Cognition Behaviour Technology

Abstract Immune checkpoint inhibitors (ICI) have revolutionized cancer treatment, but their efficacy has now reached a plateau. ICIs are the first class of treatment targeting the crosstalk between immune and tumor cells, making it crucial to understand the complex interactions within the tumor microenvironment (TME) to enhance therapeutic responses. The elevated consumption of resources by cancer cells, coupled with limited vascularization, often results in a TME that is deficient in nutrients, leading to competition for resources between cancer and stromal cells. Consequently, targeting tumor metabolism has emerged as a promising strategy to improve the efficacy of ICIs. Through metabolomic analysis, we have identified metabolic alterations in melanoma cells that are resistant to ICIs, specifically an increase in arginine synthesis and upregulation of ASS1, the rate-limiting enzyme in this pathway. By using gain and loss of function models, as well as a pharmacological inhibitor specific for ASS1, we demonstrated that modulations in the expression or activity of ASS1 is associated with translational reprogramming, characterized by an inhibition of the cap-dependent mRNA translation mediated through mTORC1/4EBP1 axis. We also demonstrated that targeting ASS1 in vivo , resensitize tumors initially resistant to ICI. Taken together, our results highlight the interaction between modulations of arginine synthesis pathway, mRNA translation reprogramming, antitumor immunity, and restauration of sensitivity to anti-PD-1. Our work also demonstrates the therapeutic potential of targeting arginine synthesis pathway, and especially ASS1, to offer new treatments to patients suffering from cutaneous melanoma resistant to ICIs.

Secondary resistance to the amino-acid-depleting agent L-asparaginase (ASNase) remains poorly understood. Using ASNase-sensitive B-cell lymphoma (BCL) models, we investigate tumor relapse during treatment. Through in vitro and in vivo metabolic profiling, here we show that ASNase triggers a metabolic reprogramming characterized by increased de novo serine biosynthesis driven by phosphoglycerate dehydrogenase (PHGDH). This response mitigates treatment-induced oxidative stress and associated DNA damage, enabling malignant cells to survive. We evidence that ASNase-treated malignant cells exhibit features of replication stress and increase activity of poly(ADP-ribose) polymerase (PARP), revealing a dependence on DNA repair. Combining ASNase with the clinically approved PARP inhibitor Olaparib enhances the antineoplastic effect of each monotherapy in vitro and in vivo. Moreover, this combination shows effectiveness in homologous recombination-proficient colorectal cancer cells, suggesting broader therapeutic potential. Overall, our study identifies tumor metabolic and genomic vulnerabilities induced by ASNase and supports a rational combination strategy using clinically approved drugs.

Purpose Mobile applications (apps) have become integral to daily life, yet fostering continued user engagement remains a challenge. This study aims to investigate factors influencing continuance intention by comparing goal-directed (e.g. educational) and experiential (e.g. gaming) apps. Design/methodology/approach Structural equation modeling analysis was applied to data extracted from 452 valid survey responses collected from users of popular Chinese mobile apps to determine the mediating effects of inner and social self-relevance and positive and negative emotions and the moderating role of app types (goal-directed vs experiential). Findings Our findings indicate that utilitarian value and social value positively influence both inner and social self-relevance, which in turn positively influence positive emotions, while hedonic value primarily impacts inner self-relevance. Inner self-relevance slightly affects brand love, while negative emotions negatively influence brand love. Furthermore, inherent (hedonic) value has a stronger influence on positive emotions than utilitarian value. A mediation analysis confirmed the mediating roles of inner and social self-relevance in the relationship between perceived value and brand love as well as the indirect effects of perceived value on negative emotions mediated via social self-relevance. Furthermore, a multiple-group analysis revealed significant variations in the influence of perceived value on self-relevance, emotions and brand love for goal-directed vis-à-vis experiential apps. Originality/value This study contributes to the literature by comprehensively examining brand love formation in mobile apps, considering both goal-directed and experiential categories. The findings provide valuable guidance for marketers and designers seeking to enhance user engagement and cultivate user-app relationships in a competitive mobile app market.

Speech features extracted from automated remote cognitive assessments correlate with performance on traditional cognitive tasks in individuals at risk of Alzheimer's Disease (AD), demonstrating their potential to support early diagnosis. However, the capability of these features to signal early AD-related brain changes remains less explored. Within the PROSPECT-AD study, 234 participants ranging from cognitively normal to mild cognitive impairment were recruited from the German DZNE longitudinal cohorts DELCODE and DESCRIBE. At home, all participants completed the phone-based and chatbot-guided Semantic Verbal Fluency task (SVF) and the Rey Auditory Verbal Learning Test (RAVLT). Linguistic and acoustic features were automatically extracted from phone call recordings using an AI model to calculate task-specific and composite cognitive scores. Structural MRI, functional MRI, and various paper-and-pencil cognitive scores were collected during cohort visits. We employed multiple linear regression, mixed-effects models, and independent component analysis (ICA), followed by voxel-wise post hoc analyses, to assess associations between digital speech-based indicators and: (1) cross-sectional brain atrophy (n=108), (2) longitudinal brain atrophy (n=90), (3) cross-sectional resting-state functional connectivity (n=86), and additionally (4) trajectories of cognitive decline (n=146). SVF correct counts were positively associated with brain volumes in the left temporal pole, left inferior, middle, and superior temporal gyri (The t(100) values ranged from 4.48 to 4.96) in voxel-wise analyses (Figure 1a). Longitudinal analyses indicated that higher SVF correct counts were linked to slower rates of hippocampal and anterior cingulate atrophy (Figure 1b). Functional connectivity analyses suggested that SVF features, such as word frequency, were associated with rsFC areas within the default mode network (The t(71) values ranged from 3.65 to 3.85) (Figure 1c). Higher composite cognitive scores, along with SVF and RAVLT features, were associated with slower cognitive decline, as measured by established paper-and-pencil cognitive assessments, including the Preclinical Alzheimer Cognitive Composite (PACC) 5, SVF, and RAVLT delayed recall (Figure 2). Phone-based cognitive assessments hold promise as a remote and scalable tool for identifying AD-related structural and functional brain changes. They offer predictive value for cognitive trajectories in pre-dementia populations. This approach could aid in identifying individuals at risk while guiding further evaluation, broadening their utility beyond cognitive screening.

BackgroundThe increasing demand for emergency department (ED) services has led to overcrowding, impacting the quality and accessibility of healthcare. The objectives were to evaluate how general practitioners (GPs) manage unscheduled visits, including patients redirected from emergency departments and/or medical dispatch centers, and to identify potential barriers to accepting these patients.MethodsWe conducted a cross-sectional survey in France from April 2020 to March 2021, utilizing a self-administered, web-based, anonymous pre-tested questionnaire distributed among the members of professional society and social network. The questionnaire was divided into three sections, namely: (1) demographics of GP respondents; (2) current organization for handling unscheduled visits, and (3) potential barriers to implementing dedicated schedule slots for patients redirected from EDs. We used multivariable logistic regression to investigate associations between personal and practice characteristics.ResultsA total of 1,317 GPs participated in the survey. The majority were female (59%), aged between 31 and 40 years (43%) and located in semi-rural areas (66%). Overall, 89% reported to allocate specific slots for unscheduled care visits. However, only 16% had their slots open to emergency/dispatch center-referred patients. The majority (83%) of GPs showed no interest in setting aside dedicated slots for ED redirected patients, 62% were against sharing information about their unscheduled visit slots with EDs, and 88% opposed the automatic scheduling of ED patients into their clinics. The main barriers to the implementation of dedicated slots for unscheduled visit were a lack of interest (46%), time constraints (48%), and organizational challenges (9%). GPs with smaller patient bases and those using computerized systems showed greater openness to communicate availability for unscheduled care.ConclusionMost French GPs surveyed, representing approximatively 2% of the overall French GP population, integrate daily slots for unscheduled visits into their practice but they are typically reserved for their existing patient base. The survey further revealed that two-thirds of these GPs are unwilling to communicate the availability of these slots to EDs. Additionally, an even larger proportion would refuse to allow automatic scheduling of ED patients into their clinics if redirection strategies were implemented at their local hospitals.Supplementary InformationThe online version contains supplementary material available at 10.1186/s12875-025-03012-8.

ObjectiveTreatment of incompetent superficial veins can be associated with postoperative complications and pain, potentially impacting on patients’ satisfaction. Early identification of patients at higher risk of complications could help tailor postoperative management. The aim of this study was to develop machine learning models to predict 30-day postoperative outcomes in patients undergoing intervention for superficial venous incompetence.MethodsA database from a prospective vascular registry (Qualivein) was searched from January 2014 until February 2024 to identify patients who underwent superficial venous intervention in France. Data collected included clinical and procedural characteristics and outcomes (pain, physical ability, postoperative complications) during the 30-day follow-up. After feature transformation, an XG-Boost model was used to predict postoperative outcomes. The dataset was randomly split into training (50%) and testing (50%), and four balancing methods were tested.ResultsIn total, 4219 patients were included (mean age, 54 ± 13 years; 34.0% men). The mean pain score at 30-day was 0.52 ± 1.45, the physical ability score was 8.96 ± 2.50, and postoperative complications occurred in 181 patients (4.3%). The best performing model predicted the occurrence of short-term and mid-term pain rebound, with accuracies of 0.824 ± 0.011 and 0.954 ± 0.005, respectively. The model achieved an accuracy of 0.844 ± 0.009 to predict time to recover full physical ability, with a sensitivity of 0.847 ± 0.009 and a positive predictive value of 0.852 ± 0.0008. Thirty-day postoperative complications were predicted with an accuracy of 0.933 ± 0.007.ConclusionsThe machine learning model demonstrated its performances to predict 30-day postoperative outcomes after venous intervention including occurrence of complications, pain, and time to recover physical ability.