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Record W4406347885

Using flow-cytometry in measuring platelet activity in type 2 diabetes and predicting macrovascular complications.

2025· article· en· W4406347885 on OpenAlexaff
Mai Aly, Fatema A El-Osily, Eman R. Badawy, Mohamed M. Shehab, Mohammad H AbdEllah-Alaui, Dina A. Hamad

Bibliographic record

VenuePubMed · 2025
Typearticle
Languageen
FieldMedicine
TopicAdipokines, Inflammation, and Metabolic Diseases
Canadian institutionsMinistry of Agriculture
Fundersnot available
KeywordsFlow cytometryMedicineType 2 diabetesPlateletDiabetes mellitusInternal medicineCardiologyImmunologyEndocrinology
DOInot available

Abstract

fetched live from OpenAlex

Platelets are hyperactive in patients with type2 diabetes (T2DM), they adhere to vascular endothelium and play a key role in macrovascular complications. Platelets activity can be measured by flow-cytometry (cluster of differentiation (CD) 41, CD 42, CD 62, CD 63), which allows detection of surface antigens in a sensitive and specific manner. This study aimed to describe platelets activity in T2DM in association with cardiovascular and cerebrovascular complications in relation to duration of diabetes (DM). This was a case-control study with 130 participants (65 diabetic cases and 65 normal controls). All cases were subjected to history and clinical examination, base-line laboratory investigations and surface expression of platelets receptors e.g. CD 41% and mean fluorescent intensity (MFI), CD 42% and MFI, CD 62% and MFI, CD 63% and MFI were determined by flow-cytometry. There was a statistically significant higher expression of CD 62%, CD 62 MFI, CD 63% and CD 63 MFI (p < 0.001 for all) in diabetic cases compared to controls. There were significantly higher CD 62 %, CD 62 MFI, CD 63% and CD 63 MFI in cases with cardiovascular complications (p=0.001, p < 0.001, p=0.05 and p=0.007, respectively) and in cases with cerebrovascular complications compared to cases without complications (p=0.05, p=0.008, p=0.035, p=0.017, respectively). A significant positive correlation was found between glycated hemoglobin, body mass index and CD 62 %, CD 62 MFI and CD 63%. Using the receiver operating characteristic curve showed that CD 62 %, CD 62 MFI, CD 63 % and CD 63 MFI have a diagnostic ability to early predict DM (area under the curve (AUC)=0.998) as well as cardiovascular (AUC=0.855) and cerebrovascular (AUC=0.765) complications. In conclusion CD 62%, CD 62 MFI, CD 63% and CD 63 MFI markers have a diagnostic ability for early prediction of cardiovascular and cerebrovascular complications among diabetic patients.

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)0.003
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.036
GPT teacher head0.266
Teacher spread0.230 · 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 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

Citations0
Published2025
Admission routes1
Has abstractyes

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