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[Mutation spectrum of phenylalanine hydroxylase gene in patients with phenylketonuria in Tianjin and surrounding areas of Northern China].

2010· article· en· W2406841880 on OpenAlexaboutno aff
Song Li, Li-heng Dang, Yingtao Meng, Bojing Fu

Bibliographic record

VenuePubMed · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolism and Genetic Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsPhenylalanine hydroxylaseExonGeneticsMissense mutationIntronSingle-strand conformation polymorphismGeneMutationRNA splicingBiologyGene mutationDenaturing high performance liquid chromatographyMolecular biologyPhenylalanineRNAAmino acid

Abstract

fetched live from OpenAlex

OBJECTIVE: To investigate the characteristics of the phenylalanine hydroxylase (PAH) gene mutations in patients with phenylketonuria (PKU) in Tianjin and surrounding area, in order to provide basic information for genetic counseling and prenatal gene diagnosis. METHODS: All of the 13 exons and flanking introns of the PAH gene from 99 patients with PKU were amplified by polymerase chain reaction and analyzed by single strand conformation polymorphism (SSCP), denaturing high performance liquid chromatography (DHPLC) and DNA sequencing. RESULTS: Mutations were found in all exons or flanking introns of the PAH gene except for exons 9 and 13. A total of 41 different mutations were identified which corresponded to 93.94% (186/198) of the PAH alleles, including 22 missense mutations (53.6%), 7 nonsense mutations (17.1%), 9 splicing junction mutations(22.0%), and 3 deletion mutations (7.3%). Six novel mutations (IVS3nt+1g--> a, A165D, Q301X, G344D, P362L and R413G) were identified and another 6 mutations (S16fsdelCT, R71H, IVS5nt+1g--> a, G239S, R243X and R261X) were reported in Chinese population for the first time according to the databases from http://www.pahdb.mcgill.ca. The most common mutations included 243Q (36/198,18.18%), V399V (22/198, 11.1%), R111X (19/198, 9.6%), E6nt-96A--> g (18/198, 9.1%), R413P (15/198, 7.6%) and Y356X (13/198, 6.6%). In addition, 4 silent mutations (except V399V) in exons and 8 variations in introns were found in this study. The IVS1nt+40t--> g and IVS10nt-31g--> a were confirmed as novel variations by international PAH databases and IVS5nt-54g--> a was the first report in China. CONCLUSION: The frequencies of six common mutations were close to that in Beijing area of China, but it was different in sequence. The extensive mutation spectrum of the PAH gene showed higher heterogeneity in Tianjin and surrounding areas of Northern China comparing with other reports. According to this report, exons 7 and 11 are the hot spots and should be detected first for PAH gene quick diagnosis in this area, then comes exons 3, 6 and 12, and finally exons 5, 10 and others.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
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 head0.002
GPT teacher head0.169
Teacher spread0.167 · 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".

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Citations2
Published2010
Admission routes1
Has abstractyes

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