Ultrastructure expansion microscopy in Trypanosoma brucei

The recently developed ultrastructure expansion microscopy (U-ExM) technique allows us to increase the spatial resolution within a cell or tissue for microscopic imaging through the physical expansion of the sample. In this study, we validate the use of U-ExM in Trypanosoma brucei measuring the expansion factors of several different compartments/organelles and thus verify the isotropic expansion of the cell. We furthermore demonstrate the use of this sample preparation protocol for future studies by visualizing the nucleus and kDNA, as well as proteins of the cytoskeleton, the basal body, the mitochondrion and the endoplasmic reticulum. Lastly, we discuss the challenges and opportunities of U-ExM.

Evaluation of Physical, Spatial and Demographic Expansions in Ilam City from 1956 to 2016

The physical and spatial expansion of cities, which often taken place without planning, caused numerous environmental, health, economic and social problems. This study investigates the physical, spatial, and demographic development and expansion of Ilam city in Iran for over 60 years. To achieve these goals, library studies, data analysis, and field studies were applied. The process of development in Ilam and its demographic changes from 1956 to 2016 has been presented, and then, the spatial-physical expansion of the city is evaluated. The results showed that several factors had impacted the physical development and expansion of Ilam. The highest growth was observed between 1976 and 1986. Also, the development of the city has been more horizontal. The study results show the correlation, intensity, extension, and mechanism of conversion and land-use change in Ilam city and embody its spatial-physical expansion.

Age, size and body condition do not equally reflect population response to habitat change in the common spadefoot toad Pelobates fuscus

Urbanization impacts biodiversity both directly through physical expansion over land, and indirectly due to land use conversion and human behaviors associated with urban areas. We assessed the response of a common spadefoot toad population (Pelobates fuscus) to habitat loss and fragmentation resulting from urban development by studying changes in size, body condition and age parameters. We compared samples collected in the early 2000s (sample A) and later on during 2012–2014 (sample B). The terrestrial habitats in the study area were severely reduced and fragmented due to the expansion of the human settlement. We found no significant differences in the age parameters between the two sampling periods; the median lifespan shortened from 3.5 (sample A) to 3.0 years (sample B), while the other age parameters were similar in both samples. In contrast, snout-vent length, body mass and body condition experienced a significant decrease over time. Our results suggest that changes in body size and body condition, rather than age parameters, better reflect the response of the common spadefoot toad population to declining habitat quality. Therefore, body measurements can provide reliable estimates of the impact of habitat degradation in amphibian populations.

Analysis of Physical Expansion Training Based on Edge Computing and Artificial Intelligence

The effective development of physical expansion training benefits from the rapid development of computer technology, especially the integration of Edge Computing (EC) and Artificial Intelligence (AI) technology. Physical expansion training is mainly based on the collective form, and how to improve the quality of training to achieve results has become the content of everyone’s attention. As a representative technology in the field of AI, deep learning and EC evolving from traditional cloud computing technology are all well applied to physical expansion training. Traditional EC methods have problems such as high computing cost and long computing time. In this paper, deep learning technology is introduced to optimize EC methods. The EC cycle is set through the Internet of Things (IoT) topology to obtain the data upload speed. The CNN (Convolutional Neural Network) model introduces deep reinforcement learning technology, implements convolution calculations, and completes the resource allocation of EC for each trainer’s wearable sensor device, which realizes the optimization of EC based on deep reinforcement learning. The experiment results show that the proposed method can effectively control the server’s occupancy time, the energy cost of the edge server, and the computing cost. The proposed method in this paper can also improve the resource allocation ability of EC, ensure the uniform speed of the computing process, and improve the efficiency of EC.

Ultrastructure Expansion Microscopy inTrypanosoma brucei

Abstract-IntroductionThe recently developed ultrastructure expansion microscopy (U-ExM) technique allows to increase the spatial resolution within a cell or tissue for microscopic imaging through the physical expansion of the sample. In this study we validate the use of U-ExM inTrypanosoma bruceiby visualizing the nucleus and kDNA as well as proteins of the cytoskeleton, the basal body, the mitochondrion and the ER.T. bruceiis a unicellular flagellated protozoan parasite and the causative agent of human African sleeping sickness and Nagana in cattle.The highly polarized parasite cell body is about 25 μm in length and is shaped by the subpellicular microtubule corset. Its single flagellum emanates from the posterior part of the cell and is attached along the entire cell body.T. bruceiThe cell contains all typical organelles of eukaryotic cells including ER, Golgi and mitochondrion. Interestingly, Golgi and mitochondrion are single unit organelles in this protozoan parasite. The signature feature of trypanosomes is the single unit mitochondrial genome, the kinetoplast DNA (kDNA) that is organized in a complex structure of interlocked mini- and maxicircles. The kDNA is segregated during cell division by the tripartite attachment complex (TAC) that connects it via the mitochondrial membranes to the base of the flagellum.

A New Integrated Approach for Municipal Landfill Siting Based on Urban Physical Growth Prediction: A Case Study Mashhad Metropolis in Iran

Due to irregular and uncontrolled expansion of cities in developing countries, currently operational landfill sites cannot be used in the long-term, as people will be living in proximity to these sites and be exposed to unhygienic circumstances. Hence, this study aims at proposing an integrated approach for determining suitable locations for landfills while considering their physical expansion. The proposed approach utilizes the fuzzy analytical hierarchy process (FAHP) to weigh the sets of identified landfill location criteria. Furthermore, the weighted linear combination (WLC) approach was applied for the elicitation of the proper primary locations. Finally, the support vector machine (SVM) and cellular automation-based Markov chain method were used to predict urban growth. To demonstrate the applicability of the developed approach, it was applied to a case study, namely the city of Mashhad in Iran, where suitable sites for landfills were identified considering the urban growth in different geographical directions for this city by 2048. The proposed approach could be of use for policymakers, urban planners, and other decision-makers to minimize uncertainty arising from long-term resource allocation.

Microwave Foaming of Materials: An Emerging Field

In the last two decades, the application of microwave heating to the processing of materials has to become increasingly widespread. Microwave-assisted foaming processes show promise for industrial commercialization due to the potential advantages that microwaves have shown compared to conventional methods. These include reducing process time, improved energy efficiency, solvent-free foaming, reduced processing steps, and improved product quality. However, the interaction of microwave energy with foaming materials, the effects of critical processing factors on microwave foaming behavior, and the foamed product’s final properties are still not well-explored. This article reviews the mechanism and principles of microwave foaming of different materials. The article critically evaluates the impact of influential foaming parameters such as blowing agent, viscosity, precursor properties, microwave conditions, additives, and filler on the interaction of microwave, foaming material, physical (expansion, cellular structure, and density), mechanical, and thermal properties of the resultant foamed product. Finally, the key challenges and opportunities for developing industrial microwave foaming processes are identified, and areas for potential future research works are highlighted.

Polo-like kinase 1 independently controls microtubule-nucleating capacity and size of the centrosome

SUMMARYCentrosomes are composed of a centriolar core surrounded by a pericentriolar material (PCM) matrix that docks microtubule-nucleating γ-tubulin complexes. During mitotic entry, the PCM matrix increases in size and nucleating capacity in a process called centrosome maturation. Polo-like kinase 1 (PLK1) localizes to centrosomes and phosphorylates PCM matrix proteins to drive their self-assembly, which leads to PCM expansion; this expansion has been assumed to passively increase microtubule nucleation to support spindle assembly. Here, we show that PLK1 directly controls the generation of binding sites for γ-tubulin complexes on the PCM matrix, independently of PCM expansion. Selective inhibition of PLK1-dependent γ-tubulin docking leads to spindle defects and impaired chromosome segregation, without affecting PCM expansion, highlighting the importance of phospho-regulated centrosomal γ-tubulin docking sites in spindle assembly. Inhibiting both γ-tubulin docking and PCM expansion by mutating substrate target sites fully accounts for the actions of PLK-1 in transforming the centrosome during mitotic entry.Summary StatementPolo-like kinase 1-mediated physical expansion of centrosomes during mitotic entry is proposed to passively increase their microtubule nucleating capacity. Ohta et al. show instead that generation of microtubule-nucleating sites is directly controlled by Polo-like kinase 1, independently of centrosome size.