Quantifying the effect of defective viral genomes in respiratory syncytial virus infections

Defective viral genomes (DVGs) are viral genomes that contain only a partial viral RNA and so cannot replicate within cells on their own. If a cell containing DVGs is subsequently infected with a complete viral genome, the DVG can then use the missing proteins expressed by the full genome in order to replicate itself. Since the cell is producing defective genomes, it has less resources to produce fully functional virions and thus release of complete virions is often suppressed. Here, we use data from challenge studies of respiratory syncytial virus (RSV) in healthy adults to quantify the effect of DVGs. We use a mathematical model to fit the data, finding that late onset of DVGs and prolonged DVG detection are associated with lower infection rates and higher clearance rates. This result could have implications for the use of DVGs as a therapeutic

Parameter Optimisation of Carbon Nanotubes Synthesis via Hexane Decomposition over Minerals Generated from Anadara granosa

The synthesis of carbon nanotubes (CNTs) by the chemical vapour deposition (CVD) method using natural calcite from Anadara granosa shells as the metal catalyst support was studied. Hexane and iron (Fe) were used as the carbon precursor and the active component of the catalyst, respectively. Response surface methodology (RSM) based on central composite design (CCD) was used to optimise the effect of total iron loading, the duration of reaction, and reaction temperature. The optimal conditions were total iron loading of 7.5%, a reaction time of 45 min, and a temperature of 850°C with a resulting carbon yield of 131.62%. Raman spectra, field-emission-scanning electron microscopy (FESEM) and transmission electron microscopy (TEM) analyses showed that the CNTs were of the multiwalled type (MWNTs)

Exp-function Method for Wick-type Stochastic Combined KdV-mKdV Equations

Exp-function method is proposed to present soliton and periodic wave solutions for variable coefficients combined KdV- mKdV equation. By means of Hermite transform and white noise analysis, we consider the variable coefficients and Wick-type stochastic combined KdV-mKdV equations. As a result, we can construct new and more general formal solutions. These solutions include exact stochastic soliton and periodic wave solutions.Keywords: combined KdV-mKdV equation, Exp-function method, Wick product, Hermite transform, White noise

A convex selective segmentation model based on a piece-wise constant metric guided edge detector function

The challenge of segmentation for noisy images, especially those that have light in their backgrounds, is still exists in many advanced state-of-the-art segmentation models. Furthermore, it is significantly difficult to segment such images. In this article, we provide a novel variational model for the simultaneous restoration and segmentation of noisy images that have intensity inhomogeneity and high contrast background illumination and light. The suggested concept combines the multi-phase segmentation technology with the statistical approach in terms of local region knowledge and details of circular regions that are, in fact, centered at every pixel to enable in-homogeneous image restoration. The suggested model is expressed as a fuzzy set and is resolved using the multiplier alternating direction minimization approach. Through several tests and numerical simulations with plausible assumptions, we have evaluated the accuracy and resilience of the proposed approach over various kinds of real and synthesized images in the existence of intensity inhomogeneity and light in the background. Additionally, the findings are contrasted with those from cutting-edge two-phase and multi-phase methods, proving the superiority of our proposed approach for images with noise, background light, and inhomogeneity

Generalized Solutions of Wick-type Stochastic KdV-Burgers Equations Using Exp-function Method

Variable coefficients and Wick-type stochastic KdV-Burgers equations are researched. Expfunction method is proposed to present soliton and periodic wave solutions for variable coefficients KdVBurgers equation. Generalized white noise functional solutions for Wick-type stochastic KdV-Burgersequations are showed via Hermite transform and white noise analysis.Keywords: KdV-Burgers equation; Exp-function method; Wick product; Hermite transform; White noise

Relations structure-odeur soufrée pour une série de composés organiques

Les relations structure-odeur soufrée sont établies en choisisant les fragments de molécules comme descripteurs selon les principes de la méthode GESDEM (Genération et Sélection de Descripteurs et Elaboration de Motifs). La série étudiée comporte 48 molécules soufrées et 34 non-soufrées. 96 % des molécules ont été classées en tant que telles par un modèle obtenu en utilisant un réseau neuronal (RN) de configuration 8-5-1

Modeling Dynamic Spatio-Temporal Correlations for Urban Traffic Flows Prediction

Prediction of traffic crowd movement is one of the most important component in many applications' domains ranging from urban management to transportation schedule. The key challenge of citywide crowd flows prediction is how to model spatial and dynamic temporal correlation. However, in recent years several studies have been done, but they lack the ability to effectively and simultaneously model spatial and temporal dependencies among traffic crowd flows. To address this issue, in this article a novel spatio-temporal deep hybrid neural network proposed termed STD-Net to forecast citywide crowd traffic flows. More specifically, STD-Net contains four major branches, i.e., closeness, period volume, weekly volume, and external branches, respectively. We design a residual neural network unit for each property to depict the spatio-temporal features of traffic flows. For various branches, STD-Net provides distinct weights and then combines the outputs of four branches together. Extensive experiments on two large-scale datasets from New York bike and Beijing taxi have demonstrated that STD-Net achieves competitive performances the existing state-of-the-art prediction baselines

BET proteins are associated with the induction of small airway fibrosis in COPD

Rationale In COPD, small airway fibrosis occurs due to increased extracellular matrix (ECM) deposition in and around the airway smooth muscle (ASM) layer. Studies of immune cells and peripheral lung tissue have shown that epigenetic changes occur in COPD but it is unknown whether airway mesenchymal cells are reprogrammed. Objectives Determine if COPD ASM cells have a unique epigenetic response to profibrotic cytokine transforming growth factor beta 1 (TGF-beta 1). Methods Primary human ASM cells from COPD and non-COPD smoking patients were stimulated with TGF-beta 1. Gene array analysis performed to identify differences in ECM expression. Airway accumulation of collagen 15 alpha 1 and tenascin-C proteins was assessed. Aforementioned ASM cells were stimulated with TGF-beta 1 +/- epigenetic inhibitors with qPCR quantification of COL15A1 and TNC. Global histone acetyltransferase (HAT) and histone deacetylase (HDAC) activity were assessed. chromatin immunoprecipitation (ChIP)-qPCR for histone H3 and H4 acetylation at COL15A1 and TNC promoters was carried out. Effects of bromoterminal and extraterminal domain (BET) inhibitor JQ1(+) on expression and acetylation of ECM target genes were assessed. Measurements and main results COPD ASM show significantly higher COL15A1 and TNC expression in vitro and the same trend for higher levels of collagen 15a1 and tenascin-c deposited in COPD airways in vivo. Epigenetic screening indicated differential response to HDAC inhibition. ChIP-qPCR revealed histone H4 acetylation at COL15A1 and TNC promoters in COPD ASM only. ChIP-qPCR found JQ1(+) pretreatment significantly abrogated TGF-beta 1 induced histone H4 acetylation at COL15A1 and TNC. Conclusions BET protein binding to acetylated histones is important in TGF-beta 1 induced expression of COL15A1 and TNC and maintenance of TGF-beta 1 induced histone H4 acetylation in cell progeny

The diagnostic accuracy of intraoperative frozen section biopsy for diagnosis of sentinel lymph node metastasis in breast cancer patients: a meta-analysis

: Sentinel lymph node (SLN) sampling is important for evaluating the nodal stage of breast cancer when the axillary nodes are clinically free of metastasis. The intraoperative frozen section (IFS) of SLN is used for lymph node assessment. This meta-analysis aims to provide evidence about the diagnostic accuracy and the applicability of IFS of SLN in breast cancer patients. Data were collected by searching PubMed, Cochrane, Scopus, and Web of Science electronic databases for trials matching our eligibility criteria. The statistical analysis included the sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and pooled studies' diagnostic odds ratio outcomes. The analyses were conducted using the Open Meta-analyst software. This meta-analysis pooled the results of 110 studies. The overall sensitivity of IFS for SLN metastasis was 74.7%; 95% CI [72.0, 77.2], P < 0.001. It was 31.4% 95% CI [25.2, 38.3], P < 0.001 for the micro-metastasis, and 90.2%; 95% CI [86.5, 93.0], P < 0.001 for the macro-metastasis. The overall specificity was 99.4%; 95% CI [99.2, 99.6], P < 0.001. The overall positive likelihood ratio was 121.4; 95% CI [87.9, 167.6], P < 0.001, and the overall negative likelihood ratio was 0.226; 95% CI [0.186, 0.274], P < 0.001. The overall diagnostic odds ratio of IFS for diagnosing SLN metastasis was 569.5; 95% CI [404.2, 802.4], P < 0.001. The intraoperative frozen section of SLN has good sensitivity for diagnosing breast cancer macro-metastasis. However, the sensitivity is low for micro-metastasis. The specificity is very satisfactory

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries