Improving cost-efficiency for MPs density separation by zinc chloride reuse

The methodology used to extract and quantify microplastics (MPs) in aquatic systems are still not standardized. Salt saturated solutions, such as sodium chloride (NaCl), zinc chloride (ZnCl2) and/or sodium iodide (NaI), are normally added to separate dense plastics from aquatic samples. However, the most effective reagents are also the most expensive (e.g. ZnCl2 and NaI). To decrease this cost, a reuse process of the salt solutions should be applied. The reuse process has been widely investigated for the NaI solution neglecting the ZnCl2. Hence, the aim of this study was to present a simple methodology to reuse the ZnCl2 solution ensuring the efficiency of the product. Results of the present study showed that ZnCl2 solution could be reused at least five times maintaining an efficiency above 95 %. •The ZnCl2 reuse decreases the cost of the methodology.•The efficiency of ZnCl2 solution after five filtrations remains above 95 % (all polymers are detected and recovered).•The use of this salt solution is the most cost-effective methodology to isolate MPs from aquatic samples.publishe

Multilayer Complex Network Descriptors for Color-Texture Characterization

A new method based on complex networks is proposed for color-texture analysis. The proposal consists on modeling the image as a multilayer complex network where each color channel is a layer, and each pixel (in each color channel) is represented as a network vertex. The network dynamic evolution is accessed using a set of modeling parameters (radii and thresholds), and new characterization techniques are introduced to capt information regarding within and between color channel spatial interaction. An automatic and adaptive approach for threshold selection is also proposed. We conduct classification experiments on 5 well-known datasets: Vistex, Usptex, Outex13, CURet and MBT. Results among various literature methods are compared, including deep convolutional neural networks with pre-trained architectures. The proposed method presented the highest overall performance over the 5 datasets, with 97.7 of mean accuracy against 97.0 achieved by the ResNet convolutional neural network with 50 layers.Comment: 20 pages, 7 figures and 4 table

Trajectories of sleep quality during the first three years after breast cancer diagnosis

Objective: To identify trajectories of sleep quality up to three years after breast cancer diagnosis and to assess differences in characteristics of patients across distinct trajectories. Methods: A total of 458 breast cancer patients underwent a neurological evaluation before treatment and at one and three years after diagnosis. Clinical data were obtained throughout the follow-up. Anxiety and depression were evaluated at baseline, using the Hospital Anxiety and Depression Scale. In all sessions of follow-up, sleep quality was assessed using the Pittsburgh Sleep Quality Index. Model-based clustering was used to identify groups of patients with homogeneous variation in sleep quality. Results: We identified three trajectories of variation in sleep quality, named “low” (LSQ), “medium” (MSQ), and “high sleep quality” (HSQ). Women in the HSQ trajectory presented good sleep quality during the three years. LSQ and MSQ trajectories were characterized by poor sleep quality during the whole period, although during the first year the latter depicted a significant deterioration of sleep quality and the former a significant improvement. Patients included in the LSQ trajectory were more likely to have clinically significant anxiety and depression at baseline. The two trajectories with worse sleep quality were associated with neuropathic pain three years after cancer diagnosis. Conclusions: This study provides a model for describing the variation in sleep quality during the first three years after breast cancer diagnosis, based on three main trajectories. Further studies are needed understanding the heterogeneity of the individual trajectories within each of these major patterns of variation.This study was funded by FEDER through the Operational Programme Competitiveness and Internationalization (POCI-01-0145-FEDER-016867) and national funding from the Foundation for Science and Technology – FCT (Portuguese Ministry of Science, Technology and Higher Education) (PTDC/DTP-EPI/7283/2014) under the Unidade de Investigação em Epidemiologia - Instituto de Saúde Pública da Universidade do Porto (EPIUnit) (POCI-01-0145-FEDER-006862; Ref.UID/DTP/04750/2013); the PhD Grant SFRH/BD/92630/2013 (Filipa Fontes) co-funded by the FCT and the POPH/FSE Program. Data management activities up to the first year of follow-up were supported by the Chair on Pain Medicine of the Faculty of Medicine, University of Porto and by the Grünenthal Foundation – Portugal

Study of the Organic Extraction and Acidic Leaching of Chars Obtained in the Pyrolysis of Plastics, Tire Rubber and Forestry Biomass Wastes

AbstractThe present work aims to perform a characterization of chars obtained in the co-pyrolysis of waste mixtures composed by plastics, tires and pine biomass, to provide knowledge about the composition, leaching behavior and risk assessment of these materials in order to define strategies for their possible valorization or safe disposal. The chars were submitted to sequential solvent extractions with organic solvents of increasing polarity that allow the recovery of significant amounts of the pyrolysis oils trapped in the crude chars improving the yield of the pyrolysis liquids. An acidic demineralization procedure was successfully applied to the chars and high efficiency removals of the majority of the heavy metals were achieved. The demineralization study also demonstrated that hazardous heavy metals such as chromium, nickel and cadmium are significantly immobilized in the char matrix, and other heavy metals of concern such as zinc and lead will not represent a leaching problem if acidic conditions were not used. The obtained chars present sufficient quality and characteristics to be used as fuel or alternatively, to be used as adsorbents or precursors of activated carbon

Neuropathic pain after breast cancer treatment and its impact on sleep quality one year after cancer diagnosis

OBJECTIVES: Data regarding the impact of breast cancer treatment-related neuropathic pain (NP) on sleep quality are scarce. Therefore, we aimed to assess the impact of breast cancer treatment-related NP on patients' sleep quality, during the first year after cancer diagnosis. MATERIALS AND METHODS: A total of 501 breast cancer patients were followed prospectively. Incident NP was identified through systematic evaluations after treatments and one year after enrolment. NP severity was quantified using the Brief Pain Inventory severity subscale and sleep quality was evaluated through the Pittsburgh Sleep Quality Index (PSQI), at baseline and after one year. Adjusted regression coefficients (β) and 95% confidence intervals (95%CI) were used to quantify the relation between NP and the variation in the PSQI z-scores. RESULTS: The occurrence of NP was associated with a deterioration in sleep quality during the first year of follow-up, more pronounced among those with good sleep quality (PSQI≤5) than those with poor sleep quality at baseline (PSQI>5) (β = 0.44, 95%CI: 0.11 to 0.77 versus β = 0.33, 95%CI: 0.08 to 0.59). These differences were accentuated when only the cases of NP with greater severity were considered (β = 0.86, 95%CI: 0.37 to 1.35 versus β = 0.31, 95%CI: -0.08 to 0.64). Within the PSQI components, daytime dysfunction and sleep duration were the most impaired by NP. CONCLUSION: Our findings highlight the importance of the promotion of sleep hygiene among breast cancer patients diagnosed with NP, especially among those with good sleep quality before treatments.info:eu-repo/semantics/publishedVersio

Reliability and validity of the Pittsburgh Sleep Quality Index in breast cancer patients

Purpose: We aimed to assess the factor structure, internal consistency, test-retest reliability, and construct validity of the European Portuguese version of the Pittsburgh Sleep Quality Index (PSQI) in breast cancer patients. Methods: This study was based on a cohort of breast cancer patients, among whom the PSQI was used to measure sleep quality three years after cancer diagnosis (N = 474). A sample of 62 participants underwent additional PSQI testing, wore a wrist actigraph for five consecutive days, and was reevaluated with the PSQI after one month. A confirmatory factor analysis, considering the components suggested by the principal component analysis (PCA), was performed to determine model fit. To evaluate internal consistency and test-retest reliability, Cronbach’s alpha and intraclass correlation coefficient (ICC) were calculated, respectively. To assess construct validity, Spearman’s correlation coefficients were computed between PSQI scores and actigraphy measures and other theoretical related constructs. Results: PCA suggested one or two components. The latter showed better fit to the data, though the two factors were strongly correlated (r = 0.76) and internal consistency was not satisfactory for one of the factors. Regarding the one-factor model, internal consistency (Cronbach’s alpha = 0.70) and test-retest reliability (ICC = 0.76) were adequate. Sleep duration, habitual sleep efficiency, and sleep disturbance dimensions were significantly correlated with the corresponding actigraphy measures; the PSQI global score derived from the one-factor model was more strongly correlated with subjective sleep complaints (r ≥ 0.60). Conclusions: The unidimensional construct of the European Portuguese version of the PSQI showed adequate reliability and validity among breast cancer patients.This study was funded by FEDER through the Operational Programme Competitiveness and Internationalization (POCI-01-0145-FEDER-016867) and national funding from the Foundation for Science and Technology (FCT) (Portuguese Ministry of Science, Technology and Higher Education) (PTDC/DTP-EPI/7283/2014) under the Unidade de Investigação em Epidemiologia - Instituto de Saúde Pública da Universidade do Porto (EPIUnit) (POCI-01-0145-FEDER-006862; Ref.UID/DTP/04750/2013); the PhD Grant SFRH/BD/92630/2013 (Filipa Fontes) co-funded by the FCT and the POPH/FSE Program

Impacto da insulinoterapia prévia no prognóstico dos pacientes diabéticos com síndromes coronárias agudas

Impact of previous insulin therapy on the prognosis of diabetic patients with acute coronary syndrome

The impact of breast cancer treatments on sleep quality 1 year after cancer diagnosis

Purpose: The increasing number of women living longer with potential side effects of breast cancer treatment highlights the need of a comprehensive assessment of its burden. Therefore, we aimed to quantify the relation between different breast cancer treatments and sleep quality 1 year after diagnosis. Methods: A cohort of 502 newly diagnosed breast cancer patients was prospectively followed. Sleep quality was evaluated with the Pittsburgh Sleep Quality Index (PSQI), at baseline and at the 1-year follow-up. Odds ratios (OR) were computed to quantify the association between patient characteristics and poor sleep quality (PSQI score >5) at baseline, and relative risks (RR) were computed for the association between treatments and the occurrence of poor sleep quality at 1 year. Results A total of 60.2% of the patients had poor sleep quality before breast cancer treatments, especially those with anxiety [OR = 2.86, 95% confidence interval (95%CI) 1.92 to 4.27] or depression (OR = 5.25, 95%CI 2.01 to 13.67). Radiotherapy increased the risk of poor sleep quality at 1 year (RR = 3.71, 95%CI 1.15 to 11.96, for a cumulative dose >50 Gy) and there was a tendency for a higher risk in those submitted to chemotherapy, although not statistically significant. Conclusions Our study shows that sleep disturbances are frequent before cancer treatment and confirms their co-occurrence with other medical conditions, such as anxiety and depression. Different breast cancer treatments increase the risk of impaired sleep quality, therefore contributing to the global disability associated with cancer treatments.FF and ARC have received co-funded by the BFundação para a Ciência e a Tecnologia^ and the POPH/FSE Program (grant numbers SFRH/BD/92630/2013 and SFRH/BD/102181/2014, respectively). Data management activities were supported by the Chair on Pain Medicine of the Faculty of Medicine, University of Porto and by the Grünenthal Foundation – Portugal