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Tyler C Hein Leigh G Goetschius Vonnie C McLoyd Jeanne Brooks-Gunn Sara S McLanahan Colter Mitchell Nestor L Lopez-Duran Luke W Hyde Christopher S Monk 《Social cognitive and affective neuroscience》2020,15(11):1252
BackgroundChildhood adversity is, unfortunately, highly prevalent and strongly associated with later psychopathology. Recent theories posit that two dimensions of early adversity, threat and deprivation, have distinct effects on brain development. The current study evaluated whether violence exposure (threat) and social deprivation (deprivation) were associated with adolescent amygdala and ventral striatum activation, respectively, in a prospective, well-sampled, longitudinal cohort using a pre-registered, open science approach.MethodsOne hundred and sixty-seven adolescents from the Fragile Families and Child Wellbeing Study completed functional magnetic resonance imaging (fMRI) scanning. Prospective longitudinal data from ages 3, 5 and 9 years were used to create indices of childhood violence exposure and social deprivation. We evaluated whether these dimensions were associated with adolescent brain function in response to threatening and rewarding faces.ResultsChildhood violence exposure was associated with decreased amygdala habituation (i.e. more sustained activation) and activation to angry faces in adolescence, whereas childhood social deprivation was associated with decreased ventral striatum activation to happy faces in adolescence. These associations held when adjusting for the other dimension of adversity (e.g., adjusting for social deprivation when examining associations with violence exposure), the interaction of the two dimensions of adversity, gender, internalizing psychopathology, and current life stress.ConclusionsConsistent with recent theories, different forms of early adversity were associated with region-specific differences in brain activation. 相似文献
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Multivariate survival data are frequently encountered in biomedical applications in the form of clustered failures (or recurrent events data). A popular way of analyzing such data is by using shared frailty models, which assume that the proportional hazards assumption holds conditional on an unobserved cluster-specific random effect. Such models are often incorporated in more complicated joint models in survival analysis. If the random effect distribution has finite expectation, then the conditional proportional hazards assumption does not carry over to the marginal models. It has been shown that, for univariate data, this makes it impossible to distinguish between the presence of unobserved heterogeneity (eg, due to missing covariates) and marginal nonproportional hazards. We show that time-dependent covariate effects may falsely appear as evidence in favor of a frailty model also in the case of clustered failures or recurrent events data, when the cluster size or number of recurrent events is small. When true unobserved heterogeneity is present, the presence of nonproportional hazards leads to overestimating the frailty effect. We show that this phenomenon is somewhat mitigated as the cluster size grows. We carry out a simulation study to assess the behavior of test statistics and estimators for frailty models in such contexts. The gamma, inverse Gaussian, and positive stable shared frailty models are contrasted using a novel software implementation for estimating semiparametric shared frailty models. Two main questions are addressed in the contexts of clustered failures and recurrent events: whether covariates with a time-dependent effect may appear as indication of unobserved heterogeneity and whether the additional presence of unobserved heterogeneity can be detected in this case. Finally, the practical implications are illustrated in a real-world data analysis example. 相似文献
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Can EGFR mutation status be reliably determined in pre‐operative needle biopsies from adenocarcinomas of the lung? 下载免费PDF全文
Kim Hein Lindahl Flemming Brandt Sørensen Søren Peter Jonstrup Karen Ege Olsen Siegfried Loeschke 《APMIS : acta pathologica, microbiologica, et immunologica Scandinavica》2015,123(4):289-297
The identification of EGFR mutations in non‐small‐cell lung cancer is important for selecting patients, who may benefit from treatment with EGFR tyrosine kinase inhibitors. The analysis is usually performed on cytological aspirates and/or histological needle biopsies, representing a small fraction of the tumour volume. The aim of the present investigation was to evaluate the diagnostic performance of this molecular test. We retrospectively included 201 patients with primary adenocarcinoma of the lung. EGFR mutation status (exon 19 deletions and exon 21 L858R point mutation) was evaluated on both pre‐operative biopsies (131 histological and 70 cytological) and on the surgical specimens, using PCR. Samples with low tumour cell fraction were assigned to laser micro‐dissection (LMD). We found nine (4.5%) patients with EGFR mutation in the lung tumour resections, but failed to identify mutation in one of the corresponding pre‐operative, cytological specimens. Several (18.4%) analyses of the pre‐operative biopsies were inconclusive, especially in case of biopsies undergoing LMD and regarding exon 21 analysis. Discrepancy of mutation status in one patient may reflect intra‐tumoural heterogeneity or technical issues. Moreover, several inconclusive results in the diagnostic biopsies reveal that attention must be paid on the suitability of pre‐operative biopsies for EGFR mutation analysis. 相似文献
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David Ross Tristan Maerz Michael Kurdziel Joel Hein Shashin Doshi Asheesh Bedi Kyle Anderson Kevin Baker 《Clinical orthopaedics and related research》2015,473(5):1655-1664