Implications of SARS-CoV-2 spike protein interactions with Zn-bound form of ACE2: a computational structural study.

The COVID-19 pandemic has generated a major interest in designing inhibitors to prevent SARS-CoV-2 binding on host cells to protect against infection. One promising approach to such research utilizes molecular dynamics simulation to identify potential inhibitors that can prevent the interaction between spike (S) protein on the virus and angiotensin converting enzyme 2 (ACE2) receptor on the host cells. In these studies, many groups have chosen to exclude the ACE2-bound zinc (Zn) ion, which is critical for its enzymatic activity. While the relatively distant location of Zn ion from the S protein binding site (S1 domain), combined with the difficulties in modeling this ion has motivated the decision of exclusion, Zn can potentially contribute to the structural stability of the entire protein, and thus, may have implications on S protein-ACE2 interaction. In this study, the authors model both the ACE2-S1 and ACE2-inhibitor (mAb) system to investigate if there are variations in structure and the readouts due to the presence of Zn ion. Although distant from the S1 or inhibitor binding region, inclusion/exclusion of Zn has statistically significant effects on the structural stability and binding free energy in these systems. In particular, the binding free energy of the ACE2-S1 and ACE2-inhibitor structures is - 3.26 and - 14.8 kcal/mol stronger, respectively, in the Zn-bound structure than in the Zn-free structures. This finding suggests that including Zn may be important in screening potentially inhibitors and may be particularly important in modeling monoclonal antibodies, which may be more sensitive to changes in antigen structure.

KCa3.1-dependent uptake of the cytotoxic DNA-binding dye Hoechst 33258 into cancerous but not healthy cervical cells.

The poor and nonselective penetration of current chemotherapeutics across the plasma membranes of cancer cells, which is necessary for the targeted disruption of the intracellular machinery, remains a major pharmaceutical challenge. In several cell types, including mast cells and macrophages, exposure to extracellular ATP is known to stimulate passive entry of large and otherwise membrane impermeable cationic dyes, which is usually attributed to conduction through ionotropic P2X receptors. Here, we report that elevations in cytosolic Ca2+ stimulate the rapid uptake and nuclear accumulation of a DNA-binding fluorescent cation, Hoechst 33258 (H33258), in cervical cancer cells. The H33258 uptake was dependent on activation of intermediate conductance Ca2+-activated K+ channels (KCa3.1), and direct stimulation of the channel with the activators SKA 31 and DCEBIO was sufficient to induce cellular uptake of H33258 directly. In contrast to the results from cancerous cervical cells, KCa3.1-dependent H33258 uptake was rarely observed in epithelial cells derived from the ectocervix and transformation zone of healthy cervical tissue. Furthermore, whole-cell patch clamp experiments and assessment of membrane potential using the slow voltage-sensitive dye bis-(1,3-diethylthiobarbituric acid)trimethine oxonol revealed a significant difference in functional KCa3.1 activity between cancerous and healthy cervical epithelial cells, which correlated strongly with the incidence of KCa3.1-dependent H33258 uptake. Finally, we show that activation of KCa3.1 channels caused a modest but significant sensitization of cancer cells to the growth suppressant effects of H33258, lending plausibility to the idea of using KCa3.1 channel activators to enhance cell penetration of small cationic toxins into cancer cells expressing these channels.

Ivermectin-induced cell death of cervical cancer cells in vitro a consequence of precipitate formation in culture media.

The anthelmintic ivermectin has been reported to possess anticancer and antiviral efficacy. However, the effective concentrations reported in vitro are near the predicted aqueous solubility limit for this hydrophobic drug. We observed that ivermectin-induced cell death in two cervical cancer cell lines correlated with the formation of solid ivermectin aggregates in both serum-free and serum-supplemented culture media. Filtration of ivermectin particles >0.2 µm abolished these cytolytic effects in both cell lines. An inhibitory effect on cell proliferation persisted for filtered solutions, but only for ivermectin concentrations higher than reported to be clinically attainable in humans. In addition to the importance of distinguishing between free and bound drug in solution, our data emphasize the importance of acknowledging the likely solubility limit of hydrophobic drugs when assessing their in vitro cytotoxicity.

Establishment and optimization of epithelial cell cultures from human ectocervix, transformation zone, and endocervix optimization of epithelial cell cultures.

Cervical cancer is a major public health problem and research using cell culture models has improved understanding of this disease. The human cervix contains three anatomic regions; ectocervix with stratified squamous epithelium, endocervix with secretory epithelium, and transformation zone (TZ) with metaplastic cells. Most cervical cancers originate within the TZ. However, little is known about the biology of TZ cells or why they are highly susceptible to carcinogenesis. The goal of this study was to develop and optimize methods to compare growth and differentiation of cells cultured from ectocervix, TZ or endocervix. We examined the effects of different serum-free media on cell attachment, cell growth and differentiation, and cell population doublings in monolayer culture. We also optimized conditions for organotypic culture of cervical epithelial cells using collagen rafts with human cervical stromal cells. Finally, we present a step-by-step protocol for culturing cells from each region of human cervix.

Supramolecular Nanofibers Enhance Growth Factor Signaling by Increasing Lipid Raft Mobility.

The nanostructures of self-assembling biomaterials have been previously designed to tune the release of growth factors in order to optimize biological repair and regeneration. We report here on the discovery that weakly cohesive peptide nanostructures in terms of intermolecular hydrogen bonding, when combined with low concentrations of osteogenic growth factor, enhance both BMP-2 and Wnt mediated signaling in myoblasts and bone marrow stromal cells, respectively. Conversely, analogous nanostructures with enhanced levels of internal hydrogen bonding and cohesion lead to an overall reduction in BMP-2 signaling. We propose that the mechanism for enhanced growth factor signaling by the nanostructures is related to their ability to increase diffusion within membrane lipid rafts. The phenomenon reported here could lead to new nanomedicine strategies to mediate growth factor signaling for translational targets.

Bioactive DNA-peptide nanotubes enhance the differentiation of neural stem cells into neurons.

We report the construction of DNA nanotubes covalently functionalized with the cell adhesion peptide RGDS as a bioactive substrate for neural stem cell differentiation. Alteration of the Watson-Crick base pairing program that builds the nanostructures allowed us to probe independently the effect of nanotube architecture and peptide bioactivity on stem cell differentiation. We found that both factors instruct synergistically the preferential differentiation of the cells into neurons rather than astrocytes.

Post-assembly functionalization of supramolecular nanostructures with bioactive peptides and fluorescent proteins by native chemical ligation.

Post-assembly functionalization of supramolecular nanostructures has the potential to expand the range of their applications. We report here the use of the chemoselective native chemical ligation (NCL) reaction to functionalize self-assembled peptide amphiphile (PA) nanofibers. This strategy can be used to incorporate specific bioactivity on the nanofibers, and as a model, we demonstrate functionalization with the RGDS peptide following self-assembly. Incorporation of bioactivity is verified by the observation of characteristic changes in fibroblast morphology following NCL-mediated attachment of the signal to PA nanofibers. The NCL reaction does not alter the PA nanofiber morphology, and biotinylated RGDS peptide was found to be accessible on the nanofiber surface after ligation for binding with streptavidin-conjugated gold nanoparticles. In order to show that this strategy is not limited to short peptides, we utilized NCL to conjugate yellow fluorescent protein and/or cyan fluorescent protein to self-assembled PA nanofibers. Förster resonance energy transfer and fluorescence anisotropy measurements are consistent with the immobilization of the protein on the PA nanofibers. The change in electrophoretic mobility of the protein upon conjugation with PA molecules confirmed the formation of a covalent linkage. NCL-mediated attachment of bioactive peptides and proteins to self-assembled PA nanofibers allows the independent control of self-assembly and bioactivity while retaining the biodegradable peptide structure of the PA molecule and thus can be useful in tailoring design of biomaterials.

Interaction of Microbes with Microplastics and Nanoplastics in the Agroecosystems-Impact on Antimicrobial Resistance.

Microplastics (MPs) and nanoplastics (NPs) are hotspots for the exchange of antimicrobial resistance genes (ARGs) between different bacterial taxa in the environment. Propagation of antimicrobial resistance (AMR) is a global public health issue that needs special attention concerning horizontal gene transfer (HGT) under micro-nano plastics (MNPs) pressure. Interactions between MNPs and microbes, or mere persistence of MNPs in the environment (either water or soil), influence microbial gene expressions, affecting autochthonous microbiomes, their resistomes, and the overall ecosystem. The adsorption of a range of co-contaminants on MNPs leads to the increased interaction of pollutants with microbes resulting in changes in AMR, virulence, toxin production, etc. However, accurately estimating the extent of MNP infestation in agroecosystems remains challenging. The main limitation in estimating the level of MNPs contamination in agroecosystems, surface and subsurface waters, or sediments is the lack of standardized protocols for extraction of MPs and analytical detection methods from complex high organic content matrices. Nonetheless, recent advances in MPs detection from complex matrices with high organic matter content are highly promising. This review aims to provide an overview of relevant information available to date and summarize the already existing knowledge about the mechanisms of MNP-microbe interactions including the different factors with influence on HGT and AMR. In-depth knowledge of the enhanced ARGs propagation in the environment under the influence of MNPs could raise the needed awareness, about future consequences and emergence of multidrug-resistant bacteria.

Factors Affecting Human Papillomavirus Vaccine Trends in the United States of America.

Background Routine immunization of both girls and boys starting from nine years of age with the human papillomavirus (HPV) vaccine is the current recommendation. The objective of this retrospective study using National Health and Nutrition Examination Survey data was to evaluate the influence of sociodemographic factors on the series initiation and completion of the HPV vaccine from 2011 to 2020. Methodology The chi-square test was used to examine the statistical significance of the association between categorical variables and receipt of the HPV vaccine. The Cochran-Armitage test for trend was employed to assess the statistical significance of temporal trends in risk factors associated with rates of HPV vaccination. These trends were further quantified by a significant rate ratio by comparing them against the most recent survey years. Results HPV vaccine uptake was higher in the 9-14-year age group across survey years and had increased for both males and females over that time. The first dose of the HPV vaccine was most likely to be received by the 11-18-year age group. In the most recent survey of 2017-2020, the highest number of vaccination series completion was achieved for Gardasil®. Conclusions Improved physician efforts and strategies to vaccinate males, low socioeconomic strata patients, and ethnic minorities in more numbers are needed.

Utilizing logistic regression to compare risk factors in disease modeling with imbalanced data: a case study in vitamin D and cancer incidence.

Imbalanced data, a common challenge encountered in statistical analyses of clinical trial datasets and disease modeling, refers to the scenario where one class significantly outnumbers the other in a binary classification problem. This imbalance can lead to biased model performance, favoring the majority class, and affecting the understanding of the relative importance of predictive variables. Despite its prevalence, the existing literature lacks comprehensive studies that elucidate methodologies to handle imbalanced data effectively. In this study, we discuss the binary logistic model and its limitations when dealing with imbalanced data, as model performance tends to be biased towards the majority class. We propose a novel approach to addressing imbalanced data and apply it to publicly available data from the VITAL trial, a large-scale clinical trial that examines the effects of vitamin D and Omega-3 fatty acid to investigate the relationship between vitamin D and cancer incidence in sub-populations based on race/ethnicity and demographic factors such as body mass index (BMI), age, and sex. Our results demonstrate a significant improvement in model performance after our undersampling method is applied to the data set with respect to cancer incidence prediction. Both epidemiological and laboratory studies have suggested that vitamin D may lower the occurrence and death rate of cancer, but inconsistent and conflicting findings have been reported due to the difficulty of conducting large-scale clinical trials. We also utilize logistic regression within each ethnic sub-population to determine the impact of demographic factors on cancer incidence, with a particular focus on the role of vitamin D. This study provides a framework for using classification models to understand relative variable importance when dealing with imbalanced data.

A stronger association of depression with rheumatoid arthritis in presence of obesity and hypertriglyceridemia.

Background: Rheumatoid arthritis (RA) is an autoimmune disorder characterized by chronic and systemic inflammation. Recent research underscores the role of chronic inflammation in multiple common RA comorbidities such as depression, obesity, and cardiovascular diseases (CVDs), suggesting a potential overlap of the pathogenic mechanisms for RA. However, it is not well understood how the coexistence of these comorbid conditions impacts the risk of RA and whether any such association relates to body's inflammatory state. Methods: We used data from the 2007-2010 United States National Health and Nutrition Examination Survey (NHANES) database and compared RA prevalence between subsamples with the presence of any two conditions among depression, obesity, and hypertriglyceridemia (HTG). Each subsample was further divided into three categories based on the serum level of the inflammatory marker C-reactive protein (CRP) and analyzed for statistically significant differences using three-way χ2 tests of independence. Results: The study was conducted on 4,136 patients who fulfilled the inclusion criteria (representing 163,540,241 individuals after adjustment for sampling weights). Rates of depression, obesity, and HTG were found to be significantly higher (P < 0.001) among the subjects with RA compared with the control population with no arthritis. The presence of depression along with obesity or HTG showed a noticeably higher RA prevalence but such an association was not observed for the combination of obesity and HTG. The synergistic effect of HTG with depression was found to be most prominent at a medium CRP level (1-3 mg/L), while for obesity, the effect was observed across all CRP levels examined. These findings were further confirmed by the three-way χ2 test for independence. Conclusions: The presence of obesity or HTG in subjects suffering from depression might pose an increased risk of RA. Inflammatory mechanisms potentially play an important underlying role as suggested by the strong dependency of the association to CRP level. Identification of synergistic associations between RA risk conditions could provide useful information to predict the development and progress of RA.

Interrelation between Stress Management and Secretion Systems of Ralstonia solanacearum: An In Silico Assessment.

Ralstonia solanacearum (Rs), the causative agent of devastating wilt disease in several major and minor economic crops, is considered one of the most destructive bacterial plant pathogens. However, the mechanism(s) by which Rs counteracts host-associated environmental stress is still not clearly elucidated. To investigate possible stress management mechanisms, orthologs of stress-responsive genes in the Rs genome were searched using a reference set of known genes. The genome BLAST approach was used to find the distributions of these orthologs within different Rs strains. BLAST results were first confirmed from the KEGG Genome database and then reconfirmed at the protein level from the UniProt database. The distribution pattern of these stress-responsive factors was explored through multivariate analysis and STRING analysis. STRING analysis of stress-responsive genes in connection with different secretion systems of Rs was also performed. Initially, a total of 28 stress-responsive genes of Rs were confirmed in this study. STRING analysis revealed an additional 7 stress-responsive factors of Rs, leading to the discovery of a total of 35 stress-responsive genes. The segregation pattern of these 35 genes across 110 Rs genomes was found to be almost homogeneous. Increasing interactions of Rs stress factors were observed in six distinct clusters, suggesting six different types of stress responses: membrane stress response (MSR), osmotic stress response (OSR), oxidative stress response (OxSR), nitrosative stress response (NxSR), and DNA damage stress response (DdSR). Moreover, a strong network of these stress responses was observed with type 3 secretion system (T3SS), general secretory proteins (GSPs), and different types of pili (T4P, Tad, and Tat). To the best of our knowledge, this is the first report on overall stress response management by Rs and the potential connection with secretion systems.

COVID-19 in New York state: Effects of demographics and air quality on infection and fatality.

The coronavirus disease 2019 (COVID-19) has had a global impact that has been unevenly distributed among and even within countries. Multiple demographic and environmental factors have been associated with the risk of COVID-19 spread and fatality, including age, gender, ethnicity, poverty, and air quality among others. However, specific contributions of these factors are yet to be understood. Here, we attempted to explain the variability in infection, death, and fatality rates by understanding the contributions of a few selected factors. We compared the incidence of COVID-19 in New York State (NYS) counties during the first wave of infection and analyzed how different demographic and environmental variables associate with the variation observed across the counties. We observed that infection and death rates, two important COVID-19 metrics, to be highly correlated with both being highest in counties located near New York City, considered as one of the epicenters of the infection in the US. In contrast, disease fatality was found to be highest in a different set of counties despite registering a low infection rate. To investigate this apparent discrepancy, we divided the counties into three clusters based on COVID-19 infection, death, or fatality, and compared the differences in the demographic and environmental variables such as ethnicity, age, population density, poverty, temperature, and air quality in each of these clusters. Furthermore, a regression model built on this data reveals PM2.5 and distance from the epicenter are significant risk factors for infection, while disease fatality has a strong association with age and PM2.5. Our results demonstrate that for the NYS, demographic components distinctly associate with specific aspects of COVID-19 burden and also highlight the detrimental impact of poor air quality. These results could help design and direct location-specific control and mitigation strategies.

COVID-19 in the U.S. during pre-vaccination period: Shifting impact of sociodemographic factors and air pollution.

Pandemic "wave" usually refers to the rise and fall of the infections with time, however, for a large country, the variations due to geographical location could be considerable. In this work, we investigated COVID-19 infection and fatality across the U.S. during the pandemic waves in the pre-vaccination period (January 2020-December 2020). Focusing on counties with a population ≥100,000, the data from the entire period were first segmented into two equal phases roughly corresponding to the first pandemic wave and subsequent surge, and each phase was further divided into two zones based on infection rate. We studied the potential influences of six sociodemographic variables (population density, age, poverty, education, and percentage of Hispanic and African American population) and four air pollutants (PM2.5, NO2, SO2, and O3) on the differences in infection and fatality observed among different phases and zones. We noticed a distinct difference in the overall impact of COVID-19 between the two phases of the pre-vaccination period with a substantial decrease in the fatality in the second phase despite an increase in the infection. Analysis using log-linear regression modeling further revealed a shift in the impact of several risk factors considered in this study. For example, population density and lesser education were found to be significant for infection during the first phase of the pandemic alone. Furthermore, population density and lesser education along with poverty and NO2 level had a significant contribution to fatality during the first phase of the pandemic, while age over 65 years was important in both phases. Interestingly, the effects of many of these factors were found to be significant only in the zones with higher infection rates. Our findings indicate that the impacts of several well-known sociodemographic and environmental risk factors for COVID-19 are not constant throughout the course of the pandemic, and therefore, careful considerations should be made about their role when developing preventative and mitigative measures.

The Effects of Vision-Deprived Progressive Resistance Training on One-Repetition Maximum Bench Press Performance: An Exploratory Study.

The objective of this study was to determine whether vision-occluded progressive resistance training would increase upper-extremity movement performance using the one-repetition maximum (1-RM) bench press. Participants (n = 57) were recruited from a historically black college and university (HBCU), cross-matched by sex, age (±1 year), 1-RM (±2.27 kg), 1-RM/weight (±0.1), and 1-RM/lean mass ratio (±0.1), and randomly assigned to either the experimental group (vision occluded) or the control group. Participants performed resistance training for 6 weeks prior to beginning the study, and 1-RM was assessed the week prior to the beginning of the study. Weight and body composition were measured using a BOD POD. Of the 57 participants who started the study, 34 completed the study (Experimental = 16, Control = 18) and were reassessed the week after completing the 6-week-long training protocol. Using a combination of Mann−Whitney U and Wilcoxon signed-rank tests, we found that when accounting for changes in lean muscle mass, individuals who trained with their vision occluded reported significantly greater improvements in 1-RM strength compared to those who did not (p < 0.05). The findings from our study suggest that vision-occluded progressive resistance training increases upper-extremity performance when assessed using the bench press. These findings may have significant practical implications in both sports and rehabilitation, as these techniques may be used to enhance performance in athletes and/or improve rehabilitation effectiveness.

Factors Influencing Motivation to Perform Mental and Physical Tasks During the Initial Lockdown Period of the COVID-19.

Drastic changes to lifestyles have occurred during the COVID-19 pandemic. An unintended consequence of stay at home orders is increased isolation and less social interaction for many people. For overall wellbeing it is important to stay both physically and mentally active; however, for many individual's motivation may be a barrier. There are non-modifiable (e.g. sex, age, personality, infection rates in the area) and modifiable factors (e.g. physical activity, diet, sleep) that may be associated with motivation to perform physical and mental tasks. We collected data from 794 subjects using an online survey between April 13th to May 3rd of 2020. Survey questionnaires included demographics, personality traits, diet, sleep, physical activity levels, mental workload and motivation to perform mental and physical tasks. Multiple linear regression analyses were used to assess the association between non-modifiable and modifiable variables on motivation to perform mental and physical tasks. The results of our analyses suggest that those who reported a higher quality of diet (REAP-S score), exercised vigorously, and reduced their sedentary time, reported higher motivation to perform both mental and physical tasks. Those who were employed and had higher grit were more motivated to perform physical tasks. Lower trait physical energy was associated with greater motivation to perform mental tasks. Our findings support that during challenging times, such as the COVID-19 pandemic, it is important for healthcare practitioners to emphasize the importance healthy lifestyle behaviors to prevent individuals from experiencing a lack of motivation to perform both mental and physical tasks. Future research should focus on trying to determine the directionality of the relationship between specific healthy lifestyle behaviors and motivation.

Socioeconomic Factors Associated With the Risk and Prevalence of Dental Caries and Dental Treatment Trends in Children: A Cross-Sectional Analysis of National Survey of Children's Health (NSCH) Data, 2016-2019.

Introduction In the United States of America, early childhood caries (ECC) is the most common chronic childhood disease of early onset, with dental caries being the most prevalent chronic disease among children aged 6-19 years. Children without an established medical home, from low-income households, and who are uninsured have historically shown to be prone to dental caries and attribute to higher health care costs. Early recognition of these risk factors by a pediatrician helps prevent the development of medical and psychosocial complications in the child. Methods The cross-sectional data of the prevalence of dental caries and dental treatment trends in children and three socioeconomic risk factors, namely establishment of a medical home, household income, and child's health insurance, were accessed from the National Survey of Children's Health (NSCH) for the years 2016-2019. The association of the risk factors with the prevalence of dental caries and with the prevalence of dental treatment were analyzed using two-sample proportion tests and chi-square (χ2) tests for dichotomous categorical variables and non-dichotomous categorical variables, respectively. Standardized residuals were calculated and analyzed as well. Furthermore, the odds ratios were calculated and utilized to quantify the influence of each category on the highly associated category with having teeth decay and not receiving dental treatment under each socioeconomic risk factor. Results The results of this study revealed that the three socioeconomic factors considered have statistically significant associations with tooth decay and dental treatment. The prevalence and associative risk of tooth decay and untreated caries were the highest in the children without a medical home. Additionally, the odds of having tooth decay was >50% higher for the children from the lowest household income category (0-99% federal poverty level [FPL]) compared to those from the high household income categories (200-399% FPL and >400% FPL). Public insurance coverage was associated with the highest prevalence of dental caries and not receiving fluoride treatment. Furthermore, the likelihood of not availing dental treatment is nearly two times or more higher for the uninsured children than children having public insurance, or private insurance, or a combination of both. Conclusion Our study findings reveal that children belonging to certain socioeconomic risk categories are at a higher risk of developing dental caries and not receiving dental treatment. As a consequence, the study implies that increased support and expansion of public health insurance will benefit oral health care for the children. Pediatricians play an integral part in developing a medical home for the child by providing preventative dental care and establishing continued care through dental referrals.

A Bayesian Model to Analyze the Association of Rheumatoid Arthritis With Risk Factors and Their Interactions.

Rheumatoid arthritis (RA) is a chronic autoimmune disorder that commonly manifests as destructive joint inflammation but also affects multiple other organ systems. The pathogenesis of RA is complex where a variety of factors including comorbidities, demographic, and socioeconomic variables are known to associate with RA and influence the progress of the disease. In this work, we used a Bayesian logistic regression model to quantitatively assess how these factors influence the risk of RA, individually and through their interactions. Using cross-sectional data from the National Health and Nutrition Examination Survey (NHANES), a set of 11 well-known RA risk factors such as age, gender, ethnicity, body mass index (BMI), and depression were selected to predict RA. We considered up to third-order interactions between the risk factors and implemented factor analysis of mixed data (FAMD) to account for both the continuous and categorical natures of these variables. The model was further optimized over the area under the receiver operating characteristic curve (AUC) using a genetic algorithm (GA) with the optimal predictive model having a smoothed AUC of 0.826 (95% CI: 0.801-0.850) on a validation dataset and 0.805 (95% CI: 0.781-0.829) on a holdout test dataset. Apart from corroborating the influence of individual risk factors on RA, our model identified a strong association of RA with multiple second- and third-order interactions, many of which involve age or BMI as one of the factors. This observation suggests a potential role of risk-factor interactions in RA disease mechanism. Furthermore, our findings on the contribution of RA risk factors and their interactions to disease prediction could be useful in developing strategies for early diagnosis of RA.

Differential Impact of COVID-19 Risk Factors on Ethnicities in the United States.

The coronavirus disease (COVID-19) has revealed existing health inequalities in racial and ethnic minority groups in the US. This work investigates and quantifies the non-uniform effects of geographical location and other known risk factors on various ethnic groups during the COVID-19 pandemic at a national level. To quantify the geographical impact on various ethnic groups, we grouped all the states of the US. into four different regions (Northeast, Midwest, South, and West) and considered Non-Hispanic White (NHW), Non-Hispanic Black (NHB), Hispanic, Non-Hispanic Asian (NHA) as ethnic groups of our interest. Our analysis showed that infection and mortality among NHB and Hispanics are considerably higher than NHW. In particular, the COVID-19 infection rate in the Hispanic community was significantly higher than their population share, a phenomenon we observed across all regions in the US but is most prominent in the West. To gauge the differential impact of comorbidities on different ethnicities, we performed cross-sectional regression analyses of statewide data for COVID-19 infection and mortality for each ethnic group using advanced age, poverty, obesity, hypertension, cardiovascular disease, and diabetes as risk factors. After removing the risk factors causing multicollinearity, poverty emerged as one of the independent risk factors in explaining mortality rates in NHW, NHB, and Hispanic communities. Moreover, for NHW and NHB groups, we found that obesity encapsulated the effect of several other comorbidities such as advanced age, hypertension, and cardiovascular disease. At the same time, advanced age was the most robust predictor of mortality in the Hispanic group. Our study quantifies the unique impact of various risk factors on different ethnic groups, explaining the ethnicity-specific differences observed in the COVID-19 pandemic. The findings could provide insight into focused public health strategies and interventions.

Prevalence of Common Comorbidities in Rheumatoid Arthritis in Rural New York Compared With National Data.

Background Rheumatoid arthritis (RA) is a systemic autoimmune disease with multiple known comorbidities and risk factors. The rate and severity of different comorbidities among RA patients are influenced by various demographic, behavioral, and socioeconomic factors, which can vary widely between urban and rural areas. However, limited information is currently available regarding the association of comorbidities with RA in rural settings. In this study, we investigated the prevalence of common comorbidities and risk factors of RA among RA patients from a rural hospital located in rural northern New York and compared them against national patient records obtained from the National Hospital Ambulatory Medical Care Survey (NHAMCS). Methodology We compared de-identified patient records of 153 RA patients obtained from St. Lawrence Health (SLH) to 198 RA patients from the NHAMCS. After performing the descriptive analyses and removing outliers, two-sample tests of proportions were used for comparing the binary categories of sex, age, obesity, hypertension, chronic obstructive pulmonary disease (COPD), and congestive heart failure (CHF) between the two datasets. These analyses were applied to both weighted and unweighted sets of national data, and a p-value of <0.05 was considered statistically significant. The differences were then explored at a greater resolution by binning body mass index, blood pressure (BP), COPD prevalence, and tobacco usage data across different age groups. Results A significantly higher rate of diastolic hypertension (χ2 = 17.942, w = 0.232, p < 0.001) and over two times higher prevalence of COPD (χ2 = 7.635, w = 0.147, p = 0.006) were observed among RA patients in the rural group. The rates of CHF were significantly different only when sample weighting was applied. When categorized by age groups, diastolic BP showed a peak at 40-49 years, coinciding with the age group for high tobacco smoking and peak disease activity in rural RA patients. Conclusions A higher prevalence of comorbidities of RA such as hypertension (diastolic) and COPD are observed in patients from northern rural New York compared to the national average. Our findings indicate that rural RA patients might have a distinct comorbidity burden, suggesting the need for larger-scale studies.