Obesity and metabolic syndrome promote malignancies through chronic inflammation and sustained activation of insulin and insulin-like growth factor-1 (IGF-1) signaling. Skeletal muscle is central to this tumor-promoting milieu because it governs insulin-stimulated glucose disposal, lipid oxidation, and endocrine crosstalk. This narrative review explores whether melatonin signaling in skeletal muscle, particularly via melatonin receptor 2 (MT2), represents a modifiable node within the obesity-cancer axis. Experimental evidence indicates that melatonin activates MT2-linked Gi/o and calcium-sensitive pathways converging on phosphoinositide 3-kinase-protein kinase B (PI3K-Akt), extracellular signal-regulated kinases (ERK), and calcium/calmodulin-dependent protein kinase II-adenosine monophosphate-activated protein kinase-peroxisome proliferator-activated receptor gamma coactivator 1-alpha (CaMKII-AMPK-PGC-1 alpha) signaling. These pathways enhance insulin sensitivity, mitochondrial function, and lipid partitioning while reducing myosteatosis and cellular stress. By improving muscle quality, melatonin may lower systemic insulin and IGF-1 drive and inflammatory adipokine tone that fuel tumor-promoting PI3K-Akt-mammalian target of rapamycin (mTOR) signaling. However, human evidence remains limited and timing-dependent. Melatonin exposure in the fed state or near carbohydrate intake may worsen glycemia, particularly in carriers of melatonin receptor 1B (MTNR1B) risk alleles. Chronobiology-informed, genotype-guided trials with detailed muscle phenotyping and cancer-relevant endpoints are warranted.
Introduced non-native ungulates can alter ecosystem processes and generate management conflicts. Thus, understanding spatial behavior and habitat use in invaded landscapes is highly relevant. We investigated seasonal home range and habitat selection of the natively African mountain species aoudad Ammotragus lervia, introduced in the Southern Dinaric Alps, Croatia, using GPS telemetry data. We used Kernel Density Estimates to estimate seasonal home range size and assessed habitat selection in several temporal scales through integrated Step Selection Analysis. Aoudad exhibited marked seasonal variation in home range size, with more restricted space use during the warm period, potentially suggesting aggregation in more favorable microhabitats under drier conditions. Habitat selection revealed consistent preference for high elevations and steep slopes, while the species avoided north facing and east facing aspects and areas with high tree cover density in both warm and cold seasons. During the night, avoidance of tree covered areas intensified and selection shifted towards steeper terrain, consistent with patterns expected under increased perceived predation risk. Weather conditions further modulated habitat selection, with temperature and wind influencing selection of slope and elevation, respectively. Overall, our findings support the capacity of the African aoudad to persist under Mediterranean mountain conditions.
As cities expand, natural and semi-natural habitats are increasingly restricted in extent and connectivity, posing major challenges for biodiversity conservation. Urban parks, as nodes of green infrastructure, improve ecological connectivity in the urban landscape, yet their functional role in supporting urban plant communities remains challenging to quantify. This study aimed to investigate whether differences in the functional role of urban parks are reflected by their spatial location within the green infrastructure. We applied a bipartite species-park network approach to assess the role of urban parks in supporting plant species in three historic cities in north-eastern Italy. In 2024, we surveyed 57 parks, recorded vascular plant species in nested plots and measured park attributes including area, distance to the city centre, distance to other parks and tree canopy cover. Species–park networks were used to quantify the functional role of each park through park specialisation, importance, compositional representativeness, and colonisation potential. Statistical models showed that parks further from the city centre supported richer plant communities and hosted species more dependent on individual parks, while parks at intermediate distances from the centre acted as compositional links between parks closer and further from the city centre. Parks with greater tree canopy cover tended to host species that achieved comparatively higher local cover but showed reduced compositional representativeness to other parks. Our results revealed that the functional role of parks in supporting plant communities was strongly associated with their spatial location within the green infrastructure, providing insights for urban biodiversity conservation and landscape planning.
There has been a noticeable increase in the prevalence of mental health issues, prompting research into the relationship between mental health and people's implicit theories about their intelligence, or their mindsets. This study investigated the relationships between mindset, well-being, and depressive symptoms. A positive relationship between a fixed mindset and depressive symptomatology (H1) was hypothesised. Additionally, H2 assumed that well-being and mindset were good predictors of depressive symptomatology. The study comprised a sample of 874 users of the Slovene online platform 'Positive Psychology for a Better Life'. The online survey included measures of mindset (the Revised Implicit Theories of Intelligence (Self-Theory) Scale), well-being (the Mental Health Continuum-Short Form [MHC-SF]), and depressive symptomatology (the Center for Epidemiologic Studies Depression Scale [CES-D]). The results showed a positive correlation between a fixed mindset and depressive symptomatology, thus supporting H1. To test whether well-being and mindset are good predictors of depressive symptomatology, discriminant analysis was performed. There was a significant effect of the independent variables on the dependent variable. The model correctly classified 76.9% of participants based on their personal and social antecedents of well-being and mindset, as measured by CES-D scale scores, so H2 was also supported. In conclusion, mindset is reflected in one's perception of mental health. Therefore, it is crucial to create growth mindset initiatives and curricula in education. Our analysis shows that the MHC-SF and Implicit Self-Theory scales are adequate for predicting depression in Positive Psychology Platform users. These findings could stimulate future research in this area.
In hospitality SMEs, digital transformation is increasingly linked to sustainability goals. However, evidence on how corporate social responsibility (CSR) relates to the adoption of artificial intelligence (AI) in owner-managed firms remains limited. This study examines CSR practices, managerial attitudes toward AI, and AI adoption in micro and small restaurant SMEs in a small European Union (EU) economy. Using survey data from 157 Slovenian restaurant SMEs and structural equation modelling, CSR is conceptualised as an enacted, practice-based orientation. At the same time, managerial attitudes toward AI are modelled as the key mechanism preceding adoption. Results reveal an asymmetric relationship between CSR and AI. Employee-related CSR practices, which are mainly institutionalised, do not significantly influence managerial AI attitudes. In contrast, environmental CSR practices are negatively associated with AI attitudes, indicating more cautious evaluations among environmentally responsible managers. Managerial attitudes toward AI are positively and significantly associated with AI adoption, confirming their central role in adoption decisions. Financial performance, measured by objective revenue data, does not emerge as a direct outcome of AI adoption but rather operates as a contextual condition shaping how CSR practices relate to managerial attitudes and how those attitudes translate into adoption decisions. Overall, the findings indicate that CSR does not uniformly translate into managerial attitudes toward AI and subsequent AI adoption in restaurant SMEs.
