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Record W1938819762 · doi:10.1161/jaha.115.001920

Tumor Necrosis Factor‐α Underlies Loss of Cortical Dendritic Spine Density in a Mouse Model of Congestive Heart Failure

2015· article· en· W1938819762 on OpenAlexaff
Anja Meißner, Naomi P. Visanji, M. Abdul Momen, Rui Feng, Beverly M. Francis, Steffen‐Sebastian Bolz, Lili‐Naz Hazrati

Bibliographic record

VenueJournal of the American Heart Association · 2015
Typearticle
Languageen
FieldNeuroscience
TopicNeuroinflammation and Neurodegeneration Mechanisms
Canadian institutionsSt. Michael's HospitalToronto General HospitalHeart and Stroke FoundationToronto Western HospitalUniversity of Toronto
Fundersnot available
KeywordsMedicineHeart failureNeuroinflammationProinflammatory cytokineCardiologyDendritic spineTumor necrosis factor alphaInternal medicineHippocampusPathologyInflammation

Abstract

fetched live from OpenAlex

BACKGROUND: Heart failure (HF) is a progressive disorder characterized by reduced cardiac output and increased peripheral resistance, ultimately leading to tissue perfusion deficits and devastating consequences for several organs including the brain. We previously described a tumor necrosis factor-α (TNF-α)-dependent enhancement of posterior cerebral artery tone and concomitant reduced cerebral blood flow in a mouse model of early HF in which blood pressure remains minimally affected. HF is often associated with cognitive impairments such as memory deficits, even before any overt changes in brain structure and function occur. The pathophysiology underlying the development of cognitive impairments in HF is unknown, and appropriate treatment strategies are lacking. METHODS AND RESULTS: We used a well-established mouse model in which HF was induced by experimental myocardial infarction produced by permanent surgical ligation of the left anterior descending coronary artery (infarct size ≈25% of the left ventricular wall). Ligated mice developed enlarged hearts, congested lungs, and reduced cardiac output and blood pressure, with elevated peripheral resistance within 6 to 8 weeks after ligation. In this study, we demonstrated the significance of the proinflammatory cytokine TNF-α during HF-mediated neuroinflammation and associated impaired hippocampus-independent nonspatial episodic memory function. Augmented cerebral TNF-α expression and microglial activation in HF mice, indicative of brain inflammation, were accompanied by morphological changes and significant reduction of cortical dendritic spines (61.39±8.61% for basal and 61.04±9.18% for apical spines [P<0.001]). The significance of TNF-α signaling during the observed HF-mediated neurodegenerative processes is supported by evidence showing that sequestration or genetic deletion of TNF-α ameliorates the observed reduction of cortical dendritic spines (33.51±7.63% for basal and 30.13±6.98% for apical spines in wild-type mice treated with etanercept; 17.09±6.81% for basal and 17.21±7.29% for apical spines in TNF-α(-/-)). Moreover, our data suggest that alterations in cerebral serum and glucocorticoid-inducible kinase 1 (SgK1) expression and phosphorylation during HF may be TNF-α dependent and that an increase of SgK1 phosphorylation potentially plays a role in the HF-associated reduction of dendritic spine density. CONCLUSIONS: Our findings demonstrate that TNF-α plays a pivotal role in HF-mediated neuroinflammation and associated alterations of cortical dendritic spine density and has the potential to reveal novel treatment strategies for HF-associated memory deficits.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.043
GPT teacher head0.284
Teacher spread0.241 · 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 designBench or experimental
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

Citations56
Published2015
Admission routes1
Has abstractyes

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