Fabrication and Mechanical Properties of Chitosan-Montmorillonite Nano-composite

Chitosan has found various applications in gastrointestinal stent, biomedical implants as well as an effective absorbent in waste water treatment. However, the material suffers from low strength and large shrinkage upon dehydration. The current project is aimed to develop a process to fabricate chitosan composites with the addition of functionalised montmorillonite nanoparticles and to examine the effect of ceramic content on the mechanical behavior of the composites. This paper describes the fabrication of chitosan with montmorrillonite composites and the mechanical testing of the samples and the mechanical behaviour of the composites, as well as the observations of the microstructure. The effects of composition and microstructure on the mechanical properties of the composite are investigated. The results indicate that the nanoparticles are dispersed uniformly in the matrix up to 40wt% using high speed homogeniser. The elastic modulus increases monotonically with the addition of nanoparticles, but the fracture strength drops due to the defects introduced by the nanoparticles.</jats:p

dCas9-based epigenome editing suggests acquisition of histone methylation is not sufficient for target gene repression.

Distinct epigenomic profiles of histone marks have been associated with gene expression, but questions regarding the causal relationship remain. Here we investigated the activity of a broad collection of genomically targeted epigenetic regulators that could write epigenetic marks associated with a repressed chromatin state (G9A, SUV39H1, Krüppel-associated box (KRAB), DNMT3A as well as the first targetable versions of Ezh2 and Friend of GATA-1 (FOG1)). dCas9 fusions produced target gene repression over a range of 0- to 10-fold that varied by locus and cell type. dCpf1 fusions were unable to repress gene expression. The most persistent gene repression required the action of several effector domains; however, KRAB-dCas9 did not contribute to persistence in contrast to previous reports. A 'direct tethering' strategy attaching the Ezh2 methyltransferase enzyme to dCas9, as well as a 'recruitment' strategy attaching the N-terminal 45 residues of FOG1 to dCas9 to recruit the endogenous nucleosome remodeling and deacetylase complex, were both successful in targeted deposition of H3K27me3. Surprisingly, however, repression was not correlated with deposition of either H3K9me3 or H3K27me3. Our results suggest that so-called repressive histone modifications are not sufficient for gene repression. The easily programmable dCas9 toolkit allowed precise control of epigenetic information and dissection of the relationship between the epigenome and gene regulation

Lightcurve Classification in Massive Variability Surveys II: Transients towards the Large Magellanic Cloud

Automatic classification of variability is now possible with tools like neural networks. Here, we present two neural networks for the identification of microlensing events -- the first discriminates against variable stars and the second against supernovae. The inputs to the networks include parameters describing the shape and the size of the lightcurve, together with colour of the event. The network computes the posterior probability of microlensing, together with an estimate of the likely error. An algorithm is devised for direct calculation of the microlensing rate from the output of the neural networks. We present a new analysis of the microlensing candidates towards the Large Magellanic Cloud (LMC). The neural networks confirm the microlensing nature of only 7 of the possible 17 events identified by the MACHO experiment. This suggests that earlier estimates of the microlensing optical depth towards the LMC may have been overestimated. A smaller number of events is consistent with the assumption that all the microlensing events are caused by the known stellar populations in the outer Galaxy/LMC.Comment: 11 pages, MNRAS, in pres

On accuracy of PDF divergence estimators and their applicability to representative data sampling

Generalisation error estimation is an important issue in machine learning. Cross-validation traditionally used for this purpose requires building multiple models and repeating the whole procedure many times in order to produce reliable error estimates. It is however possible to accurately estimate the error using only a single model, if the training and test data are chosen appropriately. This paper investigates the possibility of using various probability density function divergence measures for the purpose of representative data sampling. As it turned out, the first difficulty one needs to deal with is estimation of the divergence itself. In contrast to other publications on this subject, the experimental results provided in this study show that in many cases it is not possible unless samples consisting of thousands of instances are used. Exhaustive experiments on the divergence guided representative data sampling have been performed using 26 publicly available benchmark datasets and 70 PDF divergence estimators, and their results have been analysed and discussed

Work stress and cancer researchers : an exploration of the challenges, experiences and training needs of UK cancer researchers.

Work stress is a significant issue for many UK healthcare professionals, in particular those working in the field of oncology. However, there have been very few attempts to explore the challenges, experiences or training needs of researchers working in cancer research. In doing so, we will be better positioned to support and develop these researchers. 18 UK oncology researchers from a variety of backgrounds took part in a semi-structured interview. Interviews were transcribed and analysed using thematic analysis. The analysis identified two overarching themes: logistical research issues (workload, accessing/ recruiting participants, finances) and sensitive research issues (emotional demands, professional boundaries, sensitivity around recruitment). One cross-cutting theme, supportive strategies (support and training, coping mechanisms), was seen to influence both logistical and sensitive research issues. While further research is needed to fully understand the causes and impact of work stress on cancer researchers, three specific issues were highlighted: emotional demands are relevant to quantitative and mixed methods researchers as well as those engaged in qualitative research; the researchers’ background (experience; clinical/non-clinical) was influential and an exploration of effective coping strategies is required; and there is a clear need for adequate support systems and training to be available, particularly for early career researchers.</p

Inflammatory thresholds and the species-specific effects of colonising bacteria in stable chronic obstructive pulmonary disease

There has been increasing interest in the use of newer, culture-independent techniques to study the airway microbiome of COPD patients. We investigated the relationships between the three common potentially pathogenic microorganisms (PPMs) Haemophilus influenzae, Streptococcus pneumoniae and Moraxella catarrhalis, as detected by quantitative PCR (qPCR), and inflammation and health status in stable patients in the London COPD cohort