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Background: During the initial phase of the COVID-19 pandemic, the Government of India implemented a nationwide lockdown, sealing borders across states and districts. The northeastern region of India, surrounded by three international borders and connected to mainland India by a narrow passage, faced particular isolation. This isolation resulted in these states forming a relatively closed population. Consequently, the availability of population-based data from Indian Council of Medical Research, tracked through national identification cards, offered a distinctive opportunity to understand the spread of the virus among non-vaccinated and non-exposed populations. This research leverages this dataset to comprehend the repercussions within isolated populations. Methods: The inter-district variability was visualized using geospatial analysis. The patterns do not follow any established grounded theories on disease spread. Out of 7.1 million total data weekly 0.35 million COVID-19-positive northeast data was taken from April 2020 to February 2021 including "date, test result, population density, area, latitude, longitude, district, and state" to identify the spread pattern using a modified reaction-diffusion model (MRD-Model) and Geographic Information System. Findings: The analysis of the closed population group revealed an initial uneven yet rapidly expanding geographical spread characterized by a high diffusion rate α approximately 0.4503 and a lower reaction rate ß approximately 0.0256, which indicated a slower growth trajectory of case numbers rather than exponential escalation. In the latter stages, COVID-19 incidence reached zero in numerous districts, while in others, the reported cases did not exceed 100. Interpretation: The MRD-Model effectively captured the disease transmission dynamics in the abovementioned setting. This enhanced understanding of COVID-19 spread in remote, isolated regions provided by the MRD modelling framework can guide targeted public health strategies for similar isolated areas. Funding: This study is Funded by Indian Council of Medical Research (ICMR).
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Autonomic dysfunction is associated with cardiovascular and neurological disease, including hypertension, heart failure, anxiety, and stress-related disorders. Prior studies demonstrated that late gestation exposure to dexamethasone (DEX) resulted in female-biased increases in stress-responsive mean arterial pressure (MAP) and heart rate (HR), suggesting a role for glucocorticoid-mediated programming of autonomic dysfunction. The present study investigated the influence of sympathetic (SYM) or parasympathetic (PS) blockade on cardiovascular function in male and female rat offspring of mothers injected with DEX in utero (gestation days [GD]18-21). At 11-12-weeks of age, MAP, HR, and heart rate variability (HRV) were evaluated at baseline and in response to SYM antagonists (α 1 -adrenoceptor + ß 1 -adrenoceptor), a PS (muscarinic) antagonist, or saline (SAL). To assess stress-responsive function, rats were exposed to acute restraint. Tyrosine hydroxylase was measured in adrenals and left ventricle, and gene expression for the ß 1 adrenergic receptor was measured in left ventricle. Maternal DEX injection reduced basal HRV in male and female offspring. SYM blockade attenuated increases in stress-responsive HR and MAP. PS blockade elevated stress-responsive HR and MAP to a greater extent in Vehicle females. SYM and PS blockade produced equivalent effects on HR and MAP responses in male offspring, regardless of maternal treatment. Based on these findings, we suggest that maternal DEX injection disrupted autonomic regulation of cardiovascular function in females, resulting in a shift toward greater SYM input and less input from PS. Future studies will investigate whether changes in autonomic function are mediated by changes in central autonomic circuitry. New and Noteworthy: These studies use pharmacological antagonists to characterize the nature of the autonomic dysregulation induced in female offspring exposed to the synthetic glucocorticoid, dexamethasone, in utero . The female offspring of dams injected with dexamethasone in late gestation show a reduction in vulnerability to parasympathetic blockade and an increase in responses to acute restraint stress even in the presence of sympathetic blockade. This suggests that late gestation dexamethasone disrupts the normal development of the autonomic function in females leading to a shift in the sympathovagal balance.
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Spatiotemporal analysis is a critical tool for understanding COVID-19 spread. This study examines the pattern of spatial distribution of COVID-19 cases across India, based on data provided by the Indian Council of Medical Research (ICMR). The research investigates temporal patterns during the first, second, and third waves in India for an informed policy response in case of any present or future pandemics. Given the colossal size of the dataset encompassing the entire nation's data during the pandemic, a time-bound convenience sampling approach was employed. This approach was carefully designed to ensure a representative sample from advancing timeframes to observe time-based patterns in data. Data were captured from March 2020 to December 2022, with a 5-day interval considered for downloading the data. We employ robust spatial analysis techniques, including the Moran's I index for spatial correlation assessment and the Getis Ord Gi* statistic for cluster identification. It was observed that positive COVID-19 cases in India showed a positive auto-correlation from May 2020 till December 2022. Moran's I index values ranged from 0.11 to 0.39. It signifies a strong trend over the last 3 years with [Formula: see text] of 0.74 on order 3 polynomial regression. It is expected that high-risk zones can have a higher number of cases in future COVID-19 waves. Monthly clusters of positive cases were mapped through ArcGIS software. Through cluster maps, high-risk zones were identified namely Kerala, Maharashtra, New Delhi, Tamil Nadu, and Gujarat. The observation is: high-risk zones mostly fall near coastal areas and hotter climatic zones, contrary to the cold Himalayan region with Montanne climate zone. Our aggregate analysis of 3 years of COVID-19 cases suggests significant patterns of interconnectedness between the Indian Railway network, climatic zones, and geographical location with COVID-19 spread. This study thereby underscores the vital role of spatiotemporal analysis in predicting and managing future COVID-19 waves as well as future pandemics for an informed policy response.
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COVID-19 , Humanos , Índia/epidemiologia , COVID-19/epidemiologia , Sistemas de Informação Geográfica , Análise Espaço-Temporal , Análise EspacialRESUMO
This study examined the hypothesis that xanthosine (XS) treatment would promote mammary-specific gene expression and stem cell transcripts and have a positive influence on milk yield of dairy goats. Seven primiparous Beetal goats were assigned to the study. Five days after kidding, one gland (either left or right) was infused with XS (TRT) twice daily for 3 d and the other gland with no XS infusion served as a control (CON). Mammary biopsies were collected at 10 d and RNA was isolated. Gene expression analysis of milk synthesis genes, mammary stem/progenitor cell markers, cell proliferation and differentiation markers were performed using real time quantitative PCR (RT-qPCR). Results showed that the transcripts of milk synthesis genes (BLG4, CSN2, LALBA, FABP3, CD36) and mammary stem/progenitor cell markers (ALDH1 and NR5A2) were increased in as a result of XS treatment. Average milk yield in TRT glands was increased marginally (approximately ~2% P = 0·05, paired t-test) per gland relative to CON gland until 7 wk. After 7 wk, milk yield of TRT and CON glands did not differ. Analysis of milk composition revealed that protein, lactose, fat and solids-not-fat percentages remained the same in TRT and CON glands. These results suggest that XS increases expression of milk synthesis genes, mammary stem/progenitor cells and has a small effect on milk yield.
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Expressão Gênica/efeitos dos fármacos , Cabras , Lactação/genética , Glândulas Mamárias Animais/metabolismo , Ribonucleosídeos/farmacologia , Animais , Biomarcadores/análise , Diferenciação Celular/genética , Proliferação de Células/genética , Feminino , Lactação/efeitos dos fármacos , Lactação/fisiologia , Glândulas Mamárias Animais/citologia , Leite/química , Proteínas do Leite/análise , Proteínas do Leite/genética , Reação em Cadeia da Polimerase , RNA Mensageiro/análise , Reação em Cadeia da Polimerase Via Transcriptase Reversa/veterinária , Células-Tronco/fisiologia , XantinasRESUMO
Chloramphenicol (Cam) is a broad-spectrum antibiotic used to combat bacterial infections in humans and animals. Cam export from bacterial cells is one of the mechanisms by which pathogens resist Cam's antibacterial effects, and several different proteins are known to facilitate this process. However, to date no report exists on any specific transport protein that facilitates Cam uptake. The proton-coupled oligopeptide transporter (POT) YdgR from Escherichia coli is a prototypical member of the POT family, functioning in proton-coupled uptake of di- and tripeptides. By following bacterial growth and conducting LC-MS-based assays we show here that YdgR facilitates Cam uptake. Some YdgR variants displaying reduced peptide uptake also exhibited reduced Cam uptake, indicating that peptides and Cam bind YdgR at similar regions. Homology modeling of YdgR, Cam docking, and mutational studies suggested a binding mode that resembles that of Cam binding to the multidrug resistance transporter MdfA. To our knowledge, this is the first report of Cam uptake into bacterial cells mediated by a specific transporter protein. Our findings suggest a specific bacterial transporter for drug uptake that might be targeted to promote greater antibiotic influx to increase cytoplasmic antibiotic concentration for enhanced cytotoxicity.