Checkpoint kinase 2 controls insulin secretion and glucose homeostasis.

After the discovery of insulin, a century ago, extensive work has been done to unravel the molecular network regulating insulin secretion. Here we performed a chemical screen and identified AZD7762, a compound that potentiates glucose-stimulated insulin secretion (GSIS) of a human ß cell line, healthy and type 2 diabetic (T2D) human islets and primary cynomolgus macaque islets. In vivo studies in diabetic mouse models and cynomolgus macaques demonstrated that AZD7762 enhances GSIS and improves glucose tolerance. Furthermore, genetic manipulation confirmed that ablation of CHEK2 in human ß cells results in increased insulin secretion. Consistently, high-fat-diet-fed Chk2-/- mice show elevated insulin secretion and improved glucose clearance. Finally, untargeted metabolic profiling demonstrated the key role of the CHEK2-PP2A-PLK1-G6PD-PPP pathway in insulin secretion. This study successfully identifies a previously unknown insulin secretion regulating pathway that is conserved across rodents, cynomolgus macaques and human ß cells in both healthy and T2D conditions.

Covariation of preadult environmental exposures, adult brain imaging phenotypes, and adult personality traits.

Exposure to preadult environmental exposures may have long-lasting effects on mental health by affecting the maturation of the brain and personality, two traits that interact throughout the developmental process. However, environment-brain-personality covariation patterns and their mediation relationships remain unclear. In 4297 healthy participants (aged 18-30 years), we combined sparse multiple canonical correlation analysis with independent component analysis to identify the three-way covariation patterns of 59 preadult environmental exposures, 760 adult brain imaging phenotypes, and five personality traits, and found two robust environment-brain-personality covariation models with sex specificity. One model linked greater stress and less support to weaker functional connectivity and activity in the default mode network, stronger activity in subcortical nuclei, greater thickness and volume in the occipital, parietal and temporal cortices, and lower agreeableness, consciousness and extraversion as well as higher neuroticism. The other model linked higher urbanicity and better socioeconomic status to stronger functional connectivity and activity in the sensorimotor network, smaller volume and surface area and weaker functional connectivity and activity in the medial prefrontal cortex, lower white matter integrity, and higher openness to experience. We also conducted mediation analyses to explore the potential bidirectional mediation relationships between adult brain imaging phenotypes and personality traits with the influence of preadult environmental exposures and found both environment-brain-personality and environment-personality-brain pathways. We finally performed moderated mediation analyses to test the potential interactions between macro- and microenvironmental exposures and found that one category of exposure moderated the mediation pathways of another category of exposure. These results improve our understanding of the effects of preadult environmental exposures on the adult brain and personality traits and may facilitate the design of targeted interventions to improve mental health by reducing the impact of adverse environmental exposures.

Connectivity gradients in spontaneous brain activity at multiple frequency bands.

The intrinsic organizational structure of the brain is reflected in spontaneous brain oscillations. Its functional integration and segregation hierarchy have been discovered in space by leveraging gradient approaches to low-frequency functional connectivity. This hierarchy of brain oscillations has not yet been fully understood, since previous studies have mainly concentrated on the brain oscillations from a single limited frequency range (~ 0.01-0.1 Hz). In this work, we extended the frequency range and performed gradient analysis across multiple frequency bands of fast resting-state fMRI signals from the Human Connectome Project and condensed a frequency-rank cortical map of the highest gradient. We found that the coarse skeletons of the functional organization hierarchy are generalizable across the multiple frequency bands. Beyond that, the highest integration levels of connectivity vary in the frequency domain across different large-scale brain networks. These findings are replicated in another independent dataset and demonstrated that different brain networks can integrate information at varying rates, indicating the significance of examining the intrinsic architecture of spontaneous brain activity from the perspective of multiple frequency bands.

Shifting gradients of macroscale cortical organization mark the transition from childhood to adolescence.

The transition from childhood to adolescence is marked by pronounced shifts in brain structure and function that coincide with the development of physical, cognitive, and social abilities. Prior work in adult populations has characterized the topographical organization of the cortex, revealing macroscale functional gradients that extend from unimodal (somatosensory/motor and visual) regions through the cortical association areas that underpin complex cognition in humans. However, the presence of these core functional gradients across development as well as their maturational course have yet to be established. Here, leveraging 378 resting-state functional MRI scans from 190 healthy individuals aged 6 to 17 y old, we demonstrate that the transition from childhood to adolescence is reflected in the gradual maturation of gradient patterns across the cortical sheet. In children, the overarching organizational gradient is anchored within the unimodal cortex, between somatosensory/motor and visual territories. Conversely, in adolescence, the principal gradient of connectivity transitions into an adult-like spatial framework, with the default network at the opposite end of a spectrum from primary sensory and motor regions. The observed gradient transitions are gradually refined with age, reaching a sharp inflection point in 13 and 14 y olds. Functional maturation was nonuniformly distributed across cortical networks. Unimodal networks reached their mature positions early in development, while association regions, in particular the medial prefrontal cortex, reached a later peak during adolescence. These data reveal age-dependent changes in the macroscale organization of the cortex and suggest the scheduled maturation of functional gradient patterns may be critically important for understanding how cognitive and behavioral capabilities are refined across development.

Homotopic local-global parcellation of the human cerebral cortex from resting-state functional connectivity.

Resting-state fMRI is commonly used to derive brain parcellations, which are widely used for dimensionality reduction and interpreting human neuroscience studies. We previously developed a model that integrates local and global approaches for estimating areal-level cortical parcellations. The resulting local-global parcellations are often referred to as the Schaefer parcellations. However, the lack of homotopic correspondence between left and right Schaefer parcels has limited their use for brain lateralization studies. Here, we extend our previous model to derive homotopic areal-level parcellations. Using resting-fMRI and task-fMRI across diverse scanners, acquisition protocols, preprocessing and demographics, we show that the resulting homotopic parcellations are as homogeneous as the Schaefer parcellations, while being more homogeneous than five publicly available parcellations. Furthermore, weaker correlations between homotopic parcels are associated with greater lateralization in resting network organization, as well as lateralization in language and motor task activation. Finally, the homotopic parcellations agree with the boundaries of a number of cortical areas estimated from histology and visuotopic fMRI, while capturing sub-areal (e.g., somatotopic and visuotopic) features. Overall, these results suggest that the homotopic local-global parcellations represent neurobiologically meaningful subdivisions of the human cerebral cortex and will be a useful resource for future studies. Multi-resolution parcellations estimated from 1479 participants are publicly available (https://github.com/ThomasYeoLab/CBIG/tree/master/stable_projects/brain_parcellation/Yan2023_homotopic).

Gene transcriptional expression of cortical thinning during childhood and adolescence.

The cognitive and behavioral development of children and adolescents is closely related to the maturation of brain morphology. Although the trajectory of brain development has been depicted in detail, the underlying biological mechanism of normal cortical morphological development in childhood and adolescence remains unclear. By combining the Allen Human Brain Atlas dataset with two single-site magnetic resonance imaging data including 427 and 733 subjects from China and the United States, respectively, we performed partial least squares regression and enrichment analysis to explore the relationship between the gene transcriptional expression and the development of cortical thickness in childhood and adolescence. We found that the spatial model of normal cortical thinning during childhood and adolescence is associated with genes expressed predominantly in astrocytes, microglia, excitatory and inhibitory neurons. Top cortical development-related genes are enriched for energy-related and DNA-related terms and are associated with psychological and cognitive disorders. Interestingly, there is a great deal of similarity between the findings derived from the two single-site datasets. This fills the gap between early cortical development and transcriptomes, which promotes an integrative understanding of the potential biological neural mechanisms.

Blood urea nitrogen to creatinine ratio is associated with physical frailty in older-aged Chinese: a cross-sectional study.

BACKGROUND: The relationship between the ratio of blood urea nitrogen to creatinine (BUN/Cr) and physical frailty in elderly patients remains unclear. The study aims to investigate the association between the BUN/Cr ratio and physical frailty in the elderly Chinese population. METHODS: In this cross-sectional analysis, the clinical data of 5213 participants from 2015 were selected from the China Health and Retirement Longitudinal Study (CHARLS). The demographic variables (including age and gender) and health behavior (including smoking and drinking history), anthropometric (including systolic and diastolic blood pressure, waist circumference (WC), etc.), physical performances (i.e., grip strength, repeated chair stands, etc.), and biochemical indicators (i.e., blood urea nitrogen (BUN), creatinine(Cr), total cholesterol (TC), triglycerides (TG), etc.) were measured. The association between the BUN/Cr ratio and physical frailty was analyzed. RESULTS: After adjusting for potential confounding factors, smooth curve fitting showed a linear relationship between the BUN/Cr ratio and grip strength, a non-linear relationship between the BUN/Cr ratio, and repeated chair-rising time. The fully adjusted linear regression results showed a negative association between the BUN/Cr ratio and grip strength. In the multivariate, piecewise linear regression, when the BUN/Cr ratio was greater than 18.60, the repeated chair-rising time increased with the increase in BUN/Cr ratio (ß = 0.046, 95%CI 0.025, 0.066; p < 0.001). However, we did not observe a significant correlation when the BUN/Cr ratio was less than 18.60 (ß = -0.007, 95%CI -0.046, 0.032; p = 0.717). CONCLUSION: This study demonstrated that the BUN/Cr ratio might be associated with physical frailty in older-aged Chinese, and this association requires further investigation.

Growth charts of brain morphometry for preschool children.

Brain development from 1 to 6 years of age anchors a wide range of functional capabilities and carries early signs of neurodevelopmental disorders. However, quantitative models for depicting brain morphology changes and making individualized inferences are lacking, preventing the identification of early brain atypicality during this period. With a sample size of 285, we characterized the age dependence of the cortical thickness and subcortical volume in neurologically normal children and constructed quantitative growth charts of all brain regions for preschool children. While the cortical thickness of most brain regions decreased with age, the entorhinal and parahippocampal regions displayed an inverted-U shape of age dependence. Compared to the cortical thickness, the normalized volume of subcortical regions exhibited more divergent trends, with some regions increasing, some decreasing, and some displaying inverted-U-shaped trends. The growth curve models for all brain regions demonstrated utilities in identifying brain atypicality. The percentile measures derived from the growth curves facilitate the identification of children with developmental speech and language disorders with an accuracy of 0.875 (area under the receiver operating characteristic curve: 0.943). Our results fill the knowledge gap in brain morphometrics in a critical development period and provide an avenue for individualized brain developmental status evaluation with demonstrated sensitivity. The brain growth charts are shared with the public (http://phi-group.top/resources.html).

Impaired Ocular Tracking and Cortical Atrophy in Idiopathic Rapid Eye Movement Sleep Behavior Disorder.

BACKGROUND: Idiopathic rapid eye movement sleep behavior disorder (iRBD) is a prodromal stage of synucleinopathies. Patients with synucleinopathies frequently display eye movement abnormalities. However, whether patients with iRBD have eye movement abnormalities remains unknown. OBJECTIVE: The aim of this study was to assess eye movement abnormalities and related gray matter alterations and explore whether such abnormalities can serve as biomarkers to indicate phenoconversion to synucleinopathies in iRBD. METHODS: Forty patients with iRBD with early disease progression and 35 healthy control subjects participated in a 15-minute ocular-tracking task that evaluated their control of eye movement abilities. They also underwent clinical assessments for olfactory function, nonmotor symptoms, and autonomic symptoms, all of which are biomarkers to predict phenoconversion to synucleinopathies in iRBD. A subgroup of the participants (20 patients with iRBD and 20 healthy control subjects) also participated in structural magnetic resonance imaging. RESULTS: The ocular-tracking ability in patients with iRBD was inferior to that of healthy control subjects in two aspects: pursuit initiation and steady-state tracking. Cortical thinning in the right visual area V4 in patients with iRBD is coupled with impaired pursuit initiation. Furthermore, prolonged pursuit initiation in patients with iRBD exhibits a trend of correlation with olfactory loss, the earliest biomarker that develops prior to other prodromal biomarkers. CONCLUSIONS: We found ocular-tracking abnormalities in patients with iRBD even early in their disease progression that have not been reported before. These abnormalities are coupled with atrophy of brain areas involved in the perception of object motion and might indicate phenoconversion to synucleinopathies in iRBD. © 2022 International Parkinson and Movement Disorder Society.

Eliminating accidental deviations to minimize generalization error and maximize replicability: Applications in connectomics and genomics.

Replicability, the ability to replicate scientific findings, is a prerequisite for scientific discovery and clinical utility. Troublingly, we are in the midst of a replicability crisis. A key to replicability is that multiple measurements of the same item (e.g., experimental sample or clinical participant) under fixed experimental constraints are relatively similar to one another. Thus, statistics that quantify the relative contributions of accidental deviations-such as measurement error-as compared to systematic deviations-such as individual differences-are critical. We demonstrate that existing replicability statistics, such as intra-class correlation coefficient and fingerprinting, fail to adequately differentiate between accidental and systematic deviations in very simple settings. We therefore propose a novel statistic, discriminability, which quantifies the degree to which an individual's samples are relatively similar to one another, without restricting the data to be univariate, Gaussian, or even Euclidean. Using this statistic, we introduce the possibility of optimizing experimental design via increasing discriminability and prove that optimizing discriminability improves performance bounds in subsequent inference tasks. In extensive simulated and real datasets (focusing on brain imaging and demonstrating on genomics), only optimizing data discriminability improves performance on all subsequent inference tasks for each dataset. We therefore suggest that designing experiments and analyses to optimize discriminability may be a crucial step in solving the replicability crisis, and more generally, mitigating accidental measurement error.

Tunable Dirac states in doped B2S3 monolayers.

Two-dimensional (2D) Dirac materials have been a research hotspot due to their intriguing properties, such as high carrier mobility and ballistic charge transport. Here, we demonstrate that the B2S3 monolayer with a hexagonal structure, which has been reported as a photocatalyst, can be tuned to new 2D Dirac materials by doping atoms. The Young's modulus can reach 65.23 N m-1, indicating that the monolayer can be used as a buffer materials. The electronic structures of the pristine B2S3 monolayer show that some Dirac points appear but do not occur exactly on the Fermi level (EF). Fortunately, we find that the Dirac cone can be tuned to the EF by doping C, N, or Sn atoms. The C-doped B2S3 monolayer can be a half-metallic Dirac material, which has significant potential application in spintronics. For N- and Sn-doped B2S3 monolayers, the typical kagome bands are formed near the EF, which arise from three molecular orbitals hybridized by B, S, and N (Sn) atoms. These outstanding properties render the doped B2S3 monolayers promising 2D Dirac materials for future nanoelectronic devices.

Individual-Specific Areal-Level Parcellations Improve Functional Connectivity Prediction of Behavior.

Resting-state functional magnetic resonance imaging (rs-fMRI) allows estimation of individual-specific cortical parcellations. We have previously developed a multi-session hierarchical Bayesian model (MS-HBM) for estimating high-quality individual-specific network-level parcellations. Here, we extend the model to estimate individual-specific areal-level parcellations. While network-level parcellations comprise spatially distributed networks spanning the cortex, the consensus is that areal-level parcels should be spatially localized, that is, should not span multiple lobes. There is disagreement about whether areal-level parcels should be strictly contiguous or comprise multiple noncontiguous components; therefore, we considered three areal-level MS-HBM variants spanning these range of possibilities. Individual-specific MS-HBM parcellations estimated using 10 min of data generalized better than other approaches using 150 min of data to out-of-sample rs-fMRI and task-fMRI from the same individuals. Resting-state functional connectivity derived from MS-HBM parcellations also achieved the best behavioral prediction performance. Among the three MS-HBM variants, the strictly contiguous MS-HBM exhibited the best resting-state homogeneity and most uniform within-parcel task activation. In terms of behavioral prediction, the gradient-infused MS-HBM was numerically the best, but differences among MS-HBM variants were not statistically significant. Overall, these results suggest that areal-level MS-HBMs can capture behaviorally meaningful individual-specific parcellation features beyond group-level parcellations. Multi-resolution trained models and parcellations are publicly available (https://github.com/ThomasYeoLab/CBIG/tree/master/stable_projects/brain_parcellation/Kong2022_ArealMSHBM).

CHIMGEN: a Chinese imaging genetics cohort to enhance cross-ethnic and cross-geographic brain research.

The Chinese Imaging Genetics (CHIMGEN) study establishes the largest Chinese neuroimaging genetics cohort and aims to identify genetic and environmental factors and their interactions that are associated with neuroimaging and behavioral phenotypes. This study prospectively collected genomic, neuroimaging, environmental, and behavioral data from more than 7000 healthy Chinese Han participants aged 18-30 years. As a pioneer of large-sample neuroimaging genetics cohorts of non-Caucasian populations, this cohort can provide new insights into ethnic differences in genetic-neuroimaging associations by being compared with Caucasian cohorts. In addition to micro-environmental measurements, this study also collects hundreds of quantitative macro-environmental measurements from remote sensing and national survey databases based on the locations of each participant from birth to present, which will facilitate discoveries of new environmental factors associated with neuroimaging phenotypes. With lifespan environmental measurements, this study can also provide insights on the macro-environmental exposures that affect the human brain as well as their timing and mechanisms of action.

Coordination Polymer Derived Porous Carbon Activated in Situ by the ZnCl2 Dot: Capacitances Greatly Enhanced by Redox-Activity Additives in Electrolytes.

Herein, a 1D zinc coordination polymer [Zn(bibp)Cl2]∞ (CP-2-ZX) was assembled from the reaction of 4,4'-bis(imidazol-1-yl)-biphenyl (bibp) with ZnCl2. Through a calcination-thermolysis strategy, sponge-like highly porous carbon AC-Zn-CP was prepared by employing the coralloid sample of CP-2-ZX as the precursor. For comparisons, a series of activated carbon (AC-n) was obtained by the similar heating process on the mixture of bibp with ZnCl2 at different mass ratios. The results illustrate that the atomically dispersed ZnCl2 dot in the 1D chain of CP-2-ZX has an in situ activation effect on the generation of AC-Zn-CP, which can greatly promote the porosity and achieve high-efficiency utilization of ZnCl2. Therefore, the atomically dispersed activating agent provides a new method for environmentally friendly production of porous carbon materials. Significantly, the AC-Zn-CP electrode displays specific capacitance of 215 F g-1 in 3 M KOH solution, which will be largely promoted to 1419 F g-1 in the redox active electrolyte of K3[Fe(CN)6]/KOH. AC-Zn-CP also shows remarkable cycling stability (the capacity retention is 89.0% after 5000 cycles). Moreover, the fabricated symmetric supercapacitor owns a high energy density of 34.8 Wh kg-1 at 785.5 W kg-1. So, the AC-Zn-CP∩K3[Fe(CN)6] system has wide application prospects in supercapacitors.

Reliability map of individual differences reflected in inter-subject correlation in naturalistic imaging.

Understanding individual differences in brain function is an essential aim of neuroscience. Naturalistic imaging links neural activity to real-life contexts and reflects individual differences in brain response. These unique features make it a promising tool for individualized psychiatry. An essential prerequisite for the extensive use of this paradigm is the reliable representation of inter-individual relationships. We used a test-retest approach to examine whether the naturalistic paradigm reliably represents inter-individual differences, which brain regions have the superior capability, and whether the ability alters with the contents of the stimuli. We quantified the reliability of the inter-subject relationships in repeated scans of two movie clips: a natural sight view and an emotion-evoking story. Besides statistical inference, we included resting-state scans, behavioral tests, and questionnaires as references for the comparison. The results showed that over one-third area of the brain could reliably characterize the inter-individual relationship, and the superior temporal lobe demonstrated comparable reliability representation with the State and Trait Anxiety Inventory. Furthermore, the temporal lobe regions could retain this capability across emotional movies with different contents. This study provides a base for pushing the naturalistic imaging paradigm towards clinical applications and proposes reliable target brain regions for future studies.

Sample sizes and population differences in brain template construction.

Spatial normalization or deformation to a standard brain template is routinely used as a key module in various pipelines for the processing of magnetic resonance imaging (MRI) data. Brain templates are often constructed using MRI data from a limited number of subjects. Individual brains show significant variabilities in their morphology; thus, sample sizes and population differences are two key factors that influence brain template construction. To address these influences, we employed two independent groups from the Human Connectome Project (HCP) and the Chinese Human Connectome Project (CHCP) to quantify the impacts of sample sizes and population on brain template construction. We first assessed the effect of sample size on the construction of volumetric brain templates using data subsets from the HCP and CHCP datasets. We applied a voxel-wise index of the deformation variability and a logarithmically transformed Jacobian determinant to quantify the variability associated with the template construction and modeled the brain template variability as a power function of the sample size. At the system level, the frontoparietal control network and dorsal attention network demonstrated higher deformation variability and logged Jacobian determinants, whereas other primary networks showed lower variability. To investigate the population differences, we constructed Caucasian and Chinese standard brain atlases (namely, US200 and CN200). The two demographically matched templates, particularly the language-related areas, exhibited dramatic bilaterally in supramarginal gyri and inferior frontal gyri differences in their deformation variability and logged Jacobian determinant. Using independent data from the HCP and CHCP, we examined the segmentation and registration accuracy and observed significant reduction in the performance of the brain segmentation and registration when the population-mismatched templates were used in the spatial normalization. Our findings provide evidence to support the use of population-matched templates in human brain mapping studies. The US200 and CN200 templates have been released on the Neuroimage Informatics Tools and Resources Clearinghouse (NITRC) website (https://www.nitrc.org/projects/us200_cn200/).

Rational design of [e]-fusion induced high-performance DHP/CPD based photoswitches.

We report an effective strategy for improving the electronic transport and switching behaviors of dimethyldihydropyrene/cyclophanediene (DHP/CPD)-based molecular devices, an intriguing photoswitch that can be triggered by ultraviolet/visible (UV-vis) light irradiation. Aiming to obtain molecular devices with high on-off ratios, we assess a series of molecular designs formed by [e]-fusing different arenes on a conjugated macrocycle to modulate the photochemical and electronic properties. Here, the switching mechanism and transport properties of [e]-fused DHP/CPD-based nanojunctions are theoretically investigated by first-principles calculations. As a result, the large diversity in electrical conductance between the closed and open forms certifies the substantial switching behavior observed in these sandwich structures. The maximum on-off ratios in all designed photoswitches are greater than 102. Further analysis confirms the improvement of switching performance caused by [e]-fusion. Notably, in the benzo-fused molecular junctions, the maximum on-off ratio is up to 103, which is 55 times larger than that of the un-fused one. We also find that the position of the switch core can remarkably affect the performance of photoswichable nanodevices.

Spatial Topography of Individual-Specific Cortical Networks Predicts Human Cognition, Personality, and Emotion.

Resting-state functional magnetic resonance imaging (rs-fMRI) offers the opportunity to delineate individual-specific brain networks. A major question is whether individual-specific network topography (i.e., location and spatial arrangement) is behaviorally relevant. Here, we propose a multi-session hierarchical Bayesian model (MS-HBM) for estimating individual-specific cortical networks and investigate whether individual-specific network topography can predict human behavior. The multiple layers of the MS-HBM explicitly differentiate intra-subject (within-subject) from inter-subject (between-subject) network variability. By ignoring intra-subject variability, previous network mappings might confuse intra-subject variability for inter-subject differences. Compared with other approaches, MS-HBM parcellations generalized better to new rs-fMRI and task-fMRI data from the same subjects. More specifically, MS-HBM parcellations estimated from a single rs-fMRI session (10 min) showed comparable generalizability as parcellations estimated by 2 state-of-the-art methods using 5 sessions (50 min). We also showed that behavioral phenotypes across cognition, personality, and emotion could be predicted by individual-specific network topography with modest accuracy, comparable to previous reports predicting phenotypes based on connectivity strength. Network topography estimated by MS-HBM was more effective for behavioral prediction than network size, as well as network topography estimated by other parcellation approaches. Thus, similar to connectivity strength, individual-specific network topography might also serve as a fingerprint of human behavior.

Spontaneous low-frequency fluctuations in the neural system for emotional perception in major psychiatric disorders: amplitude similarities and differences across frequency bands

Background: Growing evidence indicates both shared and distinct features of emotional perception in schizophrenia, bipolar disorder and major depressive disorder. In these disorders, alterations in spontaneous low-frequency fluctuations have been reported in the neural system for emotional perception, but the similarities and differences in the amplitude of low-frequency fluctuation (ALFF) across the 3 disorders are unknown. Methods: We compared ALFF and its signal balance in the neural system for emotional perception at 2 frequency bands (slow-5 and slow-4) in 119 participants with schizophrenia, 100 with bipolar disorder, 123 with major depressive disorder and 183 healthy controls. We performed exploratory Pearson partial correlation analyses to determine the relationship between ALFF signal balance and clinical variables. Results: We observed commonalities in ALFF change patterns across the 3 disorders for emotional perception neural substrates, such as increased ALFF in the anterior cerebrum (including subcortical, limbic, paralimbic and heteromodal cortical regions) and decreased ALFF in the posterior visual cortices. Schizophrenia, bipolar disorder and major depressive disorder showed significantly decreased ALFF signal balance in the neural system for emotional perception at both slow-5 and slow-4 frequency bands, with the greatest alterations for schizophrenia, followed by bipolar disorder and major depressive disorder. We found a negative correlation between ALFF signal balance and negative/disorganized symptoms in slow-4 across the 3 disorders. Limitations: The relatively broad age range in our sample and the cross-sectional study design may not account for our findings. Conclusion: The extent of the commonalities we observed further support the concept of core neurobiological disruptions shared among the 3 disorders; ALFF signal balance could be an important neuroimaging marker for the diagnosis and treatment of schizophrenia, bipolar disorder and major depressive disorder.

Maternal betaine status, but not that of choline or methionine, is inversely associated with infant birth weight.

Maternal one-carbon metabolism during pregnancy is crucial for fetal development and programming by DNA methylation. However, evidence on one-carbon biomarkers other than folate is lacking. We, therefore, investigated whether maternal plasma methyl donors, that is, choline, betaine and methionine, are associated with birth outcomes. Blood samples were obtained from 115 women during gestation (median 26·3 weeks, 90 % range 22·7-33·0 weeks). Plasma choline, betaine, methionine and dimethylglycine were measured using HPLC-tandem MS. Multivariate linear and logistic regression models were used to estimate the association between plasma biomarkers and birth weight, birth length, the risk of small-for-gestational-age and large-for-gestational-age (LGA). Higher level of maternal betaine was associated with lower birth weight (-130·3 (95 % CI -244·8, -15·9) per 1 sd increment for log-transformed betaine). Higher maternal methionine was associated with lower risk of LGA, and adjusted OR, with 95 % CI for 1 sd increase in methionine concentration was 0·44 (95 % CI 0·21, 0·89). Stratified analyses according to infant sex or maternal plasma homocysteine status showed that reduction in birth weight in relation to maternal betaine was only limited to male infants or to who had higher maternal homocysteine status (≥5·1 µmol/l). Higher maternal betaine status was associated with reduced birth weight. Maternal methionine was inversely associated with LGA risk. These findings are needed to be replicated in future larger studies.