Fungi from Geothermal Soils in Yellowstone National Park

Geothermal soils near Amphitheater Springs in Yellowstone National Park were characterized by high temperatures (up to 70°C), high heavy metal content, low pH values (down to pH 2.7), sparse vegetation, and limited organic carbon. From these soils we cultured 16 fungal species. Two of these species were thermophilic, and six were thermotolerant. We cultured only three of these species from nearby cool (0 to 22°C) soils. Transect studies revealed that higher numbers of CFUs occurred in and below the root zone of the perennial plant Dichanthelium lanuginosum (hot springs panic grass). The dynamics of fungal CFUs in geothermal soil and nearby nongeothermal soil were investigated for 12 months by examining soil cores and in situ mesocosms. For all of the fungal species studied, the temperature of the soil from which the organisms were cultured corresponded with their optimum axenic growth temperature.     

Cell-IQ visualization of motility,cell mass,and osteogenic differentiation of multipotent mesenchymal stromal cells cultured with relief calcium phosphate coating

The Cell-IQ continuous surveillance system allowed us to establish the following changes in a 14- day culture in vitro: a twofold suppression of the directional migration of multipotent mesenchymal stromal cells of human adipose tissue (MMSC-AT) towards the samples with a microarc calcium phosphate (CP) coating from synthetic hydroxyapatite; a tenfold decrease in the cell mass on the interphase with the samples, which was accompanied by a slight reduction in the expression of membrane determinants of stromal stem cells; and an enhancement of their osteogenic differentiation (osteocalcin secretion and mineralized matrix formation) on the 21st day of the study. Calcium phosphate particles, but not the calcium and phosphorus ions, may trigger the phenotypic transformation of the MMSC-AT behavior in vitro.     

Organ transplantation in Bulgaria

The transplantation program in Bulgaria started in 1968 with renal transplantations to a child and adult woman. In 1986 the first heart transplantation was performed. To date a total of 10 heart transplants have been performed, including one combined heart/lung. A liver transplantation program was launched in 2005 with a total number of 16 transplantations—7 from living donors and 9 from deceased donors. The highest transplantation activity is registered in the field of renal transplantation. During the period 1980–2006, 462 Bulgarian recipients of kidney were transplanted in Bulgaria. The ratio between transplantations from deceased and living related donors is approximately 1:0.9. Annual transplantation activity varies among the years from 1 to 12 renal transplantations p.m.p./per year. The 1- (80.7% vs. 63.1%), 5- (57.86% vs. 39.0%) and 10-year (42.65% vs. 23.62%) graft survival rates are higher for recipients of living donor kidneys compared to those of deceased donor. In 1983 a National kidney waiting list was established. Currently the number of the registered patients eligible for renal transplantation is 885. The proportion of sensitized patients in the waiting list is 20.45% and 4.34% of them are hyperimmunized. Recently HLAMatchmaker program has been implemented not only for sensitized patients but also for those with rare alleles and haplotypes. Post-transplant immunological monitoring showed a strong association between alloantibody presence and delayed graft function (Chi-square = 10.73, P < 0.001), acute rejection (Chi-square = 14.504, P < 0.001), chronic rejection (Chi-square = 12.84, P < 0.001) and graft loss (Chi-square = 20.283, P < 0.001). Based on the experience in our transplant center a strategy for improvement of long-term renal graft survival was developed and implemented.     

FGF signaling preserves the integrity of endothelial adherens junctions

Fibroblast growth factor (FGF)-activated signaling regulates an array of cellular processes ranging from embryonic development to tissue repair. A recent paper by Murakami et al. identifies a potentially important role for FGF signaling in maintenance of endothelial barrier homeostasis through the regulation of adherens junctions.     

Novel nuclear-encoded subunits of the chloroplast NAD(P)H dehydrogenase complex

The NAD(P)H dehydrogenase (NDH) complex functions in photosystem I cyclic electron transfer in higher plant chloroplasts and is crucial for plant responses to environmental stress. Chloroplast NDH complex is a close relative to cyanobacterial NDH-1L complex, and all fifteen subunits so far identified in NDH-1L have homologs in the chloroplast NDH complex. Here we report on the identification of two nuclear-encoded proteins NDH48 and NDH45 in higher plant chloroplasts and show their intimate association with the NDH complex. These two membrane proteins are shown to interact with each other and with the NDH complex enriched in stroma thylakoids. Moreover, the deficiency of either the NDH45 protein or the NDH48 protein in respective mutant plants leads to severe defects in both the accumulation and the function of the NDH complex. The NDH48 and NDH45 proteins are not components of the hydrophilic connecting domain of the NDH complex but are strongly attached to the hydrophobic membrane domain. We conclude that NDH48 and NDH45 are novel nuclear-encoded subunits of the chloroplast NDH complex and crucial both for the stable structure and function of the NDH complex.     

NLStradamus: a simple Hidden Markov Model for nuclear localization signal prediction

Background  

Nuclear localization signals (NLSs) are stretches of residues within a protein that are important for the regulated nuclear import of the protein. Of the many import pathways that exist in yeast, the best characterized is termed the 'classical' NLS pathway. The classical NLS contains specific patterns of basic residues and computational methods have been designed to predict the location of these motifs on proteins. The consensus sequences, or patterns, for the other import pathways are less well-understood.     

Combination of Two but Not Three Current Targeted Drugs Can Improve Therapy of Chronic Myeloid Leukemia

Chronic myeloid leukemia (CML) is a cancer of the hematopoietic system and has been treated with the drug Imatinib relatively successfully. Drug resistance, acquired by mutations, is an obstacle to success. Two additional drugs are now considered and could be combined with Imatinib to prevent resistance, Dasatinib and Nilotinib. While most mutations conferring resistance to one drug do not confer resistance to the other drugs, there is one mutation (T315I) that induces resistance against all three drugs. Using computational methods, the combination of two drugs is found to increase the probability of treatment success despite this cross-resistance. Combining more than two drugs, however, does not provide further advantages. We also explore possible combination therapies using drugs currently under development. We conclude that among the targeted drugs currently available for the treamtent of CML, only the two most effective ones should be used in combination for the prevention of drug resistance.     

Optimizing Combination Therapies with Existing and Future CML Drugs

Small-molecule inhibitors imatinib, dasatinib and nilotinib have been developed to treat Chromic Myeloid Leukemia (CML). The existence of a triple-cross-resistant mutation, T315I, has been a challenging problem, which can be overcome by finding new inhibitors. Many new compounds active against T315I mutants are now at different stages of development. In this paper we develop an algorithm which can weigh different combination treatment protocols according to their cross-resistance properties, and find the protocols with the highest probability of treatment success. This algorithm also takes into account drug toxicity by minimizing the number of drugs used, and their concentration. Although our methodology is based on a stochastic model of CML microevolution, the algorithm itself does not require measurements of any parameters (such as mutation rates, or division/death rates of cells), and can be used by medical professionals without a mathematical background. For illustration, we apply this algorithm to the mutation data obtained in [1], [2].