The purpose of this study is to investigate the biostimulation effect of 532 nm CW laser on the metabolism of Saccharomyces cerevisiae yeast. Cells were irradiated by 532 nm Nd:YAG laser using 0.153 W/cm2 power density at 30, 45, 60,180 and 300 seconds exposure times in their respective orders. Intrafluorescence parameters were measured by detection the autofluorescence intensity, proliferation rate and Imaging the fluorescent mitochondria using confocal laser scanning microscope. The results showed that the 30 and 45 second exposure times seem to have stimulated changes in the cells that led to increase proliferation, viability and mitochondrial activity. Autofluorescence of cells increased after 45 and 60 seconds exposure time. After 300 seconds there seems to be very noticeable decrease in proliferation, viability and autofluorescence. Confocal microscopy images showed that here is a correlation between fluorescence intensity using mitochondrial probes and proliferation rates of cells.
Introduction
Saccharomyces cerevisiae is one of the most important fungi in the history of the world. This yeast is responsible for the production of alcoholic beverages and bread and a source of protein and was used in biotechnology and genetics as a host for the genes of other organisms (Madigan, et al. 2006). Low energy laser irradiation of which output power is in the range of mW modulates various biological effects and has been shown to have positive effect on living organisms both in vitro and in vivo. However, the true effect of low energy laser on cell proliferation is sill controversial, because of conflicting reports on the effects of visible laser light on the cells in culture (Antonio, et al., 2002).
There are many evidences that the most intracellular autofluorescence
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Forecasting is one of the important topics in the analysis of time series, as the importance of forecasting in the economic field has emerged in order to achieve economic growth. Therefore, accurate forecasting of time series is one of the most important challenges that we seek to make the best decision, the aim of the research is to suggest employing hybrid models to predict daily crude oil prices. The hybrid model consists of integrating the linear component, which represents Box Jenkins models, and the non-linear component, which represents one of the methods of artificial intelligence, which is the artificial neural network (ANN), support vector regression (SVR) algorithm and it was shown that the proposed hybrid models in the predicti
... Show MoreBackground: Indeterminate colitis (IC), a term
originated by pathologists to characterize confounding
histopathlogic appearance of resected mucosa, has
become catch phrase for cases in which diagnostic
criteria at all levels elude classification as Crohn's
disease (CD) or ulcerative colitis (UC).
OBJECTIVES: evaluate the prevalence of pANCA
expression in the sera and its isotypes.
Patients and methods: PATIENTS GROUP
consisted of 60 patients (40 males and 20 females)
with indeterminate colitis and their age range was (19-
84 years). CONTROL GROUP consisted of 30 (15
males and 15 females) healthy volunteers and their
age range was (20- 66 years).
Antineutrophil cytoplasmic ( pANCA and cANCA)
te
The importance of forecasting has emerged in the economic field in order to achieve economic growth, as forecasting is one of the important topics in the analysis of time series, and accurate forecasting of time series is one of the most important challenges in which we seek to make the best decision. The aim of the research is to suggest the use of hybrid models for forecasting the daily crude oil prices as the hybrid model consists of integrating the linear component, which represents Box Jenkins models and the non-linear component, which represents one of the methods of artificial intelligence, which is long short term memory (LSTM) and the gated recurrent unit (GRU) which represents deep learning models. It was found that the proposed h
... Show MorePeriodontitis is one of the most prevalent bacterial diseases affecting man with up to 90% of the global population affected. Its severe form can lead to the tooth loss in 10-15% of the population worldwide. The disease is caused by a dysbiosis of the local microbiota and one organism that contributes to this alteration in the bacterial population is Prophyromonas gingivalis. This organism possesses a range of virulence factors that appear to contribute to its growth and survival at a periodontal site amongst which is its ability to invade oral epithelial cells. Such an invasion strategy provides a means of evasion of host defence mechanisms, persistence at a site and the opportunity for dissemination to other sites in the mouth. However, p
... Show MoreBackground: Chronic suppurative otitis media (CSOM) is the result of aninitial episode of acute otitis media and is characterized by a persistent discharge from the middle ear through a tympanic perforation for at least 2 weeks duration. It is an important cause of preventable hearing loss, particularly in the developing world.Methods. 1. To get an overview on the bacterial ear infection profile in general 2. To assess the antibiotic resistance of Pseudomonal infection (PS) particularly since it is usually the commonest infection to cause otitis media and the most difficult to treat due to the problem of multi drug resistance... A cross sectional study was done which included 405 patient of CSOM patients196 (48%) case were males ,209 (52
... Show MoreBackground: Chronic suppurative otitis media (CSOM) is the result of an initial episode of acute otitis media and is characterized by a persistent discharge from the middle ear through a tympanic perforation for at least 2 weeks duration. It is an important cause of preventable hearing loss, particularly in the developing world.Objective: To get an overview on the bacterial ear infection profile in general and to assess the antibiotic resistance of Pseudomonal infection (PS) particularly since it is usually the commonest infection to cause otitis media and the most difficult to treat due to the problem of multi drug resistance..Methods: A cross sectional study was done which included 405 patients of CSOM patients, 196 (48%) case were mal
... Show MoreSurvival analysis is widely applied in data describing for the life time of item until the occurrence of an event of interest such as death or another event of understudy . The purpose of this paper is to use the dynamic approach in the deep learning neural network method, where in this method a dynamic neural network that suits the nature of discrete survival data and time varying effect. This neural network is based on the Levenberg-Marquardt (L-M) algorithm in training, and the method is called Proposed Dynamic Artificial Neural Network (PDANN). Then a comparison was made with another method that depends entirely on the Bayes methodology is called Maximum A Posterior (MAP) method. This method was carried out using numerical algorithms re
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Smart cities have recently undergone a fundamental evolution that has greatly increased their potentials. In reality, recent advances in the Internet of Things (IoT) have created new opportunities by solving a number of critical issues that are allowing innovations for smart cities as well as the creation and computerization of cutting-edge services and applications for the many city partners. In order to further the development of smart cities toward compelling sharing and connection, this study will explore the information innovation in smart cities in light of the Internet of Things (IoT) and cloud computing (CC). IoT data is first collected in the context of smart cities. The data that is gathered is uniform. The Internet of Things,
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Beyond the immediate content of speech, the voice can provide rich information about a speaker's demographics, including age and gender. Estimating a speaker's age and gender offers a wide range of applications, spanning from voice forensic analysis to personalized advertising, healthcare monitoring, and human-computer interaction. However, pinpointing precise age remains intricate due to age ambiguity. Specifically, utterances from individuals at adjacent ages are frequently indistinguishable. Addressing this, we propose a novel, end-to-end approach that deploys Mozilla's Common Voice dataset to transform raw audio into high-quality feature representations using Wav2Vec2.0 embeddings. These are then channeled into our self-attentio
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