Teratoma formation by human embryonic stem cells: Evaluation of essential parameters for future safety studies

Transplantation of human embryonic stem cells (hESC) into immune-deficient mice leads to the formation of differentiated tumors comprising all three germ layers, resembling spontaneous human teratomas. Teratoma assays are considered the gold standard for demonstrating differentiation potential of pluripotent hESC and hold promise as a standard for assessing safety among hESC-derived cell populations intended for therapeutic applications. We tested the potency of teratoma formation in seven anatomical transplantation locations (kidney capsule, muscle, subcutaneous space, peritoneal cavity, testis, liver, epididymal fat pad) in SCID mice with and without addition of Matrigel, and found that intramuscular teratoma formation was the most experimentally convenient, reproducible, and quantifiable. In the same experimental setting, we compared undifferentiated hESC and differentiated populations enriched for either beating cardiomyocytes or definitive endoderm derivatives (insulin-secreting beta cells), and showed that all cell preparations rapidly formed teratomas with varying percentages of mesoderm, ectoderm, and endoderm. In limiting dilution experiments, we found that as little as two hESC colonies spiked into feeder fibroblasts produced a teratoma, while a more rigorous single-cell titration achieved a detection limit of 1/4000. In summary, we established core parameters essential for facilitating safety profiling of hESC-derived products for future therapeutic applications.     

Leptin, Leptin Receptors and ACTH Immunoreactivities are Present in the Gastrointestinal Tract and the Neural Tube of Tadpoles of the Newt Triturus

Leptin, its receptor and ACTH were detected by immunohistochemistry in the gastrointestinal tract and the neural tube of the amphibian urodele, Triturus cristatus carnifex, during development. These molecules were found after hatching of tadpoles, starting from stage 41. In the gastrointestinal tract, cells immunoreactive to leptin and its receptor were first revealed in the stomach, the liver and the gut and then in the pancreas. Both immunoreactives were colocalized in the same cells in some areas. Immunostaining for ACTH appeared at stages 43/45 in the stomach, the gut and the pancreas. In adjacent sections, a few cells immunoreactive to both ACTH and leptin receptor were detected. A few cells were immunoreactive to both insulin and leptin receptor. Immunoreactivities to leptin and its receptor were also found in adjacent sections of the neural tube, often colocalized in the same cell. Moreover, in prosencephalon, mesencephalon, rhomboencephalon and spinal cord, ACTH-immunoreactive cells were detected in the same areas as the leptin receptor immunoreactive cells. These results suggest the existence of a neuroendocrine network in newt tadpoles both at the central level, where it resembles that of mammals, and at the peripheral level, where it may act locally to regulate food intake and metabolism, e.g. yolk digestion.     

Acid-sensing ion channel 3 mediates peripheral anti-hyperalgesia effects of acupuncture in mice inflammatory pain

Background  

Peripheral tissue inflammation initiates hyperalgesia accompanied by tissue acidosis, nociceptor activation, and inflammation mediators. Recent studies have suggested a significantly increased expression of acid-sensing ion channel 3 (ASIC3) in both carrageenan- and complete Freund's adjuvant (CFA)-induced inflammation. This study tested the hypothesis that acupuncture is curative for mechanical hyperalgesia induced by peripheral inflammation.     

Protein structure similarity from principle component correlation analysis

Background  

Owing to rapid expansion of protein structure databases in recent years, methods of structure comparison are becoming increasingly effective and important in revealing novel information on functional properties of proteins and their roles in the grand scheme of evolutionary biology. Currently, the structural similarity between two proteins is measured by the root-mean-square-deviation (RMSD) in their best-superimposed atomic coordinates. RMSD is the golden rule of measuring structural similarity when the structures are nearly identical; it, however, fails to detect the higher order topological similarities in proteins evolved into different shapes. We propose new algorithms for extracting geometrical invariants of proteins that can be effectively used to identify homologous protein structures or topologies in order to quantify both close and remote structural similarities.     

Conditional random pattern model for copy number aberration detection

Background  

DNA copy number aberration (CNA) is very important in the pathogenesis of tumors and other diseases. For example, CNAs may result in suppression of anti-oncogenes and activation of oncogenes, which would cause certain types of cancers. High density single nucleotide polymorphism (SNP) array data is widely used for the CNA detection. However, it is nontrivial to detect the CNA automatically because the signals obtained from high density SNP arrays often have low signal-to-noise ratio (SNR), which might be caused by whole genome amplification, mixtures of normal and tumor cells, experimental noise or other technical limitations. With the reduction in SNR, many false CNA regions are often detected and the true CNA regions are missed. Thus, more sophisticated statistical models are needed to make the CNAs detection, using the low SNR signals, more robust and reliable.     

The effect of n-3 long-chain polyunsaturated fatty acids and lipoic acid on the heart in the ovariectomized rat model of menopause

Menopause occurs as consequence of ovarian senescence that leads to a drop of oestrogen hormone. The decreased oestrogen levels combined with the impairment of the redox system may contribute to the increased risk of postmenopausal cardiovascular disease. Supplementation with antioxidants may be an alternative to reduce cardiovascular risk. The study evaluated the effect of dietary supplementation with docosahexaenoic acid (DHA), eicosapentaenoic acid (EPA), and α-lipoic acid (LA) for a period of 16 weeks on oxidative stress biomarkers in the hearts of ovariectomized 3-month-old rats. Ovariectomy did not increase the level of the damage markers malondialdehyde and carbonyl, and both were decreased by LA supplementation. Ovariectomy increased the levels of the endogenous antioxidants glutathione, vitamin C and H₂O₂ consumption, after restoration by DHA, EPA, and LA supplementation. Vitamin E, glutathione peroxidase, glutathione-S-transferase, and superoxide dismutase are not altered by ovariectomy. Lipid and protein damage are not increased after ovariectomy and a portion of the endogenous antioxidants concomitantly increased, suggesting that hearts may be protected by these antioxidants. DHA, EPA, and LA restored these endogenous antioxidants, showing that all evaluated supplements are effective in modulating the antioxidant redox system in the heart. LA showed additional effect on redox markers, decreasing lipid and protein damage markers.     

Semi-supervised drug-protein interaction prediction from heterogeneous biological spaces

Background

Predicting drug-protein interactions from heterogeneous biological data sources is a key step for in silico drug discovery. The difficulty of this prediction task lies in the rarity of known drug-protein interactions and myriad unknown interactions to be predicted. To meet this challenge, a manifold regularization semi-supervised learning method is presented to tackle this issue by using labeled and unlabeled information which often generates better results than using the labeled data alone. Furthermore, our semi-supervised learning method integrates known drug-protein interaction network information as well as chemical structure and genomic sequence data.

Results

Using the proposed method, we predicted certain drug-protein interactions on the enzyme, ion channel, GPCRs, and nuclear receptor data sets. Some of them are confirmed by the latest publicly available drug targets databases such as KEGG.

Conclusions

We report encouraging results of using our method for drug-protein interaction network reconstruction which may shed light on the molecular interaction inference and new uses of marketed drugs.