Evaluating the Association Between Depressive Symptoms and Glycemic Control Among Residents of Rural Appalachia

Introduction: Type 2 diabetes mellitus (T2DM) is associated with a range of co-morbid physical and psychological conditions, including depression. Yet there is a dearth of evidence regarding the prevalence of depression among those in Appalachia living with T2DM; this gap persists despite the higher regional prevalence of T2DM and challenging social determinants of health. Purpose: This study aimed to provide greater detail about the relationships between T2DM and depressive symptoms in adults living in Appalachia Kentucky. Methods: The present study was a cross-sectional analysis of baseline data derived from an ongoing study of Appalachia Kentucky adults living with T2DM. Outcome data included demographics, Center for Epidemiologic Studies Depression Scale, point-of-care HbA1c, and the Summary of Diabetes Self-Care Activities. Bivariate analysis was conducted using Pearson’s correlation to determine the statistically significant relationships between variables which were then included in a multiple regression model. Results: The sample (N=365), consisted primarily of women (n=230, 64.6%) of mean age 64 years (±10.6); almost all (98%) were non-Hispanic White (n=349), and most were married (n=208, 59.1%). The majority (47.2%) reported having two comorbid conditions (n=161), including T2DM, and the mean HbA1c was 7.7% (1.7). Nearly 90% were nonsmokers (n=319). Depressive symptoms were reported in 25% (n=90) of participants. A higher number of comorbid conditions, increased age, Medicaid insurance, tobacco use, lower financial status, female sex, and disability compared to fully employed status all were correlated with a higher rate of depressive symptoms (r ≤ 0.2). The regression indicated that depressive symptoms were associated with age (β = –0.010, p = 0.001); full-time employment status compared to those who are disabled (β = –.0209, p = 0.18); men compared to women (β = –0.122, p = 0.042), and those who smoke compared to nonsmokers (β = 0.175, p = 0.038). Implications: Depressive symptoms were correlated with T2DM among this sample of Appalachian residents with poorly controlled T2DM, especially among women. Given the vast number of social determinants (e.g., poverty, food insecurity, and rurality) affecting this population, healthcare providers must assess for depression and consider its negative influence on the patient’s ability to achieve glycemic control

The effects of stimulus complexity on the preattentive processing of self-generated and nonself voices: an ERP study

The ability to differentiate one's own voice from the voice of somebody else plays a critical role in successful verbal self-monitoring processes and in communication. However, most of the existing studies have only focused on the sensory correlates of self-generated voice processing, whereas the effects of attentional demands and stimulus complexity on self-generated voice processing remain largely unknown. In this study, we investigated the effects of stimulus complexity on the preattentive processing of self and nonself voice stimuli. Event-related potentials (ERPs) were recorded from 17 healthy males who watched a silent movie while ignoring prerecorded self-generated (SGV) and nonself (NSV) voice stimuli, consisting of a vocalization (vocalization category condition: VCC) or of a disyllabic word (word category condition: WCC). All voice stimuli were presented as standard and deviant events in four distinct oddball sequences. The mismatch negativity (MMN) ERP component peaked earlier for NSV than for SGV stimuli. Moreover, when compared with SGV stimuli, the P3a amplitude was increased for NSV stimuli in the VCC only, whereas in the WCC no significant differences were found between the two voice types. These findings suggest differences in the time course of automatic detection of a change in voice identity. In addition, they suggest that stimulus complexity modulates the magnitude of the orienting response to SGV and NSV stimuli, extending previous findings on self-voice processing.This work was supported by Grant Numbers IF/00334/2012, PTDC/PSI-PCL/116626/2010, and PTDC/MHN-PCN/3606/2012, funded by the Fundacao para a Ciencia e a Tecnologia (FCT, Portugal) and the Fundo Europeu de Desenvolvimento Regional through the European programs Quadro de Referencia Estrategico Nacional and Programa Operacional Factores de Competitividade, awarded to A.P.P., and by FCT Doctoral Grant Number SFRH/BD/77681/2011, awarded to T.C.info:eu-repo/semantics/publishedVersio

Amino-acid PET versus MRI guided re-irradiation in patients with recurrent glioblastoma multiforme (GLIAA) – protocol of a randomized phase II trial (NOA 10/ARO 2013-1)

Background: The higher specificity of amino-acid positron emission tomography (AA-PET) in the diagnosis of gliomas, as well as in the differentiation between recurrence and treatment-related alterations, in comparison to contrast enhancement in T1-weighted MRI was demonstrated in many studies and is the rationale for their implementation into radiation oncology treatment planning. Several clinical trials have demonstrated the significant differences between AA-PET and standard MRI concerning the definition of the gross tumor volume (GTV). A small single-center non-randomized prospective study in patients with recurrent high grade gliomas treated with stereotactic fractionated radiotherapy (SFRT) showed a significant improvement in survival when AA-PET was integrated in target volume delineation, in comparison to patients treated based on CT/MRI alone. Methods: This protocol describes a prospective, open label, randomized, multi-center phase II trial designed to test if radiotherapy target volume delineation based on FET-PET leads to improvement in progression free survival (PFS) in patients with recurrent glioblastoma (GBM) treated with re-irradiation, compared to target volume delineation based on T1Gd-MRI. The target sample size is 200 randomized patients with a 1:1 allocation ratio to both arms. The primary endpoint (PFS) is determined by serial MRI scans, supplemented by AA-PET-scans and/or biopsy/surgery if suspicious of progression. Secondary endpoints include overall survival (OS), locally controlled survival (time to local progression or death), volumetric assessment of GTV delineated by either method, topography of progression in relation to MRIor PET-derived target volumes, rate of long term survivors (> 1 year), localization of necrosis after re-irradiation, quality of life (QoL) assessed by the EORTC QLQ-C15 PAL questionnaire, evaluation of safety of FET-application in AA-PET imaging and toxicity of re-irradiation. Discussion: This is a protocol of a randomized phase II trial designed to test a new strategy of radiotherapy target volume delineation for improving the outcome of patients with recurrent GBM. Moreover, the trial will help to develop a standardized methodology for the integration of AA-PET and other imaging biomarkers in radiation treatment planning. Trial registration: The GLIAA trial is registered with ClinicalTrials.gov (NCT01252459, registration date 02.12.2010), German Clinical Trials Registry (DRKS00000634, registration date 10.10.2014), and European Clinical Trials Database (EudraCT-No. 2012-001121-27, registration date 27.02.2012)

The Mediating/Moderating Role of Cultural Context Factors on Self-Care Practices among Those Living with Diabetes in Rural Appalachia

Background The aim of this study was to examine whether cultural factors, such as religiosity and social support, mediate/moderate the relationship between personal/psychosocial factors and T2DM self-care in a rural Appalachian community. Methods Regression models were utilized to assess for mediation and moderation. Multilevel linear mixed effects models and GEE-type logistic regression models were fit for continuous (social support, self-care) and binary (religiosity) outcomes, respectively. Results The results indicated that cultural context factors (religiosity and social support) can mediate/moderate the relationship between psychosocial factors and T2DM self-care. Specifically, after adjusting for demographic variables, the findings suggested that social support may moderate the effect of depressive symptoms and stress on self-care. Religiosity may moderate the effect of distress on self-care, and empowerment was a predictor of self-care but was not mediated/moderated by the assessed cultural context factors. When considering health status, religiosity was a moderately significant predictor of self-care and may mediate the relationship between perceived health status and T2DM self-care. Conclusions This study represents the first known research to examine cultural assets and diabetes self-care practices among a community-based sample of Appalachian adults. We echo calls to increase the evidence on social support and religiosity and other contextual factors among this highly affected population. Trial registration US National Library of Science identifier NCT03474731. Registered March 23, 2018, www.clinicaltrials.gov

Velocity-space sensitivity of the time-of-flight neutron spectrometer at JET

The velocity-space sensitivities of fast-ion diagnostics are often described by so-called weight functions. Recently, we formulated weight functions showing the velocity-space sensitivity of the often dominant beam-target part of neutron energy spectra. These weight functions for neutron emission spectrometry (NES) are independent of the particular NES diagnostic. Here we apply these NES weight functions to the time-of-flight spectrometer TOFOR at JET. By taking the instrumental response function of TOFOR into account, we calculate time-of-flight NES weight functions that enable us to directly determine the velocity-space sensitivity of a given part of a measured time-of-flight spectrum from TOFOR

Full-length human placental sFlt-1-e15a isoform induces distinct maternal phenotypes of preeclampsia in mice

<div><p>Objective</p><p>Most anti-angiogenic preeclampsia models in rodents utilized the overexpression of a truncated soluble fms-like tyrosine kinase-1 (sFlt-1) not expressed in any species. Other limitations of mouse preeclampsia models included stressful blood pressure measurements and the lack of postpartum monitoring. We aimed to 1) develop a mouse model of preeclampsia by administering the most abundant human placental sFlt-1 isoform (hsFlt-1-e15a) in preeclampsia; 2) determine blood pressures in non-stressed conditions; and 3) develop a survival surgery that enables the collection of fetuses and placentas and postpartum (PP) monitoring.</p><p>Methods</p><p>Pregnancy status of CD-1 mice was evaluated with high-frequency ultrasound on gestational days (GD) 6 and 7. Telemetry catheters were implanted in the carotid artery on GD7, and their positions were verified by ultrasound on GD13. Mice were injected through tail-vein with adenoviruses expressing hsFlt-1-e15a (n = 11) or green fluorescent protein (GFP; n = 9) on GD8/GD11. Placentas and pups were delivered by cesarean section on GD18 allowing PP monitoring. Urine samples were collected with cystocentesis on GD6/GD7, GD13, GD18, and PPD8, and albumin/creatinine ratios were determined. GFP and hsFlt-1-e15a expression profiles were determined by qRT-PCR. Aortic ring assays were performed to assess the effect of hsFlt-1-e15a on endothelia.</p><p>Results</p><p>Ultrasound predicted pregnancy on GD7 in 97% of cases. Cesarean section survival rate was 100%. Mean arterial blood pressure was higher in hsFlt-1-e15a-treated than in GFP-treated mice (∆MAP = 13.2 mmHg, p = 0.00107; GD18). Focal glomerular changes were found in hsFlt-1-e15a -treated mice, which had higher urine albumin/creatinine ratios than controls (109.3±51.7μg/mg vs. 19.3±5.6μg/mg, p = 4.4x10^-2; GD18). Aortic ring assays showed a 46% lesser microvessel outgrowth in hsFlt-1-e15a-treated than in GFP-treated mice (p = 1.2x10^-2). Placental and fetal weights did not differ between the groups. One mouse with liver disease developed early-onset preeclampsia-like symptoms with intrauterine growth restriction (IUGR).</p><p>Conclusions</p><p>A mouse model of late-onset preeclampsia was developed with the overexpression of hsFlt-1-e15a, verifying the <i>in vivo</i> pathologic effects of this primate-specific, predominant placental sFlt-1 isoform. HsFlt-1-e15a induced early-onset preeclampsia-like symptoms associated with IUGR in a mouse with a liver disease. Our findings support that hsFlt-1-e15a is central to the terminal pathway of preeclampsia, and it can induce the full spectrum of symptoms in this obstetrical syndrome.</p></div

Racism as a determinant of health: a systematic review and meta-analysis

Despite a growing body of epidemiological evidence in recent years documenting the health impacts of racism, the cumulative evidence base has yet to be synthesized in a comprehensive meta-analysis focused specifically on racism as a determinant of health. This meta-analysis reviewed the literature focusing on the relationship between reported racism and mental and physical health outcomes. Data from 293 studies reported in 333 articles published between 1983 and 2013, and conducted predominately in the U.S., were analysed using random effects models and mean weighted effect sizes. Racism was associated with poorer mental health (negative mental health: r = -.23, 95% CI [-.24,-.21], k = 227; positive mental health: r = -.13, 95% CI [-.16,-.10], k = 113), including depression, anxiety, psychological stress and various other outcomes. Racism was also associated with poorer general health (r = -.13 (95% CI [-.18,-.09], k = 30), and poorer physical health (r = -.09, 95% CI [-.12,-.06], k = 50). Moderation effects were found for some outcomes with regard to study and exposure characteristics. Effect sizes of racism on mental health were stronger in cross-sectional compared with longitudinal data and in non-representative samples compared with representative samples. Age, sex, birthplace and education level did not moderate the effects of racism on health. Ethnicity significantly moderated the effect of racism on negative mental health and physical health: the association between racism and negative mental health was significantly stronger for Asian American and Latino(a) American participants compared with African American participants, and the association between racism and physical health was significantly stronger for Latino(a) American participants compared with African American participants.<br /

Who benefits? Health equity and the Translational Science Benefits Model

IntroductionEvaluating the impacts of translational science is crucial for demonstrating the quality, relevance, and societal benefits of research. This paper presents current results of efforts to expand the Translational Science Benefits Model (TSBM), a framework and toolkit originally developed at Washington University in St. Louis with 30 specific, real-world benefits across clinical, community, economic, and policy domains. In response to a growing emphasis on health and social equity, we have refined the TSBM to better address and integrate ideas of fairness and justice.MethodsOur methods included a literature scan to identify health equity gaps in the framework, community listening sessions in St. Louis, MO, and Madison, WI, and thematic analysis to incorporate equity into the TSBM.ResultsThe results introduce new dimensions within the existing TSBM domains that include 10 new benefits, all emphasizing themes of trust, power, and access.DiscussionOur aim is to enhance the relevance and utility of the framework and tools to researchers, practitioners, and those affected by implementations of findings from translational science and research. The integration of equity into the TSBM supports continued growth in the number of users and uses of the framework and toolkit to demonstrate health and social impact

Accelerated search for biomolecular network models to interpret high-throughput experimental data

<p>Abstract</p> <p>Background</p> <p>The functions of human cells are carried out by biomolecular networks, which include proteins, genes, and regulatory sites within DNA that encode and control protein expression. Models of biomolecular network structure and dynamics can be inferred from high-throughput measurements of gene and protein expression. We build on our previously developed fuzzy logic method for bridging quantitative and qualitative biological data to address the challenges of noisy, low resolution high-throughput measurements, i.e., from gene expression microarrays. We employ an evolutionary search algorithm to accelerate the search for hypothetical fuzzy biomolecular network models consistent with a biological data set. We also develop a method to estimate the probability of a potential network model fitting a set of data by chance. The resulting metric provides an estimate of both model quality and dataset quality, identifying data that are too noisy to identify meaningful correlations between the measured variables.</p> <p>Results</p> <p>Optimal parameters for the evolutionary search were identified based on artificial data, and the algorithm showed scalable and consistent performance for as many as 150 variables. The method was tested on previously published human cell cycle gene expression microarray data sets. The evolutionary search method was found to converge to the results of exhaustive search. The randomized evolutionary search was able to converge on a set of similar best-fitting network models on different training data sets after 30 generations running 30 models per generation. Consistent results were found regardless of which of the published data sets were used to train or verify the quantitative predictions of the best-fitting models for cell cycle gene dynamics.</p> <p>Conclusion</p> <p>Our results demonstrate the capability of scalable evolutionary search for fuzzy network models to address the problem of inferring models based on complex, noisy biomolecular data sets. This approach yields multiple alternative models that are consistent with the data, yielding a constrained set of hypotheses that can be used to optimally design subsequent experiments.</p