95038 research outputs found
Sort by
Complex bacterial diversity of Guaymas Basin hydrothermal sediments revealed by synthetic long-read sequencing (LoopSeq)
Get PDFHydrothermal sediments host phylogenetically diverse and physiologically complex microbial communities. Previous studies of microbial community structure in hydrothermal sediments have typically used short-read sequencing approaches. To improve on these approaches, we use LoopSeq, a high-throughput synthetic long-read sequencing method that has yielded promising results in analyses of microbial ecosystems, such as the human gut microbiome. In this study, LoopSeq is used to obtain near-full length (approximately 1,400–1,500 nucleotides) bacterial 16S rRNA gene sequences from hydrothermal sediments in Guaymas Basin. Based on these sequences, high-quality alignments and phylogenetic analyses provided new insights into previously unrecognized taxonomic diversity of sulfur-cycling microorganisms and their distribution along a lateral hydrothermal gradient. Detailed phylogenies for free-living and syntrophic sulfur-cycling bacterial lineages identified well-supported monophyletic clusters that have implications for the taxonomic classification of these groups. Particularly, we identify clusters within Candidatus Desulfofervidus that represent unexplored physiological and genomic diversity. In general, LoopSeq-derived 16S rRNA gene sequences aligned consistently with reference sequences in GenBank; however, chimeras were prevalent in sequences as affiliated with the thermophilic Candidatus Desulfofervidus and Thermodesulfobacterium, and in smaller numbers within the sulfur-oxidizing family Beggiatoaceae. Our analysis of sediments along a well-documented thermal and geochemical gradient show how lineages affiliated with different sulfur-cycling taxonomic groups persist throughout surficial hydrothermal sediments in the Guaymas Basin
Exploring Demographic Disparities in Private Well Water Testing in North Carolina
Get PDFThe natural, built, and social environments shape drinking water quality supplied by private wells. However, the combined effects of these factors are not well understood. Using North Carolina as a case study, we (i) estimate the demographic characteristics of the private well population; (ii) evaluate representation in well testing records; and (iii) demonstrate how spatial scale influences knowledge of well-using household demographics and representation in testing. We leverage a statewide database of 117,960 well testing records collected over 20 years and a national model predicting well locations. An estimated 25% well-using households identify as Black, Indigenous, and Persons of Color (BIPOC) and 15% have incomes below the poverty threshold. While there is robust well sampling (an average of 4,269 wells tested annually), we observed that most testing records were from predominately White block groups (BGs). Well-using households that did not participate in state testing were 2.4 times more likely to be from predominately BIPOC BGs compared predominately White BGs. Due to the spatial heterogeneity of the well population, demographic differences in well populations were more evident using higher resolution data. Multifaceted testing approaches that couple government-driven efforts with localized studies that engage underrepresented communities are needed to facilitate evidence-based management
Alloreactive-free CAR-VST therapy: a step forward in long-term tumor control in viral context
Get PDFCAR-T cell therapy has revolutionized immunotherapy but its allogeneic application, using various strategies, faces significant challenges including graft-versus-host disease and graft rejection. Recent advances using Virus Specific T cells to generate CAR-VST have demonstrated potential for enhanced persistence and antitumor efficacy, positioning CAR-VSTs as a promising alternative to conventional CAR-T cells in an allogeneic setting. This review provides a comprehensive overview of CAR-VST development, emphasizing strategies to mitigate immunogenicity, such as using a specialized TCR, and approaches to improve therapeutic persistence against host immune responses. In this review, we discuss the production methods of CAR-VSTs and explore optimization strategies to enhance their functionality, activation profiles, memory persistence, and exhaustion resistance. Emphasis is placed on their unique dual specificity for both antitumor and antiviral responses, along with an in-depth examination of preclinical and clinical outcomes. We highlight how these advances contribute to the efficacy and durability of CAR-VSTs in therapeutic settings, offering new perspectives for broad clinical applications. By focusing on the key mechanisms that enable CAR-VSTs to address autologous CAR-T cell challenges, this review highlights their potential as a promising strategy for developing effective allogeneic CAR-T therapies
The association between neighborhood social vulnerability and community-based rehabilitation after stroke
Get PDFBackground Timely rehabilitative care is vital for functional recovery after stroke. Social determinants may influence access to and use of post-stroke care but have been inadequately explored. The study examined the relationship between the Social Vulnerability Index (SVI) and community-based rehabilitation utilization. Methods We included 6,843 adults (51.6% female; 75.1% White; mean age 70.1) discharged home after a stroke enrolled in the COMprehensive Post-Acute Stroke Services study, a pragmatic trial conducted in 40 North Carolina hospitals from 2016–2019. Rehabilitation utilization was sourced from administrative claims. Geocoded addresses were linked to 2018 Census tract SVI. Associations between SVI and 90-day rehabilitation use, adjusted for patient’s clinical and socio-economic characteristics, were obtained from generalized estimating equations. We also examined the associations of SVI with therapy setting, types of therapy, intensity of visits, and time to first visit. Results Thirty-five percent of patients had at least one physical (PT) or occupational therapy (OT) visit within 90 days, ranging from 32.4%-38.7% across SVI quintiles. In adjusted analysis, there was no dose-reponse relationship between higher summary SVI, nor most of its sub-domains, and 90-day rehabilitation use. Greater vulnerability in household composition and disability was modestly associated with -0.4% (95% CI -4.1% to 3.4%) to -4.3% (95% CI -0.8% to -7.7%) lower rehabilitation use across SVI quartiles. Greater summary and subdomain SVI was associated with higher odds of receiving therapy in the home versus outpatient clinic (OR = 1.88, 1.58 to 2.17 for Q5 vs Q1 summary SVI) and receiving both PT and OT versus a single-type therapy (1.72, 1.48 to 1.97 for Q5 vs. Q1 summary SVI). No differences were observed for therapy intensity or time to therapy. Conclusion Use of rehabilitation care was low, and largely similar across levels of SVI and most of its subdomains. Individuals residing in areas of high SVI were more likely to receive therapy in the home and to receive dual therapy, possibly reflecting greater need among these individuals. Future studies should evaluate potential mechanisms for these findings and further identify both patient and community factors that may inform strategies to improve rehabilitation use.Clinical Trial Numberhttps://www.clinicaltrials.gov/ NCT02588664 [registration date: 2015–10-23]
The Links Between Community-Based Financial Inclusion and Household Food Availability: Evidence from Mozambique
Get PDFFinancial inclusion can boost wealth, health, and quality of life. However, few studies have examined how women’s participation in community-based financial inclusion opportunities, such as village saving and loan groups (VSLGs), relates to household food security. Using program data from central Mozambique, this study examined whether low-income women’s participation in VSLGs directly increases household food availability, as well as indirectly through increased asset ownership. Employing a post-test-only comparison group quasi-experimental design, the study sampled 205 female VSLG participants and non-participants from three sub-villages in Mozambique’s Sofala province. Structural equation modeling (SEM) results indicated that low-income women’s participation in VSLGs is directly associated with a reduction in household hunger score (β = −0.21, p < 0.01), as well as indirectly associated through the mediating role of household assets ([Sobel indirect effect] = −0.06, p = 0.05). The VSLG participants showed a significant increase in household asset ownership compared to non-VSLG participants (β = 0.15, p < 0.05). Further, increased asset ownership significantly correlated with a lower probability of household hunger (β = −0.30, p < 0.01). The results suggest that community-based financial inclusion approaches could improve the availability of food through asset building among Mozambique’s low-income women. The study offers a potential strategy for policymakers and development experts to utilize community approaches to financial inclusion to improve rural and low-income women’s livelihoods
Artificial Intelligence–Guided Lung Ultrasound by Nonexperts
Get PDFImportance: Lung ultrasound (LUS) aids in the diagnosis of patients with dyspnea, including those with cardiogenic pulmonary edema, but requires technical proficiency for image acquisition. Previous research has demonstrated the effectiveness of artificial intelligence (AI) in guiding novice users to acquire high-quality cardiac ultrasound images, suggesting its potential for broader use in LUS. Objective: To evaluate the ability of AI to guide acquisition of diagnostic-quality LUS images by trained health care professionals (THCPs). Design, Setting, and Participants: In this multicenter diagnostic validation study conducted between July 2023 and December 2023, participants aged 21 years or older with shortness of breath recruited from 4 clinical sites underwent 2 ultrasound examinations: 1 examination by a THCP operator using Lung Guidance AI and the other by a trained LUS expert without AI. The THCPs (including medical assistants, respiratory therapists, and nurses) underwent standardized AI training for LUS acquisition before participation. Interventions: Lung Guidance AI software uses deep learning algorithms guiding LUS image acquisition and B-line annotation. Using an 8-zone LUS protocol, the AI software automatically captures images of diagnostic quality. Main Outcomes and Measures: The primary end point was the proportion of THCP-acquired examinations of diagnostic quality according to a panel of 5 masked expert LUS readers, who provided remote review and ground truth validation. Results: The intention-to-treat analysis included 176 participants (81 female participants [46.0%]; mean [SD] age, 63 [14] years; mean [SD] body mass index, 31 [8]). Overall, 98.3% (95% CI, 95.1%-99.4%) of THCP-acquired studies were of diagnostic quality, with no statistically significant difference in quality compared to LUS expert-acquired studies (difference, 1.7%; 95% CI, -1.6% to 5.0%). Conclusions and Relevance: In this multicenter validation study, THCPs with AI assistance achieved LUS images meeting diagnostic standards compared with LUS experts without AI. This technology could extend access to LUS to underserved areas lacking expert personnel. Trial Registration: ClinicalTrials.gov Identifier: NCT05992324
Racial residential segregation is associated with ambient air pollution exposure after adjustment for multilevel sociodemographic factors: Evidence from eight US-based cohorts
Get PDFObjective: We examined if racial residential segregation (RRS) – a fundamental cause of disease – is independently associated with air pollution after accounting for other neighborhood and individual-level sociodemographic factors, to better understand its potential role as a confounder of air pollution-health studies.
Methods: We compiled data from eight large cohorts, restricting to non-Hispanic Black and White urban-residing participants observed at least once between 1999 and 2005. We used 2000 decennial census data to derive a spatial RRS measure (divergence index) and neighborhood socioeconomic status (NSES) index for participants’ residing Census tracts, in addition to participant baseline data, to examine associations between RRS and sociodemographic factors (NSES, education, race) and residential exposure to spatiotemporal model-predicted PM2.5 and NO2 levels. We fit random-effects meta-analysis models to pool estimates across adjusted cohort-specific multilevel models.
Results: Analytic sample included eligible participants in CHS (N = 3,605), MESA (4,785), REGARDS (22,649), NHS (90,415), NHSII (91,654), HPFS (32,625), WHI-OS (77,680), and WHI-CT (56,639). In adjusted univariate models, a quartile higher RRS was associated with 3.73% higher PM2.5 exposure (95% CI: 2.14%, 5.32%), and an 11.53% higher (95% CI: 10.83%, 12.22%) NO2 exposure on average. In fully adjusted models, higher RRS was associated with 3.25% higher PM2.5 exposure (95% CI: 1.45%, 5.05%; P < 0.05) and 10.22% higher NO2 exposure (95% CI: 6.69%, 13.74%; P < 0.001) on average.
Conclusions: Our findings indicate that RRS is associated with the differential distribution of poor air quality independent of NSES or individual race, suggesting it may be a relevant confounder to be considered in future air pollution epidemiology studies
Estimating the generation time for influenza transmission using household data in the United States
Get PDFThe generation time, representing the interval between infections in primary and secondary cases, is essential for understanding and predicting the transmission dynamics of seasonal influenza, including the real-time effective reproduction number (Rt). However, comprehensive generation time estimates for seasonal influenza, especially since the 2009 influenza pandemic, are lacking. We estimated the generation time utilizing data from a 7-site case-ascertained household study in the United States over two influenza seasons, 2021/2022 and 2022/2023. More than 200 individuals who tested positive for influenza and their household contacts were enrolled within 7 days of the first illness in the household. All participants were prospectively followed for 10 days, completing daily symptom diaries and collecting nasal swabs, which were then tested for influenza via RT-PCR. We analyzed these data by modifying a previously published Bayesian data augmentation approach that imputes infection times of cases to obtain both intrinsic (assuming no susceptible depletion) and realized (observed within household) generation times. We assessed the robustness of the generation time estimate by varying the incubation period, and generated estimates of the proportion of transmission occurring before symptomatic onset, the infectious period, and the latent period. We estimated a mean intrinsic generation time of 3.2 (95% credible interval, CrI: 2.9-3.6) days, with a realized household generation time of 2.8 (95% CrI: 2.7-3.0) days. The generation time exhibited limited sensitivity to incubation period variation. Estimates of the proportion of transmission that occurred before symptom onset, the infectious period, and the latent period were sensitive to variations in the incubation period. Our study contributes to the ongoing efforts to refine estimates of the generation time for influenza. Our estimates, derived from recent data following the COVID-19 pandemic, are consistent with previous pre-pandemic estimates, and will be incorporated into real-time Rt estimation efforts
Prevalence, predisposing factors, and turnover intention related to low back pain among health workers in Accra, Ghana
Get PDFBackground Globally, low back pain (LBP) is responsible for disability among 60.1 million people. Health workers face a higher likelihood of being exposed to LBP compared to employees in the construction and manufacturing sectors. Data on LBP among hospital workers in Ghana are however limited. This study examined the prevalence, predisposing factors and turnover intention related to LBP among health workers in the Greater Accra region of Ghana.
Methods A multi-centred facility-based cross-sectional study was conducted in the Greater Accra region from January 30 –May 31, 2023. A multi-stage sampling technique was adopted, and the study participants were selected through proportion-to-size simple random sampling. STATA 15 software was used for analysis. Logistic regression analysis was used to determine the factors associated with LBP at a p < 0.05.
Results A survey was conducted among 607 health workers in 10 public and private hospitals. The prevalence of LBP was 81.6% [95% CI: (78.2%-84.6%)]. Advanced age [AOR = 1.07 (1.00, 1.16)], working for more than 5 days in a week [AOR = 8.14 (2.65, 25.02)], working overtime [AOR = 2.00 (1.16, 3.46)], rarely involved in transferring patients [AOR = 3.22 (1.08, 9.60)], most of the time involved in transferring patients [AOR = 6.95 (2.07, 23.26)], awkward posture during work [(AOR = 2.36 (1.31, 4.25)], perceived understaffing [(AOR = 1.84 (95% CI = 1.04–3.27)], sleep duration ≥ 8 [AOR = 0.54 (0.31, 0.97)] and sitting intermittently at work [AOR = 0.31 (0.12, 0.80)] were factors significantly associated with LBP. A substantial number, 123 (24.9%), occasionally had intention of leaving their jobs.
Conclusion The study revealed a high proportion of low back pain (LBP), and turnover intention attributed to LBP. Moreover, organizational and occupational factors were found to be significantly associated with LBP. These findings underscore the importance of targeted interventions aimed at reducing the burden of LBP within these specific areas
Changes in urinary concentrations of contemporary and emerging chemicals in commerce during the COVID-19 pandemic: Insights from the Environmental influences on Child Health Outcomes (ECHO) program
Get PDFPrevious research indicates that the COVID-19 pandemic catalyzed alterations in behaviors that may impact exposures to environmental endocrine-disrupting chemicals. This includes changes in the use of chemicals found in consumer products, food packaging, and exposure to air pollutants. Within the Environmental influences on Child Health Outcomes (ECHO) program, a national consortium initiated to understand the effects of environmental exposures on child health and development, our objective was to assess whether urinary concentrations of a wide range of potential endocrine-disrupting chemicals varied before and during the pandemic. Drawing from three racially, ethnically, and socioeconomically diverse ECHO cohorts, we assessed key differences in urinary chemical concentrations related to environmental exposures through food packaging, use of disinfectants, personal care products and air pollutants using repeated urine samples in a subset of 47 participants, who contributed a urine sample prior to the pandemic (between October 2018 and February 2020) and a subsequent urine sample after the pandemic began (between March 2020 and April 2021). We measured urinary concentrations of analytes across several chemical groups, including polycyclic aromatic hydrocarbons (PAHs), phthalates/alternative plasticizers, synthetic phenols (parabens, bisphenols, triclosan, benzophenones), organophosphate esters (OPEs), insecticides and fungicides. Multivariable linear mixed models accounting for key covariates and clustering within cohort and across repeated samples were used to estimate the change in urinary analyte concentrations across time points. We observed decreases in urinary concentrations of some PAHs, bisphenols, benzophenones, and triclosan, and increases in specific OPEs. These biomarker data mirror some of the behavior changes reported in our prior work and support the observation that the pandemic-related behavior changes lead to alterations in chemical exposures that have been linked to adverse health outcomes