This paper outlines the development of artificial intelligence （AI） and its applications in traditional Chinese medicine （TCM） research， and elucidates the roles and advantages of large language models， knowledge graphs， and natural language processing in advancing syndrome identification， prescription generation， and mechanism exploration. Using spleen-stomach diseases as an example， it demonstrates the empowering effects of AI in classical literature mining， precise clinical syndrome differentiation， efficacy and safety prediction， and intelligent education， highlighting an upgraded research paradigm that evolves from data-driven and knowledge-driven approaches to intelligence-driven models. To address challenges related to privacy protection and regulatory compliance in cross-institutional data collaboration， a "trusted federated evidence-based analysis platform for TCM spleen-stomach diseases" is proposed， integrating blockchain-based smart contracts， federated learning， and secure multi-party computation. The deep integration of AI with privacy-preserving computing is reshaping research and clinical practice in TCM spleen-stomach diseases， providing feasible pathways and a technical framework for building a high-quality， trustworthy TCM big-data ecosystem and achieving precision syndrome differentiation.

ObjectiveTo investigate the efficacy of sequential tenofovir alafenamide fumarate （TAF） therapy versus the regimen of entecavir （ETV） combined with TAF in chronic hepatitis B （CHB） patients experiencing low-level viremia （LLV） after ETV therapy， as well as their impact on virologic response， liver and renal function， and blood lipid levels. MethodsA total of 217 CHB patients with LLV after ETV treatment who were admitted to Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine from May 2020 to December 2023 were enrolled， and according to the treatment regimen， they were divided into TAF group （180 patients receiving sequential TAF therapy） and combined group （37 patients receiving ETV+TAF therapy）. The propensity score matching （PSM） method was used to match the patients at a ratio of 1∶1， and finally 37 patients were included in each group to balance the baseline confounding factors. The two groups were compared in terms of hepatitis B virus DNA （HBV DNA） clearance rate， hepatitis B envelope antigen （HBeAg） clearance rate， liver and renal function parameters （liver stiffness measurement ［LSM］， platelet count ［PLT］， aspartate aminotransferase ［AST］， alanine aminotransferase ［ALT］， and creatinine ［Cr］）， blood lipid levels （total cholesterol ［TC］， triglyceride ［TG］， high-density lipoprotein cholesterol ［HDL-C］， and low-density lipoprotein cholesterol ［LDL-C］）， and the incidence rate of adverse reactions. The independent samples t-test was used for comparison of normally distributed continuous data between two groups， and the paired t-test was used for comparison within each group； the chi-square test was used for comparison of categorical data between groups. ResultsAfter 48 weeks of treatment， compared with the TAF group， the combined group had significantly higher HBV DNA clearance rate （86.49% vs 59.46%， χ²=6.852， P=0.009） and HBeAg clearance rate （59.46% vs 35.14%， χ²=4.391， P=0.036）. After treatment， compared with the TAF group， the combined group had significantly lower levels of LSM （7.01±1.50 kPa vs 7.90±1.68 kPa， t=2.404， P=0.019）， AST （18.02±2.28 U/L vs 21.12±2.85 U/L， t=5.166， P<0.001）， and ALT （19.85±3.86 U/L vs 22.00±3.90 U/L， t=2.383， P=0.020） and significantly higher levels of PLT ［（218.35±42.60）×10⁹/L vs （192.82±44.13）×10⁹/L， t=2.532， P=0.014］ and Cr （70.92±6.54 μmoL/L vs 67.60±6.13 μmoL/L， t=2.253， P=0.027）. After treatment， there was a slight increase in the level of TC in both the TAF group （5.60±0.89 mmol/L vs 5.18±0.85 mmol/L， t=2.076， P=0.041） and the combined group （5.45±0.80 mmol/L vs 5.02±0.83 mmol/L， t=2.269， P=0.026）. There was no significant difference in the incidence rate of adverse reactions between the TAF group and the combined group （21.62% vs 18.92%， χ²=0.084， P=0.772）. ConclusionFor ETV-treated CHB patients experiencing LLV， compared with sequential TAF therapy， the ETV+TAF combined therapy can effectively increase virologic response rate， alleviate liver fibrosis， and improve liver function， whereas sequential TAF therapy has less impact on renal function. Sequential or combined therapy with TAF may induce a slight increase in the level of TC， which should be taken seriously in clinical practice.

Digital government refers to the wide application of digital technology in government management and services, promoting the optimization of government governance processes, model innovation, and performance enhancement, and building a new form of digital and intelligent government operation. Laboratory animal management is an important national foundational and strategic support work. It is closely related to digital government construction, and is not only an important part of digital government construction but also a typical application of government digital transformation in the field of science and technology. Digital transformation empowering laboratory animal management is a new proposition of government governance in the digital age, and research on its systematic and holistic reform is crucial. Through digital technologies such as artificial intelligence, big data, and cloud computing, the government can optimize approval process, strengthen in-process and post-event supervision, and promote regional coordination, thereby improving laboratory animal management capacity and service levels. In addition, laboratory animal data sharing contributes to government scientific decision-making and industry supervision. This article summarizes the experience and practices of domestic leading regions in recent years, reviews the background and development process of digital transformation of laboratory animal management in Jiangsu Province, describes the current status of such digital transformation in Jiangsu Province across areas including digital infrastructure, data sharing, and government services, analyzes existing challenges in top-level design, data governance, and data sharing, and, focusing on institutional mechanisms, government functions, data governance, and support systems, puts forward corresponding transformation ideas, frameworks, and pathways and provides an outlook. Thereby it provides a reference for the high-quality development of laboratory animal management in Jiangsu Province and other regions.

Objective To analyze the predictive value of different obesity indicators on acute cerebral infarction in patients with transient ischemic attack (TIA). Methods A total of 310 patients with TIA admitted to Tangdu Hospital of Air Force Medical University from March 2022 to September 2025 were selected and classified into non-event group (276 cases) and cerebral infarction group (34 cases) based on acute cerebral infarction within 90 days. The basic data and obesity-related indicators [body mass index (BMI), waist-to-hip ratio, body adiposity index (BAI), conicity index (C-index) and a body shape index (ABSI were compared. Multivariate logistic regression analysis was utilized to screen the independent influencing factors. Receiver operating characteristic (ROC) curve was drawn to analyze the predictive efficiency. Results The age, proportions of concurrent hypertension and concurrent diabetes mellitus, ABCD2 score, waist-to-hip ratio, ABSI, C-index, BMI and BAI in the cerebral infarction group were older or higher than those in the non-event group, and the symptoms duration was longer (P<0.05). The above indicators were all related factors for acute cerebral infarction in patients with TIA within 90 days (P<0.05), and ABSI and ABCD² score were independent influencing factors (P<0.05). The prediction model was manifested as Logit (P)=− 4.205 + 0.482 × ABCD² score + 1.120 × ABSI × 100. ABSI and ABCD2 score had predictive value on the occurrence of acute cerebral infarction (P<0.05), and the predictive efficiency of combined model was higher than that of single indicator (P<0.05). Conclusion Among different obesity indicators, ABSI has the highest value on predicting recent acute cerebral infarction in TIA. The prediction model based on ABSI and ABCD2 score exhibits the best predictive efficiency.

Real-time, noninvasive programmed death-ligand 1 (PD-L1) testing using molecular imaging has enhanced our understanding of the immune environments of neoplasms and has served as a guide for immunotherapy. However, the utilization of radiotracers in the imaging of human brain tumors using positron emission tomography/computed tomography (PET/CT) remains limited. This investigation involved the synthesis of [¹⁸F]AlF-NOTA-PCP2, which is a novel peptide-based radiolabeled tracer that targets PD-L1, and evaluated its imaging capabilities in orthotopic glioblastoma (GBM) models. Using this tracer, we could noninvasively monitor radiation-induced PD-L1 changes in GBM. [¹⁸F]AlF-NOTA-PCP2 exhibited high radiochemical purity (>95%) and stability up to 4 h after synthesis. It demonstrated specific, high-affinity binding to PD-L1 in vitro and in vivo, with a dissociation constant of 0.24 nM. PET/CT imaging, integrated with contrast-enhanced magnetic resonance imaging, revealed significant accumulation of [¹⁸F]AlF-NOTA-PCP2 in orthotopic tumors, correlating with blood-brain barrier disruption. After radiotherapy (15 Gy), [¹⁸F]AlF-NOTA-PCP2 uptake in tumors increased from 9.51% ± 0.73% to 12.04% ± 1.43%, indicating enhanced PD-L1 expression consistent with immunohistochemistry findings. Fractionated radiation (5 Gy × 3) further amplified PD-L1 upregulation (13.9% ± 1.54% ID/cc) compared with a single dose (11.48% ± 1.05% ID/cc). Taken together, [¹⁸F]AlF-NOTA-PCP2 may be a valuable tool for noninvasively monitoring PD-L1 expression in brain tumors after radiotherapy.

Infectious keratitis (IK) is a leading cause of blindness worldwide, primarily resulting from improper contact lens use, trauma, and a compromised immune response. The pathogenic microorganisms responsible for IK include bacteria, fungi, viruses, and Acanthamoeba. This review examines standard therapeutic agents for treating IK, including broad-spectrum empiric antibiotics for bacterial keratitis (BK), antifungals such as voriconazole and natamycin for fungal infections, and antiviral nucleoside analogues for viral keratitis (VK). Additionally, this review discusses therapeutic agents, such as polyhexamethylene biguanide (PHMB), for the treatment of Acanthamoeba keratitis (AK). The review also addresses emerging drugs and the challenges associated with their clinical application, including anti-biofilm agents that combat drug resistance and nuclear factor kappa-B (NF-κB) pathway-targeted therapies to mitigate inflammation. Furthermore, methods of Photodynamic Antimicrobial Therapy (PDAT) are explored. This review underscores the importance of integrating novel and traditional therapies to tackle drug resistance and enhance drug delivery, with the goal of advancing treatment strategies for IK.