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Age is an independent risk factor for atrial fibrillation (AF), and curcumin can delay aging related disease through reducing oxidative stress and inflammation. However, its target in aging-related AF remains unclear. Transfer RNA-derived small RNA (tsRNA) is a novel short non-coding RNA (sncRNA), and exerts a potential regulatory function in aging. This study was to explore the therapeutic targets of curcumin in atrium of aged mice by PANDORA-seq. Aged mice (18 month) were treated with curcumin (100 mg/kg). Rapid transjugular atrial pacing was performed to observe AF inducibility. SA-β-gal staining, reactive oxygen species (ROS) detection and qRT-PCR were used to assess the degree of aging and oxidative stress/inflammation levels. PANDORA-seq was performed to reveal the differentially expressed sncRNAs in the atrium of mice. The results showed that curcumin reduced the susceptibility AF of aged mice by improving aging-related atrial fibrosis. Compared to young mice (5 month) group, aged mice yielded 473 significantly altered tsRNA sequences, while 947 tsRNA sequences were significantly altered after treated with curcumin. Enrichment analysis revealed that the target genes were mainly related to DNA damage and protein modification. Compared with the 5 month group, the expression levels of mature-mt_tRNA-Val-TAC_CCA_end, mature-mt_tRNA-Glu-TTC_CCA_end, and mature-tRNA-Asp-GTC_CCA_end were up-regulated in the 18 month group, while the expression of mature-mt_tRNA-Thr-TGT_5_end was down-regulated. This trend was reversed in the 18 month + curcumin group. Increased cellular ROS levels, inflammation expression and senescence in aged mice atrium were improved by the down-regulation of mature-mt_tRNA-Val-TAC_CCA_end. In conclusion, our findings identified mature-mt_tRNA-Val-TAC_CCA_end participated in the mechanism of aging-related atrial fibrosis, providing new intervention target of aging-related AF.

Abstract The occurrence and progression of tumors can be established through a complex interplay among tumor cells undergoing epithelial-mesenchymal transition (EMT), invasive factors and immune cells. In this study, we employed single-cell RNA sequencing (scRNA-seq) and spatially resolved transcriptomics (ST) to evaluate the pseudotime trajectory and spatial interactive relationship between EMT-invasive malignant tumors and immune cells in primary colorectal cancer (CRC) tissues at different stages (stage I/II and stage III with tumor deposit). Our research characterized the spatiotemporal relationship among different invasive tumor programs by constructing pseudotime endpoint-EMT-invasion tumor programs (EMTPs) located at the edge of ST, utilizing evolution trajectory analysis integrated with EMT-invasion genes. Strikingly, the invasive and expansive process of tumors undergoes remarkable spatial reprogramming of regulatory and immunosuppressive cells, such as myeloid-derived suppressor cells (MDSCs), tumor-associated macrophages (TAMs), regulatory T cells (Treg), and exhausted T cells (Tex). These EMTP-adjacent cell are linked to EMT-related invasion genes, especially the C-X-C motif ligand 1 (CXCL1) and CXCL8 genes that are important for CRC prognosis. Interestingly, the EMTPs in stage I mainly produce an inflammatory margin invasive niche, while the EMTPs in stage III tissues likely produce a hypoxic pre-invasive niche. Our data demonstrate the crucial role of regulatory and immunosuppressive cells in tumor formation and progression of CRC. This study provides a framework to delineate the spatiotemporal invasive niche in CRC samples. Graphical Abstract

Plasminogen activator inhibitor-1 (PAI-1), a key regulator of the fibrinolytic system, is also intimately involved in the fibrosis. Although PAI-1 may be involved in the occurrence of atrial fibrillation (AF) and thrombosis in the elderly, but whether it participated in aging-related atrial fibrosis and the detailed mechanism is still unclear. We compared the transcriptomics data of young (passage 4) versus senescent (passage 14) human atrial fibroblasts and found that PAI-1 was closely related to aging-related fibrosis. Aged mice and senescent human and mouse atrial fibroblasts underwent electrophysiological and biochemical studies. We found that p300, p53, and PAI-1 protein expressions were increased in the atrial tissue of aged mice and senescent human and mouse atrial fibroblasts. Curcumin or C646 (p300 inhibitor), or p300 knockdown inhibited the expression of PAI-1 contributing to reduced atrial fibroblasts senescence, atrial fibrosis, and the AF inducibility. Furthermore, p53 knockdown decreased the protein expression of PAI-1 and p21 in senescent human and mouse atrial fibroblasts. Our results suggest that p300/p53/PAI-1 signaling pathway participates in the mechanism of atrial fibrosis induced by aging, which provides new sights into the treatment of elderly AF.

Abstract Background Understanding the host genetic architecture and viral immunity contributes to the development of effective vaccines and therapeutics for controlling the COVID-19 pandemic. Alterations of immune responses in peripheral blood mononuclear cells play a crucial role in the detrimental progression of COVID-19. However, the effects of host genetic factors on immune responses for severe COVID-19 remain largely unknown. Methods We constructed a computational framework to characterize the host genetics that influence immune cell subpopulations for severe COVID-19 by integrating GWAS summary statistics (N = 969,689 samples) with four independent scRNA-seq datasets containing healthy controls and patients with mild, moderate, and severe symptom (N = 606,534 cells). We collected 10 predefined gene sets including inflammatory and cytokine genes to calculate cell state score for evaluating the immunological features of individual immune cells. Results We found that 34 risk genes were significantly associated with severe COVID-19, and the number of highly expressed genes increased with the severity of COVID-19. Three cell subtypes that are CD16+monocytes, megakaryocytes, and memory CD8+T cells were significantly enriched by COVID-19-related genetic association signals. Notably, three causal risk genes of CCR1, CXCR6, and ABO were highly expressed in these three cell types, respectively. CCR1 +CD16+monocytes and ABO + megakaryocytes with significantly up-regulated genes, including S100A12, S100A8, S100A9, and IFITM1, confer higher risk to the dysregulated immune response among severe patients. CXCR6 + memory CD8+ T cells exhibit a notable polyfunctionality including elevation of proliferation, migration, and chemotaxis. Moreover, we observed an increase in cell-cell interactions of both CCR1 + CD16+monocytes and CXCR6 + memory CD8+T cells in severe patients compared to normal controls among both PBMCs and lung tissues. The enhanced interactions of CXCR6 + memory CD8+T cells with epithelial cells facilitate the recruitment of this specific population of T cells to airways, promoting CD8+T cell-mediated immunity against COVID-19 infection. Conclusions We uncover a major genetics-modulated immunological shift between mild and severe infection, including an elevated expression of genetics-risk genes, increase in inflammatory cytokines, and of functional immune cell subsets aggravating disease severity, which provides novel insights into parsing the host genetic determinants that influence peripheral immune cells in severe COVID-19.

A TM-mode-pass polarization rotator and power divider with an arbitrary beam-splitting ratio constructed by an adiabatic taper, a spatial mode order convertor and a multi-mode interferometer (MMI) is proposed on the silicon-on insulator (SOI) platform. Both arbitrary power splitting and polarization selection-rotation can be realized in this single device. The measurements show that a continuously adjustable beam-splitting ratio from 1:99 to 99:1 within a 33.2 mW power consumption from 1520–1580 nm has been realized for the proposed device.

Abstract Background Primary biliary cholangitis (PBC) is a classical autoimmune disease, which is highly influenced by genetic determinants. Many genome-wide association studies (GWAS) have reported that numerous genetic loci were significantly associated with PBC susceptibility. However, the effects of genetic determinants on liver cells and its immune microenvironment for PBC remain unclear. Results We constructed a powerful computational framework to integrate GWAS summary statistics with scRNA-seq data to uncover genetics-modulated liver cell subpopulations for PBC. Based on our multi-omics integrative analysis, 29 risk genes including ORMDL3, GSNK2B, and DDAH2 were significantly associated with PBC susceptibility. By combining GWAS summary statistics with scRNA-seq data, we found that cholangiocytes exhibited a notable enrichment by PBC-related genetic association signals (Permuted P

Limited by large transmission loss, the development of transverse electric (TE) mode silicon-on-insulator (SOI) based on-chip long length chirped grating waveguide faces many difficulties now. To overcome this problem, multi-mode waveguide with a measured transmission loss of 0.7 dB/cm is applied in this paper, and a chirped spiral Bragg grating waveguide (SBGW) is proposed and experimentally demonstrated. The length of the chirped SBGW reaches 2.7 cm, which is the longest SOI based grating reported so far. The total group delay is measured to be 628 ps, with a structure size of only 0.3 mm2 due to the application of spiral configuration. The slope of the linear dispersion is -27.7 ps/nm. This integrated chirped SBGW shows great compatibility with frequently used TE mode SOI devices and has great potential for applications in microwave photonics requiring dispersion control.

The accumulation of somatic driver mutations in the human genome enables cells to gradually acquire a growth advantage and contributes to tumor development. Great efforts on protein-coding cancer drivers have yielded fruitful discoveries and clinical applications. However, investigations on cancer drivers in non-coding regions, especially long non-coding RNAs (lncRNAs), are extremely scarce due to the limitation of functional understanding. Thus, to identify driver lncRNAs integrating multi-omics data in human cancers, we proposed a computational framework, DriverLncNet, which dissected the functional impact of somatic copy number alteration (CNA) of lncRNAs on regulatory networks and captured key functional effectors in dys-regulatory networks. Applying it to 5 cancer types from The Cancer Genome Atlas (TCGA), we portrayed the landscape of 117 driver lncRNAs and revealed their associated cancer hallmarks through their functional effectors. Moreover, lncRNA RP11-571M6.8 was detected to be highly associated with immunotherapeutic targets (PD-1, PD-L1, and CTLA-4) and regulatory T cell infiltration level and their markers (IL2RA and FCGR2B) in glioblastoma multiforme, highlighting its immunosuppressive function. Meanwhile, a high expression of RP11-1020A11.1 in bladder carcinoma was predictive of poor survival independent of clinical characteristics, and CTD-2256P15.2 in lung adenocarcinoma responded to the sensitivity of methyl ethyl ketone (MEK) inhibitors. In summary, this study provided a framework to decipher the mechanisms of tumorigenesis from driver lncRNA level, established a new landscape of driver lncRNAs in human cancers, and offered potential clinical implications for precision oncology. Keywords: cancer drivers, long non-coding RNAs, copy number alterations, cancer hallmarks, immunosuppression

Substantial cancer genome sequencing efforts have discovered many important driver genes contributing to tumorigenesis. However, very little is known about the genetic alterations of long non‐coding RNAs (lncRNAs) in cancer. Thus, there is a need for systematic surveys of driver lncRNAs. Through integrative analysis of 5918 tumors across 11 cancer types, we revealed that lncRNAs have undergone dramatic genomic alterations, many of which are mutually exclusive with well‐known cancer genes. Using the hypothesis of functional redundancy of mutual exclusivity, we developed a computational framework to identify driver lncRNAs associated with different cancer hallmarks. Applying it to pan‐cancer data, we identified 378 candidate driver lncRNAs whose genomic features highly resemble the known cancer driver genes (e.g. high conservation and early replication). We further validated the candidate driver lncRNAs involved in ‘Tissue Invasion and Metastasis’ in lung adenocarcinoma and breast cancer, and also highlighted their potential roles in improving clinical outcomes. In summary, we have generated a comprehensive landscape of cancer candidate driver lncRNAs that could act as a starting point for future functional explorations, as well as the identification of biomarkers and lncRNA‐based target therapy.

Smart grids are the developmental trend of power systems and they have attracted much attention all over the world. Due to their complexities, and the uncertainty of the smart grid and high volume of information being collected, artificial intelligence techniques represent some of the enabling technologies for its future development and success. Owing to the decreasing cost of computing power, the profusion of data, and better algorithms, AI has entered into its new developmental stage and AI 2.0 is developing rapidly. Deep learning (DL), reinforcement learning (RL) and their combination-deep reinforcement learning (DRL) are representative methods and relatively mature methods in the family of AI 2.0. This article introduces the concept and status quo of the above three methods, summarizes their potential for application in smart grids, and provides an overview of the research work on their application in smart grids.

Characterizing functions of long noncoding RNAs (lncRNAs) remains a major challenge, mostly due to the lack of lncRNA-involved regulatory relationships. A wide array of genome-wide expression profiles generated by gene perturbation have been widely used to capture causal links between perturbed genes and response genes. Through annotating >600 gene perturbation profiles, over 354,000 causal relationships between perturbed genes and lncRNAs were identified. This large-scale resource of causal relations inspired us to develop a novel computational approach LnCAR for inferring lncRNAs' functions, which showed a higher accuracy than the co-expression based approach. By application of LnCAR to the cancer hallmark processes, we identified 38 lncRNAs involved in distinct carcinogenic processes. The “activating invasion & metastasis” related lncRNAs were strongly associated with metastatic progression in various cancer types and could act as a predictor of cancer metastasis. Meanwhile, the “evading immune destruction” related lncRNAs showed significant associations with immune infiltration of various immune cells and, importantly, can predict response to anti-PD-1 immunotherapy, suggesting their potential roles as biomarkers for immune therapy. Taken together, our approach provides a novel way to systematically reveal functions of lncRNAs, which will be helpful for further experimental exploration and clinical translational research of lncRNAs. Keywords: lncRNA, Function, Gene perturbation, Cancer, Immunotherapy

Engineered organoids by sequential introduction of key mutations could help modeling the dynamic cancer progression. However, it remains difficult to determine gene paths which were sufficient to capture cancer behaviors and to broadly explain cancer mechanisms. Here, as a case study of colorectal cancer (CRC), functional and dynamic characterizations of five types of engineered organoids with different mutation combinations of five driver genes (APC, SMAD4, KRAS, TP53, and PIK3CA) showed that sequential introductions of all five driver mutations could induce enhanced activation of more hallmark signatures, tending to cancer. Comparative analysis of engineered organoids and corresponding CRC tissues revealed sequential introduction of key mutations could continually shorten the biological distance from engineered organoids to CRC tissues. Nevertheless, there still existed substantial biological gaps between the engineered organoid even with five key mutations and CRC samples. Thus, we proposed an integrative strategy to prioritize gene cascading paths for shrinking biological gaps between engineered organoids and CRC tissues. Our results not only recapitulated the well-known adenoma–carcinoma sequence model (e.g., AKST-organoid with driver mutations in APC, KRAS, SMAD4, and TP53), but also provided potential paths for delineating alternative pathogenesis underlying CRC populations (e.g., A-organoid with APC mutation). Our strategy also can be applied to both organoids with more mutations and other cancers, which can improve and innovate mechanism across cancer patients for drug design and cancer therapy.

Abstract Background Sudden cardiac death (SCD) induced by malignant ventricular tachycardia (MVT) among young adults with right ventricular cardiomyopathy/dysplasia (ARVC/D) is a devastating event. Parts of ARVC/D patients have a mutation in genes encoding components of cardiac desmosomes, such as desmoglein-2 (DSG2), plakophilin-2 and desmoplakin. Case presentation Here we report a potentially pathogenic mutation in the DSG2 gene, which was identified in a family with ARVC/D using Whole Exome Sequencing (WES) and Sanger Sequencing. In all, Patient III:1 with ARVC/D carried the compound heterozygous mutations of DSG2 p.F531C and KCNE5 p.D92E/E93X, which were both inherited from her mother (II:2), who died of SCD. Carriers of DSG2p.F531C showed various phenotypes, such as ARVC/D, SCD, MVT and dilated cardiomyopathy. For III:1, there were significant low-voltage regions in the inferior-apical, inferior-lateral wall of the right ventricular epicardium and outflow tracts of the right ventricle. Under the guidance of a three-dimensional mapping system, MVT was successfully ablated with an epicardial–endocardial approach targeting for late, double or fragmental potentials after implantable cardioverter-defibrillator (ICD) electrical storms. No VT recurrence was observed during the one year of follow-up. Conclusions When coexisting with heterozygous KCNE5 p.D92E/E93X, heterozygous DSG2 p.F531C as a genetic background was found to predispose to ARVC/D, SCD and MVT, which were successfully ablated using an epicardial–endocardial approach.

Background: Immune checkpoint blockade (ICB) therapy has yielded successful clinical responses in treatment of a minority of patients in certain cancer types. Substantial efforts were made to establish biomarkers for predicting responsiveness to ICB. However, the systematic assessment of these ICB response biomarkers remains insufficient. Methods: We collected 22 transcriptome-based biomarkers for ICB response and constructed multiple benchmark datasets to evaluate the associations with clinical response, predictive performance, and clinical efficacy of them in pre-treatment patients with distinct ICB agents in diverse cancers. Results: Overall, “Immune-checkpoint molecule” biomarkers PD-L1, PD-L2, CTLA-4 and IMPRES and the “Effector molecule” biomarker CYT showed significant associations with ICB response and clinical outcomes. These immune-checkpoint biomarkers and another immune effector IFN-gamma presented predictive ability in melanoma, urothelial cancer (UC) and clear cell renal-cell cancer (ccRCC). In non-small cell lung cancer (NSCLC), only PD-L2 and CTLA-4 showed preferable correlation with clinical response. Under different ICB therapies, the top-performing biomarkers were usually mutually exclusive in patients with anti-PD-1 and anti-CTLA-4 therapy, and most of biomarkers presented outstanding predictive power in patients with combined anti-PD-1 and anti-CTLA-4 therapy. Conclusions: Our results show these biomarkers had different performance in predicting ICB response across distinct ICB agents in diverse cancers.

With the development of UHV and cross-regional distribution network, the operation and inspection of electric transmission and transformation equipment need to use big data and other new technologies to build a smart grid operation and inspection system, in order to better support the operation and inspection business. This paper analyzes the new development situation of UHV and trans-area power grid and the demand of smart grid operation and inspection service under the new situation. Combining big data analysis technology with production command and management practice, based on data and business requirements, this paper puts forward the data architecture of intelligent operation and inspection system according to big data technology, gives the technical framework and technology selection of intelligent operation and inspection system, then analyzes the application framework of intelligent operation and inspection service. The whole architecture of intelligent operation and inspection system is proposed, which provides better support for the development and application of intelligent operation and inspection system through the key architecture design. It has far-reaching application value and broad application prospect.

BACKGROUND: Glomerulosclerosis correlates with reduction in podocyte number that occurs through mechanisms which include apoptosis. Podocyte injury or podocyte loss in the renal glomerulus has been proposed as the crucial mechanism in the development of glomerulosclerosis. However, the mechanism by which podocytes respond to injury is poorly understood. TNF and TNF receptor superfamilies are important in the pathogenesis of podocyte injury and apoptosis. The ligand of receptor activator of NF-kappaB (RANKL) and receptor activator of NF-kappaB (RANK) are members of the TNF and receptor superfamilies. We investigated whether RANK-RANKL is a receptor-ligand complex for podocytes responding to injury. METHODOLOGY/PRINCIPAL FINDINGS: In this study, RANKL and RANK were examined in human podocyte diseases and a rat model of puromycin aminonucleoside nephrosis (PAN). Compared with controls, RANK and RANKL were increased in both human podocyte diseases and the rat PAN model; double immunofluorescence staining revealed that RANK protein expression was mainly attributed to podocytes. Immunoelectron microscopy showed that RANK was localized predominantly at the top of the foot process membrane and the cytoplasm of rat podocyte. In addition, RANK was upregulated in mouse podocytes in vitro after injury induced by puromycin aminonucleoside (PA). Knockdown of RANK expression by small interference RNA (siRNA) exacerbated podocyte apoptosis induced by PA. However, RANKL inhibited significantly the apoptosis of podocytes induced by PA. CONCLUSIONS/SIGNIFICANCE: These findings suggest the increase in RANK-RANKL expression is a response to podocyte injury, and RANK-RANKL may be a novel receptor-ligand complex for the survival response during podocyte injury.

Human organoids recapitulate the cell type diversity and function of their primary organs holding tremendous potentials for basic and translational research. Advances in single-cell RNA sequencing (scRNA-seq) technology and genome-wide association study (GWAS) have accelerated the biological and therapeutic interpretation of traitrelevant cell types or states. Here, we constructed a computational framework to integrate atlas-level organoid scRNA-seq data, GWAS summary statistics, expression quantitative trait loci, and gene-drug interaction data for distinguishing critical cell populations and drug targets relevant to coronavirus disease 2019 (COVID-19) severity. We found that 39 cell types across eight kinds of organoids were significantly associated with COVID-19 outcomes. Notably, subset of lung mesenchymal stem cells increased proximity with fibroblasts predisposed to repair COVID-19-damaged lung tissue. Brain endothelial cell subset exhibited significant associations with severe COVID-19, and this cell subset showed a notable increase in cell-to-cell interactions with other brain cell types, including microglia. We repurposed 33 druggable genes, including IFNAR2, TYK2, and VIPR2, and their interacting drugs for COVID-19 in a cell-type-specific manner. Overall, our results showcase that host genetic determinants have cellular-specific contribution to COVID-19 severity, and identification of cell type-specific drug targets may facilitate to develop effective therapeutics for treating severe COVID-19 and its complications. [ABSTRACT FROM AUTHOR]