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MicroRNAs can interfere with protein function by suppressing their messenger RNA translation or the synthesis of its related factors. The function of brain-derived neurotrophic factor (BDNF) is essential to the proper formation and function of the nervous system and is seen to be regulated by many microRNAs. However, understanding how microRNAs influence BDNF actions within cells requires a wider comprehension of their integrative regulatory mechanisms. Aim: In this literature review, we have synthesized the evidence of microRNA regulation on BDNF in cells and tissues, and provided an analytical discussion about direct and indirect mechanisms that appeared to be involved in BDNF regulation by microRNAs. Methods: Searches were conducted on PubMed.gov using the terms "BDNF" AND "MicroRNA" and "brain-derived neurotrophic factor" AND "MicroRNA", updated on 1 September 2023. Papers without open access were requested from the authors. One hundred and seventy-one papers were included for review and discussion. Results and Discussion: The local regulation of BDNF by microRNAs involves a complex interaction between a series of microRNAs with target proteins that can either inhibit or enhance BDNF expression, at the core of cell metabolism. Therefore, understanding this homeostatic balance provides resources for the future development of vector-delivery-based therapies for the neuroprotective effects of BDNF. [ABSTRACT FROM AUTHOR]

In this paper, we measured B cell function in elderly healthy individuals (EH) and in elderly patients with Type-2 Diabetes Mellitus (T2DM, ET2DM), which are treatment-naive, as compared to healthy young (YH) individuals. Results show a higher serum inflammatory status of elderly versus young individuals, and especially of ET2DM versus EH. This status is associated with a reduced response to the seasonal influenza vaccine and with increased frequencies of the circulating pro-inflammatory B cell subset called Double Negative (DN) B cells. B cells from ET2DM patients are not only more inflammatory but also hyper-metabolic as compared to those from EH controls. The results herein are to our knowledge the first to show that T2DM superimposed on aging further increases systemic and B cell intrinsic inflammation, as well as dysfunctional humoral immunity. Our findings confirm and extend our previously published findings showing that inflammatory B cells are metabolically supported. [ABSTRACT FROM AUTHOR]

The 80+ existing autoimmune disorders (ADs) affect billions with little prevention or treatment options, except for temporary symptomatic management, leading to enormous human suffering and a monumental financial burden. The autoantibodies formed in most ADs have been identified, allowing the development of novel anti-idiotypic antibodies to mute the autoantibodies using vaccines. Nucleoside vaccines have been successfully tested as antigen-specific immunotherapies (ASI), with mRNA technology offering multi-epitope targeting to mute multiple autoantibodies. This paper proposes using mRNA technology to produce anti-idiotypic antibodies with broad effectiveness in preventing and treating them. This paper delves into the state-of-the-art mRNA design strategies used to develop novel ASIs by selecting appropriate T cell and B cell epitopes to generate anti-idiotypic antibodies. The low cost and fast development of mRNA vaccines make this technology the most affordable for the global control of ADs. [ABSTRACT FROM AUTHOR]

Oral submucous fibrosis (OSF) affecting populations is considered a public health issue in South/Southeast Asia. The purpose of this study was to analyze the scientometric characteristics and research trends of OSF. All the papers on OSF were comprehensively retrieved from the Scopus database. Regional comparison (India versus outside of India) and chronological comparison (before 2015 versus after 2015) were performed. Among all the 1357 papers on OSF, 930 (68.5%) were from India. In India, biology research on antioxidant, oxidative stress, angiogenesis, and extracellular matrix were distinctive keywords. Risk factors of smokeless tobacco and gutkha and the roles of saliva and blood sampling were also distinctive keywords in India. In outside of India, biology research on myofibroblast, alpha smooth muscle actin, microRNA, long untranslated RNA, and protein p53 were distinctive keywords. The trend of biology research on connective tissue, genotype, genetic predisposition, messenger RNA, and cytology before 2015 has changed to research on myofibroblast, biological marker, microRNA, epithelial mesenchymal transition, extracellular matrix, and oxidative stress after 2015. The trend of clinical aspects of surgery and mouth hygiene before 2015 has changed to the aspects of adverse event/effects, complication, and quality of life after 2015. This scientometric study elucidated the current scenario and research trends of OSF, and would help in improving in reciprocal collaboration and communication for this disease control in South/Southeast Asia. [ABSTRACT FROM AUTHOR]

N4-acetylcysteine (ac4C) is a chemical modification in mRNAs that alters the structure and function of mRNA by adding an acetyl group to the N4 position of cytosine. Researchers have shown that ac4C is closely associated with the occurrence and development of various cancers. Therefore, accurate prediction of ac4C modification sites on human mRNA is crucial for revealing its role in diseases and developing new diagnostic and therapeutic strategies. However, existing deep learning models still have limitations in prediction accuracy and generalization ability, which restrict their effectiveness in handling complex biological sequence data. This paper introduces a deep learning-based model, STM-ac4C, for predicting ac4C modification sites on human mRNA. The model combines the advantages of selective kernel convolution, temporal convolutional networks, and multi-head self-attention mechanisms to effectively extract and integrate multi-level features of RNA sequences, thereby achieving high-precision prediction of ac4C sites. On the independent test dataset, STM-ac4C showed improvements of 1.81%, 3.5%, and 0.37% in accuracy, Matthews correlation coefficient, and area under the curve, respectively, compared to the existing state-of-the-art technologies. Moreover, its performance on additional balanced and imbalanced datasets also confirmed the model's robustness and generalization ability. Various experimental results indicate that STM-ac4C outperforms existing methods in predictive performance. In summary, STM-ac4C excels in predicting ac4C modification sites on human mRNA, providing a powerful new tool for a deeper understanding of the biological significance of mRNA modifications and cancer treatment. Additionally, the model reveals key sequence features that influence the prediction of ac4C sites through sequence region impact analysis, offering new perspectives for future research. [ABSTRACT FROM AUTHOR]

Abiotic stresses occur more often in combination than alone under regular field conditions limiting in more severe way crop production. Stress recognition in plants primarily occurs in the plasma membrane, modification of which is necessary to maintain homeostasis in response to it. It is known that lipid transport proteins (ns-LTPs) participate in modification of the lipidome of cell membranes. Representative of this group, ns-LTP2.8, may be involved in the reaction to abiotic stress of germinating barley plants by mediating the intracellular transport of hydrophobic particles, such as lipids, helping to maintain homeostasis. The ns-LTP2.8 protein was selected for analysis due to its ability to transport not only linear hydrophobic molecules but also compounds with a more complex spatial structure. Moreover, ns-LTP2.8 has been qualified as a member of pathogenesis-related proteins, which makes it particularly important in relation to its high allergenic potential. This paper demonstrates for the first time the influence of various abiotic stresses acting separately as well as in their combinations on the change in the ns-LTP2.8 transcript, ns-LTP2.8 protein and total soluble protein content in the embryonal axes of germinating spring barley genotypes with different ns-LTP2.8 allelic forms and stress tolerance. Tissue localization of ns-LTP2.8 transcript as well as ns-LTP2.8 protein were also examined. Although the impact of abiotic stresses on the regulation of gene transcription and translation processes remains not fully recognized, in this work we managed to demonstrate different impact on applied stresses on the fundamental cellular processes in very little studied tissue of the embryonal axis of barley. [ABSTRACT FROM AUTHOR]

Epigenetic regulation has been thoroughly investigated in recent years and has emerged as an important aspect of chronic lymphocytic leukemia (CLL) biology. Characteristic aberrant features such as methylation patterns and global DNA hypomethylation were the early findings of the research during the last decades. The investigation in this field led to the identification of a large number of genes where methylation features correlated with important clinical and laboratory parameters. Gene-specific analyses investigated methylation in the gene body enhancer regions as well as promoter regions. The findings included genes and proteins involved in key pathways that play central roles in the pathophysiology of the disease. Τhe application of these findings beyond the theoretical understanding can not only lead to the creation of prognostic and predictive models and scores but also to the design of novel therapeutic agents. The following is a review focusing on the present knowledge about single gene/gene promoter methylation or mRNA expression in CLL cases as well as records of older data that have been published in past papers. [ABSTRACT FROM AUTHOR]

Simple Summary: Cachexia and malnutrition are characteristic of oncology patients, including those with head and neck cancer (HNSCC). Fifty-six patients diagnosed with HNSCC (study group) were included in the study, and seventy patients constituted the control group. We used standardized questionnaires to assess nutritional status and cachexia. In our study, we evaluated whether ghrelin, titin, and irisin can be a useful diagnostic marker, a prognostic marker of cancer development in these patients, and whether the levels of these proteins depend on the nutritional status of the patients. We used molecular biology methods to evaluate the concentration of the selected proteins. The results indicate that the levels of ghrelin, titin, and irisin correlate well with the nutritional and cachexia status of patients with HNSCC. Until now, to our best knowledge, this is the first study assessing the changes in concentrations of these proteins in this type of cancer. The goal of this paper was the evaluation of the changes in the expression profile of irisin, ghrelin, and titin in the carcinoma tissue and in the blood of patients with head and neck squamous cell carcinoma (HNSCC), including determining the profile of their expression in relation to patient nutrition. The study included 56 patients with diagnosed squamous cell carcinoma of HNSCC in the T3 and T4 stages of the disease. Healthy control tissue specimens were collected from an area 10 mm outside the histologically negative margin. In turn, the blood and serum from the control group came from healthy volunteers treated for non-oncologic reasons (n = 70). The molecular analysis allowed us to determine the profile of irisin, ghrelin, and titin methylation, evaluate their expression on the level of mRNA (quantitative Reverse Transcription Polymerase Chain Reaction; qRT-PCR) and protein (Enzyme-Linked Immunosorbent Assay Reaction; ELISA) in the carcinoma tissue and the margin of healthy tissue, as well as in serum of patients in the study and control groups. At the start of our observations, a Body Mass Index (BMI) < 18.5 was noted in 42 of the patients, while six months after the treatment a BMI < 18.5 was noted in 29 patients. We also noted a decrease in the expression of irisin, ghrelin, and titin both on the level of mRNA and protein, as well as a potential regulation of their expression via DNA methylation. There is no convincing evidence that the proteins assayed in the present work are specific with regard to HNSSC. [ABSTRACT FROM AUTHOR]

Thousands of long-distance mobile mRNAs were identified from different grafting systems, based on high-throughput sequencing technology. Moreover, the long-distance delivery of RNAs was proved to involve multiple mechanisms. Here, we analyzed the homology, motif, and tRNA-like structure (TLS) of long-distance mobile mRNAs identified by RNA-seq as well as the RNA-binding protein (RBP) in nine grafting combinations including Arabidopsis thaliana, Vitis vinifera, Cucumis sativus, Citrullus lanatus, Nicotiana benthamiana, Malus domestica, Pyrus spp., Glycine max and Phaseolus vulgaris. Although several mRNAs were found to be shared in herbaceous, woody, and related species, the vast majority of long-distance mobile mRNAs were species-specific. Four non-specific movement-related motifs were identified, while the TLS was not necessary for mRNA long distance mobility. In addition, we found that RBPs were conserved among herbaceous and woody plants as well as related species. This paper reports a further in-depth analysis of the endogenous mechanisms by which the species-specific transportable mRNAs were selected by bioinformatics, in order to provide insights for future research on long-distance mobile mRNAs. [ABSTRACT FROM AUTHOR]

In 2023, Katalin Karikó and Drew Weissman were awarded the Nobel Prize in Physiology or Medicine for their nucleoside base modifications research that later enabled mRNA vaccine development against COVID-19. This paper briefly reviews these achievements in the context of the development of mRNA technology and its enormous potential for medicine in the prevention of various infectious diseases and cancer treatment, including personalised therapies. It is beyond any doubt that discoveries made by Karikó and Weissman were pivotal in overcoming one of the major hurdles in the practical application of mRNA molecules, i.e., the recognition of exogenous mRNAs by endosomal Toll-like receptors and downstream innate immune response, ultimately leading to the decreased translational activity of delivered mRNA and its degradation. Although the Nobel Prize for Karikó and Weissman is fully justified, it must be stressed that mRNA technology would never unfold its potential for public health without a collective scientific effort encompassing over 40 years of research. [ABSTRACT FROM AUTHOR]

mRNA-based gene editing platforms have tremendous promise in the treatment of genetic diseases. However, for this potential to be realized in vivo, these nucleic acid cargos must be delivered safely and effectively to cells of interest. Ionizable lipid nanoparticles (LNPs), the most clinically advanced non-viral RNA delivery system, have been well-studied for the delivery of mRNA but have not been systematically optimized for the delivery of mRNA-based CRISPR-Cas9 platforms. In this study, we investigated the effect of microfluidic and lipid excipient parameters on LNP gene editing efficacy. Through in vitro screening in liver cells, we discovered distinct trends in delivery based on phospholipid, cholesterol, and lipid-PEG structure in LNP formulations. Combination of top-performing lipid excipients produced an LNP formulation that resulted in 3-fold greater gene editing in vitro and facilitated 3-fold greater reduction of a therapeutically-relevant protein in vivo relative to the unoptimized LNP formulation. Thus, systematic optimization of LNP formulation parameters revealed a novel LNP formulation that has strong potential for delivery of gene editors to the liver to treat metabolic disease. [ABSTRACT FROM AUTHOR]

This document is a letter addressing errors in a published paper on van der Hoeve's syndrome, a form of osteogenesis imperfecta (OI). The authors of the paper incorrectly assumed that a single-nucleotide deletion in the COL1A1 gene would result in a stable mutant mRNA and a truncated protein. They also presented inaccurate descriptions of the causative variant and the classification of OI types. The letter corrects these errors and provides the appropriate terminology and classification. The document emphasizes the need for accurate scientific reporting and adherence to current practices in the field. [Extracted from the article]

For sequencing-based spatial transcriptomics data, the gene-spot count matrix is highly sparse. This feature is similar to scRNA-seq. The goal of this paper is to identify whether there exist genes that are frequently under-detected in Visium compared to bulk RNA-seq, and the underlying potential mechanism of under-detection in Visium. We collected paired Visium and bulk RNA-seq data for 28 human samples and 19 mouse samples, which covered diverse tissue sources. We compared the two data types and observed that there indeed exists a collection of genes frequently under-detected in Visium compared to bulk RNA-seq. We performed a motif search to examine the last 350 bp of the frequently under-detected genes, and we observed that the poly (T) motif was significantly enriched in genes identified from both human and mouse data, which matches with our previous finding about frequently under-detected genes in scRNA-seq. We hypothesized that the poly (T) motif may be able to form a hairpin structure with the poly (A) tails of their mRNA transcripts, making it difficult for their mRNA transcripts to be captured during Visium library preparation. [ABSTRACT FROM AUTHOR]

• We proposed a novel computational method for detect RNA m6A sites. • The proposed method is of powerful ability to predict RNA m6A sites in multiple species or tissues, and of across species or tissue ability. • A user-friendly webserver facilitates recognition of RNA m6A for biologists. N6-methyladenosine (m6A) is the most prevalent, abundant, and conserved internal modification in the eukaryotic messenger RNA (mRNAs) and plays a crucial role in the cellular process. Although more than ten methods were developed for m6A detection over the past decades, there were rooms left to improve the predictive accuracy and the efficiency. In this paper, we proposed an improved method for predicting m6A modification sites, which was based on bi-directional gated recurrent unit (Bi-GRU) and convolutional neural networks (CNN), called Deepm6A-MT. The Deepm6A-MT has two input channels. One is to use an embedding layer followed by the Bi-GRU and then by the CNN, and another is to use one-hot encoding, dinucleotide one-hot encoding, and nucleotide chemical property codes. We trained and evaluated the Deepm6A-MT both by the 5-fold cross-validation and the independent test. The empirical tests showed that the Deepm6A-MT achieved the state of the art performance. In addition, we also conducted the cross-species and the cross-tissues tests to further verify the Deepm6A-MT for effectiveness and efficiency. Finally, for the convenience of academic research, we deployed the Deepm6A-MT to the web server, which is accessed at the URL http://www.biolscience.cn/Deepm6A-MT/. [ABSTRACT FROM AUTHOR]

A global shift to bivalent mRNA vaccines is ongoing to counterbalance the diminishing effectiveness of the original monovalent vaccines due to the evolution of SARS-CoV-2 variants, yet substantial variation in the bivalent vaccine effectiveness (VE) exists across studies and a complete picture is lacking. We searched papers evaluating absolute or relative effectiveness of SARS-CoV-2 BA.1 type or BA.4/5 type bivalent mRNA vaccines on eight publication databases published from September 1st, 2022, to November 8th, 2023. Pooled VE against Omicron-associated infection and severe events (hospitalization and/or death) was estimated in reference to unvaccinated, ≥2 original monovalent doses, and ≥ 3 original monovalent doses. From 630 citations identified, 28 studies were included, involving 55,393,303 individuals. Bivalent boosters demonstrated higher effectiveness against symptomatic or any infection for all ages combined, with an absolute VE of 53.5 % (95 % CI: –22.2–82.3 %) when compared to unvaccinated and relative VE of 30.8 % (95 % CI: 22.5–38.2 %) and 28.4 % (95 % CI: 10.2–42.9 %) when compared to ≥ 2 and ≥ 3 original monovalent doses, respectively. The corresponding VE estimates for adults ≥ 60 years old were 22.5 % (95 % CI: 16.8–39.8 %), 31.4 % (95 % CI: 27.7–35.0 %), and 30.6 % (95 % CI: −13.2–57.5 %). Pooled bivalent VE estimates against severe events were higher, 72.9 % (95 % CI: 60.5–82.4 %), 57.6 % (95 % CI: 42.4–68.8 %), and 62.1 % (95 % CI: 54.6–68.3 %) for all ages, and 72.0 % (95 % CI: 51.4–83.9 %), 63.4 % (95 % CI: 41.0–77.3 %), and 60.7 % (95 % CI: 52.4–67.6 %) for adults ≥ 60 years old, compared to unvaccinated, ≥2 original monovalent doses, and ≥ 3 original monovalent doses, respectively. The bivalent boosters demonstrated superior protection against severe outcomes than the original monovalent boosters across age groups, highlighting the critical need for improving vaccine coverage, especially among the vulnerable older subpopulation. [ABSTRACT FROM AUTHOR]

The World Health Organization (WHO) set up the messenger ribonucleic acid (mRNA) technology transfer programme in June 2021 with a development hub in South Africa and 15 partner vaccine producers in middle-income countries. The goal was to support the sustainable development of and access to life-saving vaccines for people in these countries as a means to enhance epidemic preparedness and global public health. This initiative aims to build resilience and strengthen local vaccine research, and development and manufacturing capacity in different regions of the world, especially those areas that could not access coronavirus disease 2019 (COVID-19) vaccines in a timely way. This paper outlines the current global vaccine market and summarizes the findings of a case study on the mRNA technology transfer programme conducted from November 2022 to May 2023. The study was guided by the vision of the WHO Council on the Economics of Health for All to build an economy for health using its four work streams of value, finance, innovation and capacity. Based on the findings of the study, we offer a mission-oriented policy framework to support the mRNA technology transfer programme as a pilot for transformative change towards an ecosystem for health innovation for the common good. Parts of this vision have already been incorporated into the governance of the mRNA technology transfer programme, while other aspects, especially the common good approach, still need to be applied to achieve the goals of the programme. [ABSTRACT FROM AUTHOR]

INTRODUCTION Cigarette smoking is one of the most important causes of COPD and could induce the apoptosis of pulmonary microvascular endothelial cells (PMVECs). The conditional knockout of LRG1 from endothelial cells reduced emphysema in mice. However, the mechanism of the deletion of LRG1 from endothelial cells rescued by cigarette smoke (CS) induced emphysema remains unclear. This research aimed to demonstrate whether LRG1 promotes the apoptosis of PMVECs through KLK10 in COPD. METHODS Nineteen patients were divided into three groups: control non-COPD (n=7), smoker non-COPD (n=7), and COPD (n=5). The emphysema mouse model defined as the CS exposure group was induced by CS exposure plus cigarette smoke extract (CSE) intraperitoneal injection for 28 days. Primary PMVECs were isolated from the mouse by magnetic bead sorting method via CD31-Dynabeads. Apoptosis was detected by western blot and flow cytometry. RESULTS LRG1 was increased in lung tissue of COPD patients and CS exposure mice, and CSE-induced PMVECs apoptosis model. KLK10 was over-expressed in lung tissue of COPD patients and CS exposure mice, and CSE-induced PMVECs apoptosis model. LRG1 promoted apoptosis in PMVECs. LRG1 knockdown reversed CSE-induced apoptosis in PMVECs. The mRNA and protein expression of KLK10 were increased after over-expressed LRG1 in PMVECs isolated from mice. Similarly, both the mRNA and protein levels of KLK10 were decreased after LRG1 knockdown in PMVECs. The result of co-immunoprecipitation revealed a protein-protein interaction between LRG1 and KLK10 in PMVECs. KLK10 promoted apoptosis via the down-regulation of Bcl-2/Bax in PMVECs. KLK10 knockdown could reverse CSE-induced apoptosis in PMVECs. CONCLUSIONS LRG1 promotes apoptosis via up-regulation of KLK10 in PMVECs isolated from mice. KLK10 promotes apoptosis via the down-regulation of Bcl-2/Bax in PMVECs. There was a direct protein-protein interaction between LRG1 and KLK10 in PMVECs. Our novel findings provide insights into the understanding of LRG1/KLK10 function as a potential molecule in COPD. [ABSTRACT FROM AUTHOR]

The versatility, rapid development, and ease of production scalability of mRNA therapeutics have placed them at the forefront of biopharmaceutical research. However, despite their vast potential to treat diseases, their novelty comes with unsolved analytical challenges. A key challenge in ensuring sample purity has been monitoring residual, immunostimulatory dsRNA impurities generated during the in vitro transcription of mRNA. Here, we present a method that combines an enzyme, S1 nuclease, to identify and isolate dsRNA from an mRNA sample with a microfluidic electrophoresis analytical platform to characterize the impurity. After the method was developed and optimized, it was tested with clinically relevant, pseudouridine-modified 700 and 1800 bp dsRNA and 818–4451 nt mRNA samples. While the treatment impacted the magnitude of the fluorescent signal used to analyze the samples due to the interference of the buffer with the labeling of the sample, this signal loss was mitigated by 8.8× via treatment optimization. In addition, despite the mRNA concentration being up to 400× greater than that of the dsRNA, under every condition, there was a complete disappearance of the main mRNA peak. While the mRNA peak was digested, the dsRNA fragments remained physically unaffected by the treatment, with no change to their migration time. Using these samples, we detected 0.25% dsRNA impurities in mRNA samples using 15 μL with an analytical runtime of 1 min per sample after digestion and were able to predict their size within 8% of the expected length. The short runtime, sample consumption, and high throughput compatibility make it suitable to support the purity assessment of mRNA during purification and downstream. [ABSTRACT FROM AUTHOR]

The messenger RNA (mRNA) vaccines have progressed from a theoretical concept to a clinical reality over the last few decades. Compared to conventional vaccination methods, these vaccines have a number of benefits, such as substantial potency, rapid growth, inexpensive production, and safe administration. Nevertheless, their usefulness was restricted up to now due to worries about the erratic and ineffective circulation of mRNA in vivo. Thankfully, these worries have largely been allayed by recent technological developments, which have led to the creation of multiple mRNA vaccination platforms for cancer and viral infections. The mRNA vaccines have been demonstrated as a powerful alternative to traditional conventional vaccines because of their high potency, safety and efficacy, capacity for rapid clinical development, and potential for rapid, low‐cost manufacturing. The paper will examine the present status of mRNA vaccine technology and suggest future paths for the advancement and application of this exciting vaccine platform as a common therapeutic choice. Significance statement: With the approval of two messenger RNA (mRNA) vaccines for the prevention of infectious diseases, preclinical and clinical research on mRNA vaccines in the fields of infectious diseases and cancers has greatly expanded. The discovery and efficient delivery of highly immunogenic tumor‐specific antigens poses a substantial obstacle to the development of potent anticancer vaccinations. In this article, we want to provide a thorough and in‐depth examination of mRNA vaccines, including their mechanisms of action as well as their uses in cancer immunotherapy. [ABSTRACT FROM AUTHOR]

RNA modification, particularly pseudouridine (Ψ), has played an important role in the development of the mRNA-based COVID-19 vaccine. This is because Ψ enhances RNA stability against nuclease activity and decreases the anti-RNA immune response. Ψ also provides structural flexibility to RNA by enhancing base stacking compared with canonical nucleobases. In this report, we demonstrate the first application of pseudouridine-modified RNA as a probe (Ψ-RNA) for label-free nucleic acid biosensing. It is known that MoS2 has a differential affinity for nucleic acids, which may be translated into a unique electronic signal. Herein, the Ψ-RNA probe interacts with the pristine MoS2 surface and causes a change in interfacial electrochemical charge transfer in the MoS2 nanosheets. Compared with an unmodified RNA probe, Ψ-RNA exhibited faster adsorption and higher affinity for MoS2. Moreover, Ψ-RNA could bind to complementary RNA and DNA targets with almost equal affinity when engaged with the MoS2 surface. Ψ-RNA maintained robust interactions with the MoS2 surface following the hybridization event, perhaps through its extra amino group. The detection sensitivity of the Ψ-RNA/MoS2 platform was as low as 500 attomoles, while the results also indicate that the probe can distinguish between complementary targets, single mismatches, and non-complementary nucleic acid sequences with statistical significance. This proof-of-concept study shows that the Ψ-RNA probe may solve numerous problems of adsorption-based biosensing platforms due to its stability and structural flexibility. [ABSTRACT FROM AUTHOR]

The purpose of this paper was to construct a prognostic model, miRNA-mRNA regulatory network and proteinprotein interaction (PPI) network for lung squamous cell carcinoma (LUSC) used data from the cancer genome atlas (TCGA) database. In this study, we first downloaded and sorted out the expression matrix containing 19962 mRNA transcripts (including 502 LUSC and 51 normal control (NC) samples) and the expression matrix containing 2205 miRNA transcripts (including 478 LUSC and 45 NC samples) from the TCGA database. We obtained 389 differentially expressed miRNAs (DE-miRNAs), of which 305 were upregulated and 84 down-regulated DE-miRNAs. Next, a total of 7 prognosis-related DE-miRNAs (PDEmiRNAs) were identified by Cox regression analysis, and the prognosis model consisting of three PDE-miRNAs (hsa-miR-4746-5p, hsa-miR-556-3p and hsa-miR-489-3p) was optimized. Then, we drew the survival curves and found that the survival rates of the three PDE-miRNA high and low expression groups and the survival rates of the high-risk and low-risk patients in the prognosis model had significant statistical differences. In addition, the receiver operating characteristics (ROC) curve analysis and independent prognostic analysis confirmed that the prognostic model we built has a relatively accurate ability to predict the grouping and prognosis of LUSC patients. Finally, Cox regression analysis were used to construct the miRNA-mRNA regulatory network, which showed the regulatory relationship between PDE-miRNAs and targeted mRNAs. Moreover, we constructed the PPI network composed of 145 targeted mRNAs and the subnetwork composed of 10 hub-targeted mRNAs (FCGR3A, IL13, CCR2, PPARGC1A, FCGR3B, ACSL1, PLXNA4, LPL, KAT2B and AOC3), which showed the interaction between targeted mRNAs. The above results indicated that the prognosis model we built can predict LUSC patients relatively accurately. The miRNA-mRNA regulatory network and the PPI network of targeted mRNAs illustrated the regulatory mechanisms and interactions between RNAs, which were of certain reference significance for us to further understand the molecular pathogenesis of LUSC and for clinical early diagnosis and treatment. [ABSTRACT FROM AUTHOR]

Researchers have found that messenger RNA (mRNA) technology, which was used in COVID-19 vaccines, shows promise in treating a rare metabolic disease called propionic acidemia. The study, conducted by Moderna, involved infusing patients with mRNA coding for a missing enzyme. Although the results are preliminary, they suggest that the treatment may reduce life-threatening medical emergencies in patients with the disease. This study is significant because it demonstrates the potential of mRNA technology to treat other diseases beyond COVID-19. [Extracted from the article]

• Host DOT1L expression is upregulated on L. donovani infection. • DOT1L transcriptionally regulates HDAC1 expression, which negatively modulates the expression of defensin genes onon L. donovani infection. • HDAC1 regulates the expression of DOT1L, thus, creating a feedback loop on L. donovani infection. Leishmania donovani , a protozoan parasite, causes visceral leishmaniasis. The parasite modifies the global gene expressions of the host genome, facilitating its survival within the host. Thus, the host epigenetic modulators play important roles in host-pathogen interaction and host epigenetic modification in response to infection. Previously, we had reported that the host epigenetic modulator, histone deacetylase 1 (HDAC1) expression was upregulated on Leishmania donovani infection. This upregulation led to the repression of host defensin genes in response to the infection. In this paper, we have investigated the interplay between the host DOT1L, a histone methyltransferase, and HDAC1 in response to Leishmania donovani infection. We show that the expression of DOT1L is upregulated both at transcript and protein level following infection leading to increase in H3K79me, H3K79me2, and H3K79me3 levels. ChIP experiments showed that DOT1L regulated the expression of HDAC1. Downregulation of DOT1L using siRNA resulted in decreased expression of HDAC1 and increased transcription of defensin genes and thereby, lower parasite load. In turn, HDAC1 regulates the expression of DOT1L on Leishmania donovani infection as downregulation of HDAC1 using siRNA led to reduced expression of DOT1L. Thus, during Leishmania donovani infection, an interplay between DOT1L and HDAC1 regulates the expression of these two histone modifiers leading to downregulation of defensin gene expression. [ABSTRACT FROM AUTHOR]

Previously, researchers have employed Lipid nanoparticles (LNPs) to directly encapsulate medicines. In the realm of gene therapy, researchers have begun to employ lipid nanoparticles to encapsulate nucleic acids such as messenger RNA, small interfering RNA, and plasmid DNA, which are known as nucleic acid lipid nanoparticles. Recent breakthroughs in LNP-based medicine have provided significant prospects for the treatment of ocular disorders, such as corneal, choroidal, and retinal diseases. The use of LNP as a delivery mechanism for medicines and therapeutic genes can increase their effectiveness while avoiding undesired immune reactions. However, LNP-based medicines may pose ocular concerns. In this review, we discuss the general framework of LNP. Additionally, we review adjustable approaches and evaluate their possible risks. In addition, we examine newly described ocular illnesses in which LNP was utilized as a delivery mechanism. Finally, we provide perspectives for solving these potential issues. [Display omitted] • This paper reviewed the structure, function, synthesis method and administration mode of LNP. • This article focuses on describing the role of LNP in the treatment of eye diseases. • This review presents opportunities and challenges for the application of LNP inophthalmology. [ABSTRACT FROM AUTHOR]

Two studies published in Science reveal that some bacteria have a unique defense mechanism against viruses. These bacteria create a new gene, called neo, which produces a protein that hinders viral invaders. The mechanism involves the use of reverse transcriptases, enzymes that can produce DNA versions of RNA molecules. The discovery challenges the notion that genetic information only flows in one direction and suggests that similar cryptic genes may exist in other organisms, including humans. The findings have potential applications in genome engineering and may lead to further exploration of this defense mechanism in other organisms. [Extracted from the article]

Modified messenger RNA (mRNA) represents a rapidly emerging class of therapeutic drug product. Development of robust stability indicating methods for control of product quality are therefore critical to support successful pharmaceutical development. This paper presents an ion-pair reversed-phase liquid chromatography (IP-RPLC) method to characterise modified mRNA exposed to a wide set of stress-inducing conditions, relevant for pharmaceutical development of an mRNA drug product. The optimised method could be used for separation and analysis of large RNA, sized up to 1000 nucleotides. Column temperature, mobile phase flow rate and ion-pair selection were each studied and optimised. Baseline separations of the model RNA ladder sample were achieved using all examined ion-pairing agents. We established that the optimised method, using 100 mM Triethylamine, enabled the highest resolution separation for the largest fragments in the RNA ladder (750/1000 nucleotides), in addition to the highest overall resolution for the selected modified mRNA compound (eGFP mRNA, 996 nucleotides). The stability indicating power of the method was demonstrated by analysing the modified eGFP mRNA, upon direct exposure to heat, hydrolytic conditions and treatment with ribonucleases. Our results showed that the formed degradation products, which appeared as shorter RNA fragments in front of the main peak, could be well monitored, using the optimised method, and the relative stability of the mRNA under the various stressed conditions could be assessed. [Display omitted] • Key parameters evaluated for separation of large RNA, using IP-RPLC • Method enabled baseline separation of RNA fragments, sized between 100 – 1000 bases • Rapid high resolution analysis method for modified mRNA developed • Study of mRNA stability upon exposure to heat, hydrolytic conditions and RNases • Degradation mapping using mRNA model compound with optimised LC method [ABSTRACT FROM AUTHOR]

The present study analyzes two potential therapeutic approaches for Alzheimer's disease (AD). One is the suppression of the neuronal integrated stress response (ISR). Another is the targeted degradation of intraneuronal amyloid-beta (iAβ) via the activation of BACE1 (Beta-site Aβ-protein-precursor Cleaving Enzyme) and/or BACE2. Both approaches are rational. Both are promising. Both have substantial intrinsic limitations. However, when combined in a carefully orchestrated manner into a composite therapy they display a prototypical synergy and constitute the apparently optimal, potentially most effective therapeutic strategy for AD. [ABSTRACT FROM AUTHOR]

In this study, we investigated the effect of biphasic microcurrent electrical stimulation (b‐MES) on the epidermal healing process using a rat model of skin abrasion. We analyzed the expression levels of growth factors [fibroblast growth factor 2 (FGF2) and epidermal growth factor (EGF)] and keratin subtypes (K10) in both the b‐MES and control groups at different time points after wounding. The b‐MES group showed a significantly accelerated healing process of the epithelial tissue, resulting in more consistent healing as compared to the control group. A molecular biological analysis showed that the FGF2 mRNA expression level on Day 2 after wounding was significantly higher in the b‐MES group, whereas the EGF mRNA expression level on Days 1, 2, and 4 after wounding was significantly lower in the b‐MES group. Additionally, the K10 mRNA expression level on Days 1 and 2 after wounding was significantly higher in the b‐MES group. Our study findings suggest that b‐MES facilitates wound healing by regulating the growth factors. However, the precise mechanisms underlying these effects remain to be fully elucidated. Further research is needed to fully understand the therapeutic potential of b‐MES and its applications in clinical setting. Clinically, m‐MES requires shunting due to residual electrical charge at the application site. However, b‐MES alternates polarity, leaving no charge at the site of application. Therefore, b‐MES also has the advantage of being safer and allowing treatment for longer periods of time. [ABSTRACT FROM AUTHOR]

Most RNA-protein condensates are composed of heterogeneous immiscible phases. However, how this multiphase organization contributes to their biological functions remains largely unexplored. Drosophila germ granules, a class of RNA-protein condensates, are the site of mRNA storage and translational activation. Here, using super-resolution microscopy and single-molecule imaging approaches, we show that germ granules have a biphasic organization and that translation occurs in the outer phase and at the surface of the granules. The localization, directionality, and compaction of mRNAs within the granule depend on their translation status, translated mRNAs being enriched in the outer phase with their 5′end oriented towards the surface. Translation is strongly reduced when germ granule biphasic organization is lost. These findings reveal the intimate links between the architecture of RNA-protein condensates and the organization of their different functions, highlighting the functional compartmentalization of these condensates. Biomolecular condensates are often composed of immiscible phases. Here, the authors reveal a functional biphasic organization of germ granules, where translational repression happens in the granule core and translation in the outer phase. [ABSTRACT FROM AUTHOR]

Background : Extending the dosing interval of a primary series of mRNA COVID-19 vaccination has been employed to reduce myocarditis risk in adolescents, but previous evaluation of impact on vaccine effectiveness (VE) is limited to risk after second dose. Methods: We quantified the impact of the dosing interval based on case notifications and vaccination uptake in Hong Kong from January to April 2022, based on calendar-time proportional hazards models and matching approaches. Results: We estimated that the hazard ratio (HR) and odds ratio (OR) of infections after the second dose for extended (28 days or more) versus regular (21–27 days) dosing intervals ranged from 0.86 to 0.99 from calendar-time proportional hazards models, and from 0.85 to 0.87 from matching approaches, respectively. Adolescents in the extended dosing groups (including those who did not receive a second dose in the study period) had a higher hazard of infection than those with a regular dosing interval during the intra-dose period (HR 1.66; 95% CI 1.07, 2.59; p = 0.02) after the first dose. Conclusions: Implementing an extended dosing interval should consider multiple factors including the degree of myocarditis risk, the degree of protection afforded by each dose, and the extra protection achievable using an extended dosing interval. [ABSTRACT FROM AUTHOR]

Realizing the immense clinical potential of mRNA-based drugs will require continued development of methods to safely deliver the bioactive agents with high efficiency and without triggering side effects. In this regard, lipid nanoparticles have been successfully utilized to improve mRNA delivery and protect the cargo from extracellular degradation. Encapsulation in lipid nanoparticles was an essential factor in the successful clinical application of mRNA vaccines, which conclusively demonstrated the technology's potential to yield approved medicines. In this review, we begin by describing current advances in mRNA modifications, design of novel lipids and development of lipid nanoparticle components for mRNA-based drugs. Then, we summarize key points pertaining to preclinical and clinical development of mRNA therapeutics. Finally, we cover topics related to targeted delivery systems, including endosomal escape and targeting of immune cells, tumors and organs for use with mRNA vaccines and new treatment modalities for human diseases. [ABSTRACT FROM AUTHOR]

The 5´–3´ exoribonuclease Rat1/Xrn2 is responsible for the termination of eukaryotic mRNA transcription by RNAPII. Rat1 forms a complex with its partner proteins, Rai1 and Rtt103, and acts as a "torpedo" to bind transcribing RNAPII and dissociate DNA/RNA from it. Here we report the cryo-electron microscopy structures of the Rat1-Rai1-Rtt103 complex and three Rat1-Rai1-associated RNAPII complexes (type-1, type-1b, and type-2) from the yeast, Komagataella phaffii. The Rat1-Rai1-Rtt103 structure revealed that Rat1 and Rai1 form a heterotetramer with a single Rtt103 bound between two Rai1 molecules. In the type-1 complex, Rat1-Rai1 forms a heterodimer and binds to the RNA exit site of RNAPII to extract RNA into the Rat1 exonuclease active site. This interaction changes the RNA path in favor of termination (the "pre-termination" state). The type-1b and type-2 complexes have no bound DNA/RNA, likely representing the "post-termination" states. These structures illustrate the termination mechanism of eukaryotic mRNA transcription. The Rat1 RNase helps terminate eukaryotic mRNA transcription. Here, the authors report the cryo-EM structures of the Rat1-Rai1-Rtt103 and the Rat1-Rai1-RNAPII complexes, illustrating the mechanism of mRNA transcription termination. [ABSTRACT FROM AUTHOR]

Myocarditis is the most salient serious adverse event following messenger RNA-based Covid-19 vaccines. The highest risk is observed after the second dose compared to the first, whereas the level of risk associated with more distant booster doses seems to lie in between. We aimed to assess the relation between dosing interval and the risk of myocarditis, for both the two-dose primary series and the third dose (first booster). This matched case-control study included 7911 cases of myocarditis aged 12 or more in a period where approximately 130 million vaccine doses were administered. Here we show that longer intervals between each consecutive dose, including booster, may decrease the occurrence of vaccine-associated myocarditis by up to a factor of 4, especially under age 50. These results suggest that a minimum 6-month interval might be required when scheduling additional booster vaccination. Dosing interval has been suggested as a modifier in the risk of myocarditis associated with Covid-19 mRNA vaccination. Here, the authors show that longer intervals between each consecutive dose, including booster, may decrease the occurrence of myocarditis, especially under age 50. [ABSTRACT FROM AUTHOR]

Background: Rapid proliferation and outgrowth of tumor cells frequently result in localized hypoxia, which has been implicated in the progression of lung cancer. The present study aimed to identify key long non-coding RNAs (lncRNAs) and messenger RNAs (mRNAs) involved in hypoxia-induced A549 lung cancer cells, and to investigate their potential underlying mechanisms of action. Methods: High-throughput sequencing was utilized to obtain the expression profiles of lncRNA and mRNA in both hypoxia-induced and normoxia A549 lung cancer cells. Subsequently, a bioinformatics analysis was conducted on the differentially expressed molecules, encompassing functional enrichment analysis, protein-protein interaction (PPI) network analysis, and competitive endogenous RNA (ceRNA) analysis. Finally, the alterations in the expression of key lncRNAs and mRNAs were validated using real-time quantitative PCR (qPCR). Results: In the study, 1155 mRNAs and 215 lncRNAs were identified as differentially expressed between the hypoxia group and the normoxia group. Functional enrichment analysis revealed that the differentially expressed mRNAs were significantly enriched in various pathways, including the p53 signaling pathway, DNA replication, and the cell cycle. Additionally, key lncRNA-miRNA-mRNA relationships, such as RP11-58O9.2-hsa-miR-6749-3p-XRCC2 and SNAP25-AS1-hsa-miR-6749-3p-TENM4, were identified. Notably, the qPCR assay demonstrated that the expression of SNAP25-AS1, RP11-58O9.2, TENM4, and XRCC2 was downregulated in the hypoxia group compared to the normoxia group. Conversely, the expression of LINC01164, VLDLR-AS1, RP11-14I17.2, and CDKN1A was upregulated. Conclusion: Our findings suggest a potential involvement of SNAP25-AS1, RP11-58O9.2, TENM4, XRCC2, LINC01164, VLDLR-AS1, RP11-14I17.2, and CDKN1A in the development of hypoxia-induced lung cancer. These key lncRNAs and mRNAs exert their functions through diverse mechanisms, including the competitive endogenous RNA (ceRNA) pathway. [ABSTRACT FROM AUTHOR]

Recycling of 40S ribosomal subunits following translation termination, entailing release of deacylated tRNA and dissociation of the empty 40S from mRNA, involves yeast Tma20/Tma22 heterodimer and Tma64, counterparts of mammalian MCTS1/DENR and eIF2D. MCTS1/DENR enhance reinitiation (REI) at short upstream open reading frames (uORFs) harboring penultimate codons that confer heightened dependence on these factors in bulk 40S recycling. Tma factors, by contrast, inhibited REI at particular uORFs in extracts; however, their roles at regulatory uORFs in vivo were unknown. We examined effects of eliminating Tma proteins on REI at regulatory uORFs mediating translational control of GCN4 optimized for either promoting (uORF1) or preventing (uORF4) REI. We found that the Tma proteins generally impede REI at native uORF4 and its variants equipped with various penultimate codons regardless of their Tma-dependence in bulk recycling. The Tma factors have no effect on REI at native uORF1 and equipping it with Tma-hyperdependent penultimate codons generally did not confer Tma-dependent REI; nor did converting the uORFs to AUG-stop elements. Thus, effects of the Tma proteins vary depending on the REI potential of the uORF and penultimate codon, but unlike in mammals, are not principally dictated by the Tma-dependence of the codon in bulk 40S recycling. A study of ribosome recycling in the budding yeast shows that 40S subunit recycling factors influence translation reinitiation independently of their function in bulk recycling, which distinguishes them from their mammalian homologues [ABSTRACT FROM AUTHOR]

This study focused on the challenges posed by the fluctuating demand for COVID-19 vaccines, considering factors such as side effects, religious objections, and absenteeism, which result in the accumulation of excess vaccines. Recognizing the resulting social, economic, and environmental issues, this study investigated the application of a lateral transshipment policy for the management of the inventory of short-term vaccines, considering related unpredictabilities. A discrete event simulation built on foundational principles derived from a mixed-integer linear programming model was employed to explore the dynamics of mRNA-based vaccine distribution among two hospitals based on lateral transshipment and reordering policies. Through the simulation of various scenarios over periods of 1-30 days, transshipment based on the availability policy is employed to determine the quantity of vaccines to be transshipped, constrained to vial amounts, and the (s, S) inventory system for reordering. The results of this study underscore the efficacy of lateral transshipment, particularly in situations where demand discrepancies exist between hospitals, thereby revealing its superiority over non-transshipment strategies within 7 days. [ABSTRACT FROM AUTHOR]

CCDC78 was identified as a novel candidate gene for autosomal dominant centronuclear myopathy-4 (CNM4) approximately ten years ago. However, to date, only one family has been described, and the function of CCDC78 remains unclear. Here, we analyze for the first time a family harboring a CCDC78 nonsense mutation to better understand the role of CCDC78 in muscle. Methods: We conducted a comprehensive histopathological analysis on muscle biopsies, including immunofluorescent assays to detect multiple sarcoplasmic proteins. We examined CCDC78 transcripts and protein using WB in CCDC78-mutated muscle tissue; these analyses were also performed on muscle, lymphocytes, and fibroblasts from healthy subjects. Subsequently, we conducted RT-qPCR and transcriptome profiling through RNA-seq to evaluate changes in gene expression associated with CCDC78 dysfunction in muscle. Lastly, coimmunoprecipitation (Co-Ip) assays and mass spectrometry (LC-MS/MS) studies were carried out on extracted muscle proteins from both healthy and mutated subjects. Results: The histopathological features in muscle showed novel histological hallmarks, which included areas of dilated and swollen sarcoplasmic reticulum (SR). We provided evidence of nonsense-mediated mRNA decay (NMD), identified the presence of novel CCDC78 transcripts in muscle and lymphocytes, and identified 1035 muscular differentially expressed genes, including several involved in the SR. Through the Co-Ip assays and LC-MS/MS studies, we demonstrated that CCDC78 interacts with two key SR proteins: SERCA1 and CASQ1. We also observed interactions with MYH1, ACTN2, and ACTA1. Conclusions: Our findings provide insight, for the first time, into the interactors and possible role of CCDC78 in skeletal muscle, locating the protein in the SR. Furthermore, our data expand on the phenotype previously associated with CCDC78 mutations, indicating potential histopathological hallmarks of the disease in human muscle. Based on our data, we can consider CCDC78 as the causative gene for CNM4. [ABSTRACT FROM AUTHOR]

(1): Atopic dermatitis and psoriasis vulgaris are chronic, inflammatory diseases. Clinical presentation usually leads to a proper diagnosis, but sometimes neither clinical examination nor histopathological evaluation can be conclusive. Therefore, we aimed to build up a novel diagnostic tool and check it for accuracy. The main objective of our work was to differentiate between healthy skin (C), atopic dermatitis (AD) and psoriasis vulgaris (PV) biopsies on the base of involucrin (IVL) and human β-defensin-2 (hBD-2) concentrations and their mRNA, as well as mRNA for TPP2 and PSMB8. (2): ELISA for IVL and hBD-2 proteins and Real-time PCR for the relative expression of mRNA for: IVL (IVL mRNA), hBD-2 (hBD-2 mRNA), PSMB8 (PSMB8 mRNA) and TPP2 (TPP2 mRNA), isolated from skin biopsies taken from AD and PV patients and healthy volunteers were performed. (3): hBD-2 mRNA and PSMB8 mRNA correlated with some parameters of clinical assessment of inflammatory disease severity. hBD-2 mRNA expression, exclusively, was sufficient to distinguish inflammatory skin biopsies from the healthy ones. (4): hBD-2 mRNA and PSMB8 mRNA analysis were the most valuable parameters in differentiating AD and PV biopsies. [ABSTRACT FROM AUTHOR]

Simple Summary: Antisense oligonucleotide (ASO)-based drugs are a new class of compounds. In this review, we will discuss ASO technology, including improved delivery systems, enhanced stability, increased specificity, and challenges such as off-target effects and immune responses. ASO shows potential in cancer treatment by inhibiting the cell signaling pathways implicated in cancer progression. The inhibition of Grb2 is a potential target for ASO in leukemia treatment. This review may significantly impact the scientific community by providing a comprehensive overview of ASO-based therapies. Advancements in our comprehension of tumor biology and chemoresistance have spurred the development of treatments that precisely target specific molecules within the body. Despite the expanding landscape of therapeutic options, there persists a demand for innovative approaches to address unmet clinical needs. RNA therapeutics have emerged as a promising frontier in this realm, offering novel avenues for intervention such as RNA interference and the utilization of antisense oligonucleotides (ASOs). ASOs represent a versatile class of therapeutics capable of selectively targeting messenger RNAs (mRNAs) and silencing disease-associated proteins, thereby disrupting pathogenic processes at the molecular level. Recent advancements in chemical modification and carrier molecule design have significantly enhanced the stability, biodistribution, and intracellular uptake of ASOs, thereby bolstering their therapeutic potential. While ASO therapy holds promise across various disease domains, including oncology, coronary angioplasty, neurological disorders, viral, and parasitic diseases, our review manuscript focuses specifically on the application of ASOs in targeted cancer therapies. Through a comprehensive examination of the latest research findings and clinical developments, we delve into the intricacies of ASO-based approaches to cancer treatment, shedding light on their mechanisms of action, therapeutic efficacy, and prospects. [ABSTRACT FROM AUTHOR]

MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression post-transcriptionally. In animals, this regulation is achieved via base-pairing with partially complementary sequences on mainly 3' UTR region of messenger RNAs (mRNAs). Computational approaches that predict miRNA target interactions (MTIs) facilitate the process of narrowing down potential targets for experimental validation. The availability of new datasets of high-throughput, direct MTIs has led to the development of machine learning (ML) based methods for MTI prediction. To train an ML algorithm, it is beneficial to provide entries from all class labels (i.e., positive and negative). Currently, no high-throughput assays exist for capturing negative examples. Therefore, current ML approaches must rely on either artificially generated or inferred negative examples deduced from experimentally identified positive miRNA-target datasets. Moreover, the lack of uniform standards for generating such data leads to biased results and hampers comparisons between studies. In this comprehensive study, we collected methods for generating negative data for animal miRNAs–target interactions and investigated their impact on the classification of true human MTIs. Our study relies on training ML models on a fixed positive dataset in combination with different negative datasets and evaluating their intra- and cross-dataset performance. As a result, we were able to examine each method independently and evaluate ML models' sensitivity to the methodologies utilized in negative data generation. To achieve a deep understanding of the performance results, we analyzed unique features that distinguish between datasets. In addition, we examined whether one-class classification models that utilize solely positive interactions for training are suitable for the task of MTI classification. We demonstrate the importance of negative data in MTI classification, analyze specific methodological characteristics that differentiate negative datasets, and highlight the challenge of ML models generalizing interaction rules from training to testing sets derived from different approaches. This study provides valuable insights into the computational prediction of MTIs that can be further used to establish standards in the field. Author summary: Gene expression regulation is fundamental for all organisms' development, homeostasis, and environmental adaptation. microRNAs (miRNAs) play a central role in post-transcriptional gene regulation by binding to target mRNAs and repressing their translation or mediating their degradation. Technical challenges in experimental miRNA target identification led to growing interest in computational target prediction. While machine learning (ML) models have shown success in this area, they rely heavily on artificially generated negative examples due to limited experimental data. The diversity of methods for generating negative interactions and the lack of a uniform standardized approach introduce bias and hinder the comparison of results across different studies. In this study, we collected methods for generating negative data for animal miRNAs–target interactions and analyzed their impact on classifying true interactions in humans. Using an ML approach, we evaluated miRNA–target prediction performance within and across negative datasets. We also analyzed unique features distinguishing between the negative datasets to understand the performance results better. Our study shows that negative data is essential for accurately classifying miRNA–target interactions and that ML models struggle to apply what they have learned from the training set when faced with new data derived from different approaches. This study particularly appeals to researchers interested in miRNA–target classification. It emphasizes the need for standardized methods to enhance comparability between studies. [ABSTRACT FROM AUTHOR]

Most mammalian cells have molecular circadian clocks that generate widespread rhythms in transcript and protein abundance. While circadian clocks are robust to fluctuations in the cellular environment, little is known about the mechanisms by which the circadian period compensates for fluctuating metabolic states. Here, we exploit the heterogeneity of single cells both in circadian period and a metabolic parameter--protein stability--to study their interdependence without the need for genetic manipulation. We generated cells expressing key circadian proteins (CRYPTOCHROME1/2 (CRY1/2) and PERIOD1/2 (PER1/2)) as endogenous fusions with fluorescent proteins and simultaneously monitored circadian rhythms and degradation in thousands of single cells. We found that the circadian period compensates for fluctuations in the turnover rates of circadian repressor proteins and uncovered possible mechanisms using a mathematical model. In addition, the stabilities of the repressor proteins are circadian phase dependent and correlate with the circadian period in a phase-dependent manner, in contrast to the prevailing model. [ABSTRACT FROM AUTHOR]

The emergent role of nucleic acid-based biomarkers—microRNAs(miRNAs), long non-coding RNAs(lncRNAs), and messenger RNAs(mRNAs), is becoming increasingly prominent in disease diagnostics and risk assessment. qRT-PCR is the primary analytical method for quantitative measurement of biomarkers. Yet, the relative infancy of non-coding RNAs recognition as biomarkers poses a challenge due to the absence of a consensus on a universally accepted normalizer gene, an absolute requirement for accurate quantification. Current tools normalizer selection are fraught with statistical limitations and suboptimal graphical user interface for data visualisation. These deficiencies underscore the necessity for a balanced tool tailored to handle qRT-PCR datasets. Addressing the identified challenges, we have developed 'gQuant' tool crafted to address these limitations. We employed voting classifiers that combine predictions from multiple statistical methods. Tool's efficacy was validated through different available and in house data derived from urinary exosomal miRNAs datasets. Comparative analysis with existing tools revealed that their integrated methodologies could skew the ranking of normalizer genes, whereas 'gQuant' consistently yielded rankings characterised by lower standard-deviation, reduced covariance, and enhanced kernel density estimation values. Given 'gQuant's' promising performance, normalizer gene identification will be greatly improved, improving precision of gene expression quantification in a variety of research scenarios. The gQuant tool developed for this study is available for public use and can be accessed at [https://github.com/ABHAYHBB/gQuant-Tool]." [ABSTRACT FROM AUTHOR]

Plants employ distinct mechanisms to respond to environmental changes. Modification of mRNA by N 6-methyladenosine (m6A), known to affect the fate of mRNA, may be one such mechanism to reprogram mRNA processing and translatability upon stress. However, it is difficult to distinguish a direct role from a pleiotropic effect for this modification due to its prevalence in RNA. Through characterization of the transient knockdown-mutants of m6A writer components and mutants of specific m6A readers, we demonstrate the essential role that m6A plays in basal resistance and pattern-triggered immunity (PTI). A global m6A profiling of mock and PTI-induced Arabidopsis plants as well as formaldehyde fixation and cross-linking immunoprecipitation-sequencing of the m6A reader, EVOLUTIONARILY CONSERVED C-TERMINAL REGION2 (ECT2) showed that while dynamic changes in m6A modification and binding by ECT2 were detected upon PTI induction, most of the m6A sites and their association with ECT2 remained static. Interestingly, RNA degradation assay identified a dual role of m6A in stabilizing the overall transcriptome while facilitating rapid turnover of immune-induced mRNAs during PTI. Moreover, polysome profiling showed that m6A enhances immune-associated translation by binding to the ECT2/3/4 readers. We propose that m6A plays a positive role in plant immunity by destabilizing defense mRNAs while enhancing their translation efficiency to create a transient surge in the production of defense proteins. [ABSTRACT FROM AUTHOR]

The manuscript analyzes potential pre-mRNA biomarkers of Myasthenia gravis (MG) in thymoma in silico. GSE11967 data set and platform5188 from the Gene Expression Omnibus database apply for data preprocessing, normalization, and quality control. Quality metrics indicated high overall data integrity, with no significant outliers or batch effects detected. Differential expression analysis (DEG.) uses the limma package in R. We compared thymoma samples to normal thymus tissue to identify DEGs. The significance criteria are adjusted p -value <0.05 and a |log2 fold change| > 1. Functional enrichment and pathway analysis, ontology analysis, and KEGG pathway analysis further investigate the potential underlying biological processes. Despite the extensive use of gene expression profiling for identifying potential biomarkers and therapeutic targets, this study identifies DEGs ENSG00000112345 and ENSG00000234567 and pathways like hsa04110, hsa03013 and hsa04115 in thymoma with MG compared to normal thymus tissue using the GSE11967 dataset Plots like UMAP, Boxplot, Expression density and Mean variance demonstrate differential expression in disease and control group. The GSE11967 data set shows the presence of significant DEG and pathways in thymoma-associated MG tissue, compared to healthy tissue. A broader and integrative approach is needed to understand the complex expression biomarkers in thymoma in MG patients and other regulatory mechanisms that may contribute to the disease by multi-omic approaches. [ABSTRACT FROM AUTHOR]

Monogenic blood diseases are among the most common genetic disorders worldwide. These diseases result in significant pediatric and adult morbidity, and some can result in death prior to birth. Novel ex vivo hematopoietic stem cell (HSC) gene editing therapies hold tremendous promise to alter the therapeutic landscape but are not without potential limitations. In vivo gene editing therapies offer a potentially safer and more accessible treatment for these diseases but are hindered by a lack of delivery vectors targeting HSCs, which reside in the difficult-to-access bone marrow niche. Here, we propose that this biological barrier can be overcome by taking advantage of HSC residence in the easily accessible liver during fetal development. To facilitate the delivery of gene editing cargo to fetal HSCs, we developed an ionizable lipid nanoparticle (LNP) platform targeting the CD45 receptor on the surface of HSCs. After validating that targeted LNPs improved messenger ribonucleic acid (mRNA) delivery to hematopoietic lineage cells via a CD45-specific mechanism in vitro, we demonstrated that this platform mediated safe, potent, and long-term gene modulation of HSCs in vivo in multiple mouse models. We further optimized this LNP platform in vitro to encapsulate and deliver CRISPR-based nucleic acid cargos. Finally, we showed that optimized and targeted LNPs enhanced gene editing at a proof-of-concept locus in fetal HSCs after a single in utero intravenous injection. By targeting HSCs in vivo during fetal development, our Systematically optimized Targeted Editing Machinery (STEM) LNPs may provide a translatable strategy to treat monogenic blood diseases before birth. [ABSTRACT FROM AUTHOR]

Single-cell analysis across multiple samples and conditions requires quantitative modeling of the interplay between the continuum of cell states and the technical and biological sources of sample-to-sample variability. We introduce GEDI, a generative model that identifies latent space variations in multi-sample, multi-condition single-cell datasets and attributes them to sample-level covariates. GEDI enables cross-sample cell state mapping on par with state-of-the-art integration methods, cluster-free differential gene expression analysis along the continuum of cell states, and machine learning-based prediction of sample characteristics from single-cell data. GEDI can also incorporate gene-level prior knowledge to infer pathway and regulatory network activities in single cells. Finally, GEDI extends all these concepts to previously unexplored modalities that require joint consideration of dual measurements, such as the joint analysis of exon inclusion/exclusion reads to model alternative cassette exon splicing, or spliced/unspliced reads to model the mRNA stability landscapes of single cells. Single-cell analysis of multi-condition cohorts requires modelling the interaction between sample variables and cell states. Here, authors develop GEDI to enable integration, cluster-free differential expression analysis and regulon analysis for both gene expression and alternative splicing modalities. [ABSTRACT FROM AUTHOR]

Background. Aberrant circular RNA (circRNA) acts as an oncogene or suppressor during neoplasm initiation and development. However, the functions of most circRNAs in osteosarcoma (OS) remain unclear. Objectives. We aimed to investigate the expression, molecular functions and mechanisms underlying circRNAs in OS. Materials and methods. Network interaction, pathway enrichment and regression analyses were performed to determine differentially expressed (DE) circRNAs, microRNAs (miRNAs) and messenger RNAs (mRNAs). We constructed competitive endogenous RcodeNA (ceRNA) networks and integrated patient clinical data to analyze the relationship between the networks and prognosis. The circRNA, miRNA and mRNA data were retrieved from Gene Expression Omnibus (GEO) microarray datasets. A circRNA-miRNA-mRNA interaction network was established and visualized using miRNet. Protein interactions were investigated using STRING and Cytoscape, and hub genes were identified using the MCODE plug-in. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes (KEGG) and Reactome pathway analyses were performed to determine the DEmRNAs. LIMMA and RobustRankAggreg were used to screen for DERNAs. Node genes in the interaction network were analyzed using least absolute shrinkage and selection operator (LASSO) and Cox regression to obtain OS-related ceRNA networks. Results. We identified 9 DEcircRNAs, 243 DEmiRNAs and 211 DEmRNAs. We found that a ceRNA subnetwork, based on 1 circRNA, 1 miRNA and 8 mRNAs, was closely associated with OS prognosis. Integrating the proportional hazards model and survival analysis revealed 3 independent protective factors: adenosine triphosphate (ATP)-binding cassette sub-family A member 8 (ABCA8), catalase (CAT) and C-X-C motif chemokine ligand 12 (CXCL12). Conclusions. Our study provides novel insights into circRNA-related ceRNA networks and identifies potential prognostic biomarkers of OS. [ABSTRACT FROM AUTHOR]

Gene-gene interactions are crucial to the control of sub-cellular processes but our understanding of their stochastic dynamics is hindered by the lack of simulation methods that can accurately and efficiently predict how the distributions of gene product numbers vary across parameter space. To overcome these difficulties, here we present Holimap (high-order linear-mapping approximation), an approach that approximates the protein or mRNA number distributions of a complex gene regulatory network by the distributions of a much simpler reaction system. We demonstrate Holimap's computational advantages over conventional methods by applying it to predict the stochastic time-dependent dynamics of various gene networks, including transcriptional networks ranging from simple autoregulatory loops to complex randomly connected networks, post-transcriptional networks, and post-translational networks. Holimap is ideally suited to study how the intricate network of gene-gene interactions results in precise coordination and control of gene expression. Understanding gene-gene interactions is key to decoding cellular processes. Here, authors introduce Holimap, a method that accurately and rapidly predicts gene expression dynamics by approximating complex regulatory networks with simpler models. [ABSTRACT FROM AUTHOR]