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ImportanceCurrent measures of alopecia areata (AA) severity, such as the Severity of Alopecia Tool score, do not adequately capture overall disease impact.ObjectiveTo explore factors associated with AA severity beyond scalp hair loss, and to support the development of the Alopecia Areata Severity and Morbidity Index (ASAMI).Evidence reviewA total of 74 hair and scalp disorder specialists from multiple continents were invited to participate in an eDelphi project consisting of 3 survey rounds. The first 2 sessions took place via a text-based web application following the Delphi study design. The final round took place virtually among participants via video conferencing software on April 30, 2022.FindingsOf all invited experts, 64 completed the first survey round (global representation: Africa [4.7%], Asia [9.4%], Australia [14.1%], Europe [43.8%], North America [23.4%], and South America [4.7%]; health care setting: public [20.3%], private [28.1%], and both [51.6%]). A total of 58 specialists completed the second round, and 42 participated in the final video conference meeting. Overall, consensus was achieved in 96 of 107 questions. Several factors, independent of the Severity of Alopecia Tool score, were identified as potentially worsening AA severity outcomes. These factors included a disease duration of 12 months or more, 3 or more relapses, inadequate response to topical or systemic treatments, rapid disease progression, difficulty in cosmetically concealing hair loss, facial hair involvement (eyebrows, eyelashes, and/or beard), nail involvement, impaired quality of life, and a history of anxiety, depression, or suicidal ideation due to or exacerbated by AA. Consensus was reached that the Alopecia Areata Investigator Global Assessment scale adequately classified the severity of scalp hair loss.Conclusions and relevanceThis eDelphi survey study, with consensus among global experts, identified various determinants of AA severity, encompassing not only scalp hair loss but also other outcomes. These findings are expected to facilitate the development of a multicomponent severity tool that endeavors to competently measure disease impact. The findings are also anticipated to aid in identifying candidates for current and emerging systemic treatments. Future research must incorporate the perspectives of patients and the public to assign weight to the domains recognized in this project as associated with AA severity.

Forest school and nature-based pedagogy have grown in popularity in recent years. Previously, I examined the perspectives of parents who chose to enrol their children within these programs to learn and understand why. As I furthered my studies, I became concerned about how these forest and nature schools connect to Indigenous ways of knowing, teaching, and learning, as many claim. I wanted to examine how Forest school pedagogy and Indigenous perspectives of education may connect or not, and how these land-based pedagogies intertwine with Indigenous perspectives of land as first teacher. This work is a storying of my educational journey about land-based pedagogy, environmental education for children and how children are viewed within nature. The aim of this story is to ask what might happen when Forest pedagogies, Indigenous peoples, and their epistemologies and ontologies are assembled? The secondary purpose is to ignite pedagogical conversations amongst educators and inform about Forest School programs and how they connect to Indigenous perspectives or do not connect at all.

The US National Institute of Allergy and Infectious Diseases (NIAID), part of the National Institute of Health (NIH), convened a virtual workshop on August 8-9th, 2023 to explore potential synergies between HIV vaccine approaches that are designed to induce cellular or humoral immune responses. The goal of this workshop was to review data on leading vaccine candidates and to discuss the best strategies for combining these approaches to optimize immunity against HIV. Here, we summarize the findings reviewed at the workshop and discuss the knowledge gaps and priorities for future studies that will help accelerate the development of a preventive HIV vaccine.

The ecosystem services and immense biodiversity of Amazon rainforests are threatened by deforestation and forest degradation. A key goal of modern archaeology and paleoecology in Amazonia is to establish the extent and duration of past forest disturbance by humans. Fossil phytoliths are an established proxy to identify the duration of disturbance in lake sedimentary and soil archives. What is not known, is the spatial scale of such forest disturbances when identified by phytoliths. Here we use phytolith assemblages to detect local-scale forest openings, provide an estimate of extent, and consider long-term forest recovery. We use modern phytolith assemblages of 50 Amazonian lakes to i) assess how phytolith assemblages vary across forest cover at 5 spatial scales (100 m, 200 m, 500 m, 1 km, 2 km), ii) model which phytolith morphotypes can accurately predict forest cover at 5 spatial scales, and iii) compare phytoliths with pollen to quantify their relative ability to detect forest cover changes. DCA results show phytolith assemblages could be used to differentiate low, intermediate, and high forest cover values, but not to distinguish between biogeographical gradients across Amazonia. Beta regression models show Poaceae phytoliths can accurately predict forest cover within 200 m of Amazonian lakes. This modern calibration dataset can be used to make quantitative reconstructions of forest cover changes in Amazonia, to generate novel insights into long-term forest recovery. Combining phytoliths and pollen provides a unique opportunity to make qualitative and quantitative reconstructions of past vegetation changes, to better understand how human activities, environmental and climatic changes have shaped modern Amazonian forests.

Abstract Background Neoantigen-targeting therapies including personalized vaccines have shown promise in the treatment of cancers, particularly when used in combination with checkpoint blockade therapy. At least 100 clinical trials involving these therapies have been initiated globally. Accurate identification and prioritization of neoantigens is crucial for designing these trials, predicting treatment response, and understanding mechanisms of resistance. With the advent of massively parallel DNA and RNA sequencing technologies, it is now possible to computationally predict neoantigens based on patient-specific variant information. However, numerous factors must be considered when prioritizing neoantigens for use in personalized therapies. Complexities such as alternative transcript annotations, various binding, presentation and immunogenicity prediction algorithms, and variable peptide lengths/registers all potentially impact the neoantigen selection process. There has been a rapid development of computational tools that attempt to account for these complexities. While these tools generate numerous algorithmic predictions for neoantigen characterization, results from these pipelines are difficult to navigate and require extensive knowledge of the underlying tools for accurate interpretation. This often leads to over-simplification of pipeline outputs to make them tractable, for example, limiting prediction to a single RNA isoform or only summarizing the top ranked of many possible peptide candidates. In addition to variant detection, gene expression, and predicted peptide binding affinities, recent studies have also demonstrated the importance of mutation location, allele-specific anchor locations, and variation of T-cell response to long versus short peptides. Due to the intricate nature and number of salient neoantigen features, presenting all relevant information to facilitate candidate selection for downstream applications is a difficult challenge that current tools fail to address. Results We have created pVACview, the first interactive tool designed to aid in the prioritization and selection of neoantigen candidates for personalized neoantigen therapies including cancer vaccines. pVACview has a user-friendly and intuitive interface where users can upload, explore, select, and export their neoantigen candidates. The tool allows users to visualize candidates at multiple levels of detail including variant, transcript, peptide, and algorithm prediction information. Conclusions pVACview will allow researchers to analyze and prioritize neoantigen candidates with greater efficiency and accuracy in basic and translational settings. The application is available as part of the pVACtools software at pvactools.org and as an online server at pvacview.org.

The rate at which aerosols spread from a point source injection, such as from a ship or other stationary pollution source, is critical for accurately representing subgrid plume spreading in a climate model. Such climate model results will guide future decisions regarding the feasibility and application of large-scale intentional marine cloud brightening (MCB). Prior modeling studies have shown that the rate at which ship plumes spread may be strongly dependent on meteorological conditions, such as precipitating versus non-precipitating boundary layers and shear. In this study, we apply a Lagrangian particle model (PM-ABL v1.0), governed by a Langevin stochastic differential equation, to create a simplified framework for predicting the rate of spreading from a ship-injected aerosol plume in sheared, precipitating, and non-precipitating boundary layers. The velocity and position of each stochastic particle is predicted with the acceleration of each particle being driven by the turbulent kinetic energy, dissipation rate, momentum variance, and mean wind. These inputs to the stochastic particle velocity equation are derived from high-fidelity large-eddy simulations (LES) equipped with a prognostic aerosol–cloud microphysics scheme (UW-SAM) to simulate an aerosol injection from a ship into a cloud-topped marine boundary layer. The resulting spreading rate from the reduced-order stochastic model is then compared to the spreading rate in the LES. The stochastic particle velocity representation is shown to reasonably reproduce spreading rates in sheared, precipitating, and non-precipitating cases using domain-averaged turbulent statistics from the LES.

Abstract Background Syndecan‐1 (SDC1) is an established marker of endothelial glycocalyx shedding. Most research on SDC1 has focused on plasma or serum concentrations, and little is known about urine concentrations. Objectives Measure urinary SDC1 concentrations in dogs undergoing anesthesia with either sevoflurane or isoflurane and assess the effects of anesthesia duration and IV crystalloids on urinary SDC1 concentrations. Animals Thirty‐one client‐owned dogs undergoing anesthesia for magnetic resonance imaging (MRI) with or without surgery for suspected intervertebral disk disease (IVDD) were used. Methods Dogs with suspected IVDD were randomized to undergo anesthesia with either sevoflurane or isoflurane. Urine was collected before and immediately after anesthesia for the analysis of SDC1. Urinary creatinine concentrations also were measured, and the ratio of urinary SDC1 to urinary creatinine (USCR) was used to account for dilution. Results Median (range) USCR was significantly higher after anesthesia compared with baseline for all groups combined (P

Societal Impact Statement Global climate models that incorporate carbon sources and sinks usually consider that forest uptake of carbon is in a state of equilibrium. Both historical and paleoecological records suggest that this is commonly not the case for Amazonia. Here, the impacts of colonial practices on Amazonian Indigenous peoples and forests are reviewed. Human activities affect forests' successional stages, trajectories, and species composition. By increasing the spatial coverage of paleoecological records that focus on pre‐ and post‐Columbian periods, the long‐term interactions between humans and Amazonian forests and their role in affecting Earth's climate may be better understood. Summary Legacy effects left by the activities of Indigenous people in Amazonia are well known. Although severe, widespread, and recently occurring, the impacts left post‐1492 CE have been less investigated. We review the impact of colonial practices on Indigenous peoples and Amazonian forests. We suggest that forests comprise the sum of their past events, in a mosaic of different cumulative successional trajectories depending on the type, frequency, intensity, and timing of human influence. In regions with a history of minimal human influence, old‐growth species sensitive to fire would be the dominant landscape. In regions with high pre‐Columbian and low colonial influence, old‐growth forests carrying pre‐Columbian ecological legacies would be prevalent. Regions occupied by Indigenous groups post‐1492 CE would also carry similar ecological legacies. In regions influenced by the Jesuits, mid‐successional forests are expected to be enriched with cacao trees. In regions of latex extraction during the rubber boom, mid‐growth forests would present high abundances of early and mid‐successional species and depletion of some species. In deforested areas, we expect early successional forests with influence of exotic useful species. This patchwork of history probably plays a large role in shaping today's forests, and the biodiversity and carbon dynamics documented within them. Paleoecological work focusing on the last millennium, although scarce, has the potential to detect these mosaics of past human influence, and they should be considered when estimating forest ages and successional stages across the basin.

Background: Patients with metastatic pancreatic ductal adenocarcinoma (PDAC) have poor 5-year survival. Pharmacological ascorbate (P-AscH-, high dose, intravenous, vitamin C) has shown promise as an adjunct to chemotherapy. We hypothesized adding P-AscH- to gemcitabine and nab-paclitaxel would increase survival in patients with metastatic PDAC. Methods: Patients diagnosed with stage IV pancreatic cancer randomized 1:1 to gemcitabine and nab-paclitaxel only (SOC, control) or to SOC with concomitant P-AscH−, 75 g three times weekly (ASC, investigational). The primary outcome was overall survival with secondary objectives of determining progression-free survival and adverse event incidence. Quality of life and patient reported outcomes for common oncologic symptoms were captured as an exploratory objective. Thirty-six participants were randomized; of this 34 received their assigned study treatment. All analyses were based on data frozen on December 11, 2023. Results: Intravenous P-AscH- increased serum ascorbate levels from micromolar to millimolar levels. P-AscH- added to the gemcitabine + nab-paclitaxel (ASC) increased overall survival to 16 months compared to 8.3 months with gemcitabine + nab-paclitaxel (SOC) (HR = 0.46; 90 % CI 0.23, 0.92; p = 0.030). Median progression free survival was 6.2 (ASC) vs. 3.9 months (SOC) (HR = 0.43; 90 % CI 0.20, 0.92; p = 0.029). Adding P-AscH- did not negatively impact quality of life or increase the frequency or severity of adverse events. Conclusions: P-AscH− infusions of 75 g three times weekly in patients with metastatic pancreatic cancer prolongs overall and progression free survival without detriment to quality of life or added toxicity (ClinicalTrials.gov number NCT02905578).

IntroductionMolecular chaperones and co-chaperones are highly conserved cellular components that perform a variety of duties related to the proper three-dimensional folding of the proteome. The web of factors that carries out this essential task is called the proteostasis network (PN). Ribonucleoproteins (RNPs) represent an underexplored area in terms of the connections they make with the PN. The Survival Motor Neuron (SMN) complex is an assembly chaperone and serves as a paradigm for studying how specific RNAs are identified and paired with their client substrate proteins to form RNPs. SMN is the eponymous component of a large complex, required for the biogenesis of uridine-rich small nuclear ribonucleoproteins (U-snRNPs), that localizes to distinct membraneless organelles in both the nucleus and cytoplasm of animal cells. SMN protein forms the oligomeric core of this complex, and missense mutations in the human SMN1 gene are known to cause Spinal Muscular Atrophy (SMA). The basic framework for understanding how snRNAs are assembled into U-snRNPs is known. However, the pathways and mechanisms used by cells to regulate their biogenesis are poorly understood.MethodsGiven the importance of these processes to normal development as well as neurodegenerative disease, we set out to identify and characterize novel SMN binding partners. We carried out affinity purification mass spectrometry (AP-MS) of Drosophila SMN complexes using fly lines exclusively expressing either wildtype or SMA-causing missense alleles.ResultsBioinformatic analyses of the pulldown data, along with comparisons to proximity labeling studies carried out in human cells, revealed conserved connections to at least two other major chaperone systems including heat shock folding chaperones (HSPs) and histone/nucleosome assembly chaperones. Notably, we found that heat shock cognate protein Hsc70-4 and other HspA family members preferentially associated with SMA-causing alleles of SMN.DiscussionHsc70-4 is particularly interesting because its mRNA is aberrantly sequestered by a mutant form of TDP-43 in mouse and Drosophila ALS (Amyotrophic Lateral Sclerosis) disease models. Most important, a missense allele of Hsc70-4 (HspA8 in mammals) was recently identified as a bypass suppressor of the SMA phenotype in mice. Collectively, these findings suggest that chaperone-related dysfunction lies at the etiological root of both ALS and SMA.

Neoantigens are tumor-specific peptide sequences resulting from sources such as somatic DNA mutations. Upon loading onto major histocompatibility complex (MHC) molecules, they can trigger recognition by T cells. Accurate neoantigen identification is thus critical for both designing cancer vaccines and predicting response to immunotherapies. Neoantigen identification and prioritization relies on correctly predicting whether the presenting peptide sequence can successfully induce an immune response. Because most somatic mutations are single-nucleotide variants, changes between wild-type and mutated peptides are typically subtle and require cautious interpretation. A potentially underappreciated variable in neoantigen prediction pipelines is the mutation position within the peptide relative to its anchor positions for the patient's specific MHC molecules. Whereas a subset of peptide positions are presented to the T cell receptor for recognition, others are responsible for anchoring to the MHC, making these positional considerations critical for predicting T cell responses. We computationally predicted anchor positions for different peptide lengths for 328 common HLA alleles and identified unique anchoring patterns among them. Analysis of 923 tumor samples shows that 6 to 38% of neoantigen candidates are potentially misclassified and can be rescued using allele-specific knowledge of anchor positions. A subset of anchor results were orthogonally validated using protein crystallography structures. Representative anchor trends were experimentally validated using peptide-MHC stability assays and competition binding assays. By incorporating our anchor prediction results into neoantigen prediction pipelines, we hope to formalize, streamline, and improve the identification process for relevant clinical studies.

Electronic health records (EHRs) have been increasingly adopted in clinical practices across the United States, providing a primary source of data for clinical research, particularly observational cohort studies. EHRs are a high-yield, low-maintenance source of longitudinal real-world data for large patient populations and provide a wealth of information and clinical contexts that are useful for clinical research and translation into practice. Despite these strengths, it is important to recognize the multiple limitations and challenges related to the use of EHR data in clinical research. Missing data are a major source of error and biases and can affect the representativeness of the cohort of interest, as well as the accuracy of the outcomes and exposures. Here, we aim to provide a critical understanding of the types of data available in EHRs and describe the impact of data heterogeneity, quality, and generalizability, which should be evaluated prior to and during the analysis of EHR data. We also identify challenges pertaining to data quality, including errors and biases, and examine potential sources of such biases and errors. Finally, we discuss approaches to mitigate and remediate these limitations. A proactive approach to addressing these issues can help ensure the integrity and quality of EHR data and the appropriateness of their use in clinical studies.

Expected yield rates are essential to a survey's data collection plan, as they inform requisite sample sizes to meet the survey's objectives. Given an overall expected yield rate for a self-administered mail survey, this short take describes a simple method for using the Census Planning Database to assign differential yield rates to lower-level geographies within the study area.

Abstract Reversible axonal swelling and brainstem auditory evoked potential (BAEP) changes were observed in standard chronic (9‐month) toxicology studies in dogs treated with ritlecitinib, an oral Janus kinase 3/tyrosine kinase expressed in hepatocellular carcinoma family kinase inhibitor, at exposures higher than the approved 50‐mg human dose. To evaluate the clinical relevance of the dog toxicity finding, this phase 2a, double‐blind study assessed BAEP changes and intraepidermal nerve fiber (IENF) histology in adults with alopecia areata treated with ritlecitinib. Patients were randomized to receive oral ritlecitinib 50 mg once daily (QD) with a 4‐week loading dose of 200 mg QD or placebo for 9 months (placebo‐controlled phase); they then entered the active‐therapy extension and received ritlecitinib 50 mg QD (with a 4‐week loading dose of 200 mg in patients switching from placebo). Among the 71 patients, no notable mean differences in change from baseline (CFB) in Waves I–V interwave latency (primary outcome) or Wave V amplitude on BAEP at a stimulus intensity of 80 dB nHL were observed in the ritlecitinib or placebo group at Month 9, with no notable differences in interwave latency or Wave V amplitude between groups. The CFB in mean or median IENF density and in percentage of IENFs with axonal swellings was minimal and similar between groups at Month 9. Ritlecitinib treatment was also not associated with an imbalanced incidence of neurological and audiological adverse events. These results provide evidence that the BAEP and axonal swelling finding in dogs are not clinically relevant in humans.

The US National Institute of Allergy and Infectious Diseases (NIAID), part of the National Institute of Health (NIH), convened a virtual workshop on August 8-9th, 2023 to explore potential synergies between HIV vaccine approaches that are designed to induce cellular or humoral immune responses. The goal of this workshop was to review data on leading vaccine candidates and to discuss the best strategies for combining these approaches to optimize immunity against HIV. Here, we summarize the findings reviewed at the workshop and discuss the knowledge gaps and priorities for future studies that will help accelerate the development of a preventive HIV vaccine.

Background and Aims: Gastric cancer (GC) is a leading cause of cancer incidence and mortality globally. Population screening is limited by the low incidence and prevalence of GC in the United States. A risk prediction algorithm to identify high-risk patients allows for targeted GC screening. We aimed to determine the feasibility and performance of a logistic regression model based on electronic health records to identify individuals at high risk for noncardia gastric cancer (NCGC). Methods: We included 614 patients who had a diagnosis of NCGC between ages 40 and 80 years and who were seen at our large tertiary medical center in multiple states between 2010 and 2021. Controls without a diagnosis of NCGC were randomly selected in a 1:10 ratio of cases to controls. Multiple imputation by chained equations for missing data followed by logistic regression on imputed datasets was used to estimate the probability of NCGC. Area under the curve and the 0.632 estimator was used as the estimate for discrimination. Results: The 0.632 estimator value was 0.731, indicating robust model performance. Probability of NCGC was higher with increasing age (odds ratio [OR] = 1.16, 95% confidence interval [CI]: 1.04–1.3), male sex (OR = 1.97; 95% CI: 1.64–2.36), Black (OR = 3.07; 95% CI: 2.46–3.83) or Asian race (OR = 4.39; 95% CI: 2.60–7.42), tobacco use (OR = 1.61; 95% CI: 1.34–1.94), anemia (OR = 1.35; 95% CI: 1.09–1.68), and pernicious anemia (OR = 6.12, 95% CI: 3.42–10.95). Conclusion: We demonstrate the feasibility and good performance of an electronic health record–based logistic regression model for estimating the probability of NCGC. Future studies will refine and validate this model, ultimately identifying a high-risk cohort who could be eligible for NCGC screening.

Abstract Background Mild traumatic brain injuries receive voluminous attention in the research literature, but this is confined almost entirely to sports and military contexts. As an occupation, performing stunts in film, television, and entertainment places the head at high risk of repetitive impact and whiplash, but stunt performers do not enjoy the same level of healthcare supervision and access as that provided to sports participants. Therefore, the aim of this study was to evaluate stunt performers’ qualitative perceptions of reporting and management of head trauma in their industry. Methods After giving their informed consent, 87 motion picture and television stunt performers responded to a query about their views of ways to improve how stunt performers’ occupational head trauma—specifically head impacts and head whips that could cause a concussion—are reported and managed. We analyzed their responses via content and thematic analyses. Two researchers independently marked and categorized key words, phrases, and texts to identify codes that described participants’ comments. They then revised, discussed, and resolved coding discrepancies through consensus to establish inter-coder reliability. Next, we identified thematic patterns that described participants’ understanding of the stunt performer industry and what must change to facilitate reporting of head trauma. We derived themes from data that occurred multiple times, both within and across short answer responses. Results We identified three primary themes cited by the stunt performers as needs in their industry: (1) Need to Reduce the Stigma of Reporting a Stunt-Related Injury, (2) Need to Eliminate the “Cowboy Culture,” and (3) Need to Improve the Quality of the Work Environment. Conclusions Stunt performers are crucial members of a global entertainment industry valued at approximately US$100 billion annually. A large segment of the world’s population consumes their work in motion pictures, television, and live entertainment. When they are given an anonymous opportunity to speak, stunt performers offer insight into and recommendations for industry changes—primarily cultural and educational in nature—that could improve their physical and mental health, career longevity, and employability when they are confronted with head trauma.

Sea turtles are an iconic group of marine megafauna that have been exposed to multiple anthropogenic threats across their different life stages, especially in the past decades. This has resulted in population declines, and consequently many sea turtle populations are now classified as threatened or endangered globally. Although some populations of sea turtles worldwide are showing early signs of recovery, many still face fundamental threats. This is problematic since sea turtles have important ecological roles. To encourage informed conservation planning and direct future research, we surveyed experts to identify the key contemporary threats (climate change, direct take, fisheries, pollution, disease, predation, and coastal and marine development) faced by sea turtles. Using the survey results and current literature, we also outline knowledge gaps in our understanding of the impact of these threats and how targeted future research, often involving emerging technologies, could close those gaps.