Article in Pharmaceuticals (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact, top 87% 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
1 citing paper in PubMed, 0 citations in OpenAlex.
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
14 authors at 2 institutions in 2 countries.
Alessandra MancaLaboratory of Clinical Pharmacology and Pharmacogenetics, Department of Medical Sciences, University of Turin, Amedeo di Savoia Hospital, Corso Svizzera, 164, 10149 Turin, Italy.ORCID 0000-0002-8540-6709
Amedeo De NicolòLaboratory of Clinical Pharmacology and Pharmacogenetics, Department of Medical Sciences, University of Turin, Amedeo di Savoia Hospital, Corso Svizzera, 164, 10149 Turin, Italy.ORCID 0000-0002-5973-9948
Elisa Delia De VivoLaboratory of Clinical Pharmacology and Pharmacogenetics, Department of Medical Sciences, University of Turin, Amedeo di Savoia Hospital, Corso Svizzera, 164, 10149 Turin, Italy.ORCID 0000-0003-4826-7604
Micol FerraraUnit of Infectious Diseases, Department of Medical Sciences, University of Turin, Amedeo di Savoia Hospital, 10149 Turin, Italy.ORCID 0000-0003-0377-9630
Sharon OhSan Diego Division of Infectious Diseases and Global Public Health, University of California San Diego, La Jolla, CA 92037, USA.ORCID 0009-0001-8172-8276
Sahar KhaliliSan Diego Division of Infectious Diseases and Global Public Health, University of California San Diego, La Jolla, CA 92037, USA.
Niamh HigginsSan Diego Division of Infectious Diseases and Global Public Health, University of California San Diego, La Jolla, CA 92037, USA.
Robert G DeissSan Diego Division of Infectious Diseases and Global Public Health, University of California San Diego, La Jolla, CA 92037, USA.
Stefano BonoraUnit of Infectious Diseases, Department of Medical Sciences, University of Turin, Amedeo di Savoia Hospital, 10149 Turin, Italy.
Jessica CusatoLaboratory of Clinical Pharmacology and Pharmacogenetics, Department of Medical Sciences, University of Turin, Amedeo di Savoia Hospital, Corso Svizzera, 164, 10149 Turin, Italy.ORCID 0000-0003-1977-9694
Alice PalermitiLaboratory of Clinical Pharmacology and Pharmacogenetics, Department of Medical Sciences, University of Turin, Amedeo di Savoia Hospital, Corso Svizzera, 164, 10149 Turin, Italy.ORCID 0000-0003-0860-280X
Jacopo MulaLaboratory of Clinical Pharmacology and Pharmacogenetics, Department of Medical Sciences, University of Turin, Amedeo di Savoia Hospital, Corso Svizzera, 164, 10149 Turin, Italy.ORCID 0000-0002-9264-0114
Sara GianellaSan Diego Division of Infectious Diseases and Global Public Health, University of California San Diego, La Jolla, CA 92037, USA.
Antonio D'AvolioLaboratory of Clinical Pharmacology and Pharmacogenetics, Department of Medical Sciences, University of Turin, Amedeo di Savoia Hospital, Corso Svizzera, 164, 10149 Turin, Italy.ORCID 0000-0002-1321-4126
Ospedale Amedeo di Savoia · ITUniversity of California San Diego · US
Funding
UC San Diego Clinical and Translational Research InstituteUL1TR001442 · NCATS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI FIRESTEIN, GARY S, HOGARTH, MICHAEL · 2015 to 2024
$88.3M
VirologyP30AI036214 · NIAID · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI David Mitchell Smith · 1994 to 2026
$78.4M
HOPE - HIV Obstruction by Programmed EpigeneticsUM1AI164559 · NIAID · J. DAVID GLADSTONE INSTITUTES · PI Lishomwa C Ndhlovu, Melanie Maria Ott · 2021 to 2026
$32.2M
Project-004P01AI169609 · NIAID · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI David Mitchell Smith · 2022 to 2026
$10.6M
The HIV-associated Opioid Micro-Environment (HOME) ProjectDP2DA051915 · NIDA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI GIANELLA WEIBEL, SARA · 2020 to 2020
backgroundOpioids are considered the cornerstone of pain management: they show good efficacy as a first-line therapy for moderate to severe cancer pain. Since pharmacokinetic/pharmacodynamic information about the tissue-specific effect and toxicity of opioids is still scarce, their quantification in post-mortem autoptic specimens could give interesting insights.
methodsWe describe an ultra-high-performance liquid chromatography coupled with tandem mass spectrometry method for the simultaneous quantification of methadone, morphine, oxycodone, hydrocodone, oxymorphone, hydromorphone and fentanyl in several tissues: liver, brain, kidney, abdominal adipose tissue, lung and blood plasma. The presented method has been applied on 28 autoptic samples from different organs obtained from four deceased PLWH who used opioids for palliative care during terminal disease.
resultsSample preparation was based on tissue weighing, disruption, sonication with drug extraction medium and a protein precipitation protocol. The extracts were then dried, reconstituted and injected onto the LX50 QSight 220 (Perkin Elmer, Milan, Italy) system. Separation was obtained by a 7 min gradient run at 40 °C with a Kinetex Biphenyl 2.6 µm, 2.1 × 100 mm. Concerning the analyzed samples, higher opioids concentrations were observed in tissues than in plasma. Particularly, O-MOR and O-COD showed higher concentrations in kidney and liver than other tissues (>15-20 times greater) and blood plasma (>100 times greater).
conclusionsResults in terms of linearity, accuracy, precision, recovery and matrix effect fitted the recommendations of FDA and EMA guidelines, and the sensitivity was high enough to allow successful application on human autoptic specimens from an ethically approved clinical study, confirming its eligibility for post-mortem pharmacological/toxicological studies.
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.
A Novel UHPLC-MS/MS Method for the Quantification of Seven Opioids in Different Human Tissues. · full record | OpenQuestion