Mpox and Vaccine Knowledge, Beliefs, and Sources of Trusted Information Among Gay, Bisexual, and Other Men Who Have Sex With Men in the U.S.

Introduction: This research aims to characterize disparities in mpox- and vaccine-related knowledge in gay, bisexual, and other men who have sex with men in the U.S. Methods: The authors conducted a study using the American Men's Internet Survey, which includes 823 cisgender (defined as their gender identity matching their sex assigned at birth) males aged ≥15 years from August 5 to 15, 2022. The authors evaluated sociodemographic and behavioral factors associated with mpox knowledge, including race/ethnicity, region, age group, and HIV pre-exposure prophylaxis use using chi-square tests. Results: The authors identified knowledge gaps, with many participants unsure about whether individuals need 2 doses of the vaccine (34.4%) and whether the vaccine confers immediate protection (27.2%). The authors observed racial and regional disparities (p<0.01), with 24.4% of non-Hispanic Black men and 18.1% of men living in the South reporting little to no mpox awareness. Among the 707 self-reported HIV-negative participants, people who used pre-exposure prophylaxis within the past year were more likely to exhibit high awareness about mpox than people who did not use pre-exposure prophylaxis. Conclusions: Findings suggest the potential to leverage existing networks (i.e., sexually transmitted infection or general health care services with pre-exposure prophylaxis use) for future targeted health service programming or education campaigns for mpox vaccination among gay, bisexual, and other men who have sex with men.

Lead optimisation of OXS007417: in vivo PK profile and hERG liability modulation to optimise a small molecule differentiation agent for the potential treatment of acute myeloid leukaemia.

The development of a safe, efficacious, and widely effective differentiation therapy for AML would dramatically improve the outlook for many patients worldwide. To this aim, our laboratory has discovered a class of differentiation agents that demonstrate tumour regression in murine models in vivo. Herein, we report a lead optimisation process around compound OXS007417, which led to improved potency, solubility, metabolic stability, and off-target toxicity of this compound class. A hERG liability was investigated and successfully alleviated through addition of nitrogen atoms into key positions of the compound. OXS008255 and OXS008474 demonstrated an improved murine PK profile in respect to OXS007417 and a delay in tumour growth in a subcutaneous in vivo model using HL-60 cells.

A review of methods for the analysis of diagnostic tests performed in sequence.

BACKGROUND: Many clinical pathways for the diagnosis of disease are based on diagnostic tests that are performed in sequence. The performance of the full diagnostic sequence is dictated by the diagnostic performance of each test in the sequence as well as the conditional dependence between them, given true disease status. Resulting estimates of performance, such as the sensitivity and specificity of the test sequence, are key parameters in health-economic evaluations. We conducted a methodological review of statistical methods for assessing the performance of diagnostic tests performed in sequence, with the aim of guiding data analysts towards classes of methods that may be suitable given the design and objectives of the testing sequence. METHODS: We searched PubMed, Scopus and Web of Science for relevant papers describing methodology for analysing sequences of diagnostic tests. Papers were classified by the characteristics of the method used, and these were used to group methods into themes. We illustrate some of the methods using data from a cohort study of repeat faecal immunochemical testing for colorectal cancer in symptomatic patients, to highlight the importance of allowing for conditional dependence in test sequences and adjustment for an imperfect reference standard. RESULTS: Five overall themes were identified, detailing methods for combining multiple tests in sequence, estimating conditional dependence, analysing sequences of diagnostic tests used for risk assessment, analysing test sequences in conjunction with an imperfect or incomplete reference standard, and meta-analysis of test sequences. CONCLUSIONS: This methodological review can be used to help researchers identify suitable analytic methods for studies that use diagnostic tests performed in sequence.

Cigarette smoking, e-cigarette use, and sociodemographic correlates of mental health and tobacco-related disease risk in the All of Us research program.

SIGNIFICANCE: Research on the conditions under which electronic cigarette (EC) use produces a net reduction in the population harm attributable to combusted cigarette (CC) use requires the triangulation of information from cohort(s) of smokers, non-smokers, EC users, and dual-users of all varieties. MATERIALS AND METHODS: This project utilizes data from the All of Us Research Program to contrast a panel of wellness and disease-risk indicators across a range of self-reported tobacco-use profiles, including smokers, current, and former EC users. This article focuses on the tobacco use history and current tobacco use status among All of Us participants enrolled between May 2017 and February 2023 (Registered Controlled Tier Curated Data Repository [CDR] v7). RESULTS: The present analytic sample included an unweighted total of N = 412 211 individuals with information on ever-use of both CC and EC. Among them, 155 901 individuals have a history of CC use, with 65 206 identified as current smokers. EC usage is reported by 64 002 individuals, with 16 619 being current users. Model predicted analyses identified distinct patterns in CC and EC usage across demographic and socioeconomic variables, with younger ages favoring ECs. DISCUSSION: Age was observed to significantly affect EC usage, and gender differences reveal that males were significantly more likely to use CC and/or EC than females or African Americans of any gender. Higher educational achievement and income were associated with lower use of both CC and EC, while lower levels of mental health were observed to increase the likelihood of using CC and EC products. CONCLUSION: Findings suggest the potential for the All of Us Research Program for investigation of causal factors driving both behavioral use transitions and cessation outcomes.

Performance of mixed effects models and generalized estimating equations for continuous outcomes in partially clustered trials including both independent and paired data.

Many clinical trials involve partially clustered data, where some observations belong to a cluster and others can be considered independent. For example, neonatal trials may include infants from single or multiple births. Sample size and analysis methods for these trials have received limited attention. A simulation study was conducted to (1) assess whether existing power formulas based on generalized estimating equations (GEEs) provide an adequate approximation to the power achieved by mixed effects models, and (2) compare the performance of mixed models vs GEEs in estimating the effect of treatment on a continuous outcome. We considered clusters that exist prior to randomization with a maximum cluster size of 2, three methods of randomizing the clustered observations, and simulated datasets with uninformative cluster size and the sample size required to achieve 80% power according to GEE-based formulas with an independence or exchangeable working correlation structure. The empirical power of the mixed model approach was close to the nominal level when sample size was calculated using the exchangeable GEE formula, but was often too high when the sample size was based on the independence GEE formula. The independence GEE always converged and performed well in all scenarios. Performance of the exchangeable GEE and mixed model was also acceptable under cluster randomization, though under-coverage and inflated type I error rates could occur with other methods of randomization. Analysis of partially clustered trials using GEEs with an independence working correlation structure may be preferred to avoid the limitations of mixed models and exchangeable GEEs.

Electrophysiology lab efficiency using cryoballoon for pulmonary vein isolation in Latin America: A sub-analysis of the Cryo Global Registry Study.

Objective: Cryoballoon ablation for pulmonary vein isolation is a time-efficient procedure that can alleviate stress on electrophysiology lab resources. This analysis modeled the impact of cryoballoon ablation on electrophysiology lab operation using data from Latin America. Methods: Data from centers in Argentina, Mexico, Colombia, and Chile of the were used as inputs for an electrophysiology lab efficiency simulation model. The model used the assumption that either two (today's electrophysiology lab operations) or three (including electrophysiology lab operational changes) cryoballoon ablation procedures could be performed per day. The endpoints were the percentage of days that resulted in 1) overtime and 2) time left for an extra non-ablation electrophysiology procedure. Results: Data from a total of 232 procedures from six Latin American centers were included in the analysis. The average electrophysiology lab occupancy time for all procedures in Latin America was 132 ± 62 minutes. In the Current Scenario (two procedures per day), 7.4% of simulated days resulted in overtime, and 81.4% had enough time for an extra electrophysiology procedure. In the Enhanced Productivity Scenario (three procedures per day), 16.4% of days used overtime, while 67.4% allowed time for an extra non-ablation electrophysiology procedure. Conclusions: Using real-world, Latin American-specific data, we found that with operational changes, three ablation procedures could feasibly be performed daily, leaving time for an extra electrophysiology procedure on more than half of days. Thus, use of cryoballoon ablation is an effective tool to enhance electrophysiology lab efficiency in resource-constrained regions such as Latin America.

Objetivos: La ablación con criobalón para el aislamiento de venas pulmonares es un procedimiento que ahorra tiempo y puede ahorrar recursos del laboratorio de electrofisiología. Este análisis modeló el impacto de la ablación con criobalón en el funcionamiento del laboratorio de electrofisiología utilizando datos de América Latina. Métodos: Los datos de los centros de Argentina, México, Colombia y Chile del se utilizaron como datos de entrada para un modelo de simulación de la eficiencia del laboratorio de electrofisiología. El modelo partió del supuesto de que se podían realizar dos (operaciones actuales del laboratorio de electrofisiología) o tres (incluidos los cambios operativos del laboratorio de electrofisiología) procedimientos de ablación con criobalón por día. Los criterios de valoración eran el porcentaje de días en los que se producían 1) horas extraordinarias y 2) tiempo restante para un procedimiento electrofisiológico adicional no relacionado con la ablación. Resultados: Se incluyeron en el análisis los datos un total de 232 procedimientos de seis centros latinoamericanos. El tiempo medio de ocupación del laboratorio de electrofisiología para todos los procedimientos en Latinoamérica fue de 132 ± 62 minutos. En el escenario actual (dos procedimientos por día), el 7,4% de los días simulados resultaron en horas extras, y el 81,4% tuvo tiempo suficiente para un procedimiento de electrofisiología adicional. En el escenario de productividad mejorada (tres procedimientos por día), el 16,4% de los días utilizó horas extraordinarias, mientras que el 67,4% dispuso de tiempo suficiente para un procedimiento electrofisiológico extra sin ablación. Conclusiones: Utilizando datos del mundo real específicos de América Latina, descubrimos que, aplicando cambios operativos, es factible realizar tres procedimientos de ablación al día, lo que deja tiempo para un procedimiento de electrofisiología adicional en más de la mitad de los días. Por lo tanto, el uso de la ablación con criobalón es una herramienta eficaz para mejorar la eficiencia de los laboratorios de electrofisiología en regiones con recursos limitados como América Latina.

A framework for medical physics compensation in an academic department.

Compensation is a key component of career satisfaction and professional growth. A new compensation model was developed to provide a framework for career growth and a compensation ladder for medical physicists with clinical responsibilities in an academic radiation oncology department. The goals for the new model were: (1) create a market competitive plan to support recruitment and retention of top physics talent, (2) incentivize clinical effort, innovation, citizenship/professional service, and academic achievement, (3) provide compensation growth opportunities separate from medical school promotions, and (4) create consistent, transparent, and fair metrics applicable to all clinical physicists in the department. The model includes a base salary, and credits for board certification, clinical tier, leadership, and academic level. Further, metrics were developed to inform the clinical tier. Years of experience is not explicitly included in the model. The model was successfully implemented for clinical physicists in a relatively large academic radiation oncology department.

The Effect of Spaced Repetition on Learning and Knowledge Transfer in a Large Cohort of Practicing Physicians.

PURPOSE: Spaced repetition is superior to repeated study for learning and knowledge retention, but literature on the effect of different spaced repetition strategies is lacking. The authors evaluated the effects of different spaced repetition strategies on long-term knowledge retention and transfer. METHOD: This prospective cohort study, conducted from October 1, 2020, through July 20, 2023, used the American Board of Family Medicine Continuous Knowledge Self-Assessment (CKSA) to assess learning and knowledge transfer of diplomates and residents. Participants were randomized to a control group or 1 of 5 spaced repetition conditions during 5 calendar quarters (January 1, 2021, to March 31, 2022). Participants in the spaced repetition groups received 6 repeated questions once or twice. Incorrectly but confidently answered questions were prioritized for repetition, with decreasing priority for questions answered incorrectly with lesser confidence. All participants received 6 rewritten questions corresponding to their initial questions chosen for repetition in quarter 10 (second quarter of calendar year 2023). RESULTS: A total of 26,258 family physicians or residents who completed the CKSA in the baseline period were randomized. Spaced repetition was superior to no spaced repetition for learning at quarter 6 (58.03% vs 43.20%, P < .001, Cohen d = 0.62) and knowledge transfer at quarter 10 (58.33% vs 52.39%, P < .001, Cohen d = 0.26). Double-spaced repetitions were superior to single-spaced repetitions for learning (62.24% vs 51.83%, P < .001, Cohen d = 0.43) and transfer (60.08% vs 55.72%, P < .001, Cohen d = 0.20). There were no meaningful differences in learning or transfer between repetition strategy chosen in the single- or double-repetition groups. CONCLUSIONS: This study affirms the value of spaced repetition in improving learning and retention in medical education and ongoing professional development.

Genomic prediction for potato (Solanum tuberosum) quality traits improved through image analysis.

Potato (Solanum tuberosum L.) is the most widely grown vegetable in the world. Consumers and processors evaluate potatoes based on quality traits such as shape and skin color, making these traits important targets for breeders. Achieving and evaluating genetic gain is facilitated by precise and accurate trait measures. Historically, quality traits have been measured using visual rating scales, which are subject to human error and necessarily lump individuals with distinct characteristics into categories. Image analysis offers a method of generating quantitative measures of quality traits. In this study, we use TubAR, an image-analysis R package, to generate quantitative measures of shape and skin color traits for use in genomic prediction. We developed and compared different genomic models based on additive and additive plus non-additive relationship matrices for two aspects of skin color, redness, and lightness, and two aspects of shape, roundness, and length-to-width ratio for fresh market red and yellow potatoes grown in Minnesota between 2020 and 2022. Similarly, we used the much larger chipping potato population grown during the same time to develop a multi-trait selection index including roundness, specific gravity, and yield. Traits ranged in heritability with shape traits falling between 0.23 and 0.85, and color traits falling between 0.34 and 0.91. Genetic effects were primarily additive with color traits showing the strongest effect (0.47), while shape traits varied based on market class. Modeling non-additive effects did not significantly improve prediction models for quality traits. The combination of image analysis and genomic prediction presents a promising avenue for improving potato quality traits.

Diverse RNA Structures Induce PRC2 Dimerization and Inhibit Histone Methyltransferase Activity.

Methyltransferase PRC2 (Polycomb Repressive Complex 2) introduces histone H3K27 trimethylation, a repressive chromatin mark, to tune the differential expression of genes. PRC2 is precisely regulated by accessory proteins, histone post-translational modifications and, notably, RNA. Research on PRC2-associated RNA has mostly focused on the tight-binding G-quadruplex (G4) RNAs, which inhibit PRC2 enzymatic activity in vitro and in cells. Our recent cryo-EM structure provided a molecular mechanism for G4 RNA inactivating PRC2 via dimerization, but it remained unclear how diverse RNAs associate with and regulate PRC2. Here, we show that a single-stranded G-rich RNA and an atypical G4 structure called pUG-fold unexpectedly also mediate near-identical PRC2 dimerization resulting in inhibition of PRC2 methyltransferase activity. The conformational flexibility of arginine-rich loops within subunits EZH2 and AEBP2 of PRC2 can accommodate diverse RNA secondary structures, resulting in protein-RNA and protein-protein interfaces similar to those observed previously with G4 RNA. Furthermore, we address a recent report that failed to detect PRC2-associated RNAs in living cells by demonstrating the insensitivity of PRC2-RNA interaction to photochemical crosslinking. Our results support the significance of RNA-mediated PRC2 regulation by showing that this interaction is not limited to a single RNA secondary structure, consistent with the broad PRC2 transcriptome containing many G-tract RNAs incapable of folding into G4 structures.

Evaluating the risk of SARS-CoV-2 reinfection with the Omicron or Delta variant in Wales, UK.

Recent studies suggest an increased risk of reinfection with the SARS-CoV-2 Omicron variant compared with previous variants, potentially due to an increased ability to escape immunity specific to older variants, high antigenic divergence of Omicron from earlier virus variants as well as its altered cell entry pathway. The present study sought to investigate epidemiological evidence for differential SARS-CoV-2 reinfection intervals and incidence rates for the Delta versus Omicron variants within Wales. Reinfections in Wales up to February 2022 were defined using genotyping and whole genome sequencing. The median inter-infection intervals for Delta and Omicron were 226 and 192 days, respectively. An incidence rate ratio of 2.17 for reinfection with Omicron compared to Delta was estimated using a conditional Poisson model, which accounted for several factors including sample collection date, age group, area of residence, vaccination and travel status. These findings are consistent with an increased risk of reinfection with the Omicron variant, and highlight the value of monitoring emerging variants that have the potential for causing further waves of cases.

A population genomics analysis of the Aotearoa New Zealand endemic rewarewa tree (Knightia excelsa).

Rewarewa (Knightia excelsa, Proteaceae) is a tree species endemic to Aotearoa New Zealand, with a natural distribution spanning Te Ika-a-Maui (North Island) and the top of Te Waipounamu (South Island). We used the pseudo-chromosome genome assembly of rewarewa as a reference and whole genome pooled sequencing from 35 populations sampled across Aotearoa New Zealand, including trees growing on Maori-owned land, to identify 1,443,255 single nucleotide polymorphisms (SNPs). Four genetic clusters located in the northern North Island (NNI), eastern North Island (NIE), western and southern North Island (NIWS), and the South Island (SI) were identified. Gene flow was revealed between the SI and NIE genetic clusters, plus bottleneck and contraction events within the genetic clusters since the mid-late Pleistocene, with divergence between North and South Island clusters estimated to have occurred ~115,000-230,000 years ago. Genotype environment analysis (GEA) was used to identify loci and genes linked with altitude, soil pH, soil carbon, slope, soil size, annual mean temperature, mean diurnal range, isothermality, annual precipitation, and precipitation seasonality. The location of the SNPs associated with these environmental variables was compared with the position of 52,192 gene-coding sequences that were predicted in the rewarewa genome using RNA sequencing. This new understanding of the genetic variation present in rewarewa and insights into the genetic control of adaptive traits will inform efforts to incorporate the species in restoration plantings and for marketing rewarewa honey based on provenance.

MAIT cell heterogeneity across paired human tissues reveals specialization of distinct regulatory and enhanced effector profiles.

Mucosal-associated invariant T (MAIT) cells are unconventional T cells that recognize microbial riboflavin pathway metabolites presented by evolutionarily conserved MR1 molecules. We explored the human MAIT cell compartment across organ donor-matched blood, barrier, and lymphoid tissues. MAIT cell population size was donor dependent with distinct tissue compartmentalization patterns and adaptations: Intestinal CD103+ resident MAIT cells presented an immunoregulatory CD39highCD27low profile, whereas MAIT cells expressing NCAM1/CD56 dominated in the liver and exhibited enhanced effector capacity with elevated response magnitude and polyfunctionality. Both intestinal CD39high and hepatic CD56+ adaptations accumulated with donor age. CD56+ MAIT cells displayed limited T cell receptor-repertoire breadth, elevated MR1 binding, and a transcriptional profile skewed toward innate activation pathways. Furthermore, CD56 was dynamically up-regulated to a persistent steady-state equilibrium after exposure to antigen or IL-7. In summary, we demonstrate functional heterogeneity and tissue site adaptation in resident MAIT cells across human barrier tissues with distinct regulatory and effector signatures.

Oral Pyronaridine Tetraphosphate Reduces Tissue Presence of Parasites in a Mouse Model of Chagas Disease.

The eukaryotic parasite Trypanosoma cruzi (T. cruzi) is responsible for Chagas disease, which results in heart failure in patients. The disease is more common in Latin America, and is an emerging infection with The Centers for Disease Control estimating that greater than 300,000 people are currently infected in the United States. This disease has also spread from South and Central America, where it is endemic to many other countries, including Australia, Japan, and Spain. Current therapy for Chagas disease is inadequate due to limited efficacy in the indeterminate and chronic phases of the disease, in addition to the adverse effects from nifurtimox and benznidazole, which are nitro-containing drugs used for therapy. There is a clear need for new therapies for the Chagas disease. Using a computational machine learning approach, we have previously shown that the antimalarial pyronaridine tetraphosphate is active against T. cruzi Brazil-luc in vitro against parasites infecting a myoblast cell line and is also active in vivo in an acute mouse model of Chagas disease when dosed i.p. We now further evaluated oral pyronaridine as a monotherapy to determine the minimum effective dose to treat acute and chronic models of Chagas disease. Our results for T. cruzi Brazil-luc demonstrated daily oral dosing with pyronaridine from 150 to 600 mg/kg resulted in statistically significant inhibition in the 7 day acute mouse model. Combination therapy with daily dosing of benznidazole and pyronaridine in the acute infection model demonstrated that 300 mg/kg pyronaridine could return statistically significant antiparasitic activity to a subtherapetic 10 mg/kg benznidazole. In contrast, pyronaridine as monotherapy or combined with benznidazole lacked efficacy in the chronic mouse model, whereas 100 mg/kg benznidazole alone demonstrated undetectable parasites in the heart of mice. Pyronaridine requires further assessment in other chronic models to identify if it can be used beyond the acute stage of T. cruzi infection.

Closing the gap between open source and commercial large language models for medical evidence summarization.

Large language models (LLMs) hold great promise in summarizing medical evidence. Most recent studies focus on the application of proprietary LLMs. Using proprietary LLMs introduces multiple risk factors, including a lack of transparency and vendor dependency. While open-source LLMs allow better transparency and customization, their performance falls short compared to the proprietary ones. In this study, we investigated to what extent fine-tuning open-source LLMs can further improve their performance. Utilizing a benchmark dataset, MedReview, consisting of 8161 pairs of systematic reviews and summaries, we fine-tuned three broadly-used, open-sourced LLMs, namely PRIMERA, LongT5, and Llama-2. Overall, the performance of open-source models was all improved after fine-tuning. The performance of fine-tuned LongT5 is close to GPT-3.5 with zero-shot settings. Furthermore, smaller fine-tuned models sometimes even demonstrated superior performance compared to larger zero-shot models. The above trends of improvement were manifested in both a human evaluation and a larger-scale GPT4-simulated evaluation.

"I probably shouldn't go in today": Inequitable access to paid sick leave and its impacts on health behaviors during the emergence of COVID-19 in the Seattle area.

This study examines inequities in access to paid sick leave (PSL) by race/ethnicity, income, and sex and the role of PSL access on leave-taking and care-seeking behaviors among Seattle-area workers in the months leading up to and during the emergence of COVID-19 in the region. Survey responses were collected online and in-person from individuals experiencing acute respiratory illness symptoms between November 2019 and March 2020 as part of a community-based respiratory viral surveillance study. Chi-square tests and log-binomial models were used to assess the association between PSL access and various socioeconomic indicators. A total of 66.6% (n = 2,276) respondents reported access to PSL. Proportionally, access to PSL was highest in respondents identifying as Asian (70.5%), followed by White (68.7%), Latine (58.4%), Multiracial (57.1%), Black (47.1%), and Other (43.1%). Access to PSL increased with household income. Eighty three percent of high-income respondents reported access compared to 52.9% of low-income households. Only 23.3% of the lowest-income households reported access to PSL. Fewer females (65.2%) than males (70.7%) reported access to PSL. Access to PSL is inequitably distributed across income, race/ethnicity, and sex. This study reinforces the vast body of knowledge on how socioeconomic inequalities increase individual and community-level vulnerability to the impacts of infectious disease outbreaks. It also supports the role of labor and economic policy in mitigating (or exacerbating) these impacts. Exemplified by the COVID-19 pandemic, universal access to PSL, especially for marginalized populations, benefits all.

KIR2DS2+ NK cells in cancer patients demonstrate high activation in response to tumour-targeting antibodies.

Strategies to mobilise natural killer (NK) cells against cancer include tumour-targeting antibodies, NK cell engagers (NKCEs) and the adoptive transfer of ex vivo expanded healthy donor-derived NK cells. Genetic and functional studies have revealed that expression of the activating killer immunoglobulin-like receptor KIR2DS2 is associated with enhanced function in NK cells from healthy donors and improved outcome in several different malignancies. The optimal strategy to leverage KIR2DS2+ NK cells therapeutically is however currently unclear. In this study, we therefore evaluated the response of KIR2DS2-expressing NK cells to activation against cancer with clinically relevant tumour-targeting antibodies and following ex vivo expansion. We identified that KIR2DS2high NK cells from patients with chronic lymphocytic leukaemia and hepatocellular carcinoma had enhanced activation in response to tumour-targeting antibodies compared to KIR2DS2- NK cells. However, the superior function of healthy donor derived KIR2DS2high NK cells was lost following ex vivo expansion which is required for adoptive transfer-based therapeutic strategies. These data provide evidence that targeting KIR2DS2 directly in cancer patients may allow for the utilisation of their enhanced effector function, however such activity may be lost following their ex vivo expansion.