Highest Connectivity Research Articles

Molecular mechanisms of ferroptosis in renal ischemia-reperfusion injury Investigated via bioinformatics analysis and animal experiments.

Kidney transplantation is a pivotal treatment for end-stage renal disease. However, renal ischemia-reperfusion injury (IRI) during surgery significantly impacts graft function. Despite unclear molecular mechanisms, no specific therapies or preventative measures are available. Gene expression profiles from renal biopsies before and after IRI were downloaded from public databases. Differentially expressed genes were identified using the Wilcoxon rank-sum test and weighted gene co-expression network analysis. Ferroptosis-associated genes were screened using the FerrDb database. The genes with the highest connectivity were identified via the protein-protein interaction (PPI) network and upstream regulatory miRNAs were found through the gene-miRNA network. A mouse renal IRI model was constructed for transcriptome sequencing and quantitative real-time polymerase chain reaction (qRT-PCR) validation to elucidate the relationship between key ferroptosis genes and regulatory miRNAs in renal IRI. Differential analysis identified 15 ferroptosis-associated genes (TNFAIP3, IL6, KLF2, EGR1, JUN, ZFP36, GDF15, CDKN1A, HSPB1, BRD2, PDK4, DUSP1, SLC2A3, DDIT3, and CXCL2) involved in renal IRI regulation. In animal experiments, ferroptosis-related genes were also upregulated in the model group. Enrichment analysis and hematoxylin-eosin pathological staining suggested these genes are primarily involved in renal inflammatory responses. PPI network analysis revealed IL6 as the gene with the highest connectivity, and the gene-miRNA network indicated IL6 might be regulated by miR-let-7a. Animal experiments revealed decreased miR-let-7a and increased IL6 levels in the model group, identifying potential therapeutic targets. MiR-let-7a regulates ferroptosis in renal IRI by targeting IL6, highlighting IL6 as a crucial gene in the ferroptosis process of renal IRI.

Differential proteomic profiles of exosomes in pediatric and adult adamantinomatous craniopharyngioma cyst fluid.

Adamantinomatous craniopharyngiomas (ACPs), commonly seen in pediatrics and adults often present with large cystic cavities that can compress surrounding tissues, causing severe visual and endocrine symptoms. Complete resection of cystic ACP is challenging, frequently leading to postoperative recurrence. The composition of the cystic fluid is complex, and to date, there has been limited research focusing on exosomes within ACP cyst fluid. We collected cyst fluid from 12 ACP patients and confirmed the presence of exosomes. Subsequently, we conducted exosomal proteomic analysis using LC-MS/MS. The patients were divided into pediatric and adult groups for the analysis of differential protein enrichment, followed by comprehensive bioinformatics analysis, including GO analysis, KEGG analysis, and PPI network analysis, among other functional pathway and protein interaction analyses. Immunohistochemistry was used to determine the tissue expression distribution of the differential protein APOA1. In our data analysis, 64 significantly differentially expressed proteins were identified, with 37 being overexpressed in the pediatric group and 27 in the adult group. Our results revealed that exosomal proteins in the pediatric group were predominantly enriched in modules and pathways related to high-density lipoprotein particle, apolipoprotein receptor binding, and the PPAR signaling pathway. Additionally, APOA1, as the hub protein with the highest connectivity in the differential protein interaction network, may play a critical role in β-amyloid metabolism pathways in pediatric ACP. This study is the first to construct a proteomic map of ACP cyst fluid exosomes, suggesting significant differences in the tumor microenvironment's lipid metabolism between pediatrics and adults.

UV-B irradiation promotes anthocyanin biosynthesis in the leaves of Lycium ruthenicum Murray.

Anthocyanins are the most valuable pigments in Lycium ruthenicum Murray (L.ruthenicum). Although ultraviolet-B (UV-B) irradiation is a key environmental factor influencing anthocyanin biosynthesis in L. ruthenicum, the deep molecular mechanism remains unclear. Herein, we examined the changes in the total anthocyanin content and transcriptomic characteristics of L. ruthenicum leaves following UV-B irradiation treatment. The results showed a twofold increase in anthocyanin content in the leaves of L. ruthenicum after the treatment. The transcriptome analysis showed that the expression of 24 structural genes identified in the anthocyanin synthesis pathway was up-regulated. In particular, F3'H (Unigene0009145) and C4H (Unigene0046607) exhibit notable up-regulation, suggesting their potential roles in anthocyanin synthesis. Protein interaction network results revealed that MYB1 (Unigene0047706) had the highest connectivity, followed by bHLH (Unigene0014085). Additionally, UVR8 (Unigene0067978) and COP1 (Unigene0008780) were found to be highly involved in UV-B signal transduction. These findings provide new insights into the genetic and biochemical mechanisms that regulate anthocyanin production, and could guide agricultural practices to reduce environmental impacts and improve crop yield and quality.

A Virtual In Vivo Dissection and Analysis of Socioaffective Symptoms Related to Cerebellum-Midbrain Reward Circuitry in Humans.

Emerging research in nonhuman animals implicates cerebellar projections to the ventral tegmental area (VTA) in appetitive behaviors, but these circuits have not been characterized in humans. Here, we mapped cerebello-VTA white matter connectivity in a cohort of men and women using probabilistic tractography on diffusion imaging data from the Human Connectome Project. We uncovered the topographical organization of these connections by separately tracking from parcels of cerebellar lobule VI, crus I/II, vermis, paravermis, and cerebrocerebellum. Results revealed that connections between the cerebellum and VTA predominantly originate in the right cerebellar hemisphere, interposed nucleus, and paravermal cortex and terminate mostly ipsilaterally. Paravermal crus I sends the most connections to the VTA compared with other lobules. We discovered a mediolateral gradient of connectivity, such that the medial cerebellum has the highest connectivity with the VTA. Individual differences in microstructure were associated with measures of negative affect and social functioning. By splitting the tracts into quarters, we found that the socioaffective effects were driven by the third quarter of the tract, corresponding to the point at which the fibers leave the deep nuclei. Taken together, we produced detailed maps of cerebello-VTA structural connectivity for the first time in humans and established their relevance for trait differences in socioaffective regulation.

Mechanism Analysis of Selenium-Containing Compounds in Alleviating Spinal Cord Injury Based on Network Pharmacology and Molecular Docking Technology.

Spinal cord injury (SCI) is a severe traumatic condition in spinal surgery characterized by nerve damage in and below the injured area. Despite advancements in understanding the pathophysiology of SCI, effective clinical treatments remain elusive. Selenium compounds have become a research hotspot due to their diverse medicinal activities. Previously, our group synthesized a selenium-containing Compound 34# with significant anti-inflammatory activity. This study aimed to explore the anti-SCI effects of selenium-containing compounds using network pharmacology, molecular docking (MD), and ADMET methods. To identify SCI-related targets and those associated with 34#, GeneCards, NCBI, and SEA databases were employed. Eight overlapping targets were considered candidate targets, and molecular docking was performed using the PDB database and AutoDock software. The STRING database was used to obtain protein-protein interactions (PPI). Molecular dynamics simulation, MM/GBSA binding free energy score, and ADMET prediction were used to evaluate the potential targets and drug properties of 34#. Finally, experiments on NSC34 cells and mice were to verify the effects of 34# on SCI. Our results revealed eight candidate targets for 34# in the treatment of SCI. PPI and MD identified ADRB2 and HTR1F as the highest connectivity with 34#. ADMET analysis confirmed the low toxicity and safety of 34#. In vitro and in vivo models validated the anti-SCI effects. Our study elucidated candidate targets for alleviating SCI with 34#, explored PPI and target-related signaling pathways, and validated its anti-SCI effects. These findings enhance our understanding of 34#'s mechanism in treating SCI, positioning it as a potential candidate for SCI prevention.

Identification of common mechanisms and biomarkers for dermatomyositis and atherosclerosis based on bioinformatics analysis.

Dermatomyositis (DM) manifests as an autoimmune and inflammatory condition, clinically characterized by subacute progressive proximal muscle weakness, rashes or both along with extramuscular manifestations. Literature indicates that DM shares common risk factors with atherosclerosis (AS), and they often co-occur, yet the etiology and pathogenesis remain to be fully elucidated. This investigation aims to utilize bioinformatics methods to clarify the crucial genes and pathways that influence the pathophysiology of both DM and AS. Microarray datasets for DM (GSE128470, GSE1551, GSE143323) and AS (GSE100927, GSE28829, GSE43292) were retrieved from the Gene Expression Omnibus (GEO) database. The weighted gene co-expression network analysis (WGCNA) was used to reveal their co-expressed modules. Differentially expression genes (DEGs) were identified using the "limma" package in R software, and the functions of common DEGs were determined by functional enrichment analysis. A protein-protein interaction (PPI) network was established using the STRING database, with central genes evaluated by the cytoHubba plugin, and validated through external datasets. Immune infiltration analysis of the hub genes was conducted using the CIBERSORT method, along with Gene Set Enrichment Analysis (GSEA). Finally, the NetworkAnalyst platform was employed to examine the transcription factors (TFs) responsible for regulating pivotal crosstalk genes. Utilizing WGCNA analysis, a total of 271 overlapping genes were pinpointed. Subsequent DEG analysis revealed 34 genes that are commonly found in both DM and AS, including 31 upregulated genes and 3 downregulated genes. The Degree Centrality algorithm was applied separately to the WGCNA and DEG collections to select the 15 genes with the highest connectivity, and crossing the two gene sets yielded 3 hub genes (PTPRC, TYROBP, CXCR4). Validation with external datasets showed their diagnostic value for DM and AS. Analysis of immune infiltration indicates that lymphocytes and macrophages are significantly associated with the pathogenesis of DM and AS. Moreover, GSEA analysis suggested that the shared genes are enriched in various receptor interactions and multiple cytokines and receptor signaling pathways. We coupled the 3 hub genes with their respective predicted genes, identifying a potential key TF, CBFB, which interacts with all 3 hub genes. This research utilized comprehensive bioinformatics techniques to explore the shared pathogenesis of DM and AS. The three key genes, including PTPRC, TYROBP, and CXCR4, are related to the pathogenesis of DM and AS. The central genes and their correlations with immune cells may serve as potential diagnostic and therapeutic targets.

The Identification of RPL4 as a Hub Gene Associated with Goat Litter Size via Weighted Gene Co-Expression Network Analysis.

Reproduction in goats is a highly complex and dynamic process of life regulation, involving coordinated regulation from various aspects such as central nervous system regulation, reproductive system development, oocyte maturation, and fertilized egg development. In recent years, researchers have identified numerous genes associated with goat reproductive performance through high-throughput sequencing, single-cell sequencing, gene knockout, and other techniques. However, there is still an urgent need to explore marker genes related to goat reproductive performance. In this study, a single-cell RNA sequencing dataset of oocytes (GSE136005) was obtained from the Gene Expression Omnibus (GEO) database. Weighted Gene Co-expression Network Analysis (WGCNA) was utilized to identify modules highly correlated with goat litter size. Through gene function enrichment analysis, it was found that genes within the modules were mainly enriched in adhesive junctions, cell cycle, and other signaling pathways. Additionally, the top 30 hub genes with the highest connectivity in WGCNA were identified. Subsequently, using Protein-Protein Interaction (PPI) network analysis, the top 30 genes with the highest connectivity within the modules were identified. The intersection of hub genes, key genes in the PPI network, and differentially expressed genes (DEGs) led to the identification of the RPL4 gene as a key marker gene associated with reproductive capacity in goat oocytes. Overall, our study reveals that the RPL4 gene in oocytes holds promise as a biological marker for assessing goat litter size, deepening our understanding of the regulatory mechanisms underlying goat reproductive performance.

Revealing the potential bioactive components and mechanism of Qianhua Gout Capsules in the treatment of gouty arthritis through network pharmacology, molecular docking and pharmacodynamic study strategies

Recent clinical studies have confirmed the effectiveness of Qianhua Gout Capsules (QGC) in the treatment of gouty arthritis (GA). However, the specific regulatory targets and mechanisms of action of QGC are still unclear. To address this gap, we utilized network pharmacology, molecular docking, and pharmacodynamic approaches to investigate the bioactive components and associated mechanisms of QGC in the treatment of GA. By employing UPLC-Q Exactive-MS, we identified the compounds present in QGC, with active ingredients defined as those with oral bioavailability ≥30 % and drug similarity ≥0.18. Subsequently, the targets of these active compounds were determined using the TCMSP database, while GA-related targets were identified from DisGeNET, GeneCards, TTD, OMIM, and DrugBank databases. Further analysis including PPI analysis, GO analysis, and KEGG pathway enrichment was conducted on the targets. Validation of the predicted results was performed using a GA rat model, evaluating pathological changes, inflammatory markers, and pathway protein expression. Our results revealed a total of 130 components, 44 active components, 16 potential shared targets, GO-enriched terms, and 47 signaling pathways related to disease targets. Key active ingredients included quercetin, kaempferol, β-sitosterol, luteolin, and wogonin. The PPI analysis highlighted five targets (PPARG, IL-6, MMP-9, IL-1β, CXCL-8) with the highest connectivity, predominantly enriched in the IL-17 signaling pathway. Molecular docking experiments demonstrated strong binding of CXCL8, IL-1β, IL-6, MMP9, and PPARG targets with the top five active compounds. Furthermore, animal experiments confirmed the efficacy of QGC in treating GA in rats, showing reductions in TNF-α, IL-6, and MDA levels, and increases in SOD levels in serum. In synovial tissues, QGC treatment upregulated CXCL8 and PPARG expression, while downregulating IL-1β, MMP9, and IL-6 expression. In conclusion, this study applied a network pharmacology approach to uncover the composition of QGC, predict its pharmacological interactions, and demonstrate its in vivo efficacy, providing insights into the anti-GA mechanisms of QGC. These findings pave the way for future investigations into the therapeutic mechanisms underlying QGC's effectiveness in the treatment of GA.

Spatial configuration Based on Relationship between Buildings and Road Network in Kupang City, East Nusa Tenggara Province, Indonesia

Oebobo District has the highest density level among all sub-districts in Kupang City. The impact of population growth and circulation is that the mobility of people and goods often occurs quickly, thus hampering efficient observation. This research highlights the need for accurate recognition to develop recommended effective and optimal space management and utilization. The focus of this research is population movement patterns by considering spatial structure. Quantitative descriptive research method used over the space syntax approach on QGIS and DepthMapX softwares. Quantification is carried out on the connectivity value to measure the level of connection in the road network and the integration value to reflect the integration between spaces. With the highest connectivity and integration scores, Oebobo District has the potential to become the city center or main activity center in Kupang City.

Sediment connectivity as a key to understand geomorphic effects of the Storm Alex in two mountain catchments of the Mediterranean Alps (Italy)

The occurrence of extreme rainfall events over mountain catchments is likely to trigger mass failure processes on hillslopes and sediment transport within the channel network. Understanding the degree of linkage between the sediment sources and transfer pathways downstream is essential in those catchments where settlements are affected by hydro-geomorphic processes, in order to plan suitable interventions for risk mitigation. A recent storm (October 2020) named “Alex”, estimated to be an extratropical cyclone with a more than 100-year return period, hit the Mediterranean Alps at the border between Italy and France, triggering deadly landslides and flooding processes. This work focuses on two adjacent mountain catchments located in the Liguria region (Italy) which share the same outlet, where a small village was damaged by high-magnitude sediment transport and deposition processes during the storm. In order to analyze sediment dynamics at the catchment scale leading to severe damage to the urban settlements at the outlet, an integrated approach was used. Very high resolution (0.5 m) satellite imagery was employed to map the mass failure processes on the hillslopes with a visual interpretation. This dataset was then compared with a map of the Index of Connectivity created using the SedInConnect 2.3 software to characterize the pre-event structural connectivity in both catchments. The integration of these two datasets permitted understanding that debris slides evolving into debris flows downstream supplied most of the sediments to the channel network. These processes concentrated mainly in a specific catchment where hillslopes have the highest connectivity with the valley bottom. This outcome provided a clear evidence that inventory maps developed soon after an extreme event, coupled with sediment connectivity datasets, can provide relevant information for future land management and risk mitigation strategies. These can be exploited to prioritize structural interventions in specific areas, to reduce the connectivity or disconnect inhabited areas from the hydro-geomorphic systems and avoid future damage.

Transcriptome Analysis of Intermittent Light Induced Early Bolting in Flowering Chinese Cabbage.

In flowering Chinese cabbage, early booting is one of the most important characteristics that is linked with quality and production. Through fixed light intensity (280 μmol·m-2·s-1) and fixed intermittent lighting in flowering Chinese cabbage, there was early bolting, bud emergence, and flowering. Moreover, the aboveground fresh weight, blade area, dry weight of blade, and quantification of the leaves in flowering Chinese cabbage were significantly reduced, while the thickness of tillers, tillers height, dry weight of tillers, and tillers weight were significantly increased. The chlorophyll contents and soil-plant analysis and development (SPAD) value decreased in the early stage and increased in the later stage. The nitrate content decreased, while the photosynthetic rate, vitamin C content, soluble sugar content, soluble protein content, phenolic content, and flavonoid content increased, and mineral elements also accumulated. In order to explore the mechanism of intermittent light promoting the early bolting and flowering of '49d' flowering Chinese cabbage, this study analyzed the transcriptional regulation from a global perspective using RNA sequencing. A total of 17,086 differentially expressed genes (DEGs) were obtained and 396 DEGs were selected that were closely related to early bolting. These DEGs were mainly involved in pollen wall assembly and plant circadian rhythm pathways, light action (34 DEGs), hormone biosynthesis and regulation (26 DEGs), development (21 DEGs), and carbohydrate synthesis and transport (6 DEGs). Three hub genes with the highest connectivity were identified through weighted gene co-expression network analysis (WGCNA): BrRVE, BrLHY, and BrRVE1. It is speculated that they may be involved in the intermittent light regulation of early bolting in flowering Chinese cabbage. In conclusion, intermittent light can be used as a useful tool to regulate plant growth structure, increase planting density, enhance photosynthesis, increase mineral accumulation, accelerate growth, and shorten the breeding cycle.

Unfurling the functional association between long intergenic noncoding RNAs (lincRNAs) and HPV16-related cervical cancer pathogenesis through weighted gene co-expression network analysis of differentially expressed lincRNAs and coding genes.

Long intergenic noncoding RNAs (lincRNAs) do not overlap annotated coding genes and are located in intergenic regions, as opposed to antisense and sense-intronic lncRNAs, located in genic regions. LincRNAs influence gene expression profiles and are thereby key to disease pathogenesis. In this study, we assessed the association between lincRNAs and HPV16-positive cervical cancer (CaCx) pathogenesis using weighted gene co-expression network analysis (WGCNA) with coding genes, comparing differentially expressed lincRNA and coding genes (DElincGs and DEcGs, respectively) in HPV16-positive patients with CaCx (n = 44) with those in HPV-negative healthy individuals (n = 34). Our analysis revealed five DElincG modules, co-expressing and correlating with DEcGs. We validated a substantial number of such module-specific correlations in the HPV16-positive cancer TCGA-CESC dataset. Four such modules, displayed significant correlations with patient traits, such as HPV16 physical status, lymph node involvement and overall survival (OS), highlighting a collaborative effect of all genes within specific modules on traits. Using the DAVID bioinformatics knowledgebase, we identified the underlying biological processes associated with these modules as cancer development and progression-associated pathways. Next, we identified the top 10 DElincGs with the highest connectivity within each functional module. Focusing on the prognostic module hub genes, downregulated CTD-2619J13.13 expression was associated with poor patient OS. This lincRNA gene interacted with 25 coding genes of its module and was associated with such biological processes as keratinization loss and keratinocyte differentiation, reflecting severe disease phenotypes. This study has translational relevance in fighting various cancers with high mortality rates in underdeveloped countries.

Identification and analysis of mitochondria-related central genes in steroid-induced osteonecrosis of the femoral head, along with drug prediction.

Steroid-induced osteonecrosis of the femoral head (SONFH) is a refractory orthopedic hip joint disease that primarily affects middle-aged and young individuals. SONFH may be caused by ischemia and hypoxia of the femoral head, where mitochondria play a crucial role in oxidative reactions. Currently, there is limited literature on whether mitochondria are involved in the progression of SONFH. Here, we aim to identify and validate key potential mitochondrial-related genes in SONFH through bioinformatics analysis. This study aims to provide initial evidence that mitochondria play a role in the progression of SONFH and further elucidate the mechanisms of mitochondria in SONFH. The GSE123568 mRNA expression profile dataset includes 10 non-SONFH (non-steroid-induced osteonecrosis of the femoral head) samples and 30 SONFH samples. The GSE74089 mRNA expression profile dataset includes 4 healthy samples and 4 samples with ischemic necrosis of the femoral head. Both datasets were downloaded from the Gene Expression Omnibus (GEO) database. The mitochondrial-related genes are derived from MitoCarta3.0, which includes data for all 1136 human genes with high confidence in mitochondrial localization based on integrated proteomics, computational, and microscopy approaches. By intersecting the GSE123568 and GSE74089 datasets with a set of mitochondrial-related genes, we screened for mitochondrial-related genes involved in SONFH. Subsequently, we used the good Samples Genes method in R language to remove outlier genes and samples in the GSE123568 dataset. We further used WGCNA to construct a scale-free co-expression network and selected the hub gene set with the highest connectivity. We then intersected this gene set with the previously identified mitochondrial-related genes to select the genes with the highest correlation. A total of 7 mitochondrial-related genes were selected. Next, we performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis on the selected mitochondrial-related genes using R software. Furthermore, we performed protein network analysis on the differentially expressed proteins encoded by the mitochondrial genes using STRING. We used the GSEA software to group the genes within the gene set in the GSE123568 dataset based on their coordinated changes and evaluate their impact on phenotype changes. Subsequently, we grouped the samples based on the 7 selected mitochondrial-related genes using R software and observed the differences in immune cell infiltration between the groups. Finally, we evaluated the prognostic significance of these features in the two datasets, consisting of a total of 48 samples, by integrating disease status and the 7 gene features using the cox method in the survival R package. We performed ROC analysis using the roc function in the pROC package and evaluated the AUC and confidence intervals using the ci function to obtain the final AUC results. Identification and analysis of 7 intersecting DEGs (differentially expressed genes) were obtained among peripheral blood, cartilage samples, hub genes, and mitochondrial-related genes. These 7 DEGs include FTH1, LACTB, PDK3, RAB5IF, SOD2, and SQOR, all of which are upregulated genes with no intersection in the downregulated gene set. Subsequently, GO and KEGG pathway enrichment analysis revealed that the upregulated DEGs are primarily involved in processes such as oxidative stress, release of cytochrome C from mitochondria, negative regulation of intrinsic apoptotic signaling pathway, cell apoptosis, mitochondrial metabolism, p53 signaling pathway, and NK cell-mediated cytotoxicity. GSEA also revealed enriched pathways associated with hub genes. Finally, the diagnostic value of these key genes for hormone-related ischemic necrosis of the femoral head (SONFH) was confirmed using ROC curves. BID, FTH1, LACTB, PDK3, RAB5IF, SOD2, and SQOR may serve as potential diagnostic mitochondrial-related biomarkers for SONFH. Additionally, they hold research value in investigating the involvement of mitochondria in the pathogenesis of ischemic necrosis of the femoral head.

Identification of potential biological processes and key genes in diabetes-related stroke through weighted gene co-expression network analysis

BackgroundType 2 diabetes mellitus (T2DM) is an established risk factor for acute ischemic stroke (AIS). Although there are reports on the correlation of diabetes and stroke, data on its pathogenesis is limited. This study aimed to explore the underlying biological mechanisms and promising intervention targets of diabetes-related stroke.MethodsDiabetes-related datasets (GSE38642 and GSE44035) and stroke-related datasets (GSE16561 and GSE22255) were obtained from the Gene Expression omnibus (GEO) database. The key modules for stroke and diabetes were identified by weight gene co-expression network analysis (WGCNA). Gene Ontology (GO) and Kyoto Encyclopedia of Genes Genomes (KEGG) analyses were employed in the key module. Genes in stroke- and diabetes-related key modules were intersected to obtain common genes for T2DM-related stroke. In order to discover the key genes in T2DM-related stroke, the Cytoscape and protein–protein interaction (PPI) network were constructed. The key genes were functionally annotated in the Reactome database.ResultsBy intersecting the diabetes- and stroke-related crucial modules, 24 common genes for T2DM-related stroke were identified. Metascape showed that neutrophil extracellular trap formation was primarily enriched. The hub gene was granulin precursor (GRN), which had the highest connectivity among the common genes. In addition, functional enrichment analysis indicated that GRN was involved in neutrophil degranulation, thus regulating neutrophil extracellular trap formation.ConclusionsThis study firstly revealed that neutrophil extracellular trap formation may represent the common biological processes of diabetes and stroke, and GRN may be potential intervention targets for T2DM-related stroke.

Plasma cell-free RNA profiling of Vietnamese Alzheimer's patients reveals a linkage with chronic inflammation and apoptosis: a pilot study.

Circulating cell-free RNA (cfRNA) is a potential hallmark for early diagnosis of Alzheimer's Disease (AD) as it construes the genetic expression level, giving insights into the pathological progress from the outset. Profiles of cfRNA in Caucasian AD patients have been investigated thoroughly, yet there was no report exploring cfRNAs in the ASEAN groups. This study examined the gap, expecting to support the development of point-of-care AD diagnosis. cfRNA profiles were characterized from 20 Vietnamese plasma samples (10 probable AD and 10 age-matched controls). RNA reads were subjected to differential expression (DE) analysis. Weighted gene correlation network analysis (WGCNA) was performed to identify gene modules that were significantly co-expressed. These modules' expression profiles were then correlated with AD status to identify relevant modules. Genes with the highest intramodular connectivity (module membership) were selected as hub genes. Transcript counts of differentially expressed genes were correlated with key AD measures-MMSE and MTA scores-to identify potential biomarkers. 136 genes were identified as significant AD hallmarks (p < 0.05), with 52 downregulated and 84 upregulated in the AD cohort. 45.6% of these genes are highly expressed in the hippocampus, cerebellum, and cerebral cortex. Notably, all markers related to chronic inflammation were upregulated, and there was a significant shift in all apoptotic markers. Three co-expressed modules were found to be significantly correlated with Alzheimer's status (p < 0.05; R2> 0.5). Functional enrichment analysis on these modules reveals an association with focal adhesion, nucleocytoplasmic transport, and metal ion response leading to apoptosis, suggesting the potential participation of these pathways in AD pathology. 47 significant hub genes were found to be differentially expressed genes with the highest connectivity. Six significant hub genes (CREB1, YTHDC1, IL1RL1, PHACTR2, ANKRD36B, RNF213) were found to be significantly correlated with MTA and MMSE scores. Other significant transcripts (XRN1, UBB, CHP1, THBS1, S100A9) were found to be involved in inflammation and neuronal death. Overall, we have identified candidate transcripts in plasma cf-RNA that are differentially expressed and are implicated in inflammation and apoptosis, which can jumpstart further investigations into applying cf-RNA as an AD biomarker in Vietnam and ASEAN countries.

Molecular mechanism of colorectal cancer and screening of molecular markers based on bioinformatics analysis.

Genomics and bioinformatics methods were used to screen genes and molecular markers correlated with colorectal cancer incidence and progression, and their biological functions were analyzed. Differentially expressed genes were obtained using the GEO2R program following colorectal cancer chip data GSE44076 retrieval from the Gene Expression Omnibus gene expression comprehensive database. An online database (David) that combines annotation, visualization, and gene discovery was utilized for investigating genes. Pathway and protein analyses were performed via resources from the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). Visual analysis of the KEGG pathway was carried out according to ClueGO and CluePedia to establish the PPI network of gene interaction between pathways; the genes with the highest connectivity were screened by the molecular complex detection analysis method as Hub genes in this study; gene expression was verified by GEPIA online analysis tool, and Kaplan-Meier survival curve was drawn for prognosis analysis. By analyzing GSE44076 microarray data, 86 genes were selected, and colorectal cancer tissues' upregulation was observed in 27 genes and downregulation in 59 ones. GO assessment revealed that the differentially expressed genes were basically correlated with retinol dehydrogenase activity, carbon dehydrogenase activity, collagen-containing extracellular matrix, anchored component of memory, and cellular hormone metabolic process. Moreover, the KEGG assessment revealed that the differential genes contained various signal pathways such as retinol metabolism, chemical carotenogenesis, and nitrogen metabolism. Through further analysis of the PPI protein network, 4 clusters were obtained, and 16 Hub genes were screened out by combining the degree of each gene. Through the analysis of each gene on the prognosis of colon cancer through the GEPIA online analysis website, it was found that the expression levels of AQP8, CXCL8, and ZG16 genes were remarkably associated with colon cancer prognosis (P < 0.05). Genomics and bioinformatics methods can effectively analyze the genes and molecular markers correlated with colorectal cancer incidence and progression, help to systematically clarify the molecular mechanism of 16 key genes in colorectal cancer development and progression, and provide a theoretically valid insight for the screening of diagnostic markers of colorectal cancer and the selection of accurate targets for drug therapy.

Integration of circulating microRNAs and transcriptome signatures identifies early-pregnancy biomarkers of preeclampsia.

MicroRNAs (miRNAs) have been implicated in the pathobiology of preeclampsia, a common hypertensive disorder of pregnancy. In a nested matched case-control cohort within the Vitamin D Antenatal Asthma Reduction Trial (VDAART), we previously identified peripheral blood mRNA signatures related to preeclampsia and vitamin D status (≤30ng/mL) during gestation from 10 to 18weeks, using differential expression analysis. Using quantitative PCR arrays, we conducted profiling of circulating miRNAs at 10-18weeks of gestation in the same VDAART cohort to identify differentially expressed (DE) miRNAs associated with preeclampsia and vitamin D status. For the validation of the expression of circulating miRNA signatures in the placenta, the HTR-8/SVneo trophoblast cell line was used. Targets of circulating miRNA signatures in the preeclampsia mRNA signatures were identified by consensus ranking of miRNA-target prediction scores from four sources. The connected component of target signatures was identified by mapping to the protein-protein interaction (PPI) network and hub targets were determined. As experimental validation, we examined the gene and protein expression of IGF1R, one of the key hub genes, as a target of the DE miRNA, miR-182-5p, in response to a miR-182-5p mimic in HTR-8/SVneo cells. Pregnant women with preeclampsia had 16 circulating DE miRNAs relative to normal pregnancy controls that were also DE under vitamin D insufficiency (9/16=56% upregulated, FDR<.05). Thirteen miRNAs (13/16=81.3%) were detected in HTR-8/SVneo cells. Overall, 16 DE miRNAs had 122 targets, of which 87 were unique. Network analysis demonstrated that the 32 targets of DE miRNA signatures created a connected subnetwork in the preeclampsia module with CXCL8, CXCL10, CD274, MMP9 and IGF1R having the highest connectivity and centrality degree. In an in vitro validation experiment, the introduction of an hsa-miR-182-5p mimic resulted in significant reduction of its target IGF1R gene and protein expression within HTR-8/SVneo cells. The integration of the circulating DE miRNA and mRNA signatures associated preeclampsia added additional insights into the subclinical molecular signature of preeclampsia. Our systems and network biology approach revealed several biological pathways, including IGF-1, that may play a role in the early pathophysiology of preeclampsia. These pathways and signatures also denote potential biomarkers for the early stages of preeclampsia and suggest possible preventive measures.

A network pharmacology approach to explore pharmacological mechanisms of Asparagus racemosus for ameliorative effect in epilepsy and comorbid progressive memory dysfunction.

Network pharmacology approach has been observed a powerful tool to predict underlying complex pharmacological mechanism of herbs. Asparagus racemosus has been reported to show ameliorative effects in treating epilepsy and comorbid memory dysfunction but mechanism of this amelioration is elusive. Hence a network pharmacology approach was employed to investigate the plausible mechanism of A. recemosus. : Bioactive compounds of A. racemosus were extracted based on the TCMSP, PCIDB, and BATMAN-TCM database. The potential targets of bioactive compounds were collected using target fishing. Epilepsy and comorbid dementia genes were collected from DISGENET. A PPI network among these targets was constructed using the intersecting key targets between herb targets and disease targets. Besides, DAVID bioinformatics resource was utilized for the pathway enrichment analysis on GO and KEGG. Ultimately, phytochemical compound-target genes-Pathways network has been assembled utilizing Cytoscape to decipher the mechanism of the herb. The network analysis revealed that 5 targets (CASP3, TNF, VEGFA, PTGS2 and CNR1) might be the key therapeutic targets of asparagus on Epilepsy comorbid Alzheimer's disease. Based on high connectivity, four hub compounds with the highest connectivity were noted and it includes Shatavarin V, Sarsasapogenin, Shatavarin IX, and Shatavarin VI. A total of 19 KEGG terms were enriched as the potential pathways of A. racemosus in Epilepsy comorbid Alzheimer's disease. This study envisaged the pharmacological and molecular mechanism of A. racemosus against epilepsy comorbid Alzheimer's disease and put forward a strategy to uncover the mechanisms of Traditional Indian Medicine based on network pharmacology. The online version contains supplementary material available at 10.1007/s40203-023-00169-x.

Assessing fish–fishery dynamics from a spatially explicit metapopulation perspective reveals winners and losers in fisheries management

Abstract Sustainable management of living resources must reconcile biodiversity conservation and socioeconomic viability of human activities. In the case of fisheries, sustainable management design is made challenging by the complex spatiotemporal interactions between fish and fisheries. We develop a comprehensive metapopulation framework integrating data on species life‐history traits, connectivity and habitat distribution to identify priority areas for fishing regulation and assess how management impacts are spatially distributed. We trial this approach on European hake fisheries in the north‐western Mediterranean, where we assess area‐based management scenarios in terms of stock status and fishery productivity to prioritize areas for protection. Model simulations show that local fishery closures have the potential to enhance both spawning stock biomass and landings on a regional scale compared to a status quo scenario, but that improving protection is easier than increasing productivity. Moreover, the interaction between metapopulation dynamics and the redistribution of fishing effort following local closures implies that benefits and drawbacks are heterogeneously distributed in space, the former being concentrated in the proximity of the protected site. A network analysis shows that priority areas for protection are those with the highest connectivity (as expressed by network metrics) if the objective is to improve the spawning stock, while no significant relationship emerges between connectivity and potential for increased landings. Synthesis and applications. Our framework provides a tool for (1) assessing area‐based management measures aimed at improving fisheries outcomes in terms of both conservation and socioeconomic viability and (2) describing the spatial distribution of costs and benefits, which can help guide effective management and gain stakeholder support. Adult dispersal remains the main source of uncertainty that needs to be investigated to effectively apply our model to fisheries regulation.

Are landholders willing to collaborate under ELMs? Promoting collaborative conservation on a landscape scale in the UK

It is now widely acknowledged that one of the ways to protect biodiversity in the UK is through a landscape scale management approach towards conservation. Achieving this will require future agri-environmental schemes to foster better opportunities for landscape scale collaboration amongst landholders – a limitation of previous agri-environmental schemes. With the UK's new Environmental Land Management schemes reflecting a stronger emphasis on collaborative management at a landscape scale, the extent to which landowners are willing to collaborate must be better understood. This will enable the potential for a collaborative Nature Recovery Network - set out in the UK's 25 Year Environmental Plan – to be fully realised.Findings from our case study in Bonhurst Farm, UK suggest that while the scenario with the highest connectivity was the preferred choice amongst participants, several barriers stand in the way of implementing it; not least the uncertainty of how it might impact the operation of their farm business. Additionally, concerns around funding, and the lack of clarity and flexibility, of future scheme could potentially hinder uptake. This is in spite of respondents’ strong inclination towards environmental conservation and increasing landscape connectivity. To address these barriers, future policies must not only involve landholders earlier in the development process of these schemes but also consider how their involvement contributes to the formulation of these schemes. Moreover, our findings also indicate that facilitators and advisors serves as key driver to the success of collaborations, with their ability to organise and implement collaborative schemes, along with their expertise knowledge, being seen as invaluable.