We assess the contribution of cardboard dust exposure to the development of work-related asthma (WRA). Prior studies on paper-dust-related breathing problems have focused on exposures in the paper milling and pulp industries. There have been no reports of asthma linked to workplace exposure to cardboard dust. From 1988 to 2022, all cases of asthma associated with paper and cardboarddust exposure reported to the Michiganstatewide surveillance system were identified. We summarize the characteristics of these workers. Eight cases of paper-dust-related asthma were identified. Seven of the cases were attributed to cardboard dust, and one to paper dust exposure. Half were exposed to cardboard dust while packaging and shipping products in cardboard containers. Five of the cases were new-onset asthma; the other three were work-aggravated asthma. No exposures were reported from paper milling or pulp industries. Cardboard dust was identified as a major contributor to the incidence of asthma associated with paper products. No cases were identified from the paper milling or pulping industry, despite most research studies reporting respiratory disease in that industry. Cardboard dust within manufacturing industries disproportionately contributed to cases of WRA in the state of Michigan, which is not reflected in the medical literature.

The most 'valuable' letter in research: is 'P' over-rated or under-rated?

Currently, prostate calculi are a common disease that is often encountered by urologists in their daily practice. In most cases, urologists do not attach clinical importance to prostate stones, detecting them accidentally during ultrasound examination against the background of pathologies such as prostatic hyperplasia, chronic prostatitis or vesiculitis. Performing surgical intervention in young patients is a complex task, the consequences of which can have a negative impact on the reproductive function of men. In the medical literature, only isolated cases of operations for prostate stones are described. This article presents a clinical case of surgical treatment of a patient who was found to have multiple large calculi of the prostate gland. Keywords: Transurethral laser lithotripsy, prostate stones, benign prostatic hyperplasia, chronic prostatitis.

MicrobExpert: A mixture-of-experts framework for cross-domain knowledge mining of food–microbe–disease associations from biomedical texts

With the exponential growth of biomedical literature, the challenge of conducting systematic reviews is becoming increasingly burdensome. We aimed to evaluate the performance of large language models (LLMs) in the automation of some or all steps of systematic reviews and meta-analyses. In this systematic review, we searched PubMed, Embase, the Cochrane Library and preprint platforms up to January 14, 2025. We included any studies assessing the performance of LLMs (eg, generative pre-trained transformer [GPT], Claude, Mistral) in any step of the systematic review process. Pairs of reviewers independently extracted data and assessed risk of bias. We conducted analyses using median (interquartile range [IQR]) for positive (PPA) and negative percent agreements (NPA), respectively, analogous to sensitivity and specificity, between LLMs and human reviewers. From 3889 unique references, we included 63 studies of which 52 reporting performance metrics for a total of 148 LLM performance assessments. Most assessments concerned GPT models (n = 114, 77%). The most frequently evaluated tasks were title and abstract screening (n = 78, 53%), data extraction (n = 23, 16%), and full-text screening (n = 20, 14%). For title and abstract screening, overall median PPA was 0.92 (IQR 0.69-0.98) and median NPA was 0.89 (0.72-0.95). For full-text screening, the overall median PPA was 0.93 (0.87-1.00) and median NPA was 0.92 (0.78-0.97). Late-generation LLMs released after GPT-4 seemed to provide higher performance than earlier models. For other tasks, authors reported overall good performances, but variability of performance metrics precluded complete quantitative synthesis. Global accuracy for data extraction tasks ranged from 0.36 to 1.00, with a median accuracy of 0.95 (IQR 0.91-0.97, n = 11). For the "risk of bias assessment" task, accuracy ranged from 0.44 to 0.90 (median = 0.62, IQR 0.53-0.76, n = 6). The performance of LLMs, particularly newer generations, shows promise in automating some repetitive steps of systematic reviews such as screening. However, their successful integration will require appropriate safeguards and careful implementation. Systematic reviews are one of the most reliable ways to answer medical and public health questions. They bring together all available studies on a topic and help clinicians and policymakers make informed decisions. However, producing a high-quality systematic review takes a lot of time and effort. Whole teams of researchers spend months screening thousands of articles, extracting data, and double-checking results. With little more than a million of new publications every year, keeping reviews up to date is becoming increasingly difficult. LLMs, such as ChatGPT, may help reduce this workload. These tools can read and summarize text and might assist with repetitive tasks like selecting relevant studies or extracting information from articles. But it is still unclear how reliable these tools are for research purposes. This is the first systematic review to assess LLMs' performance to facilitate systematic reviews. We sought to review all studies that tested LLMs in the different steps of systematic reviews and found 63 studies evaluating how well these tools performed compared with human reviewers. Overall, LLMs showed good agreement with humans for tasks such as screening titles and abstracts, and full-text articles. Newer models seemed to perform better than older ones. However, performance was more variable for complex tasks that require interpretation, such as extracting detailed data or assessing methodological quality. Our findings suggest that LLMs could help researchers work faster and make systematic reviews more efficient. However, they are not ready to replace human judgment. These tools can make mistakes, produce inconsistent results, or generate inaccurate information if not carefully supervised. In practice, LLMs should be used as assistants rather than substitutes. With proper safeguards, transparent reporting, and human oversight, they may become valuable tools to support evidence-based healthcare and help keep research up to date.

Persistent use of black stone for snakebite envenoming in tropical and subtropical Asia and Africa: a literature review.

Around 5%-10% of people with asthma have severe or uncontrolled type of asthma, which is linked to higher hospitalization, higher death rates, higher health care costs, and lower quality of life. Recent years have seen the introduction of novel medications and the identification of multiple asthma phenotypes based on specific biomarkers. The management and treatment of severe asthma have been completely transformed by biologic therapy, which has demonstrated excellent therapeutic efficacy and substantial clinical advantages. In addition to enhancing the quality of life for individuals with severe asthma, biologic therapy significantly reduces exacerbations, hospital visits, and the requirement for continuous systemic steroids. Their therapeutic efficacy is demonstrated by randomized controlled trials (RCTs), extended research, metaanalyses, and real-world data. The development and registration of biologics, new systemic medications for severe asthma are the main topics of this study, which also describes possible future treatment strategies. PubMed, Scopus, and Google Scholar were used to examine the content of recent medical literature. The results of early, important RCTs and later research into biologics for severe types of asthma are summarized in this study. Their safety and effectiveness results, which were obtained in a range of contexts, improved their generalizability and offer useful insights into their use.

ABSTRACT What is “the proven uterus,” a concept ubiquitous in US surrogacy? In this article, I interrogate this concept via content analysis of the medical/academic literature and media, and analysis of ethnographic data on US assisted reproduction. I find the seemingly neutral “proving of the uterus” visible in multiple ways in the medical literature has become a marketing term useful for the surrogacy industry, spawning the “proven surrogate.” These terms are embraced and strategically employed in the industry and by US surrogates themselves to increase their position in contract negotiations and to linguistically encapsulate their value on the market.

The ever-expanding biomedical literature necessitates an efficient and robust mining platform, with the foundational step being a reliable Biomedical Named Entity Recognition (BioNER) system. Existing approaches, such as multi-task and collaborative learning, have attempted to address dataset heterogeneity but often rely on complex architectures with task-specific layers, limiting scalability. A key research gap is the development of a unified model that optimises across multiple datasets without sacrificing performance or introducing architectural complexity. In this study, we propose a novel Loss-Masking Optimisation framework for BioNER models that enables multi-dataset training via a dataset-aware masking strategy. This approach extends the standard BERT-based NER pipeline by introducing a tag-masking array that nullifies logits for tags absent in the originating dataset, thereby reducing cross-dataset interference. Using this methodology, we trained a single BioNER model across all 16 biomedical NER datasets, achieving higher precision and overall F1 scores than conventional multi-dataset training. While some datasets showed performance gains, others stayed near baseline, and a few declined, underscoring the nuanced impact of dataset interactions. To the best of our knowledge, this is among the first studies to apply a dataset-aware loss-masking mechanism to unified multi-dataset BioNER training, offering a scalable alternative to multi-task architectures.

This systematic review and meta-analysis aimed to evaluate risk factors for acute kidney injury (AKI) after surgery for Stanford type A aortic dissection. We searched Web of Science, PubMed, Embase, Proquest, Cochrane Library, China National Knowledge Infrastructure, Wanfang, China Science and Technology Journal Database, and Chinese Biomedical Literature databases from inception to January 2026. A total of 58 case-control studies were included, assessed using the Newcastle-Ottawa Scale. Meta-analysis identified numerous significant perioperative factors. Key demographic and preoperative risk factors included age, body mass index, hypertension history, preoperative renal insufficiency, elevated cystatin C, lactate, serum creatinine, white blood cell count, and renal malperfusion, while a higher left ventricular ejection fraction was protective. Intraoperative factors such as prolonged cardiopulmonary bypass time, increased red blood cell transfusion, and total aortic arch replacement increased AKI risk, whereas higher intraoperative urine output was protective. Postoperatively, prolonged mechanical ventilation and acute respiratory insufficiency were also high-risk factors. In conclusion, multiple preoperative, intraoperative, and postoperative factors significantly influence AKI risk following Stanford type A aortic dissection surgery. Comprehensive perioperative assessment of these factors may help clinicians implement targeted management to reduce AKI incidence and improve patient outcomes.

This study aims to integrate the experiences of surrogate decision-making by family members of patients with acute stroke and to understand their feelings and needs. A qualitative meta-synthesis was conducted to extract and analyse qualitative research from PubMed, Web of Science, Embase, Cochrane, CINAHL, and Chinese databases, including China National Knowledge Internet, Wanfang Database, Chinese Biomedical Literature Database (Sinomed), and VIP database from the inception of the database to 6 November 2025. This review was conducted in accordance with the Joanna Briggs Institute (JBI) Manual for Systematic Reviews of Qualitative Evidence. Two reviewers independently performed study screening and data extraction processes. The quality of included studies was assessed using the JBI critical appraisal tool for qualitative research. For data analysis, the thematic synthesis approach proposed by Thomas and Harden was adopted. The nine included studies were synthesized into three themes and eight subthemes. The three themes were dilemmas and challenges of the surrogate decision-making process, core basis for family surrogate decision-making, and factors influencing family members' surrogate decision-making. Family members of acute stroke patients face multiple dilemmas and challenges in surrogate decision-making, necessitating scientific interventions to support decision-making. Healthcare providers should proactively strive to alleviate the decision-making burden on family members, ultimately safeguarding both the patient's optimal treatment outcomes and the family's physical and mental well-being. A protocol was registered on the PROSPERO (CRD420251182588).

BackgroundNeck pain poses a significant and growing public health challenge, with rising prevalence among younger populations and negative impacts on both quality of life and socioeconomic costs. Clinical manifestations are diverse, including restricted movement, muscle spasms, headaches, and upper limb numbness. Although drug therapy is widely used, its long-term use is limited by adverse effects. Traditional Chinese medicine (TCM) exercises offer a promising alternative, but high-quality evidence directly comparing their efficacy and safety to oral medications is currently lacking.ObjectiveThis study aims to compare the efficacy and safety of TCM exercises and oral medication in treating neck pain.MethodsWe will identify relevant randomized controlled trials (RCTs) through a systematic search of multiple databases (including PubMed, Embase, Cochrane Library, Web of Science, China National Knowledge Infrastructure [CNKI], Chinese Biomedical Literature Database [CBM], VIP, and Wanfang) from inception through September 2025. Only RCTs directly comparing TCM exercise to oral medication will be included. Study quality will be assessed using the Cochrane RoB2 tool, and the overall evidence will be graded via the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. For heterogeneity, the I² statistic and Cochran Q test will be applied. A fixed-effect model will be adopted if I²<50% and P≥.10; otherwise, subgroup analysis will be performed. Should heterogeneity persist, sensitivity analysis or a random-effects model will be employed, leading to a reduction in the GRADE rating.ResultsThis is a study protocol; therefore, no results are available at this stage. The systematic review is scheduled to commence in August 2025, with the literature search from August to September 2025, study screening from September to December 2025, data extraction and analysis from January to May 2026, and manuscript submission by June 2026.ConclusionsThis protocol outlines a systematic review and meta-analysis designed to compare the efficacy and safety of TCM exercises versus oral medications for neck pain. The completed review aims to synthesize the available evidence and clarify whether TCM exercises offer a comparable or superior alternative to pharmacotherapy. By systematically evaluating direct head-to-head RCTs, this study seeks to provide evidence-based insights to inform clinical decision-making. Potential limitations of the forthcoming review may include heterogeneity in exercise protocols, challenges in blinding, and a possible limited number or geographic concentration of available trials, which could affect the generalizability of the findings. These limitations will be considered when interpreting the results.

Chronic low back pain (CLBP) is common and often managed within multimodal, nonpharmacologic pathways. Clarifying sham-controlled effects of osteopathic manipulative treatment (OMT) can guide early clinical decisions. This study aims to estimate the short-term (≤6weeks) effects of OMT for CLBP, emphasizing sham-controlled comparisons. We preregistered a systematic review and meta-analysis (PROSPERO [Prospective Register of Systematic Reviews] CRD420251154852) and followed PRISMA 2020 (Preferred Reporting Items for Systematic reviews and Meta-Analyses 2020). Randomized trials enrolling adults with CLBP compared OMT with sham/attenuated OMT, usual care, or wait-list. The co-primary outcomes were pain (0-10; mean difference [MD]) and function (Oswestry Disability Index [ODI] or Roland-Morris Disability Questionnaire [RMDQ]; standardized mean difference [SMD]). Analyses were prespecified at end-of-treatment (≤6weeks); the single crossover trial contributed pre-crossover data only. Searches covered MEDLINE (Medical Literature Analysis and Retrieval System Online), Embase (EMBASE [Excerpta Medica dataBASE]), CENTRAL (Cochrane Central Register of Controlled Trials), CINAHL (Cumulative Index of Nursing and Allied Health), and ClinicalTrials.gov through October 2025. Random-effects models (DerSimonian-Laird with Hartung-Knapp) summarized effects with I2 and prediction intervals (PIs); risk of bias (RoB 2) and certainty (GRADE [Grading of Recommendations, Assessment, Development, and Evaluation]) were assessed. Seven trials (n≈378) met the inclusion criteria. Across five trials, OMT reduced pain vs. comparators: MD-1.32 on 0-10 scales (95 % confidence interval [CI],-1.71 to-0.93; I2=6 %; 95 % PI,-2.05 to-0.59). In sham-controlled analyses of function limited to ODI/RMDQ (k=2), OMT improved disability: SMD 1.75 (95 % CI, 1.37 to 2.13; I2=0 %). Adverse events were infrequently reported; where monitored, no serious adverse events were attributed to OMT. Certainty by GRADE was moderate for short-term pain and for sham-controlled function. At≤6weeks, OMT reduces pain and improves function vs. sham without observed serious harms, supporting its use as a low-risk adjunct within guideline-concordant, nonopioid CLBPcare.

While deep learning models have achieved remarkable diagnostic accuracy in medical imaging, their inherent "black box" nature severely impedes clinical adoption due to a lack of transparency and trust. Current eXplainable AI (XAI) methods, such as saliency maps, offer low-level feature attribution but fail to provide clinically meaningful reasoning. State-of-the-art vision-language models trained end-to-end on image-report pairs often learn to exploit superficial correlations from noisy data, generating plausible but clinically vacuous explanations. To address this critical gap, we propose K-Distill-XAI, a novel teacher-student framework that decouples visual feature learning from high-level clinical reasoning. We first train a domain-expert "teacher" Large Language Model (LLM) on a vast corpus of biomedical literature to generate canonical, text-based clinical rationales. Subsequently, we train a multimodal "student" vision-language model using a cross-modal knowledge distillation objective, compelling it to generate explanations that are semantically aligned with the teacher's expert reasoning. Extensive experiments on the public MIMIC-CXR dataset demonstrate the superiority of our approach. K-Distill-XAI significantly outperforms state-of-the-art baselines in clinical accuracy, achieving an 8% relative improvement in CheXbert F1 score for report generation. Furthermore, this distillation process also boosts classification performance and yields state-of-the-art micro-averaged AUC across 14 clinical conditions.

Network meta-analysis of the effect of different nursing management models on the intra-hospital transport of critically ill patients in the emergency department.

IntroductionAs of 2024, paid paternity leave was available in 102 countries worldwide. However, the accessibility and methods of taking paternity leave are influenced by cultural background and individual values, leading to variations in uptake rate. Both positive and negative effects of paternity leave have been reported on the health of fathers, partners and children. A comprehensive understanding of this topic is essential for medical professionals supporting fathers undertaking childcare. The aim of this review is to identify and provide an overview of research related to the impact of paternity leave on the health of fathers, their partners and their children.Methods and analysisPubMed, CINAHL, Web of Science and Ichushi-Web (Japan’s medical literature database) will be searched for published studies, and Google Scholar, ProQuest and CiNii Research (a database used to search for academic information in Japan) will be searched for grey literature. Screening will be performed by two independent reviewers. In this scoping review, we will include studies that focus on fathers taking paternity leave, their partners and their children, regardless of ethnicity or geographic location. This review will focus only on studies related to effects within 3 years after childbirth. We will not restrict study inclusion by whether paternity leave is paid or unpaid, the length of the leave or whether it was taken solely by the father. Furthermore, we will include both English and Japanese literature. The findings of this scoping review will be presented in tabular form and summarised in a way that aligns with the review questions.Ethics and disseminationThis paper does not involve human participants, so approval by an ethics committee is not required. The results of this scoping review will be presented in academic conferences and disseminated in peer-reviewed journals.Registrationhttps://osf.io/jsc89.

The present investigation is geared towards an in-depth examination of the clinical characteristics, therapeutic approaches, and pertinent considerations associated with traumatic pericallosal artery aneurysms in children. A retrospective analysis was conducted on the diagnosis and treatment process of a case of pediatric traumatic pericallosal artery aneurysm resulting from pediatric traumatic brain injury, complemented by a comprehensive review of the relevant medical literature. The patient presented with an acute epidural hematoma and cerebral herniation, necessitating the execution of epidural hematoma evacuation and decompressive craniectomy with the removal of the bone flap. The initial computed tomography angiography (CTA) did not reveal any intracranial aneurysms. However, 19 days following the surgical intervention, the patient experienced sudden coma and cerebral herniation, requiring reoperation. Postoperative digital subtraction angiography (DSA) confirmed the presence of a traumatic pericallosal artery aneurysm, which was managed through intracranial aneurysm embolization, culminating in an unfavorable prognosis. Pediatric traumatic pericallosal artery aneurysms are frequently nonspecific in clinical and radiologic manifestations, leading to the potential for missed diagnoses and severe consequences. For patients under suspicion of harboring such aneurysms, early DSA confirmation is essential. In instances of negative preliminary findings, a repeat DSA may be deemed necessary to exclude delayed-onset aneurysms. Upon diagnosis, prompt surgical or endovascular intervention is warranted.

ABSTRACT Medical hospitality is being transformed by digitalisation, raising cybersecurity concerns. This paper analyzes how digital innovation capabilities affect guest satisfaction, with perceived ease of use and usefulness as mediator factors. This paper also explores the moderating effect of cybersecurity risk. Data was gathered from 638 guests who interacted with digital medical hospitality services. Findings confirmed that digital innovation capabilities positively affected perceived ease of use and usefulness, shaping guest satisfaction. Nonetheless, cybersecurity risk dampened the positive effects of technology perceptions on guest satisfaction. Results underline the two-sided character of digital innovation as a value-generating and a risk-generating process. This paper provides valuable insights for the medical hospitality literature by combining digital innovation and cybersecurity approaches.

Systemic racism has resulted in ongoing health disparities disproportionately affecting Black/Latinx patients. The use of race in medical literature can reinforce ideas of racially distinct mechanisms of illness and lead to differential treatment based on race classifications, further exacerbating inequities. This study used an innovative debate-style curriculum to teach residents how to critically examine race in medical literature using an asthma clinical trial. Ambulatory curriculum. One hundred twenty-four internal medicine residents. A 90-min educational session included a brief article overview followed by a debate. Residents were assigned to an affirmative or opposing team to debate if studying only Black/Latinx patients in the trial was justified. The session concluded by reviewing how racism contributes to health disparities and clinical trial inequities with strategies to address these issues. Pre/post-surveys assessed comfort discussing race, appraisal of race in medical literature, and perceived importance of SDOH in research. The debate-based session enhanced residents' comfort discussing race, promoted critical thinking and perspective-taking, and equipped them with tools to appraise race-consciousness in medical literature and clinical practice.

BackgroundLeptospirosis is a globally distributed zoonotic disease with a broad clinical spectrum. Central nervous system (CNS) involvement is uncommon and under-recognized, and leptospiral-associated meningitis (LAM) is primarily described in isolated case reports and small series. No study to date has integrated institutional cases with published reports to characterize cerebrospinal fluid (CSF) profiles in LAM.MethodsWe conducted a retrospective cohort study of patients with meningitis, encephalitis, or meningoencephalitis admitted to a tertiary infectious diseases center in northeastern Brazil. Cases of LAM were identified among patients with aseptic meningitis. In parallel, a narrative literature review was performed, and a meta-summary of published cases was constructed. CSF parameters from both datasets were extracted and analyzed using descriptive statistics and graphical (boxplot) methods.ResultsAmong 809 patients with meningitis or encephalitis, 447 presented with aseptic meningitis. Three cases (0.67%) of LAM were identified, presenting as isolated meningitis or meningoencephalitis. Among 179 patients, including 176 identified in the medical literature, mean CSF values were: cellularity 68 cells/mm3 (range, 30–7800), lymphocytes 73% (0–100), neutrophils 18% (0–96), glucose 60 mg/dL (0–140), and protein 67–90 mg/dL (31–2590). CSF findings in the institutional cohort showed mild to moderate pleocytosis with lymphocytic predominance, normal to elevated glucose levels, and increased protein concentrations. The integrated analysis of cohort and published cases—the first combined CSF profile synthesis of LAM—demonstrated a consistent pattern of lymphocytic pleocytosis, mildly elevated cellularity, preserved glucose levels, and increased protein, with substantial inter-case variability.ConclusionLAM is an uncommon but clinically relevant cause of CNS infection in endemic settings. This study provides the first integrated synthesis of CSF profiles from both institutional cases and published literature, supporting a characteristic but variable CSF pattern in leptospiral CNS disease. Clinicians should consider leptospirosis in patients with aseptic meningitis in endemic areas, particularly when epidemiological risk factors are present. Improved diagnostic capacity and prospective studies using standardized criteria are needed to better define disease burden and refine diagnostic and therapeutic approaches.