Proteomic signatures corresponding to histological classification and grading of soft-tissue sarcomas

We performed a global protein expression study on soft-tissue sarcoma in order to develop novel diagnostic biomarkers and allow molecular classification. 2-D difference gel electrophoresis was used to generate the global protein expression profiles of 80 soft-tissue sarcoma samples with seven different histological backgrounds. We found that 67 protein spots distinguished the subtypes of soft-tissue sarcoma. Hierarchical clustering with these 67 protein spots resulted in the grouping of all 80 sarcoma samples corresponding to the histological classification. We found that the expression pattern of tropomyosin isoforms was different in conventional and pleomorphic leiomyosarcomas. We also identified five proteins, including alpha-1-antitrypsin, alpha-actinin 1, HSP27, and elongation factor 2, that could differentiate between malignant fibrous histiocytomas and leiomyosarcomas in grade III into low-risk and high-risk groups, which differed significantly with respect to survival. These results establish proteomics as a powerful tool to develop novel biomarkers for diagnosis and molecular classification of soft-tissue sarcomas. Identification of proteins associated with survival in grade III sarcoma will allow delineation of a high-risk group that may benefit from adjuvant therapy and the exclusion of low-risk patients in whom additional therapies are unlikely to exhibit clinical benefit.     

Map Misclassification Can Cause Large Errors in Landscape Pattern Indices: Examples from Habitat Fragmentation

Although habitat fragmentation is one of the greatest threats to biodiversity worldwide, virtually no attention has been paid to the quantification of error in fragmentation statistics. Landscape pattern indices (LPIs), such as mean patch size and number of patches, are routinely used to quantify fragmentation and are often calculated using remote-sensing imagery that has been classified into different land-cover classes. No classified map is ever completely correct, so we asked if different maps with similar misclassification rates could result in widely different errors in pattern indices. We simulated landscapes with varying proportions of habitat and clumpiness (autocorrelation) and then simulated classification errors on the same maps. We simulated higher misclassification at patch edges (as is often observed), and then used a smoothing algorithm routinely used on images to correct salt-and-pepper classification error. We determined how well classification errors (and smoothing) corresponded to errors seen in four pattern indices. Maps with low misclassification rates often yielded errors in LPIs of much larger magnitude and substantial variability. Although smoothing usually improved classification error, it sometimes increased LPI error and reversed the direction of error in LPIs introduced by misclassification. Our results show that classification error is not always a good predictor of errors in LPIs, and some types of image postprocessing (for example, smoothing) might result in the underestimation of habitat fragmentation. Furthermore, our results suggest that there is potential for large errors in nearly every landscape pattern analysis ever published, because virtually none quantify the errors in LPIs themselves.     

Application and evaluation of classification trees for screening unwanted plants

Abstract Risk assessment systems for introduced species are being developed and applied globally, but methods for rigorously evaluating them are still in their infancy. We explore classification and regression tree models as an alternative to the current Australian Weed Risk Assessment system, and demonstrate how the performance of screening tests for unwanted alien species may be quantitatively compared using receiver operating characteristic (ROC) curve analysis. The optimal classification tree model for predicting weediness included just four out of a possible 44 attributes of introduced plants examined, namely: (i) intentional human dispersal of propagules; (ii) evidence of naturalization beyond native range; (iii) evidence of being a weed elsewhere; and (iv) a high level of domestication. Intentional human dispersal of propagules in combination with evidence of naturalization beyond a plants native range led to the strongest prediction of weediness. A high level of domestication in combination with no evidence of naturalization mitigated the likelihood of an introduced plant becoming a weed resulting from intentional human dispersal of propagules. Unlikely intentional human dispersal of propagules combined with no evidence of being a weed elsewhere led to the lowest predicted probability of weediness. The failure to include intrinsic plant attributes in the model suggests that either these attributes are not useful general predictors of weediness, or data and analysis were inadequate to elucidate the underlying relationship(s). This concurs with the historical pessimism that we will ever be able to accurately predict invasive plants. Given the apparent importance of propagule pressure (the number of individuals of an species released), future attempts at evaluating screening model performance for identifying unwanted plants need to account for propagule pressure when collating and/or analysing datasets. The classification tree had a cross‐validated sensitivity of 93.6% and specificity of 36.7%. Based on the area under the ROC curve, the performance of the classification tree in correctly classifying plants as weeds or non‐weeds was slightly inferior (Area under ROC curve = 0.83 ± 0.021 (±SE)) to that of the current risk assessment system in use (Area under ROC curve = 0.89 ± 0.018 (±SE)), although requires many fewer questions to be answered.     

Sensitivity of African biomes to changes in the precipitation regime

Aim Africa is identified by the Inter‐governmental Panel on Climate Change (IPCC) as the least studied continent in terms of ecosystem dynamics and climate variability. The aim of this study was (1) to adapt the Lund‐Postdam‐Jena‐GUESS (LPJ‐GUESS) ecological modelling framework to Africa by providing new parameter values for tropical plant functional types (PFT), and (2) to assess the sensitivity of some African biomes to changes in precipitation regime. Location The study area was a representative transect (0–22° N and 7–18° E) through the transition from equatorial evergreen forests to savannas, steppes and desert northwards. The transect showed large latitudinal variation in precipitation (mean rainfall ranged from 50 to 2300 mm year^?1). Methods New PFT parameters used to calibrate LPJ‐GUESS were based on modern pollen PFTs and remote sensed leaf area index (LAI). The model was validated using independent modern pollen assemblages, LAI and through comparison with White's modern potential vegetation map. Several scenarios were developed by combining changes in total rainfall amount with variation in the length of the dry season in order to test the sensitivity of African biomes. Results Simulated vegetation compared well to observed data at local and regional scales, in terms of ecosystem functioning (LAI), and composition (pollen and White's vegetation map). The assessment of the sensitivity of biomes to changes in precipitation showed that none of the ecosystems would shift towards a new type under the range of precipitation increases suggested by the IPCC (increases from 5 to 20%). However, deciduous and semi‐deciduous forests may be very sensitive to small reductions in both the amount and seasonality of precipitation. Main conclusions This version of LPJ‐GUESS parameterized for Africa simulated correctly the vegetation present over a wide precipitation gradient. The biome sensitivity assessment showed that, compared with savannas and grasslands, closed canopy forests may be more sensitive to change in precipitation regime due to the synergetic effects of changed rainfall amounts and seasonality on vegetation functioning.     

Differential effects of egg albumen content on barn swallow nestlings in relation to hatch order

In diverse animal taxa, egg mass variation mediates maternal effects with long-term consequences for offspring ontogeny and fitness. Patterns of egg mass variation with laying order differ considerably among birds, but no study has experimentally investigated the function of variation in albumen or yolk egg content in the wild. In barn swallows (Hirundo rustica), absolute and relative albumen mass increased with egg laying order. Experimental albumen removal delayed hatching, had larger negative effects on growth of late-hatched nestlings, and reduced nestling survival. Laying order positively predicted hatch order. Because nestling competitive ability depends on size, and albumen egg content influences hatchling size, present results suggest that by increasing albumen content of late eggs mothers reduce hatching asynchrony and enhance growth particularly of late-hatched nestlings. Thus, variation in albumen mass with laying order may function to mitigate the negative phenotypic consequences of hatching late in species that adopt a 'brood-survival' strategy.     

Early maternal, genetic and environmental components of antioxidant protection, morphology and immunity of yellow-legged gull (Larus michahellis) chicks

Maternal effects mediated by egg quality are important sources of offspring phenotypic variation and can influence the course of evolutionary processes. Mothers allocate to the eggs diverse antioxidants that protect the embryo from oxidative stress. In the yellow-legged gull (Larus michahellis), yolk antioxidant capacity varied markedly among clutches and declined considerably with egg laying date. Analysis of bioptic yolk samples from clutches that were subsequently partially cross-fostered revealed a positive effect of yolk antioxidant capacity on embryonic development and chick growth, but not on immunity and begging behaviour, while controlling for parentage and common environment effects. Chick plasma antioxidant capacity varied according to rearing environment, after statistically partitioning out maternal influences mediated by egg quality. Thus, the results of this study indicate that egg antioxidants are important mediators of maternal effects also in wild bird populations, especially during the critical early post-hatching phase.     

Protein sequences of linked genes are highly conserved in two bacterial species

It has been shown that proteins encoded by linked genes have similar rates of evolution and that clusters of essential genes are found in regions with low recombination rates. We show here that proteins encoded by linked genes in two closely related bacterial species, namely Escherichia coli K12 and Salmonella typhimurium LT2, evolve more slowly when compared with proteins encoded by genes that are not linked as assessed by protein sequence similarity. The proteins encoded by the identified linked genes share an average sequence identity of 82.5% compared with a 46.5% identity of proteins encoded by genes that are not linked.     

Maternal allocation of androgens and antagonistic effects of yolk androgens on sons and daughters

Mothers can influence the phenotype of their offspring by adjustingthe quality of their eggs in relation to sex and reproductivevalue of the progeny. Maternal androgens in the eggs of vertebratesmay mediate such adaptive early maternal effects. However, theevolution of early maternal effects mediated by egg androgensmay be constrained by the inability of mothers to differentiallyallocate androgens to eggs with a male or a female if androgenshave different effects on sons and daughters. In this study,we increased the concentration of androgens in the eggs of barnswallows (Hirundo rustica) within the physiological range ofvariation and analyzed the effect on nestling growth and beggingbehavior. Egg androgens increased body size and mass of sonsbut reduced these characters in daughters when compared to twocontrol groups in a repeated-measures analysis of variance ofdata collected at different ages. However, the differentialeffect of androgen on the two sexes was no longer significantwhen the analysis was restricted to the age of 12 days, whenfinal body size is attained. In a second experiment, we testedwhether mothers differentially allocated androgens to eggs withsons rather than daughters while manipulating a paternal secondarysexual character. Androgen concentration did not vary in relationto paternal ornamentation or embryo sex. Hence, antagonisticeffects of egg androgens on sons and daughters may exist inthe very early posthatching life and may constrain the evolutionof adaptive maternal effects because mothers do not differentiallyallocate androgens in relation to embryo sex.     

Protoanthropoidea (Primates, Simiiformes): A New Primate Higher Taxon and a Solution to the Rooneyia Problem

As a derivative of the hypothesis that anthropoids evolved from omomyid-like primates, the enigmatic North American fossil Rooneyia viejaensis, from the latest Eocene of Texas, is placed in a new higher taxon, Protoanthropoidea, which is proposed as the sister-group of Anthropoidea. Rooneyia and anthropoids share synapomorphically a pattern of character states relating to the unique orbital morphology of higher primates, including; highly convergent and frontated orbits roofed above by an extended frontal bone; funnel-shaped orbital fossae; orbital apices that are recessed beneath the forebrain; a deep, large lateral process of the frontal bone (upper portion of the postorbital bar) that may presage closure of the orbit by an enlarged ascending process of the zygomatic. If the sister-group of anthropoids occupied North America as part of a Laurasian geographic distribution during the Paleogene, as some primate genera did, ancestral anthropoids may likewise have occurred across Laurasia, prestaging them to enter Africa and Central/South America in two independent episodes of dispersal—without having the ancestral platyrrhines crossing the daunting Atlantic Ocean.     

Definition of grassland biomes from phytoliths in West Africa

Aim In order to enhance the effectiveness of comparisons between modelled and empirical data for present and past vegetation, it is important to improve the characterization of tropical grass‐dominated biomes reconstructed from fossil tracers. This study presents a method for assigning phytolith assemblages to tropical grass‐dominated biomes, with the objective of offering a new tool for combining pollen and phytolith data in the reconstruction of tropical biomes. Location The West African latitudinal transect studied here extends from 12° N (southern Senegal) to 23° N (southern Mauritania), passing through the Guinean, Sudanian, Sahelian and Saharan bioclimatic zones. Methods Modern phytolith assemblages were extracted from 59 soil surface samples taken throughout the study area and allocated, a priori, to three current biomes: (1) desert C₄ grassland, (2) short grass savanna, and (3) tall grass savanna. Five out of nine phytolith types identified were used as predictors in a discriminant analysis (with calibration and validation steps) for assigning phytolith assemblages to biomes. In addition, 74 modern pollen spectra from the West African transect, acquired from the African Pollen Database ( http://medias.obs‐mip.fr/apd ), were processed by the biomization method. This mathematical procedure involves assigning palynological taxa to one or more plant functional types, which represent broad classes of plants. The plant functional types, in turn, are combined to define biomes following a specific set of algorithms and rules. The resulting maps of the phytolith biomes thus derived were compared with maps of pollen biomes and of contemporary ecosystem classes. Results In the calibration and validation steps, 91.5% and up to 83%, respectively, of the phytolith samples were assigned to the correct biome. The short grass savanna and tall grass savanna biomes were assigned with similar accuracy by both the phytolith and pollen biomization methods, but the phytolith method gave substantially superior results for the desert C₄ grassland biome, providing seven out of seven correct assignments, compared with just one out of four by pollen biomization. Comparisons between an existing ecosystem map and the maps created from phytolith estimation showed close correspondence for desert C₄ grassland, short grass savanna and tall grass savanna, the latter providing correct assignments in 88, 62 and 91% of cases, respectively. Main conclusions The phytolith discriminant analysis method presented here accurately estimates three C₄ grass‐dominated biomes that are widespread in West Africa. Complementarities between the phytolith method and pollen biomization are highlighted. Combining complementary phytolith and pollen data would provide more accurate assignments of C₄ grass‐dominated biomes than pollen biomization alone.