The role of neutrophils in diabetic ulcers and targeting therapeutic strategies.

Diabetic ulcers (DUs) are a common complication of diabetes with high morbidity, poor prognosis, and a high socio-economic burden. The main pathological manifestations of DUs are chronic inflammation, impaired re-epithelialization, and impaired angiogenesis. During the inflammatory phase, neutrophils are one of the main DU cell types and act by releasing neutrophil extracellular traps (NETs), leading to poor healing in DUs. This review summarizes the role of neutrophils in the pathology and treatment of DUs, with a view to potential novel therapies and therapeutic targets.

Clinical-mediated discovery of pyroptosis in CD8+ T cell and NK cell reveals melanoma heterogeneity by single-cell and bulk sequence.

Histologically, melanoma tissues had fewer positive cells percentage of pyroptosis-related genes (PRGs), GZMA, GSDMB, NLRP1, IL18, and CHMP4A in epidermal than in normal skin. Pyroptosis, a new frontier in cancer, affects the tumor microenvironment and tumor immunotherapy. Nevertheless, the role of pyroptosis remains controversial, which reason is partly due to the heterogeneity of the cellular composition in melanoma. In this study, we present a comprehensive analysis of the single-cell transcriptome landscape of pyroptosis in melanoma specimens. Our findings reveal dysregulation in the expression of PRGs, particularly in immune cells, such as CD8+ cells (representing CD8+ T cells) and CD57+ cells (representing NK cells). Additionally, the immunohistochemical and multiplex immunofluorescence staining experiments results further confirmed GZMA+ cells and GSDMB+ cells were predominantly expressed in immune cells, especially in CD8 + T cells and NK cells. Melanoma specimens secreted a minimal presence of GZMA+ merged CD8+ T cells (0.11%) and GSDMB+ merged CD57+ cells (0.08%), compared to the control groups exhibiting proportions of 4.02% and 0.62%, respectively. The aforementioned findings indicate that a reduced presence of immune cells within tumors may play a role in diminishing the ability of pyroptosis, consequently posing a potential risk to the anti-melanoma properties. To quantify clinical relevance, we constructed a prognostic risk model and an individualized nomogram (C-index=0.58, P = 0.002), suggesting a potential role of PRGs in malignant melanoma prevention. In conclusion, our integrated single-cell and bulk RNA-seq analysis identified immune cell clusters and immune gene modules with experiment validation, contributing to our better understanding of pyroptosis in melanoma.

Metabolism-related biomarkers, molecular classification, and immune infiltration in diabetic ulcers with validation.

Diabetes mellitus (DM) can lead to diabetic ulcers (DUs), which are the most severe complications. Due to the need for more accurate patient classifications and diagnostic models, treatment and management strategies for DU patients still need improvement. The difficulty of diabetic wound healing is caused closely related to biological metabolism and immune chemotaxis reaction dysfunction. Therefore, the purpose of our study is to identify metabolic biomarkers in patients with DU and construct a molecular subtype-specific prognostic model that is highly accurate and robust. RNA-sequencing data for DU samples were obtained from the Gene Expression Omnibus (GEO) database. DU patients and normal individuals were compared regarding the expression of metabolism-related genes (MRGs). Then, a novel diagnostic model based on MRGs was constructed with the random forest algorithm, and classification performance was evaluated utilizing receiver operating characteristic (ROC) analysis. The biological functions of MRGs-based subtypes were investigated using consensus clustering analysis. A principal component analysis (PCA) was conducted to determine whether MRGs could distinguish between subtypes. We also examined the correlation between MRGs and immune infiltration. Lastly, qRT-PCR was utilized to validate the expression of the hub MRGs with clinical validations and animal experimentations. Firstly, 8 metabolism-related hub genes were obtained by random forest algorithm, which could distinguish the DUs from normal samples validated by the ROC curves. Secondly, DU samples could be consensus clustered into three molecular classifications by MRGs, verified by PCA analysis. Thirdly, associations between MRGs and immune infiltration were confirmed, with LYN and Type 1 helper cell significantly positively correlated; RHOH and TGF-ß family remarkably negatively correlated. Finally, clinical validations and animal experiments of DU skin tissue samples showed that the expressions of metabolic hub genes in the DU groups were considerably upregulated, including GLDC, GALNT6, RHOH, XDH, MMP12, KLK6, LYN, and CFB. The current study proposed an auxiliary MRGs-based DUs model while proposing MRGs-based molecular clustering and confirmed the association with immune infiltration, facilitating the diagnosis and management of DU patients and designing individualized treatment plans.

A genetic algorithm for the optimization of the thermoinduction protocol for high-level production of recombinant human-like collagen from Escherichia coli.

Production of recombinant human-like collagen (RHLC) by thermoinduction of recombinant Escherichia coli BL 21 during high cell density cultivation was investigated in a 30 L bioreactor. The effects of induction temperature (T), pH, and carbon-to-nitrogen molar ratio of the nutrient medium (C/N) were examined. The optimal thermoinduction protocol for RHLC production was determined by using a model coupling genetic algorithm and artificial neural networks. The optimal operating conditions were as follows: maintenance of induction temperature at 42°C for 3 H and then at 39.4°C until the end, induction pH at 7.03, and C/N at 4.8 (mol/mol). The theoretical maximum concentration of RHLC was 12.5 g/L, whereas the experimental value was 12.1 g/L under the optimal induction conditions.

[Extraction characteristics of sequential accelerated solvent extraction for polycyclic aromatic hydrocarbons in environmental mediums].

Polycyclic aromatic hydrocarbons (PAHs) in two soils, two sediments and an shale from the Pearl River Delta were extracted by sequential accelerated solvent extraction (ASE) with each of four different organic solvents for three times. PAHs in the first extract accounts for more than half of their total contents, and toluene displays the best extraction performance among the four employed solvents. For a given sample the source diagnostic ratios of PAHs in sequential ASE with each solvent are very similar, suggesting the validity of those ratios in source judgement by different extraction methods.