Biosensors based on peptide exposure show single molecule conformations in live cells

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A random fatigue of mechanize titanium abutment studied with Markoff chain and stochastic finite element formulation

To measure fatigue in dental implants and in its components, it is necessary to use a probabilistic analysis since the randomness in the output depends on a number of parameters (such as fatigue properties of titanium and applied loads, unknown beforehand as they depend on mastication habits). The purpose is to apply a probabilistic approximation in order to predict fatigue life, taking into account the randomness of variables. More accuracy on the results has been obtained by taking into account different load blocks with different amplitudes, as happens with bite forces during the day and allowing us to know how effects have different type of bruxism on the piece analysed.     

Noise-induced neural impulses

The firing pattern of neural pulses often show the following features: the shapes of individual pulses are nearly identical and frequency independent; the firing frequency can vary over a broad range; the time period between pulses shows a stochastic scatter. This behaviour cannot be understood on the basis of a deterministic non-linear dynamic process, e.g. the Bonhoeffer-van der Pol model. We demonstrate in this paper that a noise term added to the Bonhoeffer-van der Pol model can reproduce the firing patterns of neurons very well. For this purpose we have considered the Fokker-Planck equation corresponding to the stochastic Bonhoeffer-van der Pol model. This equation has been solved by a new Monte Carlo algorithm. We demonstrate that the ensuing distribution functions represent only the global characteristics of the underlying force field: lines of zero slope which attract nearby trajectories prove to be the regions of phase space where the distributions concentrate their amplitude. Since there are two such lines the distributions are bimodal representing repeated fluctuations between two lines of zero slope. Even in cases where the deterministic Bonhoeffer-van der Pol model does not show limit cycle behaviour the stochastic system produces a limit cycle. This cycle can be identified with the firing of neural pulses.     

Stochastic resonance as a possible mechanism of amplification of weak electric signals in living cells

The most important but still unresolved problem in bioelectromagnetics is the interaction of weak electromagnetic fields (EMFs) with living cells. Thermal and other types of noise pose restrictions in cell detection of weak signals. As a consequence, some extant experimental results that indicate low-intensity field effects cannot be accounted for, and this renders the results themselves questionable. One way out of this dead end is to search for possible mechanisms of signal amplification. In this paper, we discuss a general mechanism in which a weak signal is amplified by system noise itself. This mechanism was discovered several years ago in physics and is known, in its simplest form, as a stochastic resonance. It was shown that signal amplification may exceed a factor of 1000, which renders existing estimations of EMF thresholds highly speculative. The applicability of the stochastic resonance concept to cells is discussed particularly with respect to the possible role of the cell membrane in the amplification process. © 1994 Wiley-Liss, Inc.     

Enantioanalysis of tryptophan in whole blood samples using stochastic sensors—A screening test for gastric cancer

Tryptophan is a key amino acid related to metabolomics in gastric cancer. To date, methods were developed only for the assay of l -tryptophan, the role of d -tryptophan being not yet established. Therefore, four stochastic sensors based on different graphene materials modified with β-cyclodextrins, 2,2-diphenyl-1-picrylhydrazyl, and protoporphyrin IX were designed and used for enantioanalysis of tryptophan in whole blood samples. High sensitivities, and reliabilities were recorded when the stochastic sensors were used for the enantioanalysis of tryptophan in whole blood samples. The paper opened a new chapter in early detection of gastric cancer, based on establishing the role of d -tryptophan in metabolomics, and in early diagnosis of gastric cancer.     

Geographical vs. ecological diversification in Carex section Phacocystis (Cyperaceae): Patterns hidden behind a twisted taxonomy

Carex section Phacocystis (Cyperaceae) is one of the most diverse and taxonomically complex groups of sedges (between 116 and 147 species), with a worldwide distribution in a wide array of biomes. It has a very complicated taxonomic history, with numerous disagreements among different treatments. We studied the biogeography and niche evolution in a phylogenetic framework to unveil the relative contribution of geographical and ecological drivers to diversification of the group. We used a large species sampling of the section (82% of extant species) to build a phylogeny based on four DNA regions, constrained with a phylogenomic HybSeq tree and dated with six fossil calibrations. Our phylogenetic results recovered section Phacocystis s.s. (core Phacocystis) as sister to section Praelongae. Ancestral area reconstruction points toward the N Pacific as the cradle for the crown diversification of section Phacocystis during the Middle Miocene. Wide distributions were recurrently inferred across deep nodes. Large Northern Hemisphere lineages with geographical congruence were retrieved, pointing toward the importance of allopatric divergence at deep phylogenetic levels, whereas within-area speciation emerges as the predominant pattern at shallow phylogenetic level. The Southern Hemisphere (Neotropics, SW Pacific) was colonized several times from the Northern Hemisphere. The global expansion of Carex section Phacocystis did not entail major ecological changes along the inner branches of the phylogeny. Nevertheless, ecological differentiation seems to gain importance toward recent times.     

Stochastic multi-scale prediction on the apparent elastic moduli of trabecular bone considering uncertainties of biological apatite (BAp) crystallite orientation and image-based modelling

An assessment of the mechanical properties of trabecular bone is important in determining the fracture risk of human bones. Many uncertainty factors contribute to the dispersion of the estimated mechanical properties of trabecular bone. This study was undertaken in order to propose a computational scheme that will be able to predict the effective apparent elastic moduli of trabecular bone considering the uncertainties that are primarily caused by image-based modelling and trabecular stiffness orientation. The effect of image-based modelling which focused on the connectivity was also investigated. A stochastic multi-scale method using a first-order perturbation-based and asymptotic homogenisation theory was applied to formulate the stochastically apparent elastic properties of trabecular bone. The effective apparent elastic modulus was predicted with the introduction of a coefficient factor to represent the variation of bone characteristics due to inter-individual differences. The mean value of the predicted effective apparent Young's modulus in principal axis was found at approximately 460 MPa for respective 15.24% of bone volume fraction, and this is in good agreement with other experimental results. The proposed method may provide a reference for the reliable evaluation of the prediction of the apparent elastic properties of trabecular bone.