String Analysis Research Articles

Structural Characterization and Functional Interaction Analysis of Radiation Induced Protein Flt3 in Human and Mouse

Increasing risk of radiation exposure can be due to various reasons such as terrorist attacks, detonation of nuclear reactors, nuclear weapons, as well as acute radiation exposure on large scale poses high risk to humankind. Therefore, there is a critical need of identification and authentication of fast and early-response radiation induced harm biomarkers to distinguish between exposed and non-exposed individuals on a large-scale basis. This study deals with structural characterization of radiation induced proteins that are probable biomarkers such as Flt3L using database tools such as prot-param for physio-chemical properties, GOR IV to predict the secondary structure, swiss modelling for 3D model of protein, stitch and string analysis for protein-chemical interaction and protein-protein interaction respectively. In-silico analysis showcasing, protein Flt3L physical parameters such as theoretical PI 8.72, hydrophobicity 0.100, aliphatic index 111.81. Secondary structure, alpha helix 41.38%, extended strand 11.64%. Homology modelling showing sequence identity 74.26%, coverage 0.50 and range 1-101. In stich, Flt3 activating KITLG and showing binding affinity to Zn molecule. Identification of protein-protein interacting functional partner of Flt3L using string shows interactions with polyubiquitin-C (UBC), KITLG, Nras proto onco genes, etc, it showed experimental evidence of Flt3L and KITLG protein. Hence, by using in-silico analysis we can perform a preliminary study to predict the structures and chemical interaction of potential radiation induced probable biomarkers that can be utilized for rapid detection of radiation exposure and drugdiscovery.

Identification of Kinase Targets for Enhancing the Antitumor Activity of Eribulin in Triple-Negative Breast Cell Lines.

Triple-negative breast cancer (TNBC) is the most aggressive molecular subtype of breast cancer, and current treatments are only partially effective in disease control. More effective combination approaches are needed to improve the survival of TNBC patients. Eribulin mesylate, a non-taxane microtubule dynamics inhibitor, is approved by the U.S. Food and Drug Administration to treat metastatic breast cancer after at least two previous chemotherapeutic regimens. However, eribulin as a single agent has limited therapeutic efficacy against TNBC. High-throughput kinome library RNAi screening, Ingenuity Pathway Analysis, and STRING analysis were performed to identify target kinases for combination with eribulin. The identified combinations were validated using in vivo and ex vivo proliferation assays. We identified 135 potential kinase targets whose inhibition enhanced the antiproliferation effect of eribulin in TNBC cells, with the PI3K/Akt/mTOR and the MAPK/JNK pathways emerging as the top candidates. Indeed, copanlisib (pan-class I PI3K inhibitor), everolimus (mTOR inhibitor), trametinib (MEK inhibitor), and JNK-IN-8 (pan-JNK inhibitor) produced strong synergistic antiproliferative effects when combined with eribulin, and the PI3K and mTOR inhibitors had the most potent effects in vitro. Our data suggest a new strategy of combining eribulin with PI3K or mTOR inhibitors to treat TNBC.

Hexafluoro-2-propanol represses colorectal cancer proliferation by regulating transaminases.

Hexafluoro-2-propanol (HFIP) is a metabolite of sevoflurane used as part of the general anaesthesia technique. This study aims to investigate the effect of HFIP in colorectal cancer (CRC) and the regulation of associated genes. The differential expressed genes (DEGs) with HFIP treatment were analysed based on GEO dataset GSE56256. Due to the restricted number of studies performing RNA-Seq in CRC with HFIP treatment, we selected a CRC patient cohort (GSE23878) to obtain DEGs that were compared with DEGs from GSE56256. The DEGs with opposite expression patterns in these two GEO datasets indicate that the genes mediate the function of HFIP, thereby repress the progression of CRC. The DEGs from these two GEO datasets were analysed independently. We obtained 10 up-regulated genes in GSE23878 (CRC patient cohort) were also down-regulated in GSE56256 (HFIP cohort), therefore, these 10 genes may function as tumor suppressors in CRC and may be involved in the function of HFIP. STRING analysis demonstrated an interaction in GPT2, PSAT1 and SLC7A11. The high expression of GPT2, PSAT1 and SLC7A11 were confirmed in TCGA-COAD datasets and in CRC cells. HFIP treatment repressed GPT2, PSAT1 and SLC7A11, which resulted in an inhibited proliferation and colony formation ability of DLD-1 and HCT-116 cells. Silencing GPT2, PSAT1 and SLC7A11 showed similar effect compared to HFIP treatment. Overexpression of GPT2, PSAT1 and SLC7A11 abrogated the effect of HFIP. In conclusion, the sevoflurane metabolite HFIP plays a cancer suppression role depending on cell proliferation in colorectal cancer through the down-regulation of GPT2, PSAT1 and SLC7A11 expression.

Transcriptomic and Bioinformatic Analyses Identifying a Central Mif-Cop9-Nf-kB Signaling Network in Innate Immunity Response of Ciona robusta

The Ascidian C. robusta is a powerful model for studying innate immunity. LPS induction activates inflammatory-like reactions in the pharynx and the expression of several innate immune genes in granulocyte hemocytes such as cytokines, for instance, macrophage migration inhibitory factors (CrMifs). This leads to intracellular signaling involving the Nf-kB signaling cascade that triggers downstream pro-inflammatory gene expression. In mammals, the COP9 (Constitutive photomorphogenesis 9) signalosome (CSN) complex also results in the activation of the NF-kB pathway. It is a highly conserved complex in vertebrates, mainly engaged in proteasome degradation which is essential for maintaining processes such as cell cycle, DNA repair, and differentiation. In the present study, we used bioinformatics and in-silico analyses combined with an in-vivo LPS exposure strategy, next-generation sequencing (NGS), and qRT-PCR to elucidate molecules and the temporal dynamics of Mif cytokines, Csn signaling components, and the Nf-κB signaling pathway in C. robusta. A qRT-PCR analysis of immune genes selected from transcriptome data revealed a biphasic activation of the inflammatory response. A phylogenetic and STRING analysis indicated an evolutionarily conserved functional link between the Mif-Csn-Nf-kB axis in ascidian C. robusta during LPS-mediated inflammation response, finely regulated by non-coding molecules such as microRNAs (miRNAs).

Genome-wide screening reveals the genetic basis of mammalian embryonic eye development

BackgroundMicrophthalmia, anophthalmia, and coloboma (MAC) spectrum disease encompasses a group of eye malformations which play a role in childhood visual impairment. Although the predominant cause of eye malformations is known to be heritable in nature, with 80% of cases displaying loss-of-function mutations in the ocular developmental genes OTX2 or SOX2, the genetic abnormalities underlying the remaining cases of MAC are incompletely understood. This study intended to identify the novel genes and pathways required for early eye development. Additionally, pathways involved in eye formation during embryogenesis are also incompletely understood. This study aims to identify the novel genes and pathways required for early eye development through systematic forward screening of the mammalian genome.ResultsQuery of the International Mouse Phenotyping Consortium (IMPC) database (data release 17.0, August 01, 2022) identified 74 unique knockout lines (genes) with genetically associated eye defects in mouse embryos. The vast majority of eye abnormalities were small or absent eyes, findings most relevant to MAC spectrum disease in humans. A literature search showed that 27 of the 74 lines had previously published knockout mouse models, of which only 15 had ocular defects identified in the original publications. These 12 previously published gene knockouts with no reported ocular abnormalities and the 47 unpublished knockouts with ocular abnormalities identified by the IMPC represent 59 genes not previously associated with early eye development in mice. Of these 59, we identified 19 genes with a reported human eye phenotype. Overall, mining of the IMPC data yielded 40 previously unimplicated genes linked to mammalian eye development. Bioinformatic analysis showed that several of the IMPC genes colocalized to several protein anabolic and pluripotency pathways in early eye development. Of note, our analysis suggests that the serine-glycine pathway producing glycine, a mitochondrial one-carbon donator to folate one-carbon metabolism (FOCM), is essential for eye formation.ConclusionsUsing genome-wide phenotype screening of single-gene knockout mouse lines, STRING analysis, and bioinformatic methods, this study identified genes heretofore unassociated with MAC phenotypes providing models to research novel molecular and cellular mechanisms involved in eye development. These findings have the potential to hasten the diagnosis and treatment of this congenital blinding disease.

Sini San inhibits breast cancer cell migration and angiogenesis via the HIF 1 /VEGF pathway

Purpose: To investigate the effects of Sini San (SNS) on breast cancer (BC), and the mechanism of action.Methods: MDA-MB-231 and SK-BR-3 cells were used as breast cancer cell models. Cell viability, migration, and invasion were determined by CCK-8, Transwell and wound healing assays, respectively. SNS mechanism of action and its anti-cancer effect were investigated by network pharmacological analysis, and further verified by Immunoblot.Results: Sini San inhibited the proliferation of the breast cancer (BC) cells., and also suppressed the migration as well as the invasion of BC cells, and also restrained the angiogenesis of BC cells. In performing the network pharmacological analysis of Sini Powder in the treatment of BC, 337 drugdisease targets were obtained. PPI network was established through String, and GO and KEGG enrichment analysis was performed on the target sites. KEGG analysis showed that genes were enriched in HIF-1 and VEGF pathways.Conclusion: Sini San suppressed cell migration as well as angiogenesis via the HIF-1 /VEGF pathway

Enrichr in silico analysis of MS-based extracted candidate proteomic biomarkers highlights pathogenic pathways in systemic sclerosis

Systemic sclerosis (SSc) is a rheumatic disease characterised by vasculopathy, inflammation and fibrosis. Its aetiopathogenesis is still unknown, and the pathways/mechanisms of the disease are not clarified. This study aimed to perform in silico analysis of the already Mass Spectrometry (MS)-based discovered biomarkers of SSc to extract possible pathways/mechanisms implicated in the disease. We recorded all published candidate MS-based found biomarkers related to SSc. We then selected a number of the candidate biomarkers using specific criteria and performed pathway and cellular component analyses using Enrichr. We used PANTHER and STRING to assess the biological processes and the interactions of the recorded proteins, respectively. Pathway analysis extracted several pathways that are associated with the three different stages of SSc pathogenesis. Some of these pathways are also related to other diseases, including autoimmune diseases. We observe that these biomarkers are located in several cellular components and implicated in many biological processes. STRING analysis showed that some proteins interact, creating significant clusters, while others do not display any evidence of an interaction. All these data highlight the complexity of SSc, and further investigation of the extracted pathways/biological processes and interactions may help study the disease from a different angle.

HGCA2.0: An RNA-Seq Based Webtool for Gene Coexpression Analysis in Homo sapiens.

Genes with similar expression patterns in a set of diverse samples may be considered coexpressed. Human Gene Coexpression Analysis 2.0 (HGCA2.0) is a webtool which studies the global coexpression landscape of human genes. The website is based on the hierarchical clustering of 55,431 Homo sapiens genes based on a large-scale coexpression analysis of 3500 GTEx bulk RNA-Seq samples of healthy individuals, which were selected as the best representative samples of each tissue type. HGCA2.0 presents subclades of coexpressed genes to a gene of interest, and performs various built-in gene term enrichment analyses on the coexpressed genes, including gene ontologies, biological pathways, protein families, and diseases, while also being unique in revealing enriched transcription factors driving coexpression. HGCA2.0 has been successful in identifying not only genes with ubiquitous expression patterns, but also tissue-specific genes. Benchmarking showed that HGCA2.0 belongs to the top performing coexpression webtools, as shown by STRING analysis. HGCA2.0 creates working hypotheses for the discovery of gene partners or common biological processes that can be experimentally validated. It offers a simple and intuitive website design and user interface, as well as an API endpoint.

The key role of proteostasis at mitochondria-associated endoplasmic reticulum membrane in vanadium-induced nephrotoxicity using a proteomic strategy

Excessive vanadium (V) contamination is an attracting growing concern, which can negatively affect the health of human and ecosystems. But how V causes nephrotoxicity and the role of mitochondria-associated endoplasmic reticulum membrane (MAM) in V-induced nephrotoxicity have remained elusive. To explore the detailed mechanism and screen of potential effective drugs for V-evoked nephrotoxicity, a total of 72 ducks were divided into two groups, control group and V group (30 mg/kg V). Results showed that excessive V damaged kidney function of ducks including causing histopathological abnormality, biochemical makers derangement and oxidative stress. Then MAM of duck kidneys was extracted to investigate differentially expressed proteins (DEPs) under V exposure using proteomics analysis. Around 4240 MAM-localized proteins were identified, of which 412 DEPs showed dramatic changes, including 335 upregulated and 77 downregulated DEPs. On the basis of gene ontology (GO), string and KEGG database analysis, excessive V led to nephrotoxicity primarily by affecting MAM-mediated metabolic pathways, especially elevating the endoplasmic Reticulum (ER) proteostasis related pathway. Further validation analysis of the detected genes and proteins of ER proteostasis related pathway under V poisoning revealed a consistent relationship with proteome analysis, indicating that V disrupted MAM-mediated ER proteostasis. Accordingly, our data proved the critical role for MAM in V-evoked nephrotoxicity, particularly with MAM-mediated ER proteostasis, providing promising insights into the toxicological exploration mechanisms of V.

Transcriptome Analysis Reveals Genes Involved in Responses of Eucalyptus to Gall Wasp Infestation

Leptocybe invasa is a gall wasp causing significant damage to Eucalyptus species. This study used RNA sequencing (RNA-seq) to identify differentially expressed genes (DEGs) associated with early L. invasa infestation in eucalyptus parents and their F1-progenies. A total of 14,648 significant DEGs were identified from U22-tolerant and C153-susceptible parents, and extremely tolerant and susceptible pools of their F1-progenies. A total of 324/632 and 182/205 DEGs specific for the tolerant group and the susceptible group were up-regulated, respectively. Expression analysis by qRT-PCR of the selected DEGs was comparable with the results of RNA-seq. Expression analysis of the selected genes using the top five progenies from each pool was consistent with that in the parents. Three genes (RCA, SUI1, GCN5) were up-regulated after infestation in all tested tolerant plants, suggesting their important roles in the tolerant phenotype. Using expression and STRING analysis, our results suggest that early response at three days after gall wasp infestation increased protein and terpenoid synthesis, and increased transportation of these molecules. In addition, wounding also increased photosynthesis and glycolysis. These processes involved the interaction of several plant hormones, such as JA, Auxin, and ABA. The information obtained from this study could be useful for future Eucalyptus breeding programs.

Effects of High Glucose on Human Endothelial Cells Exposed to Simulated Microgravity.

A diabetogenic state induced by spaceflight provokes stress and health problems in astronauts. Microgravity (µg) is one of the main stressors in space causing hyperglycaemia. However, the underlying molecular pathways and synergistic effects of µg and hyperglycaemia are not fully understood. In this study, we investigated the effects of high glucose on EA.hy926 endothelial cells in simulated µg (s-µg) using a 3D clinostat and static normogravity (1g) conditions. After 14 days of cell culture under s-µg and 1g conditions, we compared the expression of extracellular matrix (ECM), inflammation, glucose metabolism, and apoptosis-related genes and proteins through qPCR, immunofluorescence, and Western blot analyses, respectively. Apoptosis was evaluated via TUNEL staining. Gene interactions were examined via STRING analysis. Our results show that glucose concentrations had a weaker effect than altered gravity. µg downregulated the ECM gene and protein expression and had a stronger influence on glucose metabolism than hyperglycaemia. Moreover, hyperglycaemia caused more pronounced changes in 3D cultures than in 2D cultures, including bigger and a greater number of spheroids, upregulation of NOX4 and the apoptotic proteins NF-κB and CASP3, and downregulation of fibronectin and transglutaminase-2. Our findings bring new insights into the possible molecular pathways involved in the diabetogenic vascular effects in µg.

The Role of Superoxide Dismutase 1 in Amyotrophic Lateral Sclerosis: Identification of Signaling Pathways, Regulators, Molecular Interaction Networks, and Biological Functions through Bioinformatics.

Mutations in superoxide dismutase 1 (SOD1) result in misfolding and aggregation of the protein, causing neurodegenerative amyotrophic lateral sclerosis (ALS). In recent years, several new SOD1 variants that trigger ALS have been identified, making it increasingly crucial to understand the SOD1 toxicity pathway in ALS. Here we used an integrated bioinformatics approach, including the Ingenuity Pathway Analysis (IPA) tool to analyze signaling pathways, regulators, functions, and network molecules of SOD1 with an emphasis on ALS. IPA toxicity analysis of SOD1 identified superoxide radicals' degradation, apelin adipocyte, ALS, NRF2-mediated oxidative stress response, and sirtuin signaling as the key signaling pathways, while the toxicity of SOD1 is exerted via mitochondrial swelling and oxidative stress. IPA listed CNR1, APLN, BTG2, MAPK, DRAP1, NFE2L2, SNCA, and CG as the upstream regulators of SOD1. IPA further revealed that mutation in SOD1 results in hereditary disorders, including ALS. The exploration of the relationship between SOD1 and ALS using IPA unveiled SOD1-ALS pathway molecules. The gene ontology (GO) analysis of SOD1-ALS pathway molecules with ShinyGO reaffirmed that SOD1 toxicity results in ALS and neurodegeneration. The GO analysis further identified enriched biological processes, molecular functions, and cellular components for SOD1-ALS pathway molecules. The construction of a protein-protein interaction network of SOD1-ALS pathway molecules using STRING and further analysis of that network with Cytoscape identified ACTB followed by TP53, IL6, CASP3, SOD1, IL1B, APP, APOE, and VEGFA as the major network hubs. Taken together, our study provides insight into the molecular underpinning of SOD1's toxicity in ALS.

Characteristics and possible mechanisms of metabolic disorder in overweight women with polycystic ovary syndrome.

Polycystic ovary syndrome (PCOS) is a kind of endocrine and metabolic disorder, disturbing the females of reproductive age. Here, we aimed to investigate the metabolic characteristics of overweight women with PCOS and analyze the possible mechanisms. We conducted a cross-sectional study on 947 patients with PCOS, who were classified according to body mass index (BMI) as overweight (BMI ≥ 24 kg/m2) or non-overweight (BMI ≤ 23.9 kg/m2). The clinical symptoms, endocrine features, metabolic status, and inflammatory levels of the patients were comprehensively assessed and compared between the patients of the two groups. Additionally, a predictive study on the correlation between inflammation and metabolism was performed using STRING and Cytoscape software, and the possible mechanisms of metabolic disorders involved in the overweight PCOS were preliminarily explored. Overweight PCOS was associated with increased average age, waist-to-hip ratio, and the incidence of acanthosis nigricans. These patients were susceptible to familial hypertension and diabetes, and exhibited evident characteristics of low levels of luteinizing hormone (LH) and the ratio of LH to follicle-stimulating hormone, and were more inclined to insulin resistance (IR). Furthermore, overweight PCOS presented with a chronic low-grade inflammation state with increased levels of inflammatory cytokines complement components C5/C5α, CXCL12/SDF-1, MIF, and Serpin E1/PAI-1 evidently compared with those in non-overweight PCOS. Pearson analysis showed that these inflammatory cytokines were directly or indirectly correlated with IR. The STRING and Cytoscape network analysis predicted that inflammatory cytokines CXCL12/SDF-1, Serpin E1/PAI-1 and MIF might be crucial for inducing IR in overweight PCOS women through various biological functions and signal transductions including the JAK-STAT cascade, ATP biosynthesis, and HIF-1 signaling. Overweight patients with PCOS are prone to low gonadal levels, IR, and chronic low-grade inflammation. Inflammatory cytokines CXCL12/SDF-1, Serpin E1/PAI-1and MIF might lead to IR through multiple biological functions and signal transductions in overweight PCOS.

Identification and clinical validation of key genes as the potential biomarkers in colorectal adenoma

BackgroundColorectal cancer (CRC), ranking third in cancer prevalence and second in mortality worldwide, is mainly derived from colorectal adenoma (CRA). CRA is a common benign disease in the intestine with rapidly increasing incidence and malignant potential. Therefore, this study aimed to recognize significant biomarkers and original pathogenesis in CRA.MethodsTranscriptome data of GSE8671, GSE37364, and GSE15960 were downloaded from the Gene Expression Omnibus (GEO) datasets, and differentially expressed genes (DEGs) were screened. Functional pathways enrichment, protein–protein interaction (PPI) network, stem-correlation analysis, CIBERSORT, risk score and survival analyses were performed. RT-qPCR and immunohistochemical staining were applied to verify our results. ResultsScreening for significant DEGs in each dataset, we identified 230 robust DEGs, including 127 upregulated and 103 downregulated genes. Functional pathways enrichment showed that these DEGs were distinctly enriched in various tumor-associated pathways, such as growth factor activity, extracellular structure organization, neutrophil activation, and inflammatory response. We filtered out two hub genes via STRING and Modules analysis, including CA2 and HSD11B2. Stem-correlation analysis displayed that hub genes were negatively associated with stem-related genes (Olfm4, CD44, CCND1 and MYC). The CIBERSORT algorithm indicated that Macrophage2, activated mast cells, and Neutrophils promoted CRA progression through inflammation. Survival analysis showed that CA2 and HSD11B2 were positively associated with survival outcomes in CRC.ConclusionOur study has successfully identified the critical role of two core genes in the development and oncogenesis of CRA, which provides novel insight into the underlying pathogenesis, potential biomarkers and therapeutic targets.

Digital twin and contact analysis of ultra-long distance coiled tubing operation structures

Background: Coiled tubing operation is a high-quality operation method that considers both cost and efficiency in current oil and gas well operations. There is a significant difference between the calculation and prediction before operation and the actual operation. The reason is that the complex wellbore trajectory makes it difficult to evaluate the contact state between coiled tubing and wellbore, resulting in a significant error in the pipe string mechanics calculation and analysis. Methods: Aiming at the contact problem between coiled tubing and wellbore in the process of coiled tubing operation, the digital twin unit of coiled tubing and wellbore is established in this study. By constructing a feedback correction collision contact algorithm, the contact state of coiled tubing and casing under different three-dimensional trajectory models was simulated. Results: The research results show that the digital twin coiled tubing and contact algorithm can effectively predict the contact state of coiled tubing operations; the verification model shows that the contact algorithm can accurately analyze the contact state of different well trajectories. Conclusions: The digital twin of the coiled tubing operation structure and its contact algorithm can effectively solve the problem of deterministic friction state in the process of mechanical calculation of the tubing string, which has important guiding significance and engineering value for the mechanical calculation and operation safety analysis of coiled tubing operation.

Comprehensively analyzing the genetic alterations, and identifying key genes in ovarian cancer.

Though significant improvements have been made in the treatment methods for ovarian cancer (OC), the prognosis for OC patients is still poor. Exploring hub genes associated with the development of OC and utilizing them as appropriate potential biomarkers or therapeutic targets is highly valuable. In this study, the differentially expressed genes (DEGs) were identified from an independent GSE69428 Gene Expression Omnibus (GEO) dataset between OC and control samples. The DEGs were processed to construct the protein-protein interaction (PPI) network using STRING. Later, hub genes were identified through Cytohubba analysis of the Cytoscape. Expression and survival profiling of the hub genes were validated using GEPIA, OncoDB, and GENT2. For exploring promoter methylation levels and genetic alterations in hub genes, MEXPRESS and cBioPortal were utilized, respectively. Moreover, DAVID, HPA, TIMER, CancerSEA, ENCORI, DrugBank, and GSCAlite were used for gene enrichment analysis, subcellular localization analysis, immune cell infiltration analysis, exploring correlations between hub genes and different diverse states, lncRNA-miRNA-mRNA co-regulatory network analysis, predicting hub gene-associated drugs, and conducting drug sensitivity analysis, respectively. In total, 8947 DEGs were found between OC and normal samples in GSE69428. After STRING and Cytohubba analysis, 4 hub genes including TTK (TTK Protein Kinase), (BUB1 mitotic checkpoint serine/threonine kinase B) BUB1B, (Nucleolar and spindle-associated protein 1) NUSAP1, and (ZW10 interacting kinetochore protein) ZWINT were selected as the hub genes. Further, it was validated that these 4 hub genes were significantly up-regulated in OC samples compared to normal controls, but overexpression of these genes was not associated with overall survival (OS). However, genetic alterations in those genes were found to be linked with OS and disease-free (DFS) survival. Moreover, this study also revealed some novel links between TTK, BUB1B, NUSAP1, and ZWINT overexpression and promoter methylation status, immune cell infiltration, miRNAs, gene enrichment terms, and various chemotherapeutic drugs. Four hub genes, including TTK, BUB1B, NUSAP1, and ZWINT, were revealed as tumor-promotive factors in OC, having the potential to be utilized as novel biomarkers and therapeutic targets for OC management.

Utilizing In Silico Approaches to Investigate the Signaling Pathway's Crucial Function in Pennisetum glaucum Under Thermal Stress.

Pearl millet (Pennisetum glaucum (L.)) is a remarkable cereal crop known for its ability to thrive in challenging environmental conditions. Despite its resilience, the intricate molecular mechanisms behind its toughness remain a mystery. To address this knowledge gap, we conducted advanced next-generation RNA sequencing. This approach allowed us to compare the gene expression profiles of pearl millet seedlings exposed to heat stress with those grown under standard conditions. Our main focus was on the shoots of 13-day-old pearl millet plants, which we subjected to a brief heat stress episode at 50°C for 60 seconds. Within the vast genomic landscape comprising 36 041 genes, we successfully identified a set of 10 genes that exhibited significant fold changes, ranging from 11 to 14-fold compared to the control conditions. These 10 genes were previously unknown to have such substantial changes in expression compared to the control. To uncover the functional significance hidden within these transcriptomic findings, we utilized computational tools such as MEME, String, and phylogenetic tree analysis. These efforts collectively revealed conserved domains within the transcriptomic landscape, hinting at potential functions associated with these genetic sequences. Of particular note, the distinct transcriptomic patterns specific to pearl millet leaves under thermal stress shed light on intricate connections to fundamental biological processes. These processes included the Ethylene-activated signaling pathway, Regulation of intracellular signal transduction, Negative regulation of signal transduction, Protein autophosphorylation, and Intracellular signal transduction. Together, these processes provide insight into the molecular strategies employed by pearl millet to overcome thermal stress challenges. By integrating cutting-edge RNA sequencing techniques and computational analyses, we have embarked on unraveling the genetic components and pathways that empower pearl millet's resilience in the face of adversity. This newfound understanding has the potential to not only advance our knowledge of plant stress responses but also contribute to enhancing crop resilience in challenging environmental conditions.

Next generation drug connectivity mapping for acquiring therapeutic agents to differentially regulate myelination.

Next generation drug connectivity mapping for acquiring therapeutic agents to differentially regulate myelination.

Association of IL-8-251T/A (rs4073) gene polymorphism with Systemic lupus erythematosus in a cohort of Egyptian patients.

Systemic lupus erythematosus (SLE) susceptibility was found to be correlated with genetic polymorphisms. Therefore, the current study aimed to investigate the association of the IL-8-251T/A polymorphism with the risk of SLE. A total of 135 SLE patients and 75 controls were enrolled in our study. The IL-8-251T/A polymorphism was analysed by PCR-RFLP. Also, the serum concentration of IL-8 was measured using ELISA. Finally, investigate possible IL-8 pathways in SLE pathogenesis by using the STRING database. Our results revealed that the risk of having SLE in AA genotype carriers was significantly increased (OR=1.92, 95% CI=1.23-3.10, p=0.006) when compared with TT genotype carriers. Patients with SLE had a significantly higher frequency of the A allele (OR=1.37, 95% CI=1.09-1.7; P=0.01) than controls. Serum IL-8 levels were significantly increased in SLE patients (77.81±21.27; p<0.001) when compared to healthy controls (48.85±7.89). Also, it was found that the serum IL-8 level had significant positive correlations with proteinuria, ESR, ANA, urea and SELADI, and significant negative correlations with RBCs count, C3 and hemoglobin. According to ROC curve analysis, serum IL-8 levels are a good biomarker for the detection of SLE disease, with 87.5% sensitivity and 85% specificity. STRING analysis revealed that IL-8 interacts with key SLE signaling pathway members such as TNF-α, IL-1β, IL-6, and IL-10. There was a correlation between the IL-8-251T/A polymorphism and the risk of SLE. Our findings also suggest that the IL8-251 A allele may be an important risk factor for the development of SLE.

Identification of Kynurenic Acid-Induced Apoptotic Biomarkers in Gastric Cancer-Derived AGS Cells through Next-Generation Transcriptome Sequencing Analysis

Understanding the triggers and therapeutic targets for gastric cancer, one of the most common cancers worldwide, can provide helpful information for the development of therapeutics. RNA sequencing technology can be utilized to identify complex disease targets and therapeutic applications. In the present study, we aimed to establish the pharmacological target of Kynurenic acid (KYNA) for gastric cancer AGS cells and to identify the biological network. RNA sequencing identified differentially expressed genes (DEGs) between KYNA-treated and untreated cells. A total of 278 genes were differentially expressed, of which 120 genes were up-regulated, and 158 genes were down-regulated. Gene ontology results confirmed that KYNA had effects such as a reduction in genes related to DNA replication and nucleosome organization on AGS cells. Protein-protein interaction was confirmed through STRING analysis, and it was confirmed that cancer cell growth and proliferation were inhibited through KEGG, Reactome, and Wiki pathway analysis, and various signaling pathways related to cancer cell death were induced. It was confirmed that KYNA treatment reduced the gene expression of cancer-causing AP-1 factors (Fos, Jun, ATF, and JDP) in AGS cell lines derived from gastric cancer. Overall, using next-generation transcriptome sequencing data and bioinformatics tools, we confirmed that KYNA had an apoptosis effect by inducing changes in various genes, including factor AP-1, in gastric cancer AGS cells. This study can identify pharmacological targets for gastric cancer treatment and provide a valuable resource for drug development.