Acute leukemia is a critical neoplasm of white blood cells. In order to differentiate between the metabolic alterations associated with two subtypes of acute leukemia, acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML), we investigated the serum of ALL and AML patients and compared with two controls (healthy and aplastic anemia) using 1H NMR (nuclear magnetic resonance) spectroscopy. Thirty-seven putative metabolites were identified using Carr-Purcell-Meiboom-Gill (CPMG) sequence. The use of PLS-DA and OPLS-DA models gave results with 84.38% and 90.63% classification rate, respectively. The metabolites responsible for classification are mainly lipids, lactate and glucose. Compared with controls, ALL and AML patients showed serum metabonomic differences involving aberrant metabolism pathways including glycolysis, TCA cycle, lipoprotein changes, choline and fatty acid metabolisms.

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This paper analyses and applies a spatio-statistical failure rate (SSFR) technique for landslide susceptibility zonation in the Hindu Kush region, Pakistan. The study area (Shahpur valley) is located in the eastern Hindu Kush mountain system. In Shahpur valley, land sliding is a recurrent and costly extreme event. Geologically, this region constitutes the youngest mountain systems and almost every year landslide-induced losses are reported. The frequency and intensity of landslide events is expected to further increase in future due to rapid population growth over the fragile slopes, infrastructural development and deforestation. In order to achieve objectives of the study, data were obtained from both primary and secondary sources. In Shahpur valley, an inventory of the past 300 landslide events of various sizes has been identified and marked on a SPOT satellite image of 2.5 m resolution. In order to identify the influence of landslide triggering factors, such as geology, tectonic structures, land use, slope angle, slope aspect, roads and streams, a univariate SSFR technique has been tested and applied for calculating the susceptibility score in each class of the selected parameters. Based on factor maps and cumulative score, the landslide susceptibility zones have been developed and validated appearing to be significantly reflecting the pattern of the past landslide events.

Artonin I can be developed as potential antimicrobial and resistance reversal agent.

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This study focuses on the analysis of flood susceptibility and resultant zonation for risk management using frequency ratio model in District Charsadda, Pakistan. To achieve the study objectives, a reconnaissance survey was conducted, and frequent flood inundated areas were identified in the study area by interpretation of Landsat 7 image together with the intensive field survey, a total of 161 flooded locations were demarcated at different part of the district with handheld GPS. As a result, an inventory of spatial database of past flood inundation was generated and role of all the influencing factors for detecting the extent of flood susceptibility. During flood susceptibility analysis, ten conditioning parameters including: elevation, slope, aspect, curvature, plan curvature, profile curvature, proximity to roads, proximity to streams, proximity to river and land use/land cover were selected. A correlation between conditioning factors and flood was calculated using frequency ratio method. Consequently, the summation of frequency ratio values was taken for all the parameters for development of flood susceptibility index. The flood susceptibility index was then classified into five zones of very low (27.64%), low (39.88%), moderately susceptible (22.25%), high susceptible (7.78%), very high (2.46%). So, for the likelihood of the model was determined using success rate curve method, area under curve acquired for the model was 0.9226. The flood susceptibility zones could be used for flood risk management and land use planning for minimizing the potential risk in the floodplain of rivers flowing through the study area.

By using internal combinatorial library we were able to identify (4R)-thiazolidines carboxylic acid and its 2-substituted analogs as active inhibitors of urease. Molecular modeling and virtual screening were utilized to find out potential compounds. Computational techniques were employed at database of 90,000 ligands and selected the structure representing the low energy conformations, Grid and FlexX docking algorithms were used and the top binding ligands were synthesized and screened in wet-lab.