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Background Linezolid-induced thrombocytopenia is the main factor restricting the clinical application of linezolid. Objectives To investigate the relationship between PNU-14230 concentration and linezolid-induced thrombocytopenia and further develop and validate a risk model for predicting linezolid-induced thrombocytopenia. Methods A regression model was constructed to predict the occurrence of linezolid-induced thrombocytopenia, and further externally validated. The predictive performance was evaluated by receiver operating characteristic curve and Hosmer–Lemeshow test. Linezolid C min and PNU-142300 concentrations were compared for different kidney function groups. The Kaplan–Meier method was used to estimate the difference in cumulative incidence of linezolid-induced thrombocytopenia among different kidney function patients. Results In the derivation (n = 221) and validation (n = 158) cohorts, 28.5% and 24.1% of critically ill patients developed linezolid-induced thrombocytopenia. Logistic regression analysis indicated that the independent risk factors were linezolid C min, PNU-142300 concentration, baseline platelet count, renal insufficiency (RI) and continuous venovenous haemofiltration (CVVH). The AUC for the risk model was 0.901, and the model was good (P  = 0.633). The model also showed good discrimination (AUC 0.870) and calibration (P  = 0.282) in the external validation cohort. Compared with normal kidney function patients, patients with RI and CVVH had higher linezolid C min and PNU-142300 concentrations (P < 0.001) and higher cumulative incidence of linezolid-induced thrombocytopenia (P < 0.001). Conclusions PNU142300 concentration, as well as linezolid C min, might identify patients at risk of linezolid-induced thrombocytopenia. The risk prediction model had good predictive performance for linezolid-induced thrombocytopenia development. Concentrations of linezolid and PNU-142300 accumulated in patients with RI and CVVH. [ABSTRACT FROM AUTHOR]

Increased inflammatory responses and oxidative stress at the wound site following skin trauma impair healing. Furthermore, skin scarring places fibroblasts under severe mechanical stress and aggravates pathological fibrosis. A novel liposomal composite hydrogel is engineered for wound microenvironment remodeling, incorporating dual-loaded liposomes into gelatin methacrylate to create a nanocomposite hydrogel. Notably, tetrahydrocurcumin (THC) and hepatocyte growth factor (HGF) are encapsulated in the hydrophobic and hydrophilic layers of liposomes, respectively. The composite hydrogel maintains porous nanoarchitecture, demonstrating sustainable THC and HGF release and enhanced mechanical properties and biocompatibility. This system effectively promotes cell proliferation and angiogenesis and attenuates apoptosis. It decreases the expression of the inflammatory factors by inhibiting the high-mobility group box /receptor for advanced glycation end product/NF-κB (HMGB1/RAGE/NF-κB)pathway and increases macrophage polarization from M1 to M2 in vitro, effectively controlling inflammatory responses. It exhibits remarkable antioxidant properties by scavenging excess reactive oxygen species and free radicals. Most importantly, it effectively prevents scar formation by restraining the transforming growth factor beta (TGF-β)/Smads pathway that downregulates associated fibrotic factors. It demonstrates strong therapeutic effects against inflammation and fibrosis in a rat skin wound model with biosafety, advancing the development of innovative hydrogel-based therapeutic delivery strategies for clinical scarless wound therapy., (© 2024 Wiley‐VCH GmbH.)

Objective: To evaluate the predictive value and to verify the clinical effect of JPKD-vancomycin for the trough concentration of vancomycin in patients with augmented renal clearance (ARC), and to provide a reference for clinical individualized drug therapy., Methods: A retrospective analysis was conducted. The clinical data of 48 adult patients with ARC using vancomycin and monitoring steady-state trough concentration of vancomycin admitted to Suzhou Hospital Affiliated to Nanjing Medical University from July 2013 to July 2017 were collected. A combination of classical Vancomycin Calculator software and JPKD-vancomycin software was used. Based on the individual conditions of patients [gender, age, height, weight, serum creatinine (SCr), disease status], Vancomycin Calculator software was used to obtain the recommended regimen and its steady-state trough concentration, and then JPKD-vancomycin software was used to predict the steady-state trough concentration of initial regimen. If the regimen was adjusted during the treatment, JPKD-vancomycin software was used to predict the steady-state trough concentration of the adjusted regimen. The measured values of steady-state trough concentration were recorded. The weight deviation between predicted concentration and measured concentration (WRES) was calculated. WRES < 30% was considered as good prediction, and the predictive value of JPKD-vancomycin software was evaluated for vancomycin trough concentration., Results: Forty-eight patients with ARC were enrolled, of whom 24 patients had adjusted the dosing regimen during the treatment. The initial concentration of blood samples was 48, after adjusting the dosage regimen, 24 blood samples were collected. The initial and adjusted daily dose of vancomycin was (2 000±500) mg/d and (2 500±600) mg/d, respectively, and the initial trough concentrations and adjusted trough concentrations was (8.4±7.3) mg/L and (9.1±4.3) mg/L, respectively. Only 14.6% and 25.0% of initial and adjusted trough concentrations reached the target range (10-20 mg/L) without significant difference (P > 0.05). The WRES value of adjusted trough concentrations predicted by JPKD-vancomycin software was significantly lower than that of initial regimen [10.6% (3.0%, 16.4%) vs. 14.3% (10.5%, 38.2%), P < 0.05], and the percentage of WRES < 30% also tended to increase [95.8% (23/24) vs. 70.8% (34/48), P < 0.05]. The well predictive rate of JPKD-vancomycin software for vancomycin trough concentration was 79.2% (57/72), but there were 15 patients with WRES > 30%., Conclusions: JPKD-vancomycin software has good predictive value for the vancomycin trough concentration of ARC patients, especially for the trough concentration after adjusting the treatment regimen. JPKD-vancomycin can provide a reference for the design of clinical individualized application of vancomycin.