Differential effects of the second SARS-CoV-2 mRNA vaccine dose on T cell immunity in naive and COVID-19 recovered individuals

The rapid development of mRNA-based vaccines against the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) led to the design of accelerated vaccination schedules that have been extremely effective in naive individuals. While a two-dose immunization regimen with the BNT162b2 vaccine has been demonstrated to provide a 95% efficacy in naive individuals, the effects of the second vaccine dose in individuals who have previously recovered from natural SARS-CoV-2 infection has not been investigated in detail. In this study, we characterize SARS-CoV-2 spike-specific humoral and cellular immunity in naive and previously infected individuals during and after two doses of BNT162b2 vaccination. Our results demonstrate that, while the second dose increases both the humoral and cellular immunity in naive individuals, COVID-19 recovered individuals reach their peak of immunity after the first dose. These results suggests that a second dose, according to the current standard regimen of vaccination, may be not necessary in individuals previously infected with SARS-CoV-2.Research reported in this publication was supported in part by the National Cancer Institute of the NIH (5R01HD102614-02; R01CA249204 and R01CA248984) and an ISMMS seed fund to E.G. The authors gratefully acknowledge use of the services and facilities of the Tisch Cancer Institute supported by a NCI Cancer Center Support Grant (P30 CA196521). M.S. was supported by a NCI training grant (T32CA078207). This work was supported by an ISMMS seed fund to J.O.; Instituto de Salud Carlos III (COV20-00668) to R.C.R.; the Instituto de Salud Carlos III, Spanish Ministry of Science and Innovation (COVID-19 research call COV20/00181) co-financed by the European Development Regional Fund “A way to achieve Europe” to E.P.; the Instituto de Salud Carlos III, Spain (COV20/00170); the Government of Cantabria, Spain (2020UIC22-PUB-0019) to M.L.H.; the Instituto de Salud Carlos III (PI16CIII/00012) to P.P.; the Fondo Social Europeo e Iniciativa de Empleo Juvenil YEI (Grant PEJ2018-004557-A) to M.P.E.; and by REDInREN 016/009/009 ISCIII. This project has received funding from the European Union Horizon 2020 research and innovation programs VACCELERATE and INsTRuCT under grant agreements 101037867 and 860003.S

Histone deacetylase 9 promotes endothelial to mesenchymal transition and an unfavorable atherosclerotic plaque phenotype

Endothelial-mesenchymal transition (EndMT) is associated with various cardiovascular diseases and in particular with atherosclerosis and plaque instability. However, the molecular pathways that govern EndMT are poorly defined. Specifically, the role of epigenetic factors and histone deacetylases (HDACs) in controlling EndMT and the atherosclerotic plaque phenotype remains unclear. Here, we identified histone deacetylation, specifically that mediated by HDAC9 (a class IIa HDAC), as playing an important role in both EndMT and atherosclerosis. Using in vitro models, we found class IIa HDAC inhibition sustained the expression of endothelial proteins and mitigated the increase in mesenchymal proteins, effectively blocking EndMT. Similarly, ex vivo genetic knockout of Hdac9 in endothelial cells prevented EndMT and preserved a more endothelial-like phenotype. In vivo, atherosclerosis-prone mice with endothelial-specific Hdac9 knockout showed reduced EndMT and significantly reduced plaque area. Furthermore, these mice displayed a more favorable plaque phenotype, with reduced plaque lipid content and increased fibrous cap thickness. Together, these findings indicate that HDAC9 contributes to vascular pathology by promoting EndMT. Our study provides evidence for a pathological link among EndMT, HDAC9, and atherosclerosis and suggests that targeting of HDAC9 may be beneficial for plaque stabilization or slowing the progression of atherosclerotic disease

Spaceflight modulates gene expression in the whole blood of astronauts

abstract: Astronauts are exposed to a unique combination of stressors during spaceflight, which leads to alterations in their physiology and potentially increases their susceptibility to disease, including infectious diseases. To evaluate the potential impact of the spaceflight environment on the regulation of molecular pathways mediating cellular stress responses, we performed a first-of-its-kind pilot study to assess spaceflight-related gene-expression changes in the whole blood of astronauts. Using an array comprised of 234 well-characterized stress-response genes, we profiled transcriptomic changes in six astronauts (four men and two women) from blood preserved before and immediately following the spaceflight. Differentially regulated transcripts included those important for DNA repair, oxidative stress, and protein folding/degradation, including HSP90AB1, HSP27, GPX1, XRCC1, BAG-1, HHR23A, FAP48, and C-FOS. No gender-specific differences or relationship to number of missions flown was observed. This study provides a first assessment of transcriptomic changes occurring in the whole blood of astronauts in response to spaceflight.The final version of this article, as published in Npj Microgravity, can be viewed online at: http://www.nature.com/articles/npjmgrav20163

Neural Network Prediction of ICU Length of Stay Following Cardiac Surgery Based on Pre-Incision Variables

<div><p>Background</p><p>Advanced predictive analytical techniques are being increasingly applied to clinical risk assessment. This study compared a neural network model to several other models in predicting the length of stay (LOS) in the cardiac surgical intensive care unit (ICU) based on pre-incision patient characteristics.</p><p>Methods</p><p>Thirty six variables collected from 185 cardiac surgical patients were analyzed for contribution to ICU LOS. The Automatic Linear Modeling (ALM) module of IBM-SPSS software identified 8 factors with statistically significant associations with ICU LOS; these factors were also analyzed with the Artificial Neural Network (ANN) module of the same software. The weighted contributions of each factor (“trained” data) were then applied to data for a “new” patient to predict ICU LOS for that individual.</p><p>Results</p><p>Factors identified in the ALM model were: use of an intra-aortic balloon pump; O₂ delivery index; age; use of positive cardiac inotropic agents; hematocrit; serum creatinine ≥ 1.3 mg/deciliter; gender; arterial pCO₂. The r² value for ALM prediction of ICU LOS in the initial (training) model was 0.356, p <0.0001. Cross validation in prediction of a “new” patient yielded r² = 0.200, p <0.0001. The same 8 factors analyzed with ANN yielded a training prediction r² of 0.535 (p <0.0001) and a cross validation prediction r² of 0.410, p <0.0001. Two additional predictive algorithms were studied, but they had lower prediction accuracies. Our validated neural network model identified the upper quartile of ICU LOS with an odds ratio of 9.8(p <0.0001).</p><p>Conclusions</p><p>ANN demonstrated a 2-fold greater accuracy than ALM in prediction of observed ICU LOS. This greater accuracy would be presumed to result from the capacity of ANN to capture nonlinear effects and higher order interactions. Predictive modeling may be of value in early anticipation of risks of post-operative morbidity and utilization of ICU facilities.</p></div

CXCR4 and CXCR7 play distinct roles in cardiac lineage specification and pharmacologic β-adrenergic response

CXCR4 and CXCR7 are prominent G protein-coupled receptors (GPCRs) for chemokine stromal cell-derived factor-1 (SDF-1/CXCL12). This study demonstrates that CXCR4 and CXCR7 induce differential effects during cardiac lineage differentiation and β-adrenergic response in human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs). Using lentiviral vectors to ablate CXCR4 and/or CXCR7 expression, hiPSC-CMs were tested for phenotypic and functional properties due to gene knockdown. Gene expression and flow cytometry confirmed the pluripotent and cardiomyocyte phenotype of undifferentiated and differentiated hiPSCs, respectively. Although reduction of CXCR4 and CXCR7 expression resulted in a delayed cardiac phenotype, only knockdown of CXCR4 delayed the spontaneous beating of hiPSC-CMs. Knockdown of CXCR4 and CXCR7 differentially altered calcium transients and β-adrenergic response in hiPSC-CMs. In engineered cardiac tissues, depletion of CXCR4 or CXCR7 had opposing effects on developed force and chronotropic response to β-agonists. This work demonstrates distinct roles for the SDF-1/CXCR4 or CXCR7 network in hiPSC-derived ventricular cardiomyocyte specification, maturation and function

ANN Parameter Weights.

<p>The prediction weights generated by the neural network for each interaction among the 8 pre-incision factors ("input layer") and the 4 nodes ("hidden layer"), and the output weights of each node to the prediction of ICU length of stay; bias weights are also contributed from the input layer and the hidden layer.</p

The architecture of the typical neural network utilized in the SPSS Artificial Neural Network module for the 8 pre-incision factors.

<p>The architecture of the typical neural network utilized in the SPSS Artificial Neural Network module for the 8 pre-incision factors.</p

Neutrophil derived CSF1 induces macrophage polarization and promotes transplantation tolerance

The colony-stimulating factor 1 (CSF1) regulates the differentiation and function of tissue macrophages and determines the outcome of the immune response. The molecular mechanisms behind CSF1-mediated macrophage development remain to be elucidated. Here we demonstrate that neutrophil-derived CSF1 controls macrophage polarization and proliferation, which is necessary for the induction of tolerance. Inhibiting neutrophil production of CSF1 or preventing macrophage proliferation, using targeted nanoparticles loaded with the cell cycle inhibitor simvastatin, abrogates the induction of tolerance. These results provide new mechanistic insights into the developmental requirements of tolerogenic macrophages and identify CSF1 producing neutrophils as critical regulators of the immunological response

Pre-incision variables chosen for predictive analytical modeling from a data base of 185 cardiac surgical patients.

<p>Pre-incision variables chosen for predictive analytical modeling from a data base of 185 cardiac surgical patients.</p

The Final Decision Tree Model that was Assessed for Prediction of ICU LOS.

<p>The Final Decision Tree Model that was Assessed for Prediction of ICU LOS.</p