TRANSCRIPTOME ANALYSIS OF MOUSE SPLEEN IN RESPONSE TO EGG OVOMUCOID TREATMENT (141.11)
Bibliographic record
Abstract
Abstract Food allergy is a serious health concern among infants and young children. Despite its growing prevalence, our current understanding of the molecular mechanism(s) of food allergy remains incomplete. In this study, transcriptome profile of spleen from BALB/c mice was analyzed using Affymetrix arrays. Female BALB/c mice 6-8 weeks of age were orally exposed twice weekly for 5 wks with 1 mg of egg ovomucoid (OVM) and 10 µg of cholera toxin (CT). Control mice were similarly sensitized with 100 µl of 10 µg/µl amino acid solution and CT. At wk 6, experimental and control mice were challenged by intraperitoneal (i.p.) injection with 1 mg of OVM and amino acid solution respectively. Mice were euthanized 40 min post challenge to collect the spleens. Total RNA extracted from spleen was subjected to microarray hybridization. Analysis of microarray data revealed 87 genes differentially expressed with at least ±1.5 fold (p≤0.05). Gene ontology (GO) analysis revealed several biological processes related to hypersensitivity, inflammation or immune response. Biological network analysis illustrated connections among some differentially expressed genes and several immune or hypersensitivity related processes. Expression of five differentially expressed genes from microarray experiment was validated by real-time RT-PCR. Results from this study revealed a network of genes that may enable us to better understand the underlying molecular mechanism(s) of food allergy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".