Impact of industrial effluents on ground water and soil quality in the vicinity of industrial area of Panipat city, India

The present paper is aimed towards the assessment of heavy metal contamination of agricultural soil due to irrigation with contaminated ground water affected by textile industrial effluents at Panipat city in India. Samples of ground water and irrigated soils from textile industrial area were analyzed for various heavy metals, viz. Mn, Ni, Fe, Cu, Cd, Pb and Zn, using Atomic Absorption Spectrophotometry. Metal transfer factors from ground water to irrigated agricultural soil and from soil to ground water were calculated for heavy metals. The findings deal with the distribution of heavy metals in ground water of industrial area and irrigated agricultural soil. Transfer factors for heavy metals from effluent to ground water were observed to be 0.436, 1.180, 6.461, 2.401, 2.790, 3.178 and 0.634 for Cd, Cu, Fe, Mn, Ni, Pb and Zn respectively. These were found to be very high from ground water to agriculture soil due to the natural shale value of heavy metals in soil system. Thus, untreated industrial effluents can cause an environmental threat to ground water resources and affects soil quality and agricultural plant productivity

STANDARDIZED CREATIVE FIND METHOD FOR RELATIONAL INFORMATION

Stretching The Keyword Search Concept Towards Relational Information Is An Engaged Portion Of Study Within Database And Understanding Retrieval Community In The Last Few Years. Abundant Techniques Were Forecasted, However No Matter Several Guides There Remain Inadequate Consistency For Assessment Of Forecasted Search Techniques. Our Understanding With Conventional Techniques Of Search Techniques Submit That Random Evaluations That Can Come Into View Inside The Literature Aren't Enough. They Were According To Survey Of Existing Evaluations By Information Retrieval Community For Assessment Of Retrieval Systems. Our Earlier Efforts Have In Contrast Techniques Of Relational Keyword Search Regarding Search Efficiency Try Not To Imagine Runtime Performance. Inside Our Work We Submit Most Meticulous Assessment Of Empirical Performance Concerning Relational Keyword Search That Has Came Out Up To Now Inside The Literature. Modified From Numerous Evaluations That Have Been Reported In Literature, Ours Examine Overall, Finish-To-Finish Performance Of Techniques Concerning Relational Keyword Search. Unlike Several Evaluations That Can Come Into View Inside The Literature, Our Benchmark Utilize Reasonable Data Sets And Practical Queries To Look At The Different Tradeoffs Created In Fashion Of Search Techniques. It Is The First Effort To Combine Performance And Appearance Efficiency In Character In Particular Figures Of Search Techniques

Time lagged information theoretic approaches to the reverse engineering of gene regulatory networks

Background: A number of models and algorithms have been proposed in the past for gene regulatory network (GRN) inference; however, none of them address the effects of the size of time-series microarray expression data in terms of the number of time-points. In this paper, we study this problem by analyzing the behaviour of three algorithms based on information theory and dynamic Bayesian network (DBN) models. These algorithms were implemented on different sizes of data generated by synthetic networks. Experiments show that the inference accuracy of these algorithms reaches a saturation point after a specific data size brought about by a saturation in the pair-wise mutual information (MI) metric; hence there is a theoretical limit on the inference accuracy of information theory based schemes that depends on the number of time points of micro-array data used to infer GRNs. This illustrates the fact that MI might not be the best metric to use for GRN inference algorithms. To circumvent the limitations of the MI metric, we introduce a new method of computing time lags between any pair of genes and present the pair-wise time lagged Mutual Information (TLMI) and time lagged Conditional Mutual Information (TLCMI) metrics. Next we use these new metrics to propose novel GRN inference schemes which provides higher inference accuracy based on the precision and recall parameters. Results: It was observed that beyond a certain number of time-points (i.e., a specific size) of micro-array data, the performance of the algorithms measured in terms of the recall-to-precision ratio saturated due to the saturation in the calculated pair-wise MI metric with increasing data size. The proposed algorithms were compared to existing approaches on four different biological networks. The resulting networks were evaluated based on the benchmark precision and recall metrics and the results favour our approach. Conclusions: To alleviate the effects of data size on information theory based GRN inference algorithms, novel time lag based information theoretic approaches to infer gene regulatory networks have been proposed. The results show that the time lags of regulatory effects between any pair of genes play an important role in GRN inference schemes

The chromatin remodelling enzymes SNF2H and SNF2L position nucleosomes adjacent to CTCF and other transcription

Within the genomes of metazoans, nucleosomes are highly organised adjacent to the binding sites for a subset of transcription factors. Here we have sought to investigate which chromatin remodelling enzymes are responsible for this. We find that the ATP-dependent chromatin remodelling enzyme SNF2H plays a major role organising arrays of nucleosomes adjacent to the binding sites for the architectural transcription factor CTCF sites and acts to promote CTCF binding. At many other factor binding sites SNF2H and the related enzyme SNF2L contribute to nucleosome organisation. The action of SNF2H at CTCF sites is functionally important as depletion of CTCF or SNF2H affects transcription of a common group of genes. This suggests that chromatin remodelling ATPase's most closely related to the Drosophila ISWI protein contribute to the function of many human gene regulatory elements

High resolution imaging reveals heterogeneity in chromatin states between cells that is not inherited through cell division

BACKGROUND: Genomes of eukaryotes exist as chromatin, and it is known that different chromatin states can influence gene regulation. Chromatin is not a static structure, but is known to be dynamic and vary between cells. In order to monitor the organisation of chromatin in live cells we have engineered fluorescent fusion proteins which recognize specific operator sequences to tag pairs of syntenic gene loci. The separation of these loci was then tracked in three dimensions over time using fluorescence microscopy. RESULTS: We established a work flow for measuring the distance between two fluorescently tagged, syntenic gene loci with a mean measurement error of 63 nm. In general, physical separation was observed to increase with increasing genomic separations. However, the extent to which chromatin is compressed varies for different genomic regions. No correlation was observed between compaction and the distribution of chromatin markers from genomic datasets or with contacts identified using capture based approaches. Variation in spatial separation was also observed within cells over time and between cells. Differences in the conformation of individual loci can persist for minutes in individual cells. Separation of reporter loci was found to be similar in related and unrelated daughter cell pairs. CONCLUSIONS: The directly observed physical separation of reporter loci in live cells is highly dynamic both over time and from cell to cell. However, consistent differences in separation are observed over some chromosomal regions that do not correlate with factors known to influence chromatin states. We conclude that as yet unidentified parameters influence chromatin configuration. We also find that while heterogeneity in chromatin states can be maintained for minutes between cells, it is not inherited through cell division. This may contribute to cell-to-cell transcriptional heterogeneity. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12860-016-0111-y) contains supplementary material, which is available to authorized users