388 research outputs found

    Review of microdialysis in brain tumors, from concept to application: First Annual Carolyn Frye-Halloran Symposium

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    In individuals with brain tumors, pharmacodynamic and pharmacokinetic studies of therapeutic agents have historically used analyses of drug concentrations in serum or cerebrospinal fluid, which unfortunately do not necessarily reflect concentrations within the tumor and adjacent brain. This review article introduces to neurological and medical oncologists, as well as pharmacologists, the application of microdialysis in monitoring drug metabolism and delivery within the fluid of the interstitial space of brain tumor and its surroundings. Microdialysis samples soluble molecules from the extracellular fluid via a semipermeable membrane at the tip of a probe. In the past decade, it has been used predominantly in neurointensive care in the setting of brain trauma, vasospasm, epilepsy, and intracerebral hemorrhage. At the first Carolyn Frye-Halloran Symposium held at Massachusetts General Hospital in March 2002, the concept of microdialysis was extended to specifically address its possible use in treating brain tumor patients. In doing so we provide a rationale for the use of this technology by a National Cancer Institute consortium, New Approaches to Brain Tumor Therapy, to measure levels of drugs in brain tissue as part of phase 1 trials. Originally published Neuro-oncology, Vol. 6, No. 1, Jan 200

    Patient-Specific Lymphocyte Loss Kinetics as Biomarker of Spleen Dose in Patients Undergoing Radiation Therapy for Upper Abdominal Malignancies

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    Purpose: Radiation therapy (RT)-induced lymphopenia (RIL) is linked with inferior survival in esophageal and pancreatic cancers. Previous work has demonstrated a correlation between spleen dose and RIL risk. The present study correlates spleen dose-volume parameters with fractional lymphocyte loss rate (FLL) and total percent change in absolute lymphocyte count (%ΔALC) and suggests spleen dose constraints to reduce RIL risk. Methods and materials: This registry-based study included 140 patients who underwent RT for pancreatic (n = 67), gastroesophageal (n = 61), or biliary tract (n = 12) adenocarcinoma. Patient-specific parameters of lymphocyte loss kinetics, including FLL and %ΔALC, were calculated based on serial ALCs obtained during RT. Spearman's rho was used to correlate spleen dose-volume parameters with %ΔALC, end-treatment ALC, and FLL. Multivariable logistic regression was used to identify predictors of ≥grade 3 and grade 4 RIL. Results: Spleen dose-volume parameters, including mean spleen dose (MSD), all correlated with %ΔALC, end-treatment ALC, and FLL. Controlling for baseline ALC and planning target volume (PTV), an increase in any spleen dose-volume parameter increased the odds of developing ≥grade 3 lymphopenia. Each 1-Gy increase in MSD increased the odds of ≥grade 3 RIL by 18.6%, and each 100-cm3 increase in PTV increased the odds of ≥grade 3 lymphopenia by 20%. Patients with baseline ALC < 1500 cells/μL had a high risk of ≥grade 3 RIL regardless of MSD or PTV. FLL was an equally good predictor of ≥grade 3 lymphopenia as any spleen dose-volume parameter. Conclusions: In patients undergoing RT for upper abdominal malignancies, higher spleen dose is associated with higher per-fraction lymphocyte loss rates, higher total %ΔALC, and increased odds of severe lymphopenia. Spleen dose constraints should be individualized based on baseline ALC and PTV size to minimize RIL risk, although our findings require validation in larger, ideally prospective data sets

    Vispark: GPU-accelerated distributed visual computing using spark

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    With the growing need of big-data processing in diverse application domains, MapReduce (e.g., Hadoop) has become one of the standard computing paradigms for large-scale computing on a cluster system. Despite its popularity, the current MapReduce framework suffers from inflexibility and inefficiency inherent to its programming model and system architecture. In order to address these problems, we propose Vispark, a novel extension of Spark for GPU-accelerated MapReduce processing on array-based scientific computing and image processing tasks. Vispark provides an easy-to-use, Python-like high-level language syntax and a novel data abstraction for MapReduce programming on a GPU cluster system. Vispark introduces a programming abstraction for accessing neighbor data in the mapper function, which greatly simplifies many image processing tasks using MapReduce by reducing memory footprints and bypassing the reduce stage. Vispark provides socket-based halo communication that synchronizes between data partitions transparently from the users, which is necessary for many scientific computing problems in distributed systems. Vispark also provides domain-specific functions and language supports specifically designed for high-performance computing and image processing applications. We demonstrate the performance of our prototype system on several visual computing tasks, such as image processing, volume rendering, K-means clustering, and heat transfer simulation.clos

    Midwall Fibrosis Is an Independent Predictor of Mortality in Patients With Aortic Stenosis

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    ObjectivesThe goal of this study was to assess the prognostic significance of midwall and infarct patterns of late gadolinium enhancement (LGE) in aortic stenosis.BackgroundMyocardial fibrosis occurs in aortic stenosis as part of the hypertrophic response. It can be detected by LGE, which is associated with an adverse prognosis in a range of other cardiac conditions.MethodsBetween January 2003 and October 2008, consecutive patients with moderate or severe aortic stenosis undergoing cardiovascular magnetic resonance with administration of gadolinium contrast were enrolled into a registry. Patients were categorized into absent, midwall, or infarct patterns of LGE by blinded independent observers. Patient follow-up was completed using patient questionnaires, source record data, and the National Strategic Tracing Service.ResultsA total of 143 patients (age 68 ± 14 years; 97 male) were followed up for 2.0 ± 1.4 years. Seventy-two underwent aortic valve replacement, and 27 died (24 cardiac, 3 sudden cardiac deaths). Compared with those with no LGE (n = 49), univariate analysis revealed that patients with midwall fibrosis (n = 54) had an 8-fold increase in all-cause mortality despite similar aortic stenosis severity and coronary artery disease burden. Patients with an infarct pattern (n = 40) had a 6-fold increase. Midwall fibrosis (hazard ratio: 5.35; 95% confidence interval: 1.16 to 24.56; p = 0.03) and ejection fraction (hazard ratio: 0.96; 95% confidence interval: 0.94 to 0.99; p = 0.01) were independent predictors of all-cause mortality by multivariate analysis.ConclusionsMidwall fibrosis was an independent predictor of mortality in patients with moderate and severe aortic stenosis. It has incremental prognostic value to ejection fraction and may provide a useful method of risk stratification. (The Prognostic Significance of Fibrosis Detection in Cardiomyopathy; NCT00930735

    Association of genetic variants in complement factor H and factor H-related genes with systemic lupus erythematosus susceptibility

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    Systemic lupus erythematosus (SLE), a complex polygenic autoimmune disease, is associated with increased complement activation. Variants of genes encoding complement regulator factor H (CFH) and five CFH-related proteins (CFHR1-CFHR5) within the chromosome 1q32 locus linked to SLE, have been associated with multiple human diseases and may contribute to dysregulated complement activation predisposing to SLE. We assessed 60 SNPs covering the CFH-CFHRs region for association with SLE in 15,864 case-control subjects derived from four ethnic groups. Significant allelic associations with SLE were detected in European Americans (EA) and African Americans (AA), which could be attributed to an intronic CFH SNP (rs6677604, in intron 11, Pmeta = 6.6×10-8, OR = 1.18) and an intergenic SNP between CFHR1 and CFHR4 (rs16840639, Pmeta = 2.9×10-7, OR = 1.17) rather than to previously identified disease-associated CFH exonic SNPs, including I62V, Y402H, A474A, and D936E. In addition, allelic association of rs6677604 with SLE was subsequently confirmed in Asians (AS). Haplotype analysis revealed that the underlying causal variant, tagged by rs6677604 and rs16840639, was localized to a ~146 kb block extending from intron 9 of CFH to downstream of CFHR1. Within this block, the deletion of CFHR3 and CFHR1 (CFHR3-1Δ), a likely causal variant measured using multiplex ligation-dependent probe amplification, was tagged by rs6677604 in EA and AS and rs16840639 in AA, respectively. Deduced from genotypic associations of tag SNPs in EA, AA, and AS, homozygous deletion of CFHR3-1Δ (Pmeta = 3.2×10-7, OR = 1.47) conferred a higher risk of SLE than heterozygous deletion (Pmeta = 3.5×10-4, OR = 1.14). These results suggested that the CFHR3-1Δ deletion within the SLE-associated block, but not the previously described exonic SNPs of CFH, might contribute to the development of SLE in EA, AA, and AS, providing new insights into the role of complement regulators in the pathogenesis of SLE

    Genome-wide analyses as part of the international FTLD-TDP whole-genome sequencing consortium reveals novel disease risk factors and increases support for immune dysfunction in FTLD

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    Frontotemporal lobar degeneration with neuronal inclusions of the TAR DNA-binding protein 43 (FTLD-TDP) represents the most common pathological subtype of FTLD. We established the international FTLD-TDP whole genome sequencing consortium to thoroughly characterize the known genetic causes of FTLD-TDP and identify novel genetic risk factors. Through the study of 1,131 unrelated Caucasian patients, we estimated that C9orf72 repeat expansions and GRN loss-of-function mutations account for 25.5% and 13.9% of FTLD-TDP patients, respectively. Mutations in TBK1 (1.5%) and other known FTLD genes (1.4%) were rare, and the disease in 57.7% of FTLD-TDP patients was unexplained by the known FTLD genes. To unravel the contribution of common genetic factors to the FTLD-TDP etiology in these patients, we conducted a two-stage association study comprising the analysis of whole-genome sequencing data from 517 FTLD-TDP patients and 838 controls, followed by targeted genotyping of the most associated genomic loci in 119 additional FTLD-TDP patients and 1653 controls. We identified three genome-wide significant FTLD-TDP risk loci: one new locus at chromosome 7q36 within the DPP6 gene led by rs118113626 (pvalue=4.82e-08, OR=2.12), and two known loci: UNC13A, led by rs1297319 (pvalue=1.27e-08, OR=1.50) and HLA-DQA2 led by rs17219281 (pvalue=3.22e-08, OR=1.98). While HLA represents a locus previously implicated in clinical FTLD and related neurodegenerative disorders, the association signal in our study is independent from previously reported associations. Through inspection of our whole genome sequence data for genes with an excess of rare loss-of-function variants in FTLD-TDP patients (n≥3) as compared to controls (n=0), we further discovered a possible role for genes functioning within the TBK1-related immune pathway (e.g. DHX58, TRIM21, IRF7) in the genetic etiology of FTLD-TDP. Together, our study based on the largest cohort of unrelated FTLD-TDP patients assembled to date provides a comprehensive view of the genetic landscape of FTLD-TDP, nominates novel FTLD-TDP risk loci, and strongly implicates the immune pathway in FTLD-TDP pathogenesis

    Frontotemporal dementia and its subtypes: a genome-wide association study

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    SummaryBackground Frontotemporal dementia (FTD) is a complex disorder characterised by a broad range of clinical manifestations, differential pathological signatures, and genetic variability. Mutations in three genes—MAPT, GRN, and C9orf72—have been associated with FTD. We sought to identify novel genetic risk loci associated with the disorder. Methods We did a two-stage genome-wide association study on clinical FTD, analysing samples from 3526 patients with {FTD} and 9402 healthy controls. To reduce genetic heterogeneity, all participants were of European ancestry. In the discovery phase (samples from 2154 patients with {FTD} and 4308 controls), we did separate association analyses for each {FTD} subtype (behavioural variant FTD, semantic dementia, progressive non-fluent aphasia, and {FTD} overlapping with motor neuron disease FTD-MND), followed by a meta-analysis of the entire dataset. We carried forward replication of the novel suggestive loci in an independent sample series (samples from 1372 patients and 5094 controls) and then did joint phase and brain expression and methylation quantitative trait loci analyses for the associated (p&lt;5 × 10−8) single-nucleotide polymorphisms. Findings We identified novel associations exceeding the genome-wide significance threshold (p&lt;5 × 10−8). Combined (joint) analyses of discovery and replication phases showed genome-wide significant association at 6p21.3, \{HLA\} locus (immune system), for rs9268877 (p=1·05 × 10−8; odds ratio=1·204 95% \{CI\} 1·11–1·30), rs9268856 (p=5·51 × 10−9; 0·809 0·76–0·86) and rs1980493 (p value=1·57 × 10−8, 0·775 0·69–0·86) in the entire cohort. We also identified a potential novel locus at 11q14, encompassing RAB38/CTSC (the transcripts of which are related to lysosomal biology), for the behavioural \{FTD\} subtype for which joint analyses showed suggestive association for rs302668 (p=2·44 × 10−7; 0·814 0·71–0·92). Analysis of expression and methylation quantitative trait loci data suggested that these loci might affect expression and methylation in cis. Interpretation Our findings suggest that immune system processes (link to 6p21.3) and possibly lysosomal and autophagy pathways (link to 11q14) are potentially involved in FTD. Our findings need to be replicated to better define the association of the newly identified loci with disease and to shed light on the pathomechanisms contributing to FTD. Funding The National Institute of Neurological Disorders and Stroke and National Institute on Aging, the Wellcome/MRC Centre on Parkinson's disease, Alzheimer's Research UK, and Texas Tech University Health Sciences Center
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