Search

Deep learning (DL) models for medical image classification frequently struggle to generalize to data from outside institutions. Additional clinical data are also rarely collected to comprehensively assess and understand model performance amongst subgroups. Following the development of a single-center model to identify the lung sliding artifact on lung ultrasound (LUS), we pursued a validation strategy using external LUS data. As annotated LUS data are relatively scarce—compared to other medical imaging data—we adopted a novel technique to optimize the use of limited external data to improve model generalizability. Externally acquired LUS data from three tertiary care centers, totaling 641 clips from 238 patients, were used to assess the baseline generalizability of our lung sliding model. We then employed our novel Threshold-Aware Accumulative Fine-Tuning (TAAFT) method to fine-tune the baseline model and determine the minimum amount of data required to achieve predefined performance goals. A subgroup analysis was also performed and Grad-CAM++ explanations were examined. The final model was fine-tuned on one-third of the external dataset to achieve 0.917 sensitivity, 0.817 specificity, and 0.920 area under the receiver operator characteristic curve (AUC) on the external validation dataset, exceeding our predefined performance goals. Subgroup analyses identified LUS characteristics that most greatly challenged the model’s performance. Grad-CAM++ saliency maps highlighted clinically relevant regions on M-mode images. We report a multicenter study that exploits limited available external data to improve the generalizability and performance of our lung sliding model while identifying poorly performing subgroups to inform future iterative improvements. This approach may contribute to efficiencies for DL researchers working with smaller quantities of external validation data.

Abstract Background and objective Phenytoin is extensively protein bound with a narrow therapeutic range. The unbound phenytoin is pharmacologically active, but total concentrations are routinely measured in clinical practice. The relationship between free and total phenytoin has been described by various binding models with inconsistent findings. Systematic comparison of these binding models in a single experimental setting is warranted to determine the optimal binding behaviors. Methods Non-linear mixed-effects modeling was conducted on retrospectively collected data (n = 37 adults receiving oral or intravenous phenytoin) using a stochastic approximation expectation–maximization algorithm in MonolixSuite-2019R2. The optimal base structural model was initially developed and utilized to compare four binding models: Winter–Tozer, linear binding, non-linear single-binding site, and non-linear multiple-binding site. Each binding model was subjected to error and covariate modeling. The final model was evaluated using relative standard errors (RSEs), goodness-of-fit plots, visual predictive check, and bootstrapping. Results A one-compartment, first-order absorption, Michaelis–Menten elimination, and linear protein-binding model best described the population pharmacokinetics of free phenytoin at typical clinical concentrations. The non-linear single-binding-site model also adequately described phenytoin binding but generated larger RSEs. The non-linear multiple-binding-site model performed the worst, with no identified covariates. The optimal linear binding model suggested a relatively high binding capacity using a single albumin site. Covariate modeling indicated a positive relationship between albumin concentration and the binding proportionality constant. Conclusions The linear binding model best described the population pharmacokinetics of unbound phenytoin in adult subjects and may be used to improve the prediction of free phenytoin concentrations.

Job applicants vary in the extent to which they fake or stay honest in employment interviews, yet the contextual and demographic factors underlying these behaviors are unclear. To help answer this question, we drew on Ellingson and McFarland’s (2011) framework of faking based in valence-instrumentality-expectancy theory. Study 1 collected normative data and established baseline distributions for instrumentality-expectancy beliefs from a Canadian municipality. Results indicated that most respondents had low levels of instrumentality-expectancy beliefs for faking, but high levels for honesty. Moreover, income, education, and age were antecedents of instrumentality-expectancy beliefs. Study 2 extended these findings with a United States sample and sought to determine if they could be explained by individual differences. Results demonstrated that financial insecurity predicted instrumentality of faking, whereas age predicted expectancy of faking. Finally, valence-instrumentality-expectancy beliefs were all predictors of self-reported faking in a past interview.

Background: Annotating large medical imaging datasets is an arduous and expensive task, especially when the datasets in question are not organized according to deep learning goals. Here, we propose a method that exploits the hierarchical organization of annotating tasks to optimize efficiency. Methods: We trained a machine learning model to accurately distinguish between one of two classes of lung ultrasound (LUS) views using 2908 clips from a larger dataset. Partitioning the remaining dataset by view would reduce downstream labelling efforts by enabling annotators to focus on annotating pathological features specific to each view. Results: In a sample view-specific annotation task, we found that automatically partitioning a 780-clip dataset by view saved 42 min of manual annotation time and resulted in 55±6 additional relevant labels per hour. Conclusions: Automatic partitioning of a LUS dataset by view significantly increases annotator efficiency, resulting in higher throughput relevant to the annotating task at hand. The strategy described in this work can be applied to other hierarchical annotation schemes.

Objectives Lung ultrasound (LUS) is a portable, low-cost respiratory imaging tool but is challenged by user dependence and lack of diagnostic specificity. It is unknown whether the advantages of LUS implementation could be paired with deep learning (DL) techniques to match or exceed human-level, diagnostic specificity among similar appearing, pathological LUS images.Design A convolutional neural network (CNN) was trained on LUS images with B lines of different aetiologies. CNN diagnostic performance, as validated using a 10% data holdback set, was compared with surveyed LUS-competent physicians.Setting Two tertiary Canadian hospitals.Participants 612 LUS videos (121 381 frames) of B lines from 243 distinct patients with either (1) COVID-19 (COVID), non-COVID acute respiratory distress syndrome (NCOVID) or (3) hydrostatic pulmonary edema (HPE).Results The trained CNN performance on the independent dataset showed an ability to discriminate between COVID (area under the receiver operating characteristic curve (AUC) 1.0), NCOVID (AUC 0.934) and HPE (AUC 1.0) pathologies. This was significantly better than physician ability (AUCs of 0.697, 0.704, 0.967 for the COVID, NCOVID and HPE classes, respectively), p

Lung ultrasound (LUS) is an accurate thoracic imaging technique distinguished by its handheld size, low-cost, and lack of radiation. User dependence and poor access to training have limited the impact and dissemination of LUS outside of acute care hospital environments. Automated interpretation of LUS using deep learning can overcome these barriers by increasing accuracy while allowing point-of-care use by non-experts. In this multicenter study, we seek to automate the clinically vital distinction between A line (normal parenchyma) and B line (abnormal parenchyma) on LUS by training a customized neural network using 272,891 labelled LUS images. After external validation on 23,393 frames, pragmatic clinical application at the clip level was performed on 1162 videos. The trained classifier demonstrated an area under the receiver operating curve (AUC) of 0.96 (±0.02) through 10-fold cross-validation on local frames and an AUC of 0.93 on the external validation dataset. Clip-level inference yielded sensitivities and specificities of 90% and 92% (local) and 83% and 82% (external), respectively, for detecting the B line pattern. This study demonstrates accurate deep-learning-enabled LUS interpretation between normal and abnormal lung parenchyma on ultrasound frames while rendering diagnostically important sensitivity and specificity at the video clip level.

Abstract Background Student-run free clinics are critical for medical education and medical care of underserved populations. This paper explores the feasibility of establishing ethical preventative health services at student-run free clinics such as the Rochester Education and Advocacy for Community Health (REACH) Clinic, affiliated with the Mayo Clinic Alix School of Medicine. Our analysis discusses the challenges and ethical considerations of providing preventative healthcare in student-run clinics. This paper also provides recommendations for implementing preventative care at REACH and other student-run clinics. Methods A literature search was conducted by an experienced librarian across four databases using keywords “student-run clinics” and “preventative healthcare.” Additionally, contributing authors identified and gathered data about community service organizations that provide preventative healthcare services to residents of Rochester, MN and surrounding areas. Results The literature search yielded 50 articles, 20 of which were included in the narrative review. Vaccinations and cancer screenings were the two preventative care initiatives most commonly undertaken by student-run clinics. The benefits of student-run clinic initiatives for both patients and students were an emerging theme. Clinics often achieved high vaccination and screening rates, and integration of preventative care topics into medical curricula was valued by students. However, the limitations of student-run clinics also emerged as a theme, particularly limitations to resources and comprehensive follow-up. 15 community health organizations in/around Rochester, MN were identified; of these, five provide preventative healthcare services. Conclusion Student-run clinics like REACH play a key role in delivering preventative care to underserved populations, bridging critical gaps in our healthcare system, and benefiting patients and students alike. However, the ethical principles of beneficence and non-maleficence should be considered when student-run clinics decide what services to offer. Preventative care has been successfully implemented at other student-run clinics but requires careful arrangement of adequate follow-up care, especially when it comes to cancer screening. Vaccinations are a low-cost, high-impact initiative that can be feasibly implemented at most student-run clinics.

Patient interviewing pedagogy in medical education has not evolved to comprehensively capture the biopsychosocial model of healthcare delivery. While gathering a patient’s social history targets important aspects of social context it does not adequately capture and account for the real-time reassessment required to understand evolving factors that influence exposure to drivers of health inequities, social determinants of health, and access to supports that promote health. The authors offer a patient interviewing approach called the Contextual Interview (CI) that specifically targets dynamic and ever-changing social context information. To substantiate the use of the CI in medical education, the authors conducted a qualitative review of the Accreditation Council for Graduate Medical Education Milestones for primary care specialties (Family Medicine, Internal Medicine, and Pediatrics). Milestones were coded to the extent to which they reflected the learner’s need to acknowledge, assess, synthesize and/or apply patient contextual data in real-time patient encounters. Approximately 1 in 5 milestones met the context-related and patient-facing criteria. This milestone review further highlights the need for more intentional training in eliciting meaningful social context data during patient interviewing. The CI as a cross-cutting, practical, time-conscious, and semi-structured patient interviewing approach that deliberately elicits information to improve the clinician’s sense and understanding of a patient’s social context. The authors reviewed future directions in researching adapted versions of the CI for undergraduate and graduate medical education.

Abstract Spontaneous symmetry breaking and emergent polar order are each of fundamental importance to a range of scientific disciplines, as well as generating rich phase behaviour in liquid crystals (LCs). Here, we show the union of these phenomena to lead to two previously undiscovered polar liquid states of matter. Both phases have a lamellar structure with an inherent polar ordering of their constituent molecules. The first of these phases is characterised by polar order and a local tilted structure; the tilt direction processes about a helix orthogonal to the layer normal, the period of which is such that we observe selective reflection of light. The second new phase type is anti-ferroelectric, with the constituent molecules aligning orthogonally to the layer normal. This has led us to term the phases the $${{{{{\rm{Sm}}}}}}{{{{{{\rm{C}}}}}}}_{{{{{{\rm{P}}}}}}}^{{{{{{\rm{H}}}}}}}$$ Sm C P H and SmAAF phases, respectively. Further to this, we obtain room temperature ferroelectric nematic (NF) and $${{{{{\rm{Sm}}}}}}{{{{{{\rm{C}}}}}}}_{{{{{{\rm{P}}}}}}}^{{{{{{\rm{H}}}}}}}$$ Sm C P H phases via binary mixture formulation of the novel materials described here with a standard NF compound (DIO), with the resultant materials having melting points (and/or glass transitions) which are significantly below ambient temperature. The new soft matter phase types discovered herein can be considered as electrical analogues of topological structures of magnetic spins in hard matter.

Polar liquid crystals possess 3D orientational order coupled with unidirectional electric polarity, yielding fluid ferroelectrics. Such polar phases are generated by rod‐like molecules with large electric dipole moments. 2,5‐Disubstituted 1,3‐dioxane is commonly employed as a polar motif in said systems, and herein it is shown to suffer from thermal instability as a consequence of equatorial‐trans to axial‐trans isomerism at elevated temperatures. Isosteric building blocks are utilized as potential replacements for the 1,3‐dioxane unit, and in doing so new examples of fluid ferroelectric systems are obtained. For binary mixtures of certain composition, the emergence of a new fluid antiferroelectric phase, a finding not observed for either of the parent molecules, is observed. This study also reveals a critical tipping point for the emergence of polar order in otherwise apolar systems. These results hint at the possibility for uncovering new highly ordered polar liquid‐crystalline phases and delineate distinct transition mechanisms in orientational and polar ordering.

Movement disorders such as cervical dystonia, blepharospasm, and hemifacial spasm negatively impact the quality of life of people living with these conditions. Botulinum toxin (BoNT) injections are commonly used to treat these disorders. We sought to describe patient characteristics, BoNT utilization, and potential adverse events (AEs) among patients with cervical dystonia, blepharospasm, and hemifacial spasm using Optum’s de-identified Clinformatics® Data Mart Database. Patients were required to have a diagnosis of the specific condition plus evidence of treatment with BoNT between 8/1/2010 and 5/31/2022. Cervical dystonia patients were commonly females (76%) and aged 45 and older (78%); both blepharospasm and hemifacial spasm patients were commonly females (both 69%) and aged 65 and older (61% and 56%, respectively). Anticholinergics were commonly used (65–82% across cohorts), as were peripheral muscle relaxants for cervical dystonia patients specifically (31%). The median number of injections per year was 2 with the median weeks between injections being between 13 and 15. Of the AEs evaluated, dyspnea was identified frequently across all the cohorts (14–20%). The findings were similar for different BoNT formulations. More research is needed to thoroughly describe BoNT utilization, such as the doses injected, and to optimize treatment for patients with these conditions.

Chronic sialorrhea is a condition characterized by excessive drooling, often associated with neurological and neuromuscular disorders such as Parkinson’s disease, cerebral palsy, and stroke. Despite its prevalence, it remains underdiagnosed and poorly understood, leading to a lack of comprehensive data on patient demographics, clinical characteristics, and treatment patterns. This study aimed to help fill these existing gaps by analyzing real-world data using Optum’s de-identified Clinformatics® Data Mart Database. Patients were required to have a diagnosis indicative of sialorrhea plus evidence of sialorrhea treatment between 1/1/2007 and 5/31/2022. Two cohorts were analyzed: patients with evidence of newly diagnosed sialorrhea and associated treatment, and sialorrhea patients initiating incobotulinumtoxinA. Clinical characteristics, comorbidities, symptoms, and treatment utilization were described before and after diagnosis and incobotulinumtoxinA initiation. No formal statistical comparisons were performed. Patients were predominantly aged 65 or older, male, and non-Hispanic white. Parkinson’s disease and cerebral palsy were the most common comorbidities among adults and children, respectively. Treatment patterns suggest that anticholinergics are more commonly used than botulinum toxin therapy. The findings offer valuable information for improving diagnosis and treatment approaches and suggest a need for further research into treatment effectiveness, safety, and disease burden.

Vernonia amygdalina is an African traditional leafy vegetable which is a source of income for many households involved in its production in West and Central Africa. The species possesses several medicinal and nutritional properties. Despite its importance, there is limited information on farmers’ access to seed, seed production practices, seed trade, and related constraints. This research aimed at investigating farmers’ seed access and management practices. A non-probabilistic snowball method was used to sample and interview 164 bitter leaf seed sector actors from urban and peri-urban areas in Benin. Results indicated that vegetable farming is mainly practiced by men and it was the main occupation for 94.47% of the farmers interviewed. A significant association was found between the location and farmers’ experience (p-value = 0.01358). A diversity of Vernonia amygdalina morphotypes were found. Sixty-three percent of the farmers surveyed use seeds as planting material, 29% use purchased seedlings and only 7% use stem cuttings for Vernonia amygdalina production. Most of the seeds used (74%) were from farmer-saved seeds, harvested from isolated plants during production. The main constraints to V. amygdalina production reported by farmers were the unavailability of seeds (41% of respondents), low germination percentage (18%) and low seed longevity (12%). Findings from this study can inform solutions to improve farmers’ access to high-quality seeds and enhance V. amygdalina vegetable production.

BackgroundThough there has been considerable effort to implement machine learning (ML) methods for health care, clinical implementation has lagged. Incorporating explainable machine learning (XML) methods through the development of a decision support tool using a design thinking approach is expected to lead to greater uptake of such tools. ObjectiveThis work aimed to explore how constant engagement of clinician end users can address the lack of adoption of ML tools in clinical contexts due to their lack of transparency and address challenges related to presenting explainability in a decision support interface. MethodsWe used a design thinking approach augmented with additional theoretical frameworks to provide more robust approaches to different phases of design. In particular, in the problem definition phase, we incorporated the nonadoption, abandonment, scale-up, spread, and sustainability of technology in health care (NASSS) framework to assess these aspects in a health care network. This process helped focus on the development of a prognostic tool that predicted the likelihood of admission to an intensive care ward based on disease severity in chest x-ray images. In the ideate, prototype, and test phases, we incorporated a metric framework to assess physician trust in artificial intelligence (AI) tools. This allowed us to compare physicians’ assessments of the domain representation, action ability, and consistency of the tool. ResultsPhysicians found the design of the prototype elegant, and domain appropriate representation of data was displayed in the tool. They appreciated the simplified explainability overlay, which only displayed the most predictive patches that cumulatively explained 90% of the final admission risk score. Finally, in terms of consistency, physicians unanimously appreciated the capacity to compare multiple x-ray images in the same view. They also appreciated the ability to toggle the explainability overlay so that both options made it easier for them to assess how consistently the tool was identifying elements of the x-ray image they felt would contribute to overall disease severity. ConclusionsThe adopted approach is situated in an evolving space concerned with incorporating XML or AI technologies into health care software. We addressed the alignment of AI as it relates to clinician trust, describing an approach to wire framing and prototyping, which incorporates the use of a theoretical framework for trust in the design process itself. Moreover, we proposed that alignment of AI is dependent upon integration of end users throughout the larger design process. Our work shows the importance and value of engaging end users prior to tool development. We believe that the described approach is a unique and valuable contribution that outlines a direction for ML experts, user experience designers, and clinician end users on how to collaborate in the creation of trustworthy and usable XML-based clinical decision support tools.

Abstract Herbivorous insects and their host plants comprise most known species on Earth. Illuminating how herbivory repeatedly evolved in insects from nonherbivorous lineages is critical to understanding how this biodiversity is created and maintained. We characterized the trophic niche of Scaptomyza flava, a representative of a lineage nested within the Drosophila that transitioned to herbivory ~10–15 million years ago. We used natural history studies to determine whether S. flava is a true herbivore or a cryptic microbe‐feeder, given that the ancestral character state for the family Drosophilidae is likely microbe‐feeding. Specifically, we quantified oviposition substrate choice and larval viability across food types, trophic‐related morphological traits, and nitrogen isotope and sterol profiles across putatively herbivorous and nonherbivorous drosophilids. The results of these studies show that S. flava is an obligate herbivore of living plants. Paired with its genetic model host, Arabidopsis thaliana, S. flava is a novel and powerful system for exploring mechanisms underlying the evolution of herbivory, a complex trait that enabled the exceptional diversification of insects.

Abstract Impaired cerebrovascular function contributes to the genesis of age‐related cognitive decline. In this study, the hypothesis is tested that impairments in neurovascular coupling (NVC) responses and brain network function predict cognitive dysfunction in older adults. Cerebromicrovascular and working memory function of healthy young (n = 21, 33.2±7.0 years) and aged (n = 30, 75.9±6.9 years) participants are assessed. To determine NVC responses and functional connectivity (FC) during a working memory (n‐back) paradigm, oxy‐ and deoxyhemoglobin concentration changes from the frontal cortex using functional near‐infrared spectroscopy are recorded. NVC responses are significantly impaired during the 2‐back task in aged participants, while the frontal networks are characterized by higher local and global connection strength, and dynamic FC (p < 0.05). Both impaired NVC and increased FC correlate with age‐related decline in accuracy during the 2‐back task. These findings suggest that task‐related brain states in older adults require stronger functional connections to compensate for the attenuated NVC responses associated with working memory load.

Background: The ability to maintain muscle function decreases with age and loss of proteostatic function. Diet, drugs, and genetic interventions that restrict nutrients or nutrient signaling help preserve long-term muscle function and slow age-related decline. Previously, it was shown that attenuating protein synthesis downstream of the mechanistic target of rapamycin (mTOR) gradually increases expression of heat shock response (HSR) genes in a manner that correlates with increased resilience to protein unfolding stress. Here, we investigate the role of specific tissues in mediating the cytoprotective effects of low translation. Methods: This study uses genetic tools (transgenic Caenorhabditis elegans (C. elegans), RNA interference and gene expression analysis) as well as physiological assays (survival and paralysis assays) in order to better understand how specific tissues contribute to adaptive changes involving cellular cross-talk that enhance proteostasis under low translation conditions. Results: We use the C. elegans system to show that lowering translation in neurons or the germline increases heat shock gene expression and survival under conditions of heat stress. In addition, we find that low translation in these tissues protects motility in a body muscle-specific model of proteotoxicity that results in paralysis. Low translation in neurons or germline also results in increased expression of certain muscle regulatory and structural genes, reversing reduced expression normally observed with aging in C. elegans. Enhanced resilience to protein unfolding stress requires neuronal expression of cbp-1. Conclusions: Low translation in either neurons or the germline orchestrate protective adaptation in other tissues, including body muscle.

The highly conserved integrated stress response (ISR) reduces and redirects mRNA translation in response to certain forms of stress and nutrient limitation. It is activated when kinases phosphorylate a key residue in the alpha subunit of eukaryotic translation initiation factor 2 (eIF2). General Control Nonderepressible-2 (GCN2) is activated to phosphorylate eIF2α by the presence of uncharged tRNA associated with nutrient scarcity, while protein kinase R-like ER kinase-1 (PERK) is activated during the ER unfolded protein response (UPRER). Here, we investigated the role of the ISR during nutrient limitation and ER stress with respect to changes in protein synthesis, translationally driven mRNA turnover, and survival in Caenorhabditis elegans. We found that, while GCN2 phosphorylates eIF2α when nutrients are restricted, the ability to phosphorylate eIF2α is not required for changes in translation, nonsense-mediated decay, or lifespan associated with dietary restriction (DR). Interestingly, loss of both GCN2 and PERK abolishes increased lifespan associated with dietary restriction, indicating the possibility of other substrates for these kinases. The ISR was not dispensable under ER stress conditions, as demonstrated by the requirement for PERK and eIF2α phosphorylation for decreased translation and wild type-like survival. Taken together, results indicate that the ISR is critical for ER stress and that other translation regulatory mechanisms are sufficient for increased lifespan under dietary restriction.

Abstract Background Metagenomics analyses can be negatively impacted by DNA contamination. While external sources of contamination such as DNA extraction kits have been widely reported and investigated, contamination originating within the study itself remains underreported. Results Here, we applied high-resolution strain-resolved analyses to identify contamination in two large-scale clinical metagenomics datasets. By mapping strain sharing to DNA extraction plates, we identified well-to-well contamination in both negative controls and biological samples in one dataset. Such contamination is more likely to occur among samples that are on the same or adjacent columns or rows of the extraction plate than samples that are far apart. Our strain-resolved workflow also reveals the presence of externally derived contamination, primarily in the other dataset. Overall, in both datasets, contamination is more significant in samples with lower biomass. Conclusion Our work demonstrates that genome-resolved strain tracking, with its essentially genome-wide nucleotide-level resolution, can be used to detect contamination in sequencing-based microbiome studies. Our results underscore the value of strain-specific methods to detect contamination and the critical importance of looking for contamination beyond negative and positive controls. Video Abstract

Abstract Introduction Most patients significantly benefit from cochlear implantation (CI). However, speech understanding varies widely, with a small proportion of patients demonstrating limited audiometric outcomes. While there are well‐documented determinants of poor performance, there remains a cohort of patients that do not meet expected outcomes. Preoperative prognostication is desirable to manage expectations, ensure value of the intervention, and reduce risk. The objective of the study is to evaluate variables found within a single CI center's most limited functioning cohort following implantation. Methods A retrospective review of a single CI program's cohort of (344 ears) patients implanted between 2011 and 2018 whose 1‐year postimplantation AzBio scores fall 2 SDs below the mean was performed. Exclusion criteria includes skullbase pathology, pre/peri‐lingual deafness, cochlear anatomic abnormalities, English as an additional language, and limited electrode insertion depth. Overall, 26 patients were identified. Results The study population's postimplantation net benefit AzBio score is 18% compared to the entire program's 47% (p

Abstract During HIV infection, intron-containing viral mRNAs are exported from the cell nucleus to the cytoplasm to complete the replication cycle. Cellular restrictions on the export of incompletely spliced transcripts are overcome by a viral protein, Rev, and an RNA structure found in all unspliced and incompletely spliced viral mRNAs, the Rev Response Element (RRE). Primary HIV isolates display substantial variation in the sequence and functional activity of Rev proteins. We analyzed Rev from two primary isolates with disparate activity that resulted in differences in in vitro fitness of replication-competent viral constructs. The results showed that amino acid differences within the oligomerization domain, but not the arginine-rich motif or the nuclear export signal, determined the level of Rev activity. Two specific amino acid substitutions were sufficient to alter the low-activity Rev to a high-activity phenotype. Other mutations in Rev sequences had unpredictable effects on activity that differed between the two Rev backbones. The sensitivity of Rev function level to small sequence changes likely permits modulation of Rev-RRE activity during HIV infection, which may play a role in pathogenesis. The functional consequences of Rev mutations differed between primary isolates, highlighting the challenge of generalizing studies of Rev conducted using laboratory HIV strains.

Social isolation is a well-documented contributor to poor mental and physical health, and interventions promoting social connectedness have been associated with various health benefits. This study examined predictors of participation in a telephone-based social connectedness intervention for socially isolated older adults. Data were obtained from a social-connectedness intervention that paired college students with Houston-area, community-dwelling adults aged 65 years and older and enrolled in Medicare Advantage plans. We combined machine learning and regression techniques to identify significant predictors of program participation. The following machine-learning methods were implemented: (1) k -nearest neighbors, (2) decision tree and ensembles of decision trees, (3) gradient-boosted decision tree, and (4) random forest. The primary outcome was a binary flag indicating participation in the telephone-based social-connectedness intervention. The most predictive variables in the ML models, with scores corresponding to the 90th percentile or greater, were included in the regression analysis. The predictive ability of each model showed high discriminative power, with test accuracies greater than 95%. Our findings suggest that telephone-based social-connectedness interventions appeal to individuals with disabilities, depression, arthritis, and higher risk scores. scores. Recognizing features that predict participation in social-connectedness programs is the first step to increasing reach and fostering patient engagement.

Intrinsically fluorescent liquid crystals are highly sought after for a variety of applications. Most of the measurements of photo-physical properties of liquid crystals are made in dilute solutions, which is mainly due to the relative ease of both these measurements and the interpretation of data. The fluorescence spectra depend on a number of parameters including the concentration in liquid crystal solutions, the device geometry, and the mesophase in which the spectra have been measured. Working with neat, or concentrated, liquid crystal samples adds experimental complexities such as the inner filter effect (IFE), which affects the collection of data, interpretation of the results, and accuracy of the conclusions. In this paper, we present a systematic study of the photo-physical properties of both a model reference material, Nile red, and a nematic liquid crystal, 4-cyano-4′-pentylbiphenyl (5CB). The influence on the emission spectra of an increasing solute concentration is investigated and discussed. Moreover, a detailed investigation of the influence of the used device geometry, as well as the choice of appropriate data fitting methodologies, are presented.

Early in insect embryo development, many nuclei share one large cell, travel varied paths and self-organize into a single layer. Donoughe et al. illuminate this process with live-imaging, modeling, and experimental changes to the embryo’s shape.

Summary: Background: Heart transplantation is an effective treatment offering the best recovery in both quality and quantity of life in those affected by refractory, severe heart failure. However, transplantation is limited by donor organ availability. The reintroduction of heart donation after the circulatory determination of death (DCD) in 2014 offered an uplift in transplant activity by 30%. Thoraco-abdominal normothermic regional perfusion (taNRP) enables in-situ reperfusion of the DCD heart. The objective of this paper is to assess the clinical outcomes of DCD donor hearts recovered and transplanted from donors undergoing taNRP. Method: This was a multicentre retrospective observational study. Outcomes included functional warm ischaemic time, use of mechanical support immediately following transplantation, perioperative and long-term actuarial survival and incidence of acute rejection requiring treatment. 157 taNRP DCD heart transplants, performed between February 2, 2015, and July 29, 2022, have been included from 15 major transplant centres worldwide including the UK, Spain, the USA and Belgium. 673 donations after the neurological determination of death (DBD) heart transplantations from the same centres were used as a comparison group for survival. Findings: taNRP resulted in a 23% increase in heart transplantation activity. Survival was similar in the taNRP group when compared to DBD. 30-day survival was 96.8% ([92.5%–98.6%] 95% CI, n = 156), 1-year survival was 93.2% ([87.7%–96.3%] 95% CI, n = 72) and 5-year survival was 84.3% ([69.6%–92.2%] 95% CI, n = 13). Interpretation: Our study suggests that taNRP provides a significant boost to heart transplantation activity. The survival rates of taNRP are comparable to those obtained for DBD transplantation in this study. The similar survival may in part be related to a short warm ischaemic time or through a possible selection bias of younger donors, this being an uncontrolled observational study. Therefore, our study suggests that taNRP offers an effective method of organ preservation and procurement. This early success of the technique warrants further investigation and use. Funding: None of the authors have a financial relationship with a commercial entity that has an interest in the subject.

Abstract Introduction The COVID‐19 pandemic and associated measures implemented by authorities have created additional stressors and increased the risk of psychological illnesses among people living with HIV (PLWH). Yet, there is no collective evidence on the mental health status of this population during the global pandemic and associated factors. This scoping review aimed to synthesize the evidence in the current literature related to the mental health outcomes and challenges faced by PLWH during the COVID‐19 pandemic, identify the associated factors with psychological distress and summarize various coping strategies to ease these psychological distresses used by this population. Methods We conducted a scoping review following the PRISMA‐ScR guideline and a literature search in four electronic databases in August 2022. Three reviewers independently screened all the search records and extracted the data from studies that met the inclusion criteria. Factors associated with worsened mental health outcomes were synthesized according to the socio‐ecological framework. Results Among 1100 research records, 45 articles met the eligibility criteria and were included in the final review and data extraction, most of which were quantitative analyses. PLWH reported high rates of mental health problems during the pandemic. Multi‐level factors were associated with increased psychological distress, including substance use, antiretroviral adherence, social support, financial hardship and economic vulnerability during the pandemic. PLWH used social media as a coping strategy to foster social support to deal with growing mental distress. Increased mental health illnesses were associated with increased substance use, it was also found associated with suboptimal medication adherence and antiretroviral therapy (ART) care engagement. Discussion PLWH experienced high rates of mental health illnesses, such as depression during the global COVID‐19 pandemic. There is an urgent need to provide comprehensive HIV treatment and mental health services as the pandemic continues to evolve. Conclusions The review summarized how the mental health of PLWH was affected during the COVID‐19 pandemic. Future work in the implementation of effective interventions to promote mental health in this population is needed, not only to ensure their quality of life but also to help them maintain ART adherence and healthcare during more unprecedented times.

PurposeBevacizumab-related imaging abnormality (BRIA), appearing as areas of restricted diffusion on magnetic resonance imaging (MRI) and representing atypical coagulative necrosis pathologically, has been observed in patients with brain tumors receiving radiotherapy and bevacizumab. We investigated the role of cumulative radiation dose in BRIA development in a voxel-wise analysis.MethodsPatients (n = 18) with BRIA were identified. All had high-grade gliomas or brain metastases treated with radiotherapy and bevacizumab. Areas of BRIA were segmented semi-automatically on diffusion-weighted MRI with apparent diffusion coefficient (ADC) images. To avoid confounding by possible tumor, hypoperfusion was confirmed with perfusion imaging. ADC images and radiation dose maps were co-registered to a high-resolution T1-weighted MRI and registration accuracy was verified. Voxel-wise normal tissue complication probability analyses were performed using a logistic model analyzing the relationship between cumulative voxel equivalent total dose in 2 Gy fractions (EQD2) and BRIA development at each voxel. Confidence intervals for regression model predictions were estimated with bootstrapping.ResultsAmong 18 patients, 39 brain tumors were treated. Patients received a median of 4.5 cycles of bevacizumab and 1-4 radiation courses prior to BRIA appearance. Most (64%) treated tumors overlapped with areas of BRIA. The median proportion of each BRIA region of interest volume overlapping with tumor was 98%. We found a dose-dependent association between cumulative voxel EQD2 and the relative probability of BRIA (β0 = -5.1, β1 = 0.03 Gy-1, γ = 1.3).ConclusionsBRIA is likely a radiation dose-dependent phenomenon in patients with brain tumors receiving bevacizumab and radiotherapy. The combination of radiation effects and tumor microenvironmental factors in potentiating BRIA in this population should be further investigated.

Community-based monitoring is a promising strategy for collaboratively documenting knowledge that has become increasingly widespread among Indigenous communities, institutions, and governments across the Arctic. In January 2012, the Nunavut Wildlife Management Board launched the Community-Based Monitoring Network (CBMN) to document current Inuit harvesting practices using modern technology by engaging Inuit harvesters in Nunavut who hunt, fish, gather, and observe wildlife. We provide an overview of the CBMN and discuss the challenges and opportunities of integrating data gathered through the CBMN in co-management decision-making. The CBMN has resulted in the collection of 7225 wildlife harvest and 2623 observation records by 85 harvesters in seven communities during 5594 on the land trips covering a combined area of approximately 400 000 km2. The CBMN represents a powerful approach to knowledge production by Inuit harvesters that is relevant to wildlife managers and co-management agencies. However, the data collected through the Nunavut Wildlife Management Board’s CBMN neither follow conventional wildlife study scientific standards, nor match the outputs of participatory Inuit Qaujimajatuqangit social science research. Instead, it represents a hybrid form of the types of information typically used in resource management discussions. Although such data can inform decision-making, further work may be necessary to fulfill this potential. Nunalingni uumajunik nauttiqsuaqarniq aturuminaqtuulluni upalungaijautiuvuq katujjillutik titiraqsivalliajut qaujimanirijaujunik taakkualu atuqtauvalliatuinnaliqtut nunaqaqqaaqsimajut nunalinginnit, pilirivingnut, ammalu gavamaujuni ukiuqtaqtulimaami. Jaannuari 2012-ngutillugu, nunavut uumajulirijirjuat katimajingit (NWMB) saqqittilauqsimajut nunalingni uumajunik nauttiqsuaqarnirmut piliriamik (CBMN) titiraqtauvalliaqullugit ullumiujuq inuit angunasugusingit aturlutik uajamuuqtunik ullumi atuqtauvaliqtunik nunavumi inuit angunasukpaktut, iqalugasukpaktut, nuatsivaktut, amma nauttiqsuaqaqpaktut uumajunik. unikkaaqaqattaqtugut qanuittuuninganik nunalingni uumajunik nauttiqsuaqarnirmut piliriangujumik ammalu uqautaullutik aksururnarningit ammalu piviksaujut nuattiqullugit tusagaksanik qaritaujakkut aturlugu nunalingni uumajunik nauttiqsuaqanirmut piliriangujuq atuqtauqattarniarmata aulatsijiuqatigiingujunut isumaliuqasuaqtillugit. nunalingni uumajunik nauttiqsuaqarnirmut pilirianguningagut nuattisimaliqtut tusagaksanik 7,225-nik aujaujuvinirnut ammalu 2,623-ngujut takujaujut titiraqtaullutik 85-ngujunut angunasuktinut 7-ngujuni nunaliujuni 5,594-ngirsurłutik aullaqtillugit nunami katitainnarillugit nuna aullarviusimajuq anginiqaqtigilluni sikkitaullutik kilaamitus 400,000 km2. Nunalingni uumajunik nauttiqsuaqanirmut piliriangujuq kiggaqtuivuq sanngijumik piliriaqarninginnut qaujimanirijaujut nuatautillugit inungnut angunasuktinut taakkua nuataujut atuutiqarniaqtillugit uumajulirinirmut aulatsijiujunut ammalu aulatsijiuqataujut pilirivinginnut. Kisianili, taakkua qaritaujakkut tusagaksat nuataujut nunavut uumajulirijirjuat katimajingita nunalingni uumajunik nauttiqsuaqarnirmut piliriangitigut maliksisimangittuq piusirijanginnik uumajunik qaujisainirivaktangita qaujisaqtimmariujut maliganginnik, ammalu angummatijaungittut saqqitauvaktut inungnut ilauqataujunut inuit qaujimajatuqanginnut inuusirmik qaujisaqtimmarit qaujisainirivaktangannut. Kisianili, kiggaqtuijut ajjigiingittunik tusagaksanik atuqtaugajuktunik tusaumattiarlutik isumaliuqtiujut isumauliqattaqullugit, tamatumunga iqqanaijakkannituinnariaqaqpugut pijariiqtaujunnaqullugu piviksaliangusimajuq.

Nutritional studies rely on various biological specimens for FA determination, yet it is unclear how levels of serum NEFAs correlate with other circulating lipid pools. Here, we used a high-throughput method (