Cell Spinpods: A Simple Inexpensive Device to Determine Suspension Culture and Toxicity Effects on Renal Proximal Tubular Cells
Bibliographic record
Abstract
Abstract Rotating forms of suspension culture allow cells to aggregate into spheroids, prevent the de-differentiating influence of adherence to plastic surfaces, and, perhaps most importantly of all, provide physiologically relevant, in vivo levels of shear stress. Suspension culture technology has not, however, been widely implemented, in large part because the vessels are prohibitively expensive, labor-intensive to use, and are difficult to scale for industrial applications. Our solution addresses each of these challenges in a new vessel called a cell spinpod. These small 3.5 mL capacity vessels are constructed from injection molded thermoplastic polymer components. They contain self-sealing axial silicone rubber ports, and fluoropolymer, breathable membranes. Here we report the development of injection molded cell spinpods with two-fluid modeling of the flow and stresses. Their validation was accomplished using immortalized human renal proximal tubular cells for functional assays, renal damage marker release, and differential gene expression analysis via next-generation sequencing. During exposure to myeloma immunoglobulin light chains, rotation increased both toxin-induced cell death, and release of clinically validated nephrotoxicity cytokine markers in a toxin-specific pattern. Cell spinpods are a sensitive tool for detecting nephrotoxicity in vitro.
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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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".