scholarly journals Equilibrium Distributions of Populations of Biological Species on Networks of Social Sites

2018 ◽  
Vol 13 (sup1) ◽  
pp. 74-98
Author(s):  
Min Wang ◽  
Wen Zhou ◽  
Zhijun Wu
Keyword(s):  
Biological Species ◽  
Equilibrium Distributions

A TEM study of electron tunneling in biological macromolecules

1987 ◽  
Vol 45 ◽  
pp. 140-141
Author(s):  
J. A. Panitz
Keyword(s):  
Stark Effect ◽  
Electron Tunneling ◽  
Imaging Modality ◽  
Tunneling Current ◽  
Biological Species ◽  
Scanning Tunneling ◽  
Biological Macromolecules ◽  
Flat Surfaces ◽  
Virus Particles ◽  
Stm Images

Tunneling is a ubiquitous phenomenon. Alpha particle disintegration, the Stark effect, superconductivity in thin films, field-emission, and field-ionization are examples of electron tunneling phenomena. In the scanning tunneling microscope (STM) electron tunneling is used as an imaging modality. STM images of flat surfaces show structure at the atomic level. However, STM images of large biological species deposited onto flat surfaces are disappointing. For example, unstained virus particles imaged in the STM do not resemble their TEM counterparts.It is not clear how an STM image of a biological species is formed. Most biological species are large compared to the nominal electrode separation of ∼ 1nm that is required for electron tunneling. To form an image of a biological species, the tunneling electrodes must be separated by a distance that would normally be too large for a tunneling current to be observed.

Graphene and Graphene Oxide Applications for SERS Sensing and Imaging

2019 ◽  
Vol 26 (38) ◽  
pp. 6878-6895 ◽  
Author(s):  
Anna Jabłońska ◽  
Aleksandra Jaworska ◽  
Mateusz Kasztelan ◽  
Sylwia Berbeć ◽  
Barbara Pałys
Keyword(s):  
Graphene Oxide ◽  
Surface Enhanced Raman Spectroscopy ◽  
Biological Species ◽  
Chemical Mechanism ◽  
Aromatic Molecules ◽  
Sers Enhancement ◽  
Reduced Graphene ◽  
Surface Enhanced Raman ◽  
Active Nanoparticles ◽  
Fluorescence Quencher

: Surface Enhanced Raman Spectroscopy (SERS) has a long history as an ultrasensitive platform for the detection of biological species from small aromatic molecules to complex biological systems as circulating tumor cells. Thanks to unique properties of graphene, the range of SERS applications has largely expanded. Graphene is efficient fluorescence quencher improving quality of Raman spectra. It contributes also to the SERS enhancement factor through the chemical mechanism. In turn, the chemical flexibility of Reduced Graphene Oxide (RGO) enables tunable adsorption of molecules or cells on SERS active surfaces. Graphene oxide composites with SERS active nanoparticles have been also applied for Raman imaging of cells. This review presents a survey of SERS assays employing graphene or RGO emphasizing the improvement of SERS enhancement brought by graphene or RGO. The structure and physical properties of graphene and RGO will be discussed too.

Simulation for enhancement in sensitivity of chalcogenide glasses-based fibre optic evanescent absorption sensor for malignant tissue detection

2020 ◽  
Vol 12 ◽  
Author(s):  
Ritesh Kumar Singh ◽  
Adarsh Chandra Mishra ◽  
Pooja Lohia ◽  
D.K. Dwivedi
Keyword(s):  
Evanescent Wave ◽  
Chalcogenide Glasses ◽  
Biological Tissues ◽  
Biological Species ◽  
Primary Objective ◽  
Effect Of Temperature ◽  
Refractive Indices ◽  
Core Radius ◽  
Source Illumination ◽  
Study Results

Background: Refractive index determination of biological tissues is a challenging issue. Many biological species also show vibrational signature in infrared domain. The chalcogenide-based glasses can be used to make the fiber optic evanescent wave sensors for detection of analyte. Objectives: The primary objective is to study the effect of various parameters on the sensitivity of chalcogenide glass-based evanescent wave sensor for biological tissue detection. Methods: An evanescent wave sensor has been proposed with collimated source illumination and uniform tapering. The chalcogenide materials are chosen such that the weakly guiding approximation could be followed. Complex refractive indices of liver tissue samples have been taken for the analysis of sensitivity via method of evanescent absorption coefficient. Equations for sensitivity have been solved analytically using MATLAB software. Results: The simplification of the formula for sensitivity leads to the inference that the sensitivity is a function of core radius, refractive indices of sample tissues and wavelength used. Moreover, since the refractive indices of the materials are also a function of temperature, therefore a change in temperature results into change in the profile of guiding mode. Hence the effect of temperature must also be observed. The initial simulation parameters are taken; core radius 100 µm, sensing length 4 cm and wavelength 1.0 µm. In the NIR region we have a better sensitivity of detection for all the tissues samples and the risk of photodamage of the biosamples is reduced to a good extent. It has been found that sensitivity decreases with wavelength and core radius whereas increases with temperature. It has also been shown that sensitivity is found to be better with collimated in comparison with diffused source. Conclusion: The comparative study results that one should operate at shorter NIR region of wavelength for higher sensitivity. The collimated source illumination should be preferred over diffused one for launching the light within the fiber to have high sensitivity. Further, length of sensing region should be larger but the fiber core radius should be smaller. The proposed biosensor is robust and can also be used many times if the probe (sensing region) is cleaned properly. Moreover, a small amount of analyte is enough for the detection. Thus, the proposed sensor is very useful for bio-medical applications with its high performance, accuracy and robustness.

State-dependent signalling in queueing networks

1994 ◽  
Vol 26 (02) ◽  
pp. 436-455 ◽  
Author(s):  
W. Henderson ◽  
B. S. Northcote ◽  
P. G. Taylor
Keyword(s):  
Queueing Networks ◽  
State Dependence ◽  
Product Form ◽  
Batch Size ◽  
Single Server ◽  
Negative Customers ◽  
Affect Control ◽  
State Dependent ◽  
Special Cases ◽  
Equilibrium Distributions

It has recently been shown that networks of queues with state-dependent movement of negative customers, and with state-independent triggering of customer movement have product-form equilibrium distributions. Triggers and negative customers are entities which, when arriving to a queue, force a single customer to be routed through the network or leave the network respectively. They are ‘signals' which affect/control network behaviour. The provision of state-dependent intensities introduces queues other than single-server queues into the network. This paper considers networks with state-dependent intensities in which signals can be either a trigger or a batch of negative customers (the batch size being determined by an arbitrary probability distribution). It is shown that such networks still have a product-form equilibrium distribution. Natural methods for state space truncation and for the inclusion of multiple customer types in the network can be viewed as special cases of this state dependence. A further generalisation allows for the possibility of signals building up at nodes.

scholarly journals Flow Control Techniques for Enhancing the Bio-Recognition Performance of Microfluidic-Integrated Biosensors

2021 ◽  
Vol 11 (15) ◽  
pp. 7168
Author(s):  
Fatemeh Shahbazi ◽  
Mohammad Souri ◽  
Masoud Jabbari ◽  
Amir Keshmiri
Keyword(s):  
Flow Control ◽  
Recognition Performance ◽  
Active Flow Control ◽  
Geometry Optimization ◽  
Cost Effective ◽  
Optimization Methods ◽  
Biological Species ◽  
Binding Assays ◽  
Dna Strands ◽  
Diffusion Migration

Biosensors are favored devices for the fast and cost-effective detection of biological species without the need for laboratories. Microfluidic integration with biosensors has advanced their capabilities in selectivity, sensitivity, controllability, and conducting multiple binding assays simultaneously. Despite all the improvements, their design and fabrication are still challenging and time-consuming. The current study aims to enhance microfluidic-integrated biosensors’ performance. Three different functional designs are presented with both active (with the help of electroosmotic flow) and passive (geometry optimization) methods. For validation and further studies, these solutions are applied to an experimental setup for DNA hybridization. The numerical results for the original case have been validated with the experimental data from previous literature. Convection, diffusion, migration, and hybridization of DNA strands during the hybridization process have been simulated with finite element method (FEM) in 3D. Based on the results, increasing the velocity on top of the functionalized surface, by reducing the thickness of the microchamber in that area, would increase the speed of surface coverage by up to 62%. An active flow control with the help of electric field would increase this speed by 32%. In addition, other essential parameters in the fabrication of the microchamber, such as changes in pressure and bulk concentration, have been studied. The suggested designs are simple, applicable and cost-effective, and would not add extra challenges to the fabrication process. Overall, the effect of the geometry of the microchamber on the time and effectiveness of biosensors is inevitable. More studies on the geometry optimization of the microchamber and position of the electrodes using machine learning methods would be beneficial in future works.

scholarly journals Role of Long Non-Coding RNAs and the Molecular Mechanisms Involved in Insulin Resistance

2021 ◽  
Vol 22 (14) ◽  
pp. 7256
Author(s):  
Vianet Argelia Tello-Flores ◽  
Fredy Omar Beltrán-Anaya ◽  
Marco Antonio Ramírez-Vargas ◽  
Brenda Ely Esteban-Casales ◽  
Napoleón Navarro-Tito ◽  
...  
Keyword(s):  
Insulin Resistance ◽  
Protein Kinase ◽  
Molecular Mechanisms ◽  
Cyclic Adenosine Monophosphate ◽  
Adenosine Monophosphate ◽  
Biological Species ◽  
Necrosis Factor Alpha ◽  
Polypyrimidine Tract Binding Protein ◽  
Non Coding Rnas

Long non-coding RNAs (lncRNAs) are single-stranded RNA biomolecules with a length of >200 nt, and they are currently considered to be master regulators of many pathological processes. Recent publications have shown that lncRNAs play important roles in the pathogenesis and progression of insulin resistance (IR) and glucose homeostasis by regulating inflammatory and lipogenic processes. lncRNAs regulate gene expression by binding to other non-coding RNAs, mRNAs, proteins, and DNA. In recent years, several mechanisms have been reported to explain the key roles of lncRNAs in the development of IR, including metastasis-associated lung adenocarcinoma transcript 1 (MALAT1), imprinted maternal-ly expressed transcript (H19), maternally expressed gene 3 (MEG3), myocardial infarction-associated transcript (MIAT), and steroid receptor RNA activator (SRA), HOX transcript antisense RNA (HOTAIR), and downregulated Expression-Related Hexose/Glucose Transport Enhancer (DREH). LncRNAs participate in the regulation of lipid and carbohydrate metabolism, the inflammatory process, and oxidative stress through different pathways, such as cyclic adenosine monophosphate/protein kinase A (cAMP/PKA), phosphatidylinositol 3-kinase/protein kinase B (PI3K/AKT), polypyrimidine tract-binding protein 1/element-binding transcription factor 1c (PTBP1/SREBP-1c), AKT/nitric oxide synthase (eNOS), AKT/forkhead box O1 (FoxO1), and tumor necrosis factor-alpha (TNF-α)/c-Jun-N-terminal kinases (JNK). On the other hand, the mechanisms linked to the molecular, cellular, and biochemical actions of lncRNAs vary according to the tissue, biological species, and the severity of IR. Therefore, it is essential to elucidate the role of lncRNAs in the insulin signaling pathway and glucose and lipid metabolism. This review analyzes the function and molecular mechanisms of lncRNAs involved in the development of IR.

scholarly journals Dynamics of Microsatellite Divergence Under Stepwise Mutation and Proportional Slippage/Point Mutation Models

Genetics ◽  
2001 ◽  
Vol 159 (2) ◽  
pp. 839-852 ◽  
Author(s):  
Peter P Calabrese ◽  
Richard T Durrett ◽  
Charles F Aquadro
Keyword(s):  
Point Mutations ◽  
Genetic Distances ◽  
Mutational Bias ◽  
Human Populations ◽  
Mutation Model ◽  
Perfect Repeat ◽  
Stepwise Mutation ◽  
Equilibrium Distributions ◽  
Theoretical Results ◽  
Polymerase Slippage

Abstract Recently Kruglyak, Durrett, Schug, and Aquadro showed that microsatellite equilibrium distributions can result from a balance between polymerase slippage and point mutations. Here, we introduce an elaboration of their model that keeps track of all parts of a perfect repeat and a simplification that ignores point mutations. We develop a detailed mathematical theory for these models that exhibits properties of microsatellite distributions, such as positive skewness of allele lengths, that are consistent with data but are inconsistent with the predictions of the stepwise mutation model. We use our theoretical results to analyze the successes and failures of the genetic distances (δμ)2 and DSW when used to date four divergences: African vs. non-African human populations, humans vs. chimpanzees, Drosophila melanogaster vs. D. simulans, and sheep vs. cattle. The influence of point mutations explains some of the problems with the last two examples, as does the fact that these genetic distances have large stochastic variance. However, we find that these two features are not enough to explain the problems of dating the human-chimpanzee split. One possible explanation of this phenomenon is that long microsatellites have a mutational bias that favors contractions over expansions.

Sign in / Sign up

Export Citation Format

Share Document