The role of myeloid differentiation of hematopoietic stem cells in pregnancy immunological tolerance: a systematic review.

The present research aimed to conduct a comprehensive critical analysis of existing literature, focusing on the differentiation of myeloid cells from hematopoietic stem cells within the context of immunological tolerance during pregnancy. A comprehensive systematic review was conducted by searching databases including PubMed, Scopus Biomedicine, EBSCOhost, ScienceDirect, Embase, Cochrane Library, and Web of Science. The focus was on the role of myeloid differentiation from hematopoietic stem cells in modulating immune tolerance, particularly during pregnancy and in certain disease states where they act to suppress the immune response. The quality of the evidence gathered was assessed using the GRADE rating system. Our analysis maintains objectivity and independence from the outcomes presented. The current systematic review offers a synthesis of existing research on the transformation of hematopoietic stem cells into fibroblasts across different tissue types. A thorough search of databases such as PubMed, EBSCOhost, Embase, ScienceDirect, Cochrane Library, and Web of Science was performed in conjunction with a specialist in medical information to identify original research on the derivation of fibroblasts following hematopoietic stem cell transplantation. This search yielded a total of 159 studies, of which 10 met the criteria for inclusion in this review. Reflecting on the constraints of this preliminary review, further in-depth and scientific investigations are warranted to comprehensively assess the impact of varied treatments, with a recommendation for clinicians to proceed with increased circumspection. The myeloid differentiation pathway of hematopoietic stem cells is pivotal in modulating the immune environment during pregnancy, supporting the sustenance of a healthy gestational period. Future research in this domain is expected to advance our understanding of the immunological processes occurring at the maternal-fetal boundary.

Construction and Validation of a MRI­Based Radiomic Nomogram to Predict Overall Survival in Patients with Local Advanced Cervical Cancer: A Multicenter Study.

BACKGROUND: Cervical cancer is the fourth most common cancer among women. Radiomics has emerged as a new approach providing valuable information for cancer management. The aim of this study was to construct a radiomics nomogram to accurately predict survival outcomes in patients with locally advanced cervical cancer. METHODS: This retrospective study enrolled a total of 582 locally advanced cervical cancer patients from three center (training cohort: n = 228; internal validation cohort: n = 98; external validation cohort: n = 256). Radiomic features were extracted from pretreatment MRI images. Least absolute shrinkage and selection operator logistic regression were applied to select radiomic features and calculated the radiomic scores. Univariate and multivariate Cox proportional hazards regression analyses were used to identify the independent prognostic clinic-radiological factors for cervical cancer, which were incorporated into the nomogram. RESULTS: A total of six radiomic features were found to be associated with overall survival (OS) of locally advanced cervical cancer patients. The AUC of radiomic scores in the training cohort was 0.634-0.708 for the training cohort, 0.725-0.762 for internal validation cohort and 0.788-0.881 for the external validation cohort. Age, parametrial invasion, and radiomic score were the independent prognostic indicators for cervical cancer patients (Age: HR=1.041, 95% CI=1.012-1.071, p = 0.006; Parametrial invasion: HR=4.755, 95% CI=1.493-15.144, p = 0.008; HR=2.324, 95% CI=1.050-5.143, p = 0.037). The nomogram model incorporating these factors showed favorable discrimination in predicting the overall survival rates of cervical cancer patients, with the AUC values of 0.809, 0.808, and 0.862 for 1-, 2-, and 3-year predictions. The decision curve analysis (DCA) indicated that the nomogram model achieved the highest clinical net benefit across the entire range of reasonable threshold probabilities. CONCLUSION: The nomogram, incorporating clinicopathological factors and radiomic features derived from MRI images, showed satisfactory discrimination in predicting the OS rates of locally advanced cervical cancer patients.

Transcription factor c-fos induces the development of premature ovarian insufficiency by regulating MALAT1/miR-22-3p/STAT1 network.

BACKGROUND: The current study attempted to investigate the role of transcription factor c-fos in the development of premature ovarian insufficiency (POI) as well as the underlying mechanism involving the MALAT1/miR-22-3p/STAT1 ceRNA network. METHODS: Bioinformatics analysis was performed to extract POI-related microarray dataset for identifying the target genes. Interaction among c-fos, MALAT1, miR-22-3p, and STAT1 was analyzed. An in vivo POI mouse model was prepared followed by injection of sh-c-fos and sh-STAT1 lentiviruses. Besides, an in vitro POI cell model was constructed to study the regulatory roles of c-fos, MALAT1, miR-22-3p, and STAT1. RESULTS: c-fos, MALAT1, and STAT1 were highly expressed in ovarian tissues from POI mice and CTX-induced KGN cells, while miR-22-3p was poorly expressed. c-fos targeted MALAT1 and promoted MALAT1 transcription. MALAT1 competitively bound to miR-22-3p and miR-22-3p could suppress STAT1 expression. Mechanically, c-fos aggravated ovarian function impairment in POI mice and inhibited KGN cell proliferation through regulation of the MALAT1/miR-22-3p/STAT1 regulatory network. CONCLUSION: Our findings highlighted inducing role of the transcription factor c-fos in POI through modulation of the MALAT1/miR-22-3p/STAT1 ceRNA network.