Validation of ketamine as a pharmacological model of thalamic dysconnectivity across the illness course of schizophrenia.

N-methyl-D-aspartate receptor (NMDAR) hypofunction is a leading pathophysiological model of schizophrenia. Resting-state functional magnetic resonance imaging (rsfMRI) studies demonstrate a thalamic dysconnectivity pattern in schizophrenia involving excessive connectivity with sensory regions and deficient connectivity with frontal, cerebellar, and thalamic regions. The NMDAR antagonist ketamine, when administered at sub-anesthetic doses to healthy volunteers, induces transient schizophrenia-like symptoms and alters rsfMRI thalamic connectivity. However, the extent to which ketamine-induced thalamic dysconnectivity resembles schizophrenia thalamic dysconnectivity has not been directly tested. The current double-blind, placebo-controlled study derived an NMDAR hypofunction model of thalamic dysconnectivity from healthy volunteers undergoing ketamine infusions during rsfMRI. To assess whether ketamine-induced thalamic dysconnectivity was mediated by excess glutamate release, we tested whether pre-treatment with lamotrigine, a glutamate release inhibitor, attenuated ketamine's effects. Ketamine produced robust thalamo-cortical hyper-connectivity with sensory and motor regions that was not reduced by lamotrigine pre-treatment. To test whether the ketamine thalamic dysconnectivity pattern resembled the schizophrenia pattern, a whole-brain template representing ketamine's thalamic dysconnectivity effect was correlated with individual participant rsfMRI thalamic dysconnectivity maps, generating "ketamine similarity coefficients" for people with chronic (SZ) and early illness (ESZ) schizophrenia, individuals at clinical high-risk for psychosis (CHR-P), and healthy controls (HC). Similarity coefficients were higher in SZ and ESZ than in HC, with CHR-P showing an intermediate trend. Higher ketamine similarity coefficients correlated with greater hallucination severity in SZ. Thus, NMDAR hypofunction, modeled with ketamine, reproduces the thalamic hyper-connectivity observed in schizophrenia across its illness course, including the CHR-P period preceding psychosis onset, and may contribute to hallucination severity.

Thalamic dysconnectivity in the psychosis risk syndrome and early illness schizophrenia.

BACKGROUND: Schizophrenia (SZ) is associated with thalamic dysconnectivity. Compared to healthy controls (HCs), individuals with SZ have hyperconnectivity with sensory regions, and hypoconnectivity with cerebellar, thalamic, and prefrontal regions. Despite replication of this pattern in chronically ill individuals, less is known about when these abnormalities emerge in the illness course and if they are present prior to illness onset. METHODS: Resting-state functional magnetic resonance imaging data were collected from psychosis risk syndrome (PRS) youth (n = 45), early illness SZ (ESZ) (n = 74) patients, and HCs (n = 85). Age-adjusted functional connectivity, seeded from the thalamus, was compared among the groups. RESULTS: Significant effects of group were observed in left and right middle temporal regions, left and right superior temporal regions, left cerebellum, and bilateral thalamus. Compared to HCs, ESZ demonstrated hyperconnectivity to all temporal lobe regions and reduced connectivity with cerebellar, anterior cingulate, and thalamic regions. Compared to HCs, PRS demonstrated hyperconnectivity with the left and right middle temporal regions, and hypoconnectivity with the cerebellar and other thalamic regions. Compared to PRS participants, ESZ participants were hyperconnected to temporal regions, but did not differ from PRS in hypoconnectivity with cerebellar and thalamic regions. Thalamic dysconnectivity was unrelated to positive symptom severity in ESZ or PRS groups. CONCLUSIONS: PRS individuals demonstrated an intermediate level of thalamic dysconnectivity, whereas ESZ showed a pattern consistent with prior observations in chronic samples. These cross-sectional findings suggest that thalamic dysconnectivity may occur prior to illness onset and become more pronounced in early illness stages.

Effectiveness of the family-based model of dialectical behavior therapy for both suicidal adolescents and young adults in an academic medical center.

BACKGROUND: Dialectical behavior therapy (DBT) is an effective approach to decreasing suicidal behaviors; the adapted, family-based model for adolescents (through 18 years old; DBT-A) also demonstrates efficacy. Data on higher dropout rates based on age, initial research on DBT with young adults in the community, and the theory that underlies DBT suggest that adaptations may also be appropriate for young adults. This study examines the effectiveness of DBT-A, presents preliminary data on delivering DBT-A to young adults (ages 18-26), and compares clinical characteristics, service utilization, and outcomes to adolescent clients (ages 13-17) to guide clinical considerations and future research on implementing DBT-A. METHODS: Data were collected from a DBT-A clinic and included results from semi-structured diagnostic interviews, chart review, and scores on self-report measures. The Suicide Ideation Questionnaire and Beck Depression Inventory (BDI), given at program entry, after completion of one rotation through the skills modules, and at graduation, were used to evaluate outcomes. Outcomes were benchmarked against prior DBT-A trials. Adolescents' and young adults' clinical characteristics, service utilization, and outcomes were compared. RESULTS: The effect size observed was smaller than in efficacy trials. Few differences were observed between teens (n = 87) and young adults (n = 45). Young adults were more likely to have participated in intensive services before DBT-A. They participated in fewer family sessions and graduated in fewer months compared to teens. CONCLUSION: This study supports the use of the family-based model of DBT for suicidal teens and young adults although future research is needed to improve the effectiveness of this model when implemented in real-world settings.

Deficient auditory predictive coding during vocalization in the psychosis risk syndrome and in early illness schizophrenia: the final expanded sample.

BACKGROUND: During vocalization, efference copy/corollary discharge mechanisms suppress the auditory cortical response to self-generated sounds. Previously, we found attenuated vocalization-related auditory cortical suppression in psychosis and a similar trend in the psychosis risk syndrome. Here, we report data from the final sample of early illness schizophrenia patients (ESZ), individuals at clinical high risk for psychosis (CHR), and healthy controls (HC). METHODS: Event-related potentials (ERP) were recorded from ESZ (n = 84), CHR (n = 71), and HC (n = 103) participants during a vocalization paradigm. The N1 ERP component was elicited during production (Talk) and playback (Listen) of vocalization. Age effects on N1 suppression (Talk-Listen), Talk N1, and Listen N1 were compared across groups. N1 measures were adjusted for normal aging before testing for group differences. RESULTS: Both ESZ and CHR groups showed reduced Talk-Listen N1 suppression relative to HC, but did not differ from each other. Listen N1 was reduced in ESZ, but not in CHR, relative to HC. Deficient Talk-Listen N1 suppression was associated with greater unusual thought content in CHR individuals. N1 suppression increased with age in HC (12-36 years), and while CHR individuals showed a similar age-related increase, no such relationship was evident in ESZ. CONCLUSIONS: Putative efference copy/corollary discharge-mediated auditory cortical suppression during vocalization is deficient in ESZ and precedes psychosis onset, particularly in CHR individuals with greater unusual thought content. Furthermore, this suppression increases from adolescence through early adulthood, likely reflecting the effects of normal brain maturation. This maturation effect is disrupted in ESZ, presumably due to countervailing illness effects.

Understanding clothed buried remains: the analysis of decomposition fluids and their influence on clothing in model burial environments.

Previous studies of fabric degradation have shown promising results for post-mortem interval estimations based on differences in the degradation states of clothing in the presence of decomposing remains. It is crucial to determine if a body was present when using the degradation state as an indicator of time since death. For this study, fabric samples from buried pig remains were collected and analyzed using attenuated total reflectance Fourier transform infrared spectroscopy and chromatography- mass spectrometry. Three different fabrics were investigated; 100% cotton, 100% polyester and a polyester-cotton blend. Distinct visual changes were observed between the experimental and control graves, with the fabrics in the control grave degrading more rapidly. There was also a difference between the fabric types, whereby the natural fabrics degraded much faster than the synthetic ones. Principal component analysis was used to determine that the cotton control samples could be statistically separated based on their degradation state. The presence of lipids and proteins were useful for separating "wetter" graves from those drier in nature as well as the control graves. Clothing evidence was demonstrated to provide quantitative time since death information, as well as indicating the decomposition site in the event of intentional or unintentional movement.

Dynamic functional connectivity impairments in early schizophrenia and clinical high-risk for psychosis.

Individuals at clinical high-risk (CHR) for psychosis are characterized by attenuated psychotic symptoms. Only a minority of CHR individuals convert to full-blown psychosis. Therefore, there is a strong interest in identifying neurobiological abnormalities underlying the psychosis risk syndrome. Dynamic functional connectivity (DFC) captures time-varying connectivity over short time scales, and has the potential to reveal complex brain functional organization. Based on resting-state functional magnetic resonance imaging (fMRI) data from 70 healthy controls (HCs), 53 CHR individuals, and 58 early illness schizophrenia (ESZ) patients, we applied a novel group information guided ICA (GIG-ICA) to estimate inherent connectivity states from DFC, and then investigated group differences. We found that ESZ patients showed more aberrant connectivities and greater alterations than CHR individuals. Results also suggested that disease-related connectivity states occurred in CHR and ESZ groups. Regarding the dominant state with the highest contribution to dynamic connectivity, ESZ patients exhibited greater impairments than CHR individuals primarily in the cerebellum, frontal cortex, thalamus and temporal cortex, while CHR and ESZ populations shared common aberrances mainly in the supplementary motor area, parahippocampal gyrus and postcentral cortex. CHR-specific changes were also found in the connections between the superior frontal gyrus and calcarine cortex in the dominant state. Our findings suggest that CHR individuals generally show an intermediate functional connectivity pattern between HCs and SZ patients but also have unique connectivity alterations.

Reducing variation in decomposition odour profiling using comprehensive two-dimensional gas chromatography.

Challenges in decomposition odour profiling have led to variation in the documented odour profile by different research groups worldwide. Background subtraction and use of controls are important considerations given the variation introduced by decomposition studies conducted in different geographical environments. The collection of volatile organic compounds (VOCs) from soil beneath decomposing remains is challenging due to the high levels of inherent soil VOCs, further confounded by the use of highly sensitive instrumentation. This study presents a method that provides suitable chromatographic resolution for profiling decomposition odour in soil by comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry using appropriate controls and field blanks. Logarithmic transformation and t-testing of compounds permitted the generation of a compound list of decomposition VOCs in soil. Principal component analysis demonstrated the improved discrimination between experimental and control soil, verifying the value of the data handling method. Data handling procedures have not been well documented in this field and standardisation would thereby reduce misidentification of VOCs present in the surrounding environment as decomposition byproducts. Uniformity of data handling and instrumental procedures will reduce analytical variation, increasing confidence in the future when investigating the effect of taphonomic variables on the decomposition VOC profile.

Detection of decomposition volatile organic compounds in soil following removal of remains from a surface deposition site.

PURPOSE: Cadaver-detection dogs use volatile organic compounds (VOCs) to search for human remains including those deposited on or beneath soil. Soil can act as a sink for VOCs, causing loading of decomposition VOCs in the soil following soft tissue decomposition. The objective of this study was to chemically profile decomposition VOCs from surface decomposition sites after remains were removed from their primary location. METHODS: Pig carcasses were used as human analogues and were deposited on a soil surface to decompose for 3 months. The remains were then removed from each site and VOCs were collected from the soil for 7 months thereafter and analyzed by comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry (GC×GC-TOFMS). RESULTS: Decomposition VOCs diminished within 6 weeks and hydrocarbons were the most persistent compound class. Decomposition VOCs could still be detected in the soil after 7 months using Principal Component Analysis. CONCLUSIONS: This study demonstrated that the decomposition VOC profile, while detectable by GC×GC-TOFMS in the soil, was considerably reduced and altered in composition upon removal of remains. Chemical reference data is provided by this study for future investigations of canine alert behavior in scenarios involving scattered or scavenged remains.

Correction to "Insights into the Effects of Violating Statistical Assumptions for Dimensionality Reduction for Chemical "-omics" Data with Multiple Explanatory Variables".

[This corrects the article DOI: 10.1021/acsomega.3c01613.].

Adjustment of Regional Cortical Thickness Measures for Global Cortical Thickness Obscures Deficits Across the Schizophrenia Spectrum: A Cautionary Note about Normative Modeling of Brain Imaging Data.

Recent neuroimaging studies and publicly-disseminated analytic tools advocate that regional morphometric analyses covary for global thickness. We empirically demonstrate that this statistical approach severely underestimates regional thickness dysmorphology in psychiatric disorders. Study 1 included 90 healthy controls, 51 clinical high-risk for psychosis, and 78 early illness schizophrenia participants. Study 2 included 56 healthy controls, 83 non-affective psychosis, and 30 affective psychosis participants. We examined global and regional thickness correlations, global thickness group differences, and regional thickness group differences with/without global thickness covariation. Global and regional thickness were strongly correlated across groups. Global thickness was lower in schizophrenia-spectrum groups versus other groups. Regional thickness deficits in schizophrenia-spectrum groups were attenuated/eliminated with global thickness covariation. Depriving regional thickness of its shared variance with global thickness removes disease-related effects. This statistical method results in erroneous conclusions that regional thickness is normal in disorders like schizophrenia or clinical high-risk syndrome.

Brain Age Gap in Early Illness Schizophrenia and the Clinical High-Risk Syndrome: Associations With Experiential Negative Symptoms and Conversion to Psychosis.

BACKGROUND AND HYPOTHESIS: Brain development/aging is not uniform across individuals,spawning efforts to characterize brain age from a biological perspective to model the effects of disease and maladaptive life processes on the brain. The brain age gap represents the discrepancy between estimated brain biological age and chronological age (in this case, based on structural magnetic resonance imaging, MRI). Structural MRI studies report an increased brain age gap (biological age > chronological age) in schizophrenia, with a greater brain age gap related to greater negative symptom severity. Less is known regarding the nature of this gap early in schizophrenia (ESZ), if this gap represents a psychosis conversion biomarker in clinical high-risk (CHR-P) individuals, and how altered brain development and/or agingmap onto specific symptom facets. STUDY DESIGN: Using structural MRI, we compared the brain age gap among CHR-P (n = 51), ESZ (n = 78), and unaffected comparison participants (UCP; n = 90), and examined associations with CHR-P psychosis conversion (CHR-P converters n = 10; CHR-P non-converters; n = 23) and positive and negative symptoms. STUDY RESULTS: ESZ showed a greater brain age gap relative to UCP and CHR-P (Ps < .010). CHR-P individuals who converted to psychosis showed a greater brain age gap (P = .043) relative to CHR-P non-converters. A larger brain age gap in ESZ was associated with increased experiential (P = .008), but not expressive negative symptom severity. CONCLUSIONS: Consistent with schizophrenia pathophysiological models positing abnormal brain maturation, results suggest abnormal brain development is present early in psychosis. An increased brain age gap may be especially relevant to motivational and functional deficits in schizophrenia.

The use of lipids from textiles as soft-tissue biomarkers of human decomposition.

The ability to determine the post-mortem interval (PMI) in complex death investigations involving human remains, is a vital task faced by law enforcement. Establishing the PMI in a case can significantly aid in the reconstruction of forensically relevant events surrounding that death. However, due to the complexities surrounding the decomposition of human remains, the determination of the PMI still remains a challenge in some cases. Thus, the identification of biomarkers of human decomposition are an emerging, and essential, area of research. Previous studies have also demonstrated great success in the use of textiles as a host to indirectly capture decomposition by-products. This study reports the successful adaptation and optimisation of an analytical chemical workflow for the targeted analysis of lipids from textiles associated with decomposing human remains using gas-chromatography (GC) coupled with tandem mass spectrometry (MS/MS). This study discusses novel information regarding the complex challenges of matrix effects observed with decomposition samples. In addition, the first lipid profiles obtained from textiles associated with two decomposing human donors from the Australian Facility for Taphonomic Experimental Research (AFTER) using GC-MS/MS are presented.

A forensically validated genetic toolkit for the species and lineage identification of the highly trafficked shingleback lizard (Tiliqua rugosa).

Shingleback lizards (Tiliqua rugosa) are among the most trafficked native fauna from Australia in the illegal pet trade. There are four morphologically recognised subspecies of shinglebacks, all with differing overseas market values. Shinglebacks from different geographic locales are often trafficked and housed together, which may complicate identifying the State jurisdiction where the poaching event occurred. Additionally, shinglebacks can be housed and trafficked with other species within the same genus, which may complicate DNA analysis, especially in scenarios where indirect evidence (e.g. swabs, faeces) is taken for analysis. In this study, a forensic genetic toolkit was designed and validated to target shingleback DNA for species identification and geographic origin. To do this, field sampling across Australia was conducted to expand the phylogeographic sampling of shinglebacks across their species range and include populations suspected to be poaching hotspots. A commonly used universal reptile primer set (ND4/LEU) was then validated for use in forensic casework related to the genus Tiliqua. Two additional ND4 primer sets were designed and validated. The first primer set was designed and demonstrated to preferentially amplify an ∼510 bp region of the genus Tiliqua over other reptiles and builds on existing data to expand the available phylogeographic database. The second primer set was designed and demonstrated to solely amplify an ∼220 bp region of T. rugosa ND4 over any other reptile species. Through the validation process, all primers were demonstrated to amplify T. rugosa DNA from a variety of sample types (e.g. degraded, low quality and mixed). Two of the primer sets were able to distinguish the genetic lineage of T. rugosa from the phylogeographic database. This work provides the first forensically validated toolkit and phylogeographic genetic database for Squatmate lizards.

The use of generalized linear mixed models to investigate postmortem lipids in textiles.

Human remains are oftentimes located with textile materials, making them a ubiquitous source of physical evidence. Human remains are also frequently discovered in outdoor environments, increasing the exposure to scavenging activity and soft-tissue decomposition. In such cases, postmortem interval (PMI) estimations can be challenging for investigators when attempting to use traditional methods for reconstructive purposes. Lipid analysis is an emerging area of research in forensic taphonomy, with recent works demonstrating success with the detection and monitoring of lipids over time. In this work, generalized linear mixed models (GLMMs) were utilized to perform rigorous statistical analyses on 30 lipid outcomes in combination with accumulated-degree-days (ADD). The results of this study were consistent with recent works, indicating oleic and palmitic acids to be the most suitable lipids in textiles to target for future use as soft-tissue biomarkers of human decomposition. Interspecies differences between humans and pigs were also addressed in this work.

Insights into the Effects of Violating Statistical Assumptions for Dimensionality Reduction for Chemical "-omics" Data with Multiple Explanatory Variables.

Biological volatilome analysis is inherently complex due to the considerable number of compounds (i.e., dimensions) and differences in peak areas by orders of magnitude, between and within compounds found within datasets. Traditional volatilome analysis relies on dimensionality reduction techniques which aid in the selection of compounds that are considered relevant to respective research questions prior to further analysis. Currently, compounds of interest are identified using either supervised or unsupervised statistical methods which assume the data residuals are normally distributed and exhibit linearity. However, biological data often violate the statistical assumptions of these models related to normality and the presence of multiple explanatory variables which are innate to biological samples. In an attempt to address deviations from normality, volatilome data can be log transformed. However, whether the effects of each assessed variable are additive or multiplicative should be considered prior to transformation, as this will impact the effect of each variable on the data. If assumptions of normality and variable effects are not investigated prior to dimensionality reduction, ineffective or erroneous compound dimensionality reduction can impact downstream analyses. It is the aim of this manuscript to assess the impact of single and multivariable statistical models with and without the log transformation to volatilome dimensionality reduction prior to any supervised or unsupervised classification analysis. As a proof of concept, Shingleback lizard (Tiliqua rugosa) volatilomes were collected across their species distribution and from captivity and were assessed. Shingleback volatilomes are suspected to be influenced by multiple explanatory variables related to habitat (Bioregion), sex, parasite presence, total body volume, and captive status. This work determined that the exclusion of relevant multiple explanatory variables from analysis overestimates the effect of Bioregion and the identification of significant compounds. The log transformation increased the number of compounds that were identified as significant, as did analyses that assumed that residuals were normally distributed. Among the methods considered in this work, the most conservative form of dimensionality reduction was achieved through analyzing untransformed data using Monte Carlo tests with multiple explanatory variables.

Cortical and subcortical brain morphometry abnormalities in youth at clinical high-risk for psychosis and individuals with early illness schizophrenia.

Neuroimaging studies have documented morphometric brain abnormalities in schizophrenia, but less is known about them in individuals at clinical high-risk for psychosis (CHR-P), including how they compare with those observed in early schizophrenia (ESZ). Accordingly, we implemented multivariate profile analysis of regional morphometric profiles in CHR-P (n = 89), ESZ (n = 93) and healthy controls (HC; n = 122). ESZ profiles differed from HC and CHR-P profiles, including 1) cortical thickness: significant level reduction and regional non-parallelism reflecting widespread thinning, except for entorhinal and pericalcarine cortex, 2) basal ganglia volume: significant level increase and regional non-parallelism reflecting larger caudate and pallidum, and 3) ventricular volume: significant level increase with parallel regional profiles. CHR-P and ESZ cerebellar profiles showed significant non-parallelism with HC profiles. Regional profiles did not significantly differ between groups for cortical surface area or subcortical volume. Compared to CHR-P followed for ≥18 months without psychosis conversion (n = 31), CHR-P converters (n = 17) showed significant non-parallel ventricular volume expansion reflecting specific enlargement of lateral and inferolateral regions. Antipsychotic dosage in ESZ was significantly correlated with frontal cortical thinning. Results suggest that morphometric abnormalities in ESZ are not present in CHR-P, except for ventricular enlargement, which was evident in CHR-P who developed psychosis.

Rich-club connectivity and structural connectome organization in youth at clinical high-risk for psychosis and individuals with early illness schizophrenia.

Brain dysconnectivity has been posited as a biological marker of schizophrenia. Emerging schizophrenia connectome research has focused on rich-club organization, a tendency for brain hubs to be highly-interconnected but disproportionately vulnerable to dysconnectivity. However, less is known about rich-club organization in individuals at clinical high-risk for psychosis (CHR-P) and how it compares with abnormalities early in schizophrenia (ESZ). Combining diffusion tensor imaging (DTI) and magnetic resonance imaging (MRI), we examined rich-club and global network organization in CHR-P (n = 41) and ESZ (n = 70) relative to healthy controls (HC; n = 74) after accounting for normal aging. To characterize rich-club regions, we examined rich-club MRI morphometry (thickness, surface area). We also examined connectome metric associations with symptom severity, antipsychotic dosage, and in CHR-P specifically, transition to a full-blown psychotic disorder. ESZ had fewer connections among rich-club regions (ps < .024) relative to HC and CHR-P, with this reduction specific to the rich-club even after accounting for other connections in ESZ relative to HC (ps < .048). There was also cortical thinning of rich-club regions in ESZ (ps < .013). In contrast, there was no strong evidence of global network organization differences among the three groups. Although connectome abnormalities were not present in CHR-P overall, CHR-P converters to psychosis (n = 9) had fewer connections among rich-club regions (ps < .037) and greater modularity (ps < .037) compared to CHR-P non-converters (n = 19). Lastly, symptom severity and antipsychotic dosage were not significantly associated with connectome metrics (ps < .012). Findings suggest that rich-club and connectome organization abnormalities are present early in schizophrenia and in CHR-P individuals who subsequently transition to psychosis.

Mild traumatic brain injury: are ED providers identifying which patients are at risk?

OBJECTIVE: To identify patients with specific ED discharge diagnoses reporting symptoms associated with a mild traumatic brain injury (MTBI), compare frequency/severity of MTBI symptoms by discharge diagnosis, investigate head injury education provided at ED discharge, and learn about changes made by MTBI patients after injury. METHODS: The Post Concussion Symptom Scale, a demographic questionnaire, and open-ended questions about the impact the injury had on patients' lives were completed by 52 ED patients, at least 2 weeks after injury, discharged with concussion/closed head injury, head laceration, motor vehicle crash (MVC), or whiplash/cervical strain diagnoses. RESULTS: Between 1 and 23 MTBI symptoms were reported by 84.6% of the participants. Headache and fatigue were the most common; female patients had almost twice as many symptoms on average as male patients. Of MVC patients, 83.3% reported moderate severity scores for all 4 Post Concussion Symptom Scale categories, and these represented the highest overall severity scores. Concussion/closed head injury diagnosis patients received the most head injury education. The majority of patients were more cautious after injury. CONCLUSION: Most participants reported having MTBI symptoms. Although MVC participants reported the most severe MTBI symptoms, they had the least head injury education. Emergency nurses need to be aware patients may have an MTBI regardless of their presenting symptoms or injury severity.