ReviewForensic sciences research2024
How new nanotechnologies are changing the opioid analysis scenery? A comparison with classical analytical methods.
Review in Forensic sciences research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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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.
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.
Who cites it
0 citing papers in PubMed, 4 citations in OpenAlex.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Opioids such as heroin, fentanyl, raw opium, and morphine have become a serious threat to the world population in the recent past, due to their increasing use and abuse. The detection of these drugs in biological samples is usually carried out by spectroscopic and/or chromatographic techniques, but the need for quick, sensitive, selective, and low-cost new analytical tools has pushed the development of new methods based on selective nanosensors, able to meet these requirements. Modern sensors, which utilize "next-generation" technologies like nanotechnology, have revolutionized drug detection methods, due to easiness of use, their low cost, and their high sensitivity and reliability, allowing the detection of opioids at trace levels in raw, pharmaceutical, and biological samples (e.g
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Registered trials
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.