Evidence map›Paper›PMID 41425326›Full record

ArticleACS measurement science au2025

A Non-Faradaic Impedimetric Label-Free Immunosensor Integrated with PCCODE Logic for Stratified Monitoring of Post-COVID Conditions.

Georgeena Mathew, Sasya Madhurantakam, Annapoorna Hochihally Ramasubramanya, Jayanth Babu Karnam, Vikram Narayanan Dhamu, Sriram Muthukumar, Shalini Prasad

Abstract read
In one paragraph

Article in ACS measurement science au, 2025. 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

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

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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

7 authors.

Georgeena MathewDepartment of Bioengineering, The University of Texas at Dallas, Richardson, Texas 75080, United States.
Sasya MadhurantakamDepartment of Bioengineering, The University of Texas at Dallas, Richardson, Texas 75080, United States.
Annapoorna Hochihally RamasubramanyaDepartment of Bioengineering, The University of Texas at Dallas, Richardson, Texas 75080, United States.
Jayanth Babu KarnamEnLiSense LLC., 1813 Audubon Pondway, Allen, Texas 75013, United States.
Vikram Narayanan DhamuEnLiSense LLC., 1813 Audubon Pondway, Allen, Texas 75013, United States.
Sriram MuthukumarEnLiSense LLC., 1813 Audubon Pondway, Allen, Texas 75013, United States.ORCID https://orcid.org/0000-0002-8761-7278
Shalini PrasadDepartment of Bioengineering, The University of Texas at Dallas, Richardson, Texas 75080, United States.ORCID https://orcid.org/0000-0002-2404-3801

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 pandemic has presented significant challenges for the effectiveness of existing diagnostic tools in detecting and monitoring infections. Currently, there is an increased emphasis on the potential challenges faced by individuals during their postrecovery phase. The impact of post-COVID conditions (PCC) has substantially influenced perspectives on disease management, fostering a positive trend toward personal healthcare. Here, we report a ZnO-modified, non-Faradaic impedimetric biosensor for the rapid detection of TRAIL and D-dimer across clinically relevant ranges. The dual-analyte platform demonstrated great sensitivity (LOD: 3.4 pg/mL for TRAIL, 8.9 ng/mL for D-dimer), with high specificity in human plasma. Optimized surface chemistry and impedance analysis enabled reliable signal acquisition from 5 μL samples in 5 min. Beyond detection, we introduce the PCCODE (Post-COVID Co-dysregulation Evaluator) threshold-based classifier model using quantified concentration output values-TRAIL <50 pg/mL, D-dimer >1000 ng/mL-to encode biomarker signals in four binary states. This logic-driven system was constructed using exogenously spiked plasma samples and validated through signal-mapped heatmaps, allowing stratification of healthy, inflammation, immune dysregulation, and post-COVID categories. Together, the biosensor and classifier framework enable real-time, mechanism-informed stratification of PCC, marking a significant advance toward point-of-care diagnostics.

Indexed as

D-dimerlabel-free immunosensornon-faradaic electrochemical sensingpost-COVID conditionsthreshold-based classifier logicTRAIL

Identifiers

PMID41425326
PMCPMC12715731

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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.