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Improved Deep Learning Prediction of TCR–HLA Associations
Get PDFUnderstanding the relationship between T cell receptors (TCRs) and human leukocyte antigens (HLAs) is essential to elucidate the specificity of the immune response, uncover mechanisms of autoimmunity, and advance targeted immunotherapies. We have previously developed a deep learning method, DePTH (Deep Learning Prediction of TCR–HLA associations), to predict the association between a TCR and an HLA based on their amino acid sequences. In this work, we demonstrate that DePTH can make accurate predictions of TCR–HLA associations in two additional datasets. We have also investigated the influence of two confounders: TCR generation probability and the sequence length of CDR3 (Complementarity-Determining Region 3), and conclude that DePTH learns additional information beyond these two factors. Building on these insights, we combined training data from the two new datasets to train two new versions of DePTH: DePTH 2.0 and DePTH 2.1
Implementing a Geriatric Assessment-Guided Rehabilitation Care Model in Community Oncology Care: Feasibility and Impact on Patient-Reported and Performance-Based Outcomes
Get PDFBackground: Adults with cancer who are pre-frail or frail are at risk of poor outcomes. Geriatric assessment (GA) is recommended to assess and manage vulnerability and risk of frailty in older adults with cancer (≥65) and to inform referrals in supportive services, including rehabilitation. Yet, adoption of the GA in community oncology practice lags, and frailty among adults younger than 65 often goes undetected and/or unaddressed. We evaluated the feasibility of a GA-guided rehabilitation care model and assessed changes in patient-reported and performance-based outcomes after rehabilitation. Methods: Adults (≥18 years) starting systemic therapy at a community oncology practice enrolled in the study. The GA was administered online and monthly for one year. Frailty/pre-frailty was identified using a previously validated 44-item index. The oncology team was notified of frail/pre-frail patients and then made referrals to outpatient rehabilitation. Feasibility outcomes (recruitment, retention, fidelity) and participant acceptability [7 items, 0–5 Likert scale] were analyzed descriptively. Patient-reported and performance-based outcomes were examined using the paired t-test. Results: 48% of eligible patients enrolled (N = 141), and 83% completed at least one GA. Frailty/pre-frailty was identified in 40% of the GAs, resulting in 282 referrals to rehabilitation (99% fidelity). Acceptability scores ranged from 3.5 ± 1.7 to 4.7 ± 0.6. Participants who attended rehabilitation (52%) improved significantly in outcomes measuring health-related quality of life, mobility, aerobic capacity, and strength (all p < 0.05). Conclusion: Implementing a GA-guided rehabilitation care model was feasible and acceptable to patients receiving systemic treatment. Those who attended rehabilitation experienced significant improvement in patient-reported and performance-based outcomes
Heterogeneity in brain morphology and psychological, cognitive, and contextual factors of gender identity
Get PDFOnce understood in binary terms, gender identity is increasingly recognized as a multidimensional and continuous construct shaped by both sociocultural and neurobiological factors. Although prior studies have reported associations between gender identity and brain structure, few have adopted an integrative approach to examine how gender identity emerges. Drawing on a large, non‐clinical sample of young adults from the Amsterdam Open Magnetic Resonance Imaging Collection ( n = 544), this study integrated psychological assessments, socioeconomic indicators, and structural MRI to investigate the relationship between gender identity and brain morphology. For participants assigned female at birth, a feminine identity was linked to reduced cortical thickness in several brain regions, including the parahippocampal, fusiform, lingual, and pericalcarine cortices. Among these regions, two distinct pathways related to the fusiform cortex were identified: a self‐referential pathway (through the parahippocampal cortex) and a visual‐perceptual pathway (through the pericalcarine and lingual cortices). Besides, an additional pathway related to the fusiform cortex was also identified, which connected higher socioeconomic status to crystallized intelligence. For participants assigned male at birth, a feminine identity was associated with increased anxiety and reduced cortical thickness in visual‐emotional regions. In contrast, masculine identity was linked to a larger cortical area in the supramarginal gyrus and insula. Altogether, these findings suggest that gender identity is embedded in distributed neural systems that support self‐representation, and that its structural correlates emerge through distinct psychological and cognitive‐contextual mechanisms. By moving beyond binary classification, this study may offer a more nuanced neurobiological model of gendered self‐concept in the general population. Key points What is already known about this topic? Gender identity has often been examined within binary frameworks (male vs. female or cisgender vs. transgender). Prior neuroimaging studies largely focused on clinical or transgender populations, overlooking variability in general populations. Most research has relied on categorical comparisons, rarely integrating psychological or socioeconomic factors alongside brain structure. What does this study add? Feminine gender identity in biologically female individuals was linked to reduced cortical thickness in the parahippocampal, fusiform, lingual, and pericalcarine cortices. Structural equation modeling revealed two distinct psychological pathways (autobiographical memory–based and visual–perceptual) and an independent socioeconomic–cognitive pathway shaping fusiform morphology. Findings highlight gender identity as a multidimensional factor embedded in distributed neural systems, moving beyond binary sex‐based models
COVID‐19 Stress and Resilience: A Longitudinal Cohort Study of First‐Year College Students
Get PDFINTRODUCTION: The COVID-19 pandemic affected all dimensions of the college experience. Research has explored COVID-19 stress and resilience factors, though this study is generally cross-sectional and lacks pre-pandemic baseline measures. Women and sexual/gender minority (SGM) college students experienced higher levels of COVID-19 stress but the effect on resilience is unknown. METHODS: Analysis of longitudinal survey data on a 2019 cohort of first-year college students attending a large public university in the southeast US (N = 444; average age at baseline 18.9; 67% female). We created a two-factor index of academic- and illness-related COVID-19 stress in June-July 2020 and assessed associations with resilience (as measured by the Brief Resilience Scale, BRS) throughout students' college careers. RESULTS: Resilience was lowest during students' junior year of college (October 2021) and returned to baseline levels by senior year. Cis women and SGM students experienced higher levels of COVID-19 academic and illness stress than cis men and non-SGM students. Academic and illness COVID-19 stress were associated with lower resilience; academic stress had larger initial negative associations that resolved by senior year, while illness stress had smaller initial negative associations that persisted. Academic and illness stress were more impactful for cis man and cis woman students, respectively. COVID-19 stress was not associated with resilience among SGM students. CONCLUSIONS: COVID-19 illness stress was associated with persistently lower perceived resilience among college students. Associations differed by gender and sexual/gender minority status. Students may benefit from resilience interventions to prepare for future emergencies and improve their well-being
A comprehensive comparison on clustering methods for multi-slice spatially resolved transcriptomics data analysis
Get PDFSpatial transcriptomics (ST) data, by providing spatial information, enable simultaneous analysis of gene expression distributions and their spatial patterns within tissue. Clustering or spatial domain detection represents an essential methodology for ST data, facilitating the exploration of spatial organizations with shared gene expression or histological characteristics. Traditionally, clustering algorithms for ST have focused on individual tissue sections. However, the emergence of numerous contiguous tissue sections derived from the same or similar tissue specimens within or across individuals has led to the development of multi-slice clustering methods. In this study, we assess seven single-slice and four multi-slice clustering methods on two simulated datasets and four real datasets. Additionally, we investigate the effectiveness of preprocessing techniques, including spatial coordinate alignment (e.g. PASTE) and gene expression batch effect removal (e.g. Harmony), on clustering performance. Our study provides a comprehensive comparison of clustering methods for multi-slice ST data, serving as a practical guide for method selection in various scenarios
A Direct-to-Patient Digital Health Program for Lung Cancer Screening: A Randomized Clinical Trial.
Get PDFScreening chest computed tomography (CT) scans reduce lung cancer mortality in high-risk individuals, but less than 20% of eligible individuals are screened in the US.To determine whether a direct-to-patient digital health program increases lung cancer screening.Randomized clinical trial enrolling individuals aged 50 to 77 years who met Centers for Medicare & Medicaid Services criteria for lung cancer screening between April 18, 2022, and May 30, 2023, at 2 academic health systems in the southeastern US. The date of last follow-up was September 30, 2024.Participants were randomized 1:1 to the mPATH-Lung program, a digital health program delivered outside a clinical visit that included a brief decision aid and option to request a screening appointment (n = 669) or enhanced usual care, in which patients were notified of their lung cancer screening eligibility and advised to speak with their primary care clinician (n = 664).The primary outcome was completion of any chest CT within 16 weeks. Secondary outcomes included screening decisions, process measures (screening visits, CT scans ordered), clinical outcomes (lung cancer screening results, lung cancers diagnosed), screening harms, and implementation outcomes.Electronic invitations were sent to 26 909 individuals with a smoking history in their electronic health record; 3267 completed website eligibility questions and 1333 were deemed eligible and enrolled. The mean age was 60.7 years (SD, 6.8 years); 864 (65%) were female; 232 (17%) were Black and 1054 (79%) were non-Hispanic White; and 621 (47%) had commercial insurance and 595 (45%) had public insurance. Chest CT completion was higher in the mPATH-Lung group than in controls (24.5% [164/669] vs 17.0% [113/664]; odds ratio, 1.6; 95% CI, 1.2-2.1). Among patients who completed screening CT, false-positive results occurred in 12.7% (19/150) of mPATH-Lung participants and 8.4% (8/95) of controls. Invasive procedures were performed in 2.0% (3/150) in the intervention group and 1.1% (1/95) in the control group, with no complications.Compared with enhanced usual care, a direct-to-patient digital health intervention increased rates of lung cancer screening. Future research should assess the reach and effectiveness of digital lung cancer screening interventions across diverse populations and health care settings. ClinicalTrials.gov Identifier: NCT04083859
Wave VI User Guide to Using Cross-Sectional and Longitudinal Weights
Get PDFThe National Longitudinal Study of Adolescent to Adult Health (Add Health) is a longitudinal study of a nationally representative sample of over 20,000 adolescents who were in grades 7-12 during the 1994-95 school year and who have been followed for six waves to date, most recently in 2022-2025. Over the years, Add Health has collected rich demographic, social, familial, socioeconomic, behavioral, psychosocial, cognitive, and health survey data from participants and their parents; a vast array of contextual data from participants’ schools, neighborhoods, and geographies of residence; and in-home physical and biological data from participants, including genetic markers, blood-based assays, anthropometric measures, and medications. Ancillary studies have added even more data over the years (Harris et al. 2019).
The overall goal of Add Health Wave VI was to collect and disseminate the comprehensive data needed to best understand the social, economic, psychosocial, contextual, and biological determinants of health trajectories and disparities among this nationally representative cohort of Americans as they age into midlife.
Wave VI of Add Health used a multifaceted, mixed-mode design similar to that used in Wave V. The Wave VI sample was split into two random subsamples, Samples 1 and 2. Similar to the mixed mode subsamples in Wave V (Samples 1, 2a and 3 in Wave V), the data collection for Sample 1 employed a mixed-mode, two-phase survey design. In the first phase, sample members were contacted primarily by mail, email or text message and asked to complete a web questionnaire. In the second phase, a subsample of nonrespondents was followed up through nonresponse follow-up (NRFU). Most of these cases were completed online, and others were completed via in-person interviews when needed. Similar to Sample 2b in Wave V, the data collection for Sample 2 in Wave VI largely employed an in-person interview collection mode. In addition, in Wave VI, Sample 2 nonrespondents were provided a web questionnaire as follow-up (an approach that was not used in Wave V)
The NLRP1 inflammasome is an essential and selective mediator of axon pruning in neurons
Get PDFAxon pruning is a unique process neurons utilize to selectively degenerate axon branches while keeping the neuronal cell body intact. The mechanisms of axon pruning have much in common with those of apoptosis. Both axon pruning and apoptosis pathways require key apoptotic proteins (Bax, Caspase-9, Caspase-3). Interestingly, axon pruning does not require Apaf-1, a key member of the apoptosome complex. As such, exactly how caspases are activated in an apoptosome-independent manner during axon pruning is unknown. Here we show that neurons utilize the NLRP1 inflammasome, an innate immune sensor of pathogens, specifically for axon pruning. Strikingly, NLRP1b-deficient neurons were unable to prune axons both in vitro and in vivo, but fully capable of degenerating during apoptosis. Our results reveal NLRP1 as an immune molecule engaged by neurons for an unexpected physiological function independent of its pathogen-induced proinflammatory role
Effect of Geometric Design on the Mechanical Performance of Digital Light Processing (DLP)-Printed Microneedles
Get PDFThis study describes the processing of microneedle (MN) arrays with three different heights of arrowhead (600 µm (A1), 800 µm (A2), and 1000 µm (A3)), pyramid (600 µm (P1), 800 µm (P2), and 1000 µm (P3)), and turret (600 µm (T1), 800 µm (T2), and 1000 µm (T3)) designs using a digital light processing (DLP)-based 3D printing method. The 3D-printed MNs were examined for their morphological characteristics and mechanical performance. Scanning electron microscopy (SEM) imaging confirmed that all of the MNs were fabricated without fracture or bending. Each design exhibited distinct structural characteristics: arrowhead MNs displayed a well-defined morphology with sharp tips, pyramid MNs showed slight layering, and turret MNs, characterized by a wider base and sharp tips, had a smoother surface compared to the other designs. Mechanical tests revealed that the arrowhead MNs carried less load and were more prone to bending, while the pyramid and turret designs provided higher mechanical stability and penetration capacity. The pyramid design (P3) showed the highest mechanical strength, while turret MNs offered a more stable performance despite lower penetration capacity. These findings highlight the critical role of geometric design in optimizing MN performance for effective transdermal drug delivery
Reply to Keeler, J.L.; Steinhäuser, J.L. Comment on “Wu et al. Peripheral Biomarkers of Anorexia Nervosa: A Meta-Analysis. Nutrients 2024, 16, 2095”
Get PDFThank you for the constructive feedback on our recent meta-analysis on peripheral biomarkers in anorexia nervosa (AN