Diversity and dispersal history of the talitrids (Crustacea: Amphipoda: Talitridae) of Bermuda

Five taxa of talitrid amphipods were found in the archipelago of Bermuda, of which three were recorded there for the first time. Four of these are supralittoral wrack generalists: Platorchestia monodi BOLD:AAB3402, (a unique Molecular Operational Taxonomic Unit according to the Barcode Index Number system), a related species recognized by molecular methods, Platorchestia platensis BOLD:AAA2949, Mexorchestia carpenteri carpenteri BOLD:AAC1491 and Tethorchestia antillensis; and one a terrestrial leaf-litter generalist: Talitroides alluaudi. A key is provided to discriminate between the formally described talitrids of Bermuda. Dispersal mechanisms from the American continent to Bermuda were considered for all taxa based on species distributions along the North American Atlantic coast and also investigated by molecular methods, using genetic population differentiation and haplotype network analysis based on the barcode region of cytochrome c oxidase subunit I gene. For P. monodi BOLD:AAB3402 the genetic results suggest that some dispersal events occurred before human colonization of Bermuda but are equivocal about the source population and therefore the direction of dispersal. Some very recent synanthropic dispersal is possible with this species. For the other two species studied genetically, P. platensis BOLD:AAA2949 and M. c. carpenteri BOLD:AAC1491, the small population samples analysed support dispersal to Bermuda from the American mainland, before human occupation of Bermuda, although the available sample size was limited for these species. The available limited direct, non-genetic evidence supports synanthropic transport for Talitroides alluaudi. Platorchestia monodi BOLD:AAB3402 is found in the same wrack habitat as P. platensis BOLD:AAA2949 on Bermuda, apparently without interbreeding. No evidence was found that driftwood specialist talitrids had become established in Bermuda.     

Phospholipid flippases attenuate LPS-induced TLR4 signaling by mediating endocytic retrieval of Toll-like receptor 4

P4-ATPases are lipid flippases that catalyze the transport of phospholipids to create membrane phospholipid asymmetry and to initiate the biogenesis of transport vesicles. Here we show, for the first time, that lipid flippases are essential to dampen the inflammatory response and to mediate the endotoxin-induced endocytic retrieval of Toll-like receptor 4 (TLR4) in human macrophages. Depletion of CDC50A, the β-subunit that is crucial for the activity of multiple P4-ATPases, resulted in endotoxin-induced hypersecretion of proinflammatory cytokines, enhanced MAP kinase signaling and constitutive NF-κB activation. In addition, CDC50A-depleted THP-1 macrophages displayed reduced tolerance to endotoxin. Moreover, endotoxin-induced internalization of TLR4 was strongly reduced and coincided with impaired endosomal MyD88-independent signaling. The phenotype of CDC50A-depleted cells was also induced by separate knockdown of two P4-ATPases, namely ATP8B1 and ATP11A. We conclude that lipid flippases are novel elements of the innate immune response that are essential to attenuate the inflammatory response, possibly by mediating endotoxin-induced internalization of TLR4.     

The cellular autophagy/apoptosis checkpoint during inflammation

Cell death is a major determinant of inflammatory disease severity. Whether cells live or die during inflammation largely depends on the relative success of the pro-survival process of autophagy versus the pro-death process of apoptosis. These processes interact and influence each other during inflammation and there is a checkpoint at which cells irrevocably commit to either one pathway or another. This review will discuss the concept of the autophagy/apoptosis checkpoint and its importance during inflammation, the mechanisms of inflammation leading up to the checkpoint, and how the checkpoint is regulated. Understanding these concepts is important since manipulation of the autophagy/apoptosis checkpoint represents a novel opportunity for treatment of inflammatory diseases caused by too much or too little cell death.     

Targeting mitochondria by α-tocopheryl succinate overcomes hypoxia-mediated tumor cell resistance to treatment

Rapidly proliferating tumor cells easily become hypoxic. This results in acquired stability towards treatment with anticancer drugs. Here, we show that cells grown at 0.1 % oxygen are more resistant towards treatment with the conventionally used anticancer drugs doxorubicin and cisplatin. The stimulation of apoptosis, as assessed by the number of cells in the SubG1 fraction of the cell cycle, release of cytochrome c into the cytosol, activation of caspase-3, and cleavage of PARP, was markedly suppressed under low oxygen content or when hypoxia was mimicked by deferoxamine. Hypoxia or deferoxamine treatment was accompanied by stabilization of the hypoxia-inducible factor (HIF-1). The downregulation of HIF-1 using siRNA technique restored cell sensitivity to treatment under hypoxic conditions to the levels detected under normoxic conditions. In contrast to cisplatin or doxorubicin, α-tocopheryl succinate (α-TOS), a compound that targets mitochondria, stimulated cell death irrespective of the oxygen concentration. Moreover, under hypoxic condition cell death induced by α-TOS was even enhanced. Thus, α-TOS can successfully overcome resistance to treatment caused by hypoxia, which makes α-TOS an attractive candidate for antitumor therapy via mitochondrial targeting.     

ARFIMA approximation and forecasting of the limiting aggregate structure of long‐memory process

This article studies Man and Tiao's (2006) low‐order autoregressive fractionally integrated moving‐average (ARFIMA) approximation to Tsai and Chan's (2005b) limiting aggregate structure of the long‐memory process. In matching the autocorrelations, we demonstrate that the approximation works well, especially for larger d values. In computing autocorrelations over long lags for larger d value, using the exact formula one might encounter numerical problems. The use of the ARFIMA(0, d, d?₁) model provides a useful alternative to compute the autocorrelations as a really close approximation. In forecasting future aggregates, we demonstrate the close performance of using the ARFIMA(0, d, d?₁) model and the exact aggregate structure. In practice, this provides a justification for the use of a low‐order ARFIMA model in predicting future aggregates of long‐memory process. Copyright © 2008 John Wiley & Sons, Ltd.