Certain amounts of precipitate in CoCrFeNiMox (simplified as Mox) is beneficial to the wear resistance; however, the optimal chemical content of Mo and the anti-wear mechanism behind it remains unclear. The Mox (x = 0, 0.3, 0.5, 1, 1.5 in molar ratio) high entropy alloys (HEAs) were manufactured, the evolution of their microstructure, mechanical, friction, and wear properties with Mo content was studied. The results displayed that the mechanical properties of the FCC solid solution were enhanced from Mo0 to Mo0.3, then kept unchanged till x = 1.5. The volume fraction of the precipitates increased with Mo content. The Mo1 presents the lower average friction coefficient and wear rate, attributed to the desired types, amount, size, distribution of the hard σ and μ phases in the ductile FCC solid solution. The detailed mechanism behind their tribological behaviors were discussed in the manuscript.

A series of FeCrNiMnAlx (x=0, 0.3, 0.5, 0.8, 1.0 in molar ratio) high entropy alloys (HEAs) were prepared by the vacuum arc melting method. The effects of Al content on the microstructure, mechanical, and wear properties were investigated. For FeCrNiMn alloy, the microstructure was the main homogeneous structure with face-centered cubic (FCC) phase, whilst FeCrNiMnAl0.3 produced a dendritic microstructure consisting of a mixture of FCC+BCC+B2 phases, and the mixture BCC+B2 dendritic interdendritic microstructure appeared when the molar ratio of Al is beyond 0.5. The hardness and yield stress of the HEAs are effectively improved with the increased Al amount but the ductility is lowered. In this case, FeCrNiMnAl alloy showed decreased yield stress due to the deteriorated ductility. Moreover, the friction coefficient decreases and the wear resistance improved with the increased aluminum content. FeCrNiMnAl0.8 HEAs have the best wear resistance due to the advantages of achieving a balance of strength and ductility.

Four FeCrNiMnMo x (x=0, 0.1, 0.3, 0.5, in molar ratio) high-entropy alloys (HEAs) were synthesized by vacuum arc melting to explore the potential impact of Mo on the microstructure, mechanical properties, and passivation and electrochemical behaviors in 0.5 M H 2 SO 4 solution. The results display that the FeCrNiMn alloy exhibits a single face-centered cubic (FCC) structure while the microstructures of the FeCrNiMnMo 0.1 , FeCrNiMnMo 0.3 , and FeCrNiMnMo 0.5 alloys consist of the FCC and σ phase. The appear of the σ phase ascribed to the addition of Mo enhances the hardness and yield strength with the sacrifice of plasticity. The FeCrNiMnMo x HEAs achieve the maximum hardness of 414 HV 0.2 and the highest compressive yield strength of 830 MPa when x=0.5, but compressive fracture strain is lowered to 10.8%. X-ray photoelectron spectroscopy (XPS) and electrochemical analysis show that the passivation film in FeCrNiMnMo x alloy mainly consists of chromium oxides and molybdenum oxides. Mo has a beneficial effect on the corrosion resistance of the FeCrNiMnMo x HEAs in a 0.5 M H 2 SO 4 solution by increasing the corrosion potential (E corr ) and decreasing the corrosion current density (I corr ) and passivation current density (I pass ). The FeCrNiMnMo 0.1 alloy shows the best corrosion resistance, mainly due to its passivation film consisting of a large proportion of chromium oxide (Cr 2 O 3 ). More Mo additions promote the formation of the precipitate of σ phase and the matrix regions depleted Cr and Mo elements adverse to the resistance to preferential localized corrosion.

Impaired liver function is one of the complications of acute cholecystitis, and improper treatment can lead to acute liver failure and even death. Therefore, timely evaluation of liver function provides a reliable basis for clinical diagnosis and treatment. However, no biomarkers have been identified to predict liver injury in patients with cholecystitis. Deep sequencing was used to analyze microRNA expression profiles in plasma exosomes from cholecystitis patients. Sequencing results were confirmed by quantitative real-time PCR (RT-qPCR). The findings demonstrated that biomarker panels consisting of multiple exosome-derived miRNAs improved the sensitivity of cholecystitis prediction. Further analysis revealed that hsa-miR-4440 and hsa-miR-6808-5p could specifically suggest the risk of early liver injury in patients with cholecystitis, with AUROCs of 0.895(95% CI: 0.764 to 1.025) and 0.804(95% CI: 0.6495 to 0.9589) respectively. Additionally, our GWAS analysis based on the results published by the FinnGen Biobank found that ALT was limitedly associated with cholecystitis, demonstrating the importance of our research into novel predictive biomarkers of early liver injury. Biomarker panels composed of multiple exosome-derived miRNAs could accurately predict cholecystitis. Furthermore, hsa-miR-4440 and hsa-miR-6808-5p could serve as early predictors of liver injury in patients with cholecystitis, thereby aiding in the selection of clinical treatment modalities.

Background: Cervical cancer (CC), the fourth most common cancer among women worldwide, has high morbidity and mortality. Necroptosis is a newly discovered form of cell death that plays an important role in cancer development, progression, and metastasis. However, the expression of necroptosis-related genes (NRGs) in CC and their relationship with CC prognosis remain unclear. Therefore, we screened the signature NRGs in CC and constructed a risk prognostic model.Methods: We downloaded gene data and clinical information of patients with cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) from The Cancer Genome Atlas (TCGA) database. We performed functional enrichment analysis on the differentially expressed NRGs (DENRGs). We constructed prognostic models and evaluated them by Cox and LASSO regressions for DENRGs, and validated them using the International Cancer Genome Consortium (ICGC) dataset. We used the obtained risk score to classify patients into high- and low-risk groups. We employed the ESTIMATE and single sample gene set enrichment analysis (ssGSEA) algorithms to explore the relationship between the risk score and the clinical phenotype and the tumor immune microenvironment.Results: With LASSO regression, we established a prognostic model of CC including 16 signature DENRGs (TMP3, CHMP4C, EEF1A1, FASN, TNF, S100A10, IL1A, H1.2, SLC25A5, GLTP, IFNG, H2AC13, TUBB4B, AKNA, TYK2, and H1.5). The risk score was associated with poor prognosis in CC. Survival was lower in the high-risk group than the low-risk group. The nomogram based on the risk score, T stage, and N stage showed good prognostic predictive power. We found significant differences in immune scores, immune infiltration analysis, and immune checkpoints between the high- and low-risk groups (p < 0.05).Conclusion: We screened for DENRGs based on the TCGA database by using bioinformatics methods, and constructed prognostic models based on the signature DENRGs, which we confirmed as possibly having important biological functions in CC. Our study provides a new perspective on CC prognosis and immunity, and offers a series of new targets for future treatment.