Moral injury (MI) spans biological, psychological, social, and spiritual domains, yet systematic bibliometric evaluation remains scarce. A bibliometric analysis of Scopus-indexed publications containing "moral injury" (1992-2025) was conducted using three search strategies (i) Title-Abstract-Keywords (TAK), (ii) Abstract-only (AO), and (iii) Title-only (TO). Publication types, annual trends, and the performance of authors, institutions, countries, sponsors, and journals were examined. A total of 2,081 documents were identified, including articles (1,491), reviews (164), book chapters (193), and editorials (75). TAK yielded 1,655 records, AO 1,400 records, and TO 879 records, demonstrating notable variation in dataset size. Output remained limited until 2017, followed by rapid growth from 2018, peaking in 2025. The USA led global production, followed by the UK, Canada, and Australia. TAK analysis identified the most prolific authors in this review by country: in the USA, Maguen, S. (36) and Koenig, H.G. (34); in the UK, Greenberg, N. (37) and Murphy, D. (36); in Canada, McKinnon, M.C. (23) and Nazarov, A. (21); and in Australia, Carey, L.B. (13) and Nickerson, A. (10). Other top contributors by country are also identified. Within this study, prolific institutions included VA Medical Center, King's College London, Western University, McMaster University, Duke University Medical Center, and the Boston University Chobanian and Avedisian School of Medicine. Prominent journals were 'Psychological Trauma: Theory, Research, Practice, and Policy', the 'European Journal of Psychotraumatology', 'Traumatology', 'Frontiers in Psychiatry', and the 'Journal of Religion and Health'. Title-based co-word analysis (AO and TO datasets) identified ten thematic clusters covering psychological outcomes, military and healthcare contexts, ethics, assessment, and interventions. Analysis of the top 100 most cited papers highlighted five foundational themes in conceptualization, measurement, mental health outcomes, and treatment approaches. MI research expanded rapidly after 2018, emphasizing the need for methodological transparency through a bibliometric study across multidisciplinary fields. While not all authors/coauthors or their respective institutions and nations have been acknowledged within this analysis of MI research, nevertheless the significant leaders have been identified, as have a number of key research and clinical themes. Search strategy selection however, substantially determines dataset size, contributor visibility, and thematic representation, hence a number of limitations regarding this analysis are noted.

Personalized psychopharmacotherapy remains a critical yet underdeveloped frontier in psychiatry, as traditional approaches often fail to address substantial interindividual variability in drug efficacy and tolerability. While demographic, clinical, and genetic factors have improved treatment precision, they do not fully account for observed heterogeneity. Recent advances highlight the promise of personality traits, particularly as operationalized by Cloninger’s Seven-Factor Model, as novel biomarkers for treatment optimization. This model distinguishes between temperament—biologically-based, heritable predispositions—and character, which is shaped by environmental, developmental, and cultural factors. Mapping these dimensions to neurochemical pathways offers a framework for tailoring pharmacological interventions to individual neurobiological profiles, potentially enhancing symptom control, tolerability, and adherence. Integrating personality assessment with pharmacogenomics, neuroimaging, and computational phenotyping may enable more holistic patient stratification, fostering the development of precision psychiatry. However, significant methodological, practical, and ethical challenges persist, including inconsistent findings, concerns regarding validity and generalizability, and the risk of stigmatization or misuse of sensitive data. Future research should prioritize large-scale, diverse, and longitudinal studies that leverage advances in artificial intelligence and integrative biomarker platforms. Interdisciplinary collaboration and rigorous ethical oversight are essential to translate the theoretical promise of personality-informed psychopharmacotherapy into effective, equitable, and patient-centered clinical practice. Ultimately, incorporating personality biomarkers may redefine the landscape of individualized psychiatric care and advance the goals of precision psychiatry.

In 2022, a group of 10 international researchers spanning nine countries published an article on the assessment of a Persian version of an interpersonal mindfulness scale (IMS). That article, published in Frontiers in Psychiatry, was retracted on 4 September 2023. The retraction notice cites, as its main factor, abusive authorship practices that have the hallmarks of paper mill engagement. This study aimed to appreciate the literature that has cited that retracted paper. Two years after its retraction, by 1 September 2025, that article has already accumulated 37 citations, according to Google Scholar, Scopus and Web of Science, clustered around two education journals, Hindawi’s (Wiley) Education Research International and Springer Nature’s Language Testing in Asia. These journals cited the retracted article 13 and 5 times, respectively. This paper, while recording the literature that has cited that retracted article, notes that IMS researchers need to be mindful of the literature they cite and rely upon.

Tai Chi has demonstrated beneficial effects in managing insomnia. However, no bibliometric analysis has systematically examined the relationship between Tai Chi and insomnia. This study aims to quantitatively evaluate the global research landscape and emerging trends related to "Tai Chi and insomnia" from 2006 to 2025 using bibliometric methods, thereby offering evidence-based insights and guidance for future basic and clinical research. A bibliometric analysis was conducted using data retrieved from the Web of Science Core Collection (WoSCC)) and Scopus databases for the period 2006-2025. The data were processed and visualized using Bibliometrix (R software), VOSviewer, and CiteSpace. A total of 281 valid articles from the WoSCC and 489 from Scopus were included. The number of publications on Tai Chi and insomnia has steadily increased over the past two decades. China and the United States are the primary contributors to research in this field, forming an international collaboration network centered around the University of California, Los Angeles (UCLA) and the University of Hong Kong. Among them, Professor Michael R. Irwin from UCLA is the most prolific author and maintains the widest collaborative network in this domain. Frontiers in Psychiatry and Sleep Medicine Reviews show the highest publication volumes, whereas Sleep ranks first in citation frequency and functions as a key hub for academic collaboration. Using cluster analysis, keyword frequency assessment, co-word mapping, and thematic evolution analysis, we identified several prominent research hotspots. These hotspots primarily focus on three areas: the clinical application and efficacy evaluation of Tai Chi in specific patient populations with sleep disorders, mechanistic and evidence-based investigations of Tai Chi interventions for insomnia, and comparative or integrative studies of Tai Chi with other non-pharmacological treatments for insomnia. The therapeutic potential of Tai Chi for insomnia has garnered growing global interest and is poised to become a major focus in insomnia management. This study provides a comprehensive overview of the field's current status and key research trends, offering valuable direction for future studies.

Robot and AI applications in obsessive-compulsive disorder and related disorders: A bibliometric analysis of publications from 2010 to 2025.

Patients suffering from depression frequently encounter extended periods of low moods and lack of enjoyment or enthusiasm for activities. It leads to suicidal thoughts and presents a potential hazard to their safety. Nowadays, there has been significant progress in researching the effectiveness and safety of esketamine in treating depression. Hence, this paper employs bibliometric analysis to investigate the evolution and future research trajectories of this domain. We utilize Excel, VOSviewer, and CiteSpace software to generate bibliometric network visualizations to analyze, construct, and quantitatively evaluate pertinent literature, which facilitates a lucid and intuitive presentation of the trends and frontiers in this research domain. Annual publications increased from 2015 to 2024, totaling 925 articles, with 286 studies published in 2024. The USA published the most papers (n=308), followed by China (n=260) and Canada (n=114). Three of the top journals were Journal of Affective Disorders (n=56,IF=4.90), Frontiers in Psychiatry (n=38,IF=5.44), and International Journal of Neuropsychopharmacology (n=21,IF=4.50). The most published authors were McIntyre, Roger S (n=52), followed by Hashimoto, Kenji (n=49), Rosenblat, Joshua D (n=41). The keywords that have been relevant to the topic for the last decade are "treatment-resistant depression", "efficacy", "antidepressant" and "suicidal ideation". This bibliometric analysis showed a significant increase in research on the use of esketamine in the treatment of depression. The main focus of current research is still the assessment of long-term use safety. In addition, the huge difference in research resources between developed countries and low- and middle-income countries remains an unresolved issue.

Prescription digital therapeutics (PDTs) are Food and Drug Administration (FDA)-authorized software-based treatments designed to treat a range of conditions on the smartphone. Their development and deployment rely on four foundational scientific domains: clinical, engagement, regulatory, and implementation. However, the relative representation of these domains in the PDT literature has not been systematically characterized. We conducted a bibliometric and thematic analysis of PubMed-indexed articles published between 2020 and 2025 containing the term "prescription digital therapeutic(s)." Metadata and abstracts were extracted, cleaned, and analyzed using natural language processing for this review. Topic modeling was performed to identify key thematic areas, and each abstract was classified into one or more of the four foundational domains using a structured keyword heuristic framework. Trends in publication volume, authorship, domain co-occurrence, and thematic focus were visualized. Sixty-one unique articles met the inclusion criteria. Publication activity increased over time, peaking in 2022 and 2024. Most first authors were based in the United States, with industry-affiliated authorships predominating. The most frequently publishing journals were Frontiers in Psychiatry and Health Affairs (Millwood). Clinical science was referenced in 45 (74%) papers, followed by engagement science in 35 (58%), regulatory science in 28 (46%), and implementation science in 18 (29%). Only seven (12%) articles addressed all four domains. Topic modeling identified five major themes: substance use and cost modeling, regulatory frameworks, insomnia treatment, engagement strategies, and gamified pediatric interventions. Co-occurrence analysis revealed strong overlap between clinical and engagement domains, while regulatory and implementation science appeared less frequently in combination. The literature on PDTs remains concentrated in clinical and engagement domains, with limited attention to regulatory strategy and real-world implementation. Greater integration across all four scientific domains is needed to ensure that PDTs are not only effective but also scalable, fundable, and embedded into routine care.

Artificial Intelligence (AI), has garnered attention in research on attention deficit hyperactivity disorder (ADHD). In the future, AI may have clinical applications in ADHD, particularly in facilitating the objective diagnosis and classification of ADHD. This study aimed to comprehensively analyze the current status and research frontiers of AI applications in ADHD, identifying hotspots and trends to guide future research directions and promote clinical advancements in this field. Articles in the field of AI applications in ADHD were from the Web of Science Core Collection (WoSCC) database. Analysis was conducted using CiteSpace 6.3.R.1. Additionally, high-impact articles were analyzed. A total of 342 articles from 50 countries and regions were included. The United States led with 103 articles, having the highest H-index of 21, followed by China with 69 articles, and England with 34 articles. The State University of New York System produced the most articles (11), and Frontiers in Psychiatry had the most articles (12). Burst keywords in 2022-2024 included "diagnosis," "network," "attention deficit hyperactivity disorder" and "artificial intelligence." AI technologies have become a prominent topic in ADHD research, with the United States, China, and England leading in articles and influence. The State University of New York System was the most influential institution, while Frontiers in Psychiatry stood out as the key journal. Utilizing networks and other AI technologies for diagnosing ADHD represents current hotspots and future trends, potentially offering objective indicators for ADHD.

IntroductionPrader-Willi syndrome (PWS) is a rare neurodevelopmental and multisystemic disorder. This syndrome is most often caused by paternal deletion or a maternal disomy of chromosome 15. PWS is characterized by hypotonia, hypogonadism, and hyperphagia. Intellectual disability, impaired social skills, emotional regulation, sleep disorders and behavioral problems (tantrums, temper outbursts, obsessive–compulsive symptoms, skin picking) are also present. Autism spectrum disorder, mood disorders, anxiety, and psychosis are common in these individuals. (Bos-Roubos et al. Frontiers in psychiatry 2022; 13 897138).ObjectivesThe aim of the case is providing a review of psychiartric and behavioral problems in PWS.MethodsClinical case description and literature review on the subject.ResultsWe report a clinical case of a 23 year old man who was diagnosed with PWS. Clinical features includes intellectual disability, obesity, scoliosis bracing, probable hypoventilation-obesity syndrome [using non-invasive ventilation], hypercholesterolemia and hypogonadism. He took 3 doses of testosterone in 2017, which had to be suspended due to serious changes in behavior. Behavioral sporadic problems, reactive to the environment, are also present such as impulsiveness, stubbornness, aggressive outbursts, oppositional behavior, self-injuring behavior (placement of foreign bodies in the ear canal), card obsession and suspicious posture. This clinical condition has an impact on PWS relatives and at social level. He was medicated with Paliperidone 9mg; Topiramate 50mg; Clozapine 25mg; Escitalopram 10mg; and Haloperidol 2mg/ml (SOS). Currently, the patient is stable, with little weight gain and sporadic episodes of greater impulsivity without clinical relevance. He has participating in integrated activities at the institution.ConclusionsThe main limitations in adolescence/adulthood are psychiatric and behavioral comorbidities, in association with hyperphagia and intellectual disability, which become more prominent with age. However, these symptoms are highly variable among individuals of different ages. Antipsychotics have been used for management of psychiatric and/or behavioral comorbidities. Other medications have also been used such as antidepressants (SSRI), antiepileptics, mood stabilizers and the response may vary depending on the individual. Weight gain, due to atypical antipsychotics, can be mitigated when food has controlled access. PWS has a major impact on the individual’s social and family environment, which requires an appropriate multidisciplinary strategy. A safe and constant environment as well as behavioral management programs must be ensured. (Butler et al. Current pediatric reviews 2019; 15 207-244).Disclosure of InterestNone Declared

In this Genomic Press Interview, Dr. Consuelo Walss-Bass, a groundbreaking researcher in psychiatric genetics, explores the fundamental question that has shaped her scientific journey: “Why does my sister have schizophrenia and I do not?” As the John S. Dunn Foundation Distinguished Chair in Psychiatry at the University of Texas Health Science Center at Houston, Dr. Walss-Bass has dedicated her career to unraveling the complex biological mechanisms underlying severe mental health disorders. Her groundbreaking work integrates genomic, proteomic, and clinical research to translate genetic discoveries into practical applications for patient care. Born and educated in Torreón, Mexico, Dr. Walss-Bass overcame significant barriers in engineering to become a distinguished scientist, establishing the UTHealth-Houston Brain Collection as an invaluable resource for studying the molecular foundations of mental illness. Her innovative work with induced pluripotent stem cells has opened new avenues for personalized psychiatric medicine, while her integrated approach to understanding how genetic makeup interacts with environmental factors represents one of the most promising frontiers in psychiatry. Beyond her research contributions, she demonstrates a profound commitment to mentoring the next generation of scientists, particularly those from underrepresented backgrounds. Through this comprehensive interview, Dr. Walss-Bass shares insights into both her personal connection to mental illness that motivated her transition from cancer research to psychiatric genetics and her vision for destigmatizing mental health disorders by uncovering their biological underpinnings, ultimately aiming to improve diagnosis, treatment, and public understanding of conditions like schizophrenia and bipolar disorder.

Artificial intelligence and neuromodulation: A new frontier in psychiatry

Abstract Background In current days, smartphone use is inevitable in everyday life and has increased drastically over recent decades not only in adults but also in adolescents. Even though smartphone provides convenience and produces personal pleasure, the potential causable problems due to excessive smartphone use (ESU) of adolescents have been reported continuously. As ESU of adolescents became one of the important social issue, the connection between specific personality traits and ESU is being studied continuously. Aims & Objectives This study explored whether altered resting state functional connectivity (rsFC) is related to personality traits and other psychological factors in adolescents demonstrating ESU compared to healthy controls (HCs). Methods Thirty six adolescents (38.7%) were prone to ESU and fifty seven adolescents were HCs. Smartphone Addiction Proneness Scale for Adolescents (S-scale) was used to measure ESU and adolescent version of temperament and character inventory (JTCI) was used to measure personality traits in this study. For rsFC analysis, the left and right central executive network (CEN), the salience network (SN) and default mode network (DMN) were included in the analysis in order to investigate the brain networks related to personality traits that impact ESU. In addition, orbitofrontal cortex (OFC), midcingulate cortex (MCC) and nucleus accumbens (NAcc), which are related to reward processing and cognitive control, were included in the analysis in order to examine the brain networks related to temperament and character subscales of TCI that influence ESU. Results Mean scores of ESU adolescents were lower in persistence than HCs. In addition, HCs group had a positive correlation with novelty seeking and a negative correlation with persistence in bivariate correlation analysis. However, ESU group had no significant correlation with TCI personality traits. In the rsFC, ESU group showed lower functional connectivity in brain regions related to the salience network compared with HCs. ESU showed lower connectivity between the left middle cingulate cortex (MCC) and left superior parietal lobule, and between the left MCC and left postcentral gyrus. In addition, lower connectivity between the left posterior cingulate gyrus and right precentral gyrus and between the left orbital frontoinsula and right precentral gyrus were shown in ESU. Discussion & Conclusions This study suggests that smartphone proneness was associated with low persistence in terms of temperament and it was engaged in neurofunctional alterations. References Chun, J.W., Choi, J., Cho, H., Choi, M.R., Ahn, K.J., Choi, J.S. and Kim, D.J., 2018. Role of frontostriatal connectivity in adolescents with excessive smartphone use. Frontiers in psychiatry, 9, p.437. Chun, J.W., Park, C.H., Kim, J.Y., Choi, J., Cho, H., Jung, D.J., Ahn, K.J., Choi, J.S., Kim, D.J. and Choi, I.Y., 2020. Altered core networks of brain connectivity and personality traits in internet gaming disorder. Journal of Behavioral Addictions, 9(2), pp.298-311. Kheradmand, A., Amirlatifi, E.S. and Rahbar, Z., 2023. Personality traits of university students with smartphone addiction. Frontiers in Psychiatry, 14, p.1083214.

Abstract Background Recent studies have also shown that mitochondrial function and oxidative stress might play important roles in bone metabolism. Whether patients with opioid use disorder (OUD) experienced a decrease in bone density and an increased risk of osteoporosis and fractures through this mechanism is still unknown. Therefore, we examined the mitochondrial function between health control subjects the OUD patients under methadone maintenance treatment. Methods We conducted a cross-sectional cohort study. Patients with OUD receiving methadone maintenance treatment in Changhua Christian Hospital in Taiwan were recruited. We compared the difference between patients with OUD and without OUD in Mitochondrial DNA (mtDNA) copy number, oxidative modification of mtDNA index(mtDNA(DeltaCT)), and 8-hydroxy-2'-deoxyguanosine. Results Finally, 29 patients from MMT were allocated in opioid group. 37 health control subjects were allocated in control group. Patients in opioid group had significantly lower mtDNA than those in control group. Besides, patients in opioid group also had significantly lower DeltaCT and 8-hydroxy-2'-deoxyguanosine than those in control group. Conclusions Mitochondrial dysfunction was found in patients with OUD in our study. The precise role of mitochondrial dysfunction in bone density metabolism in this population should be further investigated. References Wen-Yu Hsu, et al. (2019) Association between opioid use disorder and fractures: a population-based study. Addiction. 114(11):2008-2015. Wen-Yu Hsu, et al. (2018) Medications Used for Cognitive Enhancement in Patients With Schizophrenia, Bipolar Disorder, Alzheimer's Disease, and Parkinson's Disease. Frontiers in Psychiatry. 9:91.

BackgroundDepression is common and costly. First-line antidepressants are ineffective for many and have little impact against cognitive deficits. Stimulating 5-HT4 receptors (5-HT4R) rapidly improves learning and has antidepressant-like effects in rodents 1,2. The highly-selective 5-HT4R agonist, prucalopride (licensed for constipation), had a facilitatory effect on behavioural learning/memory in healthy humans after a single 3 and 6 days' treatment 4,5. Neurally, it also increased hippocampal activity 4 and reduced activation within the default mode network 5, findings supported at a network level by resting state analyses 6.Aims & ObjectivesHere, we present results from 2 further translational studies, examining 5-HT4R agonists in the context of mental illness. In study 1, we hypothesised that 5-HT4R agonism in participants with un-medicated depression would also increase hippocampal activation during a memory encoding task. In study 2, using a live electronic health record database, we investigated whether a prescription of prucalopride for constipation compared to alternative anti-constipation agents would reduce the future risk of depression.MethodFor study 1, 57 right-handed un-medicated depressed patients were randomised to a 5-HT4R agonist PF-04995274 (15mg) or placebo in a double-blind design. 53 participants received a 3T scan and fMRI memory task eliciting hippocampal activation 7 on day 6-9. Emotionally-neutral “familiar” pictures were viewed before the scan, and again in the scanner with similar “novel” images. Imaging data were analysed with FSL and corrected for multiple comparisons/sex/perfusion/grey matter. Study 2 was an emulated target trial using anonymised routinely collected data from TriNetX Analytics. We included adults without prior mental illness who received either a prescription of prucalopride (primary cohort) or linaclotide/lubiprostone (comparator cohorts). Cohorts were matched for 118 covariates capturing sociodemographics, comorbidities, and concurrent medications. The primary outcome was a first diagnosis of depressive disorder (ICD-10 F32) within two years of prescription date.Results5-HT4 versus placebo participants had significantly lower HAM-D scores after study 1 [HAM-D 17: F(1,56)=7.6; p<0.01]. In hippocampal analyses, while processing scenes, the 5-HT4 group had significantly increased activity to novel compared to familiar images, particularly in the left hemisphere [condition*hemisphere*group: F(1,49)=3.56, p=0.04, ηρ2=0.08); novel vs familiar (i) prucalopride L (p=0.035) &R hemisphere (p=0.050); (ii) placebo L (p=0.789) &R hemisphere (p=0.053)]. In study 2, treatment with prucalopride was associated with reduced incidence of depression compared to both lubiprostone [HR 0.84, 95% CI 0.73-0.96, p=0.01, n=7101) and linaclotide (HR 0.85, 95% CI 0.75-0.97, p=0.016, n=6460]. Secondary analyses indicated robustness and specificity of the results.Discussion & ConclusionIn participants with un-medicated depression, the 5-HT4R agonist PF-04995274 increased hippocampal activation during a memory task; a replication of previous results in healthy volunteers using another 5-HT4R agonist. The pharmaco-epidemiological findings also suggest 5-HT4R agonists may be novel agents in the prevention of depression. Results from both studies are consistent with preclinical evidence establishing a key role for 5-HT4Rs in mood disorders and cognitive deficits.References1) Lucas G, Rymar VV, Du J, et al. Serotonin(4) (5-HT(4)) receptor agonists are putative antidepressants with a rapid onset of action. Neuron 2007; 55(5): 712-25.2) Murphy SE, de Cates AN, Gillespie AL, et al. Translating the promise of 5HT4 receptor agonists for the treatment of depression. Psychol Med 2021; 51(7): 1111-20.3) Murphy S, Wright L, Browning M, Cowen P, Harmer C. A role for 5-HT4 receptors in human learning and memory. Psychol Med 2020; 50(16): 2722-30.4)de Cates AN, Wright LC, Martens MAG, et al. Deja-vu? Neural and behavioural effects of the 5-HT4 receptor agonist, prucalopride, in a hippocampal-dependent memory task. Trans Psychiatry 2021; 11: 497.5) de Cates AN, Martens MAG, Wright LC, et al. The effect of the 5-HT4 agonist, prucalopride, on an fMRI faces task in the healthy human brain. Frontiers in Psychiatry 2022; 13(859123).6) de Cates AN, Martens MAG, Wright LC, et al. 5-HT4 receptor agonist effects on functional connectivity in the human brain; Implications for pro-cognitive action. Biol Psychiatry Cogn Neurosci Neuroimaging 2023.7) Filippini N, MacIntosh BJ, Hough MG, et al. Distinct patterns of brain activity in young carriers of the APOE-epsilon4 allele. Proc Natl Acad Sci U S A 2009; 106(17): 7209-14.

BackgroundSchizophrenia is associated with excess mortality compared to the general population for both COVID-19 and pneumonia (1,2). Immune dysfunction may play a role in poorer outcomes. Schizophrenia has been associated with altered serum cytokine levels (3) and blunted response to vaccines relative to healthy controls (4). Patients with psychotic disorders have an increased risk of COVID-19 infection despite vaccination (5).Aims & ObjectivesWe tested the hypothesis that COVID-19 vaccine response is lower in schizophrenia relative to controls. With clozapine reported to have immunosuppressant effects, we also tested the hypothesis that patients treated with clozapine have a significantly lower response to Pneumococcal vaccination compared to healthy volunteers.MethodsWe employed an open-label prospective study involving 4 cohorts. First, patients with psychotic disorders on any antipsychotic medication and matched healthy controls received the COVID- 19 vaccine. A separate cohort of patients on clozapine treatment and matched healthy controls received the Pneumovax-23 vaccine. Patients were recruited from adult mental health teams in South London and Maudsley NHS Foundation Trust. Controls with no history of psychosis were recruited from the same region. All participants provided baseline blood samples prior to receiving either the COVID-19 or Pneumovax-23 vaccine. Samples were then obtained 1-month post-vaccination, including SARS-CoV-2 spike protein IgG and anti-Pneumococcal total IgG (according to received vaccine). Also, in participants receiving Pneumovax-23, cytokines (IL-5, IL-6, IL-10, TNF-α, IFN-γ) and immunoglobulins (IgM, IgA, and IgG) were analysed at baseline and 6-hours post-vaccination to assess acute immune response.Results24 patients and 33 controls received the COVID-19 vaccine. Changes in SARS-CoV-2 spike protein IgG levels were significantly lower in patients (mean [SD]: +2.94 [1.80]) versus controls (+3.95 [1.64]; t55=-2.20, p=0.03). All controls positively seroconverted while 3 patients, who were all prescribed clozapine, did not. Collection of Pneumovax-23 response data is ongoing. Currently, 21 clozapine-treated patients and 13 controls have received the vaccine. Baseline general IgG levels were significantly lower in patients (8.82 [2.59]) compared to controls (12.40 [2.77], t31=-4.4, p<0.001). Of these, 16 patients and 12 controls had baseline negative immunity to Pneumococcus. Changes in anti- Pneumococcal total IgG was significantly lower in patients (+33.93 [30.57]) compared to controls (+59.79 [23.59], t26=-2.43, p=0.02). All but 1 control positively seroconverted, while 8 patients on clozapine did not reach protective anti-Pneumococcal antibody levels. Changes in cytokines or immunoglobulins at 6-hours post Pneumovax-23 did not differ between groups.Discussion & ConclusionsCOVID-19 vaccine response was lower in patients with psychotic disorders relative to controls, suggesting an impaired immune response to the SARS-CoV-2 spike protein. Clozapine-treated patients had an impaired Pneumococcal vaccine response compared to healthy volunteers, with 50% not achieving protective antibody levels. Our findings indicate that patients with psychotic disorders, particularly those treated with clozapine, are at risk of inadequate immunity despite vaccination efforts. Future studies should aim to control for demographic confounders and examine long-term vaccine response.References1)De Hert, M. et al. (2022) “COVID-19-related mortality risk in people with severe mental illness: A systematic and critical review,” Frontiers in psychiatry, 12. doi: 10.3389/fpsyt.2021.798554.2)Chou, F. H.-C., Tsai, K.-Y. and Chou, Y.-M. (2013) “The incidence and all-cause mortality of pneumonia in patients with schizophrenia: A nine-year follow-up study,” Journal of psychiatric research, 47(4), pp. 460–466. doi: 10.1016/j.jpsychires.2012.12.007.3)Pillinger, T. et al. (2019) “A meta-analysis of immune parameters, variability, and assessment of modal distribution in psychosis and test of the immune subgroup hypothesis,” Schizophrenia bulletin, 45(5), pp. 1120–1133. doi: 10.1093/schbul/sby160.4)Xiao, K. et al. (2022) “Immune response to vaccination in adults with mental disorders: A systematic review,” Journal of affective disorders, 304, pp. 66–77. doi: 10.1016/j.jad.2022.02.025.5)Nishimi, K. et al. (2022) “Association of psychiatric disorders with incidence of SARS-CoV-2 breakthrough infection among vaccinated adults,” JAMA network open, 5(4), p. e227287. doi: 10.1001/jamanetworkopen.2022.7287.

BackgroundMethamphetamine-induced psychosis (MIP) is characterized by transient episodes, but a substantial portion persists long-term (Wearne &Cornish 2018). While symptom similarities exist between MIP and schizophrenia (Sz), their neural correlates remain uncertain. Furthermore, research into the neural basis underlying the presence and duration of MIP psychosis has been limited.Aims & ObjectivesThis study aimed to investigate whether there would be differences in discriminatory ability when classifying methamphetamine (METH) users with or without psychosis and Sz using Sz classifier derived from resting-state fMRI. We also aimed to explore potential differences in the presence and duration of psychosis in METH users.MethodUtilizing the machine learning algorithms (Yamashita et al. 2020), we constructed an Sz classifier using whole-brain functional connectivity from resting-state fMRI data sourced from a Japanese database with 78 Sz patients and 340 healthy individuals (Tanaka et al. 2021). The classifier was tested using independent datasets. For the Taiwan dataset, which consisted of 35 Sz patients, 106 regular METH users and 45 healthy individuals, we applied this classifier to differentiate fMRI data of Sz patients and METH users from healthy individuals. METH users were grouped as MNP (no psychosis, 30 participants), MBP (psychosis lasting 7-30 days, 52 participants), and MPP (psychosis >30 days, 24 participants). Discriminatory abilities of these groups were then compared.ResultsThe Sz classifier's performance ranged from an AUC of 0.77 to 0.86, indicating reliable discriminatory performance. In the Taiwan dataset, Sz exhibited the highest AUC (0.90), followed closely by MPP (AUC: 0.82). Both MBP and MNP displayed values around 0.6. These patterns were consistent in accuracy.Discussion & ConclusionBoth Sz and MPP demonstrated high discriminatory capacities, in contrast to MBP and MNP, which showed less distinction. This suggests that persistent MIP shares neurobiological characteristics more similar to Sz, while transient MIP shares more similar to METH users without psychosis and healthy individuals. The slight differences in performance between Sz and MPP might shed light on their respective pathophysiology. Our method provides a framework for categorizing METH users by their psychosis manifestation and duration, highlighting shared and distinct neurobiological aspects of MIP and Sz.ReferencesWearne, T. A., &Cornish, J. L. (2018). A Comparison of Methamphetamine-Induced Psychosis and Schizophrenia: A Review of Positive, Negative, and Cognitive Symptomatology. Frontiers in psychiatry, 9, 491.Yamashita, A., Sakai, Y., Yamada, T., Yahata, N., Kunimatsu, A., Okada, N., Itahashi, T., Hashimoto, R., Mizuta, H., Ichikawa, N., Takamura, M., Okada, G., Yamagata, H., Harada, K., Matsuo, K., Tanaka, S. C., Kawato, M., Kasai, K., Kato, N., Takahashi, H. &Imamizu, H. (2020). Generalizable brain network markers of major depressive disorder across multiple imaging sites. PLoS biology, 18(12), e3000966.Tanaka, S. C., Yamashita, A., Yahata, N., Itahashi, T., Lisi, G., Yamada, T., Ichikawa, N., Takamura, M., Yoshihara, Y., Kunimatsu, A., Okada, N., Hashimoto, R., Okada, G., Sakai, Y., Morimoto, J., Narumoto, J., Shimada, Y., Mano, H., Yoshida, W., Seymour, B. &Imamizu, H. (2021). A multi-site, multi-disorder resting- state magnetic resonance image database. Scientific data, 8(1), 227.

BackgroundWhereas ketamine has displayed robust antidepressant effects in treatment-resistant depression (TRD) (Han et al., 2016), only 30-40% of patients with TRD respond to ketamine therapy (Wilkinson et al., 2018; Sakurai et al., 2020). Several postmortem studies have shown decreased myelination in patients with depression (Hamidi, Drevets and Price, 2004; Altshuler et al., 2010), and an animal study suggested that increased myelination may underlie the antidepressant effects of ketamine for TRD (Huang et al., 2023). Quantitative susceptibility mapping (QSM) is a magnetic resonance imaging technique for assessing magnetic susceptibility in brain tissues, which can examine the degrees of iron deposition and myelination (Harada et al., 2022). Several studies noted increased susceptibility in the subcortical regions of patinets with depression (Yao et al., 2017; Zhang et al., 2019; Duan et al., 2022; Wang et al., 2022). However, no study has examined the relationship between magnetic susceptibility and ketamine treatment efficacy in patients with TRD.Aims and ObjectionsTo evaluate whether pre-treatment subcortical susceptibility can predict clinical outcomes post-ketamine infusion, we conducted a post-hoc analysis of data from a placebo-controlled, double-blind, randomized clinical trial (DBRCT) followed by an open-label trial, where the efficacy of repeated ketamine infusion was examined in patients with TRD.MethodsIn this DBRCT, 34 patients with TRD were either treated with intravenous ketamine (0.5 mg/kg) or placebo, which were administered over 40 minutes, twice weekly for two weeks. After the DBRCT was completed, those allocated to the placebo group were enrolled in an open-label trial, in which the participants received the same ketamine treatment as in DBRCT. The primary outcome was the Montgomery-Å sberg Depression Rating Scale (MADRS) score difference between pre- and post- treatment. All participants underwent 3T MRI scans using a 32-channel head/neck coil with the following parameters: repetition time/first echo time = 44.0/3.6 ms, echo spacing = 5.91 ms, and number of echoes = 8. We measured magnetic susceptibility in the region of interest (ROI), including 10 subcortical structures defined by the ITK-SNAP software. Univariate regression analyses were performed to examine the association between susceptibility in each ROI before ketamine infusion and the change in MADRS total scores after treatment from baseline.ResultsAmong the 34 patients who participated in the original clinical trial, 13 (DBRCT, n=7; open-label phase, n=6) were included in this post-hoc analysis. The mean change in MADRS total score between ketamine treatment was -7.8 ± 6.3. Positive correlations between the baseline susceptibility in the left globus pallidus externa (GPe) (β = 152.8, p = 0.035), left globus pallidus interna (GPi) (β = 153.2, p = 0.042), left substantia nigra (SN) (β = 142.3, p = 0.017) and right SN (β = 131.5, p = 0.031), and the change in MADRS total scores following the treatment.Discussion and ConclusionThe baseline myelination measured by QSM in the left GPe, left GPi, and bilateral SN may predict a favorable response to ketamine treatment in patients with TRD.ReferencesAltshuler, L. L. et al. (2010), “Amygdala astrocyte reduction in subjects with major depressive disorder but not bipolar disorder,” Bipolar Disorders, 12(5), pp. 541–549.Duan, X. et al. (2022), “Quantitative Susceptibility Mapping of Brain Iron Deposition in Patients With Recurrent Depression,” Psychiatry Investigation, 19(8), pp. 668–675.Hamidi, M., Drevets, W. C., and Price, J. L. (2004), “Glial reduction in amygdala in major depressive disorder is due to oligodendrocytes,” Biological Psychiatry, 55(6), pp. 563–569.Han, Y. et al. (2016), “Efficacy of ketamine in the rapid treatment of major depressive disorder: a meta- analysis of randomized, double-blind, placebo-controlled studies,” Neuropsychiatric Disease and Treatment, 12, pp. 2859–2867.Harada, T. et al. (2022), “Quantitative Susceptibility Mapping: Basic Methods and Clinical Applications,” Radiographics: A Review, a Publication of the Radiological Society of North America, Inc., 42(4), pp. 1161–1176.Huang, C. et al. (2023), “Myelin-associated oligodendrocytic basic protein-dependent myelin repair confers the long-lasting antidepressant effect of ketamine." Molecular psychiatry. doi: 10.1038/s41380-023-02288-5.Sakurai, H. et al. (2020), “Long-term outcome in outpatients with depression treated with acute and maintenance intravenous ketamine: A retrospective chart review,” Journal of Affective Disorders, 276, pp. 660–666.Wang, F. et al. (2022), “Alterations in brain iron deposition with progression of late-life depression measured by magnetic resonance imaging (MRI)-based quantitative susceptibility mapping,” Quantitative imaging in medicine and surgery, 12(7), pp. 3873–3888.Wilkinson, S. T. et al. (2018), “Acute and Longer-Term Outcomes Using Ketamine as a Clinical Treatment at the Yale Psychiatric Hospital,” The Journal of Clinical Psychiatry, 79(4). doi: 10.4088/JCP.17m11731. Yao, S. et al. (2017), “Quantitative Susceptibility Mapping Reveals an Association between Brain Iron Load and Depression Severity,” Frontiers in Human Neuroscience, 11, p. 442.Zhang, W. et al. (2019), “Brain Iron Deposits in Thalamus Is an Independent Factor for Depressive Symptoms Based on Quantitative Susceptibility Mapping in an Older Adults Community Population,” Frontiers in Psychiatry / Frontiers Research Foundation, 10, p. 734.

IntroductionDigital mental health care system includes the interventions delivered via digital technologies, such as mobile apps, websites, or virtual reality (VR). A recent upsurge in the digital mental healthcare care services has been observed in the last 5 years. With its core advantage of reaching the unreached, wider coverage, cost and time effectivity, all eyes are on the digital mental health care system. It is definitely a mechanism to cater rising prevalence of mental health concern, stigma towards mental health, accessibility and cost and uplift the psychological wellbeing. Success of the digital mental health care system has been researched world-wide. However, the same is not unaffected by the ethical concerns.MethodsThis study aims to perform a comprehensive bibliometric analysis of scholarly articles on ethical concerns and dilemmas of digital mental health care by utilizing data extracted from the Scopus database from 2000 to 2024 by analysing 123 research articles. Statistical descriptive analysis in combination with performance analysis and co-word analysis was used to understand the research trends, leading countries and country collaborations studying ethical concerns related to digital mental healthcare.Result and discussionThe first publication appeared in 2000 with zero research till the year 2005. In this decade till 2010 we can observe only 4 publications. Consistent publishing started trending upward through 2018, observing the largest increase during pandemic in 2020 and onwards constituting 100 publications. The United States of America is the leading country studying ethical dilemmas in Digital Mental healthcare, with 42 papers followed by United Kingdom with 23 publications. The most influential peace of research with 490 citations is article co-authored by Barak et al. (2009), which is defining internet-supported therapeutic interventions and related concerns. BMJ Open is noted as the leading journal which is publishing issues concerning Digital Mental Healthcare with 18 publications, followed by Frontiers in Psychiatry and JMIR Mental Health. Analyses reflects that the top cited articles on Digital Mental healthcare are specifically directed on bringing out some of the key concerns of data privacy, emergency response, therapist competency and consent which requires appropriate handling Otherwise they may be cause of distress to client and question the trustworthiness of the Digital Mental Health Care system.ConclusionThe concerns brought out through this bibliometric analysis could be important guiding principles for online mental health services. Alongside, mental health professionals operating online must have orientation on the ethical concerns surrounding online mental healthcare.

Background: Sleep disorders, such as insomnia, are pervasive and frequently comorbid with depression, significantly affecting the quality of life of patients. Insomnia is characterized by difficulty initiating or maintaining sleep, which leads to impairment. Depression is characterized by persistent sadness and loss of interest, and it often features symptoms of insomnia. Understanding their interaction will be done for treatment strategies concerning both disorders. Despite the existence of extensive studies on insomnia and depression, there is a significant gap in bibliometric analysis specifically addressing the comorbidity of these two conditions. Objectives: This study is aimed at conducting a bibliometric analysis of research in insomnia comorbid with depression (ICD) to identify research trends, collaboration patterns, influential works, and hotspots. Methods: The study involved performance analysis to evaluate research productivity and trends, science mapping to visualize the intellectual structure and thematic evolution of the field, and network analysis to examine research collaboration and knowledge structure. Tools such as VOSviewer, CiteSpace, and GraphPad Prism were utilized for data analysis. Results: A total of 1624 publications on the comorbidity of insomnia and depression from 2000 to 2024 were included, encompassing both articles and reviews. Publication volume showed a steady growth from 2000 to 2008, followed by a significant increase from 2019 onward. The United States was the most productive country, followed by China. Key authors such as Allison G. Harvey, Charles M. Morin, and Daniel J. Buysse have made substantial contributions to the field. Major influential journals included Sleep Medicine, Journal of Affective Disorders, and Frontiers in Psychiatry. Research trends identified included the exploration of neurobiological mechanisms, cognitive behavioral therapy for insomnia (CBT-i), and personalized treatment approaches. Conclusion: This bibliometric analysis provides valuable insights into the evolving landscape of research on ICD. Future research should focus on personalized, multimodal interventions, expanding the application of CBT-i, exploring neurobiological mechanisms, and improving patients' quality of life through integrated treatment strategies.

BackgroundLanguage deficits, restricted and repetitive interests, and social difficulties are among the characteristics of autism spectrum disorder (ASD). Machine learning and neuroimaging have also been combined to examine ASD. Utilizing bibliometric analysis, this study examines the current state and hot topics in machine learning for ASD.ObjectiveA research bibliometric analysis of the machine learning application in ASD trends, including research trends and the most popular topics, as well as proposed future directions for research.MethodsFrom 1999 to 2023, the Web of Science Core Collection (WoSCC) was searched for publications relating to machine learning and ASD. Authors, articles, journals, institutions, and countries were characterized using Microsoft Excel 2021 and VOSviewer. Analysis of knowledge networks, collaborative maps, hotspots, and trends was conducted using VOSviewer and CiteSpace.ResultsA total of 1357 papers were identified between 1999 and 2023. There was a slow growth in publications until 2016; then, between 2017 and 2023, a sharp increase was recorded. Among the most important contributors to this field were the United States, China, India, and England. Among the top major research institutions with numerous publications were Stanford University, Harvard Medical School, the University of California, the University of Pennsylvania, and the Chinese Academy of Sciences. Wall, Dennis P. was the most productive and highest-cited author. Scientific Reports, Frontiers In Neuroscience Autism Research, and Frontiers In Psychiatry were the three productive journals. “autism spectrum disorder”, “machine learning”, “children”, “classification” and “deep learning” are the central topics in this period.ConclusionCooperation and communication between countries/regions need to be enhanced in future research. A shift is taking place in the research hotspot from “Alzheimer's Disease”, “Mild Cognitive Impairment” and “cortex” to “artificial intelligence”, “deep learning”, “electroencephalography” and “pediatrics”. Crowdsourcing machine learning applications and electroencephalography for ASD diagnosis should be the future development direction. Future research about these hot topics would promote understanding in this field.