Referee report. For: Local membrane deformation and micro-injury lead to qualitatively different responses in osteoblasts [v1; approved 1, http://f1000r.es/3o7]
Bibliographic record
Abstract
Micro-damage of bone tissue is known to regulate bone turnover. However, it is unknown if individual bone cells can differentiate between membrane deformation and micro-injury. We generated osteoblasts from mouse bone marrow or bone morphogenetic protein 2-transfected C2C12 cells. Single cells were mechanically stimulated by indentation with the atomic force microscopy probe with variable force load either resulting in membrane deformation only, or leading to membrane penetration and micro-injury. Changes in the cytosolic free calcium concentration ([Ca 2+ ] i ) in fluo4-AM loaded cells were analyzed. When deformation only was induced, it resulted in an immediate elevation of [Ca 2+ ] i which was localized to the probe periphery. Multiple consecutive local Ca 2+ responses were induced by sequential application of low level forces, with characteristic recovery time of ~2 s. The duration of [Ca 2+ ] i elevations was directly proportional to the tip-cell contact time. In contrast, cell micro-injury resulted in transient global elevations of [Ca 2+ ] i , the magnitude of which was independent of the tip-cell contact time. Sequential micro-injury of the same cell did not induce Ca 2+ response within 30 s of the first stimulation. Both local and global Ca 2+ elevations were blocked in Ca 2+ -free media or in the presence of stretch-activated channel blocker Gd 3+ . In addition, amount of Ca 2+ released during global responses was significantly reduced in the presence of PLC inhibitor Et-18-OCH 3 . Thus, we found qualitative differences in calcium responses to mechanical forces inducing only membrane deformation or deformation leading to micro-injury.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.528 | 0.248 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".