Simulated-Physiological Loading Conditions Preserve Biological and Mechanical Properties of Caprine Lumbar Intervertebral Discs in Ex Vivo Culture

Low-back pain (LBP) is a common medical complaint and associated with high societal costs. Degeneration of the intervertebral disc (IVD) is assumed to be an important causal factor of LBP. IVDs are continuously mechanically loaded and both positive and negative effects have been attributed to different loading conditions

The conservation and uniqueness of the caspase family in the basal chordate, amphioxus

<p>Abstract</p> <p>Background</p> <p>The caspase family, which plays a central role in apoptosis in metazoans, has undergone an expansion in amphioxus, increasing to 45 members through domain recombination and shuffling.</p> <p>Results</p> <p>In order to shed light on the conservation and uniqueness of this family in amphioxus, we cloned three representative caspase genes, designated as <it>bbtCaspase-8, bbtCaspase-1/2 </it>and <it>bbtCaspase3</it>-like, from the amphioxus <it>Branchiostoma belcheri tsingtauense</it>. We found that <it>bbtCaspase-8 </it>with conserved protein architecture is involved in the Fas-associated death domain-Caspase-8 mediated pro-apoptotic extrinsic pathway, while <it>bbtCaspase3</it>-like may mediate a nuclear apoptotic pathway in amphioxus. Also, <it>bbtCaspase-1/2 </it>can co-localize with <it>bbtFADD2 </it>in the nucleus, and be recruited to the cytoplasm by amphioxus apoptosis associated speck-like proteins containing a caspase recruitment domain, indicating that <it>bbtCaspase-1/2 </it>may serve as a switch between apoptosis and caspase-dependent innate immune response in invertebrates. Finally, amphioxus extrinsic apoptotic pathway related caspases played important roles in early embryogenesis.</p> <p>Conclusions</p> <p>Our study not only demonstrates the conservation of <it>bbtCaspase-8 </it>in apoptosis, but also reveals the unique features of several amphioxus caspases with novel domain architectures arose some 500 million years ago.</p

Expression of oestrogen receptors, ERα, ERβ, and ERβ variants, in endometrial cancers and evidence that prostaglandin F may play a role in regulating expression of ERα

<p>Abstract</p> <p>Background</p> <p>Endometrial cancer is the most common gynaecological malignancy; risk factors include exposure to oestrogens and high body mass index. Expression of enzymes involved in biosynthesis of oestrogens and prostaglandins (PG) is often higher in endometrial cancers when compared with levels detected in normal endometrium. Oestrogens bind one of two receptors (ERα and ERβ) encoded by separate genes. The full-length receptors function as ligand-activated transcription factors; splice variant isoforms of ERβ lacking a ligand-binding domain have also been described. PGs act in an autocrine or paracrine manner by binding to specific G-protein coupled receptors.</p> <p>Methods</p> <p>We compared expression of ERs, progesterone receptor (PR) and cyclooxygenase-2 (COX-2) in stage 1 endometrial adenocarcinomas graded as well (G1), moderately (G2) or poorly (G3) differentiated (n ≥ 10 each group) using qRTPCR, single and double immunohistochemistry. We used endometrial adenocarcinoma cell lines to investigate the impact of PGF2α on expression of ERs and PR.</p> <p>Results</p> <p>Full length ERβ (ERβ1) and two ERβ variants (ERβ2, ERβ5) were expressed in endometrial cancers regardless of grade and the proteins were immunolocalised to the nuclei of cells in both epithelial and stromal compartments. Immunoexpression of COX-2 was most intense in cells that were ERα^neg/low. Expression of PR in endometrial adenocarcinoma (Ishikawa) cell lines and tissues broadly paralleled that of ERα. Treatment of adenocarcinoma cells with PGF2α reduced expression of ERα but had no impact on ERβ1. Cells incubated with PGF2α were unable to increase expression of PR mRNA when they were incubated with E2.</p> <p>Conclusion</p> <p>We have demonstrated that ERβ5 protein is expressed in stage 1 endometrial adenocarcinomas. Expression of three ERβ variants, including the full-length protein is not grade-dependent and most cells in poorly differentiated cancers are ERβ^pos/ERα^neg. We found evidence of a link between COX-2, its product PGF2α, and expression of ERα and PR that sheds new light on the cross talk between steroid and PG signalling pathways in this disease.</p

The Drosophila melanogaster host model

The deleterious and sometimes fatal outcomes of bacterial infectious diseases are the net result of the interactions between the pathogen and the host, and the genetically tractable fruit fly, Drosophila melanogaster, has emerged as a valuable tool for modeling the pathogen–host interactions of a wide variety of bacteria. These studies have revealed that there is a remarkable conservation of bacterial pathogenesis and host defence mechanisms between higher host organisms and Drosophila. This review presents an in-depth discussion of the Drosophila immune response, the Drosophila killing model, and the use of the model to examine bacterial–host interactions. The recent introduction of the Drosophila model into the oral microbiology field is discussed, specifically the use of the model to examine Porphyromonas gingivalis–host interactions, and finally the potential uses of this powerful model system to further elucidate oral bacterial-host interactions are addressed

The poly-omics of ageing through individual-based metabolic modelling

Abstract Background Ageing can be classified in two different ways, chronological ageing and biological ageing. While chronological age is a measure of the time that has passed since birth, biological (also known as transcriptomic) ageing is defined by how time and the environment affect an individual in comparison to other individuals of the same chronological age. Recent research studies have shown that transcriptomic age is associated with certain genes, and that each of those genes has an effect size. Using these effect sizes we can calculate the transcriptomic age of an individual from their age-associated gene expression levels. The limitation of this approach is that it does not consider how these changes in gene expression affect the metabolism of individuals and hence their observable cellular phenotype. Results We propose a method based on poly-omic constraint-based models and machine learning in order to further the understanding of transcriptomic ageing. We use normalised CD4 T-cell gene expression data from peripheral blood mononuclear cells in 499 healthy individuals to create individual metabolic models. These models are then combined with a transcriptomic age predictor and chronological age to provide new insights into the differences between transcriptomic and chronological ageing. As a result, we propose a novel metabolic age predictor. Conclusions We show that our poly-omic predictors provide a more detailed analysis of transcriptomic ageing compared to gene-based approaches, and represent a basis for furthering our knowledge of the ageing mechanisms in human cells

Advances in structure elucidation of small molecules using mass spectrometry

The structural elucidation of small molecules using mass spectrometry plays an important role in modern life sciences and bioanalytical approaches. This review covers different soft and hard ionization techniques and figures of merit for modern mass spectrometers, such as mass resolving power, mass accuracy, isotopic abundance accuracy, accurate mass multiple-stage MS(n) capability, as well as hybrid mass spectrometric and orthogonal chromatographic approaches. The latter part discusses mass spectral data handling strategies, which includes background and noise subtraction, adduct formation and detection, charge state determination, accurate mass measurements, elemental composition determinations, and complex data-dependent setups with ion maps and ion trees. The importance of mass spectral library search algorithms for tandem mass spectra and multiple-stage MS(n) mass spectra as well as mass spectral tree libraries that combine multiple-stage mass spectra are outlined. The successive chapter discusses mass spectral fragmentation pathways, biotransformation reactions and drug metabolism studies, the mass spectral simulation and generation of in silico mass spectra, expert systems for mass spectral interpretation, and the use of computational chemistry to explain gas-phase phenomena. A single chapter discusses data handling for hyphenated approaches including mass spectral deconvolution for clean mass spectra, cheminformatics approaches and structure retention relationships, and retention index predictions for gas and liquid chromatography. The last section reviews the current state of electronic data sharing of mass spectra and discusses the importance of software development for the advancement of structure elucidation of small molecules