The immune system responds to cancer in two main ways. First, there are prewired responses involving myeloid cells, innate lymphocytes and innate-like adaptive lymphocytes that either reside in premalignant tissues or migrate directly to tumours, and second, there are antigen priming-dependent responses, in which adaptive lymphocytes are primed in secondary lymphoid organs before homing to tumours. Transforming growth factor-β (TGFβ) - one of the most potent and pleiotropic regulatory cytokines - controls almost every stage of the tumour-elicited immune response, from leukocyte development in primary lymphoid organs to their priming in secondary lymphoid organs and their effector functions in the tumour itself. The complexity of TGFβ-regulated immune cell circuitries, as well as the contextual roles of TGFβ signalling in cancer cells and tumour stromal cells, necessitates the use of rigorous experimental systems that closely recapitulate human cancer, such as autochthonous tumour models, to uncover the underlying immunobiology. The diverse functions of TGFβ in healthy tissues further complicate the search for effective and safe cancer therapeutics targeting the TGFβ pathway. Here we discuss the contextual complexity of TGFβ signalling in tumour-elicited immune responses and explain how understanding this may guide the development of mechanism-based cancer immunotherapy. <<<

Mash extends the MinHash dimensionality-reduction technique to include a pairwise mutation distance and P value significance test, enabling the efficient clustering and search of massive sequence collections. Mash reduces large sequences and sequence sets to small, representative sketches, from which global mutation distances can be rapidly estimated. We demonstrate several use cases, including the clustering of all 54,118 NCBI RefSeq genomes in 33 CPU h; real-time database search using assembled or unassembled Illumina, Pacific Biosciences, and Oxford Nanopore data; and the scalable clustering of hundreds of metagenomic samples by composition. Mash is freely released under a BSD license ( https://github.com/marbl/mash ). <<<

Importance: Childhood poverty has been associated with increased internalizing and externalizing problems in adolescence, a period of peak onset for psychiatric problems. The underlying neural mechanisms remain unclear because longitudinal studies of poverty, brain structure, and changes in psychiatric symptoms are lacking.Objective: To examine whether structural differences in cortical regions mediate the association between household poverty and change in psychiatric symptoms in early adolescence.Design, Setting, and Participants: This longitudinal cohort study used baseline and 1-year follow-up data from the Adolescent Brain Cognitive Development Study. Children aged 9 to 10 years in the US were enrolled between September 1, 2016, and October 15, 2018. Data analysis was performed from August 13, 2021, to September 30, 2022.Exposures: Household poverty as measured by income-to-needs ratio, which incorporates family income and adjusts for family size as a percentage of the federal poverty level.Main Outcomes and Measures: Mediators were children's cortical surface area, thickness, and volume, obtained using magnetic resonance imaging. Internalizing and externalizing problems at 1-year follow-up were outcomes measured by maternal report using the Child Behavior Checklist. Analyses were adjusted for baseline psychiatric problems and sociodemographic variables, including sex, race and ethnicity, parental educational level, and study site.Results: Of the 7569 children (mean [SD] age, 9.91 [0.62] years; 3970 boys [52.5%]) included in the analysis, 1042 children (13.8%) lived below the poverty threshold between 2016 and 2018. Poverty was associated with increased externalizing symptoms score at 1-year follow-up (b = 1.57; 95% CI, 1.14-1.99), even after adjustment for baseline externalizing symptoms (b = 0.35; 95% CI, 0.06-0.64). The longitudinal associations of poverty with increases in externalizing problems over time were mediated by reductions in surface area in multiple cortical regions that support executive functioning (middle frontal gyrus), decision-making (lateral orbitofrontal cortex), visual processing (fusiform gyrus), auditory processing (transverse temporal gyrus), and emotion and language processing (superior temporal gyrus).Conclusions and Relevance: The findings of this study suggest that childhood poverty is associated with increases in externalizing problems, but not internalizing problems, over time in early adolescence. This association is mediated by reductions in cortical surface area across numerous brain regions. These findings highlight potential neurobiological mechanisms underlying the link between poverty and the emergence of externalizing problems during early adolescence. <<<

Mark Schmitt, Fatih Ceteci, Jalaj Gupta, Marina Pesic, Tim W Böttger, Adele M Nicolas, Kilian B Kennel, Esther Engel, Matthias Schewe, Asude Callak Kirisözü, Valentina Petrocelli, Yasamin Dabiri, Julia Varga, Mallika Ramakrishnan, Madina Karimova, Andrea Ablasser, Toshiro Sato, Melek C Arkan, Frederic J de Sauvage, Florian R Greten <<<

Solid cancers exhibit a dynamic balance between cell death and proliferation ensuring continuous tumour maintenance and growth. Increasing evidence links enhanced cancer cell apoptosis to paracrine activation of cells in the tumour microenvironment initiating tissue repair programs that support tumour growth, yet the direct effects of dying cancer cells on neighbouring tumour epithelia and how this paracrine effect potentially contributes to therapy resistance are unclear. Here we demonstrate that chemotherapy-induced tumour cell death in patient-derived colorectal tumour organoids causes ATP release triggering P2X4 (also known as P2RX4) to mediate an mTOR-dependent pro-survival program in neighbouring cancer cells, which renders surviving tumour epithelia sensitive to mTOR inhibition. The induced mTOR addiction in persisting epithelial cells is due to elevated production of reactive oxygen species and subsequent increased DNA damage in response to the death of neighbouring cells. Accordingly, inhibition of the P2X4 receptor or direct mTOR blockade prevents induction of S6 phosphorylation and synergizes with chemotherapy to cause massive cell death induced by reactive oxygen species and marked tumour regression that is not seen when individually applied. Conversely, scavenging of reactive oxygen species prevents cancer cells from becoming reliant on mTOR activation. Collectively, our findings show that dying cancer cells establish a new dependency on anti-apoptotic programs in their surviving neighbours, thereby creating an opportunity for combination therapy in P2X4-expressing epithelial tumours. <<<

Braydon Meyer, Samuel Clifton, Warwick Locke, Phuc-Loi Luu, Qian Du, Dilys Lam, Nicola J Armstrong, Beena Kumar, Niantao Deng, Kate Harvey, Alex Swarbrick, Vinod Ganju, Susan J Clark, Ruth Pidsley, Clare Stirzaker <<<

Neoadjuvant chemotherapy (NAC) is used to treat triple-negative breast cancer (TNBC) prior to resection. Biomarkers that accurately predict a patient's response to NAC are needed to individualise therapy and avoid chemotoxicity from unnecessary chemotherapy. We performed whole-genome DNA methylation profiling on diagnostic TNBC biopsy samples from the Sequential Evaluation of Tumours Undergoing Preoperative (SETUP) NAC study. We found 9 significantly differentially methylated regions (DMRs) at diagnosis which were associated with response to NAC. We show that 4 of these DMRs are associated with TNBC overall survival (P < 0.05). Our results highlight the potential of DNA methylation biomarkers for predicting NAC response in TNBC. <<<

β-Galactosidases catalyze the hydrolysis of β(1-3) and β(1-4) galactosyl bonds in oligosaccharides as well as the inverse reaction of enzymatic condensation and transglycosylation. Here we report the crystallographic structures of Penicillium sp. β-galactosidase and its complex with galactose solved by the SIRAS quick cryo-soaking technique at 1.90 Å and 2.10 Å resolution, respectively. The amino acid sequence of this 120 kDa protein was first assigned putatively on the basis of inspection of the experimental electron density maps and then determined by nucleotide sequence analysis. Primary structure alignments reveal that Penicillium sp. β-galactosidase belongs to family 35 of glycosyl hydrolases (GHF-35). This model is the first 3D structure for a member of GHF-35. Five distinct domains which comprise the structure are assembled in a way previously unobserved for β-galactosidases. Superposition of this complex with other β-galactosidase complexes from several hydrolase families allowed the identification of residue Glu200 as the proton donor and residue Glu299 as the nucleophile involved in catalysis. Penicillium sp. β-galactosidase is a glycoprotein containing seven N-linked oligosaccharide chains and is the only structure of a glycosylated β-galactosidase described to date. <<<

Several lipogenic genes have been shown to have effects on lipid metabolism: stearoyl CoA desaturase 1 (SCD1) catalyzes the desaturation of several fatty acids (FA) in the cis-Delta(9) position in mammary glands of ruminant animals, diacylglycerol acyltransferase 1 (DGAT1) is a key enzyme in triacylglycerol synthesis in the mammary gland, and sterol regulatory element binding protein (SREBP-1) is a transcription factor that regulates expression levels of the SCD1 gene and other genes relevant to lipid and FA metabolism in adipose tissue and mammary gland. In this work, 351 Italian Brown cows were genotyped for polymorphisms in the SCD1, SREBP-1, and DGAT1 genes to reveal the allelic distribution in the population. Subsequently, effects on individual milk FA composition and on cis-9 unsaturated/saturated FA ratios, a proxy of mammary stearoyl CoA desaturase activity, were investigated. The genotypes of SCD1 (A293V) and DGAT1 (K232A) were determined by an approach based on the ligation detection reaction and a universal array, whereas the genotype of SREBP-1 (84-bp insertion-deletion) was revealed by PCR amplification of intron 5. The genotype analysis showed an unbalanced distribution of alleles within all genes, being the allele with higher gene frequency at 82, 84, and 98% for SCD1, SREBP-1, and DGAT1, respectively. Significant associations between SCD1 and DGAT1 polymorphisms and milk FA composition were found, whereas SREBP-1 polymorphism was not associated with milk FA composition. In particular, SCD1 showed significant association with C14:1 cis-9 and C14:1 cis-9/C14:0, which is considered the best proxy of the desaturation activity in mammary gland. The DGAT1 polymorphism had the strongest association with milk FA composition, which confirmed the key role of DGAT1 in lipid metabolism of mammary gland. However, the unbalanced distribution of alleles in all polymorphisms investigated suggested that the size of population should be increased to confirm the results of the present study. <<<

This paper introduces Quicksilver, a fast deformable image registration method. Quicksilver registration for image-pairs works by patch-wise prediction of a deformation model based directly on image appearance. A deep encoder-decoder network is used as the prediction model. While the prediction strategy is general, we focus on predictions for the Large Deformation Diffeomorphic Metric Mapping (LDDMM) model. Specifically, we predict the momentum-parameterization of LDDMM, which facilitates a patch-wise prediction strategy while maintaining the theoretical properties of LDDMM, such as guaranteed diffeomorphic mappings for sufficiently strong regularization. We also provide a probabilistic version of our prediction network which can be sampled during the testing time to calculate uncertainties in the predicted deformations. Finally, we introduce a new correction network which greatly increases the prediction accuracy of an already existing prediction network. We show experimental results for uni-modal atlas-to-image as well as uni-/multi-modal image-to-image registrations. These experiments demonstrate that our method accurately predicts registrations obtained by numerical optimization, is very fast, achieves state-of-the-art registration results on four standard validation datasets, and can jointly learn an image similarity measure. Quicksilver is freely available as an open-source software. <<<

Episodic memory enables humans to encode and later vividly retrieve information about our rich experiences, yet the neural representations that support this mental capacity are poorly understood. Using a large fMRI dataset ( = 468) of face-name associative memory tasks and principal component analysis to examine neural representational dimensionality (RD), we found that the human brain maintained a high-dimensional representation of faces through hierarchical representation within and beyond the face-selective regions. Critically, greater RD was associated with better subsequent memory performance both within and across participants, and this association was specific to episodic memory but not general cognitive abilities. Furthermore, the frontoparietal activities could suppress the shared low-dimensional fluctuations and reduce the correlations of local neural responses, resulting in greater RD. RD was not associated with the degree of item-specific pattern similarity, and it made complementary contributions to episodic memory. These results provide a mechanistic understanding of the role of RD in supporting accurate episodic memory. <<<

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale. Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter; identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation; analyses timings and patterns of tumour evolution; describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity; and evaluates a range of more-specialized features of cancer genomes. <<<

Longitudinal fetal brain atlas is a powerful tool for understanding and characterizing the complex process of fetus brain development. Existing fetus brain atlases are typically constructed by averaged brain images on discrete time points independently over time. Due to the differences in onto-genetic trends among samples at different time points, the resulting atlases suffer from temporal inconsistency, which may lead to estimating error of the brain developmental characteristic parameters along the timeline. To this end, we proposed a multi-stage deep-learning framework to tackle the time inconsistency issue as a 4D (3D brain volume + 1D age) image data denoising task. Using implicit neural representation, we construct a continuous and noise-free longitudinal fetus brain atlas as a function of the 4D spatial-temporal coordinate. Experimental results on two public fetal brain atlases (CRL and FBA-Chinese atlases) show that the proposed method can significantly improve the atlas temporal consistency while maintaining good fetus brain structure representation. In addition, the continuous longitudinal fetus brain atlases can also be extensively applied to generate finer 4D atlases in both spatial and temporal resolution. <<<

Predicting the future motion of road agents is a critical task in an autonomous driving pipeline. In this work, we address the problem of generating a set of scene-level, or joint, future trajectory predictions in multi-agent driving scenarios. To this end, we propose FJMP, a Factorized Joint Motion Prediction framework for multi-agent interactive driving scenarios. FJMP models the future scene interaction dynamics as a sparse directed interaction graph, where edges denote explicit interactions between agents. We then prune the graph into a directed acyclic graph (DAG) and decompose the joint prediction task into a sequence of marginal and conditional predictions according to the partial ordering of the DAG, where joint future trajectories are decoded using a directed acyclic graph neural network (DAGNN). We conduct experiments on the INTERACTION and Argoverse 2 datasets and demonstrate that FJMP produces more accurate and scene-consistent joint trajectory predictions than non-factorized approaches, especially on the most interactive and kinematically interesting agents. FJMP ranks 1st on the multi-agent test leaderboard of the INTERACTION dataset. <<<

Following a key developmental task of childhood-building a foundation of self-knowledge in the form of domain-specific self-concepts-adolescents begin to explore their emerging identities in ways that foster autonomy and connectedness. Neuroimaging studies of self-related processes demonstrate enhanced engagement of the ventromedial prefrontal cortex in adolescence, which may facilitate and reflect the development of identity by integrating the value of potential actions and choices. Drawing from neuroeconomic and social cognitive accounts, we propose that motivated behavior during adolescence can be modeled by a general value-based decision-making process centered around value accumulation in the ventromedial prefrontal cortex. This approach advances models of adolescent neurodevelopment that focus on reward sensitivity and cognitive control by considering more diverse value inputs, including contributions of developing self- and identity-related processes. It also considers adolescent decision making and behavior from adolescents' point of view rather than adults' perspectives on what adolescents should value or how they should behave. <<<

How could machines learn as efficiently as humans and animals? How could machines learn to reason and plan? How could machines learn representations of percepts and action plans at multiple levels of abstraction, enabling them to reason, predict, and plan at multiple time horizons? This position paper proposes an architecture and training paradigms with which to construct autonomous intelligent agents. It combines concepts such as configurable predictive world model, behavior driven through intrinsic motivation, and hierarchical joint embedding architectures trained with self-supervised learning. <<<

Yongcai Huang, Haihai Wang, Yidong Zhu, Xing Huang, Shuai Li, Xingguo Wu, Yao Zhao, Zhigui Bao, Li Qin, Yongbo Jin, Yahui Cui, Guangjin Ma, Qiao Xiao, Qiong Wang, Jiechen Wang, Xuerong Yang, Hongjun Liu, Xiaoduo Lu, Brian A Larkins, Wenqin Wang, Yongrui Wu <<<

Teosinte, the wild ancestor of maize (Zea mays subsp. mays), has three times the seed protein content of most modern inbreds and hybrids, but the mechanisms that are responsible for this trait are unknown. Here we use trio binning to create a contiguous haplotype DNA sequence of a teosinte (Zea mays subsp. parviglumis) and, through map-based cloning, identify a major high-protein quantitative trait locus, TEOSINTE HIGH PROTEIN 9 (THP9), on chromosome 9. THP9 encodes an asparagine synthetase 4 enzyme that is highly expressed in teosinte, but not in the B73 inbred, in which a deletion in the tenth intron of THP9-B73 causes incorrect splicing of THP9-B73 transcripts. Transgenic expression of THP9-teosinte in B73 significantly increased the seed protein content. Introgression of THP9-teosinte into modern maize inbreds and hybrids greatly enhanced the accumulation of free amino acids, especially asparagine, throughout the plant, and increased seed protein content without affecting yield. THP9-teosinte seems to increase nitrogen-use efficiency, which is important for promoting a high yield under low-nitrogen conditions. <<<

Differential expression (DE) analysis and gene set enrichment (GSE) analysis are commonly applied in single cell RNA sequencing (scRNA-seq) studies. Here, we develop an integrative and scalable computational method, iDEA, to perform joint DE and GSE analysis through a hierarchical Bayesian framework. By integrating DE and GSE analyses, iDEA can improve the power and consistency of DE analysis and the accuracy of GSE analysis. Importantly, iDEA uses only DE summary statistics as input, enabling effective data modeling through complementing and pairing with various existing DE methods. We illustrate the benefits of iDEA with extensive simulations. We also apply iDEA to analyze three scRNA-seq data sets, where iDEA achieves up to five-fold power gain over existing GSE methods and up to 64% power gain over existing DE methods. The power gain brought by iDEA allows us to identify many pathways that would not be identified by existing approaches in these data. <<<

Shaohua Hu, Hao Xu, Xiaohua Meng, Xiangxiang Bai, Junli Xu, Jinru Ji, Chaoqun Ying, Yunbo Chen, Ping Shen, Yunxiao Zhou, Beiwen Zheng, Yonghong Xiao <<<

is an emerging species and has increasingly been reported to cause life-threatening infections and even outbreaks in humans. Nevertheless, there is little data regarding the geographical distribution, phylogenetic structure, and transmission across the globe, especially in Asia. We utilize whole-genome sequencing (WGS) data to define a global population framework, phylogenetic structure, geographical distribution, and transmission evaluation of pathogens. The geographical distribution diagram revealed the emerging pathogenic bacteria already distributed in various countries worldwide, especially in the USA and China. Strikingly, phylogenetic analysis showed a part of our China original shared the same ancestor with the USA outbreak strain, which implies the possibility of localized outbreaks and global spread. These closer related strains also contained ICEEaI, which might insert into a disrupted DNA repair gene and made the strain more liable to mutation and outbreak infection. BEAST analysis showed that the most recent common ancestor for ICEEaI was dated twelve years ago, and China might be the most likely recent source of this bacteria. Our study sheds light on the potential possibility of causing the large-scale outbreak and rapid global dissemination. Continued genomic surveillance of the dynamics of populations will generate further knowledge for optimizing future prevent global outbreak infections. <<<

Maria Hurskainen, Ivana Mižíková, David P Cook, Noora Andersson, Chanèle Cyr-Depauw, Flore Lesage, Emmi Helle, Laurent Renesme, Robert P Jankov, Markku Heikinheimo, Barbara C Vanderhyden, Bernard Thébaud <<<

During late lung development, alveolar and microvascular development is finalized to enable sufficient gas exchange. Impaired late lung development manifests as bronchopulmonary dysplasia (BPD) in preterm infants. Single-cell RNA sequencing (scRNA-seq) allows for assessment of complex cellular dynamics during biological processes, such as development. Here, we use MULTI-seq to generate scRNA-seq profiles of over 66,000 cells from 36 mice during normal or impaired lung development secondary to hyperoxia with validation of some of the findings in lungs from BPD patients. We observe dynamic populations of cells, including several rare cell types and putative progenitors. Hyperoxia exposure, which mimics the BPD phenotype, alters the composition of all cellular compartments, particularly alveolar epithelium, stromal fibroblasts, capillary endothelium and macrophage populations. Pathway analysis and predicted dynamic cellular crosstalk suggest inflammatory signaling as the main driver of hyperoxia-induced changes. Our data provides a single-cell view of cellular changes associated with late lung development in health and disease. <<<

Joseph M. Replogle , Reuben A. Saunders , Angela N. Pogson , Jeffrey A. Hussmann , Alexander Lenail , Alina Guna , Lauren Mascibroda , Eric J. Wagner , Karen Adelman , Gila Lithwick-Yanai , Nika Iremadze , Florian Oberstrass , Doron Lipson , Jessica L. Bonnar , Marco Jost , Thomas M. Norman , Jonathan S. Weissman <<<

A central goal of genetics is to define the relationships between genotypes and phenotypes. High-content phenotypic screens such as Perturb-seq (CRISPR-based screens with single-cell RNA-sequencing readouts) enable massively parallel functional genomic mapping but, to date, have been used at limited scales. Here, we perform genome-scale Perturb-seq targeting all expressed genes with CRISPR interference (CRISPRi) across >2.5 million human cells. We use transcriptional phenotypes to predict the function of poorly characterized genes, uncovering new regulators of ribosome biogenesis (including CCDC86, ZNF236, and SPATA5L1), transcription (C7orf26), and mitochondrial respiration (TMEM242). In addition to assigning gene function, single-cell transcriptional phenotypes allow for in-depth dissection of complex cellular phenomena—from RNA processing to differentiation. We leverage this ability to systematically identify genetic drivers and consequences of aneuploidy and to discover an unanticipated layer of stress-specific regulation of the mitochondrial genome. Our information-rich genotype-phenotype map reveals a multidimensional portrait of gene and cellular function. <<<

Arash Jamshidi, Minetta C Liu, Eric A Klein, Oliver Venn, Earl Hubbell, John F Beausang, Samuel Gross, Collin Melton, Alexander P Fields, Qinwen Liu, Nan Zhang, Eric T Fung, Kathryn N Kurtzman, Hamed Amini, Craig Betts, Daniel Civello, Peter Freese, Robert Calef, Konstantin Davydov, Saniya Fayzullina, Chenlu Hou, Roger Jiang, Byoungsok Jung, Susan Tang, Vasiliki Demas, Joshua Newman, Onur Sakarya, Eric Scott, Archana Shenoy, Seyedmehdi Shojaee, Kristan K Steffen, Virgil Nicula, Tom C Chien, Siddhartha Bagaria, Nathan Hunkapiller, Mohini Desai, Zhao Dong, Donald A Richards, Timothy J Yeatman, Allen L Cohn, David D Thiel, Donald A Berry, Mohan K Tummala, Kristi McIntyre, Mikkael A Sekeres, Alan Bryce, Alexander M Aravanis, Michael V Seiden, Charles Swanton <<<

In the Circulating Cell-free Genome Atlas (NCT02889978) substudy 1, we evaluate several approaches for a circulating cell-free DNA (cfDNA)-based multi-cancer early detection (MCED) test by defining clinical limit of detection (LOD) based on circulating tumor allele fraction (cTAF), enabling performance comparisons. Among 10 machine-learning classifiers trained on the same samples and independently validated, when evaluated at 98% specificity, those using whole-genome (WG) methylation, single nucleotide variants with paired white blood cell background removal, and combined scores from classifiers evaluated in this study show the highest cancer signal detection sensitivities. Compared with clinical stage and tumor type, cTAF is a more significant predictor of classifier performance and may more closely reflect tumor biology. Clinical LODs mirror relative sensitivities for all approaches. The WG methylation feature best predicts cancer signal origin. WG methylation is the most promising technology for MCED and informs development of a targeted methylation MCED test. <<<