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Background: Neurosurgery demands exceptional precision due to the brain's complex and delicate structures, necessitating precise targeting of pathological targets. Achieving optimal outcomes depends on the surgeon's ability to accurately differentiate between healthy and pathological tissues during operations. Raman spectroscopy (RS) has emerged as a promising innovation, offering real-time, in vivo non-invasive biochemical tissue characterization. This literature review evaluates the current research on RS applications in intraoperative neurosurgery, emphasizing its potential to enhance surgical precision and patient outcomes. Methods: Following PRISMA guidelines, a comprehensive systematic review was conducted using PubMed to extract relevant peer-reviewed articles. The inclusion criteria focused on original research discussing real-time RS applications with human tissue samples in or near the operating room, excluding retrospective studies, reviews, non-human research, and other non-relevant publications. Results: Our findings demonstrate that RS significantly improves tumor margin delineation, with handheld devices achieving high sensitivity and specificity. Stimulated Raman Histology (SRH) provides rapid, high-resolution tissue images comparable to traditional histopathology but with reduced time to diagnosis. Additionally, RS shows promise in identifying tumor types and grades, aiding precise surgical decision-making. RS techniques have been particularly beneficial in enhancing the accuracy of glioma surgeries, where distinguishing between tumor and healthy tissue is critical. By providing real-time molecular data, RS aids neurosurgeons in maximizing the extent of resection (EOR) while minimizing damage to normal brain tissue, potentially improving patient outcomes and reducing recurrence rates. Conclusions: This review underscores the transformative potential of RS in neurosurgery, advocating for continued innovation and research to fully realize its benefits. Despite its substantial potential, further research is needed to validate RS's clinical utility and cost-effectiveness. [ABSTRACT FROM AUTHOR]

Conduit pulmonary arterial stiffening and the resultant increase in pulmonary vascular impedance have emerged as an important underlying driver of pulmonary arterial hypertension (PAH). Given that matrix deposition is central to vascular remodeling, we evaluated the role of the collagen cross-linking enzyme lysyl oxidase like 2 (LOXL2) in this study. Human pulmonary artery smooth muscle cells (PASMCs) subjected to hypoxia showed increased LOXL2 secretion. LOXL2 activity and expression were markedly higher in primary PASMCs isolated from the pulmonary arteries of the rat Sugen 5416 + hypoxia (SuHx) model of severe pulmonary hypertension (PH). Similarly, LOXL2 protein and mRNA levels were increased in the pulmonary arteries (PA) and lungs of rats with PH (SuHx and monocrotaline (MCT) models). Pulmonary arteries (PAs) isolated from the rats with PH exhibited hypercontractility to phenylephrine and attenuated vasorelaxation elicited by acetylcholine, indicating severe endothelial dysfunction. Tensile testing revealed a significant increase in PA stiffness in PH. Treatment with PAT-1251, a novel small-molecule LOXL2 inhibitor, improved active and passive properties of the PA ex vivo. There was an improvement in right heart function as measured by right ventricular pressure volume loops in vivo with PAT-1251. Importantly, PAT-1251 treatment ameliorated PH, resulting in improved pulmonary artery pressures, right ventricular remodeling, and survival. Hypoxia-induced LOXL2 activation is a causal mechanism in pulmonary artery stiffening in PH and pulmonary artery mechanical and functional decline. LOXL2 inhibition with PAT-1251 could be a promising approach to improve pulmonary artery pressures, right ventricular elastance, cardiac relaxation, and survival in PAH. NEW & NOTEWORTHY: Pulmonary arterial stiffening contributes to the progression of PAH and the deterioration of right heart function. This study shows that LOXL2 is upregulated in rat models of PH. LOXL2 inhibition halts pulmonary vascular remodeling and improves PA contractility, endothelial function, and PA pressure, resulting in prolonged survival. Thus, LOXL2 is an important mediator of PA remodeling and stiffening in PH and a promising target to improve PA pressures and survival in PH. [ABSTRACT FROM AUTHOR]

The green algal genus Trebouxia is the most frequently encountered photobiont of the lichen symbiosis. The single-celled symbionts have a worldwide distribution, including all continents and climate zones. The vast, largely undescribed, diversity of Trebouxia lineages is currently grouped into four phylogenetic clades (A, C, I, and S), based on a multilocus phylogeny. Genomes are still scarce, however, and it is unclear how the phylogenetic diversity, the broad ecological tolerances, and the ability to form symbioses with many different fungal host species are reflected in genome-wide differences. Here, we generated PacBio-based de novo genomes of six Trebouxia lineages belonging to the Clades A and S, isolated from lichen individuals of the genus Umbilicaria. Sequences belonging to Clade S have been reported in a previous study, but were reassembled and reanalyzed here. Genome sizes ranged between 63.08 and 73.88 Mb. Repeat content accounted for 9% to 16% of the genome sequences. Based on RNA evidence, we predicted 14,109 to 16,701 gene models per genome, of which 5,203 belonged to a core set of gene families shared by all 6 lineages. Between 121 and 454, gene families are specific to each lineage. About 53% of the genes could be functionally annotated. The presence of biosynthetic gene clusters (6 to 17 per genome) suggests that Trebouxia algae are able to synthesize alkaloids, saccharides, terpenes, NRPSs, and T3PKSs. Phylogenomic comparisons of the six strains indicate prevalent gene gain during Trebouxia evolution. Some of the gene families that exhibited significant evolutionary changes (i.e. gene expansion and contraction) are associated with metabolic processes linked to protein phosphorylation, which is known to have a role in photosynthesis regulation, particularly under changing light conditions. Overall, there is substantial genomic divergence within the algal genus Trebouxia , which may contribute to the genus' large ecological amplitude concerning fungal host diversity and climatic niches. [ABSTRACT FROM AUTHOR]

Background: Physiologic MRI-based tumor habitat analysis has the potential to predict patient outcomes by identifying the spatiotemporal habitats of glioblastoma. This study aims to prospectively validate the cut-off for tumor progression obtained from tumor habitat analysis based on physiologic MRI in ascertaining time-to-progression (TTP) and the site of progression in glioblastoma patients following concurrent chemoradiotherapy (CCRT). Methods: In this prospective study (ClinicalTrials.gov ID: NCT02613988), we will recruit patients with IDH-wild type glioblastoma who underwent CCRT and obtained immediate post-operative and three serial post-CCRT MRI scans within a three-month interval, conducted using diffusion-weighted imaging and dynamic susceptibility contrast imaging. Voxels from cerebral blood volume and apparent diffusion coefficient maps will be grouped using k-means clustering into three spatial habitats (hypervascular cellular, hypovascular cellular, and nonviable tissue). The spatiotemporal habitats of the tumor will be evaluated by comparing changes in each habitat between the serial MRI scans (post-operative and post-CCRT #1, #2, and #3). Associations between spatiotemporal habitats and TTP will be analyzed using cox proportional hazard modeling. The site of progression will be matched with spatiotemporal habitats. Discussion: The perfusion- and diffusion-derived tumor habitat in glioblastoma is expected to stratify TTP and may serve as an early predictor for tumor progression in patients with IDH wild-type glioblastoma. Trial registration: ClinicalTrials.gov ID: NCT02613988. [ABSTRACT FROM AUTHOR]

L -Glutamic acid (L -Glu) is a basic unit of proteins and also serves as an important neurotransmitter in the central nervous system. Its structural properties are critical for biological functions and selective receptor recognition. Although this molecule has been extensively studied, the low frequency vibrational behavior that is closely related to conformational changes and the intermolecular interactions between L -Glu and its receptors are still unclear. In this study, we acquired the fingerprint spectrum of L -Glu by using air plasma terahertz (THz) time-domain spectroscopy in the 0.5–18 THz range. The low frequency vibrational characteristics of L -Glu were investigated through density functional theory (DFT) calculations. The THz responses of the ligand binding domain of the NMDAR– L -Glu complex were studied by the ONIOM method, with a focus on discussing the normal modes and interactions of ligand L -Glu and water molecules. The results illustrate that THz spectroscopy exhibits a sensitive response to the influence of L -Glu on the structure of the NMDAR. The water molecules in proteins have various strong vibration modes in the THz band, showing specificity, diversity and complexity of vibrational behavior. There is potential for influencing and regulating the structural stability of the NMDAR– L -Glu complex through water molecules. [ABSTRACT FROM AUTHOR]

Featured Application: The information obtained from this study can be useful for coaches and performance analysts of teams. By taking into account the factors that contribute to securing one of the top positions in the league standings, coaches are encouraged to adopt ball possession strategies with patience and short passes to create gaps in the opponent's defense and, at the right moment, execute through balls aiming to enter the attacking third and create goal opportunities. On the other hand, teams are advised to avoid long passes, as these may lead to a loss of team cohesion and create large distances between the lines. Finally, this information is also useful for team scouts in identifying players who are suitable for implementing the aforementioned strategies. Introduction: Performance analysis is essential for coaches and a topic of extensive research. The advancement of technology and Artificial Intelligence (AI) techniques has revolutionized sports analytics. Aim: The primary aim of this article is to present a robust, explainable machine learning (ML) model that identifies the key factors that contribute to securing one of the top three positions in the standings of the French Ligue 1, ensuring participation in the UEFA Champions League for the following season. Materials and Methods: This retrospective observational study analyzed data from all 380 matches of the 2022–23 French Ligue 1 season. The data were obtained from the publicly-accessed website "whoscored" and included 34 performance indicators. This study employed Sequential Forward Feature Selection (SFFS) and various ML algorithms, including XGBoost, Support Vector Machine (SVM), and Logistic Regression (LR), to create a robust, explainable model. The SHAP (SHapley Additive Explanations) model was used to enhance model interpretability. Results: The K-means Cluster Analysis categorized teams into groups (TOP TEAMS, 3 teams/REST TEAMS, 17 teams), and the ML models provided significant insights into the factors influencing league standings. The LR classifier was the best-performing classifier, achieving an accuracy of 75.13%, a recall of 76.32%, an F1-score of 48.03%, and a precision of 35.17%. "SHORT PASSES" and "THROUGH BALLS" were features found to positively influence the model's predictions, while "TACKLES ATTEMPTED" and "LONG BALLS" had a negative impact. Conclusions: Our model provided satisfactory predictive accuracy and clear interpretability of results, which gave useful information to stakeholders. Specifically, our model suggests adopting a strategy during the ball possession phase that relies on short passes (avoiding long ones) and aiming to enter the attacking third and the opponent's penalty area with through balls. [ABSTRACT FROM AUTHOR]

Cell communication coordinates developmental processes, maintains homeostasis, and contributes to disease. Therefore, understanding the relationship between cells in a shared environment is crucial. Here we introduce Positive Ultra-bright Fluorescent Fusion For Identifying Neighbours (PUFFFIN), a cell neighbour-labelling system based upon secretion and uptake of positively supercharged fluorescent protein s36GFP. We fused s36GFP to mNeonGreen or to a HaloTag, facilitating ultra-bright, sensitive, colour-of-choice labelling. Secretor cells transfer PUFFFIN to neighbours while retaining nuclear mCherry, making identification, isolation, and investigation of live neighbours straightforward. PUFFFIN can be delivered to cells, tissues, or embryos on a customisable single-plasmid construct composed of interchangeable components with the option to incorporate any transgene. This versatility enables the manipulation of cell properties, while simultaneously labelling surrounding cells, in cell culture or in vivo. We use PUFFFIN to ask whether pluripotent cells adjust the pace of differentiation to synchronise with their neighbours during exit from naïve pluripotency. PUFFFIN offers a simple, sensitive, customisable approach to profile non-cell-autonomous responses to natural or induced changes in cell identity or behaviour. Synopsis: While there are some options for labeling cellular neighbours, they often have low flexibility, require modification of multiple cells with different plasmids, or are otherwise technically challenging. To overcome these limitations, this study develops Positive Ultra-bright Fluorescent Fusion For Identifying Neighbours (PUFFFIN), a method based on secretion and receptor-independent uptake of a positively charged fluorescent fusion molecule. PUFFFIN uses a universal uptake mechanism to deliver fluorescent label to neighbouring cells without the need to engineer them with label-uptake machinery. All PUFFFIN components are encoded on a single modular plasmid, amenable to delivery by transfection, electroporation, or lentivirus. PUFFFIN enables ultra-bright colour-of-choice labelling for unambiguous and rapid labelling of neighbours in cell culture or in vivo. PUFFFIN labelling does not compromise viability, enabling functional analysis of live neighbours. PUFFFIN labelling is used to demonstrate that pluripotent cells adjust the pace of differentiation to synchronise with their neighbours. Positive Ultra-bright Fluorescent Fusion For Identifying Neighbours, or PUFFFIN, allows visualization and isolation of surrounding cells in culture, tissues, or embryos to profile non-cell-autonomous responses. [ABSTRACT FROM AUTHOR]

Quantum computing is an exciting field with high disruptive potential, but very difficult to access. For this reason, many approaches to teaching quantum computing are being developed worldwide. This always raises questions about the didactic concept, the content actually taught, and how to measure the success of the teaching concept. In 2022 and 2023, the authors taught a total of nine two-week MOOCs (massive open online courses) with different possible learning paths on the Hasso Plattner Institute's OpenHPI platform. The purpose of the platform is to make computer science education available to everyone free of charge. The nine quantum courses form a self-contained curriculum. A total of more than 17,000 course attendances have been taken by about 7400 natural persons, and the number is still rising. This paper presents the course concept and evaluates the anonymized data on the background of the participants, their behaviour in the courses, and their learning success. This paper is the first to analyze such a large dataset of MOOC-based quantum computing education. The summarized results are a heterogeneous personal background of the participants biased towards IT professionals, a majority following the didactic recommendations, and a high success rate, which is strongly correlatated with following the didactic recommendations. The amount of data from such a large group of quantum computing learners provides many avenues for further research in the field of quantum computing education. The analyses show that the MOOCs are a low-threshold concept for getting into quantum computing. It was very well received by the participants. The concept can serve as an entry point and guide for the design of quantum computing courses. [ABSTRACT FROM AUTHOR]

This paper outlines an alternative approach to teaching quantum computing at the high school level, tailored for students with limited prior knowledge in advanced mathematics and physics. This approach diverges from traditional methods by building upon foundational concepts in classical computing before gradually introducing quantum mechanics, thereby simplifying the entry into this complex field. The course was initially implemented in a program for gifted high school students under the Hong Kong Education Bureau and received encouraging feedback, indicating its potential effectiveness for a broader student audience. A key element of this approach is the practical application through portable NMR quantum computers, which provides students with hands-on experience. The paper describes the structure of the course, including the organization of the lectures, the integration of the hardware of the portable nuclear magnetic resonance (NMR) quantum computers, the Gemini/Triangulum series, and detailed lecture notes in Additional file 1. The initial success in the specialized program and ongoing discussions to expand the course to regular high schools in Hong Kong and Shenzhen suggest the viability of this approach for wider educational application. By focusing on accessibility and student engagement, this approach presents a valuable perspective on introducing quantum computing concepts at the high school level, aiming to enhance student understanding and interest in the field. [ABSTRACT FROM AUTHOR]

Lichen as mutualistic symbiosis is the dominant organism in various extreme terrestrial environment on Earth, however, the mechanisms of their adaptation to extreme habitats have not been fully elucidated. In this study, we chose the Antarctic dominant lichen species Usnea aurantiacoatra to generate a high-quality genome, carried out phylogenetic analysis using maximum likelihood and identify genes under positive selection. We performed functional enrichment analysis on the positively selected genes (PSGs) and found that most of the PSGs focused on transmembrane transporter activity and vacuole components. This suggest that the genes related to energy storage and transport in Antarctic U. aurantiacoatra were affected by environmental pressure. Inside of the 86 PSGs screened, two protein interaction networks were identified, which were RNA helicase related proteins and regulator of G-protein signaling related proteins. The regulator of the G-protein signaling gene (UaRGS1) was chosen to perform further verification by the lichen genetic manipulation system Umbilicaria muhlenbergii. Given that the absence of UmRgs1 resulted in elevated lethality to cold shock, the role for UaRgs1 in Antarctic U. aurantiacoatra resistance to cold can be inferred. The investigation of lichen adaptation to extreme environments at the molecular level will be opened up. [ABSTRACT FROM AUTHOR]

With the advent of the Fourth Industrial Revolution and the era of big data, the ability to handle data has become essential. This has heightened the importance and necessity of data literacy competencies. The purpose of this study is to propose a framework for data literacy competencies. To achieve this goal, data literacy frameworks from eight countries and twelve pieces of literature on data literacy competencies were analyzed and synthesized, resulting in five categories and twenty-three competencies. The five categories are: data understanding and ethics, data collection and management, data analysis and evaluation, data utilization, and data governance and systems. It is hoped that the data literacy competency framework proposed in this study will serve as a foundational resource for policies, curricula, and the enhancement of individual data literacy competencies. [ABSTRACT FROM AUTHOR]

In human–robot interaction studies, trust is often defined as a process whereby a trustor makes themselves vulnerable to a trustee. The role of vulnerability however is often overlooked in this process but could play an important role in the gaining and maintenance of trust between users and robots. To better understand how vulnerability affects human–robot trust, we first reviewed the literature to create a conceptual model of vulnerability with four vulnerability categories. We then performed a meta-analysis, first to check the overall contribution of the variables included on trust. The results showed that overall, the variables investigated in our sample of studies have a positive impact on trust. We then conducted two multilevel moderator analysis to assess the effect of vulnerability on trust, including: (1) an intercept model that considers the relationship between our vulnerability categories and (2) a non-intercept model that treats each vulnerability category as an independent predictor. Only model 2 was significant, suggesting that to build trust effectively, research should focus on improving robot performance in situations where the users are unsure how reliable the robot will be. As our vulnerability variable is derived from studies of human–robot interaction and researcher reflections about the different risks involved, we relate our findings to these domains and make suggestions for future research avenues. [ABSTRACT FROM AUTHOR]

The aim was to present a descriptive 10-season summary of injury data from all teams of a professional football club using a heat map approach. Injuries and exposure time were registered according to the FIFA consensus in all men's and women's teams from Athletic Club over 10 seasons. A team-by-injury table was created, showing the incidence, median severity, and burden in each cell. Cells were coloured based on the injury burden value using a green – yellow–red gradient (lowest to highest). The highest overall injury burden was found in the women's 2nd and 1st teams and the men's U(under)17 team (>200 days lost/1000 h). Muscle injury burden demonstrated an increasing pattern with age. Knee joint/ligament injuries, particularly anterior cruciate ligament ruptures, had the highest impact on women's teams, followed by the men's 2nd team. In comparison, ankle joint/ligament injuries had a relatively low injury burden in most teams. Growth-related injuries were the most impactful injuries in the men's U15 and younger teams, and the women's U14 team. In conclusion, epidemiological data on injuries can inform and guide injury management processes. New and improved visualization methods might be important assets when presenting injury data to key decision-makers. [ABSTRACT FROM AUTHOR]

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Background/Objectives: Chemerin is an adipokine involved in inflammatory and metabolic diseases, and its circulating levels have been associated with inflammatory parameters in various patient cohorts. Severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) infection, which causes COVID-19, triggers inflammatory pathways. However, the association between serum chemerin levels and COVID-19 disease severity and outcomes has not been definitively established. Methods: In this study, serum chemerin levels were analyzed in 64 patients with moderate COVID-19 and 60 patients with severe disease. Results: The results showed that serum chemerin levels were comparable between these two groups and slightly higher than in healthy controls. Notably, COVID-19 patients with hypertension exhibited elevated serum chemerin levels, while those with liver cirrhosis had lower levels. When patients with these comorbidities were excluded from the analyses, serum chemerin levels in COVID-19 patients were similar to those in healthy controls. Positive correlations were observed between serum chemerin levels and markers such as alkaline phosphatase, C-reactive protein, eosinophils, and lymphocytes in the entire cohort, as well as in the subgroup excluding patients with hypertension and cirrhosis. Additionally, urinary chemerin levels were comparable between COVID-19 patients and controls, and neither hypertension nor dialysis significantly affected urinary chemerin levels. Both survivors and non-survivors had similar serum and urinary chemerin levels. Conclusions: In conclusion, this study suggests that comorbidities such as arterial hypertension and liver cirrhosis do have a more significant impact on serum chemerin levels than SARS-CoV-2 infection itself. [ABSTRACT FROM AUTHOR]

There is a recognized need to understand the current state of programming implementation in the Swedish compulsory school system. This study focused specifically on the implementation of programming in the school subject of technology for grades 4–6. In Sweden, the responsibility for choosing teaching and learning material lies with individual teachers. Recent studies have indicated the prevalence of visual programming languages (VPLs) in classrooms. However, no empirical research has specifically investigated why teachers select particular programming learning environments (PLEs) and the challenges they have overcome in this process. Therefore, this study aimed to explore the PLEs used by teachers and the factors influencing their choices. In addition, this study explored the role of pedagogical content knowledge (PCK) and the influence of systemic and situational amplifiers and filters in shaping the programming education landscape, highlighting the importance of understanding these factors for effective implementation. Semi-structured interviews were conducted with 14 experienced programming teachers in grades 4–6 to gather insights. The results revealed that VPLs, particularly Scratch, have been widely adopted, but the study also identified three textual programming languages being utilized. Furthermore, the findings indicate that teachers' previous education plays a significant role in shaping their PLE preferences. This suggests that programming education in both professional development and preservice teacher training is crucial for effective implementation. By investigating PLE choices and the factors influencing them, this study contributes to a better understanding of the current landscape of programming education in Sweden's compulsory school system. [ABSTRACT FROM AUTHOR]

The analysis of the interaction between main bionts (mycobiont and photobiont) in the lichen symbiosis delivers substantial information about their preferences in the selection of symbiotic partners, and their ecological preferences. The selectivity in the Parmelia genus has been defined as strong so far. However, data on this lichen genus, which includes several widely distributed species, are biogeographically limited. Therefore, using specialization indicators and extended sampling, in this study, we estimated the interactions between the main bionts of selected Parmelia spp., using two levels of estimation (species/OTU and haplotype). A comparison of mycobiont-photobiont interactions at different levels showed that considering only mycobiont species and Trebouxia OTUs, greater specialization is found, while Parmelia species studied in this work present a more generalistic strategy in photobiont choice when haplotypes are considered. Despite the uneven sampling of Parmelia species, the interpretation of specialization within species and individuals of the genus leads to a more precise and accurate interpretation of their adaptation strategies. Furthermore, the data from P. sulcata indicate the existence of a different pool of compatible haplotypes in some geographical regions compared to neighboring areas. This observation suggests the potential influence of climatic factors. [ABSTRACT FROM AUTHOR]

Embryonic stem cells (ESCs) are remarkable for the high activity level of ubiquitin–proteasome system—the molecular machinery of protein degradation in the cell. Various forms of the proteasome complexes comprising different subunits and interacting regulators are responsible for the substrate selectivity and degradation. Immunoproteasomes are amongst these forms which play an important role in antigen presentation; however, a body of recent evidence suggests their functions in pluripotent stem cells. Previous studies have established three consecutive phases of pluripotency, featured by epiblast cells and their cultured counterparts: naïve, formative, and primed phase. In this work, we report that immunoproteasomes and their chaperone co-regulators are suppressed in the naïve state but are readily upregulated in the formative phase of the pluripotency continuum, featured by epiblast-like cells (EpiLCs). Our data lay ground for the further investigation of the biological functions of immunoproteasome in the regulation of proteostasis during early mammalian development. [ABSTRACT FROM AUTHOR]

A reliable, versatile means of assessing visuo-motor reaction time (V-MRT) is important to football (soccer) players for many reasons, including the fact that faster V-MRT is a critical sport skill that may even play a role in reducing common sports injuries to the lower muscle extremities that can be associated with lost time on the field. We aimed to determine the test-retest reliability and minimum detectable change (MDC) of the Brain Pro System for assessing lower-extremity V-MRT in young male football players. We had 68 participants (M age = 16.35, SD = 1.71 years) perform two assessment sessions one-week apart. For test-retest reliability, we calculated a one-way intra-class correlation coefficient (ICC) at the 95% confidence interval and provided the standard error of measurement (SEM) and minimum detectable change (MDC) (MDC = SEM × 1.96 × √2) for V-MRTs. We obtained excellent V-MRT test-retest reliability for dominant lower-extremity, non-dominant lower-extremity, and dominant and non-dominant lower-extremities (ICC2,1 =.93, 95%CI =.89–.96; ICC2,1 =.94, 95%CI =.91–.96; ICC2,1 =.96, 95%CI =.94–.97; respectively). The calculated MDC for the dominant lower-extremity V-MRT, the non-dominant lower-extremity V-MRT, and dominant and non-dominant lower-extremities (random) V-MRT were 1.21 seconds, 1.13 seconds, and 1.21 seconds, respectively. Brain Pro System had excellent reliability for assessing lower-extremity V-MRT in young male football players. The MDC values at the 95% confidence level (MDC95) we obtained were reliable for assessing clinically meaningful V-MRT changes. [ABSTRACT FROM AUTHOR]

This study investigates the level of awareness among teachers regarding the use of artificial intelligence (AI) in education, focusing on whether this awareness varies according to socio-demographic characteristics, access to technology, and specific knowledge and beliefs about AI. Conducted in Northern Cyprus during the 2023–2024 academic year, this study employed a survey model with purposive and snowball sampling methods, involving 164 teachers. Teachers at different levels, namely, primary school, secondary school, high school, and university, were included in this study. The "Artificial Intelligence Awareness Scale", developed by Ferikoğlu and Akgün (2022), was used to measure AI awareness. Data normality was verified through skewness and kurtosis values, allowing for parametric statistical tests such as t-tests, one-way ANOVA, logistic regression, and chi-square analysis. This study explored the distribution of AI use across different school types and educational levels and assessed the impact of sub-dimensions of AI awareness on its application in teaching. Findings revealed no significant influence of teacher demographics (age, gender, education level, type of school, institution level, and monthly income) on AI awareness. However, usage patterns indicated that university lecturers were more likely to incorporate AI in their teaching, followed by primary and high school teachers, with secondary school teachers using it the least. A Multilayer Neural Network Analysis identified practical knowledge as the most critical factor influencing the use of AI in teaching (importance weight of 0.450), followed by beliefs and attitudes (0.298), relatability (0.148), and theoretical knowledge (0.104). These results highlight the importance of practical knowledge for fostering AI integration in educational practices, underscoring significant implications for teacher training and professional development programs. [ABSTRACT FROM AUTHOR]

In the wake of the COVID-19 pandemic, the Russian war of aggression against Ukraine and the resurgence of the Middle East conflict, government measures to support the economy have intervened massively in economic activity and thus influenced the real insolvency situation. This situation creates disruptive conditions in insolvency counselling and requires comprehensive risk management for the strategic safeguarding of internal processes in insolvency counselling companies. Despite a number of academic articles that address a lack of risk awareness in insolvency counselling, there have been no valid statistical surveys on this topic to date. The topic has also been largely ignored in practice. This article presents a study that examines risk management in insolvency advisory companies in the context of government intervention in the global economy from 2020 to 2023. The aim of the research is to assess the necessity and existence of risk management in these companies. A survey of 350 insolvency advisors was conducted between March and April 2024, from which 113 complete data sets could be analysed. The central hypothesis of the research study is that a significant majority of insolvency advisory companies have insufficient risk awareness and do not implement comprehensive risk management strategies. The survey results confirm that risk management is rarely practised and that a well-founded risk awareness is lacking in most consulting companies. It is noteworthy that two-thirds of those surveyed consider the benefits of risk management to be low, although more than half of those surveyed recognise increased risks due to government crisis measures. Ultimately, this study concludes with a recommendation that a standardised EU insolvency regulation could offer the greatest benefits for the insolvency sector, as it would simplify risk management for consultants in all member states. [ABSTRACT FROM AUTHOR]

Quiet ego is a relatively novel, increasingly studied, multi-dimensional concept characterized by a compassionate, interdependent worldview and an adaptive balance between self-interest and concern for others. Quiet ego has been associated with a range of characteristics that can promote relationship quality, responding effectively in the face of challenges, and greater well-being. However, it is currently unknown to what extent quiet ego translates across cultures and settings. The present research leverages cultural and organizational theories to evaluate the conceptual and structural validity of quiet ego for Latinx/Hispanic individuals in the U.S. and to examine relationships among quiet ego, work supervisor relationship quality, and goals in the workplace. Employed college student participants (n = 831; nLatinx/Hispanic = 305) completed an online survey, and collected data were subjected to confirmatory factor analysis and path analysis. Findings confirmed the overall structural model of quiet ego with four primary dimensions (perspective taking, inclusive identity, detached awareness, and growth-mindedness) and indicated that this structure did not differ between Latinx/Hispanic and non-Latinx/Hispanic subsamples. Further, results cohered with the proposed model suggesting that quiet ego might facilitate relationship quality with a workplace supervisor, which, in turn could foster balanced, intrinsically motivating perceptions that one's work goals benefit both oneself and others (mutual gain motivation). The study suggests that quiet ego may be a construct with meaning and utility in Latinx/Hispanic populations and in employment settings. However, further research is needed, and specific suggestions for future study are discussed. [ABSTRACT FROM AUTHOR]

The integration of artificial intelligence and data literacy (AI&DL) into education, both in the curriculum and especially in the training and further education of teachers, is a challenge that is becoming increasingly important both internationally and in the European context. Nevertheless, there are currently few programs or successful approaches for the realization of this integration—especially for the integration of AI&DL into teacher training. However, the training and further education of teachers at different school levels is essential for the successful integration of AI&DL into everyday school life and curricula. To tackle this problem, the TrainDL project opened a dialog with teachers and European policy makers. In the course of the project, an overview of the situation in a number of European countries was created. In-depth desk research, several stakeholder and policy building workshops and the processing and analysis of policy documents in a specially developed compare system, in preparation for an interactive online policy monitor, were conducted to create an overview of the situation regarding policies in the AI&DL educational context. [ABSTRACT FROM AUTHOR]

In this paper, the effects of the rapid advancement of generative artificial intelligence (Gen AI) in higher education (HE) are discussed. A mixed exploratory research approach was employed to understand these impacts, combining analysis of current research trends and students' perceptions of the effects of Gen AI tools in academia. Through bibliometric analysis and systematic literature review, 64 publications (indexed in the SCOPUS and Web of Science databases) were examined, highlighting Gen AI's disruptive effect on the pedagogical aspects of HE. The impacts identified by the literature were compared with the perceptions held by computer science students of two different HE institutions (HEIs) on the topic. An exploratory study was developed based on the application of a questionnaire to a group of 112 students. The results suggest that while Gen AI can enhance academic work and learning feedback, it requires appropriate pedagogical support to foster critical, ethical, and digital literacy competencies. Students demonstrate awareness of both the risks and benefits associated with Gen AI in academic settings. The research concludes that failing to recognize and effectively use Gen AI in HE impedes educational progress and the adequate preparation of citizens and workers to think and act in an AI-mediated world. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI), especially generative AI (GenAI), is rapidly permeating every aspect of our lives, driving an accelerated evolution of how we work, play, and learn, thus necessitating new competencies for teachers and students. This study develops and validates an AI competency framework tailored for teachers and students, with an emphasis on researcher-teacher co-creation. The researcherteacher collaboration highlights the importance of teacher involvement in the design process, ensuring the framework's alignment with real-world educational practices. The framework identifies four key skills: identification of AI mechanisms and their operation; effective and informed use of AI; AI agency: proactive and value-generating utilization of AI; and ethical use of AI, each with specific abilities and components. It also outlines necessary values, attitudes, and knowledge for engaging with AI in education, aiming to prepare teachers and students for an AI-saturated world. This study discusses the need for assessment indicators and assimilation models. [ABSTRACT FROM AUTHOR]

Objective: It is well known that glucose and lipid metabolism disorders and insulin resistance are common in sepsis, which affect the occurrence and prognosis of multiple organ dysfunction in septic patients. Previous study reported the predictive value of triglyceride-glucose index (TyG), a clinical indicator for insulin resistance, in postoperative delirium patients. However, it remains unclear whether the TyG index is a novel predictive biomarker for sepsis-associated delirium. The aim of this study is to explore the relationship between TyG index and the risk of delirium in patients with sepsis. Methods: Adult septic patients were identified from the MIMIC-IV database and divided into four groups based on the mean value of TyG. The primary outcome was the incidence of delirium. The association between TyG and the risk of developing delirium was evaluated by restricted cubic spline (RCS), multivariate logistic regression and subgroup analysis. Propensity Score Matching (PSM) method was used to balance the baseline data. Results: A total of 3,331 septic patients were included in the analysis, and further divided into four groups: Q1 (TyG ≤ 8.67), Q2 (8.67 < TyG ≤ 9.08), Q3 (9.08 < TyG ≤ 9.61), and Q4 (TyG > 9.61). The RCS curves demonstrated a non-linear positive relationship between TyG index and the risk of developing delirium, and an optimal cut-of value 9.09 was recommended. After balancing the baseline information by PSM, patients in the TyG > 9.09 group had a significant higher incidence of delirium compared with those in the TyG ≤ 9.09 group. In logistic regression analysis, TyG > 9.09 was significantly associated with lower risk of developing delirium in both original cohort (OR 1.54–1.78, all P < 0.001) and the PSM cohort (OR 1.41–1.48, all P < 0.001). No association was found between the TyG index and mortality (all P > 0.05). In subgroup analysis, our findings were consistent (all OR > 1 in all subgroups). Conclusion: Our study demonstrated an independent association between TyG index and increased risk of delirium in septic patients, indicating that TyG index can serve as a biomarker for delirium in sepsis. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this article was to identify differences in evaluations of factors affecting trust in academics and direct supervisors as perceive by Generation Z from Poland, Spain and Turkey. Design/methodology/approach: The presented analyzes constitute a part of a broader study on the trust that generation Z place in entities from various spheres of life. The article focuses on the academic teachers and supervisors. The research was carried out with the use of CAWI and PAPI methods on a sample of 656 respondents. Findings: The aspects most and least influential on trust in both academics and supervisors were identified, statistically significant differences in the perception of these aspects depending on nationality were analyzed, and a correlation between respondents' evaluations of individual factors of trust. Research limitations/implications: The research sample (lack of representativeness of the sample). Practical implications: The article indicates which trust constructs should paid attention supervisor especially in the aspect of working in multinational teams. Originality/value: The article indicates differences in the perception of trust constructs among young Poles, Spaniards and Turks. The article is addressed primarily to people managing multinational teams and academic teachers teaching students of various nationalities. [ABSTRACT FROM AUTHOR]

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Purpose: Research on the effects of feedback frequency has reported mixed findings. To tackle this problem, the current study focuses on specific feedback signs (i.e. negative feedback). By integrating the face management theory and attribution theory, this study examined the mediating effect of trust in supervisors and the moderating effect of employee-attributed performance promotion motives for negative feedback. Design/methodology/approach: A field study with 176 participants and two supplemental experiments with 143 and 100 participants, respectively, were conducted to test the theoretical model. Findings: Results revealed that the frequency of supervisory negative feedback negatively influenced employees' trust in supervisors, which in turn influenced employees' perceptions of feedback utility and learning performance. These indirect effects can be alleviated when employees have high degrees of performance promotion attribution for supervisor motives. Originality/value: This research extends feedback research by integrating feedback frequency with a specific sign of feedback and revealing a moderated mediation effect of the negative feedback frequency. [ABSTRACT FROM AUTHOR]

Copyright of Italian Journal of Health Education, Sport & Inclusive Didactics is the property of Edizioni Universitarie Romane and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Computational thinking (CT), an essential 21st century skill, incorporates key computer science concepts such as abstraction, algorithms, and debugging. Debugging is particularly underrepresented in the CT training literature. This multi-level meta-analysis focused on debugging as a core CT skill, and investigated the effects of various debugging interventions. Moderator analyses revealed which interventions were effective, in which situations, and for what kind of learner. A significant overall mean effect of debugging interventions ( g ¯ = 0.64, CI = (0.32, 0.96), p <.001), was found based on 62 effect sizes from 18 source articles. Significant between-studies variation indicated that true effects could range from −0.54 to 1.82. In addition, sensitivity analyses and checks on confounding provided further understandings of intervention features and their impacts. Interventions using enhanced debuggers and systematic instruction were particularly effective in fostering debugging skills. Debugging intervention effects varied by participant population and potentially by publication type. Moreover, debugging interventions had impact regardless of how debugging skills were measured, programming medium used, control-group type, and whether the study was randomized. Future studies should investigate the best practices for improving debugging abilities for whom and under what circumstances. [ABSTRACT FROM AUTHOR]

Purpose: Leveraging Emerson's theory of power and motivated reasoning, this study aims to explore how the net power of an individual and actual, instead of perceived, vulnerability results in asymmetric trust and distrust development in a dyadic relationship. Design/methodology/approach: Based on extant literature and gaps in the literature, this conceptual paper hypothesises and proposes trust formation based on power dynamics and vulnerability. Findings: This research extends the knowledge base by exploring the role of actual vulnerability over perceived vulnerability in trust formation and distrust formation. Research limitations/implications: The research propositions imply that the dyadic trust formation process is not rational, and trust itself is not symmetrical but asymmetrical. The net power possessed by one individual over the other drives trust. Net power balance determines the actual vulnerability of the focal individual, and then the individual, through motivated reasoning, trusts or distrusts another individual. Scholars, going forward, could explore how trust formation varies at group and firm levels. Originality/value: Extant literature has not explored the role of power imbalance in determining actual (versus perceived) vulnerability that influences trust formation between parties. The conceptual paper fills this gap. [ABSTRACT FROM AUTHOR]

Copyright of Bulletin of the 'Carol I' National Defence University / Buletinul Universitatii Nationale de Aparare 'Carol I' is the property of Carol I National Defence University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Datenschutz und Datensicherheit - DuD is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The growing impact and importance of artificial intelligence in society has led to an increasing interest for the potential of artificial intelligence as an educational tool in schools to aid both students and teachers. In this study we investigate digitally skilled K-12 mathematics teachers’ (N=85) attitudes towards and expectations on the role of artificial intelligence in the classroom. The study was done by conducting and analyzing the results of a web-based survey among Swedish and Finnish speaking mathematics teachers using a mixed methods strategy. The Will, Skill and Tool framework was used for the analysis. The survey was done before the introduction of ChatGPT-3. The results indicate that the teachers’ attitudes toward AI tools in school are characterized by interest, openness, and awareness. Teachers have a balanced view on the possibilities and risks of AI use in school. However, the teachers also stress that there is a risk that AI tools will shift the focus from learning key mathematical skills towards learning and interaction with the AI tools themselves. The research concluded that the K-12 mathematics teachers surveyed have broad experience with digital tools and will likely become early adopters of AI tools in the classroom. [ABSTRACT FROM AUTHOR]

Cu is an essential micronutrient for various physiological processes in almost all human cell types. Given the critical role of Cu in a wide range of cellular processes, the local concentrations of Cu and the cellular distribution of Cu transporter proteins in the lung are essential for maintaining a steady-state internal environment. Dysfunctional Cu metabolism or regulatory pathways can lead to an imbalance in Cu homeostasis in the lungs, affecting both acute and chronic pathological processes. Recent studies have identified a new form of Cu-dependent cell death called cuproptosis, which has generated renewed interest in the role of Cu homeostasis in diseases. Cuproptosis differs from other known cell death pathways. This occurs through the direct binding of Cu ions to lipoylated components of the tricarboxylic acid cycle during mitochondrial respiration, leading to the aggregation of lipoylated proteins and the subsequent downregulation of Fe-S cluster proteins, which causes toxic stress to the proteins and ultimately leads to cell death. Here, we discuss the impact of dysregulated Cu homeostasis on the pathogenesis of various respiratory diseases, including asthma, chronic obstructive pulmonary disease, idiopathic interstitial fibrosis, and lung cancer. We also discuss the therapeutic potential of targeting Cu. This study highlights the intricate interplay between copper, cellular processes, and respiratory health. Copper, while essential, must be carefully regulated to maintain the delicate balance between necessity and toxicity in living organisms. This review highlights the need to further investigate the precise mechanisms of copper interactions with infections and immune inflammation in the context of respiratory diseases and explore the potential of therapeutic strategies for copper, cuproptosis, and other related effects. [ABSTRACT FROM AUTHOR]

In this study, the library ESG evaluation indicators specialized for libraries were developed, and based on which, a survey was conducted targeting the actual libraries to evaluate the ESG level of libraries. As a result of the study, first, among the ESG evaluation indicators, the indicators of the social field and the governance field are demonstrating high in which field of the library's ESG evaluation indicators will appear the highest. The social area's high score of 3.70 seems to be because the protection of users' rights, occupational safety, and contribution to society and the local community are very closely related to the original role of the library. Second, it may be seen that there is a difference between the questions in the corporate governance part, while the averages are the same. In the case of library's cooperation, it turned out that it was 3.94 in the necessity evaluation of the evaluation indicators, but it was lowered to 3.61 in the actual library situation evaluation. Meanwhile, in connection with the activities of the director of library and the board of directors, it may be seen that the index evaluation increased from 3.32 to 3.58 in the actual evaluation. [ABSTRACT FROM AUTHOR]

In times of crisis, resilience has become a popular buzzword in supply chain management as a counterpart to efficiency and lean management. But how can supply chain resilience be addressed by companies and how can a process for assessing it be designed and established? The aim of this paper is to highlight the issue from both a practical and a scientific perspective, and to point the way forward for practical research. We present the strategic concept of an impact-oriented approach that, in contrast to standard risk management, proposes to first analyze the material flows of a supply chain to uncover its vulnerable elements before identifying specific risk events. The approach is flanked by three Practitioner Principles for resource-efficient application: i) use existing data in a reduced and structured manner, ii) examine Key Resilience Areas to assess vulnerabilities, and iii) consider the resilience appetite of supply chain managers. [ABSTRACT FROM AUTHOR]

Carbamazepine (CBZ) is commonly prescribed for epilepsy and frequently used in polypharmacy. However, concerns arise regarding its ability to induce the metabolism of other drugs, including itself, potentially leading to the undertreatment of co-administered drugs. Additionally, CBZ exhibits nonlinear pharmacokinetics (PK), but the root causes have not been fully studied. This study aims to investigate the mechanisms behind CBZ's nonlinear PK and its induction potential on CYP3A4 and CYP2C9 enzymes. To achieve this, we developed and validated a physiologically based pharmacokinetic (PBPK) parent–metabolite model of CBZ and its active metabolite Carbamazepine-10,11-epoxide in GastroPlus®. The model was utilized for Drug–Drug Interaction (DDI) prediction with CYP3A4 and CYP2C9 victim drugs and to further explore the underlying mechanisms behind CBZ's nonlinear PK. The model accurately recapitulated CBZ plasma PK. Good DDI performance was demonstrated by the prediction of CBZ DDIs with quinidine, dolutegravir, phenytoin, and tolbutamide; however, with midazolam, the predicted/observed DDI AUClast ratio was 0.49 (slightly outside of the two-fold range). CBZ's nonlinear PK can be attributed to its nonlinear metabolism caused by autoinduction, as well as nonlinear absorption due to poor solubility. In further applications, the model can help understand DDI potential when CBZ serves as a CYP3A4 and CYP2C9 inducer. [ABSTRACT FROM AUTHOR]

Although Machine Learning (ML) is found practically everywhere, few understand the technology behind it. This presents new challenges to extend computing education by including ML concepts in order to help students to understand its potential and limits and empowering them to become creators of intelligent solutions. Therefore, we developed an introductory course to teach basic ML concepts, such as fundamentals of neural networks as well as limitations and ethical concerns in alignment with the K-12 Guidelines for Artificial Intelligence. It also teaches the application of these concepts, by guiding the students to develop a first classification model of recycling trash images using Google Teachable Machine. In order to promote ML education, the interactive course is available online in Brazilian Portuguese to be used as an extracurricular course or in an interdisciplinary way as part of science classes covering recycling topics. The course was applied and evaluated through a series of exploratory case studies with a total of 108 middle and high school students. The results of the evaluation show that middle and high school students were able to understand ML concepts and develop an image classification model. No substantial difference with regard to the educational stage, gender and instructional mode was observed. The course was also perceived as an enjoyable learning experience motivating students to learn more about ML. [ABSTRACT FROM AUTHOR]

The study examined the effect of teaching text-based programming with a physical programming tool on secondary school students' computational thinking skills and self-efficacy perceptions. The study was conducted according to a sequential explanatory design as a mixed method research. The study group consisted of 85 secondary school students. Within the scope of the study, a physical programming tool called Micro:bit was used to teach Python programming for a period of 6 weeks. Data were collected using the Self-Efficacy Perception Scale for Computational Thinking Skill, Bebras: International Challenge on Informatics and Computational Thinking Tasks, tests focused on programming tool, concepts, and processes, and through semi-structured interview questioning. According to the findings obtained from pretests and posttests, a significant and positive difference was found in the students' computational thinking skills and self-efficacy perceptions towards computational thinking skill. As a result of having received instruction in programming, the students satisfactorily learnt the required programming concepts and processes. Through learning Python programming with a physical programming tool, the students not only gained the skills required to write appropriate syntax, and to test and debug code, but they also learnt programming concepts such as variables, conditional expressions, loops, and functions. [ABSTRACT FROM AUTHOR]

Copyright of GMS Journal for Medical Education is the property of German Medical Science Publishing House gGmbH and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study introduces a compact Raman spectrometer with a 1064 nm excitation laser coupled with a fiber probe and an inexpensive motorized stage, offering a promising alternative to widely used Raman imaging instruments with 785 nm excitation lasers. The benefits of 1064 nm excitation for biomedical applications include further suppression of fluorescence background and deeper tissue penetration. The performance of the 1064 nm instrument in detecting cancer in human bladder resectates is demonstrated. Raman images with 1064 nm excitation were collected ex vivo from 10 human tumor and non-tumor bladder specimens, and the results are compared to previously published Raman images with 785 nm excitation. K-Means cluster (KMC) analysis is used after pre-processing to identify Raman signatures of control, tumor, necrosis, and lipid-rich tissues. Hierarchical cluster analysis (HCA) groups the KMC centroids of all specimens as input. The tools for data processing and hyperspectral analysis were compiled in an open-source Python library called SpectraMap (SpMap). In spite of lower spectral resolution, the 1064 nm Raman instrument can differentiate between tumor and non-tumor bladder tissues in a similar way to 785 nm Raman spectroscopy. These findings hold promise for future clinical hyperspectral Raman imaging, in particular for specimens with intense fluorescence background, e.g., kidney stones that are discussed as another widespread urological application. [ABSTRACT FROM AUTHOR]

This study examines the mediating role of teachers’ perceived administrator support in the relationship between principals’ social justice leadership behaviors and teachers’ trust in principals. The sample of the study, which was designed in the relational survey model, consists of 903 teachers working in public schools in a metropolitan city in Southeast Türkiye. In the context of the research model, the SPSS Process Macro (Model-4) application developed by Hayes (2018) was used to determine the mediation effect. Because of the analysis of the research data, it was determined that the social justice leadership behaviors exhibited by school principals predicted both teachers’ trust in the principal and teachers’ perceived administrator support positively and statistically significantly. On the other hand, it was concluded that perceived administrator support plays a mediating role in the relationship between principals’ social justice leadership behaviors and teachers’ trust in principals. In this context, it can be stated that if school administrators’ social justice leadership behaviors increase, both the administrator support perceived by teachers and their trust in the principal will increase. [ABSTRACT FROM AUTHOR]

The integration of artificial intelligence (AI) topics into K–12 school curricula is a relatively new but crucial challenge faced by education systems worldwide. Attempts to address this challenge are hindered by a serious lack of curriculum materials and tools to aid teachers in teaching AI. This article introduces the theoretical foundations and design principles for implementing co-design projects in AI education, empirically tested in 12 Finnish classrooms. The article describes a project where 4th- and 7th-graders (N = 213) explored the basics of AI by creating their own AI-driven applications. Additionally, a framework for distributed scaffolding is presented, aiming to foster children’s agency, understanding, creativity, and ethical awareness in the age of AI. [ABSTRACT FROM AUTHOR]

Background: Airway epithelium is an important component of airway structure and the initiator of airway remodeling in asthma. The changes of extracellular matrix (ECM), such as collagen deposition and structural disturbance, are typical pathological features of airway remodeling. Thus, identifying key mediators that derived from airway epithelium and capable of modulating ECM may provide valuable insights for targeted therapy of asthma. Methods: The datasets from Gene Expression Omnibus database were analyzed to screen differentially expressed genes in airway epithelium of asthma. We collected bronchoscopic biopsies and serum samples from asthmatic and healthy subjects to assess lysyl oxidase like 2 (LOXL2) expression. RNA sequencing and various experiments were performed to determine the influences of LOXL2 knockdown in ovalbumin (OVA)-induced mouse models. The roles and mechanisms of LOXL2 in bronchial epithelial cells were explored using LOXL2 small interfering RNA, overexpression plasmid and AKT inhibitor. Results: Both bioinformatics analysis and further experiments revealed that LOXL2 is highly expressed in airway epithelium of asthmatics. In vivo, LOXL2 knockdown significantly inhibited OVA-induced ECM deposition and epithelial-mesenchymal transition (EMT) in mice. In vitro, the transfection experiments on 16HBE cells demonstrated that LOXL2 overexpression increases the expression of N-cadherin and fibronectin and reduces the expression of E-cadherin. Conversely, after silencing LOXL2, the expression of E-cadherin is up-regulated. In addition, the remodeling and EMT process that induced by transforming growth factor-β1 could be enhanced and weakened after LOXL2 overexpression and silencing in 16HBE cells. Combining the RNA sequencing of mouse lung tissues and experiments in vitro, LOXL2 was involved in the regulation of AKT signaling pathway. Moreover, the treatment with AKT inhibitor in vitro partially alleviated the consequences associated with LOXL2 overexpression. Conclusions: Taken together, the results demonstrated that epithelial LOXL2 plays a role in asthmatic airway remodeling partly via the AKT signaling pathway and highlighted the potential of LOXL2 as a therapeutic target for airway remodeling in asthma. [ABSTRACT FROM AUTHOR]