Evidence map›Paper›PMID 26037289›Full record

ArticleJournal of clinical laboratory analysis2016

Development of a Novel Urine Alzheimer-Associated Neuronal Thread Protein ELISA Kit and Its Potential Use in the Diagnosis of Alzheimer's Disease.

Lina Ma, Rong Wang, Ying Han, Shuli Sheng, Jianan Zhu, Zhijuan Ji, Zhiwei Zhao, Ziqing Cao, Peichang Wang

Abstract read
In one paragraph

Article in Journal of clinical laboratory analysis, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.1field-weighted citation impact, top 23% of its field
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

11 citing papers in PubMed, 29 citations in OpenAlex.

  1. Article
  2. The China Alzheimer Report 2025.General psychiatry · 2025
    Review
  3. Review
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Urinary AD7c-NTP Evaluates Cognition Impairment and Differentially Diagnoses AD and MCI.American journal of Alzheimer's disease and other dementias
    Article
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

9 authors at 1 institution in 1 country.

Lina MaCentral Laboratory, Xuanwu Hospital, Capital Medical University, Key Laboratory for Neurodegenerative Disease of Ministry of Education, Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, China.
Rong WangCentral Laboratory, Xuanwu Hospital, Capital Medical University, Key Laboratory for Neurodegenerative Disease of Ministry of Education, Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, China.
Ying HanDepartment of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China.
Shuli ShengCentral Laboratory, Xuanwu Hospital, Capital Medical University, Key Laboratory for Neurodegenerative Disease of Ministry of Education, Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, China.
Jianan ZhuShenzhen Anqun Biotech CO., Ltd., Shenzhen, China.
Zhijuan JiCentral Laboratory, Xuanwu Hospital, Capital Medical University, Key Laboratory for Neurodegenerative Disease of Ministry of Education, Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, China.
Zhiwei ZhaoCentral Laboratory, Xuanwu Hospital, Capital Medical University, Key Laboratory for Neurodegenerative Disease of Ministry of Education, Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, China.
Ziqing CaoDepartment of Neurology, Beijing Chaoyanmen Hospital, Beijing, China.
Peichang WangDepartment of Clinical Laboratory, Xuanwu Hospital, Capital Medical University, Beijing, China.
Capital Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAlzheimer's disease (AD) is an age-related chronic degenerative disease that damages the nervous system. A noninvasive and simple method for early detection of AD is extremely important for the diagnosis and prognosis of AD. Thus, we aimed to develop an enzyme-linked immunosorbent assay (ELISA) kit to detect urine Alzheimer-associated neuronal thread protein (AD7C-NTP), and to evaluate its clinical value for the diagnosis of AD.

methodsImmunogenic AD7C-NTP peptide fragments were synthesized by the solid-phase method and used for immunizing mice or rabbits to generate anti-AD7C-NTP antibodies. The urine AD7C-NTP ELISA kit was then established; the generated mouse anti-AD7C-NTP antibody was used as a capture antibody, the biotin-labeled rabbit anti-AD7C-NTP antibody was used as a detection antibody, and avidin labeled by horseradish peroxidase was used as a substrate. The first morning urine specimens of 121 AD patients and 118 age-matched controls were collected, and the urine AD7C-NTP levels were detected by the above ELISA kit.

resultsMouse and rabbit anti-AD7C-NTP antibody ELISA titer was found to be 1:8,000 and 1:32,000, respectively. A single band with a relative molecular mass of 41 kDa was found in human brain specimens by Western blot assay, which was identified as AD7C-NTP antibody. The urine AD7C-NTP concentration of the AD patients was higher than that of the age-matched controls, the sensitivity was 89.3% and the specificity was 84.7%.

conclusionsOur study demonstrated that our newly developed urine AD7C-NTP ELISA kit has suggested potential for diagnosing AD in a Chinese population, suggesting it may be a useful diagnostic kit for detecting early AD.

Indexed as

Alzheimer DiseaseAnimalsEnzyme-Linked Immunosorbent AssayFrontal LobeHippocampusHumansImmunohistochemistryMaleMiceNerve Tissue ProteinsRabbitsReference StandardsSensitivity and SpecificityAD7c-NTP protein, humanNerve Tissue ProteinsAlzheimer-associated neuronal thread proteinAlzheimer diseaseenzyme-linked immunosorbent assayurine

Identifiers

PMID26037289
PMCPMC6807133
OpenAlexW1517756135

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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.