Fluorescent carbon dioxide indicators

Over the last decade, fluorescence has become the dominant tool in biotechnology and medical imaging. These exciting advances have been underpinned by the advances in time-resolved techniques and instrumentation, probe design, chemical / biochemical sensing, coupled with our furthered knowledge in biology. Complementary volumes 9 and 10, Advanced Concepts of Fluorescence Sensing: Small Molecule Sensing and Advanced Concepts of Fluorescence Sensing: Macromolecular Sensing, aim to summarize the current state of the art in fluorescent sensing. For this reason, Drs. Geddes and Lakowicz have invited chapters, encompassing a broad range of fluorescence sensing techniques. Some chapters deal with small molecule sensors, such as for anions, cations, and CO2, while others summarize recent advances in protein-based and macromolecular sensors. The Editors have, however, not included DNA or RNA based sensing in this volume, as this were reviewed in Volume 7 and is to be the subject of a more detailed volume in the near future

Earthquake catalog-based machine learning identification of laboratory fault states and the effects of magnitude of completeness

Machine learning regression can predict macroscopic fault properties such as shear stress, friction, and time to failure using continuous records of fault zone acoustic emissions. Here we show that a similar approach is successful using event catalogs derived from the continuous data. Our methods are applicable to catalogs of arbitrary scale and magnitude of completeness. We investigate how machine learning regression from an event catalog of laboratory earthquakes performs as a function of the catalog magnitude of completeness. We find that strong model performance requires a sufficiently low magnitude of completeness, and below this magnitude of completeness, model performance saturates

Building nonparametric nn-body force fields using Gaussian process regression

Constructing a classical potential suited to simulate a given atomic system is a remarkably difficult task. This chapter presents a framework under which this problem can be tackled, based on the Bayesian construction of nonparametric force fields of a given order using Gaussian process (GP) priors. The formalism of GP regression is first reviewed, particularly in relation to its application in learning local atomic energies and forces. For accurate regression it is fundamental to incorporate prior knowledge into the GP kernel function. To this end, this chapter details how properties of smoothness, invariance and interaction order of a force field can be encoded into corresponding kernel properties. A range of kernels is then proposed, possessing all the required properties and an adjustable parameter $n$ governing the interaction order modelled. The order $n$ best suited to describe a given system can be found automatically within the Bayesian framework by maximisation of the marginal likelihood. The procedure is first tested on a toy model of known interaction and later applied to two real materials described at the DFT level of accuracy. The models automatically selected for the two materials were found to be in agreement with physical intuition. More in general, it was found that lower order (simpler) models should be chosen when the data are not sufficient to resolve more complex interactions. Low $n$ GPs can be further sped up by orders of magnitude by constructing the corresponding tabulated force field, here named "MFF".Comment: 31 pages, 11 figures, book chapte

Volatile and glycosidically bound composition of Loureiro and Alvarinho wines

Composition of Loureiro and Alvarinho wines from the Vinhos Verdes region, respecting free volatile compounds as well as glycosidically bound aroma precursors, was exhaustively determined by GC-MS after adsorption on XAD-2 resin. On the whole, were identified and quantified 120 volatile compounds in the free fraction and 77 glycosidically bound compounds, belonging to C6-compounds, alcohols, fatty acids ethyl esters, esters of organic acids, acetates, monoterpenic alcohols, monoterpenic oxides and diols, C13-norisoprenoids, volatile phenols, volatile fatty acids and carbonyl compounds. Globally, the wines of the two cultivars present similar composition on volatiles. However, respecting varietal compounds, Loureiro wines are richer than Alvarinho ones with regard to C6-compounds and monoterpenic compounds, occurring the opposite for volatile phenols. It was also demonstrate that wines of both varieties may benefit the aroma reserve, present as glycoconjugates, as it is susceptible of being technologically explored. Linalool, Ho-trienol, α-terpineol, contributing with fruity and floral notes, and β-damascenone mostly for Alvarinho, confering tropical fruit notes, are the varietal compounds which may particularly influence the aroma of these wines. Respecting fermentative compounds, Alvarinho is also particularly rich in fatty acids ethyl esters related to lipid metabolism and acetates of fusel alcohols, which can provide it a fruity character; Loureiro contains higher levels of esters of organic acids and 2-phenylethanol, conferring fruity and floral notes. Sensory analysis agree with chemical analyses showing a pronounced tree and tropical fruit character for Alvarinho wines while Loureiro wines present more intense citrus fruit notes.Centre of Biological Engineering of Universidade do Minho; Estação Vitivinícola Amândio Galhano (EVAG); Solar de Serrade; EVAG; Comissão de Viticultura da Região dos Vinhos Verdes

From DNA sequence to application: possibilities and complications

The development of sophisticated genetic tools during the past 15 years have facilitated a tremendous increase of fundamental and application-oriented knowledge of lactic acid bacteria (LAB) and their bacteriophages. This knowledge relates both to the assignments of open reading frames (ORF’s) and the function of non-coding DNA sequences. Comparison of the complete nucleotide sequences of several LAB bacteriophages has revealed that their chromosomes have a fixed, modular structure, each module having a set of genes involved in a specific phase of the bacteriophage life cycle. LAB bacteriophage genes and DNA sequences have been used for the construction of temperature-inducible gene expression systems, gene-integration systems, and bacteriophage defence systems. The function of several LAB open reading frames and transcriptional units have been identified and characterized in detail. Many of these could find practical applications, such as induced lysis of LAB to enhance cheese ripening and re-routing of carbon fluxes for the production of a specific amino acid enantiomer. More knowledge has also become available concerning the function and structure of non-coding DNA positioned at or in the vicinity of promoters. In several cases the mRNA produced from this DNA contains a transcriptional terminator-antiterminator pair, in which the antiterminator can be stabilized either by uncharged tRNA or by interaction with a regulatory protein, thus preventing formation of the terminator so that mRNA elongation can proceed. Evidence has accumulated showing that also in LAB carbon catabolite repression in LAB is mediated by specific DNA elements in the vicinity of promoters governing the transcription of catabolic operons. Although some biological barriers have yet to be solved, the vast body of scientific information presently available allows the construction of tailor-made genetically modified LAB. Today, it appears that societal constraints rather than biological hurdles impede the use of genetically modified LAB.