State legislators play a central role in U.S. vaccination policymaking, yet little is known about how social media engagement dynamics structure elected officials' online anti-vaccine messaging. We examine whether public engagement with lawmakers' anti-vaccine posts functions as a behavioral feedback loop, characterized by subsequent production of anti-vaccine content from those same legislators. Using a large-scale digital trace dataset of tweets from 2,619 state legislators in 2021, we identify 83,130 vaccine-related tweets and 3,314 anti-vaccine tweets via transformer-based text classification. We model anti-vaccine posting at the legislator-month level with an integrated set of individual, state, and temporal predictors, including partisan time trends and state-level pandemic conditions. We find that greater engagement with prior anti-vaccine tweets is associated with a higher probability of posting anti-vaccine content in subsequent months. We further show that replies tend to mirror the stance of legislators' vaccine-related tweets, suggesting that public engagement can amplify legislators' perceptions of audience agreement, sustaining continued anti-vaccine communication. Additionally, anti-vaccine tweets are more likely than other vaccine-related tweets to link to low-credibility sources, indicating that engagement-driven reinforcement may facilitate the circulation of misleading information. Overall, these findings illustrate how public interaction with social media platforms' engagement architectures shapes elite political communication and the informational politics of public-health governance.
L-malic acid is one of the most important acids present in fruits. Its determination is important in the manufacture of beer, fruit and vegetable products. In the wine industry, its level is monitored during malolactic fermentation. It is also added to a variety of products as food preservative and flavor enhancer. To validate the performance of the Enzytec™ Liquid L-Malic acid test kit for the determination of L-Malic Acid in foods and beverages such as fruit juice (concentrates and products), vegetable juice, wine, beer, sauces, and carbonated soft drinks. The kit contains two ready-to-use components only which makes handling easy and suitable for automation. L-malic acid is oxidized to oxaloacetate by L-malate dehydrogenase and NAD+. The NADH produced is equivalent to the amount of L-malate converted and is measured at 340 nm. The Limit of Detection (LOD) was determined to be 8 mg/L for 100 µL test volume and the measurement range is 15 to 500 mg/L. Trueness was checked by analyzing a reference wine sample resulting in a recovery between 96 and 99%. Recovery was checked by spiking and resulted in mean values from 97 to 105% for red wine, beer, soft drink, carrot juice, apple juice, acerola juice concentrate, BBQ sauce, and quince jelly. Relative intermediate precision is between 1.5 and 3.6% for carrot juice, BBQ sauce, NIST SRM 3282, and a reference wine. D-tartaric acid and meso-tartaric acid interfere and cause a creep during the reaction. Sulfite interferes at concentrations higher than 0.025 g/L but can be masked by glyoxal. For automation, three applications with different test volumes were validated. Linearity is given from 3.5 to 2500 mg/L. The method was approved as AOAC Official Method of Analysis℠. Real time and in-use stability are at least 24 months.
Background Physicians are frequently portrayed as principal drivers of American healthcare spending, although they often lack control over the prices, benchmarks, ownership structures, and corporate revenue flows attached to the care they provide. We examined whether federal cost policy directs scrutiny and containment toward economic actors in proportion to their control over price and revenue. Methodology We conducted a purposive structured descriptive analysis of major federal payment and cost-containment policies from January 2001 through July 2026. Evidence was organized into the following three ledgers: who receives the cuts, who controls and captures the money, and who receives the blame. A transparent, nonexhaustive inventory compared physician, insurer, pharmaceutical, and device-sector policies by breadth, automaticity, inflation sensitivity, durability, and reversibility. Rhetorical framing was assessed through matched Centers for Medicare & Medicaid Services (CMS) communications issued during the 2025-2026 policy period, and each principal finding was classified under an explicit four-level evidentiary standard. Results Medicare physician fee-schedule updates increased approximately 14% from 2000 through 2023 while the Medicare Economic Index increased approximately 52%; through 2024, the gap was approximately 14% versus 56%. The conversion factor declined from $38.26 in 2001 to $33.40-$33.57 in 2026. Physician payment remained subject to annual administered pricing, budget neutrality, temporary congressional relief, and recurring valuation adjustments. Among the major provisions examined, corporate-sector restrictions were more selective or reversible: the device excise tax and health-insurer fee were repealed; the Inflation Reduction Act created a recurring negotiation framework whose first 10 prices took effect in 2026, with CMS estimating $6 billion in net Medicare savings had those prices applied in 2023 and $1.5 billion in beneficiary savings in 2026; and Medicare Advantage payments increased 5.06% for 2026 despite MedPAC-estimated payments of $76-$84 billion above fee-for-service equivalence. International comparisons found U.S. prescription drug prices at 278% of prices in 33 peer countries overall and brand originator gross prices at 422%. Federal audit and transparency data documented payer-side control over realized claim payment. In an illustrative matched comparison of three CMS communications, physician policy was framed through waste and efficiency, insurer policy through access and stability, and manufacturer policy through innovation and certainty. Conclusions Across the major federal policies examined, physicians faced continuous, automatic, and inflation-insensitive payment restraint despite limited control over administered unit prices. Sectors with greater control over prices, claims adjudication, market access, and revenue capture generally faced narrower, later, or more reversible restrictions and more protective official framing. This convergent pattern supports a descriptive Scrutiny-Control Inversion. It does not establish coordinated intent or prove that political spending caused the observed policy outcomes.
Large language models (LLMs) have the potential to provide individualized preventive care guidance at scale. Research, however, has found mixed performance among a small set of LLMs queried about select preventive care activities. These findings call for testing a larger set of LLMs on a wider range of preventive care topics. This study aims to assess whether various popular LLMs generate outputs about preventive care consistent with a comprehensive set of recommendations from the US Preventive Services Task Force (USPSTF). We investigated whether 35 popular LLMs produced outputs consistent with all publicly available USPSTF recommendations (n=142) published as of May 2025. The study occurred in 2 waves (wave 1, 2025: 28 LLMs; wave 2, 2026: 10 LLMs; 3 LLMs overlapping across waves). LLMs received queries from simulated users who, in baseline prompts, sought nonbinding, hypothetical advice about whether to participate in particular preventive care activities given their inclusion in a relevant population. LLM raters assessed LLM-USPSTF concordance (interrater reliability, wave 1: κ=0.8893; wave 2: κ=0.9366). Wave 2 tested chain-of-thought, few-shot, and role-based prompts (3 variants each for 426 tests per prompting approach per model). Wave 2 also tested an iterative prompt that sought clarification about previous LLM responses and a prompt that eliminated the user's reference to nonbinding, hypothetical advice. Automated methods classified responses to detect sources of LLM-USPSTF discrepancy. Further tests prompted LLMs to rate preventive care activities for relevant populations using the USPSTF grading scale. Focusing on cases where LLM raters agreed, the study found in its baseline prompts that the LLM with the highest concordance rate generated responses consistent with USPSTF recommendations in 66.92% (89/133) of tests in wave 1 and 87.77% (122/139) of tests in wave 2; the LLM with the lowest rate accorded with USPSTF recommendations in 45.19% (61/135) of tests in wave 1 and in 50.36% (69/137) of tests in wave 2. Eliminating reference to nonbinding, hypothetical advice did not alter the highest-performing model's rate of concordance (122/139, 87.77%). The highest concordance rate increased with chain-of-thought (404/421, 95.96%), role-based (371/416, 89%), and iterative prompting (127/140, 90.71%); however, it moderately decreased with few-shot prompting (361/419, 86.15%). Automated content analysis found high rates of LLMs avoiding definitive recommendations. When prompted to grade preventive care activities, the highest-performing LLM matched USPSTF grades in 85.92% (122/142) of tests in wave 1 and in 94.37% (134/142) of tests in wave 2. LLMs' consistency with USPSTF recommendations varies. Deviations result mainly from LLMs' avoidance of definitive statements. LLM-USPSTF concordance has improved markedly in newer models, and this concordance increases with particular prompting approaches.
To systematically evaluate the overall performance, subject-based differences, and question type adaptability of five mainstream large language models (ChatGPT, DeepSeek, Kimi, Qwen, and Doubao) in the Chinese National Pharmacist Licensing Examination (CNPLE), and to explore their feasibility as auxiliary tools for pharmaceutical examinations. A cross-sectional comparative study design was adopted. The practice questions of the 2024 CNPLE were used as the evaluation dataset, covering 480 standardized questions across four subjects: Pharmaceutical Professional Knowledge (I), Pharmaceutical Professional Knowledge (II), Comprehensive Knowledge and Skills of Pharmacy, and Pharmaceutical Administration and Regulation. The question types included Type A (single best choice), Type B (matching choice), Type C (comprehensive analysis), and Type X (multiple choice). Standardized prompts were used for independent tests using the official web versions of each model with default parameters. Each question was input separately in a new conversation session to avoid contextual interference. Taking the official standard answers as the gold standard, the subject accuracy rate, question type accuracy rate, and overall accuracy rate of each model were calculated. To compare the overall performance among the five models, Cochran's Q test was applied. Post-hoc pairwise comparisons were performed using McNemar's test with Bonferroni correction for multiple comparisons. All five models exceeded the 60% passing score threshold of the CNPLE. The overall accuracy ranking was: Kimi (89.58%) > Doubao (88.96%) > DeepSeek (87.29%) > Qwen (77.92%) > ChatGPT (72.50%). Cochran's Q test showed a statistically significant difference in the overall accuracy among the five models (Q = 111.39, df = 4, P < 0.001). Pairwise comparisons showed no significant differences among Kimi, Doubao and DeepSeek (P > 0.05), while all three performed significantly better than Qwen and ChatGPT (P < 0.001). At the subject level, all models achieved the best performance in Pharmaceutical Professional Knowledge (II) (average accuracy 89.50%) and relatively weak performance in Pharmaceutical Administration and Regulation (average accuracy 76.50%). At the question type level, Type C questions yielded the highest average accuracy (90.00%), whereas Type X questions had the lowest average accuracy (69.00%). In this single-run evaluation, the Chinese large language models tested achieved higher overall accuracy than ChatGPT under the same conditions. Among them, Kimi, Doubao and DeepSeek have reached an excellent performance level. Different models present differentiated advantages across subjects and question types. Regulatory subjects and Type X (multiple-answer) questions are common challenges for all models. The findings indicate that mainstream LLMs possess considerable potential as auxiliary tools for the CNPLE, and can provide intelligent support for pharmaceutical education and examination preparation.
Excess mortality has emerged as a comprehensive indicator of overall mortality burden of the COVID-19 pandemic, reflecting both direct and indirect deaths beyond officially reported COVID-19 fatalities. However, the substantial cross-national variation in excess mortality remains incompletely explained, particularly in relation to structural heterogeneity across countries. This study examines whether pandemic mortality differs according to economic development and national preparedness. We analysed 59 countries from 2020 to 2024. Excess mortality ratios were estimated based on pre-pandemic mortality trends (2015-2019). Countries were classified as advanced or emerging market economies based on the International Monetary Fund criteria. National preparedness was assessed by the 2021 Global Health Security (GHS) Index. Associations between preparedness and excess mortality were evaluated using regression models and interpreted using SHapley Additive exPlanations (SHAP)-based analysis to quantify domain-level contributions to predict mortality. Excess mortality peaked globally in 2020 and 2021 and declined thereafter. During the early period of the pandemic, emerging market economies experienced consistently higher total and non-COVID (excluding officially reported COVID-19 deaths) excess mortality than did advanced economies. Using the pooled analyses during the early pandemic period (2020-2021), higher overall GHS Index scores were significantly associated with lower excess mortality. However, this association weakened after stratification by economic development stage, indicating that the pooled associations were largely driven by structural differences between economic groups. Early detection and risk environment as preparedness domains were strongly associated with reduced excess mortality. Cross-national differences in pandemic mortality were primarily shaped by structural capacity gradients rather than preparedness scores. Therefore, preparedness indices might function better as indicators of broader structural capacity than predictors of mortality outcomes in comparable economic contexts. Strengthening pandemic resilience should prioritise surveillance capacity and institutional robustness to enhance baseline preparedness capacity.
This study aimed to map and analyze the normative evolution and institutional challenges related to the reproductive health of trans men and transmasculine people in Brazil. A scoping review was carried out according to the methodological guidelines of the JBI, registered on the Open Science Framework. The retrieved scientific studies included articles, theses, dissertations, academic papers, and various official regulations. The findings show that, despite important legal frameworks, these regulations emerged in historical contexts in which the identity categories and specific demands of trans men and transmasculine people were not yet consolidated in the public and legal debate. Notably, by remaining without substantive updates, these provisions produce effects of exclusion and invisibility, showing the persistence of a cisheteronormative logic in the structuring of access to reproductive health. Recent advances include the recognition of trans parenting in official documents and the creation of specific materials, such as the Transgesta prenatal booklet. However, critical gaps persist in access to fertilization, gamete preservation, and family planning, as do symbolic and institutional barriers to health care. This study shows that the fulfilment of sexual and reproductive rights of this group depends on more inclusive normative frameworks and on the transformation of institutional practices and the training of healthcare providers. The historical and critical analysis of policies in this study evince advances, setbacks, and omissions, contributing to expand knowledge about the reproductive health of trans men and transmasculine people in Brazil. Este estudo teve como objetivo mapear e analisar a evolução normativa e os desafios institucionais relacionados à saúde reprodutiva de homens trans e pessoas transmasculinas no Brasil. Uma revisão de escopo foi realizada de acordo com as diretrizes metodológicas do JBI, registrado no Open Science Framework. Foram localizados estudos científicos, incluindo artigos, teses, dissertações, artigos acadêmicos e diversas regulamentações oficiais. Os achados revelam que, embora existam marcos legais importantes, essas regulamentações foram formuladas em contextos históricos onde as categorias de identidade e as demandas específicas de homens trans e pessoas transmasculinas ainda não estavam consolidadas no debate público e jurídico. No entanto, ao permanecerem sem atualizações substanciais, essas disposições produzem efeitos de exclusão e invisibilidade, revelando a persistência de uma lógica cisheteronormativa na estruturação do acesso à saúde reprodutiva. Avanços recentes incluem o reconhecimento da parentalidade trans em documentos oficiais e a criação de materiais específicos, como o livreto pré-natal Transgesta. No entanto, persistem lacunas críticas no acesso à fertilização, preservação de gametas e planejamento familiar, além de barreiras simbólicas e institucionais ao cuidado da saúde. O estudo mostra que a realização dos direitos sexuais e reprodutivos desse grupo depende não apenas de estruturas normativas mais inclusivas, mas também da transformação das práticas institucionais e da formação de profissionais de saúde. Concluiu-se que a análise histórica e crítica das políticas nos permite compreender avanços, retrocessos e omissões, contribuindo para ampliar o conhecimento sobre a saúde reprodutiva de homens trans e pessoas transmasculinas no Brasil. Este estudio tuvo como objetivo mapear y analizar la evolución normativa y los desafíos institucionales relacionados con la salud reproductiva de hombres transgénero y de personas transmasculinas en Brasil. Se realizó una revisión de alcance de acuerdo con las directrices metodológicas del JBI, registradas en el Open Science Framework. Se localizaron estudios científicos, incluidos artículos, tesis, disertaciones, trabajos académicos y diversas reglamentaciones oficiales. Los hallazgos revelan que, si bien existen importantes hitos legales, estas reglamentaciones se formularon en contextos históricos en los que las categorías de identidad y las demandas específicas de los hombres trans y de las personas transmasculinas aún no estaban consolidadas en el debate público y jurídico. Sin embargo, al no haber sido actualizadas sustancialmente, estas disposiciones producen efectos de exclusión e invisibilidad, lo que revela la persistencia de una lógica cisheteronormativa en la estructuración del acceso a la salud reproductiva. Entre los avances recientes se incluyen el reconocimiento de la paternidad transgénero en documentos oficiales y la creación de materiales específicos, como el folleto prenatal Transgesta. Sin embargo, persisten importantes deficiencias en el acceso a la fertilización, a la preservación de gametos y a la planificación familiar, además de barreras simbólicas e institucionales al cuidado de salud. El estudio demuestra que el ejercicio de los derechos sexuales y reproductivos de este grupo depende no solo de estructuras normativas más inclusivas, sino también de la transformación de las prácticas institucionales y de la formación de profesionales de la salud. Se concluyó que el análisis histórico y crítico de las políticas permite comprender los avances, los retrocesos y las omisiones, lo que contribuye a una comprensión más amplia de la salud reproductiva de los hombres transgénero y de las personas transmasculinas en Brasil.
Aim: To conduct a comprehensive analysis of the legal guarantees for Ukrainian law enforcement officers performing their official duties in areas of military (combat) operations, and their impact on the preservation of mental and physical health. The research also aims to identify the relationship between the level of implementation of these guarantees, psycho-emotional state, occupational stress, and the risks of burnout among this category of personnel. Materials and Methods: The study was designed as an interdisciplinary empirical legal study combining legal, medico-social, and statistical methods. It included comparative legal analysis, an anonymous survey, and statistical processing of the data. The study involved 48 law enforcement officers with experience of service in combat zones or other high-risk conditions. The main research instrument was an adapted questionnaire assessing psychological competencies and the perception of legal guarantees. Results: The respondents highly rated the importance of psychological competencies for professional communication, while self-assessment of communicative skills was moderately high. At the same time, indicators of stress prevention, perception of legal guarantees, legal certainty, maladaptive behaviour risks, and mental health remained at an average level. The lowest scores were related to access to psychological assistance and access to rest and rotation. Correlation analysis showed that stronger legal guarantees were associated with lower occupational stress, while greater legal certainty was linked to better self-assessed mental health. Insufficient legal guarantees were significantly associated with emotional burnout. Conclusions: Legal guarantees for law enforcement personnel in combat conditions should be regarded not only as a formal element of service status, but also as a practical mechanism for preserving mental and physical health. Strengthening legal certainty, improving access to psychological and medical support, and ensuring effective rest and rotation mechanisms are essential for reducing stress and burnout and for enhancing professional resilience.
Traditional villages in China serve as important carriers of rural cultural heritage but are increasingly threatened by rapid urbanisation and uneven regional development. Understanding their spatial distribution and integration within cultural-tourism networks is essential for developing effective conservation and regional planning strategies. Using a national dataset of 8,157 officially designated traditional villages, combined with city-level tourism indicators and three categories of cultural heritage carriers (A-level scenic spots, intangible cultural heritage, and protected cultural relics), this study developed an integrated analytical framework based on spatial statistical analysis, spatial correlation analysis, and K-means clustering to evaluate spatial differentiation and cultural-tourism integration patterns. The results reveal a pronounced "south-dense, north-sparse" spatial distribution with persistent regional inequality. Traditional villages exhibit weak correlations with overall tourism performance but strong spatial coupling with A-level scenic spots, moderate associations with protected cultural relics, and limited integration with intangible cultural heritage, indicating a selective and uneven embedding structure. Based on these relationships, Chinese cities can be classified into four development types: comprehensive leading areas, scenic-village integration areas, balanced development areas, and potential development areas, each characterised by distinct cultural-tourism integration pathways. The findings demonstrate that traditional villages function as selectively embedded nodes within China's cultural-tourism network rather than uniformly integrated tourism resources. This typology provides a practical basis for differentiated conservation policies, cultural heritage management, and place-based tourism planning while offering new insights into the spatial organisation of cultural heritage systems at the national scale.
Real-time forecasts of seasonal respiratory outbreaks are critical for public health preparedness and healthcare planning. Multi-model ensembles, which combine predictions from individual models, have become a leading approach for operational outbreak forecasting. Their success, however, depends in part on the assumption that component models make sufficiently independent errors. Here, we examined this assumption using archived real-time forecasts for influenza hospitalizations and influenza-like illness (ILI) in the United States. We found that component models with diverse structures and calibration methods shared systematic forecast errors during epidemic growth and around epidemic peaks, reflecting the common challenge of tracking rapid changes in epidemic dynamics from real-time surveillance data. Because such shared errors cannot be fully corrected by ensembling alone, we developed a deep learning framework that learns structured residual errors from historical forecasts and uses them to correct ensemble predictions. This framework improved influenza hospitalization forecasts across horizons and geographic scales, reducing the Weighted Interval Score by up to 20% at the national level and 12% across states relative to official ensemble forecasts, with the largest improvements at the near-term horizon and during epidemic growth and peak periods. We further showed that learned residual structures transferred across ensembles formed from different component models, making the approach robust to changes in model participation across seasons. The framework also improved ensemble forecasts for ILI, although gains were more modest. These findings reveal a fundamental challenge in ensemble forecasting and provide a generalizable approach for improving real-time epidemic forecasts.
This study evaluated the current landscape of deceased organ donation across the 5 Central Asian nations ( Kazakhstan, Uzbekistan, Tajikistan, Kyrgyzstan, and Turkmenistan ) and identified the multifactorial causes behind the regional "transplant gap." The study specifically focused on renal transplant programs, which constitute the vast majority of transplant activities and waiting lists in the region. We conducted a comprehensive analysis using a multidisciplinary approach, which included an audit of national legislative frameworks and official health ministry reports from 1972 to 2024. We performed qualitative synthesis on expert discourse from theologians, health care professionals ( including urologists and transplant surgeons ), and bioethicists to identify informal socio - cultural barriers. The study conformed to the 1975 Helsinki Declaration guidelines. Despite modern legal frameworks permitting deceased donation, clinical implementation remains nonexistent in most of the 5 republics, with activity almost exclusively limited to living related kidney and liver donation. Kazakhstan is the only nation with a sustained deceased donor program, where kidney transplants represent approximately 90 % of the national waiting list. However, the region faces a staggering 88 % family refusal rate. Religious misconceptions and the enduring influence of Tengrist "intact body" taboos were identified as pivotal factors hindering the transition from living to deceased donation. The failure of deceased donation programs in Central Asia is rooted in a unique synthesis of "Folk Islam" and ancestral nomadic traditions. Because the regional transplant capacity is primarily centered around urological and nephrological care, national strategies must integrate cultural resonance into these clinical settings. Success depends on reframing organ donation as a modern manifestation of traditional nomadic values through partnerships between medical specialists and religious leaders.
Aim: To analyze the availability of medicinal products for the Ukrainian population under martial law, identify key challenges in the pharmaceutical sector, and substantiate adaptive approaches for ensuring continuous pharmaceutical provision. Materials and Methods: A systematic analysis of regulatory, legal, and empirical data (2022-2025) was conducted using sources from the Ministry of Health of Ukraine, the Ministry of Digital Transformation of Ukraine, the State Service of Ukraine on Medicines and Drugs Control, and international organizations. The search covered the period from February 2022 to early 2026, corresponding to the duration of full-scale war and martial law in Ukraine. Sources were included if they addressed pharmaceutical provision, access to medicines, or pharmacy services; reflected the functioning of healthcare or pharmaceutical systems under crisis or wartime conditions; provided empirical data, regulatory information, or analytical insights; and were published in peer-reviewed journals, official reports, or credible professional and industry platforms in English or Ukrainian. Sources were excluded if they were not relevant to pharmaceutical accessibility or healthcare delivery, lacked analytical or factual content, duplicated previously identified sources, or originated from unverified platforms. The initial search and screening resulted in 68 sources. After preliminary screening and relevance assessment, 32 sources were selected for full-text review. Ultimately, 21 sources were included in the final analysis, forming the evidence base of this study. Conclusions: The pharmaceutical sector in Ukraine demonstrated high adaptive capacity under martial law. Despite infrastructural damage, workforce shortages, disrupted supply chains, and reduced affordability, the implementation of adaptive mechanisms improved access to essential medicines. Alternative delivery models (mobile pharmacies and "Ukrposhta. Pharmacy"), digital monitoring tools, regulatory simplification, and financial support programs enhanced both physical and economic accessibility. The integrated approach combining regulatory flexibility, digitalization, and alternative distribution systems ensures continuity of pharmaceutical provision and strengthens long-term resilience under crisis conditions.
The proliferation of unregistered, substandard, and falsified (SF) veterinary pharmaceuticals represents a critical global threat to animal health, food security, and environmental conservation. In sub-Saharan Africa, these products exacerbate the emergence of antimicrobial resistance (AMR), potentially accelerating the transition toward a "post-antibiotic" era. Despite Ethiopia's relatively developed regulatory framework compared to neighboring states, vulnerabilities such as inadequate diagnostic facilities, porous supply chains, and limited postmarketing surveillance results in enforcement persist. This descriptive study was conducted to determine the prevalence and quality profile of selected veterinary antimicrobials, including antibacterials, anthelmintics, and antiprotozoals, circulating in the Ethiopian market. Postmarket quality surveillance (PMS) study was conducted across five administrative regions. A total of 142 samples were collected and evaluated through three distinct regulatory tiers: verification of Ethiopian Agricultural Authority (EAA) registration status, standardized visual/physical screening, and official pharmacopeial (compendial) laboratory testing. The majority of sampled products (95.7%) were imported, predominantly from China (75.7%) and India (15.0%). Primary sampling sites included veterinary retail outlets (50.7%) and clinics (22.9%). Regulatory analysis revealed that 17.9% (n = 25) of samples were unregistered. Visual screening identified an administrative substandard prevalence of 24.3% among registered products. Of the 44 samples subjected to compendial laboratory analysis, 22.7% (n = 10) failed to meet established pharmacopeial specifications. While suspected falsified products were identified through labeling discrepancies, laboratory confirmation of falsification is ongoing. Unregistered and substandard veterinary medicines are circulating in the Ethiopian supply chain, posing severe risks to animal health and contributing to the regional AMR crisis. These findings necessitate urgent, concerted efforts from stakeholders to strengthen the national regulatory system, enhance EAA laboratory capacity, and secure the pharmaceutical supply chain through targeted postmarketing enforcement.
The electrocardiogram (ECG) is an essential non-invasive tool for detecting cardiac abnormalities; however, accurate interpretation often requires specialized expertise that may be unavailable in resource-limited clinical settings. While deep learning models have demonstrated high classification performance, many existing architectures remain computationally intensive and lack assessments of predictive reliability, hindering their deployment in clinical decision support systems. In this study, we propose a lightweight hybrid framework integrating Convolutional Neural Networks (CNN) and Fast Fourier Transform (FFT) components. This architecture combines time-domain morphological representations learned from raw ECG signals with physiologically relevant spectral features to enable accurate and efficient classification. Unlike previous approaches, this work emphasizes reliable model evaluation by incorporating probability calibration and a rigorous patient-wise validation protocol. The proposed method was evaluated on the publicly available PTB-XL dataset using the official 10-fold cross-validation protocol for both binary and five-class multi-label classification. In addition to conventional discrimination metrics, model reliability was assessed using Expected Calibration Error (ECE). The model achieved an accuracy of 92.42% and an AUC of 97.8% for binary classification, alongside a macro-AUC of 92.46% for five- class multi-label classification. Calibration analysis demonstrated well-calibrated probability estimates with low ECE values. Despite its competitive performance, the architecture is highly efficient, containing only 87K parameters and 0.26 GFLOPs. These findings highlight the potential of lightweight hybrid architectures combined with calibration-aware evaluation to support reliable AI-assisted ECG diagnostics in resource-constrained healthcare settings.
Aim: To analyze medico-legal challenges and the practical application of patients' will certification in healthcare institutions during inpatient care. Materials and Methods: A retrospective medico-legal analysis of court decisions from the Unified State Register of Court Decisions of Ukraine (2015-2026) was conducted. Of more than 450 identified cases, 60 met the inclusion criteria related to disputes over wills certified in healthcare institutions. Statistical analysis included Pearson's χ² test, Fisher's exact test, and odds ratios (OR) with 95% confidence intervals (CI). Additionally, a survey of 28 medical professionals assessed practical aspects and challenges of will certification in clinical settings. Results: Wills certified by medical professionals and healthcare institution officials accounted for 60.0% of cases, while 40.0% were notarized. The proportion of wills declared invalid or void was significantly higher in the medical group (41.7%) compared to the notarial group (12.5%). A statistically significant association was identified between the certifying subject and court outcomes (χ² = 5.83; p=0.016; Fisher's exact test p=0.031). Certification by medical personnel was associated with a fivefold increase in the likelihood of invalidation (OR=5.0; 95% CI: 1.24-20.15). Survey findings revealed insufficient legal knowledge and difficulties in assessing testamentary capacity and voluntariness. Conclusions: Wills certified in healthcare settings demonstrate lower legal reliability compared to notarized wills. This may be attributed to clinical, organizational, and legal factors, including challenges in capacity assessment and limited legal training of medical staff. The findings highlight the need for improved interdisciplinary protocols.
Hypertension has multiple risk factors that need to be identified in specific contexts to guide the prioritization and implementation of effective control strategies. To assess the association between hypertension and risk factors in Peruvian outpatients. An analytical, retrospective, observational study was conducted in 286 patients attending a primary healthcare center. High blood pressure and risk factor values were obtained using two diagnostic interpretation guides adapted by official institutions. Univariate analysis was performed using frequency distributions, and associations were assessed with the chi-square test for homogeneity (p<0.05) and prevalence odds ratios. A total of 37.76% of patients had hypertension. The most frequent risk factors were low HDL cholesterol (56.29%) and elevated body mass index (60.49%). Elevated HbA1c was associated with a more than threefold increased risk of hypertension. Elevated total cholesterol, LDL cholesterol, and fasting blood glucose were associated with a more than twofold increased risk in women. In men, increased waist circumference was associated with a more than threefold increased risk, and in older adults, with a more than twofold increased risk. Context shapes the association between hypertension and risk factors, given the specific characteristics of each setting and differing social determinants. Hypertension was significantly associated with elevated HbA1c, total cholesterol, LDL cholesterol, fasting blood glucose, and waist circumference. Timely and appropriate interventions targeting the identified risk factors could slow the occurrence of hypertension. La hipertensión arterial presenta factores de riesgo, que requieren ser identificados en contextos específicos para la priorización y operativización de estrategias de control efectivas. Asociar la hipertensión arterial y los factores de riesgo en pacientes ambulatorios peruanos. Estudio analítico, retrospectivo y observacional, efectuado con 286 pacientes que acudieron a un centro de salud primario. Los valores de hipertensión arterial y factores de riesgo se obtuvieron mediante dos guías de interpretación diagnóstica, adaptadas de instituciones oficiales. El análisis univariado fue a través de frecuencias y la asociación con el chi cuadrado de homogeneidad (p<0,05) y odds ratio de prevalencia. El 37,76% de pacientes tenían hipertensión arterial, los factores de riesgo más frecuentes fueron el C-HDL disminuido (56,29%) y el índice de masa corporal elevado (60,49%), la HbA1c elevada representó más de 3 veces riesgo para hipertensión arterial, el C-Total, el C-LDL y la glucemia en ayunas elevados más de 2 veces riesgo en mujeres, en varones el perímetro abdominal elevado más de 3 veces riesgo y en adultos mayores más de 2 veces riesgo. El contexto determina la asociación de la hipertensión arterial con los factores de riesgo, debido a las características propias de cada lugar y a los determinantes sociales diferenciados. La hipertensión arterial se asoció de manera significativa con la HbA1c, C-Total, C-LDL, glucemia en ayunas y perímetro abdominal elevados. La intervención oportuna y acertada sobre los factores de riesgo identificados, ralentizaría la ocurrencia de hipertensión arterial. A hipertensão apresenta fatores de risco que precisam ser identificados em contextos específicos para a priorização e implementação de estratégias de controle eficazes. Determinar a associação entre hipertensão e fatores de risco em pacientes ambulatoriais peruanos. Trata-se de um estudo analítico, retrospectivo e observacional realizado com 286 pacientes atendidos em um centro de atenção primária à saúde. Os valores de hipertensão e fatores de risco foram obtidos utilizando dois guias de interpretação diagnóstica adaptados de instituições oficiais. A análise univariada foi realizada utilizando frequências, e as associações foram avaliadas pelo teste qui-quadrado para homogeneidade (p<0,05) e pela razão de chances para prevalência. 37,76% dos pacientes apresentavam hipertensão. Os fatores de risco mais frequentes foram colesterol HDL reduzido (56,29%) e índice de massa corporal elevado (60,49%). A hemoglobina glicada (HbA1c) elevada representou um risco mais de três vezes maior para hipertensão. Níveis elevados de colesterol total, colesterol LDL e glicemia de jejum representaram um risco mais que duas vezes maior em mulheres, enquanto circunferência abdominal elevada representou um risco mais que três vezes maior em homens e mais que duas vezes maior em idosos. O contexto determina a associação da hipertensão com os fatores de risco, devido às características específicas de cada local e aos determinantes sociais diferenciados. A hipertensão foi significativamente associada a níveis elevados de HbA1c, colesterol total, colesterol LDL, glicemia de jejum e circunferência abdominal. Intervenções oportunas e adequadas sobre os fatores de risco identificados podem retardar o desenvolvimento da hipertensão.
The Asian Games are often discussed as a regional counterpart to the Olympics, yet their political significance remains insufficiently examined. This article addresses this gap by asking how host states use the Asian Games as a political platform. The study draws on a comparative analysis of recent host cases, including China, South Korea, Indonesia, Qatar, and Japan. It uses official documents, government promotional materials, media coverage, and firsthand observations to examine the political meanings attached to hosting. The article argues that host states use the Asian Games to advance political claims through the act of hosting itself. More specifically, they use the event to shape national self-representation, stage diplomatic signaling, and seek external recognition. The article shows that the political significance of the Asian Games lies not simply in the images and messages that hosts seek to project, but also in the responses these efforts generate. By shifting attention from sport as display to sport as a process of political negotiation, the article demonstrates that the Asian Games offer a distinctive lens through which to understand how identity, diplomacy, and recognition are contested in contemporary Asia.
With the advent of novel systemic therapies that provide high response rates, such as lenvatinib, atezolizumab-bevacizumab, durvalumab-tremelimumab, and nivolumab-ipilimumab, treatment strategies for patients with advanced hepatocellular carcinoma (HCC) have markedly evolved, and discussions on conversion therapy - which, broadly speaking, combines these systemic therapies with locoregional modalities - have become commonplace. However, the term "conversion therapy" has not yet been clearly defined, making it difficult to compare treatment outcomes among studies. To address this issue, the Japan Liver Cancer Association established a consensus-based "Working Group on the Definition of Conversion" as an official project of the association. The working group comprised experts in hepatobiliary surgery, hepatology, and radiology, with a rapporteur responsible for drafting and revising the definitions. The group proposed standardized definitions for "conversion surgery," "neoadjuvant therapy," and "ablation as conversion therapy," while recommending that transcatheter arterial chemoembolization should not be classified as conversion therapy due to its limited curative potential. The definitions also introduced two key concepts: functional conversion (based on the hepatic functional reserve) and oncological conversion (based on the tumor status). Adoption of these definitions is expected to facilitate appropriate evaluation of pretreatments and outcomes of conversion therapy. Ultimately, these efforts are expected to contribute to refining clinical decision-making, providing a common framework for guideline development and future clinical studies, and improving the outcomes of multidisciplinary treatments for advanced HCC; however, further validation is required.
Timely and highly accurate diagnoses by physicians play a crucial role in improving the quality and effectiveness of patient treatment outcomes. Currently, the use of artificial intelligence capabilities in this area has garnered the attention of many health science researchers. Therefore, the main goal of this preliminary study was to compare the text-based diagnostic reasoning performance of emergency medicine physicians and large language models in definitive and differential diagnoses using standardized clinical vignettes. This descriptive comparative study evaluated the diagnostic accuracy of 10 emergency medicine physicians and 4 large language models (LLMs)-ChatGPT (GPT-5.2), Gemini 3, Microsoft Copilot (GPT-4), and Claude Opus 4.1-using 10 standardized clinical vignettes. All LLMs were accessed via official web interfaces. Clinical vignettes were developed from emergency department presentations, validated by an expert panel, and presented as text-only inputs to all evaluators. Diagnostic accuracy was assessed using a standardized scoring protocol: definitive diagnoses required an exact match with expert-derived reference standards, while differential diagnoses required ≥ 3 matches. Overall diagnostic accuracy was the primary outcome. Data were analyzed using Pearson's Chi-square test, McNemar's test, and Generalized Estimating Equation (GEE) logistic regression with Bonferroni correction (SPSS version 28). A total of 280 diagnostic evaluations (10 clinical cases assessed by 14 evaluators across 2 diagnosis types) were analyzed. Overall diagnostic accuracy was 61.79%. AI models demonstrated significantly higher overall accuracy (73.75%) compared to emergency medicine physicians (57.00%, p = 0.014). Across all evaluators, definitive diagnoses were more accurate than differential diagnoses (70.71% vs. 52.86%). Generalized Estimating Equation (GEE) analysis revealed a significant interaction between evaluator group and diagnosis type (p = 0.036). Specifically, physicians experienced a significant decline in accuracy when providing differential diagnoses compared to definitive diagnoses (45.0% vs. 69.0%, p = 0.003; remained significant after Bonferroni correction). In contrast, AI models maintained consistently high accuracy across both diagnosis types, with no significant difference between definitive (75.0%) and differential (72.5%) diagnoses (p = 1.000). Large language models outperformed emergency medicine physicians in overall diagnostic accuracy and demonstrated superior consistency across different types of diagnostic tasks. While human physicians struggled significantly with differential diagnoses, AI models maintained high and stable performance regardless of the diagnostic complexity. These findings indicate that AI possesses robust pattern-recognition and reasoning capabilities, suggesting it could serve as a highly reliable clinical decision support tool, particularly in complex scenarios requiring differential diagnostic reasoning. Due to study limitations, such as the small number of clinical scenarios and assessors, these findings should be interpreted with significant caution.
To develop, implement, and describe a systematic six-phase methodology for creating accessible breast cancer education materials for people with intellectual disabilities (PwIDD), integrating WHO translation guidelines, Inclusion Europe standards, and co-production principles. A six-phase sequential methodology development study conducted January-November 2024. Five official Polish breast cancer education materials underwent readability analysis using validated linguistic software. Dual-audience materials were developed following Inclusion Europe guidelines, adapted with permissions from Macmillan Cancer Support and the Get in Touch Foundation. WHO translation protocols guided Polish-to-English adaptation. Pilot testing employed participatory methodology with PwIDD and their carers. International pilot testing at a European training event assessed cross-cultural applicability. Readability analysis revealed all existing materials scored 4-5/7 on a 7-point difficulty scale, exceeding accessibility thresholds (recommended: 1-2/7). Developed materials successfully employed a dual-audience approach providing simplified content for PwIDD and detailed information for carers. WHO-guided translation maintained semantic equivalence and accessibility features across languages. Pilot testing with 36 participants (18 PwIDD, 18 carers) across two workshops confirmed comprehensibility, cultural appropriateness, and practical usability. International testing indicated that the methodology was feasible to apply across cultural contexts. The systematic methodology successfully addressed accessibility barriers in existing health education resources, producing materials that performed effectively in pilot testing across cultural contexts. The dual-audience approach represents a methodological advancement supporting collaborative healthcare decision-making while respecting individual autonomy. Longitudinal evaluation of educational effectiveness is needed before broader equity impact claims can be substantiated. The six-phase framework offers a replicable, evidence-based approach for healthcare systems and policy-makers developing accessible health education materials. Provider communication guidelines support clinical implementation. The methodology addresses the urgent need for accessible cancer prevention resources and has potential for application across diverse health topics and populations.