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Perry disease (PeD) is a rare, neurodegenerative, genetic disorder inherited in an autosomal dominant manner. The disease manifests as parkinsonism, with psychiatric symptoms on top, such as depression or sleep disorders, accompanied by unexpected weight loss, central hypoventilation, and aggregation of DNA-binding protein (TDP-43) in the brain. Due to the genetic cause, no causal treatment for PeD is currently available. The only way to improve the quality of life of patients is through symptomatic therapy. This work aims to review the latest data on potential PeD treatment, specifically from the medicinal chemistry and computer-aided drug design (CADD) points of view. We select proteins that might represent therapeutic targets for symptomatic treatment of the disease: monoamine oxidase B (MAO-B), serotonin transporter (SERT), dopamine D2 (D2R), and serotonin 5-HT1A (5-HT1AR) receptors. We report on compounds that may be potential hits to develop symptomatic therapies for PeD and related neurodegenerative diseases and relieve its symptoms. We use Phase pharmacophore modeling software (version 2023.08) implemented in Schrödinger Maestro as a ligand selection tool. For each of the chosen targets, based on the resolved protein–ligand structures deposited in the Protein Data Bank (PDB) database, pharmacophore models are proposed. We review novel, active compounds that might serve as either hits for further optimization or candidates for further phases of studies, leading to potential use in the treatment of PeD.

The future of therapy for neurodegenerative diseases (NDs) relies on new strategies targeting multiple pharmacological pathways. Our research led to obtaining the compound AR71 [(E)-3-(3,4,5-trimethoxyphenyl)-1-(4-(3-(piperidin-1-yl)propoxy)phenyl)prop-2-en-1-one], which has high affinity for human H[sub.3]R (Ki = 24 nM) and selectivity towards histamine H[sub.1] and H[sub.4] receptors (Ki > 2500 nM), and showed anti-inflammatory activity in a model of lipopolysaccharide-induced inflammation in BV-2 cells. The presented tests confirmed its antagonist/inverse agonist activity profile and good metabolic stability while docking studies showed the binding mode to histamine H[sub.1], H[sub.3], and H[sub.4] receptors. In in vitro tests, cytotoxicity was evaluated at three cell lines (neuroblastoma, astrocytes, and human peripheral blood mononuclear cells), and a neuroprotective effect was observed in rotenone-induced toxicity. In vivo experiments in a mouse neuropathic pain model demonstrated the highest analgesic effects of AR71 at the dose of 20 mg/kg body weight. Additionally, AR71 showed antiproliferative activity in higher concentrations. These findings suggest the need for further evaluation of AR71’s therapeutic potential in treating ND and CNS cancer using animal experimental models.

The future of therapy for neurodegenerative diseases (NDs) relies on new strategies targeting multiple pharmacological pathways. Our research led to obtaining the compound AR71 [(E)-3-(3,4,5-trimethoxyphenyl)-1-(4-(3-(piperidin-1-yl)propoxy)phenyl)prop-2-en-1-one], which has high affinity for human H3R (Ki = 24 nM) and selectivity towards histamine H1 and H4 receptors (Ki > 2500 nM), and showed anti-inflammatory activity in a model of lipopolysaccharide-induced inflammation in BV-2 cells. The presented tests confirmed its antagonist/inverse agonist activity profile and good metabolic stability while docking studies showed the binding mode to histamine H1, H3, and H4 receptors. In in vitro tests, cytotoxicity was evaluated at three cell lines (neuroblastoma, astrocytes, and human peripheral blood mononuclear cells), and a neuroprotective effect was observed in rotenone-induced toxicity. In vivo experiments in a mouse neuropathic pain model demonstrated the highest analgesic effects of AR71 at the dose of 20 mg/kg body weight. Additionally, AR71 showed antiproliferative activity in higher concentrations. These findings suggest the need for further evaluation of AR71’s therapeutic potential in treating ND and CNS cancer using animal experimental models.

The future of therapy for neurodegenerative diseases (NDs) relies on new strategies targeting multiple pharmacological pathways. Our research led to obtaining the compound AR71 [(E)-3-(3,4,5-trimethoxyphenyl)-1-(4-(3-(piperidin-1-yl)propoxy)phenyl)prop-2-en-1-one], which has high affinity for human H R (K = 24 nM) and selectivity towards histamine H and H receptors (K > 2500 nM), and showed anti-inflammatory activity in a model of lipopolysaccharide-induced inflammation in BV-2 cells. The presented tests confirmed its antagonist/inverse agonist activity profile and good metabolic stability while docking studies showed the binding mode to histamine H , H , and H receptors. In in vitro tests, cytotoxicity was evaluated at three cell lines (neuroblastoma, astrocytes, and human peripheral blood mononuclear cells), and a neuroprotective effect was observed in rotenone-induced toxicity. In vivo experiments in a mouse neuropathic pain model demonstrated the highest analgesic effects of AR71 at the dose of 20 mg/kg body weight. Additionally, AR71 showed antiproliferative activity in higher concentrations. These findings suggest the need for further evaluation of AR71's therapeutic potential in treating ND and CNS cancer using animal experimental models.

Environmental and occupational exposure to various metals has been a major public health concern and the subject of many studies. With the development of industry and transportation, environmental pollution has markedly worsened. As a result, metals are now ubiquitous and are absorbed into the body with food, drinking water, and polluted air. Exposure to these elements leads to numerous health problems, affecting almost every system of the human body, including the skeletal system. Bone is a specific research material that is difficult to obtain, therefore chemical analyses of metal concentrations in this tissue are rarely found in the literature. Nevertheless, bone, due to its long regeneration period, can serve as a biomarker of a long-term metal accumulation resulting from environmental or occupational exposure. Our study was conducted on bone samples harvested from inhabitants of the Upper Silesia region during hip replacement surgery. Femoral heads removed during surgery were sectioned into slices and further subdivided into samples comprising articular cartilage, cortical bone, and trabecular bone. Concentrations of 12 trace elements were measured with an atomic absorption spectrophotometry method. We found significant correlation between concentrations of these metal elements in the samples of cortical bone. This is determined not only by the physiological functions of these metals in hydroxyapatite, but also by the specific mineral structure of the bone tissue.

The concentrations of 12 elements (Ni, Ma, Cr, Cd, Pb, Cu, Fe, Zn, Mg, K, Na, Ca) were determined in cross-sections of human femur heads. The highest concentrations of these elements was found in the cortical bone, and the lowest concentrations occurred in the trabecular bone, with exception of the E cross-section, in which the lowest values were found in articular cartilage. The average concentrations of Na, Ca, K, and Mg were highest in cortical bone and lowest in articular cartilage. Pb was found in higher concentrations in articular cartilage and lowest in trabecular bone, with exception of cross-sections A and E. The Fe contents in the cortical parts were highest in cross-sections A, B, and D. Cu was highest in cross-sections B, C, and D of articular cartilage. These results show that the contents of the selected metals in the femur head varied considerably. As expected, the largest concentrations were found in the outmost part of cross-section E and the lowest in its innermost one, possibly related to mechanical stress.

Energy from biogas is widely available, inexpensive, and often contributes to waste management, making it one of the most promising renewable energy sources. The main factors influencing this process’ efficiency include the substrates’ chemical composition, temperature, and digester load. This paper presents the possibilities offered by a biogas plant built at a farm specialising in dairy cows. The dependence of the power generated in the micro biogas plant on its technical parameters was analysed in detail. Studies carried out by the authors in an agricultural microgas plant (with an electrical output of 40 kW) have shown that they are designed to maintain continuous energy production, despite changing process parameters such as digester mass level, biogas height, temperature or slurry flow into the digester. However, from the point of view of the amount of electricity generated, changes would have to be made to the design of the biogas plant. Firstly, a more powerful generator would have to be installed to cover the electricity requirements of the equipment installed in the biogas plant so that power close to the rated capacity of the biogas plant is still sent to the grid. Secondly, replacing the two existing agitators of the digestion mass (9 kW each) with more agitators of lower power (e.g., four agitators of 4.5 kW each) would be necessary. These should be programmed so that one of the agitators operates at any given time (the operating time of a given agitator should depend on the composition of the digestate).

We define a formalism of a self-consistent description of the ground state of a weakly interacting Bose system, accounting for higher order terms in expansion of energy in the diluteness parameter. The approach is designed to be applied to a Bose–Bose mixture in a regime of weak collapse where quantum fluctuations lead to stabilization of the system and formation of quantum liquid droplets. The approach is based on the generalized Gross–Pitaevskii equation accounting for quantum depletion and renormalized anomalous density terms. The equation is self-consistently coupled to modified Bogoliubov equations. We derive well defined procedure to calculate the zero temperature renormalized anomalous density—the quantity needed to correctly describe the formation of quantum liquid droplet. We pay particular attention to the case of droplets harmonically confined in some directions. The method allows to determine the Lee–Huang–Yang-type contribution to the chemical potential of inhomogeneous droplets when the local density approximation fails.

The article presents a measurement system that captures two components of a motor vehicle’s magnetic profile, which are associated with the real and imaginary part of the impedance of a narrow inductive loop sensor. The proposed algorithm utilizes both components of the impedance magnetic profile to detect vehicle axles, including lifted axles. Accuracies of no less than 71.8% were achieved for vehicles travelling with a lifted axle, and no less than 98.8% for other vehicles. The axle detection accuracy was determined during a series of experiments carried out under normal traffic conditions, using profile analysis, video footage and reference signals from an axle load detector on a total of 4000 vehicles.

The article presents the Parrot AI smart system, which supports physicians specialising in internal medicine and pediatrics. The solution is designed to automate time-consuming administrative processes and assist physicians in clinical decision-making. The main purpose of the system is to relieve medical staff of administrative tasks, such as manually filling out medical records, which translates into increased work efficiency and more time to focus on direct contact with patients. Parrot AI uses advanced natural language processing methods and generative language models to enable automated semantic analysis of medical interviews. Based on this, the system generates the content necessary to complete the electronic medical records and assists the physician by suggesting preliminary diagnoses and treatment options. Interaction with the patient can take place both at the initial medical interview stage (via chatbot or voicebot) and during a personal appointment at the clinic. Functional tests have demonstrated that the solution is highly effective. All tested components of the system achieved results well above the 80% effectiveness threshold, confirming the validity of further implementing the system into everyday clinical practice. Parrot AI has the potential not only to streamline physicians’ work, but also to improve the quality and consistency of medical records.