Cryoloading: introducing large molecules into live synaptosomes
Bibliographic record
Abstract
Neurons communicate with their target cells primarily by the release of chemical transmitters from presynaptic nerve terminals. The study of CNS presynaptic nerve terminals, isolated as synaptosomes (SSMs) has, however, been hampered by the typical small size of these structures that precludes the introduction of non-membrane permeable test substances such as peptides and drugs. We have developed a method to introduce large alien compounds of at least 150 kDa into functional synaptosomes. Purified synaptosomes are frozen in cryo-preserving buffer containing the alien compound. Upon defrosting, many of the SSMs contain the alien compound presumably admitted by bulk buffer-transfer through the surface membranes that crack and reseal during the freeze/thaw cycle. ~80% of the cryoloaded synaptosomes were functional and recycled synaptic vesicles (SVs), as assessed by a standard styryl dye uptake assay. Access of the cryoloaded compound into the cytoplasm and biological activity were confirmed by block of depolarization-induced SV recycling with membrane-impermeant BAPTA (a rapid Ca(2+)-scavenger), or botulinum A light chain (which cleaves the soluble NSF attachment protein receptor (SNARE) protein SNAP25). A major advantage of the method is that loaded frozen synaptosomes can be stored virtually indefinitely for later experimentation. We also demonstrate that individual synaptosome types can be identified by immunostaining of receptors associated with its scab of attached postsynaptic membrane. Thus, cryoloading and scab-staining permits the examination of SV recycling in identified individual CNS presynaptic nerve terminals.
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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 | 0.000 | 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".