MétaCan
Menu
Back to cohort
Record W4395677203 · doi:10.21203/rs.3.rs-4290737/v1

Detectability of Cytokine and Chemokine using ELISA, following Sample-inactivation using Triton X-100 or Heat

2024· preprint· en· W4395677203 on OpenAlexaff
Erica Hofer Labossiere, Sandra Nora González Díaz, Stephanie Enns, Paul Lopez, Xuefen Yang, Biniam Kidane, Gloria Vázquez‐Grande, Abu Bakar Siddik, Sam Kam-Pun Kung, Paul Sandstrom, Amir Ravandi, T. Blake Ball, Ruey‐Chyi Su

Bibliographic record

VenueResearch Square · 2024
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Biosensing Techniques and Applications
Canadian institutionsSt. Boniface HospitalHealth Sciences CentreUniversity of ManitobaPublic Health Agency of Canada
Fundersnot available
KeywordsChemokineSample (material)CytokineChemistryChromatographyImmunologyMedicineBiochemistry

Abstract

fetched live from OpenAlex

Abstract Background Routine characterization of clinical samples for their immunological responses against infectious pathogens often involves assessing cytokine/chemokine profiles and/or production of pathogen-specific antibodies. To prevent transmission of infectious materials in laboratories, these clinical samples are often inactivated by detergents or heat before the molecular assays are performed. Antibody-based molecular assays, such as ELISA, are highly sensitive to conformational changes in analytes. How specific inactivation procedures impact on cytokine/chemokine detectability in the clinical samples is not fully elucidated. This study compared two commonly used inactivation methods (Triton X-100, heat-inactivation) and untreated native samples in the cytokine/chemokine assays. Method Plasma, endotracheal tube aspirate (ETTA), and nasopharyngeal (NP) samples underwent inactivation with 0.05% Triton X-100 or heat (60°C, 1 hour). Cytokines/chemokine levels were assessed using Meso-Scale-Multi-Spot assays. Data were analyzed against untreated samples using one-way and Tukey’s multiple comparisons tests. Additionally, the conformational instability of cytokines/chemokines, predicted by their amino acid sequence, was examined to determine its contribution to detectability in inactivated samples. Results Heat treatment significantly impacted cytokine/chemokine detection across sample types. IL-1α levels were substantially reduced in ETTA, NP, and plasma samples. In heat-inactivated plasma, IL-12p40, IL-15, IL-16, VEGF, IL-7, and TNF-β, among 36 cytokines, were reduced by 33-99% (p-values ≤0.02). Conversely, Triton X-100 minimally affected cytokine/chemokine detection in plasma and NP samples by 11-37% (p-values ≤0.04). Triton X-100 increased the detection of IL-15, IL-16, IL-1α, VEGF, and IL-7 levels in NP samples. Triton X-100-inactivated ETTA samples showed no significant impact on cytokine/chemokine detectability. Heat inactivation had more profound impacts on protein detectability. Structural analysis revealed heat-affected cytokines had more hydrophobic residues and higher instability indices, although protein features alone could not reliably predict susceptibility. Conclusion Our findings demonstrated the importance of empirical assessments of inactivation protocols in the measurements of cytokine/chemokine responses in clinical samples. Overall, Triton X-100 performed better than heat inactivation in preserving protein conformation for antibodies-based immunological studies.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.104
GPT teacher head0.459
Teacher spread0.355 · 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
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueResearch SquareSame topicAdvanced Biosensing Techniques and ApplicationsFrench-language works237,207