Is volumetric modulated arc therapy with constant dose rate a valid option in radiation therapy for head and neck cancer patients?

Background

Intensity-modulated radiotherapy (IMRT) improves dose distribution in head and neck (HN) radiation therapy. Volumetric-modulated arc therapy (VMAT), a new form of IMRT, delivers radiation in single or multiple arcs, varying dose rates (VDR-VMAT) and gantry speeds, has gained considerable attention. Constant dose rate VMAT (CDR-VMAT) associated with a fixed gantry speed does not require a dedicated linear accelerator like VDR-VMAT. The present study explored the feasibility, efficiency and delivery accuracy of CDR-VMAT, by comparing it with IMRT and VDR-VMAT in treatment planning for HN cancer.

Specific pathogen detection using bioorthogonal chemistry and diagnostic magnetic resonance

The development of faster and more sensitive detection methods capable of identifying specific bacterial species and strains has remained a longstanding clinical challenge. Thus to date, the diagnosis of bacterial infections continues to rely on the performance of time-consuming microbiological cultures. Here, we demonstrate the use of bioorthogonal chemistry for magnetically labeling specific pathogens to enable their subsequent detection by nuclear magnetic resonance. Antibodies against a bacterial target of interest were first modified with trans-cyclooctene and then coupled to tetrazine-modified magnetic nanoprobes, directly on the bacteria. This labeling method was verified by surface plasmon resonance as well as by highly specific detection of Staphylococcus aureus using a miniaturized diagnostic magnetic resonance system. Compared to other copper-free bioorthogonal chemistries, the cycloaddition reaction reported here displayed faster kinetics and yielded higher labeling efficiency. Considering the short assay times and the portability of the necessary instrumentation, it is feasible that this approach could be adapted for clinical use in resource-limited settings.     

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.     

Lysosomal proteolysis in skeletal muscle

Lysosomal proteases are abundantly expressed in fetal muscles, but poorly represented in the adult skeletal muscles. The lysosomal proteolytic system is nonetheless stimulated in adult muscles in a variety of pathological conditions. Furthermore, recent investigations describe autophagosomes in muscle fibers in vitro and in vivo, and report myopathies with excessive autophagy. This review presents our current knowledge about the lysosomal proteolytic system and summarizes the evidences pertaining to the role of lysosomes and autophagosomes in muscle physiology and pathology.     

Alternative RNA structures formed during transcription depend on elongation rate and modify RNA processing

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Bcl-2 antiapoptotic proteins inhibit Beclin 1-dependent autophagy

Apoptosis and autophagy are both tightly regulated biological processes that play a central role in tissue homeostasis, development, and disease. The anti-apoptotic protein, Bcl-2, interacts with the evolutionarily conserved autophagy protein, Beclin 1. However, little is known about the functional significance of this interaction. Here, we show that wild-type Bcl-2 antiapoptotic proteins, but not Beclin 1 binding defective mutants of Bcl-2, inhibit Beclin 1-dependent autophagy in yeast and mammalian cells and that cardiac Bcl-2 transgenic expression inhibits autophagy in mouse heart muscle. Furthermore, Beclin 1 mutants that cannot bind to Bcl-2 induce more autophagy than wild-type Beclin 1 and, unlike wild-type Beclin 1, promote cell death. Thus, Bcl-2 not only functions as an antiapoptotic protein, but also as an antiautophagy protein via its inhibitory interaction with Beclin 1. This antiautophagy function of Bcl-2 may help maintain autophagy at levels that are compatible with cell survival, rather than cell death.     

The glycosylation-dependent interaction of perlecan core protein with LDL: implications for atherosclerosis

Perlecan is a major heparan sulfate (HS) proteoglycan in the arterial wall. Previous studies have linked it to atherosclerosis. Perlecan contains a core protein and three HS side chains. Its core protein has five domains (DI–DV) with disparate structures and DII is highly homologous to the ligand-binding portion of LDL receptor (LDLR). The functional significance of this domain has been unknown. Here, we show that perlecan DII interacts with LDL. Importantly, the interaction largely relies on O-linked glycans that are only present in the secreted DII. Among the five repeat units of DII, most of the glycosylation sites are from the second unit, which is highly divergent and rich in serine and threonine, but has no cysteine residues. Interestingly, most of the glycans are capped by the negatively charged sialic acids, which are critical for LDL binding. We further demonstrate an additive effect of HS and DII on LDL binding. Unlike LDLR, which directs LDL uptake through endocytosis, this study uncovers a novel feature of the perlecan LDLR-like DII in receptor-mediated lipoprotein retention, which depends on its glycosylation. Thus, perlecan glycosylation may play a role in the early LDL retention during the development of atherosclerosis.     

GABA-receptive microglia selectively sculpt developing inhibitory circuits

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Leucine limitation induces autophagy and activation of lysosome-dependent proteolysis in C2C12 myotubes through a mammalian target of rapamycin-independent signaling pathway

Loss of muscle mass usually characterizes different pathologies (sepsis, cancer, trauma) and also occurs during normal aging. One reason for muscle wasting relates to a decrease in food intake. This study addressed the role of leucine as a regulator of protein breakdown in mouse C2C12 myotubes and aimed to determine which cellular responses regulate the process. Determination of the rate of protein breakdown indicated that leucine is one key regulator of this process in myotubes because starvation for this amino acid is responsible for 30-40% of the total increase generated by total amino acid starvation. Leucine restriction rapidly accelerates the rate of protein breakdown (+11 to 15% (p < 0.001) after 1 h of starvation) in a dose-dependent manner. By using various inhibitors, evidence is provided that acceleration of protein catabolism results mainly from an induction of autophagy, activation of lysosome-dependent proteolysis, without modification of mRNA levels encoding the lysosomal cathepsins B, L, or D. Those results suggest that autophagy is an essential cellular response for increasing protein breakdown in muscle following food deprivation. Induction of autophagy precedes a decrease in global protein synthesis (-20% to -30% (p < 0.001)) that occurs after 3 h of leucine starvation. Inhibition of the mammalian target of rapamycin (mTOR) activity does not abolish the effect of leucine starvation and the level of phosphorylated ribosomal S6 protein is not affected by leucine withdrawal. These latter data provide clear evidence that the mTOR signaling pathway is not involved in the mediation of leucine effects on both protein synthesis and degradation in C2C12 myotubes.