ArticleJournal of Zhejiang University. Science. B2026
Selenocystine-based fluorescence assay combined with structural prediction for functional analysis of cystine transporter variants in cystinuria.
Article in Journal of Zhejiang University. Science. B, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Intelligent biosensing and point-of-care testing: from molecular recognition to decentralized precision care.Journal of Zhejiang University. Science. B · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
objectivesCystine stones account for 1%‒2% of adult and up to 10% of pediatric kidney stones. They result from cystinuria, an autosomal recessive disorder caused by mutations in solute carrier family 3 member 1 (
methodsUsing human embryonic kidney 293 (HEK293) cells transiently co-expressing wild-type or mutant
resultsThe affinity of the SLC3A1/SLC7A9 complex was comparably apparent for selenocystine (Michaelis constant
conclusionsThe integrated approach employed in this work, which combines a sensitive selenocystine fluorescence assay with artificial intelligence (AI)-powered structural analysis, enables the rapid, precise diagnosis of cystinuria variants. This platform is compatible with standard microplate-reader infrastructure and offers potential utility in variant-interpretation pipelines and future genotype-guided therapeutic decision-making, pending prospective clinical validation.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.