Effect of screening abdominal ultrasound examination on the decision to pursue advanced diagnostic tests and treatment in dogs with neurologic disease.

BackgroundAbdominal ultrasound examinations (AUS) are commonly performed before advanced neurodiagnostics to screen for diseases that might affect diagnostic plans and prognosis.ObjectivesDescribe the type and frequency of abnormalities found by AUS in dogs presenting with a neurological condition, identify risk factors associated with abnormalities, and evaluate treatment decisions based on findings.AnimalsSeven hundred and fifty-nine hospitalized dogs.MethodsRetrospective study. Medical records of dogs presented from 2007 to 2009 for neurologic disease were searched for signalment, neuroanatomic localization, and AUS findings. Whether dogs had advanced neurodiagnostics and treatment was analyzed.ResultsFifty-eight percent of dogs had abnormal findings on AUS. Probability of abnormalities increased with age (P < 0.001). Nondachshund breeds had higher probability of abnormal AUS than dachshunds (odds ratio [OR] = 1.87). Eleven percent of dogs did not have advanced neurodiagnostics and in 1.3%, this was because of abnormal AUS. Dogs with ultrasonographic abnormalities were less likely than dogs without to have advanced neurodiagnostics (OR = 0.3 [95% confidence interval [CI]: 0.17, 0.52]), however, the probability of performing advanced diagnostics was high regardless of normal (OR = 0.95 [95% CI: 0.92, 0.97]) or abnormal (OR = 0.85 [95% CI: 0.81, 0.88]) AUS. Treatment was more often pursued in small dogs and less often in dogs with brain disease.Conclusions and clinical importanceFindings from screening AUS had a small negative effect on the likelihood of pursuing advanced neurodiagnostics. Although it should be included in the extracranial diagnostic workup in dogs with significant history or physical examination abnormalities, AUS is considered a low-yield diagnostic test in young dogs and dachshunds

A BLUEPRINT FOR IMPLEMENTING GRAND CHALLENGE SCHOLARS’ PROGRAMME: A CASE STUDY OF TAYLOR’S UNIVERSITY

The National Academy for Engineering announced 14 Grand Challenges for the 21st Century engineers to address in order to ensure a sustainable future for the generations to come. These grand challenges are in four broad areas, namely, energy and environment, health, security and learning and computation. This paper reports on a Grand Challenges Scholars’ Programme that is developed to prepare the engineering students to be able to address the grand challenges using the CDIO framework and focusing on five components; research experience, interdisciplinary curriculum, entrepreneurship, global dimension and service learning. The programme is voluntary and the candidates are expected to commit additional learning time. The programme was launched with 16 participants who are expected to graduate in 2016. A preliminary assessment of the programs shows that the participants found the programme useful in developing an array of CDIO skills. The School intends to continue offering this programme with the intention of integrating it with a holistic education approach

A Hybrid Microwave-Optical Applicator for Local Muscle Warming and Monitoring

Local warming of human tissue causes vasodilation and therefore blood volume to increase. Such thermal blood volume response allows the assessment of microcirculation in tissue, providing clinically important information. The deep warming is provided by a novel microwave applicator, which has a annular-ring microstrip patch operating at 2450 MHz with a superstrate interface layer to improve the coupling of electromagnetic (EM) waves into the skin. The design is based on computer simulations of specific absorption rate (SAR) and thermal distribution of the EM waves in a biological medium. The simulation results show that the applicator can elevate the muscle temperature by 3 to 4^{\circ}\mathrm{C}. The thermal response is measured by an integrated optical probe which measures tissue oxygenation changes in deep tissue using the near infrared spectroscopy technique

Improved content aware scene retargeting for retinitis pigmentosa patients

<p>Abstract</p> <p>Background</p> <p>In this paper we present a novel scene retargeting technique to reduce the visual scene while maintaining the size of the key features. The algorithm is scalable to implementation onto portable devices, and thus, has potential for augmented reality systems to provide visual support for those with tunnel vision. We therefore test the efficacy of our algorithm on shrinking the visual scene into the remaining field of view for those patients.</p> <p>Methods</p> <p>Simple spatial compression of visual scenes makes objects appear further away. We have therefore developed an algorithm which removes low importance information, maintaining the size of the significant features. Previous approaches in this field have included <it>seam carving</it>, which removes low importance seams from the scene, and <it>shrinkability </it>which dynamically shrinks the scene according to a generated importance map. The former method causes significant artifacts and the latter is inefficient. In this work we have developed a new algorithm, combining the best aspects of both these two previous methods. In particular, our approach is to generate a <it>shrinkability </it>importance map using as seam based approach. We then use it to dynamically shrink the scene in similar fashion to the <it>shrinkability </it>method. Importantly, we have implemented it so that it can be used in real time without prior knowledge of future frames.</p> <p>Results</p> <p>We have evaluated and compared our algorithm to the <it>seam carving </it>and image <it>shrinkability </it>approaches from a content preservation perspective and a compression quality perspective. Also our technique has been evaluated and tested on a trial included 20 participants with simulated tunnel vision. Results show the robustness of our method at reducing scenes up to 50% with minimal distortion. We also demonstrate efficacy in its use for those with simulated tunnel vision of 22 degrees of field of view or less.</p> <p>Conclusions</p> <p>Our approach allows us to perform content aware video resizing in real time using only information from previous frames to avoid jitter. Also our method has a great benefit over the ordinary resizing method and even over other image retargeting methods. We show that the benefit derived from this algorithm is significant to patients with fields of view 20° or less.</p

The performance of alternative forecasting methods for SETAR models

We compare a number of methods that have been proposed in the literature for obtaining h-step ahead minimum mean square error forecasts for SETAR models. These forecasts are compared to those from an AR model. The comparison of forecasting methods is made using Monte Carlo simulation. The Monte Carlo method of calculating SETAR forecasts is generally at least as good as that of the other methods we consider. An exception is when the disturbances in the SETAR model come from a highly asymmetric distribution, when a Bootstrap method is to be preferred. An empirical application calculates multi-period forecasts from a SETAR model of US GNP using a number of the forecasting methods. We find that whether there are improvements in forecast performance relative to a linear AR model depends on the historical epoch we select, and whether forecasts are evaluated conditional on the regime the process was in at the time the forecast was made

Characterization and comparison of toxin-producing isolates of Dinophysis acuminata from New England and Canada

Following the identification of the first toxic isolate of Dinophysis acuminata from the northwestern Atlantic, we conducted detailed investigations into the morphology, phylogeny, physiology, and toxigenicity of three isolates from three sites within the northeastern U.S./Canada region: Eel Pond and Martha\u27s Vineyard, Massachusetts, and the Bay of Fundy. Another isolate, collected from the Gulf of Mexico, was grown under the same light, temperature, and prey conditions for comparison. Despite observed phenotypic heterogeneity, morphometrics and molecular evidence classified the three northwestern Atlantic isolates as D. acuminata Claparede & Lachmann, whereas the isolate from the Gulf of Mexico was morphologically identified as D. cf. ovum. Physiological and toxin analyses supported these classifications, with the three northwestern Atlantic isolates being more similar to each other with respect to growth rate, toxin profile, and diarrhetic shellfish poisoning (DSP) toxin content (okadaic acid + dinophysistoxin 1/cell) than they were to the isolate from the Gulf of Mexico, which had toxin profiles similar to those published for D. cf. ovum F. Schutt. The DSP toxin content, 0.01-1.8 pg okadaic acid (OA) + dinophysistoxin (DTX1) per cell, of the three northwestern Atlantic isolates was low relative to other D. acuminata strains from elsewhere in the world, consistent with the relative scarcity of shellfish harvesting closures due to DSP toxins in the northeastern U. S. and Canada. If this pattern is repeated with the analyses of more geographically and temporally dispersed isolates from the region, it would appear that the risk of significant DSP toxin outbreaks in the northwestern Atlantic is low to moderate. Finally, the morphological, physiological, and toxicological variability within D. acuminata may reflect spatial (and/or temporal) population structure, and suggests that sub-specific resolution may be helpful in characterizing bloom dynamics and predicting toxicity

Chemical constituents of the leaves of Alnus nepalensis D. Don. (Betulaceae)

Taraxeryl acetate (1), physcion (2), 1-nonacosanol (3), b-sitosterol (4), quercetin (5), b-sitosterol 3-O-b-D-glucopyranoside (6), and quercitrin  (7) were isolated from the leaves of Alnus nepalensis D. Don. (Betulaceae). Their structures were determined by spectroscopic methods

Metabolomic Profiling of Post-Mortem Brain Reveals Changes in Amino Acid and Glucose Metabolism in Mental Illness Compared with Controls

Metabolomic profiling was carried out on 53 post-mortem brain samples from subjects diagnosed with schizophrenia, depression, bipolar disorder (SDB), diabetes, and controls. Chromatography on a ZICpHILIC column was used with detection by Orbitrap mass spectrometry. Data extraction was carried out with m/z Mine 2.14 with metabolite searching against an in-house database. There was no clear discrimination between the controls and the SDB samples on the basis of a principal components analysis (PCA) model of 755 identified or putatively identified metabolites. Orthogonal partial least square discriminant analysis (OPLSDA) produced clear separation between 17 of the controls and 19 of the SDB samples (R2CUM 0.976, Q2 0.671, p-value of the cross-validated ANOVA score 0.0024). The most important metabolites producing discrimination were the lipophilic amino acids leucine/isoleucine, proline, methionine, phenylalanine, and tyrosine; the neurotransmitters GABA and NAAG and sugar metabolites sorbitol, gluconic acid, xylitol, ribitol, arabinotol, and erythritol. Eight samples from diabetic brains were analysed, six of which grouped with the SDB samples without compromising the model (R2 CUM 0.850, Q2 CUM 0.534, p-value for cross-validated ANOVA score 0.00087). There appears on the basis of this small sample set to be some commonality between metabolic perturbations resulting from diabetes and from SDB