LncRNA HOXA­AS2 promotes the progression of epithelial ovarian cancer via the regulation of miR­372.

Long non-coding RNAs, such as homeobox A cluster antisense RNA2 (HOXA-AS2) are understood to be involved in tumor growth and development of numerous cancers. However, the role of HOXA-AS2 in the progression of human epithelial ovarian cancer (EOC) remains unclear. In the present study, the expression of HOXA-AS2 was found to be upregulated in EOC tissues compared with noncancerous tissues, and to be strongly correlated to an advanced Federation International of Gynecology and Obstetrics grade and poor prognosis. Knockdown of HOXA-AS2 in the EOC cells inhibited cell proliferation, invasion and migration, as well as inducing cell apoptosis. The ENCORI database was used to screen the microRNAs (miRNAs/miRs) that bound to HOXA-AS2, and one was tested using RNA pull-down and luciferase reporter assays. It was demonstrated that HOXA-AS2 functioned through the competing endogenous RNA mechanism to regulate miR-372. It was also demonstrated that the downregulation of miR-372 reversed the inhibitory effects of the knockdown of HOXA-AS2 in EOC cells. These results indicated that HOXA-AS2 promoted EOC progression by regulating the miR-372, which suggests that HOXA-AS2 may be a therapy target for EOC.

Cognitive simulation along with neural adaptation explain effects of suggestions: a novel theoretical framework.

Hypnosis is an effective intervention with proven efficacy that is employed in clinical settings and for investigating various cognitive processes. Despite their practical success, no consensus exists regarding the mechanisms underlying well-established hypnotic phenomena. Here, we suggest a new framework called the Simulation-Adaptation Theory of Hypnosis (SATH). SATH expands the predictive coding framework by focusing on (a) redundancy elimination in generative models using intrinsically generated prediction errors, (b) adaptation due to amplified or prolonged neural activity, and (c) using internally generated predictions as a venue for learning new associations. The core of our treatise is that simulating proprioceptive, interoceptive, and exteroceptive signals, along with the top-down attenuation of the precision of sensory prediction errors due to neural adaptation, can explain objective and subjective hypnotic phenomena. Based on these postulations, we offer mechanistic explanations for critical categories of direct verbal suggestions, including (1) direct-ideomotor, (2) challenge-ideomotor, (3) perceptual, and (4) cognitive suggestions. Notably, we argue that besides explaining objective responses, SATH accounts for the subjective effects of suggestions, i.e., the change in the sense of agency and reality. Finally, we discuss individual differences in hypnotizability and how SATH accommodates them. We believe that SATH is exhaustive and parsimonious in its scope, can explain a wide range of hypnotic phenomena without contradiction, and provides a host of testable predictions for future research.

Interface-guided phenotyping of coding variants in the transcription factor RUNX1.

Single-gene missense mutations remain challenging to interpret. Here, we deploy scalable functional screening by sequencing (SEUSS), a Perturb-seq method, to generate mutations at protein interfaces of RUNX1 and quantify their effect on activities of downstream cellular programs. We evaluate single-cell RNA profiles of 115 mutations in myelogenous leukemia cells and categorize them into three functionally distinct groups, wild-type (WT)-like, loss-of-function (LoF)-like, and hypomorphic, that we validate in orthogonal assays. LoF-like variants dominate the DNA-binding site and are recurrent in cancer; however, recurrence alone does not predict functional impact. Hypomorphic variants share characteristics with LoF-like but favor protein interactions, promoting gene expression indicative of nerve growth factor (NGF) response and cytokine recruitment of neutrophils. Accessible DNA near differentially expressed genes frequently contains RUNX1-binding motifs. Finally, we reclassify 16 variants of uncertain significance and train a classifier to predict 103 more. Our work demonstrates the potential of targeting protein interactions to better define the landscape of phenotypes reachable by missense mutations.

Using continuous relative phase and modified vector coding analyses to quantify spinal coordination and coordinative variability for healthy and chronic low back pain patients: An exploratory comparative analysis.

Differences in coordination and coordinative variability are common in people with low back pain. While differences may relate to the different analyses used to quantify these metrics, the preferred approach remains unclear. We aimed to compare coordination and coordinative variability, in people with and without low back pain performing a lifting/lowering task, using continuous relative phase and vector coding procedures, and to identify which technique better detects group differences. Upper lumbar (T12-L3), lower lumbar (L3-S1), and hip angular kinematics were measured using electromagnetic motion capture during 10 crate lifting/lowering repetitions from adults with (n = 47) and without (n = 17) low back pain. Coordination and coordinative variability for the Hip-Lower Lumbar and Lower Lumbar-Upper Lumbar joint pairs were quantified using mean absolute relative phase and deviation phase (continuous relative phase), and coupling angle and coupling angle variability (vector coding), respectively. T-tests examined group differences in coordination and variability. Cohen's d bootstrapping analyses identified the more sensitive technique for detecting group differences. Less in-phase and more variable behavior was observed in the low back pain group, mostly independent of joint pair and analytical technique (P < 0.05, Cohen's d range = 0.61 to 1.33). Qualitatively, the low back group limited motion at the lower lumbar spine during lifting/lowering. Continuous relative phase was more sensitive in detecting group differences in coordinative variability, while vector coding was more sensitive towards differences in coordination. These procedures convey distinct information and have their respective merits. Researchers should consider the choice of analytical techniques based on their study objectives.

The role of long non-coding RNA in Crohn's disease.

Emerging evidence has illuminated the pivotal role of long noncoding RNAs (lncRNAs) in orchestrating immunological functions and autoimmune responses. In the context of Crohn's disease (CD), an array of novel lncRNAs has been identified in the plasma and intestinal tissues of afflicted individuals, suggesting a dualistic influence on the disease progression, either exacerbating or mitigating its course. Current research has demonstrated the involvement of lncRNAs in competitive endogenous RNA, the inflammation process, epithelial barrier function, gut microbiota imbalance, and epigenetic regulation. This review aims to encapsulate the current knowledge on the lncRNA contribution to CD and underscore potential avenues for future research. LncRNAs are increasingly recognized as significant biomarkers and potential therapeutic targets, holding a key position in the pathogenesis of CD. Furthermore, the unique attributes of circulating lncRNAs, such as minimal side effects, combinational therapy potential, and personalized medicine, render them as promising therapeutic tools for individual health management in CD.

Gas5 regulates early-life stress-induced anxiety and spatial memory.

Early-life stress (ES) induced by maternal separation (MS) remains a proven causality of anxiety and memory deficits at later stages of life. Emerging studies have shown that MS-induced gene expression in the hippocampus is operated at the level of transcription. However, the extent of involvement of non-coding RNAs in MS-induced behavioural deficits remains unexplored. Here, we have investigated the role of synapse-enriched long non-coding RNAs (lncRNAs) in anxiety and memory upon MS. We observed that MS led to an enhancement of expression of the lncRNA growth arrest specific 5 (Gas5) in the hippocampus; accompanied by increased levels of anxiety and deficits in spatial memory. Gas5 knockdown in early life was able to reduce anxiety and partially rescue the spatial memory deficits of maternally separated adult mice. However, the reversal of MS-induced anxiety and memory deficits is not attributed to Gas5 activity during neuronal development as Gas5 RNAi did not influence spine development. Gene Ontology analysis revealed that Gas5 exerts its function by regulating RNA metabolism and translation. Our study highlights the importance of MS-regulated lncRNA in anxiety and spatial memory.

Understanding Cognitive Behavioral Therapy for Psychosis Through the Predictive Coding Framework.

Psychological treatments for persecutory delusions, particularly cognitive behavioral therapy for psychosis, are efficacious; however, mechanistic theories explaining why they work rarely bridge to the level of cognitive neuroscience. Predictive coding, a general brain processing theory rooted in cognitive and computational neuroscience, has increasing experimental support for explaining symptoms of psychosis, including the formation and maintenance of delusions. Here, we describe recent advances in cognitive behavioral therapy for psychosis-based psychotherapy for persecutory delusions, which targets specific psychological processes at the computational level of information processing. We outline how Bayesian learning models employed in predictive coding are superior to simple associative learning models for understanding the impact of cognitive behavioral interventions at the algorithmic level. We review hierarchical predictive coding as an account of belief updating rooted in prediction error signaling. We examine how this process is abnormal in psychotic disorders, garnering noisy sensory data that is made sense of through the development of overly strong delusional priors. We argue that effective cognitive behavioral therapy for psychosis systematically targets the way sensory data are selected, experienced, and interpreted, thus allowing for the strengthening of alternative beliefs. Finally, future directions based on these arguments are discussed.

Delusions are distressing and disabling psychiatric symptoms. Cognitive behavioral therapy for psychosis (CBTp) is the leading psychotherapeutic approach for treating delusions. Predictive coding is a contemporary cognitive neuroscience framework that is increasingly being used to explain mechanisms of delusions. In this article, we attempt to integrate CBTp within the predictive coding framework, outlining how effective CBTp techniques impact aspects of the predictive coding model to contribute to cutting-edge treatment and cognitive neuroscience research on delusions and inform recommendations for treatment advancement.

tRNA-derived RNA fragment, tRF-18-8R6546D2, promotes pancreatic adenocarcinoma progression by directly targeting ASCL2.

Pancreatic adenocarcinoma (PAAD) is a life-threatening cancer. Exploring new diagnosis and treatment targets helps improve its prognosis. tRNA-derived small non-coding RNAs (tsRNAs) are a novel type of gene expression regulators and their dysregulation is closely related to many human cancers. Yet the expression and functions of tsRNAs in PAAD are not well understood. Our study used RNA sequencing to identify tsRNA expression profiles in PAAD cells cultured in no or high glucose media and found tRF-18-8R6546D2 was an uncharacterized tsRNA, which has significantly high expression in PAAD cells and tissues. Clinically, tRF-18-8R6546D2 is linked to poor prognosis in PAAD patients and can be used to distinguish them from healthy populations. Functionally, in vitro and vivo, tRF-18-8R6546D2 over-expression promoted PAAD cell proliferation, migration and invasion, inhibited apoptosis, whereas tRF-18-8R6546D2 knock-down showed opposite effects. Mechanistically, tRF-18-8R6546D2 promoted PAAD malignancy partly by directly silencing ASCL2 and further regulating its downstream genes such as MYC and CASP3. These findings show that tRF-18-8R6546D2 is a novel oncogenic factor and can be a promising diagnostic or prognostic biomarker and therapeutic target for PAAD.

A low-activity cortical network selectively encodes syntax.

Syntax, the abstract structure of language, is a hallmark of human cognition. Despite its importance, its neural underpinnings remain obscured by inherent limitations of non-invasive brain measures and a near total focus on comprehension paradigms. Here, we address these limitations with high-resolution neurosurgical recordings (electrocorticography) and a controlled sentence production experiment. We uncover three syntactic networks that are broadly distributed across traditional language regions, but with focal concentrations in middle and inferior frontal gyri. In contrast to previous findings from comprehension studies, these networks process syntax mostly to the exclusion of words and meaning, supporting a cognitive architecture with a distinct syntactic system. Most strikingly, our data reveal an unexpected property of syntax: it is encoded independent of neural activity levels. We propose that this "low-activity coding" scheme represents a novel mechanism for encoding information, reserved for higher-order cognition more broadly.

Deletion of miR-146a enhances therapeutic protein restoration in model of dystrophin exon skipping.

Duchenne muscular dystrophy (DMD) is a progressive muscle disease caused by the absence of dystrophin protein. One current DMD therapeutic strategy, exon skipping, produces a truncated dystrophin isoform using phosphorodiamidate morpholino oligomers (PMOs). However, the potential of exon skipping therapeutics has not been fully realized as increases in dystrophin protein have been minimal in clinical trials. Here, we investigate how miR-146a-5p, which is highly elevated in dystrophic muscle, impacts dystrophin protein levels. We find inflammation strongly induces miR-146a in dystrophic, but not wild-type myotubes. Bioinformatics analysis reveals that the dystrophin 3' UTR harbors a miR-146a binding site, and subsequent luciferase assays demonstrate miR-146a binding inhibits dystrophin translation. In dystrophin-null mdx52 mice, co-injection of miR-146a reduces dystrophin restoration by an exon 51 skipping PMO. To directly investigate how miR-146a impacts therapeutic dystrophin rescue, we generated mdx52 with body-wide miR-146a deletion (146aX). Administration of an exon skipping PMO via intramuscular or intravenous injection markedly increases dystrophin protein levels in 146aX vs. mdx52 muscles while skipped dystrophin transcript levels are unchanged supporting a post-transcriptional mechanism of action. Together, these data show that miR-146a expression opposes therapeutic dystrophin restoration, suggesting miR-146a inhibition warrants further research as a potential DMD exon skipping co-therapy.

CircHTT(2,3,4,5,6) - co-evolving with the HTT CAG-repeat tract - modulates Huntington's disease phenotypes.

Circular RNA (circRNA) molecules have critical functions during brain development and in brain-related disorders. Here, we identified and validated a circRNA, circHTT(2,3,4,5,6), stemming from the Huntington's disease (HD) gene locus that is most abundant in the central nervous system (CNS). We uncovered its evolutionary conservation in diverse mammalian species, and a correlation between circHTT(2,3,4,5,6) levels and the length of the CAG-repeat tract in exon-1 of HTT in human and mouse HD model systems. The mouse orthologue, circHtt(2,3,4,5,6), is expressed during embryogenesis, increases during nervous system development, and is aberrantly upregulated in the presence of the expanded CAG tract. While an IRES-like motif was predicted in circH TT (2,3,4,5,6), the circRNA does not appear to be translated in adult mouse brain tissue. Nonetheless, a modest, but consistent fraction of circHtt(2,3,4,5,6) associates with the 40S ribosomal subunit, suggesting a possible role in the regulation of protein translation. Finally, circHtt(2,3,4,5,6) overexpression experiments in HD-relevant STHdh striatal cells revealed its ability to modulate CAG expansion-driven cellular defects in cell-to-substrate adhesion, thus uncovering an unconventional modifier of HD pathology.

Development and evaluation of a disulfidoptosis-related lncRNA index for prognostication in clear cell renal cell carcinoma.

Background: This study introduces a novel prognostic tool, the Disulfidoptosis-Related lncRNA Index (DRLI), integrating the molecular signatures of disulfidoptosis and long non-coding RNAs (lncRNAs) with the cellular heterogeneity of the tumor microenvironment, to predict clinical outcomes in patients with clear cell renal cell carcinoma (ccRCC). Methods: We analyzed 530 tumor and 72 normal samples from The Cancer Genome Atlas (TCGA), employing k-means clustering based on disulfidoptosis-associated gene expression to stratify ccRCC samples into prognostic groups. lncRNAs correlated with disulfidoptosis were identified and used to construct the DRLI, which was validated by Kaplan-Meier and receiver operating characteristic curves. We utilized single-cell deconvolution analysis to estimate the proportion of immune cell types within the tumor microenvironment, while the ESTIMATE and TIDE algorithms were employed to assess immune infiltration and potential response to immunotherapy. Results: The Disulfidoptosis-Related lncRNA Index (DRLI) effectively stratified ccRCC patients into high and low-risk groups, significantly impacting survival outcomes (P < 0.001). High-risk patients, marked by a unique lncRNA profile associated with disulfidoptosis, faced worse prognoses. Single-cell analysis revealed marked tumor microenvironment heterogeneity, especially in immune cell makeup, correlating with patient risk levels. In prognostic predictions, DRLI outperformed traditional clinical indicators, achieving AUC values of 0.779, 0.757, and 0.779 for 1-year, 3-year, and 5-year survival in the training set, and 0.746, 0.734, and 0.750 in the validation set. Notably, while the constructed nomogram showed exceptional predictive capability for short-term prognosis (AUC = 0.877), the DRLI displayed remarkable long-term predictive accuracy, with its AUC value reaching 0.823 for 10-year survival, closely approaching the nomogram's performance. Conclusions: The study introduces the DRLI as a groundbreaking molecular stratification tool for ccRCC, enhancing prognostic precision and potentially guiding personalized treatment strategies. This advancement is particularly significant in the context of long-term survival predictions. Our findings also elucidate the complex interplay between disulfidoptosis, lncRNAs, and the immune microenvironment in ccRCC, offering a comprehensive perspective on its pathogenesis and progression. The DRLI and the nomogram together represent significant strides in ccRCC research, highlighting the importance of molecular-based assessments in predicting patient outcomes.

Genome-wide characterization of drought-responsive long non-coding RNAs in sorghum (Sorghum bicolor).

Drought stress strongly affects crop yield. Although knowledge of long non-coding RNAs (lncRNAs) has been updated continuously and rapidly, information about lncRNAs in drought resistance regulation is extremely limited in sorghum. Here, lncRNA-sequencing was performed with seedlings of a sorghum cultivar (Jinza29) under three water control treatments to investigate the mechanism of lncRNAs responsible for drought resistance in sorghum. A total of 377 differentially expressed lncRNAs (DElncRNAs) were identified. We also predicted 4322 and 2827 transcripts as potential cis-target and trans-target genes for drought-responsive lncRNAs, respectively. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that those target genes exhibited marked enrichment into "oxidoreductase activity", "signal transducer activity", "DNA repair", "photosynthesis", "glutathione metabolism", and "phenylpropanoid biosynthesis" and other terms associated with abiotic stress resistance. Moreover, several lncRNAs were estimated to modulate the expression of other genes related to stress response and photosynthetic carbon metabolism. Additionally, we found 107 DElncRNAs that might be candidate target mimics for 56 miRNAs. LncRNAs play important roles in drought adaptation of sorghum through interacting with protein-encoding genes. The obtained results provided novel insights into the biological characteristics of lncRNAs and offered potential regulatory factors for genetically enhancing drought resistance in sorghum.

Unsupervised denoising of the non-invasive fetal electrocardiogram with sparse domain Kalman filtering and vectorcardiographic loop alignment.

Even though the electrocardiogram (ECG) has potential to be used as a monitoring or diagnostic tool for fetuses, the use of non-invasive fetal ECG is complicated by relatively high amounts of noise and fetal movement during the measurement. Moreover, machine learning-based solutions to this problem struggle with the lack of clean reference data, which is difficult to obtain. To solve these problems, this work aims to incorporate fetal rotation correction with electrocardiogram denoising into a single unsupervised end-to-end trainable method. This method uses the vectorcardiogram (VCG), a 3-dimensional representation of the ECG, as an input and extends the previously introduced Kalman-LISTA method with a Kalman filter for the estimation of fetal rotation, applying denoising to the rotation-corrected VCG. The resulting method was shown to outperform denoising auto-encoders by more than 3dB while achieving a rotation tracking error of less than 33°. Furthermore, the method was shown to be robust to a difference in signal to noise ratio between electrocardiographic leads and different rotational velocities. Future work should aim at improving the method's generalizability and evaluation of the method's value in research and clinical use. This value might not only derive from the denoised fetal ECG, but from the method's objective measure for fetal rotation as well due to it's potential for early detection of fetal complications.

[Viroids : infectious non coding RNAs]. / Les viroïdes : des ARN infectieux non codants.

Viroids are the smallest non-coding infectious RNAs (between 246 and 401 nucleotides) known to be highly structured and replicate autonomously in the host plants. Although they do not encode any peptides, viroids induce visible symptoms in susceptible host plants. This article provides an overview of their physical and biological properties, the diseases they cause and their significance for the plants. The mechanisms underlying the expression of symptoms in host plants, their detection and various strategies employed for diseases prevention are also developed.

Epigenetic programming of chicken germ cells: a comparative review.

Chicken embryos serve as an important model for investigating germ cells due to their ease of accessibility and manipulation within the egg. Understanding the development of germ cells is particularly crucial, as they are the only cell types capable of transmitting genetic information to the next generation. Therefore, gene expression regulation in germ cells is important for genomic function. Epigenetic programming is a crucial biological process for the regulation of gene expression without altering the genome sequence. Although epigenetic programming is evolutionarily conserved, several differences between chickens and mammals have been revealed. In this review, we compared the epigenetic regulation of germ cells in chickens and mammals (mainly mice as a representative species). In mammals, migrating primordial germ cells (precursors for germ cells [PGCs]) undergo global DNA demethylation and persist until sexual differentiation, while in chickens, DNA is demethylated until reaching the gonad but remethylated when sexually differentiated. Prospermatogonia is methylated at the onset of mitotic arrest in mammals, while DNA is demethylated at mitotic arrest in chickens. Furthermore, genomic imprinting and inactivation of sex chromosomes are differentially regulated through DNA methylation in chickens and mammals. Chickens and mammals exhibit different patterns of histone modifications during germ cell development, and non-coding RNA, which is not involved in PGC differentiation in mice, plays an important role in chicken PGC development. Additionally, several chicken-specific non-coding RNAs have been identified. In conclusion, we summarized current knowledge of epigenetic gene regulation of chicken germ cells, comparing that of mammals, and highlighted notable differences between them.

Global research states and trends of micro RNA in irritable bowel syndrome: a bibliometric analysis.

Irritable bowel syndrome (IBS) is a common chronic gastrointestinal disorder, but its diagnosis and treatment remain obscure. Non-coding RNAs (ncRNAs), as potential biomarkers, have attracted increasing attention in digestive diseases. Here, we present a comprehensive research status, development trends, and valuable insights in this subject area. The literature search was performed using Web of Science Core Collection. VOSviewer 1.6.20, Citespace 6.2.R4, and Microsoft Excel 2021 were used for bibliometric analysis. A total of 124 articles were included in the analysis. Overall, publication patterns fluctuated. Globally, People's Republic of China, the USA, and Germany were the top three contributors of publications. Guangzhou University of Chinese Medicine, University of California, Mayo Clinic, and University of California, Los Angeles contributed the highest number of publications. The pathways and specific mechanisms by which ncRNAs regulate transcription and translation and thus regulate the pathophysiological processes of IBS are the main research hotspots in this field. We found that microRNA (miRNAs) are intricately involved in the regulation of key pathologies such as viscera sensitivity, intestinal permeability, intestinal mucosal barrier, immunoinflammatory response, and brain-gut axis in the IBS, and these topics have garnered significant attention in research community. Notably, microecological disorders are also associated with IBS pathogenesis, and ncRNA may play an important role in the interactions between host and intestinal flora. This is the first bibliometric study to comprehensively summarize the research hotspots and trends related to IBS and ncRNAs (especially miRNAs). Our findings will help understand the role of ncRNAs in IBS and provide guidance to future studies.

"Using network analysis modularity to group health code systems and decrease dimensionality in machine learning models".

Background: Machine learning (ML) prediction models in healthcare and pharmacy-related research face challenges with encoding high-dimensional Healthcare Coding Systems (HCSs) such as ICD, ATC, and DRG codes, given the trade-off between reducing model dimensionality and minimizing information loss. Objectives: To investigate using Network Analysis modularity as a method to group HCSs to improve encoding in ML models. Methods: The MIMIC-III dataset was utilized to create a multimorbidity network in which ICD-9 codes are the nodes and the edges are the number of patients sharing the same ICD-9 code pairs. A modularity detection algorithm was applied using different resolution thresholds to generate 6 sets of modules. The impact of four grouping strategies on the performance of predicting 90-day Intensive Care Unit readmissions was assessed. The grouping strategies compared: 1) binary encoding of codes, 2) encoding codes grouped by network modules, 3) grouping codes to the highest level of ICD-9 hierarchy, and 4) grouping using the single-level Clinical Classification Software (CCS). The same methodology was also applied to encode DRG codes but limiting the comparison to a single modularity threshold to binary encoding.The performance was assessed using Logistic Regression, Support Vector Machine with a non-linear kernel, and Gradient Boosting Machines algorithms. Accuracy, Precision, Recall, AUC, and F1-score with 95% confidence intervals were reported. Results: Models utilized modularity encoding outperformed ungrouped codes binary encoding models. The accuracy improved across all algorithms ranging from 0.736 to 0.78 for the modularity encoding, to 0.727 to 0.779 for binary encoding. AUC, recall, and precision also improved across almost all algorithms. In comparison with other grouping approaches, modularity encoding generally showed slightly higher performance in AUC, ranging from 0.813 to 0.837, and precision, ranging from 0.752 to 0.782. Conclusions: Modularity encoding enhances the performance of ML models in pharmacy research by effectively reducing dimensionality and retaining necessary information. Across the three algorithms used, models utilizing modularity encoding showed superior or comparable performance to other encoding approaches. Modularity encoding introduces other advantages such as it can be used for both hierarchical and non-hierarchical HCSs, the approach is clinically relevant, and can enhance ML models' clinical interpretation. A Python package has been developed to facilitate the use of the approach for future research.