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Mind the gap – Interthalamic adhesions in prodromal and clinical Alzheimer’s disease

2025· article· en· W4414564275 on OpenAlexfundno aff
Gonzalo Forno, Julie Vidal, Rachel H. Tan, John P. Aggleton, Emmanuel J. Barbeau, Michael Hornberger

Bibliographic record

VenueBrain Research Bulletin · 2025
Typearticle
Languageen
FieldNeuroscience
TopicCerebrospinal fluid and hydrocephalus
Canadian institutionsnot available
FundersNational Institute of Biomedical Imaging and BioengineeringCanadian Institutes of Health ResearchNational Institutes of HealthAgencia Nacional de Investigación y DesarrolloGenentechIXICODoD Alzheimer's Disease Neuroimaging InitiativeH. Lundbeck A/SServierEisaiNorthern California Institute for Research and EducationPfizerNovartis Pharmaceuticals CorporationUniversity of Southern CaliforniaBiogenEli Lilly and CompanyBristol-Myers SquibbBioClinicaU.S. Department of DefenseAlzheimer's Disease Neuroimaging InitiativeMeso Scale DiagnosticsNational Institute on AgingAlzheimer's Association
KeywordsDiseaseProdromal StagePathophysiologyPathogenesisSeverity of illness

Abstract

fetched live from OpenAlex

The interthalamic adhesion (IA) is an anatomical bridge connecting the left and right thalamus. While prior studies have explored its prevalence and function in healthy populations, stroke, hydrocephalus, and schizophrenia, none have examined the IA in the context of Alzheimer’s disease (AD). This study aims to analyse the prevalence of the IA in the prodromal to clinical AD continuum and evaluate the association with AD cerebrospinal fluid (CSF) biomarkers and thalamic, hippocampal, and ventricular volumes. IA prevalence was assessed in 542 MRIs from the Alzheimer’s Disease Neuroimaging Initiative (ADNI), including healthy controls (HC), early mild cognitive impairment (EMCI), late MCI (LMCI), and AD patients. Inter-rater reliability was assessed with Cohen’s Kappa, and a chi-squared test (χ2) examined rater differences. Binary and multinomial logistic regressions evaluated the effect of CSF biomarkers, volumes, and clinical data on IA prevalence and type. There were no significant differences in IA prevalence or variants across the four groups. The single IA was the most common type, while bilobar and double variants were less frequent. Post-hoc analysis, however, showed that AD CSF biomarker measures showed positive associations with the broad IA subtype in HC and EMCI. The study found no overall differences in IA prevalence or its variants related to prodromal or clinical AD. Still, elevated Aβ42, p-Tau levels, and larger thalamic volume were linked to a higher likelihood of a broad IA. These findings suggest that the IA may be involved in prodromal AD pathophysiological processes. • AD have a decreased probability of having a broad IA compared to HC and EMCI. • Larger thalamic volumes increased the probability of a broad IA. • Increased CSF Aβ 42 levels were related to bigger thalamic volumes in the HC/EMCI and LMIC/AD group. • Increased phosphorylated tau levels were related to bigger thalamic volumes in the HC/EMCI group. • The 3rd ventricle volume was the most important predictor of an IA.

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)0.002
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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.162
GPT teacher head0.447
Teacher spread0.285 · 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".

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Citations1
Published2025
Admission routes1
Has abstractyes

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