Weighted gene co-expression network analysis and machine learning identified the lipid metabolism-related gene LGMN as a novel biomarker for keloid.

The aetiology of keloid formation remains unclear, and existing treatment modalities have not definitively established a successful approach. Therefore, it is necessary to identify reliable and novel keloid biomarkers as potential targets for therapeutic interventions. In this study, we performed differential expression analysis and functional enrichment analysis on the keloid related datasets, and found that multiple metabolism-related pathways were associated with keloid formation. Subsequently, the differentially expressed genes (DEGs) were intersected with the results of weighted gene co-expression network analysis (WGCNA) and the lipid metabolism-related genes (LMGs). Then, three learning machine algorithms (SVM-RFE, LASSO and Random Forest) together identified legumain (LGMN) as the most critical LMGs. LGMN was overexpressed in keloid and had a high diagnostic performance. The protein-protein interaction (PPI) network related to LGMN was constructed by GeneMANIA database. Functional analysis of indicated PPI network was involved in multiple immune response-related biological processes. Furthermore, immune infiltration analysis was conducted using the CIBERSORT method. M2-type macrophages were highly infiltrated in keloid tissues and were found to be significantly and positively correlated with LGMN expression. Gene set variation analysis (GSVA) indicated that LGMN may be related to promoting fibroblast proliferation and inhibiting their apoptosis. Moreover, eight potential drug candidates for keloid treatment were predicted by the DSigDB database. Western blot, qRT-PCR and immunohistochemistry staining results confirmed that LGMN was highly expressed in keloid. Collectively, our findings may identify a new biomarker and therapeutic target for keloid and contribute to the understanding of the potential pathogenesis of keloid.

Non-invasive diagnosis of acute kidney injury using Mn-doped carbon dots-based magnetic resonance imaging.

As Gd-based contrast agents suffer from the risk of causing nephrogenic systemic fibrosis, less toxic contrast agents are urgently needed in contrast-enhanced magnetic resonance imaging (CE-MRI) of kidney injury. Herein, we develop a non-invasive diagnosis method for acute kidney injury using CE-MRI based on manganese-doped carbon dots (Mn-CDs). The synthesized Mn-CDs possess an ultrasmall size of 5 nm, good biocompatibility, and a high T1 relaxation rate (10.8 mM-1 s-1), which can produce effective positive enhancement in the kidneys and clearly show the fine structures of the kidneys including the cortex, outer medulla, and inner medulla. In an acute kidney injury model, Mn-CDs-based CE-MRI can not only accurately and intuitively reveal the site of kidney injury consistent with the pathological analysis, but also reflect the functional changes in the injured kidney. Collectively, our study provides a new strategy for the non-invasive diagnosis of acute kidney injury using CE-MRI based on Mn-CDs.

Two-dimensional nanovermiculite and polycaprolactone electrospun fibers composite scaffolds promoting diabetic wound healing.

BACKGROUND: Promoting diabetic wound healing is still a challenge, and angiogenesis is believed to be essential for diabetic wound healing. Vermiculite is a natural clay material that is very easy to obtain and exhibits excellent properties of releasing bioactive ions, buffering pH, adsorption, and heat insulation. However, there are still many unsolved difficulties in obtaining two-dimensional vermiculite and using it in the biomedical field in a suitable form. RESULTS: In this study, we present a versatile organic-inorganic composite scaffold, which was constructed by embedding two-dimensional vermiculite nanosheets in polycaprolactone electrospun fibers, for enhancing angiogenesis through activation of the HIF-1α signaling pathway and promoting diabetic wound healing both in vitro and in vivo. CONCLUSIONS: Together, the rational-designed polycaprolactone electrospun fibers-based composite scaffolds integrated with two-dimensional vermiculite nanosheets could significantly improve neo-vascularization, re-epithelialization, and collagen formation in the diabetic wound bed, thus promoting diabetic wound healing. This study provides a new strategy for constructing bioactive materials for highly efficient diabetic wound healing.

Reducing relapse and accelerating osteogenesis in rapid maxillary expansion using an injectable mesoporous bioactive glass/fibrin glue composite hydrogel.

Rapid maxillary expansion (RME), as a common treatment for craniomaxillofacial deformity, faces the challenge of high relapse rates and unsatisfactory therapeutic effects. In this study, a standardized Sprague-Dawley (SD) rat RME model was first established with a modified expander as well as retainer design and optimized anterior maxillary expanding force of 100 g which exerted the most synchronized mobility of mid-palatal suture and incisors. Via the standardized model, the high relapse rate was proven to be attributed to insufficient osteogenesis in expanded suture, requiring long-term retainer wearing in clinical situations. To reduce the relapse rate, mesoporous bioactive glass/fibrin glue (MBG/FG) composite hydrogels were developed for an in situ minimal invasive injection that enhance osteogenesis in the expanded palate. The component of 1 wt% MBG was adopted for enhanced mechanical strength, matched degradation rate and ion dissolution, excellent in vitro biocompatibility and osteoinductivity. Effects of 1%MBG/FG composite hydrogel on osteogenesis in expanded mid-palatal sutures with/without retention were evaluated in the standardized model. The results demonstrated that injection of 1%MBG/FG composite hydrogel significantly promoted bone formation within the expanded mid-palatal suture, inhibited osteoclastogenesis and benefited the balance of bone remodeling towards osteogenesis. Combination of retainer and injectable biomaterial was demonstrated as a promising treatment to reduce relapse rate and enhance osteogenesis after RME. The model establishment and the composite hydrogel development in this article might provide new insight to other craniomaxillofacial deformity treatment and design of bone-repairing biomaterials with higher regenerative efficiency.

Identification and validation of a TTN-associated immune prognostic model for skin cutaneous melanoma.

TTN is the most commonly mutated gene in skin cutaneous melanoma (SKCM). Tumor mutational burden (TMB) can generate new antigens that regulate the recognition of T cells, which will significantly affect the prognosis of patients. The TTN gene has a long coding sequence and a high number of mutant sites, which allows SKCM patients to produce higher TMB and may influence the immune response. It has been found that the overall survival (OS) of SKCM patients with TTN mutation was significantly higher than that of wild-type patients. However, the effect of TTN mutation on the immune microenvironment of SKCM has not been fully investigated. Here, we systematically explored the relationship and potential mechanisms between TTN mutation status and the immune response. We first revealed that TTN mutated SKCM were significantly associated with four immune-related biological processes. Next, 115 immune genes differentially expressed between TTN mutation and wild-type SKCM patients were found to significantly affect the OS of SKCM patients. Then, we screened four immune-related genes (CXCL9, PSMB9, CD274, and FCGR2A) using LASSO regression analysis and constructed a TTN mutation-associated immune prognostic model (TM-IPM) to distinguish the SKCM patients with a high or low risk of poor prognosis, independent of multiple clinical characteristics. SKCM in the low-risk group highly expressed a large number of immune-related genes, and functional enrichment analysis of these genes showed that this group was involved in multiple immune processes and pathways. Furthermore, the nomogram constructed by TM-IPM with other clinicopathological parameters can provide a predictive tool for clinicians. Moreover, we found that CD8+ T cells were significantly enriched in the low-risk group. The expression level of immune checkpoints was higher in the low-risk group than in the high-risk group. Additionally, the response to chemotherapeutic agents was higher in the low-risk group than in the high-risk group, which may be related to the long survival in the low-risk group. Collectively, we constructed and validated a TM-IPM using four immune-related genes and analyzed the potential mechanisms of TM-IPM to predict patient prognosis and response to immunotherapy from an immunological perspective.