Rapid detection of IDH mutations in gliomas by intraoperative mass spectrometry.

The development and performance of two mass spectrometry (MS) workflows for the intraoperative diagnosis of isocitrate dehydrogenase (IDH) mutations in glioma is implemented by independent teams at Mayo Clinic, Jacksonville, and Huashan Hospital, Shanghai. The infiltrative nature of gliomas makes rapid diagnosis necessary to guide the extent of surgical resection of central nervous system (CNS) tumors. The combination of tissue biopsy and MS analysis used here satisfies this requirement. The key feature of both described methods is the use of tandem MS to measure the oncometabolite 2-hydroxyglutarate (2HG) relative to endogenous glutamate (Glu) to characterize the presence of mutant tumor. The experiments i) provide IDH mutation status for individual patients and ii) demonstrate a strong correlation of 2HG signals with tumor infiltration. The measured ratio of 2HG to Glu correlates with IDH-mutant (IDH-mut) glioma (P < 0.0001) in the tumor core data of both teams. Despite using different ionization methods and different mass spectrometers, comparable performance in determining IDH mutations from core tumor biopsies was achieved with sensitivities, specificities, and accuracies all at 100%. None of the 31 patients at Mayo Clinic or the 74 patients at Huashan Hospital were misclassified when analyzing tumor core biopsies. Robustness of the methodology was evaluated by postoperative re-examination of samples. Both teams noted the presence of high concentrations of 2HG at surgical margins, supporting future use of intraoperative MS to monitor for clean surgical margins. The power of MS diagnostics is shown in resolving contradictory clinical features, e.g., in distinguishing gliosis from IDH-mut glioma.

Use of Bevacizumab in recurrent glioblastoma: a scoping review and evidence map.

BACKGROUND: Glioblastoma (GBM) is the most malignant primary tumor in the brain, with poor prognosis and limited effective therapies. Although Bevacizumab (BEV) has shown promise in extending progression-free survival (PFS) treating GBM, there is no evidence for its ability to prolong overall survival (OS). Given the uncertainty surrounding BEV treatment strategies, we aimed to provide an evidence map associated with BEV therapy for recurrent GBM (rGBM). METHODS: PubMed, Embase, and the Cochrane Library were searched for the period from January 1, 1970, to March 1, 2022, for studies reporting the prognoses of patients with rGBM receiving BEV. The primary endpoints were overall survival (OS) and quality of life (QoL). The secondary endpoints were PFS, steroid use reduction, and risk of adverse effects. A scoping review and an evidence map were conducted to explore the optimal BEV treatment (including combination regimen, dosage, and window of opportunity). RESULTS: Patients with rGBM could gain benefits in PFS, palliative, and cognitive advantages from BEV treatment, although the OS benefits could not be verified with high-quality evidence. Furthermore, BEV combined therapy (especially with lomustine and radiotherapy) showed higher efficacy than BEV monotherapy in the survival of patients with rGBM. Specific molecular alterations (IDH mutation status) and clinical features (large tumor burden and double-positive sign) could predict better responses to BEV administration. A low dosage of BEV showed equal efficacy to the recommended dose, but the optimal opportunity window for BEV administration remains unclear. CONCLUSIONS: Although OS benefits from BEV-containing regimens could not be verified in this scoping review, the PFS benefits and side effects control supported BEV application in rGBM. Combining BEV with novel treatments like tumor-treating field (TTF) and administration at first recurrence may optimize the therapeutic efficacy. rGBM with a low apparent diffusion coefficient (ADCL), large tumor burden, or IDH mutation is more likely to benefit from BEV treatment. High-quality studies are warranted to explore the combination modality and identify BEV-response subpopulations to maximize benefits.

Cell Cycle-Related FAM64A Could be Activated by TGF-ß Signaling to Promote Glioma Progression.

Gliomas are aggressive brain tumors characterized by uncontrolled cell proliferation. FAM64A, a cell cycle-related gene, has been found to promote cell proliferation in various tumors, including gliomas. However, the regulatory mechanism and clinical significance of FAM64A in gliomas remain unclear. In this study, we investigated FAM64A expression in gliomas with different grades and constructed FAM64A silenced cell lines to study its functions. Our results demonstrated that FAM64A was highly expressed in glioblastoma (P < 0.001) and associated with a poor prognosis (P < 0.001). Expression profiles at the single-cell resolution indicated FAM64A could play a role in a cell-cycle-dependent way to promote glioma cell proliferation. We further observed that FAM64A silencing in glioma cells resulted in disrupted proliferation and migration ability, and increased cell accumulation in the G2/M phase (P = 0.034). Additionally, TGF-ß signaling upregulates FAM64A expression, and SMAD4 and FAM64A co-localize in high-grade glioma tissues. We found FAM64A knockdown inhibited TGF-ß-induced epithelial-mesenchymal transition in glioma. Our findings suggest that FAM64A could serve as a diagnostic and therapeutic target in gliomas.

A new approach to optimizing aeration using XGB-Bi-LSTM via the online monitoring of oxygen transfer efficiency and oxygen uptake rate.

In wastewater treatment plants (WWTPs), aeration is vital for microbial oxygen needs. To achieve carbon neutrality, optimizing aeration for energy and emissions reduction is imperative. Machine learning (ML) is used in wastewater treatment to reveal complex rules in large data sets has become a trend. In this vein, the present paper proposes an aeration optimization approach based on the extreme gradient boosting-bidirectional long short-term memory (XGB-Bi-LSTM) model via the online monitoring of oxygen transfer efficiency (OTE) and oxygen uptake rate (OUR), thus allowing WWTPs to conserve energy and reduce indirect carbon emissions. The approach uses gain algorithm of XGB to calculate the importance of features and identify important parameters, and then uses Bi-LSTM to predict the target with important parameters as features. Operational data from a WWTP in Suzhou, China, is employed to train and test the approach, the performance of which is compared with ML models suitable for regression prediction tasks (XGB, random forest, light gradient boosting machine, gradient boosting and LSTM). Experimental results show the approach requires only a small number of input parameters to achieve good performance and outperforms other machine-learning models. When OTE and dissolved oxygen (DO) are used as features to predict the alpha factor (αF; since diffusers were used, multiply by the pollution factor F), the R-squared (R2) is 0.9977, the root mean square error (RMSE) is 0.0043, the mean absolute percentage error (MAPE) is 0.0069 and the median absolute error (MedAE) is 0.0032. When the predicted αF and the OUR are used as features to predict the air flow rate of an aeration unit, the R2 is 0.9901, the RMSE is 3.6150, the MAPE is 0.0209 and the MedAE is 1.5472. Using our optimized aeration approach, the energy consumption can be reduced by 23%.

Optimization on structure and operation parameters of biofilter for decentralized sewage treatment.

Aiming for treating decentralized domestic wastewater in rural China, this study evaluates the effects of ceramsite size and structure, and water recirculation parameters, upon the performance of recirculating biofilter (RBF). RBF shows stable capability of chemical oxygen demand (COD) remediation and ammonia nitrification. In addition, the microbial flora and structures of the various layers in the system are analyzed via high-throughput sequencing in order to study the microbial diversity. The results indicate that while the ceramic particle size has no significant influence on the COD remediation capacity, the ceramics with smaller particle sizes exhibit better ammonia nitrogen (NH4+-N) removal ability, with a first-order linear relationship between the influent ammonia nitrogen load and the effluent NH4+-N concentration in RBF (R2 > 0.64). An increased hydraulic load and intermittent operation are shown to deteriorate the water quality with respect to NH4+-N, while an increased recirculation ratio increases the removal rate of NH4+-N from the effluent. Further, the water distribution time has a stronger effect upon the NH4+-N concentration in the effluent than does the recirculation ratio. Moreover, the microbial structure of the multi-layer recirculating trickle biofilter varies significantly during the process. The results indicate that a high recirculation ratio, long water distribution time, and multi-layer structure will be beneficial for improving the pollutant treatment capacity of RBF.

Gene clusters based on OLIG2 and CD276 could distinguish molecular profiling in glioblastoma.

BACKGROUND: The molecular profiling of glioblastoma (GBM) based on transcriptomic analysis could provide precise treatment and prognosis. However, current subtyping (classic, mesenchymal, neural, proneural) is time-consuming and cost-intensive hindering its clinical application. A simple and efficient method for classification was imperative. METHODS: In this study, to simplify GBM subtyping more efficiently, we applied a random forest algorithm to conduct 26 genes as a cluster featured with hub genes, OLIG2 and CD276. Functional enrichment analysis and Protein-protein interaction were performed using the genes in this gene cluster. The classification efficiency of the gene cluster was validated by WGCNA and LASSO algorithms, and tested in GSE84010 and Gravandeel's GBM datasets. RESULTS: The gene cluster (n = 26) could distinguish mesenchymal and proneural excellently (AUC = 0.92), which could be validated by multiple algorithms (WGCNA, LASSO) and datasets (GSE84010 and Gravandeel's GBM dataset). The gene cluster could be functionally enriched in DNA elements and T cell associated pathways. Additionally, five genes in the signature could predict the prognosis well (p = 0.0051 for training cohort, p = 0.065 for test cohort). CONCLUSIONS: Our study proved the accuracy and efficiency of random forest classifier for GBM subtyping, which could provide a convenient and efficient method for subtyping Proneural and Mesenchymal GBM.

The diagnostic value of lower glucose consumption for IDH1 mutated gliomas on FDG-PET.

BACKGROUND: Non-invasive diagnosis of IDH1 mutation for gliomas has great clinical significance, and PET has natural advantage to detect metabolism, as IDH mutated gliomas share lower glucose consumption. METHODS: Clinical data of patients with gliomas and 18F-FDG PET were retrospectively reviewed. Receiver operating characteristic curve (ROC) analysis was conducted, and standard uptake value (SUV) was estimated in combination with grades or IDH1 mutation. The glucose consumption was investigated with U251 cells expressing wild-type or mutated IDH1 by glucose assay. Quantification of glucose was determined by HPLC in clinical tissues. Meanwhile, bioinformatics and western blot were applied to analyze the expression level of metabolic enzymes (e.g. HK1, PKM2, PC) in gliomas. RESULTS: Seventy-one glioma cases were enrolled, including 30 carrying IDH1 mutation. The sensitivity and specificity dependent on SUVmax (3.85) predicting IDH1 mutation reached 73.2 and 86.7%, respectively. The sensitivity and specificity of differentiating grades by SUVmax (3.1) were 92.3 and 64.4%, respectively. Glucose consumption of U251 IDH1 mutant cells (0.209 ± 0.0472 mg/ml) was obviously lower than IDH1wild-type cells (0.978 ± 0.0773 mg/ml, P = 0.0001) and astrocyte controls (0.335 ± 0.0592 mg/ml, P = 0.0451). Meanwhile, the glucose quantity in IDH1mutant glioma samples were significantly lower than those in IDH1 wild-type tissues (1.033 ± 1.19608 vs 6.361 ± 4.3909 mg/g, P = 0.0051). Silico analysis and western blot confirmed that HK1 and PKM2 in IDH1 wild-type gliomas were significantly higher than in IDH1 mutant group, while PC was significantly higher in IDH1 mutant gliomas. CONCLUSION: SUVmax on PET can predict IDH1 mutation with adequate sensitivity and specificity, as is supported by reduced glucose consumption in IDH1 mutant gliomas.

B7H3 regulates differentiation and serves as a potential biomarker and theranostic target for human glioblastoma.

B7H3 (CD276), a co-stimulator molecule of the cell surface B7 protein superfamily, is expressed on glioblastomas (GBM). Recently, B7H3 functions beyond immune costimulation have been demonstrated. However, the mechanisms underlying B7H3 function are diverse and not well understood. GBM tumors contain undifferentiated self-renewing cells, which confound therapeutic attempts. We investigated the role of B7H3 in the regulation of GBM cell differentiation and the regulatory pathways involved. Analysis of public databases (TCGA, Rembrandt, and GEO NCBI) and RNA sequencing were performed to explore the role of B7H3 in GBM. Knockdown and overexpression of B7H3, were used to verify the downstream pathway in vitro. Further studies in vivo were performed to support the new finding. Bioinformatics analysis identified a correlation between the expression of B7H3, the expression of glioma self-renewing cell (GSC)-related genes, and MYC expression. These observations were verified by RNA-sequencing analyses in primary GBM cell lines. In vitro knockdown of B7H3-induced differentiation, associated with downregulation of SMAD6 (a TGF-ß pathway inhibitor) and enhancement of SMAD1 phosphorylation-induced SMAD4 expression. Importantly, activation of the TGF-ß pathway resulted in downregulation of MYC expression. In vivo assays conducted in a human GBM cell line xenograft mouse model demonstrated that B7H3 knockdown decreased MYC expression and inhibited tumor growth. B7H3 knockdown could regulate GBM differentiation by modulating MYC expression. So, B7H3 could serve as a potential theranostic target for the treatment of patients with GBM.

Prediction of Novel Trigonal Chloride Superionic Conductors as Promising Solid Electrolytes for All-Solid-State Lithium Batteries.

Recently emerging lithium ternary chlorides have attracted increasing attention for solid-state electrolytes (SSEs) due to their favorable combination between ionic conductivity and electrochemical stability. However, a noticeable discrepancy in Li-ion conductivity persists between chloride SSEs and organic liquid electrolytes, underscoring the need for designing novel chloride SSEs with enhanced Li-ion conductivity. Herein, an intriguing trigonal structure (i.e., Li3SmCl6 with space group P3112) is identified using the global structure searching method in conjunction with first-principles calculations, and its potential for SSEs is systematically evaluated. Importantly, the structure of Li3SmCl6 exhibits a high ionic conductivity of 15.46 mS cm-1 at room temperature due to the 3D lithium percolation framework distinct from previous proposals, associated with the unique in-plane cation ordering and stacking sequences. Furthermore, it is unveiled that Li3SmCl6 possesses a wide electrochemical window of 0.73-4.30 V vs Li+/Li and excellent chemical interface stability with high-voltage cathodes. Several other Li3MCl6 (M = Er, and In) materials with isomorphic structures to Li3SmCl6 are also found to be potential chloride SSEs, suggesting the broader applicability of this structure. This work reveals a new class of ternary chloride SSEs and sheds light on strategy for structure searching in the design of high-performance SSEs.

Exploratory study on the metabolic similarity of denitrifying carbon sources.

Mixed carbon sources have been developed for denitrification to eliminate the "carbon dependency" problem of single carbon. The metabolic correlation between different carbon sources is significant as guidance for the development of novel mixed carbon sources. In this study, to explore the metabolic similarity of denitrifying carbon sources, we selected alcohols (methanol, ethanol, and glycerol) and saccharide carbon sources (glucose, sucrose, and starch). Batch denitrification experiments revealed that methanol-acclimated sludge improved the denitrification rate of both methanol (14.42 mg-N/gMLVSS*h) and ethanol (9.65 mg-N/gMLVSS*h), whereas ethanol-acclimated sludge improved the denitrification rate of both methanol (7.80 mg-N/gMLVSS*h) and ethanol (22.23 mg-N/gMLVSS*h). In addition, the glucose-acclimated sludge and sucrose-acclimated sludge possibly improved the denitrification rate of glucose and sucrose, and the glycerol-acclimated sludge improved the denitrification rate of volatile fatty acids (VFAs), alcohols, and saccharide carbon sources. Functional gene analysis revealed that methanol, ethanol, and glycerol exhibited active alcohol oxidation and glyoxylate metabolism, and glycerol, glucose, and sucrose exhibited active glycolysis metabolism. This indicated that the similarity in the denitrification metabolism of these carbon sources was based on functional gene similarity, and glycerol-acclimated sludge exhibited the most diverse metabolism, which ensured its good denitrification effect with other carbon sources.