Abstract: Background: Burnout is a significant concern among healthcare professionals, particularly in high-stress environments such as intensive care units (ICUs). While prior research has linked burnout to self-reported stress and psychological distress, objective physiological markers like heart rate variability (HRV) may offer a more reliable assessment of occupational stress and burnout risk. Our previous pilot study suggested an association between HRV and stress; however, it did not incorporate standardized burnout assessments. This study aims to bridge that gap by examining the relationship between HRV, self-reported stress, and validated burnout scales. Additionally, it seeks to identify key predictors of burnout and develop a predictive model for early risk detection. Methods: This cross-sectional observational study included 57 nurses and nursing assistants working in ICUs and general hospital wards. Participants completed validated burnout assessments, including the Cuestionario para la Evaluación del Síndrome de Quemarse por el Trabajo (CESQT; Spanish Burnout Inventory), the Maslach Burnout Inventory (MBI), the Professional Quality of Life Scale (ProQOL), and the State-Trait Anxiety Inventory (STAI). HRV parameters were recorded using a Biosignals Plux system for 10 minutes at rest before the start of the work shift and analyzed with the OpenSignals software. Extracted HRV metrics included the root mean square of successive differences (rMSSD), low-frequency to high-frequency ratio (LF/HF), Standard Deviation 1 and 2 Ratio (SD1/SD2 ratio), and Poincaré area. Statistical analyses involved descriptive statistics, correlation analysis, and group comparisons to examine differences in burnout across workplace conditions, shift types, and shift durations. A logistic regression model with 10-fold cross-validation was developed to predict burnout risk, integrating HRV parameters, psychological distress, and occupational factors. Results: HRV parameters were significantly associated with self-reported stress and burnout indicators, reinforcing their potential role as objective biomarkers of occupational stress. Night shift workers and those with extended work hours exhibited higher burnout levels and greater autonomic dysregulation. The predictive model demonstrated strong accuracy in identifying individuals at risk of burnout. The model integrating HRV parameters, psychological distress, and occupational factors (Model 2) achieved an AUC-ROC of 0.832 (95% CI: 0.735–0.929) and an accuracy of 79.1%, outperforming the model based solely on demographic and psychometric data (Model 1, AUC-ROC = 0.791, 95% CI: 0.685–0.897, accuracy = 76.3%). HRV and psychological stress emerged as key contributing factors. Conclusion: These findings highlight HRV as a promising tool for the objective assessment of burnout risk in healthcare professionals. The predictive model developed provides a framework for early identification of high-risk individuals, enabling targeted interventions to improve well-being and staff retention in healthcare settings. Future research should validate these findings in larger cohorts and assess the long-term applicability of HRV-based monitoring systems in occupational health programs.

Abstract: There is extensive literature covering the use of video games in the assessment and treatment of mental disorders, as well as their harmful effects. A review of research papers published between 2002 and 2023 on this topic was conducted. Video games are useful for assessing cognitive abilities and symptoms of Attention Deficit Hyperactivity Disorder (ADHD). Research on video games as therapeutic tools includes ADHD, cognition, developmental coordination disorder, autism spectrum disorder, affective disorders, and substance use. Within the review of research on the harmful effects of video games, addiction to them stands out, encompassing studies in cognition, genetics, and neuroimaging; the literature also includes the emergence or worsening of violent behaviors, as well as sleep and mood disorders. There has been controversy, with no causal relationship being demonstrated. Conclusions: Video games can be tools for cognitive assessment and treatment of ADHD and other disorders. The long-term effects of video games should be examined.

Abstract: Recent drug enforcement activities have possibly suggested the presence of some calcium channel blocker antihypertensives in association with cocaine. The seizure revealed the possibility that the two drugs might have been used together for some unknown reasons. Hence, this study aimed at investigating the nature and frequency of adverse drug reactions (ADRs) reported in association with the concomitant use of calcium channel blockers (CCBs) and cocaine, using data from the FDA Adverse Event Reporting System (FAERS). After removing duplicate reports, a total of 67 cases involving concomitant use of cocaine and CCBs were analysed and were stratified into three groups based on the CCB involved: verapamil (n = 19), diltiazem (n = 30), and amlodipine (n = 18). Logistic regression analysis identified “completed suicide” (β = 0.35) and “product use for unknown indication” (β = 0.33) as the strongest predictors of fatal outcomes. Age revealed a modest negative association with fatal outcome (β = -0.93, intercept = 4.07). Concomitant substance use was reported in over 84% of cases. Frequently co-used substances included opioids, benzodiazepines, antidepressants, antihistamines and alcohol. Poly-drug use was most pronounced in the diltiazem group, which exhibited the highest burden of opioid and alcohol co-exposure. It is here suggested tat clinicians should exercise caution when managing individuals who use cocaine, due to the potential for increased toxicity and lethality when CCBs are co-used, either as part of a prescribed treatment or if CCBs are present as adulterants in cocaine.

Abstract: This paper presents an analysis of the severity of alcohol use disorder (AUD) based on electroencephalogram (EEG) signals and alcohol drinking experiments by utilizing power spectral density (PSD) and the transitions that occur as individuals drink alcohol in increasing amounts. We use data from brain-computer interface (BCI) experiments using alcohol stimulus recorded from a group of seventeen alcohol-drinking male participants and the assessment scores of the alcohol use disorders identification test (AUDIT). This method investigates the mild, moderate, and severe symptoms of AUD using the three key domains of AUDIT, which are hazardous alcohol use, dependence symptoms, and severe alcohol use. We utilize the EEG spectral power of the theta, alpha, and beta frequency bands by observing the transitions from the initial to the final phase of alcohol consumption. Our results are compared for people with low-risk alcohol consumption, harmful or hazardous alcohol consumption, and lastly, the likelihood of AUD based on the individual assessment scores of the AUDIT. We use Balanced Iterative Reducing and Clustering using Hierarchies (BIRCH) to cluster the results of the transitions in EEG signals and the overall brain activity of all the participants for the entire duration of the alcohol-drinking experiments. This study can be useful in creating an automatic AUD severity level detection tool for alcoholics to aid in early intervention and supplement evaluations by mental health professionals.

Abstract: Electroconvulsive therapy (ECT) remains one of the most effective interventions for treatment-resistant psychiatric disorders, particularly major depressive disorder and bipolar disorder. Despite extensive clinical and preclinical investigations the precise neurobiological mechanisms underlying ECT’s therapeutic effects are not fully understood. This review explores the molecular and cellular pathways involved in ECT, emphasizing its impact on neurotrophic signaling, oxidative stress, apoptosis, and neuroplasticity. Evidence suggests that ECT modulates brain-derived neurotrophic factor (BDNF) and other neurotrophic factors, promoting synaptic plasticity and neuronal survival. Additionally, ECT influences the hypothalamic-pituitary-adrenal (HPA) axis, reduces neuroinflammation, and alters neurotransmitter systems, contributing to its antidepressant effects. Recent findings also highlight the role of mitochondrial function and oxidative stress regulation in ECT-induced neural adaptation. By synthesizing current molecular insights, this review provides a comprehensive perspective on the neurobiological mechanisms of ECT, offering potential directions for future research and therapeutic advancements in brain stimulation.

Abstract: Background/Objectives: Nonverbal synchrony—the temporal coordination of physical behaviors such as head movement and gesture—is a critical component of effective social communication. Individuals with autism spectrum disorder (ASD) are often described as having impairments in such synchrony, but objective and scalable tools to measure these disruptions remain limited. This study aims to assess body motion synchrony in ASD using phase-based features as potential markers of social timing impairments. Methods: We applied a phase difference detection algorithm to high-resolution triaxial accelerometer data obtained during structured, unidirectional verbal communication. Seventy-two participants (36 typically developing [TD]–TD and 36 TD–ASD) were divided into dyads. ASD participants always assumed the listener role, enabling the isolation of receptive synchrony. Four distribution-based features—synchrony activity, directionality, variability, and coherence—were extracted from the phase difference data to assess synchrony dynamics. Results: Compared to the TD group, the ASD group exhibited significantly lower synchrony activity (ASD: 5.96 vs. TD: 9.63 times/min, p = 0.0008, Cohen’s d = 1.23), greater temporal variability (ASD: 384.4 ms vs. TD: 311.1 ms, p = 0.0036, d = 1.04), and reduced coherence (ASD: 0.13 vs. TD: 0.81, p = 0.036, d = 0.73). Although the mean phase difference did not differ significantly between groups, the ASD group displayed weaker and more irregular synchrony patterns, indicating impaired temporal stability. Conclusions: Our findings highlight robust impairments in nonverbal head motion synchrony in ASD, not only frequency but also in terms of temporal stability and convergence. The use of phase-based synchrony features provides a continuous, high-resolution, language-independent metric for social timing. These metrics offer substantial potential as behavioral biomarkers for diagnostic support and intervention monitoring in ASD.

Abstract: Epigenetic modifications play a crucial role in gene regulation and have been implicated in various physiological processes and disease conditions. DNA methylation (DNAm) has been implicated in the etiology and progression of many stress-related psychiatric behaviors such as depression. The ability to manipulate DNAm may provide a means to reverse and treat such disorders. Although CRISPR-based technologies have enabled locus-specific DNAm editing, their clinical applicability may be limited due to immunogenicity concerns and off-target effects. In this study, we introduce a novel approach for targeted DNAm manipulation using single-stranded, methylated DNA probes. We designed probes targeting the glucocorticoid response element (GRE) within the FKBP5 (FK506 binding protein 5) gene, a key regulator of stress response and depressive symptoms, and the promoter region of the MAOA (monoamine oxidase A) gene. In both HEK293 human embryonic kidney and mouse pituitary AtT-20 cells, transfection with their respective methylated probes significantly increased DNAm at targeted CpG sites in a persistent and dose-dependent manner. Importantly, the induced methylation effectively attenuated glucocorticoid-induced upregulation of FKBP5 gene expression. Alteration of methylation was specific to single-stranded probes, as double-stranded methylated probes and unmethylated probes showed no significant effects. Our findings suggest that methylated DNA probes have the potential to function as a simple tool for targeted epigenetic manipulation and serve as a safer alternative to CRISPR-based epigenome editing tools for the treatment of stress-related disorders such as depression.

Abstract: Substance use disorders (SUDs) remain a global public health challenge, with traditional treatment methods often hindered by barriers such as accessibility, stigma, and cost. Telemedicine and online interventions offer promising alternatives to overcome these obstacles. These technologies provide flexible, accessible, and private treatment options that can rival traditional approaches in efficacy. Research indicates that telemedicine achieves comparable outcomes in terms of abstinence rates and treatment retention, while also expanding access to underserved populations. Benefits include reduced stigma, cost-effectiveness, continuous monitoring, and enhanced patient engagement. However, challenges such as technological barriers, regulatory constraints, and maintaining high standards of care must be addressed. Future directions involve integrating telemedicine with traditional care, advancing personalized medicine through data analytics, and fostering policy adaptations to ensure equitable access. Telemedicine thus represents a transformative innovation, with the potential to significantly enhance SUD treatment outcomes globally.

Abstract: Background: Cannabis use is associated with an increased risk of developing psychosis in youth and younger adults (YAYA). However, differences in accessibility and consumption patterns may influence prevalence rates in different populations. This study aimed to investigate the prevalence of cannabis use and its associations among young adults attending an Early Psychosis Intervention (EPI) program in Southeast Ontario. Methods: A cross-sectional study of 116 youth and young adults enrolled in the Southeast Ontario EPI program between 2016 and 2019. Demographic characteristics and psychiatric diagnoses were identified from the clinical records. Statistical analyses were performed to examine the prevalence of cannabis use, its correlation and association with alcohol and other substance use, and the association with psychotic disorders. Results: The study revealed a very high prevalence of cannabis use among YAYA attending the EPI program, with 82.8% self-reporting cannabis use. Males showed a higher prevalence of cannabis use (71.9% than females 28.1%), with a male-to-female ratio of 2.6:1. Significant associations were found between cannabis use and psychiatric disorders, including psychosis and substance-induced psychotic disorder (SIP) (P-value< 0.05). Conclusion: This study highlights the need for the screening and recognition of harmful cannabis use with specific and targeted interventions to reduce the potential serious mental health effects in youth and young adults presenting with early psychosis. Early intervention incorporating motivational enhancement, and lower-risk cannabis use alongside psychological and pharmacological therapies serve to reduce the harmful impact of cannabis, shortening the duration of untreated psychosis and supporting functional recovery.

Abstract: Psychosis is one of the leading causes of disability worldwide. Individuals with an early onset, known as early-onset psychosis (EOP), tend to experience a worse prognosis and shorter life expectancy. The etiology of EOP remains unclear, but hypotheses suggest that both environmental and biological factors interact in its development. Epigenetic mechanisms are known to serve as the interface between environmental exposures and biological processes, emerging as potential tools to better understand the etiology of EOP. We characterized the sociodemographic and clinical characteristics, as well as genome-wide epigenetic markers, in Mexican patients with EOP. We found that patients with EOP have a higher epigenetic age using Wu`s clock (p=0.015). In addition, we observed that a reduction in years of schooling is associated with an increase in epigenetic age (Levine clock, =5.07, p=0.001). In our epigenome-wide association study, we identified eight CpGs associated with EOP. Noteworthy, a psychosis-methylation risk score (EOP-MRS) was associated with panic disorder (=1.36, p=0.03), as well as auditory (=1.28, p=0.04) and visual (=1.22, p=0.04) hallucinations. In conclusion, years of education have an impact in epigenetic age. Additionally, our study suggests associations of DNA methylation with EOP. Finally, we developed an MRS that associates clinical manifestations of psychosis.

Abstract: Despite lithium's presence in modern psychiatry for three quarters of a century, the mechanisms of its therapeutic action have not been fully elucidated. In the article, the evolution of the views on these mechanisms is presented, and both the old and new findings are discussed. Among the old mechanisms, lithium effect on the purinergic system, electrolyte metabolism and membrane transport, second messenger systems: cyclic nucleotide and phosphatidylinositol (PI), glycogen synthase kinase-3beta (GSK-3β), brain-derived neurotrophic factor, and neurotransmitters, are discussed. The new data have been obtained from in vitro studies, molecular biology and genetic researches. They also showed the effect of lithium on the immune system, biological rhythms, and telomere functions. In the article, each lithium mechanism is considered in the light of its association with the pathogenesis of bipolar disorder or/and as a marker of lithium response. This review, although not complete, shows that the possible mechanisms of lithium action are multifold. It turned out that many apparent “old” mechanisms had their revival in research performed in the 21st century. Additionally, many studies eventually converged on the mechanisms postulated in the 1980s/1990s of inhibitiing GSK-3β and PI by lithium.

Abstract: Sensory dysregulation represents a core challenge in autism spectrum disorder (ASD), affecting perception, behavior, and adaptive functioning. The brain's ability to reorganize, known as neuroplasticity, serves as the basic principle for therapeutic interventions targeting these deficits. Neuroanatomical mechanisms include altered connectivity in the sensory and visual cortices, limbic system and amygdala, while imbalances of neurotransmitters, in particular glutamate and gamma-aminobutyric acid (GABA), contribute to atypical sensory processing. Traditional therapies used in sensory integration are based on the principles of neuroplasticity. Increasingly, new treatments use this knowledge, and modern therapies such as neurofeedback, transcranial stimulation, and immersive virtual environments are promising in modulating neuronal circuits. However, further research is needed to optimize interventions and confirm long-term effectiveness. This narrative review discusses the role of neuroplasticity in the etiopathogenesis of sensory integration deficits in autism spectrum disorder. The neuroanatomical and neurotransmitter basis of impaired perception of sensory stimuli is considered, and traditional and recent therapies for sensory integration are discussed.

Abstract: Vitamin B12 (cobalamin) is essential for neurodevelopment, particularly during pregnancy and early childhood. Its deficiency has been implicated in neurological disorders, but also autism spectrum disorder (ASD). Maternal B12 levels influence fetal brain development, and inadequate intake may increase ASD risk. Postnatally, insufficient cobalamin in a child’s diet could further impact neurodevelopment. One mechanism linking B12 deficiency to ASD involves its role in gut microbiota balance. Dysbiosis, common in ASD, is associated with low-grade inflammation and gut-brain axis disruptions. Additionally, B12 is crucial for neurotransmitter metabolism, including serotonin and dopamine synthesis, and for neuronal myelination—both essential for cognitive and behavioral function. Despite emerging evidence, the link between B12 and ASD remains inconclusive due to inconsistent findings. Research suggests B12 may serve as a biomarker for disease progression and treatment response. However, most studies rely on single-time-point measurements, failing to account for individual variability and external influences such as diet and environment. Longitudinal studies are needed to clarify whether early B12 supplementation could mitigate ASD symptoms. Identifying children at risk of deficiency and promoting maternal and early-life nutrition may aid in prevention and intervention.

Abstract: Background/objectives: Most individuals who have a familial or clinical risk to develop psychosis remain free from psychopathology. Identifying neural markers of resilience in these at-risk individuals may help clarify underlying mechanisms and yield novel targets for (early) intervention. However, in contrast to studies on risk biomarkers, studies on neural markers of resilience to psychosis are scarce. The current study aims to identify potential brain markers of resilience to psychosis. Methods: A systematic review of the literature yielded a total of 43 MRI studies reporting resilience-associated brain changes in individuals with elevated risk for psychosis. Label-based meta-analysis was used to synthesize findings across MRI modalities. Results: Resilience-associated brain changes were significantly overreported among regions of the default mode and language network, and among highly connected and central brain regions. Conclusions: These findings suggest that DMN and language-associated brain regions and central brain hubs may be hotspots for resilience-associated brain changes. These neural systems are thus of key interest as targets of inquiry and, possibly, intervention in at-risk populations.

Abstract: Obsessive-compulsive disorder (OCD) is a complex psychiatric condition characterized by significant heterogeneity in symptomatology and treatment response. Advances in neuroimaging, EEG, and other multimodal datasets have created opportunities to identify biomarkers and predict outcomes, yet traditional statistical methods often fall short in analyzing such high-dimensional data. Deep learning (DL) offers powerful tools for addressing these challenges by leveraging architectures capable of classification, prediction, and data generation. This brief review provides an overview of five key DL architectures—feedforward neural networks, convolutional neural networks, recurrent neural networks, generative adversarial networks, and transformers—and their applications in OCD research and clinical practice. We highlight how these models have been used to identify neural predictors of treatment response, diagnose and classify OCD, and advance precision psychiatry. We conclude by discussing the clinical implementation of DL, summarizing its advances and promises in OCD, and underscoring key challenges for the field.

Abstract: In recent years, bipolar disorder (BD), a multifaceted mood disorder marked by severe episodic mood fluctuations, has been shown to have an impact on disability-adjusted life-years (DALYs). The increasing prevalence of BD highlights the need for better di-agnostic tools , particularly those involving genetic insights. Genetic association studies can play a crucial role in identifying variations linked to BD, shedding light on its ge-netic underpinnings and potential therapeutic targets. Our research utilized data from the Taiwan Precision Medicine Array (TPM Array), aiming to identify significant single nucleotide polymorphisms (SNPs) associated with BD. Notably, we identified the var-iant rs11156606 in the ABCD1 gene, which plays a role in fatty acid metabolism—a process potentially connected to BD pathophysiology. Subsequent linkage disequilib-rium (LD) analysis of rs11156606 revealed a strongly associated variant, rs73640819, located within the ABCD1 3’ untranslated region (3’UTR), suggesting a regulatory role on ABCD1 RNA functionality. Additionally, our findings indicate that the variant rs3829533 is in strong LD with rs3751800 and rs3751801, which significantly affect the coding sequence of the MTHFSD gene. These findings enhance the genetic under-standing of BD in the Taiwanese Han population and highlight the value of genetic research in advancing our knowledge of bipolar disorder.

Abstract: Background/Objectives: Studies from various countries indicate that nurses are a professional group at increased risk of depression and suicide. Hospital work involves managing life-and-death situations and coping with physical and emotional pain and suffering alongside patients and their families. The lack of adequate mental health and trauma support can adversely affect not only the mental state of nurses, but also their ability and competence to provide support to people experiencing mental crises, including suicidal thoughts. The aim of the study was to assess the epidemiology of depression and suicidal behavior in nursing staff and to examine their competence to talk about suicide. Methods: The cross-sectional study comprised 400 nurses employed in various hospital wards across Poland. Researchers utilized a demographic-descriptive questionnaire, an original questionnaire assessing competence in discussing suicidal topics, and two standardized psychometric tools: the Suicidal Behavior Questionnaire (SBQ-R) and the Patient Health Questionnaire (PHQ-9). The survey was administered via an online questionnaire. Results: The study revealed that nurses are a professional group at high risk of depression and suicide. The highest severity of symptoms was reported among those receiving psychological support and psychiatric treatment. However, these individuals demonstrated greater competence in providing assistance to people in suicidal crises compared to those who did not receive such help. The use of psychological and psychiatric help was a decisive factor in whether a nurse would become a "wounded healer" or an “walking wounded unhealed healer". Conclusions: Given the magnitude of mental health and suicide risks among nurses, it is imperative to implement primary, secondary, and tertiary prevention measures for both nursing staff and students preparing to enter the profession.

Abstract: Modern neuroscience understands the brain as a complex system whose functional properties are determined by the myriads of interactions of its cellular components. In the difficult route to obtain better understanding of this organ, mathematical tools have become ever more effective, and we are now able to simulate the dynamics of brain signals from digital representations that have high fidelity to experimental data. However, these simulations are generated by inherently simple neuronal models that contain assumptions that, by necessity, can be at times far removed from the underlying neurobiology. Here we develop an integrated view of brain dynamics that describes how the neurovascular units — made of neurons, capillaries and glia — collectively determine the development of the functional properties of brain neuronal populations and maintain their homeostatic control. These interactions are instructed by genetic programmes modulated by local environmental conditions. These complexities can be integrated into generative models and supply helpful analytics able to link the observable data to neurobiological entities if detailed brain mappings of molecular and cellular components are available. We further highlight how the development of these generative models could be relevant to the understanding of psychiatric conditions.

Abstract: Background: The uneven distribution of psychiatrists across the United States has led to a significant deficiency in psychiatric care, particularly in rural and remote areas. Telepsychiatry has emerged as an effective solution to bridge this gap, providing comparable outcomes to in-person services. Objective: This case series aims to highlight the effectiveness of telepsychiatry in diagnosing and managing catatonia, a complex neuropsychiatric condition whose diagnosis often requires physical examination, through consultation-liaison (CL) psychiatry services. Methods: We describe three cases of catatonia managed via telepsychiatry by the CL psychiatry service at The University of Pittsburgh Medical Center. CL psychiatrists located in the university hospital diagnosed and managed catatonia via telepsychiatry in patients medically hospitalized in non-urban hospitals with assistance from an in-person clinician. Each case was assessed for diagnostic accuracy and treatment outcomes using the Bush Francis Catatonia Rating Scale. Results: The use of telepsychiatry facilitated timely diagnosis and treatment of catatonia. All patients showed significant improvement, demonstrating the viability of CL telepsychiatry in managing complex conditions like catatonia in the medical setting. Conclusion: CL Telepsychiatry is a critical tool in addressing the shortage of psychiatric care in underserved areas. It may be effective in facilitating the diagnosis and treatment of catatonia in medical hospitals, ensuring patients receive timely and appropriate care.

Abstract: Background: Schizotypal traits are notably prevalent among children diagnosed with Autism Spectrum Disorder (ASD). Both conditions commonly exhibit impairments in executive functions (EF), which encompass "cool" and "hot" processes. The observed deficits in these EF domains across ASD and schizotypy underscore a compelling need to investigate how their co-occurrence impacts EF. Methods: This study investigated the impact of co-occurring autistic and schizotypal traits on EF in 63 children diagnosed with ASD, aged 7 to 12 years. Participants were assessed using the Autism Diagnostic Observation Schedule-2 (ADOS-2), the Melbourne Assessment of Schizotypy in Kids (MASK), and a battery of hot and cool EF tests. Results: Correlational analyses revealed a significant association between MASK score and working memory, as well as between ADOS scores and various cool EF components (i.e., working memory, inhibition & planning). Hierar-chical regression analyses showed that the interaction between ADOS and MASK scores signifi-cantly predicted performance on hot EF (i.e., affective decision-making), but not on cool EF tasks. Conclusions: These findings suggest that the co-occurrence of ASD and schizotypal traits may have differential effects on cool and hot EF domains. Understanding how the combination of autistic and schizotypal traits affects cognitive processes may inform tailored interventions and support strategies for individuals presenting with these traits.