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Dietary DHA-rich Supplementation Decreases Neurotoxic Lipid Mediators in Participants with Type II Diabetes and Neuropathic Pain

2024· preprint· en· W4404579674 on OpenAlexaboutno aff
Alfonso Manuel Durán, Francis Zamora, Marino De León

Bibliographic record

VenuePreprints.org · 2024
Typepreprint
Languageen
FieldNursing
TopicFatty Acid Research and Health
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineDocosahexaenoic acidType 2 diabetesDiabetes mellitusEicosapentaenoic acidLipid profileInternal medicineType 2 Diabetes MellitusPharmacologyEndocrinologyFatty acidPolyunsaturated fatty acidBiochemistryBiology

Abstract

fetched live from OpenAlex

A growing body of evidence indicates a link between circulating neurotoxic lipids and the development of chronic neuroinflammatory diseases in the peripheral and central nervous systems. Therefore, strategies to modify circulating lipid profiles may complement the management of neuroinflammatory diseases, including neuropathic pain. In a previous study, we observed a sig-nificant shift in the metabolomic profile of patients' plasma with symptoms of painful diabetic neuropathy (pDN) following three months of docosahexaenoic acid (DHA)-rich supplementation, leading to improved pDN symptoms. However, it is important to identify the specific lipid mediators responsible for this therapeutic effect and elucidate potential mechanism(s). This study investigates whether DHA-rich supplementation reduces neurotoxic lipid mediators associated with pDN in individuals with type 2 diabetes mellitus (T2DM). Forty volunteers diagnosed with type 2 diabetes were enrolled in the "En Balance-PLUS" diabetes education study. The volunteers participated in weekly lifestyle/nutrition education and daily supplementation with 1000 mg DHA and 200 mg eicosapentaenoic acid. The Short-Form McGill Pain Questionnaire validated the clinical determination of baseline and post-intervention pain complaints. Untargeted Lipidomic analyses were conducted using blood serum collected at baseline and after three months of participation in the dietary regimen. The lipidomic data were analyzed using a non-parametric paired Wilcoxon rank-sum test and random forest analysis. ELISA further eval-uated participant serum samples to investigate associated biomarkers of necrosis (MLKL), autophagy (ATG5), and lipid chaperone protein (FABP5). Untargeted lipidomic analysis revealed that several neurotoxic-associated lipids significantly decreased after DHA-rich supplementation. Also, circulating levels of MLKL were reduced, while protein levels of ATG5 and FABP5 significantly increased. The reduction of circulating neurotoxic lipids and increase of neuroprotective lipids following DHA-rich supplementation is consistent with the reported roles of omega-3 polyunsaturated fatty acids (PUFAs) in reducing adverse symptoms associated with neuroinflammatory diseases and painful neuropathy.

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: Non-randomized trial · Consensus signal: none
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)0.0000.000
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)0.0020.000

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 head0.118
GPT teacher head0.380
Teacher spread0.262 · 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 designNon-randomized trial
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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Citations0
Published2024
Admission routes1
Has abstractyes

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