Psychological correlates of self-reported functional limitation in patients with ankylosing spondylitis

Introduction  

Functional status is an integral component of health-related quality of life in patients with ankylosing spondylitis (AS). The purpose of this study was to investigate the role of psychological variables in self-reported functional limitation in patients with AS, while controlling for demographic and medical variables.     

Basal forebrain cholinergic system in the dementias: Vulnerability,resilience, and resistance

The basal forebrain cholinergic neurons (BFCN) provide the primary source of cholinergic innervation of the human cerebral cortex. They are involved in the cognitive processes of learning, memory, and attention. These neurons are differentially vulnerable in various neuropathologic entities that cause dementia. This review summarizes the relevance to BFCN of neuropathologic markers associated with dementias, including the plaques and tangles of Alzheimer's disease (AD), the Lewy bodies of diffuse Lewy body disease, the tauopathy of frontotemporal lobar degeneration (FTLD-TAU) and the TDP-43 proteinopathy of FTLD-TDP. Each of these proteinopathies has a different relationship to BFCN and their corticofugal axons. Available evidence points to early and substantial degeneration of the BFCN in AD and diffuse Lewy body disease. In AD, the major neurodegenerative correlate is accumulation of phosphotau in neurofibrillary tangles. However, these neurons are less vulnerable to the tauopathy of FTLD. An intriguing finding is that the intracellular tau of AD causes destruction of the BFCN, whereas that of FTLD does not. This observation has profound implications for exploring the impact of different species of tauopathy on neuronal survival. The proteinopathy of FTLD-TDP shows virtually no abnormal inclusions within the BFCN. Thus, the BFCN are highly vulnerable to the neurodegenerative effects of tauopathy in AD, resilient to the neurodegenerative effect of tauopathy in FTLD and apparently resistant to the emergence of proteinopathy in FTLD-TDP and perhaps also in Pick's disease. Investigations are beginning to shed light on the potential mechanisms of this differential vulnerability and their implications for therapeutic intervention.

     

T cell activation by coxsackievirus B4 antigens in type 1 diabetes mellitus: evidence for selective TCR Vbeta usage without superantigenic activity.

Numerous clinical and epidemiological studies link enteroviruses such as the Coxsackie virus group with the autoimmune disease type 1 diabetes mellitus (DM). In addition, there are reports that patients with type 1 DM are characterized by skewing of TCR Vbeta chain selection among peripheral blood and intraislet T lymphocytes. To examine these issues, we analyzed TCR Vbeta chain-specific up-regulation of the early T cell activation marker, CD69, on CD4 T cells after incubation with Coxsackievirus B4 (CVB4) Ags. CD4 T cells bearing the Vbeta chains 2, 7, and 8 were the most frequently activated by CVB4. Up-regulation of CD69 by different TCR families was significantly more frequent in new onset type 1 DM patients (p = 0.04), 100% of whom (n = 8) showed activation of CD4 T cells bearing Vbeta8, compared with 50% of control subjects (n = 8; p = 0.04). T cell proliferation after incubation with CVB4 Ags required live, nonfixed APCs, suggesting that the selective expansion of CD4 T cells with particular Vbeta chains resulted from conventional antigen processing and presentation rather than superantigen activity. Heteroduplex analysis of TCR Vbeta chain usage after CVB4 stimulation indicated a relatively polyclonal, rather than oligo- or monoclonal response to viral Ags. These results provide evidence that new-onset patients with type 1 DM and healthy controls are primed against CVB4, and that CD4 T cell responses to the virus have a selective TCR Vbeta chain usage which is driven by viral Ags rather than a superantigen.     

Early oviposition experience affects patch residence time in a foraging parasitoid

Parasitoids learn olfactory and visual cues that are associated with their hosts, and use these cues to forage more efficiently. Classical conditioning theory predicts that encounters with high-quality hosts will lead to better learning of host-associated cues than encounters with low-quality hosts. We tested this prediction in a two-phase laboratory experiment with the parasitoid Trichogramma thalense Pinto & Oatman (Hymenoptera: Trichogrammatidae) and the host Anagasta kuehniella Zeller (Lepidoptera: Pyralidae).Host quality during the first exposure to hosts affected later foraging behavior for some experimental treatments, as predicted. We used a learning model, followed by patch-time optimization, to interpret our findings. We first simulated the parasitoids' host encounters during the experiment, and predicted their estimate of patch quality after each encounter. We then used dynamic optimization to predict the parasitoids' optimal patch residence times. The model reproduces the trends of the experimental results.     

Chronobiology by moonlight

Most studies in chronobiology focus on solar cycles (daily and annual). Moonlight and the lunar cycle received considerably less attention by chronobiologists. An exception are rhythms in intertidal species. Terrestrial ecologists long ago acknowledged the effects of moonlight on predation success, and consequently on predation risk, foraging behaviour and habitat use, while marine biologists have focused more on the behaviour and mainly on reproduction synchronization with relation to the Moon phase. Lately, several studies in different animal taxa addressed the role of moonlight in determining activity and studied the underlying mechanisms. In this paper, we review the ecological and behavioural evidence showing the effect of moonlight on activity, discuss the adaptive value of these changes, and describe possible mechanisms underlying this effect. We will also refer to other sources of night-time light (‘light pollution’) and highlight open questions that demand further studies.     

Size patterns among competitors: ecological character displacement and character release in mammals, with special reference to island populations

Morphological relationship among sympatric animal species have often been seen as indirect evidence for competition. Many early ecomorphological studies revealed patterns that were taken as indicating character displacement and character release, driven by competition or lack thereof. These patterns may result from a coevolutionary morphological response or from species sorting according to size. Thus, the relationship between morphology and competition may be crucial for understanding both the morphological evolution of animals and the role of competition in structuring communities. Some earlier research perceived as indicating morphological relationships conditioned by interaction of species was conducted on mammals, particularly carnivores. Subsequent criticism in the ecological literature demonstrated that many of the perceived patterns could not be statistically confirmed, thus calling into question this line of evidence for competition. More recent ecological literature relies on strong statistical analyses and careful consideration both of guild composition and of which morphological traits should be examined. This literature, resting largely on mammals, includes several cases that suggest a coevolutionary morphological response to interspecific competition. These studies have focused on the thropic apparatus directly related to food procurement by mammals — the teeth. Island mammals often show striking morphological patterns, some of which have been interpreted as resulting from release from competition with mainland species that have not reached islands. However, few of these patterns were critically evaluated to demonstrate their support for the hypothesis of character release. Despite several decades of interest and research, many questions regarding competitively induced morphological patterns remain unresolved and require further research. Mammals are especially promising subjects for such researh.     

RNA Graph Partitioning for the Discovery of RNA Modularity: A Novel Application of Graph Partition Algorithm to Biology

Graph representations have been widely used to analyze and design various economic, social, military, political, and biological networks. In systems biology, networks of cells and organs are useful for understanding disease and medical treatments and, in structural biology, structures of molecules can be described, including RNA structures. In our RNA-As-Graphs (RAG) framework, we represent RNA structures as tree graphs by translating unpaired regions into vertices and helices into edges. Here we explore the modularity of RNA structures by applying graph partitioning known in graph theory to divide an RNA graph into subgraphs. To our knowledge, this is the first application of graph partitioning to biology, and the results suggest a systematic approach for modular design in general. The graph partitioning algorithms utilize mathematical properties of the Laplacian eigenvector (µ2) corresponding to the second eigenvalues (λ2) associated with the topology matrix defining the graph: λ2 describes the overall topology, and the sum of µ2′s components is zero. The three types of algorithms, termed median, sign, and gap cuts, divide a graph by determining nodes of cut by median, zero, and largest gap of µ2′s components, respectively. We apply these algorithms to 45 graphs corresponding to all solved RNA structures up through 11 vertices (∼220 nucleotides). While we observe that the median cut divides a graph into two similar-sized subgraphs, the sign and gap cuts partition a graph into two topologically-distinct subgraphs. We find that the gap cut produces the best biologically-relevant partitioning for RNA because it divides RNAs at less stable connections while maintaining junctions intact. The iterative gap cuts suggest basic modules and assembly protocols to design large RNA structures. Our graph substructuring thus suggests a systematic approach to explore the modularity of biological networks. In our applications to RNA structures, subgraphs also suggest design strategies for novel RNA motifs.