Biotransformations Performed by Yeasts on Aromatic Compounds Provided by Hop—A Review

The biodiversity of some Saccharomyces (S.) strains for fermentative activity and metabolic capacities is an important research area in brewing technology. Yeast metabolism can render simple beers very elaborate. In this review, we examine much research addressed to the study of how different yeast strains can influence aroma by chemically interacting with specific aromatic compounds (mainly terpenes) from the hop. These reactions are commonly referred to as biotransformations. Exploiting biotransformations to increase the product’s aroma and use less hop goes exactly in the direction of higher sustainability of the brewing process, as the hop generally represents the highest part of the raw materials cost, and its reduction allows to diminish its environmental impact

Dip Hopping Technique and Yeast Biotransformations in Craft Beer Productions

This paper evaluates the effects of an alternative hopping technique, called dip hopping, on beer. This technique involves infusing hops in hot water (or in a portion of wort) and subsequently combining the infusion with the wort (after wort cooling) directly in the fermenter when the yeast is added for fermentation. The reference beers were produced employing the “traditional” late hopping technique, and the experimental beers were produced using the dip hopping technique. A variety of hops with a significant concentration of essential oil and a strain of yeast with high β-glucosidic activity capable of releasing aromatic molecules from precursors supplied by hops were used. The samples were analysed in terms of alcohol content, degree of attenuation, colour, and bitterness. Sensory analysis and gas chromatography analysis were also performed. The data showed statistically significant differences between the reference beers and the experimental beers, with the latter featuring greater hints of citrus, fruity, floral, and spicy aromas. As an overall effect, there was an increase in the olfactory and gustatory pleasantness of the beers produced with the dip hopping technique

Screen-detected vs clinical breast cancer: the advantage in the relative risk of lymph node metastases decreases with increasing tumour size

Screen-detected (SD) breast cancers are smaller and biologically more indolent than clinically presenting cancers. An often debated question is: if left undiagnosed during their preclinical phase, would they become more aggressive or would they only increase in size? This study considered a registry-based series (1988–1999) of 3329 unifocal, pT1a-pT3 breast cancer cases aged 50–70 years, of which 994 were SD cases and 2335 clinical cases. The rationale was that (1) the average risk of lymph node involvement (N+) is lower for SD cases, (2) nodal status is the product of biological aggressiveness and chronological age of the disease, (3) for any breast cancer, tumour size is an indicator of chronological age, and (4) for SD cases, tumour size is specifically an indicator of the duration of the preclinical phase, that is, an inverse indicator of lead time. The hypothesis was that the relative protection of SD cases from the risk of N+ and, thus, their relative biological indolence decrease with increasing tumour size. The odds ratio (OR) estimate of the risk of N+ was obtained from a multiple logistic regression model that included terms for detection modality, tumour size category, patient age, histological type, and number of lymph nodes recovered. A term for the detection modality-by-tumour size category interaction was entered, and the OR for the main effect of detection by screening vs clinical diagnosis was calculated. This increased linearly from 0.05 (95% confidence interval: 0.01–0.39) in the 2–7 mm size category to 0.95 (0.64–1.40) in the 18–22 mm category. This trend is compatible with the view that biological aggressiveness of breast cancer increases during the preclinical phase

Nonextensive Thermostatistics and the H-Theorem

The kinetic foundations of Tsallis' nonextensive thermostatistics are investigated through Boltzmann's transport equation approach. Our analysis follows from a nonextensive generalization of the ``molecular chaos hypothesis". For $q>0$, the $q$-transport equation satisfies an $H$-theorem based on Tsallis entropy. It is also proved that the collisional equilibrium is given by Tsallis' $q$-nonextensive velocity distribution.Comment: 4 pages, no figures, corrected some typo

A Dynamic Approach to the Thermodynamics of Superdiffusion

We address the problem of relating thermodynamics to mechanics in the case of microscopic dynamics without a finite time scale. The solution is obtained by expressing the Tsallis entropic index q as a function of the Levy index alpha, and using dynamical rather than probabilistic arguments.Comment: 4 pages, new revised version resubmitted to Phys. Rev. Let

Average Entropy of a Subsystem from its Average Tsallis Entropy

In the nonextensive Tsallis scenario, Page's conjecture for the average entropy of a subsystem[Phys. Rev. Lett. {\bf 71}, 1291(1993)] as well as its demonstration are generalized, i.e., when a pure quantum system, whose Hilbert space dimension is $mn$, is considered, the average Tsallis entropy of an $m$-dimensional subsystem is obtained. This demonstration is expected to be useful to study systems where the usual entropy does not give satisfactory results.Comment: Revtex, 6 pages, 2 figures. To appear in Phys. Rev.

L\'{e}vy scaling: the Diffusion Entropy Analysis applied to DNA sequences

We address the problem of the statistical analysis of a time series generated by complex dynamics with a new method: the Diffusion Entropy Analysis (DEA) (Fractals, {\bf 9}, 193 (2001)). This method is based on the evaluation of the Shannon entropy of the diffusion process generated by the time series imagined as a physical source of fluctuations, rather than on the measurement of the variance of this diffusion process, as done with the traditional methods. We compare the DEA to the traditional methods of scaling detection and we prove that the DEA is the only method that always yields the correct scaling value, if the scaling condition applies. Furthermore, DEA detects the real scaling of a time series without requiring any form of de-trending. We show that the joint use of DEA and variance method allows to assess whether a time series is characterized by L\'{e}vy or Gauss statistics. We apply the DEA to the study of DNA sequences, and we prove that their large-time scales are characterized by L\'{e}vy statistics, regardless of whether they are coding or non-coding sequences. We show that the DEA is a reliable technique and, at the same time, we use it to confirm the validity of the dynamic approach to the DNA sequences, proposed in earlier work.Comment: 24 pages, 9 figure

Reply: An inverse association between tumour size and overdiagnosis may explain the results by Bucchi et al

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A novel approach to quantify random error explicitly in epidemiological studies

The most frequently used methods for handling random error are largely misunderstood or misused by researchers. We propose a simple approach to quantify the amount of random error which does not require solid background in statistics for its proper interpretation. This method may help researchers refrain from oversimplistic interpretations relying on statistical significance

Tomato: a crop species amenable to improvement by cellular and molecular methods

Tomato is a crop plant with a relatively small DNA content per haploid genome and a well developed genetics. Plant regeneration from explants and protoplasts is feasable which led to the development of efficient transformation procedures. In view of the current data, the isolation of useful mutants at the cellular level probably will be of limited value in the genetic improvement of tomato. Protoplast fusion may lead to novel combinations of organelle and nuclear DNA (cybrids), whereas this technique also provides a means of introducing genetic information from alien species into tomato. Important developments have come from molecular approaches. Following the construction of an RFLP map, these RFLP markers can be used in tomato to tag quantitative traits bred in from related species. Both RFLP's and transposons are in the process of being used to clone desired genes for which no gene products are known. Cloned genes can be introduced and potentially improve specific properties of tomato especially those controlled by single genes. Recent results suggest that, in principle, phenotypic mutants can be created for cloned and characterized genes and will prove their value in further improving the cultivated tomato.