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Record W3038055031 · doi:10.3390/cells9061547

Insight into Salivary Gland Aquaporins

2020· review· en· W3038055031 on OpenAlexafffund
Claudia D’Agostino, Osama A. Elkashty, Clara Chivasso, Jason Perret, Simon D. Tran, Christine Delporte

Bibliographic record

VenueCells · 2020
Typereview
Languageen
FieldMedicine
TopicSalivary Gland Disorders and Functions
Canadian institutionsMcGill University
FundersFonds de Recherche du Québec - SantéFonds De La Recherche Scientifique - FNRS
KeywordsAquaporinSecretionSalivaSalivary glandTransmembrane proteinMedicineWater transportCancerBiologyCancer researchCell biologyBioinformaticsPathologyInternal medicineWater flow

Abstract

fetched live from OpenAlex

The main role of salivary glands (SG) is the production and secretion of saliva, in which aquaporins (AQPs) play a key role by ensuring water flow. The AQPs are transmembrane channel proteins permeable to water to allow water transport across cell membranes according to osmotic gradient. This review gives an insight into SG AQPs. Indeed, it gives a summary of the expression and localization of AQPs in adult human, rat and mouse SG, as well as of their physiological role in SG function. Furthermore, the review provides a comprehensive view of the involvement of AQPs in pathological conditions affecting SG, including Sjögren's syndrome, diabetes, agedness, head and neck cancer radiotherapy and SG cancer. These conditions are characterized by salivary hypofunction resulting in xerostomia. A specific focus is given on current and future therapeutic strategies aiming at AQPs to treat xerostomia. A deeper understanding of the AQPs involvement in molecular mechanisms of saliva secretion and diseases offered new avenues for therapeutic approaches, including drugs, gene therapy and tissue engineering. As such, AQP5 represents a potential therapeutic target in different strategies for the treatment of xerostomia.

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)0.000
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.002

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.

Opus teacher head0.044
GPT teacher head0.313
Teacher spread0.269 · 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
GenreReview

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

Citations67
Published2020
Admission routes2
Has abstractyes

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