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Erturk, A.

Publications and source records attributed to Erturk, A..

21 records · Page 2Linked to original sources

Automated analysis of whole brain vasculature using machine learning

Tissue clearing methods enable imaging of intact biological specimens without sectioning. However, reliable and scalable analysis of such large imaging data in 3D remains a challenge. Towards this goal, we developed a deep learning-based framework to quantify and analyze the brain vasculature, named Vessel Segmentation & Analysis Pipeline (VesSAP). Our pipeline uses a fully convolutional network with a transfer learning approach for segmentation. We systematically analyzed vascular features of the whole brains including their length, bifurcation points and radius at the micrometer scale by registering them to the Allen mouse brain atlas. We reported the first evidence of secondary intracranial collateral vascularization in CD1-Elite mice and found reduced vascularization in the brainstem as compared to the cerebrum. VesSAP thus enables unbiased and scalable quantifications for the angioarchitecture of the cleared intact mouse brain and yields new biological insights related to the vascular brain function.\n\nGRAPHICAL ABSTRACT\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=135 SRC=\"FIGDIR/small/613257_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (51K):\norg.highwire.dtl.DTLVardef@8c79eborg.highwire.dtl.DTLVardef@984d3aorg.highwire.dtl.DTLVardef@f62d9borg.highwire.dtl.DTLVardef@2c20bc_HPS_FORMAT_FIGEXP M_FIG Supporting material of VesSAP is available at http://DISCOtechnologies.org/VesSAP\n\nC_FIG

neuroscience↗

Deep learning reveals cancer metastasis and therapeutic antibody targeting in whole body

Reliable detection of disseminated tumor cells and of the biodistribution of tumor-targeting therapeutic antibodies within the entire body has long been needed to better understand and treat cancer metastasis. Here, we developed an integrated pipeline for automated quantification of cancer metastases and therapeutic antibody targeting, named DeepMACT. First, we enhanced the fluorescent signal of tumor cells more than 100-fold by applying the vDISCO method to image single cancer cells in intact transparent mice. Second, we developed deep learning algorithms for automated quantification of metastases with an accuracy matching human expert manual annotation. Deep learning-based quantifications in a model of spontaneous metastasis using human breast cancer cells allowed us to systematically analyze clinically relevant features such as size, shape, spatial distribution, and the degree to which metastases are targeted by a therapeutic monoclonal antibody in whole mice. DeepMACT can thus considerably improve the discovery of effective therapeutic strategies for metastatic cancer. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=137 SRC="FIGDIR/small/541862v1_ufig1.gif" ALT="Figure 1"> View larger version (49K): org.highwire.dtl.DTLVardef@ffe1b9org.highwire.dtl.DTLVardef@13c55eborg.highwire.dtl.DTLVardef@2ccb6corg.highwire.dtl.DTLVardef@df55e9_HPS_FORMAT_FIGEXP M_FIG C_FIG Supplementary Movies and deep learning algorithms of DeepMACT are available at http://discotechnologies.org/DeepMACT/

cancer biology↗

Panoptic vDISCO imaging reveals neuronal connectivity, remote trauma effects and meningeal vessels in intact transparent mice

Analysis of entire transparent rodent bodies could provide holistic information on biological systems in health and disease. However, it has been challenging to reliably image and quantify signal from endogenously expressed fluorescent proteins in large cleared mouse bodies due to the low signal contrast. Here, we devised a pressure driven, nanobody based whole-body immunolabeling technology to enhance the signal of fluorescent proteins by up to two orders of magnitude. This allowed us to image subcellular details in transparent mouse bodies through bones and highly autofluorescent tissues, and perform quantifications. We visualized for the first-time whole-body neuronal connectivity of an entire adult mouse and discovered that brain trauma induces degeneration of peripheral axons. We also imaged meningeal lymphatic vessels and immune cells through the intact skull and vertebra in naive animals and trauma models. Thus, our new approach can provide an unbiased holistic view of biological events affecting the nervous system and the rest of the body.\n\n\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=151 SRC=\"FIGDIR/small/374785_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (62K):\norg.highwire.dtl.DTLVardef@8fad72org.highwire.dtl.DTLVardef@c41ed5org.highwire.dtl.DTLVardef@1c470eaorg.highwire.dtl.DTLVardef@1d144cb_HPS_FORMAT_FIGEXP M_FIG C_FIG Note: Manuscript videos are available at Supplementary material section of BioRxiv and at the following link http://vdisco.isd-muc.de/

neuroscience↗