005-0.791 mg/kg). According to the guidelines of the World Health Organisation (WHO) concerning the limits of contamination of samples of herbal raw materials with heavy metals, lead levels exceeding the limits were only noted in 24 samples of herbs (18%). In all of the analysed samples of spices, tea, and coffee, no instances of exceeded limits were noted for any of the analysed heavy metals. The values of TTHQmax (in relation to the consumption of the analysed products) were as follows up to 4.23 × 10-2 for spices, up to 2.51 × 10-1 for herbs, up to 4.03 × 10-2 for China tea, and up to 1.25 × 10-1 for roasted coffee beans. As the value of THQ ≤1, there is no probability of the appearance of undesirable effects related to the consumption of the analysed group of raw materials and products of plant origin. The CR value for As (max. value) was 1.29 × 10-5, which is lower than the maximum acceptable level of 1 × 10-4 suggested by United States Environmental Protection Agency (USEPA).A variety of screening approaches have been proposed to diagnose epileptic seizures, using electroencephalography (EEG) and magnetic resonance imaging (MRI) modalities. Artificial intelligence encompasses a variety of areas, and one of its branches is deep learning (DL). Before the rise of DL, conventional machine learning algorithms involving feature extraction were performed. This limited their performance to the ability of those handcrafting the features. However, in DL, the extraction of features and classification are entirely automated. The advent of these techniques in many areas of medicine, such as in the diagnosis of epileptic seizures, has made significant advances. In this study, a comprehensive overview of works focused on automated epileptic seizure detection using DL techniques and neuroimaging modalities is presented. Various methods proposed to diagnose epileptic seizures automatically using EEG and MRI modalities are described. In addition, rehabilitation systems developed for epileptic seizures using DL have been analyzed, and a summary is provided. The rehabilitation tools include cloud computing techniques and hardware required for implementation of DL algorithms. The important challenges in accurate detection of automated epileptic seizures using DL with EEG and MRI modalities are discussed. The advantages and limitations in employing DL-based techniques for epileptic seizures diagnosis are presented. Finally, the most promising DL models proposed and possible future works on automated epileptic seizure detection are delineated.The usage of face masks has been mandated in many countries in an attempt to diminish the spread of SARS-CoV-2. In this cross-sectional study, we aimed to determine face mask-wearing behaviors and practices in 1173 young Polish people during the second wave of the COVID-19 epidemic in October 2020. The majority of respondents (97.4%) declared that they wore face masks in areas/situations where it is mandatory. The most common types of utilized face masks were cloth masks (47.7%) and surgical masks (47%), followed by respirators (N95/FFP3) (3.2%) and half-face elastomeric respirators (0.9%). Over 38% reported frequently disinfecting their face masks, especially females. Respondents reporting personal atopic predisposition (64.5% vs.  https://www.selleckchem.com/products/pf-04620110.html  72.1%; p = 0.02) or sensitive skin (65.5% vs. 74.3%; p = 0.005) declared multiple use of face masks less commonly than other individuals. Individuals suffering from facial skin lesions declared disinfecting face masks more commonly (40.8% vs. 34.9%; p = 0.04). Overall, the self-declared utilization of face masks among young people in Poland has improved since the beginning of the epidemic as compared with our previous study. Until the mass vaccination of the public is achieved and government policy is changed, face mask use remains a valuable tool to decrease the transmission of SARS-CoV-2.Cognitive decline and kidney disease are significant public health problems that share similar characteristics and risk factors. The pathophysiology of the kidney-brain axis is not completely understood, and studies analysing the relationship between the biomarkers of kidney damage and cognitive impairment show different results. This article focuses on the epidemiological and clinical aspects concerning the association of albuminuria, a marker for endothelial dysfunction and microvascular disease, and cognitive impairment in patients with chronic kidney disease, diabetic kidney disease and end-stage kidney disease. Most studies show a positive relationship between albuminuria and cognitive impairment in all groups, but evidence in type 2 diabetes (T2D) patients is limited. We briefly discuss the mechanisms underlying these associations, such as damage to the microvascular circulation, leading to hypoperfusion and blood pressure fluctuations, as well as increased inflammation and oxidative stress, both in the brain and in the kidneys. Further clinical and epidemiological studies developed to understand the interplay between the kidneys and brain diseases will hopefully lead to a reduction in cognitive impairment in these patients.Viral diseases can seriously damage the vineyard productivity and the quality of grape and wine products. Therefore, the study of the species composition and range of grapevine viruses is important for the development and implementation of strategies and tactics to limit their spread and increase the economic benefits of viticulture. In 2014-2019, we carried out a large-scale phytosanitary monitoring of Russian commercial vineyards in the Krasnodar region, Stavropol region and Republic of Crimea. A total of 1857 samples were collected and tested for the presence of Grapevine rupestris stem pitting-associated virus (GRSPaV), Grapevine virus A (GVA), Grapevine leafroll-associated virus-1 (GLRaV-1), Grapevine leafroll-associated virus-2 (GLRaV-2), Grapevine leafroll-associated virus-3 (GLRaV-3), Grapevine fanleaf virus (GFLV), and Grapevine fleck virus (GFkV) using RT-PCR. Out of all samples tested, 54.5% were positive for at least one of the viruses (GRSPaV, GVA, GLRaV-1, GLRaV-2, GLRaV-3, GFLV, GFkV) in the Stavropol region, 49.