CytoSolve: A Scalable Computational Method for Dynamic Integration of Multiple Molecular Pathway Models

A grand challenge of computational systems biology is to create a molecular pathway model of the whole cell. Current approaches involve merging smaller molecular pathway models’ source codes to create a large monolithic model (computer program) that runs on a single computer. Such a larger model is difficult, if not impossible, to maintain given ongoing updates to the source codes of the smaller models. This paper describes a new system called CytoSolve that dynamically integrates computations of smaller models that can run in parallel across different machines without the need to merge the source codes of the individual models. This approach is demonstrated on the classic Epidermal Growth Factor Receptor (EGFR) model of Kholodenko. The EGFR model is split into four smaller models and each smaller model is distributed on a different machine. Results from four smaller models are dynamically integrated to generate identical results to the monolithic EGFR model running on a single machine. The overhead for parallel and dynamic computation is approximately twice that of a monolithic model running on a single machine. The CytoSolve approach provides a scalable method since smaller models may reside on any computer worldwide, where the source code of each model can be independently maintained and updated

Intense violet–blue emission and paramagnetism of nanocrystalline Gd3+ doped ZnO ceramics

Nanocrystalline Zn1-xGdxO (x = 0, 0.02, 0.04, 0.06, and 0.08) ceramics were synthesized by ball milling and subsequent solid-state reaction. The transmission electron microscopy (TEM) micrograph of as synthesized samples revealed the formation of crystallites with an average diameter of 60 nm, and the selected area electron diffraction (SAED) pattern confirmed the formation of wurtzite structure. A red shift in the band gap was observed with increasing Gd3+ concentration. The photoluminescence of nanocrystalline Gd3+ doped ZnO exhibited a strong violet–blue emission. Concentration dependence of the emission intensity of Gd3+ in ZnO was studied, and the critical concentration was found to be 4 mol% of Gd3+. The Gd3+ doped ZnO exhibited paramagnetic behavior at room temperature, and the magnetic moment increased with Gd3+ concentration

Proton-Assisted Amino Acid Transporter PAT1 Complexes with Rag GTPases and Activates TORC1 on Late Endosomal and Lysosomal Membranes

Mammalian Target of Rapamycin Complex 1 (mTORC1) is activated by growth factor-regulated phosphoinositide 3-kinase (PI3K)/Akt/Rheb signalling and extracellular amino acids (AAs) to promote growth and proliferation. These AAs induce translocation of mTOR to late endosomes and lysosomes (LELs), subsequent activation via mechanisms involving the presence of intralumenal AAs, and interaction between mTORC1 and a multiprotein assembly containing Rag GTPases and the heterotrimeric Ragulator complex. However, the mechanisms by which AAs control these different aspects of mTORC1 activation are not well understood. We have recently shown that intracellular Proton-assisted Amino acid Transporter 1 (PAT1)/SLC36A1 is an essential mediator of AA-dependent mTORC1 activation. Here we demonstrate in Human Embryonic Kidney (HEK-293) cells that PAT1 is primarily located on LELs, physically interacts with the Rag GTPases and is required for normal AA-dependent mTOR relocalisation. We also use the powerful in vivo genetic methodologies available in Drosophila to investigate the regulation of the PAT1/Rag/Ragulator complex. We show that GFP-tagged PATs reside at both the cell surface and LELs in vivo, mirroring PAT1 distribution in several normal mammalian cell types. Elevated PI3K/Akt/Rheb signalling increases intracellular levels of PATs and synergistically enhances PAT-induced growth via a mechanism requiring endocytosis. In light of the recent identification of the vacuolar H+-ATPase as another Rag-interacting component, we propose a model in which PATs function as part of an AA-sensing engine that drives mTORC1 activation from LEL compartments

One-year clinical outcome of patients with nonvalvular atrial fibrillation: Insights from KERALA-AF registry.

BackgroundWe report patient characteristics, treatment pattern and one-year clinical outcome of nonvalvular atrial fibrillation (NVAF) from Kerala, India. This cohort forms part of Kerala Atrial Fibrillation (KERALA-AF) registry which is an ongoing large prospective study.MethodsKERALA-AF registry collected data of adults with previously or newly diagnosed atrial fibrillation (AF) during April 2016 to April 2017. A total of 3421 patients were recruited from 53 hospitals across Kerala state. We analysed one-year follow-up outcome of 2507 patients with NVAF.ResultsMean age at recruitment was 67.2 years (range 18-98) and 54.8% were males. Main co-morbidities were hypertension (61.2%), hyperlipidaemia (46.2%) and diabetes mellitus (37.2%). Major co-existing diseases were chronic kidney disease (42.1%), coronary artery disease (41.6%), and chronic heart failure (26.4%). Mean CHA2DS2-VASc score was 3.18 (SD ± 1.7) and HAS-BLED score, 1.84 (SD ± 1.3). At baseline, use of oral anticoagulants (OAC) was 38.6% and antiplatelets 32.7%. On one-month follow-up use of OAC increased to 65.8% and antiplatelets to 48.3%. One-year all-cause mortality was 16.48 and hospitalization 20.65 per 100 person years. The main causes of death were cardiovascular (75.0%), stroke (13.1%) and others (11.9%). The major causes of hospitalizations were acute coronary syndrome (35.0%), followed by arrhythmia (29.5%) and heart failure (8.4%).ConclusionsDespite high risk profile of patients in this registry, use of OAC was suboptimal, whereas antiplatelets were used in nearly half of patients. A relatively high rate of annual mortality and hospitalization was observed in patients with NVAF in Kerala AF Registry

Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability

The spatial scaling of species interaction networks

International audienceSpecies-area relationships (SARs) are pivotal to understand the distribution of biodiversity across spatial scales. We know little, however, about how the network of biotic interactions in which biodiversity is embedded changes with spatial extent. Here we develop a new theoretical framework that enables us to explore how different assembly mechanisms and theoretical models affect multiple properties of ecological networks across space. We present a number of testable predictions on network-area relationships (NARs) for multi-trophic communities. Network structure changes as area increases because of the existence of different SARs across trophic levels, the preferential selection of generalist species at small spatial extents and the effect of dispersal limitation promoting beta-diversity. Developing an understanding of NARs will complement the growing body of knowledge on SARs with potential applications in conservation ecology. Specifically, combined with further empirical evidence, NARs can generate predictions of potential effects on ecological communities of habitat loss and fragmentation in a changing world

The Gene Ontology: enhancements for 2011

The Gene Ontology (GO) (http://www.geneontology.org) is a community bioinformatics resource that represents gene product function through the use of structured, controlled vocabularies. The number of GO annotations of gene products has increased due to curation efforts among GO Consortium (GOC) groups, including focused literature-based annotation and ortholog-based functional inference. The GO ontologies continue to expand and improve as a result of targeted ontology development, including the introduction of computable logical definitions and development of new tools for the streamlined addition of terms to the ontology. The GOC continues to support its user community through the use of e-mail lists, social media and web-based resources