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Artificial intelligence (AI) is emerging as a prominent technological advancement. It is the act of replicating human intelligence for many purposes. In contrast to conventional methodologies, artificial intelligence (AI) is undergoing tremendous advancements. The present state of artificial intelligence (AI) technology enables them to effectively address numerous intricate difficulties with proficiency comparable to a human's. The significance of advancements in AI is particularly evident in machine learning, where the techniques and algorithms are effectively applied to address many problems, including those in nanotechnology. In contemporary nanotechnology, it is crucial to expedite the search for the most favorable synthesis parameters while developing novel nanomaterials. The convergence of machine learning and nanotechnology necessitates a comprehensive examination of existing data on the application of artificial intelligence (AI) in addressing challenges in the nanomaterials science field. This review should encompass various stages, including computer design, chemical synthesis, and diagnostics of the resultant nanomaterials. Significant emphasis is placed on employing machine-learning technologies to investigate the thermal and dynamic characteristics of nanofluids, the sorption processes of nanocomposites, the catalytic activity of nanoparticles, and the toxicity of nanoparticles. Additionally, these technologies are utilized to address nanosensor issues and process experimental data acquired during the diagnostics of different nanomaterial properties.

The effects of suburbanization can be examined from several aspects, but beyond the individual decisions that initiated it, the real estate market aspects, or the transformation of land use, the effects on local communities and their reactions are rarely highlighted in professional circles. In our work within the agglomeration of Bratislava, the Slovak capital, we researched individual and collective opinions on suburbanization, as well as the questions and potential conflict situations arising among members of the “host community.” A striking element of the study area is that migration also means a change in the linguistic environment, as the newcomers often arrive from a predominantly Slovakspeaking city to an area mostly inhabited by the Hungarian minority. This adds additional dimensions to suburbanization and the responses it generates. Experiences show that the municipalities affected by the process use independent, yet in certain respects similar, strategies to manage it, and as part of these strategies, the ethnic factor also appears prominently in some topics.

Abstract We present the Feynman rules for leading-twist gauge-invariant quark and gluon operators with an arbitrary number of total derivatives and applicable to any order in perturbation theory. This generalizes previous results and constitutes a necessary ingredient in the computation of the matrix elements of the corresponding operators. The results are written in a form appropriate for implementation in a computer algebra system. To illustrate the latter we provide implementations in Mathematica and FORM, which are made available at https://github.com/vtsam/NKLO . Graphical abstract

Abstract Juveniles of three cyprinids with various diets and habitat preferences were collected from the Szamos River (Hungary) during a period of pollution in November 2013: the herbivorous, benthic nase (Chondrostoma nasus), the benthivorous, benthic barbel (Barbus barbus), and the omnivorous, pelagic chub (Squalius cephalus). Our study aimed to assess the accumulation of these elements across species with varying diets and habitat preferences, as well as their potential role in biomonitoring efforts. The Ca, K, Mg, Na, Cd, Cr, Cu, Fe, Mn, Pb, Sr, and Zn concentration was analyzed in muscle, gills, and liver using MP-AES. The muscle and gill concentrations of Cr, Cu, Fe, and Zn increased with trophic level. At the same time, several differences were found among the trace element patterns related to habitat preferences. The trace elements, including Cd, Pb, and Zn, which exceeded threshold concentrations in the water, exhibited higher accumulations mainly in the muscle and gills of the pelagic chub. Furthermore, the elevated concentrations of trace elements in sediments (Cr, Cu, Mn) demonstrated higher accumulation in the benthic nase and barbel. Our findings show habitat preference as a key factor in juvenile bioindicator capability, advocating for the simultaneous use of pelagic and benthic juveniles to assess water and sediment pollution status.

In humans, interactions with objects are often embedded in communicative exchanges. Objects offer unique affordances to explore, carry functions and hold cultural relevance, which can shape children’s interactions and communication. Research indicates that the use of artificial objects, such as certain toys, helps promote pre-linguistic communication, consequently impacting language development. Given that chimpanzees use objects extensively compared to other great apes, and considering the differences between chimpanzees and bonobos in intrinsic motivation for tool use and the extended developmental period during which they learn to use objects, it is reasonable to expect that objects may influence chimpanzees’ communication. Here, we examined interactions of 31 immature sanctuary-living chimpanzees with non-novel artificial and natural objects and tested their vocal and facial expressions, applying methods previously designed for children. Our results showed an increase in these expressions associated with artificial objects. These findings provide the first empirical evidence that chimpanzee communicative expressions may be influenced by inherent properties of objects, potentially promoting varied communication, comparable to the impact distinctive objects have on pre-linguistic children. By exploring this connection between object-centric interactions and communication, this study reveals deep phylogenetic roots where objects may have shaped great ape communication and possibly evolutionary foundations of language.

The reemergence of primitive reflexes (PRs) in older age is related to cognitive impairment. Currently, there are no means to prevent or slow their reappearance, but research evidence exists for their control in children. Therefore, this experiment investigated whether a 16-week special sensorimotor exercise program could benefit older adults and whether the intervention-induced changes (if any) may be associated with various indices of mental health. Of 115 adults over 60, 95 completed the study (mean age = 76.37 ± SD = 7.04 years, 22 % men). The experimental group (n = 38) showed an almost threefold decline in PRs compared to controls. In contrast, the control group (n = 57) exhibited a nearly threefold increase in PRs compared to the intervention group. Cognitive function increased in the experimental but not in the control group. Changes in PRs over the 16-week intervention were positively related to negative mental health indices (hopelessness and perceived stress) and negatively related to well-being. These findings suggest that the here-presented mild sensorimotor exercises could affect older adults' reemerging PRs and that changes in PRs are associated with mental health benefits. These results may open new research avenues toward preventing cognitive and psychological decline in older adults.

Jelen tanulmány azt vizsgálja, hogy mi lett a sorsa a mohácsi csatavesztést követően a „középkori magyar zsinati táj” normaszövegének, a késő középkori esztergomi szinodális könyvnek. Ezeket a határozatokat a középkori Magyar Királyságban csaknem másfél évszázadig használták a hazai egyházmegyék. Milyen tünetei voltak a középkori szöveg elavulásának? Hogyan nyúltak hozzá a magyar főpapok e szöveghez a nagyszombati zsinat (1560) előtt? Azonnal elfeledték? Módosították? Hogyan állt szolgálatába a technikai újítás, azaz a nyomtatás ennek a zsinati tevékenységnek? Az 1526 és 1560 közötti, átmenetinek tekinthető korszak három történeti forrásának vizsgálatával a fenti kérdésekre keresem a választ. E három forrás a Váraljai Szaniszló szepesi prépost által 1545-ben tartott zsinat ordójának egy kora újkori másolata, a Bornemisza Pál nyitrai adminisztrátor által az 1494-es nyitrai egyházmegyei zsinati határozatok mellékleteként 1560-ban kinyomtatott annotációk, valamint a nagyszombati zsinatot megelőző 1559-es pozsonyi püspökgyűlés jegyzőkönyve. E források mindegyikre nem csak az átmeneti korszak zsinati tevékenységének értékelése szempontjából tartalmaz értékes adatokat, hanem éppúgy a középkori egyház korábbi történetét kutatók számára is számos, megfontolás tárgyát képező kérdést vet fel.

Abstract Background Interstitial lung diseases (ILD) comprise a heterogeneous group of mainly chronic lung diseases with different disease trajectories. Progression (PF-ILD) occurs in up to 50% of patients and is associated with increased mortality. Methods The EXCITING-ILD (Exploring Clinical and Epidemiological Characteristics of Interstitial Lung Diseases) registry was analysed for disease trajectories in different ILD. The course of disease was classified as significant (absolute forced vital capacity FVC decline > 10%) or moderate progression (FVC decline 5–10%), stable disease (FVC decline or increase

Summary: Background: Mucositis is a common and highly impactful side effect of conventional and emerging cancer therapy and thus the subject of intense investigation. Although common practice, mucositis assessment is heterogeneously adopted and poorly guided, impacting evidence synthesis and translation. The Multinational Association of Supportive Care in Cancer (MASCC) Mucositis Study Group (MSG) therefore aimed to establish expert recommendations for how existing mucositis assessment tools should be used, in clinical care and trials contexts, to improve the consistency of mucositis assessment. Methods: This study was conducted over two stages (January 2022–July 2023). The first phase involved a survey to MASCC-MSG members (January 2022–May 2022), capturing current practices, challenges and preferences. These then informed the second phase, in which a set of initial recommendations were prepared and refined using the Delphi method (February 2023–May 2023). Consensus was defined as agreement on a parameter by >80% of respondents. Findings: Seventy-two MASCC-MSG members completed the first phase of the study (37 females, 34 males, mainly oral care specialists). High variability was noted in the use of mucositis assessment tools, with a high reliance on clinician assessment compared to patient reported outcome measures (PROMs, 47% vs 3%, 37% used a combination). The World Health Organization (WHO) and Common Terminology Criteria for Adverse Events (CTCAE) scales were most commonly used to assess mucositis across multiple settings. Initial recommendations were reviewed by experienced MSG members and following two rounds of Delphi survey consensus was achieved in 91 of 100 recommendations. For example, in patients receiving chemotherapy, the recommended tool for clinician assessment in clinical practice is WHO for oral mucositis (89.5% consensus), and WHO or CTCAE for gastrointestinal mucositis (85.7% consensus). The recommended PROM in clinical trials is OMD/WQ for oral mucositis (93.3% consensus), and PRO-CTCAE for gastrointestinal mucositis (83.3% consensus). Interpretation: These new recommendations provide much needed guidance on mucositis assessment and may be applied in both clinical practice and research to streamline comparison and synthesis of global data sets, thus accelerating translation of new knowledge into clinical practice. Funding: No funding was received.

Abstract Background Interstitial lung diseases (ILD) comprise a heterogeneous group of mainly chronic lung diseases with more than 200 entities and relevant differences in disease course and prognosis. Little data is available on hospitalisation patterns in ILD. Methods The EXCITING-ILD (Exploring Clinical and Epidemiological Characteristics of Interstitial Lung Diseases) registry was analysed for hospitalisations. Reasons for hospitalisation were classified as all cause, ILD-related and respiratory hospitalisations, and patients were analysed for frequency of hospitalisations, time to first non-elective hospitalisation, mortality and progression-free survival. Additionally, the risk for hospitalisation according to GAP index and ILD subtype was calculated by Cox proportional-hazard models as well as influencing factors on prediction of hospitalisation by logistic regression with forward selection. Results In total, 601 patients were included. 1210 hospitalisations were recorded during the 6 months prior to registry inclusion until the last study visit. 800 (66.1%) were ILD-related, 59.3% of admissions were registered in the first year after inclusion. Mortality was associated with all cause, ILD-related and respiratory-related hospitalisation. Risk factors for hospitalisation were advanced disease (GAP Index stages II and III) and CTD (connective tissue disease)-ILDs. All cause hospitalisations were associated with pulmonary hypertension (OR 2.53, p = 0.005). ILD-related hospitalisations were associated with unclassifiable ILD and concomitant emphysema (OR = 2.133, p = 0.001) as well as with other granulomatous ILDs and a positive smoking status (OR = 3.082, p = 0.005). Conclusion Our results represent a crucial contribution in understanding predisposing factors for hospitalisation in ILD and its major impact on mortality. Further studies to characterize the most vulnerable patient group as well as approaches to prevent hospitalisations are warranted.

Automatic road segmentation from three-dimensional point cloud data has gained increasing interest recently. However, it is still challenging to do this task automatically due to the wide variations of roads and complex environments, especially in non-urban areas. This research proposed a comprehensive approach for using shallow neural networks to segment non-urban road point clouds to support autonomous driving applications. The proposed approach involves converting raw point cloud data into a regular grid of cells or partial clouds. Initially, a shallow neural network based on cells’ properties (cell plane fitting error, cell average intensity, cell elevation range, and cell weighted density) was employed to extract road cells from raw point cloud data. The road cells were refined and segmented into inside-road and road border point clouds based on morphologic operations. A point-wise shallow neural network was used to extract road points from the border point clouds based on intensity and geometric features (roughness, curvature, and change rate of the normal). A precise road surface point cloud is obtained by merging the inside-road and filtered border point clouds. The method performance was evaluated for two datasets captured using a mobile laser scanner (MLS). In the first dataset, the road points were extracted at average completeness, correctness, quality, and overall accuracy of 98.40%, 99.13%, 97.56%, and 98.47%, respectively. Similarly, the method achieved high scores for the second dataset with 97.22% completeness, 99.02% correctness, 96.29% quality, and 98.71% overall accuracy. The method performance demonstrates an advancement when compared to various state-of-the-art methods and also confirms its adaptability to different road environments.

Abstract Background Mental health problems are a common phenomenon among higher-education students. How these mental health problems manifest themselves appears to differ between male and female students. While the latter group bears a greater risk of developing internalizing problems, with depression being particularly prevalent, these problems manifest themselves in male students mainly via externalizing disorders, with alcohol abuse being the most prevalent. Available cross-national research on students’ mental health during the COVID-19 pandemic, to date, mainly focused on the prevalence of depressive symptoms, thereby ignoring a possible gendered impact of the pandemic. Methods The current study used the COVID-19 International Student Well-Being Study, which collected data on students’ mental health during the first wave of the COVID-19 pandemic in 26 countries, and multilevel modeling was applied. Results It finds that, overall, female students reported more depressive feelings, and male students reported more excessive alcohol consumption. The strictness of the governmental containment measures explained a substantial amount of these gender differences in depressive feelings, but not in excessive alcohol consumption. Conclusions Our study highlights that the COVID-19 pandemic had a gendered impact on students’ mental health. Studies that ignore the gendered impact of the COVID-19 pandemic are therefore limited in scope.

Abstract Background RNA editing has been described as promoting genetic heterogeneity, leading to the development of multiple disorders, including cancer. The cytosine deaminase APOBEC3B is implicated in tumor evolution through DNA mutation, but whether it also functions as an RNA editing enzyme has not been studied. Results Here, we engineer a novel doxycycline-inducible mouse model of human APOBEC3B-overexpression to understand the impact of this enzyme in tissue homeostasis and address a potential role in C-to-U RNA editing. Elevated and sustained levels of APOBEC3B lead to rapid alteration of cellular fitness, major organ dysfunction, and ultimately lethality in mice. Importantly, RNA-sequencing of mouse tissues expressing high levels of APOBEC3B identifies frequent UCC-to-UUC RNA editing events that are not evident in the corresponding genomic DNA. Conclusions This work identifies, for the first time, a new deaminase-dependent function for APOBEC3B in RNA editing and presents a preclinical tool to help understand the emerging role of APOBEC3B as a driver of carcinogenesis.

The aim of this work was to synthesize, characterize and apply advanced antimicrobial biocompatible electrospun polymers suitable for medical implants for surgical repairs. Injuries to the musculoskeletal system often necessitate surgical repair, but current treatments can still lead to high failure rates, such as 40% for the repair of rotator cuff tears. Therefore, there is an urgent need for the development of new biocompatible materials that can effectively support the repair of damaged tissues. Additionally, infections acquired during hospitalization, particularly those caused by antibiotic-resistant bacteria, result in more fatalities than AIDS, tuberculosis, and viral hepatitis combined. This underscores the critical necessity for the advancement of antimicrobial implants with specialized coatings capable of combating Methicillin-resistant Staphylococcus aureus (MRSA) and Methicillin-sensitive Staphylococcus aureus (MSSA), two strains notoriously known for their antibiotic resistance. Therefore, we developed an antimicrobial coating incorporating nanoparticle mixtures using the sol-gel process and applied it to electrospun polycaprolactone (PCL) filaments, followed by thorough characterization by using spectroscopic (FTIR, Raman, NMR) microscopic (SEM and SEM-EDX), and tensile test. The results have shown that the integration of electro-spinning technology for yarn production, coupled with surface modification techniques, holds significant potential for creating antimicrobial materials suitable for medical implants for surgical repairs.

The incidence of diabetes, including type 2 diabetes (T2DM), is increasing sharply worldwide. To reverse this, more effective approaches in prevention and treatment are needed. In our review, we sought to summarize normal insulin action and the pathways that primarily influence the development of T2DM. Normal insulin action involves mitogenic and metabolic pathways, as both are important in normal metabolic processes, regeneration, etc. However, through excess energy, both can be hyperactive or attenuated/inactive leading to disturbances in the cellular and systemic regulation with the consequence of cellular stress and systemic inflammation. In this review, we detailed the beneficial molecular changes caused by some important components of nutrition and by exercise, which act in the same molecular targets as the developed drugs, and can revert the damaged pathways. Moreover, these induce entire networks of regulatory mechanisms and proteins to restore unbalanced homeostasis, proving their effectiveness as preventive and complementary therapies. These are the main steps for success in prevention and treatment of developed diseases to rid the body of excess energy, both from stored fats and from overnutrition, while facilitating fat burning with adequate, regular exercise in healthy people, and together with necessary drug treatment as required in patients with insulin resistance and T2DM.

The design and optimization of antimicrobial materials (polymers, biomolecules, or nanocomposites) can be significantly advanced by computational methodologies like molecular dynamics (MD), which provide insights into the interactions and stability of the antimicrobial agents within the polymer matrix, and machine learning (ML) or design of experiment (DOE), which predicts and optimizes antimicrobial efficacy and material properties. These innovations not only enhance the efficiency of developing antimicrobial polymers but also enable the creation of materials with tailored properties to meet specific application needs, ensuring safety and longevity in their usage. Therefore, this paper will present the computational methodologies employed in the synthesis and application of antimicrobial polymers, biomolecules, and nanocomposites. By leveraging advanced computational techniques such as MD, ML, or DOE, significant advancements in the design and optimization of antimicrobial materials are achieved. A comprehensive review on recent progress, together with highlights of the most relevant methodologies’ contributions to state-of-the-art materials science will be discussed, as well as future directions in the field will be foreseen. Finally, future possibilities and opportunities will be derived from the current state-of-the-art methodologies, providing perspectives on the potential evolution of polymer science and engineering of novel materials.

Guided inquiry-based learning has been shown to be a promising method for science education; however, despite its advantages it is rarely used in chemistry teaching in Hungary. One of the reasons for this is the lack of tried-and-tested inquiry-based teaching materials with detailed guides that teachers can readily use in their classrooms. As part of a four-year research project, new teaching materials were designed to foster scientific reasoning and scientific process skills in chemistry education in Hungary. From these materials, in this study, a guided inquiry-based chemistry task was tested with 9th-grade students (N = 88) who had no previous experience with the method. Before the activity, the students' mid-term grades were collected, and the Lawson Classroom Test of Scientific Reasoning (LCTSR) was administered to describe the sample. During the activity, students worked in groups (n = 21). Data were collected through content analysis of the student worksheets, classroom observations using a rubric, and student questionnaires to explore the learning paths and identify possible obstacles. Our findings support that guided inquiry learning is suitable for students who are new to the method if appropriate scaffolding is given. The data showed the phases of the inquiry cycle in which more guidance is necessary. Formulating hypotheses, recording observations, and evaluating the hypotheses based on the evidence were found to be the most critical steps in the learning process. More than half of the groups disregarded the collected evidence and accepted their original hypotheses, despite their unproven validity, suggesting that they did not understand the true nature of the scientific inquiry. Chemistry grades and the LCTSR scores could not predict reliably the students' success in solving the inquiry task. The results of the student questionnaire showed that the students enjoyed the inquiry session. They mostly found their work successful, but they overestimated the level of their inquiry skills in some cases.

Introduction The presence of eating disorders is often associated with serious physical complications, self-destruction, and suicidal tendencies. Furthermore, eating disorders may often present as a symptom of or in comorbidity with personality disorders. In order to treat eating disorder patients successfully we need a more complex and individual approach taking into consideration the specific personality dysfunctions and traits present in the patient underlying symptomatic manifestations. Recently a paradigm shift in conceptualisation of personality disorders led to the introduction of a dimensional concept focusing on severity of dysfunction in both ICD-11 and DSM-5 in its Alternative Model for Personality Disorders (AMPD). IN addition, DSM-5 as part of AMPD also considers the presence of 5 domains of pathological personality traits including 25 facets. This more complex mapping of personality could aid understanding personality contributors to psychopathology not only in personality disorders and could aid treatment by providing targets for psychotherapy. Objectives Our aim was to compare pathological personality traits according to DSM-5 AMPD in eating disorder patients, and matched healthy control subjects. Methods We are launching a large project focusing on personality disorders. For this analysis we used the adult form of PID-5 to assess pathological personality traits along 5 domains and 25 facets in eating disorder patients and psychiatrically healthy controls. Data were analyzed with the Mann-Whitney test using R. Results Preliminary results of a pilot analysis in 14 eating disorder patients and matched psychiatrically health controls are shown. Comparing the data of the two groups, a significant difference was observed in several personality facets, including Anxiousness, Deceitfulness, Grandiosity, Impulsivity, Manipulativeness, Perceptual dysregulation, Rigid perfectionism, Submissiveness, and Unusual beliefs. These differences in the above facets reflect differences in the two groups in all pathological personality domains including Anhedonia, Negative affect, Antagonism, Disinhibition, and Psychoticism. Conclusions Our results show complex differences between eating disorder patients and healthy control subjects in several facets, pointing to a unique pattern and the affectedness of all pathological personality domains. Such results could possibly add to identifying personality trait targets for psychotherapy in eating disorders besides increasing our understanding on the etiopsychopathology of this serious psychiatric illness. Our study is ongoing, but more complex analyses involving further measures and variables in larger samples bring the hope for increasing effectiveness of treatment for anorexia. Disclosure of Interest None Declared