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Red blood cells, platelet, hemoglobin, and mean corpuscular hemoglobin are the only suitable parameters without refrigeration during 24 h storage. When CBC and DLC are performed, 4 °C can be recommended as the most suitable storage temperature for 12 h storage.

Red blood cells, platelet, hemoglobin, and mean corpuscular hemoglobin are the only suitable parameters without refrigeration during 24 h storage. When CBC and DLC are performed, 4 °C can be recommended as the most suitable storage temperature for 12 h storage.Background To investigate the influence of lipid metabolism disorders on the risk of deep vein thrombosis. Methods A total of 200 subjects participated in the study, 100 of whom experienced DVT with or without PTE, and 100 healthy subjects representing the control group. We classified patients and controls in terms of serum concentrations of chylomicrons, LDL, IDL, VLDL, and HDL particles, as those with or without hyperlipoproteinemia and in terms of serum Lp (a) lipoprotein levels, as those with hyperLp (a) lipoproteinemia (serum Lp (a) values >0.3 g/L) and those without hyperLp (a) lipoproteinemia (serum Lp (a) values less then 0.3 g/L). Based on the modified and supplemented Fredrickson classification, participants with verified existences of hyperlipoproteinemia were classified into subgroups based on the type of hyperlipoproteinemia. Unconditional logistic regression was used to calculate ORs with 95% CIS as a measure of the relative risks for venous thrombosis in participants with hyperlipoproteinemia .54 OR 1.85; 95% CI 0.84-4.04). Conclusions Hypercholesterolemia doubles the risk of deep vein thrombosis development.Background Insulin-like growth factor binding protein-4 (IGFBP-4), a member of the insulin-like growth factor (IGF) family, transports, and regulates the activity of IGFs. The pregnancy-associated plasma protein-A (PAPP-A) has proteolytic activity towards IGFBP-4, and both proteins have been associated with a variety of cancers, including lung cancer. Thus, we aimed to evaluate the use of IGFBP-4 and PAPP-A as potential biomarkers for lung cancer. Methods Eighty-three volunteers, including 60 patients with lung cancer and 23 healthy individuals, were included in this study. The patients with lung cancer were selected based on their treatment status, histological subgroup, and stage of the disease. Enzyme-linked immunosorbent assays were used to assess the serum levels of IGFBP-4 and PAPPA, whereas the IGF-1 levels were measured using a chemiluminescent immunometric assay. Results The serum IGFBP-4 levels in all patient groups, regardless of the treatment status and histological differences, were significantly higher than those in the control group (p less then 0.005). However, the serum PAPP-A levels in the untreated patient group were found to be higher than those in the control group, but this difference was not statistically significant (p=0.086). selleck kinase inhibitor Conclusions The serum PAPP-A and IGFBP-4 levels are elevated in lung cancer. However, IGFBP-4 may have better potential than PAPP-A as a lung cancer biomarker.

Globally, all medical laboratories seeking accreditation should meet international quality standards to perform certain specific tests. Quality management program provides disciplines targeted to ensure that quality standards have been implemented by a laboratory in order to generate correct results. The hallmark of the accreditation process is method verification and quality assurance. Before introducing a new method in your laboratory, it is important to assess certain performance characteristics that reflect the concept of method verification.

In this review, we illustrated how to verify the performance characteristics of a new method according to the recent guidelines. It includes an assessment of precision, trueness, analytical sensitivity, detection limits, analytical specificity, interference, measuring range, linearity, and measurement uncertainty.

Although the presence of several updated guidelines used to determine the performance characteristics of new methods in clinical chemistry laboratories, the real practice raised several concerns with the application of these guidelines which in need for further consideration in the upcoming updates of these guidelines.

Although the presence of several updated guidelines used to determine the performance characteristics of new methods in clinical chemistry laboratories, the real practice raised several concerns with the application of these guidelines which in need for further consideration in the upcoming updates of these guidelines.Financial contagion refers to the spread of market turmoils, for example from one country or index to another country or another index. It is standardly assessed by modelling the evolution of the correlation matrix, for example of returns, usually after removing univariate dynamics with the GARCH model. However, significant events like crises visible in one financial market are usually reflected in other financial markets/countries simultaneously in several dimensions, i.e., in general, entire distributions of returns in other markets are affected. These distributions are determined/described by their expected value, variance, skewness, kurtosis and other statistics that determine the shape of the distribution function of returns, which can be based on higher (mixed) moments. These descriptive statistics are not constant over time, and, moreover, they can interreact within the given market and among the markets over time. In this article we propose, and use for the daily values of five indexes (CAC40, DAX30, DJIA, FTSE250 and WIG20) over the time period 2006-2017, a new, simple and computationally inexpensive methodology to automatically extend contagion evaluation from the evolution of the correlation matrix to the evolution of multiple higher mixed moments as well. Specifically, the joint distribution of normalized variables for each pair of indexes is modeled as a polynomial with time evolving coefficients estimated using an exponential moving average. As we can obtain any arbitrary number of evolving mixed moments this way, its dimensionality reduction using PCA (principal component analysis) is also discussed, obtaining a lower number of dominating and relatively independent features, which can each be interpreted through a polynomial that describes the corresponding perturbation of joint distribution. We obtain features that describe the interrelations among stock markets in several dimensions and that provide information about the current stage of crisis and the strength of the contagion process.The aim of the present study was to test an explanatory model for individual and social wellbeing which incorporates the advantages of using digital technologies during the COVID-19 pandemic. The study was carried out in Italy, one of the countries that has been most severely affected by the pandemic worldwide. The study was designed to include variables that might be specifically pertinent to the uniqueness of the restrictions imposed by the pandemic. Adults living in Italy (n = 1412) completed an online survey during the lockdown period in March 2020. Results showed two distinct digital interaction processes highlighted by the facilitating use of online emotions ("e-motions") and online social support ("e-support"). In short, e-motions were positively related to posttraumatic growth, which in turn was positively associated with positive mental health and higher engagement in prosocial behaviors. Moreover, individuals who perceived themselves as having greater e-support were characterized by higher levels of positive mental health, which it turn was positively associated with prosocial behaviors. Collectively, these two digital interaction processes suggest that digital technologies appear to be critical resources in helping individuals cope with difficulties raised by the COVID-19 pandemic.This paper deals with the recognition of selected burning liquids by convolutional neural networks (CNNs). Three CNNs (AlexNet, GoogLeNet and ResNet-50) were trained, validated and tested (in the MATLAB 2020b software) for the recognition of selected liquids (ethanol, propanol and pentane) using photographs of the flames they produce. For training, validation and test photographs of the liquids under investigation burning in a 106-mm-diameter vessel were used. The accuracy of all the CNNs under investigation during the tests was above 99%. In addition the trained CNNs were tested using photographs of the flames generated by the liquids under investigation burning in a vessel with a diameter of 75 mm. The accuracy of the trained CNNs in this additional test ranged from 37 to 42% (GoogLeNet) through 62-73% (ResNet-50) up to 51-80% (AlexNet) - the results varied dependent upon the relative size of the flame in the photograph under analysis (in most cases an increase in the relative size caused an increase in accuracy). The accuracy of the AlexNet can be improved from 80% to almost 96% using an algorithm. The principle of the algorithm is the analysis of 10 photographs of the same liquid in the same vessel (taken over a few seconds) followed by the recognition based on an identical classification for at least 6 out of 10 photographs. link2 An accuracy of 96% is sufficient for the rapid recognition of burning liquids in practical applications.

The online version contains supplementary material available at 10.1007/s10973-021-10903-2.

The online version contains supplementary material available at 10.1007/s10973-021-10903-2.The paper aims to identify the factors that cause prospective tourists' hesitation to travel. The study also examines whether this relationship is mediated by the tourist perception in Bangladesh. The study is of quantitative design, and the relationships between tourist knowledge, tourist health risk, and destination personality with tourist hesitation were explored using a sample of 322 Bangladeshi prospective tourists. The three relationships were also examined through tourist perception. By using cross-sectional data, the researchers hypothesized that tourist knowledge, tourist health risk, and destination personality have a positive and significant effect on tourist hesitation. Besides, the researchers also hypothesized that tourist perception mediates the relationships between tourist knowledge, tourist health risk, and destination personality with tourist hesitation. In this respect, the Smart PLS 3.0 was employed to analyze the data. The results of the study confirm findings of previous related studie. link3 Besides, the results may assist stakeholders of tourist destinations in understanding tourist perception and the causes of tourist's hesitation.The growing availability of data and the emergence of business analytics ecosystems offer possibilities for companies developing innovative business models. However, the disruptive impact of these business models on society is not always judged favourably. This paper explores the growing tensions in the relationship between disruptive Big Data companies and society through the lens of legitimacy - a judgement about the fit and propriety of an entity, such as a company, to society. The study is based on four instrumental cases where Big Data organisations were faced with challenges to their legitimacy. The findings elaborate how digital transformations require companies to understand and manage how much to disrupt and how much to conform to social norms and values. Big Data businesses face a dynamic and paradoxical tension between the potential costs and benefits of their disruptive business models. The topic of legitimacy management is also addressed, drawing out implications for practice.

The online version contains supplementary material available at 10.