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Record W4408245565 · doi:10.1111/ene.70107

Microglial Activation Visualized by [<scp><sup>18</sup>F</scp>]‐<scp>DPA714 PET</scp> Is a Potential Marker of Severity and Prognosis for Anti‐<scp>LGI1</scp> Encephalitis

2025· article· en· W4408245565 on OpenAlexaboutno aff
Jingguo Wang, Jingjie Ge, Bo Deng, Huamei Lin, Yang Wen-bo, Tianyang Sheng, Weijun Tang, Hai Yu, Xiang Zhang, Yarong Li, Xiaoni Liu, Chuantao Zuo, Xiangjun Chen

Bibliographic record

VenueEuropean Journal of Neurology · 2025
Typearticle
Languageen
FieldMedicine
TopicAutoimmune Neurological Disorders and Treatments
Canadian institutionsnot available
FundersScience and Technology Commission of Shanghai Municipality
KeywordsTranslocator proteinHippocampusMedicineAutoimmune encephalitisEncephalitisMicrogliaLimbic encephalitisNeuroinflammationCerebrospinal fluidPathologyInternal medicineImmunologyInflammation

Abstract

fetched live from OpenAlex

ABSTRACT Background and Purpose Whether microglial activation plays an important role in the pathogenesis of autoimmune encephalitis (AE), such as anti‐leucine‐rich, glioma‐inactivated‐1 (LGI1) encephalitis, remains unknown. [ 18 F]‐DPA714 PET targeting the translocator protein (TSPO) is a novel method to detect neuroinflammation via visualizing activated microglia. In this study, we aimed to investigate the application of [ 18 F]‐DPA714 PET in anti‐LGI1 encephalitis. Methods Patients with anti‐LGI1 encephalitis and non‐inflammatory controls (NIC) underwent [ 18 F]‐DPA714 PET scans were enrolled. Standardized uptake value ratios normalized to the cerebellum (SUVRc) in LGI1‐AE patients were calculated for semi‐quantitative analysis. The microglial activation marker, soluble triggering receptor expressed on myeloid cells 2 (sTREM2) was measured in cerebrospinal fluid (CSF) to demonstrate its correlation with [ 18 F]‐DPA714 PET imaging. Logistic regression analysis was used to identify potential predictors of prognosis. Results Forty‐six patients with anti‐LGI1 encephalitis were included in this study. Increased TSPO uptake was identified in the hippocampus, frontal cortex, and caudate nucleus. Montreal Cognitive Assessment (MoCA) score was significantly correlated with SUVRc in the hippocampus ( R 2 = 0.13, p = 0.034) and frontal cortex ( R 2 = 0.13, p = 0.017). Overexpressed sTREM2 in CSF was correlated with SUVRc in the hippocampus ( R 2 = 0.18, p = 0.04). SUVRc in the hippocampus significantly decreased after immunotherapy and was associated with improvement of MoCA score ( R 2 = 0.54, p = 0.023). Increased SUVRc in the frontal cortex and hippocampus was associated with unfavorable disability recovery (odds ratio [OR] = 7.1, 95% CI 1.67–29.9, p = 0.008) and persistent amnesia (OR = 5.4, 95% CI 1.3–22.2, p = 0.021) respectively. Conclusion Microglial activation visualized by [ 18 F]‐DPA714 PET is associated with clinical features and may be used as a potential biomarker for therapeutic and prognostic evaluation.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.452
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.273
Teacher spread0.260 · 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 teacher head, not a consensus.

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

Citations9
Published2025
Admission routes1
Has abstractyes

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