Cigarette smoking is the leading preventable cause of premature death in the US. Quitting can significantly reduce the risk of adverse health effects. However, much is unknown about the factors prospectively associated with the behavioral step of making a quit attempt. The present study leveraged supervised machine learning, data from a prior experimental study, and exploratory methods to investigate longitudinal associations between smoking history, cognitive and behavioral indices, and quit attempts reported at a four-week follow-up assessment.

Secondary analysis of a project that enrolled 278 adult cigarette smokers (18-69 years old) for a prospective study of predictors of making a quit attempt(s). Analyses were based on N = 231 with non-missing data through the one-month follow-up, separated into training (n = 185, of whom 36 made a quit attempt) and testing (n =46, of whom 9 made a quit attempt) subsets.

In the testing subset, a random forest model with class weights to address class imbalance and a linear support vector machine model performed best of the models tested, albeit not very well (eg, F₁ values of 0.36 in the testing set). Feature importance metrics suggested that contemplation status and perceived risks of "I will eat more" and "I will miss the taste of cigarettes" were of highest importance in classifications. All models had better specificity than sensitivity. Poor performance in the testing set may have resulted in part from small sample size.

While reliable predictions of quit attempts were not obtained across the train-test split, the present study leverages bottom-up, data-driven approaches, and machine learning methods to explore the understudied behavioral step of initiating a quit attempt. Future studies should continue exploring predictors of quit attempts, along with how they may differ from predictors of sustained smoking cessation. Data-driven machine learning methods have the potential to progress precision medicine efforts by clarifying generalizable mechanisms underlying clinical outcomes.

Bipolar depression (BPD) lacks reliable peripheral biomarkers for early diagnosis. Sphingomyelin (SM) and ceramide (Cer) are bioactive lipids implicated in neuronal membrane signaling, yet their diagnostic utility in young adults with BPD remains unclear.

We conducted a single-center exploratory untargeted lipidomics study focusing on SM and Cer species in plasma from 26 young adults (18-26 years) with BPD at baseline and after three weeks of quetiapine and magnesium valproate treatment (BPD3w), alongside 27 sex- and age-matched healthy controls (HC). Group comparisons of total SM, total Cer, and SM/Cer ratio were performed; ROC curves assessed discriminative ability. A Venn diagram approach, followed by LASSO regression with bootstrap averaging, identified a refined candidate biomarker panel from 140 SM/Cer species.

Both BPD and BPD3w groups exhibited elevated total SM and Cer relative to HC, whereas the SM/Cer ratio was significantly reduced. Paired analysis revealed that total SM and the SM/Cer ratio decreased after treatment (both P < 0.05), while total Cer remained unchanged. Intersection analysis yielded 14 candidate lipids, which were further refined via LASSO regression (λ = 100) with bootstrap averaging to a 4-species panel: Cer(t20:1/24:3), Cer(d19:1/25:3), SM(t18:0/22:0), and Cer(t17:0/22:0), with an AUC of 0.975 (95% CI: 0.917-1.000), representing an unvalidated internally derived estimate pending further validation. Correlation analysis revealed that Cer(d19:1/25:3), Cer(t17:0/22:0), and SM(t18:0/22:0) were positively correlated with depressive, anxiety, and manic symptom severity (HAMD, HAMA, and YMRS). Cer(t20:1/24:3) showed a modest negatively correlation with HAMD, but not with HAMA or YMRS. Additionally, Cer(t20:1/24:3) and SM(t18:0/22:0) exhibited sex-dependent differences.

Plasma SM and Cer profiles are altered in young adults with BPD and show a partial trend toward normalization following short-term treatment. A refined 4-species panel showed promising but internally derived discriminative performance in this exploratory study. While peripheral sphingolipid signatures may serve as potential biomarkers for BPD, these findings require validation in independent cohorts before any clinical application.

Gamma-aminobutyric acid (GABA) is an inhibitory neurotransmitter recognized for its antihypertensive, anxiolytic, neuroprotective, and cognitive-enhancing properties. Functional foods enriched with naturally produced GABA have emerged as promising dietary interventions to modulate the microbiota-gut-brain axis and promote mental well-being. In the current study, a novel GABA-enriched plant-based almond yogurt was developed using the psychobiotic strain Enterococcus faecalis RIT BM_S15-3, a human breast milk-derived isolate, as the starter culture. To the best of our knowledge, this is the first report highlighting the use of a human breast milk-derived psychobiotic Enterococcus faecalis RIT BM_S15-3 to produce GABA-enriched almond yogurt. The fermentation parameters were systematically optimized to obtain maximum GABA enrichment while ensuring microbial viability and product quality. Unlike previous studies that primarily optimize plant-based yogurts for texture or antioxidant properties, this study focused on maximizing microbial GABA biosynthesis by optimizing L-monosodium glutamate (L-MSG) concentration, fermentation temperature, and fermentation time. The confirmatory experiment resulted in a GABA concentration of 29 mM in the final yogurt developed almond yogurt exhibited high antioxidant activity in DPPH and ABTS assays, with total phenolic and flavonoid contents showing higher activity than those of commercially available dairy and non-dairy yogurt. We optimized the fermentation conditions to improve GABA yield, including L-monosodium glutamate (L-MSG) concentration, fermentation time, and fermentation temperature. The results indicated a GABA yield of 29 mM in the yogurt after optimization. The almond yogurt showed a suitable water-holding capacity, viscosity, and favorable sensory acceptability (overall score: 7.52), as well as functional stability during refrigerated storage. A 21-day storage study showed sustained GABA retention together with maintenance of viable probiotic populations, indicating good functional stability of the developed product. This study emphasizes the feasibility of developing a naturally GABA-enriched, probiotic almond yogurt as a potential next-generation functional food with prospective applications in microbiota-gut-brain axis modulation. Although the observed functional characteristics suggest promise for supporting neurological health, further in vivo and clinical studies are required to establish anti-anxiety and neuroprotective efficacy.

A growing body of evidence, primarily from high-income nations, suggests that extreme weather events can have a profound impact on mental health.

To contribute to a more inclusive understanding of this public health threat, we reviewed the literature to understand the impact of climate-related extreme weather events on mental health in the West African context.

This study is a systematic review of studies based in West Africa.

Our literature search of six databases (PubMed/MEDLINE, Index to Nursing and Allied Health Literature [CINAHL], EMBASE, PsycINFO, Cochrane and Web of Science) from January 2007 to December 2024 identified 2968 articles of which 13 met study inclusion criteria.

These 13 studies were predominantly cross-sectional and qualitative. The studies took place in four West African countries (Burkina Faso, Ghana, Nigeria and Sierra Leone) and reported direct and indirect relationships between climate-related weather events and poor mental health. The articles also highlighted that certain groups like women and persons of low socioeconomic status are likely to experience more adverse mental health impacts due to gender roles and factors associated with a lower social standing. The studies further suggest bolstering population climate health education, reforming building and development mechanisms, and targeting social programmes to women and other vulnerable groups as potential strategies to address the negative impact of climate on mental well-being.

Findings from this study as well as continued investments in mental health clinical capacity will be important for meeting existing shortfalls in mitigating the impact of climate change on mental health.

There is a need for greater research investment in larger studies, in more West African countries, and including substantial proportions of the population like children.

Tremendous maturation in brain structure and function, underlying very rapid cognitive development, occurs in the early years of life, yet it has been difficult to obtain reliable measures of brain function over this period. A major challenge has been the difficulty of acquiring reliable neuroimaging data from awake young children, who often struggle to tolerate conventional imaging environments or remain still during scanning. Existing approaches each involves important compromises between spatial and temporal resolution, movement tolerance and practicality for use in early childhood. Optically pumped magnetometers (OPMs), a recent advance in magnetoencephalography (MEG) technology, are expanding the developmental neuroimaging toolkit. By enabling adaptable, wearable, and movement-tolerant MEG systems, OPMs retain the excellent spatial and temporal resolution of conventional cryogenic MEG technology while improving suitability for infants, toddlers, and young children. In this commentary, we briefly review the current functional neuroimaging toolkit used across development and discuss how OPMs are transforming the study of the developing brain. We highlight recent applications of OPMs to study early life, their potential for investigating brain-behaviour relationships and social interaction, and their promise for improving inclusion of clinical populations traditionally underrepresented in neuroimaging research. We also outline remaining technical and methodological challenges that should be addressed as the field continues to grow.

The spiritual health of veterinarians is challenged by moral distress that expresses a conflict between personal core values and clinical practice. The morally resilient veterinarian experiences and addresses moral distress in constructive ways that express care for patients, owners, colleagues and society. As such, moral resilience is a positive aspect of spiritual health that can be built through reflections and dialogue on the ethical, existential, spiritual and religious questions raised by veterinary practice. Veterinarians often face complex moral dilemmas when attempting to balance the interests of animal patients, their owners, the veterinary business, surrounding society, and themselves. When it is not possible to accommodate all these responsibilities, moral distress may occur, a state associated with compassion fatigue, burnout and depression. Human spirituality concerns a person's central relationships with the self, others, nature, animals and "the sacred" giving meaning, purpose and values to life. Consequently, moral distress affects not only physical, social and mental health, but also spiritual-existential health and well-being, as it disrupts these core relationships in a way that defies simple technical and practical solutions. We argue that strategies to increase moral resilience (and thus spiritual health) should include conversations with peers and mentors aiming to articulate experiences of moral distress and reinterpret their meaning. Since moral distress in a veterinary clinic involves emotions, values and ideas about the human-animal relationship, resilience-building reflections and conversations must address existential themes like personal responsibility, guilt, acceptance, forgiveness and moral agency. These questions cannot be answered by scientific knowledge alone, but involve personal faith perspectives (secular-existential, spiritual or religious). Consequently, veterinarians, both individually and collectively, should increase attention to the broader existential context of clinical work in order to cultivate moral resilience and enhance spiritual health.

Self-harm (SH) is common, but its severity varies. Severe cases may involve extensive hospitalization and high suicide risk. Although SH is associated with post-traumatic stress disorder (PTSD), personality disorder (PD), and complex cases of PD-PTSD comorbidity, factors related to SH severity are sparsely researched.

The study aims to investigate how SH severity relates to PTSD symptoms and different domains of personality functioning. The study also aims to explore indirect associations of interpersonal functioning, PTSD symptoms and SH severity.

In a multicenter cross-sectional design, the study included outpatients admitted for personality disorder treatment (n = 361) and psychiatric inpatients (n = 42) with frequent (>5) or long (>4 weeks) admissions in the previous year due to SH (N _total = 403, period 2019-2022). Patient self-reports included current (last 6 months) SH and suicide attempts, PTSD symptoms, and self and interpersonal domains of personality functioning.

More severe PTSD symptoms and poorer self-functioning (self-control and identity integration) were significantly and independently associated with greater SH severity. The association between PTSD symptoms and increasing SH severity was partially mediated by greater impairment of self-control and identity integration. Interpersonal domains were not associated with SH severity.

This study highlights post-traumatic stress and personality problems as common clusters of symptoms among patients with increasingly severe SH. Further exploration indicated personality functioning self-domains as potential drivers of the association between post-traumatic symptoms and SH severity. Results support integrated, individualized treatment addressing SH in light of both trauma burden and personality functioning.

Although obstructive sleep apnea (OSA) related hypoxia shows stronger associations with multiple complications than respiratory disturbance, its impact on linear growth, a major pediatric concern, remains unclear. This study investigates independent effects of hypoxia and respiratory disturbance on the height of children with OSA.

This retrospective, cross-sectional study clinically evaluated children with suspicious OSA from January 2013 to June 2025. Individuals with other sleep disorders, severe neuropsychiatric disorders and physical disorders were excluded. Subjects underwent overnight polysomnography (PSG) and height measurement. OSA was defined as apnea-hypopnea index (AHI) ≥1 event/hour, and those with AHI <1 event/hour served as the non-OSA reference group. AHI and percentage of total sleep time with oxygen saturation < 90% (T90%), were separately used to evaluate the severity of respiratory disturbance (mild, 1≤AHI < 5 events/h; moderate, 5≤AHI < 10 events/h; severe, AHI ≥10 events/h) and hypoxia (T90% quartiles). Height z-scores ≤-1 SD defined subclinical growth impairment. Linear and logistic regression models analyzed the independent associations between AHI and T90% and height and subclinical growth impairment. Nutrition, endocrine disorders, chronic illnesses, and parental height were not collected and adjusted in this study.

A total of 2443 children were included (348 children without OSA, 2095 children with OSA). In linear regression models, higher T90% was associated with a lower height z-score in the full sample (B = -0.005, 95% CI: -0.010 to -0.000, P = 0.033) and children with OSA (B = -0.005, 95% CI: -0.010 to -0.000, P = 0.034), whereas AHI was not (full sample: B = -0.003, 95% CI: -0.006 to 0.001, P = 0.111; children with OSA: B = -0.002, 95% CI: -0.005 to 0.002, P = 0.330).Logistic models showed higher odds of subclinical growth impairment in children with moderate (OR = 1.73, 95% CI: 1.05-2.84) or severe OSA (OR = 1.96, 95% CI: 1.19-3.21) and in those in the highest T90% quartile (OR = 2.17, 95% CI: 1.30-3.60), compared with children without OSA. These associations remained stable in females and children aged 2-9 years.

To our knowledge, this is the first study to show that greater respiratory disturbance and nocturnal hypoxemia are associated with a higher risk of short stature in children with OSA. These findings support routine height assessment in the clinical management of pediatric OSA.

Ketamine Assisted Psychotherapy (KAP) is a developing modality with broad impact on humans suffering with a variety of emotional and relationship difficulties that encompass many diagnostic entities. Our application of KAP has extended to and included the treatment of adolescents and young adults in a family therapy format. Given the increasing scope and complexity of the adolescent mental health crisis and the frequent failures to respond to conventional treatment, the promise of KAP deserves thorough investigation.

We previously described the process of KAP in our adolescent population that included four case reports exemplifying our approach. Here we report on the longitudinal clinical experience of 19 adolescents and young adults (ages 14-24; mean age 19.3 ± 3.1 years; 11 female, 7 male, 1 non-binary) who completed three or more KAP sessions at a single community outpatient clinic.

BDI-II scores declined by an estimated 0.65 points per visit (95% CI: -0.90, -0.40) and HAM-A scores by 0.21 points per visit (95% CI: -0.44, +0.01), based on linear mixed-effects models. Approximately 63.2% of patients (12/19) achieved medium or large individual treatment effects on BDI; 47.4% (9/19) on HAM-A. Physician and patient reports indicated overall benefit in 68.4% of cases (13/19), including marked reductions in suicidality in at-risk patients. Ketamine was well tolerated across 167 documented sessions; nausea was the only notable adverse event, occurring in 5.4% of sessions and largely manageable with standard antiemetics. No hospitalizations, substance misuse, or evidence of neurological harm occurred over a median individual follow-up of 5.6 months (mean 10.1, range 0.9-36.4 months).

These findings suggest that KAP is feasible and well tolerated in a diagnostically complex adolescent population, with clinically meaningful reductions in depression and a similar trend for anxiety associated with continued treatment. To our knowledge, this is the first report to provide longitudinal quantitative data for office-based KAP in adolescents and young adults, and it establishes a foundation for and supports the design of future controlled trials in this population.

Artificial intelligence (AI) is increasingly influencing the management of neuropsychiatric disorders, extending its role beyond assistive diagnosis toward adaptive intervention and individualized disease management. Digital phenotyping enables continuous assessment of multimodal behavioral and biological signals, allowing neuropsychiatric disorders to be modeled as dynamic rather than static processes. This review summarizes current AI-driven approaches for neuropsychiatric assessment and intervention, including computer vision-based behavioral analysis, wearable sensing, neuroimaging biomarkers, digital therapeutics, virtual reality, social robotics, and brain-computer interfaces. We further discuss emerging closed-loop frameworks that integrate real-time state estimation with adaptive intervention strategies, shifting neuropsychiatric AI from passive observation toward continuous therapeutic optimization. Despite rapid progress, integration between phenotyping and intervention remains limited, and most closed-loop systems are still confined to experimental settings. Key challenges include multimodal representation, interpretability, generalizability across populations and devices, and translation into real-world clinical workflows. We argue that the primary bottleneck in AI-driven neuropsychiatry is no longer prediction accuracy alone, but the ability to connect continuous patient-state estimation with clinically meaningful adaptive action. Finally, we outline future directions toward clinically grounded, human-AI collaborative neuropsychiatric systems.