Saccharopine and 2-aminoadipic acid in Reseda odorata

2(S),2′(S)-N⁶-(2′-Glutaryl)lysine (l-saccharopine) and 2(S)-2-aminoadipic acid have been isolated from Reseda odorata. When traditional isolation procedures are used l-pyrosaccharopine (5(S),5′(S)-N-(5′-amino-5′-carboxy-pentyl)-2-pyrrolidone-5-carboxylic acid) is formed from l-saccharopine by lactamisation. The degree of lactamisation during various isolation steps has been studied, The amino acids were identified by IR and PMR spectroscopy and the configurations established by enzymic and polarimetric analyses. The contents of saccharopine and 2-amino-adipic acid have been determined relative to the total nitrogen content at various stages in the growth cycle of R. odorata.     

Presence of a pineal nerve in sheep and rabbit fetuses

The presence of a nerve located just caudal to the pineal gland in the midsagittal plane is demonstrated in sheep and rabbit fetuses. This nerve lies freely in the subarachnoid space and extends from the pineal gland to a region of the CNS located dorsal to the rostralmost part of the subcommissural organ (SCO). In rabbit fetuses the nerve is obsered on days 23 and 24 of gestation; we suggest that it is an ontogenetic equivalent to the pineal nerve of anuran amphibians. The developmental fate of the mammalian fetal pineal nerve is dicussed.     

Prevalence of Edwards' syndrome. Clustering and seasonal variation?

Summary The incidence of Edwards' syndrome was found to be 1 per 4857 newborn children of 34000 consecutively newborn children in two Danish counties. Six of the 7 cases were born during the months of February through April.The incidence was high compared with the expected incidence of Edwards' syndrome of approximately 1 per 10000. This might be due to clustering in the area studied during the period 1967 to 1973.The finding of variations in incidence of children with Edwards' syndrome in different parts of the world, as well as the finding of seasonal variation in birth of such children, indicates that some of the etiological factors of nondisjunction of chromosome 18 are of an environmental nature.     

Feather mites (Acari: Astigmata) and body condition of their avian hosts: a large correlative study

Feather mites are arthropods that live on or in the feathers of birds, and are among the commonest avian ectosymbionts. However, the nature of the ecological interaction between feather mites and birds remains unclear, some studies reporting negative effects of feather mites on their hosts and others reporting positive or no effects. Here we use a large dataset comprising 20 189 measurements taken from 83 species of birds collected during 22 yr in 151 localities from seven countries in Europe and North Africa to explore the correlation between feather mite abundance and body condition of their hosts. We predicted that, if wing‐dwelling feather mites are parasites, a negative correlation with host body condition should be found, while a mutualistic interaction should yield positive correlation. Although negative relationships between feather mite abundance and host body condition were found in a few species of birds, the sign of the correlation was positive in most bird species (69%). The overall effect size was only slightly positive (r =0.066). The effect of feather mite abundance explained <10% of variance in body condition in most species (87%). Results suggest that feather mites are not parasites of birds, but rather that they hold a commensalistic relationship where feather mites may benefit from feeding on uropygial gland secretions of their hosts and birds do not seem to obtain a great benefit from the presence of feather mites.     

Modelling the Human Immune System by Combining Bioinformatics and Systems Biology Approaches

Over the past decade a number of bioinformatics tools have been developed that use genomic sequences as input to predict to which parts of a microbe the immune system will react, the so-called epitopes. Many predicted epitopes have later been verified experimentally, demonstrating the usefulness of such predictions. At the same time, simulation models have been developed that describe the dynamics of different immune cell populations and their interactions with microbes. These models have been used to explain experimental findings where timing is of importance, such as the time between administration of a vaccine and infection with the microbe that the vaccine is intended to protect against. In this paper, we outline a framework for integration of these two approaches. As an example, we develop a model in which HIV dynamics are correlated with genomics data. For the first time, the fitness of wild type and mutated virus are assessed by means of a sequence-dependent scoring matrix, derived from a BLOSUM matrix, that links protein sequences to growth rates of the virus in the mathematical model. A combined bioinformatics and systems biology approach can lead to a better understanding of immune system-related diseases where both timing and genomic information are of importance.     

Long-Term Miscanthus Yields Influenced by Location,Genotype, Row Distance,Fertilization and Harvest Season

Long-term yield studies in perennial crops like miscanthus are important to determine mean annual energy yield and the farmer’s economy. In two Danish field trials, annual yield of two miscanthus genotypes was followed over a 20-year period. The trials were established in 1993 on loamy sand in Foulum and on coarse sand in Jyndevad. Effects of genotype, row distance and fertilization were investigated. In both trials, yield development over time was characterized by an increase during the first years, optimum yields after 7–8 years and a decrease to a lower level which remained relatively constant from year 11 to 20. Spring harvest reduced the yield by 34–42 % compared to autumn harvest. In Foulum annual fertilization with 75 kg ha^?1 N increased the yield of the genotype Goliath (Miscanthus sinensis) by 26 %. Additional N fertilization only increased the yield of Goliath little, and the genotype Giganteus (Miscanthus?×?giganteus) did not respond to fertilization at all. The highest mean yield in Foulum for the period 1997–2012 was obtained with the shortest row distance (～18,000 rather than ～12,000 plants ha^?1) and harvested in late autumn, namely 13.1 and 12.0 Mg ha^?1 DM annually for Giganteus and Goliath, respectively. In Jyndevad, where only Goliath was studied, the highest yield during 1995–2001 was obtained by short row distance, autumn harvest and annual fertilization with 75 kg ha^?1 N, with yield increasing up to 116 % in response to fertilization. A mean yield of 14.4 Mg ha^?1 DM was achieved over the period 1995–2012.     

NetMHCIIpan-2.0 - Improved pan-specific HLA-DR predictions using a novel concurrent alignment and weight optimization training procedure

Background

Macrophages represent the front lines of our immune system; they recognize and engulf pathogens or foreign particles thus initiating the immune response. Imaging macrophages presents unique challenges, as most optical techniques require labeling or staining of the cellular compartments in order to resolve organelles, and such stains or labels have the potential to perturb the cell, particularly in cases where incomplete information exists regarding the precise cellular reaction under observation. Label-free imaging techniques such as Raman microscopy are thus valuable tools for studying the transformations that occur in immune cells upon activation, both on the molecular and organelle levels. Due to extremely low signal levels, however, Raman microscopy requires sophisticated image processing techniques for noise reduction and signal extraction. To date, efficient, automated algorithms for resolving sub-cellular features in noisy, multi-dimensional image sets have not been explored extensively.

Results

We show that hybrid z-score normalization and standard regression (Z-LSR) can highlight the spectral differences within the cell and provide image contrast dependent on spectral content. In contrast to typical Raman imaging processing methods using multivariate analysis, such as single value decomposition (SVD), our implementation of the Z-LSR method can operate nearly in real-time. In spite of its computational simplicity, Z-LSR can automatically remove background and bias in the signal, improve the resolution of spatially distributed spectral differences and enable sub-cellular features to be resolved in Raman microscopy images of mouse macrophage cells. Significantly, the Z-LSR processed images automatically exhibited subcellular architectures whereas SVD, in general, requires human assistance in selecting the components of interest.

Conclusions

The computational efficiency of Z-LSR enables automated resolution of sub-cellular features in large Raman microscopy data sets without compromise in image quality or information loss in associated spectra. These results motivate further use of label free microscopy techniques in real-time imaging of live immune cells.     

Subjecting the theory of the small‐island effect to Ockham’s razor

Species–area curves from islands and other isolates often differ in shape from sample‐area curves generated from mainlands or sections of isolates (or islands), especially at finer scales. We examine two explanations for this difference: (1) the small‐island effect (SIE), which assumes the species–area curve is composed of two distinctly different curve patterns; and (2) a sigmoid or depressed isolate species–area curve with no break‐points (in arithmetic space). We argue that the application of Ockham’s razor – the principle that the simplest, most economical explanation for a hypothesis should be accepted over less parsimonious alternatives – leads to the conclusion that the latter explanation is preferable. We hold that there is no reason to assume the ecological factors or patterns that affect the shapes of isolate (or island) curves cause two distinctly different patterns. This assumption is not required for the alternative, namely that these factors cause a single (though depressed) isolate species–area curve with no break‐points. We conclude that the theory of the small‐island effect, despite its present standing as an accepted general pattern in nature, should be abandoned.     

Choice of Allocations and Constructs for Attributional or Consequential Life Cycle Assessment and Input‐Output Analysis

The divide between attributional and consequential research perspectives partly overlaps with the long‐standing methodological discussions in the life cycle assessment (LCA) and input‐output analysis (IO) research communities on the choice of techniques and models for dealing with situations of coproduction. The recent harmonization of LCA allocations and IO constructs revealed a more diverse set of coproduction models than had previously been understood. This increased flexibility and transparency in inventory modeling warrants a re‐evaluation of the treatment of coproduction in analyses with attributional and consequential perspectives. In the present article, the main types of coproductions situations and of coproduction models are reviewed, along with key desirable characteristics of attributional and consequential studies. A concordance analysis leads to clear recommendations, which call for important refinements to current guidelines for both LCA/IO practitioners and database developers. We notably challenge the simple association between, on the one hand, attributional LCA and partition allocation, and on the one hand, consequential LCA and substitution modeling.