FeIII Chelated with Humic Acid with Easy Synthesis Conditions and Good Performance as Anode Materials for Lithium-Ion Batteries.

In this work, we prepared a green, cheap material by chelating humic acid with ferric ions (HA-Fe) and used it as an anode material in LIBs for the first time. From the SEM, TEM, XPS, XRD, and nitrogen adsorption-desorption experimental results, it was found that the ferric ion can chelate with humic acid successfully under mild conditions and can increase the surface area of materials. Taking advantage of the chelation between the ferric ions and HA, the capacity of HA-Fe is 586 mAh·g-1 at 0.1 A·g-1 after 1000 cycles. Moreover, benefitting from the chelation effect, the activation degree of HA-Fe (about 8 times) is seriously improved compared with pure HA material (about 2 times) during the change-discharge process. The capacity retention ratio of HA-Fe is 55.63% when the current density increased from 0.05 A·g-1 to 1 A·g-1, which is higher than that of HA (32.55%) and Fe (24.85%). In the end, the storage mechanism of HA-Fe was investigated with ex-situ XPS measurements, and it was found that the C=O and C=C bonds are the activation sites for storage Li ions but have different redox voltages.

A Multiparametric MRI-Based Radiomics Nomogram for Preoperative Prediction of Survival Stratification in Glioblastoma Patients With Standard Treatment.

OBJECTIVE: To construct and validate a radiomics nomogram for preoperative prediction of survival stratification in glioblastoma (GBM) patients with standard treatment according to radiomics features extracted from multiparameter magnetic resonance imaging (MRI), which could facilitate clinical decision-making. METHODS: A total of 125 eligible GBM patients (53 in the short and 72 in the long survival group, separated by an overall survival of 12 months) were randomly divided into a training cohort (n = 87) and a validation cohort (n = 38). Radiomics features were extracted from the MRI of each patient. The T-test and the least absolute shrinkage and selection operator algorithm (LASSO) were used for feature selection. Next, three feature classifier models were established based on the selected features and evaluated by the area under curve (AUC). A radiomics score (Radscore) was then constructed by these features for each patient. Combined with clinical features, a radiomics nomogram was constructed with independent risk factors selected by the logistic regression model. The performance of the nomogram was assessed by AUC, calibration, discrimination, and clinical usefulness. RESULTS: There were 5,216 radiomics features extracted from each patient, and 5,060 of them were stable features judged by the intraclass correlation coefficients (ICCs). 21 features were included in the construction of the radiomics score. Of three feature classifier models, support vector machines (SVM) had the best classification effect. The radiomics nomogram was constructed in the training cohort and exhibited promising calibration and discrimination with AUCs of 0.877 and 0.919 in the training and validation cohorts, respectively. The favorable decision curve analysis (DCA) indicated the clinical usefulness of the radiomics nomogram. CONCLUSIONS: The presented radiomics nomogram, as a non-invasive tool, achieved satisfactory preoperative prediction of the individualized survival stratification of GBM patients.

Online calculator to predict early mortality in patient with surgically treated recurrent lower-grade glioma.

PURPOSE: The aim of this study was to investigate the epidemiological characteristics and associated risk factors of recurrent lower-grade glioma [LGG] (WHO grades II and III) according to the 2016 updated WHO classification paradigm and finally develop a model for predicting early mortality (succumb within a year after reoperation) in recurrent LGG patients. METHODS: Data were obtained from consecutive patients who underwent surgery for primary LGG and reoperation for tumor recurrence. The end point "early mortality" was defined as death within 1 year after the reoperation. Predictive factors, including basic clinical characteristics and laboratory data, were retrospectively collected. RESULTS: A final nomogram was generated for surgically treated recurrent LGG. Factors that increased the probability of early mortality included older age (P = 0.042), D-dimer> 0.187 (P = 0.007), RDW > 13.4 (P = 0.048), PLR > 100.749 (P = 0.014), NLR > 1.815 (P = 0.047), 1p19q intact (P = 0.019), IDH1-R132H Mutant (P = 0.048), Fib≤2.80 (P = 0.018), lack of Stupp concurrent chemoradiotherapy (P = 0.041), and an initial symptom of epilepsy (P = 0.047). The calibration curve between the prediction from this model and the actual observations showed good agreement. CONCLUSION: A nomogram that predicts individualized probabilities of early mortality for surgically treated recurrent LGG patients could be a practical clinical tool for counseling patients regarding treatment decisions and optimizing therapeutic approaches. Free online software implementing this nomogram is provided at https://warrenwrl.shinyapps.io/RecurrenceGliomaEarlyM/.

Prediction of blood supply in vestibular schwannomas using radiomics machine learning classifiers.

This study attempts to explore the radiomics-based features of multi-parametric magnetic resonance imaging (MRI) and construct a machine-learning model to predict the blood supply in vestibular schwannoma preoperatively. By retrospectively collecting the preoperative MRI data of patients with vestibular schwannoma, patients were divided into poor and rich blood supply groups according to the intraoperative recording. Patients were divided into training and test cohorts (2:1), randomly. Stable features were retained by intra-group correlation coefficients (ICCs). Four feature selection methods and four classification methods were evaluated to construct favorable radiomics classifiers. The mean area under the curve (AUC) obtained in the test set for different combinations of feature selecting methods and classifiers was calculated separately to compare the performance of the models. Obtain and compare the best combination results with the performance of differentiation through visual observation in clinical diagnosis. 191 patients were included in this study. 3918 stable features were extracted from each patient. Least absolute shrinkage and selection operator (LASSO) and logistic regression model was selected as the optimal combinations after comparing the AUC calculated by models, which predicted the blood supply of vestibular schwannoma by K-Fold cross-validation method with a mean AUC = 0.88 and F1-score = 0.83. Radiomics machine-learning classifiers can accurately predict the blood supply of vestibular schwannoma by preoperative MRI data.

Advanced Diagnosis of Glioma by Using Emerging Magnetic Resonance Sequences.

Glioma, the most common primary brain tumor in adults, can be difficult to discern radiologically from other brain lesions, which affects surgical planning and follow-up treatment. Recent advances in MRI demonstrate that preoperative diagnosis of glioma has stepped into molecular and algorithm-assisted levels. Specifically, the histology-based glioma classification is composed of multiple different molecular subtypes with distinct behavior, prognosis, and response to therapy, and now each aspect can be assessed by corresponding emerging MR sequences like amide proton transfer-weighted MRI, inflow-based vascular-space-occupancy MRI, and radiomics algorithm. As a result of this novel progress, the clinical practice of glioma has been updated. Accurate diagnosis of glioma at the molecular level can be achieved ahead of the operation to formulate a thorough plan including surgery radical level, shortened length of stay, flexible follow-up plan, timely therapy response feedback, and eventually benefit patients individually.

Preoperative Prediction of Meningioma Consistency via Machine Learning-Based Radiomics.

OBJECTIVES: The aim of this study was to establish and validate a radiomics nomogram for predicting meningiomas consistency, which could facilitate individualized operation schemes-making. METHODS: A total of 172 patients was enrolled in the study (train cohort: 120 cases, test cohort: 52 cases). Tumor consistency was classified as soft or firm according to Zada's consistency grading system. Radiomics features were extracted from multiparametric MRI. Variance selection and LASSO regression were used for feature selection. Then, radiomics models were constructed by five classifiers, and the area under curve (AUC) was used to evaluate the performance of each classifiers. A radiomics nomogram was developed using the best classifier. The performance of this nomogram was assessed by AUC, calibration and discrimination. RESULTS: A total of 3840 radiomics features were extracted from each patient, of which 3719 radiomics features were stable features. 28 features were selected to construct the radiomics nomogram. Logistic regression classifier had the highest prediction efficacy. Radiomics nomogram was constructed using logistic regression in the train cohort. The nomogram showed a good sensitivity and specificity with AUCs of 0.861 and 0.960 in train and test cohorts, respectively. Moreover, the calibration graph of the nomogram showed a favorable calibration in both train and test cohorts. CONCLUSIONS: The presented radiomics nomogram, as a non-invasive prediction tool, could predict meningiomas consistency preoperatively with favorable accuracy, and facilitated the determination of individualized operation schemes.

Erratum: Dihydroartemisinin inhibits the Raf/ERK/MEK and PI3K/AKT pathways in glioma cells.

[This corrects the article DOI: 10.3892/ol.2015.3699.].

Effects of Preoperative Carbamazepine Treatment on Microvascular Decompression for Classical Trigeminal Neuralgia.

BACKGROUND: Carbamazepine (CBZ) is the first-line therapy for trigeminal neuralgia (TN), and microvascular decompression (MVD) is considered to be an effective surgical treatment for TN. However, the effect of preoperative CBZ treatment on MVD outcome is not clear. METHODS: From 2013 to 2019, 63 patients with classical TN underwent MVD at the First Affiliated Hospital of Zhengzhou University, China. Data were collected through telephone follow-up and electronic medical records in April 2020. Short-term surgical outcome and long-term follow-up data were estimated by univariate and multivariate analysis. RESULTS: Multivariate analysis indicated that preoperative CBZ treatment was not a significant predictor for short-term outcomes of MVD (P > 0.05). Multivariate analysis for the long-term outcome of MVD indicated that preoperative CBZ treatment could predict postoperative recurrence of TN (P < 0.05). CONCLUSIONS: For patients with classical TN, a longer preoperative medication history of CBZ treatment had no significant effect on short-term outcome of MVD, but CBZ treatment was associated with a poor long-term outcome following MVD.

Preoperative Predictors of Early Mortality Risk in Isocitrate Dehydrogenase-Wild-Type Glioblastoma Patients Treated with Standard Therapy.

PURPOSE: Early identification of early mortality for glioblastoma (GBM) patients based on laboratory findings at the time of diagnosis could improve the overall survival. The study aimed to explore preoperative factors associated with higher risk of early death (within 1 year after surgery) for isocitrate dehydrogenase (IDH) -wild-type (wt) GBM patients. PATIENTS AND METHODS: We conducted a retrospective analysis of 194 IDH-wt GBM patients who underwent standard treatment. The probability of dying within 1 year after gross total resection (GTR) was defined as the end point "early mortality". Retrospective collection of predictive factors including clinical characteristics and laboratory data at diagnosis. RESULTS: Median follow-up time after GTR was 16 months (3-41 months). Forty-two patients died within 1 year after surgery (1-year mortality rate: 21.6%). All potential predictive factors were assessed on univariate analyses, which revealed the following factors as associated with higher risk of early death: older age (P = 0.013), occurrence of non-seizures symptoms (P = 0.042), special tumor positions (P = 0.046), higher neutrophil-to-lymphocyte ratio (NLR) (P = 0.015), higher red blood cell distribution width (RDW) (P = 0.019), higher lactate dehydrogenase (LDH) (P = 0.005), and higher fibrinogen (FIB) (P = 0.044). In a multivariate analysis, tumor location (P = 0.012), NLR (P = 0.032) and LDH (P = 0.002) were independent predictors of early mortality. The C-index of the nomogram was 0.795. The calibration curve showed good agreement between prediction by nomogram and actual observation. CONCLUSION: Tumor location, preoperative elevated NLR and serum LDH level were independent predictors for 1-year mortality after GTR. We indicate that increased preoperative NLR or LDH may guide patients to review head magnetic resonance imaging (MRI) more frequently and regularly to monitor tumor progression.

Clinical practice guidelines for the management of adult diffuse gliomas.

To follow the revision of the fourth edition of WHO classification and the recent progress on the management of diffuse gliomas, the joint guideline committee of Chinese Glioma Cooperative Group (CGCG), Society for Neuro-Oncology of China (SNO-China) and Chinese Brain Cancer Association (CBCA) updated the clinical practice guideline. It provides recommendations for diagnostic and management decisions, and for limiting unnecessary treatments and cost. The recommendations focus on molecular and pathological diagnostics, and the main treatment modalities of surgery, radiotherapy, and chemotherapy. In this guideline, we also integrated the results of some clinical trials of immune therapies and target therapies, which we think are ongoing future directions. The guideline should serve as an application for all professionals involved in the management of patients with adult diffuse glioma and also a source of knowledge for insurance companies and other institutions involved in the cost regulation of cancer care in China and other countries.

A Hematological-Related Prognostic Scoring System for Patients With Newly Diagnosed Glioblastoma.

BACKGROUND: Glioblastoma is the most common primary malignant brain tumor. Recent studies have shown that hematological biomarkers have become a powerful tool for predicting the prognosis of patients with cancer. However, most studies have only investigated the prognostic value of unilateral hematological markers. Therefore, we aimed to establish a comprehensive prognostic scoring system containing hematological markers to improve the prognostic prediction in patients with glioblastoma. PATIENTS AND METHODS: A total of 326 patients with glioblastoma were randomly divided into a training set and external validation set to develop and validate a hematological-related prognostic scoring system (HRPSS). The least absolute shrinkage and selection operator Cox proportional hazards regression analysis was used to determine the optimal covariates that constructed the scoring system. Furthermore, a quantitative survival-predicting nomogram was constructed based on the hematological risk score (HRS) derived from the HRPSS. The results of the nomogram were validated using bootstrap resampling and the external validation set. Finally, we further explored the relationship between the HRS and clinical prognostic factors. RESULTS: The optimal cutoff value for the HRS was 0.839. The patients were successfully classified into different prognostic groups based on their HRSs (P < 0.001). The areas under the curve (AUCs) of the HRS were 0.67, 0.73, and 0.78 at 0.5, 1, and 2 years, respectively. Additionally, the 0.5-, 1-y, and 2-y AUCs of the HRS were 0.51, 0.70, and 0.79, respectively, which validated the robust prognostic performance of the HRS in the external validation set. Based on both univariate and multivariate analyses, the HRS possessed a strong ability to predict overall survival in both the training set and validation set. The nomogram based on the HRS displayed good discrimination with a C-index of 0.81 and good calibration. In the validation cohort, a high C-index value of 0.82 could still be achieved. In all the data, the HRS showed specific correlations with age, first presenting symptoms, isocitrate dehydrogenase mutation status and tumor location, and successfully stratified them into different risk subgroups. CONCLUSIONS: The HRPSS is a powerful tool for accurate prognostic prediction in patients with newly diagnosed glioblastoma.

Behavior-Oriented Nomogram for the Stratification of Lower-Grade Gliomas to Improve Individualized Treatment.

Secondary glioblastomas (sGBM) are derived from previously lower-grade [World Health Organization (WHO) grades II or III] gliomas. Lower-grade benign-behaving gliomas may retain their former grade following recurrence, or may become malignant higher-grade glioblastomas. Prediction of tumor behavior in lower-grade gliomas is critical for individualized glioma therapy. A total of 89 patients were included between January 2000 and January 2019 in the present study to establish a nomogram via univariate and multivariate logistic regression analyses. Nomogram predictive performance was tested in the validation group. We then analyzed 36 O-6-methylguanine-DNA methyltransferase (MGMT) unmethylated lower-grade gliomas from patients seen at West China Hospital of Sichuan University. Survival statistics were calculated with the Kaplan-Meier method. Two clinical factors (molecular diagnosis and WHO grade), five radiological factors (location, cortical involvement, multicentricity, uniformity, and margin enhancement), one biomarker (1p19q codeletion), and a combination of three biomarkers (IDH+/ATRX-/TP53-) were associated with glioma upgrading. Nomograms positive for these prognostic factors had an AUC of 0.880 in the derivation group and 0.857 in the validation group. The calibration and score-stratified survival curves for the derivation group and validation group were good. An operational nomogram was published at https://warrenwrl.shinyapps.io/DynNomapp/. The overall survival of secondary gliomas in the MGMT-unmethylated cohort were influenced independently by the use of temozolomide during the treatment of formerly low-grade gliomas (p=0.00096). Clinical and radiological factors and biomarker-based behavior-oriented nomograms may offer a feasible identification tool for the detection of sGBM precursors. This method may further assist neurosurgeons with the stratification of lower-grade glioma cases and thus the development of better, more individualized treatment plans.

A nomogram to predict the progression-free survival of clival chordoma.

OBJECTIVE: Chordoma shows poor patient prognosis because of its high recurrence rate. Even though many clinical factors and biomarkers are reported to be associated with prognosis, no prediction model has been applied clinically. Thus, the authors aim to derive and validate a prognostic nomogram to predict progression-free survival (PFS) of chordoma. METHODS: A total of 201 patients were randomly divided into a derivation group (151 cases) and a validation group (50 cases). The expression levels of biomarkers were quantified using tissue microarray analysis. A nomogram was established via univariate and multivariate Cox regression analysis in the derivation group. The predictive performance of the nomogram was then tested in the validation group. RESULTS: The mean follow-up interval was 57 months (range 26-107 months). One clinical factor and 3 biomarkers were confirmed to be associated with PFS, including degree of resection, E-cadherin, Ki-67, and VEGFA. The nomogram with these prognostic factors had areas under the receiver operating characteristic curve of 0.87 and 0.95 in the derivation group at 3 years and 5 years, respectively, compared with 0.87 and 0.84 in the validation group. Calibration and score-stratified survival curve were good in the derivation group and validation group, respectively. CONCLUSIONS: The established nomogram performs well for predicting the PFS of chordoma and for risk stratification, which could facilitate prognostic evaluation and follow-up.

Prognostic value of preoperative hematological markers combined with molecular pathology in patients with diffuse gliomas.

The prediction of clinical outcome for patients with infiltrative gliomas is challenging. Although preoperative hematological markers have been proposed as predictors of survival in glioma and other cancers, systematic investigations that combine these data with other relevant clinical variables are needed to improve prognostic accuracy and patient outcomes. We investigated the prognostic value of preoperative hematological markers, alone and in combination with molecular pathology, for the survival of 592 patients with Grade II-IV diffuse gliomas. On univariate analysis, increased neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and monocyte-to-lymphocyte ratio (MLR), and decreased albumin-to-globulin ratio (AGR), all predicted poor prognosis in Grade II/III gliomas. Multivariate analysis incorporating tumor status based on the presence of IDH mutations, TERT promoter mutations, and 1p/19q codeletion showed that in lower-grade gliomas, high NLR predicted poorer survival for the triple-negative, IDH mutation only, TERT mutation only, and IDH and TERT mutation groups. NLR was an independent prognostic factor in Grade IV glioma. We therefore propose a prognostic model for diffuse gliomas based on the presence of IDH and TERT promoter mutations, 1p/19q codeletion, and NLR. This model classifies lower-grade gliomas into nine subgroups that can be combined into four main risk groups based on survival projections.

Long noncoding RNA ENST00000413528 sponges microRNA-593-5p to modulate human glioma growth via polo-like kinase 1.

AIMS: In this study, we examined the expression of lncRNA ENST00000413528 in glioma and determined its role in glioma development. METHODS: LncRNA ENST00000413528 was detected in glioma tissues by lncRNA microarray. Then, we performed real-time PCR, CCK-8, colony formation assay, flow cytometry, caspase-3/7 assay and animal experiment to detect the function of ENST00000413528 in glioma after ENST00000413528 knockdown. Subsequent bioinformatics analysis, luciferase reporter assays and RNA immunoprecipitation (RIP) assay western blotting indicated possible downstream regulatory molecules. The expression of PLK1 in glioma tissues was also examined by immunohistochemistry staining. RESULTS: Expression of ENST00000413528 was significantly increased in glioma tissues and LN229 and U251 cells. PLK1 protein could not be detected in peritumoral brain edema (PTBE) tissues; however, it showed an increasing number of positively cytoplasmic stained from WHO-Grade II to Grade III gliomas. Knockdown of ENST00000413528 in glioma cells inhibited cell proliferation and colony formation abilities, induced the G0/G1 arrest of the cell cycle, and promoted apoptosis. The dual reporter assay and RNA immunoprecipitation assay verified the interaction between ENST00000413528 and miR-593. We also demonstrated that polo-like kinase 1 (PLK1) was regulated by miR-593; PLK1 messenger RNA lacking 3'UTR partially reversed the effects caused by ENST00000413528 knockdown or miR-593 upregulation. CONCLUSION: lncRNA ENST00000413528 is closely related to the development of glioma via the miR-593-5p/PLK1 pathway.

Band-Gap Tuning of Organic-Inorganic Hybrid Palladium Perovskite Materials for a Near-Infrared Optoelectronics Response.

Organic-inorganic hybrid material is a recent hot topic in the scientific community. The best band gap for the entire solar absorption spectrum is about 1.1 eV. However, the lead perovskite band gap is about 1.5 eV. Therefore, developing organic-inorganic hybrid material toward the broader light harvesting of the solar spectrum is extremely urgent. In this study, we prepare three kinds of organic-inorganic hybrid palladium perovskite materials, including (CH3NH3)2PdCl4, (CH3NH3)2PdCl4-x Br x , and CH3NH3PdI3, for an optoelectronic response. The absorption cut offs of (CH3NH3)2PdCl4, (CH3NH3)2PdCl4-x Br x , and CH3NH3PdI3 are approximately 600, 700, and 1000 nm, respectively. The band gaps of (CH3NH3)2PdCl4, (CH3NH3)2PdCl4-x Br x , and CH3NH3PdI3 are determined to be approximately 2.15, 1.87, and 1.25 eV, respectively. To the best of our knowledge, this is the first study that discusses adsorption properties and photoelectric behavior of organic-inorganic hybrid palladium perovskite materials. Interestingly, the photoelectric response of the devices based on CH3NH3PdI3 reaches 950 nm. The results will attract attention in the fields of optical recorders, optical memory, security, light capture, and light treatment.

Synthesis, Crystal Structure, UV-Vis Adsorption Properties, Photoelectric Behavior, and DFT Computational Study of All-Inorganic and Lead-Free Copper Halide Salt K2Cu2Cl6.

In this study, all-inorganic copper halide salt K2Cu2Cl6 single-crystal and thin films were prepared. The single-crystal diffraction data belonged to the monoclinic K2Cu2Cl6 (space group = P 2(1)/C, unit cell parameters of a = 4.0340 Å, b = 13.7987 Å, c = 8.7445 Å, α = 90.000, ß = 97.123, and γ = 90.000). As far as we know, this is the first study of the copper halide salt K2Cu2Cl6 for optoelectronic applications. The band gap of K2Cu2Cl6 is calculated to be approximately 1.85 eV. A low-cost photodetector based on the K2Cu2Cl6 thin film was efficient under different monochromatic light from 330 to 390 nm with different chopping frequencies (1.33-30 Hz). Density functional theory (DFT) computational results indicate that the valence bands (VBs) and conduction bands (CBs) are shifted up in energy using the orbital-dependent correction to the DFT energy. Partial density of states reveals that the VBs and narrow CBs are derived from the hybrid orbitals of Cu2+ 3d and Cl- p, respectively.

Tuning Ni-Foam into NiOOH/FeOOH Heterostructures toward Superior Water Oxidation Catalyst via Three-Step Strategy.

Splitting of water into hydrogen and oxygen has become a strategic research topic. In the two semi-reactions of water splitting, water oxidation is preferred to the four-electron-transfer process with a higher overpotential (η) and is the decisive step in water splitting. Therefore, efficient water oxidation catalysts must be developed. IrO x and RuO x catalysts are currently the most efficient catalysts in water oxidation. However, the limited reserve and high prices of precious metals, such as Ir and Ru, limit future large-scale industrial production of water oxidation catalysts. In this study, we tune inert Ni-foam into highly active NiOOH/FeOOH heterostructures as water oxidation catalysts via three-step strategy (surface acid-treating, electroplating, and electrooxidation). NiOOH/FeOOH heterostructures as water oxidation catalysts only require η of 257 mV to reach a current density of 10 mA cm-2, which is superior to that of IrO2/Ni-foam (280 mV). The high electrochemically active surface area (72.50 cm2) and roughness factor demonstrate abundant interfaces in NiOOH/FeOOH heterostructures, thus accelerating water oxidation activity. The small value (4.8 Ω cm2) of charge transfer resistance (R ct) indicate that fast electronic exchange occurs between NiOOH/FeOOH heterostructures catalyst and reaction of water oxidation. Hydrogen-to-oxygen volume ratios (approximately 2:1) indicate an almost overall water splitting by the double-electrode system. Faraday efficiency of H2 or O2 is close to 90% at 2:1 hydrogen-to-oxygen volume ratio. NiOOH/FeOOH heterostructures exhibit good stability. The results provide significance in fundamental research and practical applications in solar water splitting, artificial photoelectrochemical cells, and electrocatalysts.

RIZ1 and histone methylation status in pituitary adenomas.

RIZ1 displays strong tumor-suppressive activities, which has a potential histone methyltransferase activity. The objective of the study was to evaluate the level and the methylation status of RIZ1 and analyze its association with clinicopathological features and the histone in the pituitary adenomas. We found that RIZ1-positive cases were 11/50 and H-Scores 22.75 ± 11.83 in invasive pituitary adenomas and 26/53 and 66.3 ± 21.7 in non-invasive pituitary adenomas (χ2 = 8.182, p = 0.004). RIZ1 and C-myc showed the opposite trend in these cases. The methylation levels of RIZ1 were more than 50% in 30.4% (7/23) CpG sites through MALDI-TOF Mass array. There was significant difference (p < 0.01) in 4 CpG sites between invasive pituitary adenoma group and non-invasive pituitary adenoma group; furthermore, the relieved methylation levels of H3K4/H3K9 and enhanced methylation levels of H3K27 in the patients' serum were found. Furthermore, there was statistic difference of H3K4 and H3K27 methylation between invasive pituitary adenoma and non-invasive pituitary adenoma group (p < 0.01). The average progression-free survival in high RIZ1 group was 52.63 ± 7.62 months and 26.06 ± 4.23 months in low RIZ1 group (p < 0.05). Promoter region methylation of RIZ1 may play an important role in the epigenetic silencing of RIZ1 expression in pituitary adenomas, which may translate into important diagnostic and therapeutic applications.

Long non-coding RNA MALAT1 promotes proliferation and suppresses apoptosis of glioma cells through derepressing Rap1B by sponging miR-101.

Long non-coding RNAs (lncRNAs) have been recently shown to be dysregulated and closely related to several cancers. Here, we aimed to elucidate the function and the possible molecular mechanisms of lncRNA Metastasis-associated lung Adenocarcinoma transcript-1 (MALAT1) in human glioma. Quantitative real-time PCR (qRT-PCR) was used to detect the expressions of MALAT1, miR-101 and Rap1B mRNA in U251 and U87 cells. The protein level of Rap1B was examined by western blot assays. Moreover, the proliferation and apoptosis of U251 and U87 cells were determined by CCK-8 assay and flow cytometry analysis, respectively. Additionally, the targets of miR-101 were identified by target prediction and luciferase reporter assays. The results demonstrated that MALAT1 and Rap1B were upregulated, while miR-101 expression was downregulated in glioma cell lines U251 and U87. MALAT1 and Rap1B knockdown could inhibit proliferation and induce apoptosis of glioma cells. Moreover, MALAT1 promoted the Rap1B expression by sponging miR-101 in U251 and U87 cells. Furthermore, miR-101 downregulation or Rap1B overexpression reversed the proliferation inhibitory and apoptosis induction of glioma cell lines caused by MALAT1 knockdown. Taken together, MALAT1 promotes proliferation and suppresses apoptosis of glioma cells through derepressing Rap1B by sponging miR-101. The present study elucidates a novel MALAT1-miR-101-Rap1B regulatory axis in glioma, contributing to a better understanding of the glioma pathogenesis and providing a promising therapeutic target for glioma patients.