Patellar tendon in vivo regional strain with varying knee angle

Purpose: Descriptive data on the aspects of site specific in vivo tendon strain with varying knee joint angle are non-existent. The present study determines and compares surface and deep layer strain of the patellar tendon during isometric contractions across a range of knee joint angles. Methods: Male participants (age 22.0 ± 3.4) performed ramped isometric knee extensions at knee joint angles of 900, 700, 500 and 300 of flexion. Strain patterns of the anterior and posterior regions of the patellar tendon were determined using real-time B-mode ultrasonography at each knee joint angle. Regional strain measures were compared using an automated pixel tracking method. Results: Strain was seen to be greatest for both the anterior and posterior regions with the knee at 900 (7.76 ± 0.89% and 5.06 ± 0.76%). Anterior strain was seen to be significantly greater (p<0.05) than posterior strain for all knee angles apart from 300, 900 = (7.76 vs. 5.06%), 700 = (4.77 vs. 3.75%), and 500 = (3.74 vs. 2.90%). The relative strain (ratio of anterior to posterior), was greatest with the knee joint angle at 900, and decreased as the knee joint angle reduced. Conclusions: The results from this study indicate that not only are there greater absolute tendon strains with the knee in greater flexion, but that the knee joint angle affects the regional strain differentially, resulting in greater shear between the tendon layers with force application when the knee is in greater degrees of flexion. These results have important implications for rehabilitation and training

Trisomy 9 syndrome in a neonate with unusual features

Aim of the Work: To report a newborn infant with multiple congenital anomalies and apparent complete trisomy 9 in the blood. Review will be included.Methods: Clinical examination, TORCH screening, echocardiography, skeletal survey, ultrasound head and abdomen were done. In addition chromosomal analysis of a peripheral blood sample using GTG, CBG banding and FISH techniques were employed.Results: Multiple congenital anomalies including craniofacial features, centralnervous, cardiovascular, skeletal, gastric and urogenital systems becauseof chromosomal abnormality which indicated: 47, XY, inv (9) (p12;q13) + inv(9) (p12;q13) mat. Conclusion: Our case could be a new case of apparently complete trisomy 9syndrome with unusual findings.Key Words: Trisomy 9, congenital anomalies, karyotype, FIS

Biosurfactant as the next antimicrobial agents in pharmaceutical applications

The number of patients with antimicrobial resistance is growing as a result of new emerging microbes or overuse of antibiotics. A new substitute to the existing antimicrobial agents is important in time to come to control the mortality rate in the global population. Natural substances, like biosurfactants or commonly known as microbial surfactants could be a potential antimicrobial agent to medical personnel’s consideration as some biosurfactants exhibits antimicrobial activity. Hence, this paper will briefly highlight some of the findings from contemporary researchers who have tested different biosurfactants for potential antimicrobial activity

A Retrospective Study of Common Diseases of Animals in a Private Clinic in Kaduna Metropolitan

Data from clinical records of ECWA Veterinary Clinic, Kaduna, were retrieved for diseases of livestock retrospectively over a period of 10 years (January1997 – December 2006). The data was analyzed using descriptive statistics. The results indicate that a total of 5296 cases were handled during the 10 year study period and 48 different disease conditions werediagnosed and treated. Of the 48 disorders, Helminthosis appeared to be the most common disease condition with 2177(41%) of all cases handled, followed by Piroplasmosis 771(14.2%), Myiasis 572(10.9%), Bacterial infections 538(10.7%), Ectoparasitism 318(6%), Canine parvoviral enteritis267(5.04%), Mange 242(4.7%), Traumatic injury 1 3 2 ( 2 . 5 1%) , S e p t i c emi a 8 0 ( 1 . 5%) a n d Dermatomycosis 40(0.55%). Other conditionshandled included Caudectomy 20(0.38%), hematoma 16(0.30%), castration 15(0.28%), canine distemper 11(0.21%), food poisoning, fracture, infectious canine hepatitis presenting 10 (0.19%) each. Othersinclude Orchidectomy 7(0.13%), pinnal ulcers 6(0.11%), malnutrition 5(0.09%), organophosphate poisoning and still were handled 4 (0.08%) times each, while Conjuctivitis and Orchitis were handled only 3(0.06%) times each. There are other 11 diseases grouped as A which appeared only twice each throughout the study totaling 22(0.42%) and other 13 diseases grouped as B appeared only once each totaling 13(0.25%). Canine species were the most presented of all animal species with 4413(83.3%), followed by bovine 383(7.23%), ovine 260(4.9%), caprine 170(3.2%), porcine 50(0.94%), feline 19(0.35%) and equine 1(0.02%). Lack of routine de-worming and location of the clinic is responsiblefor this outcome. The findings elucidate the relevance of private veterinary clinics in disease reporting.Keywords: Common diseases of livestock, Helminthosis, Piroplasmosis, ECWA Veterinary clinic, Kaduna Stat

Application of Metaheuristic Algorithms and ANN Model for Univariate Water Level Forecasting

With the rapid development of machine learning (ML) models, the artificial neural network (ANN) is being increasingly applied for forecasting hydrological processes. However, researchers have not treated hybrid ML models in much detail. To address these issues, this study herein suggests a novel methodology to forecast the monthly water level (WL) based on multiple lags of the Tigris River in Al-Kut, Iraq, over ten years. The methodology includes preprocessing data methods, and the ANN model optimises with a marine predator algorithm (MPA). In the optimisation procedure, to decrease uncertainty and expand the predicting range, the slime mould algorithm (SMA-ANN), constriction coefficient-based particle swarm optimisation and chaotic gravitational search algorithms (CPSOCGSA-ANN), and particle swarm optimisation (PSO-ANN) are applied to compare and validate the MPA-ANN model performance. Analysis of results revealed that the data pretreatment methods improved the original data quality and selected the ideal predictors' scenario by singular spectrum analysis and mutual information methods, respectively. For example, the correlation coefficient of the first lag improved from 0.648 to 0.938. Depending on various evaluation metrics, MPA-ANN tends to forecast WL better than SMA-ANN, PSO-ANN, and CPSOCGSA-ANN algorithms with coefficients of determination of 0.94, 0.81, 0.85, and 0.90, respectively. Evidence shows that the proposed methodology yields excellent results, with a scatter index equal to 0.002. The research outcomes represent an additional step towards evolving various hybrid ML techniques, which are valuable to practitioners wishing to forecast WL data and the management of water resources in light of environmental shifts

Application of hybrid machine learning models and data pre-processing to predict water level of watersheds: Recent trends and future perspective

The community’s well-being and economic livelihoods are heavily influenced by the water level of watersheds. The changes in water levels directly affect the circulation processes of lakes and rivers that control water mixing and bottom sediment resuspension, further affecting water quality and aquatic ecosystems. Thus, these considerations have made the water level monitoring process essential to save the environment. Machine learning hybrid models are emerging robust tools that are successfully applied for water level monitoring. Various models have been developed, and selecting the optimal model would be a lengthy procedure. A timely, detailed, and instructive overview of the models’ concepts and historical uses would be beneficial in preventing researchers from overlooking models’ potential selection and saving significant time on the problem. Thus, recent research on water level prediction using hybrid machines is reviewed in this article to present the “state of the art” on the subject and provide some suggestions on research methodologies and models. This comprehensive study classifies hybrid models into four types algorithm parameter optimisation-based hybrid models (OBH), pre-processing-based hybrid models (PBH), the components combination-based hybrid models (CBH), and hybridisation of parameter optimisation-based with preprocessing-based hybrid models (HOPH); furthermore, it explains the pre-processing of data in detail. Finally, the most popular optimisation methods and future perspectives and conclusions have been discussed

Mutations underlying 3-Hydroxy-3-Methylglutaryl CoA Lyase deficiency in the Saudi population

BACKGROUND: 3-Hydroxy-3-Methylglutaric aciduria (3HMG, McKusick: 246450) is an autosomal recessive branched chain organic aciduria caused by deficiency of the enzyme 3-Hydroxy-3-Methylglutaryl CoA lyase (HL, HMGCL, EC 4.1.3.4). HL is encoded by HMGCL gene and many mutations have been reported. 3HMG is commonly observed in Saudi Arabia. METHODS: We utilized Whole Genome Amplification (WGA), PCR and direct sequencing to identify mutations underlying 3HMG in the Saudi population. Two patients from two unrelated families and thirty-four 3HMG positive dried blood spots (DBS) were included. RESULTS: We detected the common missense mutation R41Q in 89% of the tested alleles (64 alleles). 2 alleles carried the frame shift mutation F305fs (-2) and the last two alleles had a novel splice site donor IVS6+1G>A mutation which was confirmed by its absence in more than 100 chromosomes from the normal population. All mutations were present in a homozygous state, reflecting extensive consanguinity. The high frequency of R41Q is consistent with a founder effect. Together the three mutations described account for >94% of the pathogenic mutations underlying 3HMG in Saudi Arabia. CONCLUSION: Our study provides the most extensive genotype analysis on 3HMG patients from Saudi Arabia. Our findings have direct implications on rapid molecular diagnosis, prenatal and pre-implantation diagnosis and population based prevention programs directed towards 3HMG

An empirical approach towards the efficient and optimal production of influenza-neutralizing ovine polyclonal antibodies demonstrates that the novel adjuvant CoVaccine HT(TM) is functionally superior to Freund's adjuvant

Passive immunotherapies utilising polyclonal antibodies could have a valuable role in preventing and treating infectious diseases such as influenza, particularly in pandemic situations but also in immunocompromised populations such as the elderly, the chronically immunosuppressed, pregnant women, infants and those with chronic diseases. The aim of this study was to optimise current methods used to generate ovine polyclonal antibodies. Polyclonal antibodies to baculovirus-expressed recombinant influenza haemagglutinin from A/Puerto Rico/8/1934 H1N1 (PR8) were elicited in sheep using various immunisation regimens designed to investigate the priming immunisation route, adjuvant formulation, sheep age, and antigen dose, and to empirically ascertain which combination maximised antibody output. The novel adjuvant CoVaccine HT™ was compared to Freund’s adjuvant which is currently the adjuvant of choice for commercial production of ovine polyclonal Fab therapies. CoVaccine HT™ induced significantly higher titres of functional ovine anti-haemagglutinin IgG than Freund’s adjuvant but with fewer side effects, including reduced site reactions. Polyclonal hyperimmune sheep sera effectively neutralised influenza virus in vitro and, when given before or after influenza virus challenge, prevented the death of infected mice. Neither the age of the sheep nor the route of antigen administration appeared to influence antibody titre. Moreover, reducing the administrated dose of haemagglutinin antigen minimally affected antibody titre. Together, these results suggest a cost effective way of producing high and sustained yields of functional ovine polyclonal antibodies specifically for the prevention and treatment of globally significant diseases.Natalie E. Stevens, Cara K. Fraser, Mohammed Alsharifi, Michael P. Brown, Kerrilyn R. Diener, John D. Haybal

SEND: a system for electronic notification and documentation of vital sign observations

Background: Recognising the limitations of a paper-based approach to documenting vital sign observations and responding to national clinical guidelines, we have explored the use of an electronic solution that could improve the quality and safety of patient care. We have developed a system for recording vital sign observations at the bedside, automatically calculating an Early Warning Score, and saving data such that it is accessible to all relevant clinicians within a hospital trust. We have studied current clinical practice of using paper observation charts, and attempted to streamline the process. We describe our user-focussed design process, and present the key design decisions prior to describing the system in greater detail. Results: The system has been deployed in three pilot clinical areas over a period of 9 months. During this time, vital sign observations were recorded electronically using our system. Analysis of the number of observations recorded (21,316 observations) and the number of active users (111 users) confirmed that the system is being used for routine clinical observations. Feedback from clinical end-users was collected to assess user acceptance of the system. This resulted in a System Usability Scale score of 77.8, indicating high user acceptability. Conclusions: Our system has been successfully piloted, and is in the process of full implementation throughout adult inpatient clinical areas in the Oxford University Hospitals. Whilst our results demonstrate qualitative acceptance of the system, its quantitative effect on clinical care is yet to be evaluated