In this task, you are given a passage which has a question and the context. You have to generate an answer to the question based on the information present in the context.

Input: Consider Input: Context: To systematically review methodological articles which focus on nonpublication of studies and to describe methods of detecting and/or quantifying and/or adjusting for dissemination in meta-analyses. To evaluate whether the methods have been applied to an empirical data set for which one can be reasonably confident that all studies conducted have been included.', 'We systematically searched Medline, the Cochrane Library, and Web of Science, for methodological articles that describe at least one method of detecting and/or quantifying and/or adjusting for dissemination bias in meta-analyses.', 'The literature search retrieved 2,224 records, of which we finally included 150 full-text articles. A great variety of methods to detect, quantify, or adjust for dissemination bias were described. Methods included graphical methods mainly based on funnel plot approaches, statistical methods, such as regression tests, selection models, sensitivity analyses, and a great number of more recent statistical approaches. Only few methods have been validated in empirical evaluations using unpublished studies obtained from regulators (Food and Drug Administration, European Medicines Agency).\Question: Are methods for detecting , quantifying , and adjusting for dissemination bias in meta-analysis described?

Output: We present an overview of existing methods to detect, quantify, or adjust for dissemination bias. It remains difficult to advise which method should be used as they are all limited and their validity has rarely been assessed. Therefore, a thorough literature search remains crucial in systematic reviews, and further steps to increase the availability of all research results need to be taken.

Input: Consider Input: Context: We sought to assess whether mechanical unloading has beneficial effects on cardiomyocytes from doxorubicin-induced cardiomyopathy in rats.', 'Mechanical unloading by a left ventricular assist device (LVAD) improves the cardiac function of terminal heart failure in humans. However, previous animal studies have failed to demonstrate beneficial effects of mechanical unloading in the myocardium.', 'The effects of mechanical unloading by heterotopic abdominal heart transplantation were evaluated in the myocardium from doxorubicin-treated rats by analyzing the intracellular free calcium level ([Ca(2+)](i)) and the levels of intracellular Ca(2+)-regulatory proteins.', 'In doxorubicin-treated rats, the duration of cell shortening and [Ca(2+)](i) transients in cardiomyocytes was prolonged (432 +/- 28.2% of control in 50% relaxation time; 184 +/- 10.5% of control in [Ca(2+)](i) 50% decay time). Such prolonged time courses significantly recovered after mechanical unloading (114 +/- 10.4% of control in 50% relaxation time; 114 +/- 5.8% of control in 50% decay time). These effects were accompanied by an increase in sarcoplasmic reticulum Ca(2+) ATPase (SERCA2a) protein levels (0.97 +/- 0.05 in unloaded hearts vs. 0.41+/- 0.09 in non-unloaded hearts). The levels of other intracellular Ca(2+)-regulatory proteins (phospholamban and ryanodine receptor) were not altered after mechanical unloading in doxorubicin-treated hearts. These parameters in unloaded hearts without doxorubicin treatment were similar to normal hearts.\Question: Does mechanical unloading improve intracellular Ca2+ regulation in rats with doxorubicin-induced cardiomyopathy?

Output: Mechanical unloading increases functional sarcoplasmic reticulum Ca(2+) ATPase and improves [Ca(2+)](i) handling and contractility in rats with doxorubicin-induced cardiomyopathy. These beneficial effects of mechanical unloading were not observed in normal hearts.

Input: Consider Input: Context: Pancreatic ductal adenocarcinoma (PDAC) is a lethal malignancy associated with poor survival rates. Fast detection of PDAC appears to be the most relevant strategy to improve the long-term survival of patients.', 'Our objective was to identify new markers in peripheral blood that differentiates between PDAC patients and healthy controls.', 'Peripheral blood samples from PDAC patients (n=18) and controls (n=18) were analyzed by whole genome cDNA microarray hybridization. The most relevant genes were validated by quantitative real-time PCR (RT-qPCR) in the same set of samples. Finally, our gene prediction set was tested in a blinded set of new peripheral blood samples (n=30).', 'Microarray studies identified 87 genes differentially expressed in peripheral blood samples from PDAC patients. Four of these genes were selected for analysis by RT-qPCR, which confirmed the previously observed changes. In our blinded validation study, the combination of CLEC4D and IRAK3 predicted the diagnosis of PDAC with 93% accuracy, with a sensitivity of 86% and specificity of 100%.\Question: Does transcriptional profiling of peripheral blood in pancreatic adenocarcinoma patients identify diagnostic biomarkers?
Output: Peripheral blood gene expression profiling is an useful tool for the diagnosis of PDAC. We present a validated four-gene predictor set (ANKRD22, CLEC4D, VNN1, and IRAK3) that may be useful in PDAC diagnosis.