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Record W2988404632 · doi:10.7554/elife.29595.018

Author response: Clearance of beta-amyloid is facilitated by apolipoprotein E and circulating high-density lipoproteins in bioengineered human vessels

2017· peer-review· en· W2988404632 on OpenAlexaff
Jérôme Robert, Emily B. Button, Brian Yuen, Megan Gilmour, Kevin Kang, Arvin Bahrabadi, Sophie Stukas, Wenchen Zhao, Iva Kulić, Cheryl L. Wellington

Bibliographic record

Venuenot available
Typepeer-review
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCerebral amyloid angiopathyApolipoprotein EAmyloid (mycology)Amyloid betaDementiaClearanceDiseaseLipoproteinBiochemistry of Alzheimer's diseasePathologyMedicineNeuroscienceAlzheimer's diseaseBiologyAmyloid precursor proteinInternal medicineCholesterol

Abstract

fetched live from OpenAlex

Alzheimer’s disease causes gradual loss of memory and difficulties in learning. The brains of patients with the disease show several abnormalities including deposits of a peptide molecule called beta-amyloid that is known to be toxic to nerve cells. This peptide can also cause damage to the brain by accumulating within the muscular walls of large blood vessels, a condition known as cerebral amyloid angiopathy (CAA) and is present in most Alzheimer’s disease patients. A group of molecules known as lipoproteins, which transport fats throughout body fluids, are thought to be involved in the process by which beta-amyloid leaves the brain. Apolipoprotein E (apoE) is one such molecule and it is made in the brain by cells called astrocytes. There are three different versions of apoE that are associated with different levels of risk of developing Alzheimer’s disease. Other lipoproteins, such as high-density lipoprotein, which is present in the blood, may also play a role in clearing beta-amyloid proteins from the brain. However, it has been difficult to investigate the roles of these lipoproteins in Alzheimer’s disease because current test-tube models do not fully mimic the composition of human brain blood vessels or show how they work. Robert et al. have used a tissue engineering approach to generate the first three-dimensional model of human brain blood vessels that can reproduce cerebral amyloid angiopathy. To make the model, different types of human cells similar to those found in real blood vessels and astrocytes were grown under conditions that resemble real-life conditions, including mimicking blood flow through the engineered vessels. Having established that the engineered vessels behaved similarly to normal blood vessels, Robert et al. used them to test whether lipoproteins helped to clear beta-amyloid proteins from the vessels. These experiments showed that a form of apoE that protects against Alzheimer’s disease was more effective in transporting beta-amyloid proteins across the walls of blood vessels than other forms of apoE. Further experiments showed that high-density lipoprotein in the blood and apoE on the brain side of the vessel work together to help transport beta-amyloid into the vessels. Together, these findings show that the model of CAA developed by Robert et al. provides a valuable new tool for exploring how this condition develops. The model could also be used more widely in the future, for example, to study how to deliver new drugs that could help treat Alzheimer’s disease into the brain.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.127
Threshold uncertainty score0.423

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.016
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0040.002
Open science0.0020.002
Research integrity0.0150.009
Insufficient payload (model declined to judge)0.1270.050

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.

Opus teacher head0.067
GPT teacher head0.375
Teacher spread0.309 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations1
Published2017
Admission routes1
Has abstractyes

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