Data Analytics and Psychiatry

Epigenetic age estimators indicating faster/slower biological aging vs chronological age independently associate with several age-related outcomes; however, longitudinal associations with cognitive function are understudied. We examined associations of epigenetic age estimators with cognitive function measured annually.

Veterans receiving inpatient psychiatric services with limitations in activities of daily living (ADLs) benefit from occupational therapy, yet disparities in access are unknown.

Long-term potentiation (LTP)-like activity can be induced by stimulation protocols such as paired associative stimulation (PAS). We aimed to determine whether PAS-induced LTP-like activity (PAS-LTP) of the dorsolateral prefrontal cortex (DLPFC) is associated with cortical thickness and other structural measures impaired in Alzheimer's dementia (AD). We also explored longitudinal relationships between these brain structures and PAS-LTP response after a repetitive PAS (rPAS) intervention. Mediation and regression analyses were conducted using data from randomized controlled trials with AD and healthy control participants. PAS-electroencephalography assessed DLPFC PAS-LTP. DLPFC thickness and surface area were acquired from T1-weighted magnetic resonance imaging. Fractional anisotropy and mean diffusivity (MD) of the superior longitudinal fasciculus (SLF)-a tract important to induce PAS-LTP-were measured with diffusion-weighted imaging. AD participants exhibited reduced DLPFC thickness and increased SLF MD. There was also some evidence that reduction in DLPFC thickness mediates DLPFC PAS-LTP impairment. Longitudinal analyses showed preliminary evidence that SLF MD, and to a lesser extent DLPFC thickness, is associated with DLPFC PAS-LTP response to active rPAS. This study expands our understanding of the relationships between brain structural changes and neuroplasticity. It provides promising evidence for a structural predictor to improving neuroplasticity in AD with neurostimulation. This article is part of a discussion meeting issue 'Long-term potentiation: 50 years on'.

Guidelines recommend an analgesia-first strategy for sedation during mechanical ventilation, but associations between opioids provided during mechanical ventilation and posthospitalization opioid-related outcomes are unclear.

Self-body satisfaction is considered a psychological factor for exercise dependence (EXD). However, the potential neuropsychological mechanisms underlying this association remain unclear.

Past work has shown that people with schizophrenia exhibit more cross-subject heterogeneity in their functional connectivity patterns. However, it remains unclear whether specific brain networks are implicated, whether common confounds could explain the results, or whether task activations might also be more heterogeneous. Unambiguously establishing the existence and extent of functional heterogeneity constitutes a first step toward understanding why it emerges and what it means clinically.

Elucidating biological mechanisms contributing to bipolar disorder (BD) is key to improved diagnosis and treatment development. With converging evidence implicating the metabotropic glutamate receptor 5 (mGlu5) in the pathology of BD, here, we therefore test the hypothesis that recently identified deficits in mGlu5 are associated with functional brain differences during emotion processing in BD.

To describe the pattern of the prevalence of mental health problems during the first year of the COVID-19 pandemic and examine the impact of containment measures on these trends.

To investigate gender-specific factors associated with case complexity in a population-based sample of middle-aged and older adults using a holistic approach to complexity.

The Ethiopian Primary Healthcare Clinical Guidelines (EPHCG) seek to improve quality of primary health care, while also expanding access to care for people with Non-Communicable Diseases and Mental Health Conditions (NCDs/MHCs). The aim of this study was to identify barriers and enablers to implementation of the EPHCG with a particular focus on NCDs/MHCs.

By analyzing 15,000 samples from 348 mammalian species, we derive DNA methylation (DNAm) predictors of maximum life span ( = 0.89), gestation time ( = 0.96), and age at sexual maturity ( = 0.85). Our maximum life-span predictor indicates a potential innate longevity advantage for females over males in 17 mammalian species including humans. The DNAm maximum life-span predictions are not affected by caloric restriction or partial reprogramming. Genetic disruptions in the somatotropic axis such as growth hormone receptors have an impact on DNAm maximum life span only in select tissues. Cancer mortality rates show no correlation with our epigenetic estimates of life-history traits. The DNAm maximum life-span predictor does not detect variation in life span between individuals of the same species, such as between the breeds of dogs. Maximum life span is determined in part by an epigenetic signature that is an intrinsic species property and is distinct from the signatures that relate to individual mortality risk.

Evidence on the effectiveness of multidomain lifestyle interventions to prevent cognitive decline in older people without dementia is mixed. Embedded in the World-Wide FINGERS initiative, FINGER-NL aims to investigate the effectiveness of a 2-year multidomain lifestyle intervention on cognitive functioning in older Dutch at risk individuals.

Community-based video interventions offer an effective and potentially scalable early interaction coaching tool for caregivers living in low resource settings. We tested the Universal Baby (UB) video innovation; an early interaction coaching tool using video sourced and produced locally with early child development (ECD) expert supervision.

The importance of integrated care for complex, multiple long term conditions was acknowledged before the COVID pandemic but remained a challenge. The pandemic and consequent development of Long COVID required rapid adaptation of health services to address the population's needs, requiring service redesigns including integrated care. This Delphi consensus study was conducted in the UK and found similar integrated care priorities for Long COVID and complex, multiple long term conditions, provided by 480 patients and health care providers, with an 80% consensus rate. The resultant recommendations were based on more than 1400 responses from survey participants and were supported by patients, health care professionals, and by patient charities. Participants identified the need to allocate resources to: support integrated care, provide access to care and treatments that work, provide diagnostic procedures that support the personalization of treatment in an integrated care environment, and enable structural consultation between primary and specialist care settings including physical and mental health care. Based on the findings we propose a model for delivering integrated care by a multidisciplinary team to people with complex multisystem conditions. These recommendations can inform improvements to integrated care for complex, multiple long term conditions and Long COVID at international level.

The high heritability of ALS contrasts with its low molecular diagnosis rate post-genetic testing, pointing to potential undiscovered genetic factors. To aid the exploration of these factors, we introduced EpiOut, an algorithm to identify chromatin accessibility outliers that are regions exhibiting divergent accessibility from the population baseline in a single or few samples. Annotation of accessible regions with histone ChIP-seq and Hi-C indicates that outliers are concentrated in functional loci, especially among promoters interacting with active enhancers. Across different omics levels, outliers are robustly replicated, and chromatin accessibility outliers are reliable predictors of gene expression outliers and aberrant protein levels. When promoter accessibility does not align with gene expression, our results indicate that molecular aberrations are more likely to be linked to post-transcriptional regulation rather than transcriptional regulation. Our findings demonstrate that the outlier detection paradigm can uncover dysregulated regions in rare diseases. EpiOut is available at github.com/uci-cbcl/EpiOut.

Overdose Fatality Review (OFR) is an important public health tool for shaping overdose prevention strategies in communities. However, OFR teams review only a few cases at a time, which typically represent a small fraction of the total fatalities in their jurisdiction. Such limited review could result in a partial understanding of local overdose patterns, leading to policy recommendations that do not fully address the broader community needs.

Prenatal exposure to alcohol and tobacco has been associated with child regulatory abilities and problems, but less is known about the associations with cannabis exposure. This review seeks to address this gap primarily focusing on the effects of maternal cannabis use on the child. Thus, we investigate the association between pre- and postnatal cannabis exposure of the child and regulatory abilities and problems, as well as the underlying neurobiological mechanisms potentially mediating the associations. According to the PRISMA guidelines, a systematic literature review was performed based on a systematic literature search through Medline (PubMed), Web of Science and PsycInfo, including studies assessing children aged 0-6 years with cannabis exposure in the preconception, pre-or postnatal period (preconception, pre- and postnatal cannabis exposure [PCE]) and investigating child regulatory abilities, regulatory problems or neurobiological mechanisms. Of n = 1061 screened articles, n = 33 were finally included. Diminished regulatory abilities are more likely to be found in infants after PCE, while specific regulatory problems tend to be more frequently found after two years of age. Possible mechanisms are related to changes in methylation and expression of key genes involved in endocannabinoid, dopaminergic and opioid systems, increased cortisol reactivity and altered Secretory Immunoglobulin A levels. Furthermore, PCE has been associated with changes in brain structure and connectivity. Current findings indicate that PCE is associated with both age-dependent alterations in self-regulation and neurobiological changes in young children. However, evidence is limited due to the number of studies, small sample sizes and lack of control for maternal psychopathology. Longitudinal studies including psychometric data from mothers are needed in order to further understand the implications of PCE.Trial registration: The review is registered with PROSPERO (ID: CRD42023425115).

Angiotensin converting enzyme 2 (ACE2) serves as the primary receptor for the SARS-CoV-2 virus and has implications for the functioning of the cardiovascular system. Based on our previously published bioinformatic analysis, in this study we aimed to analyze the diagnostic and predictive utility of miRNAs (miR-10b-5p, miR-124-3p, miR-200b-3p, miR-26b-5p, miR-302c-5p) identified as top regulators of ACE2 network with potential to affect cardiomyocytes and cardiovascular system in patients with COVID-19. The expression of miRNAs was determined through qRT-PCR in a cohort of 79 hospitalized COVID-19 patients as well as 32 healthy volunteers. Blood samples and clinical data of COVID-19 patients were collected at admission, 7-days and 21-days after admission. We also performed SHAP analysis of clinical data and miRNAs target predictions and advanced enrichment analyses. Low expression of miR-200b-3p at the seventh day of admission is indicative of predictive value in determining the length of hospital stay and/or the likelihood of mortality, as shown in ROC curve analysis with an AUC of 0.730 and a p-value of 0.002. MiR-26b-5p expression levels in COVID-19 patients were lower at the baseline, 7 and 21-days of admission compared to the healthy controls (P < 0.0001). Similarly, miR-10b-5p expression levels were lower at the baseline and 21-days post admission (P = 0.001). The opposite situation was observed in miR-124-3p and miR-302c-5p. Enrichment analysis showed influence of analyzed miRNAs on IL-2 signaling pathway and multiple cardiovascular diseases through COVID-19-related targets. Moreover, the COVID-19-related genes regulated by miR-200b-3p were linked to T cell protein tyrosine phosphatase and the HIF-1 transcriptional activity in hypoxia. Analysis focused on COVID-19 associated genes showed that all analyzed miRNAs are strongly affecting disease pathways related to CVDs which could be explained by their strong interaction with the ACE2 network.

Psychological interventions delivered by non-specialist providers have shown mixed results for treating maternal depression. mHealth solutions hold the possibility for unobtrusive behavioural data collection to identify challenges and reinforce change in psychological interventions. We conducted a proof-of-concept study using passive sensing integrated into a depression intervention delivered by non-specialists to twenty-four adolescents and young mothers (30% 15-17 years old; 70% 18-25 years old) with infants (< 12 months old) in rural Nepal. All mothers showed a reduction in depression symptoms as measured with the Beck Depression Inventory. There were trends toward increased movement away from the house (greater distance measured through GPS data) and more time spent away from the infant (less time in proximity measured with the Bluetooth beacon) as the depression symptoms improved. There was considerable heterogeneity in these changes and other passively collected data (speech, physical activity) throughout the intervention. This proof-of-concept demonstrated that passive sensing can be feasibly used in low-resource settings and can personalize psychological interventions. Care must be taken when implementing such an approach to ensure confidentiality, data protection, and meaningful interpretation of data to enhance psychological interventions.

Racial discrimination is a psychosocial stressor associated with youths' risk for psychiatric symptoms. Scarce data exist on the moderating role of amygdalar activation patterns among Black youths in the US.

Incongruent perceptions of parental emotional expressivity between parents and adolescents may signify relational challenges, potentially impacting adolescents' socioemotional adjustment. Direct evidence is still lacking and father-adolescent discrepancies are overlooked. This study employed a multi-informant design to investigate whether both mother-adolescent and father-adolescent discrepancies in perceptions of parental expressivity are related to adolescents' mental well-being, specifically focusing on loneliness and depression. Analyzing data from 681 families (mean age of adolescents = 15.5 years old, 51.2% girls, 40% only-children) in China revealed that adolescents tended to perceive paternal and maternal emotional expressivity more negatively than their parents, particularly fathers. Polynomial regression and response surface analysis showed significant links between parent-adolescent congruence and incongruence and adolescent loneliness. (In)Congruence between adolescents and mothers or fathers predicted later adolescent depression, mediated by adolescent loneliness and varied by the dimension of emotional expressivity. These findings provide insights into the roles of mothers' and fathers' emotional expressivity in shaping children's mental well-being during adolescence.

Research in machine-learning (ML) algorithms using natural behavior (i.e., text, audio, and video data) suggests that these techniques could contribute to personalization in psychology and psychiatry. However, a systematic review of the current state-of-the-art is missing. Moreover, individual studies often target ML experts, and may overlook potential clinical implications of their findings. In a narrative accessible to mental health professionals, we present a systematic review, conducted in 5 psychology and 2 computer-science databases. We included 128 studies assessing the predictive power of ML algorithms using text, audio, and/or video data in the prediction of anxiety and post-traumatic stress (PTSD). Most studies (n = 87) aimed at predicting anxiety, the remainder (n = 41) focused on PTSD. They were mostly published since 2019, in computer science journals, and tested algorithms using text (n = 72), as opposed to audio or video. They focused mainly on general populations (n = 92), less on laboratory experiments (n = 23) or clinical populations (n = 13). Methodological quality varied, as did reported metrics of the predictive power, hampering comparison across studies. Two thirds of studies, focusing on both disorders, reported acceptable to very good predictive power (including high-quality studies only). Results of 33 studies were uninterpretable, mainly due to missing information. Research into ML algorithms using natural behavior is in its infancy, but shows potential to contribute to diagnostics of mental disorders, such as anxiety and PTSD, in the future, if standardization of methods, reporting of results, and research in clinical populations are improved.

Schizophrenia lacks a clear definition at the neuroanatomical level, capturing the sites of origin and progress of this disorder. Using a network-theory approach called epicenter mapping on cross-sectional magnetic resonance imaging from 1124 individuals with schizophrenia, we identified the most likely "source of origin" of the structural pathology. Our results suggest that the Broca's area and adjacent frontoinsular cortex may be the epicenters of neuroanatomical pathophysiology in schizophrenia. These epicenters can predict an individual's response to treatment for psychosis. In addition, cross-diagnostic similarities based on epicenter mapping over of 4000 individuals diagnosed with neurological, neurodevelopmental, or psychiatric disorders appear to be limited. When present, these similarities are restricted to bipolar disorder, major depressive disorder, and obsessive-compulsive disorder. We provide a comprehensive framework linking schizophrenia-specific epicenters to multiple levels of neurobiology, including cognitive processes, neurotransmitter receptors and transporters, and human brain gene expression. Epicenter mapping may be a reliable tool for identifying the potential onset sites of neural pathophysiology in schizophrenia.

Although the association between mental disorder and metabolic syndrome as a bidirectional relationship has been demonstrated, there is little knowledge of the cumulative and individual effect of these conditions on peripartum mental health. This study aims to investigate the association between metabolic syndrome conditions (MetS-C) and maternal mental illness in the perinatal period, while exploring time to incident mental disorder diagnosis in postpartum women.

Herein, we examined the correlation between platelet/high-density lipoprotein cholesterol ratio (PHR) and symptoms of depression among United States adults.

Although comprehensive and widespread guidelines on how to conduct systematic reviews of outcome measurement instruments (OMIs) exist, for example from the COSMIN (COnsensus-based Standards for the selection of health Measure- ment INstruments) initiative, key information is often missing in published reports. This article describes the development of an extension of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guideline: PRISMA-COSMIN for OMIs 2024.

Major Depressive Disorder (MDD) is a common, frequently chronic condition characterized by substantial molecular alterations and pathway dysregulations. Single metabolite and targeted metabolomics platforms have revealed several metabolic alterations in depression, including energy metabolism, neurotransmission, and lipid metabolism. More comprehensive coverage of the metabolome is needed to further specify metabolic dysregulations in depression and reveal previously untargeted mechanisms. Here, we measured 820 metabolites using the metabolome-wide Metabolon platform in 2770 subjects from a large Dutch clinical cohort with extensive clinical phenotyping (1101 current MDD, 868 remitted MDD, 801 healthy controls) at baseline, which were repeated in 1805 subjects at 6-year follow up (327 current MDD, 1045 remitted MDD, 433 healthy controls). MDD diagnosis was based on DSM-IV psychiatric interviews. Depression severity was measured with the Inventory of Depressive Symptomatology Self-report. Associations between metabolites and MDD status and depression severity were assessed at baseline and at 6-year follow-up. At baseline, 139 and 126 metabolites were associated with current MDD status and depression severity, respectively, with 79 overlapping metabolites. Adding body mass index and lipid-lowering medication to the models changed results only marginally. Among the overlapping metabolites, 34 were confirmed in internal replication analyses using 6-year follow-up data. Downregulated metabolites were enriched with long-chain monounsaturated (P = 6.7e-07) and saturated (P = 3.2e-05) fatty acids; upregulated metabolites were enriched with lysophospholipids (P = 3.4e-4). Mendelian randomization analyses using genetic instruments for metabolites (N = 14,000) and MDD (N = 800,000) showed that genetically predicted higher levels of the lysophospholipid 1-linoleoyl-GPE (18:2) were associated with greater risk of depression. The identified metabolome-wide profile of depression indicated altered lipid metabolism with downregulation of long-chain fatty acids and upregulation of lysophospholipids, for which causal involvement was suggested using genetic tools. This metabolomics signature offers a window on depression pathophysiology and a potential access point for the development of novel therapeutic approaches.

Persistence and distress distinguish more clinically significant psychotic-like experiences (PLEs) from those that are less likely to be associated with impairment and/or need for care. Identifying risk factors that differentiate clinically relevant PLEs early in development is important for improving our understanding of the etiopathogenesis of these experiences. Machine learning analyses examined the most important baseline factors distinguishing persistent distressing PLEs.

Infants' motivation to engage with the social world depends on the interplay between individual brain's characteristics and previous exposure to social cues such as the parent's smile or eye contact. Different hypotheses about why specific combinations of emotional expressions and gaze direction engage children have been tested with group-level approaches rather than focusing on individual differences in the social brain development. Here, a novel Artificial Intelligence-enhanced brain-imaging approach, Neuroadaptive Bayesian Optimisation (NBO), was applied to infant electro-encephalography (EEG) to understand how selected neural signals encode social cues in individual infants. EEG data from 42 6- to 9-month-old infants looking at images of their parent's face were analysed in real-time and used by a Bayesian Optimisation algorithm to identify which combination of the parent's gaze/head direction and emotional expression produces the strongest brain activation in the child. This individualised approach supported the theory that the infant's brain is maximally engaged by communicative cues with a negative valence (angry faces with direct gaze). Infants attending preferentially to faces with direct gaze had increased positive affectivity and decreased negative affectivity. This work confirmed that infants' attentional preferences for social cues are heterogeneous and shows the NBO's potential to study diversity in neurodevelopmental trajectories.

Previous research established the associations between childhood trauma and psychosis, but the effects of childhood trauma on psychotic-like experiences (PLEs) among people living with HIV (PLWH) and the potential mediation mechanisms in these associations remain unclear.

Alzheimer's disease (AD) is a brain network disorder where pathological proteins accumulate through networks and drive cognitive decline. Yet, the role of network connectivity in facilitating this accumulation remains unclear. Using in-vivo multimodal imaging, we show that the distribution of tau and reactive microglia in humans follows spatial patterns of connectivity variation, the so-called gradients of brain organization. Notably, less distinct connectivity patterns ("gradient contraction") are associated with cognitive decline in regions with greater tau, suggesting an interaction between reduced network differentiation and tau on cognition. Furthermore, by modeling tau in subject-specific gradient space, we demonstrate that tau accumulation in the frontoparietal and temporo-occipital cortices is associated with greater baseline tau within their functionally and structurally connected hubs, respectively. Our work unveils a role for both functional and structural brain organization in pathology accumulation in AD, and supports subject-specific gradient space as a promising tool to map disease progression.

Surface-enhanced Raman spectroscopy (SERS), a rapid, low-cost, non-invasive, ultrasensitive, and label-free technique, has been widely used in-situ and ex-situ biomedical diagnostics questions. However, analyzing and interpreting the untargeted spectral data remains challenging due to the difficulty of designing an optimal data pre-processing and modelling procedure. In this paper, we propose a Multi-branch Attention Raman Network (MBA-RamanNet) with a multi-branch attention module, including the convolutional block attention module (CBAM) branch, deep convolution module (DCM) branch, and branch weights, to extract more global and local information of characteristic Raman peaks which are more distinctive for classification tasks. CBAM, including channel and spatial aspects, is adopted to enhance the distinctive global information on Raman peaks. DCM is used to supplement local information of Raman peaks. Autonomously trained branch weights are applied to fuse the features of each branch, thereby optimizing the global and local information of the characteristic Raman peaks for identifying diseases. Extensive experiments are performed for two different neurological disorders classification tasks via untargeted serum SERS data. The results demonstrate that MBA-RamanNet outperforms commonly used CNN methods with an accuracy of 88.24% for the classification of healthy controls, mild cognitive impairment, Alzheimer's disease, and Non-Alzheimer's dementia; an accuracy of 90% for the classification of healthy controls, elderly depression, and elderly anxiety.

Depression has emerged as a modifiable risk factor for cardiovascular disease (CVD). However, evidence on whether depressive symptoms measured using a self-report questionnaire are associated with CVD incidence is scarce. Therefore, we aimed to investigate the association between depressive symptoms and CVD risk using data from national health examinations and insurance claim records.

Discrepancies between sleep diaries and sensor-based sleep parameters are widely recognized. This study examined the effect of showing sensor-based sleep parameters while completing a daily diary. The provision of sensor-based data was expected to reduce variance but not change the mean of self-reported sleep parameters, which would in turn align better with sensor-based data compared to a control diary.

Stepped, evidence-based and integrated care service models have the potential to be used as a reference for mental health services. RECOVER aimed to evaluate cost savings, effectiveness, and cost-effectiveness of such a model within a two arm, assessor- and data analysist-blinded RCT in Hamburg, Germany. Participants aged 16-79 years with mental disorders were randomly assigned either to RECOVER or treatment as usual (TAU). Primary outcomes comprised costs, effectiveness (combined symptoms, functioning, quality of life), and cost-effectiveness, hierarchically ordered. Outcomes were evaluated according to the ITT principle, group differences regarding costs with adjusted generalized linear models, effectiveness with ANCOVA models, and cost-effectiveness with the incremental cost-effectiveness ratio (ICER) and cost-effectiveness acceptability curves (CEACs). Between 1/1/2018 and 12/31/2020, n = 891 were finally included (n = 477 in RECOVER, n = 444 in TAU). RECOVER was associated with significantly lower annual total costs (-22 %), health and social care costs (-25 %) and hospital costs (-50 %). Effectiveness analyses showed a significantly better outcome for RECOVER with the fully imputed data . The CEACs descriptively demonstrated that RECOVER was cost-effective with a probability of >95 %. Treatment in RECOVER resulted in substantial cost reductions with better cost-effectiveness. RECOVER can be recommended as a reference model for comprehensive and integrated mental health services.

To evaluate the effects of behavioral health interventions delivered within pediatric integrated primary care models on clinical outcomes.

Evidence links lifestyle factors with Alzheimer's disease (AD). We report the first randomized, controlled clinical trial to determine if intensive lifestyle changes may beneficially affect the progression of mild cognitive impairment (MCI) or early dementia due to AD.

Clozapine is an off-label drug used in most countries to prevent suicide in individuals with schizophrenia. However, few studies have reported real-world prescription practices. This study aimed to explore the association between a history of suicidal behavior and clozapine prescribing during eight weeks of hospitalization for individuals with early-stage schizophrenia.

Lithium (Li) remains the treatment of choice for bipolar disorders (BP). Its mood-stabilizing effects help reduce the long-term burden of mania, depression and suicide risk in patients with BP. It also has been shown to have beneficial effects on disease-associated conditions, including sleep and cardiovascular disorders. However, the individual responses to Li treatment vary within and between diagnostic subtypes of BP (e.g. BP-I and BP-II) according to the clinical presentation. Moreover, long-term Li treatment has been linked to adverse side-effects that are a cause of concern and non-adherence, including the risk of developing chronic medical conditions such as thyroid and renal disease. In recent years, studies by the Consortium on Lithium Genetics (ConLiGen) have uncovered a number of genetic factors that contribute to the variability in Li treatment response in patients with BP. Here, we leveraged the ConLiGen cohort (N = 2064) to investigate the genetic basis of Li effects in BP. For this, we studied how Li response and linked genes associate with the psychiatric symptoms and polygenic load for medical comorbidities, placing particular emphasis on identifying differences between BP-I and BP-II.

Anxiety and depression can seriously undermine mental health and quality of life globally. The consumption of junk foods, including ultra-processed foods, fast foods, unhealthy snacks, and sugar-sweetened beverages, has been linked to mental health. The aim of this study is to use the published literature to evaluate how junk food consumption may be associated with mental health disorders in adults.

Tau-first cognitive proteinopathy (TCP) denotes a clinical phenotype of Alzheimer disease (AD) showing Florzolotau(18F) positron emission tomography (PET) positivity but a negative amyloid status.

This meta-analysis aimed to describe the efficacy of bumetanide in improving infarct volume, brain edema, and behavioral outcomes in animal models of cerebral ischemia. Embase, PubMed and Web of Science databases were searched from their inception to February 2024 (INPLASY:202430023). Data on the animal species, stroke model, drug dose, time of treatment, method of administration, study quality, and outcomes were extracted and pooled in a meta-analysis. The combined standardized mean difference (SMD) or mean difference (MD) estimates and 95% confidence intervals (CIs) were calculated using random- or fixed-effects models. Thirteen eligible studies involving >200 animals fulfilled the inclusion criteria and were included in this meta-analysis. Meta-analyses demonstrated that bumetanide treatment significantly reduced cerebral infarct volume (SMD: -0.42; 95% CI: -0.75, -0.09; < 0.01; = 186 animals) and consistently relieved brain edema (SMD: -1.39; 95% CI: -2.06, -0.72; < 0.01; = 64 animals). Subgroup analyses demonstrated that bumetanide treatment reduced infarct volume in transient but not permanent cerebral ischemia models. When administered after the stroke, it was more effective than treatment initiation before the stroke. Eight studies assessed the effect of bumetanide on behavioral function and the results showed that bumetanide treatment significantly improved neurobehavioral deficits (SMD: -2.35; 95% CI: -2.72, -1.97; < 0.01; = 250 animals). We conclude that bumetanide appears to be effective in reducing infarct volume and brain edema and improving behavioral recovery in animal models of cerebral ischemia. This mechanism needs to be confirmed through further investigation.

Post-COVID-19 Condition (PCC) is a prevalent, persistent and debilitating phenomenon occurring three or more months after resolution of acute COVID-19 infection. Fatigue and depressive symptoms are commonly reported in PCC. We aimed to further characterize PCC by assessing the relationship between fatigue and depressive symptom severity in adults with PCC.

Although it is well recognized that autism spectrum disorder (ASD) is associated with atypical dynamic functional connectivity patterns, the dynamic changes in brain intrinsic activity over each time point and the potential molecular mechanisms associated with atypical dynamic temporal characteristics in ASD remain unclear. Here, we employed the Hidden Markov Model (HMM) to explore the atypical neural configuration at every scanning time point in ASD, based on resting-state functional magnetic resonance imaging (rs-fMRI) data from the Autism Brain Imaging Data Exchange. Subsequently, partial least squares regression and pathway enrichment analysis were employed to explore the potential molecular mechanism associated with atypical neural dynamics in ASD. 8 HMM states were inferred from rs-fMRI data. Compared to typically developing, individuals on the autism spectrum showed atypical state-specific temporal characteristics, including number of states and occurrences, mean life time and transition probability between states. Moreover, these atypical temporal characteristics could predict communication difficulties of ASD, and states assoicated with negative activation in default mode network and frontoparietal network, and positive activation in somatomotor network, ventral attention network, and limbic network, had higher predictive contribution. Furthermore, a total of 321 genes was revealed to be significantly associated with atypical dynamic brain states of ASD, and these genes are mainly enriched in neurodevelopmental pathways. Our study provides new insights into characterizing the atypical neural dynamics from a moment-to-moment perspective, and indicates a linkage between atypical neural configuration and gene expression in ASD.

In the UK in May 2016, standardised packaging of tobacco products was implemented, including minimum pack sizes of 20 sticks or 30 g loose tobacco. The change was intended to reduce uptake by increasing upfront costs to young people, but there was concern it may unintentionally increase consumption among people smoking. This study aimed to assess whether the introduction of the policy was associated with changes in (1) mean daily factory-made (FM)/roll-your-own (RYO) cigarettes consumption among people smoking predominantly (a) FM and (b) RYO cigarettes; and (2) current smoking prevalence among 16-24-year-olds.

African Americans (AAs) face cardiovascular health (CVH) disparities linked to systemic racism. The 2020 police killing of Mr. George Floyd in Minneapolis, Minnesota, alongside the COVID-19 pandemic, exacerbated adverse psychosocial factors affecting CVH outcomes among AAs. This manuscript describes the study protocol and participant characteristics in an ancillary study exploring the relationship between biopsychosocial factors and CVH among AAs.

Human spaceflight has historically been managed by government agencies, such as the NASA Twins Study, but new commercial spaceflight opportunities have opened spaceflight to a broader population. In 2021, the SpaceX Inspiration4 mission launched the first-ever all civilian crew to low Earth orbit, which included the youngest American astronaut (age 29), novel in-flight experimental technologies (handheld ultrasound imaging, smartwatch wearables, and immune profiling), ocular alignment measurements, and new protocols for in-depth, multi-omic molecular and cellular profiling. Here we report the primary findings from the 3-day spaceflight mission, which induced a broad range of physiological and stress responses, neurovestibular changes indexed by ocular misalignment, and altered neurocognitive functioning, some of which match long-term spaceflight, but almost all of which did not differ from baseline (pre-flight) after return to Earth. Overall, these preliminary civilian spaceflight data suggest that short-duration missions do not pose a significant health risk, and moreover present a rich opportunity to measure the earliest phases of adaptation to spaceflight in the human body at anatomical, cellular, physiologic, and cognitive levels. Finally, these methods and results lay the foundation for an open, rapidly expanding biomedical database for astronauts, which can inform countermeasure development for both private and government-sponsored space missions.

Distributed hypothalamic-midbrain neural circuits help orchestrate complex behavioral responses during social interactions. Given rapid advances in optical imaging, it is a fundamental question how population-averaged neural activity measured by multi-fiber photometry (MFP) for calcium fluorescence signals correlates with social behaviors is a fundamental question. This paper aims to investigate the correspondence between MFP data and social behaviors. Approach: We propose a state-space analysis framework to characterize mouse MFP data based on dynamic latent variable models, which include a continuous-state linear dynamical system (LDS) and a discrete-state hidden semi-Markov model (HSMM). We validate these models on extensive MFP recordings during aggressive and mating behaviors in male-male and male-female interactions, respectively. Main Results: Our results show that these models are capable of capturing both temporal behavioral structure and associated neural states, and produce interpretable latent states. Our approach is also validated in computer simulations in the presence of known ground truth. Significance: Overall, these analysis approaches provide a state-space framework to examine neural dynamics underlying social behaviors and reveals mechanistic insights into the relevant networks. .

Disease-modifying therapies (DMTs) for Alzheimer's disease (AD) have early evidence of efficacy. Widespread delivery of DMTs will require major service reconfiguration. Treatment pathways will need to include triaging for eligibility, regular infusions and baseline and follow-up MRI scanning. A critical step in planning is provision of real-world estimates of patients likely to be eligible for triaging, but these are challenging to obtain.

The recent acceleration of commercial, private, and multi-national spaceflight has created an unprecedented level of activity in low Earth orbit (LEO), concomitant with the highest-ever number of crewed missions entering space and preparations for exploration-class (>1 year) missions. Such rapid advancement into space from many new companies, countries, and space-related entities has enabled a"Second Space Age." This new era is also poised to leverage, for the first time, modern tools and methods of molecular biology and precision medicine, thus enabling precision aerospace medicine for the crews. The applications of these biomedical technologies and algorithms are diverse, encompassing multi-omic, single-cell, and spatial biology tools to investigate human and microbial responses to spaceflight. Additionally, they extend to the development of new imaging techniques, real-time cognitive assessments, physiological monitoring, and personalized risk profiles tailored for astronauts. Furthermore, these technologies enable advancements in pharmacogenomics (PGx), as well as the identification of novel spaceflight biomarkers and the development of corresponding countermeasures. In this review, we highlight some of the recent biomedical research from the National Aeronautics and Space Administration (NASA), Japan Aerospace Exploration Agency (JAXA), European Space Agency (ESA), and other space agencies, and also detail the commercial spaceflight sector's (e.g. SpaceX, Blue Origin, Axiom, Sierra Space) entrance into aerospace medicine and space biology, the first aerospace medicine biobank, and the myriad upcoming missions that will utilize these tools to ensure a permanent human presence beyond LEO, venturing out to other planets and moons.

Mentalizing refers to the ability to understand one's own and others' mental states. Mentalizing is considered a key component of social cognition and healthy personality development. A multinational assessment tools able to appraise the multidimensional and multifaceted aspects of this complex construct are needed.

Poor sleep quality is a serious concern among diabetes mellitus patients, adversely affecting glycemic management and the prognosis of diabetic patients. Therefore, the main aim of this study was to estimate the overall pooled prevalence of poor sleep quality and its associated factors among diabetic patients in Sub-Saharan Africa.

Methadone is a mu (μ) opioid receptor agonist used clinically in adults and children to manage opioid use disorder, neonatal abstinence syndrome, and acute and chronic pain. It is typically marketed as a racemic mixture of R- and S-enantiomers. R-methadone has 30-to 50-fold higher analgesic potency than S-methadone, and S-methadone has a greater adverse effect (prolongation) on the cardiac QTc interval. Methadone undergoes stereoselective metabolism. CYP2B6 is the primary enzyme responsible for catalyzing the metabolism of both enantiomers to the inactive metabolites, S- and R-2-ethylidene-1,5-dimethyl-3,3-diphenylpyrrolidine (S- and R-EDDP). Genetic variation in the CYP2B6 gene has been investigated in the context of implications for methadone pharmacokinetics, dose, and clinical outcomes. Most CYP2B6 variants result in diminished or loss of CYP2B6 enzyme activity, which can lead to higher plasma methadone concentrations (affecting S- more than R-methadone). However, the data do not consistently indicate that CYP2B6-based metabolic variability has a clinically significant effect on methadone dose, efficacy, or QTc prolongation. Expert analysis of the published literature does not support a change from standard methadone prescribing based on CYP2B6 genotype (updates at www.cpicpgx.org).

There is a lack of distinct and measurable outcomes in psychiatric and/or mental health nursing which negatively impacts guiding clinical practice, assessing evidence-based nursing interventions, ensuring future-proof nursing education and establishing visibility as a profession and discipline. Psychiatric and/or mental health nursing struggle to demonstrate patient-reported outcomes to assess the effectiveness of their practice. A systematic review that summarising patient-reported outcomes, associated factors, measured nursing care/interventions and used measurement scales of psychiatric and/or mental health nursing in the adult population in acute, intensive and forensic psychiatric wards in hospitals will capture important information on how care can be improved by better understanding what matters and what is important to patients themselves. This review can contribute to the design, planning, delivery and assessment of the quality of current and future nursing care METHODS AND ANALYSIS: This protocol follows the Cochrane methodological guidance on systematic reviews of interventions and The Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocol. The search strategy will be identified by consultations with clinical and methodological experts and by exploring the literature. The databases Ovid MEDLINE, CINAHL, EMBASE, APA PsychARTICLES, Web of Science and Scopus will be searched for all published studies. Studies will be screened and selected with criteria described in the population, intervention, control and outcomes format after a pilot test by two researchers. Studies will be screened in two stages: (1) title and abstract screening and (2) full-text screening. Data extraction and the quality assessment based on the Johanna Briggs Institute guidelines will be conducted by two researchers. Data will be presented in a narrative synthesis.

Although the incidence of mental health problems is highest in young people, the majority do not seek help. Reducing the discrepancy between need for care and access to services requires an understanding of the user perspective, which is largely lacking. This study aimed to examine preferences for mental health service attributes and their relative importance among young people, as well as the potential impact on actual help-seeking intentions.

Schizophrenia affects 24 million people worldwide. Digital health interventions drawing on psychological principles have been developed, but their effectiveness remains unclear. This parallel, assessor-blinded, randomized clinical trial aimed to investigate whether a cognitive behaviour therapy-informed digital health intervention (Actissist app) confers added benefit on psychotic symptoms over and above remote symptom monitoring (ClinTouch app). Participants recruited from UK community health services were randomized 1:1 to receive either Actissist plus treatment as usual (TAU) or ClinTouch plus TAU. Eligible participants were adults with schizophrenia-spectrum psychosis within five years of first episode onset meeting a criterion level of positive symptoms severity. The primary outcome was Positive and Negative Syndrome Scale (PANSS) symptoms total score at 12 weeks post-randomization. Intention-to-treat analysis included 172 participants, with 149 participants (86.6 %) providing primary outcome data. Actissist plus TAU was not associated with greater reduction than an active control remote symptom monitoring app (ClinTouch) in PANSS total score at post-randomization. There were no significant effects between groups across secondary measures. There were no serious adverse reactions. Both groups improved on the primary psychotic symptoms measure at primary end-point and on secondary measures over time. The Actissist app is safe but not superior to digital symptom monitoring.

There are a growing number of neuroimaging studies motivating joint structural and functional brain connectivity. Brain connectivity of different modalities provides insight into brain functional organization by leveraging complementary information, especially for brain disorders such as schizophrenia. In this paper, we propose a multi-modal independent component analysis (ICA) model that utilizes information from both structural and functional brain connectivity guided by spatial maps to estimate intrinsic connectivity networks (ICNs). Structural connectivity is estimated through whole-brain tractography on diffusion-weighted MRI (dMRI), while functional connectivity is derived from resting-state functional MRI (rs-fMRI). The proposed structural-functional connectivity and spatially constrained ICA (sfCICA) model estimates ICNs at the subject level using a multi-objective optimization framework. We evaluated our model using synthetic and real datasets (including dMRI and rs-fMRI from 149 schizophrenia patients and 162 controls). Multi-modal ICNs revealed enhanced functional coupling between ICNs with higher structural connectivity, improved modularity, and network distinction, particularly in schizophrenia. Statistical analysis of group differences showed more significant differences in the proposed model compared to the unimodal model. In summary, the sfCICA model showed benefits from being jointly informed by structural and functional connectivity. These findings suggest advantages in simultaneously learning effectively and enhancing connectivity estimates using structural connectivity.

Acute COVID-19 infection can be followed by diverse clinical manifestations referred to as Post Acute Sequelae of SARS-CoV2 Infection (PASC). Studies have shown an increased risk of being diagnosed with new-onset psychiatric disease following a diagnosis of acute COVID-19. However, it was unclear whether non-psychiatric PASC-associated manifestations (PASC-AMs) are associated with an increased risk of new-onset psychiatric disease following COVID-19. A retrospective electronic health record (EHR) cohort study of 2,391,006 individuals with acute COVID-19 was performed to evaluate whether non-psychiatric PASC-AMs are associated with new-onset psychiatric disease. Data were obtained from the National COVID Cohort Collaborative (N3C), which has EHR data from 76 clinical organizations. EHR codes were mapped to 151 non-psychiatric PASC-AMs recorded 28-120 days following SARS-CoV-2 diagnosis and before diagnosis of new-onset psychiatric disease. Association of newly diagnosed psychiatric disease with age, sex, race, pre-existing comorbidities, and PASC-AMs in seven categories was assessed by logistic regression. There were significant associations between a diagnosis of any psychiatric disease and five categories of PASC-AMs with odds ratios highest for neurological, cardiovascular, and constitutional PASC-AMs with odds ratios of 1.31, 1.29, and 1.23 respectively. Secondary analysis revealed that the proportions of 50 individual clinical features significantly differed between patients diagnosed with different psychiatric diseases. Our study provides evidence for association between non-psychiatric PASC-AMs and the incidence of newly diagnosed psychiatric disease. Significant associations were found for features related to multiple organ systems. This information could prove useful in understanding risk stratification for new-onset psychiatric disease following COVID-19. Prospective studies are needed to corroborate these findings.

Improved knowledge of factors that influence treatment engagement could help treatment providers and systems better engage patients. The present study used machine learning to explore associations between individual- and neighborhood-level factors, and SUD treatment engagement.

Abnormalities in cortical excitability and plasticity have been considered to underlie the pathophysiology of schizophrenia. Transcranial magnetic stimulation (TMS) combined with electroencephalography (TMS-EEG) can provide a direct evaluation of cortical responses to TMS. Here, we employed TMS-EEG to investigate cortical responses to orbitofrontal cortex (OFC) stimulation in schizophrenia.

Social anxiety disorder is a common psychiatric condition that severely affects quality of life of individuals and is a significant societal burden. Although many risk factors for social anxiety exist, it is currently unknown how social fear sensitivity manifests biologically. Furthermore, since some individuals are resilient and others are susceptible to social fear, it is important to interrogate the mechanisms underpinning individual response to social fear situations. The microbiota-gut-brain axis has been associated with social behaviour, has recently been linked with social anxiety disorder, and may serve as a therapeutic target for modulation. Here, we assess the potential of this axis to be linked with social fear extinction processes in a murine model of social anxiety disorder. To this end, we correlated differential social fear responses with microbiota composition, central gene expression, and immune responses. Our data provide evidence that microbiota variability is strongly correlated with alterations in social fear behaviour. Moreover, we identified altered gene candidates by amygdalar transcriptomics that are linked with social fear sensitivity. These include genes associated with social behaviour (Armcx1, Fam69b, Kcnj9, Maoa, Serinc5, Slc6a17, Spata2, and Syngr1), inflammation and immunity (Cars, Ckmt1, Klf5, Maoa, Map3k12, Pex5, Serinc5, Sidt1, Spata2), and microbe-host interaction (Klf5, Map3k12, Serinc5, Sidt1). Together, these data provide further evidence for a role of the microbiota-gut-brain axis in social fear responses.

Persistent olfactory dysfunction (OD) following loss of smell associated with SARS-CoV-2 infection is a major feature of long COVID. Perspectives on the prevalence of persistent OD predominantly rely on self-reported olfactory function. Few studies have tracked longitudinal rates of recovery using psychophysical assessment among patients presenting for evaluation of persistent OD beyond a window of acute recovery. Data anchored in standardized testing methods are needed to counsel patients who fail to acutely regain their sense of smell. This study aims to quantify the degree of persistent OD in post-COVID-19 patients who experience subjective and psychophysical OD.

Schizophrenia is a severe psychological disorder. The current diagnosis mainly relies on clinical symptoms and lacks laboratory evidence, which makes it very difficult to make an accurate diagnosis especially at an early stage. Plasma protein profiles of schizophrenia patients were obtained and compared with healthy controls using 4D-DIA proteomics technology. Furthermore, 79 DEPs were identified between schizophrenia and healthy controls. GO functional analysis indicated that DEPs were predominantly associated with responses to toxic substances and platelet aggregation, suggesting the presence of metabolic and immune dysregulation in patients with schizophrenia. KEGG pathway enrichment analysis revealed that DEPs were primarily enriched in the chemokine signaling pathway and cytokine receptor interactions. A diagnostic model was ultimately established, comprising three proteins, namely, PFN1, GAPDH and ACTBL2. This model demonstrated an AUC value of 0.972, indicating its effectiveness in accurately identifying schizophrenia. PFN1, GAPDH and ACTBL2 exhibit potential as biomarkers for the early detection of schizophrenia. The findings of our studies provide novel insights into the laboratory-based diagnosis of schizophrenia.

Our society faces a great diversity of opportunities for youth. The 10-year Growing Up Together in Society (GUTS) program has the long-term goal to understand which combination of measures best predict societal trajectories, such as school success, mental health, well-being, and developing a sense of belonging in society. Our leading hypothesis is that self-regulation is key to how adolescents successfully navigate the demands of contemporary society. We aim to test these questions using socio-economic, questionnaire (including experience sampling methods), behavioral, brain (fMRI, sMRI, EEG), hormonal, and genetic measures in four large cohorts including adolescents and young adults. Two cohorts are designed as test and replication cohorts to test the developmental trajectory of self-regulation, including adolescents of different socioeconomic status thereby bridging individual, family, and societal perspectives. The third cohort consists of an entire social network to examine how neural and self-regulatory development influences and is influenced by whom adolescents and young adults choose to interact with. The fourth cohort includes youth with early signs of antisocial and delinquent behavior to understand patterns of societal development in individuals at the extreme ends of self-regulation and societal participation, and examines pathways into and out of delinquency. We will complement the newly collected cohorts with data from existing large-scale population-based and case-control cohorts. The study is embedded in a transdisciplinary approach that engages stakeholders throughout the design stage, with a strong focus on citizen science and youth participation in study design, data collection, and interpretation of results, to ensure optimal translation to youth in society.

This special issue of Behavioral Sciences & the Law presents six articles that focus on various issues related to social media in forensic mental health evaluations. These eclectic articles provide updated information about social media's use and navigating difficult ethical concerns. Ranging from violence risk assessment to disability evaluations, the up-to-date information in this special issue allows the forensic evaluator to be more prepared when they inevitably encounter information from social media. As social media continues to grow, both in terms of overall use and the number of available platforms, forensic clinicians will need to remain cognizant of the ways these data can be appropriately utilized as collateral data.

Social anxiety disorder is a prevalent mental health condition that significantly impairs social interactions, academic performance, and professional functioning in children, adolescents, and youth. This study aimed to investigate the global prevalence of social anxiety disorder across these developmental stages. Six electronic databases (PubMed, Scopus, Web of Science, Embase, ScienceDirect and Google Scholar) were systematically searched for studies related to the prevalence of social anxiety disorder in children, adolescents and youth. Random-effects models were employed for data analysis and Comprehensive Meta-Analysis Version 2.0. Heterogeneity was assessed using the I index. A total of 38 studies were included in the final analysis. The global prevalence of social anxiety disorder was estimated to be 4.7% in children, 8.3% in adolescents, and 17% in youth. These findings suggest a progressive increase in the prevalence of SAD across these developmental stages. Considering the prevalence of social anxiety disorder in this study, policymakers can use the findings of this study to inform and develop effective prevention strategies for individuals and communities most susceptible to this disorder.

Previous observational inquiries have revealed a correlation between depression and infectious maladies. This study seeks to elucidate the causal linkages between depression, specifically Major Depressive Disorder (MDD), and infectious diseases. Nevertheless, the causative nature of the association between MDD and infectious diseases remains elusive. Two-sample Mendelian Randomization (MR) analyses was executed utilizing single nucleotide polymorphisms (SNPs) significantly connected with MDD and infectious diseases as instrumental variables (IVs). A series of sensitivity analyses were subsequently conducted. Genetic variants linked to MDD were employed as instrumental variables sourced from a genome-wide meta-analyses comprising 500,199 individuals. Summary-level data on five infectious diseases, including candidiasis, pneumonia, skin and soft tissue infections (SSTI), upper respiratory tract infections (URTI), and urinary tract infections (UTI), were acquired from the UK Biobank and FinnGen study. Our findings evinced that genetically predicted MDD exhibited a heightened risk of candidiasis (OR = 1.52, 95% CI 1.06-2.17; P = 2.38E-02), pneumonia (OR = 1.14, 95% CI 1.01-1.29; P = 3.16E-02), URTI (OR = 1.23, 95% CI 1.12-1.36; P = 3.71E-05), and UTI (OR = 1.26, 95% CI 1.12-1.42; P = 8.90E-05). Additionally, we identified bidirectional causal relationships between UTI and MDD. The associations between MDD and the risk of URTI and UTI remained consistent in multivariable MR analyses, accounting for genetically predicted smoking and body mass index. In conclusion, this investigation ascertained a causal connection between MDD and the susceptibility to infectious diseases, particularly URTI and UTI.

This study examines the association between healthcare indicators and hospitalization rates in three high-income European countries, namely Estonia, Latvia, and Lithuania, from 2015 to 2020.

Specific phobia is a common anxiety disorder, but the literature on associated brain structure alterations exhibits substantial gaps. The ENIGMA Anxiety Working Group examined brain structure differences between individuals with specific phobias and healthy control subjects as well as between the animal and blood-injection-injury (BII) subtypes of specific phobia. Additionally, the authors investigated associations of brain structure with symptom severity and age (youths vs. adults).

The relative contributions of genetic variation and experience in shaping the morphology of the adolescent brain are not fully understood. Using longitudinal data from 11,665 subjects in the ABCD Study, we fit vertex-wise variance components including family effects, genetic effects, and subject-level effects using a computationally efficient framework. Variance in cortical thickness and surface area is largely attributable to genetic influence, whereas sulcal depth is primarily explained by subject-level effects. Our results identify areas with heterogeneous distributions of heritability estimates that have not been seen in previous work using data from cortical regions. We discuss the biological importance of subject-specific variance and its implications for environmental influences on cortical development and maturation.

 Older adults are at increased risk of psychotic symptoms and even more at risk of medication nonadherence due to various factors specific to their age including memory impairment. This study aimed to examine the availability of long-acting injectable antipsychotics (LAIs) in US mental health (MH) facilities that serve older adults.

Transparency can build trust in the scientific process, but scientific findings can be undermined by poor and obscure data use and reporting practices. The purpose of this work is to report how data from the Adolescent Brain Cognitive Development (ABCD) Study has been used to date, and to provide practical recommendations on how to improve the transparency and reproducibility of findings.

Sleep-wake disturbances frequently present in Veterans with mild traumatic brain injury (mTBI). These TBI-related sleep impairments confer significant burden and commonly exacerbate other functional impairments. Therapies to improve sleep following mTBI are limited and studies in Veterans are even more scarce. In our previous pilot work, morning bright light therapy (MBLT) was found to be a feasible behavioral sleep intervention in Veterans with a history of mTBI; however, this was single-arm, open-label, and non-randomized, and therefore was not intended to establish efficacy. The present study, LION (light vs ion therapy) extends this preliminary work as a fully powered, sham-controlled, participant-masked randomized controlled trial (NCT03968874), implemented as fully remote within the VA (target n=120 complete). Randomization at 2:1 allocation ratio to: 1) active: MBLT (n=80), and 2) sham: deactivated negative ion generator (n=40); each with identical engagement parameters (60-min duration; within 2-hrs of waking; daily over 28-day duration). Participant masking via deception balanced expectancy assumptions across arms. Outcome measures were assessed following a 14-day baseline (pre-intervention), following 28-days of device engagement (post-intervention), and 28-days after the post-intervention assessment (follow-up). Primary outcomes were sleep measures, including continuous wrist-based actigraphy, self-report, and daily sleep dairy entries. Secondary/exploratory outcomes included cognition, mood, quality of life, circadian rhythm via dim light melatonin onset, and biofluid-based biomarkers. Participant drop out occurred in <10% of those enrolled, incomplete/missing data was present in <15% of key outcome variables, and overall fidelity adherence to the intervention was >85%, collectively establishing feasibility and acceptability for MBLT in Veterans with mTBI.

Tau positron emission tomography (PET) is a reliable neuroimaging technique for assessing regional load of tau pathology in the brain, commonly used in Alzheimer's disease (AD) research and clinical trials. However, its routine clinical use is limited by cost and accessibility barriers. Here we explore using machine learning (ML) models to predict clinically useful tau-PET outcomes from low-cost and non-invasive features, e.g., basic clinical variables, plasma biomarkers, and structural magnetic resonance imaging (MRI). Results demonstrated that models including plasma biomarkers yielded highly accurate predictions of tau-PET burden (best model: R-squared=0.66-0.68), with especially high contribution from plasma P-tau217. In contrast, MRI variables stood out as best predictors (best model: R-squared=0.28-0.42) of asymmetric tau load between the two hemispheres (an example of clinically relevant spatial information). The models showed high generalizability to external test cohorts with data collected at multiple sites. Based on these results, we also propose a proof-of-concept two-step classification workflow, demonstrating how the ML models can be translated to a clinical setting. This study reveals current potential in predicting tau-PET information from scalable cost-effective variables, which could improve diagnosis and prognosis of AD.

The objective of the current study was to describe and analyse associations between childhood emotional abuse, severity of depressive symptoms, and analgesic expectations of drinking in individuals with alcohol use disorder (AUD).

Despite uncertainty about the specific molecular mechanisms driving major depressive disorder (MDD), the Wnt signaling pathway stands out as a potentially influential factor in the pathogenesis of MDD. Known for its role in intercellular communication, cell proliferation, and fate, Wnt signaling has been implicated in diverse biological phenomena associated with MDD, spanning neurodevelopmental to neurodegenerative processes. In this systematic review, we summarize the functional differences in protein and gene expression of the Wnt signaling pathway, and targeted genetic association studies, to provide an integrated synthesis of available human data examining Wnt signaling in MDD. Thirty-three studies evaluating protein expression (n = 15), gene expression (n = 9), or genetic associations (n = 9) were included. Only fifteen demonstrated a consistently low overall risk of bias in selection, comparability, and exposure. We found conflicting observations of limited and distinct Wnt signaling components across diverse tissue sources. These data do not demonstrate involvement of Wnt signaling dysregulation in MDD. Given the well-established role of Wnt signaling in antidepressant response, we propose that a more targeted and functional assessment of Wnt signaling is needed to understand its role in depression pathophysiology. Future studies should include more components, assess multiple tissues concurrently, and follow a standardized approach.

Psilocybin-assisted psychotherapy (PAP) is a promising treatment option for depression, with randomized controlled trials (RCTs) providing preliminary support for its safety and efficacy. However, there is a lack of consistency across existing treatment protocols and psychotherapeutic approaches. The objective of this review is to summarize and compare current psychotherapy methods of PAP in treating depression and distress in life-threatening illnesses. We sought to comprehensively summarize published psychotherapy protocols from clinical trials to provide insights for future practices.

Six percent of patients with Leigh syndrome (LS) present with infantile epileptic spasms syndrome (IESS). However, treatment strategies for IESS with LS remain unclear. This retrospective study aimed to evaluate the efficacy and safety of treatment strategies in patients with IESS complicated by LS and Leigh-like syndrome (LLS).

We previously surveyed adults with systemic sclerosis (SSc) regarding COVID-19 vaccination in April-May 2021. The objective of the present study was to update through June-July 2022 and assess self-reported (1) COVID-19 vaccination rates, including boosters; (2) vaccine-related adverse events; (3) peri‑vaccination immunosuppressive medication management; (4) vaccine hesitancy; and (5) prevalence and severity of COVID-19 infections.

This study aimed to identify atypical hubs in the whole-brain networks of patients with schizophrenia (SZ) and examine the effects of antipsychotic medications, using electroencephalography (EEG) data.

Stressors for health care workers (HCWs) during the COVID-19 pandemic have been manifold, with high levels of depression and anxiety alongside gaps in care. Identifying the factors most tied to HCWs' psychological challenges is crucial to addressing HCWs' mental health needs effectively, now and for future large-scale events.

Treating individuals with a mental disorder and a history of criminal behavior (mentally disordered offenders [MDOs]) aims to enable patients to maintain their health and facilitate social rehabilitation while preventing adverse outcomes, such as violent recidivism or suicide. Understanding and responding to their own insight on their criminal behavior is crucial to achieving this goal. This article aims to develop a Japanese version of the Gudjonsson Blame Attribution Inventory-Revised (GBAI-R) and investigate the reliability and validity of the scale for MDOs in Japan.

Understanding the appropriate prescription of psychotropics for hospitalized patients in terms of preventing falls is an important issue. The aim of this study was to assess the associations between the occurrence of falls and the use of various individual psychotropics in hospitalized patients.

During the prodromal stage of Alzheimer's disease (AD), neurodegenerative changes can be identified by measuring volumetric loss in AD-prone brain regions on MRI. Cognitive assessments that are sensitive enough to measure the early brain-behavior manifestations of AD and that correlate with biomarkers of neurodegeneration are needed to identify and monitor individuals at risk for dementia. Weak sensitivity to early cognitive change has been a major limitation of traditional cognitive assessments. In this study, we focused on expanding our previous work by determining whether a digitized cognitive stress test, the Loewenstein-Acevedo Scales for Semantic Interference and Learning, Brief Computerized Version (LASSI-BC) could differentiate between Cognitively Unimpaired (CU) and amnestic Mild Cognitive Impairment (aMCI) groups. A second focus was to correlate LASSI-BC performance to volumetric reductions in AD-prone brain regions. Data was gathered from 111 older adults who were comprehensively evaluated and administered the LASSI-BC. Eighty-seven of these participants (51 CU; 36 aMCI) underwent MR imaging. The volumes of 12 AD-prone brain regions were related to LASSI-BC and other memory tests correcting for False Discovery Rate (FDR). Results indicated that, even after adjusting for initial learning ability, the failure to recover from proactive semantic interference (frPSI) on the LASSI-BC differentiated between CU and aMCI groups. An optimal combination of frPSI and initial learning strength on the LASSI-BC yielded an area under the ROC curve of 0.876 (76.1% sensitivity, 82.7% specificity). Further, frPSI on the LASSI-BC was associated with volumetric reductions in the hippocampus, amygdala, inferior temporal lobes, precuneus, and posterior cingulate.

This study explores the role of transactive memory capability as a mediator in the relationship between social media usage and job performance. Drawing on transactive memory theory, we hypothesized that individuals who use social media more intensively for task-oriented purposes and relationship building are more likely to develop transactive memory capability, which in turn enhances their job performance. A survey was conducted among 816 employees in China from various industries to collect data on their social media usage patterns, transactive memory capability, and job performance. Results from structural equation modeling indicate that social media usage has a positive impact on job performance. Additionally, transactive memory capability mediates the relationship between social media usage and job performance. This study has contribution in literature by demonstrating the beneficial effects of social media usage on the development of transactive memory capability and job performance. It is suggested that social media usage can be used a valuable tool for enhancing performance of employees. Employees should gain an understanding of how social media fosters the development of transactive memory capability to utilize it more effectively. These findings also suggest that the way individuals use social media can influence their ability to access and share knowledge within their social networks, ultimately impacting their job performance.

Coercion is frequently used in mental health practice. Since it overrides some patients' fundamental human rights, adequate use of coercion requires legal and ethical justifications. Having internationally standardised datasets to benchmark and monitor coercion reduction programs is desirable. However, only a few countries have specific, open, publicly accessible registries for this issue.

The current biomarker-supported diagnosis of Alzheimer's disease (AD) is hindered by invasiveness and cost issues. This study aimed to address these challenges by utilizing portable electroencephalography (EEG). We propose a novel, non-invasive, and cost-effective method for identifying AD, using a sample of patients with biomarker-verified AD, to facilitate early and accessible disease screening.

Higher than expected rates of mental health and/or addiction (MHA) concerns have been documented since the onset of the COVID-19 pandemic. A more up-to-date prevalence of MHA outcomes and the factors associated with the occurrence of MHA concerns remains unclear. This study examined the prevalence of MHA outcomes and factors associated with screening positive for symptoms of depression only, anxiety only, and both depression and anxiety two years into the COVID-19 pandemic in Ontario, Canada.

Sleep-related eating disorder (SRED) is a non-REM parasomnia with potentially significant negative effects on general health (dangerous activities during night eating episodes, obesity, or metabolic syndrome, for example). Although the history of SRED encompasses more than six decades, public awareness and even the awareness of the mental health specialists of this disorder is very limited, a phenomenon that hinders the development of research in this field. Therefore, a systematic review based on PRISMA 2020 guidelines explored the available evidence for SRED found in four electronic databases (PubMed, Cochrane Collaboration, Google Scholar, and Clarivate/Web of Science). A number of 94 primary and secondary reports were retrieved, investigating aspects regarding the risk factors, epidemiology, clinical data and differential diagnosis, epidemiology, structured evaluation, and treatment of SRED. Based on the results of these reports, Z-drugs, but also certain benzodiazepines, antidepressants, antipsychotics, and psychostimulants may trigger the onset of SRED. Psychiatric and neurologic disorders have also been associated with SRED, either as risk factors or comorbid conditions. Cerebral glucose metabolism dysfunctions, neurotransmitter dysfunctions, and genetic factors have been invoked as pathogenetic contributors. Structured assessment of SRED is possible, but there is a dearth of instruments dedicated to this purpose. Data on the prevalence and treatment of SRED exist, but good-quality epidemiological studies and clinical trials are still missing. In conclusion, future research is expected to address the shortcomings of SRED exploration by creating the conditions for better quality and larger group clinical research. The need for such investigation is granted by the importance of this pathology and its negative functional consequences.

Equine-assisted services (EAS) has received attention as a potential treatment strategy for post-traumatic stress disorder (PTSD), as existing literature indicates that symptoms may decrease following EAS. Relatively little is known about the mechanisms at play during lessons and if physiological measures are impacted. The objectives of this pilot study were to 1) explore the effects of adaptive horsemanship (AH) lessons on symptoms of PTSD, hormone concentrations, and social motor synchrony; 2) determine if physiological changes occur as veterans interact with horses; and 3) explore if the interaction between veteran and horse changes over the 8-week session.

The risk of suicide and completed suicides among young university students presents critical challenges to mental and public health in Colombia and worldwide. Employing a quantifiable approach to comprehend the factors associated with these challenges can aid in visualizing the path towards anticipating and controlling this phenomenon.

Positive psychology interventions (PPIs) are effective at increasing happiness and decreasing depressive symptoms. PPIs are often administered as self-guided web-based interventions, but not all persons benefit from web-based interventions. Therefore, it is important to identify whether someone is likely to benefit from web-based PPIs, in order to triage persons who may not benefit from other interventions. In the current study, we used machine learning to predict individual response to a web-based PPI, in order to investigate baseline prognostic indicators of likelihood of response ( = 120). Our models demonstrated moderate correlations (happiness: = 0.30 ± 0.09; depressive symptoms: = 0.39 ± 0.06), indicating that baseline features can predict changes in happiness and depressive symptoms at a 6-month follow-up. Thus, machine learning can be used to predict outcome changes from a web-based PPI and has important clinical implications for matching individuals to PPIs based on their individual characteristics.

Although women often experience mental health comorbidities in the perinatal period, the evidence-base for psychological therapy across diagnostic boundaries in the perinatal period remains limited. As there is a need to understand experiences of therapy, irrespective of diagnosis, to inform intervention provision, the aims of this study were to explore women's experiences of psychological therapy for perinatal mental health difficulties and to identify the mechanisms that women attributed to the most significant therapeutic change for themselves and/or the mother-infant relationship.

The lack of cognitive awareness, anosognosia, is a clinical deficit in Alzheimer's disease (AD) dementia. However, an increased awareness of cognitive function, hypernosognosia, may serve as a marker in the preclinical stage. Subjective cognitive decline (SCD) might correspond to the initial symptom in the dynamic trajectory of awareness, but SCD might be absent along with low awareness of actual cognitive performance in the preclinical stage. We hypothesized that distinct meta-cognitive profiles, both hypernosognosia and anosognosia, might be identified in preclinical-AD. This research evaluated the association between cerebrospinal fluid (CSF) AD biomarkers and the awareness of episodic memory, further exploring dyadic (participant-partner) SCD reports, in the preclinical Alzheimer's continuum.

Although greater lifetime stressor exposure has been associated with physical and mental health issues in the general population, relatively little is known about how lifetime stressors impact the physical and mental health of elite athletes or the factors moderating this association. Given that many elite athletes show signs of perfectionism, and that this trait has been linked with ill-health, it is possible that perfectionism may moderate the lifetime stressor-health relationship. To test this possibility, we examined how cumulative lifetime stressor exposure was associated with general mental and physical health complaints in elite athletes, and the extent to which these associations were moderated by perfectionism. Participants were 110 elite athletes (64 female; = 29.98 years, = 10.54) who completed assessments of lifetime stressor exposure, physical health, psychological distress, and perfectionism. As hypothesised, hierarchical regression analyses revealed that experiencing more severe lifetime stressors was related to poorer physical and mental health. Furthermore, self-oriented perfectionism moderated the association between lifetime stressor count and severity and physical health, but not mental health. Overall, these data demonstrate stressor-specific effects among elite athletes and highlight the potential importance of assessing lifetime stressor exposure and perfectionistic tendencies in order to improve athlete health and well-being.

Researchers are rapidly developing and deploying highly portable MRI technology to conduct field-based research. The new technology will widen access to include new investigators in remote and unconventional settings and will facilitate greater inclusion of rural, economically disadvantaged, and historically underrepresented populations. To address the ethical, legal, and societal issues raised by highly accessible and portable MRI, an interdisciplinary Working Group (WG) engaged in a multi-year structured process of analysis and consensus building, informed by empirical research on the perspectives of experts and the general public. This article presents the WG's consensus recommendations. These recommendations address technology quality control, design and oversight of research, including safety of research participants and others in the scanning environment, engagement of diverse participants, therapeutic misconception, use of artificial intelligence algorithms to acquire and analyze MRI data, data privacy and security, return of results and managing incidental findings, and research participant data access and control.

The concept of caring stress and its specific management has received less attention than other dimensions of stress in nurses. Therefore, to clarify the concept of caring stress, a scoping review study was designed. This scoping review aimed to investigate the concept of caring stress among clinical nurses and examine the strategies used for its management.

Angelman syndrome (AS) is a neurogenetic disorder caused by mutations or deletions in the maternally-inherited allele, leading to a loss of UBE3A protein expression in neurons. The paternally-inherited allele is epigenetically silenced in neurons during development by a noncoding transcript (). The absence of neuronal UBE3A results in severe neurological symptoms, including speech and language impairments, intellectual disability, and seizures. While no cure exists, therapies aiming to restore UBE3A function-either by gene addition or by targeting -are under development. Progress in developing these treatments relies heavily on inferences drawn from mouse studies about the function of UBE3A in the human brain. To aid translational efforts and to gain an understanding of UBE3A and biology with greater relevance to human neurodevelopmental contexts, we investigated UBE3A and expression in the developing brain of the rhesus macaque, a species that exhibits complex social behaviors, resembling aspects of human behavior to a greater degree than mice. Combining immunohistochemistry and hybridization, we mapped UBE3A and regional and cellular expression in normal prenatal, neonatal, and adolescent rhesus macaque brains. We show that key hallmarks of UBE3A biology, well-known in rodents, are also present in macaques, and suggest paternal silencing in neurons-but not glial cells-in the macaque brain, with onset between gestational day 48 and 100. These findings support proposals that early-life, perhaps even prenatal, intervention is optimal for overcoming the maternal allele loss of linked to AS.

Depression is a severe and treatable mental illness that significantly affects individuals' daily activities. Obstetric care providers are the most vulnerable group for depression because they work in an emergency to save two lives at a time, share the stress of women during labor, and are at great risk for contamination.