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Record W2804624977 · doi:10.1149/ma2018-01/42/2427

A Versatile Redox Responsive Nanoferrogels Based Sensor for Metabolics Analytics

2018· article· en· W2804624977 on OpenAlexaff
Samuel M. Mugo, Weihao Lu, Nicole Funk

Bibliographic record

VenueECS Meeting Abstracts · 2018
Typearticle
Languageen
FieldEngineering
TopicElectrochemical sensors and biosensors
Canadian institutionsMacEwan University
Fundersnot available
KeywordsRedoxNanotechnologyAerogelSelf-healing hydrogelsMaterials scienceChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Developed is an inexpensive label free redox responsive nanoferrogel molecular receptor integrated in a chemoresisistive sensor for rapid detection of Reactive Oxygen Species (ROS) such as H2O2 and H2O2 deriving metabolites, species are of interest in myriad applications including clinical, environmental, food, and plant physiology. Inexpensively fashioned by contact printing of redox responsive poly(N-isopropylacrylamide hydrogels herewith called ‘nanoferrogel’ on a conductive nanocellulose paper aerogel, the sensor is designed for specimen surface attachment as wearables, non-invasive transdermal sensors, and can be configured as microneedle sensor for in vivo analysis. Operating via ROS oxidation of the nanoferrogel trapped in the conductive aerogel film, the oxidized nanoferrogel volume change results in an overall change in conductivity, linearly proportional to ROS/ROS deriving metabolite concentration. In the presentation, the responsivity of the nanoferrogel to different ROS species such as H2O2, oxylipin, antioxidants will be demonstrated. The nanoferrogel based H2O2 sensor figures of merit, featuring, rapid (≤ 1min) H2O2 response, high selectivity, low limits of detection (≤ 0.01 µM),and broad linear dynamic range of (≤ 0.03 µM to ≥ 1.5M) will be highlighted. The nanoferrogel is perfectly recyclable, by electrochemical regeneration, affording ≥ 15 multiple usable cycles. Also showcased will be the adaptability of nanoferrogel for different sensor design configurations (e.g. micro/nanoelectrode systems), with some preliminary data attesting to the sensors utility for fundamental studies and detection of efflux of endogenous and exogenous H2O2 in single cells and other redox biomolecules, (e.g. glucose, choline). Preliminarily the sensor can be used for detection of bacterial (model used in our study Escherichia coli) autoinducers and metabolites, of importance in bacterial communication-quorum sensing. This would be a useful platform for understanding bacterial biofilm formation. Further, the nanoferrogel sensor fashioned for utility as a wearable device for detection of redox potential and inherent sweat metabolites will be demonstrated.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.240
Teacher spread0.225 · 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 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

Citations0
Published2018
Admission routes1
Has abstractyes

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