Evidence map›Paper›PMID 36339041›Full record

ArticleFrontiers in chemistry2022

Rapid magnetic separation: An immunoassay platform for the SERS-based detection of subarachnoid hemorrhage biomarkers.

Ying Wang, Jingyi Sun, Peng Zhao, Hui Yi, Hui Yuan, Mingfeng Yang, Baoliang Sun, Fengyuan Che

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in chemistry, 2022. 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
0.2field-weighted citation impact, top 43% 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

0 citing papers in PubMed, 2 citations in OpenAlex.

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

8 authors at 3 institutions in 1 country.

Ying WangLinyi People's Hospital, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, Shandong, China.
Jingyi SunShandong Provincial Hospital, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, Shandong, China.
Peng ZhaoLinyi People's Hospital, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, Shandong, China.
Hui YiLinyi People's Hospital, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, Shandong, China.
Hui YuanSecond Affiliated Hospital, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, Shandong, China.
Mingfeng YangSecond Affiliated Hospital, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, Shandong, China.
Baoliang SunLinyi People's Hospital, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, Shandong, China.
Fengyuan CheLinyi People's Hospital, Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, Shandong, China.
Shandong First Medical University · CNLinyi People's Hospital · CNShandong Provincial Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The blood-brain barrier (BBB) is of vital importance to the progression and prognosis of subarachnoid hemorrhage (SAH). The construction of a simple, sensitive, and accurate detection assay for measuring the biomarkers associated with BBB injury is still an urgent need owing to the complex pathogenesis of SAH and low expression levels of pathological molecules. Herein, we introduced surface-enhanced Raman scattering (SERS) label-embedded Fe

Indexed as

biosensorsblood-brain barrierdouble detectionsubarachnoid hemorrhagesurface enhance Raman scattering

Identifiers

PMID36339041
PMCPMC9634124
OpenAlexW4306970014

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.