Hasil untuk "Medicine (General)"

R. Wachter, L. Goldman

Yihe Wu, Jiayun Nian, Hongxu Liu et al.

Abstract Objective To analyze the regularities and clinical features of sintilimab-related autoimmune myocarditis, and to summarize the differential diagnosis key points between sintilimab-related autoimmune myocarditis and acute myocardial infarction. Methods The case reports about sintilimab-related autoimmune myocarditis were searched on databases from the establishment of the database to April 1st 2024. The relevant medical records were searched on the hospital information system of Beijing Hospital of Traditional Chinese Medicine in the past 3 years. The case reports and medical records were collected for statistical analysis. Result Twenty three cases were collected including 22 case reports and 1 case record. Most of the sintilimab-related autoimmune myocarditis were in elderly men aged 60–75 years old and occurred between the end of the first dose of treatment to the beginning of the second dose. The symptom was nonspecific such as chest tightness and palpitation, sometimes with symptom of myasthenia as muscle weakness or myositisand as muscle soreness. Elevated cardiac biomarkers and changes in electrocardiogram were common, and decreased left ventricular ejection fraction was rarely seen in echocardiography. 9 cases underwent coronary angiography or computed coronary tomography angiography, and 3 cases underwent cardiovascular magnetic resonance. Conclusion The manifestations of sintilimab-related autoimmune myocarditis are not specific. The medication history and concomitant symptoms are of warning value. Coronary angiography or coronary computed coronary tomography angiography can be helpful when ruling out acute myocardial infarction. Cardiovascular magnetic resonance and myocardial biopsy can confirm the diagnosis. Cardiac biomarkers and the electrocardiogram can assist in diagnosis and prognosis assessment.

Zhongyang Du, Mengjing Liang, Xiaodan Wang et al.

Introduction: Heavy metal pollution including lead (Pb) has become one of the serious global issues threatening food security, human health, and the ecosystem. Exogenous application of astaxanthin (ATX), a potent natural antioxidant, has been shown to enhance plant tolerance to various abiotic stresses. However, the role of endogenous ATX in alleviating Pb stress and the underlying molecular mechanisms remain poorly understood. Objectives: This study aimed to systematically investigate the effects and mechanism of endogenous ATX in biofortified tobacco (T-ATX) in promoting plant growth, particularly enhancing plant tolerance to Pb toxicity and blocking Pb pollution. Methods: Pot experiments were employed to investigate plant growth and Pb tolerance as well as Pb absorption and translocation in T-ATX and wild-type (SNN) tobacco seedlings subjected to various doses of Pb stress. Multiple physiological and cellular examinations were conducted, followed by integrated omics approaches in this study. Results: T-ATX plants exhibited an increased plant height, root length, leaf area, and biomass compared to SNN under Pb stress. T-ATX displayed higher levels of chlorophyll, photosynthetic efficiency, antioxidant enzyme activities, and non-enzymatic antioxidants, with improved integrity of subcellular structures. Remarkably, Pb content in various organs and Pb translocation coefficient were significantly reduced in T-ATX. Multiple genes and metabolites associated with antioxidant defense mechanisms, detoxification pathways, carotenoid metabolism, Pb ion transport, and plant hormone signal transduction were significantly upregulated in T-ATX tobacco plants. Conclusion: Endogenous ATX enriched in the T-ATX genotype significantly confers plant healthy performance and high tolerance to Pb stress by enhancing the antioxidant defense system, maintaining cellular structural integrity, reducing Pb absorption and translocation, upregulating detoxification and the related signaling pathways. These findings provide new insights into the endogenous ATX-mediated molecular mechanisms to promote plant growth and mitigate Pb toxicity, establishing a foundation for using ATX-fortified crops for green control technology of heavy metal pollution.

Jinglin He, Yunqi Guo, Lai Kwan Lam et al.

Traditional Chinese Medicine (TCM) represents a rich repository of ancient medical knowledge that continues to play an important role in modern healthcare. Due to the complexity and breadth of the TCM literature, the integration of AI technologies is critical for its modernization and broader accessibility. However, this integration poses considerable challenges, including the interpretation of obscure classical Chinese texts and the modeling of intricate semantic relationships among TCM concepts. In this paper, we develop OpenTCM, an LLM-based system that combines a domain-specific TCM knowledge graph and Graph-based Retrieval-Augmented Generation (GraphRAG). First, we extract more than 3.73 million classical Chinese characters from 68 gynecological books in the Chinese Medical Classics Database, with the help of TCM and gynecology experts. Second, we construct a comprehensive multi-relational knowledge graph comprising more than 48,000 entities and 152,000 interrelationships, using customized prompts and Chinese-oriented LLMs such as DeepSeek and Kimi to ensure high-fidelity semantic understanding. Last, we empower OpenTCM with GraphRAG, enabling high-fidelity ingredient knowledge retrieval and diagnostic question-answering without model fine-tuning. Experimental evaluations demonstrate that OpenTCM achieves mean expert scores (MES) of 4.378 in ingredient information retrieval and 4.045 in diagnostic question-answering tasks, outperforming state-of-the-art solutions in real-world TCM use cases.

Jiatong Han

Traditional Chinese Medicine (TCM) theory is built on imagistic thinking, in which medical principles and diagnostic and therapeutic logic are structured through metaphor and metonymy. However, existing English translations largely rely on literal rendering, making it difficult for target-language readers to reconstruct the underlying conceptual networks and apply them in clinical practice. This study adopted a human-in-the-loop (HITL) framework and selected four passages from the medical canon Huangdi Neijing that are fundamental in theory. Through prompt-based cognitive scaffolding, DeepSeek V3.1 was guided to identify metaphor and metonymy in the source text and convey the theory in translation. In the evaluation stage, ChatGPT 5 Pro and Gemini 2.5 Pro were instructed by prompts to simulate three types of real-world readers. Human translations, baseline model translations, and prompt-adjusted translations were scored by the simulated readers across five cognitive dimensions, followed by structured interviews and Interpretative Phenomenological Analysis (IPA). Results show that the prompt-adjusted LLM translations perform best across all five dimensions, with high cross-model and cross-role consistency. The interview themes reveal differences between human and machine translation, effective strategies for metaphor and metonymy transfer, and readers' cognitive preferences. This study provides a cognitive, efficient, and replicable HITL methodological pathway for the translation of ancient, concept-dense texts such as TCM.

Xinhan Zheng, Huyu Wu, Ruotai Li et al.

Traditional Chinese medicine (TCM) exhibits remarkable therapeutic efficacy in disease treatment and healthcare through patienti-specific formulas. However, current AI-based TCM formula recommendation models and methods mainly focus on data-based textual associations between symptoms and herbs, and have not fully utilized their features and relations at different scales, especially at the molecular scale. To address these limitations, we propose the Fusion of Multiscale Associations of Symptoms and Herbs (FMASH), an novel framework that effectively combines molecular-scale features and macroscopic properties of herbs with clinical symptoms, and provides the refined representation of their multiscale associations, enhancing the effectiveness of TCM formula recommendation. This framework can integrate molecular-scale chemical features and macroscopic properties of herbs, and capture complex local and global relations in the heterogeneous graph of symptoms and herbs, providing the effective embedding representation of their multiscale features and associations in a unified semantic space. Based on the refined feature representation, the framework is not only compatible with both traditional unordered formula recommendation task and the ordered herb sequence generation task, but also improves model's performance in both tasks. Comprehensive evaluations demonstrate FMASH's superior performance on the TCM formula recommendation over the state-of-the-art (SOTA) baseline, achieving relative improvements of 9.45\% in Precision@5, 12.11% in Recall@5, and 11.01% in F1@5 compared to the SOTA model on benchmark datasets. This work facilitates the practical application of AI-based TCM formula recommendation system.

Jacob E. Aronoff, Benjamin C. Trumble

The rise in chronic diseases over the last century presents a significant health and economic burden globally. Here we apply evolutionary medicine and life history theory to better understand their development. We highlight an imbalanced metabolic axis of growth and proliferation (anabolic) versus maintenance and dormancy (catabolic), focusing on major mechanisms including IGF-1, mTOR, AMPK, and Klotho. We also relate this axis to the hyperfunction theory of aging, which similarly implicates anabolic mechanisms like mTOR in aging and disease. Next, we highlight the Brain-Body Energy Conservation model, which connects the hyperfunction theory with energetic trade-offs that induce hypofunction and catabolic health risks like impaired immunity. Finally, we discuss how modern environmental mismatches exacerbate this process. Following our review, we discuss future research directions to better understand health risk. This includes studying IGF-1, mTOR, AMPK, and Klotho and how they relate to health and aging in human subsistence populations, including with lifestyle shifts. It also includes understanding their role in the developmental origins of health and disease as well as the social determinants of health disparities. Further, we discuss the need for future studies on exceptionally long-lived species to understand potentially underappreciated trade-offs and costs that come with their longevity. We close with considering possible implications for therapeutics, including (1) compensatory pathways counteracting treatments, (2) a Goldilocks zone, in which suppressing anabolic metabolism too far introduces catabolic health risks, and (3) species constraints, in which therapeutics tested in shorter lived species with greater anabolic imbalance will be less effective in humans.

Lalisa Saeaeh, Pornprom Sitthivethayanont, Theerawat Chalacheewa et al.

Abstract Background The 15-item Quality of Recovery scale (QoR-15), a short form of the QoR-40, is a widely used self-reported tool for measuring the postoperative quality of recovery. It has been translated into many languages. In this study, we aimed to validate a translated Thai version of the QoR-15 in patients undergoing elective abdominal surgery under general anesthesia. Methods This was a single-center observational cohort study. The QoR-15 was translated into Thai and culturally adapted, which led to the items on severe and moderate pain being merged, yielding a 14-item scale: the QoR-14-Thai. Next, the QoR-14-Thai, a checklist measuring the patients’ activities of daily living (ADL), and a 100-mm visual analog scale for assessing their global health (VAS-GH) were administered to the study patients before and 24 h after their abdominal surgery. The validity, reliability, responsiveness, and feasibility of the QoR-14-Thai were assessed. Results Among 166 patients, 140 completed the questionnaires, achieving a questionnaire completion rate of 100%. We observed moderate convergent validity between the postoperative QoR-14-Thai and the VAS-GH (r = 0.54, p < 0.001) and ADL checklist (r = 0.50, p < 0.001). The QoR-14-Thai was negatively correlated with the length of hospital stay (r = − 0.23, p < 0.006) and postoperative admission to the intensive care unit (r = − 0.85, p = 0.001). The QoR-14-Thai had excellent internal consistency (Cronbach’s alpha = 0.869), split-half reliability (0.913), test–retest reliability (0.94), and high responsiveness (Cohen’s effect size: 1.01, standardized response mean: 0.73). The median time to complete the questionnaire was 2 min (interquartile range: 1–2). Conclusions The QoR-14-Thai was deemed a valid, reliable, and convenient tool for evaluating the quality of recovery after elective abdominal surgery. Trial registration This study was registered prospectively on the Thai Clinical Trials Registry, identifier TCTR20210326009, on March 26, 2021.

Zahra Nafisi, Adele Pouyafard, Amene Hosseini Yekani et al.

Introduction: Dental injuries are very common and negatively affect an individual's life. The effective management of emergencies in such situations depends on the knowledge of non-experts, such as healthcare providers, who are on-site during the event. This study aimed to investigate the knowledge extent and self-perceived practice of healthcare providers in elementary schools in Abarkuh City regarding the emergency management of traumatic dental injuries. Methods: This descriptive cross-sectional study utilized an online, anonymous questionnaire designed to gather demographic information, assess the background of previous exposure to dental traumatic injuries, and evaluate caregivers' performance in managing such injuries. The questionnaire was distributed to virtual groups of healthcare providers, who had one week to complete it. The collected data were analyzed using descriptive statistics and linear regression tests. Results: A total of 189 questionnaires were filled out, resulting in a response rate of 80.77%. The average knowledge score of the respondents was 5.63 ± 1.98 out of a possible 10 points, whereas their respondents’ average performance score was 4.48 ± 1.86 on the scale of 7 points. Linear regression analysis indicated that the caregivers' previous knowledge significantly influenced their knowledge level (p < 0.001). After adjusting for demographic variables, the study revealed that caregivers' work experience positively impacted their knowledge score (p = 0.009). However, the self-reported performance ratings of healthcare providers did not show any significant correlation with demographic variables. Conclusion: The results of this study show that primary school healthcare workers have inadequate knowledge and self-reported performance concerning dental injuries resulting from trauma.

Sjoerd J.D. Tjalsma, Niels J. Rinzema, Marjon J.A.M. Verstegen et al.

Summary: Cell-type-specific gene activation is regulated by enhancers, sometimes located at large genomic distances from target gene promoters. Whether distal enhancers require specific factors to orchestrate gene regulation remains unclear. Here, we used enhancer distance-controlled reporter screens to find candidate factors. We depleted them and employed activity-by-contact predictions to genome-wide classify genes based on enhancer distance. Predicted distal enhancers typically control tissue-restricted genes and often are strong enhancers. We find cohesin, but also mediator, most specifically required for long-range activation, with cohesin repressing short-range gene activation and prioritizing distal over proximal HBB genes competing for shared enhancers. Long-range controlled genes are also most sensitive to perturbations of other regulatory proteins and to BET inhibitor JQ1, this being more a consequence of their distinct enhancer features than distance. Our work predicts that lengthening of intervening sequences can help limit the expression of target genes to specialized cells with optimal trans-factor environments.

Zagalioti SC, Ziaka M, Exadaktylos A et al.

Sofia-Chrysovalantou Zagalioti,1 Mairi Ziaka,2 Aristomenis Exadaktylos,2 Barbara Fyntanidou1 1Department of Emergency Medicine, AHEPA University General Hospital, Aristotle University of Thessaloniki, Thessaloniki, Greece; 2Department of Emergency Medicine, Inselspital University Hospital, University of Bern, Bern, SwitzerlandCorrespondence: Sofia-Chrysovalantou Zagalioti, Email sofia_zag@yahoo.comBackground: Accurate decision-making in triage largely determines the amount of time required for a patient to be evaluated and treated while in the emergency department. Nursing staff worldwide have similar learning characteristics with similar working hours and common goals, despite the fact that different triage scales are used globally. The aim of this mini review is to present the different educational methods and identify the most effective for triage training of triage nurses.Materials and Methods: We screened studies concerning triage education for nurses in Emergency Department, in databases including PubMed, CENTRAL and CINAHL. From November 12, 2023 to February 15, 2024, databases were searched for relevant literature. “Triage education” OR “triage training” AND “emergency nurses” OR “triage nurses” were the MeSH terms.Results: There are various educational methods, including traditional, web-based, audiovisual, simulation-based, blended learning, and other specialized approaches. Almost all of the studies that are currently available demonstrate how effectively an educational intervention might improve nurses’ comprehension of triage. Except for one, every study concluded that the educational intervention significantly improved nurses’ triage knowledge. Comparing the included studies is challenging due to their heterogeneity, and applying the results in practice requires caution.Conclusion: The majority of studies reported that educational interventions effectively increased nurses’ triage knowledge. Blended learning in conjunction with refresher courses enhanced triage-related knowledge and decision-making; however, additional research is required to ascertain whether this approach is superior to the others and whether these improvements will last.Keywords: educational method, emergency department, triage education

Kapil Sayal, Laura Wyatt, Louise Thomson et al.

Background Emotional disorders are common in children and young people and can significantly impair their quality of life. Evidence-based treatments require a timely and appropriate diagnosis. The utility of standardised diagnostic assessment tools may aid the detection of emotional disorders, but there is limited evidence of their clinical value. Objectives To assess the clinical effectiveness and cost effectiveness of a standardised diagnostic assessment for children and young people with emotional difficulties referred to Child and Adolescent Mental Health Services. A nested qualitative process evaluation aimed to identify the barriers and facilitators to using a standardised diagnostic assessment tool in Child and Adolescent Mental Health Services. Design A United Kingdom, multicentre, two-arm, parallel-group randomised controlled trial with a nested qualitative process evaluation. Setting Eight National Health Service Trusts providing multidisciplinary specialist Child and Adolescent Mental Health Services. Participants Children and young people aged 5–17 years with emotional difficulties referred to Child and Adolescent Mental Health Services, excluding emergency/urgent referrals that required an expedited assessment. In the qualitative process evaluation, 15 young people aged 16–17 years, 38 parents/carers and 56 healthcare professionals participated in semistructured interviews. Interventions Participants were randomly assigned (1 : 1) following referral receipt to intervention (the development and well-being assessment) and usual care, or usual care only. Main outcome measures Primary outcome was a clinician-made diagnosis decision about the presence of an emotional disorder within 12 months of randomisation, collected from Child and Adolescent Mental Health Services clinical records. Secondary outcomes collected from clinical records included referral acceptance, time to offer and start treatment/interventions and discharge. Data were also self-reported from participants through online questionnaires at baseline, 6 and 12 months post randomisation, and the cost effectiveness of the intervention was investigated. Results One thousand two hundred and twenty-five (1225) children and young people were randomly assigned (1 : 1) to study groups between 27 August 2019 and 17 October 2021; 615 were assigned to the intervention and 610 were assigned to the control group. Adherence to the intervention (full/partial completion of the development and well-being assessment) was 80% (494/615). At 12 months, 68 (11%) participants in the intervention group received an emotional disorder diagnosis versus 72 (12%) in the control group [adjusted risk ratio 0.94 (95% confidence interval 0.70 to 1.28); p = 0.71]. Child and Adolescent Mental Health Services acceptance of the index referral [intervention 277 (45%) vs. control 262 (43%); risk ratio: 1.06 (95% confidence interval: 0.94 to 1.19)] or any referral by 18 months [intervention 374 (61%) vs. control 352 (58%); risk ratio: 1.06 (95% confidence interval: 0.97 to 1.16)] was similar between groups. There was no evidence of any differences between groups for any other secondary outcomes. The qualitative nested process evaluation identified a number of barriers and facilitators to the use of the development and well-being assessment during the trial, particularly at the assessment and diagnosis stages of the Child and Adolescent Mental Health Services pathway. Limitations It was not possible to mask participants, clinicians or site researchers collecting source data to treatment allocation. Conclusions We found no evidence that completion of the development and well-being assessment aided the detection of emotional disorders in this study. Using the development and well-being assessment in this way cannot be recommended for clinical practice. Future research To determine longer-term service use outcomes and to investigate whether receipt of a clinical diagnosis makes a difference to clinical outcomes and care/intervention receipt. Funding This synopsis presents independent research funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme as award number 16/96/09. Plain language summary Emotional difficulties are common in children and young people, and many may be referred to Child and Adolescent Mental Health Services. Referrals are sometimes rejected because of insufficient information. Even if the referral is accepted, a clinical diagnosis is often not reached. A correct diagnosis is vital so that the right help can be offered. We investigated whether a standardised online information-gathering package (development and well-being assessment) helps with the assessment and diagnosis process in Child and Adolescent Mental Health Services. We invited children and young people and their families, following a routine (non-urgent) referral into Child and Adolescent Mental Health Services, from eight National Health Services Trusts across England. One thousand two hundred and twenty-five (1225) families took part – half received usual care (control group), and half received usual care and were also asked to complete the development and well-being assessment (development and well-being assessment group). Families also completed questionnaires about the child’s/young person’s mental health at the beginning of the study and then 6 and 12 months later. Child and Adolescent Mental Health Services clinical records were reviewed 12 and 18 months after joining the study to look at what care was offered and received through Child and Adolescent Mental Health Services. We also interviewed a range of young people, family members and staff in Child and Adolescent Mental Health Services about their views and experience of using the development and well-being assessment and the summary development and well-being assessment report. At 12-month follow-up, there was no difference in the number receiving an emotional disorder diagnosis; 11% in the development and well-being assessment group and 12% in the control group. The same was found at 18 months (14% vs. 15%). There was no difference between the groups in the time taken to reach a diagnosis or to offer or start treatment, nor was there any significant impact on whether Child and Adolescent Mental Health Services accepted the referral. The interviews showed that young people and families found the development and well-being assessment and report to be useful; however, the development and well-being assessment report was not used consistently, as intended, by clinicians during assessments to aid diagnosis. These findings show that completing the development and well-being assessment after referral into Child and Adolescent Mental Health Services did not have any impact on whether a diagnosis was made by Child and Adolescent Mental Health Services or on the care received.

Manjiang Yu, Xue Li

In time-critical decisions, human decision-makers can interact with AI-enabled situation-aware software to evaluate many imminent and possible scenarios, retrieve billions of facts, and estimate different outcomes based on trillions of parameters in a fraction of a second. In high-order reasoning, "what-if" questions can be used to challenge the assumptions or pre-conditions of the reasoning, "why-not" questions can be used to challenge on the method applied in the reasoning, "so-what" questions can be used to challenge the purpose of the decision, and "how-about" questions can be used to challenge the applicability of the method. When above high-order reasoning questions are applied to assist human decision-making, it can help humans to make time-critical decisions and avoid false-negative or false-positive types of errors. In this paper, we present a model of high-order reasoning to offer recommendations in evidence-based medicine in a time-critical fashion for the applications in ICU. The Large Language Model (LLM) is used in our system. The experiments demonstrated the LLM exhibited optimal performance in the "What-if" scenario, achieving a similarity of 88.52% with the treatment plans of human doctors. In the "Why-not" scenario, the best-performing model tended to opt for alternative treatment plans in 70% of cases for patients who died after being discharged from the ICU. In the "So-what" scenario, the optimal model provided a detailed analysis of the motivation and significance of treatment plans for ICU patients, with its reasoning achieving a similarity of 55.6% with actual diagnostic information. In the "How-about" scenario, the top-performing LLM demonstrated a content similarity of 66.5% in designing treatment plans transferring for similar diseases. Meanwhile, LLMs managed to predict the life status of patients after their discharge from the ICU with an accuracy of 70%.

Lingxia Qiao, Ali Khalilimeybodi, Nathaniel J Linden-Santangeli et al.

Understanding the mechanisms of interactions within cells, tissues, and organisms is crucial to driving developments across biology and medicine. Mathematical modeling is an essential tool for simulating biological systems and revealing biochemical regulatory mechanisms. Building on experiments, mechanistic models are widely used to describe small-scale intracellular networks and uncover biochemical mechanisms in healthy and diseased states. The rapid development of high-throughput sequencing techniques and computational tools has recently enabled models that span multiple scales, often integrating signaling, gene regulatory, and metabolic networks. These multiscale models enable comprehensive investigations of cellular networks and thus reveal previously unknown disease mechanisms and pharmacological interventions. Here, we review systems biology models from classical mechanistic models to larger, multiscale models that integrate multiple layers of cellular networks. We introduce several examples of models of hypertrophic cardiomyopathy, exercise, and cancer cell proliferation. Additionally, we discuss methods that increase the certainty and accuracy of model predictions. Integrating multiscale models has become a powerful tool for understanding disease and inspiring drug discoveries by incorporating omics data within the cell and across tissues and organisms.

Zheng Zhu, Xiaofeng Wang, Wangbo Zhao et al.

General world models represent a crucial pathway toward achieving Artificial General Intelligence (AGI), serving as the cornerstone for various applications ranging from virtual environments to decision-making systems. Recently, the emergence of the Sora model has attained significant attention due to its remarkable simulation capabilities, which exhibits an incipient comprehension of physical laws. In this survey, we embark on a comprehensive exploration of the latest advancements in world models. Our analysis navigates through the forefront of generative methodologies in video generation, where world models stand as pivotal constructs facilitating the synthesis of highly realistic visual content. Additionally, we scrutinize the burgeoning field of autonomous-driving world models, meticulously delineating their indispensable role in reshaping transportation and urban mobility. Furthermore, we delve into the intricacies inherent in world models deployed within autonomous agents, shedding light on their profound significance in enabling intelligent interactions within dynamic environmental contexts. At last, we examine challenges and limitations of world models, and discuss their potential future directions. We hope this survey can serve as a foundational reference for the research community and inspire continued innovation. This survey will be regularly updated at: https://github.com/GigaAI-research/General-World-Models-Survey.

Xue-Qing Zhang, Xiaoyang Xu, N. Bertrand et al.

The application of nanotechnology to personalized medicine provides an unprecedented opportunity to improve the treatment of many diseases. Nanomaterials offer several advantages as therapeutic and diagnostic tools due to design flexibility, small sizes, large surface-to-volume ratio, and ease of surface modification with multivalent ligands to increase avidity for target molecules. Nanomaterials can be engineered to interact with specific biological components, allowing them to benefit from the insights provided by personalized medicine techniques. To tailor these interactions, a comprehensive knowledge of how nanomaterials interact with biological systems is critical. Herein, we discuss how the interactions of nanomaterials with biological systems can guide their design for diagnostic, imaging and drug delivery purposes. A general overview of nanomaterials under investigation is provided with an emphasis on systems that have reached clinical trials. Finally, considerations for the development of personalized nanomedicines are summarized such as the potential toxicity, scientific and technical challenges in fabricating them, and regulatory and ethical issues raised by the utilization of nanomaterials.

A. White, R. Atmar, S. Greenberg

J. Wislar, A. Flanagin, P. Fontanarosa et al.

Objectives To assess the prevalence of honorary and ghost authors in six leading general medical journals in 2008 and compare this with the prevalence reported by authors of articles published in 1996. Design Cross sectional survey using a web based questionnaire. Setting International survey of journal authors. Participants Sample of corresponding authors of 896 research articles, review articles, and editorial/opinion articles published in six general medical journals with high impact factors in 2008: Annals of Internal Medicine, JAMA, Lancet, Nature Medicine, New England Journal of Medicine, and PLoS Medicine. Main outcome measures Self reported compliance with International Committee of Medical Journal Editors (ICMJE) criteria for authorship for all authors on the selected articles. Results A total of 630/896 (70.3%) corresponding authors responded to the survey. The prevalence of articles with honorary authorship or ghost authorship, or both, was 21.0% (95% CI 18.0% to 24.3%), a decrease from 29.2% reported in 1996 (P=0.004). Based on 545 responses on honorary authorship, 96 articles (17.6% (95% CI 14.6% to 21.0%)) had honorary authors (range by journal 12.2% to 29.3%), a non-significant change from 1996 (19.3%; P=0.439). Based on 622 responses on ghost authorship, 49 articles (7.9% (6.0% to 10.3%)) had ghost authors (range by journal 2.1% to 11.0%), a significant decline from 1996 (11.5%; P=0.023). The prevalence of honorary authorship was 25.0% in original research reports, 15.0% in reviews, and 11.2% in editorials, whereas the prevalence of ghost authorship was 11.9% in research articles, 6.0% in reviews, and 5.3% in editorials. Conclusions Evidence of honorary and ghost authorship in 21% of articles published in major medical journals in 2008 suggests that increased efforts by scientific journals, individual authors, and academic institutions are essential to promote responsibility, accountability, and transparency in authorship, and to maintain integrity in scientific publication.

Emma Chen, Aman Kansal, Julie Chen et al.

We propose the Multimodal Clinical Benchmark for Emergency Care (MC-BEC), a comprehensive benchmark for evaluating foundation models in Emergency Medicine using a dataset of 100K+ continuously monitored Emergency Department visits from 2020-2022. MC-BEC focuses on clinically relevant prediction tasks at timescales from minutes to days, including predicting patient decompensation, disposition, and emergency department (ED) revisit, and includes a standardized evaluation framework with train-test splits and evaluation metrics. The multimodal dataset includes a wide range of detailed clinical data, including triage information, prior diagnoses and medications, continuously measured vital signs, electrocardiogram and photoplethysmograph waveforms, orders placed and medications administered throughout the visit, free-text reports of imaging studies, and information on ED diagnosis, disposition, and subsequent revisits. We provide performance baselines for each prediction task to enable the evaluation of multimodal, multitask models. We believe that MC-BEC will encourage researchers to develop more effective, generalizable, and accessible foundation models for multimodal clinical data.

Janine B. Kastelijn, Yorick L. van de Pavert, Marc G. Besselink et al.

Abstract Background Malignant gastric outlet obstruction (GOO) is a debilitating condition that frequently occurs in patients with malignancies of the distal stomach and (peri)ampullary region. The standard palliative treatment for patients with a reasonable life expectancy and adequate performance status is a laparoscopic surgical gastrojejunostomy (SGJ). Recently, endoscopic ultrasound-guided gastroenterostomy (EUS-GE) emerged as a promising alternative to the surgical approach. The present study aims to compare these treatment modalities in terms of efficacy, safety, and costs. Methods The ENDURO-study is a multicentre, open-label, parallel-group randomized controlled trial. In total, ninety-six patients with gastric outlet obstruction caused by an irresectable or metastasized malignancy will be 1:1 randomized to either SGJ or EUS-GE. The primary endpoint is time to tolerate at least soft solids. The co-primary endpoint is the proportion of patients with persisting or recurring symptoms of gastric outlet obstruction for which a reintervention is required. Secondary endpoints are technical and clinical success, quality of life, gastroenterostomy dysfunction, reinterventions, time to reintervention, adverse events, quality of life, time to start chemotherapy, length of hospital stay, readmissions, weight, survival, and costs. Discussion The ENDURO-study assesses whether EUS-GE, as compared to SGJ, results in a faster resumption of solid oral intake and is non-inferior regarding reinterventions for persistent or recurrent obstructive symptoms in patients with malignant GOO. This trial aims to guide future treatment strategies and to improve quality of life in a palliative setting. Trial registration International Clinical Trials Registry Platform (ICTRP): NL9592. Registered on 07 July 2021.