The research and development of innovative drug have progressed remarkably, but the long development circle and high failure rate have become the bottleneck. Drug repurposing, discovering new indications of approved drugs, is a strategy to overcome these obstacles. By exploring new indications for approved drugs, rapid progress has been made in basic research and clinical translation in recent years. Rich resources of drugs, proven security, efficient development workflow and reduced cost are core advantages of this strategy, making the strategy a crucial direction of optimizing the pipeline of drug research and development. This review systematically summarizes drug repurposing cases that have received clinical approval over the past five years, and proposes core strategies for drug repurposing, including approaches based on targets, pathways, drug similarity, post-treatment phenotypes, and clinical side effects, aiming to provide some strategic guidance for drug repurposing efforts.

Flap transplantation is a critical surgical strategy for the reconstruction of tissue defects caused by trauma, tumor resection, and congenital malformations, and its survival rate directly determines surgical efficacy and patient prognosis. Following transplantation, flaps inevitably undergo ischemia-reperfusion (I/R) injury, during which oxidative stress, inflammatory responses, and metabolic disturbances are intricately intertwined, ultimately leading to cellular injury and tissue necrosis. Recent studies have demonstrated that multiple forms of programmed cell death—including apoptosis, pyroptosis, ferroptosis, necroptosis, and PANoptosis—play central roles in flap I/R injury. The extensive crosstalk and molecular interactions among these pathways form a highly complex cell death network. Specifically, apoptosis is mediated by the imbalance of Bcl-2 family proteins and the activation of cysteine-dependent aspartate-specific protease (caspase) cascades; pyroptosis is driven by the NLRP3-caspase-1-GSDMD axis, resulting in membrane pore formation and the release of pro-inflammatory cytokines; ferroptosis is characterized by iron-dependent lipid peroxidation and dysfunction of glutathione peroxidase 4 (GPX4); necroptosis is triggered by the receptor-interacting serine/threonine-protein kinase 1 (RIPK1)-RIPK3-MLKL signaling complex, leading to membrane rupture; and PANoptosis represents an integrated form of inflammatory cell death that coordinates multiple death pathways. Importantly, these forms of programmed cell death are not independent but are interconnected through extensive signaling crosstalk. Key regulatory molecules, including caspase-8, reactive oxygen species (ROS), nuclear factor-κB (NF-κB), and nuclear factor erythroid 2-related factor 2 (Nrf2), collectively modulate the dynamic balance among these pathways. Therefore, the multidimensional interplay and spatiotemporal dynamics of programmed cell death constitute a fundamental pathological basis of flap I/R injury. This review systematically summarizes the latest advances in the mechanisms and interactions of various programmed cell death pathways in flap I/R injury, aiming to elucidate the underlying regulatory network. These insights may provide novel theoretical foundations for optimizing flap protection strategies, improving flap survival, and promoting tissue repair.

Objective:Ménière's disease（MD） is a common disorder of the inner ear. The fluctuating clinical symptoms and the absence of gold standards for diagnosis have posed serious problems for clinical diagnosis and treatment over the years. With the development of science and technology, artificial intelligence （AI） has been widely used in the field of medicine, and the potential of AI application to MD is demonstrated. The purpose of this review is to outline the use of AI in MD. Initially, specific instances where AI aids in differentiating MD from other causes of vertigo are presented. Furthermore, the role of AI in the evaluation of Endolymphatic Hydrops （EH）, particularly through imaging and biochemical assays, is highlighted due to its correlation with MD. Additionally, the effectiveness of AI in managing MD patients and forecasting disease progression is examined. In conclusion, the prevalent challenges hindering the clinical integration of AI in MD treatment are discussed, alongside potential strategies to surmount these barriers.
Humans ; Meniere Disease/diagnosis* ; Artificial Intelligence ; Endolymphatic Hydrops/diagnosis*

To analyze potential adverse drug events(ADEs) associated with ustekinumab and upadacitinib in the treatment of inflammatory bowel disease(IBD) based on an international authoritative database, thereby providing evidence for clinical medication safety.

BackgroundGraduate students frequently face life events， many of which may adversely affect their mental well-being. However， the interaction between life events and the development of depression， anxiety， and somatic symptoms remains unclear. ObjectiveTo explore the relationship between life events and the development of depressive， anxiety and somatic symptoms in graduate students， thereby informing prevention strategies for these conditions. MethodsA sample of 6 722 newly enrolled graduate students at a comprehensive university in Southwest China from September to November 2018 was selected. The assessment was conducted using the Adolescent Self-rating Life Events Checklist （ASLEC）， the 7-item Generalized Anxiety Disorder scale-7 item （GAD-7）， the Patient Health Questionnaire Depression Scale-9 item （PHQ-9）， and the Patient Health Questionnaire-15 （PHQ-15）. Network analysis was implemented by using the bootnet and qgraph packages in the R software （version 4.2.3）， with centrality indices calculated to identify core and bridge symptoms within the network. ResultsThe study encompassed a total of 6 171 graduate students， representing 91.80% of the target population. The prevalence rates of anxiety， depressive， and somatic symptoms among graduate students were 12.59% （777/6 171）， 16.63% （1 026/6 171）， and 27.66% （1 707/6 171）， respectively. Network analysis revealed that 'academic stress' was the core symptom with the highest strength and expected influence （both values=1.207）， while 'feeling down， depressed， or hopeless' was the bridge symptom with the highest bridge strength and bridge expected influence （both values=0.454）. There was no significant difference in global network strength and edge weight between women and men （P>0.05）. ConclusionAcademic stress， emerging as the core symptom， assumes a dominant position within the symptom network and exhibits strong interactions with other negative affective states. There was no gender difference in the network structure.

To analyze the distribution of serotypes and antimicrobial resistance of clinical Salmonella isolates from multiple centers across China.