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Competing Interests: We declare no competing interests. We would like to acknowledge the use of ChatGPT version 3.5 February, 2023 (OpenAI, San Francisco, CA, USA) in the editing of this Comment, specifically in the discussion of equitability and in the conclusion section (appendix). The use of a large language model has greatly assisted us in rephrasing and ensuring the clarity and effectiveness of our language, and highlights the potential of language models in aiding researchers and health-care professionals save valuable time by effectively and efficiently communicate in written words the concepts that they wish to express.

Introduction: The ASTS implemented a task force in 2018 to increase residents' interest in careers in organ transplantation. National meetings offer important experiences that can increase interest. The present study examines an association that exists between presenting at a major transplant surgery meeting and a trainee's likelihood of pursuing a career in transplant surgery., Methods: All abstracts from the ASTS State of the Art Winter Symposium from 2010 to 2019 were evaluated. Using a combination of internet-based resources, it was determined if the presenter was a resident, what year of residency they were in, and if that individual went into a transplant fellowship., Results: 1544 abstracts were reviewed and 133 were presented by residents. Out of residents that presented, 68.4% (54/79) were senior residents and 31.6% (25/79) were junior residents. Of senior residents, 66.7% (36/54) went into transplant fellowships, while only 20.0% (5/25) of junior residents went into transplant fellowships. Being a senior resident when presenting was statistically significant for pursuing a transplant fellowship (P = .000113)., Discussion: Senior residents who present at ASTS SAWS are likely to pursue a transplant surgery fellowship. Junior residents who present are less likely to pursue transplantation, and this represents an opportunity to improve the engagement of young surgeons in the specialty.

Amyotrophic Lateral Sclerosis (ALS) is a progressive and incurable neurodegenerative disease resulting in the loss of motor neurons, eventually leading to death. ALS results in complex physical, emotional, and spiritual care needs. Specialty Palliative Care (SPC) is a medical specialty for patients with serious illness that provides an extra layer of support through complicated symptom management, goals of care conversations, and support to patients and families during hard times. Using MEDLINE, APA Psychinfo, and Dynamed databases, we reviewed the literature of SPC in ALS to inform and support an expert opinion perspective on this topic. This manuscript focuses on several key areas of SPC for ALS including insurance and care models, advance care planning, symptom management, quality of life, caregiver support, and end-of-life care. Recommendations to improve specialty palliative care for patients with ALS are reviewed in the discussion section.

Abstract The utility of spatial omics in leveraging cellular interactions in normal and diseased states for precision medicine is hampered by a lack of strategies for matching disease states with spatial heterogeneity-guided cellular annotations. Here we use a spatial context-dependent approach that matches spatial pattern detection to cell annotation. Using this approach in existing datasets from ulcerative colitis patient colonic biopsies, we identified architectural complexities and associated difficult-to-detect rare cell types in ulcerative colitis germinal-center B cell follicles. Our approach deepens our understanding of health and disease pathogenesis, illustrates a strategy for automating nested architecture detection for highly multiplexed spatial biology data, and informs precision diagnosis and therapeutic strategies.

Objectives To assess incidence, severity and predictors of COVID-19, including protective post-vaccination levels of antibodies to the receptor-binding domain of SARS-CoV-2 spike protein (anti-RBD), informing further vaccine strategies for patients with immune-mediated inflammatory diseases (IMIDs) on immunosuppressive medication.Methods IMIDs on immunosuppressives and healthy controls (HC) receiving SARS-CoV-2 vaccines were included in this prospective observational study. COVID-19 and outcome were registered and anti-RBD antibodies measured 2–5 weeks post-immunisation.Results Between 15 February 2021 and 15 February 2023, 1729 IMIDs and 350 HC provided blood samples and self-reported COVID-19. The incidence of COVID-19 was 66% in patients and 67% in HC, with re-infection occurring in 12% of patients. Severe COVID-19 was recorded in 22 (2%) patients and no HC. No COVID-19-related deaths occurred. Vaccine-induced immunity gave higher risk of COVID-19 (HR 5.89 (95% CI 4.45 to 7.80)) than hybrid immunity. Post-immunisation anti-RBD levels

Abstract To date, there is a considerable heterogeneity of methods to score Allostatic Load (AL). Here we propose a comprehensive algorithm (ALCS) that integrates commonly used approaches to generate AL risk categories and assess associations to brain structure deterioration. In a cohort of cognitively normal mid-life adults (n = 620, age 51.3 ± 5.48 years), we developed a comprehensive composite for AL scoring incorporating gender and age differences, high quartile approach, clinical reference values, and current medications, to then generate AL risk categories. Compared to the empirical approach (ALES), ALCS showed better model fit criteria and a strong association with age and sex. ALSC categories were regressed against brain and white matter hyperintensity (WMH) volumes. Higher AL risk categories were associated with increased total, periventricular, frontal, and left parietal WMH volumes, also showing better fit compared to ALES. When cardiovascular biomarkers were removed from the ALSC algorithm, only left-frontal WMHV remained associated with AL, revealing a strong vascular burden influencing the index. Our results agree with previous evidence and suggest that sustained stress exposure enhances brain deterioration in mid-life adults. Showing better fit than ALES, our comprehensive algorithm can provide a more accurate AL estimation to explore how stress exposure enhances age-related health decline.

Background: Bright light therapy (BLT) has not been well-studied in adolescents with major depressive disorder, particularly in outpatient settings. Methods: We conducted an 8-week clinical trial of BLT in adolescents recruited from a primary care practice with moderate to severe major depression. Acceptability and feasibility were defined by daily use of the light box and integration into daily routines. To assess treatment effects, we utilized the Short Mood and Feelings Questionnaire (SMFQ) and actigraphic sleep variables. Results: Of the nine enrolled adolescents, the rate of daily use of the light therapy box was 100% at week 2, 78% at week 4 (n = 7), and 67% at weeks 6 and 8 (n = 6). Participants were better able to integrate midday BLT compared to morning BLT into their day-to-day routines. Mean depression scores improved during the 2-week placebo lead-in (dim red light—DRL) and continued to show significant improvement through 6 weeks of BLT. Sleep efficiency increased significantly (p = 0.046), and sleep onset latency showed a trend toward a significant decrease (p = 0.075) in the BLT phase compared to the DRL phase. Conclusion: Bright light treatment that was self-administered at home was feasible, acceptable, and effective for adolescent outpatients with depression. Findings support the development of larger, well-powered, controlled clinical trials of BLT in coordination with primary care.

Abstract There has recently been an explosion of studies implicating the human microbiome in playing a critical role in many disease and wellness states. The etiology of abnormal semen analysis (SA) parameters is not identified in 30% of cases; investigations involving the semen microbiome may bridge this gap. Here, we explore the relationship between the semen microbiome and alterations of sperm parameters. We recruited men presenting for fertility evaluation or vasectomy consultation with proven biological paternity. SA and next generation sequencing was performed. Differential abundance testing using Analysis of composition of Microbiota with Bias Correction (ANCOM-BC) was performed along with canonical correlational analysis for microbial community profiling. Men with abnormal (N = 27) sperm motility showed a higher abundance of Lactobacillus iners compared to those with normal (N = 46) sperm motility (mean proportion 9.4% versus 2.6%, p = 0.046). This relationship persisted on canonical correlational analysis (r = 0.392, p = 0.011). Men with abnormal sperm concentration (N = 20) showed a higher abundance of Pseudomonas stutzeri (2.1% versus 1.0%, p = 0.024) and Pseudomonas fluorescens (0.9% versus 0.7%, p = 0.010), but a lower abundance of Pseudomonas putida (0.5% versus 0.8%, p = 0.020), compared to those with normal sperm concentration (N = 53). Major limitations are related to study design (cross-sectional, observational). Our results suggest that a small group of microorganisms may play a critical role in observed perturbations of SA parameters. Some of these microbes, most notably Lactobacillus iners, have been described extensively within other, fertility-related, contexts, whereas for others, this is the first report where they have potentially been implicated. Advances in our understanding of the semen microbiome may contribute to potentially new therapeutic avenues for correcting impairments in sperm parameters and improving male fertility.

Abstract To investigate ideological symmetries and asymmetries in the expression of online prejudice, we used machine-learning methods to estimate the prevalence of extreme hostility in a large dataset of Twitter messages harvested in 2016. We analyzed language contained in 730,000 tweets on the following dimensions of bias: (1) threat and intimidation, (2) obscenity and vulgarity, (3) name-calling and humiliation, (4) hatred and/or racial, ethnic, or religious slurs, (5) stereotypical generalizations, and (6) negative prejudice. Results revealed that conservative social media users were significantly more likely than liberals to use language that involved threat, intimidation, name-calling, humiliation, stereotyping, and negative prejudice. Conservatives were also slightly more likely than liberals to use hateful language, but liberals were slightly more likely than conservatives to use obscenities. These findings are broadly consistent with the view that liberal values of equality and democratic tolerance contribute to ideological asymmetries in the expression of online prejudice, and they are inconsistent with the view that liberals and conservatives are equally prejudiced.

AbstractBackground The exhaustive information about non-communicable diseases associated with COVID-19 and severe acute respiratory syndrome corona virus-2 (SARS-CoV-2) are getting easier to find in the literature. However, there is a lack of knowledge regarding tuberculosis (TB) and chronic obstructed pulmonary disease (COPD), with numerous infections in COVID-19 patients.Objectives Priority is placed on determining the patient’s prognosis based on the presence or absence of TB and COPD. Additionally, a comparison is made between the risk of death and the likelihood of recovery in terms of time in COVID-19 patients who have either COPD or TB.Methodology At the DHQ Hospital in Muzaffargarh, Punjab, Pakistan, 498 COVID-19 patients with TB and COPD were studied retrospectively. The duration of study started in February 2022 and concluded in August 2022. The Kaplan–Meier curves described time-to-death and time-to-recovery stratified by TB and COPD status. The Wilcoxon test compared the survival rates of people with TB and COPD in two matched paired groups and their status differences with their standard of living.Results The risk of death in COVID-19 patients with TB was 1.476 times higher than in those without (95% CI: 0.949–2.295). The recovery risk in COVID-19 patients with TB was 0.677 times lower than in those without (95% CI: 0.436–1.054). Similarly, patients with TB had a significantly shorter time to death (p=.001) and longer time to recovery (p=.001).Conclusions According to the findings, the most significant contributor to an increased risk of morbidity and mortality in TB and COPD patients was the COVID-19.KEY MESSAGESSARS-Cov-19 is a new challenge for the universe in terms of prevention and treatment for people with tuberculosis and chronic obstructive pulmonary disease, among other diseases.Propensity score matching to control for potential biases.Compared to hospitalized patients with and without (TB and COPD) had an equivalently higher mortality rate.

Despite much progress, image processing remains a significant bottleneck for high-throughput analysis of microscopy data. One popular platform for single-cell time-lapse imaging is the mother machine, which enables long-term tracking of microbial cells under precisely controlled growth conditions. While several mother machine image analysis pipelines have been developed in the past several years, adoption by a non-expert audience remains a challenge. To fill this gap, we implemented our own software, MM3, as a plugin for the multidimensional image viewer napari. napari-MM3 is a complete and modular image analysis pipeline for mother machine data, which takes advantage of the high-level interactivity of napari. Here, we give an overview of napari-MM3 and test it against several well-designed and widely used image analysis pipelines, including BACMMAN and DeLTA. Researchers often analyze mother machine data with custom scripts using varied image analysis methods, but a quantitative comparison of the output of different pipelines has been lacking. To this end, we show that key single-cell physiological parameter correlations and distributions are robust to the choice of analysis method. However, we also find that small changes in thresholding parameters can systematically alter parameters extracted from single-cell imaging experiments. Moreover, we explicitly show that in deep learning-based segmentation, ‘what you put is what you get’ (WYPIWYG) – that is, pixel-level variation in training data for cell segmentation can propagate to the model output and bias spatial and temporal measurements. Finally, while the primary purpose of this work is to introduce the image analysis software that we have developed over the last decade in our lab, we also provide information for those who want to implement mother machine-based high-throughput imaging and analysis methods in their research.

Aims We attempted to improve clinical outcome measures (HbA1c, blood pressure, preventive foot care) in a high-risk population of diabetic patients living in Northern Haiti.

Abstract We have investigated the efficacy of superparamagnetic iron oxide nanoparticles (SPIONs) as positive T1 contrast agents for low-field magnetic resonance imaging (MRI) at 64 millitesla (mT). Iron oxide-based agents, such as the FDA-approved ferumoxytol, were measured using a variety of techniques to evaluate T1 contrast at 64 mT. Additionally, we characterized monodispersed carboxylic acid-coated SPIONs with a range of diameters (4.9–15.7 nm) in order to understand size-dependent properties of T1 contrast at low-field. MRI contrast properties were measured using 64 mT MRI, magnetometry, and nuclear magnetic resonance dispersion (NMRD). We also measured MRI contrast at 3 T to provide comparison to a standard clinical field strength. SPIONs have the capacity to perform well as T1 contrast agents at 64 mT, with measured longitudinal relaxivity (r1) values of up to 67 L mmol−1 s−1, more than an order of magnitude higher than corresponding r1 values at 3 T. The particles exhibit size-dependent longitudinal relaxivities and outperform a commercial Gd-based agent (gadobenate dimeglumine) by more than eight-fold at physiological temperatures. Additionally, we characterize the ratio of transverse to longitudinal relaxivity, r2/r1 and find that it is ~ 1 for the SPION based agents at 64 mT, indicating a favorable balance of relaxivities for T1-weighted contrast imaging. We also correlate the magnetic and structural properties of the particles with models of nanoparticle relaxivity to understand generation of T1 contrast. These experiments show that SPIONs, at low fields being targeted for point-of-care low-field MRI systems, have a unique combination of magnetic and structural properties that produce large T1 relaxivities.

Abstract In the U.S. political conservatives hold less favorable attitudes than liberals about immigration and immigrant groups. We hypothesized that one reason for this ideological gap is that conservatives are more likely to believe that immigrants are not as justifying of the American system as they should be. This hypothesis was tested in an online study (N = 404) with respect to four immigrant groups: Europeans, East Asians, Middle Easterners, and Latin Americans. Results revealed that conservatism was positively associated with (a) prescriptive beliefs that immigrants should engage in high levels of system justification, and (b) descriptive beliefs that immigrants—except for Middle Eastern immigrants—generally do endorse high levels of system justification. Importantly, conservatives perceived a bigger difference than liberals between prescriptive and descriptive beliefs about immigrants’ system justification levels, and this difference mediated the association between conservatism and attitudes and feelings about non-European (but not European) immigrants. These findings support a new “Perceived System Justification Deficit Model of Prejudice” in which expectations about others’ degree of ideological support for the societal status quo may contribute to out-group bias and perhaps even discrimination.

Abstract Circulating miR-371a-3p has excellent performance in the detection of viable (non-teratoma) germ cell tumor (GCT) pre-orchiectomy; however, its ability to detect occult disease is understudied. To refine the serum miR-371a-3p assay in the minimal residual disease setting we compared performance of raw (Cq) and normalized (∆Cq, RQ) values from prior assays, and validated interlaboratory concordance by aliquot swapping. Revised assay performance was determined in a cohort of 32 patients suspected of occult retroperitoneal disease. Assay superiority was determined by comparing resulting receiver-operator characteristic (ROC) curves using the Delong method. Pairwise t-tests were used to test for interlaboratory concordance. Performance was comparable when thresholding based on raw Cq vs. normalized values. Interlaboratory concordance of miR-371a-3p was high, but reference genes miR-30b-5p and cel-miR-39-3p were discordant. Introduction of an indeterminate range of Cq 28–35 with a repeat run for any indeterminate improved assay accuracy from 0.84 to 0.92 in a group of patients suspected of occult GCT. We recommend that serum miR-371a-3p test protocols are updated to (a) utilize threshold-based approaches using raw Cq values, (b) continue to include an endogenous (e.g., miR-30b-5p) and exogenous non-human spike-in (e.g., cel-miR-39-3p) microRNA for quality control, and (c) to re-run any sample with an indeterminate result.

Abstract Vaccine discovery against eukaryotic parasites is not trivial as highlighted by the limited number of known vaccines compared to the number of protozoal diseases that need one. Only three of 17 priority diseases have commercial vaccines. Live and attenuated vaccines have proved to be more effective than subunit vaccines but adversely pose more unacceptable risks. One promising approach for subunit vaccines is in silico vaccine discovery, which predicts protein vaccine candidates given thousands of target organism protein sequences. This approach, nonetheless, is an overarching concept with no standardised guidebook on implementation. No known subunit vaccines against protozoan parasites exist as a result of this approach, and consequently none to emulate. The study goal was to combine current in silico discovery knowledge specific to protozoan parasites and develop a workflow representing a state-of-the-art approach. This approach reflectively integrates a parasite’s biology, a host's immune system defences, and importantly, bioinformatics programs needed to predict vaccine candidates. To demonstrate the workflow effectiveness, every Toxoplasma gondii protein was ranked in its capacity to provide long-term protective immunity. Although testing in animal models is required to validate these predictions, most of the top ranked candidates are supported by publications reinforcing our confidence in the approach.

IntroductionBurnout poses a substantial, ongoing threat to healthcare worker (HCW) wellbeing and to the delivery of safe, quality healthcare. While systemic and organization-level changes in healthcare are critically important, HCWs also need individual-level skills to promote resilience. The objective of this trial is to test feasibility, acceptability, and efficacy of PARK, an online self-guided positive affect regulation intervention, in a sample of healthcare workers during the COVID-19 pandemic.Design and methodsIn the context of the unprecedented rise in burnout during the COVID-19 pandemic, we conducted a randomized waitlist-controlled trial of the Positive Affect Regulation sKills (PARK) program-a five-week, online, self-guided coping skills intervention nested within an ongoing cohort of HCWs. N = 554 healthcare workers were randomly assigned to receive the intervention immediately or to receive the intervention after approximately 12 weeks. Outcomes included change in burnout, emotional wellbeing (positive affect, meaning and purpose, depression, anxiety) and sleep over approximately 12 weeks. Analyses included mixed-effects linear regression models comparing change over time in outcomes between intervention and control conditions.ResultsOne third (n = 554) of the participants in the cohort of HCWs consented to participate and enrolled in PARK in April 2022. Compared to those who did not enroll, participants in the trial reported higher burnout, poorer emotional wellbeing, and poorer sleep at baseline (April, 2022; all ps < .05). Intent-to-treat analyses showed that participants randomly assigned to the intervention immediately (PARK-Now) improved significantly on anxiety (within-group change on PROMIS T-score = -0.63; p = .003) whereas those in the waitlist (PARK-Later) did not (within group T-score change 0.04, p = 0.90). The between-group difference in change, however, was not statistically significant (B = -0.67 p = 0.10). None of the other wellbeing outcomes changed significantly in the intervention group compared to the waitlist. Additional as-treated analyses indicated that those participants who completed all 5 of the weekly online lessons (N = 52; 9.4%) improved significantly more on the primary outcome of positive affect compared to those who enrolled in PARK but completed zero lessons (n = 237; 42.8%; B = 2.85; p = .0001).ConclusionsOnline self-guided coping skills interventions like PARK can be effective in targeted samples and future work will focus on adaptations to increase engagement and tailor PARK for HCWs who could most benefit.

The COVID-19 outbreak led governmental officials to close many businesses and schools, including colleges and universities. Thus, the ability to resume normal campus operation required adoption of safety measures to monitor and respond to COVID-19. The objective of this study was to determine the efficacy of wastewater-based epidemiology as a surveillance method in monitoring COVID-19 on a college campus. The use of wastewater monitoring as part of a surveillance program to control COVID-19 outbreaks at East Carolina University was evaluated. During the Spring and Fall 2021 semesters, wastewater samples (N = 830) were collected every Monday, Wednesday, and Friday from the sewer pipes exiting the dormitories on campus. Samples were analyzed for SARS-CoV-2 and viral quantification was determined using qRT-PCR. During the Spring 2021 semester, there was a significant difference in SARS-CoV-2 virus copies in wastewater when comparing dorms with the highest number student cases of COVID-19 and those with the lowest number of student cases, (p = 0.002). Additionally, during the Fall 2021 semester it was observed that when weekly virus concentrations exceeded 20 copies per ml, there were new confirmed COVID-19 cases 85% of the time during the following week. Increases in wastewater viral concentration spurred COVID-19 swab testing for students residing in dormitories, aiding university officials in effectively applying COVID testing policies. This study showed wastewater-based epidemiology can be a cost-effective surveillance tool to guide other surveilling methods (e.g., contact tracing, nasal/salvia testing, etc.) to identify and isolate afflicted individuals to reduce the spread of pathogens and potential outbreaks within a community.

BackgroundThe binding of low-density lipoprotein (LDL) to proteoglycans (PGs) in the extracellular matrix (ECM) of the arterial intima is a key initial step in the development of atherosclerosis. Although many techniques have been developed to assess this binding, most of the methods are labor-intensive and technically challenging to standardize across research laboratories. Thus, sensitive, and reproducible assay to detect LDL binding to PGs is needed to screen clinical populations for atherosclerosis risk.ObjectivesThe aim of this study was to develop a quantitative, and reproducible assay to evaluate the affinity of LDL towards PGs and to replicate previously published results on LDL-PG binding.MethodsImmunofluorescence microscopy was performed to visualize the binding of LDL to PGs using mouse vascular smooth muscle (MOVAS) cells. An in-cell ELISA (ICE) was also developed and optimized to quantitatively measure LDL-PG binding using fixed MOVAS cells cultured in a 96-well format.ResultsWe used the ICE assay to show that, despite equal APOB concentrations, LDL isolated from adults with cardiovascular disease bound to PG to a greater extent than LDL isolated from adults without cardiovascular disease (pConclusionWe have developed an LDL-PG binding assay that is capable of detecting differences in PG binding affinities despite equal APOB concentrations. Future work will focus on candidate apolipoproteins that enhance or diminish this interaction.

IntroductionDuring the coronavirus disease 2019 pandemic, high levels of burnout were reported among healthcare workers. This study examines the association of work absenteeism and frequency of thoughts in leaving current job with burnout among a cohort of healthcare workers during the COVID-19 pandemic.MethodsA cross-sectional survey of healthcare workers was conducted from April-May, 2022 on healthcare workers from 10 hospitals, 18 immediate care centers, and 325 outpatient practices in the Chicago area and surrounding Illinois suburbs. Logistic regression models were used to assess the association of burnout scores (Oldenburg Burnout Inventory—OLBI) and its sub-scores (exhaustion and disengagement scores) with work absenteeism and thoughts of leaving work.ResultsOne-fifth and 60% of respondents (n = 1,825) reported unplanned absenteeism and thoughts of leaving their job, respectively. After adjusting for covariates, higher burnout scores, especially exhaustion scores, were associated with increased odds of unplanned absenteeism (OR = 1.04, 95% CI: 1.01–1.08). Burnout scores and both sub-scores were also positively associated with the frequency of thoughts of leaving work, e.g., each unit increase in the OLBI burnout score was associated with 1.39 (95% CI: 1.34–1.43) times higher odds of thinking about leaving work “a lot/constantly” vs. “never”.DiscussionOverall, this study cohort showed a positive association between burnout scores and unplanned work absenteeism (and frequency of thoughts in leaving job) during the COVID-19 pandemic. More research is needed to support healthcare worker well-being during times of stress and direct solutions to addressing unplanned absenteeism in the light of a pandemic.

IntroductionAs the global population ages, the economic, societal, and personal burdens associated with worsening cognition and dementia onset are growing. It is therefore becoming ever more critical to understand the factors associated with cognitive decline. One such factor is sleep. Adequate sleep has been shown to maintain cognitive function and protect against the onset of chronic disease, whereas sleep deprivation has been linked to cognitive impairment and the onset of depression and dementia.ObjectivesHere, we aim to identify and explore mechanistic links between several sleep parameters, depressive symptoms and cognition in a cohort of middle-aged adults.MethodsWe investigated data from the PREVENT dementia programme via structural equation modeling to illustrate links between predictor variables, moderator variables, and two cognitive constructs (i.e., Executive Function and Memory).ResultsOur model demonstrated that sleep quality, and total hours of sleep were related to participants' depressive symptoms, and that, participant apathy was related to higher scores on the Epworth Sleepiness and Lausanne NoSAS Scales. Subsequently, depressive symptoms, but not sleep or apathy ratings, were associated with Executive Function.ConclusionsWe provide evidence for an indirect relationship between sleep and cognition mediated by depressive symptoms in a middle-aged population. Our results provide a base from which cognition, dementia onset, and potential points of intervention, may be better understood.

Abstract Objective Two main fungal leaf spot diseases occur in peanut, namely early leaf spot (ELS) and late leaf spot (LLS), these cause a yearly average of $44 million losses. Limited genetic information, 3534 bp of sequencing, exists about the causal agent of LLS, Cercosporidium personatum (syn. Nothopassalora personata, syn. Phaeoisariopsis personata). The extremely slow growth of this fungus, approximately 1 cm colony in 6 months, and challenges in nucleic acid extractions have hindered research on LLS. Our goal in this work is to provide a reference genome for research on this pathogen. Results Whole genome and transcriptome sequencing of the LLS fungus were obtained. A total of 233,542,110 reads of the genome were de novo assembled resulting in 1061 scaffolds, and estimated genome size 27,597,787 bp. RNA sequencing resulted in 11,848,198 reads that were de novo assembled into 13,343 contigs. Genome annotation resulted in 10,703 putative genes. BUSCO analysis of the genome and annotation resulted in 91.1% and 89.5% completeness, respectively. Phylogenetic dendrograms for 5442 bp and 4401 bp of RNA Polymerase II largest and second largest subunits, and for 5474 bp of the ribosomal RNA cistron of C. personatum are presented in relation to closely related fungi.

Abstract Genetic characterisation of circulating influenza viruses directs annual vaccine strain selection and mitigation of infection spread. We used next-generation sequencing to locally generate whole genomes from 116 A(H1N1)pdm09 and 118 A(H3N2) positive patient swabs collected across Uganda between 2010 and 2018. We recovered sequences from 92% (215/234) of the swabs, 90% (193/215) of which were whole genomes. The newly-generated sequences were genetically and phylogenetically compared to the WHO-recommended vaccines and other Africa strains sampled since 1994. Uganda strain hemagglutinin (n = 206), neuraminidase (n = 207), and matrix protein (MP, n = 213) sequences had 95.23–99.65%, 95.31–99.79%, and 95.46–100% amino acid similarity to the 2010–2020 season vaccines, respectively, with several mutated hemagglutinin antigenic, receptor binding, and N-linked glycosylation sites. Uganda influenza type-A virus strains sequenced before 2016 clustered uniquely while later strains mixed with other Africa and global strains. We are the first to report novel A(H1N1)pdm09 subclades 6B.1A.3, 6B.1A.5(a,b), and 6B.1A.6 (± T120A) that circulated in Eastern, Western, and Southern Africa in 2017–2019. Africa forms part of the global influenza ecology with high viral genetic diversity, progressive antigenic drift, and local transmissions. For a continent with inadequate health resources and where social distancing is unsustainable, vaccination is the best option. Hence, African stakeholders should prioritise routine genome sequencing and analysis to direct vaccine selection and virus control.

Systemic lupus erythematosus (SLE) is a systemic autoimmune disease with a dramatic sex bias, affecting 9 times more women than men. Activation of Toll-like receptor 7 (TLR7) by self-RNA is a central pathogenic process leading to aberrant production of type I interferon (IFN) in SLE, but the specific RNA molecules that serve as TLR7 ligands have not been defined. By leveraging gene expression data and the known sequence specificity of TLR7, we identified the female-specific X-inactive specific transcript (XIST) long noncoding RNA as a uniquely rich source of TLR7 ligands in SLE. XIST RNA stimulated IFN-α production by plasmacytoid DCs in a TLR7-dependent manner, and deletion of XIST diminished the ability of whole cellular RNA to activate TLR7. XIST levels were elevated in blood leukocytes from women with SLE compared with controls, correlated positively with disease activity and the IFN signature, and were enriched in extracellular vesicles released from dying cells in vitro. Importantly, XIST was not IFN inducible, suggesting that XIST is a driver, rather than a consequence, of IFN in SLE. Overall, our work elucidated a role for XIST RNA as a female sex–specific danger signal underlying the sex bias in SLE.

Objectives For eligible patient groups, hospital-at-home (HaH) programmes have been shown to deliver equivalent patient outcomes with cost reduction compared with standard care. This study aims to establish a benchmark of inpatient admissions that could potentially be substituted by HaH services.Design Descriptive retrospective cohort study.Setting Academic tertiary hospital in Singapore.Participants 124 253 medical admissions over 20 months (January 2016 to August 2017).Primary and secondary outcome measures The primary measure was the proportion of hospitalised patients who may be eligible for HaH, based on eligibility criteria adapted for the Singapore context. The secondary measures were the utilisation patterns and outcomes of these patients.Results Applying generalised eligibility criteria to the retrospective dataset showed that 53.0% of 124 253 medical admissions fitted the eligibility criteria for HaH based on administrative data. 46.8% of such patients had a length of stay

Summary: Background: Lateral spine images for vertebral fracture assessment can be easily obtained on modern bone density machines. Abdominal aortic calcification (AAC) can be scored on these images by trained imaging specialists to assess cardiovascular disease risk. However, this process is laborious and requires careful training. Methods: Training and testing of model performance of the convolutional neural network (CNN) algorithm for automated AAC-24 scoring utilised 5012 lateral spine images (2 manufacturers, 4 models of bone density machines), with trained imaging specialist AAC scores. Validation occurred in a registry-based cohort study of 8565 older men and women with images captured as part of routine clinical practice for fracture risk assessment. Cox proportional hazards models were used to estimate the association between machine-learning AAC (ML-AAC-24) scores with future incident Major Adverse Cardiovascular Events (MACE) that including death, hospitalised acute myocardial infarction or ischemic cerebrovascular disease ascertained from linked healthcare data. Findings: The average intraclass correlation coefficient between imaging specialist and ML-AAC-24 scores for 5012 images was 0.84 (95% CI 0.83, 0.84) with classification accuracy of 80% for established AAC groups. During a mean follow-up 4 years in the registry-based cohort, MACE outcomes were reported in 1177 people (13.7%). With increasing ML-AAC-24 scores there was an increasing proportion of people with MACE (low 7.9%, moderate 14.5%, high 21.2%), as well as individual MACE components (all p-trend

Abstract A method to capture three-dimensional (3D) objects image data under extremely low light level conditions, also known as Photon Counting Imaging (PCI), was reported. It is demonstrated that by combining a PCI system with computational integral imaging algorithms, a 3D scene reconstruction and recognition is possible. The resulting reconstructed 3D images often look degraded (due to the limited number of photons detected in a scene) and they, therefore, require the application of superior image restoration techniques to improve object recognition. Recently, Deep Learning (DL) frameworks have been shown to perform well when used for denoising processes. In this paper, for the first time, a fully unsupervised network (i.e., U-Net) is proposed to denoise the photon counted 3D sectional images. In conjunction with classical U-Net architecture, a skip block is used to extract meaningful patterns from the photons counted 3D images. The encoder and decoder blocks in the U-Net are connected with skip blocks in a symmetric manner. It is demonstrated that the proposed DL network performs better, in terms of peak signal-to-noise ratio, in comparison with the classical TV denoising algorithm.

Abstract Circulating protease inhibitors are important regulators of inflammation that are implicated in the pathophysiology of heart failure (HF). Secretory leukocyte protease inhibitor (SLPI) is a serine protease inhibitor which protects pulmonary tissues against inflammatory damage; however, its role in HF is not well understood. We sought to evaluate associations of circulating SLPI and genetically-mediated serum SLPI with incident HF and its subtypes in a multi-ethnic cohort of adults using clinical and genetic epidemiological approaches. Among 2,297 participants in the Multi-Ethnic Study of Atherosclerosis (MESA), each doubling of serum SLPI was independently associated with incident HF (HR 1.77; 95% CI 1.02–3.02; P = 0.04), particularly incident HF with preserved ejection fraction (HFpEF; HR 2.44; 95% CI 1.23–4.84; P = 0.01) but not HF with reduced ejection fraction (HFrEF; HR 0.95; 95% CI 0.36–2.46; P = 0.91). Previously reported circulating SLPI protein quantitative trait loci (pQTLs) were not associated with serum SLPI levels or incident HF among MESA participants. In conclusion, baseline serum SLPI levels, but not genetically-determined serum SLPI, were significantly associated with incident HF and HFpEF over long-term follow-up in a multi-ethnic cohort. Serum circulating SLPI may be a correlate of inflammation that sheds insight on the pathobiology of HFpEF.

Purpose: Clomiphene citrate (CC) is prescribed off-label in men to improve testosterone and sperm parameters, but the duration of treatment needed to reach maximal benefit remains unclear. Our objective was to examine temporal effects of CC on total testosterone (TT) and semen analysis (SA) using longitudinal follow-up data in treated men. Materials and Methods: We analyzed an IRB-approved database of men treated with CC (25 mg q.d. or 50 mg q.o.d.) from January 2016 through May 2021. We identified patients with 3, 6, 9, and 12 month follow-up data for TT and 3, 6, and 9 month follow-up SA. Mean absolute changes in TT and sperm concentration compared to baseline were calculated, along with 95% confidence intervals. Men with prior genitourinary procedures or hormone therapy were excluded. Paired t-tests were used to compare TT and sperm concentration at each time point to baseline (alpha=0.05). Results: One hundered thirty-four men received CC, mean age 37.7 years (SD 6.7, range 24–52). TT at all follow-ups (3, 6, 9, and 12 months) were available for 25 men, and SA at 3, 6, and 9 months for 26 men. Baseline TT was 358±145 ng/dL and sperm concentration was 13±17.2 M/mL. Significant improvement in TT was identified at 3 months (62.7 ng/dL, 95% CI: 0.49–125.0, p=0.048), additional benefit at 6 months (181.8 ng/dL, 95% CI: 114.1–249.5, p

Abstract Coral reef habitat is created when calcium carbonate production by calcifiers exceeds removal by physical and biological erosion. Carbonate budget surveys provide a means of quantifying the framework-altering actions of diverse assemblages of marine species to determine net carbonate production, a single metric that encapsulates reef habitat persistence. In this study, carbonate budgets were calculated for 723 sites across the Florida Reef Tract (FRT) using benthic cover and parrotfish demographic data from NOAA’s National Coral Reef Monitoring Program, as well as high-resolution LiDAR topobathymetry. Results highlight the erosional state of the majority of the study sites, with a trend towards more vulnerable habitat in the northern FRT, especially in the Southeast Florida region (− 0.51 kg CaCO3 m−2 year−1), which is in close proximity to urban centers. Detailed comparison of reef types reveals that mid-channel reefs in the Florida Keys have the highest net carbonate production (0.84 kg CaCO3 m−2 year−1) and indicates that these reefs may be hold-outs for reef development throughout the region. This study reports that Florida reefs, specifically their physical structure, are in a net erosional state. As these reefs lose structure, the ecosystem services they provide will be diminished, signifying the importance of increased protections and management efforts to offset these trends.

Abstract Background Diffuse pleural mesothelioma (DPM) is an aggressive malignancy that, despite recent treatment advances, has unacceptably poor outcomes. Therapeutic research in DPM is inhibited by a paucity of preclinical models that faithfully recapitulate the human disease. Methods We established 22 patient-derived xenografts (PDX) from 22 patients with DPM and performed multi-omic analyses to deconvolute the mutational landscapes, global expression profiles, and molecular subtypes of these PDX models and compared features to those of the matched primary patient tumors. Targeted next-generation sequencing (NGS; MSK-IMPACT), immunohistochemistry, and histologic subtyping were performed on all available samples. RNA sequencing was performed on all available PDX samples. Clinical outcomes and treatment history were annotated for all patients. Platinum-doublet progression-free survival (PFS) was determined from the start of chemotherapy until radiographic/clinical progression and grouped into < or ≥ 6 months. Results PDX models were established from both treatment naïve and previously treated samples and were noted to closely resemble the histology, genomic landscape, and proteomic profiles of the parent tumor. After establishing the validity of the models, transcriptomic analyses demonstrated overexpression in WNT/β-catenin, hedgehog, and TGF-β signaling and a consistent suppression of immune-related signaling in PDXs derived from patients with worse clinical outcomes. Conclusions These data demonstrate that DPM PDX models closely resemble the genotype and phenotype of parental tumors, and identify pathways altered in DPM for future exploration in preclinical studies.

Abstract Natural infection as well as vaccination with live or attenuated viruses elicit tissue resident, CD8+ memory T cell (Trm) response. Trm cells so elicited act quickly upon reencounter with the priming agent to protect the host. These Trm cells express a unique molecular signature driven by the master regulators—Runx3 and Hobit. We previously reported that intranasal instillation of a subunit vaccine in a prime boost vaccination regimen installed quick-acting, CD8+ Trm cells in the lungs that protected against lethal vaccinia virus challenge. It remains unexplored whether CD8+ Trm responses so elicited are driven by a similar molecular signature as those elicited by microbes in a real infection or by live, attenuated pathogens in conventional vaccination. We found that distinct molecular signatures distinguished subunit vaccine-elicited lung interstitial CD8+ Trm cells from subunit vaccine-elicited CD8+ effector memory and splenic memory T cells. Nonetheless, the transcriptome signature of subunit vaccine elicited CD8+ Trm resembled those elicited by virus infection or vaccination. Clues to the basis of tissue residence and function of vaccine specific CD8+ Trm cells were found in transcripts that code for chemokines and chemokine receptors, purinergic receptors, and adhesins when compared to CD8+ effector and splenic memory T cells. Our findings inform the utility of protein-based subunit vaccination for installing CD8+ Trm cells in the lungs to protect against respiratory infectious diseases that plague humankind.

Abstract Globally, tunas are among the most valuable fish stocks, but are also inherently difficult to monitor and assess. Samples of larvae of Western Atlantic bluefin tuna Thunnus thynnus (Linnaeus, 1758) from standardized annual surveys in the northern Gulf of Mexico provide a potential source of “offspring” for close-kin mark-recapture (CKMR) estimates of abundance. However, the spatial patchiness and highly skewed numbers of larvae per tow suggest sampled larvae may come from a small number of parents, compromising the precision of CKMR. We used high throughput genomic profiling to study sibship within and among larval tows from the 2016 standardized Gulf-wide survey compared to targeted sampling carried out in 2017. Full- and half-siblings were found within both years, with 12% of 156 samples in 2016 and 56% of 317 samples in 2017 having at least one sibling. There were also two pairs of cross cohort half-siblings. Targeted sampling increased the number of larvae collected per sampling event but resulted in a higher proportion of siblings. The combined effective sample size across both years was about 75% of the nominal size, indicating that Gulf of Mexico larval collections could be a suitable source of juveniles for CKMR in Western Atlantic bluefin tuna.

Abstract Coronavirus disease 2019 (COVID-19) continues to significantly impact the global population, thus countermeasure platforms that enable rapid development of therapeutics against variants of SARS-CoV-2 are essential. We report use of a phage display human antibody library approach to rapidly identify neutralizing antibodies (nAbs) against SARS-CoV-2. We demonstrate the binding and neutralization capability of two nAbs, STI-2020 and STI-5041, against the SARS-CoV-2 WA-1 strain as well as the Alpha and Beta variants. STI-2020 and STI-5041 were protective when administered intravenously or intranasally in the golden (Syrian) hamster model of COVID-19 challenged with the WA-1 strain or Beta variant. The ability to administer nAbs intravenously and intranasally may have important therapeutic implications and Phase 1 healthy subjects clinical trials are ongoing.

During alveolar repair, alveolar type 2 (AT2) epithelial cell progenitors rapidly proliferate and differentiate into flat AT1 epithelial cells. Failure of normal alveolar repair mechanisms can lead to loss of alveolar structure (emphysema) or development of fibrosis, depending on the type and severity of injury. To test if β1-containing integrins are required during repair following acute injury, we administered E. coli lipopolysaccharide (LPS) by intratracheal injection to mice with a postdevelopmental deletion of β1 integrin in AT2 cells. While control mice recovered from LPS injury without structural abnormalities, β1-deficient mice had more severe inflammation and developed emphysema. In addition, recovering alveoli were repopulated with an abundance of rounded epithelial cells coexpressing AT2 epithelial, AT1 epithelial, and mixed intermediate cell state markers, with few mature type 1 cells. AT2 cells deficient in β1 showed persistently increased proliferation after injury, which was blocked by inhibiting NF-κB activation in these cells. Lineage tracing experiments revealed that β1-deficient AT2 cells failed to differentiate into mature AT1 epithelial cells. Together, these findings demonstrate that functional alveolar repair after injury with terminal alveolar epithelial differentiation requires β1-containing integrins.

Key Clinical Message A 64‐year‐old female presented with malaise and fever 11 days after a closed, minimally displaced humerus surgical neck fracture. MR imaging revealed an abscess around the fracture, which is a very rare occurrence in adults. Two open debridements and IV antibiotics eradicated the infection. Reverse total shoulder arthroplasty was eventually performed for fracture nonunion.

Clostridioides difficile is the most important cause of healthcare-associated diarrhea in the United States. The high incidence and recurrence rates of C. difficile infection (CDI), associated with high morbidity and mortality, pose a public health challenge. Although antibiotics targeting C. difficile bacteria are the first treatment choice, antibiotics also disrupt the indigenous gut flora and, therefore, create an environment that is favorable for recurrent CDI. The challenge of treating CDI is further exacerbated by the rise of antibiotic-resistant strains of C. difficile, placing it among the top five most urgent antibiotic resistance threats in the USA. The evolution of antibiotic resistance in C. difficile involves the acquisition of new resistance mechanisms, which can be shared among various bacterial species and different C. difficile strains within clinical and community settings. This review provides a summary of commonly used diagnostic tests and antibiotic treatment strategies for CDI. In addition, it discusses antibiotic treatment and its resistance mechanisms. This review aims to enhance our current understanding and pinpoint knowledge gaps in antimicrobial resistance mechanisms in C. difficile, with an emphasis on CDI therapies.

Clostridioides difficile infection (CDI) is a leading nosocomial infection, posing a substantial public health challenge within the United States and globally. CDI typically occurs in hospitalized elderly patients who have been administered antibiotics; however, there has been a rise in the occurrence of CDI in the community among young adults who have not been exposed to antibiotics. C. difficile releases toxins, which damage large intestinal epithelium, leading to toxic megacolon, sepsis, and even death. Unfortunately, existing antibiotic therapies do not always prevent these consequences, with up to one-third of treated patients experiencing a recurrence of the infection. Host factors play a crucial role in the pathogenesis of CDI, and accumulating evidence shows that modulation of host immune responses may potentially alter the disease outcome. In this review, we provide an overview of our current knowledge regarding the role of innate and adaptive immune responses on CDI outcomes. Moreover, we present a summary of non-antibiotic microbiome-based therapies that can effectively influence host immune responses, along with immunization strategies that are intended to tackle both the treatment and prevention of CDI.

A method is detailed for introducing computer usage into any course in a medical curriculum and concomitantly stimulating student utilization of such technology. It is felt medicine will rely more heavily upon computer uses in the future, and that familiarity with computer technology provides confidence and competence in physician usage. (MP)

Abstract The J-Matrix approach for scattering is extended to the time-dependent Schrödinger equation (TDSE) for one electron atoms in external few cycle attosecond fields. To this purpose, the wave function is expanded in square integrable ( $$L^2$$ L 2 ) Sturmian functions and an equation system for the transition amplitudes is established. Outside the interaction zone, boundary conditions are imposed at the border in the $$L^2$$ L 2 function space. These boundary conditions correspond to outgoing waves (Siegert states) and minimize reflections at the $$L^2$$ L 2 boundary grid. Outgoing wave behaviour in the asymptotic region is achieved by employing Pollaczek functions. The method enables the treatment of light - atom interactions within arbitrary external fields. Using a partial wave decomposition, the coupled differential equation system is solved by a Runge-Kutta method. As a proof of the method ionization processes of atomic hydrogen in half and few cycle attosecond fields are examined. The electron energy spectrum is calculated and the numerical implementation will be presented. Different forms of the interaction operator are considered and the convergence behaviour is discussed. Results are compared to other studies which use independent approaches like finite difference methods. Remarkable agreement is achieved even with strong field strengths of the electromagnetic field. It is demonstrated that expanding in $$L^2$$ L 2 functions and imposing boundary conditions at the limit in the $$L^2$$ L 2 function space can be an advantageous alternative to conventional propagation methods using complex absorbing potentials or complex scaling.

Abstract The World Health Organisation reported in 2020 that six of the top 10 sources of death in low-income countries are parasites. Parasites are microorganisms in a relationship with a larger organism, the host. They acquire all benefits at the host’s expense. A disease develops if the parasitic infection disrupts normal functioning of the host. This disruption can range from mild to severe, including death. Humans and livestock continue to be challenged by established and emerging infectious disease threats. Vaccination is the most efficient tool for preventing current and future threats. Immunogenic proteins sourced from the disease-causing parasite are worthwhile vaccine components (subunits) due to reliable safety and manufacturing capacity. Publications with ‘subunit vaccine’ in their title have accumulated to thousands over the last three decades. However, there are possibly thousands more reporting immunogenicity results without mentioning ‘subunit’ and/or ‘vaccine’. The exact number is unclear given the non-standardised keywords in publications. The study aim is to identify parasite proteins that induce a protective response in an animal model as reported in the scientific literature within the last 30 years using machine learning and natural language processing. Source code to fulfil this aim and the vaccine candidate list obtained is made available.

Abstract There is widespread evidence of plant viruses manipulating behavior of their insect vectors as a strategy to maximize infection of plants. Often, plant viruses and their insect vectors have multiple potential host plant species, and these may not overlap entirely. Moreover, insect vectors may not prefer plant species to which plant viruses are well-adapted. In such cases, can plant viruses manipulate their insect vectors to preferentially feed and oviposit on plant species, which are suitable for viral propagation but less suitable for themselves? To address this question, we conducted dual- and no-choice feeding studies (number and duration of probing events) and oviposition studies with non-viruliferous and viruliferous [carrying beet curly top virus (BCTV)] beet leafhoppers [Circulifer tenellus (Baker)] on three plant species: barley (Hordeum vulgare L.), ribwort plantain (Plantago lanceolata L.), and tomato (Solanum lycopersicum L.). Barley is not a host of BCTV, whereas ribwort plantain and tomato are susceptible to BCTV infection and develop a symptomless infection and severe curly top symptoms, respectively. Ribwort plantain plants can be used to maintain beet leafhopper colonies for multiple generations (suitable), whereas tomato plants cannot be used to maintain beet leafhopper colonies (unsuitable). Based on dual- and no-choice experiments, we demonstrated that BCTV appears to manipulate probing preference and behavior by beet leafhoppers, whereas there was no significant difference in oviposition preference. Simulation modeling predicted that BCTV infection rates would to be higher in tomato fields with barley compared with ribwort plantain as a trap crop. Simulation model results supported the hypothesis that manipulation of probing preference and behavior may increase BCTV infection in tomato fields. Results presented were based on the BCTV-beet leafhopper pathosystem, but the approach taken (combination of experimental studies with complementary simulation modeling) is widely applicable and relevant to other insect-vectored plant pathogen systems involving multiple plant species.

BACKGROUND Elevated circulating branched chain amino acids (BCAAs), measured at a single time point in middle life, are strongly associated with an increased risk of developing type 2 diabetes mellitus (DM). However, the longitudinal patterns of change in BCAAs through young adulthood and their association with DM in later life are unknown.METHODS We serially measured BCAAs over 28 years in the Coronary Artery Risk Development in Young Adults (CARDIA) study, a prospective cohort of apparently healthy Black and White young adults at baseline. Trajectories of circulating BCAA concentrations from years 2–30 (for prevalent DM) or years 2–20 (for incident DM) were determined by latent class modeling.RESULTS Among 3,081 apparently healthy young adults, trajectory analysis from years 2–30 revealed 3 distinct BCAA trajectory groups: low-stable (n = 1,427), moderate-stable (n = 1,384), and high-increasing (n = 270) groups. Male sex, higher body mass index, and higher atherogenic lipid fractions were more common in the moderate-stable and high-increasing groups. Higher risk of prevalent DM was associated with the moderate-stable (OR = 2.59, 95% CI: 1.90–3.55) and high-increasing (OR = 6.03, 95% CI: 3.86–9.43) BCAA trajectory groups in adjusted models. A separate trajectory group analysis from years 2–20 for incident DM after year 20 showed that moderate-stable and high-increasing trajectory groups were also significantly associated with higher risk of incident DM, after adjustment for clinical variables and glucose levels.CONCLUSION BCAA levels track over a 28-year span in most young adults, but serial clinical metabolomic measurements identify subpopulations with rising levels associated with high risk of DM in later life.FUNDING This research was supported by the NIH, under grants R01 HL146844 (JTW) and T32 HL069771 (MRC). The CARDIA study is conducted and supported by the NIH National Heart, Lung, and Blood Institute in collaboration with the University of Alabama at Birmingham (HHSN268201800005I and HHSN268201800007I), Northwestern University (HHSN268201800003I), the University of Minnesota (HHSN268201800006I), and Kaiser Foundation Research Institute (HHSN268201800004I).

Limited genomic sampling in many high-incidence countries has impeded studies of severe respiratory syndrome coronavirus 2 (SARS-CoV-2) genomic epidemiology. Consequently, critical questions remain about the generation and global distribution of virus genetic diversity. We investigated SARS-CoV-2 transmission dynamics in Gujarat, India, during the state’s first epidemic wave to shed light on spread of the virus in one of the regions hardest hit by the pandemic. By integrating case data and 434 whole-genome sequences sampled across 20 districts, we reconstructed the epidemic dynamics and spatial spread of SARS-CoV-2 in Gujarat. Our findings indicate global and regional connectivity and population density were major drivers of the Gujarat outbreak. We detected >100 virus lineage introductions, most of which appear to be associated with international travel. Within Gujarat, virus dissemination occurred predominantly from densely populated regions to geographically proximate locations that had low population density, suggesting that urban centers contributed disproportionately to virus spread.

Abstract We provide a pipeline for data preprocessing, biomarker selection, and classification of liquid chromatography–mass spectrometry (LCMS) serum samples to generate a prospective diagnostic test for Lyme disease. We utilize tools of machine learning (ML), e.g., sparse support vector machines (SSVM), iterative feature removal (IFR), and k-fold feature ranking to select several biomarkers and build a discriminant model for Lyme disease. We report a 98.13% test balanced success rate (BSR) of our model based on a sequestered test set of LCMS serum samples. The methodology employed is general and can be readily adapted to other LCMS, or metabolomics, data sets.

Abstract Acute lymphoblastic leukemia (ALL) is the most common type of childhood cancer. Treatments of ALL predispose survivors to obesity, which increases the risk of cardiovascular disease and diabetes. The hallmark of obesity is excess fat mass, and adiposity is a superior predictor of cardiometabolic risk when compared to Body Mass Index (BMI), yet clinical measures of adiposity in children are lacking. The Tri-Ponderal Mass Index (TMI) (kg/m3) is a more accurate adiposity measure compared to BMI z-score in the general pediatric population. This cross-sectional study aimed to validate TMI as an adiposity measure against DEXA scan-derived adiposity, and to compare it to BMI z-score, in pediatric ALL survivors. This study was a retrospective chart review of pediatric ALL survivors diagnosed between 2004 and 2015 at McMaster Children’s Hospital, a tertiary pediatric center in Ontario, Canada. One hundred and thirteen patients (Female n = 55, 48.70%) were included, and adiposity was measured using DEXA scans. Exploratory partial correlations and linear regression analyses were adjusted for age, sex, ethnicity, and ALL risk status. Both TMI and BMI z-score correlated with the DEXA-measured fat mass percentage (FM%) (partial correlation TMI versus FM% r = 0.56; p value

Background Acute febrile neutrophilic dermatosis (Sweet syndrome) is a potentially fatal multiorgan inflammatory disease characterized by fever, leukocytosis, and a rash with a neutrophilic infiltrate. The disease pathophysiology remains elusive, and current dogma suggests that Sweet syndrome is a process of reactivity to an unknown antigen. Corticosteroids and steroid-sparing agents remain frontline therapies, but refractory cases pose a clinical challenge.Methods A 51-year-old woman with multiorgan Sweet syndrome developed serious corticosteroid-related side effects and was refractory to steroid-sparing agents. Blood counts, liver enzymes, and skin histopathology supported the diagnosis. Whole-genome sequencing, transcriptomic profiling, and cellular assays of the patient’s skin and neutrophils were performed.Results We identified elevated IL-1 signaling in lesional Sweet syndrome skin caused by a PIK3R1 gain-of-function mutation specifically found in neutrophils. This mutation increased neutrophil migration toward IL-1β and neutrophil respiratory burst. Targeted treatment of the patient with an IL-1 receptor 1 antagonist resulted in a dramatic therapeutic response and enabled a tapering off of corticosteroids.Conclusion Dysregulated PI3K/AKT signaling is the first signaling pathway linked to Sweet syndrome and suggests that this syndrome may be caused by acquired mutations that modulate neutrophil function. Moreover, integration of molecular data across multiple levels identified a distinct subtype within a heterogeneous disease that resulted in a rational and successful clinical intervention. Future patients will benefit from efforts to identify potential mutations. The ability to directly interrogate the diseased skin allows this method to be generalizable to other inflammatory diseases and demonstrates a potential personalized medicine approach for patients with clinically challenging disease.Funding Sources Berstein Foundation, NIH, Veterans Affairs (VA) Administration, Moseley Foundation, and H.T. Leung Foundation.

Abstract Background:The Food and Drug Administration (FDA) reviews safety, efficacy, and the quality of medical devices through its regulatory process. The FDA Safety and Innovation Act (FDASIA) of 2012 was aimed at accelerating the regulatory process for medical devices. Objectives:The purpose of our study was to (1) quantify characteristics of pivotal clinical trials (PCTs) supporting the premarket approval of endovascular medical devices and (2) analyze trends over the last two decades in light of the FDASIA. Methods:We surveyed the study designs of endovascular devices with PCTs from the US FDA pre-market approval medical devices database. The effect of FDASIA on key design parameters (e.g., randomization, masking, and number of enrolled patients) was estimated using an interrupted time series analysis (segmented regression). Results:We identified 117 devices between 2000–2018. FDASIA was associated with a decrease in double blinding (p < 0.0001) and a decrease in historical comparators (p < 0.0001). Discussion:Our results reveal an overall trend of decreased regulatory requirements as it relates to clinical trial characteristics, but a compensatory increased rate of post-approval across device classes. Furthermore, there was an emphasis on proving equivalence or non-inferiority rather than more use of active comparators in clinical trials. Medical device stakeholders, notably clinicians, must be aware of the shifting regulatory landscape in order to play an active role in promoting patient safety.