68 research outputs found

    Retention of Low Income Children in Three Dental Studies Investigating Early Childhood Caries

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    Background: To our knowledge no dental studies have looked closely at subject retention, which is crucial to better understand oral health disparities. In this paper, we report retention rates and review and attempt to assess which retention strategies utilized in 3 dental research studies investigating ECC were effective for retaining WIC-enrolled children. The purpose of this paper is to discuss challenges that were encountered when working with these populations, describe characteristics of those not retained, and summarize some recommendations for future dental studies working at WIC sites. Methods: Three dental studies were conducted at WIC clinics in Iowa. Retention strategies focused on maintenance of contact over time, persistence in rescheduling appointments, utilization of incentives, high recruitment, and frequent communication with parents and program staff. Results: Retention rates in the studies ranged from 60 to 75 percent at the final research interventions. Studies were challenged by frequent moves of subjects, missed appointments, disconnected phones, busy schedules of parents, transportation problems, loss of child custody, family illness, and lack of interest. Those not retained in the studies were more likely to be younger, single, and less educated, with a lower household income and a non-Caucasian child. Lower retention was also associated with the presence of carious lesions. Conclusions: Despite many challenges, studies had good retention rates and benefited from the retention strategies. Future dental studies at WIC clinics may also benefit from arranging transportation, obtaining a free, 800 callback number, and offering after-hours appointments for working parents

    Alteration of renal respiratory Complex-III during experimental type-1 diabetes

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    <p>Abstract</p> <p>Background</p> <p>Diabetes has become the single most common cause for end-stage renal disease in the United States. It has been established that mitochondrial damage occurs during diabetes; however, little is known about what initiates mitochondrial injury and oxidant production during the early stages of diabetes. Inactivation of mitochondrial respiratory complexes or alteration of their critical subunits can lead to generation of mitochondrial oxidants, mitochondrial damage, and organ injury. Thus, one goal of this study was to determine the status of mitochondrial respiratory complexes in the rat kidney during the early stages of diabetes (5-weeks post streptozotocin injection).</p> <p>Methods</p> <p>Mitochondrial complex activity assays, blue native gel electrophoresis (BN-PAGE), Complex III immunoprecipitation, and an ATP assay were performed to examine the effects of diabetes on the status of respiratory complexes and energy levels in renal mitochondria. Creatinine clearance and urine albumin excretion were measured to assess the status of renal function in our model.</p> <p>Results</p> <p>Interestingly, of all four respiratory complexes only cytochrome c reductase (Complex-III) activity was significantly decreased, whereas two Complex III subunits, Core 2 protein and Rieske protein, were up regulated in the diabetic renal mitochondria. The BN-PAGE data suggested that Complex III failed to assemble correctly, which could also explain the compensatory upregulation of specific Complex III subunits. In addition, the renal F<sub>0</sub>F<sub>1</sub>-ATPase activity and ATP levels were increased during diabetes.</p> <p>Conclusion</p> <p>In summary, these findings show for the first time that early (and selective) inactivation of Complex-III may contribute to the mitochondrial oxidant production which occurs in the early stages of diabetes.</p

    Cerebral small vessel disease genomics and its implications across the lifespan

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    White matter hyperintensities (WMH) are the most common brain-imaging feature of cerebral small vessel disease (SVD), hypertension being the main known risk factor. Here, we identify 27 genome-wide loci for WMH-volume in a cohort of 50,970 older individuals, accounting for modification/confounding by hypertension. Aggregated WMH risk variants were associated with altered white matter integrity (p = 2.5×10-7) in brain images from 1,738 young healthy adults, providing insight into the lifetime impact of SVD genetic risk. Mendelian randomization suggested causal association of increasing WMH-volume with stroke, Alzheimer-type dementia, and of increasing blood pressure (BP) with larger WMH-volume, notably also in persons without clinical hypertension. Transcriptome-wide colocalization analyses showed association of WMH-volume with expression of 39 genes, of which four encode known drug targets. Finally, we provide insight into BP-independent biological pathways underlying SVD and suggest potential for genetic stratification of high-risk individuals and for genetically-informed prioritization of drug targets for prevention trials.Peer reviewe

    Federated learning enables big data for rare cancer boundary detection.

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    Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing

    Author Correction: Federated learning enables big data for rare cancer boundary detection.

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    10.1038/s41467-023-36188-7NATURE COMMUNICATIONS14

    The genetic architecture of the human cerebral cortex

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    The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

    Post-intervention Status in Patients With Refractory Myasthenia Gravis Treated With Eculizumab During REGAIN and Its Open-Label Extension

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    OBJECTIVE: To evaluate whether eculizumab helps patients with anti-acetylcholine receptor-positive (AChR+) refractory generalized myasthenia gravis (gMG) achieve the Myasthenia Gravis Foundation of America (MGFA) post-intervention status of minimal manifestations (MM), we assessed patients' status throughout REGAIN (Safety and Efficacy of Eculizumab in AChR+ Refractory Generalized Myasthenia Gravis) and its open-label extension. METHODS: Patients who completed the REGAIN randomized controlled trial and continued into the open-label extension were included in this tertiary endpoint analysis. Patients were assessed for the MGFA post-intervention status of improved, unchanged, worse, MM, and pharmacologic remission at defined time points during REGAIN and through week 130 of the open-label study. RESULTS: A total of 117 patients completed REGAIN and continued into the open-label study (eculizumab/eculizumab: 56; placebo/eculizumab: 61). At week 26 of REGAIN, more eculizumab-treated patients than placebo-treated patients achieved a status of improved (60.7% vs 41.7%) or MM (25.0% vs 13.3%; common OR: 2.3; 95% CI: 1.1-4.5). After 130 weeks of eculizumab treatment, 88.0% of patients achieved improved status and 57.3% of patients achieved MM status. The safety profile of eculizumab was consistent with its known profile and no new safety signals were detected. CONCLUSION: Eculizumab led to rapid and sustained achievement of MM in patients with AChR+ refractory gMG. These findings support the use of eculizumab in this previously difficult-to-treat patient population. CLINICALTRIALSGOV IDENTIFIER: REGAIN, NCT01997229; REGAIN open-label extension, NCT02301624. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that, after 26 weeks of eculizumab treatment, 25.0% of adults with AChR+ refractory gMG achieved MM, compared with 13.3% who received placebo

    Minimal Symptom Expression' in Patients With Acetylcholine Receptor Antibody-Positive Refractory Generalized Myasthenia Gravis Treated With Eculizumab

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    The efficacy and tolerability of eculizumab were assessed in REGAIN, a 26-week, phase 3, randomized, double-blind, placebo-controlled study in anti-acetylcholine receptor antibody-positive (AChR+) refractory generalized myasthenia gravis (gMG), and its open-label extension

    Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990–2017: A systematic analysis for the Global Burden of Disease Study 2017