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Record W4281702791 · doi:10.1503/jpn.210124

The functional and structural associations of aberrant microglial activity in major depressive disorder

2022· article· en· W4281702791 on OpenAlexafffundvenue
Jasmine D. Cakmak, Linshan Liu, Stefan E. Poirier, Betsy Schaefer, Raju Poolacherla, Amer M. Burhan, Priyadharshini Sabesan, Keith St. Lawrence, Jean Théberge, Justin W. Hicks, Elizabeth Finger, Lena Palaniyappan, Udunna Anazodo

Bibliographic record

VenueJournal of Psychiatry and Neuroscience · 2022
Typearticle
Languageen
FieldNeuroscience
TopicTryptophan and brain disorders
Canadian institutionsRobarts Clinical TrialsOntario Shores Centre for Mental Health SciencesLondon Health Sciences CentreUniversity of TorontoLawson Health Research InstituteWestern University
FundersDepartment of Psychiatry, University of TorontoLondon Health Sciences CentreLawson Health Research Institute
KeywordsMajor depressive disorderAnterior cingulate cortexInsulaPsychologyDiffusion MRINeuroscienceFractional anisotropyDefault mode networkMedicineFunctional connectivityWhite matterInternal medicineMagnetic resonance imagingCognition

Abstract

fetched live from OpenAlex

Background: Major depressive disorder (MDD) is a debilitating mental illness that has been linked to increases in markers of inflammation, as well as to changes in brain functional and structural connectivity, particularly between the insula and the subgenual anterior cingulate cortex (sgACC). In this study, we directly related inflammation and dysconnectivity in treatment-resistant MDD by concurrently measuring the following: microglial activity with [18F]N-2-(fluoroethoxyl)benzyl-N-(4phenoxypyridin-3-yl)acetamide ([18F]FEPPA) positron emission tomography (PET); the severity of MDD; and functional or structural connectivity among insula or sgACC nodes. Methods: Twelve patients with treatment-resistant MDD (8 female, 4 male; mean age ± standard deviation 54.9 ± 4.5 years and 23 healthy controls (11 female, 12 male; 60.3 ± 8.5 years) completed a hybrid [18F]FEPPA PET and MRI acquisition. From these, we extracted relative standardized uptake values for [18F]FEPPA activity and Pearson r-to- z scores representing functional connectivity from our regions of interest. We extracted diffusion tensor imaging metrics from the cingulum bundle, a key white matter bundle in MDD. We performed regressions to relate microglial activity with functional connectivity, structural connectivity and scores on the 17-item Hamilton Depression Rating Scale. Results: We found significantly increased [18F]FEPPA uptake in the left sgACC in patients with treatment-resistant MDD compared to healthy controls. Patients with MDD also had a reduction in connectivity between the sgACC and the insula. The [18F]FEPPA uptake in the left sgACC was significantly related to functional connectivity with the insula, and to the structural connectivity of the cingulum bundle. [18F]FEPPA uptake also predicted scores on the Hamilton Depression Rating Scale. Limitations: A relatively small sample size, lack of functional task data and concomitant medication use may have affected our findings. Conclusion: We present preliminary evidence linking a network-level dysfunction relevant to the pathophysiology of depression and related to increased microglial activity in MDD.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.020
GPT teacher head0.266
Teacher spread0.246 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations25
Published2022
Admission routes3
Has abstractyes

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