Cellular Level

At the cellular level, communications via the membrane are called the bespeak transduction, and facilitated with the ligands or messengers, such as proteins, peptide hormones.

From: Nonequilibrium Thermodynamics , 2002

Using mechanics to map genotype to phenotype

Mark A. Miodownik , in On Growth, Form and Computers, 2003

11.three.3 Robust construction

Clearly surface tension is a major force at the cellular level and nature has to deal with it if information technology wants to build organisms. We take seen from the examples in the previous section that as well as having to debate with surface tension, organisms can actively manipulate surface tension effects to construct and rearrange cellular material. Is this show that organisms employ surface tension as a natural cocky-assembly mechanism?

Unfortunately, this is non a straightforward question to answer. Physical forces tend to push systems into a state of equilibrium, which is mostly in one direction only; this is the essence of the second police force of thermodynamics. But the development of organisms is a dynamic process in which jail cell rearrangement is ongoing. The cell sorting examples outlined above are demonstrations of the fact that cells obey physical laws. Yet only in the instance of the convergent extension accept we postulated that these forces are actually harnessed to change the morphology of an organism. For nature to harness surface tension it needs not only to change the surface tension of dissimilar parts of the cells but too to time and control the mechanism. This is a much more sophisticated chore than merely using naturally occurring surface tension forces to pull cells together.

A sailing illustration will serve to further illustrate the point. Sailing with the wind behind you lot is like shooting fish in a barrel, any kind of sail volition go y'all moving forrad. Notwithstanding, you can also use the wind to take you back from the management you came. To sail into the wind, you need to tack. Tacking is non easy. Information technology involves turning at the right moments and setting the sails in exactly the right style. It is a complicated technique but, notwithstanding, uses the same driving force, the current of air, to move a boat in the opposite direction. Tacking requires the boat crew to time their deportment with respect to their motion, the gunkhole's direction and the wind's direction and strength. The decisions most when to tack crave more merely timing; they require feedback about the electric current conditions and noesis nearly the gunkhole's behaviour. In other words they require data processing.

The same is probably truthful in biological systems. The patterning mechanisms issuing from surface tension forces are probably used in many unlike ways to help build organisms. Furthermore, the way in which the organism controls the force will almost certainly require feedback loops and information processing. These control mechanisms will also have an bear upon on how repeatable the transformations can be. Information technology is all very well showing that a change in the surface free energy of these cells at this fourth dimension means they volition self-gather into a layer. Merely how consistent is it? A layer may always form, just how rapidly does it grade and are there always the same number of cells in that layer? In other words, biological organisms need robust mechanisms. These are not necessarily every bit uncomplicated as they may at first appear (Barkai and Leiber, 1997; Eldar et al., 2002).

Read total chapter

URL:

https://www.sciencedirect.com/science/article/pii/B978012428765550044X

Cytomics: From Cell States to Predictive Medicine

One thousand. Valet , ... A. Kriete , in Computational Systems Biology, 2006

Abstruse

Cytomics, the systematic study of biological system and behavior at the cellular level, has developed out of computational imaging and catamenia cytometry and promises to provide essential information for systems biological science. The ability to perform high-content and high-throughput imaging and analysis to reveal circuitous cellular phenotypes will not only further our understanding of how cells and tissues carry out their functions but too provide insight into the mechanisms past which these functions are disrupted.

Advances in flow, chemical, and tissue cytometry extend the applicability of cytomics to tissues, cytological smears, and blood and other body fluids. As such, cytomics not just provides a new framework for spatiotemporal systems biology but enriches personalized or individualized medicine. This can have the course of individual disease course predictions for therapy pick purposes as well equally identification of discriminatory bio-parameter patterns.

Read full chapter

URL:

https://www.sciencedirect.com/science/article/pii/B9780120887866500356

Metabolic Engineering

Jens Nielsen , in Encyclopedia of Physical Scientific discipline and Applied science (3rd Edition), 2003

4 Metabolic Network Analysis

A key attribute in the field of metabolic engineering is analysis at the cellular level in order to empathize the cellular function in detail. Of item importance is quantification of fluxes through the different metabolic pathways and analysis of how these fluxes are controlled. The metabolic fluxes represent a very detailed phenotypic label, and the in vivo fluxes are the end issue of many different types of regulation within the cell (see Fig. 5). In recent years some very powerful techniques have been adult for quantification of metabolic fluxes and for identification of the active metabolic network—frequently referred to every bit metabolic network analysis. Metabolic network assay basically consists of two steps:

Effigy 5. Control of flux at different levels. The transcription of genes to mRNA is controlled, and together with control of mRNA deposition this determines the mRNA levels in the cell. The mRNAs are translated into proteins, either enzymes catalyzing biochemical reactions or regulatory proteins acting as transcriptional factors or protein kinases. Finally, the enzymes catalyzing biochemical reactions determine the levels of the metabolites, which influence the metabolic fluxes straight or indirectly through feedback interaction with regulatory proteins. Thus the metabolites indirectly may control both transcription and translation.
•

Identification of the metabolic network structure (or pathway topology)

•

Quantification of the fluxes through the branches of the metabolic network

For identification of the metabolic network structure, one may gain much information through the extensive biochemistry literature and biochemical databases available on the spider web (see, eastward.m., www.genome.ad.jp, which gives consummate metabolic maps with direct links to sequenced genes and other information almost the private enzymes). Thus, there are many reports on the presence of specific enzyme activities in many different species, and for virtually industrially important microorganisms the major metabolic routes have been identified. However, in many cases the complete metabolic network structure is not known, i.east., some of the pathways carrying significant fluxes have not been identified in the microorganism investigated. In these cases enzyme assays can be used to confirm the presence of specific enzymes and determine the cofactor requirements in these pathways, e.m., whether the enzyme uses NADH or NADPH every bit cofactor. Even though enzyme assays are valuable for confirming the presence of active pathways, they are of limited use for identification of pathways in the studied microorganism. For these purposes, isotope-labeled substrates is a powerful tool, and especially the use of 13C-labeled glucose and subsequent analysis of the labeling pattern of the intracellular metabolites has proven to be very useful for identification of the metabolic network structure. The labeling pattern of 13C in intracellular metabolites may be analyzed either using NMR or using gas chromatography–mass spectroscopy (GC-MS), with the latter technique beingness superior due to its high speed and sensitivity.

When the metabolic network construction has been identified, it is important to quantify the fluxes through the unlike branches in the network. The simplest approach to quantify the fluxes is by using the concept of metabolite balancing (see Fig. 6). Here fabric balances are fix up over each metabolite in the network structure, and assuming steady state in the metabolite concentrations a set of algebraic equations relating the fluxes is obtained. These equations impose a prepare of constraints on the fluxes through the individual reactions in the network. Past measuring some of the fluxes or by using linear programming, information technology is then possible to calculate the fluxes through all the branches of the network. Detect that cofactors may link the private pathway segments, and thus impose additional constraints on the fluxes. Due to its simplicity, the concept of metabolite balancing is attractive, but information technology has some limitations. Thus, the flux estimates depend on the cofactor balances, i.e., the balances for NADH and NADPH, and information technology is therefore of import that all reactions involving these cofactors within the cell are included. Since it is unlikely that all reactions involving these cofactors have been identified, metabolite balancing may result in poor estimates of some metabolic fluxes.

FIGURE 6. Quantification of metabolic fluxes by metabolite balancing. It can mostly be assumed that inside the cell the germination and consumption of metabolites is counterbalanced (merely immediately subsequently large perturbations does the metabolite concentration change). This gives a set of constraints on the fluxes, and this can be generalized to the matrix equation specified in the figure. In the instance at that place are 3 equations, and with six fluxes it is possible to calculate 3 fluxes if three are measured, i.e., the degrees of freedom is three. Note that the balance for metabolite A is obvious, and for this reason linear segments in the metabolic network are normally lumped into overall reactions. In many cases cofactors impose additional constraints between the fluxes, and thus the degrees of freedom may be farther reduced.

Through the use of 13C-labeled glucose and measurement of the labeling pattern of the intracellular metabolites by NMR or GC-MS, it becomes possible to apply balances for the individual carbon atoms in addition to the metabolite balances. Therefore an additional set of constraints is obtained, and it is therefore not necessary to include balances for cofactors. Furthermore, since many balances for the individual carbon atoms can be practical, an overdetermined organisation of equations is obtained, i.eastward., there are more equations than unknown fluxes. This redundancy in the equation system enables a more robust interpretation of the fluxes, and it also enables estimation of reversible fluxes in the network. Conspicuously the utilise of labeled substrates enables a much amend interpretation of the metabolic fluxes, but it is also a more complex procedure. Get-go of all, measurement of the labeling pattern of the intracellular metabolites requires more than avant-garde analytical procedures, only the equation system is also far more complicated. In recent years this arroyo has been demonstrated, notwithstanding, to work very well for estimation of the fluxes in many dissimilar microorganisms.

Metabolic network analysis is clearly a very powerful tool for phenotypic characterization. It is, however, important to underline that the technique has no predictive power. Only in few cases do the estimated fluxes by itself point to a strategy for directed genetic modifications. In nearly cases flux analysis is only useful when dissimilar strains are compared or there is performed a comparison of the same strain grown at different ecology conditions (meet Fig. 7). Through such comparisons it may exist possible to derive correlations between the productivity and sure fluxes, and from such correlations a hypothesis about possible limitations inside the prison cell may be derived.

Effigy 7. Metabolic fluxes estimated using xiiiC-labeled glucose. (A) Fluxes estimated in a high and low yielding strain of P. chrysogenum. The left figures bespeak fluxes in the low yielding strain and the right figures indicate the fluxes in the loftier yielding strain. Information technology is observed that there is a slightly higher flux through the pentose phosphate pathway in the high yielding strain, which may be explained by the increased demand for NADPH in this strain. This points to a possible correlation between penicillin production and pentose phosphate pathway activity. [The data are taken from Christensen, B., Thykær, J., and Nielsen, J. (2000). Appl. Microbiol. Biotechnol. 54, 212–217.] (B) Fluxes estimated in S. cerevisiae grown at respectively loftier and depression specific glucose uptake rates. The fluxes at high specific glucose uptake rates are the left figures and the fluxes at low specific glucose uptake rates are the right figures. At high specific glucose uptake rates in that location is ethanol germination due to the Crabtree consequence, and respiration is repressed resulting in no flux through the TCA wheel. Due to the Crabtree effect, the yield of biomass on glucose is low and in that location is therefore a depression requirement for NADPH and precursors of the pentose phosphate pathway, and the flux through this pathway is therefore depression. [The data are taken from Gombert, A. K., dos Santos, M. 1000., Christensen, B., and Nielsen, J. (2001). J. Bacteriol. 183, 1441–1451.]

Read full chapter

URL:

https://www.sciencedirect.com/scientific discipline/article/pii/B0122274105004221

Electrophysiology

S.E. Pagnotta , in Encyclopedia of Condensed Matter Physics, 2005

Channel Function

As discussed in previous paragraphs, electric activity of biological systems at the cellular level consists of ion movement through highly specialized channels spanning the cell membrane. "Native" channels, normally expressed in a particular cell, can exist studied. Even so, a deep understanding of the ion channels functioning is now greatly facilitated past the use of item experimental systems, such as artificial and natural membranes in which specific ion channels can be selectively expressed. For natural membranes, ionic channels are newly synthesized by foreign Deoxyribonucleic acid or RNA injected into a large living prison cell (such every bit the Xenopus laevis oocyte) via large pipettes.

Apart from the choice of the system expressing the ion channels under investigation, unlike techniques can exist used to record their electrical activity. A cardinal method for electrophysiological studies, namely the single-cell patch clench, was adult around 1978 by Sakmann and Neher. The starting point of this technique is the formation of a loftier-resistance (gigaohm) seal when the tip of a burn down-polished drinking glass micropipette is pressed against a cultured or acutely isolated cell membrane. The gigaohm seal essentially allows a high current proceeds, and low noise amplification, necessary for recording small, brief currents passing through unmarried ionic channels. After this showtime step, the patch-clench method tin can be applied in at least iv configurations: cell-fastened, inside-out, exterior-out, and whole-cell (Figure 6). The start three configurations allow study of individual ion channels nether different weather condition.

Effigy half-dozen. The four configuration of the patch-clench technique.

The cell-attached configuration (Figure 6a) is essentially obtained with the germination of the gigaohm seal. In this manner, the electric activity of single channels, present under the pipette tip, is recorded without disruption of the jail cell membrane. In the inside-out and outside-out configurations, the membrane patch is detached from the cell after the gigaohm seal is formed, and single-aqueduct activity is recorded in isolation from the cell. In particular, in the within-out configuration (Effigy 6c), the patch of membrane is gently pulled away from the cell, and the patch remains attached to the pipette with its cytoplasmic surface now exposed to the bathing solution. On the other hand, to reach the outside-out configuration (Effigy 6d), the patch of membrane is gently pulled away from the cell simply after an intermediate pace (the whole-cell configuration that volition be described below), in which the membrane patch nether the pipette is ruptured by applying a strong suction to the recording pipette interior. Once detached, the membrane seals over the pipette tip, in favorable cases forming a membrane patch in which the extracellular membrane surface is exposed to the bathing solution.

The concluding configuration is the whole-prison cell clamp (Figure 6b). It is a form of the cell-fastened configuration that uses the aforementioned pipette type and gigaohm seal method described above but that, by rupturing the membrane nether the tip, allows recording of the "macroscopic" or summed currents flowing through all channels in the unabridged cellular membrane, rather than through a single channel, and for this reason is mainly used to study cellular electric role (as it will be described in the side by side paragraph). In this configuration, the diffusible contents of the pipette exchange with those of the prison cell over time.

Read full affiliate

URL:

https://www.sciencedirect.com/scientific discipline/article/pii/B0123694019003958

Molecular and Cellular Manipulations for Hereafter Nanomedicine

A. Ikai , in The World of Nano-Biomechanics (2d Edition), 2017

14.iv Cell Surgery

The obvious target of application of nano-biomechanics is, as nosotros envision, the cellular-level surgery in a sense that a microsurgical knife comes in contact with a specific local expanse on a living cell and manipulates the action and localization of membrane proteins or penetrates the cell and operates on the intracellular structures to correct any of their defects. Using such techniques nosotros can also recover a small amount of proteins from the cell membrane, mitochondria, and other subcellular structures from the inside of the nucleus. By operating on the genetic material in the nucleus and mitochondria, doctors tin change the properties of the offspring of the operated cells. If the cell is an embryonic stem cell, the tissues and organs to be reproduced from information technology will have its contradistinct characteristics. Thus, at that place is an enormous potential for cellular-level surgery in the hereafter.

We first cell surgery by opening a hole on the cell membrane without serious injuries to the cell. Footling is known well-nigh the recovery procedure of the injured cell or about the disquisitional size of the hole for recovery of the cell. Experiments conducted in several laboratories take already led to the aggregating of seminal cognition about these processes [6]. Using a focused pulse light amplification by stimulated emission of radiation axle, i tin can now cut or create a hole in a local role of intracellular structures without breaking through the prison cell membrane [7–9].

Read full chapter

URL:

https://www.sciencedirect.com/science/commodity/pii/B9780444636867000146

Models based on cellular automata for the assay of biomedical systems

Alejandro Talaminos-Barroso , ... Laura María Roa-Romero , in Control Applications for Biomedical Engineering Systems, 2020

4.1 Epidemiology

The incidence of contagious diseases has a not bad importance in health policy (van Panhuis et al., 2013) and mathematical models in epidemiology have been used to analyze, predict, and control the outbreak of infectious epidemics and propose possible control strategies.

Generally, epidemiological models can exist classified into two types of approaches: on the one hand, those focused on the propagation and infection dynamics in a population clearly delimited at a geographical level and, on the other mitt, a biological study on the mechanisms involved in the expansion of a virus at the cellular level inside an organism.

With respect to the first group of works, archetype models in epidemiology describe the different states in which population groups can be constitute considering the transmission of an communicable diseases, including aspects such equally the nonhomogeneous distribution of the population, migratory movements, and interactions in a local context. In addition, CA permit the modeling of the physiological characteristics of individuals susceptible to contracting a affliction or beingness infected with a virus. Each individual of the population considered is an object independent in a box in the CA and the transition of the different states depends on the health status of the individual, in add-on to the conditions of the surrounding individuals (Sharma and Gupta, 2017). In full general, the simplest models are those that consider two groups of populations: susceptible (S) and infected (I), called SI models. Other approaches include three subpopulations: susceptible-infectious-susceptible (SIS models), where infection does not confer immunity and infected individuals return to the susceptible state. At that place are other models that consider a new population group chosen exposed (Due east), formed by people who are non infected simply who do non present symptoms, and depending on the disease involved, can exist infected or non. These models are chosen SEIS models and describe the flows of people between susceptible-exposed-infectious-susceptible. Another type of models of four populations are those that modify from the susceptible to recovered group (R), which are those individuals who become immunized once they accept overcome an infection. These types of models with 4 population groups (susceptible-exposed-infectious-recovered) are called SEIR models. Finally, it is also possible to consider models with five groups of populations to consider an infection that does not permit any immunity and recovered individuals return to existence susceptible once more (SEIRS models). Several examples of models based on the classic approaches presented earlier are discussed at present.

Situngkir (2004) explores the epidemiological touch of avian flu illness in Indonesia using a SIR model. The model uses a ii-dimensional cellular space with a von Neumann neighborhood and results showed that the economic factors and control policies of Southeast Asian countries have a strong touch on on the spread of this disease. On the other hand, the geographical feature formed by a conglomerate of islands reduces the severity of the spread. Some other similar model for the same disease is presented in Pfeifer et al. (2008), although the model described tin be adapted and applied to other epidemiological processes. In this case, five possible states are considered (latent, infectious, recovered, incubating, and symptomatic) bold the Moore neighborhood and including the possibility of classifying the population by age groups. In detail, this study focuses on the region of the State of Tyrol (Austria), where unlike population densities, due to orography and big valleys, hinder the spread of the disease. Finally, a recent work based on CA (Yang et al., 2017) studied the infectious spread of HIV in Chongqing (China) by applying a 2-dimensional cell space of more than than 1000 boxes (corresponding to an area with a radius of 10 km and four divisions with respect to economic and geographical levels) and a fixed boundary condition. The results obtained with the model were consequent with available evidence.

On the other hand, epidemiological models based on CA that written report the spread of a virus at cellular level inside an organism are more than numerous and diverse. For case, the outbreak of Ebola in 2014–15 led to the emergence of models, such as the one presented in Burkhead and Hawkins (2015). This study proposed a two-dimensional CA considering four possible states: healthy prison cell (H), infected prison cell (I1), delayed infected prison cell (I2), and expressionless cell (D). The transition rules consider that the two types of infected cells are as well infectious and when the prison cell reaches the state D, a new good for you jail cell replaces information technology in the next iteration. The piece of work presents simulations based on different conditions considering the state of the allowed system: fully functional, with delayed and with compromised response. In the proposed scenario with a fully functional immune system, state I2 is never reached because a jail cell in state I1 passes quickly to state D in the next iteration. In this case, the rules of state transition are as follows:

•

A cell in state H changes to state I1 in the next iteration if at that place is at least one jail cell with country I1 around it.

•

A cell in state I1 changes to state D in the adjacent iteration.

•

A cell in land D changes to land H in the next iteration.

Fig. 16 shows the example of a scenario described with fully functional immune arrangement, limited to nine cells to simplify the problem and considering initial conditions with two cells in country I1.

Fig. 16

Fig. 16. Simulation of three iterations for the example presented in Burkhead and Hawkins (2015) with fully functional immune system.

In the other two scenarios presented, the immune system with delayed response gives rising to the appearance of cells with land I2 afterward previously passing through state I1. On the other hand, cells are non regenerated and dice at some point in the simulation when the allowed system is compromised, reaching the irreversible state D, assuming at least one cell in the state I1 or I2 at the initial instant. Fig. 17 shows the simulation for iii iterations considering the immune organisation with delayed response (A) and compromised response (B), and the same initial conditions equally in the previous case.

Fig. 17

Fig. 17. Simulation of 3 iterations for the example presented in Burkhead and Hawkins (2015) with delayed response (A) and compromised immune system (B).

The infectious processes induced by slow virus affliction usually crave a greater number of states. For example, in another piece of work by the same authors, merely focused on HIV (Burkhead et al., 2009), a two-dimensional CA with seven states is presented to model the spread of infection in the lymph node, considering different levels of infection. Another example simplified to four states (healthy, infected-A1, infected-A2, and dead) was presented in Zorzenon dos Santos and Coutinho (2001), describing the importance of the lymph node, spatial location, and local interactions in HIV infection dynamics, as suggested in the literature. In this line, the work in Jafelice et al. (2009) presents a two-dimensional CA based on quadrangular boxes in a 31 × 31 space for the report of HIV through the circulatory organization, where infected or uninfected cells are considered, every bit well every bit the blood and antibodies. The aim of this piece of work was to reproduce the evolution of HIV in the circulatory system, considering the furnishings of antiretroviral therapy. In general, HIV has been one of the most studied viruses from the point of view of CA modeling and there are an important number of published works.

Another virus that has been extensively studied from an automaton-based modeling perspective is the avian influenza virus and its unlike subtypes. For case, (Beauchemin et al., 2005) presents a model where the transmission of the avian influenza virus in an organism is analyzed considering two types of cells: epithelial cells and immune cells. On the one hand, epithelial cells can be found in five states: healthy, infected, expressing, infectious, and dead. The following are the main transitions betwixt states:

•

Salubrious cells are transformed into infected cells assigning a probability associated with the number of neighboring infectious cells.

•

The expressing state represents the infected cells that begin to release the viral peptide and become infectious cells after a period of time.

•

All cells die later a certain time associated to a life expectancy parameter.

•

Expressing and infectious cells die when they are recognized by an immune cell.

•

The regeneration of dead cells is included in the model.

On the other hand, immune cells tin can be found in two states: virgin or mature. The virus is not considered as a type of jail cell in the automaton, merely the infection is adamant by directly propagation from i epithelial cell to another. Dimensionally, this model is characterized past a two-dimensional infinite with a quadrangular grid, where each epithelial cell is located in a stock-still position throughout the simulation catamenia, while allowed cells move randomly and interact under certain circumstances with epithelial cells. The results obtained showed that the model tin exist used as a testing tool to investigate various theoretical aspects of viral infections, especially in the context of avian flu disease. Other models related to this type of virus have been presented in contempo years (Guan et al., 2016; Situngkir, 2004; Zhang, 2017).

To a lesser extent, other viruses and diseases have been studied, among them:

•

Chagas affliction (Slimi et al., 2009), studied with a model that describes the space-time interaction of the epidemiological dynamics betwixt insects (adults and larvae) at the geographical level of a village in the Yucatan peninsula (Mexico). The aim of this piece of work was to evaluate and ameliorate the efficiency of the utilise of insecticides, equally well equally to propose alternative control strategies, like the use of musquito nets or the cleaning of backyards.

•

Hepatitis B (Xiao et al., 2006), modeled by a two-dimensional space with periodic boundary and ii prison cell types representing hepatocytes: resistant (R) or susceptible (Due south) to viral replication. The possible states considered in this model were: salubrious cell type R, healthy cell type S, infected cell blazon R, infected cell type Southward, defectively infected cell, and expressionless cell (removed by the allowed system or subsequently their lifetime). Viral particles and immune cells were not explicitly considered, and the infection is spread betwixt hepatocytes. The work explains some dynamics associated with transmission of hepatitis B virus, allowing the adaptation of the model to be applied to other persistent infections with replicating parasites.

•

Zika virus (Alvarado et al., 2018), studied from a model-based perspective at the cellular level on the basis of experimental data observed in laboratory. For this purpose, a 2-dimensional CA model of 400 × 400 boxes was proposed, considering round boxes to ameliorate mimic the shape in a cell civilisation. Biologically, Zika virus-infected cells have fourth dimension to release viral particles, increasing the likelihood of infecting neighboring cells until the resources are consumed. In that moment, a new phase leads to jail cell death. In the proposed model, four possible states were considered: healthy (H), infected (I), condensed (C), which are those cells that have been infected for a flow of time, and expressionless (D). Finally, the model can be adapted to other viral cultures.

•

Lyme affliction is a type of bacterial infection transmitted to humans past the bite of an infected tick. The work in Li et al. (2012) presented a model for the manual of this bacterium in an environment with Ixodidae ticks. The cellular infinite considered in the model was quadrangular, with a dimension of 50 × 50 boxes and ii types of objects in the automaton: ticks and hosts. There are three stages associated with the evolution of the tick: larva, nymph, and adult; and hosts can be of two types: on the ane hand, reservoir hosts, including vertebrates such as rodents, insects, and bird species that contribute to the maintenance of transmission; on the other hand, reproduction hosts such every bit fallow deer and cows, which provide blood to a significant number of developed ticks. The cellular infinite is divided into different habitats where tick-host interaction is analyzed. With respect to the habitat, 3 possible types of the zones are considered: woodland, grassland, and nonvegetated. The host has the power to move through the cellular space, considering unlike move patterns that differ from the type of habitat in which they are establish. On the other hand, transition rules for tick development and pathogen transmission may vary depending on the habitat and the development stage of the tick. Different types of simulation were performed with habitat blocks of 1 × 1, 2 × 2, 5 × 5, and x × 10 boxes, where each cake represents a habitat type. The results showed that habitat fragmentation is a run a risk for the acquisition of Lyme disease, every bit supported by other authors.

•

Hantavirus is a group of viruses that are transmitted to humans through contact with urine, saliva, or feces from infected rodents. A model based on CA was presented (Abdul Karim et al., 2009) for describing the spread of this virus between rodents. For this purpose, a jail cell space was proposed with Moore neighborhood, toroidal boundary conditions, and ii states: infected and uninfected. Two characteristics of hantavirus infection are included in the model. On the i hand, the complete disappearance of the infection in a rodent population when certain climatic atmospheric condition associated with seasonality (temporal feature). On the other manus, the population of rodents tin increase or reduce taking into business relationship the availability of food resources (spatial characteristic). The results showed that susceptible and infected populations reach a stable value after a series of time intervals, depending on temporal and spatial characteristics as well equally initial conditions.

Three-dimensional cellular spaces accept likewise been used to model the propagation of infectious diseases. For example, (Khabouze et al., 2015) presents a CA model because a 3D cellular space to draw the interactions betwixt cells and the hepatitis B virus, both at the surface level and within the liver. The model is based on the von Neumann neighborhood with four possible states: healthy hepatocytes R (resistant to viral replication), healthy hepatocytes S (susceptible to viral replication), infected hepatocytes I and expressionless hepatocytes D. Each simulation performed in the work initializes the salubrious hepatocytes R and Southward with different percentages. The results showed that increasing the percent of hepatocytes Due south impact on viral load and decrease the number of salubrious cells, which explains why a child with a smaller liver is more susceptible to developing the virus than an adult.

Read full chapter

URL:

https://www.sciencedirect.com/scientific discipline/article/pii/B9780128174616000147

Volume 2

Fengli Zhang , ... Shang-Tian Yang , in Encyclopedia of Tissue Engineering and Regenerative Medicine, 2019

Mechanical force

Mechanical strength, which occurs in some regions of body, affects the command of tissue morphologies. At the cellular level, there are ii types of mechanical forces: internal and external. Here simply the effects of external force on stem cells in bioreactor will be discussed. External forcefulness tin can be transmitted into cells through actin cytoskeleton, which prompts cells to respond. Physiological actions generate unlike external forces to cells. For instance, pinch and shear lead to cell deformation, and tension causes cell elongation and jail cell nucleus deformation. Therefore, mimicking mechanical forces that stem cells experience in vivo can help in engineering stem cell environments in vitro.

Mechanical force can bear upon stem cell differentiation. In one study, mechanical stress in a 3D culture system promoted cardiomyocyte structural and functional maturation of ESC-derived progenitors, while mechanical stress in a 2nd civilization system promoted smooth muscle differentiation. The results propose that mechanical force in different culture systems may have different effects on prison cell differentiation. In another report, MSCs casted in blazon I collagen gels in tensioning bioreactors differentiated into fibroblast-like cells with upregulated α-smoothen muscle actin, while monolayer cells in plastic culture plates differentiated into adipocytes, osteocytes and chondrocytes. The study suggests that minute, cell-derived strength could touch MSCs fate choice. Likewise, mechanical tension enhanced osteogenic differentiation of os marrow MSCs by increasing the expression of long noncoding RNA H19, which sponged miR-138 and upward-regulated focal adhesion kinase to induce osteogenesis. Human being periodontal ligament stem cells were differentiated into keratocytes with dome-shaped mechanical stimulation in a Flexcell Tension System, producing multilamellar jail cell sheets resembling native human being corneal stroma for potential clinical applications. Apart from the upshot of mechanical strength on stem cell differentiation, the effect on viability was also studied. A novel bioreactor mimicking bitter strength was used to report the effect and machinery of mechanical loading on human being dental pulp stem cells in an agarose scaffold, and results showed that additional mechanical loading increased viable jail cell numbers besides as osteogenic differentiation. In summary, mechanical forces attune stem jail cell fate and peculiarly affect stem cell differentiation into musculus cells or bone.

Read full chapter

URL:

https://www.sciencedirect.com/science/article/pii/B9780128012383655307

Targeted Drug Commitment: Multifunctional Nanoparticles and Directly Micro-Drug Delivery to Tumors

Cloudless Kleinstreuer , ... Andrew Kennedy , in Ship in Biological Media, 2013

10.3.2.7 Multifunctional Nanoparticles

To further improve the effectiveness of gratis transport, multifunctional nanoparticles tin exist designed with components that notice diseases at the cellular level, raise medical images, ballast the particles to diseased sites and release therapeutic compounds. This can be accomplished through the inclusion of protective coatings, the incorporation of dissimilar targeting ligands and the encapsulation of image-dissimilarity agents, therapeutic nanodrugs and ferric crystals for magnetic steering (see Fig. ten.three). Examples of such nanostructures include: polymer uni-molecular micelles loaded with PET isotope chelator, tumor targeting ligands, and doxorubicin for drug detection, targeting and handling of tumors [39], fluorescent quantum dots (QDs) loaded with aptamers and doxorubicin for imaging, targeting and therapeutics [twoscore], carbon nanotubes for detecting cancerous cells and delivering nanodrugs to these cells [33] and luminescent mesoporous NPs that combine simultaneous cancer-cell imaging plus drug delivery [41]. Figures x.3c and 10.3e describe semi-porous silica (or polymer) particles, covered with ligands as well as a hydrophilic coating and loaded with nanodrugs plus ferric nano-crystals, in case of magnetic steering towards the diseased site. In another example, ultrasound in combination with temperature and/or pH-responsive properties of NPs, loaded with nanodrugs and ferric crystals, are currently being tested for both local drug commitment to tumors and hyperthermia treatment (see [27]).

Figure 10.iii. Schematics of multifunctional nanoparticles.

Read full affiliate

URL:

https://www.sciencedirect.com/science/article/pii/B9780124158245000102

Mucoadhesive Polymers: Gateway to Innovative Drug Delivery

Muhammad Yaqoob , ... Andreas Bernkop-Schnürch , in Modeling and Control of Drug Delivery Systems, 2021

7.3 Mucoadhesive Nanoparticles

Nanoparticles accept bore in nanometer range and possess certain properties and functions that differ significantly from original material when it interacts at cellular level. Due to college penetration in mucus gel layer, nanoparticles show more mucoadhesion as compared to micro particles [145]. Polymers like polyacrylates, PLGA, chitosan are being studied to prepare these mucoadhesive nanoparticles [146]. Solid lipid nanoparticles (SLNs) accept also gained attention of researchers in recent years because of the inherent backdrop of encapsulating lipophilic drugs with higher payload [21]. After preparation SLNs are fabricated mucoadhesive by surface modification i.e. coating the SLNs past mucoadhesive polymers such every bit sodium alginate and poloxamer, chitosan, and its various derivatives [21, 147–149]. In an in vivo study, Kharia et al. notice that the nanoparticles containing poloxamer remain attached two folds longer time in stomach and small intestine in comparing to conventional dosage course [150]. In another in vivo study in rats, Carbopol 934-P-loaded nanoparticles stayed for 12   h as compared to control which terminal for three   h [151].

Read full chapter

URL:

https://www.sciencedirect.com/science/commodity/pii/B9780128211854000208

OVERVIEW OF EXPERIMENTAL FINDINGS

V. Nabokov,Ada or Ardor: A Family Chronicle, in Magnetobiology, 2002

2.4.ii Characteristic experimental data

The temporal correlation of various indices of geomagnetic action with a wide variety of biological characteristics and processes was observed. Such correlations fix in at the cellular level or even at the level of chemic reactions in vitro, e.chiliad.,

in the Piccardi reaction. It is difficult, therefore, to find a process in the biosphere that would non correlate with some parameters of the helio-geosphere.

In many frequency ranges nether nearly 0.1 Hz a correlation of GMF variations with some biological processes has been found. The pioneering works were those by Chizhevskii and Piccardi. Some of their papers (eastward.m., Piccardi, 1962; Chizhevskii, 1976) have laid a dramatic foundation for the farther development of heliobiology. Information technology has taken well-nigh half a century for investigations into helio-geobiocorrelations to be promoted from the status of a "pseudo-science" to, at kickoff, an exotic (Gnevyshev and Oll, 1971) and and so to a common domain of scientific research (Shnoll, 1995a). It is rapidly becoming one of the hottest fields now.

• A voluminous monograph by Dubrov (1978) addresses the studies of correlation of biospheric processes in objects ranging from constitute and microorganism cells to higher animals, humans, and ecological systems, with variations of the geomagnetic field within a wide range of times scales, from hours to decades. The book contains more than 1200 references to original works of Russian and international researchers. Juxtaposing geophysical and biomedical information, the author has shown quite convincingly for the first fourth dimension that the bio-GMF correlations are non an exotic phenomenon, but rather a common fact that warrants careful investigation. In what follows the correlations contained in that book are provided between geomagnetic correlations and some processes of vital activity, mutations, cancer, and and so on.

Figure 2.29 shows regression assay data for an approximately synchronous grade of two processes. 1 of them is the variation of the density of chromosome

Figure two.29. Correlation diagram. Variation of the GMF horizontal component and the change in the chromosome aberration frequency in rat liver cells. Processed data of Fig. 34 (Dubrov, 1978).

structural defects in rat liver cells upon an injection of dipine, an antitumor training. The other process is the variation of the magnitude of the GMF horizontal component at the experiment site. Effigy two.30 provides the circadian rhythm of the mitosis of human carcinoma cells and the GMF inclination value inside appropriate time spans. Effigy ii.31 is a plot of the seasonal variation of chromosome inversions of the ST gene in Drosophila under natural conditions and the mean monthly variations of inclination.

Figure 2.xxx. The daily rhythm behavior of cancer cell mitoses and the variation of geomagnetic field inclination, according to Fig. 32 in the monograph (Dubrov, 1978).

Figure ii.31. The behavior of the natural seasonal mutation procedure and the variation of the GMF parameter, according to Fig. 65 from the monograph (Dubrov, 1978).

Correlation diagrams for these graphs are given in Fig. two.32 and Fig. 2.33. These graphs are seen to show correlation connections for various time scales, which is evidence for the hypothesis of the direct influence of GMF variations on the beliefs of biological processes.

Effigy ii.32. Correlation diagramof the biological and geomagnetic processes in Fig. 2.thirty.

Effigy 2.33. Correlation diagram of biological and geomagnetic processes in Fig. two.31.

• In some plants, enhancements and retardations of their evolution was observed (Kamenir and Kirillov, 1995) when the Earth passed through sectors with positive and negative polarity of the interplanetary MF, respectively. It was shown (Alexandrov, 1995) that the activity biorhythms in aquatic organisms vary with the regional MF. The bioluminescence of Photobacterium bacteria changes markedly during magnetic storms (Berzhanskaya et al., 1995), then that changes occur a day or two earlier the onset of a storm and terminal for two or iii days after the tempest has ebb.

• Gurfinkell et al. (1995) conducted regular measurements of capillary claret flow in 80 centre ischemia cases. On the twenty-four hour period of a magnetic storm 60-70% patients showed impaired capillary blood flows. At the same fourth dimension, only 20–30% of patients responded

to changes in the atmospheric pressure.

• Oraevskii et al. (1995) found that fifty-fifty short-term variations of the interplanetary MF polarity inside 24 h correlate with serious medical maladies. Shown in Fig. 2.34 is the regression analysis of their data. At that place is a meaning correlation between the number of emergency calls in connection with myocardium infarction (on days with anomalously large or anomalously small number of calls) and the alphabetize of interplanetary MF variations. The alphabetize was approximately equal to the daily integral B z , i.e., to the z-component of the interplanetary MF. Information technology was worked out equally a sum of hourly values of

Figure 2.34. Correlation diagram: the abscissa axis is the interplanetary MF index, the ordinate axis is the daily number of emergency calls in connection with myocardium infarction; data of Oraevskii et al. (1995) processed, the confidence interval at a level of 0.95.

B s = { 0 , undefined B z undefined ≥ 0 − B z , undefined B z < 0

during the 24-h interval shifted 6 h back in relation to the 24 h under consideration.

The authors obtained a similar statistics for emergency calls in connexion with insult, hypertonic crisis, bronchial asthma, epilepsy, and diverse injuries.

• Villoresi et al. (1995) conducted a thorough statistical analysis of the relation of the incidence of astute cardiovascular pathologies in the years 1979–1981 with the GMF variations. The authors showed that strong planetary-scale geomagnetic storms are related to the growth in the number of myocardium infarction cases past 13% to within a statistical confidence of 9σ, and the number of brain insults, by 7% with a statistical confidence of 4.5σ. Information technology was plant that such pathologies as myocardium infarction, stenocardia, and cardiac rhythm violations correlate in a similar manner with the onset of geomagnetic storms (Gurfinkell et al., 1998). Figure 2.35 provides those findings.

Co-ordinate to observational bear witness gleaned over ix years (Zillberman, 1992) a correlation was revealed of geomagnetic activity, Ap -index, with a density of true predictions in mass-number lotteries, R = −0.125 for significance 99.74%. The density correlated with Ap precisely on the day of event and did not correlate with that index on previous or later days.

Too, correlations were found of the geomagnetic perturbations with the subtract in morphine analgesic result in mice (Ossenkopp et al., 1983); of the alphabetize of brusk-period oscillations of the H-component of the GMF with the brain functional status (Belisheva et al., 1995); of a change in the direction of the interplanetary MF with leucocyte and hemoglobin content in mouse blood (Ryabyh and Mansurova, 1992); of the daily sum of K -indices with the suicide frequency (Ashkaliev et al., 1995); of the Ap -index with the criminal activity in Moscow (Chibrikin et al., 1995b); of the Ap -alphabetize with the amount of cash circulating in Russia (Chibrikin et al., 1995a); of the occurrences of magnetic storms with the probability of air crashes (Sizov et al., 1997).

For more information on a variety of biospheric processes that correlate with the geomagnetic activity run into some special issues of the Biophysics journal (Pushchino, 1992, 1995, 1998), and collections of works (Gnevyshev and Oll, 1971, 1982; Krasnogorskaya, 1984, 1992).

Read full chapter

URL:

https://www.sciencedirect.com/science/article/pii/B9780121000714500046