ASC deficiency suppresses proliferation and prevents medulloblastoma incidence

Apoptosis-associated speck-like protein containing a caspase recruitment domain (ASC) is silenced by promoter methylation in many types of tumors, yet ASC’s role in most cancers remains unknown. Here, we show that ASC is highly expressed in a model of medulloblastoma, the most common malignant pediatric brain cancer; ASC is also expressed in human medulloblastomas. Importantly, while ASC deficiency did not affect normal cerebellar development, ASC knock-out mice on the Smoothened (ND2:SmoA1) transgenic model of medulloblastoma exhibited a profound reduction in medulloblastoma incidence and a delayed tumor onset. A similar decrease in tumorigenesis with ASC deficiency was also seen in the hGFAP-Cre:SmoM2 mouse model of medulloblastoma. Interestingly, hyperproliferation of the external granule layer (EGL) was comparable at P20 in both the wildtype and ASC-deficient SmoA1 mice. However, while the apoptosis and differentiation markers remained unchanged at this age, proliferation makers were decreased, and the EGL was reduced in thickness and area by P60. This reduction in proliferation with ASC deficiency was also seen in isolated SmoA1 cerebellar granule precursor cells in vitro, indicating that the effect of ASC deletion on proliferation was cell autonomous. Interestingly, ASC deficient SmoA1 cerebella exhibited disrupted expression of genes in the TGF-β pathway and increased level of nuclear Smad3. Together, these results demonstrate an unexpected role for ASC in Sonic hedgehog-driven medulloblastoma tumorigenesis, thus identifying ASC as a promising novel target for anti-tumor therapy

TRY plant trait database – enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

(U-Th)/He chronology: part 2. Considerations for evaluating, integrating, and interpreting conventional individual aliquot data

The (U-Th)/He dating technique is an essential tool in Earth science research with diverse thermochronologic, geochronologic, and detrital applications. It is now used in a wide range of tectonic, structural, petrological, sedimentary, geomorphic, volcanological, and planetary studies. While in some circumstances the interpretation of (U-Th)/He data is relatively straightforward, in other cases it is less so. In some geologic contexts, individual analyses of the same mineral from a single sample are expected to yield dates that differ well beyond their analytical uncertainty owing to variable He diffusion kinetics. Although much potential exists to exploit this phenomenon to decipher more detailed thermal history information, distinguishing interpretable intra-sample data variation caused by kinetic differences between crystals from uninterpretable overdispersion caused by other factors can be challenging. Nor is it always simple to determine under what circumstances it is appropriate to integrate multiple individual analyses using a summary statistic such as a mean sample date or to decide on the best approach for incorporating data into the interpretive process of thermal history modeling. Here we offer some suggestions for evaluating data, attempt to summarize the current state of thinking on the statistical characterization of data sets, and describe the practical choices (e.g., model structure, path complexity, data input, weighting of different geologic and chronologic information) that must be made when setting up thermal history models. We emphasize that there are no hard and fast rules in any of these realms, which continue to be an important focus of improvement and community discussion, and no single interpretational and modeling philosophy should be forced on data sets. The guiding principle behind all suggestions made here is for transparency in reporting the steps and assumptions associated with evaluating, integrating, and interpreting data, which will promote the continued development of (U-Th)/He chronology

(U-Th)/He chronology: part 1. Data, uncertainty, and reporting

The field of (U-Th)/He geochronology and thermochronology has grown enormously over the past ∼25 years. The tool is applicable across much of geologic time, new (U-Th)/He chronometers are under continuous development, and the method is used in a diverse array of studies. Consequently, the technique has a rapidly expanding user base, and new labs are being established worldwide. This presents both opportunities and challenges. Currently there are no universally agreed-upon protocols for reporting measured (U-Th)/He data or data derivatives. Nor are there standardized practices for reporting He diffusion kinetic, 4He/3He, or continuous ramped heating data. Approaches for reporting uncertainties associated with all types of data also vary widely. Here, we address these issues. We review the fundamentals of the methods, the types of materials that can be dated, how data are acquired, the process and choices associated with data reduction, and make recommendations for data and uncertainty reporting. We advocate that both the primary measured and derived data be reported, along with statements of assumptions, appropriate references, and clear descriptions of the methods used to compute derived data from measured values. The adoption of more comprehensive and uniform approaches to data and uncertainty reporting will enable data to be re-reduced in the future with different interpretative contexts and data reduction methods, and will facilitate inter-comparison of data sets generated by different laboratories. Together, this will enhance the value, cross-disciplinary use, reliability, and ongoing development of (U-Th)/He chronology