Trajectory of depressive symptoms over adolescence in autistic and neurotypical youth.

BACKGROUND: Adolescence coincides with a dramatic rise in the onset of psychiatric conditions including depression. Depression symptoms may be particularly prevalent and impairing for youth with autism spectrum disorder (ASD). While prior research suggests adolescence is associated with worsening depression symptoms for typically developing (TD) and autistic youth, it is unclear if they follow a similar course. METHOD: The study examined the trajectory of depressive symptoms in autistic and neurotypical youth over a 4-year longitudinal study using linear and logistic mixed effects models. In youth with clinically relevant depressive scores (t-score > 65), moderating factors (i.e., diagnosis, age, puberty, sex) were explored. During Year 1, the sample included 244 youth 10-to-13 years: 140 in the ASD group (36 females) and 104 in the TD group (46 females). RESULTS: Autistic youth had elevated depression scores compared to TD peers (p < 0.001) and females were higher than males in both groups (p = 0.001). There was significant diagnosis by age (p < 0.001) and diagnosis by pubertal stage (p < 0.05) interactions. In the ASD group, elevated depressive scores presented in early adolescence and decreased during middle adolescence and puberty, whereas the TD group showed the opposite trend with an increase in depression symptoms with advancing development. LIMITATIONS: Limitations include an unequal sex distribution (fewer females), non-representative autistic sample (e.g., cognition and race/ethnicity), and potential confound of the COVID-19 pandemic. CONCLUSIONS: Autistic youth present with higher rates of depressive symptoms early in development; yet, approaching middle adolescence and puberty, the symptom trajectory in the autistic youth declines coinciding with an increase in the TD youth. While group trajectories are divergent, they lead to similar levels of depression in late adolescence with higher symptoms in females. Findings suggest a period of quiescence in depressive symptomology influenced by biopsychosocial factors impacting affective profiles.

Gender diversity in autistic and neurotypical youth over adolescence and puberty: A longitudinal study.

Recent research in autism spectrum disorder (ASD) has suggested a higher prevalence of gender diversity in individuals diagnosed with ASD. Adolescence is a critical period for the consolidation of gender identity, yet the extent to which the experience of gender diversity is stable over adolescence and puberty in autistic youth is poorly understood. The aim of the study was to examine the consistency of gender diversity using the gender diversity screening questionnaire for self- and parent-report of youth (GDSQ-S, GDSQ-P) over a four-year longitudinal study of pubertal development in youth with ASD (N = 140, 36 assigned-female-at birth (AFAB)) and typical development (TD, N = 104, 58 assigned-male-at-birth [AMAB]) and their parents. The extent to which diagnosis (ASD vs. TD), assigned sex (AFAB vs. AMAB) and developmental level (age, puberty) predict GDSQ trajectory over time was explored. There was a significant diagnosis by sex-assigned-at-birth by age interaction for GDSQ-S Gender Diversity, p = 0.002, showing higher scores in autistic AFAB youth over adolescence, and TD AFAB showing initially lower, then increasing levels over adolescence. For GDSQ-P, Gender Incongruence was significantly different between the groups, p = 0.032, showing higher incongruence for autistic AFAB around age 10, decreasing between age 12-14 before increasing again, while TD AFAB evidence the inverse trend. AMAB trends were stable. The significant diagnostic, developmental and sex-based differences indicate AFAB youth experience greater gender diversity that evolves over development. Findings suggest gender identity formation is nuanced and may be influenced by pubertal progression, hormonal patterns, and psychosocial factors. Results underscore the need for enhanced understanding of the unique, dynamic profiles of females-assigned-at-birth.

Lifespan development of thalamic nuclei and characterizing thalamic nuclei abnormalities in schizophrenia using normative modeling.

Thalamic abnormalities have been repeatedly implicated in the pathophysiology of schizophrenia and other neurodevelopmental disorders. Uncovering the etiology of thalamic abnormalities and how they may contribute to illness phenotypes faces at least two obstacles. First, the typical developmental trajectories of thalamic nuclei and their association with cognition across the lifespan are largely unknown. Second, modest effect sizes indicate marked individual differences and pose a significant challenge to personalized medicine. To address these knowledge gaps, we characterized the development of thalamic nuclei volumes using normative models generated from the Human Connectome Project Lifespan datasets (5-100+ years), then applied them to an independent clinical cohort to determine the frequency of thalamic volume deviations in people with schizophrenia (17-61 years). Normative models revealed diverse non-linear age effects across the lifespan. Association nuclei exhibited negative age effects during youth but stabilized in adulthood until turning negative again with older age. Sensorimotor nuclei volumes remained relatively stable through youth and adulthood until also turning negative with older age. Up to 18% of individuals with schizophrenia exhibited abnormally small (i.e., below the 5th centile) mediodorsal and pulvinar volumes, and the degree of deviation, but not raw volumes, correlated with the severity of cognitive impairment. While case-control differences are robust, only a minority of patients demonstrate unusually small thalamic nuclei volumes. Normative modeling enables the identification of these individuals, which is a necessary step toward precision medicine.

Spatial nonstationarity of image noise in widefield optical imaging and its effects on cluster-based inference for resting-state functional connectivity.

BACKGROUND: Resting-state functional connectivity (RSFC) analysis with widefield optical imaging (WOI) is a potentially powerful tool to develop imaging biomarkers in mouse models of disease before translating them to human neuroimaging with functional magnetic resonance imaging (fMRI). The delineation of such biomarkers depends on rigorous statistical analysis. However, statistical understanding of WOI data is limited. In particular, cluster-based analysis of neuroimaging data depends on assumptions of spatial stationarity (i.e., that the distribution of cluster sizes under the null is equal at all brain locations). Whether actual data deviate from this assumption has not previously been examined in WOI. NEW METHOD: In this manuscript, we characterize the effects of spatial nonstationarity in WOI RSFC data and adapt a "two-pass" technique from fMRI to correct cluster sizes and mitigate spatial bias, both parametrically and nonparametrically. These methods are tested on multi-institutional data. RESULTS AND COMPARISON WITH EXISTING METHODS: We find that spatial nonstationarity has a substantial effect on inference in WOI RSFC data with false positives much more likely at some brain regions than others. This pattern of bias varies between imaging systems, contrasts, and mouse ages, all of which could affect experimental reproducibility if not accounted for. CONCLUSIONS: Both parametric and nonparametric corrections for nonstationarity result in significant improvements in spatial bias. The proposed methods are simple to implement and will improve the robustness of inference in optical neuroimaging data.

Transcriptional cartography integrates multiscale biology of the human cortex.

The cerebral cortex underlies many of our unique strengths and vulnerabilities, but efforts to understand human cortical organization are challenged by reliance on incompatible measurement methods at different spatial scales. Macroscale features such as cortical folding and functional activation are accessed through spatially dense neuroimaging maps, whereas microscale cellular and molecular features are typically measured with sparse postmortem sampling. Here, we integrate these distinct windows on brain organization by building upon existing postmortem data to impute, validate, and analyze a library of spatially dense neuroimaging-like maps of human cortical gene expression. These maps allow spatially unbiased discovery of cortical zones with extreme transcriptional profiles or unusually rapid transcriptional change which index distinct microstructure and predict neuroimaging measures of cortical folding and functional activation. Modules of spatially coexpressed genes define a family of canonical expression maps that integrate diverse spatial scales and temporal epochs of human brain organization - ranging from protein-protein interactions to large-scale systems for cognitive processing. These module maps also parse neuropsychiatric risk genes into subsets which tag distinct cyto-laminar features and differentially predict the location of altered cortical anatomy and gene expression in patients. Taken together, the methods, resources, and findings described here advance our understanding of human cortical organization and offer flexible bridges to connect scientific fields operating at different spatial scales of human brain research.

Enhanced Patient Portal Engagement Associated with Improved Weight Loss Outcomes in Post-Bariatric Surgery Patients.

Background: Bariatric surgery is an effective intervention for obesity, but it requires comprehensive postoperative self-management to achieve optimal outcomes. While patient portals are generally seen as beneficial in engaging patients in health management, the link between their use and post-bariatric surgery weight loss remains unclear. Objective: This study investigated the association between patient portal engagement and postoperative body mass index (BMI) reduction among bariatric surgery patients. Methods: This retrospective longitudinal study included patients who underwent Roux-en-Y gastric bypass (RYGB) or sleeve gastrectomy (SG) at Vanderbilt University Medical Center (VUMC) between January 2018 and March 2021. Using generalized estimating equations, we estimated the association between active days of postoperative patient portal use and the reduction of BMI percentage (%BMI) at 3, 6, and 12 months post-surgery. Covariates included duration since surgery, the patient's age at the time of surgery, gender, race and ethnicity, type of bariatric surgery, severity of comorbid conditions, and socioeconomic disadvantage. Results: The study included 1,415 patients, mostly female (80.9%), with diverse racial and ethnic backgrounds. 805 (56.9%) patients underwent RYGB and 610 (43.1%) underwent SG. By one-year post-surgery, the mean (SD) %BMI reduction was 31.1% (8.3%), and the mean (SD) number of patient portal active days was 61.0 (41.2). A significantly positive association was observed between patient portal engagement and %BMI reduction, with variations revealed over time. Each 10-day increment of active portal use was associated with a 0.57% ([95% CI: 0.42- 0.72], P < .001) and 0.35% ([95% CI: 0.22- 0.49], P < .001) %BMI reduction at 3 and 6 months postoperatively. The association was not statistically significant at 12 months postoperatively (ß=-0.07, [95% CI: -0.24- 0.09], P = .54). Various portal functions, including messaging, visits, my record, medical tools, billing, resources, and others, were positively associated with %BMI reduction at 3- and 6-months follow-ups. Conclusions: Greater patient portal engagement, which may represent stronger adherence to postoperative instructions, better self-management of health, and enhanced communication with care teams, was associated with improved postoperative weight loss. Future investigations are needed to identify important portal features that contribute to the long-term success of weight loss management.

Use of ECT for Children With and Without Catatonia: A Single-Site Retrospective Analysis.

OBJECTIVES: The objective study was to investigate the safety and efficacy of electroconvulsive therapy (ECT) in a retrospective cohort of pediatric patients. METHODS: A single-site retrospective analysis was conducted of patients aged younger than 18 years who received ECT in a private university hospital from January 28, 2012 to April 8, 2023. Treatment efficacy and adverse events were determined retrospectively through review of the medical record. RESULTS: A total of 36 pediatric patients met the inclusion criteria. Catatonia was the most common presenting indication for ECT, followed by psychosis and suicidal ideation. For all patients, Clinical Global Impressions-Improvement scale scores indicated that it was very likely for a subject to experience at least "much improvement" with the estimated probability of receiving a Clinical Global Impressions-Improvement scale score better than 3 of 0.852 (t.s. = 16.3; P < 0.001; 95% confidence interval, 0.711-0.931). All patients with catatonia demonstrated a positive clinical response and experienced a statistically significant reduction in total Bush-Francis Catatonia Rating Scale scores observed (t = 11.9; df = 20; SD = 6.3; P < 0.001; 95% confidence interval, 12.6-17.9). No significant adverse events were reported for any patient in the cohort. However, 14 (38.9%) patients experienced prolonged seizures, all of which were terminated with propofol (mean, 49.7 mg). CONCLUSIONS: This study provides further data supporting the safe and effective use of pediatric ECT in the treatment of various psychiatric conditions. However, more research is needed to determine the risk factors associated with prolonged seizures and the optimal seizure parameters in young people.

Smaller anterior hippocampal subfields in the early stage of psychosis.

Hippocampal volume is smaller in schizophrenia, but it is unclear when in the illness the changes appear and whether specific regions (anterior, posterior) and subfields (CA1, CA2/3, dentate gyrus, subiculum) are affected. Here, we used a high-resolution T2-weighted sequence specialized for imaging hippocampal subfields to test the hypothesis that anterior CA1 volume is lower in early psychosis. We measured subfield volumes across hippocampal regions in a group of 90 individuals in the early stage of a non-affective psychotic disorder and 70 demographically similar healthy individuals. We observed smaller volume in the anterior CA1 and dentate gyrus subfields in the early psychosis group. Our findings support models that implicate anterior CA1 and dentate gyrus subfield deficits in the mechanism of psychosis.

Study design features that improve effect sizes in cross-sectional and longitudinal brain-wide association studies.

Brain-wide association studies (BWAS) are a fundamental tool in discovering brain-behavior associations. Several recent studies showed that thousands of study participants are required to improve the replicability of BWAS because actual effect sizes are much smaller than those reported in smaller studies. Here, we perform analyses and meta-analyses of a robust effect size index (RESI) using 63 longitudinal and cross-sectional magnetic resonance imaging studies from the Lifespan Brain Chart Consortium (77,695 total scans) to demonstrate that optimizing study design is critical for improving standardized effect sizes and replicability in BWAS. A meta-analysis of brain volume associations with age indicates that BWAS with larger covariate variance have larger effect size estimates and that the longitudinal studies we examined have systematically larger standardized effect sizes than cross-sectional studies. We propose a cross-sectional RESI to adjust for the systematic difference in effect sizes between cross-sectional and longitudinal studies that allows investigators to quantify the benefit of conducting their study longitudinally. Analyzing age effects on global and regional brain measures from the United Kingdom Biobank and the Alzheimer's Disease Neuroimaging Initiative, we show that modifying longitudinal study design through sampling schemes to increase between-subject variability and adding a single additional longitudinal measurement per subject can improve effect sizes. However, evaluating these longitudinal sampling schemes on cognitive, psychopathology, and demographic associations with structural and functional brain outcome measures in the Adolescent Brain and Cognitive Development dataset shows that commonly used longitudinal models can, counterintuitively, reduce effect sizes. We demonstrate that the benefit of conducting longitudinal studies depends on the strengths of the between- and within-subject associations of the brain and non-brain measures. Explicitly modeling between- and within-subject effects avoids conflating the effects and allows optimizing effect sizes for them separately. These findings underscore the importance of considering study design features to improve the replicability of BWAS.

In-hospital catatonia, delirium, and coma and mortality: Results from the delirium and catatonia prospective cohort investigation.

BACKGROUND: Catatonia, a form of acute brain dysfunction typically linked with severe affective and psychotic disorders, occurs in critical illness with delirium and coma. Delirium and coma are associated with mortality, though catatonia's relationship with mortality is unclear. We aim to describe whether catatonia, delirium, and coma are associated with mortality. METHODS: We enrolled a convenience cohort of critically ill adults (N = 378) at an academic medical center. We assessed catatonia, delirium, and coma using the Bush-Francis Catatonia Rating Scale, the Confusion Assessment Method for the Intensive Care Unit and the Richmond Agitation-Sedation Scale, respectively. We tested the associations between previous day brain dysfunction state occurrence with in-hospital and one-year mortality using multivariable time-dependent risk models. Additionally, we tested the association between brain dysfunction duration and one-year mortality. RESULTS: Catatonia was not associated with death on the day after diagnosis during hospitalization, and neither previous catatonia occurrence nor duration was associated with one-year mortality. Delirium was not associated with death on any day following diagnosis during hospitalization, and neither previous delirium occurrence nor duration was associated with one-year mortality. The occurrence of coma was associated with death on any day after diagnosis during hospitalization (HR 2.30,CI 1.19-4.44,p = 0.014), as well as through one year following hospital discharge (HR 1.68,CI 1.09-2.59,p = 0.02). CONCLUSIONS: Coma, but neither catatonia nor delirium, was associated with future day in-hospital and one-year mortality. More research is needed to understand catatonia's clinical impact. Delirium results differ from existing literature likely due to cohort demographics and size. Coma results highlight the prognostic significance of suppressed arousal while critically ill.

Statistical analysis of single-cell protein data.

Immune modulation is considered a hallmark of cancer initiation and progression, with immune cell density being consistently associated with clinical outcomes of individuals with cancer. Multiplex immunofluorescence (mIF) microscopy combined with automated image analysis is a novel and increasingly used technique that allows for the assessment and visualization of the tumor microenvironment (TME). Recently, application of this new technology to tissue microarrays (TMAs) or whole tissue sections from large cancer studies has been used to characterize different cell populations in the TME with enhanced reproducibility and accuracy. Generally, mIF data has been used to examine the presence and abundance of immune cells in the tumor and stroma compartments; however, this aggregate measure assumes uniform patterns of immune cells throughout the TME and overlooks spatial heterogeneity. Recently, the spatial contexture of the TME has been explored with a variety of statistical methods. In this PSB workshop, speakers will present some of the state-of-the-art statistical methods for assessing the TIME from mIF data.

Molecular cartography uncovers evolutionary and microenvironmental dynamics in sporadic colorectal tumors.

Colorectal cancer exhibits dynamic cellular and genetic heterogeneity during progression from precursor lesions toward malignancy. Analysis of spatial multi-omic data from 31 human colorectal specimens enabled phylogeographic mapping of tumor evolution that revealed individualized progression trajectories and accompanying microenvironmental and clonal alterations. Phylogeographic mapping ordered genetic events, classified tumors by their evolutionary dynamics, and placed clonal regions along global pseudotemporal progression trajectories encompassing the chromosomal instability (CIN+) and hypermutated (HM) pathways. Integrated single-cell and spatial transcriptomic data revealed recurring epithelial programs and infiltrating immune states along progression pseudotime. We discovered an immune exclusion signature (IEX), consisting of extracellular matrix regulators DDR1, TGFBI, PAK4, and DPEP1, that charts with CIN+ tumor progression, is associated with reduced cytotoxic cell infiltration, and shows prognostic value in independent cohorts. This spatial multi-omic atlas provides insights into colorectal tumor-microenvironment co-evolution, serving as a resource for stratification and targeted treatments.

Investigating Social Competence in a Pilot Randomized Clinical Trial of a Theatre-Based Intervention Enhanced for Adults with Autism Spectrum Disorder.

Autism spectrum disorder (ASD) is characterized by challenges in social competence that persist in adulthood, yet few treatment options exist. A pilot randomized clinical trial (RCT) of a peer-mediated, theatre-based intervention with established efficacy in youth with ASD was examined in autistic adults. The final sample consisted of forty-seven 18-to-40-year-old participants randomized to the experimental (EXP N = 23) or waitlist control (WLC N = 24) condition. A multimodal, social interdependent model was employed to examine social competence changes in brain (incidental face memory (IFM) using event-related potentials), cognition (Wechsler Memory Scale-III), behavior (Contextual Assessment of Social Skills) and function (Social Responsiveness Scale (SRS); Adaptive Behavior Assessment Scale (ABAS) Social Composite). Using analysis of covariance in which pretest was controlled in the model, posttest between-group differences were observed on IFM (p = 0.016, η2 = 0.139, d = 0.79) and several social and adaptive functional (SRS, ABAS) outcomes in social communication and interaction (SCI) (p = 0.019, η2 = 0.121, d = -00.45), communication (p = 0.044 η2 = 0.09, d = -00.31), and motivation (p = 0.001, η2 = 0.229, d = -0.79) domains. At two-month follow-up, gains in social motivation remained (p = 0.041, η2 = 0.100, d = -0.77). The results offer preliminary support for a unique theatre-based social skills intervention for autistic adults who have few treatment options to enhance social competence. The trial was pre-registered with ClinicalTrials.gov (Identifier: NCT04349644).

Network Enrichment Significance Testing in Brain-Phenotype Association Studies.

Functional networks often guide our interpretation of spatial maps of brain-phenotype associations. However, methods for assessing enrichment of associations within networks of interest have varied in terms of both scientific rigor and underlying assumptions. While some approaches have relied on subjective interpretations, others have made unrealistic assumptions about the spatial structure of imaging data, leading to inflated false positive rates. We seek to address this gap in existing methodology by borrowing insight from a method widely used in genomics research for testing enrichment of associations between a set of genes and a phenotype of interest. We propose Network Enrichment Significance Testing (NEST), a flexible framework for testing the specificity of brain-phenotype associations to functional networks or other sub-regions of the brain. We apply NEST to study phenotype associations with structural and functional brain imaging data from a large-scale neurodevelopmental cohort study.

GammaGateR: semi-automated marker gating for single-cell multiplexed imaging.

Motivation: Multiplexed immunofluorescence (mIF) is an emerging assay for multichannel protein imaging that can decipher cell-level spatial features in tissues. However, existing automated cell phenotyping methods, such as clustering, face challenges in achieving consistency across experiments and often require subjective evaluation. As a result, mIF analyses often revert to marker gating based on manual thresholding of raw imaging data. Results: To address the need for an evaluable semi-automated algorithm, we developed GammaGateR, an R package for interactive marker gating designed specifically for segmented cell-level data from mIF images. Based on a novel closed-form gamma mixture model, GammaGateR provides estimates of marker-positive cell proportions and soft clustering of marker-positive cells. The model incorporates user-specified constraints that provide a consistent but slide-specific model fit. We compared GammaGateR against the newest unsupervised approach for annotating mIF data, employing two colon datasets and one ovarian cancer dataset for the evaluation. We showed that GammaGateR produces highly similar results to a silver standard established through manual annotation. Furthermore, we demonstrated its effectiveness in identifying biological signals, achieved by mapping known spatial interactions between CD68 and MUC5AC cells in the colon and by accurately predicting survival in ovarian cancer patients using the phenotype probabilities as input for machine learning methods. GammaGateR is a highly efficient tool that can improve the replicability of marker gating results, while reducing the time of manual segmentation. Availability and Implementation: The R package is available at https://github.com/JiangmeiRubyXiong/GammaGateR.

Hippocampal Network Dysfunction in Early Psychosis: A 2-Year Longitudinal Study.

Background: Hippocampal abnormalities are among the most consistent findings in schizophrenia. Numerous studies have reported deficits in hippocampal volume, function, and connectivity in the chronic stage of illness. While hippocampal volume and function deficits are also present in the early stage of illness, there is mixed evidence of both higher and lower functional connectivity. Here, we use graph theory to test the hypothesis that hippocampal network connectivity is broadly lowered in early psychosis and progressively worsens over 2 years. Methods: We examined longitudinal resting-state functional connectivity in 140 participants (68 individuals in the early stage of psychosis, 72 demographically similar healthy control individuals). We used an anatomically driven approach to quantify hippocampal network connectivity at 2 levels: 1) a core hippocampal-medial temporal lobe cortex (MTLC) network; and 2) an extended hippocampal-cortical network. Group and time effects were tested in a linear mixed effects model. Results: Early psychosis patients showed elevated functional connectivity in the core hippocampal-MTLC network, but contrary to our hypothesis, did not show alterations within the broader hippocampal-cortical network. Hippocampal-MTLC network hyperconnectivity normalized longitudinally and predicted improvement in positive symptoms but was not associated with increasing illness duration. Conclusions: These results show abnormally elevated functional connectivity in a core hippocampal-MTLC network in early psychosis, suggesting that selectively increased hippocampal signaling within a localized cortical circuit may be a marker of the early stage of psychosis. Hippocampal-MTLC hyperconnectivity could have prognostic and therapeutic implications.

The developmental trajectory of diurnal cortisol in autistic and neurotypical youth.

Increasing age and puberty affect the hypothalamic pituitary adrenal (HPA) axis maturation, which is likely associated with an increase in environmental demands (e.g., social) and vulnerability for the onset of psychiatric conditions (e.g., depression). There is limited research as to whether such patterns are consonant in youth with autism spectrum disorder (ASD), a condition marked by social challenges, dysregulation of the HPA axis, and higher rates of depression setting the stage for enhanced vulnerability during this developmental period.The current study interrogated diurnal cortisol by examining (1) cortisol expression longitudinally over the pubertal transition between autistic and neurotypical youth, (2) the trajectory of diurnal cortisol and the unique contributions of age vs. puberty, and (3) potential sex differences. As hypothesized, results indicate autistic compared to typically developing youth demonstrate a shallower diurnal slope and elevated evening cortisol. These differences were in the context of higher cortisol and flatter rhythms based on age and pubertal development. Also, sex-based differences emerged such that females in both groups had higher cortisol, flatter slopes, and higher evening cortisol than males. The results show that despite the trait-like stability of diurnal cortisol, HPA maturation is impacted by age, puberty, sex, as well as an ASD diagnosis.

Alternative psychopharmacologic treatments for pediatric catatonia: a retrospective analysis.

Introduction: Pediatric catatonia is a highly co-morbid condition with treatment options often limited to electroconvulsive therapy (ECT) or lorazepam. However, lorazepam may not be readily available, and access to ECT is limited by restrictive legislation and stigma. This study aims to provide alternative treatment options for pediatric catatonia. Methods: The study involved a single-site retrospective analysis of a private university hospital in the southern United States. The study included patients under eighteen with catatonia who received psychopharmacologic treatment with an agent other than lorazepam. The patients were evaluated with the Bush-Francis Catatonia Rating Scale (BFCRS), Kanner Catatonia Severity Scale (KCS), and Kanner Catatonia Examination (KCE) at the time of initial evaluation and upon stabilization. A retrospective clinical global impressions-improvement (CGI-I) score was assigned by four authors. Results: 102 pediatric patients diagnosed with catatonia were identified, and 31 met criteria for the study. 20 (65%) were white, 6 (19%) were Black, 4 (13%) were Hispanic, and 1 (3%) were Indian. Most patients (N = 18; 58%) were insured by Medicaid. The mean age at the time of catatonia diagnosis was 13.5 years. All patients were stabilized on either clonazepam or diazepam, with 21 (68%) requiring treatment with an additional medication of either an anti-epileptic, N-methyl-D-aspartate (NMDA) receptor antagonist, and aripiprazole or clozapine. Statistically significant reductions in the BFCRS [t = 11.2, df = 30, std = 6.3, p < 0.001, 95% CI = (7.8, 15.1)], KCS [t = 4.6, df = 38, p < 0.001, 95% CI = (12.0, 31.0)], and KCE [t = 7.8, df = 30, std = 1.8, p < 0.001, 95% CI = (1.9, 3.2)] were observed. For CGI-I the results showed that the estimated probability of observing a score better than no change (>4) is 0.976 [t.s. = 43.2, p < 0.001, 95% CI = (0.931,0.992)], indicating the average subject is expected to experience some improvement. Discussion: In conclusion, all patients responded to these treatments with improvement in their catatonic symptoms. Alternative pharmacologic interventions for catatonia, including benzodiazepines other than lorazepam, valproic acid, NMDA receptor antagonists, and atypical antipsychotics were safe and effective in treating catatonia in this population.

Statistical Analysis of Multiplex Immunofluorescence and Immunohistochemistry Imaging Data.

Advances in multiplexed single-cell immunofluorescence (mIF) and multiplex immunohistochemistry (mIHC) imaging technologies have enabled the analysis of cell-to-cell spatial relationships that promise to revolutionize our understanding of tissue-based diseases and autoimmune disorders. Multiplex images are collected as multichannel TIFF files; then denoised, segmented to identify cells and nuclei, normalized across slides with protein markers to correct for batch effects, and phenotyped; and then tissue composition and spatial context at the cellular level are analyzed. This chapter discusses methods and software infrastructure for image processing and statistical analysis of mIF/mIHC data.