The AlphaZero algorithm has been successfully applied in a range of discretedomains, most notably board games. It utilizes a neural network, that learns avalue and policy function to guide the exploration in a Monte-Carlo TreeSearch. Although many search improvements have been proposed for Monte-CarloTree Search in the past, most of them refer to an older variant of the UpperConfidence bounds for Trees algorithm that does not use a policy for planning.We introduce a new, improved search algorithm for AlphaZero which generalizesthe search tree to a directed acyclic graph. This enables information flowacross different subtrees and greatly reduces memory consumption. Along withMonte-Carlo Graph Search, we propose a number of further extensions, such asthe inclusion of Epsilon-greedy exploration, a revised terminal solver and theintegration of domain knowledge as constraints. In our evaluations, we use theCrazyAra engine on chess and crazyhouse as examples to show that these changesbring significant improvements to AlphaZero. <<<

Abstract We introduce unitary-gate randomized benchmarking (URB) for qudit gates by extending single- and multi-qubit URB to single- and multi-qudit gates. Specifically, we develop a qudit URB procedure that exploits unitary 2-designs. Furthermore, we show that our URB procedure is not simply extracted from the multi-qubit case by equating qudit URB to URB of the symmetric multi-qubit subspace. Our qudit URB is elucidated by using pseudocode, which facilitates incorporating into benchmarking applications. <<<

Andrew W. Senior, Richard Evans, John Jumper, James Kirkpatrick, Laurent Sifre, Tim Green, Chongli Qin, Augustin Žídek, Alexander W. R. Nelson, Alex Bridgland, Hugo Penedones, Stig Petersen, Karen Simonyan, Steve Crossan, Pushmeet Kohli, David T. Jones, David Silver, Koray Kavukcuoglu, Demis Hassabis <<<

The consolidation of discrete experiences into a coherent narrative shapes the cognitive map, providing structured mental representations of our experiences. In this process, past memories are reactivated and replayed in sequence, fostering hippocampal-cortical dialogue. However, brain-wide engagement coinciding with sequential reactivation (or replay) of memories remains largely unexplored. In this study, employing simultaneous EEG-fMRI, we capture both the spatial and temporal dynamics of memory replay. We find that during mental simulation, past memories are replayed in fast sequences as detected via EEG. These transient replay events are associated with heightened fMRI activity in the hippocampus and medial prefrontal cortex. Replay occurrence strengthens functional connectivity between the hippocampus and the default mode network, a set of brain regions key to representing the cognitive map. On the other hand, when subjects are at rest following learning, memory reactivation of task-related items is stronger than that of pre-learning rest, and is also associated with heightened hippocampal activation and augmented hippocampal connectivity to the entorhinal cortex. Together, our findings highlight a distributed, brain-wide engagement associated with transient memory reactivation and its sequential replay. <<<

AbstractWith the further transformation of The Large Sky Area Multi-Object Fiber Spectroscopic Telescope, the new generation of fiber positioner robot chooses a 4 mm hollow cup motor with minimum phase inductance. Because the load of the fiber positioner robot is constant and the inertia of the motor is very small, an open loop positioning control method based on Space Vector Pulse Width Modulation is proposed, and the specific open loop parameters are directly tuned by relevant experimental strategies. The critical factors of the open loop driving mode are discussed in detail from four aspects: subdivision, fundamental frequency, wave generation mode and peak current. Based on the actual fiber positioner robot, the hardware driver and assessment platform are built. The positioning tests show that the method proposed is practical and effective, and meets the precision positioning demand of the new generation optical fiber positioner robot. <<<

An essential prerequisite for evolution by natural selection is variation among individuals in traits that affect fitness. The ability of a system to produce selectable variation, known as evolvability, thus markedly affects the rate of evolution. Although the immune system is among the fastest-evolving components in mammals, the sources of variation in immune traits remain largely unknown. Here we show that an important determinant of the immune system's evolvability is its organization into interacting modules represented by different immune cell types. By profiling immune cell variation in bone marrow of 54 genetically diverse mouse strains from the Collaborative Cross, we found that variation in immune cell frequencies is polygenic and that many associated genes are involved in homeostatic balance through cell-intrinsic functions of proliferation, migration and cell death. However, we also found genes associated with the frequency of a particular cell type that are expressed in a different cell type, exerting their effect in what we term cyto-trans. The vertebrate evolutionary record shows that genes associated in cyto-trans have faced weaker negative selection, thus increasing the robustness and hence evolvability of the immune system. This phenomenon is similarly observable in human blood. Our findings suggest that interactions between different components of the immune system provide a phenotypic space in which mutations can produce variation with little detriment, underscoring the role of modularity in the evolution of complex systems. <<<

Michael S Haney, Róbert Pálovics, Christy Nicole Munson, Chris Long, Patrik K Johansson, Oscar Yip, Wentao Dong, Eshaan Rawat, Elizabeth West, Johannes C M Schlachetzki, Andy Tsai, Ian Hunter Guldner, Bhawika S Lamichhane, Amanda Smith, Nicholas Schaum, Kruti Calcuttawala, Andrew Shin, Yung-Hua Wang, Chengzhong Wang, Nicole Koutsodendris, Geidy E Serrano, Thomas G Beach, Eric M Reiman, Christopher K Glass, Monther Abu-Remaileh, Annika Enejder, Yadong Huang, Tony Wyss-Coray <<<

Several genetic risk factors for Alzheimer's disease implicate genes involved in lipid metabolism and many of these lipid genes are highly expressed in glial cells. However, the relationship between lipid metabolism in glia and Alzheimer's disease pathology remains poorly understood. Through single-nucleus RNA sequencing of brain tissue in Alzheimer's disease, we have identified a microglial state defined by the expression of the lipid droplet-associated enzyme ACSL1 with ACSL1-positive microglia being most abundant in patients with Alzheimer's disease having the APOE4/4 genotype. In human induced pluripotent stem cell-derived microglia, fibrillar Aβ induces ACSL1 expression, triglyceride synthesis and lipid droplet accumulation in an APOE-dependent manner. Additionally, conditioned media from lipid droplet-containing microglia lead to Tau phosphorylation and neurotoxicity in an APOE-dependent manner. Our findings suggest a link between genetic risk factors for Alzheimer's disease with microglial lipid droplet accumulation and neurotoxic microglia-derived factors, potentially providing therapeutic strategies for Alzheimer's disease. <<<

Wenkang Chen, Lu Chen, Xuan Zhang, Ning Yang, Jianghua Guo, Min Wang, Shenghui Ji, Xiangyu Zhao, Pengfei Yin, Lichun Cai, Jing Xu, Lili Zhang, Yingjia Han, Yingni Xiao, Gen Xu, Yuebin Wang, Shuhui Wang, Sheng Wu, Fang Yang, David Jackson, Jinkui Cheng, Saihua Chen, Chuanqing Sun, Feng Qin, Feng Tian, Alisdair R. Fernie, Jiansheng Li, Jianbing Yan, Xiaohong Yang <<<

A better understanding of the extent of convergent selection among crops could greatly improve breeding programs. We found that the quantitative trait locus KRN2 in maize and its rice ortholog, OsKRN2 , experienced convergent selection. These orthologs encode WD40 proteins and interact with a gene of unknown function, DUF1644, to negatively regulate grain number in both crops. Knockout of KRN2 in maize or OsKRN2 in rice increased grain yield by ~10% and ~8%, respectively, with no apparent trade-offs in other agronomic traits. Furthermore, genome-wide scans identified 490 pairs of orthologous genes that underwent convergent selection during maize and rice evolution, and these were enriched for two shared molecular pathways. KRN2 , together with other convergently selected genes, provides an excellent target for future crop improvement. <<<

AbstractHuman Leukocyte Antigens (HLA) are cell surface molecules, central in coordinating innate and adaptive immune responses, that are targets of strong diversifying natural selection by pathogens. Of these pathogens, human herpesviruses have a uniquely ancient relationship with our species, where coevolution likely has reciprocating impact on HLA and viral genomic diversity. Consistent with this notion, genetic variation at multiple HLA loci is strongly associated with modulating immunity to herpesvirus infection. Here, we synthesize published genetic associations of HLA with herpesvirus infection and disease, both from case/control and genome-wide association studies. We analyze genetic associations across the eight human herpesviruses and identify HLA alleles that are associated with diverse herpesvirus-related phenotypes. We find that whereas most HLA genetic associations are virus- or disease-specific, HLA-A*01 and HLA-A*02 allotypes may be more generally associated with immune susceptibility and control, respectively, across multiple herpesviruses. Connecting genetic association data with functional corroboration, we discuss mechanisms by which diverse HLA and cognate receptor allotypes direct variable immune responses during herpesvirus infection and pathogenesis. Together, this review examines the complexity of HLA-herpesvirus interactions driven by differential T cell and Natural Killer cell immune responses. <<<

AbstractDepression and anxiety are common and often comorbid mental health disorders that represent risk factors for aging-related conditions. Brain aging has shown to be more advanced in patients with major depressive disorder (MDD). Here, we extend prior work by investigating multivariate brain aging in patients with MDD, anxiety disorders, or both, and examine which factors contribute to older-appearing brains. Adults aged 18–57 years from the Netherlands Study of Depression and Anxiety underwent structural MRI. A pretrained brain-age prediction model based on >2000 samples from the ENIGMA consortium was applied to obtain brain-predicted age differences (brain PAD, predicted brain age minus chronological age) in 65 controls and 220 patients with current MDD and/or anxiety. Brain-PAD estimates were associated with clinical, somatic, lifestyle, and biological factors. After correcting for antidepressant use, brain PAD was significantly higher in MDD (+2.78 years, Cohen’sd = 0.25, 95% CI −0.10-0.60) and anxiety patients (+2.91 years, Cohen’sd = 0.27, 95% CI −0.08-0.61), compared with controls. There were no significant associations with lifestyle or biological stress systems. A multivariable model indicated unique contributions of higher severity of somatic depression symptoms (b = 4.21 years per unit increase on average sum score) and antidepressant use (−2.53 years) to brain PAD. Advanced brain aging in patients with MDD and anxiety was most strongly associated with somatic depressive symptomatology. We also present clinically relevant evidence for a potential neuroprotective antidepressant effect on the brain-PAD metric that requires follow-up in future research. <<<

The grand challenge in structure-based drug design is achieving accurate prediction of binding free energies. Molecular dynamics (MD) simulations enable modeling of conformational changes critical to the binding process, leading to calculation of thermodynamic quantities involved in estimation of binding affinities. With recent advancements in computing capability and predictive accuracy, MD based virtual screening has progressed from the domain of theoretical attempts to real application in drug development. Approaches including the Molecular Mechanics Poisson Boltzmann Surface Area (MM-PBSA), Linear Interaction Energy (LIE), and alchemical methods have been broadly applied to model molecular recognition for drug discovery and lead optimization. Here we review the varied methodology of these approaches, developments enhancing simulation efficiency and reliability, remaining challenges hindering predictive performance, and applications to problems in the fields of medicine and biochemistry. <<<

Junxiang Chen, Zhonghui Xu, Li Sun, Ke Yu, Craig P Hersh, Adel Boueiz, John E Hokanson, Frank C Sciurba, Edwin K Silverman, Peter J Castaldi, Kayhan Batmanghelich <<<

Rationale: Chronic obstructive pulmonary disease (COPD) is characterized by pathologic changes in the airways, lung parenchyma, and persistent inflammation, but the links between lung structural changes and blood transcriptome patterns have not been fully described.Objections: The objective of this study was to identify novel relationships between lung structural changes measured by chest computed tomography (CT) and blood transcriptome patterns measured by blood RNA sequencing (RNA-seq).Methods: CT scan images and blood RNA-seq gene expression from 1223 participants in the COPD Genetic Epidemiology (COPDGene®) study were jointly analyzed using deep learning to identify shared aspects of inflammation and lung structural changes that we labeled image-expression axes (IEAs). We related IEAs to COPD-related measurements and prospective health outcomes through regression and Cox proportional hazards models and tested them for biological pathway enrichment.Results: We identified 2 distinct IEAs: IEAemph which captures an emphysema-predominant process with a strong positive correlation to CT emphysema and a negative correlation to forced expiratory volume in 1 second and body mass index (BMI); and IEAairway which captures an airway-predominant process with a positive correlation to BMI and airway wall thickness and a negative correlation to emphysema. Pathway enrichment analysis identified 29 and 13 pathways significantly associated with IEAemph and IEAairway, respectively (adjusted p<0.001).Conclusions: Integration of CT scans and blood RNA-seq data identified 2 IEAs that capture distinct inflammatory processes associated with emphysema and airway-predominant COPD. <<<

The chelicerate body plan is distinguished from other arthropod groups by its division of segments into 2 tagmata: the anterior prosoma (“cephalothorax”) and the posterior opisthosoma (“abdomen”). Little is understood about the genetic mechanisms that establish the prosomal-opisthosomal (PO) boundary. To discover these mechanisms, we created high-quality genomic resources for the large-bodied spider Aphonopelma hentzi. We sequenced specific territories along the antero-posterior axis of developing embryos and applied differential gene expression analyses to identify putative regulators of regional identity. After bioinformatic screening for candidate genes that were consistently highly expressed in only 1 tagma (either the prosoma or the opisthosoma), we validated the function of highly ranked candidates in the tractable spider model Parasteatoda tepidariorum. Here, we show that an arthropod homolog of the Iroquois complex of homeobox genes is required for proper formation of the boundary between arachnid tagmata. The function of this homolog had not been previously characterized, because it was lost in the common ancestor of Pancrustacea, precluding its investigation in well-studied insect model organisms. Knockdown of the spider copy of this gene, which we designate as waist-less, in P. tepidariorum resulted in embryos with defects in the PO boundary, incurring discontinuous spider germ bands. We show that waist-less is required for proper specification of the segments that span the prosoma-opisthosoma boundary, which in adult spiders corresponds to the narrowed pedicel. Our results demonstrate the requirement of an ancient, taxon-restricted paralog for the establishment of the tagmatic boundary that defines Chelicerata. <<<

The completion of the Human Genome Project has provided a foundational blueprint for understanding human life. Nonetheless, understanding the intricate mechanisms through which our genetic blueprint is involved in disease or orchestrates development across temporal and spatial dimensions remains a profound scientific challenge. Recent breakthroughs in cellular omics technologies have paved new pathways for understanding the regulation of genomic elements and the relationship between gene expression, cellular functions, and cell fate determination. The advent of spatial omics technologies, encompassing both imaging and sequencing-based methodologies, has enabled a comprehensive understanding of biological processes from a cellular ecosystem perspective. This review offers an updated overview of how spatial omics has advanced our understanding of the translation of genetic information into cellular heterogeneity and tissue structural organization and their dynamic changes over time. It emphasizes the discovery of various biological phenomena, related to organ functionality, embryogenesis, species evolution, and the pathogenesis of diseases. <<<

This paper introduces ZeusAI, an artificial intelligence system developed toplay the board game 7 Wonders Duel. Inspired by the AlphaZero reinforcementlearning algorithm, ZeusAI relies on a combination of Monte Carlo Tree Searchand a Transformer Neural Network to learn the game without human supervision.ZeusAI competes at the level of top human players, develops both known andnovel strategies, and allows us to test rule variants to improve the game'sbalance. This work demonstrates how AI can help in understanding and enhancingboard games. <<<

Recent advances in computer vision and deep learning techniques have facilitated significant progress in video scene understanding, thus helping film and television practitioners achieve accurate video editing. However, so far, publicly available semantic segmentation datasets are mostly limited to indoor scenes, city streets, and natural images, often ignoring example objects in action movies, which is a research gap that needs to be urgently filled. In this paper, we introduce a large-scale, high-precision semantic segmentation dataset of props in Chinese martial arts movie clips, named ChineseMPD. Specifically, this dataset first establishes segmentation rules and general review criteria for audiovisual data, and then provides semantic segmentation annotations for six weapon props (Gun, Sword, Stick, Knife, Hook, and Arrow) with a summary of 32,992 objects.To the best of our knowledge, this dataset is the largest semantic segmentation dataset for movie props to date. ChineseMPD dataset not only significantly expands the application of traditional tasks of computer vision such as object detection and scene understanding, but also opens up new avenues for interdisciplinary research. <<<

We reliably judge locations of static objects when we walk despite the retinal images of these objects moving with every step we take. Here, we showed our brains solve this optical illusion by adopting an allocentric spatial reference frame. We measured perceived target location after the observer walked a short distance from the home base. Supporting the allocentric coding scheme, we found the intrinsic bias , which acts as a spatial reference frame for perceiving location of a dimly lit target in the dark, remained grounded at the home base rather than traveled along with the observer. The path-integration mechanism responsible for this can utilize both active and passive (vestibular) translational motion signals, but only along the horizontal direction. This asymmetric path-integration finding in human visual space perception is reminiscent of the asymmetric spatial memory finding in desert ants, pointing to nature’s wondrous and logically simple design for terrestrial creatures. <<<