Single-Cell Transcriptomics Reveals the Cellular Heterogeneity of Cardiovascular Diseases

“A world in a wild flower, and a bodhi in a leaf,” small cells contain huge secrets. The vasculature is composed of many multifunctional cell subpopulations, each of which is involved in the occurrence and development of cardiovascular diseases. Single-cell transcriptomics captures the full picture of genes expressed within individual cells, identifies rare or de novo cell subpopulations, analyzes single-cell trajectory and stem cell or progenitor cell lineage conversion, and compares healthy tissue and disease-related tissue at single-cell resolution. Single-cell transcriptomics has had a profound effect on the field of cardiovascular research over the past decade, as evidenced by the construction of cardiovascular cell landscape, as well as the clarification of cardiovascular diseases and the mechanism of stem cell or progenitor cell differentiation. The classification and proportion of cell subpopulations in vasculature vary with species, location, genotype, and disease, exhibiting unique gene expression characteristics in organ development, disease progression, and regression. Specific gene markers are expected to be the diagnostic criteria, therapeutic targets, or prognostic indicators of diseases. Therefore, treatment of vascular disease still has lots of potentials to develop. Herein, we summarize the cell clusters and gene expression patterns in normal vasculature and atherosclerosis, aortic aneurysm, and pulmonary hypertension to reveal vascular heterogeneity and new regulatory factors of cardiovascular disease in the use of single-cell transcriptomics and discuss its current limitations and promising clinical potential

Emerging role of ubiquitin-specific protease 14 in oncogenesis and development of tumor: Therapeutic implication.

Ubiquitin (Ub) is a small protein that can be attached to substrate proteins to direct their degradation via the proteasome. Deubiquitinating enzymes (DUBs) reverse this process by removing ubiquitin from its substrate protein. Over the past few decades, ubiquitin-specific protease 14 (USP14), a member of the DUBs, has emerged as an important player in various types of cancers. In this article, we review and summarize biological function of USP14 in tumorigenesis and multiple signaling pathways. To determine its role in cancer, we analyzed USP14 gene expression across a panel of tumors, and discussed that it could serve as a novel bio-marker in several types of cancer. And recent contributions indicated that USP14 has been shown to act as a tumor-promoting gene via the AKT, NF-κB, MAPK pathways etc. Besides, drugs targeting USP14 have shown potential anti-tumor effect and clinical significance. We focus on recent studies that explore the link between USP14 and cancer, and further discuss USP14 as a novel target for cancer therapy

Emerging role of ubiquitin-specific protease 14 in oncogenesis and development of tumor: Therapeutic implication

Abstract(#br)Ubiquitin (Ub) is a small protein that can be attached to substrate proteins to direct their degradation via the proteasome. Deubiquitinating enzymes (DUBs) reverse this process by removing ubiquitin from its substrate protein. Over the past few decades, ubiquitin-specific protease 14 (USP14), a member of the DUBs, has emerged as an important player in various types of cancers. In this article, we review and summarize biological function of USP14 in tumorigenesis and multiple signaling pathways. To determine its role in cancer, we analyzed USP14 gene expression across a panel of tumors, and discussed that it could serve as a novel bio-marker in several types of cancer. And recent contributions indicated that USP14 has been shown to act as a tumor-promoting gene via the AKT, NF-κB, MAPK pathways etc. Besides, drugs targeting USP14 have shown potential anti-tumor effect and clinical significance. We focus on recent studies that explore the link between USP14 and cancer, and further discuss USP14 as a novel target for cancer therapy

Automated identification and quantification of myocardial inflammatory infiltration in digital histological images to diagnose myocarditis

This study aims to develop a new computational pathology approach that automates the identification and quantification of myocardial inflammatory infiltration in digital HE-stained images to provide a quantitative histological diagnosis of myocarditis.898 HE-stained whole slide images (WSIs) of myocardium from 154 heart transplant patients diagnosed with myocarditis or dilated cardiomyopathy (DCM) were included in this study. An automated DL-based computational pathology approach was developed to identify nuclei and detect myocardial inflammatory infiltration, enabling the quantification of the lymphocyte nuclear density (LND) on myocardial WSIs. A cutoff value based on the quantification of LND was proposed to determine if the myocardial inflammatory infiltration was present. The performance of our approach was evaluated with a five-fold cross-validation experiment, tested with an internal test set from the myocarditis group, and confirmed by an external test from a double-blind trial group. An LND of 1.02/mm2 could distinguish WSIs with myocarditis from those without. The accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) in the five-fold cross-validation experiment were 0.899 plus or minus 0.035, 0.971 plus or minus 0.017, 0.728 plus or minus 0.073 and 0.849 plus or minus 0.044, respectively. For the internal test set, the accuracy, sensitivity, specificity, and AUC were 0.887, 0.971, 0.737, and 0.854, respectively. The accuracy, sensitivity, specificity, and AUC for the external test set reached 0.853, 0.846, 0.858, and 0.852, respectively. Our new approach provides accurate and reliable quantification of the LND of myocardial WSIs, facilitating automated quantitative diagnosis of myocarditis with HE-stained images.Comment: 21 pages,5 figures,6 Tables, 25 reference

Aromatic Glucosinolate Biosynthesis Pathway in Barbarea vulgaris and its Response to Plutella xylostella Infestation

The inducibility of the glucosinolate resistance mechanism is an energy-saving strategy for plants, but whether induction would still be triggered by glucosinolate-tolerant Plutella xylostella (diamondback moth, DBM) after a plant had evolved a new resistance mechanism (e.g. saponins in Barbara vulgaris) was unknown. In B. vulgaris, aromatic glucosinolates derived from homo-phenylalanine are the dominate glucosinolates, but their biosynthesis pathway are unclear in this plant. In this study, we used G-type (pest-resistant) and P-type (pest-susceptible) B. vulgaris to compare glucosinolate levels and the expression profiles of their biosynthesis genes before and after infestation by DBM larvae. Two different stereoisomers of hydroxylated aromatic glucosinolates are dominant in G- and P-type B. vulgaris, respectively, and are induced by DBM. The transcripts of genes in the glucosinolate biosynthesis pathway and their corresponding transcription factors were identified from an Illumina dataset of G- and P-type B. vulgaris. Many genes involved or potentially involved in glucosinolate biosynthesis were induced in both plant types. The expression patterns of six DBM induced genes were validated by quantitative PCR (qPCR), while six long-fragment genes were validated by molecular cloning. The core structure biosynthetic genes showed high sequence similarities between the two genotypes. In contrast, the sequence identity of two apparent side chain modification genes, the SHO gene in the G-type and the RHO in P-type plants, showed only 77.50% identity in coding DNA sequences and 65.48% identity in deduced amino acid sequences. The homology to GS-OH in Arabidopsis, DBM induction of the transcript and a series of qPCR and glucosinolate analyses of G-type, P-type and F1 plants indicated that these genes control the production of S and R isomers of 2-hydroxy-2-phenylethyl glucosinolate. These glucosinolates were significantly induced by P. xylostella larvae in both the susceptiple P-type and the resistant G-type, even though saponins are the main DBM-resistance causing metabolites in G-type plants. Indol-3-ylmethylglucosinolate was induced in the G-type only. These data will aid our understanding of the biosynthesis and induction of aromatic glucosinolates at the molecular level and also increase our knowledge of the complex mechanisms underpinning defense induction in plants

In situ-constructed LixMoS2 with highly exposed interface boosting high-loading and long-life cathode for all-solid-state Li–S batteries

As the persistent concerns regarding sluggish reaction kinetics and insufficient conductivities of sulfur cathodes in all-solid-state Li–S batteries (ASSLSBs), numerous carbon additives and solid-state electrolytes (SSEs) have been incorporated into the cathode to facilitate ion/electron pathways around sulfur. However, this has resulted in a reduced capacity and decomposition of SSEs. Therefore, it is worth exploring neotype sulfur hosts with electronic/ionic conductivity in the cathode. Herein, we present a hybrid cathode composed of few-layered S/MoS2/C nanosheets (<5 layers) that exhibits high-loading and long-life performance without the need of additional carbon additives in advanced ASSLSBs. The multifunctional MoS2/C host exposes the abundant surface for intimate contacting sites, in situ-formed LixMoS2 during discharging as mixed ion/electron conductive network improves the S/Li2S conversion, and contributes extra capacity for the part of active materials. With a high active material content (S + MoS2/C) of 60 wt% in the S/MoS2/C/Li6PS5Cl cathode composite (the carbon content is only ~3.97 wt%), the S/MoS2/C electrode delivers excellent electrochemical performance, with a high reversible discharge capacity of 980.3 mAh g−1 (588.2 mAh g−1 based on the whole cathode weight) after 100 cycles at 100 mA g−1. The stable cycling performance is observed over 3500 cycles with a Coulombic efficiency of 98.5% at 600 mA g−1, while a high areal capacity of 10.4 mAh cm−2 is achieved with active material loading of 12.8 mg cm−2

Vegetable Genetic Resources in China

China is recognized as an important region for plant biodiversity based on its vast and historical collection of vegetable germplasm. The aim of this review is to describe the exploration status of vegetable genetic resources in China, including their collection, preservation, evaluation, and utilization. China has established a number of national-level vegetable genetic resources preservation units, including the National Mid-term Genebank for Vegetable Germplasm Resources, the National Germplasm Repository for Vegetatively-Propagated Vegetables, and the National Germplasm Repository for Aquatic Vegetables. In 2015, at least 36 000 accessions were collected and preserved in these units. In the past decade, 44 descriptors and data standards for different species have been published, and most accessions have been evaluated for screening the germplasms for specific important traits such as morphological characteristics, disease resistance, pest resistance, and stress tolerance. Moreover, the genetic diversity and evolution of some vegetable germplasms have been evaluated at the molecular level. Recently, more than 1 000 accessions were distributed to researchers and breeders each year by various means for vegetable research and production. However, additional wild-relative and abroad germplasms from other regions need to be collected and preserved in the units to expand genetic diversity. Furthermore, there is a need to utilize advanced techniques to better understand the background and genetic diversity of a wide range of vegetable genetic resources. This review will provide agricultural scientists’ insights into the genetic diversity in China and provide information on the distribution and potential utilization of these valuable genetic resources. Keywords: vegetable, genetic resource, preservation, evaluation, utilizatio

Machine learning-based microarray analyses indicate low-expression genes might collectively influence PAH disease.

Accurately predicting and testing the types of Pulmonary arterial hypertension (PAH) of each patient using cost-effective microarray-based expression data and machine learning algorithms could greatly help either identifying the most targeting medicine or adopting other therapeutic measures that could correct/restore defective genetic signaling at the early stage. Furthermore, the prediction model construction processes can also help identifying highly informative genes controlling PAH, leading to enhanced understanding of the disease etiology and molecular pathways. In this study, we used several different gene filtering methods based on microarray expression data obtained from a high-quality patient PAH dataset. Following that, we proposed a novel feature selection and refinement algorithm in conjunction with well-known machine learning methods to identify a small set of highly informative genes. Results indicated that clusters of small-expression genes could be extremely informative at predicting and differentiating different forms of PAH. Additionally, our proposed novel feature refinement algorithm could lead to significant enhancement in model performance. To summarize, integrated with state-of-the-art machine learning and novel feature refining algorithms, the most accurate models could provide near-perfect classification accuracies using very few (close to ten) low-expression genes