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The Transforming Growth Factor beta (TGF-β) family consists of numerous secreted peptide growth factors that play significant roles in cell function, tissue patterning, and organismal homeostasis, including wound repair and immunity. Typically studied as homodimers, these ligands have the potential to diversify their functions through ligand interactions that may enhance, repress, or generate novel functions. In the nematode Caenorhabditis elegans, there are only five TGF-β ligands, providing an opportunity to dissect ligand interactions in fewer combinations than in vertebrates. As in vertebrates, these ligands can be divided into bone morphogenetic protein (BMP) and TGF-β/Activin subfamilies that predominantly signal through discrete signaling pathways. The BMP subfamily ligand DBL-1 has been well studied for its role in the innate immune response in C. elegans. Here we show that all five TGF-β ligands play a role in survival on bacterial pathogens. We also demonstrate that multiple TGF-β ligand pairs act nonredundantly as part of this response. We show that the two BMP-like ligands–DBL-1 and TIG-2 –function independently of each other in the immune response, while TIG2/BMP and the TGF-β/Activin-like ligand TIG-3 function together. Structural modeling supports the potential for TIG-2 and TIG-3 to form heterodimers. Additionally, we identify TIG-2 and TIG-3 as members of a rare subset of TGF-β ligands lacking the conserved cysteine responsible for disulfide linking mature dimers. Finally, we show that canonical DBL1/BMP receptor and Smad signal transducers function in the response to bacterial pathogens, while components of the DAF7 TGF-β/Activin signaling pathway do not play a major role in survival. These results demonstrate a novel potential for BMP and TGF-β/Activin subfamily ligands to interact and may provide a mechanism for distinguishing the developmental and homeostatic functions of these ligands from an acute response such as the innate immune response to bacterial pathogens. Author summary: The first line of defense upon exposure to a pathogen consists of innate immunity, which includes barrier functions and cell-cell communication. These cell-cell communication signaling pathways are highly conserved across species, enabling the use of simpler genetically tractable model organisms for their study. One such signaling pathway is the Transforming Growth Factor beta (TGF-β) pathway, which is conserved from invertebrates to vertebrates. TGF-β signaling ligands can be broadly divided into two major groups: the TGF-β/Activin group and the bone morphogenetic protein (BMP) group. There is compelling evidence that heterodimers have biological activities that differ from homodimers, but to this time, heterodimers have only been observed within subfamilies and not across subfamilies. In humans, there are 33 TGF-β ligands. In comparison, there are only five ligands in the nematode C. elegans, providing an opportunity to dissect ligand interactions in fewer combinations than in vertebrates. In this work, we show that all five ligands contribute to survival on bacterial pathogens to different extents and with specificity concerning the pathogen. Strikingly, genetic evidence and structural modeling support the existence of cross-subfamily interaction between BMP and TGF-β/Activin ligands. [ABSTRACT FROM AUTHOR]

In Canada, extreme heat occurrences present significant risks to public health, particularly for vulnerable groups like older individuals and those with preexisting health conditions. Accurately predicting indoor temperatures during these events is crucial for informing public health strategies and mitigating the adverse impacts of extreme heat. While current systems rely on outdoor temperature data, incorporating real-time indoor temperature estimations can significantly enhance decision-making and strengthen overall health system responses. Sensor-based technologies, such as ecobee smart thermostats installed in homes, enable effortless collection of indoor temperature and humidity data. This study evaluates the efficacy of deep learning models in predicting indoor temperatures during heat waves using smart thermostat data, to enhance public health responses. Utilizing ecobee smart thermostats, we analyzed indoor temperature trends and developed forecasting models. Our findings indicate the potential of integrating IoT and deep learning into health warning systems, enabling proactive interventions, and improving sustainable health care practices in extreme heat scenarios. This approach highlights the role of digital health innovations in creating the resilient and sustainable healthcare systems against climate-related health adversities. [ABSTRACT FROM AUTHOR]

Atrial fibrillation (AF) recurrence has become common in patients who have undergone catheter ablation. High neutrophil lymphocyte ratios (NLR) have been linked to an increased risk of recurrent AF. The research is, however, not conclusive. This meta-analysis addressed the value of easily accessible and affordable pre-and postablation NLR levels as indicators of AF recurrence in patients who had undergone ablation. We searched PubMed, SCOPUS, and Google Scholar for pertinent studies through May 2023. Using random effects models, the aggregated odds ratio (OR) of pre-and post-NLR and AF recurrence was estimated. Inter-study heterogeneity was described using I² statistics and leave-one-out sensitivity analysis. A p-value < .05 was considered statistically significant. The literature search yielded 270 studies, seven of which were included in this meta-analysis of 1923 patients who experienced AF recurrence after undergoing ablation. There are five retrospective and two prospective studies with a mean follow-up of 20.5 months. The unadjusted odds ratio (OR) of AF recurrence for preablation NLR was 1.33 (95% CI: 1.04-1.71, p < .01, I² = 95.49%), while the adjusted OR was 1.45 (95% CI: 0.87-2.43, p < .01, I² = 95.1%). The unadjusted odds ratio (OR) for postablation NLR was 1.21 (95% CI: 1.09-1.36, p < .01, I² = 85.9%), and the adjusted odds ratio (OR) was 1.28 (95% CI: 0.93-1.76), demonstrating significant heterogeneity (I² = 95.32%) with a p-value < .01. NLR was significantly associated with AF recurrence prediction. To detect AF recurrence, we recommend that clinicians add a simple NLR blood test to their diagnostic modalities. [ABSTRACT FROM AUTHOR]

Our study aimed to assess the effect of weekend versus weekday hospital admissions on all-cause mortality in patients with acute myocardial infarction (AMI) and COVID-19 during the COVID-19 pandemic. We analyzed data from the National Inpatient Sample (NIS) 2020, identifying patients with co-existing AMI and COVID-19 admitted on weekdays and weekends. Baseline demographics, comorbidities, and outcomes were assessed. A multivariable regression analysis was conducted, adjusting for confounders to determine the odds of all-cause mortality. Among 74,820 patients, 55,145 (73.7%) were admitted on weekdays, while 19,675 (26.3%) were admitted on weekends. Weekend admissions showed slightly higher proportions of men (61.3% vs. 60%) and whites (56.3% vs. 54.9%) with a median age of 73 years (range: 62-82). The overall all-cause mortality had an odds ratio (OR) of 1.00 (95% CI, 0.92-1.09; P = 0.934). After adjusting for covariates, there was no significant associations between mortality and hospital type (rural: OR = 1.04; 95% CI, 0.78-1.39; P = 0.789; urban teaching: OR = 1.04; 95% CI, 0.94-1.14; P = 0.450) or geographic region (Northeast: OR = 1.16; 95% CI, 0.96-1.39; P = 0.12; Midwest: OR = 0.99; 95% CI, 0.83-1.17; P = 0.871; South: OR = 0.97; 95% CI, 0.85-1.12; P = 0.697; West: OR = 0.94; 95% CI, 0.77-1.15; P = 0.554). There was no significant difference in the rate of all-cause mortality among patients admitted for AMI and COVID-19 between weekdays and weekends. [ABSTRACT FROM AUTHOR]

Byline: Birinder. Paul, Gurjot. Singh, Nahush. Bansal, Gaganeep. Singh, Gunchan. Paul Background: Dopaminergic medications administered to remedy motor symptoms in Parkinson's disease are associated with an enhanced risk for impulse [...]

Introduction Retrograde ureteroscopy with holmium laser lithotripsy (HLL) is a standard treatment for urolithiasis. Moses technology has been shown to improve fragmentation efficiency in vitro; however, it is still unclear how it performs clinically compared to standard HLL. We performed a systematic review and meta-analysis evaluating the differences in efficiency and outcomes between Moses mode and standard HLL. Material and methods We searched the MEDLINE, EMBASE, and CENTRAL databases for randomized clinical trials and cohort studies comparing Moses mode and standard HLL in adults with urolithiasis. Outcomes of interest included operative (operation, fragmentation, and lasing times; total energy used; and ablation speed) and perioperative parameters (stone-free rate and overall complication rate). Results The search identified six studies eligible for analysis. Compared to standard HLL, Moses was associated with significantly shorter average lasing time (mean difference [MD] -0.95, 95% confidence interval [CI] -1.22 to -0.69 minutes), faster stone ablation speed (MD 30.45, 95% CI 11.56-49.33 mm3/min), and higher energy used (MD 1.04, 95% CI 0.33-1.76 kJ). Moses and standard HLL were not significantly different in terms of operation (MD -9.89, 95% CI -25.14 to 5.37 minutes) and fragmentation times (MD -1.71, 95% CI -11.81 to 8.38 minutes), as well as stone-free (odds ratio [OR] 1.04, 95% CI 0.73-1.49) and overall complication rates (OR 0.68, 95% CI 0.39-1.17). Conclusions While perioperative outcomes were equivalent between Moses and standard HLL, Moses was associated with faster lasing time and stone ablation speeds at the expense of higher energy usage. [ABSTRACT FROM AUTHOR]