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The Twentieth Century and Beyond
Published in Scott M. Jackson, Skin Disease and the History of Dermatology, 2023
All these varied ways of arranging skin diseases lead one to the following two conclusions: dermatology is a highly challenging field, and there was no clear winner among Willan, Alibert, Bazin, Hebra, and the others as to how to properly arrange skin diseases. Perhaps they are all winners, as our current system is a hodgepodge of all of these arrangements. Our current system evolved during the twentieth century and cannot be attributed to any one person or persons. In many ways, it resulted from a simple impetus: the need to arrange information in textbooks. Finally, it should be pointed out that a specific classification of skin diseases is not overly useful for dermatologists, practically speaking. More important than classification is the formation of a different diagnosis that is morphology-driven, and even more helpful, diagnosis-driven, as the present author's work with this topic has shown.13
Streptomyces: A Potential Source of Natural Antimicrobial Drug Leads
Published in Mahendra Rai, Chistiane M. Feitosa, Eco-Friendly Biobased Products Used in Microbial Diseases, 2022
Mahmoud A. Elfaky, Hanaa Nasr, Ilham Touiss, Mohamed L. Ashour
Antibiotic production on a large scale is often done in liquid cultures. The macroscopic morphology of the mycelium is almost universally recognized as being linked to the development of secondary metabolites. Differentiation and secondary metabolism followed the development of pellets and clumps. As a result, new methods for observing macroscopic morphology have been established. Pellet size was measured using laser diffraction. The pellet size distribution of culture populations was determined using flow cytometry. A useful algorithm for characterizing the morphology of filamentous microorganisms in liquid cultures was recently created as a plug-in for the open-source program ImageJ. The activity of Streptomyces liquid cultures has been predicted using mathematical models focused on pellet/clump morphology (Manteca and Yagüe 2018).
Methods of Evaluation in Orthopaedic Animal Research
Published in Yuehuei H. An, Richard J. Friedman, Animal Models in Orthopaedic Research, 2020
Histologic evaluations of bone, cartilage, ligament, tendon, synovium, and other soft tissues have been used extensively in orthopaedic research (see Chapter 7). Observation and characterization are normally done under a light microscope. Descriptive histology and histomorphometry are the two main types of histological study. Depending on the particular situation, either or both may be used. Descriptive histology is used to give a general picture of the tissue of interest, including the morphology, structure, and arrangement of cells or matrix. Scoring systems are often designed in order to semi-quantify the components of interest. An example of this is the estimation of quantity of new bone formation in a bone defect (Table 3 in Chapter 13). Full bone formation in a defect is scored as 3, moderate bone formation as 2, mild bone formation as 1, and no new bone formation as 0. The data is analyzed using non-parametric analysis of variance. Examples of other such scoring systems can be found in the appropriate chapters. Systems have been developed for evaluation of fracture healing (Table 5 in Chapter 11), bone defect repair (Table 5 in Chapter 13), cartilage defect repair (Table 3 in Chapter 16), and biocompatibility of soft tissue implants (Table 1 in Chapter 20).
Critical assessment of AI in drug discovery
Published in Expert Opinion on Drug Discovery, 2021
W. Patrick Walters, Regina Barzilay
In order to apply machine learning to images, one must first transform the image into a suitable representation. The first generation of image-based approaches aims to extract pertinent cellular features. These features were found informative by scientists who analyzed changes in cell morphology upon treatment with drug molecules. Machines can be trained to automate their extraction from images, thereby increasing experimental throughput and reducing bias inherent in human visual Inspection. Modern computational approaches can also operate at a much higher resolution than human interpretation. The Cell Profiler package [87,88], developed by the Carpenter group at the Broad Institute, is capable of identifying more than 700 distinct cellular features. These features can be transformed into a vector that is subsequently used as input for machine learning.
An automated image analysis platform for the study of weakly -adhered cells
Published in Biofouling, 2021
Zhijing Wan, Ben T. MacVicar, Shea Wyatt, Diana E. Varela, Rajkumar Padmawar, Dennis K. Hore
A morphological closing operation can be used after the Canny edge detection to ensure that the borders of all cells are as complete as possible (Soille 2004). Once the routine has smoothed out the noise and found the potential edges, the algorithm takes those edges and uses non-maximum suppression to find the pixels that have the sharpest gradient so that the edges become thin. This process removes all pixels which may not be part of an edge (Canny 1986). Finally, a hysteresis thresholding is performed. All pixels over a certain value (100 in the example) are considered to be edges and all pixels less than a lower threshold value (75) are rejected. Pixel values inside that range are classified by connectivity, i.e. they are determined to be edges if they are adjacent to a pixel that has been classified as an edge. The Canny parameters that control the degree of hysteresis are useful to adjust to modulate the thresholding when dealing with low contrast situations in which the cells are difficult to separate from the background. Mathematical morphology is a field that deals with the processing and analysis of geometric structures. In the case of images, these structures are formed on an integer grid. To form the grid, a structuring element which helps define the operation is used. For this report, the structuring element is a five-by-five square which is denoted by
Biological investigations on therapeutic effect of chitosan encapsulated nano resveratrol against gestational diabetes mellitus rats induced by streptozotocin
Published in Drug Delivery, 2020
Shengye Du, Yan Lv, Na Li, Xianxia Huang, Xuemei Liu, Hui Li, Chao Wang, Yi-Fang Jia
The synthesized nanoparticles were encapsulated with chitosan molecules through ion gelation method (Calvo et al., 1997). The chitosan molecules own positive electric charges due to the existence of the amine group (NH2) which will be protonated as NH3+. Also, the presence of amine and hydroxyl groups provides the ability to the formation of zinc metal complexes. The morphology characters such as size, shape, and surface morphology were examined by electron microscopic techniques. Mostly, the particles are monodispersed, spherical, and exist without any aggregation (Figure 1(A–C)). CS–ZnO–RS showed an average particle size at 38 nm (Figure 1(D)). The zeta potential of CS–ZnO–RS was 39.1 mV, which is displayed in Figure 1(E). The positive charges of CS–ZnO–RS cooperated that the amino groups of chitosan occurred in the surface of nanocomposite and greater than 25.0 mV which revealed that the nanoparticle suspensions were stable and not easy to aggregate (Jeong et al., 2016). The result of DSC is presented in Figure 2(A). Initially, the CS–ZnO–RS was decomposed with temperature. While increasing the temperature (150 °C), it was enhanced and completed at ∼257 °C. Furthermore, the DSC curves show a corresponding peak for ZnO at 257 °C.