Protocol for a systematic review and thematic synthesis of patient experiences of central venous access devices in anti-cancer treatment

Background: Three types of central venous access devices (CVADs)—peripherally inserted central catheters (PICCs), skin-tunnelled central catheters (Hickman-type devices), and implantable chest wall Ports (Ports)—are routinely used in the intravenous administration of anti-cancer treatment. These devices avoid the need for peripheral cannulation and allow for home delivery of treatment. Assessments of these devices have tended to focus on medical and economic factors, but there is increased interest in the importance of patient experiences and perspectives in this area. The aim of this systematic review is to synthesise existing research regarding patient experiences of these CVADs to help clinicians guide, prepare, and support patients receiving CVADs for the administration of anti-cancer treatment. Method: A systematic search of MEDLINE, Embase, and CINAHL research databases will be carried out along with a supplementary reference list search. This review will include quantitative, qualitative, and mixed methods studies published in peer-review journals, reporting some aspect(s) of patient experiences or perspectives regarding the use of PICC, Hickman, or Port CVADs for the administration of anti-cancer drugs. The methodological quality and risk of bias of included papers will be assessed using the Mixed Methods Appraisal Tool (MMAT). Relevant outcome data will be extracted from included studies and analysed using a thematic synthesis approach. Discussion: The results section of the review will comprise thematic synthesis of quantitative studies, thematic synthesis of qualitative studies, and the aggregation of the two. Results will aim to offer an account of current understandings of patient experiences and perspective regarding PICC, Hickman-type, and Port devices in the context of anti-cancer treatment. Confidence in cumulative evidence will be assessed using the Confidence in the Evidence from Reviews of Qualitative research (CERQual) approach

A Common Variant Associated with Dyslexia Reduces Expression of the KIAA0319 Gene

Numerous genetic association studies have implicated the KIAA0319 gene on human chromosome 6p22 in dyslexia susceptibility. The causative variant(s) remains unknown but may modulate gene expression, given that (1) a dyslexia-associated haplotype has been implicated in the reduced expression of KIAA0319, and (2) the strongest association has been found for the region spanning exon 1 of KIAA0319. Here, we test the hypothesis that variant(s) responsible for reduced KIAA0319 expression resides on the risk haplotype close to the gene's transcription start site. We identified seven single-nucleotide polymorphisms on the risk haplotype immediately upstream of KIAA0319 and determined that three of these are strongly associated with multiple reading-related traits. Using luciferase-expressing constructs containing the KIAA0319 upstream region, we characterized the minimal promoter and additional putative transcriptional regulator regions. This revealed that the minor allele of rs9461045, which shows the strongest association with dyslexia in our sample (max p-value = 0.0001), confers reduced luciferase expression in both neuronal and non-neuronal cell lines. Additionally, we found that the presence of this rs9461045 dyslexia-associated allele creates a nuclear protein-binding site, likely for the transcriptional silencer OCT-1. Knocking down OCT-1 expression in the neuronal cell line SHSY5Y using an siRNA restores KIAA0319 expression from the risk haplotype to nearly that seen from the non-risk haplotype. Our study thus pinpoints a common variant as altering the function of a dyslexia candidate gene and provides an illustrative example of the strategic approach needed to dissect the molecular basis of complex genetic traits

Strategies to inhibit tumour associated integrin receptors: rationale for dual and multi-antagonists

YesThe integrins are a family of 24 heterodimeric transmembrane cell surface receptors. Involvement in cell attachment to the extracellular matrix, motility, and proliferation identifies integrins as therapeutic targets in cancer and associated conditions; thrombosis, angiogenesis and osteoporosis. The most reported strategy for drug development is synthesis of an agent that is highly selective for a single integrin receptor. However, the ability of cancer cells to change their integrin repertoire in response to drug treatment renders this approach vulnerable to the development of resistance and paradoxical promotion of tumor growth. Here, we review progress towards development of antagonists targeting two or more members of the RGD-binding integrins, notably αvβ3, αvβ5, αvβ6, αvβ8, α5β1, and αIIbβ3, as anticancer therapeutics

Kualitas Hidup Pasien Diabetes Melitus Tipe 2 di Puskesmas Se Kota Kupang

Diabetes Mellitus is well known as a chronic disease which can lead to a decrease in quality of life in all domains. The study aims to explore the diabetic type 2 patient\u27s quality of life and find out the factors affecting in type 2 diabetic mellitus patients. The cross-sectional study design is used that included 65 patient with type 2 diabetes mellitus, in 11 public health centers of Kupang City. Data were collected by using Short Form Survey (SF-36) that assessed 8-scale health profile. Independent sample t-test is used to analyze the correlation between the factors affecting and the quality of life. the study showed that the QoL of DM patients decreased in all 8- health profile including physical functioning, social functioning, mental health, general health, pain, change in the role due to physical problems and emotional problems. The Study also showed there was a relationship between gender, duration of suffering from Diabetes mellitus, and complications to the quality of life. Male perceived a better quality of life than female

Guard cell and whole plant expression of AtTOR improves performance under drought and enhances water use efficiency.

Water use efficiency is an important target for breeding of improved drought resistance. Minimizing leaf transpirational water loss plays a key role in drought resistance. But this reduces CO2 levels in leaves, which often reduces photosynthetic efficiency and yield. Signaling pathways play important roles in stress responses, and identifying the molecular, biochemical, and physiological determinants underlying drought signaling may offer new drought mitigating strategies. To explore these possibilities, and because of the importance of stomata in drought response and photosynthesis, we employed guard cell (GC)-targeted and constitutive overexpression of the Target of Rapamycin (TOR) kinase, a master regulator of signaling networks, in transgenic Arabidopsis. To investigate the impact of these AtTOR transgenes in drought, we conducted physiological and molecular investigations into drought responses, including leaf water loss, photosynthetic CO2 assimilation, stomatal H2O/CO2 conductance, leaf chlorophyll content, and global gene expression in response to drought in wild-type and AtTOR-expressing Arabidopsis. Links between both guard cell-localized and whole plant AtTOR overexpression were identified, revealing TOR is involved in conservation of water and sustained photosynthetic performance, along with identification of genes associated with drought response in WT versus AtTOR-expressing transgenic lines. These findings suggest that targeted guard cell AtTOR expression should help achieve a balance between plant water conservation during drought, and maintaining plant performance, by minimizing reductions in photosynthesis. Manipulation of guard cell AtTOR expression could be an effective avenue for developing crops with enhanced drought resistance and increased yield under drought stress, resulting in enhanced water use efficiency

A minimally invasive technique for closing an iatrogenic subclavian artery cannulation using the Angio-Seal closure device: two case reports

<p>Abstract</p> <p>Introduction</p> <p>In the two cases described here, the subclavian artery was inadvertently cannulated during unsuccessful access to the internal jugular vein. The puncture was successfully closed using a closure device based on a collagen plug (Angio-Seal, St Jude Medical, St Paul, MN, USA). This technique is relatively simple and inexpensive. It can provide clinicians, such as intensive care physicians and anesthesiologists, with a safe and straightforward alternative to major surgery and can be a life-saving procedure.</p> <p>Case presentation</p> <p>In the first case, an anesthetist attempted ultrasound-guided access to the right internal jugular vein during the preoperative preparation of a 66-year-old Caucasian man. A 7-French (Fr) triple-lumen catheter was inadvertently placed into his arterial system. In the second case, an emergency physician inadvertently placed a 7-Fr catheter into the subclavian artery of a 77-year-old Caucasian woman whilst attempting access to her right internal jugular vein. Both arterial punctures were successfully closed by means of a percutaneous closure device (Angio-Seal). No complications were observed.</p> <p>Conclusions</p> <p>Inadvertent subclavian arterial puncture can be successfully managed with no adverse clinical sequelae by using a percutaneous vascular closure device. This minimally invasive technique may be an option for patients with non-compressible arterial punctures. This report demonstrates two practical points that may help clinicians in decision-making during daily practice. First, it provides a practical solution to a well-known vascular complication. Second, it emphasizes a role for proper vascular ultrasound training for the non-radiologist.</p

Dose and energy dependence of mechanical properties of focused electron beam induced pillar deposits from Cu(C5HF6O2)2

Bending and vibration tests performed inside the scanning electron microscope were used to mechanically characterize high-aspect pillars grown by focused electron-beam (FEB) induced deposition from the precursor Cu(C5HF6O2)2. Supported by finite element (FE) analysis the Young's modulus was determined from load-deflection measurements using cantilever-based force sensing and the material density from additional resonance vibration analysis. The pillar material consisted of a carbonaceous (C, O, F, H containing) matrix which embeds 5...10 at. % Cu deposited at 5 keV and 20 keV primary electron energy and 100 pA beam current, depending on primary electron energy. Young's moduli of the FEB deposits increased from 17+/-6 GPa to 25+/-8 GPa with increasing electron dose. The density of the carbonaceous matrix shows a dependence on the primary electron energy: 1.2+/-0.3 g cm-3 (5 keV) and 2.2+/-0.5 g cm-3 (20 keV). At a given primary energy a correlation with the irradiation dose is found. Quality factors determined from the phase relation at resonance of the fundamental pillar vibration mode were in the range of 150 to 600 and correlated to the deposited irradiation energy.Comment: 17 pages, 9 figures, 2 table

Hepatitis B virus infection as a neglected tropical disease

PCM is funded by a Wellcome Trust Intermediate Fellowship Grant (ref 110110/Z/15/Z).Peer reviewe

The STRANDS project: long-term autonomy in everyday environments

Thanks to the efforts of the robotics and autonomous systems community, the myriad applications and capacities of robots are ever increasing. There is increasing demand from end users for autonomous service robots that can operate in real environments for extended periods. In the Spatiotemporal Representations and Activities for Cognitive Control in Long-Term Scenarios (STRANDS) project (http://strandsproject.eu), we are tackling this demand head-on by integrating state-of-the-art artificial intelligence and robotics research into mobile service robots and deploying these systems for long-term installations in security and care environments. Our robots have been operational for a combined duration of 104 days over four deployments, autonomously performing end-user-defined tasks and traversing 116 km in the process. In this article, we describe the approach we used to enable long-term autonomous operation in everyday environments and how our robots are able to use their long run times to improve their own performance

A comparison of machine learning algorithms for chemical toxicity classification using a simulated multi-scale data model

<p>Abstract</p> <p>Background</p> <p>Bioactivity profiling using high-throughput <it>in vitro </it>assays can reduce the cost and time required for toxicological screening of environmental chemicals and can also reduce the need for animal testing. Several public efforts are aimed at discovering patterns or classifiers in high-dimensional bioactivity space that predict tissue, organ or whole animal toxicological endpoints. Supervised machine learning is a powerful approach to discover combinatorial relationships in complex <it>in vitro/in vivo </it>datasets. We present a novel model to simulate complex chemical-toxicology data sets and use this model to evaluate the relative performance of different machine learning (ML) methods.</p> <p>Results</p> <p>The classification performance of Artificial Neural Networks (ANN), K-Nearest Neighbors (KNN), Linear Discriminant Analysis (LDA), Naïve Bayes (NB), Recursive Partitioning and Regression Trees (RPART), and Support Vector Machines (SVM) in the presence and absence of filter-based feature selection was analyzed using K-way cross-validation testing and independent validation on simulated <it>in vitro </it>assay data sets with varying levels of model complexity, number of irrelevant features and measurement noise. While the prediction accuracy of all ML methods decreased as non-causal (irrelevant) features were added, some ML methods performed better than others. In the limit of using a large number of features, ANN and SVM were always in the top performing set of methods while RPART and KNN (k = 5) were always in the poorest performing set. The addition of measurement noise and irrelevant features decreased the classification accuracy of all ML methods, with LDA suffering the greatest performance degradation. LDA performance is especially sensitive to the use of feature selection. Filter-based feature selection generally improved performance, most strikingly for LDA.</p> <p>Conclusion</p> <p>We have developed a novel simulation model to evaluate machine learning methods for the analysis of data sets in which in vitro bioassay data is being used to predict in vivo chemical toxicology. From our analysis, we can recommend that several ML methods, most notably SVM and ANN, are good candidates for use in real world applications in this area.</p