This paper proposes a new game-search algorithm, PN-MCTS, which combinesMonte-Carlo Tree Search (MCTS) and Proof-Number Search (PNS). These twoalgorithms have been successfully applied for decision making in a range ofdomains. We define three areas where the additional knowledge provided by theproof and disproof numbers gathered in MCTS trees might be used: final moveselection, solving subtrees, and the UCB1 selection mechanism. We test allpossible combinations on different time settings, playing against vanilla UCTon several games: Lines of Action ($7$$\times$$7$ and $8$$\times$$8$ boardsizes), MiniShogi, Knightthrough, and Awari. Furthermore, we extend this newalgorithm to properly address games with draws, like Awari, by adding anadditional layer of PNS on top of the MCTS tree. The experiments show thatPN-MCTS is able to outperform MCTS in all tested game domains, achieving winrates up to 96.2% for Lines of Action. <<<

Wolfram Höps, Marjan M. Weiss, Ronny Derks, Jordi Corominas Galbany, Amber den Ouden, Simone van den Heuvel, Raoul Timmermans, Jos Smits, Tom Mokveld, Egor Dolzhenko, Xiao Chen, Arthur van den Wijngaard, Michael A. Eberle, Helger G. Yntema, Alexander Hoischen, Christian Gilissen, Lisenka E.L.M. Vissers <<<

Simeng Hu, Can Hu, Jingli Xu, Pengfei Yu, Li Yuan, Ziyu Li, Haohong Liang, Yanqiang Zhang, Jiahui Chen, Qing Wei, Shengjie Zhang, Litao Yang, Dan Su, Yian Du, Zhiyuan Xu, Fan Bai, Xiangdong Cheng <<<

This work considers the category distribution heterogeneity in federatedlearning. This issue is due to biased labeling preferences at multiple clientsand is a typical setting of data heterogeneity. To alleviate this issue, mostprevious works consider either regularizing local models or fine-tuning theglobal model, while they ignore the adjustment of aggregation weights andsimply assign weights based on the dataset size. However, based on ourempirical observations and theoretical analysis, we find that the dataset sizeis not optimal and the discrepancy between local and global categorydistributions could be a beneficial and complementary indicator for determiningaggregation weights. We thus propose a novel aggregation method, FederatedLearning with Discrepancy-aware Collaboration (FedDisco), whose aggregationweights not only involve both the dataset size and the discrepancy value, butalso contribute to a tighter theoretical upper bound of the optimization error.FedDisco also promotes privacy-preservation, communication and computationefficiency, as well as modularity. Extensive experiments show that our FedDiscooutperforms several state-of-the-art methods and can be easily incorporatedwith many existing methods to further enhance the performance. Our code will beavailable at https://github.com/MediaBrain-SJTU/FedDisco. <<<

L. F. Johansson, E. N. de Boer, H. A. de Weerd, F. van Dijk, M. G. Elferink, G. H. Schuring-Blom, R. F. Suijkerbuijk, R. J. Sinke, G. J. te Meerman, R. H. Sijmons, M. A. Swertz, B. Sikkema-Raddatz <<<

AbstractNon-invasive prenatal testing (NIPT) of cell-free DNA in maternal plasma, which is a mixture of maternal DNA and a low percentage of fetal DNA, can detect fetal aneuploidies using massively parallel sequencing. Because of the low percentage of fetal DNA, methods with high sensitivity and precision are required. However, sequencing variation lowers sensitivity and hampers detection of trisomy samples. Therefore, we have developed three algorithms to improve sensitivity and specificity: the chi-squared-based variation reduction (χ2VR), the regression-based Z-score (RBZ) and the Match QC score. The χ2VR reduces variability in sequence read counts per chromosome between samples, the RBZ allows for more precise trisomy prediction, and the Match QC score shows if the control group used is representative for a specific sample. We compared the performance of χ2VR to that of existing variation reduction algorithms (peak and GC correction) and that of RBZ to trisomy prediction algorithms (standard Z-score, normalized chromosome value and median-absolute-deviation-based Z-score). χ2VR and the RBZ both reduce variability more than existing methods, and thereby increase the sensitivity of the NIPT analysis. We found the optimal combination of algorithms was to use both GC correction and χ2VR for pre-processing and to use RBZ as the trisomy prediction method. <<<

Jiawang Tao, Zichao Wu, Yanran Liang, Jiongliang Wang, Miaoxiu Tang, Sunan Huang, Fan Jiang, Guangqi Zhou, Lin Guo, Shengxian Yuan, Yinxiong Li, Jie Wang <<<

Background and Aims: Promoting liver regeneration while inhibiting fibrogenesis represented an attractive strategy for treating liver diseases, with hepatic stellate cells (HSCs) being crucial to both processes. This study aimed to identify specific targets in HSCs that simultaneously facilitated regeneration and suppressed fibrosis, and elucidated their molecular mechanisms. Approach and Results: Through comparing acute and chronic liver injury mouse models induced by CCl4 injections, we revealed that HSCs exhibited dual functionality, expressing pro-regenerative and pro-fibrogenic genes following injury. Analyzing RNA-seq data from primary HSCs of these models, along with publicly available single-cell RNA-seq data of HSCs, we identified transcription factor Lhx2, specifically expressed in HSCs, emerged as a potential regulator of the dual functions. Notably, Lhx2 showed significantly higher expression in HSCs from healthy liver tissue compared to fibrotic liver, in both mouse and human models. Lhx2 knockdown impaired liver function recovery and cellular proliferation after acute liver injury. Consistent changes were observed in mice with HSC-specific Lhx2 overexpression. Additionally, Lhx2 overexpression not only promoted hepatocyte proliferation but also exhibited an anti-fibrogenic function after chronic injury. Mechanistically, Lhx2 suppressed multiple functions of activated HSCs, including fibrogenesis, proliferation and migration, and up-regulated SMAD6 to block TGF-β signaling pathway. Moreover, Lhx2 was an upstream regulator of various pro-regenerative factors, especially HGF, which is crucial for liver regeneration. Conclusions: We demonstrated that Lhx2 had pro-regenerative and anti-fibrogenic functions, and elucidated its regulatory mechanism. The study provided a potential target with dual effects for treating liver diseases. <<<

This paper shows that masked autoencoders (MAE) are scalable self-supervisedlearners for computer vision. Our MAE approach is simple: we mask randompatches of the input image and reconstruct the missing pixels. It is based ontwo core designs. First, we develop an asymmetric encoder-decoder architecture,with an encoder that operates only on the visible subset of patches (withoutmask tokens), along with a lightweight decoder that reconstructs the originalimage from the latent representation and mask tokens. Second, we find thatmasking a high proportion of the input image, e.g., 75%, yields a nontrivialand meaningful self-supervisory task. Coupling these two designs enables us totrain large models efficiently and effectively: we accelerate training (by 3xor more) and improve accuracy. Our scalable approach allows for learninghigh-capacity models that generalize well: e.g., a vanilla ViT-Huge modelachieves the best accuracy (87.8%) among methods that use only ImageNet-1Kdata. Transfer performance in downstream tasks outperforms supervisedpre-training and shows promising scaling behavior. <<<

Lovisa Franzén, Martina Olsson Lindvall, Michael Hühn, Victoria Ptasinski, Laura Setyo, Benjamin P. Keith, Astrid Collin, Steven Oag, Thomas Volckaert, Annika Borde, Joakim Lundeberg, Julia Lindgren, Graham Belfield, Sonya Jackson, Anna Ollerstam, Marianna Stamou, Patrik L. Ståhl, Jorrit J. Hornberg <<<

AbstractIdiopathic pulmonary fibrosis (IPF) is a progressive lung disease with poor prognosis and limited treatment options. Efforts to identify effective treatments are thwarted by limited understanding of IPF pathogenesis and poor translatability of available preclinical models. Here we generated spatially resolved transcriptome maps of human IPF (n = 4) and bleomycin-induced mouse pulmonary fibrosis (n = 6) to address these limitations. We uncovered distinct fibrotic niches in the IPF lung, characterized by aberrant alveolar epithelial cells in a microenvironment dominated by transforming growth factor beta signaling alongside predicted regulators, such as TP53 and APOE. We also identified a clear divergence between the arrested alveolar regeneration in the IPF fibrotic niches and the active tissue repair in the acutely fibrotic mouse lung. Our study offers in-depth insights into the IPF transcriptional landscape and proposes alveolar regeneration as a promising therapeutic strategy for IPF. <<<

ABSTRACT Shigella infection poses a significant public health challenge in the developing world. However, lack of a widely available mouse model that replicates human shigellosis creates a major bottleneck to better understanding of disease pathogenesis and development of newer drugs and vaccines. BALB/c mice pre-treated with streptomycin and iron (FeCl 3 ) plus desferrioxamine intraperitoneally followed by oral infection with virulent Shigella flexneri 2a resulted in diarrhea, loss of body weight, bacterial colonization and progressive colitis characterized by disruption of epithelial lining, loss of crypt architecture with goblet cell depletion, increased polymorphonuclear infiltration into the mucosa, submucosal swelling (edema), and raised proinflammatory cytokines and chemokines in the large intestine. To evaluate the usefulness of the model for vaccine efficacy studies, mice were immunized intranasally with a recombinant protein vaccine containing Shigella invasion protein invasion plasmid antigen B (IpaB). Vaccinated mice conferred protection against Shigella , indicating that the model is suitable for testing of vaccine candidates. To protect both Shigella and Salmonella , a chimeric recombinant vaccine (rIpaB–T2544) was developed by fusing IpaB with Salmonella outer membrane protein T2544. Vaccinated mice developed antigen-specific serum IgG and IgA antibodies and a balanced Th1/Th2 response and were protected against oral challenge with Shigella ( S. flexneri 2a , Shigella dysenteriae , and Shigella sonnei ) using our present mouse model and Salmonella ( Salmonella Typhi and Paratyphi) using an iron overload mouse model. We describe here the development of an oral S higella infection model in wild-type mouse. This model was successfully used to demonstrate the immunogenicity and protective efficacy of a candidate protein subunit vaccine against Shigella . <<<

Ting Liu, Jianan Rao, Wenting Hu, Bowen Cui, Jiaoyang Cai, Yuhan Liu, Huiying Sun, Xiaoxiao Chen, Yanjing Tang, Jing Chen, Xiang Wang, Han Wang, Wubin Qian, Binchen Mao, Sheng Guo, Ronghua Wang, Yu Liu, Shuhong Shen <<<

AbstractStudies have revealed key genomic aberrations in pediatric acute myeloid leukemia (AML) based on Western populations. It is unknown to what extent the current genomic findings represent populations with different ethnic backgrounds. Here we present the genomic landscape of driver alterations of Chinese pediatric AML and discover previously undescribed genomic aberrations, including the XPO1-TNRC18 fusion. Comprehensively comparing between the Chinese and Western AML cohorts reveal a substantially distinct genomic alteration profile. For example, Chinese AML patients more commonly exhibit mutations in KIT and CSF3R, and less frequently mutated of genes in the RAS signaling pathway. These differences in mutation frequencies lead to the detection of previously uncharacterized co-occurring mutation pairs. Importantly, the distinct driver profile is clinical relevant. We propose a refined prognosis risk classification model which better reflected the adverse event risk for Chinese AML patients. These results emphasize the importance of genetic background in precision medicine. <<<