Intelligent image-based in situ single-cell isolation

Quantifying heterogeneities within cell populations is important for many fields including cancer research and neurobiology; however, techniques to isolate individual cells are limited. Here, we describe a high-throughput, non-disruptive, and cost-effective isolation method that is capable of capturing individually targeted cells using widely available techniques. Using high-resolution microscopy, laser microcapture microscopy, image analysis, and machine learning, our technology enables scalable molecular genetic analysis of single cells, targetable by morphology or location within the sample.Peer reviewe

RNA secondary structure prediction from multi-aligned sequences

It has been well accepted that the RNA secondary structures of most functional non-coding RNAs (ncRNAs) are closely related to their functions and are conserved during evolution. Hence, prediction of conserved secondary structures from evolutionarily related sequences is one important task in RNA bioinformatics; the methods are useful not only to further functional analyses of ncRNAs but also to improve the accuracy of secondary structure predictions and to find novel functional RNAs from the genome. In this review, I focus on common secondary structure prediction from a given aligned RNA sequence, in which one secondary structure whose length is equal to that of the input alignment is predicted. I systematically review and classify existing tools and algorithms for the problem, by utilizing the information employed in the tools and by adopting a unified viewpoint based on maximum expected gain (MEG) estimators. I believe that this classification will allow a deeper understanding of each tool and provide users with useful information for selecting tools for common secondary structure predictions.Comment: A preprint of an invited review manuscript that will be published in a chapter of the book `Methods in Molecular Biology'. Note that this version of the manuscript may differ from the published versio

Characterization and therapeutic application of canine adipose mesenchymal stem cells to treat elbow osteoarthritis

Visceral adipose tissue (AT) obtained from surgical waste during routine ovariectomies was used as a source for isolating canine mesenchymal stem cells (MSCs). As determined by cytofluorimetry, passage 2 cells expressed MSC markers CD44 and CD90 and were negative for lineage-specific markers CD34 and CD45. The cells differentiated toward osteogenic, adipogenic, and chondrogenic directions. With therapeutic aims, 30 dogs (39 joints) suffering from elbow dysplasia (ED) and osteoarthritis (OA) were intra-articularly transplanted with allogeneic MSCs suspended in 0.5% hyaluronic acid (HA). A highly significant improvement was achieved without any medication as demonstrated by the degree of lameness during the follow-up period of 1 y. Control arthroscopy of 1 transplanted dog indicated that the cartilage had regenerated. Histological analysis of the cartilage biopsy confirmed that the regenerated cartilage was of hyaline type. These results demonstrate that transplantation of allogeneic adipose tissue-derived mesenchymal stem cells (AT-MSCs) is a novel, noninvasive, and highly effective therapeutic tool in treating canine elbow dysplasia