Hebertjama3761

Plastic is widely used for human activities (food packaging, medical, technological devices, etc.) and there is a growing concern regarding the risks for environmental and human health because they have still not been fully evaluated. Particularly, microplastics (primary and secondary) are present in all environmental compartments and this poses a potential threat because of their entry into the food chain. Furthermore, microplastics can absorb numerous pollutants that can be accumulated in the human body through bioaccumulation and biomagnification processes. We carried out a systematic review using a PRISMA approach to verify the efficiency of wastewater treatment plants (WWTPs) for microplastic removal. The international databases (PubMed, Science Direct, Scopus) were used to find published studies on efficiency of wastewater treatment plants (WWTPs) for microplastic removal. The search period was between January 2010 and June 2020. Over 1000 full research papers were initially selected through the use of in the near future, efficient and common standardized protocols for monitoring MPs should be drawn up, as well as increasing the knowledge of sources and strategies to further reduce microplastics contamination of treated wastewater.The concept of lysosomotropic agents significantly changed numerous aspects of cellular biochemistry, biochemical pharmacology, and clinical medicine. In the present review, we focused on numerous low-molecular and high-molecular lipophilic basic compounds and on the role of lipophagy and autophagy in experimental and clinical medicine. Attention was primarily focused on the most promising agents acting as autophagy inducers, which offer a new window for treatment and/or prophylaxis of various diseases, including type 2 diabetes mellitus, Parkinson's disease, and atherosclerosis. The present review summarizes current knowledge on the lysosomotropic features of medical drugs, as well as autophagy inducers, and their role in pathological processes.Natalizumab (NAT) was the first disease modifying therapy used for the treatment of relapsing-remitting multiple sclerosis (MS) that was designed with a specific mechanism of action that targets an important step of the MS immunopathology, directly blocking the T lymphocyte intrusion in the central nervous system. Initially, it was considered that NAT carried no biological effects on the peripheral immune response. The purpose of our study was to assess the effects of NAT on the peripheral pro and anti-inflammatory cytokines and to reveal possible correlations between them and the clinical activity of the disease. We noticed a significant decrease in interleukin (IL)-17, tumor necrosis factor-alpha (TNF-α) and IL-31 serum levels in treated patients. The lack of relapses during the study was associated with low baseline IL-17 level. The patients that had an increase in the disability score during the study had significantly lower IL-17 and higher IL-1β baseline levels. IL-17 can be used as a biomarker for disease activity but also for progression assessment in NAT treated patients. NAT has a far more complex mechanism compared to what was initially believed, besides modulating lymphocyte trafficking through the blood-brain barrier, it also changes the peripheral levels of pro and anti-inflammatory cytokines in MS patients.This article aims to provide a critical review of the scientific research on technostress. As such, global references in this field are identified and highlighted in order to manage pre-existing knowledge and establish future 'bridges' among researchers, and to enhance the presently dispersed understanding of this subject. A scientometric meta-analysis of publications on technostress was conducted to achieve this objective. Mainstream journals from the Web of Science (WoS) were used to identify current topics, relevant journals, prolific authors, institutions, and countries, 'schools of thought' and the thematic areas around which current technostress debate revolves. In this article a significant contribution comes from the use of the scientific activity itself, together with scientometric meta-analysis techniques and the application of this scientific activity, its impact and relational character, to discover relevant countries, research organizations and authors which can constitute a global reference to demarcate this knowledge frontier, and who lead the 'critical mass' of global technostress researchers. This study also distinguishes between the relevant themes studied, with co-keywords plus bibliographic coupling citation, and examines the kind of stress the most prolific authors have considered and, therefore, to discover those topics which should be studied further to deepen this research field, in search of a post-disciplinary knowledge that allows unity of focus in technology and psychology.In this article, a compact dual-laser sensor based on an off-axis integrated-cavity output spectroscopy and time-division multiplexing method is reported. A complete dual-channel optical structure is developed and integrated on an optical cavity, which allows two distributed feedback (DFB) lasers operating at wavelengths of 1603 nm and 1651 nm to measure the concentration of CO2 and CH4, simultaneously. Performances of the dual-laser sensor are experimentally evaluated by using standard air (with a mixture of CO2 and CH4). The limit of detection (LoD) is 0.271 ppm and 1.743 ppb at a 20 s for CO2 and CH4, respectively, and the noise equivalent absorption sensitivities are 2.68 × 10-10 cm-1 Hz-1/2 and 3.88 × 10-10 cm-1 Hz-1/2, respectively. Together with a commercial instrument, the dual-laser sensor is used to measure CO2 and CH4 concentration over 120 h and verify the regular operation of the sensor for the detection of ambient air. Furthermore, a first-order exponential moving average algorithm is implemented as an effective digital filtering method to estimate the gas concentration.Fertigation management of banana plantations at a plot scale is expanding rapidly in Brazil. learn more To guide nutrient management at such a small scale, genetic, environmental and managerial features should be well understood. Machine learning and compositional data analysis (CoDa) methods can measure the effects of feature combinations on banana yield and rank nutrients in the order of their limitation. Our objectives are to review ML and CoDa models for application at regional and local scales, and to customize nutrient diagnoses of fertigated banana at the plot scale. We documented 940 "Prata" and "Cavendish" plot units for tissue and soil tests, environmental and managerial features, and fruit yield. A Neural Network informed by soil tests, tissue tests and other features was the most proficient learner (AUC up to 0.827). Tissue nutrients were shown to have the greatest impact on model accuracy. Regional nutrient standards were elaborated as centered log ratio means and standard deviations of high-yield and nutritionally balanced specimens.