Alquilação de tolueno com propeno, através de complexo ferro (II) ᵦ- diimina homogêneo e heterogeneizado em MCM-41, Al-MCM-41 e SBA-15

This work describes the synthesis and aplication of homogeneous and heterogenized iron catalysts in the alkylation reaction of toluene with propene, empolying experimental design. The homogenous complex was obtained trough the synthesis of the organic ligand folowed by the complexation of the iron(II) chloride. As to the heterogenized complexes, first were synthetized the inorganic supports (SBA-15, MCM-41 and Al-MCM-41). Then, it was synthetized the ligand again, that through funcionalization with chloropropyltrimethoxysilane (CPTMS), was anchored on the support previously calcinated. To these anchored ligands, was complexed the iron(II) chloride, previously solubilizated in tetrahydrofuran (THF). The organic ligand characterization was accomplished trough nuclear magnetic resonance (NMR) and Infrared spectroscopy (IV). The supports were characterized with x-ray diffraction (DRX), texture analysis with nitrogen adsorption/desorption (before and after the anchoring), termogravimetric analysis (TG) and infrared (IV). The metalic content was quantified trough the atomic absorption spectrophotometry (AAS). The complexes were tested in catalytic reactions emolying ethylaluminium sesquichloride (EASC) as co-catalyst in steel reactor, under mecanic stirring. The reaction conditions ranged from 4 to 36 ◦C, with many aluminum/iron ratios. The catalysts were actives in homogeneous and heterogenized ways. The homogenous catalytic complex showed a maximum turnover frequency (TOF) of 8.63 ×103 · h −1 , while, in some conditions, the anchored complexes showed better results, with TOF of until 8.08 ×103 · h −1 . Aditionally, it was possible to determine an equation, to the homogenous catalyst, that describes the product quantity in function of reacional temperature and aluminum/iron ratio.

Radiotherapy Treatment Assessment using DCE-MRI

Abstract

The goal of modern radiotherapy is to precisely deliver a prescribed radiation dose to delineated target volumes that contain a significant amount of tumor cells while sparing the surrounding healthy tissues/organs. Precise delineation of treatment and avoidance volumes is the key for the precision radiation therapy. In recent years, considerable clinical and research efforts have been devoted to integrate MRI into radiotherapy workflow motivated by the superior soft tissue contrast and functional imaging possibility. Dynamic contrast-enhanced MRI (DCE-MRI) is a noninvasive technique that measures properties of tissue microvasculature. Its sensitivity to radiation-induced vascular pharmacokinetic (PK) changes has been preliminary demonstrated. In spite of its great potential, two major challenges have limited DCE-MRI’s clinical application in radiotherapy assessment: the technical limitations of accurate DCE-MRI imaging implementation and the need of novel DCE-MRI data analysis methods for richer functional heterogeneity information.

This study aims at improving current DCE-MRI techniques and developing new DCE-MRI analysis methods for particular radiotherapy assessment. Thus, the study is naturally divided into two parts. The first part focuses on DCE-MRI temporal resolution as one of the key DCE-MRI technical factors, and some improvements regarding DCE-MRI temporal resolution are proposed; the second part explores the potential value of image heterogeneity analysis and multiple PK model combination for therapeutic response assessment, and several novel DCE-MRI data analysis methods are developed.

I. Improvement of DCE-MRI temporal resolution. First, the feasibility of improving DCE-MRI temporal resolution via image undersampling was studied. Specifically, a novel MR image iterative reconstruction algorithm was studied for DCE-MRI reconstruction. This algorithm was built on the recently developed compress sensing (CS) theory. By utilizing a limited k-space acquisition with shorter imaging time, images can be reconstructed in an iterative fashion under the regularization of a newly proposed total generalized variation (TGV) penalty term. In the retrospective study of brain radiosurgery patient DCE-MRI scans under IRB-approval, the clinically obtained image data was selected as reference data, and the simulated accelerated k-space acquisition was generated via undersampling the reference image full k-space with designed sampling grids. Two undersampling strategies were proposed: 1) a radial multi-ray grid with a special angular distribution was adopted to sample each slice of the full k-space; 2) a Cartesian random sampling grid series with spatiotemporal constraints from adjacent frames was adopted to sample the dynamic k-space series at a slice location. Two sets of PK parameters’ maps were generated from the undersampled data and from the fully-sampled data, respectively. Multiple quantitative measurements and statistical studies were performed to evaluate the accuracy of PK maps generated from the undersampled data in reference to the PK maps generated from the fully-sampled data. Results showed that at a simulated acceleration factor of four, PK maps could be faithfully calculated from the DCE images that were reconstructed using undersampled data, and no statistically significant differences were found between the regional PK mean values from undersampled and fully-sampled data sets. DCE-MRI acceleration using the investigated image reconstruction method has been suggested as feasible and promising.

Second, for high temporal resolution DCE-MRI, a new PK model fitting method was developed to solve PK parameters for better calculation accuracy and efficiency. This method is based on a derivative-based deformation of the commonly used Tofts PK model, which is presented as an integrative expression. This method also includes an advanced Kolmogorov-Zurbenko (KZ) filter to remove the potential noise effect in data and solve the PK parameter as a linear problem in matrix format. In the computer simulation study, PK parameters representing typical intracranial values were selected as references to simulated DCE-MRI data for different temporal resolution and different data noise level. Results showed that at both high temporal resolutions (<1s) and clinically feasible temporal resolution (~5s), this new method was able to calculate PK parameters more accurate than the current calculation methods at clinically relevant noise levels; at high temporal resolutions, the calculation efficiency of this new method was superior to current methods in an order of 102. In a retrospective of clinical brain DCE-MRI scans, the PK maps derived from the proposed method were comparable with the results from current methods. Based on these results, it can be concluded that this new method can be used for accurate and efficient PK model fitting for high temporal resolution DCE-MRI.

II. Development of DCE-MRI analysis methods for therapeutic response assessment. This part aims at methodology developments in two approaches. The first one is to develop model-free analysis method for DCE-MRI functional heterogeneity evaluation. This approach is inspired by the rationale that radiotherapy-induced functional change could be heterogeneous across the treatment area. The first effort was spent on a translational investigation of classic fractal dimension theory for DCE-MRI therapeutic response assessment. In a small-animal anti-angiogenesis drug therapy experiment, the randomly assigned treatment/control groups received multiple fraction treatments with one pre-treatment and multiple post-treatment high spatiotemporal DCE-MRI scans. In the post-treatment scan two weeks after the start, the investigated Rényi dimensions of the classic PK rate constant map demonstrated significant differences between the treatment and the control groups; when Rényi dimensions were adopted for treatment/control group classification, the achieved accuracy was higher than the accuracy from using conventional PK parameter statistics. Following this pilot work, two novel texture analysis methods were proposed. First, a new technique called Gray Level Local Power Matrix (GLLPM) was developed. It intends to solve the lack of temporal information and poor calculation efficiency of the commonly used Gray Level Co-Occurrence Matrix (GLCOM) techniques. In the same small animal experiment, the dynamic curves of Haralick texture features derived from the GLLPM had an overall better performance than the corresponding curves derived from current GLCOM techniques in treatment/control separation and classification. The second developed method is dynamic Fractal Signature Dissimilarity (FSD) analysis. Inspired by the classic fractal dimension theory, this method measures the dynamics of tumor heterogeneity during the contrast agent uptake in a quantitative fashion on DCE images. In the small animal experiment mentioned before, the selected parameters from dynamic FSD analysis showed significant differences between treatment/control groups as early as after 1 treatment fraction; in contrast, metrics from conventional PK analysis showed significant differences only after 3 treatment fractions. When using dynamic FSD parameters, the treatment/control group classification after 1st treatment fraction was improved than using conventional PK statistics. These results suggest the promising application of this novel method for capturing early therapeutic response.

The second approach of developing novel DCE-MRI methods is to combine PK information from multiple PK models. Currently, the classic Tofts model or its alternative version has been widely adopted for DCE-MRI analysis as a gold-standard approach for therapeutic response assessment. Previously, a shutter-speed (SS) model was proposed to incorporate transcytolemmal water exchange effect into contrast agent concentration quantification. In spite of richer biological assumption, its application in therapeutic response assessment is limited. It might be intriguing to combine the information from the SS model and from the classic Tofts model to explore potential new biological information for treatment assessment. The feasibility of this idea was investigated in the same small animal experiment. The SS model was compared against the Tofts model for therapeutic response assessment using PK parameter regional mean value comparison. Based on the modeled transcytolemmal water exchange rate, a biological subvolume was proposed and was automatically identified using histogram analysis. Within the biological subvolume, the PK rate constant derived from the SS model were proved to be superior to the one from Tofts model in treatment/control separation and classification. Furthermore, novel biomarkers were designed to integrate PK rate constants from these two models. When being evaluated in the biological subvolume, this biomarker was able to reflect significant treatment/control difference in both post-treatment evaluation. These results confirm the potential value of SS model as well as its combination with Tofts model for therapeutic response assessment.

In summary, this study addressed two problems of DCE-MRI application in radiotherapy assessment. In the first part, a method of accelerating DCE-MRI acquisition for better temporal resolution was investigated, and a novel PK model fitting algorithm was proposed for high temporal resolution DCE-MRI. In the second part, two model-free texture analysis methods and a multiple-model analysis method were developed for DCE-MRI therapeutic response assessment. The presented works could benefit the future DCE-MRI routine clinical application in radiotherapy assessment.

Effect of different thistle flower ecotypes as milk-clotting in Serra da Estrela cheese

Purpose – Thistle flower( Cynara cardunculus) aqueous extracts, as rich source of milk-clotting peptidases, have been widely used for cheeses marketed under the Registry of the Protected Designation of Origin, as it is the case of Serra da Estrela cheese, manufactured from raw ewes’ milk and without addition of any commercial starter culture. This paper aims at studying the influence of six different ecotypes of thistle flowers in cheese properties during the ripening and of final products. Design/methodology/approach – Cheeses were produced with different thistle flower extracts and then the clotting time, weight and colour of cheeses, as well as texture properties and sensorial characteristics, were evaluated. Findings – The clotting time varied from 47 to 66 min, and the weight loss along ripening varied between 32 and 40 per cent. There was some influence of thistle flower ecotype on the colour during ripening and in the final product. The results of texture analysis revealed significant differences between the thistle ecotypes: crust firmness varying from 2.4 to 5.6 N; inner firmness from 0.82 to 1.82 N; stickiness from 0.5 to 1.60 N; adhesiveness from 3.0 to 11.3 N.s; and Ecotype C was particularly distinguishable. Sensorial evaluation revealed differences among the cheeses, with Ecotype C receiving the highest score for global appreciation. Originality/value – The usage of different extracts of thistle flower to produce Serra da Estrela cheese with different properties is a novelty, and it allows the possibility of manipulating this parameter in the future so as to produce cheeses with specific characteristics, addressed to different consumer targets.

Bone Mass and Bone Quality Are Altered by Hypoactivity in the Chicken

International audience

Texture Image Analysis in Differentiating Malignant from Benign Adrenal Cortical Tumors in Children and Adults

Objective: To investigate the possible role of chromatin texture parameters, nuclear morphology, DNA ploidy and clinical functional status in discriminating benign from malignant adrenocortical tumors (ACT). Patients and Methods: Forty-eight cases of clinically benign (n=40) and clinically malignant (n=8) ACT with a minimum of 5-years` follow-up were evaluated for chromatin texture parameters (run length, standard deviation, configurable run length, valley, slope, peak and other 21 Markovian features that describe the distribution of the chromatin in the nucleus), nuclear morphology (nuclear area, nuclear perimeter, nuclear maximum and minumum diameter, nuclear shape), and DNA ploidy. Nuclear parameters were evaluated in Feulgen-stained 5 mu m paraffin-sections analyzed using a CAS 200 image analyzer. Results: Since ACTs present different biological features in children and adults, patients were divided into two groups: children (<= 15 years) and adults (>15 years). In the group of children DNA ploidy presented a marginal significance (p=0.05) in discriminating ACTs. None of the parameters discriminated between malignant and benign ACT in the adult group. Conclusion: ACTs are uncommon and definitive predictive criteria for malignancy remain uncertain, particularly in children. Our data point to DNA content evaluated by image analysis as a new candidate tool for this challenging task. Texture image analysis did not help to differentiate malignant from benign adrenal cortical tumors in children and adults.

Analysis of sensitivity with respect to a compositional parameter : A comment on 'Local sensitivity analysis for compositional data with application to soil texture in hydrologic modelling' by L. Loosvelt and co-authors

A comment about the article “Local sensitivity analysis for compositional data with application to soil texture in hydrologic modelling” writen by L. Loosvelt and co-authors. The present comment is centered in three specific points. The first one is related to the fact that the authors avoid the use of ilr-coordinates. The second one refers to some generalization of sensitivity analysis when input parameters are compositional. The third tries to show that the role of the Dirichlet distribution in the sensitivity analysis is irrelevant

Fractal analysis of leaf-texture properties as a tool for taxonomic and identification purposes: a case study with species from Neotropical Melastomataceae (Miconieae tribe)

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Estimate of concrete block texture using image analysis

The texture of concrete blocks is very important and is often the decisive factor when choosing a product, particularly if the building specifications call for high-strength blocks allied to low-cost finish, in which case exposed blocks with a closer texture are often preferred. Furthermore, a closer texture, especially for exteriors, may be a vital factor in ensuring the building's durability. At present, however, there is no standard to quantify the texture of a structural block. Further, when studying masonry blocks compressive strength should never be overlooked. This article discusses a procedure to produce concrete block textures with and without the addition of lime, but still to achieve the required compressive strength. The method used in this study, to evaluate texture, proved to be simpler and cheaper than methods reported by other authors in the literature. The addition of small quantities of lime proved beneficial for both texture and compressive strength. Increasing the amount of lime further, however, only improved texture.

Statistical analysis of texture in trunk images for biometric identification of tree species

The identification of tree species is a key step for sustainable management plans of forest resources, as well as for several other applications that are based on such surveys. However, the present available techniques are dependent on the presence of tree structures, such as flowers, fruits, and leaves, limiting the identification process to certain periods of the year Therefore, this article introduces a study on the application of statistical parameters for texture classification of tree trunk images. For that, 540 samples from five Brazilian native deciduous species were acquired and measures of entropy, uniformity, smoothness, asymmetry (third moment), mean, and standard deviation were obtained from the presented textures. Using a decision tree, a biometric species identification system was constructed and resulted to a 0.84 average precision rate for species classification with 0.83accuracy and 0.79 agreement. Thus, it can be considered that the use of texture presented in trunk images can represent an important advance in tree identification, since the limitations of the current techniques can be overcome.

Analysis of texture,

"COO-2118-0035."

Computer methods for analysis and synthesis of visual texture,

"C00-2118-0048."

The Impact of Carbonate Texture on the Quantification of Total Porosity by Image Analysis

Date of Acceptance: 31/08/2015 The authors would like to thank Total E&P and BG Group for project funding and support and the Industry Technology Facilitator for enabling the collaborative development (grant number 3322PSD). The authors would also like to thank Aberdeen Formation Evaluation Society and the College of Physical Sciences at the University of Aberdeen for partial financial support. Dougal Jerram, Raymi Castilla, Claude Gout, Frances Abbots and an anonymous reviewer are thanked for their constructive comments and suggestions to improve the standard of this manuscript. The authors would also like to express their gratitude toJohn Still and Colin Taylor for technical assistance in the laboratory and Nick Timms (Curtin University) and Angela Halfpenny (CSIRO) for their assistance with the full thin section scanning equipment.

The Impact of Carbonate Texture on the Quantification of Total Porosity by Image Analysis

Date of Acceptance: 31/08/2015 The authors would like to thank Total E&P and BG Group for project funding and support and the Industry Technology Facilitator for enabling the collaborative development (grant number 3322PSD). The authors would also like to thank Aberdeen Formation Evaluation Society and the College of Physical Sciences at the University of Aberdeen for partial financial support. Dougal Jerram, Raymi Castilla, Claude Gout, Frances Abbots and an anonymous reviewer are thanked for their constructive comments and suggestions to improve the standard of this manuscript. The authors would also like to express their gratitude toJohn Still and Colin Taylor for technical assistance in the laboratory and Nick Timms (Curtin University) and Angela Halfpenny (CSIRO) for their assistance with the full thin section scanning equipment.