MétaCan
Menu
Back to cohort
Record W2902676362 · doi:10.1111/jmi.12773

Real‐time parallel 3D multiple particle tracking with single molecule centrifugal force microscopy

2018· article· en· W2902676362 on OpenAlex
Kou Li, Hai Lei, Chunguang Hu, Hongbin Li, Xiaolong Hu

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Microscopy · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicForce Microscopy Techniques and Applications
Canadian institutionsUniversity of British Columbia
FundersNatural Science Foundation of Tianjin CityNational Natural Science Foundation of ChinaNational Science Foundation
KeywordsTracking (education)Magnetic tweezersOptical tweezersComputer scienceMicroscopyMicroscopeParticle (ecology)Frame rateMicrofluidicsResolution (logic)Graphics processing unitTemporal resolutionComputational scienceNanotechnologyMaterials sciencePhysicsOpticsComputer visionArtificial intelligenceParallel computing

Abstract

fetched live from OpenAlex

Real-time tracking of multiple particles is key for quantitative analysis of dynamic biophysical processes and materials science via time-lapse microscopy image data, especially for single molecule biophysical techniques, such as magnetic tweezers and centrifugal force microscopy. However, real-time multiple particle tracking with high resolution is limited by the current imaging processes or tracking algorithms. Here, we demonstrate 1 nm resolution in three dimensions in real-time with a graphics-processing unit (GPU) based on a compute unified device architecture (CUDA) parallel computing framework instead of only a central processing unit (CPU). We also explore the trade-offs between processing speed and size of the utilized regions of interest and a maximum speedup of 137 is achieved with the GPU compared with the CPU. Moreover, we utilize this method with our recently self-built centrifugal force microscope (CFM) in experiments that track multiple DNA-tethered particles. Our approach paves the way for high-throughput single molecule techniques with high resolution and efficiency. LAY DESCRIPTION: Particles are widely used as probes in life sciences through their motions. In single molecule techniques such as optical tweezers and magnetic tweezers, microbeads are used to study intermolecular or intramolecular interactions via beads tracking. Also tracking multiple beads' motions could study cell-cell or cell-ECM interactions in traction force microscopy. Therefore, particle tracking is of key important during these researches. However, parallel 3D multiple particle tracking in real-time with high resolution is a challenge either due to the algorithm or the program. Here, we combine the performance of CPU and CUDA-based GPU to make a hybrid implementation for particle tracking. In this way, a speedup of 137 is obtained compared the program before only with CPU without loss of accuracy. Moreover, we improve and build a new centrifugal force microscope for multiple single molecule force spectroscopy research in parallel. Then we employed our program into centrifugal force microscope for DNA stretching study. Our results not only demonstrate the application of this program in single molecule techniques, also indicate the capability of multiple single molecule study with centrifugal force microscopy.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.047
Threshold uncertainty score0.898

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.275
Teacher spread0.266 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it