The Isolation, Culture, and Cryopreservation of Human Rectus Sheath Fibroblasts
Bibliographic record
Abstract
The vast majority of pelvic and intra-abdominal surgery is undertaken through at least one incision, through either the linea alba or the rectus sheath. These connective tissue layers are formed from the aponeuroses of the rectus muscles (anterior and posterior rectus sheath) and are vital for the structural integrity of the abdominal wall. Poor healing of these connective tissues after surgery can lead to significant morbidity for patients, who can develop unsightly and painful incisional hernias. Fibroblasts within the rectus sheath are responsible for laying down and remodeling collagen during the healing process after surgery. Despite their importance for this healing process, such cells have not been studied in vitro. In order to carry out such work, researchers must first be able to isolate these cells from human tissue and culture them successfully so they may be used for experimentation. This article provides an extensive and detailed protocol for the isolation, culture, cryopreservation, and thawing of human rectus sheath fibroblasts (RSFs). In our hands, this protocol develops confluent cultures of primary fibroblasts within 2 weeks, and sufficient cultures ready for freezing and storage after a further 2 to 4 weeks. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol: Collagenase digestion of human rectus sheath and isolation of RSFs Alternate Protocol: Collagenase digestion of human rectus sheath and isolation of RSFs, digestion in flask Support Protocol: Cryopreservation and thawing of human RSFs.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.005 |
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".