ObjectiveHepatocellular carcinoma (HCC) represents 90% of all primary liver cancers. The main risk factors associated with HCC include viral hepatitis (B and/or C), alcohol abuse, and metabolic dysfunction-associated steatotic liver disease (MASLD), which progressively advance to liver fibrosis, cirrhosis, and ultimately evolve into HCC. Surgical resection represents the most effective treatment for HCC, while recent advances in immunotherapy, including immune checkpoint inhibitors and adoptive cell therapies, have provided improved treatment prospects for patients with unresectable HCC. However, the complex metabolic heterogeneity of HCC limits the therapeutic efficacy. Metabolic intermediates acyl-CoA not only provide energy and substrates for numerous biochemical reactions but also serve as donors for protein lysine acylation, a major class of post-translational modification (PTM). Therefore, a deeper understanding of the molecular mechanisms underlying protein lysine acylation and hepatocarcinogenesis is urgently needed. MethodsThe levels of protein lysine acylation and silence information regulator 5 (SIRT5) expression levels in clinical HCC samples were analyzed by Western blot. Quantitative malonylome and succinylome of HCC samples were analyzed by antibody-based affinity enrichment coupled with tandem mass spectrometry. The proliferation of HCC cells was analyzed with Cell Counting Kit-8 (CCK-8) assays, the apoptosis was quantified by Annexin V-FITC/propidium iodide (PI) staining coupled with flow cytometry, and the ability of cells to migrate was assayed by Transwell assays. The enzymatic activity of glutathione S-transferase Mu 1 (GSTM1) was quantified. Transgenic mice with hepatic overexpression of SIRT5 were constructed using CRISPR-Cas9, and primary hepatocarcinogenesis was induced by administration of diethylnitrosamine. ResultsWestern blot analysis indicated that the expression level of SIRT5 was elevated in clinical samples from HCC patients, and the levels of lysine malonylation, glutarylation, and succinylation were significantly reduced in HCC tissues. Knockout of SIRT5 in MHCC-97H and MHCC-97L hepatoma cells suppressed cell proliferation, and increased the percentage of apoptotic cells significantly. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the differentially malonylome and succinylome of HCC samples revealed significant enrichment in two major classes of biological processes: core energy metabolism (e.g., glycolysis/gluconeogenesis, tricarboxylic acid metabolic process, fatty acid beta oxidation) and detoxification and oxidative stress response (e.g., response to toxic substance, chemical carcinogenesis, reactive oxygen species (ROS)). SIRT5 removes malonylation from lysine residues in GSTM1 and restores its detoxification activity, which is crucial for the survival of hepatocytes under stressed conditions. More importantly, in vivo experiment indicated that hepatic-specific overexpression of SIRT5 in mice accelerated diethylnitrosamine-induced liver fibrosis and hepatocarcinogenesis, indicating the critical role of SIRT5 in HCC progression. ConclusionThis study highlights the previously unrecognized SIRT5-GSTM1 axis as a key regulator in hepatocarcinogenesis, and suggests a potential target for the treatment of patients with HCC.

Objective:To investigate the molecular characteristics of low-risk acute myeloid leukemia(AML)at recurrence,and analyze the factors affecting retreatment efficacy and prognosis.Methods:A retrospective analysis was conducted on the clinical and laboratory data of 31 patients with newly diagnosed low-risk AML who relapsed during consolidation treatment or follow-up after treatment in our hospital from April 2017 to January 2023.Gene mutations before and after relapse were compared,retreatment efficacy following relapse was evaluated,and univariate and multivariate analyses were performed to identify factors influencing treatment efficacy and prognosis.Results:Gene sequencing results after relapse showed that the most common newly acquired mutation was FLT3-ITD,while RAS mutation detected at initial diagnosis were predisposed to loss of expression during relapse.The median overall survival(OS)after relapse for the entire cohort was 349(170-528)days,with non-hematopoietic stem cell transplantation(HSCT)group and HSCT group demonstrating median survival times of 210(106-314)days and not reached,respectively(P=0.001).Multivariate analysis revealed that age ≥60 years was a significant risk factor for achieving remission after retreatment in initially diagnosed low-risk AML patients who experienced relapse(OR=18.222,95％CI:1.188-279.597,P=0.037).Additionally,DNMT3A mutation was identified as an independent risk factor for OS(HR=13.165,95％CI:2.018-85.877,P=0.007),while HSCT post-relapse demonstrated significant survival benefits(HR=0.133,95％CI:0.025-0.698,P=0.017)and served as an independent protective factor for OS.Conclusion:Relapsed low-risk AML is often associated with loss of RAS and novel mutations in FLT3-ITD.Age ≥ 60 years and DNMT3A mutations were identified as independent adverse factors for achieving subsequent remission and post-relapse survival,respectively,while HSCT significantly improved patient outcomes.

Objective:To observe the clinical efficacy of repetitive transcranial magnetic stimulation(rTMS)combined with mindfulness-based cognitive therapy(MBCT)in patients with alcohol withdrawal syndrome(AWS).Methods:The 120 patients with AWS who were observed in this study were all male patients admitted to our hospital from June 2021 to June 2024,the patients were divided into group A(conventional treatment,40 cases),group B(group A combined with rTMS,40 cases),and group C(group B combined with MBCT,40 cases)according to random number table method.The clinical efficacy,self-control ability[Modified Clinical Institution Alcohol Dependence Withdrawal Assessment Scale(CIWA-Ar)score,Visual Analog Scale of Psychological Craving for Alcohol(VAS)score and Pennsylvania Alcohol Craving Scale(PACS)score],anxiety and depression degree assessment[Hamilton Depression Scale(HAMD)score,Hamilton Anxiety Scale(HAMA)score]and quality of life[36 Short Form Health Survey(SF-36)Score],relapse rate and readmission rate were compared among the three groups.Results:The total effective rate of group A,group B and group C increased successively(P＜0.05).The CIWA-Ar,PACS and VAS scores in group B and group C after treatment were lower than those in group A,and group C was lower than that in group B(P＜0.05).The HAMD and HAMA scores of group B and group C after treatment were lower than those in group A,and group C was lower than that in group B(P＜0.05).The SF-36 score of group B and group C after treatment was higher than those in group A,and group C was higher than that in group B(P＜0.05).Relapse rate and readmission rate in groups B and C were lower than those in group A,and group C was lower than that in group B(P＜0.05).Conclusion:The application of rTMS combined with MBCT in patients with AWS can improve clinical efficacy and quality of life,alleviate anxiety and depression,improve patients' self-control ability,reduce relapse rate and readmission rate,with definite effects.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Aim To explore the mechanism of hispidu-lin in the treatment of cervical cancer by using network pharmacology and molecular docking methods and veri-fy it by in vitro experiments.Methods Cervical canc-er HeLa and SiHa cells were cultivated in vitro,and CCK-8 assay,cloning assay,scratch assay,transwell as-say,and flow cytometry were used to detect the effects of hispidulin on cell proliferation,migration,invasion,and apoptosis.SwissTarget Prediction was used to ob-tain predicted targets for hispidulin.Potential targets for cervical cancer were screened in GeneCards disease database.R software Venn package was used to obtain the intersection target genes of hispidulin and cervical cancer,STRING website and Cytoscape software were used to obtain protein-protein interaction(PPI)net-work,and the core targets were screened.The GEIPA data analysis platform was employed to analyze the dif-ferential gene expression levels of core targets in cervi-cal cancer.Gene Ontology(GO)and Kyoto Encyclo-pedia of Genes and Genomes(KEGG)enrichment a-nalysis were performed,and molecular docking was car-ried out on key targets.Western blot was used to detect the regulatory effects of hispidulin on the expression of key proteins PI3K,p-Akt,as well as core target pro-teins MMP9 and RARP1 in the PI3K/Akt signaling pathway.Results Cell experiments showed that after treatment with hispidulin,the proliferation and colony formation abilities of HeLa and SiHa cells significantly decreased in a concentration-and time-dependent man-ner.At the same time,the lateral and longitudinal mi-gration and invasion abilities of HeLa cells decreased,and the level of apoptosis significantly increased.A to-tal of 87 intersection targets between hispidulin and cervical cancer were obtained,and eight core targets,namely,Akt1,EGFR,SRC,ESR1,PTGS2,GSK3β,MMP9,and PARP1,were selected based on the degree values in network topology analysis.KEGG enrichment screening identified PI3K/Akt signaling pathway,canc-er pathway,and other signaling pathways.The molecu-lar docking results showed that hispidulin had strong affinity activity with AktⅠ,P13K,MMP9,and RARP1.Western blot results showed downregulation of PI3K,p-Akt expression,as well as MMP9 and RARP1 expres-sion.Conclusions Hispidulin can inhibit the prolif-eration,migration,invasion,and promote apoptosis of cervical cancer cells by downregulating the PI3K/Akt signaling pathway and the expression of MMP9 and RARP1.

Objective:To observe the clinical efficacy of repetitive transcranial magnetic stimulation(rTMS)combined with mindfulness-based cognitive therapy(MBCT)in patients with alcohol withdrawal syndrome(AWS).Methods:The 120 patients with AWS who were observed in this study were all male patients admitted to our hospital from June 2021 to June 2024,the patients were divided into group A(conventional treatment,40 cases),group B(group A combined with rTMS,40 cases),and group C(group B combined with MBCT,40 cases)according to random number table method.The clinical efficacy,self-control ability[Modified Clinical Institution Alcohol Dependence Withdrawal Assessment Scale(CIWA-Ar)score,Visual Analog Scale of Psychological Craving for Alcohol(VAS)score and Pennsylvania Alcohol Craving Scale(PACS)score],anxiety and depression degree assessment[Hamilton Depression Scale(HAMD)score,Hamilton Anxiety Scale(HAMA)score]and quality of life[36 Short Form Health Survey(SF-36)Score],relapse rate and readmission rate were compared among the three groups.Results:The total effective rate of group A,group B and group C increased successively(P＜0.05).The CIWA-Ar,PACS and VAS scores in group B and group C after treatment were lower than those in group A,and group C was lower than that in group B(P＜0.05).The HAMD and HAMA scores of group B and group C after treatment were lower than those in group A,and group C was lower than that in group B(P＜0.05).The SF-36 score of group B and group C after treatment was higher than those in group A,and group C was higher than that in group B(P＜0.05).Relapse rate and readmission rate in groups B and C were lower than those in group A,and group C was lower than that in group B(P＜0.05).Conclusion:The application of rTMS combined with MBCT in patients with AWS can improve clinical efficacy and quality of life,alleviate anxiety and depression,improve patients' self-control ability,reduce relapse rate and readmission rate,with definite effects.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Aim To explore the mechanism of hispidu-lin in the treatment of cervical cancer by using network pharmacology and molecular docking methods and veri-fy it by in vitro experiments.Methods Cervical canc-er HeLa and SiHa cells were cultivated in vitro,and CCK-8 assay,cloning assay,scratch assay,transwell as-say,and flow cytometry were used to detect the effects of hispidulin on cell proliferation,migration,invasion,and apoptosis.SwissTarget Prediction was used to ob-tain predicted targets for hispidulin.Potential targets for cervical cancer were screened in GeneCards disease database.R software Venn package was used to obtain the intersection target genes of hispidulin and cervical cancer,STRING website and Cytoscape software were used to obtain protein-protein interaction(PPI)net-work,and the core targets were screened.The GEIPA data analysis platform was employed to analyze the dif-ferential gene expression levels of core targets in cervi-cal cancer.Gene Ontology(GO)and Kyoto Encyclo-pedia of Genes and Genomes(KEGG)enrichment a-nalysis were performed,and molecular docking was car-ried out on key targets.Western blot was used to detect the regulatory effects of hispidulin on the expression of key proteins PI3K,p-Akt,as well as core target pro-teins MMP9 and RARP1 in the PI3K/Akt signaling pathway.Results Cell experiments showed that after treatment with hispidulin,the proliferation and colony formation abilities of HeLa and SiHa cells significantly decreased in a concentration-and time-dependent man-ner.At the same time,the lateral and longitudinal mi-gration and invasion abilities of HeLa cells decreased,and the level of apoptosis significantly increased.A to-tal of 87 intersection targets between hispidulin and cervical cancer were obtained,and eight core targets,namely,Akt1,EGFR,SRC,ESR1,PTGS2,GSK3β,MMP9,and PARP1,were selected based on the degree values in network topology analysis.KEGG enrichment screening identified PI3K/Akt signaling pathway,canc-er pathway,and other signaling pathways.The molecu-lar docking results showed that hispidulin had strong affinity activity with AktⅠ,P13K,MMP9,and RARP1.Western blot results showed downregulation of PI3K,p-Akt expression,as well as MMP9 and RARP1 expres-sion.Conclusions Hispidulin can inhibit the prolif-eration,migration,invasion,and promote apoptosis of cervical cancer cells by downregulating the PI3K/Akt signaling pathway and the expression of MMP9 and RARP1.

This study was aimed at establishing a method of ultra-fast quantitative PCR for Brucella detection.We used an exogenous recombinant plasmid as the internal reference and targeted the T4SS secretion system,an important Brucella viru-lence factor,to design specific primers and probes.The sensitivity,specificity,and repeatability of this method were evaluated,and a standard curve was constructed.The coincidence rate of detection findings with this method versus quantitative PCR was determined.This method markedly decreased the detection time to only 10 minutes.The standard curve demonstrated a good linear relationship(Y=-3.410 7x+38.357,R2=0.998 5)with a low minimum detection limit of 10 copies/μL.The method exhibited good specificity and did not specifically amplify several common clinical bacteria other than Brucella.The de-tection of three concentrations of positive plasmids yielded coefficients of variation(CVs)of 0.20％to 0.91％,thus demonstra-ting the method's excellent repeatability.Furthermore,140 clinical samples were analyzed concurrently with the fluorescence PCR method,which yielded a 100％compliance rate and consistent results.Our findings indicated that the Brucella ultra-fast quantitative PCR was ultrafast;had high sensitivity,high specificity,and good specificity;and can be used for the clinical de-tection of Brucella and emergency investigation of epidemics.Therefore,this method is valuable for the early diagnosis of Bru-cella.

Objective:To investigate the molecular characteristics of low-risk acute myeloid leukemia(AML)at recurrence,and analyze the factors affecting retreatment efficacy and prognosis.Methods:A retrospective analysis was conducted on the clinical and laboratory data of 31 patients with newly diagnosed low-risk AML who relapsed during consolidation treatment or follow-up after treatment in our hospital from April 2017 to January 2023.Gene mutations before and after relapse were compared,retreatment efficacy following relapse was evaluated,and univariate and multivariate analyses were performed to identify factors influencing treatment efficacy and prognosis.Results:Gene sequencing results after relapse showed that the most common newly acquired mutation was FLT3-ITD,while RAS mutation detected at initial diagnosis were predisposed to loss of expression during relapse.The median overall survival(OS)after relapse for the entire cohort was 349(170-528)days,with non-hematopoietic stem cell transplantation(HSCT)group and HSCT group demonstrating median survival times of 210(106-314)days and not reached,respectively(P=0.001).Multivariate analysis revealed that age ≥60 years was a significant risk factor for achieving remission after retreatment in initially diagnosed low-risk AML patients who experienced relapse(OR=18.222,95％CI:1.188-279.597,P=0.037).Additionally,DNMT3A mutation was identified as an independent risk factor for OS(HR=13.165,95％CI:2.018-85.877,P=0.007),while HSCT post-relapse demonstrated significant survival benefits(HR=0.133,95％CI:0.025-0.698,P=0.017)and served as an independent protective factor for OS.Conclusion:Relapsed low-risk AML is often associated with loss of RAS and novel mutations in FLT3-ITD.Age ≥ 60 years and DNMT3A mutations were identified as independent adverse factors for achieving subsequent remission and post-relapse survival,respectively,while HSCT significantly improved patient outcomes.