A convolutional neural network characterizes the properties of very small biomolecules without requiring prior detection. (Image by H. Klein Moberg.)Deep learning for nanofluidic scattering microscopy
Henrik Klein Moberg
Date: 23 August 2023
Time: 8:15 AM PDT
We show that a custom ResNet-inspired CNN architecture trained on simulated biomolecule trajectories surpasses the performance of standard algorithms in terms of tracking and determining the molecular weight and hydrodynamic radius of biomolecules in the low-kDa regime in optical microscopy. We show that high accuracy and precision is retained even below the 10-kDa regime, constituting approximately an order of magnitude improvement in limit of detection compared to current state-of-the-art, enabling analysis of hitherto elusive species of biomolecules such as cytokines (~5-25 kDa) important for cancer research and the protein hormone insulin (~5.6 kDa), potentially opening up entirely new avenues of biological research.
The Soft Matter Lab participates to the SPIE Optics+Photonics conference in San Diego, CA, USA, 20-24 August 2023, with the presentations listed below.
Agnese Callegari: Playing with active matter
21 August 2023 • 4:05 PM – 4:20 PM PDT | Conv. Ctr. Room 6D
Giovanni Volpe is also co-author of the presentations:
Jiawei Sun (KI): (Poster) Assessment of nonlinear changes in functional brain connectivity during aging using deep learning
21 August 2023 • 5:30 PM – 7:00 PM PDT | Conv. Ctr. Exhibit Hall A
Blanca Zufiria Gerbolés (KI): (Poster) Exploring age-related changes in anatomical brain connectivity using deep learning analysis in cognitively healthy individuals
21 August 2023 • 5:30 PM – 7:00 PM PDT | Conv. Ctr. Exhibit Hall A
Mite Mijalkov (KI): Uncovering vulnerable connections in the aging brain using reservoir computing
22 August 2023 • 9:15 AM – 9:30 AM PDT | Conv. Ctr. Room 6C
A convolutional neural network characterizes the properties of very small biomolecules without requiring prior detection. (Image by H. Klein Moberg.)Seeing the invisible: deep learning optical microscopy for label-free biomolecule screening in the sub-10 kDa regime
Henrik Klein Moberg, Christoph Langhammer, Daniel Midtvedt, Barbora Spackova, Bohdan Yeroshenko, David Albinsson, Joachim Fritzsche, Giovanni Volpe Submitted to SPIE-ETAI Date: 23 August 2022 Time: 9:15 (PDT)
We show that a custom ResNet-inspired CNN architecture trained on simulated biomolecule trajectories surpasses the performance of standard algorithms in terms of tracking and determining the molecular weight and hydrodynamic radius of biomolecules in the low-kDa regime in NSM optical microscopy. We show that high accuracy and precision is retained even below the 10-kDa regime, constituting approximately an order of magnitude improvement in limit of detection compared to current state-of-the-art, enabling analysis of hitherto elusive species of biomolecules such as cytokines (~5-25 kDa) important for cancer research and the protein hormone insulin (~5.6 kDa), potentially opening up entirely new avenues of biological research.
The Soft Matter Lab participates to the SPIE Optics+Photonics conference in San Diego, CA, USA, 21-25 August 2022, with the presentations listed below.
Martin Selin: Scalable construction of quantum dot arrays using optical tweezers and deep learning (@SPIE)
22 August 2022 • 11:05 AM – 11:25 AM PDT | Conv. Ctr. Room 5A
Jesus Pineda: Revealing the spatiotemporal fingerprint of microscopic motion using geometric deep learning (@SPIE)
23 August 2022 • 11:05 AM – 11:25 AM PDT | Conv. Ctr. Room 5A
Anna Canal Garcia: Multilayer brain connectivity analysis in Alzheimer’s disease using functional MRI data (@SPIE)
24 August 2022 • 2:25 PM – 2:45 PM PDT | Conv. Ctr. Room 5A
Mite Mijalkov: A novel method for quantifying men and women-like features in brain structure and function (@SPIE)
24 August 2022 • 3:05 PM – 3:25 PM PDT | Conv. Ctr. Room 5A
Kymographs of DNA inside Channel II. (Image by the Authors.)Label-free nanofluidic scattering microscopy of size and mass of single diffusing molecules and nanoparticles
Barbora Špačková, Henrik Klein Moberg, Joachim Fritzsche, Johan Tenghamn, Gustaf Sjösten, Hana Šípová-Jungová, David Albinsson, Quentin Lubart, Daniel van Leeuwen, Fredrik Westerlund, Daniel Midtvedt, Elin K. Esbjörner, Mikael Käll, Giovanni Volpe & Christoph Langhammer
Nature Methods 19, 751–758 (2022)
doi: 10.1038/s41592-022-01491-6
Label-free characterization of single biomolecules aims to complement fluorescence microscopy in situations where labeling compromises data interpretation, is technically challenging or even impossible. However, existing methods require the investigated species to bind to a surface to be visible, thereby leaving a large fraction of analytes undetected. Here, we present nanofluidic scattering microscopy (NSM), which overcomes these limitations by enabling label-free, real-time imaging of single biomolecules diffusing inside a nanofluidic channel. NSM facilitates accurate determination of molecular weight from the measured optical contrast and of the hydrodynamic radius from the measured diffusivity, from which information about the conformational state can be inferred. Furthermore, we demonstrate its applicability to the analysis of a complex biofluid, using conditioned cell culture medium containing extracellular vesicles as an example. We foresee the application of NSM to monitor conformational changes, aggregation and interactions of single biomolecules, and to analyze single-cell secretomes.
In the event, held on Tuesday, 15 March 2022, 16:00-19:00, the ten teams that had gone through the training at the Startup Camp and developed their company ideas, pitched their companies on stage to a panel of entrepreneur experts, the other nine teams, and all business coaches at Chalmers Ventures. DeepTrack obtained the first place among the ten participants. Congrats!
Here a few pictures from the final pitching event of the Startup Camp.
Henrik. (Picture by Jonas Sandwall, Chalmers Ventures.) DeepTrack team members (left to right) Henrik, Giovanni and Jesus. (Picture by Jonas Sandwall, Chalmers Ventures.) Panelists. (Picture by Jonas Sandwall, Chalmers Ventures.)
