mdpi-ai/citelens huggingface dataset:
The role of mind wandering and anxiety in the association between internet addiction and hyperactivity-impulsivity: a serial mediation model
Field: PSYCHOLOGY

Hyperactivity-Impulsivity have significant negative effects on adolescents’ academic performance, physical and mental health, and social relationships. This study aims to deeply explore the relationship between Hyperactivity-Impulsivity in adolescents and Internet Addiction. Unlike previous studies, this study further explores a potential serial mediation model involving Mind Wandering and Anxiety. A total of 2042 adolescents completed assessments using the Internet Addiction Test (IAT), the Mind Wandering Questionnaire (MWQ), the Generalized Anxiety Disorder 2(GAD-2), and the ASRS short scale to evaluate Internet Addiction, Mind Wandering, Anxiety, and Hyperactivity-Impulsivity, respectively. Internet Addiction, Mind Wandering, and Anxiety significantly influence adolescents’ Hyperactivity-Impulsivity (p <.001). Mediation analysis further indicates that Internet Addiction is associated with Hyperactivity-Impulsivity through the serial mediating effects of Mind Wandering and Anxiety(p <.01). These findings highlight Mind Wandering and Anxiety as key mediators in the link between Internet Addiction and Hyperactivity-Impulsivity in adolescents. This study sheds light on how Internet Addiction influences Hyperactivity-Impulsivity among adolescents and underscores the importance of preventive measures. We recommend implementing interventions aimed at fostering healthy Internet usage habits and providing robust mental health support to safeguard adolescents’ physical and mental well-being.
FGFR3-TACC3 fusion gene promotes glioblastoma malignant progression through the activation of STAT3 signaling pathway
Field: ONCOLOGY

Objective: The Fibroblast growth factor receptors 3-transforming acidic coiled-coil-containing protein 3 (FGFR3-TACC3, F3-T3) oncogenic fusion gene, identified in malignant tumors such as gliomas and bladder cancer, has been particularly noted in recurrent gliomas where it is considered to drive malignant progression, thus presenting itself as a viable therapeutic target. However, the precise mechanism by which F3-T3 facilitates the malignant progression of glioma is not fully understood.Methods: Correction analysis of STAT3 and FGFR3 with major glioma mutation types and pan-cancer analysis was conducted using The Cancer Genome Atlas (TCGA) database. A series of phenotypic experiments, including CCK-8, EdU, colony-formation assay, wound healing assay, and transwell assay were conducted to detect the effects of F3-T3 on proliferation, invasion, and migration of glioma cells. The association between F3-T3 and epithelial-mesenchymal transition (EMT) was investigated through enrichment analysis of the E-MTAB-6037 gene chip database and confirmed by western blot. The underling mechanism were further inferred and validated through RNA sequencing, E-MTAB-6037 gene chip data, and western blot. The relationship between p-STAT3 expression and the WHO grade of glioma was evaluated using immunohistochemistry (IHC) and tissue microarray analysis. Furthermore, the results of vivo experiments and IHC has confirmed the impact of F3-T3 on glioma malignant progression and activation of the STAT3 signaling pathway.Results: The experimental results from this study indicate that F3-T3 accelerates the epithelial-mesenchymal transition (EMT) process in glioma cells, thereby promoting their proliferation, invasion, and migration capabilities. Mechanistically, it was determined through RNA sequencing that the signal transducer and activator of transcription 3 (STAT3) signaling pathway is crucial for the malignant progression of F3-T3. This finding was further supported through follow-up experiments conducted after STAT3 knockdown. The role of the STAT3 pathway in gliomas was also reinforced through bioinformatic analysis and immunohistochemistry (IHC) on tissue microarrays (TMA). Further in vivo experiments corroborated the role of F3-T3 in enhancing glioma growth and progression.Conclusion: F3-T3 facilitates the proliferation, invasion, migration and EMT of glioma cells, thereby promoting their malignant progression through STAT3 signaling activation. These findings highlight its potential as a therapeutic target for glioma treatment.
The role of AI for MRI-analysis in multiple sclerosis—A brief overview
Field: AI

Magnetic resonance imaging (MRI) has played a crucial role in the diagnosis, monitoring and treatment optimization of multiple sclerosis (MS). It is an essential component of current diagnostic criteria for its ability to non-invasively visualize both lesional and non-lesional pathology. Nevertheless, modern day usage of MRI in the clinic is limited by lengthy protocols, error-prone procedures for identifying disease markers (e.g., lesions), and the limited predictive value of existing imaging biomarkers for key disability outcomes. Recent advances in artificial intelligence (AI) have underscored the potential for AI to not only improve, but also transform how MRI is being used in MS. In this short review, we explore the role of AI in MS applications that span the entire life-cycle of an MRI image, from data collection, to lesion segmentation, detection, and volumetry, and finally to downstream clinical and scientific tasks. We conclude with a discussion on promising future directions.
Effect of stressors on depressive mood among long-term high-altitude workers: a moderated mediation analysis
Field: PSYCHOLOGY

Diathesis-stress theory of depression is well known, which stresses that stressor is an inducing factor for depression in general population. High altitude, a combination of variety of stressors, is a special environment that may cultivate more depression. However, how different types of stressors contribute to depression and its underlying mechanisms in high-altitude populations remain unrevealed. The study aimed to reveal the effect of different stressors on depressive mood among long-term high-altitude workers in China and further explore the mediation of emotion regulation and moderation of parent-child alienation. 2065 Chinese workers at altitude of approximate 4200 m completed a cross-sectional survey with the Baker Depression Inventory-II scale, the Emotional Regulation scale, the Parent-child Alienation scale, and the Stressors scale (i.e., environmental factors, low social support, working challenges, accommodation, personal affairs, and cognitive factors). Correlation analysis showed positive correlations between stressors and depressive mood (r = 0.05–0.94, p < 0.05). Regression analysis indicated that low social support stressor was the strongest predictor of depressive mood (β = 0.21), while working challenges, personal affairs, and cognitive factors also positively predicted depressive mood. The mediating model showed that expression inhibition played a partial mediating (promoting) role between stressors and depressive mood, accounting for 3.13% of total variance. The moderating model showed that parent-child alienation played a moderating role in the model (β = 0.01, p < 0.001); a lower level of parent-child alienation effectively alleviated the impacts of stressors on depressive mood. Stressors (working challenges, personal affairs, cognitive factors, and especially low social support) positively predict the depressive mood of long-term high-altitude workers in China. Expression inhibition plays a promoting mediation in the relationship between stressors and depressive mood. A good parent-child relationship alleviates the negative impact of stressors on depressive mood. Findings provide new empirical support for diathesis-stress theory and attract further attention to less expression inhibition and better parent-child relationships in depression prevention.
Lost in Thought or Just Lonely? Everyday Cognitive Competence in Middle Adulthood
Field: PSYCHOLOGY

Everyday cognitive competence refers to the ability to manage cognitively demanding tasks essential for maintaining functional independence. While cognitive abilities are well explored in explaining individual differences in everyday cognitive competence, growing attention has been directed toward the impact of non-cognitive factors like loneliness. This study aims to investigate how executive function (EF) components—updating, inhibition, and task shifting—predict everyday cognitive competence and whether loneliness explains the additional variance beyond EF processes. To account for the multifaceted nature of everyday cognitive competence, both performance-based (Everyday Problems Test—EPT) and self-reported measures (Cognitive Failures Questionnaire—CFQ) were administrated. The sample included 176 middle-aged adults (ages 43–65), a group suitable for investigating predictors of everyday cognitive competence in the early stages of cognitive aging. The findings reveal that updating is a significant predictor of the performance on the EPT, while loneliness is not. When self-reported cognitive lapses are considered, loneliness emerges as a significant predictor. The lack of a relationship between the EPT and CFQ, along with their differing associations with EF, loneliness, and sociodemographic factors, suggests they assess distinct aspects of everyday cognitive competence. This highlights the need for a multidimensional assessment framework to gain a comprehensive understanding of everyday cognitive competence in middle-aged adults.
Beautimeter: Harnessing GPT for Assessing Architectural and Urban Beauty Based on the 15 Properties of Living Structure
Field: AI

Beautimeter is a new tool powered by generative pre-trained transformer (GPT) technology, designed to evaluate architectural and urban beauty. Rooted in Christopher Alexander’s theory of centers, this work builds on the idea that all environments possess, to varying degrees, an innate sense of life. Alexander identified 15 fundamental properties, such as levels of scale and thick boundaries, that characterize living structure, which Beautimeter uses as a basis for its analysis. By integrating GPT’s advanced natural language processing capabilities, Beautimeter assesses the extent to which a structure embodies these 15 properties, enabling a nuanced evaluation of architectural and urban aesthetics. Using ChatGPT4o, the tool helps users generate insights into the perceived beauty and coherence of spaces. We conducted a series of case studies, evaluating images of architectural and urban environments, as well as carpets, paintings, and other artifacts. The results demonstrate Beautimeter’s effectiveness in analyzing aesthetic qualities across diverse contexts. Our findings suggest that by leveraging GPT technology, Beautimeter offers architects, urban planners, and designers a powerful tool to create spaces that resonate deeply with people. This paper also explores the implications of such technology for architecture and urban design, highlighting its potential to enhance both the design process and the assessment of built environments.
History-Aware Multimodal Instruction-Oriented Policies for Navigation Tasks
Field: AI

The rise of large-scale language models and multimodal transformers has enabled instruction-based policies, such as vision-and-language navigation. To leverage their general world knowledge, we propose multimodal annotations for action options and support selection from a dynamic, describable action space. Our framework employs a multimodal transformer that processes front-facing camera images, light detection and ranging (LIDAR) sensor’s point clouds, and tasks as textual instructions to produce a history-aware decision policy for mobile robot navigation. Our approach leverages a pretrained vision–language encoder and integrates it with a custom causal generative pretrained transformer (GPT) decoder to predict action sequences within a state–action history. We propose a trainable attention score mechanism to efficiently select the most suitable action from a variable set of possible options. Action options are text–image pairs and encoded using the same multimodal encoder employed for environment states. This approach of annotating and dynamically selecting actions is applicable to broader multidomain decision-making tasks. We compared two baseline models, ViLT (vision-and-language transformer) and FLAVA (foundational language and vision alignment), and found that FLAVA achieves superior performance within the constraints of 8 GB video memory usage in the training phase. Experiments were conducted in both simulated and real-world environments using our custom datasets for instructed task completion episodes, demonstrating strong prediction accuracy. These results highlight the potential of multimodal, dynamic action spaces for instruction-based robot navigation and beyond.
Enhancing the Classification of Imbalanced Arabic Medical Questions Using DeepSMOTE
Field: AI

The growing demand for telemedicine has highlighted the need for automated healthcare services, particularly in medical question classification. This study presents a deep learning model designed to address key challenges in telemedicine, including class imbalance and accurate routing of Arabic medical questions to the correct specialties. The model combines AraBERTv0.2-Twitter, fine-tuned for informal Arabic, with Bidirectional Long Short-Term Memory (BiLSTM) networks to capture deep semantic relationships in medical text. We used a labeled dataset of 5000 Arabic consultation records from Altibbi, covering five key medical specialties selected for their clinical relevance and frequency. The data underwent preprocessing to remove noise and normalize text. We employed stratified sampling to ensure representative distribution across the selected medical specialties. We evaluate multiple models using macro precision, macro recall, macro F1-score, weighted F1-score, and G-Mean. Our results demonstrate that DeepSMOTE combined with cross-entropy loss achieves the best performance. The findings offer statistically significant improvements and have practical implications for improving screening and patient routing in telemedicine platforms.
Addressing the associative stigma of psychiatry and psychiatrists: a survey on the attitudes of medical and nursing students and doctors in Verona, Italy
Field: PSYCHOLOGY

Negative societal attitudes toward mental health often contribute to misconceptions and stereotypes about psychiatry, a phenomenon known as “associative stigma”. This stigma can hinder collaboration between psychiatrists and other specialists and deter students from pursuing psychiatry as a career. This study focused on one of the three main components of stigma by examining attitudes toward psychiatry and psychiatrists among medical and nursing students, as well as doctors, and identifying factors that influence these attitudes. A cross-sectional survey was conducted among medical and nursing students at the University of Verona and doctors affiliated to the Medical Professional Association of Verona. Attitudes toward psychiatry were assessed using the Attitude to Psychiatry Scale. Regression analysis evaluated the relationship between participants’ characteristics and their attitudes toward psychiatry and psychiatrists. A total of 511 medical students, 394 nursing students, and 638 doctors participated in the study. While students had generally positive attitudes towards psychiatry, they perceived it as lacking full respect within medial community (84% medical, 76% nursing), having low prestige (63.5% medical, 65.9% nursing), and receiving insufficient encouragement in university courses (39% medical, 41.7% nursing). Doctors also expressed positive attitudes, though to a lesser extent than students. Their primary concerns related to patient care: 81% reported feeling emotionally drained when treating psychiatric patients, and 58.2% felt that patients were not appreciative of the care received. Female students and doctors, students who had taken psychiatric courses, and doctors in non-surgical specialties exhibited more positive attitudes. This study revealed generally positive attitudes towards psychiatry, underscoring its relevance as a medical specialty. However, concerns regarding the discipline’s perceived status and respect within the medical field highlight areas for targeted interventions to enhance its image and encourage greater interest among students and professionals.
Revealing tumor microenvironment communication through m6A single-cell analysis and elucidating immunotherapeutic potentials for cutaneous melanoma (CM)
Field: ONCOLOGY

Background The methylation of N6-methyladenosine (m6A) RNA plays a crucial role in the genetic regulation of various cancers. While m6A modifications have been extensively studied in the tumor microenvironment (TME) of several malignancies, their role in cutaneous melanoma (CM) remains unexplored. Methods Using Non-negative matrix factorization (NMF) analysis on single-cell RNA-seq data (GSE215121) from three CM samples obtained from public databases, 26 m6A RNA methylation regulators were utilized to determine TME subclusters, their expression, and function. Results Six distinct TME cell types were identified and NMF clustering further revealed unique m6A-based subpopulations of cancer-associated fibroblasts and T cells. The prognostic model demonstrated strong predictive capabilities, particularly for fibroblast and T cell m6A clusters, and highlighted COL3A1 as a critical regulator of melanoma-fibroblast interactions. Conclusion Highlighting the COL3A1 gene as a critical link and potential therapeutic target in melanoma could offer new avenues for targeted therapies and improve prognostic assessments in cutaneous melanoma.
“Somewhat of an Adult”: Understanding the “Dance” of Competing Tensions Parents Manage While Caring for an Adolescent or Young Adult (AYA) Diagnosed with Hematologic Malignancy
Field: ONCOLOGY

Background: Parents supporting AYAs with blood cancer juggle dual, competing roles as cancer caregiver and parent, which may heighten distress as they feel pulled simultaneously in two opposing directions. Likewise, AYAs encounter paradoxical needs as they revert to being more dependent on their parents to prioritize their survival while their developmental trajectory toward independence is disrupted. Parents need help understanding the underlying tensions they face in caregiving to reduce their distress and promote their connectedness with their AYA. Using a dialectical lens, we identified tensions parents encountered while caregiving in three contexts (clinical, family, and online communication) to inform a targeted psychosocial intervention. Methods: In partnership with The Leukemia & Lymphoma Society, we recruited 20 parents for in-depth interviews. Parents cared for adolescents aged 15–18 (n = 10) or emerging adults aged 19–29 (n = 10) diagnosed >3 months prior and in active treatment or within 2 years since treatment ended. Transcripts were thematically analyzed. Results: Parents described four ongoing tensions they needed to negotiate as they cared for their AYA: (1) being the driver versus passenger in their child’s care; (2) coping with cancer together as a family versus separately; (3) deciding to reveal versus conceal information; and (4) expecting normative developmental and disease trajectories versus disrupted trajectories. These tensions characterize the complex caregiving “dance” parents navigate in all three care contexts. Conclusions: Psychosocial education can normalize these tensions for parents to promote healthier coping and reduce distress while enhancing connectedness with their AYA. As caregiver–patient outcomes are interrelated, it may improve AYAs’ well-being.
Oncologic Outcomes of Young Breast Cancer Patients According to Tumor Biology
Field: ONCOLOGY

Background/Objectives: Young women frequently present with more aggressive breast cancer tumors. This retrospective study analyzed the oncological outcomes of patients under the age of 40 according to the tumor biology. Methods: Group comparisons were performed via the log-rank test. Recurrence and survival rates are presented according to the Kaplan–Meier method. Results: In total, 88 women (mean age 36) were included, but two presented with bilateral cancer, resulting in 90 tumors. Triple-negative carcinoma was most common, with 26.7% (n = 24); 11.1% (n = 10) were luminal A; 23.3% (n = 21) were luminal B HER2-negative; 15.6% (n = 14) were luminal B HER2-positive; and 6.7% (n = 6) were HER2-positive (non-luminal). Moreover, 26.1% (n = 23) of patients experienced recurrence (mean 40 months), with the highest recurrence rate in the HER2-positive (50%) and triple-negative (30.4%) groups. The 3- and 5-year recurrence-free survival rates were 84.9% and 77.3%, and the overall survival rates were 93.1% and 90.3%, respectively. No statistically significant differences in oncological outcomes were observed (p = 0.164). Conclusions: The results show that young women tend to have triple-negative and fast-growing breast carcinomas, with worse overall survival in the triple-negative group. More research is needed on the pathomechanisms of breast cancer development in young women, especially those leading to disease progression and resistance to therapy.
Psychometric Properties of the Adverse Childhood Experiences Abuse Short Form (ACE-ASF) for Ecuadorian Youth
Field: PSYCHOLOGY

Adverse childhood experiences, such as abuse, are a risk factor for mental health and poor socio-emotional development in adulthood. Assessing these experiences in specific populations allows for the identification of patterns and the implementation of preventive interventions. Objective: To evaluate the psychometric properties of the abbreviated version of the Adverse Childhood Experiences Abuse Form (ACE-ASF) in Ecuadorian youth, aiming to ensure the validity, reliability, and consistency of the instrument in accurately measuring abuse dimensions in this Ecuadorian population. Methodology: An instrumental study was conducted on the psychometric properties of the eight-item ACE-ASF, applying it to a sample of 840 university students (52.1% females and 47.9% males). The evaluation focused on analyzing the factorial structure and internal consistency of the instrument in this sample. Results: The two-factor model showed a satisfactory fit across all levels of invariance (configural, metric, scalar, and strict), with acceptable fit indices (CFI, TLI, GFI, RMSEA, and SRMR). The internal consistency was adequate, as assessed using the McDonald’s omega and Cronbach’s alpha coefficients. Convergent and discriminant validity were confirmed using the AVE and HTMT indices, ensuring proper differentiation between the dimensions assessed. Conclusion: The ACE-ASF proved to be a valid and reliable instrument for assessing abuse experiences in Ecuadorian youth. Its two-factor structure reflects distinct yet related dimensions, providing a useful tool for identifying adverse childhood experiences in this population.