IntroductionDiabetes, hypertension, and hypercholesterolemia are common chronic diseases among Hispanics, a group projected to comprise 30% of the US population by 2050. Mexican Americans are the largest ethnically distinct subgroup among Hispanics. We assessed the prevalence of and risk factors for undiagnosed and untreated diabetes, hypertension, and hypercholesterolemia among Mexican Americans in Cameron County, Texas.MethodsWe analyzed cross-sectional baseline data collected from 2003 to 2008 in the Cameron County Hispanic Cohort, a randomly selected, community-recruited cohort of 2,000 Mexican American adults aged 18 or older, to assess prevalence of diabetes, hypertension, and hypercholesterolemia; to assess the extent to which these diseases had been previously diagnosed based on self-report; and to determine whether participants who self-reported having these diseases were receiving treatment. We also assessed social and economic factors associated with prevalence, diagnosis, and treatment.ResultsApproximately 70% of participants had 1 or more of the 3 chronic diseases studied. Of these, at least half had had 1 of these 3 diagnosed, and at least half of those who had had a disease diagnosed were not being treated. Having insurance coverage was positively associated with having the 3 diseases diagnosed and treated, as were higher income and education level.ConclusionsAlthough having insurance coverage is associated with receiving treatment, important social and cultural barriers remain. Failure to provide widespread preventive medicine at the primary care level will have costly consequences.
The novel coronavirus disease (COVID-19) pandemic has impacted health and wellbeing globally. To strengthen preventive and clinical care amid this pandemic, technological innovations like artificial intelligence (AI) are increasingly used in different contexts. This bibliometric study aimed to assess the current scholarly development and prominent research domains in applications of AI technologies in COVID-19 research. A total of 105 articles were retrieved from MEDLINE database that emphasized on the use of AI in the context of COVID-19. Most articles had multiple authors with a collaboration index of 7.18. Moreover, most of the articles were produced from the USA (22.86%) and China (21.9%), whereas developing countries were underrepresented among the contributing nations. Furthermore, several research domains were identified, including prevention and control, diagnostics, epidemiological characteristics, therapeutics, psychological conditions, and different areas of data sciences related to COVID-19. The current bibliometric evidence shows the early stage of development in this field, which necessitates equitable applications of AI in COVID-19 research emphasizing on health disparities, socio-legal issues, vaccine development, and applied public health research in this pandemic.
The inhibitory effect of CD8+ T-cells from HIV-infected or HIV-seronegative individuals on HIV replication in the naturally-infected CD4+ T-cells in vitro was examined. Not only autologous CD8+ T-cells from HIV-infected individuals but also allogeneic CD8+ T-cells from HIV-seronegative individuals prevented or delayed HIV replication, even in transwell cocultures using a semi-permeable 0.45 micron filter. The level of the inhibitory effect of allogeneic CD8+ T-cells from the HIV-seronegative individuals on the HIV replication was varied among CD4+ T-cells obtained from HIV-infected individuals used. The results suggested that CD8+ T-cells from HIV-seronegative individuals as well as HIV-infected individuals could produce some cytokine(s) which suppress HIV replication in vitro. The sensitivity to the cytokine(s) might be variable among HIV strains, depending on differences in the nucleotide sequence of different HIV-1 strains. Further studies of control of HIV replication by CD8+ anti-HIV cytokine(s) should provide new strategies for the therapy of HIV infection.
Antimicrobial resistance gene mcr-1 has been disseminated globally since its first discovery in Southern China in late 2015. However, the mcr-1 gene had not been identified previously in Salmonella isolates from poultry in Bangladesh. Here, we aimed to explore antimicrobial resistance gene mcr-1 in Salmonella isolates. Eighty two Salmonella isolates were isolated and characterized from suspected poultry specimens received from different zones of the country. A phenotypic disc diffusion assay with 15 antimicrobial agents was performed following CLSI standard. The disk diffusion assay showed that, all of the isolates presented high resistance to colistin (92.68%), oxytetracycline (86.59%), co-trimoxazole (76.83%), ciprofloxacin (73.17%) and enrofloxacin (65.85%). Further, randomly selected 10 Salmonella isolates were analyzed by polymerase chain reaction (PCR) targeting genus-specific invA and antimicrobial (colistin) resistance mcr-1 genes. Five were confirmed for the presence of the mcr-1 gene belonging to Salmonella spp. Further, sequencing followed by phylogenetic analysis revealed divergent evolutionary relation between the LptA and MCR proteins rendering them resistant to colistin. Three-dimensional homology structures of MCR-1 proteins were constructed and verified using different bioinformatics tools. Moreover, molecular docking interactions suggested that, MCR-1 and LptA share a similar substrate binding cavity which could be validated for the functional analysis. The results represent here is the first molecular and in silico analysis of colistin resistance mcr-1 gene of Salmonella in poultry in Bangladesh, which may emphasize the importance of the study on antibiotic resistance genes requiring for national monitoring and strategic surveillance in the country.
Background: Urinary tract infection (UTI) has become the most frequent bacterial infections worldwide. It is well established that Escherichia coli is the predominant cause of UTI. The aim of our study was to evaluate the rates of resistance to fluroquinolone and third generation cephalosporin among the patients with UTI due to E.Coli and to assess the potential correlation between both trends. Methods: The study was a cross sectional observational study conducted at the Department of Pharmacology and Therapeutics in collaboration with Department of Microbiology of Sylhet Women’s Medical College and Hospital from 1st July 2019 to 30th June 2020. Results: A total of 246 urine samples were collected from patients with UTI followed by isolation and identification of E.coli strains. Antibiotic sensitivity and resistance analysis was performed by the disc diffusion method employing multiple antibiotic discs. The sensitivity was monitored by zone of inhibition around the disc. Overall rates of resistance to fluroquinolone and third generation cephalosporin were 70.31% and 65.10% respectively. The rates of co-resistance to both fluroquinolone and third generation cephalosporin was 53.13%. Conclusion: Our study suggests that fluroquinolone should be reserved and third generation cephalosporin should be used with caution among patients with E.coli.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.