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BACKGROUND: Globally, type-2 diabetes mellitus is increasing in epidemic proportions. A major cause of concern in India is the increasing incidence of cases, especially troubling is the observed increase in younger age groups with no risk factors. New evidence suggests that many environmental factors, such as air pollution, persistent organic pollutants (POPs), and environmental estrogens are implicated as risk factors for type-2 diabetes mellitus. Animal and human epidemiological studies have shown ubiquitous lipophilic substances, including POPs, are frequently associated with type-2 diabetes mellitus. Such studies have not been undertaken in Indian youth. METHODS: This is a cross-sectional study that explored the association between POPs and type-2 diabetes mellitus in Indian urban and rural population. About 7 ml of venous blood was collected from all consenting patients and serum was separated immediately and was transported to the lab for further analysis. Serum levels of POPs, including organochlorine (OC) compounds and organophosphorus pesticides, were estimated using sample gas chromatography-mass spectrometry (GC-MS). The fasting blood sugar values and the serum levels of POPS were tested using Pearson correlation coefficient. The magnitude of increase in blood sugar corresponding to increase in POPs was analyzed using linear regression analysis. The odds ratios (ORs) were expressed at 95% confidence intervals (CIs). RESULTS: Three OC pesticides and one organophosphate pesticide were strongly associated with increasing blood sugar levels after adjusting for age, sex, and body mass index - lindane (OR 4.95, 95% CI 1.03-23.73), DDT o, p' (OR 3.50, 95% CI 1.04-11.73), dimethoate (OR 19.31, 95% CI 4.22-88.37), and dichlorvas (OR 6.33, 95% CI 1.28-31.18).
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In 2017, Tamil Nadu, a southern state, had the second highest number of dengue cases from India. In the present study, the serotype-specific differences in the clinical manifestations and laboratory parameters among hospitalized children with dengue were investigated and molecular characterization of the circulating dengue virus (DENV) serotypes during 2017 in Tamil Nadu was performed. Eighty children with dengue-like symptoms consecutively admitted to a tertiary care hospital and positive for DENV NS1 antigen were investigated for DENV serotype utilizing a real-time reverse transcriptase based polymerase chain reaction assay. Complete envelope (E) gene sequencing of the DENV strains was performed. Seventy samples were positive for serotyping (25 DENV-1, 17 DENV-2, six DENV-3, and 22 DENV-4). DENV-4 infections were associated with elevated levels of liver enzymes; Alanine aminotransferase (P = .021) and aspartate aminotransferase (P = .001). However, none of the serotype was associated with any specific clinical features and severe dengue. Asian and American/African genotypes of DENV-1 were cocirculating. The circulating genotype was cosmopolitan for DENV-2 with multiple lineages, genotype III for DENV-3 and genotype I for DENV-4. Unique mutations were present in the 2017 DENV-4 isolates. The present study suggests the association of DENV-4 with elevated liver enzymes in children hospitalized for dengue. Further, the study reports the genetic diversity of DENV circulating in Tamil Nadu during 2017. The study calls for continuous monitoring of the circulating serotypes and genotypes at regional level in India which might result in a region wise database useful in predicting future outbreaks.
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Virus del Dengue/clasificación , Virus del Dengue/genética , Dengue/virología , Variación Genética , Adolescente , Alanina Transaminasa/metabolismo , Aspartato Aminotransferasas/metabolismo , Niño , Preescolar , Estudios Transversales , Dengue/sangre , Dengue/epidemiología , Virus del Dengue/aislamiento & purificación , Femenino , Genotipo , Hospitalización , Humanos , India/epidemiología , Lactante , Hígado/enzimología , Masculino , Filogenia , Estudios Prospectivos , Serotipificación , Dengue Grave/epidemiología , Dengue Grave/virología , Índice de Severidad de la EnfermedadRESUMEN
BACKGROUND: Essential events of cell development and homeostasis are revealed by the associated changes of cell morphology and therefore have been widely used as a key indicator of physiological states and molecular pathways affecting various cellular functions via cytoskeleton. Cell motility is a complex phenomenon primarily driven by the actin network, which plays an important role in shaping the morphology of the cells. Most of the morphology based features are approximated from cell periphery but its dynamics have received none to scant attention. We aim to bridge the gap between membrane dynamics and cell states from the perspective of whole cell movement by identifying cell edge patterns and its correlation with cell dynamics. RESULTS: We present a systematic study to extract, classify, and compare cell dynamics in terms of cell motility and edge activity. Cell motility features extracted by fitting a persistent random walk were used to identify the initial set of cell subpopulations. We propose algorithms to extract edge features along the entire cell periphery such as protrusion and retraction velocity. These constitute a unique set of multivariate time-lapse edge features that are then used to profile subclasses of cell dynamics by unsupervised clustering. CONCLUSIONS: By comparing membrane dynamic patterns exhibited by each subclass of cells, correlated trends of edge and cell movements were identified. Our findings are consistent with published literature and we also identified that motility patterns are influenced by edge features from initial time points compared to later sampling intervals.
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Membrana Celular/metabolismo , Movimiento Celular , Actinas/metabolismo , Actinas/fisiología , Animales , Línea Celular , Citoesqueleto/metabolismo , Macrófagos/citología , Macrófagos/metabolismo , Ratones , Microtúbulos/metabolismoRESUMEN
BACKGROUND: High content screening techniques are increasingly used to understand the regulation and progression of cell motility. The demand of new platforms, coupled with availability of terabytes of data has challenged the traditional technique of identifying cell populations by manual methods and resulted in development of high-dimensional analytical methods. RESULTS: In this paper, we present sub-populations analysis of cells at the tissue level by using dynamic features of the cells. We used active contour without edges for segmentation of cells, which preserves the cell morphology, and autoregressive modeling to model cell trajectories. The sub-populations were obtained by clustering static, dynamic and a combination of both features. We were able to identify three unique sub-populations in combined clustering. CONCLUSION: We report a novel method to identify sub-populations using kinetic features and demonstrate that these features improve sub-population analysis at the tissue level. These advances will facilitate the application of high content screening data analysis to new and complex biological problems.
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Movimiento Celular/fisiología , Biología Computacional/métodos , Macrófagos/citología , Animales , Células/citología , Células Cultivadas , Macrófagos/metabolismo , Ratones , Reconocimiento de Normas Patrones AutomatizadasRESUMEN
We introduce a tool for text mining, Dragon Plant Biology Explorer (DPBE) that integrates information on Arabidopsis (Arabidopsis thaliana) genes with their functions, based on gene ontologies and biochemical entity vocabularies, and presents the associations as interactive networks. The associations are based on (1) user-provided PubMed abstracts; (2) a list of Arabidopsis genes compiled by The Arabidopsis Information Resource; (3) user-defined combinations of four vocabulary lists based on the ones developed by the general, plant, and Arabidopsis GO consortia; and (4) three lists developed here based on metabolic pathways, enzymes, and metabolites derived from AraCyc, BRENDA, and other metabolism databases. We demonstrate how various combinations can be applied to fields of (1) gene function and gene interaction analyses, (2) plant development, (3) biochemistry and metabolism, and (4) pharmacology of bioactive compounds. Furthermore, we show the suitability of DPBE for systems approaches by integration with "omics" platform outputs. Using a list of abiotic stress-related genes identified by microarray experiments, we show how this tool can be used to rapidly build an information base on the previously reported relationships. This tool complements the existing biological resources for systems biology by identifying potentially novel associations using text analysis between cellular entities based on genome annotation terms. Thus, it allows researchers to efficiently summarize existing information for a group of genes or pathways, so as to make better informed choices for designing validation experiments. Last, DPBE can be helpful for beginning researchers and graduate students to summarize vast information in an unfamiliar area. DPBE is freely available for academic and nonprofit users at http://research.i2r.a-star.edu.sg/DRAGON/ME2/.