TASK DEFINITION: In this task, you are given a abstract of article and corresponding title of an article. Your task is to generate label "yes" if title is right for article, otherwise generate "no".
PROBLEM: Abstract: In the mammalian brain, astrocytes modulate neuronal function, in part, by synchronizing neuronal firing and coordinating synaptic networks. Little, however, is known about how this is accomplished from a structural standpoint. To investigate the structural basis of astrocyte-mediated neuronal synchrony and synaptic coordination, the three-dimensional relationships between cortical astrocytes and neurons was investigated. Using a transgenic and viral approach to label astrocytes with enhanced green fluorescent protein, we performed a three-dimensional reconstruction of astrocytes from tissue sections or live animals in vivo. We found that cortical astrocytes occupy nonoverlapping territories similar to those described in the hippocampus. Using immunofluorescence labeling of neuronal somata, a single astrocyte enwraps on average four neuronal somata with an upper limit of eight. Single-neuron dye-fills allowed us to estimate that one astrocyte contacts 300-600 neuronal dendrites. Together with the recent findings showing that glial Ca2+ signaling is restricted to individual astrocytes in vivo, and that Ca2+ signaling leads to gliotransmission, we propose the concept of functional islands of synapses in which groups of synapses confined within the boundaries of an individual astrocyte are modulated by the gliotransmitter environment controlled by that astrocyte. Our description offers a new structurally based conceptual framework to evaluate functional data involving interactions between neurons and astrocytes in the mammalian brain.. Title: Synaptic islands defined by the territory of a single astrocyte.

SOLUTION: yes

PROBLEM: Abstract: PURPOSE This study aims to provide a better set of DNA methylation markers in urine sediments for sensitive and specific detection of bladder cancer. EXPERIMENTAL DESIGN Fifty-nine tumor-associated genes were profiled in three bladder cancer cell lines, a small cohort of cancer biopsies and urine sediments by methylation-specific PCR. Twenty-one candidate genes were then profiled in urine sediments from 132 bladder cancer patients (8 cases for stage 0a; 68 cases for stage I; 50 cases for stage II; 4 cases for stages III; and 2 cases for stage IV), 23 age-matched patients with noncancerous urinary lesions, 6 neurologic diseases, and 7 healthy volunteers.
RESULTS Despite six incidences of four genes reported in 3 of 23 noncancerous urinary lesion patients analyzed, cancer-specific hypermethylation in urine sediments were reported for 15 genes (P < 0.05). Methylation assessment of an 11-gene set (SALL3, CFTR, ABCC6, HPR1, RASSF1A, MT1A, RUNX3, ITGA4, BCL2, ALX4, MYOD1, DRM, CDH13, BMP3B, CCNA1, RPRM, MINT1, and BRCA1) confirmed the existing diagnosis of 121 among 132 bladder cancer cases (sensitivity, 91.7%) with 87% accuracy. Significantly, more than 75% of stage 0a and 88% of stage I disease were detected, indicating its value in the early diagnosis of bladder cancer. Interestingly, the cluster of reported methylation markers used in the U.S. bladder cancers is distinctly different from that identified in this study, suggesting a possible epigenetic disparity between the American and Chinese cases.
CONCLUSIONS Methylation profiling of an 11-gene set in urine sediments provides a sensitive and specific detection of bladder cancer.. Title: A novel set of DNA methylation markers in urine sediments for sensitive/specific detection of bladder cancer.

SOLUTION: yes

PROBLEM: Abstract: In traditional Kaplan-Meier or Cox regression analysis, usually a risk factor measured at baseline is related to mortality thereafter. During follow-up, however, things may change: either the effect of a fixed baseline risk factor may vary over time, resulting in a weakening or strengthening of associations over time, or the risk factor itself may vary over time. In this paper, short-term versus long-term effects (so-called time-dependent effects) of a fixed baseline risk factor are addressed. An example is presented showing that underweight is a strong risk factor for mortality in dialysis patients, especially in the short run. In contrast, overweight is a risk factor for mortality, which is stronger in the long run than in the short run. In addition, the analysis of how time-varying risk factors (so-called time-dependent risk factors) are related to mortality is demonstrated by paying attention to the pitfall of adjusting for sequelae. The proper analysis of effects over time should be driven by a clear research question. Both kinds of research questions, that is those of time-dependent effects as well those of time-dependent risk factors, can be analyzed with time-dependent Cox regression analysis. It will be shown that using time-dependent risk factors usually implies focusing on short-term effects only.. Title: Survival analysis: time-dependent effects and time-varying risk factors.

SOLUTION:
yes