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.     

Synthesis, characterization and photophysical properties of mixed ligand tris(polypyridyl)chromium(III) complexes, [Cr(phen)2L]

A series of new heteroleptic, tris(polypyridyl)chromium(III) complexes, [Cr(phen)₂L]³⁺ (L = substituted phenanthrolines or bipyridines), has been prepared and characterized, and their photophyical properties in a number of solvents have been investigated. X-ray crystallography measurements confirmed that the cationic (3+) units contain only one ligand L plus two phenanthroline ligands. Electrochemical and photophysical data showed that both ground state potentials and lifetime decays are sensitive to ligand structure and the nature of the solvent with the exception of compounds containing L = 5-amino-1,10-phenanthroline (aphen) and 2,2′-bipyrimidine (bpm). Addition of electron-donating groups in the ligand structure shifts redox potentials to more negative values than those observed for the parent compound, [Cr(phen)₃]³⁺. Emission decays show a complex dependence with the solvent. The longest lifetime was observed for [Cr(phen)₂(dip)]³⁺ (dip = 4,7-diphenylphenanthroline) in air-free aqueous solutions, τ = 273 μs. Solvent effects are explained in terms of the affinity of hydrophobic complexes for non-polar solvent molecules and the solvent microstructure surrounding chromium units.     

Advanced Cell Mapping Visualizations for Single Cell Functional Proteomics Enabling Patient Stratification

Highly multiplexed single‐cell functional proteomics has emerged as one of the next‐generation toolkits for a deeper understanding of functional heterogeneity in cell. Different from the conventional population‐based bulk and single‐cell RNA‐Seq assays, the microchip‐based proteomics at the single‐cell resolution enables a unique identification of highly polyfunctional cell subsets that co‐secrete many proteins from live single cells and most importantly correlate with patient response to a therapy. The 32‐plex IsoCode chip technology has defined a polyfunctional strength index (PSI) of pre‐infusion anti‐CD19 chimeric antigen receptor (CAR)‐T products, that is significantly associated with patient response to the CAR‐T cell therapy. To complement the clinical relevance of the PSI, a comprehensive visualization toolkit of 3D uniform manifold approximation and projection (UMAP) and t‐distributed stochastic neighbor embedding (t‐SNE) in a proteomic analysis pipeline is developed, providing more advanced analytical algorithms for more intuitive data visualizations. The UMAP and t‐SNE of anti‐CD19 CAR‐T products reveal distinct cytokine profiles between nonresponders and responders and demonstrate a marked upregulation of antitumor‐associated cytokine signatures in CAR‐T cells from responding patients. Using this powerful while user‐friendly analytical tool, the multi‐dimensional single‐cell data can be dissected from complex immune responses and uncover underlying mechanisms, which can promote correlative biomarker discovery, improved bioprocessing, and personalized treatment development.     

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.