Lipids Lay Thyselves Down: Redox-Induced Lipid Vesicle Fusion Onto Ferrocene-Terminated Self-Assembled Monolayers
Bibliographic record
Abstract
Due to the attractive electrochemical properties of ferrocene (fast electron transfer, low oxidation potential, and two stable redox states), ferrocenylalkanethiolates on gold are the most studied and employed electroactive self-assembled monolayer (SAM) system. Oxidation of the SAM-confined ferrocenes to ferroceniums is accompanied by the formation of ion-pairs with counter-ions in solution [1,2]. Ferrocene-terminated SAMs exhibit a reversible electrochemistry in the presence of anionic surfactants such as n-alkyl sulfates and sulfonates, while the less chaotropic n-alkyl phosphates and carboxylates lead to the irreversible oxidation of the SAM-confined ferrocene (Fig. A) [3]. Cyclic voltammetry indicates that these latter surfactants form strong ion pairs with the oxidized ferroceniums; an oxidation peak is observed for the first anodic potential sweep but no reduction peak is detected during the reverse sweep. No redox peaks are observed in subsequent sweeps. The surface plasmon resonance signal does not return back to its original value during reduction, indicating an irreversible adsorption of material to the surface, which in turn suggests the formation of a stable and insoluble ferrocenium-surfactant anion complex or deposit that blocks the redox process. In this work, atomic force microscopy is used to investigate the association of sodium n-dodecanoate to the SAM surface. This electrochemical approach appears to be an effective strategy for triggering the formation of solid-supported lipid membranes by the fusion of phospholipid vesicles onto the ferrocenylalkanethiolate SAM. In fact, phospholipids are double-tailed amphiphiles and these can associate with the oxidized ferrocene (Fig. B). A potential-step hold at 0,64 V for only five minutes induces the immediate adsorption of phosphatidylserine (DMPS, POPS and DOPS) at the SAM-gold/electrolyte interface with a full surface coverage. This technique is a versatile tool that offers many benefits such as, a faster supported lipid bilayers formation mimicking the biological membranes, a larger variety of lipid composition, structure and chemical nature, and a possibility of using metal surfaces considering their potential applications in electrochemical techniques, spectroscopic techniques and surface plasmon resonance. In this work, AFM-based nano-shaving, force spectroscopy, and surface plasmon resonance are combined to determine the thickness of the obtained lipid membrane. References [1] E. Dionne, T. Sultana and A. Badia, J. Am. Chem. Soc. 135, 17457-17468 (2013). [2] E. Dionne and A. Badia, ACS Appl. Mater. Interfaces 9, 5607-5621 (2017). [3] A. Salis and B. W. Ninham, Chem. Soc. Rev. 43, 7358-7377 (2014). Figure 1
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) | 0.000 | 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".