Phonological and semantic influences on auditory word perception in children with and without reading impairments using magnetoencephalography (MEG) and electroencephalography (EEG)

Thesis (Ph. D.)--Harvard-MIT Division of Health Sciences and Technology, 2007.Includes bibliographical references (p. 117-135).Children with dyslexia struggle with learning to read despite adequate intelligence, motivation, and schooling. Over the years, there has been a growing consensus about the role of phonological processing in reading disability. Poor readers typically do worse than their normal reading peers on tasks that require phonological processing which has been linked, directly or indirectly, to their speech perception abilities. The work in this thesis combined behavioral, MEG, and EEG methods to examine how normal and reading-impaired children, 7-13 years of age, perceive speech under varying degrees of phonological contrast (1 vs. 3 phonetic features). In a series of auditory word perception experiments, good and poor readers were found to do worse in accuracy and/or reaction times in phonologically similar (i.e., 1-feature contrast) than phonologically dissimilar (i.e., 2 or 3-feature contrast) conditions. Despite the similar behavioral performance and EEG responses for the two groups, a region of interest (ROI) based MEG approach revealed differences in the brain activation of the two groups in superior temporal regions at 140 to 300 ms.(cont.) In the auditory word discrimination task, differences in activation were found in good readers but not poor readers, as a function of the degree of phonological contrast, reflecting poor readers' lack of sensitivity to the phonological characteristics of the word stimuli. In the sentence plausibility judgment task, the impaired phonological processing abilities of the poor readers may have led them to rely more on top-down sentence context to perceptually disambiguate phonologically confusing terminal words, thereby deceiving them into accepting the phonologically similar incongruent sentences as being congruent. This may account for the poor reader group's reduced brain activation in the phonologically demanding condition in the sentence task. The results of the experiments are consistent with a phonological view of reading disability according to which children with reading impairments have poorly defined phonological representations.by Daniel T. Wehner.Ph.D

Axial forces and bending moments in the loaded rabbit tibia in vivo

<p>Abstract</p> <p>Background</p> <p>Different animal models are used as fracture models in orthopaedic research prior to implant use in humans, although biomechanical forces can differ to a great extend between species due to variable anatomic conditions, particularly with regard to the gait. The rabbit is an often used fracture model, but biomechanical data are very rare. The objective of the present study was to measure axial forces, bending moments, and bending axis directly in the rabbit tibia <it>in vivo</it>. The following hypothesis was tested: Axial forces and bending moments in the mid-diaphysis of rabbit tibia differ from other experimental animals or indirectly calculated data.</p> <p>Methods</p> <p>A minifixateur system with 4 force sensors was developed and attached to rabbit tibia (<it>n </it>= 4), which were subsequently ostectomised. Axial forces, bending moments and bending angles were calculated telemetrically during weight bearing in motion between 6 and 42 days post operation.</p> <p>Results</p> <p>Highest single values were 201% body weight [% bw] for axial forces and 409% bw cm for bending moments. Whereas there was a continous decrease in axial forces over time after day 10 (<it>P </it>= 0.03 on day 15), a decrease in bending moments was inconsistent (<it>P </it>= 0.03 on day 27). High values for bending moments were frequently, but not consistently, associated with high values for axial forces.</p> <p>Conclusion</p> <p>Axial forces in rabbit tibia exceeded axial forces in sheep, and differed from indirectly calculated data. The rabbit is an appropriate fracture model because axial loads and bending moments in rabbit tibia were more closely to human conditions than in sheep tibia as an animal model.</p

Inhibition of IL-1beta improves Glycaemia in a Mouse Model for Gestational Diabetes

Gestational diabetes mellitus (GDM) is one of the most common diseases associated with pregnancy, however, the underlying mechanisms remain unclear. Based on the well documented role of inflammation in type 2 diabetes, the aim was to investigate the role of inflammation in GDM. We established a mouse model for GDM on the basis of its two major risk factors, obesity and aging. In these GDM mice, we observed increased Interleukin-1β (IL-1β) expression in the uterus and the placenta along with elevated circulating IL-1β concentrations compared to normoglycemic pregnant mice. Treatment with an anti-IL-1β antibody improved glucose-tolerance of GDM mice without apparent deleterious effects for the fetus. Finally, IL-1β antagonism showed a tendency for reduced plasma corticosterone concentrations, possibly explaining the metabolic improvement. We conclude that IL-1β is a causal driver of impaired glucose tolerance in GDM

Probing Real Sensory Worlds of Receivers with Unsupervised Clustering

The task of an organism to extract information about the external environment from sensory signals is based entirely on the analysis of ongoing afferent spike activity provided by the sense organs. We investigate the processing of auditory stimuli by an acoustic interneuron of insects. In contrast to most previous work we do this by using stimuli and neurophysiological recordings directly in the nocturnal tropical rainforest, where the insect communicates. Different from typical recordings in sound proof laboratories, strong environmental noise from multiple sound sources interferes with the perception of acoustic signals in these realistic scenarios. We apply a recently developed unsupervised machine learning algorithm based on probabilistic inference to find frequently occurring firing patterns in the response of the acoustic interneuron. We can thus ask how much information the central nervous system of the receiver can extract from bursts without ever being told which type and which variants of bursts are characteristic for particular stimuli. Our results show that the reliability of burst coding in the time domain is so high that identical stimuli lead to extremely similar spike pattern responses, even for different preparations on different dates, and even if one of the preparations is recorded outdoors and the other one in the sound proof lab. Simultaneous recordings in two preparations exposed to the same acoustic environment reveal that characteristics of burst patterns are largely preserved among individuals of the same species. Our study shows that burst coding can provide a reliable mechanism for acoustic insects to classify and discriminate signals under very noisy real-world conditions. This gives new insights into the neural mechanisms potentially used by bushcrickets to discriminate conspecific songs from sounds of predators in similar carrier frequency bands

Uncovering the Molecular Machinery of the Human Spindle—An Integration of Wet and Dry Systems Biology

The mitotic spindle is an essential molecular machine involved in cell division, whose composition has been studied extensively by detailed cellular biology, high-throughput proteomics, and RNA interference experiments. However, because of its dynamic organization and complex regulation it is difficult to obtain a complete description of its molecular composition. We have implemented an integrated computational approach to characterize novel human spindle components and have analysed in detail the individual candidates predicted to be spindle proteins, as well as the network of predicted relations connecting known and putative spindle proteins. The subsequent experimental validation of a number of predicted novel proteins confirmed not only their association with the spindle apparatus but also their role in mitosis. We found that 75% of our tested proteins are localizing to the spindle apparatus compared to a success rate of 35% when expert knowledge alone was used. We compare our results to the previously published MitoCheck study and see that our approach does validate some findings by this consortium. Further, we predict so-called “hidden spindle hub”, proteins whose network of interactions is still poorly characterised by experimental means and which are thought to influence the functionality of the mitotic spindle on a large scale. Our analyses suggest that we are still far from knowing the complete repertoire of functionally important components of the human spindle network. Combining integrated bio-computational approaches and single gene experimental follow-ups could be key to exploring the still hidden regions of the human spindle system

The study of atmospheric ice-nucleating particles via microfluidically generated droplets

Ice-nucleating particles (INPs) play a significant role in the climate and hydrological cycle by triggering ice formation in supercooled clouds, thereby causing precipitation and affecting cloud lifetimes and their radiative properties. However, despite their importance, INP often comprise only 1 in 10³–10⁶ ambient particles, making it difficult to ascertain and predict their type, source, and concentration. The typical techniques for quantifying INP concentrations tend to be highly labour-intensive, suffer from poor time resolution, or are limited in sensitivity to low concentrations. Here, we present the application of microfluidic devices to the study of atmospheric INPs via the simple and rapid production of monodisperse droplets and their subsequent freezing on a cold stage. This device offers the potential for the testing of INP concentrations in aqueous samples with high sensitivity and high counting statistics. Various INPs were tested for validation of the platform, including mineral dust and biological species, with results compared to literature values. We also describe a methodology for sampling atmospheric aerosol in a manner that minimises sampling biases and which is compatible with the microfluidic device. We present results for INP concentrations in air sampled during two field campaigns: (1) from a rural location in the UK and (2) during the UK’s annual Bonfire Night festival. These initial results will provide a route for deployment of the microfluidic platform for the study and quantification of INPs in upcoming field campaigns around the globe, while providing a benchmark for future lab-on-a-chip-based INP studies

The Atmospheric River Tracking Method Intercomparison Project (ARTMIP): Quantifying Uncertainties in Atmospheric River Climatology

Atmospheric rivers (ARs) are now widely known for their association with high‐impact weather events and long‐term water supply in many regions. Researchers within the scientific community have developed numerous methods to identify and track of ARs—a necessary step for analyses on gridded data sets, and objective attribution of impacts to ARs. These different methods have been developed to answer specific research questions and hence use different criteria (e.g., geometry, threshold values of key variables, and time dependence). Furthermore, these methods are often employed using different reanalysis data sets, time periods, and regions of interest. The goal of the Atmospheric River Tracking Method Intercomparison Project (ARTMIP) is to understand and quantify uncertainties in AR science that arise due to differences in these methods. This paper presents results for key AR‐related metrics based on 20+ different AR identification and tracking methods applied to Modern‐Era Retrospective Analysis for Research and Applications Version 2 reanalysis data from January 1980 through June 2017. We show that AR frequency, duration, and seasonality exhibit a wide range of results, while the meridional distribution of these metrics along selected coastal (but not interior) transects are quite similar across methods. Furthermore, methods are grouped into criteria‐based clusters, within which the range of results is reduced. AR case studies and an evaluation of individual method deviation from an all‐method mean highlight advantages/disadvantages of certain approaches. For example, methods with less (more) restrictive criteria identify more (less) ARs and AR‐related impacts. Finally, this paper concludes with a discussion and recommendations for those conducting AR‐related research to consider.Fil: Rutz, Jonathan J.. National Ocean And Atmospheric Administration; Estados UnidosFil: Shields, Christine A.. National Center for Atmospheric Research; Estados UnidosFil: Lora, Juan M.. University of Yale; Estados UnidosFil: Payne, Ashley E.. University of Michigan; Estados UnidosFil: Guan, Bin. California Institute of Technology; Estados UnidosFil: Ullrich, Paul. University of California at Davis; Estados UnidosFil: O'Brien, Travis. Lawrence Berkeley National Laboratory; Estados UnidosFil: Leung, Ruby. Pacific Northwest National Laboratory; Estados UnidosFil: Ralph, F. Martin. Center For Western Weather And Water Extremes; Estados UnidosFil: Wehner, Michael. Lawrence Berkeley National Laboratory; Estados UnidosFil: Brands, Swen. Meteogalicia; EspañaFil: Collow, Allison. Universities Space Research Association; Estados UnidosFil: Goldenson, Naomi. University of California at Los Angeles; Estados UnidosFil: Gorodetskaya, Irina. Universidade de Aveiro; PortugalFil: Griffith, Helen. University of Reading; Reino UnidoFil: Kashinath, Karthik. Lawrence Bekeley National Laboratory; Estados UnidosFil: Kawzenuk, Brian. Center For Western Weather And Water Extremes; Reino UnidoFil: Krishnan, Harinarayan. Lawrence Berkeley National Laboratory; Estados UnidosFil: Kurlin, Vitaliy. University of Liverpool; Reino UnidoFil: Lavers, David. European Centre For Medium-range Weather Forecasts; Estados UnidosFil: Magnusdottir, Gudrun. University of California at Irvine; Estados UnidosFil: Mahoney, Kelly. Universidad de Lisboa; PortugalFil: Mc Clenny, Elizabeth. University of California at Davis; Estados UnidosFil: Muszynski, Grzegorz. University of Liverpool; Reino Unido. Lawrence Bekeley National Laboratory; Estados UnidosFil: Nguyen, Phu Dinh. University of California at Irvine; Estados UnidosFil: Prabhat, Mr.. Lawrence Bekeley National Laboratory; Estados UnidosFil: Qian, Yun. Pacific Northwest National Laboratory; Estados UnidosFil: Ramos, Alexandre M.. Universidade Nova de Lisboa; PortugalFil: Sarangi, Chandan. Pacific Northwest National Laboratory; Estados UnidosFil: Viale, Maximiliano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales. Provincia de Mendoza. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales. Universidad Nacional de Cuyo. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales; Argentin