Evaluation of the physical properties of experimental macromolecular crowding systems
Bibliographic record
Abstract
Biological cells are crowded environments consisting of both large and small molecules. The macromolecular crowding observed in biological cells is likely very important to the structure and function of a living cell. Since the macromolecules can interact with each other, this makes the system complex and there remain several open questions. In the laboratory, artificial crowder molecules can be used to create experimental model systems that mimic the cellular environment. Artificial crowders such as the polysaccharide, Ficoll, have long been assumed to be compact and colloidal, but a holistic understanding of its structure and dynamics is lacking. This thesis investigates the structure of Ficoll using multiple experimental techniques. We report rheology, small angle neutron scattering, self diffusion and relaxation measurements using nuclear magnetic resonance experiments on two widely used artificial crowder molecules, Ficoll-70 and Ficoll-400. Our results, combining measures of structure, diffusion, relaxation and rheology, show that Ficolls are more polymer like than colloid like. Importantly, we find that the self-diffusion of HDO molecules in the suspension is an efficient probe to evaluate volume occupancy of the suspension under investigation. We then evaluate the physical properties of a protein crowder solution, BSA, and phytoglycogen, a natural plant based dendrimer using the methods developed to evaluate the Ficoll suspension properties. For all crowders, we find that the self diffusion coefficient decreases exponentially with a characteristic concentration of 10-12 wt %. We also observe that the NMR transverse relaxation of the solvent is a sensitive, independent measure of water confinement, which can be correlated with suspension rheology and self diffusion. To summarize, the highlight of this thesis is that structural and dynamical methods that report on macromolecules as well as solvent can provide a more complete view of macromolecular crowding.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".