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Abstract Free Fecal Liquid (FFL), also termed Fecal Water Syndrome (FWS), is an ailment in horses characterized by variable solid and liquid (water) phases at defecation. The liquid phase can be excreted before, during, or after the solid defecation phase. While the underlying causes of FFL are unknown, hindgut dysbiosis is suggested to be associated with FFL. Three European studies investigated dysbiosis in horses with FFL using 16S rRNA sequencing and reported results that conflicted between each other. In the present study, we also used 16S rRNA sequencing to study the fecal microbial composition in 14 Canadian horses with FFL, and 11 healthy stable mate controls. We found no significant difference in fecal microbial composition between FFL and healthy horses, which further supports that dysbiosis is not associated with FFL.

Exercise performance tends to suffer during the morning compared to the evening, which may decrease potential training adaptations. Currently, it is unclear how nutritional interventions may affect this phenomenon and whether supplementation may allow for the attainment of optimal performance regardless of the time of day. The purpose of this study was to investigate the effects of acute yohimbine ingestion on morning-associated decrements in performance and psychophysiological responses to exercise. Physically active females (n = 16) were recruited to participate in three total visits, each with a different treatment: (1) placebo-morning (PL-AM), (2) yohimbine-morning (YHM-AM; oral 2.5 mg), and (3) placebo-afternoon (PM). The morning and afternoon visits occurred between 7:00–8:00 h and 16:00–17:00 h, respectively. The experimental treatments in the morning were ingested 20 min prior to capillary blood collection, which was completed pre- and post-exercise. Following a warm-up, participants completed a 2000 m time trial on a rowing ergometer. Power output, heart rate (HR), and rating of perceived exertion (RPE) were recorded every minute. Time to competition (TTC) and subjective energy, focus, and alertness were documented post-exercise. Pre- and post-exercise blood lactate (La) and plasma hypoxanthine (HX) levels were also assessed. The trials were separated by a 48 h washout period. The results showed that power output (p = 0.010) was lower and TTC (p = 0.003) was significantly slower with PL-AM compared to PM. Furthermore, YHM-AM resulted in higher power output (p = 0.035) and faster TTC (p = 0.007) compared to PL-AM, with no differences compared to PM (p > 0.05). Post-exercise La was significantly lower with YHM-AM compared to PL-AM (p = 0.046) and PM (p = 0.001). Pre-exercise plasma HX, as measured via conversion to xanthine, was significantly higher with PM (p = 0.039), while the levels trended higher with YHM-AM (p = 0.060) compared to PL-AM. Subjective energy was higher with YHM-AM (p = 0.045) and PM (p = 0.009) compared to PL-AM, while alertness was only higher for YHM-AM compared to PL-AM (p = 0.045). No statistical differences between the treatments were found for RPE or HR (p > 0.05). These findings indicate that YHM ingestion attenuates performance decrements in the morning. Improvements in performance may be underpinned by improved feelings of energy and alterations in metabolism. Practically, YHM may represent an effective ergogenic aid to combat a lack of energy and low performance during the morning.

Abstract Task-related neural activity is widespread across populations of neurons during goal-directed behaviors. However, little is known about the synaptic reorganization and circuit mechanisms that lead to broad activity changes. Here we trained a subset of neurons in a spiking network with strong synaptic interactions to reproduce the activity of neurons in the motor cortex during a decision-making task. Task-related activity, resembling the neural data, emerged across the network, even in the untrained neurons. Analysis of trained networks showed that strong untrained synapses, which were independent of the task and determined the dynamical state of the network, mediated the spread of task-related activity. Optogenetic perturbations suggest that the motor cortex is strongly-coupled, supporting the applicability of the mechanism to cortical networks. Our results reveal a cortical mechanism that facilitates distributed representations of task-variables by spreading the activity from a subset of plastic neurons to the entire network through task-independent strong synapses.

We developed an inherently interpretable multilevel Bayesian framework for representing variation in regression coefficients that mimics the piecewise linearity of ReLU-activated deep neural networks. We used the framework to formulate a survival model for using medical claims to predict hospital readmission and death that focuses on discharge placement, adjusting for confounding in estimating causal local average treatment effects. We trained the model on a 5% sample of Medicare beneficiaries from 2008 and 2011, based on their 2009-2011 inpatient episodes (approximately 1.2 million), and then tested the model on 2012 episodes (approximately 400 thousand). The model scored an out-of-sample AUROC of approximately 0.75 on predicting all-cause readmissions-defined using official Centers for Medicare and Medicaid Services (CMS) methodology-or death within 30-days of discharge, being competitive against XGBoost and a Bayesian deep neural network, demonstrating that one need-not sacrifice interpretability for accuracy. Crucially, as a regression model, it provides what blackboxes cannot-its exact gold-standard global interpretation, explicitly defining how the model performs its internal "reasoning" for mapping the input data features to predictions. In doing so, we identify relative risk factors and quantify the effect of discharge placement. We also show that the posthoc explainer SHAP provides explanations that are inconsistent with the ground truth model reasoning that our model readily admits.

Purpose: To report a case of overload venous choroidopathy in a patient with superior vena cava syndrome. Observations: A patient presented with episcleral vessel dilation, bilateral subretinal fluid accumulations in the maculae and unilateral serous choroidal detachment. He had a medical history of kidney transplantation and was on chronic corticosteroids. Separately he had also experienced recurrent bilateral innominate vein occlusion and superior vena cava stenosis, consistent with a diagnosis of superior vena cava syndrome. His presentation was further complicated by a retinal vein occlusion in the left eye which was treated with anti-vascular endothelial growth factor intravitreal injections. The bilateral subretinal fluid accumulations responded well to photodynamic therapy. Conclusions and Importance: We report a constellation of findings including venous overload choroidopathy and retinal vein occlusion as ocular manifestations of superior vena cava syndrome. The pathophysiologic changes leading to these findings could aid in the understanding of these related conditions.

mRNA regulatory sequences control gene expression at multiple levels including translation initiation and mRNA decay. The 5' terminal sequences of mRNAs have unique regulatory potential because of their proximity to key post-transcriptional regulators. Here we have systematically probed the function of 5' terminal sequences in gene expression in human cells. Using a library of reporter mRNAs initiating with all possible 7-mer sequences at their 5' ends, we find an unexpected impact on transcription that underlies 200-fold differences in mRNA expression. Library sequences that promote high levels of transcription mirrored those found in native mRNAs and define two basic classes with similarities to classic Initiator (Inr) and TCT core promoter motifs. By comparing transcription, translation and decay rates, we identify sequences that are optimized for both efficient transcription and growth-regulated translation and stability, including variants of terminal oligopyrimidine (TOP) motifs. We further show that 5' sequences of endogenous mRNAs are enriched for multi-functional TCT/TOP hybrid sequences. Together, our results reveal how 5' sequences define two general classes of mRNAs with distinct growth-responsive profiles of expression across synthesis, translation and decay.

COVID-19 presentations range from mild to moderate through severe disease but also manifest with persistent illness or viral recrudescence. We hypothesized that the spectrum of COVID-19 disease manifestations was a consequence of SARS-CoV-2-mediated delay in the pathogen-associated molecular pattern (PAMP) response, including dampened type I interferon signaling, thereby shifting the balance of the immune response to be dominated by damage-associated molecular pattern (DAMP) signaling. To test the hypothesis, we constructed a parsimonious mechanistic mathematical model. After calibration of the model for initial viral load and then by varying a few key parameters, we show that the core model generates four distinct viral load, immune response and associated disease trajectories termed “patient archetypes”, whose temporal dynamics are reflected in clinical data from hospitalized COVID-19 patients. The model also accounts for responses to corticosteroid therapy and predicts that vaccine-induced neutralizing antibodies and cellular memory will be protective, including from severe COVID-19 disease. This generalizable modeling framework could be used to analyze protective and pathogenic immune responses to diverse viral infections.

Identifying neural substrates of behavior requires defining actions in terms that map onto brain activity. Brain and muscle activity naturally correlate via the output of motor neurons, but apart from simple movements it has been difficult to define behavior in terms of muscle contractions. By mapping the musculature of the pupal fruit fly and comprehensively imaging muscle activation at single-cell resolution, we here describe a multiphasic behavioral sequence in Drosophila. Our characterization identifies a previously undescribed behavioral phase and permits extraction of major movements by a convolutional neural network. We deconstruct movements into a syllabary of co-active muscles and identify specific syllables that are sensitive to neuromodulatory manipulations. We find that muscle activity shows considerable variability, with sequential increases in stereotypy dependent upon neuromodulation. Our work provides a platform for studying whole-animal behavior, quantifying its variability across multiple spatiotemporal scales, and analyzing its neuromodulatory regulation at cellular resolution.

Replacement of dysfunctional retinal pigmented epithelium (RPE) with grafts derived from stem cells has the potential to improve vision for patients with retinal disorders. In fact, the potential is such that a great number of groups are attempting to realize this therapy through individual strategies with a variety of stem cell products, hosts, immunomodulatory regimen, and techniques to assess the success of their design. Comparing the findings of different investigators is complicated by a number of factors. The immune response varies greatly between xenogeneic and allogeneic transplantation. A unique immunologic environment is created in the subretinal space, the target of RPE grafts. Both functional assessment and imaging techniques used to evaluate transplants are susceptible to erroneous conclusions. Lastly, the pharmacologic regimens used in RPE transplant trials are as numerous and variable as the trials themselves, making it difficult to determine useful results. This review will discuss the causes of these complicating factors, digest the strategies and results from clinical and preclinical studies, and suggest places for improvement in the design of future transplants and investigations.

The purpose of this study was to examine the effects of preferred versus non-preferred music volume on relative power output, trial time to completion (TTC), heart rate (HR), rate of perceived exertion (RPE), and motivation during endurance rowing exercise. Physically active females (age 18–25) volunteered to participate. In a crossover counterbalanced design, participants completed two trials: non-preferred (NPV) and preferred (PV) music volume. Participants began with a rowing warm-up at 50% of HRmax for 5 min. Following this, participants completed a 2000 m rowing time trial as quickly as possible. Relative power output, HR, and RPE were documented each minute during the exercise bout. TTC and motivation levels were documented at the cessation of exercise. Results showed that there were no significant differences between NPV and PV for relative power output (p = 0.287; d = 0.17), TTC (p = 0.816; d = 0.01), and HR (p = 0.956; d = 0.08). However, RPE was significantly lower (p = 0.002; d = 0.86) and motivation was significantly higher (p < 0.001; d = 2.14) during the PV condition versus NPV. Findings suggest that while PV does not impart performance-enhancing effects during endurance exercise compared to NPV, it may improve psychological responses related to intensity and effort which could have important implications for enduring intense exercise and training.

Cortical spreading depression (CSD) is the propagation of a relatively slow wave in cortical brain tissue that is linked to a number of pathological conditions such as stroke and migraine. Most of the existing literature investigates the dynamics of short term phenomena such as the depolarization and repolarization of membrane potentials or large ion shifts. Here, we focus on the clinically-relevant hour-long state of neurovascular malfunction in the wake of CSDs. This dysfunctional state involves widespread vasoconstriction and a general disruption of neurovascular coupling. We demonstrate, using a mathematical model, that dissolution of calcium that has aggregated within the mitochondria of vascular smooth muscle cells can drive an hour-long disruption. We model the rate of calcium clearance as well as the dynamical implications on overall blood flow. Based on reaction stoichiometry, we quantify a possible impact of calcium phosphate dissolution on the maintenance of F0F1-ATP synthase activity.

Supraphysiological MYC levels are oncogenic. Originally considered a typical transcription factor recruited to E-boxes (CACGTG), another theory posits MYC a global amplifier increasing output at all active promoters. Both models rest on large-scale genome-wide ”-omics’. Because the assumptions, statistical parameter and model choice dictates the ‘-omic’ results, whether MYC is a general or specific transcription factor remains controversial. Therefore, an orthogonal series of experiments interrogated MYC’s effect on the expression of synthetic reporters. Dose-dependently, MYC increased output at minimal promoters with or without an E-box. Driving minimal promoters with exogenous (glucocorticoid receptor) or synthetic transcription factors made expression more MYC-responsive, effectively increasing MYC-amplifier gain. Mutations of conserved MYC-Box regions I and II impaired amplification, whereas MYC-box III mutations delivered higher reporter output indicating that MBIII limits over-amplification. Kinetic theory and experiments indicate that MYC activates at least two steps in the transcription-cycle to explain the non-linear amplification of transcription that is essential for global, supraphysiological transcription in cancer.

The National Comprehensive Cancer Network expanded their lung cancer screening (LCS) criteria to comprise one additional clinical risk factor, including chronic obstructive pulmonary disease (COPD). The electronic medical record (EMR) is a source of clinical information that could identify high-risk populations for LCS, including a diagnosis of COPD; however, an unsubstantiated COPD diagnosis in the EMR may lead to inappropriate LCS referrals. We aimed to detect the prevalence of unsubstantiated COPD diagnosis in the EMR for LCS referrals, to determine the efficacy of utilizing the EMR as an accurate population-based eligibility screening “trigger” using modified clinical criteria. We performed a multicenter review of all individuals referred to three LCS programs from 2012 to 2015. Each individual’s EMR was searched for COPD diagnostic terms and the presence of a diagnostic pulmonary functionality test (PFT). An unsubstantiated COPD diagnosis was defined by an individual’s EMR containing a COPD term with no PFTs present, or the presence of PFTs without evidence of obstruction. A total of 2834 referred individuals were identified, of which 30% (840/2834) had a COPD term present in their EMR. Of these, 68% (571/840) were considered unsubstantiated diagnoses: 86% (489/571) due to absent PFTs and 14% (82/571) due to PFTs demonstrating no evidence of postbronchodilation obstruction. A large proportion of individuals referred for LCS may have an unsubstantiated COPD diagnosis within their EMR. Thus, utilizing the EMR as a population-based eligibility screening tool, employing expanded criteria, may lead to individuals being referred, potentially, inappropriately for LCS.

A postsecondary education holds the promise of higher lifetime earnings and social mobility, but too many low-income students never complete their degrees. We propose a set of policy recommendations based on the highly effective Accelerated Study in Associate Programs (ASAP) at the City University of New York (CUNY). CUNY ASAP is a comprehensive and integrated program that addresses multiple barriers to student success by providing students with enhanced advising as well as academic and career services, financial support, and a highly structured degree pathway. ASAP has been shown to have large positive effects on associate degree graduation rates and to cost less per graduate than regular college services. A national policy based on the ASAP model could serve as a highly effective anti-poverty strategy.

The mammalian target of rapamycin complex 1 (mTORC1) is a master regulator of cell growth that is commonly deregulated in human diseases. Here we find that mTORC1 controls a transcriptional program encoding amino acid transporters and metabolic enzymes through a mechanism also used to regulate protein synthesis. Bioinformatic analysis of mTORC1-responsive mRNAs identified a promoter element recognized by activating transcription factor 4 (ATF4), a key effector of the integrated stress response. ATF4 translation is normally induced by the phosphorylation of eukaryotic initiation factor 2 alpha (eIF2α) through a mechanism that requires upstream open reading frames (uORFs) in the ATF4 5′ UTR. mTORC1 also controls ATF4 translation through uORFs, but independently of changes in eIF2α phosphorylation. mTORC1 instead employs the 4E-binding protein (4E-BP) family of translation repressors. These results link mTORC1-regulated demand for protein synthesis with an ATF4-regulated transcriptional program that controls the supply of amino acids to the translation machinery.

The aim of a genome-wide association study (GWAS) is to identify loci in the human genome affecting a phenotype of interest. This review summarizes some recent work on conceptual and methodological aspects of GWAS. The average effect of gene substitution at a given causal site in the genome is the key estimand in GWAS, and we argue for its fundamental importance. Implicit in the definition of average effect is a linear model relating genotype to phenotype. The fraction of the phenotypic variance ascribable to polymorphic sites with nonzero average effects in this linear model is called the heritability, and we describe methods for estimating this quantity from GWAS data. Finally, we show that the theory of compressed sensing can be used to provide a sharp estimate of the sample size required to identify essentially all sites contributing to the heritability of a given phenotype.

Spiking activity of neurons engaged in learning and performing a task show complex spatiotemporal dynamics. While the output of recurrent network models can learn to perform various tasks, the possible range of recurrent dynamics that emerge after learning remains unknown. Here we show that modifying the recurrent connectivity with a recursive least squares algorithm provides sufficient flexibility for synaptic and spiking rate dynamics of spiking networks to produce a wide range of spatiotemporal activity. We apply the training method to learn arbitrary firing patterns, stabilize irregular spiking activity in a network of excitatory and inhibitory neurons respecting Dale’s law, and reproduce the heterogeneous spiking rate patterns of cortical neurons engaged in motor planning and movement. We identify sufficient conditions for successful learning, characterize two types of learning errors, and assess the network capacity. Our findings show that synaptically-coupled recurrent spiking networks possess a vast computational capability that can support the diverse activity patterns in the brain.

Glucocorticoid steroids are among the most prescribed drugs each year. Nonetheless, the many undesirable side effects, and lack of selectivity, restrict their greater usage. Research to increase glucocorticoid specificity has spanned many years. These efforts have been hampered by the ability of glucocorticoids to both induce and repress gene transcription and also by the lack of success in defining any predictable properties that control glucocorticoid specificity. Correlations of transcriptional specificity have been observed with changes in steroid structure, receptor and chromatin conformation, DNA sequence for receptor binding, and associated cofactors. However, none of these studies have progressed to the point of being able to offer guidance for increased specificity. We summarize here a mathematical theory that allows a novel and quantifiable approach to increase selectivity. The theory applies to all three major actions of glucocorticoid receptors: induction by agonists, induction by antagonists, and repression by agonists. Simple graphical analysis of competition assays involving any two factors (steroid, chemical, peptide, protein, DNA, etc.) yields information (1) about the kinetically described mechanism of action for each factor at that step where the factor acts in the overall reaction sequence and (2) about the relative position of that step where each factor acts. These two pieces of information uniquely provide direction for increasing the specificity of glucocorticoid action. Consideration of all three modes of action indicate that the most promising approach for increased specificity is to vary the concentrations of those cofactors/pharmaceuticals that act closest to the observed end point. The potential for selectivity is even greater when varying cofactors/pharmaceuticals in conjunction with a select class of antagonists.

AbstractObjective We investigated associations between changes in national food energy supply and in average population body weight.Methods We collected data from 24 high-, 27 middle- and 18 low-income countries on the average measured body weight from global databases, national health and nutrition survey reports and peer-reviewed papers. Changes in average body weight were derived from study pairs that were at least four years apart (various years, 1971-2010). Selected study pairs were considered to be representative of an adolescent or adult population, at national or subnational scale. Food energy supply data were retrieved from the Food and Agriculture Organization of the United Nations food balance sheets. We estimated the population energy requirements at survey time points using Institute of Medicine equations. Finally, we estimated the change in energy intake that could theoretically account for the observed change in average body weight using an experimentally-validated model.Findings In 56 countries, an increase in food energy supply was associated with an increase in average body weight. In 45 countries, the increase in food energy supply was higher than the model-predicted increase in energy intake. The association between change in food energy supply and change in body weight was statistically significant overall and for high-income countries (P< 0.001).Conclusion The findings suggest that increases in food energy supply are sufficient to explain increases in average population body weight, especially in high-income countries. Policy efforts are needed to improve the healthiness of food systems and environments to reduce global obesity.

The different amounts of residual partial agonist activity (PAA) of antisteroids under assorted conditions have long been useful in clinical applications but remain largely unexplained. Not only does a given antagonist often afford unequal induction for multiple genes in the same cell but also the activity of the same antisteroid with the same gene changes with variations in concentration of numerous cofactors. Using glucocorticoid receptors as a model system, we have recently succeeded in constructing from first principles a theory that accurately describes how cofactors can modulate the ability of agonist steroids to regulate both gene induction and gene repression. We now extend this framework to the actions of antisteroids in gene induction. The theory shows why changes in PAA cannot be explained simply by differences in ligand affinity for receptor and requires action at a second step or site in the overall sequence of reactions. The theory also provides a method for locating the position of this second site, relative to a concentration limited step (CLS), which is a previously identified step in glucocorticoid-regulated transactivation that always occurs at the same position in the overall sequence of events of gene induction. Finally, the theory predicts that classes of antagonist ligands may be grouped on the basis of their maximal PAA with excess added cofactor and that the members of each class differ by how they act at the same step in the overall gene induction process. Thus, this theory now makes it possible to predict how different cofactors modulate antisteroid PAA, which should be invaluable in developing more selective antagonists.

Policymakers must make management decisions despite incomplete knowledge and conflicting model projections. Little guidance exists for the rapid, representative, and unbiased collection of policy-relevant scientific input from independent modeling teams. Integrating approaches from decision analysis, expert judgment, and model aggregation, we convened multiple modeling teams to evaluate COVID-19 reopening strategies for a mid-sized United States county early in the pandemic. Projections from seventeen distinct models were inconsistent in magnitude but highly consistent in ranking interventions. The 6-mo-ahead aggregate projections were well in line with observed outbreaks in mid-sized US counties. The aggregate results showed that up to half the population could be infected with full workplace reopening, while workplace restrictions reduced median cumulative infections by 82%. Rankings of interventions were consistent across public health objectives, but there was a strong trade-off between public health outcomes and duration of workplace closures, and no win-win intermediate reopening strategies were identified. Between-model variation was high; the aggregate results thus provide valuable risk quantification for decision making. This approach can be applied to the evaluation of management interventions in any setting where models are used to inform decision making. This case study demonstrated the utility of our approach and was one of several multimodel efforts that laid the groundwork for the COVID-19 Scenario Modeling Hub, which has provided multiple rounds of real-time scenario projections for situational awareness and decision making to the Centers for Disease Control and Prevention since December 2020.

It has been shown that the same canonical cortical circuit model with mutual inhibition and a fatigue process can explain perceptual rivalry and other neurophysiological responses to a range of static stimuli. However, it has been proposed that this model cannot explain responses to dynamic inputs such as found in intermittent rivalry and rivalry memory, where maintenance of a percept when the stimulus is absent is required. This challenges the universality of the basic canonical cortical circuit. Here, we show that by including an overlooked realistic small nonspecific background neural activity, the same basic model can reproduce intermittent rivalry and rivalry memory without compromising static rivalry and other cortical phenomena. The background activity induces a mutual-inhibition mechanism for short-term memory, which is robust to noise and where fine-tuning of recurrent excitation or inclusion of sub-threshold currents or synaptic facilitation is unnecessary. We prove existence conditions for the mechanism and show that it can explain experimental results from the quartet apparent motion illusion, which is a prototypical intermittent rivalry stimulus.

Substituting sugar-free for sugar-sweetened beverages reduces weight gain. This effect may be more pronounced in children with a high body mass index (BMI) because their sensing of kilocalories might be compromised. We investigated the impact of sugar-free versus sugary drinks separately in children with a higher and a lower initial BMI z score, and predicted caloric intakes and degree of compensation in the two groups.This is a secondary, explorative analysis of our double-blind randomized controlled trial (RCT) which showed that replacement of one 250-mL sugary drink per day by a sugar-free drink for 18 months significantly reduced weight gain. In the 477 children who completed the trial, mean initial weights were close to the Dutch average. Only 16% were overweight and 3% obese. Weight changes were expressed as BMI z-score, i.e. as standard deviations of the BMI distribution per age and sex group. We designated the 239 children with an initial BMI z-score below the median as 'lower BMI' and the 238 children above the median as 'higher BMI'. The difference in caloric intake from experimental beverages between treatments was 86 kcal/day both in the lower and in the higher BMI group. We used a multiple linear regression and the coefficient of the interaction term (initial BMI group times treatment), indicated whether children with a lower BMI responded differently from children with a higher BMI. Statistical significance was defined as p ≤ 0.05. Relative to the sugar sweetened beverage, consumption of the sugar-free beverage for 18 months reduced the BMI z-score by 0.05 SD units within the lower BMI group and by 0.21 SD within the higher BMI group. Body weight gain was reduced by 0.62 kg in the lower BMI group and by 1.53 kg in the higher BMI group. Thus the treatment reduced the BMI z-score by 0.16 SD units more in the higher BMI group than in the lower BMI group (p = 0.04; 95% CI -0.31 to -0.01). The impact of the intervention on body weight gain differed by 0.90 kg between BMI groups (p = 0.09; 95% CI -1.95 to 0.14). In addition, we used a physiologically-based model of growth and energy balance to estimate the degree to which children had compensated for the covertly removed sugar kilocalories by increasing their intake of other foods. The model predicts that children with a lower BMI had compensated 65% (95% CI 28 to 102) of the covertly removed sugar kilocalories, whereas children with a higher BMI compensated only 13% (95% CI -37 to 63).The children with a BMI above the median might have a reduced tendency to compensate for changes in caloric intake. Differences in these subconscious compensatory mechanisms may be an important cause of differences in the tendency to gain weight. If further research bears this out, cutting down on the intake of sugar-sweetened drinks may benefit a large proportion of children, especially those who show a tendency to become overweight.ClinicalTrials.gov NCT00893529.

Gene repression by transcription factors, and glucocorticoid receptors (GR) in particular, is a critical, but poorly understood, physiological response. Among the many unresolved questions is the difference between GR regulated induction and repression, and whether transcription cofactor action is the same in both. Because activity classifications based on changes in gene product level are mechanistically uninformative, we present a theory for gene repression in which the mechanisms of factor action are defined kinetically and are consistent for both gene repression and induction. The theory is generally applicable and amenable to predictions if the dose-response curve for gene repression is non-cooperative with a unit Hill coefficient, which is observed for GR-regulated repression of AP1LUC reporter induction by phorbol myristate acetate. The theory predicts the mechanism of GR and cofactors, and where they act with respect to each other, based on how each cofactor alters the plots of various kinetic parameters vs. cofactor. We show that the kinetically-defined mechanism of action of each of four factors (reporter gene, p160 coactivator TIF2, and two pharmaceuticals [NU6027 and phenanthroline]) is the same in GR-regulated repression and induction. What differs is the position of GR action. This insight should simplify clinical efforts to differentially modulate factor actions in gene induction vs. gene repression.

Synthesis of mRNA in eukaryotes involves the coordinated action of many enzymatic processes, including initiation, elongation, splicing, and cleavage. Kinetic competition between these processes has been proposed to determine RNA fate, yet such coupling has never been observed in vivo on single transcripts. In this study, we use dual-color single-molecule RNA imaging in living human cells to construct a complete kinetic profile of transcription and splicing of the β-globin gene. We find that kinetic competition results in multiple competing pathways for pre-mRNA splicing. Splicing of the terminal intron occurs stochastically both before and after transcript release, indicating there is not a strict quality control checkpoint. The majority of pre-mRNAs are spliced after release, while diffusing away from the site of transcription. A single missense point mutation (S34F) in the essential splicing factor U2AF1 which occurs in human cancers perturbs this kinetic balance and defers splicing to occur entirely post-release.

Much progress has been made in uncovering the computational capabilities of spiking neural networks. However, spiking neurons will always be more expensive to simulate compared to rate neurons because of the inherent disparity in time scales - the spike duration time is much shorter than the inter-spike time, which is much shorter than any learning time scale. In numerical analysis, this is a classic stiff problem. Spiking neurons are also much more difficult to study analytically. One possible approach to making spiking networks more tractable is to augment mean field activity models with some information about spiking correlations. For example, such a generalized activity model could carry information about spiking rates and correlations between spikes self-consistently. Here, we will show how this can be accomplished by constructing a complete formal probabilistic description of the network and then expanding around a small parameter such as the inverse of the number of neurons in the network. The mean field theory of the system gives a rate-like description. The first order terms in the perturbation expansion keep track of covariances.

We investigate the dynamics of a deterministic finite-sized network of synaptically coupled spiking neurons and present a formalism for computing the network statistics in a perturbative expansion. The small parameter for the expansion is the inverse number of neurons in the network. The network dynamics are fully characterized by a neuron population density that obeys a conservation law analogous to the Klimontovich equation in the kinetic theory of plasmas. The Klimontovich equation does not possess well-behaved solutions but can be recast in terms of a coupled system of well-behaved moment equations, known as a moment hierarchy. The moment hierarchy is impossible to solve but in the mean field limit of an infinite number of neurons, it reduces to a single well-behaved conservation law for the mean neuron density. For a large but finite system, the moment hierarchy can be truncated perturbatively with the inverse system size as a small parameter but the resulting set of reduced moment equations that are still very difficult to solve. However, the entire moment hierarchy can also be re-expressed in terms of a functional probability distribution of the neuron density. The moments can then be computed perturbatively using methods from statistical field theory. Here we derive the complete mean field theory and the lowest order second moment corrections for physiologically relevant quantities. Although we focus on finite-size corrections, our method can be used to compute perturbative expansions in any parameter.

Cofactors are intimately involved in steroid-regulated gene expression. Two critical questions are (1) the steps at which cofactors exert their biological activities and (2) the nature of that activity. Here we show that a new mathematical theory of steroid hormone action can be used to deduce the kinetic properties and reaction sequence position for the functioning of any two cofactors relative to a concentration limiting step (CLS) and to each other. The predictions of the theory, which can be applied using graphical methods similar to those of enzyme kinetics, are validated by obtaining internally consistent data for pair-wise analyses of three cofactors (TIF2, sSMRT, and NCoR) in U2OS cells. The analysis of TIF2 and sSMRT actions on GR-induction of an endogenous gene gave results identical to those with an exogenous reporter. Thus new tools to determine previously unobtainable information about the nature and position of cofactor action in any process displaying first-order Hill plot kinetics are now available.

We used a bivariate (multivariate) linear mixed-effects model to estimate the narrow-sense heritability (h(2)) and heritability explained by the common SNPs (h(g)(2)) for several metabolic syndrome (MetS) traits and the genetic correlation between pairs of traits for the Atherosclerosis Risk in Communities (ARIC) genome-wide association study (GWAS) population. MetS traits included body-mass index (BMI), waist-to-hip ratio (WHR), systolic blood pressure (SBP), fasting glucose (GLU), fasting insulin (INS), fasting trigylcerides (TG), and fasting high-density lipoprotein (HDL). We found the percentage of h(2) accounted for by common SNPs to be 58% of h(2) for height, 41% for BMI, 46% for WHR, 30% for GLU, 39% for INS, 34% for TG, 25% for HDL, and 80% for SBP. We confirmed prior reports for height and BMI using the ARIC population and independently in the Framingham Heart Study (FHS) population. We demonstrated that the multivariate model supported large genetic correlations between BMI and WHR and between TG and HDL. We also showed that the genetic correlations between the MetS traits are directly proportional to the phenotypic correlations.

The use of noninvasive transcranial electrical stimulation (tES) has rapidly increased over the past two decades. Yet, tES continues to be largely implemented in laboratory and rehabilitation settings, thereby limiting accessibility to the broader population. We have previously demonstrated that transcranial alternating current stimulation (tACS) in the theta (4-7 Hz) band improves cognitive control, such as multitasking, in younger adults following a single tACS session, as well as in older adults following three tACS sessions. Here, the goal was to extend our in-lab results by (1) assessing the feasibility for at-home tACS and (2) evaluating whether five tACS sessions may yield continuing improvements in multitasking ability in young adults. Participants (aged 18 - 34 years) received bilateral prefrontal tACS while engaged in an adaptive multitasking training over five consecutive days in their home settings. Participants were randomly assigned to receive either 20-minutes of theta or delta tACS during daily multitasking training. Prior to and on the day immediately following five days of tACS, we assessed performance on single task, multitask, and sustained attention ability with analyses of variance statistics. 92.1% of participants were able to self-administer tACS at home without researcher assistance. However, we observed that both theta and delta tACS groups exhibited improvements in both single and multitask performance. Compared to previously collected data, five days of theta tACS was comparable to one day of theta tACS. However, theta tACS has continued benefits in older, but not younger adults as evidenced by previous research. Both groups similarly improved in sustained attention. These results demonstrate that laboratory paradigms utilizing neurostimulation can be effectively deployed in a home environment without direct support from research personnel. Moreover, these results suggest that while theta tACS may facilitate multitasking improvements over one session, multiple sessions of theta tACS results in diminishing returns in young adults. Additional research will be required to confirm if delta activity plays an important role in multitasking ability.

G protein-coupled receptors (GPCRs) are a superfamily of integral membrane proteins vital for signaling and are important targets for pharmaceutical intervention in humans. Previously, we identified a group of ten amino acid positions (called key positions), within the seven transmembrane domain (7TM) interhelical region, which had high mutual information with each other and many other positions in the 7TM. Here, we estimated the evolutionary selection pressure at those key positions. We found that the key positions of receptors for small molecule natural ligands were under strong negative selection. Receptors naturally activated by lipids had weaker negative selection in general when compared to small molecule-activated receptors. Selection pressure varied widely in peptide-activated receptors. We used this observation to predict that a subgroup of orphan GPCRs not under strong selection may not possess a natural small-molecule ligand. In the subgroup of MRGX1-type GPCRs, we identified a key position, along with two non-key positions, under statistically significant positive selection.

Food waste contributes to excess consumption of freshwater and fossil fuels which, along with methane and CO(2) emissions from decomposing food, impacts global climate change. Here, we calculate the energy content of nationwide food waste from the difference between the US food supply and the food consumed by the population. The latter was estimated using a validated mathematical model of metabolism relating body weight to the amount of food eaten. We found that US per capita food waste has progressively increased by approximately 50% since 1974 reaching more than 1400 kcal per person per day or 150 trillion kcal per year. Food waste now accounts for more than one quarter of the total freshwater consumption and approximately 300 million barrels of oil per year.

G protein-coupled receptors (GPCRs) are a superfamily of seven transmembrane-spanning proteins involved in a wide array of physiological functions and are the most common targets of pharmaceuticals. This study aims to identify a cohort or clique of positions that share high mutual information. Using a multiple sequence alignment of the transmembrane (TM) domains, we calculated the mutual information between all inter-TM pairs of aligned positions and ranked the pairs by mutual information. A mutual information graph was constructed with vertices that corresponded to TM positions and edges between vertices were drawn if the mutual information exceeded a threshold of statistical significance. Positions with high degree (i.e. had significant mutual information with a large number of other positions) were found to line a well defined inter-TM ligand binding cavity for class A as well as class C GPCRs. Although the natural ligands of class C receptors bind to their extracellular N-terminal domains, the possibility of modulating their activity through ligands that bind to their helical bundle has been reported. Such positions were not found for class B GPCRs, in agreement with the observation that there are not known ligands that bind within their TM helical bundle. All identified key positions formed a clique within the MI graph of interest. For a subset of class A receptors we also considered the alignment of a portion of the second extracellular loop, and found that the two positions adjacent to the conserved Cys that bridges the loop with the TM3 qualified as key positions. Our algorithm may be useful for localizing topologically conserved regions in other protein families.

An imbalance between energy intake and energy expenditure will lead to a change in body weight (mass) and body composition (fat and lean masses). A quantitative understanding of the processes involved, which currently remains lacking, will be useful in determining the etiology and treatment of obesity and other conditions resulting from prolonged energy imbalance. Here, we show that a mathematical model of the macronutrient flux balances can capture the long-term dynamics of human weight change; all previous models are special cases of this model. We show that the generic dynamic behavior of body composition for a clamped diet can be divided into two classes. In the first class, the body composition and mass are determined uniquely. In the second class, the body composition can exist at an infinite number of possible states. Surprisingly, perturbations of dietary energy intake or energy expenditure can give identical responses in both model classes, and existing data are insufficient to distinguish between these two possibilities. Nevertheless, this distinction has important implications for the efficacy of clinical interventions that alter body composition and mass.

We conducted genome-wide association studies (GWAS) of relative intake from the macronutrients fat, protein, carbohydrates, and sugar in over 235,000 individuals of European ancestries. We identified 21 unique, approximately independent lead SNPs. Fourteen lead SNPs are uniquely associated with one macronutrient at genome-wide significance (P

Over 70% of undergraduate students hold part-time jobs while in college. Certain aspects are positively and/or negatively impacted by employment in college, such as a student's academic performance, relationships, and self-worth. As such, research examining factors that might positively influence work-related outcomes (and subsequent collegiate experiences) for student workers is warranted. The current work utilized the Leader-Member Exchange as a theoretical framework to examine how work-related factors (i.e., leadership qualities and the supervisor-employee relationship) impact job satisfaction among student workers. Seventy-eight undergraduate students completed the study. Leadership qualities and supervisor-employee relationship positively correlated with job satisfaction; however, further analysis revealed that the relationship between the supervisor and employee was a significant mediator. These findings add unique information to prior research and might be used by individuals who work with student employees. Additional implications of this work as well as limitations are discussed.