Evaluation of enteral formulas for nutrition, health, and quality of life among stroke patients

Enteral nutritional support has been used via tube feeding for dysphagic stroke patients. We performed long and short term trials to evaluate the effects of commercial enteral nutritional supports on nutrition and health in stroke patients (mRS = 3~5) and quality of life in their caregivers. For a long term study, we recruited chronic (≥ 1 yrs) stroke patients (n = 6) and administered them 6 cans/day (1,200 kcal) of the commercial enteral formula N for 6 months according to IRB-approved protocol. We collected peripheral blood at 0, 2, 4 and 6 months. For a short term study, we recruited acute (≤ 3 months) stroke patients (n = 12) and randomly administered them two different commercial enteral formulas, N or J, for 2 weeks. We collected their blood at 0, 4, 7 and 14 day of the administration. Blood samples were analyzed to quantify 19 health and nutritional biomarkers and an oxidative stress biomarker, malondialdehyde (MDA). In order to evaluate quality of life, we also obtained the sense of competence questionnaire (SCQ) from all caregivers at 'before' and 'after trials'. As results, the enteral formula, N, improved hemoglobin and hematocrit levels in the long term trial and maintained most of biomarkers within normal ranges. The SCQ levels of caregivers were improved in the long term treatment (P < 0.05). In a case of the short term study, both of enteral formulas were helpful to maintain nutritional status of the patients. In addition, MDA levels were decreased in the acute patients following formula consumption (0.05 < P < 0.1). Most of health and nutrition outcomes were not different, even though there is a big difference in price of the two products. Thus, we evaluate the formula N has equal nutritional efficacy compared to the formula J. In addition, long term use of enteral formula N can be useful to health and nutrition of stroke patients, and the quality of life for their caregivers

Gold Nanoparticle-Enhanced and Roll-to-Roll Nanoimprinted LSPR Platform for Detecting Interleukin-10

Localized surface plasmon resonance (LSPR) is a powerful platform for detecting biomolecules including proteins, nucleotides, and vesicles. Here, we report a colloidal gold (Au) nanoparticle-based assay that enhances the LSPR signal of nanoimprinted Au strips. The binding of the colloidal Au nanoparticle on the Au strip causes a red-shift of the LSPR extinction peak, enabling the detection of interleukin-10 (IL-10) cytokine. For LSPR sensor fabrication, we employed a roll-to-roll nanoimprinting process to create nanograting structures on polyethylene terephthalate (PET) film. By the angled deposition of Au on the PET film, we demonstrated a double-bent Au structure with a strong LSPR extinction peak at ~760 nm. Using the Au LSPR sensor, we developed an enzyme-linked immunosorbent assay (ELISA) protocol by forming a sandwich structure of IL-10 capture antibody/IL-10/IL-10 detection antibody. To enhance the LSPR signal, we introduced colloidal Au nanocube (AuNC) to be cross-linked with IL-10 detection antibody for immunogold assay. Using IL-10 as a model protein, we successfully achieved nanomolar sensitivity. We confirmed that the shift of the extinction peak was improved by 450% due to plasmon coupling between AuNC and Au strip. We expect that the AuNC-assisted LSPR sensor platform can be utilized as a diagnostic tool by providing convenient and fast detection of the LSPR signal. © Copyright © 2020 Baek, Song, Lee, Kim, Kim, Wi, Ok, Park, Hong, Kwak, Lee and Nam.1

25th annual computational neuroscience meeting: CNS-2016

The same neuron may play different functional roles in the neural circuits to which it belongs. For example, neurons in the Tritonia pedal ganglia may participate in variable phases of the swim motor rhythms [1]. While such neuronal functional variability is likely to play a major role the delivery of the functionality of neural systems, it is difficult to study it in most nervous systems. We work on the pyloric rhythm network of the crustacean stomatogastric ganglion (STG) [2]. Typically network models of the STG treat neurons of the same functional type as a single model neuron (e.g. PD neurons), assuming the same conductance parameters for these neurons and implying their synchronous firing [3, 4]. However, simultaneous recording of PD neurons shows differences between the timings of spikes of these neurons. This may indicate functional variability of these neurons. Here we modelled separately the two PD neurons of the STG in a multi-neuron model of the pyloric network. Our neuron models comply with known correlations between conductance parameters of ionic currents. Our results reproduce the experimental finding of increasing spike time distance between spikes originating from the two model PD neurons during their synchronised burst phase. The PD neuron with the larger calcium conductance generates its spikes before the other PD neuron. Larger potassium conductance values in the follower neuron imply longer delays between spikes, see Fig. 17.Neuromodulators change the conductance parameters of neurons and maintain the ratios of these parameters [5]. Our results show that such changes may shift the individual contribution of two PD neurons to the PD-phase of the pyloric rhythm altering their functionality within this rhythm. Our work paves the way towards an accessible experimental and computational framework for the analysis of the mechanisms and impact of functional variability of neurons within the neural circuits to which they belong

Coarse-to-Fine Deep Metric Learning for Remote Sensing Image Retrieval

Remote sensing image retrieval (RSIR) is the process of searching for identical areas by investigating the similarities between a query image and the database images. RSIR is a challenging task owing to the time difference, viewpoint, and coverage area depending on the shooting circumstance, resulting in variations in the image contents. In this paper, we propose a novel method based on a coarse-to-fine strategy, which makes a deep network more robust to the variations in remote sensing images. Moreover, we propose a new triangular loss function to consider the whole relation within the tuple. This loss function improves the retrieval performance and demonstrates better performance in terms of learning the detailed information in complex remote sensing images. To verify our methods, we experimented with the Google Earth South Korea dataset, which contains 40,000 images, using the evaluation metric Recall@n. In all experiments, we obtained better performance results than those of the existing retrieval training methods. Our source code and Google Earth South Korea dataset are available online

Optimization and Extended Applicability of Simplified Slug Flow Model for Liquid-Gas Flow in Horizontal and Near Horizontal Pipes

The accurate prediction of pressure loss for two-phase slug flow in pipes with a simple and powerful methodology has been desired. The calculation of pressure loss has generally been performed by complicated mechanistic models, most of which require the iteration of many variables. The objective of this study is to optimize the previously proposed simplified slug flow model for horizontal pipes, extending the applicability to turbulent flow conditions, i.e., high mixture Reynolds number and near horizontal pipes. The velocity field previously measured by particle image velocimetry further supports the suggested slug flow model which neglects the pressure loss in the liquid film region. A suitable prediction of slug characteristics such as slug liquid holdup and translational velocity (or flow coefficient) is required to advance the accuracy of calculated pressure loss. Therefore, the proper correlations of slug liquid holdup, flow coefficient, and friction factor are identified and utilized to calculate the pressure gradient for horizontal and near horizontal pipes. The optimized model presents a fair agreement with 2191 existing experimental data (0.001 &le; &mu;L &le; 0.995 Pa∙s, 7 &le; ReM &le; 227,007 and &minus;9 &le; &theta; &le; 9), showing &minus;3% and 0.991 as values of the average relative error and the coefficient of determination, respectively

Expression of androgen receptors and inhibin/activin alpha and betaA subunits in breast apocrine lesions

The importance of androgens and their receptors inhibin and activin remains unknown for mammary epithelial cells. We investigated the role of these hormones in breast apocrine lesions (BAL) using immunohistochemistry to study androgen receptors (AR) and the inhibin/activin alpha and betaA subunits. Forty-two cases of BAL were evaluated, including 22 cases of fibrocystic disease (FCD) showing prominent apocrine changes, 10 intraductal papillomas with extensive apocrine metaplasia, 5 cases of apocrine carcinoma in situ (CIS), and 5 cases of apocrine carcinoma. Fifty non-apocrine lesions were included as controls: 20 cases of FCD, 5 cases of DCIS, and 25 cases of invasive ductal carcinoma. AR was more frequently expressed in BAL than in non-apocrine lesions (p=0.001). AR expression was not related to tumor progression. AR showed a significant positive correlation with betaA subunits (r=0.832, p<0.001), and an inverse correlation with alpha subunits (r=-0.233). The alpha and betaA subunits demonstrated a significant inverse correlation with each other (r=-0.271, p=0.0048). As the expression of the alpha and betaA subunits reflects inhibin and activin A, respectively, AR and activin A may be implicated in apocrine morphogenesis, but not in tumor progression

Incidence and Levels of Deoxynivalenol, Fumonisins and Zearalenone Contaminants in Animal Feeds Used in Korea in 2012

The objective of this study was to evaluate the occurrence and levels of deoxynivalenol (DON), fumonisins B1 and B2 (FBs), and zearalenone (ZEN) contaminants in animal feeds used in Korea in 2012. Contamination with DON was observed in 91.33% and 53.33% in compound feeds and feed ingredients, respectively. Among compound feeds, poultry layer feed (laying) exhibited the highest contaminant level of 1.492 mg/kg. FBs contaminants were present in compound feeds and feed ingredients at 93.33% and 83.33%, respectively. Most poultry broiler (early) feeds were highly contaminated with FBs, and one of these feeds detected the level as 12.823 mg/kg as the highest level. The levels of ZEN in compound feeds and feed ingredients were 71.33% and 47%, respectively. Ninety-eight percent of compound feeds for cattle were contaminated with ZEN, and the highest contamination level of 0.405 mg/kg was observed in cattle fatting feeds

MEDICAL IMAGING APPARATUS AND METHOD FOR PROCESSING MEDICAL IMAGE

A medical imaging apparatus includes a data acquirer configured to acquire measured data acquired by detecting an X-ray transmitted by an X-ray source to an object, and an image processor configured to acquire an initial image based on the measured data, alternately estimate region of interest (ROI)-outside measured data and ROI-inside measured data based on the measured data and the initial image, and acquire a reconstructed image based on the ROI-inside measured data.</p