Antonio Maria D'ONofrio

Central nervous system (CNS) tumors account for nearly one third of pediatric cancers and remain the leading cause of cancer-related mortality in children. Cranial radiotherapy is a cornerstone of treatment for many high-grade and embryonal brain tumors, often in combination with surgery and chemotherapy. However, improved survival has been accompanied by a growing burden of late neurocognitive, emotional, social, and endocrine sequelae. Damage to hippocampal neural stem and progenitor cells partly drives radiation-induced cognitive decline, which leads to reduced neurogenesis and increased gliogenesis. Lithium has emerged as a promising strategy to protect or repair the irradiated brain through its neuroprotective, anti-inflammatory, anti-apoptotic, and pro-neurogenic effects. Preclinical evidence supports its potential to mitigate radiation-induced brain injury. In cellular models, lithium appears to protect neural progenitors and hippocampal neurons from irradiation-related damage but does not confer comparable protection to tumor cells. In juvenile rodent models, lithium administration before, during, or after cranial irradiation has been associated with reduced apoptosis in hippocampal neurogenic regions, preservation or restoration of neurogenesis, attenuation of neuroinflammation, and improvement of cognitive and behavioral outcomes. Importantly, delayed lithium treatment has also shown restorative effects, indicating a potential role as a neuroregenerative strategy for survivors with late effects. Mechanistically, these benefits appear to arise from modulation of apoptotic pathways, GSK-3β-related signaling, neurogenic cell fate, and epigenetic programs that promote neuronal differentiation over gliogenesis. These data have provided the rationale for early clinical translation and ongoing trials now assessing whether lithium can improve neurocognitive outcomes after cranial radiotherapy in pediatric brain tumor patients. This narrative review summarizes the preclinical basis and emerging clinical evidence for lithium as a potential adjunct to radiotherapy while discussing key unresolved issues, including optimal timing, treatment duration, tumor safety, and patient selection.

Self-care and illness perception are key determinants of adaptation to inflammatory bowel disease (IBD), but their relationship may be heterogeneous and poorly captured by average-level associations. This multicenter cross-sectional study examined whether self-care behaviors were associated with illness perception and explored whether distinct patient profiles could be identified from their combined behavioral and cognitive-emotional patterns. Between April and June 2024, adult patients were recruited consecutively from nine Italian IBD units and completed validated measures of self-care, illness perception, self-care self-efficacy, and psychological distress. Structural equation modeling was used to test the association between self-care domains and illness perception, followed by unsupervised cluster analysis. Among 450 participants with complete data, the structural equation model showed satisfactory fit, but no self-care domain was significantly associated with illness perception. Four clinically interpretable profiles emerged: Engaged Copers, Overwhelmed and Passive, Detached and Vulnerable, and Minimizers with Functional Engagement. The profiles differed markedly in illness perception and self-care behaviours, with large effect sizes, whereas anxiety and self-care self-efficacy showed statistically significant but small between-profile differences. No statistically significant omnibus differences were observed in generational distribution, exercise habits, or disease activity. These findings suggest that self-care and illness perception are not related through a simple linear association. Person-centered profiling may support tailored self-management education and psychological assessment in routine IBD care.

Introduction: Bipolar Disorder (BD) presents with heterogeneous longitudinal cycling patterns, including Manic-Depressive-free Interval (MDI), Depressive-Manic-free Interval (DMI), and Irregular (IRR) cycles. Studies investigating how these cycle types affect clinical course re-main limited. This study aimed to examine a large, well-characterised sample of patients with BD types I (BD-I) and II (BD-II). Methods: Life charts were used to determine the type of cycle, collecting information on first affective episode type, hospitalisations (presence or absence), suicidal ideation/attempts, psychiatric family history, seasonality, agitated depression, predominant polarity, and diagnostic subtype (BD-I vs. BD-II). The impact of cycle type on clinical course was analysed through univariate and multivariate models. Results: Of 378 BD patients, 140 (37.0%) had MDI cycles, 92 (24.3%) had DMI cycles, and 146 (38.6%) had IRR cycles. Multivariate analyses showed MDI patients were more likely to have a manic onset compared to DMI and IRR (p < 0.001). They also showed a higher likelihood of hypomanic onset compared to DMI (p < 0.001). Conversely, DMI was associated with a depressive onset relative to MDI and IRR (p < 0.001). Seasonality was more frequent in patients with regular cycles (MDI and DMI) compared to IRR (p < 0.001). Hospitalisations were more frequent in MDI and DMI cycles compared to IRR, but the association survived only for MDI in multivariate analysis. MDI patients had a higher prevalence of manic predominant polarity and lower rates of depressive predominant polarity compared to both DMI and IRR (p < 0.001). A BD-II diagnosis was significantly more frequent in DMI and IRR (p < 0.001), and a BD-I diagnosis was more prevalent in MDI (p < 0.001). Discussion: Cycle type affected the BD clinical course, with MDI tending to show more frequent hospitalisations, BD-I diagnosis, and manic predominant polarity, while DMI and IRR patients had more BD-II diagnoses. Conclusion: Findings underscore the importance of classifying BD based on cycle patterns and suggest that taking into account these patterns may support more personalised treatment planning and improve clinical outcomes.

Background/Objectives: Autistic traits are distributed dimensionally across psychiatric populations, yet their systematic assessment in mood and psychotic spectrum disorders remains limited. While elevated autistic traits have been documented in schizophrenia spectrum disorders, evidence in bipolar disorder (BD) and major depressive disorder (MDD) is scarce, and no studies have applied the clinician-rated PANSS Autism Severity Score (PAUSS) to mood disorder populations. This study aims to investigate the presence and severity of autistic traits across psychotic spectrum disorder (PSD), BD, and MDD in an outpatient sample using the PAUSS. Methods: In this cross-sectional naturalistic outpatient study, clinically stable adult patients with MDD, BD, or PSD, without autism spectrum disorder, were assessed with the Brief Psychiatric Rating Scale (BPRS) and PAUSS. Group comparisons, adjusted models, correlation analyses, principal component analysis, and multinomial logistic regression were performed. Results: A total of 165 patients were included (MDD, n = 84, BD, n = 45, PSD, n = 36). Compared with the mood disorder groups, PSD patients were younger and showed higher BPRS scores. PSD was also characterized by significantly higher PAUSS total, social, and communication scores, whereas PAUSS RRB did not differ in univariate analyses. In the overall sample, BPRS severity correlated positively with all PAUSS dimensions, while age showed only weak or non-significant associations. Diagnosis-stratified analyses revealed that the association between psychopathology and autistic traits was present in MDD and BD, but not in PSD. PCA showed that autistic trait dimensions converged on a broad common profile and differed across diagnostic groups, with PSD showing the most distinct pattern. In multinomial logistic regression, higher BPRS, higher PAUSS social and communication scores, and younger age independently distinguished PSD from MDD and BD; PAUSS RRB showed an inverse association only in the multivariable model. Conclusions: This study supports a transdiagnostic perspective on autistic traits in adult psychiatric populations, highlighting disorder-specific differences across diagnostic categories. Social and communication impairments emerged as key dimensions distinguishing PSD from mood disorders. Assessing autistic traits in psychiatric settings may improve diagnostic precision and inform personalized, stratified treatment approaches.

Background and aimChildhood trauma is a major transdiagnostic risk factor for mood disorders, whereas resilience may mitigate its long-term impact, yet their domain-specific interplay remains poorly defined. This study examined the multidimensional associations between childhood trauma and resilience in major depressive disorder, bipolar disorder, and healthy controls. We tested whether specific trauma subtypes differentially predict distinct resilience domains across diagnostic groups.MethodsIn this cross-sectional study, 300 participants (200 patients with mood disorders and 100 healthy controls) were included. Childhood trauma was assessed using the Childhood Trauma Questionnaire, and resilience was measured with the Connor–Davidson Resilience Scale, enabling domain-specific analyses of resilience profiles.ResultsPatients with mood disorders showed significantly lower resilience and higher childhood trauma exposure than healthy controls, with no differences between unipolar and bipolar disorder. All resilience domains except Spiritual Influences were reduced in patients. PCA-derived dimensions of resilience and childhood trauma robustly distinguished patients from controls but failed to separate unipolar from bipolar disorder, indicating shared latent vulnerability patterns. Correlation analyses showed inverse associations between childhood trauma and resilience in healthy controls and unipolar depression, but not in bipolar disorder. Across the full sample and within patients only, emotional neglect emerged as the strongest and most consistent independent predictor of reduced resilience, particularly affecting perceived control, personal competence, positive acceptance of change, and spiritual influences.ConclusionA careful assessment of developmental history, including subtle forms of childhood trauma such as emotional neglect, is essential for understanding resilience differences in mood disorders. Identifying these vulnerabilities may help reveal compromised resilience domains and guide more personalized, resilience-oriented interventions.

Background and Objectives: Psychological resilience is increasingly recognized as a determinant of how patients respond to surgical stress, yet its role in perioperative medicine remains poorly defined. This narrative review aims to synthesize current evidence on resilience in surgical populations from a psychobiological perspective, spanning conceptual models, measurement approaches, clinical correlates, biological mechanisms, and intervention strategies. Materials and Methods: This narrative review was conducted to examine psychological resilience in adult surgical populations from an integrated psychobiological and perioperative perspective. A structured literature search was performed in December 2026 using PubMed, Scopus, and PsycInfo, combining resilience-related constructs with surgical, perioperative, biological, and clinical outcome keywords. Eligible publications included observational, longitudinal, interventional, translational, and conceptually relevant studies addressing resilience in adult surgical settings. Evidence was synthesized qualitatively across predefined domains, including conceptualization and measurement of resilience, associations with perioperative outcomes, neuroendocrine and inflammatory mechanisms, and resilience-modulating interventions within perioperative and Enhanced Recovery After Surgery (ERAS) frameworks. Results: Contemporary models conceptualize resilience as a dynamic, context-dependent process supported by interacting psychological, biological, and social factors. In surgical cohorts, higher resilience is consistently associated with better patient-reported outcomes, including quality of life, pain control, and emotional adjustment, and in some studies with survival and functional recovery. Preoperative depression, anxiety, maladaptive coping, and low social support converge as components of a broader “resilience profile” linked to poorer postoperative trajectories. Biologically, resilient phenotypes are characterized by more regulated hypothalamic–pituitary–adrenal and autonomic responses and reduced inflammatory activation. Psychological therapies, prehabilitation programs, and selected pharmacological strategies show convergent, though heterogeneous, signals of benefit and can be interpreted as indirect resilience-enhancing interventions. Conclusions: Resilience appears to be a clinically meaningful, potentially modifiable construct that links psychosocial functioning, biological vulnerability, and postoperative outcomes. Incorporating resilience assessment into preoperative risk stratification and systematically embedding resilience-building strategies within perioperative and ERAS pathways may support more personalized, psychologically informed surgical care. Prospective, multidomain studies are needed to validate measurement tools, clarify mechanisms, and test resilience-targeted interventions in surgical populations.

Background/Objectives: Avoidant/restrictive food intake disorder (ARFID) and psychotic disorders are clinically distinct conditions yet occasionally co-occur in ways that complicate assessment and treatment. ARFID is characterised by avoidance of food due to sensory sensitivities, fear of aversive consequences, or low interest in eating, without body-image distortion. Recent meta-analytic evidence suggests that ARFID affects a substantial proportion of the population and is associated with a considerable social burden. Psychosis is characterised by positive symptoms (hallucinations and delusions), negative symptoms (avolition, blunted affect, and social withdrawal), and cognitive impairments affecting thought, perception, and behaviour. Methods: Across the limited literature, shared mechanisms between ARFID and psychotic disorders appear to converge on pathological avoidance, which may arise from sensory overstimulation, obsessive–compulsive features, or delusional beliefs about food. Case reports indicate that psychosis may both mimic ARFID and exacerbate food avoidance, while severe malnutrition can itself precipitate or worsen psychotic symptoms, blurring diagnostic boundaries. Results: Abnormalities in interoception, sensory sensitivity, and disrupted perception of bodily signals are manifestations of both ARFID and psychosis, suggesting a potential bridging pathway contributing to vulnerability and clinical overlap. Conclusions: Given the paucity of empirical studies and the reliance on isolated case reports, systematic investigation is mandatory and necessary to clarify shared mechanisms, refine differential diagnosis, and guide integrated treatment approaches. Given the heterogeneity of symptoms in comorbid patients, a personalised approach is suggested for treating these patients.

Background: Late-onset depression (LOD) represents a distinct clinical and biological phenotype emerging in the context of global population ageing. This study aims to synthesize current evidence on the epidemiology, risk factors, mechanistic pathways, and therapeutic approaches of LOD, integrating biological, psychological, and social dimensions. Methods: This narrative review synthesizes recent evidence across epidemiology, clinical symptomatology, neurobiology, and treatment. Where conceptually appropriate or empirically overlapping, we incorporate findings from the broader late-life depression (LLD) literature. Results: LOD emerges (as a distinct clinical and biological entity in later life) as a clinically and biologically meaningful presentation of depression in later life, representing a minority of depressive cases. It is defined by prominent apathy, psychomotor slowing, and cognitive impairment, and is closely linked to frailty, medical comorbidity, and heightened dementia risk. Pathophysiological mechanisms converge on vascular, inflammatory, oxidative, and neuroplasticity pathways, while psychosocial adversity further shapes onset and course. Treatment prioritizes efficacy and tolerability amid multiple morbidity; SSRIs and SNRIs are first-line, with pro-dopaminergic or dual-action agents addressing anhedonia and apathy, and neuromodulation or augmentation strategies reserved for resistance. Integrative approaches combining pharmacotherapy, psychotherapy, and lifestyle interventions are essential to optimize outcomes in aging populations. Conclusions: Late-onset depression (is a distinct, biologically and psychosocially driven disorder) represents a biologically and psychosocially enriched subtype in its own within the spectrum of late-life depression, requiring integrated, personalized care. Addressing neurovascular mechanisms, psychosocial adversity, and prevention through coordinated geriatric and psychiatric strategies may improve outcomes in aging populations.