Objective To investigate the sputum metabolic profiles of patients with occupational coal workers' pneumoconiosis (CWP) by an untargeted metabolomics method, and to identify relevant differential metabolic pathways and potential biomarkers. Methods A total of 12 male patients with stage Ⅰ CWP were selected as the CWP group, and 16 healthy male individuals were selected as the control group, using a judgmental sampling method. Sputum metabolites of individuals in both groups were detected to perform non-targeted metabolomic analysis using the ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry. Differential metabolites (DMs) and their pathways were screened using principal component analysis, partial least squares discriminant analysis, and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Potential biomarkers were analyzed and identified via the receiver operating characteristic curve (ROC). Results There were apparent metabolic alterations observed in sputum of CWP patients compared with healthy controls. In the positive ion mode, a total of 42 DMs were identified in sputum from CWP patients, including 19 downregulated and 23 upregulated metabolites. In the negative ion mode, a total of 25 DMs were identified in sputum from CWP patients, including 16 downregulated and 9 upregulated metabolites. KEGG enrichment analysis of sputum from CWP patients showed that seven DMs pathways were enriched in ABC transporters, histidine metabolism, phenylalanine metabolism, arachidonic acid metabolism, linoleic acid metabolism, purine metabolism, and oxidative phosphorylation, involving 26 DMs. ROC analysis indicated that 16(R)-hydroxyarachidonic acid, pyrophosphate, and 2-hydroxyphenylacetate of these 26 DMs may serve as potential biomarkers for CWP. Conclusion Sputum metabolomic profiles were altered in CWP patients compared with healthy controls. The potential biomarkers of CWP prevention and treatment are 16(R)-hydroxyarachidonic acid, pyrophosphate, and 2-hydroxyphenylacetate.

Objective To discuss the efficacy of transcatheter arterial chemoembolization(TACE)in combination with targeted therapy and immune checkpoint inhibitors for advanced hepatocellular carcinoma(HCC),and to identify the influencing factors.Methods A total of 60 patients with advanced HCC,who were admitted to the Air Force Medical Center of China from January 2016 to December 2022,were enrolled in this study.Thirty patients received TACE combined with targeted therapy and immune checkpoint inhibitors(TACE-L-P group),and the other 30 patients received TACE combined with targeted therapy(TACE-L group).The progression-free survival(PFS),overall survival(OS),disease control rate(DCR),and objective response rate(ORR)were compared between the two groups.Results In the TACE-L group and TACE-L-P group,the median PFS(mPFS)was 7 months and 10 months respectively(P=0.011),the median OS(mOS)was 15.5 months and 29 months respectively(P=0.014).Child-Pugh class B(HR=3.89,95％CI:1.27-11.94,P=0.018)and Barcelona Clinic Liver Cancer(BCLC)stage C(HR=2.83,95％CI:1.32-6.03,P=0.007)were the independent risk factors for OS,while micro wave ablation(HR=0.21,95％CI:0.07-0.63,P=0.005)and TACE-L-P(HR=0.09,95％CI:0.03-0.3,P=0.001)were the independent protection factors for OS.Besides,elevated bilirubin level(HR=1.03,95％CI:1-1.06,P=0.032)and elevated gamma-glutamyl transferase(GGT)level(HR=1.01,95％CI:1-1.01,P=0.002)were the independent risk factors for disease progression,and TACE-L-P(HR=0.27,95％CI:0.09-0.79,P=0.017)was the independent protection factor for disease progression.The ORR and DCR in TACE-L-P group were remarkably higher than those in TACE-L group,which were 43.4％vs 13.3％and 63.4％vs 23.3％respectively,the differences between the two groups were statistically significant(both P＜0.05).Conclusion In treating advanced HCC,TACE combined with targeted therapy and immune checkpoint inhibitors is superior to TACE combined with targeted therapy in therapeutic efficacy.

BACKGROUND: T-cell lymphoblastic lymphoma/acute lymphoblastic leukemia (T-LBL/ALL) is an aggressive form of hematological malignancy associated with poor prognosis in adult patients. Histone deacetylases (HDACs) are aberrantly expressed in T-LBL/ALL and are considered potential therapeutic targets. Here, we investigated the antitumor effect of a novel HDAC inhibitor, chidamide, on T-LBL/ALL. METHODS: HDAC1, HDAC2 and HDAC3 levels in T-LBL/ALL cell lines and patient samples were compared with those in normal controls. Flow cytometry, transmission electron microscopy, and lactate dehydrogenase release assays were conducted in Jurkat and MOLT-4 cells to assess apoptosis and pyroptosis. A specific forkhead box O1 (FOXO1) inhibitor was used to rescue pyroptosis and upregulated gasdermin E (GSDME) expression caused by chidamide treatment. The role of the FOXO1 transcription factor was evaluated by dual-luciferase reporter and chromatin immunoprecipitation assays. The efficacy of chidamide in vivo was evaluated in a xenograft mouse. RESULTS: The expression of HDAC1, HDAC2 and HDAC3 was significantly upregulated in T-LBL/ALL. Cell viability was obviously inhibited after chidamide treatment. Pyroptosis, characterized by cell swelling, pore formation on the plasma membrane and lactate dehydrogenase leakage, was identified as a new mechanism of chidamide treatment. Chidamide triggered pyroptosis through caspase 3 activation and GSDME transcriptional upregulation. Chromatin immunoprecipitation assays confirmed that chidamide led to the increased transcription of GSDME through a more relaxed chromatin structure at the promoter and the upregulation of FOXO1 expression. Moreover, we identified the therapeutic effect of chidamide in vivo . CONCLUSIONS This study suggested that chidamide exerts an antitumor effect on T-LBL/ALL and promotes a more inflammatory form of cell death via the FOXO1/GSDME axis, which provides a novel choice of targeted therapy for patients with T-LBL/ALL.
Humans ; Pyroptosis/drug effects* ; Forkhead Box Protein O1/genetics* ; Aminopyridines/pharmacology* ; Animals ; Mice ; Benzamides/pharmacology* ; Cell Line, Tumor ; Precursor T-Cell Lymphoblastic Leukemia-Lymphoma/drug therapy* ; Phosphate-Binding Proteins/metabolism* ; Histone Deacetylase Inhibitors/pharmacology* ; Jurkat Cells ; Histone Deacetylases/metabolism* ; Apoptosis/drug effects* ; Gasdermins

The identification and optimization of mutations in nanobodies are crucial for enhancing their therapeutic potential in disease prevention and control. However, this process is often complex and time-consuming, which limit its widespread application in practice. In this study, we developed a workflow, named Evolutionary-Nanobody (EvoNB), to predict key mutation sites of nanobodies by combining protein language models (PLMs) and molecular dynamic (MD) simulations. By fine-tuning the ESM2 model on a large-scale nanobody dataset, the ability of EvoNB to capture specific sequence features of nanobodies was significantly enhanced. The fine-tuned EvoNB model demonstrated higher predictive accuracy in the conserved framework and highly variable complementarity-determining regions of nanobodies. Additionally, we selected four widely representative nanobody-antigen complexes to verify the predicted effects of mutations. MD simulations analyzed the energy changes caused by these mutations to predict their impact on binding affinity to the targets. The results showed that multiple mutations screened by EvoNB significantly enhanced the binding affinity between nanobody and its target, further validating the potential of this workflow for designing and optimizing nanobody mutations. Additionally, sequence-based predictions are generally less dependent on structural absence, allowing them to be more easily integrated with tools for structural predictions, such as AlphaFold 3. Through mutation prediction and systematic analysis of key sites, we can quickly predict the most promising variants for experimental validation without relying on traditional evolutionary or selection processes. The EvoNB workflow provides an effective tool for the rapid optimization of nanobodies and facilitates the application of PLMs in the biomedical field.

Objective To explore the relationship of microRNA(miR)-155,miR-92a and miR-126 with in-stent restenosis(ISR)after percutaneous coronary intervention(PCI)in elderly patients with coronary heart disease(CHD).Methods A total of 118 elderly CHD patients receiving PCI in our hospital from January 2021 to June 2023 were enrolled,and according to whether ISR occurred by coronary angiography(CAG)at 1 year after surgery,they were divided into a stenosis group(45 cases)and a non-stenosis group(73 cases).Their baseline data,number of stent,stent diameter,medication,coronary artery lesion score,and serum expression levels of miR-155,miR-92a and miR-126 were compared between the two groups.The correlation of expression levels of the three miRNAs and clinical indicators was analyzed.Multivariate logistic regression analysis was performed to identify the risk factors of ISR in elderly CHD patients.ROC curve was adopted to analyze the diagnostic value of the three miRNAs for ISR in the elderly patients.Results Signifi-cantly higher BMI,SBP and DBP,and larger proportions of stent count ≥3 and stent diameter＜3 mm were observed in the stenosis group than the non-stenosis group(P＜0.05,P＜0.01).The expression levels of miR-155 and miR-126 were obviously lower,while that of miR-92a was nota-bly higher in the stenosis group than the non-stenosis group(P＜0.01).Pearson correlation analy-sis showed that miR-155 and miR-126 were negatively correlated with BMI,SBP,DBP,and stent count,and positively correlated with stent diameter(P＜0.01);miR-92a was positively correlated with BMI,SBP,DBP,and stent count,and negatively with stent diameter(P＜0.01).Multivariate logistic regression analysis suggested that stent count,stent diameter and miR-92a were risk fac-tors for ISR in elderly CHD patients after PCI,and miR-155 and miR-126 were protective factors(P＜0.05,P＜0.01).ROC curve analysis revealed that the AUC value of miR-155,miR-92a,and miR-126 alone and combined together was 0.742,0.778,0.751 and 0.853,respectively,with a sen-sitivity of 86.67％,71.11％,73.33％and 93.33％respectively,and the combined detection showed better diagnostic value for ISR than the single detection(P＜0.01).Conclusion Down-regulation of miR-155 and miR-126 and up-regulation of miR-92a may be involved in the occurrence of ISR in elderly CHD patients after PCI.Monitoring the three miRNAs is beneficial to auxiliary clinical prediction for ISR after PCI.

Plant-derived bioactive peptides have become a research hotspot in the fields of food and medicine due to their high source safety,easy absorption and utilization by the human body,and potential edible and medicinal value.Bioactive peptides can be classified into antihypertensive,hypoglycemic,hypolipidemic,anticancer,antioxidant,antimicrobial,and anti-inflammatory peptides according to their functions.Among these,antihypertensive,hypoglycemic,and hypolipidemic peptides are collectively referred to as cardiovascular active peptides,which can be used for the treatment and prevention of cardiovascular diseases and have an important role in the development of modem biomedicine.This review focused on the preparation methods,separation,purification,and identification techniques of bioactive peptides,as well as their mechanisms of action and applications in regulating cardiovascular diseases,aiming to provide a reference for further development and application of plant-derived cardiovascular peptides.

The identification and optimization of mutations in nanobodies are crucial for enhancing their thera-peutic potential in disease prevention and control.However,this process is often complex and time-consuming,which limit its widespread application in practice.In this study,we developed a work-flow,named Evolutionary-Nanobody(EvoNB),to predict key mutation sites of nanobodies by combining protein language models(PLMs)and molecular dynamic(MD)simulations.By fine-tuning the ESM2 model on a large-scale nanobody dataset,the ability of EvoNB to capture specific sequence features of nanobodies was significantly enhanced.The fine-tuned EvoNB model demonstrated higher predictive accuracy in the conserved framework and highly variable complementarity-determining regions of nanobodies.Additionally,we selected four widely representative nanobody-antigen complexes to verify the predicted effects of mutations.MD simulations analyzed the energy changes caused by these mu-tations to predict their impact on binding affinity to the targets.The results showed that multiple mu-tations screened by EvoNB significantly enhanced the binding affinity between nanobody and its target,further validating the potential of this workflow for designing and optimizing nanobody mutations.Additionally,sequence-based predictions are generally less dependent on structural absence,allowing them to be more easily integrated with tools for structural predictions,such as AlphaFold 3.Through mutation prediction and systematic analysis of key sites,we can quickly predict the most promising variants for experimental validation without relying on traditional evolutionary or selection processes.The EvoNB workflow provides an effective tool for the rapid optimization of nanobodies and facilitates the application of PLMs in the biomedical field.

Objective:To investigate the role of calcium-binding protein S100A9 in acute lung injury induced by hepatic ischemia-reperfusion (HIR) in mice, and to explore its relationship with nuclear factor erythroid 2-related factor 2 (Nrf2).Methods:A total of 12 specific pathogen-free (SPF) male wild-type (WT) and 12 S100A9 knockout (S100A9 KO) C57BL/6J mice aged 6~8 weeks and weighing 20-25 g were randomly divided into four groups using a random number table: WT+Sham group, S100A9 KO+Sham group, WT+HIR group, and S100A9 KO+HIR group ( n=6 per group). The HIR model was established by clamping the portal vein and hepatic artery of the left and median liver lobes for 60 minutes followed by reperfusion. At 6 hours post-reperfusion, mice were anesthetized again, and blood samples were collected from the inferior vena cava. Both lungs were harvested. The lung wet-to-dry (W/D) weight ratio was measured. Hematoxylin and eosin (HE) staining was used to assess histopathological changes and calculate lung injury scores. The levels of inflammatory markers—S100A9, tumor necrosis factor-α (TNF-α), and interleukin-6 (IL-6) —as well as oxidative stress indicators including myeloperoxidase (MPO), reactive oxygen species (ROS), malondialdehyde (MDA), and superoxide dismutase (SOD) in serum and lung tissue were measured. Western blotting was used to assess the expression levels of nuclear and cytoplasmic Nrf2, and cytoplasmic HO-1. Results:Compared with the WT+Sham group, both the WT+HIR and S100A9 KO+HIR groups showed significantly increased lung injury scores, W/D ratio, TNF-α, IL-6, ROS, MPO, and MDA levels (all P<0.05). Compared with the WT+HIR group, the S100A9 KO+HIR group exhibited significantly reduced levels of these indicators (all P<0.05). Moreover, the S100A9 KO+HIR group showed elevated nuclear Nrf2 expression and decreased cytoplasmic Nrf2 expression, accompanied by increased expression of HO-1, Gclm, Gclc, and Nqo1 (all P<0.05). Conclusion:Upregulation of S100A9 is involved in the development of HIR-induced acute lung injury, possibly through inhibition of Nrf2 nuclear translocation.

Objective:To evaluate the mid-term efficacy of sleeve gastrectomy combined with single anastomosis gastric-ileal bypass (SASI) for treating gastroesophageal reflux disease (GERD) after laparoscopic sleeve gastrectomy (LSG).Methods:Clinical data of 10 patients with post-LSG GERD undergoing SASI at the Department of Hernia and Bariatric Surgery, the First Affiliated Hospital of University of Science and Technology of China between Jan 2022 and Oct 2024 was retrospectively analyzed. Surgical safety and mid-term outcomes were evaluated.Results:The mean follow-up period was (25.40±17.33) months. The GerdQ score significantly decreased from (14.00±2.05) preoperatively to (5.70±1.49) postoperatively ( t=10.330, P<0.001), with a GERD remission rate of 90 % (9/10). Postoperative body weight and body mass index (BMI) both showed statistically significant reductions compared to preoperative values. Weight dropped from (110.29±22.92) kg to (84.95±15.89) kg ( t=5.889, P<0.001), and BMI decreased from (38.98±7.16) kg/m2 to (30.02±4.88) kg/m2 ( t=6.086, P<0.001). The percentage of excess weight loss was 65.88%±32.85%, and the percentage of total weight loss was 22.43%±9.65%. Only one patient experienced transient postoperative diarrhea, which resolved spontaneously, and no severe malnutrition cases were observed. Conclusion:SASI effectively improves GERD symptoms after LSG with favorable safety, serving as a suitable revisional surgical option for those patients.

[Objective] To validate and optimize the platelet transfusion refractoriness (PTR) prediction model for patients with hematological disorders established by our center. [Methods] The data of patients with hematological diseases who received platelet transfusions from December 2021 to December 2022 were used as the training set, and data from January 2023 to December 2023 as the validation set. The validation set data was used to validate the predictive model constructed on the training set. Relevant risk factors for PTR were collected through literature review and preliminary studies。 The patients were divided into effective and ineffective groups according to the corrected count increment (CCI) of platelet counts. Predictive factors were screened using univariate and multivariate logistic regression. The calibration of the model were assessed via calibration curves, while discrimination, accuracy, sensitivity, and specificity were evaluated using receiver operating characteristic (ROC) curves Clinical utility was further analyzed with decision curve analysis (DCA). [Results] The Hosmer-Lemeshow (H-L) goodness-of-fit test for the validation set yielded S: P=0.000, indicating that the original model needs optimization. Baseline comparisons and logistic regression identified the number of red blood cell units (RBCU) and platelet units (PLT-U) transfused as key predictors for the optimized model. The H-L goodness-of-fit test S: P values for the training and validation sets were 0.930 and 0.056, respectively; the ROC areas were 0.793 5 and 0.809 4, specificities 90.95% and 84.21%, sensitivities 59.26% and 70.04%, and accuracies 78.14% and 74.10%, respectively. DCA demonstrated clinical net benefit within a prediction probability threshold range of 0.2-0.8. [Conclusion] Transfusion volumes of RBC-U and PLT-U were inversely associated with PTR in hematological patients. The resulting PTR prediction model exhibits moderate predictive efficacy and clinical benefit.