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While conventional nutrition research has yielded biomarkers such as doubly labeled water for energy metabolism and 24-h urinary nitrogen for protein intake, a critical need exists for additional, equally robust biomarkers that allow for objective assessment of specific food intake and dietary exposure. Recent advances in high-throughput MS combined with improved metabolomics techniques and bioinformatic tools provide new opportunities for dietary biomarker development. In September 2018, the NIH organized a 2-d workshop to engage nutrition and omics researchers and explore the potential of multiomics approaches in nutritional biomarker research. The current Perspective summarizes key gaps and challenges identified, as well as the recommendations from the workshop that could serve as a guide for scientists interested in dietary biomarkers research. Topics addressed included study designs for biomarker development, analytical and bioinformatic considerations, and integration of dietary biomarkers with other omics techniques. Several clear needs were identified, including larger controlled feeding studies, testing a variety of foods and dietary patterns across diverse populations, improved reporting standards to support study replication, more chemical standards covering a broader range of food constituents and human metabolites, standardized approaches for biomarker validation, comprehensive and accessible food composition databases, a common ontology for dietary biomarker literature, and methodologic work on statistical procedures for intake biomarker discovery. Multidisciplinary research teams with appropriate expertise are critical to moving forward the field of dietary biomarkers and producing robust, reproducible biomarkers that can be used in public health and clinical research.

Scientific progress depends on the quality and credibility of research methods. As discourse on rigor, transparency, and reproducibility joins the cacophony of nutrition information and misinformation in mass media, buttressing the real and perceived reliability of nutrition science is more important than ever. This broad topic was the focus of a 2016 plenary session, "Scientific Rigor and Competing Interests in the Nutrition Research Landscape." This article summarizes and expands on this session in an effort to increase understanding and dialogue with regard to factors that limit the real and perceived reliability of nutrition science and steps that can be taken to mitigate those factors. The end goal is to both earn and merit greater trust in nutrition science by both the scientific community and the general public. The authors offer suggestions in each of the domains of education and training, communications, research conduct, and procedures and policies to help achieve this goal. The authors emphasize the need for adequate funding to support these efforts toward greater rigor and transparency, which will be resource demanding and may require either increased research funding or the recognition that a greater proportion of research funding may need to be allocated to these tasks.

Dietary protein provides essential amino acids (EAAs) for the synthesis of new proteins plus an array of other metabolic functions; many of these functions are sensitive to postprandial plasma and intracellular amino acid concentrations. Recent research has focused on amino acids as metabolic signals that influence the rate of protein synthesis, inflammation responses, mitochondrial activity, and satiety, exerting their influence through signaling systems including mammalian/mechanistic target of rapamycin complex 1 (mTORC1), general control nonrepressed 2 (GCN2), glucagon-like peptide 1 (GLP-1), peptide YY (PYY), serotonin, and insulin. These signals represent meal-based responses to dietary protein. The best characterized of these signals is the leucine-induced activation of mTORC1, which leads to the stimulation of skeletal muscle protein synthesis after ingestion of a meal that contains protein. The response of this metabolic pathway to dietary protein (i.e., meal threshold) declines with advancing age or reduced physical activity. Current dietary recommendations for protein are focused on total daily intake of 0.8 g/kg body weight, but new research suggests daily needs for older adults of ≥1.0 g/kg and identifies anabolic and metabolic benefits to consuming at least 20-30 g protein at a given meal. Resistance exercise appears to increase the efficiency of EAA use for muscle anabolism and to lower the meal threshold for stimulation of protein synthesis. Applying this information to a typical 3-meal-a-day dietary plan results in protein intakes that are well within the guidelines of the Dietary Reference Intakes for acceptable macronutrient intakes. The meal threshold concept for dietary protein emphasizes a need for redistribution of dietary protein for optimum metabolic health.

Branched-chain amino acids (BCAAs) are important nutrient signals that have direct and indirect effects. Frequently, BCAAs have been reported to mediate antiobesity effects, especially in rodent models. However, circulating levels of BCAAs tend to be increased in individuals with obesity and are associated with worse metabolic health and future insulin resistance or type 2 diabetes mellitus (T2DM). A hypothesized mechanism linking increased levels of BCAAs and T2DM involves leucine-mediated activation of the mammalian target of rapamycin complex 1 (mTORC1), which results in uncoupling of insulin signalling at an early stage. A BCAA dysmetabolism model proposes that the accumulation of mitotoxic metabolites (and not BCAAs per se) promotes β-cell mitochondrial dysfunction, stress signalling and apoptosis associated with T2DM. Alternatively, insulin resistance might promote aminoacidaemia by increasing the protein degradation that insulin normally suppresses, and/or by eliciting an impairment of efficient BCAA oxidative metabolism in some tissues. Whether and how impaired BCAA metabolism might occur in obesity is discussed in this Review. Research on the role of individual and model-dependent differences in BCAA metabolism is needed, as several genes (BCKDHA, PPM1K, IVD and KLF15) have been designated as candidate genes for obesity and/or T2DM in humans, and distinct phenotypes of tissue-specific branched chain ketoacid dehydrogenase complex activity have been detected in animal models of obesity and T2DM.

As the COVID-19 pandemic caused severe disruption to education enterprises throughout the world, the main response by educational institutions was to move to online learning environments. The purpose of this study was to understand better how instructors could improve online learning for a professional-level week-long short course in a highly technical area (data analytics), which had, pre-COVID, been a hands-on computer, laboratory-based learning experience. The authors used self-study of professional practice to elicit and understand the major issues and concerns of the transition to an online learning environment. Under the guidance of a colleague in teacher education, three course instructors recorded and analyzed their experiences and, through discussion and data analysis, gained a deeper understanding of three challenging dimensions: course adaption to the online environment, personnel considerations, and technological considerations. Through the reflection that self-study provided, several of these challenges were addressed in subsequent courses. Self-study provided the instructors with an opportunity to reflect on the transition of the course to an online environment. This, in turn, provided an opportunity for course improvement and, arguably more importantly, an opportunity for the instructors to better understand each other's concerns and desires as it pertained to the course. [ABSTRACT FROM AUTHOR]

BackgroundForecasting methods rely on trends and averages of prior observations to forecast COVID-19 case counts. COVID-19 forecasts have received much media attention, and numerous platforms have been created to inform the public. However, forecasting effectiveness varies by geographic scope and is affected by changing assumptions in behaviors and preventative measures in response to the pandemic. Due to time requirements for developing a COVID-19 vaccine, evidence is needed to inform short-term forecasting method selection at county, health district, and state levels. ObjectiveCOVID-19 forecasts keep the public informed and contribute to public policy. As such, proper understanding of forecasting purposes and outcomes is needed to advance knowledge of health statistics for policy makers and the public. Using publicly available real-time data provided online, we aimed to evaluate the performance of seven forecasting methods utilized to forecast cumulative COVID-19 case counts. Forecasts were evaluated based on how well they forecast 1, 3, and 7 days forward when utilizing 1-, 3-, 7-, or all prior–day cumulative case counts during early virus onset. This study provides an objective evaluation of the forecasting methods to identify forecasting model assumptions that contribute to lower error in forecasting COVID-19 cumulative case growth. This information benefits professionals, decision makers, and the public relying on the data provided by short-term case count estimates at varied geographic levels. MethodsWe created 1-, 3-, and 7-day forecasts at the county, health district, and state levels using (1) a naïve approach, (2) Holt-Winters (HW) exponential smoothing, (3) a growth rate approach, (4) a moving average (MA) approach, (5) an autoregressive (AR) approach, (6) an autoregressive moving average (ARMA) approach, and (7) an autoregressive integrated moving average (ARIMA) approach. Forecasts relied on Virginia’s 3464 historical county-level cumulative case counts from March 7 to April 22, 2020, as reported by The New York Times. Statistically significant results were identified using 95% CIs of median absolute error (MdAE) and median absolute percentage error (MdAPE) metrics of the resulting 216,698 forecasts. ResultsThe next-day MA forecast with 3-day look-back length obtained the lowest MdAE (median 0.67, 95% CI 0.49-0.84, P

Validation is the process of determining if a model adequately represents the system under study for the model’s intended purpose. Validation is a critical component in building the credibility of a simulation model with its end-users. Effectively conducting validation can be a daunting task for both novice and experienced simulation developers. Further compounding the difficult task of conducting validation is that there is no universally accepted approach for assessing a simulation. These challenges are particularly relevant to the paradigm of Agent-Based Modeling and Simulation (ABMS) because of the complexity found in these models’ mechanisms and in the real-world situations they attempt to represent. To aid both the novice and expert in conducting a validation process for an agent-based simulation, this article reviews nine methods that are useful for this process, including foundational topics of docking, empirical validation, sampling, and visualization, as well as advanced topics of bootstrapping, causal analysis, inverse generative social science, and role-playing. Each method is reviewed with respect to its benefits and limitations as a validation-supporting method for ABMS. Suggestions that may support a validation plan for an agent-based simulations, are also provided. This article is an introductory guide for understanding and conducting ABMS validation for developers of all experience levels. [ABSTRACT FROM AUTHOR]

Roux-en-Y gastric bypass surgery (GBS) is the most effective treatment for morbid obesity. GBS is a restrictive malabsorptive procedure, but many patients also report altered taste preferences. This study investigated the effects of GBS or a sham operation (SH) on body weight, glucose tolerance, and behavioral and neuronal taste functions in the obese Otsuka Long-Evans Tokushima Fatty (OLETF) rats lacking CCK-1 receptors and lean controls (LETO). OLETF-GBS rats lost body weight (-26%) and demonstrated improved glucose tolerance. They also expressed a reduction in 24-h two-bottle preference for sucrose (0.3 and 1.0 M) and decreased 10-s lick responses for sucrose (0.3 through 1.5 M) compared with OLETF-SH or LETO-GBS. A similar effect was noted for other sweet compounds but not for salty, sour, or bitter tastants. In lean rats, GBS did not alter responses to any stimulus tested. Extracellular recordings from 170 taste-responsive neurons of the pontine parabrachial nucleus revealed a rightward shift in concentration responses to oral sucrose in obese compared with lean rats (OLETF-SH vs. LETO-SH): overall increased response magnitudes (above 0.9 M), and maximum responses occurring at higher concentrations (+0.46 M). These effects were reversed by GBS, and neural responses in OLETF-GBS were statistically not different from those in any LETO groups. These findings confirm obesity-related alterations in taste functions and demonstrate the ability of GBS to alleviate these impairments. Furthermore, the beneficial effects of GBS appear to be independent of CCK-1 receptor signaling. An understanding of the underlying mechanisms for reduced preferences for sweet taste could help in developing less invasive treatments for obesity. overeating; dietary obesity; surgical weight reduction; insulin resistance; palatability; gustatory coding; cholecystokinin-1 receptor doi: 10.1152/ajpgi.00070.2010.

Endotoxin (LPS) and sepsis decrease mammalian target of rapamycin (mTOR) activity in skeletal muscle, thereby reducing protein synthesis. Our study tests the hypothesis that inhibition of branched-chain amino acid (BCAA) catabolism, which elevates circulating BCAA and stimulates mTOR, will blunt the LPS-induced decrease in muscle protein synthesis. Wild-type (WT) and mitochondrial branched-chain aminotransferase (BCATm) knockout mice were studied 4 h after Escherichia coli LPS or saline. Basal skeletal muscle protein synthesis was increased in knockout mice compared with WT, and this change was associated with increased eukaryotic initiation factor (eIF)-4E binding protein-1 (4E-BP1) phosphorylation, eIF4E*eIF4G binding, 4E-BP1*raptor binding, and eIF3*raptor binding without a change in the mTOR*raptor complex in muscle. LPS decreased muscle protein synthesis in WT mice, a change associated with decreased 4E-BP1 phosphorylation as well as decreased formation of eIF4E.eIF4G, 4E-BP1*raptor, and eIF3*raptor complexes. In BCATm knockout mice given LPS, muscle protein synthesis only decreased to values found in vehicle-treated WT control mice, and this ameliorated LPS effect was associated with a coordinate increase in 4E-BP1*raptor, eIF3*raptor, and 4E-BP1 phosphorylation. Additionally, the LPS-induced increase in muscle cytokines was blunted in BCATm knockout mice, compared with WT animals. In a separate study, 7-day survival and muscle mass were increased in BCATm knockout vs. WT mice after polymicrobial peritonitis. These data suggest that elevating blood BCAA is sufficient to ameliorate the catabolic effect of LPS on skeletal muscle protein synthesis via alterations in protein-protein interactions within mTOR complex-1, and this may provide a survival advantage in response to bacterial infection. branched-chain amino acids; raptor; mTOR; skeletal muscle; eIF3 doi: 10.1152/ajpregu.00297.2010.

The hindgut hypothesis posits improvements in Type 2 diabetes after gastric bypass surgery are due to enhanced delivery of undigested nutrients to the ileum, which increase incretin production and insulin sensitivity. The present study investigates the effect of ileal interposition (IT), surgically relocating a segment of distal ileum to the proximal jejunum, on glucose tolerance, insulin sensitivity, and glucose transport in the obese Zucker rat. Two groups of obese Zucker rats were studied: IT and sham surgery ad libitum fed (controls). Changes in food intake, body weight and composition, glucose tolerance, insulin sensitivity and tissue glucose uptake, and insulin signaling as well as plasma concentrations of glucagon-like peptide-1 and glucose-dependent insulinotropic peptide were measured. The IT procedure did not significantly alter food intake, body weight, or composition. Obese Zucker rats demonstrated improved glucose tolerance 3 wk after IT compared with the control group (P < 0.05). Euglycemic, hyperinsulinemic clamp and 1-[[sup.14]C]-2-deoxyglucose tracer studies indicate that 1T improves whole body glucose disposal, insulin-stimulated glucose uptake, and the ratio of phospho- to total Akt (P < 0.01 vs. control) in striated muscle. After oral glucose, the plasma concentration of glucagon-like peptide-1 was increased, whereas GIP was decreased following IT. Enhanced nutrient delivery to the ileum after IT improves glucose tolerance, insulin sensitivity and muscle glucose uptake without altering food intake, body weight, or composition. These findings support the concept that anatomic and endocrine alterations in gut function play a role in the improvements in glucose homeostasis after the IT procedure. ileal transposition; obesity; diabetes; incretin; GLP-1 doi: 10.1152/ajpgi.00525.2009.