Caloric restriction (CR) is a dietary intervention that reduces calorie intake without inducing malnutrition, demonstrating lifespan-extending effects in preclinical studies and some human trials, along with potential benefits in ameliorating age-related ailments. Caloric restriction mimetics (CRMs) are compounds mimicking CR effects, offering a potential therapeutic avenue for age-related diseases. This study explores the potential protective effects of CR on the brain neocortex (GSE11291) and the identification of CRMs using integrative bioinformatics and systems biology approaches. Our findings indicate that long-term CR activates cellular pathways improving mitochondrial function, enhancing antioxidant capacity, and reducing inflammation, potentially providing neuroprotection. The key signaling pathways enriched in our study include PPAR, mTOR, FoxO, AMPK, and Notch signaling pathways, which are crucial regulators of metabolism, cellular stress response, neuroprotection, and longevity. We identify key signaling molecules and molecular mechanisms associated with CR, including transcription factors, kinase regulators, and microRNAs linked to differentially expressed genes. Furthermore, potential CRMs such as rapamycin, replicating CR-related health benefits, are identified. Additionally, machine learning models were developed to classify small molecules based on their CNS activity and anti-inflammatory properties. As a proof of concept, we have demonstrated the ischemic neuroprotective effects of two top-ranked candidate reference molecules (CRMs) using the oxygen-glucose deprivation (OGD) model, an established in vitro stroke model. However, further investigations are essential to fully elucidate the therapeutic potential of these CRMs. In summary, our study suggests that long-term CR entails protective mechanisms preserving and safeguarding neuronal function, potentially impacting the treatment of age-related neurological diseases. Moreover, our findings contribute to the identification of potential genes and regulatory molecules involved in CR, along with potential CRMs, providing a promising foundation for future research in the field of neurological disorder treatment.

Human Endogenous Retroviruses (HERVs), which can be activated by viral infections, have complex roles in gene regulation and immune modulation. However, their contribution to disease progression is not yet fully understood. Dengue fever ranges from mild symptoms to severe cases characterized by plasma leakage and immune dysregulation, providing a relevant context to investigate these interactions.

This study comes up with a comprehensive analysis of differentially expressed HERVs (DE-HERVs), protein-coding genes (DEGs), and regulatory elements such as microRNAs (DE-miRNA) and non-LTR retroviruses (DE-LINEs and DE-SINEs) derived from the transcriptomes of Brazilian dengue patients across different disease stages.

The results show that DE-HERVs are associated with key genes identified in severe dengue cases, including ARG1, SLC15A2, COL3A1, SVEP1, CH25H, CST7, CXCR1, IL18RAP, SORL1, and TACR1, suggesting their role in immune modulation and endothelial permeability. Specifically, the upregulation of CXCR1 and IL18RAP genes in patients who progressed to severe dengue correlates with a complex regulatory network involving down-regulated microRNAs (miRNAs) and non-LTR retroviruses, emphasizing their relevance to inflammation and vascular permeability. MicroRNAs and non-LTR retroviruses were found to regulate these genes differently across dengue stages, with non-LTR elements appearing predominantly in non-severe cases and miRNA expression profiles varying across the comparison groups.

These findings improve our understanding of the molecular mechanisms underlying dengue progression and suggest that HERV-related regulatory networks may influence viral infections. Further research is required to clarify the specific roles of HERVs in dengue pathogenesis.

Adipose tissue plays a pivotal role in systemic metabolism and maintaining bodily homeostasis. Exosomes from adipose tissues, known as AT-Exos, are recognized as important messengers in the communication between adipose tissue and other organs. Despite this, the alterations in exosome composition and the functional disparities among depot-specific AT-Exos in obesity remain elusive.

In this work, we utilized lipidomics and microRNA (miRNA) sequencing to elucidate the lipid and miRNA profiles of AT-Exos in a diet-induced obesity model. We identified obesity-related miRNAs in AT-Exos and further explored their mechanisms using gain- and loss-of-function experiments. To evaluate the metabolic effects of AT-Exos on adipocytes, we conducted RNA-sequencing (RNA-seq) and confirmed our findings through Quantitative Real-time PCR (qPCR) and Western bolt analyses. Meanwhile, a mouse model with intraperitoneal injections was utilized to validate the role of exosomes derived from visceral white adipose tissue (vWAT-Exos) in obesity progression in vivo. Finally, we explored potential therapeutic intervention strategies targeting AT-Exos, particularly focusing on modulating the SIRPα-CD47 axis to enhance macrophage phagocytosis using Leptin-deficient (ob/ob) mice and SIRPα knock-out mice.

Our study revealed that obesity-related metabolism affects the biological processes of AT-Exos, with depot-specific secretion patterns. In obesity, the lipidome profile of AT-Exos was significantly altered, and diet can modify the miRNA content and function within these exosomes, influencing lipid metabolism and inflammatory pathways that contribute to metabolic dysregulation. Specifically, we identified that miR-200a-3p and miR-200b-3p promoted lipid accumulation in 3T3L1 cells partly through the PI3K/AKT/mTOR pathway. RNA-Seq analysis revealed that AT-Exos from different fat depots exerted distinct effects on adipocyte metabolism, with obese vWAT-Exos being notably potent in triggering inflammation and lipid accumulation in diet-induced obesity. Additionally, we found that inhibiting the SIRPα-CD47 axis can mitigate metabolic disorders induced by obese vWAT-Exos or ob/ob mice, partly due to the enhanced clearance of vWAT-Exos. Consistent with this, SIRPα-deficient mice exhibited a reduction in vWAT-Exos and displayed greater resistance to obesity.

This study elucidates that diet-induced obesity altered the lipid and miRNA profiles of AT-Exos, which involved in modulating adipocyte inflammation and metabolic balance. The SIRPα-CD47 axis emerges as a potential therapeutic target for obesity and its associated complications.

Alzheimer's disease (AD) is a slow brain degeneration disorder in which the accumulation of beta-amyloid precursor plaque and an intracellular neurofibrillary tangle of hyper-phosphorylated tau proteins in the brain have been implicated in neurodegeneration. In this study, we identified the most important genes that are unique and sensitive in the entorhinal region of the brain to target AD effectively. At first, microarrays data are selected and constructed protein-protein interaction network (PPIN) and gene regulatory network (GRN) from differentially expressed genes (DEGs) using Cytoscape software. Then, networks analysis was performed to determine hubs, bottlenecks, clusters, and signaling pathways in AD. Finally, critical genes were selected as targets for repurposing drugs. Analyzing the constructed PPIN and GRN identified CD44, ELF1, HSP90AB1, NOC4L, BYSL, RRP7A, SLC17A6, and RUVBL2 as critical genes that are dysregulated in the entorhinal region of AD suffering patients. The functional enrichment analysis revealed that DEG nodes are involved in the synaptic vesicle cycle, glutamatergic synapse, PI3K-Akt signaling pathway, retrograde endocannabinoid signaling, endocrine and other factor-regulated calcium reabsorption, ribosome biogenesis in eukaryotes, and nicotine addiction. Gentamicin, isoproterenol, and tumor necrosis factor are repurposing new drugs that target CD44, which plays an important role in the development of AD. Following our model validation using the existing experimental data, our model based on previous experimental reports suggested critical molecules and candidate drugs involved in AD for further investigations in vitro and in vivo.

Postoperative cognitive dysfunction (POCD) represents a post-surgical complication that features progressive cognitive impairment and memory loss, often occurring in elderly patients. This study aimed to investigate the potential biological mechanisms underlying POCD.

Male C57BL/6 mice (2 and 17 months old) were randomly assigned to surgery or control groups. The surgery group underwent laparotomy under 1.5% isoflurane anesthesia, while controls received no intervention. Cognitive function was assessed 7-10 days post-surgery using open field, Y-maze, and novel object recognition tests. Hippocampal mRNA expression was analyzed using Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment. A competing endogenous RNA (ceRNA) network was constructed using microRNA (miRNA) target prediction databases (miRanda, miRTarbase, miRcode) and sequencing results. Key findings were validated by RT-qPCR and immunofluorescence. The Connectivity Map (CMap) database was queried to predict potential POCD treatments.

Aging significantly affected mice's spontaneous activity in the open field test (F1, 28 = 8.933, P < 0.01) and the proportion of time spent in the center area (F1, 28 = 5.387, P < 0.05). Surgery significantly reduced the rate of spontaneous alternations in the Y-maze (F1, 28 = 16.94, P < 0.001) and the recognition index in novel object recognition test (F1, 28 = 6.839, P < 0.05) in aging mice, but had no effect on young mice. Transcriptome analysis revealed that aging and surgery downregulated multiple neurogenesis-related genes in the hippocampus. Doublecortin (DCX) immunofluorescence staining confirmed reduced hippocampal neurogenesis in aging mice, which was further decreased after surgery. We identified several key lncRNAs and miRNAs implicated in neurogenesis regulation. Additionally, drugs were predicted as potential therapeutic candidates for POCD treatment.

Both aging and surgery have complex effects on the hippocampal transcriptome in mice. The significant decrease in neurogenesis may be a potential reason for the increased susceptibility of aging mice to POCD. The identified key regulatory lncRNAs, miRNAs, and drugs provide potential therapeutic targets for POCD prevention and treatment.

A systems medicine understanding of the regulatory molecular circuits that underpin breast cancer is essential for early cancer detection and precision/personalized medicine in clinical oncology. Transcription factors (TFs), microRNAs (miRNAs), and long non-coding RNAs (lncRNAs) control gene expression and cell biology, and by extension, serve as pillars of the regulatory circuits that determine human health and disease. We report here the development of a regulatory circuit analysis program, miRCuit, constructing 10 different types of regulatory elements involving messenger RNA, miRNA, lncRNA, and TFs. Using the miRCuit, we analyzed expression profiling data from 179 invasive ductal breast carcinoma and 51 normal tissue samples from the Gene Expression Omnibus database. We identified eight circuit types along with two special types of circuits, one of which highlighted the significant roles of lncRNA CASC15, miR-130b-3p, and TF KLF5 in breast cancer development and progression. These findings advance our understanding of the regulatory molecules associated with breast cancer. Moreover, miRCuit offers a new avenue for users to construct circuits from regulatory molecules for potential applications to decipher disease pathogenesis.

Primary open-angle glaucoma (POAG) is a subtype of glaucoma that accounts for 60%~70% of all cases. Its pathogenic mechanism is intricate and its pathogenic process is concealed. Numerous significant biological processes associated with POAG continue to be elucidated.

In this study, by exploring the expression data of POAG tissues and normal tissues, we mined the regulatory lncRNAs and mRNAs closely associated with the pathogenesis and progression of POAG by exploring a regulatory network of competing endogenous RNA (ceRNA), established by integrating gene expression data with the known lncRNA-miRNA and miRNA-mRNA-regulatory interactions. The key regulatory pathways and regulatory elements of POAG were identified by topological analysis. Simultaneously, the exome data of 28 cases with POAG and healthy controls were analyzed to identify high-frequency mutations and genes.

A total of 2712 differentially expressed genes were identified, including 1828 mRNAs and 884 lncRNAs. Network analysis suggested that lncRNAs such as HAGLR, HOTAIR and MIR29B2CHG, and mRNAs such as PPP6R3, BMPR2 and CFL2, may be involved in the onset and progression of POAG. In addition, 55 mutations with potential pathogenicity were identified.

These genes and mutations provide novel potential genetic heterogeneity and genetic susceptibility of POAG, as well as fresh suggestions for elucidating the molecular mechanism underlying the pathogenesis of POAG.

HIV-associated neurocognitive disorder (HAND) is a complication of chronic inflammation caused by HIV infection that impairs cognitive and motor functions. HAND can occur at any age, regardless of the duration of infection, even in people living with HIV (PLWH) whose blood viral load is controlled by antiretroviral therapy. The diagnosis of HAND requires a battery of neuropsychological tests, which is time-consuming and burdensome, limiting its effectiveness for screening PLWH. Here, we aimed to identify biomarkers for quantitatively diagnosing and screening for HAND using minimally invasive blood tests. Neuronal-derived exosomes (neuroexosomes) were isolated from the peripheral blood of PLWH, and the transcriptomes of their microRNAs (miRNAs) were analyzed. We identified five upregulated miRNAs (hsa-miR-16-5p, hsa-miR-26a-3p, hsa-92a-3p, hsa-miR-103a-3p, and hsa-miR-185-5p), and two downregulated miRNA (hsa-miR-3613-3p and hsa-miR-4668-5p) in PLWH diagnosed with HAND (HAND PLWH). Functional analysis of five miRNAs whose expression levels increased in HAND PLWH using the database showed that these miRNAs are involved in motor proteins and endocytosis, which are associated with nerve function. The expression levels of hsa-miR-16-5p, hsa-miR-103a-3p, and hsa-miR-185-5p were significantly higher than those in the non-HIV controls and non-HAND PLWH, suggesting that these miRNAs are potential biomarkers for HAND. Since there were no changes in known dementia miRNA biomarkers in HAND PLWH, the miRNAs identified in this study will allow for early differentiation of HAND.

Inter-tissue communicators (ITCs) are intricate and essential aspects of our body, as they are the keepers of homeostatic equilibrium. It is no surprise that the dysregulation of the exchange between tissues are at the core of various disorders. Among such conditions, autoimmune diseases (AIDs) refer to a collection of pathological conditions where the miscommunication drives the immune system to mistakenly attack one's own body. Due to their myriad and diverse pathophysiologies, AIDs cannot be easily diagnosed or treated, and continuous efforts are required to seek for potential diagnostic markers or therapeutic targets. The identification of ITCs with significant involvement in the disease states is therefore crucial. Here, we present InTiCAR, Inter-Tissue Communicators for Autoimmune diseases by Random walk with restart, which is a network exploration-based analysis method that suggests disease-specific ITCs based on prior knowledge of disease genes, without the need for the external expression data. We first show that distinct ITC profile s can be acquired for various diseases by InTiCAR. We further illustrate that, for autoimmune diseases (AIDs) specifically, the disease-specific ITCs outperform disease genes in diagnosing patients using the UK Biobank plasma proteome dataset. Also, through CMap LINCS dataset, we find that high perturbation on the AIDs genes can be observed by the disease-specific ITCs. Our results provide and highlight unique perspectives on biological network analysis by focusing on the entities of extracellular communications.

Thoracic aortic aneurysm (TAA) represents an aortic pathology that is caused by the deranged integrity of the three layers of the aortic wall and is related to severe morbidity and mortality. Consequently, it is crucial to identify the biomarkers implicated in the pathogenesis and biology of TAA. The aim of the current computational study was to assess the differential gene expression profile of the gap junction proteins (GJPs) in patients with TAA to identify novel potential biomarkers for the diagnosis and treatment of this disease.

We implemented bioinformatics methodology to construct the gene network of the GJPs family, evaluate their expression in pathologic aortic tissue excised from patients with TAA, and compare it with healthy controls. We also investigated the related biological functions and miRNA families.

We extracted raw data related to the transcriptomic profile of selected genes from a microarray dataset, incorporating 43 TAA and 43 healthy control samples. A total of 17 GJPs were evaluated. Eight GJPs (47%) were downregulated in TAA (GJA3, GJA9, GJA10, GJB1 GJC2, GJD2, GJD3, and GJD4). We also demonstrated the important correlations among the differentially expressed genes (DEGs). Four GJPs (GJA3, GJA9, GJC2, and GJD3) were associated with fair discrimination and calibration traits in predicting TAA presentation. Finally, we performed gene set enrichment analysis (GSEA) and identified the major biological functions and miRNA families (hsa-miR-5001-3p, hsa-miR-942-5p, hsa-miR-7113-3p, hsa-miR-6867-3p, and hsa-miR-4685-3p) associated with the DEGs.

These outcomes support the important role of certain gap junction proteins in the pathogenesis of TAA.

MicroRNAs (miRNAs) are small non-coding RNAs (18-26 nucleotides) that regulate gene expression by interacting with target mRNAs, affecting various physiological and pathological processes. miRTarBase, a database of experimentally validated miRNA-target interactions (MTIs), now features over 3 817 550 validated MTIs from 13 690 articles, significantly expanding its previous version. The updated database includes miRNA interactions with therapeutic agents, revealing roles in drug resistance and therapeutic strategies. It also highlights miRNAs as predictive, safety and monitoring biomarkers for toxicity assessment, clinical treatment guidance and therapeutic optimization. The expansion of miRNA-mRNA and miRNA-miRNA networks allows the identification of key regulatory genes and co-regulatory miRNAs, providing deeper insights into miRNA functions and critical target genes. Information on oxidized miRNA sequences has been added, shedding light on how oxidative modifications influence miRNA targeting and regulation. The integration of the LLAMA3 model into the NLP pipeline, alongside prompt engineering, enables the efficient identification of MTIs and miRNA-disease associations without large training datasets. An updated data integration and a redesigned user interface enhance accessibility, reinforcing miRTarBase as an essential resource for molecular oncology, drug development and related fields. The updated miRTarBase is available at https://mirtarbase.cuhk.edu.cn/∼miRTarBase/miRTarBase_2025.

While ultrasonography effectively diagnoses Hashimoto's thyroiditis (HT), exploring its transcriptomic landscape could reveal valuable insights into disease mechanisms. This study aimed to identify HT-associated RNA signatures and investigate their potential for enhanced molecular characterization. Samples comprising 31 HT patients and 30 healthy controls underwent RNA sequencing of peripheral blood. Differential expression analysis identified transcriptomic features, which were integrated using multi-omics factor analysis. Pathway enrichment, co-expression, and regulatory network analyses were performed. A novel machine-learning model was developed for HT molecular characterization using stacking techniques. HT patients exhibited increased thyroid volume, elevated tissue hardness, and higher antibody levels despite being in the early subclinical stage. Analysis identified 79 HT-associated transcriptomic features (3 mRNA, 6 miRNA, 64 lncRNA, 6 circRNA). Co-expression (77 nodes, 266 edges) and regulatory (18 nodes, 45 edges) networks revealed significant hub genes and modules associated with HT. Enrichment analysis highlighted dysregulation in immune system, cell adhesion and migration, and RNA/protein regulation pathways. The novel stacking-model achieved 95% accuracy and 97% AUC for HT molecular characterization. This study demonstrates the value of transcriptome analysis in uncovering HT-associated signatures, providing insights into molecular changes and potentially guiding future research on disease mechanisms and therapeutic strategies.

Recently, microRNAs (miRNAs) have attracted significant interest as predictive biomarkers for various types of dementia, including Alzheimer's disease (AD), vascular dementia (VaD), dementia with Lewy bodies (DLB), normal pressure hydrocephalus (NPH), and mild cognitive impairment (MCI). Machine learning (ML) methods enable the integration of miRNAs into highly accurate predictive models of dementia.

To investigate the differential expression of miRNAs across dementia subtypes compared to normal controls (NC) and analyze their enriched biological and disease pathways. Additionally, to evaluate the use of these miRNAs in binary and multiclass ML models for dementia prediction in both overall and sex-specific datasets.

Using data comprising 1685 Japanese individuals (GSE120584 and GSE167559), we performed differential expression analysis to identify miRNAs associated with five dementia groups in both overall and sex-specific datasets. Pathway enrichment analyses were conducted to further analyze these miRNAs. ML classifiers were used to create predictive models of dementia.

We identified novel differentially expressed miRNA biomarkers distinguishing NC from five dementia subtypes. Incorporating these miRNAs into ML classifiers resulted in up to a 27% improvement in dementia risk prediction. Pathway analysis highlighted neuronal and eye disease pathways associated with dementia risk. Sex-specific analyses revealed unique biomarkers for males and females, with miR-128-1-5 as a protective factor for males in AD, VaD, and DLB, and miR-4488 as a risk factor for female AD, highlighting distinct pathways and potential therapeutic targets for each sex.

Our findings support existing dementia etiology research and introduce new potential and sex-specific miRNA biomarkers.

Oocyte aging is a significant factor in the negative reproductive outcomes of older women. However, the pathogenesis of oocyte aging remains unclear. This study aimed to identify the hub genes involved in oocyte aging via bioinformatics methods.

The oocyte aging datasets GSE155179 and GSE158802 were obtained from the GEO database and analyzed as the training set. The GSE164371 dataset was then defined as the validation set. Differentially expressed genes were analyzed via the limma package and weighted gene coexpression network analysis, and intersected with cellular senescence-associated genes from the Cell Senescence database. The hub genes were identified via three machine learning algorithms, namely, support vector machine recursive feature elimination, random forest, and least absolute shrinkage and selection operator logistic, which were also confirmed via the validation set. Finally, a microRNA-mRNA‒transcription factor regulatory network and single-gene gene set enrichment analysis were performed to clarify the pathogenesis of oocyte aging.

A competing endogenous RNA network of GSE155179 and GSE158802 with 124 mRNAs, 31 long noncoding RNAs, and 31 miRNAs was constructed. Two modules with 814 genes were considered the key modules of oocyte aging. PDIK1L, SIRT1, and MCU were subsequently identified as hub genes; on the basis of these hub genes, a regulatory network of oocyte aging with 8 miRNAs, 3 mRNAs, and 227 TFs was ultimately constructed.

This study contributes to a deeper understanding of oocyte aging and may aid in the development of therapeutic approaches to improve reproductive outcomes in older women.

Three types of highly promising small RNA therapeutics, namely, small interfering RNAs (siRNAs), microRNAs (miRNAs) and the RNA subtype of antisense oligonucleotides (ASOs), offer advantages over small-molecule drugs. These small RNAs can target any gene product, opening up new avenues of effective and safe therapeutic approaches for a wide range of diseases. In preclinical research, synthetic small RNAs play an essential role in the investigation of physiological and pathological pathways as silencers of specific genes, facilitating discovery and validation of drug targets in different conditions. Off-target effects of small RNAs, however, could make it difficult to interpret experimental results in the preclinical phase and may contribute to adverse events of small RNA therapeutics. Out of the two major types of off-target effects we focused on the hybridization-dependent, especially on the miRNA-like off-target effects. Our main aim was to discuss several approaches, including sequence design, chemical modifications and target prediction, to reduce hybridization-dependent off-target effects that should be considered even at the early development phase of small RNA therapy. Because there is no standard way of predicting hybridization-dependent off-target effects, this review provides an overview of all major state-of-the-art computational methods and proposes new approaches, such as the possible inclusion of network theory and artificial intelligence (AI) in the prediction workflows. Case studies and a concise survey of experimental methods for validating in silico predictions are also presented. These methods could contribute to interpret experimental results, to minimize off-target effects and hopefully to avoid off-target-related adverse events of small RNA therapeutics. LINKED ARTICLES: This article is part of a themed issue Non-coding RNA Therapeutics. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v182.2/issuetoc.

Exosomes, nano-sized extracellular vesicles released by all cells, play a key role in intercellular communication and carry tumorigenic properties that impact surrounding or distant cells. The complexity of the exosomal molecular interactome and its effects on recipient cells still remain unclear. This study aims to decipher the molecular profile and interactome of lung adenocarcinoma A549 cell-derived exosomes using multi-omics and bioinformatics approaches.

We performed comprehensive morphological and physicochemical characterization of exosomes isolated from cell culture supernatant of A549 cells in vitro, using DLS, cryo-TEM, Western blot, and flow cytometry. Proteomic and miRNA high-throughput profiling, coupled with bioinformatics network analysis, were applied to elucidate the exosome molecular cargo. A comparative miRNA analysis was also conducted with exosomes derived from normal lung fibroblast MRC-5 cells.

Exosomes exhibited an average size of ~40 nm and disk-shaped lipid bilayer structures, with tetraspanins CD9 and CD63 validated as exosomal markers. Proteomic analysis identified 68 proteins, primarily linked to the extracellular matrix organization and metabolic processes. miRNA sequencing revealed 72 miRNAs, notably hsa-miR-619-5p, hsa-miR-122-5p, hsa-miR-9901, hsa-miR-7704, and hsa-miR-151a-3p, which are involved in regulating metabolic processes, gene expression, and tumorigenic pathways. Th integration of proteomic and miRNA data through a proteogenomics approach identified dually affected genes including ERBB2, CD44, and APOE, impacted by both exosomal miRNA targeting and protein interactions through synergistic or antagonistic interactions. Differential analysis revealed a distinct miRNA profile in A549 exosomes, associated with cancer-related biological processes, compared to MRC-5 exosomes; notably, hsa-miR-619-5p emerged as a promising candidate for future clinical biomarker studies. The network analysis also revealed genes targeted by multiple upregulated tumor-associated miRNAs in potential exosome-recipient cells.

This integrative study provides insights into the molecular interactome of lung adenocarcinoma A549 cell-derived exosomes, providing a foundation for future research on exosomal cargo and its role in tumor cell communication, growth, and progression.

In recent years, different laboratories have provided evidence on the role of miRNAs in regulation of corneal epithelial metabolism, permeability and wound healing, as well as their alteration after surgery and in some ocular pathologies. We searched the available databases reporting miRNA expression in the human eye, looking for miRNAs highly expressed in central cornea, which could be crucial for maintenance of the epithelial phenotype. Using the rabbit RCE1(5T5) cell line as a model of corneal epithelial differentiation, we describe the participation of miR-141-3p as a possible negative regulator of the proliferative/migratory phenotype in corneal epithelial cells. The expression of miR-141-3p followed a time course similar to the differentiation-linked KRT3 cytokeratin, being delayed 24-48 hours relative to PAX6 expression; such result suggested that miR-141-3p only regulates the expression of terminal phenotype. Inhibition of miR-141-3p led to increased cell proliferation and motility, and induced the expression of molecular makers characteristic of an Epithelial Mesenchymal Transition (EMT). Comparison between the transcriptional profile of cells in which miR-141-3p was knocked down, and the transcriptomes from proliferative non-differentiated and differentiated stratified epithelia suggest that miR-141-3p is involved in the expression of terminal differentiation mediating the arrest of cell proliferation and inhibiting the EMT in highly motile early differentiating cells.

Integrative analysis of multi-omics data has the potential to yield valuable and comprehensive insights into the molecular mechanisms underlying complex diseases such as cancer and Alzheimer's disease. However, a number of analytical challenges complicate multi-omics data integration. For instance, -omics data are usually high-dimensional, and sample sizes in multi-omics studies tend to be modest. Furthermore, when genes in an important pathway have relatively weak signal, it can be difficult to detect them individually. There is a growing body of literature on knowledge-guided learning methods that can address these challenges by incorporating biological knowledge such as functional genomics and functional proteomics into multi-omics data analysis. These methods have been shown to outperform their counterparts that do not utilize biological knowledge in tasks including prediction, feature selection, clustering, and dimension reduction. In this review, we survey recently developed methods and applications of knowledge-guided multi-omics data integration methods and discuss future research directions.

Histone deacetylases (HDACs) and sirtuins (SIRTs) are important epigenetic regulators of cancer pathways. There is a limited understanding of how transcriptional regulation of their genes is affected by chemotherapeutic agents, and how such transcriptional changes affect tumour sensitivity to drug treatment. We investigated the concerted transcriptional response of HDAC and SIRT genes to 15 approved antitumor agents in the NCI-60 cancer cell line panel. Antitumor agents with diverse mechanisms of action induced upregulation or downregulation of multiple HDAC and SIRT genes. HDAC5 was upregulated by dasatinib and erlotinib in the majority of the cell lines. Tumour cell line sensitivity to kinase inhibitors was associated with upregulation of HDAC5, HDAC1, and several SIRT genes. We confirmed changes in HDAC and SIRT expression in independent datasets. We also experimentally validated the upregulation of HDAC5 mRNA and protein expression by dasatinib in the highly sensitive IGROV1 cell line. HDAC5 was not upregulated in the UACC-257 cell line resistant to dasatinib. The effects of cancer drug treatment on expression of HDAC and SIRT genes may influence chemosensitivity and may need to be considered during chemotherapy.

Rainbow trout (Oncorhynchus mykiss) is an economically significant freshwater-farmed fish worldwide, and the frequent outbreaks of infectious hematopoietic necrosis (IHN) in recent years have gravely compromised the healthy growth of the rainbow trout aquaculture industry. Fish skin is an essential immune barrier against the invasion of external pathogens, but it is poorly known about the role of circRNAs in rainbow trout skin. Therefore, we examined the expression profiles of circRNAs in rainbow trout skin following IHNV infection using RNA-seq. A total of 6607 circRNAs were identified, of which 34 circRNAs were differentially expressed (DE) and these DE circRNA source genes were related to immune-related pathways such as Toll-like receptor signaling pathway, NOD-like receptor signaling pathway, Cytokine-cytokine receptor interaction, ubiquitin mediated proteolysis, and ferroptosis. We used qRT-PCR, Sanger sequencing, and subcellular localization to validate the chosen DE circRNAs, confirming their localization and expression patterns in rainbow trout skin. Further, 12 DE circRNAs were selected to construct the circRNA-miRNA-mRNA regulatory network, finding one miRNA could connect one or more circRNAs and mRNAs, and some miRNAs were reported to be associated with antiviral immunity. The functional prediction findings revealed that novel_circ_002779 and novel_circ_004118 may act as sponges for miR-205-z and miR-155-y to regulate the expression of target genes TLR8 and PIK3R1, respectively, and participated in the antiviral immune responses in rainbow trout. These results shed light on the immunological mechanism of circRNAs in rainbow trout skin and offer fundamental information for further research on the innate immune system and breeding rainbow trout resistant to disease.

MicroRNAs (miRNAs) maintain cellular homeostasis by blocking mRNAs by binding with them to fine-tune the expression of genes across numerous biological pathways. The 2024 Nobel Prize in Medicine and Physiology for discovering miRNAs was long overdue. We anticipate a deluge of research work involving miRNAs to repeat the history of prizes awarded for research on other RNAs. Although miRNA therapies are included for several complex diseases, the realization that miRNAs regulate genes and their roles in addressing therapies for hundreds of diseases are expected; but with advancement in drug discovery tools, we anticipate even faster entry of new drugs. To promote this, we provide details of the current science, logic, intellectual property, formulations, and regulatory process with anticipation that many more researchers will introduce novel therapies based on the discussion and advice provided in this paper.

MicroRNAs (miRNAs) are critical regulators in various biological processes to cleave or repress translation of messenger RNAs (mRNAs). Accurately predicting miRNA targets is essential for developing miRNA-based therapies for diseases such as cancer and cardiovascular disease. Traditional miRNA target prediction methods often struggle due to incomplete knowledge of miRNA-target interactions and lack interpretability. To address these limitations, we propose miCGR, an end-to-end deep learning framework for predicting functional miRNA targets. MiCGR employs 2D convolutional neural networks alongside an enhanced Chaos Game Representation (CGR) of both miRNA sequences and their candidate target site (CTS) on mRNA. This advanced CGR transforms genetic sequences into informative 2D graphical representations based on sequence composition and subsequence frequencies, and explicitly incorporates important prior knowledge of seed regions and subsequence positions. Unlike one-dimensional methods based solely on sequence characters, this approach identifies functional motifs within sequences, even if they are distant in the original sequences. Our model outperforms existing methods in predicting functional targets at both the site and gene levels. To enhance interpretability, we incorporate Shapley value analysis for each subsequence within both miRNA sequences and their target sites, allowing miCGR to achieve improved accuracy, particularly with more lenient CTS selection criteria. Finally, two case studies demonstrate the practical applicability of miCGR, highlighting its potential to provide insights for optimizing artificial miRNA analogs that surpass endogenous counterparts.

In recent years, COVID-19 and tuberculosis have emerged as major infectious diseases, significantly contributing to global mortality as respiratory illnesses. There is increasing evidence of a reciprocal influence between these diseases, exacerbating their incidence, severity, and mortality rates.

This study involved retrieving COVID-19 and tuberculosis data from the GEO database and identifying common differentially expressed genes. Machine learning techniques, specifically random forest analysis, were applied to pinpoint key genes for diagnosing COVID-19. The Cibersort algorithm was employed to estimate immune cell infiltration in individuals with COVID-19. Additionally, single-cell sequencing was used to study the distribution of VNN1 within immune cells, and molecular docking provided insights into potential drugs targeting these critical prognosis genes.

GMNN, SCD, and FUT7 were identified as robust diagnostic markers for COVID-19 across training and validation datasets. Importantly, VNN1 was associated with the progression of severe COVID-19, showing a strong correlation with clinical indicators and immune cell infiltration. Single-cell sequencing demonstrated a predominant distribution of VNN1 in neutrophils, and molecular docking highlighted potential pharmacological targets for VNN1.

This study enhances our understanding of the shared pathogenic mechanisms underlying tuberculosis and COVID-19, providing essential insights that could improve the diagnosis and treatment of severe COVID-19 cases.

Aneurysm treatments are crucial to minimize the rupture risk. The underlying molecular processes mediating cellular remodeling, endothelialization, and aneurysm healing following endovascular treatment are poorly understood. The current study aims to explore circulating miRNA as a treatment and outcome-associated biomarkers in patients undergoing endovascular treatment.

Patients undergoing endovascular interventions for unruptured intracranial aneurysms, using either flow diverter placement or coil embolization, were enrolled. Blood samples were collected before the intervention and during a follow-up period between 6 and 18 months. Total mRNA/miRNA was isolated from plasma, followed by RNA-seq analysis. Gene Ontology analysis was used to identify pathways linked to altered miRNA expression.

Twenty-three patients participated, with 13 (56.5%) undergoing flow diversion and 10 (43.5%) coil embolization. The median follow-up sample collection time was 10.70 months (SEM ± 1.32). No significant differences in angiographic occlusion were noted between intervention groups. Differentially expressed miRNAs were not identified between groups at baseline. However, at follow-up, 39 miRNAs were upregulated and 41 were downregulated, independent of intervention. Notably, three miRNAs (miR-4746-5p, miR-4685-3p, and miR-490-3p) were downregulated in the flow diversion group compared to the coil embolization group. Bioinformatics analysis revealed associations with upregulated fluid shear stress, p53, adherens junction pathways, along with downregulated apoptosis pathways.

This study suggests that fluid shear stress and apoptosis may influence aneurysm healing or thromboembolic events in flow diverter-treated patients. Further research is warranted to elucidate the functional significance of these findings in treatment outcomes, providing valuable insights for improved patient care in intracranial aneurysm management.

Increasing evidence from human and animal model studies indicates the significant role of microRNAs (miRNAs) in pancreatic beta cell function, insulin signaling, immune responses, and pathogenesis of type 1 diabetes (T1D).

We aimed, using next-generation sequencing, to screen miRNAs from peripheral blood mononuclear cells of eight independent Kuwaiti-Arab families with T1D affected siblings, consisting of 18 T1D patients and 18 unaffected members, characterized by no parent-to-child inheritance pattern.

Our analysis revealed 20 miRNAs that are differentially expressed in T1D patients compared with healthy controls. Module-based weighted gene co-expression network analysis prioritized key consensus miRNAs in T1D pathogenesis. These included hsa-miR-320a-3p, hsa-miR-139-3p, hsa-miR-200-3p, hsa-miR-99b-5p and hsa-miR-6808-3p. Functional enrichment analysis of differentially expressed miRNAs indicated that PI3K-AKT is one of the key pathways perturbed in T1D. Gene ontology analysis of hub miRNAs also implicated PI3K-AKT, along with mTOR, MAPK, and interleukin signaling pathways, in T1D. Using quantitative RT-PCR, we validated one of the key predicted miRNA-target gene-transcription factor networks in an extended cohort of children with new-onset T1D positive for islet autoantibodies. Our analysis revealed that hsa-miR-320a-3p and its key targets, including PTEN, AKT1, BCL2, FOXO1 and MYC, are dysregulated in T1D, along with their interacting partners namely BLIMP3, GSK3B, CAV1, CXCL3, TGFB, and IL10. Receiver Operating Characteristic analysis highlighted the diagnostic potential of hsa-miR-320a-3p, CAV1, GSK3B and MYC for T1D.

Our study presents a novel link between hsa-miR-320a-3p and T1D, and highlights its key regulatory role in the network of mRNA markers and transcription factors involved in T1D pathogenesis.

Considering the importance of accurate information of full-length (FL) transcripts in functional analysis, researchers prefer to develop new sequencing methods based on third-generation sequencing (TGS) rather than short-read sequencing. Several FL circRNA sequencing strategies have been developed. However, the current methods are inapplicable to low-biomass samples, since a large amount of total RNAs are acquired for circRNA enrichment before library preparation. In this work, we developed an effective method to detect FL circRNAs from a nanogram level (1-100 ng) of total RNAs based on a nanopore platform. Additionally, prior to the library preparation process, we added a series of 24 nt barcodes for each sample to reduce the cost and operating time. Using this method, we profiled circRNA expression in the striatum, hippocampus and cerebral cortex of a Parkinson's disease (PD) mouse model. Over 6% of reads were effective for FL circRNA identification in most datasets. Notably, a reduction in the RNA initial input resulted in a lower correlation between replicates and the detection efficiency for longer circRNA, but the lowest input (1 ng) was able to detect numerous FL circRNAs. Next, we systematically identified over 263 934 circRNAs in PD and healthy mice using the lower-input FL sequencing method, some of which came from 50.52% of PD-associated genes. Moreover, significant changes were observed in the circRNA expression pattern at an isoform level, and high-confidence protein translation evidence was predicted. Overall, we developed an effective method to characterize FL circRNAs from low-input samples and provide a comprehensive insight into the biological function of circRNAs in PD at an isoform level.

The prevalence of cardiovascular diseases (CVDs) is increasing in the last decades, even is the main cause of death in first world countries being atherosclerosis one of the principal triggers. Therefore, there is an urgent need to decipher the underlying mechanisms involved in atherosclerosis progression. In this respect, microRNAs dysregulation is frequently involved in the progression of multiple diseases including CVDs. Our aim was to demonstrate that let-7d-5p unbalance could contribute to the pathophysiology of atherosclerosis and serve as a potential diagnostic biomarker. We evaluated let-7d-5p levels in vascular biopsies and exosome-enriched extracellular vesicles (EVs) from patients with carotid atherosclerosis and healthy donors. Moreover, we overexpressed let-7d-5p in vitro in vascular smooth muscle cells (VSMCs) to decipher the targets and the underlying mechanisms regulated by let-7d-5p in atherosclerosis. Our results demonstrate that let-7d-5p was significantly upregulated in carotid plaques from overweight patients with carotid atherosclerosis. Moreover, in EVs isolated from plasma, we found that let-7d-5p levels were increased in carotid atherosclerosis patients compared to control subjects specially in overweight patients. Receiver Operating Characteristic (ROC) analyses confirmed its utility as a diagnostic biomarker for atherosclerosis. In VSMCs, we demonstrated that increased let-7d-5p levels impairs cell proliferation and could serve as a protective mechanism against inflammation by impairing NF-κB pathway without affecting insulin resistance. In summary, our results highlight the role of let-7d-5p as a potential therapeutic target for atherosclerosis since its overexpression induce a decrease in inflammation and VSMCs proliferation, and also, as a novel non-invasive diagnostic biomarker for atherosclerosis in overweight patients.

Presbycusis, also referred to as age-related hearing loss (ARHL), is a multifaceted condition caused by the natural aging process affecting the auditory system. Genome-wide association studies (GWAS) in human populations can identify potential genes linked to ARHL. Despite this, our knowledge of the biochemical and molecular mechanisms behind the condition remains incomplete. This study aims to evaluate a potential protective tool for ARHL treatment by comparing human blood-based target gene-miRNA associations regulated in ARHL. To identify promising target genes for ARHL, we utilized an mRNA assay. To determine the role of miRNA in ARHL, we investigated the expression profile of miRNA in whole blood in ARHL patients with real-time polymerase chain reaction (RT-qPCR). A reporter gene assay was performed to confirm the regulation of candidate genes by microRNA. Through RT-qPCR validation analysis, we finally confirmed the relationship between ARHL and the role of the interferon-gamma (IFNG) gene. This gene can be regarded as an age-related gene. Through gene ontology (GO) analysis, it has been found that these genes are enriched in pathways related to apoptosis. Among them, IFNG induces an inflammatory response, apoptotic cell death, and cellular senescence. We found that miR-409-3p downregulates the expression of the IFNG in vitro. In addition, the downregulation of the IFNG by miRNA 409-3p promoted cell apoptosis and suppressed proliferation. In conclusion, our study produced gene signatures and associated microRNA regulation that could be a protective key for ARHL patients. IFNG genes and miR-409-3p should be investigated for their usefulness as a new biomarker for treatment modality.

Apelin is an endogenous prepropeptide that regulates cardiac homeostasis and various physiological processes. Intravenous injection has been shown to improve cardiac contractility in patients with heart failure. However, its short half-life prevents studying its impact on left ventricular remodeling in the long term. Here, we aim to study whether microparticle-mediated slow release of apelin improves heart function and left ventricular remodeling in mice with myocardial infarction (MI).

A cardiac patch was fabricated by embedding apelin-containing microparticles in a fibrin gel scaffold. MI was induced via permanent ligation of the left anterior descending coronary artery in adult C57BL/6J mice followed by epicardial patch placement immediately after (acute MI) or 28 days (chronic MI) post-MI. Four groups were included in this study, namely sham, MI, MI plus empty microparticle-embedded patch treatment, and MI plus apelin-containing microparticle-embedded patch treatment. Cardiac function was assessed by transthoracic echocardiography. Cardiomyocyte morphology, apoptosis, and cardiac fibrosis were evaluated by histology. Cardioprotective pathways were determined by RNA sequencing, quantitative polymerase chain reaction, and Western blot.

The level of endogenous apelin was largely reduced in the first 7 days after MI induction and it was normalized by day 28. Apelin-13 encapsulated in poly(lactic-co-glycolic acid) microparticles displayed a sustained release pattern for up to 28 days. Treatment with apelin-containing microparticle-embedded patch inhibited cardiac hypertrophy and reduced scar size in both acute and chronic MI models, which is associated with improved cardiac function. Data from cellular and molecular analyses showed that apelin inhibits the activation and proliferation of cardiac fibroblasts by preventing transforming growth factor-β-mediated activation of Smad2/3 (supporessor of mothers against decapentaplegic 2/3) and downstream profibrotic gene expression.

Poly(lactic-co-glycolic acid) microparticles prolonged the apelin release time in the mouse hearts. Epicardial delivery of the apelin-containing microparticle-embedded patch protects mice from both acute and chronic MI-induced cardiac dysfunction, inhibits cardiac fibrosis, and improves left ventricular remodeling.

The aim of this study was to investigate the correlation between cuproptosis-related genes and immunoinfiltration in keloid, develop a predictive model for keloid occurrence, and explore potential therapeutic drugs. The microarray datasets (GSE7890 and GSE145725) were obtained from Gene Expression Omnibus database to identify the differentially expressed genes (DEGs) between keloid and nonkeloid samples. Key genes were identified through immunoinfiltration analysis and DEGs and then analyzed for Gene Ontology and Kyoto Encyclopedia of Genes and Genomes, followed by the identification of protein-protein interaction networks, transcription factors, and miRNAs associated with key genes. Additionally, a logistic regression analysis was performed to develop a predictive model for keloid occurrence, and potential candidate drugs for keloid treatment were identified. Three key genes (FDX1, PDHB, and DBT) were identified, showing involvement in acetyl-CoA biosynthesis, mitochondrial matrix, oxidoreductase activity, and the tricarboxylic acid cycle. Immune infiltration analysis suggested the involvement of B cells, Th1 cells, dendritic cells, T helper cells, antigen-presenting cell coinhibition, and T cell coinhibition in keloid. These genes were used to develop a logistic regression-based nomogram for predicting keloid occurrence with an area under the curve of 0.859 and good calibration. We identified 32 potential drug molecules and extracted the top 10 compounds based on their P-values, showing promise in targeting key genes and potentially effective against keloid. Our study identified some genes in keloid pathogenesis and potential therapeutic drugs. The predictive model enhances early diagnosis and management. Further research is needed to validate and explore clinical implications.

The importance of the immune system in regulating tumor growth by inducing immune cell-mediated cytotoxicity associated with patients' outcomes has been highlighted in the past years by an increasing life expectancy in patients with cancer on treatment with different immunotherapeutics. However, tumors often escape immune surveillance, which is accomplished by different mechanisms. Recent studies demonstrated an essential role of small non-coding RNAs, such as microRNAs (miRNAs), in the post-transcriptional control of immune modulatory molecules. Multiple methods have been used to identify miRNAs targeting genes involved in escaping immune recognition including miRNAs targeting CTLA-4, PD-L1, HLA-G, components of the major histocompatibility class I antigen processing machinery (APM) as well as other immune response-relevant genes in tumors. Due to their function, these immune modulatory miRNAs can be used as (1) diagnostic and prognostic biomarkers allowing to discriminate between tumor stages and to predict the patients' outcome as well as response and resistance to (immuno) therapies and as (2) therapeutic targets for the treatment of tumor patients. This review summarizes the role of miRNAs in tumor-mediated immune escape, discuss their potential as diagnostic, prognostic and predictive tools as well as their use as therapeutics including alternative application methods, such as chimeric antigen receptor T cells.

The emerging zoonotic West Nile virus (WNV) has serious impact on public health. Thus, understanding the molecular basis of WNV infections in mammalian hosts is important to develop improved diagnostic and treatment strategies. In this context, the role of microRNAs (miRNAs) has been analyzed by several studies under different conditions and with different outcomes. A systematic comparison is therefore necessary. Furthermore, additional information from mRNA target expression data has rarely been taken into account to understand miRNA expression profiles under WNV infections. We conducted a meta-analysis of publicly available miRNA expression data from multiple independent studies, and analyzed them in a harmonized way to increase comparability. In addition, we used gene-set tests on mRNA target expression data to further gain evidence about differentially expressed miRNAs. For this purpose, we also studied the use of target information from different databases. We detected a substantial number of miRNA that emerged as differentially expressed from several miRNA datasets, and from the mRNA target data analysis as well. When using mRNA target data, we found that the targetscan databases provided the most useful information. We demonstrated improved miRNA detection through research synthesis of multiple independent miRNA datasets coupled with mRNA target set testing, leading to the discovery of multiple miRNAs which should be taken into account for further research on the molecular mechanism of WNV infections.

Pregnancy is a complex process involving complex molecular interaction networks, such as between miRNA-protein, protein-protein, metabolite-metabolite, and protein-metabolite interactions. Advances in technology have led to the identification of many pregnancy-associated microRNA (miRNA), protein, and metabolite fingerprints in dairy cows. An array of miRNA, protein, and metabolite fingerprints produced during the early pregnancy of dairy cows were described. We have found the in silico interaction networks between miRNA-protein, protein-protein, metabolite-metabolite, and protein-metabolite. We have manually constructed miRNA-protein-metabolite interaction networks such as bta-miR-423-3p-IGFBP2-PGF2α interactomes. This interactome is obtained by manually combining the interaction network formed between bta-miR-423-3p-IGFBP2 and the interaction network between IGFBP2-PGF2α with IGFBP2 as a common interactor with bta-miR-423-3p and PGF2α with the provided sources of evidence. The interaction between bta-miR-423-3p and IGFBP2 has many sources of evidence including a high miRanda score of 169, minimum free energy (MFE) score of -25.14, binding probability (p) of 1, and energy of -25.5. The interaction between IGFBP2 and PGF2α occurs at high confidence scores (≥0.7 or 70%). Interestingly, PGF2α is also found to interact with different metabolites, such as PGF2α-PGD2, PGF2α-thromboxane B2, PGF2α-PGE2, and PGF2α-6-keto-PGF1α at high confidence scores (≥0.7 or 70%). Furthermore, the interactions between C3-PGE2, C3-PGD2, PGE2-PGD2, PGD2-thromboxane B2, PGE2-thromboxane B2, 6-keto-PGF1α-thromboxane B2, and PGE2-6-keto-PGF1α were also obtained at high confidence scores (≥0.7 or 70%). Therefore, we propose that miRNA-protein-metabolite interactomes involving miRNA, protein, and metabolite fingerprints of early pregnancy of dairy cows such as bta-miR-423-3p, IGFBP2, PGF2α, PGD2, C3, PGE2, 6-keto-PGF1 alpha, and thromboxane B2 may form the key regulatory networks and players of pregnancy regulation in dairy cows. This is the first study involving miRNA-protein-metabolite interactomes obtained in the early pregnancy stage of dairy cows.

Multisystem inflammatory syndrome in children (MIS-C) is an imperative pediatric inflammatory condition closely linked to COVID-19, which garners substantial attention since the onset of the pandemic. Like Kawasaki illness, this condition is characterized by an overactive immune response, leading to symptoms including pyrexia, cardiac and renal complications. To elucidate the pathogenesis of MIS-C and identify potential biomarkers, we conducted an extensive examination of specific cytokines (IL-6, IL-1β, IL-6R, IL-10, and TNF-α) and microRNA (miRNA) expression profiles at various intervals (ranging from 3 to 20 days) in the peripheral blood sample of a severely affected MIS-C patient. Our investigation revealed a gradual decline in circulating levels of IL-6, IL-1β, IL-10, and TNF-α following intravenous immune globulin (IVIG) therapy. Notably, IL-6 exhibited a significant reduction from 74.30 to 1.49 pg./mL, while IL-6R levels remained consistently stable throughout the disease course. Furthermore, we observed an inverse correlation between the expression of hsa-miR-596 and hsa-miR-224-5p and the aforementioned cytokines. Our findings underscore a robust association between blood cytokine and miRNA concentrations and the severity of MIS-C. These insights enhance our understanding of the genetic regulatory mechanisms implicated in MIS-C pathogenesis, offering potential avenues for early biomarker detection and therapy monitoring through miRNA analysis.

The main objective of the current study is to investigate the pathways and therapeutic targets linked to stevioside in the management of T2D using computational approaches.

We collected RNA-seq datasets from NCBI, then employed GREIN to retrieve differentially expressed genes (DEGs). Computer-assisted techniques DAVID, STRING and NetworkAnalyst were used to explore common significant pathways and therapeutic targets associated with T2D and stevioside. Molecular docking and dynamics simulations were conducted to validate the interaction between stevioside and therapeutic targets.

Gene ontology and KEGG analysis revealed that prostaglandin synthesis, IL-17 signaling, inflammatory response, and interleukin signaling were potential pathways targeted by stevioside in T2D. Protein-protein interactions (PPI) analysis identified six common hub proteins (PPARG, PTGS2, CXCL8, CCL2, PTPRC, and EDN1). Molecular docking results showed best binding of stevioside to PPARG (-8 kcal/mol) and PTGS2 (-10.1 kcal/mol). Finally, 100 ns molecular dynamics demonstrated that the binding stability between stevioside and target protein (PPARG and PTGS2) falls within the acceptable range.

This study reveals that stevioside exhibits significant potential in controlling T2D by targeting key pathways and stably binding to PPARG and PTGS2. Further research is necessary to confirm and expand upon these significant computational results.

The number of patients with COVID-19 caused by severe acute respiratory syndrome coronavirus 2 is still increasing. In the case of COVID-19 and tuberculosis (TB), the presence of one disease affects the infectious status of the other. Meanwhile, coinfection may result in complications that make treatment more difficult. However, the molecular mechanisms underpinning the interaction between TB and COVID-19 are unclear. Accordingly, transcriptome analysis was used to detect the shared pathways and molecular biomarkers in TB and COVID-19, allowing us to determine the complex relationship between COVID-19 and TB. Two RNA-seq datasets (GSE114192 and GSE163151) from the Gene Expression Omnibus were used to find concerted differentially expressed genes (DEGs) between TB and COVID-19 to identify the common pathogenic mechanisms. A total of 124 common DEGs were detected and used to find shared pathways and drug targets. Several enterprising bioinformatics tools were applied to perform pathway analysis, enrichment analysis and networks analysis. Protein-protein interaction analysis and machine learning was used to identify hub genes (GAS6, OAS3 and PDCD1LG2) and datasets GSE171110, GSE54992 and GSE79362 were used for verification. The mechanism of protein-drug interactions may have reference value in the treatment of coinfection of COVID-19 and TB.