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Record W2955729399 · doi:10.18502/rmm.v6i3.4611

Use of Protein-Protein Interaction Network for Biomarker Identification in Oocyte Maturation

2019· article· en· W2955729399 on OpenAlexfundno aff
Golzar Farhadi, Jamal Fayazi, Hedayat Allah Roshanfekr, Mahmoud Nazari, Elham Behdani

Bibliographic record

VenueResearch in Molecular Medicine · 2019
Typearticle
Languageen
FieldMedicine
TopicReproductive Biology and Fertility
Canadian institutionsnot available
FundersUniversité Laval
KeywordsBiologyGene expressionGeneMicroarray analysis techniquesMicroarrayOocyteGene expression profilingGeneticsEmbryo

Abstract

fetched live from OpenAlex

Background: Oocyte maturation begins at the embryonic stage and continues throughout life. The effect of Follicle- Stimulating hormone (FSH) on gene of genes was evaluated using GEO access codes for the data set GSE38345. Materials and Methods: The microarray data containing the gene expression information from cow oocytes show that their maturation is influenced by FSH. Data analysis was performed using GEO2R. After identifying the genes and examining the different genes expressed, two gene groups with increased and decreased expression were identified. The interaction of each of the gene groups was examined using the STRING database, based on the co-expression information. The meaningful sub networks were explored using the Clusterone software. Gene ontology was performed using the comparative GO database. The miRNA-mRNA interaction network was also studied based on the miRWalk database. Finally, meaningful networks and subnets obtained by the Cytoscape software, were designed. Results: Comparison of oocyte gene expression data between the pre-maturation and postmaturation stages after treatment with FSH revealed 5958 genes with increased expression and 4275 genes with decreased expression. Examination of the protein interaction network among the set of increased and decreased expression genes based on string information revealed 262 genes with increased expression and 147 genes with decreased expression (high confidence (0.7) data). RPS3, NUSAP1, TBL3, and ATP5H showed increased expression and were effective in the positive regulation of rRNA processing, cell division, mitochondrial ATP synthesis coupled proton, and in oxidative phosphorylation and progesterone-mediated functions. WDR46 and MRPL22 showed decreased expression, which were important in the regulation of SRP-dependent co-translational proteins targeting the membrane, RNA secondary structure, unwinding, and functional pathways of ribosomal and RNA polymerase. The most important miRNA genes in the protein network of increased and decreased gene expression were bta-miR-10b-5p and miR-29b-2-5p. Conclusion: Examination of the genes expressed in the oocyte maturation pathway revealed nuclear, mitochondrial, and miRNA genes. Increasing and decreasing gene expression helps maintain equilibrium, which can be a biological marker.

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)0.004
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.764
Threshold uncertainty score0.298

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.141
GPT teacher head0.432
Teacher spread0.291 · 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

Citations4
Published2019
Admission routes1
Has abstractyes

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