A mutation in aminopeptidase N (CD13) isolated from a patient suffering from leukemia leads to an arrest in the endoplasmic reticulum

Human aminopeptidase N (APN) is used as a routine marker for myelomonocytic cells in hematopoietic malignant disorders. Its gene and surface expressions are increased in cases of malignant transformation, inflammation, or T cell activation, whereas normal B and resting T cells lack detectable APN protein expression. In this study we elucidated the intracellular distribution, expression pattern, and enzymatic activity of a naturally occurring mutation in the coding region of the APN gene. At physiological temperatures the mutant protein is enzymatically inactive, persists as a mannose-rich polypeptide in the endoplasmic reticulum, and is ultimately degraded by an endoplasmic reticulum-associated degradation pathway. It shows in part the distinct behavior of a temperature-sensitive mutant with a permissive temperature of 32 degrees C, leading to correct sorting of the Golgi compartment accompanied by the acquisition of proper glycosylation but without reaching the cell-surface membrane and without regaining its enzymatic activity. Because the patient bearing this mutation suffered from leukemia, possible links to the pathogenesis of leukemia are discussed.     

Observing the observer (II): deciding when to decide

In a companion paper [1], we have presented a generic approach for inferring how subjects make optimal decisions under uncertainty. From a Bayesian decision theoretic perspective, uncertain representations correspond to "posterior" beliefs, which result from integrating (sensory) information with subjective "prior" beliefs. Preferences and goals are encoded through a "loss" (or "utility") function, which measures the cost incurred by making any admissible decision for any given (hidden or unknown) state of the world. By assuming that subjects make optimal decisions on the basis of updated (posterior) beliefs and utility (loss) functions, one can evaluate the likelihood of observed behaviour. In this paper, we describe a concrete implementation of this meta-Bayesian approach (i.e. a Bayesian treatment of Bayesian decision theoretic predictions) and demonstrate its utility by applying it to both simulated and empirical reaction time data from an associative learning task. Here, inter-trial variability in reaction times is modelled as reflecting the dynamics of the subjects' internal recognition process, i.e. the updating of representations (posterior densities) of hidden states over trials while subjects learn probabilistic audio-visual associations. We use this paradigm to demonstrate that our meta-Bayesian framework allows for (i) probabilistic inference on the dynamics of the subject's representation of environmental states, and for (ii) model selection to disambiguate between alternative preferences (loss functions) human subjects could employ when dealing with trade-offs, such as between speed and accuracy. Finally, we illustrate how our approach can be used to quantify subjective beliefs and preferences that underlie inter-individual differences in behaviour.     

Structure Learning in a Sensorimotor Association Task

Learning is often understood as an organism''s gradual acquisition of the association between a given sensory stimulus and the correct motor response. Mathematically, this corresponds to regressing a mapping between the set of observations and the set of actions. Recently, however, it has been shown both in cognitive and motor neuroscience that humans are not only able to learn particular stimulus-response mappings, but are also able to extract abstract structural invariants that facilitate generalization to novel tasks. Here we show how such structure learning can enhance facilitation in a sensorimotor association task performed by human subjects. Using regression and reinforcement learning models we show that the observed facilitation cannot be explained by these basic models of learning stimulus-response associations. We show, however, that the observed data can be explained by a hierarchical Bayesian model that performs structure learning. In line with previous results from cognitive tasks, this suggests that hierarchical Bayesian inference might provide a common framework to explain both the learning of specific stimulus-response associations and the learning of abstract structures that are shared by different task environments.     

Avoiding a crisis of motivation for ocean management under global environmental change

Climate change and ocean acidification are altering marine ecosystems and, from a human perspective, creating both winners and losers. Human responses to these changes are complex, but may result in reduced government investments in regulation, resource management, monitoring and enforcement. Moreover, a lack of peoples’ experience of climate change may drive some towards attributing the symptoms of climate change to more familiar causes such as management failure. Taken together, we anticipate that management could become weaker and less effective as climate change continues. Using diverse case studies, including the decline of coral reefs, coastal defences from flooding, shifting fish stocks and the emergence of new shipping opportunities in the Arctic, we argue that human interests are better served by increased investments in resource management. But greater government investment in management does not simply mean more of “business‐as‐usual.” Management needs to become more flexible, better at anticipating and responding to surprise, and able to facilitate change where it is desirable. A range of technological, economic, communication and governance solutions exists to help transform management. While not all have been tested, judicious application of the most appropriate solutions should help humanity adapt to novel circumstances and seek opportunity where possible.     

Palaeontology in the third dimension: a comprehensive guide for the integration of three-dimensional content in publications

During the last decade, three-dimensional, digital models have become increasingly important in geosciences and in particular in palaeontological research. Although significant advances in hard- and software technology have facilitated the acquisition and creation of such models, the presentation of three-dimensional data is still greatly handicapped by the traditionally two-dimensional means of publication. The ability to integrate three-dimensional (3D) models, which can be interactively manipulated, into portable document format (PDF) documents not only considerably improves their accessibility, but also represents an innovative, but so far neglected, approach for the presentation and communication of digital data. This article introduces and illustrates a comprehensive workflow for the creation of 3D PDFs, incorporating different techniques and methodological steps, and using both commercial and freely available software resources. Advantages and disadvantages of each method are discussed, and are accompanied by selected examples of digital models. These examples encompass different methods of data acquisition (computed tomography, synchrotron radiation X-ray tomographic microscopy, photogrammetry) and span a wide range of sizes and taxonomic groups. To the best of the author’s knowledge, this article represents the first application of 3D PDF technology fully integrated into a scientific publication in palaeontology or even geosciences, and not restricted to supplementary material. It provides the reader with extended visual information and facilitates the dissemination of data. As both authors and readers benefit greatly from their usage, it is argued that 3D PDFs should become an accepted standard in palaeontological publications of three-dimensional models.     

Distinct binding properties distinguish LQ-type calmodulin-binding domains in cyclic nucleotide-gated channels

Cyclic nucleotide-gated (CNG) channels operate as transduction channels in photoreceptors and olfactory receptor neurons. Direct binding of cGMP or cAMP opens these channels which conduct a mixture of monovalent cations and Ca(2+). Upon activation, CNG channels generate intracellular Ca(2+) signals that play pivotal roles in the transduction cascades of the visual and olfactory systems. Channel activity is controlled by negative feedback mechanisms that involve Ca(2+)-calmodulin, for which all CNG channels possess binding sites. Here we compare the binding properties of the two LQ-type calmodulin binding sites, both of which are thought to be involved in channel regulation. They reside on the isoforms CNGB1 and CNGA4. The CNGB1 subunit is present in rod photoreceptors and olfactory receptor neurons. The CNGA4 subunit is only expressed in olfactory receptor neurons, and there are conflicting results as to its role in calmodulin-mediated feedback inhibition. We examined the interaction of Ca(2+)-calmodulin with two recombinant proteins that encompass either of the two LQ sites. Comparing binding properties, we found that the LQ site of CNGB1 binds Ca(2+)-calmodulin at 10-fold lower Ca(2+) levels than the LQ site of CNGA4. Our data provide biochemical evidence against a contribution of CNGA4 to feedback inhibition. In accordance with previous work on photoreceptor CNG channels, our results indicate that feedback control is the exclusive role of the B-subunits in photoreceptors and olfactory receptor neurons.     

The Nse2/Mms21 SUMO ligase of the Smc5/6 complex in the maintenance of genome stability

There exist three highly-conserved structural maintenance of chromosomes (Smc) complexes that ensure genome stability during eukaryotic cell division. There are the well-characterized cohesin and condensin complexes and the third Smc complex, Smc5/6. Nse2/Mms21, a SUMO ligase, is a component of the Smc5/6 complex and recent data have indicated that Nse1 may function as a ubiquitin ligase. Smc5/6 regulates sister chromatid cohesion, homologous recombination and chromatin structure and conformation. This review examines the functions of Smc5/6 in DNA repair and the maintenance of genomic integrity and explores the roles of the associated SUMO and ubiquitin ligases. Recent findings have indicated that Smc5/6 may play a topological role in chromosome dynamics, which may help understand the complexity of its activities.     

First microwave-assisted synthesis of an electron-rich phosphane and its coordination chemistry with platinum(II) and palladium(II)

The P-O ligand 3-(di(2-methoxyphenyl)phosphanyl)propionic acid (HL) was synthesized by a microwave-assisted reaction of a secondary phosphane. The coordination of HL to Pt(II) yielded the neutral mononuclear complex trans-[PtCl(κ(2)-P,O-L)(κ-P-HL)] (1), while the reaction of PdClMe(η(4)-COD) (COD?=?1,4-cyclooctadiene) with HL in the presence of NEt(3) gave the anionic Pd(II) compound of the formula (HNEt(3))[PdClMe(κ(2)-P,O-L)] (2). Upon crystallization of the latter compound the neutral chloride-bridged dimetallic compound cis-[Pd(μ-Cl)Me(HL)](2) (3) was obtained. HL, 1 and 3·CH(2)Cl(2) have been characterized by single crystal X-ray structure analyses.