* and Hans Ngodock...4. TITLE AND SUBTITLE Background- Error Correlation Model Based on the Implicit Solution of a Diffusion Equation 5a. CONTRACT NUMBER 5b. GRANT...2001), which sought to model error correlations based on the explicit solution of a generalized diffusion equation. The implicit solution is

Skin lesion computational diagnosis of dermoscopic images: Ensemble models based on input feature manipulation.

PubMed

Oliveira, Roberta B; Pereira, Aledir S; Tavares, João Manuel R S

2017-10-01

The number of deaths worldwide due to melanoma has risen in recent times, in part because melanoma is the most aggressive type of skin cancer. Computational systems have been developed to assist dermatologists in early diagnosis of skin cancer, or even to monitor skin lesions. However, there still remains a challenge to improve classifiers for the diagnosis of such skin lesions. The main objective of this article is to evaluate different ensemble classification models based on input feature manipulation to diagnose skin lesions. Input feature manipulation processes are based on feature subset selections from shape properties, colour variation and texture analysis to generate diversity for the ensemble models. Three subset selection models are presented here: (1) a subset selection model based on specific feature groups, (2) a correlation-based subset selection model, and (3) a subset selection model based on feature selection algorithms. Each ensemble classification model is generated using an optimum-path forest classifier and integrated with a majority voting strategy. The proposed models were applied on a set of 1104 dermoscopic images using a cross-validation procedure. The best results were obtained by the first ensemble classification model that generates a feature subset ensemble based on specific feature groups. The skin lesion diagnosis computational system achieved 94.3% accuracy, 91.8% sensitivity and 96.7% specificity. The input feature manipulation process based on specific feature subsets generated the greatest diversity for the ensemble classification model with very promising results. Copyright © 2017 Elsevier B.V. All rights reserved.

Development of a Clinical Forecasting Model to Predict Comorbid Depression Among Diabetes Patients and an Application in Depression Screening Policy Making.

PubMed

Jin, Haomiao; Wu, Shinyi; Di Capua, Paul

2015-09-03

Depression is a common but often undiagnosed comorbid condition of people with diabetes. Mass screening can detect undiagnosed depression but may require significant resources and time. The objectives of this study were 1) to develop a clinical forecasting model that predicts comorbid depression among patients with diabetes and 2) to evaluate a model-based screening policy that saves resources and time by screening only patients considered as depressed by the clinical forecasting model. We trained and validated 4 machine learning models by using data from 2 safety-net clinical trials; we chose the one with the best overall predictive ability as the ultimate model. We compared model-based policy with alternative policies, including mass screening and partial screening, on the basis of depression history or diabetes severity. Logistic regression had the best overall predictive ability of the 4 models evaluated and was chosen as the ultimate forecasting model. Compared with mass screening, the model-based policy can save approximately 50% to 60% of provider resources and time but will miss identifying about 30% of patients with depression. Partial-screening policy based on depression history alone found only a low rate of depression. Two other heuristic-based partial screening policies identified depression at rates similar to those of the model-based policy but cost more in resources and time. The depression prediction model developed in this study has compelling predictive ability. By adopting the model-based depression screening policy, health care providers can use their resources and time better and increase their efficiency in managing their patients with depression.

A Micro-Level Data-Calibrated Agent-Based Model: The Synergy between Microsimulation and Agent-Based Modeling.

PubMed

Singh, Karandeep; Ahn, Chang-Won; Paik, Euihyun; Bae, Jang Won; Lee, Chun-Hee

2018-01-01

Artificial life (ALife) examines systems related to natural life, its processes, and its evolution, using simulations with computer models, robotics, and biochemistry. In this article, we focus on the computer modeling, or "soft," aspects of ALife and prepare a framework for scientists and modelers to be able to support such experiments. The framework is designed and built to be a parallel as well as distributed agent-based modeling environment, and does not require end users to have expertise in parallel or distributed computing. Furthermore, we use this framework to implement a hybrid model using microsimulation and agent-based modeling techniques to generate an artificial society. We leverage this artificial society to simulate and analyze population dynamics using Korean population census data. The agents in this model derive their decisional behaviors from real data (microsimulation feature) and interact among themselves (agent-based modeling feature) to proceed in the simulation. The behaviors, interactions, and social scenarios of the agents are varied to perform an analysis of population dynamics. We also estimate the future cost of pension policies based on the future population structure of the artificial society. The proposed framework and model demonstrates how ALife techniques can be used by researchers in relation to social issues and policies.

Machine Learning and Deep Learning Models to Predict Runoff Water Quantity and Quality

NASA Astrophysics Data System (ADS)

Bradford, S. A.; Liang, J.; Li, W.; Murata, T.; Simunek, J.

2017-12-01

Contaminants can be rapidly transported at the soil surface by runoff to surface water bodies. Physically-based models, which are based on the mathematical description of main hydrological processes, are key tools for predicting surface water impairment. Along with physically-based models, data-driven models are becoming increasingly popular for describing the behavior of hydrological and water resources systems since these models can be used to complement or even replace physically based-models. In this presentation we propose a new data-driven model as an alternative to a physically-based overland flow and transport model. First, we have developed a physically-based numerical model to simulate overland flow and contaminant transport (the HYDRUS-1D overland flow module). A large number of numerical simulations were carried out to develop a database containing information about the impact of various input parameters (weather patterns, surface topography, vegetation, soil conditions, contaminants, and best management practices) on runoff water quantity and quality outputs. This database was used to train data-driven models. Three different methods (Neural Networks, Support Vector Machines, and Recurrence Neural Networks) were explored to prepare input- output functional relations. Results demonstrate the ability and limitations of machine learning and deep learning models to predict runoff water quantity and quality.

A methodology for reduced order modeling and calibration of the upper atmosphere

NASA Astrophysics Data System (ADS)

Mehta, Piyush M.; Linares, Richard

2017-10-01

Atmospheric drag is the largest source of uncertainty in accurately predicting the orbit of satellites in low Earth orbit (LEO). Accurately predicting drag for objects that traverse LEO is critical to space situational awareness. Atmospheric models used for orbital drag calculations can be characterized either as empirical or physics-based (first principles based). Empirical models are fast to evaluate but offer limited real-time predictive/forecasting ability, while physics based models offer greater predictive/forecasting ability but require dedicated parallel computational resources. Also, calibration with accurate data is required for either type of models. This paper presents a new methodology based on proper orthogonal decomposition toward development of a quasi-physical, predictive, reduced order model that combines the speed of empirical and the predictive/forecasting capabilities of physics-based models. The methodology is developed to reduce the high dimensionality of physics-based models while maintaining its capabilities. We develop the methodology using the Naval Research Lab's Mass Spectrometer Incoherent Scatter model and show that the diurnal and seasonal variations can be captured using a small number of modes and parameters. We also present calibration of the reduced order model using the CHAMP and GRACE accelerometer-derived densities. Results show that the method performs well for modeling and calibration of the upper atmosphere.

Variable cycle control model for intersection based on multi-source information

NASA Astrophysics Data System (ADS)

Sun, Zhi-Yuan; Li, Yue; Qu, Wen-Cong; Chen, Yan-Yan

2018-05-01

In order to improve the efficiency of traffic control system in the era of big data, a new variable cycle control model based on multi-source information is presented for intersection in this paper. Firstly, with consideration of multi-source information, a unified framework based on cyber-physical system is proposed. Secondly, taking into account the variable length of cell, hysteresis phenomenon of traffic flow and the characteristics of lane group, a Lane group-based Cell Transmission Model is established to describe the physical properties of traffic flow under different traffic signal control schemes. Thirdly, the variable cycle control problem is abstracted into a bi-level programming model. The upper level model is put forward for cycle length optimization considering traffic capacity and delay. The lower level model is a dynamic signal control decision model based on fairness analysis. Then, a Hybrid Intelligent Optimization Algorithm is raised to solve the proposed model. Finally, a case study shows the efficiency and applicability of the proposed model and algorithm.

The Systems Biology Markup Language (SBML) Level 3 Package: Flux Balance Constraints.

PubMed

Olivier, Brett G; Bergmann, Frank T

2015-09-04

Constraint-based modeling is a well established modelling methodology used to analyze and study biological networks on both a medium and genome scale. Due to their large size, genome scale models are typically analysed using constraint-based optimization techniques. One widely used method is Flux Balance Analysis (FBA) which, for example, requires a modelling description to include: the definition of a stoichiometric matrix, an objective function and bounds on the values that fluxes can obtain at steady state. The Flux Balance Constraints (FBC) Package extends SBML Level 3 and provides a standardized format for the encoding, exchange and annotation of constraint-based models. It includes support for modelling concepts such as objective functions, flux bounds and model component annotation that facilitates reaction balancing. The FBC package establishes a base level for the unambiguous exchange of genome-scale, constraint-based models, that can be built upon by the community to meet future needs (e. g. by extending it to cover dynamic FBC models).

The Systems Biology Markup Language (SBML) Level 3 Package: Flux Balance Constraints.

PubMed

Olivier, Brett G; Bergmann, Frank T

2015-06-01

Constraint-based modeling is a well established modelling methodology used to analyze and study biological networks on both a medium and genome scale. Due to their large size, genome scale models are typically analysed using constraint-based optimization techniques. One widely used method is Flux Balance Analysis (FBA) which, for example, requires a modelling description to include: the definition of a stoichiometric matrix, an objective function and bounds on the values that fluxes can obtain at steady state. The Flux Balance Constraints (FBC) Package extends SBML Level 3 and provides a standardized format for the encoding, exchange and annotation of constraint-based models. It includes support for modelling concepts such as objective functions, flux bounds and model component annotation that facilitates reaction balancing. The FBC package establishes a base level for the unambiguous exchange of genome-scale, constraint-based models, that can be built upon by the community to meet future needs (e. g. by extending it to cover dynamic FBC models).

Comparison of lung tumor motion measured using a model-based 4DCT technique and a commercial protocol.

PubMed

O'Connell, Dylan; Shaverdian, Narek; Kishan, Amar U; Thomas, David H; Dou, Tai H; Lewis, John H; Lamb, James M; Cao, Minsong; Tenn, Stephen; Percy, Lee P; Low, Daniel A

To compare lung tumor motion measured with a model-based technique to commercial 4-dimensional computed tomography (4DCT) scans and describe a workflow for using model-based 4DCT as a clinical simulation protocol. Twenty patients were imaged using a model-based technique and commercial 4DCT. Tumor motion was measured on each commercial 4DCT dataset and was calculated on model-based datasets for 3 breathing amplitude percentile intervals: 5th to 85th, 5th to 95th, and 0th to 100th. Internal target volumes (ITVs) were defined on the 4DCT and 5th to 85th interval datasets and compared using Dice similarity. Images were evaluated for noise and rated by 2 radiation oncologists for artifacts. Mean differences in tumor motion magnitude between commercial and model-based images were 0.47 ± 3.0, 1.63 ± 3.17, and 5.16 ± 4.90 mm for the 5th to 85th, 5th to 95th, and 0th to 100th amplitude intervals, respectively. Dice coefficients between ITVs defined on commercial and 5th to 85th model-based images had a mean value of 0.77 ± 0.09. Single standard deviation image noise was 11.6 ± 9.6 HU in the liver and 6.8 ± 4.7 HU in the aorta for the model-based images compared with 57.7 ± 30 and 33.7 ± 15.4 for commercial 4DCT. Mean model error within the ITV regions was 1.71 ± 0.81 mm. Model-based images exhibited reduced presence of artifacts at the tumor compared with commercial images. Tumor motion measured with the model-based technique using the 5th to 85th percentile breathing amplitude interval corresponded more closely to commercial 4DCT than the 5th to 95th or 0th to 100th intervals, which showed greater motion on average. The model-based technique tended to display increased tumor motion when breathing amplitude intervals wider than 5th to 85th were used because of the influence of unusually deep inhalations. These results suggest that care must be taken in selecting the appropriate interval during image generation when using model-based 4DCT methods. Copyright © 2017 American Society for Radiation Oncology. Published by Elsevier Inc. All rights reserved.

Data-base development for water-quality modeling of the Patuxent River basin, Maryland

USGS Publications Warehouse

Fisher, G.T.; Summers, R.M.

1987-01-01

Procedures and rationale used to develop a data base and data management system for the Patuxent Watershed Nonpoint Source Water Quality Monitoring and Modeling Program of the Maryland Department of the Environment and the U.S. Geological Survey are described. A detailed data base and data management system has been developed to facilitate modeling of the watershed for water quality planning purposes; statistical analysis; plotting of meteorologic, hydrologic and water quality data; and geographic data analysis. The system is Maryland 's prototype for development of a basinwide water quality management program. A key step in the program is to build a calibrated and verified water quality model of the basin using the Hydrological Simulation Program--FORTRAN (HSPF) hydrologic model, which has been used extensively in large-scale basin modeling. The compilation of the substantial existing data base for preliminary calibration of the basin model, including meteorologic, hydrologic, and water quality data from federal and state data bases and a geographic information system containing digital land use and soils data is described. The data base development is significant in its application of an integrated, uniform approach to data base management and modeling. (Lantz-PTT)

Inductive reasoning.

PubMed

Hayes, Brett K; Heit, Evan; Swendsen, Haruka

2010-03-01

Inductive reasoning entails using existing knowledge or observations to make predictions about novel cases. We review recent findings in research on category-based induction as well as theoretical models of these results, including similarity-based models, connectionist networks, an account based on relevance theory, Bayesian models, and other mathematical models. A number of touchstone empirical phenomena that involve taxonomic similarity are described. We also examine phenomena involving more complex background knowledge about premises and conclusions of inductive arguments and the properties referenced. Earlier models are shown to give a good account of similarity-based phenomena but not knowledge-based phenomena. Recent models that aim to account for both similarity-based and knowledge-based phenomena are reviewed and evaluated. Among the most important new directions in induction research are a focus on induction with uncertain premise categories, the modeling of the relationship between inductive and deductive reasoning, and examination of the neural substrates of induction. A common theme in both the well-established and emerging lines of induction research is the need to develop well-articulated and empirically testable formal models of induction. Copyright © 2010 John Wiley & Sons, Ltd. For further resources related to this article, please visit the WIREs website. Copyright © 2010 John Wiley & Sons, Ltd.

The galaxy clustering crisis in abundance matching

NASA Astrophysics Data System (ADS)

Campbell, Duncan; van den Bosch, Frank C.; Padmanabhan, Nikhil; Mao, Yao-Yuan; Zentner, Andrew R.; Lange, Johannes U.; Jiang, Fangzhou; Villarreal, Antonio

2018-06-01

Galaxy clustering on small scales is significantly underpredicted by sub-halo abundance matching (SHAM) models that populate (sub-)haloes with galaxies based on peak halo mass, Mpeak. SHAM models based on the peak maximum circular velocity, Vpeak, have had much better success. The primary reason for Mpeak-based models fail is the relatively low abundance of satellite galaxies produced in these models compared to those based on Vpeak. Despite success in predicting clustering, a simple Vpeak-based SHAM model results in predictions for galaxy growth that are at odds with observations. We evaluate three possible remedies that could `save' mass-based SHAM: (1) SHAM models require a significant population of `orphan' galaxies as a result of artificial disruption/merging of sub-haloes in modern high-resolution dark matter simulations; (2) satellites must grow significantly after their accretion; and (3) stellar mass is significantly affected by halo assembly history. No solution is entirely satisfactory. However, regardless of the particulars, we show that popular SHAM models based on Mpeak cannot be complete physical models as presented. Either Vpeak truly is a better predictor of stellar mass at z ˜ 0 and it remains to be seen how the correlation between stellar mass and Vpeak comes about, or SHAM models are missing vital component(s) that significantly affect galaxy clustering.

Model Based Mission Assurance: Emerging Opportunities for Robotic Systems

NASA Technical Reports Server (NTRS)

Evans, John W.; DiVenti, Tony

2016-01-01

The emergence of Model Based Systems Engineering (MBSE) in a Model Based Engineering framework has created new opportunities to improve effectiveness and efficiencies across the assurance functions. The MBSE environment supports not only system architecture development, but provides for support of Systems Safety, Reliability and Risk Analysis concurrently in the same framework. Linking to detailed design will further improve assurance capabilities to support failures avoidance and mitigation in flight systems. This also is leading new assurance functions including model assurance and management of uncertainty in the modeling environment. Further, the assurance cases, a structured hierarchal argument or model, are emerging as a basis for supporting a comprehensive viewpoint in which to support Model Based Mission Assurance (MBMA).

When Habits Are Dangerous: Alcohol Expectancies and Habitual Decision Making Predict Relapse in Alcohol Dependence.

PubMed

Sebold, Miriam; Nebe, Stephan; Garbusow, Maria; Guggenmos, Matthias; Schad, Daniel J; Beck, Anne; Kuitunen-Paul, Soeren; Sommer, Christian; Frank, Robin; Neu, Peter; Zimmermann, Ulrich S; Rapp, Michael A; Smolka, Michael N; Huys, Quentin J M; Schlagenhauf, Florian; Heinz, Andreas

2017-12-01

Addiction is supposedly characterized by a shift from goal-directed to habitual decision making, thus facilitating automatic drug intake. The two-step task allows distinguishing between these mechanisms by computationally modeling goal-directed and habitual behavior as model-based and model-free control. In addicted patients, decision making may also strongly depend upon drug-associated expectations. Therefore, we investigated model-based versus model-free decision making and its neural correlates as well as alcohol expectancies in alcohol-dependent patients and healthy controls and assessed treatment outcome in patients. Ninety detoxified, medication-free, alcohol-dependent patients and 96 age- and gender-matched control subjects underwent functional magnetic resonance imaging during the two-step task. Alcohol expectancies were measured with the Alcohol Expectancy Questionnaire. Over a follow-up period of 48 weeks, 37 patients remained abstinent and 53 patients relapsed as indicated by the Alcohol Timeline Followback method. Patients who relapsed displayed reduced medial prefrontal cortex activation during model-based decision making. Furthermore, high alcohol expectancies were associated with low model-based control in relapsers, while the opposite was observed in abstainers and healthy control subjects. However, reduced model-based control per se was not associated with subsequent relapse. These findings suggest that poor treatment outcome in alcohol dependence does not simply result from a shift from model-based to model-free control but is instead dependent on the interaction between high drug expectancies and low model-based decision making. Reduced model-based medial prefrontal cortex signatures in those who relapse point to a neural correlate of relapse risk. These observations suggest that therapeutic interventions should target subjective alcohol expectancies. Copyright © 2017 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Dopamine selectively remediates 'model-based' reward learning: a computational approach.

PubMed

Sharp, Madeleine E; Foerde, Karin; Daw, Nathaniel D; Shohamy, Daphna

2016-02-01

Patients with loss of dopamine due to Parkinson's disease are impaired at learning from reward. However, it remains unknown precisely which aspect of learning is impaired. In particular, learning from reward, or reinforcement learning, can be driven by two distinct computational processes. One involves habitual stamping-in of stimulus-response associations, hypothesized to arise computationally from 'model-free' learning. The other, 'model-based' learning, involves learning a model of the world that is believed to support goal-directed behaviour. Much work has pointed to a role for dopamine in model-free learning. But recent work suggests model-based learning may also involve dopamine modulation, raising the possibility that model-based learning may contribute to the learning impairment in Parkinson's disease. To directly test this, we used a two-step reward-learning task which dissociates model-free versus model-based learning. We evaluated learning in patients with Parkinson's disease tested ON versus OFF their dopamine replacement medication and in healthy controls. Surprisingly, we found no effect of disease or medication on model-free learning. Instead, we found that patients tested OFF medication showed a marked impairment in model-based learning, and that this impairment was remediated by dopaminergic medication. Moreover, model-based learning was positively correlated with a separate measure of working memory performance, raising the possibility of common neural substrates. Our results suggest that some learning deficits in Parkinson's disease may be related to an inability to pursue reward based on complete representations of the environment. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Model-Based Assurance Case+ (MBAC+): Tutorial on Modeling Radiation Hardness Assurance Activities

NASA Technical Reports Server (NTRS)

Austin, Rebekah; Label, Ken A.; Sampson, Mike J.; Evans, John; Witulski, Art; Sierawski, Brian; Karsai, Gabor; Mahadevan, Nag; Schrimpf, Ron; Reed, Robert A.

2017-01-01

This presentation will cover why modeling is useful for radiation hardness assurance cases, and also provide information on Model-Based Assurance Case+ (MBAC+), NASAs Reliability Maintainability Template, and Fault Propagation Modeling.

PID-based error signal modeling

NASA Astrophysics Data System (ADS)

Yohannes, Tesfay

1997-10-01

This paper introduces a PID based signal error modeling. The error modeling is based on the betterment process. The resulting iterative learning algorithm is introduced and a detailed proof is provided for both linear and nonlinear systems.

Comparing large-scale computational approaches to epidemic modeling: agent-based versus structured metapopulation models.

PubMed

Ajelli, Marco; Gonçalves, Bruno; Balcan, Duygu; Colizza, Vittoria; Hu, Hao; Ramasco, José J; Merler, Stefano; Vespignani, Alessandro

2010-06-29

In recent years large-scale computational models for the realistic simulation of epidemic outbreaks have been used with increased frequency. Methodologies adapt to the scale of interest and range from very detailed agent-based models to spatially-structured metapopulation models. One major issue thus concerns to what extent the geotemporal spreading pattern found by different modeling approaches may differ and depend on the different approximations and assumptions used. We provide for the first time a side-by-side comparison of the results obtained with a stochastic agent-based model and a structured metapopulation stochastic model for the progression of a baseline pandemic event in Italy, a large and geographically heterogeneous European country. The agent-based model is based on the explicit representation of the Italian population through highly detailed data on the socio-demographic structure. The metapopulation simulations use the GLobal Epidemic and Mobility (GLEaM) model, based on high-resolution census data worldwide, and integrating airline travel flow data with short-range human mobility patterns at the global scale. The model also considers age structure data for Italy. GLEaM and the agent-based models are synchronized in their initial conditions by using the same disease parameterization, and by defining the same importation of infected cases from international travels. The results obtained show that both models provide epidemic patterns that are in very good agreement at the granularity levels accessible by both approaches, with differences in peak timing on the order of a few days. The relative difference of the epidemic size depends on the basic reproductive ratio, R0, and on the fact that the metapopulation model consistently yields a larger incidence than the agent-based model, as expected due to the differences in the structure in the intra-population contact pattern of the approaches. The age breakdown analysis shows that similar attack rates are obtained for the younger age classes. The good agreement between the two modeling approaches is very important for defining the tradeoff between data availability and the information provided by the models. The results we present define the possibility of hybrid models combining the agent-based and the metapopulation approaches according to the available data and computational resources.

Support vector methods for survival analysis: a comparison between ranking and regression approaches.

PubMed

Van Belle, Vanya; Pelckmans, Kristiaan; Van Huffel, Sabine; Suykens, Johan A K

2011-10-01

To compare and evaluate ranking, regression and combined machine learning approaches for the analysis of survival data. The literature describes two approaches based on support vector machines to deal with censored observations. In the first approach the key idea is to rephrase the task as a ranking problem via the concordance index, a problem which can be solved efficiently in a context of structural risk minimization and convex optimization techniques. In a second approach, one uses a regression approach, dealing with censoring by means of inequality constraints. The goal of this paper is then twofold: (i) introducing a new model combining the ranking and regression strategy, which retains the link with existing survival models such as the proportional hazards model via transformation models; and (ii) comparison of the three techniques on 6 clinical and 3 high-dimensional datasets and discussing the relevance of these techniques over classical approaches fur survival data. We compare svm-based survival models based on ranking constraints, based on regression constraints and models based on both ranking and regression constraints. The performance of the models is compared by means of three different measures: (i) the concordance index, measuring the model's discriminating ability; (ii) the logrank test statistic, indicating whether patients with a prognostic index lower than the median prognostic index have a significant different survival than patients with a prognostic index higher than the median; and (iii) the hazard ratio after normalization to restrict the prognostic index between 0 and 1. Our results indicate a significantly better performance for models including regression constraints above models only based on ranking constraints. This work gives empirical evidence that svm-based models using regression constraints perform significantly better than svm-based models based on ranking constraints. Our experiments show a comparable performance for methods including only regression or both regression and ranking constraints on clinical data. On high dimensional data, the former model performs better. However, this approach does not have a theoretical link with standard statistical models for survival data. This link can be made by means of transformation models when ranking constraints are included. Copyright © 2011 Elsevier B.V. All rights reserved.

Automated visualization of rule-based models

PubMed Central

Tapia, Jose-Juan; Faeder, James R.

2017-01-01

Frameworks such as BioNetGen, Kappa and Simmune use “reaction rules” to specify biochemical interactions compactly, where each rule specifies a mechanism such as binding or phosphorylation and its structural requirements. Current rule-based models of signaling pathways have tens to hundreds of rules, and these numbers are expected to increase as more molecule types and pathways are added. Visual representations are critical for conveying rule-based models, but current approaches to show rules and interactions between rules scale poorly with model size. Also, inferring design motifs that emerge from biochemical interactions is an open problem, so current approaches to visualize model architecture rely on manual interpretation of the model. Here, we present three new visualization tools that constitute an automated visualization framework for rule-based models: (i) a compact rule visualization that efficiently displays each rule, (ii) the atom-rule graph that conveys regulatory interactions in the model as a bipartite network, and (iii) a tunable compression pipeline that incorporates expert knowledge and produces compact diagrams of model architecture when applied to the atom-rule graph. The compressed graphs convey network motifs and architectural features useful for understanding both small and large rule-based models, as we show by application to specific examples. Our tools also produce more readable diagrams than current approaches, as we show by comparing visualizations of 27 published models using standard graph metrics. We provide an implementation in the open source and freely available BioNetGen framework, but the underlying methods are general and can be applied to rule-based models from the Kappa and Simmune frameworks also. We expect that these tools will promote communication and analysis of rule-based models and their eventual integration into comprehensive whole-cell models. PMID:29131816

Modelling Students' Visualisation of Chemical Reaction

ERIC Educational Resources Information Center

Cheng, Maurice M. W.; Gilbert, John K.

2017-01-01

This paper proposes a model-based notion of "submicro representations of chemical reactions". Based on three structural models of matter (the simple particle model, the atomic model and the free electron model of metals), we suggest there are two major models of reaction in school chemistry curricula: (a) reactions that are simple…

A Gaussian random field model for similarity-based smoothing in Bayesian disease mapping.

PubMed

Baptista, Helena; Mendes, Jorge M; MacNab, Ying C; Xavier, Miguel; Caldas-de-Almeida, José

2016-08-01

Conditionally specified Gaussian Markov random field (GMRF) models with adjacency-based neighbourhood weight matrix, commonly known as neighbourhood-based GMRF models, have been the mainstream approach to spatial smoothing in Bayesian disease mapping. In the present paper, we propose a conditionally specified Gaussian random field (GRF) model with a similarity-based non-spatial weight matrix to facilitate non-spatial smoothing in Bayesian disease mapping. The model, named similarity-based GRF, is motivated for modelling disease mapping data in situations where the underlying small area relative risks and the associated determinant factors do not vary systematically in space, and the similarity is defined by "similarity" with respect to the associated disease determinant factors. The neighbourhood-based GMRF and the similarity-based GRF are compared and accessed via a simulation study and by two case studies, using new data on alcohol abuse in Portugal collected by the World Mental Health Survey Initiative and the well-known lip cancer data in Scotland. In the presence of disease data with no evidence of positive spatial correlation, the simulation study showed a consistent gain in efficiency from the similarity-based GRF, compared with the adjacency-based GMRF with the determinant risk factors as covariate. This new approach broadens the scope of the existing conditional autocorrelation models. © The Author(s) 2016.

Reacting Chemistry Based Burn Model for Explosive Hydrocodes

NASA Astrophysics Data System (ADS)

Schwaab, Matthew; Greendyke, Robert; Steward, Bryan

2017-06-01

Currently, in hydrocodes designed to simulate explosive material undergoing shock-induced ignition, the state of the art is to use one of numerous reaction burn rate models. These burn models are designed to estimate the bulk chemical reaction rate. Unfortunately, these models are largely based on empirical data and must be recalibrated for every new material being simulated. We propose that the use of an equilibrium Arrhenius rate reacting chemistry model in place of these empirically derived burn models will improve the accuracy for these computational codes. Such models have been successfully used in codes simulating the flow physics around hypersonic vehicles. A reacting chemistry model of this form was developed for the cyclic nitramine RDX by the Naval Research Laboratory (NRL). Initial implementation of this chemistry based burn model has been conducted on the Air Force Research Laboratory's MPEXS multi-phase continuum hydrocode. In its present form, the burn rate is based on the destruction rate of RDX from NRL's chemistry model. Early results using the chemistry based burn model show promise in capturing deflagration to detonation features more accurately in continuum hydrocodes than previously achieved using empirically derived burn models.

Modeling marine oily wastewater treatment by a probabilistic agent-based approach.

PubMed

Jing, Liang; Chen, Bing; Zhang, Baiyu; Ye, Xudong

2018-02-01

This study developed a novel probabilistic agent-based approach for modeling of marine oily wastewater treatment processes. It begins first by constructing a probability-based agent simulation model, followed by a global sensitivity analysis and a genetic algorithm-based calibration. The proposed modeling approach was tested through a case study of the removal of naphthalene from marine oily wastewater using UV irradiation. The removal of naphthalene was described by an agent-based simulation model using 8 types of agents and 11 reactions. Each reaction was governed by a probability parameter to determine its occurrence. The modeling results showed that the root mean square errors between modeled and observed removal rates were 8.73 and 11.03% for calibration and validation runs, respectively. Reaction competition was analyzed by comparing agent-based reaction probabilities, while agents' heterogeneity was visualized by plotting their real-time spatial distribution, showing a strong potential for reactor design and process optimization. Copyright © 2017 Elsevier Ltd. All rights reserved.

Resource management and scheduling policy based on grid for AIoT

NASA Astrophysics Data System (ADS)

Zou, Yiqin; Quan, Li

2017-07-01

This paper has a research on resource management and scheduling policy based on grid technology for Agricultural Internet of Things (AIoT). Facing the situation of a variety of complex and heterogeneous agricultural resources in AIoT, it is difficult to represent them in a unified way. But from an abstract perspective, there are some common models which can express their characteristics and features. Based on this, we proposed a high-level model called Agricultural Resource Hierarchy Model (ARHM), which can be used for modeling various resources. It introduces the agricultural resource modeling method based on this model. Compared with traditional application-oriented three-layer model, ARHM can hide the differences of different applications and make all applications have a unified interface layer and be implemented without distinction. Furthermore, it proposes a Web Service Resource Framework (WSRF)-based resource management method and the encapsulation structure for it. Finally, it focuses on the discussion of multi-agent-based AG resource scheduler, which is a collaborative service provider pattern in multiple agricultural production domains.

The effects of geometric uncertainties on computational modelling of knee biomechanics

NASA Astrophysics Data System (ADS)

Meng, Qingen; Fisher, John; Wilcox, Ruth

2017-08-01

The geometry of the articular components of the knee is an important factor in predicting joint mechanics in computational models. There are a number of uncertainties in the definition of the geometry of cartilage and meniscus, and evaluating the effects of these uncertainties is fundamental to understanding the level of reliability of the models. In this study, the sensitivity of knee mechanics to geometric uncertainties was investigated by comparing polynomial-based and image-based knee models and varying the size of meniscus. The results suggested that the geometric uncertainties in cartilage and meniscus resulting from the resolution of MRI and the accuracy of segmentation caused considerable effects on the predicted knee mechanics. Moreover, even if the mathematical geometric descriptors can be very close to the imaged-based articular surfaces, the detailed contact pressure distribution produced by the mathematical geometric descriptors was not the same as that of the image-based model. However, the trends predicted by the models based on mathematical geometric descriptors were similar to those of the imaged-based models.

Modeling method of time sequence model based grey system theory and application proceedings

NASA Astrophysics Data System (ADS)

Wei, Xuexia; Luo, Yaling; Zhang, Shiqiang

2015-12-01

This article gives a modeling method of grey system GM(1,1) model based on reusing information and the grey system theory. This method not only extremely enhances the fitting and predicting accuracy of GM(1,1) model, but also maintains the conventional routes' merit of simple computation. By this way, we have given one syphilis trend forecast method based on reusing information and the grey system GM(1,1) model.

Pharmacokinetic modeling in aquatic animals. 1. Models and concepts

USGS Publications Warehouse

Barron, M.G.; Stehly, Guy R.; Hayton, W.L.

1990-01-01

While clinical and toxicological applications of pharmacokinetics have continued to evolve both conceptually and experimentally, pharmacokinetics modeling in aquatic animals has not progressed accordingly. In this paper we present methods and concepts of pharmacokinetic modeling in aquatic animals using multicompartmental, clearance-based, non-compartmental and physiologically-based pharmacokinetic models. These models should be considered as alternatives to traditional approaches, which assume that the animal acts as a single homogeneous compartment based on apparent monoexponential elimination.

Agent based reasoning for the non-linear stochastic models of long-range memory

NASA Astrophysics Data System (ADS)

Kononovicius, A.; Gontis, V.

2012-02-01

We extend Kirman's model by introducing variable event time scale. The proposed flexible time scale is equivalent to the variable trading activity observed in financial markets. Stochastic version of the extended Kirman's agent based model is compared to the non-linear stochastic models of long-range memory in financial markets. The agent based model providing matching macroscopic description serves as a microscopic reasoning of the earlier proposed stochastic model exhibiting power law statistics.

Finding Groups Using Model-Based Cluster Analysis: Heterogeneous Emotional Self-Regulatory Processes and Heavy Alcohol Use Risk

ERIC Educational Resources Information Center

Mun, Eun Young; von Eye, Alexander; Bates, Marsha E.; Vaschillo, Evgeny G.

2008-01-01

Model-based cluster analysis is a new clustering procedure to investigate population heterogeneity utilizing finite mixture multivariate normal densities. It is an inferentially based, statistically principled procedure that allows comparison of nonnested models using the Bayesian information criterion to compare multiple models and identify the…

The Agent-based Approach: A New Direction for Computational Models of Development.

ERIC Educational Resources Information Center

Schlesinger, Matthew; Parisi, Domenico

2001-01-01

Introduces the concepts of online and offline sampling and highlights the role of online sampling in agent-based models of learning and development. Compares the strengths of each approach for modeling particular developmental phenomena and research questions. Describes a recent agent-based model of infant causal perception. Discusses limitations…

Testing the Model-Observer Similarity Hypothesis with Text-Based Worked Examples

ERIC Educational Resources Information Center

Hoogerheide, Vincent; Loyens, Sofie M. M.; Jadi, Fedora; Vrins, Anna; van Gog, Tamara

2017-01-01

Example-based learning is a very effective and efficient instructional strategy for novices. It can be implemented using text-based worked examples that provide a written demonstration of how to perform a task, or (video) modelling examples in which an instructor (the "model") provides a demonstration. The model-observer similarity (MOS)…

Exact Hybrid Particle/Population Simulation of Rule-Based Models of Biochemical Systems

PubMed Central

Stover, Lori J.; Nair, Niketh S.; Faeder, James R.

2014-01-01

Detailed modeling and simulation of biochemical systems is complicated by the problem of combinatorial complexity, an explosion in the number of species and reactions due to myriad protein-protein interactions and post-translational modifications. Rule-based modeling overcomes this problem by representing molecules as structured objects and encoding their interactions as pattern-based rules. This greatly simplifies the process of model specification, avoiding the tedious and error prone task of manually enumerating all species and reactions that can potentially exist in a system. From a simulation perspective, rule-based models can be expanded algorithmically into fully-enumerated reaction networks and simulated using a variety of network-based simulation methods, such as ordinary differential equations or Gillespie's algorithm, provided that the network is not exceedingly large. Alternatively, rule-based models can be simulated directly using particle-based kinetic Monte Carlo methods. This “network-free” approach produces exact stochastic trajectories with a computational cost that is independent of network size. However, memory and run time costs increase with the number of particles, limiting the size of system that can be feasibly simulated. Here, we present a hybrid particle/population simulation method that combines the best attributes of both the network-based and network-free approaches. The method takes as input a rule-based model and a user-specified subset of species to treat as population variables rather than as particles. The model is then transformed by a process of “partial network expansion” into a dynamically equivalent form that can be simulated using a population-adapted network-free simulator. The transformation method has been implemented within the open-source rule-based modeling platform BioNetGen, and resulting hybrid models can be simulated using the particle-based simulator NFsim. Performance tests show that significant memory savings can be achieved using the new approach and a monetary cost analysis provides a practical measure of its utility. PMID:24699269

Exact hybrid particle/population simulation of rule-based models of biochemical systems.

PubMed

Hogg, Justin S; Harris, Leonard A; Stover, Lori J; Nair, Niketh S; Faeder, James R

2014-04-01

Detailed modeling and simulation of biochemical systems is complicated by the problem of combinatorial complexity, an explosion in the number of species and reactions due to myriad protein-protein interactions and post-translational modifications. Rule-based modeling overcomes this problem by representing molecules as structured objects and encoding their interactions as pattern-based rules. This greatly simplifies the process of model specification, avoiding the tedious and error prone task of manually enumerating all species and reactions that can potentially exist in a system. From a simulation perspective, rule-based models can be expanded algorithmically into fully-enumerated reaction networks and simulated using a variety of network-based simulation methods, such as ordinary differential equations or Gillespie's algorithm, provided that the network is not exceedingly large. Alternatively, rule-based models can be simulated directly using particle-based kinetic Monte Carlo methods. This "network-free" approach produces exact stochastic trajectories with a computational cost that is independent of network size. However, memory and run time costs increase with the number of particles, limiting the size of system that can be feasibly simulated. Here, we present a hybrid particle/population simulation method that combines the best attributes of both the network-based and network-free approaches. The method takes as input a rule-based model and a user-specified subset of species to treat as population variables rather than as particles. The model is then transformed by a process of "partial network expansion" into a dynamically equivalent form that can be simulated using a population-adapted network-free simulator. The transformation method has been implemented within the open-source rule-based modeling platform BioNetGen, and resulting hybrid models can be simulated using the particle-based simulator NFsim. Performance tests show that significant memory savings can be achieved using the new approach and a monetary cost analysis provides a practical measure of its utility.

FacetModeller: Software for manual creation, manipulation and analysis of 3D surface-based models

NASA Astrophysics Data System (ADS)

Lelièvre, Peter G.; Carter-McAuslan, Angela E.; Dunham, Michael W.; Jones, Drew J.; Nalepa, Mariella; Squires, Chelsea L.; Tycholiz, Cassandra J.; Vallée, Marc A.; Farquharson, Colin G.

2018-01-01

The creation of 3D models is commonplace in many disciplines. Models are often built from a collection of tessellated surfaces. To apply numerical methods to such models it is often necessary to generate a mesh of space-filling elements that conforms to the model surfaces. While there are meshing algorithms that can do so, they place restrictive requirements on the surface-based models that are rarely met by existing 3D model building software. Hence, we have developed a Java application named FacetModeller, designed for efficient manual creation, modification and analysis of 3D surface-based models destined for use in numerical modelling.

Precision assessment of model-based RSA for a total knee prosthesis in a biplanar set-up.

PubMed

Trozzi, C; Kaptein, B L; Garling, E H; Shelyakova, T; Russo, A; Bragonzoni, L; Martelli, S

2008-10-01

Model-based Roentgen Stereophotogrammetric Analysis (RSA) was recently developed for the measurement of prosthesis micromotion. Its main advantage is that markers do not need to be attached to the implants as traditional marker-based RSA requires. Model-based RSA has only been tested in uniplanar radiographic set-ups. A biplanar set-up would theoretically facilitate the pose estimation algorithm, since radiographic projections would show more different shape features of the implants than in uniplanar images. We tested the precision of model-based RSA and compared it with that of the traditional marker-based method in a biplanar set-up. Micromotions of both tibial and femoral components were measured with both the techniques from double examinations of patients participating in a clinical study. The results showed that in the biplanar set-up model-based RSA presents a homogeneous distribution of precision for all the translation directions, but an inhomogeneous error for rotations, especially internal-external rotation presented higher errors than rotations about the transverse and sagittal axes. Model-based RSA was less precise than the marker-based method, although the differences were not significant for the translations and rotations of the tibial component, with the exception of the internal-external rotations. For both prosthesis components the precisions of model-based RSA were below 0.2 mm for all the translations, and below 0.3 degrees for rotations about transverse and sagittal axes. These values are still acceptable for clinical studies aimed at evaluating total knee prosthesis micromotion. In a biplanar set-up model-based RSA is a valid alternative to traditional marker-based RSA where marking of the prosthesis is an enormous disadvantage.

Modeling of Mixing Behavior in a Combined Blowing Steelmaking Converter with a Filter-Based Euler-Lagrange Model

NASA Astrophysics Data System (ADS)

Li, Mingming; Li, Lin; Li, Qiang; Zou, Zongshu

2018-05-01

A filter-based Euler-Lagrange multiphase flow model is used to study the mixing behavior in a combined blowing steelmaking converter. The Euler-based volume of fluid approach is employed to simulate the top blowing, while the Lagrange-based discrete phase model that embeds the local volume change of rising bubbles for the bottom blowing. A filter-based turbulence method based on the local meshing resolution is proposed aiming to improve the modeling of turbulent eddy viscosities. The model validity is verified through comparison with physical experiments in terms of mixing curves and mixing times. The effects of the bottom gas flow rate on bath flow and mixing behavior are investigated and the inherent reasons for the mixing result are clarified in terms of the characteristics of bottom-blowing plumes, the interaction between plumes and top-blowing jets, and the change of bath flow structure.

Base stock system for patient vs impatient customers with varying demand distribution

NASA Astrophysics Data System (ADS)

Fathima, Dowlath; Uduman, P. Sheik

2013-09-01

An optimal Base-Stock inventory policy for Patient and Impatient Customers using finite-horizon models is examined. The Base stock system for Patient and Impatient customers is a different type of inventory policy. In case of the model I, Base stock for Patient customer case is evaluated using the Truncated Exponential Distribution. The model II involves the study of Base-stock inventory policies for Impatient customer. A study on these systems reveals that the Customers wait until the arrival of the next order or the customers leaves the system which leads to lost sale. In both the models demand during the period [0, t] is taken to be a random variable. In this paper, Truncated Exponential Distribution satisfies the Base stock policy for the patient customer as a continuous model. So far the Base stock for Impatient Customers leaded to a discrete case but, in this paper we have modeled this condition into a continuous case. We justify this approach mathematically and also numerically.

Using Model Replication to Improve the Reliability of Agent-Based Models

NASA Astrophysics Data System (ADS)

Zhong, Wei; Kim, Yushim

The basic presupposition of model replication activities for a computational model such as an agent-based model (ABM) is that, as a robust and reliable tool, it must be replicable in other computing settings. This assumption has recently gained attention in the community of artificial society and simulation due to the challenges of model verification and validation. Illustrating the replication of an ABM representing fraudulent behavior in a public service delivery system originally developed in the Java-based MASON toolkit for NetLogo by a different author, this paper exemplifies how model replication exercises provide unique opportunities for model verification and validation process. At the same time, it helps accumulate best practices and patterns of model replication and contributes to the agenda of developing a standard methodological protocol for agent-based social simulation.

Gaps Analysis of Integrating Product Design, Manufacturing, and Quality Data in The Supply Chain Using Model-Based Definition

PubMed Central

Trainer, Asa; Hedberg, Thomas; Feeney, Allison Barnard; Fischer, Kevin; Rosche, Phil

2017-01-01

Advances in information technology triggered a digital revolution that holds promise of reduced costs, improved productivity, and higher quality. To ride this wave of innovation, manufacturing enterprises are changing how product definitions are communicated – from paper to models. To achieve industry's vision of the Model-Based Enterprise (MBE), the MBE strategy must include model-based data interoperability from design to manufacturing and quality in the supply chain. The Model-Based Definition (MBD) is created by the original equipment manufacturer (OEM) using Computer-Aided Design (CAD) tools. This information is then shared with the supplier so that they can manufacture and inspect the physical parts. Today, suppliers predominantly use Computer-Aided Manufacturing (CAM) and Coordinate Measuring Machine (CMM) models for these tasks. Traditionally, the OEM has provided design data to the supplier in the form of two-dimensional (2D) drawings, but may also include a three-dimensional (3D)-shape-geometry model, often in a standards-based format such as ISO 10303-203:2011 (STEP AP203). The supplier then creates the respective CAM and CMM models and machine programs to produce and inspect the parts. In the MBE vision for model-based data exchange, the CAD model must include product-and-manufacturing information (PMI) in addition to the shape geometry. Today's CAD tools can generate models with embedded PMI. And, with the emergence of STEP AP242, a standards-based model with embedded PMI can now be shared downstream. The on-going research detailed in this paper seeks to investigate three concepts. First, that the ability to utilize a STEP AP242 model with embedded PMI for CAD-to-CAM and CAD-to-CMM data exchange is possible and valuable to the overall goal of a more efficient process. Second, the research identifies gaps in tools, standards, and processes that inhibit industry's ability to cost-effectively achieve model-based-data interoperability in the pursuit of the MBE vision. Finally, it also seeks to explore the interaction between CAD and CMM processes and determine if the concept of feedback from CAM and CMM back to CAD is feasible. The main goal of our study is to test the hypothesis that model-based-data interoperability from CAD-to-CAM and CAD-to-CMM is feasible through standards-based integration. This paper presents several barriers to model-based-data interoperability. Overall, the project team demonstrated the exchange of product definition data between CAD, CAM, and CMM systems using standards-based methods. While gaps in standards coverage were identified, the gaps should not stop industry's progress toward MBE. The results of our study provide evidence in support of an open-standards method to model-based-data interoperability, which would provide maximum value and impact to industry. PMID:28691120

A Method for Generating Reduced Order Linear Models of Supersonic Inlets

NASA Technical Reports Server (NTRS)

Chicatelli, Amy; Hartley, Tom T.

1997-01-01

For the modeling of high speed propulsion systems, there are at least two major categories of models. One is based on computational fluid dynamics (CFD), and the other is based on design and analysis of control systems. CFD is accurate and gives a complete view of the internal flow field, but it typically has many states and runs much slower dm real-time. Models based on control design typically run near real-time but do not always capture the fundamental dynamics. To provide improved control models, methods are needed that are based on CFD techniques but yield models that are small enough for control analysis and design.

Brief introductory guide to agent-based modeling and an illustration from urban health research.

PubMed

Auchincloss, Amy H; Garcia, Leandro Martin Totaro

2015-11-01

There is growing interest among urban health researchers in addressing complex problems using conceptual and computation models from the field of complex systems. Agent-based modeling (ABM) is one computational modeling tool that has received a lot of interest. However, many researchers remain unfamiliar with developing and carrying out an ABM, hindering the understanding and application of it. This paper first presents a brief introductory guide to carrying out a simple agent-based model. Then, the method is illustrated by discussing a previously developed agent-based model, which explored inequalities in diet in the context of urban residential segregation.

Brief introductory guide to agent-based modeling and an illustration from urban health research

PubMed Central

Auchincloss, Amy H.; Garcia, Leandro Martin Totaro

2017-01-01

There is growing interest among urban health researchers in addressing complex problems using conceptual and computation models from the field of complex systems. Agent-based modeling (ABM) is one computational modeling tool that has received a lot of interest. However, many researchers remain unfamiliar with developing and carrying out an ABM, hindering the understanding and application of it. This paper first presents a brief introductory guide to carrying out a simple agent-based model. Then, the method is illustrated by discussing a previously developed agent-based model, which explored inequalities in diet in the context of urban residential segregation. PMID:26648364

Arranging ISO 13606 archetypes into a knowledge base.

PubMed

Kopanitsa, Georgy

2014-01-01

To enable the efficient reuse of standard based medical data we propose to develop a higher level information model that will complement the archetype model of ISO 13606. This model will make use of the relationships that are specified in UML to connect medical archetypes into a knowledge base within a repository. UML connectors were analyzed for their ability to be applied in the implementation of a higher level model that will establish relationships between archetypes. An information model was developed using XML Schema notation. The model allows linking different archetypes of one repository into a knowledge base. Presently it supports several relationships and will be advanced in future.

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

PubMed

Ho, K M; Pavey, W

2017-03-01

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

Semi-active control of magnetorheological elastomer base isolation system utilising learning-based inverse model

NASA Astrophysics Data System (ADS)

Gu, Xiaoyu; Yu, Yang; Li, Jianchun; Li, Yancheng

2017-10-01

Magnetorheological elastomer (MRE) base isolations have attracted considerable attention over the last two decades thanks to its self-adaptability and high-authority controllability in semi-active control realm. Due to the inherent nonlinearity and hysteresis of the devices, it is challenging to obtain a reasonably complicated mathematical model to describe the inverse dynamics of MRE base isolators and hence to realise control synthesis of the MRE base isolation system. Two aims have been achieved in this paper: i) development of an inverse model for MRE base isolator based on optimal general regression neural network (GRNN); ii) numerical and experimental validation of a real-time semi-active controlled MRE base isolation system utilising LQR controller and GRNN inverse model. The superiority of GRNN inverse model lays in fewer input variables requirement, faster training process and prompt calculation response, which makes it suitable for online training and real-time control. The control system is integrated with a three-storey shear building model and control performance of the MRE base isolation system is compared with bare building, passive-on isolation system and passive-off isolation system. Testing results show that the proposed GRNN inverse model is able to reproduce desired control force accurately and the MRE base isolation system can effectively suppress the structural responses when compared to the passive isolation system.

Data Clustering and Evolving Fuzzy Decision Tree for Data Base Classification Problems

NASA Astrophysics Data System (ADS)

Chang, Pei-Chann; Fan, Chin-Yuan; Wang, Yen-Wen

Data base classification suffers from two well known difficulties, i.e., the high dimensionality and non-stationary variations within the large historic data. This paper presents a hybrid classification model by integrating a case based reasoning technique, a Fuzzy Decision Tree (FDT), and Genetic Algorithms (GA) to construct a decision-making system for data classification in various data base applications. The model is major based on the idea that the historic data base can be transformed into a smaller case-base together with a group of fuzzy decision rules. As a result, the model can be more accurately respond to the current data under classifying from the inductions by these smaller cases based fuzzy decision trees. Hit rate is applied as a performance measure and the effectiveness of our proposed model is demonstrated by experimentally compared with other approaches on different data base classification applications. The average hit rate of our proposed model is the highest among others.

FlyBase portals to human disease research using Drosophila models

PubMed Central

Millburn, Gillian H.; Crosby, Madeline A.; Gramates, L. Sian; Tweedie, Susan

2016-01-01

ABSTRACT The use of Drosophila melanogaster as a model for studying human disease is well established, reflected by the steady increase in both the number and proportion of fly papers describing human disease models in recent years. In this article, we highlight recent efforts to improve the availability and accessibility of the disease model information in FlyBase (http://flybase.org), the model organism database for Drosophila. FlyBase has recently introduced Human Disease Model Reports, each of which presents background information on a specific disease, a tabulation of related disease subtypes, and summaries of experimental data and results using fruit flies. Integrated presentations of relevant data and reagents described in other sections of FlyBase are incorporated into these reports, which are specifically designed to be accessible to non-fly researchers in order to promote collaboration across model organism communities working in translational science. Another key component of disease model information in FlyBase is that data are collected in a consistent format ­­– using the evolving Disease Ontology (an open-source standardized ontology for human-disease-associated biomedical data) – to allow robust and intuitive searches. To facilitate this, FlyBase has developed a dedicated tool for querying and navigating relevant data, which include mutations that model a disease and any associated interacting modifiers. In this article, we describe how data related to fly models of human disease are presented in individual Gene Reports and in the Human Disease Model Reports. Finally, we discuss search strategies and new query tools that are available to access the disease model data in FlyBase. PMID:26935103

Cellular-based modeling of oscillatory dynamics in brain networks.

PubMed

Skinner, Frances K

2012-08-01

Oscillatory, population activities have long been known to occur in our brains during different behavioral states. We know that many different cell types exist and that they contribute in distinct ways to the generation of these activities. I review recent papers that involve cellular-based models of brain networks, most of which include theta, gamma and sharp wave-ripple activities. To help organize the modeling work, I present it from a perspective of three different types of cellular-based modeling: 'Generic', 'Biophysical' and 'Linking'. Cellular-based modeling is taken to encompass the four features of experiment, model development, theory/analyses, and model usage/computation. The three modeling types are shown to include these features and interactions in different ways. Copyright © 2012 Elsevier Ltd. All rights reserved.

An Exact Model-Based Method for Near-Field Sources Localization with Bistatic MIMO System.

PubMed

Singh, Parth Raj; Wang, Yide; Chargé, Pascal

2017-03-30

In this paper, we propose an exact model-based method for near-field sources localization with a bistatic multiple input, multiple output (MIMO) radar system, and compare it with an approximated model-based method. The aim of this paper is to propose an efficient way to use the exact model of the received signals of near-field sources in order to eliminate the systematic error introduced by the use of approximated model in most existing near-field sources localization techniques. The proposed method uses parallel factor (PARAFAC) decomposition to deal with the exact model. Thanks to the exact model, the proposed method has better precision and resolution than the compared approximated model-based method. The simulation results show the performance of the proposed method.

USE OF BIOLOGICALLY BASED COMPUTATIONAL MODELING IN MODE OF ACTION-BASED RISK ASSESSMENT – AN EXAMPLE OF CHLOROFORM

EPA Science Inventory

The objective of current work is to develop a new cancer dose-response assessment for chloroform using a physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) model. The PBPK/PD model is based on a mode of action in which the cytolethality of chloroform occurs when the ...

Argumentation in Science Education: A Model-Based Framework

ERIC Educational Resources Information Center

Bottcher, Florian; Meisert, Anke

2011-01-01

The goal of this article is threefold: First, the theoretical background for a model-based framework of argumentation to describe and evaluate argumentative processes in science education is presented. Based on the general model-based perspective in cognitive science and the philosophy of science, it is proposed to understand arguments as reasons…

Ground motion simulation for the 23 August 2011, Mineral, Virginia earthquake using physics-based and stochastic broadband methods

USGS Publications Warehouse

Sun, Xiaodan; Hartzell, Stephen; Rezaeian, Sanaz

2015-01-01

Three broadband simulation methods are used to generate synthetic ground motions for the 2011 Mineral, Virginia, earthquake and compare with observed motions. The methods include a physics‐based model by Hartzell et al. (1999, 2005), a stochastic source‐based model by Boore (2009), and a stochastic site‐based model by Rezaeian and Der Kiureghian (2010, 2012). The ground‐motion dataset consists of 40 stations within 600 km of the epicenter. Several metrics are used to validate the simulations: (1) overall bias of response spectra and Fourier spectra (from 0.1 to 10 Hz); (2) spatial distribution of residuals for GMRotI50 peak ground acceleration (PGA), peak ground velocity, and pseudospectral acceleration (PSA) at various periods; (3) comparison with ground‐motion prediction equations (GMPEs) for the eastern United States. Our results show that (1) the physics‐based model provides satisfactory overall bias from 0.1 to 10 Hz and produces more realistic synthetic waveforms; (2) the stochastic site‐based model also yields more realistic synthetic waveforms and performs superiorly for frequencies greater than about 1 Hz; (3) the stochastic source‐based model has larger bias at lower frequencies (<0.5  Hz) and cannot reproduce the varying frequency content in the time domain. The spatial distribution of GMRotI50 residuals shows that there is no obvious pattern with distance in the simulation bias, but there is some azimuthal variability. The comparison between synthetics and GMPEs shows similar fall‐off with distance for all three models, comparable PGA and PSA amplitudes for the physics‐based and stochastic site‐based models, and systematic lower amplitudes for the stochastic source‐based model at lower frequencies (<0.5  Hz).

An object-oriented description method of EPMM process

NASA Astrophysics Data System (ADS)

Jiang, Zuo; Yang, Fan

2017-06-01

In order to use the object-oriented mature tools and language in software process model, make the software process model more accord with the industrial standard, it’s necessary to study the object-oriented modelling of software process. Based on the formal process definition in EPMM, considering the characteristics that Petri net is mainly formal modelling tool and combining the Petri net modelling with the object-oriented modelling idea, this paper provides this implementation method to convert EPMM based on Petri net into object models based on object-oriented description.

Preliminary Cost Model for Space Telescopes

NASA Technical Reports Server (NTRS)

Stahl, H. Philip; Prince, F. Andrew; Smart, Christian; Stephens, Kyle; Henrichs, Todd

2009-01-01

Parametric cost models are routinely used to plan missions, compare concepts and justify technology investments. However, great care is required. Some space telescope cost models, such as those based only on mass, lack sufficient detail to support such analysis and may lead to inaccurate conclusions. Similarly, using ground based telescope models which include the dome cost will also lead to inaccurate conclusions. This paper reviews current and historical models. Then, based on data from 22 different NASA space telescopes, this paper tests those models and presents preliminary analysis of single and multi-variable space telescope cost models.

Research on Turbofan Engine Model above Idle State Based on NARX Modeling Approach

NASA Astrophysics Data System (ADS)

Yu, Bing; Shu, Wenjun

2017-03-01

The nonlinear model for turbofan engine above idle state based on NARX is studied. Above all, the data sets for the JT9D engine from existing model are obtained via simulation. Then, a nonlinear modeling scheme based on NARX is proposed and several models with different parameters are built according to the former data sets. Finally, the simulations have been taken to verify the precise and dynamic performance the models, the results show that the NARX model can well reflect the dynamics characteristic of the turbofan engine with high accuracy.

A new approach towards image based virtual 3D city modeling by using close range photogrammetry

NASA Astrophysics Data System (ADS)

Singh, S. P.; Jain, K.; Mandla, V. R.

2014-05-01

3D city model is a digital representation of the Earth's surface and it's related objects such as building, tree, vegetation, and some manmade feature belonging to urban area. The demand of 3D city modeling is increasing day to day for various engineering and non-engineering applications. Generally three main image based approaches are using for virtual 3D city models generation. In first approach, researchers used Sketch based modeling, second method is Procedural grammar based modeling and third approach is Close range photogrammetry based modeling. Literature study shows that till date, there is no complete solution available to create complete 3D city model by using images. These image based methods also have limitations This paper gives a new approach towards image based virtual 3D city modeling by using close range photogrammetry. This approach is divided into three sections. First, data acquisition process, second is 3D data processing, and third is data combination process. In data acquisition process, a multi-camera setup developed and used for video recording of an area. Image frames created from video data. Minimum required and suitable video image frame selected for 3D processing. In second section, based on close range photogrammetric principles and computer vision techniques, 3D model of area created. In third section, this 3D model exported to adding and merging of other pieces of large area. Scaling and alignment of 3D model was done. After applying the texturing and rendering on this model, a final photo-realistic textured 3D model created. This 3D model transferred into walk-through model or in movie form. Most of the processing steps are automatic. So this method is cost effective and less laborious. Accuracy of this model is good. For this research work, study area is the campus of department of civil engineering, Indian Institute of Technology, Roorkee. This campus acts as a prototype for city. Aerial photography is restricted in many country and high resolution satellite images are costly. In this study, proposed method is based on only simple video recording of area. Thus this proposed method is suitable for 3D city modeling. Photo-realistic, scalable, geo-referenced virtual 3D city model is useful for various kinds of applications such as for planning in navigation, tourism, disasters management, transportations, municipality, urban and environmental managements, real-estate industry. Thus this study will provide a good roadmap for geomatics community to create photo-realistic virtual 3D city model by using close range photogrammetry.

Multi-model comparison on the effects of climate change on tree species in the eastern U.S.: results from an enhanced niche model and process-based ecosystem and landscape models

Treesearch

Louis R. Iverson; Frank R. Thompson; Stephen Matthews; Matthew Peters; Anantha Prasad; William D. Dijak; Jacob Fraser; Wen J. Wang; Brice Hanberry; Hong He; Maria Janowiak; Patricia Butler; Leslie Brandt; Chris Swanston

2016-01-01

Context. Species distribution models (SDM) establish statistical relationships between the current distribution of species and key attributes whereas process-based models simulate ecosystem and tree species dynamics based on representations of physical and biological processes. TreeAtlas, which uses DISTRIB SDM, and Linkages and LANDIS PRO, process...

Defeaturing CAD models using a geometry-based size field and facet-based reduction operators.

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

Quadros, William Roshan; Owen, Steven James

2010-04-01

We propose a method to automatically defeature a CAD model by detecting irrelevant features using a geometry-based size field and a method to remove the irrelevant features via facet-based operations on a discrete representation. A discrete B-Rep model is first created by obtaining a faceted representation of the CAD entities. The candidate facet entities are then marked for reduction by using a geometry-based size field. This is accomplished by estimating local mesh sizes based on geometric criteria. If the field value at a facet entity goes below a user specified threshold value then it is identified as an irrelevant featuremore » and is marked for reduction. The reduction of marked facet entities is primarily performed using an edge collapse operator. Care is taken to retain a valid geometry and topology of the discrete model throughout the procedure. The original model is not altered as the defeaturing is performed on a separate discrete model. Associativity between the entities of the discrete model and that of original CAD model is maintained in order to decode the attributes and boundary conditions applied on the original CAD entities onto the mesh via the entities of the discrete model. Example models are presented to illustrate the effectiveness of the proposed approach.« less

Fecal indicator organism modeling and microbial source tracking in environmental waters: Chapter 3.4.6

USGS Publications Warehouse

Nevers, Meredith; Byappanahalli, Muruleedhara; Phanikumar, Mantha S.; Whitman, Richard L.

2016-01-01

Mathematical models have been widely applied to surface waters to estimate rates of settling, resuspension, flow, dispersion, and advection in order to calculate movement of particles that influence water quality. Of particular interest are the movement, survival, and persistence of microbial pathogens or their surrogates, which may contaminate recreational water, drinking water, or shellfish. Most models devoted to microbial water quality have been focused on fecal indicator organisms (FIO), which act as a surrogate for pathogens and viruses. Process-based modeling and statistical modeling have been used to track contamination events to source and to predict future events. The use of these two types of models require different levels of expertise and input; process-based models rely on theoretical physical constructs to explain present conditions and biological distribution while data-based, statistical models use extant paired data to do the same. The selection of the appropriate model and interpretation of results is critical to proper use of these tools in microbial source tracking. Integration of the modeling approaches could provide insight for tracking and predicting contamination events in real time. A review of modeling efforts reveals that process-based modeling has great promise for microbial source tracking efforts; further, combining the understanding of physical processes influencing FIO contamination developed with process-based models and molecular characterization of the population by gene-based (i.e., biological) or chemical markers may be an effective approach for locating sources and remediating contamination in order to protect human health better.

Drug Distribution. Part 1. Models to Predict Membrane Partitioning.

PubMed

Nagar, Swati; Korzekwa, Ken

2017-03-01

Tissue partitioning is an important component of drug distribution and half-life. Protein binding and lipid partitioning together determine drug distribution. Two structure-based models to predict partitioning into microsomal membranes are presented. An orientation-based model was developed using a membrane template and atom-based relative free energy functions to select drug conformations and orientations for neutral and basic drugs. The resulting model predicts the correct membrane positions for nine compounds tested, and predicts the membrane partitioning for n = 67 drugs with an average fold-error of 2.4. Next, a more facile descriptor-based model was developed for acids, neutrals and bases. This model considers the partitioning of neutral and ionized species at equilibrium, and can predict membrane partitioning with an average fold-error of 2.0 (n = 92 drugs). Together these models suggest that drug orientation is important for membrane partitioning and that membrane partitioning can be well predicted from physicochemical properties.

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

NASA Astrophysics Data System (ADS)

Nazarian, Shahin; Das, Debasish

2013-04-01

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

Model-Based Development of Automotive Electronic Climate Control Software

NASA Astrophysics Data System (ADS)

Kakade, Rupesh; Murugesan, Mohan; Perugu, Bhupal; Nair, Mohanan

With increasing complexity of software in today's products, writing and maintaining thousands of lines of code is a tedious task. Instead, an alternative methodology must be employed. Model-based development is one candidate that offers several benefits and allows engineers to focus on the domain of their expertise than writing huge codes. In this paper, we discuss the application of model-based development to the electronic climate control software of vehicles. The back-to-back testing approach is presented that ensures flawless and smooth transition from legacy designs to the model-based development. Simulink report generator to create design documents from the models is presented along with its usage to run the simulation model and capture the results into the test report. Test automation using model-based development tool that support the use of unique set of test cases for several testing levels and the test procedure that is independent of software and hardware platform is also presented.

Is questionnaire-based sitting time inaccurate and can it be improved? A cross-sectional investigation using accelerometer-based sitting time

PubMed Central

Gupta, Nidhi; Christiansen, Caroline Stordal; Hanisch, Christiana; Bay, Hans; Burr, Hermann; Holtermann, Andreas

2017-01-01

Objectives To investigate the differences between a questionnaire-based and accelerometer-based sitting time, and develop a model for improving the accuracy of questionnaire-based sitting time for predicting accelerometer-based sitting time. Methods 183 workers in a cross-sectional study reported sitting time per day using a single question during the measurement period, and wore 2 Actigraph GT3X+ accelerometers on the thigh and trunk for 1–4 working days to determine their actual sitting time per day using the validated Acti4 software. Least squares regression models were fitted with questionnaire-based siting time and other self-reported predictors to predict accelerometer-based sitting time. Results Questionnaire-based and accelerometer-based average sitting times were ≈272 and ≈476 min/day, respectively. A low Pearson correlation (r=0.32), high mean bias (204.1 min) and wide limits of agreement (549.8 to −139.7 min) between questionnaire-based and accelerometer-based sitting time were found. The prediction model based on questionnaire-based sitting explained 10% of the variance in accelerometer-based sitting time. Inclusion of 9 self-reported predictors in the model increased the explained variance to 41%, with 10% optimism using a resampling bootstrap validation. Based on a split validation analysis, the developed prediction model on ≈75% of the workers (n=132) reduced the mean and the SD of the difference between questionnaire-based and accelerometer-based sitting time by 64% and 42%, respectively, in the remaining 25% of the workers. Conclusions This study indicates that questionnaire-based sitting time has low validity and that a prediction model can be one solution to materially improve the precision of questionnaire-based sitting time. PMID:28093433

Recommending Education Materials for Diabetic Questions Using Information Retrieval Approaches

PubMed Central

Wang, Yanshan; Shen, Feichen; Liu, Sijia; Rastegar-Mojarad, Majid; Wang, Liwei

2017-01-01

Background Self-management is crucial to diabetes care and providing expert-vetted content for answering patients’ questions is crucial in facilitating patient self-management. Objective The aim is to investigate the use of information retrieval techniques in recommending patient education materials for diabetic questions of patients. Methods We compared two retrieval algorithms, one based on Latent Dirichlet Allocation topic modeling (topic modeling-based model) and one based on semantic group (semantic group-based model), with the baseline retrieval models, vector space model (VSM), in recommending diabetic patient education materials to diabetic questions posted on the TuDiabetes forum. The evaluation was based on a gold standard dataset consisting of 50 randomly selected diabetic questions where the relevancy of diabetic education materials to the questions was manually assigned by two experts. The performance was assessed using precision of top-ranked documents. Results We retrieved 7510 diabetic questions on the forum and 144 diabetic patient educational materials from the patient education database at Mayo Clinic. The mapping rate of words in each corpus mapped to the Unified Medical Language System (UMLS) was significantly different (P<.001). The topic modeling-based model outperformed the other retrieval algorithms. For example, for the top-retrieved document, the precision of the topic modeling-based, semantic group-based, and VSM models was 67.0%, 62.8%, and 54.3%, respectively. Conclusions This study demonstrated that topic modeling can mitigate the vocabulary difference and it achieved the best performance in recommending education materials for answering patients’ questions. One direction for future work is to assess the generalizability of our findings and to extend our study to other disease areas, other patient education material resources, and online forums. PMID:29038097

An OpenACC-Based Unified Programming Model for Multi-accelerator Systems

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

Kim, Jungwon; Lee, Seyong; Vetter, Jeffrey S

2015-01-01

This paper proposes a novel SPMD programming model of OpenACC. Our model integrates the different granularities of parallelism from vector-level parallelism to node-level parallelism into a single, unified model based on OpenACC. It allows programmers to write programs for multiple accelerators using a uniform programming model whether they are in shared or distributed memory systems. We implement a prototype of our model and evaluate its performance with a GPU-based supercomputer using three benchmark applications.

The Mixed Instrumental Controller: Using Value of Information to Combine Habitual Choice and Mental Simulation

PubMed Central

Pezzulo, Giovanni; Rigoli, Francesco; Chersi, Fabian

2013-01-01

Instrumental behavior depends on both goal-directed and habitual mechanisms of choice. Normative views cast these mechanisms in terms of model-free and model-based methods of reinforcement learning, respectively. An influential proposal hypothesizes that model-free and model-based mechanisms coexist and compete in the brain according to their relative uncertainty. In this paper we propose a novel view in which a single Mixed Instrumental Controller produces both goal-directed and habitual behavior by flexibly balancing and combining model-based and model-free computations. The Mixed Instrumental Controller performs a cost-benefits analysis to decide whether to chose an action immediately based on the available “cached” value of actions (linked to model-free mechanisms) or to improve value estimation by mentally simulating the expected outcome values (linked to model-based mechanisms). Since mental simulation entails cognitive effort and increases the reward delay, it is activated only when the associated “Value of Information” exceeds its costs. The model proposes a method to compute the Value of Information, based on the uncertainty of action values and on the distance of alternative cached action values. Overall, the model by default chooses on the basis of lighter model-free estimates, and integrates them with costly model-based predictions only when useful. Mental simulation uses a sampling method to produce reward expectancies, which are used to update the cached value of one or more actions; in turn, this updated value is used for the choice. The key predictions of the model are tested in different settings of a double T-maze scenario. Results are discussed in relation with neurobiological evidence on the hippocampus – ventral striatum circuit in rodents, which has been linked to goal-directed spatial navigation. PMID:23459512

The mixed instrumental controller: using value of information to combine habitual choice and mental simulation.

PubMed

Pezzulo, Giovanni; Rigoli, Francesco; Chersi, Fabian

2013-01-01

Instrumental behavior depends on both goal-directed and habitual mechanisms of choice. Normative views cast these mechanisms in terms of model-free and model-based methods of reinforcement learning, respectively. An influential proposal hypothesizes that model-free and model-based mechanisms coexist and compete in the brain according to their relative uncertainty. In this paper we propose a novel view in which a single Mixed Instrumental Controller produces both goal-directed and habitual behavior by flexibly balancing and combining model-based and model-free computations. The Mixed Instrumental Controller performs a cost-benefits analysis to decide whether to chose an action immediately based on the available "cached" value of actions (linked to model-free mechanisms) or to improve value estimation by mentally simulating the expected outcome values (linked to model-based mechanisms). Since mental simulation entails cognitive effort and increases the reward delay, it is activated only when the associated "Value of Information" exceeds its costs. The model proposes a method to compute the Value of Information, based on the uncertainty of action values and on the distance of alternative cached action values. Overall, the model by default chooses on the basis of lighter model-free estimates, and integrates them with costly model-based predictions only when useful. Mental simulation uses a sampling method to produce reward expectancies, which are used to update the cached value of one or more actions; in turn, this updated value is used for the choice. The key predictions of the model are tested in different settings of a double T-maze scenario. Results are discussed in relation with neurobiological evidence on the hippocampus - ventral striatum circuit in rodents, which has been linked to goal-directed spatial navigation.

Population pharmacokinetics of busulfan in pediatric and young adult patients undergoing hematopoietic cell transplant: a model-based dosing algorithm for personalized therapy and implementation into routine clinical use.

PubMed

Long-Boyle, Janel R; Savic, Rada; Yan, Shirley; Bartelink, Imke; Musick, Lisa; French, Deborah; Law, Jason; Horn, Biljana; Cowan, Morton J; Dvorak, Christopher C

2015-04-01

Population pharmacokinetic (PK) studies of busulfan in children have shown that individualized model-based algorithms provide improved targeted busulfan therapy when compared with conventional dose guidelines. The adoption of population PK models into routine clinical practice has been hampered by the tendency of pharmacologists to develop complex models too impractical for clinicians to use. The authors aimed to develop a population PK model for busulfan in children that can reliably achieve therapeutic exposure (concentration at steady state) and implement a simple model-based tool for the initial dosing of busulfan in children undergoing hematopoietic cell transplantation. Model development was conducted using retrospective data available in 90 pediatric and young adult patients who had undergone hematopoietic cell transplantation with busulfan conditioning. Busulfan drug levels and potential covariates influencing drug exposure were analyzed using the nonlinear mixed effects modeling software, NONMEM. The final population PK model was implemented into a clinician-friendly Microsoft Excel-based tool and used to recommend initial doses of busulfan in a group of 21 pediatric patients prospectively dosed based on the population PK model. Modeling of busulfan time-concentration data indicates that busulfan clearance displays nonlinearity in children, decreasing up to approximately 20% between the concentrations of 250-2000 ng/mL. Important patient-specific covariates found to significantly impact busulfan clearance were actual body weight and age. The percentage of individuals achieving a therapeutic concentration at steady state was significantly higher in subjects receiving initial doses based on the population PK model (81%) than in historical controls dosed on conventional guidelines (52%) (P = 0.02). When compared with the conventional dosing guidelines, the model-based algorithm demonstrates significant improvement for providing targeted busulfan therapy in children and young adults.

Promoting Model-based Definition to Establish a Complete Product Definition

PubMed Central

Ruemler, Shawn P.; Zimmerman, Kyle E.; Hartman, Nathan W.; Hedberg, Thomas; Feeny, Allison Barnard

2016-01-01

The manufacturing industry is evolving and starting to use 3D models as the central knowledge artifact for product data and product definition, or what is known as Model-based Definition (MBD). The Model-based Enterprise (MBE) uses MBD as a way to transition away from using traditional paper-based drawings and documentation. As MBD grows in popularity, it is imperative to understand what information is needed in the transition from drawings to models so that models represent all the relevant information needed for processes to continue efficiently. Finding this information can help define what data is common amongst different models in different stages of the lifecycle, which could help establish a Common Information Model. The Common Information Model is a source that contains common information from domain specific elements amongst different aspects of the lifecycle. To help establish this Common Information Model, information about how models are used in industry within different workflows needs to be understood. To retrieve this information, a survey mechanism was administered to industry professionals from various sectors. Based on the results of the survey a Common Information Model could not be established. However, the results gave great insight that will help in further investigation of the Common Information Model. PMID:28070155

Base Flow Model Validation

NASA Technical Reports Server (NTRS)

Sinha, Neeraj; Brinckman, Kevin; Jansen, Bernard; Seiner, John

2011-01-01

A method was developed of obtaining propulsive base flow data in both hot and cold jet environments, at Mach numbers and altitude of relevance to NASA launcher designs. The base flow data was used to perform computational fluid dynamics (CFD) turbulence model assessments of base flow predictive capabilities in order to provide increased confidence in base thermal and pressure load predictions obtained from computational modeling efforts. Predictive CFD analyses were used in the design of the experiments, available propulsive models were used to reduce program costs and increase success, and a wind tunnel facility was used. The data obtained allowed assessment of CFD/turbulence models in a complex flow environment, working within a building-block procedure to validation, where cold, non-reacting test data was first used for validation, followed by more complex reacting base flow validation.

Model-Based Prognostics of Hybrid Systems

NASA Technical Reports Server (NTRS)

Daigle, Matthew; Roychoudhury, Indranil; Bregon, Anibal

2015-01-01

Model-based prognostics has become a popular approach to solving the prognostics problem. However, almost all work has focused on prognostics of systems with continuous dynamics. In this paper, we extend the model-based prognostics framework to hybrid systems models that combine both continuous and discrete dynamics. In general, most systems are hybrid in nature, including those that combine physical processes with software. We generalize the model-based prognostics formulation to hybrid systems, and describe the challenges involved. We present a general approach for modeling hybrid systems, and overview methods for solving estimation and prediction in hybrid systems. As a case study, we consider the problem of conflict (i.e., loss of separation) prediction in the National Airspace System, in which the aircraft models are hybrid dynamical systems.

CDMBE: A Case Description Model Based on Evidence

PubMed Central

Zhu, Jianlin; Yang, Xiaoping; Zhou, Jing

2015-01-01

By combining the advantages of argument map and Bayesian network, a case description model based on evidence (CDMBE), which is suitable to continental law system, is proposed to describe the criminal cases. The logic of the model adopts the credibility logical reason and gets evidence-based reasoning quantitatively based on evidences. In order to consist with practical inference rules, five types of relationship and a set of rules are defined to calculate the credibility of assumptions based on the credibility and supportability of the related evidences. Experiments show that the model can get users' ideas into a figure and the results calculated from CDMBE are in line with those from Bayesian model. PMID:26421006

LIFETIME LUNG CANCER RISKS ASSOCIATED WITH INDOOR RADON EXPOSURE BASED ON VARIOUS RADON RISK MODELS FOR CANADIAN POPULATION.

PubMed

Chen, Jing

2017-04-01

This study calculates and compares the lifetime lung cancer risks associated with indoor radon exposure based on well-known risk models in the literature; two risk models are from joint studies among miners and the other three models were developed from pooling studies on residential radon exposure from China, Europe and North America respectively. The aim of this article is to make clear that the various models are mathematical descriptions of epidemiologically observed real risks in different environmental settings. The risk from exposure to indoor radon is real and it is normal that variations could exist among different risk models even when they were applied to the same dataset. The results show that lifetime risk estimates vary significantly between the various risk models considered here: the model based on the European residential data provides the lowest risk estimates, while models based on the European miners and Chinese residential pooling with complete dosimetry give the highest values. The lifetime risk estimates based on the EPA/BEIR-VI model lie within this range and agree reasonably well with the averages of risk estimates from the five risk models considered in this study. © Crown copyright 2016.

Teaching EFL Writing: An Approach Based on the Learner's Context Model

ERIC Educational Resources Information Center

Lin, Zheng

2017-01-01

This study aims to examine qualitatively a new approach to teaching English as a foreign language (EFL) writing based on the learner's context model. It investigates the context model-based approach in class and identifies key characteristics of the approach delivered through a four-phase teaching and learning cycle. The model collects research…

Cycles of Exploration, Reflection, and Consolidation in Model-Based Learning of Genetics

ERIC Educational Resources Information Center

Kim, Beaumie; Pathak, Suneeta A.; Jacobson, Michael J.; Zhang, Baohui; Gobert, Janice D.

2015-01-01

Model-based reasoning has been introduced as an authentic way of learning science, and many researchers have developed technological tools for learning with models. This paper describes how a model-based tool, "BioLogica"™, was used to facilitate genetics learning in secondary 3-level biology in Singapore. The research team co-designed…

Character and Local Wisdom-Based Instructional Model of Bahasa Indonesia in Vocational High Schools

ERIC Educational Resources Information Center

Anggraini, Purwati; Kusniarti, Tuti

2017-01-01

This research aimed at establishing a character and local wisdom-based instructional model of Bahasa Indonesia. The learning model based on local wisdom literature is very important to prepared, because this model can enrich the knowledge and develop the character of students. Meanwhile, the textbook can broaden the student teachers about the…

A PHYSIOLOGICALLY BASED PHARMACOKINETIC/PHARMACODYNAMIC (PBPK/PD) MODEL FOR ESTIMATION OF CUMULATIVE RISK FROM EXPOSURE TO THREE N-METHYL CARBAMATES: CARBARYL, ALDICARB, AND CARBOFURAN

EPA Science Inventory

A physiologically-based pharmacokinetic (PBPK) model for a mixture of N-methyl carbamate pesticides was developed based on single chemical models. The model was used to compare urinary metabolite concentrations to levels from National Health and Nutrition Examination Survey (NHA...

Comparing model-based adaptive LMS filters and a model-free hysteresis loop analysis method for structural health monitoring

NASA Astrophysics Data System (ADS)

Zhou, Cong; Chase, J. Geoffrey; Rodgers, Geoffrey W.; Xu, Chao

2017-02-01

The model-free hysteresis loop analysis (HLA) method for structural health monitoring (SHM) has significant advantages over the traditional model-based SHM methods that require a suitable baseline model to represent the actual system response. This paper provides a unique validation against both an experimental reinforced concrete (RC) building and a calibrated numerical model to delineate the capability of the model-free HLA method and the adaptive least mean squares (LMS) model-based method in detecting, localizing and quantifying damage that may not be visible, observable in overall structural response. Results clearly show the model-free HLA method is capable of adapting to changes in how structures transfer load or demand across structural elements over time and multiple events of different size. However, the adaptive LMS model-based method presented an image of greater spread of lesser damage over time and story when the baseline model is not well defined. Finally, the two algorithms are tested over a simpler hysteretic behaviour typical steel structure to quantify the impact of model mismatch between the baseline model used for identification and the actual response. The overall results highlight the need for model-based methods to have an appropriate model that can capture the observed response, in order to yield accurate results, even in small events where the structure remains linear.

Stability of model-based event-triggered control systems: a separation property

NASA Astrophysics Data System (ADS)

Hao, Fei; Yu, Hao

2017-04-01

To save resource of communication, this paper investigates the model-based event-triggered control systems. Two main problems are considered in this paper. One is, for given plant and model, to design event conditions to guarantee the stability of the systems. The other is to consider the effect of the model matrices on the stability. The results show that the closed-loop systems can be asymptotically stabilised with any model matrices in compact sets if the parameters in the event conditions are within the designed ranges. Then, a separation property of model-based event-triggered control is proposed. Namely, the design of the controller gain and the event condition can be separated from the selection of the model matrices. Based on this property, an adaption mechanism is introduced to the model-based event-triggered control systems, which can further improve the sampling performance. Finally, a numerical example is given to show the efficiency and feasibility of the developed results.

An Investigation of Two Finite Element Modeling Solutions for Biomechanical Simulation Using a Case Study of a Mandibular Bone.

PubMed

Liu, Yun-Feng; Fan, Ying-Ying; Dong, Hui-Yue; Zhang, Jian-Xing

2017-12-01

The method used in biomechanical modeling for finite element method (FEM) analysis needs to deliver accurate results. There are currently two solutions used in FEM modeling for biomedical model of human bone from computerized tomography (CT) images: one is based on a triangular mesh and the other is based on the parametric surface model and is more popular in practice. The outline and modeling procedures for the two solutions are compared and analyzed. Using a mandibular bone as an example, several key modeling steps are then discussed in detail, and the FEM calculation was conducted. Numerical calculation results based on the models derived from the two methods, including stress, strain, and displacement, are compared and evaluated in relation to accuracy and validity. Moreover, a comprehensive comparison of the two solutions is listed. The parametric surface based method is more helpful when using powerful design tools in computer-aided design (CAD) software, but the triangular mesh based method is more robust and efficient.

Basic Diagnosis and Prediction of Persistent Contrail Occurrence using High-resolution Numerical Weather Analyses/Forecasts and Logistic Regression. Part II: Evaluation of Sample Models

NASA Technical Reports Server (NTRS)

Duda, David P.; Minnis, Patrick

2009-01-01

Previous studies have shown that probabilistic forecasting may be a useful method for predicting persistent contrail formation. A probabilistic forecast to accurately predict contrail formation over the contiguous United States (CONUS) is created by using meteorological data based on hourly meteorological analyses from the Advanced Regional Prediction System (ARPS) and from the Rapid Update Cycle (RUC) as well as GOES water vapor channel measurements, combined with surface and satellite observations of contrails. Two groups of logistic models were created. The first group of models (SURFACE models) is based on surface-based contrail observations supplemented with satellite observations of contrail occurrence. The second group of models (OUTBREAK models) is derived from a selected subgroup of satellite-based observations of widespread persistent contrails. The mean accuracies for both the SURFACE and OUTBREAK models typically exceeded 75 percent when based on the RUC or ARPS analysis data, but decreased when the logistic models were derived from ARPS forecast data.

Improving flood forecasting capability of physically based distributed hydrological model by parameter optimization

NASA Astrophysics Data System (ADS)

Chen, Y.; Li, J.; Xu, H.

2015-10-01

Physically based distributed hydrological models discrete the terrain of the whole catchment into a number of grid cells at fine resolution, and assimilate different terrain data and precipitation to different cells, and are regarded to have the potential to improve the catchment hydrological processes simulation and prediction capability. In the early stage, physically based distributed hydrological models are assumed to derive model parameters from the terrain properties directly, so there is no need to calibrate model parameters, but unfortunately, the uncertanties associated with this model parameter deriving is very high, which impacted their application in flood forecasting, so parameter optimization may also be necessary. There are two main purposes for this study, the first is to propose a parameter optimization method for physically based distributed hydrological models in catchment flood forecasting by using PSO algorithm and to test its competence and to improve its performances, the second is to explore the possibility of improving physically based distributed hydrological models capability in cathcment flood forecasting by parameter optimization. In this paper, based on the scalar concept, a general framework for parameter optimization of the PBDHMs for catchment flood forecasting is first proposed that could be used for all PBDHMs. Then, with Liuxihe model as the study model, which is a physically based distributed hydrological model proposed for catchment flood forecasting, the improverd Particle Swarm Optimization (PSO) algorithm is developed for the parameter optimization of Liuxihe model in catchment flood forecasting, the improvements include to adopt the linear decreasing inertia weight strategy to change the inertia weight, and the arccosine function strategy to adjust the acceleration coefficients. This method has been tested in two catchments in southern China with different sizes, and the results show that the improved PSO algorithm could be used for Liuxihe model parameter optimization effectively, and could improve the model capability largely in catchment flood forecasting, thus proven that parameter optimization is necessary to improve the flood forecasting capability of physically based distributed hydrological model. It also has been found that the appropriate particle number and the maximum evolution number of PSO algorithm used for Liuxihe model catchment flood forcasting is 20 and 30, respectively.

Constitutive Models for Design of Sustainable Concrete Structures

NASA Astrophysics Data System (ADS)

Brozovsky, J.; Cajka, R.; Koktan, J.

2018-04-01

The paper deals with numerical models of reinforced concrete which are expected to be useful to enhance design of sustainable reinforced concrete structures. That is, the models which can deliver higher precision of results than the linear elastic models but which are still feasible for engineering practice. Such models can be based on an elastic-plastic material. The paper discusses properties of such models. A material model based of the Chen criteria and the Ohtani hardening model for concrete was selected for further development. There is also given a comparison of behaviour of such model with behaviour of a more complex smeared crack model which is based on principles of fracture mechanics.

Comparison of the landslide susceptibility models in Taipei Water Source Domain, Taiwan

NASA Astrophysics Data System (ADS)

WU, C. Y.; Yeh, Y. C.; Chou, T. H.

2017-12-01

Taipei Water Source Domain, locating at the southeast of Taipei Metropolis, is the main source of water resource in this region. Recently, the downstream turbidity often soared significantly during the typhoon period because of the upstream landslides. The landslide susceptibilities should be analysed to assess the influence zones caused by different rainfall events, and to ensure the abilities of this domain to serve enough and quality water resource. Generally, the landslide susceptibility models can be established based on either a long-term landslide inventory or a specified landslide event. Sometimes, there is no long-term landslide inventory in some areas. Thus, the event-based landslide susceptibility models are established widely. However, the inventory-based and event-based landslide susceptibility models may result in dissimilar susceptibility maps in the same area. So the purposes of this study were to compare the landslide susceptibility maps derived from the inventory-based and event-based models, and to interpret how to select a representative event to be included in the susceptibility model. The landslide inventory from Typhoon Tim in July, 1994 and Typhoon Soudelor in August, 2015 was collected, and used to establish the inventory-based landslide susceptibility model. The landslides caused by Typhoon Nari and rainfall data were used to establish the event-based model. The results indicated the high susceptibility slope-units were located at middle upstream Nan-Shih Stream basin.

Work domain constraints for modelling surgical performance.

PubMed

Morineau, Thierry; Riffaud, Laurent; Morandi, Xavier; Villain, Jonathan; Jannin, Pierre

2015-10-01

Three main approaches can be identified for modelling surgical performance: a competency-based approach, a task-based approach, both largely explored in the literature, and a less known work domain-based approach. The work domain-based approach first describes the work domain properties that constrain the agent's actions and shape the performance. This paper presents a work domain-based approach for modelling performance during cervical spine surgery, based on the idea that anatomical structures delineate the surgical performance. This model was evaluated through an analysis of junior and senior surgeons' actions. Twenty-four cervical spine surgeries performed by two junior and two senior surgeons were recorded in real time by an expert surgeon. According to a work domain-based model describing an optimal progression through anatomical structures, the degree of adjustment of each surgical procedure to a statistical polynomial function was assessed. Each surgical procedure showed a significant suitability with the model and regression coefficient values around 0.9. However, the surgeries performed by senior surgeons fitted this model significantly better than those performed by junior surgeons. Analysis of the relative frequencies of actions on anatomical structures showed that some specific anatomical structures discriminate senior from junior performances. The work domain-based modelling approach can provide an overall statistical indicator of surgical performance, but in particular, it can highlight specific points of interest among anatomical structures that the surgeons dwelled on according to their level of expertise.

The impacts of data constraints on the predictive performance of a general process-based crop model (PeakN-crop v1.0)

NASA Astrophysics Data System (ADS)

Caldararu, Silvia; Purves, Drew W.; Smith, Matthew J.

2017-04-01

Improving international food security under a changing climate and increasing human population will be greatly aided by improving our ability to modify, understand and predict crop growth. What we predominantly have at our disposal are either process-based models of crop physiology or statistical analyses of yield datasets, both of which suffer from various sources of error. In this paper, we present a generic process-based crop model (PeakN-crop v1.0) which we parametrise using a Bayesian model-fitting algorithm to three different sources: data-space-based vegetation indices, eddy covariance productivity measurements and regional crop yields. We show that the model parametrised without data, based on prior knowledge of the parameters, can largely capture the observed behaviour but the data-constrained model greatly improves both the model fit and reduces prediction uncertainty. We investigate the extent to which each dataset contributes to the model performance and show that while all data improve on the prior model fit, the satellite-based data and crop yield estimates are particularly important for reducing model error and uncertainty. Despite these improvements, we conclude that there are still significant knowledge gaps, in terms of available data for model parametrisation, but our study can help indicate the necessary data collection to improve our predictions of crop yields and crop responses to environmental changes.

Comparison between two statistically based methods, and two physically based models developed to compute daily mean streamflow at ungaged locations in the Cedar River Basin, Iowa

USGS Publications Warehouse

Linhart, S. Mike; Nania, Jon F.; Christiansen, Daniel E.; Hutchinson, Kasey J.; Sanders, Curtis L.; Archfield, Stacey A.

2013-01-01

A variety of individuals from water resource managers to recreational users need streamflow information for planning and decisionmaking at locations where there are no streamgages. To address this problem, two statistically based methods, the Flow Duration Curve Transfer method and the Flow Anywhere method, were developed for statewide application and the two physically based models, the Precipitation Runoff Modeling-System and the Soil and Water Assessment Tool, were only developed for application for the Cedar River Basin. Observed and estimated streamflows for the two methods and models were compared for goodness of fit at 13 streamgages modeled in the Cedar River Basin by using the Nash-Sutcliffe and the percent-bias efficiency values. Based on median and mean Nash-Sutcliffe values for the 13 streamgages the Precipitation Runoff Modeling-System and Soil and Water Assessment Tool models appear to have performed similarly and better than Flow Duration Curve Transfer and Flow Anywhere methods. Based on median and mean percent bias values, the Soil and Water Assessment Tool model appears to have generally overestimated daily mean streamflows, whereas the Precipitation Runoff Modeling-System model and statistical methods appear to have underestimated daily mean streamflows. The Flow Duration Curve Transfer method produced the lowest median and mean percent bias values and appears to perform better than the other models.

Extending rule-based methods to model molecular geometry and 3D model resolution.

PubMed

Hoard, Brittany; Jacobson, Bruna; Manavi, Kasra; Tapia, Lydia

2016-08-01

Computational modeling is an important tool for the study of complex biochemical processes associated with cell signaling networks. However, it is challenging to simulate processes that involve hundreds of large molecules due to the high computational cost of such simulations. Rule-based modeling is a method that can be used to simulate these processes with reasonably low computational cost, but traditional rule-based modeling approaches do not include details of molecular geometry. The incorporation of geometry into biochemical models can more accurately capture details of these processes, and may lead to insights into how geometry affects the products that form. Furthermore, geometric rule-based modeling can be used to complement other computational methods that explicitly represent molecular geometry in order to quantify binding site accessibility and steric effects. We propose a novel implementation of rule-based modeling that encodes details of molecular geometry into the rules and binding rates. We demonstrate how rules are constructed according to the molecular curvature. We then perform a study of antigen-antibody aggregation using our proposed method. We simulate the binding of antibody complexes to binding regions of the shrimp allergen Pen a 1 using a previously developed 3D rigid-body Monte Carlo simulation, and we analyze the aggregate sizes. Then, using our novel approach, we optimize a rule-based model according to the geometry of the Pen a 1 molecule and the data from the Monte Carlo simulation. We use the distances between the binding regions of Pen a 1 to optimize the rules and binding rates. We perform this procedure for multiple conformations of Pen a 1 and analyze the impact of conformation and resolution on the optimal rule-based model. We find that the optimized rule-based models provide information about the average steric hindrance between binding regions and the probability that antibodies will bind to these regions. These optimized models quantify the variation in aggregate size that results from differences in molecular geometry and from model resolution.

Comparing niche- and process-based models to reduce prediction uncertainty in species range shifts under climate change.

PubMed

Morin, Xavier; Thuiller, Wilfried

2009-05-01

Obtaining reliable predictions of species range shifts under climate change is a crucial challenge for ecologists and stakeholders. At the continental scale, niche-based models have been widely used in the last 10 years to predict the potential impacts of climate change on species distributions all over the world, although these models do not include any mechanistic relationships. In contrast, species-specific, process-based predictions remain scarce at the continental scale. This is regrettable because to secure relevant and accurate predictions it is always desirable to compare predictions derived from different kinds of models applied independently to the same set of species and using the same raw data. Here we compare predictions of range shifts under climate change scenarios for 2100 derived from niche-based models with those of a process-based model for 15 North American boreal and temperate tree species. A general pattern emerged from our comparisons: niche-based models tend to predict a stronger level of extinction and a greater proportion of colonization than the process-based model. This result likely arises because niche-based models do not take phenotypic plasticity and local adaptation into account. Nevertheless, as the two kinds of models rely on different assumptions, their complementarity is revealed by common findings. Both modeling approaches highlight a major potential limitation on species tracking their climatic niche because of migration constraints and identify similar zones where species extirpation is likely. Such convergent predictions from models built on very different principles provide a useful way to offset uncertainties at the continental scale. This study shows that the use in concert of both approaches with their own caveats and advantages is crucial to obtain more robust results and that comparisons among models are needed in the near future to gain accuracy regarding predictions of range shifts under climate change.

Climate change impacts on tree ranges: model intercomparison facilitates understanding and quantification of uncertainty.

PubMed

Cheaib, Alissar; Badeau, Vincent; Boe, Julien; Chuine, Isabelle; Delire, Christine; Dufrêne, Eric; François, Christophe; Gritti, Emmanuel S; Legay, Myriam; Pagé, Christian; Thuiller, Wilfried; Viovy, Nicolas; Leadley, Paul

2012-06-01

Model-based projections of shifts in tree species range due to climate change are becoming an important decision support tool for forest management. However, poorly evaluated sources of uncertainty require more scrutiny before relying heavily on models for decision-making. We evaluated uncertainty arising from differences in model formulations of tree response to climate change based on a rigorous intercomparison of projections of tree distributions in France. We compared eight models ranging from niche-based to process-based models. On average, models project large range contractions of temperate tree species in lowlands due to climate change. There was substantial disagreement between models for temperate broadleaf deciduous tree species, but differences in the capacity of models to account for rising CO(2) impacts explained much of the disagreement. There was good quantitative agreement among models concerning the range contractions for Scots pine. For the dominant Mediterranean tree species, Holm oak, all models foresee substantial range expansion. © 2012 Blackwell Publishing Ltd/CNRS.

Using concept maps to describe undergraduate students’ mental model in microbiology course

NASA Astrophysics Data System (ADS)

Hamdiyati, Y.; Sudargo, F.; Redjeki, S.; Fitriani, A.

2018-05-01

The purpose of this research was to describe students’ mental model in a mental model based-microbiology course using concept map as assessment tool. Respondents were 5th semester of undergraduate students of Biology Education of Universitas Pendidikan Indonesia. The mental modelling instrument used was concept maps. Data were taken on Bacteria sub subject. A concept map rubric was subsequently developed with a maximum score of 4. Quantitative data was converted into a qualitative one to determine mental model level, namely: emergent = score 1, transitional = score 2, close to extended = score 3, and extended = score 4. The results showed that mental model level on bacteria sub subject before the implementation of mental model based-microbiology course was at the transitional level. After implementation of mental model based-microbiology course, mental model was at transitional level, close to extended, and extended. This indicated an increase in the level of students’ mental model after the implementation of mental model based-microbiology course using concept map as assessment tool.

WORKSHOP ON APPLICATION OF STATISTICAL METHODS TO BIOLOGICALLY-BASED PHARMACOKINETIC MODELING FOR RISK ASSESSMENT

EPA Science Inventory

Biologically-based pharmacokinetic models are being increasingly used in the risk assessment of environmental chemicals. These models are based on biological, mathematical, statistical and engineering principles. Their potential uses in risk assessment include extrapolation betwe...

High-Throughput Physiologically Based Toxicokinetic Models for ToxCast Chemicals

EPA Science Inventory

Physiologically based toxicokinetic (PBTK) models aid in predicting exposure doses needed to create tissue concentrations equivalent to those identified as bioactive by ToxCast. We have implemented four empirical and physiologically-based toxicokinetic (TK) models within a new R ...

Evaluating the effect of human activity patterns on air pollution exposure using an integrated field-based and agent-based modelling framework

NASA Astrophysics Data System (ADS)

Schmitz, Oliver; Beelen, Rob M. J.; de Bakker, Merijn P.; Karssenberg, Derek

2015-04-01

Constructing spatio-temporal numerical models to support risk assessment, such as assessing the exposure of humans to air pollution, often requires the integration of field-based and agent-based modelling approaches. Continuous environmental variables such as air pollution are best represented using the field-based approach which considers phenomena as continuous fields having attribute values at all locations. When calculating human exposure to such pollutants it is, however, preferable to consider the population as a set of individuals each with a particular activity pattern. This would allow to account for the spatio-temporal variation in a pollutant along the space-time paths travelled by individuals, determined, for example, by home and work locations, road network, and travel times. Modelling this activity pattern requires an agent-based or individual based modelling approach. In general, field- and agent-based models are constructed with the help of separate software tools, while both approaches should play together in an interacting way and preferably should be combined into one modelling framework, which would allow for efficient and effective implementation of models by domain specialists. To overcome this lack in integrated modelling frameworks, we aim at the development of concepts and software for an integrated field-based and agent-based modelling framework. Concepts merging field- and agent-based modelling were implemented by extending PCRaster (http://www.pcraster.eu), a field-based modelling library implemented in C++, with components for 1) representation of discrete, mobile, agents, 2) spatial networks and algorithms by integrating the NetworkX library (http://networkx.github.io), allowing therefore to calculate e.g. shortest routes or total transport costs between locations, and 3) functions for field-network interactions, allowing to assign field-based attribute values to networks (i.e. as edge weights), such as aggregated or averaged concentration values. We demonstrate the approach by using six land use regression (LUR) models developed in the ESCAPE (European Study of Cohorts for Air Pollution Effects) project. These models calculate several air pollutants (e.g. NO2, NOx, PM2.5) for the entire Netherlands at a high (5 m) resolution. Using these air pollution maps, we compare exposure of individuals calculated at their x, y location of their home, their work place, and aggregated over the close surroundings of these locations. In addition, total exposure is accumulated over daily activity patterns, summing exposure at home, at the work place, and while travelling between home and workplace, by routing individuals over the Dutch road network, using the shortest route. Finally, we illustrate how routes can be calculated with the minimum total exposure (instead of shortest distance).

Impact on house staff evaluation scores when changing from a Dreyfus- to a Milestone-based evaluation model: one internal medicine residency program's findings.

PubMed

Friedman, Karen A; Balwan, Sandy; Cacace, Frank; Katona, Kyle; Sunday, Suzanne; Chaudhry, Saima

2014-01-01

As graduate medical education (GME) moves into the Next Accreditation System (NAS), programs must take a critical look at their current models of evaluation and assess how well they align with reporting outcomes. Our objective was to assess the impact on house staff evaluation scores when transitioning from a Dreyfus-based model of evaluation to a Milestone-based model of evaluation. Milestones are a key component of the NAS. We analyzed all end of rotation evaluations of house staff completed by faculty for academic years 2010-2011 (pre-Dreyfus model) and 2011-2012 (post-Milestone model) in one large university-based internal medicine residency training program. Main measures included change in PGY-level average score; slope, range, and separation of average scores across all six Accreditation Council for Graduate Medical Education (ACGME) competencies. Transitioning from a Dreyfus-based model to a Milestone-based model resulted in a larger separation in the scores between our three post-graduate year classes, a steeper progression of scores in the PGY-1 class, a wider use of the 5-point scale on our global end of rotation evaluation form, and a downward shift in the PGY-1 scores and an upward shift in the PGY-3 scores. For faculty trained in both models of assessment, the Milestone-based model had greater discriminatory ability as evidenced by the larger separation in the scores for all the classes, in particular the PGY-1 class.

An accurate nonlinear stochastic model for MEMS-based inertial sensor error with wavelet networks

NASA Astrophysics Data System (ADS)

El-Diasty, Mohammed; El-Rabbany, Ahmed; Pagiatakis, Spiros

2007-12-01

The integration of Global Positioning System (GPS) with Inertial Navigation System (INS) has been widely used in many applications for positioning and orientation purposes. Traditionally, random walk (RW), Gauss-Markov (GM), and autoregressive (AR) processes have been used to develop the stochastic model in classical Kalman filters. The main disadvantage of classical Kalman filter is the potentially unstable linearization of the nonlinear dynamic system. Consequently, a nonlinear stochastic model is not optimal in derivative-based filters due to the expected linearization error. With a derivativeless-based filter such as the unscented Kalman filter or the divided difference filter, the filtering process of a complicated highly nonlinear dynamic system is possible without linearization error. This paper develops a novel nonlinear stochastic model for inertial sensor error using a wavelet network (WN). A wavelet network is a highly nonlinear model, which has recently been introduced as a powerful tool for modelling and prediction. Static and kinematic data sets are collected using a MEMS-based IMU (DQI-100) to develop the stochastic model in the static mode and then implement it in the kinematic mode. The derivativeless-based filtering method using GM, AR, and the proposed WN-based processes are used to validate the new model. It is shown that the first-order WN-based nonlinear stochastic model gives superior positioning results to the first-order GM and AR models with an overall improvement of 30% when 30 and 60 seconds GPS outages are introduced.

Stolen Base Physics

NASA Astrophysics Data System (ADS)

Kagan, David

2013-05-01

Few plays in baseball are as consistently close and exciting as the stolen base. While there are several studies of sprinting,2-4 the art of base stealing is much more nuanced. This article describes the motion of the base-stealing runner using a very basic kinematic model. The model will be compared to some data from a Major League game. The predictions of the model show consistency with the skills needed for effective base stealing.

Moving alcohol prevention research forward-Part II: new directions grounded in community-based system dynamics modeling.

PubMed

Apostolopoulos, Yorghos; Lemke, Michael K; Barry, Adam E; Lich, Kristen Hassmiller

2018-02-01

Given the complexity of factors contributing to alcohol misuse, appropriate epistemologies and methodologies are needed to understand and intervene meaningfully. We aimed to (1) provide an overview of computational modeling methodologies, with an emphasis on system dynamics modeling; (2) explain how community-based system dynamics modeling can forge new directions in alcohol prevention research; and (3) present a primer on how to build alcohol misuse simulation models using system dynamics modeling, with an emphasis on stakeholder involvement, data sources and model validation. Throughout, we use alcohol misuse among college students in the United States as a heuristic example for demonstrating these methodologies. System dynamics modeling employs a top-down aggregate approach to understanding dynamically complex problems. Its three foundational properties-stocks, flows and feedbacks-capture non-linearity, time-delayed effects and other system characteristics. As a methodological choice, system dynamics modeling is amenable to participatory approaches; in particular, community-based system dynamics modeling has been used to build impactful models for addressing dynamically complex problems. The process of community-based system dynamics modeling consists of numerous stages: (1) creating model boundary charts, behavior-over-time-graphs and preliminary system dynamics models using group model-building techniques; (2) model formulation; (3) model calibration; (4) model testing and validation; and (5) model simulation using learning-laboratory techniques. Community-based system dynamics modeling can provide powerful tools for policy and intervention decisions that can result ultimately in sustainable changes in research and action in alcohol misuse prevention. © 2017 Society for the Study of Addiction.

Mathematical modeling and characteristic analysis for over-under turbine based combined cycle engine

NASA Astrophysics Data System (ADS)

Ma, Jingxue; Chang, Juntao; Ma, Jicheng; Bao, Wen; Yu, Daren

2018-07-01

The turbine based combined cycle engine has become the most promising hypersonic airbreathing propulsion system for its superiority of ground self-starting, wide flight envelop and reusability. The simulation model of the turbine based combined cycle engine plays an important role in the research of performance analysis and control system design. In this paper, a turbine based combined cycle engine mathematical model is built on the Simulink platform, including a dual-channel air intake system, a turbojet engine and a ramjet. It should be noted that the model of the air intake system is built based on computational fluid dynamics calculation, which provides valuable raw data for modeling of the turbine based combined cycle engine. The aerodynamic characteristics of turbine based combined cycle engine in turbojet mode, ramjet mode and mode transition process are studied by the mathematical model, and the influence of dominant variables on performance and safety of the turbine based combined cycle engine is analyzed. According to the stability requirement of thrust output and the safety in the working process of turbine based combined cycle engine, a control law is proposed that could guarantee the steady output of thrust by controlling the control variables of the turbine based combined cycle engine in the whole working process.

Using SEM to Analyze Complex Survey Data: A Comparison between Design-Based Single-Level and Model-Based Multilevel Approaches

ERIC Educational Resources Information Center

Wu, Jiun-Yu; Kwok, Oi-man

2012-01-01

Both ad-hoc robust sandwich standard error estimators (design-based approach) and multilevel analysis (model-based approach) are commonly used for analyzing complex survey data with nonindependent observations. Although these 2 approaches perform equally well on analyzing complex survey data with equal between- and within-level model structures…

Evidence-Based Adequacy Model for School Funding: Success Rates in Illinois Schools that Meet Targets

ERIC Educational Resources Information Center

Murphy, Gregory J.

2012-01-01

This quantitative study explores the 2010 recommendation of the Educational Funding Advisory Board to consider the Evidence-Based Adequacy model of school funding in Illinois. This school funding model identifies and costs research based practices necessary in a prototypical school and sets funding levels based upon those practices. This study…

Applying Constructivist and Objectivist Learning Theories in the Design of a Web-based Course: Implications for Practice.

ERIC Educational Resources Information Center

Moallem, Mahnaz

2001-01-01

Provides an overview of the process of designing and developing a Web-based course using instructional design principles and models, including constructivist and objectivist theories. Explains the process of implementing an instructional design model in designing a Web-based undergraduate course and evaluates the model based on course evaluations.…

The Effect of Modeling Based Science Education on Critical Thinking

ERIC Educational Resources Information Center

Bati, Kaan; Kaptan, Fitnat

2015-01-01

In this study to what degree the modeling based science education can influence the development of the critical thinking skills of the students was investigated. The research was based on pre-test-post-test quasi-experimental design with control group. The Modeling Based Science Education Program which was prepared with the purpose of exploring…

Modeling the Player: Predictability of the Models of Bartle and Kolb Based on NEO-FFI (Big5) and the Implications for Game Based Learning

ERIC Educational Resources Information Center

Konert, Johannes; Gutjahr, Michael; Göbel, Stefan; Steinmetz, Ralf

2014-01-01

For adaptation and personalization of game play sophisticated player models and learner models are used in game-based learning environments. Thus, the game flow can be optimized to increase efficiency and effectiveness of gaming and learning in parallel. In the field of gaming still the Bartle model is commonly used due to its simplicity and good…

Patterns of Use of an Agent-Based Model and a System Dynamics Model: The Application of Patterns of Use and the Impacts on Learning Outcomes

ERIC Educational Resources Information Center

Thompson, Kate; Reimann, Peter

2010-01-01

A classification system that was developed for the use of agent-based models was applied to strategies used by school-aged students to interrogate an agent-based model and a system dynamics model. These were compared, and relationships between learning outcomes and the strategies used were also analysed. It was found that the classification system…

Modeling Long-term Creep Performance for Welded Nickel-base Superalloy Structures for Power Generation Systems

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

Shen, Chen; Gupta, Vipul; Huang, Shenyan

The goal of this project is to model long-term creep performance for nickel-base superalloy weldments in high temperature power generation systems. The project uses physics-based modeling methodologies and algorithms for predicting alloy properties in heterogeneous material structures. The modeling methodology will be demonstrated on a gas turbine combustor liner weldment of Haynes 282 precipitate-strengthened nickel-base superalloy. The major developments are: (1) microstructure-property relationships under creep conditions and microstructure characterization (2) modeling inhomogeneous microstructure in superalloy weld (3) modeling mesoscale plastic deformation in superalloy weld and (4) a constitutive creep model that accounts for weld and base metal microstructure and theirmore » long term evolution. The developed modeling technology is aimed to provide a more efficient and accurate assessment of a material’s long-term performance compared with current testing and extrapolation methods. This modeling technology will also accelerate development and qualification of new materials in advanced power generation systems. This document is a final technical report for the project, covering efforts conducted from October 2014 to December 2016.« less

Copula based prediction models: an application to an aortic regurgitation study

PubMed Central

Kumar, Pranesh; Shoukri, Mohamed M

2007-01-01

Background: An important issue in prediction modeling of multivariate data is the measure of dependence structure. The use of Pearson's correlation as a dependence measure has several pitfalls and hence application of regression prediction models based on this correlation may not be an appropriate methodology. As an alternative, a copula based methodology for prediction modeling and an algorithm to simulate data are proposed. Methods: The method consists of introducing copulas as an alternative to the correlation coefficient commonly used as a measure of dependence. An algorithm based on the marginal distributions of random variables is applied to construct the Archimedean copulas. Monte Carlo simulations are carried out to replicate datasets, estimate prediction model parameters and validate them using Lin's concordance measure. Results: We have carried out a correlation-based regression analysis on data from 20 patients aged 17–82 years on pre-operative and post-operative ejection fractions after surgery and estimated the prediction model: Post-operative ejection fraction = - 0.0658 + 0.8403 (Pre-operative ejection fraction); p = 0.0008; 95% confidence interval of the slope coefficient (0.3998, 1.2808). From the exploratory data analysis, it is noted that both the pre-operative and post-operative ejection fractions measurements have slight departures from symmetry and are skewed to the left. It is also noted that the measurements tend to be widely spread and have shorter tails compared to normal distribution. Therefore predictions made from the correlation-based model corresponding to the pre-operative ejection fraction measurements in the lower range may not be accurate. Further it is found that the best approximated marginal distributions of pre-operative and post-operative ejection fractions (using q-q plots) are gamma distributions. The copula based prediction model is estimated as: Post -operative ejection fraction = - 0.0933 + 0.8907 × (Pre-operative ejection fraction); p = 0.00008 ; 95% confidence interval for slope coefficient (0.4810, 1.3003). For both models differences in the predicted post-operative ejection fractions in the lower range of pre-operative ejection measurements are considerably different and prediction errors due to copula model are smaller. To validate the copula methodology we have re-sampled with replacement fifty independent bootstrap samples and have estimated concordance statistics 0.7722 (p = 0.0224) for the copula model and 0.7237 (p = 0.0604) for the correlation model. The predicted and observed measurements are concordant for both models. The estimates of accuracy components are 0.9233 and 0.8654 for copula and correlation models respectively. Conclusion: Copula-based prediction modeling is demonstrated to be an appropriate alternative to the conventional correlation-based prediction modeling since the correlation-based prediction models are not appropriate to model the dependence in populations with asymmetrical tails. Proposed copula-based prediction model has been validated using the independent bootstrap samples. PMID:17573974

Mathematical models of behavior of individual animals.

PubMed

Tsibulsky, Vladimir L; Norman, Andrew B

2007-01-01

This review is focused on mathematical modeling of behaviors of a whole organism with special emphasis on models with a clearly scientific approach to the problem that helps to understand the mechanisms underlying behavior. The aim is to provide an overview of old and contemporary mathematical models without complex mathematical details. Only deterministic and stochastic, but not statistical models are reviewed. All mathematical models of behavior can be divided into two main classes. First, models that are based on the principle of teleological determinism assume that subjects choose the behavior that will lead them to a better payoff in the future. Examples are game theories and operant behavior models both of which are based on the matching law. The second class of models are based on the principle of causal determinism, which assume that subjects do not choose from a set of possibilities but rather are compelled to perform a predetermined behavior in response to specific stimuli. Examples are perception and discrimination models, drug effects models and individual-based population models. A brief overview of the utility of each mathematical model is provided for each section.

Surrogate Based Uni/Multi-Objective Optimization and Distribution Estimation Methods

NASA Astrophysics Data System (ADS)

Gong, W.; Duan, Q.; Huo, X.

2017-12-01

Parameter calibration has been demonstrated as an effective way to improve the performance of dynamic models, such as hydrological models, land surface models, weather and climate models etc. Traditional optimization algorithms usually cost a huge number of model evaluations, making dynamic model calibration very difficult, or even computationally prohibitive. With the help of a serious of recently developed adaptive surrogate-modelling based optimization methods: uni-objective optimization method ASMO, multi-objective optimization method MO-ASMO, and probability distribution estimation method ASMO-PODE, the number of model evaluations can be significantly reduced to several hundreds, making it possible to calibrate very expensive dynamic models, such as regional high resolution land surface models, weather forecast models such as WRF, and intermediate complexity earth system models such as LOVECLIM. This presentation provides a brief introduction to the common framework of adaptive surrogate-based optimization algorithms of ASMO, MO-ASMO and ASMO-PODE, a case study of Common Land Model (CoLM) calibration in Heihe river basin in Northwest China, and an outlook of the potential applications of the surrogate-based optimization methods.

QSPR modeling: graph connectivity indices versus line graph connectivity indices

PubMed

Basak; Nikolic; Trinajstic; Amic; Beslo

2000-07-01

Five QSPR models of alkanes were reinvestigated. Properties considered were molecular surface-dependent properties (boiling points and gas chromatographic retention indices) and molecular volume-dependent properties (molar volumes and molar refractions). The vertex- and edge-connectivity indices were used as structural parameters. In each studied case we computed connectivity indices of alkane trees and alkane line graphs and searched for the optimum exponent. Models based on indices with an optimum exponent and on the standard value of the exponent were compared. Thus, for each property we generated six QSPR models (four for alkane trees and two for the corresponding line graphs). In all studied cases QSPR models based on connectivity indices with optimum exponents have better statistical characteristics than the models based on connectivity indices with the standard value of the exponent. The comparison between models based on vertex- and edge-connectivity indices gave in two cases (molar volumes and molar refractions) better models based on edge-connectivity indices and in three cases (boiling points for octanes and nonanes and gas chromatographic retention indices) better models based on vertex-connectivity indices. Thus, it appears that the edge-connectivity index is more appropriate to be used in the structure-molecular volume properties modeling and the vertex-connectivity index in the structure-molecular surface properties modeling. The use of line graphs did not improve the predictive power of the connectivity indices. Only in one case (boiling points of nonanes) a better model was obtained with the use of line graphs.

Arranging ISO 13606 archetypes into a knowledge base using UML connectors.

PubMed

Kopanitsa, Georgy

2014-01-01

To enable the efficient reuse of standard based medical data we propose to develop a higher-level information model that will complement the archetype model of ISO 13606. This model will make use of the relationships that are specified in UML to connect medical archetypes into a knowledge base within a repository. UML connectors were analysed for their ability to be applied in the implementation of a higher-level model that will establish relationships between archetypes. An information model was developed using XML Schema notation. The model allows linking different archetypes of one repository into a knowledge base. Presently it supports several relationships and will be advanced in future.

Pattern-oriented modeling of agent-based complex systems: Lessons from ecology

USGS Publications Warehouse

Grimm, Volker; Revilla, Eloy; Berger, Uta; Jeltsch, Florian; Mooij, Wolf M.; Railsback, Steven F.; Thulke, Hans-Hermann; Weiner, Jacob; Wiegand, Thorsten; DeAngelis, Donald L.

2005-01-01

Agent-based complex systems are dynamic networks of many interacting agents; examples include ecosystems, financial markets, and cities. The search for general principles underlying the internal organization of such systems often uses bottom-up simulation models such as cellular automata and agent-based models. No general framework for designing, testing, and analyzing bottom-up models has yet been established, but recent advances in ecological modeling have come together in a general strategy we call pattern-oriented modeling. This strategy provides a unifying framework for decoding the internal organization of agent-based complex systems and may lead toward unifying algorithmic theories of the relation between adaptive behavior and system complexity.

Pattern-Oriented Modeling of Agent-Based Complex Systems: Lessons from Ecology

NASA Astrophysics Data System (ADS)

Grimm, Volker; Revilla, Eloy; Berger, Uta; Jeltsch, Florian; Mooij, Wolf M.; Railsback, Steven F.; Thulke, Hans-Hermann; Weiner, Jacob; Wiegand, Thorsten; DeAngelis, Donald L.

2005-11-01

Agent-based complex systems are dynamic networks of many interacting agents; examples include ecosystems, financial markets, and cities. The search for general principles underlying the internal organization of such systems often uses bottom-up simulation models such as cellular automata and agent-based models. No general framework for designing, testing, and analyzing bottom-up models has yet been established, but recent advances in ecological modeling have come together in a general strategy we call pattern-oriented modeling. This strategy provides a unifying framework for decoding the internal organization of agent-based complex systems and may lead toward unifying algorithmic theories of the relation between adaptive behavior and system complexity.

Evolvable social agents for bacterial systems modeling.

PubMed

Paton, Ray; Gregory, Richard; Vlachos, Costas; Saunders, Jon; Wu, Henry

2004-09-01

We present two approaches to the individual-based modeling (IbM) of bacterial ecologies and evolution using computational tools. The IbM approach is introduced, and its important complementary role to biosystems modeling is discussed. A fine-grained model of bacterial evolution is then presented that is based on networks of interactivity between computational objects representing genes and proteins. This is followed by a coarser grained agent-based model, which is designed to explore the evolvability of adaptive behavioral strategies in artificial bacteria represented by learning classifier systems. The structure and implementation of the two proposed individual-based bacterial models are discussed, and some results from simulation experiments are presented, illustrating their adaptive properties.

The Use of Health Information Technology Within Collaborative and Integrated Models of Child Psychiatry Practice.

PubMed

Coffey, Sara; Vanderlip, Erik; Sarvet, Barry

2017-01-01

There is a consistent need for more child and adolescent psychiatrists. Despite increased recruitment of child and adolescent psychiatry trainees, traditional models of care will likely not be able to meet the need of youth with mental illness. Integrated care models focusing on population-based, team-based, measurement-based, and evidenced-based care have been effective in addressing accessibility and quality of care. These integrated models have specific needs regarding health information technology (HIT). HIT has been used in a variety of different ways in several integrated care models. HIT can aid in implementation of these models but is not without its challenges. Copyright © 2016 Elsevier Inc. All rights reserved.

Numerical analysis of base flowfield at high altitude for a four-engine clustered nozzle configuration

NASA Technical Reports Server (NTRS)

Wang, Ten-See

1993-01-01

The objective of this study is to benchmark a four-engine clustered nozzle base flowfield with a computational fluid dynamics (CFD) model. The CFD model is a pressure based, viscous flow formulation. An adaptive upwind scheme is employed for the spatial discretization. The upwind scheme is based on second and fourth order central differencing with adaptive artificial dissipation. Qualitative base flow features such as the reverse jet, wall jet, recompression shock, and plume-plume impingement have been captured. The computed quantitative flow properties such as the radial base pressure distribution, model centerline Mach number and static pressure variation, and base pressure characteristic curve agreed reasonably well with those of the measurement. Parametric study on the effect of grid resolution, turbulence model, inlet boundary condition and difference scheme on convective terms has been performed. The results showed that grid resolution and turbulence model are two primary factors that influence the accuracy of the base flowfield prediction.

Injury risk functions based on population-based finite element model responses: Application to femurs under dynamic three-point bending.

PubMed

Park, Gwansik; Forman, Jason; Kim, Taewung; Panzer, Matthew B; Crandall, Jeff R

2018-02-28

The goal of this study was to explore a framework for developing injury risk functions (IRFs) in a bottom-up approach based on responses of parametrically variable finite element (FE) models representing exemplar populations. First, a parametric femur modeling tool was developed and validated using a subject-specific (SS)-FE modeling approach. Second, principal component analysis and regression were used to identify parametric geometric descriptors of the human femur and the distribution of those factors for 3 target occupant sizes (5th, 50th, and 95th percentile males). Third, distributions of material parameters of cortical bone were obtained from the literature for 3 target occupant ages (25, 50, and 75 years) using regression analysis. A Monte Carlo method was then implemented to generate populations of FE models of the femur for target occupants, using a parametric femur modeling tool. Simulations were conducted with each of these models under 3-point dynamic bending. Finally, model-based IRFs were developed using logistic regression analysis, based on the moment at fracture observed in the FE simulation. In total, 100 femur FE models incorporating the variation in the population of interest were generated, and 500,000 moments at fracture were observed (applying 5,000 ultimate strains for each synthesized 100 femur FE models) for each target occupant characteristics. Using the proposed framework on this study, the model-based IRFs for 3 target male occupant sizes (5th, 50th, and 95th percentiles) and ages (25, 50, and 75 years) were developed. The model-based IRF was located in the 95% confidence interval of the test-based IRF for the range of 15 to 70% injury risks. The 95% confidence interval of the developed IRF was almost in line with the mean curve due to a large number of data points. The framework proposed in this study would be beneficial for developing the IRFs in a bottom-up manner, whose range of variabilities is informed by the population-based FE model responses. Specifically, this method mitigates the uncertainties in applying empirical scaling and may improve IRF fidelity when a limited number of experimental specimens are available.

Creating "Intelligent" Ensemble Averages Using a Process-Based Framework

NASA Astrophysics Data System (ADS)

Baker, Noel; Taylor, Patrick

2014-05-01

The CMIP5 archive contains future climate projections from over 50 models provided by dozens of modeling centers from around the world. Individual model projections, however, are subject to biases created by structural model uncertainties. As a result, ensemble averaging of multiple models is used to add value to individual model projections and construct a consensus projection. Previous reports for the IPCC establish climate change projections based on an equal-weighted average of all model projections. However, individual models reproduce certain climate processes better than other models. Should models be weighted based on performance? Unequal ensemble averages have previously been constructed using a variety of mean state metrics. What metrics are most relevant for constraining future climate projections? This project develops a framework for systematically testing metrics in models to identify optimal metrics for unequal weighting multi-model ensembles. The intention is to produce improved ("intelligent") unequal-weight ensemble averages. A unique aspect of this project is the construction and testing of climate process-based model evaluation metrics. A climate process-based metric is defined as a metric based on the relationship between two physically related climate variables—e.g., outgoing longwave radiation and surface temperature. Several climate process metrics are constructed using high-quality Earth radiation budget data from NASA's Clouds and Earth's Radiant Energy System (CERES) instrument in combination with surface temperature data sets. It is found that regional values of tested quantities can vary significantly when comparing the equal-weighted ensemble average and an ensemble weighted using the process-based metric. Additionally, this study investigates the dependence of the metric weighting scheme on the climate state using a combination of model simulations including a non-forced preindustrial control experiment, historical simulations, and several radiative forcing Representative Concentration Pathway (RCP) scenarios. Ultimately, the goal of the framework is to advise better methods for ensemble averaging models and create better climate predictions.

A performance model for GPUs with caches

DOE PAGES

Dao, Thanh Tuan; Kim, Jungwon; Seo, Sangmin; ...

2014-06-24

To exploit the abundant computational power of the world's fastest supercomputers, an even workload distribution to the typically heterogeneous compute devices is necessary. While relatively accurate performance models exist for conventional CPUs, accurate performance estimation models for modern GPUs do not exist. This paper presents two accurate models for modern GPUs: a sampling-based linear model, and a model based on machine-learning (ML) techniques which improves the accuracy of the linear model and is applicable to modern GPUs with and without caches. We first construct the sampling-based linear model to predict the runtime of an arbitrary OpenCL kernel. Based on anmore » analysis of NVIDIA GPUs' scheduling policies we determine the earliest sampling points that allow an accurate estimation. The linear model cannot capture well the significant effects that memory coalescing or caching as implemented in modern GPUs have on performance. We therefore propose a model based on ML techniques that takes several compiler-generated statistics about the kernel as well as the GPU's hardware performance counters as additional inputs to obtain a more accurate runtime performance estimation for modern GPUs. We demonstrate the effectiveness and broad applicability of the model by applying it to three different NVIDIA GPU architectures and one AMD GPU architecture. On an extensive set of OpenCL benchmarks, on average, the proposed model estimates the runtime performance with less than 7 percent error for a second-generation GTX 280 with no on-chip caches and less than 5 percent for the Fermi-based GTX 580 with hardware caches. On the Kepler-based GTX 680, the linear model has an error of less than 10 percent. On an AMD GPU architecture, Radeon HD 6970, the model estimates with 8 percent of error rates. As a result, the proposed technique outperforms existing models by a factor of 5 to 6 in terms of accuracy.« less

A Multi-layer Dynamic Model for Coordination Based Group Decision Making in Water Resource Allocation and Scheduling

NASA Astrophysics Data System (ADS)

Huang, Wei; Zhang, Xingnan; Li, Chenming; Wang, Jianying

Management of group decision-making is an important issue in water source management development. In order to overcome the defects in lacking of effective communication and cooperation in the existing decision-making models, this paper proposes a multi-layer dynamic model for coordination in water resource allocation and scheduling based group decision making. By introducing the scheme-recognized cooperative satisfaction index and scheme-adjusted rationality index, the proposed model can solve the problem of poor convergence of multi-round decision-making process in water resource allocation and scheduling. Furthermore, the problem about coordination of limited resources-based group decision-making process can be solved based on the effectiveness of distance-based group of conflict resolution. The simulation results show that the proposed model has better convergence than the existing models.

Modeling and experimental study of resistive switching in vertically aligned carbon nanotubes

NASA Astrophysics Data System (ADS)

Ageev, O. A.; Blinov, Yu F.; Ilina, M. V.; Ilin, O. I.; Smirnov, V. A.

2016-08-01

Model of the resistive switching in vertically aligned carbon nanotube (VA CNT) taking into account the processes of deformation, polarization and piezoelectric charge accumulation have been developed. Origin of hysteresis in VA CNT-based structure is described. Based on modeling results the VACNTs-based structure has been created. The ration resistance of high-resistance to low-resistance states of the VACNTs-based structure amounts 48. The correlation the modeling results with experimental studies is shown. The results can be used in the development nanoelectronics devices based on VA CNTs, including the nonvolatile resistive random-access memory.

Internet-based system for simulation-based medical planning for cardiovascular disease.

PubMed

Steele, Brooke N; Draney, Mary T; Ku, Joy P; Taylor, Charles A

2003-06-01

Current practice in vascular surgery utilizes only diagnostic and empirical data to plan treatments, which does not enable quantitative a priori prediction of the outcomes of interventions. We have previously described simulation-based medical planning methods to model blood flow in arteries and plan medical treatments based on physiologic models. An important consideration for the design of these patient-specific modeling systems is the accessibility to physicians with modest computational resources. We describe a simulation-based medical planning environment developed for the World Wide Web (WWW) using the Virtual Reality Modeling Language (VRML) and the Java programming language.

Emulating a System Dynamics Model with Agent-Based Models: A Methodological Case Study in Simulation of Diabetes Progression

DOE PAGES

Schryver, Jack; Nutaro, James; Shankar, Mallikarjun

2015-10-30

An agent-based simulation model hierarchy emulating disease states and behaviors critical to progression of diabetes type 2 was designed and implemented in the DEVS framework. The models are translations of basic elements of an established system dynamics model of diabetes. In this model hierarchy, which mimics diabetes progression over an aggregated U.S. population, was dis-aggregated and reconstructed bottom-up at the individual (agent) level. Four levels of model complexity were defined in order to systematically evaluate which parameters are needed to mimic outputs of the system dynamics model. Moreover, the four estimated models attempted to replicate stock counts representing disease statesmore » in the system dynamics model, while estimating impacts of an elderliness factor, obesity factor and health-related behavioral parameters. Health-related behavior was modeled as a simple realization of the Theory of Planned Behavior, a joint function of individual attitude and diffusion of social norms that spread over each agent s social network. Although the most complex agent-based simulation model contained 31 adjustable parameters, all models were considerably less complex than the system dynamics model which required numerous time series inputs to make its predictions. In all three elaborations of the baseline model provided significantly improved fits to the output of the system dynamics model. The performances of the baseline agent-based model and its extensions illustrate a promising approach to translate complex system dynamics models into agent-based model alternatives that are both conceptually simpler and capable of capturing main effects of complex local agent-agent interactions.« less

Emulating a System Dynamics Model with Agent-Based Models: A Methodological Case Study in Simulation of Diabetes Progression

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

Schryver, Jack; Nutaro, James; Shankar, Mallikarjun

An agent-based simulation model hierarchy emulating disease states and behaviors critical to progression of diabetes type 2 was designed and implemented in the DEVS framework. The models are translations of basic elements of an established system dynamics model of diabetes. In this model hierarchy, which mimics diabetes progression over an aggregated U.S. population, was dis-aggregated and reconstructed bottom-up at the individual (agent) level. Four levels of model complexity were defined in order to systematically evaluate which parameters are needed to mimic outputs of the system dynamics model. Moreover, the four estimated models attempted to replicate stock counts representing disease statesmore » in the system dynamics model, while estimating impacts of an elderliness factor, obesity factor and health-related behavioral parameters. Health-related behavior was modeled as a simple realization of the Theory of Planned Behavior, a joint function of individual attitude and diffusion of social norms that spread over each agent s social network. Although the most complex agent-based simulation model contained 31 adjustable parameters, all models were considerably less complex than the system dynamics model which required numerous time series inputs to make its predictions. In all three elaborations of the baseline model provided significantly improved fits to the output of the system dynamics model. The performances of the baseline agent-based model and its extensions illustrate a promising approach to translate complex system dynamics models into agent-based model alternatives that are both conceptually simpler and capable of capturing main effects of complex local agent-agent interactions.« less

Assessment of Energy Efficient and Model Based Control

DTIC Science & Technology

2017-06-15

ARL-TR-8042 ● JUNE 2017 US Army Research Laboratory Assessment of Energy -Efficient and Model- Based Control by Craig Lennon...originator. ARL-TR-8042 ● JUNE 2017 US Army Research Laboratory Assessment of Energy -Efficient and Model- Based Control by Craig...

The HackensackUMC Value-Based Care Model: Building Essentials for Value-Based Purchasing.

PubMed

Douglas, Claudia; Aroh, Dianne; Colella, Joan; Quadri, Mohammed

2016-01-01

The Affordable Care Act, 2010, and the subsequent shift from a quantity-focus to a value-centric reimbursement model led our organization to create the HackensackUMC Value-Based Care Model to improve our process capability and performance to meet and sustain the triple aims of value-based purchasing: higher quality, lower cost, and consumer perception. This article describes the basics of our model and illustrates how we used it to reduce the costs of our patient sitter program.

FlyBase portals to human disease research using Drosophila models.

PubMed

Millburn, Gillian H; Crosby, Madeline A; Gramates, L Sian; Tweedie, Susan

2016-03-01

The use of Drosophila melanogaster as a model for studying human disease is well established, reflected by the steady increase in both the number and proportion of fly papers describing human disease models in recent years. In this article, we highlight recent efforts to improve the availability and accessibility of the disease model information in FlyBase (http://flybase.org), the model organism database for Drosophila. FlyBase has recently introduced Human Disease Model Reports, each of which presents background information on a specific disease, a tabulation of related disease subtypes, and summaries of experimental data and results using fruit flies. Integrated presentations of relevant data and reagents described in other sections of FlyBase are incorporated into these reports, which are specifically designed to be accessible to non-fly researchers in order to promote collaboration across model organism communities working in translational science. Another key component of disease model information in FlyBase is that data are collected in a consistent format --- using the evolving Disease Ontology (an open-source standardized ontology for human-disease-associated biomedical data) - to allow robust and intuitive searches. To facilitate this, FlyBase has developed a dedicated tool for querying and navigating relevant data, which include mutations that model a disease and any associated interacting modifiers. In this article, we describe how data related to fly models of human disease are presented in individual Gene Reports and in the Human Disease Model Reports. Finally, we discuss search strategies and new query tools that are available to access the disease model data in FlyBase. © 2016. Published by The Company of Biologists Ltd.

Model-Based Economic Evaluation of Treatments for Depression: A Systematic Literature Review.

PubMed

Kolovos, Spyros; Bosmans, Judith E; Riper, Heleen; Chevreul, Karine; Coupé, Veerle M H; van Tulder, Maurits W

2017-09-01

An increasing number of model-based studies that evaluate the cost effectiveness of treatments for depression are being published. These studies have different characteristics and use different simulation methods. We aimed to systematically review model-based studies evaluating the cost effectiveness of treatments for depression and examine which modelling technique is most appropriate for simulating the natural course of depression. The literature search was conducted in the databases PubMed, EMBASE and PsycInfo between 1 January 2002 and 1 October 2016. Studies were eligible if they used a health economic model with quality-adjusted life-years or disability-adjusted life-years as an outcome measure. Data related to various methodological characteristics were extracted from the included studies. The available modelling techniques were evaluated based on 11 predefined criteria. This methodological review included 41 model-based studies, of which 21 used decision trees (DTs), 15 used cohort-based state-transition Markov models (CMMs), two used individual-based state-transition models (ISMs), and three used discrete-event simulation (DES) models. Just over half of the studies (54%) evaluated antidepressants compared with a control condition. The data sources, time horizons, cycle lengths, perspectives adopted and number of health states/events all varied widely between the included studies. DTs scored positively in four of the 11 criteria, CMMs in five, ISMs in six, and DES models in seven. There were substantial methodological differences between the studies. Since the individual history of each patient is important for the prognosis of depression, DES and ISM simulation methods may be more appropriate than the others for a pragmatic representation of the course of depression. However, direct comparisons between the available modelling techniques are necessary to yield firm conclusions.

Model-based segmentation in orbital volume measurement with cone beam computed tomography and evaluation against current concepts.

PubMed

Wagner, Maximilian E H; Gellrich, Nils-Claudius; Friese, Karl-Ingo; Becker, Matthias; Wolter, Franz-Erich; Lichtenstein, Juergen T; Stoetzer, Marcus; Rana, Majeed; Essig, Harald

2016-01-01

Objective determination of the orbital volume is important in the diagnostic process and in evaluating the efficacy of medical and/or surgical treatment of orbital diseases. Tools designed to measure orbital volume with computed tomography (CT) often cannot be used with cone beam CT (CBCT) because of inferior tissue representation, although CBCT has the benefit of greater availability and lower patient radiation exposure. Therefore, a model-based segmentation technique is presented as a new method for measuring orbital volume and compared to alternative techniques. Both eyes from thirty subjects with no known orbital pathology who had undergone CBCT as a part of routine care were evaluated (n = 60 eyes). Orbital volume was measured with manual, atlas-based, and model-based segmentation methods. Volume measurements, volume determination time, and usability were compared between the three methods. Differences in means were tested for statistical significance using two-tailed Student's t tests. Neither atlas-based (26.63 ± 3.15 mm(3)) nor model-based (26.87 ± 2.99 mm(3)) measurements were significantly different from manual volume measurements (26.65 ± 4.0 mm(3)). However, the time required to determine orbital volume was significantly longer for manual measurements (10.24 ± 1.21 min) than for atlas-based (6.96 ± 2.62 min, p < 0.001) or model-based (5.73 ± 1.12 min, p < 0.001) measurements. All three orbital volume measurement methods examined can accurately measure orbital volume, although atlas-based and model-based methods seem to be more user-friendly and less time-consuming. The new model-based technique achieves fully automated segmentation results, whereas all atlas-based segmentations at least required manipulations to the anterior closing. Additionally, model-based segmentation can provide reliable orbital volume measurements when CT image quality is poor.

A Classification Model and an Open E-Learning System Based on Intuitionistic Fuzzy Sets for Instructional Design Concepts

ERIC Educational Resources Information Center

Güyer, Tolga; Aydogdu, Seyhmus

2016-01-01

This study suggests a classification model and an e-learning system based on this model for all instructional theories, approaches, models, strategies, methods, and technics being used in the process of instructional design that constitutes a direct or indirect resource for educational technology based on the theory of intuitionistic fuzzy sets…

The Application of FIA-based Data to Wildlife Habitat Modeling: A Comparative Study

Treesearch

Thomas C., Jr. Edwards; Gretchen G. Moisen; Tracey S. Frescino; Randall J. Schultz

2005-01-01

We evaluated the capability of two types of models, one based on spatially explicit variables derived from FIA data and one using so-called traditional habitat evaluation methods, for predicting the presence of cavity-nesting bird habitat in Fishlake National Forest, Utah. Both models performed equally well, in measures of predictive accuracy, with the FIA-based model...

Continuum Fatigue Damage Modeling for Use in Life Extending Control

NASA Technical Reports Server (NTRS)

Lorenzo, Carl F.

1994-01-01

This paper develops a simplified continuum (continuous wrp to time, stress, etc.) fatigue damage model for use in Life Extending Controls (LEC) studies. The work is based on zero mean stress local strain cyclic damage modeling. New nonlinear explicit equation forms of cyclic damage in terms of stress amplitude are derived to facilitate the continuum modeling. Stress based continuum models are derived. Extension to plastic strain-strain rate models are also presented. Application of these models to LEC applications is considered. Progress toward a nonzero mean stress based continuum model is presented. Also, new nonlinear explicit equation forms in terms of stress amplitude are also derived for this case.

Vehicle-specific emissions modeling based upon on-road measurements.

PubMed

Frey, H Christopher; Zhang, Kaishan; Rouphail, Nagui M

2010-05-01

Vehicle-specific microscale fuel use and emissions rate models are developed based upon real-world hot-stabilized tailpipe measurements made using a portable emissions measurement system. Consecutive averaging periods of one to three multiples of the response time are used to compare two semiempirical physically based modeling schemes. One scheme is based on internally observable variables (IOVs), such as engine speed and manifold absolute pressure, while the other is based on externally observable variables (EOVs), such as speed, acceleration, and road grade. For NO, HC, and CO emission rates, the average R(2) ranged from 0.41 to 0.66 for the former and from 0.17 to 0.30 for the latter. The EOV models have R(2) for CO(2) of 0.43 to 0.79 versus 0.99 for the IOV models. The models are sensitive to episodic events in driving cycles such as high acceleration. Intervehicle and fleet average modeling approaches are compared; the former account for microscale variations that might be useful for some types of assessments. EOV-based models have practical value for traffic management or simulation applications since IOVs usually are not available or not used for emission estimation.

The effects of geometric uncertainties on computational modelling of knee biomechanics

PubMed Central

Fisher, John; Wilcox, Ruth

2017-01-01

The geometry of the articular components of the knee is an important factor in predicting joint mechanics in computational models. There are a number of uncertainties in the definition of the geometry of cartilage and meniscus, and evaluating the effects of these uncertainties is fundamental to understanding the level of reliability of the models. In this study, the sensitivity of knee mechanics to geometric uncertainties was investigated by comparing polynomial-based and image-based knee models and varying the size of meniscus. The results suggested that the geometric uncertainties in cartilage and meniscus resulting from the resolution of MRI and the accuracy of segmentation caused considerable effects on the predicted knee mechanics. Moreover, even if the mathematical geometric descriptors can be very close to the imaged-based articular surfaces, the detailed contact pressure distribution produced by the mathematical geometric descriptors was not the same as that of the image-based model. However, the trends predicted by the models based on mathematical geometric descriptors were similar to those of the imaged-based models. PMID:28879008

A Copula-Based Conditional Probabilistic Forecast Model for Wind Power Ramps

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

Hodge, Brian S; Krishnan, Venkat K; Zhang, Jie

Efficient management of wind ramping characteristics can significantly reduce wind integration costs for balancing authorities. By considering the stochastic dependence of wind power ramp (WPR) features, this paper develops a conditional probabilistic wind power ramp forecast (cp-WPRF) model based on Copula theory. The WPRs dataset is constructed by extracting ramps from a large dataset of historical wind power. Each WPR feature (e.g., rate, magnitude, duration, and start-time) is separately forecasted by considering the coupling effects among different ramp features. To accurately model the marginal distributions with a copula, a Gaussian mixture model (GMM) is adopted to characterize the WPR uncertaintymore » and features. The Canonical Maximum Likelihood (CML) method is used to estimate parameters of the multivariable copula. The optimal copula model is chosen based on the Bayesian information criterion (BIC) from each copula family. Finally, the best conditions based cp-WPRF model is determined by predictive interval (PI) based evaluation metrics. Numerical simulations on publicly available wind power data show that the developed copula-based cp-WPRF model can predict WPRs with a high level of reliability and sharpness.« less

The implementation of multiple intelligences based teaching model to improve mathematical problem solving ability for student of junior high school

NASA Astrophysics Data System (ADS)

Fasni, Nurli; Fatimah, Siti; Yulanda, Syerli

2017-05-01

This research aims to achieve some purposes such as: to know whether mathematical problem solving ability of students who have learned mathematics using Multiple Intelligences based teaching model is higher than the student who have learned mathematics using cooperative learning; to know the improvement of the mathematical problem solving ability of the student who have learned mathematics using Multiple Intelligences based teaching model., to know the improvement of the mathematical problem solving ability of the student who have learned mathematics using cooperative learning; to know the attitude of the students to Multiple Intelligences based teaching model. The method employed here is quasi-experiment which is controlled by pre-test and post-test. The population of this research is all of VII grade in SMP Negeri 14 Bandung even-term 2013/2014, later on two classes of it were taken for the samples of this research. A class was taught using Multiple Intelligences based teaching model and the other one was taught using cooperative learning. The data of this research were gotten from the test in mathematical problem solving, scale questionnaire of the student attitudes, and observation. The results show the mathematical problem solving of the students who have learned mathematics using Multiple Intelligences based teaching model learning is higher than the student who have learned mathematics using cooperative learning, the mathematical problem solving ability of the student who have learned mathematics using cooperative learning and Multiple Intelligences based teaching model are in intermediate level, and the students showed the positive attitude in learning mathematics using Multiple Intelligences based teaching model. As for the recommendation for next author, Multiple Intelligences based teaching model can be tested on other subject and other ability.

Comparison of a Conceptual Groundwater Model and Physically Based Groundwater Mode

NASA Astrophysics Data System (ADS)

Yang, J.; Zammit, C.; Griffiths, J.; Moore, C.; Woods, R. A.

2017-12-01

Groundwater is a vital resource for human activities including agricultural practice and urban water demand. Hydrologic modelling is an important way to study groundwater recharge, movement and discharge, and its response to both human activity and climate change. To understand the groundwater hydrologic processes nationally in New Zealand, we have developed a conceptually based groundwater flow model, which is fully integrated into a national surface-water model (TopNet), and able to simulate groundwater recharge, movement, and interaction with surface water. To demonstrate the capability of this groundwater model (TopNet-GW), we applied the model to an irrigated area with water shortage and pollution problems in the upper Ruamahanga catchment in Great Wellington Region, New Zealand, and compared its performance with a physically-based groundwater model (MODFLOW). The comparison includes river flow at flow gauging sites, and interaction between groundwater and river. Results showed that the TopNet-GW produced similar flow and groundwater interaction patterns as the MODFLOW model, but took less computation time. This shows the conceptually-based groundwater model has the potential to simulate national groundwater process, and could be used as a surrogate for the more physically based model.

Search-based model identification of smart-structure damage

NASA Technical Reports Server (NTRS)

Glass, B. J.; Macalou, A.

1991-01-01

This paper describes the use of a combined model and parameter identification approach, based on modal analysis and artificial intelligence (AI) techniques, for identifying damage or flaws in a rotating truss structure incorporating embedded piezoceramic sensors. This smart structure example is representative of a class of structures commonly found in aerospace systems and next generation space structures. Artificial intelligence techniques of classification, heuristic search, and an object-oriented knowledge base are used in an AI-based model identification approach. A finite model space is classified into a search tree, over which a variant of best-first search is used to identify the model whose stored response most closely matches that of the input. Newly-encountered models can be incorporated into the model space. This adaptativeness demonstrates the potential for learning control. Following this output-error model identification, numerical parameter identification is used to further refine the identified model. Given the rotating truss example in this paper, noisy data corresponding to various damage configurations are input to both this approach and a conventional parameter identification method. The combination of the AI-based model identification with parameter identification is shown to lead to smaller parameter corrections than required by the use of parameter identification alone.

Feature-based data assimilation in geophysics

NASA Astrophysics Data System (ADS)

Morzfeld, Matthias; Adams, Jesse; Lunderman, Spencer; Orozco, Rafael

2018-05-01

Many applications in science require that computational models and data be combined. In a Bayesian framework, this is usually done by defining likelihoods based on the mismatch of model outputs and data. However, matching model outputs and data in this way can be unnecessary or impossible. For example, using large amounts of steady state data is unnecessary because these data are redundant. It is numerically difficult to assimilate data in chaotic systems. It is often impossible to assimilate data of a complex system into a low-dimensional model. As a specific example, consider a low-dimensional stochastic model for the dipole of the Earth's magnetic field, while other field components are ignored in the model. The above issues can be addressed by selecting features of the data, and defining likelihoods based on the features, rather than by the usual mismatch of model output and data. Our goal is to contribute to a fundamental understanding of such a feature-based approach that allows us to assimilate selected aspects of data into models. We also explain how the feature-based approach can be interpreted as a method for reducing an effective dimension and derive new noise models, based on perturbed observations, that lead to computationally efficient solutions. Numerical implementations of our ideas are illustrated in four examples.

Integration agent-based models and GIS as a virtual urban dynamic laboratory

NASA Astrophysics Data System (ADS)

Chen, Peng; Liu, Miaolong

2007-06-01

Based on the Agent-based Model and spatial data model, a tight-coupling integrating method of GIS and Agent-based Model (ABM) is to be discussed in this paper. The use of object-orientation for both spatial data and spatial process models facilitates their integration, which can allow exploration and explanation of spatial-temporal phenomena such as urban dynamic. In order to better understand how tight coupling might proceed and to evaluate the possible functional and efficiency gains from such a tight coupling, the agent-based model and spatial data model are discussed, and then the relationships affecting spatial data model and agent-based process models interaction. After that, a realistic crowd flow simulation experiment is presented. Using some tools provided by general GIS systems and a few specific programming languages, a new software system integrating GIS and MAS as a virtual laboratory applicable for simulating pedestrian flows in a crowd activity centre has been developed successfully. Under the environment supported by the software system, as an applicable case, a dynamic evolution process of the pedestrian's flows (dispersed process for the spectators) in a crowds' activity center - The Shanghai Stadium has been simulated successfully. At the end of the paper, some new research problems have been pointed out for the future.

Toward On-line Parameter Estimation of Concentric Tube Robots Using a Mechanics-based Kinematic Model

PubMed Central

Jang, Cheongjae; Ha, Junhyoung; Dupont, Pierre E.; Park, Frank Chongwoo

2017-01-01

Although existing mechanics-based models of concentric tube robots have been experimentally demonstrated to approximate the actual kinematics, determining accurate estimates of model parameters remains difficult due to the complex relationship between the parameters and available measurements. Further, because the mechanics-based models neglect some phenomena like friction, nonlinear elasticity, and cross section deformation, it is also not clear if model error is due to model simplification or to parameter estimation errors. The parameters of the superelastic materials used in these robots can be slowly time-varying, necessitating periodic re-estimation. This paper proposes a method for estimating the mechanics-based model parameters using an extended Kalman filter as a step toward on-line parameter estimation. Our methodology is validated through both simulation and experiments. PMID:28717554

Gradient-based model calibration with proxy-model assistance

NASA Astrophysics Data System (ADS)

Burrows, Wesley; Doherty, John

2016-02-01

Use of a proxy model in gradient-based calibration and uncertainty analysis of a complex groundwater model with large run times and problematic numerical behaviour is described. The methodology is general, and can be used with models of all types. The proxy model is based on a series of analytical functions that link all model outputs used in the calibration process to all parameters requiring estimation. In enforcing history-matching constraints during the calibration and post-calibration uncertainty analysis processes, the proxy model is run for the purposes of populating the Jacobian matrix, while the original model is run when testing parameter upgrades; the latter process is readily parallelized. Use of a proxy model in this fashion dramatically reduces the computational burden of complex model calibration and uncertainty analysis. At the same time, the effect of model numerical misbehaviour on calculation of local gradients is mitigated, this allowing access to the benefits of gradient-based analysis where lack of integrity in finite-difference derivatives calculation would otherwise have impeded such access. Construction of a proxy model, and its subsequent use in calibration of a complex model, and in analysing the uncertainties of predictions made by that model, is implemented in the PEST suite.

Development and verification of an agent-based model of opinion leadership.

PubMed

Anderson, Christine A; Titler, Marita G

2014-09-27

The use of opinion leaders is a strategy used to speed the process of translating research into practice. Much is still unknown about opinion leader attributes and activities and the context in which they are most effective. Agent-based modeling is a methodological tool that enables demonstration of the interactive and dynamic effects of individuals and their behaviors on other individuals in the environment. The purpose of this study was to develop and test an agent-based model of opinion leadership. The details of the design and verification of the model are presented. The agent-based model was developed by using a software development platform to translate an underlying conceptual model of opinion leadership into a computer model. Individual agent attributes (for example, motives and credibility) and behaviors (seeking or providing an opinion) were specified as variables in the model in the context of a fictitious patient care unit. The verification process was designed to test whether or not the agent-based model was capable of reproducing the conditions of the preliminary conceptual model. The verification methods included iterative programmatic testing ('debugging') and exploratory analysis of simulated data obtained from execution of the model. The simulation tests included a parameter sweep, in which the model input variables were adjusted systematically followed by an individual time series experiment. Statistical analysis of model output for the 288 possible simulation scenarios in the parameter sweep revealed that the agent-based model was performing, consistent with the posited relationships in the underlying model. Nurse opinion leaders act on the strength of their beliefs and as a result, become an opinion resource for their uncertain colleagues, depending on their perceived credibility. Over time, some nurses consistently act as this type of resource and have the potential to emerge as opinion leaders in a context where uncertainty exists. The development and testing of agent-based models is an iterative process. The opinion leader model presented here provides a basic structure for continued model development, ongoing verification, and the establishment of validation procedures, including empirical data collection.