Historic landmarks in clinical transplantation: Conclusions from the consensus conference at the University of California, Los Angeles

The transplantation of organs, cells, and tissues has burgeoned during the last quarter century, with the development of multiple new specialty fields. However, the basic principles that made this possible were established over a three-decade period, beginning during World War II and ending in 1974. At the historical consensus conference held at UCLA in March 1999, 11 early workers in the basic science or clinical practice of transplantation (or both) reached agreement on the most significant contribution of this era that ultimately made transplantation the robust clinical discipline it is today. These discoveries and achievements are summarized here is six tables and annotated with references

Seminal plasma as a source of prostate cancer peptide biomarker candidates for detection of indolent and advanced disease

Background:Extensive prostate specific antigen screening for prostate cancer generates a high number of unnecessary biopsies and over-treatment due to insufficient differentiation between indolent and aggressive tumours. We hypothesized that seminal plasma is a robust source of novel prostate cancer (PCa) biomarkers with the potential to improve primary diagnosis of and to distinguish advanced from indolent disease. <br>Methodology/Principal Findings: In an open-label case/control study 125 patients (70 PCa, 21 benign prostate hyperplasia, 25 chronic prostatitis, 9 healthy controls) were enrolled in 3 centres. Biomarker panels a) for PCa diagnosis (comparison of PCa patients versus benign controls) and b) for advanced disease (comparison of patients with post surgery Gleason score <7 versus Gleason score >>7) were sought. Independent cohorts were used for proteomic biomarker discovery and testing the performance of the identified biomarker profiles. Seminal plasma was profiled using capillary electrophoresis mass spectrometry. Pre-analytical stability and analytical precision of the proteome analysis were determined. Support vector machine learning was used for classification. Stepwise application of two biomarker signatures with 21 and 5 biomarkers provided 83% sensitivity and 67% specificity for PCa detection in a test set of samples. A panel of 11 biomarkers for advanced disease discriminated between patients with Gleason score 7 and organ-confined (<pT3a) or advanced (≥pT3a) disease with 80% sensitivity and 82% specificity in a preliminary validation setting. Seminal profiles showed excellent pre-analytical stability. Eight biomarkers were identified as fragments of N-acetyllactosaminide beta-1,3-N-acetylglucosaminyltransferase​,prostatic acid phosphatase, stabilin-2, GTPase IMAP family member 6, semenogelin-1 and -2. Restricted sample size was the major limitation of the study.</br> <br>Conclusions/Significance: Seminal plasma represents a robust source of potential peptide makers for primary PCa diagnosis. Our findings warrant further prospective validation to confirm the diagnostic potential of identified seminal biomarker candidates.</br&gt

Robust Detection of Hierarchical Communities from Escherichia coli Gene Expression Data

Determining the functional structure of biological networks is a central goal of systems biology. One approach is to analyze gene expression data to infer a network of gene interactions on the basis of their correlated responses to environmental and genetic perturbations. The inferred network can then be analyzed to identify functional communities. However, commonly used algorithms can yield unreliable results due to experimental noise, algorithmic stochasticity, and the influence of arbitrarily chosen parameter values. Furthermore, the results obtained typically provide only a simplistic view of the network partitioned into disjoint communities and provide no information of the relationship between communities. Here, we present methods to robustly detect coregulated and functionally enriched gene communities and demonstrate their application and validity for Escherichia coli gene expression data. Applying a recently developed community detection algorithm to the network of interactions identified with the context likelihood of relatedness (CLR) method, we show that a hierarchy of network communities can be identified. These communities significantly enrich for gene ontology (GO) terms, consistent with them representing biologically meaningful groups. Further, analysis of the most significantly enriched communities identified several candidate new regulatory interactions. The robustness of our methods is demonstrated by showing that a core set of functional communities is reliably found when artificial noise, modeling experimental noise, is added to the data. We find that noise mainly acts conservatively, increasing the relatedness required for a network link to be reliably assigned and decreasing the size of the core communities, rather than causing association of genes into new communities.Comment: Due to appear in PLoS Computational Biology. Supplementary Figure S1 was not uploaded but is available by contacting the author. 27 pages, 5 figures, 15 supplementary file

Spatial Guilds in the Serengeti Food Web Revealed by a Bayesian Group Model

Food webs, networks of feeding relationships among organisms, provide fundamental insights into mechanisms that determine ecosystem stability and persistence. Despite long-standing interest in the compartmental structure of food webs, past network analyses of food webs have been constrained by a standard definition of compartments, or modules, that requires many links within compartments and few links between them. Empirical analyses have been further limited by low-resolution data for primary producers. In this paper, we present a Bayesian computational method for identifying group structure in food webs using a flexible definition of a group that can describe both functional roles and standard compartments. The Serengeti ecosystem provides an opportunity to examine structure in a newly compiled food web that includes species-level resolution among plants, allowing us to address whether groups in the food web correspond to tightly-connected compartments or functional groups, and whether network structure reflects spatial or trophic organization, or a combination of the two. We have compiled the major mammalian and plant components of the Serengeti food web from published literature, and we infer its group structure using our method. We find that network structure corresponds to spatially distinct plant groups coupled at higher trophic levels by groups of herbivores, which are in turn coupled by carnivore groups. Thus the group structure of the Serengeti web represents a mixture of trophic guild structure and spatial patterns, in contrast to the standard compartments typically identified in ecological networks. From data consisting only of nodes and links, the group structure that emerges supports recent ideas on spatial coupling and energy channels in ecosystems that have been proposed as important for persistence.Comment: 28 pages, 6 figures (+ 3 supporting), 2 tables (+ 4 supporting

Early Adverse Events, HPA Activity and Rostral Anterior Cingulate Volume in MDD

Prior studies have independently reported associations between major depressive disorder (MDD), elevated cortisol concentrations, early adverse events and region-specific decreases in grey matter volume, but the relationships among these variables are unclear. In the present study, we sought to evaluate the relationships between grey matter volume, early adverse events and cortisol levels in MDD.Grey matter volume was compared between 19 controls and 19 individuals with MDD using voxel-based morphometry. A history of early adverse events was assessed using the Childhood Trauma Questionnaire. Subjects also provided salivary cortisol samples. Depressed patients showed decreased grey matter volume in the rostral ACC as compared to controls. Rostral ACC volume was inversely correlated with both cortisol and early adverse events.These findings suggest a key relationship between ACC morphology, a history of early adverse events and circulating cortisol in the pathophysiology of MDD

A constructive approach for discovering new drug leads: Using a kernel methodology for the inverse-QSAR problem

<p>Abstract</p> <p>Background</p> <p>The inverse-QSAR problem seeks to find a new molecular descriptor from which one can recover the structure of a molecule that possess a desired activity or property. Surprisingly, there are very few papers providing solutions to this problem. It is a difficult problem because the molecular descriptors involved with the inverse-QSAR algorithm must adequately address the forward QSAR problem for a given biological activity if the subsequent recovery phase is to be meaningful. In addition, one should be able to construct a feasible molecule from such a descriptor. The difficulty of recovering the molecule from its descriptor is the major limitation of most inverse-QSAR methods.</p> <p>Results</p> <p>In this paper, we describe the reversibility of our previously reported descriptor, the vector space model molecular descriptor (VSMMD) based on a vector space model that is suitable for kernel studies in QSAR modeling. Our inverse-QSAR approach can be described using five steps: (1) generate the VSMMD for the compounds in the training set; (2) map the VSMMD in the input space to the kernel feature space using an appropriate kernel function; (3) design or generate a new point in the kernel feature space using a kernel feature space algorithm; (4) map the feature space point back to the input space of descriptors using a pre-image approximation algorithm; (5) build the molecular structure template using our VSMMD molecule recovery algorithm.</p> <p>Conclusion</p> <p>The empirical results reported in this paper show that our strategy of using kernel methodology for an inverse-Quantitative Structure-Activity Relationship is sufficiently powerful to find a meaningful solution for practical problems.</p

Variation in the Ovine Abomasal Lymph Node Transcriptome between Breeds Known to Differ in Resistance to the Gastrointestinal Nematode

Texel lambs are known to be more resistant to gastrointestinal nematode (GIN) infection than Suffolk lambs, with a greater ability to limit infection. The objectives of this study were to: 1) profile the whole transcriptome of abomasal lymph node tissue of GIN-free Texel and Suffolk lambs; 2) identify differentially expressed genes and characterize the immune-related biological pathways and networks associated with these genes. Abomasal lymph nodes were collected from Texel (n = 6) and Suffolk (n = 4) lambs aged 19 weeks that had been GIN-free since 6 weeks of age. Whole transcriptome profiling was performed using RNA-seq on the Illumina platform. At the time of conducting this study, a well annotated Ovine genome was not available and hence the sequence reads were aligned with the Bovine (UMD3.1) genome. Identification of differentially expressed genes was followed by pathway and network analysis. The Suffolk breed accounted for significantly more of the differentially expressed genes, (276 more highly expressed in Suffolk v 162 in Texel; P < 0.001). The four most significant differentially expressed pathways were all related to immunity and were classified as: Role of Pattern Recognition Receptors in Recognition of Bacteria and Viruses, Activation of IRF by Cytosolic Pattern Recognition Receptors, Role of RIG-I-like Receptors in Antiviral Innate Immunity, and Interferon Signaling. Of significance is the fact that all of these four pathways were more highly expressed in the Suffolk. These data suggest that in a GIN-free environment, Suffolk lambs have a more active immune profile relative to the Texel: this immune profile may contribute to the poorer efficiency of response to a GIN challenge in the Suffolk breed compared to the Texel breed

An Estimation of Erinaceidae Phylogeny: A Combined Analysis Approach

BACKGROUND: Erinaceidae is a family of small mammals that include the spiny hedgehogs (Erinaceinae) and the silky-furred moonrats and gymnures (Galericinae). These animals are widely distributed across Eurasia and Africa, from the tundra to the tropics and the deserts to damp forests. The importance of these animals lies in the fact that they are the oldest known living placental mammals, which are well represented in the fossil record, a rarity fact given their size and vulnerability to destruction during fossilization. Although the Family has been well studied, their phylogenetic relationships remain controversial. To test previous phylogenetic hypotheses, we combined molecular and morphological data sets, including representatives of all the genera. METHODOLOGY AND PRINCIPAL FINDINGS: We included in the analyses 3,218 bp mitochondrial genes, one hundred and thirty-five morphological characters, twenty-two extant erinaceid taxa, and five outgroup taxa. Phylogenetic relationships were reconstructed using both partitioned and combined data sets. As in previous analyses, our results strongly support the monophyly of both subfamilies (Galericinae and Erinaceinae), the Hylomys group (to include Neotetracus and Neohylomys), and a sister-relationship of Atelerix and Erinaceus. As well, we verified that the extremely long branch lengths within the Galericinae are consistent with their fossil records. Not surprisingly, we found significant incongruence between the phylogenetic signals of the genes and the morphological characters, specifically in the case of Hylomys parvus, Mesechinus, and relationships between Hemiechinus and Paraechinus. CONCLUSIONS: Although we discovered new clues to understanding the evolutionary relationships within the Erinaceidae, our results nonetheless, strongly suggest that more robust analyses employing more complete taxon sampling (to include fossils) and multiple unlinked genes would greatly enhance our understanding of the Erinaceidae. Until then, we have left the nomenclature of the taxa unchanged; hence it does not yet precisely reflect their phylogenetic relationships or the depth of their genetic diversity

Alcohol Induces Sensitization to Gluten in Genetically Susceptible Individuals: A Case Control Study

Background: The mechanisms of cerebellar degeneration attributed to prolonged and excessive alcohol intake remain unclear. Additional or even alternative causes of cerebellar degeneration are often overlooked in suspected cases of alcohol-related ataxia. The objectives of this study were two fold: (1) to investigate the prevalence of gluten-related serological markers in patients with alcohol-related ataxia and; (2) to compare the pattern of brain involvement on magnetic resonance imaging between patients with alcohol and gluten ataxias. Materials & Methods: Patients diagnosed with alcohol and gluten ataxias were identified from a retrospective review of patients attending a tertiary clinic. HLA genotype and serological markers of gluten-related disorders were recorded. Cerebellar volumetry, MR spectroscopy and voxel-based morphometric analyses were performed on patients and compared with matched control data. Results: Of 904 registered patients, 104 had alcohol ataxia and 159 had gluten ataxia. 61% of the alcohol ataxia group and 70% of the gluten ataxia group had HLA DQ2/DQ8 genotype compared to 30% in healthy local blood donors. 44% of patients with alcohol ataxia had antigliadin antibodies compared to 12% in the healthy local population and 10% in patients with genetically confirmed ataxias. None of the patients with alcohol ataxia and antigliadin antibodies had celiac disease compared to 40% in patients with gluten ataxia. The pattern of structural brain abnormality in patients with alcohol ataxia who had antigliadin antibodies differed from gluten ataxia and was identical to that of alcohol ataxia. Conclusions: Alcohol related cerebellar degeneration may, in genetically susceptible individuals, induce sensitization to gluten. Such sensitization may result from a primary cerebellar insult, but a more systemic effect is also possible. The duration and amount of exposure to alcohol may not be the only factors responsible for the cerebellar insult

P. falciparum and P. vivax Epitope-Focused VLPs Elicit Sterile Immunity to Blood Stage Infections

In order to design P. falciparum preerythrocytic vaccine candidates, a library of circumsporozoite (CS) T and B cell epitopes displayed on the woodchuck hepatitis virus core antigen (WHcAg) VLP platform was produced. To test the protective efficacy of the WHcAg-CS VLPs, hybrid CS P. berghei/P. falciparum (Pb/Pf) sporozoites were used to challenge immunized mice. VLPs carrying 1 or 2 different CS repeat B cell epitopes and 3 VLPs carrying different CS non-repeat B cell epitopes elicited high levels of anti-insert antibodies (Abs). Whereas, VLPs carrying CS repeat B cell epitopes conferred 98% protection of the liver against a 10,000 Pb/Pf sporozoite challenge, VLPs carrying the CS non-repeat B cell eptiopes were minimally-to-non-protective. One-to-three CS-specific CD4/CD8 T cell sites were also fused to VLPs, which primed CS-specific as well as WHcAg-specific T cells. However, a VLP carrying only the 3 T cell domains failed to protect against a sporozoite challenge, indicating a requirement for anti-CS repeat Abs. A VLP carrying 2 CS repeat B cell epitopes and 3 CS T cell sites in alum adjuvant elicited high titer anti-CS Abs (endpoint dilution titer \u3e1x106) and provided 80–100% protection against blood stage malaria. Using a similar strategy, VLPs were constructed carrying P. vivax CS repeat B cell epitopes (WHc-Pv-78), which elicited high levels of anti-CS Abs and conferred 99% protection of the liver against a 10,000 Pb/Pv sporozoite challenge and elicited sterile immunity to blood stage infection. These results indicate that immunization with epitope-focused VLPs carrying selected B and T cell epitopes from the P.falciparum and P. vivax CS proteins can elicit sterile immunity against blood stage malaria. Hybrid WHcAg-CS VLPs could provide the basis for a bivalent P. falciparum/P. vivax malaria vaccine