Overexpression, purification and characterization of the Aspergillus niger endoglucanase, EglA, in Pichia pastoris>/i>

Cellulases are industrially important hydrolytic enzymes applicable in the bioconversion of cellulosic biomass to simple sugars. In this work, an endoglucanase from Aspergillus niger ATCC 10574, EglA, was expressed in the methylotrophic yeast Pichia pastoris and the properties of the recombinant protein were characterized. The full length cDNA of eglA has been cloned into a pPICZαC expression vector and expressed extracellularly as a ~30 kDa recombinant protein in P. pastoris X-33. Pure EglA displayed optimum activity at 50°C and was stable between 30 and 55°C. The pH stability of this enzyme was shown to be in the range of pH 2.0 to 7.0 and optimum at pH 4.0. EglA showed the highest affinity toward β-glucan followed by carboxymethyl cellulose (CMC) with a specific activity of 63.83 and 9.47 U/mg, respectively. Very low or no detectable hydrolysis of cellobiose, laminarin, filter paper and avicel were observed. Metal ions such as Mn2+, Co2+, Zn2+, Mg2+, Ba2+, Fe2+, Ca2+ and K+ showed significant augmentation of endoglucanase activity, with manganese ions causing the highest increase in activity to about 2.7 fold when compared with the control assay, whereas Pd2+, Cu2+, SDS and EDTA showed inhibition of EglA activity.Key words: Cellulase, endoglucanase, recombinant, Aspergillus niger, Pichia pastoris

Beyond the Refugee Crisis how the UK news media represent asylum seekers across national boundaries

Migration is one of the most pressing, divisive issues in global politics today, and media play a crucial role in how communities understand and respond. This study examines how UK newspapers (n = 974) and popular news websites (n = 1044) reported on asylum seekers throughout 2017. It contributes to previous literature in two important ways. First, by examining the ‘new normal’ of daily news coverage in the wake of the 2015 ‘refugee crisis’ in Europe. Second, by looking at how asylum seekers from different regions are represented. The content analysis finds significant variations in how asylum seekers are reported, including terminology use and topics they are associated with. The paper also identifies important commonalities in how all asylum seekers are represented - most notably, the dominance of political elites as sources across all media content. It argues that Entman’s ‘cascade network model’ can help to explain this, with elites in one country able to influence transnational reports

Multiple microvessels extending from the coronary arteries to the left ventricle in a middle aged female presenting with ischaemic chest pain: a case report

Possible ischaemic chest pain presentations are exceedingly common. Angiographic triage of clinical, electrocardiographic or biomarker positive presentations is increasingly feasible with the expansion of cardiac catheterization facilities. This management pattern often extends to problem patients with negative biomarker screens whose symptoms appear unstable. With invasive triage even very rare congenital or developmental coronary anomalies will be more frequently recognized although their relationship to ischaemia can be confounded by association. In this a case we report a woman with widespread direct coro-ventricular micro-channel formation across the heart and an ischaemic presentation, despite angiographically normal epicoronary vessels. This pattern, while very rare, needs to be recognized as one possible phenotype in this very common clinical presentation

Limitations of the MELD score in predicting mortality or need for removal from waiting list in patients awaiting liver transplantation

<p>Abstract</p> <p>Background</p> <p>Decompensated cirrhosis is associated with a poor prognosis and liver transplantation provides the only curative treatment option with excellent long-term results. The relative shortage of organ donors renders the allocation algorithms of organs essential. The optimal strategy based on scoring systems and/or waiting time is still under debate.</p> <p>Methods</p> <p>Data sets of 268 consecutive patients listed for single-organ liver transplantation for nonfulminant liver disease between 2003 and 2005 were included into the study. The Model for End-Stage Liver Disease (MELD) and Child-Turcotte-Pugh (CTP) scores of all patients at the time of listing were used for calculation. The predictive ability not only for mortality on the waiting list but also for the need for withdrawal from the waiting list was calculated for both scores. The Mann-Whitney-U Test was used for the univariate analysis and the AUC-Model for discrimination of the scores.</p> <p>Results</p> <p>In the univariate analysis comparing patients who are still on the waiting list and patients who died or were removed from the waiting list due to poor conditions, the serum albumin, bilirubin INR, and CTP and MELD scores as well as the presence of ascites and encephalopathy were significantly different between the groups (p < 0.05), whereas serum creatinine and urea showed no difference.</p> <p>Comparing the predictive abilities of CTP and MELD scores, the best discrimination between patients still alive on the waiting list and patients who died on or were removed from the waiting list was achieved at a CTP score of ≥9 and a MELD score of ≥14.4. The sensitivity and specificity to identify mortality or severe deterioration for CTP was 69.0% and 70.5%, respectively; for MELD, it was 62.1% and 72.7%, respectively. This result was supported by the AUC analysis showing a strong trend for superiority of CTP over MELD scores (AUROC 0.73 and 0.68, resp.; p = 0.091).</p> <p>Conclusion</p> <p>The long term prediction of mortality or removal from waiting list in patients awaiting liver transplantation might be better assessed by the CTP score than the MELD score. This might have implications for the development of new improved scoring systems.</p

How do you say ‘hello’? Personality impressions from brief novel voices

On hearing a novel voice, listeners readily form personality impressions of that speaker. Accurate or not, these impressions are known to affect subsequent interactions; yet the underlying psychological and acoustical bases remain poorly understood. Furthermore, hitherto studies have focussed on extended speech as opposed to analysing the instantaneous impressions we obtain from first experience. In this paper, through a mass online rating experiment, 320 participants rated 64 sub-second vocal utterances of the word ‘hello’ on one of 10 personality traits. We show that: (1) personality judgements of brief utterances from unfamiliar speakers are consistent across listeners; (2) a two-dimensional ‘social voice space’ with axes mapping Valence (Trust, Likeability) and Dominance, each driven by differing combinations of vocal acoustics, adequately summarises ratings in both male and female voices; and (3) a positive combination of Valence and Dominance results in increased perceived male vocal Attractiveness, whereas perceived female vocal Attractiveness is largely controlled by increasing Valence. Results are discussed in relation to the rapid evaluation of personality and, in turn, the intent of others, as being driven by survival mechanisms via approach or avoidance behaviours. These findings provide empirical bases for predicting personality impressions from acoustical analyses of short utterances and for generating desired personality impressions in artificial voices

MRI-based radiomics for prognosis of pediatric diffuse intrinsic pontine glioma: an international study.

Background: Diffuse intrinsic pontine gliomas (DIPGs) are lethal pediatric brain tumors. Presently, MRI is the mainstay of disease diagnosis and surveillance. We identify clinically significant computational features from MRI and create a prognostic machine learning model. Methods: We isolated tumor volumes of T1-post-contrast (T1) and T2-weighted (T2) MRIs from 177 treatment-naïve DIPG patients from an international cohort for model training and testing. The Quantitative Image Feature Pipeline and PyRadiomics was used for feature extraction. Ten-fold cross-validation of least absolute shrinkage and selection operator Cox regression selected optimal features to predict overall survival in the training dataset and tested in the independent testing dataset. We analyzed model performance using clinical variables (age at diagnosis and sex) only, radiomics only, and radiomics plus clinical variables. Results: All selected features were intensity and texture-based on the wavelet-filtered images (3 T1 gray-level co-occurrence matrix (GLCM) texture features, T2 GLCM texture feature, and T2 first-order mean). This multivariable Cox model demonstrated a concordance of 0.68 (95% CI: 0.61-0.74) in the training dataset, significantly outperforming the clinical-only model (C = 0.57 [95% CI: 0.49-0.64]). Adding clinical features to radiomics slightly improved performance (C = 0.70 [95% CI: 0.64-0.77]). The combined radiomics and clinical model was validated in the independent testing dataset (C = 0.59 [95% CI: 0.51-0.67], Noether's test P = .02). Conclusions: In this international study, we demonstrate the use of radiomic signatures to create a machine learning model for DIPG prognostication. Standardized, quantitative approaches that objectively measure DIPG changes, including computational MRI evaluation, could offer new approaches to assessing tumor phenotype and serve a future role for optimizing clinical trial eligibility and tumor surveillance

Role of rapid urease test and histopathology in the diagnosis of Helicobacter pylori infection in a developing country

BACKGROUND: The aim of this study was to determine the effect of commonly self-prescribed proton pump inhibitors (PPI) on the results of rapid urease test and histology for the diagnosis of H. pylori infection. METHODS: One hundred-nine consecutive patients with dyspeptic symptoms attending the endoscopy suite were enrolled in this study. Antrum biopsy specimens were collected at endoscopy for the rapid urease test (Pronto Dry, Medical Instrument Corp, France) and histopathology. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and like-hood ratio of a positive and negative of Pronto Dry test were compared against histology. The gold standard test for the diagnosis of H. pylori infection was histopathology. RESULTS: Sixty-one percent (66/109) patients were males with mean age of 43 ± 14.1 years and age range 17–80 years. Fifty-two percent (57/109) were not on any medications while 48% (52/109) used PPI before presentation to the outpatients. Pronto Dry was positive in 40% (44/109) and negative in 60% (65/109). Histopathology was positive for H. pylori in 57% (62/109) and negative in 43% (47/109). The sensitivity, specificity, PPV, NPV and like-hood ratio of a positive and negative Pronto Dry test with and without PPI were 43.3%, 86.4%, 81.3%, 3.18, 0.656 and 52.8% vs 71.9%, 80%, 82.1%, 69%, 3.59 and 0.35. CONCLUSION: This study shows that the sensitivity, specificity, NPV and PPV of rapid urease test was reduced in patients who are on PPI. The exclusive use of the rapid urease test for the diagnosis of Helicobacter pylori cannot be recommended in patients with prior PPI use

Radiomic signatures of posterior fossa ependymoma: Molecular subgroups and risk profiles

BACKGROUND: The risk profile for posterior fossa ependymoma (EP) depends on surgical and molecular status [Group A (PFA) versus Group B (PFB)]. While subtotal tumor resection is known to confer worse prognosis, MRI-based EP risk-profiling is unexplored. We aimed to apply machine learning strategies to link MRI-based biomarkers of high-risk EP and also to distinguish PFA from PFB. METHODS: We extracted 1800 quantitative features from presurgical T2-weighted (T2-MRI) and gadolinium-enhanced T1-weighted (T1-MRI) imaging of 157 EP patients. We implemented nested cross-validation to identify features for risk score calculations and apply a Cox model for survival analysis. We conducted additional feature selection for PFA versus PFB and examined performance across three candidate classifiers. RESULTS: For all EP patients with GTR, we identified four T2-MRI-based features and stratified patients into high- and low-risk groups, with 5-year overall survival rates of 62% and 100%, respectively (p < 0.0001). Among presumed PFA patients with GTR, four T1-MRI and five T2-MRI features predicted divergence of high- and low-risk groups, with 5-year overall survival rates of 62.7% and 96.7%, respectively (p = 0.002). T1-MRI-based features showed the best performance distinguishing PFA from PFB with an AUC of 0.86. CONCLUSIONS: We present machine learning strategies to identify MRI phenotypes that distinguish PFA from PFB, as well as high- and low-risk PFA. We also describe quantitative image predictors of aggressive EP tumors that might assist risk-profiling after surgery. Future studies could examine translating radiomics as an adjunct to EP risk assessment when considering therapy strategies or trial candidacy