Superimposed on these effects, either dose of THC also accelerated the age-related decline in nicotinic ACh receptors. Our studies provide evidence for adverse effects of paternal THC administration on neurodevelopment in the offspring and further demonstrate that adverse impacts of drug exposure on brain development are not limited to effects mediated by the embryonic or fetal chemical environment, but rather that vulnerability is engendered by exposures occurring prior to conception, involving the father as well as the mother. © The Author(s) 2020. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. For permissions, please e-mail journals.permissions@oup.com.Transforming growth factor β (TGFβ) signaling has been recently shown to reduce anti-tumor response to PD-L1 blockade, leading to a renewed enthusiasm in developing anti-TGFβ therapies for potential combination with cancer immunotherapy agents. Inhibition of TGFβ signaling in nonclinical toxicology species is associated with serious adverse toxicities including cardiac valvulopathies and anemia. Previously, cardiovascular toxicities have been thought to be limited to small molecule inhibitors (SMIs) of TGFβ receptor and not considered to be a liability associated with pan-TGFβ neutralizing monoclonal antibodies (mAb). Here we report the toxicity findings associated with a potent pan-TGFβ neutralizing mAb (pan-TGFβ mAb; neutralizes TGFβ1, 2, and 3) after five weekly intravenous doses of 10, 30, and 100 mg/kg, followed by a 4-week recovery period, in mice and cynomolgus monkeys. Mortality was observed due to acute bleeding and cardiovascular toxicity in mice at ≥ 30 mg/kg and prolonged menstruation in female monkeys at 100 mg/kg. Additional findings considered to be on-target exaggerated pharmacology included generalized bleeding and cardiovascular toxicity in mice and monkeys; histopathologic changes in the teeth, tongue, and skin in mice; and abnormal wound healing and microscopic pathology in the bone in monkeys. Importantly, our data indicate that the cardiovascular toxicities associated with the inhibition of TGFβ signaling are not limited to SMIs, but are also observed following administration of a potent pan-TGFβ inhibiting mAb. © The Author(s) 2020. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. For permissions, please email journals.permissions@oup.com.INTRODUCTION The Department of Defense aims to maintain mission readiness of its service members. Therefore, it is important to understand factors associated with treatment seeking in order to identify areas of prevention and intervention early in a soldier's career that can promote positive functioning and increase their likelihood of seeking mental health care when necessary. METHOD Using a theory of planned behavior lens, this study identified potential barriers (risk) and facilitators (resilience) to treatment seeking among 24,717 soldiers-in-training who participated in the New Soldiers Study component of the "Army Study to Assess Risk and Resilience in Servicemembers" (Army STARRS). Approval for this study was granted by the University of Iowa IRB # 201706739.  https://www.selleckchem.com/products/mira-1.html  Hierarchal linear regression modeling and independent samples t-tests were used to examine associations between demographics and study variables, intersections of risk and resilience, and to explore differences in the likelihood of seeking help ba leverage points for early intervention or prevention prior to entering stressful military operating environments. Limitations of this study include the examination of only one military branch and exclusion of soldiers not "in-training." Future studies could consider replicating the current study using a sample of military personnel longitudinally to track behavioral trends as well as looking at military populations outside of basic combat training. © Association of Military Surgeons of the United States 2020. All rights reserved. For permissions, please e-mail journals.permissions@oup.com.INTRODUCTION Despite the great number of investigations on the effects of injuries during military service, there is limited information available on the use of self-reported instruments. This study evaluated self-reported knee pain (KP) and its effect on physical performance during military service in the Estonian Defense Forces. MATERIAL AND METHODS Ninety-five male conscripts aged 19-25 years were divided into two study groups based on the occurrence of KP or not. Self-reported KP and function according to the Knee Injury and Osteoarthritis Outcome Score (KOOS) were measured. Physical fitness level was scored using the Army Physical Fitness Test (APFT). KOOS and APFT were measured in the beginning and at the end of the 6-month period of military service. RESULTS Significant differences in favor of the group without KP (P  less then  0.001) were found for all subgroups of the KOOS. In spite of KP, the physical condition improved significantly (P  less then  0.001) in both study groups as measured with both the APFT test (22.2% increase) and running time (10.3% decrease). CONCLUSION In conclusion, self-reported KP and limited function according to KOOS did not hinder the improvement of physical condition and running speed as assessed by APFT in Estonian conscripts. © Association of Military Surgeons of the United States 2020. All rights reserved. For permissions, please e-mail journals.permissions@oup.com.Accurately inferring the genome-wide landscape of recombination rates in natural populations is a central aim in genomics, as patterns of linkage influence everything from genetic mapping to understanding evolutionary history. Here we describe ReLERNN, a deep learning method for estimating a genome-wide recombination map that is accurate even with small numbers of pooled or individually sequenced genomes. Rather than use summaries of linkage disequilibrium as its input, ReLERNN takes columns from a genotype alignment, which are then modeled as a sequence across the genome using a recurrent neural network. We demonstrate that ReLERNN improves accuracy and reduces bias relative to existing methods and maintains high accuracy in the face of demographic model misspecification, missing genotype calls, and genome inaccessibility. We apply ReLERNN to natural populations of African Drosophila melanogaster and show that genome-wide recombination landscapes, while largely correlated among populations, exhibit important population-specific differences.