Community knowledge and acceptance of larviciding for malaria control in a rural district of east-central Tanzania

The use of microbial larvicides, a form of larval source management, is a less commonly used malaria control intervention that nonetheless has significant potential as a component of an integrated vector management strategy. We evaluated community acceptability of larviciding in a rural district in east-central Tanzania using data from 962 household surveys, 12 focus group discussions, and 24 in-depth interviews. Most survey respondents trusted in the safety (73.1%) and efficacy of larviciding, both with regards to mosquito control (92.3%) and to reduce malaria infection risk (91.9%). Probing these perceptions using a Likert scale provides a more detailed picture. Focus group participants and key informants were also receptive to larviciding, but stressed the importance of sensitization before its implementation. Overall, 73.4% of survey respondents expressed a willingness to make a nominal household contribution to a larviciding program, a proportion which decreased as the proposed contribution increased. The lower-bound mean willingness to pay is estimated at 2,934 Tanzanian Shillings (approximately US$1.76) per three month period. We present a multivariate probit regression analysis examining factors associated with willingness to pay. Overall, our findings point to a receptive environment in a rural setting in Tanzania for the use of microbial larvicides in malaria control. © 2014 by the authors; licensee MDPI, Basel, Switzerland

A model of feedback control for the charge-balanced suppression of epileptic seizures

Here we present several refinements to a model of feedback control for the suppression of epileptic seizures. We utilize a stochastic partial differential equation (SPDE) model of the human cortex. First, we verify the strong convergence of numerical solutions to this model, paying special attention to the sharp spatial changes that occur at electrode edges. This allows us to choose appropriate step sizes for our simulations; because the spatial step size must be small relative to the size of an electrode in order to resolve its electrical behavior, we are able to include a more detailed electrode profile in the simulation. Then, based on evidence that the mean soma potential is not the variable most closely related to the measurement of a cortical surface electrode, we develop a new model for this. The model is based on the currents flowing in the cortex and is used for a simulation of feedback control. The simulation utilizes a new control algorithm incorporating the total integral of the applied electrical potential. Not only does this succeed in suppressing the seizure-like oscillations, but it guarantees that the applied signal will be charge-balanced and therefore unlikely to cause cortical damage

Endovascular treatment of an open cervical fracture with carotid artery tear

The dilemma of how to treat penetrating wound injuries to the neck, which involve a combination of a common carotid artery rupture and a cervical spinal fracture, is presented in this case report

A continuous mapping of sleep states through association of EEG with a mesoscale cortical model

Here we show that a mathematical model of the human sleep cycle can be used to obtain a detailed description of electroencephalogram (EEG) sleep stages, and we discuss how this analysis may aid in the prediction and prevention of seizures during sleep. The association between EEG data and the cortical model is found via locally linear embedding (LLE), a method of dimensionality reduction. We first show that LLE can distinguish between traditional sleep stages when applied to EEG data. It reliably separates REM and non-REM sleep and maps the EEG data to a low-dimensional output space where the sleep state changes smoothly over time. We also incorporate the concept of strongly connected components and use this as a method of automatic outlier rejection for EEG data. Then, by using LLE on a hybrid data set containing both sleep EEG and signals generated from the mesoscale cortical model, we quantify the relationship between the data and the mathematical model. This enables us to take any sample of sleep EEG data and associate it with a position among the continuous range of sleep states provided by the model; we can thus infer a trajectory of states as the subject sleeps. Lastly, we show that this method gives consistent results for various subjects over a full night of sleep and can be done in real time

Retinoblastoma incidence and sunlight exposure

To evaluate positive findings from an earlier report, we studied the relation between retinoblastoma incidence and ultraviolet (UV-B) radiation levels in the Surveillance, Epidemiology, and End Results (SEER) programme areas of the USA using weighted regression, as well as in international data after adjusting for race, economic development, and climate. The association was not statistically significant within the USA (P> 0.20). At an international level, the relation was significant overall and after adjusting for economic development, but it was not significant after adjusting for race and tropical climate, suggesting that environmental factors other than UV-B may be responsible for the geographic patterns of retinoblastoma. © 2000 Cancer Research Campaig

Combinatorial Roles of Heparan Sulfate Proteoglycans and Heparan Sulfates in Caenorhabditis elegans Neural Development

Heparan sulfate proteoglycans (HSPGs) play critical roles in the development and adult physiology of all metazoan organisms. Most of the known molecular interactions of HSPGs are attributed to the structurally highly complex heparan sulfate (HS) glycans. However, whether a specific HSPG (such as syndecan) contains HS modifications that differ from another HSPG (such as glypican) has remained largely unresolved. Here, a neural model in C. elegans is used to demonstrate for the first time the relationship between specific HSPGs and HS modifications in a defined biological process in vivo. HSPGs are critical for the migration of hermaphrodite specific neurons (HSNs) as genetic elimination of multiple HSPGs leads to 80% defect of HSN migration. The effects of genetic elimination of HSPGs are additive, suggesting that multiple HSPGs, present in the migrating neuron and in the matrix, act in parallel to support neuron migration. Genetic analyses suggest that syndecan/sdn-1 and HS 6-O-sulfotransferase, hst-6, function in a linear signaling pathway and glypican/lon-2 and HS 2-O-sulfotransferase, hst-2, function together in a pathway that is parallel to sdn-1 and hst-6. These results suggest core protein specific HS modifications that are critical for HSN migration. In C. elegans, the core protein specificity of distinct HS modifications may be in part regulated at the level of tissue specific expression of genes encoding for HSPGs and HS modifying enzymes. Genetic analysis reveals that there is a delicate balance of HS modifications and eliminating one HS modifying enzyme in a compromised genetic background leads to significant changes in the overall phenotype. These findings are of importance with the view of HS as a critical regulator of cell signaling in normal development and disease

Dopamine receptor D4 (DRD4) polymorphisms with reduced functional potency intensify atrophy in syndrome-specific sites of frontotemporal dementia.

ObjectiveWe aimed to understand the impact of dopamine receptor D4 (DRD4) polymorphisms on neurodegeneration in patients with dementia. We hypothesized that DRD4dampened-variants with reduced functional potency would be associated with greater atrophy in regions with higher receptor density. Given that DRD4 is concentrated in anterior regions of the limbic and cortical forebrain we anticipated genotype effects in patients with a more rostral pattern of neurodegeneration.Methods337 subjects, including healthy controls, patients with Alzheimer's disease (AD) and frontotemporal dementia (FTD) underwent genotyping, structural MRI, and cognitive/behavioral testing. We conducted whole-brain voxel-based morphometry to examine the relationship between DRD4 genotypes and brain atrophy patterns within and across groups. General linear modeling was used to evaluate relationships between genotype and cognitive/behavioral measures.ResultsDRD4 dampened-variants predicted gray matter atrophy in disease-specific regions of FTD in anterior cingulate, ventromedial prefrontal, orbitofrontal and insular cortices on the right greater than the left. Genotype predicted greater apathy and repetitive motor disturbance in patients with FTD. These results covaried with frontoinsular cortical atrophy. Peak atrophy patterned along regions of neuroanatomic vulnerability in FTD-spectrum disorders. In AD subjects and controls, genotype did not impact gray matter intensity.ConclusionsWe conclude that DRD4 polymorphisms with reduced functional potency exacerbate neuronal injury in sites of higher receptor density, which intersect with syndrome-specific regions undergoing neurodegeneration in FTD

Robust optical delay lines via topological protection

Phenomena associated with topological properties of physical systems are naturally robust against perturbations. This robustness is exemplified by quantized conductance and edge state transport in the quantum Hall and quantum spin Hall effects. Here we show how exploiting topological properties of optical systems can be used to implement robust photonic devices. We demonstrate how quantum spin Hall Hamiltonians can be created with linear optical elements using a network of coupled resonator optical waveguides (CROW) in two dimensions. We find that key features of quantum Hall systems, including the characteristic Hofstadter butterfly and robust edge state transport, can be obtained in such systems. As a specific application, we show that the topological protection can be used to dramatically improve the performance of optical delay lines and to overcome limitations related to disorder in photonic technologies.Comment: 9 pages, 5 figures + 12 pages of supplementary informatio

b-Initiated processes at the LHC: a reappraisal

Several key processes at the LHC in the standard model and beyond that involve $b$ quarks, such as single-top, Higgs, and weak vector boson associated production, can be described in QCD either in a 4-flavor or 5-flavor scheme. In the former, $b$ quarks appear only in the final state and are typically considered massive. In 5-flavor schemes, calculations include $b$ quarks in the initial state, are simpler and allow the resummation of possibly large initial state logarithms of the type $\log \frac{{\cal Q}^2}{m_b^2}$ into the $b$ parton distribution function (PDF), ${\cal Q}$ being the typical scale of the hard process. In this work we critically reconsider the rationale for using 5-flavor improved schemes at the LHC. Our motivation stems from the observation that the effects of initial state logs are rarely very large in hadron collisions: 4-flavor computations are pertubatively well behaved and a substantial agreement between predictions in the two schemes is found. We identify two distinct reasons that explain this behaviour, i.e., the resummation of the initial state logarithms into the $b$-PDF is relevant only at large Bjorken $x$ and the possibly large ratios ${\cal Q}^2/m_b^2$'s are always accompanied by universal phase space suppression factors. Our study paves the way to using both schemes for the same process so to exploit their complementary advantages for different observables, such as employing a 5-flavor scheme to accurately predict the total cross section at NNLO and the corresponding 4-flavor computation at NLO for fully exclusive studies.Comment: Fixed typo in Eq. (A.10) and few typos in Eq. (C.2) and (C.3