Label-free and noninvasive optical detection of the distribution of nanometer-size mitochondria in single cells
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.
Bibliographic record
Abstract
A microfluidic flow cytometric technique capable of obtaining information on nanometer-sized organelles in single cells in a label-free, noninvasive optical manner was developed. Experimental two-dimensional (2D) light scattering patterns from malignant lymphoid cells (Jurkat cell line) and normal hematopoietic stem cells (cord blood CD34+ cells) were compared with those obtained from finite-difference time-domain simulations. In the simulations, we assumed that the mitochondria were randomly distributed throughout a Jurkat cell, and aggregated in a CD34+ cell. Comparison of the experimental and simulated light scattering patterns led us to conclude that distinction from these two types of cells may be due to different mitochondrial distributions. This observation was confirmed by conventional confocal fluorescence microscopy. A method for potential cell discrimination was developed based on analysis of the 2D light scattering patterns. Potential clinical applications using mitochondria as intrinsic biological markers in single cells were discussed in terms of normal cells (CD34+ cell and lymphocytes) versus malignant cells (THP-1 and Jurkat cell lines).
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it