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Background: Despite observational links between serum uric acid (SUA), sex hormone-related phenotypes, and female infertility, the causality behind these associations remains uncertain. Objective: This study utilizes Bidirectional Two-Sample and Mediation Mendelian Randomization to explore the causal relationships and mediation effects of sex hormone-binding globulin (SHBG), total testosterone (TT), and estradiol on these associations. Methods: We analyzed single-nucleotide polymorphisms (SNPs) associated with SUA and sex hormone levels using data from large-scale GWAS of European populations. Female infertility data were sourced from 6,481 cases and 75,450 controls in the FinnGen Consortium. We employed methods including Inverse Variance Weighted (IVW), Weighted Median, and MR-Egger regression to assess causality. Results: We found that elevated SUA levels causally increase the risk of female infertility (IVW OR: 1.13, P=0.047). Elevated SUA levels significantly decrease SHBG levels (ß=-0.261; P=2.177e-04), with SHBG mediating 27.93% of the effect of SUA on infertility (OR=0.854; 95%CI, 0.793-0.920; P=2.853e-05). Additionally, elevated TT levels, which were associated with decreased SUA levels (ß=-0.127), showed an indirect effect on infertility mediated by SUA (ß=-0.0187; 95% CI, -0.041 to -0.003; P=0.046). Conclusion: Our findings demonstrate causal links between high SUA and increased risk of female infertility mediated by hormonal factors such as SHBG and TT. These insights suggest new avenues for infertility treatment and highlight the need for further research into these mechanisms.
Subject(s)
Estradiol , Infertility, Female , Mendelian Randomization Analysis , Polymorphism, Single Nucleotide , Sex Hormone-Binding Globulin , Testosterone , Uric Acid , Humans , Female , Sex Hormone-Binding Globulin/metabolism , Sex Hormone-Binding Globulin/genetics , Uric Acid/blood , Estradiol/blood , Infertility, Female/blood , Infertility, Female/genetics , Testosterone/blood , White People/genetics , Genome-Wide Association Study , Europe/epidemiology , Adult , Case-Control StudiesABSTRACT
An extend-policy iterative algorithm is proposed for solving the ecological evolving-lung cancer cells growth inhibition optimal drug delivery scheme. With the analysis of the cell proliferation-apoptosis process of lung cancer cells with primitive immune system and external drug interventions, such as chemotherapeutic drugs and immunological agents, a model of ecological containment of lung cancer cells mimicking injection labeling is constructed. The HJB equation for biological tissue damage has also been established by considering the concentration of lung cancer cells in the blood and the amount of drug administered. The final simulation experiment proved the effectiveness of the drug delivery scheme.
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There has been an upward trend in the incidence of glioma, with high recurrence and high mortality. The beta subunits of the 20S proteasome are encoded by the proteasome beta (PSMB) genes and may affect the proteasome's function in glioma, assembly and inhibitor binding. This study attempted to reveal the function of the proliferation and invasion of glioma cells, which is affected by proteasome 20S subunit beta 2 (PSMB2). We subjected the data downloaded from the TCGA database to ROC, survival, and enrichment analyses. After establishing the stable PSMB2 knockdown glioma cell line. We detect the changes in the proliferation, invasion and migration of glioma cells by plate colony formation assay, transwell assay, wound healing assay and flow cytometry and PSMB2 expression was verified by quantitative PCR and Western blotting to identify the mRNA and protein levels. PSMB2 expression was higher in glioma tissues, and its expression positively correlated with poor prognosis and high tumor grade and after PSMB2 knockdown, the proliferation, invasion and migration of glioma cells were weakened.
Subject(s)
Brain Neoplasms , Glioma , Humans , Brain Neoplasms/pathology , Proteasome Endopeptidase Complex/genetics , Cell Proliferation/genetics , Glioma/pathology , Cell Line, Tumor , Cell Movement/genetics , Tumor Microenvironment/geneticsABSTRACT
RATIONALE: Urinary dysfunction triggered by varicella-zoster virus (VZV) attacking the nervous system seriously affects the quality of life of patients and may even cause irreversible damage to the urinary system. This a 62-year-old man with acute urinary retention triggered by VZV, who was cured after acupuncture treatment. The rational application of acupuncture therapy to promote the recovery of bladder contraction function can effectively relieve the symptoms of dysuria, shorten the course of the disease. PATIENT CONCERNS: Symptoms included dysuria and distension of the bladder area secondary to postherpetic herpes zoster, with significant pressure and pain in his lower abdomen, accompanied by cutaneous herpes distributed over the sacral region. DIAGNOSES: The case was diagnosed as acute urinary retention (Neurogenic Bladder). Ancillary tests include urodynamic examination, Doppler ultrasound, urodynamic tests are the preferred diagnostic method and suggest: no contraction of the detrusor muscle is seen during voiding, and voiding occurs in an The absence of abdominal pressure-assisted micturition and repeated attempts to pass urine suggests detrusor weakness; residual urine suggests a severe bladder emptying disorder. Doppler ultrasound suggested overfilling of the bladder, and 1153 mL of residual urine was seen in the bladder after voiding. INTERVENTIONS: The patient developed sacral herpes and dysuria and was treated with oral antiviral drugs on the 12th day of illness. But his urinary difficulty did not improve but gradually worsened, resulting in acute urinary retention, and he then turned to the acupuncture treatment, innovative approach combined the mechanism of action of sacral neuromodulation with traditional Chinese medicine theory. OUTCOMES: The duration of acupuncture treatment totaled 12 weeks; he was able to urinate on her own and her symptoms completely disappeared. No other adverse and unintended events occurred during treatment. LESSONS: This study demonstrates that acupuncture is safe and effective in the treatment of acute urinary retention caused by VZV, which is worth recommending as a conservative treatment. Moreover, we found that the early intervention and full-term treatment with acupuncture is particularly important, provided that the right key acupoints are selected.
Subject(s)
Acupuncture Therapy , Electric Stimulation Therapy , Urinary Retention , Humans , Male , Female , Middle Aged , Urinary Retention/etiology , Urinary Retention/therapy , Herpesvirus 3, Human , Dysuria , Quality of Life , Sacrococcygeal Region , Acupuncture Therapy/adverse effects , Electric Stimulation Therapy/adverse effectsABSTRACT
Objective: Functional magnetic resonance imaging (fMRI) has been used for evaluating residual brain function and predicting the prognosis of patients with severe traumatic brain injury (sTBI). This study aimed to integrate the fractional amplitude of low-frequency fluctuation (fALFF) and functional connectivity (FC) to investigate the mechanism and prognosis of patients with sTBI. Methods: Sixty-five patients with sTBI were included and underwent fMRI scanning within 14 days after brain injury. The patient's outcome was assessed using the Glasgow Outcome Scale-Extended (GOSE) at 6 months post-injury. Of the 63 patients who met fMRI data analysis standards, the prognosis of 18 patients was good (GOSE scores ≥ 5), and the prognosis of 45 patients was poor (GOSE scores ≤ 4). First, we apply fALFF to identify residual brain functional differences in patients who present different prognoses and conjoined it in regions of interest (ROI)-based FC analysis to investigate the residual brain function of sTBI at the acute phase of sTBI. Then, the area under the curve (AUC) was used to evaluate the predictive ability of the brain regions with the difference of fALFF and FC values. Results: Patients who present good outcomes at 6 months post-injury have increased fALFF values in the Brodmann area (7, 18, 31, 13, 39 40, 42, 19, 23) and decreased FC values in the Brodmann area (28, 34, 35, 36, 20, 28, 34, 35, 36, 38, 1, 2, 3, 4, 6, 13, 40, 41, 43, 44, 20, 28 35, 36, 38) at the acute phase of sTBI. The parameters of these alterations can be used for predicting the long-term outcomes of patients with sTBI, of which the fALFF increase in the temporal lobe, occipital lobe, precuneus, and middle temporal gyrus showed the highest predictive ability (AUC = 0.883). Conclusion: We provide a compensatory mechanism that several regions of the brain can be spontaneously activated at the acute phase of sTBI in those who present with a good prognosis in the 6-month follow-up, that is, a destructive mode that increases its fALFF in the local regions and weakens its FC to the whole brain. These findings provide a theoretical basis for developing early intervention targets for sTBI patients.
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Background: Previous studies have yielded conflicting findings regarding the association between circulating lipids and lipid-lowering drugs with urinary stones, and the causal relationship between the two remains inconclusive. Objective: This study aimed to assess the causal relationship between circulating lipids (Triglycerides [TG], low-density lipoprotein cholesterol [LDL-C], high-density lipoprotein cholesterol [HDL-C], apolipoprotein A [APOA], apolipoprotein B [APOB] and Pure hypercholesterolaemia), lipid-lowering drugs (HMGCR [HMG-CoA reductase] inhibitors and PCSK9[Proprotein Convertase Subtilisin/Kexin Type 9] inhibitors) and the risk of urinary stones, using genetic data. Methods: Genetic instrumental variables (GIVs) for circulating lipids and lipid-lowering drugs were obtained from the UK Biobank and existing literature. Outcome data were extracted from a genetic association database with 3,625 urinary stone cases and 459,308 controls. Two-sample MR analysis, employing the TwoSampleMR software package in R 4.2.3, was conducted to assess the associations between multiple exposures. The primary outcome was determined using the inverse variance weighted (IVW) method for the causal relationship between exposure and outcome, while additional methods such as MR-Egger, weighted median, simple mode, and weighted mode were utilized as supplementary analyses. Robustness of the Mendelian Randomization (MR) analysis results was assessed through leave-one-out analysis and funnel plots. Results: The MR analysis revealed a significant association between elevated TG levels per 1 standard deviation and the occurrence of urinary stones (odds ratio [OR]: 1.002, 95% confidence interval [CI]: 1.000-1.003, P = 0.010). However, no significant association was observed between factors other than TG exposure and the risk of urinary stone occurrence across all methods(LDL-C: [OR], 1.001; 95% [CI], 1.000-1.003, P=0.132;HDL-C: [OR], 0.999; 95% [CI], 0.998-1.000, P=0.151;APOA:[OR] being 1.000 (95% [CI], 0.999-1.001, P=0.721;APOB: [OR] of 1.001 (95% [CI], 1.000-1.002, P=0.058;Pure hypercholesterolaemia: [OR] of 1.015 (95% [CI], 0.976-1.055, P=0.455) and lipid-lowering drugs (HMGCR inhibitors: [OR], 0.997; 95% [CI], 0.990-1.003, P=0.301 and PCSK9 inhibitors:[OR], 1.002; 95% [CI], 1.000-1.005, P=0.099). Conclusion: Our findings provide conclusive evidence supporting a causal relationship between an increased risk of urinary stones and elevated serum TG levels. However, we did not find a significant association between urinary stone occurrence and the levels of LDL-C, HDL-C, APOA, APOB, Pure hypercholesterolaemia and lipid-lowering drugs.
Subject(s)
Hypercholesterolemia , Hyperlipoproteinemia Type II , Urinary Calculi , Humans , Proprotein Convertase 9 , Cholesterol, LDL , Risk Factors , Mendelian Randomization Analysis , Hypolipidemic Agents/adverse effects , Triglycerides , Cholesterol, HDL , Apolipoproteins B , Urinary Calculi/genetics , Apolipoproteins AABSTRACT
This study analyzed sequencing and clinical data from the Cancer Genome Atlas (TCGA) and gene expression synthesis, and used Chinese glioma Genome Atlas (CGGA) data for external validation. The expression of DCP2 in normal brain and tumor tissue was compared. We analyzed the clinical and molecular characteristics and prognostic value of DCP2 in glioma. In addition, DCP2 expression levels were evaluated in 30 glioma tissue samples and upregulated in glioma samples compared to normal brain tissue (p < 0.001). Multivariate data analysis from TCGA showed that increased DCP2 expression was an independent risk factor for overall survival and prognosis of glioma patients. As indicated by the analysis of the TCGA data set. The expression level of DCP2 is closely related to tumor immunity, including tumor immune cell infiltration, immune score, and co-expression of multiple immune-related genes. In addition, DCP2 was positively correlated with IL-6 and IL-7. Glioma cell proliferation and invasion were evaluated using cell viability, colony formation, wound healing, and transwell assays.Apoptosis and cell cycle were detected by flow cytometry. DCP2 promoted the proliferation, invasion and migration of glioma cells T98G and U251, inhibited apoptosis and blocked the S phase of the cell cycle. As a result of the altered expression of DCP2, a new prognostic biomarker may be identified that can improve patient survival.These findings suggest DCP2 as a potential biomarker for the prognosis of glioma and a candidate immunotherapy target.
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This article investigates the event-driven fault-tolerance (ETFT) consensus problem for general linear multiagent systems (MASs) with partial loss of effectiveness (PLOE) and bias faults of actuators in leader-follower networks. Each agent's controller is only updated relatively infrequently at its event moments. A desirable feature of this article is that the proposed event-driven algorithm is fully distributed also independent of global information and additive fault boundaries. Based on this, a consensus error prediction model is used to avoid the limitation that each agent needs to monitor its neighbors' state under event-driven conditions continuously. We further excluded the Zeno behavior by proving that any adjacent event interval for each agent is greater than zero. The simulations verify our results.
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As a member of integrin receptor family, ITGAV (integrin subunit α V) is involved in a variety of cell biological processes and overexpressed in various cancers, which may be a potential prognostic factor. However, its prognostic value and potential function in lower-grade glioma (LGG) are still unclear, and in terms of immune infiltration, it has not been fully elucidated. Here, the expression preference, prognostic value, and clinical traits of ITGAV were investigated using The Cancer Genome Atlas database (n = 528) and the Chinese Glioma Genome Atlas dataset (n = 458). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses and gene set enrichment analysis (GSEA) were used to explore the biological function of ITGAV. Using R package "ssGSEA" analysis, it was found thatthe ITGAV mRNA expression level showed intense correlation with tumor immunity, such as tumor-infiltrating immune cells and multiple immune-related genes. In addition, ITGAV is associated with some immune checkpoints and immune checkpoint blockade (ICB) and response to chemotherapy. and the expression of ITGAV protein in LGG patients was verified via immunohistochemistry (IHC). ITGAV expression was higher in LGG tissues than in normal tissues (P < 0.001) and multifactor analysis showed that ITGAV mRNA expression was an independent prognostic factor for LGG overall survival (OS; hazard ratio = 2.113, 95% confidence interval = 1.393-3.204, P < 0.001). GSEA showed that ITGAV expression was correlated with Inflammatory response, complement response, KRAS signal, and interferon response. ssGSEA results showed a positive correlation between ITGAV expression and Th2 cell infiltration level. ITGAV mRNA was overexpressed in LGG, and high ITGAV mRNA levels were found to be associated with poor protein expression and poor OS. ITGAV is therefore a potential biomarker for the diagnosis and prognosis of LGG and may be a potential immunotherapy target.
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The INDETERMINATE DOMAIN (IDD) transcription factors mediate various aspects of plant growth and development. We previously reported that an Arabidopsis IDD subfamily regulates spatial auxin accumulation, and thus organ morphogenesis and gravitropic responses. However, its functions in stress responses are not well defined. Here, we use a combination of physiological, biochemical, molecular, and genetic approaches to provide evidence that the IDD14 cooperates with basic leucine zipper-type binding factors/ABA-responsive element (ABRE)-binding proteins (ABRE-binding factors (ABFs)/AREBs) in ABA-mediated drought tolerance. idd14-1D, a gain-of-function mutant of IDD14, exhibits decreased leaf water loss and improved drought tolerance, whereas inactivation of IDD14 in idd14-1 results in increased transpiration and reduced drought tolerance. Altered IDD14 expression affects ABA sensitivity and ABA-mediated stomatal closure. IDD14 can physically interact with ABF1-4 and subsequently promote their transcriptional activities. Moreover, ectopic expression and mutation of ABFs could, respectively, suppress and enhance plant sensitivity to drought stress in the idd14-1 mutant. Our results demonstrate that IDD14 forms a functional complex with ABFs and positively regulates drought-stress responses, thus revealing a previously unidentified role of IDD14 in ABA signaling and drought responses.
Subject(s)
Arabidopsis Proteins , Arabidopsis , Abscisic Acid/metabolism , Arabidopsis/metabolism , Arabidopsis Proteins/genetics , Arabidopsis Proteins/metabolism , Basic-Leucine Zipper Transcription Factors/genetics , Basic-Leucine Zipper Transcription Factors/metabolism , Droughts , Gene Expression Regulation, Plant , Indoleacetic Acids/metabolism , Plants, Genetically Modified/metabolism , Stress, Physiological/genetics , Transcription Factors/genetics , Transcription Factors/metabolism , Water/metabolismABSTRACT
Gliomas are the most frequent primary malignant brain tumors of the central nervous system, causing significant impairment and death. There is mounting evidence that N7 methylguanosine (m7G) RNA dysmethylation plays a significant role in the development and progression of cancer. However, the expression patterns and function of the m7G RNA methylation regulator in gliomas are yet unknown. The goal of this study was to examine the expression patterns of 31 critical regulators linked with m7G RNA methylation and their prognostic significance in gliomas. To begin, we systematically analyzed patient clinical and prognostic data and mRNA gene expression data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. We found that 17 key regulators of m7G RNA methylation showed significantly higher expression levels in gliomas. We then divided the sample into two subgroups by consensus clustering. Cluster 2 had a poorer prognosis than cluster 1 and was associated with a higher histological grade. In addition, cluster 2 was significantly enriched for cancer-related pathways. Based on this discovery, we developed a risk model involving three m7G methylation regulators. Patients were divided into high-risk and low-risk groups based on risk scores. Overall survival (OS) was significantly lower in the high-risk group than in the low-risk group. Further analysis showed that the risk score was an independent prognostic factor for gliomas.
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Inferring the structure of human populations from genetic variation data is a key task in population and medical genomic studies. Although a number of methods for population structure inference have been proposed, current methods are impractical to run on biobank-scale genomic datasets containing millions of individuals and genetic variants. We introduce SCOPE, a method for population structure inference that is orders of magnitude faster than existing methods while achieving comparable accuracy. SCOPE infers population structure in about a day on a dataset containing one million individuals and variants as well as on the UK Biobank dataset containing 488,363 individuals and 569,346 variants. Furthermore, SCOPE can leverage allele frequencies from previous studies to improve the interpretability of population structure estimates.
Subject(s)
Biological Specimen Banks , Genetics, Population , Gene Frequency/genetics , Genomics , HumansABSTRACT
Background: Glioma is the most common primary tumor of the central nervous system. The conventional glioma treatment strategies include surgical excision and chemo- and radiation-therapy. Interferon Gamma (IFN-γ) is a soluble dimer cytokine involved in immune escape of gliomas. In this study, we sought to identify IFN-γ-related genes to construct a glioma prognostic model to guide its clinical treatment. Methods: RNA sequences and clinicopathological data were downloaded from The Cancer Genome Atlas (TCGA) and the China Glioma Genome Atlas (CGGA). Using univariate Cox analysis and the Least Absolute Shrinkage and Selection Operator (LASSO) regression algorithm, IFN-γ-related prognostic genes were selected to construct a risk scoring model, and analyze its correlation with the clinical features. A high-precision nomogram was drawn to predict prognosis, and its performance was evaluated using calibration curve. Finally, immune cell infiltration and immune checkpoint molecule expression were analyzed to explore the tumor microenvironment characteristics associated with the risk scoring model. Results: Four out of 198 IFN-γ-related genes were selected to construct a risk score model with good predictive performance. The expression of four IFN-γ-related genes in glioma tissues was significantly increased compared to normal brain tissue (p < 0.001). Based on ROC analysis, the risk score model accurately predicted the overall survival rate of glioma patients at 1 year (AUC: The Cancer Genome Atlas 0.89, CGGA 0.59), 3 years (AUC: TCGA 0.89, CGGA 0.68), and 5 years (AUC: TCGA 0.88, CGGA 0.70). Kaplan-Meier analysis showed that the overall survival rate of the high-risk group was significantly lower than that of the low-risk group (p < 0.0001). Moreover, high-risk scores were associated with wild-type IDH1, wild-type ATRX, and 1P/19Q non-co-deletion. The nomogram predicted the survival rate of glioma patients based on the risk score and multiple clinicopathological factors such as age, sex, pathological grade, and IDH Status, among others. Risk score and infiltrating immune cells including CD8 T-cell, resting CD4 memory T-cell, regulatory T-cell (Tregs), M2 macrophages, resting NK cells, activated mast cells, and neutrophils were positively correlated (p < 0.05). In addition, risk scores closely associated with expression of immune checkpoint molecules such as PD-1, PD-L1, CTLA-4, LAG-3, TIM-3, TIGIT, CD48, CD226, and CD96. Conclusion: Our risk score model reveals that IFN-γ -associated genes are an independent prognostic factor for predicting overall survival in glioma, which is closely associated with immune cell infiltration and immune checkpoint molecule expression. This model will be helpful in predicting the effectiveness of immunotherapy and survival rate in patients with glioma.
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Background: Glioma is the most common primary tumor of the central nervous system and is associated with poor overall survival, creating an urgent need to identify survival-associated biomarkers. C1ORF112, an alpha-helical protein, is overexpressed in some cancers; however, its prognostic role has not yet been explored in gliomas. Thus, in this study, we attempted to address this by determining the prognostic value and potential function of C1ORF112 in low-grade gliomas (LGGs). Methods: The expression of C1ORF112 in normal and tumor tissues was analyzed using data from The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), Oncomine, and Rembrandt databases. The genetic changes of C1ORF112 in LGG were analyzed using cBioPortal. Survival analysis was used to evaluate the relationship between C1ORF112 expression and survival in patients with LGG. Correlation between immune infiltration and C1ORF112 expression was determined using Timer software. Additionally, data from three online platforms were integrated to identify the co-expressed genes of C1ORF112. The potential biological functions of C1ORF112 were investigated by enrichment analysis. Results: C1ORF112 mRNA was highly expressed in LGGs (p < 0.01). Area under the ROC curve (AUC) showed that the expression of C1ORF112 in LGG was 0.673 (95% confidence interval [CI] = 0.618-0.728). Kaplan-Meier survival analysis showed that patients with high C1ORF112 expression had lower OS than patients with low C1ORF112 expression (p < 0.05). Multivariate analysis showed that high expression of C1ORF112 was an independent prognostic factor for the overall survival in patients from TCGA and CGGA databases. C1ORF112 expression was positively correlated with six immunoinfiltrating cells (all p < 0.001). The enrichment analysis suggested the enrichment of C1ORF112 and co-expressed genes in cell cycle and DNA replication. Conclusion: This study suggested that C1ORF112 may be a prognostic biomarker and a potential immunotherapeutic target for LGG.
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Low-grade gliomas (LGGs) are slow-growing brain cancer in central nervous system neoplasms. EMILIN2 is an extracellular matrix (ECM) protein which could influence the progress of some tumour which is unclear in LGG. In our study, the methylation, expression, prognosis and immune value of EMILIN2 in LGG were analysed through bioinformatics analysis. We analysed the LGG data from The Cancer Genome Atlas (TCGA) and discovered that the EMILIN2 expression, negatively correlated to the EMILIN2 methylation, could predict a poor prognosis and was associated with different clinical parameters. Moreover, univariate and multivariate Cox regression were performed in CGGA, which showed that the EMILIN2 could be an independent prognostic biomarker in LGG. Moreover, EMILIN2 expression showed a correlation with gene makers in some immune cells, which identified the significance of EMILIN2 in immune infiltration. Finally, we used RT-PCR to verify the EMILIN2 expression level in different grades which showed there were significantly different (P < 0.05). Similarly, high expression of EMILIN2 could predict a poor prognosis (P = 0.0078). In conclusion, EMILIN2 could act as an independent prognostic biomarker which might be associated with the malignancy and development of gliomas and play a crucial role in glioma in immune infiltration.
Subject(s)
Brain Neoplasms/metabolism , Glioma/metabolism , Glycoproteins/metabolism , Adult , Aging , Biomarkers, Tumor , Brain Neoplasms/genetics , Brain Neoplasms/immunology , Female , Gene Expression Profiling , Gene Expression Regulation, Neoplastic , Glioma/genetics , Glioma/immunology , Glycoproteins/genetics , Glycoproteins/immunology , Humans , Kaplan-Meier Estimate , Male , Methylation , Middle Aged , Polymerase Chain Reaction , Predictive Value of Tests , Prognosis , Survival Analysis , TranscriptomeABSTRACT
BACKGROUND: Postoperative cerebral edema is common in patients with meningioma. It is of great clinical significance to predict the postoperative cerebral edema exacerbation (CEE) for the development of individual treatment programs in patients with meningioma. OBJECTIVE: To evaluate the value of three-dimensional radiomics Features from Multi-Parameter MRI in predicting the postoperative CEE in patients with meningioma. METHODS: A total of 136 meningioma patients with complete clinical and radiological data were collected for this retrospective study, and they were randomly divided into primary and validation cohorts. Three-dimensional radiomics features were extracted from multisequence MR images, and then screened through Wilcoxon rank sum test, elastic net and recursive feature elimination algorithms. A radiomics signature was established based support vector machine method. By combining clinical with the radiomics signature, a clin-radiomics combined model was constructed for individual CEE prediction. RESULTS: Three significance radiomics features were selected to construct a radiomics signature, with areas under the curves (AUCs) of 0.86 and 0.800 in the primary and validation cohorts, respectively. Two clinical characteristics (peritumoral edema and tumor size) and radiomics signature were determined to establish the clin-radiomics combined model, with an AUC of 0.91 in the primary cohort and 0.83 in the validation cohort. The clin-radiomics combined model showed good discrimination, calibration, and clinically useful for postoperative CEE prediction. CONCLUSIONS: By integrating clinical characteristics with radiomics signature, the clin-radiomics combined model could assist in postoperative CEE prediction before surgery, and provide a basis for surgical treatment decisions in patients with meningioma.
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BACKGROUND: Glioblastoma is the most common primary malignant brain tumor. Because of the limited understanding of its pathogenesis, the prognosis of glioblastoma remains poor. This study was conducted to explore potential competing endogenous RNA (ceRNA) network chains and biomarkers in glioblastoma by performing integrated bioinformatics analysis. METHODS: Transcriptome expression data from The Cancer Genome Atlas database and Gene Expression Omnibus were analyzed to identify differentially expressed genes between glioblastoma and normal tissues. Biological pathways potentially associated with the differentially expressed genes were explored by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis, and a protein-protein interaction network was established using the STRING database and Cytoscape. Survival analysis using Gene Expression Profiling Interactive Analysis was based on the Kaplan-Meier curve method. A ceRNA network chain was established using the intersection method to align data from four databases (miRTarBase, miRcode, TargetScan, and lncBace2.0), and expression differences and correlations were verified by quantitative reverse-transcription polymerase chain reaction analysis and by determining the Pearson correlation coefficient. Additionally, an MTS assay and the wound-healing and transwell assays were performed to evaluate the effects of complement C1s (C1S) on the viability and migration and invasion abilities of glioblastoma cells, respectively. RESULTS: We detected 2842 differentially expressed (DE) mRNAs, 2577 DE long non-coding RNAs (lncRNAs), and 309 DE microRNAs (miRNAs) that were dysregulated in glioblastoma. The final ceRNA network consisted of six specific lncRNAs, four miRNAs, and four mRNAs. Among them, four DE mRNAs and one DE lncRNA were correlated with overall survival (p < 0.05). C1S was significantly correlated with overall survival (p= 0.015). In functional assays, knockdown of C1S inhibited the proliferation and invasion of glioblastoma cell lines. CONCLUSIONS: We established four ceRNA networks that may influence the occurrence and development of glioblastoma. Among them, the MIR155HG/has-miR-129-5p/C1S axis is a potential marker and therapeutic target for glioblastoma. Knockdown of C1S inhibited the proliferation, migration, and invasion of glioblastoma cells. These findings clarify the role of the ceRNA regulatory network in glioblastoma and provide a foundation for further research.
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DNA binding proteins carry out important and diverse functions in the cell, including gene regulation, but identifying these proteins is technically challenging. In the present study, we developed a technique to capture DNA-associated proteins called reverse chromatin immunoprecipitation (R-ChIP). This technology uses a set of specific DNA probes labeled with biotin to isolate chromatin, and the DNA-associated proteins are then identified using mass spectrometry. Using R-ChIP, we identified 439 proteins that potentially bind to the promoter of the Arabidopsis thaliana gene AtCAT3 (AT1G20620). According to functional annotation, we randomly selected 5 transcription factors from these candidates, including bZIP1664, TEM1, bHLH106, BTF3, and HAT1, to verify whether they in fact bind to the AtCAT3 promoter. The binding of these 5 transcription factors was confirmed using chromatin immunoprecipitation quantitative real-time PCR and electrophoretic mobility shift assays. In addition, we improved the R-ChIP method using plants in which the DNA of interest had been transiently introduced, which does not require the T-DNA integration, and showed that this substantially improved the protein capture efficiency. These results together demonstrate that R-ChIP has a wide application to characterize chromatin composition and isolate upstream regulators of a specific gene.
Subject(s)
Chromatin Immunoprecipitation/methods , DNA-Binding Proteins/metabolism , Gene Expression Regulation, Plant , Genes, Plant , Regulatory Sequences, Nucleic Acid , Arabidopsis/genetics , Arabidopsis/metabolism , Arabidopsis Proteins/genetics , Binding Sites , Catalase/genetics , Chromatin/genetics , Chromatin/metabolism , Promoter Regions, Genetic , Protein Binding , TemperatureABSTRACT
Cadmium (Cd) is one of the most serious global environmental pollutants, which inhibits plant growth and interferes with their physiological processes. However, there have been few studies on the involvement of long noncoding RNAs (lncRNAs) in Cd tolerance. In the present study, we identified the lncRNAs from Betula platyphylla (birch) that respond to Cd stress. Thirty lncRNAs that were differentially expressed under Cd treatment were identified, including 16 upregulated and 14 downregulated lncRNAs. Nine differentially regulated lncRNAs were selected for further characterization. These lncRNAs were transiently overexpressed in birch plants to determine their roles in Cd tolerance. Among them, two lncRNAs conferred Cd tolerance and two induced sensitivity to Cd stress. We further determined the Cd tolerance of four target genes of the lncRNAs involved in Cd tolerance, including l-lactate dehydrogenase A (LDHA),heat shock protein (HSP18.1), yellow stripe-like protein (YSL9), and H/ACA ribonucleoprotein complex subunit 2-like protein (HRCS2L). Among them, HSP18.1 and LDHA showed improved tolerance to Cd stress, whereas the other two genes did not appear to be involved in Cd tolerance. These results suggested that lncRNAs can up- or downregulate their target genes to improve Cd tolerance. These results increase our understanding of lncRNA-mediated Cd tolerance.