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The rapid spread of SARS-CoV-2 caused the COVID-19 pandemic and accelerated vaccine development to prevent the spread of the virus and control the disease. Given the sustained high infectivity and evolution of SARS-CoV-2, there is an ongoing interest in developing COVID-19 serology tests to monitor population-level immunity. To address this critical need, we designed a paper-based multiplexed vertical flow assay (xVFA) using five structural proteins of SARS-CoV-2, detecting IgG and IgM antibodies to monitor changes in COVID-19 immunity levels. Our platform not only tracked longitudinal immunity levels but also categorized COVID-19 immunity into three groups: protected, unprotected, and infected, based on the levels of IgG and IgM antibodies. We operated two xVFAs in parallel to detect IgG and IgM antibodies using a total of 40 μL of human serum sample in

This column is intended to address the kinds of knotty problems and dilemmas with which many scholars grapple in studying health professions education. In this article, the authors address the challenges in proofreading a manuscript. Emerging researchers might think that someone in the production team will catch any errors. This may not always be the case. We emphasize the importance of guiding mentees to take the process of preparing a manuscript for submission seriously.

OBJECTIVE: To investigate the feasibility of pre- and post-encounter patient-reported outcome (PRO) measure collection within an outpatient integrative health and medicine (IHM) clinic and to characterize factors associated with successful completion. METHODS: We conducted a retrospective review of 27,464 outpatient IHM encounters including 9,520 chiropractic; 8,237 acupuncture; 5,847 massage; 2,345 IHM consultation; and 1,515 osteopathic manipulation treatment encounters at four clinics offering IHM over 18 months. Patients were asked to complete paper questionnaires rating pain, anxiety, and stress from 0-10 immediately pre- and post-encounter. Generalized linear mixed effect regression models were used to examine the relationship between demographic, clinical, and operational covariates and completing (1) pre-encounter and (2) paired (i.e., pre and post) PROs. RESULTS: Patients (N = 5587, mean age 49 years, 74% white, 77% female) generally presented for musculoskeletal conditions (81.7%), with a chief complaint of pain (55.1%). 21,852 (79.6%) encounters were among patients who completed pre-encounter PROs; 11,709/21,852 (53.6%) completed subsequent post-encounter PROs. Odds of PRO completion were more impacted by provider, operational, and clinical-level factors than patient factors. Covariates associated with increased odds of pre-encounter PRO completion included being female, having additional IHM encounters, and having a pain or anxiety complaint. Covariates associated with increased odds of paired PRO completion included being aged 31-40 vs. 51-60 years and having additional IHM encounters. CONCLUSION: Implementing a paper-based PRO collection system in outpatient IHM is feasible; however, collecting post-encounter PROs was challenging. Future endeavors should leverage the electronic health record and patient portals to optimize PRO collection and engage patients and clinical providers.

PURPOSE OF REVIEW: Environmental chemical exposures may disrupt child development, with long-lasting health impacts. To date, U.S. studies of early environmental exposures have been limited in size and diversity, hindering power and generalizability. With harmonized data from over 60,000 participants representing 69 pregnancy cohorts, the National Institutes of Healths Environmental influences on Child Health Outcomes (ECHO) Program is the largest study of U.S. childrens health. Here, we: (1) review ECHO-wide studies of chemical exposures and maternal-child health; and (2) outline opportunities for future research using ECHO data. RECENT FINDINGS: As of early 2024, in addition to over 200 single-cohort (or award) papers on chemical exposures supported by ECHO, ten collaborative multi-cohort papers have been made possible by ECHO data harmonization and new data collection. Multi-cohort papers have examined prenatal exposure to per- and polyfluoroalkyl substances (PFAS), phthalates, phenols and parabens, organophosphate esters (OPEs), metals, melamine and aromatic amines, and emerging contaminants. They have primarily focused on describing patterns of maternal exposure or examining associations with maternal and infant outcomes; fewer studies have examined later child outcomes (e.g., autism) although follow up of enrolled ECHO children continues. The NICHDs Data and Specimen Hub (DASH) database houses extensive ECHO data including over 470,000 chemical assay results and complementary data on priority outcome areas (pre, peri-, and postnatal, airway, obesity, neurodevelopment, and positive health), making it a rich resource for future analyses. ECHOs extensive data repository, including biomarkers of chemical exposures, can be used to advance our understanding of environmental influences on childrens health. Although few published studies have capitalized on these unique harmonized data to date, many analyses are underway with data now widely available.

Donor human milk (DHM) from a milk bank is the recommended feeding method for preterm infants when the mothers own milk (MOM) is not available. Despite this recommendation, information on the possible contamination of donor human milk and its impact on infant health outcomes is poorly characterised. The aim of this systematic review is to assess contaminants present in DHM samples that preterm and critically ill infants consume. The data sources used include PubMed, EMBASE, CINAHL and Web of Science. A search of the data sources targeting DHM and its potential contaminants yielded 426 publications. Two reviewers (S. T. and D. L.) conducted title/abstract screening through Covidence software, and predetermined inclusion/exclusion criteria yielded 26 manuscripts. Contaminant types (bacterial, chemical, fungal, viral) and study details (e.g., type of bacteria identified, study setting) were extracted from each included study during full-text review. Primary contaminants in donor human milk included bacterial species and environmental pollutants. We found that bacterial contaminants were identified in 100% of the papers in which bacterial contamination was sought (16 papers) and 61.5% of the full data set (26 papers), with the most frequently identified genera being Staphylococcus (e.g., Staphylococcus aureus and coagulase-negative Staphylococcus) and Bacillus (e.g., Bacillus cereus). Chemical pollutants were discovered in 100% of the papers in which chemical contamination was sought (eight papers) and 30.8% of the full data set (26 papers). The most frequently identified chemical pollutants included perfluoroalkyl substances (six papers), toxic metal (one paper) and caffeine (one paper). Viral and fungal contamination were identified in one paper each. Our results highlight the importance of establishing standardisation in assessing DHM contamination and future studies are needed to clarify the impact of DHM contaminants on health outcomes.

The use of the p-value in quantitative research, particularly its threshold of P < 0.05 for determining statistical significance, has long been a cornerstone of statistical analysis in research. However, this standard has been increasingly scrutinized for its potential to mislead findings, especially when the practical significance, the number of comparisons, or the suitability of statistical tests are not properly considered. In response to controversy around use of p-values, the American Statistical Association published a statement in 2016 that challenged the research community to abandon the term statistically significant. This stance has been echoed by leading scientific journals to urge a significant reduction or complete elimination in the reliance on p-values when reporting results. To provide guidance to researchers in health professions education, this paper provides a succinct overview of the ongoing debate regarding the use of p-values and the definition of p-values. It reflects on the controversy by highlighting the common pitfalls associated with p-value interpretation and usage, such as misinterpretation, overemphasis, and false dichotomization between significant and non-significant results. This paper also outlines specific recommendations for the effective use of p-values in statistical reporting including the importance of reporting effect sizes, confidence intervals, the null hypothesis, and conducting sensitivity analyses for appropriate interpretation. These considerations aim to guide researchers toward a more nuanced and informative use of p-values.

Magnetic resonance-guided focused ultrasound (MRgFUS) is a noninvasive, incisionless, radiation-free technology used to ablate tissue deep within the body. This technique has gained increased popularity following FDA approval for treatment of pain related to bone metastases and limited approval for treatment of osteoid osteoma. MRgFUS delivers superior visualization of soft tissue targets in unlimited imaging planes and precision in targeting and delivery of thermal dose which is all provided during real-time monitoring using MR thermometry. This paper provides an overview of the common musculoskeletal applications of MRgFUS along with updates on clinical outcomes and discussion of future applications.

Recently, we have proposed simple methodology to derive clearance and rate constant equations, independent of differential equations, based on Kirchhoff's Laws, a common methodology from physics used to describe rate-defining processes either in series or parallel. Our approach has been challenged in three recent publications, two published in this journal, but notably what is lacking is that none evaluate experimental pharmacokinetic data. As reviewed here, manuscripts from our laboratory have evaluated published experimental data, demonstrating that the Kirchhoff's Laws approach explains (1) why all of the experimental perfused liver clearance data appear to fit the equation that was previously believed to be the well-stirred model, (2) why linear pharmacokinetic systemic bioavailability determinations can be greater than 1, (3) why renal clearance can be a function of drug input processes, and (4) why statistically different bioavailability measures may be found for urinary excretion versus systemic concentration measurements. Our most recent paper demonstrates (5) how the universally accepted steady-state clearance approach used by the field for the past 50 years leads to unrealistic outcomes concerning the relationship between liver-to-blood Kpuu and hepatic availability FH , highlighting the potential for errors in pharmacokinetic evaluations based on differential equations. The Kirchhoff's Laws approach is applicable to all pharmacokinetic analyses of quality experimental data, those that were previously adequately explained with present pharmacokinetic theory, and those that were not. The publications that have attempted to rebut our position do not address unexplained experimental data, and we show here why their analyses are not valid. SIGNIFICANCE STATEMENT: The Kirchhoff's Laws approach to deriving clearance equations for linear systems in parallel or in series, independent of differential equations, successfully describes published pharmacokinetic data that has previously been unexplained. Three recent publications claim to refute our proposed methodology; these publications only make theoretical arguments, do not evaluate experimental data, and never demonstrate that the Kirchhoff methodology provides incorrect interpretations of experimental pharmacokinetic data, including statistically significant data not explained by present pharmacokinetic theory. We demonstrate why these analyses are invalid.

Articular cartilage damage and degeneration are among hallmark manifestations of joint injuries and arthritis, classically osteoarthritis. Cartilage compositional MRI (Cart-C MRI), a quantitative technique, which aims to detect early-stage cartilage matrix changes that precede macroscopic alterations, began development in the 1990s. However, despite the significant advancements over the past three decades, Cart-C MRI remains predominantly a research tool, hindered by various technical and clinical hurdles. This paper will review the technical evolution of Cart-C MRI, delve into its clinical applications, and conclude by identifying the existing gaps and challenges that need to be addressed to enable even broader clinical application of Cart-C MRI.

BACKGROUND: Dietary supplement (DS) use is common and increasing among older adults, though much data available on use frequencies are from surveys and performed cross-sectionally. This paper sought to assess the frequency and pattern of dietary supplement use among older adults over time. METHODS: A secondary analysis of data from the AAA LongROAD study, a longitudinal prospective cohort study of older adult drivers, using data from baseline and the first two years of follow up included a total of 2990 drivers aged 65-79 years recruited at five study sites across the US from July 2015 to March 2017. Participants underwent baseline and annual evaluations, which included a brown bag medication review. DS were identified and categorized according to type and key components. Prevalence and pattern of DS use over time and relationship to demographics were measured with frequency and Chi squared analyses. RESULTS: 84% of participants took at least one dietary supplement during the 2-year study period, and 55% of participants continually reported use. DS accounted for approximately 30% of the total pharmacologic-pill burden in all years. Participants who were White non-Hispanic, female, 75-79 years of age at baseline, and on more non-supplement medications took significantly more dietary supplements (P

Point-of-care serological and direct antigen testing offers actionable insights for diagnosing challenging illnesses, empowering distributed health systems. Here, we report a POC-compatible serologic test for Lyme disease (LD), leveraging synthetic peptides specific to LD antibodies and a paper-based platform for rapid, and cost-effective diagnosis. Antigenic epitopes conserved across Borrelia burgdorferi genospecies, targeted by IgG and IgM antibodies, are selected to develop a multiplexed panel for detection of LD antibodies from patient sera. Multiple peptide epitopes, when combined synergistically with a machine learning-based diagnostic model achieve high sensitivity without sacrificing specificity. Blinded validation with 15 LD-positive and 15 negative samples shows 95.5% sensitivity and 100% specificity. Blind testing with the CDCs LD repository samples confirms the test accuracy, matching lab-based two-tier results, correctly differentiating between LD and look-alike diseases. This LD diagnostic test could potentially replace the cumbersome two-tier testing, improving diagnosis and enabling earlier treatment while facilitating immune monitoring and surveillance.

Antibodies are used in many areas of biomedical and clinical research, but many of these antibodies have not been adequately characterized, which casts doubt on the results reported in many scientific papers. This problem is compounded by a lack of suitable control experiments in many studies. In this article we review the history of the antibody characterization crisis, and we document efforts and initiatives to address the problem, notably for antibodies that target human proteins. We also present recommendations for a range of stakeholders - researchers, universities, journals, antibody vendors and repositories, scientific societies and funders - to increase the reproducibility of studies that rely on antibodies.

Wearable activity sensors typically count movement quantity, such as the number of steps taken or the number of upper extremity (UE) counts achieved. However, for some applications, such as neurologic rehabilitation, it may be of interest to quantify the quality of the movement experience (QOME), defined, for example, as how diverse or how complex movement epochs are. We previously found that individuals with UE impairment after stroke exhibited differences in their distributions of forearm postures across the day and that these differences could be quantified with kurtosis-an established statistical measure of the peakedness of distributions. In this paper, we describe further progress toward the goal of providing real-time feedback to try to help people learn to modulate their movement diversity. We first asked the following: to what extent do different movement activities induce different values of kurtosis? We recruited seven unimpaired individuals and evaluated a set of 12 therapeutic activities for their forearm postural diversity using kurtosis. We found that the different activities produced a wide range of kurtosis values, with conventional rehabilitation therapy exercises creating the most spread-out distribution and cup stacking the most peaked. Thus, asking people to attempt different activities can vary movement diversity, as measured with kurtosis. Next, since kurtosis is a computationally expensive calculation, we derived a novel recursive algorithm that enables the real-time calculation of kurtosis. We show that the algorithm reduces computation time by a factor of 200 compared to an optimized kurtosis calculation available in SciPy, across window sizes. Finally, we embedded the kurtosis algorithm on a commercial smartwatch and validated its accuracy using a robotic simulator that wore the smartwatch, emulating movement activities with known kurtosis. This work verifies that different movement tasks produce different values of kurtosis and provides a validated algorithm for the real-time calculation of kurtosis on a smartwatch. These are needed steps toward testing QOME-focused, wearable rehabilitation.

One of Californias most pressing social and environmental challenges is the rapid expansion of the wildlands-urban interface (WUI). Multiple issues associated with WUI growth compared to more dense and compact urban form are of concern-including greatly increased fire risk, greenhouse gas emissions, and fragmentation of habitat. However, little is understood about the factors driving this growth in the first place and, specifically, its relationship to urban-regional housing dynamics. This paper connects work in urban social science, urban and regional planning, and natural sciences to highlight the potential role of housing crises in driving displacement from the urban core to relatively more affordable exurbs, and with this, WUI growth. We analyze this relationship in California, which leads the nation in lack of affordable housing, scale of WUI growth, and many associated WUI hazards, including wildfire. We offer three related arguments: first, that Californias affordable housing crisis, with its effect of driving migration to exurban areas, should be recognized as a significant urban form-related sustainability challenge; second, that to understand this challenge scholars must expand the spatial scale and analytic toolkit of both urban and WUI analysis through relational, mixed methods research; and third, that political and programmatic efforts to address Californias housing crisis should undergird efforts to address WUI growth and climate change. Ultimately, we argue that expanding access to affordable urban housing can produce a more sustainable and just urban form that mitigates WUI-related climate and environmental impacts and reduces the vulnerability of growing numbers of WUI residents living in harms way.

Aortic dissection, a critical cardiovascular condition with life-threatening implications, is distinguished by the development of a tear and its propagation within the aortic wall. A thorough understanding of the initiation and progression of these tears, or cracks, is essential for accurate diagnosis and effective treatment. This paper undertakes a fracture mechanics approach to delve into the mechanics of tear propagation in aortic dissection. Our objective is to elucidate the impact of geometric and material parameters, providing valuable insights into the determinants of this pivotal cardiovascular event. Through our investigation, we have gained an understanding of how various parameters influence the energy release rate for tear propagation in both longitudinal and circumferential directions, aligning our findings with clinical data.

BackgroundCognitive impairment and dementia are frequently under-recognized. Health system strategies anchored in primary care are essential to address gaps in timely, comprehensive diagnosis. The goal of this paper is to describe the adaptation of a tablet-based brain health assessment (TabCAT-BHA) intervention and the study protocol to test its effectiveness in improving the detection of cognitive impairment, including dementia.MethodsThis mixed-methods, pragmatic, cluster randomized, hybrid effectiveness-implementation trial is being conducted in two 18-month waves with 26 Kaiser Permanente Southern California primary care clinics, with 13 serving as intervention clinics and 13 as usual care clinics. Patients 65 years and older with memory concerns (n ~ 180,000) receiving care at the 26 clinics will be included in the analyses. Primary care clinics are provided the following practice supports as part of the TabCAT-BHA intervention: brief education and training on neurocognitive disorders and study workflows; digital tools to assess cognitive function and support clinician decision making and documentation; and registered nurse support during the work-up and post-diagnosis periods for primary care providers, patients, and families. The intervention was adapted based on engagement with multiple levels of clinical and operational leaders in the healthcare system. Effectiveness outcomes include rates of cognitive impairment diagnosis in primary care and rates of completed standardized cognitive assessments and specialist referrals with incident diagnoses. Implementation outcomes include acceptability-appropriateness-feasibility, adoption, and fidelity.ResultsWe identified seven themes organized by system-, provider-, and patient-level domains that were used to adapt the TabCAT-BHA intervention. Accordingly, changes were made to the provider education, diagnostic work-up, and post-diagnostic support. Results will be reported in fall of 2027.ConclusionsOur engagement with multiple primary and specialty care clinical and operational leaders to adapt the TabCAT-BHA intervention to these primary care clinics has informed the protocol to evaluate the interventions effectiveness for improving the detection of cognitive impairment, including dementia, in an integrated healthcare system.Trial registationClinicaltrials.gov: NCT06090578 (registered 10/24/23).

BACKGROUND: Safer conception services are needed to minimize HIV transmission among HIV sero-discordant couples desiring pregnancy. Few studies have evaluated the choices couples make when they are offered multiple safer conception methods or real-world method acceptability. This paper addresses an important knowledge gap regarding factors that influence the choice of safer conception methods, couples actual experiences using safer conception methods, and why some couples switch safer conception methods. METHODS: Between February and June 2019, we conducted semi-structured in-depth interviews among 14 men and 17 women, representing 17 couples who exited the SAFER study-a pilot safer conception study for HIV sero-discordant couples in Zimbabwe that offered couples a choice of ART with monthly viral load monitoring (ART/VL), oral PrEP, vaginal insemination, and semen washing. All couples in SAFER had used at least two safer conception methods. RESULTS: We found that safer conception method choice often centered around a desire for intimacy, condomless sex, and certainty in the conception process, particularly for men. Method-related attributes such as familiarity, perceived ease of use, side effects, and perceived level of effectiveness in preventing HIV and achieving pregnancy influenced method choice, switching, and satisfaction. Concerns were expressed about each safer conception method and couples were willing to try different methods until they found method(s) that worked for them. The majority of participants reported having positive experiences using safer conception, especially those using ART/VL + PrEP, citing that they were able to attempt pregnancy for the first time with peace of mind and experienced joy and satisfaction from being able to achieve pregnancy safely. CONCLUSIONS: The differences in method preferences and experiences voiced by participants in this study and in other studies from the region point to the importance of having a variety of safer conception options in the service delivery package and addressing concerns about paternity, intimacy, and method-related attributes to enable HIV sero-discordant couples to safely achieve their reproductive goals.

Congestive heart failure (CHF) is a fatal disease with progressive severity and no cure; the hearts inability to adequately pump blood leads to fluid accumulation and frequent hospital readmissions after initial treatments. Therefore, it is imperative to continuously monitor CHF patients during its early stages to slow its progression and enable timely medical interventions for optimal treatment. An increase in interstitial fluid pressure (IFP) is indicative of acute CHF exacerbation, making IFP a viable biomarker for predicting upcoming CHF if continuously monitored. In this paper, we present an inductor-capacitor (LC) sensor for subcutaneous wireless and continuous IFP monitoring. The sensor is composed of inexpensive planar copper coils defined by a simple craft cutter, which serves as both the inductor and capacitor. Because of its sensing mechanism, the sensor does not require batteries and can wirelessly transmit pressure information. The sensor has a low-profile form factor for subcutaneous implantation and can communicate with a readout device through 4 layers of skin (12.7 mm thick in total). With a soft silicone rubber as the dielectric material between the copper coils, the sensor demonstrates an average sensitivity as high as -8.03 MHz/mmHg during in vitro simulations.

The functional state of cells is dependent on their microenvironmental context. Prior studies described how polarizing cytokines alter macrophage transcriptomes and epigenomes. Here, we characterized the functional responses of 6 differentially polarized macrophage populations by measuring the dynamics of transcription factor nuclear factor κB (NF-κB) in response to 8 stimuli. The resulting dataset of single-cell NF-κB trajectories was analyzed by three approaches: (1) machine learning on time-series data revealed losses of stimulus distinguishability with polarization, reflecting canalized effector functions. (2) Informative trajectory features driving stimulus distinguishability (signaling codons) were identified and used for mapping a cell state landscape that could then locate macrophages conditioned by an unrelated condition. (3) Kinetic parameters, inferred using a mechanistic NF-κB network model, provided an alternative mapping of cell states and correctly predicted biochemical findings. Together, this work demonstrates that a single analytes dynamic trajectories may distinguish the functional states of single cells and molecular network states underlying them. A record of this papers transparent peer review process is included in the supplemental information.

Adolescence is a period of normative heightened sensitivity to peer influence. Individual differences in susceptibility to peers is related to individual differences in neural sensitivity, particularly in brain regions that support an increasingly greater orientation toward peers. Despite these empirically-established patterns, the more specific psychosocial and socio-cognitive factors associated with individual differences in neural sensitivity to peer influence are just beginning to gain research attention. Specific features of the factors that contribute to how adolescents process social information can inform understanding of the psychological and neurobiological processes involved in what renders adolescents to be more or less susceptible to peer influences. In this paper, we (1) review the literature about peer, family, and broader contextual influences on sensitivity to peers' positive and negative behaviors, (2) outline components of social information processing theories, and (3) discuss features of these models from the perspectives and social cognitive development and social neuroscience. We identify gaps in the current literature that need to be addressed in order to gain a more comprehensive view of adolescent neural sensitivity to peer influence. We conclude by suggesting how future neuroimaging studies can adopt components of this social information processing model to generate new lines of research.

Oculomotor deficits are common in hereditary ataxia, but disproportionally neglected in clinical ataxia scales and as outcome measures for interventional trials. Quantitative assessment of oculomotor function has become increasingly available and thus applicable in multicenter trials and offers the opportunity to capture severity and progression of oculomotor impairment in a sensitive and reliable manner. In this consensus paper of the Ataxia Global Initiative Working Group On Digital Oculomotor Biomarkers, based on a systematic literature review, we propose harmonized methodology and measurement parameters for the quantitative assessment of oculomotor function in natural-history studies and clinical trials in hereditary ataxia. MEDLINE was searched for articles reporting on oculomotor/vestibular properties in ataxia patients and a study-tailored quality-assessment was performed. One-hundred-and-seventeen articles reporting on subjects with genetically confirmed (n=1134) or suspected hereditary ataxia (n=198), and degenerative ataxias with sporadic presentation (n=480) were included and subject to data extraction. Based on robust discrimination from controls, correlation with disease-severity, sensitivity to change, and feasibility in international multicenter settings as prerequisite for clinical trials, we prioritize a core-set of five eye-movement types: (i) pursuit eye movements, (ii) saccadic eye movements, (iii) fixation, (iv) eccentric gaze holding, and (v) rotational vestibulo-ocular reflex. We provide detailed guidelines for their acquisition, and recommendations on the quantitative parameters to extract. Limitations include low study quality, heterogeneity in patient populations, and lack of longitudinal studies. Standardization of quantitative oculomotor assessments will facilitate their implementation, interpretation, and validation in clinical trials, and ultimately advance our understanding of the evolution of oculomotor network dysfunction in hereditary ataxias.

BACKGROUND: Biochemical recurrence (BCR) following primary interventional treatment occurs in approximately one-third of patients with prostate cancer (PCa). Next-generation imaging (NGI) can identify local and metastatic recurrence with greater sensitivity than conventional imaging, potentially allowing for more effective interventions. This narrative review examines the current clinical evidence on the utility of NGI for patients with BCR. METHODS: A search of PubMed was conducted to identify relevant publications on NGI applied to BCR. Given other relevant recent reviews on the topic, this review focused on papers published between January 2018 to May 2023. RESULTS: NGI technologies, including positron emission tomography (PET) radiotracers and multiparametric magnetic resonance imaging, have demonstrated increased sensitivity and selectivity for diagnosing BCR at prostate-specific antigen (PSA) concentrations

ObjectiveBlockchain has emerged as a potential data-sharing structure in healthcare because of its decentralization, immutability, and traceability. However, its use in the biomedical domain is yet to be investigated comprehensively, especially from the aspects of implementation and evaluation, by existing blockchain literature reviews. To address this, our review assesses blockchain applications implemented in practice and evaluated with quantitative metrics.Materials and methodsThis systematic review adapts the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework to review biomedical blockchain papers published by August 2023 from 3 databases. Blockchain application, implementation, and evaluation metrics were collected and summarized.ResultsFollowing screening, 11 articles were included in this review. Articles spanned a range of biomedical applications including COVID-19 medical data sharing, decentralized internet of things (IoT) data storage, clinical trial management, biomedical certificate storage, electronic health record (EHR) data sharing, and distributed predictive model generation. Only one article demonstrated blockchain deployment at a medical facility.DiscussionEthereum was the most common blockchain platform. All but one implementation was developed with private network permissions. Also, 8 articles contained storage speed metrics and 6 contained query speed metrics. However, inconsistencies in presented metrics and the small number of articles included limit technological comparisons with each other.ConclusionWhile blockchain demonstrates feasibility for adoption in healthcare, it is not as popular as currently existing technologies for biomedical data management. Addressing implementation and evaluation factors will better showcase blockchain's practical benefits, enabling blockchain to have a significant impact on the health sector.

Machine learning (ML) methods are proliferating in scientific research. However, the adoption of these methods has been accompanied by failures of validity, reproducibility, and generalizability. These failures can hinder scientific progress, lead to false consensus around invalid claims, and undermine the credibility of ML-based science. ML methods are often applied and fail in similar ways across disciplines. Motivated by this observation, our goal is to provide clear recommendations for conducting and reporting ML-based science. Drawing from an extensive review of past literature, we present the REFORMS checklist (recommendations for machine-learning-based science). It consists of 32 questions and a paired set of guidelines. REFORMS was developed on the basis of a consensus of 19 researchers across computer science, data science, mathematics, social sciences, and biomedical sciences. REFORMS can serve as a resource for researchers when designing and implementing a study, for referees when reviewing papers, and for journals when enforcing standards for transparency and reproducibility.

An important difference between brains and deep neural networks is the way they learn. Nervous systems learn online where a stream of noisy data points are presented in a non-independent, identically distributed way. Further, synaptic plasticity in the brain depends only on information local to synapses. Deep networks, on the other hand, typically use non-local learning algorithms and are trained in an offline, non-noisy, independent, identically distributed setting. Understanding how neural networks learn under the same constraints as the brain is an open problem for neuroscience and neuromorphic computing. A standard approach to this problem has yet to be established. In this paper, we propose that discrete graphical models that learn via an online maximum a posteriori learning algorithm could provide such an approach. We implement this kind of model in a neural network called the Sparse Quantized Hopfield Network. We show our model outperforms state-of-the-art neural networks on associative memory tasks, outperforms these networks in online, continual settings, learns efficiently with noisy inputs, and is better than baselines on an episodic memory task.

The intensity of global groundwater use rose from 124 m3 per capita in 1950 to 152 m3 in 2021, for a 22.6% rise in the annual per capita use. This rise in global per capita water use reflects rising consumption patterns. The global use of groundwater, which provides between 21% and 30% of the total freshwater annual consumption, will continue to expand due to the sustained population growth projected through most of the 21st century and the important role that groundwater plays in the water-food-energy nexus. The rise in groundwater use, on the other hand, has inflicted adverse impacts in many aquifers, such as land subsidence, sea water intrusion, stream depletion, and deterioration of groundwater-dependent ecosystems, groundwater-quality degradation, and aridification. This paper projects global groundwater use between 2025 and 2050. The projected global annual groundwater withdrawal in 2050 is 1535 km3 (1 km3 = 109 m3 = 810,713 acre-feet). The projected global groundwater depletion, that is, the excess of withdrawal over recharge, in 2050 equals 887 km3, which is about 61% larger than in 2021. This projection signals probable exacerbation of adverse groundwater-withdrawal impacts, which are worsened by climatic trends and the environmental requirement of groundwater flow unless concerted national and international efforts achieve groundwater sustainability.

This paper describes the SocialVidStim-a database of video stimuli available to the scientific community depicting positive and negative social evaluative and neutral statements. The SocialVidStim comprises 53 diverse individuals reflecting the demographic makeup of the USA, ranging from 9 to 41 years old, saying 20-60 positive and 20-60 negative social evaluative statements (e.g. 'You are a very trustworthy/annoying person'), and 20-60 neutral statements (e.g. 'The sky is blue'), totaling 5793 videos post-production. The SocialVidStim are designed for use in behavioral and functional magetic resonance imaging paradigms, across developmental stages, in diverse populations. This study describes stimuli development and reports initial validity and reliability data on a subset videos (N = 1890) depicting individuals aged 18-41 years. Raters perceive videos as expected: positive videos elicit positively valenced ratings, negative videos elicit negatively valenced ratings and neutral videos are rated as neutral. Test-retest reliability data demonstrate intraclass correlations in the good-to-excellent range for negative and positive videos and the moderate range for neutral videos. We also report small effects on valence and arousal that should be considered during stimuli selection, including match between rater and actor sex and actor believability. The SocialVidStim is a resource for researchers and we offer suggestions for using the SocialVidStim in future research.

The blood-brain barrier (BBB) poses a significant obstacle in developing therapeutics for neurodegenerative diseases and central nervous system (CNS) disorders. P-glycoprotein (P-gp), a multidrug resistance protein, is a critical gatekeeper in the BBB and plays a role in cancer chemoresistance. This paper uses cryo-EM P-gp structures as starting points with an induced fit docking (IFD) model to evaluate 19 pairs of compounds with known P-gp efflux data. The study reveals significant differences in binding energy and sheds light on structural modifications impact on efflux properties. In the cases examined, fluorine incorporation influences the efflux by altering the molecular conformation rather than proximal heteroatom basicity. Although there are limitations in addressing covalent interactions or when binding extends into the more flexible vestibule region of the protein, the results provide valuable insights and potential strategies to overcome P-gp efflux, contributing to the advancement of drug development for both CNS disorders and cancer therapies.

Radiation therapy (RT) plays a crucial role in the treatment of head and neck cancers (HNCs). This paper emphasizes the importance of effective communication and collaboration between radiation oncologists and dental specialists in the HNC care pathway. It also provides an overview of the role of RT in HNC treatment and illustrates the interdisciplinary collaboration between these teams to optimize patient care, expedite treatment, and prevent post-treatment oral complications. The methods utilized include a thorough analysis of existing research articles, case reports, and clinical guidelines, with terms such as dental management, oral oncology, head and neck cancer, and radiotherapy included for this review. The findings underscore the significance of the early involvement of dental specialists in the treatment planning phase to assess and prepare patients for RT, including strategies such as prophylactic tooth extraction to mitigate potential oral complications. Furthermore, post-treatment oral health follow-up and management by dental specialists are crucial in minimizing the incidence and severity of RT-induced oral sequelae. In conclusion, these proactive measures help minimize dental and oral complications before, during, and after treatment.

BACKGROUND: Reducing malnutrition is a key priority for governments in low- and middle-income countries given its lasting effects on child development, health, income, and economic growth. Strategies to improve recommended infant and young child feeding (IYCF) practices, especially during the first two years of life, are considered among the most effective. METHODS: In this paper, we evaluate the long-run impacts of an innovative education strategy based on interactive play and performing arts implemented in El Alto, Bolivia on caregivers IYCF knowledge and practices. Two thousand and fifteen households were randomly assigned to intervention and control groups. Two rounds of data were collected approximately 30 and 42 months after baseline. We estimate short-term (30 month) and longer-term (42 month) intent-to-treat effects using multivariate linear regression analysis, with and without controlling for covariates. RESULTS: The program significantly increased caregiver IYCF knowledge by 0.13 SDs in the short run, and this effect grew over time. The program also improved adherence to recommended IYCF practices by 0.23 standard deviations (SDs) in the short term, but the effect on practices dissipated over time, and no longer-term impacts were detected. Caregivers with above median baseline knowledge, number of children, and age appear to have benefited most from the program. CONCLUSIONS: Our findings suggest that entertainment-education interventions are a promising model for improving and maintaining IYCF knowledge. However, their ability to sustain more permanent changes in IYCF practices is less certain. Further evidence is needed to identify other avenues for producing long-term, sustainable behavior change, especially among indigenous populations in Latin America, where literature on education and behavior-change interventions related to IYCF practices is limited.

We present an overview of the Conference on Transformative Opportunities for Modeling in Neurorehabilitation held in March 2023. It was supported by the Disability and Rehabilitation Engineering (DARE) program from the National Science Foundations Engineering Biology and Health Cluster. The conference brought together experts and trainees from around the world to discuss critical questions, challenges, and opportunities at the intersection of computational modeling and neurorehabilitation to understand, optimize, and improve clinical translation of neurorehabilitation. We organized the conference around four key, relevant, and promising Focus Areas for modeling: Adaptation & Plasticity, Personalization, Human-Device Interactions, and Modeling In-the-Wild. We identified four common threads across the Focus Areas that, if addressed, can catalyze progress in the short, medium, and long terms. These were: (i) the need to capture and curate appropriate and useful data necessary to develop, validate, and deploy useful computational models (ii) the need to create multi-scale models that span the personalization spectrum from individuals to populations, and from cellular to behavioral levels (iii) the need for algorithms that extract as much information from available data, while requiring as little data as possible from each client (iv) the insistence on leveraging readily available sensors and data systems to push model-driven treatments from the lab, and into the clinic, home, workplace, and community. The conference archive can be found at (dare2023.usc.edu). These topics are also extended by three perspective papers prepared by trainees and junior faculty, clinician researchers, and federal funding agency representatives who attended the conference.

In 2020, we identified cancer-specific microbial signals in The Cancer Genome Atlas (TCGA) [1]. Multiple peer-reviewed papers independently verified or extended our findings [2-12]. Given this impact, we carefully considered concerns by Gihawi et al. [13] that batch correction and database contamination with host sequences artificially created the appearance of cancer type-specific microbiomes. (1) We tested batch correction by comparing raw and Voom-SNM-corrected data per-batch, finding predictive equivalence and significantly similar features. We found consistent results with a modern microbiome-specific method (ConQuR [14]), and when restricting to taxa found in an independent, highly-decontaminated cohort. (2) Using Conterminator [15], we found low levels of human contamination in our original databases (~1% of genomes). We demonstrated that the increased detection of human reads in Gihawi et al. [13] was due to using a newer human genome reference. (3) We developed Exhaustive, a method twice as sensitive as Conterminator, to clean RefSeq. We comprehensively host-deplete TCGA with many human (pan)genome references. We repeated all analyses with this and the Gihawi et al. [13] pipeline, and found cancer type-specific microbiomes. These extensive re-analyses and updated methods validate our original conclusion that cancer type-specific microbial signatures exist in TCGA, and show they are robust to methodology.

AIM: This paper describes the trajectory during 1 year of four patient-reported outcomes (PROs), namely, sleep, depressive symptoms, health-related quality of life (HrQoL), and well-being, in patients with heart failure (HF), their relationship and the patient characteristics associated with changes in these PROs. METHODS AND RESULTS: Data analyses of PROs from 603 patients (mean age 67 years; 29% female, 60% NYHA II) enrolled in the HF-Wii study. On short term, between baseline and 3 months, 16% of the patients experienced continuing poor sleep, 11% had sustained depressive symptoms, 13% had consistent poor HrQoL, and 13% consistent poor well-being. Across the entire 1-year period only 21% of the patients had good PRO scores at all timepoints (baseline, 3, 6, and 12 months). All others had at least one low score in any of the PROs at some timepoint during the study. Over the 12 months, 17% had consistently poor sleep, 17% had sustained symptoms of depression, 15% consistently rated a poor HrQoL, and 13% poor well-being. Different patient characteristics per PRO were associated with a poor outcomes across the 12 months. Age, education, New York Heart Association, and length of disease were related to two PRO domains and submaximal exercise capacity (6 min test), co-morbidity, and poor physical activity to one. CONCLUSION: In total, 79% of the patients with HF encountered problems related to sleep, depressive symptoms, HrQoL, and well-being at least once during a 1-year period. This underscores the need for continuous monitoring and follow-up of patients with HF and the need for dynamic adjustments in treatment and care regularly throughout the HF trajectory.

Hyperpolarization techniques significantly enhance the sensitivity of magnetic resonance (MR) and thus present fascinating new directions for research and applications with in vivo MR imaging and spectroscopy (MRI/S). Hyperpolarized 13C MRI/S, in particular, enables real-time non-invasive assessment of metabolic processes and holds great promise for a diverse range of clinical applications spanning fields like oncology, neurology, and cardiology, with a potential for improving early diagnosis of disease, patient stratification, and therapy response assessment. Despite its potential, technical challenges remain for achieving clinical translation. This paper provides an overview of the discussions that took place at the international workshop "New Horizons in Hyperpolarized 13C MRI," in March 2023 at the Bavarian Academy of Sciences and Humanities, Munich, Germany. The workshop covered new developments, as well as future directions, in topics including polarization techniques (particularly focusing on parahydrogen-based methods), novel probes, considerations related to data acquisition and analysis, and emerging clinical applications in oncology and other fields.

Impaired healing wounds do not proceed through the normal healing processes in a timely and orderly manner, and while they do eventually heal, their healing is not optimal. Chronic wounds, on the other hand, remain unhealed for weeks or months. In the US alone, chronic wounds impact ~8.5 million people and cost ~USD 28-90 billion per year, not accounting for the psychological and physical pain and emotional suffering that patients endure. These numbers are only expected to rise in the future as the elderly populations and the incidence of comorbidities such as diabetes, hypertension, and obesity increase. Over the last few decades, scientists have used a variety of approaches to treat chronic wounds, but unfortunately, to date, there is no effective treatment. Indeed, while there are thousands of drugs to combat cancer, there is only one single drug approved for the treatment of chronic wounds. This is in part because wound healing is a very complex process involving many phases that must occur sequentially and in a timely manner. Furthermore, models that fully mimic human chronic wounds have not been developed. In this review, we assess various models currently being used to study the biology of impaired healing and chronic non-healing wounds. Among them, this paper also highlights one model which shows significant promise; this model uses aged and obese db/db-/- mice and the chronic wounds that develop show characteristics of human chronic wounds that include increased oxidative stress, chronic inflammation, damaged microvasculature, abnormal collagen matrix deposition, a lack of re-epithelialization, and the spontaneous development of multi-bacterial biofilm. We also discuss how important it is that we continue to develop chronic wound models that more closely mimic those of humans and that can be used to test potential treatments to heal chronic wounds.

This paper reports a high-resolution isotopic study of medieval horse mobility, revealing their origins and in-life mobility both regionally and internationally. The animals were found in an unusual horse cemetery site found within the City of Westminster, London, England. Enamel strontium, oxygen, and carbon isotope analysis of 15 individuals provides information about likely place of birth, diet, and mobility during the first approximately 5 years of life. Results show that at least seven horses originated outside of Britain in relatively cold climates, potentially in Scandinavia or the Western Alps. Ancient DNA sexing data indicate no consistent sex-specific mobility patterning, although three of the five females came from exceptionally highly radiogenic regions. Another female with low mobility is suggested to be a sedentary broodmare. Our results provide direct and unprecedented evidence for a variety of horse movement and trading practices in the Middle Ages and highlight the importance of international trade in securing high-quality horses for medieval London elites.

BACKGROUND: Active commuting to school can be a meaningful contributor to overall physical activity in children. To inform better micro-level urban design near schools that can support active commuting to school, there is a need for measures that capture these elements. This paper describes the adaptation of an observational instrument for use in assessing micro-scale environments around urban elementary schools in the United States. METHODS: The Micro-scale Audit of Pedestrian Streetscapes for Safe Routes to School (MAPS-SRTS) was developed from existing audit instruments not designed for school travel environments and modifications for the MAPS-SRTS instrument include the structure of the audit tool sections, the content, the observation route, and addition of new subscales. Subscales were analyzed for inter-rater reliability in a sample of 36 schools in Austin, TX. To assess reliability for each subscale, one-way random effects single-measure intraclass correlation coefficients (ICC) were used. RESULTS: Compared to the 30 original subscales, the adapted MAPS-SRTS included 26 (86.6%) subscales with revised scoring algorithms. Most MAPS-SRTS subscales had acceptable inter-rater reliability, with an ICC of 0.97 for the revised audit tool. CONCLUSIONS: The MAPS-SRTS audit tool is a reliable instrument for measuring the school travel environment for research and evaluation purposes, such as assessing human-scale determinants of active commuting to school behavior and documenting built environment changes from infrastructure interventions.

Despite its high prevalence among dementias, Lewy body dementia (LBD) remains poorly understood with a limited, albeit growing, evidence base. The public-health burden that LBD imposes is worsened by overlapping pathologies, which contribute to misdiagnosis, and lack of treatments. For this report, we gathered and analyzed public-domain information on advocacy, funding, research outputs, and the therapeutic pipeline to identify gaps in each of these key elements. To further understand the current gaps, we also conducted interviews with leading experts in regulatory/governmental agencies, LBD advocacy, academic research, and biopharmaceutical research, as well as with funding sources. We identified wide gaps across the entire landscape, the most critical being in research. Many of the experts participated in a workshop to discuss the prioritization of research areas with a view to accelerating therapeutic development and improving patient care. This white paper outlines the opportunities for bridging the major LBD gaps and creates the framework for collaboration in that endeavor. HIGHLIGHTS: A group representing academia, government, industry, and consulting expertise was convened to discuss current progress in Dementia with Lewy Body care and research. Consideration of expert opinion,natural language processing of the literature as well as publicly available data bases, and Delphi inspired discussion led to a proposed consensus document of priorities for the field.

Repetitive transcranial magnetic stimulation (rTMS) is a rapidly developing therapeutic modality for the safe and effective treatment of neuropsychiatric disorders. However, clinical rTMS driving systems and head coils are large, heavy, and expensive, so miniaturized, affordable rTMS devices may facilitate treatment access for patients at home, in underserved areas, in field and mobile hospitals, on ships and submarines, and in space. The central component of a portable rTMS system is a miniaturized, lightweight coil. Such a coil, when mated to lightweight driving circuits, must be able to induce B and E fields of sufficient intensity for medical use. This paper newly identifies and validates salient theoretical considerations specific to the dimensional scaling and miniaturization of coil geometries, particularly figure-8 coils, and delineates novel, key design criteria. In this context, the essential requirement of matching coil inductance with the characteristic resistance of the driver switches is highlighted. Computer simulations predicted E- and B-fields which were validated via benchtop experiments. Using a miniaturized coil with dimensions of 76 mm × 38 mm and weighing only 12.6 g, the peak E-field was 87 V/m at a distance of 1.5 cm. Practical considerations limited the maximum voltage and current to 350 V and 3.1 kA, respectively; nonetheless, this peak E-field value was well within the intensity range, 60-120 V/m, generally held to be therapeutically relevant. The presented parameters and results delineate coil and circuit guidelines for a future miniaturized, power-scalable rTMS system able to generate pulsed E-fields of sufficient amplitude for potential clinical use.

Compared to a Western diet, the Mediterranean diet moves away from red meat and processed foods. Universally regarded as a healthier dietary alternative, the Mediterranean diet has garnered scientific endorsement for its ability to confer an array of compelling benefits. These health benefits encompass not only a lowered incidence of Type 2 diabetes with a reduction in obesity, but also a robust protective effect on cardiovascular health. Extensive literature exists to corroborate these health benefits; however, the impact of a Mediterranean diet on urologic diseases, specifically sexual dysfunction, lower urinary tract symptoms, stone disease, and urologic cancers are not well studied. Understanding how dietary habits may impact these urologic conditions can contribute to improved prevention and treatment strategies.A total of 955 papers from PubMed and Embase were systematically reviewed and screened. After exclusion of disqualified and duplicated studies, 58 studies consisting of randomized controlled trials, cohort studies, cross sectional studies, reviews and other meta-analyses were included in this review. 11 primary studies were related to the impact of a Mediterranean diet on sexual dysfunction, 9 primary studies regarding urinary symptoms, 8 primary studies regarding stone disease, and 9 primary studies regarding urologic cancers. All primary studies included were considered of good quality based on a New-Castle Ottawa scale. The results demonstrate a Mediterranean diet as an effective means to prevent as well as improve erectile dysfunction, nephrolithiasis, lower urinary tract symptoms, and urinary incontinence. The review highlights the need for additional research to study the impact of diet on urologic cancers and other urologic conditions such as premature ejaculation, loss of libido, female sexual dysfunction, and overactive bladder.

BACKGROUND: Male sex workers (MSWs), specifically cisgender men who exchange sex for money, goods, drugs, or other items of value with other cisgender men, are at high risk for HIV infection. Compared to men not engaged in sex work, MSWs are more likely to engage in frequent condomless sex with paying and non-paying sexual partners. While MSWs are often included as a subgroup of gay and bisexual men, data show that a large proportion identify as heterosexual; additionally, most MSWs do not identify as sex workers. This places MSWs in a unique position where they may not engage with traditional HIV prevention programs, and when they do, they may not feel comfortable, leading to poor retention. Thus, HIV prevention interventions that address MSWs unique life circumstances and provide support in exploring their sexual health options are needed. METHODS: In this protocol paper, we describe the design and procedures for a National Institute of Health-funded, randomized controlled trial testing the efficacy of PrEPare for Work,- a theory-based, manualized PrEP uptake and adherence intervention for MSW - using a 2-stage randomization design. Stage 1: MSWs are equally randomized to receive either the PrEPare for Work Stage 1 intervention (strength-based case management and facilitated PrEP linkage) or Standard of Care (SOC) to evaluate successful PrEP uptake (prescription filled) within two months post-randomization. Stage 2: Those who initiate PrEP are then equally re-randomized to receive either the PrEPare for Work Stage 2 intervention (1-on-1 skills training, problem-solving, and motivational interviewing adherence counseling and personalized, daily text message reminders) or SOC to assess adherence (Tenofovir concentrations in hair) over 12 months of follow up. Planned analyses will examine intervention efficacy, specific conceptual mediators, and hypothesized moderators. DISCUSSION: Based on our extensive preliminary research, multi-component, theory-informed interventions targeting this subpopulation of MSWs unique life circumstances are urgently needed. In this study, we are evaluating whether PrEPare for Work can improve PrEP uptake and adherence among MSWs. If this intervention is efficacious, it would be readily disseminated to diverse community organizations that serve MSWs and possibly other community or clinic-based settings. TRIAL REGISTRATION: ClinicalTrials.gov number NCT05736614, registered February 8, 2023.

Estimation of temporospatial clinical features of gait (CFs), such as step count and length, step duration, step frequency, gait speed, and distance traveled, is an important component of community-based mobility evaluation using wearable accelerometers. However, accurate unsupervised computerized measurement of CFs of individuals with Duchenne muscular dystrophy (DMD) who have progressive loss of ambulatory mobility is difficult due to differences in patterns and magnitudes of acceleration across their range of attainable gait velocities. This paper proposes a novel calibration method. It aims to detect steps, estimate stride lengths, and determine travel distance. The approach involves a combination of clinical observation, machine-learning-based step detection, and regression-based stride length prediction. The method demonstrates high accuracy in children with DMD and typically developing controls (TDs) regardless of the participants level of ability. Fifteen children with DMD and fifteen TDs underwent supervised clinical testing across a range of gait speeds using 10 m or 25 m run/walk (10 MRW, 25 MRW), 100 m run/walk (100 MRW), 6-min walk (6 MWT), and free-walk (FW) evaluations while wearing a mobile-phone-based accelerometer at the waist near the bodys center of mass. Following calibration by a trained clinical evaluator, CFs were extracted from the accelerometer data using a multi-step machine-learning-based process and the results were compared to ground-truth observation data. Model predictions vs. observed values for step counts, distance traveled, and step length showed a strong correlation (Pearsons r = -0.9929 to 0.9986, p < 0.0001). The estimates demonstrated a mean (SD) percentage error of 1.49% (7.04%) for step counts, 1.18% (9.91%) for distance traveled, and 0.37% (7.52%) for step length compared to ground-truth observations for the combined 6 MWT, 100 MRW, and FW tasks. Our study findings indicate that a single waist-worn accelerometer calibrated to an individuals stride characteristics using our methods accurately measures CFs and estimates travel distances across a common range of gait speeds in both DMD and TD peers.

Do psychedelics affect sexual functioning postacutely? Anecdotal and qualitative evidence suggests they do, but this has never been formally tested. While sexual functioning and satisfaction are generally regarded as an important aspect of human wellbeing, sexual dysfunction is a common symptom of mental health disorders. It is also a common side effect of selective serotonin reuptake inhibitors (SSRIs), a first line treatment for depression. The aim of the present paper was to investigate the post-acute effects of psychedelics on self-reported sexual functioning, combining data from two independent studies, one large and naturalistic and the other a smaller but controlled clinical trial. Naturalistic use of psychedelics was associated with improvements in several facets of sexual functioning and satisfaction, including improved pleasure and communication during sex, satisfaction with ones partner and physical appearance. Convergent results were found in a controlled trial of psilocybin therapy versus an SSRI, escitalopram, for depression. In this trial, patients treated with psilocybin reported positive changes in sexual functioning after treatment, while patients treated with escitalopram did not. Despite focusing on different populations and settings, this is the first research study to quantitively investigate the effects of psychedelics on sexual functioning. Results imply a potential positive effect on post-acute sexual functioning and highlight the need for more research on this.

This paper presents an analysis of survey data to examine the association between supervised structured mentoring and students intent to pursue a career in science. Data were collected from students in the 10 Building Infrastructure Leading to Diversity (BUILD) research training programs, developed through grants from the National Institutes of Health. Propensity score matching and multinomial logistic regression demonstrated that exposure to BUILD programs-meaning participation in undergraduate research, receipt of mentoring from a primary mentor, and/or participation as a funded scholar and/or associate of each BUILD sites training program-was associated with increased intent to pursue a science career. These findings have implications for STEM program evaluation and practice in higher education.

The linear mixed-effects model (LME) is a versatile approach to account for dependence among observations. Many large-scale neuroimaging datasets with complex designs have increased the need for LME; however LME has seldom been used in whole-brain imaging analyses due to its heavy computational requirements. In this paper, we introduce a fast and efficient mixed-effects algorithm (FEMA) that makes whole-brain vertex-wise, voxel-wise, and connectome-wide LME analyses in large samples possible. We validate FEMA with extensive simulations, showing that the estimates of the fixed effects are equivalent to standard maximum likelihood estimates but obtained with orders of magnitude improvement in computational speed. We demonstrate the applicability of FEMA by studying the cross-sectional and longitudinal effects of age on region-of-interest level and vertex-wise cortical thickness, as well as connectome-wide functional connectivity values derived from resting state functional MRI, using longitudinal imaging data from the Adolescent Brain Cognitive DevelopmentSM Study release 4.0. Our analyses reveal distinct spatial patterns for the annualized changes in vertex-wise cortical thickness and connectome-wide connectivity values in early adolescence, highlighting a critical time of brain maturation. The simulations and application to real data show that FEMA enables advanced investigation of the relationships between large numbers of neuroimaging metrics and variables of interest while considering complex study designs, including repeated measures and family structures, in a fast and efficient manner. The source code for FEMA is available via: https://github.com/cmig-research-group/cmig_tools/.

Interest in understanding the relationship between body composition and cancer survival has remained strong for decades, with a number of recent systematic reviews on the topic. However, the current state of evidence is based on heterogeneous exposure definitions based on anthropometry, yielding inconsistent findings with regard to this association. Recently the field has taken an exciting direction with the application of radiological assessments to measure specific aspects of body composition, yet reconciliation of findings from these modern assessment tools with those from the historic use of anthropometric data proves challenging. In this paper, I briefly review the biological basis for a link between body composition and cancer survival and summarize the epidemiological evidence with consideration to specific exposure measures. As enthusiasm is building around novel assessments, I conclude with a discussion of issues that researchers should be aware of when interpreting results from these new modalities.

The hippocampus plays an essential role in long-term episodic memory by supporting the recollection of contextual details, whereas surrounding regions such as the perirhinal cortex support familiarity-based recognition discriminations. Working memory - the ability to maintain information over very brief periods of time - is traditionally thought to rely heavily on frontoparietal attention networks, but recent work has shown that it can also rely on the hippocampus. However, the conditions in which the hippocampus becomes involved in working memory tasks are unclear and whether it contributes to recollection or familiarity-based responses in working memory is only beginning to be explored. In the current paper, we first review and contrast the existing amnesia literature examining recollection and familiarity in episodic and working memory. The results indicate that recollection and familiarity contribute to both episodic and working memory. However, in contrast to episodic memory, in working memory the hippocampus is particularly critical for familiarity-based rather than recollection-based discrimination. Moreover, the results indicate that the role of the hippocampus in working memory can be obscured due to criterion-induced process-masking because it primarily supports intermediate-confidence recognition decisions. We then report results from a new working memory study examining the ability of amnesics to detect global and local changes in novel complex objects (i.e., fribbles), which indicates that the hippocampus plays an especially critical role in working memory when the task requires the detection of global rather than discrete changes. We conclude by considering the results in light of neurocomputational models and proposing a general framework for understanding the relationship between episodic and working memory.

BACKGROUND: Wildfire smoke exposure has become a growing public health concern, as megafires and fires at the wildland urban interface increase in incidence and severity. Smoke contains many pollutants that negatively impact health and is linked to a number of health complications and chronic diseases. Communicating effectively with the public, especially at-risk populations, to reduce their exposure to this environmental pollutant has become a public health priority. Although wildfire smoke risk communication research has also increased in the past decade, best practice guidance is limited, and most health communications do not adhere to health literacy principles: readability, accessibility, and actionability. This scoping review identifies peer-reviewed studies about wildfire smoke risk communications to identify gaps in research and evaluation of communications and programs that seek to educate the public. METHODS: Four hundred fifty-one articles were identified from Web of Science and PubMed databases. After screening, 21 articles were included in the final sample for the abstraction process and qualitative thematic analysis. Ten articles were based in the US, with the other half in Australia, Canada, Italy, and other countries. Fifteen articles examined communication materials and messaging recommendations. Eight papers described communication delivery strategies. Eleven articles discussed behavior change. Six articles touched on risk communications for vulnerable populations; findings were limited and called for increasing awareness and prioritizing risk communications for at-risk populations. RESULTS: This scoping review found limited studies describing behavior change to reduce wildfire smoke exposure, characteristics of effective communication materials and messaging, and communication delivery strategies. Literature on risk communications, dissemination, and behavior change for vulnerable populations was even more limited. CONCLUSIONS: Recommendations include providing risk communications that are easy-to-understand and adapted to specific needs of at-risk groups. Communications should provide a limited number of messages that include specific actions for avoiding smoke exposure. Effective communications should use mixed media formats and a wide variety of dissemination strategies. There is a pressing need for more intervention research and effectiveness evaluation of risk communications about wildfire smoke exposure, and more development and dissemination of risk communications for both the general public and vulnerable populations.

Recent years have witnessed exponential growth in cardiac imaging technologies, allowing better visualization of complex cardiac anatomy and improved assessment of physiology. These advances have become increasingly important as more complex surgical and catheter-based procedures are evolving to address the needs of a growing congenital heart disease population. This state-of-the-art review presents advances in echocardiography, cardiac magnetic resonance, cardiac computed tomography, invasive angiography, 3-dimensional modeling, and digital twin technology. The paper also highlights the integration of artificial intelligence with imaging technology. While some techniques are in their infancy and need further refinement, others have found their way into clinical workflow at well-resourced centers. Studies to evaluate the clinical value and cost-effectiveness of these techniques are needed. For techniques that enhance the value of care for congenital heart disease patients, resources will need to be allocated for education and training to promote widespread implementation.

The emergence of long COVID during the ongoing COVID-19 pandemic has presented considerable challenges for healthcare professionals and researchers. The task of identifying relevant literature is particularly daunting due to the rapidly evolving scientific landscape, inconsistent definitions, and a lack of standardized nomenclature. This paper proposes a novel solution to this challenge by employing machine learning techniques to classify long COVID literature. However, the scarcity of annotated data for machine learning poses a significant obstacle. To overcome this, we introduce a strategy called medical paraphrasing, which diversifies the training data while maintaining the original content. Additionally, we propose a Data-Reweighting-Based Multi-Level Optimization Framework for Domain Adaptive Paraphrasing, supported by a Meta-Weight-Network (MWN). This innovative approach incorporates feedback from the downstream text classification model to influence the training of the paraphrasing model. During the training process, the framework assigns higher weights to the training examples that contribute more effectively to the downstream task of long COVID text classification. Our findings demonstrate that this method substantially improves the accuracy and efficiency of long COVID literature classification, offering a valuable tool for physicians and researchers navigating this complex and ever-evolving field.