Precision Psychiatry

Mental Status Assessment (MSA) holds significant importance in psychiatry. In recent years, several studies have leveraged Electroencephalogram (EEG) technology to gauge an individual's mental state or level of depression. This study introduces a novel multi-tier ensemble learning approach to integrate multiple EEG bands for conducting mental state or depression assessments. Initially, the EEG signal is divided into eight sub-bands, and then a Long Short-Term Memory (LSTM)-based Deep Neural Network (DNN) model is trained for each band. Subsequently, the integration of multi-band EEG frequency models and the evaluation of mental state or depression level are facilitated through a two-tier ensemble learning approach based on Multiple Linear Regression (MLR). The authors conducted numerous experiments to validate the performance of the proposed method under different evaluation metrics. For clarity and conciseness, the research employs the simplest commercialized one-channel EEG sensor, positioned at FP1, to collect data from 57 subjects (49 depressed and 18 healthy subjects). The obtained results, including an accuracy of 0.897, F1-score of 0.921, precision of 0.935, negative predictive value of 0.829, recall of 0.908, specificity of 0.875, and AUC of 0.8917, provide evidence of the superior performance of the proposed method compared to other ensemble learning techniques. This method not only proves effective but also holds the potential to significantly enhance the accuracy of depression assessment.

Understanding the impacts of environmental exposures on health outcomes during development is an important area of research for plenty of reasons. Collecting retrospective and prospective residential history can enrich observational studies through eventual linkages to external sources. Augmenting participant health outcome data with environmental data can better inform on the role of the environment, thereby enhancing prevention and intervention efforts. However, collecting the geospatial information needed for this type of research can be difficult, especially when data are collected directly from participants. Participants' residential histories are unique and often complex. Collecting residential history data often involves capturing precise spatial locations along specific timeframes as well as contending with recall bias and unique, complex living arrangements. When trying to assess lifetime environmental exposures, researchers must consider the many changes in location a person goes through and the timeframes in which these changes occur, ultimately creating a multidimensional and dynamic dataset. Creating data collection protocols that are feasible to administer, result in accurate data, and minimize data missingness is a major challenge to undertake. Here, we provide an overview of the protocol developed to collect the lifetime residential address information of participants in the Adolescent Brain Cognitive Development (ABCD) Study.

Antipsychotics and mood stabilisers are gathering attention for the disturbance of metabolism. This network meta-analysis aims to evaluate and rank the metabolic effects of the commonly used antipsychotics and mood stabilisers in treating bipolar disorder (BD).

Hair has become an increasingly valuable medium to investigate the association between chronic stress, stable differences in systemic cortisol secretion and later health. Assessing cortisol in hair has many advantages, notably its non-invasive and retrospective nature, the need for a single biospecimen and convenient storage until analysis. However, few studies offered empirical evidence documenting the long-term temporal stability of hair cortisol concentration (HCC) prior to analysis, especially in humans. Yet, knowing how long hair samples can be stored without compromising the accuracy of cortisol measurement is of crucial importance when planning data collection and analysis. This study examined the stability of HCC in hair samples assayed twice, five years apart.

Patients with schizophrenia have substantial comorbidity that contributes to reduced life expectancy of 10 to 20 years. Identifying modifiable comorbidities could improve rates of premature mortality. Conditions that frequently co-occur but lack shared genetic risk with schizophrenia are more likely to be products of treatment, behavior, or environmental factors and therefore are enriched for potentially modifiable associations.

Nowadays, there are emerging trends in customized and personalized photoprotection, focusing on the innovative approaches to enhance sun protection efficacy tailored to individual needs.

Essential tremor (ET) is a prevalent neurological disorder with a largely unknown underlying biology. In this genome-wide association study meta-analysis, comprising 16,480 ET cases and 1,936,173 controls from seven datasets, we identify 12 sequence variants at 11 loci. Evaluating mRNA expression, splicing, plasma protein levels, and coding effects, we highlight seven putative causal genes at these loci, including CA3 and CPLX1. CA3 encodes Carbonic Anhydrase III and carbonic anhydrase inhibitors have been shown to decrease tremors. CPLX1, encoding Complexin-1, regulates neurotransmitter release. Through gene-set enrichment analysis, we identify a significant association with specific cell types, including dopaminergic and GABAergic neurons, as well as biological processes like Rho GTPase signaling. Genetic correlation analyses reveals a positive association between ET and Parkinson's disease, depression, and anxiety-related phenotypes. This research uncovers risk loci, enhancing our knowledge of the complex genetics of this common but poorly understood disorder, and highlights CA3 and CPLX1 as potential therapeutic targets.

To evaluate the accuracy and precision of continuous overnight oxygen saturation (SpO) measurement by a commercial wrist device (WD) incorporating high-grade sensors, and investigate WD estimation of sleep-disordered breathing by quantifying overnight oxygen desaturation index (ODI) compared to polysomnography (PSG) ODI and apnea-hypopnea index (AHI) with and without sleep questionnaire data, to assess WD ability to detect obstructive sleep apnea (OSA) and determine its severity.

Pathogenic mutant huntingtin (mHTT) infiltrates the adult Huntington's disease (HD) brain and impairs fetal corticogenesis. However, most HD animal models rarely recapitulate neuroanatomical alterations in adult HD and developing brains. Thus, the human cortical organoid (hCO) is an alternative approach to decode mHTT pathogenesis precisely during human corticogenesis. Here, we replicated the altered corticogenesis in the HD fetal brain using HD patient-derived hCOs. Our HD-hCOs had pathological phenotypes, including deficient junctional complexes in the neural tubes, delayed postmitotic neuronal maturation, dysregulated fate specification of cortical neuron subtypes, and abnormalities in early HD subcortical projections during corticogenesis, revealing a causal link between impaired progenitor cells and chaotic cortical neuronal layering in the HD brain. We identified novel long, oriented, and enriched polyQ assemblies of HTTs that hold large flat Golgi stacks and scaffold clathrin+ vesicles in the neural tubes of hCOs. Flat Golgi stacks conjugated polyQ assemblies by ADP-ribosylation factor 1 (ARF1). Inhibiting ARF1 activation with Brefeldin A (BFA) disassociated polyQ assemblies from Golgi. PolyQ assembles with mHTT scaffolded fewer ARF1 and formed shorter polyQ assembles with fewer and shorter Golgi and clathrin vesicles in neural tubes of HD-hCOs compared with those in hCOs. Inhibiting the activation of ARF1 by BFA in healthy hCOs replicated impaired junctional complexes in the neural tubes. Together, endogenous polyQ assemblies with mHTT reduced the Golgi recruiting ARF1 in the neuroepithelium, impaired the Golgi structure and activities, and altered the corticogenesis in HD-hCO.

Parkinson's disease (PKD) is neurodegenerative disorder marked by tremors, bradykinesia, muscle rigidity and reduction in precise hand movements which could lead to improper oral hygiene and Periodontal disease. Current systematic review aims to review existing literature and provide assessment of periodontal health in PKD patients through a meta-analysis METHODS: Review was performed in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines and registered in PROSPERO-CRD42023451700. Databases were searched for studies having sufficient data on periodontal health in patients with PKD compared to healthy controls and reporting outcomes in terms of various periodontal parameters of probing depth (PD), plaque index (PI), clinical attachment level (CAL), presence of bleeding on probing and gingivitis. Quality assessment of included was evaluated using Newcastle Ottawa Scale (NOS).

Ketamine has been established as efficacious in adults living with Treatment-resistant Depression (TRD). Toward providing a quantifiable estimate of the clinical meaningfulness of the therapeutic benefit of ketamine, herein, we conduct a systematic review that aims to report the Number Needed to Treat (NNT) and the Number Needed to Harm (NNH).

To examine trends in incidence of acute diabetes complications in individuals with type 1 or type 2 diabetes with and without severe mental illness (SMI) in Denmark by age and calendar year.

Frontotemporal dementia (FTD) is a debilitating neurodegenerative disorder with currently no disease-modifying treatment options available. Mutations in GRN are one of the most common genetic causes of FTD, near ubiquitously resulting in progranulin (PGRN) haploinsufficiency. Small molecules that can restore PGRN protein to healthy levels in individuals bearing a heterozygous GRN mutation may thus have therapeutic value. Here, we show that epigenetic modulation through bromodomain and extra-terminal domain (BET) inhibitors (BETi) potently enhance PGRN protein levels, both intracellularly and secreted forms, in human central nervous system (CNS)-relevant cell types, including in microglia-like cells. In terms of potential for disease modification, we show BETi treatment effectively restores PGRN levels in neural cells with a GRN mutation known to cause PGRN haploinsufficiency and FTD. We demonstrate that BETi can rapidly and durably enhance PGRN in neural progenitor cells (NPCs) in a manner dependent upon BET protein expression, suggesting a gain-of-function mechanism. We further describe a CNS-optimized BETi chemotype that potently engages endogenous BRD4 and enhances PGRN expression in neuronal cells. Our results reveal a new epigenetic target for treating PGRN-deficient forms of FTD and provide mechanistic insight to aid in translating this discovery into therapeutics.

Myxofibrosarcoma is a type of soft tissue sarcoma, predominantly characterized by a high propensity for local recurrence, albeit demonstrating a relatively diminished risk for distant metastasis. Its prevalence is notably higher in elderly patients. Here, we present a case of a 73-year-old woman diagnosed with Myxofibrosarcoma. She was subjected to a whole-body bone scan using Tc-methylene diphosphonate (MDP) to survey potential bony metastasis. It revealed marked MDP accumulation with peripheral soft tissue uptake in the right lateral chest region of this patient. This imaging phenotype could potentially be attributed to the augmented vascularity within the tumor, a finding that was prominently displayed in this particular case.

An increase in the demand for quality of life following spinal cord injuries (SCIs) is associated with an increase in musculoskeletal (MSK) pain, highlighting the need for preventive measure research.

Alzheimer's disease (AD) pathology is considered to begin in the brainstem, and cerebral microglia are known to play a critical role in AD pathogenesis, yet little is known about brainstem microglia in AD. Translocator protein (TSPO) PET, sensitive to activated microglia, shows high signal in dorsal brainstem in humans, but the precise location and clinical correlates of this signal are unknown.

In the United States, the societal costs associated with drug use surpass $500 billion annually. The rewarding and reinforcing properties that drive the use of these addictive substances are typically examined concerning the neurobiological effects responsible for their abuse potential. In this review, terms such as "abuse potential," "drug," and "addictive properties" are used due to their relevance to the methodological, theoretical, and conceptual framework for understanding the phenomenon of drug-taking behavior and the associated body of preclinical and clinical literature. The use of these terms is not intended to cast aspersions on individuals with substance use disorders (SUD). Understanding what motivates substance use has been a focus of SUD research for decades. Much of this corpus of work has focused on the shared effects of each drug class to increase dopaminergic transmission within the central reward pathways of the brain, or the "reward center." However, the precise influence of each drug class on dopamine signaling, and the extent thereof, differs considerably. Furthermore, the aforementioned substances have effects on several neurobiological targets that mediate and modulate their addictive properties. The current manuscript sought to review the influence of drug class on the rewarding effects of each of the major pharmacological classes of addictive drugs (i.e., psychostimulants, opioids, nicotine, alcohol, and cannabinoids). Our review suggests that even subtle differences in drug effects can result in significant variability in the subjective experience of the drug, altering rewarding and other reinforcing effects. Additionally, this review will argue that reward (i.e., the attractive and motivational property of a stimulus) alone is not sufficient to explain the abuse liability of these substances. Instead, abuse potential is best examined as a function of both positive and negative reinforcing drug effects (i.e., stimuli that the subject will work to attain and stimuli that the subject will work to end or avoid, respectively). Though reward is central to drug use, the factors that motivate and maintain drug taking are varied and complex, with much to be elucidated.

The antidepressant effects of ketamine and esketamine are well-documented. Nonetheless, most of the underlying molecular mechanisms have to be uncovered yet. In the last decade, metabolomics has emerged as a useful means to investigate the metabolic phenotype associated with depression as well as changes induced by antidepressant treatments. This mini-review aims at summarizing the main findings from preclinical and clinical studies that used metabolomics to investigate the metabolic effects of subanesthetic, antidepressant doses of ketamine and esketamine and their relationship with clinical response. Both animal and human studies report alterations in several metabolic pathways - including the tricarboxylic acid cycle, glycolysis, the pentose phosphate pathway, lipid metabolism, amino acid metabolism, the kynurenine pathway, and the urea cycle - following the administration of ketamine or its enantiomers. Although more research is needed to clarify commonalities and differences in molecular mechanisms of action between the racemic compound and its enantiomers, these findings comprehensively support an influence of ketamine and esketamine on mitochondrial and cellular energy production, membrane homeostasis, neurotransmission, and signaling. Metabolomics may thus represent a promising strategy to clarify molecular mechanisms underlying treatment-resistant depression and related markers of clinical response to ketamine and esketamine. This body of preclinical and clinical evidence, if further substantiated, has the potential to guide clinicians towards personalized approaches, contributing to new paradigms in the clinical management of depression.

In a recent study, Kim et al. utilized gamma entrainment using sensory stimuli (GENUS) to rescue cognitive impairment and glial dysregulation associated with cisplatin and methotrexate chemotherapy, specifically when applied both throughout and after chemotherapy administration. GENUS provides a time-dependent, non-invasive method for treating chemobrain, with broader implications for resolving neurodegenerative neuroinflammation.

The response variability to repetitive transcranial magnetic stimulation (rTMS) challenges the effective use of this treatment option in patients with schizophrenia. This variability may be deciphered by leveraging predictive information in structural MRI, clinical, sociodemographic, and genetic data using artificial intelligence. We developed and cross-validated rTMS response prediction models in patients with schizophrenia drawn from the multisite RESIS trial. The models incorporated pre-treatment sMRI, clinical, sociodemographic, and polygenic risk score (PRS) data. Patients were randomly assigned to receive active (N = 45) or sham (N = 47) rTMS treatment. The prediction target was individual response, defined as ≥20% reduction in pre-treatment negative symptom sum scores of the Positive and Negative Syndrome Scale. Our multimodal sequential prediction workflow achieved a balanced accuracy (BAC) of 94% (non-responders: 92%, responders: 95%) in the active-treated group and 50% in the sham-treated group. The clinical, clinical + PRS, and sMRI-based classifiers yielded BACs of 65%, 76%, and 80%, respectively. Apparent sadness, inability to feel, educational attainment PRS, and unemployment were most predictive of non-response in the clinical + PRS model, while grey matter density reductions in the default mode, limbic networks, and the cerebellum were most predictive in the sMRI model. Our sequential modelling approach provided superior predictive performance while minimising the diagnostic burden in the clinical setting. Predictive patterns suggest that rTMS responders may have higher levels of brain grey matter in the default mode and salience networks which increases their likelihood of profiting from plasticity-inducing brain stimulation methods, such as rTMS. The future clinical implementation of our models requires findings to be replicated at the international scale using stratified clinical trial designs.

Brain aging is typically associated with a significant decline in cognitive performance. Vascular risk factors (VRF) and subsequent atherosclerosis (AS) play a major role in this process. Brain resilience reflects the brain's ability to withstand external perturbations, but the relationship of brain resilience with cognition during the aging process remains unclear. Here, we investigated how brain topological resilience (BTR) is associated with cognitive performance in the face of aging and vascular risk factors. We used data from two cross-ethnicity community cohorts, PolyvasculaR Evaluation for Cognitive Impairment and Vascular Events (PRECISE, n = 2220) and Sydney Memory and Ageing Study (MAS, n = 246). We conducted an attack simulation on brain structural networks based on k-shell decomposition and node degree centrality. BTR was defined based on changes in the size of the largest subgroup of the network during the simulation process. Subsequently, we explored the negative correlations of BTR with age, VRF, and AS, and its positive correlation with cognitive performance. Furthermore, using structural equation modeling (SEM), we constructed path models to analyze the directional dependencies among these variables, demonstrating that aging, AS, and VRF affect cognition by disrupting BTR. Our results also indicated the specificity of this metric, independent of brain volume. Overall, these findings underscore the supportive role of BTR on cognition during aging and highlight its potential application as an imaging marker for objective assessment of brain cognitive performance.

Attention-Deficit/Hyperactivity Disorder (ADHD), characterized by clinical diversity, poses diagnostic challenges often reliant on subjective assessments. Metabolomics presents an objective approach, seeking biomarkers for precise diagnosis and targeted interventions. This review synthesizes existing metabolomic insights into ADHD, aiming to reveal biological mechanisms and diagnostic potentials. A thorough PubMed and Web of Knowledge search identified studies exploring blood/urine metabolites in ADHD-diagnosed or psychometrically assessed children and adolescents. Synthesis revealed intricate links between ADHD and altered amino acid metabolism, neurotransmitter dysregulation (especially dopamine and serotonin), oxidative stress, and the kynurenine pathway impacting neurotransmitter homeostasis. Sleep disturbance markers, notably in melatonin metabolism, and stress-induced kynurenine pathway activation emerged. Distinct metabolic signatures, notably in the kynurenine pathway, show promise as potential diagnostic markers. Despite limitations like participant heterogeneity, this review underscores the significance of integrated therapeutic approaches targeting amino acid metabolism, neurotransmitters, and stress pathways. While guiding future research, this overview of the metabolomic findings in ADHD suggests directions for precision diagnostics and personalized ADHD interventions.

Alzheimer's disease (AD)-related neuropathological changes can occur decades before clinical symptoms. We aimed to investigate whether neurodevelopment and/or neurodegeneration affects the risk of AD, through reducing structural brain reserve and/or increasing brain atrophy, respectively.

Interoception is defined as the sense of the internal state of the body. Dysfunctions in interoception are found in several mental disorders, including trauma-related conditions. Mindfulness-Based Interventions (MBIs) have been shown to influence interoceptive processes. Randomised controlled trials (RCTs) have investigated whether MBIs impact symptoms and interoception in patients with trauma-related disorders. We undertook a systematic review and meta-analysis to synthesize these data. We included RCTs with an MBI arm which enrolled adult patients with trauma related-disorders or exposure to a traumatic experience, and addressed changes in interoception and trauma-related symptoms. A random-effects multivariate meta-analytic model was performed to quantify group differences in score change from baseline to follow-up. Twelve studies were included in the systematic review, and eleven in the meta-analysis. Overall, MBIs showed small to moderate positive effects on both interoception and symptoms. Despite a high heterogeneity in results, sensitivity analyses confirmed the robustness of the findings. We conclude that the efficacy of MBIs on trauma-related symptoms and interoception is supported by randomised evidence. However, further research is needed to understand whether changes in interoception might underpin the effectiveness of MBIs in trauma-related disorders.

Phosphatidylethanol (PEth) measurement in whole blood samples is established as a specific alcohol biomarker with clinical and forensic applications. Establishment of dried blood spots (DBSs) as a specimen for PEth determination offers several advantages and was the focus of this work. A liquid chromatography tandem mass spectrometry method using a 96-well format for sample preparation was developed and validated. PEth was extracted from DBSs by using isopropanol containing PEth-d5 as internal standard. The blood sampling used a commercial volumetric DBS device having a phosholipase D inhibitor incorporated to stop continuous PEth formation. The method quantified PEth in the range of 0.05-10 μmol/L, with a bias and imprecision of less than 15%. In a clinical study (n = 25) using fingerprick blood, the volumetric device offered more precise quantifications (CV 4.6%) compared with the Whatman 903 Protein Saver card device (CV 16.6%). In another clinical study (n = 48), the use of dried venous and capillary blood, and liquid venous blood was compared under real-life conditions with samples sent by postal service. The capillary and venous DBS samples gave identical results while the liquid blood gave slightly higher values. Calculation of elimination half-life (PEth 16:0/18:1) in 31 cases based on two consecutive samples with 2-9 days in between gave results (mean 6.2 days) that agree with literature but several cases with values over 10 days. In conclusion, this study demonstrates that volumetric DBS is a valid specimen for determination of PEth blood concentrations, offering several advantages.

Middle-aged and older adults with physical disabilities exhibit more common and severe depressive symptoms than those without physical disabilities. Such symptoms can greatly affect the physical and mental health and life expectancy of middle-aged and older persons with disabilities.

Rapidly improving acute respiratory distress syndrome (RIARDS) is an increasingly appreciated subgroup of ARDS in which hypoxemia improves within 24 h after initiation of mechanical ventilation. Detailed clinical and biological features of RIARDS have not been clearly defined, and it is unknown whether RIARDS is associated with the hypoinflammatory or hyperinflammatory phenotype of ARDS. The purpose of this study was to define the clinical and biological features of RIARDS and its association with inflammatory subphenotypes.

One of the challenges in bipolar disorder (BD) lies in early detection of the illness and its recurrences, to improve prognosis. Sleep disturbances (SD) have been proposed as reliable predictive markers of conversion. While preliminary studies have explored the relationship between SD and the onset of mood episodes, the results remain heterogeneous and a few have specifically examined patients' perception of prodromal symptoms and their progression until the episode occurs. Identifying prodromes represents a crucial clinical challenge, as it enables early intervention, thereby reducing the severity of BD. Therefore, the objective of this study is to better characterize and evaluate the progressive nature of SD as prodromal symptoms of mood episodes, and patients' perception of it.

Depression is often accompanied by changes in behavior, including dietary behaviors. The relationship between dietary behaviors and depression has been widely studied, yet previous research has relied on self-reported data which is subject to recall bias. Electronic device-based behavioral monitoring offers the potential for objective, real-time data collection of a large amount of continuous, long-term behavior data in naturalistic settings.

Both endocannabinoid (EC) and endogenous opioid systems are involved in nociceptive processing and may work together synergistically based on preclinical models. This study evaluated the interactive effects of preoperative beta-endorphin concentrations (a key analgesic endogenous opioid) in cerebrospinal fluid (CSF) and ECs (CSF and plasma 2-arachidonoylglycerol [2-AG] and plasma anandamide [AEA]) on postoperative opioid use and pain intensity in a prospective cohort of n = 112 pregnant patients undergoing scheduled cesarean delivery. Maternal blood and CSF samples were collected preoperatively for beta-endorphin and EC assays. Patients completed measures of outpatient opioid use (number of tablets used and days of use) and average pain intensity at 2 weeks postoperatively. Results of general linear model analyses controlling for maternal age, BMI at time of delivery, and race revealed significant multiplicative interactions between EC and beta-endorphin concentrations on number of opioid tablets used (based on pill count), days of opioid use, and total milligram morphine equivalents used in the 2 week follow-up period. Elevated preoperative plasma and CSF 2-AG predicted reduced outpatient opioid analgesic use particularly for patients low in CSF beta-endorphin. Similar analyses for pain intensity at 2-week follow-up indicated a significant interaction (p<.02) characterized by higher preoperative beta-endorphin concentrations being associated with lower subsequent pain only for individuals with low preoperative plasma AEA concentrations. Further exploration of interactions between EC and endogenous opioid inhibitory systems as they influence responses to opioid analgesics in other clinical pain populations may help guide development of precision pain management approaches. PERSPECTIVE: In the postoperative setting of patients undergoing cesarean delivery, elevated endocannabinoids were linked to reduced outpatient opioid analgesic use in individuals who had low endogenous opioid concentrations in cerebrospinal fluid. Further exploration of interactions between these two inhibitory systems as they impact on responses to pain management interventions appears warranted.

It is crucial to regulate N-methyl-D-aspartate (NMDA) function bivalently depending on the central nervous system (CNS) conditions. CNS disorders with NMDA hyperfunction are involved in the pathogenesis of neurotoxic and/or neurodegenerative disorders with elevated D-serine, one of the NMDA receptor co-agonists. On the contrary, NMDA-enhancing agents have been demonstrated to improve psychotic symptoms and cognition in CNS disorders with NMDA hypofunction. Serine racemase (SR), the enzyme regulating both D- and L-serine levels through both racemization (catalysis from L-serine to D-serine) and β-elimination (degradation of both D- and L-serine), emerges as a promising target for bidirectional regulation of NMDA function. In this study, we explored using dimethyl malonate (DMM), a pro-drug of the SR inhibitor malonate, to modulate NMDA activity in C57BL/6J male mice via intravenous administration. Unexpectedly, 400 mg/kg DMM significantly elevated, rather than decreased (as a racemization inhibitor), D-serine levels in the cerebral cortex and plasma. This outcome prompted us to investigate the regulatory effects of dodecagalloyl-α-D-xylose (α12G), a synthesized tannic acid analog, on SR activity. Our findings showed that α12G enhanced the racemization activity of human SR by about 8-fold. The simulated and fluorescent assay of binding affinity suggested a noncooperative binding close to the catalytic residues, Lys56 and Ser84. Moreover, α12G treatment can improve behaviors associated with major CNS disorders with NMDA hypofunction including hyperactivity, prepulse inhibition deficit, and memory impairment in animal models of positive symptoms and cognitive impairment of psychosis. In sum, our findings suggested α12G is a potential therapeutic for treating CNS disorders with NMDA hypofunction.

With disease-modifying treatment for Parkinson's disease (PD) associated with variants in the glucocerebrosidase gene (GBA1) under way, the challenge to design clinical trials with non-PD-manifest GBA mutation carriers (GBA1) comes within close reach. To delineate trajectories of motor and non-motor markers as well as serum neurofilament light (sNfL) levels and to evaluate clinical endpoints as outcomes for clinical trials in GBA1, longitudinal data of 56 GBA1 carriers and 112 age- and sex-matched GBA1 wildtype participants (GBA1) with up to 9 years of follow-up was analyzed using linear mixed-effects models (LMEM) and Kaplan-Meier survival analysis of clinical endpoints for motor and cognitive function. GBA1 showed worse performance in Pegboard, 20 m fast walking, global cognition as well as in executive and memory function at baseline. Longitudinally, LMEM revealed a higher annual increase of the MDS-UPDRS III bradykinesia subscore in GBA1 compared to GBA1, but comparable trajectories of all other motor and non-motor markers as well as sNfL. Kaplan-Meier survival analysis showed a significantly earlier progression to clinical endpoints of cognitive decline in GBA1. Incidence of PD was significantly higher in GBA1. In conclusion, our study extends data on GBA1 indicating early cognitive decline as a potentially characteristic feature. Comprehensive longitudinal assessments of cognitive function are crucial to delineate the evolution of early changes in GBA1 enabling a more accurate stratification and allow for a more precise definition of trial design and sample size.

Bipolar disorder is associated with increased rates of many physical disorders, but the effects of medication are unclear. We systematically investigated the associations between sustained use of first line maintenance agents, lithium versus lamotrigine and valproate, and the risk of physical disorders using a nation-wide population-based target trial emulation covering the entire 5.9 million inhabitants in Denmark. We identified two cohorts. Cohort 1: patients with a diagnosis of bipolar disorder prior to first purchase (N = 12.607). Cohort 2: all 156.678 adult patients who had their first ever purchase (since 1995) of either lithium, lamotrigine or valproate between 1997 and 2021 regardless of diagnosis. Main analyses investigated the effect of sustained exposure defined as exposure for all consecutive 6-months periods during a 10-year follow-up. Outcomes included a diagnosis of incident stroke, arteriosclerosis, angina pectoris, myocardial infarction, diabetes mellitus, myxedema, osteoporosis, dementia, Parkinson's disease, chronic kidney disease and cancer (including subtypes). In both Cohorts 1 and 2, there were no systematic statistically significant differences in associations between sustained use of lithium versus lamotrigine and valproate, respectively, and any physical disorder, including subtypes of disorders, except myxedema, for which exposure to lithium increased the absolute risk of myxedema with 7-10 % compared with lamotrigine or valproate. In conclusion, these analyses emulating a target trial of "real world" observational register-based data show that lithium does not increase the risk of developing any kind of physical disorders, except myxedema, which may be a result of detection bias.

The precise roles of screen media activity (SMA) and sleep problems in relation to child/adolescent psychopathology remain ambiguous. We investigated temporal relationships among sleep problems, SMA, and psychopathology and potential involvement of thalamus-prefrontal-cortex (PFC)-brainstem structural covariation.

Recently, we developed Research and Diagnostic Algorithm Rules (RADAR) to assess the clinical and pathway features of mood disorders. The aims of this paper are to review a) the methodology for developing continuous RADAR scores that describe the clinical and pathway features of schizophrenia, and b) a new method to visualize the clinical status of patients and the pathways implicated in RADAR graphs. We review how to interpret clinical RADAR scores, which serve as valuable tools for monitoring the staging of illness, lifetime suicidal behaviors, overall severity of illness, a general cognitive decline index, and a behavior-cognitive-psychosocial (BCPS) index that represents the "defect"; and b) pathway RADAR scores which reflect various protective (including the compensatory immune- inflammatory system) and adverse (including neuro-immune, neuro-oxidative, and neurotoxic biomarkers) outcome pathways. Using RADAR scores and machine learning, we created new, qualitatively different types of schizophrenia, such as major neurocognitive psychosis and simple psychosis. We also made RADAR graphs, which give us a quick way to compare the patient's clinical condition and pathways to those of healthy controls. We generated a personalized fingerprint for each patient, encompassing various clinical and pathway features of the disorder represented through RADAR graphs. The latter is utilized in clinical practice to assess the clinical condition of patients and identify treatment-required pathways to mitigate the risk of recurrent episodes, worsening BCPS, and increasing staging. The quantitative clinical RADAR scores should be used in schizophrenia research as dependent variables and regressed on the pathway RADAR scores.

The cost of secondary prevention of coronary heart disease (CHD) is continuing to increase, with a substantial portion of this acceleration being driven by the expense of confirmatory diagnostic testing. Conceivably, newly developed precision epigenetic technologies could drive down these costs. However, at the current time, their impact on overall expense for CHD care is poorly understood. We hypothesized that the use of a newly developed, highly sensitive, and specific epigenetic test, PrecisionCHD, could decrease the costs of secondary prevention.

Organized sexualized and ritual abuse (ORA), a contentious issue since the 1980s, remains a polarizing topic. Although there is much debate about the existence of this phenomenon, a differentiated perspective is lacking, and no representative study has yet addressed the frequency.

Continuous antipsychotic treatment is often recommended to prevent relapse in schizophrenia. However, the efficacy of antipsychotic treatment appears to diminish in patients with relapsed schizophrenia and the underlying mechanisms are still unknown. Moreover, though the findings are inconclusive, several recent studies suggest that intermittent versus continuous treatment may not significantly differ in recurrence risk and therapeutic efficacy but potentially reduce the drug dose and side effects. Notably, disturbances in fatty acid (FA) metabolism are linked to the onset/relapse of schizophrenia, and patients with multi-episode schizophrenia have been reported to have reduced FA biosynthesis. We thus utilized an MK-801-induced animal model of schizophrenia to evaluate whether two treatment strategies of clozapine would affect drug response and FA metabolism differently in the brain. Schizophrenia-related behaviors were assessed through open field test (OFT) and prepulse inhibition (PPI) test, and FA profiles of prefrontal cortex (PFC) and hippocampus were analyzed by gas chromatography-mass spectrometry. Additionally, we measured gene expression levels of enzymes involved in FA synthesis. Both intermittent and continuous clozapine treatment reversed hypermotion and deficits in PPI in mice. Continuous treatment decreased total polyunsaturated fatty acids (PUFAs), saturated fatty acids (SFAs) and FAs in the PFC, whereas the intermittent administration increased n-6 PUFAs, SFAs and FAs compared to continuous administration. Meanwhile, continuous treatment reduced the expression of Fads1 and Elovl2, while intermittent treatment significantly upregulated them. This study discloses the novel findings that there was no significant difference in clozapine efficacy between continuous and intermittent administration, but intermittent treatment showed certain protective effects on phospholipid metabolism in the PFC.

Patients with Parkinson's disease (PD) experience changes in behavior, personality, and cognition that can manifest even in the initial stages of the disease. Previous studies have suggested that mild behavioral impairment (MBI) should be considered an early marker of cognitive decline. However, the precise neurostructural underpinnings of MBI in early- to mid-stage PD remain poorly understood.

Psychiatrists face a major ethical challenge when deciding whether to make use of coercive measures in the treatment process of patients suffering from severe and persistent mental illness (SPMI). As India and Switzerland show major cultural, political and financial differences, it is hypothesized that attitudes towards coercive measures among Indian and Swiss psychiatrists will vary too. Exploring differences in attitudes between cultures strengthens the critical reflection on one's own stances and in consequence, on our way of action. Especially when it comes to situations involving power imbalances between patients and health practitioners, self-reflection is essential to prevent ethically inappropriate behavior.

Network meta-analysis (NMA) usually provides estimates of the relative effects with the highest possible precision. However, sparse networks with few available studies and limited direct evidence can arise, threatening the robustness and reliability of NMA estimates. In these cases, the limited amount of available information can hamper the formal evaluation of the underlying NMA assumptions of transitivity and consistency. In addition, NMA estimates from sparse networks are expected to be imprecise and possibly biased as they rely on large-sample approximations that are invalid in the absence of sufficient data. We propose a Bayesian framework that allows sharing of information between two networks that pertain to different population subgroups. Specifically, we use the results from a subgroup with a lot of direct evidence (a dense network) to construct informative priors for the relative effects in the target subgroup (a sparse network). This is a two-stage approach where at the first stage, we extrapolate the results of the dense network to those expected from the sparse network. This takes place by using a modified hierarchical NMA model where we add a location parameter that shifts the distribution of the relative effects to make them applicable to the target population. At the second stage, these extrapolated results are used as prior information for the sparse network. We illustrate our approach through a motivating example of psychiatric patients. Our approach results in more precise and robust estimates of the relative effects and can adequately inform clinical practice in presence of sparse networks.

: The study aims to provide a comprehensive neuropsychological analysis of psychotic spectrum disorders, including schizophrenia, bipolar disorder, and depression. It focuses on the critical aspects of cognitive impairments, diagnostic tools, intervention efficacy, and the roles of genetic and environmental factors in these disorders. The paper emphasizes the diagnostic significance of neuropsychological tests in identifying cognitive deficiencies and their predictive value in the early management of psychosis. : The study involved a systematic literature review following the PRISMA guidelines. The search was conducted in significant databases like Scopus, PsycINFO, PubMed, and Web of Science using keywords relevant to clinical neuropsychology and psychotic spectrum disorders. The inclusion criteria required articles to be in English, published between 2018 and 2023, and pertinent to clinical neuropsychology's application in these disorders. A total of 153 articles were identified, with 44 ultimately included for detailed analysis based on relevance and publication status after screening. The review highlights several key findings, including the diagnostic and prognostic significance of mismatch negativity, neuroprogressive trajectories, cortical thinning in familial high-risk individuals, and distinct illness trajectories within psychosis subgroups. The studies evaluated underline the role of neuropsychological tests in diagnosing psychiatric disorders and emphasize early detection and the effectiveness of intervention strategies based on cognitive and neurobiological markers. : The systematic review underscores the importance of investigating the neuropsychological components of psychotic spectrum disorders. It identifies significant cognitive impairments in attention, memory, and executive function, correlating with structural and functional brain abnormalities. The paper stresses the need for precise diagnoses and personalized treatment modalities, highlighting the complex interplay between genetic, environmental, and psychosocial factors. It calls for a deeper understanding of these neuropsychological processes to enhance diagnostic accuracy and therapeutic outcomes.

Alzheimer's disease (AD), a neurodegenerative disease that mostly affects the elderly, slowly impairs memory, cognition, and daily tasks. AD has long been one of the most debilitating chronic neurological disorders, affecting mostly people over 65. In this study, we investigated the use of Vision Transformer (ViT) for Magnetic Resonance Image processing in the context of AD diagnosis. ViT was utilized to extract features from MRIs, map them to a feature sequence, perform sequence modeling to maintain interdependencies, and classify features using a time series transformer. The proposed model was evaluated using ADNI T1-weighted MRIs for binary and multiclass classification. Two data collections, Complete 1Yr 1.5T and Complete 3Yr 3T, from the ADNI database were used for training and testing. A random split approach was used, allocating 60% for training and 20% for testing and validation, resulting in sample sizes of (211, 70, 70) and (1378, 458, 458), respectively. The performance of our proposed model was compared to various deep learning models, including CNN with BiL-STM and ViT with Bi-LSTM. The suggested technique diagnoses AD with high accuracy (99.048% for binary and 99.014% for multiclass classification), precision, recall, and F-score. Our proposed method offers researchers an approach to more efficient early clinical diagnosis and interventions.

To investigate the potential association between prenatal opioid exposure and the risk of neuropsychiatric disorders in children.

History of suicide attempt (SA) is the strongest predictor of a new SA and suicide. It is primordial to identify additional risk factors of suicide re-attempt. The aim of this study was to identify risk factors of suicide re-attempt in patients with recent SA followed for 2 years.

: The association of dairy product consumption with nonalcoholic fatty liver disease (NAFLD) and cirrhosis remains controversial. This study aimed to prospectively investigate the associations between the consumption of the different types of dairy products, genetic predisposition, and the risks of NAFLD and cirrhosis. : This cohort study included 190 145 participants from the UK Biobank Study. The consumption of the different types of dairy products was assessed based on the Oxford WebQ at baseline and defined as the sum of milk, yogurt, and cheese. NAFLD and cirrhosis were evaluated using hospital inpatient records and death data in the UK Biobank. The weighted genetic risk score (GRS) for NAFLD and cirrhosis was constructed using 5 and 6 single-nucleotide variants (SNVs), respectively. Cox proportional hazards regression models were utilized to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs) for the association between genetic factors and different types of dairy products with the incidence of NAFLD and cirrhosis. : During a median follow-up of 11.6 years, 1512 NAFLD and 556 cirrhosis cases were ascertained. After adjusting for several potential confounders, the HRs (95% CIs) (Q4 Q1) of NAFLD were 0.86 (0.74, 0.995) for total dairy products, 0.96 (0.84, 1.09) for high-fat dairy products, 0.78 (0.67, 0.92) for low-fat dairy products, 0.86 (0.74, 0.99) for unfermented dairy products, and 0.79 (0.68, 0.91) for fermented dairy products. The multivariable-adjusted HRs (95% CIs) (Q4 Q1) of cirrhosis were 0.75 (0.59, 0.96) for total dairy products, 0.97 (0.78, 1.19) for high-fat dairy products, 0.67 (0.51, 0.89) for low-fat dairy products, 0.75 (0.59, 0.96) for unfermented dairy products, and 0.71 (0.56, 0.90) for fermented dairy products. The associations of high-fat dairy products and fermented dairy products with NAFLD and cirrhosis were found to be nonlinear ( for nonlinear <0.05). No interaction was observed between dairy product consumption and NAFLD or cirrhosis genetic susceptibility. : Higher consumption of dairy products, except for high-fat dairy, was correlated with lower risks of NAFLD and cirrhosis, regardless of their differences in genetic susceptibility.

Recent research shows prominent effects of pregnancy and the parenthood transition on structural brain characteristics in humans. Here, we present a comprehensive study of how parental status and number of children born/fathered links to markers of brain and cellular ageing in 36,323 UK Biobank participants (age range 44.57-82.06 years; 52% female). To assess global effects of parenting on the brain, we trained a 3D convolutional neural network on T1-weighted magnetic resonance images, and estimated brain age in a held-out test set. To investigate regional specificity, we extracted cortical and subcortical volumes using FreeSurfer, and ran hierarchical clustering to group regional volumes based on covariance. Leukocyte telomere length (LTL) derived from DNA was used as a marker of cellular ageing. We employed linear regression models to assess relationships between number of children, brain age, regional brain volumes, and LTL, and included interaction terms to probe sex differences in associations. Lastly, we used the brain measures and LTL as features in binary classification models, to determine if markers of brain and cellular ageing could predict parental status. The results showed associations between a greater number of children born/fathered and younger brain age in both females and males, with stronger effects observed in females. Volume-based analyses showed maternal effects in striatal and limbic regions, which were not evident in fathers. We found no evidence for associations between number of children and LTL. Classification of parental status showed an Area under the ROC Curve (AUC) of 0.57 for the brain age model, while the models using regional brain volumes and LTL as predictors showed AUCs of 0.52. Our findings align with previous population-based studies of middle- and older-aged parents, revealing subtle but significant associations between parental experience and neuroimaging-based surrogate markers of brain health. The findings further corroborate results from longitudinal cohort studies following parents across pregnancy and postpartum, potentially indicating that the parenthood transition is associated with long-term influences on brain health.

Behaviours and their execution depend on the context and emotional state in which they are performed. The contextual modulation of behavior likely relies on regions such as the anterior cingulate cortex (ACC) that multiplex information about emotional/autonomic states and behaviours. The objective of the present study was to understand how the representations of behaviors by ACC neurons become modified when performed in different emotional states. A pipeline of machine learning techniques was developed to categorize and classify complex, spontaneous behaviors in male rats from video. This pipeline, termed HUB-DT, discovered a range of statistically separable behaviors during a task in which motivationally significant outcomes were delivered in blocks of trials that created 3 unique 'emotional contexts'. HUB-DT was capable of detecting behaviors specific to each emotional context and was able to identify and segregate the portions of a neural signal related to a behaviour and to emotional context. Overall, ∼10x as many neurons responded to behaviors in a contextually dependent versus a fixed manner, highlighting the extreme impact of emotional state on representations of behaviors that were precisely defined based on detailed analyses of limb kinematics. This type of modulation may be a key mechanism that allows the ACC to modify behavioral output based on emotional states and contextual demands. Context and emotional state affect how we see the world and behave in it. Emotional contextualization can be observed at a neural level in the anterior cingulate cortex (ACC). In this study, rats were exposed to events invoking differing emotional responses while we recorded from ensembles of ACC neurons and precisely tracked behaviors using our machine-learning pipeline, 'HUB-DT'. The extent of emotional modulational of behavioral representations by ACC neurons was striking. This modulation may be what allows the ACC to bias decisions and actions based on internal states, and more generally, may offer some insight into how models of network function can more closely reflect what is being represented in ACC.

In the present study, we explored the association between major dietary patterns, odds, and severity of anxiety disorders, which has not been clarified to date. This case-control study was conducted on 85 patients who were group-matched by gender with 170 healthy subjects. Dietary intakes were evaluated applying a 147-item validated food frequency questionnaire (FFQ). Anthropometric data collection was accomplished based on precise clinical assessments. Major dietary patterns were identified using principal component analysis (PCA). Multivariate odds ratios (OR) with 95% confidence intervals (CI) were used to investigate the association of the identified dietary patterns with anxiety disorders. Multiple linear regression analysis was used to evaluate the association between the GAD-7 score and major dietary pattern scores. Three major dietary patterns were derived through PCA labeled as 'healthy', 'Western', and 'Mixed'. Those in the top tertile of the healthy dietary pattern were less likely to have anxiety disorders (OR =   0.26; 95%CI: 0.10, 0.66), while no significant relationship was found between Western and mixed dietary patterns and the odds of anxiety disorders. The severity of anxiety disorders, assessed by the GAD-7 score, was reduced by higher adherence to healthy dietary pattern ( = 0.003), and increased by greater adherence to mixed ( = 0.002) and Western ( = 0.001) dietary patterns. We provided evidence demonstrating an inverse association of healthy dietary pattern with odds, and severity of anxiety disorders. Also, higher adherence to Western and mixed dietary patterns resulted in greater GAD-7 scores.

Sequence memory is subject to age-related decline, but the underlying processes are not yet fully understood. We analyzed electroencephalography (EEG) in 21 healthy older (60-80 years) and 26 young participants (20-30 years) and compared time-frequency spectra and theta-gamma phase-amplitude-coupling (PAC) during encoding of the order of visually presented items. In older adults, desynchronization in theta (4-8 Hz) and synchronization in gamma (30-45 Hz) power did not distinguish between subsequently correctly and incorrectly remembered trials, while there was a subsequent memory effect for young adults. Theta-gamma PAC was modulated by item position within a sequence for older but not young adults. Specifically, position within a sequence was coded by higher gamma amplitude for successive theta phases for later correctly remembered trials. Thus, deficient differentiation in theta desynchronization and gamma oscillations during sequence encoding in older adults may reflect neurophysiological correlates of age-related memory decline. Furthermore, our results indicate that sequences are coded by theta-gamma PAC in older adults, but that this mechanism might lose precision in aging.

Pregnant women who have undergone pregnancy loss often display both posttraumatic stress (PTS) and posttraumatic growth (PTG). However, the precise relationship and structure of symptomatic levels of PTS and PTG have not been well understood. This study aimed to assess the associations between PTS and PTG symptoms in women during subsequent pregnancies following a previous pregnancy loss.

Socioeconomic status (SES) influences the risk of both physical diseases, such as asthma, and neurodevelopmental conditions, including attention-deficit/hyperactivity disorder (ADHD). Using Causal Mediation Analysis on French birth-cohort data, we found a causal pathway from SES to ADHD symptoms, in part mediated by asthma. An increase in family income at age 3 by one unit resulted in lower ADHD symptoms at age 5, by -0.37 [95% CI: -0.50, -0.24] SDQ-score-points, with additional -0.04 [95% CI: -0.08, -0.01] points reduction indirectly via asthma at age 3, both with statistical significance. Importantly, family income at age 3 exerted both direct and indirect (via asthma) negative effects on later ADHD symptoms with much higher magnitudes for the direct effect. Our findings underscore the importance of apprehending ADHD symptoms in the broader context of socioeconomic disparities, along with their comorbidities with asthma, potentially influencing public health interventions and clinical practice in managing ADHD.

Adolescence is a vulnerable period for mental health. It is not easy to make a precise diagnosis during this period, as young people may present attenuated forms of psychiatric pathology, or on the contrary, a combination of several types of difficulties. Adopting a transdiagnostic and dimensional approach, based on clinical stages, and thus proposing interventions adapted to the severity of symptoms, is pertinent. As emotional dysregulation lies at the heart of many pathologies, it is a prime target for early intervention. Although interventions for adolescents are still underdeveloped, certain approaches derived from cognitive-behavioral therapies and the psychodynamic current have been adapted for adolescents and appear promising.

Ketamine has emerged as one of the most promising therapies for treatment-resistant depression. However, inter-individual variability in response to ketamine is still not well understood and it is unclear how ketamine's molecular mechanisms connect to its neural and behavioral effects.

Tobacco use disorder (TUD) is the most prevalent substance use disorder in the world. Genetic factors influence smoking behaviours and although strides have been made using genome-wide association studies to identify risk variants, most variants identified have been for nicotine consumption, rather than TUD. Here we leveraged four US biobanks to perform a multi-ancestral meta-analysis of TUD (derived via electronic health records) in 653,790 individuals (495,005 European, 114,420 African American and 44,365 Latin American) and data from UK Biobank (n = 898,680). We identified 88 independent risk loci; integration with functional genomic tools uncovered 461 potential risk genes, primarily expressed in the brain. TUD was genetically correlated with smoking and psychiatric traits from traditionally ascertained cohorts, externalizing behaviours in children and hundreds of medical outcomes, including HIV infection, heart disease and pain. This work furthers our biological understanding of TUD and establishes electronic health records as a source of phenotypic information for studying the genetics of TUD.

The diagnosis of adolescent Depressive Disorder (DD) lacks specific biomarkers, posing significant challenges. This study investigates the potential of Niacin Skin Flush Response (NSFR) as a biomarker for identifying and assessing the severity of adolescent Depressive Disorder, as well as distinguishing it from Behavioral and Emotional Disorders typically emerging in childhood and adolescence(BED).

Metabolomics provides powerful tools that can inform about heterogeneity in disease and response to treatments. In this study, we employed an electrochemistry-based targeted metabolomics platform to assess the metabolic effects of three randomly-assigned treatments: escitalopram, duloxetine, and Cognitive Behavior Therapy (CBT) in 163 treatment-naïve outpatients with major depressive disorder. Serum samples from baseline and 12 weeks post-treatment were analyzed using targeted liquid chromatography-electrochemistry for metabolites related to tryptophan, tyrosine metabolism and related pathways. Changes in metabolite concentrations related to each treatment arm were identified and compared to define metabolic signatures of exposure. In addition, association between metabolites and depressive symptom severity (assessed with the 17-item Hamilton Rating Scale for Depression [HRSD]) and anxiety symptom severity (assessed with the 14-item Hamilton Rating Scale for Anxiety [HRSA]) were evaluated, both at baseline and after 12 weeks of treatment. Significant reductions in serum serotonin level and increases in tryptophan-derived indoles that are gut bacterially derived were observed with escitalopram and duloxetine arms but not in CBT arm. These include indole-3-propionic acid (I3PA), indole-3-lactic acid (I3LA) and Indoxyl sulfate (IS), a uremic toxin. Purine-related metabolites were decreased across all arms. Different metabolites correlated with improved symptoms in the different treatment arms revealing potentially different mechanisms between response to antidepressant medications and to CBT.

Fibroids are benign neoplasms associated with severe gynecologic morbidity. There are no strategies to prevent fibroid development.

To provide a brief overview of artificial intelligence (AI) application within the field of eating disorders (EDs) and propose focused solutions for research.

This pilot study investigated the long-term impact of a surgery-only treatment (no exposure to other treatments, such as chemotherapy and radiation) for pediatric cerebellar low-grade gliomas on executive function, anxiety, and fear of pain (FOP) beliefs. Twelve patients who underwent surgical glioma resection during childhood (surgery age was 4-16 years, study visit age was 10-28 years), and 12 pain-free controls matched for age, sex, race, and handedness were tested. The spatial extent of resection was precisely mapped using magnetic resonance imaging (MRI). Executive function, anxiety, and FOP were assessed using validated self-report age-appropriate questionnaires for children and adults. Structured clinical interviews at a post-surgery follow-up visit were completed (average: 89 months, range: 20-99). No significant differences in FOP (FOPQ-C t[14 = 1.81,  = 0.09; FOPQ-III t[4] = 0.29,  = 0.79), executive function scores (BRIEF t[20] = 0.30,  = 0.28), or anxiety scores (MASC t[16] = 0.19,  = 0.85; MAQ t[4] = 1.80,  = 0.15) were found in pediatric or adult patients compared to pain-free controls. Clinical interviews mainly categorized pediatric patients as not anxious. One participant reported mild/subclinical anxiety, and one had moderate clinical anxiety. Neither psychologists nor patients endorsed impairments to executive functioning, anxiety, or FOP. Our pilot results suggest that pediatric cerebellar tumor survivors treated with surgery-only have favorable long-term functioning related to these themes. While these results are promising, they will need to be replicated in a larger patient sample.

Sex differences permeate many aspects of dementia with Lewy bodies (DLB), yet sex differences in patterns of neurodegeneration in DLB remain largely unexplored. Here, we test whether grey matter networks differ between sexes in DLB and compare these findings to sex differences in healthy controls. In this cross-sectional study, we analysed clinical and neuroimaging data of patients with DLB and cognitively healthy controls matched for age and sex. Grey matter networks were constructed by pairwise correlations between 58 regional volumes after correction for age, intracranial volume, and centre. Network properties were compared between sexes and diagnostic groups. Additional analyses were conducted on w-scored data to identify DLB-specific sex differences. Data from 119 (68.7 ± 8.4 years) men and 45 women (69.9 ± 9.1 years) with DLB, and 164 healthy controls were included in this study. Networks of men had a lower nodal strength compared to women. In comparison to healthy women, the grey matter networks of healthy men showed a higher global efficiency, modularity, and fewer modules. None of the network measures showed significant sex differences in DLB. Comparing DLB patients with healthy controls revealed global differences in women and more local differences in men. Modular analyses showed a more distinct demarcation between cortical and subcortical regions in men compared with women. While topologies of grey matter networks differed between sexes in healthy controls, those sex differences were diluted in DLB patients. These findings suggest a disease-driven convergence of neurodegenerative patterns in women and men with DLB, which may inform precision medicine in DLB.

The current study investigated the extent to which changes in attentional control contribute to performance on a visual perceptual discrimination task, on a trial-by-trial basis in a transdiagnostic clinical sample.

Accurate assessment of cerebral perfusion is vital for understanding the hemodynamic processes involved in various neurological disorders and guiding clinical decision-making. This guidelines article provides a comprehensive overview of quantitative perfusion imaging of the brain using multi-timepoint arterial spin labeling (ASL), along with recommendations for its acquisition and quantification. A major benefit of acquiring ASL data with multiple label durations and/or post-labeling delays (PLDs) is being able to account for the effect of variable arterial transit time (ATT) on quantitative perfusion values and additionally visualize the spatial pattern of ATT itself, providing valuable clinical insights. Although multi-timepoint data can be acquired in the same scan time as single-PLD data with comparable perfusion measurement precision, its acquisition and postprocessing presents challenges beyond single-PLD ASL, impeding widespread adoption. Building upon the 2015 ASL consensus article, this work highlights the protocol distinctions specific to multi-timepoint ASL and provides robust recommendations for acquiring high-quality data. Additionally, we propose an extended quantification model based on the 2015 consensus model and discuss relevant postprocessing options to enhance the analysis of multi-timepoint ASL data. Furthermore, we review the potential clinical applications where multi-timepoint ASL is expected to offer significant benefits. This article is part of a series published by the International Society for Magnetic Resonance in Medicine (ISMRM) Perfusion Study Group, aiming to guide and inspire the advancement and utilization of ASL beyond the scope of the 2015 consensus article.

The risk of developing Alzheimer's disease (AD) significantly increases in individuals carrying the APOEε4 allele. Elderly cognitively healthy individuals with APOEε4 also exist, suggesting the presence of cellular mechanisms that counteract the pathological effects of APOEε4; however, these mechanisms are unknown. We hypothesized that APOEε4 carriers without dementia might carry genetic variations that could protect them from developing APOEε4-mediated AD pathology. To test this, we leveraged whole-genome sequencing (WGS) data in the National Institute on Aging Alzheimer's Disease Family Based Study (NIA-AD FBS), Washington Heights/Inwood Columbia Aging Project (WHICAP), and Estudio Familiar de Influencia Genetica en Alzheimer (EFIGA) cohorts and identified potentially protective variants segregating exclusively among unaffected APOEε4 carriers. In homozygous unaffected carriers above 70 years old, we identified 510 rare coding variants. Pathway analysis of the genes harboring these variants showed significant enrichment in extracellular matrix (ECM)-related processes, suggesting protective effects of functional modifications in ECM proteins. We prioritized two genes that were highly represented in the ECM-related gene ontology terms, (FN1) and collagen type VI alpha 2 chain (COL6A2) and are known to be expressed at the blood-brain barrier (BBB), for postmortem validation and in vivo functional studies. An independent analysis in a large cohort of 7185 APOEε4 homozygous carriers found that rs140926439 variant in FN1 was protective of AD (OR = 0.29; 95% CI [0.11, 0.78], P = 0.014) and delayed age at onset of disease by 3.37 years (95% CI [0.42, 6.32], P = 0.025). The FN1 and COL6A2 protein levels were increased at the BBB in APOEε4 carriers with AD. Brain expression of cognitively unaffected homozygous APOEε4 carriers had significantly lower FN1 deposition and less reactive gliosis compared to homozygous APOEε4 carriers with AD, suggesting that FN1 might be a downstream driver of APOEε4-mediated AD-related pathology and cognitive decline. To validate our findings, we used zebrafish models with loss-of-function (LOF) mutations in fn1b-the ortholog for human FN1. We found that fibronectin LOF reduced gliosis, enhanced gliovascular remodeling, and potentiated the microglial response, suggesting that pathological accumulation of FN1 could impair toxic protein clearance, which is ameliorated with FN1 LOF. Our study suggests that vascular deposition of FN1 is related to the pathogenicity of APOEε4, and LOF variants in FN1 may reduce APOEε4-related AD risk, providing novel clues to potential therapeutic interventions targeting the ECM to mitigate AD risk.

Despite its high lifetime prevalence rate and the elevated disability caused by posttraumatic stress disorder (PTSD), treatments exhibit modest efficacy. In consideration of the abnormal connectivity between the dorsolateral prefrontal cortex (DLPFC) and amygdala in PTSD, several randomized controlled trials (RCTs) addressing the efficacy of different noninvasive brain stimulation (NIBS) modalities for PTSD management have been undertaken. However, previous RCTs have reported inconsistent results. The current network meta-analysis (NMA) aimed to compare the efficacy and acceptability of various NIBS protocols in PTSD management.

Substance use, including cigarettes and cannabis, is associated with poorer sustained attention in late adolescence and early adulthood. Previous studies were predominantly cross-sectional or under-powered and could not indicate if impairment in sustained attention was a consequence of substance-use or a marker of the inclination to engage in such behaviour. This study explored the relationship between sustained attention and substance use across a longitudinal span from ages 14 to 23 in over 1,000 participants. Behaviours and brain connectivity associated with diminished sustained attention at age 14 predicted subsequent increases in cannabis and cigarette smoking, establishing sustained attention as a robust biomarker for vulnerability to substance use. Individual differences in network strength relevant to sustained attention were preserved across developmental stages and sustained attention networks generalized to participants in an external dataset. In summary, brain networks of sustained attention are robust, consistent, and able to predict aspects of later substance use.

A lack of consensus on the optimal outcome measures to assess opioid use disorder (OUD) treatment efficacy and their precise definition and computation has hampered the pooling of research data for evidence synthesis and meta-analyses. This study aimed to empirically contrast multiple clinical trial definitions of treatment success by applying them to the same dataset.

The link between neuroinflammation and depression is a subject of growing interest in neuroscience and psychiatry; meanwhile, the precise mechanisms are still being unrevealed. However, glial cell activation, together with cytokine level elevation, suggests a connection between neuroinflammation and the development or exacerbation of depression. Glial cells (astrocytes) communicate with neurons via their extracellular neurotransmitter receptors, including glutamate receptors NMDARs. However, these receptor roles are controversial and enigmatic in neurological disorders, including depression. Therefore, we hypothesized whether NMDAR subnit NR2C deletion in the astrocytes exhibited anti-depressive effects concurrent with neuroinflammation prevention. To assess, we prepared astrocytic-NR2C knockout mice (G-2C: GFAPGrin2C), followed by LPS administration, behavior tests, and biochemical analysis. Stimulatingly, astrocytic-NR2C knockout mice (G-2C) did not display depressive-like behaviors, neuroinflammation, and synaptic deficits upon LPS treatment. PI3K was impaired upon LPS administration in control mice (Grin2C); however, they were intact in the hippocampus of LPS-treated G-2C mice. Further, PI3K activation (via PTEN inhibition by BPV) restored neuroinflammation and depressive-like behavior, accompanied by altered synaptic protein and spine numbers in G-2C mice in the presence of LPS. In addition, NF-κB and JNK inhibitor (BAY, SP600125) treatments reversed the effects of BPV. Moreover, these results were further validated with an NR2C antagonist DQP-1105. Collectively, these observations support the astrocytic-NR2C contribution to LPS-induced neuroinflammation, depression, and synaptic deficits.

Drug addiction represents a multifaceted and recurrent brain disorder that possesses the capability to create persistent and ineradicable pathological memory. Deep brain stimulation (DBS) has shown a therapeutic potential for neuropsychological disorders, while the precise stimulation targets and therapeutic parameters for addiction remain deficient. Among the crucial brain regions implicated in drug addiction, the dorsal raphe nucleus (DRN) has been found to exert an essential role in the manifestation of addiction memory. Thus, we investigated the effects of DRN DBS in the treatment of addiction and whether it might produce side effects by a series of behavioral assessments, including methamphetamine priming-induced reinstatement of drug seeking behaviors, food-induced conditioned place preference (CPP), open field test and elevated plus-maze test, and examined brain activity and connectivity after DBS of DRN. We found that high-frequency DBS of the DRN significantly lowered the CPP scores and the number of active-nosepokes in the methamphetamine-primed CPP test and the self-administration model. Moreover, both high-frequency and sham DBS group rats were able to establish significant food-induced place preference, and no significant difference was observed in the open field test and in the elevated plus-maze test between the two groups. Immunofluorescence staining and functional magnetic resonance imaging revealed that high-frequency DBS of the DRN could alter the activity and functional connectivity of brain regions related to addiction. These results indicate that high-frequency DBS of the DRN effectively inhibits methamphetamine priming-induced relapse and seeking behaviors in rats and provides a new target for the treatment of drug addiction.

Severe psychiatric illnesses, for instance schizophrenia, and affective diseases or autism spectrum disorders, have been associated with cognitive impairment and perturbed excitatory-inhibitory balance in the brain. Effects in juvenile mice can elucidate how erythropoietin (EPO) might aid in rectifying hippocampal transcriptional networks and synaptic structures of pyramidal lineages, conceivably explaining mitigation of neuropsychiatric diseases. An imminent conundrum is how EPO restores synapses by involving interneurons. By analyzing ~12,000 single-nuclei transcriptomic data, we generated a comprehensive molecular atlas of hippocampal interneurons, resolved into 15 interneuron subtypes. Next, we studied molecular alterations upon recombinant human (rh)EPO and saw that gene expression changes relate to synaptic structure, trans-synaptic signaling and intracellular catabolic pathways. Putative ligand-receptor interactions between pyramidal and inhibitory neurons, regulating synaptogenesis, are altered upon rhEPO. An array of in/ex vivo experiments confirms that specific interneuronal populations exhibit reduced dendritic complexity, synaptic connectivity, and changes in plasticity-related molecules. Metabolism and inhibitory potential of interneuron subgroups are compromised, leading to greater excitability of pyramidal neurons. To conclude, improvement by rhEPO of neuropsychiatric phenotypes may partly owe to restrictive control over interneurons, facilitating re-connectivity and synapse development.

has been proposed as a modifier of disease risk in FTLD-TDP, particularly in mutation carriers. Furthermore, has been investigated as a disease modifier in the context of healthy aging and across multiple neurodegenerative diseases. The objective of this study is to evaluate and compare the effect of on gray matter volume and cognition in each of the common genetic FTD groups and in sporadic FTD patients.

In vertebrates, oligodendrocytes (OLs) are glial cells of the central nervous system (CNS) responsible for the formation of the myelin sheath that surrounds the axons of neurons. The myelin sheath plays a crucial role in the transmission of neuronal information by promoting the rapid saltatory conduction of action potentials and providing neurons with structural and metabolic support. Saltatory conduction, first described in the peripheral nervous system (PNS), is now generally recognized as a universal evolutionary innovation to respond quickly to the environment: myelin helps us think and act fast. Nevertheless, the role of myelin in the central nervous system, especially in the brain, may not be primarily focused on accelerating conduction speed but rather on ensuring precision. Its principal function could be to coordinate various neuronal networks, promoting their synchronization through oscillations (or rhythms) relevant for specific information processing tasks. Interestingly, myelin has been directly involved in different types of cognitive processes relying on brain oscillations, and myelin plasticity is currently considered to be part of the fundamental mechanisms for memory formation and maintenance. However, despite ample evidence showing the involvement of myelin in cognition and neurodevelopmental disorders characterized by cognitive impairments, the link between myelin, brain oscillations, cognition and disease is not yet fully understood. In this review, we aim to highlight what is known and what remains to be explored to understand the role of myelin in high order brain processes.

Deep brain stimulation (DBS) modulates local and widespread connectivity in dysfunctional networks. Positive results are observed in several patient populations; however, the precise mechanisms underlying treatment remain unknown. Translational DBS studies aim to answer these questions and provide knowledge for advancing the field. Here, we systematically review the literature on DBS studies involving models of neurological, developmental and neuropsychiatric disorders to provide a synthesis of the current scientific landscape surrounding this topic. A systematic analysis of the literature was performed following PRISMA guidelines. 407 original articles were included. Data extraction focused on study characteristics, including stimulation protocol, behavioural outcomes, and mechanisms of action. The number of articles published increased over the years, including 16 rat models and 13 mouse models of transgenic or healthy animals exposed to external factors to induce symptoms. Most studies targeted telencephalic structures with varying stimulation settings. Positive behavioural outcomes were reported in 85.8% of the included studies. In models of psychiatric and neurodevelopmental disorders, DBS-induced effects were associated with changes in monoamines and neuronal activity along the mesocorticolimbic circuit. For movement disorders, DBS improves symptoms via modulation of the striatal dopaminergic system. In dementia and epilepsy models, changes to cellular and molecular aspects of the hippocampus were shown to underlie symptom improvement. Despite limitations in translating findings from preclinical to clinical settings, rodent studies have contributed substantially to our current knowledge of the pathophysiology of disease and DBS mechanisms. Direct inhibition/excitation of neural activity, whereby DBS modulates pathological oscillatory activity within brain networks, is among the major theories of its mechanism. However, there remain fundamental questions on mechanisms, optimal targets and parameters that need to be better understood to improve this therapy and provide more individualized treatment according to the patient's predominant symptoms.

Adaptive coding of reward is the process by which neurons adapt their response to the context of available compensations. Higher rewards lead to a stronger brain response, but the increase of the response depends on the range of available rewards. A steeper increase is observed in a narrow range, and a more gradual slope in a wider range. In schizophrenia, adaptive coding appears affected in different domains, and in the reward domain in particular. Here we tested adaptive coding of reward in a large group of patients with schizophrenia (N = 86) and controls (N = 66). We assessed 1) the association between adaptive coding deficits and symptoms; 2) the longitudinal stability of deficits (the same task was performed three months apart); 3) the stability of results between two experimental sites. We used fMRI and the Monetary Incentive Delay task to assess participant' adaptation to two different reward ranges: a narrow and a wide range. We used a region of interest analysis, evaluating adaptation within striatal and visual regions. Patients and controls underwent a full demographic and clinical assessment. We found reduced adaptive coding in patients, due to a decreased slope in the narrow reward range, with respect to that of control participants in striatal but not visual regions. This pattern was observed at both research sites. Upon re-test, patients increased their narrow range slopes, showing improved adaptive coding, whereas controls slightly reduced them. At re-test, patients with overly steep slopes in the narrow range also showed higher levels of negative symptoms. Our data confirm deficits in reward adaptation in schizophrenia and reveal a practice effect in patients, leading to improvement, with steeper slopes upon retest. However, in some patients, an overly steep slope may result in poor discriminability of larger rewards, due to early saturation of the brain response. Together, the loss of precision of reward representation in new (first exposure, underadaptation) and more familiar (re-test, overadaptation) situations may contribute to the multiple motivational symptoms in schizophrenia.

Thalamocortical loops have a central role in cognition and motor control, but precisely how they contribute to these processes is unclear. Recent studies showing evidence of plasticity in thalamocortical synapses indicate a role for the thalamus in shaping cortical dynamics through learning. Since signals undergo a compression from the cortex to the thalamus, we hypothesized that the computational role of the thalamus depends critically on the structure of corticothalamic connectivity. To test this, we identified the optimal corticothalamic structure that promotes biologically plausible learning in thalamocortical synapses. We found that corticothalamic projections specialized to communicate an efference copy of the cortical output benefit motor control, while communicating the modes of highest variance is optimal for working memory tasks. We analyzed neural recordings from mice performing grasping and delayed discrimination tasks and found corticothalamic communication consistent with these predictions. These results suggest that the thalamus orchestrates cortical dynamics in a functionally precise manner through structured connectivity.

Neuroinflammation and blood-cerebrospinal fluid barrier (BCB) disruption could be key elements in schizophrenia-spectrum disorderś(SSDs) etiology and symptom modulation. We present the largest two-stage individual patient data (IPD) meta-analysis, investigating the association of BCB disruption and cerebrospinal fluid (CSF) alterations with symptom severity in first-episode psychosis (FEP) and recent onset psychotic disorder (ROP) individuals, with a focus on sex-related differences. Data was collected from PubMed and EMBASE databases. FEP, ROP and high-risk syndromes for psychosis IPD were included if routine basic CSF-diagnostics were reported. Risk of bias of the included studies was evaluated. Random-effects meta-analyses and mixed-effects linear regression models were employed to assess the impact of BCB alterations on symptom severity. Published (6 studies) and unpublished IPD from n = 531 individuals was included in the analyses. CSF was altered in 38.8 % of individuals. No significant differences in symptom severity were found between individuals with and without CSF alterations (SMD = -0.17, 95 %CI -0.55-0.22, p = 0.341). However, males with elevated CSF/serum albumin ratios or any CSF alteration had significantly higher positive symptom scores than those without alterations (SMD = 0.34, 95 %CI 0.05-0.64, p = 0.037 and SMD = 0.29, 95 %CI 0.17-0.41p = 0.005, respectively). Mixed-effects and simple regression models showed no association (p > 0.1) between CSF parameters and symptomatic outcomes. No interaction between sex and CSF parameters was found (p > 0.1). BCB disruption appears highly prevalent in early psychosis and could be involved in positive symptomś severity in males, indicating potential difficult-to-treat states. This work highlights the need for considering BCB breakdownand sex-related differences in SSDs clinical trials and treatment strategies.

Clozapine is characterized by a large within- and between-patient variability in its pharmacokinetics, attributed to non-genetic and genetic factors. A cross-sectional analysis of clozapine trough concentration (Clz C0) issued from Tunisian schizophrenic patients was collected and analysed using a nonparametric modelling approach. We assessed the impact of demographic covariates (age, weight and sex), patient's habits (smoking status, alcohol and caffeine intake) and the genetic factors (CYP1A2*1C, CYP1A2*1F and CYP2C19*2 polymorphisms) on each pharmacokinetic parameter. An external validation of this pharmacokinetic model using an independent data set was performed. Fit goodness between observed- and individual-predicted data was evaluated using the mean prediction error (% MPE), the mean absolute prediction error (% MAPE) as a measure of bias, and the root mean squared error (% RMSE) as a measure of precision. Sixty-three CLz C0 values issued from 51 schizophrenic patients were assessed in this study and divided into building and validation groups. CYP1A2*1F polymorphism and smoking status were the only covariates significantly associated with clozapine clearance. Precision parameters were as follows: 1.02%, 0.95% and 22.4%, respectively, for % MPE, % MAPE and % RMSE. We developed and validated an accurate pharmacokinetic model able to predict Clz C0 in Tunisian schizophrenic patients using the two parameters CYP1A2*1F polymorphism and smoking.

Sex differences have been claimed an imperative factor in the optimization of psychiatric treatments. Intermittent theta-burst stimulation (iTBS), a patterned form of repetitive transcranial magnetic stimulation, is a promising non-invasive treatment option. Here, we investigated whether the real-time neural response to iTBS differs between men and women, and which mechanisms may mediate these differences. To this end, we capitalized on a concurrent iTBS/functional near-infrared spectroscopy setup over the left dorsolateral prefrontal cortex, a common clinical target, to test our assumptions. In a series of experiments, we show (1) a biological sex difference in absolute hemoglobin concentrations in the left dorsolateral prefrontal cortex in healthy participants; (2) that this sex difference is amplified by iTBS but not by cognitive tasks; and (3) that the sex difference amplified by iTBS is modulated by stimulation intensity. These results inform future stimulation treatment optimizations towards precision psychiatry.

The axons of neocortical pyramidal neurons are frequently myelinated. Heterogeneity in the topography of axonal myelination in the cerebral cortex has been attributed to a combination of electrophysiological activity, axonal morphology, and neuronal-glial interactions. Previously, we showed that axonal segment length and caliber are critical local determinants of fast-spiking interneuron myelination. However, the factors that determine the myelination of individual axonal segments along neocortical pyramidal neurons remain largely unexplored. Here, we used structured illumination microscopy to examine the extent to which axonal morphology is predictive of the topography of myelination along neocortical pyramidal neurons. We identified critical thresholds for axonal caliber and interbranch distance that are necessary, but not sufficient, for myelination of pyramidal cell axons in mouse primary somatosensory cortex (S1). Specifically, we found that pyramidal neuron axonal segments with a caliber < 0.24 μm or interbranch distance < 18.10 μm are rarely myelinated. Moreover, we further confirmed that these findings in mice are similar for human neocortical pyramidal cell myelination (caliber < 0.25 μm, interbranch distance < 19.00 μm), suggesting that this mechanism is evolutionarily conserved. Taken together, our findings suggest that axonal morphology is a critical correlate of the topography and cell-type specificity of neocortical myelination.

Artificial intelligence (AI) is rapidly transforming the field of medicine, announcing a new era of innovation and efficiency. Among AI programs designed for general use, ChatGPT holds a prominent position, using an innovative language model developed by OpenAI. Thanks to the use of deep learning techniques, ChatGPT stands out as an exceptionally viable tool, renowned for generating human-like responses to queries. Various medical specialties, including rheumatology, oncology, psychiatry, internal medicine, and ophthalmology, have been explored for ChatGPT integration, with pilot studies and trials revealing each field's potential benefits and challenges. However, the field of genetics and genetic counseling, as well as that of rare disorders, represents an area suitable for exploration, with its complex datasets and the need for personalized patient care. In this review, we synthesize the wide range of potential applications for ChatGPT in the medical field, highlighting its benefits and limitations. We pay special attention to rare and genetic disorders, aiming to shed light on the future roles of AI-driven chatbots in healthcare. Our goal is to pave the way for a healthcare system that is more knowledgeable, efficient, and centered around patient needs.

Long COVID (LongC) is associated with a myriad of symptoms including cognitive impairment. We reported at the beginning of the COVID-19 pandemic that neuronal-enriched or L1CAM+ extracellular vesicles (nEVs) from people with LongC contained proteins associated with Alzheimer's disease (AD). Since that time, a subset of people with prior COVID infection continue to report neurological problems more than three months after infection. Blood markers to better characterize LongC are elusive. To further identify neuronal proteins associated with LongC, we maximized the number of nEVs isolated from plasma by developing a hybrid EV Microfluidic Affinity Purification (EV-MAP) technique. We isolated nEVs from people with LongC and neurological complaints, AD, and HIV infection with mild cognitive impairment. Using the OLINK platform that assesses 384 neurological proteins, we identified 11 significant proteins increased in LongC and 2 decreased (BST1, GGT1). Fourteen proteins were increased in AD and forty proteins associated with HIV cognitive impairment were elevated with one decreased (IVD). One common protein (BST1) was decreased in LongC and increased in HIV. Six proteins (MIF, ENO1, MESD, NUDT5, TNFSF14 and FYB1) were expressed in both LongC and AD and no proteins were common to HIV and AD. This study begins to identify differences and similarities in the neuronal response to LongC versus AD and HIV infection.

New Psychoactive Substances (NPS) are modifying the drug scenario worldwide and have become a public health concern because of their toxicological profiles and their harmful physical/psychological effects. 3-Methoxy-Phencyclidine (3-MeO-PCP), a non-competitive antagonist of glutamate N-methyl-D-aspartate (NMDA) receptors, belongs to the phencyclidine-like subfamily of arylcyclohexylamines and has gained attention for its toxic, sometimes fatal, effects. Despite several cases of intoxication and death reported in the literature, little is known about substance-induced psychotic disorders (SIP) and potential cognitive impairment following 3-MeO-PCP intake. This literature review aimed to summarize available evidence about 3-MeO-PCP mechanisms of action and physical and psychotropic effects and to spread preliminary findings about persistent psychotic symptoms and impaired cognitive functioning. Additionally, the case of an SIP is reported in a 29-year-old man with small oral intakes of 3-MeO-PCP over two weeks until a high dose ingestion. Psychometric and neuropsychological assessment and brain [F]-fluorodeoxyglucose positron emission tomography integrated with computed tomography were used to support clinical description. Identifying and addressing the characteristic clinical features and neural substrates of NPS-induced psychoses might help clinicians with a more precise differentiation from other psychotic disorders. Although further studies are required, phenotyping the cognitive profile of NPS users might provide targets for tailored therapeutic approaches.

ADHD is a neurodevelopmental disorder that children and adults can develop. A complex interplay of genetic and environmental factors may underlie interindividual variability in ADHD and potentially related aggressive behavior. Using high-resolution molecular biology techniques, we investigated the impact of some MAOA and SLC6A4 variations on ADHD and aggressive behavior in a group of 80 Italian children with ADHD and in 80 healthy controls. We found that homozygous genotypes of MAOA rs6323 and rs1137070 were associated with an increased risk of ADHD ( = 0.02 and = 0.03, respectively), whereas the heterozygous genotypes (GT of rs6323 and CT of rs1137030) ( = 0.0002 and = 0.0006) were strongly linked to a lower risk of developing this disorder. In patients with aggressive behavior, we highlighted only a weak negative association of both MAOA polymorphisms (heterozygous genotypes) with aggressiveness, suggesting that these genotypes may be protective towards specific changes in behavior ( = 0.05). Interestingly, an increase in the GG genotype of rs6323 ( = 0.01) and a decrease in GT genotype ( = 0.0005) was also found in patients without aggressive behavior compared to controls. Regarding 5HTT gene genotyping, no allele and genotype differences have been detected among patients and controls. Our work shows that defining a genetic profile of ADHD may help in the early detection of patients who are more vulnerable to ADHD and/or antisocial and aggressive behavior and to design precision-targeted therapies.

This paper makes a case for digital mental health and provides insights into how digital technologies can enhance (but not replace) existing mental health services. We describe digital mental health by presenting a suite of digital technologies (from digital interventions to the application of artificial intelligence). We discuss the benefits of digital mental health, for example, a digital intervention can be an accessible stepping-stone to receiving support. The paper does, however, present less-discussed benefits with new concepts such as 'poly-digital', where many different apps/features (e.g. a sleep app, mood logging app and a mindfulness app, etc.) can each address different factors of wellbeing, perhaps resulting in an aggregation of marginal gains. Another benefit is that digital mental health offers the ability to collect high-resolution real-world client data and provide client monitoring outside of therapy sessions. These data can be collected using digital phenotyping and ecological momentary assessment techniques (i.e. repeated mood or scale measures via an app). This allows digital mental health tools and real-world data to inform therapists and enrich face-to-face sessions. This can be referred to as blended care/adjunctive therapy where service users can engage in 'channel switching' between digital and non-digital (face-to-face) interventions providing a more integrated service. This digital integration can be referred to as a kind of 'digital glue' that helps join up the in-person sessions with the real world. The paper presents the challenges, for example, the majority of mental health apps are maybe of inadequate quality and there is a lack of user retention. There are also ethical challenges, for example, with the perceived 'over-promotion' of screen-time and the perceived reduction in care when replacing humans with 'computers', and the trap of 'technological solutionism' whereby technology can be naively presumed to solve all problems. Finally, we argue for the need to take an evidence-based, systems thinking and co-production approach in the form of stakeholder-centred design when developing digital mental health services based on technologies. The main contribution of this paper is the integration of ideas from many different disciplines as well as the framework for blended care using 'channel switching' to showcase how digital data and technology can enrich physical services. Another contribution is the emergence of 'poly-digital' and a discussion on the challenges of digital mental health, specifically 'digital ethics'.

Sleep is fundamental to all health, especially mental health. Monitoring sleep is thus critical to delivering effective healthcare. However, measuring sleep in a scalable way remains a clinical challenge because wearable sleep-monitoring devices are not affordable or accessible to the majority of the population. However, as consumer devices like smartphones become increasingly powerful and accessible in the United States, monitoring sleep using smartphone patterns offers a feasible and scalable alternative to wearable devices. In this study, we analyze the sleep behavior of 67 college students with elevated levels of stress over 28 days. While using the open-source mindLAMP smartphone app to complete daily and weekly sleep and mental health surveys, these participants also passively collected phone sensor data. We used these passive sensor data streams to estimate sleep duration. These sensor-based sleep duration estimates, when averaged for each participant, were correlated with self-reported sleep duration (r = 0.83). We later constructed a simple predictive model using both sensor-based sleep duration estimates and surveys as predictor variables. This model demonstrated the ability to predict survey-reported Pittsburgh Sleep Quality Index (PSQI) scores within 1 point. Overall, our results suggest that smartphone-derived sleep duration estimates offer practical results for estimating sleep duration and can also serve useful functions in the process of digital phenotyping.

There is an urgent need to develop more effective and safer antipsychotics beyond dopamine 2 receptor antagonists. An emerging and promising approach is TAAR1 agonism. Therefore, we will conduct a living systematic review and meta-analysis to synthesize and triangulate the evidence from preclinical animal experiments and clinical studies on the efficacy, safety, and underlying mechanism of action of TAAR1 agonism for psychosis.

Depression is the most common psychiatric disorder that burdens modern society heavily. Numerous studies have shown that adverse childhood experiences can increase susceptibility to depression, and depression with adverse childhood experiences has specific clinical-biological features. However, the specific neurobiological mechanisms are not yet precise. Recent studies suggest that the gut microbiota can influence brain function and behavior associated with depression through the "microbe-gut-brain axis" and that the composition and function of the gut microbiota are influenced by early stress. These studies offer a possibility that gut microbiota mediates the relationship between adverse childhood experiences and depression. However, few studies directly link adverse childhood experiences, gut microbiota, and depression. This article reviews recent studies on the relationship among adverse childhood experiences, gut microbiota, and depression, intending to provide insights for new research.

Continuous recognition tasks (CRTs) assess episodic memory (EM), the central functional disturbance in Alzheimer's disease and several related disorders. The online MemTrax computerized CRT provides a platform for screening and assessment that is engaging and can be repeated frequently. MemTrax presents complex visual stimuli, which require complex involvement of the lateral and medial temporal lobes and can be completed in less than 2 min. Results include number of correct recognitions (HITs), recognition failures (MISSes = 1-HITs), correct rejections (CRs), false alarms (FAs = 1-CRs), total correct (TC = HITs + CRs), and response times (RTs) for each HIT and FA. Prior analyses of MemTrax CRT data show no effects of sex but an effect of age on performance. The number of HITs corresponds to faster RT-HITs more closely than TC, and CRs do not relate to RT-HITs. RT-HITs show a typical skewed distribution, and cumulative RT-HITs fit a negative survival curve (RevEx). Thus, this study aimed to define precisely the effects of sex and age on HITS, CRs, RT-HITs, and the dynamics of RTs in an engaged population.

Aerobic capacity has shown to predict physical and mental health-related quality of life in bipolar disorder (BD). However, the correlation between exercise respiratory capacity and mitochondrial function remains understudied. We aimed to assess longitudinally intra-individual differences in these factors during mood episodes and remission in BD.

This study investigated whether self-reported sleep quality is associated with brain amyloid beta (Aβ) accumulation.

Microglia, brain resident macrophages, play multiple roles in maintaining homeostasis, including immunity, surveillance, and protecting the central nervous system through their distinct activation processes. Identifying all types of microglia-driven populations is crucial due to the presence of various phenotypes that differ based on developmental stages or activation states. During embryonic development, the E8.5 yolk sac contains erythromyeloid progenitors that go through different growth phases, eventually resulting in the formation of microglia. In addition, microglia are present in neurological diseases as a diverse population. So far, no individual biomarker for microglia has been discovered that can accurately identify and monitor their development and attributes.

Post-traumatic stress disorder (PTSD) is an impairing mental health condition with high prevalence among military and general populations alike. PTSD service dogs are a complementary and alternative intervention needing scientific validation. We investigated whether dogs can detect putative stress-related volatile organic compounds (VOCs) in the breath of people with trauma histories (54% with PTSD) exposed to personalized trauma cues.