WHEN PRICES MISS THE MARK: METHODS FOR VALUING ENVIRONMENTAL CHANGE

Environmental Economics and Policy,

The Energy Cost of Ambulation for Traumatic Paraplegics

The purpose of this study was to determine the energy cost of ambulation in traumatic paraplegics, and to lay the groundwork for continued study into the metabolism of these patients under various conditions. Objects of consideration were the level of lesion and the rate and type of gait. Samples of air were collected with the Max Planck respirometer, and gas analysis was done by the Scholander method. The patient walked for six minutes, and recovery samples were taken to determine oxygen debt. Calculations were made on the basis of calories consumed per kilogram of body weight per minute, and also calories per meter walked per kilogram of body weight. Comparison of these patients with normal subjects showed heavy energy expenditure on the part of all paraplegics, with marked increase as the level of lesion ascends. The question is raised as to the need of ambulation in all cases, and the substitution of one hour of standing daily is suggested as ample for physiologic benefit in those patients in whom ambulation is done at excessive cost. Consideration of all aspects of paraplegia is encouraged, with ambulation as a less important goal than other goals, and caution advised in verging too much physical activity on someone who already is suffering from severe stress reaction, and with limited respiratory ability. This information is also useful in showing certain patients that ambulation is an attainable and useful goal

Experimental evaluation of the generalized vibrational theory of G protein-coupled receptor activation

Herein, we test the present iteration of the vibrational theory of protein activation by comparing predictions obtained from Turin’s vibrational theory for the activation of olfactory receptors measuring affinity and activation at a nonolfactory receptor family of G protein-coupled receptors. This was done at the CNS serotonin receptor family h5-HT2 and with both the 2,5-dimethoxy-4-iodoamphetamine and N,N-dimethyllysergamide agonists. Invalidation was performed through a comparative analysis of agonist behavior between isotopologues

Disruption of beta cell acetyl-CoA carboxylase-1 in mice impairs insulin secretion and beta cell mass

Aims/hypothesis: Pancreatic beta cells secrete insulin to maintain glucose homeostasis, and beta cell failure is a hallmark of type 2 diabetes. Glucose triggers insulin secretion in beta cells via oxidative mitochondrial pathways. However, it also feeds mitochondrial anaplerotic pathways, driving citrate export and cytosolic malonyl-CoA production by the acetyl-CoA carboxylase 1 (ACC1) enzyme. This pathway has been proposed as an alternative glucose-sensing mechanism, supported mainly by in vitro data. Here, we sought to address the role of the beta cell ACC1-coupled pathway in insulin secretion and glucose homeostasis in vivo. Methods: Acaca, encoding ACC1 (the principal ACC isoform in islets), was deleted in beta cells of mice using the Cre/loxP system. Acaca floxed mice were crossed with Ins2cre mice (βACC1KO; life-long beta cell gene deletion) or Pdx1creER mice (tmx-βACC1KO; inducible gene deletion in adult beta cells). Beta cell function was assessed using in vivo metabolic physiology and ex vivo islet experiments. Beta cell mass was analysed using histological techniques. Results: βACC1KO and tmx-βACC1KO mice were glucose intolerant and had defective insulin secretion in vivo. Isolated islet studies identified impaired insulin secretion from beta cells, independent of changes in the abundance of neutral lipids previously implicated as amplification signals. Pancreatic morphometry unexpectedly revealed reduced beta cell size in βACC1KO mice but not in tmx-βACC1KO mice, with decreased levels of proteins involved in the mechanistic target of rapamycin kinase (mTOR)-dependent protein translation pathway underpinning this effect. Conclusions/interpretation: Our study demonstrates that the beta cell ACC1-coupled pathway is critical for insulin secretion in vivo and ex vivo and that it is indispensable for glucose homeostasis. We further reveal a role for ACC1 in controlling beta cell growth prior to adulthood.</p

Core Services in the Architecture of the National Digital Library for Science Education (NSDL)

We describe the core components of the architecture for the (NSDL) National Science, Mathematics, Engineering, and Technology Education Digital Library. Over time the NSDL will include heterogeneous users, content, and services. To accommodate this, a design for a technical and organization infrastructure has been formulated based on the notion of a spectrum of interoperability. This paper describes the first phase of the interoperability infrastructure including the metadata repository, search and discovery services, rights management services, and user interface portal facilities

IRS1-Independent Defects Define Major Nodes of Insulin Resistance

SummaryInsulin resistance is a common disorder caused by a wide variety of physiological insults, some of which include poor diet, inflammation, anti-inflammatory steroids, hyperinsulinemia, and dyslipidemia. The common link between these diverse insults and insulin resistance is widely considered to involve impaired insulin signaling, particularly at the level of the insulin receptor substrate (IRS). To test this model, we utilized a heterologous system involving the platelet-derived growth factor (PDGF) pathway that recapitulates many aspects of insulin action independently of IRS. We comprehensively analyzed six models of insulin resistance in three experimental systems and consistently observed defects in both insulin and PDGF action despite a range of insult-specific defects within the IRS-Akt nexus. These findings indicate that while insulin resistance is associated with multiple deficiencies, the most deleterious defects and the origin of insulin resistance occur independently of IRS

Treatment response classes in major depressive disorder identified by model-based clustering and validated by clinical prediction models

The identification of generalizable treatment response classes (TRC[s]) in major depressive disorder (MDD) would facilitate comparisons across studies and the development of treatment prediction algorithms. Here, we investigated whether such stable TRCs can be identified and predicted by clinical baseline items. We analyzed data from an observational MDD cohort (Munich Antidepressant Response Signature [MARS] study, N = 1017), treated individually by psychopharmacological and psychotherapeutic means, and a multicenter, partially randomized clinical/pharmacogenomic study (Genome-based Therapeutic Drugs for Depression [GENDEP], N = 809). Symptoms were evaluated up to week 16 (or discharge) in MARS and week 12 in GENDEP. Clustering was performed on 809 MARS patients (discovery sample) using a mixed model with the integrated completed likelihood criterion for the assessment of cluster stability, and validated through a distinct MARS validation sample and GENDEP. A random forest algorithm was used to identify prediction patterns based on 50 clinical baseline items. From the clustering of the MARS discovery sample, seven TRCs emerged ranging from fast and complete response (average 4.9 weeks until discharge, 94% remitted patients) to slow and incomplete response (10% remitted patients at week 16). These proved stable representations of treatment response dynamics in both the MARS and the GENDEP validation sample. TRCs were strongly associated with established response markers, particularly the rate of remitted patients at discharge. TRCs were predictable from clinical items, particularly personality items, life events, episode duration, and specific psychopathological features. Prediction accuracy improved significantly when cluster-derived slopes were modelled instead of individual slopes. In conclusion, model-based clustering identified distinct and clinically meaningful treatment response classes in MDD that proved robust with regard to capturing response profiles of differently designed studies. Response classes were predictable from clinical baseline characteristics. Conceptually, model-based clustering is translatable to any outcome measure and could advance the large-scale integration of studies on treatment efficacy or the neurobiology of treatment response

Remote automated multi-generational growth and observation of an animal in low Earth orbit

The ultimate survival of humanity is dependent upon colonization of other planetary bodies. Key challenges to such habitation are (patho)physiologic changes induced by known, and unknown, factors associated with long-duration and distance space exploration. However, we currently lack biological models for detecting and studying these changes. Here, we use a remote automated culture system to successfully grow an animal in low Earth orbit for six months. Our observations, over 12 generations, demonstrate that the multi-cellular soil worm Caenorhabditis elegans develops from egg to adulthood and produces progeny with identical timings in space as on the Earth. Additionally, these animals display normal rates of movement when fully fed, comparable declines in movement when starved, and appropriate growth arrest upon starvation and recovery upon re-feeding. These observations establish C. elegans as a biological model that can be used to detect changes in animal growth, development, reproduction and behaviour in response to environmental conditions during long-duration spaceflight. This experimental system is ready to be incorporated on future, unmanned interplanetary missions and could be used to study cost-effectively the effects of such missions on these biological processes and the efficacy of new life support systems and radiation shielding technologies

The transcriptional response to oxidative stress is part of, but not sufficient for, insulin resistance in adipocytes.

Insulin resistance is a major risk factor for metabolic diseases such as Type 2 diabetes. Although the underlying mechanisms of insulin resistance remain elusive, oxidative stress is a unifying driver by which numerous extrinsic signals and cellular stresses trigger insulin resistance. Consequently, we sought to understand the cellular response to oxidative stress and its role in insulin resistance. Using cultured 3T3-L1 adipocytes, we established a model of physiologically-derived oxidative stress by inhibiting the cycling of glutathione and thioredoxin, which induced insulin resistance as measured by impaired insulin-stimulated 2-deoxyglucose uptake. Using time-resolved transcriptomics, we found > 2000 genes differentially-expressed over 24 hours, with specific metabolic and signalling pathways enriched at different times. We explored this coordination using a knowledge-based hierarchical-clustering approach to generate a temporal transcriptional cascade and identify key transcription factors responding to oxidative stress. This response shared many similarities with changes observed in distinct insulin resistance models. However, an anti-oxidant reversed insulin resistance phenotypically but not transcriptionally, implying that the transcriptional response to oxidative stress is insufficient for insulin resistance. This suggests that the primary site by which oxidative stress impairs insulin action occurs post-transcriptionally, warranting a multi-level 'trans-omic' approach when studying time-resolved responses to cellular perturbations

Remoción de contaminantes atmosféricos por el bosque urbano en el valle de Aburrá

Los bosques urbanos prestan diferentes servicios ecosistémicos, tales como la remoción de contaminantes atmosféricos, la captura de carbono, la regulación hídrica y microclimática, y la oferta de hábitat para la fauna silvestre. Esto mejora la calidad ambiental y el bienestar de la población. En este estudio se analizó la estructura del bosque urbano del valle de Aburrá y se estimó y valoró su aporte a la remoción de contaminantes atmosféricos mediante el software i-Tree Eco. Para esto se establecieron 398 parcelas de muestreo forestal y se utilizó información secundaria sobre las condiciones climáticas y de contaminación. Se encontró un 23% de cobertura arbórea en el área de estudio y una remoción de 228 toneladas de contaminantes por año (valor aproximado de 2.1 millones USD). Finalmente, se recomiendan estrategias para la optimización de este servicio y la creación de mecanismos para compensar la pérdida de coberturas arbóreas