Search results for: Madiha Gohar

Authors: Madiha El Awamie, Catherine Rees

Abstract:

Natural preservatives have been used as alternatives to traditional chemical preservatives; however, a limited number have been commercially developed and many remain to be investigated as sources of safer and effective antimicrobials. In this study, we have been investigating the antimicrobial activity of an extract of Glycyrrhiza glabra (liquorice) that was provided as a waste material from the production of liquorice flavourings for the food industry, and to investigate if this retained the expected antimicrobial activity so it could be used as a natural preservative. Antibacterial activity of liquorice extract was screened for evidence of growth inhibition against eight species of Gram-negative and Gram-positive bacteria, including Listeria monocytogenes, Listeria innocua, Staphylococcus aureus, Enterococcus faecalis and Bacillus subtilis. The Gram-negative bacteria tested include Pseudomonas aeruginosa, Escherichia coli and Salmonella typhimurium but none of these were affected by the extract. In contrast, for all of the Gram-positive bacteria tested, growth was inhibited as monitored using optical density. However parallel studies using viable count indicated that the cells were not killed meaning that the extract was bacteriostatic rather than bacteriocidal. The Minimum Inhibitory Concentration [MIC] and Minimum Bactericidal Concentration [MBC] of the extract was also determined and a concentration of 50 µg ml^-1 was found to have a strong bacteriostatic effect on Gram-positive bacteria. Microscopic analysis indicated that there were changes in cell shape suggesting the cell wall was affected. In addition, the use of a reporter strain of Listeria transformed with the bioluminescence genes luxABCDE indicated that cell energy levels were reduced when treated with either 12.5 or 50 µg ml^-1 of the extract, with the reduction in light output being proportional to the concentration of the extract used. Together these results suggest that the extract is inhibiting the growth of Gram-positive bacteria only by damaging the cell wall and/or membrane.

Keywords: antibacterial activity, bioluminescence, Glycyrrhiza glabra, natural preservative

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Authors: Javier Muro, Anja Linstadter, Florian Manner, Lisa Schwarz, Stephan Wollauer, Paul Magdon, Gohar Ghazaryan, Olena Dubovyk

Abstract:

Monitoring the trade-off between biomass production and biodiversity in grasslands is critical to evaluate the effects of management practices across environmental gradients. New generations of remote sensing sensors and machine learning approaches can model grasslands’ characteristics with varying accuracies. However, studies often fail to cover a sufficiently broad range of environmental conditions, and evidence suggests that prediction models might be case specific. In this study, biomass production and biodiversity indices (species richness and Fishers’ α) are modeled in 150 grassland plots for three sites across Germany. These sites represent a North-South gradient and are characterized by distinct soil types, topographic properties, climatic conditions, and management intensities. Predictors used are derived from Sentinel-1 & 2 and a set of topoedaphic variables. The transferability of the models is tested by training and validating at different sites. The performance of feed-forward deep neural networks (DNN) is compared to a random forest algorithm. While biomass predictions across gradients and sites were acceptable (r2 0.5), predictions of biodiversity indices were poor (r2 0.14). DNN showed higher generalization capacity than random forest when predicting biomass across gradients and sites (relative root mean squared error of 0.5 for DNN vs. 0.85 for random forest). DNN also achieved high performance when using the Sentinel-2 surface reflectance data rather than different combinations of spectral indices, Sentinel-1 data, or topoedaphic variables, simplifying dimensionality. This study demonstrates the necessity of training biomass and biodiversity models using a broad range of environmental conditions and ensuring spatial independence to have realistic and transferable models where plot level information can be upscaled to landscape scale.

Keywords: ecosystem services, grassland management, machine learning, remote sensing

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Authors: Alina Muradyan, Lina Babayan, Arsen Nanyan, Gohar Galstyan, Vigen Khachatryan

Abstract:

We present a photometric method for identifying stars, galaxies and quasars in multi-color surveys, which uses a library of ∼> 65000 color templates for comparison with observed objects. The method aims for extracting the information content of object colors in a statistically correct way, and performs a classification as well as a redshift estimation for galaxies and quasars in a unified approach based on the same probability density functions. For the redshift estimation, we employ an advanced version of the Minimum Error Variance estimator which determines the redshift error from the redshift dependent probability density function itself. The method was originally developed for the Calar Alto Deep Imaging Survey (CADIS), but is now used in a wide variety of survey projects. We checked its performance by spectroscopy of CADIS objects, where the method provides high reliability (6 errors among 151 objects with R < 24), especially for the quasar selection, and redshifts accurate within σz ≈ 0.03 for galaxies and σz ≈ 0.1 for quasars. For an optimization of future survey efforts, a few model surveys are compared, which are designed to use the same total amount of telescope time but different sets of broad-band and medium-band filters. Their performance is investigated by Monte-Carlo simulations as well as by analytic evaluation in terms of classification and redshift estimation. If photon noise were the only error source, broad-band surveys and medium-band surveys should perform equally well, as long as they provide the same spectral coverage. In practice, medium-band surveys show superior performance due to their higher tolerance for calibration errors and cosmic variance. Finally, we discuss the relevance of color calibration and derive important conclusions for the issues of library design and choice of filters. The calibration accuracy poses strong constraints on an accurate classification, which are most critical for surveys with few, broad and deeply exposed filters, but less severe for surveys with many, narrow and less deep filters.

Keywords: VO, ArVO, DFBS, FITS, image processing, data analysis

Procedia PDF Downloads 63

Authors: Sadaf Moeez, Madiha Khalid, Zoya Khalid, Sania Shaheen, Sumbul Khalid

Abstract:

Background: Inter-individual variation in response to metformin, which has been considered as a first line therapy for T2DM treatment is considerable. In the current study, it was aimed to investigate the impact of two genetic variants Leu125Phe (rs77474263) and Gly64Asp (rs77630697) in gene SLC47A1 on the clinical efficacy of metformin in T2DM Pakistani patients. Methods: The study included 800 T2DM patients (400 metformin responders and 400 metformin non-responders) along with 400 ethnically matched healthy individuals. The genotypes were determined by allele-specific polymerase chain reaction. In-silico analysis was done to confirm the effect of the two SNPs on the structure of genes. Association was statistically determined using SPSS software. Results: Minor allele frequency for rs77474263 and rs77630697 was 0.13 and 0.12. For SLC47A1 rs77474263 the homozygotes of one mutant allele ‘T’ (CT) of rs77474263 variant were fewer in metformin responders than metformin non-responders (29.2% vs. 35.5 %). Likewise, the efficacy was further reduced (7.2% vs. 4.0 %) in homozygotes of two copies of ‘T’ allele (TT). Remarkably, T2DM cases with two copies of allele ‘C’ (CC) had 2.11 times more probability to respond towards metformin monotherapy. For SLC47A1 rs77630697 the homozygotes of one mutant allele ‘A’ (GA) of rs77630697 variant were fewer in metformin responders than metformin non-responders (33.5% vs. 43.0 %). Likewise, the efficacy was further reduced (8.5% vs. 4.5%) in homozygotes of two copies of ‘A’ allele (AA). Remarkably, T2DM cases with two copies of allele ‘G’ (GG) had 2.41 times more probability to respond towards metformin monotherapy. In-silico analysis revealed that these two variants affect the structure and stability of their corresponding proteins. Conclusion: The present data suggest that SLC47A1 Leu125Phe (rs77474263) and Gly64Asp (rs77630697) polymorphisms were associated with the therapeutic response of metformin in T2DM patients of Pakistan.

Keywords: diabetes, T2DM, SLC47A1, Pakistan, polymorphism

Procedia PDF Downloads 145

Authors: Sajjad Ali Khan Sajjad Ali Khan, Gohar Ayub, Khalil Ur Rahman, Muhammad Sajid, Mumtaz Farooq, Mohammad Irshad, Haider Ali

Abstract:

A trail was carried out to know the effect of different soil media and planting time on the cuttings of cherry (Prunus avium L.) rootstock Colt at Agriculture Research Institute (ARI) Mingora swat, during winter 2011. The experiment was laid out in Randomized Complete Block Design (RCBD) with split plot arrangement and was replicated three times. Soil media (Silt, Garden soil and Silt+Garden soil+FYM) were assigned to main plots whereas, planting Dates (1st Jan, 11th Jan, 21st Jan, 1st Feb, 11th Feb, 21st Feb and 2nd March) subjected to sub plots. The data recorded on sprouting percentage, shoot diameter cutting-1, number of leaves cutting-1, rootstock height (cm), survival percentage, number of roots, root length (cm), root volume (cm3) and root weight (gm) were significantly affected by different soil media. Maximum sprouting percentage (100%), shoot diameter (1.72 mm), number of leaves cutting-1 (76.74), rootstock height (104.36 cm), survival percentage (41.67%), number of roots (76.35), root length (11.28 cm), root volume (4.43 cm3) and root weight (4.64 gm) were recorded in media M3 (Garden soil+silt+FYM). A significant response to various planting dates were observed for most of vegetative and rooting attributes of cherry rootstock Colt. 1st January plantation showed maximum sprouting percentage (100%), shoot diameter (1.99 mm), number of leaves (81.46), rootstock height (126.24 cm), survival percentage (58.12%), whereas 11th January plantation showed more number of roots (94.43), root length (10.60 cm), root volume (3.68 cm3) and root weight (3.71 gm). Based on the results from the experimental work, it is recommended that cherry cuttings should be planted in early January in soil media (Silt+Garden soil+ FYM) for better growth and development under the agro climatic conditions of temperate region.

Keywords: soil media, cherry rootstock, planting dates, growth parameters

Procedia PDF Downloads 88