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Multiple sclerosis (MS) is an autoimmune disease that affects the central nervous system. MS impacts above 2.3 million people. The first treatments for the disease were mainly immunomodulatory drugs, which addressed the symptoms rather than the disease itself. In recent years, stem cell-based therapies have emerged as a promising approach, offering potential regenerative and immunoregulatory benefits. Among these, mesenchymal stem cells (MSCs) have attracted significant attention due to their ease of isolation from various tissues, their capacity for both autologous and allogeneic use, and their ability to release key soluble factors that simultaneously modulate immune responses and promote neural repair. This review provides an updated overview of the therapeutic potential of MSCs in MS, summarizing key experimental and clinical studies that explore their mechanisms of action, efficacy, and safety profiles across different tissue sources. We also highlight current challenges in translating MSC-based therapies from bench to bedside, including inconsistent engraftment rates, dosing heterogeneity, and the inherent limitations of autologous approaches. Moreover, we discuss future perspectives and emerging therapeutic strategies, emphasizing their role as a promising frontier in personalized regenerative medicine for MS.

Wound healing is a complicated biological process primarily involving tissue regeneration and repair. However, conditions such as infection, poor blood circulation, or long-term illnesses/chronic diseases (like diabetes) can impede the healing process and cause delayed recovery. In order to address these challenges, authors developed wafers. The prepared wafers have emerged as a promising solution due to their ease of application, excellent biocompatibility, and ability to maintain a moist wound environment. These porous, sponge-like systems can also be loaded with bioactive agents, enabling sustained and controlled drug delivery. The wafer was fabricated using solvent casting method with polymeric mixture of hydroxypropyl methyl cellulose (HPMC), ethyl cellulose (EC), and polyvinyl pyrrolidone (PVP K-30) and loaded with curcumin to promote wound healing. The loaded curcumin was dispersed using a high-speed homogeniser and lyophilized in a controlled environment. The developed wafer formulation was further characterised using scanning electron microscopy (SEM), thermogravimetry-differential thermal analysis (TG-DTA), Fourier transform infrared spectroscopy (FTIR), X-ray diffraction analysis (XRD), tensile strength analysis, swelling index, and water vapour transmission rate. The in vitro drug release study was carried out mimicking USP 5 paddle-over-disc type dissolution apparatus and the results indicated that the created wafers have a sustained drug release while keeping the tissue moist. The anti-microbial potential of wafers was confirmed using the disc diffusion method. The developed wafer showed strong potential as an antibacterial wound dressing, providing controlled drug release along with fast-acting relief from bacterial infections.

The determinants of the species barrier preventing human infections with avian influenza A viruses (IAV) are incompletely understood. We previously identified loss-of-function variants of the interferon-regulated antiviral factor MxA as a genetic factor for increased susceptibility to infections with the H7N9 subtype. Given the central role of type I IFNs (IFN-I) in antiviral defence, we hypothesised that IFN-I-neutralising autoantibodies may similarly predispose to zoonotic H7N9 infection. In this observational case-control study, serum samples collected between 2013 and 2017 from 199 Chinese patients with laboratory-confirmed H7N9 infection and 531 healthy, uninfected controls (269 poultry workers, 262 close contacts) were screened for IgG autoantibodies binding IFN&#x3b1;2, IFN&#x3b2;1b, or IFN&#x3c9; using a multiplex bead-based assay. Positive samples were tested for IFN-neutralising activity in a luciferase-based reporter assay. To confirm their ability to block IFN&#x3b1;2-mediated antiviral activity, selected samples (n = 19) were analysed in IAV infection experiments. Associations between age, sex, H7N9 case status, case fatality, and the presence of neutralising autoantibodies were evaluated by logistic regression. Available whole-genome sequencing data from 26 individuals with neutralising autoantibodies were screened for variants in genes linked to IFN-I autoimmunity. Neutralising autoantibodies against at least one IFN-I were detected in 19.1% (38/199) of patients but in only 1.1% (6/531) of controls, consistent with published general population data. Most patient sera targeted IFN&#x3b1;2 and/or IFN&#x3c9; (35/199), and 18.1% (36/199) neutralised even high IFN-I concentrations of 1-10 ng/ml. The presence of neutralising autoantibodies was associated with 8.2- to 25.3-fold higher odds of H7N9 infection (p < 0.0001), depending on antibody specificity and reference group. Autoantibody prevalence increased significantly with age in patients (44.8% &#x2265;70 years; OR = 1.05; 95% CI 1.02-1.07; p = 0.0001), but was not associated with sex (OR for males vs. females = 0.52; 95% CI 0.23-1.14; p = 0.106). All selected sera containing neutralising autoantibodies blocked IFN&#x3b1;2-induced antiviral activity in cell culture. No known genetic predisposition for IFN-I autoimmunity was identified. Our findings suggest that IFN-I-targeting autoimmunity is associated with susceptibility to zoonotic IAV infection with the H7N9 subtype, and possibly also other subtypes, including panzootic H5N1. Given the ease of implementation, screening for anti-IFN-I autoantibodies could be readily integrated into surveillance or targeted testing. This could be relevant in environments with increased exposure to zoonotic IAVs. Shenzhen Medical Research Fund, National Natural Science Foundation of China, Non-profit Central Research Institute Fund of Chinese Academy of Medical Sciences, Guangdong Provincial Science and Technology Program, Program for Youzuzhikeyan of Shenzhen University, German Research Foundation, Swiss National Science Foundation.

An estimated 390 million dengue virus (DENV) infections occur per year, 70% in the Western Pacific and Southeast Asia. A prototype rapid diagnostic test (RDT) (NS1, immunoglobulin M [IgM]/immunoglobulin G [IgG]; DengueDx, Mologic) was evaluated for accuracy and ease of use for dengue diagnosis at Mahosot Hospital, Vientiane, Lao People's Democratic Republic. Five hundred twenty-six sera collected in 2017 and 2018 from patients hospitalized with suspected dengue were included. Prototype RDT results were compared to NS1 and IgM enzyme-linked immunosorbent assays and/or real-time reverse-transcription polymerase chain reaction as reference assays and to Bioline dengue RDT (NS1, IgM/IgG) as comparator. The accuracy of the image-based result interpretation (RDT scan or photograph) at day 0 and after a delay of 7 days was evaluated. Five technicians were observed when performing RDTs and interviewed on their perception of the ease of use. The overall sensitivity and the sensitivity for NS1 detection alone were significantly lower for the prototype RDT (65.2% [95% confidence interval {CI}, 59.3%-70.8%] and 44.6% [95% CI, 38.0%-51.4%], respectively) than for the Bioline RDT (76.7% [95% CI, 69.1%-83.2%], z-test P = .014; and 66.7% [95% CI, 57.5%-75.0%], z-test P < .001, respectively). The positive predictive value of the prototype RDT for detection of NS1 was >90%. Only half of the positive results were found positive when reading results from images. Correlation of >98% for positive results was obtained between reading at day 0 and reading at day 7. During ease of use assessment, when performing the Bioline RDTs the participants made fewer errors and were more satisfied than when performing the prototype RDTs. Improvement in test sensitivity and in device design would adapt the prototype RDT for Laos and similar contexts. Optimization of the prototype RDT is warranted and further evaluation in different healthcare settings would provide a more accurate estimation of the value of this RDT for dengue surveillance in remote areas.

Extractable nuclear antigen (ENA) antibody testing is universal to the diagnosis of systemic autoimmune rheumatic diseases (SARDs). However, current commercial multiplex platforms require expensive instruments and are often cost-prohibitive for routine testing in low- and middle-income settings. Pictor PictHealth&#xae; Immunoscreen ENA assay was developed as an affordable, scalable alternative for the simultaneous detection of ENA antibodies. The assay performance was compared with the Euroimmun ENA Line immunoassay and BioPlex 2200 ENA assays using clinical sera from patients with autoimmune diseases. Concordance among assays was evaluated using three-way and pairwise analyses, expressed as positive percent agreement (PPA), negative percent agreement (NPA), and overall concordance. Analytical precision was assessed within and between manufacturing lots. The Pictor multiplex assay showed high concordance with established commercial platforms. Three-way agreement across all assays ranged from 67.3% for TRIM21/Ro52 to 100% for Jo-1, with Sm, CENP-B showing concordance of 95%. Pairwise comparisons demonstrated PPA and NPA values exceeding 85% for most autoantibodies. The Pictor PictHealth&#xae; Immunoscreen ENA assay provides diagnostic performance comparable to the Euroimmun and BioPlex platforms while maintaining the ease of implementation and scalability of a traditional ELISA format. These results support its potential as a cost-effective and accessible tool for ENA antibody testing in laboratories with varying resource levels.

Completion of homework, defined as therapeutic activities assigned between sessions to reinforce skills and promote behavior change, is strongly linked to therapy outcomes. Yet, homework compliance remains low, potentially due to outdated delivery methods such as paper or email. Mobile health technologies may improve engagement by digitizing therapy tasks and tracking progress. Yosa is a mobile health app designed to facilitate homework delivery and enhance engagement between sessions for patients in therapy. The primary aim of this study was to evaluate the perceived acceptability of Yosa among licensed therapists and individuals currently receiving therapy. A secondary aim was to examine whether key Technology Acceptance Model (TAM) constructs predicted attitudes toward and intention to use Yosa. Qualitative feedback was also collected to inform iterative development and future deployment. Two cross-sectional surveys were conducted: study 1 with licensed therapists (N=45) and study 2 with current therapy patients (N=96). Participants viewed video demonstrations of Yosa, learned about Yosa's features, and rated the app on TAM constructs, including perceived usefulness, perceived ease of use, perceived risk, attitude toward, and intention to use Yosa, using 0-100 scales. For most constructs, higher scores reflected more favorable evaluations, whereas lower perceived risk scores reflected more favorable evaluations. Descriptive statistics and 95% CIs were generated for each construct in both samples, with scores interpreted relative to the neutral midpoint (50). Multiple regression analyses were conducted to examine predictors of attitude and intention to use. Qualitative feedback from the surveys was analyzed thematically. Therapists and patients reported generally favorable perceptions of Yosa across TAM domains. Among therapists and patients, ratings of the perceived usefulness of the homework feature, therapy journal, and overall app; perceived ease of use; attitudes toward Yosa; and intention to use were all above the midpoint. Perceived risk scores were mild to moderate in patients and moderate in therapists, respectively. Regression analyses indicated that perceived usefulness was a positive predictor of both attitude toward and intention to use Yosa across therapists and patients, while perceived risk was negatively associated with these outcomes in several models. Qualitative themes included requests for additional features, usability enhancements, and data privacy concerns. Therapists and patients reported generally favorable perceptions of Yosa after reviewing descriptions and video demonstrations of the platform, particularly in terms of usefulness and ease of use, supporting favorable perceptions of its potential acceptability as a digital tool for between-session therapy support. Qualitative feedback informed refinements aimed at reducing perceived risks and enhancing the intention to use.

This study aimed to explore older adults' experiences of using smart devices and mHealth apps for proactive health and identify the key factors affecting their adoption and sustained engagement. The current study utilized descriptive qualitative research methodology, adopting the Technology Acceptance Model (TAM) as the theoretical framework. Purposive sampling was used to recruit older adults from a tertiary Grade A general hospital in Hangzhou. Data were collected through semi-structured interviews and analyzed using directed content analysis. A total of 20 older adults in Hangzhou were interviewed for the study. Analyses yielded two themes and eight sub-themes: perceived usefulness (enhanced health awareness and self-efficacy, real-time health data monitoring and early warning, accuracy and reliability of information and convenient communication with medical professionals), and perceived ease of use (interface simplicity and operability, learning cost and learning support, privacy concerns and information security, and technical support and experience sharing). This descriptive qualitative study explores older adults' experiences of using smart devices and mHealth apps for proactive health, highlighting that perceived usefulness and ease of use are key determinants of their technology adoption and sustained engagement. Future digital health tool development should align with research on older adults' user experiences to ensure these technologies' universality and applicability.

Smart home technologies are often promoted as a means to support independent living and alleviate pressure on health and care systems. However, adoption among older adults remains low, and little is known about how passive, ambient technologies are experienced over time. This study aimed to examine the adoption of a Connected Care System among older adults and their caregivers in a real-world deployment, testing the applicability of the Unified Theory of Acceptance and Use of Technology model and identifying design considerations for future systems. A mixed methods study was conducted with 91 older adults who used the Connected Care System for approximately 6 months. Quantitative survey data were analyzed using structural equation modeling to assess predictors of behavior intention. Thematic analysis of open-ended survey responses was used to explore participants' experiences and perceptions of the system. Perceived ease of use (&#x3b2;=0.075; P=.02) and facilitating conditions (&#x3b2;=0.232; P<.001) were significant predictors of behavior intention, while perceived usefulness and social influence were not. Thematic analysis revealed that older adults often conceptualized usefulness in emotional and relational terms, such as peace of mind and caregiver reassurance. Adoption was frequently described as a shared process involving family members. Key barriers included low confidence in setup and reliability concerns, while valued features included passive monitoring, increased independence, and reduced caregiver burden. The findings suggest that conventional adoption models require adaptation to account for passive, caregiver-mediated smart home systems. Emotional and relational benefits, rather than task efficiency, drive perceived usefulness. Design recommendations are offered to support user-friendly, personalized, and relationally aware smart home technologies that align with the realities of aging in place.

Italy currently ranks among the world's oldest nations, with adults aged &#x2265;65 years accounting for 24.1% of the population - the highest proportion in the EU - and a projected median age of 51 years by 2050. While life expectancy at birth reaches 85.4 years for women and 81.4 for men, Healthy Life Years amount to only 69.6 and 68.5, respectively, documenting a substantial lifespan-healthspan divide. The prevalence of multimorbidity and disability exceeds 60% in adults aged &#x2265;75 years; women bear a disproportionate share of this burden, both as patients and as caregivers. Meanwhile, the Italian National Health Service (Servizio Sanitario Nazionale, SSN) remains hospital-centric, regionally fragmented, and predominantly reactive, with prevention accounting for a historically modest share of total expenditure. Against this background, longevity medicine is an emerging, prevention-oriented discipline that aims to extend healthspan - defined here as the portion of life lived in good health, with preserved physical and cognitive function and without significant disability or multimorbidity. It integrates multi-omic biomarkers, digital monitoring, adaptive trial methodology, and life-course risk stratification within a translational framework. Although most constituent tools remain at an exploratory or surrogate stage, and clinical utility has yet to be established, the emphasis on early intervention and precision prevention offers potential to reduce the accumulation of age-related disease and ease long-term pressure on the SSN. This position paper analyzes Italy's demographic and epidemiological trajectory, examines the structural constraints of the SSN, and outlines the scientific foundations of longevity medicine. It advocates for multidisciplinary translational research and identifies five strategic investment priorities: (i) clinically validated biomarkers of biological age; (ii) interoperable digital monitoring platforms; (iii) Bayesian adaptive multimodal trials; (iv) explainable-AI risk stratification tools; and (v) longevity-informed curricula in medical training. These proposals should be regarded as a staged agenda for evaluation; their relevance will depend on whether they deliver measurable gains in patient-relevant outcomes, feasibility, and cost-effectiveness within the SSN.

Patients with cancer need to make complex treatment decisions that weigh benefit, risk, and increasingly, treatment costs. Although patients desire to have information about out-of-pocket (OOP) spending to help inform such decisions, individualized OOP cost information is rarely discussed in clinical practice and often difficult for patients to access. FinCare, an online tool for generating patient-specific OOP cost estimates, was developed to address this gap. This pilot study evaluated the feasibility and acceptability of FinCare among patients receiving cancer therapy. Patients (n=10) beginning a new cancer therapy regimen were recruited to provide feedback and input. Participants' treatment and insurance information were entered into FinCare to generate individualized OOP cost estimates. After reviewing the report, participants rated its usefulness and their satisfaction with this online tool. Secondary outcomes of financial toxicity and anxiety were also assessed. FinCare successfully generated individualized monthly OOP estimates for all participants (range: $0-$2172.34/month). Acceptability was high, with 80%-90% endorsing its ease of use and high satisfaction with the information received. Qualitative comments indicated that participants found the information to be clear and helpful for planning. Receipt of individualized cost information did not result in significant changes in financial toxicity or anxiety. FinCare was feasible to implement and acceptable to patients starting a new cancer regimen. Receipt of individualized OOP cost estimates was reported to be useful and did not increase participant anxiety. Study findings, however, are limited by the small sample of patients from a single insurer and a single academic institution. Future studies comprised of larger, more diverse patient populations from multiple insurer groups and centers are warranted to demonstrate the broader feasibility and utility of this tool.

Small bronchoscopic biopsy specimens may be insufficient for molecular testing. Cytology preserves nucleic-acid quality but can be discordant with tissue-based malignant findings. We developed negative-pressure pumping fluid (NPPF), a cytological specimen generated from tissue by negative-pressure cycles, to enrich tissue-derived malignant cells. Patients undergoing bronchoscopy for suspected non-small cell lung cancer were prospectively enrolled. Biopsy tissue, bronchial lavage fluid (BLF), and NPPF were collected. Malignant cell detection was compared across specimens, and agreement with tissue was assessed by concordance rates and Cohen's &#x3ba;. Cytological quality was scored across five domains. In predefined subsets, nucleic-acid yields were compared before and after pumping, and mutation profiling using the MINtS assay was performed on NPPF and BLF when either specimen was cytology-positive. Ninety-nine patients were analysed. Concordance with tissue for malignant cell detection was higher for NPPF than for BLF (90.9% vs 71.7%; &#x3ba;&#xa0;=&#xa0;0.75 vs 0.35). The combined BLF/NPPF result, defined as positive when either specimen was positive, closely matched the conventional combined tissue/BLF result (94.9%; &#x3ba;&#xa0;=&#xa0;0.81). NPPF scored higher than BLF for minimal cell overlapping, background cleanliness, staining quality, and ease of focusing, whereas BLF showed more uniform cell distribution (all p&#xa0;<&#xa0;0.001). Negative-pressure pumping increased nucleic-acid yields. In 33 cytology-positive cases, MINtS profiles were concordant between BLF and NPPF samples. NPPF improved cytological quality and nucleic-acid recovery while preserving biopsy tissue. Its molecular utility requires validation, including direct tissue-NPPF comparison and cytology-negative cases.

After-discharge instructions often fail due to poor usability and language misalignment. We evaluated a clinician-supervised method for generating instructions for common emergency department presentations using a clinician-supervised method using large language models. Eight common ED presentations were identified via a physician needs assessment. After-discharge instructions were generated using three publicly accessible large language models (ChatGPT&#x2011;4.0, Claude&#x2011;3.5 Haiku, and Gemini&#x2011;2.0 Flash Thinking) and iteratively refined by expert physicians. After-discharge instructions were assessed for clinical accuracy, completeness, readability (Flesch Reading Ease scale), semantic similarity, and understandability. This analysis was repeated after the inclusion of reviewer edits. Five AI-simulated personas based on local marginalised patient profiles were used to identify comprehension barriers. We applied Bag&#x2011;of&#x2011;Words and BioClinical&#x202f;BERT similarity metrics to objectively quantify the semantic and contextual consistency of LLM outputs beyond what readability scores alone capture. All large language models produced clinically accurate instructions. Physician edits improved accuracy but paradoxically reduced objective readability scores. Whilst Claude was preferred for simpler language after revisions, persona reviews revealed persistent medical jargon and vague instructions that could hinder understanding for marginalised groups. Large language models with expert clinician supervision can create clinically accurate after-discharge instructions. However, clinician-led refinements decreased readability, increasing the risk of poorer post-visit patient understanding. AI-simulated personas may offer a scalable method to surface potential comprehension barriers in patient instructions, but must be followed by validation with real patients. R&#xe9;SUM&#xe9;: OBJECTIF: Les instructions apr&#xe8;s d&#xe9;chargement &#xe9;chouent souvent en raison d&#x2019;une mauvaise utilisation et d&#x2019;un mauvais alignement linguistique. Nous avons &#xe9;valu&#xe9; une m&#xe9;thode supervis&#xe9;e par un clinicien pour g&#xe9;n&#xe9;rer des instructions pour les pr&#xe9;sentations courantes aux services d&#x2019;urgence &#xe0; l&#x2019;aide d&#x2019;une m&#xe9;thode supervis&#xe9;e par un clinicien utilisant de grands mod&#xe8;les de langage. M&#xe9;THODES: Huit pr&#xe9;sentations courantes de TCA ont &#xe9;t&#xe9; identifi&#xe9;es par une &#xe9;valuation des besoins des m&#xe9;decins. Les instructions apr&#xe8;s la sortie ont &#xe9;t&#xe9; g&#xe9;n&#xe9;r&#xe9;es &#xe0; l&#x2019;aide de trois grands mod&#xe8;les de langage accessibles au public (ChatGPT&#x2010;4.0, Claude&#x2010;3.5 Haiku et Gemini&#x2010;2.0 Flash Thinking) et affin&#xe9;es de mani&#xe8;re it&#xe9;rative par des m&#xe9;decins experts. Les instructions apr&#xe8;s la sortie ont &#xe9;t&#xe9; &#xe9;valu&#xe9;es pour leur pr&#xe9;cision clinique, leur exhaustivit&#xe9;, leur lisibilit&#xe9; (&#xe9;chelle de facilit&#xe9; de lecture Flesch), leur similarit&#xe9; s&#xe9;mantique et leur compr&#xe9;hensibilit&#xe9;. Cette analyse a &#xe9;t&#xe9; r&#xe9;p&#xe9;t&#xe9;e apr&#xe8;s l&#x2019;inclusion des modifications du r&#xe9;viseur. Cinq personnes simul&#xe9;es par l&#x2019;IA, bas&#xe9;es sur des profils locaux de patients marginalis&#xe9;s, ont &#xe9;t&#xe9; utilis&#xe9;es pour identifier les obstacles &#xe0; la compr&#xe9;hension. Nous avons appliqu&#xe9; les m&#xe9;triques de similarit&#xe9; BERT Bag of&#x2010;Words et BioClinical pour quantifier objectivement la coh&#xe9;rence s&#xe9;mantique et contextuelle des r&#xe9;sultats LLM au-del&#xe0; de ce que les scores de lisibilit&#xe9; &#xe0; eux seuls capturent. R&#xe9;SULTATS: Tous les grands mod&#xe8;les de langue ont produit des instructions cliniquement pr&#xe9;cises. Le m&#xe9;decin am&#xe9;liore la pr&#xe9;cision mais paradoxalement r&#xe9;duit les scores de lisibilit&#xe9; objective. Bien que Claude ait &#xe9;t&#xe9; pr&#xe9;f&#xe9;r&#xe9; pour un langage plus simple apr&#xe8;s les r&#xe9;visions, les revues de personnes ont r&#xe9;v&#xe9;l&#xe9; un jargon m&#xe9;dical persistant et des instructions vagues qui pourraient entraver la compr&#xe9;hension pour les groupes marginalis&#xe9;s. CONCLUSIONS: Des mod&#xe8;les &#xe0; large langage supervis&#xe9;s par des cliniciens experts peuvent cr&#xe9;er des instructions cliniquement pr&#xe9;cises apr&#xe8;s la sortie. Cependant, les am&#xe9;liorations apport&#xe9;es par les cliniciens ont r&#xe9;duit la lisibilit&#xe9;, augmentant ainsi le risque d&#x2019;une mauvaise compr&#xe9;hension du patient apr&#xe8;s la visite. Les personnes simul&#xe9;es par l&#x2019;IA peuvent offrir une m&#xe9;thode &#xe9;volutive pour mettre en &#xe9;vidence les obstacles potentiels &#xe0; la compr&#xe9;hension dans les instructions des patients, mais doivent &#xea;tre suivies d&#x2019;une validation avec de vrais patients.

Generative artificial intelligence (generative AI) has been investigated for creating patient education materials (PEMs) to reduce the burden of clinical education and improve health information accessibility. However, prior studies have highlighted limitations in readability, content stability, source transparency, and generation quality. The release of ChatGPT-5.4 provides an opportunity to evaluate the inter-generation stability and usability of a newer frontier model. This study evaluates ChatGPT-5.4's performance in producing PEMs for spinal surgery. On 5 March 2026, ChatGPT-5.4 was used to address common patient questions about three prevalent spinal surgeries: lumbar disc herniation surgery, spinal fusion surgery, and spinal decompression surgery. Each question generated five independent responses. Qualitative analysis evaluated language sophistication, information depth, structural clarity, and supplementary content. Readability was measured using the Flesch-Kincaid Reading Ease (FKRE), Flesch-Kincaid Grade Level (FKGL), and Simple Measure of Gobbledygook (SMOG). Quality was assessed by two independent reviewers using the DISCERN tool, with the Intraclass Correlation Coefficient (ICC) calculated. Core medical information remained consistent across generated versions for all three question types, although variations occurred in tone, organization, and detail presentation. The average FKRE ranged from 43.02 to 57.16 ("difficult" to "standard English"), FKGL from 9.12 to 13.34, and SMOG from 8.90 to 11.84, corresponding to reading levels from advanced junior high to early university. The average DISCERN score ranged from 43.2 to 44.9 ("average" quality). ChatGPT-5.4 showed moderate-to-high inter-generation stability with limited content drift in this exemplar context. However because no earlier model was evaluated head-to-head under identical prompts, raters, and time points, this finding should be interpreted as within- study evidence of stability rather than evidence of improved stability over earlier models. Readability remained challenging, and verifiable references were absent. Within this exemplar spinal-surgery context, ChatGPT-5.4 demonstrated moderate-to-high inter-generation consistency in lexical content and core medical themes. Complex language and lack of traceable references may limit accessibility and patient trust. ChatGPT-5.4 may support spinal-surgery patient education by generating stable, clinically plausible PEMs, though factual accuracy was not independently verified. Readability remains above recommended health- literacy levels, and clinician review and plain-language optimization are required before patient use.

Nowadays, artificial intelligence Large Language Models (LLMs) are widely used by patients and physicians alike to investigate various medical topics. Pelvic floor rehabilitation has become a popular subject in recent years. The aim of this study is to assess and compare the usability, readability, and repeatability of three LLMs - ChatGPT, DeepSeek and Gemini - in relation to pelvic floor rehabilitation. A total of 35 questions derived from the three most frequently searched Google Trends keywords related to pelvic floor rehabilitation ('pelvic floor dysfunction', 'pelvic floor exercises', and 'pelvic floor physical therapy') were evaluated by two raters. The quality of the responses was assessed using the Brief DISCERN (BD), a validated tool for evaluating the quality of health information. Readability was assessed using the Flesch-Kincaid Reading Ease (FRE), the Flesch-Kincaid Reading Grade Level (FKRGL) and the Simple Measure of Gobbledygook (SMOG) index. Responses were evaluated at two separate time points to assess consistency. Statistically significant differences in the SMOG index were observed among the AI models at the first and second evaluations (p&#x2009;<&#x2009;0.001), but only at the second evaluation for FKGL (p&#x2009;=&#x2009;0.006). Significant differences were also observed between LLMs for BD scores for physical therapy section at both first and second evaluations (p&#x2009;<&#x2009;0.001, p&#x2009;=&#x2009;0.035 respectively). ChatGPT, DeepSeek and Gemini provided readable, useful and repeatable answers to questions related to pelvic floor rehabilitation. However, it is important to bear in mind that LLMs are supplementary tools.

BACKGROUND Burns remain a major public health challenge for modern healthcare systems due to high mortality and long-term consequences. This study evaluated the effectiveness of several scoring systems in predicting mortality and identified key prognostic factors in patients with severe burns. MATERIAL AND METHODS A retrospective analysis of 144 adult burn patients admitted to the intensive care unit was conducted. Mortality risk was assessed using total body surface area (TBSA), revised Baux, Abbreviated Burn Severity Index (ABSI), Belgium Outcome Burn Injury (BOBI), and Burn Mortality Prediction (BUMP) scores. Two analytical approaches were applied: a baseline clinical model including key independent variables (age, TBSA, inhalation injury), and separate logistic regression models for each scoring system. Predictive performance was evaluated using receiver operating characteristic (ROC) curves and compared using the DeLong test. RESULTS Overall mortality rate was 43.1%. Non-survivors were older (59.2 vs 46.5 years), had larger burned surface area (42.3% vs 35.3%), and more frequently presented with inhalation injury (59.7% vs 26.8%). The baseline model demonstrated excellent discriminative ability (AUROC=0.87, P<0.001). Among scoring systems, the revised BAUX achieved the highest AUROC (0.86, P<0.001), followed by BOBI and BUMP (both 0.83, P<0.001). However, pairwise comparisons showed no statistically significant differences between the best-performing scores. CONCLUSIONS The baseline clinical model and composite scoring systems demonstrated strong and comparable predictive performance. Simple clinical models based on key variables may provide an effective alternative for mortality risk assessment, while established scoring systems remain valuable due to their ease of use in routine practice. The findings highlight the need for early identification of high-risk patients and timely clinical management optimization.

The use of technology in healthcare to manage patient records, guide diagnosis, and make referrals is termed electronic healthcare. An electronic health record system called Lightwave Health Information Management System (LHIMS) was implemented in 2021 at Bolgatanga Regional Hospital (BRH). This study evaluated the opinion of users on the use of LHIMS among healthcare workers, focusing on the extent to which its use has enhanced the main dimensions of clinical work. A qualitative research design was employed to explore healthcare providers' experiences with the LHIMS. Purposive sampling was employed to recruit eleven (11) participants comprising nurses and doctors who had at least two years of experience using the LHIMS. An interview guide was used to facilitate in-depth, face-to-face interviews with all participants. Healthcare providers expressed overall satisfaction with LHIMS, citing its time-saving features, efficiency, data security, cost-effectiveness, and ease of use. Users reported receiving support from IT personnel, experienced colleagues, and stable network systems; however, challenges included inadequate staff training, documentation difficulties among nurse midwives, limited computer availability, insufficient user manuals, and frequent power interruptions. The study found that most LHIMS users were satisfied with the system, particularly its user-friendly interface and efficiency in managing and synchronizing patient data. To enhance system performance and sustain user satisfaction, the hospital should ensure uninterrupted power supply, provide mandatory training for new staff, integrate a comprehensive user manual into the LHIMS platform, and supply adequate computer resources to support effective use.

PurposeInterest in reusable menstrual products has expanded substantially over the last decade. However, there is limited published research on user experiences with these products in terms of their effectiveness in menstrual management. We assessed the acceptability of, and user experiences with, the menstrual disc-one of the newest types of reusable products-in terms of ease/difficulty of use (i.e., insertion, removal), leakages and overall comfort.Design/ApproachWe conducted a qualitative pilot study and provided students with menstrual discs to use over two menstrual cycles.SettingThe study was conducted on a mid-sized college campus in Massachusetts, U.S.ParticipantsWe recruited fourteen students who menstruate.MethodStudents completed two diary entries-one per menstrual cycle-about their experiences using the menstrual disc.ResultsThe menstrual disc was well received overall, and most students liked the long wear time, fewer changes required and the ability of the disc to self-empty. Although many students struggled with insertion initially, this improved with subsequent uses. Students noted that removal was easy but messy, which made changing in public bathrooms difficult. A few experienced major leakages when the disc became overfull. Almost all expressed willingness to use the disc as their main menstrual product.ConclusionThe menstrual disc potentially expands the range of more comfortable and convenient reusable menstrual products and should be included in reproductive health education.