ObjectiveTo evaluate the detection specificity for clinical samples and the detection capability for standard substances of five commercially available multiplex polymerase chain reaction (PCR) nucleic acid detection kits (hereinafter referred to as the kits) for respiratory pathogens, and to provide a reference for selecting appropriate detection kits for multi-pathogen nucleic acid testing of respiratory infections. MethodsA total of 60 respiratory pathogen-positive clinical samples with known redults were selected and tested using the five kits (labeled as A, B, C, D, and E). The detection rates and Kappa coefficients were calculated to evaluate the consistency between the results from these kits and those from single-pathogen PCR kits. According to the limit of detection (LOD) provided by the kits, standard substances of respiratory pathogens (including 12 types such as influenza virus, Mycoplasma pneumoniae, and Bordetella pertussis) were diluted to four concentrations (250, 500, 1 000, and 2 000 copies·mL⁻¹). All five kits were used for detection to evaluate their respective detection capabilities. ResultsCompared with the results from single-pathogen PCR kits, the five tested kits demonstrated good consistency (all Kappa >0.80). Among them, Kit A had the highest detection rate (100.00%), followed by Kits C and E (98.33%), and then Kits B and D (95.00%). All five kits showed a relatively low false negative rate (FNR) for samples with a cycle threshold (Ct) value ≤35 (≤2.38%). However, for samples with Ct values>35, the FNR increased accordingly(average FNR=6.67%, P=0.029). Kit C exhibited the highest detection sensitivity for the tested standard substances (average LOD: 458.33 copies·mL⁻¹), followed by Kit D, then Kits A/E, and finally Kit B. ConclusionThe five multiplex PCR kits showed good consistency with single-pathogen detection results, but each had its own performance emphasis. Kit A, with the highest detection rate and high throughput, is suitable for targeted viral screening. Kit B, covering the broadest pathogen spectrum (including fungi/bacteria), is suitable for comprehensive respiratory pathogen screening. Kits C, D and E, are applicable for rapid detection. It is important to note that the detection efficacy of all kits decreases for low viral load samples with Ct values >35. In practical application, selection should be based on specific screening objectives, throughput requirements, and sample types.

Chimeric antigen receptor T-cell (CAR-T) therapy, a revolutionary technology in tumor immunotherapy, has achieved breakthrough progress in the treatment of hematological malignancies. To date, multiple CAR-T products have been approved for clinical use worldwide, but progress in their application to solid tumor treatment has been slow mainly due to the highly complex biological characteristics of solid tumors. In recent years, the continuous identification of novel targets in solid tumors, continuous innovations in genetic engineering technologies, growing maturity of combination therapeutic strategies, and rapid advancement in artificial intelligence have expanded the potential applications of CAR-T therapy in solid tumor treatment, highlighting its broad translational prospects. This article systematically reviews recent clinical progress in CAR-T therapy for solid tumors, comprehensively analyzes core challenges and corresponding countermeasures, and outlines future directions.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Objective To explore the application value of combining the ultrasound breast imaging reporting and data system(BI-RADS)classification with serum fibroblast growth factor receptor 1(FGFR1)and growth differentiation factor 3(GDF3)in the differential diagnosis of benign and malignant breast masses.Methods A total of 159 patients with breast masses were selected and divided into the benign mass group(n=83)and the malignant mass group(n=76)based on postoperative pathological diagnosis.All patients underwent ultrasound examination,and enzyme-linked immunosorbent assay(ELISA)was applied to detect serum levels of FGFR1 and GDF3.Receiver operating characteristic(ROC)curve was applied to analyze the diagnostic value of ultrasound BI-RADS classification and serum FGFR1 and GDF3 levels for benign and malignant breast masses.Kappa test was applied to analyze the consistency between various diagnostic methods and pathological diagnosis.Results The serum levels of FGFR1 and GDF3,the proportions of irregular morphology,unclear boundaries,spiculation,microcalcifications,blood flow grade Ⅱ-Ⅲ and posterior echo attenuation,RI and PI were higher in the malignant tumor group than those in the benign tumor group(P＜0.05).The area under the curve(AUC)of FGFR1,GDF3 and ultrasound BI-RADS classification in the differential diagnosis of benign and malignant breast masses separately and in combination was 0.802(95%CI:0.732-0.871),0.817(95%CI:0.751-0.884),0.848(95%CI:0.784-0.912)and 0.956(95%CI:0.918-0.993),respectively.The combined diagnosis was more effective than that of the individual diagnosis of each indicator.The consistency between the individual and combined diagnosis of benign and malignant breast masses and pathological diagnosis showed that the Kappa values were 0.517,0.514,0.688 and 0.912,respectively,with the highest consistency observed in the combined diagnosis(P＜0.05).Conclusion Ultrasound BI-RADS classification combined with serum FGFR1 and GDF3 has high application value in the differential diagnosis of benign and malignant breast masses.

Objective:To provide novel genetic biomarkers for the diagnosis and treatment of sepsis,bioinformatics analysis was used to screen differentially expressed genes and identify Hub genes in sepsis.Methods:Gene Expression Omnibus(GEO)database was used to retrieve gene expression datasets of sepsis and screen for differentially expressed genes(DEGs).Protein-protein interaction(PPI)network analysis,Gene Ontology(GO)analysis,and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analysis were used to clarify the molecular mechanism of DEGs,and Hub genes were screened.Results:A total of 361 DEGs were identified,including 163 up-regulated genes and 198 down-regulated genes.Enrichment analysis revealed that these DEGs were primarily involved in antigen processing and presentation,T cell biology,cell adhesion molecules,and T cell receptor signaling pathways.CD4,TP53,PTPRC,LCK,ITGAM,ZAP70,CD247,CD2,CD3E,and HSP90AB1 were determined as optimal diagnostic biomarkers for sepsis.Conclusions:This study elucidated 10 Hub genes(CD4,TP53,PTPRC,LCK,ITGAM,ZAP70,CD247,CD2,CD3E,and HSP90AB1)as potential biomarkers for the diagnosis and treatment of sepsis.However,since the the generalizability of these Hub genes in patients with sepsis remains unvalidated,further experimental verification is still needed in the future.

Objective:To investigate the effect of internet-based perinatal nutrition clinic initiated management at different trimesters on pregnancy outcomes.Methods:Adopting a retrospective study design,1120 singleton pregnant women registered at Nanning Maternal and Child Health Hospital from March 2021 to March 2022 were included.Randomly divided into early pregnancy intervention group(single day randomized,n=551)and mid pregnancy intervention group(double day randomized,n=569)based on the registation date.Both groups received internet-based perinatal nutrition clinic initiated management.The general information,pre pregnancy BMI,weight gain during pregnancy and pregnancy outcomes between two groups were compared.The pregnancy outcomes of two different pre pregnancy weight classification groups were compared.Results:Compared of age and weight gain during pregnancy between early pregnancy intervention group and mid pregnancy intervention group,the difference was statistically significant(P＜0.05).Compared of delivery mode,hypertensive disorders of pregnancy(HDP),gestational diabetes mellitus(GDM)and macrosomia between the early pregnancy intervention group and the mid pregnancy intervention group,the difference was statistically significant(P＜0.05).Compared of low birth weight infants and weight gain during pregnancy in low body weight group between early intervention and mid intervention,the difference was statistically significant(P＜0.05).Compared of delivery mode,GDM and weight gain during pregnancy in normal weight group between early intervention and mid intervention,the difference was statistically significant(P＜0.05).Compared of delivery mode,HDP,GDM,postpartum hemorrhage,macrosomia and weight gain during pregnancy in overweight group between early intervention and mid intervention,the difference was statistically significant(P＜0.05).Compared of delivery mode,HDP,GDM and weight gain during pregnancy in obesity group between early intervention and mid intervention,the difference was statistically significant(P＜0.05).Conclusion:Early pregnancy nutrition weight management based on internet-based perinatal nutrition clinic can regulate the rate of weight gain during pregnancy,can effectively reduce the risk of HDP,GDM and cesarean section.

Objective:To provide novel genetic biomarkers for the diagnosis and treatment of sepsis,bioinformatics analysis was used to screen differentially expressed genes and identify Hub genes in sepsis.Methods:Gene Expression Omnibus(GEO)database was used to retrieve gene expression datasets of sepsis and screen for differentially expressed genes(DEGs).Protein-protein interaction(PPI)network analysis,Gene Ontology(GO)analysis,and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analysis were used to clarify the molecular mechanism of DEGs,and Hub genes were screened.Results:A total of 361 DEGs were identified,including 163 up-regulated genes and 198 down-regulated genes.Enrichment analysis revealed that these DEGs were primarily involved in antigen processing and presentation,T cell biology,cell adhesion molecules,and T cell receptor signaling pathways.CD4,TP53,PTPRC,LCK,ITGAM,ZAP70,CD247,CD2,CD3E,and HSP90AB1 were determined as optimal diagnostic biomarkers for sepsis.Conclusions:This study elucidated 10 Hub genes(CD4,TP53,PTPRC,LCK,ITGAM,ZAP70,CD247,CD2,CD3E,and HSP90AB1)as potential biomarkers for the diagnosis and treatment of sepsis.However,since the the generalizability of these Hub genes in patients with sepsis remains unvalidated,further experimental verification is still needed in the future.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.