Evidence map›Paper›PMID 38582770›Full record

ArticleScientific reports2024

Machine learning-enhanced drug testing for simultaneous morphine and methadone detection in urinary biofluids.

Mohammad Mehdi Habibi, Mitra Mousavi, Maryam Shekofteh-Gohari, Anita Parsaei-Khomami, Monireh-Alsadat Hosseini, Elnaz Haghani, Razieh Salahandish, Jahan B Ghasemi

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
2.9field-weighted citation impact, top 9% 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

3 citing papers in PubMed, 14 citations in OpenAlex.

  1. Interpol review of forensic drug chemistry, 2022-2025.Forensic science international. Synergy · 2026
    Review
  2. Review
  3. 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

8 authors at 2 institutions in 2 countries.

Mohammad Mehdi HabibiSchool of Chemistry, University College of Science, University of Tehran, P.O. Box 14155-6455, Tehran, Iran.
Mitra MousaviSchool of Chemistry, University College of Science, University of Tehran, P.O. Box 14155-6455, Tehran, Iran.
Maryam Shekofteh-GohariSchool of Chemistry, University College of Science, University of Tehran, P.O. Box 14155-6455, Tehran, Iran.
Anita Parsaei-KhomamiSchool of Chemistry, University College of Science, University of Tehran, P.O. Box 14155-6455, Tehran, Iran.
Monireh-Alsadat HosseiniSchool of Chemistry, University College of Science, University of Tehran, P.O. Box 14155-6455, Tehran, Iran.
Elnaz HaghaniLaboratory of Advanced Biotechnologies for Health Assessments (Lab-HA), Lassonde School of Engineering, York University, Toronto, ON, M3J 1P3, Canada.
Razieh SalahandishLaboratory of Advanced Biotechnologies for Health Assessments (Lab-HA), Lassonde School of Engineering, York University, Toronto, ON, M3J 1P3, Canada. raziehs@yorku.ca.
Jahan B GhasemiSchool of Chemistry, University College of Science, University of Tehran, P.O. Box 14155-6455, Tehran, Iran. Jahan.ghasemi@ut.ac.ir.
University of Tehran · IRYork University · CA

Funding

Iran National Science Foundation 4012775
6 · The paper itself

Abstract

The simultaneous identification of drugs has considerable difficulties due to the intricate interplay of analytes and the interference present in biological matrices. In this study, we introduce an innovative electrochemical sensor that overcomes these hurdles, enabling the precise and simultaneous determination of morphine (MOR), methadone (MET), and uric acid (UA) in urine samples. The sensor harnesses the strategically adapted carbon nanotubes (CNT) modified with graphitic carbon nitride (g-C

Indexed as

NanocompositesNanotubes, CarbonElectrochemical TechniquesMorphineReproducibility of ResultsUric AcidMorphineNanotubes, CarbonUric AcidDrug analysisFFT-voltametryg-C3N4-CNT nanocompositePLS method

Identifiers

PMID38582770
PMCPMC10998919
OpenAlexW4394010886

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.