The impact of telomere length on the risk of idiopathic normal pressure hydrocephalus: a bidirectional Mendelian randomization study.

Idiopathic normal pressure hydrocephalus (iNPH) affects mainly aged populations. The gradual shortening of telomere length (TL) is one of the hallmarks of aging. Whereas the genetic contribution of TL to the iNPH is incompletely understood. We aimed to investigate the causal relationship between TL and iNPH through the Mendelian randomization (MR) analysis. We respectively obtained 186 qualified single nucleotide polymorphisms (SNPs) of TL and 20 eligible SNPs of iNPH for MR analysis. The result of MR analysis showed that genetically predicted longer TL was significantly associated with a reduced odd of iNPH (odds ratio [OR] = 0.634 95% Confidence interval [CI] 0.447-0.899, p = 0.011). The causal association remained consistent in multivariable MR (OR = 0.530 95% CI 0.327-0.860, p = 0.010). However, there was no evidence that the iNPH was causally associated with the TL (OR = 1.000 95% CI 0.996-1.004, p = 0.955). Our study reveals a potential genetic contribution of TL to the etiology of iNPH, that is a genetically predicted increased TL might be associated with a reduced risk of iNPH.

The impact of neurocognitive and psychiatric disorders on the risk of idiopathic normal pressure hydrocephalus: A bidirectional Mendelian randomization study.

BACKGROUND: Neurocognitive and psychiatric disorders have been proved that they can comorbid more often with idiopathic normal pressure hydrocephalus (iNPH) than general population. However, the potential causal association between these disorders and iNPH has not been assessed. Thus, our study aims to investigate the causal relationship between them based on a bidirectional Mendelian randomization (MR) analysis. METHODS: Random effects of the inverse variance weighted (IVW) method were conducted to obtain the causal association among the neurocognitive disorders, psychiatric disorders, and iNPH. Genome-wide association studies (GWAS) of 12 neurocognitive and psychiatric disorders were downloaded via the OpenGWAS database, GWAS Catalog, and Psychiatric Genomics Consortium, whereas GWAS data of iNPH were obtained from the FinnGen consortium round 9 release, with 767 cases and 375,610 controls of European ancestry. We also conducted the sensitivity analysis in these significant causal inferences using weighted median model, Cochrane's Q test, MR-Egger regression, MR Pleiotropy Residual Sum and Outlier detect and the leave-one-out analysis. RESULTS: For most of the neurocognitive and psychiatric disorders, no causal association was established between them and iNPH. We have found that iNPH (odds ratio [OR] = 1.030, 95% confidence interval [CI]: 1.011-1.048, p = .001) is associated with increased risk for schizophrenia, which failed in validation of sensitivity analysis. Notably, genetically predicted Parkinson's disease (PD) is associated with increased risk of iNPH (OR = 1.256, 95% CI: 1.045-1.511, p = .015). CONCLUSION: Our study has revealed the potential causal effect in which PD associated with an increased risk of iNPH. Further study is warranted to investigate the association between PD and iNPH and the potential underlying mechanism.

Effects of iron homeostasis on epigenetic age acceleration: a two-sample Mendelian randomization study.

BACKGROUND: Epigenetic clocks constructed from DNA methylation patterns have emerged as excellent predictors of aging and aging-related health outcomes. Iron, a crucial element, is meticulously regulated within organisms, a phenomenon referred as iron homeostasis. Previous researches have demonstrated the sophisticated connection between aging and iron homeostasis. However, their causal relationship remains relatively unexplored. RESULTS: Through two-sample Mendelian randomization (MR) utilizing the random effect inverse variance weighted (IVW) method, each standard deviation (SD) increase in serum iron was associated with increased GrimAge acceleration (GrimAA, BetaIVW = 0.27, P = 8.54E-03 in 2014 datasets; BetaIVW = 0.31, P = 1.25E-02 in 2021 datasets), HannumAge acceleration (HannumAA, BetaIVW = 0.32, P = 4.50E-03 in 2014 datasets; BetaIVW = 0.32, P = 8.03E-03 in 2021 datasets) and Intrinsic epigenetic age acceleration (IEAA, BetaIVW = 0.34, P = 5.33E-04 in 2014 datasets; BetaIVW = 0.49, P = 9.94E-04 in 2021 datasets). Similar results were also observed in transferrin saturation. While transferrin manifested a negative association with epigenetic age accelerations (EAAs) sensitivity analyses. Besides, lack of solid evidence to support a causal relationship from EAAs to iron-related biomarkers. CONCLUSIONS: The results of present investigation unveiled the causality of iron overload on acceleration of epigenetic clocks. Researches are warranted to illuminate the underlying mechanisms and formulate strategies for potential interventions.

Impact of redox-related genes on tumor microenvironment immune characteristics and prognosis of high-grade gliomas.

Introduction: High-grade glioma (HGG) defines a group of brain gliomas characterized by contrast enhancement, high tumor heterogeneity, and poor clinical outcome. Disturbed reduction-oxidation (redox) balance has been frequently associated with the development of tumor cells and their microenvironment (TME). Methods: To study the influence of redox balance on HGGs and their microenvironment, we collected mRNA-sequencing and clinical data of HGG patients from TCGA and CGGA databases and our own cohort. Redox-related genes (ROGs) were defined as genes in the MSigDB pathways with keyword "redox" that were differentially expressed between HGGs and normal brain samples. Unsupervised clustering analysis was used to discover ROG expression clusters. Over-representation analysis (ORA), gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) were also employed to understand the biological implication of differentially expressed genes between HGG clusters. CIBERSORTx and ESTIMATE were used to profile the immune TME landscapes of tumors, and TIDE was used to evaluated the potential response to immune checkpoint inhibitors. Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression was used to construct HGG-ROG expression risk signature (GRORS). Results: Seventy-five ROGs were found and consensus clustering using the expression profile of ROGs divided the both IDH-mutant (IDHmut) and IDH-wildtype (IDHwt) HGGs into subclusters with different prognosis. Functional enrichment analysis revealed that the differential aggressiveness between redox subclusters in IDHmut HGGs were significantly associated with cell cycle regulation pathways, while IDHwt HGG redox subclusters showed differentially activated immune-related pathways. In silico TME analysis on immune landscapes in the TME showed that the more aggressive redox subclusters in both IDHmut and IDHwt HGGs may harbor a more diverse composition of tumor-infiltrating immune cells, expressed a higher level of immune checkpoints and were more likely to respond to immune checkpoint blockade. Next, we established a GRORS which showed AUCs of 0.787, 0.884, and 0.917 in predicting 1-3-year survival of HGG patients in the held-out validation datasets, and the C-index of a nomogram combining the GRORS and other prognostic information reached 0.835. Conclusion: Briefly, our results suggest that the expression pattern of ROGs was closely associated with the prognosis as well as the TME immune profile of HGGs, and may serve as a potential indicator for their response to immunotherapies.

A novel score system based on arginine metabolism-related genes to predict prognosis, characterize immune microenvironment, and forecast response to immunotherapy in IDH-wildtype glioblastoma.

Introduction: Glioblastoma is one of the most lethal cancers and leads to more than 200,000 deaths annually. However, despite lots of researchers devoted to exploring novel treatment regime, most of these attempts eventually failed to improve the overall survival of glioblastoma patients in near 20 years. Immunotherapy is an emerging therapy for cancers and have succeeded in many cancers. But most of its application in glioblastoma have been proved with no improvement in overall survival, which may result from the unique immune microenvironment of glioblastoma. Arginine is amino acid and is involved in many physiological processes. Many studies have suggested that arginine and its metabolism can regulate malignancy of multiple cancers and influence the formation of tumor immune microenvironment. However, there is hardly study focusing on the role of arginine metabolism in glioblastoma. Methods: In this research, based on mRNA sequencing data of 560 IDH-wildtype glioblastoma patients from three public cohorts and one our own cohort, we aimed to construct an arginine metabolism-related genes signature (ArMRS) based on four essential arginine metabolism-related genes (ArMGs) that we filtered from all genes with potential relation with arginine metabolism. Subsequently, the glioblastoma patients were classified into ArMRS high-risk and low-risk groups according to calculated optimal cut-off values of ArMRS in these four cohorts. Results: Further validation demonstrated that the ArMRS was an independent prognostic factor and displayed fine efficacy in prediction of glioblastoma patients' prognosis. Moreover, analyses of tumor immune microenvironment revealed that higher ArMRS was correlated with more immune infiltration and relatively "hot" immunological phenotype. We also demonstrated that ArMRS was positively correlated with the expression of multiple immunotherapy targets, including PD1 and B7-H3. Additionally, the glioblastomas in the ArMRS high-risk group would present with more cytotoxic T cells (CTLs) infiltration and better predicted response to immune checkpoint inhibitors (ICIs). Discussion: In conclusion, our study constructed a novel score system based on arginine metabolism, ArMRS, which presented with good efficacy in prognosis prediction and strong potential to predict unique immunological features, resistance to immunotherapy, and guide the application of immunotherapy in IDH-wild type glioblastoma.

Lipid metabolism-related gene signature predicts prognosis and depicts tumor microenvironment immune landscape in gliomas.

Background: Glioma is the most common primary brain tumor in adults and accounts for more than 70% of brain malignancies. Lipids are crucial components of biological membranes and other structures in cells. Accumulating evidence has supported the role of lipid metabolism in reshaping the tumor immune microenvironment (TME). However, the relationship between the immune TME of glioma and lipid metabolism remain poorly described. Materials and methods: The RNA-seq data and clinicopathological information of primary glioma patients were downloaded from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA). An independent RNA-seq dataset from the West China Hospital (WCH) also included in the study. Univariate Cox regression and LASSO Cox regression model was first to determine the prognostic gene signature from lipid metabolism-related genes (LMRGs). Then a risk score named LMRGs-related risk score (LRS) was established and patients were stratified into high and low risk groups according to LRS. The prognostic value of the LRS was further demonstrated by construction of a glioma risk nomogram. ESTIMATE and CIBERSORTx were used to depicted the TME immune landscape. Tumor Immune Dysfunction and Exclusion (TIDE) was utilized to predict the therapeutic response of immune checkpoint blockades (ICB) among glioma patients. Results: A total of 144 LMRGs were differentially expressed between gliomas and brain tissue. Finally, 11 prognostic LMRGs were included in the construction of LRS. The LRS was demonstrated to be an independent prognostic predictor for glioma patients, and a nomogram consisting of the LRS, IDH mutational status, WHO grade, and radiotherapy showed a C-index of 0.852. LRS values were significantly associated with stromal score, immune score, and ESTIMATE score. CIBERSORTx indicated remarkable differences in the abundance of TME immune cells between patients with high and low LRS risk levels. Based on the results of TIDE algorithm, we speculated that the high-risk group had a greater chance of benefiting from immunotherapy. Conclusion: The risk model based upon LMRGs could effectively predict prognosis in patients with glioma. Risk score also divided glioma patients into different groups with distinct TME immune characteristics. Immunotherapy is potentially beneficial to glioma patients with certain lipid metabolism profiles.

Causal effects of potential risk factors on postpartum depression: a Mendelian randomization study.

Background: Postpartum depression (PPD) is a type of depressive episode related to parents after childbirth, which causes a variety of symptoms not only for parents but also affects the development of children. The causal relationship between potential risk factors and PPD remains comprehensively elucidated. Methods: Linkage disequilibrium score regression (LDSC) analysis was conducted to screen the heritability of each instrumental variant (IV) and to calculate the genetic correlations between effective causal factors and PPD. To search for the causal effect of multiple potential risk factors on the incidence of PPD, random effects of the inverse variance weighted (IVW) method were applied. Sensitivity analyses, including weighted median, MR-Egger regression, Cochrane's Q test, and MR Pleiotropy Residual Sum and Outlier (MR-PRESSO), were performed to detect potential Mendelian randomization (MR) assumption violations. Multivariable MR (MVMR) was conducted to control potential multicollinearity. Results: A total of 40 potential risk factors were investigated in this study. LDSC regression analysis reported a significant genetic correlation of potential traits with PPD. MR analysis showed that higher body mass index (BMI) (Benjamini and Hochberg (BH) corrected p = 0.05), major depression (MD) (BH corrected p = 5.04E-19), and schizophrenia (SCZ) (BH corrected p = 1.64E-05) were associated with the increased risk of PPD, whereas increased age at first birth (BH corrected p = 2.11E-04), older age at first sexual intercourse (BH corrected p = 3.02E-15), increased average total household income before tax (BH corrected p = 4.57E-02), and increased years of schooling (BH corrected p = 1.47E-11) led to a decreased probability of PPD. MVMR analysis suggested that MD (p = 3.25E-08) and older age at first birth (p = 8.18E-04) were still associated with an increased risk of PPD. Conclusion: In our MR study, we found multiple risk factors, including MD and younger age at first birth, to be deleterious causal risk factors for PPD.

Purine metabolism-related gene expression signature predicts survival outcome and indicates immune microenvironment profile of gliomas.

Glioma is the most common malignant tumor in the central nervous system. The impact of metabolism on cancer development and the immune microenvironment landscape has recently gained broad attention. Purines are involved in multiple metabolic pathways. It has been proved that purine metabolism could regulate malignant biological behaviors and response to immune checkpoint inhibitors in multiple cancers. However, the relationship of purine metabolism with clinicopathological features and the immune landscape of glioma remains unclear. In this study, we explored the relationships between the expression of purine metabolism-related genes (PuMGs) and tumor features, including prognosis and microenvironment of glioma, based on analyses of 1,523 tumors from 4 public databases and our cohort. Consensus clustering based on 136 PuMGs classified the glioma patients into two clusters with significantly distinguished prognosis and immune microenvironment landscapes. Increased immune infiltration was associated with more aggressive gliomas. The prognostic Purine Metabolism-Related Genes Risk Signature (PuMRS), based on 11 critical PuMGs, stratified the patients into PuMRS low- and high-risk groups in the training set and was validated by validation sets from multiple cohorts. The high-risk group presented with significantly shorter overall survival, and further survival analysis demonstrated that the PuMRS was an independent prognostic factor in glioma. The nomogram combining PuMRS and other clinicopathological factors showed satisfactory accuracy in predicting glioma patients' prognosis. Furthermore, analyses of the tumor immune microenvironment suggested that higher PuMRS was correlated with increased immune cell infiltration and gene expression signatures of "hotË® tumors. Gliomas in the PuMRS high-risk group presented a higher expression level of multiple immune checkpoints, including PD-1 and PD-L1, and a better-predicted therapy response to immune checkpoint inhibitors. In conclusion, our study elucidated the relationship between the expression level of PuMGs and the aggressiveness of gliomas. Our study also endorsed the application of PuMRS to construct a new robust model for the prognosis evaluation of glioma patients. The correlations between the profiles of PuMGs expression and tumor immune microenvironment potentially provided guidance for immunotherapy in glioma.

Prognostic value of lactate metabolism-related gene expression signature in adult primary gliomas and its impact on the tumor immune microenvironment.

Glioma is one of the most malignant intracerebral tumors, whose treatment means was limited, and prognosis was unsatisfactory. Lactate metabolism patterns have been shown to be highly heterogenous among different tumors and produce diverse impact on the tumor microenvironment. To understand the characteristics and implications of lactate metabolism gene expression, we developed a lactate metabolism-related gene expression signature of gliomas based on RNA-sequencing data of a total of 965 patient samples from TCGA, CGGA, and our own glioma cohort. Sixty-three lactate metabolism-related genes (LMGs) were differentially expressed between glioma and normal brain tissue, and consensus clustering analysis identified two clusters distinct LMG expression patterns. The consensus clusters differed in prognosis, molecular characteristics and estimated immune microenvironment landscape involving immune checkpoint proteins, T cell dysfunction and exclusion, as well as tumor purity. Univariate Cox regression and Least Absolute Shrinkage and Selection Operator (LASSO) Cox hazard regression was applied in determining of prognosis-related lactate metabolism genes (PRLMGs), on which prognostic lactate metabolism risk score (PLMRS) was constructed. The high PLMRS group was associated with significantly poorer patient outcome. A nomogram containing PLMRS and other independent prognostic variables was established with remarkable predictive performance on patient survival. Exploration on the somatic mutations and copy number variations of the high- and low-PLMRS groups demonstrated their distinct genetic background. Together, our results indicated that the expression signature of LMG was associated with the prognosis of glioma patients and influenced the activity of immune cells in the tumor microenvironment, which may serve as a potential biomarker for predicting response of gliomas to immunotherapy.

Prognostic value of cuproptosis-related genes signature and its impact on the reshaped immune microenvironment of glioma.

Glioma is the most prevalent malignancy in the central nervous system. The impact of ion-induced cell death on malignant tumors' development and immune microenvironment has attracted broad attention in recent years. Cuproptosis is a novel copper-dependent mechanism that could potentially regulate tumor cell death by targeting mitochondria respiration. However, the role of cuproptosis in gliomas remains unclear. In the present study, we investigated the relationships between the expression of cuproptosis-related genes (CRGs) and tumor characteristics, including prognosis and microenvironment of glioma, by analyzing multiple public databases and our cohort. Consensus clustering based on the expression of twelve CRGs stratified the glioma patients into three subgroups with significantly different prognosis and immune microenvironment landscapes. Reduced immune infiltration was associated with the less aggressive CRG cluster. A prognostic CRGs risk signature (CRGRS), based on eight critical CRGs, classified the patients into low- and high-risk groups in the training set and was endorsed by validation sets from multiple cohorts. The high-risk group manifested a shorter overall survival, and further survival analysis demonstrated that the CRGRS was an independent prognostic factor. The nomogram combining CRGRS and other clinicopathological factors exhibited good accuracy in predicting the prognosis of glioma patients. Moreover, analyses of tumor immune microenvironment indicated that higher CRGRS was correlated with increased immune cell infiltration but diminished immune function. Gliomas in the high-risk group exhibited higher expression of multiple immune checkpoints, including PD-1 and PD-L1, and a better predicted therapy response to immune checkpoint inhibitors. In conclusion, our study elucidated the connections between CRGs expression and the aggressiveness of gliomas, and the application of CRGRS derived a new robust model for prognosis evaluation of glioma patients. The correlations between the profiles of CRGs expression and immune tumor microenvironment illuminated prospects and potential indications of immunotherapy for glioma.

Extraventricular site indicates higher grade but better prognosis in adult supratentorial ependymomas: a 14-year single-center retrospective cohort.

Supratentorial extraventricular ependymoma (STEE) and supratentorial intraventricular ependymoma (STIE) are two subsets of supratentorial ependymoma (SE). These two subsets have similar gene features and only differ in original sites: STEE occurs in the brain parenchyma, and STIE is located in ventricles and surrounded by cerebral spinal fluid. The present study aims to depict the diversities of these two subsets and elucidate the potential effects of the anatomic site on the tumor with the same type, grade, and molecular features. Sixty-six consecutive adult SE patients from 2008 to 2021 were enrolled in our study. Clinical data, pathological features, and long-term outcomes were analyzed retrospectively. Results demonstrated that adult STEE presented with a higher proportion of WHO grade 3 (P = .028) and higher Ki-67 index (≥10%) (P = .019) compared to adult STIE. Survival analysis demonstrated that patients of grade 3 STEE exhibited a significantly longer overall survival (OS) than patients of grade 3 STIE (median OS, 24.4 months vs. 13.0 months; P = .004). Grade 2 (hazard ratio (HR) = 0.217; P < .001) and gross total resection (GTR) (HR = 0.156; P < .001) were identified as favorable prognostic factors for all adult SE. The STEE was also associated with a lesser hazard of death for patients of grade 3 on multivariate analysis (HR = 0.263; P = .047). These findings suggested that the extraventricular site was an indicator for higher grade and better prognosis in adult supratentorial ependymoma.

Preoperative Naples prognostic score is a reliable prognostic indicator for newly diagnosed glioblastoma patients.

Background: Glioblastoma (GBM) accounts for approximately 80% of malignant gliomas and is characterized by considerable cellularity and mitotic activity, vascular proliferation, and necrosis. Naples prognostic score (NPS), based on inflammatory markers and nutritional status, has a prognostic ability in various cancers. In the current study, we aim to explore the prognostic value of operative NPS in GBM patients and compare the prognostic ability between NPS and controlling nutritional status (CONUT). Materials and methods: The retrospective analysis was carried out on consecutive newly diagnosed GBM patients who had underwent tumor resection at West China Hospital from February 2016 to March 2019. All statistical analyses were conducted using SPSS software and R software. Results: A total of 276 newly diagnosed GBM patients were enrolled in the current study. Overall survival (OS) (p < 0.001) and tumor location (p = 0.007) were significantly related to NPS. Serum albumin concentrate, cholesterol concentrate, neutrophil-to-lymphocyte ratio, lymphocyte ratio, and CONUT score were all significantly associated with NPS (p < 0.001). The Kaplan-Meier curve indicated that NPS (log-rank test, p < 0.001) and CONUT score (log-rank test, p = 0.023) were significantly associated with OS. Multivariate Cox regression revealed that both NPS and CONUT score served as independent prognostic indicators. The prognostic model with NPS had the strongest prognostic capability and best model-fitting. Conclusion: In the current study, NPS is found as an independent prognostic indicator for patients with newly diagnosed GBM, and the prognostic ability of NPS is superior to CONUT score.

[Latest Research Findings on the Role of Non-Tumor Cells in Glioma Microenvironment].

As the tumor cell-centered treatment strategies cannot curb the malignant progression of glioblastoma effectively, the therapeutic effect of glioblastoma is still not satisfactory. In addition to glioma cells, glioma microenvironment (GME) comprises massive numbers of non-tumor cells and soluble cytokines. The non-tumor cells include endothelial cells, pericytes, microglia/macrophages, mesenchymal cells, astrocytes, neurons, etc. These non-tumor cell components, together with glioma cells, form one organism which regulates the progression of glioma. Considerable progress has been been in research on GME, which will be conducive to the development of non-tumor cell targeted therapies and and improvements in the prognosis of glioma patients. Herein, we summarized the interaction of glioma cells with endothelial cells, pericytes, microglia/macrophages, astrocytes, neurons and mesenchymal cells, a topic that has been extensively researched, as well as the corresponding translational studies. We also discussed the potential challenges and opportunities of developing glioma treatments based on tumor microenvironment.

Prognostic significance of preoperative systemic inflammation response index in newly diagnosed glioblastoma patients underwent gross total resection: a propensity score matching analysis.

BACKGROUND: Glioblastoma (GBM) is the most frequent and lethal brain tumor, which possesses highly malignant characteristics and predominates in elder patients. Systemic inflammatory response index (SIRI) is a novel prognostic marker from peripheral blood, which is defined as neutrophil count × monocyte count/lymphocyte count. In the current research, we aim to explore the relationship between SIRI and newly diagnosed GBM underwent gross total resection (GTR). METHODS: A retrospective analysis was conducted on consecutive newly diagnosed GBM patients underwent operation at West China Hospital from March 2015 to January 2019. X-tile software was used to determine the optimal cut-off values of SIRI, and neutrophil to lymphocyte ratio (NLR). All statistical analyses were performed using SPSS software and R software. Propensity score matching (PSM) was conducted to adjust for imbalance of all potential confounding covariates. RESULTS: The current research included a total of 291 consecutive newly diagnosed GBM patients underwent gross total resection. Among them, 186 were male patients and 105 were female patients. In original cohort, only gender was evidently related to SIRI level. SIRI and NLR were independent prognostic indicators both in original cohort and PSM cohort. Prognostic models based on the independent prognostic factors were established, and prognostic capacity of Model SIRI was superior to Model NLR. CONCLUSION: In the current research, SIRI was determined to be an independent prognostic indicator for GBM. And the prognostic predictive ability of SIRI was stronger than NLR.

Multiple Model Evaluation of the Masseteric-to-Facial Nerve Transfer for Reanimation of the Paralyzed Face and Quick Prognostic Prediction.

Facial paralysis is negatively associated with functional, aesthetic, and psychosocial consequences. The masseteric-to-facial nerve transfer (MFNT) has many advantages in facial reanimation. The aim is to evaluate the effectiveness of our MFNT technique and define the potential factors predictive of outcome. The authors conducted a retrospective review of 20 consecutive patients who underwent MFNT using the temporofacial trunk of facial nerve. Videotapes and images were documented and evaluated according to Facial Nerve Grading Scale 2.0 (FNGS2.0) and Sunnybrook Facial Grading System (FGS). The quality-of-life was obtained using the Facial Clinimetric Evaluation (FaCE) Scale. Moreover, Facial Asymmetry Index (FAI), quantitative measurement of the width of palpebral fissure, deviation of the philtrum, and angles or excursions of the oral commissure were applied to explore the effect of the transfer metrically. Multivariable logistic regression models and Cox regression were prepared to predict the effect of MFNT by preoperative clinical features. The patients showed favorable outcomes graded by FNGS2.0, and experienced significantly improved scores in static and dynamic symmetry with slightly elevated scores in synkinesis evaluated by the Sunnybrook FGS. The score of FaCE Scale increased in all domains after reanimation. The quantitative indices indicated the symmetry restoration of the middle and lower face after MFNT. Regression analysis revealed that younger patients with severe facial paralysis are preferable to receive MFNT early for faster and better recovery, especially for traumatic causes. The findings demonstrate that MFNT is an effective technique for facial reanimation, and case screening based on clinical characteristics could be useful for surgical recommendation.

Do elderly patients (≥ 75 years old) with glioblastoma benefit from more radical surgeries in the era of temozolomide?

This study assesses the effect of extent of resection (EOR) on the longer-term survival and early mortality of elderly patients (≥ 75 years old) with glioblastoma. We used the Surveillance, Epidemiology, and End Results (SEER) database and data from our center to evaluate the effect of EOR on the long-term survival and early mortality of patients with glioblastoma. We included 50 elderly patients (≥ 75 years old) with glioblastoma visiting our hospital. The median overall survival of the patients who underwent a gross total resection, a subtotal resection, and a partial resection were 278, 200, and 83 days, respectively. The multivariate analysis showed that gross total resection (HR: 0.100; 95% CI: 0.015-0.671, p < 0.001) and subtotal reresection (HR: 0.134, 95% CI: 0.022-0.831, p < 0.001) were independent predictors of favorable prognosis when compared with partial resection. The data extracted from the SEER database also indicated that EOR was an independent predictor of OS, CCS, and early mortality. The stratification analysis revealed that gross total resection was the best protective factor of OS, early mortality, and CCS. Radical resection may improve the OS and CCS of glioblastoma patients aged ≥ 75 years and decrease early mortality.

Elevated GIGYF2 expression suppresses tumor migration and enhances sensitivity to temozolomide in malignant glioma.

Glioma is a common type of malignant and aggressive tumor in the brain. Despite progress on mechanistic studies, current understanding of the initiation and progression of glioma remains incomplete. GIGYF2 is a critical regulator in neural development and degeneration, however, its contribution in glioma is not yet elucidated. In this study, using an integrative approach spanning bioinformatic analysis and functional approaches, we explored the potential contribution of GIGYF2 in glioma. Bioinformatic data from public database and our cohort showed that GIGYF2 expression was closely associated with low glioma malignancy and better patient survival. Elevation of GIGYF2 expression impaired cell migration and enhanced temozolomide sensitivity of human glioma cells. We further establish its molecular mechanism by demonstrating that GIGYF2 inhibits MMP-9 mediated cell migration pathway and pro-survival AKT/Bax/Caspase-3 signaling. Our work identifies the suppressive role of GIGYF2 in gliomas, and clarifies the relationship between GIGYF2 expression and glioma malignancy, which may provide a potential target for future interventions.

Different materials of cranioplasty for patients undergoing decompressive craniectomy: A protocol for systematic review and network meta-analysis.

BACKGROUND: Cranioplasty is widely applied on patients who has undergone decompress craniectomy (DC) due to intractable increased intracranial pressure and the cranioplasty materials have been on the bleeding edge of biomolecular and material science. This systematic review and network meta-analysis (NMA) will be conducted to comprehensively evaluate the safety and efficacy of different cranial implants for patients with cranial defects due to various reasons. METHODS AND ANALYSIS: This protocol has been reported following the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols. The following electronic databases will be searched from the date of database establishment to September 1, 2020: PubMed, Embase, Cochrane Library, Web of Science, China National Knowledge Infrastructure, VIP, and Wanfang. Randomized controlled trials and non-randomized prospective studies focus on cranial implants will be included. Quality assessment will be conducted using Cochrane Collaboration's tool or risk of bias in nonrandomized studies of interventions based on their study designs. The primary outcome will be postoperative early mortality and implant failure while various complications for secondary outcomes. Pairwise and network meta-analysis will be conducted using STATA V.14 (StataCorp, College Station, Texas, USA). Subgroup analyses and sensitivity analyses will be conducted to assess the robustness of the results. ETHICS AND DISSEMINATION: This systematic review does not require an ethics approval or the need to obtain informed consent. The results will be published in a peer-reviewed scientific journal. PROTOCOL REGISTRATION NUMBER: INPLASY 202110001.

Prognostic Significance of Preoperative Albumin to Alkaline Phosphatase Ratio in Patients with Glioblastoma.

Objective: To explore the prognostic value of preoperative albumin to alkaline phosphatase ratio (AAPR) in patients with newly-diagnosed glioblastoma (GBM) and its association with clinical characteristics. Patients and methods: A retrospective analysis was carried out on patients with newly diagnosed GBM who had undergone operation at the Department of Neurosurgery at West China Hospital between June 1st 2016 to December 31st 2018. X-tile software was applied to determine the optimal cut-off values for AAPR, neutrophil to lymphocyte ratio (NLR), and albumin. Cox regression analyses were applied to evaluate the prognostic value of AAPR in GBM. PSM analysis was conducted to verify the results. Results: A total of 197 and 154 GBM patients were included in original cohort and PSM cohort respectively. The optimal cut-off value for AAPR, NLR, and albumin were 0.56, 4.55 and 42.2 g/L respectively. High AAPR was only significantly related to longer overall survival (OS) (p=0.010) in original cohort. In PSM cohort, no clinical variable was evidently related to the level of AAPR. AAPR was determined to be an independent prognostic indicator in both original cohort (HR=0.599, 95%CI 0.437-0.822, p=0.001) and PSM cohort (HR=0.649, 95%CI 0.459-0.918, p=0.015). Prognostic models including AAPR had better prognostic accuracy than that including albumin. Conclusion: Preoperative AAPR was determined to be an independent risk factor of prognosis in newly-diagnosed GBM patients, and its prognostic ability was stronger than albumin. And PSM analysis also validated the results.