The Truncated Isoform of Somatostatin Receptor5 (sst5TMD4) Is Associated with Poorly Differentiated Thyroid Cancer

Somatostatin receptors (ssts) are expressed in thyroid cancer cells, but their biological significance is not well understood. The aim of this study was to assess ssts in well differentiated (WDTC) and poorly differentiated thyroid cancer (PDTC) by means of imaging and molecular tools and its relationship with the efficacy of somatostatin analog treatment. Thirty-nine cases of thyroid carcinoma were evaluated (20 PDTC and 19 WDTC). Depreotide scintigraphy and mRNA levels of sst-subtypes, including the truncated variant sst5TMD4, were carried out. Depreotide scans were positive in the recurrent tumor in the neck in 6 of 11 (54%) PDTC, and in those with lung metastases in 5/11 cases (45.4%); sst5TMD4 was present in 18/20 (90%) of PDTC, being the most densely expressed sst-subtype, with a 20-fold increase in relation to sst2. In WDTC, sst2 was the most represented, while sst5TMD4 was not found; sst2 was significantly increased in PDTC in comparison to WDTC. Five depreotide positive PDTC received octreotide for 3–6 months in a pilot study with no changes in the size of the lesions in 3 of them, and a significant increase in the pulmonary and cervical lesions in the other 2. All PDTC patients treated with octreotide showed high expression of sst5TMD4. ROC curve analysis demonstrated that only sst5TMD4 discriminates between PDTC and WDTC. We conclude that sst5TMD4 is overexpressed in PDTC and may be involved in the lack of response to somatostatin analogue treatment.     

HAPLOFREQ--estimating haplotype frequencies efficiently.

A commonly used tool in disease association studies is the search for discrepancies between the haplotype distribution in the case and control populations. In order to find this discrepancy, the haplotypes frequency in each of the populations is estimated from the genotypes. We present a new method HAPLOFREQ to estimate haplotype frequencies over a short genomic region given the genotypes or haplotypes with missing data or sequencing errors. Our approach incorporates a maximum likelihood model based on a simple random generative model which assumes that the genotypes are independently sampled from the population. We first show that if the phased haplotypes are given, possibly with missing data, we can estimate the frequency of the haplotypes in the population by finding the global optimum of the likelihood function in polynomial time. If the haplotypes are not phased, finding the maximum value of the likelihood function is NP-hard. In this case, we define an alternative likelihood function which can be thought of as a relaxed likelihood function. We show that the maximum relaxed likelihood can be found in polynomial time and that the optimal solution of the relaxed likelihood approaches asymptotically to the haplotype frequencies in the population. In contrast to previous approaches, our algorithms are guaranteed to converge in polynomial time to a global maximum of the different likelihood functions. We compared the performance of our algorithm to the widely used program PHASE, and we found that our estimates are at least 10% more accurate than PHASE and about ten times faster than PHASE. Our techniques involve new algorithms in convex optimization. These algorithms may be of independent interest. Particularly, they may be helpful in other maximum likelihood problems arising from survey sampling.     

Transport of reduced nicotinamide–adenine dinucleotide into mitochondria of rat white adipose tissue

Mitochondria from rat white adipose tissue were prepared, exhibiting good respiratory control and P/O ratios. They would not oxidize NADH unless NNN'N'-tetramethyl-p-phenylenediamine was added as a carrier of reducing equivalents. These mitochondria were found to oxidize neither l-glycerol 3-phosphate nor l-glutamate plus l-malate at significant rates. The activity of aspartate aminotransferase in these mitochondria was found to be low compared with that found in rat liver mitochondria. As a consequence of this, the adipose-tissue mitochondria exhibited very low rates of cytoplasmic NADH oxidation in a reconstituted Borst (1962) cycle compared with liver mitochondria.     

Rapid conditional targeted ablation of cells expressing human CD59 in transgenic mice by intermedilysin

Conditional targeted cell ablation is a powerful approach for investigating the pathogenesis of human diseases and in vivo cellular functions. Intermedilysin (ILY) is a cytolytic pore-forming toxin secreted by Streptococcus intermedius that lyses human cells exclusively, owing to its receptor specificity for human CD59. We generated two transgenic mouse strains that express human CD59 either on erythrocytes (strain ThCD59(RBC)) or on endothelia (strain ThCD59(END)). Intravenous injection of ILY in ThCD59(RBC) mice induced acute intravascular hemolysis, leading to reduced nitric oxide bioavailability, increased platelet activation and rapid death. In ThCD59(END) mice, ILY induced rapid endothelial damage, leading to acute death and disseminated intravascular coagulation. Additionally, we show that human serum contains ILY-specific neutralizing antibodies not found in any other animal species. Together, these results suggest that this new rapid conditional targeted ILY-mediated cell ablation technique can be used in combination with any available transgenic expression system to study the physiologic role of specific cell populations.     

Detection of Molecular Paths Associated with Insulitis and Type 1 Diabetes in Non-Obese Diabetic Mouse

Recent clinical evidence suggests important role of lipid and amino acid metabolism in early pre-autoimmune stages of type 1 diabetes pathogenesis. We study the molecular paths associated with the incidence of insulitis and type 1 diabetes in the Non-Obese Diabetic (NOD) mouse model using available gene expression data from the pancreatic tissue from young pre-diabetic mice. We apply a graph-theoretic approach by using a modified color coding algorithm to detect optimal molecular paths associated with specific phenotypes in an integrated biological network encompassing heterogeneous interaction data types. In agreement with our recent clinical findings, we identified a path downregulated in early insulitis involving dihydroxyacetone phosphate acyltransferase (DHAPAT), a key regulator of ether phospholipid synthesis. The pathway involving serine/threonine-protein phosphatase (PP2A), an upstream regulator of lipid metabolism and insulin secretion, was found upregulated in early insulitis. Our findings provide further evidence for an important role of lipid metabolism in early stages of type 1 diabetes pathogenesis, as well as suggest that such dysregulation of lipids and related increased oxidative stress can be tracked to beta cells.     

Rapid Sampling of Molecular Motions with Prior Information Constraints

Proteins are active, flexible machines that perform a range of different functions. Innovative experimental approaches may now provide limited partial information about conformational changes along motion pathways of proteins. There is therefore a need for computational approaches that can efficiently incorporate prior information into motion prediction schemes. In this paper, we present PathRover, a general setup designed for the integration of prior information into the motion planning algorithm of rapidly exploring random trees (RRT). Each suggested motion pathway comprises a sequence of low-energy clash-free conformations that satisfy an arbitrary number of prior information constraints. These constraints can be derived from experimental data or from expert intuition about the motion. The incorporation of prior information is very straightforward and significantly narrows down the vast search in the typically high-dimensional conformational space, leading to dramatic reduction in running time. To allow the use of state-of-the-art energy functions and conformational sampling, we have integrated this framework into Rosetta, an accurate protocol for diverse types of structural modeling. The suggested framework can serve as an effective complementary tool for molecular dynamics, Normal Mode Analysis, and other prevalent techniques for predicting motion in proteins. We applied our framework to three different model systems. We show that a limited set of experimentally motivated constraints may effectively bias the simulations toward diverse predicates in an outright fashion, from distance constraints to enforcement of loop closure. In particular, our analysis sheds light on mechanisms of protein domain swapping and on the role of different residues in the motion.