Activation of Actuating Hydrogels with WS2 Nanosheets for Biomimetic Cellular Structures and Steerable Prompt Deformation

In the 1940's and 1950's electron microscopy conferences were attended with everybody interested in learning about the latest technical developments for one very obvious reason. There was the electron microscope with its outstanding performance but nobody could make very much use of it because we were lacking proper techniques to prepare biological specimens. The development of the thin sectioning technique with its perfectioning in 1952 changed the situation and systematic analysis of the structure of cells could now be pursued. Since then electron microscopists have in general become satisfied with the level of resolution at which cellular structures can be analyzed when applying this technique. There has been little interest in trying to push the limit of resolution closer to that determined by the resolving power of the electron microscope.

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Some aspects of the defect structure in an austenitic stainless steel

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100108714 ◽

1978 ◽

Vol 36 (1) ◽

pp. 314-315

Author(s):

R. Gonzalez ◽

L. Bru

Keyword(s):

Stainless Steel ◽

Austenitic Stainless Steel ◽

Cellular Structures ◽

Total Strain Amplitude ◽

Total Deformation ◽

Density Of Dislocations ◽

Planar Arrays ◽

Stacking Fault Tetrahedra ◽

Distribution Of Dislocations ◽

Very High

The analysis of stacking fault tetrahedra (SFT) in fatigued metals (1,2) is somewhat complicated, due partly to their relatively low density, but principally to the presence of a very high density of dislocations which hides them. In order to overcome this second difficulty, we have used in this work an austenitic stainless steel that deforms in a planar mode and, as expected, examination of the substructure revealed planar arrays of dislocation dipoles rather than the cellular structures which appear both in single and polycrystals of cyclically deformed copper and silver. This more uniform distribution of dislocations allows a better identification of the SFT.The samples were fatigue deformed at the constant total strain amplitude Δε = 0.025 for 5 cycles at three temperatures: 85, 293 and 773 K. One of the samples was tensile strained with a total deformation of 3.5%.

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Topologiacl Models of 2D Fractal Cellular Structures

Journal de Physique I ◽

10.1051/jp1:1995207 ◽

1995 ◽

Vol 5 (11) ◽

pp. 1417-1429 ◽

Cited By ~ 12

Author(s):

G. Le Caër ◽

R. Delannay

Keyword(s):

Cellular Structures

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Topological properties of cellular structures based on the staggered packing of prisms

Journal de Physique ◽

10.1051/jphys:01989005007072500 ◽

1989 ◽

Vol 50 (7) ◽

pp. 725-731 ◽

Cited By ~ 8

Author(s):

M. A. Fortes

Keyword(s):

Cellular Structures ◽

Topological Properties

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PERMEABILITY OF CELLS AND ITS IMPORTANCE IN ASSESSMENT OF FISHES AGE

Vestnik of the Russian agricultural science ◽

10.30850/vrsn/2019/1/70-73 ◽

1970 ◽

pp. 70-73

Author(s):

N. I. Maslova

Keyword(s):

Cholesterol Content ◽

The Body ◽

Cellular Structures ◽

Ratio Estimation ◽

Carbohydrate Diet ◽

Spawning Period ◽

Age Related ◽

Experimental Base ◽

Cellular Permeability ◽

Membrane Strength

The article presents analysis of material and results of their own studies on changes in the permeability of cellular structures, organs and tissues in carp, which is of great importance in determining age-related indicators. The cells permeability in liver and gonads estimation was carried out under the experimental base of VNIIR on two carp genotypes during the pre-spawning period. The carp groups taken for analysis differed significantly in their genotypes. In females of the Khrapunov group the fecundity was 2023.0 thousand units, while the number of oocytes filled with yolk was only 0.7%, in the Ostashevsky ones - 1370.0 thousand units and 8.6%, respectively. During estimation the chemical composition of the generative tissue in females and males it was established that the cholesterol and lecithin content in males is higher than that of females, while feeding dependence is observed, especially on the amount of protein in the diet. For example, in females on protein diet contained less glycogen in gonads than on females on carbohydrate diet. Lecithin and cholesterol are higher in males than in females, which corresponds to increasing the Gyurdy Ratio (estimation of cell membrane strength). In spermatogenesis the content of phospholipids and cholesterol in the liver was decreased less than during ovogenesis. This indicates a lower level of synthetic processes in the milts compared with the ovaries. The cholesterol content in sperm is higher than in caviar in 19.6 times, and phospholipids almost doubled. With increasing age, the Gyordy Ratio for caviar decreases, for sperm it increases, the percentage of caviar fertilization increases. As the body age metabolism deteriorates, cellular permeability decreases (the ratio of lecithin and cholesterol changes significantly). At the same time, the permeability of cells in different organs and tissues varies and depends on living conditions, especially feeding and to some extent on the origin. In fish the gross productivity decreases as growth slows down and more energy is spent on adaptation to environmental conditions.

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Direct Metal Laser Sintering Strategies for Fabrication of Finer Resolution Cellular Structures

SSRN Electronic Journal ◽

10.2139/ssrn.3622647 ◽

2020 ◽

Author(s):

Fatemeh Hejripour ◽

Muhammad Abdus Salam ◽

Gary L. Bowlin ◽

Ebrahim Asadi

Keyword(s):

Laser Sintering ◽

Cellular Structures ◽

Direct Metal Laser Sintering

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Synergistic effects of SnO2 and Au nanoparticles decorated on WS2 nanosheets for flexible, room-temperature CO gas sensing

Sensors and Actuators B Chemical ◽

10.1016/j.snb.2021.129493 ◽

2021 ◽

Vol 332 ◽

pp. 129493

Author(s):

Jae-Hun Kim ◽

Jin-Young Kim ◽

Ali Mirzaei ◽

Hyoun Woo Kim ◽

Sang Sub Kim

Keyword(s):

Room Temperature ◽

Au Nanoparticles ◽

Gas Sensing ◽

Synergistic Effects ◽

Ws2 Nanosheets ◽

Co Gas

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Blinking statistics and molecular counting in direct stochastic reconstruction microscopy (dSTORM)

Bioinformatics ◽

10.1093/bioinformatics/btab136 ◽

2021 ◽

Author(s):

Lekha Patel ◽

David Williamson ◽

Dylan M Owen ◽

Edward A K Cohen

Keyword(s):

Probability Distribution ◽

Single Molecule ◽

Immunological Synapse ◽

Training Data ◽

Supplementary Information ◽

Cellular Structures ◽

Exact Probability ◽

Stochastic Optical Reconstruction Microscopy ◽

Exact Probability Distribution ◽

Optical Reconstruction

Abstract Motivation Many recent advancements in single-molecule localization microscopy exploit the stochastic photoswitching of fluorophores to reveal complex cellular structures beyond the classical diffraction limit. However, this same stochasticity makes counting the number of molecules to high precision extremely challenging, preventing key insight into the cellular structures and processes under observation. Results Modelling the photoswitching behaviour of a fluorophore as an unobserved continuous time Markov process transitioning between a single fluorescent and multiple dark states, and fully mitigating for missed blinks and false positives, we present a method for computing the exact probability distribution for the number of observed localizations from a single photoswitching fluorophore. This is then extended to provide the probability distribution for the number of localizations in a direct stochastic optical reconstruction microscopy experiment involving an arbitrary number of molecules. We demonstrate that when training data are available to estimate photoswitching rates, the unknown number of molecules can be accurately recovered from the posterior mode of the number of molecules given the number of localizations. Finally, we demonstrate the method on experimental data by quantifying the number of adapter protein linker for activation of T cells on the cell surface of the T-cell immunological synapse. Availability and implementation Software and data available at https://github.com/lp1611/mol_count_dstorm. Supplementary information Supplementary data are available at Bioinformatics online.

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