OBJECTIVE To establish population pharmacokinetic model of levetiracetam （Lev） for Chinese patients with post- stroke epilepsy （PSE）， and provide reference for formulating individualized dosing regimens for Lev therapy in this specific population. METHODS Blood concentration data and clinical diagnosis and treatment information of PSE patients meeting the inclusion criteria were retrospectively collected and divided into model group and validation group at an 8∶2 ratio using a random number method. Based on the model group data， a population pharmacokinetic model was developed using nonlinear mixed-effects modeling. Internal evaluation was performed through goodness-of-fit tests and bootstrap analysis， while external validation was conducted using the validation group data. RESULTS A total of 75 blood concentration measurements from 70 PSE patients were collected， with 60 measurements from 55 patients used for model development and 15 measurements from 15 patients reserved for external validation. The final model estimated a population typical value of clearance at 2.98 L/h. Estimated glomerular filtration rate， daily dose， and homocysteine level significantly influenced clearance of Lev （P＜0.01）. The model demonstrated satisfactory predictive performance， as evidenced by goodness-of-fit tests， bootstrap analysis， and external validation results. CONCLUSIONS Daily dose， estimated glomerular filtration rate， and homocysteine level are identified as significant covariates influencing Lev clearance in Chinese PSE patients. When making clinical decisions， comprehensive consideration should be given to the patient’s treatment response， physiological and pathological conditions， and the occurrence of adverse reactions， etc. The dosage of Lev should be adjusted based on the results of population pharmacokinetic model.

This comprehensive review systematically explores the multifaceted applications, inherent challenges, and promising future directions of artificial intelligence (AI) within the medical domain. It meticulously examines AI's specific contributions to basic medical research, disease prevention, intelligent diagnosis, treatment, rehabilitation, nursing, and health management. Furthermore, the review delves into AI's innovative practices and pivotal roles in clinical trials, hospital administration, medical education, as well as the realms of medical ethics and policy formulation. Notably, the review identifies several key challenges confronting AI in healthcare, encompassing issues such as inadequate algorithm transparency, data privacy concerns, absent regulatory standards, and incomplete risk assessment frameworks. Looking ahead, the future trajectory of AI in healthcare encompasses enhancing algorithm interpretability, propelling generative AI applications, establishing robust data-sharing mechanisms, refining regulatory policies and standards, nurturing interdisciplinary talent, fostering collaboration among industry, academia, and medical institutions, and advancing inclusive, personalized precision medicine. Emphasizing the synergy between AI and emerging technologies like 5G, big data, and cloud computing, this review anticipates a new era of intelligent collaboration and inclusive sharing in healthcare. Through a multidimensional analysis, it presents a holistic overview of AI's medical applications and development prospects, catering to researchers, practitioners, and policymakers in the healthcare sector. Ultimately, this review aims to catalyze the deep integration and innovative deployment of AI technology in healthcare, thereby driving the sustainable advancement of smart healthcare.

As the volume of medical research using large language models (LLM) surges, the need for standardized and transparent reporting standards becomes increasingly critical. In January 2025, Nature Medicine published statement titled by TRIPOD-LLM reporting guideline for studies using large language models. This represents the first comprehensive reporting framework specifically tailored for studies that develop prediction models based on LLM. It comprises a checklist with 19 main items (encompassing 50 sub-items), a flowchart, and an abstract checklist (containing 12 items). This article provides an interpretation of TRIPOD-LLM’s development methods, primary content, scope, and the specific details of its items. The goal is to help researchers, clinicians, editors, and healthcare decision-makers to deeply understand and correctly apply TRIPOD-LLM, thereby improving the quality and transparency of LLM medical research reporting and promoting the standardized and ethical integration of LLM into healthcare.

Gentianopsis barbata (G. barbata) represents a significant plant species with considerable ornamental and medicinal value in China. This investigation sought to elucidate the primary constituents within the plant and investigate their pharmacological properties. Fifty triterpenoids (1-50), including nine previously undescribed compounds (1, 2, 7, 10, 20, 28, 29, 37, and 41) were isolated and characterized from the whole plants of G. barbata. Notably, compounds 1 and 2 exhibited the novel 3,4;9,10-diseco-24-homo-cycloartane triterpenoid skeleton. The isolated triterpenoids demonstrated substantial anti-inflammatory activity through inhibition of tumor necrosis factor α (TNF-α) and interleukin-6 (IL-6) cytokine secretion in LPS-induced RAW264.7 macrophages, and hepatoprotective effects by preventing tert-butyl hydroperoxide (t-BHP)-induced oxidative injury in HepG2 cells. These results demonstrate both the presence of diverse triterpenoids in G. barbata and their therapeutic potential for inflammatory and hepatic conditions, providing scientific evidence supporting the clinical application of this traditional Mongolian medicinal plant.
Triterpenes/isolation & purification* ; Mice ; Anti-Inflammatory Agents/isolation & purification* ; Animals ; Humans ; RAW 264.7 Cells ; Hep G2 Cells ; Interleukin-6/genetics* ; Tumor Necrosis Factor-alpha/genetics* ; Medicine, Mongolian Traditional ; Macrophages/immunology* ; Protective Agents/isolation & purification* ; Liver/drug effects* ; Gentianaceae/chemistry* ; Plant Extracts/chemistry* ; Molecular Structure

Objective: To investigate the prevalence of Dengue virus (DENV) infection among voluntary blood donors in Xishuangbanna Dai Autonomous Prefecture, and to evaluate the necessity of implementing nucleic acid testing (NAT) for blood donors during the rainy season (May-October). Methods: Prior to initiating donor screening, the Xishuangbanna Central Blood Center conducted in-house validation of reagent performance and participated in external quality assessment (EQA) organized by the National Center for Clinical Laboratories (NCCL). During the surveillance period (August-October 2024), a total of 2 919 donor samples were screened using a 6-sample mini-pool NAT strategy. Daily internal quality controls were recorded. Samples that tested positive in pooled screening were deconvoluted and retested in duplicate; only those reactive in both replicate wells were sent to the NCCL for confirmatory testing. At NCCL, samples underwent re-testing using five domestic NAT reagents, as well as serological assays for NS1 antigen and DENV-specific IgG/IgM. Confirmed positive samples were further characterized by serotyping, envelope (E) gene sequencing, and phylogenetic analysis using the maximum likelihood method. Results: The DENV NAT reagent demonstrated consistent detection of 40 copies/mL controls in individual donor (ID)-NAT test (mean CT: 35.61±0.40). During the 63-day quality control monitoring, DENV detection remained stable (mean CT: 22.53±0.72). The center achieved full marks in EQA assessments for 2023 and 2024. Three reactive pools were identified in initial screening, and subsequent individual testing confirmed three DENV RNA-positive donors (sample numbers: 2401, 2402, and 2403). The confirmatory test results from NCCL were: all five NAT platforms consistently detected DENV RNA in the three samples; for serological tests, 2 samples (2402, 2403) were positive for NS1 antigen, while all three samples were negative for both IgG and IgM antibodies. DENV serotyping reagents identified DENV-2 in all cases, which were further confirmed as DENV-2 Genotype Ⅱ-Cosmopolitan by E gene sequencing. Phylogenetic analysis indicated that samples 2401 and 2402 clustered with Southeast Asian strains (Thailand/MZ636802.1, Laos/PQ775621.1), while sample 2403 closely matched a previously reported local Yunnan strain (PV544686.1). Conclusion: DENV-2 infection was detected among blood donors in Xishuangbanna during the rainy season, indicating concurrent risks of imported and local transmission. We recommend implementing pooled NAT screening for blood donors in high-risk areas during dengue epidemic seasons, along with strengthened laboratory quality control, to enhance blood safety.

Tafamidis is a selective stabilizer for transthyretin （TTR）， used for the treatment of transthyretin amyloidosis with cardiomyopathy （ATTR-CM） and transthyretin amyloidosis with polyneuropathy （ATTR-PN）. This article provides a review of the basic information and clinical studies on the efficacy and safety of tafamidis. It is found that tafamidis slows down or prevents the progression of TTR amyloidosis by inhibiting the dissociation of TTR tetramers. Multiple clinical studies have shown that tafamidis has good efficacy and safety， significantly reducing all-cause mortality and cardiovascular-related hospitalization rates in patients with amyloidosis， and delaying disease progression. Although tafamidis treatment may have certain limitations， it is still a key drug for the treatment of TTR amyloidosis， and the first drug approved for the treatment of ATTR-CM.

The clinical practice guidelines of traditional Chinese medicine （TCM） have problems such as limited clinical application and unclear implementation effects， which may be related to the lack of clinical practice evidence. To provide reliable and precise evidence for clinical practice， this article proposes a model of combining TCM guidelines with real-world study， which includes 4 steps. Firstly， during the implementation process of the guidelines， a high-quality research database is established. Secondly， the recommendations in the guidelines are evaluated based on the established database in multiple dimensions， including applicability， effectiveness， safety， and cost-effectiveness， and thus their effectiveness in practical applications can be determined. Thirdly， based on the established database， core prescriptions are identified， and the targeted populations and medication plans are determined. That is， the best treatment regimen is established based on the analysis of abundant clinical data regarding the effects of different medication frequencies， dosages， and duration on efficacy. Fourthly， the guidelines are updated according to the real-world evidence. The research based on this model can provide real-world evidence for ancient and empirical prescriptions， improving their application in clinical practice. Moreover， this model can reduce research costs and improve research efficiency. When applying this model， researchers need to pay attention to the quality of real-world evidence， ensuring that it can truly reflect the situation in clinical practice. In addition， importance should be attached to the clinical application of guideline recommendations， ensuring that doctors can conduct standardized diagnosis and treatment according to the guidelines. Finally， full-process participation of multidisciplinary experts is encouraged to ensure the comprehensiveness and scientificity of the study. In conclusion， the application of this model will contribute to the development of TCM guidelines responsive to the needs of clinical practice and achieve the goal of promoting the homogenization of TCM clinical diagnosis and treatment.

As a supplement to randomized controlled trials， observational studies can provide evidence for the effectiveness of traditional Chinese medicine （TCM） treatment measures. They can also study influencing factors of diseases， etiology， and prognosis. However， there is a confounding effect due to the lack of randomization， which seriously affects the causal inference between the study factors and the outcome， resulting in confounding bias. Therefore， identifying and controlling confounding factors are key issues to be addressed in TCM observational studies. According to the causal network and the characteristics of TCM theory， confounding factors can be categorized into measured and unmeasured confounding factors. In addition， attention must be paid to identifying confounding factors and intermediate variables， as well as the interaction between confounding factors and study factors. For methods of controlling confounding factors， measured confounding factors can be controlled by stratification， multifactor analysis， propensity scores， and disease risk scores. Unmeasured and unknown confounding factors can be corrected using instrumental variable methods， difference-in-difference methods， and correction for underlying event rate ratios. Correcting and controlling confounding factors can ensure a balance between groups， and confounding bias can be reduced. In addition， methods such as sensitivity analysis and determination of interactions make the control of confounding factors more comprehensive. Due to the unique characteristics of TCM， observational studies of TCM face unique challenges in identifying and controlling confounding factors， including the ever-changing TCM treatment measures received by patients， the often-overlooked confounding effects in the four diagnostic information of TCM， and the lack of objective criteria for TCM evidence-based diagnosis. Some scholars have already conducted innovative explorations to address these issues， providing a methodological basis for conducting higher-quality TCM observational studies， so as to obtain more rigorous real-world evidence of TCM and gradually develop quality evaluation criteria for OS that are consistent with the characteristics of TCM.

ObjectTo explore the risk factors related to the intensity of post-stroke depression in patients with cerebral infarction during hospitalization in the rehabilitation department. MethodsThe hospital consultation records of cerebral infarction patients in Beijing Bo'ai Hospital from December, 2019 to February, 2023 were reviewed from the hospital information system, and those who were diagnosed as depression visited the department of psychology were selected. It was collected including general information of sexes, ages, education levels, matrimony; medical features of course, location, affected side, sensory disorders, aphasia, agrypnia, dysphagia, hand-shoulder syndrome, constipation; functioning of muscle strength and Brunnstrom stages; and scores of Mini-Mental State Examination (MMSE), National Institutes of Health Stroke Scale (NIHSS), Fugl-Meyer Assessment (FMA), Fugl-Meyer Assessment-Balance (FMA-B), modified Barthel Index (MBI) and Hamilton Depression Scale (HAMD). Patients with HAMD scores ≤ 20 were as the low group, and those > 20 were as the high group. ResultA total of 2 403 hospitalized stroke patients were included, out of which 269 patients with cerebral infarction were diagnosed as depression and visited the department of psychology; while 103 cases were in the low group and 166 cases were in the high group. The incidence of constipation was less, and the incidence of dysphagia and shoulder-hand syndrome was higher in the high group (χ² > 5.379, P < 0.05), with weaker strength of iliopsoas muscle and quadriceps muscle, earlier of Brunnstrom stage of lower extremities and hands, and worse scores of NIHSS, MMSE, FMA, FMA-B and MBI (|Z| > 2.020, t > 2.171, P < 0.05). Logistic regression showed that constipation (OR = 0.435), quadriceps muscle strength (OR = 0.782) and dysphagia (OR = 2.602) related to the intensity of post-stroke depression in convalescent patients (P < 0.05). ConclusionPost-stroke dysphagia and poor quadriceps muscle strength may exacerbate post-stroke depression; however, constipation may not.

OBJECTIVE To provide a detailed report and interpretation of the method and results for determining the weights of the technical indicators from the “multi-dimensional and multi-criteria comprehensive evaluation index system （first edition）” stated in Guideline for Multi-dimensional and Multi-criteria Comprehensive Evaluation of Chinese Patent Medicine. METHODS Normalization calculations were performed on the comprehensive weight values calculated by the analytic hierarchy process and expert weighting method to obtain the objective weights of the indicators. RESULTS The weight results of the six primary dimensions in the current comprehensive evaluation indicator system of Chinese patent medicine showed effectiveness dimension＞ safety dimension＞standard dimension＞application dimension＞scientific dimension＞economic dimension， with weight values of 0.281 0， 0.268 5， 0.195 8， 0.107 3， 0.096 1 and 0.051 3 respectively， consistent with the results of most researches currently. CONCLUSIONS The process of weight determination in this indicator system is scientifically reasonable， with clear methods and clear interpretations， and is worthy of further optimization and widespread application.