Immobilisation of Lipophilic and Amphiphilic Biomarker on Hydrophobic Microbeads
Bibliographic record
Abstract
Abstract Background Lipids and amphiphilic molecules are ubiquitous and play a central role in cell signalling, cell membrane structure, and lipid transport in the human body. However, they also appear in many diseases such as atherosclerosis, cardiovascular diseases, infections, inflammatory diseases, cancer, and autoimmune diseases. Thus, it is necessary to have detection systems for lipids and amphiphilic molecules. Microbeads can be one of these systems for the simultaneous detection of different lipophilic biomarkers. Methods Based on the fundamentals of microbead development, novel hydrophobic microbeads were produced. These not only have a hydrophobic surface, but are also fluorescently encoded and organic solvent resistant. The challenge after the development of the hydrophobic microbeads was to immobilise the amphiphilic molecules, in this study phospholipids, on the microbead surface in an oriented direction. After successful immobilisation of the biomarkers, a suitable antibody based detection assay was established. Results By passive adsorption, the phospholipids cardiolipin, phosphatidylethanolamine and phosphatidylcholine could be bound to the microbead surface. With the application of the enzymes phospholipase A2 and phospholipase C, the directional binding of the phospholipids to the microbead surface was demonstrated. The detection of directional binding indicated the need for the hydrophobic surface. Microbeads with no hydrophobic surface bound the phospholipids non-directionally (with the hydrophilic head) and were thus no longer reactively accessible for detection. Conclusion With the newly developed hydrophobic, dual coded and solvent stable microbeads it is possible to bind amphiphilic biomolecules directionally onto the microbead surfaces.
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How this classification was reachedexpand
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) | 0.000 | 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 | 0.001 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".