Inhibition of Lipoprotein-Associated Phospholipase A2 Ameliorates Inflammation and Decreases Atherosclerotic Plaque Formation in ApoE-Deficient Mice

Lipoprotein-associated phospholipase A2 (Lp-PLA2) is thought to play modulatory roles in the development of atherosclerosis. Here we evaluated the effects of a specific lp-PLA2 inhibitor on atherosclerosis in ApoE-deficient mice and its associated mechanisms.ApoE-deficient mice fed an atherogenic high-fat diet for 17 weeks were divided into two groups. One group was administered the specific lp-PLA2 inhibitor, darapladib (50 mg/kg/day; p.o.) daily for 6 weeks, while the control group was administered saline. We observed no differences in body weight and serum lipids levels between the two groups at the end of the dietary period. Notably, serum lp-PLA2 activity as well as hs-CRP (C-reactive protein) and IL-6 (Interleukin-6) levels were significantly reduced in the darapladib group, compared with the vehicle group, while the serum PAF (platelet-activating factor) levels were similar between the two groups. Furthermore, the plaque area through the arch to the abdominal aorta was reduced in the darapladib group. Another finding of interest was that the macrophage content was decreased while collagen content was increased in atherosclerotic lesions at the aortic sinus in the darapladib group, compared with the vehicle group. Finally, quantitative RT-PCR performed to determine the expression patterns of specific inflammatory genes at atherosclerotic aortas revealed lower expression of MCP-1, VCAM-1 and TNF-α in the darapladib group. inflammation and decreased plaque formation in ApoE-deficient mice, supporting an anti-atherogenic role during the progression of atherosclerosis

Expression of Kruppel-Like Factor KLF4 in Mouse Hair Follicle Stem Cells Contributes to Cutaneous Wound Healing

Kruppel-like factor KLF4 is a transcription factor critical for the establishment of the barrier function of the skin. Its function in stem cell biology has been recently recognized. Previous studies have revealed that hair follicle stem cells contribute to cutaneous wound healing. However, expression of KLF4 in hair follicle stem cells and the importance of such expression in cutaneous wound healing have not been investigated.Quantitative real time polymerase chain reaction (RT-PCR) analysis showed higher KLF4 expression in hair follicle stem cell-enriched mouse skin keratinocytes than that in control keratinocytes. We generated KLF4 promoter-driven enhanced green fluorescence protein (KLF4/EGFP) transgenic mice and tamoxifen-inducible KLF4 knockout mice by crossing KLF4 promoter-driven Cre recombinase fused with tamoxifen-inducible estrogen receptor (KLF4/CreER™) transgenic mice with KLF4(flox) mice. KLF4/EGFP cells purified from dorsal skin keratinocytes of KLF4/EGFP transgenic mice were co-localized with 5-bromo-2'-deoxyuridine (BrdU)-label retaining cells by flow cytometric analysis and immunohistochemistry. Lineage tracing was performed in the context of cutaneous wound healing, using KLF4/CreER™ and Rosa26RLacZ double transgenic mice, to examine the involvement of KLF4 in wound healing. We found that KLF4 expressing cells were likely derived from bulge stem cells. In addition, KLF4 expressing multipotent cells migrated to the wound and contributed to the wound healing. After knocking out KLF4 by tamoxifen induction of KLF4/CreER™ and KLF4(flox) double transgenic mice, we found that the population of bulge stem cell-enriched population was decreased, which was accompanied by significantly delayed cutaneous wound healing. Consistently, KLF4 knockdown by KLF4-specific small hairpin RNA in human A431 epidermoid carcinoma cells decreased the stem cell population and was accompanied by compromised cell migration.KLF4 expression in mouse hair bulge stem cells plays an important role in cutaneous wound healing. These findings may enable future development of KLF4-based therapeutic strategies aimed at accelerating cutaneous wound closure

Rationale and design of the screening of pulmonary hypertension in systemic lupus erythematosus (SOPHIE) study

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Barcoding T Cell Calcium Response Diversity with Methods for Automated and Accurate Analysis of Cell Signals (MAAACS)

International audienceWe introduce a series of experimental procedures enabling sensitive calcium monitoring in T cell populations by confocal video-microscopy. Tracking and post-acquisition analysis was performed using Methods for Automated and Accurate Analysis of Cell Signals (MAAACS), a fully customized program that associates a high throughput tracking algorithm, an intuitive reconnection routine and a statistical platform to provide, at a glance, the calcium barcode of a population of individual T-cells. Combined with a sensitive calcium probe, this method allowed us to unravel the heterogeneity in shape and intensity of the calcium response in T cell populations and especially in naive T cells, which display intracellular calcium oscillations upon stimulation by antigen presenting cells

Digital Gene Expression Analysis Based on Integrated De Novo Transcriptome Assembly of Sweet Potato [Ipomoea batatas (L.) Lam.]

Background: Sweet potato (Ipomoea batatas L. [Lam.]) ranks among the top six most important food crops in the world. It is widely grown throughout the world with high and stable yield, strong adaptability, rich nutrient content, and multiple uses. However, little is known about the molecular biology of this important non-model organism due to lack of genomic resources. Hence, studies based on high-throughput sequencing technologies are needed to get a comprehensive and integrated genomic resource and better understanding of gene expression patterns in different tissues and at various developmental stages. Methodology/Principal Findings: Illumina paired-end (PE) RNA-Sequencing was performed, and generated 48.7 million of 75 bp PE reads. These reads were de novo assembled into 128,052 transcripts ($100 bp), which correspond to 41.1 million base pairs, by using a combined assembly strategy. Transcripts were annotated by Blast2GO and 51,763 transcripts got BLASTX hits, in which 39,677 transcripts have GO terms and 14,117 have ECs that are associated with 147 KEGG pathways. Furthermore, transcriptome differences of seven tissues were analyzed by using Illumina digital gene expression (DGE) tag profiling and numerous differentially and specifically expressed transcripts were identified. Moreover, the expression characteristics of genes involved in viral genomes, starch metabolism and potential stress tolerance and insect resistance were also identified

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology.

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care