Background: Neuropsychological deficits frequently occur in diffuse lower-grade glioma (DLGG) patients, but their relationship with molecular subgroups based on the 2016 World Health Organization (WHO) Classification of Tumors of the Central Nervous System (CNS) is unclear.Methods: All patients enrolled for this study were divided into different subgroups according to the molecular-integrated 2016 CNS WHO and morphology-centric 2007 CNS WHO to compare their neurocognitive function (NCF) dysfunction. Univariate and multivariate analyses were used to assess the independent factors for NCF decline. The performance of NCF changes for discrimination of IDH and 1p19q status was evaluated by receiver operating characteristic (ROC).Results: There was no significant difference in the clinical characteristics among the molecular and morphologic subgroups. In the molecular subgroups, significant differences in NCF alterations were found in terms of attention function, working memory and executive function in grade II glioma patients; in addition to these changes in NCF, memory function and abstract thinking were also significantly different in grade III glioma patients. The pairwise comparison further confirmed that patients with astrocytoma (A)/anaplastic astrocytoma (AA) with isocitrate dehydrogenase wild-type (IDHwt) glioma were more susceptible to severe cognitive decline in terms of the NCF performance described above. For the morphologic subgroups, only working memory was significantly different in grade III glioma patients. The distribution proportion was significantly different among each subgroup of DLGG (grade II, P = 0.001; grade III, P = 0.002). The proportion of extensive NCF decline (≥5 tests) was 4, 12, and 50% in the IDH mutant oligodendroglioma (IDHm-O), IDHm-A, and IDHwt-A subgroups, and this proportion was 33, 60, and 93% in the IDHm-AO, IDHm-AA, and IDHwt-AA subgroups, respectively. In multivariate regression analysis, molecular types were independent factors for NCF alterations after adjusted the factors of tumor and demographics (p < 0.05). ROC curves suggested combined NCF tests model showed an advantage in the differentiation of IDH status.Conclusions: NCF alteration is closely related to molecular-integrated subgroups with varying degrees and frequencies in DLGG. Patients with IDHwt gliomas are more susceptible to suffer from severe and extensive NCF decline than other subgroups.

BackgroundThe extent of resection of non-contrast enhancing tumors (EOR-NCEs) has been shown to be associated with prognosis in patients with newly diagnosed glioblastoma (nGBM). This study aimed to develop and independently validate a nomogram integrated with EOR-NCE to assess individual prognosis.MethodsData for this nomogram were based on 301 patients hospitalized for nGBM from October 2011 to April 2019 at the Beijing Tiantan Hospital, Capital Medical University. These patients were randomly divided into derivation (n=181) and validation (n=120) cohorts at a ratio of 6:4. To evaluate predictive accuracy, discriminative ability, and clinical net benefit, concordance index (C-index), receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA) were calculated for the extent of resection of contrast enhancing tumor (EOR-CE) and EOR-NCE nomograms. Comparison between these two models was performed as well.ResultsThe Cox proportional hazards model was used to establish nomograms for this study. Older age at diagnosis, Karnofsky performance status (KPS)<70, unmethylated O6-methylguanine-DNA methyltransferase (MGMT) status, wild-type isocitrate dehydrogenase enzyme (IDH), and lower EOR-CE and EOR-NCE were independent factors associated with shorter survival. The EOR-NCE nomogram had a higher C-index than the EOR-CE nomogram. Its calibration curve for the probability of survival exhibited good agreement between the identical and actual probabilities. The EOR-NCE nomogram showed superior net benefits and improved performance over the EOR-CE nomogram with respect to DCA and ROC for survival probability. These results were also confirmed in the validation cohort.ConclusionsAn EOR-NCE nomogram assessing individualized survival probabilities (12-, 18-, and 24-month) for patients with nGBM could be useful to provide patients and their relatives with health care consultations on optimizing therapeutic approaches and prognosis.

Background: lncRNA MIR17HG was upregulated in glioma, and participated in promoting proliferation, migration and invasion of glioma. However, the role of MIR17HG polymorphisms in the occurrence and prognosis of glioma is still unclear.Methods: In the study, 592 glioma patients and 502 control subjects were recruited. Agena MassARRAY platform was used to detect the genotype of MIR17HG polymorphisms. Logistic regression analysis was used to evaluate the relationship between MIR17HG single nucleotide polymorphisms (SNPs) and glioma risk by odds ratio (OR) and 95% confidence intervals (CIs). Kaplan–Meier curves, Cox hazards models were performed for assessing the role of these SNPs in glioma prognosis by hazard ratios (HR) and 95% CIs.Results: We found that rs7318578 (OR = 2.25, p = 3.18´10-5) was significantly associated with glioma susceptibility in the overall participants. In the subgroup with age < 40 years, rs17735387 (OR = 1.53, p = 9.05´10-3) and rs7336610 (OR = 1.35, p = 0.016) were related to the higher glioma susceptibility. More importantly, rs17735387 (HR = 0.82, log-rank p = 0.026) were associated with the longer survival of glioma patients. The GA genotype of rs17735387 had a better overall survival (HR = 0.75, log-rank p = 0.013) and progression free survival (HR = 0.73, log-rank p = 0.032) in patients with Ⅰ-Ⅱ glioma. We also found that rs72640334 was related to the poor prognosis (HR = 1.49, Log-rank p = 0.035) in female patients. In the subgroup of patients with age ³ 40 years, rs17735387 was associated with a better prognosis (HR = 0.036, Log-rank p = 0.002).Conclusion: Our study firstly reported that MIR17HG rs7318578 was a risk factor for glioma susceptibility and rs17735387 was associated with the longer survival of glioma among Chinese Han population, which might help to enhance the understanding of MIR17HG gene in gliomagenesis.

Background lncRNA MIR17HG was upregulated in glioma, and participated in promoting proliferation, migration and invasion of glioma. However, the role of MIR17HG polymorphisms in the occurrence and prognosis of glioma is still unclear. Methods In the study, 592 glioma patients and 502 control subjects were recruited. Agena MassARRAY platform was used to detect the genotype of MIR17HG polymorphisms. Logistic regression analysis was used to evaluate the relationship between MIR17HG single nucleotide polymorphisms (SNPs) and glioma risk by odds ratio (OR) and 95% confidence intervals (CIs). Kaplan–Meier curves, Cox hazards models were performed for assessing the role of these SNPs in glioma prognosis by hazard ratios (HR) and 95% CIs. Results We found that rs7318578 (OR = 2.25, p = 3.18 × 10− 5) was significantly associated with glioma susceptibility in the overall participants. In the subgroup with age <  40 years, rs17735387 (OR = 1.53, p = 9.05 × 10− 3) and rs7336610 (OR = 1.35, p = 0.016) were related to the higher glioma susceptibility. More importantly, rs17735387 (HR = 0.82, log-rank p = 0.026) were associated with the longer survival of glioma patients. The GA genotype of rs17735387 had a better overall survival (HR = 0.75, log-rank p = 0.013) and progression free survival (HR = 0.73, log-rank p = 0.032) in patients with I-II glioma. We also found that rs72640334 was related to the poor prognosis (HR = 1.49, Log-rank p = 0.035) in female patients. In the subgroup of patients with age ≥ 40 years, rs17735387 was associated with a better prognosis (HR = 0.036, Log-rank p = 0.002). Conclusion Our study firstly reported that MIR17HG rs7318578 was a risk factor for glioma susceptibility and rs17735387 was associated with the longer survival of glioma among Chinese Han population, which might help to enhance the understanding of MIR17HG gene in gliomagenesis. In subsequent studies, we will continue to collect samples and follow up to further validate our findings and further explore the function of these MIR17HG SNPs in glioma in a larger sample size.

A data-driven estimation method for the plastic properties of alloys was proposed using indentations at neighboring positions. An instrumented indentation test is an efficient approach to measure mechanical properties such as equivalent elastic modulus and hardness. In the mechanical test, subsequent experiments are generally performed apart from existing indentations to avoid the interaction effect caused by the dependency on the deformation history of metal plasticity. In this study, the interaction effect was utilized to estimate the plastic properties, based on the difference of load-depth curves between the first and second indentations at neighboring positions. Using finite element simulations of the neighboring indentation tests, the effective experimental conditions were examined, and response surfaces of the loading curvatures were characterized to determine two material constants of a simple constitutive model of plasticity. Finally, the proposed approach was validated for application to aluminum alloys and stainless steel. It can be also applied to various alloys characterized by different elastic moduli. KEYWORDS elastic-plastic material; finite element method; mechanical testing; response surface; instrumented indentation test; material database; ARTICLE CLASSIFICATION: Data analysis (AI, machine learning, data-driven analysis, descriptor development, structure search/identification)