Cardiovascular disease is one of the most common causes of death in the world,and related western drugs usually have obvious side effects.Traditional Chinese medicine,characterized by its multi-component and multi-target,has unique advantage in the prevention and treatment of cardiovascular diseases.Cornus Officinal is a histor-ically used plants with medicinal and edible properties.Ancient books and modern literatures have shown that Cor-nus Officinal has the potential to prevent and treat cardiovascular diseases.With the in-depth study of the chemical composition and pharmacological effect of Cornus Officinal,its pharmacodynamic substances and mechanism in the prevention and treatment of cardiovascular diseases are gradually clear.This article reviews the pathways and targets of Cornus Officinal in the prevention and treatment of cardiovascular diseases in recent years,and summarizes its potential effective components,in order to provide theoretical support for the clinical application and traditional Chinese medicine development.

Objective To explore the value of deep learning image reconstruction(DLIR)algorithm to improve the quality of low keV monochromatic portal vein images of energy spectrum CT.Methods Fifty patients who underwent enhanced upper abdominal energy spectrum CT scan were selected.Mixed-model adaptive statistical iterative reconstruction-Veo(50%ASIR-V)algorithm and high-deep learning image reconstruction(DLIR-H)algorithm were used to obtain monochromatic images at 40-70 keV(with intervals of 10 keV).The CT and standard deviation(SD)values of the portal vein trunk,left and right branches,and erector spinae muscle were measured in the transverse position,and the signal-to-noise ratio(SNR)and portal vein contrast-to-noise ratio(CNR)were calculated for objective evaluation.The portal vein image quality between the two algorithms and different energy was subjectively scored by two physicians.Results In terms of objective evaluation:compared with 50%ASIR-V,the CNR and SNR of portal vein in monochromatic DLIR-H images at the same keV between 40-70 keV energy levels were increased while the SD value was decreased(P＜0.05),and the CT value was unchanged;there was no statistical difference in the magnitude of change in CNR between the two algorithms at different energy levels(P＞0.05);there was a statistically significant difference in the magnitude of change in SNR and SD value(P＜0.05)and the magnitude of change was the largest at 40 keV;comparison between different energy levels of DLIR-H,the CNR and SD value of 40 keV DLIR-H were the highest(P＜0.05),and there was no significant difference in the SNR(P＞0.05).In terms of subjective evaluation:there was no significant difference between the subjective scores of the two algorithms at the same keV from 40-70 keV(P＞0.05),and the two reconstruction algorithms at 40 keV and 50 keV had the highest subjective scores between different keV.Conclusion The DLIR algorithm can reduce the noise of low keV monochromatic images,improve the image quality of portal vein.

BACKGROUND:Knee finite element modelling can provide insight into knee mechanics,but its complex image segmentation is more difficult for researchers.With the development of deep learning techniques,deep learning techniques have been widely used in knee joint finite element modelling.OBJECTIVE:To replace the manual segmentation step in finite element modelling of the knee joint by using 3D Swin UNETR in combination with a semi-automatic segmentation technique for statistical shape models.METHODS:Manual(artificial)knee joint finite element model was developed based on MR and semi-automatic knee joint finite element model was developed based on 3D Swin UNETR+statistical shape model segmentation.The same loads and boundary conditions were applied to both models.Validation was performed by calculating the Dice similarity coefficient,mean distance,and comparing the peak equivalent stresses,maximum principal stresses,and maximum shear stresses of the two models.RESULTS AND CONCLUSION:(1)The Dice similarity coefficients of the manual and semi-automatic segmented femur and tibia were more than 98％,and the average distances were less than or equal to(0.35±0.08)mm.(2)With the longitudinal load of 750 N and 10 Nm internal overturning moment applied to the femur tip of both manual and semi-automatic finite element models,the peak equivalent stress,maximum principal stress,and maximum shear stresses of meniscus in manual finite element model were 14.12,18.54,and 7.35 MPa;peak equivalent force,maximum principal stress,and maximum shear stress of femoral cartilage were 2.22,2.15,and 1.18 MPa;peak equivalent force,maximum principal stress,and maximum shear stress of tibial cartilage were 2.50,1.91,and 1.41 MPa;semi-automatic finite element model of meniscus:peak equivalent force,maximum principal stress,and maximum shear stress were 14.93,18.53,and 7.75 MPa.The peak equivalent force,maximum principal stress,and maximum shear stress of femoral cartilage were 2.26,2.18,and 1.20 MPa;the peak equivalent stress,maximum principal stress,and maximum shear stress of tibial cartilage were 2.60,1.91,and 1.46 MPa.The peak equivalent stress,maximum principal stress,and maximum shear stress of manual and semi-automatic finite element models were basically consistent,with no significant difference(P＞0.05).(3)The semi-automatic segmentation technique proposed in this study can replace manual segmentation in creating accurate finite element models of the knee joint.

Objective To explore the value of deep learning image reconstruction(DLIR)algorithm to improve the quality of low keV monochromatic portal vein images of energy spectrum CT.Methods Fifty patients who underwent enhanced upper abdominal energy spectrum CT scan were selected.Mixed-model adaptive statistical iterative reconstruction-Veo(50%ASIR-V)algorithm and high-deep learning image reconstruction(DLIR-H)algorithm were used to obtain monochromatic images at 40-70 keV(with intervals of 10 keV).The CT and standard deviation(SD)values of the portal vein trunk,left and right branches,and erector spinae muscle were measured in the transverse position,and the signal-to-noise ratio(SNR)and portal vein contrast-to-noise ratio(CNR)were calculated for objective evaluation.The portal vein image quality between the two algorithms and different energy was subjectively scored by two physicians.Results In terms of objective evaluation:compared with 50%ASIR-V,the CNR and SNR of portal vein in monochromatic DLIR-H images at the same keV between 40-70 keV energy levels were increased while the SD value was decreased(P＜0.05),and the CT value was unchanged;there was no statistical difference in the magnitude of change in CNR between the two algorithms at different energy levels(P＞0.05);there was a statistically significant difference in the magnitude of change in SNR and SD value(P＜0.05)and the magnitude of change was the largest at 40 keV;comparison between different energy levels of DLIR-H,the CNR and SD value of 40 keV DLIR-H were the highest(P＜0.05),and there was no significant difference in the SNR(P＞0.05).In terms of subjective evaluation:there was no significant difference between the subjective scores of the two algorithms at the same keV from 40-70 keV(P＞0.05),and the two reconstruction algorithms at 40 keV and 50 keV had the highest subjective scores between different keV.Conclusion The DLIR algorithm can reduce the noise of low keV monochromatic images,improve the image quality of portal vein.

Gastric cancer remains one of the most prevalent and lethal malignancies of the digestive tract worldwide,underscoring the urgent need for more effective targeted therapeutic strategies.Poly(ADP-ri-bose)polymerase(PARP)inhibitors have demonstrated remarkable efficacy in tumors with homologous recombination repair(HRR)deficiency;however,their clinical application in gastric cancer remains limited.Clinical evidence suggests that patients harboring Helicobacter pylori infection in combination with HRR gene mutations exhibit a significantly elevated risk of developing gastric cancer,thereby supporting the potential benefit of PARP inhibition in this setting.In this study,a kinase inhibitor library was screened in combination with the PARP inhibitor olaparib in gastric cancer cells.And we identify the cy-clin-dependent kinase 8/19(CDK8/19)inhibitor Senexin A as a compound that synergistically enhances the cytotoxic effect of PARP inhibition(P<0.05).Phenotypic validation using CCK-8 and colony for-mation assays demonstrated that the combination treatment significantly suppressed cellular proliferation and clonogenic potential compared to either monotherapy(P<0.0001).Mechanistically,alkaline comet assays revealed a significant increase in DNA damage in the combination treatment group relative to either single-agent group(P<0.0001),suggesting that the synergistic effect results from the exacerbation of DNA damage via impaired DNA repair mechanisms.In addition,treatment with CDK8/19 inhibitors a-lone markedly increased the formation of γH2AX and 53BP1 foci in irradiated gastric cancer cells(P<0.0001),indicating inhibition of DNA damage repair pathways.Transcriptome sequencing further re-vealed that CDK8/19 inhibition impacts critical cellular pathways,including DNA repair,cell cycle reg-ulation,and RNA splicing.Co-immunoprecipitation assays confirmed that inhibition of CDK8/19 kinase activity significantly reduces the phosphorylation level of PARP1,suggesting a potential regulatory inter-action.Immunohistochemical analysis of tumor and adjacent non-tumor tissues from gastric cancer pa-tients demonstrated that CDK8 is significantly overexpressed in tumor tissues,supporting its potential as both a prognostic biomarker and a therapeutic target.Collectively,this study elucidates a mechanistic ba-sis by which CDK8/19 inhibition enhances the sensitivity of gastric cancer cells to PARP inhibitors.These findings provide a strong rationale for the combined use of CDK8/19 and PARP inhibitors as a tar-geted therapeutic strategy and offer promising translational implications for advancing personalized medi-cine in gastric cancer treatment.

Gastric cancer remains one of the most prevalent and lethal malignancies of the digestive tract worldwide,underscoring the urgent need for more effective targeted therapeutic strategies.Poly(ADP-ri-bose)polymerase(PARP)inhibitors have demonstrated remarkable efficacy in tumors with homologous recombination repair(HRR)deficiency;however,their clinical application in gastric cancer remains limited.Clinical evidence suggests that patients harboring Helicobacter pylori infection in combination with HRR gene mutations exhibit a significantly elevated risk of developing gastric cancer,thereby supporting the potential benefit of PARP inhibition in this setting.In this study,a kinase inhibitor library was screened in combination with the PARP inhibitor olaparib in gastric cancer cells.And we identify the cy-clin-dependent kinase 8/19(CDK8/19)inhibitor Senexin A as a compound that synergistically enhances the cytotoxic effect of PARP inhibition(P<0.05).Phenotypic validation using CCK-8 and colony for-mation assays demonstrated that the combination treatment significantly suppressed cellular proliferation and clonogenic potential compared to either monotherapy(P<0.0001).Mechanistically,alkaline comet assays revealed a significant increase in DNA damage in the combination treatment group relative to either single-agent group(P<0.0001),suggesting that the synergistic effect results from the exacerbation of DNA damage via impaired DNA repair mechanisms.In addition,treatment with CDK8/19 inhibitors a-lone markedly increased the formation of γH2AX and 53BP1 foci in irradiated gastric cancer cells(P<0.0001),indicating inhibition of DNA damage repair pathways.Transcriptome sequencing further re-vealed that CDK8/19 inhibition impacts critical cellular pathways,including DNA repair,cell cycle reg-ulation,and RNA splicing.Co-immunoprecipitation assays confirmed that inhibition of CDK8/19 kinase activity significantly reduces the phosphorylation level of PARP1,suggesting a potential regulatory inter-action.Immunohistochemical analysis of tumor and adjacent non-tumor tissues from gastric cancer pa-tients demonstrated that CDK8 is significantly overexpressed in tumor tissues,supporting its potential as both a prognostic biomarker and a therapeutic target.Collectively,this study elucidates a mechanistic ba-sis by which CDK8/19 inhibition enhances the sensitivity of gastric cancer cells to PARP inhibitors.These findings provide a strong rationale for the combined use of CDK8/19 and PARP inhibitors as a tar-geted therapeutic strategy and offer promising translational implications for advancing personalized medi-cine in gastric cancer treatment.

AIM: To observe the changes of retinal nerve fiber layer(RNFL)thickness and radial peripheral capillary(RPC)density in patients with unilateral branch retinal vein occlusion(BRVO), and further analyze the correlation between RPC density and RNFL thickness.METHODS: Observational study. Totally 37 patients with unilateral BRVO diagnosed at the ophthalmology department of First Hospital of Qinhuangdao from October 2020 to January 2022 were selected, the 37 affected eyes were the unilateral BRVO group, and 37 fellow healthy eyes were the contralateral unaffected group, and 35 healthy individuals(35 right eyes were selected)without ocular diseases during the same period were selected as the normal control group. The best corrected visual acuity, intraocular pressure, anterior segment, fundus and optical coherence tomography angiography(OCTA)were examined in both eyes of all BRVO patients and healthy individuals. The central macular thickness(CMT), the RNFL thickness, and the optic disc-AV crossing distance(DAVD)were measured by built-in software of the OCTA equipment. The optimized U-net algorithm was used to eliminate the large blood vessels, and then the RPC density was calculated. The CMT, RNFL thickness and RPC density were compared among the three groups. And the correlations of the RPC density with the CMT, RNFL thickness, and the DAVD were investigated.RESULTS: Compared with the contralateral unaffected group and the normal control group, the CMT and the RNFL thickness were significantly thickened in the unilateral BRVO group(all P<0.05); there were no statistical differences in the CMT and the RNFL thickness between the contralateral unaffected group and the normal control group(all P>0.05). The RPC density in the unilateral BRVO group increased compared with the contralateral unaffected group and decreased compared with the normal control group, but there was no statistically difference(all P>0.05). However, the RPC density in the contralateral unaffected group decreased compared with the normal control group(P<0.05). The RPC density in the unilateral BRVO group was not correlated with the CMT(P=0.960), but positively correlated with the RNFL thickness(r=0.401, P=0.014)and negatively correlated with the DAVD(r=-0.339, P=0.040).CONCLUSION: The RNFL thickened significantly and the RPC density did not change significantly in the optic disc area of BRVO patients. The RPC density is positively correlated with the RNFL thickness, indicating that the RNFL thickness can be used as a monitoring indicator to analyze and study the damage degree of the RPC density.

Objective:To explore the mechanism of Danxing Zhishuang Prescription in the treatment of Parkinson's disease (PD) by combining network pharmacology with animal models.Methods:TCMSP, BATMAN database, Genecards, and OMIM databases were retrieved to obtain the active components and action targets of Danxing Zhishuang Prescription. Venny 2.1.0 was used to intersect drug targets and PD related genes, and a protein interaction network of the intersection targets was constructed using the STRING 12.0 platform. Topology analysis was performed using Cytoscape 3.10.0 software to identify the key targets of Danxing Zhishuang Prescription on PD; GO functional and KEGG pathway enrichment analysis was performed on key targets using the WeChat platform, and molecular docking was validated through AutoDockTools 1.5.7. Using a random number table method, mice were divided into a blank control group, a model group, and a Danxing Zhishuang Prescription group, with 20 mice in each group; except for the blank group, all other groups of mice were orally administered fisetin to prepare PD models; Danxing Zhishuang Prescription group was orally administered with concentrated Danxing Zhishuang Prescription at a dosage of 10.5 g/kg, while the blank group and model group were orally administered with 0.2 ml of physiological saline for 21 days; Western blot was used to detect the expressions of Akt1, Bcl-2, Bax, and α-Syn proteins.Results:359 intersection targets, 69 core targets, and 185 active components were obtained the treatment of PD with Danxing Zhishuang Prescription. The main active components included quercetin, kaempferol, phenylalanine, etc., and the key targets were AKT1, TP53, TNF, ESR1, etc. KEGG analysis revealed several key signaling pathways, such as AGE-RAGE, PI3K-Akt, fluid shear stress and atherosclerosis signaling pathways. The validation experiment results showed that compared with the model group, the expression of Bcl-2 protein was up-regulated ( P<0.01), and the expressions of Bax, Akt1, and α-Syn proteins were down-regulated in the Danxing Zhishuang Prescription group ( P<0.01). Conclusions:Danxing Zhishuang Prescription has the advantages of multi target and multi pathway treatment for PD. Its mechanism may be related to down-regulating the expressions of Bax, Akt1, and α-Syn proteins, improving brain blood supply, regulating neurotransmitter balance, inhibiting oxidative stress response, and promoting nerve regeneration.

Objective To investigate the needs and gains of eight-year clinical medicine program students during their oncology internships,and provide reference for the reform of clinical teaching in oncology.Methods A ques-tionnaire survey was conducted among 52 students from Peking Union Medical College,Tsinghua University School of Medicine,and Peking Union Medical College"4+4"medical doctor program who underwent internships in the Department of Oncology at Peking Union Medical College from July 2023 to June 2024 in order to examine their basic knowledge of oncology,the courses they are interested in,their preference for teaching methods and the gains from the internships.The exam was conducted before and after the internship.Results All 52 students participated in the survey and examination.Most students were interested in clinical diagnosis and treatment,new drug develop-ment and progress in basic research.All students acknowledged that their ability to solve actual clinical problems had been improved after the internship in oncology,51(98.08%)recognized that their capacity of literature searching and reviewing,integrating the information and reasoning had improved,while 50(96.15%)believed that their capacity to read Computed Tomography(CT)images or perform imaging diagnosis had improved.The number of students who were interested in oncology increased from 41(78.85%)before the internship and up to 47(90.38%)after the training.The average score of the students before internship was 63.88±8.90,and then signif-icantly increased up to 82.94±9.12 afterwards.Conclusions Eight-year program students of clinical medicine are quite interested in oncology,their learning and training outcomes have been further improved through the clinical training during internship.

Objective:To investigate the factors affecting the efficacy of 131I treatment for Graves′ disease (GD) and to construct a predictive model for the treatment outcomes of 131I therapy. Methods:Retrospective analysis of the treatment efficacy was performed on 2 190 patients (547 males, 1 643 females, age (42.9±12.4) years) with GD, who received initial 131I treatment in Tianjin Medical University General Hospital between October 2013 and May 2018. Univariate analysis ( χ2 test, et al) and logistic regression were performed to analyze the possible factors affecting the efficacy of 131I treatment. An efficacy prediction model for 131I treatment of GD was constructed, and decision curve analysis (DCA) was used to evaluate the clinical utility of the prediction model. Results:The overall effectiveness rate of 131I treatment for GD patients was 99.95%(2 189/2 190), with a total cure rate of 83.74%(1 834/2 190), among which 94.11%(1 726/1 834) were cured after a single treatment. Pre-treatment thyroid mass was identified as an independent risk factor affecting the efficacy of initial 131I treatment (odds ratio ( OR)=0.983(95% CI: 0.977-0.989), P<0.001). The clinical cure rate was higher in patients who received an adequate dose of 131I compared with that in patients who didn′t receive an adequate dose (79.97%(1 537/1 922) vs 70.52%(189/268); χ2=12.57, P<0.001), but it did not increase the incidence of hypothyroidism within one year. A predictive model was constructed, and it was found that thyroid mass and disease duration had a relatively high impact on the clinical cure rate. The concordance index (C-index) of the predictive model was 0.623(95% CI: 0.593-0.654). DCA indicated that the predictive model offered substantial net benefits across a wide range of probability thresholds. Conclusions:131I treatment is effective in most patients with GD. The predictive model for efficacy of initial 131I treatment developed in this study can assist in evaluating treatment outcomes and help clinicians select the most suitable 131I treatment dose, enhancing clinical decision-making.