Over the last 10 to 15 years, active inference has helped to explain various brain mechanisms from habit formation to dopaminergic discharge and even modelling curiosity. However, the current implementations suffer from an exponential (space and time) complexity class when computing the prior over all the possible policies up to the time-horizon. Fountas et al. (2020) used Monte Carlo tree search to address this problem, leading to impressive results in two different tasks. In this paper, we present an alternative framework that aims to unify tree search and active inference by casting planning as a structure learning problem. Two tree search algorithms are then presented. The first propagates the expected free energy forward in time (i.e., towards the leaves), while the second propagates it backward (i.e., towards the root). Then, we demonstrate that forward and backward propagations are related to active inference and sophisticated inference, respectively, thereby clarifying the differences between those two planning strategies. <<<

Most proteins in cells are composed of multiple folding units (or domains) to perform complex functions in a cooperative manner. Relative to the rapid progress in single-domain structure prediction, there are few effective tools available for multi-domain protein structure assembly, mainly due to the complexity of modeling multi-domain proteins, which involves higher degrees of freedom in domain-orientation space and various levels of continuous and discontinuous domain assembly and linker refinement. To meet the challenge and the high demand of the community, we developed I-TASSER-MTD to model the structures and functions of multi-domain proteins through a progressive protocol that combines sequence-based domain parsing, single-domain structure folding, inter-domain structure assembly and structure-based function annotation in a fully automated pipeline. Advanced deep-learning models have been incorporated into each of the steps to enhance both the domain modeling and inter-domain assembly accuracy. The protocol allows for the incorporation of experimental cross-linking data and cryo-electron microscopy density maps to guide the multi-domain structure assembly simulations. I-TASSER-MTD is built on I-TASSER but substantially extends its ability and accuracy in modeling large multi-domain protein structures and provides meaningful functional insights for the targets at both the domain- and full-chain levels from the amino acid sequence alone. <<<

While many multi-robot coordination problems can be solved optimally by exact algorithms, solutions are often not scalable in the number of robots. Multi-Agent Reinforcement Learning (MARL) is gaining increasing attention in the robotics community as a promising solution to tackle such problems. Nevertheless, we still lack the tools that allow us to quickly and efficiently find solutions to large-scale collective learning tasks. In this work, we introduce the Vectorized Multi-Agent Simulator (VMAS). VMAS is an open-source framework designed for efficient MARL benchmarking. It is comprised of a vectorized 2D physics engine written in PyTorch and a set of twelve challenging multi-robot scenarios. Additional scenarios can be implemented through a simple and modular interface. We demonstrate how vectorization enables parallel simulation on accelerated hardware without added complexity. When comparing VMAS to OpenAI MPE, we show how MPE's execution time increases linearly in the number of simulations while VMAS is able to execute 30,000 parallel simulations in under 10s, proving more than 100x faster. Using VMAS's RLlib interface, we benchmark our multi-robot scenarios using various Proximal Policy Optimization (PPO)-based MARL algorithms. VMAS's scenarios prove challenging in orthogonal ways for state-of-the-art MARL algorithms. The VMAS framework is available at this https URL. A video of VMAS scenarios and experiments is available at this https URL}{here}\footnote{\url{this https URL. <<<

We address the problem of detecting human–object interactions in images using graphical neural networks. Unlike conventional methods, where nodes send scaled but otherwise identical messages to each of their neighbours, we propose to condition messages between pairs of nodes on their spatial relationships, resulting in different messages going to neighbours of the same node. To this end, we explore various ways of applying spatial conditioning under a multi-branch structure. Through extensive experimentation we demonstrate the advantages of spatial conditioning for the computation of the adjacency structure, messages and the refined graph features. In particular, we empirically show that as the quality of the bounding boxes increases, their coarse appearance features contribute relatively less to the disambiguation of interactions compared to the spatial information. Our method achieves an mAP of 31.33% on HICO-DET and 54.2% on V-COCO, significantly outperforming state-of-the-art on fine-tuned detections. <<<

The human immune system is composed of a distributed network of cells circulating throughout the body, which must dynamically form physical associations and communicate using interactions between their cell-surface proteomes. Despite their therapeutic potential, our map of these surface interactions remains incomplete. Here, using a high-throughput surface receptor screening method, we systematically mapped the direct protein interactions across a recombinant library that encompasses most of the surface proteins that are detectable on human leukocytes. We independently validated and determined the biophysical parameters of each novel interaction, resulting in a high-confidence and quantitative view of the receptor wiring that connects human immune cells. By integrating our interactome with expression data, we identified trends in the dynamics of immune interactions and constructed a reductionist mathematical model that predicts cellular connectivity from basic principles. We also developed an interactive multi-tissue single-cell atlas that infers immune interactions throughout the body, revealing potential functional contexts for new interactions and hubs in multicellular networks. Finally, we combined targeted protein stimulation of human leukocytes with multiplex high-content microscopy to link our receptor interactions to functional roles, in terms of both modulating immune responses and maintaining normal patterns of intercellular associations. Together, our work provides a systematic perspective on the intercellular wiring of the human immune system that extends from systems-level principles of immune cell connectivity down to mechanistic characterization of individual receptors, which could offer opportunities for therapeutic intervention. <<<

Ryan L Collins, Joseph T Glessner, Eleonora Porcu, Maarja Lepamets, Rhonda Brandon, Christopher Lauricella, Lide Han, Theodore Morley, Lisa-Marie Niestroj, Jacob Ulirsch, Selin Everett, Daniel P Howrigan, Philip M Boone, Jack Fu, Konrad J Karczewski, Georgios Kellaris, Chelsea Lowther, Diane Lucente, Kiana Mohajeri, Margit Nõukas, Xander Nuttle, Kaitlin E Samocha, Mi Trinh, Farid Ullah, Urmo Võsa, Epi25 Consortium, Estonian Biobank Research Team, Matthew E Hurles, Swaroop Aradhya, Erica E Davis, Hilary Finucane, James F Gusella, Aura Janze, Nicholas Katsanis, Ludmila Matyakhina, Benjamin M Neale, David Sanders, Stephanie Warren, Jennelle C Hodge, Dennis Lal, Douglas M Ruderfer, Jeanne Meck, Reedik Mägi, Tõnu Esko, Alexandre Reymond, Zoltán Kutalik, Hakon Hakonarson, Shamil Sunyaev, Harrison Brand, Michael E Talkowski <<<

Rare copy-number variants (rCNVs) include deletions and duplications that occur infrequently in the global human population and can confer substantial risk for disease. In this study, we aimed to quantify the properties of haploinsufficiency (i.e., deletion intolerance) and triplosensitivity (i.e., duplication intolerance) throughout the human genome. We harmonized and meta-analyzed rCNVs from nearly one million individuals to construct a genome-wide catalog of dosage sensitivity across 54 disorders, which defined 163 dosage sensitive segments associated with at least one disorder. These segments were typically gene dense and often harbored dominant dosage sensitive driver genes, which we were able to prioritize using statistical fine-mapping. Finally, we designed an ensemble machine-learning model to predict probabilities of dosage sensitivity (pHaplo & pTriplo) for all autosomal genes, which identified 2,987 haploinsufficient and 1,559 triplosensitive genes, including 648 that were uniquely triplosensitive. This dosage sensitivity resource will provide broad utility for human disease research and clinical genetics. <<<

Paul Petrus, Marlene Cervantes, Muntaha Samad, Tomoki Sato, Alina Chao, Shogo Sato, Kevin B Koronowski, Grace Park, Yasmine Alam, Niklas Mejhert, Marcus M Seldin, José Manuel Monroy Kuhn, Kenneth A Dyar, Dominik Lutter, Pierre Baldi, Peter Kaiser, Cholsoon Jang, Paolo Sassone-Corsi <<<

OBJECTIVE: The circadian clock aligns physiology with the 24-hour rotation of Earth. Light and food are the main environmental cues (zeitgebers) regulating circadian rhythms in mammals. Yet, little is known about the interaction between specific dietary components and light in coordinating circadian homeostasis. Herein, we focused on the role of essential amino acids.METHODS: Mice were fed diets depleted of specific essential amino acids and their behavioral rhythms were monitored and tryptophan was selected for downstream analyses. The role of tryptophan metabolism in modulating circadian homeostasis was studied using isotope tracing as well as transcriptomic- and metabolomic- analyses.RESULTS: Dietary tryptophan depletion alters behavioral rhythms in mice. Furthermore, tryptophan metabolism was shown to be regulated in a time- and light- dependent manner. A multi-omics approach and combinatory diet/light interventions demonstrated that tryptophan metabolism modulates temporal regulation of metabolism and transcription programs by buffering photic cues. Specifically, tryptophan metabolites regulate central circadian functions of the suprachiasmatic nucleus and the core clock machinery in the liver.CONCLUSIONS: Tryptophan metabolism is a modulator of circadian homeostasis by integrating environmental cues. Our findings propose tryptophan metabolism as a potential point for pharmacologic intervention to modulate phenotypes associated with disrupted circadian rhythms. <<<

BackgroundThe eukaryotic genome is capable of producing multiple isoforms from a gene by alternative polyadenylation (APA) during pre-mRNA processing. APA in the 3’-untranslated region (3’-UTR) of mRNA produces transcripts with shorter or longer 3’-UTR. Often, 3’-UTR serves as a binding platform for microRNAs and RNA-binding proteins, which affect the fate of the mRNA transcript. Thus, 3’-UTR APA is known to modulate translation and provides a mean to regulate gene expression at the post-transcriptional level. Current bioinformatics pipelines have limited capability in profiling 3’-UTR APA events due to incomplete annotations and a low-resolution analyzing power: widely available bioinformatics pipelines do not reference actionable polyadenylation (cleavage) sites but simulate 3’-UTR APA only using RNA-seq read coverage, causing false positive identifications. To overcome these limitations, we developed APA-Scan, a robust program that identifies 3’-UTR APA events and visualizes the RNA-seq short-read coverage with gene annotations.MethodsAPA-Scan utilizes either predicted or experimentally validated actionable polyadenylation signals as a reference for polyadenylation sites and calculates the quantity of long and short 3’-UTR transcripts in the RNA-seq data. APA-Scan works in three major steps: (i) calculate the read coverage of the 3’-UTR regions of genes; (ii) identify the potential APA sites and evaluate the significance of the events among two biological conditions; (iii) graphical representation of user specific event with 3’-UTR annotation and read coverage on the 3’-UTR regions. APA-Scan is implemented in Python3. Source code and a comprehensive user’s manual are freely available at https://github.com/compbiolabucf/APA-Scan.ResultAPA-Scan was applied to both simulated and real RNA-seq datasets and compared with two widely used baselines DaPars and APAtrap. In simulation APA-Scan significantly improved the accuracy of 3’-UTR APA identification compared to the other baselines. The performance of APA-Scan was also validated by 3’-end-seq data and qPCR on mouse embryonic fibroblast cells. The experiments confirm that APA-Scan can detect unannotated 3’ -UTR APA events and improve genome annotation.ConclusionAPA-Scan is a comprehensive computational pipeline to detect transcriptome-wide 3’-UTR APA events. The pipeline integrates both RNA-seq and 3’-end-seq data information and can efficiently identify the significant events with a high-resolution short reads coverage plots. <<<

The presence of senescent cells is associated with renal fibrosis. This study aims to investigate the effect of albumin-induced premature senescence on tubulointerstitial fibrosis and its possible mechanism . Different concentrations of bovine serum albumim (BSA) with or without si-p21 are used to stimulate HK-2 cells for 72 h, and SA-β-gal activity, senescence-associated secretory phenotypes (SASPs), LaminB1 are used as markers of senescence. Immunofluorescence staining is performed to characterize the G2/M phase arrest between the control and BSA groups. Alterations in the DNA damage marker γ-H2AX, fibrogenesis, and associated proteins at the G2/M phase, such as p21, p-CDC25C and p-CDK1, are evaluated. Compared with those in the control group, the SA-β-gal activity, SASP, and γ-H2AX levels are increased in the BSA group, while the level of LaminB1 is decreased. Meanwhile, HK-2 cells blocked at the G2/M phase are significantly increased under the stimulation of BSA, and the levels of p21, p-CDC25C and p-CDK1, as well as fibrogenesis are also increased. When p21 expression is inhibited, the levels of p-CDC25C and p-CDK1 are decreased and the G2/M phase arrest is improved, which decreases the production of fibrogenesis. In conclusion, BSA induces renal tubular epithelial cell premature senescence, which regulates the G2/M phase through the CDC25C/CDK1 pathway, leading to tubulointerstitial fibrosis. <<<

This article compares time invested in children across family structures as a means to understand differences in children’s development. Using data from the 1997 Panel Study of Income Dynamics’ Child Development Supplement, we measure time investments from multiple caregivers and distinguish time children spend with a caregiver alone versus shared with another caregiver. We examine six family structures—married biological parents, cohabiting biological parents, mother and stepfather, mother and cohabiting boyfriend, single mother only, and multigenerational households. The total care-giving time that children receive in married biological parent families and cohabiting biological parent families is comparable to that for children living in stepfather families and multigenerational families. This is because children in stepfather families and multigenerational households receive substantial time investments from nonresident biological fathers and grandparents, respectively. In contrast, children receive little time investment from resident nonbiological father figures; and children in single mother, cohabiting boyfriend, and multigenerational households receive little time investment from their nonresident biological fathers. Finally, children who live with married biological parents receive the greatest share of caregiving time in the form of shared caregiving compared with children in all other family structures. Our findings suggest that having two resident biological caregivers predicts greater time investments in children and that shared parenting may be an important dimension of family structure. <<<

SUMMARY: Bioinformatics applications increasingly rely on ad hoc disk storage of k-mer sets, e.g. for de Bruijn graphs or alignment indexes. Here, we introduce the K-mer File Format as a general lossless framework for storing and manipulating k-mer sets, realizing space savings of 3-5× compared to other formats, and bringing interoperability across tools.AVAILABILITY AND IMPLEMENTATION: Format specification, C++/Rust API, tools: https://github.com/Kmer-File-Format/.SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. <<<

Zhaowen Liu, Lena Palaniyappan, Xinran Wu, Kai Zhang, Jiangnan Du, Qi Zhao, Chao Xie, Yingying Tang, Wenjun Su, Yarui Wei, Kangkang Xue, Shaoqiang Han, Shih-Jen Tsai, Ching-Po Lin, Jingliang Cheng, Chunbo Li, Jijun Wang, Barbara J Sahakian, Trevor W Robbins, Jie Zhang, Jianfeng Feng <<<

Reliable mapping of system-level individual differences is a critical first step toward precision medicine for complex disorders such as schizophrenia. Disrupted structural covariance indicates a system-level brain maturational disruption in schizophrenia. However, most studies examine structural covariance at the group level. This prevents subject-level inferences. Here, we introduce a Network Template Perturbation approach to construct individual differential structural covariance network (IDSCN) using regional gray-matter volume. IDSCN quantifies how structural covariance between two nodes in a patient deviates from the normative covariance in healthy subjects. We analyzed T1 images from 1287 subjects, including 107 first-episode (drug-naive) patients and 71 controls in the discovery datasets and established robustness in 213 first-episode (drug-naive), 294 chronic, 99 clinical high-risk patients, and 494 controls from the replication datasets. Patients with schizophrenia were highly variable in their altered structural covariance edges; the number of altered edges was related to severity of hallucinations. Despite this variability, a subset of covariance edges, including the left hippocampus-bilateral putamen/globus pallidus edges, clustered patients into two distinct subgroups with opposing changes in covariance compared to controls, and significant differences in their anxiety and depression scores. These subgroup differences were stable across all seven datasets with meaningful genetic associations and functional annotation for the affected edges. We conclude that the underlying physiology of affective symptoms in schizophrenia involves the hippocampus and putamen/pallidum, predates disease onset, and is sufficiently consistent to resolve morphological heterogeneity throughout the illness course. The two schizophrenia subgroups identified thus have implications for the nosology and clinical treatment. <<<

Concentrate withdrawal and feed restriction are commonly used to reduce milk production and to facilitate dry-off, but may impair immune function in dairy cows. We investigated the effect of feed rations providing different amounts of nutrients in combination with feed restriction on performance, endocrine, and metabolic responses, as well as on leukocyte function before and after abrupt dry-off. Forty-three cows were studied from d 12 before until d 6 after dry-off (56 d before scheduled calving). Cows were fed experimental concentrates rich in crude protein (nitrogenic, n = 14), glucogenic precursors (glucogenic, n = 14), or lipids (lipogenic, n = 15). On d 3 before dry-off, total feed allowance was restricted to 50% in half of the animals of each dietary group, whereas feed allowance remained unchanged in the other animals. Performance parameters (milk yield, milk composition, and dry matter intake) were recorded, and daily blood and milk samples were taken and analyzed for various metabolic and endocrine parameters. Additionally, activity and mRNA abundance of several genes in leukocytes were measured at selected time points before and after feed restriction and dry-off, respectively. Feed restriction immediately resulted in a negative energy balance and decreased milk production. Concomitantly, concentrations of nonesterified fatty acids increased, whereas insulin, insulin-like growth factor-1, and glucagon decreased. After dry-off, energy balance turned positive and plasma nonesterified fatty acids decreased. Plasma glucose, insulin, and insulin-like growth factor-1 concentrations increased in all groups after dry-off. Glucose, insulin, and glucagon concentrations in plasma were higher in nonrestricted compared with restricted animals after dry-off. The experimental concentrate types marginally affected the investigated metabolic and endocrine factors, with the exception of elevated milk and plasma urea concentrations in cows fed the nitrogenic concentrate. Chemotactic and phagocytic activity of leukocytes were not affected by diets, feed restriction, or dry-off. Likewise, blood leukocyte mRNA abundance encoding for tumor necrosis factor α (TNF), heat shock protein family A (HSP70), and the glucose transporters (GLUT) 1 and 3 remained unchanged throughout the study period. Overall, the short-term negative energy balance induced by feed restriction was temporarily accompanied by metabolic adaptations, but did not alter the studied factors related to the immune system. Metabolic and endocrine adaptations supporting milk synthesis were continued during the first days after dry-off despite cessation of milking. Thus, the abrupt dry-off resulted in a short-term increase of glucose and triglyceride concentrations, with a delayed endocrine response to re-establish nutrient homeostasis in blood. <<<

AbstractThe nature of the representational code underlying conceptual knowledge remains a major unsolved problem in cognitive neuroscience. We assessed the extent to which different representational systems contribute to the instantiation of lexical concepts in high-level, heteromodal cortical areas previously associated with semantic cognition. We found that lexical semantic information can be reliably decoded from a wide range of heteromodal cortical areas in frontal, parietal, and temporal cortex. In most of these areas, we found a striking advantage for experience-based representational structures (i.e., encoding information about sensory-motor, affective, and other features of phenomenal experience), with little evidence for independent taxonomic or distributional organization. These results were found independently for object and event concepts. Our findings indicate that concept representations in heteromodal cortex are based, at least in part, on experiential information. They also reveal that, in most heteromodal areas, event concepts have more heterogeneous representations (i.e., they are more easily decodable) than object concepts, and that other areas beyond the traditional “semantic hubs” contribute to semantic cognition, particularly the posterior cingulate gyrus and the precuneus. <<<

Céline M Laumont, Krystel Vincent, Leslie Hesnard, Éric Audemard, Éric Bonneil, Jean-Philippe Laverdure, Patrick Gendron, Mathieu Courcelles, Marie-Pierre Hardy, Caroline Côté, Chantal Durette, Charles St-Pierre, Mohamed Benhammadi, Joël Lanoix, Suzanne Vobecky, Elie Haddad, Sébastien Lemieux, Pierre Thibault, Claude Perreault <<<

Tumor-specific antigens (TSAs) represent ideal targets for cancer immunotherapy, but few have been identified thus far. We therefore developed a proteogenomic approach to enable the high-throughput discovery of TSAs coded by potentially all genomic regions. In two murine cancer cell lines and seven human primary tumors, we identified a total of 40 TSAs, about 90% of which derived from allegedly noncoding regions and would have been missed by standard exome-based approaches. Moreover, most of these TSAs derived from nonmutated yet aberrantly expressed transcripts (such as endogenous retroelements) that could be shared by multiple tumor types. Last, we demonstrated that, in mice, the strength of antitumor responses after TSA vaccination was influenced by two parameters that can be estimated in humans and could serve for TSA prioritization in clinical studies: TSA expression and the frequency of TSA-responsive T cells in the preimmune repertoire. In conclusion, the strategy reported herein could considerably facilitate the identification and prioritization of actionable human TSAs. <<<

BACKGROUND: Accumulating evidence has shown that disorders in the gut microbiota and derived metabolites affect the development of atherosclerotic cardiovascular disease (ASCVD). However, which and how specific gut microbial metabolites contribute to the progression of atherosclerosis and the clinical relevance of their alterations remain unclear.METHODS: We performed integrated microbiome-metabolome analysis of 30 patients with coronary artery disease (CAD) and 30 age- and sex-matched healthy controls to identify CAD-associated microbial metabolites, which were then assessed in an independent population of patients with ASCVD and controls (n=256). We further investigate the effect of CAD-associated microbial metabolites on atherosclerosis and the mechanisms of the action.RESULTS: Indole-3-propionic acid (IPA), a solely microbially derived tryptophan metabolite, was the most downregulated metabolite in patients with CAD. Circulating IPA was then shown in an independent population to be associated with risk of prevalent ASCVD and correlated with the ASCVD severity. Dietary IPA supplementation alleviates atherosclerotic plaque development in ApoE-/- mice. In murine- and human-derived macrophages, administration of IPA promoted cholesterol efflux from macrophages to ApoA-I through an undescribed miR-142-5p/ABCA1 (ATP-binding cassette transporter A1) signaling pathway. Further in vivo studies demonstrated that IPA facilitates macrophage reverse cholesterol transport, correlating with the regulation of miR-142-5p/ABCA1 pathway, whereas reduced IPA production contributed to the aberrant overexpression of miR-142-5p in macrophages and accelerated the progression of atherosclerosis. Moreover, the miR-142-5p/ABCA1/reverse cholesterol transport axis in macrophages were dysregulated in patients with CAD, and correlated with the changes in circulating IPA levels.CONCLUSIONS: Our study identify a previously unknown link between specific gut microbiota-derived tryptophan metabolite and ASCVD. The microbial metabolite IPA/miR-142-5p/ABCA1 pathway may represent a promising therapeutic target for ASCVD. <<<

Mahan Nekoui , James P. Pirruccello , Paolo Di Achille , Seung Hoan Choi , Samuel N. Friedman , Victor Nauffal , Kenney Ng , Puneet Batra , Jennifer E. Ho , Anthony A. Philippakis , Steven A. Lubitz , Mark E. Lindsay , Patrick T. Ellinor <<<

Background The left ventricular outflow tract (LVOT) and ascending aorta are spatially complex, with distinct pathologies and embryologic origins. Prior work examined the genetics of thoracic aortic diameter in a single plane. Objectives We sought to elucidate the genetic basis for the diameter of the LVOT, aortic root, and ascending aorta. Methods Using deep learning, we analyzed 2.3 million cardiac magnetic resonance images from 43,317 UK Biobank participants. We computed the diameters of the LVOT, the aortic root, and at 6 locations of ascending aorta. For each diameter, we conducted a genome-wide association study and generated a polygenic score. Finally, we investigated associations between these scores and disease incidence. Results A total of 79 loci were significantly associated with at least 1 diameter. Of these, 35 were novel, and most were associated with 1 or 2 diameters. A polygenic score of aortic diameter approximately 13 mm from the sinotubular junction most strongly predicted thoracic aortic aneurysm (n = 427,016; mean HR: 1.42 per SD; 95% CI: 1.34-1.50; P = 6.67 × 10−21). A polygenic score predicting a smaller aortic root was predictive of aortic stenosis (n = 426,502; mean HR: 1.08 per SD; 95% CI: 1.03-1.12; P = 5 × 10−6). Conclusions We detected distinct genetic loci underpinning the diameters of the LVOT, aortic root, and at several segments of ascending aorta. We spatially defined a region of aorta whose genetics may be most relevant to predicting thoracic aortic aneurysm. We further described a genetic signature that may predispose to aortic stenosis. Understanding genetic contributions to proximal aortic diameter may enable identification of individuals at risk for aortic disease and facilitate prioritization of therapeutic targets. <<<

BACKGROUND: Although the American Academy of Sleep Medicine suggests at least 9 h of sleep per day for 6-12-year-olds, children in recent generations often report sleeping less than this amount. Because early adolescence is a crucial period for neurocognitive development, we aimed to investigate how insufficient sleep affects children's mental health, cognition, brain function, and brain structure over 2 years.METHODS: In this propensity score matched, longitudinal, observational cohort study, we obtained data from a population-based sample of 9-10-year-olds from 21 US study sites in the ongoing Adolescent Brain Cognitive Development (ABCD) study. Participants were categorised as having sufficient sleep or insufficient sleep on the basis of a cutoff of 9 h sleep per day. Using propensity score matching, we matched these two groups of participants on 11 key covariates, including sex, socioeconomic status, and puberty status. Participants were excluded from our analysis if they did not pass a baseline resting-state functional MRI quality check or had missing data for the covariates involved in propensity score matching. Outcome measures retrieved from the ABCD study were behavioural problems, mental health, cognition, and structural and resting-state functional brain measures, assessed at baseline and at 2-year follow-up. We examined group differences on these outcomes over those 2 years among all eligible participants. We then did mediation analyses of the neural correlates of behavioural changes induced by insufficient sleep.FINDINGS: Between Sept 1, 2016, and Oct 15, 2018, 11 878 individuals had baseline data collected for the ABCD study, of whom 8323 were eligible and included in this study (4142 participants in the sufficient sleep group and 4181 in the insufficient sleep group). Follow-up data were collected from July 30, 2018, to Jan 15, 2020. We identified 3021 matched sufficient sleep-insufficient sleep pairs at baseline and 749 matched pairs at 2-year follow-up, and observed similar differences between the groups in behaviour and neural measures at both timepoints; the effect sizes of between-group differences in behavioural measures at these two timepoints were significantly correlated with each other (r=0·85, 95% CI 0·73-0·92; p<0·0001). A similar pattern was observed in resting-state functional connectivity (r=0·54, 0·45-0·61; p<0·0001) and in structural measures (eg, in grey matter volume r=0·61, 0·51-0·69; p<0·0001). We found that cortico-basal ganglia functional connections mediate the effects of insufficient sleep on depression, thought problems, and crystallised intelligence, and that structural properties of the anterior temporal lobe mediate the effect of insufficient sleep on crystallised intelligence.INTERPRETATION: These results provide population-level evidence for the long-lasting effect of insufficient sleep on neurocognitive development in early adolescence. These findings highlight the value of early sleep intervention to improve early adolescents' long-term developmental outcomes.FUNDING: National Institutes of Health. <<<

为更好地认识与理解生育政策调整可能带来的人口红利和人力资本红利及其经济影响,本文基于中国生育政策和经济社会发展实践,构建一个异质性居民代际交叠模型,深入考察生育政策（包括最大生育数量限定和超生罚款政策）对经济增长、收入分配和社会养老保障负担的影响及其机理。研究表明,生育政策对不同人力资本居民的生育和子女教育投资决策具有明显的异质性效应,且生育数量限定和超生罚款政策的影响不同。生育数量限定政策放松对经济增长具有"倒U"型影响,对居民收入基尼系数则具有"U"型效应,有利于减轻社会养老保障负担。超生罚款政策放松亦能减轻社会养老保障负担,但会抑制经济增长、加大收入差距。加大公共教育投入总体有助于生育政策放松取得较好效果;降低代际传导性有利于生育数量限定政策放松积极作用的发挥,超生罚款政策放松则具有相反影响。上述发现对于持续优化完善我国生育政策及配套支持措施具有良好启示。 <<<