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Acute Inflammation Alters Brain Energy Metabolism in Mice and Humans: Role in Suppressed Spontaneous Activity, Impaired Cognition, and Delirium

2020· article· en· W3032925016 on OpenAlexaff
John Kealy, Carol Murray, Éadaoin W. Griffin, Ana Belén López-Rodríguez, Dáire Healy, Lucas Silva Tortorelli, John Lowry, Leiv Otto Watne, Colm Cunningham

Bibliographic record

VenueJournal of Neuroscience · 2020
Typearticle
Languageen
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsTrinity College
FundersNational Institute on AgingNational Institutes of HealthNasjonalforeningen for FolkehelsenHealth Research BoardWellcome Trust
KeywordsDeliriumInternal medicineHypoglycemiaEndocrinologyCarbohydrate metabolismMedicineCognitive declineInflammationDiabetes mellitusDementiaPsychiatryDisease

Abstract

fetched live from OpenAlex

Systemic infection triggers a spectrum of metabolic and behavioral changes, collectively termed sickness behavior, which while adaptive, can affect mood and cognition. In vulnerable individuals, acute illness can also produce profound, maladaptive, cognitive dysfunction including delirium, but our understanding of delirium pathophysiology remains limited. Here, we used bacterial lipopolysaccharide (LPS) in female C57BL/6J mice and acute hip fracture in humans to address whether disrupted energy metabolism contributes to inflammation-induced behavioral and cognitive changes. LPS (250 µg/kg) induced hypoglycemia, which was mimicked by interleukin (IL)-1β (25 µg/kg) but not prevented in IL-1RI<sup>−/−</sup> mice, nor by IL-1 receptor antagonist (IL-1RA; 10 mg/kg). LPS suppression of locomotor activity correlated with blood glucose concentrations, was mitigated by exogenous glucose (2 g/kg), and was exacerbated by 2-deoxyglucose (2-DG) glycolytic inhibition, despite preventing IL-1β synthesis. Using the ME7 model of chronic neurodegeneration in female mice, to examine vulnerability of the diseased brain to acute stressors, we showed that LPS (100 µg/kg) produced acute cognitive dysfunction, selectively in those animals. These acute cognitive impairments were mimicked by insulin (11.5 IU/kg) and mitigated by glucose, demonstrating that acutely reduced glucose metabolism impairs cognition selectively in the vulnerable brain. To test whether these acute changes might predict altered carbohydrate metabolism during delirium, we assessed glycolytic metabolite levels in CSF in humans during inflammatory trauma-induced delirium. Hip fracture patients showed elevated CSF lactate and pyruvate during delirium, consistent with acutely altered brain energy metabolism. Collectively, the data suggest that disruption of energy metabolism drives behavioral and cognitive consequences of acute systemic inflammation. <b>SIGNIFICANCE STATEMENT</b> Acute systemic inflammation alters behavior and produces disproportionate effects, such as delirium, in vulnerable individuals. Delirium has serious short and long-term sequelae but mechanisms remain unclear. Here, we show that both LPS and interleukin (IL)-1β trigger hypoglycemia, reduce CSF glucose, and suppress spontaneous activity. Exogenous glucose mitigates these outcomes. Equivalent hypoglycemia, induced by lipopolysaccharide (LPS) or insulin, was sufficient to trigger cognitive impairment selectively in animals with existing neurodegeneration and glucose also mitigated those impairments. Patient CSF from inflammatory trauma-induced delirium also shows altered brain carbohydrate metabolism. The data suggest that the degenerating brain is exquisitely sensitive to acute behavioral and cognitive consequences of disrupted energy metabolism. Thus “bioenergetic stress” drives systemic inflammation-induced dysfunction. Elucidating this may offer routes to mitigating delirium.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.014
GPT teacher head0.258
Teacher spread0.244 · 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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Citations143
Published2020
Admission routes1
Has abstractyes

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