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Record W3127897726 · doi:10.1038/s41598-021-83189-x

PHAIR: a biosensor for pH measurement in air–liquid interface cell culture

2021· article· en· W3127897726 on OpenAlexafffund
Mohammadhossein Dabaghi, Neda Saraei, Gang Xu, Abiram Chandiramohan, Jonas Yeung, Jenny Nguyen, Milica Vukmirovic, P. Ravi Selvaganapathy, Jeremy A. Hirota

Bibliographic record

VenueScientific Reports · 2021
Typearticle
Languageen
FieldChemical Engineering
TopicAnalytical Chemistry and Sensors
Canadian institutionsMcMaster University Medical CentreUniversity of British ColumbiaUniversity of WaterlooMcMaster University
FundersHospital for Sick ChildrenCanada Research Chairs
KeywordsBiosensorMiniaturizationNanotechnologyMaterials scienceCell cultureSilver chlorideElectrodeMicrofluidicsChemistryBiology

Abstract

fetched live from OpenAlex

In many biological systems, pH can be used as a parameter to understand and study cell dynamics. However, measuring pH in live cell culture is limited by the sensor ion specificity, proximity to the cell surface, and scalability. Commercially available pH sensors are difficult to integrate into a small-scale cell culture system due to their size and are not cost-effective for disposable use. We made PHAIR-a new pH sensor that uses a micro-wire format to measure pH in vitro human airway cell culture. Tungsten micro-wires were used as the working electrodes, and silver micro-wires with a silver/silver chloride coating were used as a pseudo reference electrode. pH sensitivity, in a wide and narrow range, and stability of these sensors were tested in common standard buffer solutions as well as in culture media of human airway epithelial cells grown at the air-liquid interface in a 24 well cell culture plate. When measuring the pH of cells grown under basal and challenge conditions using PHAIR, cell viability and cytokine responses were not affected. Our results confirm that micro-wire-based sensors have the capacity for miniaturization and detection of diverse ions while maintaining sensitivity. This suggests the broad application of PHAIR in various biological experimental settings.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.065
Threshold uncertainty score0.598

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.022
GPT teacher head0.249
Teacher spread0.227 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations12
Published2021
Admission routes2
Has abstractyes

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