Evaluating the Impact of Phosphate‐Buffered Saline Solutions on the Micellar Behavior of Dimeric Surfactants and Their Interaction With Lipid Membranes
Bibliographic record
Abstract
ABSTRACT Over the past few years, dicationic alkylammonium bromide dimeric surfactants have emerged as promising agents for numerous biotechnology and medical applications. However, there have been few studies examining their behavior within a biological context, particularly regarding the impact physiological buffers have on their physico‐chemical properties and how these differences impact their ability to interact with cellular lipid membranes. In this paper, we have determined the CMC values of a series of 10 and 12‐carbon main chain dimeric surfactants as a function of both spacer group length and the amount of a physiological buffer in solution, namely phosphate‐buffered‐saline (or PBS), a buffer that is relevant for biological systems under saline conditions. The impact of micellar and sub‐micellar surfactant concentrations on the phase behavior and structural integrity of model membrane systems was assessed using fluorogenic probes and correlated with cell cytotoxicity using a hemolysis assay. These results reveal a connection between the structure of the dimeric surfactants and how they interact with biological membranes. These results represent an important first step in elucidating the mechanism of the interaction of dicationic alkylammonium bromide dimeric surfactant‐mediated membrane insertion (and possible destabilization), and how this might impact the behavior of these surfactants in biochemical applications.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".