Studies on somaclonal variation in Phalaenopsis

The morphological and genetic variations in somaclones of Phalaenopsis True Lady “B79-19” derived from tissue culture were evaluated. In 1360 flowering somaclones, no apparent difference was found in the shape of the leaves, whereas flowers in some somaclones were deformed. We have demonstrated that 38 selected random primers can be used to generate amplified segments of genomic DNA and to differentiate polymorphisms of somaclonal variations in Phalaenopsis. The random amplified polymorphic DNA (RAPD) data indicated that normal and variant somaclones are not genetically identical. We also studied the banding patterns of aspartate aminotransferase (AAT) and phosphoglucomutase (PGM) in young leaves of variant and normal somaclones of Phalaenopsis. With respect to AAT, three distinct banding patterns were found in normal somaclones and only two-banded phenotypes were detected in variant somaclones. In a comparison of the banding patterns of PGM isozymes, three to four bands were detected in normal somaclones and two to three bands in variant ones. Received: 15 August 1997 / Revision received: 16 February 1998 / Accepted: 1 May 1998     

Path tortuosity of Eurasian badgers (<Emphasis Type="Italic">Meles meles</Emphasis>) in a heterogeneous Mediterranean landscape

Movement is the process by which individual organisms are displaced over time to eat, reproduce and defend resources. Fractal analysis is a technique used to study animal movement that measures spatial complexity of path tortuosity; here, we apply it to characterize the movement patterns of the Eurasian badger (Meles meles) in a Mediterranean landscape. We calculated path tortuosity overall and seasonally, and for individuals of different sexes and social groups. The influence of variables related to badgers’ resources (food, shelter, water), human infra-structures and weather conditions were analysed with respect to the tortuosity of each badger’s path. A total of 55 search paths from six badgers were considered for this study. Although badgers generally displayed convoluted movement, there were two exceptions: (a) males overall and (b) all badgers in summer; for both, movements had a lower fractal value, i.e. were less tortuous. The convoluted movement pattern generally observed is probably adapted to the clumped distribution of food in the study area. Nevertheless, our results suggest that the use of dens and latrines were the principal determinants of tortuosity of badgers’ paths while foraging.     

Sufficiency of the number of segregating sites in the limit under finite-sites mutation

We show that the number of segregating sites is a sufficient statistic for the scaled mutation parameter (θ) in the limit as the number of sites tends to infinity and there is free recombination between sites. We assume that the mutation parameter at each site tends to zero such than the total mutation parameter (θ) is constant in the limit. Our results show that Watterson’s estimator is the maximum likelihood estimator in this case, but that it estimates a composite parameter which is different for different mutation models. Some of our results hold when recombination is limited, because Watterson’s estimator is an unbiased, method-of-moments estimator regardless of the recombination rate. The quantity it estimates depends on the details of how mutations occur at each site.     

冻融作用对土壤温室气体产生与排放的影响

土壤冻融交替是中、高纬度和高海拔地区常见的自然现象,土壤在冻融期间会经历一系列物理、化学和生物变化过程。有研究表明,冻融区土壤是温室气体的重要排放源,冻融期土壤温室气体的排放量在全年总排放量中占有重要的份额,尤其是N2O。随着全球气候变暖,部分地区的土壤环境将经受更广泛和频繁的冻融交替作用,这会导致土壤温室气体排放量增加,从而又进一步促进了气候变暖。本文重点概述了冻融作用对土壤温室气体产生与排放的影响及其主要影响机制,并简要提出了目前土壤冻融研究中的一些不足以及今后值得关注和深入研究的科学问题。     

A machine learning approach for the prediction of protein surface loop flexibility

Proteins often undergo conformational changes when binding to each other. A major fraction of backbone conformational changes involves motion on the protein surface, particularly in loops. Accounting for the motion of protein surface loops represents a challenge for protein-protein docking algorithms. A first step in addressing this challenge is to distinguish protein surface loops that are likely to undergo backbone conformational changes upon protein-protein binding (mobile loops) from those that are not (stationary loops). In this study, we developed a machine learning strategy based on support vector machines (SVMs). Our SVM uses three features of loop residues in the unbound protein structures-Ramachandran angles, crystallographic B-factors, and relative accessible surface area-to distinguish mobile loops from stationary ones. This method yields an average prediction accuracy of 75.3% compared with a random prediction accuracy of 50%, and an average of 0.79 area under the receiver operating characteristic (ROC) curve using cross-validation. Testing the method on an independent dataset, we obtained a prediction accuracy of 70.5%. Finally, we applied the method to 11 complexes that involve members from the Ras superfamily and achieved prediction accuracy of 92.8% for the Ras superfamily proteins and 74.4% for their binding partners.     

Introducing digital tools for sustainable food supply management: Tackling food loss and waste in industrial canteens

Reducing food waste is essential if we want to create a more sustainable food system, which is why halving per capita food waste by 2030 has been included in the UN Sustainable Development Goals. The main aim of this paper is to demonstrate that by using digital tools to monitor food provisioning and management within canteens, it is possible to achieve a more sustainable food service management within industrial companies and to reduce the overall quantity and environmental impacts of food preparation and consumption thus achieving economic benefits. Longitudinal 2018 and 2019 data collected from the canteen of a major Italian food production company were analyzed. The results showed that the amount of food lost and wasted has decreased over time, reaping important environmental benefits and illustrating specific differences between the food lost in meal preparation and the food left on employees’ plates. It is therefore important to implement education initiatives and to use digital tools to share food-related data collected within companies among both employees and kitchen and catering staff in order to raise awareness of their behavioral strengths and weaknesses. From this perspective, new interventions at both kitchen and customer/worker levels are introduced and discussed.     

Molecular Dynamics Simulation of Dioxygen Pathways through Mini Singlet Oxygen Generator (miniSOG), a Genetically Encoded Marker and Killer Protein

In this work, molecular dynamics (MD) simulations of the permeation of proteins by small gases of biological significance have been extended from gas carrier, sensor, and enzymatic proteins to genetically encoded tags and killer proteins. To this end, miniSOG was taken as an example of current high interest, using a biased form of MD, called random‐acceleration MD. Various egress gates and binding pockets for dioxygen, as an indistinguishable mimic of singlet dioxygen, were found on both above and below the isoalloxazine plane of the flavin mononucleotide cofactor in miniSOG. Of such gates and binding pockets, those lying within two opposite cones, coaxial with a line normal to the isoalloxazine plane, and with the vertex at the center of such a plane are those most visited by the escaping gas molecule. Out of residues most capable of quenching ¹O₂, Y30, lying near the base of one such a cone, and H85, near the base of the opposite cone, are held to be most responsible for the reduced quantum yield of ¹O₂ with folded miniSOG with respect to free flavin mononucleotide in solution.     

Multivariate meta‐analysis with an increasing number of parameters

Meta‐analysis can average estimates of multiple parameters, such as a treatment's effect on multiple outcomes, across studies. Univariate meta‐analysis (UVMA) considers each parameter individually, while multivariate meta‐analysis (MVMA) considers the parameters jointly and accounts for the correlation between their estimates. The performance of MVMA and UVMA has been extensively compared in scenarios with two parameters. Our objective is to compare the performance of MVMA and UVMA as the number of parameters, p, increases. Specifically, we show that (i) for fixed‐effect (FE) meta‐analysis, the benefit from using MVMA can substantially increase as p increases; (ii) for random effects (RE) meta‐analysis, the benefit from MVMA can increase as p increases, but the potential improvement is modest in the presence of high between‐study variability and the actual improvement is further reduced by the need to estimate an increasingly large between study covariance matrix; and (iii) when there is little to no between‐study variability, the loss of efficiency due to choosing RE MVMA over FE MVMA increases as p increases. We demonstrate these three features through theory, simulation, and a meta‐analysis of risk factors for non‐Hodgkin lymphoma.     

Merits of Modelling Multivariate Survival Data Using Random Effects Proportional Odds Model

Recently, there has been a great deal of interest in the analysis of multivariate survival data. In most epidemiological studies, survival times of the same cluster are related because of some unobserved risk factors such as the environmental or genetic factors. Therefore, modelling of dependence between events of correlated individuals is required to ensure a correct inference on the effects of treatments or covariates on the survival times. In the past decades, extension of proportional hazards model has been widely considered for modelling multivariate survival data by incorporating a random effect which acts multiplicatively on the hazard function. In this article, we consider the proportional odds model, which is an alternative to the proportional hazards model at which the hazard ratio between individuals converges to unity eventually. This is a reasonable property particularly when the treatment effect fades out gradually and the homogeneity of the population increases over time. The objective of this paper is to assess the influence of the random effect on the within‐subject correlation and the population heterogeneity. We are particularly interested in the properties of the proportional odds model with univariate random effect and correlated random effect. The correlations between survival times are derived explicitly for both choices of mixing distributions and are shown to be independent of the covariates. The time path of the odds function among the survivors are also examined to study the effect of the choice of mixing distribution. Modelling multivariate survival data using a univariate mixing distribution may be inadequate as the random effect not only characterises the dependence of the survival times, but also the conditional heterogeneity among the survivors. A robust estimate for the correlation of the logarithm of the survival times within a cluster is obtained disregarding the choice of the mixing distributions. The sensitivity of the estimate of the regression parameter under a misspecification of the mixing distribution is studied through simulation. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

The Effect of Design Imbalance on the Power of the F‐test of a Variance Component in the One‐Way Random Model

The ANOVA‐based F‐test used for testing the significance of the random effect variance component is a valid test for an unbalanced one‐way random model. However, it does not have an uniform optimum property. For example, this test is not uniformly most powerful invariant (UMPI). In fact, there is no UMPI test in the unbalanced case (see Khuri , Mathew , and Sinha , 1998). The power of the F‐test depends not only on the design used, but also on the true values of the variance components. As Khuri (1996) noted, we can gain a better insight into the effect of data imbalance on the power of the F‐test using a method for modelling the power in terms of the design parameters and the variance components. In this study, generalized linear modelling (GLM) techniques are used for this purpose. It is shown that GLM, in combination with a method of generating designs with a specified degree of imbalance, is an effective way of studying the behavior of the power of the F‐test in a one‐way random model.