Formononetin attenuates psoriasiform inflammation by regulating interferon signaling pathway.

BACKGROUND: Psoriasis is a long-lasting, inflammatory, continuous illness caused through T cells and characterized mainly by abnormal growth and division of keratinocytes. Currently, corticosteroids are the preferred option. However, prolonged use of traditional topical medication can lead to adverse reactions and relapse, presenting a significant therapeutic obstacle. Improved alternative treatment options are urgently required. Formononetin (FMN) is a representative component of isoflavones in Huangqi (HQ) [Astragalus membranaceus (Fisch.) Bge.]. It possesses properties that reduce inflammation, combat oxidation, inhibit tumor growth, and mimic estrogen. Although FMN has been shown to ameliorate skin barrier devastation via regulating keratinocyte apoptosis and proliferation, there are no reports of its effectiveness in treating psoriasis. OBJECTIVE: Through transcriptomics clues and experimental investigation, we aimed to elucidate the fundamental mechanisms underlying FMN's action on psoriasis. MATERIALS AND METHODS: Cell viability was examined using CCK8 assay in this study. The results of analysis of differentially expressed genes (DEGs) between FMN-treated HaCaT cells and normal HaCaT cells using RNA-sequencing (RNA-seq) were presented on volcano plots and heatmap. Enrichment analysis was conducted on DEGs using Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO), and results were validated through RT-qPCR verification. After 12 days of FMN treatment in psoriasis mouse model, we gauged the PASI score and epidermis thickness. A variety of techniques were used to assess FMN's effectiveness on inhibiting inflammation and proliferation related to psoriasis, including RT-qPCR, HE staining, western blot, and immunohistochemistry (IHC). RESULTS: The findings indicated that FMN could suppress the growth of HaCaT cells using CCK8 assay (with IC50 = 40.64 uM) and 20 uM FMN could reduce the level of tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6) to the greatest extent. FMN-treated HaCaT cells exhibited 985 up-regulated and 855 down-regulated DEGs compared to normal HaCaT cells. GO analysis revealed that DEGs were linked to interferon (IFN) signaling pathway. Furthermore, FMN improved pathological features, which encompassed decreased erythema, scale, and thickness scores of skin lesions in psoriasis mouse model. In vivo experiments confirmed that FMN down-regulated expression of IFN-α, IFN-ß, IFN-γ, decreased secretion of TNF-α and IL-17 inflammatory factors, inhibited expression of IFN-related chemokines included Cxcl9, Cxcl10, Cxcl11 and Cxcr3 and reduced expression of transcription factors p-STAT1, p-STAT3 and IFN regulatory factor 1 (IRF1) in the imiquimod (IMQ) group. CONCLUSIONS: In summary, these results suggested that FMN played an anti-inflammatory and anti-proliferative role in alleviating psoriasis by inhibiting IFN signaling pathway, and FMN could be used as a potential therapeutic agent.

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.

Sheng-ji Hua-yu ointment ameliorates cutaneous wound healing in diabetes via up-regulating CCN1.

ETHNOPHARMACOLOGICAL RELEVANCE: Diabetic ulcers (DUs) are one of the most severe complications of diabetes, and efficacious therapeutic means are currently lacking. Sheng-ji Hua-yu (SJHY) ointment is a classical Chinese traditional prescription that can significantly attenuate DU defects, but the specific mechanism remains to be fully elucidated. AIM OF THE STUDY: In order to verify the underlying mechanism of SJHY ointment in accelerating the closure of DUs. MATERIALS AND METHODS: Modular pharmacology and molecular docking were utilized to predict the therapeutic targets of SJHY ointment against DUs. Male db/db diabetic mice and HaCaT cell models induced by methylglyoxal were used to validate the findings. RESULTS: CCN1 was proven to be the core target of SJHY ointment involved in DUs treatment. CCN1 up-regulated by SJHY treatment (0.5 g/cm2/day) at the mRNA and protein levels was detected on Day9 after wounding. With CCN1 knockdown, accelerated cell proliferation, migration, and anti-inflammatory effect of SJHY treatment (10 mg/L) were reversed. CONCLUSIONS: SJHY ointment ameliorates cutaneous wound healing by up-regulating CCN1.

Classification and biomarker gene selection of pyroptosis-related gene expression in psoriasis using a random forest algorithm.

Background: Psoriasis is a chronic and immune-mediated skin disorder that currently has no cure. Pyroptosis has been proved to be involved in the pathogenesis and progression of psoriasis. However, the role pyroptosis plays in psoriasis remains elusive. Methods: RNA-sequencing data of psoriasis patients were obtained from the Gene Expression Omnibus (GEO) database, and differentially expressed pyroptosis-related genes (PRGs) between psoriasis patients and normal individuals were obtained. A principal component analysis (PCA) was conducted to determine whether PRGs could be used to distinguish the samples. PRG and immune cell correlation was also investigated. Subsequently, a novel diagnostic model comprising PRGs for psoriasis was constructed using a random forest algorithm (ntree = 400). A receiver operating characteristic (ROC) analysis was used to evaluate the classification performance through both internal and external validation. Consensus clustering analysis was used to investigate whether there was a difference in biological functions within PRG-based subtypes. Finally, the expression of the kernel PRGs were validated in vivo by qRT-PCR. Results: We identified a total of 39 PRGs, which could distinguish psoriasis samples from normal samples. The process of T cell CD4 memory activated and mast cells resting were correlated with PRGs. Ten PRGs, IL-1ß, AIM2, CASP5, DHX9, CASP4, CYCS, CASP1, GZMB, CHMP2B, and CASP8, were subsequently screened using a random forest diagnostic model. ROC analysis revealed that our model has good diagnostic performance in both internal validation (area under the curve [AUC] = 0.930 [95% CI 0.877-0.984]) and external validation (mean AUC = 0.852). PRG subtypes indicated differences in metabolic processes and the MAPK signaling pathway. Finally, the qRT-PCR results demonstrated the apparent dysregulation of PRGs in psoriasis, especially AIM2 and GZMB. Conclusion: Pyroptosis may play a crucial role in psoriasis and could provide new insights into the diagnosis and underlying mechanisms of psoriasis.

Patient-driven discovery of CCN1 to rescue cutaneous wound healing in diabetes via the intracellular EIF3A/CCN1/ATG7 signaling by nanoparticle-enabled delivery.

Diabetic ulcers (DUs), a devastating complication of diabetes, are intractable for limited effective interventions in clinic. Based on the clinical samples and bioinformatic analysis, we found lower level of CCN1 in DU individuals. Considering the accelerated proliferation effect in keratinocytes, we propose the therapeutic role of CCN1 supplementation in DU microenvironment. To address the challenge of rapid degradation of CCN1 in protease-rich diabetic healing condition, we fabricated a nanoformulation of CCN1 (CCN1-NP), which protected CCN1 from degradation and significantly raised CCN1 intracellular delivery efficiency to 6.2-fold. The results showed that the intracellular CCN1 exhibited a greater anti-inflammatory and proliferative/migratory activities once the extracellular signal of CCN1 was blocked in vitro. The nanoformulation unveils a new mechanism that CCN1 delivered into cells interacted with Eukaryotic translation initiation factor 3 subunit A (EIF3A) to downregulate autophagy-related 7 (ATG7). Furthermore, topical application of CCN1-NP had profound curative effects on delayed wound healing in diabetes both in vitro and in vivo. Our results illustrate a novel mechanism of intracellular EIF3A/CCN1/ATG7 axis triggered by nanoformulation and the therapeutic potential of CCN1-NP for DU management.

Gene set enrichment analysis and ingenuity pathway analysis to identify biomarkers in Sheng-ji Hua-yu formula treated diabetic ulcers.

ETHNOPHARMACOLOGICAL RELEVANCE: Sheng-ji Hua-yu (SJHY) formula is a Chinese herbal prescription for diabetic ulcers (DUs) treatment, which can accelerate wound reconstruction and shorten the healing time. However, its mechanism role maintains unclear. AIM OF THE STUDY: To elucidate the molecular mechanisms of SJHY application on DUs. MATERIALS AND METHODS: To begin with, transcriptome sequencing was adopted to identified differentially expression mRNAs among normal ulcers, DUs, and DUs + SJHY treatment in vivo. Liquid chromatography-tandem mass spectrometry was applied for the quality control of SJHY formula. GO and KEGG enrichment analysis were used to identify the mechanisms underlying the therapeutic effect of SJHY formula, and then gene set enrichment analysis and ingenuity pathway analysis were conducted for functional analysis. Further, qPCR detection was performed in vivo for validation. RESULTS: SJHY administration could regulate the glucose metabolic process, AMPK and HIF-1 pathway to accelerate healing processes of DUs. Besides, CRHR1, SHH, and GAL were identified as the critical targets, and SLC6A3, GRP, FGF23, and CYP27B1 were considered as the upstream genes of SJHY treatment. Combined with animal experiments, the prediction results were validated in DUs mice model. CONCLUSIONS: This study used modular pharmacology analysis to identify the biomarkers of SJHY formula and provide the potential therapeutic targets for DUs treatment as well.

The Identification of the Biomarkers of Sheng-Ji Hua-Yu Formula Treated Diabetic Wound Healing Using Modular Pharmacology.

Sheng-Ji Hua-Yu (SJHY) formula has been proved to reduce the severity of diabetic wound healing without significant adverse events in our previous clinical trials. However, based on multi-target characteristics, the regulatory network among herbs, ingredients, and hub genes remains to be elucidated. The current study aims to identify the biomarkers of the SJHY formula for the treatment of diabetic wound healing. First, a network of components and targets for the SJHY formula was constructed using network pharmacology. Second, the ClusterONE algorithm was used to build a modular network and identify hub genes along with kernel pathways. Third, we verified the kernel targets by molecular docking to select hub genes. In addition, the biomarkers of the SJHY formula were validated by animal experiments in a diabetic wound healing mice model. The results revealed that the SJHY formula downregulated the mRNA expression of Cxcr4, Oprd1, and Htr2a, while upregulated Adrb2, Drd, Drd4, and Hrh1. Besides, the SJHY formula upregulated the kernel pathways, neuroactive ligand-receptor interaction, and cAMP signaling pathway in the skin tissue homogenate of the diabetic wound healing mice model. In summary, this study identified the potential targets and kernel pathways, providing additional evidence for the clinical application of the SJHY formula for the treatment of diabetic wound healing.

A Novel Evaluation System of Psoriasis Curative Effect Based on Bayesian Maximum Entropy Weight Self-Learning and Extended Set Pair Analysis.

BACKGROUND: Psoriasis is a complex skin disease and difficult to evaluate, and this study aimed to provide an objective and systematic approach for evaluating the efficacy of psoriasis. METHODS: We sought to construct a Bayesian network from sixteen indicators in four aspects of psoriasis (skin lesion conditions, laboratory indexes, quality of life, and accompanying symptoms) and obtained weights of each index by combining the analytic hierarchy process with maximum entropy self-learning. Furthermore, we adopted stability analysis to calculate the minimum sample size of the system. The extended set pair analysis was utilized to evaluate the efficacy based on improved weights, which overcomes the limitation of set pair analysis (unable to evaluate the efficacy with uncertain grades and thresholds). RESULTS: A total of 100 psoriasis vulgaris patients were included to evaluate the curative effect by the system. We obtained the weights of each index and the Euclidean distance for efficacy evaluation of 100 patients. The sensitivity analysis proved that the results had no significant change with the variation of single patient's indexes, which indicated that our results were stable to assess the effectiveness. CONCLUSIONS: We provided an available method of comprehensive effective evaluation of various indicators of psoriasis and based on both subjective and objective weights.

An Efficacy Predictive Method for Diabetic Ulcers Based on Higher-Order Markov Chain-Set Pair Analysis.

BACKGROUND: Clinical comprehensive decision-making of diabetic ulcers includes curative effect evaluation and curative effect prediction. Nevertheless, there are few studies on the prediction of diabetic ulcers. METHODS: Set pair analysis (SPA) was used to assess the curative effect evaluation, and therapeutic effect was evaluated by connection degree (CD). The higher-order Markov chain-SPA curative effect prediction model was established to predict the future curative effect development. The predicted results with higher-order Markov chain-SPA and traditional first-order Markov-SPA model were compared with the actual results of the patients to verify the effectiveness of prediction. RESULTS: The connection degree of index levels I and II of 15 patients with diabetic ulcers after traditional Chinese medicine (TCM) treatment increased with time, while that of index levels IV and V decreased, indicating that the curative effect tends to improve. The higher-order Markov chain-SPA model was used to predict the curative effect. The results showed that the relative errors were fewer than the traditional first-order Markov-SPA model. CONCLUSIONS: The present study suggests that a method of SPA combined with higher-order Markov-SPA is relatively effective and can be applied to the clinical prediction of diabetic ulcers, which has higher accuracy than traditional first-order curative effect prediction model.