Major depressive disorder (MDD) accounts for a substantial share of global disability-adjusted life years and remains inadequately treated despite pharmacological advances. Growing evidence implicates endocrine-disrupting chemicals (EDCs)—particularly phthalates and bisphenols—as environmental contributors to the onset of these conditions. This narrative review examines evidence from PubMed, Scopus, and Web of Science (January 2000–March 2025) on the relationship between early-life exposure to these compounds and the development of mood disorders, with emphasis on molecular and neurobiological mechanisms. Phthalates such as di(2-ethylhexyl) phthalate (DEHP), and bisphenols such as bisphenol A (BPA), are detected ubiquitously in human urine, blood, placenta, and umbilical cord blood. Key mechanisms identified include Nrf2/HO-1-driven oxidative stress and neuronal apoptosis, disruption of calcium signalling and synaptic plasticity via CREB phosphorylation deficits, epigenetic suppression of brain-derived neurotrophic factor (BDNF) via promoter hypermethylation, NF-κB/NLRP3/IL-1β neuroinflammatory cascades, interference with thyroid hormone bioavailability through transthyretin competition, and PPAR-mediated disruption of brain lipid metabolism. Prenatal and early-life exposure has been associated with ADHD, cognitive impairment, autism spectrum disorder, and elevated risk of depressive and anxiety phenotypes in epidemiological cohorts. Psychological vulnerability factors—perceived stress, deficient emotion regulation, and adverse childhood experiences—likely amplify this biological susceptibility through HPA axis sensitisation. Methodological limitations of current evidence, including reliance on single-spot urine samples and residual confounding, are critically appraised. Future research priorities include longitudinal biomonitoring cohorts, brain organoid mechanistic models, and integration of validated psychiatric assessments into environmental health study designs.
M. Lastretti, Andrea Faa, Monica Piras et al.· Environments· 0 citations
Background: Artificial intelligence (AI)-driven conversational systems are increasingly capable of simulating empathy, adapting to individual users, and fostering emotional bonds that blur the boundary between tool and companion. This scoping review maps the extent and nature of published evidence regarding psychological mechanisms underlying emotional reliance on AI chatbots and associated mental health implications. Methods: Conducted in accordance with PRISMA-ScR guidelines, we systematically searched PubMed/MEDLINE, PsycINFO, Web of Science, Scopus, and IEEE Xplore from database inception to March 2026. Two independent reviewers screened records and extracted data using the PCC (Population, Concept, Context) framework. Thematic synthesis was performed to map evidence across psychological, clinical, and developmental domains. Results: Of 1847 records identified, 46 studies met inclusion criteria. Key themes included: (1) the ELIZA effect as a foundational mechanism of human–AI attachment, with documented cases of severe dependency including fatal outcomes; (2) anthropomorphization and artificial intimacy fostered by adaptive, personalized AI design; (3) proposal of Generative AI Dependency (GAID) as a conceptual framework mapping onto behavioral addiction components, pending empirical validation; (4) particular vulnerability of adolescents and lonely individuals to exclusive affective bonds with AI; and (5) potential erosion of human relational capacities, empathy development, and tolerance for interpersonal complexity. Significant gaps were identified in longitudinal research, validated screening tools, and intervention protocols. Conclusions: Emotional reliance on AI represents an emerging clinical phenomenon with addiction-like features requiring specific diagnostic frameworks, evidence-based interventions, and ethical design guidelines. Future research should prioritize longitudinal studies examining developmental impacts and neurobiological investigations of AI-mediated reinforcement mechanisms.
M. Lastretti, M. Manchia, Matteo Fraschini et al.· Psychiatry International· 0 citations
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