FAILING OF INFORMATION TRANSMISSION BY DORSAL HIPPOCAMPUS DUE TO MICROINJECTION OF COLCHICINE IN RAT'S CORTICAL AREA 1

ABSTRACTObjective: Colchicine has been introduced recently as a neurotoxin with damage effect on neurons of hippocampal cortical area 1 (CA1). Effect ofcolchicine, a plant derived neurotoxin on memory retrieval was explored experimentally by means of novelty seeking task in intact Wistar rats.Methods: The subjects were cannulated by stereotaxic apparatus at coordinates adjusted for the CA1 area. After recovery, all animals experiencedthe novelty seeking paradigm using an unbiased conditioning device. First, they were habituated with the conditioned place preference (CPP)apparatus. They were then confined in one part of the CPP box for 3 consecutive days. Finally, the animals were microinjected colchicine (1-25 μg/rat)intra‑hippocampal CA1 prior to testing. Control group was cannulated too, but, solely injected saline (1-μl/rat, intra-CA1). The time spent in the novelpart of the device and the motivational signs of the rats were measured. Furthermore, the possible cell injury effect of the toxin on the CA1 layer wasverified.Results: The alkaloid caused significant novelty seeking behavior in the experimental animals though did not show a significant effect on thecompartment entering. The destruction effect of the neurotoxin on the treated rats' dendrites spines was evidenced.Conclusion: Based on this finding the information transmission by dorsal hippocampal pyramidal cells may impair with an administration ofneurotoxin colchicine, intra-CA1.Keywords: Colchicine, Memory retrieval, Novelty seeking behavior, Cortical area 1, Pyramidal cell layer

The Impact of Programs of Trade and Investment and Risk Reduction by the Government on Rural Income in Kermanshah Province

Government programs and policies can different impact in rural income. The main goal of this work is the study and analyses programs of trade and investment and risk reduction by the government on rural income in Kermanshah province. At the end of those comparisons w

Quantitative determination of formaldehyde by spectrophotometry utilizing multivariate Curve resolution alternating least squares

Formaldehyde is a vastly used material in industry. Nowadays, it is proven that formaldehyde is toxic and carcinogenic. Thus providing a reliable method for its quantitative determination is very important. This study proposes a UV-Vis spectrophotometric based method for determination of formaldehyde. The method is based on reaction between the analyte and Fluoral P. Spectral changes during the time were mathematically analyzed using a chemometrics technique, called "multivariate curve resolution alternating least squares" (MCR-ALS). Data processing by this chemometrics technique enhanced the reliability of the UV-Vis spectrophotometry for quantitative analysis of formaldehyde in real samples. KEY WORDS: Formaldehyde, Fluoral P, UV-Visible, Multivariate curve resolution alternating least squares; Quantitative analysis Bull. Chem. Soc. Ethiop. 2012, 26(2), 299-304.DOI: http://dx.doi.org/10.4314/bcse.v26i2.1

Earthquake risk assessment using an integrated Fuzzy Analytic Hierarchy Process with Artificial Neural Networks based on GIS: A case study of Sanandaj in Iran

Earthquakes are natural phenomena, which induce natural hazard that seriously threatens urban areas, despite significant advances in retrofitting urban buildings and enhancing the knowledge and ability of experts in natural disaster control. Iran is one of the most seismically active countries in the world. The purpose of this study was to evaluate and analyze the extent of earthquake vulnerability in relation to demographic, environmental, and physical criteria. An earthquake risk assessment (ERA) map was created by using a Fuzzy-Analytic Hierarchy Process coupled with an Artificial Neural Networks (FAHP-ANN) model generating five vulnerability classes. Combining the application of a FAHP-ANN with a geographic information system (GIS) enabled to assign weights to the layers of the earthquake vulnerability criteria. The model was applied to Sanandaj City in Iran, located in the seismically active Sanandaj-Sirjan zone which is frequently affected by devastating earthquakes. The Multilayer Perceptron (MLP) model was implemented in the IDRISI software and 250 points were validated for grades 0 and 1. The validation process revealed that the proposed model can produce an earthquake probability map with an accuracy of 95%. A comparison of the results attained by using a FAHP, AHP and MLP model shows that the hybrid FAHP-ANN model proved flexible and reliable when generating the ERA map. The FAHP-ANN model accurately identified the highest earthquake vulnerability in densely populated areas with dilapidated building infrastructure. The findings of this study are useful for decision makers with a scientific basis to develop earthquake risk management strategies

Forecasting of rainfall using different input selection methods on climate signals for neural network inputs

Long-term prediction of precipitation in planning and managing water resources, especially in arid and semi-arid countries such as Iran, has a great importance. In this paper, a method for predicting long-term precipitation using weather signals and artificial neural networks is presented. For this purpose, climatic data (large-scale signals) and meteorological data (local precipitation and temperature) with 3 to 12 months lead-times are used as inputs to predict precipitation for 3, 6, 9 and 12 months periods in 6 selected stations across Iran. A genetic algorithm (GA) and self-organized neural network (SOM) along with the application of winGamma software were comparatively used as input selection methods to choose the appropriate input variables. Examining the results, out of 96 predictions performed at all stations, in 43 cases, GA, in 28 cases, winGamma, and in 25 cases SOM have the best results compared to the other two methods. According to this, as a generalized assumption, it can be said that at least for the selected stations in this paper, the GA method is more reliable than the other two methods, and can be used to make predictions for future applications as a reliable input selection method. Moreover, among different climatic signals, Pacific Decadal Oscillation (PDO), Trans-Niño Index (TNI) and Eastern Tropical Pacific SST (NINO3) are the most repetitive indices for the most accurate forecast of each station

Adaptive Speech Enhancement Using Partial Differential Equations and Back Propagation Neural Networks

Abstract: In this work, we propose a new approach to improve the performance of speech enhancement technique based on partial differential equations. As we know, the real-world noise is highly random in nature. So we try for reduction of white Gaussian noise. The proposed method was evaluated on several speakers. The subjective and objective results show that the new method highly improves speech enhancement. Comparisons of several methods are reported

Radiobiological effects of wound fluid on breast cancer cell lines and human-derived tumor spheroids in 2D and microfluidic culture

Intraoperative radiotherapy (IORT) could abrogate cancer recurrences, but the underlying mechanisms are unclear. To clarify the effects of IORT-induced wound fluid on tumor progression, we treated breast cancer cell lines and human-derived tumor spheroids in 2D and microfluidic cell culture systems, respectively. The viability, migration, and invasion of the cells under treatment of IORT-induced wound fluid (WF-RT) and the cells under surgery-induced wound fluid (WF) were compared. Our findings showed that cell viability was increased in spheroids under both WF treatments, whereas viability of the cell lines depended on the type of cells and incubation times. Both WFs significantly increased sub-G1 and arrested the cells in G0/G1 phases associated with increased P16 and P21 expression levels. The expression level of Caspase 3 in both cell culture systems and for both WF-treated groups was significantly increased. Furthermore, our results revealed that although the migration was increased in both systems of WF-treated cells compared to cell culture media-treated cells, E-cadherin expression was significantly increased only in the WF-RT group. In conclusion, WF-RT could not effectively inhibit tumor progression in an ex vivo tumor-on-chip model. Moreover, our data suggest that a microfluidic system could be a suitable 3D system to mimic in vivo tumor conditions than 2D cell culture

Decoding Clinical Biomarker Space of COVID-19: Exploring Matrix Factorization-based Feature Selection Methods

One of the most critical challenges in managing complex diseases like COVID-19 is to establish an intelligent triage system that can optimize the clinical decision-making at the time of a global pandemic. The clinical presentation and patients’ characteristics are usually utilized to identify those patients who need more critical care. However, the clinical evidence shows an unmet need to determine more accurate and optimal clinical biomarkers to triage patients under a condition like the COVID-19 crisis. Here we have presented a machine learning approach to find a group of clinical indicators from the blood tests of a set of COVID-19 patients that are predictive of poor prognosis and morbidity. Our approach consists of two interconnected schemes: Feature Selection and Prognosis Classification. The former is based on different Matrix Factorization (MF)-based methods, and the latter is performed using Random Forest algorithm. Our model reveals that Arterial Blood Gas (ABG) O2 Saturation and C-Reactive Protein (CRP) are the most important clinical biomarkers determining the poor prognosis in these patients. Our approach paves the path of building quantitative and optimized clinical management systems for COVID-19 and similar diseases

Decomposing socioeconomic inequality in poor mental health among Iranian adult population: results from the PERSIAN cohort study

Background Socioeconomic inequality in mental health in Iran is poorly understood. This study aimed to assess socioeconomic inequality in poor mental health among Iranian adults. Methods The study used the baseline data of PERSIAN cohort study including 131,813 participants from 17 geographically distinct areas of Iran. The Erreygers Concentration index (E) was used to quantify the socioeconomic inequalities in poor mental health. Moreover, we decomposed the E to identify factors contributing to the observed socioeconomic inequality in poor mental health in Iran. Results The estimated E for poor mental health was - 0.012 (95% CI: - 0.0144, - 0.0089), indicating slightly higher concentration of mental health problem among socioeconomically disadvantaged adults in Iran. Socioeconomic inequality in poor mental health was mainly explained by gender (19.93%) and age (12.70%). Region, SES itself, and physical activity were other important factors that contributed to the concentration of poor mental health among adults with low socioeconomic status. Conclusion There exists nearly equitable distribution in poor mental health among Iranian adults, but with important variations by gender, SES, and geography. These results suggested that interventional programs in Iran should focus on should focus more on socioeconomically disadvantaged people as a whole, with particular attention to the needs of women and those living in more socially disadvantaged regions. Keywords:Mental health; Socioeconomic inequality; Concentration index; Decompositio

Global, regional, and national disability-adjusted life-years (DALYs) for 359 diseases and injuries and healthy life expectancy (HALE) for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017.

How long one lives, how many years of life are spent in good and poor health, and how the population's state of health and leading causes of disability change over time all have implications for policy, planning, and provision of services. We comparatively assessed the patterns and trends of healthy life expectancy (HALE), which quantifies the number of years of life expected to be lived in good health, and the complementary measure of disability-adjusted life-years (DALYs), a composite measure of disease burden capturing both premature mortality and prevalence and severity of ill health, for 359 diseases and injuries for 195 countries and territories over the past 28 years. Methods We used data for age-specific mortality rates, years of life lost (YLLs) due to premature mortality, and years lived with disability (YLDs) from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 to calculate HALE and DALYs from 1990 to 2017. We calculated HALE using age-specific mortality rates and YLDs per capita for each location, age, sex, and year. We calculated DALYs for 359 causes as the sum of YLLs and YLDs. We assessed how observed HALE and DALYs differed by country and sex from expected trends based on Socio-demographic Index (SDI). We also analysed HALE by decomposing years of life gained into years spent in good health and in poor health, between 1990 and 2017, and extra years lived by females compared with males. Findings Globally, from 1990 to 2017, life expectancy at birth increased by 7·4 years (95% uncertainty interval 7·1-7·8), from 65·6 years (65·3-65·8) in 1990 to 73·0 years (72·7-73·3) in 2017. The increase in years of life varied from 5·1 years (5·0-5·3) in high SDI countries to 12·0 years (11·3-12·8) in low SDI countries. Of the additional years of life expected at birth, 26·3% (20·1-33·1) were expected to be spent in poor health in high SDI countries compared with 11·7% (8·8-15·1) in low-middle SDI countries. HALE at birth increased by 6·3 years (5·9-6·7), from 57·0 years (54·6-59·1) in 1990 to 63·3 years (60·5-65·7) in 2017. The increase varied from 3·8 years (3·4-4·1) in high SDI countries to 10·5 years (9·8-11·2) in low SDI countries. Even larger variations in HALE than these were observed between countries, ranging from 1·0 year (0·4-1·7) in Saint Vincent and the Grenadines (62·4 years [59·9-64·7] in 1990 to 63·5 years [60·9-65·8] in 2017) to 23·7 years (21·9-25·6) in Eritrea (30·7 years [28·9-32·2] in 1990 to 54·4 years [51·5-57·1] in 2017). In most countries, the increase in HALE was smaller than the increase in overall life expectancy, indicating more years lived in poor health. In 180 of 195 countries and territories, females were expected to live longer than males in 2017, with extra years lived varying from 1·4 years (0·6-2·3) in Algeria to 11·9 years (10·9-12·9) in Ukraine. Of the extra years gained, the proportion spent in poor health varied largely across countries, with less than 20% of additional years spent in poor health in Bosnia and Herzegovina, Burundi, and Slovakia, whereas in Bahrain all the extra years were spent in poor health. In 2017, the highest estimate of HALE at birth was in Singapore for both females (75·8 years [72·4-78·7]) and males (72·6 years [69·8-75·0]) and the lowest estimates were in Central African Republic (47·0 years [43·7-50·2] for females and 42·8 years [40·1-45·6] for males). Globally, in 2017, the five leading causes of DALYs were neonatal disorders, ischaemic heart disease, stroke, lower respiratory infections, and chronic obstructive pulmonary disease. Between 1990 and 2017, age-standardised DALY rates decreased by 41·3% (38·8-43·5) for communicable diseases and by 49·8% (47·9-51·6) for neonatal disorders. For non-communicable diseases, global DALYs increased by 40·1% (36·8-43·0), although age-standardised DALY rates decreased by 18·1% (16·0-20·2)