Prediction of Possible Effects of Arsenic and Cadmium in Human Health Using Chemical-Protein and Protein-Protein Interaction Network
Md. Taif Ali,
Md. Ashraful Alam,
Md. Emdad Ullah,
Mohammad Arif Ashraf,
Md. Abu Sayed,
Aklima Jahan
Issue:
Volume 5, Issue 6, December 2017
Pages:
74-81
Received:
10 July 2017
Accepted:
20 July 2017
Published:
28 November 2017
Abstract: Arsenic and cadmium toxicity has demonstrated to be a crucial problem and there are many health issues interconnected with each other. The toxicity of these metals has no biological role even though remain present in some or the other form, hazardous for the human health and its proper functioning. As a result, from the very beginning, the researchers are trying to overcome the serious effects occurred by the heavy metals. The different procedures and methods are followed for minimizing the negative effects. The study was conducted to predict the probable effects and theirs targeted proteins in human body by recently developed advanced bioinformatics tools and subsequently found 10 proteins are interacted with arsenic and cadmium for each. However, these 10 proteins are independently associated with other 97 and 100 proteins. Finally, 25 common proteins have been identified which are affected by these two heavy metals. Our data mining search revealed that all of these 25 proteins are associated with the causing of cancer in human body.
Abstract: Arsenic and cadmium toxicity has demonstrated to be a crucial problem and there are many health issues interconnected with each other. The toxicity of these metals has no biological role even though remain present in some or the other form, hazardous for the human health and its proper functioning. As a result, from the very beginning, the research...
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Participatory Evaluation and Selection of Improved Irish Potato Varieties at Daro Lebu and Oda Bultum Districts of Western Hararghe Zone, Oromia Regional State, Ethiopia
Asfaw Zewdu,
Gezahagn Aseffa,
Sintayehu Girma,
Chala Benga
Issue:
Volume 5, Issue 6, December 2017
Pages:
82-89
Received:
2 December 2016
Accepted:
16 December 2016
Published:
30 November 2017
Abstract: Potato (Solanum tubersom L.) is one of the most important food crops in developed as well as developing countries. This activity was conducted during the 2013 main cropping season at Daro Lebu and Oda Bultum districts of West Hararghe Zone to identify and select among potato varieties that are adaptable to local conditions and accepted by farmers and consumers at large and to generate knowledge and information that can contribute for the seed value chain development. A total of four farmers were participated on the experiment. Gudane, Bubu, Toluma, Bete and Local check varieties were evaluated on 25m2 and 100m2 plots at Daro Lebu and Oda Bultum districts, respectively. Economic data (cost of input and revenue obtained), agronomic data and farmer feedback/preference were collected. The collected data were analyzed through descriptive statistic (mean and standard deviation) and graphs by SPSS software and qualitatively. The agronomic result shows that the average total yield harvested from Gudene and Bubu varieties were 21 ton/ha and 20.24 ton/ha, respectively. In addition, participants of field day were also select those varieties based on criteria’s like disease reaction, tuber size, marketability, number of tubers and ways of giving tubers from one plant, color, perish ability, yield amount, sweetness and short time take during catering. Economically, Gudane and Bubu varieties were more beneficiary as compared to Bete, Toluma and Local variety, which were 83,500 Eth.birr and 77,420 Eth.birr, respectively. According to other agronomic data result shows that and farmer preference criteria like disease resistant, high yielder, larger tuber size, marketable, good color and high number of tuber and others, Gudane and Bubu varieties were selected as compared to Toluma, Bete and Local varieties. Therefore, Gudane and Bubu varieties will recommend for further scale up/out for Oda Bultum and Daro Lebu districts and others area which is similar agro-ecology to Oda Baso and Jilbo kebeles.
Abstract: Potato (Solanum tubersom L.) is one of the most important food crops in developed as well as developing countries. This activity was conducted during the 2013 main cropping season at Daro Lebu and Oda Bultum districts of West Hararghe Zone to identify and select among potato varieties that are adaptable to local conditions and accepted by farmers a...
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Post Mortem Interval: Necrobiome Analysis Using Artificial Neural Networks
Khenchouche Abdelhalim,
Bouharati Khaoula,
Bouharati Saddek,
Mahnane Abbas,
Hamdi-Cherif Mokhtar
Issue:
Volume 5, Issue 6, December 2017
Pages:
90-96
Received:
5 October 2017
Accepted:
18 October 2017
Published:
8 December 2017
Abstract: Aims: In criminal investigations, it is necessary to determine the date and time of the death of a person. Different techniques are used. In this study, we try to analyze the necrobioma that characterizes all the bacteria that populate a corpse. It would be necessary to determine which bacteria first inhabit a dead organism? Which bodies are the first organs to be affected? Which microorganisms will tend to multiply post-mortem? How to establish a dynamics of bacterial diffusion and an occupation gradient according to the moment of death? Several factors are involved in this dynamic. Mathematical modeling becomes very complex. In this study, we propose an intelligent system to predict the exact date of death of the number and species found at time (t). Materials and Methods: The purpose is to determine and enumerate the bacterial colonies in the study organ. Establish the bacterial dynamics as a function of time. In this study, an artificial neural network is established. The input variables are bacterial species, their growth rates, growth conditions (temperature, humidity, soil type, and bacterial species). The rate of bacterial species in specified organ is considered as output variable. The time taken for a bacterial species to reach this rate under defined conditions determines the date of death of the person. Results: Since input variables are considered complex, uncertain, an artificial neural network demonstrates its ability to solve such complexity. After the learning phase of the network from the real data, this creates a function of correspondence between the space of inputs and output. The established system makes it possible to instantly read the time elapsed after death from the introduction of the random values at the input with the maximum precision. The proposed system remains extensible to enter variables that may have an effect on the output.
Abstract: Aims: In criminal investigations, it is necessary to determine the date and time of the death of a person. Different techniques are used. In this study, we try to analyze the necrobioma that characterizes all the bacteria that populate a corpse. It would be necessary to determine which bacteria first inhabit a dead organism? Which bodies are the fi...
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