1,650 research outputs found

    OncoLog Volume 46, Number 11/12, November-December 2001

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    Multidisciplinary Team Helps Patients with Cancer Overcome Cognitive Problems Protocols: Studies Focus on Cognitive Effects of Cancer and Its Treatment House Call: Simple Steps Can Put Patients on the Road to Well-Being Highly Selective Synthetic Binding Agents Target Different DNA Conformationshttps://openworks.mdanderson.org/oncolog/1101/thumbnail.jp

    Factors Related To Birth Transition Success Of Late-preterm Infants

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    Problem: Identifying the factors effecting birth transition success of late preterm infants may improve early recognition of newborn compromise. Multiple explanatory variables may be associated with birth transition success or failure. The purpose of the study was to determine the prevalence of, and clinical-epidemiological and demographic predictive factors for birth transition success of late preterm infants. Methods: A retrospective case-control chart review was used to compare the characteristics of successful and unsuccessful birth transition of 35 and 36 week gestational age late-preterm infants delivered in a large tertiary-care center during calendar year 2007. A mixture of categorical and numeric variables related to maternal, birth, and physiologic constructs were analyzed for their effects on birth transition as a binary outcome variable (success or failure). Results: Of 22 variables tested, four predictor variables were associated with birth transition failure: labor (OR = .42, p = .014), 5-minute Apgar score (OR = 1.79, p = .043), gender (OR = .47, p =.003), and respiratory rate (OR= 2.08, p = .001) as tested by logistic regression. The model was able to accurately assign transition failure and success at a rate of 66.7% and 74% respectively. The overall model was statistically significant (likelihood ratio chi square = 38.97(4),

    Detection of (1,3)-β-d-Glucan in Cerebrospinal Fluid in Histoplasma Meningitis

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    The diagnosis of central nervous system (CNS) histoplasmosis is often difficult. Although cerebrospinal fluid (CSF) (1,3)-β-d-glucan (BDG) is available as a biological marker for the diagnosis of fungal meningitis, there are limited data on its use for the diagnosis of Histoplasma meningitis. We evaluated CSF BDG detection, using the Fungitell assay, in patients with CNS histoplasmosis and controls. A total of 47 cases and 153 controls were identified. The control group included 13 patients with a CNS fungal infection other than histoplasmosis. Forty-nine percent of patients with CNS histoplasmosis and 43.8% of controls were immunocompromised. The median CSF BDG level was 85 pg/ml for cases, compared to <31 pg/ml for all controls (P < 0.05) and 82 pg/ml for controls with other causes of fungal meningitis (P = 0.27). The sensitivity for detection of BDG in CSF was 53.2%, whereas the specificity was 86.9% versus all controls and 46% versus other CNS fungal infections. CSF BDG levels of ≥80 pg/ml are neither sensitive nor specific to support a diagnosis of Histoplasma meningitis

    Predicting Changes in Bee Assemblages Following State Transitions at North American Dryland Ecotones

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    Drylands worldwide are experiencing ecosystem state transitions: the expansion of some ecosystem types at the expense of others. Bees in drylands are particularly abundant and diverse, with potential for large compositional differences and seasonal turnover across ecotones. To better understand how future ecosystem state transitions may influence bees, we compared bee assemblages and their seasonality among sites at the Sevilleta National Wildlife Refuge (NM, USA) that represent three dryland ecosystem types (and two ecotones) of the southwestern U.S. (Plains grassland, Chihuahuan Desert grassland, and Chihuahuan Desert shrubland). Using passive traps, we caught bees during two-week intervals from March–October, 2002–2014. The resulting dataset included 302 bee species and 56 genera. Bee abundance, composition, and diversity differed among ecosystems, indicating that future state transitions could alter bee assemblage composition in our system. We found strong seasonal bee species turnover, suggesting that bee phenological shifts may accompany state transitions. Common species drove the observed trends, and both specialist and generalist bee species were indicators of ecosystem types or months; these species could be sentinels of community-wide responses to future shifts. Our work suggests that predicting the consequences of global change for bee assemblages requires accounting for both within-year and among-ecosystem variation

    Idiosyncratic responding during movie-watching predicted by age differences in attentional control.

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    Much is known about how age affects the brain during tightly controlled, though largely contrived, experiments, but do these effects extrapolate to everyday life? Naturalistic stimuli, such as movies, closely mimic the real world and provide a window onto the brain's ability to respond in a timely and measured fashion to complex, everyday events. Young adults respond to these stimuli in a highly synchronized fashion, but it remains to be seen how age affects neural responsiveness during naturalistic viewing. To this end, we scanned a large (N = 218), population-based sample from the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) during movie-watching. Intersubject synchronization declined with age, such that older adults' response to the movie was more idiosyncratic. This decreased synchrony related to cognitive measures sensitive to attentional control. Our findings suggest that neural responsivity changes with age, which likely has important implications for real-world event comprehension and memory.This work and the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) are supported by the Biotechnology and Biological Sciences Research Council (grant number BB/H008217/1).This is the final version of the article. It first appeared from Elsevier via http://dx.doi.org/10.1016/j.neurobiolaging.2015.07.02

    Recurrent De Novo NAHR Reciprocal Duplications in the ATAD3 Gene Cluster Cause a Neurogenetic Trait with Perturbed Cholesterol and Mitochondrial Metabolism

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    Recent studies have identified both recessive and dominant forms of mitochondrial disease that result from ATAD3A variants. The recessive form includes subjects with biallelic deletions mediated by non-allelic homologous recombination. We report five unrelated neonates with a lethal metabolic disorder characterized by cardiomyopathy, corneal opacities, encephalopathy, hypotonia, and seizures in whom a monoallelic reciprocal duplication at the ATAD3 locus was identified. Analysis of the breakpoint junction fragment indicated that these 67 kb heterozygous duplications were likely mediated by non-allelic homologous recombination at regions of high sequence identity in ATAD3A exon 11 and ATAD3C exon 7. At the recombinant junction, the duplication allele produces a fusion gene derived from ATAD3A and ATAD3C, the protein product of which lacks key functional residues. Analysis of fibroblasts derived from two affected individuals shows that the fusion gene product is expressed and stable. These cells display perturbed cholesterol and mitochondrial DNA organization similar to that observed for individuals with severe ATAD3A deficiency. We hypothesize that the fusion protein acts through a dominant-negative mechanism to cause this fatal mitochondrial disorder. Our data delineate a molecular diagnosis for this disorder, extend the clinical spectrum associated with structural variation at the ATAD3 locus, and identify a third mutational mechanism for ATAD3 gene cluster variants. These results further affirm structural variant mutagenesis mechanisms in sporadic disease traits, emphasize the importance of copy number analysis in molecular genomic diagnosis, and highlight some of the challenges of detecting and interpreting clinically relevant rare gene rearrangements from next-generation sequencing data.This article is freely available via Open Access. Click on the publisher URL to access it via the publisher's site.We acknowledge funding from Wellcome ( 200990 ). S.E. is a Wellcome Senior Investigator. U.F.P. is supported by a predoctoral fellowship from the Basque Government ( PRE_2018_1_0253 ). M.M.O. is supported by a predoctoral fellowship from the University of the Basque Country ( UPV/EHU, PIF 2018 ). I.J.H. is supported by the Carlos III Health Program ( PI17/00380 ), and País Vasco Department of Health ( 2018111043 ; 2018222031 ). A.S. is supported by the UK Medical Research Council with a Senior Non-Clinical Fellowship ( MC_PC_13029 ). T. Harel is supported by the Israel Science Foundation grant 1663/17 . W.H.Y. is supported by the National Institute of General Medical Sciences of the National Institutes of Health through grant 5 P20 GM103636-07 . J.R.L. is supported by the US National Institute of Neurological Disorders and Stroke ( R35NS105078 ), the National Institute of General Medical Sciences ( R01GM106373 ), and the National Human Genome Research Institute and National Heart Lung and Blood Institute (NHGRI/NHBLI) to the Baylor-Hopkins Center for Mendelian Genomics (BHCMG, UM1 HG006542 ). R.W.T. is supported by the Wellcome Centre for Mitochondrial Research ( 203105/Z/16/Z ), the Medical Research Council (MRC) International Centre for Genomic Medicine in Neuromuscular Disease , Mitochondrial Disease Patient Cohort (UK) ( G0800674 ), the UK NIHR Biomedical Research Centre for Aging and Age-related disease award to the Newcastle upon Tyne Foundation Hospitals NHS Trust, the MRC/EPSRC Molecular Pathology Node , The Lily Foundation , and the UK NHS Highly Specialised Service for Rare Mitochondrial Disorders of Adults and Children . The DDD study presents independent research commissioned by the Health Innovation Challenge Fund (grant number HICF-1009-003). This study makes use of DECIPHER, which is funded by Wellcome. See Nature PMID: 25533962 or https://www.ddduk.org/access.html for full acknowledgment.pre-print, post-print (6 month embargo

    Transtheoretical Model-based multiple behavior intervention for weight management: Effectiveness on a population basis

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    Background: The increasing prevalence of overweight and obesity underscores the need for evidence-based, easily disseminable interventions for weight management that can be delivered on a population basis. The Transtheoretical Model (TTM) offers a promising theoretical framework for multiple behavior weight management interventions. Methods: Overweight or obese adults (BMI 25–39.9; n = 1277) were randomized to no-treatment control or home-based, stage-matched multiple behavior interventions for up to three behaviors related to weight management at 0, 3, 6, and 9 months. All participants were re-assessed at 6, 12, and 24 months. Results: Significant treatment effects were found for healthy eating (47.5% versus 34.3%), exercise (44.90% versus 38.10%), managing emotional distress (49.7% versus 30.30%), and untreated fruit and vegetable intake (48.5% versus 39.0%) progressing to Action/Maintenance at 24 months. The groups differed on weight lost at 24 months. Co-variation of behavior change occurred and was much more pronounced in the treatment group, where individuals progressing to Action/Maintenance for a single behavior were 2.5–5 times more likely to make progress on another behavior. The impact of the multiple behavior intervention was more than three times that of single behavior interventions. Conclusions: This study demonstrates the ability of TTM-based tailored feedback to improve healthy eating, exercise, managing emotional distress, and weight on a population basis. The treatment produced a high level of population impact that future multiple behavior interventions can seek to surpass

    African American Women Have a Disadvantage When It Comes to Cancer Care

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    Race has an impact on breast cancer treatment and survival. Non-Hispanic white women are more likely to survive breast cancer than African American women. Younger women are especially vulnerable. They tend to lack adequate health insurance.York's Knowledge Mobilization Unit provides services and funding for faculty, graduate students, and community organizations seeking to maximize the impact of academic research and expertise on public policy, social programming, and professional practice. It is supported by SSHRC and CIHR grants, and by the Office of the Vice-President Research & Innovation. [email protected] www.researchimpact.c

    Improving completeness of electronic problem lists through clinical decision support: a randomized, controlled trial

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    Background: Accurate clinical problem lists are critical for patient care, clinical decision support, population reporting, quality improvement, and research. However, problem lists are often incomplete or out of date. Objective: To determine whether a clinical alerting system, which uses inference rules to notify providers of undocumented problems, improves problem list documentation. Study Design and Methods: Inference rules for 17 conditions were constructed and an electronic health record-based intervention was evaluated to improve problem documentation. A cluster randomized trial was conducted of 11 participating clinics affiliated with a large academic medical center, totaling 28 primary care clinical areas, with 14 receiving the intervention and 14 as controls. The intervention was a clinical alert directed to the provider that suggested adding a problem to the electronic problem list based on inference rules. The primary outcome measure was acceptance of the alert. The number of study problems added in each arm as a pre-specified secondary outcome was also assessed. Data were collected during 6-month pre-intervention (11/2009–5/2010) and intervention (5/2010–11/2010) periods. Results: 17,043 alerts were presented, of which 41.1% were accepted. In the intervention arm, providers documented significantly more study problems (adjusted OR=3.4, p<0.001), with an absolute difference of 6,277 additional problems. In the intervention group, 70.4% of all study problems were added via the problem list alerts. Significant increases in problem notation were observed for 13 of 17 conditions. Conclusion: Problem inference alerts significantly increase notation of important patient problems in primary care, which in turn has the potential to facilitate quality improvement
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