Quantification of glucosinolates in leaves of leaf rape (Brassica napus ssp. pabularia) by near-infrared spectroscopy

The potential of near-infrared spectroscopy (NIRS) for screening the total glucosinolate (t-GSL) content, and also, the aliphatic glucosinolates gluconapin (GNA), glucobrassicanapin (GBN), progoitrin (PRO), glucoalyssin (GAL), and the indole glucosinolate glucobrassicin (GBS) in the leaf rape (Brassica napus L. ssp. pabularia DC), was assessed. This crop is grown for edible leaves for both fodder and human consumption. In Galicia (northwestern Spain) it is highly appreciated for human nutrition and have the common name of "nabicol". A collection of 36 local populations of nabicol was analysed by NIRS for glucosinolate composition. The reference values for glucosinolates, as they were obtained by high performance liquid chromatography on the leaf samples, were regressed against different spectral transformations by modified partial least-squares (MPLS) regression. The coefficients of determination in cross-validation (r2) shown by the equations for t-GSL, GNA, GBN, PRO, GAL and GBS were, respectively, 0.88, 0.73, 0.81, 0.78, 0.37 and 0.41. The standard deviation to standard error of cross-validation ratio, were for these constituents, as follows: t-GSL, 2.96; GNA, 1.94; GBN, 2.31; PRO, 2.11; GAL, 1.27, and GBS, 1.29. These results show that the equations developed for total glucosinolates, as well as those for gluconapin, glucobrassicanapin and progoitrin, can be used for screening these compounds in the leaves of this species. In addition, the glucoalyssin and glucobrassicin equations obtained, can be used to identify those samples with low and high contents. From the study of the MPLS loadings of the first three terms of the different equations, it can be concluded that some major cell components as protein and cellulose, highly participated in modelling the equations for glucosinolates.     

Hydroxyzine, promethazine and thioridazine interaction with phospholipid monomolecular layers at the air-water interface

In this work the interaction of Hydroxyzine, Promethazine and Thioridazine with Langmuir films of dipalmitoylphosphatidylcholine (dpPC) and dipalmitoylphosphatidic acid (dpPA), is studied. Temporal variations in lateral surface pressure (pi) were measured at different initial pi (pi(i)), subphase pH and drug-concentration. Drugs with the smallest (PRO) and largest (HYD) molecular size exhibited the lowest adsorption (k(a)) and the highest desorption (k(d)) rate constant values, respectively. The affinity binding constants (K(b)) obtained in monolayers followed the same profile (K(b,PRO) < K(b,HYD) < K(b,THI)) of the egg-PC/water partition coefficients (P) determined in bilayers. The drug concentration required to reach the half-maximal Deltapi at pi(i) = 14 mN/m (K(0.5)), was very sensitive to pH. The maximal increment in pi upon drug incorporation into the monolayer (deltapi(max)) will depend on the phospholipid collapse pressure (pi(c)), the monolayers's compressibility and drug's size, shape and charge. The higher pi(c) of dpPC lead to higher pi(cut-off) values (maximal pi allowing drug penetration), if compared with dpPA. In dpPC and dpPA pi(cut-off) decreased as a function of the molecular size of the uncharged drugs. In dpPA, protonated drugs became electrostatically trapped at the monolayer surface hence drug penetration, monolayer deformation and pi increase were impaired and the correlation between pi(cut-off) and drug molecular size was lost.     

1987年特大火灾后不同树种种植比例对大兴安岭森林景观的长期影响

应用空间直观景观模型(LANDIS)模拟了1987年大兴安岭北坡图强林业局特大森林火灾后在目前种植强度下,不同落叶松和樟子松种植比例(100%落叶松(P₁)、70%落叶松和30%樟子松(P₂)、50%落叶松和50%樟子松(P₃)、30%落叶松和70%樟子松(P₄)、100%樟子松(P₅)以及完全依靠天然更新(P₀)条件下森林景观的长期动态变化.结果表明,在演替的前期、中期和后期,不同种植比例均对落叶松、樟子松和白桦有显著影响;落叶松所占的面积百分比随时间的推移均呈上升趋势,而樟子松则相反;在各种植预案下,落叶松和樟子松的面积百分比均高于天然更新预案的比例,随着落叶松种植比例的增加,落叶松的多度也相应增加;樟子松在该区所占的面积百分比也随其种植比例的增大而增加.白桦在天然更新预案下所占的面积百分比明显高于种植预案下所占的比例;而不同落叶松和樟子松种植比例也对白桦面积有较大影响,樟子松种植的比例越大,白桦所占的面积百分比越高,说明落叶松比樟子松有更强的竞争能力.但P₂、P₃和P₄预案下,落叶松和樟子松的面积所占比例相差不大,但要高于完全种植落叶松(P₁)或樟子松(P₅)所占的比例.     

The Effects of Seed Dispersal on the Simulation of Long-Term Forest Landscape Change

The study of forest landscape change requires an understanding of the complex interactions of both spatial and temporal factors. Traditionally, forest gap models have been used to simulate change on small and independent plots. While gap models are useful in examining forest ecological dynamics across temporal scales, large, spatial processes, such as seed dispersal, cannot be realistically simulated across large landscapes. To simulate seed dispersal, spatially explicit landscape models that track individual species distribution are needed. We used such a model, LANDIS, to illustrate the implications of seed dispersal for simulating forest landscape change. On an artificial open landscape with a uniform environment, circular-shaped tree species establishment patterns resulted from the simulations, with areas near seed sources more densely covered than areas further from seed sources. Because LANDIS simulates at 10-y time steps, this pattern reflects an integration of various possible dispersal shapes and establishment that are caused by the annual variations in climate and other environmental variables. On real landscapes, these patterns driven only by species dispersal radii are obscured by other factors, such as species competition, disturbance, and landscape structure. To further demonstrate the effects of seed dispersal, we chose a fairly disturbed and fragmented forest landscape (approximately 500,000 ha) in northern Wisconsin. We compared the simulation results of a map with tree species (seed source locations) realistically parameterized (the real scenario) against a randomly parameterized species map (the random scenario). Differences in the initial seed source distribution lead to different simulation results of species abundance with species abundance starting at identical levels under the two scenarios. This is particularly true for the first half of the model run (0–250 y). Under the random scenario, infrequently occurring and shade tolerant species tend to be overestimated, while midabundant and midshade tolerant species tend to be underestimated. The over- and underestimation of species abundance diminish when examining long-term (500 y) landscape dynamics, because stochastic factors, such as fire, tend to make the landscapes under both scenarios converge. However, differences in spatial patterns, and especially species age-cohort distributions, can persist under the two scenarios for several hundred years. Received 24 November 1998; accepted 17 March 1999.     

Role of inflammatory mechanisms in pathogenesis of type 2 diabetes mellitus

Type 2 diabetes mellitus (T2DM) is characterized by progressive β‐cell dysfunctioning and insulin resistance. This article reviews recent literature with special focus on inflammatory mechanisms that provoke the pathogenesis of T2DM. We have focused on the recent advances in progression of T2DM including various inflammatory mechanisms that might induce inflammation, insulin resistance, decrease insulin secretion from pancreatic islets and dysfunctioning of β‐cells. Here we have also summarized the role of various pro‐inflammatory mediators involved in inflammatory mechanisms, which may further alter the normal structure of β‐cells by inducing pancreatic islet's apoptosis. In conclusion, it is suggested that the role of inflammation in pathogenesis of T2DM is crucial and cannot be neglected. Moreover, the insight of inflammatory responses in T2DM may provide a new gateway for the better treatment of diabetes mellitus. J. Cell. Biochem. 114: 525–531, 2013. © 2012 Wiley Periodicals, Inc.     

A Score Test for Association of a Longitudinal Marker and an Event with Missing Data

Summary : Often clinical studies periodically record information on disease progression as well as results from laboratory studies that are believed to reflect the progressing stages of the disease. A primary aim of such a study is to determine the relationship between the lab measurements and a disease progression. If there were no missing or censored data, these analyses would be straightforward. However, often patients miss visits, and return after their disease has progressed. In this case, not only is their progression time interval censored, but their lab test series is also incomplete. In this article, we propose a simple test for the association between a longitudinal marker and an event time from incomplete data. We derive the test using a very intuitive technique of calculating the expected complete data score conditional on the observed incomplete data (conditional expected score test, CEST). The problem was motivated by data from an observational study of patients with diabetes.