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Record W4389490047 · doi:10.1080/00207454.2023.2292951

Plasma cytokines profile in patients with Alzheimer’s and Parkinson’s Disease: a comparative study in terms of inflammation

2023· article· en· W4389490047 on OpenAlexaff
Somayeh Shateri, Seyyed Hossein Khatami, Alireza Haghbin Toutounchi, Shima Rajaei, Meisam Mahdavi, Somayeh Mahmoodi Baram, Gholam Ali Shahidi, Amir Hossein Habibi, Vajiheh Aghamollaii, Babak Ghlichnia, Lily Safakish, Alireza Doagoo, Farzaneh Salmani, Abbas Tafakhori, Aliasghar Keramatinia, Mohammad Reza Shahmohammadi, Saeed Karima

Bibliographic record

VenueInternational Journal of Neuroscience · 2023
Typearticle
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsSNC-Lavalin (Canada)
FundersShahid Beheshti University of Medical Sciences
KeywordsParkinson's diseaseInflammationMedicineDiseaseAlzheimer's diseaseNeurosciencePsychologyImmunologyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Neurodegenerative disorders such as Alzheimer's and Parkinson's disease inflict economic and health burdens on societies. Alzheimer's disease (AD), the most prevalent form of dementia, is accompanied by progressive degradation of memory, decision-making, and judgment. Parkinson's disease (PD) is characterized by resting tremor, rigidity, bradykinesia, and loss of balance. Extensive research has pinpointed inflammation as a cause of the onset and progression of both diseases. However, it has not been confirmed which one is more formidable in terms of inflammation. METHODS: To assess the extent of inflammation that is implicated in AD and PD and answer the question of which one is more inflammatory, serum levels of inflammatory biomarkers, including cytokines, chemokines, and prostaglandin E2 (PEG2), were measured in AD and PD patients as well as a healthy group. RESULTS: Our results showed a significant increase in IL-1α, IL-1β, IL-4, IL-6, IL-10, IL-12p70, IP-10, MCP-1, PEG2, and TNF-α in AD and PD patients compared with the control. Interestingly, IFN-γ did not manifest any significant difference in AD or PD patients compared with the control. CONCLUSION: As a hallmark of our results, it could be inferred that inflammation, as the underlying etiological cause, plays a more crucial role in PD compared with AD. Based on our results, it is proposed that anti-inflammatory remedies would be putatively more effective in PD rather than AD.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.233

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.041
GPT teacher head0.323
Teacher spread0.282 · 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.

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".

Quick stats

Citations12
Published2023
Admission routes1
Has abstractyes

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