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Differentially expressed miRNA profiles of serum derived extracellular vesicles from patients with acute ischemic stroke

2024· article· en· W4401689439 on OpenAlexaff
Ghulam Jeelani Pir, Muhammad Zahid, Naveed Akhtar, Raheem Ayadathil, Sajitha V. Pananchikkal, Sujata Joseph, Deborah M. Morgan, Blessy Babu, Ryan Ty Ui, S Sivasankaran, Reny Francis, Ahmed Own, Ashfaq Shuaib, Aijaz Parray, Abdelali Agouni

Bibliographic record

VenueBrain Research · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicExtracellular vesicles in disease
Canadian institutionsUniversity of Alberta
FundersQatar National Research FundQatar UniversityFonds National de la Recherche Luxembourg
KeywordsExtracellular vesiclesmicroRNAExtracellularMicrovesiclesStroke (engine)Ischemic strokeMedicineAcute strokeBioinformaticsNeuroscienceBiologyCell biologyInternal medicineGeneIschemiaBiochemistry

Abstract

fetched live from OpenAlex

BACKGROUND: MicroRNAs (miRNAs) participate in diverse cellular changes following acute ischemic stroke (AIS). Circulating miRNAs, stabilized and delivered to target cells via extracellular vesicles (EVs), are potential biomarkers to facilitate diagnosis, prognosis, and therapeutic modulation. We aimed to identify distinctive expression patterns of circulating EV-miRNAs in AIS patients. METHODS: miRNA profiles from EVs, isolated from plasma samples collected within 24 h following AIS diagnosis, were examined between a dataset of 10 age-, gender- and existing comorbidities-matched subjects (5 AIS and 5 healthy controls, HC). We measured 2578 miRNAs and identified differentially expressed miRNAs between AIS and HC. An enrichment analysis was conducted to delineate the networks and biological pathways implicated by differentially expressed microRNAs. An enrichment analysis was conducted to delineate the networks and biological pathways implicated by differentially expressed microRNAs. RESULTS: Five miRNAs were differentially expressed between stroke (AIS) versus control (HC). hsa-let-7b-5p, hsa-miR-16-5p, and hsa-miR-320c were upregulated, whereas hsa-miR-548a-3p and hsa-miR-6808-3p, with no previously reported changes in stroke were downregulated. The target genes of these miRNAs affect various cellular pathways including, RNA transport, autophagy, cell cycle progression, cellular senescence, and signaling pathways like mTOR, PI3K-Akt, and p53. Key hub genes within these networks include TP53, BCL2, Akt, CCND1, and NF-κB. These pathways are crucial for cellular function and stress response, and their dysregulation can have significant implications for the disease processes. CONCLUSION: Our findings reveal distinct circulating EV-miRNA expression patterns in AIS patients from Qatar, highlighting potential biomarkers that could aid in stroke diagnosis and therapeutic strategies. The identified miRNAs are involved in critical cellular pathways, offering novel insights into the molecular mechanisms underlying stroke pathology. Circulating EV-miRNAs differentially expressed in AIS may have a pathophysiological role and may guide further research to elucidate their precise mechanisms.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.800

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 science0.0010.000
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 head0.017
GPT teacher head0.291
Teacher spread0.274 · 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

Citations14
Published2024
Admission routes1
Has abstractyes

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