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The Translucence Teravoxel Toolkit (3TK) offers unrivaled speed and flexibility, allowing the rapid generation of custom assays.
AI-Powered 3D Quantification is the final step of our modular custom service offerings, delivering precise and robust 3D insights into the epitope of interest. If you can label it, we can quantify it.
3D histological data offers significant potential but has proven challenging to quantify for much of the scientific community.
Large terabyte-scale data sets produced by tissue clearing and light sheet imaging require extensive computational resources.
And while there are a few open source solutions for this type of quantification, their implementation often requires extensive coding experience not available to the average academic lab.
The Translucence Teravoxel Toolkit (3TK) offers unrivaled speed and flexibility, allowing the rapid generation of custom assays. Integrated AI-powered classifiers allow us to generate assays with unprecedented noise reduction and the ability to separate cell types within the same fluorescence channel. 3TK software scans, detects, segments, and quantifies objects of interest across whole 3D samples, providing comprehensive insights into the epitope of interest.
Quantification of terabyte-scale datasets is enabled by cloud and cluster computing, as well as advanced memory handling and analysis routines built from the ground up which allow for scaling and rapid processing.
For brain samples, samples are warped to the Allen reference atlas.
Translucence Biosystems specializes in quantifying a wide range of epitopes and can collaborate to create custom assays for your specific epitope of interest. If you can label it, we can quantify it.
Segmented objects can be quantified in a multitude of ways. Several metrics we can extract from segmented objects include: signal intensity, density, size, and shape.
Simply send us your stitched tiff stacks and we will send back actionable data.
Browse actionable insights generated by the
AI-Powered 3D Quantification
service
Browse actionable insights generated by our AI-Powered 3D Quantification services
The top images are a single z-plane through an intact 3D experimentally-treated brain. Iba1 immunoreactivity is shown on the left, and the corresponding cell labels from an AI-powered workflow in our 3TK software are on the right. Zoomed images show cellular morphology masks. Small seeming labels can be portions of microglia that project orthogonal to the 2D slice shown. Cell masks allow for counts, shape analysis, and fluorescence intensity measurements.
Single z-planes through a 5xFAD mouse brain demonstrate the brain-wide pattern of β-amyloid aggregates. On the left is immunoreactivity measured with an anti-β-amyloid antibody. On the right, an AI-powered workflow in our 3TK software identifies and labels plaques throughout the brain.
We trained machine learning algorithms to help segment individual microglia. In one case, we predicted the full volume of microglia to make shape determinations and in the other case we identified only the soma to generate counts.
In 5xFAD mice, Iba1(+) microglia colocalize with Amyloid plaques and become activated, retracting processes and taking on a distinct shape not seen in WT mouse brains. We trained our Al-powered workflows to selectively detect these activated plaque-associated microglia (PAMs) and not the majority of the Iba1(+) microglia in the brain that are in a homeostatic state. The PAM levels in Cerebellum, Visual and Somatomotor Areas are consistent with the Amyloid levels detected in the same mice. Across hundreds of brain area, the data from our Amyloid and PAM whole-brain quantification workflows are strongly correlated.
Clearing and staining of a whole brain from a 5xFAD Alzheimer’s Disease model mouse with an antibody recognizing β-Amyloid.
AI-powered tools determine the probability that an object is a plaque (red) or cell (green). Our 3TK workflows can then perform brain-wide regional quantification of independent object populations extracted from the same fluorescence channel.
Our Translucence Teravoxel ToolKit (3TK) software uses AI-powered workflows to identify individual Npas4(+) neurons throughout the cleared and stained intact mouse brain.
Each brain is computationally warped to the Allen Reference Brain and neurons are registered to an anatomical map to determine Npas4 expression metrics across 100’s of brain regions.
We have collapsed the hierarchical annotations into larger regions to demonstrate brain-wide Npas4 expression levels in 14 brains from mice exposed to light for various durations after housing in the dark for 24h.
These 2D heatmaps are drawn from 3D whole-brain data sets and show the level of Npas4 expression determined from the Npas4 staining intensity of individual neurons.
The Npas4 signal is quantified in 100’s of brain regions over time. We have plotted data from a few exemplar regions in the bottom left.
The volcano plot shows brain regions in blue with statistically significant elevations of Npas4 expression after light exposure.
After segmenting amyloid plaques throughout the brain, we register individual brains with the Allen Reference Brain, using the warping function to shift the x,y,z coordinated of individual plaques into a standard coordinate space. We then use the 3D brain map to produce automated regional quantification of amyloid plaque density.
The top images are a single z-plane through an intact 3D experimentally-treated brain. Iba1 immunoreactivity is shown on the left, and the corresponding cell labels from an AI-powered workflow in our 3TK software are on the right. Zoomed images show cellular morphology masks. Small seeming labels can be portions of microglia that project orthogonal to the 2D slice shown. Cell masks allow for counts, shape analysis, and fluorescence intensity measurements.
Single z-planes through a 5xFAD mouse brain demonstrate the brain-wide pattern of β-amyloid aggregates. On the left is immunoreactivity measured with an anti-β-amyloid antibody. On the right, an AI-powered workflow in our 3TK software identifies and labels plaques throughout the brain.
In 5xFAD mice, Iba1(+) microglia colocalize with Amyloid plaques and become activated, retracting processes and taking on a distinct shape not seen in WT mouse brains. We trained our Al-powered workflows to selectively detect these activated plaque-associated microglia (PAMs) and not the majority of the Iba1(+) microglia in the brain that are in a homeostatic state. The PAM levels in Cerebellum, Visual and Somatomotor Areas are consistent with the Amyloid levels detected in the same mice. Across hundreds of brain area, the data from our Amyloid and PAM whole-brain quantification workflows are strongly correlated.
Clearing and staining of a whole brain from a 5xFAD Alzheimer’s Disease model mouse with an antibody recognizing β-Amyloid.
AI-powered tools determine the probability that an object is a plaque (red) or cell (green). Our 3TK workflows can then perform brain-wide regional quantification of independent object populations extracted from the same fluorescence channel.
Our Translucence Teravoxel ToolKit (3TK) software uses AI-powered workflows to identify individual Npas4(+) neurons throughout the cleared and stained intact mouse brain.
Each brain is computationally warped to the Allen Reference Brain and neurons are registered to an anatomical map to determine Npas4 expression metrics across 100’s of brain regions.
We have collapsed the hierarchical annotations into larger regions to demonstrate brain-wide Npas4 expression levels in 14 brains from mice exposed to light for various durations after housing in the dark for 24h.
These 2D heatmaps are drawn from 3D whole-brain data sets and show the level of Npas4 expression determined from the Npas4 staining intensity of individual neurons.
The Npas4 signal is quantified in 100’s of brain regions over time. We have plotted data from a few exemplar regions in the bottom left.
The volcano plot shows brain regions in blue with statistically significant elevations of Npas4 expression after light exposure.
After segmenting amyloid plaques throughout the brain, we register individual brains with the Allen Reference Brain, using the warping function to shift the x,y,z coordinated of individual plaques into a standard coordinate space. We then use the 3D brain map to produce automated regional quantification of amyloid plaque density.
AI-Powered 3D Quantification delivers precise and robust 3D insights into the epitope of interest. If you can label it, we can quantify it.
NIH-funded tissue clearing kit users are eligible for a discounted rate on quantification services to assist in your sample analysis.
When you contact us about AI-Powered 3D Quantification services, please indicate in the comments section that you are using our kit and provide us with the email that you purchased the kit(s) with.
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