Evidence map›Paper›PMID 33939923›Full record

ArticleACS chemical neuroscience2021

Integration of Mass Spectrometry Imaging and Machine Learning Visualizes Region-Specific Age-Induced and Drug-Target Metabolic Perturbations in the Brain.

Theodosia Vallianatou, Reza Shariatgorji, Anna Nilsson, Maria Karlgren, Heather Hulme, Elva Fridjonsdottir, Per Svenningsson, Per E Andrén

Open access · hybridAbstract read
In one paragraph

Article in ACS chemical neuroscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
3.0field-weighted citation impact, top 8% 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

18 citing papers in PubMed, 34 citations in OpenAlex.

  1. Anabolic androgenic steroids induce distinct monoaminergic and lipidomic alterations in the male rat brain.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2026
    Article
  2. Review
  3. Article
  4. Review
  5. Broadband Collision-Induced Dissociation Mass Spectrometry Imaging.Journal of the American Society for Mass Spectrometry · 2025
    Article
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  7. Article
  8. Article
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  11. Review
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  13. Article
  14. Emerging Computational Methods in Mass Spectrometry Imaging.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2022
    Review
  15. Article
  16. Article
  17. Review
  18. Article
4 · The record

Corrections and comments

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.

Theodosia VallianatouMedical Mass Spectrometry Imaging, Department of Pharmaceutical Biosciences, Biomedical Centre 591, Uppsala University, SE-75124 Uppsala, Sweden.ORCID 0000-0002-1477-7756
Reza ShariatgorjiMedical Mass Spectrometry Imaging, Department of Pharmaceutical Biosciences, Biomedical Centre 591, Uppsala University, SE-75124 Uppsala, Sweden.ORCID 0000-0001-9484-0921
Anna NilssonMedical Mass Spectrometry Imaging, Department of Pharmaceutical Biosciences, Biomedical Centre 591, Uppsala University, SE-75124 Uppsala, Sweden.
Maria KarlgrenDepartment of Pharmacy, Uppsala Drug Optimization and Pharmaceutical Profiling (UDOPP), Biomedical Centre 580, Uppsala University, SE-75123 Uppsala, Sweden.
Heather HulmeMedical Mass Spectrometry Imaging, Department of Pharmaceutical Biosciences, Biomedical Centre 591, Uppsala University, SE-75124 Uppsala, Sweden.
Elva FridjonsdottirMedical Mass Spectrometry Imaging, Department of Pharmaceutical Biosciences, Biomedical Centre 591, Uppsala University, SE-75124 Uppsala, Sweden.
Per SvenningssonSection of Neurology, Department of Clinical Neuroscience, Karolinska Institutet, SE-17177 Stockholm, Sweden.
Per E AndrénMedical Mass Spectrometry Imaging, Department of Pharmaceutical Biosciences, Biomedical Centre 591, Uppsala University, SE-75124 Uppsala, Sweden.ORCID 0000-0002-4062-7743
Uppsala University · SEKarolinska Institutet · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Detailed metabolic imaging of specific brain regions in early aging may expose pathophysiological mechanisms and indicate effective neuropharmacological targets in the onset of cognitive decline. Comprehensive imaging of brain aging and drug-target effects is restricted using conventional methodology. We simultaneously visualized multiple metabolic alterations induced by normal aging in specific regions of mouse brains by integrating Fourier-transform ion cyclotron resonance mass spectrometry imaging and combined supervised and unsupervised machine learning models. We examined the interplay between aging and the response to tacrine-induced acetylcholinesterase inhibition, a well-characterized therapeutic treatment against dementia. The dipeptide carnosine (β-alanyl-l-histidine) and the vitamin α-tocopherol were significantly elevated by aging in different brain regions. l-Carnitine and acetylcholine metabolism were found to be major pathways affected by aging and tacrine administration in a brain region-specific manner, indicating altered mitochondrial function and neurotransmission. The highly interconnected hippocampus and retrosplenial cortex displayed different age-induced alterations in lipids and acylcarnitines, reflecting diverse region-specific metabolic effects. The subregional differences observed in the hippocampal formation of several lipid metabolites demonstrate the unique potential of the technique compared to standard mass spectrometry approaches. An age-induced increase of endogenous antioxidants, such as α-tocopherol, in the hippocampus was detected, suggesting an augmentation of neuroprotective mechanisms in early aging. Our comprehensive imaging approach visualized heterogeneous age-induced metabolic perturbations in mitochondrial function, neurotransmission, and lipid signaling, not always attenuated by acetylcholinesterase inhibition.

Indexed as

Pharmaceutical PreparationsAnimalsBrainMachine LearningMass SpectrometryMiceTacrinePharmaceutical PreparationsTacrineAcetylcholineagingbrain metabolomicslipidsmass spectrometry imagingtacrine

Identifiers

PMID33939923
PMCPMC8291481
OpenAlexW3159110533

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.