893 resultados para potassium cell level


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Patients with anorexia nervosa (AN) have low body weight, depleted fat stores, and reduced muscle mass. Both total body potassium (TBK) and bioelectrical impedance analysis (BIA) have been used to measure the body composition of these patients.1–4 Whereas TBK accurately measures body cell mass, the metabolically active compartment of the body, whole body potassium counters are expensive and not readily available. The purpose of this study was to investigate the potential of multiple frequency BIA (MFBIA) to monitor changes in body compartments in patients with AN.

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It is estimated that the adult human brain contains 100 billion neurons with 5-10 times as many astrocytes. Although it has been generally considered that the astrocyte is a simple supportive cell to the neuron, recent research has revealed new functionality of the astrocyte in the form of information transfer to neurons of the brain. In our previous work we developed a protocol to pattern the hNT neuron (derived from the human teratocarcinoma cell line (hNT)) on parylene-C/SiO(2) substrates. In this work, we report how we have managed to pattern hNT astrocytes, on parylene-C/SiO(2) substrates to single cell resolution. This article disseminates the nanofabrication and cell culturing steps necessary for the patterning of such cells. In addition, it reports the necessary strip lengths and strip width dimensions of parylene-C that encourage high degrees of cellular coverage and single cell isolation for this cell type. The significance in patterning the hNT astrocyte on silicon chip is that it will help enable single cell and network studies into the undiscovered functionality of this interesting cell, thus, contributing to closer pathological studies of the human brain.

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To directly assess the binding of exogenous peptides to cell surface-associated MHC class I molecules at the single cell level, we examined the possibility of combining the use of biotinylated peptide derivatives with an immunofluorescence detection system based on flow cytometry. Various biotinylated derivatives of the adenovirus 5 early region 1A peptide 234-243, an antigenic peptide recognized by CTL in the context of H-2Db, were first screened in functional assays for their ability to bind efficiently to Db molecules on living cells. Suitable peptide derivatives were then tested for their ability to generate positive fluorescence signals upon addition of phycoerythrin-labeled streptavidin to peptide derivative-bearing cells. Strong fluorescent staining of Db-expressing cells was achieved after incubation with a peptide derivative containing a biotin group at the C-terminus. Competition experiments using the unmodified parental peptide as well as unrelated peptides known to bind to Kd, Kb, or Db, respectively, established that binding of the biotinylated peptide to living cells was Db-specific. By using Con A blasts derived from different H-2 congenic mouse strains, it could be shown that the biotinylated peptide bound only to Db among > 20 class I alleles tested. Moreover, binding of the biotinylated peptide to cells expressing the Dbm13 and Dbm14 mutant molecules was drastically reduced compared to Db. Binding of the biotinylated peptide to freshly isolated Db+ cells was readily detectable, allowing direct assessment of the relative amount of peptide bound to distinct lymphocyte subpopulations by three-color flow cytometry. While minor differences between peripheral T and B cells could be documented, thymocytes were found to differ widely in their peptide binding activity. In all cases, these differences correlated positively with the differential expression of Db at the cell surface. Finally, kinetic studies at different temperatures strongly suggested that the biotinylated peptide first associated with Db molecules available constitutively at the cell surface and then with newly arrived Db molecules.

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It is estimated that the adult human brain contains 100 billion neurons with 5–10 times as many astrocytes. Although it has been generally considered that the astrocyte is a simple supportive cell to the neuron, recent research has revealed new functionality of the astrocyte in the form of information transfer to neurons of the brain. In our previous work we developed a protocol to pattern the hNT neuron (derived from the human teratocarcinoma cell line (hNT)) on parylene-C/SiO2 substrates. In this work, we report how we have managed to pattern hNT astrocytes, on parylene-C/SiO2 substrates to single cell resolution. This article disseminates the nanofabrication and cell culturing steps necessary for the patterning of such cells. In addition, it reports the necessary strip lengths and strip width dimensions of parylene-C that encourage high degrees of cellular coverage and single cell isolation for this cell type. The significance in patterning the hNT astrocyte on silicon chip is that it will help enable single cell and network studies into the undiscovered functionality of this interesting cell, thus, contributing to closer pathological studies of the human brain.

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With the increasing production and use of engineered nanoparticles it is crucial that their interaction with biological systems is understood. Due to the small size of nanoparticles, their identification and localization within single cells is extremely challenging. Therefore, various cutting-edge techniques are required to detect and to quantify metals, metal oxides, magnetic, fluorescent, as well as electron-dense nanoparticles. Several techniques will be discussed in detail, such as inductively coupled plasma atomic emission spectroscopy, flow cytometry, laser scanning microscopy combined with digital image restoration, as well as quantitative analysis by means of stereology on transmission electron microscopy images. An overview will be given regarding the advantages of those visualization/quantification systems, including a thorough discussion about limitations and pitfalls.

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Organismal development, homeostasis, and pathology are rooted in inherently probabilistic events. From gene expression to cellular differentiation, rates and likelihoods shape the form and function of biology. Processes ranging from growth to cancer homeostasis to reprogramming of stem cells all require transitions between distinct phenotypic states, and these occur at defined rates. Therefore, measuring the fidelity and dynamics with which such transitions occur is central to understanding natural biological phenomena and is critical for therapeutic interventions.

While these processes may produce robust population-level behaviors, decisions are made by individual cells. In certain circumstances, these minuscule computing units effectively roll dice to determine their fate. And while the 'omics' era has provided vast amounts of data on what these populations are doing en masse, the behaviors of the underlying units of these processes get washed out in averages.

Therefore, in order to understand the behavior of a sample of cells, it is critical to reveal how its underlying components, or mixture of cells in distinct states, each contribute to the overall phenotype. As such, we must first define what states exist in the population, determine what controls the stability of these states, and measure in high dimensionality the dynamics with which these cells transition between states.

To address a specific example of this general problem, we investigate the heterogeneity and dynamics of mouse embryonic stem cells (mESCs). While a number of reports have identified particular genes in ES cells that switch between 'high' and 'low' metastable expression states in culture, it remains unclear how levels of many of these regulators combine to form states in transcriptional space. Using a method called single molecule mRNA fluorescent in situ hybridization (smFISH), we quantitatively measure and fit distributions of core pluripotency regulators in single cells, identifying a wide range of variabilities between genes, but each explained by a simple model of bursty transcription. From this data, we also observed that strongly bimodal genes appear to be co-expressed, effectively limiting the occupancy of transcriptional space to two primary states across genes studied here. However, these states also appear punctuated by the conditional expression of the most highly variable genes, potentially defining smaller substates of pluripotency.

Having defined the transcriptional states, we next asked what might control their stability or persistence. Surprisingly, we found that DNA methylation, a mark normally associated with irreversible developmental progression, was itself differentially regulated between these two primary states. Furthermore, both acute or chronic inhibition of DNA methyltransferase activity led to reduced heterogeneity among the population, suggesting that metastability can be modulated by this strong epigenetic mark.

Finally, because understanding the dynamics of state transitions is fundamental to a variety of biological problems, we sought to develop a high-throughput method for the identification of cellular trajectories without the need for cell-line engineering. We achieved this by combining cell-lineage information gathered from time-lapse microscopy with endpoint smFISH for measurements of final expression states. Applying a simple mathematical framework to these lineage-tree associated expression states enables the inference of dynamic transitions. We apply our novel approach in order to infer temporal sequences of events, quantitative switching rates, and network topology among a set of ESC states.

Taken together, we identify distinct expression states in ES cells, gain fundamental insight into how a strong epigenetic modifier enforces the stability of these states, and develop and apply a new method for the identification of cellular trajectories using scalable in situ readouts of cellular state.

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Objective: To investigate measures aimed at defining the nutritional status of cystic fibrosis (CF) populations, this study compared standard anthropometric measurements and total body potassium (TBK) as indicators of malnutrition. Methods: Height, weight, and TBK measurements of 226 children with CF from Royal Children's Hospital, Brisbane, Australia, were analyzed. Z scores for height for age, weight for age, and weight for height were analyzed by means of the National Centre for Health Statistics reference. TBK was measured by means of whole body counting and compared with predicted TBK for age. Two criteria were evaluated with respect to malnutrition: (1) a z score < -2.0 and (2) a TBK for age <80% of predicted. Results: Males and females with CF had lower mean height-for-age and weight-for-age z scores than the National Centre for Health Statistics reference (P < .01), but mean weight-for-height z score was not significantly different. There were no significant gender differences. According to anthropometry, only 7.5% of this population were underweight and 7.6% were stunted. However, with TBK as an indicator of nutritional status, 29.9% of males and 22.0% of females were malnourished. Conclusion: There are large differences in the percentage of patients with CF identified as malnourished depending on whether anthropometry or body composition data are used as the nutritional indicator. At an individual level, weight-based indicators are not sensitive indicators of suboptimal nutritional status in CF, significantly underestimating the extent of malnutrition. Current recommendations in which anthropometry is used as the indicator of malnutrition in CF should be revised.

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The goal of this paper is to provide some insight into the relations that exist between cell level and message level performance guarantees in the context of ATM networks. Cell level guarantees are typically what the network is capable of providing, while message level guarantees are the ones of interest to users. It is, therefore, important to understand how the two are related, and which factors influence this relation. There are many different performance measures that are of importance, and in this paper we try to touch on the (three) most relevant ones. This includes comparing cell and message loss probabilities, average cell and message delays, and cell and message jitter. Specifically, we show that cell and message loss probabilities can exhibit significant differences, which strongly depend on traffic characteristics such as peak rate and burst size, i.e., for a fixed cell loss probability, the message loss probability can greatly vary when peak rate and burst size change. One reason for this sensitivity, is that message loss depends on what happen to all the cells in a message. For delay and jitter, we also find that peak rate and burst size play a role in determining the relation between cell and message performance. However, this sensitivity is not as acute as with losses since message delay and jitter are typically determined by the performance seen by only one cell, the last cell in a message. In the paper, we provide quantitative examples that illustrate the range of behaviors and identify the impact of different parameters.

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The juxtaglomerular cell tumor is a cause of secondary hypertension in adults. A 35-year-old female patient suffering from hypertension and low serum potassium had a 3 × 3 cm solid mass at the lower pole of left kidney diagnosed by abdominal sonography. Partial nephrectomy was performed and the postoperatory was uneventful. Normalization of blood pressure was observed within the first month.

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We study MCF-7 breast cancer cell movement in a transwell apparatus. Various experimental conditions lead to a variety of monotone and nonmonotone responses which are difficult to interpret. We anticipate that the experimental results could be caused by cell-to-cell adhesion or volume exclusion. Without any modeling, it is impossible to understand the relative roles played by these two mechanisms. A lattice-based exclusion process random-walk model incorporating agent-to-agent adhesion is applied to the experimental system. Our combined experimental and modeling approach shows that a low value of cell-to-cell adhesion strength provides the best explanation of the experimental data suggesting that volume exclusion plays a more important role than cell-to-cell adhesion. This combined experimental and modeling study gives insight into the cell-level details and design of transwell assays.

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Cell migration is a behaviour critical to many key biological effects, including wound healing, cancerous cell invasion and morphogenesis, the development of an organism from an embryo. However, given that each of these situations is distinctly different and cells are extremely complicated biological objects, interest lies in more basic experiments which seek to remove conflating factors and present a less complex environment within which cell migration can be experimentally examined. These include in vitro studies like the scratch assay or circle migration assay, and ex vivo studies like the colonisation of the hindgut by neural crest cells. The reduced complexity of these experiments also makes them much more enticing as problems to mathematically model, like done here. The primary goal of the mathematical models used in this thesis is to shed light on which cellular behaviours work to generate the travelling waves of invasion observed in these experiments, and to explore how variations in these behaviours can potentially predict differences in this invasive pattern which are experimentally observed when cell types or chemical environment are changed. Relevant literature has already identified the difficulty of distinguishing between these behaviours when using traditional mathematical biology techniques operating on a macroscopic scale, and so here a sophisticated individual-cell-level model, an extension of the Cellular Potts Model (CPM), is been constructed and used to model a scratch assay experiment. This model includes a novel mechanism for dealing with cell proliferations that allowed for the differing properties of quiescent and proliferative cells to be implemented into their behaviour. This model is considered both for its predictive power and used to make comparisons with the travelling waves which result in more traditional macroscopic simulations. These comparisons demonstrate a surprising amount of agreement between the two modelling frameworks, and suggest further novel modifications to the CPM that would allow it to better model cell migration. Considerations of the model’s behaviour are used to argue that the dominant effect governing cell migration (random motility or signal-driven taxis) likely depends on the sort of invasion demonstrated by cells, as easily seen by microscopic photography. Additionally, a scratch assay simulated on a non-homogeneous domain consisting of a ’fast’ and ’slow’ region is also used to further differentiate between these different potential cell motility behaviours. A heterogeneous domain is a novel situation which has not been considered mathematically in this context, nor has it been constructed experimentally to the best of the candidate’s knowledge. Thus this problem serves as a thought experiment used to test the conclusions arising from the simulations on homogeneous domains, and to suggest what might be observed should this non-homogeneous assay situation be experimentally realised. Non-intuitive cell invasion patterns are predicted for diffusely-invading cells which respond to a cell-consumed signal or nutrient, contrasted with rather expected behaviour in the case of random-motility-driven invasion. The potential experimental observation of these behaviours is demonstrated by the individual-cell-level model used in this thesis, which does agree with the PDE model in predicting these unexpected invasion patterns. In the interest of examining such a case of a non-homogeneous domain experimentally, some brief suggestion is made as to how this could be achieved.

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The movement of molecules inside living cells is a fundamental feature of biological processes. The ability to both observe and analyse the details of molecular diffusion in vivo at the single-molecule and single-cell level can add significant insight into understanding molecular architectures of diffus- ing molecules and the nanoscale environment in which the molecules diffuse. The tool of choice for monitoring dynamic molecular localization in live cells is fluorescence microscopy, especially so combining total internal reflection fluorescence with the use of fluorescent protein (FP) reporters in offering exceptional imaging contrast for dynamic processes in the cell mem- brane under relatively physiological conditions compared with competing single-molecule techniques. There exist several different complex modes of diffusion, and discriminating these from each other is challenging at the mol- ecular level owing to underlying stochastic behaviour. Analysis is traditionally performed using mean square displacements of tracked particles; however, this generally requires more data points than is typical for single FP tracks owing to photophysical instability. Presented here is a novel approach allowing robust Bayesian ranking of diffusion processes to dis-criminate multiple complex modes probabilistically. It is a computational approach that biologists can use to understand single-molecule features in live cells.

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In this study cell wall properties; moisture distribution, stiffness, thickness and cell dimension have been taken into consideration. Cell wall stiffness dependent on complex combination of plant cell microstructures, composition and water holding capacity of the cell. In this work, some preliminary steps taken by investing cell wall properties of apple in order to predict change of porosity and shrinkage during drying. Two different types of apple cell wall characteristic were investigated to correlate with porosity and shrinkage after convective drying. A scanning electron microscope (SEM), 2N Intron, a pyncometer and image J software were used in order to measure and analyze cell characteristics, water dynamics, porosity and shrinkage. Cell stiffness of red delicious apple was found higher than granny smith apples. A significant relationship has found between cell wall characteristics and both heat and mass transfer. Consequently, evolution of porosity and shrinkage noticeably influenced during convective drying by the nature of cell wall. This study has brought better understanding of porosity and shrinkage of dried food stuff in microscopic (cell) level and would provide better insight to attain energy effective drying process and quality food stuff.