QT interval dynamics in patients with ST-elevation MI

BackgroundAn association between excessively prolonged QT and ventricular arrhythmia in patients with ST-elevation myocardial infarction has been described; however, the QT dynamics, characterization, and long-term predictive value are not well known.ObjectiveTo characterize QT interval dynamics in patients undergoing ST elevation myocardial infarction (STEMI) and determine its association with mortality.MethodsA retrospective analysis of 4,936 consecutive patients, hospitalized for STEMI between 01/2013–12/2021. Patients with less than three electrocardiograms (ECGs) during index hospitalization were excluded. Baseline demographics, cardiovascular history, clinical risk factors, treatment measures, laboratory results, and mortality data were retrieved from the hospital’s electronic medical records.ResultsWe included 1,054 patients and 5,021 ECGs in our cohort with a median follow-up of 6 years [interquartile range (IQR) 4.3–7.4 years]. The QT was longer in women in comparison to men (428.6 ms ± 33.4 versus 419.8 ms ± 32.52, P-value = 0.001). QT prolongation was greater in females, elderly patients, and patients with STEMI caused by occlusion of the left anterior descending (LAD) coronary artery. We determined QT cutoff to be 445 ms. This value of QT divided our cohort upon arrival into a long QT group (217 patients, 26% of the cohort) and a “normal” QT group (835 patients, 74% of the cohort). The long QT group experienced an increase in combined short and long terms all-cause mortality. The QT upon arrival, on day 2 of hospitalization, and before discharge from the hospital, correlated with long-term mortality.ConclusionQT duration is often prolonged during STEMI; this prolongation is associated with increased mortality and adverse events. Gender is an important mediator of QT dynamics

Human Tissue-Resident Memory T Cells Are Defined by Core Transcriptional and Functional Signatures in Lymphoid and Mucosal Sites

Tissue-resident memory T cells (TRMs) in mice mediate optimal protective immunity to infection and vaccination, while in humans, the existence and properties of TRMs remain unclear. Here, we use a unique human tissue resource to determine whether human tissue memory T cells constitute a distinct subset in diverse mucosal and lymphoid tissues. We identify a core transcriptional profile within the CD69+ subset of memory CD4+ and CD8+ T cells in lung and spleen that is distinct from that of CD69− TEM cells in tissues and circulation and defines human TRMs based on homology to the transcriptional profile of mouse CD8+ TRMs. Human TRMs in diverse sites exhibit increased expression of adhesion and inhibitory molecules, produce both pro-inflammatory and regulatory cytokines, and have reduced turnover compared with circulating TEM, suggesting unique adaptations for in situ immunity. Together, our results provide a unifying signature for human TRM and a blueprint for designing tissue-targeted immunotherapies

Computational Evaluation of B-Cell Clone Sizes in Bulk Populations

B cell clones expand and contract during adaptive immune responses and can persist or grow uncontrollably in lymphoproliferative disorders. One way to monitor and track B cell clones is to perform large-scale sampling of bulk cell populations, amplifying, and sequencing antibody gene rearrangements by next-generation sequencing (NGS). Here, we describe a series of computational approaches for estimating B cell clone size in NGS immune repertoire profiling data of antibody heavy chain gene rearrangements. We define three different measures of B cell clone size—copy numbers, instances, and unique sequences—and show how these measures can be used to rank clones, analyze their diversity, and study their distribution within and between individuals. We provide a detailed, step-by-step procedure for performing these analyses using two different data sets of spleen samples from human organ donors. In the first data set, 19 independently generated biological replicates from a single individual are analyzed for B cell clone size, diversity and sampling sufficiency for clonal overlap analysis. In the second data set, B cell clones are compared in eight different organ donors. We comment upon frequently encountered pitfalls and offer practical advice with alternative approaches. Overall, we provide a series of pragmatic analytical approaches and show how different clone size measures can be used to study the clonal landscape in bulk B cell immune repertoire profiling data

Activation of Cytotoxic and Regulatory Functions of NK Cells by Sindbis Viral Vectors

Oncolytic viruses (OVs) represent a relatively novel anti-cancer modality. Like other new cancer treatments, effective OV therapy will likely require combination with conventional treatments. In order to design combinatorial treatments that work well together, a greater scrutiny of the mechanisms behind the individual treatments is needed. Sindbis virus (SV) based vectors have previously been shown to target and kill tumors in xenograft, syngeneic, and spontaneous mouse models. However, the effect of SV treatment on the immune system has not yet been studied. Here we used a variety of methods, including FACS analysis, cytotoxicity assays, cell depletion, imaging of tumor growth, cytokine blockade, and survival experiments, to study how SV therapy affects Natural Killer (NK) cell function in SCID mice bearing human ovarian carcinoma tumors. Surprisingly, we found that SV anti-cancer efficacy is largely NK cell-dependent. Furthermore, the enhanced therapeutic effect previously observed from Sin/IL12 vectors, which carry the gene for interleukin 12, is also NK cell dependent, but works through a separate IFNγ-dependent mechanism, which also induces the activation of peritoneal macrophages. These results demonstrate the multimodular nature of SV therapy, and open up new possibilities for potential synergistic or additive combinatorial therapies with other treatments

Data_Sheet_2_Computational Evaluation of B-Cell Clone Sizes in Bulk Populations.fasta

<p>B cell clones expand and contract during adaptive immune responses and can persist or grow uncontrollably in lymphoproliferative disorders. One way to monitor and track B cell clones is to perform large-scale sampling of bulk cell populations, amplifying, and sequencing antibody gene rearrangements by next-generation sequencing (NGS). Here, we describe a series of computational approaches for estimating B cell clone size in NGS immune repertoire profiling data of antibody heavy chain gene rearrangements. We define three different measures of B cell clone size—copy numbers, instances, and unique sequences—and show how these measures can be used to rank clones, analyze their diversity, and study their distribution within and between individuals. We provide a detailed, step-by-step procedure for performing these analyses using two different data sets of spleen samples from human organ donors. In the first data set, 19 independently generated biological replicates from a single individual are analyzed for B cell clone size, diversity and sampling sufficiency for clonal overlap analysis. In the second data set, B cell clones are compared in eight different organ donors. We comment upon frequently encountered pitfalls and offer practical advice with alternative approaches. Overall, we provide a series of pragmatic analytical approaches and show how different clone size measures can be used to study the clonal landscape in bulk B cell immune repertoire profiling data.</p

Data_Sheet_1_Computational Evaluation of B-Cell Clone Sizes in Bulk Populations.fasta

<p>B cell clones expand and contract during adaptive immune responses and can persist or grow uncontrollably in lymphoproliferative disorders. One way to monitor and track B cell clones is to perform large-scale sampling of bulk cell populations, amplifying, and sequencing antibody gene rearrangements by next-generation sequencing (NGS). Here, we describe a series of computational approaches for estimating B cell clone size in NGS immune repertoire profiling data of antibody heavy chain gene rearrangements. We define three different measures of B cell clone size—copy numbers, instances, and unique sequences—and show how these measures can be used to rank clones, analyze their diversity, and study their distribution within and between individuals. We provide a detailed, step-by-step procedure for performing these analyses using two different data sets of spleen samples from human organ donors. In the first data set, 19 independently generated biological replicates from a single individual are analyzed for B cell clone size, diversity and sampling sufficiency for clonal overlap analysis. In the second data set, B cell clones are compared in eight different organ donors. We comment upon frequently encountered pitfalls and offer practical advice with alternative approaches. Overall, we provide a series of pragmatic analytical approaches and show how different clone size measures can be used to study the clonal landscape in bulk B cell immune repertoire profiling data.</p