ObjectiveTo investigate the effect of mitochondrial calcium uniporter （MCU） on the cytoskeleton of pancreatic ductal epithelial cells in a mouse model of acute pancreatitis （AP） induced by caerulein （CAE）， to analyze the role of MCU in the development of AP， and to provide a theoretical basis for clinical treatment. MethodsIn the in vivo experiment， wild-type male C57BL6/J mice， aged 4 weeks， were randomly divided into control group and AP group， with 6 mice in each group. The mice in the AP group were given intraperitoneal injection of CAE to establish a model of AP， and those in the control group were given intraperitoneal injection of an equal volume of normal saline. Serum and pancreatic tissue samples were collected after 24 hours of modeling. HE staining was used to observe pancreatic histopathological changes； Western Blot was used to measure the expression levels of MCU， glutathione peroxidase 4 （GPX4）， and acyl-CoA synthetase long chain family member 4 （ASCL4）； kits were used to measure the serum level of amylase. In the in vitro experiment， the human pancreatic ductal epithelial cell line HPDE6-C7 was co-cultured with CAE for 24 hours to establish an in vitro AP model， and the cells were divided into control group， CAE group， RR （an MCU activity inhibitor） group， CAE+RR group， Fer-1 （an ferroptosis inhibitor） group， CAE+Fer-1 group， Erastin （an ferroptosis inducer） group， and CAE+Erastin group. CCK-8 assay was used to observe the influence of different agents on cell viability； Western Blot was used to measure the expression levels of MCU， GPX4， and ASCL4； immunofluorescence assay was used to measure reactive oxygen species （ROS）， actin cytoskeleton， and monolayer permeability； kits were used to measure the concentrations of malondialdehyde （MDA）， glutathione （GSH）， Fe²⁺， and total iron. A one-way analysis of variance was used for comparison of continuous data between multiple groups， and the least significant difference t-test was used for comparison between two groups. ResultsIn the in vivo experiment， compared with the control group， the AP group had significant increases in pancreatic histopathological score， the serum level of amylase， and the expression levels of MCU and ASCL4， as well as a significant reduction in the expression of GPX4 （all P<0.05）. In the in vitro experiment， compared with the control group， the CAE group had significant increases in the expression levels of MCU and ASCL4， a significant reduction in the expression of GPX4， and significant increases in the concentrations of Fe²⁺， total iron， and MDA， the green fluorescence intensity of ROS， and monolayer permeability， as well as a significant reduction in the concentration of GSH （all P<0.05）， with the presence of actin cytoskeleton disruption. Compared with the CAE group， the CAE+RR group had a significant increase in the expression level of GPX4， a significant reduction in the expression level of ASCL4， and significant reductions in the concentrations of Fe²⁺， total iron， and MDA， the green fluorescence intensity of ROS， and monolayer permeability and a significant increase in the concentration of GSH （all P<0.05）， with alleviation of actin cytoskeleton disruption. Compared with the CAE group， the CAE+Fer-1 group had significant reductions in the concentrations of Fe²⁺， total iron， and MDA， the green fluorescence intensity of ROS， and monolayer permeability and a significant increase in the concentration of GSH （all P<0.05）， with alleviation of actin cytoskeleton disruption. Compared with the CAE group， the CAE+Erastin group had significant increases in the concentrations of Fe²⁺， total iron， and MDA， the green fluorescence intensity of ROS， and monolayer permeability and a significant reduction in the concentration of GSH （all P<0.05）， with aggravation of actin cytoskeleton disruption. ConclusionDuring the onset of AP， MCU mediates oxidative stress-induced ferroptosis and leads to the disruption of the pancreatic ductal epithelial barrier， which may be one of the possible pathogeneses of AP.

ObjectiveTo delineate imaging findings using an imaging platform and investigate the correlation between MRI characteristics of spinal cord atrophy and clinical diagnosis in children with spinal cord injury (SCI). MethodsImaging data of 150 children with SCI admitted to Beijing Bo'ai Hospital, China Rehabilitation Research Center, from January, 2002 to March, 2024 were collected and imported into the imaging platform. The anteroposterior and transverse diameters of the middle part of the spinal cord at the cross-section with the most severe atrophy were measured, and the relevant indicators of the previous normal spinal cord segment were measured as controls; the radiomic features were extracted. Clinical data of the children including gender, age, cause of injury, sensory level, motor level, spinal cord injury level, injury severity and disease course were collected. ResultsSpinal cord atrophy was identified in 81 cases (54%), among which 78 cases (96%) were American Spinal Injury Association Impairment Scale (AIS) grade A and 3 cases (4%) were AIS grade C. The upper boundary of the spinal cord atrophy site strongly correlated with the injury level, motor level and sensory level (r > 0.8, P < 0.001). ConclusionMore than half of children with SCI may develop secondary spinal cord atrophy, the vast majority of whom suffer from complete spinal cord injury; the upper boundary of spinal cord atrophy is correlated with the injury level.

OBJECTIVE To provide a scientific basis for the quality evaluation and clinical application of Qingwen hufei granules. METHODS Fourteen batches of Qingwen hufei granules were used as samples to establish high-performance liquid chromatography （HPLC） fingerprints using the Similarity Evaluation System for Chromatographic Fingerprint of Traditional Chinese Medicine （2012 Edition）. The chromatographic peaks were identified and the similarity was evaluated. Cluster analysis （CA）， principal component analysis （PCA）， and orthogonal partial least squares-discriminant analysis （OPLS-DA） were used to conduct chemical pattern recognition analysis on the 14 batches of samples. Meanwhile， the contents of neochlorogenic acid （NGA）， chlorogenic acid （CHA）， cryptochlorogenic acid （CGA）， forsythoside A （FTA）， 3，5-O-dicaffeoylquinic acid （3，5-O- DA）， 4，5-O-dicaffeoylquinic acid （4，5-O-DA）， and angoroside C （AGC） in the samples were determined by HPLC. RESULTS The methodological investigation results of both the fingerprint and the content determination complied with the relevant requirements. Fourteen common peaks were indicated in the HPLC fingerprints of the 14 batches of samples， and 7 of them were identified [NGA （peak 2）， CHA （peak 3）， CGA （peak 5）， FTA （peak 11）， 3，5-O-DA （peak 12）， 4，5-O-DA （peak 13）， and AGC （peak 14）]； the similarity of each sample was greater than 0.94. The results of CA and PCA showed that the samples could be classified into 3 categories； the results of OPLS-DA indicated that peak 4 （unknown）， peak 11 （FTA）， peak 8 （unknown）， peak 9 （unknown）， and peak 1 （unknown） were the differential components. The content ranges of NGA， CHA， CGA， 3，5-O-DA， FTA， 4，5-O-DA and AGC in the 14 batches of samples were 0.210 4-0.458 7， 0.269 1-0.506 3， 0.228 1-0.461 1， 0.443 9-1.044 6， 0.066 7-0.155 7， 0.062 8-0.143 8， and 0.057 4-0.105 7 mg/g， respectively. CONCLUSIONS The HPLC fingerprint and multi-component content determination methods established in this study are efficient and reliable， and can be used for the quality evaluation of Qingwen hufei granules.

ObjectiveTo observe the effects of Yangjing Zhongyutang （YJZYT） on mitochondrial biogenesis and oxidative stress damage mediated by the silent information regulator 1 （SIRT1）/peroxisome proliferator-activated receptor gamma coactivator-1alpha （PGC-1α） signaling pathway in cyclophosphamide （CTX）-induced rats with diminished ovarian reserve （DOR）， and to explore its mechanism in improving ovarian reserve function and follicular development. MethodsForty-two 8-week-old female SD rats with normal estrous cycles were randomly divided into a blank control group （n=7） and a model group （n=35）. Rats in the model group received a single intraperitoneal injection of CTX （90 mg·kg^-1） to establish the DOR model. After modeling， estrous cycles were monitored for 7 consecutive days， and model success was confirmed based on criteria for estrous cycle disruption. After successful modeling， rats were divided into groups for intervention： estradiol valerate group （0.09 mg·kg^-1）， and YJZYT high-， medium-， and low-dose groups （19.98， 9.99， 5.00 g·kg^-1）. The blank control group and model group were given an equal volume of distilled water by gavage. All groups received daily gavage once for 4 consecutive weeks. The general state， body weight， and ovarian wet weight of rats were observed and recorded， and the ovarian organ index was calculated. Enzyme-linked immunosorbent assay （ELISA） was used to measure serum levels of follicle-stimulating hormone （FSH）， luteinizing hormone （LH）， estradiol （E₂）， anti-Müllerian hormone （AMH）， superoxide dismutase （SOD）， and glutathione peroxidase （GSH-Px）. Hematoxylin-eosin （HE） staining was performed to observe ovarian histomorphological changes and follicular development status. Immunofluorescence was used to detect reactive oxygen species （ROS） expression levels. Colorimetric assays were employed to measure adenosine triphosphate （ATP） and malondialdehyde （MDA） content in ovarian tissues. Quantitative Real-time polymerase chain reaction （Real-time PCR） was used to detect mitochondrial DNA （mtDNA） copy number and the mRNA expression levels of key genes including SIRT1， PGC-1α， nuclear respiratory factor 1 （NRF1）， and mitochondrial transcription factor A （TFAM）. Western blot was performed to detect the protein expression levels of SIRT1， PGC-1α， NRF1， and TFAM. ResultsCompared with the blank group， rats in the model group exhibited disrupted estrous cycles， obviously reduced body weight， and decreased ovarian index （P<0.05）. Ovarian histopathology revealed cortical thinning， loose structure， and a significant reduction in both primordial and growing follicles （P<0.01）. Serum FSH and LH levels were significantly elevated （P<0.01）， while E₂ and AMH levels were obviously reduced （P<0.05， P<0.01）. ATP content and mtDNA copy number decreased in ovarian tissue （P<0.01）， ROS expression increased， MDA levels rose， while SOD and GSH-Px activities obviously decreased （P<0.05， P<0.01）， mRNA and protein expression levels of SIRT1， PGC-1α， NRF1， and TFAM were obviously downregulated （P<0.05， P<0.01）. After treatment， compared with the model group， body weight and ovarian index obviously recovered in rats administered various doses of YJZYT （P<0.05）， serum E₂ and AMH levels increased， while FSH and LH levels obviously decreased （P<0.05， P<0.01）， ovarian tissue ATP content and mtDNA copy number were up-regulated， ROS and MDA levels decreased， and antioxidant enzymes SOD and GSH-Px activity obviously increased （P<0.05， P<0.01）， Gene and protein expression levels related to the SIRT1/PGC-1α /NRF1/TFAM signaling pathway were obviously up-regulated compared to the model group （P<0.05， P<0.01）， HE staining revealed that ovarian structure gradually recovered to integrity in all treatment groups， with a obviously increase in the number of primordial and growing follicles （P<0.05， P<0.01）. Granulosa cells were neatly arranged， indicating marked improvement in ovarian function. ConclusionYJZYT may improve ovarian function and follicular development in rats with diminished ovarian reserve by activating the SIRT1/PGC-1α signaling pathway， promoting mitochondrial biogenesis， enhancing mitochondrial function， and alleviating oxidative stress damage.

Objective: To understand the impact of childhood trauma on psychological distress among upper grade elemetary school students, and to explore the mediating role of leisure activities in the relationship, so as to provide a basis for developing mental health intervention strategies. Methods: From August to November 2024, a combination of convenience sampling and stratified cluster random sampling was employed to recruit 1 373 fourth to sixth grade students from four primary schools in Harbin. The Childhood Trauma Questionnaire(CTQ), a self designed leisure activity scale (including active and passive leisure activities), and the Kessler Psychological Distress Scale (K10) were used to assess childhood trauma experiences, leisure activities, and levels of psychological distress. Spearman correlation analysis and linear regression analysis were conducted to explore the relationships among childhood trauma, leisure types, leisure time, and psychological distress. Based on the mediation analysis framework proposed by Hayes (Model 4), the mediating role of leisure types in the relationship between childhood trauma and psychological distress was examined. Results: Totally 19.1% of the upper elemetary school students exhibited psychological distress, while 30.2% had experienced childhood trauma. During school days, 64.6% of the students were reported of having leisure time concentrated between 1 and 5 hours per day, whereas 67.4% reported leisure time exceeding 5 hours per day on weekends. After controlling for potential demographic confounders such as gender, grade, ethnicity, household registration, being an only child, parents educational level, co residence, and whether parents are first time married,linear regression analysis showed that childhood trauma experience had positive predictive effect on psychological distress in upper primary school students( β =0.20, P <0.01). Leisure time showed no statistically significant association with psychological distress, both on school days ( β =-0.58 to -0.56) and weekends ( β =0.26- 0.98 )(all P >0.05). Active leisure activities were negatively associated with psychological distress ( β =-0.20), while passive leisure activities were positively associated with psychological distress ( β =0.29)(both P <0.01). Leisure type partially mediated the relationship between childhood trauma and psychological distress, accounting for 11.7% of the indirect effect. Conclusion Childhood trauma experiences positively predict psychological distress in upper elementary school students, and affect psychological distress through active leisure and passive leisure.

Background Microparticles (MPs) are one of the main medium of inflammatory reaction with an important role in atherosclerotic progression. Studies on association of air pollution exposure and levels of peripheral blood MPs are limited among human. Objective To evaluate the effects of short-term exposure to air pollution on levels of peripheral blood MPs. Method A panel of 73 healthy adults was followed with 4 repeated follow-ups in Beijing, China, from November 2014 to January 2016. During each visit, we collected questionnaire information, fasting venous blood, urine, and exposures to fine particulate matter (PM_2.5), black carbon, nitric oxide, nitrogen dioxide, nitrogen oxide, sulfur dioxide, carbon monoxide, and ozone. We used linear mixed-effect models to analyze associations of air pollution exposure with levels of total MPs (TMPs) and MPs derived from various cells. Stratified analysis was conducted by levels of C-reactive protein (CRP) and malondialdehyde (MDA). Results The results showed significant associations between air pollution exposure and peripheral blood TMPs at 2 h-6 d prior to the follow-ups (P<0.05), while no statistical associations were found for MPs derived from different cell types. Significant increases in TMPs of 7.8% (95%CI: 0.7%, 15.3%) and 14.3% (95%CI: 2.8%, 27.2%) were observed with each interquartile range (IQR) increase in PM_2.5 (IQR=64.9 μg·m⁻³) at prior 18 h and NO (IQR=40.5 μg·m⁻³) at prior 48 h. Among participants with low levels of CRP and MDA, significantly positive associations were observed between air pollution exposure and levels of TMPs (P<0.05). Conclusion Short-term exposure to air pollution is significantly associated with increased levels of circulating MPs in healthy adults, and in people with lower systemic inflammation, peripheral blood MPs levels are more easily affected after exposure to air pollutants.

Objective:To explore the efficacy of deep learning-based automatic segmentation technology in the segmentation of hepatocellular carcinoma (HCC) lesions using gadoxetate disodium-enhanced MRI (EOB-MRI), and to investigate the prognostic value of radiomics analysis in predicting patient outcomes.Methods:This was a cross-sectional, retrospective study that collected data from 352 patients with solitary HCC who underwent imaging at the Harbin Medical University Cancer Hospital between June 2015 and May 2023. The patients were randomly divided into a training set ( n=213) and a validation set ( n=139) in a 3∶2 ratio using weighted random sampling. Two radiologists manually annotated the lesions. Hepatobiliary-phase EOB-MRI images were standardized, and six deep learning models,nnU-Net, nnFormer, UnetR, Swin-UnetR, UnetR++ and MedNeXt,were trained for automatic segmentation on the training set. The segmentation performance was evaluated on the validation set, and the segmentation efficacy was assessed using the Dice coefficient and 95% Hausdorff distance (HD 95), identifying of the optimal model. Radiomics features were extracted from both manual and automatic segmentation regions, and the radiomics score (Radscore) was calculated to stratify patients into high-risk and low-risk groups. Kaplan-Meier curves and log-rank tests were used to analyze the differences in relapse-free survival (RFS) and overall survival (OS) between the different stratified groups. Results:Among the automatic segmentation models, the MedNeXt model performed best in the validation set, with a Dice coefficient of 76.0%, HD 95 of 7.2, and a segmentation success rate of 90.6% (126/139). The nnFormer model was the second-best, with a Dice coefficient of 75.3%, HD 95 of 10.1, and a segmentation success rate of 89.9% (125/139). Other models showed Dice coefficients ranging from 66.3% to 74.1%. A MedNext-nnF model was established by combining the MedNeXt and nnFormer models, achieving a Dice coefficient of 78.2%, HD 95 of 5.9, and a segmentation success rate of 92.1% (128/139) in the validation group. After constructing the automatic segmentation radiomics prognostic model, patients were stratified by Radscore. Both manual and automatic segmentation models showed statistically significant differences in RFS and OS between different risk groups ( P<0.001). Conclusions:The Mednext-nnF fusion model enables efficient and automated segmentation of HCC lesions in EOB-MRI. The radiomics model constructed based on the automated segmentation demonstrates strong performance in predicting and stratifying prognostic risk.

Banxia Xiexin Decoction has the effect of harmonizing the spleen and stomach,and regulating cold and heat.It is mainly used for the treatment of epigastric fullness of mixed cold and heat in the heart,and has certain advantages in relieving symptoms,reducing recurrence rates,and ensuring safety.This article reviewed the clinical application of Banxia Xiexin Decoction from the perspectives of digestive system diseases,neurological diseases,gastrointestinal tumors,respiratory system diseases,endocrine diseases,dermatological diseases,gynecological diseases,and other diseases.It also summarized the mechanism of Banxia Xiexin Decoction from the aspects of protection of gastrointestinal mucosa,anti-inflammatory and bactericidal effects,immune regulation,regulation of neurotransmitters,anti-tumor effects,blood glucose lowering,and improvement of insulin resistance,providing reference for the in-depth research and application of Banxia Xiexin Decoction.

Diabetic kidney disease(DKD)with increasing global prevalence lacks effective therapeutic targets to halt or reverse its progression.Therapeutic targets supported by causal genetic evidence are more likely to succeed in randomized clinical trials.In this study,we integrated large-scale plasma proteomics,genetic-driven causal inference,and experimental validation to identify prioritized targets for DKD using the UK Biobank(UKB)and FinnGen cohorts.Among 2844 diabetic patients(528 with DKD),we identified 37 targets significantly associated with incident DKD,supported by both observational and causal evi-dence.Of these,22％(8/37)of the potential targets are currently under investigation for DKD or other diseases.Our prospective study confirmed that higher levels of three prioritized targets-insulin-like growth factor binding protein 4(IGFBP4),family with sequence similarity 3 member C(FAM3C),and prostaglandin D2 synthase(PTGDS)—were associated with a 4.35,3.51,and 3.57-fold increased likeli-hood of developing DKD,respectively.In addition,population-level protein-altering variants(PAVs)analysis and in vitro experiments cross-validated FAM3C and IGFBP4 as potential new target candidates for DKD,through the classic NLR family pyrin domain containing 3(NLRP3)-caspase-1-gasdermin D(GSDMD)apoptotic axis.Our results demonstrate that integrating omics data mining with causal inference may be a promising strategy for prioritizing therapeutic targets.

Objective:To explore the efficacy of deep learning-based automatic segmentation technology in the segmentation of hepatocellular carcinoma (HCC) lesions using gadoxetate disodium-enhanced MRI (EOB-MRI), and to investigate the prognostic value of radiomics analysis in predicting patient outcomes.Methods:This was a cross-sectional, retrospective study that collected data from 352 patients with solitary HCC who underwent imaging at the Harbin Medical University Cancer Hospital between June 2015 and May 2023. The patients were randomly divided into a training set ( n=213) and a validation set ( n=139) in a 3∶2 ratio using weighted random sampling. Two radiologists manually annotated the lesions. Hepatobiliary-phase EOB-MRI images were standardized, and six deep learning models,nnU-Net, nnFormer, UnetR, Swin-UnetR, UnetR++ and MedNeXt,were trained for automatic segmentation on the training set. The segmentation performance was evaluated on the validation set, and the segmentation efficacy was assessed using the Dice coefficient and 95% Hausdorff distance (HD 95), identifying of the optimal model. Radiomics features were extracted from both manual and automatic segmentation regions, and the radiomics score (Radscore) was calculated to stratify patients into high-risk and low-risk groups. Kaplan-Meier curves and log-rank tests were used to analyze the differences in relapse-free survival (RFS) and overall survival (OS) between the different stratified groups. Results:Among the automatic segmentation models, the MedNeXt model performed best in the validation set, with a Dice coefficient of 76.0%, HD 95 of 7.2, and a segmentation success rate of 90.6% (126/139). The nnFormer model was the second-best, with a Dice coefficient of 75.3%, HD 95 of 10.1, and a segmentation success rate of 89.9% (125/139). Other models showed Dice coefficients ranging from 66.3% to 74.1%. A MedNext-nnF model was established by combining the MedNeXt and nnFormer models, achieving a Dice coefficient of 78.2%, HD 95 of 5.9, and a segmentation success rate of 92.1% (128/139) in the validation group. After constructing the automatic segmentation radiomics prognostic model, patients were stratified by Radscore. Both manual and automatic segmentation models showed statistically significant differences in RFS and OS between different risk groups ( P<0.001). Conclusions:The Mednext-nnF fusion model enables efficient and automated segmentation of HCC lesions in EOB-MRI. The radiomics model constructed based on the automated segmentation demonstrates strong performance in predicting and stratifying prognostic risk.