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Record W1558809176

Correlation of MicroRNA Expressions with mutated and unmutated IgVH gene groups in chronic lymphocytic leukemia

2005· article· en· W1558809176 on OpenAlexfundno aff
Yi Zou

Bibliographic record

VenueUniversity Library - University of Saskatchewan (University of Saskatchewan) · 2005
Typearticle
Languageen
FieldMedicine
TopicChronic Lymphocytic Leukemia Research
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsChronic lymphocytic leukemiamicroRNACorrelationGeneGeneticsBiologyMutationLeukemiaCancer researchMathematics
DOInot available

Abstract

fetched live from OpenAlex

B-cell chronic lymphocytic leukemia is the most common leukemia in the adult population of Western developed countries. In 2005, an estimated 9,730 adults in the United States will be diagnosed with B-CLL and an estimated 4,600 deaths will occur. B-CLL is a common heterogeneous malignant disease with variable outcome. B-CLL is divided into two groups based on whether somatic hypermutation is observed in the variable region of the immunoglobulin heavy-chain locus (IgVH). The two distinct groups are named mutated and unmutated. The B-CLL mutated group has a more favorable prognosis than the unmutated group. Gene expression profiling has been used successfully to decipher the biological and clinical diversity of many leukemias and lymphomas. Recently, other small RNAs (microRNAs) have been shown to be important in hematopoiesis. MicroRNAs are small 20-28 nucleotide RNAs that are believed to control many important cellular and developmental processes by posttranscriptional gene silencing, translational repression, and modulating epigenetic events. We are interested in whether microRNA expression correlates with the mutational status of IgVH. This study is significant in the following ways: (1) microRNAs may become surrogate markers for the mutational status of IgVH of B-CLL, which implies a more rapid diagnostic means as compared to the current practice, and (2) microRNAs, in the particular context of B-CLL, may play some significant roles in a gene regulatory network that is further responsible for chromosomal abnormalities found in B-CLL. This thesis presents a study comparing microRNA expression in mutated and unmutated B-CLL groups. Instead of using a genome-wide expression profiling strategy, we selected a specific set of microRNAs based on their chromosome locations and mRNA targets. Specifically, we chose the following eight microRNAs (with their chromosomal abnormalities): mir16-1 (deletion 13), let-7i (trisomy 12), mir196-2 (trisomy 12), mir26a-2 (trisomy 12), mir-34b (deletion 11), mir-125b (deletion 11), mir-181C (trisomy 19), mir-125a (trisomy 19). We used solution hybridization assays to monitor the expression of microRNAs. We successfully characterized the microRNA expression in twelve B-CLL patient samples (eight mutated and four unmutated). Among the eight microRNAs examined, three (mir196-2, mir-125a, mir-125b) are not expressed in the two B-CLL groups, four (mir16-1, mir26a-2, let-7i, mir-34b) have significant differences in expressions over the two groups, and one (mir-181c) has no significant difference in expressions over the two groups.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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

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 head0.007
GPT teacher head0.186
Teacher spread0.180 · 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 designObservational
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

Citations1
Published2005
Admission routes1
Has abstractyes

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