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Record W2319867844 · doi:10.3390/ijms17040483

Mesenchymal Stem Cells Ameliorated Glucolipotoxicity in HUVECs through TSG-6

2016· article· en· W2319867844 on OpenAlexaff
Xingxing An, Li Lan, Younan Chen, Ai Luo, Zuyao Ni, Jingping Liu, Yujia Yuan, Meimei Shi, Bo Chen, Dan Long, Jingqiu Cheng, Yanrong Lu

Bibliographic record

VenueInternational Journal of Molecular Sciences · 2016
Typearticle
Languageen
FieldMedicine
TopicMesenchymal stem cell research
Canadian institutionsUniversity of Toronto
FundersNational Natural Science Foundation of China
KeywordsMesenchymal stem cellPalmitic acidGene knockdownUmbilical veinApoptosisCell biologyChemistryReactive oxygen speciesBiologyBiochemistryFatty acidIn vitro

Abstract

fetched live from OpenAlex

Glucolipotoxicity is one of the critical causal factors of diabetic complications. Whether mesenchymal stem cells (MSCs) have effects on glucolipotoxicity in human umbilical vein endothelial cells (HUVECs) and mechanisms involved are unclear. Thirty mM glucose plus 100 μM palmitic acid was used to induce glucolipotoxicity in HUVECs. MSCs and HUVECs were co-cultured at the ratio of 1:5 via Transwell system. The mRNA expressions of inflammatory factors were detected by RT-qPCR. The productions of reactive oxygen species (ROS), cell cycle and apoptosis were analyzed by flow cytometry. The tumor necrosis factor-α stimulated protein 6 (TSG-6) was knockdown in MSCs by RNA interference. High glucose and palmitic acid remarkably impaired cell viability and tube formation capacity, as well as increased the mRNA expression of inflammatory factors, ROS levels, and cell apoptosis in HUVECs. MSC co-cultivation ameliorated these detrimental effects in HUVECs, but no effect on ROS production. Moreover, TSG-6 was dramatically up-regulated by high glucose and fatty acid stimulation in both MSCs and HUVECs. TSG-6 knockdown partially abolished the protection mediated by MSCs. MSCs had protective effects on high glucose and palmitic acid induced glucolipotoxicity in HUVECs, and TSG-6 secreted by MSCs was likely to play an important role in this process.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.315

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.047
GPT teacher head0.357
Teacher spread0.310 · 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 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

Citations23
Published2016
Admission routes1
Has abstractyes

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