Clara Cordeiro

Pullulan-based nanoparticles as carriers for transmucosal protein delivery

Polymeric nanoparticles have revealed very effective in transmucosal delivery of proteins. Polysaccharides are among the most used materials for the production of these carriers, owing to their structural flexibility and propensity to evidence biocompatibility and biodegradability. In parallel, there is a preference for the use of mild methods for their production, in order to prevent protein degradation, ensure lower costs and easier procedures that enable scaling up. In this work we propose the production of pullulan-based nanoparticles by a mild method of polyelectrolyte complexation. As pullulan is a neutral polysaccharide, sulfated and aminated derivatives of the polymer were synthesized to provide pullulan with a charge. These derivatives were then complexed with chitosan and carrageenan, respectively, to produce the nanocarriers. Positively charged nanoparticles of 180-270 nm were obtained, evidencing ability to associate bovine serum albumin, which was selected as model protein. In PBS pH 7.4, pullulan-based nanoparticles were found to have a burst release of 30% of the protein, which maintained up to 24h. Nanoparticle size and zeta potential were preserved upon freeze-drying in the presence of appropriate cryoprotectants. A factorial design was approached to assess the cytotoxicity of raw materials and nanoparticles by the metabolic test MTT. Nanoparticles demonstrated to not cause overt toxicity in a respiratory cell model (Calu-3). Pullulan has, thus, demonstrated to hold potential for the production of nanoparticles with an application in protein delivery.

Hybrid nanosystems based on natural polymers as protein carriers for respiratory delivery: Stability and toxicological evaluation.

Chitosan/carrageenan/tripolyphosphate nanoparticles were previously presented as holding potential for an application in transmucosal delivery of macromolecules, with tripolyphosphate demonstrating to contribute for both size reduction and stabilisation of the nanoparticles. This work was aimed at evaluating the capacity of the nanoparticles as protein carriers for pulmonary and nasal transmucosal delivery, further assessing their biocompatibility pattern regarding that application. Nanoparticles demonstrated stability in presence of lysozyme, while freeze-drying was shown to preserve their characteristics when glucose or sucrose were used as cryoprotectants. Bovine serum albumin was associated to the nanoparticles, which were successfully microencapsulated by spray-drying to meet the aerodynamic requirements inherent to pulmonary delivery. Finally, a satisfactory biocompatibility profile was demonstrated upon exposure of two respiratory cell lines (Calu-3 and A549 cells) to the carriers. A negligible effect on cell viability along with no alterations on transepithelial electrical resistance and no induction of inflammatory response were observed.

Self-reported quality care for knee osteoarthritis: comparisons across Denmark, Norway, Portugal and the UK.

Objectives To assess and compare patient perceived quality of osteoarthritis (OA) management in primary healthcare in Denmark, Norway, Portugal and the UK. Methods Participants consulting with clinical signs and symptoms of knee OA were identified in 30 general practices and invited to complete a cross-sectional survey including quality indicators (QI) for OA care. A QI was considered as eligible if the participant had checked ‘Yes’ or ‘No’, and as achieved if the participant had checked ‘Yes’ to the indicator. The median percentage (with IQR and range) of eligible QIs achieved by country was determined and compared in negative binominal regression analysis. Achievement of individual QIs by country was determined and compared using logistic regression analyses. Results A total of 354 participants self-reported QI achievement. The median percentage of eligible QIs achieved (checked ‘Yes’) was 48% (IQR 28%, 64%; range 0–100%) for the total sample with relatively similar medians across three of four countries. Achievement rates on individual QIs showed a large variation ranging from 11% (referral to services for losing weight) to 67% (information about the importance of exercise) with significant differences in achievement rates between the countries. Conclusions The results indicated a potential for improvement in OA care in all four countries, but for somewhat different aspects of OA care. By exploring these differences and comparing healthcare services, ideas may be generated on how the quality might be improved across nations. Larger studies are needed to confirm and further explore the findings.

A Case Study of a Customer Satisfaction Problem: Bootstrap and Imputation Techniques

Bootstrap is a resampling technique proposed by Efron (The Annals of Statistics 7:1–26, 1979). It has been used in many fields, but in case of missing data studies one can find only a few references.

Boot.EXPOS in NNGC competition

In this article the authors expose an automatic procedure that combines a very popular resampling technique, the Bootstrap methodology, with one of the most widely used forecasting methods, the exponential smoothing. The merge of these two approaches originates the Boot.EXPOS. The algorithm can be summarized as follow: Given a time series, it starts by selecting the “best” EXPOS model for fitting the data, using the AIC criterion. The fitted values and the estimated EXPOS parameters are kept for later reconstructing the time series. Concerning the random part, a parametric model is fitted and then the residuals are bootstrapped. Here Boot.EXPOS procedure is applied. It can be summarized as follows: (i) fit an AR(p), where the order p is selected by AIC criterion; (ii) obtain the AR residuals; center the residuals; draw a sample with replacement from the centered residuals; (iii) obtain a bootstrapped replica recursively from the AR adjustment and using the bootstrap residuals series from the previous step; (iv) join the bootstrapped replica and the fitted EXPOS model to obtain a sample path of the initial time series; (v) use the new time series to obtain the EXPOS forecasts and forecast intervals. An additional algorithm NABoot.EXPOS was developed to handle with missing data. It detects, estimates and replaces the unobservable values.

Differences in self-reported quality of care for knee osteoarthritis across Denmark, Norway, Portugal and United Kingdom

Background Adherence to recommendations for osteoarthritis (OA) care can be measured using quality indicators (QI). In previous research differences related to the study design or the QI items make it challenging to directly compare the results. This EULAR funded study is the first that has applied the same set of QI items across four European countries. Objectives To assess and compare patient perceived quality of OA management in primary health care in Denmark, Norway, Portugal, and the United Kingdom. Methods Participants consulting general practitioners with clinical signs and symptoms of knee OA were identified in 30 general practices and invited to complete a cross-sectional survey including 14 QIs for OA care. A QI was considered as eligible if the participant had checked “Yes” or “No”, and as achieved if the participant had checked “Yes” to the indicator. The median percentage of eligible QIs achieved by country was determined and compared using negative binomial regression analyses. Achievement of individual QIs by country was determined and compared using logistic regression analyses. Results A total of 354 participants self-reported QI achievement. For the total sample, the median percentage of QIs achieved (checked ‘Yes’) was 48% (IQR 28% to 64%; range 0-100%). By country, the median percentage of QIs achieved was relatively similar across three of the countries, but significantly lower in Denmark (23%) compared to Norway (50%) even after adjustment for age, gender, BMI and comorbidity (rate ratio 0.49; 0.39, 0.62). For individual QIs related to different aspects of OA care, significant differences in self-reported achievement rates between the four countries were seen (Table 1). Achievement rates on individual QIs showed a large variation ranging from 0% (“referral to services for losing weight” & “functional assessments” in Denmark) to 83% (“information about the importance of exercise” in Norway). Compared to Norway, the achievement rates were significantly lower for 10 QIs in Denmark, 2 QIs in Portugal and 1 QI in the UK, whereas UK had significantly higher achievement rates than Norway for 5 QIs. Conclusions The results revealed a potential for improvement in OA care in all four countries, but for somewhat different aspects of OA care. By exploring these differences and comparing health care services across countries, ideas may be generated on how the quality of OA care might be improved. Larger studies are needed to confirm and further explore the findings in this study. Disclosure of Interest None declared

Forecast Intervals with Boot.EXPOS

Boot.EXPOS is an automatic computational procedure for forecasting time series developed in the Open image in new window environment joining two very popular methodologies: the exponential smoothing and the bootstrap. Results achieved in previous studies showed that this “mix scheme” seems to be a good approach to obtain point forecasts. This paper investigates the use of Boot.EXPOS in forecast intervals through the application to some well-known data sets. Results obtained show a very good performance of Boot.EXPOS in comparison with its “direct competitors,” the exponential smoothing methods.

Trend tests in time series with missing values: A case study with imputation

Testing for trend is an important problem, especially when one is dealing with environmental time series. The tests considered here are the usual t-test and the Mann-Kendall test, a nonparametric version widely used because it requires fewer assumptions. The aim is to assess the performance of two trend tests in time series with autocorrelation after an imputation method is applied to estimate the missing observations. The performance of the trend tests will be illustrated for some well-known data sets existing in R software.

How bootstrap can help in forecasting time series with more than one seasonal pattern

The search for the future is an appealing challenge in time series analysis. The diversity of forecasting methodologies is inevitable and is still in expansion. Exponential smoothing methods are the launch platform for modelling and forecasting in time series analysis. Recently this methodology has been combined with bootstrapping revealing a good performance. The algorithm (Boot. EXPOS) using exponential smoothing and bootstrap methodologies, has showed promising results for forecasting time series with one seasonal pattern. In case of more than one seasonal pattern, the double seasonal Holt-Winters methods and the exponential smoothing methods were developed. A new challenge was now to combine these seasonal methods with bootstrap and carry over a similar resampling scheme used in Boot. EXPOS procedure. The performance of such partnership will be illustrated for some well-know data sets existing in software.