Neoadjuvant chemotherapy improves survival in patients with oesophageal mucinous adenocarcinoma: Post-hoc analysis of the UK MRC OE02 and OE05 trials

Background: Adenocarcinoma with more than 50% extracellular mucin is a relatively rare histological subtype of gastrointestinal adenocarcinomas. The clinical impact of extracellular mucin in oesophageal adenocarcinoma (OeAC) has not been investigated in detail. We hypothesised that patients with mucinous OeAC (OeACmucin) do not benefit from neoadjuvant chemotherapy. Methods: OeAC patients either treated by surgery alone in the OE02 trial (S-patients) or by neoadjuvant chemotherapy followed by surgery (CS-patients) in OE02 or OE05 trials were included. Cancers from 1055 resection specimens (OE02 [test cohort]: 187 CS, 185 S; OE05 [validation cohort]: 683 CS) were classified as either mucinous (more than 50% of the tumour area consists of extracellular mucin, OeACmucin) or non-mucinous adenocarcinoma (OeACnon-mucin). The relationship between histological phenotype, clinicopathological characteristics, survival and treatment was analysed. Results: Overall, 7.3% and 9.6% OeAC were classified as OeACmucin in OE02 and OE05, respectively. In OE02, the frequency of OeACmucin was similar in S and CS-patients. Patients with OeACmucin treated with surgery alone had a poorer overall survival compared with OeACnon-mucin patients (hazard ratio: 2.222, 95% confidence interval: 1.08–4.56, P = 0.025). Patients with OeACmucin treated with neoadjuvant chemotherapy and surgery had similar survival as OeACnon-mucin patients in test and validation cohort. Conclusions: This is the first study to suggest in a post-hoc analysis of material from two independent phase III clinical trials that the poor survival of patients with mucinous OeAC can be improved by neoadjuvant chemotherapy. Future studies are warranted to identify potential underlying biological, biochemical or pharmacokinetic interactions between extracellular mucin and chemotherapy

Safety and efficacy of fluticasone propionate in the topical treatment of skin diseases

Fluticasone propionate - the first carbothioate corticosteroid - has been classified as a potent anti-inflammatory drug for dermatological use. It is available as 0.05% cream and 0.005% ointment formulations for the acute and maintenance treatment of patients with dermatological disorders such as atopic dermatitis, psoriasis and vitiligo. This glucocorticoid is characterized by high lipophilicity, high glucocorticoid receptor binding and activation, and a rapid metabolic turnover in skin. Although skin blanching following fluticasone propionate exceeds that of corticosteroids of medium strength, several clinical trials demonstrate a low potential for cutaneous and systemic side-effects, even in difficult-to-treat areas like the face, the eyelids and intertriginous areas. Even among paediatric patients with atopic dermatitis, fluticasone propionate proved to be safe and effective. These pharmacological and clinical properties are reflected by the high therapeutic index of this glucocorticoid

Synthesis of Heterogeneous Li4Ti5O12 Nanostructured Anodes with Long-Term Cycle Stability

The 0D-1D Lithium titanate (Li4Ti5O12) heterogeneous nanostructures were synthesized through the solvothermal reaction using lithium hydroxide monohydrate (Li(OH)·H2O) and protonated trititanate (H2Ti3O7) nanowires as the templates in an ethanol/water mixed solvent with subsequent heat treatment. A scanning electron microscope (SEM) and a high resolution transmission electron microscope (HRTEM) were used to reveal that the Li4Ti5O12 powders had 0D-1D heterogeneous nanostructures with nanoparticles (0D) on the surface of wires (1D). The composition of the mixed solvents and the volume ratio of ethanol modulated the primary particle size of the Li4Ti5O12 nanoparticles. The Li4Ti5O12 heterogeneous nanostructures exhibited good capacity retention of 125 mAh/g after 500 cycles at 1C and a superior high-rate performance of 114 mAh/g at 20C

Self-adaptive robot training of stroke survivors for continuous tracking movements

<p>Abstract</p> <p>Background</p> <p>Although robot therapy is progressively becoming an accepted method of treatment for stroke survivors, few studies have investigated how to adapt the robot/subject interaction forces in an automatic way. The paper is a feasibility study of a novel self-adaptive robot controller to be applied with continuous tracking movements.</p> <p>Methods</p> <p>The haptic robot Braccio di Ferro is used, in relation with a tracking task. The proposed control architecture is based on three main modules: 1) a force field generator that combines a non linear attractive field and a viscous field; 2) a performance evaluation module; 3) an adaptive controller. The first module operates in a continuous time fashion; the other two modules operate in an intermittent way and are triggered at the end of the current block of trials. The controller progressively decreases the gain of the force field, within a session, but operates in a non monotonic way between sessions: it remembers the minimum gain achieved in a session and propagates it to the next one, which starts with a block whose gain is greater than the previous one. The initial assistance gains are chosen according to a minimal assistance strategy. The scheme can also be applied with closed eyes in order to enhance the role of proprioception in learning and control.</p> <p>Results</p> <p>The preliminary results with a small group of patients (10 chronic hemiplegic subjects) show that the scheme is robust and promotes a statistically significant improvement in performance indicators as well as a recalibration of the visual and proprioceptive channels. The results confirm that the minimally assistive, self-adaptive strategy is well tolerated by severely impaired subjects and is beneficial also for less severe patients.</p> <p>Conclusions</p> <p>The experiments provide detailed information about the stability and robustness of the adaptive controller of robot assistance that could be quite relevant for the design of future large scale controlled clinical trials. Moreover, the study suggests that including continuous movement in the repertoire of training is acceptable also by rather severely impaired subjects and confirms the stabilizing effect of alternating vision/no vision trials already found in previous studies.</p

Deep Learning for Cardiologist-level Myocardial Infarction Detection in Electrocardiograms

Myocardial infarction is the leading cause of death worldwide. In this paper, we design domain-inspired neural network models to detect myocardial infarction. First, we study the contribution of various leads. This systematic analysis, first of its kind in the literature, indicates that out of 15 ECG leads, data from the v6, vz, and ii leads are critical to correctly identify myocardial infarction. Second, we use this finding and adapt the ConvNetQuake neural network model--originally designed to identify earthquakes--to attain state-of-the-art classification results for myocardial infarction, achieving $99.43\%$ classification accuracy on a record-wise split, and $97.83\%$ classification accuracy on a patient-wise split. These two results represent cardiologist-level performance level for myocardial infarction detection after feeding only 10 seconds of raw ECG data into our model. Third, we show that our multi-ECG-channel neural network achieves cardiologist-level performance without the need of any kind of manual feature extraction or data pre-processing.Comment: Accepted to the European Medical and Biological Engineering Conference (EMBEC) 202

FastTagger: an efficient algorithm for genome-wide tag SNP selection using multi-marker linkage disequilibrium

<p>Abstract</p> <p>Background</p> <p>Human genome contains millions of common single nucleotide polymorphisms (SNPs) and these SNPs play an important role in understanding the association between genetic variations and human diseases. Many SNPs show correlated genotypes, or linkage disequilibrium (LD), thus it is not necessary to genotype all SNPs for association study. Many algorithms have been developed to find a small subset of SNPs called tag SNPs that are sufficient to infer all the other SNPs. Algorithms based on the <it>r</it>²LD statistic have gained popularity because <it>r</it>²is directly related to statistical power to detect disease associations. Most of existing <it>r</it>²based algorithms use pairwise LD. Recent studies show that multi-marker LD can help further reduce the number of tag SNPs. However, existing tag SNP selection algorithms based on multi-marker LD are both time-consuming and memory-consuming. They cannot work on chromosomes containing more than 100 k SNPs using length-3 tagging rules.</p> <p>Results</p> <p>We propose an efficient algorithm called FastTagger to calculate multi-marker tagging rules and select tag SNPs based on multi-marker LD. FastTagger uses several techniques to reduce running time and memory consumption. Our experiment results show that FastTagger is several times faster than existing multi-marker based tag SNP selection algorithms, and it consumes much less memory at the same time. As a result, FastTagger can work on chromosomes containing more than 100 k SNPs using length-3 tagging rules.</p> <p>FastTagger also produces smaller sets of tag SNPs than existing multi-marker based algorithms, and the reduction ratio ranges from 3%-9% when length-3 tagging rules are used. The generated tagging rules can also be used for genotype imputation. We studied the prediction accuracy of individual rules, and the average accuracy is above 96% when <it>r</it>²≥ 0.9.</p> <p>Conclusions</p> <p>Generating multi-marker tagging rules is a computation intensive task, and it is the bottleneck of existing multi-marker based tag SNP selection methods. FastTagger is a practical and scalable algorithm to solve this problem.</p

The actin-myosin regulatory MRCK kinases: regulation, biological functions and associations with human cancer

The contractile actin-myosin cytoskeleton provides much of the force required for numerous cellular activities such as motility, adhesion, cytokinesis and changes in morphology. Key elements that respond to various signal pathways are the myosin II regulatory light chains (MLC), which participate in actin-myosin contraction by modulating the ATPase activity and consequent contractile force generation mediated by myosin heavy chain heads. Considerable effort has focussed on the role of MLC kinases, and yet the contributions of the myotonic dystrophy-related Cdc42-binding kinases (MRCK) proteins in MLC phosphorylation and cytoskeleton regulation have not been well characterized. In contrast to the closely related ROCK1 and ROCK2 kinases that are regulated by the RhoA and RhoC GTPases, there is relatively little information about the CDC42-regulated MRCKα, MRCKβ and MRCKγ members of the AGC (PKA, PKG and PKC) kinase family. As well as differences in upstream activation pathways, MRCK and ROCK kinases apparently differ in the way that they spatially regulate MLC phosphorylation, which ultimately affects their influence on the organization and dynamics of the actin-myosin cytoskeleton. In this review, we will summarize the MRCK protein structures, expression patterns, small molecule inhibitors, biological functions and associations with human diseases such as cancer

Precore Mutation of Hepatitis B Virus May Contribute to Hepatocellular Carcinoma Risk: Evidence from an Updated Meta-Analysis

BACKGROUND: Studies focused on the correlation of mutations in the genome of Hepatitis B Virus (HBV) like Pre-S mutation, Basal Core promoter (BCP), Enhancer II (EnhII), especially Precore mutation, with the risk of hepatocellular carcinoma (HCC) have triggered stiff controversies. With an increasing number of studies in this field recently, we conducted this meta-analysis to appraise the correlations. METHODS: We searched the commonly used databases both in English and Chinese till February 1(st), 2012. Meta-analysis was performed in fixed/random-effects models using STATA 10.0. Publication bias was examined through Egger's test and Begg's funnel plot. RESULTS: In total, 85 case-control studies were included involving 16745 HBV-infected patients, of whom 5781 had HCC. Statistically significant correlations were observed in Precore mutation G1896A (OR = 1.46, 95% confidence interval [CI] = 1.15-1.85, P(OR) = 0.002), G1899A (OR = 3.13, 95%CI = 2.38-4.13, P(OR)<0.001) and Pre-S mutation especially Pre-S1 deletion (OR = 2.94, 95%CI = 2.22 to 3.89) and Pre-S2 deletion (OR = 3.02, 95%CI = 2.03 to 4.50). Similar correlation existed between BCP double mutation A1762T/G1764A, T1753V, C1653T and HCC. In subgroup analysis, the Asians, genotype C or HBeAg positive patients with certain above mutations may be more susceptible to HCC. Besides, the mutations like G1896A and BCP double mutation may be associated with the progression of the liver diseases. CONCLUSIONS: Precore mutation G1896A, G1899A, deletions in Pre-S region as well as the other commonly seen mutations correlated with the increased risk of HCC, especially in Asians and may predict the progression of the liver disease

Global distribution of two fungal pathogens threatening endangered sea turtles

This work was supported by grants of Ministerio de Ciencia e Innovación, Spain (CGL2009-10032, CGL2012-32934). J.M.S.R was supported by PhD fellowship of the CSIC (JAEPre 0901804). The Natural Environment Research Council and the Biotechnology and Biological Sciences Research Council supported P.V.W. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Thanks Machalilla National Park in Ecuador, Pacuare Nature Reserve in Costa Rica, Foundations Natura 2000 in Cape Verde and Equilibrio Azul in Ecuador, Dr. Jesus Muñoz, Dr. Ian Bell, Dr. Juan Patiño for help and technical support during samplingPeer reviewedPublisher PD

Update on the Risk of Hepatocellular Carcinoma in Chronic Hepatitis B Virus Infection

Chronic hepatitis B virus infection is an important cause of liver-related morbidity and mortality, with hepatocellular carcinoma being the most life-threatening complication. Because of the highly variable clinical course of the disease, enormous research efforts have been made with the aim of revealing the factors in the natural history that are relevant to hepatocarcinogenesis. These include epidemiological studies of predisposing risk groups, viral studies of mutations within the hepatitis B viral genome, and clinical correlation of these risk factors in predicting the likelihood of development of hepatocellular cancer in susceptible hosts. This update addresses these risks, with emphasis on the latest research relevant to hepatocarcinogenesis