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Glioblastoma (GBM) is an extremely aggressive tumor of the central nervous system, with a prognosis of 12–15 months and just 3–5% of survival over 5 years. This is mainly because most patients suffer recurrence after treatment that currently consists in maximal resection followed by radio- and chemotherapy with temozolomide. The recurrent tumor shows a more aggressive behavior due to a phenotypic shift toward the mesenchymal subtype. Proneural-mesenchymal transition (PMT) may represent for GBM the equivalent of epithelial–mesenchymal transition associated with other aggressive cancers. In this review we frame this process in the high degree of phenotypic inter- and intra-tumor heterogeneity of GBM, which exists in different subtypes, each one characterized by further phenotypic variability in its stem-cell compartment. Under the selective pressure of different treatment agents PMT is induced. The mechanisms involved, as well as the significance of such event in the acquisition of a multitherapy resistance phenotype, are taken in consideration for future perspectives in new anti-GBM therapeutic options.

Highlights•Immunoinformatics tools enable rapid and accurate analysis of microbial better epitopes, and accelerate vaccine design. •rPMT is a multi-epitope recombinant toxin (PMT) antigen of P. multocida. •Vaccination of rPMT induced humoral and Th1-type cellular immune response in a mouse model. •rPMT confers 56% protection against P. multocida virulent strain.

Positron emission tomography (PET) imaging is an essential tool in clinical applications for the diagnosis of diseases due to its ability to acquire functional images to help differentiate between metabolic and biological activities at the molecular level. One key limiting factor in the development of efficient and accurate PET systems is the sensor technology in the PET detector. There are generally four types of sensor technologies employed: photomultiplier tubes (PMTs), avalanche photodiodes (APDs), silicon photomultipliers (SiPMs), and cadmium zinc telluride (CZT) detectors. PMTs were widely used for PET applications in the early days due to their excellent performance metrics of high gain, low noise, and fast timing. However, the fragility and bulkiness of the PMT glass tubes, high operating voltage, and sensitivity to magnetic fields ultimately limit this technology for future cost-effective and multi-modal systems. As a result, solid-state photodetectors like the APD, SiPM, and CZT detectors, and their applications for PET systems, have attracted lots of research interest, especially owing to the continual advancements in the semiconductor fabrication process. In this review, we study and discuss the operating principles, key performance parameters, and PET applications for each type of sensor technology with an emphasis on SiPM and CZT detectors—the two most promising types of sensors for future PET systems. We also present the sensor technologies used in commercially available state-of-the-art PET systems. Finally, the strengths and weaknesses of these four types of sensors are compared and the research challenges of SiPM and CZT detectors are discussed and summarized.

A variant of suspect screening by liquid chromatography–high-resolution mass spectrometry (LC-HRMS) is proposed in this study: Samples of a potential source of contamination and of an environmental sample close to this source are first analyzed in a non-targeted manner to select source-related suspects and to identify them. The suspect list compiled from such an exercise is then applied to LC-HRMS data of environmental samples to ascribe and to identify persistent and mobile contaminants in the water cycle that may originate from the source under study. This approach was applied to tire crumb rubber (source) and road dust (close to source); by comparison of the two data sets, 88% of the features detected in tire leachate could be excluded. Of the 48 suspects remaining, a total of 41 could be tentatively identified as either related to hexamethoxymethyl melamine or cyclic amines, benzothiazoles, or glycols. Subsequently, environmental samples were searched for these suspects: 85% were determined in an urban creek after a combined sewer overflow and 67% in the influent of a municipal wastewater treatment plant (WWTP). These exceptionally high rates of positive findings prove that this source-related smart suspect screening effectively directs the effort of selecting and identifying unknown contaminants to those related to the source of interest. The WWTP effluent and the urban creek during dry weather also showed the presence of numerous contaminants that may stem from tire and road wear particles (TRWP) in road runoff. Contribution from other sources, however, cannot be ruled out.

Purpose – This paper aims to provide an overview of theories used in the field of employees’ information systems (IS) security behavior over the past decade. Research gaps and implications for future research are worked out by analyzing and synthesizing existing literature. Design/methodology/approach – This paper presents the results of a literature review comprising 113 publications. The literature review was designed to identify applied theories and to understand the cognitive determinants in the research field. A meta-model that explains employees’ IS security behavior is introduced by assembling the core constructs of the used theories. Findings – The paper identified 54 used theories, but four behavioral theories were primarily used: Theory of Planned Behavior (TPB), General Deterrence Theory (GDT), Protection Motivation Theory (PMT) and Technology Acceptance Model (TAM). By synthesizing results of empirically tested research models, a survey of factors proven to have a significant influence on employees’ security behavior is presented. Research limitations/implications – Some relevant publications might be missing within this literature review due to the selection of search terms and/or databases. However, by conduction a forward and a backward search, this paper has limited this error source to a minimum. Practical implications – This study presents an overview of determinants that have been proven to influence employees’ behavioral intention. Based thereon, concrete training and awareness measures can be developed. This is valuable for practitioners in the process of designing Security Education, Training and Awareness (SETA) programs. Originality/value – This paper presents a comprehensive up-to-date overview of existing academic literature in the field of employees’ security awareness and behavior research. Based on a developed meta-model, research gaps are identified and implications for future research are worked out.

Persistent and mobile (PM) chemicals spread in the water cycle and have been widely detected, yet information about their sources is still scarce. In this study, 67 PM chemicals were analyzed in 19 wastewater samples taken in the sewer system of the city of Leipzig, Germany, covering different industrial, clinical, and domestic discharges. A total of 37 of these analytes could be detected, with highly variable median concentrations between substances (median: 0.5–800 µg L −1 ) and for single substances between samples (e.g., 1,4-diazabicyclo[2.2.2]octane) by up to three orders of magnitude, with the highest single concentration exceeding 10 mg L −1 ( p -cumenesulfonic acid). The emission of PM chemicals into the sewer system was classified as stemming from diffuse (14 analytes) or point sources (23 analytes), while 9 analytes fulfill both criteria. Many so-called industrial chemicals were also discharged from households (e.g., tris(2-chloroethyl) phosphate or 1H-benzotriazole). Examples for analytes showing specific sources are tetrafluoroborate (traffic-related industry and metal production and finishing), ε-caprolactam (large-scale laundry), or cyanuric acid (likely swimming pool). Furthermore, a correlation between 1-cyanoguanidine and guanylurea was observed for the traffic-related industry. This study outlines that sewer sampling can provide valuable information on the sources of PM chemicals. This knowledge is a prerequisite for their future emission control at source or substitution as an alternative to end-of-pipe treatment in municipal wastewater treatment plants. Graphical Abstract

Standard cancer chemotherapy is increasingly being supplemented with novel therapeutics to overcome known chemoresistance pathways. Resistance to treatment is common across various tumour types, driven by multiple mechanisms. One emerging contributor is protein methylation, a post-translational modification mediated by protein methyltransferases (PMTs), which regulate protein function by adding methyl groups, mainly on lysine and arginine residues. Dysregulation of protein lysine methyltransferases (PKMTs) and protein arginine methyltransferases (PRMTs) has been linked to cancer progression and drug resistance, making them attractive therapeutic targets. Consequently, several small-molecule PMT inhibitors have been developed, with some progressing to clinical trials. However, many candidates showing promise in preclinical studies fail to demonstrate efficacy or safety in later stages, limiting clinical success. This gap highlights the need to rethink current approaches to PMT inhibitor design. A deeper understanding of PMT mechanisms, catalytic domains, and their roles in chemoresistance is essential for creating more selective, potent, and clinically viable inhibitors. This review will summarise major chemoresistance pathways and PMTs implicated in cancer, then explore current and prospective PMT inhibitor classes. Building on mechanistic insights, we propose strategies to develop next-generation inhibitors with improved therapeutic potential against chemoresistant cancers.

Aim/Purpose: The UAE and other Middle Eastern countries suffer from various cybersecurity vulnerabilities that are widespread and go undetected. Still, many UAE government organizations rely on human-centric approaches to combat the growing cybersecurity threats. These approaches are ineffective due to the rapid increase in the amount of data in cyberspace, hence necessitating the employment of intelligent technologies such as AI cybersecurity systems. In this regard, this study investigates factors influencing users’ intention to adopt AI-based cybersecurity systems in the UAE. Background: Even though UAE is ranked among the top countries in embracing emerging technologies such as digital identity, robotic process automation (RPA), intelligent automation, and blockchain technologies, among others, it has experienced sluggish adoption of AI cybersecurity systems. This selectiveness in adopting technology begs the question of what factors could make the UAE embrace or accept new technologies, including AI-based cybersecurity systems. One of the probable reasons for the slow adoption and use of AI in cybersecurity systems in UAE organizations is the employee’s perception and attitudes towards such intelligent technologies. Methodology: The study utilized a quantitative approach whereby web-based questionnaires were used to collect data from 370 participants working in UAE government organizations considering or intending to adopt AI-based cybersecurity systems. The data was analyzed using the PLS-SEM approach. Contribution: The study is based on the Protection Motivation Theory (PMT) framework, widely used in information security research. However, it extends this model by including two more variables, job insecurity and resistance to change, to enhance its predictive/exploratory power. Thus, this research improves PMT and contributes to the body of knowledge on technology acceptance, especially in intelligent cybersecurity technology. Findings: This paper’s findings provide the basis from which further studies can be conducted while at the same time offering critical insights into the measures that can boost the acceptability and use of cybersecurity systems in the UAE. All the hypotheses were accepted. The relationship between the six constructs (perceived vulnerability (PV), perceived severity (PS), perceived response efficacy (PRE), perceived self-efficacy (PSE), job insecurity (JI), and resistance to change (RC)) and the intention to adopt AI cybersecurity systems in the UAE was found to be statistically significant. This paper’s findings provide the basis from which further studies can be conducted while at the same time offering critical insights into the measures that can boost the acceptability and use of cybersecurity systems in the UAE. Recommendations for Practitioners: All practitioners must be able to take steps and strategies that focus on factors that have a significant impact on increasing usage intentions. PSE and PRE were found to be positively related to the intention to adopt AI-based cybersecurity systems, suggesting the need for practitioners to focus on them. The government can enact legislation that emphasizes the simplicity and awareness of the benefits of cybersecurity systems in organizations. Recommendation for Researchers: Further research is needed to include other variables such as facilitating conditions, AI knowledge, social influence, and effort efficacy as well as other frameworks such as UTAUT, to better explain individuals’ behavioral intentions to use cybersecurity systems in the UAE. Impact on Society: This study can help all stakeholders understand what factors can increase users’ interest in investing in the applications that are embedded with security. As a result, they have an impact on economic recovery following the COVID-19 pandemic. Future Research: Future research is expected to investigate additional factors that can influence individuals’ behavioral intention to use cybersecurity systems such as facilitating conditions, AI knowledge, social influence, effort efficacy, as well other variables from UTAUT. International research across nations is also required to build a larger sample size to examine the behavior of users.

AlkB homolog 5, RNA demethylase (ALKBH5) is abnormally highly expressed in glioblastoma multiforme (GBM) and is negatively correlated with overall survival in GBM patients. In this study, we found a new mechanism that ALKBH5 and pyrroline-5-carboxylate reductase 2 (PYCR2) formed a positive feedback loop involved in proline synthesis in GBM. ALKBH5 promoted PYCR2 expression and PYCR2-mediated proline synthesis; while PYCR2 promoted ALKBH5 expression through the AMPK/mTOR pathway in GBM cells. In addition, ALKBH5 and PYCR2 promoted GBM cell proliferation, migration, and invasion, as well as proneural-mesenchymal transition (PMT). Furthermore, proline rescued AMPK/mTOR activation and PMT after silencing PYCR2 expression. Our findings reveal an ALKBH5-PYCR2 axis linked to proline metabolism, which plays an important role in promoting PMT in GBM cells and may be a promising therapeutic pathway for GBM.

Aim/Purpose: This study aims to develop a comprehensive conceptual framework that incorporates personal characteristics, social context, and technological features as significant factors that influence the intention of small-city users in China to use mobile health. Background: Mobile health has become an integral part of China’s health management system innovation, the transformation of the health service model, and a necessary government measure for promoting health service parity. However, mobile health has not yet been widely adopted in small cities in China. Methodology: The study utilized a quantitative approach whereby web-based questionnaires were used to collect data from 319 potential users in China using China’s health management system. The data was analyzed using the PLS-SEM (the partial least squares-structural equation modeling) approach. Contribution: This study integrates the protection motivation theory (PMT), which compensates for the limitations of the unified theory of acceptance and use of technology theory (UTAUT) and is a re-examination of PMT and UTAUT in a small city context in China. Findings: The findings indicate that attitude and perceived vulnerability in the personal characteristic factors, social influence and facilitating conditions in the social context factors, and performance expectancy in the technological feature factors influence users’ intention to use mobile health in small cities in China. Recommendations for Practitioners: This study provides feasible recommendations for mobile health service providers, medical institutions, and government agencies based on the empirical results. Recommendation for Researchers: As for health behavior, researchers should fully explain the intention of mobile health use in terms of holism and health behavior theory. Impact on Society: This study aims to increase users’ intention to use mobile health in small cities in China and to maximize the social value of mobile health. Future Research: Future research should concentrate on the actual usage behavior of users and simultaneously conduct a series of longitudinal studies, including studies on continued usage behavior, abandonment behavior, and abandoned-and-used behavior.