273 research outputs found

    Having Fun While Enhancing Student Engagement: Creative Approaches in Online Learning

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    This article explores various creative approaches to integrate into online counselor education classrooms. Creative approaches to learning help encourage students to be involved in classroom discussions or activities; while enhancing their critical thinking skills, professional development, and inclusivity within the classroom. This article explores the intention behind integrating creative approaches into online learning and offers several resources that instructors can use in their online classrooms

    Latent autoimmune diabetes of adulthood: case report

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    Abstract Background Primary care clinicians will see a higher incidence of type 2 diabetes in adult patients, and the diagnosis and management of an initial presentation of type 1 diabetes can pose challenges to clinicians who see it less frequently. Symptoms of hyperglycemia and risk of ketoacidosis may be missed. Further, endocrine autoimmune disease can run together in patients and families. Case presentation A 49-year-old Caucasian female with history of pituitary adenoma and Graves’ disease with history of thyroid ablation presented in the outpatient setting due to hand tingling of her right middle finger that was worse in the mornings and improved throughout the day. She also complained of excessive thirst, finding herself drinking more water than usual and waking up in the night to urinate. There was no dysuria or haematuria, and no other neurologic symptoms. She did report feeling hungry. She had no family history of diabetes, normal body mass index of 21.7, and reported taking her thyroid replacement medication every day. The differential diagnosis for her thirst included dehydration, psychogenic polydipsia, diabetes mellitus, diabetes insipidus, and anxiety. The patient had normal vital signs and was well appearing; labs were ordered for her on her way home from clinic with no medications. Labs revealed a random blood glucose level of 249 mg/dL, normal renal function, a normal B12 of 996 pg/mL, and an elevated thyroid stimulating hormone level of 25.67 u[iU]/mL. On follow up with her primary care provider 5 days later, additional labs were drawn showing A1C of 11.5%, 1+ ketonuria, a negative Acetest, and a normal basic metabolic panel, except for a fasting glucose of 248 mg/dL, and Free T3 of 2.42 pg/mL, and Free T4 of 1.7 ng/dL. Islet cell antibodies and glutamic acid decarboxylase antibodies were both positive, consistent with type 1 diabetes. She was started on insulin and improved. Conclusion Given the patient’s age, this is a less common presentation of type 1 diabetes mellitus, as a part of polyglandular autoimmune syndrome type IIIa. It serves as a reminder that clinicians should remember that patients with one autoimmune disease (in this case, h/o Graves’ disease) are at higher risk for diabetes and other endocrine autoimmune diseases and should be screened appropriately. Clinicians should keep latent type 1 diabetes in the differential in adulthood to ensure proper and timely treatment

    Towards a ‘smart’ cost–benefit tool: using machine learning to predict the costs of criminal justice policy interventions

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    BACKGROUND: The Manning Cost–Benefit Tool (MCBT) was developed to assist criminal justice policymakers, policing organisations and crime prevention practitioners to assess the benefits of different interventions for reducing crime and to select those strategies that represent the greatest economic return on investment. DISCUSSION: A challenge with the MCBT and other cost–benefit tools is that users need to input, manually, a considerable amount of point-in-time data, a process that is time consuming, relies on subjective expert opinion, and introduces the potential for data-input error. In this paper, we present and discuss a conceptual model for a ‘smart’ MCBT that utilises machine learning techniques. SUMMARY: We argue that the Smart MCBT outlined in this paper will overcome the shortcomings of existing cost–benefit tools. It does this by reintegrating individual cost–benefit analysis (CBA) projects using a database system that securely stores and de-identifies project data, and redeploys it using a range of machine learning and data science techniques. In addition, the question of what works is respecified by the Smart MCBT tool as a data science pipeline, which serves to enhance CBA and reconfigure the policy making process in the paradigm of open data and data analytics

    Effects of the coronary artery disease associated LPA and 9p21 loci on risk of aortic valve stenosis

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    Background: Aortic valve stenosis (AVS) and coronary artery disease (CAD) have a significant genetic contribution and commonly co-exist. To compare and contrast genetic determinants of the two diseases, we investigated associations of the LPA and 9p21 loci, i.e. the two strongest CAD risk loci, with risk of AVS. Methods: We genotyped the CAD-associated variants at the LPA (rs10455872) and 9p21 loci (rs1333049) in the GeneCAST (Genetics of Calcific Aortic STenosis) Consortium and conducted a meta-analysis for their association with AVS. Cases and controls were stratified by CAD status. External validation of findings was undertaken in five cohorts including 7880 cases and 851,152 controls. Results: In the meta-analysis including 4651 cases and 8231 controls the CAD-associated allele at the LPA locus was associated with increased risk of AVS (OR 1.37; 95%CI 1.24–1.52, p = 6.9 × 10−10) with a larger effect size in those without CAD (OR 1.53; 95%CI 1.31–1.79) compared to those with CAD (OR 1.27; 95%CI 1.12–1.45). The CAD-associated allele at 9p21 was associated with a trend towards lower risk of AVS (OR 0.93; 95%CI 0.88–0.99, p = 0.014). External validation confirmed the association of the LPA risk allele with risk of AVS (OR 1.37; 95%CI 1.27–1.47), again with a higher effect size in those without CAD. The small protective effect of the 9p21 CAD risk allele could not be replicated (OR 0.98; 95%CI 0.95–1.02). Conclusions: Our study confirms the association of the LPA locus with risk of AVS, with a higher effect in those without concomitant CAD. Overall, 9p21 was not associated with AVS

    Hundreds of variants clustered in genomic loci and biological pathways affect human height

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    Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.

    Coding variants in RPL3L and MYZAP increase risk of atrial fibrillation

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    Source at https://doi.org/10.1038/s42003-018-0068-9. Most sequence variants identified hitherto in genome-wide association studies (GWAS) of atrial fibrillation are common, non-coding variants associated with risk through unknown mechanisms. We performed a meta-analysis of GWAS of atrial fibrillation among 29,502 cases and 767,760 controls from Iceland and the UK Biobank with follow-up in samples from Norway and the US, focusing on low-frequency coding and splice variants aiming to identify causal genes. We observe associations with one missense (OR = 1.20) and one splice-donor variant (OR = 1.50) in RPL3L, the first ribosomal gene implicated in atrial fibrillation to our knowledge. Analysis of 167 RNA samples from the right atrium reveals that the splice-donor variant in RPL3L results in exon skipping. We also observe an association with a missense variant in MYZAP (OR = 1.38), encoding a component of the intercalated discs of cardiomyocytes. Both discoveries emphasize the close relationship between the mechanical and electrical function of the heart
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