A Method for Bio-Sequence Analysis Algorithm Development Based on the PAR Platform

The problems of biological sequence analysis have great theoretical and practical value in modern bioinformatics. Numerous solving algorithms are used for these problems, and complex similarities and differences exist among these algorithms for the same problem, causing difficulty for researchers to select the appropriate one. To address this situation, combined with the formal partition-and-recur method, component technology, domain engineering, and generic programming, the paper presents a method for the development of a family of biological sequence analysis algorithms. It designs highly trustworthy reusable domain algorithm components and further assembles them to generate specifific biological sequence analysis algorithms. The experiment of the development of a dynamic programming based LCS algorithm family shows the proposed method enables the improvement of the reliability, understandability, and development efficiency of particular algorithms

OHMI: The Ontology of Host-Microbiome Interactions

Host-microbiome interactions (HMIs) are critical for the modulation of biological processes and are associated with several diseases, and extensive HMI studies have generated large amounts of data. We propose that the logical representation of the knowledge derived from these data and the standardized representation of experimental variables and processes can foster integration of data and reproducibility of experiments and thereby further HMI knowledge discovery. A community-based Ontology of Host-Microbiome Interactions (OHMI) was developed following the OBO Foundry principles. OHMI leverages established ontologies to create logically structured representations of microbiomes, microbial taxonomy, host species, host anatomical entities, and HMIs under different conditions and associated study protocols and types of data analysis and experimental results

Three-dimensional gait analysis of orthopaedic common foot and ankle joint diseases

Walking is an indispensable mode of transportation for human survival. Gait is a characteristic of walking. In the clinic, patients with different diseases exhibit different gait characteristics. Gait analysis describes the specific situation of human gait abnormalities by observing and studying the kinematics and dynamics of limbs and joints during human walking and depicting the corresponding geometric curves and values. In foot and ankle diseases, gait analysis can evaluate the degree and nature of gait abnormalities in patients and provide an important basis for the diagnosis of patients’ diseases, the correction of abnormal gait and related treatment methods. This article reviews the relevant literature, expounds on the clinical consensus on gait, and summarizes the gait characteristics of patients with common ankle and foot diseases. Starting from the gait characteristics of individuals with different diseases, we hope to provide support and reference for the diagnosis, treatment and rehabilitation of clinically related diseases

Identification of gene mutations in six Chinese patients with maple syrup urine disease

Background: Maple syrup urine disease (MSUD) is a rare autosomal recessive amino acid metabolic disease. This study is to identify the pathogenic genetic factors of six cases of MUSD and evaluates the application value of high-throughput sequencing technology in the early diagnosis of MUSD.Methods: Clinical examination was carried out for patients and used blood tandem mass spectrometry (MS/MS), urine gas chromatography-mass spectrometry (GC/MS), and the application of high-throughput sequencing technology for detection. Validate candidate mutations by polymerase chain reaction (PCR)—Sanger sequencing technology. Bioinformatics software analyzed the variants’ pathogenicity. Using Swiss PDB Viewer software to predict the effect of mutation on the structure of BCKDHA and BCKDHB proteins.Result: A total of six MSUD patients were diagnosed, including four males and two females. Nine variants were found in three genes of six MSUD families by high-throughput sequencing, including four missense mutations: c.659C>T(p.A220V), c.818C>T(p.T273I), c.1134C>G(p.D378E), and c.1006G>A(p.G336S); two non-sense mutations: c.1291C>T(p.R431*) and c.331C>T(p.R111*); three deletion mutations: c.550delT (p.S184Pfs*46), c.718delC (p.P240Lfs*14), and c.795delG (p.N266Tfs*64). Sanger sequencing’s results were consistent with the high-throughput sequencing. The bioinformatics software revealed that the mutations were harmful, and the prediction results of Swiss PDB Viewer suggest that variation affects protein conformation.Conclusion: This study identified nine pathogenic variants in the BCKDHA, BCKDHB, and DBT genes in six MSUD families, including two novel pathogenic variants in the BCKDHB gene, which enriched the genetic mutational spectrum of the disease. High-throughput sequencing is essential for the MSUD’s differential diagnosis, early treatment, and prenatal diagnosis

Genome-Wide Association Study and Selective Sweep Analysis Reveal the Genetic Architecture of Body Weights in a Chicken F2 Resource Population

Rapid growth is one of the most important economic traits in broiler breeding programs. Identifying markers and genes for growth traits may not only benefit marker-assisted selection (MAS)/genomic selection (GS) but also provide important information for understanding the genetic architecture of growth traits in broilers. In the present study, an F2 resource population derived from a cross between the broiler and Baier yellow chicken (a Chinese local breed) was used and body weights from 1 to 12 weeks of age [body weight (BW) 1–BW12)] were measured. A total of 519 F2 birds were genome re-sequenced, and a combination of genome-wide association study (GWAS) and selective sweep analysis was carried out to characterize the genetic architecture affecting chicken body weight comprehensively. As a result, 1,539 SNPs with significant effects on body weights at different weeks of age were identified using a genome-wide efficient mixed-model association (GEMMA) package. These SNPs were distributed on chromosomes 1 and 4. Besides, windows under selection identified for BW1–BW12 varied from 1,581 to 2,265. A total of 42 genes were also identified with significant effects on BW1–BW12 based on both GWAS and selective sweep analysis. Among these genes, diacylglycerol kinase eta (DGKH), deleted in lymphocytic leukemia (DLEU7), forkhead box O17 (FOXO1), karyopherin subunit alpha 3 (KPNA3), calcium binding protein 39 like (CAB39L), potassium voltage-gated channel interacting protein 4 (KCNIP4), and slit guidance ligand 2 (SLIT2) were considered as important genes for broiler growth based on their basic functions. The results of this study may supply important information for understanding the genetic architecture of growth traits in broilers

New Construction of Family of MLCS Algorithms

The multiple longest common subsequence (MLCS) problem involves finding all the longest common subsequences of multiple character sequences. This problem is encountered in a variety of areas, including data mining, text processing, and bioinformatics, and is particularly important for biological sequence analysis. By taking the MLCS problem and algorithms for its solution as research domain, this study analyzes the domain of multiple longest common subsequence algorithms, extracts features that algorithms in the domain do and do not have in common, and creates a domain feature model for the MLCS problem by using generic programming, domain engineering, abstraction, and related technologies. A component library for the domain is designed based on the feature model for the MLCS problem, and the partition and recur (PAR) platform is used to ensure that highly reliable MLCS algorithms can be quickly assembled through component assembly. This study provides a valuable reference for obtaining rapid solutions to problems of biological sequence analysis and improves the reliability and assembly flexibility of assembling algorithms

Mid-Infrared 2.79 μm Band Er, Cr: Y₃Sc₂Ga₃O₁₂ Laser Transmission Anti-Bending Low-Loss Anti-Resonant Hollow-Core Fiber

A large core size and bending resistance are very important properties of mid-infrared energy transfer fibers, but large core sizes usually lead to the deterioration of bending properties. A negative-curvature nested node-free anti-resonant hollow-core fiber (AR-HCF) based on quartz is proposed. It was made by adding a nested layer to a previous AR-HCF design to provide an additional anti-resonance region while keeping the gap between adjacent tubes strictly correlated with the core diameter to produce a node-free structure. These features improve the fiber’s bending resistance while achieving a larger core diameter. The simulation results show that the radial air–glass anti-resonant layer is increased by the introduction of the nested anti-resonant tube, and the weak interference overlap between the fiber core and the cladding mode is reduced, so the fiber core’s limiting loss and sensitivity to bending are effectively reduced. When the capillary wall thickness t of the fiber is 0.71 μm, the core diameter D is 70 μm, the ratio of the inner diameter of the cladding capillary to the core diameter d/D is 0.62, the diameter of the nested tube is d0 = 29 μm, the fiber has a lower limiting loss at the wavelength of 2.79 μm, and the limiting loss is 3.28 × 10−4 dB/m. At the same time, the optimized structure also has good bending resistance. When the bending radius is 30 mm, the bending loss is only 4.72 × 10−2 dB/m. An anti-bending low-loss micro-structure hollow fiber with a bending radius of less than 30 mm was successfully achieved in the 2.79 μm band. An anti-bending low-loss anti-resonant hollow-core fiber with this structure constitutes a reliable choice for the light guiding system of a 2.79 μm band Er, Cr: YSGG laser therapy instrument