Battelle: By The Numbers, December 17, 2014

Iowa has made substantial economic progress over the last decade, resulting in positive trends in Iowa’s top-line measures of success.

Battelle: By The Numbers, December 17, 2014

Iowa has made substantial economic progress over the last decade, resulting in positive trends in Iowa’s top-line measures of success.

A decrease of plasma macrophage migration inhibitory factor concentration is associated with lower numbers of circulating lymphocytes in experimental Plasmodium falciparum malaria.

Macrophage migration inhibitory factor (MIF) has recently been implicated in the pathogenesis of malarial anaemia. However, field studies have reported contradictory results on circulating MIF concentrations in patients with clinically overt Plasmodium falciparum malaria. We determined plasma MIF levels over time in 10 healthy volunteers during experimental P. falciparum infection. Under fully controlled conditions, MIF levels decreased significantly during early blood-stage infection and reached a nadir at day 8 post-infection. A decrease in the number of circulating lymphocytes, which are an important source of MIF production, paralleled the decrease in MIF levels. Monocyte/macrophage counts remained unchanged. At MIF nadir, the anti-inflammatory cytokine interleukin (IL)-10, which is an inhibitor of T-cell MIF production, was detectable in only 2 of 10 volunteers. Plasma concentrations of the pro-inflammatory cytokines IL-8 and IL-1beta were only marginally elevated. We conclude that circulating MIF levels decrease early in blood-stage malaria as a result of the decline in circulating lymphocytes.

Deciphering neuron-glia compartmentalization in cortical energy metabolism.

Energy demand is an important constraint on neural signaling. Several methods have been proposed to assess the energy budget of the brain based on a bottom-up approach in which the energy demand of individual biophysical processes are first estimated independently and then summed up to compute the brain's total energy budget. Here, we address this question using a novel approach that makes use of published datasets that reported average cerebral glucose and oxygen utilization in humans and rodents during different activation states. Our approach allows us (1) to decipher neuron-glia compartmentalization in energy metabolism and (2) to compute a precise state-dependent energy budget for the brain. Under the assumption that the fraction of energy used for signaling is proportional to the cycling of neurotransmitters, we find that in the activated state, most of the energy ( approximately 80%) is oxidatively produced and consumed by neurons to support neuron-to-neuron signaling. Glial cells, while only contributing for a small fraction to energy production ( approximately 6%), actually take up a significant fraction of glucose (50% or more) from the blood and provide neurons with glucose-derived energy substrates. Our results suggest that glycolysis occurs for a significant part in astrocytes whereas most of the oxygen is utilized in neurons. As a consequence, a transfer of glucose-derived metabolites from glial cells to neurons has to take place. Furthermore, we find that the amplitude of this transfer is correlated to (1) the activity level of the brain; the larger the activity, the more metabolites are shuttled from glia to neurons and (2) the oxidative activity in astrocytes; with higher glial pyruvate metabolism, less metabolites are shuttled from glia to neurons. While some of the details of a bottom-up biophysical approach have to be simplified, our method allows for a straightforward assessment of the brain's energy budget from macroscopic measurements with minimal underlying assumptions.

Observation of a continuous interior crisis in the Hindmarsh-Rose neuron model.

Interior crises are understood as discontinuous changes of the size of a chaotic attractor that occur when an unstable periodic orbit collides with the chaotic attractor. We present here numerical evidence and theoretical reasoning which prove the existence of a chaos-chaos transition in which the change of the attractor size is sudden but continuous. This occurs in the Hindmarsh¿Rose model of a neuron, at the transition point between the bursting and spiking dynamics, which are two different dynamic behaviors that this system is able to present. Moreover, besides the change in attractor size, other significant properties of the system undergoing the transitions do change in a relevant qualitative way. The mechanism for such transition is understood in terms of a simple one-dimensional map whose dynamics undergoes a crossover between two different universal behaviors

Familial frontotemporal dementia with ubiquitin inclusion bodies and without motor neuron disease.

Frontotemporal dementia (FTD) is the second most common degenerative dementia after Alzheimer's disease and its Lewy body variant. Clinical pathology can be subdivided in three main neuropathological subtypes: frontal lobe dementia, Pick's disease and FTD with motor neuron disease (MND), all characterised by distinct histological features. Until recently the presence of ubiquitin-positive intraneuronal inclusions in the dentate gyrus, and the temporal and frontal cortex was usually associated with the MND type. Such inclusions were also observed in a few sporadic cases of FTD without or with parkinsonism (FTDP) in the absence of MND. We present here clinical, neuropathological and immunohistochemical data about a Swiss FTD family with FTDP-like features but without MND. Spongiosis and mild gliosis were observed in the grey matter. No neurofibrillary tangles, Pick bodies, Lewy bodies, senile plaques or prion-positive signals were present. However, ubiquitin-positive intracytoplasmic inclusions were detected in various structures but predominantly in the dentate gyrus. These observations support the existence of a familial form of FTDP with ubiquitin-positive intracytoplasmic inclusions (Swiss FTDP family).

Dysfunction in endoplasmic reticulum-mitochondria crosstalk underlies SIGMAR1 loss of function mediated motor neuron degeneration.

Mutations in Sigma 1 receptor (SIGMAR1) have been previously identified in patients with amyotrophic lateral sclerosis and disruption of Sigmar1 in mouse leads to locomotor deficits. However, cellular mechanisms underlying motor phenotypes in human and mouse with disturbed SIGMAR1 function have not been described so far. Here we used a combination of in vivo and in vitro approaches to investigate the role of SIGMAR1 in motor neuron biology. Characterization of Sigmar1(-/-) mice revealed that affected animals display locomotor deficits associated with muscle weakness, axonal degeneration and motor neuron loss. Using primary motor neuron cultures, we observed that pharmacological or genetic inactivation of SIGMAR1 led to motor neuron axonal degeneration followed by cell death. Disruption of SIGMAR1 function in motor neurons disturbed endoplasmic reticulum-mitochondria contacts, affected intracellular calcium signalling and was accompanied by activation of endoplasmic reticulum stress and defects in mitochondrial dynamics and transport. These defects were not observed in cultured sensory neurons, highlighting the exacerbated sensitivity of motor neurons to SIGMAR1 function. Interestingly, the inhibition of mitochondrial fission was sufficient to induce mitochondria axonal transport defects as well as axonal degeneration similar to the changes observed after SIGMAR1 inactivation or loss. Intracellular calcium scavenging and endoplasmic reticulum stress inhibition were able to restore mitochondrial function and consequently prevent motor neuron degeneration. These results uncover the cellular mechanisms underlying motor neuron degeneration mediated by loss of SIGMAR1 function and provide therapeutically relevant insight into motor neuronal diseases.

Dysfunctional SEMA3E signaling underlies gonadotropin-releasing hormone neuron deficiency in Kallmann syndrome.

Individuals with an inherited deficiency in gonadotropin-releasing hormone (GnRH) have impaired sexual reproduction. Previous genetic linkage studies and sequencing of plausible gene candidates have identified mutations associated with inherited GnRH deficiency, but the small number of affected families and limited success in validating candidates have impeded genetic diagnoses for most patients. Using a combination of exome sequencing and computational modeling, we have identified a shared point mutation in semaphorin 3E (SEMA3E) in 2 brothers with Kallmann syndrome (KS), which causes inherited GnRH deficiency. Recombinant wild-type SEMA3E protected maturing GnRH neurons from cell death by triggering a plexin D1-dependent (PLXND1-dependent) activation of PI3K-mediated survival signaling. In contrast, recombinant SEMA3E carrying the KS-associated mutation did not protect GnRH neurons from death. In murine models, lack of either SEMA3E or PLXND1 increased apoptosis of GnRH neurons in the developing brain, reducing innervation of the adult median eminence by GnRH-positive neurites. GnRH neuron deficiency in male mice was accompanied by impaired testes growth, a characteristic feature of KS. Together, these results identify SEMA3E as an essential gene for GnRH neuron development, uncover a neurotrophic function for SEMA3E in the developing brain, and elucidate SEMA3E/PLXND1/PI3K signaling as a mechanism that prevents GnRH neuron deficiency.

Multimodal stimulus coding by a gustatory sensory neuron in Drosophila larvae.

Accurate perception of taste information is crucial for animal survival. In adult Drosophila, gustatory receptor neurons (GRNs) perceive chemical stimuli of one specific gustatory modality associated with a stereotyped behavioural response, such as aversion or attraction. We show that GRNs of Drosophila larvae employ a surprisingly different mode of gustatory information coding. Using a novel method for calcium imaging in the larval gustatory system, we identify a multimodal GRN that responds to chemicals of different taste modalities with opposing valence, such as sweet sucrose and bitter denatonium, reliant on different sensory receptors. This multimodal neuron is essential for bitter compound avoidance, and its artificial activation is sufficient to mediate aversion. However, the neuron is also essential for the integration of taste blends. Our findings support a model for taste coding in larvae, in which distinct receptor proteins mediate different responses within the same, multimodal GRN.

Estimation of surface area and pore volume of activated carbons by methylene blue and iodine numbers

Data of methylene blue number and iodine number of activated carbons samples were calibrated against the respective surface area, micropore volume and total pore volume using multiple regression. The models obtained from the calibrations were used in predicting these physical properties of a test group of activated carbon samples produced from several raw materials. In all cases, the predicted values were in good agreement with the expected values. The method allows extracting more information from the methylene blue and iodine adsorption studies than normally obtained with this type of material.

Numbers and sets

In this paper I discuss the intuition behind Frege's and Russell's definitions of numbers as sets, as well as Benacerraf's criticism of it. I argue that Benacerraf's argument is not as strong as some philosophers tend to think. Moreover, I examine an alternative to the Fregean-Russellian definition of numbers proposed by Maddy, and point out some problems faced by it.

How real are real numbers?

We discuss mathematical and physical arguments against continuity and in favor of discreteness, with particular emphasis on the ideas of Émile Borel (1871-1956).

Solving Leontief Input-Output Model with Trapezoidal Fuzzy Numbers and Gauss-Seidel Algorithm

In this work a fuzzy linear system is used to solve Leontief input-output model with fuzzy entries. For solving this model, we assume that the consumption matrix from di erent sectors of the economy and demand are known. These assumptions heavily depend on the information obtained from the industries. Hence uncertainties are involved in this information. The aim of this work is to model these uncertainties and to address them by fuzzy entries such as fuzzy numbers and LR-type fuzzy numbers (triangular and trapezoidal). Fuzzy linear system has been developed using fuzzy data and it is solved using Gauss-Seidel algorithm. Numerical examples show the e ciency of this algorithm. The famous example from Prof. Leontief, where he solved the production levels for U.S. economy in 1958, is also further analyzed.