Patterning of ferroelectric nanodot arrays using a silicon nitride shadow mask

We grew well-ordered arrays of ferroelectric Pb (Zr0.2 Ti0.8) O3 (PZT) nanodots on a SrRu O3 SrTi O3 substrate by pulsed laser deposition. A silicon nitride shadow mask with ordered holes was used for patterning of the PZT arrays. Each dot has a height of ???15 nm and a diameter of ???120 nm with a similar dome shape over a large area. The ferroelectric properties of individual PZT dots were investigated by piezoresponse force microscopy. A single dot could be polarized individually and the polarized state remained unrelaxed to ???20 min.open232

Practical application of cure mixture model for long-term censored survivor data from a withdrawal clinical trial of patients with major depressive disorder

<p>Abstract</p> <p>Background</p> <p>Survival analysis methods such as the Kaplan-Meier method, log-rank test, and Cox proportional hazards regression (Cox regression) are commonly used to analyze data from randomized withdrawal studies in patients with major depressive disorder. However, unfortunately, such common methods may be inappropriate when a long-term censored relapse-free time appears in data as the methods assume that if complete follow-up were possible for all individuals, each would eventually experience the event of interest.</p> <p>Methods</p> <p>In this paper, to analyse data including such a long-term censored relapse-free time, we discuss a semi-parametric cure regression (Cox cure regression), which combines a logistic formulation for the probability of occurrence of an event with a Cox proportional hazards specification for the time of occurrence of the event. In specifying the treatment's effect on disease-free survival, we consider the fraction of long-term survivors and the risks associated with a relapse of the disease. In addition, we develop a tree-based method for the time to event data to identify groups of patients with differing prognoses (cure survival CART). Although analysis methods typically adapt the log-rank statistic for recursive partitioning procedures, the method applied here used a likelihood ratio (LR) test statistic from a fitting of cure survival regression assuming exponential and Weibull distributions for the latency time of relapse.</p> <p>Results</p> <p>The method is illustrated using data from a sertraline randomized withdrawal study in patients with major depressive disorder.</p> <p>Conclusions</p> <p>We concluded that Cox cure regression reveals facts on who may be cured, and how the treatment and other factors effect on the cured incidence and on the relapse time of uncured patients, and that cure survival CART output provides easily understandable and interpretable information, useful both in identifying groups of patients with differing prognoses and in utilizing Cox cure regression models leading to meaningful interpretations.</p

Characterization of the Fungal Microbiota (Mycobiome) in Healthy and Dandruff-Afflicted Human Scalps

The human scalp harbors a vast community of microbial mutualists, the composition of which is difficult to elucidate as many of the microorganisms are not culturable using current culture techniques. Dandruff, a common scalp disorder, is known as a causative factor of a mild seborrheic dermatitis as well as pityriasis versicolor, seborrheic dermatitis, and atopic dermatitis. Lipophilic yeast Malassezia is widely accepted to play a role in dandruff, but relatively few comprehensive studies have been reported. In order to investigate fungal biota and genetic resources of dandruff, we amplified the 26S rRNA gene from samples of healthy scalps and dandruff-afflicted scalps. The sequences were analyzed by a high throughput method using a GS-FLX 454 pyrosequencer. Of the 74,811 total sequence reads, Basidiomycota (Filobasidium spp.) was the most common phylum associated with dandruff. In contrast, Ascomycota (Acremonium spp.) was common in the healthy scalps. Our results elucidate the distribution of fungal communities associated with dandruff and provide new avenues for the potential prevention and treatment of dandruff

A New Method for Isolation of Interstitial Fluid from Human Solid Tumors Applied to Proteomic Analysis of Ovarian Carcinoma Tissue

Major efforts have been invested in the identification of cancer biomarkers in plasma, but the extraordinary dynamic range in protein composition, and the dilution of disease specific proteins make discovery in plasma challenging. Focus is shifting towards using proximal fluids for biomarker discovery, but methods to verify the isolated sample's origin are missing. We therefore aimed to develop a technique to search for potential candidate proteins in the proximal proteome, i.e. in the tumor interstitial fluid, since the biomarkers are likely to be excreted or derive from the tumor microenvironment. Since tumor interstitial fluid is not readily accessible, we applied a centrifugation method developed in experimental animals and asked whether interstitial fluid from human tissue could be isolated, using ovarian carcinoma as a model. Exposure of extirpated tissue to 106 g enabled tumor fluid isolation. The fluid was verified as interstitial by an isolated fluid:plasma ratio not significantly different from 1.0 for both creatinine and Na+, two substances predominantly present in interstitial fluid. The isolated fluid had a colloid osmotic pressure 79% of that in plasma, suggesting that there was some sieving of proteins at the capillary wall. Using a proteomic approach we detected 769 proteins in the isolated interstitial fluid, sixfold higher than in patient plasma. We conclude that the isolated fluid represents undiluted interstitial fluid and thus a subproteome with high concentration of locally secreted proteins that may be detected in plasma for diagnostic, therapeutic and prognostic monitoring by targeted methods

The UK Biobank imaging enhancement of 100,000 participants: rationale, data collection, management and future directions

UK Biobank is a population-based cohort of half a million participants aged 40–69 years recruited between 2006 and 2010. In 2014, UK Biobank started the world’s largest multi-modal imaging study, with the aim of re-inviting 100,000 participants to undergo brain, cardiac and abdominal magnetic resonance imaging, dual-energy X-ray absorptiometry and carotid ultrasound. The combination of large-scale multi-modal imaging with extensive phenotypic and genetic data offers an unprecedented resource for scientists to conduct health-related research. This article provides an in-depth overview of the imaging enhancement, including the data collected, how it is managed and processed, and future direction

Action observation training for rehabilitation in brain injuries: A systematic review and meta-analysis

Background : To systematically review and analyse the effects of Action Observation Training on adults and children with brain damage. Methods : Seven electronic databases (Cochrane, EBSCO, Embase, Eric, PubMed, Scopus and Web of Science) were searched up to 16 September 2018 to select Randomized Controlled Trials focused on adults and children with brain damage that included AOT training on upper and/or lower limb carried out for at least 1 week. Identification of studies and data extraction was conducted with two reviewers working independently. Oxford Centre for Evidence-based Medicine (March2009) – Levels of Evidence and Physiotherapy Evidence Database scale were used to grade studies. The data collected from the articles were analysed using software R, version 3.4.3. Hedge’s g values were calculated and effect size estimates were pooled across studies. Separate meta-analyses were carried out for each ICF domain (i.e. body function and activity) for upper and lower limb. Results : Out of the 210 records identified after removing duplicates, 22 were selected for systematic review and 19 were included in the meta-analysis. Thirteen studies included in the meta-analysis focused on upper limb rehabilitation (4 in children and 9 in adults) and 6 on lower limb rehabilitation (only studies in adults). A total of 626 patients were included in the meta-analysis. An overall statistically significant effect size was found for upper limb body function (0.44, 95% CI: [0.24, 0.64], p<0.001) and upper limb activity domain (0.47, 95% CI: [0.30, 0.64], p<0.001). For lower limb, only the activity domain was analysed, revealing a statistically significant overall effect size (0.56, 95% CI: [0.28, 0.84], p<0.001). Conclusions : Action Observation Training (AOT) is an innovative rehabilitation tool for individuals with brain damage, which shows promising results in improving the activity domain for upper and lower limbs, and also the body function domain for the upper limb. However, the examined studies lack uniformity and further well-designed, larger controlled trials are necessary to determine the most suitable type of AOT particularly in childre

Valorisation of Biowastes for the Production of Green Materials Using Chemical Methods

With crude oil reserves dwindling, the hunt for a sustainable alternative feedstock for fuels and materials for our society continues to expand. The biorefinery concept has enjoyed both a surge in popularity and also vocal opposition to the idea of diverting food-grade land and crops for this purpose. The idea of using the inevitable wastes arising from biomass processing, particularly farming and food production, is, therefore, gaining more attention as the feedstock for the biorefinery. For the three main components of biomass—carbohydrates, lipids, and proteins—there are long-established processes for using some of these by-products. However, the recent advances in chemical technologies are expanding both the feedstocks available for processing and the products that be obtained. Herein, this review presents some of the more recent developments in processing these molecules for green materials, as well as case studies that bring these technologies and materials together into final products for applied usage