The impact of the COVID-19 pandemic on inequalities in lifestyle behaviours and mental health and wellbeing of elementary school children in northern Canada.

Objectives: The COVID-19 pandemic has negatively affected children's lifestyle behaviours and mental health and wellbeing, and concerns have been raised that COVID-19 has also increased health inequalities. No study to date has quantified the impact of COVID-19 on health inequalities among children. We compared pre-pandemic vs. post-lockdown inequalities in lifestyle behaviours and mental health and wellbeing among children living in rural and remote northern communities. Methods: We surveyed 473 grade 4-6 students (9-12 years of age) from 11 schools in rural and remote communities in northern Canada in 2018 (pre-pandemic), and 443 grade 4-6 students from the same schools in 2020 (post-lockdown). The surveys included questions on sedentary behaviours, physical activity, dietary intake, and mental health and wellbeing. We measured inequality in these behaviors using the Gini coefficient, a unitless measure ranging from 0 to 1 with a higher value indicating greater inequality. We used temporal changes (2020 vs. 2018) in Gini coefficients to assess the impact of COVID-19 on inequalities in lifestyle behaviours and mental health and wellbeing separately among girls and boys. Results: Inequalities in all examined lifestyle behaviours increased between 2018 and 2020. Inequalities in watching TV, playing video games, and using a cell phone increased among girls, while inequalities in playing video games, using computers and tablets, and consumption of sugar, salt, saturated fat and total fat increased among boys. Changes in inequalities in mental health and wellbeing were small and not statistically significant. Conclusion: The findings suggest that the COVID-19 pandemic has exacerbated inequalities in lifestyle behaviours among children living in rural and remote northern communities. If not addressed, these differences may translate into exacerbated inequalities in future health. The findings further suggest that school health programs can help mitigate the negative impact of the pandemic on lifestyle behaviours and mental health and wellbeing.

Validation studies on migraine diagnostic tools for use in nonclinical settings: a systematic review / Estudos de validação de ferramentas de diagnóstico de enxaqueca (migrânea) para uso em ambientes não clínicos: uma revisão sistemática

Abstract Background Migraine underdiagnosis and undertreatment are so widespread, that hence is essential to diagnose migraine sufferers in nonclinical settings. A systematic review of validation studies on migraine diagnostic tools applicable to nonclinical settings can help researchers and practitioners in tool selection decisions. Objective To systematically review and critically assess published validation studies on migraine diagnostic tools for use in nonclinical settings, as well as to describe their diagnostic performance. Methods A multidisciplinary workgroup followed transparent and systematic procedures to collaborate on this work. PubMed, Medline, and Web of Science were searched for studies up to January 17, 2022. The QUADAS-2 was employed to assess methodological quality, and the quality thresholds adopted by the Global Burden Disease study were used to tail signaling questions. Results From 7,214 articles identified, a total of 27 studies examining 19 tools were eligible for inclusion. There has been no high-quality evidence to support any tool for use of migraine diagnosis in nonclinical settings. The diagnostic accuracy of the ID-migraine, structured headache and HARDSHIP questionnaires have been supported by moderate-quality evidence, with sensitivity and specificity above 70%. Of them, the HARDSHIP questionnaire has been the most extensively validated. The remaining 16 tools have provided poor-quality evidence for migraine diagnosis in nonclinical populations. Conclusions Up till now, the HARDSHIP questionnaire is the optimal choice for diagnosing migraine in nonclinical settings, with satisfactory diagnostic accuracy supported by moderate methodological quality. This work reveals the crucial next step, which is further high-quality validation studies in diverse nonclinical population groups.

Resumo Antecedentes O sub-diagnóstico e o subtratamento da enxaqueca são tão difundidos que, portanto, é essencial para diagnosticar os portadores de enxaqueca em ambientes não-clínicos. Uma revisão sistemática dos estudos de validação das ferramentas de diagnóstico da enxaqueca aplicáveis a ambientes não-clínicos pode ajudar os pesquisadores e profissionais nas decisões de seleção de ferramentas. Objetivo Revisar sistematicamente e avaliar criticamente estudos de validação publicados sobre ferramentas de diagnóstico da enxaqueca para uso em ambientes não-clínicos, bem como descrever seu desempenho diagnóstico. Métodos Um grupo de trabalho multidisciplinar seguiu procedimentos transparentes e sistemáticos para colaborar neste trabalho. PubMed, Medline e Web of Science foram pesquisados por estudos até 17 de janeiro de 2022. O QUADAS-2 foi empregado para avaliar a qualidade metodológica, e os limites de qualidade adotados pelo estudo da Global Burden Disease foram usados para responder a questões de sinalização. Resultados De 7.214 artigos identificados, um total de 27 estudos examinando 19 ferramentas foram elegíveis para inclusão. Não houve evidência de alta qualidade para apoiar qualquer ferramenta para o uso de diagnóstico de enxaqueca em ambientes não clínicos. A precisão diagnóstica do ID-Migraine, questionário de dor de cabeça estruturada e questionário HARDSHIP foram apoiados por evidências de qualidade moderada, com sensibilidade e especificidade acima de 70%. Deles, o questionário HARDSHIP foi o mais amplamente validado. As 16 ferramentas restantes forneceram provas de má qualidade para o diagnóstico de enxaqueca em populações não-clínicas. Conclusões Até agora, o questionário HARDSHIP é a escolha ideal para o diagnóstico da enxaqueca em ambientes não-clínicos, com precisão diagnóstica satisfatória apoiada por uma qualidade metodológica moderada. Este trabalho revela o próximo passo crucial, que é a realização de mais estudos de validação de alta qualidade em diversos grupos populacionais não-clínicos.

Association between Migraine and Workplace Social Support in the Social Context of China: Using a Validated Chinese Version of the DCSQ.

BACKGROUND: Workplace social support might have a protective function against migraine in the social context of China, as close co-worker relationships and collectivism are acknowledged as work values in Chinese society. OBJECTIVES: This paper aimed to analyse the association between migraine and workplace social support. The validity and reliability of the Chinese version of the Support scale of the Demand-Control-Support Questionnaire (DCSQ) used were also determined. METHODS: Following international guidelines, this study was carried out in two stages. Stage I involved translations and pilot testing to assess content and face validity of the Chinese version of the DCSQ Support scale. Stage II was a cross-sectional survey (N = 677 bank employees) to evaluate structural validity, internal consistency and test-retest reliability of the Support scale, as well as to examine the association between workplace social support and a migraine-positive diagnosis. RESULTS: A high level of social support in the workplace was associated with a 74% decreased likelihood of migraine (adjusted OR = 0.26, 95%CI: 0.14-0.46). Of the six aspects of workplace social support, co-worker support had the greatest protective effect (adjusted OR = 0.49, 95% CI: 0.39-0.60). The Chinese version of the DCSQ Support scale established satisfactory content and face validity (I-CVIs ≥ 0.78; S-CVIAVE ≥ 0.90). Confirmatory factor analysis verified its one-dimensional theoretical factor, with adequate internal consistency (Cronbach's α 0.98; item-total correlations ≥ 0.80) and test-retest reliability (weighted Kappa coefficients 0.81-0.87; percentages agreement 85.23-88.92%). CONCLUSIONS: In the Chinese social context, workplace social support could protect against migraine, with the strongest benefit coming from co-workers. This study also provides a Chinese-language DCSQ Support scale as a valid and reliable instrument for measuring workplace social support.

Validation studies on migraine diagnostic tools for use in nonclinical settings: a systematic review.

BACKGROUND: Migraine underdiagnosis and undertreatment are so widespread, that hence is essential to diagnose migraine sufferers in nonclinical settings. A systematic review of validation studies on migraine diagnostic tools applicable to nonclinical settings can help researchers and practitioners in tool selection decisions. OBJECTIVE: To systematically review and critically assess published validation studies on migraine diagnostic tools for use in nonclinical settings, as well as to describe their diagnostic performance. METHODS: A multidisciplinary workgroup followed transparent and systematic procedures to collaborate on this work. PubMed, Medline, and Web of Science were searched for studies up to January 17, 2022. The QUADAS-2 was employed to assess methodological quality, and the quality thresholds adopted by the Global Burden Disease study were used to tail signaling questions. RESULTS: From 7,214 articles identified, a total of 27 studies examining 19 tools were eligible for inclusion. There has been no high-quality evidence to support any tool for use of migraine diagnosis in nonclinical settings. The diagnostic accuracy of the ID-migraine, structured headache and HARDSHIP questionnaires have been supported by moderate-quality evidence, with sensitivity and specificity above 70%. Of them, the HARDSHIP questionnaire has been the most extensively validated. The remaining 16 tools have provided poor-quality evidence for migraine diagnosis in nonclinical populations. CONCLUSIONS: Up till now, the HARDSHIP questionnaire is the optimal choice for diagnosing migraine in nonclinical settings, with satisfactory diagnostic accuracy supported by moderate methodological quality. This work reveals the crucial next step, which is further high-quality validation studies in diverse nonclinical population groups.

ANTECEDENTES: O sub-diagnóstico e o subtratamento da enxaqueca são tão difundidos que, portanto, é essencial para diagnosticar os portadores de enxaqueca em ambientes não-clínicos. Uma revisão sistemática dos estudos de validação das ferramentas de diagnóstico da enxaqueca aplicáveis a ambientes não-clínicos pode ajudar os pesquisadores e profissionais nas decisões de seleção de ferramentas. OBJETIVO: Revisar sistematicamente e avaliar criticamente estudos de validação publicados sobre ferramentas de diagnóstico da enxaqueca para uso em ambientes não-clínicos, bem como descrever seu desempenho diagnóstico. MéTODOS: Um grupo de trabalho multidisciplinar seguiu procedimentos transparentes e sistemáticos para colaborar neste trabalho. PubMed, Medline e Web of Science foram pesquisados por estudos até 17 de janeiro de 2022. O QUADAS-2 foi empregado para avaliar a qualidade metodológica, e os limites de qualidade adotados pelo estudo da Global Burden Disease foram usados para responder a questões de sinalização. RESULTADOS: De 7.214 artigos identificados, um total de 27 estudos examinando 19 ferramentas foram elegíveis para inclusão. Não houve evidência de alta qualidade para apoiar qualquer ferramenta para o uso de diagnóstico de enxaqueca em ambientes não clínicos. A precisão diagnóstica do ID-Migraine, questionário de dor de cabeça estruturada e questionário HARDSHIP foram apoiados por evidências de qualidade moderada, com sensibilidade e especificidade acima de 70%. Deles, o questionário HARDSHIP foi o mais amplamente validado. As 16 ferramentas restantes forneceram provas de má qualidade para o diagnóstico de enxaqueca em populações não-clínicas. CONCLUSõES: Até agora, o questionário HARDSHIP é a escolha ideal para o diagnóstico da enxaqueca em ambientes não-clínicos, com precisão diagnóstica satisfatória apoiada por uma qualidade metodológica moderada. Este trabalho revela o próximo passo crucial, que é a realização de mais estudos de validação de alta qualidade em diversos grupos populacionais não-clínicos.

A Novel Theoretical Investigation of the Abu-Shady-Kaabar Fractional Derivative as a Modeling Tool for Science and Engineering.

A newly proposed generalized formulation of the fractional derivative, known as Abu-Shady-Kaabar fractional derivative, is investigated for solving fractional differential equations in a simple way. Novel results on this generalized definition is proposed and verified, which complete the theory introduced so far. In particular, the chain rule, some important properties derived from the mean value theorem, and the derivation of the inverse function are established in this context. Finally, we apply the results obtained to the derivation of the implicitly defined and parametrically defined functions. Likewise, we study a version of the fixed point theorem for α-differentiable functions. We include some examples that illustrate these applications. The obtained results of our proposed definition can provide a suitable modeling guide to study many problems in mathematical physics, soliton theory, nonlinear science, and engineering.

A Novel Computational Tool for the Fractional-Order Special Functions Arising from Modeling Scientific Phenomena via Abu-Shady-Kaabar Fractional Derivative.

Recently, a generalized fractional derivative formulation, known as Abu-Shady-Kaabar fractional derivative, is studied in detail which produces satisfactory results that are consistent with conventional definitions of fractional derivative such as Caputo and Riemann-Liouville. To derive the fractional forms of special functions, the generalized fractional derivative is used. The findings demonstrate that the current findings are compatible with Caputo findings. In addition, the fractional solution to the Bessel equation is found. While modeling phenomena in engineering, physical, and health sciences, special functions can be encountered in most modeling scenarios related to electromagnetic waves, hydrodynamics, and other related models. Therefore, there is a need for a computational tool for computing special functions in the sense of fractional calculus. This tool provides a straightforward technique for some fractional-order special functions while modeling these scientific phenomena in science, medicine, and engineering.

Mathematical modeling of COVID-19 pandemic in India using Caputo-Fabrizio fractional derivative.

The range of effectiveness of the novel corona virus, known as COVID-19, has been continuously spread worldwide with the severity of associated disease and effective variation in the rate of contact. This paper investigates the COVID-19 virus dynamics among the human population with the prediction of the size of epidemic and spreading time. Corona virus disease was first diagnosed on January 30, 2020 in India. From January 30, 2020 to April 21, 2020, the number of patients was continuously increased. In this scientific work, our main objective is to estimate the effectiveness of various preventive tools adopted for COVID-19. The COVID-19 dynamics is formulated in which the parameters of interactions between people, contact tracing, and average latent time are included. Experimental data are collected from April 15, 2020 to April 21, 2020 in India to investigate this virus dynamics. The Genocchi collocation technique is applied to investigate the proposed fractional mathematical model numerically via Caputo-Fabrizio fractional derivative. The effect of presence of various COVID parameters e.g. quarantine time is also presented in the work. The accuracy and efficiency of the outputs of the present work are demonstrated through the pictorial presentation by comparing it to known statistical data. The real data for COVID-19 in India is compared with the numerical results obtained from the concerned COVID-19 model. From our results, to control the expansion of this virus, various prevention measures must be adapted such as self-quarantine, social distancing, and lockdown procedures.

Ovine Pasteurellosis Vaccine: Assessment of the Protective Antibody Titer and Recognition of the Prevailing Serotypes.

Sheep husbandry is considered one of the most important activities in the socio-economic development in the Middle East region, especially in Iraq and Islamic Republic of Iran (IRI). Therefore this study was designed to evaluate the level of ovine pasteurellosis vaccine protective antibody titer and identification of the prevailing serotypes in Iraq (Basrah, Baghdad, Tikrit, Mosul, Erbil). The vaccine was made from pasteurella multosida Bio-type A and the serotypes of Mannheimia haemolytica. This investigation was performed from September 2021 to January 2022, in Iraq. Sheep blood sera samples were obtained from control unvaccinated and vaccinated sheep after 14, 21 and 28 days post vaccination. The results showed that out of 319 sheep blood sera samples which were evaluated using indirect Haemagglutination (IHA) test to detect Mannheimia haemolytica serotypes, the high prevalence (100 %) of M. haemolytica A2 was found in all the five study regions area, while 96.5 % was M. haemolytica A7 and 88.1 % was M. haemolytica A1. The level of antibody titer was measured by specific serum antibody titer of pasteurella multosida Bio-type A. The results revealed that out of 268 vaccinated blood sera samples the overall antibody titer were 12 (3.8 %), 16 (5%) and 17 (5.3 %) for protective antibody titer of 1:160, 1:80 and 1:40 respectively and for antibody titer of 1:20 were 15 (4.7%) and for antibody titer of 1:10 were 17 (5.3 %), whereas the antibody titer in the control group was 4 (7.8 %). The result of this study indicated that the vaccine administered has limited protective power against pasteurella multocida Bio-type A which lead to researchers for further study on identification of specific strain of pasteurella multosida and development of multivalent vaccine including the most prevalent pasteurella serotypes.

Optimization: Molecular Communication Networks for Viral Disease Analysis Using Deep Leaning Autoencoder.

Developing new treatments for emerging infectious diseases in infectious and noninfectious diseases has attracted a particular attention. The emergence of viral diseases is expected to accelerate; these data indicate the need for a proactive approach to develop widely active family specific and cross family therapies for future disease outbreaks. Viral disease such as pneumonia, severe acute respiratory syndrome type 2, HIV infection, and Hepatitis-C virus can cause directly and indirectly cardiovascular disease (CVD). Emphasis should be placed not only on the development of broad-spectrum molecules and antibodies but also on host factor therapy, including the reutilization of previously approved or developing drugs. Another new class of therapeutics with great antiviral therapeutic potential is molecular communication networks using deep learning autoencoder (DL-AEs). The use of DL-AEs for diagnosis and prognosis prediction of infectious and noninfectious diseases has attracted a particular attention. MCN is map to molecular signaling and communication that are found inside and outside the human body where the goal is to develop a new black box mechanism that can serve the future robust healthcare industry (HCI). MCN has the ability to characterize the signaling process between cells and infectious disease locations at various levels of the human body called point-to-point MCN through DL-AE and provide targeted drug delivery (TDD) environment. Through MCN, and DL-AE healthcare provider can remotely measure biological signals and control certain processes in the required organism for the maintenance of the patient's health state. We use biomicrodevices to promote the real-time monitoring of human health and storage of the gathered data in the cloud. In this paper, we use the DL-based AE approach to design and implement a new drug source and target for the MCN under white Gaussian noise. Simulation results show that transceiver executions for a given medium model that reduces the bit error rate which can be learned. Then, next development of molecular diagnosis such as heart sounds is classified. Furthermore, biohealth interface for the inside and outside human body mechanism is presented, comparative perspective with up-to-date current situation about MCN.

Deep Learning in Cancer Diagnosis and Prognosis Prediction: A Minireview on Challenges, Recent Trends, and Future Directions.

Deep learning (DL) is a branch of machine learning and artificial intelligence that has been applied to many areas in different domains such as health care and drug design. Cancer prognosis estimates the ultimate fate of a cancer subject and provides survival estimation of the subjects. An accurate and timely diagnostic and prognostic decision will greatly benefit cancer subjects. DL has emerged as a technology of choice due to the availability of high computational resources. The main components in a standard computer-aided design (CAD) system are preprocessing, feature recognition, extraction and selection, categorization, and performance assessment. Reduction of costs associated with sequencing systems offers a myriad of opportunities for building precise models for cancer diagnosis and prognosis prediction. In this survey, we provided a summary of current works where DL has helped to determine the best models for the cancer diagnosis and prognosis prediction tasks. DL is a generic model requiring minimal data manipulations and achieves better results while working with enormous volumes of data. Aims are to scrutinize the influence of DL systems using histopathology images, present a summary of state-of-the-art DL methods, and give directions to future researchers to refine the existing methods.

Exploiting Feature Selection and Neural Network Techniques for Identification of Focal and Nonfocal EEG Signals in TQWT Domain.

For drug resistance patients, removal of a portion of the brain as a cause of epileptic seizures is a surgical remedy. However, before surgery, the detailed analysis of the epilepsy localization area is an essential and logical step. The Electroencephalogram (EEG) signals from these areas are distinct and are referred to as focal, while the EEG signals from other normal areas are known as nonfocal. The visual inspection of multiple channels for detecting the focal EEG signal is time-consuming and prone to human error. To address this challenge, we propose a novel method based on differential operator and Tunable Q-factor wavelet transform (TQWT) to distinguish the focal and nonfocal signals. For this purpose, first, the EEG signal was differenced and then decomposed by TQWT. Second, several entropy-based features were derived from the TQWT subbands. Third, the efficacy of the six binary feature selection algorithms, binary bat algorithm (BBA), binary differential evolution (BDE) algorithm, firefly algorithm (FA), genetic algorithm (GA), grey wolf optimization (GWO), and particle swarm optimization (PSO), was evaluated. In the end, the selected features were fed to several machine learning and neural network classifiers. We observed that the PSO with neural networks provides an effective solution for the application of focal EEG signal detection. The proposed framework resulted in an average classification accuracy of 97.68%, a sensitivity of 97.26%, and a specificity of 98.11% in a tenfold cross-validation strategy, which is higher than the state of the art used in the public Bern-Barcelona EEG database.

Mental Health and Wellbeing of 9-12-year-old Children in Northern Canada Before the COVID-19 Pandemic and After the First Lockdown.

Objectives: Children's mental health and wellbeing declined during the first COVID-19 lockdown (Spring 2020), particularly among those from disadvantaged settings. We compared mental health and wellbeing of school-aged children observed pre-pandemic in 2018 and after the first lockdown was lifted and schools reopened in Fall 2020. Methods: In 2018, we surveyed 476 grade 4-6 students (9-12 years old) from 11 schools in socioeconomically disadvantaged communities in Northern Canada that participate in a school-based health promotion program targeting healthy lifestyle behaviours and mental wellbeing. In November-December 2020, we surveyed 467 grade 4-6 students in the same schools. The 12 questions in the mental health and wellbeing domain were grouped based on correlation and examined using multivariable logistic regression. Results: There were no notable changes pre-pandemic vs. post-lockdown in responses to each of the 12 questions or any of the sub-groupings. Conclusion: Supporting schools to implement health promotion programs may help mitigate the impact of the pandemic on children's mental health and wellbeing. The findings align with recent calls for schools to remain open as long as possible during the pandemic response.

Protective Effects of Magnesium Chloride on Liver Enzymes and Biomarkers of Oxidative Stress in high fat diet fed Rats.

The excessive consumption of high cholesterol diet has been associated with an increased incidence of obesity. This is because obesity induced pathologies with high mortality, such as complications of dyslipidaemia, diabetes mellitus, arthritis, hypertension, myocardial infarction, and hepatocellular carcinoma. Although the associated, disease are enhanced by formation of oxidative stress, lipid peroxidation and hypercholesterolaemia. Magnesium chloride is found to be beneficial in a wide range of diseases. Magnesium is one of the most neglected mineral in human body. It is crucial for a healthy and lasting life. Magnesium is responsible for the activation of more than 300 enzymes in the body. The present study intends to determine the protective effect of magnesium chloride on liver enzyme and biomarker of oxidative stress in high fat diet fed rats. Twenty (20) adult Male Wistar rats weighing (100 - 150) grams randomly divided into three treatments and one control groups of five rats each (n = 5). Group I Normal control receive normal feed only for 6weeks, Group II received high fat diet only for 6weeks, Group III received high fat diet with 250 mg/kg for 6weeks of mgcl2 and Group IV received 500 mg/kg for 6weeks of MgCl2 respectively all treatments were administered via oral route, at the end of the sixth week rats were euthanized and blood samples were drawn from the heart by cardiac puncture and used to estimate oxidative stress biomarkers (Superoxide dismutase, Catalase and Glutathione peroxidase), lipid peroxidation biomarkers (Malondialdehyde) and liver enzymes. Analysis of variance and Turkey's post hoc test were used to analyze the data obtained. In relation to the liver enzyme, the showed that there was a significant (p<0.05) decrease in value of AST, ALT and ALP in the group co-administered with the doses of the Magnesium chloride to compared to the control. For the oxidative stress biomarkers assessed, the results showed that there was significant decrease (P < 0.05) in the SOD, CAT and GPx level of the high fat diet fed groups, co-administered with   250 and 500 MgCl2, when compared with the high fat diet fed group only. Also, the lipid peroxidation shows significant (p<0.05) decrease in the groups administered the two doses of Magnesium chloride (250 and 500 mg/kg) respectively as compared to control. In relation to the liver enzyme, the showed that there were significant (p<0.05) changes in value of AST, ALT and ALP in the group co-administered with the two doses of the Magnesium chloride compared to the control. The result showed that high-fat diet induces ROS, dyslipidaemia and release of biological metabolite, as evidenced by the rise in oxidative stress and activities of liver enzymes. MgCl2 administration also protected the body against rise in the metabolites despite consumption of high-fat diet by the Wistar Rats.

Effects of Clove and Fermented Ginger on Blood Glucose, Leptin, Insulin and Insulin Receptor Levels in High Fat DietInduced Type 2 Diabetic Rabbits.

The aimed of this research is to evaluate the effects of clove and fermented ginger supplements on blood glucose,serum insulin, insulin receptor and Leptin levels of high fat diet-induced type 2 diabetes mellitus in rabbits. Clove and gingerare spices with records of medicinal value over decades. Thirty males rabbits weighing, 1-1.5kg were used for the research.Type 2 diabetes was induced by feeding the animals with a high fat diet for a period of eight weeks. Blood glucose levelswere determined after the induction period and rabbits having 140 mg/dL and above were selected for the study. The animalswere grouped into six groups with five (n=5) rabbits in each group: Group 1 (Normoglycemic control group.) received normalfeed and distilled water ad libitum for six weeks; Group 2 (Diabetic negative control group.) received normal feed anddistilled water ad libitum for six weeks; Groups 3 (Diabetic positive control.) received cholestran 0.26g/kg and normal feedfor a period of six weeks; Group 4 and 5 (diabetic rabbits) were fed on 12.5%, clove and 12.5% fermented gingerrespectively for a period of six weeks; while Group 6 were co-fed on 12.5% clove and 12.5% fermented ginger for a periodof six weeks. Fasting blood glucose levels were determined at weekly interval during the treatment period. At the end of theexperiment, the rabbits were euthanized by cervical dislocation and blood samples were collected for the determination ofinsulin, insulin receptor and leptin levels. A significantly (P<0.05) decrease in blood glucose levels was recorded in thesupplements treated groups compared to diabetic control group. Clove supplement been most effective and sustaining inantihyperglycemic activity, also appears with a significant decreasing effect on leptin levels compared to diabetic controlgroup. A significant increase in insulin levels was also noted in the fermented ginger treated group along with higher levelsof Leptin compared as compared to control group. In conclusion the result of the study show that clove and fermented gingersupplementation possesses anti-diabetic properties and may help in the control of hyperleptinaemia in type 2 diabetes.

An Observational Epidemiological Study of Exercise-induced Rhabdomyolysis Causing Acute Kidney Injury: A Single-center Experience.

Exercise-induced rhabdomyolysis (EIR) is an uncommon cause of severe rhabdomyolysis and a very rare cause of acute kidney injury (AKI). A prospective observational study of 25 patients diagnosed with EIR was conducted in a multispecialty hospital in Dubai, from 2009 to 2015. Five out of 25 patients experienced AKI necessitating temporary renal replacement therapy. The initial presentation, biochemical parameters, and clinical course of patients were monitored, to understand epidemiology and risk factors for the development of AKI. There was male preponderance (4 out of 5 patients), higher rate of systemic symptoms (all 5 patients) versus 60% in NRAKI), oligo-anuria (all 5 patients), compartment syndrome (3 out \of 5) and severe dehydration seen in patients with RAKI group. On laboratory evaluation, there was higher rise in creatinine kinase (CK) enzyme, serum and urine myoglobin levels impaired renal function on presentation, hyperuricemia, high D-dimer level, PCV of more than 55%, found to be associated with RAKI as compared to NRAKI group. Hematuria by positive urine dipstick with absent red blood cells on urinalysis, is an insensitive tool as was present in only 62% and 43% of RAKI and NRAKI groups, respectively. It was also observed that delayed pesentation for medical care, metabolic acidosis, were commonly associated with AKI. All patients with RAKI required RRT for a comparable period of time (3-4 weeks). In all of them, no deterioration or relapse reported on follow-up of 3 months.

Anti-hyperglycaemic Effects of Rutin on Blood Glucose, Oxidative Stress Biomarkers and Lipid Peroxidation in Alloxan-induced Hyperglycaemic Wistar Rats.

The present study investigated the anti-hyperglycaemic effect of rutin on blood glucose, oxidative stressbiomarkers and lipid peroxidation in alloxan induced hyperglycaemic wistar rats. Diabetes was induced in rats by anintraperitoneal (i.p) injection of alloxan monohydrate 150 mg/kg body weight. Twenty five wistar rats were divided asfollows; Group1 served as diabetic control received distilled water 2 mg/kg, Group served as positive control received 2mg/kg glibenclamide, 3, 4 and 5 received rutin at 50, 100 and 200 mg/kg body weight for 28 days respectively. At the end of the treatment, rats were sacrificed and the blood and serum were used for the analysis of blood glucose and oxidativestress biomarkers respectively. The determinations of blood glucose levels were carried out at intervals of 7, 14, 21 and 28days respectively Serum oxidative stress biomarkers lipid peroxidation, were done on the 28 days. Administrations of rutinat the three different doses 50,100 and 200 mg/kg to diabetic rats significantly (p<0.05) decreased the blood glucose levelsas compared to diabetic control. The dose of 200 mg/kg exhibited a maximum glucose lowering effect with blood glucoseof 102.8± 0.06 as compared to diabetic control 346.2±0.16. Furthermore, in relation to the oxidative stress biomarkers therewas a significant (p<0.05) increased in the levels of gluthathione peroxidase, superoxide dismutase and catalase as comparedto control. However, there was also a significant decreased in the malondialdehyde levels as compared to control. It may beconcluded that oral administration of Rutin for 28 days decreases blood glucose levels and prevented oxidative stress andantioxidant status in hyperglycaemic rats.

Effects of Fermented Ginger Rhizome (Zingiber officinale) and Fenu Greek (Trigonella foenum-graceum) Supplements on Oxidative stress and Lipid Peroxidation Biomarkers in Poloxamer-407 Induced -Hyperlipidemic Wistar Rats.

This research was aimed at investigating the Effects of Fermented Ginger Rhizome (Zingiber officinale) and Fenu Greek (Trigonella foenum-graceum) on Oxidative stress and Lipid Peroxidation Biomarkers in Poloxamer 407Induced-Hyperlipidemic Wistar Rats. Hyperlipidaemia was induced with poloxamer P407 (1.5 g/kg   b.w. i.p.) The Animals were grouped into six of five animals each group. Group 1 normal control, Group 2 served as the hyperlipidemic control, Group 3 administered 0.26 g/kg cholestyramine, Group 4 fed on Fenugreek 25% supplement. Group 5 fed on 25% fermented ginger supplement, while group 6 were fed on 25% ginger and fenu greek combined   respectively. All treatments were given for a period of four week. Serum antioxidant activities such as catalase (CAT), glutathione peroxidase (GPx), Superoxide dismutase (SOD) and Malondialdehyde were evaluated.  As regards to the catalase activity there was a significant decrease in the groups' fed on 25% fenugreek and 25% fermented ginger supplements respectively. However, co-fed with both supplements significantly increase the catalase activity as compared with the hyperlipidaemic control untreated. Comparism with the positive control cholestyramine, there was also a significant increase. Also in relation to the SOD activity there was a significant increase in the activity as compared with the hyperlipidemic control. Furthermore, the Gpx activity there was a significant increase in the as compared with the hyperlipidemic control. oxidative stress biomarker activities SOD) there was significant increase (p<0.05) when compared with hyperlipidemic control. There was a significant (p<0.05) decrease in the Malondialdehyde levels in the groups fed with the supplement when compared with hyperlipidemic control. In conclusion supplements of Fenugreek and Ginger improved antioxidant status and reduced Malondialdehyde in Poloxamer-407 Induced-Hyperlipidemic Wistar Rats.

COMMUNITY CO-DESIGNED SCHISTOSOMIASIS CONTROL INTERVENTIONS FOR SCHOOL-AGED CHILDREN IN ZANZIBAR.

Top-down biomedical interventions to control schistosomiasis in sub-Saharan Africa have had limited success, primarily because they fail to engage with the social, political, economic and ecological contexts in which they are delivered. Despite the call to foster community engagement and to adapt interventions to local circumstances, programmes have rarely embraced such an approach. This article outlines a community co-designed process, based upon Human-Centered Design, to demonstrate how this approach works in practice. It is based on initial work undertaken by social science researchers, public health practitioners and community members from the Zanzibar Islands, Tanzania, between November 2011 and December 2013. During the process, 32 community members participated in a qualitative and quantitative data-driven workshop where they interpreted data on local infections from S. haematobium and co-designed interventions with the assistance of a facilitator trained in the social sciences. These interventions included the implementation of novel school-based education and training, the identification of relevant safe play activities and events at local schools, the installation of community-designed urinals for boys and girls and the installation of community-designed laundry-washing platforms to reduce exposure to cercariae-contaminated fresh water. It is suggested that the a community co-designed process, drawing from Human-Centered Design principles and techniques, enables the development of more sustainable and effective interventions for the control of schistosomiasis.

Erratum to: Development of novel multiplex microsatellite polymerase chain reactions to enable high-throughput population genetic studies of Schistosoma haematobium.

Unfortunately, the original version of this article [1], contained a mistake. In Table 1, the primers for Sh6 and Sh9 were included incorrectly. Instead of GGGATGTATGCAGACTTG TTGTTTGGCTGCAGTAAC and GCTGAGCTTGAGATTG CTTCTGTCCCATCGATACC they should have been Sh6 Forward Primer GGTGGATTACGCAATAG, Sh6 Reverse Primer TTTAATCAACCGGGTGTC and Sh9 Forward Primer GGGATGTATGCAGACTTG, Sh9 Reverse Primer TTGTTTGGCTGCAGTAAC respectively. A corrected version of Table 1 is included below

Development of novel multiplex microsatellite polymerase chain reactions to enable high-throughput population genetic studies of Schistosoma haematobium.

BACKGROUND: Human urogenital schistosomiasis caused by Schistosoma haematobium is widely distributed across Africa and is increasingly targeted for control and regional elimination. The development of new high-throughput, cost-effective molecular tools and approaches are needed to monitor and evaluate the impact of control programs on the parasite populations. Microsatellite loci are genetic markers that can be used to investigate how parasite populations change over time and in relation to external influences such as control interventions. FINDINGS: Here, 18 existing S. haematobium microsatellite loci were optimised to enable simultaneous amplification across two novel multiplex microsatellite PCR's, each containing nine loci. Methods were developed for the cost effective and rapid processing and microsatellite analysis of S. haematobium larval stages stored on Whatman-FTA cards and proved robust on miracidia and cercariae collected from Zanzibar and Niger. CONCLUSION: The development of these novel and robust multiplex microsatellite assays, in combination with an improved protocol to elute gDNA from Whatman-FTA fixed schistosome larval stages, enables the high-throughput population genetic analysis of S. haematobium. The molecular resources and protocols described here advance the way researchers can perform multi locus-based population genetic analyses of S. haematobium as part of the evaluation and monitoring of schistosomiasis control programmes.