ArticleScientific reports2026
Deep learning analysis of particle content in extracted slow-release morphine: longer boiling reduces large fragments while retaining morphine extraction.
Article in Scientific reports, 2026. 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
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.
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.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionInjecting drug users often extract morphine from slow-release oral tablets, potentially leading to harmful particle contamination upon injection. This study assesses the efficiency of morphine extraction and particle content of filtrates produced by various methods employed by drug users in Trondheim, Norway. The findings provide important insights that can inform harm-reduction services and healthcare providers in efforts to reduce injection-related morbidity among people who already inject drugs.
methodsFour extraction methods were evaluated using 60 mg Dolcontin tablets: Method A (no coating removal, 3-minute boiling), Method B (coating removal, crushing, 3-minute boiling), Method C (coating removal, 3-minute boiling), and Method D (coating removal, 10-minute boiling). Resulting solutions were filtered using cotton balls, and morphine content was quantified using LC-MS/MS. Particle content of filtrates was analyzed using slide scanning, deep learning-based particle segmentation, and QuPath image analysis software.
resultsMorphine recovery ranged from 81.2% (Method D) to 91.3% (Method B). Method A yielded a significant presence of small insoluble particles (<100 μm), while Method B yielded the highest density of the largest particles (>500 μm). Method C exhibited the highest density of medium-sized particles (100-500 μm). Method D generated the fewest particles across all size categories.
conclusionThe extraction methods used by injecting drug users result in significant variability in morphine recovery and particle content of filtrates. Method D (10-minute vs. 3-minute boiling) demonstrated the highest efficiency in particle reduction, with only 10% less morphine recovery. Lack of coat removal significantly increases the number of primarily small (<100 μm) fragments. These findings highlight the importance of evidence-based harm-reduction measures to mitigate risks associated with injecting tablet-derived solutions. The results may support harm-reduction counselling and service design aimed at reducing particulate exposure and related complications, without endorsing or facilitating drug use.
Indexed as
Identifiers
What OpenQuestion holds
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.