The Contribution of Interleukin (17) in Iraqi Patients with Type I Diabetic and Positive Agglutination Sera with Morganella Morganii Antigens
Bibliographic record
Abstract
Background: The rising population of patients with diabetes type 1 has caused in a fast increase in the amount of patients who have diabetic complications. Objective: Isolation of bacteria from diabetic patients and detection of their antibodies in the serum of patients and rabbits. Materials and Methods: Sixty samples of blood and urine were collected from diabetic patients, a similar proportion of genders were included in 50 samples of blood from healthy as controls. Patients with diabetes diseases diagnosed by a physician collected from specialized center for endocrinology and diabetes and Kindy hospital, in Baghdad. Results: This study showed that Morganella morganii (n=9, 18%) was isolated from urine of patients. With M. morganii antigens (complete cells) as three bacteria antigens agglutinated in titer 1:64 and three in titer 1:128 of serum of patients (antibodies) whereas 1 and fife of M. morganii antigens agglutinated in serum of patients in titer 1:256 and 1:16 Consecutively. Determination of the concentration of cytokinetic proteins IL-17, using an ELISA device. The concentration of some inflammation-initiating cytokines was estimated in the serum of the studied samples, which included using IL-17 ELISA technology. The statistical results by t-test showed were significant differences between this interleukin between the patients and the control sample and under the probability level P<0.05 in the serum of the patients compared to the control sample. The results also showed a decrease in the cytokinetic concentration, as the concentration in the infected serum was 0.011 ± 0.019 (pg/mm), while its concentration in the control sample was 0.007 ± 0.033 (pg/mm) in the infected serum. Recognize the agglutination ability slide agglutination exam (anti Morganella morganii rabbit serum). Conclusion: The ability of killed antigen bacteria isolated from diabetic patients to agglutinate with their serum, and its ability to agglutinate with the serum of rabbits injected with this bacterium. The increased prevalence of agglutination and increased antibodies of patients and rabbit blood suggest this as part of the multifactorial basis for disease penetrance and susceptibility.
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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 | 0.002 |
| 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".