Localized vibrational modes in optically bound structures

We show, through analytical theory and rigorous numerical calculations, that optical binding can organize a collection of particles into stable one-dimensional lattice. This lattice, as well as other optically-bound structures, are shown to exhibit spatially localized vibrational eigenmodes. The origin of localization here is distinct from the usual mechanisms such as disorder, defect, or nonlinearity, but is a consequence of the long-ranged nature of optical binding. For an array of particles trapped by an interference pattern, the stable configuration is often dictated by the external light source, but our calculation revealed that inter-particle optical binding forces can have a profound influence on the dynamics.Comment: 4 pages, Optical Bindin

Safety and efficacy of human Wharton's Jelly-derived mesenchymal stem cells therapy for retinal degeneration

Purpose To investigate the safety and efficacy of subretinal injection of human Wharton’s Jelly-derived mesenchymal stem cells (hWJ-MSCs) on retinal structure and function in Royal College of Surgeons (RCS) rats. Methods RCS rats were divided into 2 groups: hWJ-MSCs treated group (n = 8) and placebo control group (n = 8). In the treatment group, hWJ-MSCs from healthy donors were injected into the subretinal space in one eye of each rat at day 21. Control group received saline injection of the same volume. Additional 3 animals were injected with nanogold-labelled stem cells for in vivo tracking of cells localisation using a micro-computed tomography (microCT). Retinal function was assessed by electroretinography (ERG) 3 days before the injection and repeated at days 15, 30 and 70 after the injection. Eyes were collected at day 70 for histology, cellular and molecular studies. Results No retinal tumor formation was detected by histology during the study period. MicroCT scans showed that hWJ-MSCs stayed localised in the eye with no systemic migration. Transmission electron microscopy showed that nanogold-labelled cells were located within the subretinal space. Histology showed preservation of the outer nuclear layer (ONL) in the treated group but not in the control group. However, there were no significant differences in the ERG responses between the groups. Confocal microscopy showed evidence of hWJ-MSCs expressing markers for photoreceptor, Müller cells and bipolar cells. Conclusions Subretinal injection of hWJ-MSCs delay the loss of the ONL in RCS rats. hWJ-MSCs appears to be safe and has potential to differentiate into retinal-like cells. The potential of this cell-based therapy for the treatment of retinal dystrophies warrants further studies

Randomized, Double-Blind, Placebo-Controlled Phase III Study of Tasquinimod in Men With Metastatic Castration-Resistant Prostate Cancer

PURPOSE: Tasquinimod, a novel oral therapy targeting the tumor microenvironment, significantly improved progression-free survival (PFS) in a randomized, placebo-controlled phase II trial in men with metastatic castration-resistant prostate cancer (mCRPC). This phase III study was conducted to confirm the phase II results and to detect an overall survival (OS) benefit. PATIENTS AND METHODS: Men with chemotherapy-naïve mCRPC and evidence of bone metastases were assigned (2:1) to receive tasquinimod once per day or placebo until progression or toxicity. The primary end point was radiographic PFS (rPFS; time from random assignment to radiologic progression or death) per Prostate Cancer Working Group 2 criteria and RECIST 1.1. The study had 99.9% power to detect an rPFS hazard ratio (HR) of 0.6 with a two-sided alpha error of .05 and 80% power to detect a target HR of 0.8 for OS, the key secondary end point. RESULTS: In all, 1,245 patients were randomly assigned to either tasquinimod (n = 832) or placebo (n = 413) between March 2011 and December 2012 at 241 sites in 37 countries. Baseline characteristics were balanced between groups: median age, 71 years; Karnofsky performance status ≥ 90%, 77.3%; and visceral metastases, 21.1%. Estimated median rPFS by central review was 7.0 months (95% CI, 5.8 to 8.2 months) with tasquinimod and 4.4 months (95% CI, 3.5 to 5.5 months) with placebo (HR, 0.64; 95% CI, 0.54 to 0.75; P < .001). Median OS was 21.3 months (95% CI, 19.5 to 23.0 months) with tasquinimod and 24.0 months (95% CI, 21.4 to 26.9 months) with placebo (HR, 1.10; 95% CI, 0.94 to 1.28; P = .25). Grade ≥ 3 adverse events were more frequent with tasquinimod (42.8% v 33.6%), the most common being anemia, fatigue, and cancer pain. CONCLUSION: In chemotherapy-naïve men with mCRPC, tasquinimod significantly improved rPFS compared with placebo. However, no OS benefit was observed

Iron Supported On Bioinspired Green Silica for Water Remediation

Iron has been used previously in water decontamination, either unsupported or supported on clays, polymers, carbons or ceramics such as silica. However, the reported synthesis procedures are tedious, lengthy (involving various steps), and either utilise or produce toxic chemicals. Herein, the use of a simple, rapid, bio-inspired green synthesis method is reported to prepare, for the first time a family of iron supported green nanosilica materials (Fe@GN) to create new technological solutions for water remediation. In particular, Fe@GN were employed for the removal of arsenate ions as a model for potentially toxic elements in aqueous solution. Several characterization techniques were used to study the physical, structural and chemical properties of the new Fe@GN. When evaluated as an adsorption platform for the removal of arsenate ions, Fe@GN exhibited high adsorption capacity (69 mg of As/g of Fe@GN) with superior kinetics (reaching ~35mg As/g sorbent/hr) – threefold higher than the highest removal rates reported to date. Moreover, a method was developed to regenerate the Fe@GN allowing for full recovery and reuse of the adsorbent in subsequent extractions; strongly highlighting the potential technological benefits of these new green materials

Protein-coding variants implicate novel genes related to lipid homeostasis contributing to body-fat distribution.

Body-fat distribution is a risk factor for adverse cardiovascular health consequences. We analyzed the association of body-fat distribution, assessed by waist-to-hip ratio adjusted for body mass index, with 228,985 predicted coding and splice site variants available on exome arrays in up to 344,369 individuals from five major ancestries (discovery) and 132,177 European-ancestry individuals (validation). We identified 15 common (minor allele frequency, MAF ≥5%) and nine low-frequency or rare (MAF &lt;5%) coding novel variants. Pathway/gene set enrichment analyses identified lipid particle, adiponectin, abnormal white adipose tissue physiology and bone development and morphology as important contributors to fat distribution, while cross-trait associations highlight cardiometabolic traits. In functional follow-up analyses, specifically in Drosophila RNAi-knockdowns, we observed a significant increase in the total body triglyceride levels for two genes (DNAH10 and PLXND1). We implicate novel genes in fat distribution, stressing the importance of interrogating low-frequency and protein-coding variants

Patient Controlled, Privacy Preserving IoT Healthcare Data Sharing Framework

Healthcare data personally collected by individuals with wearable devices have become important sources of information for healthcare professionals and medical research worldwide. User-Generated Data (UGD) offers unique and sometimes fine-grained insight into the lived experiences and medical conditions of patients. The sensitive subject-matter of medical data can facilitate the exploitation and/or control of victims. Data collection in medical research therefore restricts access control over participant-data to the researchers. Therefore, cultivating trust with prospective participants concerned about the security of their medical data presents formidable challenges. Anonymization can allay such concerns, but at the cost of information loss. Moreover, such techniques cannot necessarily be applied on real-time streaming health data. In this paper, we aim to analyze the technical requirements to enable individuals to share their real-time wearable healthcare data with researchers without compromising privacy. An extension for delay-free anonymization techniques for real-time streaming health data is also proposed

Standardised framework for quantitative analysisof fibrillation dynamics

The analysis of complex mechanisms underlying ventricular fibrillation (VF) and atrial fibrillation (AF) requires sophisticatedtools for studying spatio-temporal action potential (AP) propagation dynamics. However, fibrillation analysis tools are oftencustom-made or proprietary, and vary between research groups. With no optimal standardised framework for analysis, resultsfrom different studies have led to disparate findings. Given the technical gap, here we present a comprehensive framework andset of principles for quantifying properties of wavefront dynamics in phase-processed data recorded during myocardial fibrillationwith potentiometric dyes. Phase transformation of the fibrillatory data is particularly useful for identifying self-perpetuating spiralwaves or rotational drivers (RDs) rotating around a phase singularity (PS). RDs have been implicated in sustaining fibrillation,and thus accurate localisation and quantification of RDs is crucial for understanding specific fibrillatory mechanisms. In thiswork, we assess how variation of analysis parameters and thresholds in the tracking of PSs and quantification of RDs couldresult in different interpretations of the underlying fibrillation mechanism. These techniques have been described and appliedto experimental AF and VF data, and AF simulations, and examples are provided from each of these data sets to demonstratethe range of fibrillatory behaviours and adaptability of these tools. The presented methodologies are available as an opensource software and offer an off-the-shelf research toolkit for quantifying and analysing fibrillatory mechanisms

Murine mesothelin: characterization, expression, and inhibition of tumor growth in a murine model of pancreatic cancer

Background Mesothelin has attracted much interest as a tumor specific antigen; it has been reported to promote tumor development and to be a good target for cancer treatment. Most studies to date have used human mesothelin in immunocompromised mice. Since these models do not allow for study of the natural immune response to mesothelin expressing tumors, we have undertaken the characterization of mouse mesothelin so the effects of this protein can be assessed in immunocompetent mouse strains. Methods We analyzed mouse mesothelin expression, tissue distribution, shedding and biochemistry. In addition we constructed stable mesothelin overexpressing lines of the pancreatic cancer line Panc02 by two methods and tested them for growth and tumorigencity in vitro and in vivo. Results We show here that mouse mesothelin is similar to human mesothelin in biochemical characteristics, tumor expression and tissue distribution, suggesting the mouse may be a suitable model for study of mesothelin. Stable overexpression of mesothelin in a pancreatic cancer cell line did not increase cell proliferation or anchorage-independent growth in vitro, suggesting that mesothelin is not necessarily a tumor progression factor. Surprisingly overexpression of mesothelin inhibited tumor formation in vivo in immunocompetent mice. Conclusion The mouse may be a good model for studying mesothelin in the context of an intact immune response. Mesothelin is not necessarily a tumor progression factor, and indeed mesothelin overexpression inhibited tumor growth in immunocompetent mice

Co-evolution of strain design methods based on flux balance and elementary mode analysis

More than a decade ago, the first genome-scale metabolic models for two of the most relevant microbes for biotechnology applications, Escherichia coli and Saccaromyces cerevisiae, were published. Shortly after followed the publication of OptKnock, the first strain design method using bilevel optimization to couple cellular growth with the production of a target product. This initiated the development of a family of strain design methods based on the concept of flux balance analysis. Another family of strain design methods, based on the concept of elementary mode analysis, has also been growing. Although the computation of elementary modes is hindered by computational complexity, recent breakthroughs have allowed applying elementary mode analysis at the genome scale. Here we review and compare strain design methods and look back at the last ten years of in silico strain design with constraint-based models. We highlight some features of the different approaches and discuss the utilization of these methods in successful in vivo metabolic engineering applications.Novo Nordisk UK Research Foundation(NORTE-07-0124-FEDER-000028