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Abstract Cardiotrophin-like cytokine factor 1 (CLCF1) is an IL-6 family cytokine with neurotrophic and immuno-modulating functions. CLCF1 mRNA has been detected in primary and secondary lymphoid organs, and up-regulation of CLCF1 mRNA levels has been associated with the T helper (Th) 17 polarization. However, information regarding CLCF1 expression by immune cells at the protein level remains scarce. We have developed a methodology that uses a monoclonal antibody (mAb) directed against CLCF1 for the detection of human and mouse CLCF1 by flow cytometry. We have successfully detected CLCF1 protein expression in cells from the mouse pro-B cell line Ba/F3 that were transduced with CLCF1 cDNA. Interestingly, we found that the anti-CLCF1 mAb inhibits CLCF1 biological activity in vitro by binding to an epitope that encompasses site III of the cytokine. Moreover, we have detected CLCF1 expression in mouse splenic T cells, as well as in vitro differentiated Th1 cells. The specificity of the fluorescence signal was demonstrated using Clcf1-deficient lymphocytes generated using a conditional knock-out mouse model. The detection of CLCF1 protein by flow cytometry will be a valuable tool to study CLCF1 expression during normal and pathological immune responses.

Artificial intelligence in surgery has seen an expansive rise in research and clinical implementation in recent years, with many of the models being driven by machine learning. In the preoperative setting, machine learning models have been utilized to guide indications for surgery, appropriate timing of operations, calculation of risks and prognostication, along with improving estimations of time and resources required for surgeries. Intraoperative applications that have been demonstrated are visual annotations of the surgical field, automated classification of surgical phases and prediction of intraoperative patient decompensation. Postoperative applications have been studied the most, with most efforts put towards prediction of postoperative complications, recurrence patterns of malignancy, enhanced surgical education and assessment of surgical skill. Challenges to implementation of these models in clinical practice include the need for more quantity and quality of standardized data to improve model performance, sufficient resources and infrastructure to train and use machine learning, along with addressing ethical and patient acceptance considerations.

Background: Clostridioides difficile infection (CDI) has been linked to over 200,000 cases of illness in hospitalized patients and over 20,000 deaths annually. Up to 25% of patients with an initial CDI episode will experience recurrent CDI (rCDI), which most commonly occurs in the first 8 weeks following antibiotic therapy. In patients with first or multiple rCDI, infection, the microbiome is similarly disrupted, which highlights the challenges of using antibiotics alone while underscoring the need for microbiome restoration regardless of the number of recurrences. In this systematic review, we describe the role of the gastrointestinal microbiome in CDI, and systematically review fecal microbiota spores, live-brpk (VOWST™; VOS for Vowst Oral Spores) for prevention of recurrence in rCDI. Methods: The PubMed database was searched using “recurrent Clostridioides difficile infection” AND (SER-109 OR VOS) and limited to clinical trials. The search yielded 7 results: 3 articles describing 3 clinical trials (two Phase 3 trials (ECOSPOR III and ECOSPOR IV) and one Phase 2 trial (ECOSPOR)), 1 describing follow-up of ECOSPOR III, 1 describing a post hoc analysis of comorbidities in ECOSPOR III, and 2 describing health-related quality of life in ECOSPOR III. Results: Compared with placebo, VOS following standard-of-care antibiotics for CDI significantly reduced risk of recurrence at 8 weeks (relative risk, 0.32 (95% CI: 0.18–0.58); p

Although the role of RNA binding proteins (RBPs) in extracellular RNA (exRNA) biology is well established, their exRNA cargo and distribution across biofluids are largely unknown. To address this gap, we extend the exRNA Atlas resource by mapping exRNAs carried by extracellular RBPs (exRBPs). This map was developed through an integrative analysis of ENCODE enhanced crosslinking and immunoprecipitation (eCLIP) data (150 RBPs) and human exRNA profiles (6,930 samples). Computational analysis and experimental validation identified exRBPs in plasma, serum, saliva, urine, cerebrospinal fluid, and cell-culture-conditioned medium. exRBPs carry exRNA transcripts from small non-coding RNA biotypes, including microRNA (miRNA), piRNA, tRNA, small nuclear RNA (snRNA), small nucleolar RNA (snoRNA), Y RNA, and lncRNA, as well as protein-coding mRNA fragments. Computational deconvolution of exRBP RNA cargo reveals associations of exRBPs with extracellular vesicles, lipoproteins, and ribonucleoproteins across human biofluids. Overall, we mapped the distribution of exRBPs across human biofluids, presenting a resource for the community.

Abstract Drug-recalcitrant infections are a leading global-health concern. Bacterial cells benefit from phenotypic variation, which can suggest effective antimicrobial strategies. However, probing phenotypic variation entails spatiotemporal analysis of individual cells that is technically challenging, and hard to integrate into drug discovery. In this work, we develop a multi-condition microfluidic platform suitable for imaging two-dimensional growth of bacterial cells during transitions between separate environmental conditions. With this platform, we implement a dynamic single-cell screening for pheno-tuning compounds, which induce a phenotypic change and decrease cell-to-cell variation, aiming to undermine the entire bacterial population and make it more vulnerable to other drugs. We apply this strategy to mycobacteria, as tuberculosis poses a major public-health threat. Our lead compound impairs Mycobacterium tuberculosis via a peculiar mode of action and enhances other anti-tubercular drugs. This work proves that harnessing phenotypic variation represents a successful approach to tackle pathogens that are increasingly difficult to treat.

Abstract Introduction Disasters such as earthquakes, conflict, or landslides result in traumatic injuries creating surges in rehabilitation and assistive technology needs, exacerbating pre-existing unmet needs. Disasters frequently occur in countries where existing rehabilitation services are underdeveloped, hindering response to rehabilitation demand surge events. Aims The primary aim of this scoping review is therefore to synthesize the evidence on rehabilitation and assistive technology preparedness and response of health systems in LMICs to the demand associated with disasters and conflict situations. A secondary aim was to summarize related recommendations identified in the gathered literature. Methodology A scoping review was conducted using the Arksey and O’Malley framework to guide the methodological development. The results are reported in accordance with PRISMA-ScR. Four bibliographic databases were used: CINHAL, Cochrane, Pubmed, Scopus and. Key international organisations were also contacted. The search period was from 2010–2022. Eligible publications were categorized for analysis under the six World Health Organization health systems buildings blocks. Results The findings of this scoping review suggest that rehabilitation is poorly integrated into health systems disaster preparedness and response in LMICs. Of the 27 studies included in the scoping review, 14 focused on service delivery, 6 on health workforce, 4 on health information systems and 3 on the leadership and governance building block. No study focused on financing nor assistive technology. This review found the most frequently referenced recommendations for actions that should be taken to develop rehabilitation services in disasters to be: the provision early and multi-professional rehabilitation, including the provision of assistive technology and psychological support, integrated community services; disaster response specific training for rehabilitation professionals; advocacy efforts to create awareness of the importance of rehabilitation in disasters; and the integration of rehabilitation into disaster preparedness and response plans. Conclusion Findings of this scoping review suggest that rehabilitation is poorly integrated into health systems disaster preparedness and response in LMIC's, largely due to low awareness of rehabilitation, undeveloped rehabilitation health systems and a lack of rehabilitation professionals, and disaster specific training for them. The paucity of available evidence hinders advocacy efforts for rehabilitation in disaster settings and limits the sharing of experiences and lessons learnt to improve rehabilitation preparedness and response. Advocacy efforts need to be expanded.

Dengue virus (DENV) is a Flavivirus that causes the most prevalent arthropod-borne viral disease. Clinical manifestation of DENV infection ranges from asymptomatic to severe symptoms that can lead to death. Unfortunately, no antiviral treatments against DENV are currently available. In order to identify novel DENV inhibitors, we screened a library of 1,604 chemically diversified fragment-based compounds using DENV reporter viruses that allowed quantification of viral replication in infected cells. Following a validation screening, the two best inhibitor candidates were N-phenylpyridine-3-carboxamide (NPP3C) and 6-acetyl-1H-indazole (6A1HI). The half maximal effective concentration of NPP3C and 6A1H1 against DENV were 7.1 μM and 6.5 μM, respectively. 6A1H1 decreased infectious DENV particle production up to 1,000-fold without any cytotoxicity at the used concentrations. While 6A1HI was DENV-specific, NPP3C also inhibited the replication of other flaviviruses such as West Nile virus and Zika virus. Structure-activity relationship (SAR) studies with 151 analogues revealed key structural elements of NPP3C and 6A1HI required for their antiviral activity. Time-of-drug-addition experiments identified a postentry step as a target of these compounds. Consistently, using a DENV subgenomic replicon, we demonstrated that these compounds specifically impede the viral RNA replication step and exhibit a high genetic barrier-to-resistance. In contrast, viral RNA translation and the de novo biogenesis of DENV replication organelles were not affected. Overall, our data unveil NPP3C and 6A1H1 as novel DENV inhibitors. The information revealed by our SAR studies will help chemically optimize NPP3C and 6A1H1 in order to improve their anti-flaviviral potency and to challenge them in in vivo models.

In spring 2021, Nepal underwent a record wildfire season in which active fires were detected at a rate 10 times greater than the 2002–2020 average. Prior to these major wildfire events, the country experienced a prolonged precipitation deficit and extreme drought during the post-monsoon period (starting in October 2020). An analysis using observational, reanalysis, and climate model ensemble data indicates that both climate variability and climate change-induced severe drought conditions were at play. Further analysis of climate model outputs suggests the likely reoccurrence of drought conditions, thus favoring active wildfire seasons in Nepal throughout the twenty-first century. While the inter-model uncertainty is large and direct modeling of wildfire spread and suppression has not been completed, the demonstrated relationship between a drought index (the standardized precipitation and evapotranspiration index) and subsequent fire activity may offer actionable opportunities for forest managers to employ the monitoring and projection of climate anomalies at sub-seasonal to decadal timescales to inform their management strategies for Nepal’s wildlands.

Background Major bile duct injuries during laparoscopic cholecystectomy (LC), often stemming from errors in surgical judgment and visual misperception of critical anatomy, significantly impact morbidity, mortality, disability, and health care costs. Objective To enhance safe LC learning, we developed an educational mobile game, LapBot Safe Chole, which uses an artificial intelligence (AI) model to provide real-time coaching and feedback, improving intraoperative decision-making. Methods LapBot Safe Chole offers a free, accessible simulated learning experience with real-time AI feedback. Players engage with intraoperative LC scenarios (short video clips) and identify ideal dissection zones. After the response, users receive an accuracy score from a validated AI algorithm. The game consists of 5 levels of increasing difficulty based on the Parkland grading scale for cholecystitis. Results Beta testing (n=29) showed score improvements with each round, with attendings and senior trainees achieving top scores faster than junior residents. Learning curves and progression distinguished candidates, with a significant association between user level and scores (P=.003). Players found LapBot enjoyable and educational. Conclusions LapBot Safe Chole effectively integrates safe LC principles into a fun, accessible, and educational game using AI-generated feedback. Initial beta testing supports the validity of the assessment scores and suggests high adoption and engagement potential among surgical trainees.

Lysosomes coordinate cellular metabolism and growth upon sensing of essential nutrients, including cholesterol. Through bioinformatic analysis of lysosomal proteomes, we identified lysosomal cholesterol signaling (LYCHOS, previously annotated as G protein-coupled receptor 155), a multidomain transmembrane protein that enables cholesterol-dependent activation of the master growth regulator, the protein kinase mechanistic target of rapamycin complex 1 (mTORC1). Cholesterol bound to the amino-terminal permease-like region of LYCHOS, and mutating this site impaired mTORC1 activation. At high cholesterol concentrations, LYCHOS bound to the GATOR1 complex, a guanosine triphosphatase (GTPase)-activating protein for the Rag GTPases, through a conserved cytoplasm-facing loop. By sequestering GATOR1, LYCHOS promotes cholesterol- and Rag-dependent recruitment of mTORC1 to lysosomes. Thus, LYCHOS functions in a lysosomal pathway for cholesterol sensing and couples cholesterol concentrations to mTORC1-dependent anabolic signaling.

Abstract Introduction Limited data exist regarding real-world utilization of nirmatrelvir/ritonavir. We identified predictors of nirmatrelvir/ritonavir use among Veterans Affairs (VA) outpatients nationally. Methods We conducted a retrospective cohort study among outpatients with coronavirus disease 2019 (COVID-19) who were eligible to receive nirmatrelvir/ritonavir between January and December of 2022, to identify factors associated with nirmatrelvir/ritonavir use (i.e., demographics, medical history, prior medication and healthcare exposures, frailty, and other clinical characteristics) using multivariable logistic regression. Results We included 309,755 outpatients with COVID-19 who were eligible for nirmatrelvir/ritonavir, of whom 12.2% received nirmatrelvir/ritonavir. Nirmatrelvir/ritonavir uptake increased from 1.1% to 23.2% over the study period. Factors associated with nirmatrelvir/ritonavir receipt included receiving a COVID-19 booster vs. none (adjusted odds ratio [aOR] 2.19 [95% confidence interval [CI] 2.12–2.26]), age ≥ 50 vs. 18–49 years (aORs > 1.5 for all age groups ≥ 50 years), having HIV (aOR 1.36 [1.22–1.51]), being non-frail vs. severely frail (aOR 1.22 [1.13–1.33]), and having rheumatoid arthritis (aOR 1.12 [1.04–1.21). Those with concomitant use of potentially interacting antiarrhythmics (aOR 0.35 [0.28–0.45]), anticoagulants/antiplatelets (aOR 0.42 [0.40–0.45]), and/or psychiatric/sedatives (aOR 0.84 [0.81–0.87]) were less likely to receive nirmatrelvir/ritonavir. Conclusions Despite increases over time, overall utilization of nirmatrelvir/ritonavir was low. Predictors of nirmatrelvir/ritonavir utilization were consistent with known risk factors for progression to severe COVID-19, including older age and underlying medical conditions. Unvaccinated and undervaccinated patients and those receiving potentially interacting medications for cardiovascular or mental health conditions (antiarrhythmic, alpha-1 antagonist, anticoagulant/antiplatelet, sedative/hypnotic/psychiatric) were less likely to receive nirmatrelvir/ritonavir. Further education of prescribers and patients about nirmatrelvir/ritonavir treatment guidelines is needed to improve overall uptake and utilization in certain high-risk subpopulations.

Abstract Introduction Clostridioides difficile infection (CDI) causes symptoms of varying severity and negatively impacts patients’ health-related quality of life (HRQL). Despite antibiotic treatment, recurrence of CDI (rCDI) is common and imposes clinical and economic burdens on patients. Fecal microbiota, live-jslm (REBYOTA [RBL]) is newly approved in the USA for prevention of rCDI following antibiotic treatments. We analyzed efficacy and HRQL impact of RBL vs. placebo in patients at first rCDI using data from the phase 3 randomized, double-blind placebo-controlled clinical trial, PUNCH CD3. Methods This post hoc analysis included patients at first rCDI fromPUNCH CD3. Treatment success (i.e., absence of diarrhea within 8 weeks post-treatment) was analyzed adjusting for baseline patient characteristics. HRQL was measured using the Clostridioides difficile Quality of Life Survey (Cdiff32); absolute scores and change from baseline in total and domain (physical, mental, and social) scores were summarized and compared between arms. Analyses were conducted for the trial’s blinded phase only. Results Among 86 eligible patients (32.8% of the overall trial population, RBL 53 [61.6%], placebo 33 [38.4%]), RBL-treated patients had significantly lower odds of recurrence (i.e., greater probability of treatment success) at week 8 vs. placebo (odds ratio 0.35 [95% confidence interval 0.13, 0.98]). Probability of treatment success at week 8 was 81% for RBL and 60% for placebo, representing 21% absolute and 35% relative increases for RBL (crude proportions 79.2% vs. 60.6%; relative risk 0.53, p = 0.06). Additionally, RBL was associated with significantly higher Cdiff32 total (change score difference 13.5 [standard deviation 5.7], p

Abstract Background Lockdown measures of COVID-19 have had different repercussions on the well-being of households in West Africa depending on their resilience capacity. This study compares the dynamic of households’ food insecurity during COVID-19 pandemic according to their membership in different types of agricultural cooperatives in four West African countries, namely Ghana, Mali, Ivory Coast, and Senegal. Methodology We used data collected from 1270 members of agricultural cooperatives and regression analyses, to understand the link between the nature of their cooperatives and the food insecurity dynamic of their household, while controlling for other sociodemographic characteristics. Cooperative were categorized either “active” or “poorly/not active” depending on their capacity to conduct initiatives that address the needs of their members, to maintain communication between leaders and members, the participation of members to decisions, and their possession of a good understanding of business management. Food insecurity is measured using the Food Insecurity Experience Scale (FIES) and the Coping Strategy Index (CSI). Respondents were asked to answer questions related to their food security status for the period before and during the pandemic. Results The COVID-19 pandemic has adversely affected respondents' food security status. These effects varied according to the severity of sanitary measures implemented and to the dynamism of cooperatives. Households of poorly or not active cooperatives have experienced more food insecurity in Ivory Coast and Senegal than those who were members of active cooperatives; in Ghana the effects were significant but similar in both types of cooperatives. Members of both cooperatives in Mali appear to have been less affected than members in other countries. Furthermore, households of poorly/not active cooperatives have used more severe coping strategies in Ivory Coast, Ghana, and Senegal during the pandemic. Conclusions Strong collaboration and support provided by cooperatives can contribute to increase the resilience capacity of their members to shocks such as the COVID-19 pandemic.

Cytokinesis is driven in part by the constriction of a ring of actin filaments, myosin motors and other proteins. In fission yeast, three myosins contribute to cytokinesis including a Myosin-V Myo51. As Myosin-Vs typically carry cargo along actin filaments, the role of Myo51 in cytokinesis remains unclear. The previous work suggests that Myo51 may crosslink actin filaments. We hypothesized that if Myo51 crosslinks actin filaments, cells carrying double deletions of ain1, which encodes the crosslinker alpha-actinin, and myo51 (∆ain1 ∆myo51 cells) will exhibit more severe cytokinesis phenotypes than cells with the single ∆ain1 mutation. Contrary to our expectations, we found that the loss of Myo51 in ∆ain1 cells partially rescued the severity of the node clumping phenotype measured in ∆ain1 cells. Furthermore, we describe a normal process of contractile ring “shedding”, the appearance of fragments of ring material extending away from the contractile ring along the ingressing septum that occurs in the second half of constriction. We measured that ∆ain1 ∆myo51 cells exhibit premature and exaggerated shedding. Our work suggests that Myo51 is not a simple actin filament crosslinker. Instead, a role in effective node motion better recapitulates its function during ring assembly and disassembly.

The extracellular RNA communication consortium (ERCC) is an NIH-funded program aiming to promote the development of new technologies, resources, and knowledge about exRNAs and their carriers. After Phase 1 (2013-2018), Phase 2 of the program (ERCC2, 2019-2023) aims to fill critical gaps in knowledge and technology to enable rigorous and reproducible methods for separation and characterization of both bulk populations of exRNA carriers and single EVs. ERCC2 investigators are also developing new bioinformatic pipelines to promote data integration through the exRNA atlas database. ERCC2 has established several Working Groups (Resource Sharing, Reagent Development, Data Analysis and Coordination, Technology Development, nomenclature, and Scientific Outreach) to promote collaboration between ERCC2 members and the broader scientific community. We expect that ERCC2's current and future achievements will significantly improve our understanding of exRNA biology and the development of accurate and efficient exRNA-based diagnostic, prognostic, and theranostic biomarker assays.

When readers are asked to detect a target letter while reading for comprehension, they miss it more frequently when it is embedded in a frequent function word than in a less frequent content word. This missing-letter effect has been used to investigate the cognitive processes involved in reading. A similar effect, called the missing-phoneme effect has been found in aural language when participants listen to the narration of a text while searching for a target phoneme. In three experiments, we tested the hypothesis that both effects derived from the same cognitive processes, by isolating the role of word frequency and word function. In Experiment 1, we used a paper and pencil procedure for reading and a continuous narration for the listening task. In Experiments 2 and 3, we used a rapid serial visual or auditory presentation procedure to control for the effects of preprocessing upcoming information: parafoveal processing in reading and coarticulation in aural language processing. Parallel findings were observed in the reading and listening tasks. In all experiments, there was an effect of word function, and there was an effect of word frequency in Experiments 1 and 3. Results are interpreted in light of the attentional disengagement model.

Self-determination, defined by acting as the causal agent in one's life, plays a critical role in the transition from high school to postsecondary education, employment, and community living for all students, including students with significant support needs. The "Self-Determined Learning Model of Instruction" (SDLMI) is a teaching model designed to enable teachers to promote self-determined action by focusing on the goal setting and attainment process. In this article, we focus specifically on the implementation of the SDLMI with students with significant support needs, including those who have complex communication needs. We describe the SDLMI process in detail with specific examples for implementation with students with significant support needs based on several recent research studies. [For the corresponding grantee submission, see ED596342.]