Development of Techniques for the Automatic Extraction and Grade Detection of Glioma Tumors from Conventional Brain Magnetic Resonant Images

Cerebral glioma is the most prevalent primary brain tumor, which are classified broadly into low and high grades according to the degree of malignancy. High grade gliomas are highly malignant which possess a poor prognosis, and the patients survive less than eighteen months after diagnosis. Low grade gliomas are slow growing, least malignant and has better response to therapy. To date, histological grading is used as the standard technique for diagnosis, treatment planning and survival prediction. The main objective of this thesis is to propose novel methods for automatic extraction of low and high grade glioma and other brain tissues, grade detection techniques for glioma using conventional magnetic resonance imaging (MRI) modalities and 3D modelling of glioma from segmented tumor slices in order to assess the growth rate of tumors. Two new methods are developed for extracting tumor regions, of which the second method, named as Adaptive Gray level Algebraic set Segmentation Algorithm (AGASA) can also extract white matter and grey matter from T1 FLAIR an T2 weighted images. The methods were validated with manual Ground truth images, which showed promising results. The developed methods were compared with widely used Fuzzy c-means clustering technique and the robustness of the algorithm with respect to noise is also checked for different noise levels. Image texture can provide significant information on the (ab)normality of tissue, and this thesis expands this idea to tumour texture grading and detection. Based on the thresholds of discriminant first order and gray level cooccurrence matrix based second order statistical features three feature sets were formulated and a decision system was developed for grade detection of glioma from conventional T2 weighted MRI modality.The quantitative performance analysis using ROC curve showed 99.03% accuracy for distinguishing between advanced (aggressive) and early stage (non-aggressive) malignant glioma. The developed brain texture analysis techniques can improve the physician’s ability to detect and analyse pathologies leading to a more reliable diagnosis and treatment of disease. The segmented tumors were also used for volumetric modelling of tumors which can provide an idea of the growth rate of tumor; this can be used for assessing response to therapy and patient prognosis.

The electronic structure of anionic halide complexes of element 105 in aqueous solutions and their extraction by aliphatic amines

To study the complex formation of group 5 elements (Nb, Ta, Ha, and pseudoanalog Pa) in aqueous HCI solutions of medium and high concentrations the electronic structures of anionic complexes of these elements [MCl_6]^-, [MOCl_4]^-, [M(OH)-2 Cl_4]^-, and [MOCl_5]^2- have been calculated using the relativistic Dirac-Slater Discrete-Variational Method. The charge density distribution analysis has shown that tantalum occupies a specific position in the group and has the highest tendency to form the pure halide complex, [TaCl_6-. This fact along with a high covalency of this complex explains its good extractability into aliphatic amines. Niobium has equal trends to form pure halide [NbCl_6]^- and oxyhalide [NbOCl_5]^2- species at medium and high acid concentrations. Protactinium has a slight preference for the [PaOCl_5]^2- form or for the pure halide complexes with coordination number higher than 6 under these conditions. Element 105 at high HCl concentrations will have a preference to form oxyhalide anionic complex [HaOCl_5]^2- rather than [HaCl_6]^-. For the same sort of anionic oxychloride complexes an estimate has been done of their partition between the organic and aqueous phases in the extraction by aliphatic amines, which shows the following succession of the partition coefficients: P_Nb < P_Ha < P_Pa.

Catalase in fluvial biofilms: a comparison between different extraction methods and example of application in a metal-polluted river

Antioxidant enzymes are involved in important processes of cell detoxification during oxidative stress and have, therefore, been used as biomarkers in algae. Nevertheless, their limited use in fluvial biofilms may be due to the complexity of such communities. Here, a comparison between different extraction methods was performed to obtain a reliable method for catalase extraction from fluvial biofilms. Homogenization followed by glass bead disruption appeared to be the best compromise for catalase extraction. This method was then applied to a field study in a metal-polluted stream (Riou Mort, France). The most polluted sites were characterized by a catalase activity 4–6 times lower than in the low-polluted site. Results of the comparison process and its application are promising for the use of catalase activity as an early warning biomarker of toxicity using biofilms in the laboratory and in the field

Shifts in rhizosphere microbial communities and enzyme activity of Poa alpina across an alpine chronosequence

This study quantifies the influence of Poa alpina on the soil microbial community in primary succession of alpine ecosystems, and whether these effects are controlled by the successional stage. Four successional sites representative of four stages of grassland development (initial, 4 years (non-vegetated); pioneer, 20 years; transition, 75 years; mature, 9500 years old) on the Rotmoos glacier foreland, Austria, were sampled. The size, composition and activity of the microbial community in the rhizosphere and bulk soil were characterized using the chloroform-fumigation extraction procedure, phospholipid fatty acid (PLFA) analysis and measurements of the enzymes beta-glucosidase, beta-xylosidase, N-acetyl-beta-glucosaminidase, leucine aminopeptidase, acid phosphatase and sulfatase. The interplay between the host plant and the successional stage was quantified using principal component (PCA) and multidimensional scaling analyses. Correlation analyses were applied to evaluate the relationship between soil factors (C-org, N-t, C/N ratio, pH, ammonium, phosphorus, potassium) and microbial properties in the bulk soil. In the pioneer stage microbial colonization of the rhizosphere of P. alpina was dependent on the reservoir of microbial species in the bulk soil. As a consequence, the rhizosphere and bulk soil were similar in microbial biomass (ninhydrin-reactive nitrogen (NHR-N)), community composition (PLFA), and enzyme activity. In the transition and mature grassland stage, more benign soil conditions stimulated microbial growth (NHR-N, total amount of PLFA, bacterial PLFA, Gram-positive bacteria, Gram-negative bacteria), and microbial diversity (Shannon index H) in the rhizosphere either directly or indirectly through enhanced carbon allocation. In the same period, the rhizosphere microflora shifted from a G(-) to a more G(+), and from a fungal to a more bacteria-dominated community. Rhizosphere beta-xylosidase, N-acetyl-beta-glucosaminidase, and sulfatase activity peaked in the mature grassland soil, whereas rhizosphere leucine aminopeptidase, beta-glucosidase, and phosphatase activity were highest in the transition stage, probably because of enhanced carbon and nutrient allocation into the rhizosphere due to better growth conditions. Soil organic matter appeared to be the most important driver of microbial colonization in the bulk soil. The decrease in soil pH and soil C/N ratio mediated the shifts in the soil microbial community composition (bacPLFA, bacPLFA/fungPLFA, G(-), G(+)/G(-)). The activities of beta-glucosidase, beta-xylosidase and phosphatase were related to soil ammonium and phosphorus, indicating that higher decomposition rates enhanced the nutrient availability in the bulk soil. We conclude that the major determinants of the microllora vary along the successional gradient: in the pioneer stage the rhizosphere microflora was primarily determined by the harsh soil environment; under more favourable environmental conditions, however, the host plant selected for a specific microbial community that was related to the dynamic interplay between soil properties and carbon supply. (C) 2004 Elsevier Ltd. All rights reserved.

Sequential extraction and single-step cold-acid extraction: A feasibility study for use with freshwater-canal sediments

This investigation examines metal release from freshwater sediment using sequential extraction and single-step cold-acid leaching. The concentrations of Cd, Cr, Cu, Fe, Ni, Pb and Zn released using a standard 3-step sequential extraction (Rauret et al., 1999) are compared to those released using a 0.5 M HCl; leach. The results show that the three sediments behave in very different ways when subject to the same leaching experiments: the cold-acid extraction appears to remove higher relative concentrations of metals from the iron-rich sediment than from the other two sediments. Cold-acid extraction appears to be more effective at removing metals from sediments with crystalline iron oxides than the "reducible" step of the sequential extraction. The results show that a single-step acid leach can be just as effective as sequential extractions at removing metals from sediment and are a great deal less time-consuming.

Comparison of ammonium lactate, sodium bicarbonate and double calcium lactate methods for extraction of phosphorus from wetland peat soils

Procedures for routine analysis of soil phosphorus (P) have been used for assessment of P status, distribution and P losses from cultivated mineral soils. No similar studies have been carried out on wetland peat soils. The objective was to compare extraction efficiency of ammonium lactate (PAL), sodium bicarbonate (P-Olsen), and double calcium lactate (P-DCaL) and P distribution in the soil profile of wetland peat soils. For this purpose, 34 samples of the 0-30, 30-60 and 60-90 cm layers were collected from peat soils in Germany, Israel, Poland, Slovenia, Sweden and the United Kingdom and analysed for P. Mean soil pH (CaCl2, 0.01 M) was 5.84, 5.51 and 5.47 in the 0-30, 30-60 and 60-90 cm layers, respectively. The P-DCaL was consistently about half the magnitude of either P-AL or P-Olsen. The efficiency of P extraction increased in the order P-DCaL < P-AL &LE; P-Olsen, with corresponding means (mg kg(-1)) for all soils (34 samples) of 15.32, 33.49 and 34.27 in 0-30 cm; 8.87, 17.30 and 21.46 in 30-60 cm; and 5.69, 14.00 and 21.40 in 60-90 cm. The means decreased with depth. When examining soils for each country separately, P-Olsen was relatively evenly distributed in the German, UK and Slovenian soils. P-Olsen was linearly correlated (r = 0.594, P = 0.0002) with pH, whereas the three P tests (except P-Olsen vs P-DCaL) significantly correlated with each other (P = 0.017850.0001). The strongest correlation (r = 0.617, P = 0.0001) was recorded for P-AL vs P-DCaL) and the two methods were inter-convertible using a regression equation: P-AL = -22.593 + 5.353 pH + 1.423 P-DCaL, R-2 = 0.550.

Shifts in rhizosphere microbial communities and enzyme activity of Poa alpina across an alpine chronosequence

This study quantifies the influence of Poa alpina on the soil microbial community in primary succession of alpine ecosystems, and whether these effects are controlled by the successional stage. Four successional sites representative of four stages of grassland development (initial, 4 years (non-vegetated); pioneer, 20 years; transition, 75 years; mature, 9500 years old) on the Rotmoos glacier foreland, Austria, were sampled. The size, composition and activity of the microbial community in the rhizosphere and bulk soil were characterized using the chloroform-fumigation extraction procedure, phospholipid fatty acid (PLFA) analysis and measurements of the enzymes beta-glucosidase, beta-xylosidase, N-acetyl-beta-glucosaminidase, leucine aminopeptidase, acid phosphatase and sulfatase. The interplay between the host plant and the successional stage was quantified using principal component (PCA) and multidimensional scaling analyses. Correlation analyses were applied to evaluate the relationship between soil factors (C-org, N-t, C/N ratio, pH, ammonium, phosphorus, potassium) and microbial properties in the bulk soil. In the pioneer stage microbial colonization of the rhizosphere of P. alpina was dependent on the reservoir of microbial species in the bulk soil. As a consequence, the rhizosphere and bulk soil were similar in microbial biomass (ninhydrin-reactive nitrogen (NHR-N)), community composition (PLFA), and enzyme activity. In the transition and mature grassland stage, more benign soil conditions stimulated microbial growth (NHR-N, total amount of PLFA, bacterial PLFA, Gram-positive bacteria, Gram-negative bacteria), and microbial diversity (Shannon index H) in the rhizosphere either directly or indirectly through enhanced carbon allocation. In the same period, the rhizosphere microflora shifted from a G(-) to a more G(+), and from a fungal to a more bacteria-dominated community. Rhizosphere beta-xylosidase, N-acetyl-beta-glucosaminidase, and sulfatase activity peaked in the mature grassland soil, whereas rhizosphere leucine aminopeptidase, beta-glucosidase, and phosphatase activity were highest in the transition stage, probably because of enhanced carbon and nutrient allocation into the rhizosphere due to better growth conditions. Soil organic matter appeared to be the most important driver of microbial colonization in the bulk soil. The decrease in soil pH and soil C/N ratio mediated the shifts in the soil microbial community composition (bacPLFA, bacPLFA/fungPLFA, G(-), G(+)/G(-)). The activities of beta-glucosidase, beta-xylosidase and phosphatase were related to soil ammonium and phosphorus, indicating that higher decomposition rates enhanced the nutrient availability in the bulk soil. We conclude that the major determinants of the microllora vary along the successional gradient: in the pioneer stage the rhizosphere microflora was primarily determined by the harsh soil environment; under more favourable environmental conditions, however, the host plant selected for a specific microbial community that was related to the dynamic interplay between soil properties and carbon supply. (C) 2004 Elsevier Ltd. All rights reserved.