BET inhibition blocks inflammation-induced cardiac dysfunction and SARS-CoV-2 infection

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Optimal tuning of weighted kNN- and diffusion-based methods for denoising single cell genomics data

The analysis of single-cell genomics data presents several statistical challenges, and extensive efforts have been made to produce methods for the analysis of this data that impute missing values, address sampling issues and quantify and correct for noise. In spite of such efforts, no consensus on best practices has been established and all current approaches vary substantially based on the available data and empirical tests. The k-Nearest Neighbor Graph (kNN-G) is often used to infer the identities of, and relationships between, cells and is the basis of many widely used dimensionality-reduction and projection methods. The kNN-G has also been the basis for imputation methods using, e.g., neighbor averaging and graph diffusion. However, due to the lack of an agreed-upon optimal objective function for choosing hyperparameters, these methods tend to oversmooth data, thereby resulting in a loss of information with regard to cell identity and the specific gene-to-gene patterns underlying regulatory mechanisms. In this paper, we investigate the tuning of kNN- and diffusion-based denoising methods with a novel non-stochastic method for optimally preserving biologically relevant informative variance in single-cell data. The framework, Denoising Expression data with a Weighted Affinity Kernel and Self-Supervision (DEWÄKSS), uses a self-supervised technique to tune its parameters. We demonstrate that denoising with optimal parameters selected by our objective function (i) is robust to preprocessing methods using data from established benchmarks, (ii) disentangles cellular identity and maintains robust clusters over dimension-reduction methods, (iii) maintains variance along several expression dimensions, unlike previous heuristic-based methods that tend to oversmooth data variance, and (iv) rarely involves diffusion but rather uses a fixed weighted kNN graph for denoising. Together, these findings provide a new understanding of kNN- and diffusion-based denoising methods. Code and example data for DEWÄKSS is available at https://gitlab.com/Xparx/dewakss/-/tree/Tjarnberg2020branch.     

Rapid natriuretic action of aldosterone in the rat.

Rapid, nongenomic actions of aldosterone have been demonstrated in a number of cell types in vitro, including renal cell lines, but there remains little direct evidence that it is able to exert rapid effects on the kidney in the whole animal. Accordingly, the aim of this study was to determine whether aldosterone induces rapid changes in the renal handling of electrolytes or acid-base balance in the anesthetized rat. With the use of a servo-controlled fluid replacement system, spontaneous urine output by anesthetized male Sprague-Dawley rats was replaced with 2.5% dextrose. After a 3-h equilibration and a 1-h control period, rats were infused with aldosterone (42 pmol/min) or vehicle for 1 h. Aldosterone infusion induced a rapid (within 15 min) increase in sodium excretion that peaked at 0.24 +/- 0.08 compared with 0.04 +/- 0.01 micromol x min(-1) 100 x body weight(-1) (P = 0.041) in the vehicle-infused rats. This natriuresis was not associated with changes in glomerular filtration rate; urine flow rate; potassium, chloride, or bicarbonate excretion; or urine pH. The mechanisms involved are unclear, but because we have previously shown that aldosterone stimulates a rapid (4 min) increase in cAMP generation in the rat inner medullary collecting duct (IMCD) (Sheader EA, Wargent ET, Ashton N, and Balment RJ. J Endocrinol 175: 343-347, 2002), they could involve cAMP-mediated activation of the cystic fibrosis transmembrane conductance regulator chloride channel, which drives sodium secretion in the IMCD.     

Microencapsulation of nanoparticulate complexes of DNA with cationic lipids and polymers in pectin beads for targeted gene delivery

Nanoparticulate complexes of plasmid DNA (pDNA) with cationic liposomes/polymer, of approx 200 nm diameter, were encapsulated with a high degree of efficiency within calcium pectinate gel beads. Electron microscopy showed the DNA nanocomplexes to be evenly distributed throughout the gel matrix. Controlled release of pDNA-lipid nanocomplexes was achieved by the action of pectinase enzymes, whereas release of naked and polymer-complexed DNA was found to be more greatly influenced by the swelling behavior of the polysaccharide matrices in buffer alone. Physical degradation of pDNA within pectin beads was found to be accelerated during bead drying, most probably as a result of shear forces generated within the gel matrices by the evaporation of water. Plasmid complexation with cationic liposomes provided a greater degree of protection for the DNA during bead drying than complexation with cationic polymer, and was shown to successfully transfect cultured cells after release from the beads, via the action of pectinase. Observations concerning the physical stability of nanocomplexed pDNA, and its encapsulation within and release from pectin gel beads, are discussed with reference to the electrostatic interactions existing between the various components.