RANK ligand mediates progestin-induced mammary epithelial proliferation and carcinogenesis

RANK ligand (RANKL), a TNF-related molecule, is essential for osteoclast formation, function and survival through interaction with its receptor RANK. Mammary glands of RANK- and RANKL-deficient mice develop normally during sexual maturation, but fail to form lobuloalveolar structures during pregnancy because of defective proliferation and increased apoptosis of mammary epithelium. It has been shown that RANKL is responsible for the major proliferative response of mouse mammary epithelium to progesterone during mammary lactational morphogenesis, and in mouse models, manipulated to induce activation of the RANK/RANKL pathway in the absence of strict hormonal control, inappropriate mammary proliferation is observed. However, there is no evidence so far of a functional contribution of RANKL to tumorigenesis. Here we show that RANK and RANKL are expressed within normal, pre-malignant and neoplastic mammary epithelium, and using complementary gain-of-function (mouse mammary tumour virus (MMTV)-RANK transgenic mice) and loss-of function (pharmacological inhibition of RANKL) approaches, define a direct contribution of this pathway in mammary tumorigenesis. Accelerated pre-neoplasias and increased mammary tumour formation were observed in MMTV-RANK transgenic mice after multiparity or treatment with carcinogen and hormone (progesterone). Reciprocally, selective pharmacological inhibition of RANKL attenuated mammary tumour development not only in hormone- and carcinogen-treated MMTV-RANK and wild-type mice, but also in the MMTV-neu transgenic spontaneous tumour model. The reduction in tumorigenesis upon RANKL inhibition was preceded by a reduction in pre-neoplasias as well as rapid and sustained reductions in hormone- and carcinogen-induced mammary epithelial proliferation and cyclin D1 levels. Collectively, our results indicate that RANKL inhibition is acting directly on hormone-induced mammary epithelium at early stages in tumorigenesis, and the permissive contribution of progesterone to increased mammary cancer incidence is due to RANKL-dependent proliferative changes in the mammary epithelium. The current study highlights a potential role for RANKL inhibition in the management of proliferative breast disease.     

Temporal difference models describe higher-order learning in humans

The ability to use environmental stimuli to predict impending harm is critical for survival. Such predictions should be available as early as they are reliable. In pavlovian conditioning, chains of successively earlier predictors are studied in terms of higher-order relationships, and have inspired computational theories such as temporal difference learning. However, there is at present no adequate neurobiological account of how this learning occurs. Here, in a functional magnetic resonance imaging (fMRI) study of higher-order aversive conditioning, we describe a key computational strategy that humans use to learn predictions about pain. We show that neural activity in the ventral striatum and the anterior insula displays a marked correspondence to the signals for sequential learning predicted by temporal difference models. This result reveals a flexible aversive learning process ideally suited to the changing and uncertain nature of real-world environments. Taken with existing data on reward learning, our results suggest a critical role for the ventral striatum in integrating complex appetitive and aversive predictions to coordinate behaviour.     

The DNA sequence and analysis of human chromosome 13

Chromosome 13 is the largest acrocentric human chromosome. It carries genes involved in cancer including the breast cancer type 2 (BRCA2) and retinoblastoma (RB1) genes, is frequently rearranged in B-cell chronic lymphocytic leukaemia, and contains the DAOA locus associated with bipolar disorder and schizophrenia. We describe completion and analysis of 95.5 megabases (Mb) of sequence from chromosome 13, which contains 633 genes and 296 pseudogenes. We estimate that more than 95.4% of the protein-coding genes of this chromosome have been identified, on the basis of comparison with other vertebrate genome sequences. Additionally, 105 putative non-coding RNA genes were found. Chromosome 13 has one of the lowest gene densities (6.5 genes per Mb) among human chromosomes, and contains a central region of 38 Mb where the gene density drops to only 3.1 genes per Mb.     

A flagellin-induced complex of the receptor FLS2 and BAK1 initiates plant defence

Plants sense potential microbial invaders by using pattern-recognition receptors to recognize pathogen-associated molecular patterns (PAMPs). In Arabidopsis thaliana, the leucine-rich repeat receptor kinases flagellin-sensitive 2 (FLS2) (ref. 2) and elongation factor Tu receptor (EFR) (ref. 3) act as pattern-recognition receptors for the bacterial PAMPs flagellin and elongation factor Tu (EF-Tu) (ref. 5) and contribute to resistance against bacterial pathogens. Little is known about the molecular mechanisms that link receptor activation to intracellular signal transduction. Here we show that BAK1 (BRI1-associated receptor kinase 1), a leucine-rich repeat receptor-like kinase that has been reported to regulate the brassinosteroid receptor BRI1 (refs 6,7), is involved in signalling by FLS2 and EFR. Plants carrying bak1 mutations show normal flagellin binding but abnormal early and late flagellin-triggered responses, indicating that BAK1 acts as a positive regulator in signalling. The bak1-mutant plants also show a reduction in early, but not late, EF-Tu-triggered responses. The decrease in responses to PAMPs is not due to reduced sensitivity to brassinosteroids. We provide evidence that FLS2 and BAK1 form a complex in vivo, in a specific ligand-dependent manner, within the first minutes of stimulation with flagellin. Thus, BAK1 is not only associated with developmental regulation through the plant hormone receptor BRI1 (refs 6,7), but also has a functional role in PRR-dependent signalling, which initiates innate immunity.     

Global trends in emerging infectious diseases

Emerging infectious diseases (EIDs) are a significant burden on global economies and public health. Their emergence is thought to be driven largely by socio-economic, environmental and ecological factors, but no comparative study has explicitly analysed these linkages to understand global temporal and spatial patterns of EIDs. Here we analyse a database of 335 EID 'events' (origins of EIDs) between 1940 and 2004, and demonstrate non-random global patterns. EID events have risen significantly over time after controlling for reporting bias, with their peak incidence (in the 1980s) concomitant with the HIV pandemic. EID events are dominated by zoonoses (60.3% of EIDs): the majority of these (71.8%) originate in wildlife (for example, severe acute respiratory virus, Ebola virus), and are increasing significantly over time. We find that 54.3% of EID events are caused by bacteria or rickettsia, reflecting a large number of drug-resistant microbes in our database. Our results confirm that EID origins are significantly correlated with socio-economic, environmental and ecological factors, and provide a basis for identifying regions where new EIDs are most likely to originate (emerging disease 'hotspots'). They also reveal a substantial risk of wildlife zoonotic and vector-borne EIDs originating at lower latitudes where reporting effort is low. We conclude that global resources to counter disease emergence are poorly allocated, with the majority of the scientific and surveillance effort focused on countries from where the next important EID is least likely to originate.     

Assessment of the uncertainties in temperature change in China during the last century

We have used the China Homogenized Historic Temperature dataset and some long-term station series of the neighbor countries from CRUTEM3, a 5°×5° gridded dataset of monthly mean temperature since 1900, to provide a 107-year record of surface tem-perature trends and variability. We derived a comprehensive set of uncertainty estimates to accompany the data: measurement and sampling errors, uncertainties in temperature bias estimates, and uncertainties arising from limited observational coverage on large-scale averages have all been estimated. We reanalysed the temperature changes during the period of record. The best estimates of trends for 1900–2006 with uncertainties at 95% confidence range are about 0.09±0.017°C/decade for the year as a whole, and 0.14±0.021°C/decade, 0.11±0.021°C/decade, 0.04±0.017°C/decade, and 0.07±0.017°C/decade for winter, spring, summer and autumn respectively. For 1954–2006, the trends for annual, winter, spring, summer and autumn are: 0.26±0.032°C/decade, 0.35±0.046°C/decade, 0.25±0.051°C/decade, 0.16±0.037°C/decade and 0.22±0.055°C/decade. Winter saw the most significant warming trend in both 1900–2006 and 1954–2006, while during the most recent period (the satellite era, 1979–2006), all the seasons show similar warming trends: 0.45±0.13°C/decade, 0.51±0.11°C/decade, 0.52±0.16°C/decade, 0.37±0.10°C/decade and 0.50±0.16°C/decade for annual, winter, spring, summer and autumn. Trends arising from urbanization have been evaluated as less than 5% of the total warming trend for 1951–2001, so this bias was not removed.     

Expression and function of CD4 in a murine T-cell hybridoma

The CD4 (T4) antigen was originally described as a phenotypic marker specific for helper T cells, and has recently been shown to be the receptor for the human immunodeficiency virus (HIV). Functional studies using monoclonal antibodies directed at CD4 and major histocompatibility complex (MHC) class II molecules led to the suggestion that CD4 binds to the MHC class II molecules expressed on stimulator cells, enhancing T-cell responsiveness by increasing the avidity of T cell-stimulator cell interaction and/or by transmitting a positive intracellular signal. But recent evidence that antibodies to CD4 inhibit T-cell responsiveness in the absence of any putative ligand for CD4 has been interpreted as suggesting that antibody-mediated inhibition may involve the transmission of a negative signal via the CD4 molecule instead. We have infected a murine T-cell hybridoma that produces interleukin 2 (IL-2) in response to human class II HLA-DR antigens with a retroviral vector containing CD4 cDNA. The resulting CD4-expressing hybridoma cell lines produce 6- to 20-fold more IL-2 in response to HLA-DR antigens than control cell lines. Furthermore, when antigen levels are suboptimal, the response of the cell lines is entirely CD4-dependent. The data presented here clearly demonstrate that CD4 can enhance T-cell responsiveness and may be crucial in the response to suboptimal levels of antigen.     

Modular and predictable assembly of porous organic molecular crystals

Nanoporous molecular frameworks are important in applications such as separation, storage and catalysis. Empirical rules exist for their assembly but it is still challenging to place and segregate functionality in three-dimensional porous solids in a predictable way. Indeed, recent studies of mixed crystalline frameworks suggest a preference for the statistical distribution of functionalities throughout the pores rather than, for example, the functional group localization found in the reactive sites of enzymes. This is a potential limitation for 'one-pot' chemical syntheses of porous frameworks from simple starting materials. An alternative strategy is to prepare porous solids from synthetically preorganized molecular pores. In principle, functional organic pore modules could be covalently prefabricated and then assembled to produce materials with specific properties. However, this vision of mix-and-match assembly is far from being realized, not least because of the challenge in reliably predicting three-dimensional structures for molecular crystals, which lack the strong directional bonding found in networks. Here we show that highly porous crystalline solids can be produced by mixing different organic cage modules that self-assemble by means of chiral recognition. The structures of the resulting materials can be predicted computationally, allowing in silico materials design strategies. The constituent pore modules are synthesized in high yields on gram scales in a one-step reaction. Assembly of the porous co-crystals is as simple as combining the modules in solution and removing the solvent. In some cases, the chiral recognition between modules can be exploited to produce porous organic nanoparticles. We show that the method is valid for four different cage modules and can in principle be generalized in a computationally predictable manner based on a lock-and-key assembly between modules.