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End date: 2019 × Start date: 2013 × Item Type: Publication × Type: Dataset ×

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Neurobehavioral data for novel behavioral indicator of explicit awareness dataset

2017-03-26 , Wheaton, Lewis A. , Lawson, Regan R. , Gayle, Jordan O.

Deficits in sequential motor learning have been observed in many patient populations. Having an understanding of the individual neural progression associated with sequential learning in healthy individuals may provide valuable insights for effective interventions with these patients. Due to individual variability in motor skill acquisition, the temporal course of such learning will be vary, suggesting a need for a more individualized approach. Knowing when a subject becomes aware of movement patterns may provide a marker with which to identify each individual's learning time course. To avoid interfering with the incidental nature of discovery during learning, such an indicator requires an indirect, behaviorally-based approach. In Part I, our study aimed to identify a reliable behavioral indicator predictive of the presence of incidental explicit awareness in a sequential motor learning task. Part II, utilized the predictive indicator and EEG to provide neural validation of perceptual processing changes temporally correlated with the indicator. Results of Part I provide a reliable predictive indicator for the timing of explicit awareness development. Results from Part II demonstrates strong classification reliability, as well as a significant neural correlation with behavior for subjects developing awareness (EXP), not observed with subjects without awareness (NOEXP). Additionally, a temporal correlation of peak activation between neural regions was noted over frontoparietal regions, suggesting that the incidental discovery of motor patterns may involve a facilitative network during awareness development. The proposed indicator provides a tool in which to further examine potential impacts of awareness associated with incidental, or exploratory, motor learning, while the individual nature of the indicator provides a tool for monitoring progress in rehabilitative, exploratory motor learning paradigms.

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Peer J Consumption Data

2015-07-22 , Weissburg, Marc J. , Beauvais, Jeffrey

The data file contains the results of predation experiments on oyster spat by mud crabs in the presence of chemical cues produced by blue crabs fed differing amounts of mud crabs and placed different distances away. The treatment variables and levels consist of: Distance (0.25m, 0.5m, 1m, 1.5m, or 2m); Diet (High [H], Low [L], or Control [C]); and, Time (24, 48 hours). Date of experiment also is included. The measurement variables consist of Total Number Eaten, and Proportion Eaten Outside Refuge.

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Karenia brevis allelopathy compromises the lipidome, membrane integrity, and photosynthesis of competitors (dataset)

2015-12-17 , Poulin, R. X. , Kubanek, Julia

The attached data files underlie the forthcoming publication, "Karenia brevis allelopathy compromises the lipidome, membrane integrity, and photosynthesis of competitors".

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Computational analyses of gene expression profiles of ovarian and pancreatic cancer

2013-07-16 , Lili, Loukia

Cancer is a devastating disease for human society with thousands of deaths and estimated new cases every year around the globe. Intensive research efforts on understanding the disease progression and determining effective diagnostics and therapeutics have been employed for over one hundred years. Throughout this time, and in particular during the last two decades, computational-based methods have gained increasing importance in cancer biology research by providing significant advantages in the analysis and interpretation of high-throughput data at the molecular and genomic levels. More specifically, after completion of the Human Genome Project in 2003, and with the Cancer Human Genome Project underway, high-throughput biological assays (e.g., microarray chips, next generation sequencing machines) have supplied researchers thousands of measurements per experimental sample. The massive amount of related data has oftentimes been challenging to interpret and translate, particularly in cancer biology and therapeutics. This thesis reports the results of three independent studies in which high-throughput gene expression is computationally analyzed to address longstanding issues in cancer biology. Two of the studies utilize data from ovarian cancer patients while the third involves data collected from pancreatic cancer patients. In Chapter 1, I address the importance of personalized profiling in pancreatic cancer ; in Chapter 2 the role of cancer stroma in the progression of ovarian cancer and in Chapter 3 evidence for the role of epithelial-to-mesenchymal transition (EMT) in ovarian cancer metastasis. More specifically, Chapter 1 emphasizes the power of personalized molecular profiling in unmasking unique gene expression signatures that correspond to each individual patient. These individual expression patterns (individual profiling), which may be overlooked by the traditional methods of gene signatures enriched in groups of afflicted individuals (group profiling), can provide valuable information for more successful targeted therapies. In order to address this issue in pancreatic cancer, comparisons of the most significantly differentially expressed genes and functional pathways were performed between cancer and control patient samples as determined by group vs. personalized analyses. There was little to no overlap between genes/pathways identified by group analyses relative to those identified by personalized analyses. These results indicated that personalized and not group molecular profiling is the most appropriate approach for the identification of putative candidates for targeted gene therapy of pancreatic and perhaps other cancers with heterogeneous molecular etiology. Chapter 2, also with strong implications on personalized molecular profiling, unveils the functional variability of the tumor microenvironment among ovarian cancer patients. The purpose of this study was to investigate the process of microenvironmental stroma activation in human ovarian cancer by molecular analysis of matched sets of cancer and surrounding stroma tissues from individual patients. Expression patterns of genes encoding signaling molecules and compatible receptors in the cancer stroma and cancer epithelia samples indicated the existence of two sub-groups of cancer stroma with different propensities to support tumor growth. These results demonstrated that functionally significant variability exists among ovarian cancer patients in the ability of the microenvironment to modulate cancer development. Chapter 3 aims to uncover the molecular mechanisms that underlie the metastatic process with the hope that such knowledge may lead to more effective therapeutic treatments. For this purpose, pathological and molecular analyses were conducted in 14 matched sets of primary and metastatic samples from late staged ovarian cancer patients. Pathological examination revealed no morphological differences between any of the primary and metastatic samples. In contrast, gene expression analyses identified two distinct groups of patient samples. One group displayed essentially identical expression patterns to primary samples isolated from the same patients. The second group displayed expression patterns significantly different from primary samples isolated from the same patients. Predominant among the differentially expressed genes characterizing this second class of metastatic samples were genes previously associated with epithelial-to-mesenchymal transtion (EMT). These results supported a role of EMT in at least some ovarian cancer metastases and demonstrated that indistinguishable morphologies between primary and metastatic cancer samples is not sufficient evidence to negate the role of EMT in the metastatic process.

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You are what you eat: A combined metabolomics – bioassay approach to understanding prey responses to chemical cues produced by predators fed different diets dataset

2015-09-09 , Weissburg, Marc J. , Poulin, R.X. , Kubanek, Julia

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