Bioinformatics Methods Research Articles

NeoaPred: a deep-learning framework for predicting immunogenic neoantigen based on surface and structural features of peptide-human leukocyte antigen complexes.

Neoantigens, derived from somatic mutations in cancer cells, can elicit anti-tumor immune responses when presented to autologous T cells by human leukocyte antigen. Identifying immunogenic neoantigens is crucial for cancer immunotherapy development. However, the accuracy of current bioinformatic methods remains unsatisfactory. Surface and structural features of peptide-HLA class I (pHLA-I) complexes offer valuable insight into the immunogenicity of neoantigens. We present NeoaPred, a deep-learning framework for neoantigen prediction. NeoaPred accurately constructs pHLA-I complex structures, with 82.37% of the predicted structures showing an RMSD of < 1 Å. Using these structures, NeoaPred integrates differences in surface, structural, and atom group features between the mutant peptide and its wild-type counterpart to predict a foreignness score. This foreignness score is an effective factor for neoantigen prediction, achieving an AUROC (Area Under the Receiver Operating Characteristic Curve) of 0.81 and an AUPRC (Area Under the Precision-Recall Curve) of 0.54 in the test set, outperforming existing methods. The source code is released under an Apache v2.0 license and is available at the GitHub repository (https://github.com/Dulab2020/NeoaPred).

Identification of mitophagy-related genes and analysis of immune infiltration in the astrocytes based on machine learning in the pathogenesis of major depressive disorder

BackgroundsMajor depressive disorder (MDD) is a pervasive mental and mood disorder with complicated and heterogeneous etiology. Mitophagy, a selective autophagy of cells, specifically eliminates dysfunctional mitochondria. The mitochondria dysfunction in the astrocytes is regarded as a critical pathogenetic mechanism of MDD. However, studies on the mitophagy of astrocytes in MDD are scarce. To explore the impact of mitophagy on the astrocytes, we used bioinformatic methods to analyze the correlation between astrocyte-related genes and mitophagy-related genes in MDD. MethodsThe microarray dataset of MDD was downloaded from the Gene Expression Omnibus database and identified astrocyte- and mitophagy-related differentially expressed genes (AMRDEGs). We used three machine learning algorithms to identify hub AMRDEGs and constructed a diagnostic prediction model. Also, we analyzed transcription factor-gene and gene-microRNA interaction networks, and the immune infiltration in MDD and healthy controls. Besides, we performed consensus clustering analysis, immune infiltration analysis, and gene set variation analysis of MDD samples. ResultsThe present research identified 3 hub AMRDEGs (GRN, NDUFAF4, and SNCA), and a good diagnostic model with potential clinical applications was constructed and validated. Besides, we identified 6 transcription factors and 14 microRNAs. The immune infiltration analysis showed that MDD was closely related to immune cells. Gene set variant analysis showed that MDD was related to immune and mitochondrial metabolism and inflammatory signaling pathways. ConclusionsWe identified 3 hub AMRDEGs, new biomarkers for treating and diagnosing MDD and associated with immuno-inflammation. Our research provides new insights into the early diagnosis and treatment of MDD.

Elucidation of the molecular mechanism of type 2 diabetes mellitus affecting the progression of nonalcoholic steatohepatitis using bioinformatics and network pharmacology: A review.

Increasing evidence suggests that patients with diabetes are at increased risk of developing nonalcoholic steatohepatitis (NASH), but the underlying mechanisms that affect the progression of NASH remain unclear. In this study, we used bioinformatics and network pharmacology methods to explore the differentially expressed genes of NASH and the related genes of type 2 diabetes mellitus, and a total of 46 common targets were obtained. Gene ontology showed that the common targets were mainly involved in biological processes such as glucocorticoid, hormone, and bacterium responses. The Kyoto Encyclopedia of Genes and Genomes enrichment analysis signal pathways were mainly in colorectal cancer, amphetamine addition, the peroxisome proliferator-activated receptor signaling pathway, and the toll-like receptor signaling pathway. The protein-protein interaction network identified 8 hub genes, and the co-expression network was analyzed to obtain 7 related functions and mutual proportions of hub genes. A total of 120 transcription factors were predicted for hub genes. Hub genes were closely related to immune cells, including neutropils and eosinophils. In addition, we identified 15 potential candidate drugs based on hub genes that are promising for the treatment of NASH. Type 2 diabetes mellitus can affect the progression of NASH by changing hormone levels and inflammatory responses through multiple targets and signaling pathways. Eight hub genes are expected to be potential targets for subsequent treatment.

Quercetin 7-rhamnoside from Sorbaria sorbifolia exerts anti-hepatocellular carcinoma effect via DHRS13/apoptotic pathway

BackgroundPrevious research demonstrated the effects of Sorbaria sorbifolia (SS) in combating hepatocellular carcinoma (HCC). Despite SS's proven efficacy in treating HCC, the precise bioactive constituents contributing to its therapeutic benefits, along with the mechanisms behind them, warrant further exploration. PurposeThe objective of our study was to illuminate the possible elements, targets, and modulatory pathways employed by specific bioactive components in SS for HCC treatment. Study designUsing UPLC-Q-TOF-MS to analyze and quantify the bioactive constituents in the SS sample. By literature review, we gathered potential chemical constituents of SS. We used network pharmacology approaches to identify HCC-related targets of SS components, with an emphasis on core targets. To examine the core targets' importance in HCC biological processes, bioinformatics methods were utilized. Finally, molecular docking, MD simulations, and CESTA were employed to screen SS active ingredients capable of stably binding with core targets. To verify the anti-HCC effectiveness of these active components, we conducted several cellular experiments, including CCK8, wound healing, transwell, cell cycle, and apoptosis assays, as well as animal experiments like zebrafish HepG2 cell xenotransplantation, apoptosis assays, and HE staining. We also used lentivirus transfection to modulate core protein expression in HepG2 cells, creating cell models. Further cellular tests were performed to evaluate the ability of SS active ingredients to exert anti-HCC effects by interacting with the core protein to induce apoptosis. Finally, Western Blot and ELISA experiments were carried out to track changes in core protein and apoptosis-related pathway proteins after SS active ingredient treatment ResultsOur study identified 50 components in SS and 119 HCC-related target genes, with DHRS13 emerging as a core target. Further bioinformatics analysis indicated that DHRS13 expression in HCC patients correlated with prognosis and apoptotic pathways. Molecular docking revealed 20 active SS constituents effectively binding to DHRS13, MD simulations and CESTA pinpointed Quercetin 7-rhamnoside (Q7R) as the most stable binder. In-vitro and in-vivo tests verified Q7R's anti-HCC properties. Lentivirus transfection results showed that knockdown DHRS13 led to reduced cell growth and increased apoptosis, while overexpression DHRS13 led to increase cell growth and decrease apoptosis. Remarkably, our experiments found that Q7R acts as an inhibitor of DHRS13 and can reverse the suppressed apoptosis and excessive HCC proliferation caused by DHRS13 overexpression. ConclusionElevated DHRS13 expression contributes to HCC progression. Q7R effectively downregulates DHRS13, encouraging apoptosis and impeding HCC growth. As a result, Q7R shows potential as a therapeutic agent for HCC treatment, targeting the apoptotic pathway through DHRS13 regulation.

GAD1 ameliorates glioma progression through regulating cuproptosis via RAS/MAPK pathway.

Glioma represents a primary malignant tumor occurring in the central nervous system. Glutamate decarboxylase (GAD1) plays a significant role in tumor development; however, its function of GAD1 and underlying mechanisms in glioma progression remain unclear. Differentially expressed genes (DEGs) obtained from the GSE12657 and GSE15209 datasets that intersected with cuproptosis-related genes and pivot genes were identified using comprehensive bioinformatics methods. The elesclomol (ES) treatment was used to induce cuproptosis in U251 cells, which was validated by detecting intracellular copper levels and cuproptosis marker expression. Lentivirus-mediated gene overexpression was performed to explore the effects of GAD1 using functional assays in vitro and in a mouse xenograft model. The RAS agonist ML098 was used to verify the effect of GAD1 on the RAS/MAPK pathway in glioma cells. A total of 87 cuproptosis-related DEGs and seven hub genes were obtained, with five genes upregulated and two were downregulated in gliomas. Overexpression of GAD1 inhibited proliferation, invasion, and migration, promoted apoptosis of glioma cells, and suppressed tumorigenesis in vivo. In addition, GAD1 overexpression enhanced the sensitivity of glioma cells to cuproptosis. Additionally, ML098 treatment attenuated the inhibitory effect of GAD1 overexpression on the malignant phenotype of ES-treated cells. GAD1 plays an anti-oncogenic role in glioma by regulating apoptosis via inhibition of the RAS/MAPK pathway.

Bioinformatics-based Identification of Ferroptosis-related Genes and their Diagnostic Value in Gestational Diabetes Mellitus.

Gestational diabetes mellitus (GDM) is considered a risk factor for heart metabolic disorder in future mothers and offspring. Ferroptosis is a new type of programmed cell death, which may participate in the occurrence and development of GDM. This study aims to identify ferroptosis-related genes in GDM by bioinformatics methods and to explore their clinical diagnostic value. The dataset GSE103552 was analyzed using the Gene Expression Omnibus (GEO) database to screen for differentially expressed genes (DEGs) in GDM. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and proteinprotein interaction (PPI) network were performed. Gene sets for ferroptosis were retrieved in MSigDB and GSVA gene set analysis was performed on the database. Finally, logistic regression was performed to differentiate between GDM patients and controls to screen for diagnostic markers. A total of 179 DEGs were identified in the expression profile of GDM. GO and KEGG enrichment analysis revealed significant enrichment in the TGF-β, p53 signaling pathway, platelet activation, glutathione metabolism, sensory perception of taste, and leukocyte and vascular endothelial cell migration regulation. DEGs (n = 107) associated with the ferroptosis gene set were screened by GSVA analysis. The screened DEGs for disease and DEGs for ferroptosis scores were intersected and 35 intersected genes were identified. PPI identified two key genes associated with GDM as CCNB2 and CDK1. Wilcox-test showed low expression of CCNB2 and CDK1 in GDM. The area under the ROC curve (AUC) of the CCNB2 and CDK1 prognostic model was 0.822. The genes associated with ferroptosis in GDM were CCNB2 and CDK1, which can be used as valid indicators for the diagnosis of GDM.

A cancer-associated fibroblasts related risk score (CAFscore) helps to guide prognosis and personal treatment for Glioblastoma

BackgroundRecent studies have identified the presence of cancer-associated fibroblasts (CAFs) within glioblastoma (GBM), yet their biological roles and underlying mechanisms remain poorly understood. This study aimed to construct a CAF-related prognostic model to guide patient prognosis and treatment strategies.MethodWe employed various bioinformatics methods, including enrichment analysis, Weighted Gene Co-expression Network Analysis (WGCNA), Lasso regression analysis, and machine learning techniques such as XGBoost and Random Forest, to develop a novel risk index termed CAFscore. Patients were stratified into high and low CAFscore groups for subsequent survival analysis. The area under the curve (AUC) and concordance index (C-index) for CAFscore were calculated and compared against other clinical characteristics and existing prognostic models. Drug sensitivity assessments were conducted using the Oncopredict package. Functional validation of key genes was performed through scratch and invasion assays in GBM cells.ResultsOur analyses revealed four core CAF-related genes, leading to the establishment of CAFscore. Notably, patients in the high CAFscore group exhibited significantly reduced survival and exhibited enrichment in epithelial-mesenchymal transition (EMT) and inflammation response pathways. Furthermore, CAFscore showed a significant negative correlation with the sensitivity to irinotecan and its analogs, while demonstrating a positive correlation with sensitivity to 505,124 (a TGFβRI inhibitor). LRP10 emerged as a central gene within the CAFscore, displaying markedly elevated expression in GBM and a strong association with CAF infiltration. Silencing LRP10 significantly inhibited the invasive capabilities of GBM cells.ConclusionThis study presented the first CAF related prognostic model (CAFscore) in GBM, and demonstrated that the model could effectively guide patient prognosis and potentially inform personalized treatment strategies. The core gene of CAFscore, LRP10, was significantly overexpressed in GBM and might play a pivotal role in regulating CAF infiltration as well as tumor invasion and metastasis, highlighting LRP10 as a promising therapeutic target for GBM management.

The Roles of Glutaredoxins in Wheat (Triticum aestivum L.) under Biotic and Abiotic Stress Conditions, including Fungal and Hormone Treatments

Glutaredoxins (GRXs) are widely distributed oxidoreductase enzymes that play important roles in plant growth, development, and responses to various stresses. In this study, bioinformatics methods were used to identify and analyze the wheat GRX gene family and predict their properties and potential functions. RNA-seq and RT-qPCR expression analyses were used to investigate their regulatory functions under hormone treatment and fungal diseases. In this study, 86 GRX genes were identified in wheat and classified into CC-type, CGFS-type, and CPYC-type categories with no TaGRX located on chromosome 4B. The results show that TaGRXs regulate wheat transcriptional responses and have an integrative role in biotic and abiotic stress responses. TaGRXs are involved in wheat responses to Fusarium graminearum, Puccinia striiformis, and Erysiphe graminis diseases. TaGRX73-7D, TaGRX20-3A, and TaGRX29-3B play a negative regulatory role in E. graminis infection but a positive regulatory role in F. graminearum and P. striiformis infection. These TaGRXs play potential regulatory functions in wheat responses to the plant hormones and signaling molecules, including IAA, ABA, H2O2, and SA. The findings of this study lay the groundwork for further investigation of the functions of wheat GRX genes and their potential use as candidate genes for molecular breeding of stress-resistant wheat varieties.

Genome-wide analysis of the passion fruit invertase gene family reveals involvement of PeCWINV5 in hexose accumulation

BackgroundInvertases (INVs) are key enzymes in sugar metabolism, cleaving sucrose into glucose and fructose and playing an important role in plant development and the stress response, however, the INV gene family in passion fruit has not been systematically reported.ResultsIn this study, a total of 16 PeINV genes were identified from the passion fruit genome and named according to their subcellular location and chromosome position. These include six cell wall invertase (CWINV) genes, two vacuolar invertase (VINV) genes, and eight neutral/alkaline invertase (N/AINV) genes. The gene structures, phylogenetic tree, and cis-acting elements of PeINV gene family were predicted using bioinformatics methods. Results showed that the upstream promoter region of the PeINV genes contained various response elements; particularly, PeVINV2, PeN/AINV3, PeN/AINV5, PeN/AINV6, PeN/AINV7, and PeN/AINV8 had more response elements. Additionally, the expression profiles of PeINV genes under different abiotic stresses (drought, salt, cold temperature, and high temperature) indicated that PeCWINV5, PeCWINV6, PeVINV1, PeVINV2, PeN/AINV2, PeN/AINV3, PeN/AINV6, and PeN/AINV7 responded significantly to these abiotic stresses, which was consistent with cis-acting element prediction results. Sucrose, glucose, and fructose are main soluble components in passion fruit pulp. The contents of total soluble sugar, hexoses, and sweetness index increased significantly at early stages during fruit ripening. Transcriptome data showed that with an increase in fruit development and maturity, the expression levels of PeCWINV2, PeCWINV5, and PeN/AINV3 exhibited an up-regulated trend, especially for PeCWINV5 which showed highest abundance, this correlated with the accumulation of soluble sugar and sweetness index. Transient overexpression results demonstrated that the contents of fructose, glucose and sucrose increased in the pulp of PeCWINV5 overexpressing fruit. It is speculated that this cell wall invertase gene, PeCWINV5, may play an important role in sucrose unloading and hexose accumulation.ConclusionIn this study, we systematically identified INV genes in passion fruit for the first time and further investigated their physicochemical properties, evolution, and expression patterns. Furthermore, we screened out a key candidate gene involved in hexose accumulation. This study lays a foundation for further study on INV genes and will be beneficial on the genetic improvement of passion fruit breeding.

Simulated High Throughput Sequencing Datasets: A Crucial Tool for Validating Bioinformatic Pathogen Detection Pipelines.

The validation of diagnostic assays in plant pathogen detection is a critical area of research. It requires the use of both negative and positive controls containing a known quantity of the target pathogen, which are crucial elements when calculating analytical sensitivity and specificity, among other diagnostic performance metrics. High Throughput Sequencing (HTS) is a method that allows the simultaneous detection of a theoretically unlimited number of plant pathogens. However, accurately identifying the pathogen from HTS data is directly related to the bioinformatic pipeline utilized and its effectiveness at correctly assigning reads to their associated taxa. To this day, there is no consensus about the pipeline that should be used to detect the pathogens in HTS data, and results often undergo review and scientific evaluation. It is, therefore, imperative to establish HTS resources tailored for evaluating the performance of bioinformatic pipelines utilized in plant pathogen detection. Standardized artificial HTS datasets can be used as a benchmark by allowing users to test their pipelines for various pathogen infection scenarios, some of the most prevalent being multiple infections, low titer pathogens, mutations, and new strains, among others. Having these artificial HTS datasets in the hands of HTS diagnostic assay validators can help resolve challenges encountered when implementing bioinformatics pipelines for routine pathogen detection. Offering these purely artificial HTS datasets as benchmarking tools will significantly advance research on plant pathogen detection using HTS and enable a more robust and standardized evaluation of the bioinformatic methods, thereby enhancing the field of plant pathogen detection.

NR3C2 affects the proliferation and invasiveness of colon cancer cells through the Wnt/β-Catenin signaling pathway

PurposeThe aim of this study was to explore the potential correlation between the nuclear receptor subfamily 3 group C member 2 (NR3C2) and outcomes of colon cancer, along with the mechanisms underlying this association.MethodmRNA (messenger RNA) data and clinical records pertaining to colon cancer were retrieved from The Cancer Genome Atlas (TCGA) database. The analysis of NR3C2 expression discrepancies between normal colon and tumor tissues was conducted using R software. In addition, we also studied the relationship between NR3C2 expression and prognosis, pathological parameters. The relative role of NR3C2 were further predicted through bioinformatics methods and receiver operating characteristic (ROC) curve was used to evaluate the diagnostic value of NR3C2 in colon cancer. Single-cell data from colon cancer samples in the GEO (Gene Expression Omnibus) database further investigated the mechanism of the lower survival associated with NR3C2 dysregulation. NR3C2 expression in three fresh colon cancer samples and their respective paracancer samples was determined. Furthermore, colon cancer cell models overexpressing NR3C2 and with knockdown NR3C2 were constructed by lentiviral vector transfection. Cell Counting Kit-8 assay, transplantation of tumors in nude mice and transwell assays were used to examine the proliferation, migration and invasion of colon cancer cells. The effect on the Wnt/β-catenin pathway, activities of cellular autophagy and cell apoptosis were examined by assessing the expression levels of several key proteins, including Bcl-2, Bax, and LC3.ResultsWe found that NR3C2 was found a significantly lower level in colon cancer tissues than in adjacent tissues, which was associated with distant and lymphatic metastases, clinical stage, and poor clinical outcome, and it was an independent prognostic factor and potential marker of colon cancer. Single-cell transcriptome data identified the subset of circulating T and B cells with high expression of NR3C2, which is involved in TNF signaling pathway. Functional experiments show that downregulation of NR3C2 resultsed in the activation of the Wnt/β-catenin signaling pathway, and promotesd the proliferation and invasion of colon cancer cells while suppressing cell autophagy and apoptosis.ConclusionNR3C2 may regulate Wnt/β-catenin to affect the proliferation, invasion apoptosis and autophagy of colon cancer, and this axis is a potential target for the treatment of colon cancer.

Genomic Profiling of Antimicrobial Resistance Genes in Clinical Salmonella Isolates from Cattle in the Texas Panhandle, USA.

Rising antimicrobial resistance (AMR) in Salmonella serotypes host-adapted to cattle is of increasing concern to the beef and dairy industry. The bulk of the existing literature focuses on AMR post-slaughter. In comparison, the understanding of AMR in Salmonella among pre-harvest cattle is still limited, particularly in Texas, which ranks top five in beef and dairy exports in the United States; inherently, the health of Texas cattle has nationwide implications for the health of the United States beef and dairy industry. In this study, long-read whole genome sequencing and bioinformatic methods were utilized to analyze antimicrobial resistance genes (ARGs) in 98 isolates from beef and dairy cattle in the Texas Panhandle. Fisher exact tests and elastic net models accounting for population structure were used to infer associations between genomic ARG profiles and antimicrobial phenotypic profiles and metadata. Gene mapping was also performed to assess the role of mobile genetic elements in harboring ARGs. Antimicrobial resistance genes were found to be statistically different between the type of cattle operation and Salmonella serotypes. Beef operations were statistically significantly associated with more ARGs compared to dairy operations. Salmonella Heidelberg, followed by Salmonella Dublin isolates, were associated with the most ARGs. Additionally, specific classes of ARGs were only present within mobile genetic elements.

Mitochondrial genome study of Camellia oleifera revealed the tandem conserved gene cluster of nad5-nads in evolution.

Camellia oleifera is a kind of high-quality oil supply species. Its seeds contain rich unsaturated fatty acids and antioxidant active ingredients, which is a kind of high-quality edible oil. In this study, we used bioinformatics methods to decipher a hexaploid Camellia oil tree's mitochondrial (mt) genome based on second-generation sequencing data. A 709,596 bp circular map of C. oleifera mt genome was found for the first time. And 74 genes were annotated in the whole genome. Mt genomes of C. oleifera and three Theaceae species had regions with high similarity, including gene composition and gene sequence. At the same time, five conserved gene pairs were found in 20 species. In all of the mt genomes, most of nad genes existed in tandem pairs. In addition, the species classification result, which, according to the gene differences in tandem with nad5 genes, was consistent with the phylogenetic tree. These initial results provide a valuable basis for the further researches of Camellia oleifera and a reference for the systematic evolution of plant mt genomes.

Prospects for mineral biofortification of wheat: classical breeding and agronomy.

Low intake of micro- and macroelements and vitamins in food negatively affects the health of more than two billion people around the world provoking chronic diseases. For the majority of the world's population, these are soft and durum wheats that provide beneficial nutrients, however their modern high-yielding varieties have a significantly depleted grain mineral composition that have reduced mineral intake through food. Biofortification is a new research trend, whose main goal is to improve the nutritional qualities of agricultural crops using a set of classical (hybridization and selection) methods as well and the modern ones employing gene/QTL mapping, bioinformatic analysis, transgenesis, mutagenesis and genome editing. Using the classical breeding methods, biofortified varieties have been bred as a part of various international programs funded by HarvestPlus, CIMMYT, ICARDA. Despite the promise of transgenesis and genome editing, these labor-intensive methods require significant investments, so these technologies, when applied to wheat, are still at the development stage and cannot be applied routinely. In recent years, the interest in wheat biofortification has increased due to the advances in mapping genes and QTLs for agronomically important traits. The new markers obtained from wheat genome sequencing and application of bioinformatic methods (GWAS, meta-QTL analysis) has expanded our knowledge on the traits that determine the grain mineral concentration and has identified the key gene candidates. This review describes the current research on genetic biofortification of wheat in the world and in Russia and provides information on the use of cultivated and wild-relative germplasms to expand the genetic diversity of modern wheat varieties.

Early diagnosis of Trichinella spiralis and Trichinella nativa: Expression of the serine protease gene at the invasive intestinal and muscular larva stages.

Diagnosis of trichinellosis at the intestinal stage during larval development is the primary challenge in the early detection and treatment of trichinellosis. The use of serine protease as a diagnostic marker for serological tests has been the subject of various studies, but data on Trichinella nativa serine protease in the intestinal phase are still insufficient for a proper diagnosis. This study aimed to establish the duration of the intestinal phase for early diagnosis and to determine the level of expression of the serine protease gene in T. nativa and Trichinella spiralis larvae. We used European isolates from T. spiralis pigs and T. nativa larvae isolated from spontaneously infected wild carnivorous animals (wolf, Karaganda region) in Central Kazakhstan. Isolation of larvae from the meat of infected animals was carried out using the compressor method. For two species of Trichinella, 36 mice (in each group 18 mice) were infected with 250 larvae and euthanized by intramuscular injection of xylazine followed by an intravenous overdose of anestofol at 3, 5, 7, 14, 21, and 30 dpi (each day 3 infected mice) and one control group (3 mice). Sequencing and bioinformatics methods were used to determine the DNA and cDNA of the serine protease gene, and molecular methods (DNA extraction, reverse transcription polymerase chain reaction, and sequence) were used to measure the accumulation of serine protease transcripts in isolated larvae. The results showed differences in the duration of intestinal phase between T. spiralis and T. nativa. The intestinal larvae of T. nativa were observed from 7 to 30 dpi, and the intensity of invasion increased up to 30 dpi (p < 0.001), while in the case of T. spiralis, the increase in larval growth in the intestinal phase decreased to 21 dpi, and only an increase of 1.6 ± 0.88 (p < 0.01) was detected at 30 dpi. T. nativa muscle larvae were detected at 21 dpi, compared with T. spiralis at 14 dpi. This characteristic was also reflected in the levels of serine protease transcripts in the samples. Accumulation was observed in both cases higher in the muscular stage of development, whereas the duration of the intestinal stage of T. nativa made it possible to detect serine protease at 30 dpi. The intestinal stage of T. nativa lasts for 30 days, indicating that the use of T. nativa serine protease is useful for the identification of intestinal infection. Furthermore, this protein can be used to identify T. spiralis and T. nativa in laboratory samples. Serine protease can be used as a marker for serological diagnosis. Within the framework of the research topic, it is important to conduct further studies on the species specificity of the obtained recombinant protein. It is necessary to focus on identifying highly specific Trichinella proteins for early disease detection.

Let-7 reduces the proliferation and migration of oral cancer cells via PI3K/AKT signaling pathway.

The involvement of let-7 in the occurrence and progression of various cancers has been well-documented. However, the precise molecular mechanisms underlying its impact on oral cancer development remain unclear. In this study, we aimed to elucidate the role of let-7 in oral cancer progression and investigate its underlying molecular mechanisms. The expression of let-7 and high mobility group A2 (HMGA2) mRNA was assessed using the quantitative reverse transcription polymerase chain reaction. Western blot analysis was employed to detect the expression of key proteins in the PI3K/AKT signaling pathway as well as HMGA2 protein levels. The targeting relationship between let-7 and HMGA2 was predicted through bioinformatics methods and confirmed via luciferase reporter gene assay. The effects of let-7 and HMGA2 on the functionality of oral cancer cells were evaluated using 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide, colony formation assay, Transwell assay, wound healing assay, and Annexin V/PI apoptosis assay. Additionally, the impact of let-7 on the growth of oral cancer cells in vivo was investigated by inducing subcutaneous tumor formation in nude mice. Let-7 effectively suppresses the proliferation, migration, and invasion of oral cancer cells by inhibiting the activation of the PI3K/AKT signaling pathway. HMGA2, a downstream target gene of let-7, exhibits high expression in oral cancer. However, overexpression of HMGA2 diminishes the inhibitory effects induced by let-7 overexpression on the proliferation, migration, and invasion of oral cancer cells. The occurrence and progression of oral cancer cells are inhibited by Let-7 through the downregulation of HMGA2, potentially mediated by the inhibition of PI3K/AKT signaling pathway activation.

RNA sequencing reveals transcriptomic changes in PC-12 cells following plasminogen activator, tissue type overexpression.

Pheochromocytoma and paraganglioma, collectively known as PPGL, are categorized as neuroendocrine tumors with the potential for malignancy. Plasminogen activator, tissue type (PLAT) is a protein encoding gene that encodes tissue-type plasminogen activator, which converts plasminogen to plasmin. There is limited research on the association between PLAT and PPGL. Previous studies have only found that the expression level of PLAT protein is significantly increased in PPGL with deficient blood supply, and its role in the occurrence and progression of PPGL remains unclear and needs further clarification. The purpose of this study is to provide some new clues to elucidate the role of PLAT in PPGL, in order to better guide future research directions. The PC-12 cell line was selected for this study, and lentivirus transfection technology was used to construct control and PLAT overexpression cell models. Transcriptomic information of PLAT regulation in PC-12 cells was obtained through RNA sequencing, and differentially expressed genes (DEGs) were screened using bioinformatics methods. The physiological functions and related signaling pathways of these genes were analyzed. After validating the overexpression cell model and performing quality control analysis on the transcriptome sequencing data, DEGs were identified. The Gene Ontology (GO) functional enrichment analysis of DEGs revealed significant enrichment in 46 GO functions, while the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis showed significant enrichment in seven pathways. It was found that these genes were significantly enriched in functional pathways associated with mitochondrial respiratory chain and energy metabolism. This study provides some insights into the role of PLAT in pheochromocytoma and suggests directions for further research on its involvement in tumor development and angiogenesis. However, the specific regulatory mechanisms still require further validation.

Comprehensive Analysis of the Significance of Breast Cancer Gene 1 (BRCA-1) in Bladder Cancer.

Bladder carcinoma (BLCA) is characterized by high morbidity, mortality, and treatment costs. Breast cancer gene 1 (BRCA1), a tumor suppressor gene, inhibits the development of malignant tumors. However, research on the significance of BRCA1 in BLCA is limited. This study aims to explore the importance of BRCA1 in BLCA using bioinformatic methods and immunohistochemistry. Gene expression, clinical, and survival data were collected from the TCGA databases through the UCSC Xena platform (http://xena.ucsc.edu/). The TPM data from the TCGA and GETEx databases were integrated using the GEPIA database (http://GEPIA.cancer-pku.cn). The study then explored the differential expression, survival prognosis, functional enrichment, and immune cell infiltration analyses of BRCA1 in BLCA. A PPI network of BRCA1 was constructed using the STRING database, and a BRCA1-associated gene-gene interaction network was generated using the GeneMANIA database. Immunohistochemistry (IHC) assays were performed to verify the expression levels of BRCA1 in bladder tumour tissues and adjacent normal tissues. BRCA1 is associated with BLCA. Differential analysis indicated that BRCA1 acts as a risk factor for BLCA but does not show significant expression differences across genders, stages, tumor stages, lymph node stages, or metastasis stages. Additionally, staging was based on the eighth edition of the American Joint Committee on Cancer (AJCC) for BLCA. Co-expression network and Gene Set Enrichment Analysis (GESA) confirmed that BRCA1 is involved in various BLCA pathways. Furthermore, BRCA1 expression was also linked to immune cell infiltration. However, survival prognosis analysis revealed no significant correlation between the prognosis of BLCA and BRCA1. We demonstrated that BRCA1 is a prospective predicted and immunological biomarker in BLCA, offering new avenues for potential therapies.

Insights into the bZIP gene family in Osmanthus fragrans and the role of OfbZIP98 in the callus and flower

Osmanthus fragrans has important ornamental and economic value. As the callus re-differentiation process is difficult, a genetic transformation system has not been successfully established in O. fragrans. The basic leucine zipper (bZIP) transcription factors play an important role in plant growth and development. A total of 116 OfbZIP genes were identified in O. fragrans using bioinformatics methods. According to the evolutionary relationships, these genes were divided into 12 subfamilies and were found to be unevenly distributed on 23 chromosomes of O. fragrans. The quantitative real-time PCR results showed that the expression trend of OfbZIP98 was consistent with the proliferation of O. fragrans callus. The subcellular localization and yeast self-activation results showed that OfbZIP98 was localized in the nucleus and had self-activation activity. Further, phenotypic observation of over-expressed tobacco showed that compared with the wild type (WT), the transgenic strain formed callus 4 d earlier, and callus re-differentiation began on day 15. Analysis of the callus differentiation rate showed that after 20 d of culture, the differentiation rate of the leaf callus of the transgenic strain was about twice that of the WT plants. In addition, measurements of corolla diameter, corolla circumference, corolla area, and corolla tube diameter indicated that the petals of the transgenic strain were significantly larger than the WT plants. Our results showed that OfbZIP98 has the important function of promoting callus growth, re-differentiation, and flower organ enlargement. These findings provide new insights into the potential role of OfbZIP98 in the growth and development of O. fragrans.

Exploring resveratrol against Alzheimer's disease and Parkinson's disease through integrating network pharmacology, bioinformatics, and experimental validation strategy in vitro

BackgroundThe study aims to investigate the pharmacological basis and molecular mechanisms of resveratrol in the treatment of Alzheimer's disease (AD) and Parkinson's disease (PD) through the approach of treating different diseases with the same method, guided by traditional Chinese medicine theory. Utilizing network pharmacology and bioinformatics methods, this research aims to provide modern medical evidence for the theory of treating different diseases with the same method in traditional Chinese medicine. MethodsOmnibus from Swiss Target Prediction, TCMSP, SuperPred, SEA, HIT, CTD, TCMIP and Gene Expression Disease datasets for resveratrol related genes, Alzheimer's disease, and Parkinson's disease were obtained from the GEO database. Core targets were identified by weighted gene coexpression network analysis (WGCNA) and minimum absolute contraction and selection operator (LASSO). The expression of core targets was verified in AD and PD cell models. The immune characteristics of AD and PD were analyzed by CIBERSORT algorithm. Finally, the potential mechanism of resveratrol intervention on the core target was studied by molecular docking technique. ResultsThe results of network pharmacological analysis showed that resveratrol acted on 85 common targets such as STAT3 and CASP3, affected AGE-RAGE signaling pathway and PI3K-Akt signaling pathway, and showed the effect of "same disease and different treatment" for AD and PD. Three core targets associated with AD and PD (PLK4, FCGRT, and PRKAR2A) were finally identified through comprehensive transcriptome analysis, and experimentally verified in cell models of AD and PD. At the same time, the analysis of immune cell infiltration suggested that AD and PD had dysregulation of inflammation, and the core target was significantly related to M2 macrophages. ConclusionResveratrol may play a potential mechanism of "treating the same disease with different diseases" and target three core targets (PLK4, FCGRT and PRKAR2A) to improve the disease process of AD and PD by participating in the regulation of immune and inflammatory pathways. These findings have potential implications for clinical practice and future research.