Regulation of PPARγ2 Stability and Activity by SHP-1.

The protein tyrosine phosphatase Src homology region 2 domain-containing phosphatase-1 (SHP-1) plays an important role in modulating glucose and lipid homeostasis. We previously suggested a potential role of SHP-1 in the regulation of peroxisome proliferator-activated receptor γ2 (PPARγ2) expression and activity but the mechanisms were unexplored. PPARγ2 is the master regulator of adipogenesis, but how its activity is regulated by tyrosine phosphorylation is largely unknown. Here, we found that SHP-1 binds to PPARγ2 primarily via its N-terminal SH2-domain. We confirmed the phosphorylation of PPARγ2 on tyrosine-residue 78 (Y78), which was reduced by SHP-1 in vitro resulting in decreased PPARγ2 stability. Loss of SHP-1 led to elevated, agonist-induced expression of the classical PPARγ2 targets FABP4 and CD36, concomitant with increased lipid content in cells expressing PPARγ2, an effect blunted by abrogation of PPARγ2 phosphorylation. Collectively, we discovered that SHP-1 affects the stability of PPARγ2 through dephosphorylation thereby influencing adipogenesis.

Microscopy-BIDS: An Extension to the Brain Imaging Data Structure for Microscopy Data.

The Brain Imaging Data Structure (BIDS) is a specification for organizing, sharing, and archiving neuroimaging data and metadata in a reusable way. First developed for magnetic resonance imaging (MRI) datasets, the community-led specification evolved rapidly to include other modalities such as magnetoencephalography, positron emission tomography, and quantitative MRI (qMRI). In this work, we present an extension to BIDS for microscopy imaging data, along with example datasets. Microscopy-BIDS supports common imaging methods, including 2D/3D, ex/in vivo, micro-CT, and optical and electron microscopy. Microscopy-BIDS also includes comprehensible metadata definitions for hardware, image acquisition, and sample properties. This extension will facilitate future harmonization efforts in the context of multi-modal, multi-scale imaging such as the characterization of tissue microstructure with qMRI.

Rapid, automated nerve histomorphometry through open-source artificial intelligence.

We aimed to develop and validate a deep learning model for automated segmentation and histomorphometry of myelinated peripheral nerve fibers from light microscopic images. A convolutional neural network integrated in the AxonDeepSeg framework was trained for automated axon/myelin segmentation using a dataset of light-microscopic cross-sectional images of osmium tetroxide-stained rat nerves including various axonal regeneration stages. In a second dataset, accuracy of automated segmentation was determined against manual axon/myelin labels. Automated morphometry results, including axon diameter, myelin sheath thickness and g-ratio were compared against manual straight-line measurements and morphometrics extracted from manual labels with AxonDeepSeg as a reference standard. The neural network achieved high pixel-wise accuracy for nerve fiber segmentations with a mean (± standard deviation) ground truth overlap of 0.93 (± 0.03) for axons and 0.99 (± 0.01) for myelin sheaths, respectively. Nerve fibers were identified with a sensitivity of 0.99 and a precision of 0.97. For each nerve fiber, the myelin thickness, axon diameter, g-ratio, solidity, eccentricity, orientation, and individual x -and y-coordinates were determined automatically. Compared to manual morphometry, automated histomorphometry showed superior agreement with the reference standard while reducing the analysis time to below 2.5% of the time needed for manual morphometry. This open-source convolutional neural network provides rapid and accurate morphometry of entire peripheral nerve cross-sections. Given its easy applicability, it could contribute to significant time savings in biomedical research while extracting unprecedented amounts of objective morphologic information from large image datasets.

The use of a three-dimensional dynamic arm support prevents the development of muscle fatigue during repetitive manual tasks in healthy individuals.

Work-related upper extremity disorders are costly to society due to resulting medical costs, presenteeism and absenteeism. Although their aetiology is likely multifactorial, physical workplace factors are known to play an important role in their development. Promising options for preventing work-related upper extremity disorders include assistive technologies such as dynamic arm supports designed to follow the movement of the arm while compensating for its weight. The objective of this study was to assess the effects of a dynamic arm support on perceived exertion, muscle activity and movement patterns of the upper limb during repetitive manual tasks in healthy individuals. Thirty healthy right-handed individuals were allocated either a static or a dynamic task to perform with and without a dynamic arm support. During the task, surface electromyographic activity (anterior and middle deltoid, upper trapezius) and upper limb kinematics (elbow, shoulder, sternoclavicular) were measured using surface EMG and inertial sensors. Results showed that the dynamic arm support significantly reduced perceived exertion during the tasks and limited the development of muscular fatigue of the anterior and middle deltoid as demonstrated by EMG signal mean epoch amplitudes and median frequency of the EMG power spectrum. The dynamic arm support also prevented a decrease in shoulder elevation and an increase in total shoulder joint excursion during static and dynamic task, respectively. These results denote the potential benefits of dynamic arm supports in work environments. Further studies should focus on their efficacy, acceptability and implementability in work settings.

Impact of telemedicine on diagnosis, clinical management and outcomes in rural trauma patients: A rapid review.

INTRODUCTION: Rural trauma patients are at increased risk of morbidity and mortality compared to trauma patients treated in urban facilities. Factors contributing to this disparity include differences in resource availability and increased time to definitive treatment for rural patients. Telemedicine can improve the early management of these patients by enabling rural providers to consult with trauma specialists at urban centres. The purpose of this study was to assess the impact of telemedicine utilisation on the diagnosis, clinical management and outcomes of rural trauma patients. MATERIALS AND METHODS: A rapid review of the literature was performed using the concepts 'trauma', 'rural' and 'telemedicine'. Fifteen electronic databases were searched from inception to 29th June 2018. Manual searches were also conducted in relevant systematic reviews, key journals and bibliographies of included studies. RESULTS: The literature search identified 187 articles, of which 8 articles were included in the review. All 8 studies reported on clinical management, while the impact of telemedicine use on diagnosis and outcomes was reported in 4 and 5 studies, respectively. Study findings suggest that the use of telemedicine may improve patient diagnosis, streamline the process of transferring patients and reduce length of stay. Use of telemedicine had minimal impact on mortality and complications in rural trauma patients. CONCLUSIONS: The evidence identified by this rapid review suggests that telemedicine may improve the diagnosis, management and outcomes of rural trauma patients. Further research is required to validate these findings by performing large and well-designed studies in rural areas, ideally as randomised clinical trials.

Résumé Introduction: Les traumatisés en région rurale présentent un risque accru de morbidité et de mortalité comparativement aux traumatisés des établissements en région urbaine. Les facteurs qui contribuent à cette disparité sont les différences quant à la disponibilité des ressources et un délai prolongé avant d'accéder au traitement définitif chez les patients des régions rurales. La télémédecine améliore la prise en charge précoce de ces patients en permettant aux fournisseurs en milieu rural de consulter des spécialistes en traumatologie des centres urbains. Cette étude avait pour but d'évaluer l'impact de la télémédecine sur le diagnostic, la prise en charge clinique et les résultats chez les patients traumatisés en milieu rural. Méthodologie: Un examen rapide de la littérature a été effectué à l'aide des mots-clés anglais "trauma", " rural " et "telemedicine". La recherche a eu lieu dans 15 banques de données électroniques à compter de leur lancement jusqu'au 29 juin 2018. Des recherches manuelles ont également été effectuées dans les revues systématiques et publications scientifiques pertinentes et dans les bibliographies des études incluses. Résultats: La recherche de la littérature a donné lieu à 187 articles, dont 8 ont été inclus dans la revue. Les 8 études portaient sur la prise en charge clinique, alors que l'impact de la télémédecine sur le diagnostic et les résultats a fait l'objet de 4 et de 5 études, respectivement. Les résultats des études laissent croire que la télémédecine améliorerait le diagnostic, simplifierait le processus de transfert des patients et raccourcirait le séjour. La télémédecine a eu un effet minime sur la mortalité et les complications chez les patients traumatisés en milieu rural. Conclusions: Les données probantes relevées par cet examen rapide laissent croire que la télémédecine améliorerait le diagnostic, la prise en charge et les résultats chez les patients traumatisés en milieu rural. D'autres recherches sont nécessaires pour valider ces conclusions par l'entremise d'études d'envergure bien conçues menées en régions rurales, idéalement sous forme d'études cliniques à répartition aléatoire. Mots-clés: rural, télémédecine, patients traumatisés en milieu rural, diagnostic des patients en milieu rural.

Coregistered optical coherence tomography and frequency-encoded multispectral imaging for spectrally sparse color imaging.

We present a system combining optical coherence tomography (OCT) and multispectral imaging (MSI) for coregistered structural imaging and surface color imaging. We first describe and numerically validate an optimization model to guide the selection of the MSI wavelengths and their relative intensities. We then demonstrate the integration of this model into an all-fiber bench-top system. We implement frequency-domain multiplexing for the MSI to enable concurrent acquisition of both OCT and MSI at OCT acquisition rates. Such a system could be implemented in endoscopic practices to provide multimodal, high-resolution imaging of deep organ structures that are currently inaccessible to standard video endoscopes.