Search

Extrachromosomal circular DNA (eccDNA) refers to a distinct class of circular DNA molecules that exist independently from linear chromosomal DNA. Extensive evidence has firmly established the significant involvement of eccDNA in cancer initiation, progression, and evolutionary processes. However, the relationship between eccDNA and brain aging remains elusive. Here, we employed extrachromosomal circular DNA sequencing (Circle-seq) to generate a comprehensive dataset of eccDNA from six brain structures of both young and naturally-aged mice, including the olfactory bulb, medial prefrontal cortex, nucleus accumbens, caudate putamen, hippocampus, and cerebellum. Furthermore, through database annotation, we characterized the properties of mouse brain eccDNA, thereby gaining insights into the potential functions of eccDNA in the mouse brain. In conclusion, our study addresses a previously unexplored area by providing a comprehensive molecular characterization of eccDNA in brain tissues. The data presented in the study can be used as a fundamental resource to associate the molecular phenotypes of eccDNA with brain aging and gain deep insights into the biological role of eccDNA in mammalian brain aging., Extrachromosomal circular DNA (eccDNA) refers to a distinct class of circular DNA molecules that exist independently from linear chromosomal DNA. Extensive evidence has firmly established the significant involvement of eccDNA in cancer initiation, progression, and evolutionary processes. However, the relationship between eccDNA and brain aging remains elusive. Here, we employed extrachromosomal circular DNA sequencing (Circle-seq) to generate a comprehensive dataset of eccDNA from six brain structures of both young and naturally-aged mice, including the olfactory bulb, medial prefrontal cortex, nucleus accumbens, caudate putamen, hippocampus, and cerebellum. Furthermore, through database annotation, we characterized the properties of mouse brain eccDNA, thereby gaining insights into the potential functions of eccDNA in the mouse brain. In conclusion, our study addresses a previously unexplored area by providing a comprehensive molecular characterization of eccDNA in brain tissues. The data presented in the study can be used as a fundamental resource to associate the molecular phenotypes of eccDNA with brain aging and gain deep insights into the biological role of eccDNA in mammalian brain aging.

Extrachromosomal circular DNA (eccDNA) has recently gained increasing attention due to its significant role in cancer and other pathophysiologic states. The majority of circular DNAs detected by Circle-seq are small-size eccDNAs with enigmatic functions. One major technical hurdle is to synthesize eccDNA for functional identification. Here, we describe CAES (Circle-seq based Artificial EccDNA Synthesis), a promising and reliable method for artificial eccDNA synthesis. Eight eccDNAs carrying different microRNA genes (eccMIR) found in gastric cancer tissues, ranging from 329 bp to 2189 bp in size, were created utilizing the CAES method. Exonuclease V and single restriction-endonuclease digestion identified the circular structure of synthetic eccDNAs. The DNA circularization efficiency afforded by CAES ranged from 15.6% to 31.1%, which was negatively correlated with the eccDNA length. In addition, we demonstrated that CAES-synthesized eccMIRs can express both miRNA-3p and − 5p molecules efficiently independent of a canonical promoter in human cell lines. Further assays proved that these eccMIRs were functional as they were able to repress the luciferase gene containing a miRNA-target sequence in the 3′UTR as well as the endogenous mRNA targets. Finally, kinetics study revealed that eccDNA exhibited a decay rate similar to the standard plasmids and linear DNA in cultured cells. Together, this study offers a rapid and convenient method for Circle-seq users to synthesize artificial eccDNAs. It also demonstrates the promising potential of eccMIR as a bacterial DNA-free vector for safe and robust miRNA overexpression in both basic research and therapeutic applications., Extrachromosomal circular DNA (eccDNA) has recently gained increasing attention due to its significant role in cancer and other pathophysiologic states. The majority of circular DNAs detected by Circle-seq are small-size eccDNAs with enigmatic functions. One major technical hurdle is to synthesize eccDNA for functional identification. Here, we describe CAES (Circle-seq based Artificial EccDNA Synthesis), a promising and reliable method for artificial eccDNA synthesis. Eight eccDNAs carrying different microRNA genes (eccMIR) found in gastric cancer tissues, ranging from 329 bp to 2189 bp in size, were created utilizing the CAES method. Exonuclease V and single restriction-endonuclease digestion identified the circular structure of synthetic eccDNAs. The DNA circularization efficiency afforded by CAES ranged from 15.6% to 31.1%, which was negatively correlated with the eccDNA length. In addition, we demonstrated that CAES-synthesized eccMIRs can express both miRNA-3p and − 5p molecules efficiently independent of a canonical promoter in human cell lines. Further assays proved that these eccMIRs were functional as they were able to repress the luciferase gene containing a miRNA-target sequence in the 3′UTR as well as the endogenous mRNA targets. Finally, kinetics study revealed that eccDNA exhibited a decay rate similar to the standard plasmids and linear DNA in cultured cells. Together, this study offers a rapid and convenient method for Circle-seq users to synthesize artificial eccDNAs. It also demonstrates the promising potential of eccMIR as a bacterial DNA-free vector for safe and robust miRNA overexpression in both basic research and therapeutic applications.

The inference phase of Large Language Models (LLMs) is very expensive. An ideal inference stage of LLMs could utilize fewer computational resources while still maintaining its capabilities (e.g., generalization and in-context learning ability). In this paper, we try to answer the question, "During LLM inference, can we use shallow layers for easy instances; and deep layers for hard ones?" To answer this question, we first indicate that Not all Layers are Necessary during Inference by statistically analyzing the activated layers across tasks. Then, we propose a simple algorithm named AdaInfer to determine the inference termination moment based on the input instance adaptively. More importantly, AdaInfer does not alter LLM parameters and maintains generalizability across tasks. Experiments on well-known LLMs (i.e., Llama2 series and OPT) show that AdaInfer saves an average of 14.8% of computational resources, even up to 50% on sentiment tasks, while maintaining comparable performance. Additionally, this method is orthogonal to other model acceleration techniques, potentially boosting inference efficiency further.

Semantic scene completion (SSC) has recently gained popularity because it can provide both semantic and geometric information that can be used directly for autonomous vehicle navigation. However, there are still challenges to overcome. SSC is often hampered by occlusion and short-range perception due to sensor limitations, which can pose safety risks. This paper proposes a fundamental solution to this problem by leveraging vehicle-to-vehicle (V2V) communication. We propose the first generalized collaborative SSC framework that allows autonomous vehicles to share sensing information from different sensor views to jointly perform SSC tasks. To validate the proposed framework, we further build V2VSSC, the first V2V SSC benchmark, on top of the large-scale V2V perception dataset OPV2V. Extensive experiments demonstrate that by leveraging V2V communication, the SSC performance can be increased by 8.3% on geometric metric IoU and 6.0% mIOU.

With their high-fidelity scene representation capability, the attention of SLAM field is deeply attracted by the Neural Radiation Field (NeRF) and 3D Gaussian Splatting (3DGS). Recently, there has been a surge in NeRF-based SLAM, while 3DGS-based SLAM is sparse. A novel 3DGS-based SLAM approach with a fusion of deep visual feature, dual keyframe selection and 3DGS is presented in this paper. Compared with the existing methods, the proposed tracking is achieved by feature extraction and motion filter on each frame. The joint optimization of poses and 3D Gaussians runs through the entire mapping process. Additionally, the coarse-to-fine pose estimation and compact Gaussian scene representation are implemented by dual keyframe selection and novel loss functions. Experimental results demonstrate that the proposed algorithm not only outperforms the existing methods in tracking and mapping, but also has less memory usage.

Recommendation systems play a crucial role in various domains, suggesting items based on user behavior.However, the lack of transparency in presenting recommendations can lead to user confusion. In this paper, we introduce Data-level Recommendation Explanation (DRE), a non-intrusive explanation framework for black-box recommendation models.Different from existing methods, DRE does not require any intermediary representations of the recommendation model or latent alignment training, mitigating potential performance issues.We propose a data-level alignment method, leveraging large language models to reason relationships between user data and recommended items.Additionally, we address the challenge of enriching the details of the explanation by introducing target-aware user preference distillation, utilizing item reviews. Experimental results on benchmark datasets demonstrate the effectiveness of the DRE in providing accurate and user-centric explanations, enhancing user engagement with recommended item., Comment: 5 pages, 2 figures

Extrachromosomal circular DNAs (eccDNAs) carrying random genomic segments are broadly found across different cancer types, but their molecular functions and impact in gastric cancer (GC) are rarely known. In this study, we aimed to investigate the potential role of eccDNA in GC. Using the Circle-seq strategy, we observed the eccDNA abundance in gastric cancer tissues (GCT) was aberrantly higher than that of normal adjacent tissues (NAT). The high abundance of eccDNAs carrying oncogene-segments in GCT may represent the DNA damage products of amplified oncogenes. Analysis of GCT over-represented eccDNA carrying enhancer (eccEnhancer) based on data from FANTOM5 project combined with TCGA database suggested the GC over-represented eccEnhancers may contribute to development of GC. GC over-represented eccDNAs carrying pre-miRNA (eccMIR) were enriched to multiple cancer-relevant signal pathways by KEGG analysis. We then synthesized the top six GC over-represented eccMIRs and found four of them enabled high expression of miRNAs and down-regulation of miRNA-target genes in MGC803 cells. Furthermore, we observed the inheritance of GC over-represented eccMIRs benefited host cell proliferation and promoted the aggressive features of host cells. Altogether, this study revealed the GC over-represented eccDNAs carrying functional genomic segments were related to the carcinogenesis of GC and presented the capability to facilitate cancer progression, suggesting the cancerous eccDNAs may serve as a dynamic reservoir for genome plasticity and rapid adaptive evolution of cancer. Therefore, blocking the pathways for eccDNAs generation may provide a novel therapeutic strategy for the treatment of gastric cancer.

Stem borers (Lepidoptera) are common cereal pests. In many parts of the world, the species Ostrinia nubilalis and Sesamia nonagrioides stand out as important insect pests of economically important crops such as maize. Their management relied mainly on transgenic host plant resistance over the last 25 years. Technologies based on the insecticidal properties of Bacillus thuringiensis-derived proteins allowed widespread pest population suppression, especially for O. nubilalis. However, the recent discovery of Bt resistance, which has revitalized interest in both pests’ biology and management, may jeopardize the effectiveness of such transgenic technologies. Historical information on O. nubilalis bionomy may need to be reassessed in light of changing climate conditions and changing agricultural practices, as well as increased production of alternate host crops across its distribution range. The current paper examines the bioecology and historical research that has been conducted to manage these two important maize-boring pests.

N6-methyladenosine (m6A) has been demonstrated to regulate learning and memory in mice. To investigate the mechanism by which m6A modification exerts its function through its reader proteins in the hippocampus, as well as to unveil the specific subregions of the hippocampus that are crucial for memory formation, we generated dentate gyrus (DG)-, CA3-, and CA1-specific Ythdf1 and Ythdf2 conditional knockout (cKO) mice, respectively. Surprisingly, we found that only the DG-specific Ythdf2 cKO mice displayed impaired memory formation, which is inconsistent with the previous report showing that YTHDF1 was involved in this process. YTHDF2 controls the stability of its target transcripts which encode proteins that regulate the elongation of mossy fibers (MF), the axons of DG granule cells. DG-specific Ythdf2 ablation caused MF overgrowth and impairment of the MF-CA3 excitatory synapse development and transmission in the stratum lucidum. Thus, this study identifies the m6A reader YTHDF2 in dentate gyrus as the only regulator that mediates m6A modification in hippocampus-dependent learning and memory. © 2023, The Author(s), under exclusive licence to Springer Nature Limited.

As language models scale up, it becomes increasingly expensive to verify research ideas because conclusions on small models do not trivially transfer to large ones. A possible solution is to establish a generic system that accurately predicts certain metrics for large models without training them. Existing scaling laws require hyperparameter search on the largest models, limiting their predicative capability. In this paper, we present an approach (namely {\mu}Scaling) to predict the pre-training loss, based on our observations that Maximal Update Parametrization ({\mu}P) enables accurate fitting of scaling laws close to common loss basins in hyperparameter space. With {\mu}Scaling, different model designs can be compared on large scales by training only their smaller counterparts. Further, we introduce nanoLM: an affordable LLM pre-training benchmark that facilitates this new research paradigm. With around 14% of the one-time pre-training cost, we can accurately forecast the loss for models up to 52B. Our goal with nanoLM is to empower researchers with limited resources to reach meaningful conclusions on large models. We also aspire for our benchmark to serve as a bridge between the academic community and the industry. Code for {\mu}Scaling is available at https://github.com/cofe-ai/Mu-scaling. Code for nanoLLM will be available later., Comment: This is a modified and extended version of our previous Mu-scaling work released in April 2023 (see v1)

Spatio-temporal forecasting of future values of spatially correlated time series is important across many cyber-physical systems (CPS). Recent studies offer evidence that the use of graph neural networks to capture latent correlations between time series holds a potential for enhanced forecasting. However, most existing methods rely on pre-defined or self-learning graphs, which are either static or unintentionally dynamic, and thus cannot model the time-varying correlations that exhibit trends and periodicities caused by the regularity of the underlying processes in CPS. To tackle such limitation, we propose Time-aware Graph Structure Learning (TagSL), which extracts time-aware correlations among time series by measuring the interaction of node and time representations in high-dimensional spaces. Notably, we introduce time discrepancy learning that utilizes contrastive learning with distance-based regularization terms to constrain learned spatial correlations to a trend sequence. Additionally, we propose a periodic discriminant function to enable the capture of periodic changes from the state of nodes. Next, we present a Graph Convolution-based Gated Recurrent Unit (GCGRU) that jointly captures spatial and temporal dependencies while learning time-aware and node-specific patterns. Finally, we introduce a unified framework named Time-aware Graph Convolutional Recurrent Network (TGCRN), combining TagSL, and GCGRU in an encoder-decoder architecture for multi-step spatio-temporal forecasting. We report on experiments with TGCRN and popular existing approaches on five real-world datasets, thus providing evidence that TGCRN is capable of advancing the state-of-the-art. We also cover a detailed ablation study and visualization analysis, offering detailed insight into the effectiveness of time-aware structure learning., Comment: published in ICDE 2024

Large language models (LLMs) have achieved remarkable success in NLP and multimodal tasks, among others. Despite these successes, two main challenges remain in developing LLMs: (i) high computational cost, and (ii) fair and objective evaluations. In this paper, we report a solution to significantly reduce LLM training cost through a growth strategy. We demonstrate that a 101B-parameter LLM with 0.31T tokens can be trained with a budget of 100K US dollars. Inspired by IQ tests, we also consolidate an additional range of evaluations on top of existing evaluations that focus on knowledge-oriented abilities. These IQ evaluations include symbolic mapping, rule understanding, pattern mining, and anti-interference. Such evaluations minimize the potential impact of memorization. Experimental results show that our model, named FLM-101B, trained with a budget of 100K US dollars, achieves performance comparable to powerful and well-known models, e.g., GPT-3 and GLM-130B, especially on the additional range of IQ evaluations. The checkpoint of FLM-101B is released at https://huggingface.co/CofeAI/FLM-101B.

The combined effects of carbonation and chloride attack can accelerate the degradation of reinforced concrete (RC) structures. In this study, the effect of natural carbonation on the chloride binding behaviours in Ordinary Portland cement (OPC) paste was investigated. The phase-equilibrium model for the dissolution/precipitation reactions and the surface complexation model for the ionic adsorption of C–S–H were adopted. An experiment from the literature was used as the benchmark. The results indicate that Kuzel's salt is produced when OPC paste is exposed to a mild chloride attack. During the natural carbonation process, Kuzel's salt is converted into Friedel's salt. As the carbonation continues, the Friedel's salt disappears. Complete natural carbonation results in a total loss of chemical binding capacity, and only a partial loss of the physical binding capacity in cement-based materials. This completely differs from the accelerated carbonation commonly used in the laboratory, which can cause complete loss of both chemical and physical binding capacity. Therefore, the durability design of RC structures vulnerable to the combined attack of chloride and carbonation based on the results of the accelerated carbonation is conservative., Materials and Environment

Background: There is a need for functional genome-wide annotation of the protein-coding genes to get a deeper understanding of mammalian biology. Here, a new annotation strategy is introduced based on dimensionality reduction and density-based clustering of whole-body co-expression patterns. This strategy has been used to explore the gene expression landscape in pig, and we present a whole-body map of all protein-coding genes in all major pig tissues and organs. Results: An open-access pig expression map (www.rnaatlas.org ) is presented based on the expression of 350 samples across 98 well-defined pig tissues divided into 44 tissue groups. A new UMAP-based classification scheme is introduced, in which all protein-coding genes are stratified into tissue expression clusters based on body-wide expression profiles. The distribution and tissue specificity of all 22,342 protein-coding pig genes are presented. Conclusions: Here, we present a new genome-wide annotation strategy based on dimensionality reduction and density-based clustering. A genome-wide resource of the transcriptome map across all major tissues and organs in pig is presented, and the data is available as an open-access resource (www.rnaatlas.org), including a comparison to the expression of human orthologs.

Host plant expansion is an important survival strategy for tephritids as they expand their range. Successful host expansion requires tephritids to adapt to the chemical and nonchemical properties of a novel host fruit, such as fruit color, phenology, and phytochemicals. These plant properties trigger a series of processes in tephritids, with each process having its own genetic basis, which means that various genes are involved in regulating host plant expansion by tephritids. This review summarizes current knowledge on the categories and roles of genes involved in host plant expansion in several important tephritid species, including genes related to chemoreception (olfactory and gustation), vision, digestion, detoxification, development, ribosomal and energy metabolism. Chemoreception- and detoxification- and digestion-related genes are stimulated by volatile chemicals and secondary chemicals of different hosts, respectively, which are involved in the regulation of nervous signal transduction that triggers behavioral, physical, and chemical responses to the novel host fruit. Vision-, nerve-, and development-related genes and metabolism-associated genes are activated in response to nonchemical stimuli from different hosts, such as color and phenology, to regulate a comprehensive adaptation of the extending host for tephritids. The chemical and nonchemical signals of hosts activate ribosomal and energy-related genes that result in the basic regulation of many processes of host expansion, including detoxification and development. These genes do not regulate novel host use individually, but multiple genes regulate multilevel adaptation to novel host fruits via multiple mechanisms. These genes may also be potential target genes for RNAi-based control of tephritid pests.

The electrochemical CO2 reduction reaction (CO2RR) offers a green and sustainable process to convert CO2 into valuable chemical stocks and fuels. Metal is one of the most promising types of catalysts to drive an efficient and selective CO2RR. The catalytic performance of metal nanocatalysts is strongly dependent on their structural features. Recently, phase engineering of nanomaterials (PEN) has emerged as a prominent tactic to regulate the catalytic performance of metal nanocatalysts for the CO2RR. A broad range of metal nanocatalysts with conventional and unconventional crystal phases has been developed, and remarkable achievements have been made. This review summarizes the most recent developments in phase engineering of metal nanocatalysts for the electrochemical CO2RR. We first introduce the different crystal phases of metal nanocatalysts used in the CO2RR and then discuss various synthetic strategies for unconventional phases of metal nanocatalysts. After that, detailed discussions of metal nanocatalysts with conventional and unconventional phases, including amorphous phases, are presented. Finally, the challenges and perspectives in this emerging area are discussed. © 2022 The Authors

Methods for sensitive and high-throughput evaluation of CRISPR RNA-guided nucleases (RGNs) off-targets (OTs) are essential for advancing RGN-based gene therapies. Here we report SURRO-seq for simultaneously evaluating thousands of therapeutic RGN OTs in cells. SURRO-seq captures RGN-induced indels in cells by pooled lentiviral OTs libraries and deep sequencing, an approach comparable and complementary to OTs detection by T7 endonuclease 1, GUIDE-seq, and CIRCLE-seq. Application of SURRO-seq to 8150 OTs from 110 therapeutic RGNs identifies significantly detectable indels in 783 OTs, of which 37 OTs are found in cancer genes and 23 OTs are further validated in five human cell lines by targeted amplicon sequencing. Finally, SURRO-seq reveals that thermodynamically stable wobble base pair (rG•dT) and free binding energy strongly affect RGN specificity. Our study emphasizes the necessity of thoroughly evaluating therapeutic RGN OTs to minimize inevitable off-target effects.

Extrachromosomal circular DNA (eccDNA) of chromosomal origin is common in eukaryotic cells. Amplification of oncogenes on large eccDNA (ecDNA) can drive biological processes such as tumorigenesis, and identification of eccDNA by sequencing after removal of chromosomal DNA is therefore important for understanding their impact on the expressed phenotype. However, the circular mitochondrial DNA (mtDNA) might challenge the detection of eccDNA because the average somatic cell has hundreds of copies of mtDNA. Here we show that 61.2-99.5% of reads from eccDNA-enriched samples correspond to mtDNA in mouse tissues. We have developed a method to selectively remove mtDNA from total circular DNA by CRISPR/Cas9 guided cleavage of mtDNA with one single-guide RNA (sgRNA) or two sgRNAs followed by exonuclease degradation of the linearized mtDNA. Sequencing revealed that mtDNA reads were 85.9% +/- 12.6% removed from eccDNA of 9 investigated mouse tissues. CRISPR/Cas9 cleavage also efficiently removed mtDNA from a human HeLa cell line and colorectal cancer samples. We identified up to 14 times more, and also larger eccDNA in CRISPR/Cas9 treated colorectal cancer samples than in untreated samples. We foresee that the method can be applied to effectively remove mtDNA from any eukaryotic species to obtain higher eccDNA yields. (c) 2022 The Author(s). Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Identifying and protecting refugia is a priority for conservation management under projected anthropogenic climate change. We have two main objectives: the first is to explore the spatial (East Asia) and temporal (Last Glacial Maximum to year 2070) distribution patterns of dominant Castanopsis species of evergreen broad-leaved forests, also the relation with their niche breadths; the second is to identify long-term stable refugia for preserving these species and provide a framework of conservation strategies. We find that there is an extraordinary richness with 32 dominant Castanopsis species, and they form both a geographically and climatically almost unbroken connection from ca. 5°N to 38°N, having thus ecological significance. During the Mid-Holocene and, particularly, the Last Glacial Maximum, the predicted suitable areas of the species as a whole were larger than those in the present. By 2070, potentially suitable areas with high richness of dominant Castanopsis species will be reduced by 94.5 % on average. No correlation between species niche breadths and distribution ranges is found, which could be due to regional climate stability. Mountains of southwestern and southern Yunnan in China are identified as climatically long-term stable refugia for 7¿9 Castanopsis species. We recommend that these refugia have the highest priority of conservation to prevent their extinction. Our suggested urgent measures include improving the effectiveness of currently protected Castanopsis species and expanding the network of protected areas to cover a larger fraction of the refugia, as well as ensuring Castanopsis species natural regeneration potential in fragmented and natural secondary forest areas.

BACKGROUND: Extrachromosomal circular deoxyribonucleic acid (eccDNA) is evolving as a valuable biomarker, while little is known about its presence in urine.METHODS: Here, we report the discovery and analysis of urinary cell-free eccDNAs (ucf-eccDNAs) in healthy controls and patients with advanced chronic kidney disease (CKD) by Circle-Seq.RESULTS: Millions of unique ucf-eccDNAs were identified and comprehensively characterised. The ucf-eccDNAs are GC-rich. Most ucf-eccDNAs are less than 1000 bp and are enriched in four pronounced peaks at 207, 358, 553 and 732 bp. Analysis of the genomic distribution of ucf-eccDNAs shows that eccDNAs are found on all chromosomes but enriched on chromosomes 17, 19 and 20 with a high density of protein-coding genes, CpG islands, short interspersed transposable elements (SINEs) and simple repeat elements. Analysis of eccDNA junction sequences further suggests that microhomology and palindromic repeats might be involved in eccDNA formation. The ucf-eccDNAs in CKD patients are significantly higher than those in healthy controls. Moreover, eccDNA with miRNA genes is highly enriched in CKD ucf-eccDNA.CONCLUSIONS: This work discovers and provides the first deep characterisation of ucf-eccDNAs and suggests ucf-eccDNA as a valuable noninnvasive biomarker for urogenital disorder diagnosis and monitoring.

Retrosynthetic planning, which aims to find a reaction pathway to synthesize a target molecule, plays an important role in chemistry and drug discovery. This task is usually modeled as a search problem. Recently, data-driven methods have attracted many research interests and shown promising results for retrosynthetic planning. We observe that the same intermediate molecules are visited many times in the searching process, and they are usually independently treated in previous tree-based methods (e.g., AND-OR tree search, Monte Carlo tree search). Such redundancies make the search process inefficient. We propose a graph-based search policy that eliminates the redundant explorations of any intermediate molecules. As searching over a graph is more complicated than over a tree, we further adopt a graph neural network to guide the search over graphs. Meanwhile, our method can search a batch of targets together in the graph and remove the inter-target duplication in the tree-based search methods. Experimental results on two datasets demonstrate the effectiveness of our method. Especially on the widely used USPTO benchmark, we improve the search success rate to 99.47%, advancing previous state-of-the-art performance for 2.6 points., Comment: KDD2022

Messenger RNA m6A modification is shown to regulate local translation in axons. However, how the m6A codes in axonal mRNAs are read and decoded by the m6A reader proteins is still unknown. Here, it is found that the m6A readers YTHDF1 and YTHDF2 are both expressed in cerebellar granule cells (GCs) and their axons. Knockdown (KD) of YTHDF1 or YTHDF2 significantly increases GC axon growth rates in vitro. By integrating anti-YTHDF1&2 RIP-Seq with the quantitative proteomic analysis or RNA-seq after KD of YTHDF1 or YTHDF2, a group of transcripts which may mediate the regulation of GC axon growth by YTHDFs is identified. Among them, Dvl1 and Wnt5a, encoding the key components of Wnt pathway, are further found to be locally translated in axons, which are controlled by YTHDF1 and YTHDF2, respectively. Specific ablation of Ythdf1 or Ythdf2 in GCs increases parallel fiber growth, promotes synapse formation in cerebellum in vivo, and improves motor coordination ability. Together, this study identifies a mechanism by which the m6A readers YTHDF1 and YTHDF2 work synergistically on the Wnt5a pathway through regulating local translation in GC axons to control cerebellar parallel fiber development.

This paper proposed a novel large neighborhood search-adaptive genetic algorithm (LNS-AGA) for many-to-many on-orbit repairing mission planning of geosynchronous orbit (GEO) satellites with mission deadline constraint. In the many-to-many on-orbit repairing scenario, several servicing spacecrafts and target satellites are located in GEO orbits which have different inclination, RAAN and true anomaly. Each servicing spacecraft need to rendezvous with target satellites to perform repairing missions under limited fuel. The mission objective is to find the optimal servicing sequence and orbit rendezvous time of every servicing spacecraft to minimize total cost of all servicing spacecrafts with all target satellites repaired. Firstly, a time-dependent orbital rendezvous strategy is proposed, which can handle the mission deadline constraint. Besides, it is also cost-effective compared with the existing strategy. Based on this strategy, the many-to-many on-orbit repairing mission planning model can be simplified to an integer programming problem, which is established based on the vehicle routing problem with time windows (VRPTW) model. In order to efficiently find a feasible optimal solution under complicated constraints, a hybrid adaptive genetic algorithm combining the large neighborhood search procedure is designed. The operations of "destroy" and "repair" are used on the elite individuals in each generation of the genetic algorithm to enhance local search capabilities. Finally, the simulations under different scenarios are carried out to verify the effectiveness of the presented algorithm and orbital rendezvous strategy, which performs better than the traditional genetic algorithm.

The transcription factor cyclic-AMP response element-binding protein 1 (CREB1) responds to cAMP level and controls the expression of target genes, which regulates nutrition partitioning. The promoters of CREB1-targeted genes responsive to cAMP have been extensively investigated and characterized with the presence of both cAMP response element and TATA box. Compelling evidence demonstrates that CREB1 also plays an essential role in promoting tumor development. However, only very few genes required for cell survival, proliferation and migration are known to be constitutively regulated by CREB1 in tumors. Their promoters mostly do not harbor any cAMP response element. Thus, it is very likely that CREB1 regulates the expressions of distinct sets of target genes in normal tissues and tumors. The whole gene network constitutively regulated by CREB1 in tumors has remained unrevealed. Here, we employ a systematical and integrative approach to decipher this gene network in the context of both tissue cultured cancer cells and patient samples. We combine transcriptomic, Rank-Rank Hypergeometric Overlap, and Chipseq analysis, to define and characterize CREB1-regulated genes in a multidimensional fashion. A strong cancer relevance of those top-ranked targets, which meet the most stringent criteria, is eventually verified by overall survival analysis of cancer patients. These findings strongly suggest the importance of genes constitutively regulated by CREB1 for their implicative involvement in promoting tumorigenesis.

The design of CRISPR gRNAs requires accurate on-target efficiency predictions, which demand high-quality gRNA activity data and efficient modeling. To advance, we here report on the generation of on-target gRNA activity data for 10,592 SpCas9 gRNAs. Integrating these with complementary published data, we train a deep learning model, CRISPRon, on 23,902 gRNAs. Compared to existing tools, CRISPRon exhibits significantly higher prediction performances on four test datasets not overlapping with training data used for the development of these tools. Furthermore, we present an interactive gRNA design webserver based on the CRISPRon standalone software, both available via https://rth.dk/resources/crispr/. CRISPRon advances CRISPR applications by providing more accurate gRNA efficiency predictions than the existing tools.

Let $n=2m$. In the present paper, we study the binomial Boolean functions of the form $$f_{a,b}(x) = \mathrm{Tr}_1^{n}(a x^{2^m-1 }) +\mathrm{Tr}_1^{2}(bx^{\frac{2^n-1}{3} }), $$ where $m$ is an even positive integer, $a\in \mathbb{F}_{2^n}^*$ and $b\in \mathbb{F}_4^*$. We show that $ f_{a,b}$ is a bent function if the Kloosterman sum $$K_{m}\left(a^{2^m+1}\right)=1+ \sum_{x\in \mathbb{F}_{2^m}^*} (-1)^{\mathrm{Tr}_1^{m}(a^{2^m+1} x+ \frac{1}{x})}$$ equals $4$, thus settling an open problem of Mesnager. The proof employs tools including computing Walsh coefficients of Boolean functions via multiplicative characters, divisibility properties of Gauss sums, and graph theory.

Allele-specific protospacer adjacent motif (asPAM)-positioning SNPs and CRISPRs are valuable resources for gene therapy of dominant disorders. However, one technical hurdle is to identify the haplotype comprising the disease-causing allele and the distal asPAM SNPs. Here, we describe a novel CRISPR-based method (CRISPR-hapC) for haplotyping. Based on the generation (with a pair of CRISPRs) of extrachromosomal circular DNA in cells, the CRISPR-hapC can map haplotypes from a few hundred bases to over 200 Mb. To streamline and demonstrate the applicability of the CRISPR-hapC and asPAM CRISPR for allele-specific gene editing, we reanalyzed the 1000 human pan-genome and generated a high frequency asPAM SNP and CRISPR database (www.crispratlas.com/knockout) for four CRISPR systems (SaCas9, SpCas9, xCas9 and Cas12a). Using the huntingtin (HTT) CAG expansion and transthyretin (TTR) exon 2 mutation as examples, we showed that the asPAM CRISPRs can specifically discriminate active and dead PAMs for all 23 loci tested. Combination of the CRISPR-hapC and asPAM CRISPRs further demonstrated the capability for achieving highly accurate and haplotype-specific deletion of the HTT CAG expansion allele and TTR exon 2 mutation in human cells. Taken together, our study provides a new approach and an important resource for genome research and allele-specific (haplotype-specific) gene therapy.

Dipentodon sinicus Dunn. (Dipentodonaceae) is a rare and threatened relict plant species usually found co-dominating with other relict plants in subtropical forest patches in highly fragmented habitats of southwestern China, northern Vietnam and northeastern Myanmar of East Asia. To date, its management and conservation strategies in the light of climate change have not been explored. We evaluated effects of climate change on the distribution of climatically suitable areas of D. sinicus as found prevailing during the last glacial maximum (LGM), the mid-Holocene and the present time, and predicted the distribution of climatically suitable habitats in 2070 throughout East Asia. The results as derived from ecological niche modeling (ENM) show the current distribution to be limited to the prehistoric (the mid-Holocene and LGM) refugia, and to indicate decreasing probability of presence and a reducing range of distribution for 2070. In addition, the suitable areas predicted with high probability (0.5–1) only account for on average 9.8% of the total area of potential habitats (threshold‒1) among the models for the year 2070, thereby indicating that D. sinicus is highly vulnerable. Under all the future scenarios for the year 2070, 69–74.2% of potential habitats in China would be outside protected areas. We assess and propose priorities for protected areas, and provide suggestions for conservation management strategies.

Fan Li, Shan Hu, Kangle Kong, Peng Cao, Peng Han, Yu Deng, Bo Zhao Department of Thoracic Surgery, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, People’s Republic of ChinaCorrespondence: Bo Zhao Email 13006369600@163.comBackground: Pulmonary carcinosarcomas (PCSs) are a heterogeneous group of non-small-cell lung carcinomas (NSCLCs) with aggressiveness and a poor prognosis. Although genetic mutations of some common lung cancer subtypes have been extensively studied, the molecular characteristics of PCSs and the existence of abnormal target genes are unknown.Methods: In this study, the clinical and molecular characterization in 3 pulmonary sarcomatoid carcinomas (PSCs) were presented using microscope analysis and next-generation sequencing (NGS) analysis.Results: The results revealed a carcinosarcomas subtype presenting squamous cell carcinoma and sarcoma components in all 3 cases. NGS analysis showed that 182, 316 and 230 shared mutations were detected between sarcoma and lung carcinoma from 3 patients. Two identical alterations in two genes (CSMD3 and RYR3) that were all shared by the two components in 3 patients. Tumor suppressor gene TP53 (5/6, 83%) showed the highest mutation frequency for driver genes here. Additionally, we focused on an LYST mutation which was mainly present in the sarcoma components. Moreover, the clonal evolution and signature analysis confirm that lung squamous cell carcinoma and sarcoma in each PCS patient may have come from a common ancestor, and mutagenesis was possibly related to indirect effects of tobacco, age or other unknown factors.Conclusion: Our results indicate that genetic analysis and molecular targeted therapy are necessary for the identification and treatment of these rare lung tumors. CSMD3 and LYST, as common mutation genes, may be a potential therapeutic target in PCS.Keywords: non-small cell lung cancer, pulmonary carcinosarcoma, lung squamous cell carcin

Semantic road region segmentation is a high-level task, which paves the way towards road scene understanding. This paper presents a residual network trained for semantic road segmentation. Firstly, we represent the projections of road disparities in the v-disparity map as a linear model, which can be estimated by optimizing the v-disparity map using dynamic programming. This linear model is then utilized to reduce the redundant information in the left and right road images. The right image is also transformed into the left perspective view, which greatly enhances the road surface similarity between the two images. Finally, the processed stereo images and their disparity maps are concatenated to create a set of 3D images, which are then utilized to train our neural network. The experimental results illustrate that our network achieves a maximum F1-measure of approximately 91.19%, when analyzing the images from the KITTI road dataset. © 2019 IEEE.

In this paper, we present an autonomous unmanned aerial vehicle (UAV) landing system based on visual navigation. We design the landmark as a topological pattern in order to enable the UAV to distinguish the landmark from the environment easily. In addition, a dynamic thresholding method is developed for image binarization to improve detection efficiency. The relative distance in the horizontal plane is calculated according to effective image information, and the relative height is obtained using a linear interpolation method. The landing experiments are performed on a static and a moving platform, respectively. The experimental results illustrate that our proposed landing system performs robustly and accurately. © 2019 IEEE.

Mastering self-regulation strategies would seem to be essential in distance and online university studies since the workload is much greater and students need to be more independent and responsible for their own learning. By self-regulation strategies, we mean the student’s mental activities aimed at creating favorable conditions for learning, including managing their concentration, motivation, time and tasks. With the aim of identifying self-regulation strategies used or not by students enrolled in distance and online learning, an initial study of 1,060 students was conducted. Various analyses were carried out. The results indicate that at least 29% of students have difficulty setting and adhering to a study schedule and trouble getting down to work. They also have difficulty focusing on their course and maintaining attention and concentration. They generally feel tense or under pressure during their studies and afraid or worried when performing learning activities in a course. When they need help, they find it difficult to turn to other students and communicate with them in order to support their learning process. In addition, three respondent profiles were identified. They stand out in relation to strategies for task management, concentration and asking for help: (1) living alone, single and under 25 years old, (2) living with a common-law partner and 25 to 34 years old and (3) living with a spouse and children, 35 to 44 years old.

Health literacy constitutes an important step towards patient empowerment and the Web is presently the biggest repository of medical information and, thus, the biggest medical resource to be used in the learning process. However, at present, web medical information is mainly accessed through generic search engines that do not take into account the user specific needs and starting knowledge and so they are not able to support learning activities tailored to the specific user requirements. This work presents “ULearn” a meta engine that supports access, understanding and learning on the Web in the medical domain based on specific user requirements and knowledge levels towards what we call “balanced learning”. Balanced learning allows users to perform learning activities based on specific user requirements (understanding, deepening, widening and exploring) towards his/her empowerment. We have designed and developed ULearn to suggest search keywords correlated to the different user requirements and we have carried out some preliminary experiments to evaluate the effectiveness of the provided information.

Semantic road region segmentation is a high-level task, which paves the way towards road scene understanding. This paper presents a residual network trained for semantic road segmentation. Firstly, we represent the projections of road disparities in the v-disparity map as a linear model, which can be estimated by optimizing the v-disparity map using dynamic programming. This linear model is then utilized to reduce the redundant information in the left and right road images. The right image is also transformed into the left perspective view, which greatly enhances the road surface similarity between the two images. Finally, the processed stereo images and their disparity maps are concatenated to create a set of 3D images, which are then utilized to train our neural network. The experimental results illustrate that our network achieves a maximum F1-measure of approximately 91.19% when analyzing the images from the KITTI road dataset., Comment: 5 pages, 5 figures, accepted by 2019 IEEE International Conference on Imaging Systems and Techniques (IST)

We present femtosecond optical pump-terahertz probe studies on the ultrafast dynamical processes of photo-generated charge carriers in silicon photovoltaic cells with various nanostructured surfaces and doping densities. The pump-probe measurements provide direct insight on the lifetime of photo-generated carriers, frequency-dependent complex dielectric response along with photoconductivity of silicon photovoltaic cells excited by optical pump pulses. A lifetime of photo-generated carriers of tens of nanosecond is identified from the time-dependent pump-induced attenuation of the terahertz transmission. In addition, we find a large value of the imaginary part of the dielectric function and of the real part of the photoconductivity in silicon photovoltaic cells with micron length nanowires. We attribute these findings to the result of defect-enhanced electron-photon interactions. Moreover, doping densities of phosphorous impurities in silicon photovoltaic cells are also quantified using the Drude-Smith model with our measured frequency-dependent complex photoconductivities.

Today East Asia harbors many “relict” plant species whose ranges were much larger during the Paleogene-Neogene and earlier. The ecological and climatic conditions suitable for these relict species have not been identified. Here, we map the abundance and distribution patterns of relict species, showing high abundance in the humid subtropical/warm-temperate forest regions. We further use Ecological Niche Modeling to show that these patterns align with maps of climate refugia, and we predict species’ chances of persistence given the future climatic changes expected for East Asia. By 2070, potentially suitable areas with high richness of relict species will decrease, although the areas as a whole will probably expand. We identify areas in southwestern China and northern Vietnam as long-term climatically stable refugia likely to preserve ancient lineages, highlighting areas that could be prioritized for conservation of such species.

The arthropod community structure in wolfberry orchards of different management regimes were monitored from April to August in 2012 at Ningxia Hui Autonomous Region of Northwestern China. The three different management regimes included (1) orchard free of pesticide, (2) organic orchard, and (3) conventional orchard. Totally, 167 species (4 classes, 27 orders, and 76 families) contained 61 natural enemy species and 106 pest species were recorded in the experiment. The species richness of the orchard free of pesticide, organic orchard with biological control and conventional orchard with chemical control was 61, 30 and 23 species, respectively. Moreover, the corresponding coefficients in the orchard free of pesticide, conventional orchard and organic orchard were 0.864, 0.684 and 0.733, respectively. The different modules of pests varied in their responses to environmental factors depending on different feeding types. The linkage between arthropod community and environmental factors indicated that vegetation diversity, plant coverage, pesticide application and irrigation times exerted detectable contrasting effects on arthropod community and population dynamics. Finally, we suggest that habitat management (i.e. increase in plant cover and diversity) may serve as effective tactics for preventing pest population from reaching the economic injury level which minimizing the input of pesticides and fertilizers.

Geomagnetic polarity reversal boundaries are key isochronous chronological controls for the long Chinese loess sequences, and further facilitate paleoclimatic correlation between Chinese loess and marine sediments. However, owing to complexity of postdepositional remanent magnetization (pDRM) acquisition processes related to variable dust sedimentary environments on the Chinese Loess Plateau (CLP), there is a long-standing dispute concerning the downward shift of the pDRM recorded in Chinese loess. In this study, after careful stratigraphic correlation of representative climatic tie points and the Matuyama-Brunhes boundaries (MBB) in the Xifeng, Luochuan, and Mangshan loess sections with different pedogenic environments, the downward shift of the pDRM is semiquantitatively estimated and the acquisition model for the loess natural remanent magnetization (NRM) is discussed. The measured MB transition zone has been affected by the surficial mixing layer (SML) and remagnetization. Paleoprecipitation is suggested to be the dominant factor controlling the pDRM acquisition processes. Rainfall-controlled leaching would restrict the efficiency of the characterized remanent magnetization carriers aligning along the ancient geomagnetic field. We conclude that the MBB in the central CLP with moderate paleoprecipitation could be considered as an isochronous chronological control after moderate upward adjustment. A convincing case can then be made to correlate L8/S8 to MIS 18/19

This paper presents a novel selective constraint propagation method for constrained image segmentation. In the literature, many pairwise constraint propagation methods have been developed to exploit pairwise constraints for cluster analysis. However, since most of these methods have a polynomial time complexity, they are not much suitable for segmentation of images even with a moderate size, which is actually equivalent to cluster analysis with a large data size. Considering the local homogeneousness of a natural image, we choose to perform pairwise constraint propagation only over a selected subset of pixels, but not over the whole image. Such a selective constraint propagation problem is then solved by an efficient graph-based learning algorithm. To further speed up our selective constraint propagation, we also discard those less important propagated constraints during graph-based learning. Finally, the selectively propagated constraints are exploited based on $L_1$-minimization for normalized cuts over the whole image. The experimental results demonstrate the promising performance of the proposed method for segmentation with selectively propagated constraints.

Chang Li,1 Chunmeng Sun,1 Shasha Li,1 Peng Han,2 Huimin Sun,3 Ammar Ouahab,1 Yan Shen,1 Yourui Xu,1 Yerong Xiong,1 Jiasheng Tu11State Key Laboratory of Natural Medicines, Department of Pharmaceutics, China Pharmaceutical University, Nanjing, 2Chinese Pharmacopoeia Commission, Beijing, 3National Institute for Food and Drug Control, Beijing, People's Republic of ChinaAbstract: In order to limit the adverse reactions caused by polysorbate 80 in Taxotere®, a widely used formulation of docetaxel, a safe and effective nanocarrier for this drug has been developed based on micelles formed by a new class of well-defined polyoxyethylene sorbitol oleate (PSO) with sorbitol as the matrix in aqueous solution. The physicochemical properties of the amphiphilic surfactant and the resulting micelles can be easily fine-tuned by the homogeneous sorbitol matrix and pure oleic acid. Composition, critical micelle concentration, and entrapment efficiency were investigated by ultraviolet visible spectroscopy, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry, fluorospectrophotometry, and high-performance liquid chromatography. In vitro and in vivo evaluation revealed that PSO had exceptionally low hemolysis and histamine release rates compared with commercial polysorbate 80. Moreover, the tumor targeting delivery of PSO was investigated by in vivo imaging in S180 tumor-bearing mice. The results suggest that this novel delivery system, PSO, provides an acceptable alternative to polysorbate 80 for delivery of docetaxel. Further, due to the hypoallergenic nature of PSO, the mechanism of pseudoallergy caused by the polyoxyethylene nonionic surfactant was investigated. Based on in vitro cell analysis, it was assumed that the initial contact of polyoxyethylene nonionic surfactant with mast cells provoked pseudoallergy via polyamine receptor-mediated endocytosis.Keywords: polyoxyethylene nonionic surfactant, sorbitol, isosorbide, pseudoallergy, docetaxel

South China experienced an unusually complex tectonic history, and features a series of globally significant, and well well-preserved geological records. These include records of the assembly and breakup of the Neoproterozoic supercontinent Rodinia, Rodinia- and Pangea-age mantle plume events, Neoproterosoic glacial events, early complex life, large intraplate orogenic and magmatic events, extinction events around the P-T boundary, continental subduction and exhumation, and record of the transition from an Andean-type active margin to the present-day Western Pacific-type active margin. These features make a South China one of the few natural laboratories for studying fundamental geoscience problems and testing various theories and hypotheses. Professor Zheng-Xiang Li and his multinational collaborative team have been working on the tectonic evolution of the South China Block for over 25 years. Their work challenged some traditional views, yet some of their interpretations remain controversial amongst contemporary researchers. This book provides readers a summary of their views on the tectonic evolution of South China, and evidence that their interpretations were based on. It also provides a well illustrated eight-day field program in which the authors attempt to unravel the tectonic history of eastern South China through the examination of a series of carefully selected field traverses and outcrops. This latter part of the book can also serve as a materials for field workshops or short courses on tectonic analysis using multidisciplinary field observations and analytical result. The book is designed for researchers of all levels and senior geoscience students.

Systematically studying all the RXTE/PCA observations for GRS 1915+105 before November 2010, we have discovered three additional patterns in the relation between Quasi-Periodic Oscillation (QPO) frequency and photon energy, extending earlier outcomes reported by Qu et al. (2010). We have confirmed that as QPO frequency increases, the relation evolves from the negative correlation to positive one. The newly discovered patterns provide new constraints on the QPO models.

The RXTE and Swift observations on the 2009 outburst from a newly discovered transient and black-hole candidate XTE J1652$-$453 are analyzed. The source was observed by RXTE to behave a sequence of spectral states that are typical to the black hole XRBs. During the first 7 observations, the source is diagnosed to stay in a high/soft state, from the spectrum dominated by soft thermal component which contributes an average of $\sim$ 85% to the X-ray flux at 2-20keV, and from the hardness $\sim$ 0.1 showing up in the hardness-intensity diagram (HID). For the last 20 observations the spectral state is classified as {\sl low/hard} according to an average hardness of $\sim$ 0.8 and a balance between the thermal and the non-thermal components: a power-law component takes ${\geq}80%$ of total 2-20keV flux. Located in between is an {\sl intermediate} state that the source might have experienced. The usual relationship between rms and hardness presents in HRD as well. Throughout the outburst no QPOs are found in XTE J1652$-$453., Comment: 8 pages, 5 figures