Aim Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by social deficits and repetitive behaviors, yet prognostic biomarkers remain elusive. This study investigated the interplay between glymphatic function and functional network connectivity (FNC) in ASD and their longitudinal associations with clinical outcomes.Method This combined cross-sectional and two-year prospective longitudinal study included 50 ASD children and 50 controls. Glymphatic function was assessed using the along the perivascular space (ALPS) index and global blood-oxygen-level-dependent to cerebrospinal fluid (gBOLD-CSF) coupling, alongside FNC analysis.Results Cross-sectionally, ASD participants showed significantly reduced ALPS index, gBOLD-CSF coupling, and widespread FNC reductions. Longitudinally, among the 40 ASD participants who completed follow-up, glymphatic function increased over time. Greater increases in ALPS were correlated with greater reductions in ADOS-CSS. In the symptom-improved subgroup, four FNC connections (including DMN-DAN) increased over time. In contrast, no consistent pattern was found in the non-improved group. Baseline inter-network connectivity measures were associated with ADOS-CSS reduction in univariate analyses, but the multivariate model was not significant. Mediation analysis showed an indirect association between baseline gBOLD-CSF coupling and long-term ADOS-CSS reduction via DMN-DAN FNC reduction (indirect effect = -0.22, 95% CI [-0.42, -0.07]).Conclusion These findings indicate that glymphatic function and FNC are altered cross-sectionally and improve longitudinally in parallel with symptom changes in ASD and suggest that baseline gBOLD-CSF coupling is indirectly associated with long-term clinical improvement through DMN-DAN connectivity. Together, these results highlight the potential of glymphatic and functional connectivity measures as prognostic imaging markers in ASD.
Abstract Self‐harm and suicidal behavior are commonly framed as failures of emotion regulation, yet the emotions that make the body the target of harm remain under‐specified. This narrative review synthesizes evidence on self‐disgust as a candidate mechanism in non‐suicidal self‐injury (NSSI) and in suicidal ideation and behavior. Self‐disgust is an aversive self‐directed emotion organized around the appraisal of the self, and often the body, as revolting or contaminated. Cross‐sectional studies consistently link self‐disgust with NSSI, suicidal ideation, and suicide‐risk scores, and qualitative accounts place it at the center of some suicidal crises. Longitudinal studies from China suggest it mediates reciprocal links between emotional abuse and suicidal ideation and a path from body‐image concerns to NSSI. Two prospective studies testing different roles did not support them, and the only induction study of self‐harm urges is equivocal. In some studies, self‐disgust explains variance beyond depression and constructs of the interpersonal theory of suicide. Its boundaries with shame and self‐criticism are contested, and, across disorders, associations shrink when other negative self‐referential emotions are controlled for. The central proposal, that the contamination‐and‐elimination logic of disgust explains why distress is enacted on the body, builds on earlier suggestions and remains an untested hypothesis. On this hypothesis, self‐disgust is an embodied emotion whose action tendency of cleansing and removal may correspond to the phenomenology of cutting and, in some people, to a wish to eliminate a self experienced as contaminated. Implications for assessment and intervention, which remain untested, are outlined with falsifiable predictions for research.
Abstract Background Aphasic status epilepticus (ASE) is a subtype of nonconvulsive status epilepticus characterized by aphasia as its primary ictal manifestation. Although psychiatric symptoms are uncommon in ASE, they may obscure the diagnosis when present. We report an atypical case, presenting predominantly with agitation and irritability, which was rapidly diagnosed as ASE by electroencephalography (EEG) based on the abrupt symptom onset and neurological history. Case Presentation A 49‐year‐old right‐handed woman with alcohol use disorder was referred to our psychiatric hospital because of agitation, irritability, and disorganized thinking. Approximately 2 months before presentation to our hospital, she developed a generalized tonic–clonic seizure 3 days after sustaining a head injury. A left posterior fossa subdural hematoma was diagnosed, and burr‐hole evacuation was performed at a general hospital. She continued rehabilitation; however, 6 days before admission to our hospital, she suddenly developed incoherent speech with agitation and irritability, prompting referral to our psychiatric hospital. Neurological examination revealed sensory aphasia. Given the history of brain injury and abrupt symptom onset, EEG was performed and demonstrated left‐dominant periodic lateralized epileptiform discharges, confirming ASE. Antiseizure treatment resolved the EEG abnormalities and aphasia; however, aphasia, agitation, and irritability recurred with periodic lateralized epileptiform discharges. The symptoms improved with intravenous diazepam, and no recurrence was observed for >2 years following optimization of antiseizure medication. Conclusion ASE may present predominantly with psychiatric symptoms and be misdiagnosed as a primary psychiatric disorder. Recognizing symptom chronology and epileptogenic background is essential for prompting EEG evaluation and early diagnosis.
The rapid diffusion of generative artificial intelligence chatbots has repositioned these systems from productivity tools to interlocutors used for emotional support, companionship, and mental health guidance. This critical narrative review has three aims: to give mental health professionals a concise technical account of large language models; to separate the evidence and risks attached to four distinct system classes, protocolized therapeutic chatbots, clinically bounded generative systems, general‐purpose large language models used as informal therapy, and companion platforms; and to examine clinical, ethical, and regulatory implications. Literature was identified through non‐systematic, iterative database and preprint‐server searches between March and July 2026, supplemented by citation tracking and policy documents. No prespecified eligibility or screening protocol was used; the comparative claims are therefore provisional. Protocolized and clinically bounded systems carry the strongest evidence, including a meta‐analysis of generative and hybrid chatbots reporting modest short‐term symptom reduction and a randomized trial of an expert‐fine‐tuned therapeutic chatbot; these trials are brief, predominantly waitlist‐controlled, and reliant on self‐report. General‐purpose models and companion platforms may deliver immediate validation and temporary reductions in loneliness, but that evidence is largely observational, qualitative, or short‐term experimental and does not establish sustained benefit. Concerns include emotional dependence, social substitution, sycophantic reinforcement, unsafe responses to suicidal or psychotic content, commercial manipulation, and delusional beliefs temporally associated with sustained use. These systems are not a single intervention class. Their effects appear contingent on clinical structure, relational design, user vulnerability, duration and centrality of use, commercial incentives, and safeguards.
