Determination of yolk contamination in liquid egg white using Raman spectroscopy

Purified egg white is an important ingredient in a number of baked and confectionary foods because of its foaming properties. However, yolk contamination in amounts as low as 0.01% can impede the foaming ability of egg white. In this study, we used Raman spectroscopy to evaluate the hypothesis that yolk contamination in egg white could be detected based on its molecular optical properties. Yolk contaminated egg white samples (n = 115) with contamination levels ranging from 0% to 0.25% (on weight basis) were prepared. The samples were excited with a 785 nm laser and Raman spectra from 250 to 3,200 cm−1 were recorded. The Raman spectra were baseline corrected using an optimized piecewise cubic interpolation on each spectrum and then normalized with a standard normal variate transformation. Samples were randomly divided into calibration (n = 77) and validation (n = 38) data sets. A partial least squares regression (PLSR) model was developed to predict yolk contamination levels, based on the Raman spectral fingerprint. Raman spectral peaks, in the spectral region of 1,080 and 1,666 cm−1, had the largest influence on detecting yolk contamination in egg white. The PLSR model was able to correctly predict yolk contamination levels with an R2 = 0.90 in the validation data set. These results demonstrate the capability of Raman spectroscopy for detection of yolk contamination at very low levels in egg white and present a strong case for development of an on-line system to be deployed in egg processing plants

Basis Expansion in Natural Actor Critic Methods

International audienceIn reinforcement learning, the aim of the agent is to find a policy that maximizes its expected return. Policy gradient methods try to accomplish this goal by directly approximating the policy using a parametric function approximator; the expected return of the current policy is estimated and its parameters are updated by steepest ascent in the direction of the gradient of the expected return with respect to the policy parameters. In general, the policy is defined in terms of a set of basis functions that capture important features of the problem. Since the quality of the resulting policies directly depend on the set of basis func- tions, and defining them gets harder as the complexity of the problem increases, it is important to be able to find them automatically. In this paper, we propose a new approach which uses cascade-correlation learn- ing architecture for automatically constructing a set of basis functions within the context of Natural Actor-Critic (NAC) algorithms. Such basis functions allow more complex policies be represented, and consequently improve the performance of the resulting policies. We also present the effectiveness of the method empirically

Benzenesulfonamide Analogs : Synthesis, Anti-GBM Activity and Pharmacoprofiling

The tropomyosin receptor kinase A (TrkA) family of receptor tyrosine kinases (RTKs) emerge as a potential target for glioblastoma (GBM) treatment. Benzenesulfonamide analogs were identified as kinase inhibitors possessing promising anticancer properties. In the present work, four known and two novel benzenesulfonamide derivatives were synthesized, and their inhibitory activities in TrkA overexpressing cells, U87 and MEF cells were investigated. The cytotoxic effect of benzenesulfonamide derivatives and cisplatin was determined using trypan blue exclusion assays. The mode of interaction of benzenesulfonamides with TrkA was predicted by docking and structural analysis. ADMET profiling was also performed for all compounds to calculate the drug likeness property. Appropriate QSAR models were developed for studying structure–activity relationships. Compound 4-[2-(4,4-dimethyl-2,6-dioxocyclohexylidene)hydrazinyl]-N-(5-methyl-1,3,4-thiadiazol-2-yl)benzenesulfon-amide (AL106) and 4-[2-(1,3-dioxo-1,3-dihydro-2H-inden-2-ylidene)hydrazinyl]-N-(5-methyl-1,3,4-thiadiazol-2-yl)benzenesulfonamide (AL107) showed acceptable binding energies with the active sites for human nerve growth factor receptor, TrkA. Here, AL106 was identified as a potential anti-GBM compound, with an IC50 value of 58.6 µM with a less toxic effect in non-cancerous cells than the known chemotherapeutic agent, cisplatin. In silico analysis indicated that AL106 formed prominent stabilizing hydrophobic interactions with Tyr359, Ser371, Ile374 and charged interactions with Gln369 of TrkA. Furthermore, in silico analysis of all benzenesulfonamide derivatives revealed that AL106 has good pharmacokinetics properties, drug likeness and toxicity profiles, suggesting the compound may be suitable for clinical trial. Thus, benzenesulfonamide analog, AL106 could potentially induce GBM cell death through its interaction with TrkA and might be an attractive strategy for developing a drug targeted therapy to treat glioblastoma.Peer reviewe

The robustness of objective fabric pilling evaluation method

Previously, we proposed a new method to identify fabric pilling and objectively measure fabric pilling intensity based on the two-dimensional dual-tree complex wavelet reconstruction and neural network classification. Here we further evaluate the robustness of the method. Our results indicate that the pilling identification method is robust to significant variation in the brightness and contrast of the image, rotation of the image, and 2 i (i is an integer) times dilation of the image. The pilling feature vector developed to characterize the pilling intensity is robust to brightness change but is sensitive to large rotations of the image. As long as all fabric images are adjusted to have the same contrast level and the sample is illuminated from the same direction, the pilling feature vectors are comparable and can be used to classify the pilling intensity.<br /

Volumetric laser endomicroscopy and its application to Barrett's esophagus: results from a 1,000 patient registry.

Volumetric laser endomicroscopy (VLE) uses optical coherence tomography (OCT) for real-time, microscopic cross-sectional imaging. A US-based multi-center registry was constructed to prospectively collect data on patients undergoing upper endoscopy during which a VLE scan was performed. The objective of this registry was to determine usage patterns of VLE in clinical practice and to estimate quantitative and qualitative performance metrics as they are applied to Barrett's esophagus (BE) management. All procedures utilized the NvisionVLE Imaging System (NinePoint Medical, Bedford, MA) which was used by investigators to identify the tissue types present, along with focal areas of concern. Following the VLE procedure, investigators were asked to answer six key questions regarding how VLE impacted each case. Statistical analyses including neoplasia diagnostic yield improvement using VLE was performed. One thousand patients were enrolled across 18 US trial sites from August 2014 through April 2016. In patients with previously diagnosed or suspected BE (894/1000), investigators used VLE and identified areas of concern not seen on white light endoscopy (WLE) in 59% of the procedures. VLE imaging also guided tissue acquisition and treatment in 71% and 54% of procedures, respectively. VLE as an adjunct modality improved the neoplasia diagnostic yield by 55% beyond the standard of care practice. In patients with no prior history of therapy, and without visual findings from other technologies, VLE-guided tissue acquisition increased neoplasia detection over random biopsies by 700%. Registry investigators reported that VLE improved the BE management process when used as an adjunct tissue acquisition and treatment guidance tool. The ability of VLE to image large segments of the esophagus with microscopic cross-sectional detail may provide additional benefits including higher yield biopsies and more efficient tissue acquisition. Clinicaltrials.gov NCT02215291

Learning to Communicate: A Machine Learning Framework for Heterogeneous Multi-Agent Robotic Systems

We present a machine learning framework for multi-agent systems to learn both the optimal policy for maximizing the rewards and the encoding of the high dimensional visual observation. The encoding is useful for sharing local visual observations with other agents under communication resource constraints. The actor-encoder encodes the raw images and chooses an action based on local observations and messages sent by the other agents. The machine learning agent generates not only an actuator command to the physical device, but also a communication message to the other agents. We formulate a reinforcement learning problem, which extends the action space to consider the communication action as well. The feasibility of the reinforcement learning framework is demonstrated using a 3D simulation environment with two collaborating agents. The environment provides realistic visual observations to be used and shared between the two agents.Comment: AIAA SciTech 201

Sorption-Desorption Behavior of Atrazine on Soils Subjected to Different Organic Long-Term Amendments

Sorption of atrazine on soils subjected to three different organic amendments was measured using a batch equilibrium technique. A higher K(F) value (2.20 kg(-1)(mg L(-1))(-)N) was obtained for soil fertilized with compost, which had a higher organic matter (OM) content. A correlation between the K(Foc) values and the percentage of aromatic carbon in OM was observed. The highest K(Foc) value was obtained for the soil with the highest aromatic content. Higher aromatic content results in higher hydrophobicity of OM, and hydrophobic interactions play a key role in binding of atrazine, On the other hand, the soil amended with farmyard manure had a higher content of carboxylic units, which could be responsible for hydrogen bonding between atrazine and OR Dominance of hydrogen bonds compared to hydrophobic interactions can be responsible for the lower desorption capacity observed with the farmyard manure soil, The stronger hydrogen bonding can reduce the leaching of atrazine into drinking water resources and runoff to rivers and other surface waters

Left atrial volume predicts adverse cardiac and cerebrovascular events in patients with hypertrophic cardiomyopathy

<p>Abstract</p> <p>Aims</p> <p>To prospectively evaluate the relationship between left atrial volume (LAV) and the risk of clinical events in patients with hypertrophic cardiomyopathy (HCM).</p> <p>Methods</p> <p>We enrolled a total of 141 HCM patients with sinus rhythm and normal pump function, and 102 patients (73 men; mean age, 61 ± 13 years) who met inclusion criteria were followed for 30.8 ± 10.0 months. The patients were divided into two groups with or without major adverse cardiac and cerebrovascular events (MACCE), a composite of stroke, sudden death, and congestive heart failure. Detailed clinical and echocardiographic data were obtained.</p> <p>Results</p> <p>MACCE occurred in 24 patients (18 strokes, 4 congestive heart failure and 2 sudden deaths). Maximum LAV, minimum LAV, and LAV index (LAVI) corrected for body surface area (BSA) were significantly greater in patients with MACCE than those without MACCE (maximum LAV: 64.3 ± 25.0 vs. 51.9 ± 16.0 ml, p = 0.005; minimum LAV: 33.9 ± 15.1 vs. 26.2 ± 10.9 ml, p = 0.008; LAVI: 40.1 ± 15.4 vs. 31.5 ± 8.7 ml/mm², p = 0.0009), while there were no differences in the other echocardiographic parameters.</p> <p>LAV/BSA of ≥ 40.4 ml/m²to identify patients with cardiovascular complications with a sensitivity of 73% and a specificity of 88%.</p> <p>Conclusion</p> <p>LAVI may be an effective marker for detecting the risk of MACCE in patients with HCM and normal pump function.</p

Seroprevalence and factors associated with herpes simplex virus type 2 among HIV-negative high-risk men who have sex with men from Rio de Janeiro, Brazil: a cross-sectional study

Submitted by Frederico Azevedo ([email protected]) on 2010-11-04T17:19:23Z No. of bitstreams: 1 seroprevalence_and_factors.pdf: 273577 bytes, checksum: 742e51b14ff9ef765bf31b52f3fc8f1a (MD5)Made available in DSpace on 2010-11-04T17:19:23Z (GMT). No. of bitstreams: 1 seroprevalence_and_factors.pdf: 273577 bytes, checksum: 742e51b14ff9ef765bf31b52f3fc8f1a (MD5) Previous issue date: 2009Fundação Oswaldo Cruz. Instituto de Pesquisa Clínica Evandro Chagas. Rio de Janeiro, RJ, Brasil.Fundação Oswaldo Cruz. Instituto de Pesquisa Clínica Evandro Chagas. Rio de Janeiro, RJ, Brasil.Fundação Oswaldo Cruz. Instituto de Comunicação e Informação Científica e Tecnológica em Saúde. Rio de Janeiro, RJ, Brasil.Fundação Oswaldo Cruz. Instituto de Pesquisa Clínica Evandro Chagas. Rio de Janeiro, RJ, Brasil.Fundação Oswaldo Cruz. Instituto de Pesquisa Clínica Evandro Chagas. Rio de Janeiro, RJ, Brasil.Fundação Oswaldo Cruz. Instituto de Pesquisa Clínica Evandro Chagas. Rio de Janeiro, RJ, Brasil.Fundação Oswaldo Cruz. Instituto de Pesquisa Clínica Evandro Chagas. Rio de Janeiro, RJ, Brasil.Fundação Oswaldo Cruz. Instituto de Pesquisa Clínica Evandro Chagas. Rio de Janeiro, RJ, Brasil.Fundação Oswaldo Cruz. Instituto de Pesquisa Clínica Evandro Chagas. Rio de Janeiro, RJ, Brasil.Background: Herpes simplex virus type 2 (HSV-2) is the leading cause of genital ulcer disease in developing countries, including Brazil, and is especially prevalent among men who have sex with men (MSM). HSV-2 infection represents a risk factor for the acquisition and transmission of other sexually transmitted diseases. The goal of the present cross-sectional study was to estimate HSV- 2 seroprevalence and to determine the factors associated with HSV-2 seropositivity in HIVnegative high-risk MSM from Rio de Janeiro, Brazil. Methods: Stored sera were tested to estimate HSV-2 seroprevalence, while socio-demographic and sexual behavior data were used to measure associations between risk factors and HSV-2 seropositivity. Using the Poisson regression model with robust variance, prevalence ratios (PR) were used to estimate de degree of association between risk factors and HSV-2 seropositivity in bivariate and multivariate analyses. Results: Seroprevalence of HSV-2 was of 45.7% (184 out of 403). Factors independently associated with HSV-2 seroprevalence in the multivariate model were: older age (≥ 26 years, PR: 1.41 95% Confidence Interval: 1.11–1.78), non-white race (PR: 1.32 95%CI: 1.06–1.64), positive serology for syphilis (PR: 1.65 95%CI: 1.33–2.05), positive serology for hepatitis B (PR: 1.25 95%CI: 0.99–1.57), stable male partner in the past 6 months (PR: 1.42 95%CI: 1.12–1.79), and unprotected anal sex with a stable female partner (PR: 1.46 95%CI: 1.05–2.04) in the 6 months preceding the crosssectional assessment. Conclusion: The present study made evident a high prevalence of HSV-2 infection in a sample of HIV-negative high-risk MSM from Rio de Janeiro. This finding indicates the need and urgency for implementing integrated programs for the prevention of HSV-2 and other sexually transmitted diseases, and, in particular, programs targeting high-risk MSM

Internet of Things in Water Management and Treatment

The goal of the water security IoT chapter is to present a comprehensive and integrated IoT based approach to environmental quality and monitoring by generating new knowledge and innovative approaches that focus on sustainable resource management. Mainly, this chapter focuses on IoT applications in wastewater and stormwater, and the human and environmental consequences of water contaminants and their treatment. The IoT applications using sensors for sewer and stormwater monitoring across networked landscapes, water quality assessment, treatment, and sustainable management are introduced. The studies of rate limitations in biophysical and geochemical processes that support the ecosystem services related to water quality are presented. The applications of IoT solutions based on these discoveries are also discussed