Lack of Significant Elevation of Myeloid-Derived Suppressor Cells in Peripheral Blood of Chronically Hepatitis C Virus-Infected Individuals

Myeloid-derived suppressor cells (MDSC) are immature myeloid cells with immunosuppressive function. Compared to the level in healthy controls (HC), no elevation of MDSC in chronic hepatitis C (cHEP-C) patients was found, and there was no difference in MDSC based on genotype or viral load (P > 0.25). Moreover, MDSC of cHEP-C patients inhibited CD8 T cell function as efficiently as MDSC of HC did. Since we detected neither quantitative nor qualitative differences in MDSC of cHEP-C patients relative to those of HC, we postulate that MDSC in peripheral blood are most likely not significant regarding immune dysfunction in cHEP-C.     

Interleukin-1α Activity in Necrotic Endothelial Cells Is Controlled by Caspase-1 Cleavage of Interleukin-1 Receptor-2: IMPLICATIONS FOR ALLOGRAFT REJECTION*

Inflammation is a key instigator of the immune responses that drive atherosclerosis and allograft rejection. IL-1α, a powerful cytokine that activates both innate and adaptive immunity, induces vessel inflammation after release from necrotic vascular smooth muscle cells (VSMCs). Similarly, IL-1α released from endothelial cells (ECs) damaged during transplant drives allograft rejection. However, IL-1α requires cleavage for full cytokine activity, and what controls cleavage in necrotic ECs is currently unknown. We find that ECs have very low levels of IL-1α activity upon necrosis. However, TNFα or IL-1 induces significant levels of active IL-1α in EC necrotic lysates without alteration in protein levels. Increased activity requires cleavage of IL-1α by calpain to the more active mature form. Immunofluorescence and proximity ligation assays show that IL-1α associates with interleukin-1 receptor-2, and this association is decreased by TNFα or IL-1 and requires caspase activity. Thus, TNFα or IL-1 treatment of ECs leads to caspase proteolytic activity that cleaves interleukin-1 receptor-2, allowing IL-1α dissociation and subsequent processing by calpain. Importantly, ECs could be primed by IL-1α from adjacent damaged VSMCs, and necrotic ECs could activate neighboring normal ECs and VSMCs, causing them to release inflammatory cytokines and up-regulate adhesion molecules, thus amplifying inflammation. These data unravel the molecular mechanisms and interplay between damaged ECs and VSMCs that lead to activation of IL-1α and, thus, initiation of adaptive responses that cause graft rejection.     

Evaluation of <Emphasis Type="Italic">in silico</Emphasis> algorithms for use with ACMG/AMP clinical variant interpretation guidelines

Background

The American College of Medical Genetics and American College of Pathologists (ACMG/AMP) variant classification guidelines for clinical reporting are widely used in diagnostic laboratories for variant interpretation. The ACMG/AMP guidelines recommend complete concordance of predictions among all in silico algorithms used without specifying the number or types of algorithms. The subjective nature of this recommendation contributes to discordance of variant classification among clinical laboratories and prevents definitive classification of variants.

Results

Using 14,819 benign or pathogenic missense variants from the ClinVar database, we compared performance of 25 algorithms across datasets differing in distinct biological and technical variables. There was wide variability in concordance among different combinations of algorithms with particularly low concordance for benign variants. We also identify a previously unreported source of error in variant interpretation (false concordance) where concordant in silico predictions are opposite to the evidence provided by other sources. We identified recently developed algorithms with high predictive power and robust to variables such as disease mechanism, gene constraint, and mode of inheritance, although poorer performing algorithms are more frequently used based on review of the clinical genetics literature (2011–2017).

Conclusions

Our analyses identify algorithms with high performance characteristics independent of underlying disease mechanisms. We describe combinations of algorithms with increased concordance that should improve in silico algorithm usage during assessment of clinically relevant variants using the ACMG/AMP guidelines.

     

A graphical method for identifying the six types of non‐deep physiological dormancy in seeds

We present a new seed dormancy classification scheme for the non‐deep level of the class physiological dormancy (PD), which contains six types. Non‐deep PD is divided into two sublevels: one for seeds that exhibit a dormancy continuum (types 1, 2 and 3) and the other for those that do not exhibit a dormancy continuum (types 4, 5 and 6). Analysis of previous studies showed that different types of non‐deep PD also can be identified using a graphical method. Seeds with a dormancy (D) ? conditional dormancy (CD) ? non‐dormancy (ND) cycle have a low germination percentage in the early stages of CD, and during dormancy loss the germination capacity increases. However, seeds with a CD/ND (i.e. D→CD?ND) cycle germinate to a high percentage at a narrow range of temperatures in the early stages of CD. Cardinal temperatures for seeds with either a D/ND or a CD/ND cycle change during dormancy loss: the ceiling temperature increases in seeds with Type 1, the base temperature decreases in seeds with Type 2 and the base and ceiling temperatures decrease and increase, respectively, in seeds with Type 3. Criteria for distinguishing the six types of non‐deep PD and models of the temperature functions of seeds with types 1, 2 and 3 with both types of dormancy cycles are presented. The relevancy of our results to modelling the timing of weed seedling emergence is briefly discussed.