Analytics and Psychiatry

The Coronavirus Disease 2019 (COVID-19) pandemic significantly impacted the older adult population globally. This study aimed to investigate cognitive function and its relationship with inflammation in older COVID-19 survivors over a three-month follow-up to address concerns about cognitive impairment and its risk factors.

Holistic and analytic thinking are two distinct modes of thinking used to interpret the world with relative preferences varying across cultures. While most research on these thinking styles has focused on behavioral and cognitive aspects, a few studies have utilized functional magnetic resonance imaging (fMRI) to explore the correlations between brain metrics and self-reported scale scores. Other fMRI studies used single holistic and analytic thinking tasks. As a single task may involve processing in spurious low-level regions, we used two different holistic and analytic thinking tasks, namely the frame-line task and the triad task, to seek convergent brain regions to distinguish holistic and analytic thinking using multivariate pattern analysis (MVPA). Results showed that brain regions fundamental to distinguish holistic and analytic thinking include the bilateral frontal lobes, bilateral parietal lobes, bilateral precentral and postcentral gyrus, bilateral supplementary motor areas, bilateral fusiform, bilateral insula, bilateral angular gyrus, left cuneus, and precuneus, left olfactory cortex, cingulate gyrus, right caudate and putamen. Our study maps brain regions that distinguish between holistic and analytic thinking and provides a new approach to explore the neural representation of cultural constructs. We provide initial evidence connecting culture-related brain regions with language function to explain the origins of cultural differences in cognitive styles.

Kratom plant, products derived from the plant, and plant phytochemicals are of great interest among researchers, clinicians, and consumers. However, there is a paucity of rigorously collected scientific data on their risk/safety profile and public health impact. This scoping review discusses original research articles published between 2022 and 2023. It focuses on identifying publication gaps on topics related to epidemiology, public health, and risk/safety profiles comparing evidence collected by researchers from Southeast Asia and the West.

Alzheimer's disease (AD) is a neurodegenerative condition for which there is currently no available medication that can stop its progression. Previous studies suggest that mild cognitive impairment (MCI) is a phase that precedes the disease. Therefore, a better understanding of the molecular mechanisms behind MCI conversion to AD is needed.

The most common psychological impact experienced by patients with burn injuries is depression. Several significant risk factors influence depression, including sociodemographic factors (gender, employment status, socioeconomic status, and marital status) and burn characteristics (burn depth, burn area, and total burn surface area). Neutrophil-to-lymphocyte ratio (NLR) was discovered as a new biomarker for depression detection. The purpose of this study was to investigate the correlation of sociodemographic factors, burn characteristics, and NLR with the severity of depression in patients with burn injuries.

There is limited information on the association between participants' clinical status or trajectories and missing data in electronic monitoring studies of bipolar disorder (BD). We collected self-ratings scales and sensor data in 145 adults with BD. Using a new metric, Missing Data Ratio (MDR), we assessed missing self-rating data and sensor data monitoring activity and sleep. Missing data were lowest for participants in the midst of a depressive episode, intermediate for participants with subsyndromal symptoms, and highest for participants who were euthymic. Over a mean ± SD follow-up of 246 ± 181 days, missing data remained unchanged for participants whose clinical status did not change throughout the study (i.e., those who entered the study in a depressive episode and did not improve, or those who entered the study euthymic and remained euthymic). Conversely, when participants' clinical status changed during the study (e.g., those who entered the study euthymic and experienced the occurrence of a depressive episode), missing data for self-rating scales increased, but not for sensor data. Overall missing data were associated with participants' clinical status and its changes, suggesting that these are not missing at random.

This study focuses on the purification and detection of glufosinate (GLUF) and its metabolites N-acetyl GLUF and MPP in plasma samples. A Dikma Polyamino HILIC column was used for the effective retention and separation of GLUF and its metabolites, and the innovative addition of a low concentration of ammonium fluoride solution to the mobile phase effectively improved the detection sensitivity of the target analytes. Monodisperse core-shell weak cation exchange (WCX)/C bifunctional magnetic polymer composites (FeO@WCX/C) were prepared in a controllable manner, and their morphology and composition were fully characterized. The FeO@WCX/C microspheres were used as a magnetic solid-phase extraction (MSPE) adsorbent for the sample purification and detection of GLUF and its metabolites in plasma samples combined with liquid chromatography-tandem mass spectrometry (LC-MS/MS). The purification conditions of FeO@WCX/C microspheres for GLUF and its metabolites in spiked plasma samples were optimized to achieve the best MSPE efficiency. The purification mechanisms of the target analytes in plasma samples include electrostatic attraction and hydrophobic interactions. Furthermore, the effect of the molar ratio of the two functional monomers 4-VBA and 1-octadecene in the adsorbent was optimized and it shows that the bifunctional components WCX/C have a synergistic effect on the determination of GLUF and its metabolites in plasma samples. In addition, the present study compared the purification performance of the FeO@WCX/C microsphere-based MSPE method with that of the commercial Oasis WCX SPE method, and the results showed that the FeO@WCX/C microsphere-based MSPE method established in this work had a stronger ability to remove matrix interferences. Under optimal purification conditions, the recoveries of GLUF and its metabolites in plasma were 87.6-111 % with relative standard deviations (RSDs) ranging from 0.2 % to 4.8 %. The limits of detection (LODs, S/N≥3) and limits of quantification (LOQs, S/N≥10) were 0.10-0.18 μg/L and 0.30-0.54 μg/L, respectively. The MSPE-LC-MS/MS method developed in this study is fast, simple, accurate and sensitive and can be used to confirm GLUF intoxication based not only on the detection of the GLUF prototype but also on the detection of its two metabolites.

Polygenic Risk Scores (PRS) based on results from genome-wide association studies offer the prospect of risk stratification for many common and complex diseases. We developed a PRS for alcohol-associated cirrhosis by comparing single-nucleotide polymorphisms among patients with alcohol-associated cirrhosis (ALC) versus drinkers who did not have evidence of liver fibrosis/cirrhosis.

Long noncoding RNAs (lncRNAs) regulate the pathogenesis of Alzheimer's disease (AD).

Hyperserotonemia is one of the most studied endophenotypes in autism spectrum disorder (ASD), but there are still no unequivocal results about its causes or biological and behavioral outcomes. This systematic review summarizes the studies investigating the relationship between blood serotonin (5-HT) levels and ASD, comparing diagnostic tools, analytical methods, and clinical outcomes. A literature search on peripheral 5-HT levels and ASD was conducted. In total, 1104 publications were screened, of which 113 entered the present systematic review. Of these, 59 articles reported hyperserotonemia in subjects with ASD, and 26 presented correlations between 5-HT levels and ASD-core clinical outcomes. The 5-HT levels are increased in about half, and correlations between hyperserotonemia and clinical outcomes are detected in a quarter of the studies. The present research highlights a large amount of heterogeneity in this field, ranging from the characterization of ASD and control groups to diagnostic and clinical assessments, from blood sampling procedures to analytical methods, allowing us to delineate critical topics for future studies.

Brain organoids hold great potential for modeling human brain development and pathogenesis. They recapitulate certain aspects of the transcriptional trajectory, cellular diversity, tissue architecture and functions of the developing brain. In this review, we explore the engineering strategies to control the molecular-, cellular- and tissue-level inputs to achieve high-fidelity brain organoids. We review the application of brain organoids in neural disorder modeling and emerging bioengineering methods to improve data collection and feature extraction at multiscale. The integration of multiscale engineering strategies and analytical methods has significant potential to advance insight into neurological disorders and accelerate drug development.

Recent genome-wide association studies (GWAS) have reported a genetic association with Alzheimer's disease (AD) at the TNIP1/GPX3 locus, but the mechanism is unclear.

Adverse childhood experiences (ACEs) significantly impact lifelong health and well-being. Despite extensive research, a comprehensive understanding of ACEs' multifaceted impacts continues to be challenging to achieve. This study synthesizes meta-analytic evidence to provide a comprehensive view of ACEs' effects, addressing various approaches to conceptualizing ACEs and their diverse outcomes. Employing an umbrella synthesis methodology, this review integrated findings from 99 meta-analyses involving 592 effect sizes. We examined ACEs through specificity, lumping, dimensional, and child maltreatment-centric approaches, assessing their impact across six domains: biological system dysregulation, neuropsychological impairments, physical health complications, mental health conditions, social and behavioral challenges, and criminal justice involvement. The findings reveal a small to moderate overall effect size of ACEs across outcome domains. Specific ACE approaches exhibited varying impact levels, with notable differences in effects on mental health, social/behavioral issues, and criminal justice involvement. When ACEs were aggregated without distinguishing between different types, but with consideration of their cumulative effects, adverse outcomes were significantly exacerbated. The child maltreatment-centric approach consistently demonstrated substantial effects across all evaluated domains. This review underscores the heterogeneity in ACEs' impacts, influenced by the type of ACE and specific outcomes considered. It highlights the necessity for comprehensive approaches to understanding, preventing, and mitigating the effects of ACEs. These insights are vital for developing targeted interventions and informing policy-making, emphasizing the complexity and varied nature of ACEs' influence on individual development and societal well-being.

The prevalence of pediatric constipation ranges from 0.7 to 29.6% across different countries. Functional constipation accounts for 95% of pediatric constipation, and the efficacy of pharmacotherapy is limited, with a success rate of 60%. Several randomized controlled trials (RCTs) have shown the benefits of probiotic supplements in treating this condition. However, the reported strains of probiotics varied among the RCTs. We aimed to compare the efficacy and acceptability of different probiotic supplements for pediatric functional constipation. The current frequentist model-based network meta-analysis (NMA) included RCTs of probiotic supplements for functional constipation in children. The primary outcome was changes in bowel movement or stool frequency; acceptability outcome was all-cause discontinuation. Nine RCTs were included (N = 710; mean age = 5.5 years; 49.4% girls). Most probiotic products, used either alone or combined with laxatives, were associated with significantly better improvement in bowel movement or stool frequency than placebo/control. Protexin plus laxatives (standardized mean difference (SMD) = 1.87, 95% confidence interval (95% CI) = 0.85 to 2.90) were associated with the greatest improvement in bowel movement or stool frequency among all the investigated probiotic products. For the single probiotic interventions, only Lactobacillus casei rhamnosus Lcr35 was associated with significant efficacy compared to placebo/control treatments (SMD = 1.37, 95% CI: 0.32 to 2.43). All the investigated probiotic products had fecal incontinence and patient drop-out rates similar to those of placebo/control treatments.  Conclusion: The results of our NMA support the application of an advanced combination of probiotics and laxatives for pediatric functional constipation if there is no concurrent contraindication.  Registration: PROSPERO (CRD42022298724). What is Known: • Despite of the high prevalence of pediatric constipation, which ranges from 0.7% to 29.6%, the efficacy of pharmacotherapy is limited, with a success rate of 60%. Several randomized controlled trials (RCTs) have shown the benefits of probiotic supplements in treating this condition. However, the reported strains of probiotics varied among the RCTs. The widely heterogeneous strains of probiotics let the traditional meta-analysis, which pooled all different strains into one group, be nonsense and insignificant. What is New: • By conducting a comprehensive network meta-analysis, we aimed to compare the efficacy and acceptability of different strains of probiotic supplements for pediatric functional constipation. Network meta-analysis of nine randomized controlled trials revealed that the most probiotic products, used either alone or combined with laxatives, were associated with significantly better improvement in bowel movement or stool frequency than placebo/control. Protexin plus laxatives was associated with the greatest improvement in bowel movement or stool frequency among all the investigated probiotic products. For the single probiotic interventions, only Lactobacillus casei rhamnosus Lcr35 was associated with significant efficacy compared to placebo/control treatments. All the investigated probiotic products had fecal incontinence and patient drop-out rates similar to those of placebo/control treatments.

Metabolites from feces provide important insights into the functionality of the gut microbiome. As immediate freezing is not always feasible in gut microbiome studies, there is a need for sampling protocols that provide the stability of the fecal metabolome and microbiome at room temperature (RT). Here, we investigated the stability of various metabolites and the microbiome (16S rRNA) in feces collected in 95% ethanol (EtOH) and commercially available sample collection kits with specific preservatives OMNImet•GUT/OMNIgene•GUT. To simulate field-collection scenarios, the samples were stored at different temperatures at varying durations (24 h + 4 °C, 24 h RT, 36 h RT, 48 h RT, and 7 days RT) and compared to aliquots immediately frozen at -80 °C. We applied several targeted and untargeted metabolomics platforms to measure lipids, polar metabolites, endocannabinoids, short-chain fatty acids (SCFAs), and bile acids (BAs). We found that SCFAs in the nonstabilized samples increased over time, while a stable profile was recorded in sample aliquots stored in 95% EtOH and OMNImet•GUT. When comparing the metabolite levels between aliquots stored at room temperature and at +4 °C, we detected several changes in microbial metabolites, including multiple BAs and SCFAs. Taken together, we found that storing samples at RT and stabilizing them in 95% EtOH yielded metabolomic results comparable to those from flash freezing. We also found that the overall composition of the microbiome did not vary significantly between different storage types. However, notable differences were observed in the α diversity. Altogether, the stability of the metabolome and microbiome in 95% EtOH provided results similar to those of the validated commercial collection kits OMNImet•GUT and OMNIgene•GUT, respectively.

Many psychiatric disorders exhibit sex differences, but the underlying mechanisms remain poorly understood. We analyzed transcriptomics data from 2160 postmortem adult prefrontal cortex brain samples from the PsychENCODE consortium in a sex-stratified study design. We compared transcriptomics data of postmortem brain samples from patients with schizophrenia (SCZ), bipolar disorder (BD), and autism spectrum disorder (ASD) with transcriptomics data of postmortem control brains from individuals without a known history of psychiatric disease. We found that brain samples from females with SCZ, BD, and ASD showed a higher burden of transcriptomic dysfunction than did brain samples from males with these disorders. This observation was supported by the larger number of differentially expressed genes (DEGs) and a greater magnitude of gene expression changes observed in female versus male brain specimens. In addition, female patient brain samples showed greater overall connectivity dysfunction, defined by a higher proportion of gene coexpression modules with connectivity changes and higher connectivity burden, indicating a greater degree of gene coexpression variability. We identified several gene coexpression modules enriched in sex-biased DEGs and identified genes from a genome-wide association study that were involved in immune and synaptic functions across different brain cell types. We found a number of genes as hubs within these modules, including those encoding , , and . Our results suggest that in the context of psychiatric diseases, males and females exhibit different degrees of transcriptomic dysfunction and implicate immune and synaptic-related pathways in these sex differences.

Understanding how development influences medication and placebo responses in anxiety disorders could inform treatment decisions, including age-specific first- versus second-line psychopharmacological interventions. To meta-analytically compare the trajectory of selective serotonin reuptake inhibitors (SSRIs), serotonin-norepinephrine reuptake inhibitors (SNRIs), and placebo response in youth and adults with anxiety disorders. Weekly symptom severity data were extracted from prospective, randomized, parallel-group, placebo-controlled trials of SSRIs and SNRIs in children, adolescents, and adults with anxiety disorders (generalized, separation, and social anxiety disorders as well as panic disorder). Treatment response was modeled for the standardized change in continuous measures of anxiety using a Bayesian hierarchical model. Change in symptom severity was evaluated as a function of time, and analyses were conducted to determine the sensitivity of these results across sample heterogeneity and alternative functional forms. Data were included from 11 trials of youth (SSRI, κ = 7; SNRI, κ = 4) and 71 studies of adults (SSRI, κ = 46; SNRI, κ = 25). In total, 1067 youth participated in SSRI trials and 1024 in SNRI trials. In total, 10,826 adults participated in SSRI trials (placebo, = 5367; SSRI = 5,459) and 6232 in SNRI trials (placebo, = 3,128; SNRI = 3,094). A logarithmic model best described the response. Placebo response was similar in youth and adults (mean difference = -1.98 ± 6.21, 95% credible interval [CrI]: -10.2 to 14.2, = 0.750), and statistically significant improvement from baseline emerged by week 2 in both adults (mean difference: -18.34 + 1.017, 95% CrI: -20.3 to 16.3, < 0.001) and youth (mean difference: -23.74 + 3.736, 95% CrI: -31.1 to -16.4, < 0.001). SSRIs produced similar improvements for youth and adults ( = 0.129), but SNRIs produced slower improvement in youth than adults ( = 0.018). Antidepressant-related improvement occurs early in youth and adults with anxiety disorders. SSRI response is similar in adults and youth; however, SNRIs produce greater responses in adults than youth, potentially representing a developmental effect.

Chronic kidney disease (CKD) is common, costly, and life-limiting, requiring dialysis and transplantation in advanced stages. Although effective guideline-based therapy exists, the asymptomatic nature of CKD together with low health literacy, adverse social determinants of health, unmet behavioral health needs, and primary care providers' (PCP) limited understanding of CKD result in defects in screening and diagnosis. Care is fragmented between PCPs and specialty nephrologists, with limited time, expertise, and resources to address systemic gaps. In this article, the authors define how they classified defects in care and report the current numbers of patients exposed to these defects, both nationally and in their health system Accountable Care Organization. They describe use of the health system's three-pillar leadership model (believing, belonging, and building) to empower providers to transform CKD care. Believing entailed engaging individuals to believe defects in CKD care could be eliminated and were a collective responsibility. Belonging fostered the creation of learning communities that broke down silos and encouraged open communication and collaboration between PCPs and nephrologists. Building involved constructing a fractal management infrastructure with transparent reporting and shared accountability, which would enable success in innovation and transformation. The result is proactive and relational CKD care organized around the patient's needs in University Hospitals Systems of Excellence. Systems of excellence combine multiple domains of expertise to promote best practice guidelines and integrate care throughout the system. The authors further describe a preliminary pilot of the CKD System of Excellence in primary care.

Exploring the relationship between oxygen supply and myelin damage would benefit from a simultaneous quantification of myelin and cerebral blood flow (CBF) in the brain's white matter (WM). To validate an analytical method for quantifying both CBF and myelin content in the WM using dynamic [C]PiB positron emission tomography (PET).

Substantial data support a heritable basis for supraventricular tachycardias, but the genetic determinants and molecular mechanisms of these arrhythmias are poorly understood. We sought to identify genetic loci associated with atrioventricular nodal reentrant tachycardia (AVNRT) and atrioventricular accessory pathways or atrioventricular reciprocating tachycardia (AVAPs/AVRT).

The impacts of prenatal maternal affective symptoms on the placental structure are not well-established. Employing Geographic Information System (GIS) spatial autocorrelation, Moran's I, can help characterize placental thickness uniformity/variability and evaluate the impacts of maternal distress on placental topography.

Excitation/inhibition (E/I) balance plays important roles in mental disorders. Bioactive phospholipids like lysophosphatidic acid (LPA) are synthesized by the enzyme autotaxin (ATX) at cortical synapses and modulate glutamatergic transmission, and eventually alter E/I balance of cortical networks. Here, we analyzed functional consequences of altered E/I balance in 25 human subjects induced by genetic disruption of the synaptic lipid signaling modifier PRG-1, which were compared to 25 age and sex matched control subjects. Furthermore, we tested therapeutic options targeting ATX in a related mouse line. Using EEG combined with TMS in an instructed fear paradigm, neuropsychological analysis and an fMRI based episodic memory task, we found intermediate phenotypes of mental disorders in human carriers of a loss-of-function single nucleotide polymorphism of PRG-1 (PRG-1). Prg-1 animals phenocopied human carriers showing increased anxiety, a depressive phenotype and lower stress resilience. Network analysis revealed that coherence and phase-amplitude coupling were altered by PRG-1 deficiency in memory related circuits in humans and mice alike. Brain oscillation phenotypes were restored by inhibtion of ATX in Prg-1 deficient mice indicating an interventional potential for mental disorders.

Understanding the sequential progression of cognitive impairments in Parkinson's disease (PD) is crucial for elucidating neuropathological underpinnings, refining the assessment of PD-related cognitive decline stages and enhancing early identification for targeted interventions. The first aim of this study was to use an innovative event-based modeling (EBM) analytic approach to estimate the sequence of cognitive declines in PD. The second aim was to validate the EBM by examining associations with EBM-derived individual-specific estimates of cognitive decline severity and performance on independent cognitive screening measures.

Transcriptome-wide association studies (TWAS) have provided valuable insight in identifying genes that may impact cigarette smoking. Most of previous studies, however, mainly focused on European ancestry. Limited TWAS studies have been conducted across multiple ancestries to explore genes that may impact smoking behaviors. In this study, we used cis-eQTL data of cerebral cortex from multiple ancestries in MetaBrain, including European, East Asian, and African samples, as reference panels to perform multi-ancestry TWAS analyses on ancestry-matched GWASs of four smoking behaviors including smoking initiation, smoking cessation, age of smoking initiation, and number of cigarettes per day in GWAS & Sequencing Consortium of Alcohol and Nicotine use (GSCAN). Multiple-ancestry fine-mapping approach was conducted to identify credible gene sets associated with these four traits. Enrichment and module network analyses were further performed to explore the potential roles of these identified gene sets. A total of 719 unique genes were identified to be associated with at least one of the four smoking traits across ancestries. Among those, 249 genes were further prioritized as putative causal genes in multiple ancestry-based fine-mapping approach. Several well-known smoking-related genes, including PSMA4, IREB2, and CHRNA3, showed high confidence across ancestries. Some novel genes, e.g., TSPAN3 and ANK2, were also identified in the credible sets. The enrichment analysis identified a series of critical pathways related to smoking such as synaptic transmission and glutamate receptor activity. Leveraging the power of the latest multi-ancestry GWAS and eQTL data sources, this study revealed hundreds of genes and relevant biological processes related to smoking behaviors. These findings provide new insights for future functional studies on smoking behaviors.

The negative effects of the COVID-19 pandemic on youth mental health have been significant. The impact of the pandemic on eating disorders has been particularly notable, given the numerous risk factors exacerbated during the pandemic, such as increased social isolation and body image concerns associated with amplified virtual and social media exposure. Although the rise of eating disorder presentations have been documented by increased pediatric hospital admissions at an earlier ages of onset, there has, until this time, not been a meta-analytical approach to understanding the full scope of this impact on health care use. In our ever-burdened pediatric mental health care systems, it is crucial for the field to understand how health care use for eating disorders has been affected. As such, we read with keen interest the article by Madigan et al. This meta-analysis fills a gap in the field, analyzing the health care visits of close to 150,000 children and adolescents across more than 300 sites. This study highlights an important theme that has been observed across our mental health systems: there has been a significant increase in severe eating disorder symptom expression since the start of the pandemic. This article provides the empirical evidence to support what has been anecdotally and qualitatively observed across sites-namely, an increased use of higher levels of care, such as emergency rooms and inpatient units, in addition to outpatient care. This increase in service use for eating disorders has been particularly sharp among girls, adolescents, and those presenting with restricting presentations such as anorexia nervosa..

The potential efficacy of psychosocial interventions in the treatment of borderline personality disorder (BPD) is impacted by significant treatment non-completion (TNC), with meta-analytic studies reporting rates of attrition of between 25% and 28%. Increasing patient retention could facilitate outcomes and improve resource utilization, given limited healthcare services. A systematic search of PsycINFO, CINAHL, EMBASE, CENTRAL, and Web of Science Core Collection identified 33 articles that met the criteria for inclusion. Although substantial heterogeneity in terms of methodology and quality of analysis limited conclusions that could be drawn in the narrative review, a few consistent patterns of findings were elucidated, such as Cluster B personality disorder comorbidities and lower therapeutic alliance were associated with TNC. Interestingly, the severity of BPD symptoms was not a predictor of TNC. These findings are discussed in terms of their potential theoretical contribution to TNC. Clinically, there may be value in applying mindfulness and motivational interviewing strategies early on in treatment for individuals who present uncertainty about engaging in treatment. Further research to develop this empirical landscape includes focusing on high-powered replications, examining burgeoning lines of research, and investigating dynamic predictors of TNC.

Cognitive control (CC) involves a top-down mechanism to flexibly respond to complex stimuli and is impaired in schizophrenia.

Ecological Momentary Assessment (EMA) holds promise for providing insights into daily life experiences when studying mental health phenomena. However, commonly used mixed-effects linear statistical models do not fully utilize the richness of the ultidimensional time-varying data that EMA yields. Recurrent Neural Networks (RNNs) provide an alternative data analytic method to leverage more information and potentially improve prediction, particularly for non-normally distributed outcomes.

Inflammatory bowel disease (IBD) affects over 3 million Americans and has a relapsing and remitting course with up to 30% of patients experiencing exacerbations each year despite the availability of immune targeted therapies. An urgent need exists to develop adjunctive treatment approaches to better manage IBD symptoms and disease activity. Circadian disruption is associated with increased disease activity and may be an important modifiable treatment target for IBD. Morning light treatment, which advances and stabilizes circadian timing, may have the potential to improve IBD symptoms and disease activity, but no studies have explored these potential therapeutic benefits in IBD. Therefore, in this study, we aim to test the effectiveness of morning light treatment for patients with IBD.

Many patients with opioid use disorder (OUD) discontinue treatment prematurely, increasing their risk of opioid-related overdose and death. While patient-centered care is considered the gold standard in treating chronic illness, it may be practiced less frequently in the context of OUD care. Patient-provider communication can influence patients' care experiences, potentially having an impact on treatment retention and care decision-making.

Challenging behaviors like aggression and self-injury are dangerous for clients and staff in residential care. These behaviors are not well understood and therefore often labeled as "complex". Yet it remains vague what this supposed complexity entails at the individual level. This case-study used a three-step mixed-methods analytical strategy, inspired by complex systems theory. First, we construed a holistic summary of relevant factors in her daily life. Second, we described her challenging behavioral trajectory by identifying stable phases. Third, instability and extraordinary events in her environment were evaluated as potential change-inducing mechanisms between different phases.

In neuroscience, understanding how single-neuron firing contributes to distributed neural ensembles is crucial. Traditional methods of analysis have been limited to descriptions of whole population activity, or, when analyzing individual neurons, criteria for response categorization varied significantly across experiments. Current methods lack scalability for large datasets, fail to capture temporal changes and rely on parametric assumptions. There's a need for a robust, scalable, and non-parametric functional clustering approach to capture interpretable dynamics. To address this challenge, we developed a model-based, statistical framework for unsupervised clustering of multiple time series datasets that exhibit nonlinear dynamics into an -unknown number of parameterized ensembles called Functional Encoding Units (FEUs). FEU outperforms existing techniques in accuracy and benchmark scores. Here, we apply this FEU formalism to single-unit recordings collected during social behaviors in rodents and primates and demonstrate its hypothesis-generating and testing capacities. This novel pipeline serves as an analytic bridge, translating neural ensemble codes across model systems.

Psychiatric disorders often require pharmacological interventions to alleviate symptoms and improve quality of life. However, achieving an optimal therapeutic outcome is challenging due to several factors, including variability in the individual response, inter-individual differences in drug metabolism, and drug interactions in polytherapy. Therapeutic drug monitoring (TDM), by measuring drug concentrations in biological samples, represents a valuable tool to address these challenges, by tailoring medication regimens to each individual. This review analyzes the current landscape of TDM in psychiatric practice, highlighting its significance in optimizing drug dosages, minimizing adverse effects, and improving therapeutic efficacy. The metabolism of psychiatric medications (i.e., mood stabilizers, antipsychotics, antidepressants) often exhibits significant inter-patient variability. TDM can help address this variability by enhancing treatment personalization, facilitating early suboptimal- or toxic-level detection, and allowing for timely interventions to prevent treatment failure or adverse effects. Furthermore, this review briefly discusses technological advancements and analytical methods supporting the implementation of TDM in psychiatric settings. These innovations enable quick and cost-effective drug concentration measurements, fostering the widespread adoption of TDM as a routine practice in psychiatric care. In conclusion, the integration of TDM in psychiatry can improve treatment outcomes by individualizing medication regimens within the so-called precision medicine.

While our understanding of the nanoscale architecture of anterograde synaptic transmission is rapidly expanding, the qualitative and quantitative molecular principles underlying distinct mechanisms of retrograde synaptic communication remain elusive. We show that a particular form of tonic cannabinoid signaling is essential for setting target cell-dependent synaptic variability. It does not require the activity of the two major endocannabinoid-producing enzymes. Instead, by developing a workflow for physiological, anatomical, and molecular measurements at the same unitary synapse, we demonstrate that the nanoscale stoichiometric ratio of type 1 cannabinoid receptors (CBRs) to the release machinery is sufficient to predict synapse-specific release probability. Accordingly, selective decrease of extrasynaptic CBRs does not affect synaptic transmission, whereas in vivo exposure to the phytocannabinoid Δ-tetrahydrocannabinol disrupts the intrasynaptic nanoscale stoichiometry and reduces synaptic variability. These findings imply that synapses leverage the nanoscale stoichiometry of presynaptic receptor coupling to the release machinery to establish synaptic strength in a target cell-dependent manner.

Recommendations state that multidisciplinary team expertise should be utilised for more accurate survival predictions. How the multidisciplinary team discusses prognoses during meetings and how they reference time, is yet to be explored.

Glioblastomas (GBM) are the most common primary malignant brain tumors, comprising 2% of all cancers in adults. Their location and cellular and molecular heterogeneity, along with their highly infiltrative nature, make their treatment challenging. Recently, our research group reported promising results from a prospective phase II clinical trial involving allogeneic vaccination with dendritic cells (DCs). To date, six out of the thirty-seven reported cases remain alive without tumor recurrence. In this study, we focused on the characterization of infiltrating immune cells observed at the time of surgical resection. An analytical model employing a neural network-based predictive algorithm was used to ascertain the potential prognostic implications of immunological variables on patients' overall survival. Counterintuitively, immune phenotyping of tumor-associated macrophages (TAMs) has revealed the extracellular marker PD-L1 to be a positive predictor of overall survival. In contrast, the elevated expression of CD86 within this cellular subset emerged as a negative prognostic indicator. Fundamentally, the neural network algorithm outlined here allows a prediction of the responsiveness of patients undergoing dendritic cell vaccination in terms of overall survival based on clinical parameters and the profile of infiltrated TAMs observed at the time of tumor excision.

Sleep disturbances are an important symptom dimension of post-traumatic-stress-disorder (PTSD). There is no meta-analytic evidence examining the effects of all types of pharmacotherapy on sleep outcomes among patients with PTSD.

The reliability of plasma biomarkers of Alzheimer's disease (AD) can be compromised by protease-induced degradation. This can limit the feasibility of conducting plasma biomarker studies in environments that lack the capacity for immediate processing and appropriate storage of blood samples. We hypothesized that blood collection tube supplementation with protease inhibitors can improve the stability of plasma biomarkers at room temperatures (RT). In this study, we conducted a comparative analysis of blood biomarker stability in traditional ethylenediaminetetraacetic acid (EDTA) tubes versus BD™ P100 collection tubes, the latter being coated with a protease inhibitor cocktail. The stability of six plasma AD biomarkers was evaluated over time under RT conditions. We evaluated three experimental approaches. In Approach 1, pooled plasma samples underwent storage at RT for up to 96 h. In Approach 2, plasma samples isolated upfront from whole blood collected into EDTA or P100 tubes were stored at RT for 0 h or 24 h before biomarker measurements. In Approach 3, whole blood samples were collected into paired EDTA and P100 tubes, followed by storage at RT for 0 h or 24 h before isolating the plasma for analyses. Biomarkers were measured with Single Molecule Array (Simoa) and immunoprecipitation-mass spectrometry (IP-MS) assays. Both the IP-MS and Simoa methods revealed that the use of P100 tubes significantly improves the stability of Aβ42 and Aβ40 across all approaches. However, the Aβ42/Aβ40 ratio levels were significantly stabilized only in the IP-MS assay in Approach 3. No significant differences were observed in the levels of plasma p-tau181, GFAP, and NfL for samples collected using either tube type in any of the approaches. Supplementation of blood collection tubes with protease inhibitors could reduce the protease-induced degradation of plasma Aβ42 and Aβ40, and the Aβ42/40 ratio for the IP-MS assay. These findings have crucial implications for preanalytical procedures, particularly in resource-limited settings.

Technological burden and medical complexity are significant drivers of clinician burnout. Electronic health record(EHR)-based population health management tools can be used to identify high-risk patient populations and implement prophylactic health practices. Their impact on clinician burnout, however, is not well understood. Our objective was to assess the relationship between ratings of EHR-based population health management tools and clinician burnout.

To characterize current lesbian, gay, bisexual, transgender, queer, and intersex (LGBTQI +) health-related undergraduate medical education (UME) curricular content and associated changes since a 2011 study and to determine the frequency and extent of institutional instruction in 17 LGBTQI + health-related topics, strategies for increasing LGBTQI + health-related content, and faculty development opportunities.

The purpose of this study was to evaluate the efficacy of the Residential Care Transition Module, a six-session, psychosocial, and psychoeducational telehealth intervention for family caregivers of cognitively impaired relatives living in a residential long-term care setting. Eligible participants (including care recipients, regardless of time since admission) were randomized to treatment or usual care control conditions. Survey data were collected at baseline, 4 months, 8 months, and 12 months ( = 240). Primary analytic outcomes included caregiver subjective stress (a stress process mechanism) and depressive symptoms (a measure of global well-being). Secondary analytic outcomes included secondary role strains, residential care stress, caregiver sense of competence, and self-efficacy (additional mechanisms of action). General linear models tested for the main effects of the intervention at 4 months, and longitudinal mixed models examined the 12-month effects of the intervention. Post hoc analyses also examined the influence of moderators. No significant differences between the treatment and control groups for any primary analytic outcome were apparent. Caregivers in the treatment group whose relatives were admitted to residential long-term care in the prior 3 months were more likely to indicate reductions in depressive symptoms over the first 4 months of participation. Over the 12-month study period, caregivers in the treatment group who were employed reported increased self-efficacy over time. The heterogeneity of dementia care requires a broader consideration of key contextual factors that may influence the efficacy of nonpharmacological interventions. Aligning measures with the preferences, goals, and values of dementia caregivers may further demonstrate the direct benefits of interventions such as the Residential Care Transition Module. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Human brain organoid models have emerged as a promising tool for studying human brain development and function. These models preserve human genetics and recapitulate some aspects of human brain development, while facilitating manipulation in an in vitro setting. Despite their potential to transform biology and medicine, concerns persist about their fidelity. To fully harness their potential, it is imperative to establish reliable analytic methods, ensuring rigor and reproducibility. Here, we review current analytical platforms used to characterize human forebrain cortical organoids, highlight challenges, and propose recommendations for future studies to achieve greater precision and uniformity across laboratories.

Our response addresses concerns raised about our pilot trial on omega-3 for bipolar disorder. We clarify randomization procedures, highlight the benefits of eicosapentaenoic-predominant formulations for a specific bipolar patients subgroup, and justify the use of Kaplan-Meier analysis despite limitations. We acknowledge analytical challenges due to strict inclusion criteria and encourage future research on specific bipolar subtypes and larger-scale trials for robust validation.

Whether patent foramen ovale (PFO) closure benefits older patients with PFO and cryptogenic stroke is unknown because randomized controlled trials (RCTs) have predominantly enrolled patients younger than 60 years of age. Our objective was to estimate anticipated effects of PFO closure in older patients to predict the numbers needed to plan an RCT.

Securing adequate data privacy is critical for the productive utilization of data. De-identification, involving masking or replacing specific values in a dataset, could damage the dataset's utility. However, finding a reasonable balance between data privacy and utility is not straightforward. Nonetheless, few studies investigated how data de-identification efforts affect data analysis results. This study aimed to demonstrate the effect of different de-identification methods on a dataset's utility with a clinical analytic use case and assess the feasibility of finding a workable tradeoff between data privacy and utility.

To examine the factors associated with institutionalization among individuals aged 80 years and over in Germany (total sample and stratified by sex).

Alzheimer's disease (AD), the most common form of dementia, remains challenging to understand and treat despite decades of research and clinical investigation. This might be partly due to a lack of widely available and cost-effective modalities for diagnosis and prognosis. Recently, the blood-based AD biomarker field has seen significant progress driven by technological advances, mainly improved analytical sensitivity and precision of the assays and measurement platforms. Several blood-based biomarkers have shown high potential for accurately detecting AD pathophysiology. As a result, there has been considerable interest in applying these biomarkers for diagnosis and prognosis, as surrogate metrics to investigate the impact of various covariates on AD pathophysiology and to accelerate AD therapeutic trials and monitor treatment effects. However, the lack of standardization of how blood samples and collected, processed, stored analyzed and reported can affect the reproducibility of these biomarker measurements, potentially hindering progress toward their widespread use in clinical and research settings. To help address these issues, we provide fundamental guidelines developed according to recent research findings on the impact of sample handling on blood biomarker measurements. These guidelines cover important considerations including study design, blood collection, blood processing, biobanking, biomarker measurement, and result reporting. Furthermore, the proposed guidelines include best practices for appropriate blood handling procedures for genetic and ribonucleic acid analyses. While we focus on the key blood-based AD biomarkers for the AT(N) criteria (e.g., amyloid-beta [Aβ]40, Aβ42, Aβ42/40 ratio, total-tau, phosphorylated-tau, neurofilament light chain, brain-derived tau and glial fibrillary acidic protein), we anticipate that these guidelines will generally be applicable to other types of blood biomarkers. We also anticipate that these guidelines will assist investigators in planning and executing biomarker research, enabling harmonization of sample handling to improve comparability across studies.

There is little and heterogeneous knowledge on the links between the temperamental predispositions of psychopathology and the contemporary dimensional models of psychopathology, such as the Hierarchical Taxonomy of Psychopathology (HiTOP) classification system, which can be aligned with the five-factor model (FFM) of personality. This meta-analysis seeks to expand the temperamental theoretical basis of the HiTOP model by incorporating associations of temperament traits of two temperamental theories measured, respectively, by the Temperament and Character Inventory (TCI) and the Temperament Evaluation of Memphis, Pisa, Paris, and San Diego Autoquestionnaire (TEMPS-A) with (a) the FFM's personality domains and (b) HiTOP's five psychopathological spectra.

Understanding the functional connectivity between brain regions and its emergent dynamics is a central challenge. Here we present a theory-experiment hybrid approach involving iteration between a minimal computational model and in vivo electrophysiological measurements. Our model not only predicted spontaneous persistent activity (SPA) during Up-Down-State oscillations, but also inactivity (SPI), which has never been reported. These were confirmed in vivo in the membrane potential of neurons, especially from layer 3 of the medial and lateral entorhinal cortices. The data was then used to constrain two free parameters, yielding a unique, experimentally determined model for each neuron. Analytic and computational analysis of the model generated a dozen quantitative predictions about network dynamics, which were all confirmed in vivo to high accuracy. Our technique predicted functional connectivity; e. g. the recurrent excitation is stronger in the medial than lateral entorhinal cortex. This too was confirmed with connectomics data. This technique uncovers how differential cortico-entorhinal dialogue generates SPA and SPI, which could form an energetically efficient working-memory substrate and influence the consolidation of memories during sleep. More broadly, our procedure can reveal the functional connectivity of large networks and a theory of their emergent dynamics.

The interplay of physical activity (PA) with affective well-being (AWB) is highly critical to both health behaviors and health outcomes. Current prominent theories presume AWB to be crucial for PA maintenance, and PA is evidenced to foster mental health. However, thus far, PA-AWB associations have mainly been researched in laboratory settings and with interventional designs, but the everyday life perspective had not been focused on, mostly due to technological limitations. In the course of digitization, the number of studies using device-based methods to research the within-subject association of physical activity and affective well-being (PA-AWB) under ecological valid conditions increased rapidly, but a recent comprehensive systematic review of evidence across populations, age groups, and distinct AWB components remained inconclusive.

Treatment-resistant depression (TRD) occurs in roughly one-third of all individuals with major depressive disorder (MDD). Although research has suggested a significant common variant genetic component of liability to TRD, with heritability estimated at 8% when compared with non-treatment-resistant MDD, no replicated genetic loci have been identified, and the genetic architecture of TRD remains unclear. A key barrier to this work has been the paucity of adequately powered cohorts for investigation, largely because of the challenge in prospectively investigating this phenotype. The objective of this study was to perform a well-powered genetic study of TRD.

There is a paucity of studies investigating the outcomes amongst Asian stroke patients. Identifying subgroups of stroke patients at risk of poorer outcomes could identify patients who would benefit from targeted interventions. Therefore, the aim of this study was to identify which ischemic stroke patients at high risk of recurrent events and mortality.

Sexually transmitted infections (STIs), along with sexual health and behaviour, have received little attention in schizophrenia patients.

Clinical data analysis relies on effective methods and appropriate data. Recognizing distinctive clinical services and service functions may lead to improved decision-making. Our first objective is to categorize analytical methods, data sources, and algorithms used in current research on information analysis and decision support in child and adolescent mental health services (CAMHS). Our secondary objective is to identify the potential for data analysis in different clinical services and functions in which data-driven decision aids can be useful.

During the COVID-19 pandemic, Twitter (recently rebranded as "X") was the most widely used social media platform with over 2 million cancer-related tweets. The increasing use of social media among patients and family members, providers, and organizations has allowed for novel methods of studying cancer communication.

Uterine cavity pathology may affect the endometrium or myometrium, resulting in distortion of the uterine cavity, and is responsible for 2%-5% of infertility. The methods for its assessment usually involve imaging modalities like pelvic ultrasonography, often transvaginal-(TVS), and hysterosalpingography-(HSG), with hysteroscopy-(HSC) as the gold standard. However, HSC is not readily available in resource-poor-settings.

Under a risk evaluation and mitigation strategy program, esketamine nasal spray CIII requires self administration at a certified treatment center. Our objective was to identify factors associated with esketamine initiation and continuation. A retrospective observational cohort study was conducted among US adults who met treatment-resistant depression (TRD) criteria. Cases (n = 966) initiated esketamine between October 11, 2019, and February 28, 2022, and were compared to controls (n = 39,219) with TRD but no esketamine use. Outcomes included initiation, induction (8 administrations within 45 days), and interruptions (30-day treatment gap). Comorbid psychiatric conditions were identified using codes. Cases resided significantly closer to treatment centers (8.9 vs 20.3 miles). Compared to 0-9 miles, initiation rate decreased by 11.9%, 50.8%, 68.1%, 75.9%, and 92.8% for individuals residing 10-19, 20-29, 30-39, 40-49, and 50+ miles from a center. After adjustment, factors associated with increased likelihood of initiation were posttraumatic stress disorder, major depressive disorder with suicidal ideation, and male sex, while increasing distance, substance use disorder, Medicaid, Charlson Comorbidity Index (CCI), and older age were associated with lower likelihood. Factors associated with lower likelihood of completing induction were Medicaid, low socioeconomic status (SES), CCI, and Hispanic communities. Factors associated with increased likelihood of interruption were alcohol use disorder, distance, and minority communities, while generalized anxiety disorder and Medicaid were associated with lower likelihood. Travel distance, insurance, low SES, and minority communities are potential barriers to treatment. Alternative care models may be needed to ensure adequate access to care. .

Bioethics increasingly recognizes the impact of discriminatory practices based on social categories such as race, gender, sexual orientation or ability on clinical practice. Accordingly, major bioethics associations have stressed that identifying and countering structural discrimination in clinical ethics consultations is a professional obligation of clinical ethics consultants. Yet, it is still unclear how clinical ethics consultants can fulfill this obligation. More specifically, clinical ethics needs both theoretical tools to analyze and practical strategies to address structural discrimination within clinical ethics consultations. Intersectionality, a concept developed in Black feminist scholarship, is increasingly considered in bioethical theory. It stresses how social structures and practices determine social positions of privilege and disadvantage in multiple, mutually co-constitutive systems of oppression. This article aims to investigate how intersectionality can contribute to addressing structural discrimination in clinical ethics consultations with a particular focus on mental healthcare. To this end, we critically review existing approaches for clinical ethics consultants to address structural racism in clinical ethics consultations and extend them by intersectional considerations. We argue that intersectionality is a suitable tool to address structural discrimination within clinical ethics consultations and show that it can be practically implemented in two complementary ways: 1) as an analytic approach and 2) as a critical practice.

The present 21-day daily diary study (conducted 2021-2022) tested anger and racism-related vigilance as potential transdiagnostic mediators linking exposure to racial and ethnic discrimination (RED) to distress (negative affect and stress, respectively). The data analytic sample included N = 317 Mexican-origin adolescents (M = 13.5 years; 50.8% male, 46.7% female; 2.5% non-binary) from the Midwestern United States. Results from longitudinal mediation models revealed significant mediation effects through anger and racism-related vigilance, respectively, in the association between daily RED and daily distress, both within and across adolescents. Implications for theory, research, and practice are discussed so that future work can leverage these novel findings toward promoting the well-being of Mexican-origin adolescents, especially those who live in contexts of ethnoracial adversity.

Cohort and case-control data have suggested an association between low to moderate alcohol consumption and decreased risk of ischemic heart disease (IHD), yet results from Mendelian randomization (MR) studies designed to reduce bias have shown either no or a harmful association. Here we conducted an updated systematic review and re-evaluated existing cohort, case-control, and MR data using the burden of proof meta-analytical framework. Cohort and case-control data show low to moderate alcohol consumption is associated with decreased IHD risk - specifically, intake is inversely related to IHD and myocardial infarction morbidity in both sexes and IHD mortality in males - while pooled MR data show no association, confirming that self-reported versus genetically predicted alcohol use data yield conflicting findings about the alcohol-IHD relationship. Our results highlight the need to advance MR methodologies and emulate randomized trials using large observational databases to obtain more definitive answers to this critical public health question.

Dental anxiety is a prevalent issue in society, characterized by an uneasy sensation and anticipation of negative experiences in dental settings. In essence, dental anxiety, oral health literacy, and quality of life may have a relationship with each other, however, there is a shortage of evidence examining the interplay between these factors. Therefore, this study aimed to assess the relationship between dental anxiety and oral health literacy (OHL) with oral health-related quality of life (OHRQOL).

Postpartum depression (PPD) affects around 10% of women, or 1 in 7 women, after giving birth. Undiagnosed PPD was observed among 50% of mothers. PPD has an unfavorable relationship with women's functioning, marital and personal relationships, the quality of the mother-infant connection, and the social, behavioral, and cognitive development of children. We aim to determine the frequency of PPD and explore associated determinants or predictors (demographic, obstetric, infant-related, and psychosocial factors) and coping strategies from June to August 2023 in six countries.

This study aimed to evaluate the association of the six parameters, namely stimulation intensity, stimulation frequency, pulses per session, treatment duration, number of sessions, and total number of pulses with the efficacy of conventional transcranial magnetic stimulation (rTMS) over left dorsolateral prefrontal cortex for patients with treatment-resistant depression (TRD). A random-effects dose-response meta-analysis of blinded randomized controlled trials (RCTs) involving 2391 participants were conducted to examine the dose-effect relationship of six stimulation parameters. Any of the six parameters significantly individually predicted proportion of variance in efficacy: pulses per session (R²=52.7%), treatment duration (R²=51.2%), total sessions (R²=50.9%), frequency (R²=49.6%), total pulses (R²=49.5%), and intensity (R²= 40.4%). Besides, we identified frequency as a potential parameter interacting with the other five parameters, resulting in a significant increase in variance(ΔR) ranging from 5.0% to 16.7%. Finally, we found that RCTs using frequency > 10 Hz compared to those of 10 Hz showed better dose-effect relationships. We conclude that the six stimulation parameters significantly predict the dose-effect relationship of conventional rTMS on TRD. Besides, higher stimulation frequency, higher stimulation intensity, and adequate number of pulses were associated with treatment efficacy.

E-cigarette flavors can create sensations of sweetness and coolness while masking the aversiveness of nicotine. Recently, non-tobacco nicotine (NTN) products were introduced to the market, but little is known about flavors in NTN e-cigarette use. We examined associations between flavors (i.e., sweet, mint/menthol) and susceptibility to and use of NTN e-cigarettes.

Klebsiella pneumoniae (K. pneumoniae) is a member of the ESKAPE group and is responsible for severe community and healthcare-associated infections. Certain Klebsiella species have very similar phenotypes, which presents a challenge in identifying K. pneumoniae. Multidrug-resistant K. pneumoniae is also a serious global problem that needs to be addressed. A total of 190 isolates were isolated from urine (n = 69), respiratory (n = 52), wound (n = 48) and blood (n = 21) samples collected from various hospitals in the Al-Qassim, Saudi Arabia, between March 2021 and October 2022. Our study aimed to rapidly and accurately detect K. pneumoniae using the Peptide Mass Fingerprinting (PMF) technique, confirmed by real-time PCR. Additionally, screening for antibiotic susceptibility and resistance was conducted. The primary methods for identifying K. pneumoniae isolates were culture, Gram staining, and the Vitek® 2 ID Compact system. An automated MALDI Biotyper (MBT) instrument was used for proteome identification, which was subsequently confirmed using SYBR green real-time polymerase chain reaction (real-time PCR) and microfluidic electrophoresis assays. Vitek® 2 AST-GN66 cards were utilized to evaluate the antimicrobial sensitivity of K. pneumoniae isolates. According to our results, Vitek® 2 Compact accurately identified 178 out of 190 (93.68%) K. pneumoniae isolates, while the PMF technique correctly detected 188 out of 190 (98.95%) isolates with a score value of 2.00 or higher. Principal component analysis was conducted using MBT Compass software to classify K. pneumoniae isolates based on their structure. Based on the analysis of the single peak intensities generated by MBT, the highest peak values were found at 3444, 5022, 5525, 6847, and 7537 m/z. K. pneumoniae gene testing confirmed the PMF results, with 90.53% detecting entrobactin, 70% detecting 16 S rRNA, and 32.63% detecting ferric iron uptake. The resistance of the K. pneumoniae isolates to antibiotics was as follows: 64.75% for cefazolin, 62.63% for trimethoprim/sulfamethoxazole, 59.45% for ampicillin, 58.42% for cefoxitin, 57.37% for ceftriaxone, 53.68% for cefepime, 52.11% for ampicillin-sulbactam, 50.53% for ceftazidime, 52.11% for ertapenem, and 49.47% for imipenem. Based on the results of the double-disk synergy test, 93 out of 190 (48.95%) K. pneumoniae isolates were extended-spectrum beta-lactamase. In conclusion, PMF is a powerful analytical technique used to identify K. pneumoniae isolates from clinical samples based on their proteomic characteristics. K. pneumoniae isolates have shown increasing resistance to antibiotics from different classes, including carbapenem, which poses a significant threat to human health as these infections may become difficult to treat.

The findings from previous epidemiological studies of the association between regional body fat and depressive symptoms have been unclear. We aimed to determine the association between the body fat in different regions and depressive symptoms based on data from the National Health and Nutrition Examination Survey (NHANES).

Timely outpatient follow-up and readmission after discharge are common quality indicators in psychiatric care, but their association varies in previous research. We aimed to examine whether the impact of outpatient follow-up and other factors on readmission risk evolves over time in people with non-affective psychotic disorder (NAP).

The study investigated the effects of loving-kindness meditation (LKM) on doctors' communication anxiety, trust, calling, and defensive medicine practice.

The proportion of mental disorders and burden causally attributable to childhood maltreatment is unknown.

When studies use different scales to measure continuous outcomes, standardised mean differences (SMD) are required to meta-analyse the data. However, outcomes are often reported as endpoint or change from baseline scores. Combining corresponding SMDs can be problematic and available guidance advises against this practice. We aimed to examine the impact of combining the two types of SMD in meta-analyses of depression severity. We used individual participant data on pharmacological interventions (89 studies, 27,409 participants) and internet-delivered cognitive behavioural therapy (iCBT; 61 studies, 13,687 participants) for depression to compare endpoint and change from baseline SMDs at the study level. Next, we performed pairwise (PWMA) and network meta-analyses (NMA) using endpoint SMDs, change from baseline SMDs, or a mixture of the two. Study-specific SMDs calculated from endpoint and change from baseline data were largely similar, although for iCBT interventions 25% of the studies at 3 months were associated with important differences between study-specific SMDs (median 0.01, IQR -0.10, 0.13) especially in smaller trials with baseline imbalances. However, when pooled, the differences between endpoint and change SMDs were negligible. Pooling only the more favourable of the two SMDs did not materially affect meta-analyses, resulting in differences of pooled SMDs up to 0.05 and 0.13 in the pharmacological and iCBT datasets, respectively. Our findings have implications for meta-analyses in depression, where we showed that the choice between endpoint and change scores for estimating SMDs had immaterial impact on summary meta-analytic estimates. Future studies should replicate and extend our analyses to fields other than depression.

This review aims to report on recent evidence for multi-family therapy for eating disorders (MFT) across the lifespan. It is a narrative update of recent systematic, scoping and meta-analytic reviews.

Network neuroscience offers a unique framework to understand the organizational principles of the human brain. Despite recent progress, our understanding of how the brain is modulated by focal lesions remains incomplete. Resection of the temporal lobe is the most effective treatment to control seizures in pharmaco-resistant temporal lobe epilepsy (TLE), making this syndrome a powerful model to study lesional effects on network organization in young and middle-aged adults. Here, we assessed the downstream consequences of a focal lesion and its surgical resection on the brain's structural connectome, and explored how this reorganization relates to clinical variables at the individual patient level. We included adults with pharmaco-resistant TLE (n = 37) who underwent anterior temporal lobectomy between two imaging time points, as well as age- and sex-matched healthy controls who underwent comparable imaging (n = 31). Core to our analysis was the projection of high-dimensional structural connectome data-derived from diffusion MRI tractography from each subject-into lower-dimensional gradients. We then compared connectome gradients in patients relative to controls before surgery, tracked surgically-induced connectome reconfiguration from pre- to postoperative time points, and examined associations to patient-specific clinical and imaging phenotypes. Before surgery, individuals with TLE presented with marked connectome changes in bilateral temporo-parietal regions, reflecting an increased segregation of the ipsilateral anterior temporal lobe from the rest of the brain. Surgery-induced connectome reorganization was localized to this temporo-parietal subnetwork, but primarily involved postoperative integration of contralateral regions with the rest of the brain. Using a partial least-squares analysis, we uncovered a latent clinical-imaging signature underlying this pre- to postoperative connectome reorganization, showing that patients who displayed postoperative integration in bilateral fronto-occipital cortices also had greater preoperative ipsilateral hippocampal atrophy, lower seizure frequency, and secondarily generalized seizures. Our results bridge the effects of focal brain lesions and their surgical resections with large-scale network reorganization and inter-individual clinical variability, thus offering new avenues to examine the fundamental malleability of the human brain.

Predicting repetitive transcranial magnetic stimulation (rTMS) treatment outcomes in major depressive disorder (MDD) could reduce the financial and psychological risks of treatment failure. We systematically reviewed and meta-analyzed studies that leveraged neurophysiological and neuroimaging markers to predict rTMS response in MDD. Five databases were searched from inception to May 25, 2023. The primary meta-analytic outcome was predictive accuracy pooled from classification models. Regression models were summarized qualitatively. A promising marker was identified if it showed a sensitivity and specificity of 80% or higher in at least two independent studies. Searching yielded 36 studies. Twenty-two classification modeling studies produced an estimated area under the summary receiver operating characteristic curve of 0.87 (95% CI = 0.83-0.92), with 86.8% sensitivity (95% CI = 80.6-91.2%) and 81.9% specificity (95% CI = 76.1-86.4%). Frontal theta cordance measured by electroencephalography is closest to proof of concept. Predicting rTMS response using neurophysiological and neuroimaging markers is promising for clinical decision-making. However, replications by different research groups are needed to establish rigorous markers.

Alzheimer's disease (AD) is the most common neurodegenerative disorder, affecting a growing number of elderly people. In order to improve the early and differential diagnosis of AD, better biomarkers are needed. Glycosylation is a protein post-translational modification that is modulated in the course of many diseases, including neurodegeneration. Aiming to improve AD diagnosis and differential diagnosis through glycan analytics methods, we report the glycoprotein glycome of cerebrospinal fluid (CSF) isolated from a total study cohort of 262 subjects. The study cohort consisted of patients with AD, healthy controls and patients suffering from other types of dementia. CSF free-glycans were also isolated and analyzed in this study, and the results reported for the first time the presence of 19 free glycans in this body fluid. The free-glycans consisted of complete or truncated N-/O-glycans as well as free monosaccharides. The free-glycans Hex and HexNAcHexNeu5Ac were able to discriminate AD from controls and from patients suffering from other types of dementia. Regarding CSF N-glycosylation, high proportions of high-mannose, biantennary bisecting core-fucosylated N-glycans were found, whereby only about 20% of the N-glycans were sialylated. O-Glycans and free-glycan fragments were less sialylated in AD patients than in controls. To conclude, this comprehensive study revealed for the first time the biomarker potential of free glycans for the differential diagnosis of AD.

Genome-wide association studies across diverse populations may help validate and confirm genetic contributions to risk of disease. We estimated the extent of population stratification as well as the predictive accuracy of polygenic scores (PGS) derived from European samples to a data set from India. We analysed 2685 samples from two data sets, a population neurodevelopmental study (cVEDA) and a hospital-based sample of bipolar affective disorder (BD) and obsessive-compulsive disorder (OCD). Genotyping was conducted using Illumina's Global Screening Array. Population structure was examined with principal component analysis (PCA), uniform manifold approximation and projection (UMAP), support vector machine (SVM) ancestry predictions, and admixture analysis. PGS were calculated from the largest available European discovery GWAS summary statistics for BD, OCD, and externalizing traits using two Bayesian methods that incorporate local linkage disequilibrium structures (PGS-CS-auto) and functional genomic annotations (SBayesRC). Our analyses reveal global and continental PCA overlap with other South Asian populations. Admixture analysis revealed a north-south genetic axis within India ( 1.6%). The UMAP partially reconstructed the contours of the Indian subcontinent. The Bayesian PGS analyses indicates moderate-to-high predictive power for BD. This was despite the cross-ancestry bias of the discovery GWAS dataset, with the currently available data. However, accuracy for OCD and externalizing traits was much lower. The predictive accuracy was perhaps influenced by the sample size of the discovery GWAS and phenotypic heterogeneity across the syndromes and traits studied. Our study results highlight the accuracy and generalizability of newer PGS models across ancestries. Further research, across diverse populations, would help understand causal mechanisms that contribute to psychiatric syndromes and traits.

Comorbid epilepsy and challenging behaviours is quiet common in patients with ID (intellectual disability). This study aims to determine the frequency and mutual association between epilepsy and challenging behaviours. In this cross-sectional analytical study, 252 patients were enrolled through convenient sampling technique. Comorbid epilepsy and CB (challenging behaviour) were seen in 111 (44.6%) and 116 (46.6%) patients, respectively. Epilepsy and severity of intellectual disability (ID) are statistically and significantly associated with challenging behaviour. This study concluded that comorbid epilepsy is more common among people with ID as compared to the general population. The clinical variables, i.e. comorbid epilepsy and severity of ID have statistically significant association with the CB.

Personalized functional networks (FNs) derived from functional magnetic resonance imaging (fMRI) data are useful for characterizing individual variations in the brain functional topography associated with the brain development, aging, and disorders. To facilitate applications of the personalized FNs with enhanced reliability and reproducibility, we develop an open-source toolbox that is user-friendly, extendable, and includes rigorous quality control (QC), featuring multiple user interfaces (graphics, command line, and a step-by-step guideline) and job-scheduling for high performance computing (HPC) clusters. Particularly, the toolbox, named personalized functional network modeling (pNet), takes fMRI inputs in either volumetric or surface type, ensuring compatibility with multiple fMRI data formats, and computes personalized FNs using two distinct modeling methods: one method optimizes the functional coherence of FNs, while the other enhances their independence. Additionally, the toolbox provides HTML-based reports for QC and visualization of personalized FNs. The toolbox is developed in both MATLAB and Python platforms with a modular design to facilitate extension and modification by users familiar with either programming language. We have evaluated the toolbox on two fMRI datasets and demonstrated its effectiveness and user-friendliness with interactive and scripting examples. pNet is publicly available at https://github.com/MLDataAnalytics/pNet.

The relationship between diet and the management of chronic illnesses is well established. However, it is unknown the extent to which people with chronic illnesses pay attention to nutritional information and act upon the information obtained. We evaluated the menu ordering practices of adults with chronic illnesses.

Anxiety disorders are highly prevalent worldwide; however, the literature lacks a meta-analytic quantification of the risk posed by fathers' anxiety for offspring development. This systematic review and meta-analysis aimed to provide a comprehensive estimate of the magnitude of the association between paternal anxiety and emotional and behavioral problems of offspring.

This paper presents a comprehensive overview of the National Sleep Research Resource (NSRR), a National Heart Lung and Blood Institute-supported repository developed to share data from clinical studies focused on the evaluation of sleep disorders. The NSRR addresses challenges presented by the heterogeneity of sleep-related data, leveraging innovative strategies to optimize the quality and accessibility of available datasets. It provides authorized users with secure centralized access to a large quantity of sleep-related data including polysomnography, actigraphy, demographics, patient-reported outcomes, and other data. In developing the NSRR, we have implemented data processing protocols that ensure de-identification and compliance with FAIR (Findable, Accessible, Interoperable, Reusable) principles. Heterogeneity stemming from intrinsic variation in the collection, annotation, definition, and interpretation of data has proven to be one of the primary obstacles to efficient sharing of datasets. Approaches employed by the NSRR to address this heterogeneity include (1) development of standardized sleep terminologies utilizing a compositional coding scheme, (2) specification of comprehensive metadata, (3) harmonization of commonly used variables, and (3) computational tools developed to standardize signal processing. We have also leveraged external resources to engineer a domain-specific approach to data harmonization. We describe the scope of data within the NSRR, its role in promoting sleep and circadian research through data sharing, and harmonization of large datasets and analytical tools. Finally, we identify opportunities for approaches for the field of sleep medicine to further support data standardization and sharing.

Transcranial magnetic stimulation (TMS) is commonly delivered at an intensity defined by the resting motor threshold (rMT), which is thought to represent cortical excitability, even if the TMS target area falls outside of the motor cortex. This approach rests on the assumption that cortical excitability, as measured through the motor cortex, represents a 'global' measure of excitability. Another common approach to measure cortical excitability relies on the phosphene threshold (PT), measured through the visual cortex of the brain. However, it remains unclear whether either estimate can serve as a singular measure to infer cortical excitability across different brain regions. If PT and rMT can indeed be used to infer cortical excitability across brain regions, they should be correlated. To test this, we systematically identified previous studies that measured PT and rMT to calculate an overall correlation between the two estimates. Our results, based on 16 effect sizes from eight studies, indicated that PT and rMT are correlated (ρ = 0.4), and thus one measure could potentially serve as a measure to infer cortical excitability across brain regions. Three exploratory meta-analyses revealed that the strength of the correlation is affected by different methodologies, and that PT intensities are higher than rMT. Evidence for a PT-rMT correlation remained robust across all analyses. Further research is necessary for an in-depth understanding of how cortical excitability is reflected through TMS.

Chronic low back pain (cLBP) is characterized by biopsychosocial determinants that collectively result in substantial burden at the individual, community, and healthcare system levels. A growing body of literature suggests that childhood adversity is longitudinally associated with the development and maintenance of various chronic pain conditions in adulthood. Little research has investigated the psychological processes that might underlie the association between adverse childhood experiences (ACEs) and cLBP. Emotion regulation comprises a substantive part of the subjective experience of pain and may be a potential mechanism through which ACEs contribute to cLBP etiology and maintenance. Thus, the current study examined the extent to which emotion dysregulation mediated the relationship between ACEs and pain severity (pain at rest and movement-evoked pain) in adults with cLBP. Participants included 183 adults (53.0% female, 62.5% non-Hispanic Black) between the ages of 18 and 85 with cLBP. Participants self-reported on ACEs, pain, difficulties in emotion regulation, depression, and completed brief physical function tasks. In data analytic models, sociodemographic variables were included as covariates. Mediation analyses revealed that emotion regulation mediated the relationship between ACEs and cLBP severity at rest (indirect effect = 0.15 (95% CI [0.06 to 0.25]) and with movement (indirect effect = 1.50 (95% CI [0.69 to 2.57]). Findings suggest ACEs are linked to cLBP severity in adulthood though difficulties in emotion regulation. This aligns with research demonstrating that childhood maltreatment can lead to difficulties in emotion regulation which perpetuate over the lifespan to impact adult health outcomes. TRIAL REGISTRATION: This study utilized baseline data collected as part of a parent trial titled "Examining Racial and SocioEconomic Disparities in Chronic Low Back Pain" (ERASED - ClinicalTrials.gov ID: NCT03338192). PERSPECTIVE: This study presents emotion dysregulation as a psychological pathway through which childhood adversity may contribute to chronic low back pain in adulthood. This work may bolster our understanding of social experiences as risk factors for chronic pain, while identifying targets for clinical intervention.

Autism is four times more prevalent in males than females. To study whether this reflects a difference in genetic predisposition attributed to autosomal rare variants, we evaluated the sex differences in effect size of damaging protein-truncating and missense variants on autism predisposition in 47,061 autistic individuals, then compared effect sizes between individuals with and without cognitive impairment or motor delay. Although these variants mediated differential likelihood of autism with versus without motor or cognitive impairment, their effect sizes on the liability scale did not differ significantly by sex exome-wide or in genes sex-differentially expressed in the cortex. Although de novo mutations were enriched in genes with male-biased expression in the fetal cortex, the liability they conferred did not differ significantly from other genes with similar loss-of-function intolerance and sex-averaged cortical expression. In summary, autosomal rare coding variants confer similar liability for autism in females and males.

Variants in cis-regulatory elements link the noncoding genome to human brain pathology; however, detailed analytic tools for understanding the association between cell-level brain pathology and noncoding variants are lacking. CWAS-Plus, adapted from a Python package for category-wide association testing (CWAS) employs both whole-genome sequencing and user-provided functional data to enhance noncoding variant analysis, with a faster and more efficient execution of the CWAS workflow. Here, we used single-nuclei assay for transposase-accessible chromatin with sequencing to facilitate CWAS-guided noncoding variant analysis at cell-type specific enhancers and promoters. Examining autism spectrum disorder whole-genome sequencing data (n = 7,280), CWAS-Plus identified noncoding variant associations in transcription factor binding sites within conserved loci. Independently, in Alzheimer's disease whole-genome sequencing data (n = 1,087), CWAS-Plus detected rare noncoding variant associations in microglia-specific regulatory elements. These findings highlight CWAS-Plus's utility in genomic disorders and scalability for processing large-scale whole-genome sequencing data and in multiple-testing corrections. CWAS-Plus and its user manual are available at https://github.com/joonan-lab/cwas/ and https://cwas-plus.readthedocs.io/en/latest/, respectively.

Obsessive-compulsive disorder (OCD) affects ~1% of the population and exhibits a high SNP-heritability, yet previous genome-wide association studies (GWAS) have provided limited information on the genetic etiology and underlying biological mechanisms of the disorder. We conducted a GWAS meta-analysis combining 53,660 OCD cases and 2,044,417 controls from 28 European-ancestry cohorts revealing 30 independent genome-wide significant SNPs and a SNP-based heritability of 6.7%. Separate GWAS for clinical, biobank, comorbid, and self-report sub-groups found no evidence of sample ascertainment impacting our results. Functional and positional QTL gene-based approaches identified 249 significant candidate risk genes for OCD, of which 25 were identified as putatively causal, highlighting , , and genes in the MHC region. Tissue and single-cell enrichment analyses highlighted hippocampal and cortical excitatory neurons, along with D1- and D2-type dopamine receptor-containing medium spiny neurons, as playing a role in OCD risk. OCD displayed significant genetic correlations with 65 out of 112 examined phenotypes. Notably, it showed positive genetic correlations with all included psychiatric phenotypes, in particular anxiety, depression, anorexia nervosa, and Tourette syndrome, and negative correlations with a subset of the included autoimmune disorders, educational attainment, and body mass index.. This study marks a significant step toward unraveling its genetic landscape and advances understanding of OCD genetics, providing a foundation for future interventions to address this debilitating disorder.

Eating disorder (ED) subtyping studies have often extracted an undercontrolled, an overcontrolled and a resilient profile based on trait impulsivity and perfectionism. However, the extent to which methodological choices impact the coherence and distinctness of resulting subtypes remains unclear.

Critical adolescent neural refinement is controlled by the DCC (deleted in colorectal cancer) protein, a receptor for the netrin-1 guidance cue. We sought to describe the effects of reduced on neuroanatomy in the adolescent and adult mouse brain.

Amiloride is a U.S. Food and Drug Administration-approved diuretic agent used to treat hypertension and congestive heart failure. Recent human and animal studies have suggested that amiloride may also have a role in treating anxiety through its acid-sensing ion channel antagonism. Intranasal administration of amiloride nasal spray via an extemporaneously compounded preparation has the potential for rapid delivery to the site of action to achieve therapeutic outcomes in individual patients with anxiety disorders. However, these patient-specific preparations do not have the pre-formulation characterization, including chemical stability, that conventional manufactured dosage forms have. The objective of this study was to assess the estimated chemical stability of compounded amiloride nasal spray over 6 months and 12 months utilizing accelerated degradation with high heat and the Arrhenius equation. A stability-indicating highperformance liquid chromatography analytical method was employed at appropriate intervals over a 12-month period to reveal that amiloride remained chemically stable over the period tested and by extrapolation. Physical stability and compatibility with the preservative benzyl alcohol were also confirmed via visual inspection, pH monitoring, and measurement of turbidity.

Suspected adverse drug reactions (ADRs) during treatment with clozapine often prompt therapeutic drug monitoring (TDM) in clinical practice. Currently, there is no official recommendation for pharmacogenetic (PGx) testing in the context of clozapine therapy. In this case report, we demonstrate and discuss the challenges of interpreting PGx and TDM results highlighting the possibilities and limitations of both analytical methods. A 36-year-old male patient with catatonic schizophrenia was treated with clozapine. He experienced multiple hospitalizations due to elevated creatine kinase (CK) levels (up to 9000 U/L, reference range: 30-200 U/L). With no other medical explanation found, physicians suspected clozapine-induced ADRs. However, plasma levels of clozapine were consistently low or subtherapeutic upon admission, prompting us to conduct a PGx analysis and retrospectively review the patient's TDM data, progress notes, and discharge reports. We investigated two possible hypotheses to explain the symptoms despite low clozapine plasma levels: suggested the formation and accumulation of a reactive intermediate metabolite due to increased activity in cytochrome P450 3A5 and reduced activity in glutathione S-transferases 1, leading to myotoxicity. proposed under-treatment with clozapine, resulting in ineffective clozapine levels, leading to a rebound effect with increased catatonic symptoms and CK levels. After considering both data sources (PGx and TDM), hypothesis ii. appeared more plausible. By comprehensively assessing all available TDM measurements and examining them in temporal correlation with the drug dose and clinical symptoms, we observed that CK levels normalized when clozapine plasma levels were raised to the therapeutic range. This was achieved through hospitalization and closely monitored clozapine intake. Therefore, we concluded that the symptoms were not an ADR due to altered clozapine metabolism but rather the result of under-treatment. Interpreting TDM and PGx results requires caution. Relying solely on isolated PGx or single TDM values can result in misinterpretation of drug reactions. We recommend considering the comprehensive patient history, including treatment, dosages, laboratory values, clinic visits, and medication adherence.

Mental health is an essential component of the health and well-being of a person and community, and it is critical for the individual, society, and socio-economic development of any country. Mental healthcare is currently in the health sector transformation era, with emerging technologies such as artificial intelligence (AI) reshaping the screening, diagnosis, and treatment modalities of psychiatric illnesses. The present narrative review is aimed at discussing the current landscape and the role of AI in mental healthcare, including screening, diagnosis, and treatment. Furthermore, this review attempted to highlight the key challenges, limitations, and prospects of AI in providing mental healthcare based on existing works of literature. The literature search for this narrative review was obtained from PubMed, Saudi Digital Library (SDL), Google Scholar, Web of Science, and IEEE Xplore, and we included only English-language articles published in the last five years. Keywords used in combination with Boolean operators ("AND" and "OR") were the following: "Artificial intelligence", "Machine learning", Deep learning", "Early diagnosis", "Treatment", "interventions", "ethical consideration", and "mental Healthcare". Our literature review revealed that, equipped with predictive analytics capabilities, AI can improve treatment planning by predicting an individual's response to various interventions. Predictive analytics, which uses historical data to formulate preventative interventions, aligns with the move toward individualized and preventive mental healthcare. In the screening and diagnostic domains, a subset of AI, such as machine learning and deep learning, has been proven to analyze various mental health data sets and predict the patterns associated with various mental health problems. However, limited studies have evaluated the collaboration between healthcare professionals and AI in delivering mental healthcare, as these sensitive problems require empathy, human connections, and holistic, personalized, and multidisciplinary approaches. Ethical issues, cybersecurity, a lack of data analytics diversity, cultural sensitivity, and language barriers remain concerns for implementing this futuristic approach in mental healthcare. Considering these sensitive problems require empathy, human connections, and holistic, personalized, and multidisciplinary approaches, it is imperative to explore these aspects. Therefore, future comparative trials with larger sample sizes and data sets are warranted to evaluate different AI models used in mental healthcare across regions to fill the existing knowledge gaps.

The escalating global prevalence of burnout among healthcare professionals poses a serious health concern. Recent studies focus on prevalence and predictors of burnout among healthcare providers, emphasizing the need for well-being interventions. This study investigates burnout and coping mechanisms among healthcare professionals in central Uganda, addressing the dearth of knowledge about coping strategies specific to the region.

Observational studies have confirmed that mental illness and pulmonary tuberculosis are closely related and increase each other's incidence; however, whether there is a causal genetic association between the two diseases remains unknown. We attempted to answer this question using bidirectional two-sample Mendelian randomization (MR) in a large cohort study.

The relation between mental disorders (MDs) and infertility can be reciprocal. But exactly which MD affects infertility remains controversial. Our aim was to use Mendelian randomization (MR) to explore bidirectional causality between 15 MDs and male infertility and female infertility.

This rapid review used a systematic approach to examine the available literature on rehabilitation and reintegration (R&R) programs for women and children returning from contexts of violent extremism, examining common assumptions, inputs, activities and outcomes across diverse settings. Fifty-one documents including peer reviewed articles and grey literature were included in the analysis. The most common program activities identified included mental health services, community level social programs, promoting school and vocational enrollment, regular health services, and parenting training & education, though there was a lack of consensus around core program components. The analysis points to the need for a robust set of inputs and resources to implement R&R programs including government officials, child welfare, mental health professionals, teachers, law enforcement, healthcare, community leaders, and extended family. The review also uncovered a number of gaps. This includes the need to create clear and analytically distinct definitions of rehabilitation and reintegration that are applicable and relevant to key stakeholders, delineating age-appropriate activities and outcomes for young children, youth, and adults, defining frameworks for service delivery and coordination of stakeholders, and placing R&R programs within existing domains of public safety and restorative justice.

Sleep disorders such as insomnia can lead to a range of health problems. The high risk of side effects and drug abuse of traditional pharmacotherapy calls for a safer non-pharmacotherapy.

Epileptologists and psychiatrists have long observed a correlation between epilepsy and personality disorders (PDs) in their clinical practice. We conducted a comprehensive PubMed search looking for evidence on PDs in people with epilepsy (PwE). Out of over 600 results obtained without applying any time restriction, we selected only relevant studies (both analytical and descriptive) limited to English, Italian, French and Spanish languages, with a specific focus on PDs, rather than traits or symptoms, thus narrowing our search down to 23 eligible studies. PDs have been investigated in focal epilepsy (predominantly temporal lobe epilepsy - TLE), juvenile myoclonic epilepsy (JME) and psychogenic non-epileptic seizures (PNES), with heterogeneous methodology. Prevalence rates of PDs in focal epilepsy ranged from 18 to 42% in surgical candidates or post-surgical individuals, with Cluster C personality disorders or related traits and symptoms being most common. In JME, prevalence rates ranged from 8 to 23%, with no strong correlation with any specific PDs subtype. In PNES, prevalence rates ranged from 30 to 60%, with a notable association with Cluster B personality disorders, particularly borderline personality disorder. The presence of a PD in PwE, irrespective of subtype, complicates treatment management. However, substantial gaps of knowledge exist concerning the neurobiological substrate, effects of antiseizure medications and epilepsy surgery on concomitant PDs, all of which are indeed potential paths for future research.