Interventions to Facilitate Shared Decision-Making Using Decision Aids with Coronary Heart Disease Patients: Systematic Review and Meta-Analysis.

Background: Coronary heart disease (CHD) is the leading cause of death in the world. There are some decision-making conflicts in the management of chest pain, treatment methods, stent selection, and other aspects due to the unstable condition of CHD in the treatment stage. Although using decision aids to facilitate shared decision-making (SDM) contributes to high-quality decision-making, it has not been evaluated in the field of CHD. This review systematically assessed the effects of SDM in patients with CHD. Methods: We conducted a systematic review and meta-analysis of randomized controlled trials of SDM interventions in patients with CHD from database inception to 1 June 2022 (PROSPERO [Unique identifier: CRD42022338938]). We searched for relevant studies in the PubMed, Embase, Cochrane Library, Web of Science, CNKI, and Wan Fang databases. The primary outcomes were knowledge and decision conflict. The secondary outcomes were satisfaction, patient participation, trust, acceptance, quality of life, and psychological condition. Results: A total of 8244 studies were retrieved. After screening, ten studies were included in the analysis. Compared with the control group, SDM intervention with patient decision aids obviously improved patients' knowledge, decision satisfaction, participation, and medical outcomes and reduced decision-making conflict. There was no significant effect of SDM on trust. Conclusions: This study showed that SDM intervention in the form of decision aids was beneficial to decision-making quality and treatment outcomes among patients with CHD. The results of SDM interventions need to be evaluated in different environments.

Identification of potential biomarkers for cerebral palsy and the development of prediction models.

Cerebral palsy (CP) is a prevalent motor disorder originating from early brain injury or malformation, with significant variability in its clinical presentation and etiology. Early diagnosis and personalized therapeutic interventions are hindered by the lack of reliable biomarkers. This study aims to identify potential biomarkers for cerebral palsy and develop predictive models to enhance early diagnosis and prognosis. We conducted a comprehensive bioinformatics analysis of gene expression profiles in muscle samples from CP patients to identify candidate biomarkers. Six key genes (CKMT2, TNNT2, MYH4, MYH1, GOT1, and LPL) were validated in an independent cohort, and potential biological pathways and molecular networks involved in CP pathogenesis were analyzed. The importance of processes such as functional regulation, energy metabolism, and cell signaling pathways in the muscles of CP patients was emphasized. Predictive models of muscle sample biomarkers related to CP were developed and visualized. Calibration curves and receiver operating characteristic analysis demonstrated that the predictive models exhibit high sensitivity and specificity in distinguishing individuals at risk of CP. The identified biomarkers and developed prediction models offer significant potential for early diagnosis and personalized management of CP. Future research should focus on validating these biomarkers in larger cohorts and integrating them into clinical practice to improve outcomes for individuals with CP.

Phosducin-like 3 is a novel prognostic and onco-immunological biomarker in glioma: A multi-omics analysis with experimental verification.

Malignant glioma is the most frequent primary tumor of the central nervous system. PDCL3 is a member of the phosducin-like protein family, and its imbalance has been shown to be associated with several human diseases. However, the underlying role of PDCL3 in human malignant cancers, especially in malignant gliomas, is unclear. In this study, we combined public database analysis and experimental verification to explore the differential expression, prognostic value and potential functions and mechanisms of PDCL3. The results revealed that PDCL3 is upregulated in multiple cancers and acts as a potential prognostic biomarker of glioma. Mechanistically, PDCL3 expression is associated with epigenetic modifications and genetic mutations. PDCL3 may directly interact with the chaperonin-containing TCP1 complex, regulating cell malignancy, cell communication and the extracellular matrix. More importantly, the association of PDCL3 with the infiltration of immune cells, immunomodulatory genes, immune checkpoints, cancer stemness and angiogenesis suggested that PDCL3 may regulate the glioma immune landscape. Furthermore, PDCL3 interference also decreased the proliferation, invasion and migration of glioma cells. In conclusion, PDCL3 is a novel oncogene and can be adopted as a biomarker with value in assisting clinical diagnosis, predicting patient outcomes and assessing the immune landscape of the tumor microenvironment in glioma.

Development and validation of a glioma-associated mesenchymal stem cell-related gene prognostic index for predicting prognosis and guiding individualized therapy in glioma.

BACKGROUND: Recent studies have demonstrated that glioma-associated mesenchymal stem cells (GA-MSCs) are implicated in the regulation of glioma malignant progression. However, the prognostic value of GA-MSCs has not been comprehensively explored in glioma. METHODS: We extracted GA-MSCs from glioma tissues, established intracranial xenograft models in nude mice, and obtained GA-MSC-related genes (GA-MSCRGs) by using microarrays. The transcriptome data and clinical information of glioma patients were obtained from the CGGA and TCGA databases. We screened 8 prognostic GA-MSCRGs to construct a prognostic index by using the multivariate Cox regression method. The validity of the GA-MSCRGPI was verified in the training (CGGA693) and validation (TCGA and CGGA325) cohorts. The expression patterns of these 8 GA-MSCRGs were validated in 78 glioma tissue specimens by using a qRT‒PCR assay. RESULTS: GA-MSCs were successfully isolated from glioma tissues. Based on intracranial xenograft models and transcriptome microarray screening, 8 genes (MCM7, CDK6, ORC1, CCL20, TNFRSF12A, POLA1, TRAF1 and TIAM1) were selected for the construction of a GA-MSC-related gene prognostic index (GA-MSCRGPI). In both the training and validation cohorts, high GA-MSCRGPI patients showed an inferior survival outcome compared with low GA-MSCRGPI patients. A nomogram was established based on independent prognostic indicators (age, WHO grade and GA-MSCRGPI) and exhibited a strong forecasting ability for overall survival (OS). Moreover, we found that the GA-MSCRGPI could evaluate the prognosis of glioma patients undergoing chemoradiotherapy. The high GA-MSCRGPI group exhibited higher immune, stromal and ESTIMATE scores; lower tumor purity; higher infiltration of Tregs and M2-type macrophages; fewer activated NK cells; and higher expression of immune checkpoints. Tumor Immune Dysfunction and Exclusion (TIDE) showed that the high GA-MSCRGPI group had more responders to ICI therapy. The results of the genetic mutation profile and tumor mutation burden (TMB) in different GA-MSCRGPI subgroups further supplement GA-MSCRGPI-related mechanisms. Finally, the expression patterns of 8 selected GA-MSCRGs in GA-MSCRGPI were correlated with glioma WHO grades to a certain extent. CONCLUSION: The constructed GA-MSCRGPI could predict prognosis and guide individualized therapy in glioma patients.

Identifying the Hub Genes of Glioma Peritumoral Brain Edema Using Bioinformatical Methods.

Glioma peritumoral brain edema (GPTBE) is a frequent complication in patients with glioma. The severity of peritumoral edema endangers patients' life and prognosis. However, there are still questions concerning the process of GPTBE formation and evolution. In this study, the patients were split into two groups based on edema scoring findings in the cancer imaging archive (TCIA) comprising 186 TCGA-LGG patients. Using mRNA sequencing data, differential gene (DEG) expression analysis was performed, comparing the two groups to find the key genes affecting GPTBE. A functional enrichment analysis of differentially expressed genes was performed. Then, a protein-protein interaction (PPI) network was established, and important genes were screened. Gene set variation analysis (GSVA) scores were calculated for major gene sets and comparatively correlated with immune cell infiltration. Overall survival (OS) was analyzed using the Kaplan-Meier curve. A total of 59 DEGs were found, with 10 of them appearing as important genes. DEGs were shown to be closely linked to inflammatory reactions. According to the network score, IL10 was in the middle of the network. The presence of the IL10 protein in glioma tissues was verified using the human protein atlas (HPA). Furthermore, the gene sets' GSVA scores were favorably linked with immune infiltration, particularly, with macrophages. The high-edema group had higher GSVA scores than the low-edema group. Finally, Kaplan-Meier analysis revealed no differences in OS between the two groups, and eight genes were found to be related to prognosis, whereas two genes were not. GPTBE is linked to the expression of inflammatory genes.

A Risk Score Signature Consisting of Six Immune Genes Predicts Overall Survival in Patients with Lower-Grade Gliomas.

BACKGROUND: Lower-grade gliomas (LGGs) are less aggressive with a long overall survival (OS) time span. Because of individualized genomic features, a prognostic system incorporating molecular signatures can more accurately predict OS. METHODS: Differential expression analysis between LGGs and normal tissues was performed using the Gene Expression Omnibus (GEO) datasets (GSE4290 and GSE12657). Immune-related differentially expressed genes (ImmPort-DEGs) were analyzed for functional enrichment. The least absolute shrinkage and selection operator (LASSO) analysis was performed to develop an immune risk score signature (IRSS). We extracted information from the Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA) to establish and validate the model. The relationship of model gene sets with immune infiltration was analyzed based on gene set variation analysis (GSVA) scores. Patients were divided into low- and high-risk groups based on the median score. The time-dependent receiver-operating characteristic (ROC) curve and the Kaplan-Meier curve were used to evaluate the model. Then, a precise prognostic nomogram was established, and its efficacy was verified. RESULTS: A total of 18 related immune genes were identified, building a 6-gene IRSS (BMP2, F2R, FGF13, PCSK1, PRKCB, and PTGER3). DEGs were enriched in T cell and NK cell regulatory pathways. Immune infiltration analysis confirmed that the gene signature correlated with a decrease in innate immune cells. In terms of model evaluation, ROC curves at 1, 3, and 5 years showed moderate predictive ability of IRSS (AUC = 0.930, 0.797, and 0.728). The Cox regression analysis revealed that IRSS was an independent prognostic factor, and the nomogram model had good predictive ability (C - index = 0.828). Meanwhile, the predictive power of IRSS was also confirmed in the training cohort. The Kaplan-Meier results showed that the prognosis of the high-risk group was significantly worse in all cohorts. CONCLUSION: IRSS may serve as a novel survival prediction tool in the classification of LGG patients.

COL5A1 Serves as a Biomarker of Tumor Progression and Poor Prognosis and May Be a Potential Therapeutic Target in Gliomas.

Glioma is the most common malignancy of the central nervous system. Although advances in surgical resection, adjuvant radiotherapy, and chemotherapy have been achieved in the last decades, the prognosis of gliomas is still dismal. COL5A1 is one of the collagen members with minor content but prominent functions. The present study examined the biological functions, prognostic value, and gene-associated tumor-infiltrating immune cells of COL5A1 through experiments and bioinformatics analysis. We found that the overexpression of COL5A1 was positively correlated with the increasing tumor malignancies and indicated poor prognosis in gliomas. Moreover, downregulation of COL5A1 could inhibit proliferation and migration of glioma cells and enhance their temozolomide sensitivities in vitro. Further bioinformatic analysis revealed that COL5A1 and its co-expressed genes participated in a number of pathways and biological processes involved in glioma progression. Finally, we evaluated the tumor-infiltrating immune cells of gliomas depending on COL5A1 and found that the percentages of the dendritic cells, which were known as the central mediator of tumor microenvironment in gliomas, were positively associated with the expression levels of COL5A1. Taken together, COL5A1 is an important biomarker and potential therapeutic target of gliomas.

MicroRNA-370-3p inhibits human glioma cell proliferation and induces cell cycle arrest by directly targeting ß-catenin.

OBJECTIVE: The aim of this study was to explore the expression and biological role of miR-370-3p in human gliomas. METHODS: Clinical specimens from the brains of 20 glioma patients and 10 healthy controls were obtained to quantify the expression level of miR-370-3p using quantitative real-time PCR. Oligonucleotide mimics of miR-370-3p were transfected into U251 and U87-MG cells for a gain of function assay. The CCK-8 assay, colony formation assay, EdU assay and flow cytometry were used to evaluate the roles of miR-370-3p in cell proliferation and the cell cycle regulation. Western blot and luciferase activity assays were used to investigate the reciprocal relationship between miR-370-3p and its predicted target, ß-catenin. RESULTS: miR-370-3p expression was frequently found to be decreased in glioma tissues, and its expression level was negatively correlated with the malignant degree of the glioma. Overexpression of miR-370-3p showed a significant inhibitory effect on cell proliferation and accompanied cell cycle G0/G1 arrest in U251 and U87-MG cells. Furthermore, miR-370-3p inhibited the expression of the canonical Wnt pathway downstream targets cyclin D1 and c-myc via direct binding interaction with the 3'-untranslated region of ß-catenin mRNA. Reintroduction of ß-catenin could partially reverse the anti-proliferation effect of miR-370-3p. Finally, in 20 glioma tissues the expression of miR-370-3p was negatively correlated with both protein and mRNA levels of ß-catenin. CONCLUSION: miR-370-3p suppresses glioma cell growth by directly targeting ß-catenin, suggesting that the miR-370-3p/ß-catenin axis may be a target for glioma therapy.

Telomerase reverse transcriptase (TERT) rs2736100 polymorphism contributes to increased risk of glioma: evidence from a meta-analysis.

The rs2736100 polymorphism in telomerase reverse transcriptase (TERT) gene has been implicated as a risk factor for glioma in previous epidemiological studies. However, the data from these studies were inconclusive for the precise association of TERT rs2736100 with glioma. Here we employed a meta-analysis aiming to evaluate such association. The PubMed, Embase, and Web of Science were systematically searched for eligible studies. The odds ratio (OR) and 95% confidence interval (95% CI) was estimated to assess the strength of this association in fixed or random effects models. A total of 5 studies in 16 articles including 7337 cases and 12062 controls were eventually collected. Our analyses showed that there was a significant association between TERT rs2736100 polymorphism and glioma in all five genetic models(homozygous model-GG vs. TT: OR=1.64, 95% CI=1.50~1.79, P heterogeneity=0.253, I(2) =17.5%; heterozygous model-GT vs. TT: OR=1.38, 95% CI=1.27~1.49, P heterogeneity=0.235, I(2) =19.1%; dominant model-GG+GT vs. TT: OR=1.46, 95% CI=1.36~1.57, P heterogeneity=0.167, I(2) =25.5%; recessive model-GG vs. GT+TT: OR=1.31, 95% CI=1.22~1.40, P heterogeneity=0.796, I(2) =0.0%; additive model-G allele vs. T allele: OR=1.27, 95% CI=1.21~1.32, P heterogeneity=0.481, I(2) =0.0%). Further subgroup analysis on control source and ethnicity, we found similar association in population-based, hospital-based and Caucasians groups. The result of heterogeneity test were in acceptable range (P<0.05 and I(2) <50%). Egger's tests and Begg's funnel plot did not show any publication bias. Sensitivity analysis confirmed that our results were reliable. Taken together, our meta-analysis suggested that TERT rs2736100 polymorphism may greatly increase glioma risk.

Epistaxis and pituitary apoplexy due to ruptured internal carotid artery aneurysm embedded within pituitary adenoma.

Epistaxis due to ruptured internal carotid artery (ICA) aneurysm embedded within a pituitary adenoma (PA) has seldom been reported in the literature. Here we want to elaborate the incidence, mechanisms, clinical manifestations, and treatment strategy for this condition. The first survived case of a patient with epistaxis and pituitary apoplexy due to ruptured aneurysm embedded within PA was reported and the literature was reviewed. A 53-year-old male patient presented to our institution with sudden onset epistaxis and progressive vision loss. Neurological examination revealed bilateral ptosis and dilated unresponsive pupils. A CT scan showed a large mass in the pituitary fossa with bony erosion. MRI revealed a large pituitary tumor and abnormal signal intensity in the tumor. No aneurysm was noted during the pre-operative MR angiography. Abundant arterial bleeding suddenly occurred during urgent transsphenoidal surgery. Digital subtraction angiography confirmed the presence of a 14 mm unexpected saccular aneurysm of right ICA in the cavernous sinus with the dome protruding into the sella turcica. Balloon test occlusion of the right ICA was undertaken and permanent occlusion was performed. The patient recovered well and received bromocriptine and thyroid hormone replacement therapy during the follow-up period. At 14-month followup, the patient had no neurological deficits, no features of ischaemia relating to the right ICA therapeutic occlusion. Our case indicated that epistaxis and pituitary apoplexy could be due to the rupture of an ICA aneurysm embedded in a PA. Clinical suspicion should remain high when evaluating any case of epistaxis and pituitary apoplexy. Optimal treatment should take into consideration individual features of the tumor, aneurysm, and patient. Making the correct diagnosis as well as identifying an appropriate management strategy is critical in the care of such patients.