Clinical Applications of Mesenchymal Stromal Cells (MSCs) in Orthopedic Diseases

Mesenchymal stromal cells (MSCs) have the capacity for self-renewal and multi-lineage differentiation, have many advantages over other cells, and are thought to be one of the most promising cell sources for cell-based treatments. In fact, MSCs have already been widely applied in clinics as a treatment for numerous disorders, including orthopedic diseases, such as bone fracture, articular cartilage injury, osteoarthritis (OA), femoral head necrosis, degenerative disc, meniscus injury, osteogenesis imperfecta (OI), and other systemic bone diseases. With the progressions in R&D, the safety and efficacy of MSC-based treatments in orthopedic diseases have been largely recognized, but many challenges still exist. In this chapter, we intend to briefly update the recent progressions and discuss the potential issues in the target areas. Hopefully, our discussion would be helpful not only for the clinicians and the researchers in the specific disciplines but also for the general audiences

Probing Meiotic Recombination and Aneuploidy of Single Sperm Cells by Whole-Genome Sequencing

Meiotic recombination creates genetic diversity and ensures segregation of homologous chromosomes. Previous population analyses yielded results averaged among individuals and affected by evolutionary pressures. We sequenced 99 sperm from an Asian male by using the newly developed amplification method—multiple annealing and looping-based amplification cycles—to phase the personal genome and map recombination events at high resolution, which are nonuniformly distributed across the genome in the absence of selection pressure. The paucity of recombination near transcription start sites observed in individual sperm indicates that such a phenomenon is intrinsic to the molecular mechanism of meiosis. Interestingly, a decreased crossover frequency combined with an increase of autosomal aneuploidy is observable on a global per-sperm basis.Chemistry and Chemical Biolog

Query tables in Parquet format for Deep DNAshape webserver

DNA shape query tables generated by Deep DNAshape model from 5-mer to 11-mer, separated in odd and even k-mers. Use odd.txt and bp.parquet for intra-bp features and minor groove features. Use even.txt and bpstep.parquet for inter-bp features. </p

Selection and use of LIMS

SIGLEAvailable from British Library Document Supply Centre-DSC:8321.4562(no 9) / BLDSC - British Library Document Supply CentreGBUnited Kingdo

Predicting DNA structure using a deep learning method

Abstract Understanding the mechanisms of protein-DNA binding is critical in comprehending gene regulation. Three-dimensional DNA structure, also described as DNA shape, plays a key role in these mechanisms. In this study, we present a deep learning-based method, Deep DNAshape, that fundamentally changes the current k-mer based high-throughput prediction of DNA shape features by accurately accounting for the influence of extended flanking regions, without the need for extensive molecular simulations or structural biology experiments. By using the Deep DNAshape method, DNA structural features can be predicted for any length and number of DNA sequences in a high-throughput manner, providing an understanding of the effects of flanking regions on DNA structure in a target region of a sequence. The Deep DNAshape method provides access to the influence of distant flanking regions on a region of interest. Our findings reveal that DNA shape readout mechanisms of a core target are quantitatively affected by flanking regions, including extended flanking regions, providing valuable insights into the detailed structural readout mechanisms of protein-DNA binding. Furthermore, when incorporated in machine learning models, the features generated by Deep DNAshape improve the model prediction accuracy. Collectively, Deep DNAshape can serve as versatile and powerful tool for diverse DNA structure-related studies

The complete chloroplast genome of Urtica angustifolia Fisch. ex Hornem. (Urticaceae), an important kind of traditional Chinese medicine in China

Urtica angustifolia Fisch. ex Hornem. is an important Chinese medicine. Here, the complete chloroplast genome of U. angustifolia was assembled and characterized. The length of the chloroplast genome was 146,679 bp with the typical quadripartite structure, containing two inverted repeats (IRs) of 24,595 bp separated by a large single-copy (LSC) region of 79,820 bp and a small single-copy (SSC) region of 17,669 bp. The whole chloroplast genome of U. angustifolia contains 111 genes, including 77 protein-coding genes, 30 tRNA genes, and 4 rRNA genes. Nucleotide variability analysis identified three hotspot regions (trnK-rps16, ndhF-rps32, and ycf1b) for genomic divergence and 52 simple sequence repeats. Phylogenetic analysis based on the complete chloroplast genomes exhibited that U. angustifolia formed a clade with Urtica lobatifolia and Hesperocnide tenella