Comparison of risk-scoring systems in the prediction of outcome after liver resection

Background: Risk prediction techniques commonly used in liver surgery include the American Society of Anesthesiologists (ASA) grading, Charlson Comorbidity Index (CCI) and cardiopulmonary exercise tests (CPET). This study compares the utility of these techniques along with the number of segments resected as predictive tools in liver surgery. Methods: A review of a unit database of patients undergoing liver resection between February 2008 and January 2015 was undertaken. Patient demographics, ASA, CCI and CPET variables were recorded along with resection size. Clavien-Dindo grade III–V complications were used as a composite outcome in analyses. Association between predictive variables and outcome was assessed by univariate and multivariate techniques. Results: One hundred and seventy-two resections in 168 patients were identified. Grade III–V complications occurred after 42 (24.4%) liver resections. In univariate analysis of CPET variables, ventilatory equivalents for CO2 (VEqCO2) was associated with outcome. CCI score, but not ASA grade, was also associated with outcome. In multivariate analysis, the odds ratio of developing grade III–V complications for incremental increases in VEqCO2, CCI and number of liver segments resected were 1.09, 1.49 and 2.94, respectively. Conclusions: Of the techniques evaluated, resection size provides the simplest and most discriminating predictor of significant complications following liver surgery

Fine-Tuning Enhancer Models to Predict Transcriptional Targets across Multiple Genomes

Networks of regulatory relations between transcription factors (TF) and their target genes (TG)- implemented through TF binding sites (TFBS)- are key features of biology. An idealized approach to solving such networks consists of starting from a consensus TFBS or a position weight matrix (PWM) to generate a high accuracy list of candidate TGs for biological validation. Developing and evaluating such approaches remains a formidable challenge in regulatory bioinformatics. We perform a benchmark study on 34 Drosophila TFs to assess existing TFBS and cis-regulatory module (CRM) detection methods, with a strong focus on the use of multiple genomes. Particularly, for CRM-modelling we investigate the addition of orthologous sites to a known PWM to construct phyloPWMs and we assess the added value of phylogenentic footprinting to predict contextual motifs around known TFBSs. For CRM-prediction, we compare motif conservation with network-level conservation approaches across multiple genomes. Choosing the optimal training and scoring strategies strongly enhances the performance of TG prediction for more than half of the tested TFs. Finally, we analyse a 35th TF, namely Eyeless, and find a significant overlap between predicted TGs and candidate TGs identified by microarray expression studies. In summary we identify several ways to optimize TF-specific TG predictions, some of which can be applied to all TFs, and others that can be applied only to particular TFs. The ability to model known TF-TG relations, together with the use of multiple genomes, results in a significant step forward in solving the architecture of gene regulatory networks

Arabidopsis COP1 shapes the temporal pattern of CO accumulation conferring a photoperiodic flowering response

The transcriptional regulator CONSTANS (CO) promotes flowering of Arabidopsis under long summer days (LDs) but not under short winter days (SDs). Post-translational regulation of CO is crucial for this response by stabilizing the protein at the end of a LD, whereas promoting its degradation throughout the night under LD and SD. We show that mutations in CONSTITUTIVE PHOTOMORPHOGENIC 1 (COP1), a component of a ubiquitin ligase, cause extreme early flowering under SDs, and that this is largely dependent on CO activity. Furthermore, transcription of the CO target gene FT is increased in cop1 mutants and decreased in plants overexpressing COP1 in phloem companion cells. COP1 and CO interact in vivo and in vitro through the C-terminal region of CO. COP1 promotes CO degradation mainly in the dark, so that in cop1 mutants CO protein but not CO mRNA abundance is dramatically increased during the night. However, in the morning CO degradation occurs independently of COP1 by a phytochrome B-dependent mechanism. Thus, COP1 contributes to day length perception by reducing the abundance of CO during the night and thereby delaying flowering under SDs

The ε3 and ε4 Alleles of Human APOE Differentially Affect Tau Phosphorylation in Hyperinsulinemic and Pioglitazone Treated Mice

Impaired insulin signalling is increasingly thought to contribute to Alzheimer's disease (AD). The ε4 isoform of the APOE gene is the greatest genetic risk factor for sporadic, late onset AD, and is also associated with risk for type 2 diabetes mellitus (T2DM). Neuropathological studies reported the highest number of AD lesions in brain tissue of ε4 diabetic patients. However other studies assessing AD pathology amongst the diabetic population have produced conflicting reports and have failed to show an increase in AD-related pathology in diabetic brain. The thiazolidinediones (TZDs), peroxisome proliferator-activated receptor gamma agonists, are peripheral insulin sensitisers used to treat T2DM. The TZD, pioglitazone, improved memory and cognitive functions in mild to moderate AD patients. Since it is not yet clear how apoE isoforms influence the development of T2DM and its progression to AD, we investigated amyloid beta and tau pathology in APOE knockout mice, carrying human APOEε3 or ε4 transgenes after diet-induced insulin resistance with and without pioglitazone treatment.Male APOE knockout, APOEε3-transgenic and APOEε4-transgenic mice, together with background strain C57BL6 mice were kept on a high fat diet (HFD) or low fat diet (LFD) for 32 weeks, or were all fed HFD for 32 weeks and during the final 3 weeks animals were treated with pioglitazone or vehicle.All HFD animals developed hyperglycaemia with elevated plasma insulin. Tau phosphorylation was reduced at 3 epitopes (Ser396, Ser202/Thr205 and Thr231) in all HFD, compared to LFD, animals independent of APOE genotype. The introduction of pioglitazone to HFD animals led to a significant reduction in tau phosphorylation at the Ser202/Thr205 epitope in APOEε3 animals only. We found no changes in APP processing however the levels of soluble amyloid beta 40 was reduced in APOE knockout animals treated with pioglitazone

Mycorrhizal fungi suppress aggressive Agricultural weeds.

Plant growth responses to arbuscular mycorrhizal fungi (AMF) are highly variable, ranging from mutualism in a wide range of plants, to antagonism in some non-mycorrhizal plant species and plants characteristic of disturbed environments. Many agricultural weeds are non mycorrhizal or originate from ruderal environments where AMF are rare or absent. This led us to hypothesize that AMF may suppress weed growth, a mycorrhizal attribute which has hardly been considered. We investigated the impact of AMF and AMF diversity (three versus one AMF taxon) on weed growth in experimental microcosms where a crop (sunflower) was grown together with six widespread weed species. The presence of AMF reduced total weed biomass with 47% in microcosms where weeds were grown together with sunflower and with 25% in microcosms where weeds were grown alone. The biomass of two out of six weed species was significantly reduced by AMF (-66% & -59%) while the biomass of the four remaining weed species was only slightly reduced (-20% to -37%). Sunflower productivity was not influenced by AMF or AMF diversity. However, sunflower benefitted from AMF via enhanced phosphorus nutrition. The results indicate that the stimulation of arbuscular mycorrhizal fungi in agro-ecosystems may suppress some aggressive weeds

Microbiome to Brain:Unravelling the Multidirectional Axes of Communication

The gut microbiome plays a crucial role in host physiology. Disruption of its community structure and function can have wide-ranging effects making it critical to understand exactly how the interactive dialogue between the host and its microbiota is regulated to maintain homeostasis. An array of multidirectional signalling molecules is clearly involved in the host-microbiome communication. This interactive signalling not only impacts the gastrointestinal tract, where the majority of microbiota resides, but also extends to affect other host systems including the brain and liver as well as the microbiome itself. Understanding the mechanistic principles of this inter-kingdom signalling is fundamental to unravelling how our supraorganism function to maintain wellbeing, subsequently opening up new avenues for microbiome manipulation to favour desirable mental health outcome