Fractal Approach to the Study of Chromatin Texture

1998 ◽  
pp. 226-230 ◽  
Author(s):  
F. Sepulcre ◽  
J. Grau ◽  
M. García-Bonafé ◽  
A. Moragas
2000 ◽  
Vol 39 (02) ◽  
pp. 37-42 ◽  
Author(s):  
P. Hartikainen ◽  
J. T. Kuikka

Summary Aim: We demonstrate the heterogeneity of regional cerebral blood flow using a fractal approach and singlephoton emission computed tomography (SPECT). Method: Tc-99m-labelled ethylcysteine dimer was injected intravenously in 10 healthy controls and in 10 patients with dementia of frontal lobe type. The head was imaged with a gamma camera and transaxial, sagittal and coronal slices were reconstructed. Two hundred fifty-six symmetrical regions of interest (ROIs) were drawn onto each hemisphere of functioning brain matter. Fractal analysis was used to examine the spatial heterogeneity of blood flow as a function of the number of ROIs. Results: Relative dispersion (= coefficient of variation of the regional flows) was fractal-like in healthy subjects and could be characterized by a fractal dimension of 1.17 ± 0.05 (mean ± SD) for the left hemisphere and 1.15 ± 0.04 for the right hemisphere, respectively. The fractal dimension of 1.0 reflects completely homogeneous blood flow and 1.5 indicates a random blood flow distribution. Patients with dementia of frontal lobe type had a significantly lower fractal dimension of 1.04 ± 0.03 than in healthy controls. Conclusion: Within the limits of spatial resolution of SPECT, the heterogeneity of brain blood flow is well characterized by a fractal dimension. Fractal analysis may help brain scientists to assess age-, sex- and laterality-related anatomic and physiological changes of brain blood flow and possibly to improve precision of diagnostic information available for patient care.


2007 ◽  
Vol 30 (9-10) ◽  
pp. 1227-1249
Author(s):  
R. García‐Lopera ◽  
Juan E. Figueruelo ◽  
Iolanda Porcar ◽  
Agustín Campos ◽  
Concepción Abad
Keyword(s):  

2020 ◽  
Vol 12 (04) ◽  
pp. 271-275
Author(s):  
Jayaprakash Kubalady Shetty ◽  
Hannah Fathima Babu ◽  
Kishan Prasad Hosapatna Laxminarayana

Abstract Introduction Fixation is the critical step in the preservation of tissues in diagnostic pathology. The formalin is an economical and excellent fixative with the inherent property of adequate fixation. The well-established side effects of formalin include mucosal irritation, upper respiratory diseases, and corrosive injury to the gastrointestinal tract. In addition, substantial evidence exists regarding the potential role of formaldehyde as a human carcinogen. The carcinogenic and toxic effects of formalin encourage searching for alternative fixatives for tissue fixation. However, “the formalin dogma” has severely hampered the search for alternative fixatives for many years. Material and Methods Ninety tissues of liver and skeletal muscle obtained during autopsies were immersed in adequate amounts of the following fixatives: formalin (10%), methyl alcohol (70%), and acetone (100%). The comparison among the three was made based on time for fixation, preservation of tissue architecture, cell borders, cytoplasm, nuclear contours, chromatin texture, and uniformity of staining. Results The tissue preserved in formalin undergoes rapid fixation compared with alcohol and acetone. The tissue architecture, cell border characteristics of alcohol and acetone was found satisfactory compared with formalin. The cytoplasm and nuclear contour were superior with the formalin. The chromatin texture and uniformity of staining were similar with all the three fixatives. Conclusion The formalin is considered superior to most of the parameters, whereas both methyl alcohol and acetone showed nearly equivalent scores. Hence, owing to the potential human health hazards and carcinogenicity of formalin, no rational reasons hamper the complete substitution of formalin with alternative fixatives such as alcohol and acetone in diagnostic pathology and medical research.


2019 ◽  
Author(s):  
Paul W. J. Glover ◽  
Piroska Lorinczi ◽  
Saud Al-Zainaldin ◽  
Hassan Al-Ramadhan ◽  
Saddam Sinan ◽  
...  

2021 ◽  
Vol 13 (15) ◽  
pp. 8295
Author(s):  
Patricia Melin ◽  
Oscar Castillo

In this article, the evolution in both space and time of the COVID-19 pandemic is studied by utilizing a neural network with a self-organizing nature for the spatial analysis of data, and a fuzzy fractal method for capturing the temporal trends of the time series of the countries considered in this study. Self-organizing neural networks possess the capability to cluster countries in the space domain based on their similar characteristics, with respect to their COVID-19 cases. This form enables the finding of countries that have a similar behavior, and thus can benefit from utilizing the same methods in fighting the virus propagation. In order to validate the approach, publicly available datasets of COVID-19 cases worldwide have been used. In addition, a fuzzy fractal approach is utilized for the temporal analysis of the time series of the countries considered in this study. Then, a hybrid combination, using fuzzy rules, of both the self-organizing maps and the fuzzy fractal approach is proposed for efficient coronavirus disease 2019 (COVID-19) forecasting of the countries. Relevant conclusions have emerged from this study that may be of great help in putting forward the best possible strategies in fighting the virus pandemic. Many of the existing works concerned with COVID-19 look at the problem mostly from a temporal viewpoint, which is of course relevant, but we strongly believe that the combination of both aspects of the problem is relevant for improving the forecasting ability. The main idea of this article is combining neural networks with a self-organizing nature for clustering countries with a high similarity and the fuzzy fractal approach for being able to forecast the times series. Simulation results of COVID-19 data from countries around the world show the ability of the proposed approach to first spatially cluster the countries and then to accurately predict in time the COVID-19 data for different countries with a fuzzy fractal approach.


2018 ◽  
Vol 103 ◽  
pp. 128-137 ◽  
Author(s):  
Carmen Bujoreanu ◽  
Ştefan Irimiciuc ◽  
Marcelin Benchea ◽  
Florin Nedeff ◽  
Maricel Agop

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