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Importance: In the neurotypical brain, regions develop in coordinated patterns, providing a fundamental scaffold for brain function and behavior. Whether altered patterns contribute to clinical profiles in neurodevelopmental conditions, including autism, remains unclear., Objectives: To examine if, in autism, brain regions develop differently in relation to each other and how these differences are associated with molecular/genomic mechanisms and symptomatology., Design, Setting, and Participants: This study was an analysis of one the largest deep-phenotyped, case-control, longitudinal (2 assessments separated by approximately 12-24 months) structural magnetic resonance imaging and cognitive-behavioral autism datasets (EU-AIMS Longitudinal European Autism Project [LEAP]; study dates, February 2014-November 2017) and an out-of-sample validation in the Brain Development Imaging Study (BrainMapASD) independent cohort. Analyses were performed during the 2022 to 2023 period. This multicenter study included autistic and neurotypical children, adolescents, and adults. Autistic participants were included if they had an existing autism diagnosis (DSM-IV/International Statistical Classification of Diseases and Related Health Problems, Tenth Revision or DSM-5 criteria). Autistic participants with co-occurring psychiatric conditions (except psychosis/bipolar disorder) and those taking regular medications were included., Exposures: Neuroanatomy of neurotypical and autistic participants., Main Outcomes and Measures: Intraindividual changes in surface area and cortical thickness over time, analyzed via surface-based morphometrics., Results: A total of 386 individuals in the LEAP cohort (6-31 years at first visit; 214 autistic individuals, mean [SD] age, 17.3 [5.4] years; 154 male [72.0%] and 172 neurotypical individuals, mean [SD] age, 16.35 [5.7] years; 108 male [62.8%]) and 146 individuals in the BrainMapASD cohort (11-18 years at first visit; 49 autistic individuals, mean [SD] age, 14.31 [2.4] years; 42 male [85.7%] and 97 neurotypical individuals, mean [SD] age, 14.10 [2.5] years; 58 male [59.8%]). Maturational between-group differences in cortical thickness and surface area were established that were mostly driven by sensorimotor regions (eg, across features, absolute loadings for early visual cortex ranged from 0.07 to 0.11, whereas absolute loadings for dorsolateral prefrontal cortex ranged from 0.005 to 0.06). Neurodevelopmental differences were transcriptomically enriched for genes expressed in several cell types and during various neurodevelopmental stages, and autism candidate genes (eg, downregulated genes in autism, including those regulating synaptic transmission; enrichment odds ratio =3.7; P =2.6 × -10). A more neurotypical, less autismlike maturational profile was associated with fewer social difficulties and more typical sensory processing (false discovery rate P <.05; Pearson r ≥0.17). Results were replicated in the independently collected BrainMapASD cohort., Conclusions and Relevance: Results of this case-control study suggest that the coordinated development of brain regions was altered in autism, involved a complex interplay of temporally sensitive molecular mechanisms, and may be associated with both lower-order (eg, sensory) and higher-order (eg, social) clinical features of autism. Thus, examining maturational patterns may provide an analytic framework to study the neurobiological origins of clinical profiles in neurodevelopmental/mental health conditions.

Modular hip implants are a clinically successful and widely used treatment for patients with arthritis. Despite ongoing retrieval studies the understanding of the fundamental physico-chemical mechanisms of friction and wear within the head-taper interface is still limited. Here, we Raman-spectroscopically analyze structural features of the biotribological material which is formed within the taper joint between Ti6Al4V and low-carbon cobalt alloy or high-nitrogen steel surfaces in in vitro gross-slip fretting corrosion tests with bovine calf serum. As a function of the fretting duration, we investigate short and long aliphatic chains and their adsorption behavior on the cobalt- and steel-type surfaces. Using the intensity and frequency shifts of the amide I and III Raman bands, we furthermore identify progressive protein folding and unfolding including the secondary structures of α-helix, β-sheet, and random-coil configuration as well as the formation of proteinaceous clusters depending on the hydrophilicity of the metallic surfaces. We additionally find a mixture of chromates and iron oxides with tryptophan and tyrosine at the worn cobalt alloy and high-nitrogen steel surfaces, respectively. Also, for long fretting duration, sp 2 hybridized amorphous carbon is formed due to fretting-induced cleavage of proteins. STATEMENT OF SIGNIFICANCE: Despite efforts enhancing the biomedical tribology of hip implants, the impact of the organic environment on friction and wear at the femoral head-stem taper interface is limitedly understood. Using Raman spectroscopy we resolve structural changes within the biotribological material agglomerated at biomedical-grade metal alloys due to metal-organic interactions during in vitro fretting corrosion tests. Adsorption of short and long aliphatic chains, progressive protein (un)folding and proteinaceous cluster formation depend to a distinguishable extent on the fretting duration and type of alloy. Chromates and iron oxides are mixed with tryptophan and tyrosine, and amorphous carbon is formed resulting from a fretting-induced cleavage of serum proteins. Such information spectroscopically gleaned from biotribological material are vital to improve the design and performance of taper junctions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Multimodal data integration approaches, such as Linked Independent Component Analysis (LICA), increase sensitivity to brain-behaviour relationships and allow us to probe the relationship between modalities. Here we focus on inter-regional functional and structural organisation to determine if organisational patterns persist across modalities and if investigating multi-modality organisations provides increased sensitivity to brain-behaviour associations. We utilised multimodal magnetic resonance imaging (MRI; T1w, resting-state functional [fMRI] and diffusion weighted [DWI]) and behavioural data from the Human Connectome Project (HCP, n=676; 51% female). Unimodal features were extracted to produce individual grey matter density maps, probabilistic tractography connectivity matrices and connectopic maps from the T1w, DWI and fMRI data, respectively. DWI and fMRI analyses were restricted to subcortical regions for computational reasons. LICA was then used to integrate features, generating 100 novel independent components. Associations between these components and demographic/behavioural (n=308) variables were examined. 15 components were significantly associated with various demographic/behavioural measures. 2 components were strongly related to various measures of intoxication, driven by DWI and resemble components previously identified. Another component was driven by striatal functional data and related to working memory. A small number of components showed shared variance between structure and function but none of these displayed any significant behavioural associations. Our working memory findings provide support for the use of fMRI connectopic mapping in future research of working memory. Given the lack of behaviourally relevant shared variance between functional and structural organisation, as indexed here, we question the utility of integrating connectopic maps and tractography data., Competing Interests: Conflict of Interest None to declare

Neuroimaging studies have identified the anterior cingulate cortex (ACC) as one of the major targets of ketamine in the human brain, which may be related to ketamine's antidepressant (AD) mechanisms of action. However, due to different methodological approaches, different investigated populations, and varying measurement timepoints, results are not consistent, and the functional significance of the observed brain changes remains a matter of open debate. Inhibition of glutamate release during acute ketamine administration by lamotrigine provides the opportunity to gain additional insight into the functional significance of ketamine-induced brain changes. Furthermore, the assessment of trait negative emotionality holds promise to link findings in healthy participants to potential AD mechanisms of ketamine. In this double-blind, placebo-controlled, randomized, single dose, parallel-group study, we collected resting-state fMRI data before, during, and 24 h after ketamine administration in a sample of 75 healthy male and female participants who were randomly allocated to one of three treatment conditions (ketamine, ketamine with lamotrigine pre- treatment, placebo). Spontaneous brain activity was extracted from two ventral and one dorsal subregions of the ACC. Our results showed activity decreases during the administration of ketamine in all three ACC subregions. However, only in the ventral subregions of the ACC this effect was attenuated by lamotrigine. 24 h after administration, ACC activity returned to baseline levels, but group differences were observed between the lamotrigine and the ketamine group. Trait negative emotionality was closely linked to activity changes in the subgenual ACC after ketamine administration. These results contribute to an understanding of the functional significance of ketamine effects in different subregions of the ACC by combining an approach to modulate glutamate release with the assessment of multiple timepoints and associations with trait negative emotionality in healthy participants., (© 2024. The Author(s).)

Background: Limited data are available on patients with chronic lung disease (CLD) presenting with acute myocardial infarction (AMI). We aimed to analyse baseline characteristics, treatment and outcome of those patients enrolled in the Swiss nationwide prospective AMIS Plus registry., Methods: All AMI patients enrolled between January 2002 and December 2021 with data on CLD, as defined in the Charlson Comorbidity Index, were included. The primary endpoints were in-hospital mortality and major adverse cardiac and cerebrovascular events (MACCE), defined as all-cause death, reinfarction and cerebrovascular events. Baseline characteristics, in-hospital treatments and outcomes were analysed using descriptive statistics and logistic regression., Results: Among 53,680 AMI patients enrolled during this time, 5.8% had CLD. Compared with patients without CLD, CLD patients presented more frequently with non-ST-elevation myocardial infarction (MI) and type 2 MI (12.8% vs. 6.5%, p < 0.001). With respect to treatment, CLD patients were less likely to receive P2Y12 inhibitors (p < 0.001) and less likely to undergo percutaneous coronary interventions (68.7% vs. 82.5%; p < 0.001). In-hospital mortality declined in AMI patients with CLD over time (from 12% in 2002 to 7.3% in 2021). Multivariable regression analysis showed that CLD was an independent predictor for MACCE (adjusted OR was 1.28 [95% CI 1.07-1.52], p = 0.006)., Conclusion: Patients with CLD and AMI were less likely to receive evidence-based pharmacologic treatments, coronary revascularization and had a higher incidence of MACCE during their hospital stay compared to those without CLD. Over 20 years, in-hospital mortality was significantly reduced in AMI patients, especially in those with CLD., (© 2024 Stichting European Society for Clinical Investigation Journal Foundation. Published by John Wiley & Sons Ltd.)

During the SARS-CoV-2 pandemic, many countries directed substantial resources toward genomic surveillance to detect and track viral variants. There is a debate over how much sequencing effort is necessary in national surveillance programs for SARS-CoV-2 and future pandemic threats. We aimed to investigate the effect of reduced sequencing on surveillance outcomes in a large genomic data set from Switzerland, comprising more than 143k sequences. We employed a uniform downsampling strategy using 100 iterations each to investigate the effects of fewer available sequences on the surveillance outcomes: (i) first detection of variants of concern (VOCs), (ii) speed of introduction of VOCs, (iii) diversity of lineages, (iv) first cluster detection of VOCs, (v) density of active clusters, and (vi) geographic spread of clusters. The impact of downsampling on VOC detection is disparate for the three VOC lineages, but many outcomes including introduction and cluster detection could be recapitulated even with only 35% of the original sequencing effort. The effect on the observed speed of introduction and first detection of clusters was more sensitive to reduced sequencing effort for some VOCs, in particular Omicron and Delta, respectively. A genomic surveillance program needs a balance between societal benefits and costs. While the overall national dynamics of the pandemic could be recapitulated by a reduced sequencing effort, the effect is strongly lineage-dependent-something that is unknown at the time of sequencing-and comes at the cost of accuracy, in particular for tracking the emergence of potential VOCs.IMPORTANCESwitzerland had one of the most comprehensive genomic surveillance systems during the COVID-19 pandemic. Such programs need to strike a balance between societal benefits and program costs. Our study aims to answer the question: How would surveillance outcomes have changed had we sequenced less? We find that some outcomes but also certain viral lineages are more affected than others by sequencing less. However, sequencing to around a third of the original effort still captured many important outcomes for the variants of concern such as their first detection but affected more strongly other measures like the detection of first transmission clusters for some lineages. Our work highlights the importance of setting predefined targets for a national genomic surveillance program based on which sequencing effort should be determined. Additionally, the use of a centralized surveillance platform facilitates aggregating data on a national level for rapid public health responses as well as post-analyses., Competing Interests: The authors declare no conflict of interest.

Modular artificial hip joints are a clinical standard today. However, the release of wear products from the head-taper interface, which includes wear particles in the nm size range, as well as metal ions, have raised concerns. Depending on the loading of such taper joints, a wide variety of different mechanisms have been found by retrieval analyses. From these, this paper concentrates on analyzing the contribution of gross slip fretting corrosion at ultra-mild wear rates using a bovine calf serum solution (BCS) as the lubricant. The parameters were chosen based on biomechanical considerations, producing wear rates of some ng/m wear path. In parallel, the evolution of tribomaterial (third bodies) was analyzed as to its constituents and generation rates. It has already been shown earlier that, by an advantageous combination of wear mechanisms and submechanisms, certain constituents of the tribomaterial remain inside the contact area and act like extreme-pressure lubricant additives. For the known wear and corrosion resistance of austenitic high-nitrogen steels (AHNSs), which outperform CoCrMo alloys even under inflammatory conditions, we hypothesized that such steels will generate ultra-mild wear rates under gross slip fretting. While testing AHNSs against commercially available biomedical-grade materials of CoCrMo and TiAlV alloys, as well as zirconia-toughened alumina (ZTA) and against itself, it was found that AHNSs in combination with a Ti6Al4V alloy generated the smallest wear rate under gross slip fretting corrosion. This paper then discusses the wear behavior on the basis of ex situ analyses of the worn surfaces as to the acting wear mechanisms and submechanisms, as well as to the tribological reaction products.

AbstractClassic evolutionary theory predicts that predation will shift trait means and erode variance within prey species; however, several studies indicate higher behavioral trait variance and trait integration in high-predation populations. These results come predominately from field-sampled animals comparing low- and high-predation sites and thus cannot isolate the role of predation from other ecological factors, including density effects arising from higher predation. Here, we study the role of predation on behavioral trait (co)variation in experimental populations of guppies ( Poecilia reticulata ) living with and without a benthic ambush predator (Jaguar cichlid) to better evaluate the role of predation and where density was equalized among replicates twice per year. At 2.5 years after introduction of the predators (∼10 overlapping generations), 40 males were sampled from each of the six replicate populations and extensively assayed for activity rates, water column use, and latency to feed following disturbance. Individual variation was pronounced in both treatments, with substantial individual variation in means, temporal plasticity, and predictability (inverse residual variance). Predators had little effect on mean behavior, although there was some evidence for greater use of the upper water column in predator-exposed fish. There was greater variance among individuals in water column use in predator-exposed fish, and they habituated more quickly over time; individuals higher in the water column fed slower and had a reduced positive correlation with activity, although again this effect was time specific. Predators also affected the integration of personality and plasticity-among-individual variances in water column use increased, and those in activity decreased, through time-which was absent in controls. Our results contrast with the extensive guppy literature showing rapid evolution in trait means, demonstrating either increases or maintenance of behavioral variance under predation.

Background: Smartphone-based digital phenotyping enables potentially clinically relevant information to be collected as individuals go about their day. This could improve monitoring and interventions for people with Major Depressive Disorder (MDD). The aim of this systematic review was to investigate current digital phenotyping features and methods used in MDD., Methods: We searched PubMed, PsycINFO, Embase, Scopus and Web of Science (10/11/2023) for articles including: (1) MDD population, (2) smartphone-based features, (3) validated ratings. Risk of bias was assessed using several sources. Studies were compared within analysis goals (correlating features with depression, predicting symptom severity, diagnosis, mood state/episode, other). Twenty-four studies (9801 participants) were included., Results: Studies achieved moderate performance. Common themes included challenges from complex and missing data (leading to a risk of bias), and a lack of external validation., Discussion: Studies made progress towards relating digital phenotypes to clinical variables, often focusing on time-averaged features. Methods investigating temporal dynamics more directly may be beneficial for patient monitoring. European Research Council consolidator grant: 101001118, Prospero: CRD42022346264, Open Science Framework: https://osf.io/s7ay4., Competing Interests: Declaration of Competing Interest Alex Leow is on the advisory board for Buoy Health and is a cofounder of KeyWise. Christian Beckmann is a director of SBGNeuro., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

The presence of doubly uniparental inheritance (DUI) in bivalves represents a unique mode of mitochondrial transmission, whereby paternal (male-transmitted M-type) and maternal (female-transmitted F-type) haplotypes are transmitted to offspring separately. Male embryos retain both haplotypes, but the M-type is selectively removed from females. Due to the presence of heteroplasmy in males, mtDNA can recombine resulting in a 'masculinized' haplotype referred to as M f -type. While mtDNA recombination is usually rare, it has been recorded in multiple mussel species across the Northern Hemisphere. Given that mitochondria are the powerhouse of the cell, different mtDNA haplotypes may have different selective advantages under diverse environmental conditions. This may be particularly important for sperm fitness and fertilization success. In this study we aimed to i) determine the presence, prevalence of the M f -type in Australian blue mussels (Mytilus sp.) and ii) investigate the effect of M f -mtDNA on sperm performance (a fitness correlate). We found a high prevalence of recombined mtDNA (≈35 %) located within the control region of the mitochondrial genome, which occurred only in specimens that contained Southern Hemisphere mtDNA. The presence of two female mitotypes were identified in the studied mussels, one likely originating from the Northern Hemisphere, and the other either representing the endemic M. planulatus species or introduced genotypes from the Southern Hemisphere. Despite having recombination events present in a third of the studied population, analysis of sperm performance indicated no difference in fertilization success related to mitotype., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

This work illustrates the use of normative models in a longitudinal neuroimaging study of children aged 6-17 years and demonstrates how such models can be used to make meaningful comparisons in longitudinal studies, even when individuals are scanned with different scanners across successive study waves. More specifically, we first estimated a large-scale reference normative model using Hierarchical Bayesian Regression from N = 42,993 individuals across the lifespan and from dozens of sites. We then transfer these models to a longitudinal developmental cohort (N = 6285) with three measurement waves acquired on two different scanners that were unseen during estimation of the reference models. We show that the use of normative models provides individual deviation scores that are independent of scanner effects and efficiently accommodate inter-site variations. Moreover, we provide empirical evidence to guide the optimization of sample size for the transfer of prior knowledge about the distribution of regional cortical thicknesses. We show that a transfer set containing as few as 25 samples per site can lead to good performance metrics on the test set. Finally, we demonstrate the clinical utility of this approach by showing that deviation scores obtained from the transferred normative models are able to detect and chart morphological heterogeneity in individuals born preterm., (© 2024 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Background: The neurobiology of mental disorders remains poorly understood despite substantial scientific efforts, due to large clinical heterogeneity and to a lack of tools suitable to map individual variability. Normative modeling is one recently successful framework that can address these problems by comparing individuals to a reference population. The methodological underpinnings of normative modelling are, however, relatively complex and computationally expensive. Our research group has developed the python-based normative modelling package Predictive Clinical Neuroscience toolkit (PCNtoolkit) which provides access to many validated algorithms for normative modelling. PCNtoolkit has since proven to be a strong foundation for large scale normative modelling, but still requires significant computation power, time and technical expertise to develop., Methods: To address these problems, we introduce PCNportal. PCNportal is an online platform integrated with PCNtoolkit that offers access to pre-trained research-grade normative models estimated on tens of thousands of participants, without the need for computation power or programming abilities. PCNportal is an easy-to-use web interface that is highly scalable to large user bases as necessary. Finally, we demonstrate how the resulting normalized deviation scores can be used in a clinical application through a schizophrenia classification task applied to cortical thickness and volumetric data from the longitudinal Northwestern University Schizophrenia Data and Software Tool (NUSDAST) dataset., Results: At each longitudinal timepoint, the transferred normative models achieved a mean[std. dev.] explained variance of 9.4[8.8]%, 9.2[9.2]%, 5.6[7.4]% respectively in the control group and 4.7[5.5]%, 6.0[6.2]%, 4.2[6.9]% in the schizophrenia group. Diagnostic classifiers achieved AUC of 0.78, 0.76 and 0.71 respectively., Conclusions: This replicates the utility of normative models for diagnostic classification of schizophrenia and showcases the use of PCNportal for clinical neuroimaging. By facilitating and speeding up research with high-quality normative models, this work contributes to research in inter-individual variability, clinical heterogeneity and precision medicine., Competing Interests: Competing interests: CFB is director and shareholder of SBGNeuro, (Copyright: © 2023 Barkema P et al.)

The inability to control cell proliferation results in the formation of tumors in many multicellular lineages. Nonetheless, little is known about the extent of conservation of the biological traits and ecological factors that promote or inhibit tumorigenesis across the metazoan tree. Particularly, changes in food availability have been linked to increased cancer incidence in humans, as an outcome of evolutionary mismatch. Here, we apply evolutionary oncology principles to test whether food availability, regardless of the multicellular lineage considered, has an impact on tumorigenesis. We used two phylogenetically unrelated model systems, the cnidarian Hydra oligactis and the fish Danio rerio, to investigate the impact of resource availability on tumor occurrence and progression. Individuals from healthy and tumor-prone lines were placed on four diets that differed in feeding frequency and quantity. For both models, frequent overfeeding favored tumor emergence, while lean diets appeared more protective. In terms of tumor progression, high food availability promoted it, whereas low resources controlled it, but without having a curative effect. We discuss our results in light of current ideas about the possible conservation of basic processes governing cancer in metazoans (including ancestral life history trade-offs at the cell level) and in the framework of evolutionary medicine., (© 2023. The Author(s).)

There is intriguing evidence suggesting that ketamine might have distinct acute and delayed neurofunctional effects, as its acute administration transiently induces schizophrenia-like symptoms, while antidepressant effects slowly emerge and are most pronounced 24 h after administration. Studies attempting to characterize ketamine's mechanism of action by using blood oxygen level dependent (BOLD) imaging have yielded inconsistent results regarding implicated brain regions and direction of effects. This may be due to intrinsic properties of the BOLD contrast, while cerebral blood flow (CBF), as measured with arterial spin labeling, is a single physiological marker more directly related to neural activity. As effects of acute ketamine challenge are sensitive to modulation by pretreatment with lamotrigine, which inhibits glutamate release, a combination of these approaches should be particularly suited to offer novel insights. In total, 75 healthy participants were investigated in a double blind, placebo-controlled, randomized, parallel-group study and underwent two scanning sessions (acute/post 24 h.). Acute ketamine administration was associated with higher perfusion in interior frontal gyrus (IFG) and dorsolateral prefrontal cortex (DLPFC), but no other investigated brain region. Inhibition of glutamate release by pretreatment with lamotrigine abolished ketamine's effect on perfusion. At the delayed time point, pretreatment with lamotrigine was associated with lower perfusion in IFG. These findings underscore the idea that regionally selective patterns of CBF changes reflect proximate effects of modulated glutamate release on neuronal activity. Furthermore, region- specific sustained effects indicate both a swift restoration of disturbed homeostasis in DLPFC as well changes occurring beyond the immediate effects on glutamate signaling in IFG., (© 2023. The Author(s).)

An increasing number of patients with type 2 diabetes (T2DM) will require total joint replacement (TJR) in the next decade. T2DM patients are at increased risk for TJR failure, but the mechanisms are not well understood. The current study used the Zucker Diabetic-Sprague Dawley (ZDSD) rat model of T2DM with Sprague Dawley (SPD) controls to investigate the effects of intramedullary implant placement on osseointegration, peri-implant bone structure and matrix composition, and fixation strength at 2 and 10 weeks post-implant placement. Postoperative inflammation was assessed with circulating MCP-1 and IL-10 2 days post-implant placement. In addition to comparing the two groups, stepwise linear regression modeling was performed to determine the relative contribution of glucose, cytokines, bone formation, bone structure, and bone matrix composition on osseointegration and implant fixation strength. ZDSD rats had decreased peri-implant bone formation and reduced trabecular bone volume per total volume compared with SPD controls. The osseointegrated bone matrix of ZDSD rats had decreased mineral-to-matrix and increased crystallinity compared with SPD controls. Osseointegrated bone volume per total volume was not different between the groups, whereas implant fixation was significantly decreased in ZDSD at 2 weeks but not at 10 weeks. A combination of trabecular mineral apposition rate and postoperative MCP-1 levels explained 55.6% of the variance in osseointegration, whereas cortical thickness, osseointegration mineral apposition rate, and matrix compositional parameters explained 69.2% of the variance in implant fixation strength. The results support the growing recognition that both peri-implant structure and matrix composition affect implant fixation and suggest that postoperative inflammation may contribute to poor outcomes after TJR surgeries in T2DM patients. © 2023 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research., (© 2023 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.)

Environmental adversities constitute potent risk factors for psychiatric disorders. Evidence suggests the brain adapts to adversity, possibly in an adversity-type and region-specific manner. However, the long-term effects of adversity on brain structure and the association of individual neurobiological heterogeneity with behavior have yet to be elucidated. Here we estimated normative models of structural brain development based on a lifespan adversity profile in a longitudinal at-risk cohort aged 25 years (n = 169). This revealed widespread morphometric changes in the brain, with partially adversity-specific features. This pattern was replicated at the age of 33 years (n = 114) and in an independent sample at 22 years (n = 115). At the individual level, greater volume contractions relative to the model were predictive of future anxiety. We show a stable neurobiological signature of adversity that persists into adulthood and emphasize the importance of considering individual-level rather than group-level predictions to explain emerging psychopathology., (© 2023. The Author(s).)

Background: Disruptive behavior disorders (DBD) are heterogeneous at the clinical and the biological level. Therefore, the aims were to dissect the heterogeneous neurodevelopmental deviations of the affective brain circuitry and provide an integration of these differences across modalities., Methods: We combined two novel approaches. First, normative modeling to map deviations from the typical age-related pattern at the level of the individual of (i) activity during emotion matching and (ii) of anatomical images derived from DBD cases ( n = 77) and controls ( n = 52) aged 8-18 years from the EU-funded Aggressotype and MATRICS consortia. Second, linked independent component analysis to integrate subject-specific deviations from both modalities., Results: While cases exhibited on average a higher activity than would be expected for their age during face processing in regions such as the amygdala when compared to controls these positive deviations were widespread at the individual level. A multimodal integration of all functional and anatomical deviations explained 23% of the variance in the clinical DBD phenotype. Most notably, the top marker, encompassing the default mode network (DMN) and subcortical regions such as the amygdala and the striatum, was related to aggression across the whole sample., Conclusions: Overall increased age-related deviations in the amygdala in DBD suggest a maturational delay, which has to be further validated in future studies. Further, the integration of individual deviation patterns from multiple imaging modalities allowed to dissect some of the heterogeneity of DBD and identified the DMN, the striatum and the amygdala as neural signatures that were associated with aggression.

Background: Reward processing has been proposed to underpin the atypical social feature of autism spectrum disorder (ASD). However, previous neuroimaging studies have yielded inconsistent results regarding the specificity of atypicalities for social reward processing in ASD., Aims: Utilising a large sample, we aimed to assess reward processing in response to reward type (social, monetary) and reward phase (anticipation, delivery) in ASD., Method: Functional magnetic resonance imaging during social and monetary reward anticipation and delivery was performed in 212 individuals with ASD (7.6-30.6 years of age) and 181 typically developing participants (7.6-30.8 years of age)., Results: Across social and monetary reward anticipation, whole-brain analyses showed hypoactivation of the right ventral striatum in participants with ASD compared with typically developing participants. Further, region of interest analysis across both reward types yielded ASD-related hypoactivation in both the left and right ventral striatum. Across delivery of social and monetary reward, hyperactivation of the ventral striatum in individuals with ASD did not survive correction for multiple comparisons. Dimensional analyses of autism and attention-deficit hyperactivity disorder (ADHD) scores were not significant. In categorical analyses, post hoc comparisons showed that ASD effects were most pronounced in participants with ASD without co-occurring ADHD., Conclusions: Our results do not support current theories linking atypical social interaction in ASD to specific alterations in social reward processing. Instead, they point towards a generalised hypoactivity of ventral striatum in ASD during anticipation of both social and monetary rewards. We suggest this indicates attenuated reward seeking in ASD independent of social content and that elevated ADHD symptoms may attenuate altered reward seeking in ASD.

Genome sequences from evolving infectious pathogens allow quantification of case introductions and local transmission dynamics. We sequenced 11,357 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes from Switzerland in 2020-the sixth largest effort globally. Using a representative subset of these data, we estimated viral introductions to Switzerland and their persistence over the course of 2020. We contrasted these estimates with simple null models representing the absence of certain public health measures. We show that Switzerland's border closures decoupled case introductions from incidence in neighboring countries. Under a simple model, we estimate an 86 to 98% reduction in introductions during Switzerland's strictest border closures. Furthermore, the Swiss 2020 partial lockdown roughly halved the time for sampled introductions to die out. Last, we quantified local transmission dynamics once introductions into Switzerland occurred using a phylodynamic model. We found that transmission slowed 35 to 63% upon outbreak detection in summer 2020 but not in fall. This finding may indicate successful contact tracing over summer before overburdening in fall. The study highlights the added value of genome sequencing data for understanding transmission dynamics.

Introduction: Cognition and emotion are fundamentally integrated in the brain and mutually contribute to behavior. The relation between working memory (WM) and emotion is particularly suited to investigate cognition-emotion interaction since WM is an essential component of many higher cognitive functions. Ketamine affects not only WM but also has a profound impact on emotional processing. Effects of acute ketamine challenge are sensitive to modulation by pretreatment with lamotrigine, which inhibits glutamate release. Accordingly, a combination of these approaches should be particularly suited to investigate cognition-emotion interaction., Methods: Seventy five healthy subjects were investigated in a double-blind, placebo-controlled, randomized, single-dose, parallel-group study with three treatment conditions. All subjects underwent two scanning sessions (acute/post 24 h)., Results: Compared to placebo, acute ketamine administration induced significant dissociative, psychotomimetic, and cognitive effects, as well as an increase in neural activity during WM for positive stimuli. Inhibition of glutamate release by pretreatment with lamotrigine did not influence ketamine's subjective effects, but significantly attenuated its impact on emotional WM and associated neural activity. There was no effect on these measures 24 h after ketamine administration., Conclusion: Our results demonstrate differential acute effects of modulated glutamate release and a swift restoration of disturbed neurobehavioral homeostasis in healthy subjects., (© 2023 S. Karger AG, Basel.)

Abnormal emotional processing in major depressive disorder (MDD) has been associated with increased activation to negative stimuli in cortico-limbic brain regions. The authors investigated whether treatment with BI 1358894, a small-molecule inhibitor of the transient receptor potential cation channel subfamily C leads to attenuated activity in these areas in MDD patients. 73 MDD patients were randomized to receive a single oral dose of BI 1358894 (100 mg), citalopram (20 mg), or matching placebo. Brain responses to emotional faces and scenes were investigated using functional magnetic resonance imaging. Primary endpoints were BOLD signal changes in response to negative faces in cortico-limbic brain regions, i.e. bilateral amygdala (AMY), dorsolateral prefrontal cortex, anterior insula (AI), and anterior cingulate cortex. Secondary endpoints were BOLD signal changes in response to negative scenes. For each region, separate ANOVA models were computed for the comparison of treatments (BI 1358894 or citalopram) vs. placebo. The adjusted treatment differences in the % BOLD signal changes in the faces task showed that BI 1358894 induced signal reduction in bilateral AMY and left AI. In the scenes task, BI 1358894 demonstrated significant signal reduction in bilateral AMY, AI, anterior cingulate cortex and left dorsolateral prefrontal cortex. Citalopram failed to induce any significant reductions in BOLD signal in both tasks. BI 1358894-mediated inhibition of the transient receptor potential cation channel subfamily resulted in strong signal reduction in cortico-limbic brain regions, thereby supporting development of this mechanism of action for MDD patients., Competing Interests: Declaration of Competing Interest SJ, VS, RF, SM, CT, CSchu and AWun are employees of Boehringer Ingelheim International GmbH. SG and CSschm have served as consultants to and received research support from Boehringer Ingelheim International GmbH. CP and LH are consultants for Boehringer Ingelheim International GmbH. CB and MM are employees of SBGneuro contracted to perform the blinded analysis. CK, IN, CB, MM, and AWei have no conflicts to disclose., (Copyright © 2022. Published by Elsevier B.V.)

Background: Difficulties in social communication are a defining clinical feature of autism. However, the underlying neurobiological heterogeneity has impeded targeted therapies and requires new approaches to identifying clinically relevant bio-behavioural subgroups. In the largest autism cohort to date, we comprehensively examined difficulties in facial expression recognition, a key process in social communication, as a bio-behavioural stratification biomarker, and validated them against clinical features and neurofunctional responses., Methods: Between 255 and 488 participants aged 6-30 years with autism, typical development and/or mild intellectual disability completed the Karolinska Directed Emotional Faces task, the Reading the Mind in the Eyes Task and/or the Films Expression Task. We first examined mean-group differences on each test. Then, we used a novel intersection approach that compares two centroid and connectivity-based clustering methods to derive subgroups based on the combined performance across the three tasks. Measures and subgroups were then related to clinical features and neurofunctional differences measured using fMRI during a fearful face-matching task., Results: We found significant mean-group differences on each expression recognition test. However, cluster analyses showed that these were driven by a low-performing autistic subgroup (~ 30% of autistic individuals who performed below 2SDs of the neurotypical mean on at least one test), while a larger subgroup (~ 70%) performed within 1SD on at least 2 tests. The low-performing subgroup also had on average significantly more social communication difficulties and lower activation in the amygdala and fusiform gyrus than the high-performing subgroup., Limitations: Findings of autism expression recognition subgroups and their characteristics require independent replication. This is currently not possible, as there is no other existing dataset that includes all relevant measures. However, we demonstrated high internal robustness (91.6%) of findings between two clustering methods with fundamentally different assumptions, which is a critical pre-condition for independent replication., Conclusions: We identified a subgroup of autistic individuals with expression recognition difficulties and showed that this related to clinical and neurobiological characteristics. If replicated, expression recognition may serve as bio-behavioural stratification biomarker and aid in the development of targeted interventions for a subgroup of autistic individuals., (© 2022. The Author(s).)

The assessment of contaminants of emerging concern, alone and in mixtures, and their effects on marine biota requires attention. 5-Fluorouracil is a cytostatic category 3 anti-cancer medication (IARC) that is used to treat a variety of cancers, including colon, pancreatic, and breast cancer. In the presence of other pollutants, this pharmaceutical can interact and form mixtures of contaminants, such as adhering to plastics and interaction with metal nanoparticles. This study aimed to comprehend the effects of 5-Fluorouracil (5FU; 10 ng/L) and a mixture of emerging contaminants (Mix): silver nanoparticles (nAg; 20 nm; 10 μg/L), polystyrene nanoparticles (nPS; 50 nm; 10 μg/L) and 5FU (10 ng/L), in an in vivo (21 days) exposure of the mussel Mytilus galloprovincialis. A multibiomarker approach namely genotoxicity, the antioxidant defence system (superoxide dismutase (SOD), catalase (CAT), glutathione peroxidases (GPx), glutathione - S - transferases (GST) activities), and oxidative damage (LPO) was used to assess the effects in gills and digestive gland of mussels. Both treatments cause genotoxicity in mussel's haemolymph, and antagonism between contaminants was observed in the Mix. Genotoxicity observed confirms 5FU's mode of action (MoA) by DNA damage. The antioxidant defence system of mussels exposed to 5FU kicked in and counter balanced ROS generated during the exposure, though the same was not seen in Mix-exposed mussels. Mussels were able to withstand the effects of the single compound but not the effects of the Mix. For oxidative stress and damage, the interactions of the components of the mixture have a synergistic effect., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Since the beginning of the coronavirus disease 2019 (COVID-19) pandemic, molecular diagnostics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have taken center stage in the detection of infected individuals for isolation purposes but also in the mass surveillance as a preventive strategy to contain the virus spread. While nasopharyngeal swabs (NPS) have remained the golden standard substrate, salivary diagnostic for SARS-CoV-2 has been proposed as an alternative and noninvasive measure in vulnerable individuals. Nevertheless, there is a widespread assumption that salivary reverse-transcription polymerase chain reaction (RT-PCR) does not match the quality of testing using NPS and particular care should be taken in respect to food or beverage intake, when sampling saliva. Our study indicates that without any precaution in the selection of 190 patients, nor restriction over the time window of sampling, there is 99% match in the COVID-19 positivity between NPS and saliva when using RT-PCR, with a reported Delta in thermal cycles (Cts) values for the viral genes Envelope (E) and Open reading frame 1ab (Orf1ab) between 0 and 2, a 98.7% sensitivity and 100% specificity. This high accuracy is maintained in pooling configurations that can be used for mass-testing purposes in professional and educational settings. The further advantage to using crude saliva as compared to NPS or mouthwash is that direct methods yield robust results. Overall, our study validates and promotes the use of salivary diagnostic for COVID-19 eliminating the need of a medical practitioner for the sampling, resolving the unpleasantness of the NPS intervention and empowering the patient to do self-testing in times of need., (© 2022 The Authors. Journal of Medical Virology published by Wiley Periodicals LLC.)

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by difficulties in social communication, but also great heterogeneity. To offer individualized medicine approaches, we need to better target interventions by stratifying autistic people into subgroups with different biological profiles and/or prognoses. We sought to validate neural responses to faces as a potential stratification factor in ASD by measuring neural (electroencephalography) responses to faces (critical in social interaction) in N = 436 children and adults with and without ASD. The speed of early-stage face processing (N170 latency) was on average slower in ASD than in age-matched controls. In addition, N170 latency was associated with responses to faces in the fusiform gyrus, measured with functional magnetic resonance imaging, and polygenic scores for ASD. Within the ASD group, N170 latency predicted change in adaptive socialization skills over an 18-month follow-up period; data-driven clustering identified a subgroup with slower brain responses and poor social prognosis. Use of a distributional data-driven cutoff was associated with predicted improvements of power in simulated clinical trials targeting social functioning. Together, the data provide converging evidence for the utility of the N170 as a stratification factor to identify biologically and prognostically defined subgroups in ASD.

An increasing number of large-scale multi-modal research initiatives has been conducted in the typically developing population, e.g. Dev. Cogn. Neur. 32:43-54, 2018; PLoS Med. 12(3):e1001779, 2015; Elam and Van Essen, Enc. Comp. Neur., 2013, as well as in psychiatric cohorts, e.g. Trans. Psych. 10(1):100, 2020; Mol. Psych. 19:659-667, 2014; Mol. Aut. 8:24, 2017; Eur. Child and Adol. Psych. 24(3):265-281, 2015. Missing data is a common problem in such datasets due to the difficulty of assessing multiple measures on a large number of participants. The consequences of missing data accumulate when researchers aim to integrate relationships across multiple measures. Here we aim to evaluate different imputation strategies to fill in missing values in clinical data from a large (total N = 764) and deeply phenotyped (i.e. range of clinical and cognitive instruments administered) sample of N = 453 autistic individuals and N = 311 control individuals recruited as part of the EU-AIMS Longitudinal European Autism Project (LEAP) consortium. In particular, we consider a total of 160 clinical measures divided in 15 overlapping subsets of participants. We use two simple but common univariate strategies-mean and median imputation-as well as a Round Robin regression approach involving four independent multivariate regression models including Bayesian Ridge regression, as well as several non-linear models: Decision Trees (Extra Trees., and Nearest Neighbours regression. We evaluate the models using the traditional mean square error towards removed available data, and also consider the Kullback-Leibler divergence between the observed and the imputed distributions. We show that all of the multivariate approaches tested provide a substantial improvement compared to typical univariate approaches. Further, our analyses reveal that across all 15 data-subsets tested, an Extra Trees regression approach provided the best global results. This not only allows the selection of a unique model to impute missing data for the LEAP project and delivers a fixed set of imputed clinical data to be used by researchers working with the LEAP dataset in the future, but provides more general guidelines for data imputation in large scale epidemiological studies., (© 2022. The Author(s).)

Background: Despite various existing scores that predict morbidity and mortality of patients with cirrhotic liver disease (CLD), data on specific risk stratification of patients with CLD undergoing colorectal surgery (CRS) are rare. The aim of this study was to assess in-hospital morbidity and mortality of patients with liver cirrhosis scheduled for CRS, with specific focus on possible pitfalls of surgery in this special cohort., Methods: Between 1996 and 2018, 54 patients with CLD undergoing CRS were identified and included in this study cohort. Postoperative morbidity and mortality were assessed using the Clavien/Dindo (C/D) classification as well as by type of complication. Univariate and multivariate analyses were performed to analyze the predictive factors for increased postoperative morbidity., Results: Of the patients, 37% patients died during the procedure or postoperatively. Major complications were seen in 23.1% of patients (>C/D IIIb). Patients with Child B or C cirrhosis as well as patients undergoing emergency surgery experienced significantly more major complications ( p = 0.04 and p = 0.023, respectively). The most common complications were bleeding requiring blood transfusion (51.1%) and cardiocirculatory instability due to bleeding or sepsis (44.4%). In 53.7% of patients, an anastomosis was created without a protective ostomy. Anastomotic leakage occurred in 20.7% of these patients. Multivariate analysis showed that a primary anastomosis without a protective ostomy was the strongest risk factor for major complications ( p = 0.042)., Discussion: Morbidity and mortality after CRS in patients with CLD remains high and is not only influenced by liver function but also by surgical variables. Considering the high rate of anastomotic leakage, creating a protective or definitive ostomy must be considered with regard to the underlying pathology, the extent of CLD, and the patient's condition. Moreover, our data suggest that surgery in these most fragile patients should be performed only in experienced centers with immediate contact to hepatologists and experts in hemostasis., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 van Beekum, Beckmann, Semaan, Manekeller, Matthaei, Braun, Willis, Kalff and Vilz.)

(1) Background: Some COVID-19 vaccine recipients show breakthrough infection. It remains unknown, which factors contribute to risks and severe outcomes. Our aim was to identify risk factors for SCoV2 breakthrough infections in fully vaccinated individuals. (2) Methods: We conducted a retrospective case-control study from 28 December 2020 to 25 October 2021. Data of all patients with breakthrough infection was compared to data of all vaccine recipients in the Canton of Basel-City, Switzerland. Further, breakthrough infections by Alpha- and Delta-variants were compared. (3) Results: Only 0.39% (488/126,586) of all vaccine recipients suffered from a breakthrough infection during the observational period, whereof most cases were asymptomatic or mild (97.2%). Breakthrough infections after full vaccination occurred in the median after 78 days (IQR 47-123.5). Factors with lower odds for breakthrough infection were age (OR 0.987) and previous COVID-19 infection prior to vaccination (OR 0.296). Factors with higher odds for breakthrough infection included vaccination with Pfizer/BioNTech instead of Moderna (OR 1.459), chronic disease (OR 2.109), and healthcare workers (OR 1.404). (4) Conclusions: Breakthrough infections are rare and mild but can occur early after vaccination. This implies that booster vaccination might be initiated earlier, especially for risk groups. Due to new variants emerging repeatedly, continuous monitoring of breakthrough infections is crucial.

The amplitude of activation in brain resting state networks (RSNs), measured with resting-state functional magnetic resonance imaging, is heritable and genetically correlated across RSNs, indicating pleiotropy. Recent univariate genome-wide association studies (GWASs) explored the genetic underpinnings of individual variation in RSN activity. Yet univariate genomic analyses do not describe the pleiotropic nature of RSNs. In this study, we used a novel multivariate method called genomic structural equation modeling to model latent factors that capture the shared genomic influence on RSNs and to identify single nucleotide polymorphisms (SNPs) and genes driving this pleiotropy. Using summary statistics from GWAS of 21 RSNs reported in UK Biobank (N = 31,688), the genomic latent factor analysis was first conducted in a discovery sample (N = 21,081), and then tested in an independent sample from the same cohort (N = 10,607). In the discovery sample, we show that the genetic organization of RSNs can be best explained by two distinct but correlated genetic factors that divide multimodal association networks and sensory networks. Eleven of the 17 factor loadings were replicated in the independent sample. With the multivariate GWAS, we found and replicated nine independent SNPs associated with the joint architecture of RSNs. Further, by combining the discovery and replication samples, we discovered additional SNP and gene associations with the two factors of RSN amplitude. We conclude that modeling the genetic effects on brain function in a multivariate way is a powerful approach to learn more about the biological mechanisms involved in brain function., (© 2022 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Energy expenditure (EE) is generally viewed as tumorigenic, due to production of reactive oxygen species (ROS) that can damage cells and DNA. On this basis, individuals within a species that sustain high EE should be more likely to develop cancer. Here, we argue the opposite, that high EE may be net protective effect against cancer, despite high ROS production. This is possible because individuals that sustain high EE have a greater energetic capacity (=greater energy acquisition, expenditure and ability to up-regulate output), and can therefore allocate energy to multiple cancer-fighting mechanisms with minimal energetic trade-offs. Our review finds that individuals sustaining high EE have greater antioxidant production, lower oxidative stress, greater immune function and lower cancer incidence. Our hypothesis and literature review suggest that EE may indeed be net protective against cancer, and that individual variation in energetic capacity may be a key mechanism to understand the highly individual nature of cancer risk in contemporary human populations and laboratory animals. Lay summary The process of expending energy generates reactive oxygen species that can lead to oxidative stress, cell and DNA damage, and the accumulation of this damage is thought to be a major contributor to many ageing related diseases that include cancer. Here, we challenge this view, proposing how and why high energy expenditure (EE) may actually be net protective against cancer, and provide literature support for our hypothesis. We find individuals with high sustained EE have greater energetic capacity and thus can invest more in repair to counter oxidative stress, and more in immune function, both of which reduce cancer risk. Our hypothesis provides a novel mechanism to understand the highly individual nature of cancer, why taller individuals are more at risk, why physically active individuals have lower cancer risk, and why regular exercise can reduce cancer risk., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Foundation for Evolution, Medicine, and Public Health.)

Defining reference models for population variation, and the ability to study individual deviations is essential for understanding inter-individual variability and its relation to the onset and progression of medical conditions. In this work, we assembled a reference cohort of neuroimaging data from 82 sites (N=58,836; ages 2-100) and used normative modeling to characterize lifespan trajectories of cortical thickness and subcortical volume. Models are validated against a manually quality checked subset (N=24,354) and we provide an interface for transferring to new data sources. We showcase the clinical value by applying the models to a transdiagnostic psychiatric sample (N=1985), showing they can be used to quantify variability underlying multiple disorders whilst also refining case-control inferences. These models will be augmented with additional samples and imaging modalities as they become available. This provides a common reference platform to bind results from different studies and ultimately paves the way for personalized clinical decision-making., Competing Interests: SR, CF, RD, SK, TW, MZ, PB, AW, SV, DA, LH, JB, PD, PM, RM, AS, CS, IT, ED, SC, BP, MH, SB, LH, DA, CW, LW, RZ, AM No competing interests declared, OA is a consultant for HealthLytix and received speaker's honorarium from Lundbeck and Sunovion, HR received speaker's honorarium from Lundbeck and Janssen, CB is director and shareholder of SBGNeuro Ltd, (© 2022, Rutherford et al.)

Background: The neurocognitive mechanisms underlying autism spectrum disorder (ASD) remain unclear. Progress has been largely hampered by small sample sizes, variable age ranges and resulting inconsistent findings. There is a pressing need for large definitive studies to delineate the nature and extent of key case/control differences to direct research towards fruitful areas for future investigation. Here we focus on perception of biological motion, a promising index of social brain function which may be altered in ASD. In a large sample ranging from childhood to adulthood, we assess whether biological motion preference differs in ASD compared to neurotypical participants (NT), how differences are modulated by age and sex and whether they are associated with dimensional variation in concurrent or later symptomatology., Methods: Eye-tracking data were collected from 486 6-to-30-year-old autistic (N = 282) and non-autistic control (N = 204) participants whilst they viewed 28 trials pairing biological (BM) and control (non-biological, CTRL) motion. Preference for the biological motion stimulus was calculated as (1) proportion looking time difference (BM-CTRL) and (2) peak look duration difference (BM-CTRL)., Results: The ASD group showed a present but weaker preference for biological motion than the NT group. The nature of the control stimulus modulated preference for biological motion in both groups. Biological motion preference did not vary with age, gender, or concurrent or prospective social communicative skill within the ASD group, although a lack of clear preference for either stimulus was associated with higher social-communicative symptoms at baseline., Limitations: The paired visual preference we used may underestimate preference for a stimulus in younger and lower IQ individuals. Our ASD group had a lower average IQ by approximately seven points. 18% of our sample was not analysed for various technical and behavioural reasons., Conclusions: Biological motion preference elicits small-to-medium-sized case-control effects, but individual differences do not strongly relate to core social autism associated symptomatology. We interpret this as an autistic difference (as opposed to a deficit) likely manifest in social brain regions. The extent to which this is an innate difference present from birth and central to the autistic phenotype, or the consequence of a life lived with ASD, is unclear., (© 2021. The Author(s).)

Background: In December 2020, the United Kingdom (UK) reported a SARS-CoV-2 Variant of Concern (VoC) which is now named B.1.1.7. Based on initial data from the UK and later data from other countries, this variant was estimated to have a transmission fitness advantage of around 40-80 % (Volz et al., 2021; Leung et al., 2021; Davies et al., 2021)., Aim: This study aims to estimate the transmission fitness advantage and the effective reproductive number of B.1.1.7 through time based on data from Switzerland., Methods: We generated whole genome sequences from 11.8 % of all confirmed SARS-CoV-2 cases in Switzerland between 14 December 2020 and 11 March 2021. Based on these data, we determine the daily frequency of the B.1.1.7 variant and quantify the variant's transmission fitness advantage on a national and a regional scale., Results: We estimate B.1.1.7 had a transmission fitness advantage of 43-52 % compared to the other variants circulating in Switzerland during the study period. Further, we estimate B.1.1.7 had a reproductive number above 1 from 01 January 2021 until the end of the study period, compared to below 1 for the other variants. Specifically, we estimate the reproductive number for B.1.1.7 was 1.24 [1.07-1.41] from 01 January until 17 January 2021 and 1.18 [1.06-1.30] from 18 January until 01 March 2021 based on the whole genome sequencing data. From 10 March to 16 March 2021, once B.1.1.7 was dominant, we estimate the reproductive number was 1.14 [1.00-1.26] based on all confirmed cases. For reference, Switzerland applied more non-pharmaceutical interventions to combat SARS-CoV-2 on 18 January 2021 and lifted some measures again on 01 March 2021., Conclusion: The observed increase in B.1.1.7 frequency in Switzerland during the study period is as expected based on observations in the UK. In absolute numbers, B.1.1.7 increased exponentially with an estimated doubling time of around 2-3.5 weeks. To monitor the ongoing spread of B.1.1.7, our plots are available online., (Copyright © 2021 The Author(s). Published by Elsevier B.V. All rights reserved.)

Over the past decade, biomarker discovery has become a key goal in psychiatry to aid in the more reliable diagnosis and prognosis of heterogeneous psychiatric conditions and the development of tailored therapies. Nevertheless, the prevailing statistical approach is still the mean group comparison between "cases" and "controls," which tends to ignore within-group variability. In this educational article, we used empirical data simulations to investigate how effect size, sample size, and the shape of distributions impact the interpretation of mean group differences for biomarker discovery. We then applied these statistical criteria to evaluate biomarker discovery in one area of psychiatric research-autism research. Across the most influential areas of autism research, effect size estimates ranged from small (d = 0.21, anatomical structure) to medium (d = 0.36 electrophysiology, d = 0.5, eye-tracking) to large (d = 1.1 theory of mind). We show that in normal distributions, this translates to approximately 45% to 63% of cases performing within 1 standard deviation (SD) of the typical range, i.e., they do not have a deficit/atypicality in a statistical sense. For a measure to have diagnostic utility as defined by 80% sensitivity and 80% specificity, Cohen's d of 1.66 is required, with still 40% of cases falling within 1 SD. However, in both normal and nonnormal distributions, 1 (skewness) or 2 (platykurtic, bimodal) biologically plausible subgroups may exist despite small or even nonsignificant mean group differences. This conclusion drastically contrasts the way mean group differences are frequently reported. Over 95% of studies omitted the "on average" when summarising their findings in their abstracts ("autistic people have deficits in X"), which can be misleading as it implies that the group-level difference applies to all individuals in that group. We outline practical approaches and steps for researchers to explore mean group comparisons for the discovery of stratification biomarkers., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: Jan K Buitelaar has been a consultant to / member of advisory board of / and/or speaker for Shire, Roche, Medice, and Servier. He is not an employee of any of these companies, and not a stock shareholder of any of these companies. He has no other financial or material support, including expert testimony, patents, royalties.Christopher Chatham is a full-time employee of D Hoffmann-La Roche Ltd. Declan Murphy has served on a SAB for Roche; and is running a clinical trial with them. Antonia San José Cáceres is a consultant for Servier Laboratories and is involved in clinical trials conducted by Servier. All other authors declare no conflict of interest.

Globally, outbreaks of Avian Influenza Virus (AIV) in poultry continue to burden economies and endanger human, livestock and wildlife health. Wild waterbirds are often identified as possible sources for poultry infection. Therefore, it is important to understand the ecological and environmental factors that directly influence infection dynamics in wild birds, as these factors may thereby indirectly affect outbreaks in poultry. In Australia, where large parts of the country experience erratic rainfall patterns, intense rainfalls lead to wild waterfowl breeding events at temporary wetlands and increased proportions of immunologically naïve juvenile birds. It is hypothesized that after breeding, when the temporary wetlands dry, increasing densities of immunologically naïve waterbirds returning to permanent water bodies might strongly contribute to AIV prevalence in wild waterfowl in Australia. Since rainfall has been implicated as an important environmental driver in AIV dynamics in wild waterbirds in southeast Australia and wild waterbirds are identified globally to have a role in virus spillover into poultry, we hypothesise that rainfall events have an indirect effect on AIV outbreaks in poultry in southeast Australia. In this study we investigated this hypothesis by examining the correlation between the timing of AIV outbreaks in poultry in and near the Murray-Darling basin in relation to temporal patterns in regional rainfall since 1970. Our findings support our hypothesis and suggest that the risk of AIV outbreaks in poultry increases after a period of high rainfall, with peak AIV risk two years after the onset of the high-rainfall period. This is presumably triggered by increased rates of waterbird breeding and consequent higher proportions of immunologically naïve juvenile waterbirds entering the population directly after major rainfall events, which subsequently aggregate near permanent water bodies when the landscape dries out., (© 2021. The Author(s).)

Chemomechanical preparation of the root canal system is considered to be the most important part of root canal treatment, including both mechanical removal of tissue remnants and dentine chips, and chemical elimination of biofilm and microorganisms. A number of different solutions and agitation techniques have been proposed for that purpose. It was the aim of the present study to investigate whether root canal cleanliness can be improved by using a hydroxyapatite nanoparticle-containing solution with and without sonic or ultrasonic agitation. Seventy-four single-rooted teeth were divided into four experimental groups ( n = 15) and two control groups ( n = 7). All teeth were split longitudinally and a groove and three holes were cut into the root canal wall and filled with dentinal debris. Final irrigation was performed using sodium hypochlorite or a hydroxyapatite nanoparticle-containing solution (Vector polish) activated with a sonically or an ultrasonically driven endodontic file. Two calibrated investigators rated the remaining debris using a four-score scale. The results were analyzed using a non-parametric test with α < 0.05. Sonic and ultrasonic irrigation with sodium hypochlorite cleaned the grooves and holes well from debris. The hydroxyapatite nanoparticles activated by a sonic file cleaned grooves and holes equally well. Ultrasonically activated nanoparticles performance was clearly inferior. The syringe control-group left large amounts of debris in grooves and holes. The use of the hydroxyapatite nanoparticles used in this study did not improve removal of debris.

Background: Psychiatric medication that has a soothing effect on limbic responses to affective stimuli could improve affective instability symptoms as observed in borderline personality disorder (BPD). The objective of this study was to investigate whether citalopram versus placebo reduces the response of the affective neural circuitry during an emotional challenge., Methods: A total of 30 female individuals with a BPD diagnosis participated in a placebo-controlled, double-blind crossover trial design. Three hours after oral drug intake, individuals with BPD viewed affective pictures while undergoing functional magnetic resonance imaging. Blood oxygen level-dependent responses to images of negative affective scenes and faces showing negative emotional expressions were assessed in regions of interest (amygdala, anterior cingulate cortex, anterior insula, dorsolateral prefrontal cortex). Blood perfusion at rest was assessed with arterial spin labeling., Results: The neural response to pictures showing negative affective scenes was not significantly affected by citalopram (n = 23). Citalopram significantly reduced the amygdala response to pictures of faces with negative affective expressions (n = 25, treatment difference left hemisphere: -0.06 ± 0.16, p < .05; right hemisphere: -0.06 ± 0.17, p < .05). We observed no significant effects of citalopram on the other regions. The drug did not significantly alter blood perfusion at rest., Conclusions: Citalopram can alter the amygdala response to affective stimuli in BPD, which is characterized by overly responsive affective neural circuitry., (Copyright © 2021 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Behavioral and physiological ecologists have long been interested in explaining the causes and consequences of trait variation, with a focus on individual differences in mean values. However, the majority of phenotypic variation typically occurs within individuals, rather than among individuals (as indicated by average repeatability being less than 0.5). Recent studies have further shown that individuals can also differ in the magnitude of variation that is unexplained by individual variation or environmental factors (i.e., residual variation). The significance of residual variation, or why individuals differ, is largely unexplained, but is important from evolutionary, methodological, and statistical perspectives. Here, we broadly reviewed literature on individual variation in behavior and physiology, and located 39 datasets with sufficient repeated measures to evaluate individual differences in residual variance. We then analyzed these datasets using methods that permit direct comparisons of parameters across studies. This revealed substantial and widespread individual differences in residual variance. The magnitude of individual variation appeared larger in behavioral traits than in physiological traits, and heterogeneity was greater in more controlled situations. We discuss potential ecological and evolutionary implications of individual differences in residual variance and suggest productive future research directions., Competing Interests: None declared., (© 2021 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.)

The rapid spread of the SARS-CoV-2 lineages B.1.1.7 (N501Y.V1) throughout the UK, B.1.351 (N501Y.V2) in South Africa, and P.1 (B.1.1.28.1; N501Y.V3) in Brazil has led to the definition of variants of concern (VoCs) and recommendations for lineage specific surveillance. In Switzerland, during the last weeks of December 2020, we established a nationwide screening protocol across multiple laboratories, focusing first on epidemiological and microbiological definitions. In January 2021, we validated and implemented an N501Y-specific PCR to rapidly screen for VoCs, which are then confirmed using amplicon sequencing or whole genome sequencing (WGS). A total of 13,387 VoCs have been identified since the detection of the first Swiss case in October 2020, with 4194 being B.1.1.7, 172 B.1.351, and 7 P.1. The remaining 9014 cases of VoCs have been described without further lineage specification. Overall, all diagnostic centers reported a rapid increase of the percentage of detected VOCs, with a range of 6 to 46% between 25 to 31 of January 2021 increasing towards 41 to 82% between 22 to 28 of February. A total of 739 N501Y positive genomes were analysed and show a broad range of introduction events to Switzerland. In this paper, we describe the nationwide coordination and implementation process across laboratories, public health institutions, and researchers, the first results of our N501Y-specific variant screening, and the phylogenetic analysis of all available WGS data in Switzerland, that together identified the early introduction events and subsequent community spreading of the VoCs.

Following a lack of detected change in white shark Carcharodon carcharias L. 1758 diet and nutritional condition attributed to the interaction with the cage-diving industry, Lusseau and Derous (Tourism Management, 2019, 75, 547-549) cautioned the use of muscle lipids and fatty acids in this context, advocating for other biomarkers. This study provides additional evidence from peer-reviewed literature to contend the usefulness of elasmobranch muscle fatty acid profiles to detail diet and habitat use. It also presents findings from a controlled experiment on captive Port Jackson sharks Heterodontus portusjacksoni (Meyer 1793) whereby long-term (daily for 33 days) 3 min exhaustive chase exercise changed muscle lipid class profiles, supporting its use to infer nutritional condition after activities such as interactions with wildlife tourism operators. Conversely, the unaltered muscle fatty acid and lipid content suggests their use in trophic ecology is not confounded by activities such as interacting with tourism operators, remaining useful biomarkers to investigate diet and habitat use., (© 2020 Fisheries Society of the British Isles.)

Research on the gut-brain axis has accelerated substantially over the course of the last years. Many reviews have outlined the important implications of understanding the relation of the gut microbiota with human brain function and behavior. One substantial drawback in integrating gut microbiome and brain data is the lack of integrative multivariate approaches that enable capturing variance in both modalities simultaneously. To address this issue, we applied a linked independent component analysis (LICA) to microbiota and brain connectivity data.We analyzed data from 58 healthy females (mean age =  21.5 years). Magnetic Resonance Imaging data were acquired using resting state functional imaging data. The assessment of gut microbial composition from feces was based on sequencing of the V4 16S rRNA gene region. We used the LICA model to simultaneously factorize the subjects' large-scale brain networks and microbiome relative abundance data into 10 independent components of spatial and abundance variation.LICA decomposition resulted in four components with non-marginal contribution of the microbiota data. The default mode network featured strongly in three components, whereas the two-lateralized fronto-parietal attention networks contributed to one component. The executive-control (with the default mode) network was associated to another component. We found that the abundance of Prevotella genus was associated with the strength of expression of all networks, whereas Bifidobacterium was associated with the default mode and frontoparietal-attention networks.We provide the first exploratory evidence for multivariate associative patterns between the gut microbiota and brain network connectivity in healthy humans considering the complexity of both systems.

A key principle of brain organization is the functional integration of brain regions into interconnected networks. Functional MRI scans acquired at rest offer insights into functional integration via patterns of coherent fluctuations in spontaneous activity, known as functional connectivity. These patterns have been studied intensively and have been linked to cognition and disease. However, the field is fractionated. Diverging analysis approaches have segregated the community into research silos, limiting the replication and clinical translation of findings. A primary source of this fractionation is the diversity of approaches used to reduce complex brain data into a lower-dimensional set of features for analysis and interpretation, which we refer to as brain representations. In this Primer, we provide an overview of different brain representations, lay out the challenges that have led to the fractionation of the field and that continue to form obstacles for convergence, and propose concrete guidelines to unite the field.

Brain growth charts and age-normed brain templates are essential resources for researchers to eventually contribute to the care of individuals with atypical developmental trajectories. The present work generates age-normed brain templates for children and adolescents at one-year intervals and the corresponding growth charts to investigate the influences of age and ethnicity using a common pediatric neuroimaging protocol. Two accelerated longitudinal cohorts with the identical experimental design were implemented in the United States and China. Anatomical magnetic resonance imaging (MRI) of typically developing school-age children (TDC) was obtained up to three times at nominal intervals of 1.25 years. The protocol generated and compared population- and age-specific brain templates and growth charts, respectively. A total of 674 Chinese pediatric MRI scans were obtained from 457 Chinese TDC and 190 American pediatric MRI scans were obtained from 133 American TDC. Population- and age-specific brain templates were used to quantify warp cost, the differences between individual brains and brain templates. Volumetric growth charts for labeled brain network areas were generated. Shape analyses of cost functions supported the necessity of age-specific and ethnicity-matched brain templates, which was confirmed by growth chart analyses. These analyses revealed volumetric growth differences between the two ethnicities primarily in lateral frontal and parietal areas, regions which are most variable across individuals in regard to their structure and function. Age- and ethnicity-specific brain templates facilitate establishing unbiased pediatric brain growth charts, indicating the necessity of the brain charts and brain templates generated in tandem. These templates and growth charts as well as related codes have been made freely available to the public for open neuroscience (https://github.com/zuoxinian/CCS/tree/master/H3/GrowthCharts)., Competing Interests: Conflict of interest The authors declare that they have no conflict of interest., (Copyright © 2020 Science China Press. Published by Elsevier B.V. All rights reserved.)

Cellular cheating leading to cancers exists in all branches of multicellular life, favoring the evolution of adaptations to avoid or suppress malignant progression, and/or to alleviate its fitness consequences. Ecologists have until recently largely neglected the importance of cancer cells for animal ecology, presumably because they did not consider either the potential ecological or evolutionary consequences of anticancer adaptations. Here, we review the diverse ways in which the evolution of anticancer adaptations has significantly constrained several aspects of the evolutionary ecology of multicellular organisms at the cell, individual, population, species, and ecosystem levels and suggest some avenues for future research., (© 2020.)

Increased physical activity reduces cancer risk in humans, but why this whole-organism attribute reduces cancer remains unclear. Active individuals tend to have high capacity to generate energy on a sustained basis, which in turn can permit greater immune responses crucial for fighting emerging neoplasia. Thus, we suggest energetic capacity as a potential mechanism to explain the activity-cancer link, given that humans are intrinsically (not externally) energy limited. Human and rodent studies show that individuals with high energetic capacity mount greater immune responses and have lower cancer incidence; these trends persist after controlling for actual physical activity, supporting a direct role of energetic capacity. If true, exercise efforts might best target those that increase one's energetic capacity, which may be both individual and exercise specific., (Copyright © 2020 Elsevier Inc. All rights reserved.)

In the last few years the involvement of the medial prefrontal cortex (mPFC) in memory processing has received increased attention. It has been shown to be centrally involved when we use prior knowledge (schemas) to improve learning of related material. With the mPFC also being one of the core hubs of the default mode network (DMN) and the DMN's role in memory retrieval, we decided to investigate whether the mPFC in a schema paradigm acts independent of the DMN. We tested this with data from a cross-sectional developmental study with a schema paradigm. During retrieval of schema items, the mPFC decoupled from the DMN with the degree of decoupling predicting memory performance. This finding suggests that a demand specific reconfiguration of the DMN supports schema memory. Additionally, we found that in the control condition, which relied on episodic memory, activity in the parahippocampal gyrus was positively related to memory performance. We interpret these results as a demand specific network reconfiguration of the DMN: a decoupling of the mPFC to support schema memory and a decoupling of the parahippocampal gyrus facilitating episodic memory., (Copyright © 2020. Published by Elsevier Inc.)

Investigating the contribution of biology to human cognition has assumed a bottom-up causal cascade where genes influence brain systems that activate, communicate, and ultimately drive behavior. Yet few studies have directly tested whether cognitive traits with overlapping genetic underpinnings also rely on overlapping brain systems. Here, we report a step-wise exploratory analysis of genetic and functional imaging overlaps among cognitive traits. We used twin-based genetic analyses in the human connectome project (HCP) dataset (N ​= ​486), in which we quantified the heritability of measures of cognitive functions, and tested whether they were driven by common genetic factors using pairwise genetic correlations. Subsequently, we derived activation maps associated with cognitive tasks via functional imaging meta-analysis in BrainMap (N ​= ​4484), and tested whether cognitive traits that shared genetic variation also exhibited overlapping brain activation. Our genetic analysis determined that six cognitive measures (cognitive flexibility, no-go continuous performance, fluid intelligence, processing speed, reading decoding and vocabulary comprehension) were heritable (0.3 ​< ​h 2  ​< ​0.5), and genetically correlated with at least one other heritable cognitive measure (0.2 ​< ​ρ g  ​< ​0.35). The meta-analysis showed that two genetically-correlated traits, cognitive flexibility and fluid intelligence (ρ g  ​= ​0.24), also had a significant brain activation overlap (ρ perm  ​= ​0.29). These findings indicate that fluid intelligence and cognitive flexibility rely on overlapping biological features, both at the neural systems level and at the molecular level. The cross-disciplinary approach we introduce provides a concrete framework for data-driven quantification of biological convergence between genetics, brain function, and behavior in health and disease., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Autism spectrum disorder (ASD) is a neurodevelopmental condition with key deficits in social functioning. It is widely assumed that the biological underpinnings of social impairment are neurofunctional alterations in the "social brain," a neural circuitry involved in inferring the mental state of a social partner. However, previous evidence comes from small-scale studies and findings have been mixed. We therefore carried out the to-date largest study on neural correlates of mentalizing in ASD., Methods: As part of the Longitudinal European Autism Project, we performed functional magnetic resonance imaging at six European sites in a large, well-powered, and deeply phenotyped sample of individuals with ASD (N = 205) and typically developing (TD) individuals (N = 189) aged 6 to 30 years. We presented an animated shapes task to assess and comprehensively characterize social brain activation during mentalizing. We tested for effects of age, diagnosis, and their association with symptom measures, including a continuous measure of autistic traits., Results: We observed robust effects of task. Within the ASD sample, autistic traits were moderately associated with functional activation in one of the key regions of the social brain, the dorsomedial prefrontal cortex. However, there were no significant effects of diagnosis on task performance and no effects of age and diagnosis on social brain responses. Besides a lack of mean group differences, our data provide no evidence for meaningful differences in the distribution of brain response measures. Extensive control analyses suggest that the lack of case-control differences was not due to a variety of potential confounders., Conclusions: Contrary to prior reports, this large-scale study does not support the assumption that altered social brain activation during mentalizing forms a common neural marker of ASD, at least with the paradigm we employed. Yet, autistic individuals show socio-behavioral deficits. Our work therefore highlights the need to interrogate social brain function with other brain measures, such as connectivity and network-based approaches, using other paradigms, or applying complementary analysis approaches to assess individual differences in this heterogeneous condition.

Overweight and obesity are considered among the major health concerns worldwide. The body mass index is a frequently used measure for overweight and obesity and is associated with common non-communicable diseases such as diabetes type II, cardiovascular diseases and certain cancers. However, the body mass index does not account for the distribution of body fat and relative fat to muscle mass. 3D laser-based photonic full body scans provide detailed information on various body circumferences, surfaces, and volumes as well as body height and weight (using an integrated scale). In the literature, body scans showed good feasibility, reliability, and validity, while also demonstrating a good correlation with health parameters linked to the metabolic syndrome. However, systematic differences between body scan derived measurements and manual measurements remain an issue. This study aimed to assess these systematic differences for body height, waist circumference, and body mass index using cross-sectional data from a homogenous sample of 52 young Swiss male volunteers. In addition to 3D laser-based photonic full body scans and correlative manual measurements, body fat distribution was assessed through bioelectrical impedance analysis. Overall, an excellent correlation was found between measurements of waist circumference and body mass index, and good correlation between body mass index and total fat mass, as well as between waist circumference and visceral fat mass as assessed by bioelectrical impedance analysis. Volunteers were shorter in height measured by body scan when compared to manual measurements. This systematic difference became smaller when volunteers stood in the scanner in a completely upright position with their feet together. Waist circumference was slightly smaller for manual measurements than for body scan derived values. This systematic difference was larger in overweight volunteers compared to leaner volunteers., Competing Interests: The authors declare there are no competing interests., (©2019 Beckmann et al.)