Stable flow-induced expression of KLK10 inhibits endothelial inflammation and atherosclerosis.

Atherosclerosis preferentially occurs in arterial regions exposed to disturbed blood flow (d-flow), while regions exposed to stable flow (s-flow) are protected. The proatherogenic and atheroprotective effects of d-flow and s-flow are mediated in part by the global changes in endothelial cell (EC) gene expression, which regulates endothelial dysfunction, inflammation, and atherosclerosis. Previously, we identified kallikrein-related peptidase 10 (Klk10, a secreted serine protease) as a flow-sensitive gene in mouse arterial ECs, but its role in endothelial biology and atherosclerosis was unknown. Here, we show that KLK10 is upregulated under s-flow conditions and downregulated under d-flow conditions using in vivo mouse models and in vitro studies with cultured ECs. Single-cell RNA sequencing (scRNAseq) and scATAC sequencing (scATACseq) study using the partial carotid ligation mouse model showed flow-regulated Klk10 expression at the epigenomic and transcription levels. Functionally, KLK10 protected against d-flow-induced permeability dysfunction and inflammation in human artery ECs, as determined by NFκB activation, expression of vascular cell adhesion molecule 1 and intracellular adhesion molecule 1, and monocyte adhesion. Furthermore, treatment of mice in vivo with rKLK10 decreased arterial endothelial inflammation in d-flow regions. Additionally, rKLK10 injection or ultrasound-mediated transfection of Klk10-expressing plasmids inhibited atherosclerosis in Apoe-/- mice. Moreover, KLK10 expression was significantly reduced in human coronary arteries with advanced atherosclerotic plaques compared to those with less severe plaques. KLK10 is a flow-sensitive endothelial protein that serves as an anti-inflammatory, barrier-protective, and anti-atherogenic factor.

A therapeutic neutralizing antibody targeting receptor binding domain of SARS-CoV-2 spike protein.

Vaccines and therapeutics are urgently needed for the pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Here, we screen human monoclonal antibodies (mAb) targeting the receptor binding domain (RBD) of the viral spike protein via antibody library constructed from peripheral blood mononuclear cells of a convalescent patient. The CT-P59 mAb potently neutralizes SARS-CoV-2 isolates including the D614G variant without antibody-dependent enhancement effect. Complex crystal structure of CT-P59 Fab/RBD shows that CT-P59 blocks interaction regions of RBD for angiotensin converting enzyme 2 (ACE2) receptor with an orientation that is notably different from previously reported RBD-targeting mAbs. Furthermore, therapeutic effects of CT-P59 are evaluated in three animal models (ferret, hamster, and rhesus monkey), demonstrating a substantial reduction in viral titer along with alleviation of clinical symptoms. Therefore, CT-P59 may be a promising therapeutic candidate for COVID-19.

A smartphone metabolomics platform and its application to the assessment of cisplatin-induced kidney toxicity.

The application of smartphones to medical devices has been gaining attention in addressing accessibility and cost issues in healthcare, and the detection of medically relevant compounds has been demonstrated using customized smartphone hardware and/or software. Metabolomics, a newly rising omics field, has also spawned many medical applications but requires highly sophisticated and expensive equipment. Here, we describe a portable smartphone platform, built with readily available and affordable materials, that can perform all of the critical aspects of metabolomics. Excluding the smartphone itself, the total materials for the platform were obtained at less than US $20. For spectral data acquisition, the system utilized visible light (400-700 nm) and a built-in camera. All of the data processing, statistical analysis, and final-visualization components necessary for decision making were implemented in the smartphone platform. The platform is generally applicable as long as the analytes absorb visible light. We provide a proof-of-concept example wherein the metabolomics platform was applied to the assessment of cisplatin-induced kidney toxicity in a rat model, correctly predicting 7 out of 8 test samples.