High-Grade Osteosarcoma of the Foot: Presentation, Treatment, Prognostic Factors, and Outcome of 23 Cooperative Osteosarcoma Study Group COSS Patients

Osteosarcoma of the foot is a very rare presentation of a rare tumor entity. In a retrospective analysis, we investigated tumor- and treatment-related variables and outcome of patients registered in the Cooperative Osteosarcoma Study Group (COSS) database between January 1980 and April 2016 who suffered from primary high-grade osteosarcoma of the foot. Among the 23 eligible patients, median age was 32 years (range: 6-58 years), 10 were female, and 13 were male. The tarsus was the most commonly affected site (n=16). Three patients had primary metastases. All patients were operated: 5 underwent primary surgery and 18 received surgery following preoperative chemotherapy. In 21 of the 23 patients, complete surgical remission was achieved. In 4 of 17 patients, a poor response to neoadjuvant chemotherapy was observed in the resected primary tumors. Median follow-up was 4.2 years (range: 0.4-18.5). At the last follow-up, 15 of the 23 patients were alive and 8 had died. Five-year overall and event-free survival estimates were 64% (standard error (SE) 12%) and 54% (SE 13%), which is similar to that observed for osteosarcoma in general. Event-free and overall survival correlated with primary metastatic status and completeness of surgery. Our findings show that high-grade osteosarcoma in the foot has a similar outcome as osteosarcoma of other sites

Understanding the Adaptive Growth Strategy of Lactobacillus plantarum by In Silico Optimisation

In the study of metabolic networks, optimization techniques are often used to predict flux distributions, and hence, metabolic phenotype. Flux balance analysis in particular has been successful in predicting metabolic phenotypes. However, an inherent limitation of a stoichiometric approach such as flux balance analysis is that it can predict only flux distributions that result in maximal yields. Hence, previous attempts to use FBA to predict metabolic fluxes in Lactobacillus plantarum failed, as this lactic acid bacterium produces lactate, even under glucose-limited chemostat conditions, where FBA predicted mixed acid fermentation as an alternative pathway leading to a higher yield. In this study we tested, however, whether long-term adaptation on an unusual and poor carbon source (for this bacterium) would select for mutants with optimal biomass yields. We have therefore adapted Lactobacillus plantarum to grow well on glycerol as its main growth substrate. After prolonged serial dilutions, the growth yield and corresponding fluxes were compared to in silico predictions. Surprisingly, the organism still produced mainly lactate, which was corroborated by FBA to indeed be optimal. To understand these results, constraint-based elementary flux mode analysis was developed that predicted 3 out of 2669 possible flux modes to be optimal under the experimental conditions. These optimal pathways corresponded very closely to the experimentally observed fluxes and explained lactate formation as the result of competition for oxygen by the other flux modes. Hence, these results provide thorough understanding of adaptive evolution, allowing in silico predictions of the resulting flux states, provided that the selective growth conditions favor yield optimization as the winning strategy

Approaching the ideal elastic limit of metallic glasses

The ideal elastic limit is the upper bound to the stress and elastic strain a material can withstand. This intrinsic property has been widely studied for crystalline metals, both theoretically and experimentally. For metallic glasses, however, the ideal elastic limit remains poorly characterized and understood. Here we show that the elastic strain limit and the corresponding strength of submicron-sized metallic glass specimens are about twice as high as the already impressive elastic limit observed in bulk metallic glass samples, in line with model predictions of the ideal elastic limit of metallic glasses. We achieve this by employing an in situ transmission electron microscope tensile deformation technique. Furthermore, we propose an alternative mechanism for the apparent 'work hardening' behaviour observed in the tensile stress–strain curves

Spontaneous Reaction Silencing in Metabolic Optimization

Metabolic reactions of single-cell organisms are routinely observed to become dispensable or even incapable of carrying activity under certain circumstances. Yet, the mechanisms as well as the range of conditions and phenotypes associated with this behavior remain very poorly understood. Here we predict computationally and analytically that any organism evolving to maximize growth rate, ATP production, or any other linear function of metabolic fluxes tends to significantly reduce the number of active metabolic reactions compared to typical non-optimal states. The reduced number appears to be constant across the microbial species studied and just slightly larger than the minimum number required for the organism to grow at all. We show that this massive spontaneous reaction silencing is triggered by the irreversibility of a large fraction of the metabolic reactions and propagates through the network as a cascade of inactivity. Our results help explain existing experimental data on intracellular flux measurements and the usage of latent pathways, shedding new light on microbial evolution, robustness, and versatility for the execution of specific biochemical tasks. In particular, the identification of optimal reaction activity provides rigorous ground for an intriguing knockout-based method recently proposed for the synthetic recovery of metabolic function.Comment: 34 pages, 6 figure

Secluded Dark Matter Coupled to a Hidden CFT

Models of secluded dark matter offer a variant on the standard WIMP picture and can modify our expectations for hidden sector phenomenology and detection. In this work we extend a minimal model of secluded dark matter, comprised of a U(1)'-charged dark matter candidate, to include a confining hidden-sector CFT. This provides a technically natural explanation for the hierarchically small mediator-scale, with hidden-sector confinement generating m_{gamma'}>0. Furthermore, the thermal history of the universe can differ markedly from the WIMP picture due to (i) new annihilation channels, (ii) a (potentially) large number of hidden-sector degrees of freedom, and (iii) a hidden-sector phase transition at temperatures T << M_{dm} after freeze out. The mediator allows both the dark matter and the Standard Model to communicate with the CFT, thus modifying the low-energy phenomenology and cosmic-ray signals from the secluded sector.Comment: ~50p, 8 figs; v2 JHEP versio

On the Accessibility of Adaptive Phenotypes of a Bacterial Metabolic Network

The mechanisms by which adaptive phenotypes spread within an evolving population after their emergence are understood fairly well. Much less is known about the factors that influence the evolutionary accessibility of such phenotypes, a pre-requisite for their emergence in a population. Here, we investigate the influence of environmental quality on the accessibility of adaptive phenotypes of Escherichia coli's central metabolic network. We used an established flux-balance model of metabolism as the basis for a genotype-phenotype map (GPM). We quantified the effects of seven qualitatively different environments (corresponding to both carbohydrate and gluconeogenic metabolic substrates) on the structure of this GPM. We found that the GPM has a more rugged structure in qualitatively poorer environments, suggesting that adaptive phenotypes could be intrinsically less accessible in such environments. Nevertheless, on average ∼74% of the genotype can be altered by neutral drift, in the environment where the GPM is most rugged; this could allow evolving populations to circumvent such ruggedness. Furthermore, we found that the normalized mutual information (NMI) of genotype differences relative to phenotype differences, which measures the GPM's capacity to transmit information about phenotype differences, is positively correlated with (simulation-based) estimates of the accessibility of adaptive phenotypes in different environments. These results are consistent with the predictions of a simple analytic theory that makes explicit the relationship between the NMI and the speed of adaptation. The results suggest an intuitive information-theoretic principle for evolutionary adaptation; adaptation could be faster in environments where the GPM has a greater capacity to transmit information about phenotype differences. More generally, our results provide insight into fundamental environment-specific differences in the accessibility of adaptive phenotypes, and they suggest opportunities for research at the interface between information theory and evolutionary biology

Single feature polymorphisms (SFPs) for drought tolerance in pigeonpea (Cajanus spp.)

Single feature polymorphisms (SFPs) are microarray-based molecular markers that are detected by hybridization of DNA or cRNA to oligonucleotide probes. With an objective to identify the potential polymorphic markers for drought tolerance in pigeonpea [Cajanus cajan (L.) Millspaugh], an important legume crop for the semi-arid tropics but deficient in genomic resources, Affymetrix Genome Arrays of soybean (Glycine max), a closely related species of pigeonpea were used on cRNA of six parental genotypes of three mapping populations of pigeonpea segregating for agronomic traits like drought tolerance and pod borer (Helicoverpa armigiera) resistance. By using robustified projection pursuit method on 15 pair-wise comparisons for the six parental genotypes, 5,692 SFPs were identified. Number of SFPs varied from 780 (ICPL 8755 × ICPL 227) to 854 (ICPL 151 × ICPL 87) per parental combination of the mapping populations. Randomly selected 179 SFPs were used for validation by Sanger sequencing and good quality sequence data were obtained for 99 genes of which 75 genes showed sequence polymorphisms. While associating the sequence polymorphisms with SFPs detected, true positives were observed for 52.6% SFPs detected. In terms of parental combinations of the mapping populations, occurrence of true positives was 34.48% for ICPL 151 × ICPL 87, 41.86% for ICPL 8755 × ICPL 227, and 81.58% for ICP 28 × ICPW 94. In addition, a set of 139 candidate genes that may be associated with drought tolerance has been identified based on gene ontology analysis of the homologous pigeonpea genes to the soybean genes that detected SFPs between the parents of the mapping populations segregating for drought tolerance

Inhibition of Monkeypox virus replication by RNA interference

The Orthopoxvirus genus of Poxviridae family is comprised of several human pathogens, including cowpox (CPXV), Vaccinia (VACV), monkeypox (MPV) and Variola (VARV) viruses. Species of this virus genus cause human diseases with various severities and outcome ranging from mild conditions to death in fulminating cases. Currently, vaccination is the only protective measure against infection with these viruses and no licensed antiviral drug therapy is available. In this study, we investigated the potential of RNA interference pathway (RNAi) as a therapeutic approach for orthopox virus infections using MPV as a model. Based on genome-wide expression studies and bioinformatic analysis, we selected 12 viral genes and targeted them by small interference RNA (siRNA). Forty-eight siRNA constructs were developed and evaluated in vitro for their ability to inhibit viral replication. Two genes, each targeted with four different siRNA constructs in one pool, were limiting to viral replication. Seven siRNA constructs from these two pools, targeting either an essential gene for viral replication (A6R) or an important gene in viral entry (E8L), inhibited viral replication in cell culture by 65-95% with no apparent cytotoxicity. Further analysis with wild-type and recombinant MPV expressing green fluorescence protein demonstrated that one of these constructs, siA6-a, was the most potent and inhibited viral replication for up to 7 days at a concentration of 10 nM. These results emphasis the essential role of A6R gene in viral replication, and demonstrate the potential of RNAi as a therapeutic approach for developing oligonucleotide-based drug therapy for MPV and other orthopox viruses

Landscape Encodings Enhance Optimization

Hard combinatorial optimization problems deal with the search for the minimum cost solutions (ground states) of discrete systems under strong constraints. A transformation of state variables may enhance computational tractability. It has been argued that these state encodings are to be chosen invertible to retain the original size of the state space. Here we show how redundant non-invertible encodings enhance optimization by enriching the density of low-energy states. In addition, smooth landscapes may be established on encoded state spaces to guide local search dynamics towards the ground state