Aggressive chemotherapy in adult primary myelodysplastic syndromes. A report on 29 cases

Twenty-nine adult patients with primary myelodysplastic syndromes (MDS) and an excess of marrow blasts were treated by aggressive chemotherapy while still in MDS phase (20 cases) or after progression to ANLL (9 cases). Median age was 47.5 (range 18-68). Twenty-eight patients received a combination of Rubidazone and Ara C and 1 received High dose Ara C. Fourteen patients (48%) achieved complete remission (CR), 5 (17%) were treatment failures (F) and 10 (35%) died during therapy induced aplasia (DA). Median disease free survival was 8.5 months. Median survival of the whole population was 6 months from the onset of treatment, and 17 months in patients achieving CR. These results were significantly less favorable than those obtained at our institution in de novo ANLL with the same chemotherapy regimens. No statistically significant prognostic factors of treatment outcome emerged but patients with normal cytogenetic findings seemed to have both a higher CR rate and longer remissions than patients with abnormal karyotypes. Patients under 50 did not have higher CR rates than older patients, although they had longer remissions (with 3 out of 6 CRs exceeding 2 years). Finally, treatment outcome and survival were identical in patients treated in the MDS phase and in those treated after progression to ANLL. Combination chemotherapy is a highly toxic approach in MDS and essentially seems to benefit younger patients with a normal karyotype, in whom some long remissions can be obtained.     

Century‐long apparent decrease in intrinsic water‐use efficiency with no evidence of progressive nutrient limitation in African tropical forests

Forests exhibit leaf‐ and ecosystem‐level responses to environmental changes. Specifically, rising carbon dioxide (CO₂) levels over the past century are expected to have increased the intrinsic water‐use efficiency (iWUE) of tropical trees while the ecosystem is gradually pushed into progressive nutrient limitation. Due to the long‐term character of these changes, however, observational datasets to validate both paradigms are limited in space and time. In this study, we used a unique herbarium record to go back nearly a century and show that despite the rise in CO₂ concentrations, iWUE has decreased in central African tropical trees in the Congo Basin. Although we find evidence that points to leaf‐level adaptation to increasing CO₂—that is, increasing photosynthesis‐related nutrients and decreasing maximum stomatal conductance, a decrease in leaf δ¹³C clearly indicates a decreasing iWUE over time. Additionally, the stoichiometric carbon to nitrogen and nitrogen to phosphorus ratios in the leaves show no sign of progressive nutrient limitation as they have remained constant since 1938, which suggests that nutrients have not increasingly limited productivity in this biome. Altogether, the data suggest that other environmental factors, such as increasing temperature, might have negatively affected net photosynthesis and consequently downregulated the iWUE. Results from this study reveal that the second largest tropical forest on Earth has responded differently to recent environmental changes than expected, highlighting the need for further on‐ground monitoring in the Congo Basin.     

Liana communities exhibit different species composition,diversity and community structure across forest types in the Congo Basin

Lianas are poorly characterized for central African forests. We quantify variation in liana composition, diversity and community structure in different forest types in the Yangambi Man and Biosphere Reserve, Democratic Republic of Congo. These attributes of liana assemblages were examined in 12 1-ha plots, randomly demarcated within regrowth forest, old growth monodominant forest, old growth mixed forest and old growth edge forest. Using a combination of multivariate and univariate community analyses, we visualize the patterns of these liana assemblage attributes and/or test for their significant differences across forest types. The combined 12 1-ha area contains 2,638 lianas (≥2 cm diameter) representing 105 species, 49 genera and 22 families. Liana species composition differed significantly across forest types. Taxonomic diversity was higher in old growth mixed forests compared to old growth monodominant and regrowth forests. Trait diversity was higher than expected in the regrowth forest as opposed to the rest of forest types. Similarly, the regrowth forest differed from the rest of forest types in the pattern of liana species ecological traits and diameter frequency distribution. The regrowth forest was also less densely populated in lianas and had lower liana total basal area than the rest of forest types. We speculate that the mechanism of liana competitive exclusion by dominant tree species is mainly responsible for the lower liana species diversity in monodominant compared to mixed forests. We attribute variation in liana community structure between regrowth and old growth forests mostly to short development time of size hierarchies.     

Macrophage elastase (MMP-12) in expanding murine adipose tissue

Background

Matrix metalloproteinases (MMPs) are known to play a role in adipose tissue development, but little information is available on the role of individual proteinases. Expansion of adipose tissue is associated with an increased macrophage content. Macrophage elastase (MMP-12) has an important role in macrophage infiltration, which induces pro-inflammatory effects in adipose tissue.

Methods

The role of MMP-12 was investigated in adipose tissues of MMP-12 deficient and wild-type control mice kept on normal chow or on high fat diet for 15 weeks.

Results

MMP-12 deficiency had no significant effect on total body weight or on subcutaneous (SC) or gonadal (GON) adipose tissue mass. Adipocyte and blood vessel size and density in SC and GON adipose tissues of obese mice were also comparable in MMP-12 deficient and control mice. Macrophage infiltration in SC and GON adipose tissues was not affected by MMP-12 deficiency, but the amount of crown-like structures (CLS) was significantly lower. MMP-12 deficiency did not affect elastin content in the extracellular matrix of SC or GON adipose tissue.

Conclusions

Adipose tissue mass and composition in mice with nutritionally induced obesity was not markedly affected by MMP-12 deficiency, except for an apparently lower degree of CLS.

General Significance

MMP-12 does not seem to be essential for macrophage infiltration in adipose tissue, but contributes to the formation of CLS surrounding moribund adipocytes.     

Towards a new classification of the giant paraphyletic genus Cyperus (Cyperaceae): phylogenetic relationships and generic delimitation in C4 Cyperus

Maximum likelihood and Bayesian inference analyses of nuclear ribosomal DNA (ETS1f) and plastid DNA (rpl32‐trnL, trnH‐psbA) sequence data are presented for ‘C₄ Cyperus’ (Cyperaceae). The term ‘C₄ Cyperus’ encompasses all species of Cyperus s.l. that use C₄ photosynthesis linked with chlorocyperoid vegetative anatomy. Sampling comprises 107 specimens of 104 different taxa, including many of the subdivisions of C₄ Cyperus s.s. and all C₄ segregate genera (Alinula, Ascolepis, Kyllinga, Lipocarpha, Pycreus, Queenslandiella, Remirea, Sphaerocyperus and Volkiella). According to our results, C₄ Cyperus is a well‐supported monophyletic clade nested in C₃ Cyperus. Despite the lack of resolution along the backbone of the C₄ Cyperus clade and for some internal branches, several well‐supported clades can be distinguished. The first clade in C₄ Cyperus is formed by Cyperus cuspidatus and C. waterloti. Other recognizable and well‐supported clades correspond to segregate genera, i.e. Ascolepis, Lipocarpha including Volkiella, and Kyllinga. Species of C₄ Cyperus s.s. form a core grade in which the C₄ segregate genera are embedded. Pycreus, the largest segregate genus composed of c. 120 species, is not monophyletic as it includes several C₄ species of Cyperus s.s. This study establishes a phylogenetic framework for revising the classification and character evolution in Cyperus s.l. © 2013 The Linnean Society of London     

Relating Phylogenetic Trees to Transmission Trees of Infectious Disease Outbreaks

Transmission events are the fundamental building blocks of the dynamics of any infectious disease. Much about the epidemiology of a disease can be learned when these individual transmission events are known or can be estimated. Such estimations are difficult and generally feasible only when detailed epidemiological data are available. The genealogy estimated from genetic sequences of sampled pathogens is another rich source of information on transmission history. Optimal inference of transmission events calls for the combination of genetic data and epidemiological data into one joint analysis. A key difficulty is that the transmission tree, which describes the transmission events between infected hosts, differs from the phylogenetic tree, which describes the ancestral relationships between pathogens sampled from these hosts. The trees differ both in timing of the internal nodes and in topology. These differences become more pronounced when a higher fraction of infected hosts is sampled. We show how the phylogenetic tree of sampled pathogens is related to the transmission tree of an outbreak of an infectious disease, by the within-host dynamics of pathogens. We provide a statistical framework to infer key epidemiological and mutational parameters by simultaneously estimating the phylogenetic tree and the transmission tree. We test the approach using simulations and illustrate its use on an outbreak of foot-and-mouth disease. The approach unifies existing methods in the emerging field of phylodynamics with transmission tree reconstruction methods that are used in infectious disease epidemiology.     

Occupancy modelling as a new approach to assess supranational trends using opportunistic data: a pilot study for the damselfly Calopteryx splendens

There is limited information available on changes in biodiversity at the European scale, because there is a lack of data from standardised monitoring for most species groups. However, a great number of observations made without a standardised field protocol is available in many countries for many species. Such opportunistic data offer an alternative source of information, but unfortunately such data suffer from non-standardised observation effort and geographical bias. Here we describe a new approach to compiling supranational trends using opportunistic data which adjusts for these two major imperfections. The non-standardised observation effort is dealt with by occupancy modelling, and the unequal geographical distribution of sites by a weighting procedure. The damselfly Calopteryx splendens was chosen as our test species. The data were collected from five countries (Ireland, Great Britain, the Netherlands, Belgium and France), covering the period 1990–2008. We used occupancy models to estimate the annual number of occupied 1 × 1 km sites per country. Occupancy models use presence-absence data, account for imperfect detection of species, and thereby correct for between-year variability in observation effort. The occupancy models were run per country in a Bayesian mode of inference using JAGS. The occupancy estimates per country were then aggregated to assess the supranational trend in the number of occupied 1 × 1 km². To adjust for the unequal geographical distribution of surveyed sites, we weighted the countries according to the number of sites surveyed and the range of the species per country. The distribution of C. splendens has increased significantly in the combined five countries. Our trial demonstrated that a supranational trend in distribution can be derived from opportunistic data, while adjusting for observation effort and geographical bias. This opens new perspectives for international monitoring of biodiversity.     

Finding Evidence for Local Transmission of Contagious Disease in Molecular Epidemiological Datasets

Surveillance systems of contagious diseases record information on cases to monitor incidence of disease and to evaluate effectiveness of interventions. These systems focus on a well-defined population; a key question is whether observed cases are infected through local transmission within the population or whether cases are the result of importation of infection into the population. Local spread of infection calls for different intervention measures than importation of infection. Besides standardized information on time of symptom onset and location of cases, pathogen genotyping or sequencing offers essential information to address this question. Here we introduce a method that takes full advantage of both the genetic and epidemiological data to distinguish local transmission from importation of infection, by comparing inter-case distances in temporal, spatial and genetic data. Cases that are part of a local transmission chain will have shorter distances between their geographical locations, shorter durations between their times of symptom onset and shorter genetic distances between their pathogen sequences as compared to cases that are due to importation. In contrast to generic clustering algorithms, the proposed method explicitly accounts for the fact that during local transmission of a contagious disease the cases are caused by other cases. No pathogen-specific assumptions are needed due to the use of ordinal distances, which allow for direct comparison between the disparate data types. Using simulations, we test the performance of the method in identifying local transmission of disease in large datasets, and assess how sensitivity and specificity change with varying size of local transmission chains and varying overall disease incidence.