Artificial tumor matrices and bioengineered tools for tumoroid generation
Bibliographic record
Abstract
The tumor microenvironment (TME) is critical for tumor growth and metastasis. The TME contains cancer-associated cells, tumor matrix, and tumor secretory factors. The fabrication of artificial tumors, so-called tumoroids, is of great significance for the understanding of tumorigenesis and clinical cancer therapy. The assembly of multiple tumor cells and matrix components through interdisciplinary techniques is necessary for the preparation of various tumoroids. This article discusses current methods for constructing tumoroids (tumor tissue slices and tumor cell co-culture) for pre-clinical use. This article focuses on the artificial matrix materials (natural and synthetic materials) and biofabrication techniques (cell assembly, bioengineered tools, bioprinting, and microfluidic devices) used in tumoroids. This article also points out the shortcomings of current tumoroids and potential solutions. This article aims to promotes the next-generation tumoroids and the potential of them in basic research and clinical application.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".