The alternative pathway (AP) of the complement system is a key contributor to the pathogenesis of several diseases including paroxysmal nocturnal hemoglobinuria (PNH), atypical hemolytic uremic syndrome (aHUS), C3 glomerular disease (C3G) and age-related macular degeneration (AMD). Complement factor B (CFB) is a trypsin-like serine protein that circulates in the human bloodstream in a latent form. As a key node of the alternative pathway, it is an important target for the treatment of diseases mediated by the complement system. With the successful launch of iptacopan, the CFB small molecule inhibitors has become a current research hotspot, a number of domestic and foreign pharmaceutical companies are actively developing CFB small molecule inhibitors. In this paper, the research progress of CFB small molecule inhibitors in recent years is systematically summarized, the representative compounds and their activities are introduced according to structural types and design ideas, so as to provide reference and ideas for the subsequent research on CFB small molecule inhibitors.

BackgroundDepression has become a public health concern that affects the physical and mental health of college students. acute stress response is a risk factor of depression. Exploring the relationship and mechanism between acute stress response and depression is of great significance for preventing and intervening depression in college students. ObjectiveTo examine the relationship between acute stress response and depression among college students， and to analyze the mediating role of rumination and the moderated effect of perceived social support， so as to provide references for the prevention and intervention of depression in college student . MethodsFrom March to April 2020， a cluster sampling method was employed to select 1 355 college students from three universities in Hubei， Jiangxi and Guangxi Zhuang Autonomous Region. Participants were assessed with Acute Stress Disorder Scale （ASDS）， Ruminative Responses Scale （RRS）， Brief form of Perceived Social Support Questionnaire （F-SozU） and Patients' Health Questionnaire Depression Scale-9 item （PHQ-9）. Pearson correlation analysis was adopted to examine the correlation between the scores of each scale. The mediating role of rumination between acute stress response and depression and the moderated role of perceived social support were examined respectively by using Model 4 and Model 14 in Macro Program Process 3.3. ResultsA total of 1 303 valid questionnaires were collected， yielding a valid response rate of 96.16%. The results of Pearson correlation analysis showed that ASDS score was positively correlated with RRS score and PHQ-9 score （r=0.649， 0.528， P<0.01） among college students. The mediation analysis results demonstrated that rumination played a partial mediating role between acute stress response and depression， with the mediating effect value of 0.273 （95% CI：0.222~0.328）， accounting for 68.59% of the total effect. Perceived social support played a moderated role in the latter path of the mediation model （rumination → depression） （β=-0.004， 95% CI： -0.017~-0.004， P<0.01）. ConclusionRumination played a partial mediating role between acute stress response and depression in college students， and perceptive social support played a moderated role between rumination and depression. ［Funded by Scientific Research Fund Project of Education Department of Yunnan Province （number， 2025J0437）］

The rapid development of artificial intelligence (AI), especially generative AI (GenAI), has already brought, and will continue to bring, revolutionary changes to our daily production and life, as well as create new opportunities and challenges for diagnostic and therapeutic practices in the medical field. Haihe Hospital of Tianjin University collaborates with the National Supercomputer Center in Tianjin, Tianjin University, and other institutions to carry out research in areas such as smart healthcare, smart services, and smart management. We have conducted research and development of a full-process disease diagnosis and treatment assistance system based on GenAI in the field of smart healthcare. The development of this project is of great significance. The first goal is to upgrade and transform the hospital's information center, organically integrate it with existing information systems, and provide the necessary computing power storage support for intelligent services within the hospital. We have implemented the localized deployment of three models: Tianhe "Tianyuan", WiNGPT, and DeepSeek. The second is to create a digital avatar of the chief physician/chief physician's voice and image by integrating multimodal intelligent interaction technology. With generative intelligence as the core, this solution provides patients with a visual medical interaction solution. The third is to achieve deep adaptation between generative intelligence and the entire process of patient medical treatment. In this project, we have developed assistant tools such as intelligent inquiry, intelligent diagnosis and recognition, intelligent treatment plan generation, and intelligent assisted medical record generation to improve the safety, quality, and efficiency of the diagnosis and treatment process. This study introduces the content of a full-process disease diagnosis and treatment assistance system, aiming to provide references and insights for the digital transformation of the healthcare industry.
Artificial Intelligence ; Humans ; Delivery of Health Care ; Generative Artificial Intelligence

Gastric cancer with peritoneal metastasis (GCPM) is a common and lethal manifestation of advanced gastric cancer, with a median survival of only 5-11 months. This consensus was developed by 30 experts from Asia (China, Japan, Korea, and Singapore) using the Delphi method and the GRADE evidence grading system. A total of 29 statements were formulated, covering the diagnosis and assessment of GCPM, indications for laparoscopic exploration and NIPS (normothermic intraperitoneal and systemic treatment), treatment regimens, prevention and management of complications, criteria for conversion surgery, and postoperative intraperitoneal therapy. The consensus aims to standardize clinical practice and improve the prognosis of patients with GCPM.

The liver,as the core metabolic organ of the human body,undertakes multiple critical physiological functions such as protein synthesis,xenobiotic metabolism,and immune regulation.Liver failure represents a major disease process in patients with end-stage liver disease,characterized clinically by coagulopathy,abnormal bilirubin metabolism,and multiple organ dysfunction.Depending on the disease course,liver failure can be classified into four types:acute,subacute,acute-on-chronic,and chronic.The pathogenic mechanisms are complex,involving interactions among various factors such as pathogen infections,dysregulation of the immune microenvironment,and gut microbiota disturbances,which pose significant challenges for clinical diagnosis and treatment.This review summarizes the abnormalities in innate and adaptive immune responses,as well as the molecular mechanisms of immune metabolic dysregulation during the occurrence and progression of liver failure.It further explores the pivotal role of immune cell dysfunction in the disease process,aiming to provide a theoretical basis for targeted immune therapies in liver failure.

Exosomes are extracellular vesicles that regulate various signaling pathways in the body by mediating the release of proteins, nucleic acids and lipids, thus playing an important role in pathophysiological processes such as inflammation, tumor, immunity and nervous system. More and more studies have shown that exosomal non-coding RNA (ncRNA) plays a crucial role in pancreatic diseases. This article reviews the role of exosome ncRNA in the occurrence, diagnosis and treatment of pancreatic diseases such as acute pancreatitis and pancreatic cancer, in order to provide a reference for clinical practice.

AIM To explore the effects of Buyang Huanwu Decoction on mitochondrial oxidative damage and PKCε-Nampt pathway in rats following cerebral ischemia reperfusion(I/R).METHODS The rats were randomly divided into the sham operation group,the model group,Buyang Huanwu Decoction group(14.3 g/kg)and edaravone group(3 mg/kg).Except those of the sham operation group,SD rats of other groups were induced into models of brain I/R injury by MCAO method,followed by corresponding drug administration 24 hours after operation.After 7 days of administration,the rats had their neurological deficit evaluated by neurological function scoring;thier expression of neuron marker MAP-2 detected by immunofluorescence staining;their neuron damage observed and the oxidative damage evaluated through assessment of their ROS levels and MDA and SOD activities;their changes of mitochondrial membrane potential detected by fluorescent probe JC-1;their ratio of NAD+/NADH detected using modified enzyme circulation method;their expressions of PKCε,p-PKCε and Nampt proteins detected with Western blot;and their positive expressions of p-PKCε and Nampt proteins detected with immunohistochemistry method.RESULTS Compared with the model group,Buyang Huanwu Decoction group shared decreased cerebral infarction volume and neurological function score(P<0.05);increased cerebral fluorescence intensity of MAP-2(P<0.05);reduced neuronal damage,decreased cerebral levels of ROS and MDA(P<0.05);increased SOD activity,mitochondrial membrane potential and NAD+/NADH ratio(P<0.05);and increased protein expressions of p-PKCε and Nampt(P<0.05).CONCLUSION Buyang Huanwu Decoction can improve mitochondrial function and reduce brain I/R injury in rats by activating their PKCε-Nampt signaling pathway.

Aim To explore the impacts of high mobility group box 1 (HMGB1) on the phenotypes, endocy-tosis and extracellular signal-regulated kinase (ERK)/ Jun N-terminal protein kinase (JNK)/P38 mitogen-ac-tivated protein kinase (MAPK) signaling pathway in indoxyl sulfate (IS) -induced dendritic cells (DCs). Methods After treatment with 30, 300 and 600 (xmol · L

Objective:To investigate the diagnostic value of an intelligent assisted grading algorithm for nuclear cataract using anterior segment optical coherence tomography (AS-OCT) images.Methods:A diagnostic test study was conducted.AS-OCT image data were collected from 939 cases of 1 608 eyes of nuclear cataract patients at the Shanghai Tenth People's Hospital of Tongji University from November 2020 to September 2021.The data were obtained from the electronic case system and met the requirements for clinical reading clarity.Among them, there were 398 cases of 664 male eyes and 541 cases of 944 female eyes.The ages of the patients ranged from 18 to 94 years, with a mean age of (65.7±18.6) years.The AS-OCT images were labelled manually from one to six levels according to the Lens Opacities Classification System Ⅲ (LOCS Ⅲ grading system) by three experienced clinicians.This study proposed a global-local cataract grading algorithm based on multi-level ranking, which contains five basic binary classification global local network (GL-Net).Each GL-Net aggregates multi-scale information, including the cataract nucleus region and original image, for nuclear cataract grading.Based on ablation test and model comparison test, the model's performance was evaluated using accuracy, precision, sensitivity, F1 and Kappa, and all results were cross-validated by five-fold.This study adhered to the Declaration of Helsinjki and was approrved by Shanghai Tenth People's Hospital of Tongji University (No.21K216).Results:The model achieved the results with an accuracy of 87.81%, precision of 88.88%, sensitivity of 88.33%, F1 of 88.51%, and Kappa of 85.22% on the cataract dataset.The ablation experiments demonstrated that ResNet18 combining local and global features for multi-level ranking classification improved the accuracy, recall, specificity, F1, and Kappa metrics.Compared with ResNet34, VGG16, Ranking-CNN, MRF-Net models, the performance index of this model were improved.Conclusions:The deep learning-based AS-OCT nuclear cataract image multi-level ranking classification algorithm demonstrates high accuracy in grading cataracts.This algorithm may help ophthalmologists in improving the diagnostic accuracy and efficiency of nuclear cataract.