Beliefs about the consequences of stress, stress mindsets, are associated with health and performance outcomes under stress. This article reports the development and examination of the psychometric properties of a measure of stress mindset The Stress Control Mindset Measure (SCMM). The measure is consistent with theory on mindsets about self-attributes and conceptualizes stress mindset as the extent to which individuals endorse beliefs that stress can be enhancing.

The study adopted a correlational cross-sectional survey design in two student samples. Undergraduate students from an Australian university (Sample 1, N=218) and a UK university (Sample 2, N=214) completed the SCMM and measures of health and well-being outcomes.

Confirmatory factor analyses supported a four-factor structure and strict measurement invariance across samples (ΔCFI<0.01). Quizartinib mouse Reliability, convergent validity, discriminant validity, and concurrent validity of the overall SCMM were supported in both samples. Incremental validity was supported for most outcomes, accounting for significantly more variance (between 2.2% and 5.9%) in health and well-being outcomes than an existing measure.

Current data provide preliminary support for the SCMM as a reliable and valid measure with good psychometric properties and theoretically consistent relations with health outcomes under stress. Findings provide initial evidence supporting the potential utility of the SCMM in future research examining relations between stress mindsets and health and performance outcomes.

Current data provide preliminary support for the SCMM as a reliable and valid measure with good psychometric properties and theoretically consistent relations with health outcomes under stress. Findings provide initial evidence supporting the potential utility of the SCMM in future research examining relations between stress mindsets and health and performance outcomes.MET inhibitors have shown activity in non-small-cell lung cancer patients (NSCLC) with MET amplification and exon 14 skipping (METΔex14). However, patient stratification is imperfect, and thus, response rates have varied widely. Here, we studied MET alterations in 474 advanced NSCLC patients by nCounter, an RNA-based technique, together with next-generation sequencing (NGS), fluorescence in situ hybridization (FISH), immunohistochemistry (IHC), and reverse transcriptase polymerase chain reaction (RT-PCR), exploring correlation with clinical benefit. Of the 474 samples analyzed, 422 (89%) yielded valid results by nCounter, which identified 13 patients (3%) with METΔex14 and 15 patients (3.5%) with very-high MET mRNA expression. These two subgroups were mutually exclusive, displayed distinct phenotypes and did not generally coexist with other drivers. For METΔex14, 3/8 (37.5%) samples positive by nCounter tested negative by NGS. Regarding patients with very-high MET mRNA, 92% had MET amplification by FISH and/or NGS. However, FISH failed to identify three patients (30%) with very-high MET RNA expression, among which one received MET tyrosine kinase inhibitor treatment deriving clinical benefit. Our results indicate that quantitative mRNA-based techniques can improve the selection of patients for MET-targeted therapies.Mitochondria-targeted photodynamic therapy (Mt-PDT), which enables the photogenerated cytotoxic oxygen species with fatal oxidative damage to block mitochondrial functions, has been considered as a promising method to enhance the anticancer effectiveness. Aiming at the challenges of PDT, in the past few decades, numerous mitochondria-targeting molecular agents have been developed to boost the PDT efficacy via directly destroying the mitochondria or activating mitochondria-mediated cell death pathways. Herein, a review for recent advances of Mt-PDT is highlighted including mitochondrial targeting design principles and strategies, therapeutic performance of mitochondria-targeted agents-mediated PDT as well as the agent-free Mt-PDT. In addition, it puts together the achievements of the combinatory mitochondria-anchoring PDT and other anticancer strategies, demonstrating the advantages provided by Mt-PDT. The existing challenges are discussed and future settlements for the development of mitochondria-specific agents are also forecasted.Gallbladder carcinoma (GBC) commonly occurs in gastrointestinal malignancy and has the fifth highest mortality rate among gastrointestinal malignancy. Recently, miR-188-5p, a small noncoding RNA, has been implicated in various types of cancer such as nasopharyngeal carcinoma, oral squamous cell carcinoma, liver cancer, and prostate cancer. However, the effect of miR-188-5p on GBC remains unclear. Here, we demonstrated that miR-188-5p was downregulated in GBC tissues, and downregulation of miR-188-5p correlated with larger tumor size, lymph node metastasis, and extensive metastasis. In addition, the overall survival time of patients with higher miR-188-5p expression was significantly longer than that of patients with low-miR-188-5p expression. Moreover, downregulation of miR-188-5p promoted the proliferation, migration, and invasion of GBC cells, while its overexpression inhibited cell invasion and induced cell apoptosis, and arrested GBC growth in vivo. Importantly, miR-188-5p-dependent tumorigenesis was correlated with Wnt/β-catenin signaling and p-38/JNK signaling. In conclusion, miR-188-5p plays a direct role in GBC tumorigenesis. Our study suggests that miR-188-5p could serve as a novel diagnosis marker and therapeutic target in GBC.

The significant abnormalities of precuneus (PC), which are associated with brain dysfunction, have been identified in cirrhotic patients with covert hepatic encephalopathy (CHE). The present study aimed to apply radiomics analysis to identify the significant radiomic features in PC and their subregions, combine with clinical risk factors, then build and evaluate the classification models for CHE diagnosis.

106 HBV-related cirrhotic patients (54 had current CHE and 52 had non-CHE) underwent the three-dimensional T1-weighted imaging. For each participant, PC and their subregions were segmented and extracted a large number of radiomic features and then identified the features with significant discriminative power as the radiomics signature. The logistic regression analysis was employed to develop and evaluate the classification models, which are constructed using the radiomics signature and clinical risk factors.

The classification model (R-C model) achieved best diagnostic performance, which incorporated radiomics signature (4 radiomic features from right PC), venous blood ammonia, and the Child-Pugh stage.