Xinyi Dai

Background: Some studies found that red blood cell count (RBC) was an unrecognized risk factor for non-alcoholic fatty liver disease (NAFLD). While the epidemiological data underpinning the evidence is very limited. As there are some differences between the latest criteria of metabolic dysfunction-associated fatty liver disease (MAFLD) and NAFLD, itis necessary to evaluate the relationship between RBC and MAFLD. Methods: We performed a cross-sectional analysis of the National Health and Nutritional Examination Survey (NHANES)2017-2018 cohort, including 4477 participants. Hepatic steatosis was determined when the value of controlled attenuation parameter (CAP) obtained by Fibroscan was ≥274 dB/m. Multivariate logistic regression analysis was used to estimate the association between RBC and MAFLD. We estimated the adjusted odds ratio (OR) of RBC for MAFLD, and the nonlinear relationship between RBC and MAFLD was further described using smooth curve fittings and threshold-effect analysis. Results: We found that MAFLD risk was significantly higher according to RBC quartiles. The adjusted odds ratio (OR) and 95% confidence intervals (CIs)for the highest RBC quartile were 1.5(1.0, 2.3) for male and 1.1 (0.8, 1.6) for female, respectively. As for male, a non-linear relationship was discovered between RBCs and MAFLD, with a RBC threshold of 4.2. The effect sizes and confidence intervals on the right side of the inflection point were 1.5 (1.0, 2.0) (P for nonlinearity = 0.027). The sensitivity analysis showed a similar result. Conclusion: We demonstrated that that elevated RBC level is associated with the higher risk of MAFLD in male. The positive relationship was not significant in females after full adjustment. Our finding provided novel evidence indicating that RBCs might be a potential biomarker for MAFLD.

Advanced gastric cancer (GC) is a significant threat to human health. Oridonin (ORI), isolated from the Chinese herb Rabdosia rubescens, has demonstrated great potential in GC therapy. However, the application of ORI in the clinic was greatly hindered by its poor solubility, low bioavailability, and rapid plasma clearance. Herein, a simple and novel redox-sensitive ORI polymeric prodrug formulation was synthesized by covalently attaching ORI to poly(ethylene glycol)-block-poly(L-lysine) via a disulfide linker, which can self-assemble into micelles (P-ss-ORI) in aqueous solutions and produce low critical micelle concentrations (about 10 mg L⁻¹), characterized by small size (about 80 nm), negative surface charge (about −12 mV), and high drug loading efficiency (18.7%). The in vitro drug release study showed that P-ss-ORI can rapidly and completely release ORI in a glutathione (GSH)-rich environment and under low pH conditions. Moreover, in vitro and in vivo investigations confirmed that P-ss-ORI could remarkably extend the blood circulation time of ORI, enrich in tumor tissue, be effectively endocytosed by GC cancer cells, and quickly and completely release the drug under high intracellular GSH concentrations and low pH conditions, all these characteristics ultimately inhibit the growth of GC. This redox and pH dual-responsive P-ss-ORI formulation provides a useful strategy for GC treatment.

Head and neck squamous cell carcinoma (HNSCC) is a heterogeneous disease characterized by different molecular subgroups and clinical features. Therefore, it is important to uncover reliable molecular biomarkers for distinguishing different risk patient subgroup. Here, we conducted a multi-omics analysis to examine the joint predictive power of a multi-type RNA signature in the prognosis of HNSCC patients through integration analysis of mRNA, miRNA, and lncRNA expression profiles and clinical data in a large number of HNSCC patients. A multi-type RNA signature (15SigRS) was constructed which can classify patients into the high-risk group and low-risk group with the significantly different outcome [hazard ratio (HR) = 2.718, 95% confidence interval (CI), 2.258–3.272, p < 0.001] in the discovery data set, and subsequently validated in the Cancer Genome Atlas (TCGA) testing data set (HR = 1.299, 95% CI, 1.170–1.442, p < 0.001) and another independent GSE65858 data set (HR = 1.077, 95% CI, 1.016–1.143, p = 0.013). Further multivariate Cox regression analysis and stratification analysis demonstrated the independence of predictive performance of the 15SigRS relative to conventional clinicopathological factors. Furthermore, the 15SigRS has a prior performance in prognostic prediction than other single RNA type-based signatures. Functional analysis suggested that the 15SigRS are involved in immune- or metabolism-related KEGG pathways. In summary, our study demonstrated the potential application of mixed RNA types as molecular markers for predicting the outcome of cancer patients.