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8,942 results for “Prostate”
The mRNA profile from rats ventral prostate submitted to maternal low protein diet
GEO Series GSE180673. Rattus norvegicus. 16 samples. Type: Expression profiling by high throughput sequencing.
Transcriptome regulated by mitochondrial uncouplers in prostate cancer cells
GEO Series GSE276044. Homo sapiens. 6 samples. Type: Expression profiling by high throughput sequencing.
Patients diagnosed with prostate cancer between 2010 and 2015 from the SEER
<p>Clinicopathological information on patients diagnosed with prostate cancer between 2010 and 2015 from the SEER</p>
Investigating Chemotherapeutic Applications of Cannabinoid Compounds in Prostate Cancer.
<p>This folder holds data regarding the research project "Investigating Chemotherapeutic Applications of Cannabinoid Compounds in Prostate Cancer" carried out by Amy Kinsella and supervised by Dr. Antoinette Perry.</p> <p>These files containing the results of effect of the cannabinoid GL4a on cell viability and apoptosis in the prostate cancer cell lines PC3 and DU145. These results were obtained via MTT assay and flow cytometry.</p> <p>The files containing the flow graphs do not have the labels altered and subsequently the labeling of the apoptosis graphs is incorrect. Apoptosis graphs with corrected labeling can be seen the the flow results.</p>
Data from: Quantifying post- laser ablation prostate therapy changes on MRI via a domain-specific biomechanical model: preliminary findings
Focal laser ablation destroys cancerous cells via thermal destruction of tissue by a laser. Heat is absorbed, causing thermal necrosis of the target region. It combines the aggressive benefits of radiation treatment (destroying cancer cells) without the harmful side effects (due to its precise localization). MRI is typically used pre-treatment to determine the targeted area, and post-treatment to determine efficacy by detecting necrotic tissue, or tumor recurrence. However, no system exists to quantitatively evaluate the post-treatment effects on the morphology and structure via MRI. To quantify these changes, the pre- and post-treatment MR images must first be spatially aligned. The goal is to quantify (a) laser-induced shape-based changes, and (b) changes in MRI parameters post-treatment. The shape-based changes may be correlated with treatment efficacy, and the quantitative effects of laser treatment over time is currently poorly understood. This work attempts to model changes in gland morphology following laser treatment due to (1) patient alignment, (2) changes due to surrounding organs such as the bladder and rectum, and (3) changes due to the treatment itself. To isolate the treatment-induced shape-based changes, the changes from (1) and (2) are first modeled and removed using a finite element model (FEM). A FEM models the physical properties of tissue. The use of a physical biomechanical model is important since a stated goal of this work is to determine the physical shape-based changes to the prostate from the treatment, and therefore only physical real deformations are to be allowed. A second FEM is then used to isolate the physical, shape-based, treatment-induced changes. We applied and evaluated our model in capturing the laser induced changes to the prostate morphology on eight patients with 3.0 Tesla, T2-weighted MRI, acquired approximately six months following treatment. Our results suggest the laser treatment causes a decrease in prostate volume, which appears to manifest predominantly at the site of ablation. After spatially aligning the images, changes to MRI intensity values are clearly visible at the site of ablation. Our results suggest that our new methodology is able to capture and quantify the degree of laser-induced changes to the prostate. The quantitative measurements reflecting of the deformation changes can be used to track treatment response over time.
Validation and implementation of a mobile app decision support system for quality assurance of tumor boards. Analyzing the concordance rates for prostate cancer from a multidisciplinary tumor board of a University Cancer Center
<p>The data set contains anonymized clinicopathologic data of patients with prostate cancer. The data was used to determine concordance rates between recommendations proposed by the digital decision support system EasyOncology and actual treatment recommendations given by a tumor board. </p>
CTC identification and characterization in prostate cancer using K/V protocol and imaging flow cytometry - part 1
<p>This project aimed to identify and characterize circulating tumor cells (CTCs) in peripheral blood of 33 prostate cancer patients. Fraction of peripheral blood mononuclear cells putatively containing CTCs was isolated using density gradient centrifugation. Pan-keratin/vimentin/CD45/CD31/DAPI immunofluorescent staining was performer and DAPI+ or DAPI+CD45/CD31- objects were collected using Amnis® ImageStream®XMk II, Cytek® Biosciences, Inc (lasers: 405 nm, 488 nm, 642 nm, magnification 40x, slow speed flow).</p>
CTC identification and characterization in prostate cancer using K/V protocol and imaging flow cytometry - part 3
<p>This project aimed to identify and characterize circulating tumor cells (CTCs) in peripheral blood of 33 prostate cancer patients. Fraction of peripheral blood mononuclear cells putatively containing CTCs was isolated using density gradient centrifugation. Pan-keratin/vimentin/CD45/CD31/DAPI immunofluorescent staining was performer and DAPI+ or DAPI+CD45/CD31- objects were collected using Amnis® ImageStream®XMk II, Cytek® Biosciences, Inc (lasers: 405 nm, 488 nm, 642 nm, magnification 40x, slow speed flow).</p>
CTC identification and characterization in prostate cancer using K/V protocol and imaging flow cytometry - part 12
<p>This project aimed to identify and characterize circulating tumor cells (CTCs) in peripheral blood of 33 prostate cancer patients. Fraction of peripheral blood mononuclear cells putatively containing CTCs was isolated using density gradient centrifugation. Pan-keratin/vimentin/CD45/CD31/DAPI immunofluorescent staining was performer and DAPI+ or DAPI+CD45/CD31- objects were collected using Amnis® ImageStream®XMk II, Cytek® Biosciences, Inc (lasers: 405 nm, 488 nm, 642 nm, magnification 40x, slow speed flow).</p>
CTC identification and characterization in prostate cancer using K/V protocol and imaging flow cytometry - part 8
<p>This project aimed to identify and characterize circulating tumor cells (CTCs) in peripheral blood of 33 prostate cancer patients. Fraction of peripheral blood mononuclear cells putatively containing CTCs was isolated using density gradient centrifugation. Pan-keratin/vimentin/CD45/CD31/DAPI immunofluorescent staining was performer and DAPI+ or DAPI+CD45/CD31- objects were collected using Amnis® ImageStream®XMk II, Cytek® Biosciences, Inc (lasers: 405 nm, 488 nm, 642 nm, magnification 40x, slow speed flow).</p>
CTC identification and characterization in prostate cancer using K/V protocol and imaging flow cytometry - part 5
<p>This project aimed to identify and characterize circulating tumor cells (CTCs) in peripheral blood of 33 prostate cancer patients. Fraction of peripheral blood mononuclear cells putatively containing CTCs was isolated using density gradient centrifugation. Pan-keratin/vimentin/CD45/CD31/DAPI immunofluorescent staining was performer and DAPI+ or DAPI+CD45/CD31- objects were collected using Amnis® ImageStream®XMk II, Cytek® Biosciences, Inc (lasers: 405 nm, 488 nm, 642 nm, magnification 40x, slow speed flow).</p>
CTC identification and characterization in prostate cancer using K/V protocol and imaging flow cytometry - part 11
<p>This project aimed to identify and characterize circulating tumor cells (CTCs) in peripheral blood of 33 prostate cancer patients. Fraction of peripheral blood mononuclear cells putatively containing CTCs was isolated using density gradient centrifugation. Pan-keratin/vimentin/CD45/CD31/DAPI immunofluorescent staining was performer and DAPI+ or DAPI+CD45/CD31- objects were collected using Amnis® ImageStream®XMk II, Cytek® Biosciences, Inc (lasers: 405 nm, 488 nm, 642 nm, magnification 40x, slow speed flow).</p>
CTC identification and characterization in prostate cancer using K/V protocol and imaging flow cytometry - part 10
<p>This project aimed to identify and characterize circulating tumor cells (CTCs) in peripheral blood of 33 prostate cancer patients. Fraction of peripheral blood mononuclear cells putatively containing CTCs was isolated using density gradient centrifugation. Pan-keratin/vimentin/CD45/CD31/DAPI immunofluorescent staining was performer and DAPI+ or DAPI+CD45/CD31- objects were collected using Amnis® ImageStream®XMk II, Cytek® Biosciences, Inc (lasers: 405 nm, 488 nm, 642 nm, magnification 40x, slow speed flow).</p>
CTC identification and characterization in prostate cancer using K/V protocol and imaging flow cytometry - part 9
<p>This project aimed to identify and characterize circulating tumor cells (CTCs) in peripheral blood of 33 prostate cancer patients. Fraction of peripheral blood mononuclear cells putatively containing CTCs was isolated using density gradient centrifugation. Pan-keratin/vimentin/CD45/CD31/DAPI immunofluorescent staining was performer and DAPI+ or DAPI+CD45/CD31- objects were collected using Amnis® ImageStream®XMk II, Cytek® Biosciences, Inc (lasers: 405 nm, 488 nm, 642 nm, magnification 40x, slow speed flow).</p>
CTC identification and characterization in prostate cancer using K/V protocol and imaging flow cytometry - part 6
<p>This project aimed to identify and characterize circulating tumor cells (CTCs) in peripheral blood of 33 prostate cancer patients. Fraction of peripheral blood mononuclear cells putatively containing CTCs was isolated using density gradient centrifugation. Pan-keratin/vimentin/CD45/CD31/DAPI immunofluorescent staining was performer and DAPI+ or DAPI+CD45/CD31- objects were collected using Amnis® ImageStream®XMk II, Cytek® Biosciences, Inc (lasers: 405 nm, 488 nm, 642 nm, magnification 40x, slow speed flow).</p>
CTC identification and characterization in prostate cancer using K/V protocol and imaging flow cytometry - part 4
<p>This project aimed to identify and characterize circulating tumor cells (CTCs) in peripheral blood of 33 prostate cancer patients. Fraction of peripheral blood mononuclear cells putatively containing CTCs was isolated using density gradient centrifugation. Pan-keratin/vimentin/CD45/CD31/DAPI immunofluorescent staining was performer and DAPI+ or DAPI+CD45/CD31- objects were collected using Amnis® ImageStream®XMk II, Cytek® Biosciences, Inc (lasers: 405 nm, 488 nm, 642 nm, magnification 40x, slow speed flow).</p>
CTC identification and characterization in prostate cancer using K/V protocol and imaging flow cytometry - part 7
<p>This project aimed to identify and characterize circulating tumor cells (CTCs) in peripheral blood of 33 prostate cancer patients. Fraction of peripheral blood mononuclear cells putatively containing CTCs was isolated using density gradient centrifugation. Pan-keratin/vimentin/CD45/CD31/DAPI immunofluorescent staining was performer and DAPI+ or DAPI+CD45/CD31- objects were collected using Amnis® ImageStream®XMk II, Cytek® Biosciences, Inc (lasers: 405 nm, 488 nm, 642 nm, magnification 40x, slow speed flow).</p>
Dataset for: Radiation therapy induces innate immune responses in patients treated for prostate cancers
<p><strong>Purpose </strong></p> <p>Radiation therapy (RT) is a curative therapeutic modality used to treat cancers as a single agent or in combination with surgery and chemotherapy. Advanced RT technologies enable treatment with large fraction, highly conformal, radiation doses to effect free-radical damage to cellular DNA leading to cell cycle arrest, cell death, and innate immune response stimulation.</p> <p><strong>Experimental Design </strong></p> <p>To understand systemic clinical responses after radiation exposure, high throughput proteomic and metabolomic analyses were performed on plasma obtained from cancer patients at intervals after prostate stereotactic body radiation therapy. Pathway analysis and multivariate analyses were used to delineate molecular alterations following radiation therapy and its correlation with clinical outcomes.</p> <p><strong>Results</strong></p> <p>DNA Damage Response (DDR) and cell cycle signaling increased within the first hour after treatment and returned to baseline by one month. Innate immune response signaling also increased within one hour of treatment but persisted for up to three months thereafter. Furthermore, robust immune responses and metabolite elevations, consistent with an early proinflammatory M1-mediated innate immune activation, were observed in patients in remission, whereas patients experiencing PSA-determined disease progression demonstrated less robust immune responses and M2-mediated metabolite elevations.</p> <p><strong>Conclusion/Discussion</strong></p> <p>To our knowledge, these data are the first report of longitudinal proteomic and metabolomic molecular responses in patients after radiation therapy for cancers. The data supports innate immune activation as a critical clinical response of patients receiving radiation therapy for prostate cancer. Furthermore, we propose that the observed innate immune responses may be generalized to the treatment of other cancer types, potentially informing multidisciplinary therapeutic strategies for cancer treatment.</p>
Prostate MRI clinically significant cancer
<p>This data set is part of the public development data for the <a href="http://auc23.grand-challenge.org/">2023 Automated Universal Classification Challenge</a> (AUC23). The data set concerns clinically significant prostate cancer classification on bi-parametric magnetic resonance imaging (bpMRI) and was derived from the <a href="https://pi-cai.grand-challenge.org/">Prostate Imaging: Cancer AI (PI-CAI)</a> challenge's <a href="https://zenodo.org/record/6624726#.ZGI4GXZBzIU">public training and development dataset</a> (v2.0). The data set was originally introduced and described by <a href="https://zenodo.org/record/6522364">Saha et al. (2022)</a>, and no images or patient information were added. Data was restructured in compliance with the <a href="https://auc23.grand-challenge.org/">AUC23</a> challenge format. The data set contains 1500 anonymized prostate bpMRI scans from 1476 patients acquired between 2012-2021 at three centers (Radboud University Medical Center, University Medical Center Groningen, Ziekenhuis Groep Twente) based in The Netherlands.</p> <p>Images are 4D tensors:</p> <ul> <li>0: 3D Axial T2-weighted imaging (T2W)</li> <li>1: 3D Axial apparent diffusion coefficient maps (ADC)</li> <li>2: 3D Axial high b-value (≥ 1000 s/mm2) diffusion-weighted imaging (HBV)</li> </ul> <p>Classification labels:</p> <ul> <li>0: Benign or indolent prostate cancer</li> <li>1: Clinically significant prostate cancer (csPCa)</li> </ul> <p>Folder structure:</p> <p>imagesTr (root folder with all patients and studies)<br> ├── 10417_1000424_0000.mha (axial T2W imaging for study 1000424)<br> ├── 10417_1000424_0001.mha (axial ADC imaging for study 1000424)<br> ├── 10417_1000424_0002.mha (axial HBV imaging for study 1000424)<br> ├── ...<br> ├── 11251_1001274_0000.mha (axial T2W imaging for study 1001274)<br> ├── 11251_1001274_0001.mha (axial ADC imaging for study 1001274)<br> ├── 11251_1001274_0002.mha (axial HBV imaging for study 1001274)<br> ├── ...</p> <p> </p> <p>Please cite the following article if you are using the <a href="https://zenodo.org/record/6522364">PI-CAI: Public Training and Development Dataset</a>:</p> <pre><code>A. Saha, J. J. Twilt, J. S. Bosma, B. van Ginneken, D. Yakar, M. Elschot, J. Veltman, J. J. Fütterer, M. de Rooij, H. Huisman, "Artificial Intelligence and Radiologists at Prostate Cancer Detection in MRI: The PI-CAI Challenge (Study Protocol)", DOI: 10.5281/zenodo.6522364 </code></pre> <p> </p>
CTC identification and characterization in prostate cancer using K/V protocol and imaging flow cytometry - part 2
<p>This project aimed to identify and characterize circulating tumor cells (CTCs) in peripheral blood of 33 prostate cancer patients. Fraction of peripheral blood mononuclear cells putatively containing CTCs was isolated using density gradient centrifugation. Pan-keratin/vimentin/CD45/CD31/DAPI immunofluorescent staining was performer and DAPI+ or DAPI+CD45/CD31- objects were collected using Amnis® ImageStream®XMk II, Cytek® Biosciences, Inc (lasers: 405 nm, 488 nm, 642 nm, magnification 40x, slow speed flow).</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.