Voyage inside the cell: Microsystems and nanoengineering for intracellular measurement and manipulation
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
Abstract Properties of organelles and intracellular structures play important roles in regulating cellular functions, such as gene expression, cell motility and metabolism. The ability to directly interrogate intracellular structures inside a single cell for measurement and manipulation has significant implications in the understanding of subcellular and suborganelle activities, diagnosing diseases, and potentially developing new therapeutic approaches. In the past few decades, a number of technologies have been developed to study single-cell properties. However, methods of measuring intracellular properties and manipulating subcellular structures have been largely underexplored. Due to the even smaller size of intracellular targets and lower signal-to-noise ratio than that in whole-cell studies, the development of tools for intracellular measurement and manipulation is challenging. This paper reviews emerging microsystems and nanoengineered technologies for sensing and quantitative measurement of intracellular properties and for manipulating structures inside a single cell. Recent progress and limitations of these new technologies as well as new discoveries and prospects are discussed.
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 | 0.001 | 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