9 research outputs found
NetPath: a public resource of curated signal transduction pathways
NetPath, a novel community resource of curated human signaling pathways is presented and its utility demonstrated using immune signaling data
Clinico-Epidemiological Profile of COVID-19 Patients with Omicron Variant Admitted in a Tertiary Care Center, South India
Theranirajan Ethirajan,1,* Gopalakrishnan Natarajan,2,* Rajendran Velayudham,3,* Pavithra Jayakumaran,4 Indumathi Karnan,1 Karthick Rajendran,5 Sudhakaran Doraisamy,6 Sripriya Chenakeswarar Sridhar,7 Purushoth Kumaran,1 Kabilan Kamaraj,1 Anuradha Kandasamy,7 Murugan Natarajan8 1Madras Medical College, Chennai, India; 2Institute of Nephrology, Madras Medical College, Chennai, India; 3Institute of Internal Medicine, Madras Medical College, Chennai, India; 4Institute of Pathology, Madras Medical College, Chennai, India; 5Multidisciplinary Research Unit (MRU), Madras Medical College, Chennai, India; 6Critical Care Medicine, Madras Medical College, Chennai, India; 7Viral Research and Diagnostic Laboratory, Madras Medical College, Chennai, India; 8Institute of Thoracic Medicine, Madras Medical College, Chennai, India*These authors contributed equally to this workCorrespondence: Murugan Natarajan, Institute of Thoracic Medicine, Madras Medical College and Rajiv Gandhi Government General Hospital, Chennai, Tamil Nadu, 600003, India, Email [email protected] and Objectives: Omicron, a variant of SARS COV2, is looming large as a cause of global concern. Its high transmissibility can pose challenges in healthcare allocation in a highly populous country like India. Studying the behaviour of the virus among the Indian population will definitely help in planning for the impending omicron surge, so we conducted a preliminary analysis of the clinical and epidemiological characteristics of the suspected omicron cases in the early part of the surge.Methodology: The study was conducted in the Rajiv Gandhi Government General Hospital, from 17th December 2021 to 11th January 2022. A total number of 159 consecutive patients ≥ 18 years of age with the S gene target failure were enrolled and clinically followed up during hospitalisation.Results: Nearly half (n = 79, 49.7%) were aged between 18 and 30 years and the mean (SD) age of the patients was 35.1 (14.9); 52.8% (n = 84) were males and 54.7% (n = 87) were healthcare workers. The NLR ratio and CRP were raised in unvaccinated individuals. Out of 159 patients, only 4 patients required oxygen and all the others showed a mild course of illness and there was no mortality.Conclusion: The clinical course of suspected omicron patients was mild in those who were vaccinated. Unvaccinated individuals with comorbid illness need to be closely monitored for prompt referral for acute care. Further studies are needed in the high-risk group with omicron.Keywords: COVID-19, coronavirus, SARS-CoV-2, omicron, variant of concern, S gene target failur
Hydromagnetic forced convective flow of Carreau nanofluid over a wedge/plate/stagnation of the plate
SILAC-based quantitative proteomic approach to identify potential biomarkers from the esophageal squamous cell carcinoma secretome
The identification of secreted proteins that are differentially expressed between non-neoplastic and esophageal squamous cell carcinoma (ESCC) cells can provide potential biomarkers of ESCC. We used a SILAC-based quantitative proteomic approach to compare the secretome of ESCC cells with that of non-neoplastic esophageal squamous epithelial cells. Proteins were resolved by SDS-PAGE and tandem mass spectrometry analysis (LC-MS/MS) of in-gel trypsindigested peptides was carried out on a high-accuracy qTOF mass spectrometer. In total, we identified 441 proteins in the combined secretomes, including 120 proteins with ≥ 2-fold upregulation in the ESCC secretome vs. that of non-neoplastic esophageal squamous epithelial cells. In this study, several potential protein biomarkers previously known to be increased in ESCC including matrix metalloproteinase 1, transferrin receptor and transforming growth factor beta-induced 68 kDa were identified as overexpressed in the ESCC-derived secretome. In addition, we identified several novel proteins that have not been previously reported to be associated with ESCC. Among the novel candidate proteins identified, protein disulfide isomerase family a member 3 (PDIA3), GDP dissociation inhibitor 2 (GDI2) and lectin galactoside binding soluble 3 binding protein (LGALS3BP) were further validated by immunoblot analysis and immunohistochemical labeling using tissue microarrays. This tissue microarray analysis showed overexpression of protein disulfide isomerase family a member 3, GDP dissociation inhibitor 2 and lectin galactoside binding soluble 3 binding protein in 93, 93 and 87% of 137 ESCC cases, respectively. Hence, we conclude that these potential biomarkers are excellent candidates for further evaluation to test their role and efficacy in the early detection of ESCC
Effects of partial slip on chemically reactive solute transfer in the boundary layer flow over an exponentially stretching sheet with suction/blowing
The biopax community standard for pathway data sharing
BioPAX (Biological Pathway Exchange) is a standard language to represent biological pathways at the molecular and cellular level. Its major use is to facilitate the exchange of pathway data (http://www.biopax.org). Pathway data captures our understanding of biological processes, but its rapid growth necessitates development of databases and computational tools to aid interpretation. However, the current fragmentation of pathway information across many databases with incompatible formats presents barriers to its effective use. BioPAX solves this problem by making pathway data substantially easier to collect, index, interpret and share. BioPAX can represent metabolic and signaling pathways, molecular and genetic interactions and gene regulation networks. BioPAX was created through a community process. Through BioPAX, millions of interactions organized into thousands of pathways across many organisms, from a growing number of sources, are available. Thus, large amounts of pathway data are available in a computable form to support visualization, analysis and biological discovery