Regression Models For Prediction Of Water Quality In Krishna River

The River Krishna and its tributaries drain three important states of South India. The river water plays a very important role in the overall socioeconomic development of Andhra Pradesh.  In large river basins monitoring non-point sources pollution is rather difficult and expensive and is subjected to analytical errors. Hence, modeling water quality using land use data of the basin is attempted in the present study. The contribution from non-point sources (runoff from the river basin) is quiet considerable as the river drains various type of land uses. In this context, it is necessary to make a detailed study of the water quality of the river, to estimate the level of pollution and also main sources of pollution. Correlation studies explain the relationships, between dissolved solids concentration and land use of the basins. The multiple regression models accounted for significant variation in concentrations for majority of dissolved solids. The predicted concentrations are in good agreement with the observed values. The proposed models can be useful for planning land use controls in integrated water quality management program. As water quality of flowing water is closely linked to the land use in the basin, it is essential to include land use management in future river basin planning. Carefully designed land use studies to identify characterized and quantity of non point sources is essential elements to be emphasized to plan water quality management programme. The results of study indicate relative importance of non point sources pollution in addition to point sources pollution. Keywords: Dissolved solids, Land use planning , Regression models, Water quality

In vitro cytotoxicity, in vivo pharmacokinetic studies and tissue distribution studies of multifunctional citric acid dendrimers using the drug Cytarabine

Dendrimers are considered the emerging polymeric architectures, known for their well defined molecular-weight, polydispersity, uniformity and high-surface functionality. These nano-architectures are capable of encapsulating low-high molecular-weight drug moieties in their interior or exterior through covalent bonding and host-guest interactions. Further, large surface volume made researchers to implicate dendrimers in biomedical and therapeutic applications. Regardless of the massive applications, sometimes its use is limited because of the cytotoxicity produced.  Considering this, the present research is focused on the synthesis and PEGylation of citric acid dendrimers. PEGylation is an act of conjugating polyethylene glycol to dendrimers that completely eliminates the toxicity issues associated with dendrimers and render them biocompatible. Cytarabine was loaded in the dendritic architecture to target specifically the tumor cells. Dendrimers are made tumor specific by incorporating certain agents that get cleaved in tumor environment. Synthesized dendrimers were studied for its effect on acute cytotoxicity, tissue-distributions and pharmacokinetic parameters

Performance of no-till maize under drip-fertigation in a double cropping system in semi arid Telangana state of India

Availability of water for Agriculture is becoming increasingly difficult, besides the cost of power for applying it. Improving the water and nitrogen use efficiency has become imperative in present day’s Agriculture. Drip irrigation and fertigation provides the efficient use of limited water with increased water and nutrient use efficiency, respec- tively. A field experiment was conducted during post rainy season of two consecutive years (2011 and 2012), in sandy loam soils of Warangal, Telangana State, India to study the response of no-till maize (Zea mays L) after aerobic rice (Oryza sativa L) to drip irrigation and nitrogen fertigation under semi-arid environment. The experiment was laid out in split plot design with four replications. Three irrigation schedules viz. drip irrigation at 75% Pan Evaporation (PE); 100% PE and 125% PE were taken as main plots and three nitrogen levels through fertigation viz. 120, 160, and 200 kg ha-1 as sub plots. The growth parameters (plant height, LAI, drymatter accumulation), root volume and dry weight, yield attributes (cobs plant-1, kernels cob-1, kernel weight cob-1) kernel yield, stover yield and nitrogen uptake of no till maize increased with increase in water input from 75% PE to 100% PE irrigation schedule in drip irrigation but could not reach the level of significance at 125% PE. Tasseling and silking was hastened in 125% PE schedule. Increase in the level of N application through fertigation from 120 to 160 kg N ha-1 resulted in the increase of all the growth parameters, yield attributes, kernel yield, stover yield and nitrogen uptake. Barrenness and test weight were unaffected by either the irrigation schedules or nitrogen levels. The economic indicators (gross returns, net returns and net benefit: cost ratio) were higher with the irrigation schedule of 125% PE and nitrogen dose of 200 kg N ha-1 applied through fertigation. Increased water input from 75 to 125% PE resulted in decreased water use efficiency but enhanced nitrogen use efficiency while the reverse trend was found with respect to N levels under fertigation

Sparse Social Domains Based Scalable Learning of Collective Behaviour

Abstract-Social networking is process where many people get connected with each other share their views and images. Social Networking has become very important these days where many people get connected globally, every individual today has an social networking site account for example we can consider Facebook which has gained a lot of importance when compared to other social networking sites. We have many social networking domains available in the market like Facebook, Twitter, Linkedin and many others. Social Network is good and interesting at the other side it is insecure also. Now a day's social network accounts are hacked so it is very important for every individual to logout properly in the system where they have used the network and also they should not share their account details with anyone which may lead to illegal issues. In this paper we are performing a scalable learning of a particular user through the usage of their social network and also giving a report like the main purpose for which the social network site was used by that user. Apart from the scalable learning we are also checking with the access control in the social networks where a user can share their views or images or videos to a specific group or to friends secretly. As the social network has gained more significance every individual is curious to get more likes to their posts so it is a very important task to stop the fake accounts or detect the Sybil users in the network. This paper does three tasks in total which are scalable learning, sharing access rights and detection of fake accounts

Toxic Comment Classification using Deep Learning

Online Conversation media serves as a means for individuals to engage, cooperate, and exchange ideas; however, it is also considered a platform that facilitates the spread of hateful and offensive comments, which could significantly impact one's emotional and mental health. The rapid growth of online communication makes it impractical to manually identify and filter out hateful tweets. Consequently, there is a pressing need for a method or strategy to eliminate toxic and abusive comments and ensure the safety and cleanliness of social media platforms. Utilizing LSTM, Character-level CNN, Word-level CNN, and Hybrid model (LSTM + CNN) in this toxicity analysis is to classify comments and identify the different types of toxic classes by means of a comparative analysis of various models. The neural network models utilized for this analysis take in comments extracted from online platforms, including both toxic and non-toxic comments. The results of this study can contribute towards the development of a web interface that enables the identification of toxic and hateful comments within a given sentence or phrase, and categorizes them into their respective toxicity classes

Limonene and BEZ 235 induce apoptosis in COLO-320 and HCT-116 colon cancer cells

Deregulated apoptosis is the hall mark of many cancers, therefore every defect in apoptosis pathway could be a potential target for cancer treatment.The anticancer mechanism of limonene could be multifactorial. However, induction of apoptosis in cancer cells is proposed as the predominant mechanism in several of preclinical studies. Therefore, we determined to investigate the role of apoptosis in the anticancer activity of limonene and BEZ235 combination in COLO-320 and HCT-116 colon cancer cells. Cells after treatments were assessed for apoptosis by DAPI staining for fluorescent microscopic examination of apoptotic cells, estimation of caspases activities, Bcl-2 family proteins in addition to cell cycle analysis by flowcytometry. Results show that both drugs induced apoptosis as demonstrated by increased caspases activity, significant alterations in pro and anti-apoptotic proteins of Bcl-2 family in promoting apoptosis and cell cycle arrest at G1 phase. Over all, it is indicated that limonene and BEZ exerted anticancer activity is mediated through induction of apoptosis involving mitochondria mediated intrinsic death pathway in the selected CRC cells

Limonene and BEZ 235 inhibits growth of COLO-320 and HCT-116 colon cancer cells

D-Limonene is a dietary monoterpene with significant anticancer activity against many cancer types in preclinical and clinical studies. The study is designed to investigate synergistic anticancer effects of limonene and BEZ235 combination in COLO-320 and HCT-116 colon cancer cells. Cells were treated with both the drugs alone and in combination and the effects on cell viability; cell migration and clonogenic potential were examined. Results show that both drugs exhibited dose and time dependant cytotoxicity on the cell lines tested. CompuSyn analysis of the drug combination effects revealed the strong synergistic interaction of the combination. Our results also indicate that COLO-320 cells were more sensitive for anticancer effects of the drugs than HCT-116 cells. The presence of Ras and PI3K mutations in HCT-116 cells could possibly be one of the main reasons for the observed outcome as compared to the wild type expressions of them in COLO-320 cells

FRA2A is a CGG repeat expansion associated with silencing of AFF3

Folate-sensitive fragile sites (FSFS) are a rare cytogenetically visible subset of dynamic mutations. Of the eight molecularly characterized FSFS, four are associated with intellectual disability (ID). Cytogenetic expression results from CGG tri-nucleotide-repeat expansion mutation associated with local CpG hypermethylation and transcriptional silencing. The best studied is the FRAXA site in the FMR1 gene, where large expansions cause fragile X syndrome, the most common inherited ID syndrome. Here we studied three families with FRA2A expression at 2q11 associated with a wide spectrum of neurodevelopmental phenotypes. We identified a polymorphic CGG repeat in a conserved, brain-active alternative promoter of the AFF3 gene, an autosomal homolog of the X-linked AFF2/FMR2 gene: Expansion of the AFF2 CGG repeat causes FRAXE ID. We found that FRA2A-expressing individuals have mosaic expansions of the AFF3 CGG repeat in the range of several hundred repeat units. Moreover, bisulfite sequencing and pyrosequencing both suggest AFF3 promoter hypermethylation. cSNP-analysis demonstrates monoallelic expression of the AFF3 gene in FRA2A carriers thus predicting that FRA2A expression results in functional haploinsufficiency for AFF3 at least in a subset of tissues. By whole-mount in situ hybridization the mouse AFF3 ortholog shows strong regional expression in the developing brain, somites and limb buds in 9.5-12.5dpc mouse embryos. Our data suggest that there may be an association between FRA2A and a delay in the acquisition of motor and language skills in the families studied here. However, additional cases are required to firmly establish a causal relationship

Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021. Methods: The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk–outcome pairs. Pairs were included on the basis of data-driven determination of a risk–outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk–outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk–outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws. Findings: Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7–9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4–9·2]), smoking (5·7% [4·7–6·8]), low birthweight and short gestation (5·6% [4·8–6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8–6·0]). For younger demographics (ie, those aged 0–4 years and 5–14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9–27·7]) and environmental and occupational risks (decrease of 22·0% [15·5–28·8]), coupled with a 49·4% (42·3–56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9–21·7] for high BMI and 7·9% [3·3–12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6–1·9) for high BMI and 1·3% (1·1–1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4–78·8) for child growth failure and 66·3% (60·2–72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP). Interpretation: Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions