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

Objective To discuss the effect of multidisciplinary family empowerment mode in home care for patients after receiving percutaneous endoscopic gastrostomy(PEG).Methods A total of 86 patients,who received initial PEG at the Jilin Provincial Cancer Hospital of China from January 2021 to July 2023,were selected for this study.The patients were randomly divided into observation group.The patients of the control group received routine nursing guidance for gastrostomy,while the patients of the observation group received multidisciplinary family empowerment nursing mode.The self-care ability[using self-care ability scale of the elderly(SASE)score],health behavior ability[using self-rating scale of health behavior ability(SRAHP)score],incidence of complications,and healing time of complications were compared between the two groups.Results In the observation group the SASE[(129.48±5.48)points vs.(73.05±12.04)points]and the SRAHP[(80.14±1.00)points vs.(70.25±7.92)points]were significantly higher than those in the control group(all P＜0.05),the incidence of complications was lower than that in the control group,and the healing time of complications was shorter than that in the control group.Conclusion The implementation of multidisciplinary family empowerment nursing mode can improve the self-care ability and health behavior ability of patients after receiving PEG,reduce postoperative complications,as well as shorten the healing time of complications,therefore,this nursing mode is suitable for home patients after receiving PEG.

Objective·To develop physiologically based pharmacokinetic(PBPK)models specifically designed for the Chinese population by utilizing the combination of clozapine and fluvoxamine as a case,and predict the drug-drug interaction(DDI)associated with the combination medication of clozapine,ultimately optimizing the dosage of clozapine.Methods·By obtaining the physicochemical parameters,absorption,distribution,metabolism,excretion(ADME)-related parameters,and physiologically relevant parameters of the Chinese population through literature and pharmacology-related databases,PBPK models for the clozapine and fluvoxamine were constructed by using PK-Sim? software.The models' accuracy was evaluated by comparing predicted values of the area under the curve(AUC)and peak concentration(Cmax)to observed data,using the mean percentage error(MPE)and mean absolute percentage error(MAPE)as evaluation indicators.The models were validated against real-world plasma drug concentration data.Additionally,combining the inhibitory effect of fluvoxamine on clozapine,models for the combination therapy of clozapine and fluvoxamine were developed to predict the pharmacokinetic changes of clozapine.The presence of clinically significant DDI was determined by using the 90%confidence interval of the AUC ratio(AUCR)or Cmax ratio(CmaxR)as evaluation metrics,with a non-effect boundary set at 80%?125%.The pharmacokinetic changes of clozapine upon co-administration with fluvoxamine based on PBPK models were quantified,and a dosage optimization for clozapine was developed.Results·The constructed model of clozapine and fluvoxamine was considered accurate if the absolute value of the MPE was≤10%and the MAPE was<25%during validation,indicating that the predicted concentration-time curves were accurate.The PBPK model for the co-administration of clozapine and fluvoxamine was able to accurately predict pharmacokinetic parameters if the ratio of predicted AUC to observed AUC was within 1.25.The prediction of PBPK model for the co-administration showed that the 90%confidence intervals for AUCR and CmaxR of the combination therapy of clozapine and fluvoxamine were not entirely within the ineffective effect boundary,indicating a clinically significant DDI when these two drugs were used concomitantly.Moreover,the dose optimization according to the PBPK models indicated that when subjects were co-administered with clozapine and fluvoxamine,reducing the dose of clozapine to 50%of the original dose could maintain the exposure levels of clozapine consistent with monotherapy.Conclusion·The established PBPK model can effectively simulate the impact of combination therapy on pharmacokinetic changes of clozapine,providing valuable insights for predicting potential DDI and optimizing dosage regimens.If clozapine needs to be co-administered with fluvoxamine during the treatment,clinicians should remain vigilant for clinically significant DDI and contemplate optimizing the dosage of clozapine accordingly.

Leonurine(SCM-198)was discovered as one of the active constituents of the Herba Leonuri(HL).Now it can be artificially synthesized.Several recent researches has proven that it exhibits anti-inflammatory effect in several systems in animal models and cell culture in vitro.The key mechanism involves downgrading the activity of nuclear transcription factor-κB(NF-κB),thereby inhibiting the phosphorylation of several signal pathways such as PI3K/Akt,MAPK,ERK,and JNK,or upregulating the activity of Nrf2 related pathways,resulting in downregulated expression of inflammatory cytokines such as tumor necrosis factor-α(TNF-α),IL-1β,IL-2,IL-6,IL-8,inducible nitric oxide synthase(iNOS),cyclooxygenase-2(COX-2),chemokines,adhesion molecules,etc.Owing to the advantages of high safety and efficiency,the ease of administration,as well as its effectiveness in many organs and systems,leonurine has a widely prospect for future research and clinical applications.This article reviews the progress in the fundamental research of leonurine in multiple inflammation-related disease,and it could be expect to offer new possibilities for the treatment of these disease.

Objective To investigate the prediction of diffusion kurtosis imaging(DKI)and intra voxel incoherent motion(IVIM)imaging global histogram parameters for the efficacy of neoadjuvant chemotherapy(NAC)in patients diagnosed with breast invasive ductal carcinoma.Methods A total of 69 patients with breast invasive ductal carcinoma confirmed by penetration pathology were retrospectively selected.Prior to undergoing NAC,all patients underwent sequential scans including MR conventional(T1WI,T2WI),dynamic contrast enhancement(DCE),DKI,and IVIM.After surgery,the patients were divided into significant group(40 patients)and non-significant group(29 patients)based on the efficacy of NAC,which was evaluated using the Miller-Payne(MP)grading method criteria.The differences in global histogram parameters of DKI[mean diffusivity(MD),mean kurtosis(MK)]and IVIM(D value,f value,D*value)between the significant group and the non-significant group were compared by the two-independent sample t-test and Mann-Whitney U test.In addition,the receiver operating characteristic(ROC)curve was plotted,and Spearman rank correlation analysis was used to evaluate the diagnostic efficacy and correlation of DKI and IVIM global histogram parameters in predicting NAC efficacy.The DeLong test was used to compare whether there was statistical significance in area under the curve(AUC)differences among histogram parameters.Results The DKI MD value(90th percentile,mean,median,maximum,range,root mean square),IVIM D value(mean,range,root mean square,median)and D*value(entropy,90th percentile)of patients with breast invasive ductal carcinoma in the significant group with efficacy of NAC were higher than those in the non-significant group,while the DKI MK value(mean and median)were lower than those in the non-significant group,and all the differences mentioned above were statistically significant(P＜0.05).The AUC,sensitivity and specificity of DKI combined with IVIM global histogram parameters were the highest,which were 0.816,72.41％and 90.00％,respectively.MD value,D value and D*value were negatively correlated with the efficacy of NAC in breast invasive ductal carcinoma.MK value was positively correlated with NAC efficacy significance.Conclusion DKI combined with IVIM global histogram parameters can effectively predict the efficacy of NAC in patients with breast invasive ductal carcinoma and provide effective value for clinical NAC preoperative efficacy evaluation.

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.