Evidence map›Paper›PMID 39194620›Full record

ReviewBiosensors2024

Needle-Shaped Biosensors for Precision Diagnoses: From Benchtop Development to In Vitro and In Vivo Applications.

Ruier Xue, Fei Deng, Tianruo Guo, Alexander Epps, Nigel H Lovell, Mohit N Shivdasani

Abstract readReview
In one paragraph

Review in Biosensors, 2024. 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

6 authors.

Ruier XueGraduate School of Biomedical Engineering, UNSW Sydney, Sydney, NSW 2052, Australia.ORCID 0009-0007-9956-1981
Fei DengGraduate School of Biomedical Engineering, UNSW Sydney, Sydney, NSW 2052, Australia.ORCID 0000-0002-5606-0278
Tianruo GuoGraduate School of Biomedical Engineering, UNSW Sydney, Sydney, NSW 2052, Australia.ORCID 0000-0001-6348-6771
Alexander EppsGraduate School of Biomedical Engineering, UNSW Sydney, Sydney, NSW 2052, Australia.
Nigel H LovellGraduate School of Biomedical Engineering, UNSW Sydney, Sydney, NSW 2052, Australia.ORCID 0000-0003-1637-1079
Mohit N ShivdasaniGraduate School of Biomedical Engineering, UNSW Sydney, Sydney, NSW 2052, Australia.ORCID 0000-0002-0692-4971

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To achieve the accurate recognition of biomarkers or pathological characteristics within tissues or cells, in situ detection using biosensor technology offers crucial insights into the nature, stage, and progression of diseases, paving the way for enhanced precision in diagnostic approaches and treatment strategies. The implementation of needle-shaped biosensors (N-biosensors) presents a highly promising method for conducting in situ measurements of clinical biomarkers in various organs, such as in the brain or spinal cord. Previous studies have highlighted the excellent performance of different N-biosensor designs in detecting biomarkers from clinical samples in vitro. Recent preclinical in vivo studies have also shown significant progress in the clinical translation of N-biosensor technology for in situ biomarker detection, enabling highly accurate diagnoses for cancer, diabetes, and infectious diseases. This article begins with an overview of current state-of-the-art benchtop N-biosensor designs, discusses their preclinical applications for sensitive diagnoses, and concludes by exploring the challenges and potential avenues for next-generation N-biosensor technology.

Indexed as

Biosensing TechniquesAnimalsBiomarkersHumansPrecision MedicineBiomarkersclinical biomarkerscomplex clinical samplesin situ detectionneedle-shaped biosensorprecision diagnosis

Identifiers

PMID39194620
PMCPMC11353061

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.