Recovery From Alcohol or Drug Abuse: The Relationship Between Identity Styles and Recovery Behaviors

The purpose of this study was to explore the relationship between identity styles and recovery from substance abuse. Consistent findings have established a relationship be- tween identity diffusion and substance misuse, but no research has explored the influence of identity styles on recovery processes. Participants (N = 252) from treatment and recovery-based facilities and groups using a 12-step recovery model were assessed with the Identity Style Inventory (White, Wampler, & Winn, 1998) and self-report measures of pretreatment addiction, length of continuous abstinence, quality of recovery, and recovery progress. Those with a diffuse/avoidant style had shorter lengths of continuous abstinence, fewer recovery-oriented behaviors, lower quality of recovery, and less recovery progress than those with an information style, suggesting an important relationship be- tween identity styles and the process of recovery from substance abuse

Discovery of host-directed modulators of virus infection by probing the SARS-CoV-2-host protein-protein interaction network

The ongoing coronavirus disease 2019 (COVID-19) pandemic has highlighted the need to better understand virus-host interactions. We developed a network-based method that expands the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2)-host protein interaction network and identifies host targets that modulate viral infection. To disrupt the SARS-CoV-2 interactome, we systematically probed for potent compounds that selectively target the identified host proteins with high expression in cells relevant to COVID-19. We experimentally tested seven chemical inhibitors of the identified host proteins for modulation of SARS-CoV-2 infection in human cells that express ACE2 and TMPRSS2. Inhibition of the epigenetic regulators bromodomain-containing protein 4 (BRD4) and histone deacetylase 2 (HDAC2), along with ubiquitin-specific peptidase (USP10), enhanced SARS-CoV-2 infection. Such proviral effect was observed upon treatment with compounds JQ1, vorinostat, romidepsin and spautin-1, when measured by cytopathic effect and validated by viral RNA assays, suggesting that the host proteins HDAC2, BRD4 and USP10 have antiviral functions. We observed marked differences in antiviral effects across cell lines, which may have consequences for identification of selective modulators of viral infection or potential antiviral therapeutics. While network-based approaches enable systematic identification of host targets and selective compounds that may modulate the SARS-CoV-2 interactome, further developments are warranted to increase their accuracy and cell-context specificity.Peer reviewe

Evaluation of CSF and plasma biomarkers of brain melanocortin activity in response to caloric restriction in humans

The melanocortin neuronal system, which consists of hypothalamic proopiomelanocortin (POMC) and agouti-related protein (AgRP) neurons, is a leptin target that regulates energy balance and metabolism, but studies in humans are limited by a lack of reliable biomarkers to assess brain melanocortin activity. The objective of this study was to measure the POMC prohormone and its processed peptide, β-endorphin (β-EP), in cerebrospinal fluid (CSF) and AgRP in CSF and plasma after calorie restriction to validate their utility as biomarkers of brain melanocortin activity. CSF and plasma were obtained from 10 lean and obese subjects after fasting (40 h) and refeeding (24 h), and from 8 obese subjects before and after 6 wk of dieting (800 kcal/day) to assess changes in neuropeptide and hormone levels. After fasting, plasma leptin decreased to 35%, and AgRP increased to 153% of baseline. During refeeding, AgRP declined as leptin increased; CSF β-EP increased, but POMC did not change. Relative changes in plasma and CSF leptin were blunted in obese subjects. After dieting, plasma and CSF leptin decreased to 46% and 70% of baseline, CSF POMC and β-EP decreased, and plasma AgRP increased. At baseline, AgRP correlated negatively with insulin and homeostasis model assessment (HOMA-IR), and positively with the Matsuda index. Thus, following chronic calorie restriction, POMC and β-EP declined in CSF, whereas acutely, only β-EP changed. Plasma AgRP, however, increased after both acute and chronic calorie restriction. These results support the use of CSF POMC and plasma AgRP as biomarkers of hypothalamic melanocortin activity and provide evidence linking AgRP to insulin sensitivity

Coupled Weather and Wildfire Behavior Modeling at Los Alamos: An Overview

Over the past two years, researchers at Los Alamos National Laboratory (LANL) have been engaged in coupled weather/wildfire modeling as part of a broader initiative to predict the unfolding of crisis events. Wildfire prediction was chosen for the following reasons: (1) few physics-based wild-fire prediction models presently exist; (2) LANL has expertise in the fields required to develop such a capability; and (3) the development of this predictive capability would be enhanced by LANL`s strength in high performance computing. Wildfire behavior models have historically been used to predict fire spread and heat release for a prescribed set of fuel, slope, and wind conditions (Andrews 1986). In the vicinity of a fire, however, atmospheric conditions are constantly changing due to non-local weather influences and the intense heat of the fire itself. This non- linear process underscores the need for physics-based models that treat the atmosphere-fire feedback. Actual wildfire prediction with full-physics models is both time-critical and computationally demanding, since it must include regional- to local-scale weather forecasting together with the capability to accurately simulate both intense gradients across a fireline, and atmosphere/fire/fuel interactions. Los Alamos has recently (January 1997) acquired a number of SGI/Cray Origin 2000 machines, each presently having 32 to 64 processors. These high performance computing systems are part of the Department of Energy`s Accelerated Strategic Computing Initiative (ASCI). While offering impressive performance now, upgrades to the system promise to deliver over 1 Teraflop (10(12) floating point operations per second) at peak performance before the turn of the century

Pre‐pregnancy health of women with pre‐existing diabetes or previous gestational diabetes : analysis of pregnancy risk factors and behavioural data from a digital tool

Aims: To examine health behaviours and risk factors in women with pre‐existing diabetes or previous gestational diabetes mellitus who are planning pregnancy. Methods: Health behaviour, risk factor and demographic data obtained from a digital pregnancy planning advisory tool (Tommy's charity UK) were analysed. Descriptive statistical analysis was performed, stratified by diabetes type. Results: Data from 84,359 women, including 668 with type 1 diabetes, 707 with type 2 diabetes and 1785 with previous gestational diabetes obtained over a 12‐month period (September 2019–September 2020) were analysed. 65%, 95%CI (61,68%) of women with type 2 diabetes and 46%, 95%CI (43,48%) with previous gestational diabetes were obese (BMI ≥30 kg/m2), compared with 26%, 95%CI (26,26%) without diabetes. Use of folic acid supplements was low; 41%, 95%CI (40,41%) of women without diabetes and 42%, 95%CI (40,45%) with previous gestational diabetes reported taking folic acid (any dose) while 47%, 95%CI (43.50%) women with type 1 diabetes and 44%, 95%CI (40,47%) women with type 2 diabetes respectively reported taking the recommended dose (5 mg). More women with type 1 diabetes and type 2 diabetes reported smoking (20%, 95%CI [17,23%] and 23%, 95%CI [20,26%] respectively) and taking illicit/recreational drugs (7%, 95%CI [6,10%] and 9%, 95% CI [7,11%]) compared to women without diabetes (smoking 17%, 95% CI [16,17%], drug use 5%, 95%CI [5,5%]). Alcohol consumption, low levels of physical activity and of fruit and vegetable intake were also evident. Conclusions: This study highlights the potential of online pregnancy planning advisory tools to reach high‐risk women and emphasises the need to improve pre‐pregnancy care for women with pre‐existing diabetes and previous gestational diabetes, many of whom are actively seeking advice. It is also the first to describe pre‐pregnancy health behaviours in women with previous gestational diabetes

Teaching Medical Students to Help Patients Manage Their Weight: Outcomes of an Eight-School Randomized Controlled Trial

BACKGROUND: Given the rising rates of obesity there is a pressing need for medical schools to better prepare students for intervening with patients who have overweight or obesity and for prevention efforts. OBJECTIVE: To assess the effect of a multi-modal weight management curriculum on counseling skills for health behavior change. DESIGN: A pair-matched, group-randomized controlled trial (2015-2020) included students enrolled in eight U.S. medical schools randomized to receive either multi-modal weight management education (MME) or traditional weight management education (TE). SETTING/PARTICIPANTS: Students from the class of 2020 (N=1305) were asked to participate in an objective structured clinical examination (OSCE) focused on weight management counseling and complete pre and post surveys. A total of 70.1% of eligible students (N=915) completed the OSCE and 69.3% (N=904) completed both surveys. INTERVENTIONS: The MME implemented over three years included a web-based course, a role-play classroom exercise, a web-patient encounter with feedback, and an enhanced clerkship experience with preceptors trained in weight management counseling (WMC). Counseling focused on the 5As (Ask, Advise, Assess, Assist, Arrange) and patient-centeredness. MEASUREMENTS: The outcome was student 5As WMC skills assessed using an objective measure, an OSCE, scored using a behavior checklist, and a subjective measure, student self-reported skills for performing the 5As. RESULTS: Among MME students who completed two of three WMC components compared to those who completed none, exposure was significantly associated with higher OSCE scores and self-reported 5A skills. LIMITATIONS: Variability in medical schools requiring participation in the WMC curriculum. CONCLUSIONS: This trial revealed that medical students struggle with delivering weight management counseling to their patients who have overweight or obesity. Medical schools, though restrained in adding curricula, should incorporate should incorporate multiple WMC curricula components early in medical student education to provide knowledge and build confidence for supporting patients in developing individualized plans for weight management. NIH TRIAL REGISTRY NUMBER: R01-194787

Vacuolating cytotoxin and variants in Atg16L1 that disrupt autophagy promote Helicobacter pylori infection in humans

Peer reviewedPreprin

Classifying depression symptom severity: Assessment of speech representations in personalized and generalized machine learning models

There is an urgent need for new methods that improve the management and treatment of Major Depressive Disorder (MDD). Speech has long been regarded as a promising digital marker in this regard, with many works highlighting that speech changes associated with MDD can be captured through machine learning models. Typically, findings are based on cross-sectional data, with little work exploring the advantages of personalization in building more robust and reliable models. This work assesses the strengths of different combinations of speech representations and machine learning models, in personalized and generalized settings in a two-class depression severity classification paradigm. Key results on a longitudinal dataset highlight the benefits of personalization. Our strongest performing model set-up utilized self-supervised learning features and convolutional neural network (CNN) and long short-term memory (LSTM) back-end