Search results for: disease forecast

Authors: Jiajia Peng, Jianqing Qiu, Jianjun Ren, Yu Zhao

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Background: Insufficient sleep has been focused on as a public health epidemic. However, a comprehensive analysis of disease trajectory associated with unhealthy sleep habits is still unclear currently. Objective: This study sought to comprehensively clarify the disease's trajectory in relation to the overall poor sleep pattern and unhealthy sleep behaviors separately. Methods: 410,682 participants with available information on sleep behaviors were collected from the UK Biobank at the baseline visit (2006-2010). These participants were classified as having high- and low risk of each sleep behavior and were followed from 2006 to 2020 to identify the increased risks of diseases. We used Cox regression to estimate the associations of high-risk sleep behaviors with the elevated risks of diseases, and further established diseases trajectory using significant diseases. The low-risk unhealthy sleep behaviors were defined as the reference. Thereafter, we also examined the trajectory of diseases linked with the overall poor sleep pattern by combining all of these unhealthy sleep behaviors. To visualize the disease's trajectory, network analysis was used for presenting these trajectories. Results: During a median follow-up of 12.2 years, we noted 12 medical conditions in relation to unhealthy sleep behaviors and the overall poor sleep pattern among 410,682 participants with a median age of 58.0 years. The majority of participants had unhealthy sleep behaviors; in particular, 75.62% with frequent sleeplessness, and 72.12% had abnormal sleep durations. Besides, a total of 16,032 individuals with an overall poor sleep pattern were identified. In general, three major disease clusters were associated with overall poor sleep status and unhealthy sleep behaviors according to the disease trajectory and network analysis, mainly in the digestive, musculoskeletal and connective tissue, and cardiometabolic systems. Of note, two circularity disease pairs (I25→I20 and I48→I50) showed the highest risks following these unhealthy sleep habits. Additionally, significant differences in disease trajectories were observed in relation to sex and sleep medication among individuals with poor sleep status. Conclusions: We identified the major disease clusters and high-risk diseases following participants with overall poor sleep health and unhealthy sleep behaviors, respectively. It may suggest the need to investigate the potential interventions targeting these key pathways.

Keywords: sleep, poor sleep, unhealthy sleep behaviors, disease trajectory, UK Biobank

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Authors: Selin Guney, Andres Riquelme

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Among the main purposes of optimal and efficient forecasts of agricultural commodity prices is to guide the firms to advance the economic decision making process such as planning business operations and marketing decisions. Governments are also the beneficiaries and suppliers of agricultural price forecasts. They use this information to establish a proper agricultural policy, and hence, the forecasts affect social welfare and systematic errors in forecasts could lead to a misallocation of scarce resources. Various empirical approaches have been applied to forecast commodity prices that have used different methodologies. Most commonly-used approaches to forecast commodity sectors depend on classical time series models that assume values of the response variables are precise which is quite often not true in reality. Recently, this literature has mostly evolved to a consideration of fuzzy time series models that provide more flexibility in terms of the classical time series models assumptions such as stationarity, and large sample size requirement. Besides, fuzzy modeling approach allows decision making with estimated values under incomplete information or uncertainty. A number of fuzzy time series models have been developed and implemented over the last decades; however, most of them are not appropriate for forecasting repeated and nonconsecutive transitions in the data. The modeling scheme used in this paper eliminates this problem by introducing Markov modeling approach that takes into account both the repeated and nonconsecutive transitions. Also, the determination of length of interval is crucial in terms of the accuracy of forecasts. The problem of determining the length of interval arbitrarily is overcome and a methodology to determine the proper length of interval based on the distribution or mean of the first differences of series to improve forecast accuracy is proposed. The specific purpose of this paper is to propose and investigate the potential of a new forecasting model that integrates methodologies for determining the proper length of interval based on the distribution or mean of the first differences of series and Fuzzy Time Series- Markov Chain model. Moreover, the accuracy of the forecasting performance of proposed integrated model is compared to different univariate time series models and the superiority of proposed method over competing methods in respect of modelling and forecasting on the basis of forecast evaluation criteria is demonstrated. The application is to daily corn and soybean prices observed at three commercially important North Carolina markets; Candor, Cofield and Roaring River for corn and Fayetteville, Cofield and Greenville City for soybeans respectively. One main conclusion from this paper is that using fuzzy logic improves the forecast performance and accuracy; the effectiveness and potential benefits of the proposed model is confirmed with small selection criteria value such MAPE. The paper concludes with a discussion of the implications of integrating fuzzy logic and nonarbitrary determination of length of interval for the reliability and accuracy of price forecasts. The empirical results represent a significant contribution to our understanding of the applicability of fuzzy modeling in commodity price forecasts.

Keywords: commodity, forecast, fuzzy, Markov

Procedia PDF Downloads 197

Authors: O. P. Popoola, O. A. Alawode, M. O. Olayiwola, A. M. Oladele

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This research work is based on using discriminant analysis to forecast crime rate in Nigeria between 1996 and 2008. The work is interested in how gender (male and female) relates to offences committed against the government, against other properties, disturbance in public places, murder/robbery offences and other offences. The data used was collected from the National Bureau of Statistics (NBS). SPSS, the statistical package was used to analyse the data. Time plot was plotted on all the 29 offences gotten from the raw data. Eigenvalues and Multivariate tests, Wilks’ Lambda, standardized canonical discriminant function coefficients and the predicted classifications were estimated. The research shows that the distribution of the scores from each function is standardized to have a mean O and a standard deviation of 1. The magnitudes of the coefficients indicate how strongly the discriminating variable affects the score. In the predicted group membership, 172 cases that were predicted to commit crime against Government group, 66 were correctly predicted and 106 were incorrectly predicted. After going through the predicted classifications, we found out that most groups numbers that were correctly predicted were less than those that were incorrectly predicted.

Keywords: discriminant analysis, DA, multivariate analysis of variance, MANOVA, canonical correlation, and Wilks’ Lambda

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Authors: Salman Mohamadi, Seyed Mohammad Ali Tayaranian Hosseini, Hamidreza Amindavar

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In this paper, we provide a procedure to analyze and model EEG (electroencephalogram) signal as a time series using ARIMA-GARCH to predict an epileptic attack. The heteroskedasticity of EEG signal is examined through the ARCH or GARCH, (Autore- gressive conditional heteroskedasticity, Generalized autoregressive conditional heteroskedasticity) test. The best ARIMA-GARCH model in AIC sense is utilized to measure the volatility of the EEG from epileptic canine subjects, to forecast the future values of EEG. ARIMA-only model can perform prediction, but the ARCH or GARCH model acting on the residuals of ARIMA attains a con- siderable improved forecast horizon. First, we estimate the best ARIMA model, then different orders of ARCH and GARCH modelings are surveyed to determine the best heteroskedastic model of the residuals of the mentioned ARIMA. Using the simulated conditional variance of selected ARCH or GARCH model, we suggest the procedure to predict the oncoming seizures. The results indicate that GARCH modeling determines the dynamic changes of variance well before the onset of seizure. It can be inferred that the prediction capability comes from the ability of the combined ARIMA-GARCH modeling to cover the heteroskedastic nature of EEG signal changes.

Keywords: epileptic seizure prediction , ARIMA, ARCH and GARCH modeling, heteroskedasticity, EEG

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Authors: Hamid Rostami Jaz, Kamran Ameri Siahooei

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Up to now different methods have been used to forecast the index returns and the index rate. Artificial intelligence and artificial neural networks have been one of the methods of index returns forecasting. This study attempts to carry out a comparative study on the performance of different Radial Base Neural Network and Feed-Forward Perceptron Neural Network to forecast investment returns on the index. To achieve this goal, the return on investment in Tehran Stock Exchange index is evaluated and the performance of Radial Base Neural Network and Feed-Forward Perceptron Neural Network are compared. Neural networks performance test is applied based on the least square error in two approaches of in-sample and out-of-sample. The research results show the superiority of the radial base neural network in the in-sample approach and the superiority of perceptron neural network in the out-of-sample approach.

Keywords: exchange index, forecasting, perceptron neural network, Tehran stock exchange

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Authors: Manish Pandey, Gurinderjit Kaur, Meenu Talwar, Sachin Chauhan, Jagbir Gill

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Health-care management systems are a unit of nice connection as a result of the supply a straightforward and fast management of all aspects relating to a patient, not essentially medical. What is more, there are unit additional and additional cases of pathologies during which diagnosing and treatment may be solely allotted by victimization medical imaging techniques. With associate ever-increasing prevalence, medical pictures area unit directly acquired in or regenerate into digital type, for his or her storage additionally as sequent retrieval and process. Data Mining is the process of extracting information from large data sets through using algorithms and Techniques drawn from the field of Statistics, Machine Learning and Data Base Management Systems. Forecasting may be a prediction of what's going to occur within the future, associated it's an unsure method. Owing to the uncertainty, the accuracy of a forecast is as vital because the outcome foretold by foretelling the freelance variables. A forecast management should be wont to establish if the accuracy of the forecast is within satisfactory limits. Fuzzy regression strategies have normally been wont to develop shopper preferences models that correlate the engineering characteristics with shopper preferences relating to a replacement product; the patron preference models offer a platform, wherever by product developers will decide the engineering characteristics so as to satisfy shopper preferences before developing the merchandise. Recent analysis shows that these fuzzy regression strategies area units normally will not to model client preferences. We tend to propose a Testing the strength of Exponential Regression Model over regression toward the mean Model.

Keywords: health-care management systems, fuzzy regression, data mining, forecasting, fuzzy membership function

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Authors: Lourdes Hanna, Edward Poluyi, Chibuikem Ikwuegbuenyi, Eghosa Morgan, Grace Imaguezegie

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Background: Degeneration of the central nervous system (CNS), also known as neurodegeneration, describes an age-associated progressive loss of the structure and function of neuronal materials, leading to functional and mental impairments. Main body: Neuroinflammation contributes to the continuous worsening of neurodegenerative states which are characterised by functional and mental impairments due to the progressive loss of the structure and function of neu-ronal materials. Some of the most common neurodegenerative diseases include Alzheimer’s disease (AD), Parkinson’s disease (PD) and amyotrophic lateral sclerosis (ALS). Whilst neuroinflammation is a key contributor to the progression of such disease states, it is not the single cause as there are multiple factors which contribute. Theoretically, non-steroidal anti-inflammatory drugs (NSAIDs) have potential to target neuroinflammation to reduce the severity of disease states. Whilst some animal models investigating the effects of NSAIDs on the risk of neurodegenerative diseases have shown a beneficial effect, this is not the same finding. Conclusion: Further investigation using more advanced research methods is required to better understand neuroinflammatory pathways and understand if there is still a potential window for NSAID efficacy.

Keywords: intervention, central nervous system, neurodegeneration, neuroinflammation

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Authors: Shadi Kanan, Ghada Shahrour, Barbara Broome, Donna Bernert, Muntaha Alibrahim, Dana Hansen

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Coronary artery disease is responsible for over 7 million deaths a year worldwide. In developing countries, such as Jordan, the incidence of coronary artery disease exceeds that of developed countries. One contributing factor to this disparity is decreased physical activity among the population, for reasons related to specific cultural and religious values. Using the theory of planned behaviour, the purpose of this study was to investigate the intentions of Jordanian patients with coronary artery disease regarding physical activity. A total of 109 patients with coronary artery disease were recruited for this cross-sectional study from King Abdullah University Hospital in Jordan. A 15-item questionnaire based on the theory of planned behaviour was used to assess participants’ attitudes, subjective norms, perceived behavioural control and intentions towards engagement in physical activity. Perceived behavioural control was found to have the strongest significant relationship with participants’ intentions to engage in physical activity. Barriers to physical activity included lack of time, lack of support from family or friends, and feelings of exhaustion. Lifestyle interventions for patients with coronary artery disease should focus on fostering a sense of control over the environment to encourage patients to engage in physical activity.

Keywords: coronary artery disease, perceived behavioural control, subjective norms, theory of planned behaviour

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Authors: Oya Bulut, Oguzhan Avci, Zafer Bulut, Atilla Simsek

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Livestock breeders have focused on the improvement of production traits with little or no attention for improvement of disease resistance traits. In order to determine the association between the genetic structure of the individual gene loci with possibility of the occurrence and the development of diseases, MHC (major histocompatibility complex) are frequently used. Because of their importance in the immune system, MHC locus is considered as candidate genes for resistance/susceptibility against to different diseases. Major histocompatibility complex (MHC) molecules play a critical role in both innate and adaptive immunity and have been considered candidate molecular markers of an association between polymorphisms and resistance/susceptibility to diseases. The purpose of this study is to give some information about MHC genes become an important area of study in recent years in terms of animal husbandry and determine the relation between MHC genes and resistance/susceptibility to disease.

Keywords: MHC, polymorphism, disease, resistance

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Authors: Khanh To Duc, Monica Chiogna, Gianfranco Adimari

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With three diagnostic categories, assessment of the performance of diagnostic tests is achieved by the analysis of the receiver operating characteristic (ROC) surface, which generalizes the ROC curve for binary diagnostic outcomes. The volume under the ROC surface (VUS) is a summary index usually employed for measuring the overall diagnostic accuracy. When the true disease status can be exactly assessed by means of a gold standard (GS) test, unbiased nonparametric estimators of the ROC surface and VUS are easily obtained. In practice, unfortunately, disease status verification via the GS test could be unavailable for all study subjects, due to the expensiveness or invasiveness of the GS test. Thus, often only a subset of patients undergoes disease verification. Statistical evaluations of diagnostic accuracy based only on data from subjects with verified disease status are typically biased. This bias is known as verification bias. Here, we consider the problem of correcting for verification bias when continuous diagnostic tests for three-class disease status are considered. We assume that selection for disease verification does not depend on disease status, given test results and other observed covariates, i.e., we assume that the true disease status, when missing, is missing at random. Under this assumption, we discuss several solutions for ROC surface analysis based on imputation and re-weighting methods. In particular, verification bias-corrected estimators of the ROC surface and of VUS are proposed, namely, full imputation, mean score imputation, inverse probability weighting and semiparametric efficient estimators. Consistency and asymptotic normality of the proposed estimators are established, and their finite sample behavior is investigated by means of Monte Carlo simulation studies. Two illustrations using real datasets are also given.

Keywords: imputation, missing at random, inverse probability weighting, ROC surface analysis

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Authors: Rujijan Vichivanives, Kittiya Poonsilp, Canasanan Wanavijit

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This research aims to create mobile tools to analyze rice disease quickly and easily. The principle of object-oriented software engineering and objective-C language were used for software development methodology and the principle of decision tree technique was used for analysis method. Application users can select the features of rice disease or the color appears on the rice leaves for recognition analysis results on iOS mobile screen. After completing the software development, unit testing and integrating testing method were used to check for program validity. In addition, three plant experts and forty farmers have been assessed for usability and benefit of this system. The overall of users’ satisfaction was found in a good level, 57%. The plant experts give a comment on the addition of various disease symptoms in the database for more precise results of the analysis. For further research, it is suggested that image processing system should be developed as a tool that allows users search and analyze for rice diseases more convenient with great accuracy.

Keywords: rice disease, data analysis system, mobile application, iOS operating system

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Authors: Jibran Abbasy, Rizwan Sultan, Ammar Humayun, Tabish Chawla

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Background: Hydatid disease caused by Echinococcus Granulosus affects liver in 70-90% of cases. Dogs are the definitive host while humans are the accidental host. Modalities used for its treatment are especially important for our population as the disease is endemic in many Asian countries. The aim of the study was to perform an audit of the various modalities used for treatment of hydatid disease of liver and the response to each modality in tertiary care center of Pakistan. Materials and Methods: Retrospective audit of patients diagnosed and treated for Hydatid disease of the liver at Aga Khan University Hospital from 1st January 2007 to 31st December 2014 was completed. All patients aged 16 and above were included. Patients who had extra hepatic disease and missing records were excluded. Outcome measures were morbidity, mortality and recurrence of the disease. Results: During the study period 56 patients were treated for isolated hepatic hydatid disease and were included. Mean age was 39 years with 48% being females and 52% males. Most common presenting complaint was abdominal pain seen in 53% of patients(n=41). Duration of symptoms was less than 6 months in 74% (n=38). Mostly right lobe was involved in 69% (n=38).Most common treatment modality used was surgery in 34 patients followed by PAIR in 14 patients while 8 patients were treated medically. At a median follow up of 34 months recurrence was seen in 2 patients treated with PAIR while no patient treated with surgery had recurrence with the median follow up of 20 months. While no morbidity and mortality were observed in PAIR, but in surgery 5 patients had morbidity while 1 patient had mortality. Conclusion: Our data is comparative to other studies in terms of morbidity, mortality, and recurrence. We had adequate follow up. In our study PAIR and surgery both are effective and have less complications and recurrence rate. Surgery is still the gold standard in terms of recurrence.

Keywords: echinococcous granulosus, puncture aspiration irrigation reaspiration (PAIR), surgery, hydatid disease

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Authors: Amirreza Razzaghipour Sorkhab

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One of the most common disorders among humans is hearing impairment. This paper provides an evidence base that recovers understanding of Meniere’s disease and highlights the physical and mental health correlates of the disorder. Meniere's disease is more common in the elderly. The term idiopathic endolymphatic hydrops has been attributed to this disease by some in the previous. Meniere’s disease demonstrations a genetic tendency, and a family history is found in 10% of cases, with an autosomal dominant inheritance pattern. The COCH gene may be one of the hereditary factors contributing to Meniere’s disease, and the possibility of a COCH mutation should be considered in patients with Meniere’s disease symptoms. Should be considered Missense mutations in the COCH gene cause the autosomal dominant sensorineural hearing loss and vestibular disorder. Meniere’s disease is a complex, heterogeneous disorder of the inner ear and that is characterized by episodes of vertigo lasting from minutes to hours, fluctuating sensorineural hearing loss, tinnitus, and aural fullness. The existing evidence supports the suggestion that age and sleep disorder are risk factors for Meniere's disease. Many factors have been reported to precipitate the progress of Menier, including endolymphatic hydrops, immunology, viral infection, inheritance, vestibular migraine, and altered intra-labyrinthine fluid dynamics. Although there is currently no treatment that has a proven helpful effect on hearing levels or on the long-term evolution of the disease, however, in the primary stages, the hearing may improve among attacks, but a permanent hearing loss occurs in the majority of cases. Current publications have proposed a role for the intratympanic use of medicine, mostly aminoglycosides, for the control of vertigo. more than 85% of patients with Meniere's disease are helped by either changes in lifestyle and medical treatment or minimally aggressive surgical procedures such as intratympanic steroid therapy, intratympanic gentamicin therapy, and endolymphatic sac surgery. However, unilateral vestibular extirpation methods (intratympanic gentamicin, vestibular nerve section, or labyrinthectomy) are more predictable but invasive approaches to control the vertigo attacks. Medical therapy aimed at reducing endolymph volume, such as low-sodium diet, diuretic use, is the typical initial treatment.

Keywords: meniere's disease, endolymphatic hydrops, hearing loss, vertigo, tinnitus, COCH gene

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Authors: Nisha Thapa, Ram Prasad Mainali, Prakriti Chand

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Broadleaf mustard is a commercialized leafy vegetable of Nepal. However, its utilization is hindered in terms of production and productivity due to the high intensity of insects, pests, and diseases causing great loss. The plant protection part of the crop’s disease and damage intensity has not been studied much from research perspectives in Nepal. The research aimed to evaluate broadleaf mustard genotypes for resistance against different diseases. A total of 35 native genotypes of broadleaf mustard were screened at weekly intervals by scoring the plants for ten weeks. Five different diseases, such as Rhizoctonia root rot, Alternaria blight, black rot, turnip mosaic virus disease, and white rust, were reported from the broad leaf mustard genotypes. Out of 35 genotypes, 23 genotypes were found with very high Rhizoctonia Root Rot severity, whereas 8 genotypes showed very high Alternaria blight severity. Likewise, 3 genotypes were found with high Black rot severity, and 1 genotype was found with very high Turnip mosaic virus disease incidence. Similarly, 2 genotypes were found to have very high White rust severity. Among the disease of national importance, Rhizoctonia root rot was found to be the most severe disease with the greatest loss. Broadleaf mustard genotypes like Rato Rayo, CO 1002, and CO 11007 showed average to the high level of field resistance; therefore, these genotypes should be used, conserved, and stored in a mustard improvement program as the disease resistance quality or susceptibility of these genotypes can be helpful for seed producing farmers, companies and other stakeholders through varietal improvement and developmental works that further aids in sustainable disease management of the vegetable.

Keywords: genotype, disease resistance, Rhizoctonia root rot severity, varietal improvement

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Authors: Sahar Shams

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Coeliac disease (CD) is a widely reported disease particularly in countries with predominant Caucasian populations. It presents with many signs and symptoms including iron deficiency (ID) and iron deficiency anaemia/anaemia (IDA/A). The exact association between ID, IDA/A and CD and how accurate these signs are in diagnosing CD is not fully known. This systematic review was conducted to investigate the accuracy of both ID & IDA/A as a diagnostic indicator for CD and whether it warrants point of care testing. A systematic review was performed looking at studies published in MEDLINE, Embase, Cochrane Library, and Web of Science. QUADAS-2 tool was used to assess risk of bias in each study. ROC curve and forest plots were generated as part of the meta-analysis after data extraction. 16 studies were identified in total, 13 of which were IDA/A studies and 3 ID studies. The prevalence of CD regardless of diagnostic indicator was assumed as 1%. The QUADAS-2 tool indicated most of studies as having high risk of bias. The PPV for CD was higher in those with ID than for those with IDA/A. Meta-analysis showed the overall odds of having CD is 5 times higher in individuals with ID & IDA/A. The ROC curve showed that there is definitely an association between both diagnostic indicators and CD, the association is not a particularly strong one due to great heterogeneity between studies. Whilst an association between IDA/A & ID and coeliac disease was evident, the results were not deemed significant enough to prompt coeliac disease testing in those with IDA/A & ID.

Keywords: anemia, iron deficiency anemia, coeliac disease, point of care testing

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Authors: Abdela Bulbula

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Background: Marek’s disease virus is a devastating infection, causing high morbidity and mortality in chickens in Ethiopia. Methods: The current study was conducted from March to November, 2021 with the general objective of performing antemortem and postmortem, isolation, and molecular detection of Marek’s disease virus from outbreak cases in southwestern Ethiopia. Accordingly, based on outbreak information reported from the study sites namely, Bedelle, Yayo, and Bonga towns in southwestern Ethiopia, 50 sick chickens were sampled. The backyard and intensive farming systems of chickens were included in the sampling and priorities were given for chickens that showed clinical signs that are characteristics of Marek’s disease. Results: By clinical examinations, paralysis of legs and wings, gray eye, loss of weight, difficulty in breathing, and depression were recorded on all chickens sampled for this study and death of diseased chickens was observed. In addition, enlargement of the spleen and gross lesions of the liver and heart were recorded during postmortem examination. The death of infected chickens was observed in both vaccinated and non-vaccinated flocks. Out of 50 pooled feather follicle samples, Marek’s disease virus was isolated from 14/50 (28%) by cell culture method and out of six tissue samples, the virus was isolated from 5/6(83.30%). By Real time polymerization chain reaction technique, which was targeted to detect the Meq gene, Marek’s disease virus was detected from 18/50 feather follicles which accounts for 36% of sampled chickens. Conclusion: In general, the current study showed that the circulating Marek’s disease virus in southwestern Ethiopia was caused by the oncogenic Gallid herpesvirus-2 (Serotype-1). Further research on molecular characterization of revolving virus in current and other regions is recommended for effective control of the disease through vaccination.

Keywords: Ethioi, Marek's disease, isolation, molecular

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Authors: Rachel Karasenty Saltoun, Charlotte Roddick, Chelsea D. Christie, Frances Chen

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Moving has become an integral part of many people’s lives. This research explores whether relocating to a new city is associated with an increase in loneliness and cardiovascular disease risk and if this increased risk diminishes with continued residency. To test this, various psychosocial variables and three cardiovascular disease risk markers (C-reactive protein, albumin, blood pressure) were assessed on two groups of individuals: those who have moved to Vancouver, Canada in the previous 6 weeks (‘Movers’) and those who have lived in Vancouver for at least five years (‘Non-Movers’). It was hypothesized that individuals who had recently relocated would have heightened levels of loneliness, blood pressure (BP), albumin, and C-reactive protein (CRP) compared to those who had not recently relocated. Length of residency was hypothesized to moderate these effects, such that after a few months, loneliness levels and cardiovascular disease risk would decrease among those who had recently relocated. Correlational analysis indicated a trend between the change in CRP and albumin levels and loneliness overtime on an individual level. However, these results must be interpreted with caution due to the small sample size. As Vancouver’s immigration rates continue to grow, this study has important implications regarding the social support resources offered to new immigrants, as well as bringing awareness at the healthcare level of the potential increase in cardiovascular disease risk among those who have recently relocated.

Keywords: cardiovascular disease risk, loneliness, moving, residential mobility

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Authors: Mai M. Farid, Ximeng Yang, Tomoharu Kuboyama, Chihiro Tohda

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Trigonelline is a major alkaloid component derived from Trigonella foenum-graecum L. (fenugreek) and has been reported before as a potential neuroprotective agent, especially in Alzheimer’s disease (AD). However, the previous data were unclear and used model mice were not well established. In the present study, the effect of trigonelline on memory function was investigated in Alzheimer’s disease transgenic model mouse, 5XFAD which overexpresses the mutated APP and PS1 genes. Oral administration of trigonelline for 14 days significantly enhanced object recognition and object location memories. Plasma and cerebral cortex were isolated at 30 min, 1h, 3h, and 6 h after oral administration of trigonelline. LC-MS/MS analysis indicated that trigonelline was detected in both plasma and cortex from 30 min after, suggesting good penetration of trigonelline into the brain. In addition, trigonelline significantly ameliorated axonal and dendrite atrophy in Amyloid β-treated cortical neurons. These results suggest that trigonelline could be a promising therapeutic candidate for AD.

Keywords: alzheimer’s disease, cortical neurons, LC-MS/MS analysis, trigonelline

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Authors: Nqobile Muleya, Winston Garira, Godwin Mchau

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Citrus Black Spot (CBS) is a fungal disease that is responsible for huge economical loss and poses a threat to the citrus industry worldwide. We construct a mathematical model framework for citrus black spot between fruits to characterise the dynamics of the disease development, paying attention to the pathogen life cycle. We have made an observation from the model analysis that the initial inoculum from ascomata is very important for disease development and thereafter it is no longer important due to conidia which is responsible for secondary infection. Most importantly, the model indicated that ascospores and conidia are very important parameters in developing citrus black spot within a short distance. The basic reproductive number and its importance in relation to citrus black spot persistence are outlined. A numerical simulation of the model was done to explain the theoretical findings.

Keywords: epidemiological modelling, Guidnardia citricarpa, life cycle stage, fungal, disease development

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Authors: Himanshi Allahabadi

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Plants have found a widespread use in medicine traditionally, including the treatment of cognitive disorders, especially, neurodegenerative diseases such as Alzheimer's disease and Parkinson's disease. In terms of indigenous medicine, it has been found that many potential drugs can be isolated from plant products, including those for dementia. Plant product is widely distributed in plant kingdom and forms a major antioxidant source in the human diet, is Polyphenols. There are four important groups of polyphenols: phenolic acids, flavonoids, stilbenes, and lignans. Due to their high antioxidant capacity, interest in their study has greatly increased. There are several methods for discovering and characterizing active compounds isolated from plant sources, now available. The results obtained so far seem fulfilling, but additionally, mechanism of functioning of polyphenols at the molecular level, as well as their application in human health need to be researched upon. Also, even though the neuroprotective effects of flavonoids have been much talked about, much of the data in support of this statement has come from animal studies rather than human studies. This review is based on a multi-faceted study of medicinal plants, i.e. phytochemicals, with special focus on flavanones and their relevance in remedy of Parkinson's disease.

Keywords: dementia, parkinson's disease, flavanones, polyphenols, substantia nigra

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Authors: Niya Chen, Jennifer Chan

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In the financial market, risk management helps to minimize potential loss and maximize profit. There are two ways to assess risks; the first way is to calculate the risk directly based on the volatility. The most common risk measurements are Value at Risk (VaR), sharp ratio, and beta. Alternatively, we could look at the quantile of the return to assess the risk. Popular return models such as GARCH and stochastic volatility (SV) focus on modeling the mean of the return distribution via capturing the volatility dynamics; however, the quantile/expectile method will give us an idea of the distribution with the extreme return value. It will allow us to forecast VaR using return which is direct information. The advantage of using these non-parametric methods is that it is not bounded by the distribution assumptions from the parametric method. But the difference between them is that expectile uses a second-order loss function while quantile regression uses a first-order loss function. We consider several quantile functions, different volatility measures, and estimates from some volatility models. To estimate the expectile of the model, we use Realized Conditional Autoregressive Expectile (CARE) model with the bayesian method to achieve this. We would like to see if our proposed models outperform existing models in cryptocurrency, and we will test it by using Bitcoin mainly as well as Ethereum.

Keywords: expectile, CARE Model, CARR Model, quantile, cryptocurrency, Value at Risk

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Authors: Lidia Kowalska, Edward Arseniuk

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Glume and leaf blotch is a disease of wheat caused by necrotrophic fungus Parastagonospora nodorum. It is a serious pathogen in many wheat-growing areas throughout the world. Use of resistant cultivars is the most effective and economical means to control the above-mentioned disease. Plant breeders and pathologists have worked intensively to incorporate resistance to the pathogen in new cultivars. Conventional methods of breeding for resistance can be supported by using the biotechnological ones, i.e., somatic embryogenesis and androgenesis. Therefore, an effort was undertaken to compare genetic variation in P. nodorum resistance among winter wheat somaclones, dihaploids and conventional varieties. For the purpose, a population of 16 somaclonal and 4 dihaploid wheat lines from six crosses were used to assess their resistance to P. nodorum under field conditions. Lines were grown in disease-free (fungicide protected) and inoculated micro plots in 2 replications of a split-plot design in a single environment. The plant leaves were inoculated with a mixture of P. nodorum isolates three times. Spore concentrations were adjusted to 4 x 10⁶ of viable spores per one milliliter. The disease severity was rated on a scale, where > 90% – susceptible, < 10% - resistant. Disease ratings of plant leaves showed statistically significant differences among all lines tested. Higher resistance to P. nodorum was observed more often on leaves of somaclonal lines than on dihaploid ones. On average, disease, severity reached 15% on leaves of somaclones and 30% on leaves of dihaploids. Some of the genotypes were showing low leaf infection, e.g. dihaploid D-33 (disease severity 4%) and a somaclone S-1 (disease severity 2%). The results from this study prove that dihaploid and somaclonal variation might be successfully used as an additional source of wheat resistance to the pathogen and it could be recommended to use in commercial breeding programs. The reported results prove that biotechnological methods may effectively be used in breeding for disease resistance of wheat to fungal necrotrophic pathogens.

Keywords: glume and leaf blotch, somaclonal, androgenic variation, wheat, resistance breeding

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Authors: S. Hallal, Z. Chami, A. Hadji-Lehtihet, S. Sokhal-Boudella, A. Berhoune, L. Yargui

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Gaucher disease is the most common lysosomal storage in our population, it is due to a deficiency of β –glucosidase acid. The enzyme deficiency causes a pathological accumulation of undegraded substrate in lysosomes. This metabolic overload is responsible for a multisystemic disease with hepatosplenomegaly, anemia, thrombocytopenia, and bone involvement. Neurological involvement is rare. The laboratory diagnosis of Gaucher disease consists of phenotypic diagnosis by determining the enzymatic activity of β - glucosidase by fluorimetric method, a study by genotypic diagnosis in the GBA gene, limiting the search recurrent mutations (N370S, L444P, 84 GG); PCR followed by an enzymatic digestion. Abnormal profiles were verified by sequencing. Monitoring of treated patients is provided by the determination of chitotriosidase. Our experience spaning a period of 6 years (2007-2014) has enabled us to diagnose 78 patients out of a total of 328 requests from the various departments of pediatrics, internal medicine, neurology. Genotypic diagnosis focused on the entire family of 9 children treated at pediatric CHU Mustapha, which help define the clinical form; or 5 of them had type III disease, carrying the L444P mutation in the homozygous state. Three others were composite (N370/L444P) (N370S/other unintended mutation in our study), and only in one family no recurrent mutation has been found. This molecular study permits screening of heterozygous essential for genetic counseling.

Keywords: Gaucher disease, mutations, N370S, L444P

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Authors: Mostafa A. Amer, I. A. El-Samra, I. I. Abou-ElSeoud, S. M. El-Abd, N. K. Shawertamimi

Abstract:

Tomato Fusarium wilt disease caused by Fusarium oxysporum f. sp. Lycopercisi (FOL) is considered one of the most destructive diseases in Egypt. Effect of some biotic inducers such as Bacillus megaterium var. phosphaticum, Glomus intraradices and Glomus macrocarpum at seven different mixed treatments, was tested for their ability to induce resistance in tomato plants against the disease. According to pathogenicity tests, all the tested isolates of FOL showed wilt symptoms on both of the tested cultivars; however, they considerably varied in percentages of disease incidence (DI) and disease severity (DS). Castle Rock was more susceptible than Peto 86, which was relatively resistant. Pretreatment of both cultivars, under greenhouse conditions, with the tested biotic inducers alone or in combination with each other's, significantly increased the induction of chitinase, β-1,3-glucanase, peroxidase, and polyphenoloxidase and reduced disease incidence and severity, compared with untreated noninoculated (C1) and untreated inoculated (C2) controls. Application of a combination of BMP, with GI and GM was the most effective in increasing the induction rated of the tested enzymes, compared with the other treatments. Induction of enzymes in most of the tested bioinducers treatments gradually increased, attaining maximum values after 48 or/and 72 hrs after challenging with FOL, then gradually declined. GI was the least effective bioinducer.

Keywords: F. oxysporum f. sp. lycopersici, defense enzymes, induced systemic resistance, ISR, B. megaterium var. phosphaticum, G. macrocarpum, G. intraradices

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Authors: Osagiede Efosa Kelvin

Abstract:

The Ebola virus disease (EVD); also Ebola hemorrhagic fever, is a disease of humans and other primates caused by Ebola viruses. Signs and symptoms typically start between two days and three weeks after contracting the virus as a fever, sore throat, muscle pain, and headaches. Then, vomiting, diarrhoea and rash usually follow, along with decreased function of the liver and kidneys. At this time, some people begin to bleed both internally and externally. The first death in Nigeria was reported on 25 July 2014: a Liberian-American with Ebola flew from Liberia to Nigeria and died in Lagos soon after arrival. As part of the effort to contain the disease, possible contacts were monitored –353 in Lagos and 451 in Port Harcourt On 22 September, the World Health Organisation reported a total of 20 cases, including eight deaths. The WHO's representative in Nigeria officially declared Nigeria Ebola-free on 20 October after no new active cases were reported in the follow-up contact. This paper looks at the Ebola Virus in general and the measures taken by Nigeria to combat its spread.

Keywords: Ebola virus, hemorrhagic fever, Nigeria, outbreak

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Authors: Hazel Ann Gianelli Cu, Stephanie Co, Radcliff Cobankiat

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Objectives: TRC101/Veverimer is an orally administered, non absorbed, sodium- and counterion-free hydrochloric acid binder for the treatment of metabolic acidosis associated with chronic kidney disease. The main objective of this study is to determine the efficacy of TRC 101/ Veverimer 6g/day in increasing serum bicarbonate levels of chronic kidney disease patients with metabolic acidosis. In this meta analysis, we also aim to look at safety outcomes, adverse effects and if the level of serum bicarbonate reached metabolic alkalosis when given TRC101/Veverimer. Methodology: Pubmed, Cochrane, Google Scholar and Science direct were used to search for randomized controlled trials about TRC101/Veverimer use in Chronic kidney disease patients with metabolic acidosis. Search strategy according to the Prisma checklist was done with evaluation of biases and synthesis of results using the Cochrane Review Manager software 5.4. Results: Two randomized controlled trials involving 371 chronic kidney disease patients were included in this study. Results show there was a significant increase in the serum bicarbonate level when given TRC101/Veverimer compared to the placebo. Both studies had a significant number of participants who completed the studies until the end. P value of <0.00001 was used in both studies with a confidence interval of 95%. Conclusion: TRC101/Veverimer 6g/day was shown to effectively and safely increase serum bicarbonate or achieve normalization in chronic kidney disease patients with metabolic acidosis as compared with a placebo. This was associated with delayed progression of kidney disease with improvement of physical functioning, however longer duration of future studies is ideal in order to assess further the long advantages and consequences of TRC 101/Veverimer.

Keywords: chronic kidney disease, metabolic acidosis, Veverimer, TRC101

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Authors: Sintayehu W. Dejene, Ignas M. A. Heitkönig, Herbert H. T. Prins, Zewdu K. Tessema, Willem F. de Boer

Abstract:

Current theories on diversity-disease relationships describe host species diversity and species identity as important factors influencing disease risk, either diluting or amplifying disease prevalence in a community. Whereas the simple term ‘diversity’ embodies a set of animal community characteristics, it is not clear how different measures of species diversity are correlated with disease risk. We, therefore, tested the effects of species richness, Pielou’s evenness and Shannon’s diversity on bTB risk in cattle in the Afar Region and Awash National Park between November 2013 and April 2015. We also analysed the identity effect of a particular species and the effect of host habitat use overlap on bTB risk. We used the comparative intradermal tuberculin test to assess the number of bTB infected cattle. Our results suggested a dilution effect through species evenness. We found that the identity effect of greater kudu - a maintenance host – confounded the dilution effect of species diversity on bTB risk. bTB infection was positively correlated with habitat use overlap between greater kudu and cattle. Different diversity indices have to be considered together for assessing diversity-disease relationships, for understanding the underlying causal mechanisms. We posit that unpacking diversity metrics is also relevant for formulating control strategies to manage cattle in ecosystems characterized by seasonally limited resources and intense wildlife-livestock interactions.

Keywords: evenness, diversity, greater kudu, identity effect, maintenance hosts, multi-host disease ecology, habitat use overlap

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Authors: Oluwaponmile David Alao

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Due to an increase in the death rate as a result of heart attack. There is need to develop a system that can be useful in the diagnosis of the disease at the medical centre. This system will help in preventing misdiagnosis that may occur from the medical practitioner or the physicians. In this research work, heart disease dataset obtained from UCI repository has been used to develop an intelligent prediction diagnosis system. The system is modeled on a feedforwad neural network and trained with back propagation neural network. A recognition rate of 86% is obtained from the testing of the network.

Keywords: heart disease, artificial neural network, diagnosis, prediction system

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Authors: Manish Subedi, Bijay Bartaula, Ashok R. Pant, Purbesh Adhikari, Sanjib K. Sharma

Abstract:

Background: The pattern of glomerular disease varies worldwide. In absence of kidney disease/Kidney biopsy registry in Nepal, the exact etiology of different forms of glomerular disease is primarily unknown in our country. Method: We retrospectively analyzed 175 cases of renal biopsies performed from dated September 2014 to August 2016 at B. P. Koirala Institute of Health Sciences, Dharan, Nepal. Results: The commonest indication for renal biopsy was nephrotic syndrome (34.9%), followed by Systemic lupus erythematosus with suspected renal involvement (22.3%). Majority of patients were in the 30-60 year bracket (57.2%), with the mean age of the patients being 35.37 years. The average number of glomeruli per core was 13, with inadequate sampling in 5.1%. IgA nephropathy (17%) was found to be the most common primary glomerular disease, followed by membranous nephropathy (14.6%) and FSGS (14.6%). The commonest secondary glomerular disease was lupus nephritis. Complications associated with renal biopsy were pain at biopsy site in 18% of cases, hematuria in 6% and perinephric hematoma in 4% cases. Conclusion: The commonest primary and secondary glomerular disease was IgA nephropathy and lupus nephritis respectively. The high prevalence of Systemic lupus erythematosus with lupus nephritis among Nepalese in comparison with other developing countries warrants further evaluation. As an initial attempt towards documentation of glomerular diseases in the national context, this study should serve as a stepping stone towards the eventual establishment of a full-fledged national registry of glomerular diseases in Nepal.

Keywords: glomerular, Nepal, renal biopsy, systemic lupus erythematoses

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Authors: Ramin Vafadary, Maryam Khanbaghi

Abstract:

Forecasting electricity load is important for various purposes like planning, operation, and control. Forecasts can save operating and maintenance costs, increase the reliability of power supply and delivery systems, and correct decisions for future development. This paper compares various time series methods to forecast 24 hours ahead of electricity load. The methods considered are the Holt-Winters smoothing, SARIMA Modeling, LSTM Network, Fbprophet, and Tensorflow probability. The performance of each method is evaluated by using the forecasting accuracy criteria, namely, the mean absolute error and root mean square error. The National Renewable Energy Laboratory (NREL) residential energy consumption data is used to train the models. The results of this study show that the SARIMA model is superior to the others for 24 hours ahead forecasts. Furthermore, a Bagging technique is used to make the predictions more robust. The obtained results show that by Bagging multiple time-series forecasts, we can improve the robustness of the models for 24 hours ahead of electricity load forecasting.

Keywords: bagging, Fbprophet, Holt-Winters, LSTM, load forecast, SARIMA, TensorFlow probability, time series

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