Diagnosing sternal wound infection (SWI) following median sternotomy remains laborious and troublesome, resulting in high mortality rates and great harm to patients. Early intervention and prevention are critical and challenging. This study aimed to develop a simple risk prediction model to identify high-risk populations of SWI and to guide examination programs and intervention strategies.

A retrospective analysis was conducted on the clinical data obtained from 6715 patients who underwent median sternotomy between January 2016 and December 2020. The least absolute shrink and selection operator (LASSO) regression method selected the optimal subset of predictors, and multivariate logistic regression helped screen the significant factors. The nomogram model was built based on all significant factors. Area under the curve (AUC), calibration curve and decision curve analysis (DCA) were used to assess the model's performance.

LASSO regression analysis selected an optimal subset containing nine predictors that were all statistically significant in multivariate logistic regression analysis. Independent risk factors of SWI included female [odds ratio (OR) = 3.405, 95% confidence interval (CI) = 2.535–4.573], chronic obstructive pulmonary disease (OR = 4.679, 95% CI = 2.916–7.508), drinking (OR = 2.025, 95% CI = 1.437–2.855), smoking (OR = 7.059, 95% CI = 5.034–9.898), re-operation (OR = 3.235, 95% CI = 1.087–9.623), heart failure (OR = 1.555, 95% CI = 1.200–2.016) and repeated endotracheal intubation (OR = 1.975, 95% CI = 1.405–2.774). Protective factors included bone wax (OR = 0.674, 95% CI = 0.538–0.843) and chest physiotherapy (OR = 0.446, 95% CI = 0.248–0.802). The AUC of the nomogram was 0.770 (95% CI = 0.745–0.795) with relatively good sensitivity (0.798) and accuracy (0.620), exhibiting moderately good discernment. The model also showed an excellent fitting degree on the calibration curve. Finally, the DCA presented a remarkable net benefit.

A visual and convenient nomogram-based risk calculator built on disease-associated predictors might help clinicians with the early identification of high-risk patients of SWI and timely intervention.

Hypertrophic scarring remains a critical challenge in regenerative medicine because of the limited efficacy of current antifibrotic therapies. Although dermal papilla cells (DPCs) exhibit intrinsic scar-inhibitory potential, their therapeutic utility is constrained by rapid replicative senescence and poor scalability in traditional monolayer cultures, necessitating innovative strategies to enhance cellular functionality and manufacturing feasibility.

A self-feeder layer 3D (SFL-3D) platform was established to reprogram primary human DPCs into rejuvenated three-dimensional DPC (tdDPC) spheroids via autocrine–paracrine signalling activation. tdDPC-derived extracellular vesicles (tdDPC-EVs) were isolated from culture supernatants by differential centrifugation. The antifibrotic effects of tdDPC-EVs were systematically evaluated using human scar fibroblasts through scratch wound healing assays, CCK-8 proliferation assays, and fibrotic marker analysis [Western blotting and immunofluorescence staining for α-smooth muscle actin (α-SMA) and collagen I]. Bioinformatics was used to predict key pathways involved in hypertrophic scar (HS) pathogenesis, whereas gain/loss-of-function studies investigated the miR-26a-5p/CCNE2 regulatory axis. Therapeutic validation was performed in a rabbit ear hypertrophic scar model with histopathological and molecular profiling.

Compared with conventional 3D cultures, the SFL-3D system demonstrated superior proliferative support, enabling stable tdDPC expansion beyond 10 passages while maintaining high viability and enhanced EV biogenesis. miR-26a-5p-enriched tdDPC-EVs attenuated fibrosis through two mechanisms: (1) silencing CCNE2 to block PI3K/AKT-driven collagen overproduction and (2) suppressing α-SMA + myofibroblast differentiation. In the rabbit ear HS model, tdDPC-EV administration reduced the scar elevation index and restored the collagen Ⅰ/Ⅲ ratio to near-physiological levels.

This study positions tdDPC-EVs as a scalable acellular therapy that overcomes the replicative senescence and manufacturing limitations of cellular approaches. The antiscarring efficacy of these EVs, which is mediated by the miR-26a-5p/CCNE2/PI3K/AKT axis, highlights their clinical potential as precision-targeted strategies for hypertrophic scar management. The SFL-3D platform further provides a translatable framework for EV-based regenerative therapeutics.