Objective To investigate the causal relationship between metabolic syndrome and breast cancer by using a bidirectional two-sample Mendelian randomization (MR) approach. Methods Genome-wide association study (GWAS) summary statistics for metabolic syndrome and breast cancer were acquired from the Integrative Epidemiology Unit GWAS database and the GWAS Catalog, with populations encompassing the United States and East Asia. A bidirectional causal design was employed: a forward analysis with metabolic syndrome as the exposure and breast cancer as the outcome, followed by a reverse analysis wherein their roles were interchanged. The inverse-variance weighting (IVW) method was primarily used for effect estimation, supplemented by MR-Egger regression, the weighted median method, the simple mode method, and the weighted mode method. Instrument variable strength was screened using the F-statistic (F>10). Robustness of the results was assessed through heterogeneity tests, horizontal pleiotropy tests, forest plots, and leave-one-out sensitivity analyses. Results The IVW analysis indicated no significant causal relationship between metabolic syndrome and breast cancer (OR=1.00, 95%CI: 0.97-1.03), P>0.05). Sensitivity analyses yielded consistent results, suggesting the good robustness of the study findings. Conclusion This study found no evidence to support a causal relationship, either positive or negative, between metabolic syndrome and breast cancer.

Objective:To investigates the efficacy and safety of allogeneic hematopoietic stem cell transplantation(allo-HSCT)in treating older patients(≥60 years old)with hematologic malignancies.Methods:We conducted a retrospective study involving 67 patients aged 60 years and above, diagnosed with malignant hematological diseases, who received allo-HSCT at the Clinical Research Centrer for Haematologic Diseases of the First Affiliated Hospital of Soochow University between June 2015 and March 2023.We collected pre-transplant data, including the patients' age, gender, pre-transplantation disease risk stratification, disease status, and the haematopoietic cell transplantation comorbidity index(HCT-CI). We retrospectively analyzed clinical data regarding treatment-related toxicity, infections, acute and chronic graft-versus-host disease(a/cGVHD), as well as recurrent and non-recurrent deaths, to estimate the overall survival(OS)rate and event-free survival (EFS)rate.Results:Sixty-seven patients were included in the study, comprising 55 males(82.1%)and 12 females(17.9%), with a median age of 63(61, 65) years .The cohort consisted of 42 cases of acute myeloid leukaemia, 22 cases of myelodysplastic syndromes, and 3 cases of acute lymphoblastic leukaemia.The Kaplan-Meier analysis showed that the 1-year OS and EFS rates were 62.9% and 59.2%, respectively, while the 2-year OS and EFS rates were 55.3% and 51.8%, respectively.The cumulative incidence of 1-year non-relapse mortality and relapse was 25.4% and 21.2%, respectively.A total of 13 patients developed grade Ⅱ-Ⅳ aGVHD, with a 1-year cumulative incidence of 22.0%, and 7 patients developed cGVHD requiring treatment.When stratified by age group, the OS rate was higher in patients aged 60~64 years compared to those aged ≥65 years; however, this difference was not statistically significant(Log-rank χ2=0.99, P=0.317). In contrast, when stratified by disease load, the OS rate was significantly higher in the complete remission(CR)group than in the non-CR group, with a statistically significant difference(Log-rank χ2=15.04, P<0.001). When stratified by donor type, the OS rate was higher in the human leukocyte antigens (HLA) allogeneic group compared to the haploinsufficiency group; however, the difference was not statistically significant(Log-rank χ2=2.71, P=0.100). Twenty-seven patients died at an average of 125 days (range 3-1 054 days) after HSCT.The causes of death included leukemia recurrence in 9 cases (33.3%), infection in 8 cases (29.6%), GVHD in 5 cases (18.5%), poor implantation in 3 cases (11.1%), multi-organ failure in 1 case (3.7%), and cerebrovascular accident in 1 case (3.7%). The results of multifactorial analysis indicated that a pre-transplant tumor load greater than 5% was an independent risk factor for OS after transplantation ( HR=4.59, 95% CI: 2.01-10.42, P<0.001)as well as for disease recurrence ( OR=13.11, 95% CI: 1.96-87.87, P=0.008). Additionally, the occurrence of infection was identified as an independent risk factor for non-recurrent death after transplantation( OR=3.95, 95% CI: 1.13 to 13.71, P=0.031). Conclusions:For patients aged 60 years or older with hematologic malignancies, HSCT can serve as a viable treatment option, particularly for those with refractory recurrence and high cytogenetic risk, as it has the potential to significantly enhance prognosis and increase both EFS and OS rates.

The study investigated the intrinsic changes in material basis of Angelicae Sinensis Radix during wine processing by headspace-gas chromatography-ion mobility spectrometry(HS-GC-IMS), headspace-solid phase microextraction-gas chromatography-mass spectrometry(HS-SPME-GC-MS), and ultra-high performance liquid chromatography-quadrupole-orbitrap mass spectrometry(UPLC-Q-Orbitrap-MS) combined with chemometrics. HS-GC-IMS fingerprints of Angelicae Sinensis Radix before and after wine processing were established to analyze the variation trends of volatile components and characterize volatile small-molecule substances before and after processing. Principal component analysis(PCA) and orthogonal partial least squares-discriminant analysis(OPLS-DA) were employed for differentiation and difference analysis. A total of 89 volatile components in Angelicae Sinensis Radix were identified by HS-GC-IMS, including 14 unsaturated hydrocarbons, 16 aldehydes, 13 ketones, 9 alcohols, 16 esters, 6 organic acids, and 15 other compounds. HS-SPME-GC-MS detected 118 volatile components, comprising 42 unsaturated hydrocarbons, 11 aromatic compounds, 30 alcohols, 8 alkanes, 6 organic acids, 4 ketones, 7 aldehydes, 5 esters, and 5 other volatile compounds. UPLC-Q-Orbitrap-MS identified 76 non-volatile compounds. PCA revealed distinct clusters of raw and wine-processed Angelicae Sinensis Radix samples across the three detection methods. Both PCA and OPLS-DA effectively discriminated between the two groups, and 145 compounds(VIP>1) were identified as critical markers for evaluating processing quality, including 4-methyl-3-penten-2-one, ethyl 2-methylpentanoate, and 2,4-dimethyl-1,3-dioxolane detected by HS-GC-IMS, angelic acid, β-pinene, and germacrene B detected by HS-SPME-GC-MS, and L-tryptophan, licoricone, and angenomalin detected by UPLC-Q-Orbitrap-MS. In conclusion, the integration of the three detection methods with chemometrics elucidates the differences in the chemical material basis between raw and wine-processed Angelicae Sinensis Radix, providing a scientific foundation for understanding the processing mechanisms and clinical applications of wine-processed Angelicae Sinensis Radix.
Wine/analysis* ; Gas Chromatography-Mass Spectrometry/methods* ; Chromatography, High Pressure Liquid/methods* ; Angelica sinensis/chemistry* ; Solid Phase Microextraction/methods* ; Drugs, Chinese Herbal/isolation & purification* ; Chemometrics ; Volatile Organic Compounds/chemistry* ; Principal Component Analysis ; Ion Mobility Spectrometry/methods*

ObjectivePrimary liver cancer, predominantly hepatocellular carcinoma (HCC), is a significant global health issue, ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality. Accurate and early diagnosis of HCC is crucial for effective treatment, as HCC and non-HCC malignancies like intrahepatic cholangiocarcinoma (ICC) exhibit different prognoses and treatment responses. Traditional diagnostic methods, including liver biopsy and contrast-enhanced ultrasound (CEUS), face limitations in applicability and objectivity. The primary objective of this study was to develop an advanced, light-weighted classification network capable of distinguishing HCC from other non-HCC malignancies by leveraging the automatic analysis of brightness changes in CEUS images. The ultimate goal was to create a user-friendly and cost-efficient computer-aided diagnostic tool that could assist radiologists in making more accurate and efficient clinical decisions. MethodsThis retrospective study encompassed a total of 161 patients, comprising 131 diagnosed with HCC and 30 with non-HCC malignancies. To achieve accurate tumor detection, the YOLOX network was employed to identify the region of interest (ROI) on both B-mode ultrasound and CEUS images. A custom-developed algorithm was then utilized to extract brightness change curves from the tumor and adjacent liver parenchyma regions within the CEUS images. These curves provided critical data for the subsequent analysis and classification process. To analyze the extracted brightness change curves and classify the malignancies, we developed and compared several models. These included one-dimensional convolutional neural networks (1D-ResNet, 1D-ConvNeXt, and 1D-CNN), as well as traditional machine-learning methods such as support vector machine (SVM), ensemble learning (EL), k-nearest neighbor (KNN), and decision tree (DT). The diagnostic performance of each method in distinguishing HCC from non-HCC malignancies was rigorously evaluated using four key metrics: area under the receiver operating characteristic (AUC), accuracy (ACC), sensitivity (SE), and specificity (SP). ResultsThe evaluation of the machine-learning methods revealed AUC values of 0.70 for SVM, 0.56 for ensemble learning, 0.63 for KNN, and 0.72 for the decision tree. These results indicated moderate to fair performance in classifying the malignancies based on the brightness change curves. In contrast, the deep learning models demonstrated significantly higher AUCs, with 1D-ResNet achieving an AUC of 0.72, 1D-ConvNeXt reaching 0.82, and 1D-CNN obtaining the highest AUC of 0.84. Moreover, under the five-fold cross-validation scheme, the 1D-CNN model outperformed other models in both accuracy and specificity. Specifically, it achieved accuracy improvements of 3.8% to 10.0% and specificity enhancements of 6.6% to 43.3% over competing approaches. The superior performance of the 1D-CNN model highlighted its potential as a powerful tool for accurate classification. ConclusionThe 1D-CNN model proved to be the most effective in differentiating HCC from non-HCC malignancies, surpassing both traditional machine-learning methods and other deep learning models. This study successfully developed a user-friendly and cost-efficient computer-aided diagnostic solution that would significantly enhances radiologists’ diagnostic capabilities. By improving the accuracy and efficiency of clinical decision-making, this tool has the potential to positively impact patient care and outcomes. Future work may focus on further refining the model and exploring its integration with multimodal ultrasound data to maximize its accuracy and applicability.

Objective To investigate the effect of cordyceps sinensis(CS)on the activation of fibroblasts through IL-6 trans-signaling pathway and its specific mechanism in the treatment of renal fibrosis.Methods Renal fibrosis mouse model was established by unilateral ischemia/reperfusion(UIR),and the mice were administered intragastrically CS,soluble glycoprotein 130 Fc(sgp130Fc)or Hyper-IL-6.Masson's trichrome staining was utilized to identify tubulointerstitial fibrosis.PAS staining was utilized to assess the extent of renal injury.Western blot was employed to analyze the expression levels of fibrosis markers[alpha-smooth muscle actin(α-SMA),fibronectin(FN)]and proteins associated with IL-6 trans-signaling pathway[phosphorylated signal transducer and activator of transcription 3(p-STAT3),soluble interleukin-6 receptor(sIL-6R)].The expression and localization of proteins were additionally detected by immunohistochemistry,immunofluorescence and qPCR.The effect of cordyceps sinensis extract cordycepin on IL-6 trans-signaling in fibroblasts was further investigated in vitro.Results The results from in vivo experiments showed that administration of CS during the chronic phase demonstrated a beneficial protective impact on inflammation and fibrosis in the affected kidney,and serum creatinine levels and collagen deposition were decreased.Western blot analysis revealed a decrease in the expression levels of α-SMA,FN,as well as IL-6 trans-signaling pathway protein p-STAT3,sIL-6R in the treatment group.Additionally,the mRNA expression levels of chemokines monocyte chemoattractant protein-1(MCP-1)and C-X-C motif chemokine ligand 12(CXCL12)were also decreased in the CS treatment group.Additionally,Hyper-IL-6 can partially counteract the therapeutic effects of CS.In vitro experiments further demonstrated that cordycepin inhibited the secretion of IL-6 from NRK-52E.Combined treatment of recombinant IL-6 and sIL-6R protein activated NRK-49F,leading to a significant increase in α-SMA,FN,and p-STAT3 expression levels.Cordycepin or sgp130Fc treatment significantly inhibited the proliferation of fibroblasts induced by IL-6 trans-signaling pathway.Conclusion CS can significantly reduce IL-6 secretion by renal tubular epithelial cells and inhibit the activation of IL-6 trans-signaling pathway in fibroblasts,thereby ameliorating renal interstitial fibrosis.

Objective To summarize the changing prevalence of carbapenem resistance in Enterobacterales based on the data of CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021 for improving antimicrobial treatment in clinical practice.Methods Antimicrobial susceptibility testing was performed using a commercial automated susceptibility testing system according to the unified CHINET protocol.The results were interpreted according to the breakpoints of the Clinical & Laboratory Standards Institute(CLSI)M100 31st ed in 2021.Results Over the seven-year period(2015-2021),the overall prevalence of carbapenem-resistant Enterobacterales(CRE)was 9.43％(62 342/661 235).The prevalence of CRE strains in Klebsiella pneumoniae,Citrobacter freundii,and Enterobacter cloacae was 22.38％,9.73％,and 8.47％,respectively.The prevalence of CRE strains in Escherichia coli was 1.99％.A few CRE strains were also identified in Salmonella and Shigella.The CRE strains were mainly isolated from respiratory specimens(44.23±2.80)％,followed by blood(20.88±3.40)％and urine(18.40±3.45)％.Intensive care units(ICUs)were the major source of the CRE strains(27.43±5.20)％.CRE strains were resistant to all the β-lactam antibiotics tested and most non-β-lactam antimicrobial agents.The CRE strains were relatively susceptible to tigecycline and polymyxins with low resistance rates.Conclusions The prevalence of CRE strains was increasing from 2015 to 2021.CRE strains were highly resistant to most of the antibacterial drugs used in clinical practice.Clinicians should prescribe antimicrobial agents rationally.Hospitals should strengthen antibiotic stewardship in key clinical settings such as ICUs,and take effective infection control measures to curb CRE outbreak and epidemic in hospitals.

Objective To characterize the changing species distribution and antibiotic resistance profiles of respiratory isolates in hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Methods Commercial automated antimicrobial susceptibility testing systems and disk diffusion method were used to test the susceptibility of respiratory bacterial isolates to antimicrobial agents following the standardized technical protocol established by the CHINET program.Results A total of 589 746 respiratory isolates were collected from 2015 to 2021.Overall,82.6％of the isolates were Gram-negative bacteria and 17.4％were Gram-positive bacteria.The bacterial isolates from outpatients and inpatients accounted for(6.0±0.9)％and(94.0±0.1)％,respectively.The top microorganisms were Klebsiella spp.,Acinetobacter spp.,Pseudomonas aeruginosa,Staphylococcus aureus,Haemophilus spp.,Stenotrophomonas maltophilia,Escherichia coli,and Streptococcus pneumoniae.Each microorganism was isolated from significantly more males than from females(P＜0.05).The overall prevalence of methicillin-resistant S.aureus(MRSA)was 39.9％.The prevalence of penicillin-resistant S.pneumoniae was 1.4％.The prevalence of extended-spectrum β-lactamase(ESBL)-producing E.coli and K.pneumoniae was 67.8％and 41.3％,respectively.The overall prevalence of carbapenem-resistant E.coli,K.pneumoniae,Enterobacter cloacae,Pseudomonas aeruginosa,and Acinetobacter baumannii was 3.7％,20.8％,9.4％,29.8％,and 73.3％,respectively.The prevalence of β-lactamase was 96.1％in Moraxella catarrhalis and 60.0％in Haemophilus influenzae.The H.influenzae isolates from children(＜18 years)showed significantly higher resistance rates to β-lactam antibiotics than the isolates from adults(P＜0.05).Conclusions Gram-negative bacteria are still predominant in respiratory isolates associated with serious antibiotic resistance.Antimicrobial resistance surveillance should be strengthened in clinical practice to support accurate etiological diagnosis and appropriate antimicrobial therapy based on antimicrobial susceptibility testing results.

Objective To identify determinants of subtherapeutic voriconazole(VRCZ)concentrations in allogeneic hematopoietic stem cell transplantation(allo-HSCT)recipients and to develop/validate a nomogram-based risk prediction model.Methods This study retrospectively analyzed 310 VRCZ therapeutic drug monitoring(TDM)measurements from allo-HSCT recipients at 310 patients who under went allo-HSCT surgery at Hebei Yanda Ludaopei Hospital from October 2022 to October 2024 and received VRCZ for the prevention and treatment of invasive fungal infections before transplantion were selected as the study subjects.Cases were stratified into target-concentration group(0.5～5.0μg/ml)and subtherapeutic group(<0.5μg/ml).Through single factor and multiple factor Logistic regression analysis,indeipendent predictive factors forvecz plasma concentration non-compliance were screened,and a column chart prediction model(NPM)was constructed.The performance of the model was evaluateding area under the receiver operating characteristic curve(AUC),Hosmer-Lemeshow(H-L)goodness-of-fit test,and decision curve analysis(DCA).Results Among 310 VRCZ-TDM measurements,71.61%(222/310)achieved target concentrations.Multivariate analysis showed that CYP2C19 intermediate metabolite,daily dose of cyclosporine A(CSA),daily dose of VRCZ,creatinine(Cr)>97 μmol/L,albumin(Alb)and C-reactive protein(CRP)were independent influencing factors for VRCZ blood drug concentration non-compliance(Wald χ2=4.046～13.221,all P＜0.05).The nomogram demonstrated excellent discrimination,calibration(H-L goodness of fit test χ2=2.663,P=0.954),and clinical utility with net benefit across 0.05～0.96 risk thresholds.Conclusion The nomogram incorporating CYP2C19 gene phenotype,daily CSA dosing,daily VRCZ dosing,Cr levels,Alb and CRP provides a validated tool for optimizing VRCZ therapy in allo-HSCT recipients,enabling precision dosing strategies.

Objective To examine the changing prevalence and antimicrobial resistance profiles of Burkholderia cepacia in 52 hospitals across China from 2015 to 2021.Methods A total of 9 261 strains of B.cepacia were collected from 52 hospitals between January 1,2015 and December 31,2021.Antimicrobial susceptibility of the strains was tested using Kirby-Bauer method or automated antimicrobial susceptibility testing systems according to a unified protocol.The results were interpreted according to the breakpoints released in the Clinical & Laboratory Standards Institute(CLSI)guidelines(2023 edition).Results A total of 9 261 strains of B.cepacia were isolated from all age groups,especially elderly patients.The proportion was 11.1％(1 032 strains)in children,significantly lower than the proportion in adults.About half(46.5％,4 310/9 261)of the strains were isolated from patients at least 60 years old and 42.3％(3 919/9 261)of the strains were isolated from young adults.Most isolates(71.1％)were isolated from sputum and respiratory secretions,followed by urine(10.7％)and blood samples(8.1％).B.cepacia isolates were highly susceptible to the five antimicrobial agents recommended in the CLSI M100 document(33rd edition,2023).B.cepacia isolates showed relatively higher resistance rates to meropenem and levofloxacin.However,the resistance rates to ceftazidime,trimethoprim-sulfamethoxazole,and minocycline remained below 8.1％.The percentage of B.cepacia strains resistant to levofloxacin was the highest compared to other antibiotics in any of the three age groups(from 12.4％in the patients＜18 years old to 20.6％in the patients aged 60 years or older).Conclusions B.cepacia is one of the clinically important non-fermenting gram-negative bacteria.Accurate and timely reporting of antimicrobial susceptibility test results and ongoing antimicrobial resistance surveillance are helpful for rational prescription of antimicrobial agents and proper prevention and control of nosocomial infections.

Aim To explore the mechanism of baicalin combined with heat stimulation in treating acute lym-phoblastic leukemia(ALL)based on network pharma-cology and in vitro experiments.Methods The CCK-8 assay was used to screen the suitable conditions for heat stimulation to interfere ALL cell lines Jurkat,CCRF-CEM,Hut-78 and a normal lymphocyte HMy2.CIR,and the effects of baicalin combined with heat stimulation on the proliferation of three ALL cell lines and a normal lymphocyte were tested.The key targets of baicalin combined with fever stimulation for the treatment of ALL were obtained based on network phar-macological analysis,and the potential mechanisms were predicted by gene ontology(GO)annotation and kyoto encyclopedia of genes and genomes(KEGG)en-richment.The expression levels of TNF-α,AKT1,TYMS and CASP3 mRNA in ALL cell lines Jurkat and CCRF-CEM were examined by RT-qPCR with baicalin alone and baicalin combined with heat stimulation.Results The optimal conditions for heat stimulation to intervene ALL cells were 41 ℃ for 24 h,and heat stimulation combined with baicalin synergistically inhibited the growth of ALL cell lines and effectively reduced the cy-totoxicity of baicalin.Based on the network pharmaco-logical analysis,55 intersecting targets of baicalin with ALL diseases and 77 intersecting targets of baicalin with fever were obtained.The results of GO annotation and KEGG enrichment suggested that baicalin com-bined with fever stimulation to intervene ALL might be associated with influencing intracellular reactive oxygen species metabolism,DNA transcription and apoptotic processes involved in cysteine enzymes.Apoptosis,TNF and IL-17 signaling pathways were the key pathways for baicalin combined with heat stimulation in treating ALL.Under heat stimulation at 41 ℃ using SDHA gene as housekeeping gene,in vitro experiments showed that baicalin significantly up-regulated the expression of TNF-α and CASP3,and down-regulated the expression of TYMS in ALL cells.Conclusions Based on net-work pharmacologic analyses and in vitro experiments,baicalin combined with heat stimulation can regulate TNF-α and CASP3 gene levels in ALL cells and de-stroy cellular structure to promote cell apoptosis,thus synergistically treating ALL.