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Background:. Brief alcohol interventions use patient-provider communication to promote alcohol cessation. We characterized the receipt of this intervention in chronic liver disease (CLD). Methods:. We surveyed patients with CLD for weekly drinking patterns and examined associations with patient-provider communication receipt. Results:. Among 840 participants, 82.1% and 56.5% reported ≥1 standard drink weekly and excessive alcohol consumption, respectively. Patient-provider communication was lower in noncirrhotic (adjusted odds ratio:0.34, 95% CI: 0.22–0.54) and nonalcohol-associated CLD (adjusted odds ratio: 0.22, 95% CI: 0.15–0.34) among individuals drinking ≥1 standard drink weekly, and similarly in noncirrhotic CLD (adjusted odds ratio: 0.45, 95% CI: 0.21–0.95) among those with excessive drinking. Conclusions:. Brief alcohol interventions are underutilized in noncirrhotic and nonalcohol-associated CLD.

Background: Mortality is high for severe alcohol-associated hepatitis (AH). Corticosteroids are the standard of care for patients without contraindications. Recent data showed that interleukin-1β receptor antagonist anakinra attenuated inflammation and liver damage. We designed a multicenter, double-blind, randomized controlled trial to assess the safety and efficacy of anakinra compared to prednisone. Methods: Patients meeting the clinical and biochemical criteria for severe AH with MELD scores between 20 and 35 were recruited at eight clinical sites. Eligible patients enrolled in the study were randomized to anakinra, 100 mg subcutaneous injection for 14 days, plus zinc sulfate 220 mg for 90 days, vs. prednisone 40 mg PO daily for 30 days. Matching placebos for anakinra, zinc, and prednisone were provided to mask the treatment. Participants were followed for 180 days. The primary outcome was overall survival at 90 days. An unadjusted log-rank test was used to compare the survival of the two treatments in the first 90 days. Between July 10, 2020, and March 4, 2022, we screened 1082 patients with severe AH, and 147 eligible patients were enrolled and randomized. The average baseline MELD score was 25 [range 20–35], Maddrey discriminant function (MDF) was 59.4 [range 20.2–197.5]. The mean aspartate transaminase (AST)-to-alanine transaminase (ALT) ratio was 3.5. The baseline characteristics were not statistically different between the two treatment groups. Conclusions: The study provided a direct comparison of the survival benefits and safety profiles of anakinra plus zinc vs. prednisone in patients with severe AH.

Background. Alcohol-associated liver disease (ALD) is the leading indication for liver transplantation (LT) in the United States. Alcohol use disorder relapse can lead to graft failure and the need for liver retransplantation (re-LT). Despite the rising incidence of LT for ALD, the practice of re-LT for recurrent ALD is not well understood. We aimed to define the practice of re-LT for recurrent ALD during the last 20 y. Methods. Using the US national transplant registry, adults who underwent re-LT for recurrent ALD were compared with LT recipients who died from recurrent ALD and propensity score–matched re-LT recipients with non-ALD indications. All groups had at least 1-y survival of their primary graft. Kaplan-Meier analysis was used to calculate 1- and 5-y survivals. Results. Between 2000 and 2020, 74 re-LTs were performed for recurrent ALD (1.0% of all re-LTs). There was an increase in recurrent ALD re-LT practice from 2017 to 2020 versus 2014 to 2016 (20 versus 2). At the time of re-LT, patients with recurrent ALD had a significant decrease in body mass index (median 25.1 versus 28.8 kg/m2; P

Background. The 2013 HIV Organ Policy Equity Act has increased liver transplantation (LT) in HIV+ patients; however, transplant centers may remain reluctant to perform LT in HIV/hepatitis C virus (HCV)-coinfected patients due to inferior outcomes. We aimed to assess how direct-acting antivirals (DAAs) have impacted HIV+/HCV+-coinfected LT recipient outcomes. Methods. national data including 70 125 adult LT recipients between 2008 and 2019 were analyzed. Kaplan-Meier survival analysis and Cox proportional hazards model were used to analyze outcomes. Results. LT for HIV+ individuals increased in the DAA era from 28 in 2014 to 64 in 2019 (23 had HIV+/HCV+ coinfection). In the pre-DAA era, HIV+/HCV+-coinfected LT recipients had an increased risk of graft failure compared with HIV−/HCV−-uninfected LT recipients (hazard ratio [HR], 1.85; P

Objective: Recent studies have suggested a critical role for toll-like receptor 4 (TLR4) in the development of alcoholic liver disease. As TLR4 is widely expressed throughout the body, it is unclear which TLR4-expressing cell types contribute to alcohol-induced liver damage. Methods: We selectively ablated TLR4 in hepatocytes and myeloid cells. Male mice were fed a liquid diet containing either 5% alcohol or pair-fed a control diet for 4 weeks to examine chronic alcohol intake-induced liver damage and inflammation. In addition, mice were administered a single oral gavage of alcohol to investigate acute alcohol drinking-associated liver injury. Results: We found that selective hepatocyte TLR4 deletion protected mice from chronic alcohol-induced liver injury and fatty liver. This result was in part due to decreased expression of endogenous lipogenic genes and enhanced expression of genes involved in fatty acid oxidation. In addition, mice lacking hepatocyte TLR4 exhibited reduced mRNA expression of inflammatory genes in white adipose tissue. Furthermore, in an acute alcohol binge model, hepatocyte TLR4 deficient mice had significantly decreased plasma alanine transaminase (ALT) levels and attenuated hepatic triglyceride content compared to their alcohol-gavaged control mice. In contrast, deleting TLR4 in myeloid cells did not affect the development of chronic-alcohol induced fatty liver, despite the finding that mice lacking myeloid cell TLR4 had significantly reduced circulating ALT concentrations. Conclusions: These findings suggest that hepatocyte TLR4 plays an important role in regulating alcohol-induced liver damage and fatty liver disease. Keywords: Alcoholic fatty liver disease, Toll-like receptor 4, Hepatocyte, Myeloid cell, Liver injury, Inflammation

Background: More than two million U.S. families receive home visiting services each year, yet little is known about the content and process of home visit interventions. Home visit observations are a recommended tool to address this gap in knowledge, but guidance regarding how much observation time is needed to provide a trustworthy picture of home visits is not available. Objective: This study estimated the length of observation needed to provide a reliable description of the content and process of home visits delivered through an Early Head Start (EHS) home-based program. Methods: Observations of 555 home visits involving 88 families and 17 home visitors were coded with the Home Visit Observation Form--Revised (HVOF-R). The HVOF-R describes the proportions of time spent among several subcategories within each of three major categories: Primary Interaction Partners, Content of Interactions, and Nature of the Home Visitor's Interactions. The psychometric theory of test reliability guided use of bootstrap resampling and the Spearman-Brown prediction formula to estimate the duration of observation necessary to achieve conventional psychometric standards of reliability (r = 0.90 and r = 0.80). Results: Results showed that 40-60 min of a home visit observation yields a reliable estimate of the proportion of time spent on most key features of home visits, especially those behaviors observed most frequently, including interactions among the home visitor, parent, and/or child. Conclusion: Fairly brief observations yield reliable description of home visit activities, and use of observation is recommended to guide program implementation efforts and enhance program quality.

This study incorporated institutional characteristics (e.g., Carnegie type, selectivity) and resource allocations (e.g., instructional expenditures, student affairs expenditures) into a statistical model to predict undergraduate graduation rates. Instructional expenditures, library expenditures, and a number of institutional classification variables were significant predictors of graduation rates. Based on these results, recommendations as well as warranted cautions are included about allocating academic financial resources to optimize graduation rates

Shoreline position (e.g., beach width) is a critical component of flooding and overtopping forecasts but difficult to predict accurately. We model beach width changes with a supervised machine learning (ML) approach informed by equilibrium principles. The time history of wave energy anomalies that force equilibrium models is used as an ML input feature. The sweeping simplifying equilibrium model assumptions relating beach width change to anomalies are replaced with data‐based ML results. Supervised learning regression methods including linear, support vector, decision trees, and ensemble regressors are tested. Observations for model training and testing includes weekly to quarterly beach elevation surveys spanning approximately 500 m alongshore and 8 years at two beaches, each supplemented with several months of ∼100 sub‐weekly surveys. These beaches, with different sediment types (sand vs. sand‐cobble mix), both widen in summer in response to the seasonal wave climate, in agreement with a generic equilibrium model. Differences in backshore erodability contribute to differing beach responses in the stormiest (El Niño) year that are reproduced by a simple extra trees regression model but not by the equilibrium model. With sufficiently extensive training data, the ML model outperforms equilibrium by providing flexibility and complexity in the response to wave forcing. The present ML and equilibrium models both fail to simulate a uniquely stunted beach recovery unlike other recoveries in the training data. Plain Language Summary: Beach elevation surveys are compared at two beaches in San Diego County. Both beaches narrow during winter as large wave events transport sand offshore and widen during summer as gentle waves move sand onshore. The seasonality of such beaches has been characterized by simple models that primarily rely on wave energy relative to an average state to predict beach width changes, known as equilibrium models. Here, we highlight some of the limitations of equilibrium models, such as a tendency to over predict winter erosion at a beach backed by non‐erodible infrastructure. We demonstrate that machine learning models, when trained with sufficient observations, can predict beach width changes more accurately than equilibrium models. Key Points: The Equilibrium‐informed extra tree (ET) regression machine learning model uses input features of only wave history, inspired by equilibrium conceptsWith sufficient training, ET outperforms a widely used equilibrium model [ABSTRACT FROM AUTHOR]

We identified gaps in safe food handling practices that may be placing older adults at increased risk of food-borne illness. A convenience sample of 1,019 older adults completed the Food Safety Behavior Questionnaire. Majority groups among participants were those who were female, those who were White, and those who were widowed. Participants had lower adherences to safe practices related to temperature control, attention to sell-by/use-by dates on food packages, and cross-contamination. Adherences were significantly (p < 0.05) influenced by gender, race/ethnicity, age, marital status, and education. Our findings suggest the need for older adult-focused safe food handling education related to temperature control, product selection practices, and cross-contamination. [Additional support for this research was provided by the U.S. Department of Agriculture Supplemental Nutrition Assistance Program, in collaboration with the Iowa Department of Public Health and Iowa State University Extension and Outreach.]

Despite decades of messaging, most Americans still consume excess fats and sugars, but inadequate fiber, potassium, and calcium. Nutrient-rich foods (NRFs) have a high density of favorable nutrients related to calories. Choosing NRFs could lower risk of nutrition-related chronic diseases and aid in their control. We hypothesized that having greater knowledge of NRFs, the presence of a nutrition-related chronic disease or risk factor, and positive Health Belief Model (HBM) views would be predictive of the likelihood of eating NRFs. Through a national online survey panel, 976 adults aged 18–80 completed demographic, health, NRF knowledge, attitudes, and HBM construct questions. Participants were 77% White, 52% women, and 55% had a nutrition-related disease or risk factor. Multivariable HBM scales were generated by theory, principal components, and reliability analysis. NRF knowledge was significantly higher for women, Whites, households without children, and persons without a nutrition-related disease (all p ≤ 0.015). 'Likelihood of eating NRFs' was significantly higher for persons with a nutrition-related disease, Whites, married participants, main food shoppers, and households with children (all p ≤ 0.022). Regressing demographic and HBM constructs on the 'likelihood of eating NRFs' resulted in R2 of 0.435. Nutrition-related disease and HBM constructs of self-efficacy, perceived benefits, and cues to action were predictive of the likelihood of eating NRFs, but higher NRF knowledge was negatively associated. [ABSTRACT FROM AUTHOR]

Heavy drinkers are at risk for a spectrum of histologic alcohol-related liver injury: steatosis, alcoholic steatohepatitis (ASH), alcohol-related fibrosis, and cirrhosis. Alcoholic hepatitis (AH), the clinical entity associated with severe ASH, has high short-term mortality. The standard-of-care therapy, prednisolone, has limited efficacy and many side effects; no other treatment has consistently shown survival benefit. The National Institute on Alcohol Abuse and Alcoholism (NIAAA)-funded Alcoholic Hepatitis Consortia carry out translational research on pathophysiologic mechanisms, genetic and environmental risk factors, phase II clinical trials, and development of biomarkers. The consortia members were convened by the National Institutes of Health to address diagnostic criteria and practical issues related to clinical AH research, and to develop a set of common data elements to harmonize ongoing and future trials. This was accomplished through 3 face-to-face meetings of the investigators and representatives of the National Institutes of Health, and subsequent electronic communications over the course of 6 months. Evidence for the recommendations was based on published trials and observational data from several of the consortia members. A draft manuscript was iteratively reviewed by members of the consortia. The goal was to reach agreements on recommendations and definitions that could facilitate trial design, and simultaneously be tested by research groups pooling their data. The recommendations made here are specifically directed to achieve better uniformity in clinical trials, rather than serving as clinical practice guidelines.

In a cluster-randomized study, we investigate the impact of an argument-based approach to teaching science in elementary school on science learning and critical thinking skills. Forty-eight schools participated in the study, with data on 9,963 students across the 2 years of the intervention. Annual standardized tests assessing science content knowledge were used to evaluate the effect of the intervention on science using a hierarchical linear model. To assess critical thinking abilities, scores for the Cornell Critical Thinking instrument were assessed for the 2,353 students in fifth grade using a multilevel model. While no statistically significant gains were found for science content, there was statistically significant evidence that the intervention was associated with an improvement in critical thinking scores (p < 0.05, ES = 0.167). In particular, the strongest gains were for students in the following groups: individual education plan, free and reduced price lunch, and English language learners.

Multiple regression was performed on four dependent variables derived from the results of a student survey measuring attitudes about student leadership: (a) leadership is important to the student, (b) the student considers himself or herself to be a leader, (c) leadership will be important to the student after college, and (d) leaders need to be able to work in teams or groups. Each of 10 independent variables was a significant predictor of one or more dependent variables. (Contains 7 tables.)

This study incorporated institutional characteristics (e.g., Carnegie type, selectivity) and resource allocations (e.g., instructional expenditures, student affairs expenditures) into a statistical model to predict undergraduate graduation rates. Instructional expenditures, library expenditures, and a number of institutional classification variables were significant predictors of graduation rates. Based on these results, recommendations as well as warranted cautions are included about allocating academic financial resources to optimize graduation rates. (Contains 5 tables and 2 notes.)