Cardiac Metabolism, Reprogramming, and Diseases.

Cardiovascular diseases (CVD) account for the largest bulk of deaths worldwide, posing a massive burden on societies and the global healthcare system. Besides, the incidence and prevalence of these diseases are on the rise, demanding imminent action to revert this trend. Cardiovascular pathogenesis harbors a variety of molecular and cellular mechanisms among which dysregulated metabolism is of significant importance and may even proceed other mechanisms. The healthy heart metabolism primarily relies on fatty acids for the ultimate production of energy through oxidative phosphorylation in mitochondria. Other metabolites such as glucose, amino acids, and ketone bodies come next. Under pathological conditions, there is a shift in metabolic pathways and the preference of metabolites, termed metabolic remodeling or reprogramming. In this review, we aim to summarize cardiovascular metabolism and remodeling in different subsets of CVD to come up with a new paradigm for understanding and treatment of these diseases.

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.

Rnd3 suppresses endothelial cell pyroptosis in atherosclerosis through regulation of ubiquitination of TRAF6.

BACKGROUND: As the main pathological basis for various cardiovascular and cerebrovascular diseases, atherosclerosis has become one of the leading causes of death and disability worldwide. Emerging evidence has suggested that Rho GTPase Rnd3 plays an indisputable role in cardiovascular diseases, although its function in atherosclerosis remains unclear. Here, we found a significant correlation between Rnd3 and pyroptosis of aortic endothelial cells (ECs). METHODS: ApoeKO mice were utilized as a model for atherosclerosis. Endothelium-specific transgenic mice were employed to disrupt the expression level of Rnd3 in vivo. Mechanistic investigation of the impact of Rnd3 on endothelial cell pyroptosis was carried out using liquid chromatography tandem mass spectrometry (LC-MS/MS), co-immunoprecipitation (Co-IP) assays, and molecular docking. RESULTS: Evidence from gain-of-function and loss-of-function studies denoted a protective role for Rnd3 against ECs pyroptosis. Downregulation of Rnd3 sensitized ECs to pyroptosis under oxidized low density lipoprotein (oxLDL) challenge and exacerbated atherosclerosis, while overexpression of Rnd3 effectively prevented these effects. LC-MS/MS, Co-IP assay, and molecular docking revealed that Rnd3 negatively regulated pyroptosis signaling by direct interaction with the ring finger domain of tumor necrosis factor receptor-associated factor 6 (TRAF6). This leads to the suppression of K63-linked TRAF6 ubiquitination and the promotion of K48-linked TRAF6 ubiquitination, inhibiting the activation of NF-κB and promoting the degradation of TRAF6. Moreover, TRAF6 knockdown countered Rnd3 knockout-evoked exacerbation of EC pyroptosis in vivo and vitro. CONCLUSIONS: These findings establish a critical functional connection between Rnd3 and the TRAF6/NF-κB/NLRP3 signaling pathway in ECs, indicating the essential role of Rnd3 in preventing pyroptosis of ECs.

circSOX4 Enhances Hepatocellular Carcinoma Progression via miR-218-5p/YY1 Signaling.

Liver cancer ranks fifth leading malignancy in incidence and third in mortality worldwide. Recently, its comprehensive treatment has greatly progressed; however, the prognosis is still poor due to difficulties in early diagnosis, high recurrence and metastasis rates, and lack of specific treatment. The search for new molecular biological factors that target the early diagnosis of cancer, predict recurrence, evaluate treatment efficacy, and identify high-risk individuals and specific therapeutic targets during follow-up becomes a great urgent task. circSOX4 is upregulated in lung cancer and plays the role of oncogene. This study attempted to assess circSOX4's role in hepatocellular carcinoma (HCC). HCC tissues and cells were collected to measure circSOX4 level by qRT-PCR, cell behaviors by CCK-8 assay and Transwell assay, and relationship between circSOX4 and downstream targets by dual-luciferase gene assay and RIP. circSOX4 was upregulated in HCC tissue and cell lines, and its level was correlated with reduced patient survival. Interestingly, circSOX4 knockdown reduced HCC behaviors, glucose consumption, and lactate production. Furthermore, circSOX4 knockdown resulted in decreased in vivo tumor growth. circSOX4 was confirmed to target miR-218-5p, and the effect of circSOX4 downregulation on inhibiting tumor growth was diminished after miR-218-5p inhibition or YY1 overexpression in HCC cells. circSOX4 expression is closely associated with HCC through miR-218-5p and YY1-dependent pathways and may be a target and marker for HCC.

Pore Structure and Adsorption Characteristics of Maceral Groups: Insights from Centrifugal Flotation Experiment of Coals.

Coal has various types of macerals, which have different pore structures and adsorption properties that change with coal's thermal metamorphism. In-depth study of the characteristics of different coal macerals, especially the pore structure and adsorption properties, can better predict the coal reservoir gas storage capacity and migration ability. In this study, the sub-samples enriched in a specific maceral group with different coal ranks and particle sizes were obtained by centrifugal flotation experiments. Then, experiments containing low-temperature N2 isotherm adsorption (LT-N2GA), low-temperature CO2 isotherm adsorption (LT-CO2GA), and methane isothermal adsorption were carried out on the sub-samples to quantitatively analyze the evolution characteristics of pore structure and adsorption properties of different maceral groups. The results showed the following: (1) The separation effect of the light maceral groups by centrifugal flotation experiments increased with the decrease of particle sizes, which were treated with the heavy liquid of low and medium densities, while that of the heavy maceral groups had the relatively best separation effect in the particle sizes of 0.1-0.125 mm, which were treated with the heavy liquid of high densities. (2) The vitrinite-enriched samples had more ultra-micropores (mainly within the diameter range of 0.4-0.65 nm), while the inertinite enriched samples had more mesopores and transition pores (mainly within the diameter range of 40-50 nm). (3) For the low-rank coal, inertinite had more potential methane adsorption capacity. However, for the medium- and high-rank coal, vitrinite had more potential methane adsorption capacity. (4) For the low-rank coal, the adsorption potential and adsorption space increased with the increase of the inertinite content, while the adsorption potential, adsorption space, and surface free energy for the medium- and high-rank coal increased with the increase of vitrinite content. It is expected that the results can deepen the understanding about the gas storage capacity and migration ability and be used in the prevention of gas outburst and the reduction of carbon emission.

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.

Establishment and verification of a prognostic model of liver cancer by RNA-binding proteins based on the TCGA database.

Background: Globally, liver cancer is one of the most common malignant tumors and is the third leading cause of cancer deaths. RNA-binding protein (RBP) is a general term for a class of proteins that bind to RNA to regulate metabolic processes. The expression of RNA-binding proteins is related to the prognosis of liver cancer patients. Methods: The RBP gene expression data of liver cancer were extracted from the TCGA database. First, the differentially expressed RBPs (DE RBPs) were selected through enrichment analysis and volcano mapping. Then, the prognosis-related RBP genes were selected through single-factor Cox regression analysis. The key prognosis-related RBPs were further screened by multifactor Cox regression analysis, and a formula for the patient's risk coefficient was obtained. Finally, based on the patient's risk score, a nomogram was established and verified. Results: We extracted 374 cancer tissue samples and 50 normal tissue samples with the clinical information from each sample. Through enrichment analysis, we screened 208 upregulated RBPs and 122 downregulated RBPs. Prognosis-related high-risk genes were EEF1E1, NOP56, UPF3B, SF3B4, SMG5, CD3EAP, BRCA1, BARD1, XPO5, CSTF2, EZH2, EXO1, RRP12, PRIM1, LIN28B, NROB1 and TCOF1, and the low-risk genes were MRPL46, RCL1, MRPL54, CPEB3, IFIT5, PPARGC1A, EIF2AK4, SEPSECS, ACO1, SECISBP2 L and ZCCHC24. Further multivariate Cox regression analysis was performed on the prognosis-related RBPs, and the three key prognosis-related RBPs were screened out, which were BARD1, NR0B1 and EIF2AK4. A patient risk coefficient calculation formula was obtained: risk score = (1.207×BARD1 Exp) + (0.483×NR0B1 Exp) + (-0.720×EIF2AK4 Exp). Finally, a nomogram was established based on the risk score to predict the survival time of patients from 1 to 5 years. Conclusions: The nomogram has good predictive value for the survival time of liver cancer patients.

circRNA Hsa_circ_0020850 Silence Represses the Development of Lung Adenocarcinoma via Regulating miR-195-5p/IRS2 Axis.

BACKGROUND: The dysregulated circular RNAs (circRNAs) are relevant to lung adenocarcinoma development. Nevertheless, the function and mechanism of hsa_circ_0020850 (circ_0020850) in lung adenocarcinoma development are uncertain. METHODS: A total of 35 lung adenocarcinoma patients were recruited, and the tumor and normal tissue samples were harvested. A549 and PC-9 cells were exhibited for the experiments in vitro. circ_0020850, microRNA-195-5p (miR-195-5p) and insulin receptor substrate 2 (IRS2) abundances were detected via quantitative reverse transcription-polymerase chain reaction or Western blot. Cell proliferation, apoptosis, migration and invasion were measured via cell counting kit-8 (CCK8) assay, colony formation, flow cytometry, transwell and Western blot. The relationship between miR-195-5p and circ_0020850 or IRS2 was tested via dual-luciferase reporter analysis. The function of circ_0020850 on cell growth in vivo was measured via xenograft model. RESULTS: circ_0020850 expression was enhanced in lung adenocarcinoma tissues and cells. circ_0020850 silence suppressed cell proliferation, migration and invasion and facilitated apoptosis. miR-195-5p was targeted via circ_0020850, and its knockdown reversed the inhibitive effect of circ_0020850 silence on lung adenocarcinoma development. IRS2 was targeted via miR-195-5p, and miR-195-5p inhibited cell proliferation, migration and invasion and induced apoptosis via decreasing IRS2. circ_0020850 knockdown decreased IRS2 expression via regulating miR-195-5p. circ_0020850 down-regulation decreased lung adenocarcinoma xenograft tumor growth. CONCLUSION: circ_0020850 knockdown repressed lung adenocarcinoma cell proliferation, migration and invasion and promoted apoptosis via regulating miR-195-5p and IRS2.