Detection of novel viruses in porcine fecal samples from China

BACKGROUND: Pigs are well known source of human infectious disease. To better understand the spectrum of viruses present in pigs, we utilized the 454 Life Sciences GS-FLX high-throughput sequencing platform to sequence stool samples from healthy pigs. FINDINGS: Total nucleic acid was extracted from stool samples of healthy piglets and randomly amplified. The amplified materials were pooled and processed using a high-throughput pyrosequencing technique. The raw sequences were deconvoluted on the basis of the barcode and then processed through a standardized bioinformatics pipeline. The unique reads (348, 70 and 13) had limited similarity to known astroviruses, bocaviruses and parechoviruses. Specific primers were synthesized to assess the prevalence of the viruses in healthy piglets. Our results indicate extremely high rates of positivity. CONCLUSIONS: Several novel astroviruses, bocaviruses and Ljungan-like viruses were identified in stool samples from healthy pigs. The rates of isolation for the new viruses were high. The high detection rate, diverse sequences and categories indicate that pigs are well-established reservoirs for and likely sources of different enteric viruses

Next-Generation Sequencing Data-Based Association Testing of a Group of Genetic Markers for Complex Responses Using a Generalized Linear Model Framework

To study the relationship between genetic variants and phenotypes, association testing is adopted; however, most association studies are conducted by genotype-based testing. Testing methods based on next-generation sequencing (NGS) data without genotype calling demonstrate an advantage over testing methods based on genotypes in the scenarios when genotype estimation is not accurate. Our objective was to develop NGS data-based methods for association studies to fill the gap in the literature. Single-variant testing methods based on NGS data have been proposed, including our previously proposed single-variant NGS data-based testing method, i.e., UNC combo method. The NGS data-based group testing method has been proposed by us using a linear model framework which can handle continuous responses. In this paper, we extend our linear model-based framework to a generalized linear model-based framework so that the methods can handle other types of responses especially binary responses which is a common problem in association studies. To evaluate the performance of various estimators and compare them we performed simulation studies. We found that all methods have Type I errors controlled, and our NGS data-based methods have better performance than genotype-based methods for other types of responses, including binary responses (logistics regression) and count responses (Poisson regression), especially when sequencing depth is low. We have extended our previous linear model (LM) framework to a generalized linear model (GLM) framework and derived NGS data-based methods for a group of genetic variables. Compared with our previously proposed LM-based methods, the new GLM-based methods can handle more complex responses (for example, binary responses and count responses) in addition to continuous responses. Our methods have filled the literature gap and shown advantage over their corresponding genotype-based methods in the literature

Late cardioprotection of exercise preconditioning against exhaustive exercise-induced myocardial injury by up-regulatation of connexin 43 expression in rat hearts

AbstractObjectiveTo investigate the expression of myocardium connexin 43 (Cx43) in late exercise preconditioning (LEP) cardioprotection.MethodsEight-week-old adult male Sprague Dawley rats were randomly assigned into four groups (n = 8). Myocardial injury was judged in accordance with serum levels of cTnⅠ and NT-proBNP as well as hematoxylin basicfuchsin picric acid staining of myocardium. Cx43 mRNA was detected by in situ hybridization and qualified by real-time fluorescence quantitative PCR. Cx43 protein was localized by immunohistochemistry and its expression level was determined by western blotting.ResultsThe LEP obviously attenuated the myocardial ischemia/hypoxia injury caused by exhaustive exercise. There was no significant difference of Cx43 mRNA level between the four groups. Cx43 protein level was decreased significantly in group EE (P < 0.05). However, LEP produced a significant increase in Cx43 protein level (P < 0.05), and the decreased Cx43 protein level in exhaustive exercise was significantly up-regulated by LEP (P < 0.05).ConclusionsLEP protects rat heart against exhaustive exercise-induced myocardial injury by up-regulating the expression of myocardial Cx43

Efficient 3PC for Binary Circuits with Application to Maliciously-Secure DNN Inference

In this work, we focus on maliciously secure 3PC for binary circuits with honest majority. While the state-of-the-art (Boyle et al. CCS 2019) has already achieved the same amortized communication as the best-known semi-honest protocol (Araki et al. CCS 2016), they suffer from a large computation overhead: when comparing with the best-known implementation result (Furukawa et al. Eurocrypt 2017) which requires $9\times$ communication cost of Araki et al., the protocol by Boyle et al. is around $4.5\times$ slower than that of Furukawa et al. In this paper, we design a maliciously secure 3PC protocol that matches the same communication as Araki et al. with comparable concrete efficiency as Furukawa et al. To obtain our result, we manage to apply the distributed zero-knowledge proofs (Boneh et al. Crypto 2019) for verifying computations over $\mathbb{Z}_2$ by using \emph{prime} fields and explore the algebraic structure of prime fields to make the computation of our protocol friendly for native CPU computation. Experiment results show that our protocol is around $3.5\times$ faster for AES circuits than Boyle et al. We also applied our protocol to the binary part (e.g. comparison and truncation) of secure deep neural network inference, and results show that we could reduce the time cost of achieving malicious security in the binary part by more than $67\%$. Besides our main contribution, we also find a hidden security issue in many of the current probabilistic truncation protocols, which may be of independent interest

DISSCO: direct imputation of summary statistics allowing covariates

Background: Imputation of individual level genotypes at untyped markers using an external reference panel of genotyped or sequenced individuals has become standard practice in genetic association studies. Direct imputation of summary statistics can also be valuable, for example in meta-analyses where individual level genotype data are not available. Two methods (DIST and ImpG-Summary/LD), that assume a multivariate Gaussian distribution for the association summary statistics, have been proposed for imputing association summary statistics. However, both methods assume that the correlations between association summary statistics are the same as the correlations between the corresponding genotypes. This assumption can be violated in the presence of confounding covariates

TaskMatrix.AI: Completing Tasks by Connecting Foundation Models with Millions of APIs

Artificial Intelligence (AI) has made incredible progress recently. On the one hand, advanced foundation models like ChatGPT can offer powerful conversation, in-context learning and code generation abilities on a broad range of open-domain tasks. They can also generate high-level solution outlines for domain-specific tasks based on the common sense knowledge they have acquired. However, they still face difficulties with some specialized tasks because they lack enough domain-specific data during pre-training or they often have errors in their neural network computations on those tasks that need accurate executions. On the other hand, there are also many existing models and systems (symbolic-based or neural-based) that can do some domain-specific tasks very well. However, due to the different implementation or working mechanisms, they are not easily accessible or compatible with foundation models. Therefore, there is a clear and pressing need for a mechanism that can leverage foundation models to propose task solution outlines and then automatically match some of the sub-tasks in the outlines to the off-the-shelf models and systems with special functionalities to complete them. Inspired by this, we introduce TaskMatrix.AI as a new AI ecosystem that connects foundation models with millions of APIs for task completion. Unlike most previous work that aimed to improve a single AI model, TaskMatrix.AI focuses more on using existing foundation models (as a brain-like central system) and APIs of other AI models and systems (as sub-task solvers) to achieve diversified tasks in both digital and physical domains. As a position paper, we will present our vision of how to build such an ecosystem, explain each key component, and use study cases to illustrate both the feasibility of this vision and the main challenges we need to address next

Comprehensive analysis of SSRs and database construction using all complete gene-coding sequences in major horticultural and representative plants

Simple sequence repeats (SSRs) are one of the most important genetic markers and widely exist in most species. Here, we identified 249,822 SSRs from 3,951,919 genes in 112 plants. Then, we conducted a comprehensive analysis of these SSRs and constructed a plant SSR database (PSSRD). Interestingly, more SSRs were found in lower plants than in higher plants, showing that lower plants needed to adapt to early extreme environments. Four specific enriched functional terms in the lower plant Chlamydomonas reinhardtii were detected when it was compared with seven other higher plants. In addition, Guanylate_cyc existed in more genes of lower plants than of higher plants. In our PSSRD, we constructed an interactive plotting function in the chart interface, and users can easily view the detailed information of SSRs. All SSR information, including sequences, primers, and annotations, can be downloaded from our database. Moreover, we developed Web SSR Finder and Batch SSR Finder tools, which can be easily used for identifying SSRs. Our database was developed using PHP, HTML, JavaScript, and MySQL, which are freely available at http://www.pssrd.info/. We conducted an analysis of the Myb gene families and flowering genes as two applications of the PSSRD. Further analysis indicated that whole-genome duplication and whole-genome triplication played a major role in the expansion of the Myb gene families. These SSR markers in our database will greatly facilitate comparative genomics and functional genomics studies in the future

Novel Human Bocavirus in Children with Acute Respiratory Tract Infection

Human bocavirus (HBoV) and HBoV2, two human bocavirus species, were found in 18 and 10 of 235 nasopharyngeal aspirates, respectively, from children hospitalized with acute respiratory tract infection. Our results suggest that, like HBoV, HBoV2 is distributed worldwide and may be associated with respiratory and enteric diseases

Single-cell transcriptome and antigen-immunoglobin analysis reveals the diversity of B cells in non-small cell lung cancer

Background Malignant transformation and progression of cancer are driven by the co-evolution of cancer cells and their dysregulated tumor microenvironment (TME). Recent studies on immunotherapy demonstrate the efficacy in reverting the anti-tumoral function of T cells, highlighting the therapeutic potential in targeting certain cell types in TME. However, the functions of other immune cell types remain largely unexplored. Results We conduct a single-cell RNA-seq analysis of cells isolated from tumor tissue samples of non-small cell lung cancer (NSCLC) patients, and identify subtypes of tumor-infiltrated B cells and their diverse functions in the progression of NSCLC. Flow cytometry and immunohistochemistry experiments on two independent cohorts confirm the co-existence of the two major subtypes of B cells, namely the naïve-like and plasma-like B cells. The naïve-like B cells are decreased in advanced NSCLC, and their lower level is associated with poor prognosis. Co-culture of isolated naïve-like B cells from NSCLC patients with two lung cancer cell lines demonstrate that the naïve-like B cells suppress the growth of lung cancer cells by secreting four factors negatively regulating the cell growth. We also demonstrate that the plasma-like B cells inhibit cancer cell growth in the early stage of NSCLC, but promote cell growth in the advanced stage of NSCLC. The roles of the plasma-like B cell produced immunoglobulins, and their interacting proteins in the progression of NSCLC are further validated by proteomics data. Conclusion Our analysis reveals versatile functions of tumor-infiltrating B cells and their potential clinical implications in NSCLC