-
Implementation of International Telemedicine Network with Rapid Coronavirus Registration by Resonant Technology to Neutralize the Pandemic
Issue:
Volume 8, Issue 2, December 2020
Pages:
29-35
Received:
2 October 2020
Accepted:
19 October 2020
Published:
26 October 2020
Abstract: The World Health Organization calls for better use of evidence and information from COVID-19 surveillance systems to optimize the only approach at our disposal to minimize transmission: to identify, isolate, test and treat each case of the disease. Track and quarantine each contact. Digital technologies play a leading role in contact tracking. Digital technology and artificial intelligence are well established in the fight against the pandemic. In many countries, telemedicine is used alongside traditional care, especially in rural areas, and is now actively used in the context of COVID-19. Telemedicine has proved to be a very effective tool for combating telemedicine to counter the virus. We have not yet realized the full potential of telemedicine. It should open up opportunities for all people to develop an international culture of health and neutralize the pandemic. COVID-19 Various technologies are used to identify COVID-19. Researchers from George Washington University have created a miniature device that allows you to almost instantly detect the presence of COVID-19 (MedicalXpress) in human blood. The operation of the device is based on the color spectroscopy method, and the analysis results can be obtained using a mobile application. The author of the article proposes to use resonant technology for detecting COVID-19. Resonance technology is implemented by a micro-device, designed in the form of a pendant, which is convenient to wear to everyone. The micro-device for detecting COVID-19 is connected to the telemedicine center, which promptly fixes the morbid patient and provides him with the necessary services. Telemedicine centres of various countries are connected to the international medical network for the prompt registration of coronavirus, the exchange of information, decision-making and the provision of services to foreign citizens.
Abstract: The World Health Organization calls for better use of evidence and information from COVID-19 surveillance systems to optimize the only approach at our disposal to minimize transmission: to identify, isolate, test and treat each case of the disease. Track and quarantine each contact. Digital technologies play a leading role in contact tracking. Digi...
Show More
-
Population Status, Habitat Use of Non-human Primates and Human-Wildlife Conflict in Zengmewerweria Forest Area, Ankober District, North-eastern Ethiopia
Alemayehu Bekele,
Tewodros Kumssa
Issue:
Volume 8, Issue 2, December 2020
Pages:
36-42
Received:
1 October 2020
Accepted:
19 October 2020
Published:
27 October 2020
Abstract: Threats to the survival of wild primate population have greatly increased. Most primate populations today face ongoing habitat disturbance, yet not all species respond to disturbance the same way, while many primate species experience declines in population density. There is no much information on the population status and density of primates in Zengmewerweria forest area. Their for study on the Population status, density, and habitat use of non-human primates and cause of human-wildlife conflict was carried out in Zengmewerweria forest area, Ankober district, north- eastern Ethiopia conducted from September 2018 to December 2020. Aim of this study was to provide information on population status, density and habitat use of non-human primate and human-wildlife conflict in the forest. Total counting method was used to collect data on the population status of non-human primates in six counting blocks. Questionnaire and group discussion were used to collect data about human-wildlife conflict as well as to assess the attitude of society about wildlife. Data were analyzed using SPSS software. Only two species of non-human primates Grivet monkey (Chlorocebus aethiops) and Black and white colobus (Colobus guereza) were identified in the forest. The total populations of Colobus guereza were 44 and 36 individuals during the dry and wet seasons respectively. There was no significant seasonal difference between seasons (χ2=1.3, df=1, P > 0.05). Similarly the total number of grivet monkey recorded during the dry season was 140 and the wet season was 117 and there was no a significant difference in the number between seasons (χ2=2.6, df=1 P > 0.05). The average density of grivet monkey and colobus was 39.67 and 12.35 individuals per kilometer square respectively. Illegal expanding for farming and illegal resource use, loss of wildlife habitat, increasing deforestation and overgrazing were the major problems encountered in the study area. Therefore, Woreda Administration should work a lot with the community to limit negative activities and protect the Forest. Furthermore, different conservation measures should be taken to increase the number of primates.
Abstract: Threats to the survival of wild primate population have greatly increased. Most primate populations today face ongoing habitat disturbance, yet not all species respond to disturbance the same way, while many primate species experience declines in population density. There is no much information on the population status and density of primates in Ze...
Show More
-
Evaluation of Bread Wheat (Triticum Aestivum L.) Genotypes for Stem and Yellow Rust Resistance in Ethiopia
Wondwesen Shiferaw,
Mohammed Abinasa,
Wuletaw Tadesse
Issue:
Volume 8, Issue 2, December 2020
Pages:
43-51
Received:
21 September 2020
Accepted:
5 October 2020
Published:
30 October 2020
Abstract: Wheat production in Ethiopia is challenged by different biotic stress. Among these biotic stresses, stem rust (Puccinia graminis f. sp. Tritici) and yellow rust (P. striiformis Westend. f. sp. Tritici) are the most devastating.. Improvement of wheat genotypes through incorporation of resistant genes to stem rust and yellow rust and testing them under hot spot areas is the most economical and environmentally friendly approach to develop resistant cultivars. Field experiment using an augmented design was undertaken at Kulumsa during 2016/17 and 2017/18 cropping season to evaluate the response of 119 elite spring bread wheat genotypes and three checks for stem and yellow rust. Based on the disease severity 71.4% and 96.6% of the genotypes showed the lowest score (0-10%) for stem rust in the first and second cropping season, respectively. About 59.7% and 66.4% of the genotypes were also showed the lowest disease severity (0-10%) for yellow rust during 2016/17 and 2017/18 cropping season, respectively. The genotypes showed significant (≤0.05) difference in Area Under Disease Progress Curve (AUDPC) for stem rust and yellow rust during 2016/17 and 2017/18 cropping season but there was significant difference (≤0.05) in Coefficient of Infection (CI) for stem rust during the first cropping season only. The genotypes exhibited significant difference (≤0.01) and (≤0.001) in CI for yellow rust in the first and second cropping season, respectively. Negative association of grain yield and thousand kernel weight with stem and yellow rust was found in both cropping season. Among the genotypes ASEEL-1//MILAN/PASTOR/3/SHAMISS-3, ZERBA6/FLAG6/3/TAM200/PASTOR//TOBA97, ZERBA-6/FLAG6/3/TAM200/PASTOR//TOBA97, NJOROSD-2/SHIHAB-12 and ICBW 206971//SHUHA-4/CHAM8/3/SIRAJ are highly resistant for both yellow and stem rust in both cropping season.
Abstract: Wheat production in Ethiopia is challenged by different biotic stress. Among these biotic stresses, stem rust (Puccinia graminis f. sp. Tritici) and yellow rust (P. striiformis Westend. f. sp. Tritici) are the most devastating.. Improvement of wheat genotypes through incorporation of resistant genes to stem rust and yellow rust and testing them und...
Show More
-
Survival Model for Diabetes Mellitus Patients’ Using Support Vector Machine
Samson Alobalorun Bamidele,
Adanze Asinobi,
Ngozi Chidozie Egejuru,
Peter Adebayo Idowu
Issue:
Volume 8, Issue 2, December 2020
Pages:
52-61
Received:
30 May 2020
Accepted:
23 October 2020
Published:
4 November 2020
Abstract: This study developed a model for the survival of diabetes mellitus patients in Nigeria. The study identified the variables monitored during the treatment of diabetes mellitus patients, formulated, and validated the predictive model for the survival time of diabetes mellitus patients. In order to achieve the aim of this study, structured interview with professional physicians so as to identify the variables for the survival time of diabetes mellitus with historical datasets were collected based on the variables monitored during treatment. The model was formulated using the support vector machine based on the variables identified and simulated using the WEKA Software using the historical datasets for training the model. The results showed that data collected from 29 patients at a hospital located in south-western Nigeria consisting of 32 attributes with a target class containing information about the survival time of each diabetes mellitus patient. The study concluded that the model can also be integrated into existing Health Information System (HIS) which captures and manages clinical information which can be fed to the predictive model thus improving the decisions affecting the patient’s outcome and the real-time assessment of clinical information affecting the patient’s survival of diabetes.
Abstract: This study developed a model for the survival of diabetes mellitus patients in Nigeria. The study identified the variables monitored during the treatment of diabetes mellitus patients, formulated, and validated the predictive model for the survival time of diabetes mellitus patients. In order to achieve the aim of this study, structured interview w...
Show More
-
Cellular Interactions, Metabolism, Assessment and Control of Aflatoxins: An Update
Syeda Mona Hassan,
Shahzad Sharif Mughal,
Syed Khurram Hassan,
Asif Ibrahim,
Huma Hassan
Issue:
Volume 8, Issue 2, December 2020
Pages:
62-71
Received:
22 June 2020
Accepted:
2 November 2020
Published:
19 November 2020
Abstract: Aspergillus spp., the fungus containing aflatoxin, is commonly spread in nature and contains severely polluted food sources from humans and wildlife, resulting in risks to health and even mortality of species. In plants, such as maize and peanuts, the spores of Aspergillus paraciticus and Aspergillus flavus can grow on the surface of stigma. The germ tube goes into the developing embryo and mimics pollen germ tubes. Aflatoxins are naturally occurring substances, so it is difficult to remove them completely from products. However, they should be lessened to minimum possible level. There is also a strong need for research into aflatoxins to establish effective methods for their correct identification , quantification and monitoring to ensure public health safety. The chemistry and biosynthesis process of aflatoxins is addressed in a succinct fashion along with their occurrence and the toxic health threats to humans and livestock. This analysis focuses primarily on aflatoxin tools, development, identification and control techniques to ensure food and feed safety. The study is very useful to health-conscious customers and academic authorities in the related fields. In addition , the availability of information on toxicity of aflatoxins would help ensure food safety and solve potential problems for the rising population by reducing the occurrence of outbreaks related to aflatoxins.
Abstract: Aspergillus spp., the fungus containing aflatoxin, is commonly spread in nature and contains severely polluted food sources from humans and wildlife, resulting in risks to health and even mortality of species. In plants, such as maize and peanuts, the spores of Aspergillus paraciticus and Aspergillus flavus can grow on the surface of stigma. The ge...
Show More
-
Vitality and Implication of Natural Products from Moringa oleifera: An Eco-Friendly Approach
Nyla Mubeen,
Syeda Mona Hassan,
Shahzad Sharif Mughal,
Syed Khurram Hassan,
Asif Ibrahim,
Huma Hassan,
Maryam Mushtaq
Issue:
Volume 8, Issue 2, December 2020
Pages:
72-76
Received:
22 June 2020
Accepted:
2 November 2020
Published:
19 November 2020
Abstract: In this study we screened Moringa oleifera for bioactive secondary metabolites and biological activity. Secondary metabolites were detected by phytochemical tests, and biological activity was confirmed through anti-oxidant assays. Phytochemicals (phenolics and flavonoids) was done by using methanol, ethanol and aqueous extracts. Phytochemical analysis of Moringa oleifera extracts was performed in terms of TPCs and TFCs, revealed that aqueous ethanolic extract offered highest TPCs (46.5 mg GAE/g DW) and TFCs (79.2 mg CE/g DW). Antioxidant activity was determined by DPPH radical scavenging activity and measure of reducing power. Results revealed that aqueous ethanolic extract showed highest radical scavenging activity and also exhibited maximum reducing potential. Reults indicates that M. oleifera have potential antibacterial, antifungal, antimicrobial, antiseptic, anti-inflammatory, antioxidant, anti-malarial, and anti-rheumatic activities. Antioxidant activity of leaves extract of Moringa oleifera was evaluated by 1, 1-diphenyl-2-picry l-hydrazyl (DPPH) and reducing power. These data support Moringa oleifera as having enough potential to be used safely as a potent antioxidant.
Abstract: In this study we screened Moringa oleifera for bioactive secondary metabolites and biological activity. Secondary metabolites were detected by phytochemical tests, and biological activity was confirmed through anti-oxidant assays. Phytochemicals (phenolics and flavonoids) was done by using methanol, ethanol and aqueous extracts. Phytochemical analy...
Show More
-
Bioinformatics Analysis Identifies Potential Key Genes of Peripheral Blood Mononuclear Cell in Idiopathic Pulmonary Fibrosis
Lijun Liu,
Daxia Cai,
Yi Wu
Issue:
Volume 8, Issue 2, December 2020
Pages:
77-89
Received:
4 November 2020
Accepted:
17 November 2020
Published:
27 November 2020
Abstract: Idiopathic pulmonary fibrosis (IPF) is a chronic progressive fibrotic interstitial pneumonia with progressive worsening of dyspnea and lung function. The etiology of IPF is unknown, and the pathogenesis remains unclear. Our study aimed to investigate the key genes of the peripheral blood mononuclear cell in IPF by bioinformatics analysis. Our study used the online Gene Expression Omnibus (GEO) microarray expression profiling dataset GSE28042 to identify differentially expressed genes (DEGs) between IPF patients and healthy controls. We performed the Gene Ontology (GO) and pathway enrichment analyses of genes for annotation, visualization, and integrated discovery. The STRING database constructed Protein-protein interaction (PPI) network analysis, and hub genes were identified by the CytoHubba plugin. Moreover, we used the receiver operating characteristic (ROC) curve to assess the diagnostic value of the hub genes. In total, 28 upregulated and 44 downregulated genes were identified in the differential expression analysis. The protein-protein interaction network (PPI) was established with 69 nodes and 68 edges. The top 10 hub genes were JUN, FOS, STAT3, SOCS3, JUNB, DUSP1, IL4, FCER1A, MS4A2, and CPA3. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enriched for the important module containing hub genes contained Fc epsilon RI signaling pathway, TNF signaling pathway, Jak-STAT signaling pathway, and MAPK signaling pathway. Additionally, the identified hub genes show high functional similarity and diagnostic value in IPF. Our study used bioinformatics analysis to provide new insight into the mechanisms underlying IPF. However, more experiments are needed to explore the relationships between the top 10 hub genes and IPF in the future.
Abstract: Idiopathic pulmonary fibrosis (IPF) is a chronic progressive fibrotic interstitial pneumonia with progressive worsening of dyspnea and lung function. The etiology of IPF is unknown, and the pathogenesis remains unclear. Our study aimed to investigate the key genes of the peripheral blood mononuclear cell in IPF by bioinformatics analysis. Our study...
Show More
-
Quantitative Spatial Analysis on Whole Slide Images Using U-Net
Sanghoon Lee,
Yanjun Zhao,
Mohamed Masoud,
Saeid Belkasim
Issue:
Volume 8, Issue 2, December 2020
Pages:
90-96
Received:
22 October 2020
Accepted:
18 November 2020
Published:
4 December 2020
Abstract: Advances in whole slide imaging technology have promoted a high use of digital slide images and generated a large volume of image data that is reliable and useful in determining treatment outcome. Recent technologies closely related to machine learning and deep learning algorithms have contributed to the success of digital histopathology by analyzing the digitized slide images providing quantitative information that are useful for faster turnaround times and effective treatment for the patient. The digital histopathological image analysis has received much attention due to its capability of mitigating the problem of the hand-crafted features. Features directly learned from raw data are trainable within the deep learning procedure and can be used for the histopathology image classification task. However, understanding the spatial context of cancer cells is still a challenging issue because of the heterogeneity of the tumor microenvironment which varies greatly, preventing successful diagnosis and leads to inappropriate therapeutic approaches for cancer patients. In this paper, we present a spatial analysis method for tumor microenvironment analysis using the U-Net architecture, a semantic segmentation deep-learning model, for a better understanding of the spatial relations between tissue types. We demonstrate the effectiveness of the U-Net architecture using a dataset created by an international crowdsourcing study. Moreover, we show that the quantitative estimates can be derived from the univariate spatial analysis.
Abstract: Advances in whole slide imaging technology have promoted a high use of digital slide images and generated a large volume of image data that is reliable and useful in determining treatment outcome. Recent technologies closely related to machine learning and deep learning algorithms have contributed to the success of digital histopathology by analyzi...
Show More