Background: Diabetic foot ulcers (DFUs) are one of the most popular and severe complications of diabetes. The persistent non-healing of DFUs may eventually contribute to severe complications such as amputation, which presents patients with significant physical and psychological challenges. Fibroblasts are critical cells in wound healing and perform essential roles in all phases of wound healing. In diabetic foot patients, the disruption of fibroblast function exacerbates the non-healing of the wound. This study aimed to summarize the hotspots and evaluate the global research trends on fibroblast-related DFUs through bibliometric analysis.Methods: Scientific publications on the study of fibroblast-related DFUs from January 1, 2000 to April 27, 2022 were retrieved from the Web of Science Core Collection (WoSCC). Biblioshiny software was primarily performed for the visual analysis of the literature, CiteSpace software and VOSviewer software were used to validate the results.Results: A total of 479 articles on fibroblast-related DFUs were retrieved. The most published countries, institutions, journals, and authors in this field were the USA, The Chinese University of Hong Kong, Wound Repair and Regeneration, and Seung-Kyu Han. In addition, keyword co-occurrence networks, historical direct citation networks, thematic map, and the trend topics map summarize the research hotspots and trends in this field.Conclusion: Current studies indicated that research on fibroblast-related DFUs is attracting increasing concern and have clinical implications. The cellular and molecular mechanisms of the DFU pathophysiological process, the molecular mechanisms and therapeutic targets associated with DFUs angiogenesis, and the measures to promote DFUs wound healing are three worthy research hotspots in this field.

Background: The coronavirus disease 2019 (COVID-19) has induced a worldwide epidemiological event with a high infectivity and mortality. However, the predicting biomarkers and their potential mechanism in the progression of COVID-19 are not well known. Objective: The aim of this study is to identify the candidate predictors of COVID-19 and investigate their underlying mechanism. Methods: The retrospective study was conducted to identify the potential laboratory indicators with prognostic values of COVID-19 disease. Then, the prognostic nomogram was constructed to predict the overall survival of COVID-19 patients. Additionally, the scRNA-seq data of BALF and PBMCs from COVID-19 patients were downloaded to investigate the underlying mechanism of the most important prognostic indicators in lungs and peripherals, respectively. Results: In total, 304 hospitalized adult COVID-19 patients in Wuhan Jinyintan Hospital were included in the retrospective study. CEA was the only laboratory indicator with significant difference in the univariate (P < 0.001) and multivariate analysis (P = 0.020). The scRNA-seq data of BALF and PBMCs from COVID-19 patients were downloaded to investigate the underlying mechanism of CEA in lungs and peripherals, respectively. The results revealed the potential roles of CEA were significantly distributed in type II pneumocytes of BALF and developing neutrophils of PBMCs, participating in the progression of COVID-19 by regulating the cell–cell communication. Conclusion: This study identifies the prognostic roles of CEA in COVID-19 patients and implies the potential roles of CEACAM8-CEACAM6 in the progression of COVID-19 by regulating the cell–cell communication of developing neutrophils and type II pneumocyte.

Background: Bladder urothelial carcinoma (BLCA) is a malignancy with a high incidence worldwide. One-third of patients may experience aggressive progression later on, and 70% of patients who have undergone surgical intervention will still suffer from metastasis. Materials and Methods: RNA sequencing profiles of BLCA samples were obtained from The Cancer Genome Atlas (TCGA) database. Differential expression and univariate Cox regression analyses were performed to identify prognosis-related differentially expressed immune genes (DEIGs). Subsequently, a proportional hazards model of DEIGs was then constructed by univariate regression analysis. Differential expression and correlation analyses, CIBERSORT, Single Sample Gene Set Enrichment Analysis (ssGSEA), GSVA were conducted on transcription factors (TFs), immune cells/pathways and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. The regulation network was then constructed. Eventually, ATAC-seq, ChIP-seq, scRNA-seq, and multiple online databases were employed for further validation. Results: A proportional hazards model of 31 DEIGs was constructed and risk score was calculated and proven to be a independent prognostic factor. Then 5 immune genes were characterized to be significantly correlated with bone metastasis, stage and TF expression simultaneously. 4 TFs were identified to be significantly correlated with prognosis and RBP7 expression. 5 immune cells/pathways were revealed to be significantly correlated with RBP7 expression. Only 1 KEGG pathway was identified to be significant in Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA) analyses. The regulatory relationship was then constructed, in which the correlation between EBF1 and RBP7 (R = 0.677, p < 0.001), Th2 cells and RBP7 (R = 0.23, p < 0.001), the oocyte meiosis pathway and RBP7 (R = 0.14, p = 0.042) were the most statistically significant. The results were further confirmed by Assay for Transposase Accessible Chromatin with high-throughput sequencing (ATAC-seq), Chromatin Immunoprecipitation sequencing (ChIP-seq), single-cell RNA sequencing (scRNA-seq), and multiple online databases validation. Conclusions: This study revealed that the EBF1-RBP7 regulatory relationship had potential importance in the bone metastasis in BLCA through Th2 cells and the oocyte meiosis pathway.

With the continuous advancement of materials science, cell biology, and biotechnology, tissue engineering has introduced novel solutions to traditional wound healing approaches, particularly demonstrating significant potential in addressing complex or non-healing wounds. One of the key technologies in this field, dermal scaffolds, serve as wound coverage materials that mimic the structural framework of the dermis. They primarily assume the function of extracellular matrix, providing space for cell attachment, migration, and proliferation, thus supporting cellular growth and regulating multiple biological processes in healing. Tissue engineering utilizes combinations of natural or synthetic scaffolds, seeded cells, or growth factors to induce distinct effects in angiogenesis, extracellular matrix deposition, and functional recovery. Therefore, various bioengineered dermal scaffolds hold significant potential for clinical translation in wound healing. This review outlines various extracellular matrix molecules utilized in the development of dermal scaffolds, emphasizes recent progress in cell- and growth factor-modified scaffolds, and discusses the challenges and future perspectives in this evolving field.

Background: Papillary thyroid cancer (PTC) is the most common thyroid cancer, but current molecular features inadequately stratify its risk. Whether distinct underlying mechanisms can further classify PTC and improve prognostic precision remains unclear. Methods: We integrated single-cell RNA sequencing data (158,577 cells from 11 PTC patients; GEO: GSE184362) with bulk-RNA sequencing data from The Cancer Genome Atlas Thyroid Carcinoma (TCGA-THCA) cohort (501 patients). Multi-omics analyses were employed to elucidate PTC heterogeneity, identify malignant cell differentiation and prognosis-related genes (MCD&PRGs), and construct a novel molecular classification, the Oncogenic Signature Of Papillary Thyroid Carcinoma Classification (OSPTCC). A prognostic risk score was developed, and the classification's prognostic relevance was further explored in an independent institutional cohort using qRT-PCR. Results: Single-cell analysis revealed three malignant cell differentiation states (PTC1-3) and a 34-gene signature (MCD&PRGs). This formed the basis of our Oncogenic Signature Of Papillary Thyroid Carcinoma Classification (OSPTCC), defining three subtypes: Inflammation-associated (IPTCC), BRAF/autophagy-related (BAPTCC), and lipid metabolism-related (LPTCC). These subtypes showed distinct molecular profiles and significantly different progression-free survival (IPTCC poorest, P = 0.044). A 7-gene risk score derived from MCD&PRGs independently predicted prognosis (multivariate HR = 21.511, P < 0.001). qRT-PCR validation in an independent cohort (n = 48) using key markers (DEPTOR, APOE, APOC1) confirmed that OSPTCC-based risk stratification correlated with adverse clinical features, including higher recurrence rates in the high-risk group (P = 0.007). Conclusions: This study introduces OSPTCC, a prognostically significant molecular classification for PTC based on tumor cell differentiation states. The identified subtypes, characterized by distinct biological mechanisms, provide deeper insights into PTC's molecular pathology and offer a framework for improved risk stratification and potential precision therapies.

Emerging studies demonstrate that PIWI-interacting RNAs (piRNAs) participate in the development of cancers. 75 pairs of papillary thyroid carcinoma (PTC) samples and 31 benign thyroid nodule samples were included in this three-phase biomarker identifying study. First, piRNA expression profiles of five pairs of PTC samples were acquired piRNA sequencing. The expression of all upregulated piRNAs were further validated by RT-qPCR. Paired t and nonparametric test were used to evaluate the association between all upregulated piRNAs and clinic stage. The expression levels of key piRNAs were corrected by demographic data to construct a multivariate model to distinguish malignant nodules from benign. Additionally, the intersection between target genes of key piRNAs and differentially expressed genes in The Cancer Genome Atlas (TCGA) PTC samples were used to perform enrichment analysis. Only piR-13643 and piR-21238 were significantly upregulated in PTC and associated with clinic stage. Moreover, both piR-13643 (Area Under Curve (AUC): 0.821) and piR-21238 (AUC: 0.823) showed better performance in distinguishing malignant nodules from benign than currently used biomarkers HBME1 (AUC: 0.590). Based on our findings, piR-13643 and piR-21238 were observed to be significantly upregulated in human PTC. PIWI-interacting RNAs could serve as promising novel biomarkers for accurate detection of PTC.