OBJECTIVE To investigate the effects and mechanisms of Lycium ruthenicum Murr. in improving sleep. METHODS Network pharmacology was employed to identify the active components of L. ruthenicum and their associated disease targets， followed by enrichment analysis. A caffeine‑induced zebrafish model of sleep deprivation was established ， and the zebrafish were treated with L. ruthenicum Murr. extract （LRME） at concentrations of 0.1， 0.2 and 0.4 mg/mL， respectively； 24 h later， behavioral changes of zebrafish and pathological alterations in brain neurons were subsequently observed. The levels of inflammatory factors [interleukin-6 （IL-6）， IL-1β， IL-10， tumor necrosis factor-α （TNF-α）]， oxidative stress markers [superoxide dismutase （SOD）， malondialdehyde （MDA）， glutathione peroxidase （GSH-Px）， catalase （CAT）]， and neurotransmitters [5- hydroxytryptamine （5-HT）， γ-aminobutyric acid （GABA）， glutamic acid （Glu）， dopamine （DA）， and norepinephrine （NE）] were measured. The protein expression levels of protein kinase B1 （AKT1）， phosphorylated AKT1 （p-AKT1）， epidermal growth factor receptor （EGFR）， B-cell lymphoma 2 （Bcl-2）， sarcoma proto-oncogene，non-receptor tyrosine kinase （SRC）， and heat shock protein 90α family class A member 1 （HSP90AA1） in the zebrafish were also determined. RESULTS A total of 12 active components and 176 intersecting disease targets were identified through network pharmacology analysis. Among these， apigenin， naringenin and others were recognized as core active compounds， while AKT1， EGFR and others served as key targets； EGFR tyrosine kinase inhibitor resistance signaling pathway was identified as the critical pathway. The sleep improvement rates in zebrafish of LRME low-， medium-， and high-dose groups were 54.60%， 69.03% and 77.97%， 开发。E-mail：hjp_yft@163.com respectively， while the inhibition ratios of locomotor distance were 0.57， 0.83 and 0.95， respectively. Compared with the model group， the number of resting counts， resting time and resting distance were significantly increased/extended in LRME medium- and high-dose groups （P＜0.05）. Neuronal damage in the brain was alleviated. Additionally， the levels of IL-6， IL-1β， TNF-α， MDA， Glu， DA and NE， as well as the protein expression levels of AKT1， p-AKT1， EGFR， SRC and HSP90AA1， were markedly reduced （P＜0.05）， while the levels of IL-10， SOD， GSH-Px， CAT， 5-HT and GABA， as well as Bcl-2 protein expression， were significantly elevated （P＜0.05）. CONCLUSIONS L. ruthenicum Murr. demonstrates sleep-improving effects， and its specific mechanism may be related to the regulation of inflammatory responses， oxidative stress， neurotransmitter balance， and the EGFR tyrosine kinase inhibitor resistance signaling pathway.

Background: Patients with coarctation of the aorta (CoA) and an interrupted aortic arch (IAA) may present with small mitral valves (MVs) and a reduced left ventricular (LV) volume. Biventricular repair (BVR) in these patients is dependent on adequate size of the left cardiac structures.Purpose: This study evaluated the impact of the hemodynamic characteristics of atrial septal defects (ASDs) on MV growth following surgical repair. Methods: We retrospectively reviewed the data of patients diagnosed with CoA or IAA between 2007 and 2024. The z score for MV size measured 6 months postoperatively (Z2) was compared with the preoperative MV size (Z1). The factors associated with MV growth were also studied. Results: A total of 161 patients with CoA or IAA were included. Transthoracic echocardiography was used to assess the MV and LV dimensions preoperatively and 6 months postoperatively. Of the cohort, 155 (96.3%) underwent initial BVR and 6 underwent single-ventricle palliation. MV z scores significantly increased following BVR (mean change: +0.45±1.35; P<0.001) but decreased after single-ventricle repair (-0.56±0.49, P=0.04). Multivariate analysis identified the initial MV z score and ASD pressure gradient as independent predictors of MV growth (R2=0.39). Conclusion Annular growth of the MV was not observed in patients who underwent single-ventricle palliation. In contrast, among patients who achieved BVR, those with a small preoperative MV annulus and low ASD pressure gradient demonstrated subsequent catch-up MV growth, suggesting that adequate left-sided preload is essential for MV development.

Purpose: This study assessed the performance of the ultrasound-guided attenuation parameter (UGAP) in diagnosing and grading hepatic steatosis in patients with metabolic dysfunctionassociated steatotic liver disease (MASLD). Magnetic resonance imaging proton density fat fraction (MRI-PDFF) served as the reference standard. Methods: Patients with hepatic steatosis were enrolled in this prospective study and underwent UGAP measurements. MRI-PDFF values of ≥5%, ≥15%, and ≥25% were used as references for the diagnosis of steatosis grades ≥S1, ≥S2, and S3, respectively. Spearman correlation coefficients and area under the receiver operating characteristic curves (AUCs) were calculated. Results: Between July 2023 and June 2024, the study included 88 patients (median age, 40 years; interquartile range [IQR], 36 to 46 years), of whom 54.5% (48/88) were men and 45.5% (40/88) were women. Steatosis grades exhibited the following distribution: 22.7% (20/88) had S0, 50.0% (44/88) had S1, 21.6% (19/88) had S2, and 5.7% (5/88) had S3. The success rate for UGAP measurements was 100%. The median UGAP value was 0.74 dB/cm/MHz (IQR, 0.65 to 0.82 dB/ cm/MHz), and UGAP values were positively correlated with MRI-PDFF (r=0.77, P<0.001). The AUCs of UGAP for the diagnoses of ≥S1, ≥S2, and S3 steatosis were 0.91, 0.90, and 0.88, respectively. In the subgroup analysis, 98.4% (60/61) of patients had valid controlled attenuation parameter (CAP) values. UGAP measurements were positively correlated with CAP values (r=0.65, P<0.001). Conclusion Using MRI-PDFF as the reference standard, UGAP demonstrates good diagnostic performance in the detection and grading of hepatic steatosis in patients with MASLD.

Hepatolenticular degeneration is a rare disease,and the number of cases of primary liver cancer occurring on the basis of liver cirrhosis caused by hepatolenticular degeneration is very small.This paper reports a case of hepatolenticular degeneration with primary liver cancer,and then reviews and summarizes current cases of this disease both domestically and internationally.
Humans ; Hepatolenticular Degeneration/complications* ; Liver Neoplasms/complications*

Objective To investigate the value of ultrasonographic features combined with immunohistochemistry in predicting axillary lymph node metastasis in middle-aged women with breast cancer.Methods A retrospective analysis was conducted on 827 middle-aged female breast cancer patients who underwent surgical treatment at the Affiliated Hospital of Chengde Medical University from June 2017 to June 2023.Ultrasonographic and immunohistochemical information was collected,and the patients were randomly allocated into a training set(579 patients)and a validation set(248 patients).Univariate and multivariate Logistic regression analyses were performed to identify ultrasonographic and immunohistochemical risk factors associated with axillary lymph node metastasis in these patients,and a nomogram model was developed.Receiver operating characteristic curves and calibration curves were established to evaluate the performance of the nomogram model,and clinical decision curves were built to assess the clinical value of the model.Results The maximum diameter,morphology,boundary,calcification,and expression of human epidermal growth facor receptor 2 and Ki-67 in breast cancer lesions were identified as risk factors for predicting axillary lymph node metastasis in middle-aged women.The areas under the curve of the nomogram model on the training and validation sets were 0.747(0.707-0.787)and 0.714(0.647-0.780),respectively.Calibration curves and clinical decision curves indicated good consistency and performance of the model.Conclusion The nomogram model constructed based on ultrasonographic features and immunohistochemistry of the primary breast cancer lesion demonstrates high value in predicting axillary lymph node metastasis in middle-aged women with breast cancer.
Humans ; Female ; Breast Neoplasms/diagnostic imaging* ; Middle Aged ; Lymphatic Metastasis/diagnostic imaging* ; Axilla ; Retrospective Studies ; Nomograms ; Ultrasonography ; Immunohistochemistry ; Lymph Nodes/diagnostic imaging* ; Risk Factors ; Ki-67 Antigen

Objective To investigate the expression levels of class Ⅰ histone deacetylases(HDAC)in the serum of patients with newly diagnosed psoriatic arthritis(PsA)and screen out serological indicators that are of significance for early diagnosis and assessment of disease activity.Methods A total of 49 PsA patients newly diagnosed in Shanxi Provincial People's Hospital from August 2022 to February 2024 and 30 healthy individuals(control group)were enrolled in this study.Demographic data were collected,and disease severity was assessed.Serum samples were collected,and the expression levels of class Ⅰ HDAC(HDAC1,HDAC2,HDAC3,and HDAC8)in the serum of each group were determined by ELISA.The correlations between the expression levels of class Ⅰ HDAC and clinical assessment indicators in each group were evaluated.Multivariate Logistic regression was adopted to analyze the risk factors affecting the disease activity of PsA patients.The receiver operating characteristic curve was used to evaluate the diagnostic efficacy of the risk factors affecting the disease activity of PsA patients.Results Compared with the control group,PsA patients showed up-regulated expression levels of HDAC1(P=0.003),HDAC2(P=0.010),HDAC3(P=0.003),and HDAC8(P=0.018)in the serum.The serum HDAC1 level of PsA patients was positively correlated with erythrocyte sedimentation rate(r=0.344,P=0.028).The serum HDAC2 level was positively correlated with the overall assessment of disease activity(r=0.468,P=0.001),the disease activity index of arthritis(r=0.401,P=0.007),the number of swollen joints(r=0.308,P=0.042),hospital anxiety and depression scale(HADS)score of anxiety(r=0.360,P=0.018),and HADS score of depression(r=0.302,P=0.047).The serum HDAC3 level was correlated with erythrocyte sedimentation rate(r=0.542,P<0.001),C-reactive protein(CRP)level(r=0.440,P<0.001),HADS score of anxiety(r=0.420,P=0.005),interleukin-6 level(r=0.397,P=0.004),the overall assessment of disease activity(r=0.318,P=0.036),and the course of psoriatic arthritis(r=0.330,P=0.028).The serum HDAC8 level was positively correlated with HADS score of anxiety(r=0.477,P=0.008)and erythrocyte sedimentation rate(r=0.385,P=0.039).Compared with the patients with low disease activity,those with moderate to high disease activity presented up-regulated expression of HDAC3(P=0.041).HDAC2(P=0.028)and CRP(P=0.034)were risk factors for moderate to high disease activity in PsA patients.HDAC2(area under the curve=0.802,P=0.003)and CRP(area under the curve=0.718,P=0.033)had diagnostic value for the progression of PsA.Conclusions The expression levels of class Ⅰ HDAC in the serum of patients with newly diagnosed PsA were significantly different.The serum levels of HDAC2 and CRP are expected to become serological indicators for the early diagnosis and disease activity assessment of PsA.
Humans ; Histone Deacetylases/blood* ; Arthritis, Psoriatic/diagnosis* ; Male ; Female ; Histone Deacetylase 1/blood* ; Histone Deacetylase 2/blood* ; Adult ; Middle Aged ; Clinical Relevance ; Repressor Proteins

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.

The scientific research and innovation capabilities of medical students are intrinsically linked to the sustained and high-quality development of national healthcare initiatives.Cultivating outstanding medi-cal students with independent scientific capabilities and innovative consciousness is a critical component in the education and training of high-level medical professionals.Our investigation revealed that within the imperfections of the cultivating model,some faculty and students at medical schools have an insufficient understanding of scientific research and innovation and lack motivation for engaging in such activities,which hinder the progression of scientific research activities.Consequently,we initiated a teaching practice and exploratory study on the"tutorial system"aimed at fostering medical students'scientific research and innovation abilities.Based on the principle of"research informing teaching,teaching and research advan-cing together,"this study implements a"tutorial system"coordinated by tutors,supplemented by graduate and undergraduate student mentors,to cultivate innovative thinking,stimulate interest in scientific re-search,and enhance practical and research skills among medical students.Through collaborative efforts within"scientific research innovation teams,"various educational methods—including preliminary re-search,in-class and extracurricular activities,intra-group and inter-group interactions,and theoretical and practical applications—are employed to improve and strengthen the cultivation of medical students'scientif-ic research and innovation abilities.This study aims to provide valuable references for optimizing medical education management systems and enhancing the quality of medical student training.