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Adverse health effects associated with diesel exhaust (DE) are thought to be mediated in part by oxidative stress, but the detailed mechanisms are largely unknown. MicroRNAs (miRNAs) regulate gene expression post-transcriptionally and may respond to exposures such as DE. We profiled peripheral blood cellular miRNAs in participants with mild asthma who were exposed to controlled DE with and without antioxidant supplementation. Thirteen participants with asthma underwent controlled inhalation of filtered air and DE in a double-blinded, randomized crossover study of three conditions: a) DE plus placebo (DEP), b) filtered air plus placebo (FAP), or c) DE with N-acetylcysteine supplementation (DEN). Total cellular RNA was extracted from blood drawn before exposure and 6 hr after exposure for miRNA profiling by the NanoString nCounter assay. MiRNAs significantly associated with DEP exposure and a predicted target [nuclear factor (erythroid-derived 2)-like 2 (NRF2)] as well as antioxidant enzyme genes were assessed by reverse transcription-quantitative polymerase chain reaction (RT-qPCR) for validation, and we also assessed the ability of N-acetylcysteine supplementation to block the effect of DE on these specific miRNAs. 8-hydroxy-2'-deoxyguanosine (8-OHdG) was measured in plasma as a systemic oxidative stress marker. Expression of miR-21, miR-30e, miR-215, and miR-144 was significantly associated with DEP. The change in miR-144 was validated by RT-qPCR. NRF2 and its downstream antioxidant genes [glutamate cysteine ligase catalytic subunit (GCLC) and NAD(P)H:quinone oxidoreductase 1 (NQO1)] were negatively associated with miR-144 levels. Increases in miR-144 and miR-21 were associated with plasma 8-hydroxydeoxyguanosine 8-OHdG level and were blunted by antioxidant (i.e, DEN). Systemic miRNAs with plausible biological function are altered by acute moderate-dose DE exposure. Oxidative stress appears to mediate DE-associated changes in miR-144.

The finding that small non-coding RNAs (ncRNAs) are able to control gene expression in a sequence specific manner has had a massive impact on biology. Recent improvements in high throughput sequencing and computational prediction methods have allowed the discovery and classification of several types of ncRNAs. Based on their precursor structures, biogenesis pathways and modes of action, ncRNAs are classified as small interfering RNAs (siRNAs), microRNAs (miRNAs), PIWI-interacting RNAs (piRNAs), endogenous small interfering RNAs (endo-siRNAs or esiRNAs), promoter associate RNAs (pRNAs), small nucleolar RNAs (snoRNAs) and sno-derived RNAs. Among these, miRNAs appear as important cytoplasmic regulators of gene expression. miRNAs act as post-transcriptional regulators of their messenger RNA (mRNA) targets via mRNA degradation and/or translational repression. However, it is becoming evident that miRNAs also have specific nuclear functions. Among these, the most studied and debated activity is the miRNA-guided transcriptional control of gene expression. Although available data detail quite precisely the effectors of this activity, the mechanisms by which miRNAs identify their gene targets to control transcription are still a matter of debate. Here, we focus on nuclear functions of miRNAs and on alternative mechanisms of target recognition, at the promoter lavel, by miRNAs in carrying out transcriptional gene silencing.

Squamous cell carcinoma of the oral cavity (OSCC) is the sixth most common malignancy. Surgery is mainstay treatment for oral cancers. Surgery in locally advanced OSCC presents many challenges primarily because the head and neck have critical structures that can be damaged by tumor or treatment. It is thought that neoadjuvant chemotherapy (NC) in locally advanced OSCC is able to shrink tumor size. Chemoresistancy is a problem due to hypoxic microenvironment characterized by increased expression of HIF-1[alpha]. It is also regulated by miR-210 as well as increased expression of CD44 and CD133. Melatonin has a powerful antioxidant and oncostatic effects that are expected to improve tumor hypoxia and clinical response. Fifty patients with OSCC were included and randomized. miR-210 and CD44 expression were measured before and after intervention using qRT-PCR absolute quantification, and clinical response was evaluated according to RECIST 1.1 criteria. This study aims to determine the effect of melatonin in improving the clinical response of patients with locally advanced oral squamous cell carcinoma (OSCC) after neoadjuvant chemotherapy to miR-210 and CD44 expression. Melatonin administration reduced miR-210 levels but not significant (p = 0.767). CD44 expression also decreased in the melatonin group compared with placebo yet was not significant (p = 0.103). There was a decrease in the expression of miR-210 and CD44 followed by a decrease in the percentage of residual tumor but not significant (p = 0.114). In OSCC, the addition of 20-mg melatonin to neoadjuvant chemotherapy (NC) reduced the expression of miR-210 and CD44 and decreased the percentage of tumor residue; however, no statistically significant result was observed.

Key Points MicroRNAs (miRNAs) are small RNAs (∼22 nucleotides long) that post-transcriptionally regulate the expression of thousands of genes in a broad range of organisms. miRNA expression profiling is useful for identifying miRNAs that are important in the regulation of a range of processes, including organismal development, tissue differentiation and disease pathology. miRNAs show promise as biomarkers for various diseases. miRNAs are more stable than mRNAs in many specimen types and are more readily measured than proteins. However, sample type, processing and RNA extraction methods can have a substantial impact on the results of miRNA profiling, and therefore quality and quantity assessment is recommended. Biogenesis of miRNAs occurs through multiple steps and includes the intermediate primary miRNA and precursor miRNA forms, as well as post-transcriptional nucleotide additions and deletions, leading to 'isomiRs'. Choice of platform and analysis in miRNA profiling should include consideration of the need to distinguish between different forms of miRNAs. Three main approaches are currently well established for miRNA profiling: quantitative reverse transcription PCR (qRT-PCR), hybridization-based methods (for example, DNA microarrays) and high-throughput sequencing (that is, RNA sequencing). The optimal choice of platform depends on the specific experimental goals. Analysis of miRNA-profiling data typically includes data processing, data quality assessment, data normalization and calculation of differential expression. The optimal approach to data analysis depends on the platform selected and the nature of the experiment. Owing to the important role of microRNAs in gene regulation, profiling repertoires of expressed microRNAs can be informative in basic research and clinical settings. This Review describes the methods that are available for microRNA profiling and considerations for choosing among analytical options. MicroRNAs (miRNAs) are small RNAs that post-transcriptionally regulate the expression of thousands of genes in a broad range of organisms in both normal physiological contexts and in disease contexts. miRNA expression profiling is gaining popularity because miRNAs, as key regulators in gene expression networks, can influence many biological processes and also show promise as biomarkers for disease. Technological advances have spawned a multitude of platforms for miRNA profiling, and an understanding of the strengths and pitfalls of different approaches can aid in their effective use. Here, we review the major considerations for carrying out and interpreting results of miRNA-profiling studies.

Synthetic DNA motors have great potential to mimic natural protein motors in cells but the operation of synthetic DNA motors in living cells remains challenging and has not been demonstrated. Here we report a DNAzyme motor that operates in living cells in response to a specific intracellular target. The whole motor system is constructed on a 20 nm gold nanoparticle (AuNP) decorated with hundreds of substrate strands serving as DNA tracks and dozens of DNAzyme molecules each silenced by a locking strand. Intracellular interaction of a target molecule with the motor system initiates the autonomous walking of the motor on the AuNP. An example DNAzyme motor responsive to a specific microRNA enables amplified detection of the specific microRNA in individual cancer cells. Activated by specific intracellular targets, these self-powered DNAzyme motors will have diverse applications in the control and modulation of biological functions. Synthetic DNA nanomachines have been designed to perform a variety of tasks in vitro . Here, the authors build a nanomotor system that integrates a DNAzyme and DNA track on a gold nanoparticle, to facilitate cellular uptake, and apply it as a real-time miRNA imaging tool in living cells.

Background The aim of the current study was to determine if 4 weeks of consumption of Bang® Pre-Workout Master Blaster® (BMB; Vital Pharmaceuticals Inc., Weston, FL) combined with resistance training resulted in greater increases in muscle mass and maximal strength compared with resistance training combined with placebo (PLA). Additionally, we aimed to determine if BMB ingestion combined with resistance training preferentially altered resting skeletal muscle expression of microRNAs (miRs) or resting serum insulin-like growth factor (IGF-1). Methods Sixteen recreationally-active men completed the study. The study employed a block-randomized, double-blind, placebo-controlled, parallel design. Participants completed two testing sessions separated by 4 weeks of resistance exercise combined with daily supplementation of BMB or PLA. At each testing session, hemodynamics, body composition, and muscle and blood samples were obtained followed by strength assessments of the lower- and upper-body via measurement of squat and bench press one-repetition maximum (1-RM), respectively. A separate general linear model was utilized for analysis of each variable to determine the effect of each supplement (between-factor) over time (within-factor) using an a priori probability level of ≤0.05. Results No significant effects were observed for dietary intake, hemodynamics, fat mass, body fat percentage, or serum IGF-1. A greater increase in total body mass (3.19 kg, 95% CI, 1.98 kg, 4.40 kg vs. 0.44 kg, 95% CI, − 0.50 kg, 1.39 kg) and lean body mass (3.15 kg, 95% CI, 1.80 kg, 4.49 kg vs. 0.89 kg, 95% CI, − 0.14 kg, 1.93 kg) was observed for the BMB group compared with PLA ( p  <  0.01). A significant increase over time was observed for miR-23a ( p  = 0.02) and miR-23b ( p  = 0.05) expression. A greater increase in squat 1-RM was observed for the BMB group (23.86 kg, 95% CI, 16.75 kg, 30.97 kg) compared with the PLA group (14.20 kg, 95% CI, 7.04 kg, 21.37 kg, p  = 0.04). Conclusions BMB supplementation combined with resistance exercise training for 4 weeks resulted in superior adaptations in maximal strength and LBM compared with resistance training with a placebo. No adverse resting hemodynamic or clinical blood safety markers were observed as a result of BMB supplementation. The superior outcomes associated with BMB supplementation could not be explained by resting serum IGF-1 or the skeletal muscle miRs measured, although resting miR-23a and miR-23b expression both increased as a result of resistance training.

The interplay between abnormalities in genes coding for proteins and noncoding microRNAs (miRNAs) has been among the most exciting yet unexpected discoveries in oncology over the last decade. The complexity of this network has redefined cancer research as miRNAs, produced from what was once considered \"genomic trash,\" have shown to be crucial for cancer initiation, progression, and dissemination. Naturally occurring miRNAs are very short transcripts that never produce a protein or amino acid chain, but act by regulating protein expression during cellular processes such as growth, development, and differentiation at the transcriptional, posttranscriptional, and/or translational level. In this review article, miRNAs are presented as ubiquitous players involved in all cancer hallmarks. The authors also describe the most used methods to detect their expression, which have revealed the identity of hundreds of miRNAs dysregulated in cancer cells or tumor microenvironment cells. Furthermore, the role of miRNAs as hormones and as reliable cancer biomarkers and predictors of treatment response is discussed. Along with this, the authors explore current strategies in designing miRNA-targeting therapeutics, as well as the associated challenges that research envisions to overcome. Finally, a new wave in molecular oncology translational research is introduced: the study of long noncoding RNAs.

Extracellular RNAs (exRNAs) in human body fluids are emerging as effective biomarkers for detection of diseases. Saliva, as the most accessible and noninvasive body fluid, has been shown to harbor exRNA biomarkers for several human diseases. However, the entire spectrum of exRNA from saliva has not been fully characterized. Using high-throughput RNA sequencing (RNA-Seq), we conducted an in-depth bioinformatic analysis of noncoding RNAs (ncRNAs) in human cell-free saliva (CFS) from healthy individuals, with a focus on microRNAs (miRNAs), piwi-interacting RNAs (piRNAs), and circular RNAs (circRNAs). Our data demonstrated robust reproducibility of miRNA and piRNA profiles across individuals. Furthermore, individual variability of these salivary RNA species was highly similar to those in other body fluids or cellular samples, despite the direct exposure of saliva to environmental impacts. By comparative analysis of >90 RNA-Seq data sets of different origins, we observed that piRNAs were surprisingly abundant in CFS compared with other body fluid or intracellular samples, with expression levels in CFS comparable to those found in embryonic stem cells and skin cells. Conversely, miRNA expression profiles in CFS were highly similar to those in serum and cerebrospinal fluid. Using a customized bioinformatics method, we identified >400 circRNAs in CFS. These data represent the first global characterization and experimental validation of circRNAs in any type of extracellular body fluid. Our study provides a comprehensive landscape of ncRNA species in human saliva that will facilitate further biomarker discoveries and lay a foundation for future studies related to ncRNAs in human saliva.

There is an increasing interest in using microRNAs (miRNA) as biomarkers in autoimmune diseases. They are easily accessible in many body fluids but it is controversial if they are circulating freely or are encapsulated in microvesicles, particularly exosomes. We investigated if the majority of miRNas in serum and saliva are free-circulating or concentrated in exosomes. Exosomes were isolated by ultracentrifugation from fresh and frozen human serum and saliva. The amount of selected miRNAs extracted from the exosomal pellet and the exosome-depleted serum and saliva was compared by quantitative RT-PCR. Some miRNAs tested are ubiquitously expressed, others were previously reported as biomarkers. We included miRNAs previously reported to be free circulating and some thought to be exosome specific. The purity of exosome fraction was confirmed by electronmicroscopy and western blot. The concentration of miRNAs was consistently higher in the exosome pellet compared to the exosome-depleted supernatant. We obtained the same results using an equal volume or equal amount of total RNA as input of the RT-qPCR. The concentration of miRNA in whole, unfractionated serum, was between the exosomal pellet and the exosome-depleted supernatant. Selected miRNAs, which were detectable in exosomes, were undetectable in whole serum and the exosome-depleted supernantant. Exosome isolation improves the sensitivity of miRNA amplification from human biologic fluids. Exosomal miRNA should be the starting point for early biomarker studies to reduce the probability of false negative results involving low abundance miRNAs that may be missed by using unfractionated serum or saliva.

Recently, a growing number of biological research and scientific experiments have demonstrated that microRNA (miRNA) affects the development of human complex diseases. Discovering miRNA-disease associations plays an increasingly vital role in devising diagnostic and therapeutic tools for diseases. However, since uncovering associations via experimental methods is expensive and time-consuming, novel and effective computational methods for association prediction are in demand. In this study, we developed a computational model of Matrix Decomposition and Heterogeneous Graph Inference for miRNA-disease association prediction (MDHGI) to discover new miRNA-disease associations by integrating the predicted association probability obtained from matrix decomposition through sparse learning method, the miRNA functional similarity, the disease semantic similarity, and the Gaussian interaction profile kernel similarity for diseases and miRNAs into a heterogeneous network. Compared with previous computational models based on heterogeneous networks, our model took full advantage of matrix decomposition before the construction of heterogeneous network, thereby improving the prediction accuracy. MDHGI obtained AUCs of 0.8945 and 0.8240 in the global and the local leave-one-out cross validation, respectively. Moreover, the AUC of 0.8794+/-0.0021 in 5-fold cross validation confirmed its stability of predictive performance. In addition, to further evaluate the model's accuracy, we applied MDHGI to four important human cancers in three different kinds of case studies. In the first type, 98% (Esophageal Neoplasms) and 98% (Lymphoma) of top 50 predicted miRNAs have been confirmed by at least one of the two databases (dbDEMC and miR2Disease) or at least one experimental literature in PubMed. In the second type of case study, what made a difference was that we removed all known associations between the miRNAs and Lung Neoplasms before implementing MDHGI on Lung Neoplasms. As a result, 100% (Lung Neoplasms) of top 50 related miRNAs have been indexed by at least one of the three databases (dbDEMC, miR2Disease and HMDD V2.0) or at least one experimental literature in PubMed. Furthermore, we also tested our prediction method on the HMDD V1.0 database to prove the applicability of MDHGI to different datasets. The results showed that 50 out of top 50 miRNAs related with the breast neoplasms were validated by at least one of the three databases (HMDD V2.0, dbDEMC, and miR2Disease) or at least one experimental literature.