Reconstruction of eye movements during blinks

In eye movement research in reading, the amount of data plays a crucial role for the validation of results. A methodological problem for the analysis of the eye movement in reading are blinks, when readers close their eyes. Blinking rate increases with increasing reading time, resulting in high data losses, especially for older adults or reading impaired subjects. We present a method, based on the symbolic sequence dynamics of the eye movements, that reconstructs the horizontal position of the eyes while the reader blinks. The method makes use of an observed fact that the movements of the eyes before closing or after opening contain information about the eyes movements during blinks. Test results indicate that our reconstruction method is superior to methods that use simpler interpolation approaches. In addition, analyses of the reconstructed data show no significant deviation from the usual behavior observed in readers

Self-Supervised Learning for Cardiac MR Image Segmentation by Anatomical Position Prediction

In the recent years, convolutional neural networks have transformed the field of medical image analysis due to their capacity to learn discriminative image features for a variety of classification and regression tasks. However, successfully learning these features requires a large amount of manually annotated data, which is expensive to acquire and limited by the available resources of expert image analysts. Therefore, unsupervised, weakly-supervised and self-supervised feature learning techniques receive a lot of attention, which aim to utilise the vast amount of available data, while at the same time avoid or substantially reduce the effort of manual annotation. In this paper, we propose a novel way for training a cardiac MR image segmentation network, in which features are learnt in a self-supervised manner by predicting anatomical positions. The anatomical positions serve as a supervisory signal and do not require extra manual annotation. We demonstrate that this seemingly simple task provides a strong signal for feature learning and with self-supervised learning, we achieve a high segmentation accuracy that is better than or comparable to a U-net trained from scratch, especially at a small data setting. When only five annotated subjects are available, the proposed method improves the mean Dice metric from 0.811 to 0.852 for short-axis image segmentation, compared to the baseline U-net

High dimensional biological data retrieval optimization with NoSQL technology.

Background High-throughput transcriptomic data generated by microarray experiments is the most abundant and frequently stored kind of data currently used in translational medicine studies. Although microarray data is supported in data warehouses such as tranSMART, when querying relational databases for hundreds of different patient gene expression records queries are slow due to poor performance. Non-relational data models, such as the key-value model implemented in NoSQL databases, hold promise to be more performant solutions. Our motivation is to improve the performance of the tranSMART data warehouse with a view to supporting Next Generation Sequencing data. Results In this paper we introduce a new data model better suited for high-dimensional data storage and querying, optimized for database scalability and performance. We have designed a key-value pair data model to support faster queries over large-scale microarray data and implemented the model using HBase, an implementation of Google's BigTable storage system. An experimental performance comparison was carried out against the traditional relational data model implemented in both MySQL Cluster and MongoDB, using a large publicly available transcriptomic data set taken from NCBI GEO concerning Multiple Myeloma. Our new key-value data model implemented on HBase exhibits an average 5.24-fold increase in high-dimensional biological data query performance compared to the relational model implemented on MySQL Cluster, and an average 6.47-fold increase on query performance on MongoDB. Conclusions The performance evaluation found that the new key-value data model, in particular its implementation in HBase, outperforms the relational model currently implemented in tranSMART. We propose that NoSQL technology holds great promise for large-scale data management, in particular for high-dimensional biological data such as that demonstrated in the performance evaluation described in this paper. We aim to use this new data model as a basis for migrating tranSMART's implementation to a more scalable solution for Big Data

Emerging pharmacotherapy of tinnitus

Tinnitus, the perception of sound in the absence of an auditory stimulus, is perceived by about 1 in 10 adults, and for at least 1 in 100, tinnitus severely affects their quality of life. Because tinnitus is frequently associated with irritability, agitation, stress, insomnia, anxiety and depression, the social and economic burdens of tinnitus can be enormous. No curative treatments are available. However, tinnitus symptoms can be alleviated to some extent. The most widespread management therapies consist of auditory stimulation and cognitive behavioral treatment, aiming at improving habituation and coping strategies. Available clinical trials vary in methodological rigor and have been performed for a considerable number of different drugs. None of the investigated drugs have demonstrated providing replicable long-term reduction of tinnitus impact in the majority of patients in excess of placebo effects. Accordingly, there are no FDA or European Medicines Agency approved drugs for the treatment of tinnitus. However, in spite of the lack of evidence, a large variety of different compounds are prescribed off-label. Therefore, more effective pharmacotherapies for this huge and still growing market are desperately needed and even a drug that produces only a small but significant effect would have an enormous therapeutic impact. This review describes current and emerging pharmacotherapies with current difficulties and limitations. In addition, it provides an estimate of the tinnitus market. Finally, it describes recent advances in the tinnitus field which may help overcome obstacles faced in the pharmacological treatment of tinnitus. These include incomplete knowledge of tinnitus pathophysiology, lack of well-established animal models, heterogeneity of different forms of tinnitus, difficulties in tinnitus assessment and outcome measurement and variability in clinical trial methodology. © 2009 Informa UK Ltd.Fil: Langguth, Berthold. Universitat Regensburg; AlemaniaFil: Salvi, Richard. State University of New York; Estados UnidosFil: Elgoyhen, Ana Belen. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Ingeniería Genética y Biología Molecular "Dr. Héctor N. Torres"; Argentin

Localization of a 64-kDa phosphoprotein in the lumen between the outer and inner envelopes of pea chloroplasts

The identification and localization of a marker protein for the intermembrane space between the outer and inner chloroplast envelopes is described. This 64-kDa protein is very rapidly labeled by [γ-32P]ATP at very low (30 nM) ATP concentrations and the phosphoryl group exhibits a high turnover rate. It was possible to establish the presence of the 64-kDa protein in this plastid compartment by using different chloroplast envelope separation and isolation techniques. In addition comparison of labeling kinetics by intact and hypotonically lysed pea chloroplasts support the localization of the 64-kDa protein in the intermembrane space. The 64-kDa protein was present and could be labeled in mixed envelope membranes isolated from hypotonically lysed plastids. Mixed envelope membranes incorporated high amounts of 32P from [γ-32P]ATP into the 64-kDa protein, whereas separated outer and inner envelope membranes did not show significant phosphorylation of this protein. Water/Triton X-114 phase partitioning demonstrated that the 64-kDa protein is a hydrophilic polypeptide. These findings suggest that the 64-kDa protein is a soluble protein trapped in the space between the inner and outer envelope membranes. After sonication of mixed envelope membranes, the 64-kDa protein was no longer present in the membrane fraction, but could be found in the supernatant after a 110000 × g centrifugation

Head orientation benefit to speech intelligibility in noise for cochlear implant users and in realistic listening conditions

Cochlear implant (CI) users suffer from elevated speech-reception thresholds and may rely on lip reading. Traditional measures of spatial release from masking quantify speech-reception-threshold improvement with azimuthal separation of target speaker and interferers and with the listener facing the target speaker. Substantial benefits of orienting the head away from the target speaker were predicted by a model of spatial release from masking. Audio-only and audio-visual speech-reception thresholds in normal-hearing (NH) listeners and bilateral and unilateral CI users confirmed model predictions of this head-orientation benefit. The benefit ranged 2–5 dB for a modest 30� orientation that did not affect the lip-reading benefit. NH listeners’ and CI users’ lip-reading benefit measured 3 and 5 dB, respectively. A head-orientation benefit of �2 dB was also both predicted and observed in NH listeners in realistic simulations of a restaurant listening environment. Exploiting the benefit of head orientation is thus a robust hearing tactic that would benefit both NH listeners and CI users in noisy listening conditions

Phospholipid-Derived Fatty Acids and Quinones as Markers for Bacterial Biomass and Community Structure in Marine Sediments

Phospholipid-derived fatty acids (PLFA) and respiratory quinones (RQ) are microbial compounds that have been utilized as biomarkers to quantify bacterial biomass and to characterize microbial community structure in sediments, waters, and soils. While PLFAs have been widely used as quantitative bacterial biomarkers in marine sediments, applications of quinone analysis in marine sediments are very limited. In this study, we investigated the relation between both groups of bacterial biomarkers in a broad range of marine sediments from the intertidal zone to the deep sea. We found a good log-log correlation between concentrations of bacterial PLFA and RQ over several orders of magnitude. This relationship is probably due to metabolic variation in quinone concentrations in bacterial cells in different environments, whereas PLFA concentrations are relatively stable under different conditions. We also found a good agreement in the community structure classifications based on the bacterial PLFAs and RQs. These results strengthen the application of both compounds as quantitative bacterial biomarkers. Moreover, the bacterial PLFA- and RQ profiles revealed a comparable dissimilarity pattern of the sampled sediments, but with a higher level of dissimilarity for the RQs. This means that the quinone method has a higher resolution for resolving differences in bacterial community composition. Combining PLFA and quinone analysis as a complementary method is a good strategy to yield higher resolving power in bacterial community structure

An overview of the mid-infrared spectro-interferometer MATISSE: science, concept, and current status

MATISSE is the second-generation mid-infrared spectrograph and imager for the Very Large Telescope Interferometer (VLTI) at Paranal. This new interferometric instrument will allow significant advances by opening new avenues in various fundamental research fields: studying the planet-forming region of disks around young stellar objects, understanding the surface structures and mass loss phenomena affecting evolved stars, and probing the environments of black holes in active galactic nuclei. As a first breakthrough, MATISSE will enlarge the spectral domain of current optical interferometers by offering the L and M bands in addition to the N band. This will open a wide wavelength domain, ranging from 2.8 to 13 um, exploring angular scales as small as 3 mas (L band) / 10 mas (N band). As a second breakthrough, MATISSE will allow mid-infrared imaging - closure-phase aperture-synthesis imaging - with up to four Unit Telescopes (UT) or Auxiliary Telescopes (AT) of the VLTI. Moreover, MATISSE will offer a spectral resolution range from R ~ 30 to R ~ 5000. Here, we present one of the main science objectives, the study of protoplanetary disks, that has driven the instrument design and motivated several VLTI upgrades (GRA4MAT and NAOMI). We introduce the physical concept of MATISSE including a description of the signal on the detectors and an evaluation of the expected performances. We also discuss the current status of the MATISSE instrument, which is entering its testing phase, and the foreseen schedule for the next two years that will lead to the first light at Paranal.Comment: SPIE Astronomical Telescopes and Instrumentation conference, June 2016, 11 pages, 6 Figure

The role of PYY in pancreatic islet physiology and surgical control of diabetes.

Bariatric surgery in obese individuals leads to rapid and lasting remission of type 2 diabetes (T2D). This phenomenon occurs independently of weight loss possibly via a combination of factors. The incretin hormone GLP-1 has so far been recognised as a critical factor. However, recent data have indicated that elevation in another gut hormone, peptide tyrosine tyrosine (PYY), may drive the beneficial effects of surgery. Here we discuss recent findings on PYY-mediated control of glucose homeostasis and its role in diabetes, in the context of what is known for GLP-1. Identification of factors that increase the expression of PYY following bariatric surgery and elucidation of its role in diabetes reversal may have clinical relevance as a nonsurgical therapy for T2D