Changes in Rates of Suicide by Mass Shooters, 1980-2019.

OBJECTIVE: The rate of worldwide mass shootings increased almost 400% over the last 40 years. About 30% are followed by the perpetrator's fatal or nonfatal suicide attempt. METHOD: We examined the rate of fatal and nonfatal attempts among 528 mass shooters over the last 40 years and their relationship to detected mental illness to better understand this specific context of suicide. We collected information on U.S.-based, personal-cause mass murders that involved one or more firearms, from online sources. RESULTS: A greater proportion of mass shooters from 2000 to 2019 took or attempted to take their own lives (40.5%) compared with those from 1980 to 1999 (23.2%, p < 0.001). More than double the proportion of perpetrators who made a fatal or nonfatal suicide attempt had a history of non-psychotic psychiatric/neurologic symptoms (38.9%), compared with perpetrators who did not make a fatal or nonfatal suicide attempt (18.1%; p < 0.001). Among mass shooters who made fatal or nonfatal suicide attempts, 77 of 175 (44%) did not have any recorded psychiatric, neurologic, or substance use condition. Of the 98 mass shooters who made fatal or non-fatal suicide attempts and had a psychiatric, substance use, or neurologic condition, 41 had depressive disorders. CONCLUSION: It is possible that a lack of information about the perpetrators' mental health or suicidal ideation led to an underestimation of their prevalence. These data suggest that suicide associated with mass shootings may represent a specific context for suicide, and approaches such as psychological autopsy can help to ascertain when psychiatric illness mediates the relationship between mass shootings and suicide.

We examined 528 mass shootings.A greater proportion of mass shooters from 2000-2019 made a fatal or nonfatal suicide attempt (123/304, 40.5%) compared with mass shooters from 1980-1999 (52/224, 23.2%), χ2 = 17.3, p<.001.More than double the proportion of perpetrators who made a fatal or nonfatal suicide attempt had a history of non-psychotic psychiatric/neurologic symptoms (38.9%), compared with those who did not (18.1%; p < 0.001).Among mass shooters who made a fatal or nonfatal suicide attempt, 77 of 175 (44%) did not have any recorded psychiatric, neurologic, or substance use condition. However, it is possible that a lack of information about the perpetrators' mental health or suicidal ideation led to an underestimation of their prevalence.These results suggest that perpetrators may have considered suicide a potential outcome of such an event, and/or that the perpetrators' high levels of aggression and anger, accompanied by an impaired capacity for restraint, resulted in homicide followed by suicidal behavior.Psychological autopsies can clarify the role of psychiatric illness and more extreme aggressive traits in homicide-suicide instances of mass shootings.

Immune-Targeted Therapies for Depression: Current Evidence for Antidepressant Effects of Monoclonal Antibodies.

Importance: Increasing evidence suggests a potential role of immune-modulatory drugs for treatment-resistant depression. This scoping review explores the emerging evidence regarding the antidepressant effects of monoclonal antibodies (mAbs), a relatively newer class of immune therapeutics with favorable safety profile.Observations: PubMed was searched up to November 2023 for English publications addressing the antidepressant effects of mAbs, including meta-analyses, randomized controlled trials, open-label, single-arm studies, and case series. Several mAbs have shown potential antidepressant effects, but most studies in primary inflammatory disorders included patients with mild depression. Only infliximab and sirukumab were directly examined in individuals with primary depression. mAbs that do not require laboratory monitoring, such as ixekizumab and dupilumab, could hold potential promise if future studies establish their safety profile regarding suicide risk.Conclusions and Relevance: The use of several mAbs for the treatment of primary inflammatory disorders has been associated with improvement of comorbid depressive symptoms. Given their unique mechanisms of action, mAbs may offer a new hope for depressed patients who do not respond to currently available antidepressants. Further research addressing individuals with more severe depressive symptoms is essential. Direct examination of antidepressant effects of mAbs in people with primary depressive disorders is also crucial to refine their clinical use in the treatment of depression.

Temporal Interactions between Neural Proxies forMemory Recall, Negative Affect, and EmotionRegulation in Major Depression.

Dysfunction in emotion regulation (ER) and autobiographical memory are components of major depressive disorder (MDD). However, little is known about how they mechanistically interact with mood disturbances in real time. Using machine learning-based neural signatures, we can quantify negative affect (NA), ER, and memory continuously to evaluate how these processes dynamically interact in MDD. Unmedicated individuals with MDD (N=45) and healthy volunteers (HV; N=38) completed a negative autobiographical memory functional magnetic resonance imaging task wherein they recalled, distanced from (an ER strategy), and immersed into memories. We used a negative affect signature (PINES) and an emotion regulation signature (ERS) to quantify moment-to-moment NA and ER. We then examined whether memory engagement, indexed by hippocampal activity, predicted subsequent change in PINES and ERS over time. During memory recall and immersion, greater hippocampal activity predicted increased PINES across groups. During distancing, greater hippocampal activity in HVs predicted increased ERS but not PINES. In MDD, greater hippocampal activity predicted increased PINES but not ERS. Findings suggest abnormalities in the real-time relationship between memory, NA, and ER in MDD. During distancing, as predicted, HVs showed an attenuation of the linkage between memory engagement and NA, and they had subsequent increases in ER following memory reactivation. In contrast, MDD was characterized by continued linkage between memory engagement and NA, without subsequent increases in ER. Deficits in engagement of ER and ineffective modulation of NA following negative memory recall may contribute to the mood disturbances in MDD and are potential targets for clinical intervention.

Relationships of DSM-5 PTSD symptom clusters to suicidal ideation and death ideation in outpatient military veterans.

Veterans with PTSD are at higher risk for suicide. This study examined the specific associations of PTSD symptom clusters with suicidal ideation (SI) and death ideation (DI), independently from depressive symptom clusters. Participants included 695 Israeli male outpatient military veterans (M = 25.35 years, SD = 5.65), divided into subsamples of probable PTSD (PTSD Checklist for DSM-5 [PCL-5] ≥ 33) and subthreshold PTSD scores (PCL-5 < 33). Data were extracted from medical chartsand self-report questionnaires. The main analyses included logistic regression to evaluate the associations between SI and DI (Brief Symptom Inventory, items 9 and 39) and PTSD symptom clusters (PCL-5), controlling for depressive symptom clusters (Beck Depression Inventory; cognitive-affective and somatization) in each subsample. The results showed that, for veterans with probable PTSD, the negative alterations in cognition and mood symptom cluster was positively correlated with SI and DI, while avoidance was negatively correlated with SI, independently from depressive symptoms clusters. In those with sub-syndromal PTSD, the re-experiencing cluster was positively correlated with DI, independently from the depressive symptom clusters. These findings highlight the importance of targeting PTSD components, such as negative alterations in cognition and mood symptoms experienced by veterans with PTSD, as part of suicide prevention efforts.

Dental Attrition and its Association With the Signs and Symptoms of TMJ Dysfunction and Radiographic Condylar Changes - An Observational Study.

To determine the level of dental attrition and its relation to signs of TMJ dysfunction adding to condylar alterations analyzed by conventional TMJ Tomography and to propose the correlation between dental attrition and signs of TMJ dysfunction and condylar changes. Patients for the study were selected from the regular outpatient Department of Oral Medicine, Diagnosis and Radiology, Rajah Muthiah Dental College and Hospital, Annamalai University, Chidambaram, with performed criteria. The radiographic examination of TMJ is performed by the PLANMECA OPG machine using the tomographic program. Statistical analysis was performed using a Chi-square test to determine the relation between attrition and temporomandidular disorders [TMD] signs and symptoms. The study group comprises 60 subjects who are having dental attrition, and they are divided into three groups according to their age: Group I, 20-40 age; Group II, 41-60 age; Group III, more than 60 age 80% of the samples had one or more tooth with significant attrition with grades of two or more on a 0-4 scale The prevalence of changes in condylar morphology was more in individuals above 40 yrs (33.33%) as compared to those below the age of 40 with a total prevalence of 41.67%. The most common symptom reported is tooth sensitivity, joint sounds, and muscle tenderness. The last reported are scalloped tongue, buccal mucosa ridging, referred pain, and limitation of mouth opening. Out of the 25 subjects who showed condylar changes, 10 subjects had symptoms of TMD. The symptoms reported are strain in the mouth opening, tenderness in jaw movements, and TMJ clicking sounds. Attrition is not a predictable sign of TMJ dysfunction, yet a finite association was defined between attrition and signs and symptoms of TMJ dysfunction. Studies involving larger samples compared with additional radiographic modalities are recommended.

Occurrence and characteristics of suicidal ideation in psychiatrically healthy individuals based on ecological momentary assessment.

Decedents with no known mental disorder comprise 5-40% of suicides, suggesting that suicide ideation (SI) and behavior may occur in the psychiatrically healthy with important implications for suicide risk screening. Healthy Volunteers (HV) and patients with Major Depressive Disorder (MDD) provided 7 days of Ecological Momentary Assessment (EMA) data about SI and stressors. Longitudinal mixed effects logistic regression models compared HV and patient SI and stressors. Mixed effects linear regression models compared HVs' and patients' SI score change from the previous epoch's SI score when each stressor occurred. HVs (n = 42) reported less frequent (p < 0.001) and less intense SI (p < 0.003) than patients (n = 80), yet did endorse SI and/or SI-related items in 44% of EMA epochs, endorsing SI items in 25% of epochs with non-zero SI scores. For 7 of 8 stressors, patients reported stressors more often than HVs (all p < 0.001) responding to them with increased SI (0.0001 < p < 0.0472). HVs were relatively resilient to stressors, reporting SI increases only in response to neglect (p < 0.0147). Although SI and SAs are documented among psychiatrically healthy individuals, scientific attention to these observations has been scant. Real-time SI measurement showed that HVs' SI was less pronounced than MDD patients', but was endorsed, nonetheless. Patients were more likely to report stressors than HVs, perhaps due to greater sensitivity to the environment, and reported SI in response to stressors, which was less common in HVs. Both MDD patients and HVs most often manifested passive SI (viz, "decreased wish to live"). However, passive SI (viz, "desire for death"), may predict suicide, even absent SI per se (thinking about killing yourself). This study validates the utility of real-time SI assessment, showing that HVs endorse SI items in 11% of epochs, which implies that suicide risk screening focused on those with mental disorders may be too narrow an approach.

Temporal prediction of suicidal ideation in an ecological momentary assessment study with recurrent neural networks.

INTRODUCTION: 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. METHODS: As part of a broader research study of suicidal thoughts and behavior in people with borderline personality disorder (BPD), eighty-four participants engaged in EMA data collection over one week, answering questions multiple times each day about suicidal ideation (SI), stressful events, coping strategy use, and affect. RNNs and mixed-effects linear regression models (MEMs) were trained and used to predict SI. Root mean squared error (RMSE), mean absolute percent error (MAPE), and a pseudo-R2 accuracy metric were used to compare SI prediction accuracy between the two modeling methods. RESULTS: RNNs had superior accuracy metrics (full model: RMSE = 3.41, MAPE = 42 %, pseudo-R2 = 26 %) compared with MEMs (full model: RMSE = 3.84, MAPE = 56 %, pseudo-R2 = 16 %). Importantly, RNNs showed significantly more accurate prediction at higher values of SI. Additionally, RNNs predicted, with significantly higher accuracy, the SI scores of participants with depression diagnoses and of participants with higher depression scores at baseline. CONCLUSION: In this EMA study with a moderately sized sample, RNNs were better able to learn and predict daily SI compared with mixed-effects models. RNNs should be considered as an option for EMA analysis.

Omics Approaches to Investigate the Pathogenesis of Suicide.

Suicide is the second leading cause of death in U.S. adolescents and young adults and is generally associated with a psychiatric disorder. Suicidal behavior has a complex etiology and pathogenesis. Moderate heritability suggests genetic causes. Associations between childhood and recent life adversity indicate contributions from epigenetic factors. Genomic contributions to suicide pathogenesis remain largely unknown. This article is based on a workshop held to design strategies to identify molecular drivers of suicide neurobiology that would be putative new treatment targets. The panel determined that while bulk tissue studies provide comprehensive information, single-nucleus approaches that identify cell type-specific changes are needed. While single-nuclei techniques lack information on cytoplasm, processes, spines, and synapses, spatial multiomic technologies on intact tissue detect cell alterations specific to brain tissue layers and subregions. Because suicide has genetic and environmental drivers, multiomic approaches that combine cell type-specific epigenome, transcriptome, and proteome provide a more complete picture of pathogenesis. To determine the direction of effect of suicide risk gene variants on RNA and protein expression and how these interact with epigenetic marks, single-nuclei and spatial multiomics quantitative trait loci maps should be integrated with whole-genome sequencing and genome-wide association databases. The workshop concluded with a recommendation for the formation of an international suicide biology consortium that will bring together brain banks and investigators with expertise in cutting-edge omics technologies to delineate the biology of suicide and identify novel potential treatment targets to be tested in cellular and animal models for drug and biomarker discovery to guide suicide prevention.

A Human Brain Map of Mitochondrial Respiratory Capacity and Diversity.

Mitochondrial oxidative phosphorylation (OxPhos) powers brain activity1,2, and mitochondrial defects are linked to neurodegenerative and neuropsychiatric disorders3,4, underscoring the need to define the brain's molecular energetic landscape5-10. To bridge the cognitive neuroscience and cell biology scale gap, we developed a physical voxelization approach to partition a frozen human coronal hemisphere section into 703 voxels comparable to neuroimaging resolution (3×3×3 mm). In each cortical and subcortical brain voxel, we profiled mitochondrial phenotypes including OxPhos enzyme activities, mitochondrial DNA and volume density, and mitochondria-specific respiratory capacity. We show that the human brain contains a diversity of mitochondrial phenotypes driven by both topology and cell types. Compared to white matter, grey matter contains >50% more mitochondria. We show that the more abundant grey matter mitochondria also are biochemically optimized for energy transformation, particularly among recently evolved cortical brain regions. Scaling these data to the whole brain, we created a backward linear regression model integrating several neuroimaging modalities11, thereby generating a brain-wide map of mitochondrial distribution and specialization that predicts mitochondrial characteristics in an independent brain region of the same donor brain. This new approach and the resulting MitoBrainMap of mitochondrial phenotypes provide a foundation for exploring the molecular energetic landscape that enables normal brain functions, relating it to neuroimaging data, and defining the subcellular basis for regionalized brain processes relevant to neuropsychiatric and neurodegenerative disorders.

PET Imaging of the Serotonin 1A Receptor in Major Depressive Disorder: Hierarchical Multivariate Analysis of [11C]WAY100635 Overcomes Outcome Measure Discrepancies.

The serotonin 1A receptor has been linked to both the pathophysiology of major depressive disorder (MDD) and the antidepressant action of serotonin reuptake inhibitors. Most PET studies of the serotonin 1A receptor in MDD used the receptor antagonist radioligand, [carbonyl-11C]WAY100635; however the interpretation of the combined results has been contentious owing to reports of higher or lower binding in MDD with different outcome measures. The reasons for these divergent results originate from several sources, including properties of the radiotracer itself, which complicate its quantification and interpretation; as well as from previously reported differences between MDD and healthy volunteers in both reference tissue binding and plasma free fraction, which are typically assumed not to differ. Recently, we have developed two novel hierarchical multivariate methods which we validated for the quantification and analysis of [11C]WAY100635, which show better accuracy and inferential efficiency compared to standard analysis approaches. Importantly, these new methods should theoretically be more resilient to many of the factors thought to have caused the discrepancies observed in previous studies. We sought to apply these methods in the largest [11C]WAY100635 sample to date, consisting of 160 individuals, including 103 MDD patients, of whom 50 were not-recently-medicated and 53 were antidepressant-exposed, as well as 57 healthy volunteers. While the outcome measure discrepancies were substantial using conventional univariate analysis, our multivariate analysis techniques instead yielded highly consistent results across PET outcome measures and across pharmacokinetic models, with all approaches showing higher serotonin 1A autoreceptor binding potential in the raphe nuclei of not-recently-medicated MDD patients relative to both healthy volunteers and antidepressant-exposed MDD patients. Moreover, with the additional precision of estimates afforded by this approach, we can show that while binding is also higher in projection areas in this group, these group differences are approximately half of those in the raphe nuclei, which are statistically distinguishable from one another. These results are consistent with the biological role of the serotonin 1A autoreceptor in the raphe nuclei in regulating serotonin neuron firing and release, and with preclinical and clinical evidence of deficient serotonin activity in MDD due to over expression of autoreceptors resulting from genetic and/or epigenetic effects. These results are also consistent with downregulation of autoreceptors as a mechanism of action of selective serotonin reuptake inhibitors. In summary, the results using multivariate analysis approaches therefore demonstrate both face and convergent validity, and may serve to provide a resolution and consensus interpretation for the disparate results of previous studies examining the serotonin 1A receptor in MDD.

Relationship of Major Depressive Disorder and Schizophrenia Polygenic Risk Scores to Suicide: A Comparison Between European and Asian Ancestry Populations.

Psychiatric diagnosis rates in suicide decedents appear higher in European ancestry populations compared with East Asians. Shared genetic components exist between major depressive disorder (MDD)/schizophrenia (SCZ) and suicide, but no study has compared these shared polygenic architectures between Europeans and East Asians. We compared polygenic risk scores (PRSs) for MDD/SCZ determined from large data sets specific to each ancestry in European and East Asian suicide decedent samples. MDD/SCZ PRSs appeared more prominent in European suicides compared with Japanese suicides. A greater coexistence of psychiatric disorders in European suicide decedents than in East Asian suicide decedents may be partly explained by genetics. Our results are limited by the smaller sample size of our suicide decedents and sample size disparities between the European discovery data set and the East Asian data set for MDD/SCZ, resulting in less statistical power to detect robust difference between the two ancestries.

Psychiatric diagnosis in suicides appears more common in Europeans than in East Asians.This is the first comparison of suicide genome-wide association studies between Europeans and East Asians.Major depressive disorder/schizophrenia polygenic risk scores for suicide were more significant for Europeans than for East Asians.

Acute Dissociation and Ketamine's Antidepressant and Anti-Suicidal Ideation Effects in a Midazolam-Controlled Trial.

OBJECTIVE: We sought to explore relationships of acute dissociative effects of intravenous ketamine with change in depression and suicidal ideation and with plasma metabolite levels in a randomized, midazolam-controlled trial. METHODS: Data from a completed trial in suicidal, depressed participants (n = 40) randomly assigned to ketamine was used to examine relationships between ketamine treatment-emergent dissociative and psychotomimetic symptoms with pre/post-infusion changes in suicidal ideation and depression severity. Nonparametric correlational statistics were used. These methods were also used to explore associations between dissociative or psychotomimetic symptoms and blood levels of ketamine and metabolites in a subset of participants (n = 28) who provided blood samples immediately post-infusion. RESULTS: Neither acute dissociative nor psychotomimetic effects of ketamine were associated with changes in suicidal ideation or depressive symptoms from pre- to post-infusion. Norketamine had a trend-level, moderate inverse correlation with dissociative symptoms on Day 1 post-injection (P = .064; P =.013 removing 1 outlier). Dehydronorketamine correlated with Clinician-Administered Dissociative States Scale scores at 40 minutes (P = .034), 230 minutes (P = .014), and Day 1 (P = .012). CONCLUSION: We did not find evidence that ketamine's acute, transient dissociative, or psychotomimetic effects are associated with its antidepressant or anti-suicidal ideation actions. The correlation of higher plasma norketamine with lower dissociative symptoms on Day 1 post-treatment suggests dissociation may be more an effect of the parent drug.

Decoding Suicide Decedent Profiles and Signs of Suicidal Intent Using Latent Class Analysis.

Importance: Suicide rates in the US increased by 35.6% from 2001 to 2021. Given that most individuals die on their first attempt, earlier detection and intervention are crucial. Understanding modifiable risk factors is key to effective prevention strategies. Objective: To identify distinct suicide profiles or classes, associated signs of suicidal intent, and patterns of modifiable risks for targeted prevention efforts. Design, Setting, and Participants: This cross-sectional study used data from the 2003-2020 National Violent Death Reporting System Restricted Access Database for 306 800 suicide decedents. Statistical analysis was performed from July 2022 to June 2023. Exposures: Suicide decedent profiles were determined using latent class analyses of available data on suicide circumstances, toxicology, and methods. Main Outcomes and Measures: Disclosure of recent intent, suicide note presence, and known psychotropic usage. Results: Among 306 800 suicide decedents (mean [SD] age, 46.3 [18.4] years; 239 627 males [78.1%] and 67 108 females [21.9%]), 5 profiles or classes were identified. The largest class, class 4 (97 175 [31.7%]), predominantly faced physical health challenges, followed by polysubstance problems in class 5 (58 803 [19.2%]), and crisis, alcohol-related, and intimate partner problems in class 3 (55 367 [18.0%]), mental health problems (class 2, 53 928 [17.6%]), and comorbid mental health and substance use disorders (class 1, 41 527 [13.5%]). Class 4 had the lowest rates of disclosing suicidal intent (13 952 [14.4%]) and leaving a suicide note (24 351 [25.1%]). Adjusting for covariates, compared with class 1, class 4 had the highest odds of not disclosing suicide intent (odds ratio [OR], 2.58; 95% CI, 2.51-2.66) and not leaving a suicide note (OR, 1.45; 95% CI, 1.41-1.49). Class 4 also had the lowest rates of all known psychiatric illnesses and psychotropic medications among all suicide profiles. Class 4 had more older adults (23 794 were aged 55-70 years [24.5%]; 20 100 aged ≥71 years [20.7%]), veterans (22 220 [22.9%]), widows (8633 [8.9%]), individuals with less than high school education (15 690 [16.1%]), and rural residents (23 966 [24.7%]). Conclusions and Relevance: This study identified 5 distinct suicide profiles, highlighting a need for tailored prevention strategies. Improving the detection and treatment of coexisting mental health conditions, substance and alcohol use disorders, and physical illnesses is paramount. The implementation of means restriction strategies plays a vital role in reducing suicide risks across most of the profiles, reinforcing the need for a multifaceted approach to suicide prevention.

Risk of suicide attempts and intentional self-harm on alprazolam.

BACKGROUND: From 2000-2021, U.S. suicide deaths have risen 36 %. Identification of pharmacological agents associated with increased suicide risk and safer alternatives may help reduce this trend. METHODS: An exposure-only within-subject time-to-event pharmacoepidemiologic study of the dynamic association between alprazolam treatment and suicide attempts over 2-years. Parallel analyses were conducted for diazepam, lorazepam and buspirone. Data for 2,495,520 patients were obtained from U.S. private insurance medical claims MarketScan from 2010 to 2019. FINDINGS: Alprazolam was associated with over a doubling of risk of suicide attempts (HR=2.21, 95 % CI=2.06,2.38). A duration-response analysis for the modal dose (0.5 mg) revealed a 5 % increase in suicidal events per additional month of treatment (HR=1.05, 95 % CI=1.04,1.07). Parallel analyses with long-acting (diazepam) and short-acting (lorazepam), found similar associations (diazepam HR=2.87, 95 % CI=2.56,3.21; lorazepam HR=1.83, 95 % CI=1.69,2.00), whereas the non-benzodiazepine anxiolytic, buspirone, showed significantly less risk (HR=1.25, 95 % CI=1.13,1.38), and no increased risk in patients with an attempt history (HR=1.05, 95 % CI=0.70,1.59). INTERPRETATION: This study confirmed an earlier signal linking alprazolam to increased suicide attempt risk. The increased risk extends to benzodiazepines in general, regardless of half-life and risk of withdrawal seizure. Buspirone appears to be a safer treatment than benzodiazepines, particularly in patients at increased risk for suicide.

A Human Brain Map of Mitochondrial Respiratory Capacity and Diversity.

Mitochondrial oxidative phosphorylation (OxPhos) powers brain activity1,2, and mitochondrial defects are linked to neurodegenerative and neuropsychiatric disorders3,4, underscoring the need to define the brain's molecular energetic landscape5-10. To bridge the cognitive neuroscience and cell biology scale gap, we developed a physical voxelization approach to partition a frozen human coronal hemisphere section into 703 voxels comparable to neuroimaging resolution (3×3×3 mm). In each cortical and subcortical brain voxel, we profiled mitochondrial phenotypes including OxPhos enzyme activities, mitochondrial DNA and volume density, and mitochondria-specific respiratory capacity. We show that the human brain contains a diversity of mitochondrial phenotypes driven by both topology and cell types. Compared to white matter, grey matter contains >50% more mitochondria. We show that the more abundant grey matter mitochondria also are biochemically optimized for energy transformation, particularly among recently evolved cortical brain regions. Scaling these data to the whole brain, we created a backward linear regression model integrating several neuroimaging modalities11, thereby generating a brain-wide map of mitochondrial distribution and specialization that predicts mitochondrial characteristics in an independent brain region of the same donor brain. This new approach and the resulting MitoBrainMap of mitochondrial phenotypes provide a foundation for exploring the molecular energetic landscape that enables normal brain functions, relating it to neuroimaging data, and defining the subcellular basis for regionalized brain processes relevant to neuropsychiatric and neurodegenerative disorders.

Knowledge-based quality assurance of a comprehensive set of organ at risk contours for head and neck radiotherapy.

Introduction: Manual review of organ at risk (OAR) contours is crucial for creating safe radiotherapy plans but can be time-consuming and error prone. Statistical and deep learning models show the potential to automatically detect improper contours by identifying outliers using large sets of acceptable data (knowledge-based outlier detection) and may be able to assist human reviewers during review of OAR contours. Methods: This study developed an automated knowledge-based outlier detection method and assessed its ability to detect erroneous contours for all common head and neck (HN) OAR types used clinically at our institution. We utilized 490 accurate CT-based HN structure sets from unique patients, each with forty-two HN OAR contours when anatomically present. The structure sets were distributed as 80% for training, 10% for validation, and 10% for testing. In addition, 190 and 37 simulated contours containing errors were added to the validation and test sets, respectively. Single-contour features, including location, shape, orientation, volume, and CT number, were used to train three single-contour feature models (z-score, Mahalanobis distance [MD], and autoencoder [AE]). Additionally, a novel contour-to-contour relationship (CCR) model was trained using the minimum distance and volumetric overlap between pairs of OAR contours to quantify overlap and separation. Inferences from single-contour feature models were combined with the CCR model inferences and inferences evaluating the number of disconnected parts in a single contour and then compared. Results: In the test dataset, before combination with the CCR model, the area under the curve values were 0.922/0.939/0.939 for the z-score, MD, and AE models respectively for all contours. After combination with CCR model inferences, the z-score, MD, and AE had sensitivities of 0.838/0.892/0.865, specificities of 0.922/0.907/0.887, and balanced accuracies (BA) of 0.880/0.900/0.876 respectively. In the validation dataset, with similar overall performance and no signs of overfitting, model performance for individual OAR types was assessed. The combined AE model demonstrated minimum, median, and maximum BAs of 0.729, 0.908, and 0.980 across OAR types. Discussion: Our novel knowledge-based method combines models utilizing single-contour and CCR features to effectively detect erroneous OAR contours across a comprehensive set of 42 clinically used OAR types for HN radiotherapy.

Microwave engineered NiZrO3@GNP as efficient electrode material for energy storage applications.

Supercapacitors (SCs) have emerged as attractive energy storage devices due to their rapid charge/discharge rates, long cycle life, and high-power density. However, the development of innovative electrode materials to achieve high-performance remains crucial to meet future requirements in supercapacitor technology. In this work, we have explored the potential of a microwave-engineered NiZrO3@GNP composite as a promising electrode material for SCs. A microwave assisted hydrothermal approach was adopted for the fabrication of the NiZrO3@GNP nanocomposite. Structural and morphological investigations showed its structural richness and its chemical compositions. When applied as a SC electrode, this innovative combination exhibits battery-like behaviour with higher specific capacity (577.63 C g-1) with good cyclic stability, and good performance. We have assembled an asymmetric-type two-electrode SC device and analysed its electrochemical features. This NiZrO3@GNP device exhibits the specific capacity of 47 C g-1 with capacitance retention of 70% after 2000 charge-discharge cycles. Further research on optimizing the synthesis process and exploring different device configurations could pave the way for even higher-performance supercapacitors in the future.

Brain and blood transcriptome profiles delineate common genetic pathways across suicidal ideation and suicide.

Human genetic studies indicate that suicidal ideation and behavior are both heritable. Most studies have examined associations between aberrant gene expression and suicide behavior, but behavior risk is linked to the severity of suicidal ideation. Through a gene network approach, this study investigates how gene co-expression patterns are associated with suicidal ideation and severity using RNA-seq data in peripheral blood from 46 live participants with elevated suicidal ideation and 46 with no ideation. Associations with the presence of suicidal ideation were found within 18 co-expressed modules (p < 0.05), as well as in 3 co-expressed modules associated with suicidal ideation severity (p < 0.05, not explained by severity of depression). Suicidal ideation presence and severity-related gene modules with enrichment of genes involved in defense against microbial infection, inflammation, and adaptive immune response were identified and investigated using RNA-seq data from postmortem brain that revealed gene expression differences with moderate effect sizes in suicide decedents vs. non-suicides in white matter, but not gray matter. Findings support a role of brain and peripheral blood inflammation in suicide risk, showing that suicidal ideation presence and severity are associated with an inflammatory signature detectable in blood and brain, indicating a biological continuity between ideation and suicidal behavior that may underlie a common heritability.

Intramuscular ketamine vs. midazolam for rapid risk-reduction in suicidal, depressed emergency patients: Clinical trial design and rationale.

Emergency department (ED) visits for suicidal ideation or behavior have been increasing in all age groups, particularly younger adults. A rapid-acting treatment to reduce suicidal thinking, adapted for ED use, is needed. Previous studies have shown a single dose of ketamine can improve depression and suicidal ideation within hours. However, most studies used 40 min intravenous infusions which can be impractical in a psychiatric ED. The ER-Ketamine study we describe here is a randomized midazolam-controlled clinical trial (RCT; NCT04640636) testing intramuscular (IM) ketamine's feasibility, safety, and effectiveness to rapidly reduce suicidal ideation and depression in a psychiatric ED. A pre-injection phase involves screening, informed consent, eligibility confirmation, and baseline assessment of suicidal ideation, depression, and comorbidities. The randomized double-blind IM injection is administered in the ED under research staff supervision, vital sign monitoring, pharmacokinetic blood sampling, and clinical assessments. The post-injection phase occurs on a psychiatric inpatient unit with follow-up research assessments through four weeks post-discharge. Outcome measures are feasibility, safety, and effects on suicidal ideation and depression at 24 h post-injection, and through follow-up. The target sample is N = 90 adults in a major depressive episode, assessed by ED clinicians as warranting hospitalization for suicide risk. Here we report design, rationale, and preliminary feasibility and safety for this ongoing study. Demographics of the 53 participants (ages 18 to 65 years) randomized to date suggest a diverse sample tending towards younger adults.