Conceptual and Experimental Tools to Understand Spatial Effects and Transport Phenomena in Nonlinear Biochemical Networks Illustrated with Patchy Switching
Why this work is in the frame
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Bibliographic record
Abstract
Many biochemical systems are spatially heterogeneous and exhibit nonlinear behaviors, such as state switching in response to small changes in the local concentration of diffusible molecules. Systems as varied as blood clotting, intracellular calcium signaling, and tissue inflammation are all heavily influenced by the balance of rates of reaction and mass transport phenomena including flow and diffusion. Transport of signaling molecules is also affected by geometry and chemoselective confinement via matrix binding. In this review, we use a phenomenon referred to as patchy switching to illustrate the interplay of nonlinearities, transport phenomena, and spatial effects. Patchy switching describes a change in the state of a network when the local concentration of a diffusible molecule surpasses a critical threshold. Using patchy switching as an example, we describe conceptual tools from nonlinear dynamics and chemical engineering that make testable predictions and provide a unifying description of the myriad possible experimental observations. We describe experimental microfluidic and biochemical tools emerging to test conceptual predictions by controlling transport phenomena and spatial distribution of diffusible signals, and we highlight the unmet need for in vivo tools.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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) | 0.000 | 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 it