Near telomere-to-telomere assembly of the Tarim pigeon (Columba livia) genome.

Pigeons serve as important model animals and commercial poultry. The Tarim pigeon, as a breed of Columba livia, is a locally indigenous breed unique to China. While the genome of C.

Microbiome and Microbial Pure Culture Study Reveal Commensal Microorganisms Alleviate Serovar Pullorum Infection in Chickens.

Pullorum disease, an intestinal disease in chickens caused by serovar pullorum ( Pullorum), is a significant threat to the poultry industry and results in substantial economic losses. The bacteria's transmission, both vertical and horizontal, makes it difficult to completely eliminate it. Control strategies for pullorum disease primarily involve stringent eradication programs that cull infected birds and employ antibiotics for treatment.

One-Step Genetic Modification by Embryonic Doral Aorta Injection of Adenoviral CRISPR/Cas9 Vector in Chicken.

In the avian species, genetic modification by cell nuclear transfer is infeasible due to its unique reproductive system. The in vitro primordial germ cell modification approach is difficult and cumbersome, although it is the main method of genetic modification in chickens. In the present study, the adenoviral CRISPR/Cas9 vector was directly microinjected into the dorsal aorta of chicken embryos to achieve in vivo genetic modification.

A Method for Inferring Polymers Based on Linear Regression and Integer Programming.

A novel framework has recently been proposed for designing the molecular structure of chemical compounds with a desired chemical property using both artificial neural networks and mixed integer linear programming. In this paper, we design a new method for inferring a polymer based on the framework. For this, we introduce a new way of representing a polymer as a form of monomer and define new descriptors that feature the structure of polymers.

Molecular Design Based on Integer Programming and Splitting Data Sets by Hyperplanes.

A novel framework for designing the molecular structure of chemical compounds with a desired chemical property has recently been proposed. The framework infers a desired chemical graph by solving a mixed integer linear program (MILP) that simulates the computation process of two functions: a feature function defined by a two-layered model on chemical graphs and a prediction function constructed by a machine learning method. To improve the learning performance of prediction functions in the framework, we design a method that splits a given data set C into two subsets C,i=1,2 by a hyperplane in a chemical space so that most compounds in the first (resp.

One-Pot Visual Detection of African Swine Fever Virus Using CRISPR-Cas12a.

African swine fever virus (ASFV) is a leading cause of worldwide agricultural loss. ASFV is a highly contagious and lethal disease for both domestic and wild pigs, which has brought enormous economic losses to a number of countries. Conventional methods, such as general polymerase chain reaction and isothermal amplification, are time-consuming, instrument-dependent, and unsatisfactorily accurate.

Dynamics of Small Non-coding RNA Profiles and the Intestinal Microbiome of High and Low Weight Chickens.

The host and its symbiotic bacteria form a biological entity, holobiont, in which they share a dynamic connection characterized by symbiosis, co-metabolism, and coevolution. However, how these collaborative relationships were maintained over evolutionary time remains unclear. In this research, the small non-coding RNA (sncRNA) profiles of cecum and their bacteria contents were measured from lines of chickens that have undergone long-term selection for high (HWS) or low (LWS) 56-day body weight.

An Inverse QSAR Method Based on Linear Regression and Integer Programming.

Background: Drug design is one of the important applications of biological science. Extensive studies have been done on computer-aided drug design based on inverse quantitative structure activity relationship (inverse QSAR), which is to infer chemical compounds from given chemical activities and constraints. However, exact or optimal solutions are not guaranteed in most of the existing methods.

The functional role of fecal microbiota transplantation on Salmonella Enteritidis infection in chicks.

The intestinal microbiota plays important roles in animal health and growth. We investigated the efficacy and mechanisms of fecal microbiota transplantation (FMT) from adult SPF chickens against Salmonella Enteritidis (SE) infection in chicks. We transplanted 160 recipient SPF chicks (1-day-old) that were randomly divided into four groups, Ca (challenge), Cb (non-challenge), Fa (FMT and challenge) and Fb (FMT without challenge).

Transcriptomic Analysis of Knockout in the Early Differentiation of Chicken Fetal Myoblasts.

In mammals, is a known negative regulator of muscle growth and development, but its role in birds is poorly understood. To investigate the molecular mechanism of on muscle growth and development in chickens, we knocked out in chicken fetal myoblasts (CFMs) and sequenced the mRNA transcriptomes. The amplicon sequencing results show that the editing efficiency of the cells was 76%.

A Novel Method for Inferring Chemical Compounds With Prescribed Topological Substructures Based on Integer Programming.

Drug discovery is one of the major goals of computational biology and bioinformatics. A novel framework has recently been proposed for the design of chemical graphs using both artificial neural networks (ANNs) and mixed integer linear programming (MILP). This method consists of a prediction phase and an inverse prediction phase.

A novel method for inference of acyclic chemical compounds with bounded branch-height based on artificial neural networks and integer programming.

Analysis of chemical graphs is becoming a major research topic in computational molecular biology due to its potential applications to drug design. One of the major approaches in such a study is inverse quantitative structure activity/property relationship (inverse QSAR/QSPR) analysis, which is to infer chemical structures from given chemical activities/properties. Recently, a novel two-phase framework has been proposed for inverse QSAR/QSPR, where in the first phase an artificial neural network (ANN) is used to construct a prediction function.

An Inverse QSAR Method Based on a Two-Layered Model and Integer Programming.

A novel framework for inverse quantitative structure-activity relationships (inverse QSAR) has recently been proposed and developed using both artificial neural networks and mixed integer linear programming. However, classes of chemical graphs treated by the framework are limited. In order to deal with an arbitrary graph in the framework, we introduce a new model, called a two-layered model, and develop a corresponding method.

Emerging role of long non-coding RNA MALAT1 in predicting clinical outcomes of patients with digestive system malignancies: A meta-analysis.

Digestive system malignancies are the most common cancer types worldwide and exhibit an extremely low overall 5-year survival rate. Therefore, clinically applicable biomarkers for predicting clinical outcome are urgently required. Metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) is abnormally expressed in several cancer types.