Clinical Pattern of Inflammatory bowel disease in central reigon, Saudi Arabia
Bibliographic record
Abstract
Abstract Background The identification of semen stain is one of the most common human stains that can provide crucial information for crime scene reconstruction and forensic investigation. In sexual assault cases semen identification helps to prove victim’s allegations it also provides a material for DNA analysis that generate the genetic profile of the alleged suspect. The rapid Stain Identification of Human Semen (RSIDTM-Semen) bioassay is designed to detect specifically the presence of human semenogelin. Test development is completed within 10 minutes and can detect as little as 2.5 nL of human semen and it does not cross-react with other human or nonhuman tissues. The detection protocol can be completely integrated into the procedures for DNA extraction and analysis. Aim To assess the efficacy of RSIDTM – Semen strip test for the detection of human semen under some different variables (different fabrics, different time intervals and mixed with vaginal secretions) in order to be used in the routine forensic work of sexual assault cases and for further personal identification. Methodology: Semen samples were collected from four male participants. Vaginal specimens were collected from four female participants on cotton, linen or nylon-tipped swabs (2 swabs from each female). Each semen sample was divided into two portions; one used for semen only test group and the other mixed with vaginal secretions for the mixed test group. One of the fabrics tipped vaginal swab was mixed with semen for the mixed test group and the other used as a positive control group to test the sensitivity and specificity of the RSIDTM – Semen strip. The semen samples were deposited over different fabrics at the same time. All the samples were left to dry for 15 minutes at room temperature then extracted and analyzed according to the protocol designed for The Rapid Stain Identification Test (RSIDTM – Semen). The collected samples were studied as two test groups and one control group. Each of the previous groups, was categorized into 4 subgroups (a, b, c and d) according to the time interval of semen extraction (zero (on the spot), 2, 4, 6 and 10 days respectively). Results Semen could be identified in 100% of tested samples of the semen only group as well as of the combined semen and vagina group over cotton and linen fabrics at all the different tested time intervals. However, semen extracted from nylon fabric was identified in tested samples of the semen only group and of the combined semen and vagina group only at zero time only and couldn’t be identified at the rest of tested time intervals. Conclusion the current study evidenced that the new RSIDTM-semen kit is a reliable method for semen identification over different types of fabrics even in the presence of vaginal secretions. It also resists environmental factors up to 10 days. Background: Inflammatory bowel disease (IBD) is A chronic inflammatory disorder of the gastrointestinal tract (GIT). IBD comprises Crohn’s disease (CD) and Ulcerative Colitis (UC). Patients with CD and UC may present with variety of clinical presentations according to the activity of the disease. The treatment of IBD varies according to degree of activity. The demographics and clinical patterns of IBD have not been adequately studies in Saudi Arabia. Thus, the current study investigated the clinical presentation, course and outcome of IBD in a hospital in the Central region, Saudi Arabia. Methodology This prospective study included 92 patients from December 1, 2017, to August 31, 2018. The study constituted clinical history, screening through surveys that consisted of open ended and closed ended questions, and physical and laboratory assessment. Result There was no significant gender difference presents by male to female (M: F) 20:21 in UC and 23:28 in CD. The study showed that the most affected age group was the 4th decade in age group 31 to 40 years old represent that 56%. The most common presenting symptoms in active ulcerative colitis and Crohn’s disease were diarrhea, abdominal pain , weight loss, headache and fever. The study patients presented in different stages according to Montreal classification with the highest prevalence in Montreal stage two by 16.30% in UC and 22.82% in CD. Among patients with diarrhea, the vast majority due to infectious cause followed by UC the CD. Arthralgia’s, arthritis and ophthalmic manifestations were the most frequent extra-intestinal manifestations. Conclusion As progression of IBD in Saudi Arabia the health organization should research more in IBD and the cause of increase it’s incidence
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".