In one paragraphArticle in medRxiv : the preprint server for health sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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 registryThe 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 literatureWho cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
4 · The recordCorrections and comments
5 · Who and what moneyAuthors and funding
11 authors.
Xinyi LiCenter for Studies of Addiction, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia PA.ORCID 0000-0003-3136-4811 Gene-Jack WangNational Institute of Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda MD.ORCID 0000-0002-5017-9905 Natasha GiddensDivision of Child and Adolescent Psychiatry, Donald and Barbara Zucker School of Medicine, Hofstra University, Glen Oaks, NY, USA.ORCID 0000-0003-0368-1780 Melanie SchwandtNational Institute of Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda MD.ORCID 0000-0002-8355-4900 Nancy DiazgranadosNational Institute of Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda MD.ORCID 0000-0002-7415-8455 Kevin G LynchCenter for Studies of Addiction, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia PA.ORCID 0000-0002-0426-0323 Nora D VolkowNational Institute of Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda MD.ORCID 0000-0001-6668-0908 Zhenhao ShiCenter for Studies of Addiction, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia PA.ORCID 0000-0001-5697-2034 Corinde E WiersCenter for Studies of Addiction, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia PA.ORCID 0000-0002-2934-8794 Funding
Ketone-sup before Pub: Effects of ketone supplementation on brain energetics and alcohol consumption in alcohol use disorderR01AA031570 · NIAAA · UNIVERSITY OF PENNSYLVANIA · PI Corinde E Wiers · 2025 to 2026
$1.1MMultivariate Modeling of the Neural Mechanisms of Treatment Response in Opioid AddictionK01DA051709 · NIDA · UNIVERSITY OF PENNSYLVANIA · PI SHI, ZHENHAO · 2021 to 2025
$916kModulation of alcohol sensitivity and alcohol tolerance by exogenous ketones in humansR33AA031088 · NIAAA · UNIVERSITY OF PENNSYLVANIA · PI Ravi Prakash Reddy Nanga, Corinde E Wiers · 2026 to 2026
$796kModulation of alcohol sensitivity and alcohol tolerance by exogenous ketones in humansR21AA031088 · NIAAA · UNIVERSITY OF PENNSYLVANIA · PI NANGA, RAVI PRAKASH REDDY, WIERS, CORINDE E · 2024 to 2025
$421kKetone supplementation as an intervention to alleviate alcohol withdrawal and improve brain energetics in Alcohol Use DisorderR21AA031337 · NIAAA · UNIVERSITY OF PENNSYLVANIA · PI NANGA, RAVI PRAKASH REDDY, WIERS, CORINDE E · 2024 to 2025
$376kThe effects of ketogenic diet on alcohol intoxicationK99AA031746 · NIAAA · UNIVERSITY OF PENNSYLVANIA · PI Xinyi Li · 2025 to 2026
$231kNIAAA NIH HHS K99 AA031746NIAAA NIH HHS R01 AA031570NIAAA NIH HHS R21 AA031088NIAAA NIH HHS R21 AA031337NIAAA NIH HHS R33 AA031088NIDA NIH HHS K01 DA051709
6 · The paper itselfAbstract
Previous studies have linked opioid use to altered metabolic profiles, but findings have been inconsistent and mechanisms remain unclear. One potential mechanism involves increased adiposity, leading to chronic low-grade inflammation that elevates metabolic risk. Here, we examined metabolic profiles in individuals with opioid use disorder (OUD) and matched non-OUD controls, focusing on the sequential mediating roles of BMI and inflammation. Data from individuals with OUD (n=281) and non-OUD (n=246) were drawn from a natural history screening protocol from the National Institute on Alcohol Abuse and Alcoholism intramural program. Groups were matched on age, sex, race, ethnicity, socioeconomic status, and education via propensity score matching. Metabolic measures included BMI, blood glucose, hemoglobin A1c (HbA1c), and lipid profiles, with lipid imbalance indexed by the atherogenic index of plasma (AIP). Inflammatory markers included C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR). Individuals with OUD had significantly higher BMI (F
Indexed as
body weight gaininflammationmetabolismnutritionopioid use disorder
Identifiers
PMID42064932
PMCPMC13127524
What Socratic holds
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