The specific and multifaceted service needs of young people have driven the development of youth-specific integrated primary mental healthcare models, such as the internationally pioneering headspace services in Australia. Although these services were designed for early intervention, they often need to cater for young people with severe conditions and complex needs, creating challenges in service planning and resource allocation. There is, however, a lack of understanding and consensus on the definition of complexity in such clinical settings.

This retrospective study involved analysis of headspace’s clinical minimum data set from young people accessing services in Australia between 1 July 2018 and 30 June 2019. Based on consultations with experts, complexity factors were mapped from a range of demographic information, symptom severity, diagnoses, illness stage, primary presenting issues and service engagement patterns. Consensus clustering was used to identify complexity subgroups based on identified factors. Multinomial logistic regression was then used to evaluate whether these complexity subgroups were associated with other risk factors.

A total of 81,622 episodes of care from 76,021 young people across 113 services were analysed. Around 20% of young people clustered into a ‘high complexity’ group, presenting with a variety of complexity factors, including severe disorders, a trauma history and psychosocial impairments. Two moderate complexity groups were identified representing ‘distress complexity’ and ‘psychosocial complexity’ (about 20% each). Compared with the ‘distress complexity’ group, young people in the ‘psychosocial complexity’ group presented with a higher proportion of education, employment and housing issues in addition to psychological distress, and had lower levels of service engagement. The distribution of complexity profiles also varied across different headspace services.

The proposed data-driven complexity model offers valuable insights for clinical planning and resource allocation. The identified groups highlight the importance of adopting a holistic and multidisciplinary approach to address the diverse factors contributing to clinical complexity. The large number of young people presenting with moderate-to-high complexity to headspace early intervention services emphasises the need for systemic change in youth mental healthcare to ensure the availability of appropriate and timely support for all young people.

Adolescence is a period marked by highest vulnerability to the onset of depression, with profound implications for adult health. Neuroimaging studies have revealed considerable atrophy in brain structure in these patients with depression. Of particular importance are regions responsible for cognitive control, reward, and self-referential processing. However, the causal structural networks underpinning brain region atrophies in adolescents with depression remain unclear.

This study aimed to investigate the temporal course and causal relationships of gray matter atrophy within the brains of adolescents with depression.

We analyzed T1-weighted structural images using voxel-based morphometry in first-episode adolescent patients with depression (n=80, 22 males; age = 15.57±1.78) and age, gender matched healthy controls (n=82, 25 males; age = 16.11±2.76) to identify the disease stage-specific gray matter abnormalities. Then, with granger causality analysis, we arranged the patients’ illness duration chronologically to construct the causal structural covariance networks that investigated the causal relationships of those atypical structures.

Compared to controls, smaller volumes in ventral medial prefrontal cortex (vmPFC), dorsal anterior cingulate cortex (dACC), middle cingulate cortex (MCC) and insula areas were identified in patients with less than 1 year illness duration, and further progressed to the subgenual ACC, regions of default, frontoparietal networks in longer duration. Causal network results revealed that dACC, vmPFC, MCC and insula were prominent nodes projecting exerted positive causal effects to regions of the default mode and frontoparietal networks. The dACC, vmPFC and insula also had positive projections to the reward network, which included mainly the thalamus, caudate and putamen, while MCC also exerted a positive causal effect on the insula and thalamus.

These findings revealed the progression of structural atrophy in adolescent patients with depression and demonstrated the causal relationships between regions involving cognitive control, reward and self-referential processes.

None Declared

The occurrence of depression in adolescence, a critical period of brain development, linked with neuroanatomical and cognitive abnormalities. Neuroimaging studies have identified hippocampal abnormalities in those of adolescent patients. However, few studies have investigated the atypically developmental trends in hippocampal subfields in adolescents with depression and their relationships with cognitive dysfunctions.

To explore the structural abnormalities of hippocampal subfields in patients with youth depression and examine how these abnormalities associated with cognitive deficits.

We included a sample of 79 first-episode depressive patients (17 males, age = 15.54±1.83) and 71 healthy controls (23 males, age = 16.18±2.85). The severity of these adolescent patients was assessed by depression scale, suicidal risk and self-harm behavior. Nine cognitive tasks were used to evaluate memory, cognitive control and attention abilities for all participants. Bilateral hippocampus were segmented into 12 subfields with T1 and T2 weighted images using Freesurfer v6.0. A mixed analysis of variance was performed to assess the differences in subfields volumes between all patients and controls, and between patients with mild and severe depression. Finally, LASSO regression was conducted to explore the associations between hippocampal subfields and cognitive abnormalities in patients.

We found significant subfields atrophy in the CA1, CA2/3, CA4, dentate gyrus, hippocampal fissure, hippocampal tail and molecular layer subfields in patients. For those patients with severe depression, hippocampal subfields showed greater extensive atrophy than those in mild, particularly in CA1-4 subfields extending towards the subiculum. These results were similar across various severity assessments. Regression indicated that hippocampal subfields abnormalities had the strongest associations with memory dysfunction, and relatively week associations with cognitive control and attention. Notably, CA4 and dentate gyrus had the highest weights in the regression model.

As depressive severity increases, hippocampal subfield atrophy tends to spread from CA regions to surrounding areas, and primarily affects memory function in patients with youth depression. These results suggest hippocampus might be markers in progression of adolescent depression, offering new directions for early clinical intervention.

None Declared

Daylength and the rates of changes in daylength have been associated with seasonal fluctuations in psychiatric symptoms and in cognition and mood in healthy adults. However, variations in human brain glucose metabolism in concordance with seasonal changes remain under explored.

In this cross-sectional study, we examined seasonal effects on brain glucose metabolism, which we measured using 18F-fluorodeoxyglucose-PET in 97 healthy participants. To maximize the sensitivity of regional effects, we computed relative metabolic measures by normalizing the regional measures to white matter metabolism. Additionally, we explored the role of rest–activity rhythms/sleep–wake activity measured with actigraphy in the seasonal variations of regional brain metabolic activity.

We found that seasonal variations of cerebral glucose metabolism differed across brain regions. Glucose metabolism in prefrontal regions increased with longer daylength and with greater day-to-day increases in daylength. The cuneus and olfactory bulb had the maximum and minimum metabolic values around the summer and winter solstice respectively (positively associated with daylength), whereas the temporal lobe, brainstem, and postcentral cortex showed maximum and minimum metabolic values around the spring and autumn equinoxes, respectively (positively associated with faster daylength gain). Longer daylength was associated with greater amplitude and robustness of diurnal activity rhythms suggesting circadian involvement.

The current findings advance our knowledge of seasonal patterns in a key indicator of brain function relevant for mood and cognition. These data could inform treatment interventions for psychiatric symptoms that peak at specific times of the year.

Greenhouse gas emissions and land use change – from deforestation, forest degradation, and agricultural intensification – are contributing to climate change and biodiversity loss. Important land-based strategies such as planting trees or growing bioenergy crops (with carbon capture and storage) are needed to achieve the goals of the Paris Climate Agreement and to enhance biodiversity.

The integrated Land Ecosystems Atmospheric Processes Study (iLEAPS) is an international knowledge-exchange and capacity-building network, specializing in ecosystems and their role in controlling the exchange of water, energy and chemical compounds between the land surface and the atmosphere. We outline priority directions for land–atmosphere interaction research and its contribution to the sustainable development agenda.

Greenhouse-gas emissions from human activities and land use change (from deforestation, forest degradation, and agricultural intensification) are contributing to climate change and biodiversity loss. Afforestation, reforestation, or growing bioenergy crops (with carbon capture and storage) are important land-based strategies to achieve the goals of the Paris Climate Agreement and to enhance biodiversity. The effectiveness of these actions depends on terrestrial ecosystems and their role in controlling or moderating the exchange of water, heat, and chemical compounds between the land surface and the atmosphere.

The integrated Land Ecosystems Atmospheric Processes Study (iLEAPS), a global research network of Future Earth, enables the international community to communicate and remain up to date with developments and concepts about terrestrial ecosystems and their role in global water, energy, and biogeochemical cycles. Covering critically important topics such as fire, forestry, wetlands, methane emissions, urban areas, pollution, and climate change, the iLEAPS Global Research Programme sits center stage for some of the most important environmental questions facing humanity. In this paper, we outline the new challenges and opportunities for land–atmosphere interaction research and its role in supporting the broader sustainable development agenda.

Future directions for research into land–atmosphere interactions that supports the sustainable development agenda

Evaluation of adult antibiotic order sets (AOSs) on antibiotic stewardship metrics has been limited. The primary outcome was to evaluate the standardized antimicrobial administration ratio (SAAR). Secondary outcomes included antibiotic days of therapy (DOT) per 1,000 patient days (PD); selected antibiotic use; AOS utilization; Clostridioides difficile infection (CDI) cases; and clinicians’ perceptions of the AOS via a survey following the final study phase.

This 5-year, single-center, quasi-experimental study comprised 5 phases from 2017 to 2022 over 10-month periods between August 1 and May 31.

The study was conducted in a 752-bed tertiary care, academic medical center.

Our institution implemented AOSs in the electronic medical record (EMR) for common infections among hospitalized adults.

For the primary outcome, a statistically significant decreases in SAAR were detected from phase 1 to phase 5 (1.0 vs 0.90; P < .001). A statistically significant decreases were detected in DOT per 1,000 PD (4,884 vs 3,939; P = .001), fluoroquinolone orders (407 vs 175; P < .001), carbapenem orders (147 vs 106; P = .024), and clindamycin orders (113 vs 73; P = .01). No statistically significant change in mean vancomycin orders was detected (991 vs 902; P = .221). A statistically significant decrease in CDI cases was also detected (7.8, vs 2.4; P = .002) but may have been attributable to changes in CDI case diagnosis. Clinicians indicated that the AOSs were easy to use overall and that they helped them select the appropriate antibiotics.

Implementing AOS into the EMR was associated with a statistically significant reduction in SAAR, antibiotic DOT per 1,000 PD, selected antibiotic orders, and CDI cases.

To determine the association between blood markers of white matter injury (e.g., serum neurofilament light and phosphorylated neurofilament heavy) and a novel neuroimaging technique measuring microstructural white matter changes (e.g., diffusion kurtosis imaging) in regions (e.g., anterior thalamic radiation and uncinate fasciculus) known to be impacted in traumatic brain injury (TBI) and associated with symptoms common in those with chronic TBI (e.g., sleep disruption, cognitive and emotional disinhibition) in a heterogeneous sample of Veterans and non-Veterans with a history of remote TBI (i.e., >6 months).

Participants with complete imaging and blood data (N=24) were sampled from a larger multisite study of chronic mild-moderate TBI. Participants ranged in age from young to middle-aged (mean age = 34.17, SD age = 10.96, range = 19-58) and primarily male (66.7%). The number of distinct TBIs ranged from 1-5 and the time since most recent TBI ranged from 0-30 years. Scores on a cognitive screener (MoCA) ranged from 22-30 (mean = 26.75). We performed bivariate correlations with mean kurtosis (MK) in the anterior thalamic radiation (ATR; left, right) uncinate fasciculus (UF; left, right), and serum neurofilament light (NFL), and phosphorylated neurofilament heavy (pNFH). Both were log transformed for non-normality. Significance threshold was set at p<0.05.

pNFH was significantly and negatively correlated to MK in the right (r=-0.446) and left (r=-0.599) UF and right (r=-0.531) and left (r=-0.469) ATR. NFL showed moderate associations with MK in the right (r=-0.345) and left (r=-0.361) UF and little to small association in the right (r=-0.063) and left (r=-0.215) ATR. In post-hoc analyses, MK in both the left (r=0.434) and right (r=0.514) UF was positively associated with performance on a frontally-mediated list-learning task (California Verbal Learning Test, 2nd Edition; Trials 1-5 total).

Results suggest that serum pNFH may be a more sensitive blood marker of microstructural complexity in white matter regions frequently impacted by TBI in a chronic mild-moderate TBI sample. Further, it suggests that even years after a mild-moderate TBI, levels of pNFH may be informative regarding white matter integrity in regions related to executive functioning and emotional disinhibition, both of which are common presenting problems when these patients are seen in a clinical setting.

Multiple sclerosis (MS) is associated with cognitive and social cognitive deficits. Social cognition impairments may include difficulty with facial expression and emotion recognition. People with MS (PwMS) may also not be aware of their cognitive challenges as demonstrated through discrepant objective and subjective assessments. Research recently conducted in demyelinated mouse models demonstrated that metformin, a drug typically used to treat type II diabetes mellitus (DMII), promotes remyelination and reverses existent social cognition impairment by repressing the monoacylglycerol lipase (MgII) enzyme in the brain. We aim to translate this basic science research and are conducting a pilot study to determine if metformin improves social cognition in PwMS. This project will compare social cognition in those with MS and comorbid DMII who are treated with metformin and those who are not. For the purposes of this interim data analysis, we collapse across both MS groups who are, and who are not, treated with metformin. The current objective is to evaluate the relationship between subjective (i.e., perceived empathy), objective social cognition and information processing speed (IPS) in PwMS and co-morbid diabetes.

Preliminary data on 15 PwMS are included. Participants completed a demographic questionnaire, a cognitive assessment battery, an objective social cognition assessment and self-report questionnaires. These questionnaires assessed subjective social cognition, fatigue, mood, and disability level.

Preliminary results showed that IPS was positively correlated with the affective empathy domain of social cognition, r = .53, p = .04. Additionally, IPS was positively correlated with objective social cognition, r = .71, p = 003. Follow-up regression analyses demonstrated that IPS predicted objective social cognition, R2 = .71, SE = 3.04, F(1,13) = 13.36, p = .003 and subjective social cognition, R2 = .53, SE = 5.39, F(1,13) = 4.97, p = .04. However, subjective and objective measures of social cognition were not correlated, p > .05 and remained uncorrelated when IPS was controlled for, p > .05.

A majority of the variance in social perception is explained by IPS, suggesting that how quickly one can think may be a fundamental cognitive process to allow optimal functioning in social situations. While the reason for the relationship between IPS and subjective social cognition is perhaps less apparent, it may reflect a more global cognitive compromise that impacts both cognitive and social processes. This lends support to the Relative Consequence Model that suggests IPS deficits are a fundamental cognitive deficit underlying other more complex cognitive processes. The lack of correlation between subjective perception of empathy and objective social cognition requires further exploration and could potentially be related to some individuals with MS having a diminished ability to judge their own social proficiency. Further analyses with a larger sample will be conducted to assess group differences in social cognitive outcomes and MgII levels between metformin and non-metformin groups. If PwMS who take metformin have better social cognition compared to PwMS who do not take metformin, Mgll levels can be used as a biomarker to guide metformin treatment with the goal of improving social cognition.

Despite associations between hypoglycemia and cognitive performance using cross-sectional and experimental methods (e.g., Insulin clamp studies), few studies have evaluated this relationship in a naturalistic setting. This pilot study utilizes an EMA study design in adults with T1D to examine the impact of hypoglycemia and hyperglycemia, measured using CGM, on cognitive performance, measured via ambulatory assessment.

Twenty adults with T1D (mean age 38.9 years, range 26-67; 55% female; 55% bachelor’s degree or higher; mean HbA1c = 8.3%, range 5.4% - 12.5%), were recruited from the Joslin Diabetes Center at SUNY Upstate Medical University. A blinded Dexcom G6 CGM was worn during everyday activities while completing 3-6 daily EMAs using personal smartphones. EMAs were delivered between 9 am and 9 pm, for 15 days. EMAs included 3 brief cognitive tests developed by testmybrain.org and validated for brief mobile administration (Gradual Onset CPT d-prime, Digit Symbol Matching median reaction time, Multiple Object Tracking percent accuracy) and self-reported momentary negative affect. Day-level average scores were calculated for the cognitive and negative affect measures. Hypoglycemia and hyperglycemia were defined as the percentage of time spent with a sensor glucose value <70 mg/dL or > 180 mg/dL, respectively. Daytime (8 am to 9 pm) and nighttime (9 pm to 8 am) glycemic excursions were calculated separately. Multilevel models estimated the between- and within-person association between the night prior to, or the same day, time spent in hypoglycemia or hyperglycemia and cognitive performance (each cognitive test was modeled separately). To evaluate the effect of between-person differences, person-level variables were calculated as the mean across the study and grand-mean centered. To evaluate the effect of within-person fluctuations, day-level variables were calculated as deviations from these person-level means.

Within-person fluctuations in nighttime hypoglycemia were associated with daytime processing speed. Specifically, participants who spent a higher percentage of time in hypoglycemia than their average percentage the night prior to assessment performed slower than their average performance on the processing speed test (Digit Symbol Matching median reaction time, b = 94.16, p = 0.042), while same day variation in hypoglycemia was not associated with variation in Digit Symbol Matching performance. This association remained significant (b = 97.46, p = 0.037) after controlling for within-person and between-person effects of negative affect. There were no significant within-person associations between time spent in hyperglycemia and Digit Symbol Matching, nor day/night hypoglycemia or hyperglycemia and Gradual Onset CPT or Multiple Object Tracking.

Our findings from this EMA study suggest that when individuals with T1D experience more time in hypoglycemia at night (compared to their average), they have slower processing speed the following day, while same day hypoglycemia and hyperglycemia does not similarly impact processing speed performance. These results showcase the power of intensive longitudinal designs using ambulatory cognitive assessment to uncover novel determinants of cognitive variation in real world settings that have direct clinical applications for optimizing cognitive performance. Future research with larger samples is needed to replicate these findings.

Determine associations between cognitive outcomes in remote TBI (i.e., at least 6 months post injury), a blood marker of neural degeneration (i.e., Tau), and diffusion kurtosis imaging (DKI) measures (e.g., mean or radial kurtosis). Because DKI imaging is sensitive to the environmental complexity of the imaged area, we sought to investigate regions known to be associated with the cognitive and emotional sequalae of TBI, such as the anterior thalamic radiations, uncinate fasciculus, and the corpus callosum.

41 individuals with mild-to-moderate TBI and a mean age(SD) of 36.1(10.4) years underwent DKI, a blood draw, and neuropsychological assessments. 23 healthy controls (HC) with a mean age(SD) of 35.2(15.2) years underwent the blood draw and assessments, but no imaging. Higher diffusion kurtosis indicates more restricted diffusion, possibly due to greater complexity within the imaged region. Thus, in the context of TBI, DKI can be used as a proxy measurement for biological processes that alter the complexity of imaged environments, such as reactive gliosis. Some people show cognitive deficits long after TBI and this could be associated with increased inflammation and membrane protein aggregates in damaged brain regions. We used bivariate correlations and general linear models to investigate the association of mean kurtosis (MK) in long white matter tracts and Tau (total or phosphorylated) to color-word Stroop scores; a measure of fronto-subcortical function.

In patients with TBI, MK was significantly associated with serum total Tau (TTau) in the right (r=-0.396) and left (r=-0.555) uncinate fasciculus (UF), right (r=-0.402) and left (r=-0.504) anterior thalamic radiations (ATR), and the genu (r=-0.526) and body (r=-0.404) of the corpus callosum (CC). TTau had a significant association with word Stroop scores, F(1,63)=-2.546, p=0.013. However, there was no significant effect of group (i.e., TBI or HC), F(2,63)=-0.426, p=0.672, on cognitive performance. When models were implemented that included both TTau and MK in either the UF or ATR as explanatory variables to predict word Stroop scores, TTau levels and MK in the right UF explained a significant amount of the variance in Stroop performance, F(1,29)=2.215, p=0.025. Further, there was also a significant association between radial kurtosis in the right UF and Stroop word scores (r= 0.366).

Our results show that an indicator of biological complexity (DKI) in cognitively important brain regions is associated with cognitive performance and Tau in patients with remote mild-to-moderate TBI. The UF is a critical fronto-temporal/subcortical pathway that has previously been implicated in the manifestation of executive dysfunction and mood dysregulation in TBI. Tau is an important marker of neurodegeneration implicated in Alzheimer’s disease, Parkinson’s disease, and chronic traumatic encephalopathy (CTE), and DKI is potentially sensitive to markers of neurodegeneration. The association of Tau and DKI measures is novel and shows concordance between blood and brain imaging markers and cognitive performance in patients with mild to moderate TBI.