Evidence map›Paper›PMID 42547697›Full record

ArticleApplied biochemistry and biotechnology2026

Electrochemical Quantification of Parathyroid Hormone Using an Aptamer-Functionalized Magnetic Nanoparticle System.

Reza Didarian, Almina Gülerman, Veli Cengiz Özalp, Özcan Erel, Nimet Yildirim-Ti̇rgi̇l

Abstract read
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In one paragraph

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

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0citing papers in PubMed
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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

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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

5 authors.

Reza DidarianDepartment of Biomedical Engineering, Ankara Yıldırım Beyazıt University, Ayvalı Mah. Takdir Cad.150 Sk, Ankara, Etlik - Keçiören, Türkiye, 06010, Turkey.
Almina GülermanDepartment of Metallurgy and Materials Engineering, Ankara Yıldırım Beyazıt University, Ankara, Türkiye, Turkey.
Veli Cengiz ÖzalpDepartment of Medical Biology, School of Medicine, Atılım University, Ankara, Türkiye, Turkey.
Özcan ErelDepartment of Biochemistry, Faculty of Medicine, Ankara Yıldırım Beyazıt University, Ankara, Türkiye, Turkey.
Nimet Yildirim-Ti̇rgi̇lDepartment of Biomedical Engineering, Ankara Yıldırım Beyazıt University, Ayvalı Mah. Takdir Cad.150 Sk, Ankara, Etlik - Keçiören, Türkiye, 06010, Turkey. nyildirim.tirgil@aybu.edu.tr.ORCID http://orcid.org/0000-0002-5973-8830

Funding

The Scientific and Technological Research Council of Turkey (TÜBİTAK) 121Z938
6 · The paper itself

Abstract

In this study, we developed a highly sensitive and specific aptamer-based electrochemical biosensor for the quantitative analysis of parathyroid hormone (PTH) for intraoperative parathormone (ioPTH) analysis. By leveraging the intrinsic electrochemical activity of PTH, a direct detection method was first optimized on carbon screen-printed electrodes (SPEs). The biosensor's performance was then significantly enhanced by using aptamer-functionalized magnetic nanoparticles, which selectively captured and enriched the PTH target from complex matrices. The developed method demonstrated a low limit of detection (LOD) of 1.9 pg/mL and a wide linear range of 5-400 pg/mL, validating its high sensitivity and broad applicability for clinical use. The biosensor also exhibited high specificity against common interferents in biological fluids and excellent long-term stability, retaining over 75% of its initial activity for 3 months. Clinical validation using real patient serum samples showed a high correlation of up to 96.72% with a commercial ELISA kit, confirming the biosensor's reliability as a rapid, accurate diagnostic tool. The successful integration of aptamer technology with a practical electrochemical platform offers a promising alternative to conventional immunoassays for real-time, point-of-care PTH monitoring.

Indexed as

AptamerClinical ValidationElectrochemical BiosensorIntraoperative ParathormoneMagnetic NanoparticlesParathyroidectomyPTH

Identifiers

PMID42547697

What OpenQuestion holds

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Registered trials

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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.