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 effects of histone deacetylase (HDAC) levels on the proliferation and apoptosis of Burkitt lymphoma cells, and the changes in related signaling molecules in the PI3K/AKT/mTOR signaling pathway, so as to explore the pathogenesis of Burkitt lymphoma. METHODS: HDAC levels in Burkitt lymphoma were detected by RT-PCR and Western blot. CA46 and RAJI cells were treated with the HDAC selective inhibitor VPA. CCK8 assay was used to detect the proliferation ability of cells. Western Blot was used to measure the expression of apoptosis-related proteins, PI3K/AKT/mTOR signaling pathway proteins and their phosphorylation levels. RESULTS: The expression levels of classⅠ HDAC in Burkitt lymphoma were higher than those in normal cells, and the HDAC1 inhibitor VPA could inhibit the proliferation of CA46 and RAJI cells. VPA decreased HDAC expression in CA46 and RAJI cells, inhibited the phosphorylation of PI3K/AKT/mTOR pathway molecules AKT and p70S6K, increased the expression of apoptotic proteins Cleaved Caspase-3, Cleaved Caspase-8, Cleaved Caspase-9 and Bax, and decreased the expression of anti-apoptotic proteins Bcl-2 and PARP. CONCLUSION Inhibition of HDAC activity can Attenuate the proliferation of Burkitt lymphoma cells and induce apoptosis by inhibiting the PI3K/AKT/mTOR signaling pathway activity.
Humans ; Burkitt Lymphoma/pathology* ; Apoptosis ; Cell Proliferation ; Signal Transduction ; Proto-Oncogene Proteins c-akt/metabolism* ; Phosphatidylinositol 3-Kinases/metabolism* ; Cell Line, Tumor ; Histone Deacetylases/metabolism* ; TOR Serine-Threonine Kinases/metabolism* ; Histone Deacetylase Inhibitors/pharmacology* ; Phosphorylation

Although enteric glial cell (EGC) abnormal activation is reported to be involved in the pathogenesis of Parkinson's disease (PD), and inhibition of EGC gliosis alleviated gut and dopaminergic neuronal dysfunction was verified in our previous study, the potential role of gut microbiota on EGC function in PD still need to be addressed. In the present study, fecal microbiota transplantation revealed that EGC function was regulated by gut microbiota. By employing 16S rRNA and metabolomic analysis, we identified that 3-indolepropionic acid (IPA) was the most affected differential microbial metabolite that regulated EGC gliosis. The protective effects of IPA on PD were validated in rotenone-stimulated EGCs and rotenone (30 mg/kg i.g. for 4 weeks)-induced PD mice, as indicated by decreased inflammation, improved intestinal and brain barrier as well as dopaminergic neuronal function. Mechanistic study showed that IPA targeted pregnane X receptor (PXR) in EGCs, and inhibition of IL-13Rα1 involved cytokine-cytokine receptor interaction pathway, leading to inactivation of downstream JAK1-STAT6 pathway. Our data not only provided evidence that EGC gliosis was critical in spreading intestinal damage to brain, but also highlighted the potential role of microbial metabolite IPA in alleviating PD pathological damages through gut-brain axis.

Tailored lipid nanoparticles (LNPs)-mediated small interfering RNA (siRNA) nanomedicines show promise in treating liver disease, such as acute liver injury (ALI) and non-alcoholic steatohepatitis (NASH). However, constructing LNPs that address biosafety concerns, ensure efficient delivery, and target specific hepatic subcellular fractions has been challenging. To evade above obstacles, we develop three novel self-degradable "gemini-like" ionizable lipids (SS-MA, SS-DC, SS-MH) by incorporating disulfide bonds and modifying the length of ester bond and tertiary amino head. Our findings reveal that the disulfide-bond-bridged LNPs exhibit reduction-responsive drug release, improving both biosafety and siRNA delivery efficiency. Furthermore, the distance of ester bond and tertiary amino head significantly influences the LNPs' pK _a, thereby affecting endosomal escape, hemolytic efficiency, absorption capacity of ApoE, uptake efficiency of hepatocytes and liver accumulation. We also develop the modified-mannose LNPs (M-LNP) to target liver macrophages specifically. The optimized M-MH_LNP@TNFα exhibits potential in preventing ALI by decreasing tumor necrosis factor α (TNFα) levels in the macrophages, while MH_LNP@DGAT2 could treat NASH by selectively degrading diacylglycerol O-acyltransferase 2 (DGAT2) in the hepatocytes. Our findings provide new insights into developing novel highly effective and low-toxic "gemini-like" ionizable lipids for constructing LNPs, potentially achieving more effective treatment for hepatic diseases.

[This corrects the article DOI: 10.1016/j.apsb.2025.02.029.].

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.

Objective To investigate the association of spleen volume with the risk of non-alcoholic fatty liver disease(NAFLD)as well as their causal relationship.Methods We included 90 NAFLD cases and 47 healthy controls who had received contrast-enhanced computed tomography(CT)scan of the abdomen at the Second Affiliated Hospital of Xi'an Jiaotong University from November 2022 to November 2023.We conducted three-dimensional reconstruction of the spleen through a deep learning network model using a two-stage coarse-to-fine segmentation approach.We compared the two groups using the two-sample t test or Mann-Whitney U test for continuous data and using the chi-square test for categorical data;evaluated the correlation between spleen volume and liver function indicators through Pearson correlation or Spearman rank correlation analyses;determined the factors influencing the development of NAFLD through multivariable Logistic regression analysis;and further assessed the casual relationship between spleen volume and NAFLD using the inverse variance-weighted two-sample Mendelian randomization(IVW-MR)method.Results Spleen volume was significantly larger in NAFLD cases than in controls(272.93±104.16 vs 204.37±81.20 cm3,P<0.001).The Spearman rank correlation analysis showed that spleen volume was positively correlated with the hepatic steatosis index(rs=0.422,P<0.001)and gamma-glutamyl transferase levels(rs=0.211,P=0.047)in patients with NAFLD.The multivariable Logistic regression analysis indicated that spleen volume was an independent risk factor for the development of NAFLD(odds ratio[OR]=1.01,95%confidence interval[CI]:1.00-1.02,P=0.049).The IVW-MR analysis detected a causal relationship between spleen volume and NAFLD(OR=1.16,95%CI:1.05-1.28,P=0.005).Conclusion Increased spleen volume may be a risk factor for the development and progression of NAFLD.Further studies are still needed to investigate the specific mechanism.

Objective:To analyze the effect of high serum ferritin(SF)before transplantation on erythrocyte,granulocyte and platelet implantation in unrelated cord blood transplantation(UCBT)patients with myelodysplastic syndrome(MDS)and acute myeloid leukemia(AML).Methods:The medical records of 60 patients with MDS and AML who underwent UCBT in the First Affiliated Hospital of University of Science and Technology of China from January 2020 to December 2022 were retrospectively collected.According to the SF level before transplantation,they were divided into high SF group(SF ≥ 1 000 μg/L,n=20)and non-high SF group(SF＜1 000 μg/L,n=40).The red blood cell(RBC)infusion volume before transplantation,implantation time of RBC,granulocyte and platelet,implantation risk and prognosis were analyzed and compared between the two groups.Results:There was no correlation between the level of SF before transplantation and RBC infusion.After transplantation,the median implantation time of RBC in the high SF group was 28.5(14-149)d,which was longer than 21(10-83)d in the non-high SF group(P＜0.05).The median time of granulocyte engraftment in the high SF group was 16.5(12-63)d,while that in the non-high SF group was 16(12-49)d,with no statistical difference between the two groups(P＞0.05).The median platelet engraftment time in the high SF group was 45(12-206)d,while that in the non-high SF group was 35.5(14-149)d,with no statistical difference between the two groups(P＞0.05).Kaplan-Meier cumulative implantation probability analysis showed that the rate of erythroid implantation in the non-high SF group was higher than that in the high SF group(P＜0.05),while there was no significant difference in the rates of granulocyte and platelet implantation between the two groups(P＞0.05).The 1-year overall survival rates of the non-high SF group and high SF group were 95％and 90％,respectively,with no statistical difference between the two groups(P＞0.05).Conclusion:SF levels before cord blood transplantation in MDS and AML patients have an impact on post transplant erythroid implantation.Detecting and intervening of iron load in patients before transplant may be beneficial for improving implantation and prognosis.

Inflammatory bowel disease (IBD), including ulcerative colitis and Crohn's disease, is a chronic inflammation of the gastrointestinal tract with unknown etiology. The cause of IBD is widely considered multifactorial, with prevailing hypotheses suggesting that the microbiome and various environmental factors contribute to inappropriate activation of the mucosal immune system in genetically susceptible individuals. Although the incidence of IBD has stabilized in Western countries, it is rapidly increasing in newly industrialized countries, particularly China, making IBD a global disease. Significant changes in multiple biomarkers before IBD diagnosis during the preclinical phase provide opportunities for earlier diagnosis and intervention. Advances in technology have driven the development of telemonitoring tools, such as home-testing kits for fecal calprotectin, serum cytokines, and therapeutic drug concentrations, as well as wearable devices for testing sweat cytokines and heart rate variability. These tools enable real-time disease activity assessment and timely treatment strategy adjustments. A wide range of novel drugs for IBD, including interleukin-23 inhibitors (mirikizumab, risankizumab, and guselkumab) and small-molecule drugs (etrasimod and upadacitinib), have been introduced in the past few years. Despite these advancements, approximately one-third of patients remain primary non-responders to the initial treatment, and half eventually lose response over time. Precision medicine integrating multi-omics data, advanced combination therapy, and complementary approaches, including stem cell transplantation, psychological therapies, neuromodulation, and gut microbiome modulation therapy, may offer solutions to break through the therapeutic ceiling.
Humans ; Inflammatory Bowel Diseases/therapy*