Screening of differentially expressed RNAs and identifying a ceRNA axis during cadmium-induced oxidative damage in pancreatic ß cells.

Cadmium, a common metal pollutant, has been demonstrated to induce type 2 diabetes by disrupting pancreatic ß cells function. In this study, transcriptome microarray was utilized to identify differential gene expression in oxidative damage to pancreatic ß cells following cadmium exposure. The results indicated that a series of mRNAs, LncRNAs, and miRNAs were altered. Of the differentially expressed miRNAs, miR-29a-3p exhibited the most pronounced alteration, with an 11.62-fold increase relative to the control group. Following this, the target gene of miR-29a-3p was identified as Col3a1 through three databases (miRDB, miRTarbase and Tarbase), which demonstrated a decrease across the transcriptome microarray. The upstream target gene of miR-29a-3p was identified as NONMMUT036805, with decreased expression observed in the microarray. Finally, the expression trend of NONMMUT036805/miR-29a-3p/Col3a1 was reversed following NAC pretreatment. This was accompanied by a reduction in oxidative damage indicators, MDA/ROS/GSH-Px appeared to be negatively affected to varying degrees. In conclusion, this study has demonstrated that multiple RNAs are altered during cadmium exposure-induced oxidative damage in pancreatic ß cells. The NONMMUT036805/miR-29a-3p/Col3a1 axis has been shown to be involved in this process, which provides a foundation for the identification of potential targets for cadmium toxicity intervention.

Towards an enhanced understanding of osteoanabolic effects of PTH-induced microRNAs on osteoblasts using a bioinformatic approach.

In this study, we used a bioinformatic approach to construct a miRNA-target gene interaction network potentially involved in the anabolic effect of parathyroid hormone analogue teriparatide [PTH (1-34)] on osteoblasts. We extracted a dataset of 26 microRNAs (miRNAs) from previously published studies and predicted miRNA target interactions (MTIs) using four software tools: DIANA, miRWalk, miRDB, and TargetScan. By constructing an interactome of PTH-regulated miRNAs and their predicted target genes, we elucidated signaling pathways regulating pluripotency of stem cells, the Hippo signaling pathway, and the TGF-beta signaling pathway as the most significant pathways in the effects of PTH on osteoblasts. Furthermore, we constructed intersection of MTI networks for these three pathways and added validated interactions. There are 8 genes present in all three selected pathways and a set of 18 miRNAs are predicted to target these genes, according to literature data. The most important genes in all three pathways were BMPR1A, BMPR2 and SMAD2 having the most interactions with miRNAs. Among these miRNAs, only miR-146a-5p and miR-346 have validated interactions in these pathways and were shown to be important regulators of these pathways. In addition, we also propose miR-551b-5p and miR-338-5p for further experimental validation, as they have been predicted to target important genes in these pathways but none of their target interactions have yet been verified. Our wet-lab experiment on miRNAs differentially expressed between PTH (1-34) treated and untreated mesenchymal stem cells supports miR-186-5p from the literature obtained data as another prominent miRNA. The meticulous selection of miRNAs outlined will significantly support and guide future research aimed at discovering and understanding the crucial pathways of osteoanabolic PTH-epigenetic effects on osteoblasts. Additionally, they hold potential for the discovery of new PTH target genes, innovative biomarkers for the effectiveness and safety of osteoporosis-affected treatment, as well as novel therapeutic targets.

Identification of hub genes and key pathways in arsenic-treated rice (Oryza sativa L.) based on 9 topological analysis methods of CytoHubba.

BACKGROUND: Arsenic is a toxic metalloid that can cause acute and chronic adverse health problems. Unfortunately, rice, the primary staple food for more than half of the world's population, is generally regarded as a typical arsenic-accumulating crop plant. Evidence indicates that arsenic stress can influence the growth and development of the rice plant, and lead to high concentrations of arsenic in rice grain. But the underlying mechanisms remain unclear. METHODS: In the present research, the possible molecules and pathways involved in rice roots in response to arsenic stress were explored using bioinformatics methods. Datasets that involving arsenic-treated rice root and the "study type" that was restricted to "Expression profiling by array" were selected and downloaded from Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between the arsenic-treated group and the control group were obtained using the online web tool GEO2R. Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed to investigate the functions of DEGs. The protein-protein interactions (PPI) network and the molecular complex detection algorithm (MCODE) of DEGs were analyzed using STRING and Cystoscope, respectively. Important nodes and hub genes in the PPI network were predicted and explored using the Cytoscape-cytoHubba plug-in. RESULTS: Two datasets, GSE25206 and GSE71492, were downloaded from Gene Expression Omnibus (GEO) database. Eighty common DEGs from the two datasets, including sixty-three up-regulated and seventeen down-regulated genes, were then selected. After functional enrichment analysis, these common DEGs were enriched mainly in 10 GO items, including glutathione transferase activity, glutathione metabolic process, toxin catabolic process, and 7 KEGG pathways related to metabolism. After PPI network and MCODE analysis, 49 nodes from the DEGs PPI network were identified, filtering two significant modules. Next, the Cytoscape-cytoHubba plug-in was used to predict important nodes and hub genes. Finally, five genes [Os01g0644000, PRDX6 (Os07g0638400), PRX112 (Os07g0677300), ENO1(Os06g0136600), LOGL9 (Os09g0547500)] were verified and could serve as the best candidates associated with rice root in response to arsenic stress. CONCLUSIONS: In summary, we elucidated the potential pathways and genes in rice root in response to arsenic stress through a comprehensive bioinformatics analysis.

An integrated bioinformatics approach reveals the potential role of microRNA-30b-5p and let-7a-5p during SARS CoV-2 spike-1 mediated neuroinflammation.

SARS-CoV-2 induced neuroinflammation contributing to neurological sequelae is one of the critical outcomes of long-COVID, however underlying regulatory mechanisms involved therein are poorly understood. We deciphered the profile of dysregulated microRNAs, their targets, associated pathways, protein-protein interactions (PPI), transcription factor-hub genes interaction networks, hub genes-microRNA co-regulatory networks in SARS-CoV-2 Spike-1 (S1) stimulated microglial cells along with candidate drug prediction using RNA-sequencing and multiple bioinformatics approaches. We identified 11 dysregulated microRNAs in the S1-stimulated microglial cells (p < 0.05). KEGG analysis revealed involvement of important neuroinflammatory pathways such as MAPK signalling, PI3K-AKT signalling, Ras signalling and axon guidance. PPI analysis further identified 11 hub genes involved in these pathways. Real time PCR validation confirmed a significant upregulation of microRNA-30b-5p and let-7a-5p; proinflammatory cytokines- IL-6, TNF-α, IL-1ß, GM-CSF; and inflammatory genes- PIK3CA and AKT in the S1-stimulated microglial cells, while PTEN and SHIP1 expression was decreased as compared to the non-stimulated cells. Drug prediction analysis further indicated resveratrol, diclofenac and rapamycin as the potential drugs based on their degree of interaction with hub genes. Thus, targeting of these microRNAs and/or their intermediate signalling molecules would be a prospective immunotherapeutic approach in alleviating SARS-CoV-2-S1 mediated neuroinflammation; and needs further investigations.

Network medicine analysis for dissecting the therapeutic mechanism of consensus TCM formulae in treating hepatocellular carcinoma with different TCM syndromes.

Introduction: Hepatocellular carcinoma (HCC) is a major cause of cancer-related mortality worldwide. Traditional Chinese Medicine (TCM) is widely utilized as an adjunct therapy, improving patient survival and quality of life. TCM categorizes HCC into five distinct syndromes, each treated with specific herbal formulae. However, the molecular mechanisms underlying these treatments remain unclear. Methods: We employed a network medicine approach to explore the therapeutic mechanisms of TCM in HCC. By constructing a protein-protein interaction (PPI) network, we integrated genes associated with TCM syndromes and their corresponding herbal formulae. This allowed for a quantitative analysis of the topological and functional relationships between TCM syndromes, HCC, and the specific formulae used for treatment. Results: Our findings revealed that genes related to the five TCM syndromes were closely associated with HCC-related genes within the PPI network. The gene sets corresponding to the five TCM formulae exhibited significant proximity to HCC and its related syndromes, suggesting the efficacy of TCM syndrome differentiation and treatment. Additionally, through a random walk algorithm applied to a heterogeneous network, we prioritized active herbal ingredients, with results confirmed by literature. Discussion: The identification of these key compounds underscores the potential of network medicine to unravel the complex pharmacological actions of TCM. This study provides a molecular basis for TCM's therapeutic strategies in HCC and highlights specific herbal ingredients as potential leads for drug development and precision medicine.

Transcriptome Profiles Reveal Key Regulatory Networks during Single and Multifactorial Stresses Coupled with Melatonin Treatment in Pitaya (Selenicereus undatus L.).

In response to evolving climatic conditions, plants frequently confront multiple abiotic stresses, necessitating robust adaptive mechanisms. This study focuses on the responses of Selenicereus undatus L. to both individual stresses (cadmium; Cd, salt; S, and drought; D) and their combined applications, with an emphasis on evaluating the mitigating effects of (M) melatonin. Through transcriptome analysis, this study identifies significant gene expression changes and regulatory network activations. The results show that stress decreases pitaya growth rates by 30%, reduces stem and cladode development by 40%, and increases Cd uptake under single and combined stresses by 50% and 70%, respectively. Under stress conditions, enhanced activities of H2O2, POD, CAT, APX, and SOD and elevated proline content indicate strong antioxidant defenses. We identified 141 common DEGs related to stress tolerance, most of which were related to AtCBP, ALA, and CBP pathways. Interestingly, the production of genes related to signal transduction and hormones, including abscisic acid and auxin, was also significantly induced. Several calcium-dependent protein kinase genes were regulated during M and stress treatments. Functional enrichment analysis showed that most of the DEGs were enriched during metabolism, MAPK signaling, and photosynthesis. In addition, weighted gene co-expression network analysis (WGCNA) identified critical transcription factors (WRKYs, MYBs, bZIPs, bHLHs, and NACs) associated with antioxidant activities, particularly within the salmon module. This study provides morpho-physiological and transcriptome insights into pitaya's stress responses and suggests molecular breeding techniques with which to enhance plant resistance.

Bioinformatics analysis of oxidative stress genes in the pathogenesis of ulcerative colitis based on a competing endogenous RNA regulatory network.

Background: Ulcerative colitis (UC) is a common chronic disease associated with inflammation and oxidative stress. This study aimed to construct a long noncoding RNA (lncRNA)-microRNA (miRNA)-messenger RNA (mRNA) network based on bioinformatics analysis and to explore oxidative stress-related genes underlying the pathogenesis of UC. Methods: The GSE75214, GSE48959, and GSE114603 datasets were downloaded from the Gene Expression Omnibus database. Following differentially expressed (DE) analysis, the regulatory relationships among these DERNAs were identified through miRDB, miRTarBase, and TargetScan; then, the lncRNA-miRNA-mRNA network was established. The Molecular Signatures Database (MSigDB) was used to search oxidative stress-related genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed for functional annotation and enrichment analyses. Based on the drug gene interaction database DGIdb, drugs that interact with oxidative stress-associated genes were explored. A dextran sulfate sodium (DSS)-induced UC mouse model was used for experimental validation. Results: A total of 30 DE-lncRNAs, 3 DE-miRNAs, and 19 DE-mRNAs were used to construct a lncRNA-miRNA-mRNA network. By comparing these 19 DE-mRNAs with oxidative stress-related genes in MSigDB, three oxidative stress-related genes (CAV1, SLC7A11, and SLC7A5) were found in the 19 DEM sets, which were all negatively associated with miR-194. GO and KEGG analyses showed that CAV1, SLC7A11, and SLC7A5 were associated with immune inflammation and steroid hormone synthesis. In animal experiments, the results showed that dexamethasone, a well-known glucocorticoid drug, could significantly decrease the expression of CAV1, SLC7A11, and SLC7A5 as well as improve UC histology, restore antioxidant activities, inhibit inflammation, and decrease myeloperoxidase activity. Conclusion: SLC7A5 was identified as a representative gene associated with glucocorticoid therapy resistance and thus may be a new therapeutic target for the treatment of UC in the clinic.

Insight into Mantle Cell Lymphoma Pathobiology, Diagnosis, and Treatment Using Network-Based and Drug-Repurposing Approaches.

Mantle cell lymphoma (MCL) is a rare, incurable, and aggressive B-cell non-Hodgkin lymphoma (NHL). Early MCL diagnosis and treatment is critical and puzzling due to inter/intra-tumoral heterogeneity and limited understanding of the underlying molecular mechanisms. We developed and applied a multifaceted analysis of selected publicly available transcriptomic data of well-defined MCL stages, integrating network-based methods for pathway enrichment analysis, co-expression module alignment, drug repurposing, and prediction of effective drug combinations. We demonstrate the "butterfly effect" emerging from a small set of initially differentially expressed genes, rapidly expanding into numerous deregulated cellular processes, signaling pathways, and core machineries as MCL becomes aggressive. We explore pathogenicity-related signaling circuits by detecting common co-expression modules in MCL stages, pointing out, among others, the role of VEGFA and SPARC proteins in MCL progression and recommend further study of precise drug combinations. Our findings highlight the benefit that can be leveraged by such an approach for better understanding pathobiology and identifying high-priority novel diagnostic and prognostic biomarkers, drug targets, and efficacious combination therapies against MCL that should be further validated for their clinical impact.

Identification and Comprehensive Analysis of circRNA-miRNA-mRNA Regulatory Networks in A2780 Cells Treated with Resveratrol.

Ovarian cancer (OC) is one of the most commonplace gynecological malignancies. This study explored the effects of resveratrol (RES) on OC cell proliferation and apoptosis. Proliferation activity was measured for A2780 cells treated with RES for 24 h and 48 h at concentrations of 0, 10, 25, 50, 75, 100, 150, 200, and 300 µM. RNA sequencing (RNA-seq) was performed to analyze the circular RNA (circRNA), microRNA (miRNA), and messenger RNA (mRNA) expression spectrum. The differentially expressed genes included 460 circRNAs, 1988 miRNAs, and 1671 mRNAs, and they were subjected to analyses including Gene Ontology, the Kyoto Encyclopedia of Genes and Genomes (KEGG), and Reactome enrichment. We selected signaling pathways enriched in the cell processes by mRNA KEGG, comprehensively analyzed the circRNA-miRNA-mRNA regulatory network, and verified several miRNAs expressed in the regulatory network diagram using the quantitative real-time polymerase chain reaction. The data showed that the cell proliferation of A2780 cells treated with RES for 24 h or 48 h decreased with increasing concentrations of RES. The circRNA-miRNA-mRNA regulatory network that we constructed provides new insights into the ability of RES to inhibit cell proliferation and promote apoptosis in A2780 cells.

Non-Hereditary Obesity Type Networks and New Drug Targets: An In Silico Approach.

Obesity, a chronic, preventable disease, has significant comorbidities that are associated with a great human and financial cost for society. The aim of the present work is to reconstruct the interactomes of non-hereditary obesity to highlight recent advances of its pathogenesis, and discover potential therapeutic targets. Obesity and biological-clock-related genes and/or gene products were extracted from the biomedical literature databases PubMed, GeneCards and OMIM. Their interactions were investigated using STRING v11.0 (a database of known and predicted physical and indirect associations among genes/proteins), and a high confidence interaction score of >0.7 was set. We also applied virtual screening to discover natural compounds targeting obesity- and circadian-clock-associated proteins. Two updated and comprehensive interactomes, the (a) stress- and (b) inflammation-induced obesidomes involving 85 and 93 gene/gene products of known and/or predicted interactions with an average node degree of 9.41 and 10.8, respectively, were produced. Moreover, 15 of these were common between the two non-hereditary entities, namely, ADIPOQ, ADRB2/3, CCK, CRH, CXCL8, FOS, GCG, GNRH1, IGF1, INS, LEP, MC4R, NPY and POMC, while phelligridin E, a natural product, may function as a potent FOX1-DBD interaction blocker. Molecular networks may contribute to the understanding of the integrated regulation of energy balance/obesity pathogenesis and may associate chronopharmacology schemes with natural products.

Unique regulatory network of dragon fruit simultaneously mitigates the effect of vanadium pollutant and environmental factors.

Under changing climatic conditions, plants are simultaneously facing conflicting stresses in nature. Plants can sense different stresses, induce systematic ROS signals, and regulate transcriptomic, hormonal, and stomatal responses. We performed transcriptome analysis to reveal the integrative stress response regulatory mechanism underlying heavy metal stress alone or in combination with heat and drought conditions in pitaya (dragon fruit). A total of 70 genes were identified from 31,130 transcripts with conserved differential expression. Furthermore, weighted gene co-expression network analysis (WGCNA) identified trait-associated modules. By integrating information from three modules and protein-protein interaction (PPI) networks, we identified 10 interconnected genes associated with the multifaceted defense mechanism employed by pitaya against co-occurring stresses. To further confirm the reliability of the results, we performed a comparative analysis of 350 genes identified by three trait modules and 70 conserved genes exhibiting their dynamic expression under all treatments. Differential expression pattern of genes and comparative analysis, have proven instrumental in identifying ten putative structural genes. These ten genes were annotated as PLAT/LH2, CAT, MLP, HSP, PB1, PLA, NAC, HMA, and CER1 transcription factors involved in antioxidant activity, defense response, MAPK signaling, detoxification of metals and regulating the crosstalk between the complex pathways. Predictive analysis of putative candidate genes, potentially governing single, double, and multifactorial stress response, by several signaling systems and molecular patterns. These findings represent a valuable resource for pitaya breeding programs, offering the potential to develop resilient "super pitaya" plants.

Transcriptome-wide m6A methylation profile reveals tissue specific regulatory networks in switchgrass (Panicum virgatum L.) under cadmium stress.

The heavy metal cadmium (Cd), known for its high toxicity, poses a grave threat to human health through the food chain. N6-methyladenosine (m6A), the most abundant internal modification, regulates plant adaptation to various adversities, yet the panorama of m6A modifications in switchgrass under cadmium stress remains elusive. This study examines the physiological responses of switchgrass roots and shoots exposed to 50 µM CdCl2, alongside an overview of transcriptome-wide m6A methylation patterns. After cadmium treatment, methylation modifications are primarily enriched near stop codons and the 3'UTR region, with a negative correlation between m6A modification and gene expression levels. In shoots, approximately 58 % of DEGs with m6A modifications show upregulation in expression and decrease in m6A peaks, including zinc transporter 4-like (ZIP4). In roots, about 43 % of DEGs with m6A modifications exhibit downregulation in expression and increase in m6A peaks, such as the ABC transporter family member (ABCG25). We further validate the m6A enrichment, gene expression and mRNA stability of ZIP4 in response to Cd treatment. The results suggest that the negative correlation of m6A enrichment and gene expression is due to altered mRNA stability. Our study establishes an m6A regulatory network governing cadmium transport in switchgrass roots and shoots, offering new avenues for candidate gene manipulation in phytoremediation applications of heavy metal pollution.

Identification of critical genes and metabolic pathways in rheumatoid arthritis and osteoporosis toward drug repurposing.

BACKGROUND: Rheumatoid arthritis (RA) and osteoporosis (OP) are considered to be complex diseases. In recent studies, a positive association between RA and OP has been reported triggering growing research interest. This study aims to investigate the drugs related to critical genes in RA and OP, using bioinformatics approaches, toward drug repurposing. METHOD: RA and OP genes were identified. The RA-OP PPI network was constructed and analyzed using the STRING and Cytoscape, respectively. Hub genes and modules were extracted and enriched Gene Ontology, through the WebGestalt and g:Profiler. The identification of the drugs related to critical genes using the DGIDB, and extracted the miRNAs using miRWalk and miRNet. RESULTS: By network clustering, five significant modules were obtained that have important roles in the immune system. IL6, TNF, IL1B, STAT3, TGFB1, TP53, HIF1A, CCL2, IL10, and MMP9 were found as the top 10 hub genes in the RA-OP network. Hub genes were shown to have implications in inflammatory response, significant functions in cytokine receptor binding, and localized mostly in extracellular space. By investigating the drugs related to hub genes, 16 drugs were identified as repurposing candidate drugs. The 10 drugs included Hydroxychloroquine, Infliximab, Adalimumab, Etanercept, Certolizumab, Cyclosporine, Diacerein, Gevokizumab, Canakinumab, and Olokizumab proposed for OP. Also, six drugs including Pirfenidone, Pentoxifylline, Vadimezan, Rilonacept, Metelimumab, and Siltuximab have important roles in inflammatory control and were proposed for both RA and OP. CONCLUSIONS: The results of the present study can provide novel insights into the pathogenesis and treatment of RA and OP.

Network pharmacology-based approach to investigate the molecular targets and molecular mechanisms of Rosmarinus officinalis L. for treating aging-related disorders.

Aging, a natural biological process, presents challenges in maintaining physiological well-being and is associated with increased vulnerability to diseases. Addressing aging mechanisms is crucial for developing effective preventive and therapeutic strategies against age-related ailments. Rosmarinus officinalis L. is a medicinal herb widely used in traditional medicine, containing diverse bioactive compounds that have been studied for their antioxidant and anti-inflammatory properties, which are associated with potential health benefits. Using network pharmacology, this study investigates the anti-aging function and underlying mechanisms of R. officinalis. Through network pharmacology analysis, the top 10 hub genes were identified, including TNF, CTNNB1, JUN, MTOR, SIRT1, and others associated with the anti-aging effects. This analysis revealed a comprehensive network of interactions, providing a holistic perspective on the multi-target mechanism underlying Rosemary's anti-aging properties. GO and KEGG pathway enrichment analysis revealed the relevant biological processes, molecular functions, and cellular components involved in treating aging-related conditions. KEGG pathway analysis shows that anti-aging targets of R. officinalis involved endocrine resistance, pathways in cancer, and relaxin signaling pathways, among others, indicating multifaceted mechanisms. Genes like MAPK1, MMP9, and JUN emerged as significant players. These findings enhance our understanding of R. officinalis's potential in mitigating aging-related disorders through multi-target effects on various biological processes and pathways. Such approaches may reduce the risk of failure in single-target and symptom-based drug discovery and therapy.

Multiple algorithms highlight key brain genes driven by multiple anesthetics.

Anesthesia serves as a pivotal tool in modern medicine, creating a transient state of sensory deprivation to ensure a pain-free surgical or medical intervention. While proficient in alleviating pain, anesthesia significantly modulates brain dynamics, metabolic processes, and neural signaling, thereby impairing typical cognitive functions. Furthermore, anesthesia can induce notable impacts such as memory impairment, decreased cognitive function, and diminished intelligence, emphasizing the imperative need to explore the concealed repercussions of anesthesia on individuals. In this investigation, we aggregated gene expression profiles (GSE64617, GSE141242, GSE161322, GSE175894, and GSE178995) from public repositories following second-generation sequencing analysis of various anesthetics. Through scrutinizing post-anesthesia brain tissue gene expression utilizing Gene Set Enrichment Analysis (GSEA), Robust Rank Aggregation (RRA), and Weighted Gene Co-expression Network Analysis (WGCNA), this research aims to pinpoint pivotal genes, pathways, and regulatory networks linked to anesthesia. This undertaking not only enhances comprehension of the physiological changes brought about by anesthesia but also lays the groundwork for future investigations, cultivating new insights and innovative perspectives in medical practice.

Tianhe Zhuifeng Gao reverses inflammatory response and attenuates bone/cartilage destruction in rheumatoid arthritis via PSMC2-RUNX2-COL1A1 axis based on transcriptional regulatory network analysis and experimental validation.

BACKGROUND: Tianhe Zhuifeng Gao (TZG) is an authorized Chinese patent drug with satisfying clinical efficacy, especially for RA patients with cold-dampness syndrome. However, its underlying pharmacological mechanisms remain unclear. METHOD: Anti-arthritic effects of TZG were evaluated using an adjuvant-induced arthritis (AIA) rat model. Transcriptional regulatory network analysis based on synovial tissues obtained from AIA rats, combining with our previous analysis based on whole blood samples from RA patients with cold-dampness syndrome and co-immunoprecipitation were performed to identify involved dominant pathways, which were experimentally verified using AIA-wind-cold-dampness stimulation modified (AIA-M) animal model. RESULTS: TZG treatment dramatically attenuated joint injury and inflammatory response in AIA rats, and PSMC2-RUNX2-COL1A1 axis, which was closely associated with bone/cartilage damage, was inferred to be one of therapeutic targets of TZG against RA. Experimentally, TZG displayed obvious pharmacological effects for alleviating the joint inflammation and destruction through reinstating the body weight, reducing the arthritis score, the limbs diameters, the levels of RF and CRP, and the inflammatory cytokines, recovering the thymus and spleen indexes, diminishing bone and cartilage destruction, as well elevating the pain thresholds of AIA-M rats. In addition, TZG markedly reversed the abnormal energy metabolism in AIA-M rats through enhancing articular temperature, daily water consumption, and regulating expression levels of energy metabolism parameters and hormones. Moreover, TZG also significantly modulated the abnormal expression levels of PSMC2, RUNX2 and COL1A1 proteins in the ankle tissues of AIA-M rats. CONCLUSION: TZG may exert the bone protective effects in RA therapy via regulating bone and cartilage damage-associated PSMC2-RUNX2-COL1A1 axis.

Elucidating the potential of isorhapontigenin in targeting the MgrA regulatory network: a paradigm shift for attenuating MRSA virulence.

As methicillin-resistant Staphylococcus aureus (MRSA) exhibits formidable resistance to many drugs, the imperative for alternative therapeutic strategies becomes increasingly evident. At the heart of our study is the identification of a novel inhibitor through fluorescence anisotropy assays, specifically targeting the crucial multiple gene regulator A (MgrA) regulatory network in S. aureus. Isorhapontigenin (Iso), a natural compound, exhibits outstanding inhibitory efficacy, modulating bacterial virulence pathways without exerting direct bactericidal activity. This suggests a paradigm shift toward attenuating virulence instead of purely focusing on bacterial elimination. Through comprehensive in vitro and in vivo evaluations, we elucidated the complex interplay between Iso and MgrA, leading to reduced S. aureus adhesion, and overall virulence. At the cellular level, Iso offers significant protection to A549 cells infected with S. aureus, reducing cellular damage. Importantly, Iso augments the chemotaxis of neutrophils, curtailing the immune evasion capabilities of S. aureus. Furthermore, in vivo investigations highlight the notable effectiveness of Iso against MRSA-induced pneumonia and within the Galleria mellonella infection model, underscoring its pivotal role in the evolving realm of antibacterial drug discovery. Significantly, when Iso is used in combination with vancomycin, it outperforms its solo application, indicating a more pronounced therapeutic impact. This seminal research emphasizes Iso's potential as a primary defense against the surge of multidrug-resistant pathogens, heralding new prospects in antimicrobial therapy.

Single-cell transcriptional profile of CD34+ hematopoietic progenitor cells from del(5q) myelodysplastic syndromes and impact of lenalidomide.

While myelodysplastic syndromes with del(5q) (del(5q) MDS) comprises a well-defined hematological subgroup, the molecular basis underlying its origin remains unknown. Using single cell RNA-seq (scRNA-seq) on CD34+ progenitors from del(5q) MDS patients, we have identified cells harboring the deletion, characterizing the transcriptional impact of this genetic insult on disease pathogenesis and treatment response. Interestingly, both del(5q) and non-del(5q) cells present similar transcriptional lesions, indicating that all cells, and not only those harboring the deletion, may contribute to aberrant hematopoietic differentiation. However, gene regulatory network (GRN) analyses reveal a group of regulons showing aberrant activity that could trigger altered hematopoiesis exclusively in del(5q) cells, pointing to a more prominent role of these cells in disease phenotype. In del(5q) MDS patients achieving hematological response upon lenalidomide treatment, the drug reverts several transcriptional alterations in both del(5q) and non-del(5q) cells, but other lesions remain, which may be responsible for potential future relapses. Moreover, lack of hematological response is associated with the inability of lenalidomide to reverse transcriptional alterations. Collectively, this study reveals transcriptional alterations that could contribute to the pathogenesis and treatment response of del(5q) MDS.

Prioritizing drug targets by perturbing biological network response functions.

Therapeutic interventions are designed to perturb the function of a biological system. However, there are many types of proteins that cannot be targeted with conventional small molecule drugs. Accordingly, many identified gene-regulatory drivers and downstream effectors are currently undruggable. Drivers and effectors are often connected by druggable signaling and regulatory intermediates. Methods to identify druggable intermediates therefore have general value in expanding the set of targets available for hypothesis-driven validation. Here we identify and prioritize potential druggable intermediates by developing a network perturbation theory, termed NetPert, for response functions of biological networks. Dynamics are defined by a network structure in which vertices represent genes and proteins, and edges represent gene-regulatory interactions and protein-protein interactions. Perturbation theory for network dynamics prioritizes targets that interfere with signaling from driver to response genes. Applications to organoid models for metastatic breast cancer demonstrate the ability of this mathematical framework to identify and prioritize druggable intermediates. While the short-time limit of the perturbation theory resembles betweenness centrality, NetPert is superior in generating target rankings that correlate with previous wet-lab assays and are more robust to incomplete or noisy network data. NetPert also performs better than a related graph diffusion approach. Wet-lab assays demonstrate that drugs for targets identified by NetPert, including targets that are not themselves differentially expressed, are active in suppressing additional metastatic phenotypes.

Cannabinerol Prevents Endoplasmic Reticulum and Mitochondria Dysfunctions in an In Vitro Model of Alzheimer's Disease: A Network-Based Transcriptomic Analysis.

Neurodegenerative disorders are affecting millions of people worldwide, impacting the healthcare system of our society. Among them, Alzheimer's disease (AD) is the most common form of dementia, characterized by severe cognitive impairments. Neuropathological hallmarks of AD are ß-amyloid (Aß) plaques and neurofibrillary tangles, as well as endoplasmic reticulum and mitochondria dysfunctions, which finally lead to apoptosis and neuronal loss. Since, to date, there is no definitive cure, new therapeutic and prevention strategies are of crucial importance. In this scenario, cannabinoids are deeply investigated as promising neuroprotective compounds for AD. In this study, we evaluated the potential neuroprotective role of cannabinerol (CBNR) in an in vitro cellular model of AD via next-generation sequencing. We observed that CBNR pretreatment counteracts the Aß-induced loss of cell viability of differentiated SH-SY5Y cells. Moreover, a network-based transcriptomic analysis revealed that CBNR restores normal mitochondrial and endoplasmic reticulum functions in the AD model. Specifically, the most important genes regulated by CBNR are related mainly to oxidative phosphorylation (COX6B1, OXA1L, MT-CO2, MT-CO3), protein folding (HSPA5) and degradation (CUL3, FBXW7, UBE2D1), and glucose (G6PC3) and lipid (HSD17B7, ERG28, SCD) metabolism. Therefore, these results suggest that CBNR could be a new neuroprotective agent helpful in the prevention of AD dysfunctions.