Chunming Lyu

Background: Profound pharmacokinetic variability complicates individualized teicoplanin therapy in critically ill patients with bloodstream infection. We aimed to develop and externally validate an interpretable machine learning (ML) model for predicting teicoplanin plasma concentrations in this population. Methods: This retrospective two-center real-world study included 260 intensive care unit patients from one center as the modeling cohort (randomly split 8:2 into training and internal test sets) and 91 patients from an independent center as the external validation cohort. Ten ML and deep learning algorithms were constructed using demographic, clinical, and laboratory variables. The optimal model was interpreted via Shapley additive explanations (SHAP). Results: The extreme gradient boosting (XGBoost) model achieved the most favorable point estimates. On the internal test set (n = 52): the model yielded an R ² of 0.73 (95% CI 0.56–0.81), RMSE of 3.22 (95% CI 2.62–3.77), MAE of 2.52 (95% CI 1.98–3.10), and ±30% prediction accuracy (P30%) of 78.8% (95% CI 67.3–88.5). On the external validation cohort (n = 91), it achieved an R ² of 0.76 (95% CI 0.69–0.80), RMSE of 3.61 (95% CI 3.08–4.14), MAE of 2.89 (95% CI 2.48–3.35), and P30% of 69.2% (95% CI 59.3–78.0). After Holm–Bonferroni correction, paired bootstrap comparisons showed XGBoost significantly outperformed 5 of 9 comparator algorithms in the internal test set and 7 of 9 in the external cohort, with performance comparable to several other tree-based ensemble methods. SHAP analysis identified daily dose, hemodialysis, and mechanical ventilation as features positively associated with predicted teicoplanin concentrations. Conclusion: This internally and externally validated interpretable XGBoost model delivers consistent cross-cohort performance, and serves as a dose-anchored adjunct to conventional therapeutic drug monitoring, providing a preliminary methodological foundation for exploring individualized teicoplanin dosing strategies.

Prosthetic loosening represents a catastrophic postoperative complication in artificial joint replacement, resulting in severe patient morbidity and substantial healthcare costs. This investigation aimed to develop a novel strategy for preventing prosthetic loosening. Two-dimensional MXene V₂C nanosheets were synthesized and subsequently immobilized onto three-dimensional porous sulfonated polyetheretherketone (SPEEK) surfaces with polydopamine (PDA) to form V₂C-PDA@SPEEK (Abbrev. V₂C-PS). The biocompatibility was systematically evaluated using rat bone marrow mesenchymal stem cells (rBMSCs) and murine models. The osteogenic differentiation potential of V₂C-PS was assessed through real-time PCR analysis, Alkaline phosphatase (ALP) staining, and Alizarin Red staining. The in vivo osteogenic capacity of V₂C-PS surrounding the implant material was evaluated in rat femoral models using micro-CT analysis, biomechanical pull-out testing, sequential fluorescent labeling of newly formed bone, and Van Gieson staining. The molecular mechanisms underlying V₂C-PS -mediated osteogenic differentiation of rBMSCs were investigated both in vitro and in vivo using chemical inhibitors, β-catenin shRNA lentiviral silencing, and β-catenin mRNA lentiviral overexpression. The results demonstrated that V₂C-PS exhibited excellent biocompatibility. Quantitative analysis revealed substantial upregulation (p < 0.05) of critical osteogenic markers, including RUNX2 (4.4-fold), COL-1 (5.7-fold), OCN (3.3-fold), BMP-2 (4.4-fold), OPN (3.1-fold), BSP (3.3-fold), ON (4.3-fold), and OSX (2.83-fold), in the 25V₂C-PS treatment group compared to PS group. The bone parameters were also remarkably enhanced in the 25V₂C-PS group (BMD increased by 241 %, bone-implant contact by 159 %, BV/TV by 225 %, Tb.N by 281 %, Tb.Th by 214 %, maximum pull-out force by 250 %, and Tp.Sp decreased by 33 %). Furthermore, V₂C-PS were found to enhance rBMSC osteogenic differentiation through activation of the Wnt/β-catenin signaling pathway. This study presents a promising approach for preventing orthopedic prosthetic loosening and demonstrates significant potential for clinical translation.

DFO-PS joint material enhanced bone growth via macrophage regulation and stem cell control, improving trabecular thickness and fixation strength with biomineralization potential.

Hypertrophic scars (HSs) develop due to excessive collagen deposition and abnormal fibroblast proliferation during wound healing, significantly impacting patient quality of life. Three dosages of GA ointments were administered to rabbit ear HS models to investigate the potential efficacy and mechanism of gallic acid (GA) on HS. Daily application of ointment was performed on the matrix group, the GA ointment groups, and the silicone gel group for 28 days. (No drug treatment was performed on the skin and model groups as a blank group and vehicle group, and silicone gel ointment was topically administered to the silicone gel group as a positive control group.) Scar specimens were collected for histopathology analysis, RNA sequencing analysis, real-time quantitative polymerase chain reaction, and Western blot analysis at the first, second, and fourth weeks after the treatment. Low-dose and medium-dose GA effectively suppressed HS formation and markedly decreased fibroblast infiltration levels and scar thickness. Moreover, decreased expression of TRPC3 mRNA and TGF-β1, p-Smad2/3, and Smad2/3 protein was observed in the low- and medium-dose GA groups and the silicone gel group. This study provides evidence for the efficacy of GA in treating HS and sheds light on its potential underlying pharmacological mechanisms.

Hypertrophic scar (HS) is a typical pathological response during skin injury, which can lead to pain, itching, and contracture in patients and even affect their physical and mental health. The complexity of the wound healing process leads to the formation of HS affected by many factors. Several treatments are available for HS, whereas some have more adverse reactions and can even cause new injuries with exacerbated scarring. Traditional Chinese Medicine (TCM) has a rich source, and most botanical drugs have few side effects, providing new ideas and methods for treating HS. This paper reviews the formation process of HS, the therapeutic strategy for HS, the research progress of TCM with its relevant mechanisms in the treatment of HS, and the related new drug delivery system of TCM, aiming to provide ideas for further research of botanical compounds in the treatment of HS, to promote the discovery of more efficient botanical candidates for the clinical treatment of HS, to accelerate the development of the new drug delivery system and the final clinical application, and at the same time, to promote the research on the anti-HS mechanism of multiherbal preparations (Fufang), to continuously improve the quality control and safety and effectiveness of anti-HS botanical drugs in clinical application.