Depression is a common mental disorder that falls under the category of "stagnation syndrome" in traditional Chinese medicine （TCM）. Its complex pathogenesis poses challenges for the development of novel therapeutic agents. Currently， clinically used antidepressants are often accompanied by significant side effects， and statistics show that about one-third of patients do not respond to these medications. TCM demonstrates advantages in the treatment of depression through multi-target， multi-pathway and multi-mechanistic approaches. Pinelliae Rhizoma， a phlegm-resolving herb， exhibits effects such as drying dampness and resolving phlegm， as well as eliminating stuffiness and reducing masses. The characteristics of harmonizing Yin and Yang and resolving stagnation in the middle energizer align precisely with the pathogenesis of depression syndrome， demonstrating therapeutic efficacy in affected patients. Literature studies have found that the active ingredients of Pinelliae Rhizoma， such as cavidine， baicalein， β-sitosterol， as well as Pinelliae Rhizoma herb pairs， such as Pinelliae Rhizoma-Magnoliae Officinalis Cortex， Pinelliae Rhizoma-husked sorghum， Pinelliae Rhizoma-Prunellae Spica， exhibit significant antidepressant effects. Furthermore， TCM formulas containing Pinelliae Rhizoma as the principal therapeutic agent， such as Banxia Xiexin Tang， Banxia Houpo Tang， and Wendan Tang， as well as formulas incorporating Pinelliae Rhizoma like compound Xiaochaihu Tang， Chaihu Jia Longgu Muli Tang， and Erchen Tang， have also demonstrated favorable antidepressant efficacy. The antidepressant mechanism of these agents may involve modulation of 5-hydroxytryptamine （5-HT） and dopamine （DA） levels， up-regulation of brain-derived neurotrophic factor （BDNF） expression， regulation of the hypothalamus-pituitary-adrenal （HPA） axis， reduction of oxidative stress， modulation of nuclear transcription factor-κB （NF-κB） signaling pathway， and inhibition of microglia-mediated inflammatory responses. This review summarized the antidepressant mechanisms and clinical applications of the active components， herb pairs， and TCM formulas containing Pinelliae Rhizoma， aiming to provide a reference for modern research on the use of Pinelliae Rhizoma in antidepressant therapy.

Objective To analyze the relationship of protein intake level with high-sensitivity C-reactive protein (hs-CRP), interleukin-6 (IL-6), and tumor necrosis factor-α (TNF-α) in patients with diabetic kidney disease (DKD) and its influence on prognosis. Methods A total of 325 patients with DKD admitted from June 2021 to June 2024 were included and classified into a low protein group and a high protein group. The levels of hs-CRP, IL-6, and TNF-α were compared between the two groups of patients before follow-up and after 1 year of follow-up. The correlation was analyzed by linear mixed model. The incidence of endpoint events during follow-up and disease progression-free survival time were compared between the two groups. Results The inflammatory indicators exhibited no statistical differences between the two groups before follow-up (P>0.05). After 1 year of follow-up, the levels of hs-CRP, IL-6, and TNF-α in the two groups were higher than those before follow-up, and the levels in the high protein group were higher than those in the low protein group (P<0.05). Linear mixed model analysis suggested that the protein intake level, time, and the interaction term of protein intake level × time were correlated with the changes of hs-CRP, IL-6 and TNF-α levels (P<0.05). The incidence rate of endpoint events in the high-protein group during follow-up was 24.84% (40/161), which was significantly higher than 12.80% (21/164) in the low-protein group (χ²=7.724, P=0.005). The disease progression-free survival time was longer in the low-protein group than that in the high-protein group (Log Rank χ²=9.007, P=0.003). Conclusion The level of protein intake in patients with diabetic kidney disease is closely related to inflammatory response and prognosis.

AIM: To investigate the differences in morphological structure and retinal blood perfusion between the affected eye and the contralateral healthy eye using optical coherence tomography angiography(OCTA)in patients with idiopathic macular epiretinal membrane(IMEM)before and after surgery, and to evaluate the association of these parameters with functional and anatomical outcomes to inform prognostic assessment. METHODS:A prospective study was conducted at Zhejiang Provincial People's Hospital between January 2023 and December 2024. Consecutive patients diagnosed with unilateral IMEM were enrolled; the fellow eye served as an internal control. All participants underwent standardized ophthalmic evaluations, including optical coherence tomography(OCT), OCTA, and color fundus photography. Key quantitative parameters assessed included best-corrected visual acuity(BCVA), central macular thickness(CMT), foveal avascular zone(FAZ)area, vessel density in the inner capillary plexus(ICP), superficial capillary plexus(SCP), deep capillary plexus(DCP), and choroidal capillary perfusion area(CCPA). Measurements were obtained preoperatively and at 1 and 3 mo postoperatively. Correlation analyses were performed between the above parameters and postoperative BCVA and CMT.RESULTS: This study enrolled 30 patients(60 eyes)diagnosed with IMEM, comprising 14 males and 16 females, with a mean age of 65.4±10.8 y.At baseline, IMEM-affected eyes demonstrated significantly reduced BCVA, DCP density, and FAZ area, alongside significantly increased CMT and CCPA, compared with contralateral controls. Following vitrectomy with membrane peeling, CMT decreased significantly at both 1 and 3 mo(both P<0.05)postoperatively; DCP density and BCVA showed significant improvement(both P<0.05). No significant change in FAZ area was observed postoperatively(P>0.05). At 3 mo postoperatively, BCVA of the affected eye was negatively correlated with CMT(r=-0.549, P=0.022). At 1 mo postoperatively, CMT was negatively correlated with preoperative DCP and FAZ, positively correlated with preoperative CMT, and positively correlated with ICP and SCP at 1 mo postoperatively, and negatively correlated with FAZ at 1 mo postoperatively(all P<0.05). Furthermore, CMT at 3 mo postoperatively was negatively correlated with preoperative DCP(r=-0.498,P=0.042).CONCLUSION:In patients with IMEM, the affected eyes exhibit significantly reduced DCP density and FAZ area, alongside increased CMT and CCPA. Following vitrectomy with membrane peeling, CMT decreased progressively, DCP density demonstrated partial restoration, and vision improved gradually. Preoperatively, smaller CMT larger DCP, and FAZ were associated with more favorable surgical outcomes; postoperatively, smaller ICP and SCP densities—combined with a larger FAZ—also correlated with better functional recovery.

Dietary interventions such as fasting are gaining increasing attention for their synergistic effects in anti-tumor therapy, yet the precise underlying mechanisms remain incompletely understood. Recent research has unveiled a novel mode of cell death named “mitoxyperilysis”, providing a fresh perspective on the molecular mechanisms by which fasting may interfere with tumor treatment. This form of death is primarily triggered by the synergy between metabolic dysfunction and innate immune activation. Its mechanism involves the mTORC2 signaling pathway mediating prolonged abnormal contact between damaged mitochondria and the plasma membrane. This leads to massive local release of reactive oxygen species (ROS), which further induces lipid peroxidation of the plasma membrane, ultimately resulting in the physical rupture and death of the cell. The most significant distinction between mitoxyperilysis and classical cell death pathways lies in its independence from caspases and GSDMD. This comment aims to systematically elucidate the process, molecular mechanisms, and differences from other classical cell death pathways of mitoxyperilysis, while also exploring its potential for clinical translation in oncological diseases. Targeting induction of mitoxyperilysis may enhance the efficacy of existing anti-tumor drugs and overcome chemotherapy resistance. However, intervention protocols require further optimization to achieve an optimal balance between safety and therapeutic effectiveness in clinical application.

ObjectiveTo analyze the etiological characteristics and risk factors of autosomal dominant polycystic kidney disease （ADPKD） complicated with urinary tract infection （UTI）. MethodsA retrospective analysis was performed on 244 patients with ADPKD admitted to the Department of Nephrology. The patients were stratified into a study group （n=138） and a control group （n=106） according to the presence or absence of concurrent UTI. All patients in the study group underwent etiological testing and drug susceptibility testing. Clinical data of both groups were collected to identify the risk factors for ADPKD complicated with UTI. ResultsA total of 105 pathogens were detected in 138 cases in the study group， including 79 Gram-negative bacteria， 20 Gram-positive bacteria and 6 fungi. Escherichia coli showed a relatively high resistance rate to ampicillin， piperacillin and ciprofloxacin. Enterococcus faecalis had a relatively high resistance rate to tetracycline. There were statistically significant differences between the study group and the control group in terms of gender， history of urinary tract infection， C-reactive protein （CRP）， increased urine red blood cells， increased urine white blood cells， increased percentage of neutrophils， blood sodium， blood calcium， total cholesterol， serum iron and transferrin saturation （P<0.05）. Multivariate binary Logistic regression analysis revealed that female gender （OR=2.236， P=0.004）， history of urinary tract infection （OR=2.383， P=0.002）， increased urine white blood cells （OR=2.726， P=0.001）， increased percentage of neutrophils （OR=1.040， P=0.010）， elevated C-reactive protein （OR=1.011， P=0.007） and elevated blood calcium （OR=4.389， P=0.024） were risk factors of urinary tract infection in ADPKD patients （P<0.05）. ConclusionThe main pathogens of UTI in patients with ADPKD are Gram-negative bacteria. Female， previous history of urinary tract infection， urinary leukocytosis， increased percentage of neutrophils， increased CRP and increased serum calcium are risk factors of UTI.

Forensic medicine has been designated as a first-level discipline,presenting new opportunities and challenges for the development of forensic medicine.Since the 1980s,the establishment of foren-sic medicine discipline and the cultivation of high-level forensic talents have become hot topics in the development of forensic medicine in China.Since the 13th Five-Year Plan,the forensic team of Shanxi Medical University has been aiming at the forefront,proposing the development goals of"Five First-class"and the discipline development path"Six Major Achievements".It has selected benchmark disci-plines,identified gaps in disciplinary development,unified thoughts,formulated completion timelines,concentrated superior resources,assigned tasks to individuals,and created an"Organized Fill-in-the-Blank Format"forensic medicine discipline construction model with the characteristics of the new era.The construction model of forensic medicine has achieved good results in the goals,discipline frame-work,scientific research,talent cultivation,discipline team and platform construction,forming a rela-tively complete discipline construction and management system,and accumulating valuable experience for the construction of first-level discipline and high-level talent cultivation of forensic medicine.

Objective To explore a deep learning-based automatic bone age estimation model for elbow joint X-ray images of Chinese Han adolescents and children and evaluate its performance.Methods A total of 943(517 males and 426 females)elbow joint frontal view X-ray images of Chinese Han ado-lescents and children aged 6.00 to<16.00 years were collected from East,South,Central and North-west China.Three experimental schemes were adopted for bone age estimation.Scheme 1:Directly in-put preprocessed images into the regression model;Scheme 2:Train a segmentation network using"key elbow joint bone annotations"as labels,then input segmented images into the regression model;Scheme 3:Train a segmentation network using"full elbow joint bone annotations"as labels,then in-put segmented images into the regression model.For segmentation,the optimal model was selected from U-Net,UNet++and TransUNet.For regression,VGG16,VGG19,InceptionV2,InceptionV3,ResNet34,ResNet50,ResNet101 and DenseNet121 models were selected for bone age estimation.The dataset was randomly split into 80%(754 samples)for training and validation for model fitting and hyperparameter tuning,and 20%(189 samples)as an internal test set to test the performance of the trained model.An additional 104 elbow joint X-ray images from the same demographic and age group were col-lected and used as an external test set.Model performance was evaluated by comparing the mean ab-solute error(MAE),root mean square error(RMSE),accuracies within±0.7 years(P±0.7 years)and±1.0 years(P±1.0 years)between the estimated age and the actual age,and by drawing radar charts,scat-ter plots,and heatmaps.Results When segmented with Scheme 3,the UNet++model achieved good segmentation performance with a segmentation loss of 0.000 4 and an accuracy of 93.8%at a learning rate of 0.000 1.In the internal test set,the DenseNet121 model with Scheme 3 yielded the best results with MAE,P±0.7 years and P±1.0 years being 0.83 years,70.03%,and 84.30%,respectively.In the external test set,the DenseNet121 model with Scheme 3 also performed best,with an average MAE of 0.89 years and an average RMSE of 1.00 years.Conclusion When performing automatic bone age estima-tion using elbow joint X-ray images in Chinese Han adolescents and children,it is recommended to use the UNet++model for segmentation.The DenseNet121 model with Scheme 3 achieves optimal per-formance.Using segmentation networks,especially that trained with annotation areas encompassing the full elbow joint including the distal humerus,proximal radius,and proximal ulna,can improve the ac-curacy of bone age estimation based on elbow joint X-ray images.

Objective To explore a deep learning network model suitable for bone age estimation using shoulder joint X-ray images in Chinese Han adolescents.Methods A retrospective collection of 1 286 shoulder joint X-ray images of Chinese Han adolescents aged 12.0 to<18.0 years(708 males and 578 females)was conducted.Using random sampling,approximately 80%of the samples(1 032 cases)were selected as the training and validation sets for model learning,selection and optimization,and the other 20%samples(254 cases)were used as the test set to evaluate the model's generalization ability.The original single-channel shoulder joint X-ray images and dual-channel inputs combining original images with segmentation labels(manually annotated shoulder joint regions multiplied pixel-by-pixel with original images,followed by segmentation via the U-Net++network to retain only key shoulder joint region information)were respectively input into four network models,namely VGG16,ResNet18,ResNet50 and DenseNet121 for bone age estimation.Additionally,manual bone age estimation was con-ducted on the test set data,and the results were compared with the four network models.The mean absolute error(MAE),root mean square error(RMSE),coefficient of determination(R2),and Pear-son correlation coefficient(PCC)were used as main evaluation indicators.Results In the test set,the bone age estimation results of the four models with dual-channel input of shoulder joint X-ray images outperformed those with single-channel input in all four evaluation indicators.Among them,DenseNet121 with dual-channel input achieved best results with MAE of 0.54 years,RMSE of 0.82 years,R2 of 0.76,and PCC(r)of 0.88.Manual estimation yielded an MAE of 0.82 years,ranking second only to dual-channel DenseNet121.Conclusion The DenseNet121 model with dual-channel input combined with original images and segmentation labels is superior to manual evaluation results,and can effectively estimate the bone age of Chinese Han adolescents.

Objective To investigate the correlation of serum human epididymis protein 4(HE4)and lung injury Prediction(LIPS)score with sepsis-associated acute respiratory distress syndrome(ARDS)and 28 d mortality.Methods A total of 207 patients with sepsis admitted to the hospital from January 2021 to January 2024 were selected.According to the presence or absence of ARDS,the patients were divided into ARDS group(73 cases)and non-ARDS group(134 cases).According to the 28 d survival,the ARDS group was further di-vided into death group(26 cases)and survival group(47 cases).HE4 level was detected by electrochemilumi-nescence,and LIPS score was calculated.Multivariate Logistic regression model was used to analyze the influ-encing factors of death in ARDS patients.Point biserial correlation was used to analyze the correlation between serum HE4,LIPS score and 28 d death in ARDS patients.The receiver operating characteristic(ROC)curve was used to evaluate the value of serum HE4 and LIPS score in the diagnosis of sepsis-associated ARDS and predicting 28 d mortality.Results Compared with non-ARDS group,the serum HE4 level and LIPS score were significantly increased in ARDS group(P<0.05).The independent risk factors for sepsis-associated ARDS were increased SOFA score,increased blood lactic acid,increased HE4 and increased LIPS score(P<0.05).The 28 d mortality of 73 patients with sepsis-associated ARDS was 35.62%(26/73).Compared with the survival group,the serum HE4 and LIPS scores were increased in the death group(P<0.05).Serum HE4 and LIPS scores were positively correlated with 28 d mortality in patients with sepsis-associated ARDS(r=0.605,0.579,P<0.05).The area under the curve(AUC)of serum HE4 combined with LIPS score in the di-agnosis of sepsis-associated ARDS was 0.909,which was larger than 0.828 and 0.806 of serum HE4 and LIPS score alone(Z=3.360,3.387,all P<0.05).The AUC of serum HE4 combined with LIPS score in predicting 28 d mortality of patients with sepsis-associated ARDS was 0.891,which was larger than 0.808 and 0.779 of by serum HE4 and LIPS score alone(Z=2.028,2.017,all P<0.05).Conclusion The elevated serum HE4 level and LIPS score are independent risk factors for sepsis-associated ARDS,and are closely related to 28 d mortality.The combination of serum HE4 and LIPS score has a high value in the diagnosis of sepsis-associated ARDS and the prediction of 28 d mortality.

In the past, aortic dissection, aortic aneurysm, and other aortic diseases, primarily rely on surgical intervention. In recent years, due to breakthroughs in materials science, endovascular therapy has become the first choice for the surgical treatment of most aortic diseases. However, traditional endovascular repair cannot fully meet the clinical needs for certain complex lesions involving the aortic arch and the originations of visceral arteries. The emergence of physician-modified stent technology has brought new hope for the treatment of complex aortic diseases. This article provides a detailed introduction to the concept, development, technical characteristics, and applications of physician-modified stents in the treatment of aortic diseases, analyzing their advantages and limitations. Physician-modified stents serve as a powerful complement to traditional endovascular interventions and commercial branched stents, yet further research and refinement are still required.