Project description:This article reports the proteomic legacy of in vivo exposure to the xenobiotic, acrylamide, on the epithelial cell population of the proximal segments of the mouse epididymis. Specifically, adult male mice were administered acrylamide (25 mg/kg bw/day) or vehicle control for five consecutive days before dissection of the epididymis. Epididymal epithelial cells were isolated from the proximal (caput) epididymal segment and subjected to quantitative proteomic analysis using multiplexed tandem mass tag (TMT) labeling coupled to mass spectrometry. Here, we report the data generated by this strategy, including the identification of 4405 caput epididymal epithelial cell proteins, approximately 6.8% of which displayed altered expression in response to acrylamide challenge. Our interpretation and discussion of these data features in the article "Acrylamide modulates the mouse epididymal proteome to drive alterations in the sperm small non-coding RNA profile and dysregulate embryo development".
Project description:We have performed whole transcriptome sequencing of 5-FU resistant and 5-FU sensitive tumors generated in a mouse model of de novo carcinogenesis that closely recapitulates tumor initiation, progression and maintenance in vivo. Tumors were generated using the DMBA/TPA model of chemically induced carcinogenesis [1], tumor-bearing mice were subsequently treated with 5-FU, and tumor growth as well as response to treatment was monitored by measuring tumor volume twice a week. Based on these measurements, we selected two 5-FU resistant and two 5-FU sensitive tumors and performed whole transcriptome sequencing and in order to identify differentially expressed transcripts between the two sets. Data obtained is deposited and available through NCBI SRA (reference number SRP155180 - https://www.ncbi.nlm.nih.gov/sra/?term=SRP155180).
Project description:In this article we report the complete data obtained in-vivo for the paper: "Lines of Baillarger in vivo and ex-vivo: myelin contrast across lamina at 7T MRI and histology" (Fracasso et al., 2015) [1]. Single participant data (4 participants) from the occipital lobe acquisition are reported for axial, coronal and sagittal slices; early visual area functional localization and laminar profiles are reported. Data from whole brain images are reported and described (5 participants), for axial, coronal and sagittal slices. Laminar profiles from occipital, parietal and frontal lobes are reported. The data reported in this manuscript complements the paper (Fracasso et al., 2015) [1] by providing the full set of results from the complete pool of participants, on a single-participant basis. Moreover, we provide histological images from the ex-vivo sample reported in Fracasso et al. (2015) [1].
Project description:We introduce HumanBrainAtlas, an initiative to construct a highly detailed, open-access atlas of the living human brain that combines high-resolution in vivo MR imaging and detailed segmentations previously possible only in histological preparations. Here, we present and evaluate the first step of this initiative: a comprehensive dataset of two healthy male volunteers reconstructed to a 0.25 mm isotropic resolution for T1w, T2w, and DWI contrasts. Multiple high-resolution acquisitions were collected for each contrast and each participant, followed by averaging using symmetric group-wise normalisation (Advanced Normalisation Tools). The resulting image quality permits structural parcellations rivalling histology-based atlases, while maintaining the advantages of in vivo MRI. For example, components of the thalamus, hypothalamus, and hippocampus are often impossible to identify using standard MRI protocols-can be identified within the present data. Our data are virtually distortion free, fully 3D, and compatible with the existing in vivo Neuroimaging analysis tools. The dataset is suitable for teaching and is publicly available via our website (hba.neura.edu.au), which also provides data processing scripts. Instead of focusing on coordinates in an averaged brain space, our approach focuses on providing an example segmentation at great detail in the high-quality individual brain. This serves as an illustration on what features contrasts and relations can be used to interpret MRI datasets, in research, clinical, and education settings.
Project description:Adipose tissue is crucial for energy storage and release, ensuring energy homeostasis within the body. Disturbances in the physiology of adipose tissue have been associated with various health disorders, such as obesity and diabetes. The reproductive cycle represents a fundamental biological pattern in female physiology. Although previous research has highlighted the substantial regulatory influence of ovarian hormones on adipose tissue, our understanding of the comprehensive changes in adipose tissue throughout the reproductive cycle remains limited. In this study, we examined the transcriptomic profile of female mouse-adipose tissue across their complete estrous cycles. The findings provided detailed descriptions of the datasets generated, including information on data collection, processing, and quality control. The study also demonstrated the robustness of these data through various validation steps. These findings serve as crucial resources for investigating the role of estrous cycle rhythmicity in important adipose tissue processes in the future.
Project description:ChEMBL is a large-scale, open-access drug discovery resource containing bioactivity information primarily extracted from scientific literature. A substantial dataset of more than 135,000 in vivo assays has been collated as a key resource of animal models for translational medicine within drug discovery. To improve the utility of the in vivo data, an extensive data curation task has been undertaken that allows the assays to be grouped by animal disease model or phenotypic endpoint. The dataset contains previously unavailable information about compounds or drugs tested in animal models and, in conjunction with assay data on protein targets or cell- or tissue- based systems, allows the investigation of the effects of compounds at differing levels of biological complexity. Equally, it enables researchers to identify compounds that have been investigated for a group of disease-, pharmacology- or toxicity-relevant assays.