Evidence map›Paper›PMID 42299341›Full record

ArticleFrontiers in genetics2026

Identification of novel

Yao Peng, Yi-Lin Sang, Wu Zhu, Ning Zhang, Yi Sun, Ge Lin, Guang-Xiu Lu, Yue-Qiu Tan, Juan Du, Fu-Yan Wang and 1 more

Abstract read
In one paragraph

Article in Frontiers in genetics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Yao Peng *Hunan Guangxiu Hospital Affiliated with Hunan Normal University, Hunan Normal University Health Science Center, Changsha, Hunan, China.
Yi-Lin Sang *Department of Immunology, Xiangya School of Basic Medical Science, Central South University, Changsha, Hunan, China.
Wu ZhuDepartment of Immunology, Xiangya School of Basic Medical Science, Central South University, Changsha, Hunan, China.
Ning ZhangDepartment of Immunology, Xiangya School of Basic Medical Science, Central South University, Changsha, Hunan, China.
Yi SunInstitute of Reproductive and Stem Cell Engineering, NHC Key Laboratory of Human Stem Cell and Reproductive Engineering, Xiangya School of Basic Medical Sciences, Central South University, Changsha, Hunan, China.
Ge LinHunan Guangxiu Hospital Affiliated with Hunan Normal University, Hunan Normal University Health Science Center, Changsha, Hunan, China.
Guang-Xiu LuHunan Guangxiu Hospital Affiliated with Hunan Normal University, Hunan Normal University Health Science Center, Changsha, Hunan, China.
Yue-Qiu TanHunan Guangxiu Hospital Affiliated with Hunan Normal University, Hunan Normal University Health Science Center, Changsha, Hunan, China.
Juan DuHunan Guangxiu Hospital Affiliated with Hunan Normal University, Hunan Normal University Health Science Center, Changsha, Hunan, China.
Fu-Yan WangDepartment of Immunology, Xiangya School of Basic Medical Science, Central South University, Changsha, Hunan, China.
Wen-Bin HeHunan Guangxiu Hospital Affiliated with Hunan Normal University, Hunan Normal University Health Science Center, Changsha, Hunan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Severe combined immunodeficiency (SCID) is one of the most severe forms of primary immunodeficiency. Methods: Whole-Exome Sequencing was performed on five individuals from the three families. A series of Results: We identified seven Conclusion: This study identified seven

Indexed as

functional analysesjak3pathogenicity assessmentsevere combined immunodeficiencyvariants of uncertain significance

Identifiers

PMID42299341
PMCPMC13265061

What OpenQuestion holds

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Registered trials

None linked

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.