Article in Addiction biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.5field-weighted citation impact, top 33% 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
4 citing papers in PubMed, 2 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
8 authors at 2 institutions in 1 country.
Constanza Garcia-KellerDepartment of Neurosciences, Medical University of South Carolina, Charleston, South Carolina, USA.ORCID 0000-0002-3141-9571
Madeline HohmeisterDepartment of Neurosciences, Medical University of South Carolina, Charleston, South Carolina, USA.
Kailyn SeidlingDepartment of Neurosciences, Medical University of South Carolina, Charleston, South Carolina, USA.
Lauren BeloateDepartment of Neurosciences, Medical University of South Carolina, Charleston, South Carolina, USA.
Vivian ChiomaDepartment of Neurosciences, Medical University of South Carolina, Charleston, South Carolina, USA.
Sade SpencerDepartment of Pharmacology, Medical Discovery Team on Addiction, University of Minnesota, Minneapolis, Minnesota, USA.ORCID 0000-0001-8663-9056
Peter KalivasDepartment of Neurosciences, Medical University of South Carolina, Charleston, South Carolina, USA.ORCID 0000-0001-9487-0119
Daniela NeuhoferDepartment of Neurosciences, Medical University of South Carolina, Charleston, South Carolina, USA.ORCID 0000-0001-5726-7855
Medical University of South Carolina · USUniversity of Minnesota · US
Funding
COCA: Project 4. Neurocircuit Strategy to Decrease Cocaine Cue ReactivityP50DA046373 · NIDA · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI KALIVAS, PETER W · 2019 to 2023
$9.9M
GLUTAMATE AND CRAVING FOR COCAINER01DA012513 · NIDA · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI KALIVAS, PETER W · 2000 to 2024
$7.5M
OPIOIDS, AMPHETAMINE &COCAIN IN DRUG ABUSER01DA003906 · NIDA · WASHINGTON STATE UNIVERSITY · PI KALIVAS, PETER W · 1985 to 2019
$3.6M
COCAINE, OPIOIDS AND DRUG ABUSER37DA003906 · NIDA · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI KALIVAS, PETER W · 2000 to 2009
$3.0M
Circuit Mechanisms for Conditioned Stress Regulation of AddictionR00DA047426 · NIDA · MEDICAL COLLEGE OF WISCONSIN · PI GARCIA KELLER, CONSTANZA · 2022 to 2024
$747k
Circuit Mechanisms for Conditioned Stress Regulation of AddictionK99DA047426 · NIDA · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI GARCIA KELLER, CONSTANZA · 2019 to 2021
$439k
The role of ventral pallidal cannabinoid and opioid signaling in cross-sensitization between THC and cue-induced heroin seekingR21DA048337 · NIDA · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI NEUHOFER, DANIELA · 2020 to 2021
Drugs of abuse induce cell type-specific adaptations in D1- and D2-medium spiny neurons (MSNs) in the nucleus accumbens core (NAcore) that can bias signalling towards D1-MSNs and enhance relapse vulnerability. Whether Δ
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.