Studying the Formulation of Shallot (Allium Ascalonicum L.) Ethanol Extract Gel as Treatment of Excision Wounds in Rats

Onion bulbs (Allium ascalonicum L.) contain alkaloid compounds and saponins which can accelerate the wound healing process. Therefore, a study was conducted on the wound healing effect of excision of ethanol extract of onion bulbs (Allium ascalonicum L.) in the form of a gel against mice (Rattus novergicus). The purpose of this research was to study the stability of the preparation as well as the effectiveness and optimum concentration in excision wound healing from the ethanolic extract of shallot (Allium ascalonicum L.) in gel dosage form. The concentration variants used were 5%, 10%, and 20%. The method used was sample extraction by maceration and wound gel was made in 3 concentrations, namely 5%, 10%, and 20% then a stability test was carried out on the preparation by cycling test method at 4⁰C and 40⁰C for 6 cycles. Besides that, gel base was also used as a negative control and octadine® gel as a positive control, then the back skin of a rat (Rattus novergicus) was injured using a surgical knife. The results of the observation of the stability of the wound gel preparation were stable both at 4⁰C and at 40⁰C. Reduction of the length of the wound at the beginning of the treatment until the wound was completely closed showed that the ethanol extract gel preparation of shallot bulbs (Allium ascalonicum L.) could reduce and heal cuts in rats with a concentration of 20% which showed the most effective wound healing effect.Onion bulbs (Allium ascalonicum L.) contain alkaloid compounds and saponins which can accelerate the wound healing process. Therefore, a study was conducted on the wound healing effect of excision of ethanol extract of onion bulbs (Allium ascalonicum L.) in the form of a gel against mice (Rattus novergicus). The purpose of this research was to study the stability of the preparation as well as the effectiveness and optimum concentration in excision wound healing from the ethanolic extract of shallot (Allium ascalonicum L.) in gel dosage form. The concentration variants used were 5%, 10%, and 20%. The method used was sample extraction by maceration and wound gel was made in 3 concentrations, namely 5%, 10%, and 20% then a stability test was carried out on the preparation by cycling test method at 4⁰C and 40⁰C for 6 cycles. Besides that, gel base was also used as a negative control and octadine® gel as a positive control, then the back skin of a rat (Rattus novergicus) was injured using a surgical knife. The results of the observation of the stability of the wound gel preparation were stable both at 4⁰C and at 40⁰C. Reduction of the length of the wound at the beginning of the treatment until the wound was completely closed showed that the ethanol extract gel preparation of shallot bulbs (Allium ascalonicum L.) could reduce and heal cuts in rats with a concentration of 20% which showed the most effective wound healing effect

Real-Time Detection of Abandoned Object using Centroid Difference Method

An abandoned object is one that remains stationary for an extended period. Such object might contain explosives and if left on purpose could cause death and injuries to people especially in crowded places. Abandoned objects need to be detected on time to prevent what might endanger people’s lives and health. Various methods have been developed to detect abandoned objects. The most reliable one is the vision-based method which automatically detects the abandoned object using image processing. The efficiency of the method was tested and evaluated on the customized datasets as well as the i-Lids advanced video surveillance system database. The Self -organizing Background Subtraction (SOBS) method overrides other methods in terms of its detection accuracy and simplicity of implementation, but fails for dynamic background scenarios. This work presents a real time vision-based object detection method using the centroid difference to improve on the accuracy of the detection and to tackle challenges of dynamic background of the SOBS method. Matlab Image processing toolbox was used to achieve this goal. The strategy is basically decomposed into two; foreground detection and stationary foreground object (SFO) detection. Gaussian Mixture Model is used for detecting the presence of newly introduced object into a scene (foreground detection), while the blob tracking approach based on frame counting is used to determine whether the detected foreground object is static/ abandoned or not. The results show that the detection accuracy of 83% was obtained which outperform the SOBS method with 67% accuracy. Future research should focus on tracking the person that abandoned the object for onward prosecution

The application of support vector machine in classifying potential archers using bio-mechanical indicators

This study classifies potential archers from a set of bio-mechanical indicators trained via different Support Vector Machine (SVM) models. 50 youth archers drawn from a number of archery programmes completed a one end archery shooting score test. Bio-mechanical evaluation of postural sway, bow movement, muscles activation of flexor and extensor as well as static balance were recorded. k-means clustering technique was used to cluster the archers based on the indicators tested. Fine, medium and coarse radial basis function kernel-based SVM models were trained based on the measured indicators. The five-fold cross-validation technique was utilised in the present investigation. It was shown from the present study, that the employment of SVM is able to assist coaches in identifying potential athletes in the sport of archery

Fully Automatic Expression-Invariant Face Correspondence

We consider the problem of computing accurate point-to-point correspondences among a set of human face scans with varying expressions. Our fully automatic approach does not require any manually placed markers on the scan. Instead, the approach learns the locations of a set of landmarks present in a database and uses this knowledge to automatically predict the locations of these landmarks on a newly available scan. The predicted landmarks are then used to compute point-to-point correspondences between a template model and the newly available scan. To accurately fit the expression of the template to the expression of the scan, we use as template a blendshape model. Our algorithm was tested on a database of human faces of different ethnic groups with strongly varying expressions. Experimental results show that the obtained point-to-point correspondence is both highly accurate and consistent for most of the tested 3D face models

Advanced leiomyosarcoma of the uterus: a case report and literature review

Uterine leiomyosarcoma is a rare malignancy accounting for 1-2% of uterine malignancies with an annual incidence of 0.5-7 per 100,000 women. It occurs mostly between the 5th to 7th decades of life hence found more among postmenopausal women.  The aetiology is mostly unknown however, in 0.2% of cases, it originates from sarcomatous degeneration in a pre-existing benign uterine fibroid. Leiomyosarcoma can be mistaken for uterine leiomyoma also known as the uterine fibroid.  It is an aggressive tumour that has a poor prognosis, with or without treatment. This case report aimed to report and discuss the occurrence of leiomyosarcoma as a differential diagnosis of abnormal uterine bleeding in this environment among other conditions. This will bring to the fore awareness among gynaecologists, pathologists, radiologists and oncologists that leiomyosarcoma of the uterus, though rare, should be considered in cases of menorrhagia with suspected uterine fibroid to avoid mistaking it for a diagnosis of uterine fibroid/leiomyoma. It is, therefore, imperative to consider leiomyosarcoma in a pre-menopausal and perimenopausal women diagnosed of abnormal uterine bleeding with symptomatic uterine fibroid. MRI serves as a good tool in differentiating the two pathologies.

Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability

Evidence for perinatal and child health care guidelines in crisis settings: can Cochrane help?

<p>Abstract</p> <p>Background</p> <p>It is important that healthcare provided in crisis settings is based on the best available research evidence. We reviewed guidelines for child and perinatal health care in crisis situations to determine whether they were based on research evidence, whether Cochrane systematic reviews were available in the clinical areas addressed by these guidelines and whether summaries of these reviews were provided in Evidence Aid.</p> <p>Methods</p> <p>Broad internet searches were undertaken to identify relevant guidelines. Guidelines were appraised using AGREE and the clinical areas that were relevant to perinatal or child health were extracted. We searched The Cochrane Database of Systematic Reviews to identify potentially relevant reviews. For each review we determined how many trials were included, and how many were conducted in resource-limited settings.</p> <p>Results</p> <p>Six guidelines met selection criteria. None of the included guidelines were clearly based on research evidence. 198 Cochrane reviews were potentially relevant to the guidelines. These reviews predominantly addressed nutrient supplementation, breastfeeding, malaria, maternal hypertension, premature labour and prevention of HIV transmission. Most reviews included studies from developing settings. However for large portions of the guidelines, particularly health services delivery, there were no relevant reviews. Only 18 (9.1%) reviews have summaries in Evidence Aid.</p> <p>Conclusions</p> <p>We did not identify any evidence-based guidelines for perinatal and child health care in disaster settings. We found many Cochrane reviews that could contribute to the evidence-base supporting future guidelines. However there are important issues to be addressed in terms of the relevance of the available reviews and increasing the number of reviews addressing health care delivery.</p