The pathogenesis of metabolic dysfunction-associated steatotic liver disease （MASLD） is fundamentally rooted in spleen deficiency and is closely associated with phlegm turbidity， damp-heat and blood stasis. Clinically， liver constraint with spleen deficiency and internal retention of damp turbidity represent the predominant traditional Chinese medicine （TCM） syndrome patterns. Researches have indicated intrinsic connections between the syndrome patterns and biological indicators such as gut microbiota and metabolic profiles. Regarding treatment， classical famous formulas， modern empirical formulas， and newly developed TCM drugs show positive effects in regulating glucose and lipid metabolism， improving insulin resistance， and alleviating metabolic inflammation， exhibiting multi-target mechanisms of action； acupuncture and other external therapies also provide adjunctive value. Nevertheless， current researches still have limitations such as the lack of high-quality clinical evidence and insufficient systematic elucidation of the uncerlying mechanisms. Future efforts should focus on conducting high-quality TCM clinical trials with hard endpoint outcomes such as hepatic histology outcomes， and utilizing modern technologies like multi-omics to elucidate TCM's mechanisms of action， thereby advancing the position of TCM as a first-line therapeutic strategy for MASLD.

Objective To analyze the effect of releasing the lower pulmonary ligament on right residual lung expansion after right upper lobe resection under different body mass index (BMI) levels. Methods The clinical data of patients who underwent thoracoscopic right upper lobe resection in the First Affiliated Hospital with Nanjing Medical University from 2021 to 2022 were retrospectively analyzed. Patients were divided into a group A (17 kg/m2＜BMI≤23 kg/m2), a group B (23 kg/m2＜BMI≤29 kg/m2) and a group C (BMI＞29 kg/m2) according to BMI. The presence of residual cavity was judged by chest X-ray at 7-10 days after operation, the degree of compensation change of the right main bronchus angle was measured, and the changes in lung volume were determined by CT three-dimensional reconstruction. Results A total of 157 patients who underwent thoracoscopic right upper lobe resection were included, including 71 males and 86 females, with an average age of (59.7±11.2) years. There were 50 patients in the group A, 75 patients in the group B, and 32 patients in the group C. In the group A, compared with those without releasing the lower pulmonary ligament, patients with releasing had a lower incidence of postoperative residual cavity (P=0.016), greater changes in bronchus angle (P<0.001), and smaller changes in lung volume (P<0.001). In the group B and C, there was no significant effect of releasing the lower pulmonary ligament on postoperative residual cavity, bronchus angle, and lung volume changes (P>0.05). Conclusion For patients with thin and long body shape and low BMI, releasing the lower pulmonary ligament is helpful to promote the expansion of the residual lung after right upper lobe resection and reduce the occurrence of postoperative residual cavity in patients.

ObjectiveTo investigate the mechanisms by which Huanglian Jiedutang （HLJDT） modulates microglial （MG） phenotypes through the sialic acid-binding Ig-like lectin 2 （SIGLEC2/CD22）/Src-homology-2-domain-containing protein tyrosine phosphatase-1 （SHP-1）/phosphorylated protein kinase B （p-Akt） signaling pathway， thereby promoting myelin repair and alleviating agitation-like behaviors in vascular dementia （VAD）. MethodsSixty C57BL/6J mice were randomly assigned to a sham （normal） group， model group， HLJDT low-， medium-， and high-dose groups （2.5， 5， and 10 g·kg^-1·d^-1）， and a risperidone group （2 mg·kg^-1·d^-1）， with 10 mice per group. VAD was induced by bilateral common carotid artery stenosis （BCAS）. From day 42， mice received drug interventions for 2 weeks. Agitation-like behaviors were assessed using the resident-intruder test. After behavioral testing， ventrolateral part of the ventromedial hypothalamus （VMHvl） tissues were collected. Western blot was used to measure protein levels of myelin oligodendrocyte glycoprotein （MOG）， myelin basic protein （MBP）， proteolipid protein （PLP）， inducible nitric oxide synthase （iNOS）， arginase-1 （Arg1）， CD86， CD206， and CD22， SHP-1， and p-Akt. Immunofluorescence was used to evaluate myelin-associated glycoprotein （MAG） intensity and the proportion of iNOS⁺/ionized calcium-binding adapter molecule 1 （Iba1）⁺ cells. ELISA was used to detect tumor necrosis factor-α （TNF-α）， interleukin （IL）-6， and IL-1β. ResultsCompared with the normal group， the model group exhibited markedly increased biting and aggressive behaviors and shortened attack latency （P<0.01）. MOG， MBP， and PLP protein levels and MAG fluorescence intensity were significantly reduced （P<0.05， P<0.01）. INOS and CD86 expression and TNF-α， IL-6， and IL-1β levels were significantly elevated （P<0.01）. CD22 and SHP-1 expression increased significantly （P<0.01）， whereas p-Akt expression decreased （P<0.01）. Compared with the model group， the medium- and high-dose HLJDT groups and the risperidone group showed markedly reduced biting and aggression （P<0.05， P<0.01） and prolonged attack latency （P<0.01）. MOG， MBP， and PLP levels and MAG fluorescence intensity were significantly increased （P<0.05， P<0.01）. INOS， CD86， TNF-α， IL-6， and IL-1β levels decreased significantly （P<0.05， P<0.01）. CD22 and SHP-1 expression decreased， while p-Akt expression increased significantly （P<0.05， P<0.01）. ConclusionHLJDT may modulate CD22/SHP-1/p-Akt signaling in the VMHvl， promote the shift of MG toward an anti-inflammatory and phagocytic phenotype， enhance myelin repair， and improve agitation-like behaviors in VAD mice.

Combined with elastic network model(ENM),the perturbation response scanning(PRS)has emerged as a robust technique for pinpointing allosteric interactions within proteins.Here,we proposed the PRS analysis of drug-target networks(DTNs),which could provide a promising avenue in network medicine.We demonstrated the utility of the method by introducing a deep learning and network perturbation-based framework,for drug repurposing of multiple sclerosis(MS).First,the MS comorbidity network was constructed by performing a random walk with restart algorithm based on shared genes between MS and other diseases as seed nodes.Then,based on topological analysis and functional annotation,the neurotransmission module was identified as the"therapeutic module"of MS.Further,perturbation scores of drugs on the module were calculated by constructing the DTN and introducing the PRS analysis,giving a list of repurposable drugs for MS.Mechanism of action analysis both at pathway and structural levels screened dihydroergocristine as a candidate drug of MS by targeting a serotonin receptor of se-rotonin 2B receptor(HTR2B).Finally,we established a cuprizone-induced chronic mouse model to evaluate the alteration of HTR2B in mouse brain regions and observed that HTR2B was significantly reduced in the cuprizone-induced mouse cortex.These findings proved that the network perturbation modeling is a promising avenue for drug repurposing of MS.As a useful systematic method,our approach can also be used to discover the new molecular mechanism and provide effective candidate drugs for other complex diseases.

Trauma can disrupt the body′s internal environment, resulting in organ dysfunction. This may manifest as symptoms such as acute respiratory distress, liver and kidney dysfunction, circulatory disorders and neurological damage. Mitochondrial quality control (MQC), encompassing processes like autophagy, dynamic changes, and biogenesis, plays an essential role in maintaining mitochondrial function. Stress responses following trauma can cause mitochondrial dysfunction and MQC imbalance, thereby exacerbating organ injury. Correcting MQC imbalance can improve organ function. Current researches on MQC in post-traumatic organ dysfunction mainly focuses on imbalance in specific MQC mechanism, lacking a systemic understanding of its incidence and progression. To this end, the authors reviewed the progress in researches on the impact of MQC imbalance on post-traumatic organ dysfunction, aiming to provide insights for clinical treatment.

Objective To develop a predictive model integrating clinical features,deep learning(DL),and radiomics based on T2-weighted imaging for prenatal assessment of postpartum hemorrhage(PPH)risk in high-risk pregnant women.Methods A total of 538 pregnant women with ultrasound-reported high-risk placenta accrete were retrospectively enrolled and divided into training,internal test,and external test cohorts.A nnUNet model was trained for automatic placental segmentation.Univariate and multivariate analyses were conducted on clinical features to identify those associated with PPH.Quantitative radiomic features were extracted from the placental region,and a random forest model was developed to predict estimated blood loss(EBL)and PPH risk.A DenseNet-based multi-task DL model was trained to predict PPH risk,EBL,and placenta previa status.Finally,a DL-radiomics ensemble(DRE)model was constructed by integrating clinical features,DL outputs,and radiomics scores.Diagnostic performance was evaluated using the area under the receiver operating characteristic curve(AUC)and DeLong test.Results The DRE model achieved AUC values of 0.874(95%CI:0.792-0.951)and 0.836(95%CI:0.648-0.974)in the internal and external test cohorts,respectively,significantly outperforming the standalone clinical,DL,and radiomics models.Incorporation of EBL regression improved the performance of the PPH classification model,with the external test AUC increasing from 0.261-0.788 to 0.836.Conclusion The DRE model integrating DL and radiomics can efficiently predict PPH risk and assist in the clinical management of high-risk pregnancies.

Objective:To analyze the multi antigen distribution characteristics of Rh blood group system in Shunde area of Guangdong Province,explore the feasibility of Rh phenotype compatible blood transfusion for blood recipients in this area,and formulate the precise blood transfusion strategies.Methods:From June 2022 to December 2024,113 226 hospitalized patients scheduled for blood transfusion in Shunde Hospital of Southern Medical University and 30 832 blood donors'blood samples provided by Shunde central blood station in the same period were detected for ABO blood group and Rh phenotype by microcolumn gel method,and the Rh phenotype data of the recipients and blood donors were compared and analyzed.Results:Among 113 226 blood samples,112 963 cases(99.77％)were RhD positive,with CCDee(54.96％)and CcDEe(28.21％)phenotypes being the main phenotypes;263 cases(0.23％)were RhD negative,with ccDee(50.19％)and CcDee(36.88％)as the main phenotype.Among 30 832 blood donor samples,CCDee(54.65％)and CcDEe(27.93％)were the main phenotypes of Rh phenotype with RhD positive.The positive rates of D,C,c,E and e antigens of blood recipients and blood donors were in the same order from high to low D＞e＞C＞c＞E.The frequency of e antigen in RhD positive recipients with different ABO blood groups was statistically different from that of blood donors(P＜0.05),while there was no statistical difference in the other four antigens(P＞0.05),the distribution of ccDEe phenotypes was statistically different(P＜0.05),but there was no statistical difference in the distribution of other eight phenotypes(P＞0.05).In RhD positive recipients,the probability of finding compatible blood for phenotype CcDEe was 100％,the probability of finding compatible blood for phenotype CCDee,CCDEe and DcDee was 54％-65％,and the probability of finding compatible blood for other phenotypes was less than 10％.Providing blood with CCDee and ccDEE phenotypes according to Rh blood matching scheme can meet the needs of more than 99％of patients with 9 Rh phenotype compatible blood transfusion in this region.Conclusion:Rh phenotype detection should be carried out for hospitalized patients to be transfused,and the precise transfusion strategy of Rh phenotype isotype or compatibility should be implemented to make the transfusion treatment of patients more safe and reliable.

Facing of mounting resource constraints and rising demands for personalization in medical education,regional anatomy teaching urgently requires transformation.In this paper,we focus on the regional anatomy of the thoracic wall,in order to explore a novel AI-driven teaching paradigm.Anchored in the core principle of"virtual-real integration with cadaveric dissection as the cornerstone,"the paradigm redefines educational objective and constructs an intelligent,closed-loop teaching model integrating students,computers,and instructors.Leveraging the robust support of digital intelligence(e.g.,DeepSeek),this paradigm incorporates interactive method including group collaboration,branching instruction,and gamified assessments.It achieves a comprehensive intelligent transformation of the entire teaching process-from goal setting and plan customization to activity implementation,task completion,outcome exchange,multidimensional evaluation,and reflective iteration.This new paradigm centers on medical students and leverages digital intelligence to activate deep personalized learning potential.It seamlessly integrates fundamental anatomical knowledge with clinical scenarios(e.g.,key anatomy in breast cancer surgery,flap design in breast reconstruction),and significantly enhances clinical decision-making abilities,scientific research and innovative thinking,as well as medical humanistic literacy,paving a new path for intelligent medical education.

Aim To explore the mechanism of the effect of siRNA-mediated MAGE-3 silencing on intesti-nal flora,gastric mucosal PTEN expression and liver metastasis in rats with gastric cancer based on MAPK/ERK signaling pathway.Methods Thirty rats were randomly divided into the normal(CO)group,model(MO)group,and MAGE-3 silenced(SM)group,with 10 rats in each group.The model of MO group and SM group was established by MNNG gavage meth-od.After successful modeling,the SM group was intri-toneally injected with 20 μg·kg-1 shRNA MAGE-3 lentiviral vector.The number of intestinal flora in rats was detected by selective medium of intestinal flora,the expression of PTEN in gastric mucosa was detected by immunohistochemistry,liver metastasis was detected by HE staining,and the protein expression of MAPK/ERK signaling pathway was detected by Western blot.The regulatory effect of siRNA-mediated MAGE-3 si-lencing on MAPK/ERK signaling pathway was verified in vitro.Results Compared with CO group,the con-tents of Enterococcus and Escherichia coli,the protein expressions of P-MEK1,P-ERK1 and P-ELK1 in MO group increased(P＜0.05),while the contents of Lactobacillus and Bifidobacterium and the expression of PTEN decreased(P＜0.05).In SM group,the con-tents ofEnterococcus,Escherichiacoli,P-MEK1,P-ERK1 and P-ELK1 protein expressions decreased(P＜0.05),while the contents of Lactobacillus,Bifidobac-terium and PTEN expression increased(P＜0.05).Compared with group CO,the protein expressions of P-MEK1,p-ERK1 and P-ELK1 in group MO were not significantly different(P＞0.05),while the protein expressions of P-MEK1,p-ERK1 and P-ELK1 in group SM were reduced compared with group MO(P＜0.05).Conclusions siRNA-mediated MAGE-3 si-lencing can significantly improve intestinal flora,pro-mote the expression of PTEN in gastric mucosa,and inhibit liver metastasis in rats with gastric cancer.The mechanism may be related to the inhibition of MAPK/ERK signaling pathway.

Objective:To construct a decision tree model to predict the risk of breast cancer in patients with pathological nipple discharge.Methods:A total of 157 patients with pathological nipple discharge,who were diagnosed and treated at Weifang Municipal Hospital of Traditional Chinese Medicine from January 2019 to April 2024 and met the inclusion criteria,were selected.A risk prediction model for concurrent breast cancer in patients with pathological nipple discharge was developed using Logistic regression analysis.A decision tree was then constructed,and the predictive performance of the model was assessed based on the area under the receiver operating characteristic curve(AUC).Re-sults:The incidence of concurrent breast cancer among patients with pathological nipple discharge was 24.2%.Accord-ing to the results of binary Logistic regression analysis,elevated CEA and CA 153 levels in nipple discharge,as well as bloody discharge,emerged as independent risk factors for the development of breast cancer in such patients(P<0.05).Based on these findings,a decision tree model was constructed to predict the risk of concurrent breast cancer in patients with pathological nipple discharge.The validation results showed that the Logistic regression model had an AUC value of 0.800,while the decision tree model achieved an AUC value of 0.889.Conclusions:The decision tree model,built upon the identified influencing factors,exhibits strong predictive power for the risk of developing concurrent breast can-cer in patients with pathological nipple discharge,thus facilitating more precise preoperative diagnoses by clinicians for these patients.