Biophysical and biochemical attributes of hybrid epithelial/mesenchymal phenotypes

The Epithelial-Mesenchymal Transition (EMT) is a biological phenomenon associated with explicit phenotypic and molecular changes in cellular traits. Unlike the earlier-held popular belief of it being a binary process, EMT is now thought of as a landscape including diverse hybrid E/M phenotypes manifested by varying degrees of the transition. These hybrid cells can co-express both epithelial and mesenchymal markers and/or functional traits, and can possess the property of collective cell migration, enhanced tumor-initiating ability, and immune/targeted therapy-evasive features, all of which are often associated with worse patient outcomes. These characteristics of the hybrid E/M cells have led to a surge in studies that map their biophysical and biochemical hallmarks that can be helpful in exploiting their therapeutic vulnerabilities. This review discusses recent advances made in investigating hybrid E/M phenotype(s) from diverse biophysical and biochemical aspects by integrating live cell-imaging, cellular morphology quantification and mathematical modelling, and highlights a set of questions that remain unanswered about the dynamics of hybrid E/M states.

Homosexuality and the Politics of LGBT Movements in Israel

Two processes have been central to the LGBT (lesbian, gay, transgender and bisexual) movement in politics since the end of the 1980’s: NGOization, which has led to the practice of assimilation, and homo-nationalism, representing a binary process of normalization and national inclusion. The amalgamation of NGOization and homonationalism have greatly influenced the movements, their agenda, practices, achievements and networks. The article sheds light on the broad neoliberal processes used by the Israeli LGBT movements to achieve power and status. The analysis traces major milestones from the 1980’s to the 21st century. Viewed through a neoliberal perspective, LGBT social movements are revealed to have worked and grown and become more institutionalized and normalized. However, this does not reflect the attainment of more power by the LGBT social movements in Israel; it is indicative rather of their privatization by the state which enables LGBT social movements to fill a niche under the government’s exclusive responsibility. Thus, in the 21st century, the value and valuation of LGBT subjects have been established not so much by the work of their social movements but through their economic and urban power reflective of ’post-homonationalism.

Biophysical and Biochemical Attributes of Hybrid Epithelial/Mesenchymal Phenotypes

The Epithelial- Mesenchymal Transition (EMT) is a biological phenomenon associated with explicit phenotypic and molecular changes in cellular traits. Unlike the earlier-held popular belief of it being a binary process, EMT is now thought of as a landscape including diverse hybrid E/M phenotypes manifested by varying degrees of the transition. These hybrid cells can co-express both epithelial and mesenchymal markers and/or functional traits, and can possess the property of collective cell migration, enhanced tumor-initiating ability, and immune/targeted therapy-evasive features, all of which are often associated with worse patient outcomes. These characteristics of the hybrid E/M cells have led to a surge in studies that map their biophysical and biochemical hallmarks that can be helpful in exploiting their therapeutic vulnerabilities. This review discusses recent advances made in investigating hybrid E/M phenotype(s) from diverse biophysical and biochemical aspects by integrating live cell-imaging, cellular morphology quantification and mathematical modeling, and highlights a set of questions that remain unanswered about the dynamics of hybrid E/M states.

Pengolahan Citra Digital Untuk Menghitung Ekstrasi Ciri Greenbean Kopi Robusta Dan Arabika (Studi Kasus: Kopi Temanggung)

This study aims to determine the extraction of features contained in robusta and arabica coffee greenbeans to make objects detectable and can be drawn into mathematical numbers. The method used is the original image which is converted to RGB and then grayscaling is carried out followed by a binary process that aims to change the image into binary form (0 and 1) after the digital image processing is complete the process of extracting the characteristics of greenbean coffee based on width, height, perimeter, surface area, roundness percentage, and perimeter of each coffee greenbean so that it can be understood mathematically. The results of the binary image process carried out morphological operations, the morphological process there is an erosion and dilation process. The results of the erosion and dilation process are carried out feature extraction to get the length, height, circumference, roundness ratio and perimeter of an image image. Then the value is stored in the database as a feature extraction of each greenbean coffee.The result of feature extraction obtained from coffee greenbean samples with a mean width of 7.7 pixels, height 11, circumference 31.3, surface area 69.5, roundness percentage 89,559, and perimeter 1,674 of greenbean robusta coffee while for arabica greenbean can be width 13.2 pixels, height 18.8, circumference 51.2, surface area 199.9, percentage of roundness 94.548, and perimeter 1.6000038 with total data taken were 20 greenbean coffees.

LambdaNet: A Fully Convolutional Architecture for Directional Change Detection

Change detection in image pairs has traditionally been a binary process, reporting either “Change” or “No Change.” In this paper, we present LambdaNet, a novel deep architecture for performing pixel-level directional change detection based on a four class classification scheme. LambdaNet successfully incorporates the notion of “directional change” and identifies differences between two images as “Additive Change” when a new object appears, “Subtractive Change” when an object is removed, “Exchange” when different objects are present in the same location, and “No Change.” To obtain pixel annotated change maps for training, we generated directional change class labels for the Change Detection 2014 dataset. Our tests illustrate that LambdaNet would be suitable for situations where the type of change is unstructured, such as change detection scenarios in satellite imagery.