Peptidomics insights: neutrophil extracellular traps (NETs) related to the chronic subdural hemorrhage.

Chronic subdural hemorrhage (CSDH) refers to a hematoma with an envelope between the dura mater and the arachnoid membrane and is more common among the elderly. It was reported that the dura mater, which is highly vascularized with capillary beds, precapillary arterioles and postcapillary venules play an important role in the protection of the central nervous system (CNS). Numerous evidences suggests that peptides play an important role in neuroprotection of CNS. However, whether dura mater derived endogenous peptides participate in the pathogenesis of CSDH remains undetermined. In the current study, the peptidomic profiles were performed in human dura of CSDH (three patients) and the relative control group (three non-CSDH samples) by LC-MS (liquid chromatography-mass spectrometry). The results suggested that a total of 569 peptides were differentially expressed in the dura matter of CSDH compared with relative controls, including 217 up-regulated peptides and 352 down-regulated peptides. Gene Ontology (GO) analysis demonstrated that the precursor proteins of those differentially expressed peptides were involved in the various biological processes. Interestingly, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis suggested that NETs participated in the pathogenies of CSDH. Further investigate showed that H3Cit was significantly elevated in the dural and hematoma membranes of patients with CSDH compared to patients without CSDH. Taken together, our results showed the differentially expressed peptides in human dura mater of CSDH and demonstrated that NETs formation in the dural and hematoma membranes might be involved in the pathogenesis of CSDH. It is worth noting that pharmacological inhibition of NETs may have potential therapeutic implications for CSDH.

CBX7 reprograms metabolic flux to protect against meningioma progression by modulating the USP44/c-MYC/LDHA axis.

Meningioma is one of the most common primary neoplasms in the central nervous system, whereas there is still no specific molecularly targeted therapy that has been approved for the clinical treatment of aggressive meningiomas. There is therefore an urgent demand to decrypt the biological and molecular landscape of malignant meningioma. Here, through the in-silica prescreening and 10-year follow-up of 445 meningioma patients, we uncovered that CBX7 is progressively decreased with malignancy grade and neoplasia stage in meningioma and a high CBX7 expression level predicts a favorable prognosis in meningioma patients. CBX7 restoration significantly induces cell cycle arrest and inhibits meningioma cell proliferation. iTRAQ-based proteomics analysis indicated that CBX7 restoration triggers the metabolic shift from glycolysis to oxidative phosphorylation. The mechanistic study demonstrated that CBX7 promotes the proteasome-dependent degradation of c-MYC proteins by transcriptionally inhibiting the expression of a c-MYC deubiquitinase, USP44, which attenuates c-MYC-mediated transactivation of LDHA transcripts and further inhibits glycolysis and subsequent cellular proliferation. More importantly, the functional role of CBX7 was further confirmed in both subcutaneous and orthotopic meningioma xenografts mouse models and human meningioma patients. Together, our results shed light on the critical role of CBX7 during meningioma malignancy progression and identified the CBX7/USP44/c-MYC/LDHA axis as a promising therapeutic target against meningioma progression.

Predicting meningioma grades and pathologic marker expression via deep learning.

OBJECTIVES: To establish a deep learning (DL) model for predicting tumor grades and expression of pathologic markers of meningioma. METHODS: A total of 1192 meningioma patients from two centers who underwent surgical resection between September 2018 and December 2021 were retrospectively included. The pathological data and post-contrast T1-weight images for each patient were collected. The patients from institute I were subdivided into training, validation, and testing sets, while the patients from institute II served as the external testing cohort. The fine-tuned ResNet50 model based on transfer learning was adopted to classify WHO grade in the whole cohort and predict Ki-67 index, H3K27me3, and progesterone receptor (PR) status of grade 1 meningiomas. The predictive performance was evaluated by the accuracy and loss curve, confusion matrix, receiver operating characteristic curve (ROC), and area under curve (AUC). RESULTS: The DL prediction model for each label achieved high predictive performance in two cohorts. For WHO grade prediction, the area under the curve (AUC) was 0.966 (95%CI 0.957-0.975) in the internal testing set and 0.669 (95%CI 0.643-0.695) in the external validation cohort. The AUC in predicting Ki-67 index, H3K27me3, and PR status were 0.905 (95%CI 0.895-0.915), 0.773 (95%CI 0.760-0.786), and 0.771 (95%CI 0.750-0.792) in the internal testing set and 0.591 (95%CI 0.562-0.620), 0.658 (95%CI 0.648-0.668), and 0.703 (95%CI 0.674-0.732) in the external validation cohort, respectively. CONCLUSION: DL models can preoperatively predict meningioma grades and pathologic marker expression with favorable predictive performance. CLINICAL RELEVANCE STATEMENT: Our DL model could predict meningioma grades and expression of pathologic markers and identify high-risk patients with WHO grade 1 meningioma, which would suggest a more aggressive operative intervention preoperatively and a more frequent follow-up schedule postoperatively. KEY POINTS: WHO grades and some pathologic markers of meningioma were associated with therapeutic strategies and clinical outcomes. A deep learning-based approach was employed to develop a model for predicting meningioma grades and the expression of pathologic markers. Preoperative prediction of meningioma grades and the expression of pathologic markers was beneficial for clinical decision-making.

Identification of potential functional peptides involved in demyelinating injury in the central nervous system.

Multiple sclerosis (MS) is a chronic inflammatory neurologic disease characterized by the demyelinating injury of the central nervous system (CNS). It was reported that the mutant peptide came from myelin proteolipid protein (PLP) and myelin basic protein (MBP) might play a critical role in immunotherapy function of MS. However, endogenous peptides in demyelinating brain tissue of MS and their role in the pathologic process of MS have not been revealed. Here, we performed peptidomic analysis of freshly isolated corpus callosum (CC) from the brains of CPZ-treated mice and normal diet controls of male C57BL/6 mice by LC-MS/MS. Identified a total of 217 peptides were expressed at different levels in MS mice model compared with controls. By performed GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) analysis, we found that the precursor protein of these differently expressed peptides (DEPs) were associated with myelin sheath and oxidative phosphorylation. Our study is the first brain peptidomic of MS mice model, revealing the distinct features of DEPs in demyelination brain tissue. These DPEs may provide further insight into the pathogenesis and complexity of MS, which would facilitate the discovery of the potential novel and effective strategy for the treatment of MS.

Changed epidemiology of narcolepsy before, during, and after the 2009 H1N1 pandemic: a nationwide narcolepsy surveillance network study in mainland China, 1990-2017.

STUDY OBJECTIVES: Increased incidence of narcolepsy was reported in children during the 2009 H1N1 pandemic following Pandemrix, a H1N1 flu vaccine. A link with A(H1N1) pdm09 infections remains controversial. Using nationwide surveillance data from China (1990 to 2017), the epidemiology of narcolepsy was analyzed. METHODS: Individual records of narcolepsy patients were collected from 15 of 42 hospitals across China known to diagnose cases. Incidence was estimated assuming the representativeness of these hospitals. Age-specific incidence, epidemiological and clinical characteristics of patients were evaluated before, during, and after the 2009 H1N1 pandemic. Sensitivity analyses were conducted by including NT1 cases only and excluding the effect of the 2009 H1N1 vaccination. RESULTS: Average annual incidence was 0.79 per 100 000 person-years (PY) from 1990 to 2017 and 1.08 per 100 000 PY from 2003 to 2017. Incidence increased 4.17 (95% CI 4.12, 4.22) and 1.42 (95% CI 1.41, 1.44) fold during and after the 2009 H1N1 pandemic when compared to baseline. These results were robust in sensitivity analyses. Patients with the onset of narcolepsy during the pandemic period were younger (notably in 5-9-year-old strata), and the age shift toward younger children reversed to baseline following the pandemic. CONCLUSIONS: Increased incidence of narcolepsy was observed during the 2009 H1N1 pandemic period. This is likely to be associated with the circulation of the wild type A(H1N1)pdm09 virus. This observation should be considered for future influenza pandemic preparedness plans.

A novel method for extraction of platinum from spent automotive catalyst: utilization of spent fluid catalytic cracking catalyst as flux.

A novel method of smelting of mixture of spent automotive catalyst (SAC) and spent fluid catalytic cracking catalyst (SFCC) to recover platinum and prepare glass slag was investigated. Compared to other metals collection processes for single hazardous waste solid, this method reduced the amount of fluxing materials addition and increased the processing types of hazardous solid waste simultaneously. The optimum SFCC addition, iron collector addition, Na2B2O4•10H2O addition, CaO/SiO2 mass ratio, temperature, and holding time for platinum recovery were 20, 11, 16 wt%, 0.6, 1550-1600°C, and 60 min, respectively. In this proposed combined process, more than 98% of platinum is efficiently recovered from SAC. Meanwhile, the concentration of platinum in glass slag was less than 7 g/t. The leaching characteristics of heavy metals in slag confirmed the obtained glass slag is a non-hazardous slag due to the low leaching rate of heavy metal ions. This article proposed an effective and environmentally friendly method for the recovery of platinum from SAC via a combined smelting process.

Application of MRI-Based Radiomics in Preoperative Prediction of NF2 Alteration in Intracranial Meningiomas.

Purpose: This study aimed to investigate the feasibility of predicting NF2 mutation status based on the MR radiomic analysis in patients with intracranial meningioma. Methods: This retrospective study included 105 patients with meningiomas, including 60 NF2-mutant samples and 45 wild-type samples. Radiomic features were extracted from magnetic resonance imaging scans, including T1-weighted, T2-weighted, and contrast T1-weighted images. Student's t-test and LASSO regression were performed to select the radiomic features. All patients were randomly divided into training and validation cohorts in a 7:3 ratio. Five linear models (RF, SVM, LR, KNN, and xgboost) were trained to predict the NF2 mutational status. Receiver operating characteristic curve and precision-recall analyses were used to evaluate the model performance. Student's t-tests were then used to compare the posterior probabilities of NF2 mut/loss prediction for patients with different NF2 statuses. Results: Nine features had nonzero coefficients in the LASSO regression model. No significant differences was observed in the clinical features. Nine features showed significant differences in patients with different NF2 statuses. Among all machine learning algorithms, SVM showed the best performance. The area under curve and accuracy of the predictive model were 0.85; the F1-score of the precision-recall curve was 0.80. The model risk was assessed by plotting calibration curves. The p-value for the H-L goodness of fit test was 0.411 (p> 0.05), which indicated that the difference between the obtained model and the perfect model was statistically insignificant. The AUC of our model in external validation was 0.83. Conclusion: A combination of radiomic analysis and machine learning showed potential clinical utility in the prediction of preoperative NF2 status. These findings could aid in developing customized neurosurgery plans and meningioma management strategies before postoperative pathology.

Digital twin key technology on rare earth process.

Digital twin can be defined as a digital equivalent of an object of which it can mirror its behavior and status or virtual replicas of real physical entities in Cyberspace. To an extent, it also can simulate and predict the states of equipment or systems through smart algorithms and massive data. Hence, the digital twin is emerging used in intelligent manufacturing Systems in real-time and predicting system failure and also has introduced into a variety of traditional industries such as construction, Agriculture. Rare earth production is a typical process industry, and its Extraction Process enjoys the top priority in the industry. However, the extraction process is usually characterized by nonlinear behavior, large time delays, and strong coupling of various process variables. In case of failures happened in the process, the whole line would be shut down. Therefore, the digital twin is introduced into the design of process simulation to promote the efficiency and intelligent level of the Extraction Process. This paper proposes the techniques to build the rare earth digital twin such as soft measurement of component content, component content process simulation, control optimization strategy, and virtual workshop, etc. At the end, the validity of the model is verified, and a case study is conducted to verify the feasibility of the whole Digital twin framework.

LncRNA-IMAT1 Promotes Invasion of Meningiomas by Suppressing KLF4/hsa-miR22-3p/Snai1 Pathway.

Malignant meningiomas often show invasive growth that makes complete tumor resection challenging, and they are more prone to recur after radical resection. Invasive meningioma associated transcript 1 (IMAT1) is a long noncoding RNA located on Homo sapiens chromosome 17 that was identified by our team based on absolute expression differences in invasive and non-invasive meningiomas. Our studies indicated that IMAT1 was highly expressed in invasive meningiomas compared with non-invasive meningiomas. In vitro studies showed that IMAT1 promoted meningioma cell invasion through the inactivation of the Krüppel-like factor 4 (KLF4)/hsa-miR22-3p/Snai1 pathway by acting as a sponge for hsa-miR22-3p, and IMAT1 knockdown effectively restored the tumor suppressive properties of KLF4 by preserving its tumor suppressor pathway. In vivo experiments confirmed that IMAT1 silencing could significantly inhibit the growth of subcutaneous tumors and prolong the survival period of tumor-bearing mice. Our findings demonstrated that the high expression of IMAT1 is the inherent reason for the loss of the tumor suppressive properties of KLF4 during meningioma progression. Therefore, we believe that IMAT1 may be a potential biological marker and treatment target for meningiomas.

[A study to identify obstructive sleep apnea syndrome based on 24 h ambulatory blood pressure data].

Sleep apnea causes cardiac arrest, sleep rhythm disorders, nocturnal hypoxia and abnormal blood pressure fluctuations in patients, which eventually lead to nocturnal target organ damage in hypertensive patients. The incidence of obstructive sleep apnea hypopnea syndrome (OSAHS) is extremely high, which seriously affects the physical and mental health of patients. This study attempts to extract features associated with OSAHS from 24-hour ambulatory blood pressure data and identify OSAHS by machine learning models for the differential diagnosis of this disease. The study data were obtained from ambulatory blood pressure examination data of 339 patients collected in outpatient clinics of the Chinese PLA General Hospital from December 2018 to December 2019, including 115 patients with OSAHS diagnosed by polysomnography (PSG) and 224 patients with non-OSAHS. Based on the characteristics of clinical changes of blood pressure in OSAHS patients, feature extraction rules were defined and algorithms were developed to extract features, while logistic regression and lightGBM models were then used to classify and predict the disease. The results showed that the identification accuracy of the lightGBM model trained in this study was 80.0%, precision was 82.9%, recall was 72.5%, and the area under the working characteristic curve (AUC) of the subjects was 0.906. The defined ambulatory blood pressure features could be effectively used for identifying OSAHS. This study provides a new idea and method for OSAHS screening.

Adsorption mechanisms for cadmium from aqueous solutions by oxidant-modified biochar derived from Platanus orientalis Linn leaves.

To understand the adsorption mechanisms of Cd2+ by oxidant-modified biochar (OMB) derived from Platanus orientalis Linn (POL) leaves, batch adsorption experiments and characterization were carried out. The results showed that, KMnO4-modified biochar (MBC) could more effectively remove Cd2+ from aqueous solution than H2O-, H2O2-, and K2Cr2O7-modified biochar (WBC, HBC and PBC, respectively). The highest removal efficiency was 98.57%, which was achieved by the addition of 2 g L-1 MBC at pH 6.0. According to the Langmuir fitting parameters, the maximum adsorption capacity for MBC was 52.5 mg g-1 at 30 â„ƒ, which was twice as high as that for original biochar. MBC had the largest specific surface area with many particles distributed on the surface before and after adsorption, which were confirmed to be MnOx by XPS analysis. The complexation with MnOx was the main mechanism. Besides, O-containing groups complexation, precipitation, cation-π intraction, and ion exchange also participated in the adsorption. However, WBC, HBC and PBC did not achieve ideal removal effects, and their stability was inferior. This could be attributed to the weakening of ion exchange and precipitation. This study not only demonstrates the potential of MBC, but also provides insight into strategies for the utilization of waste resources.

TERT Alterations Predict Tumor Progression in De Novo High-Grade Meningiomas Following Adjuvant Radiotherapy.

BACKGROUND: Adjuvant radiotherapy (RT) is one of the most commonly used treatments for de novo high-grade meningiomas (HGMs) after surgery, but genetic determinants of clinical benefit are poorly characterized. OBJECTIVE: We describe efforts to integrate clinical genomics to discover predictive biomarkers that would inform adjuvant treatment decisions in de novo HGMs. METHODS: We undertook a retrospective analysis of 37 patients with de novo HGMs following RT. Clinical hybrid capture-based sequencing assay covering 184 genes was performed in all cases. Associations between tumor clinical/genomic characteristics and RT response were assessed. Overall survival (OS) and progression-free survival (PFS) curves were plotted using the Kaplan-Meier method. RESULTS: Among the 172 HGMs from a single institution, 42 cases (37 WHO grade 2 meningiomas and five WHO grade 3 meningiomas) were identified as de novo HGMs following RT. Only TERT mutations [62.5% C228T; 25% C250T; 12.5% copy number amplification (CN amp.)] were significantly associated with tumor progression after postoperative RT (adjusted p = 0.003). Potential different somatic interactions between TERT and other tested genes were not identified. Furthermore, TERT alterations (TERT-alt) were the predictor of tumor progression (Fisher's exact tests, p = 0.003) and were associated with decreased PFS (log-rank test, p = 0.0114) in de novo HGMs after RT. CONCLUSION: Our findings suggest that TERT-alt is associated with tumor progression and poor outcome of newly diagnosed HGM patients after postoperative RT.

Recovery of nickel and preparation of ferronickel alloy from spent petroleum catalyst via cooperative smelting-vitrification process with coal fly ash.

Spent petroleum catalyst (SPC) is a highly toxic material since it contains heavy metals and hazardous substances. A novel recycling technology based on the cooperative smelting-vitrification process by using coal fly ash (CFA) as a fluxing material was proposed. The benefits of employing CFA in this cooperative smelting-vitrification process of SPC have been demonstrated via the results of lab-scale and scale-up experiments. The experimental results indicated that with a collector iron (Fe) addition of 26 wt%, a C/O molar ration of 1.4, and an H3BO3 addition of 14 wt%, the maximum nickel (Ni) recovery was ∼98% by controlling the CFA addition of 40-50 wt%, basicity of 0.4-0.5, smelting temperature of 1550°C, and smelting time of 60 min, respectively. In this process, a ferronickel (Ni-Fe) alloy with a high Ni grade of 10 wt% was successfully obtained, which could be directly further produced stainless steel. Meanwhile, a glass slag with a low Ni content (below 0.12 wt%) was also obtained, and its leaching characteristics further confirmed it is a non-hazardous slag because heavy metals were successfully encapsulated in glass slag, and thereby, this proposed method achieved the transformation from hazardous solid waste to general solid waste. The results of the 10 kg scale-up experiment indicated the possibility of industrialization of this new technology. Therefore, the process proposed in this study is a practical and promising process for Ni recovery from SPC and reutilization of CFA.

m6A Regulator Expression Segregates Meningiomas Into Biologically Distinct Subtypes.

BACKGROUND: Meningiomas are the most common primary intracranial tumors in adults. According to the 2021 World Health Organization (WHO) classification of central nervous system tumors, approximately 80% of meningiomas are WHO grade 1, that is, histopathologically benign, whereas about 20% are WHO grade 2 or grade 3, showing signs of atypia or malignancy. The dysregulation of N6-methylation (m6A) regulators is associated with disorders of diverse critical biological processes in human cancer. This study aimed to explore whether m6A regulator expression was associated with meningioma molecular subtypes and immune infiltration. METHODS: We evaluated the m6A modification patterns of 160 meningioma samples based on 19 m6A regulators and correlated them with immune infiltration characteristics. Novel molecular subtypes were defined based on prognostic hub gene expression. RESULTS: Two meningioma clusters were identified based on the expression of 19 m6A regulators. In cluster 1, 607 differentially expressed genes (DEGs) were upregulated and 519 were downregulated. A total of 1,126 DEGs comprised three gene expression modules characterized by turquoise, blue, and gray. Functional annotation suggested that the turquoise module was involved in Wnt-related and other important cancer-related pathways. We identified 32 hub genes in this module by constructing a protein-protein interaction network. The meningioma samples were divided into two molecular subtypes. EPN1, EXOSC4, H2AX, and MZT2B not only showed significant differences between meningioma molecular subtypes but also had the potential to be the marker genes of specific meningioma subtypes. CONCLUSION: m6A regulator gene expression may be a novel prognostic marker in meningioma.

Metals smelting-collection method for recycling of platinum group metals from waste catalysts: A mini review.

Platinum group metals (PGMs) are widely applied in the field of catalysts due to their excellent catalyst activity and high-temperature stability. The rapid generation of the waste catalyst has become the significant characteristic of PGMs with the accelerating consumption of limited PGMs nature resources. It is necessary to recover/recycle PGMs from a waste catalyst for both economic and environmental benefits. This paper reviews the PGMs recovery from waste catalysts using a metals smelting-collection process, which belongs to the main pyrometallurgical process, in the presence of various metal collectors, such as lead, copper, iron, matte, print circuit board (PCB) or reactive metals of calcium and magnesium. The current status of recovery of PGMs from waste catalysts through the addition of various metals as the collector is discussed and existing advantages and challenges are highlighted in this paper. Meanwhile, in the view of the promising processes of PGMs recovery, the influencing factors such as the economic, environmentally friendly, sustainable recycling, commercial scale, and low-grade materials are considered.

Prognostic Model That Predicts Benefits of Adjuvant Radiotherapy in Patients With High Grade Meningioma.

OBJECTIVE: Adjuvant radiotherapy is the main treatment modality for high grade meningioma after surgical resection; however, recurrence and survival outcomes vary. The aim of this study was to create a new "prognostic score" that allows personalized recommendations for post-operative adjuvant radiotherapy in patients with high grade meningioma. METHODS: Clinical data were collected from 115 patients with high grade meningioma treated with surgical resection and adjuvant radiotherapy. A prognostic model was built based on the hazards ratios of independent prognostic factors yielded by multivariate cox proportional analysis. Calibration and discrimination of the prognostic score was evaluated using good of fit test and Harrel's C index, respectively. RESULTS: A total of 115 high grade meningioma patients (72 atypical and 43 anaplastic meningiomas) were enrolled. Three factors were independently associated with progression-free survival (PFS): extent of resection (GTR vs. STR), recurrent status (de novo vs. recurrent), and Ki-67 labeling index (<5% vs. ≥ 5%). The respective ß-coefficients were used to generate the "prognostic score". The cohort was divided into low-risk and high-risk groups based on the median prognostic score. Good of fit test showed strong calibration (P = 0.7133) and Harrel's C index 0.766 indicated a strong discrimination capability of the prognostic score. The Harrel's C index for OS was 0.60. CONCLUSIONS: Our prognostic model using three basic clinical parameters robustly separated high grade meningioma patients who benefit vs. do not benefit from adjuvant radiotherapy. External validation of our model is warranted to help improve patient selection suitable for adjuvant radiotherapy.

High Tumor Mitochondrial DNA Content Correlates With an Improved Patient's Outcome in WHO Grade III Meningioma.

Background: Studies have shown mitochondrial genome content (mtDNA content) varies in many malignancies. However, its distribution and prognostic values in high-grade meningioma remain largely unknown. In this retrospective study, we sought to assess a putative correlation between the mtDNA content and clinical characteristics. Methods: Mitochondrial DNA was extracted from 87 World Health Organization grade III meningioma samples using a qPCR method. The distribution of mtDNA content in WHO grade III meningioma and its correlations with clinical variables were assessed. Furthermore, we prognostic values were also determined. Results: Mean mtDNA content was 617.7 (range, 0.8-3000). There was no mtDNA distribution difference based on the histological subtypes (P = 0.07). Tumors with preoperative radiation were associated with lower mtDNA content (P = 0.041), whereas no correlations with other clinical variables were observed. A high mtDNA content was associated with significantly better PFS (P = 0.044) and OS (P = 0.019). However, in patients who received postoperative radiotherapy, low mtDNA content was associated with better PFS (P = 0.028), while no difference in OS was observed (P = 0.272). Low mtDNA content was also associated with better OS and PFS in subgroups of patients with ER negative status (PFS, P = 0.002; OS, P = 0.002). Conclusions: Consistent with other tumors, high mtDNA content was associated with better outcome in WHO grade III meningioma in our cohort. However, for patients who received post-operative radiation therapy, low mtDNA content was associated with better PFS. These findings suggest that mtDNA content may further be explored as a potential biomarker for high-grade meningioma patients and for those who received postoperative radiation therapy.

The CREB-binding protein inhibitor ICG-001: a promising therapeutic strategy in sporadic meningioma with NF2 mutations.

BACKGROUND: Meningiomas with Neurofibromin 2 gene mutations (NF2-mutant meningiomas) account for ~40% of the sporadic meningiomas. However, there is still no effective drug treatment for the disease. METHODS: Expression profile of Merlin protein was explored through immunohistochemistry in a meningioma patient cohort (n = 346). A 20-agent library covering a wide range of meningioma relevant targets was tested using meningioma cell lines IOMM-Lee (NF2 wildtype) and CH157-MN (NF2 deficient). Therapeutic effects and biological mechanisms of the identified compound, ICG-001, in NF2-mutant meningiomas were further characterized in vitro and in patient-derived xenograft (PDX) models. RESULTS: Low Merlin expression was associated with meningioma proliferation and poor clinical outcomes in a large patient series. ICG-001, a cAMP-responsive element binding (CREB)-binding protein (CBP) inhibitor, selectively suppressed tumor growth of cells with low Merlin expression. Besides, ICG-001 mediated CH157-MN and IOMM-Lee growth inhibition primarily through robust induction of the G1 cell-cycle arrest. Treatment with ICG-001 alone significantly reduced the growth of NF2-mutant xenografts in mice, as well. We also provide further evidence that ICG-001 inhibits proliferation of NF2-mutant meningioma cells at least partly through attenuating the FOXM1-mediated Wnt/ß-catenin signaling. CONCLUSIONS: This study highlights the importance of ligand-mediated Wnt/ß-catenin signaling as well as its drugable potency in NF2-mutant meningioma.

Long-term outcomes of multimodality management for parasagittal meningiomas.

PURPOSE: The aim of this study was to systematically analyze the clinical characteristics of a large cohort of parasagittal meningioma (PM) and to evaluate the patients' outcomes and best treatment strategies based on tumor features. METHODS: To minimize selection bias we performed a single-institutional review of PM with restricted criteria. One hundred and ninety-two consecutive patients who met criteria for inclusion were reviewed from 2003 to 2011 in our general hospital. RESULTS: A total of 131 cases (68.2%) were with WHO grade I, while grade II and grade III PMs constituted 40 (20.8%) and 21 cases (10.9%). Higher histological grade was associated with loss of trimethylation of H3K27 (P = 0.000). For WHO grade I PMs, GTR was significantly associated with a better PFS (P = 0.023); however, adjuvant radiotherapy did not benefit patients with STR (P = 0.215). For de novo high-grade (WHO grade II and III) PMs (n = 37), adjuvant radiotherapy was associated with a significantly longer OS (P = 0.013), while no difference was observed between GTR and STR (P = 0.654). In recurrent high-grade PM patients (n = 24), GTR combined with adjuvant radiotherapy increased PFS (P = 0.005). CONCLUSIONS: This study demonstrated that PMs were a heterogeneous group of tumors with a high proportion of high-grade tumors that often displayed aggressive clinical behaviors. Low-grade PM benefited from radical resection, whereas high-grade de novo PM did not. Adjuvant radiotherapy significantly prolonged OS for high-grade primary PM, but did not impact survival of patients with subtotally resected low-grade tumors. Long-term outcome of high-grade recurrent PMs was dismal. We thus show that extent of tumor resection, tumor grade and tumor recurrent status inform therapeutic decisions for PMs.

Enhancing Photodynamic Therapy Efficacy of Upconversion-Based Nanoparticles Conjugated with a Long-Lived Triplet Excited State Iridium(III)-Naphthalimide Complex: Toward Highly Enhanced Hypoxia-Inducible Factor-1.

Metal-based photosensitizers are of great interest in photodynamic therapy (PDT) due to their tunable photophysicochemical characteristics and structure flexibility. Herein, an iridium-based photosensitizer (1) with a long-lived intraligand (3IL) excited state has been designed and synthesized, which shows significantly enhanced singlet oxygen (1O2) generation efficiency (∼45 folds) relative to that of the model iridium(III) complex (2) under 460 nm irradiation. In order to achieve deep tissue penetration, complex 1 was further covalently bonded to the upconversion nanoparticles (UCNPs). Besides, 1-benzyl-3-(5'-hydroxymethyl-2'-furyl)indazole (YC-1), an effective HIF-1α inhibitor, was physically adsorbed into the hydrophobic layer at the surface of UCNPs. Once upon near-infrared (NIR) irradiation, iridium complex 1-mediated toxic 1O2 was generated for PDT, whose efficient conversion of oxygen to 1O2 during the PDT would exacerbate the hypoxic condition of tumor tissue and lead to the upregulation of HIF-1α for the following HIF-1 targeting tumor therapy. This study highlights the potential for applying a nanoplatform composed of a long-lived iridium-based photosensitizer and an HIF-1α inhibitor in tumor therapy, which converts PDT-induced tumor hypoxia to a therapy advantage, thus opening up ideas to overcome the hypoxia in PDT therapy.