Bibliographic record
Abstract
Traditionally, cell culture has been done in culture flasks or well plates where the volumes and length scales involved in the culture environment are many orders of magnitude larger than the size scale of individual cells. To better tailor medical care to an individual patient, it may be necessary to carry out genetic, physiological, and biochemical analyses on very small cell samples and to have an in vitro cell culture environment that more closely approximates the in vivo conditions. A microfluidic device that integrates both cell handling and long-term 3-D cell culture techniques is presented. The designed microdevice traps cells with alginate, an ionically cross-linking hydrogel, which mimics the extra cellular matrix within our body. To encapsulate the cells, a solution of calcium ions is introduced in parallel with the alginate precursor cell suspension. Alginate hydrogel forms at the interface and as the region of gel grows it traps cells inside. This is a reversible process; the gel matrix can be dissolved and the cells can be released by the addition of ethylene-diaminetetraacetic acid (EDTA), a calcium chelator. To show that the microfluidic device is reliable for long term mammalian cell culture, hepatocytes and breast tumor cells were cultured within the alginate gel layer inside the microfluidic device for more than two weeks. Hepatocytes were able to form three-dimensional aggregates within the microfluidic hydrogel environment. We further demonstrate the possibility of performing anticancer agent screening within this device. Breast tumor cells seeded in the microchannel were treated with doxorubicin, a common chemotherapy drug. Compared to controls, the doxorubicin inhibited cell proliferation. In future, this system will have applications in cell-based testing and in studies involving small cell populations, such as cancer cells obtained from needle biopsies of tumors.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".