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.

Q: Context: To assess how different imputation methods used to account for missing variance data in primary studies influence tests of heterogeneity and pooled results from a meta-analysis with continuous outcomes.', 'Point and variance estimates for changes in serum creatinine, glomerular filtration rate, systolic blood pressure, and diastolic blood pressure were variably reported among 48 primary longitudinal studies of living kidney donors (71%-78% of point estimates were reported, 8%-13% of variance data were reported). We compared the results of meta-analysis, which either were restricted to available data or used four methods to impute missing variance data. These methods used reported P-values, reported nonparametric summaries, results from other similar studies using multiple imputation, or results from estimated correlation coefficients.', 'Significant heterogeneity was present in all four outcomes regardless of the imputation methods applied. The random effects point estimates and 95% confidence intervals varied little across imputation methods, and the differences were not clinically significant.\Question: Do imputing variance estimates alter the conclusions of a meta-analysis with continuous outcomes : a case study of changes in renal function after living kidney donation?

A: Different methods to impute the variance data in the primary studies did not alter the conclusions from this meta-analysis of continuous outcomes. Such reproducibility increases confidence in the results. However, as with most meta-analyses, there was no gold standard of truth, and results must be interpreted judiciously. The generalization of these findings to other meta-analyses, which differ in outcomes, missing data, or between-study heterogeneity, requires further consideration.
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Q: Context: Women diagnosed with pregnancy-associated breast cancer postpartum have a worse prognosis, stage for stage, than other women with breast cancer. The time of breast involution is tumor promotional. The extracellular matrix protein tenascin-C is upregulated during involution in animal models and promotes breast cancer progression. It interacts with transforming growth factor (TGF)β, which also is involved in breast involution and breast cancer progression. Little is known about the expression of tenascin-C during human breast involution, nor its relationship to TGFβ. The purpose of this study was to investigate the expression of tenascin-C throughout lactation, as well as its relationship to TGFβ1 and TGFβ2.', 'Three milk samples from 25 lactating women (transitional, whole, and wean) were collected, separated into components (cells, fat, and skim), and the skim fraction analyzed for total protein, tenascin-C, TGFβ1, and TGFβ2. Tenascin-C, TGFβ1, and TGFβ2 were detectable in all milk samples.', 'Highest tenascin-C levels on average were found in whole milk, whereas highest mean TGFβ1 and TGFβ2 levels were in wean milk. Wean samples on average had higher levels of both TGFβ1 (26%) and TGFβ2 (>500%) than matched transitional milk samples. Tenascin-C levels in wean milk were associated with nursing length (p = 0.048). Combining all three milk collection time points, tenascin-C exhibited a weak inverse correlation with TGFβ1 and TGFβ2 (p < 0.1). The inverse correlation at the wean time point was stronger for TGFβ2 than -1 (-0.37 versus -0.25). Tenascin-C, a protein known to promote breast cancer progression, is expressed throughout lactation.\Question: Does expression of the Extracellular Matrix Protein Tenascin-C vary During Lactation?

A: The inverse correlation with TGFβ2 in wean milk suggests a possible interaction during breast involution, which should be further investigated.
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Q: Context: Recent studies indicate that a1-adrenergic receptors (a1-ARs) are cardioprotective by preventing cardiac myocyte death and augmenting contractility in heart failure. Although G-protein-coupled receptors are assumed to localize to and signal at the plasma membrane, we previously demonstrated that endogenous a1-ARs localize to the nuclei in adult cardiac myocytes. However, the functional consequence of this nuclear localization remains unclear. Here, we attempted to reconcile nuclear localization of a1-ARs with their physiologic function by examining a1-AR-induced contractility in adult cardiac myocytes.', 'By measuring shortening in unloaded, cultured adult cardiac myocytes, we found that the a1A-subtype regulated contractility through phosphorylation of cardiac troponin I (cTnI) at the protein kinase C (PKC) site, threonine 144. Reconstitution of an a1A-subtype nuclear localization mutant in cardiac myocytes lacking a1-ARs failed to rescue nuclear a1A-mediated phosphorylation of cTnI and myocyte contractility. Leptomycin B, the nuclear export inhibitor, also blocked a1A-mediated phosphorylation of cTnI. These data indicate that a1-AR signaling originates in the nucleus. Consistent with these observations, we localized the a1A-subtype to the inner nuclear membrane, identified PKCa, d, and e in the nucleus, and found that a1-ARs activate PKCd in nuclei isolated from adult cardiac myocytes. Finally, we found that a PKCd nuclear localization mutant blunted a1-induced phosphorylation of cTnI.\Question: Is nuclear localization of a1A-adrenergic receptors required for signaling in cardiac myocytes : an “ inside-out ” a1-AR signaling pathway?

A:
Together, our data identify a novel, “inside-out” nuclear a1A-subtype/PKCd/cTnI-signaling pathway that regulates contractile function in adult cardiac myocytes. Importantly, these data help resolve the discrepancy between nuclear localization of a1-ARs and a1-AR-mediated physiologic function.
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