Citations

Mechanical ventilation remains a cornerstone of acute respiratory failure management, but ventilator-induced lung injury persists despite lung-protective strategies focused on limiting tidal volume (V T ), plateau pressure, and driving pressure. Mechanical power has emerged as a comprehensive metric that quantifies the total energy delivered to the lungs per unit time by integrating V T , airway pressures, breathing frequency, flow, and PEEP into a single physiologic measure. Observational studies through 2025 show that elevated mechanical power is associated with worse outcomes, including increased mortality, fewer ventilator-free days, and longer ICU stays, with breathing frequency identified as a major contributor even when other settings remain within protective ranges. Although no universal injurious threshold exists because of patient variability, normalization strategies such as indexing mechanical power to predicted body weight or respiratory system compliance have shown promise in improving prognostic value, although consensus on the optimal method is lacking. Currently, mechanical power should be considered a complementary bedside tool that integrates multiple ventilator variables, helps identify key contributors to lung stress and strain, and may support individualized ventilator adjustments to reduce cumulative injury risk as further evidence and technology evolve.

Chimeric antigen receptor (CAR) T cell therapy faces many challenges against solid tumors including T cell exhaustion and poor CAR durability. Here, we show that engaging the CAR T cell endogenous T cell receptor (TCR) using an oncolytic virus enhances CAR T cell functionality, durability, and therapy. Upon combination therapy of solid tumors with CAR T cells and vesicular stomatitis virus (VSV), a subpopulation of antiviral, TCR-primed CAR T cells was generated with enhanced effector functions, altered activation states, and differential gene and protein expression when compared to non–TCR-primed CAR T cells. Single-cell RNA sequencing showed clonal expansion of anti-VSV CAR T cells and enhancement of effector-associated genes with VSV-mediated CAR T cell expansion. CD4 T cells played a pivotal role in the development of these TCR-primed CAR T cells. These results provide a strong rationale both for a novel use of systemic oncolytic virotherapy and for directly exploiting the CAR T cell TCR to fine tune the CAR T cell phenotype and function.

Abstract The persistent global rise in atherosclerotic cardiovascular disease (ASCVD) challenges the effectiveness of current risk factor-based algorithms in primary prevention. Most myocardial infarctions occur in individuals without prior symptoms or recognized standard modifiable risk factors, underscoring the need to improve risk stratification. Coronary CT imaging, including coronary artery calcium scoring (CACS) and coronary computed tomography angiography (CCTA), enables direct non-invasive visualization of coronary atherosclerosis, supporting a shift from population-based prevention towards personalized, disease-based risk assessment and targeted preventive treatment. CCTA provides comprehensive evaluation of plaque burden, composition, stenosis severity, and high-risk plaque (HRP) features, thereby refining risk stratification and guiding personalized treatment decisions. The presence and total burden of coronary atherosclerotic plaque are considered the primary CCTA-derived markers for guiding preventive therapy, while noncalcified plaque burden and HRP features may support treatment intensification. Advances in CT technology, including photon-counting CT, and the application of artificial intelligence-based tools may further refine risk assessment by enabling accurate and reproducible plaque quantification and characterization. Although no randomized trials have yet demonstrated that CCTA-based screening improves clinical outcomes in asymptomatic individuals compared with standard care, the same is true of traditional cardiovascular risk scores. Three large ongoing randomized trials are currently evaluating whether CCTA-guided, personalized prevention strategies can reduce ASCVD events. The results are eagerly awaited and may redefine the role of CCTA in asymptomatic individuals.

Abstract This literature‐based systematic review and associated guidelines provide evidence‐based paradigms for the management of locoregionally recurrent rectal cancer (LRRC). This multispecialty committee included gastrointestinal radiation and medical oncology, gastroenterology, radiology, and colorectal surgery. As is the standard, the previously described American Radium Society Appropriate Use Criteria methodology for this project was followed rigorously, with the Population, Intervention, Comparator, Outcome, Timing, and Study Design framework and Preferred Reporting Items for Systematic Reviews and Meta‐Analyses methodology to assess the evidence. RAND/University of California Los Angeles consensus methodology (modified Delphi) was used to rate the appropriateness of treatment options. Published between January 1, 2013, and July 16, 2025, 116 peer‐reviewed trials provided the evidence: 10 were well‐designed randomized phase 2/3 trials, 29 were moderately well designed trials that accounted for most common biases (matched cohort and phase 2), 76 trials had design limitations (retrospective), and one was a meta‐analysis. Clinical cases were created as examples to illustrate current acceptable management of LRRC. Treatment and prognosis are influenced by prior therapy and the site(s) and extent of LRRC. The ability to achieve a margin‐negative surgical resection is the ultimate determinant of survival and local control. Preoperative systemic therapy, radiation therapy, or a combination of the two can facilitate tumor downsizing and improve the likelihood of a margin‐negative resection. An individualized multidisciplinary approach is required to ensure the best outcome. Although this review does not suggest a major alteration of current practice, it provides reassuring evidence of the importance of combined‐modality therapy.

Abstract Exposure to asbestos is the primary cause of mesothelioma, however the processes underpinning its initiation and evolutionary trajectory remain elusive. To address this knowledge gap, we conducted whole exome sequencing and phylogenetic analysis of 277 mesotheliomas. Using multidimensional Dirichlet process clustering we inferred phylogenies, uncovering mutation order dominated by early 13q,1p, 8p, 6q and 22q somatic copy number alterations. Mesotheliomas exhibit a spectrum of genomic intra-tumor heterogeneity spanning linear (L) to highly branched (B) tree topologies, quantifiable by the Weighted Shannon Entropy (WSE). Somatic copy number alterations emerge earlier than single nucleotide variants (SNVs), and at a much faster relative rate in L-mesotheliomas. BAP1 is the only positively selected driver in L-mesotheliomas, whereas, B-mesotheliomas harbor multiple positively selected drivers and an aggressive phenotype, including a bias of loss of RPL5, and MTAP deletion linked to breakpoint enriched with long interspersed nuclear elements. L-trees had lower WSE, but greater T-cell inflammation and tertiary lymphoid structures, despite having a lower neoantigen burden. WSE is higher in larger volume, immunologically cold mesotheliomas, and is associated with shorter survival. In summary, progressive genomic heterogeneity is a defining feature of more aggressive mesothelioma yet illuminates opportunities for precision therapeutic intervention.

Abstract Antidepressants are widely prescribed for major depressive disorder, yet only one-third of patients achieve remission after initial treatment. Previous genome-wide association studies (GWAS) of clinically assessed antidepressant response combined multiple antidepressant classes, potentially obscuring class-specific effects. This study focused on selective serotonin reuptake inhibitors (SSRIs), often first-line due to better tolerability. Data from 15 cohorts across four ancestries were integrated: European (N = 3887; 11 studies), East Asian (N = 1068; 4), African (N = 277; 1), and Admixed American (N = 250; 1). GWAS of non-remission and percentage improvement were conducted within cohorts, followed by ancestry-specific meta-analyses and trans-ancestry meta-regression. Single nucleotide polymorphism (SNP)-based heritability was estimated in European samples. Polygenic scores were used for leave-one-out prediction and to assess shared genetic architecture with psychiatric traits. Gene-level and gene-set enrichment analyses were also performed. No genome-wide significant variants were identified for either outcome in any ancestry-specific or trans-ancestry analyses. However, trans-ancestry meta-regression yielded eight independent loci with suggestive associations (p < 1 × 10 −5 ) for non-remission and 17 for percentage improvement. Gene-set analyses revealed nominal enrichment of the serotonergic synapse pathway for non-remission. SNP-based heritability estimates were not significantly different from zero for either outcome. Better SSRI response was nominally associated with lower genetic predisposition to major depressive disorder, post-traumatic stress disorder, and schizophrenia. This study represents the largest trans-ancestry GWAS of SSRI response, highlighting emerging biological signals. Limited power emphasises the need for larger and ancestrally diverse cohorts to better characterise the genetic architecture of antidepressant response.

Summary Human spaceflight has historically been led by government agencies, but the emergence of commercial organizations is enabling broader participation and new research opportunities. In this study, we present a comprehensive molecular characterization of early human responses to spaceflight, leveraging multi-omics data across the first three weeks of two commercial missions. Biospecimens from six individuals, four from the Axiom 2 mission (10 days) and two from Axiom 3 (21 days), were analyzed using single-cell and bulk RNA sequencing, alongside proteomic profiling. Individual and integrative analyses of these datasets reveal systemic changes in cell types, transcripts, and proteins related to immune regulation, osteoclast differentiation, NF-κB signaling, and blood homeostasis pathways. Importantly, several of the detected pathways align with physiological patterns observed in longer-duration missions. This work establishes a foundational resource for understanding early adaptation to spaceflight at the cellular and molecular levels, providing insights to reduce future space-travel health risks. Highlights First integrated multi-omics analysis using single-cell, bulk RNA sequencing and proteomic profiling of early human spaceflight responses across two commercial missions (Ax-2 and Ax-3). Distinct PBMC clustering was observed across Ax-2 and Ax-3, and post-flight samples. It showed fewer monocytes, dendritic cells, and megakaryocytes with increased naïve CD4⁺ and cytotoxic T cells. Multi-omics integration identifies shared biological signatures, including osteoclast differentiation, metabolic stress, and coagulation changes. These findings lay the foundation for developing countermeasures to protect immune, skeletal, and vascular health during spaceflight.

Abstract Clinical medical physics is a profession that intersects with various groups as part of a broader healthcare team, including dosimetrists, radiation therapists, radiologic and MRI technologists, IT specialists, and physicians. Success in this field requires academic and technical excellence as well as comprehensive skills for working effectively within an interdisciplinary healthcare team. When hiring medical physics residents, the selection of well‐rounded and highly qualified candidates can be facilitated through a holistic review process that ensures consideration of traditional metrics such as academic performance while also accounting for the importance of various experiences, personal attributes, and intrinsic motivations that impact clinical performance and patient care. The Association of American Medical Colleges (AAMC) emphasizes an overall consideration of Experiences, Attributes, Competencies, and Metrics (EACM) as important for the search process. As part of the healthcare community, medical physics shares the same commitment to high‐quality patient care. By adopting the AAMC's EACM framework, medical physics residency programs can strengthen the fairness, rigor, and overall effectiveness of their application review processes—ultimately benefiting applicants, the medical physics community, and the patients we serve. This Society of Directors of Academic Medical Physics Programs (SDAMPP) task report aims to provide information and resources for applying holistic review to the applicant selection process for medical physics residency programs. Our objective is to enable program directors to reevaluate their selection methods in the context of institutional and program missions and goals and to improve the quality and specificity of recruitment by integrating holistic review concepts into their residency recruitment processes. This initiative can inspire change in recruitment practices, aid programs in hiring well‐rounded and well‐qualified residents, and support the professional growth of our trainees in healthcare. This report provides an overview of holistic reviews and its core principles. We review the current literature and provide evidence from successful implementations of holistic review in other medical fields to illustrate how it can benefit our field. Furthermore, we outline actionable recommendations to facilitate transitioning to a holistic review framework and address potential barriers with practical solutions. A supplemental workbook is provided to guide residency programs in developing their own holistic application review and interview processes. With this report, we aim to provide practical implementation guidelines that will allow residency program directors to implement a selection methodology that comprehensively assesses the full qualifications of individual candidates and ultimately fosters the development of versatile and competent clinical medical physicists who are best equipped to advance the field, meet patient needs, and improve patient care.

Abstract Pain assessment plays a critical role in clinical decision-making, yet conventional methods rely heavily on subjective self-reports such as the Visual Analog Scale (VAS) or the Numeric Rating Scale (NRS). These approaches fail in scenarios involving infants, sedated patients, unconscious individuals, or those with cognitive or communication impairments. To address this gap, this research proposes PainNet, an AI-driven, real-time facial pain recognition system that integrates deep learning-based object detection with Action Unit (AU)–based pain intensity scoring. The system uses YOLOv8 for rapid facial expression detection and incorporates Py-Feat to extract pain-relevant AUs, enabling computation of the Prkachin and Solomon Pain Intensity (PSPI) score. A balanced dataset comprising 500 images sourced from Delaware, BioVid, and RaFD was curated, annotated, and preprocessed for training. The YOLOv8-based binary pain vs. no-pain classifier achieved a mean Average Precision (mAP) of 0.89 and an F1-score of 0.80 on the test dataset, demonstrating strong performance in diverse environments and facial variations. The design emphasizes computational efficiency by activating AU analysis only when YOLOv8 detects probable pain, making PainNet suitable for continuous monitoring in ICUs, elder-care facilities, and telemedicine systems. This study demonstrates that the fusion of real-time object detection and clinically validated AU scoring can significantly advance automated, objective, and scalable pain assessment.

Objective: To develop a predictive model for pathological complete response (pCR) after total neoadjuvant therapy (TNT) to inform selection for watch-and-wait (W/W). Summary Background Data: Patient selection for W/W after TNT for locally advanced rectal cancer remains challenging. Methods: An ensemble of tabular foundation models was fine-tuned in adults with clinical stage II or III microsatellite stable primary rectal adenocarcinoma undergoing TNT and total mesorectal excision (TNT+TME) from 2018-2023 to predict pCR, using pre-TNT, post-TNT and pre-TME variables. This model was externally validated on patients having TNT and W/W (TNT+W/W) to predict persistent clinical complete response (pcCR; the absence of local regrowth, distant metastases, or persistent near-cCR). Area under the receiver operator curve (AUROC), area under the precision-recall curve (AUPRC), and Brier score were calculated with 95% confidence intervals (CI). Results: Among 308 patients that underwent TNT+TME (median age 56; 40% female), the model predicted pCR with an AUROC 0.71 (95% CI 0.65-0.77), AUPRC 0.44 (95% CI 0.35-0.57), and was well calibrated with a Brier score of 0.17 (95% CI 0.15-0.20). At external validation in a cohort of 83 patients that are being managed with TNT+W/W (median age 57; 37% female), the model predicted pcCR with an AUROC 0.69 (95% CI 0.57-0.82), AUPRC 0.90 (95% CI 0.82-0.96), and Brier score of 0.30 (95% CI 0.26-0.33), improving to 0.17 with recalibration. Conclusions: This novel predictive model demonstrated good discrimination and calibration for pCR after TNT+TME with utility in TNT+W/W for pcCR after appropriate recalibration, supporting its application for W/W patient selection.