Multifaceted Characterization of Human Embryonic Stem Cell-Derived Mesenchymal Stem/Stromal Cells Revealed Amelioration of Acute Liver Injury in NOD-SCID Mice.

Human embryonic stem cells (hESCs) are advantaged sources for large-scale and homogeneous mesenchymal stem/stromal cells (MSCs) generation. However, due to the limitations in high-efficiency procedures for hESC-MSCs induction, the systematic and detailed information of mesengenesis and early MSC development are largely obscure. In this study, we took advantage of the well-established twist-related protein 1 (TWIST1)-overexpressing hESCs and two small molecular cocktails (CHIR99021, decitabine) for high-efficient MSC induction. To assess the multidimensional biological and transcriptomic characteristics, we turned to cellular and molecular methods, such as flow cytometry (FCM), quantitative reverse transcription-polymerase chain reaction (qRT-PCR), in vitro tri-lineage differentiation, cytokine secretion analysis, in vivo transplantation for acute liver injury (ALI) management, and bioinformatics analyses (eg, gene ontology-biological processes [GO-BP], Kyoto Encyclopedia of Genes and Genomes [KEGG], HeatMap, and principal component analysis [PCA]). By combining TWIST1 overexpression (denoted as T) and the indicated small molecular cocktails (denoted as S), hESCs high-efficiently differentiated into MSCs (denoted as TS-MSCs, induced by T and S combination) within 2 weeks. TS-MSCs satisfied the criteria for MSC definition and revealed comparable tri-lineage differentiation potential and ameliorative efficacy upon ALI mice. According to RNA-sequencing (SEQ) analysis, we originally illuminated the gradual variations in gene expression pattern and the concomitant biofunctions of the programmed hESC-MSCs. Overall, our data indicated the feasibility of high-efficient generation of hESC-MSCs by TWIST1 and cocktail-based programming. The generated hESC-MSCs revealed multifaceted in vivo and in vitro biofunctions as adult BM-MSCs, which collectively suggested promising prospects in ALI management in future.

A comparative study of the predictive value of four models for death in patients with severe burns.

OBJECTIVE: To assess the prognostic value of the Ryan score, Belgian Outcome of Burn Injury (BOBI) score,revised Baux (rBaux) score, and a new model (a Logit(P)-based scoring method created in 2020) for predicting mortality risk in patients with extremely severe burns and to conduct a comparative analysis. METHODS: A retrospective analysis was conducted on 599 burn patients who met the inclusion criteria and were admitted to the burn unit of the First Affiliated Hospital of Nanchang University from 2017 to 2022. Relevant information was collected, and receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA) were plotted for each of the four models in assessing mortality in these burn patients using both age-stratified and unstratified forms. The ROC curve section was further compared with the area under the curve (AUC), optimal cutoff value, as well as its sensitivity and specificity. Additionally, the quality of the AUC was assessed using the Delong test. RESULT: Among the patients who met the inclusion criteria, 532 were in the survival group and 67 in the death group. Irrespective of age stratification, the novel model exhibited superior performance with an AUC of 0.868 (95% CI: 0.838-0.894) among all four models predicting mortality risk in included patients, and also demonstrated better AUC quality than other models; the calibration curves showed that the accuracy of all four models was good; the DCA curves showed that the clinical utility of the novel model and rBuax score were better. In the comparison of four scoring models across different age groups, the new model demonstrated the largest AUC in both 0-19 years (0.954, 95% CI 0.914-0.979) and 20-59 years groups (0.838, 95% CI 0.793-0.877), while rBuax score exhibited the highest AUC in ≥ 60 years group (0.708, 95% CI of 0.602-0.800). The calibration curves showed that the four models exhibited greater accuracy within the age range of 20-59 years, while the DCA curves indicated that both the novel model and rBuax score scale displayed better prediction in both the 20-59 and ≥ 60 years groups. CONCLUSIONS: All four models demonstrate accurate and effective prognostication for patients with severe burns. Both the novel model and rBaux score exhibit enhanced prediction utility. In terms of the model itself alone, the new model is not simpler than, for example, the rBaux score, and whether it can be applied clinicallyinvolves further study.