This review evaluates the therapeutic effects of polysaccharides derived from mushroom species that have medicinal and edible properties. The fungal polysaccharides were recently studied, focusing on their modulation of the gut microbiota and their impact on various diseases. The study covers both clinical and preclinical studies, detailing the results and highlighting the significant influence of these polysaccharides on gut microbiota modulation. It discusses the potential health benefits derived from incorporating these polysaccharides into the diet for managing chronic diseases such as diabetes, neurodegenerative disorders, and cancer. Furthermore, the review emphasizes the interaction between fungal polysaccharides and the gut microbiota, underscoring their role in modulating the gut microbial community. It presents a systematic analysis of the findings, demonstrating the substantial impact of fungal polysaccharides on gut microbiota composition and function, which may contribute to their therapeutic effects in various chronic conditions. We conclude that the modulation of the gut microbiota by these polysaccharides may play a crucial role in mediating their therapeutic effects, offering a promising avenue for further research and potential applications in disease prevention and treatment. Full article

Imbalances in the redox state of the liver arise during metabolic processes, inflammatory injuries, and proliferative liver disorders. Acute exposure to intracellular reactive oxygen species (ROS) results from high levels of oxidative stress (OxS) that occur in response to hepatic ischemia/reperfusion injury (IRI) and metabolic diseases of the liver. Antisense oligonucleotides (ASOs) are an emerging class of gene expression modulators that target RNA molecules by Watson–Crick binding specificity, leading to RNA degradation, splicing modulation, and/or translation interference. Here, we review ASO inhibitor/activator strategies to modulate transcription and translation that control the expression of enzymes, transcription factors, and intracellular sensors of DNA damage. Several small-interfering RNA (siRNA) drugs with N-acetyl galactosamine moieties for the liver have recently been approved. Preclinical studies using short-activating RNAs (saRNAs), phosphorodiamidate morpholino oligomers (PMOs), and locked nucleic acids (LNAs) are at the forefront of proof-in-concept therapeutics. Future research targeting intracellular OxS-related pathways in the liver may help realize the promise of precision medicine, revolutionizing the customary approach to caring for and treating individuals afflicted with liver-specific conditions. Full article

Thiourea and its derivatives have become a significant focal point within the organic synthesis field, garnering attention for their diverse biological applications, including antibacterial, antioxidant, anticancer, anti-inflammatory, anti-Alzheimer, antituberculosis and antimalarial properties. My objective is to present a comprehensive and easily understandable analysis of recent advancements in the organic synthesis of thiourea derivatives. My focus is on the structure and activity of these derivatives over the past five years, highlighting the significant progress made in the field of organic synthesis. Additionally, I evaluate the current state of research in this area and provide an overview of the latest trends and future prospects. This review will prove to be beneficial for researchers, academics and industry professionals involved in drug development and organic synthesis. Full article

Hypertension is a chronic, multifactorial disease, leading to high cardiovascular morbidity and mortality globally. Despite the advantages of pharmaceutical treatments, natural products have gained scientific interest due to their emerging phytotherapeutic properties. Chios mastic is a natural Greek product, consisting of bioactive compounds which modify microRNAs’ (small, expression-regulating molecules) expression. In this study, we investigated the antihypertensive properties of Chios mastic through the assessment of miR-21 levels. Herein, plasma samples of 57 individuals with hypertension, recruited for the purposes of the HYPER-MASTIC study, were analyzed. This was a clinical trial with Chios mastic supplements in which the patients were divided into groups receiving high and low mastic doses and placebo supplements, respectively. miR-21 was significantly upregulated in patients compared to normotensive individuals. Mean changes in miR-21 levels were statistically significant, after adjusting for sex and age, between the placebo and low-dose group and between the low- and high-dose group. Post-intervention miR-21 levels were positively associated with night-time systolic blood pressure, pulse pressure, and central systolic mean arterial pressure and negatively associated with night-time pulse wave velocity in the low-dose group. Our findings suggest a potential implication of miR-21 in the association of Chios mastic with night-time blood pressure measurements. Full article

To broaden the applications of wood, it is necessary to prepare flame-retardant coatings that can protect wood substrates during combustion. In this study, a bio-based, intumescent, flame-retardant phytic acid–melamine polyelectrolyte (PM) was prepared using phosphorus-rich biomass phytic acid and nitrogen-rich melamine as raw materials through an ion crosslinking reaction. Subsequently, a series of bio-based, flame-retardant wood coatings were prepared by optimizing the structure of urea–formaldehyde resin with the addition of melamine, sodium lignosulfonate, and PM as a flame-retardant curing agent. Woods coated with PM-containing coatings displayed significantly improved flame-retardant performances in comparison to uncoated woods. For PM-cured woods, the measured values of total heat release and total smoke production were 91.51% and 57.80% lower, respectively, compared with those of uncoated wood. Furthermore, the fire growth index decreased by 97.32%, indicating a lower fire hazard. This increase in flame retardancy and smoke suppression performance is due to the dense expanded carbon layer formed during the combustion of the coating, which isolates oxygen and heat. In addition, the mechanical properties of the flame-retardant coatings cured with PM are similar to those cured with a commercial curing agent, NH₄Cl. In addition, the prepared flame-retardant coating can also stain the wood. This study proves the excellent flame-retarding and curing effect of ammonium phytate in urea–formaldehyde resin coatings and provides a new approach for the application of bio-based flame retardants in wood coatings. Full article

Background: Careful macroscopic assessment of surgical scars is needed to avoid routine scar resection during cytoreductive surgery (CRS) for peritoneal metastases (PM). This study aimed to analyze the correlation between macroscopically suspected and microscopically confirmed scar metastases (SMs), and to analyze the prognostic impact of not undergoing routine scar resection. Method: All patients with previous surgery, treated with CRS and hyperthermic intraperitoneal chemotherapy, for colorectal PM or pseudomyxoma peritonei (PMP), at Uppsala University Hospital in 2013–2021, were included. Macroscopic SMs in surgical reports were compared with histopathological analyses. Results: In total, 227 patients were included. Among colorectal PM patients (n = 156), SM was macroscopically suspected in 41 (26%) patients, and 63 (40%) underwent scar resection. SM was confirmed in 19 (30%). Among patients with macroscopic suspicion, 45% had confirmed SM (positive predictive value, PPV). A total of 1 of 23 (4%) patients with no macroscopic suspicion had SM (negative predictive value, NPV = 96%). Among the PMP patients (n = 71), SM was macroscopically suspected in 13 (18%), and 28 (39%) underwent scar resection, of whom 12 (43%) had SM. The PPV was 77%. Occult SM was found in 1 of 14 (NPV = 93%). Not undergoing routine scar resection did not affect recurrence-free survival (RFS, p = 0.2) or overall survival (OS, p = 0.1) in colorectal PM patients or PMP patients (RFS p = 0.7, OS p = 0.7). Conclusion: Occult SM is uncommon and scar resection does not affect RFS or OS. Therefore, macroscopically benign-appearing scars can be left without resection, though resection should be performed upon suspicion or uncertainty. Full article

From 2001 to 2020, three typhoons with similar moving paths and intensities were found to trigger markedly different cooling off northeastern Taiwan. They were typhoons Utor (2001), Nuri (2008), and Hagupit (2008), which led to maximum sea surface temperature (SST) cooling temperatures of 8.8, 2.7, and 1.4 °C, respectively. The drastic cooling discrepancy implies that the existing understanding of the key mechanism leading to the cooling off northeastern Taiwan could be insufficient. For further exploring the key reason(s) contributing to the marked discrepancy, a regional oceanic modeling system (ROMS) was used to reconstruct the background oceanic environment corresponding to three typhoon passages. Results show that the wide radius of maximum winds of typhoon Utor contributes to the strongest SST cooling by enhancing the Kuroshio intrusion (KI) onto the shelf northeast of Taiwan. Heat budget diagnostics explain why including tidal forcing can substantially promote SST cooling. The process was associated mainly with a stronger vertical advection tied to the influence of de-stratification by tidal mixing. Finally, warmer Taiwan Strait currents, driven by wind forcing the typhoons to pass zonally through the north South China Sea, intruded clockwise into the Longdong coast and accelerated the recovery of sea surface cooling around Longdong. Full article

Negative temperature coefficient (NTC) chip thermistors were thermally coupled to form a novel device (TCCT) aimed for application in microelectronics. It consists of two NTC chip thermistors Th₁ and Th₂, which are small in size (0603) and power (1/10 W). They are in thermal junction, but concurrently they are electrically isolated. The first thermistor Th₁ generates heat as a self-heating component at a constant supply voltage U (input thermistor), while the second thermistor Th₂ receives heat as a passive component (output thermistor). The temperature dependence R(T) of NTC chip thermistors was measured in the climatic test chamber, and the exponential factor B_10/30 of thermistor resistance was determined. After that, a self–heating current I₁ of the input thermistor was measured vs. supply voltage U and ambient temperature T_a as a parameter. Input resistance R₁ was determined as a ratio of U and I₁ while output thermistor resistance R₂ was measured by a multimeter concurrently with the current I₁. Temperatures T₁ and T₂ of both thermistors were determined using the Steinhart–Hart equation. Heat transfer, thermal response, stability, and inaccuracy were analyzed. The application of thermally coupled NTC chip thermistors is expected in microelectronics for the input to output electrical decoupling/thermal coupling of slow changeable signals. Full article

In order to effectively protect and verify the copyright information of multimedia digital works, this paper proposes a zero-watermarking algorithm based on carrier image feature point descriptors. The constructed feature matrix of this algorithm consists of two parts: the feature descriptor vector calculated from scale-invariant feature reconstruction transform (SIFRT) and the multi-radius local binary pattern (MrLBP) descriptor vector. The algorithm performs a standardization, feature decomposition, and redundancy reduction on the traditional keypoint descriptor matrix, combines it with the texture feature matrix, and achieves the dimensional matching of copyright information. The advantage of this algorithm lies in its non-modification of the original data. Compared to computing global features, the local features computed from a subset of key points reduce the amount of attack interference introduced during copyright verification, thereby reducing the number of erroneous pixel values that are introduced. The algorithm introduces a timestamp mechanism when uploading the generated zero-watermarking image to a third-party copyright center, preventing subsequent tampering. Experimental data analysis demonstrates that the algorithm exhibits good discriminability, security, and robustness. Full article

The successful detection of key components within satellites is a crucial prerequisite for executing on-orbit capture missions. Due to the inherent data-driven functionality, deep learning-based component detection algorithms rely heavily on the scale and quality of the dataset for their accuracy and robustness. Nevertheless, existing satellite image datasets exhibit several deficiencies, such as the lack of satellite motion states, extreme illuminations, or occlusion of critical components, which severely hinder the performance of detection algorithms. In this work, we bridge the gap via the release of a novel dataset tailored for the detection of key components of satellites. Unlike the conventional datasets composed of synthetic images, the proposed Typical Components of Satellites (TYCOS) dataset comprises authentic photos captured in a simulated space environment. It encompasses three types of satellite, three types of key components, three types of illumination, and three types of motion state. Meanwhile, scenarios with occlusion in front of the satellite are also taken into consideration. On the basis of TYCOS, several state-of-the-art detection methods are employed in rigorous experiments followed by a comprehensive analysis, which further enhances the development of space scene perception and satellite safety. Full article

Modern microtechnology methods are widely used to create neural networks on a chip with a connection architecture demonstrating properties of modularity and hierarchy similar to brain networks. Such in vitro networks serve as a valuable model for studying the interplay of functional architecture within modules, their activity, and the effectiveness of inter-module interaction. In this study, we use a two-chamber microfluidic platform to investigate functional connectivity and global activity in hierarchically connected modular neural networks. We found that the strength of functional connections within the module and the profile of network spontaneous activity determine the effectiveness of inter-modular interaction and integration activity in the network. The direction of intermodular activity propagation configures the different densities of inhibitory synapses in the network. The developed microfluidic platform holds the potential to explore function-structure relationships and efficient information processing in two- or multilayer neural networks, in both healthy and pathological states. Full article

Skeletal muscle atrophy (SMA) is caused by a rise in muscle breakdown and a decline in protein synthesis, with a consequent loss of mass and function. This study characterized the effect of an amino acid mixture (AA) in models of SMA, focusing on mitochondria. C57/Bl6 mice underwent immobilization of one hindlimb (I) or cardiotoxin-induced muscle injury (C) and were compared with controls (CTRL). Mice were then administered AA in drinking water for 10 days and compared to a placebo group. With respect to CTRL, I and C reduced running time and distance, along with grip strength; however, the reduction was prevented by AA. Tibialis anterior (TA) muscles were used for histology and mitochondria isolation. I and C resulted in TA atrophy, characterized by a reduction in both wet weight and TA/body weight ratio and smaller myofibers than those of CTRL. Interestingly, these alterations were lightly observed in mice treated with AA. The mitochondrial yield from the TA of I and C mice was lower than that of CTRL but not in AA-treated mice. AA also preserved mitochondrial bioenergetics in TA muscle from I and C mice. To conclude, this study demonstrates that AA prevents loss of muscle mass and function in SMA by protecting mitochondria. Full article

Beam position uncertainties along the beam trajectory arise from the accelerator, beamline, and scanning magnets (SMs). They can be monitored in real time, e.g., through strip ionization chambers (ICs), and treatments can be paused if needed. Delivery is more reliable and accurate if the beam position is projected from monitored nozzle parameters to the isocenter, allowing for accurate online corrections to be performed. Beam position projection algorithms are also used in post-delivery log file analyses. In this paper, we investigate the four potential algorithms that can be applied to all pencil beam scanning (PBS) nozzles. For some combinations of nozzle configurations and algorithms, however, the projection uses beam properties determined offline (e.g., through beam tuning or technical commissioning). The best algorithm minimizes either the total uncertainty (i.e., offline and online) or the total offline uncertainty in the projection. Four beam position algorithms are analyzed (A1–A4). Two nozzle lengths are used as examples: a large nozzle (1.5 m length) and a small nozzle (0.4 m length). Three nozzle configurations are considered: IC after SM, IC before SM, and ICs on both sides. Default uncertainties are selected for ion chamber measurements, nozzle entrance beam position and angle, and scanning magnet angle. The results for other uncertainties can be determined by scaling these results or repeating the error propagation. We show the propagation of errors from two locations and the SM angle to the isocenter for all the algorithms. The best choice of algorithm depends on the nozzle length and is A1 and A3 for the large and small nozzles, respectively. If the total offline uncertainty is to be minimized (a better choice if the offline uncertainty is not stable), the best choice of algorithm changes to A1 for the small nozzle for some hardware configurations. Reducing the nozzle length can help to reduce the gantry size and make proton therapy more accessible. This work is important for designing smaller nozzles and, consequently, smaller gantries. This work is also important for log file analyses. Full article

Background: Obesity is a chronic inflammatory disorder that increases the risk of cardiovascular diseases (CVDs). Given the high CVD mortality rate among individuals with obesity, early screening should be considered. Plasminogen activator inhibitor (PAI-1), a cytokine that links obesity and CVDs, represents a promising biomarker. However, PAI-1 is not part of the clinical routine due to its high cost. Therefore, it is necessary to find good predictors that would allow an indirect assessment of PAI-1. Methods: This study enrolled 47 women with severe obesity (SO). The obtained anthropometric measurements included weight, height, neck (NC), waist (WC), and hip circumference (HC). Blood samples were collected to analyse glucose and lipid profiles, C-reactive protein, liver markers, adiponectin, and PAI-1 (determined by ELISA immunoassay). Homeostasis model assessment-adiponectin (HOMA-AD), homeostasis model assessment of insulin resistance (HOMA-IR), quantitative insulin sensitivity check index (QUICKI), triglyceride–glucose index (TyG), and atherogenic index of plasma (AIP) were calculated. The women were grouped according to PAI-1 levels. The data were analysed using IBM SPSS Statistics, version 21. The significance level for the analysis was set at 5%. Results: Women with SO who have higher levels of PAI-1 have lower values of high-density lipoprotein cholesterol (HDL) (p = 0.037) and QUICKI (0.020) and higher values of HOMA-AD (0.046) and HOMA-IR (0.037). HOMA-IR was demonstrated to be a good predictor of PAI-1 in this sample (B = 0.2791; p = 0.017). Conclusions: HOMA-IR could be used as a predictor of PAI-1 levels, pointing out the relevance of assessing glycaemic parameters for the prevention of CVDs in women with SO. Full article

Formative assessment (FA) provides lecturers and learners with information about the quality and development of different tasks. Formative feedback becomes an essential element that increases the quality of these tasks, guides learners in the process, and motivates them to be actively involved, acquiring the learning objectives and skills. A digital learning ecosystems (DLE) offers the possibility of a quality, effective, and sustainable education, enabling people to carry on with their training from anywhere, at any time, and through personal pathways. In this framework, we present a descriptive study with a qualitative approach to explore the views of 91 participants regarding the process of FA in second language acquisition (SLA) in a DLE. According to the results, the DLE provides the necessary tools to favour FA, and to obtain valuable data on the learners’ academic achievements in SLA. The learners take an active role in learning English and competence development such as reading, writing, and listening, and other skills such as digital competence, communication, problem solving, empathy, or creativity. The data obtained help lecturers to identify learners’ difficulties in SLA and address them with different didactic strategies. It can be concluded that FA plays a relevant role in SLA in a DLE. Full article

This research paper presents a novel approach to identifying biomarkers that can be used to prognosticate patients with triple-negative breast cancer (TNBC) eligible for neoadjuvant therapy. The study utilized survival and RNA sequencing data from a cohort of TNBC patients and identified 276 genes whose expression was related to survival in such patients. The gene expression data were then used to classify patients into two major groups based on the presence or absence of Wingless/Integrated-pathway (Wnt-pathway) and mesenchymal (Mes) markers (Wnt/Mes). Patients with a low expression of Wnt/Mes-related genes had a favorable outcome, with no deaths observed during follow-up, while patients with a high expression of Wnt/Mes genes had a higher mortality rate of 50% within 19 months. The identified gene list could be validated and potentially used to shape treatment options for TNBC patients eligible for neoadjuvant therapy providing valuable insights into the development of more effective treatments for TNBC. Our data also showed significant variation in gene expression profiles before and after chemotherapy, with most tumors switching to a more mesenchymal/stem cell-like profile. To verify this observation, we performed an in silico analysis to classify breast cancer tumors in Prediction Analysis of Microarray 50 (PAM50) molecular classes before treatment and after treatment using gene expression data. Our findings demonstrate that following drug intervention and metastasis, certain tumors undergo a transition to alternative subtypes, resulting in diminished therapeutic efficacy. This underscores the necessity for reevaluation of patients who have experienced relapse or metastasis post-chemotherapy, with a focus on molecular subtyping. Tailoring treatment strategies based on these refined subtypes is imperative to optimize therapeutic outcomes for affected individuals. Full article

Background and Objectives: We aimed to develop a predictive model for the outcome of bruxism treatments using ultrasonography (USG)-based machine learning (ML) techniques. This study is a quantitative research study (predictive modeling study) in which different treatment methods applied to bruxism patients are evaluated through artificial intelligence. Materials and Methods: The study population comprised 102 participants with bruxism in three treatment groups: Manual therapy, Manual therapy and Kinesio Tape or Botulinum Toxin-A injection. USG imaging was performed on the masseter muscle to calculate muscle thickness, and pain thresholds were evaluated using an algometer. A radiomics platform was utilized to handle imaging and clinical data, as well as to perform a subsequent radiomics statistical analysis. Results: The area under the curve (AUC) values of all machine learning methods ranged from 0.772 to 0.986 for the training data and from 0.394 to 0.848 for the test data. The Support Vector Machine (SVM) led to excellent discrimination between bruxism and normal patients from USG images. Radiomics characteristics in pre-treatment ultrasound scans of patients, showing coarse and nonuniform muscles, were associated with a greater chance of less effective pain reduction outcomes. Conclusions: This study has introduced a machine learning model using SVM analysis on ultrasound (USG) images for bruxism patients, which can detect masseter muscle changes on USG. Support Vector Machine regression analysis showed the combined ML models can also predict the outcome of the pain reduction. Full article

Cardiovascular diseases (CVDs) are highly prevalent, sudden onset, and relatively fatal, posing a significant public health burden. Long-term dynamic electrocardiography, which can continuously record the long-term dynamic ECG activities of individuals in their daily lives, has high research value. However, ECG signals are weak and highly susceptible to external interference, which may lead to false alarms and misdiagnosis, affecting the diagnostic efficiency and the utilization rate of healthcare resources, so research on the quality of dynamic ECG signals is extremely necessary. Aimed at the above problems, this paper proposes a dynamic ECG signal quality assessment method based on CNN and LSTM that divides the signal into three quality categories: the signal of the Q1 category has a lower noise level, which can be used for reliable diagnosis of arrhythmia, etc.; the signal of the Q2 category has a higher noise level, but it still contains information that can be used for heart rate calculation, HRV analysis, etc.; and the signal of the Q3 category has a higher noise level that can interfere with the diagnosis of cardiovascular disease and should be discarded or labeled. In this paper, we use the widely recognized MIT-BIH database, based on which the model is applied to realistically collect exercise experimental data to assess the performance of the model in dealing with real-world situations. The model achieves an accuracy of 98.65% on the test set, a macro-averaged F1 score of 98.5%, and a high F1 score of 99.71% for the prediction of Q3 category signals, which shows that the model has good accuracy and generalization performance. Full article

Climate change necessitates urgent actions to mitigate carbon dioxide (CO₂) emissions from fossil fuel-based energy generation. Among various strategies, the deployment of carbon capture and storage (CCS) solutions is critical for reducing emissions from point sources such as power plants and heavy industries. In this context, cryogenic carbon capture (CCC) via desublimation has emerged as a promising technology. While CCC offers high separation efficiency, minimal downstream compression work, and integration potential with existing industrial processes, challenges such as low operating temperatures and equipment costs persist. Ongoing research aims to address these hurdles in order to optimize the desublimation processes for widespread implementation. This review consolidates diverse works from the literature, providing insights into the strengths and limitations of CCC technology, including the latest pilot plant scale demonstrations. The transformative potential of CCC is first assessed on a theoretical basis, such as thermodynamic aspects and mass transfer phenomena. Then, recent advancements in the proposed process configurations are critically assessed and compared through key performance indicators. Furthermore, future research directions for this technology are clearly highlighted. Full article

The importance of sleep for healthy brain function is widely acknowledged. However, it remains unclear how the internal generation of dreams might facilitate cognitive processes. In this perspective, we review a computational approach inspired by artificial intelligence that proposes a framework for how dreams occurring during rapid-eye-movement (REM) sleep can contribute to learning and creativity. In this framework, REM dreams are characterized by an adversarial process that, against the dream reality, tells a discriminator network to classify the internally created sensory activity as real. Such an adversarial dreaming process is shown to facilitate the emergence of real-world semantic representations in higher cortical areas. We further discuss the potential contributions of adversarial dreaming beyond learning, such as balancing fantastic and realistic dream elements and facilitating the occurrence of creative insights. We characterize non-REM (NREM) dreams, where a single hippocampal memory is replayed at a time, as serving the complementary role of improving the robustness of cortical representations to environmental perturbations. We finally explain how subjects can become aware of the adversarial REM dreams, but less of the NREM dreams, and how content- and state-awareness in wake, dream, and lucid dreaming may appear. Full article

This ABIGENE pharmacokinetic (PK) study sought mainly to characterize the unchanged drug PK during long-term abiraterone acetate (AA) administration in advanced prostate cancer patients (81 patients). It was observed that individual AA concentrations remained constant over treatment time, with no noticeable changes during repeated long-term drug administration for up to 120 days. There was no correlation between AA concentrations and survival outcomes. However, a significant association between higher AA concentrations and better clinical benefit was observed (p = 0.041). The safety data did not correlate with the AA PK data. A significant positive correlation (r = 0.40, p < 0.001) was observed between mean AA concentration and patient age: the older the patient, the higher the AA concentration. Patient age was found to impact steady-state AA concentration: the older the patient, the higher the mean AA concentration. Altogether, these data may help to guide future research and clinical trials in order to maximize the benefits of AA metastatic castration-resistant prostate cancer patients. Full article

With the development of e-commerce in Poland, consumer awareness has evolved. Buyers not only compared prices and assessed the quality of products but also began to take into account the impact of their purchases on the environment, which was previously an overlooked aspect. This growing environmental awareness is part of a broader effort to address environmental issues and support practices that promote sustainability. Currently, there is a noticeable increase in ecological awareness among society, government bodies, and the scientific community, strengthening human interaction with the natural environment. The aim of this study was to examine changes in ecological awareness and ecological attitudes among Polish e-consumers over ten years and their impact on online shopping behavior. This study explored how the ecological attitudes of Polish e-consumers have evolved over the last decade and what impact these changes in environmental attitudes have had on the online purchasing behavior of these consumers. Longitudinal studies were used to enable the analysis of changes over time. The research technique was based on repeated measurements of the same phenomena and features, carried out on diverse research samples from the same population, using the same methods and tools. This study was conducted twice, in 2010 and 2020, on a sample of 1150 people in each of these years. This research employed an online survey questionnaire, which included scales for assessing the personality traits of e-consumers and the determinants of online shopping. A significant change was found in e-consumers’ attitudes towards the natural environment and their purchasing preferences. This change has had a clear impact on purchasing behavior, including an increase in the importance of convenience, access to detailed product information, and a wide range of products offered, reflecting more conscious and convenience-oriented consumer behavior. Full article