ArticleMolecular biology reports2023
Mass Spectrometry based identification of site-specific proteomic alterations and potential pathways underlying the pathophysiology of schizophrenia.
Article in Molecular biology reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed, 4 citations in OpenAlex.
- Machine learning-based predictive models and subtypes patterns in peripheral blood of schizophrenia based on a machine learning computational framework.Schizophrenia (Heidelberg, Germany) · 2026Article
- Protein Kinase Expression of the AKT/mTOR Signaling Pathway in Peripheral Mononuclear Cells of Schizophrenia Patients: A Pilot Study.NeuroSci · 2025Article
- Multi-omics identification and validation of oxidative phosphorylation-related hub genes in schizophrenia.Frontiers in genetics · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
Abstract
backgroundSchizophrenia (SZ) is a complex multifactorial disorder that affects 1% of the population worldwide with no available effective treatment. Although proteomic alterations are reported in SZ however proteomic expression aberrations among different brain regions are not fully determined. Therefore, the present study aimed spatial differential protein expression profiling of three distinct regions of SZ brain and identification of associated affected biological pathways in SZ progression. METHODS AND
resultsComparative protein expression profiling of three distinct autopsied human brain regions (i.e., substantia nigra, hippocampus and prefrontal cortex) of SZ was performed with respective healthy controls. Using two-dimensional electrophoresis (2DE)-based nano liquid chromatography tandem mass spectrometry (Nano-LC MS /MS) analysis, 1443 proteins were identified out of which 58 connote to be significantly dysregulated, representing 26 of substantia nigra,14 of hippocampus and 18 of prefrontal cortex. The 58 differentially expressed proteins were further analyzed using Ingenuity pathway analysis (IPA). The IPA analysis provided protein-protein interaction networks of several proteins including nuclear factor kappa-light-chain-enhancer of activated B cells (NF-kb), extracellular signal regulated kinases 1/2 (ERK1/2), alpha serine / Threonine-protein kinase (AKT1), cellular tumor antigen p53 (TP53) and amyloid precursor protein (APP), holding prime positions in networks and interacts with most of the identified proteins and their closely interacting partners.
conclusionThese findings provide conceptual insights of novel SZ related pathways and the cross talk of co and contra regulated proteins. This spatial proteomic analysis will further broaden the conceptual framework for schizophrenia research in future.
Indexed as
Identifiers
What Socratic 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 Socratic graph.