There is an increasing amount of evidence which links the pathogenesis of irritable bowel syndrome (IBS) with food IgG hyperreactivity. Some authors have suggested that food IgG hyperreactivity could be also involved in the pathophysiology of major depressive disorder (MDD). The aim of this study was to compare levels of serum IgG against 39 selected food antigens between three groups of participants: patients with MDD (MDD group), patients with IBS (IBS group) and healthy controls (HC group). The study included 65 participants (22 in the MDD group, 22 in the IBS group and 21 in the HC group). Serum IgG levels were examined using enzyme-linked immunosorbent assay (ELISA). Medical records, clinical data and laboratory results were collected for the analysis. IgG food hyperreactivity (interpreted as an average of levels of IgG antibodies above 7.5 µg/mL) was detected in 28 (43%) participants, including 14 (64%) from the MDD group, ten (46%) from the IBS group and four (19%) from the HC group. We found differences between extreme IgG levels in MDD versus HC groups and in IBS versus HC groups. Patients with MDD had significantly higher serum levels of total IgG antibodies and IgG against celery, garlic and gluten compared with healthy controls. The MDD group also had higher serum IgG levels against gluten compared with the IBS group. Our results suggest dissimilarity in immune responses against food proteins between the examined groups, with the highest immunoreactivity in the MDD group. Further studies are needed to repeat and confirm these results in bigger cohorts and also examine clinical utility of IgG-based elimination diet in patients with MDD and IBS.

Transport is an area that is developing at a tremendous pace. This development applies not only to electric and hybrid cars appearing more and more often on the road but also to those of an autonomous or semi-autonomous nature. This applies to both passenger cars and vans. In many different publications, you can find a description of a number of benefits of using automated guided vehicles (AGV) for logistics and technical tasks, e.g., in the workplace. An important aspect is the use of knowledge management and machine learning, i.e., artificial intelligence (AI), to design these types of processes. An important issue in the construction of autonomous vehicles is the IT connection of sensors receiving signals from the environment. These signals are data for deep learning algorithms. The data after IT processing enable the decision-making by AI systems, while the used machine learning algorithms and neural networks are also needed for video image analysis in order to identify and classify registered objects. The purpose of this article is to present and verify a mathematical model used to respond to vehicles’ demand for a transport service under set conditions. The optimal conditions of the system to perform the transport task were simulated, and the efficiency of this system and benefits of this choice were determined.

Background: Lung cancer is the leading cause of cancer-related deaths. Early diagnosis may improve the prognosis. Methods: Using quantitative methylation-specific real-time PCR (qMSP-PCR), we assessed the methylation status of two genes (in two subsequent regions according to locations in their promoter sequences) related to carcinogenesis, DICER and DROSHA, in 101 plasma samples (obtained prior to the treatment) of lung cancer patients and 45 healthy volunteers. Results: The relative level of methylation of DROSHA was significantly lower (p = 0.012 for first and p < 0.00001 for the second region) and DICER significantly higher (p = 0.029 for the first region) in cancer patients. The relative level of methylation of DROSHA was significantly (p = 0.037) higher in patients with early-stage NSCLC (IA-IIIA) and could discriminate them from healthy people with a sensitivity of 71% and specificity of 76% (AUC = 0.696, 95% CI: 0.545–0.847, p = 0.011) for the first region and with a sensitivity of 60% and specificity of 85% (AUC = 0.795, 95% CI: 0.689–0.901, p < 0.0001) for the second region. Methylation analysis of the first region of the DICER enabled the distinction of NSCLC patients from healthy individuals with a sensitivity of 96% and specificity of 60% (AUC = 0.651, 95% CI: 0.517–0.785, p = 0.027). The limitations of the study include its small sample size, preliminary nature, being an observational type of study, and the lack of functional experiments allowing for the explanation of the biologic backgrounds of the observed associations. Conclusion: The obtained results indicate that the assessment of DICER and DROSHA methylation status can potentially be used as a biomarker for the early detection of lung cancer.

Metals perform many important physiological functions in the human body. The distribution of elements in different tissues is not uniform. Moreover, some structures can be the site of an accumulation of essential or toxic metals, leading to multi-directional intracellular damage. In the nervous system, these disorders are especially dangerous. Metals dyshomeostasis has been linked to a variety of neurological disorders which end up leading to permanent injuries. The multi-elemental composition of the human brain is still the subject of numerous investigations and debates. In this study, for the first time, the meninges, i.e., the dura mater and the arachnoid, were examined for their elemental composition by means of inductively coupled plasma mass spectrometry (ICP-MS). Tissue samples were collected post mortem from those who died suddenly as a result of suicide (n = 20) or as a result of injuries after an accident (n = 20). The interactions between 51 elements in both groups showed mainly weak positive correlations, which dominated the arachnoid mater compared to the dura mater. The study showed differences in the distribution of some elements within the meninges in the studied groups. The significant differences concerned mainly metals from the lanthanide family (Ln), macroelements (Na, K, Ca, Mg), a few micronutrients (Co), and toxic cadmium (Cd). The performed evaluation of the elemental distribution in the human meninges sheds new light on the trace metals metabolism in the central nervous system, although we do not yet fully understand the role of the human meninges.

Recently, we have seen an increase in interest in autonomous mobility around the world. Autonomous vehicles have enormous potential, and the development of radar, information, communication, and measurement technologies brings us closer and closer to this type of mobility. This article considers the principles of planning and selecting routes for transport tasks. The research on the values of indicators characterizing the transport process was carried out for a simple case, when vehicles move along a fixed route without disturbances. The research used mathematical modelling based on the theory of Markov random systems to determine the capacity of the system, the average length of the queue for service, and the average number of transport tasks. The simulations were carried out for the assumed number of vehicles m = 15 and for points requiring service N = 40. The ranges were obtained wherein the number of occupied vehicles oscillated around 30% (for ρ = 0.1), when all the vehicles were occupied (for ρ = 0.625), and when the system became inefficient.