Yongjun Ma

Introduction: Current Toxoplasma gondii (TOX), Epstein–Barr virus (EBV), rubella virus, human cytomegalovirus (HCMV), and herpes simplex virus types I and II (HSV I and II) (TORCHes) diagnostic methods are limited by challenges, such as multi-step workflows and cold-chain dependency. This study aimed to develop an integrated “sample-in-result-out” system combining rapid nucleic acid release, room-temperature-stable multiplex polymerase chain reaction (PCR), and automated interpretation to improve diagnostic accuracy. Methods: We utilized a self-prepared lysis buffer for fast nucleic acid extraction from diverse sample types. Primers, probes, and reaction components for six TORCHes pathogens were fabricated into freeze-dried microspheres via vacuum freeze-drying, enabling single-tube multicolor melting curve analysis (MMCA). The companion software, TORCHes-MCAv1.0, was used to automate pathogen typing and result reporting. Evaluation metrics encompassed sensitivity, specificity, precision, stability, and anti-interference ability. The system was validated using 210 clinical samples compared to commercial single-target qPCR, with Sanger sequencing resolving any discrepancies. Results: Nucleic acid extraction and release were completed within 1 min. Freeze-dried microspheres demonstrated exceptional repeatability, with T _m intra- and inter-batch CVs of 0.03–0.18%. Limits of detection (LoD) were 200 copies/mL for HSV-I/II, HCMV, and TOX, and 500 copies/mL for EBV and RV. Specificity analysis showed no cross-reactivity with non-target pathogens. Stability testing confirmed the microspheres could be stored stably at room temperature for 1 year. Clinical validation showed near-perfect agreement with qPCR (Kappa = 0.965–1.000), with all seven discrepant results confirmed correct via sequencing. The TORCHes-MCAv1.0 software achieved 100% concordance with manual interpretation. Conclusion: We developed a robust, streamlined integrated TORCHes detection system. Its simplicity, stability, and high-throughput nature make it a valuable complementary tool for confirming active infection and differentiating pathogen subtypes in complex clinical scenarios.

Currently, there are many studies on the relationship between the ADIPOQ gene polymorphisms and the onset of type 2 diabetes (T2D), and the research results vary among different regions and ethnic groups. However, there are relatively few studies on the relationship between ADIPOQ gene polymorphisms and the occurrence and severity of diabetic kidney disease (DKD). This study aims to investigate the association of DKD with the ADIPOQ gene polymorphisms rs2241766 and rs1063537 in patients with T2D in the Han population in southern China. A total of 347 patients with type 2 diabetic kidney disease (T2DKD) from the Jinhua area in central Zhejiang between 2021 and 2023 were enrolled as the case group, which was divided into the microalbuminuria phase (group I: urinary albumin-to-creatinine ratio [UACR] 30–299 mg/g, 185 cases) and the macroalbuminuria phase (group II: UACR ≥ 300 mg/g, 162 cases) based on UACR. Meanwhile, 191 patients with T2D and without kidney disease were recruited as the control group during the same period. The KASP-PCR (competitive allele-specific polymerase chain reaction) technique was used for genotyping of the rs2241766 and rs1063537 loci in the ADIPOQ gene, aiming to explore their associations with the occurrence and severity of T2DKD. The frequency of the TT genotype at the rs1063537 locus was 8.6% in group I and 15.4% in group II, with a statistically significant difference in distribution between the 2 groups ( P < .05). After adjusting for age, gender, body mass index (BMI), diabetes duration, hypertension status, creatinine, and fasting plasma glucose, this genotype was significantly associated with the macroalbuminuria phase of T2DKD ( P = .016), meaning that carriers of the TT genotype had a 2.47-fold higher risk of developing macroalbuminuria compared with those with the CC genotype. No statistically significant differences were observed in the genotype distributions of the rs2241766 and rs1063537 loci in the ADIPOQ gene between the case group and the control group ( P > .05). In the Han population in southern China, the TT genotype at the rs1063537 locus of the ADIPOQ gene in patients with T2DKD is significantly associated with the presence of the macroalbuminuria stage.

Background: The role of high-density lipoprotein cholesterol (HDL-C) in diabetic kidney disease (DKD) remains controversial. This study aimed to delineate the subgroup-specific relationships between the two by exploring cumulative and threshold effects. Methods: 3,040 patients with type 2 diabetes and no baseline evidence of DKD were included. Cox proportional hazards regression models were performed to investigate the potential relationship between HDL-C level and DKD risk. To address subgroup heterogeneity, sex-stratified restricted cubic splines (RCS) were employed to model nonlinear relationships. The optimal threshold was identified through the maximum selected statistics and validated via 1,000 bootstrap iterations. Subgroup analyses stratified by sex, diabetes duration, and metabolic status were performed to evaluate heterogeneity. Survival analysis using Kaplan-Meier curves further validated these threshold effects. Results: During a median follow-up of 3.13 years, 665 subjects (21.9%) progressed to DKD. Overall, each 1 mmol/L increase in HDL-C level independently reduced DKD risk by 43%. RCS analysis demonstrated an inverse correlation between HDL-C and DKD risk (P for overall = 0.025, P for nonlinear = 0.317), with increased risk reduction at lower concentrations, plateauing at higher levels. A robust threshold of 0.93 mmol/L was identified, showing significantly stronger protection against DKD progression (hazard ratio (HR) = 0.69, P < 0.001) compared to the traditional cutoff (HR = 0.86, P = 0.109). Females showed continuous protection (HR = 0.41, P = 0.009) without threshold dependency. The male and diabetes duration < 10 years subgroups exhibited threshold effects at > 0.93 mmol/L without continuous protection. The metabolically unstable (hypertension, poorly controlled glycemia, body mass index (BMI) > 28 kg/m²) and BMI < 24 kg/m² subgroups displayed dual effects (P < 0.05). Survival analysis confirmed lower cumulative DKD incidence with HDL-C > 0.93 mmol/L (P = 0.007). Conclusions: This study reveals sex- and metabolic context-dependent heterogeneity in HDL-C-DKD associations: males and short-duration diabetes exhibited threshold effects (0.93 mmol/L), females showed continuous protection, and subgroups with hypertension, poorly controlled glycemia, or obesity (BMI > 28 kg/m²) exhibited both continuous protection and threshold effects. These findings may inform individualized risk stratification in specific populations.

Background: Previous studies have compared the incidence of pertussis before and during the COVID-19 pandemic, finding that public health measures related to COVID-19 contributed to a temporary decline in reported pertussis cases during the pandemic. However, the post-pandemic period has seen a resurgence in respiratory infections, influenced by relaxed health measures and decreased public vigilance. This study investigates the epidemiological dynamics of pertussis among patients with acute respiratory tract infections (ARTI) in Zhejiang Province, China, providing essential reference information for ongoing public health strategies.Methods: This study analyzed multicenter data from January 2023 to May 2024, involving 8,560 patients with ARTI from three hospitals in Zhejiang Province. Inclusion criteria included patients who presented with cough symptoms and were clinically diagnosed with either acute upper respiratory tract infections (URTI) or acute lower respiratory tract infections (LRTI), and who had undergone at least one Bordetella pertussis DNA test. The study analyzed the epidemiological changes of pertussis positivity rates and their associations with time, age, gender, and diagnosis types (URTI and LRTI).Results: From January 2023 to May 2024, the positivity rate and testing number for pertussis among patients with ARTI generally showed a gradual increasing pattern. In March 2024, the positivity rate reached its peak at 31.58%, followed by a weekly decline. The overall positivity rate was 23.59%, with no significant differences observed between genders. Pertussis incidence was higher in patients with LRTI (24.49%) compared to those with URTI (18.63%, OR = 1.40, 95% CI: 1.20–1.63, p < 0.001) and in outpatients (25.32%) compared to inpatients (6.09%, OR = 4.17, 95% CI: 3.07–5.64, p < 0.001). According to a generalized additive model analysis, there was a wave-shaped, non-linear relationship between age and pertussis incidence, with a relatively high rate observed in the 5 to 17 age group, peaking at age 10 (33.85%). Additionally, the impact of age, patient type, and diagnosis type on the pertussis infection rate varied across different age groups.Conclusion: After the COVID-19 pandemic, the positivity rate of pertussis in Zhejiang Province peaked in early 2024 and then showed a declining pattern. Children and adolescents were particularly affected, emphasizing the need for enhanced vaccination and public health interventions in this population.

Studies have indicated that low high-density lipoprotein cholesterol (HDL-C) level is an important risk factor for diabetic kidney disease (DKD) in patients with type 2 diabetes (T2D). However, whether higher HDL-C levels decrease the risk of developing DKD remains unclear. This study aimed to clarify the relationship between HDL-C levels and DKD risk in individuals with T2D in China. In total, 936 patients with T2D were divided into DKD and non-DKD groups. The association between HDL-C levels and DKD risk was evaluated using logistic regression analysis and restricted cubic spline curves adjusted for potential confounders. Threshold effect analysis of HDL-C for DKD risk was also performed. Higher HDL-C levels did not consistently decrease the DKD risk. Furthermore, a nonlinear association with threshold interval effects between HDL-C levels and the incidence of DKD was observed. Patients with HDL-C ≤ 0.94 mmol/L or HDL-C > 1.54 mmol/L had significantly higher DKD risk after adjusting for confounding factors. Interestingly, the association between high HDL-C levels and increased DKD risk was more significant in women. A U-shaped association between HDL-C levels and DKD risk was observed; therefore, low and high HDL-C levels may increase the DKD risk in patients with T2D.

Background: Previous studies have confirmed that the triglyceride glucose (TyG) index, recognized as a reliable marker of insulin resistance, is an important risk factor for diabetic kidney disease (DKD). However, it is still unclear whether the DKD risk continues to increase linearly with the elevation of TyG index. This study aimed to thoroughly investigated the intrinsic relationship between TyG index and DKD risk in type 2 diabetes (T2D).Methods: This cross-sectional study included 933 patients with T2D in China, who were categorized into DKD and non-DKD groups and stratified by TyG index levels. Logistic regression analysis identified the independent risk factors for DKD. The association between DKD risk and TyG index was evaluated using the restricted cubic spline (RCS) curves analysis. The R package ‘CatPredi’ was utilized to determine the optimal cut-off point for the relationship between DKD risk and TyG index, followed by threshold effect analysis.Results: The prevalence of DKD was 33.01%. After adjusting for confounding factors, TyG index was identified as a prominent clinical risk factor for DKD, showing the highest odds ratio (OR 1.57 (1.26 - 1.94), P 9.35, DKD risk increased gradually with rising TyG index. Among patients with TyG index > 9.35, each 1-unit increase was associated with a 1.94-fold increased DKD risk (OR=1.94 (1.10 - 3.43), P=0.022).Conclusion: The DKD risk presented a threshold effect with the increase of TyG index, initially stable at a low level, and then gradually rising when the TyG index is above 9.35.

Background: Our previous cross-sectional study has demonstrated the independently non-linear relationship between fasting C-peptide with renal dysfunction odds in patients with type 2 diabetes (T2D) in China. This longitudinal observational study aims to explore the role of serum C-peptide in risk prediction of new-onset renal dysfunction, then construct a predictive model based on serum C-peptide and other clinical parameters.Methods: The patients with T2D and normal renal function at baseline were recruited in this study. The LASSO algorithm was performed to filter potential predictors from the baseline variables. Logistic regression (LR) was performed to construct the predictive model for new-onset renal dysfunction risk. Power analysis was performed to assess the statistical power of the model.Results: During a 2-year follow-up period, 21.08% (35/166) of subjects with T2D and normal renal function at baseline progressed to renal dysfunction. Six predictors were determined using LASSO regression, including baseline albumin-to-creatinine ratio, glycated hemoglobin, hypertension, retinol-binding protein-to-creatinine ratio, quartiles of fasting C-peptide, and quartiles of fasting C-peptide to 2h postprandial C-peptide ratio. These 6 predictors were incorporated to develop model for renal dysfunction risk prediction using LR. Finally, the LR model achieved a high efficiency, with an AUC of 0.83 (0.76 - 0.91), an accuracy of 75.80%, a sensitivity of 88.60%, and a specificity of 70.80%. According to the power analysis, the statistical power of the LR model was found to be 0.81, which was at a relatively high level. Finally, a nomogram was developed to make the model more available for individualized prediction in clinical practice.Conclusion: Our results indicated that the baseline level of serum C-peptide had the potential role in the risk prediction of new-onset renal dysfunction. The LR model demonstrated high efficiency and had the potential to guide individualized risk assessments for renal dysfunction in clinical practice.

Background: Previous studies had showed divergent findings on the associations of C-peptide and/or uric acid (UA) with renal dysfunction odds in patients with type 2 diabetes mellitus (T2DM). We hypothesized that there were non-linear relationships between C-peptide, UA and renal dysfunction odds. This study aimed to further investigate the relationships of different stratification of C-peptide and UA with renal dysfunction in patients with T2DM.Method: We conducted a cross-sectional real-world observational study of 411 patients with T2DM. The levels of fasting C-peptide, 2h postprandial C-peptide, the ratio of fasting C-peptide to 2h postprandial C-peptide (C0/C2 ratio), UA and other characteristics were recorded. Restricted cubic spline (RCS) curves was performed to evaluated the associations of stratified C-peptide and UA with renal dysfunction odds.Results: Fasting C-peptide, C0/C2 ratio and UA were independently and significantly associated with renal dysfunction in patients with T2DM as assessed by multivariate analyses (p < 0.05). In especial, non-linear relationships with threshold effects were observed among fasting C-peptide, UA and renal dysfunction according to RCS analyses. Compared with patients with 0.28 ≤ fasting C-peptide ≤ 0.56 nmol/L, patients with fasting C-peptide < 0.28 nmol/L (OR = 1.38, p = 0.246) or fasting C-peptide > 0.56 nmol/L (OR = 1.85, p = 0.021) had relatively higher renal dysfunction odds after adjusting for confounding factors. Similarly, compared with patients with 276 ≤ UA ≤ 409 μmol/L, patients with UA < 276 μmol/L (OR = 1.32, p = 0.262) or UA > 409 μmol/L (OR = 6.24, p < 0.001) had relatively higher odds of renal dysfunction.Conclusion: The renal dysfunction odds in patients with T2DM was non-linearly associated with the levels of serum fasting C-peptide and UA. Fasting C-peptide and UA might have the potential role in odds stratification of renal dysfunction.