Biomedical subjects

Li Zeng

Publications and source records attributed to Li Zeng.

5 recordsLinked to original sources

PubMed2026

A stent-plus-irrigation protocol after adolescent hypospadias repair: a multicentre randomised controlled trial.

OBJECTIVES: To evaluate whether a stent-plus-irrigation protocol reduces complication rates following hypospadias repair in adolescents compared with catheter drainage alone. PATIENTS AND METHODS: In this multicentre randomised controlled trial, adolescents (Tanner Stage II-V) undergoing hypospadias repair were randomly assigned to either a stent-plus-irrigation group or a catheter-drainage group. The catheter-drainage group received standard urethral catheter drainage alone, whereas the stent-plus-irrigation group received an additional small-calibre urethral stent positioned within the reconstructed urethra and twice-daily saline irrigation. The primary outcome was the overall postoperative complication rate; secondary outcomes included urinary function and cosmetic outcomes. RESULTS: A total of 172 adolescents were assessed for eligibility, with 150 participants (75 in the stent-plus-irrigation group and 75 in the catheter-drainage group) included in the final analysis. Compared with the catheter-drainage group, the stent-plus-irrigation group demonstrated a significantly lower overall complication rate (risk ratio [RR] 0.33, 95% confidence interval [CI] 0.20-0.56; P < 0.001), urethral fistula rate (RR 0.27, 95% CI 0.14-0.51; P < 0.001), and surgical site infection (SSI) rate (RR 0.43, 95% CI 0.21-0.87; P = 0.020). CONCLUSIONS: A postoperative stent-plus-irrigation protocol was associated with lower rates of postoperative complications, particularly urethral fistula and SSI, compared with catheter drainage alone after adolescent hypospadias repair. Because the intervention included both an additional urethral stent and saline irrigation, the independent contribution of irrigation cannot be determined in this two-arm trial.

Humans↗

PubMed2026

Associations of clinical and laboratory parameters with pediatric urolithiasis composition: A retrospective, single-center study.

OBJECTIVE: To investigate demographic, clinical, and laboratory factors associated with distinct stone compositions in children. METHODS: This retrospective study included 237 children aged <14 years who underwent stone composition analysis between July 2008 and November 2023. Demographic, clinical, and laboratory data were collected, and propensity score matching (PSM) was used to control for confounding factors. RESULTS: The urate component (uric acid anhydrous, ammonium acid urate, and sodium urate) was most prevalent in infants, males, and non-Han children, whereas the calcium oxalate component predominated in older children. Analysis of coexisting components revealed urate is the most common partner to calcium oxalate (67.6%), and vice versa (82.8%). Struvite most frequently coexisted with carbonate apatite (60%), while carbonate apatite most often coexisted with calcium oxalate (54%). After PSM, the urate component was independently associated with host metabolic dysregulation, including lower high-density lipoprotein (β = -0.175, 95% CI: -0.279 to -0.071, p = 0.001) and with coagulation dysfunction, as evidenced by a prolonged prothrombin time (β = 0.595, 95% CI: 0.125 to 1.064, p = 0.014). Additionally, preoperative urinary tract infection (UTI) and congenital urinary tract anomalies were independently associated with both carbonate apatite and struvite components, with directionally consistent but quantitatively unstable signals in the struvite cohort, whereas the calcium oxalate component exhibited an inverse association with UTI (OR = 0.156, 95% CI: 0.030 to 0.819, p = 0.028). Furthermore, the carbonate apatite component was also independently associated with an elevated systemic immune-inflammation index (β = 416.53, 95% CI: 60.05 to 773.01, p = 0.024) and systemic inflammation response index (β = 1.286, 95% CI: 0.086 to 2.487, p = 0.038). CONCLUSION: Urate component was prevalent in infants, males, and non-Han children, whereas calcium oxalate predominated in older children. After adjusting for confounders, urate composition was associated with metabolic abnormalities, the carbonate apatite component was linked to infection and anatomical malformations, and a similar directional pattern was observed in the struvite cohort.

Humans↗

PubMed2026

Unveiling the BMI Risk Threshold for Osteoarthritis: Multi-Database Causal and Nonlinear Evidence.

OBJECTIVE: To characterize the nonlinear relationship between BMI and osteoarthritis (OA), and to identify BMI thresholds that inform precise prevention strategies. METHODS: This multi-database study integrated Global burden of disease 2021, National Health and Nutrition Examination Survey 2007-2018, and Genome-Wide Association Studies. A generalized additive model was performed to visualize the BMI-OA relationship, adjusting for multiple confounders. We applied segmented logistic regression models to identify potential threshold effects and used Mendelian randomization to estimate the causal effects of BMI on OA subtypes. RESULTS: From 1990 to 2021, the age-standardized prevalence and years lived with disability rates for OA were highest in regions with high SDI. OA prevalence rose nonlinearly with BMI, with breakpoints at 24.00 and 41.58 kg/m2. Each unit increase in BMI was associated with higher odds of OA between 24.00 and 41.58 kg/m2 (OR = 1.022, 95% CI: 1.003-1.041) and above 41.58 kg/m2 (OR = 1.055, 95% CI: 1.022-1.090). Women and individuals aged ≥ 45 years exhibited a higher susceptibility to knee osteoarthritis. BMI was causally associated with knee osteoarthritis (OR = 1.63, 95% CI 1.50-1.77) and hip osteoarthritis (OR = 1.54, 95% CI 1.40-1.70). CONCLUSIONS: These findings suggest that OA risk awareness and weight-management strategies should begin before BMI reaches the high range, particularly among individuals with BMI exceeding 24.00 kg/m2.

Humans↗

PubMed2025

An image-based protein-ligand binding representation learning framework via multi-level flexible dynamics trajectory pre-training.

MOTIVATION: Accurate prediction of protein-ligand binding (PLB) relationships plays a crucial role in drug discovery, which helps identify drugs that modulate the activity of specific targets. Traditional biological assays for measuring PLB relationships are time consuming and costly. In addition, models for predicting PLB relationships have been developed and widely used in drug discovery tasks. However, learning more accurate PLB representations is essential to meet the stringent standards required for drug discovery. RESULTS: We propose an image-based PLB representation learning framework, called ImagePLB, which equips ligand representation learner (LRL) and protein representation learner (PRL) to accept 3D multi-view ligand images and protein graphs as input, respectively, and learns rich interaction information between ligand and protein through a binding representation learner (BRL). Considering the scarcity of protein-ligand pairs, we further propose a multi-level next trajectory prediction (MLNTP) task to pre-train ImagePLB on the 4D flexible dynamics trajectory of 16 972 complexes, including ligand level, protein level, and complex level, to learn information related to trajectories. Besides, by introducing trajectory regularization (TR), we effectively alleviate the problem of high (even almost identical) feature similarity caused by adjacent trajectories. Compared with the current state-of-the-art methods, ImagePLB has achieved competitive improvements on PLB-related prediction tasks, including protein-ligand affinity and efficacy prediction tasks. This study opens the door to the image-based PLB learning paradigm. AVAILABILITY AND IMPLEMENTATION: All data and implementation details of code can be obtained from https://github.com/HongxinXiang/ImagePLB.

Ligands↗

PubMed2025

The proteogenomic landscape of the human kidney and implications for cardio-kidney-metabolic health.

Nearly one-third of the global population is affected by cardio-kidney-metabolic (CKM) diseases; however, the molecular mechanisms underlying CKM diseases are poorly understood. Here we show that tissue proteomics provide critical insights not captured by tissue gene expression or blood proteomics information by performing whole-genome and RNA sequencing and proteomics analysis of human kidney samples (n = 337), and we generated a publicly available database. Via Bayesian co-localization and Mendelian randomization analyses of kidney protein quantitative trait loci and 36 CKM genome-wide association studies, we prioritized 89 proteins for CKM traits. We prioritized relationships that could underlie the interconnectedness of CKM traits and discovered multiple and targetable mechanisms for CKM diseases, including the potential role of kidney angiopoietin-like protein 3 (ANGPTL3) in serum lipid levels and kidney function as well as the role of charged multivesicular body protein 1A in kidney function and hypertension. Notably, we identify pathways with confluence of evidence from genetic loci, tissue gene expression and protein levels for CKM traits. In summary, our large-scale kidney proteomics study uncovers proteins and targetable mechanisms prioritized for CKM diseases.

Humans↗