Crossing Barriers<i>: In Vitro</i> Cancer Model for Studying Monocyte Migration across Endothelial Barriers
Bibliographic record
Abstract
Monocytes originate in the bone marrow and make up 2–10% of all white blood cells, circulating in the blood to damaged tissue and disease sites, where they differentiate into macrophages or dendritic cells. In solid tumors such as glioblastoma, monocytes recruited from the blood to the tumor site differentiate into tumor-associated macrophages (TAMs), which play a key role in tumor progression and metastasis. The endothelial vessel wall plays a significant role in the migration, activation, and polarization of these monocytes. Therefore, it is crucial to incorporate an endothelial cell (EC) barrier within an in vitro cancer model for elucidating transendothelial migration of monocytes along with high-throughput screening capabilities. The IFlowPlate is a high-throughput organ-on-a-chip device created on a 384-well plate modified by creating 128 tissue compartments created by connecting three wells with a single channel to model interstitial flow. Due to its simple design, it can be easily modified to model any tissue type. To study the effects of the EC barrier on tumor-promoted monocyte migration, cancer spheroids were embedded within a fibrin hydrogel with an EC barrier on the hydrogel surface to mimic the vessel wall. THP-1 monocyte migration was observed in the presence of patient-derived glioblastoma cancer spheroids and interstitial flow, and the presence of the human umbilical vein endothelial cell (HUVEC) barrier slowed and reduced monocyte migration compared with controls without EC barriers. Inflammatory cytokines, such as granulocyte–macrophage colony-stimulating factor (GM-CSF), interleukin-6 (IL-6), interleukin-10 (IL-10), and interleukin-1β (IL-1β) secretion levels increased, while tumor necrosis factor α (TNF-α) and interleukin-12p40 (IL-12p40) levels decreased and monocyte chemoattractant protein-1 (MCP-1) and interleukin-8 (IL-8) levels remained unchanged in the presence of the EC barrier and spheroids, confirming the importance of the EC barrier for monocyte activation and migration. The EC barrier plays a crucial role in promoting and controlling monocyte migration in vivo . The IFlowPlate with a functional EC barrier can be used to model monocyte migration in vitro to study the role of monocytes in cancer prognosis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".