This paper examines psychoanalysts' affective and defensive responses to artificial intelligence (AI) through the lens of originary technicity, the philosophical claim that technology is constitutive of the human rather than external to it. Drawing on Freudian theory-particularly the uncanny-alongside object relations and posthumanist thought, the author argues that psychotherapy's moral panic about AI reflects a splitting of the human from the technological that mirrors colonialist Subject/Other dualisms. Prompts are explored as drive derivatives, and the dyadic engagement between user and chatbot is analyzed as a site of unconscious projection and defense mechanisms, including idealization and disavowal. The paper explores how the holding environment of the clinical frame is threatened and potentially transformed by algorithmic systems that model human subjectivity back to us. Winnicott's concept of transitional phenomena offers a less persecutory frame for understanding AI as neither wholly internal nor external, neither purely human nor purely machine. The author encourages psychoanalysis to engage with AI through countertransference awareness rather than reactivity, and to distinguish between technology as such and the capitalist and colonialist systems that deploy it.[1].

Depression and anxiety are prevalent worldwide, yet fewer than 20% of individuals in low- and middle-income countries receive appropriate care. Cultural norms play a significant role in how symptoms are expressed and how individuals seek help. In Nepal, traditional healers are often preferred over mental health specialists. This qualitative study explored how symptom presentation and perceived causes impact treatment-seeking behaviour among adults receiving care for depression or anxiety. Twenty-four participants (13 with depression, 9 with anxiety, and 2 with both conditions) were recruited from Jhapa, Chitwan, and Kailali districts through primary healthcare providers, psychosocial counselors, and mental health specialists. Individual interviews were conducted using the adapted McGill Illness Narrative Interview (MINI) to explore symptom experiences, illness narratives, perceived causes, and help-seeking patterns. Thematic analysis of the data was done using NVIVO software. Participants reported a range of emotional, cognitive, and physical symptoms including fear, anxiety, restlessness, irritability, sadness, and hopelessness. Somatic complaints like headaches, fatigue, and gastrointestinal issues were often interpreted as consequences of psychological stress. Some participants described dissociative experiences, such as detachment, amnesia, or perceptual distortions, leading to panic or self-harm. Stressors mentioned included financial hardships, bereavement, family conflicts, trauma, and culturally ingrained fears. Most participants initially sought help from biomedical providers like private clinics, hospitals, health centers, or health camps with some also consulting traditional healers. Education and caste played a significant role in treatment choices, with individuals with higher education and from higher castes more likely to seek biomedical care first. Gender and age had minimal impact. The study underscores the importance of culturally sensitive, community-based mental health programs to reduce stigma and ensure equitable access to care for depression and anxiety in Nepal.

Short tandem repeat expansions underlie a class of neurological and neuromuscular diseases known as repeat expansion disorders, yet the precise characterisation of these repeats remains technically challenging. Conventional amplification-based methods fail to resolve repeat length accurately due to amplification bias and sequence homogeneity. Here, we present a single-molecule nanopore-based strategy that enables direct quantification of tandem repeats in native RNA. By assembling RNA:DNA nanostructures that encode specific repeat number, we achieve repeat size discrimination with a resolution of 18 nucleotides. Using tandem repeat-containing RNA, we successfully detect and discriminate disease-relevant repeat lengths associated with myotonic dystrophy types 1 (DM1) and 2 (DM2), and congenital central hypoventilation syndrome-1. Finally, we apply our method to total RNA extracted from a DM1 human cell line model, demonstrating its compatibility with complex biological samples. Our approach offers a platform for studying repeat expansion biology at the single-molecule level, with broad implications for diagnostics, clinical research and multiplexed repeat profiling.

Transdiagnostic psychotherapies have been gaining in popularity due in part to their hypothesized ability to address multiple emotional disorders via a single protocol. However, to date, most randomized clinical trials of these treatments have focused on patients with anxiety disorders, or in mixed samples, limiting their use in other diagnoses. The present study compared Transdiagnostic Behavior Therapy (TBT) to disorder-specific therapies (DSTs) in 304 veterans with principal diagnoses of major depressive disorder (MDD), posttraumatic stress disorder (PTSD), or panic disorder. Disorder-specific symptom outcomes and overall impairment were assessed at baseline, mid-treatment, and posttreatment. Structural equation modeling was used to evaluate changes in outcomes over time via latent growth curve models. Support for noninferiority between TBT and the matching DSTs was found in participants with PTSD and panic disorder for the disorder-specific symptom scales and for overall impairment scores across diagnoses. Similar effect sizes were obtained for MDD, although noninferiority could not be concluded because confidence intervals were wide. Similar scores for patient satisfaction and treatment completion also were observed across TBT and the comparison DSTs. Together, these findings suggest that TBT demonstrates comparable efficacy to the established DSTs in addressing symptoms of depressive disorders (MDD), trauma and stressor-related disorders (PTSD), and the anxiety disorders (panic disorder). Thus, ongoing dissemination and implementation efforts for TBT should be considered for a wider range of diagnoses, easing provider training burden and expanding treatment coverage in clinical settings.

Individuals with social anxiety disorder (SAD) have been found to have distinct patterns of nonverbal synchrony with others. In the present study, we examined whether patterns of nonverbal synchrony differ between individuals with SAD and individuals with panic disorder (PD). We examined diagnostic interviews of 29 individuals with SAD and 22 individuals with PD, and assessed nonverbal synchrony using motion energy analysis (MEA). We divided interviews into 10 segments and derived nonverbal synchrony indices for each segment to capture changes in nonverbal synchrony over the course of the interview. According to our first hypothesis, we found that nonverbal synchrony was best modelled by a sinusoidal model (r[2] = .59) which explained significantly more variance than linear, quadratic and logarithmic models. This suggests that nonverbal synchrony is best characterized by a repeating pattern of increases and decreases. According to our second hypothesis, we found that sine wave amplitudes were greater among individuals with SAD compared to those with PD. Thus, individuals with SAD experienced greater fluctuations in nonverbal synchrony during the interview, compared to individuals with PD. We discuss these findings in the context of models of SAD and models of synchrony, as well as suggest implications for research and clinical practice.

Oil and gas pipeline accidents not only caused casualties, economic losses and environmental pollution, but also brought great panic to the public. In order to prevent and reduce oil and gas pipeline accidents, it is necessary to study the main causes of oil and gas pipeline accidents. Its purpose is provide targeted safety measures for accident prevention and control. In this article, the main causes of oil and gas pipeline accidents based on improved TOPSIS method are studied. Firstly, a causal network of oil and gas pipeline accidents based on complex network theory is constructed. Secondly, by analyzing network importance evaluation indicators of the nodes, the determination of the main causes of oil and gas pipeline accidents are transformed into the multi-attribute decision-making evaluation of the importance of accident causal network nodes. Thirdly, a main causes determination method for oil and gas pipeline accidents based on improved TOPISIS method is proposed. The proposed method combines complex network theory, multi-attribute decision theory and improved TOPSISI method, and can address the issue of the significant impact of the correlation between node importance evaluation indicators in the causal network of oil and gas pipeline accidents on decision-making results. Subsequently, the method is applied to the study of main causes and preventive measures of an oil and gas pipelines in central China. Based on the mentioned analysis, targeted safety measures are put forward to prevent oil and gas pipeline accidents. Therefore, this study can provide decision-making basis for oil and gas pipeline accidents safety management.

Panic attacks (PAs) are acute anxiety episodes that are pervasive, with one in 10 individuals having experienced a PA in the past year. PAs impair daily functioning and are associated with an increase in emergency room visits and suicide attempts. Despite their impact, the unpredictable nature of PAs makes them challenging to manage. PAs are transdiagnostic, occurring in individuals across and without a mental health diagnosis. However, prior work has largely focused on PA indications within individuals with panic disorder. This study identifies PA risk factors from over 6 months of passive sensing data recorded by Oura Rings in 182 young adults with and without adverse childhood experiences and psychiatric diagnoses, beyond just panic disorder. Our findings reveal that changes in Oura Ring-derived measures are associated with next-day PAs, with distinct associations observed across different mental health diagnoses. For individuals with panic disorder, the likelihood of PA increases with time spent inactive. For those with depression, the likelihood of PA increases with decreased variation in nightly respiratory rate, decreased rapid eye movement sleep, and increased time spent in high-intensity activity. For those without a mental health diagnosis, the likelihood of PA increases with decreased heart rate variability. Data aggregation window sizes that capture the associations with PA risk vary by diagnosis and the type of feature, suggesting that cumulative physiological patterns from windows up to 7 days before a PA contribute to onset. These findings point to the possibility that continuous monitoring of panic attack risk could one day support preventive mental health intervention.

Obsessive compulsive disorder (OCD) is significantly heritable, but only a fraction of the contributory genetic variation has been identified, and the molecular etiology involved remains obscure. Identifying rare contributory variants of large effect would be an important milestone in helping to elucidate the mechanisms involved. Analysis of densely affected pedigrees is a potentially useful strategy to bypass the sample size challenges of standard case-control approaches. Here we performed whole genome sequencing (WGS) of 25 individuals across two multiplex OCD pedigrees. We prioritised rare variants using a Bayesian inference approach which incorporates variant pathogenicity and co-segregation with OCD. In the first pedigree, we identified a highly deleterious missense variant in NPY5R , carried by the majority of affected individuals. This gene is brain-expressed and has previously been implicated in panic disorder and internet addiction GWAS studies. In the second pedigree, we identified a large deletion of DLGAP1 and a missense variant in MAPK8IP3 , that perfectly co-segregated in a specific branch of the family: both genes have previously been implicated in OCD and autism. Both genes contribute to a protein interaction network including ERBB4 and RAPGEF1 which we had previously identified in a large Tourette Syndrome pedigree. Our analysis suggests that both energy homeostasis and downstream signalling from the post-synaptic density may both be important avenues for future research.

Hyperarousal is a common symptom key to the severity of insomnia-, depression-, anxiety-, posttraumatic stress- and attention deficit/hyperactivity disorders. Hyperarousal however remained a loosely defined construct assessed with different questionnaires in different disorders. Here we addressed the unresolved question whether hyperarousal may be one common transdiagnostic construct or rather has multiple, possibly disorder-specific, dimensions.