Immunological Profile of Type II Egyptian Diabetic Patients
Bibliographic record
Abstract
Background: Diabetes mellitus (DM) and its associated secondary complications are some of the leading induce of deaths worldwide. Aim: The aim of the study is to estimate changes in the levels of biochemical parameters as fasting blood sugar (FBS), postprandial blood sugar (PP2BS) and glycosylated hemoglobin (HbA1c); and immunological parameters as Complement proteins C3, Complement proteins C4, Immunoglobulin's (IgA, IgE, IgG, and IgM) and C-peptide of type 2 diabetic patients to obtain a full immunological and physiological profile for type 2 diabetes. Subjects and Methods: Blood samples from 25 type 2 diabetic patients and 5 healthy subjects were randomly selected from Banha University hospitals in Kalyubiyya, Egypt. Serum sugar and glycosylated hemoglobin were assayed by using chemical analyzer (chem 7). C3, C4, IgA, IgE, IgG, IgM and C-peptide were measured by ELISA Results: FBS, PP2BS, and HbA1c significant increase in type 2 diabetic patients compared to healthy subjects. C3, IgA, IgE, IgG, and C-peptide showed a significant increase in type 2 diabetic patients compared to healthy subjects. Conclusion: FBS, PP2BS, and HbA1c used as good tools for the diagnosis of diabetes mellitus. Type 2 diabetes in the current studied subjects is characterized by alternative pathway activation. Immunological biomarkers such as C3, IgA, IgE, and IgG were increased in type 2 diabetic patients by poor control of diabetes and long duration of disease.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".