Living organisms can produce corresponding functions by responding to external and internal stimuli, and this irritability plays a pivotal role in nature. Inspired by such natural temporal responses, the development and design of nanodevices with the ability to process time-related information could facilitate the development of molecular information processing systems. Here, we proposed a DNA finite-state machine that can dynamically respond to sequential stimuli signals. To build this state machine, a programmable allosteric strategy of DNAzyme was developed. This strategy performs the programmable control of DNAzyme conformation using a reconfigurable DNA hairpin. Based on this strategy, we first implemented a finite-state machine with two states. Through the modular design of the strategy, we further realized the finite-state machine with five states. The DNA finite-state machine endows molecular information systems with the ability of reversible logic control and order detection, which can be extended to more complex DNA computing and nanomachines to promote the development of dynamic nanotechnology. <<<

Neutering (including spaying) of male and female dogs in the first year after birth has become routine in the U.S. and much of Europe, but recent research reveals that for some dog breeds, neutering may be associated with increased risks of debilitating joint disorders and some cancers, complicating pet owners' decisions on neutering. The joint disorders include hip dysplasia, cranial cruciate ligament tear or rupture, and elbow dysplasia. The cancers include lymphoma, mast cell tumor, hemangiosarcoma, and osteosarcoma. In previous studies on the Golden Retriever, Labrador Retriever and German Shepherd Dog, neutering before a year of age was associated with increased risks of one or more joint disorders, 2-4 times that of intact dogs. The increase was particularly seen with dogs neutered by 6 months of age. In female Golden Retrievers, there was an increase in one or more of the cancers followed to about 2-4 times that of intact females with neutering at any age. The goal of the present study was to expand and use the same data collection and analyses to cover an additional 29 breeds, plus three varieties of Poodles. There were major breed differences in vulnerability to neutering, both with regard to joint disorders and cancers. In most cases, the caregiver can choose the age of neutering without increasing the risks of these joint disorders or cancers. Small-dog breeds seemed to have no increased risks of joint disorders associated with neutering, and in only two small breeds (Boston Terrier and Shih Tzu) was there a significant increase in cancers. To assist pet owners and veterinarians in deciding on the age of neutering a specific dog, guidelines that avoid increasing the risks of a dog acquiring these joint disorders or cancers are laid out for neutering ages on a breed-by-breed and sex basis. <<<

ChIP-seq is a powerful method for obtaining genome-wide maps of protein-DNA interactions and epigenetic modifications. CHANCE (CHip-seq ANalytics and Confidence Estimation) is a standalone package for ChIP-seq quality control and protocol optimization. Our user-friendly graphical software quickly estimates the strength and quality of immunoprecipitations, identifies biases, compares the user's data with ENCODE's large collection of published datasets, performs multi-sample normalization, checks against quantitative PCR-validated control regions, and produces informative graphical reports. CHANCE is available at https://github.com/songlab/chance. <<<

Nicholas McGranahan, Rachel Rosenthal, Crispin T Hiley, Andrew J Rowan, Thomas B K Watkins, Gareth A Wilson, Nicolai J Birkbak, Selvaraju Veeriah, Peter Van Loo, Javier Herrero, Charles Swanton, TRACERx Consortium <<<

Immune evasion is a hallmark of cancer. Losing the ability to present neoantigens through human leukocyte antigen (HLA) loss may facilitate immune evasion. However, the polymorphic nature of the locus has precluded accurate HLA copy-number analysis. Here, we present loss of heterozygosity in human leukocyte antigen (LOHHLA), a computational tool to determine HLA allele-specific copy number from sequencing data. Using LOHHLA, we find that HLA LOH occurs in 40% of non-small-cell lung cancers (NSCLCs) and is associated with a high subclonal neoantigen burden, APOBEC-mediated mutagenesis, upregulation of cytolytic activity, and PD-L1 positivity. The focal nature of HLA LOH alterations, their subclonal frequencies, enrichment in metastatic sites, and occurrence as parallel events suggests that HLA LOH is an immune escape mechanism that is subject to strong microenvironmental selection pressures later in tumor evolution. Characterizing HLA LOH with LOHHLA refines neoantigen prediction and may have implications for our understanding of resistance mechanisms and immunotherapeutic approaches targeting neoantigens. VIDEO ABSTRACT. <<<

Luis R Lopes, Soledad Garcia-Hernández, Massimiliano Lorenzini, Marta Futema, Olga Chumakova, Dmitry Zateyshchikov, Maria Isidoro-Garcia, Eduardo Villacorta, Luis Escobar-Lopez, Pablo Garcia-Pavia, Raquel Bilbao, David Dobarro, Maria Sandin-Fuentes, Claudio Catalli, Blanca Gener Querol, Ainhoa Mezcua, Jose Garcia Pinilla, Torsten Bloch Rasmussen, Ana Ferreira-Aguar, Pablo Revilla-Martí, Maria Teresa Basurte Elorz, Alicia Bautista Paves, Juan Ramon Gimeno, Ana Virginia Figueroa, Raul Franco-Gutierrez, Maria Eugenia Fuentes-Cañamero, Marina Martinez Moreno, Martin Ortiz-Genga, Jesus Piqueras-Flores, Karina Analia Ramos, Ainars Rudzitis, Luis Ruiz-Guerrero, Ricardo Stein, Mayte Triguero-Bocharán, Luis de la Higuera, Juan Pablo Ochoa, Dad Abu-Bonsrah, Cecilia Y T Kwok, Jacob B Smith, Enzo R Porrello, Mohammed M Akhtar, Joanna Jager, Michael Ashworth, Petros Syrris, David A Elliott, Lorenzo Monserrat, Perry M Elliott <<<

AIMS: The aim of this study was to determine the frequency of heterozygous truncating ALPK3 variants (ALPK3tv) in patients with hypertrophic cardiomyopathy (HCM) and confirm their pathogenicity using burden testing in independent cohorts and family co-segregation studies.METHODS AND RESULTS: In a discovery cohort of 770 index patients with HCM, 12 (1.56%) were heterozygous for ALPK3tv [odds ratio(OR) 16.11, 95% confidence interval (CI) 7.94-30.02, P = 8.05e-11] compared to the Genome Aggregation Database (gnomAD) population. In a validation cohort of 2047 HCM probands, 32 (1.56%) carried heterozygous ALPK3tv (OR 16.17, 95% CI 10.31-24.87, P < 2.2e-16, compared to gnomAD). Combined logarithm of odds score in seven families with ALPK3tv was 2.99. In comparison with a cohort of genotyped patients with HCM (n = 1679) with and without pathogenic sarcomere gene variants (SP+ and SP-), ALPK3tv carriers had a higher prevalence of apical/concentric patterns of hypertrophy (60%, P < 0.001) and of a short PR interval (10%, P = 0.009). Age at diagnosis and maximum left ventricular wall thickness were similar to SP- and left ventricular systolic impairment (6%) and non-sustained ventricular tachycardia (31%) at baseline similar to SP+. After 5.3 ± 5.7 years, 4 (9%) patients with ALPK3tv died of heart failure or had cardiac transplantation (log-rank P = 0.012 vs. SP- and P = 0.425 vs. SP+). Imaging and histopathology showed extensive myocardial fibrosis and myocyte vacuolation.CONCLUSIONS: Heterozygous ALPK3tv are pathogenic and segregate with a characteristic HCM phenotype. <<<

Recent visual question answering (VQA) frameworks employ different combinations of attention techniques to derive a correct answer. Attention techniques in vision-language tasks have mostly achieved success through the improvement of local features for both modalities. Attention as a concept is heavily established by human cognition mechanism. Different combinations of attention techniques are not well proven as a means of human cognition. Neural networks were originally inspired by the structure of the human brain. Many researchers have recently resorted to frameworks that resemble the human brain, and their models have achieved high performance. To this end, we aim to consider a framework that utilizes human biological and psychological concepts to achieve a good understanding of vision and language modalities. In this view, we introduce a hierarchical reasoning based on a perception action cycle (HIPA) framework to tackle VQA tasks. It integrates the reasoning process of multi-modalities with the perception action cycle (PAC), which explains the learning mechanism of humans about the surrounding world. It comprehends the visual modality through three phases of reasoning: object-level attention, organization, and interpretation. It comprehends the language modality through word-level attention, interpretation, and conditioning. Subsequently, vision and language modalities are interpreted dependently in a cyclic and hierarchical way throughout the entire framework. For further assessment of the visual and language features, we argue that image-question pairs of the same answer ought to have similar visual and language features eventually. As a result, we conduct visual and language feature evaluation experiments using metrics such as standard deviation of cosine similarity and Manhattan distance. We show that employing PAC in our framework improves the standard deviation compared with other VQA frameworks. For further assessment, we also test the novel proposed HIPA on the visual relationship detection (VRD) tasks. The proposed method achieves the state-of-the-art results on the TDIUC and VRD datasets and obtains competitive results on the VQA 2.0 dataset. <<<

Neural-symbolic computing (NeSy), which pursues the integration of the symbolic and statistical paradigms of cognition, has been an active research area of Artificial Intelligence (AI) for many years. As NeSy shows promise of reconciling the advantages of reasoning and interpretability of symbolic representation and robust learning in neural networks, it may serve as a catalyst for the next generation of AI. In the present paper, we provide a systematic overview of the important and recent developments of research on NeSy AI. Firstly, we introduce study history of this area, covering early work and foundations. We further discuss background concepts and identify key driving factors behind the development of NeSy. Afterward, we categorize recent landmark approaches along several main characteristics that underline this research paradigm, including neural-symbolic integration, knowledge representation, knowledge embedding, and functionality. Then, we briefly discuss the successful application of modern NeSy approaches in several domains. Finally, we identify the open problems together with potential future research directions. This survey is expected to help new researchers enter this rapidly-developing field and accelerate progress towards data-and knowledge-driven AI. <<<

The tumor microenvironment is a dynamic cellular milieu that interacts with cancer cells and promotes tumor progression and metastasis. However, the specific mechanisms by which the tumor microenvironment impacts cancer cells' behaviors remain poorly understood. In this study, enriched cancer-associated fibroblasts (CAFs) were observed in tumor tissues isolated from epidermal growth factor receptor tyrosine kinase inhibitors (EGFR TKIs) resistant non-small cell lung cancer (NSCLC) patients. CAFs isolated from tumor tissues were capable of producing tryptophan metabolite kynurenine (Kyn), which significantly increased the proliferation and EGFR TKIs resistance of NSCLC cells. In this study, it was further observed that the activation of tryptophan 2,3-dioxygenase (TDO) in CAFs, resulted in the enhanced capability of tryptophan metabolism in them compared to normal fibroblasts. As a result, Kyn produced by CAFs facilitated the up-regulation of Aryl Hydrocarbon Receptor (AhR) signals in NSCLC, thereby resulting in the downstream ATK and ERK signaling pathways activation. Finally, inhibition of AhR signals efficiently prevented tumor growth and development of EGFR TKIs resistance, eventually improved the outcome of EGFR TKIs, and described a promising therapeutic strategy for NSCLC. <<<

The medial (MEC) and lateral entorhinal cortex (LEC), widely studied in rodents, are well defined and characterized. In humans, however, the exact locations of their homologues remain uncertain. Previous functional magnetic resonance imaging (fMRI) studies have subdivided the human EC into posteromedial (pmEC) and anterolateral (alEC) parts, but uncertainty remains about the choice of imaging modality and seed regions, in particular in light of a substantial revision of the classical model of EC connectivity based on novel insights from rodent anatomy. Here, we used structural, not functional imaging, namely diffusion tensor imaging (DTI) and probabilistic tractography to segment the human EC based on differential connectivity to other brain regions known to project selectively to MEC or LEC. We defined MEC as more strongly connected with presubiculum and retrosplenial cortex (RSC), and LEC as more strongly connected with distal CA1 and proximal subiculum (dCA1pSub) and lateral orbitofrontal cortex (OFC). Although our DTI segmentation had a larger medial-lateral component than in the previous fMRI studies, our results show that the human MEC and LEC homologues have a border oriented both towards the posterior-anterior and medial-lateral axes, supporting the differentiation between pmEC and alEC. <<<

Image compression is a fundamental research field and many well-known compression standards have been developed for many decades. Recently, learned compression methods exhibit a fast development trend with promising results. However, there is still a performance gap between learned compression algorithms and reigning compression standards, especially in terms of widely used PSNR metric. In this paper, we explore the remaining redundancy of recent learned compression algorithms. We have found accurate entropy models for rate estimation largely affect the optimization of network parameters and thus affect the rate-distortion performance. Therefore, in this paper, we propose to use discretized Gaussian Mixture Likelihoods to parameterize the distributions of latent codes, which can achieve a more accurate and flexible entropy model. Besides, we take advantage of recent attention modules and incorporate them into network architecture to enhance the performance. Experimental results demonstrate our proposed method achieves a state-of-the-art performance compared to existing learned compression methods on both Kodak and high-resolution datasets. To our knowledge our approach is the first work to achieve comparable performance with latest compression standard Versatile Video Coding (VVC) regarding PSNR. More importantly, our approach generates more visually pleasant results when optimized by MS-SSIM. This project page is at this https URL this https URL <<<

Brain atlases are spatial references for integrating, processing, and analyzing brain features gathered from different individuals, sources, and scales. Here we introduce a collection of joint surface-volume atlases that chart postnatal development of the human brain in a spatiotemporally dense manner from two weeks to two years of age. Our month-specific atlases chart normative patterns and capture key traits of early brain development and are therefore conducive to identifying aberrations from normal developmental trajectories. These atlases will enhance our understanding of early structural and functional development by facilitating the mapping of diverse features of the infant brain to a common reference frame for precise multifaceted quantification of cortical and subcortical changes. <<<

Jimin Tan, Nina Shenker-Tauris, Javier Rodriguez-Hernaez, Eric Wang, Theodore Sakellaropoulos, Francesco Boccalatte, Palaniraja Thandapani, Jane Skok, Iannis Aifantis, David Fenyö, Bo Xia, Aristotelis Tsirigos <<<

Investigating how chromatin organization determines cell-type-specific gene expression remains challenging. Experimental methods for measuring three-dimensional chromatin organization, such as Hi-C, are costly and have technical limitations, restricting their broad application particularly in high-throughput genetic perturbations. We present C.Origami, a multimodal deep neural network that performs de novo prediction of cell-type-specific chromatin organization using DNA sequence and two cell-type-specific genomic features-CTCF binding and chromatin accessibility. C.Origami enables in silico experiments to examine the impact of genetic changes on chromatin interactions. We further developed an in silico genetic screening approach to assess how individual DNA elements may contribute to chromatin organization and to identify putative cell-type-specific trans-acting regulators that collectively determine chromatin architecture. Applying this approach to leukemia cells and normal T cells, we demonstrate that cell-type-specific in silico genetic screening, enabled by C.Origami, can be used to systematically discover novel chromatin regulation circuits in both normal and disease-related biological systems. <<<

Although the quantitative trait locus (QTL) on chromosome 18 (BTA18) associated with paternal calving ease and stillbirth in Holstein Friesian cattle and its cross has been known for over 20 years, to our knowledge, the exact causal genetic sequence has yet escaped identification. The aim of this study was to re-examine the region of the published QTL on BTA18 and to investigate the possible reasons behind this elusiveness. For this purpose, we carried out a combined linkage disequilibrium and linkage analysis using genotyping data of 2,697 German Holstein Friesian (HF) animals and subsequent whole-genome sequencing (WGS) data analyses and genome assembly of HF samples. We confirmed the known QTL in the 95% confidence interval of 1.089 Mbp between 58.34 and 59.43 Mbp on BTA18. Additionally, these 4 SNPs in the near-perfect linkage disequilibrium with the QTL haplotype were identified: rs381577268 (on 57,816,137 bp, C/T), rs381878735 (on 59,574,329 bp, A/T), rs464221818 (on 59,329,176 bp, C/T), and rs472502785 (on 59,345,689 bp, T/C). Search for the causal mutation using short and long-read sequences, and methylation data of the BTA18 QTL region did not reveal any candidates though. The assembly showed problems in the region, as well as an abundance of segmental duplications within and around the region. Taking the QTL of BTA18 in Holstein cattle as an example, the data presented in this study comprehensively characterize the genomic features that could also be relevant for other such elusive QTL in various other cattle breeds and livestock species as well. <<<

Three distinct neurodevelopmental disorders arise primarily from deletions or duplications that occur at the 15q11-q13 locus: Prader-Willi syndrome, Angelman syndrome, and 15q11-q13 duplication syndrome. Each of these disorders results from the loss of function or overexpression of at least 1 imprinted gene. This article discusses the clinical background, genetic cause, diagnostic strategy, and management of each of these 3 disorders. <<<

Modern CNNs are learning the weights of vast numbers of convolutional operators. In this paper, we raise the fundamental question if this is actually necessary. We show that even in the extreme case of only randomly initializing and never updating spatial filters, certain CNN architectures can be trained to surpass the accuracy of standard training. By reinterpreting the notion of pointwise (1×1) convolutions as an operator to learn linear combinations (LC) of frozen (random) spatial filters, we are able to analyze these effects and propose a generic LC convolution block that allows tuning of the linear combination rate. Empirically, we show that this approach not only allows us to reach high test accuracies on CIFAR and ImageNet but also has favorable properties regarding model robustness, generalization, sparsity, and the total number of necessary weights. Additionally, we propose a novel weight sharing mechanism, which allows sharing of a single weight tensor between all spatial convolution layers to massively reduce the number of weights. <<<

Modern CNNs are learning the weights of vast numbers of convolutional operators. In this paper, we raise the fundamental question if this is actually necessary. We show that even in the extreme case of only randomly initializing and never updating spatial filters, certain CNN architectures can be trained to surpass the accuracy of standard training. By reinterpreting the notion of pointwise (1×1) convolutions as an operator to learn linear combinations (LC) of frozen (random) spatial filters, we are able to analyze these effects and propose a generic LC convolution block that allows tuning of the linear combination rate. Empirically, we show that this approach not only allows us to reach high test accuracies on CIFAR and ImageNet but also has favorable properties regarding model robustness, generalization, sparsity, and the total number of necessary weights. Additionally, we propose a novel weight sharing mechanism, which allows sharing of a single weight tensor between all spatial convolution layers to massively reduce the number of weights. <<<

Handwritten Chinese text recognition (HCTR) has been an active research topic for decades. However, most previous studies solely focus on the recognition of cropped text line images, ignoring the error caused by text line detection in real-world applications. Although some approaches aimed at page-level text recognition have been proposed in recent years, they either are limited to simple layouts or require very detailed annotations including expensive line-level and even character-level bounding boxes. To this end, we propose PageNet for end-to-end weakly supervised page-level HCTR. PageNet detects and recognizes characters and predicts the reading order between them, which is more robust and flexible when dealing with complex layouts including multi-directional and curved text lines. Utilizing the proposed weakly supervised learning framework, PageNet requires only transcripts to be annotated for real data; however, it can still output detection and recognition results at both the character and line levels, avoiding the labor and cost of labeling bounding boxes of characters and text lines. Extensive experiments conducted on five datasets demonstrate the superiority of PageNet over existing weakly supervised and fully supervised page-level methods. These experimental results may spark further research beyond the realms of existing methods based on connectionist temporal classification or attention. The source code is available at https://github.com/shannanyinxiang/PageNet. <<<

A somewhat contradictory published body of evidence suggests that sex impacts severity outcomes of human leptospirosis. In this study, we used an acute animal model of disease to analyze leptospirosis in male and female hamsters infected side by side with low but increasing doses of serovar Copenhageni. We found that male hamsters were considerably more susceptible to leptospirosis, given that only 6.3% survived infection, whereas 68.7% of the females survived the same infection doses. In contrast to the females, male hamsters had high burdens of in kidney and high histopathological scores after exposure to low infection doses (∼10 bacteria). In hamsters infected with higher doses of (∼10 bacteria), differences in pathogen burdens as well as cytokine and fibrosis transcript levels in kidney were not distinct between sexes. Our results indicate that male hamsters infected with are more susceptible to severe leptospirosis after exposure to lower infectious doses than females. <<<

Tumor-derived circulating cell-free DNA (cfDNA) provides critical clues for cancer early diagnosis, yet it often suffers from low sensitivity. Here, we present a cancer early diagnosis approach using tumor fractions deciphered from circulating cfDNA methylation signatures. We show that the estimated fractions of tumor-derived cfDNA from cancer patients increase significantly as cancer progresses in two independent datasets. Employing the predicted tumor fractions, we establish a Bayesian diagnostic model in which training samples are only derived from late-stage patients and healthy individuals. When validated on early-stage patients and healthy individuals, this model exhibits a sensitivity of 86.1% for cancer early detection and an average accuracy of 76.9% for tumor localization at a specificity of 94.7%. By highlighting the potential of tumor fractions on cancer early diagnosis, our approach can be further applied to cancer screening and tumor progression monitoring. <<<

Erika Erickson, Japheth E Gado, Luisana Avilán, Felicia Bratti, Richard K Brizendine, Paul A Cox, Raj Gill, Rosie Graham, Dong-Jin Kim, Gerhard König, William E Michener, Saroj Poudel, Kelsey J Ramirez, Thomas J Shakespeare, Michael Zahn, Eric S Boyd, Christina M Payne, Jennifer L DuBois, Andrew R Pickford, Gregg T Beckham, John E McGeehan <<<

Enzymatic deconstruction of poly(ethylene terephthalate) (PET) is under intense investigation, given the ability of hydrolase enzymes to depolymerize PET to its constituent monomers near the polymer glass transition temperature. To date, reported PET hydrolases have been sourced from a relatively narrow sequence space. Here, we identify additional PET-active biocatalysts from natural diversity by using bioinformatics and machine learning to mine 74 putative thermotolerant PET hydrolases. We successfully express, purify, and assay 51 enzymes from seven distinct phylogenetic groups; observing PET hydrolysis activity on amorphous PET film from 37 enzymes in reactions spanning pH from 4.5-9.0 and temperatures from 30-70 °C. We conduct PET hydrolysis time-course reactions with the best-performing enzymes, where we observe differences in substrate selectivity as function of PET morphology. We employed X-ray crystallography and AlphaFold to examine the enzyme architectures of all 74 candidates, revealing protein folds and accessory domains not previously associated with PET deconstruction. Overall, this study expands the number and diversity of thermotolerant scaffolds for enzymatic PET deconstruction. <<<