Collision-Based Electrochemical Detection of Lysozyme Aggregation.

Proteins are utilized across many biomedical and pharmaceutical industries; therefore, methods for rapid and accurate monitoring of protein aggregation are needed to ensure proper product quality. Although these processes have been previously studied, it is difficult to comprehensively evaluate protein folding and aggregation by traditional characterization techniques such as atomic force microscopy (AFM), electron microscopy, or X-ray diffraction, which require sample pre-treatment and do not represent native state proteins in solution. Herein, we report early tracking of lysozyme (Lyz) aggregation states by using single-particle collision electrochemistry (SPCE) of silver nanoparticle (AgNP) redox probes. The method relies on monitoring the rapid interaction of Lyz with AgNPs, which decreases the number of single AgNPs available for collisions and ultimately the frequency of oxidative impacts in the chronoamperometric profile. When Lyz is in a non-aggregated monomeric form, the protein forms a homogeneous coverage onto the surface of AgNPs, stabilizing the particles. When Lyz is aggregated, part of the AgNP surface remains uncoated, promoting the agglomeration of Lyz-AgNP conjugates. The frequency of AgNP impacts decreases with increasing aggregation time, providing a metric to track protein aggregation. Visualizations of integrated oxidation charge-transfer data displayed significant differences between the charge transfer per impact for AgNP samples alone and in the presence of non-aggregated and aggregated Lyz with 99% confidence using parametric ANOVA tests. Electrochemical results revealed meaningful associations with UV-vis, circular dichroism, and AFM, demonstrating that SPCE can be used as an alternative method for studying protein aggregation. This electrochemical technique could serve as a powerful tool to indirectly evaluate protein stability and screen protein samples for formation of aggregates.

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.

Potential biomarkers of the mature intervertebral disc identified at the single cell level.

Intervertebral disc (IVD) degeneration and trauma is a major socio-economic burden and the focus of cell-based regenerative medicine approaches. Despite numerous ongoing clinical trials attempting to replace ailing IVD cells with mesenchymal stem cells, a solid understanding of the identity and nature of cells in a healthy mature IVD is still in need of refinement. Although anatomically simple, the IVD is comprised of heterogeneous cell populations. Therefore, methods involving cell pooling for RNA profiling could be misleading. Here, by using RNA in situ hybridization and z proportion test, we have identified potential novel biomarkers through single cell assessment. We quantified the proportion of RNA transcribing cells for 50 genetic loci in the outer annulus fibrosus (AF) and nucleus pulposus (NP) in coccygeal bovine discs isolated from tails of four skeletally mature animals. Our data reconfirm existing data and suggest 10 novel markers such as Lam1 and Thy1 in the outer AF and Gli1, Gli3, Noto, Scx, Ptprc, Sox2, Zscan10 and LOC101904175 in the NP, including pluripotency markers, that indicate stemness potential of IVD cells. These markers could be added to existing biomarker panels for cell type characterization. Furthermore, our data once more demonstrate heterogeneity in cells of the AF and NP, indicating the need for single cell assessment by methods such as RNA in situ hybridization. Our work refines the molecular identity of outer AF and NP cells, which can benefit future regenerative medicine and tissue engineering strategies in humans.

Ecological consequences of urban blue space transformation.

This study presents the ecological consequences of the blue space conversion and its qualitative degradation in the English Bazar Municipality (EBM) and its surrounding area. The primary blue spaces of the area, the marshy wetland called Chatra and Mohananda river, are the most affected due to urban activities like built-up expansion and sewage and wastewater discharge. Built-up development encroached more than 300 m within wetland territory and caused a 0.57 km2 conversion of wetland area. It is also evident within the bed of the Mohananda river. Agriculture also caused the conversion of the blue space. As a result, the wetland's ecosystem service value (ESV) was reduced by 12.7%, along with a reduction of cultural services by 27.86%. The massive pouring of sewage and wastewater caused hyper-eutrophication in almost the entire wetland area. The trophic state index (TSI) value increased significantly in the last 10 years, causing high growth and areal expansion of water hyacinth. The expanding settlements and agricultural land that captured the river channel face inundation vulnerability during peak discharge. Extreme danger level discharge causes floods in the extensive municipality area. The areal encroachment, water extraction, sewage and wastewater discharge, and water quality deterioration caused severe hydro-ecological degradation of the river. Since blue space is critically essential for urban environmental health, these ecological consequences can cause a crisis for urban wellbeing. Therefore, the anthropogenic adversities towards the urban blue space must be restricted, and the blue space's ecological sustenance must be paid enough attention.

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.

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.

Characterizing respiratory aerosol emissions during sustained phonation.

OBJECTIVE: To elucidate the role of phonation frequency (i.e., pitch) and intensity of speech on respiratory aerosol emissions during sustained phonations. METHODS: Respiratory aerosol emissions are measured in 40 (24 males and 16 females) healthy, non-trained singers phonating the phoneme /a/ at seven specific frequencies at varying vocal intensity levels. RESULTS: Increasing frequency of phonation was positively correlated with particle production (r = 0.28, p < 0.001). Particle production rate was also positively correlated (r = 0.37, p < 0.001) with the vocal intensity of phonation, confirming previously reported findings. The primary mode (particle diameter ~0.6 µm) and width of the particle number size distribution were independent of frequency and vocal intensity. Regression models of the particle production rate using frequency, vocal intensity, and the individual subject as predictor variables only produced goodness of fit of adjusted R2 = 40% (p < 0.001). Finally, it is proposed that superemitters be defined as statistical outliers, which resulted in the identification of one superemitter in the sample of 40 participants. SIGNIFICANCE: The results suggest there remain unexplored effects (e.g., biomechanical, environmental, behavioral, etc.) that contribute to the high variability in respiratory particle production rates, which ranged from 0.2 particles/s to 142 particles/s across all trials. This is evidenced as well by changes in the distribution of participant particle production that transitions to a more bimodal distribution (second mode at particle diameter ~2 µm) at higher frequencies and vocal intensity levels.

Decay of bacterial pathogens, fecal indicators, and real-time quantitative PCR genetic markers in manure-amended soils.

This study examined persistence and decay of bacterial pathogens, fecal indicator bacteria (FIB), and emerging real-time quantitative PCR (qPCR) genetic markers for rapid detection of fecal pollution in manure-amended agricultural soils. Known concentrations of transformed green fluorescent protein-expressing Escherichia coli O157:H7/pZs and red fluorescent protein-expressing Salmonella enterica serovar Typhimurium/pDs were added to laboratory-scale manure-amended soil microcosms with moisture contents of 60% or 80% field capacity and incubated at temperatures of -20°C, 10°C, or 25°C for 120 days. A two-stage first-order decay model was used to determine stage 1 and stage 2 first-order decay rate coefficients and transition times for each organism and qPCR genetic marker in each treatment. Genetic markers for FIB (Enterococcus spp., E. coli, and Bacteroidales) exhibited decay rate coefficients similar to that of E. coli O157:H7/pZs but not of S. enterica serovar Typhimurium/pDs and persisted at detectable levels longer than both pathogens. Concentrations of these two bacterial pathogens, their counterpart qPCR genetic markers (stx1 and ttrRSBCA, respectively), and FIB genetic markers were also correlated (r = 0.528 to 0.745). This suggests that these qPCR genetic markers may be reliable conservative surrogates for monitoring fecal pollution from manure-amended land. Host-associated qPCR genetic markers for microbial source tracking decayed rapidly to nondetectable concentrations, long before FIB, Salmonella enterica serovar Typhimurium/pDs, and E. coli O157:H7/pZs. Although good indicators of point source or recent nonpoint source fecal contamination events, these host-associated qPCR genetic markers may not be reliable indicators of nonpoint source fecal contamination events that occur weeks following manure application on land.

Impact of Sociodemographic Factors on Dental Caries in Children and Availing Fluoride Treatment: A Study Based on National Survey of Children's Health (NSCH) Data 2016-2019.

Introduction Dental caries is a global health issue. It is a largely preventable, multifactorial non-communicable disease. Given the gravity of the situation, in 2014 United States Preventive Services Task Force recommended that the primary care physician apply fluoride varnish from the eruption of the first tooth till the child attains five years of age. Using 2016-2019 National Survey of Children's Health (NSCH) cross-sectional representative data, the aim of this study was to determine if the child's age, gender, and race are predictors of the child having decayed teeth or cavities in the past 12 months and if they had availed preventative dental services from the dentist in the past 12 months in the US and if so, did they receive fluoride treatment. Methods The prevalence of dental caries and dental treatment among children under each category of sociodemographic risk factors were estimated using 2016-2019 NSCH's cross-sectional representative data on two survey questions. Then, the statistical significance of the association of the categorical risk factors with the prevalence of dental caries and the association of the categorical risk factors with the prevalence of fluoride dental treatment were tested using two-sample proportion tests and chi-square tests. Further, chi-square residual analysis was employed to better understand the nature of the association and to reveal the degree of contribution to the test statistic from each categorical combination of risk factors. Results Prevalence and associative risk of tooth decay in children was the highest in the 6-11 years age group across all three years under study. The 6-11 years age group had the highest prevalence and association of receiving fluoride treatment across all three years. In our study, the prevalence of dental caries in children by race varied according to the year. In 2016-2017 and 2018-2019, it was the Hispanic population with the highest prevalence of tooth decay. In 2017-2018 the highest prevalence was seen in the Non-Hispanic Black (NHB) population. Across all three years, the Hispanic population had the highest associative risk of tooth decay. The Non-Hispanic White (NHW) population had the highest prevalence and association with receiving fluoride treatment across all three years. Male children were found to have the higher prevalence and associative risk of decayed teeth across all three survey years. Conclusion Dental caries is a worldwide health burden. However, it can be prevented by different precautionary measures. The results of our study revealed that certain sociodemographic factors such as age, gender, and race of the child make certain groups of the child population more at risk for the development of dental caries; most notable findings were that the male children were significantly associated to have decayed teeth and not availing dental fluoride treatment for which limited information is available in the literature. Additionally, the age groups 1-5 and 6-11 were significantly associated with the prevalence of not receiving dental treatment and the prevalence of dental caries, respectively. More active participation of pediatricians in getting trained for the application of fluoride varnish and helping getting their patients established with dental services per recommendations will help streamline preventative dental care.

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.

Six Minutes of Physical Activity Improves Mood in Older Adults: A Pilot Study.

BACKGROUND AND PURPOSE: The purposes of this study were to examine (1) differences in mood and motivation among older adults after the completion of 6 minutes of self-paced walking (6MW) and (2) the relationship between pace and magnitude of mood change. METHODS: Eleven participants completed 3 days of testing where energy, fatigue, tension, depression, confusion, mental and physical energy, and motivation to perform mental tasks were measured before and after the 6MW. A repeated-measures analysis of variance was used to examine changes in mood and motivation, and a bivariate Pearson correlation was used to determine relationships between pace and magnitude of changes in mood. RESULTS: Faster pace was associated with significant improvements (P < .05) in fatigue, energy, tension, confusion, total mood disturbance, state mental fatigue, and state physical energy. A significant relationship was noted between pace and changes in energy, fatigue, state mental and physical energy, and fatigue in the expected direction. DISCUSSION: Results indicate that mood is influenced by pace of the activity. Findings suggest that even 6 minutes of physical activity can improve moods, which may impact how physical therapists approach prescribing exercise to older adults.

Predicting home and community walking activity in people with stroke.

OBJECTIVE: To determine the ability of the 6-minute walk test (6MWT) and other commonly used clinical outcome measures to predict home and community walking activity in high-functioning people with stroke. DESIGN: Cross-sectional. SETTING: Outpatient physical therapy clinic. PARTICIPANTS: Participants (N=32) with chronic stroke (n=19; >6mo poststroke) with self-selected gait speed (GS) faster than .40m/s and age-matched healthy participants (n=13). INTERVENTIONS: Not applicable. INDEPENDENT VARIABLES: 6MWT, self-selected GS, Berg Balance Scale (BBS), lower extremity motor section of the Fugl-Meyer Assessment, and Stroke Impact Scale. Dependent variable: average steps taken per day during a 7-day period, measured using an accelerometer. RESULTS: 6MWT, self-selected GS, and BBS were moderately related to home and community walking activity. The 6MWT was the only predictor of average steps taken per day; it explained 46% of the variance in steps per day. CONCLUSIONS: The 6MWT is a useful outcome measure in higher functioning people with stroke to guide intervention and assess community walking activity.