SCAR: Single-cell and Spatially-resolved Cancer Resources.

Advances in sequencing and imaging technologies offer a unique opportunity to unravel cell heterogeneity and develop new immunotherapy strategies for cancer research. There is an urgent need for a resource that effectively integrates a vast amount of transcriptomic profiling data to comprehensively explore cancer tissue heterogeneity and the tumor microenvironment. In this context, we developed the Single-cell and Spatially-resolved Cancer Resources (SCAR) database, a combined tumor spatial and single-cell transcriptomic platform, which is freely accessible at http://8.142.154.29/SCAR2023 or http://scaratlas.com. SCAR contains spatial transcriptomic data from 21 tumor tissues and single-cell transcriptomic data from 11 301 352 cells encompassing 395 cancer subtypes and covering a wide variety of tissues, organoids, and cell lines. This resource offers diverse functional modules to address key cancer research questions at multiple levels, including the screening of tumor cell types, metabolic features, cell communication and gene expression patterns within the tumor microenvironment. Moreover, SCAR enables the analysis of biomarker expression patterns and cell developmental trajectories. SCAR also provides a comprehensive analysis of multi-dimensional datasets based on 34 state-of-the-art omics techniques, serving as an essential tool for in-depth mining and understanding of cell heterogeneity and spatial location. The implications of this resource extend to both cancer biology research and cancer immunotherapy development.

SCAN: Spatiotemporal Cloud Atlas for Neural cells.

The nervous system is one of the most complicated and enigmatic systems within the animal kingdom. Recently, the emergence and development of spatial transcriptomics (ST) and single-cell RNA sequencing (scRNA-seq) technologies have provided an unprecedented ability to systematically decipher the cellular heterogeneity and spatial locations of the nervous system from multiple unbiased aspects. However, efficiently integrating, presenting and analyzing massive multiomic data remains a huge challenge. Here, we manually collected and comprehensively analyzed high-quality scRNA-seq and ST data from the nervous system, covering 10 679 684 cells. In addition, multi-omic datasets from more than 900 species were included for extensive data mining from an evolutionary perspective. Furthermore, over 100 neurological diseases (e.g. Alzheimer's disease, Parkinson's disease, Down syndrome) were systematically analyzed for high-throughput screening of putative biomarkers. Differential expression patterns across developmental time points, cell types and ST spots were discerned and subsequently subjected to extensive interpretation. To provide researchers with efficient data exploration, we created a new database with interactive interfaces and integrated functions called the Spatiotemporal Cloud Atlas for Neural cells (SCAN), freely accessible at http://47.98.139.124:8799 or http://scanatlas.net. SCAN will benefit the neuroscience research community to better exploit the spatiotemporal atlas of the neural system and promote the development of diagnostic strategies for various neurological disorders.

BRD9-mediated control of the TGF-ß/Activin/Nodal pathway regulates self-renewal and differentiation of human embryonic stem cells and progression of cancer cells.

Bromodomain-containing protein 9 (BRD9) is a specific subunit of the non-canonical SWI/SNF (ncBAF) chromatin-remodeling complex, whose function in human embryonic stem cells (hESCs) remains unclear. Here, we demonstrate that impaired BRD9 function reduces the self-renewal capacity of hESCs and alters their differentiation potential. Specifically, BRD9 depletion inhibits meso-endoderm differentiation while promoting neural ectoderm differentiation. Notably, supplementation of NODAL, TGF-ß, Activin A or WNT3A rescues the differentiation defects caused by BRD9 loss. Mechanistically, BRD9 forms a complex with BRD4, SMAD2/3, ß-CATENIN and P300, which regulates the expression of pluripotency genes and the activity of TGF-ß/Nodal/Activin and Wnt signaling pathways. This is achieved by regulating the deposition of H3K27ac on associated genes, thus maintaining and directing hESC differentiation. BRD9-mediated regulation of the TGF-ß/Activin/Nodal pathway is also demonstrated in the development of pancreatic and breast cancer cells. In summary, our study highlights the crucial role of BRD9 in the regulation of hESC self-renewal and differentiation, as well as its participation in the progression of pancreatic and breast cancers.

SPEED: Single-cell Pan-species atlas in the light of Ecology and Evolution for Development and Diseases.

It is a challenge to efficiently integrate and present the tremendous amounts of single-cell data generated from multiple tissues of various species. Here, we create a new database named SPEED for single-cell pan-species atlas in the light of ecology and evolution for development and diseases (freely accessible at http://8.142.154.29 or http://speedatlas.net). SPEED is an online platform with 4 data modules, 7 function modules and 2 display modules. The 'Pan' module is applied for the interactive analysis of single cell sequencing datasets from 127 species, and the 'Evo', 'Devo', and 'Diz' modules provide comprehensive analysis of single-cell atlases on 18 evolution datasets, 28 development datasets, and 85 disease datasets. The 'C2C', 'G2G' and 'S2S' modules explore intercellular communications, genetic regulatory networks, and cross-species molecular evolution. The 'sSearch', 'sMarker', 'sUp', and 'sDown' modules allow users to retrieve specific data information, obtain common marker genes for cell types, freely upload, and download single-cell datasets, respectively. Two display modules ('HOME' and 'HELP') offer easier access to the SPEED database with informative statistics and detailed guidelines. All in all, SPEED is an integrated platform for single-cell RNA sequencing (scRNA-seq) and single-cell whole-genome sequencing (scWGS) datasets to assist the deep-mining and understanding of heterogeneity among cells, tissues, and species at multi-levels, angles, and orientations, as well as provide new insights into molecular mechanisms of biological development and pathogenesis.

Identification of crosstalk genes relating to ECM-receptor interaction genes in MASH and DN using bioinformatics and machine learning.

This study aimed to identify genes shared by metabolic dysfunction-associated fatty liver disease (MASH) and diabetic nephropathy (DN) and the effect of extracellular matrix (ECM) receptor interaction genes on them. Datasets with MASH and DN were downloaded from the Gene Expression Omnibus (GEO) database. Pearson's coefficients assessed the correlation between ECM-receptor interaction genes and cross talk genes. The coexpression network of co-expression pairs (CP) genes was integrated with its protein-protein interaction (PPI) network, and machine learning was employed to identify essential disease-representing genes. Finally, immuno-penetration analysis was performed on the MASH and DN gene datasets using the CIBERSORT algorithm to evaluate the plausibility of these genes in diseases. We found 19 key CP genes. Fos proto-oncogene (FOS), belonging to the IL-17 signalling pathway, showed greater centrality PPI network; Hyaluronan Mediated Motility Receptor (HMMR), belonging to ECM-receptor interaction genes, showed most critical in the co-expression network map of 19 CP genes; Forkhead Box C1 (FOXC1), like FOS, showed a high ability to predict disease in XGBoost analysis. Further immune infiltration showed a clear positive correlation between FOS/FOXC1 and mast cells that secrete IL-17 during inflammation. Combining the results of previous studies, we suggest a FOS/FOXC1/HMMR regulatory axis in MASH and DN may be associated with mast cells in the acting IL-17 signalling pathway. Extracellular HMMR may regulate the IL-17 pathway represented by FOS through the Mitogen-Activated Protein Kinase 1 (ERK) or PI3K-Akt-mTOR pathway. HMMR may serve as a signalling carrier between MASH and DN and could be targeted for therapeutic development.

Molecular Expression and Prognostic Implications of Krüppel-Like Factor 3 (KLF3) in Clear Cell Renal Cell Carcinoma.

A major subtype of renal cancer is clear cell renal cell carcinoma (ccRCC). Krüppel-like factor 3 (KLF3) dysfunction is also revealed leading to poor prognosis in multiple cancer types. However, dysregulation and molecular dynamics of KLF3 underlying ccRCC progression still remains elusive. Here KLF3 gene and protein expressions in ccRCC were explored using data cohorts from The Cancer Genome Atlas (TCGA), Human Protein Atlas (HPA), Clinical Proteomic Tumor Analysis Consortium (CPTAC) and verified them in our patient cohort. Correlations of KLF3 expression with clinicopathological features, epigenetic modification, and immune microenvironment characteristics were further investigated. KLF3 was significantly down-regulated expressed in ccRCC tissues compared to adjacent normal controls. Adverse pathological parameters and poor prognosis were associated with lower expression of KLF3. Mechanically, KLF3 regulation was mainly attributed to CpG island methylation. KLF3-high expression subgroup was significantly enriched in cell signaling pathways most associated with EMT markers, angiogenesis, inflammatory response, apoptosis, TGF-ß, degradation of ECM, G2M checkpoint, and PI3K-AKT-mTOR. Based on GDSC database, KLF3 upregulation was identified to be associated with higher sensitivities towards PI3K-Akt-mTOR pathway inhibitors such as PI-103, PIK-93, and OSI-027. In addition, patients with down-regulated KLF3 expressions were found more sensitive towards Trametinib, Cetuximab, and Erlotinib. Collectively, our findings suggest that KLF3 may act as a suitable biomarker for prognosis prediction, tumor microenvironment (TME) phenotype identification, thereby helping ccRCC patients to make better therapeutic decisions.

Network-based integrative analysis of single-cell transcriptomic and epigenomic data for cell types.

Advances in single-cell biotechnologies simultaneously generate the transcriptomic and epigenomic profiles at cell levels, providing an opportunity for investigating cell fates. Although great efforts have been devoted to either of them, the integrative analysis of single-cell multi-omics data is really limited because of the heterogeneity, noises and sparsity of single-cell profiles. In this study, a network-based integrative clustering algorithm (aka NIC) is present for the identification of cell types by fusing the parallel single-cell transcriptomic (scRNA-seq) and epigenomic profiles (scATAC-seq or DNA methylation). To avoid heterogeneity of multi-omics data, NIC automatically learns the cell-cell similarity graphs, which transforms the fusion of multi-omics data into the analysis of multiple networks. Then, NIC employs joint non-negative matrix factorization to learn the shared features of cells by exploiting the structure of learned cell-cell similarity networks, providing a better way to characterize the features of cells. The graph learning and integrative analysis procedures are jointly formulated as an optimization problem, and then the update rules are derived. Thirteen single-cell multi-omics datasets from various tissues and organisms are adopted to validate the performance of NIC, and the experimental results demonstrate that the proposed algorithm significantly outperforms the state-of-the-art methods in terms of various measurements. The proposed algorithm provides an effective strategy for the integrative analysis of single-cell multi-omics data (The software is coded using Matlab, and is freely available for academic https://github.com/xkmaxidian/NIC ).

Phase III clinical trial comparing the efficacy and safety of adamgammadex with sugammadex for reversal of rocuronium-induced neuromuscular block.

BACKGROUND: Preliminary clinical trials of adamgammadex, a new cyclodextrin-based selective reversal agent, have demonstrated its efficacy in reversing neuromuscular block by rocuronium. METHODS: This multicentre, randomised, double-blind, positive-controlled, non-inferiority phase III clinical trial compared the efficacy and safety of adamgammadex and sugammadex. We randomised 310 subjects to receive adamgammadex (4 mg kg-1) or sugammadex (2 mg kg-1) at reappearance of the second twitch of the train-of-four (TOF), and standard safety data were collected. RESULTS: For the primary outcome, the proportion of patients with TOF ratio ≥0.9 within 5 min was 98.7% in the adamgammadex group vs 100% in the sugammadex group, with a point estimate and 95% confidence interval (CI) of 1.3% (-4.6%, +1.3%); the lower limit was greater than the non-inferiority margin of -10%. For the key secondary outcome, the median (inter quartile range) time from the start of administration of adamgammadex or sugammadex to recovery of TOF ratio to 0.9 was 2.25 (1.75, 2.75) min and 1.75 (1.50, 2.00) min, respectively. The difference was 0.50 (95% CI: 0.25, 0.50); the upper limit was lower than the non-inferiority margin of 5 min. In addition, there were no inferior results observed in secondary outcomes. Adamgammadex had a lower incidence of adverse drug reactions compared with sugammadex (anaphylactic reaction, recurarisation, decreased heart rate, and laryngospasm; P=0.047). CONCLUSIONS: Adamgammadex was non-inferior to sugammadex with a possible lower incidence of adverse drug reactions compared with sugammadex. Adamgammadex may have a potential advantage in terms of its overall risk-benefit profile. CLINICAL TRIAL REGISTRATION: Chinese Clinical Trial Registry, ChiCTR2000039525. Registered October 30, 2020. https://www.chictr.org.cn/showproj.html?proj=56825.

Diagnostic performance of coronary computed tomography angiography stenosis score for coronary stenosis.

BACKGROUND: Coronary computed tomography angiography stenosis score (CCTA-SS) is a proposed diagnosis score that considers the plaque characteristics, myocardial function, and the diameter reduction rate of the lesions. This study aimed to evaluate the diagnostic performance of the CCTA-SS in seeking coronary artery disease (CAD). METHODS: The 228 patients with suspected CAD who underwent CCTA and invasive coronary angiography (ICA) procedures were under examination. The diagnostic performance was evaluated with the receiver operating curve (ROC) for CCTA-SS in detecting CAD (defined as a diameter reduction of ≥ 50%) and severe CAD (defined as a diameter reduction of ≥ 70%). RESULTS: The area under ROC (AUC) of CCTA-SS was 0.909 (95% CI: 0.864-0.943), which was significantly higher than that of CCTA (AUC: 0.826; 95% CI: 0.771-0.873; P = 0.0352) in diagnosing of CAD with a threshold of 50%. The optimal cutoff point of CCTA-SS was 51% with a sensitivity of 90.66%, specificity of 95.65%, positive predictive value of 98.80%, negative predictive value of 72.13%, and accuracy of 91.67%, whereas the optimal cutoff point of CCTA was 55%, and the corresponding values were 87.36%, 93.48%, 98.15%, 65.15%, and 88.60%, respectively. With a threshold of 70%, the performance of CCTA-SS with an AUC of 0.927 (95% CI: 0.885-0.957) was significantly higher than that of CCTA with an AUC of 0.521 (95% CI: 0.454-0.587) (P < 0.0001). CONCLUSIONS: CCTA-SS significantly improved the diagnostic accuracy of coronary stenosis, including CAD and severe CAD, compared with CCTA.

Spectrum Situation Awareness for Space-Air-Ground Integrated Networks Based on Tensor Computing.

The spectrum situation awareness problem in space-air-ground integrated networks (SAGINs) is studied from a tensor-computing perspective. Tensor and tensor computing, including tensor decomposition, tensor completion and tensor eigenvalues, can satisfy the application requirements of SAGINs. Tensors can effectively handle multidimensional heterogeneous big data generated by SAGINs. Tensor computing is used to process the big data, with tensor decomposition being used for dimensionality reduction to reduce storage space, and tensor completion utilized for numeric supplementation to overcome the missing data problem. Notably, tensor eigenvalues are used to indicate the intrinsic correlations within the big data. A tensor data model is designed for space-air-ground integrated networks from multiple dimensions. Based on the multidimensional tensor data model, a novel tensor-computing-based spectrum situation awareness scheme is proposed. Two tensor eigenvalue calculation algorithms are studied to generate tensor eigenvalues. The distribution characteristics of tensor eigenvalues are used to design spectrum sensing schemes with hypothesis tests. The main advantage of this algorithm based on tensor eigenvalue distributions is that the statistics of spectrum situation awareness can be completely characterized by tensor eigenvalues. The feasibility of spectrum situation awareness based on tensor eigenvalues is evaluated by simulation results. The new application paradigm of tensor eigenvalue provides a novel direction for practical applications of tensor theory.

Driver gene detection through Bayesian network integration of mutation and expression profiles.

MOTIVATION: The identification of mutated driver genes and the corresponding pathways is one of the primary goals in understanding tumorigenesis at the patient level. Integration of multi-dimensional genomic data from existing repositories, e.g., The Cancer Genome Atlas (TCGA), offers an effective way to tackle this issue. In this study, we aimed to leverage the complementary genomic information of individuals and create an integrative framework to identify cancer-related driver genes. Specifically, based on pinpointed differentially expressed genes, variants in somatic mutations and a gene interaction network, we proposed an unsupervised Bayesian network integration (BNI) method to detect driver genes and estimate the disease propagation at the patient and/or cohort levels. This new method first captures inherent structural information to construct a functional gene mutation network and then extracts the driver genes and their controlled downstream modules using the minimum cover subset method. RESULTS: Using other credible sources (e.g. Cancer Gene Census and Network of Cancer Genes), we validated the driver genes predicted by the BNI method in three TCGA pan-cancer cohorts. The proposed method provides an effective approach to address tumor heterogeneity faced by personalized medicine. The pinpointed drivers warrant further wet laboratory validation. AVAILABILITY AND IMPLEMENTATION: The supplementary tables and source code can be obtained from https://xavieruniversityoflouisiana.sharefile.com/d-se6df2c8d0ebe4800a3030311efddafe5. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PHF6 recruits BPTF to promote HIF-dependent pathway and progression in YAP-high breast cancer.

BACKGROUND: Aberrant epigenetic remodeling events contribute to progression and metastasis of breast cancer (Bca). The specific mechanims that epigenetic factors rely on to mediate tumor aggressiveness remain unclear. We aimed to elucidate the roles of epigenetic protein PHF6 in breast tumorigenesis. METHODS: Published datasets and tissue samples with PHF6 staining were used to investigate the clinical relevance of PHF6 in Bca. CCK-8, clony formation assays were used to assess cell growth capacity. Cell migration and invasion abilities were measured by Transwell assay. The gene mRNA and protein levels were measured by quantitative real-time PCR and western blot. Chromatin immunoprecipitation (ChIP)-qPCR assays were used to investigate transcriptional relationships among genes. The Co-immunoprecipitation (Co-IP) assay was used to validate interactions between proteins. The CRISPR/Cas9 editing technology was used to construct double HIF knockout (HIF-DKO) cells. The subcutaneous xenograft model and orthotopic implantation tumor model were used to asess in vivo tumor growth. RESULTS: In this study, we utilized MTT assay to screen that PHF6 is required for Bca growth. PHF6 promotes Bca proliferation and migration. By analyzing The Cancer Genome Atlas breast cancer (TCGA-Bca) cohort, we found that PHF6 was significantly higher in tumor versus normal tissues. Mechanistically, PHF6 physically interacts with HIF-1α and HIF-2α to potentiate HIF-driven transcriptional events to initiate breast tumorigenesis. HIF-DKO abolished PHF6-mediated breast tumor growth, and PHF6 deficiency in turn impaired HIF transcriptional effects. Besides, hypoxia could also rely on YAP activation, but not HIF, to sustain PHF6 expressions in Bca cells. In addition, PHF6 recuits BPTF to mediate epigenetic remodeling to augment HIF transcriptional activity. Targeting PHF6 or BPTF inhibitor (AU1) is effective in mice models. Lastly, PHF6 correlated with HIF target gene expression in human breast tumors, which is an independent prognostic regulator. CONCLUSIONS: Collectively, this study identified PHF6 as a prognostic epigenetic regulator for Bca, functioning as a HIF coactivator. The fundamental mechanisms underlying YAP/PHF6/HIF axis in breast tumors endowed novel epigenegtic targets for Bca treatment.

Comparative analysis of single cell lung atlas of bat, cat, tiger, and pangolin.

Horseshoe bats (Rhinolophus sinicus) might help maintain coronaviruses severely affecting human health, such as severe acute respiratory syndrome coronavirus (SARS-CoV). Bats may be more tolerant of viral infection than other mammals due to their unique immune system, but the exact mechanism remains to be fully explored. During the coronavirus disease 2019 (COVID-19) pandemic, multiple animal species were diseased by coronavirus infection, especially in the respiratory system. Herein, a comparative analysis with single nucleus transcriptomic data of the lungs across four species, including horseshoe bat, cat, tiger, and pangolin, were conducted. The distribution of entry factors for twenty-eight respiratory viruses was characterized for the four species. Our findings might increase our understanding of the immune background of horseshoe bats.

The expression level of fibroblast growth factor gene in serum samples of lung cancer patients.

Lung cancer, one of the most deadly and dangerous types of cancer in the world, kills many men and women every year. Activation of fibroblast growth factor signals plays a role in the pathogenesis of several cancers, including lung cancer. Also, this factor may indicate prognosis and is related to the survival rate in patients with NSCLC. Therefore, this research investigated the level of fibroblast growth factor gene expression in the serum of people with lung cancer. In this research, 60 serum samples of healthy people and 60 serum samples of people with NSCLC were prepared, and personal and clinicopathological information of the studied people were collected by questionnaires. Then, plasma isolation, RNA extraction, cDNA synthesis, primers design, implementation, and changes in fibroblast growth factor gene expression in the serum of healthy and lung cancer patients were evaluated by the Real-time PCR method. REST software was used to analyze the results. The findings showed no significant difference in the expression of the fibroblast growth factor gene in the serum of people with the first to third stages of metastasis. However, in the serum of patients with the fourth stage of metastasis, the expression level of this gene was significantly decreased by 3.92 times compared to normal samples (P<0.05). According to the results of this study, it is possible to use the expression level of the fibroblast growth factor gene in people's serum to predict the metastasis stage of lung cancer.

The effect of silica exposure on the risk of lung cancer: A meta-analysis.

Lung cancer is an incurable disease with an increased mortality rate caused by the inhalation of dust-containing crystalline silica particles. Silica exposure is one of the most important occupational hazards in the world. Whether the association between silica exposure and lung cancer is because of the fibrotic process or to the effect of respirable silica itself is unclear. The International Agency for Research on Cancer (IARC) classified silica as a human lung carcinogen. The opinion of lung cancer is a question that has been addressed in this review. Three electronic databases, including MEDLINE, Scopus, and Web of Science, were used to search for relevant literature from 2000 to 2022. To evaluate the relationship between exposure to silica and developing lung cancer, we performed a meta-analysis using the random-effects model. For each study, the overall odds ratio (OR), relative risk (RR) with 95% confidence intervals (CI), and p values were calculated. An extensive database search resulted in the selection of 20 (case-control and nested case-control studies were selected) out of 527 studies. Among the 20 selected studies, 7 studies showed a significant association between silica exposure and an increased risk of lung cancer. Further analysis showed that among the selected studies, six studies showed a significant correlation between combined exposure to silica and smoking with an increased risk of lung cancer. The data from the present study showed that smoking habits increased the impact of silica exposure on the initiation of lung carcinogenesis in exposed workers.

Etomidate-Induced Myoclonus in Sprague-Dawley Rats Involves Neocortical Glutamate Accumulation and N -Methyl- d -Aspartate Receptor Activity.

BACKGROUND: Etomidate-induced myoclonus, a seizure-like movement, is of interest to anesthetists. However, its origin in the brain and its underlying mechanism remain unclear. METHODS: Adult male Sprague-Dawley rats were anesthetized with etomidate, propofol, or lidocaine plus etomidate. We assessed the incidence of myoclonus, behavioral scores, and levels of glutamate and γ-aminobutyric acid (GABA) in the neocortex and hippocampus. To determine the origin and how N -methyl- d -aspartate receptors (NMDARs) modulate etomidate-induced neuroexcitability, the local field potential and muscular tension were monitored. Calcium imaging in vitro and immunoblotting in vivo were conducted to investigate the mechanisms underlying myoclonus. RESULTS: The incidence of etomidate (1.5 mg/kg in vivo)-induced myoclonus was higher than that of propofol (90% vs 10%, P = .0010) and lidocaine plus etomidate (90% vs 20%, P = .0050). Etomidate at doses of 3.75 and 6 mg/kg decreased the mean behavioral score at 1 (mean difference [MD]: 1.80, 95% confidence interval [CI], 0.58-3.02; P = .0058 for both), 2 (MD: 1.60, 95% CI, 0.43-2.77; P = .0084 and MD: 1.70, 95% CI, 0.54-2.86; P = .0060), 3 (MD: 1.60, 95% CI, 0.35-2.85; P = .0127 and MD: 1.70, 95% CI, 0.46-2.94; P = .0091) minutes after administration compared to etomidate at a dose of 1.5 mg/kg. In addition, 0.5 and 1 µM etomidate in vitro increased neocortical intracellular calcium signaling; this signaling decreased when the concentration increased to 5 and 10 µM. Etomidate increased the glutamate level compared to propofol (mean rank difference: 18.20; P = .003), and lidocaine plus etomidate (mean rank difference: 21.70; P = .0002). Etomidate in vivo activated neocortical ripple waves and was positively correlated with muscular tension amplitude (Spearman's r = 0.785, P < .0001). Etomidate at 1.5 mg/kg decreased the K-Cl cotransporter isoform 2 (KCC2) level compared with propofol (MD: -1.15, 95% CI, -1.47 to -0.83; P < .0001) and lidocaine plus etomidate (MD: -0.64, 95% CI, -0.96 to -0.32; P = .0002), DL-2-amino-5-phosphopentanoic acid (AP5) suppressed these effects, while NMDA enhanced them. CONCLUSIONS: Etomidate-induced myoclonus or neuroexcitability is concentration dependent. Etomidate-induced myoclonus originates in the neocortex. The underlying mechanism involves neocortical glutamate accumulation and NMDAR modulation and myoclonus correlates with NMDAR-induced downregulation of KCC2 protein expression.

Lateral classification system predicts the collapse of JIC type C1 nontraumatic osteonecrosis of the femoral head: a retrospective study.

PURPOSES: The aim of this study was to construct a lateral classification system for nontraumatic osteonecrosis of femoral head (NONFH) through three-dimensional reconstruction of the necrotic area to assist in evaluating the prognosis of patients with JIC type C1. METHODS: Retrospective analysis of patients with JIC type C1 NONFH from January 2018 to December 2020. All patients were followed up for more than 3.5 years. The patients were divided into collapse group and non-collapse group according to whether the femoral head collapsed during the follow-up.Lateral classification system for femoral head necrosis is constructed through three-dimensional reconstruction of the necrotic area.Comparison of lateral classification system,midsagittal necrosis angle(MNA)and general data between the two groups.Furthermore, ROC curve analysis and survival analysis were performed. RESULTS: 318 patients were included in this study.There was a significant difference between the two groups in the lateral classification system (P < 0.05). In addition, the MNA in the collapsed group was significantly greater than that in the non-collapse group(P < 0.05). As revealed by the results of ROC analysis, the cutoff point of MNA was 104.5° (P < 0.05).According to the survivorship analysis, the mean survival time of the hips of patients with MNA less than 104.5°was greater than that of patients with MNA over 104.5° (P < 0.05). The survival rates of 3.5 years femoral head were 45.8%, 33.7%, 14.8%, 93.0%, and 100% for lateral classification system 1, 2, 3, 4, and 5, respectively. CONCLUSION: Necrosis involving the anterior aspect of the femoral head is an important risk factor for collapse. The Lateral classification system can effectively predict the femoral head collapse in JIC C1 type NONFH patients, supplementing the deficiency of JIC classification in evaluating the front of the femoral head.

Benzo[a]pyrene and a high-fat diet induce aortic injury and promote low-density lipoprotein accumulation in the endothelium.

Benzo[a]pyrene (BaP) is a ubiquitous environmental pollutant which mainly exposed though diet. High-fat diet (HFD) can induce atherosclerosis, as can BaP. Unhealthy dietary habits lead to high intake of both BaP and lipids. However, the combined effect of BaP and HFD on atherosclerosis and lipid accumulation in the arterial wall, the initial stage of atherosclerosis, is unclear. In this study, C57BL/6 J mice were subchronically exposed to BaP and a HFD, and the mechanism of lipid accumulation was investigated in EA.hy926 and HEK293 cells. Results showed that BaP and HFD increased blood lipids and damaged aortic wall synergistically. Meanwhile, LDL enhanced the toxicity of BaP, and BaP promoted the production of reactive oxygen species and malonaldehyde in EA.hy926 cells, which aggravated LDL-induced cell injury. Moreover, BaP and HFD/LDL induced LDL accumulation in the aortic wall of C57BL/6 J mice/EA.hy926, and the mechanism was by activating AHR/ARNT heterodimer to combine with the scavenger receptor BⅠ (SR-BⅠ) and activin receptor-like kinase 1 (ALK1) promoter regions to transcriptional upregulate its expression, which enhanced the uptake of LDL, and promoting the production of AGEs to inhibit reverse cholesterol transport by SR-BI. BaP and lipid synergistically promoted aortic and endothelial damage, and the health risk of their combined intake should be paid attention to.

ABF1 Positively Regulates Rice Chilling Tolerance via Inducing Trehalose Biosynthesis.

Chilling stress seriously limits grain yield and quality worldwide. However, the genes and the underlying mechanisms that respond to chilling stress remain elusive. This study identified ABF1, a cold-induced transcription factor of the bZIP family. Disruption of ABF1 impaired chilling tolerance with increased ion leakage and reduced proline contents, while ABF1 over-expression lines exhibited the opposite tendency, suggesting that ABF1 positively regulated chilling tolerance in rice. Moreover, SnRK2 protein kinase SAPK10 could phosphorylate ABF1, and strengthen the DNA-binding ability of ABF1 to the G-box cis-element of the promoter of TPS2, a positive regulator of trehalose biosynthesis, consequently elevating the TPS2 transcription and the endogenous trehalose contents. Meanwhile, applying exogenous trehalose enhanced the chilling tolerance of abf1 mutant lines. In summary, this study provides a novel pathway 'SAPK10-ABF1-TPS2' involved in rice chilling tolerance through regulating trehalose homeostasis.

Photocatalytic Co-Reduction of N2 and CO2 with CeO2 Catalyst for Urea Synthesis.

The effective conversion of carbon dioxide (CO2 ) and nitrogen (N2 ) into urea by photocatalytic reaction under mild conditions is considered to be a more environmentally friendly and promising alternative strategies. However, the weak adsorption and activation ability of inert gas on photocatalysts has become the main challenge that hinder the advancement of this technique. Herein, we have successfully established mesoporous CeO2-x nanorods with adjustable oxygen vacancy concentration by heat treatment in Ar/H2 (90 % : 10 %) atmosphere, enhancing the targeted adsorption and activation of N2 and CO2 by introducing oxygen vacancies. Particularly, CeO2 -500 (CeO2 nanorods heated treatment at 500 °C) revealed high photocatalytic activity toward the C-N coupling reaction for urea synthesis with a remarkable urea yield rate of 15.5 µg/h. Besides, both aberration corrected transmission electron microscopy (AC-TEM) and Fourier transform infrared (FT-IR) spectroscopy were used to research the atomic surface structure of CeO2 -500 at high resolution and to monitor the key intermediate precursors generated. The reaction mechanism of photocatalytic C-N coupling was studied in detail by combining Density Functional Theory (DFT) with specific experiments. We hope this work provides important inspiration and guiding significance towards highly efficient photocatalytic synthesis of urea.