Construction of a mitophagy-related prognostic signature for predicting prognosis and tumor microenvironment in lung adenocarcinoma.

Background: Mitophagy is the selective degradation of mitochondria by autophagy. It becomes increasingly clear that mitophagy pathways are important for cancer cells to adapt to their high-energy needs. However, which genes associated with mitophagy could be used to prognosis cancer is unknown. Methods: We created a clinical prognostic model using mitophagy-related genes (MRGs) in lung adenocarcinoma (LUAD) patients for the first time, and we employed bioinformatics methods to search for biomarkers that affect the progression and prognosis of LUAD. Transcriptome data for LUAD were obtained from The Cancer Genome Atlas (TCGA) database, and additional expression data from LUAD patients were sourced from the Gene Expression Omnibus (GEO) database. Furthermore, 25 complete MRGs were identified based on annotations from the MSigDB database. Results: A comparison of the mitophagy scores between the groups with high and low scores was done using receiver operating characteristic (ROC) curves, which also revealed the differential gene expression patterns between the two groups. Using Kaplan-Meier analysis, two prognostic MRGs from the groups with high and low mitophagy scores were identified: TOMM40 and VDAC1. Using univariate and multivariate Cox regression, the relationship between the expression levels of these two genes and prognostic clinical features of LUAD was examined further.The prognosis of LUAD patients was shown to be significantly correlated (P < 0.05) with the expression levels of these two genes. Conclusions: Our prognostic model would improve the prognosis of LUAD and guide clinical treatments.

Adult classic Bartter syndrome: a case report with 5-year follow-up and literature review.

Bartter syndrome (BS) is a rare, inherited salt-losing renal tubular disorder characterized by secondary hyperaldosteronism, hypokalemia, hypochloremia, metabolic alkalosis, and low-to-normal blood pressure. Classic BS, or BS Type 3, the most common subtype in the Asian population, is caused by a molecular defect in ClC-Kb, a voltage-gated chloride channel in renal tubules, due to CLCNKB gene mutation. Because the onset of BS is more common in children than in adults, the diagnosis, treatment outcomes, genotype/phenotype association, and follow-up of adult-onset BS Type 3 are limited. This case report describes the findings in a 20-year-old man who was admitted with hypokalemic paralysis, with clinical manifestations were similar to those of Gitelman syndrome (GS); however, the patient was later diagnosed to have BS Type 3 through genetic testing (NM_000085.4 (CLCNKB): c.1052G>T). A literature review showed that no homozygous mutations have been reported to date. After 5 years of treatment and follow-up, we found that this genotype requires high levels of potassium and is prone to urinary protein and metabolic syndrome. Distinguishing adult-onset BS from GS is challenging in clinical practice. However, genetic diagnosis can help solve this problem effectively, and genotypes play a guiding role in treatment planning.

A Conditional Mutual Information Estimator for Mixed Data and an Associated Conditional Independence Test.

In this study, we focus on mixed data which are either observations of univariate random variables which can be quantitative or qualitative, or observations of multivariate random variables such that each variable can include both quantitative and qualitative components. We first propose a novel method, called CMIh, to estimate conditional mutual information taking advantages of the previously proposed approaches for qualitative and quantitative data. We then introduce a new local permutation test, called LocAT for local adaptive test, which is well adapted to mixed data. Our experiments illustrate the good behaviour of CMIh and LocAT, and show their respective abilities to accurately estimate conditional mutual information and to detect conditional (in)dependence for mixed data.