Generation and dynamics of an endogenous, self-generated signaling gradient across a migrating tissue.

In animals, many cells reach their destinations by migrating toward higher concentrations of an attractant. However, the nature, generation, and interpretation of attractant gradients are poorly understood. Using a GFP fusion and a signaling sensor, we analyzed the distribution of the attractant chemokine Sdf1 during migration of the zebrafish posterior lateral line primordium, a cohort of about 200 cells that migrates over a stripe of cells uniformly expressing sdf1. We find that a small fraction of the total Sdf1 pool is available to signal and induces a linear Sdf1-signaling gradient across the primordium. This signaling gradient is initiated at the rear of the primordium, equilibrates across the primordium within 200 min, and operates near steady state. The rear of the primordium generates this gradient through continuous sequestration of Sdf1 protein by the alternate Sdf1-receptor Cxcr7. Modeling shows that this is a physically plausible scenario.

Economic analysis of high-oleic soybeans in dairy rations.

We evaluate the potential economic impact of using high-oleic soybeans (HOS) in dairy rations based on a synthesis of results from 5 prior feeding trials. Milk income less feed costs (MILFC) per cow per day is calculated based on assumed increases in milkfat production and increased cost of rations including HOS. The effects of changes in MILFC are evaluated for herds with different numbers of milking cows, and the total volume of HOS required to support different proportions of US dairy cows is calculated. A dynamic supply-chain model assesses the potential market impacts of increases in butterfat supply. The increase in milkfat from the substitution of 5% of ration dry matter with whole HOS (1.4 kg/cow per day) has the potential to increase MILFC by up to $0.27/cow per day or increase the average value of milk by $0.29/45.4 kg for a cow producing 41 kg/d. Changes in MILFC are highly correlated with the price of butter but were positive for butter prices observed from January 2014 to September 2020. The effects of HOS on MILFC suggest the potential for increases in farm profitability of $33,000/yr for a dairy feeding 500 milking cows. Scaled-up use of HOS by US dairy farmers would increase butterfat supplies and lower the butterfat price to a small extent, but these aggregated effects do not offset the positive effects of MILFC at the farm level.

Analysing the potential impacts of three interventions on fruit and vegetable consumption in urban Kenya using participatory systems modelling.

OBJECTIVE: This study uses participatory modelling with stakeholders to assess the potential impacts of three interventions intended to increase fruit and vegetable (F&V) consumption in urban Kenya. DESIGN: A participatory process using Group Model Building (GMB) developed a conceptual model of the determinants of vegetable consumption. A subsequent quantitative System Dynamics model using data from primary and secondary sources simulated vegetable consumption from 2020 to 2024 under three proposed interventions suggested by stakeholders: increasing consumer awareness, reducing post-harvest losses and increasing farm yields. Model analyses assumed mean parameter values and assessed uncertainty using 200 simulations with randomised parameter values. SETTING: The research was implemented in Nairobi, Kenya with simulation analyses of mean per capita consumption in this location. PARTICIPANTS: Workshops convened diverse F&V value chain stakeholders (farmers, government officials, NGO staff and technical experts) to develop the conceptual model, data inputs and intervention scenarios. RESULTS: Increasing consumer awareness was simulated to increase vegetable consumption by relatively modest amounts by 2024 (5 g/person/d from a base of 131 g/person/d) under mean assumed value of value chain response parameters. Reducing perishability was simulated to reduce consumption due to the higher costs required to reduce losses. Increasing farm yields was simulated to have the largest impact on consumption at assumed parameter values (about 40 g/person/d) but would have a negative impact on farm profits, which could undermine efforts to implement this intervention. CONCLUSIONS: The combination of GMB and simulation modelling informed intervention priorities for an important public health nutrition issue.

Rapid volume pulsation of the extracellular space coincides with epileptiform activity in mice and depends on the NBCe1 transporter.

KEY POINTS: Extracellular space (ECS) rapid volume pulsation (RVP) accompanying epileptiform activity is described for the first time. Such RVP occurs robustly in several in vitro and in vivo mouse models of epileptiform activity. In the in vitro 4-aminopyridine model of epileptiform activity, RVP depends on the activity of the electrogenic Na+ /HCO3- cotransporter (NBCe1). NBCe1 pharmacological inhibition suppresses RVP and epileptiform activity. Inhibition of changes in ECS volume may be a useful target in epilepsy patients who are resistant to current treatments. ​ ABSTRACT: The extracellular space (ECS) of the brain shrinks persistently by approximately 35% during epileptic seizures. Here we report the discovery of rapid volume pulsation (RVP), further transient drops in ECS volume which accompany events of epileptiform activity. These transient ECS contractions were observed in multiple mouse models of epileptiform activity both in vivo (bicuculline methiodide model) and in vitro (hyaluronan synthase 3 knock-out, picrotoxin, bicuculline and 4-aminopyridine models). By using the probe transients quantification (PTQ) method we show that individual pulses of RVP shrank the ECS by almost 15% in vivo. In the 4-aminopyridine in vitro model, the individual pulses of RVP shrank the ECS by more than 4%, and these transient changes were superimposed on a persistent ECS shrinkage of 36% measured with the real-time iontophoretic method. In this in vitro model, we investigated several channels and transporters that may be required for the generation of RVP and epileptiform activity. Pharmacological blockages of Na+ /K+ /2Cl- cotransporter type 1 (NKCC1), K+ /Cl- cotransporter (KCC2), the water channel aquaporin-4 (AQP4) and inwardly rectifying potassium channel 4.1 (Kir4.1) were ineffective in halting the RVP and the epileptiform activity. In contrast, pharmacological blockade of the electrogenic Na+ /HCO3- cotransporter (NBCe1) by 4,4'-diisothiocyano-2,2'-stilbenedisulfonic acid (DIDS) eliminated both the RVP and the persistent ECS shrinkage. Importantly, this blocker also stopped the epileptiform activity. These results demonstrate that RVP is closely associated with epileptiform activity across several models of epileptiform activity and therefore the underlying mechanism could potentially represent a novel target for epilepsy management and treatment.

Feature Extraction for Heroin-Use Classification Using Imbalanced Random Forest Methods.

BACKGROUND AND AIMS: The National Survey on Drug Use and Health (NSDUH) contains a large number of responses and many features. This study aims to identify features from within NSDUH that are important in classifying heroin use. Proper implementation of random forest (RF) techniques copes with the highly imbalanced nature of heroin usage among respondents to identify features that are prominent in classification models involving nonlinear combinations of predictive variables. To date, methods for the proper application of RF to imbalanced medical datasets have not been defined. Methods: Three different RF classification techniques are applied to the 2016 NSDUH. The techniques are compared using scoring criteria, including area under the precision recall curve (AUPRC), to identify the best model. Variable importance scores (VIS) are checked for stability across the three models and the VIS from the best model are used to highlight features and categories of features that most influence the classification of heroin users. Findings: The best performing method was RF with random oversampling (AUPRC = 0.5437). The category of features regarding other drug use was most important (average z-scored VIS = 1.66) followed by age-of-first-use features (0.32). The most important individual feature was cocaine usage (z-scored VIS = 11.05), followed by crack usage (6.51). The most important individual feature other than specific drug use flags was the use of marijuana under the age of 18 (3.11). This study demonstrates a method for the use of RF in feature extraction from imbalanced medical datasets with many predictors.

Corrections to "Visual Analytics for Decision-Making During Pandemics".

[This corrects the article DOI: 10.1109/MCSE.2020.3023288.].

COVID-19 and the agri-food system in the United States and Canada.

Agri-food supply chains in North America have become remarkably efficient, supplying an unprecedented variety of items at the lowest possible cost. However, the initial stages of the COVID-19 pandemic and the near-total temporary loss of the foodservice distribution channel, exposed a vulnerability that many found surprising. Instead of continued shortages, however, the agri-food sector has since moved back to near normal conditions with prices and production levels similar to those typically observed in years prior to the pandemic. Ironically, the specialization in most food supply chains designed for "just-in-time" delivery to specific customers with no reserve capacity, which led to the initial disruptions, may have also been responsible for its rapid rebound. A common theme in assessing the impacts across the six commodities examined is the growing importance of understanding the whole supply chain. Over the longer term, a continuation of the pandemic could push the supply chain toward greater consolidation of firms and diversification of products given the increasing option value of maintaining flexibility. Other structural changes will be felt through input markets, most notably labour, as the trend toward greater automation will continue to accelerate as a response to meeting concerns about a consistent supply of healthy and productive workers. The economic fall out from the pandemic may lead to greater concentration in the sector as some firms are not able to survive the downturn and changes in consumer food buying behaviour, including movement toward online shopping and enhanced demand for attributes associated with resiliency, such as local. On the other hand, online shopping may provide opportunities for small producers and processors to shorten supply chains and reach customers directly. In the long term, COVID-19 impacts on global commerce and developing country production are more uncertain and could influence poverty reduction. While COVID-19's impacts on North American agriculture should have minimal effect on the Sustainable Development Goals (SDGs) through food prices, the ongoing global trends in trade and agribusiness accelerated by the pandemic are relevant for achievement of the SDGs.

Reduction of Dimensionality in Monte Carlo Simulation of Diffusion in Extracellular Space Surrounding Cubic Cells.

The real-time iontophoretic method has measured volume fraction and tortuosity of the interstitial component of extracellular space in many regions and under different conditions. To interpret these data computer models of the interstitial space (ISS) of the brain are constructed by representing cells as Basic Cellular Structures (BCS) surrounded by a layer of ISS and replicating this combination to make a 3D ensemble that approximates brain tissue with a specified volume fraction. Tortuosity in such models is measured by releasing molecules of zero size into the ISS and allowing them to execute random walks in the ISS of the ensemble using a Monte Carlo algorithm. The required computational resources for such simulations may be high and here we show that in many situations the 3D problem may be reduced to a quasi-1D problem with consequent reduction in resources. We take the simplest BCS in the form of cubes and use MCell software to perform the Monte Carlo simulations but the analysis described here may be extended in principle to more complex BCS and an ISS that has a defined viscosity and an extracellular matrix that interacts with diffusing molecules. In the course of this study we found that the original analytical description of the relation between volume fraction and tortuosity for an ensemble of cubes may require a small correction.

Visual Analytics for Decision-Making During Pandemics.

We introduce a trans-disciplinary collaboration between researchers, healthcare practitioners, and community health partners in the Southwestern U.S. to enable improved management, response, and recovery to our current pandemic and for future health emergencies. Our Center work enables effective and efficient decision-making through interactive, human-guided analytical environments. We discuss our PanViz 2.0 system, a visual analytics application for supporting pandemic preparedness through a tightly coupled epidemiological model and interactive interface. We discuss our framework, current work, and plans to extend the system with exploration of what-if scenarios, interactive machine learning for model parameter inference, and analysis of mitigation strategies to facilitate decision-making during public health crises.

Interactions between insulin and diet on striatal dopamine uptake kinetics in rodent brain slices.

Diet influences dopamine transmission in motor- and reward-related basal ganglia circuitry. In part, this reflects diet-dependent regulation of circulating and brain insulin levels. Activation of striatal insulin receptors amplifies axonal dopamine release in brain slices, and regulates food preference in vivo. The effect of insulin on dopamine release is indirect, and requires striatal cholinergic interneurons that express insulin receptors. However, insulin also acts directly on dopamine axons to increase dopamine uptake by promoting dopamine transporter (DAT) surface expression, counteracting enhanced dopamine release. Here, we determined the functional consequences of acute insulin exposure and chronic diet-induced changes in insulin on DAT activity after evoked dopamine release in striatal slices from adult ad-libitum fed (AL) rats and mice, and food-restricted (FR) or high-fat/high-sugar obesogenic (OB) diet rats. Uptake kinetics were assessed by fitting evoked dopamine transients to the Michaelis-Menten equation and extracting Cpeak and Vmax . Insulin (30 nm) increased both parameters in the caudate putamen and nucleus accumbens core of AL rats in an insulin receptor- and PI3-kinase-dependent manner. A pure effect of insulin on uptake was unmasked using mice lacking striatal acetylcholine, in which increased Vmax caused a decrease in Cpeak . Diet also influenced Vmax , which was lower in FR vs. AL. The effects of insulin on Cpeak and Vmax were amplified by FR but blunted by OB, consistent with opposite consequences of these diets on insulin levels and insulin receptor sensitivity. Overall, these data reveal acute and chronic effects of insulin and diet on dopamine release and uptake that will influence brain reward pathways.

Brain Extracellular Space: The Final Frontier of Neuroscience.

Brain extracellular space is the narrow microenvironment that surrounds every cell of the central nervous system. It contains a solution that closely resembles cerebrospinal fluid with the addition of extracellular matrix molecules. The space provides a reservoir for ions essential to the electrical activity of neurons and forms an intercellular chemical communication channel. Attempts to reveal the size and structure of the extracellular space using electron microscopy have had limited success; however, a biophysical approach based on diffusion of selected probe molecules has proved useful. A point-source paradigm, realized in the real-time iontophoresis method using tetramethylammonium, as well as earlier radiotracer methods, have shown that the extracellular space occupies ∼20% of brain tissue and small molecules have an effective diffusion coefficient that is two-fifths that in a free solution. Monte Carlo modeling indicates that geometrical constraints, including dead-space microdomains, contribute to the hindrance to diffusion. Imaging the spread of macromolecules shows them increasingly hindered as a function of size and suggests that the gaps between cells are predominantly ∼40 nm with wider local expansions that may represent dead-spaces. Diffusion measurements also characterize interactions of ions and proteins with the chondroitin and heparan sulfate components of the extracellular matrix; however, the many roles of the matrix are only starting to become apparent. The existence and magnitude of bulk flow and the so-called glymphatic system are topics of current interest and controversy. The extracellular space is an exciting area for research that will be propelled by emerging technologies.

Variable neighborhood search for reverse engineering of gene regulatory networks.

A new search heuristic, Divided Neighborhood Exploration Search, designed to be used with inference algorithms such as Bayesian networks to improve on the reverse engineering of gene regulatory networks is presented. The approach systematically moves through the search space to find topologies representative of gene regulatory networks that are more likely to explain microarray data. In empirical testing it is demonstrated that the novel method is superior to the widely employed greedy search techniques in both the quality of the inferred networks and computational time.

Environmental and Economic Impacts of Localizing Food Systems: The Case of Dairy Supply Chains in the Northeastern United States.

We developed and evaluated an empirical model of the U.S. dairy supply chain with a high degree of spatial and product disaggregation to assess the impacts of increasing localization of the northeast region's fluid milk supply on food miles, supply chain costs, greenhouse gas and criteria pollutant emissions, economic activity, and employment. Evaluation included comparison to regional production values and sensitivity analysis of demand and unit cost assumptions. Our analysis compares a baseline to two localization scenarios based on state boundaries and multiple-state subregions. Localization scenarios increased total distances fluid milk traveled by 7-15%, overall supply chain costs by 1-2%, and emissions of greenhouse gases (CO2 equivalent) criteria pollutants such as oxides of nitrogen and particulate matter smaller than 2.5 µm associated with fluid milk transportation by 7-15% per month. The impacts of localization on employment and economic activity are positive, but changes are small on a percentage basis. Our analyses indicate that the definition used for localization has an impact on outcomes and that efforts to localize food systems may benefit from a more systems-oriented approach.

Restoration of Severely Atrophic Jaws.

For many patients, there is no other option. The CDI is an eposteal implant that becomes firmly attached to underlying bone. More than 25 years of experience with the implant have shown that the implant is capable of supporting both removable and fixed appliances. Once the many constituent factors of this process are understood and taken into account, the CDI becomes a powerful device in the armamentarium of the implant dentist. Furthermore, it often represents the only tool that can be employed to successfully correct cases involving severely atrophic jaws.

Sheet and void porous media models for brain interstitial space.

The interstitial space (ISS) component of brain extracellular space resembles an unconsolidated porous medium. Previous analysis of the diffusion of small molecules in this domain shows that the typical porosity is 0.2 and typical tortuosity 1.6. An ensemble of cubic cells separated by uniform sheets of ISS cannot generate the measured tortuosity, even if some of the tortuosity value is attributed to interstitial viscosity, so more complex models are needed. Here two models are analysed: the corner cubic void (CCV) and the edge tunnel void (ETV). Both models incorporate dead spaces formed from local expansions of the ISS to increase geometrical tortuosity. Using Monte Carlo simulation of diffusion it is found that in the range of normal porosities, the square of the tortuosity is a linear function of the ratio of void to sheet volumes for the CCV model and this model can generate the experimentally observed tortuosities. For abnormally high porosities, however, the linear relation fails. The ETV model shows a quartic functional relation and can only generate the observed tortuosity if interstitial viscosity is present. The CCV model is used to analyse the recently described changes in porosity between asleep and awake brain states.

Multiple-year farm-level assessments of trade-offs between GHG emissions and income: case examples of two farming systems in Northern Nigeria.

This study quantifies the trade-offs between welfare (measured by income) and greenhouse gas (GHG) emissions in two farming systems of Northern Nigeria using data for 5 years from 2015 to 2019. The analyses employ a farm-level optimization model that maximizes the value of production less purchased input costs for agricultural activities including the production of trees, sorghum, groundnut or soybeans, and multiple livestock species. We compare income and GHG emissions without constraints to scenarios requiring reductions in emissions of either 10% or the maximum reduction feasible while maintaining minimum household consumption levels. For both locations and all years, we find that reductions in GHG emissions would lower household incomes and require substantive modifications to production patterns and input use. However, the extents to which reductions are possible and the patterns of income-GHG trade-offs vary, indicating that such effects are site-specific and time-variable. The variable nature of these trade-offs suggests challenges for the design of any program that would seek to compensate farmers for reductions in their GHG emissions.

Economic analysis of alternative nutritional management of dual-purpose cow herds in central coastal Veracruz, Mexico.

Market information was combined with predicted input-output relationships in an economic analysis of alternative nutritional management for dual-purpose member herds of the Genesis farmer organization of central coastal Veracruz, Mexico. Cow productivity outcomes for typical management and alternative feeding scenarios were obtained from structured sets of simulations in a companion study of productivity limitations and potentials using the Cornell Net Carbohydrate and Protein System model (Version 6.0). Partial budgeting methods and sensitivity analysis were used to identify economically viable alternatives based on expected change in milk income over feed cost (change in revenues from milk sales less change in feed costs). Herd owners in coastal Veracruz have large economic incentives, from $584 to $1,131 in predicted net margin, to increase milk sales by up to 74% across a three-lactation cow lifetime by improving diets based on good quality grass and legume forages. This increment is equal to, or exceeds, in value the total yield from at least one additional lactation per cow lifetime. Furthermore, marginal rates of return (change in milk income over feed costs divided by change in variable costs when alternative practices are used) of 3.3 ± 0.8 indicate clear economic incentives to remove fundamental productivity vulnerabilities due to chronic energy deficits and impeded growth of immature cows under typical management. Sensitivity analyses indicate that the economic outcomes are robust for a variety of market conditions.

Limitations and potentials of dual-purpose cow herds in Central Coastal Veracruz, Mexico.

Feed chemical and kinetic composition and animal performance information was used to evaluate productivity limitations and potentials of dual-purpose member herds of the Genesis farmer organization of central coastal Veracruz, Mexico. The Cornell Net Carbohydrate and Protein System model (Version 6.0) was systematically applied to specific groups of cows in structured simulations to establish probable input-output relationships for typical management, and to estimate probable outcomes from alternative management based on forage-based dietary improvements. Key herd vulnerabilities were pinpointed: chronic energy deficits among dry cows of all ages in late gestation and impeded growth for immature cows. Regardless of the forage season of calving, most cows, if not all, incur energy deficits in the final trimester of gestation; thus reducing the pool of tissue energy and constraining milking performance. Under typical management, cows are smaller and underweight for their age, which limits feed intake capacity, milk production and the probability of early postpartum return to ovarian cyclicity. The substitution of good-quality harvested forage for grazing increased predicted yields by about one-third over typical scenarios for underweight cows. When diets from first parturition properly supported growth and tissue repletion, milk production in second and third lactations was predicted to improve about 60%. Judiciously supplemented diets based on good quality grass and legume forages from first calving were predicted to further increase productivity by about 80% across a three-lactation cow lifetime. These dual-purpose herd owners have large incentives to increase sales income by implementing nutritional strategies like those considered in this study.