Modern humans in Sarawak, Malaysian Borneo, during Oxygen Isotope Stage 3: palaeoenvironmental evidence from the Great Cave of Niah

During recent reinvestigations in the Great Cave of Niah in Borneo, the ‘Hell Trench’ sedimentary sequence seen by earlier excavators was re-exposed. Early excavations here yielded the earliest anatomically-modern human remains in island Southeast Asia. Calibrated radiocarbon dates, pollen, algal microfossils, palynofacies, granulometry and geochemistry of the ‘Hell Trench’ sequence provide information about environmental and vegetational changes, elements of geomorphic history and information about human activity. The ‘Hell’ sediments were laid down episodically in an ephemeral stream or pool. The pollen suggests cyclically changing vegetation with forest habitats alternating with more open environments; indicating that phases with both temperatures and precipitation reduced compared with the present. These events can be correlated with global climate change sequences to produce a provisional dating framework. During some forest phases, high counts of Justicia, a plant which today colonises recently burnt forest areas, point to fire in the landscape. This may be evidence for biomass burning by humans, presumably to maintain forest-edge habitats. There is evidence from palynofacies for fire on the cave floor in the ‘Hell’ area. Since the area sampled is beyond the limit of plant growth, this is evidence for human activity. The first such evidence is during an episode with significant grassland indicators, suggesting that people may have reached the site during a climatic phase characterised by relatively open habitats ~50 ka. Thereafter, people were able to maintain a relatively consistent presence at Niah. The human use of the ‘Hell’ area seems to have intensified through time, probably because changes in the local hydrological regime made the area dryer and more suitable for human use.

Cutting edge: Langerin+ dendritic cells in the mesenteric lymph node set the stage for skin and gut immune system cross-talk.

Topical transcutaneous immunization (TCI) presents many clinical advantages, but its underlying mechanism remains unknown. TCI induced Ag-specific IgA Ab-secreting cells expressing CCR9 and CCR10 in the small intestine in a retinoic acid-dependent manner. These intestinal IgA Abs were maintained in Peyer\'s patch-null mice but abolished in the Peyer\'s patch- and lymph node-null mice. The mesenteric lymph node (MLN) was shown to be the site of IgA isotype class switching after TCI. Unexpectedly, langerin(+)CD8alpha(-) dendritic cells emerged in the MLN after TCI; they did not migrate from the skin but rather differentiated rapidly from bone marrow precursors. Depletion of langerin(+) cells impaired intestinal IgA Ab responses after TCI. Taken together, these findings suggest that MLN is indispensable for the induction of intestinal IgA Abs following skin immunization and that cross-talk between the skin and gut immune systems might be mediated by langerin(+) dendritic cells in the MLN.

Modelling the MAPK signalling pathway using a two-stage identification algorithm

Signal transduction pathways describe the dynamics of cellular response to input signalling molecules at receptors on the cell membrane. The Mitogen-Activated Protein Kinase (MAPK) cascade is one of such pathways that are involved in many important cellular processes including cell growth and proliferation. This paper describes a black-box model of this pathway created using an advanced two-stage identification algorithm. Identification allows us to capture the unique features and dynamics of the pathway and also opens up the possibility of regulatory control design. In the approach described, an optimal model is obtained by performing model subset selection in two stages, where the terms are first determined by a forward selection method and then modified using a backward selection model refinement. The simulation results demonstrate that the model selected using the two-stage algorithm performs better than with the forward selection method alone.

Comparative analysis of synovial fluid and plasma proteomes in juvenile arthritis - Proteomic patterns of joint inflammation in early stage disease

Synovial fluid is a potential source of novel biomarkers for many arthritic disorders involving joint inflammation, including juvenile idiopathic arthritis. We first compared the distinctive protein ‘fingerprints’ of local inflammation in synovial fluid with systemic profiles within matched plasma samples. The synovial fluid proteome at the time of joint inflammation was then evaluated across clinical subgroups to identify early disease associated proteins. We measured the synovial fluid and plasma proteomes using the two-dimensional fluorescence difference gel electrophoresis approach. Image analysis software was used to highlight the expression levels of joint and subgroup associated proteins across the study cohort (n = 32). A defined subset of 30 proteins had statistically significant differences (p < 0.05) between sample types such that synovial fluid could be differentiated from plasma. Furthermore distinctive synovial proteome expression patterns segregate patient subgroups. Protein expression patterns localized in the chronically inflamed joint therefore have the potential to identify patients more likely to suffer disease which will spread from a single joint to multiple joints. The proteins identified could act as criteria to prevent disease extension by more aggressive therapeutic intervention directed at an earlier stage than is currently possible.

The Impact of Admissions for the Management of End-stage renal disease on hospital bed occupancy

BACKGROUND:

End-stage renal disease (ESRD) is increasingly prevalent but the inpatient costs associated with this condition are poorly defined due to limitations with data extraction and failure to differentiate between hospitalisation for renal and non-renal disease reasons. The impact of admissions primarily for the management of ESRD on hospital bed utilisation was assessed over a 5-year period in a large teaching hospital.

METHODS:

All admission episodes were reviewed and the ESRD group was identified by a primary International Classification of Diseases code for ESRD or a non-specific primary renal failure code with a secondary code for ESRD. The frequency and duration of hospitalisation and contribution to bed day occupancy of this group with ESRD was determined.

RESULTS:

There were 70,808 patients responsible for a total of 116,915 admissions and 919,212 bed days over the study period. Of these, 988 (1.4%) patients were admitted for the management of ESRD, accounting for 2,387 (2.0%) of admissions and utilisation of 23,011 (2.5%) bed days. After adjustment for age and gender, those admitted for ESRD management were significantly more likely to have a prolonged admission exceeding 30 days (odds ratio 1.46, 95% confidence interval 1.23-1.72, p < 0.001). When the admission was an emergency rather than an elective event, the patient was 4.6 times more likely to be hospitalised for over 30 days.

CONCLUSIONS:

Persons admitted for ESRD management are hospitalised more frequently and for longer than the overall inpatient population, occupying a substantial number of bed days.

Short interfering RNA-mediated gene silencing in Globodera pallida and Meloidogyne incognita infective stage juveniles

The analysis of gene function through RNA interference (RNAi)-based reverse genetics in plant parasitic nematodes (PPNs) remains inexplicably reliant on the use of long double-stranded RNA (dsRNA) silencing triggers; a practice inherently disadvantageous due to the introduction of superfluous dsRNA sequence. increasing chances of aberrant or off-target gene silencing through interactions between nascent short interfering RNAs (siRNAs) and non-cognate mRNA targets. Recently, we have shown that non-nematode, long dsRNAs have a propensity to elicit profound impacts on the phenotype and migrational abilities of both root knot and cyst nematodes. This study presents, to our knowledge for the first time, gene-specific knockdown of FMRFamide-like peptide (flp) transcripts, using discrete 21 bp siRNAs in potato cyst nematode Globodera pallida, and root knot nematode Meloidogyne incognita infective (J2) stage juveniles. Both knockdown at the transcript level through quantitative (q)PCR analysis and functional data derived from migration assay, indicate that siRNAs targeting certain areas of the FMRFamide-like peptide (FLP) transcripts are potent and specific in the silencing of gene function. In addition, we present a method of manipulating siRNA activity through the management of strand thermodynamics. Initial evaluation of strand thermodynamics as a determinant of RNA-induced Silencing Complex (RISC) strand selection (inferred from knockdown efficacy) in the siRNAs presented here suggested that the purported influence of 5' stand stability on guide incorporation may be somewhat promiscuous. However, we have found that on strategically incorporating base mismatches in the sense strand of a G. pallida-specific siRNA we could specifically increase or decrease the knockdown of its target (specific to the antisense strand), presumably through creating more favourable thermodynamic profiles for incorporation of either the sense (non-target-specific) or antisense (target-specific) strand into a cleavage-competent RISC. Whilst the efficacy of similar approaches to siRNA modification has been demonstrated in the context of Drosophila whole-cell lysate preparations and in mammalian cell cultures, it remained to be seen how these sense strand mismatches may impact on gene silencing in vivo, in relation to different targets and in different sequence contexts. This work presents the first application of such an approach in a whole organism; initial results show promise. (C) 2009 Australian Society for Parasitology Inc. Published by Elsevier Ltd. All rights reserved.

Evaluation of Five Interleukin Genes for Association with End-Stage Renal Disease in White Europeans

Background: Genetic variation within interleukin genes has been reported to be associated with end-stage renal disease (ESRD). These findings have not been consistently replicated. No study has yet reported the comprehensive investigation of IL1A, IL1B, IL1RN, IL6 and IL10 genes. Methods: 664 kidney transplant recipients (cases) and 577 kidney donors (controls) were genotyped to establish if common variants in interleukin genes are associated with ESRD. Single nucleotide polymorphism (SNP) genotype data for each gene were downloaded for a northern and western European population from the International HapMap Project. Haploview was used to visualize linkage disequilibrium and select tag SNPs. Thirty SNPs were genotyped using MassARRAY (R) iPLEX Gold technology and data were analyzed using the chi(2) test for trend. Independent replication was conducted in 1,269 individuals with similar phenotypic characteristics. Results: Investigating all common variants in IL1A, IL1B, IL1RN, IL6 and IL10 genes revealed a statistically significant association (rs452204 p(empirical) = 0.02) with one IL1RN variant and ESRD. This IL1RN SNP tags three other variants, none of which have previously been reported to be associated with renal disease. Independent replication in a separate transplant population of comparable size did not confirm the original observation. Conclusions: Common variants in these five candidate interleukin genes are not major risk factors for ESRD in white Europeans. Copyright (C) 2010 S. Karger AG, Basel

Two-stage mixed discrete-continuous identification of radial basis function (RBF) neural models for nonlinear systems

The identification of nonlinear dynamic systems using radial basis function (RBF) neural models is studied in this paper. Given a model selection criterion, the main objective is to effectively and efficiently build a parsimonious compact neural model that generalizes well over unseen data. This is achieved by simultaneous model structure selection and optimization of the parameters over the continuous parameter space. It is a mixed-integer hard problem, and a unified analytic framework is proposed to enable an effective and efficient two-stage mixed discrete-continuous; identification procedure. This novel framework combines the advantages of an iterative discrete two-stage subset selection technique for model structure determination and the calculus-based continuous optimization of the model parameters. Computational complexity analysis and simulation studies confirm the efficacy of the proposed algorithm.