Renal lymphatic vessel density is clinically relevant in kidney disease but is still assessed by slow, subjective visual estimation. We evaluated a weakly supervised, attention-based multiple-instance learning framework for automated detection and quantification of renal lymphatic vessel density on D2-40-stained whole-slide images (WSIs). Methods: Two independent internal datasets from Tongji Hospital were collected, including 198 cases of chronic kidney disease (CKD) and 50 cases of hypertensive nephropathy (HTN). All biopsies were immunohistochemically stained for D2-40 and digitized as WSIs. Pathologists provided only slide-level labels (D2-40 high vs. D2-40 low). Tissue regions were automatically segmented, tiled into patches, and encoded using a pretrained convolutional neural network. Patch embeddings were then analyzed with a clustering-constrained attention multiple-instance learning (CLAM) model. Unlike conventional multiple-instance learning (MIL) methods that only weight instances, CLAM jointly performs attention-based instance selection and instance-level clustering to distinguish positive from negative evidence within each slide, yielding more discriminative slide-level features and interpretable attention maps. Performance was compared with a classic MIL model trained on the same features. Results: CLAM achieved area under the receiver operating characteristic curves of 0.942 and 0.858 on the CKD and HTN datasets, respectively, outperforming classic MIL (0.866 and 0.801). Attention maps highlighted lymphatic-rich regions consistent with renal pathologists’ assessments. Conclusions: This clustering-constrained, attention-based weakly supervised framework enables fully automated, reproducible quantification of renal lymphatic vessel density from WSIs, providing renal pathologists with rapid visual and numerical support for diagnosis and risk stratification in CKD and HTN.

Background/Aims: Dysregulated cholesterol metabolism is a hallmark of hepatocellular carcinoma (HCC) that drives tumor initiation and progression. However, clinical targeting of cholesterol metabolism has yielded limited benefits due to stringent feedback in tumor cells. Identifying a central mediator capable of restoring cholesterol homeostasis within the cell’s intrinsically fine-tuned regulatory framework is urgently needed. Methods: We integrated a proteomic dataset from patients with cholesterol-dysregulated HCC into a global cholesterol metabolic regulatory network to identify potential therapeutic targets for disrupted cholesterol homeostasis. The prognostic significance of the candidate targets was further validated in an independent cohort through immunohistochemistry. Functional and mechanistic studies were conducted in vitro using HCC cell lines and in vivo using mouse models. The pharmacological efficacy of the candidate agent was evaluated in both subcutaneous and orthotopic HCC mouse models. Results: ER lipid raft-associated 1 (ERLIN1), a pivotal regulator of cholesterol metabolism reprogramming, was identified as an independent favorable prognostic indicator in HCC. ERLIN1 constrains HCC progression both in vitro and in vivo by stabilizing the INSIG1–SCAP–SREBP2 axis and maintaining the metabolic balance of intracellular cholesterol. Under hypoxia, impaired factor-inhibiting hypoxia-1-dependent hydroxylation of ASB11 at asparagine residues 90 and 92 enhances ASB11-mediated ERLIN1 degradation. Pharmacological targeting of this axis using zoledronic acid (ZoA) attenuated HCC progression by weakening the ASB11–ERLIN1 interaction and restoring cholesterol homeostasis. Conclusions ERLIN1 represents a druggable metabolic vulnerability in cholesterol-dysregulated HCC. Targeting the ASB11–ERLIN1 axis with the clinically approved ZoA reestablishes cholesterol homeostasis and offers a promising therapeutic strategy to overcome the current limitations of cholesterol-targeted HCC therapies.

OBJECTIVE To systematically analyze the trends in the volume and value of out-licensing deals by Chinese biopharmaceutical companies over the past two decades， and to quantitatively identify factors associated with deal value， thereby providing an evidence base for policymakers and corporate managers. METHODS Based on the PharnexCloud database， information on out-licensing deals disclosed by Chinese biopharmaceutical companies between January 1， 2005 and December 31， 2025 was collected， and executed deals with disclosed specific financial terms were included for analysis. Descriptive statistical analyses of deal value， product characteristics and deal characteristics were performed using Stata SE 18.0； with the natural logarithm of deal value as the dependent variable， stepwise multiple regression models were constructed to examine the associations of product and deal characteristics with deal value. RESULTS A total of 210 out-licensing deals were included， with a cumulative deal value of approximately 214.151 billion dollars and a mean deal value of 1.020 billion dollars . The trading market expanded rapidly from 2020 onward， with the annual deal value reaching a record 95.687 billion dollars in 2025. Multiple regression analysis showed that the deal value of products at the drug discovery stage was significantly lower than that at the preclinical stage [regression coefficient （ β ） ＝－1.995， 95% confidence interval （CI）： －3.256 to －0.734， P ＜0.05 ] ； the deal value of oncology products was significantly higher than that of other therapeutic areas （ β ＝0.828， 95%CI： 0.224 to 1.431， P ＜0.05）； global licensing （ β ＝1.690， 95%CI： 1.107 to 2.273， P ＜0.05） and co-development arrangements （ β ＝0.849， 95%CI： 0.084 to 1.615， P ＜0.05） were significantly associated with higher deal value. CONCLUSIONS Out-licensing deals by Chinese biopharmaceutical companies have achieved significant growth in both volume and value over the past two decades. Oncology products， global licensing， and co-development arrangements are significantly and positively associated with higher deal value.

Objective To develop a deep learning-based denoising model for accelerating Monte Carlo(MC)simulation of electronic portal imaging device(EPID)transit dose images.Methods A total of 500 EPID fields were collected from 100 lung cancer patients undergoing 5-field intensity-modulated radiotherapy,with 400 fields randomly selected as training set,50 fields as validation set,and 50 fields as test set.EPID transit dose image datasets with low particle counts(1×107)and high particle counts(1×109)were simulated using the GPU-accelerated MC dose calculation engine ARCHER.A denoising network model named SUNet was constructed based on Swin Transformer and U-Net,and trained using low-particle-count images as input and high-particle-count images as output.Following training,SUNet model was used to denoise low-particle-count EPID images in the test set.Denoising performance was evaluated using structural similarity index(SSIM),peak signal-to-noise ratio(PSNR),and Gamma passing rates(3%/2 mm),and the computational efficiency of MC simulation combined with SUNet model was analyzed.Results Compared with the original low-particle-count images,the SUNet-denoised images showed significantly improved quality,reduced noise points,and smoother dose distribution.When benchmarked against high-particle-count images,the SUNet-denoised images achieved an average SSIM greater than 0.9,an average PSNR higher than 32 dB,and an average gamma passing rate exceeding 90%.The MC simulation combined with SUNet model required only 1.88 s to simulate a single EPID transit dose image,representing an approximate 40-fold improvement in computational efficiency as compared with high-particle-count MC simulation.Conclusion The deep learning-based denoising model substantially accelerates MC simulation of EPID transit dose images while preserving both image quality and dose accuracy,which provides possibilities for EPID-basedin vivodose verification.

Objective:To investigate the clinical application of ultrasound-guided cervical plexus block combined with superior laryngeal nerve block in tracheotomy for burn patients.Methods:A total of 88 burn patients who underwent tracheotomy from January 2022 to December 2022 were divided into observation group(44 cases)and matched group(44 cases).The matched group received conventional general anesthesia,while the observation group underwent ultrasound-guided cervical plexus block combined with superior laryngeal nerve block.The operation time,anesthetic effect,intraoperative hemodynamic parameters,postoperative complications,and patient satisfaction were compared.Results:The surgery time in the observation group was shorter than that in the matched group(P＜0.05).The anesthetic effect in the observation group was superior to that in the matched group,with more stable intraoperative hemodynamics,and smaller fluctuations in heart rate and mean arterial pressure(P＜0.05).The incidence of postoperative cough reflex,hoarseness,postoperative pain score,and respiratory complications in the observation group were lower than those in the matched group(P＜0.05).Patient satisfaction in the observation group was higher than that in the matched group(P＜0.05).Conclusion:Ultrasound-guided cervical plexus block combined with superior laryngeal nerve block for tracheotomy in burn patients can effectively improve anesthetic effect,reduce operation time,stabilize intraoperative hemodynamics,reduce postoperative complications,and improve patient satisfaction,which is worthy of clinical application.

Objective To explore the scheme for the deployment and withdrawal of the surgical module of the new-type tent hospital system.Methods A set of standardized scheme for deploying and withdrawing the surgical module of the new-type tent hosital system was proposed and implemented in terms of labor division,operation precedure,operation technique and precaution.The operating time,number of operational errors and number of equipment damages were recorded for each of the five deployment and withdrawal operations before and after the program was executed,and the team members'immediate heart rate,percentage of maximum heart rate(MHR)and rating of perceived exercise(RPE)at the end of the operation were recorded after the program was implemented.SPSS 26.0 software was used for statistical analysis.Results The standardized scheme had the deployment time shortened from(85.15±11.430)min to(58.23±8.513)min,withdrawal time decreased from(65.36±9.369)min to(48.92±7.129)min,with the differences being statistically significant(P＜0.05);the numbers of operatio-nal errors and equipment damages were both reduced when compared with those before the implementation of the schemce;the immediate heart rate of the team members at the end of the operation ranged from 43 to 157 beats/min,with an average value of 151.1 beats/min,the individual MHR percentages were from 75％to 87％,with an average value of 81.1％,and the RPE scores were from 14 to 17,with an average value of 15.3,which all could be categorized as moderate-operation intensity.Condusion The standardized deployment and withdrawal scheme for the surgical module meets the needs of actual combat and training assessment,and thus is worthy promoting in medical institutions equipped with the surgical module of the new-type tent hosital system.[Chinese Medical Equipment Journal,2025,46(2):74-79]

Objective:To investigate the value of coronary CTA (CCTA)-based traditional features and radiomics of plaque in the identification of culprit lesions that caused acute myocardial infarction (AMI).Methods:This was a retrospective multicenter study. From July 2016 to November 2023, a total of 344 patients from the Affiliated Hospital of Qingdao University (training cohort, n=184), Shandong Provincial Hospital Affiliated to Shandong First Medical University (validation cohort, n=88) and Qilu Hospital of Shandong University (test cohort, n=72) who received percutaneous coronary intervention (PCI) due to AMI and underwent CCTA within 48 hours of AMI were enrolled. The culprit plaques and non-culprit plaques were identified using a combination of electrocardiogram, CCTA, and angiographic findings. The vessel, plaque location, plaque type, Coronary Artery Disease-Reporting and Data System (CAD-RADS) score, high-risk plaque characteristics, plaque length, plaque volume, and burden were analyzed, and 1 904 radiomics features were extracted for each plaque. The traditional imaging model, the radiomics model, and the combined model were established by using multivariate Logistic regression analysis. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of each model in identifying culprit lesions. The DeLong test was used for the comparison of AUC between every two models. The net reclassification index (NRI) was used to evaluate the incremental value of the combined model to the traditional imaging model and the radiomics model. The decision curve analysis (DCA) was used to assess the clinical net benefit of these models. A correlation heatmap was used to evaluate the correlation between the radiomics score and traditional CCTA factors. The interpretable analysis of the decision process of the combined model was performed by the Shapley Additive exPlanations (SHAP). Results:In the validation cohort and the test cohort, the AUC of the traditional imaging model developed by the vessel, plaque type, positive remodeling and CAD-RADS score was 0.898 (95% CI 0.869-0.922) and 0.881 (95% CI 0.848-0.910), respectively. The radiomics model developed by six radiomics features was 0.863 (95% CI 0.831-0.891) and 0.863 (95% CI 0.827-0.864), respectively. The AUC of the combined model was 0.930 (95% CI 0.905-0.950)and 0.919 (95% CI 0.889-0.942), respectively. In the validation cohort and the test cohort, the AUC of the combined model was higher than that of the traditional imaging model ( Z=4.013, 4.272, P<0.001) and that of the radiomics model ( Z=4.819, 3.784, P<0.001), respectively. In the validation cohort, the combined model yielded an NRI of 20.43% (95% CI 10.43%-30.44%, P<0.001) and 20.21% (95% CI 9.62%-30.80%, P<0.001) for identifying culprit lesions compared with the traditional imaging model and the radiomics model, respectively. In the test cohort, the combined model yielded an NRI of 28.05% (95% CI 16.72%-39.38%, P<0.001) and 23.57% (95% CI 13.58%-33.56%, P<0.001) for identifying culprit lesions compared with the traditional imaging model and the radiomics model, respectively. DCA showed the combined model had the highest clinical net benefit. The correlation heatmap showed the radiomics score was not correlated or only weakly correlated with traditional CCTA factors. SHAP indicated the radiomics and CAD-RADS score contributed significantly to the model. Conclusion:The CCTA-based traditional features and radiomics of plaque have favorable performance for the identification of culprit plaques in patients with AMI.

Objective:To observe the role of impulsivity in cognitive impairment in manic episodes of bipolar Ⅰ disorder(BPDTI)patients.Methods:180 cases of patients with BPDTI manic episodes admitted to our hospital from February 2024 to December 2024 were selected as the manic group,and another 180 cases of volunteers who were psychologically tested as normal during the same period were selected as the healthy group.The impulse Barratt-11 scale(BIS-11)and the MATRICS Consensus Cognitive Test(MCCB)were used to investigate and evaluate impulsivity and cognitive function,and correlation analysis and risk factor analysis were conducted.Results:In the BIS-11 scale,there was no statistically significant difference between the two groups in the unplanned factor(P＞0.05),but there were significant differences compared between the two groups in cognitive,motor factors,and total score(P＜0.05).The MCCB scores of the manic group in information processing speed,working memory,word learning,visual learning,social cognition,reasoning and problem solving,and attention vigilance were significantly lower than those of the healthy group(P＜0.05).The relationship between BIS-11 total score and cognitive impulsivity factor and MCCB total score and word learning showed there were negative correlation(P＜0.05);The exercise factor in the BIS-11 scale were negatively correlated with the MCCB total score and working memory factor(P＜0.05);The unplanned factor in the BIS-11 scale showed there were negative correlation with the MCCB total score,word learning(P＜0.05),and information processing speed.BIS-11,the number of years of education was an influencing factor for BPDTI mania(P＜0.05).Conclusion:BPDTI mania patients had high impulsivity and cognitive impairment,high impulsivity and number of years of education were influencing factors for mania,high impulsivity affected cognitive function through corresponding brain regions,aggravating the condition.

A mounting body of research suggests that circRNAs significantly contribute to the develop-ment of myocardial fibrosis.The microarray results of human circular RNA expression profile indicated that circHERC4_041 expression increased in the myocardium of patients with heart failure,RT-qPCR a-nalysis confirmed that the myocardial expression level of circHERC4_041 in individuals with heart failure were considerably elevated compared to that in healthy organ donors.Fluorescence in situ hybridization(FISH)confirmed that circHERC4_041 was abundant in the cytoplasm of human cardiomyocyte AC16.Overexpression of circHERC4_041 in mouse myocardial fibroblasts(mCFs)mediated by adenovirus in-hibited the expression of fibrosis-related proteins in mCFs.Experiments involving cell proliferation,wound healing,and Transwell assays demonstrated that overexpression of circHERC4_041 suppressed the growth and mobility of mCFs(P＜0.001).Sequence analysis results suggested that circHERC4_041 con-tains potential ribosome entry sequence(IRES)and open reading frame(ORF).Western blot confirmed that circHERC4_041 could translate the 516 amino acid HERC4-516aa protein,which was mainly located in the cytoplasm of the cell.Cell functional experiments confirmed that circHERC4_041 inhibited the fi-brotic phenotype of mCFs by specifically translating HERC4-516aa(P＜0.05).The specific interaction between HERC4-516aa and transglutaminase 2(TGM2)was confirmed by IP-MS screening and Co-IP i-dentification.Further results found that the degradation of TGM2 was promoted through proteasome path-way.The overexpression of TGM2 in mCFs facilitated by adenoviral vectors could counteract the suppres-sive effects of HERC4-516aa on the fibrotic phenotype of mCFs.Therefore,this study confirmed that the HERC4-516aa protein translated by circHERC4_041 can specifically bind to TGM2 to inhibit the fibrotic phenotype of myocardial fibroblasts.

Aim To explore the underlying molecular mechanism of Alisol A 24-acetate(24A)in improving oxygen-glucose deprivation/reoxygenation(OGD/R)injury in brain microvascular endothelial cells(BMECs)and its correlation with miR-98-5p/transi-ent receptor potential melastatin-2(TRPM2).Meth-ods The ischemia-reperfusion injury in brain micro-vascular endothelial cells(BMECs)was established u-sing bEnd.3 cells subjected to 8 h of oxygen-glucose deprivation followed by 16 h of re-oxygenation.The cells were intervened by miR-98-5p mimics and/or 18.77 μmol·L-1 24A for 24 h and divided into the control group,OGD/R group,OGD/R+24A group,OGD/R+24A+miR-98-5p mimics group and OGD/R+miR-98-5p mimics group.The mRNA levels of miR-98-5p and TRPM2 were detected by qPCR.IL-1 β and TNF-α levels were detected by ELISA.The expression levels of TRPM2,p-AKT,p-GSK3 β,AKT,GSK3 β,Bcl-2,Bax,ZO-1,Occludin,Claudin-5 were detected by Western blot.Apoptosis and reactive oxygen species(ROS)levels were detected by flow cytometry.The targeting relationship between miR-98-5p and TRPM2 was verified using dual luciferase assay.Results Compared with the control group,the apoptosis of OGD/R group was obvious,Bcl-2/Bax decreased,ZO-1,Occludin,Claudin-5 decreased,IL-1 β,TNF-α and ROS increased,miR-98-5p,p-AKT/AKT,p-GSK3β/GSK3β decreased but TRPM2 increased.But com-pared with the OGD/R group,except the control group,the other three groups showed the opposite trend in the above aspects;compared with the OGD/R+24A group,OGD/R+24A+miR-98-5p mimics group showed decreased apoptosis,decreased degradation of ZO-1,Occludin and Claudin-5,and decreased inflam-mation and ROS.miR-98-5p,p-AKT/AKT,p-GSK3β/GSK3β increased and TRPM2 decreased.However,compared with the OGD/R+24A+miR-98-5p mimics group,the OGD/R+miR-98-5p mimics group reversed this trend.Dual luciferase confirmed that miR-98-5p targeted regulation of TRPM2.Conclusion 24A in-hibits the expression of TRPM2 in BMECs through miR-98-5p,regulates AKT/GSK3β signal pathway,re-duces OGD/R inflammation and oxidative stress-medi-ated apoptosis,prevents the degradation of ZO-1,Oc-cludin and Claudin-5,and improves BBB permeability.