In Vivo RNAi Screening Identifies a Leukemia-Specific Dependence on Integrin Beta 3 Signaling

We used an in vivo small hairpin RNA (shRNA) screening approach to identify genes that are essential for MLL-AF9 acute myeloid leukemia (AML). We found that Integrin Beta 3 (Itgb3) is essential for murine leukemia cells in vivo and for human leukemia cells in xenotransplantation studies. In leukemia cells, Itgb3 knockdown impaired homing, downregulated LSC transcriptional programs, and induced differentiation via the intracellular kinase Syk. In contrast, loss of Itgb3 in normal hematopoietic stem and progenitor cells did not affect engraftment, reconstitution, or differentiation. Finally, using an Itgb3 knockout mouse model, we confirmed that Itgb3 is dispensable for normal hematopoiesis but is required for leukemogenesis. Our results establish the significance of the Itgb3 signaling pathway as a potential therapeutic target in AML.National Institutes of Health (U.S.) (Harvard Stem Cell Institute. GlaxoSmithKline. Grant P01 CA108631)National Institutes of Health (U.S.) (Harvard Stem Cell Institute. GlaxoSmithKline. Grant RC1 CA145229)National Institutes of Health (U.S.) (Harvard Stem Cell Institute. GlaxoSmithKline. Grant R01 CA140292)National Institutes of Health (U.S.) (Harvard Stem Cell Institute. GlaxoSmithKline. Grant CA148180

Impact—Shredding Processing of Whole-Plant Corn: Machine Performance, Physical Properties, and In Situ Ruminant Digestion

An intensive processing mechanism that combined impact and shredding was applied to create physical disruption of whole-plant corn as a means to increase in situ dry matter (DM) digestion in lactating dairy cows. A ratio of treatment leachate conductivity relative to that of an ultimately processed treatment, defined as a processing level index, was used to quantify material physical disruption. Two processing levels were compared to a control treatment, which applied conventional chopping and kernel processing. The non-grain fraction was substantially size-reduced by processing such that only 28% to 51% by mass of this material remained greater than 6.4 mm length. After processing with the experimental processor, greater than 85% of kernels passed through a 4.75 mm screen, and the corn silage processing score (CSPS) was 18 to 27 percentage points greater than the control. The highly fiberized material was more compliant; thus, compacted density was 9% to 17% greater than the control. During in situ digestion experiments, processing significantly increased the rapidly soluble DM fraction by 10 percentage points and the extent of DM disappearance by 5 percentage points through 16 h incubation

An Introductory Tutorial on Cardiovascular Pharmacogenetics for Healthcare Providers

10.1002/cpt.2957CLINICAL PHARMACOLOGY & THERAPEUTICS1142275-28

An Introductory Tutorial on Cardiovascular Pharmacogenetics for Healthcare Providers

Pharmacogenetics can improve clinical outcomes by reducing adverse drug effects and enhancing therapeutic efficacy for commonly used drugs that treat a wide range of cardiovascular diseases. One of the major barriers to the clinical implementation of cardiovascular pharmacogenetics is limited education on this field for current healthcare providers and students. The abundance of pharmacogenetic literature underscores its promise, but it can also be challenging to learn such a wealth of information. Moreover, current clinical recommendations for cardiovascular pharmacogenetics can be confusing because they are outdated, incomplete, or inconsistent. A myriad of misconceptions about the promise and feasibility of cardiovascular pharmacogenetics among healthcare providers also has halted clinical implementation. Therefore, the main goal of this tutorial is to provide introductory education on the use of cardiovascular pharmacogenetics in clinical practice. The target audience is any healthcare provider (or student) with patients that use or have indications for cardiovascular drugs. This tutorial is organized into the following 6 steps: (1) understand basic concepts in pharmacogenetics; (2) gain foundational knowledge of cardiovascular pharmacogenetics; (3) learn the different organizations that release cardiovascular pharmacogenetic guidelines and recommendations; (4) know the current cardiovascular drugs/drug classes to focus on clinically and the supporting evidence; (5) discuss an example patient case of cardiovascular pharmacogenetics; and (6) develop an appreciation for emerging areas in cardiovascular pharmacogenetics. Ultimately, improved education among healthcare providers on cardiovascular pharmacogenetics will lead to a greater understanding for its potential in improving outcomes for a leading cause of morbidity and mortality

Development and external validation of prediction models to predict implantable cardioverter-defibrillator efficacy in primary prevention of sudden cardiac death

Aims This study was performed to develop and externally validate prediction models for appropriate implantable cardioverter-defibrillator (ICD) shock and mortality to identify subgroups with insufficient benefit from ICD implantation. Methods and results We recruited patients scheduled for primary prevention ICD implantation and reduced left ventricular function. Bootstrapping-based Cox proportional hazards and Fine and Gray competing risk models with likely candidate predictors were developed for all-cause mortality and appropriate ICD shock, respectively. Between 2014 and 2018, we included 1441 consecutive patients in the development and 1450 patients in the validation cohort. During a median follow-up of 2.4 (IQR 2.1–2.8) years, 109 (7.6%) patients received appropriate ICD shock and 193 (13.4%) died in the development cohort. During a median follow-up of 2.7 (IQR 2.0–3.4) years, 105 (7.2%) received appropriate ICD shock and 223 (15.4%) died in the validation cohort. Selected predictors of appropriate ICD shock were gender, NSVT, ACE/ARB use, atrial fibrillation history, Aldosterone-antagonist use, Digoxin use, eGFR, (N)OAC use, and peripheral vascular disease. Selected predictors of all-cause mortality were age, diuretic use, sodium, NT-pro-BNP, and ACE/ARB use. C-statistic was 0.61 and 0.60 at respectively internal and external validation for appropriate ICD shock and 0.74 at both internal and external validation for mortality. Conclusion Although this cohort study was specifically designed to develop prediction models, risk stratification still remains challenging and no large group with insufficient benefit of ICD implantation was found. However, the prediction models have some clinical utility as we present several scenarios where ICD implantation might be postponed

Development and external validation of prediction models to predict implantable cardioverter-defibrillator efficacy in primary prevention of sudden cardiac death

AIMS: This study was performed to develop and externally validate prediction models for appropriate implantable cardioverter-defibrillator (ICD) shock and mortality to identify subgroups with insufficient benefit from ICD implantation. METHODS AND RESULTS: We recruited patients scheduled for primary prevention ICD implantation and reduced left ventricular function. Bootstrapping-based Cox proportional hazards and Fine and Gray competing risk models with likely candidate predictors were developed for all-cause mortality and appropriate ICD shock, respectively. Between 2014 and 2018, we included 1441 consecutive patients in the development and 1450 patients in the validation cohort. During a median follow-up of 2.4 (IQR 2.1-2.8) years, 109 (7.6%) patients received appropriate ICD shock and 193 (13.4%) died in the development cohort. During a median follow-up of 2.7 (IQR 2.0-3.4) years, 105 (7.2%) received appropriate ICD shock and 223 (15.4%) died in the validation cohort. Selected predictors of appropriate ICD shock were gender, NSVT, ACE/ARB use, atrial fibrillation history, Aldosterone-antagonist use, Digoxin use, eGFR, (N)OAC use, and peripheral vascular disease. Selected predictors of all-cause mortality were age, diuretic use, sodium, NT-pro-BNP, and ACE/ARB use. C-statistic was 0.61 and 0.60 at respectively internal and external validation for appropriate ICD shock and 0.74 at both internal and external validation for mortality. CONCLUSION: Although this cohort study was specifically designed to develop prediction models, risk stratification still remains challenging and no large group with insufficient benefit of ICD implantation was found. However, the prediction models have some clinical utility as we present several scenarios where ICD implantation might be postponed

Development and external validation of prediction models to predict implantable cardioverter-defibrillator efficacy in primary prevention of sudden cardiac death

AIMS: This study was performed to develop and externally validate prediction models for appropriate implantable cardioverter-defibrillator (ICD) shock and mortality to identify subgroups with insufficient benefit from ICD implantation. METHODS AND RESULTS: We recruited patients scheduled for primary prevention ICD implantation and reduced left ventricular function. Bootstrapping-based Cox proportional hazards and Fine and Gray competing risk models with likely candidate predictors were developed for all-cause mortality and appropriate ICD shock, respectively. Between 2014 and 2018, we included 1441 consecutive patients in the development and 1450 patients in the validation cohort. During a median follow-up of 2.4 (IQR 2.1-2.8) years, 109 (7.6%) patients received appropriate ICD shock and 193 (13.4%) died in the development cohort. During a median follow-up of 2.7 (IQR 2.0-3.4) years, 105 (7.2%) received appropriate ICD shock and 223 (15.4%) died in the validation cohort. Selected predictors of appropriate ICD shock were gender, NSVT, ACE/ARB use, atrial fibrillation history, Aldosterone-antagonist use, Digoxin use, eGFR, (N)OAC use, and peripheral vascular disease. Selected predictors of all-cause mortality were age, diuretic use, sodium, NT-pro-BNP, and ACE/ARB use. C-statistic was 0.61 and 0.60 at respectively internal and external validation for appropriate ICD shock and 0.74 at both internal and external validation for mortality. CONCLUSION: Although this cohort study was specifically designed to develop prediction models, risk stratification still remains challenging and no large group with insufficient benefit of ICD implantation was found. However, the prediction models have some clinical utility as we present several scenarios where ICD implantation might be postponed