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Bipolar disorders (BDs) are among the leading causes of morbidity and disability. Objective biological markers, such as those based on brain imaging, could aid in clinical management of BD. Machine learning (ML) brings neuroimaging analyses to individual subject level and may potentially allow for their diagnostic use. However, fair and optimal application of ML requires large, multi-site datasets. We applied ML (support vector machines) to MRI data (regional cortical thickness, surface area, subcortical volumes) from 853 BD and 2167 control participants from 13 cohorts in the ENIGMA consortium. We attempted to differentiate BD from control participants, investigated different data handling strategies and studied the neuroimaging/clinical features most important for classification. Individual site accuracies ranged from 45.23% to 81.07%. Aggregate subject-level analyses yielded the highest accuracy (65.23%, 95% CI = 63.47-67.00, ROC-AUC = 71.49%, 95% CI = 69.39-73.59), followed by leave-one-site-out cross-validation (accuracy = 58.67%, 95% CI = 56.70-60.63). Meta-analysis of individual site accuracies did not provide above chance results. There was substantial agreement between the regions that contributed to identification of BD participants in the best performing site and in the aggregate dataset (Cohen's Kappa = 0.83, 95% CI = 0.829-0.831). Treatment with anticonvulsants and age were associated with greater odds of correct classification. Although short of the 80% clinically relevant accuracy threshold, the results are promising and provide a fair and realistic estimate of classification performance, which can be achieved in a large, ecologically valid, multi-site sample of BD participants based on regional neurostructural measures. Furthermore, the significant classification in different samples was based on plausible and similar neuroanatomical features. Future multi-site studies should move towards sharing of raw/voxelwise neuroimaging data.

BackgroundChildhood maltreatment (CM) plays an important role in the development of major depressive disorder (MDD). The aim of this study was to examine whether CM severity and type are associated with MDD-related brain alterations, and how they interact with sex and age.MethodsWithin the ENIGMA-MDD network, severity and subtypes of CM using the Childhood Trauma Questionnaire were assessed and structural magnetic resonance imaging data from patients with MDD and healthy controls were analyzed in a mega-analysis comprising a total of 3872 participants aged between 13 and 89 years. Cortical thickness and surface area were extracted at each site using FreeSurfer.ResultsCM severity was associated with reduced cortical thickness in the banks of the superior temporal sulcus and supramarginal gyrus as well as with reduced surface area of the middle temporal lobe. Participants reporting both childhood neglect and abuse had a lower cortical thickness in the inferior parietal lobe, middle temporal lobe, and precuneus compared to participants not exposed to CM. In males only, regardless of diagnosis, CM severity was associated with higher cortical thickness of the rostral anterior cingulate cortex. Finally, a significant interaction between CM and age in predicting thickness was seen across several prefrontal, temporal, and temporo-parietal regions.ConclusionsSeverity and type of CM may impact cortical thickness and surface area. Importantly, CM may influence age-dependent brain maturation, particularly in regions related to the default mode network, perception, and theory of mind.

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors.

Abstract Ketamine shows rapid antidepressant effects peaking 24 h after administration. The antidepressant effects may occur through changes in glutamatergic metabolite levels and resting-state functional connectivity (rsFC) within the default mode network (DMN). A multistage drug effect of ketamine has been suggested, inducing acute effects on dysfunctional network configuration and delayed effects on homeostatic synaptic plasticity. Whether the DMN-centered delayed antidepressant-related changes are associated with the immediate changes remains unknown. Thirty-five healthy male participants (25.1 ± 4.2 years) underwent 7 T magnetic resonance spectroscopy (MRS) and resting-state functional magnetic resonance imaging (rsfMRI) before, during, and 24 h after a single S-ketamine or placebo infusion. Changes in glutamatergic measures and rsFC in the DMN node pregenual anterior cingulate cortex (pgACC) were examined. A delayed rsFC decrease of the pgACC to inferior parietal lobe (family-wise error corrected p (p FWEc) = 0.018) and dorsolateral prefrontal cortex (PFC; p FWEc = 0.002) was detected that was preceded by an immediate rsFC increase of the pgACC to medial PFC (p FWEc

Black Carbon is an important climate forcer with poorly constraint historic emission fluxes and therefore large emission uncertainty. Here, ice-core data are combined with modelling to reconstruct historical emissions of Black carbon and finding gaps with the existing inventories, which implies potential climate sensitivity biases

Abstract Pronounced glacial and interglacial climate cycles characterized northern ecosystems during the Pleistocene. Our understanding of the resultant community transformations and past ecological interactions strongly depends on the taxa found in fossil assemblages. Here, we present a shotgun metagenomic analysis of sedimentary ancient DNA (sedaDNA) to infer past ecosystem‐wide biotic composition (from viruses to megaherbivores) from the Middle and Late Pleistocene at the Batagay megaslump, East Siberia. The shotgun DNA records of past vegetation composition largely agree with pollen and plant metabarcoding data from the same samples. Interglacial ecosystems at Batagay attributed to Marine Isotope Stage (MIS) 17 and MIS 7 were characterized by forested vegetation (Pinus, Betula, Alnus) and open grassland. The microbial and fungal communities indicate strong activity related to soil decomposition, especially during MIS17. The local landscape likely featured more open, herb‐dominated areas, and the vegetation mosaic supported birds and small omnivorous mammals. Parts of the area were intermittently/partially flooded as suggested by the presence of water‐dependent taxa. During MIS 3, the sampled ecosystems are identified as cold‐temperate, periodically flooded grassland. Diverse megafauna (Mammuthus, Equus, Coelodonta) coexisted with small mammals (rodents). The MIS 2 ecosystems existed under harsher conditions, as suggested by the presence of cold‐adapted herbaceous taxa. Typical Pleistocene megafauna still inhabited the area. The new approach, in which shotgun sequencing is supported by metabarcoding and pollen data, enables the investigation of community composition changes across a broad range of taxonomic groups and inferences about trophic interactions and aspects of soil microbial ecology.

The Batagay megaslump, a permafrost thaw feature in north-eastern Siberia, provides access to ancient permafrost up to ∼650 kyr old. We aimed to assess the permafrost-locked organic matter (OM) quality and to deduce palaeo-environmental information on glacial–interglacial timescales. We sampled five stratigraphic units exposed on the 55 m high slump headwall and analysed lipid biomarkers (alkanes, fatty acids and alcohols). Our findings revealed similar biogeochemical signatures for the glacial periods: the lower ice complex (Marine Isotope Stage (MIS) 16 or earlier), the lower sand unit (sometime between MIS 16–6) and the upper ice complex (MIS 4–2). The OM in these units has a terrestrial character, and microbial activity was likely limited. Contrarily, the n-alkane and fatty acid distributions differed for the units from interglacial periods: the woody layer (MIS 5), separating the lower sand unit and the upper ice complex, and the Holocene cover (MIS 1), on top of the upper ice complex. The woody layer, marking a permafrost degradation disconformity, contained markers of terrestrial origin (sterols) and high microbial decomposition (iso- and anteiso-fatty acids). In the Holocene cover, biomarkers pointed to wet depositional conditions and we identified branched and cyclic alkanes, which are likely of microbial origin. Higher OM decomposition characterised the interglacial periods. As climate warming will continue permafrost degradation in the Batagay megaslump and in other areas, large amounts of deeply buried ancient OM with variable composition and degradability are mobilised, likely significantly enhancing greenhouse gas emissions from permafrost regions.

Background: Anhedonia is a key symptom of major depressive disorder (MDD). Anhedonia is associated with aberrant reward processing, but whether it might interfere similarly with the neural processing of aversive stimuli, such as monetary loss, remains unknown. We aimed to investigate potential associations between anhedonia and neural response during reward and loss processing in patients with MDD. Methods: We investigated blood-oxygen-level-dependent response in the orbitofrontal cortex, cingulate cortex, insula and basal ganglia during monetary reward and loss processing in 182 patients with MDD, using a card-guessing paradigm. We measured anhedonia with the Social and Physical Anhedonia Scale (SASPAS), and we tested for the main and interaction effects of SASPAS scores and the experimental condition (reward or loss) in a full factorial model. Results: We detected a negative main effect of anhedonia, as well as a significant interaction effect of anhedonia and the experimental condition, on orbitofrontal and insular neural response. Post hoc analyses revealed that the interaction was driven by a significant association between higher anhedonia scores and hypoactivation during loss processing. We observed no significant association between anhedonia and neural response during reward processing. Limitations: This study had a cross-sectional design. Conclusion: Our findings confirmed that altered neural processing in the orbitofrontal cortex and insula is a neurobiological feature of anhedonic symptomatology in people with MDD. The pronounced association between anhedonia and blunted neural response during loss processing supports a broader concept for the neurobiological basis of anhedonia. Hence, MDD with anhedonic features might be characterized by reduced neural response to external stimuli, potentially because of amotivation., Introduction Anhedonia is one of the core symptoms of major depressive disorder (MDD) in addition to low mood, according to the International Statistical Classification of Diseases and Related Health Problems, [...]

High childhood emotional maltreatment (CM-EMO) is reported in mood and anxiety disorders. The associations with an increased risk for psychopathology are not fully understood. One potential factor may be through alterations in gamma-Aminobutyric acid (GABA). The pregenual anterior cingulate cortex (pgACC) is an important brain region for emotion processing and its’ GABA levels were previously implicated in mood and anxiety disorders pathophysiology. We examined the association between the self-reported CM-EMO in adulthood and GABA + levels in the pgACC and in a control region, anterior mid cingulate cortex. GABA+ and total creatine (tCr) were measured in the pgACC and aMCC voxels in seventy-four healthy volunteers (32 (43%) women, ages 19–54, age [standard deviation] = 27.1 [6.5]) using proton magnetic resonance spectroscopy at 7 T. Childhood Trauma Questionnaire was completed by adult participants to measure retrospective self-reported experience of emotional neglect (CM-EMO-NEG) and emotional abuse (CM-EMO-AB) during childhood. Linear mixed models tested the interaction between the region and the two subscales, and GABA+/tCr ratios, with an adjusted alpha = 0.025. Following, linear models, including with covariates were tested. There was an interaction effect between region and CM-EMO-NEG (B = −0.007, p = 0.009), driven by a negative relationship between CM-EMO-NEG and GABA+/tCr in the pgACC (B = −0.004, p = 0.013). Results for CM-EMO-NEG were robust to inclusion of different covariates (ps

Novel approaches are needed to accurately classify and monitor sleep patterns in older adults, particularly those with cognitive impairment and non-normative sleep. Traditional methods ignore underlying sleep architecture in these patient populations, and other modern approaches tend to focus on healthy, normative patient populations. In this paper, we developed a model using a long-short-term memory neural network (LSTM) and trained it on a sample of older, non-normative patients. The 22 nights of data collected were trained on gold-standard polysomnography (PSG) as ground truth and were compared against the clinical standard threshold-based method for sleep detection. The LSTM more than doubled the traditional method's ability to detect clinically-relevant wakefulness during sleep (37.7% vs. 15%) without significantly sacrificing accuracy (67.7% vs. 75%) or precision (90.7% vs. 94%) of sleep classification.

Changes to structural and functional connectivity can give rise to neurodegeneration and neurodevelopmental diseases. Here the authors investigate molecular and connectomic patterns in 13 different neurological, psychiatric and neurodevelopmental diseases from the ENIGMA consortium.

Abstract Former prospective studies showed that the occurrence of relapse in Major Depressive Disorder (MDD) is associated with volume loss in the insula, hippocampus and dorsolateral prefrontal cortex (DLPFC). However, these studies were confounded by the patient’s lifetime disease history, as the number of previous episodes predict future recurrence. In order to analyze neural correlates of recurrence irrespective of prior disease course, this study prospectively examined changes in brain structure in patients with first-episode depression (FED) over 2 years. N = 63 FED patients and n = 63 healthy controls (HC) underwent structural magnetic resonance imaging at baseline and after 2 years. According to their disease course during the follow-up interval, patients were grouped into n = 21 FED patients with recurrence (FEDrec) during follow-up and n = 42 FED patients with stable remission (FEDrem). Gray matter volume changes were analysed using group by time interaction analyses of covariance for the DLPFC, hippocampus and insula. Significant group by time interactions in the DLPFC and insula emerged. Pairwise comparisons showed that FEDrec had greater volume decline in the DLPFC and insula from baseline to follow-up compared with FEDrem and HC. No group by time interactions in the hippocampus were found. Cross-sectional analyses at baseline and follow-up revealed no differences between groups. This longitudinal study provides evidence for neural alterations in the DLPFC and insula related to a detrimental course in MDD. These effects of recurrence are already detectable at initial stages of MDD and seem to occur without any prior disease history, emphasizing the importance of early interventions preventing depressive recurrence.

Deep dermal and full thickness burns are typically closed with split thickness skin grafting. In less extensive burns where donor skin is readily available healing is usually achieved with meshed split skin grafting. Meek micrografting is an alternative technique that is well-recognised for more extensive burns, but can also have a place in managing smaller total body surface area (TBSA) burns primarily to minimise donor site size and its associated morbidity.We present our 9-year experience of using Meek grafting in a series of 11 cases involving ≤20% TBSA burn injuries, and describe our method for minimising theatre time. We achieved 80.7% graft take at 4 weeks post-grafting and demonstrated 100% healing of all wounds at an average of 58.1 (31–83) days after the final Meek grafting operation. Our results demonstrated that Meek grafting achieves comparable healing to conventional grafting with a similar surgical time and reduced donor size.

IntroductionThe Russian invasion of Ukraine and the resulting consequences are in the center of political discussions, media, and likely individual thinking of the population in Germany. Yet, the impact of this prolonged exposure on mental health is not known hitherto.MethodsUsing the population based cohort study DigiHero from three federal states (Saxony-Anhalt, Saxony, and Bavaria), we assessed anxiety levels (GAD-7), depressive symptoms (PHQ-9), and distress (modified PDI) in the first weeks of war and 6 months later.ResultsOf those 19,432, who responded in the first weeks of war, 13,934 (71.1%) responded also 6 months later. While anxiety and emotional distress decreased during the 6 months, their average scores were still elevated, and a substantial fraction of respondents displayed clinically relevant sequelae. Persons from low-income households were especially affected, specifically by fears related to the personal financial situation. Those who reacted with a particularly strong fear in the beginning of war were more likely to have persistent clinically relevant symptoms of depression and anxiety also 6 months later.DiscussionThe Russian invasion of Ukraine is accompanied by continuing impairment of mental health in the German population. Fears surrounding the personal financial situation are a strong determinant.

Neuropsychiatric symptoms, such as executive dysfunction, fatigue and depression, are highly prevalent and severely incapacitating among Long- and Post-COVID patients (Schou et al., 2021), to the point where some are unable to resume their jobs and even their daily lives. While the prognosis of these patients remains elusive, cognition worsens over time in many of them (Lu et al., 2020). Perivascular inflammation in the brain, as a consequence of the blood-brain barrier damage caused by SARS-CoV-2 (Yang et al., 2020), is one of the mechanisms of ongoing systemic and intracerebral inflammation proposed to contribute to these long-lasting symptoms. We thus investigated two surrogate measurements of glymphatics, enlarged perivascular spaces in T1-w magnetic resonance imaging and three-dimensional propagation of cardiorespiratory pulsations in ultrafast magnetic resonance encephalography (Barghoorn et al., 2021), in 60 neuropsychiatric long-COVID patients, 30 healthy COVID-19 survivors and 30 never-infected healthy controls. We provide evidence of EPVS burden being associated with cognitive impairment and cardiorespiratory pulsations slightly varying among these groups. We hypothesize glymphatic clearance dysfunction might be a way for post-COVID to transition into a neurodegenerative disorder.

Glacial legacies preserved in permafrost such as buried glacial ice of the last ice age are of increasing concern in the Western Canadian Arctic. Permafrost collapse due to melting ground ice largely follows the margins of the maximum Laurentide Ice Sheet extent and therefore predetermines the postglacial landscape evolution in this region. Another type of ground ice, (i.e., wedge ice) of late Pleistocene and Holocene age associated with permafrost aggradation, is also widespread here. Our study on Herschel Island (Qikiqtaruk, Beaufort Sea) re-examines previous data and applies stable-isotope and dissolved organic carbon (DOC) analyses as well as radiocarbon dating on DOC and particulate plant macrofossil remains preserved in massive ground ice, wedge ice and host deposits.Newly obtained DOC ages of the massive ice span from 32 220 to 25 830 cal BP and extend the only previously available direct age determination (CO2-derived radiocarbon age of 21 290 cal BP) properly into the Last Glacial Maximum as the formation time of the massive ice. Its newly obtained isotopic composition exhibits mean values of −33.1 ± 0.6‰ in δ18O, of −257 ± 4‰ in δD and 7.6 ± 0.9‰ in deuterium excess (d) fitting into previously reported respective data ranges. The very low (negative) stable isotope composition of the massive ice, the numerous enclosed spherical air bubbles as well as the very low mean DOC content of 0.7 ± 0.1 mg L−1 provide strong evidence for an origin as glacier ice that was buried and has survived since deglaciation.The newly studied wedge ice on Herschel Island formed during the Holocene between 9220 and 3470 cal BP, and shows a distinct isotopic composition with mean values of −18.4 ± 1.1‰ in δ18O, −138 ± 9‰ in δD and a mean deuterium excess (d) of 8.8 ± 1.4‰. Such isotopic wedge-ice record as well as its mean DOC concentration of 4.3 ± 2.1 mg L−1 fall within the range of previously studied Holocene ice wedges in the region. The directly-dated stable isotope record of ice-wedge growth on Herschel Island indicates a winter cooling trend towards the mid-Holocene, even though most available records attribute this cooling rather to the warm season while the winter temperatures over this period are not constrained yet.The extraordinarily rich ground-ice inventory of Herschel Island offers insights into the glacial and postglacial landscape evolution of the Western Canadian Arctic. Here, paleoenvironmental research highlights ice sheet-permafrost interactions over glacial, deglacial and postglacial timescales.

IntroductionEmotional awareness is the ability to identify, interpret, and verbalize the emotional responses of oneself and those of others. The Levels of Emotional Awareness Scale (LEAS) is an objective performance inventory that accurately measures an individual's emotional awareness. LEAS assessments are typically scored manually and are therefore both time consuming and cognitively demanding. This study presents a German electronic scoring program for the LEAS (geLEAS), the first non-English computerized assessment approach of the LEAS.MethodsData were collected from a healthy German community sample (N = 208). We developed a modern software for computerizing LEAS scoring, an open-source text-based emotion assessment tool called VETA (Verbal Emotion in Text Assessment). We investigated if the software would arrive at similar results as hand scoring in German and if emotional awareness would show similar associations to sociodemographic information and psychometric test results as in previous studies.ResultsThe most frequently used scoring method of the geLEAS shows excellent internal consistency (α = 0.94) and high correlations with hand scoring (r = 0.97, p < 0.001). Higher emotional awareness measured by the geLEAS is associated with female gender, older age, and higher academic achievement (all p < 0.001). Moreover, it is linked to the ability to identify emotions in facial expressions (p < 0.001) and more accurate theory of mind functioning (p < 0.001).DiscussionAn automated method for evaluating emotional awareness greatly expands the ability to study emotional awareness in clinical care and research. This study aims to advance the use of emotional awareness as a clinical and scientific parameter.

Cyanobacteria have raised great interest in biotechnology, e.g., for the sustainable production of molecular hydrogen (H2) using electrons from water oxidation. However, this is hampered by various constraints. For example, H2-producing enzymes compete with primary metabolism for electrons and are usually inhibited by molecular oxygen (O2). In addition, there are a number of other constraints, some of which are unknown, requiring unbiased screening and systematic engineering approaches to improve the H2 yield. Here, we introduced the regulatory [NiFe]-hydrogenase (RH) of Cupriavidus necator (formerly Ralstonia eutropha) H16 into the cyanobacterial model strain Synechocystis sp. PCC 6803. In its natural host, the RH serves as a molecular H2 sensor initiating a signal cascade to express hydrogenase-related genes when no additional energy source other than H2 is available. Unlike most hydrogenases, the C. necator enzymes are O2-tolerant, allowing their efficient utilization in an oxygenic phototroph. Similar to C. necator, the RH produced in Synechocystis showed distinct H2 oxidation activity, confirming that it can be properly matured and assembled under photoautotrophic, i.e., oxygen-evolving conditions. Although the functional H2-sensing cascade has not yet been established in Synechocystis yet, we utilized the associated two-component system consisting of a histidine kinase and a response regulator to drive and modulate the expression of a superfolder gfp gene in Escherichia coli. This demonstrates that all components of the H2-dependent signal cascade can be functionally implemented in heterologous hosts. Thus, this work provides the basis for the development of an intrinsic H2 biosensor within a cyanobacterial cell that could be used to probe the effects of random mutagenesis and systematically identify promising genetic configurations to enable continuous and high-yield production of H2via oxygenic photosynthesis.