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Record W4410488639 · doi:10.1016/j.gimo.2025.103438

Genomic insights into Rett syndrome-like features in Bangladeshi participants

2025· article· en· W4410488639 on OpenAlex
Hosneara Akter, Muhammad Mizanur Rahman, Rabeya Akter Mim, Atikur Rahaman, Tamannyat Binte Eshaque, Farjana Binta Omar, Masuma Afrin Taniya, Amirul Islam, Bassam Jamalalail, Nasna Nassir, Binte Zehra, Shaoli Sarker, K. M. Furkan Uddin, AHM Nurun Nabi, Marc Woodbury‐Smith, Mohammed Uddin

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueGenetics in Medicine Open · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics and Neurodevelopmental Disorders
Canadian institutionsQueen's UniversityGenome Canada
FundersAl Jalila Foundation
KeywordsMECP2Rett syndromeGeneticsExome sequencingFrameshift mutationMedical geneticsMissense mutationBiologyGenomicsSanger sequencingPhenotypeGeneDNA sequencingBioinformaticsGenome

Abstract

fetched live from OpenAlex

Purpose: -targeted sequencing (TS) and exome sequencing (ES). Methods: variants. Data were processed using the Genome Analysis Toolkit and American College of Medical Genetics and Genomics-guided pathogenicity analysis was conducted with ANNOVAR and GenomeArc Horizon. Copy-number variation analysis was performed using CNVkit, and variants were classified according to the American College of Medical Genetics and Genomics guidelines. Results: ). The overall diagnostic yield for TS and ES was 85.2% (23/27). Conclusion: This genetic study of clinically diagnosed Bangladeshi RTT participants identifies new genes involved in the etiology of RTT-like phenotypes and expands the phenotypic spectrum of known genes linked to neurodevelopmental disorders.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.773
Threshold uncertainty score0.901

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.019
GPT teacher head0.307
Teacher spread0.288 · 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