ArticleNature methods2024
Multiscale biochemical mapping of the brain through deep-learning-enhanced high-throughput mass spectrometry.
Article in Nature methods, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.
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
34 citing papers in PubMed.
- The lipidomic architecture of the mouse brain.Nature · 2026Article
- Truthful visualizations for mass spectrometry imaging enable high-spatial-resolution interactiveScience advances · 2026Article
- Computational Mass Spectrometry Imaging in the Era of AI.Chemical reviews · 2026Review
- MALDI Mass Spectrometry Imaging in Alzheimer's Disease Lipidomics: Matrix Selection, Spatial Lipid Pathology and Emerging Analytical Strategies.International journal of molecular sciences · 2026Review
- Tissue Heterogeneity-Driven Parallel Acquisition for High-Coverage MS/MS Imaging of Lipids.Angewandte Chemie (International ed. in English) · 2026Article
- Venous Nanoflap Oscillations: Biomechanical Determinants and Hydrodynamic Consequences in the Deep Cerebral Venous System.International journal of molecular sciences · 2026Review
- A lipidomics roadmap: from basic research to societal challenges.Nature communications · 2026Review
- Advances in Functional and Metabolic Imaging for Early Tumor Treatment Response and Resistance Evaluation: A Review.Cancers · 2026Review
- In vivo multimodal neurochemical interfaces for real-time decoding of brain circuit.Nature reviews. Neuroscience · 2026Review
- Mass spectrometry imaging tutorial: From cancer biomarker discovery to clinical applications.Analytica chimica acta · 2026Review
- Mass spectrometry imaging-based explainable machine learning reveals the biochemical landscapes of the mouse brain.Free neuropathology · 2026Article
- Multiscale measurement of brain tissue and cell biomechanics using a mouse model.Biophysics reports · 2025Article
- Towards time-resolved multiscale and multimodal imaging.Npj imaging · 2025Review
- Deciphering the three-dimensional biomolecular distribution in the Alzheimer's disease brain: A multiomic approach integrating immunohistochemistry with MALDI MS imaging.Analytica chimica acta · 2025Article
- Multimodal mass spectrometry imaging for plaque- and region-specific neurolipidomics in Alzheimer's disease mouse models.Nature communications · 2025Article
- Integrating Model-Based Reconstruction and Deep Learning for Accelerating Mass Spectrometry Imaging.Analytical chemistry · 2025Article
- Innovative Application of a Multifunctional Sucrose-Gelatin Hydrogel Matrix in Desorption Electrospray Ionization-Mass Spectrometry Imaging.Analytical chemistry · 2025Article
- Spatial lipidomics reveals demyelination and remyelination dynamics in the mouse brain.Journal of lipid research · 2025Article
- De-MSI: A Deep Learning-Based Data Denoising Method to Enhance Mass Spectrometry Imaging by Leveraging the Chemical Prior Knowledge.Analytical chemistry · 2025Article
- The Future of a Myriad of Accelerated Biodiscoveries Lies in AI-Powered Mass Spectrometry and Multiomics Integration.Journal of mass spectrometry : JMS · 2025Article
Corrections and comments
- Update of
Authors and funding
6 authors.
Funding
Abstract
Spatial omics technologies can reveal the molecular intricacy of the brain. While mass spectrometry imaging (MSI) provides spatial localization of compounds, comprehensive biochemical profiling at a brain-wide scale in three dimensions by MSI with single-cell resolution has not been achieved. We demonstrate complementary brain-wide and single-cell biochemical mapping using MEISTER, an integrative experimental and computational mass spectrometry (MS) framework. Our framework integrates a deep-learning-based reconstruction that accelerates high-mass-resolving MS by 15-fold, multimodal registration creating three-dimensional (3D) molecular distributions and a data integration method fitting cell-specific mass spectra to 3D datasets. We imaged detailed lipid profiles in tissues with millions of pixels and in large single-cell populations acquired from the rat brain. We identified region-specific lipid contents and cell-specific localizations of lipids depending on both cell subpopulations and anatomical origins of the cells. Our workflow establishes a blueprint for future development of multiscale technologies for biochemical characterization of the brain.
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.