Howellbowling8933

DFNA25 is an autosomal-dominant and progressive form of human deafness caused by mutations in the SLC17A8 gene, which encodes the vesicular glutamate transporter type 3 (VGLUT3). To resolve the mechanisms underlying DFNA25, we studied phenotypes of mice harbouring the p.A221V mutation in humans (corresponding to p.A224V in mice). Using auditory brainstem response and distortion product otoacoustic emissions, we showed progressive hearing loss with intact cochlear amplification in the VGLUT3A224V/A224V mouse. The summating potential was reduced, indicating the alteration of inner hair cell (IHC) receptor potential. Scanning electron microscopy examinations demonstrated the collapse of stereocilia bundles in IHCs, leaving those from outer hair cells unaffected. In addition, IHC ribbon synapses underwent structural and functional modifications at later stages. Using super-resolution microscopy, we observed oversized synaptic ribbons and patch-clamp membrane capacitance measurements showed an increase in the rate of the sustained releasable pool exocytosis. These results suggest that DFNA25 stems from a failure in the mechano-transduction followed by a change in synaptic transfer. The VGLUT3A224V/A224V mouse model opens the way to a deeper understanding and to a potential treatment for DFNA25. KEY POINTS The vesicular glutamate transporter type 3 (VGLUT3) loads glutamate into the synaptic vesicles of auditory sensory cells, the inner hair cells (IHCs). The VGLUT3-p.A211V variant is associated with human deafness DFNA25. Y-27632 cell line Mutant mice carrying the VGLUT3-p.A211V variant show progressive hearing loss. IHCs from mutant mice harbour distorted stereocilary bundles, which detect incoming sound stimulation, followed by oversized synaptic ribbons, which release glutamate onto the afferent nerve fibres. These results suggest that DFNA25 stems from the failure of auditory sensory cells to faithfully transduce acoustic cues into neural messages.

Amyotrophic lateral sclerosis (ALS), a neurodegenerative disease characterized by the degeneration of upper and lower motor neurons, progressive wasting and paralysis of voluntary muscles and is currently incurable. Although considered to be a pure motor neuron disease, increasing evidence indicates that the sole protection of motor neurons by a single targeted drug is not sufficient to improve the pathological phenotype. We therefore evaluated the therapeutic potential of the multi-target drug used to treatment of coronary artery disease, trimetazidine, in SOD1

mice.

As a metabolic modulator, trimetazidine improves glucose metabolism. Furthermore, trimetazidine enhances mitochondrial metabolism and promotes nerve regeneration, exerting an anti-inflammatory and antioxidant effect. We orally treated SOD1

mice with trimetazidine, solubilized in drinking water at a dose of 20 mg kg

, from disease onset. We assessed the impact of trimetazidine on disease progression by studying metabolic parameters, grip strength and histological alterations in skeletal muscle, peripheral nerves and the spinal cord.

Trimetazidine administration delays motor function decline, improves muscle performance and metabolism, and significantly extends overall survival of SOD1

mice (increased median survival of 16 days and 12.5 days for male and female respectively). Moreover, trimetazidine prevents the degeneration of neuromuscular junctions, attenuates motor neuron loss and reduces neuroinflammation in the spinal cord and in peripheral nerves.

In SOD1

mice, therapeutic effect of trimetazidine is underpinned by its action on mitochondrial function in skeletal muscle and spinal cord.

In SOD1G93A mice, therapeutic effect of trimetazidine is underpinned by its action on mitochondrial function in skeletal muscle and spinal cord.

Organ-at-risk contouring is still a bottleneck in radiotherapy, with many deep learning methods falling short of promised results when evaluated on clinical data. We investigate the accuracy and time-savings resulting from the use of an interactive-machine-learning method for an organ-at-risk contouringtask.

We implement an open-source interactive-machine-learning software application that facilitates corrective-annotation for deep-learning generated contours on X-ray CT images. A trained-physician contoured 933 hearts using our software by delineating the first image, starting model training, and then correcting the model predictions for all subsequent images. These corrections were added into the training data, which was used for continuously training the assisting model. From the 933 hearts, the same physician also contoured the first 10 and last 10 in Eclipse (Varian) to enable comparison in terms of accuracy andduration.

We find strong agreement with manual delineations, with a dice score of 0.95. The annotations created using corrective-annotation also take less time to create as more images are annotated, resulting in substantial time savings compared to manual methods. After 923 images had been delineated, hearts took 2 min and 2 s to delineate on average, which includes time to evaluate the initial model prediction and assign the needed corrections, compared to 7 min and 1 s when delineatingmanually.

Our experiment demonstrates that interactive-machine-learning with corrective-annotation provides a fast and accessible way for non computer-scientists to train deep-learning models to segment their own structures of interest as part of routine clinicalworkflows.

Our experiment demonstrates that interactive-machine-learning with corrective-annotation provides a fast and accessible way for non computer-scientists to train deep-learning models to segment their own structures of interest as part of routine clinical workflows.

Accurate and robust auto-segmentation of highly deformable organs (HDOs), for example, stomach or bowel, remains an outstanding problem due to these organs' frequent and large anatomical variations. Yet, time-consuming manual segmentation of these organs presents a particular challenge to time-limited modern radiotherapy techniques such as on-line adaptive radiotherapy and high-dose-rate brachytherapy. We propose a machine-assisted interpolation (MAI) that uses prior information in the form of sparse manual delineations to facilitate rapid, accurate segmentation of the stomach from low field magnetic resonance images (MRI) and the bowel from computed tomography (CT) images.

Stomach MR images from 116 patients undergoing 0.35T MRI-guided abdominal radiotherapy and bowel CT images from 120 patients undergoing high dose rate pelvic brachytherapy treatment were collected. For each patient volume, the manual delineation of the HDO was extracted from every 8th slice. These manually drawn contours were first int potential to expedite the process of HDO delineation within the radiation therapy workflow.

The proposed MAI algorithm significantly outperformed LI in terms of accuracy and robustness for both stomach segmentation from low-field MRIs and bowel segmentation from CT images. At this time, FAS methods for HDOs still require significant manual editing. Therefore, we believe that the MAI algorithm has the potential to expedite the process of HDO delineation within the radiation therapy workflow.Psychophysical data indicate that humans can discriminate visual scenes based on their skewness, i.e. the ratio of dark and bright patches within a visual scene. It has also been shown that at a phenomenological level this skew discrimination is described by the so-called blackshot mechanism, which accentuates strong negative contrasts within a scene. Here, we present a set of observations suggesting that the underlying computation might start as early as the cone phototransduction cascade, whose gain is higher for strong negative contrasts than for strong positive contrasts. We recorded from goldfish cone photoreceptors and found that the asymmetry in the phototransduction gain leads to responses with larger amplitudes when using negatively rather than positively skewed light stimuli. This asymmetry in amplitude was present in the cone photocurrent, voltage response and synaptic output. Given that the properties of the phototransduction cascade are universal across vertebrates, it is possible that the mechanitive contrasts (bright patches). Unlike the implicit assumption often contained within models of downstream visual neurons, our data show that cone photoreceptors do not simply relay linearly filtered versions of visual stimuli to downstream circuitry, but that they also emphasize specific stimulus features. Given that the phototransduction cascade properties among vertebrate retinas are mostly universal, our data imply that the skew discrimination by human subjects reported in psychophysical studies might stem from the asymmetric gain function of the phototransduction cascade.Addiction researchers are interested in the ability of neural signals, like the P3 component of the ERP, to index individual differences in liability factors like motivational reactivity to alcohol/drug cues. The reliability of these measures directly impacts their ability to index individual differences, yet little attention has been paid to their psychometric properties. The present study fills this gap by examining within-session internal consistency reliability (ICR) and between-session test-retest reliability (TRR) of the P3 amplitude elicited by images of alcoholic beverages (Alcohol Cue P3) and non-alcoholic drinks (NADrink Cue P3) as well as the difference between them, which isolates alcohol cue-specific reactivity in the P3 (ACR-P3). Analyses drew on data from a large sample of alcohol-experienced emerging adults (session 1 N = 211, 55% female, aged 18-20 yr; session 2 N = 98, 66% female, aged 19-21 yr). Evaluated against domain-general thresholds, ICR was excellent (M ± SD; r= 0.902 ± 0.030) and TRR was fair (r = 0.706 ± 0.020) for Alcohol Cue P3 and NADrink Cue P3, whereas for ACR-P3, ICR and TRR were poor (r = 0.370 ± 0.071; r = 0.201 ± 0.042). These findings indicate that individual differences in the P3 elicited by cues for ingested liquid rewards are highly reliable and substantially stable over 8-10 months. Individual differences in alcohol cue-specific P3 reactivity were less reliable and less stable. The conditions under which alcohol/drug cue-specific reactivity in neural signals is adequately reliable and stable remain to be discovered.

Prothrombotic fibrin clot properties, including increased clot density, are in part genetically determined. We investigated whether fibrinogen alpha-chain gene (FGA) c.991A>G (rs6050), fibrinogen beta chain gene (FGB) -455G>A (rs1800790) and factor XIII gene (F13) c.103G>T (rs5985) polymorphisms affect plasma fibrin clot properties in patients with acute pulmonary embolism (PE).

As many as 126 normotensive patients with PE, free of cancer, were genotyped by TaqMan assay. Fibrin clot permeability (K

), clot lysis time (CLT) and endogenous thrombin potential (ETP) were assessed on admission.

The minor allele frequencies were as follows FGA rs6050 (n=62, 0.31), FGB rs1800790 (n=40, 0.17) and F13 rs5985 (n=49, 0.23). There were no differences related to any of the polymorphisms with regard to demographic, clinical and laboratory data, except for fibrinogen concentration, which was higher in carriers of F13 rs5985 polymorphism (p=.024), and PE combined with deep-vein thrombosis, which was less prevalent in FGB rs1800790 polymorphism carriers (p=.