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Record W4289869029 · doi:10.3389/fnagi.2022.919766

Green tea improves cognitive function through reducing AD-pathology and improving anti-oxidative stress capacity in Chinese middle-aged and elderly people

2022· article· en· W4289869029 on OpenAlexaboutno aff
Ran Zhang, Lei Zhang, Li Zeng, Ping Zhang, Hao Song, Dong-ai Yao, Jing Cao, Junjian Zhang

Bibliographic record

VenueFrontiers in Aging Neuroscience · 2022
Typearticle
Languageen
FieldNeuroscience
TopicNeurological Disease Mechanisms and Treatments
Canadian institutionsnot available
FundersWuhan UniversityNational Natural Science Foundation of China
KeywordsMontreal Cognitive AssessmentOxidative stressMalondialdehydeStroop effectCognitionGlutathione peroxidaseMedicineSuperoxide dismutaseInternal medicineEffects of sleep deprivation on cognitive performanceNeuropsychologyVerbal learningCognitive declinePsychologyDiseaseDementiaPsychiatry

Abstract

fetched live from OpenAlex

Background: Numerous benefits of green tea have been reported. However, the effects of green tea on cognitive function remain disputable and the mechanism is still unclear. Objective: To investigate the relationship of green tea consumption with cognitive function and related blood biomarkers among Chinese middle-aged and elderly people. Methods: A total of 264 participants aged 50–70 years old were enrolled from Zhongnan Hospital of Wuhan University. They were interviewed about green tea consumption patterns and underwent neuropsychological tests covering five main cognitive domains to assess cognition including Montreal Cognitive Assessment (MoCA) and the other 10 scales. Then we detected serum oxidative stress biomarkers including Superoxide Dismutase (SOD), Malondialdehyde (MDA), Glutathione Peroxidase (GPx), Glutathione Reductase (GR), and Alzheimer’s disease (AD) markers including β-amyloid (Aβ) 40 , Aβ 42 , and phosphorylated tau-181 (pTau 181 ). Results: In the tea-consuming group, the MoCA scores ( P = 0.000), Hopkins Verbal Learning Test (HVLT) immediate recall ( P = 0.012) and delayed recall ( P = 0.013) were significantly higher while Trail Making Test-B ( P = 0.005) and Victoria Stroop test interference ( P = 0.000) were lower. In terms of oxidative stress markers, the tea-consuming group had lower serum MDA levels ( P = 0.002) and higher serum SOD ( P = 0.005) and GPx ( P = 0.007) levels. In terms of AD markers, serum pTau 181 (P < 0.000), Aβ 42 ( P = 0.019) and total Aβ levels ( P = 0.034) but not serum Aβ 40 levels, were lower in the tea-consuming group. In the logistic regression analysis, there was a significant negative correlation between green tea consumption and cognitive impairment (OR = 0.26, 95 % CI 0.13 0.52 for high group). Conclusion: Regular green tea consumption is associated with better cognitive function among Chinese middle-aged and elderly people, mainly reflected in memory and executive function. It may achieve protective effects by reducing AD-related pathology and improving anti-oxidative stress capacity and higher levels of tea consumption have a stronger protective effect.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.767
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.030
GPT teacher head0.246
Teacher spread0.216 · 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

Citations28
Published2022
Admission routes1
Has abstractyes

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