Saskatchewan Health

About: Saskatchewan Health is a government organization based out in Regina, Saskatchewan, Canada. It is known for research contribution in the topics: Population & Health care. The organization has 442 authors who have published 489 publications receiving 7728 citations.

An independent replication of PARK16 in Asian samples.

Abstract: Parkinson disease (PD) is the most common neurodegenerative movement disorder with age-related prevalence. Approximately 1% of the population is affected at 65 years, which increases to 4%–5% in 85-year-olds.1 To date, several loci containing pathogenic or risk variants have been identified; the most recent, PARK16 , was nominated through 2 genome-wide association studies (GWAS) using samples of Japanese and European ancestry.2,3 This new locus, located in 1q32, was originally identified in the Asian study with p values ranging from 10 −7 to 10 −12 . PARK16 did not reach significance level in the European GWAS or its replication ( p value >10 −4 ); however, combining samples from stage I and II indicated an association. The most significant SNP in the European study (rs823128) showed a 1% difference in minor allele frequency (MAF) between patients with PD (4%) and control subjects (3%), resulting in an odds ratio (OR) of 0.66 ( p value = 7.3 × 10 −8 ) (of note, the allele frequencies seem to have been mistakenly switched in the combined analysis).3 In contrast, the MAF of rs823128 appears to be more common in the Japanese population, with a lower frequency in patients with PD (10%) …

Predictive performance of comorbidity measures in administrative databases for diabetes cohorts

Abstract: Background The performance of comorbidity measures for predicting mortality in chronic disease populations and using ICD-9 diagnosis codes in administrative health data has been investigated in several studies, but less is known about predictive performance with ICD-10 data and for other health outcomes. This study investigated predictive performance of five comorbidity measures for population-based diabetes cohorts in administrative data. The objectives were to evaluate performance for: (a) disease-specific and general health outcomes, (b) data based on the ICD-9 and ICD-10 diagnoses, and (c) different age groups.

The protocol for the Cannabidiol in children with refractory epileptic encephalopathy (CARE-E) study: a phase 1 dosage escalation study.

Abstract: Initial studies suggest pharmaceutical grade cannabidiol (CBD) can reduce the frequency of convulsive seizures and lead to improvements in quality of life in children affected by epileptic encephalopathies. With limited access to pharmaceutical CBD, Cannabis extracts in oil are becoming increasingly available. Physicians show reluctance to recommend Cannabis extracts given the lack of high quality safety data especially regarding the potential for harm caused by other cannabinoids, such as Δ9-tetrahydrocannabinol (Δ9-THC). The primary aims of the study presented in this protocol are (i) To determine whether CBD enriched Cannabis extract is safe and well-tolerated for pediatric patients with refractory epilepsy, (ii) To monitor the effects of CBD-enriched Cannabis extract on the frequency and duration of seizure types and on quality of life. Twenty-eight children with treatment resistant epileptic encephalopathy ranging in age from 1 to 10 years will be recruited in four Canadian cities into an open-label, dose-escalation phase 1 trial. The primary objectives for the study are (i) To determine if the CBD-enriched Cannabis herbal extract is safe and well-tolerated for pediatric patients with treatment resistant epileptic encephalopathy and (ii) To determine the effect of CBD-enriched Cannabis herbal extract on the frequency and duration of seizures. Secondary objectives include (i) To determine if CBD-enriched Cannabis herbal extracts alter steady-state levels of co-administered anticonvulsant medications. (ii) To assess the relation between dose escalation and quality of life measures, (iii) To determine the relation between dose escalation and steady state trough levels of bioactive cannabinoids. (iv) To determine the relation between dose escalation and incidence of adverse effects. This paper describes the study design of a phase 1 trial of CBD-enriched Cannabis herbal extract in children with treatment-resistant epileptic encephalopathy. This study will provide the first high quality analysis of safety of CBD-enriched Cannabis herbal extract in pediatric patients in relation to dosage and pharmacokinetics of the active cannabinoids. http://clinicaltrials.gov [Internet]. Bethesda (MD): National Library of Medicine (US). 2016 Dec 16. Identifier NCT03024827, Cannabidiol in Children with Refractory Epileptic Encephalopathy: CARE-E; 2017 Jan 19 [cited 2017 Oct]; Available from: http://clinicaltrials.gov/ct2/show/NCT03024827

Brain benzodiazepine receptors in fathead minnows and the behavioral response to alarm pheromone

Abstract: Fathead minnows (Pimephales promelas) exposed to 1 or 10 mg/l chlordiazepoxide showed normal alarm behavior during the presentation of alarm pheromone. Fish exposed to 20 mg/l drug, however, showed little or no behavioral alarm and did not appear sedated. A food extract stimulus presented after alarm pheromone led to a large foraging response by fish exposed to 20 mg/l chlordiazepoxide. Control fish or fish exposed to 1 to 10 mg/l drug showed less tendency to begin foraging. Exposure to 1, 10, or 20 mg/l chlordiazepoxide for 3 hr did not affect whole-brain concentrations of tryptophan, 5-hydroxytryptamine, 5-hydroxyindoleacetic acid, tyrosine, or dopamine. The binding of [3H]diazepam to specific brain receptor sites (KD=10nM, estimated Bmax = 3.3 fmol/mg wet weight) could be displaced by chlordiazepoxide (IC50 = 1.6 μM). The results suggest that benzodiazepine receptors in the central nervous system of lower vertebrates may function in ways similar to those in mammals, i.e., the modulation of behavior in anxiety-like states.

Hybrid-Collaborative Noise2Noise Denoiser for Low-Dose CT Images

Abstract: Low-dose computed tomography (LDCT) has yet to get its full potential benefit due to excessive quantum noise. Although learning to restore an image using two noisy images in the Noise2Noise (N2N) model has shown good promise for different noise models, it does not perform well in LDCT. In this article, we have introduced a collaborative technique to train multiple N2N generators simultaneously and learn the image representation from LDCT images. We have presented three models using this collaborative N2N (CN) principle employing CN two generators (CN2G), CN three generators (CN3G), and hybrid CN3G (HCN3G). The CN3G model has shown better performance than the CN2G model in terms of denoised image quality at the expense of an additional LDCT image. The HCN3G model has taken the advantages of both these models by managing to train three collaborative generators using only two LDCT images by leveraging one previous work called blind source separation (BSS) with block matching 3-D (BM3D). To make the collaboration among different generators more efficient, we have introduced collaborative loss terms among the generators. All three methods have shown improved performance in terms of peak signal-to-noise ratio and structural similarity index metrics compared to similar benchmark methods.