Dynamics of Engineered Artificial Membranes and Biosensors
Bibliographic record
Abstract
In simple terms a biological membrane consists of two layers of fat that slide on each other – hence membranes are called lipid bilayers. Biological membranes include more than just the cell membrane. Within the cell, there are several structures that are bound by membranes; these structures are called organelles and include the nucleus, mitochondria, endoplasmic reticulum, Gogli apparatus, and lysomes. Why Membranes? Why biological membranes? Membranes and the macromolecules embedded in them perform extremely important biological functions. They form selectively permeable barriers that enclose cells and organelles within the cell. The cell membrane is the target of physical, chemical, and biological agents such as thermal and mechanical stress, toxins, hormones, viruses, and microbes. Biological membranes exhibit remarkable properties. Embedded in the membrane are protein macromolecules that perform crucial functions for a living cell. For example, ion channels are subnanosized pores formed out of proteins in the membrane that selectively open and close and allow ions to flow into the cell. It is known that almost 25 percent of genes code for membrane proteins. Also, more than 50 percent of available drugs target membrane proteins [369]. Cytoskeletal filaments and sterols, such as cholesterol, give structural stability to the membrane. Antimicrobial drugs bind to specific sites in the membrane of bacterial cells and induce pores in the membrane that compromise the integrity of the membrane and lead to bacterial cell death. Applying a voltage across a membrane causes the membrane to spontaneously form pores – this process is called electroporation and is crucial for drug delivery mechanisms. A membrane has several moving parts that comprise lipids and macromolecules that perform a variety of biological tasks. For example, the assembly of new cellular membranes commonly results from old membranes in which membrane-bound enzymes construct new lipid molecules. These new lipid molecules then either diffuse into the old membrane or form vesicles which can merge with other membranes via vesicle fusion. Vesicle fusion requires the coordination of several proteins and macromolecules as biological membranes do not spontaneously fuse. The process of vesicle fusion and cellular membrane assembly is still an active area of research.
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".