Cashclarke3610

Moreover, an in vivo experiment confirmed the inhibitory role of silenced ELF1 in tumor growth, with a decreased level of MEIS1 and GFI1. Taken together, our study elucidated a potential mechanism that ELF1 promoted cell progression by increasing GFI1 and METS1 as well as decreasing FBW7 expression in glioma.MicroRNAs (miRNAs) are important regulators in the process of cardiac hypertrophy and heart failure. Previous studies have shown that miR-199a is upregulated in pressure-overload cardiac hypertrophy and that inhibition of miR-199a attenuates cardiac hypertrophy in vitro. However, the therapeutic role of anti-miR-199a treatment in the cardiac hypertrophy in vivo model is less known. Here, we show an efficient and useful method to treat mouse cardiac hypertrophy and restore cardiac function through injection of adeno-associated virus (AAV)-mediated anti-miR-199a tough decoys (TuDs). RNA-seq transcriptome analysis indicated that genes related to cytoplasmic translation and mitochondrial respiratory chain complex assembly were upregulated in anti-miR-199a-treated recovered hearts. We further validated that PGC-1α is the direct target of miR-199a involved in the therapeutic effect and the regulation of the PGC-1α/ERRα axis and that the downstream pathway of mitochondrial fatty acid oxidation and oxidative phosphorylation constitute the underlying mechanism of the restored mitochondrial structure and function in our anti-miR-199a-treated mice. UAMC-3203 purchase Our study highlights the important regulatory role of miR-199a in cardiac hypertrophy and the value of the AAV-mediated miRNA delivery system.Patients with myotonic dystrophy type 1 (DM1) identify chronic fatigue as the most debilitating symptom, which manifests in part as prolonged recovery after exercise. Clinical features of DM1 result from pathogenic gain-of-function activity of transcripts containing an expanded microsatellite CUG repeat (CUGexp). In DM1 mice, therapies targeting the CUGexp transcripts correct the molecular phenotype, reverse myotonia, and improve muscle pathology. However, the effect of targeted molecular therapies on fatigue in DM1 is unknown. Here, we use two mouse models of DM1, age-matched wild-type controls, an exercise-activity assay, electrical impedance myography, and therapeutic antisense oligonucleotides (ASOs) to show that exaggerated exercise-induced fatigue progresses with age, is unrelated to muscle fiber size, and persists despite correction of the molecular phenotype for 3 months. In old DM1 mice, ASO treatment combined with an exercise training regimen consisting of treadmill walking 30 min per day 6 days per week for 3 months reverse all measures of fatigue. Exercise training without ASO therapy improves some measures of fatigue without correction of the molecular pathology. Our results highlight a key limitation of ASO monotherapy for this clinically important feature and support the development of moderate-intensity exercise as an adjuvant for targeted molecular therapies of DM1.Cardiac fibrosis occurs in most cardiac diseases, which reduces cardiac muscle compliance, impairs both systolic and diastolic heart function and, ultimately, leads to heart failure. Long noncoding RNAs (lncRNAs) have recently emerged as important regulators of a variety of biological processes; however, little is known about the expression and function of lncRNAs in cardiac fibrosis. Using unbiased transcriptome profiling in a mouse model of myocardial infarction (MI), we identified a cardiac fibroblast-enriched lncRNA (AK048087) named cardiac fibroblast-associated transcript (Cfast), which is significantly elevated after MI. Silencing Cfast expression by small interfering RNAs (siRNAs) or lentiviral short hairpin RNAs (shRNAs) resulted in suppression of fibrosis-related gene expression and transdifferentiation of myofibroblasts into cardiac fibroblasts. Depletion of Cfast by lentiviral shRNAs in mouse hearts significantly attenuated cardiac fibrosis induced by MI or isoproterenol-infusion. Importantly, inhibition of Cfast ameliorated cardiac function following cardiac injury. RNA pull-down followed by mass spectrometry analyses identified COTL1 (coactosin-like 1) as one of the Cfast interacting proteins. Mechanistically, Cfast competitively inhibits the COTL1 interaction with TRAP1 (transforming growth factor-β receptor-associated protein 1), which enhances TGF-β signaling by augmenting SMAD2/SMAD4 complex formation. Therefore, our study identifies Cfast as a novel cardiac fibroblast-enriched lncRNA that regulates cardiac fibroblast activation in response to pathophysiological stress. Cfast could serve as a potential therapeutic target for the prevention of cardiac fibrosis and cardiac diseases.

Evidence-based smoking cessation support tools (EBSTs) can double the quitting chances, but uptake among smokers is low. A digital decision aid (DA) could help smokers choose an EBST in concordance with their values and preferences, but it is unclear which type of smokers are interested in a digital DA. We hypothesized that smokers' general decision-making style (GDMS) could be used to identify early adopters. This study therefore aimed to identify smoker profiles based on smokers' GDMS and investigate these profiles' association with intention to use a digital DA.

A cross-sectional dataset (N = 200 smokers intending to quit) was used to perform a hierarchical cluster analysis based on smokers' GDMS scores.

Clusters were compared on demographic and socio-cognitive variables. Mediation analyses were conducted to see if the relationship between cluster membership and intention was mediated through socio-cognitive variables (e.g., attitude).

Two clusters were identified;





(n = 134) were more avoidant, more regretful and tended to depend more on others in their decision making, while





(n = 66) were more spontaneous and intuitive in their decision making. Cluster membership was significantly related to intention to use a DA, with





being more interested. Yet, this association ceased to be significant when corrected for socio-cognitive variables (e.g., attitude). This indicates that cluster membership affected intention via socio-cognitive variables.

The GDMS can be used to identify smokers who are interested in a digital DA early on. As such, the GDMS can be used to tailor recruitment and DA content.

The GDMS can be used to identify smokers who are interested in a digital DA early on. As such, the GDMS can be used to tailor recruitment and DA content.