Computational Pathology for Prediction of Isocitrate Dehydrogenase Gene Mutation from Whole Slide Images in Adult Patients with Diffuse Glioma.

Isocitrate dehydrogenase gene (IDH) mutation is one of the most important molecular markers of glioma. Accurate detection of IDH status is a crucial step for integrated diagnosis of adult-type diffuse gliomas. Herein, a clustering-based hybrid of a convolutional neural network and a vision transformer deep learning model was developed to detect IDH mutation status from annotation-free hematoxylin and eosin-stained whole slide pathologic images of 2275 adult patients with diffuse gliomas. For comparison, a pure convolutional neural network, a pure vision transformer, and a classic multiple-instance learning model were also assessed. The hybrid model achieved an area under the receiver operating characteristic curve of 0.973 in the validation set and 0.953 in the external test set, outperforming the other models. The hybrid model's ability in IDH detection between difficult subgroups with different IDH status but shared histologic features, achieving areas under the receiver operating characteristic curve ranging from 0.850 to 0.985 in validation and test sets. These data suggest that the proposed hybrid model has a potential to be used as a computational pathology tool for preliminary rapid detection of IDH mutation from whole slide images in adult patients with diffuse gliomas.

Writers, readers, and erasers RNA modifications and drug resistance in cancer.

Drug resistance in cancer cells significantly diminishes treatment efficacy, leading to recurrence and metastasis. A critical factor contributing to this resistance is the epigenetic alteration of gene expression via RNA modifications, such as N6-methyladenosine (m6A), N1-methyladenosine (m1A), 5-methylcytosine (m5C), 7-methylguanosine (m7G), pseudouridine (Ψ), and adenosine-to-inosine (A-to-I) editing. These modifications are pivotal in regulating RNA splicing, translation, transport, degradation, and stability. Governed by "writers," "readers," and "erasers," RNA modifications impact numerous biological processes and cancer progression, including cell proliferation, stemness, autophagy, invasion, and apoptosis. Aberrant RNA modifications can lead to drug resistance and adverse outcomes in various cancers. Thus, targeting RNA modification regulators offers a promising strategy for overcoming drug resistance and enhancing treatment efficacy. This review consolidates recent research on the role of prevalent RNA modifications in cancer drug resistance, with a focus on m6A, m1A, m5C, m7G, Ψ, and A-to-I editing. Additionally, it examines the regulatory mechanisms of RNA modifications linked to drug resistance in cancer and underscores the existing limitations in this field.

Radiomic profiling for insular diffuse glioma stratification with distinct biologic pathway activities.

Current literature emphasizes surgical complexities and customized resection for managing insular gliomas; however, radiogenomic investigations into prognostic radiomic traits remain limited. We aimed to develop and validate a radiomic model using multiparametric magnetic resonance imaging (MRI) for prognostic prediction and to reveal the underlying biological mechanisms. Radiomic features from preoperative MRI were utilized to develop and validate a radiomic risk signature (RRS) for insular gliomas, validated through paired MRI and RNA-seq data (N = 39), to identify core pathways underlying the RRS and individual prognostic radiomic features. An 18-feature-based RRS was established for overall survival (OS) prediction. Gene set enrichment analysis (GSEA) and weighted gene coexpression network analysis (WGCNA) were used to identify intersectional pathways. In total, 364 patients with insular gliomas (training set, N = 295; validation set, N = 69) were enrolled. RRS was significantly associated with insular glioma OS (log-rank p = 0.00058; HR = 3.595, 95% CI:1.636-7.898) in the validation set. The radiomic-pathological-clinical model (R-P-CM) displayed enhanced reliability and accuracy in prognostic prediction. The radiogenomic analysis revealed 322 intersectional pathways through GSEA and WGCNA fusion; 13 prognostic radiomic features were significantly correlated with these intersectional pathways. The RRS demonstrated independent predictive value for insular glioma prognosis compared with established clinical and pathological profiles. The biological basis for prognostic radiomic indicators includes immune, proliferative, migratory, metabolic, and cellular biological function-related pathways.

Physiologically based pharmacokinetic modeling for confirming the role of CYP3A1/2 and P-glycoprotein in detoxification mechanism between glycyrrhizic acid and aconitine in rats.

Fuzi, an effective common herb, is often combined with Gancao to treat disease in clinical practice with enhancing its efficacy and alleviating its toxicity. The major toxic and bioactive compounds in Fuzi and Gancao are aconitine (AC) and glycyrrhizic acid (GL), respectively. This study aims to elucidate detoxification mechanism between AC and GL from pharmacokinetic perspective using physiologically based pharmacokinetic (PBPK) model. In vitro experiments exhibited that AC was mainly metabolized by CYP3A1/2 in rat liver microsomes and transported by P-glycoprotein (P-gp) in Caco-2 cells. Kinetics assays showed that the Km and Vmax of AC towards CYP3A1/2 were 2.38 µM and 57.3 pmol/min/mg, respectively, whereas that of AC towards P-gp was 11.26 µM and 147.1 pmol/min/mg, respectively. GL markedly induced the mRNA expressions of CYP3A1/2 and MDR1a/b in rat primary hepatocytes. In vivo studies suggested that the intragastric and intravenous administration of GL significantly reduced systemic exposure of AC by 27% and 33%, respectively. Drug-drug interaction (DDI) model of PBPK predicted that co-administration of GL would decrease the exposure of AC by 39% and 45% in intragastric and intravenous dosing group, respectively. The consistency between predicted data and observed data confirmed that the upregulation of CYP3A1/2 and P-gp was the crucial detoxification mechanism between AC and GL. Thus, this study provides a demonstration for elucidating the compatibility mechanisms of herbal formula using PBPK modeling and gives support for the clinical co-medication of Fuzi and Gancao.

Development and validation of a liquid chromatography-tandem mass spectrometry method for simultaneous quantification of eight Xiakucao Oral liquid-related compounds in rat plasma and its application in pharmacokinetic study.

Xiakucao Oral Liquid (XKCOL) has been widely used for treating mammary gland hyperplasia and goiter in China. However, its pharmacokinetic data have been missing to date. To conduct its pharmacokinetic study, we established an LC-tandem mass spectrometry method for the simultaneous determination of eight XKCOL-related compounds in rat plasma. Liquid-liquid extraction was used for the sampling process. Chromatographic separation was performed on a Phenomenon Luna C18 column with a mobile phase of methanol and 2 mM ammonium acetate, using gradient elution at a flow rate of 0.8 mL/min. Detection was performed in the multiple reaction monitoring mode using negative electrospray ionization (ESI-) with optimized MS parameters. Endogenous substances and carryover did not interfere in the detection of analytes. The calibration curves showed a good linear relationship within the linear ranges. The intra- and inter-batch accuracy and precision were 94.8%-110.0% and ≤11.2%, respectively. There was no significant matrix effect and the recovery was reproducible. The dilution of samples did not affect the accuracy and precision. The solution and plasma samples were stable under the various test conditions. The major components of XKCOL absorbed into the blood were salvianic acid A and rosmarinic acid. They demonstrated linear kinetics over the dose range used in this study.

Low expression of GRM4 is associated with poor prognosis and tumor immune infiltration in glioma.

INTRODUCTION: The metabotropic glutamate receptor 4 (mGlu4, GRM4) exhibits significant expression within the central nervous system (CNS) and has been implicated to be correlated with a poor prognosis. OBJECTIVE: This study was aimed to elucidate the relationship between the expression profile of GRM4 and the prognosis of glioma patients. METHODS: RNA-sequencing datasets from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and China Glioma Genome Atlas (CGGA) repositories were used to evaluate the potential relationship. The value of clinical prognostic about GRM4 was assessed using clinical survival data from CGGA and TCGA. The GEPIA database was used to select genes like GRM4. PPI network was constructed by the database of (STRING), GO and KEGG analyses were performed. TargetScan, TarBase, miRDB, and starBase were used to explore miRNAs that could regulate GRM4 expression. EWAS Data Hub, MethSurv, and MEXPRESS were used for the analysis and relationship between DNA methylation and GRM4 expression and prognosis in glioma. TIMER2.0 and CAMOIP databases were used to assess the association between immune cell infiltration and GRM4. Human GBM cell lines were used to validate the function of GRM4. RESULTS: Our study shows that GRM4 is under expressed among gliomas and accompanied by poorer OS. Multivariate analysis showed that low mRNA expression of GRM4 was an independent factor of prognostic for shorter OS in all glioma patients. MiR-1262 affects the malignant phenotype of gliomas through GRM4. Methylation of DNA plays an important role in the instruction of GRM4 expression, the methylation level of GRM4 in glioma tissue is higher in comparison to normal tissue, and the higher methylation level was accompanied with the worse prognosis. Further analysis showed that GRM4 mRNA expression in GBM linked negatively with common lymphoid progenitor, Macrophage M1, Macrophage, and T cell CD4+ Th2, but not with the tumor purity. Overexpression of GRM4 prevents the migration of human GBM cell lines in vitro. CONCLUSION: GRM4 may have a substantial impact on the infiltration of immune cells and serve as a valuable prognostic biomarker in gliomas.

Changes of ecological vulnerability in areas with different urban expansion patterns- A case study in the Yanhe river basin, China.

Urban expansion has the potentiality to disrupt ecosystems and form highly fragile urban landscapes. However, studies investigating the impact of different urban expansion patterns on the ecological environments are relatively limited. Taking the Yanhe river basin, a typical basin in a loess region, as a case study, we developed an ecological vulnerability assessment system as well as assessed the main drivers of ecological vulnerability for different time periods (1990, 2000, 2010 and 2018). Additionally, we classified each urban expansion region into three different patterns according to the landscape expansion index, and analyzed changes in the ecological vulnerability under these three diverse patterns. Finally, the Kruskal-Wallis rank sum test was applied to compare the factors for the different changes in ecological vulnerability across different urban expansion patterns. Our investigation also aimed to elucidate the impacts of different urban expansion patterns on ecological vulnerability and identify key physical-social-economic-climatic drivers. The results indicate that the ecological vulnerability index (EVI) of the study area is decreasing gradually from the peak value of 0.459 in 2000 to 0.383 in 2018. Habitat quality index is found to be the most influencing factor, followed by aridity index and building density (mean q of 0.53, 0.46, and 0.42, respectively). Our study also reveals that the outlying expansion areas have the greatest increase in EVI at 0.38, with edge and infill expansions at 0.31 and 0.27, respectively. It is also found that when the overall environment is improving, the outlying expansion areas have the smallest decrease in EVI. Initial ecological vulnerability and key drivers may explain this difference. Therefore, results of this study indicate that the ecological impacts of diverse urban expansion patterns are significantly different, among which outlying expansions should receive prioritized attention.

The impact of grazing activities and environmental conditions on the stability of alpine grassland ecosystems.

Globally, grazing activities have profound impacts on the structure and function of ecosystems. This study, based on a 20-year MODIS time series dataset, employs remote sensing techniques and the Seasonal-Trend decomposition using Loess (STL) algorithm to quantitatively assess the stability of alpine grassland ecosystems from multiple dimensions, and to reveal the characteristics of grazing activities and environmental conditions on ecosystem stability. The results indicate that only 5.77% of the area remains undisturbed, with most areas experiencing varying degrees of disturbance. Further analysis shows that grazing activities in high vegetation coverage areas are the main source of interference. In areas with concentrated interference, elevation and slope have a positive correlation with resistance stability, but a negative correlation with recovery stability. Precipitation and landscape diversity have positive effects on both resistance stability and recovery stability. Vegetation coverage and grazing intensity have a negative correlation with resistance stability, but a positive correlation with recovery stability. This highlights the complex interactions between human activities, environmental factors, and ecosystem stability. The findings emphasize the need for targeted conservation and management strategies to mitigate disturbances to ecosystems affected by human activities and enhance their stability.

Biological underpinnings of radiomic magnetic resonance imaging phenotypes for risk stratification in IDH wild-type glioblastoma.

BACKGROUND: To develop and validate a conventional MRI-based radiomic model for predicting prognosis in patients with IDH wild-type glioblastoma (GBM) and reveal the biological underpinning of the radiomic phenotypes. METHODS: A total of 801 adult patients (training set, N = 471; internal validation set, N = 239; external validation set, N = 91) diagnosed with IDH wild-type GBM were included. A 20-feature radiomic risk score (Radscore) was built for overall survival (OS) prediction by univariate prognostic analysis and least absolute shrinkage and selection operator (LASSO) Cox regression in the training set. GSEA and WGCNA were applied to identify the intersectional pathways underlying the prognostic radiomic features in a radiogenomic analysis set with paired MRI and RNA-seq data (N = 132). The biological meaning of the conventional MRI sequences was revealed using a Mantel test. RESULTS: Radscore was demonstrated to be an independent prognostic factor (P < 0.001). Incorporating the Radscore into a clinical model resulted in a radiomic-clinical nomogram predicting survival better than either the Radscore model or the clinical model alone, with better calibration and classification accuracy (a total net reclassification improvement of 0.403, P < 0.001). Three pathway categories (proliferation, DNA damage response, and immune response) were significantly correlated with the prognostic radiomic phenotypes. CONCLUSION: Our findings indicated that the prognostic radiomic phenotypes derived from conventional MRI are driven by distinct pathways involved in proliferation, DNA damage response, and immunity of IDH wild-type GBM.

Leveraging a disulfidptosis­related lncRNAs signature for predicting the prognosis and immunotherapy of glioma.

BACKGROUND: Gliomas, a prevalent form of primary brain tumors, are linked with a high mortality rate and unfavorable prognoses. Disulfidptosis, an innovative form of programmed cell death, has received scant attention concerning disulfidptosis-related lncRNAs (DRLs). The objective of this investigation was to ascertain a prognostic signature utilizing DRLs to forecast the prognosis and treatment targets of glioma patients. METHODS: RNA-seq data were procured from The Cancer Genome Atlas database. Disulfidptosis-related genes were compiled from prior research. An analysis of multivariate Cox regression and the least absolute selection operator was used to construct a risk model using six DRLs. The risk signature's performance was evaluated via Kaplan-Meier survival curves and receiver operating characteristic curves. Additionally, functional analysis was carried out using GO, KEGG, and single-sample GSEA to investigate the biological functions and immune infiltration. The research also evaluated tumor mutational burden, therapeutic drug sensitivity, and consensus cluster analysis. Reverse transcription quantitative PCR was conducted to validate the expression level of DRLs. RESULTS: A prognostic signature comprising six DRLs was developed to predict the prognosis of glioma patients. High-risk patients had significantly shorter overall survival than low-risk patients. The robustness of the risk model was validated by receiver operating characteristic curves and subgroup survival analysis. Risk model was used independently as a prognostic indicator for the glioma patients. Notably, the low-risk patients displayed a substantial decrease in the immune checkpoints, the proportion of immune cells, ESTIMATE and immune score. IC50 values from the different risk groups allowed us to discern three drugs for the treatment of glioma patients. Lastly, the potential clinical significance of six DRLs was determined. CONCLUSIONS: A novel six DRLs signature was developed to predict prognosis and may provide valuable insights for patients with glioma seeking novel immunotherapy and targeted therapy.

LncRNA WEE2-AS1 is a diagnostic biomarker that predicts poor prognoses in patients with glioma.

BACKGROUND: Glioma is characterized by high morbidity, high mortality, and poor prognosis. Despite tremendous advances in the treatment of glioma, the prognosis of patients with glioma is still unsatisfactory. There is an urgent need to discover novel molecular markers that effectively predict prognosis in patients with glioma. The investigation of the role of WEE2-AS1 in various tumors is an emerging research field, but the biological function and prognostic value of WEE2-AS1 in glioma have rarely been reported. This study aimed to assess the value of WEE2-AS1 as a potential prognostic marker of glioma. METHODS: Gene expression (RNA-Seq) data of patients with glioma were extracted from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) databases. The Wilcoxon rank sum test was used to analyze the expression of WEE2-AS1 in the cells and tissues of glioma. The Kruskal-Wallis rank sum test, Wilcoxon rank sum test, and logistic regression were used to evaluate the relationship between clinical variables and expression of WEE2-AS1. Cox regression analysis and the Kaplan-Meier method were used to evaluate the prognostic factors in glioma. A nomogram based on Cox multivariate analysis was used to predict the impact of WEE2-AS1 on glioma prognosis. Gene Set Enrichment Analysis (GSEA) was used to identify key WEE2-AS1-associated signaling pathways. Spearman's rank correlation was used to elucidate the association between WEE2-AS1 expression and immune cell infiltration levels. RESULTS: We found that WEE2-AS1 was overexpressed in a variety of cancers, including glioma. High expression of WEE2-AS1 was associated with glioma progression. We determined that the expression of WEE2-AS1 might be an independent risk factor for the survival and prognosis of patients with glioma. We further observed that the mechanism of WEE2-AS1-mediated tumorigenesis involved neuroactive ligand-receptor interaction, cell cycle, and the infiltration of immune cells into the glioma microenvironment. CONCLUSION: These findings demonstrate that WEE2-AS1 is a promising biomarker for the diagnosis and prognosis of patients with glioma. An increased understanding of its effects on the regulation of cell growth may lead to the development of clinical applications that improve the prognostic status of patients with glioma.

Radiomic features from multiparametric magnetic resonance imaging predict molecular subgroups of pediatric low-grade gliomas.

BACKGROUND: We aimed to develop machine learning models for prediction of molecular subgroups (low-risk group and intermediate/high-risk group) and molecular marker (KIAA1549-BRAF fusion) of pediatric low-grade gliomas (PLGGs) based on radiomic features extracted from multiparametric MRI. METHODS: 61 patients with PLGGs were included in this retrospective study, which were divided into a training set and an internal validation set at a ratio of 2:1 based on the molecular subgroups or the molecular marker. The patients were classified into low-risk and intermediate/high-risk groups, BRAF fusion positive and negative groups, respectively. We extracted 5929 radiomic features from multiparametric MRI. Thereafter, we removed redundant features, trained random forest models on the training set for predicting the molecular subgroups or the molecular marker, and validated their performance on the internal validation set. The performance of the prediction model was verified by 3-fold cross-validation. RESULTS: We constructed the classification model differentiating low-risk PLGGs from intermediate/high-risk PLGGs using 4 relevant features, with an AUC of 0.833 and an accuracy of 76.2% in the internal validation set. In the prediction model for predicting KIAA1549-BRAF fusion using 4 relevant features, an AUC of 0.818 and an accuracy of 81.0% were achieved in the internal validation set. CONCLUSIONS: The current study demonstrates that MRI radiomics is able to predict molecular subgroups of PLGGs and KIAA1549-BRAF fusion with satisfying sensitivity. TRIAL REGISTRATION: This study was retrospectively registered at clinicaltrials.gov (NCT04217018).

Potential therapeutic action of tauroursodeoxycholic acid against cholestatic liver injury via hepatic Fxr/Nrf2 and CHOP-DR5-caspase-8 pathway.

Cholestasis is a pathophysiologic syndrome with limited therapeutic options. Tauroursodeoxycholic acid (TUDCA) has been employed to treat hepatobiliary disorders and is as effective as UDCA in alleviating cholestatic liver disease in clinical trials. Until now, TUDCA's mechanism of action toward cholestasis remains unclear. In the present study, cholestasis was induced with a cholic acid (CA)-supplemented diet or α-naphthyl isothiocyanate (ANIT) gavage in wild-type and Farnesoid X Receptor (FXR) deficient mice, using obeticholic acid (OCA) as control. The effects of TUDCA on liver histological changes, transaminase level, bile acid composition, hepatocyte death, expression of Fxr and nuclear factor erythroid 2-related factor 2 (Nrf2) and target genes, as well as apoptotic signaling pathways, were investigated. Treating CA-fed mice with TUDCA markedly alleviated liver injury, attenuated bile acids retention in liver and plasma, increased Fxr and Nrf2 nuclear levels and modulated the expression of targets regulating synthesis and transportation of bile acids, including BSEP, MRP2, NTCP and CYP7A1. TUDCA, but not OCA, activated Nrf2 signaling and exerted protective effects against cholestatic liver injury in Fxr-/- mice fed with CA. Furthermore, in both mice with CA- and ANIT-induced cholestasis, TUDCA decreased expression of GRP78 and CCAAT/enhancer-binding protein homologous protein (CHOP), reduced death receptor 5 (DR5) transcription, caspase-8 activation, and BID cleavage, and subsequently inhibited activation of executioner caspases and apoptosis in liver. We confirmed that TUDCA protected against cholestatic liver injury by alleviating BAs burden of dually activating hepatic Fxr and Nrf2. Moreover, inhibiting CHOP-DR5-caspase-8 pathway contributed to the anti-apoptotic effect of TUDCA in cholestasis.

Improving Noninvasive Classification of Molecular Subtypes of Adult Gliomas With Diffusion-Weighted MR Imaging: An Externally Validated Machine Learning Algorithm.

BACKGROUND: Genetic testing for molecular markers of gliomas sometimes is unavailable because of time-consuming and expensive, even limited tumor specimens or nonsurgery cases. PURPOSE: To train a three-class radiomic model classifying three molecular subtypes including isocitrate dehydrogenase (IDH) mutations and 1p/19q-noncodeleted (IDHmut-noncodel), IDH wild-type (IDHwt), IDH-mutant and 1p/19q-codeleted (IDHmut-codel) of adult gliomas and investigate whether radiomic features from diffusion-weighted imaging (DWI) could bring additive value. STUDY TYPE: Retrospective. POPULATION: A total of 755 patients including 111 IDHmut-noncodel, 571 IDHwt, and 73 IDHmut-codel cases were divided into training (n = 480) and internal validation set (n = 275); 139 patients including 21 IDHmut-noncodel, 104 IDHwt, and 14 IDHmut-codel cases were utilized as external validation set. FIELD STRENGTH/SEQUENCE: A 1.5 T or 3.0 T/multiparametric MRI, including T1-weighted (T1), T1-weighted gadolinium contrast-enhanced (T1c), T2-weighted (T2), fluid attenuated inversion recovery (FLAIR), and DWI. ASSESSMENT: The performance of multiparametric radiomic model (random-forest model) using 22 selected features from T1, T2, FLAIR, T1c images and apparent diffusion coefficient (ADC) maps, and conventional radiomic model using 20 selected features from T1, T2, FLAIR, and T1c images was assessed in internal and external validation sets by comparing probability values and actual incidence. STATISTICAL TESTS: Mann-Whitney U test, Chi-Squared test, Wilcoxon test, receiver operating curve (ROC), and area under the curve (AUC); DeLong analysis. P < 0.05 was statistically significant. RESULTS: The multiparametric radiomic model achieved AUC values for IDHmut-noncodel, IDHwt, and IDHmut-codel of 0.8181, 0.8524, and 0.8502 in internal validation set and 0.7571, 0.7779, and 0.7491 in external validation set, respectively. Multiparametric radiomic model showed significantly better diagnostic performance after DeLong analysis, especially in classifying IDHwt and IDHmut-noncodel subtypes. DATA CONCLUSION: Radiomic features from DWI could bring additive value and improve the performance of conventional MRI-based radiomic model for classifying the molecular subtypes especially IDHmut-noncodel and IDHwt of adult gliomas. TECHNICAL EFFICACY: Stage 2.

The choleretic role of tauroursodeoxycholic acid exacerbates alpha-naphthylisothiocyanate induced cholestatic liver injury through the FXR/BSEP pathway.

The aim of this study was to determine the effect of tauroursodeoxycholic acid (TUDCA) on the alpha-naphthylisothiocyanate (ANIT)-induced model of cholestasis in mice. Wild-type and farnesoid X receptor (FXR)-deficient (Fxr-/- ) mice were used to generate cholestasis models by gavage with ANIT. Obeticholic acid (OCA) was used as a positive control. In wild-type mice, treatment with TUDCA for 7 days resulted in a dramatic increase in serum levels of alanine aminotransferase (ALT), with aggravation of bile infarcts and hepatocyte necrosis with ANIT-induction. TUDCA activated FXR to upregulate the expression of bile salt export pump (BSEP), increasing bile acids (BAs)-dependent bile flow, but aggravating cholestatic liver injury when bile ducts were obstructed resulting from ANIT. In contrast, TUDCA improved the liver pathology and decreased serum ALT and alkaline phosphatase (ALP) levels in ANIT-induced Fxr-/- mice. Furthermore, TUDCA inhibited the expression of cleaved caspase-3 and reduced the area of terminal deoxynucleotidyl transferase dUTP nick-end labeling (TUNEL) staining in the model mice. TUDCA also upregulated anion exchanger 2 (AE2) protein expression, protecting cholangiocytes against excessive toxic BAs. Our results showed that TUDCA aggravated cholestatic liver injury via the FXR/BSEP pathway when bile ducts were obstructed, although TUDCA inhibited apoptotic activity and protected cholangiocytes against excessive toxic BAs.

Follow-up outcomes of different bypass surgical modalities for adults with ischaemic-type moyamoya disease.

PURPOSE: The preferred surgical method for treating adults with moyamoya disease (MMD) remains controversial. The purpose of this study was to compare the efficacy of different surgical methods in the treatment of adults with ischaemic-type MMD. METHODS: We retrospectively analyzed the data of patients with ischaemic-type MMD who underwent indirect bypass (IB), direct bypass (DB), or combined bypass (CB) at the First Affiliated Hospital of Zhengzhou University from January 2013 to December 2019. Postoperative complications, improvements in neurological function, haemodynamics, recurrent stroke and neovascularization were compared. RESULTS: A total of 310 adults (371 hemispheres) with ischaemic-type MMD were included in our study. Ninety, 127, and 154 hemispheres underwent IB, DB and CB, respectively. A total of 24 (6.5%) ischaemic events and 8 (2.8%) symptomatic hyperperfusion events occurred after the operations. There was no significant difference in postoperative complications among the three types of surgery (p = 0.300). During the follow-up period, there were 21 cases (5.7%) of recurrent ischaemia and 12 cases (3.2%) of recurrent haemorrhage. Kaplan-Meier survival analysis showed that the ischaemia-free survival of the CB group was significantly longer than that of the IB group (p = 0.047), but there was no significant difference in haemorrhage-free survival among the three groups (p = 0.660). Six months after the operation, DB and CB were superior to IB in improving cerebral blood flow and neovascularization (p = 0.002), but there was no significant difference in the improvement of neurological function among the three groups at the last follow-up (p = 0.784). CONCLUSION: The three surgical methods achieved satisfactory results in the treatment of ischaemic-type MMD. DB and CB can significantly improve haemodynamics and reduce recurrent stroke. In terms of improving neurological function, the curative effect of the three surgical methods remains to be further explored.

Remora Optimization Algorithm with Enhanced Randomness for Large-Scale Measurement Field Deployment Technology.

In the large-scale measurement field, deployment planning usually uses the Monte Carlo method for simulation analysis, which has high algorithm complexity. At the same time, traditional station planning is inefficient and unable to calculate overall accessibility due to the occlusion of tooling. To solve this problem, in this study, we first introduced a Poisson-like randomness strategy and an enhanced randomness strategy to improve the remora optimization algorithm (ROA), i.e., the PROA. Simultaneously, its convergence speed and robustness were verified in different dimensions using the CEC benchmark function. The convergence speed of 67.5-74% of the results is better than the ROA, and the robustness results of 66.67-75% are better than those of the ROA. Second, a deployment model was established for the large-scale measurement field to obtain the maximum visible area of the target to be measured. Finally, the PROA was used as the optimizer to solve optimal deployment planning; the performance of the PROA was verified by simulation analysis. In the case of six stations, the maximum visible area of the PROA reaches 83.02%, which is 18.07% higher than that of the ROA. Compared with the traditional method, this model shortens the deployment time and calculates the overall accessibility, which is of practical significance for improving assembly efficiency in large-size measurement field environments.

Diffractive lensless imaging with optimized Voronoi-Fresnel phase.

Lensless cameras are a class of imaging devices that shrink the physical dimensions to the very close vicinity of the image sensor by replacing conventional compound lenses with integrated flat optics and computational algorithms. Here we report a diffractive lensless camera with spatially-coded Voronoi-Fresnel phase to achieve superior image quality. We propose a design principle of maximizing the acquired information in optics to facilitate the computational reconstruction. By introducing an easy-to-optimize Fourier domain metric, Modulation Transfer Function volume (MTFv), which is related to the Strehl ratio, we devise an optimization framework to guide the optimization of the diffractive optical element. The resulting Voronoi-Fresnel phase features an irregular array of quasi-Centroidal Voronoi cells containing a base first-order Fresnel phase function. We demonstrate and verify the imaging performance for photography applications with a prototype Voronoi-Fresnel lensless camera on a 1.6-megapixel image sensor in various illumination conditions. Results show that the proposed design outperforms existing lensless cameras, and could benefit the development of compact imaging systems that work in extreme physical conditions.

Role of ferroptosis-related genes in coronary atherosclerosis and identification of key genes: integration of bioinformatics analysis and experimental validation.

BACKGROUND: Coronary atherosclerosis (CA) is the most common type of atherosclerosis. However, the inherent pathogenesis and mechanisms of CA are unclear, and the relationship with ferroptosis-related genes (FRGs) has not been reported. The purpose of this study was to use bioinformatics techniques to evaluate potential therapeutic targets for CA.Please provide the given name for author "Dingshun".Please provide the given name for author "Dingshun". METHODS: First, the GSE132651 dataset was acquired from the Gene Expression Omnibus database. Gene Ontology enrichment analysis, Kyoto Encyclopedia of Genes and Genomes enrichment analysis, and Protein-Protein interaction network were successively conducted. Next, overlapping genes between hub genes and CA genes were found. FRGs were found when comparing the CA group with the normal group. The correlation between overlapping genes and FRGs was further analyzed. At last, we performed Elisa to validate the expression of these genes in human blood specimens. Mice aortic tissues were used for western blot to detect the expression of proteins. RESULTS: Based on the GSE132651 dataset, 102 differentially expressed genes were identified. Five overlapping genes between hub genes and CA genes were found (CCNA2, RRM2, PBK, PCNA, CDK1). TFRC and GPX4 were found to be FRGs. TFRC was positively correlated with CCNA2, PBK, PCNA, CDK1, RRM2, with CDK1 being the strongest correlation. GPX4 was negatively correlated with these genes, among which CCNA2 was the strongest correlation. The ELISA results showed that CCNA2, CDK1, and TFRC expression were markedly increased in serum of the CA samples compared with controls, while GPX4 expression was markedly decreased in the CA samples. The western blot results show that GPX4 expression was lower in the model group, TFRC, CDK1, and CCNA2 protein expression were high in the model group. CONCLUSIONS: Ferroptosis-related genes GPX4 and TFRC were closely correlated with the identified overlapping genes CCNA2 and CDK1, which may serve as targeted therapies for the treatment of CA.

One-Dimensional Chains in Pentanary Chalcogenides A2Ba3Cu2Sb2S10 (A = K, Rb, Cs) Displaying a Photocurrent Response.

The discovery of new inorganic functional chalcogenides is of fundamental importance in structure chemistry and materials science. Herein, a new type of pentanary thioantimonates, A2Ba3Cu2Sb2S10 (A = K, Rb, Cs), has been discovered by a solvothermal method at low temperature. These isostructural compounds belong to the monoclinic space group C2/m (No. 12) and comprise unique one-dimensional (1D) [Cu2Sb2S10]8- chains surrounded by discrete A+ and Ba2+ cations. Such a 1D chain structure is the first case of chalcogenides in the X/Cu/Sb/Q (X = cations; Q = chalcogen) system. The energy gaps range from 1.90 to 1.98 eV for A2Ba3Cu2Sb2S10 (A = K, Rb, Cs) were obtained from the UV-visible reflectance spectroscopy. Moreover, Rb2Ba3Cu2Sb2S10 displays an intriguing photocurrent response under simulated solar-light illumination. The theoretical calculations were also carried out to understand the interrelationship of the optical performance and electronic structure.