All Politics is Local: The Renminbi's Prospects as a Future Global Currency

Recent years have seen a heated discussion over Chinese capital account liberalization and internationalization of China’s currency, the renminbi (RMB). Against the backdrop of a weak U.S. economy and China’s growing international economic clout, there has been speculation about the RMB replacing the U.S. dollar as the world’s leading currency. Subramanian (2011: 1), for instance, maintains that “the renminbi could become the premier reserve currency by the end of this decade, or early next decade.” Much of the current discourse recalls past discussions when other currencies, especially the Japanese yen (Burstein 1988; Kwan 1994; Taguchi 1994) and the Euro (Chinn and Frankel 2007), were seen as candidates to “dethrone” the dollar

Regulators of genetic risk of breast cancer identified by integrative network analysis.

Genetic risk for breast cancer is conferred by a combination of multiple variants of small effect. To better understand how risk loci might combine, we examined whether risk-associated genes share regulatory mechanisms. We created a breast cancer gene regulatory network comprising transcription factors and groups of putative target genes (regulons) and asked whether specific regulons are enriched for genes associated with risk loci via expression quantitative trait loci (eQTLs). We identified 36 overlapping regulons that were enriched for risk loci and formed a distinct cluster within the network, suggesting shared biology. The risk transcription factors driving these regulons are frequently mutated in cancer and lie in two opposing subgroups, which relate to estrogen receptor (ER)(+) luminal A or luminal B and ER(-) basal-like cancers and to different luminal epithelial cell populations in the adult mammary gland. Our network approach provides a foundation for determining the regulatory circuits governing breast cancer, to identify targets for intervention, and is transferable to other disease settings.This work was funded by Cancer Research UK and the Breast Cancer Research Foundation. MAAC is funded by the National Research Council (CNPq) of Brazil. TEH held a fellowship from the US DOD Breast Cancer Research Program (W81XWH-11-1-0592) and is currently supported by an RAH Career Development Fellowship (Australia). TEH and WDT are funded by the NHMRC of Australia (NHMRC) (ID: 1008349 WDT; 1084416 WDT, TEH) and Cancer Australia/National Breast Cancer Foundation (ID 627229; WDT, TEH). BAJP is a Gibb Fellow of Cancer Research UK. We would like to acknowledge the support of The University of Cambridge, Cancer Research UK and Hutchison Whampoa Limited.This is the author accepted manuscript. The final version is available from NPG via http://dx.doi.org/10.1038/ng.345

Demographic History of Indigenous Populations in Mesoamerica Based on mtDNA Sequence Data

The genetic characterization of Native American groups provides insights into their history and demographic events. We sequenced the mitochondrial D-loop region (control region) of 520 samples from eight Mexican indigenous groups. In addition to an analysis of the genetic diversity, structure and genetic relationship between 28 Native American populations, we applied Bayesian skyline methodology for a deeper insight into the history of Mesoamerica. AMOVA tests applying cultural, linguistic and geographic criteria were performed. MDS plots showed a central cluster of Oaxaca and Maya populations, whereas those from the North and West were located on the periphery. Demographic reconstruction indicates higher values of the effective number of breeding females (Nef) in Central Mesoamerica during the Preclassic period, whereas this pattern moves toward the Classic period for groups in the North and West. Conversely, Nef minimum values are distributed either in the Lithic period (i.e. founder effects) or in recent periods (i.e. population declines). The Mesomerican regions showed differences in population fluctuation as indicated by the maximum Inter-Generational Rate (IGRmax): i) Center-South from the lithic period until the Preclassic; ii) West from the beginning of the Preclassic period until early Classic; iii) North characterized by a wide range of temporal variation from the Lithic to the Preclassic. Our findings are consistent with the genetic variations observed between central, South and Southeast Mesoamerica and the North-West region that are related to differences in genetic drift, structure, and temporal survival strategies (agriculture versus hunter-gathering, respectively). Interestingly, although the European contact had a major negative demographic impact, we detect a previous decline in Mesoamerica that had begun a few hundred years before

Contrasting roles of histone 3 lysine 27 demethylases in acute lymphoblastic leukaemia

T-cell acute lymphoblastic leukaemia (T-ALL) is a haematological malignancy with a dismal overall prognosis, including a relapse rate of up to 25%, mainly because of the lack of non-cytotoxic targeted therapy options. Drugs that target the function of key epigenetic factors have been approved in the context of haematopoietic disorders, and mutations that affect chromatin modulators in a variety of leukaemias have recently been identified; however, ‘epigenetic’ drugs are not currently used for T-ALL treatment. Recently, we described that the polycomb repressive complex 2 (PRC2) has a tumour-suppressor role in T-ALL. Here we delineated the role of the histone 3 lysine 27 (H3K27) demethylases JMJD3 and UTX in T-ALL. We show that JMJD3 is essential for the initiation and maintenance of T-ALL, as it controls important oncogenic gene targets by modulating H3K27 methylation. By contrast, we found that UTX functions as a tumour suppressor and is frequently genetically inactivated in T-ALL. Moreover, we demonstrated that the small molecule inhibitor GSKJ4 (ref. 5) affects T-ALL growth, by targeting JMJD3 activity. These findings show that two proteins with a similar enzymatic function can have opposing roles in the context of the same disease, paving the way for treating haematopoietic malignancies with a new category of epigenetic inhibitors.National Institutes of Health (U.S.) (Grant R37-HD04502

Ευρετικές προσεγγίσεις του μοναδιάστατου προβλήματος πακετοποίησης

Article 59.1, of the International Code of Nomenclature for Algae, Fungi, and Plants (ICN; Melbourne Code), which addresses the nomenclature of pleomorphic fungi, became effective from 30 July 2011. Since that date, each fungal species can have one nomenclaturally correct name in a particular classification. All other previously used names for this species will be considered as synonyms. The older generic epithet takes priority over the younger name. Any widely used younger names proposed for use, must comply with Art. 57.2 and their usage should be approved by the Nomenclature Committee for Fungi (NCF). In this paper, we list all genera currently accepted by us in Dothideomycetes (belonging to 23 orders and 110 families), including pleomorphic and non-pleomorphic genera. In the case of pleomorphic genera, we follow the rulings of the current ICN and propose single generic names for future usage. The taxonomic placements of 1261 genera are listed as an outline. Protected names and suppressed names for 34 pleomorphic genera are listed separately. Notes and justifications are provided for possible proposed names after the list of genera. Notes are also provided on recent advances in our understanding of asexual and sexual morph linkages in Dothideomycetes. A phylogenetic tree based on four gene analyses supported 23 orders and 75 families, while 35 families still lack molecular data

Ustekinumab as Induction and Maintenance Therapy for Crohn’s Disease

BACKGROUND Ustekinumab, a monoclonal antibody to the p40 subunit of interleukin-12 and inter-leukin-23, was evaluated as an intravenous induction therapy in two populations with moderately to severely active Crohn’s disease. Ustekinumab was also evaluated as subcutaneous maintenance therapy. METHODS We randomly assigned patients to receive a single intravenous dose of ustekinumab (either 130 mg or approximately 6 mg per kilogram of body weight) or placebo in two induction trials. The UNITI-1 trial included 741 patients who met the criteria for primary or secondary nonresponse to tumor necrosis factor (TNF) antagonists or had unacceptable side effects. The UNITI-2 trial included 628 patients in whom conventional therapy failed or unacceptable side effects occurred. Patients who completed these induction trials then participated in IM-UNITI, in which the 397 patients who had a response to ustekinumab were randomly assigned to receive subcutaneous maintenance injections of 90 mg of ustekinumab (either every 8 weeks or every 12 weeks) or placebo. The primary end point for the induction trials was a clinical response at week 6 (defined as a decrease from baseline in the Crohn’s Disease Activity Index [CDAI] score of ≥100 points or a CDAI score <150). The primary end point for the maintenance trial was remission at week 44 (CDAI score <150). RESULTS The rates of response at week 6 among patients receiving intravenous ustekinumab at a dose of either 130 mg or approximately 6 mg per kilogram were significantly higher than the rates among patients receiving placebo (in UNITI-1, 34.3%, 33.7%, and 21.5%, respectively, with P≤0.003 for both comparisons with placebo; in UNITI-2, 51.7%, 55.5%, and 28.7%, respectively, with P<0.001 for both doses). In the groups receiving maintenance doses of ustekinumab every 8 weeks or every 12 weeks, 53.1% and 48.8%, respectively, were in remission at week 44, as compared with 35.9% of those receiving placebo (P = 0.005 and P = 0.04, respectively). Within each trial, adverse-event rates were similar among treatment groups. CONCLUSIONS Among patients with moderately to severely active Crohn’s disease, those receiving intravenous ustekinumab had a significantly higher rate of response than did those receiving placebo. Subcutaneous ustekinumab maintained remission in patients who had a clinical response to induction therapy. (Funded by Janssen Research and Development; ClinicalTrials.gov numbers, NCT01369329, NCT01369342, and NCT01369355.

Impact of protein supplementation during endurance training on changes in skeletal muscle transcriptome

Background: Protein supplementation improves physiological adaptations to endurance training, but the impact on adaptive changes in the skeletal muscle transcriptome remains elusive. The present analysis was executed to determine the impact of protein supplementation on changes in the skeletal muscle transcriptome following 5- weeks of endurance training. Results: Skeletal muscle tissue samples from the vastus lateralis were taken before and after 5-weeks of endurance training to assess changes in the skeletal muscle transcriptome. One hundred and 63 genes were differentially expressed after 5-weeks of endurance training in both groups (q-value 0.05). Endurance training primarily affected expression levels of genes related to extracellular matrix and these changes tended to be greater in PRO than in CON. Conclusions: Protein supplementation subtly impacts endurance training-induced changes in the skeletal muscle transcriptome. In addition, our transcriptomic analysis revealed that the extracellular matrix may be an important factor for skeletal muscle adaptation in response to endurance training. This trial was registered at clinicaltrials.gov as NCT03462381, March 12, 201

Identification of differentially expressed subnetworks based on multivariate ANOVA

<p>Abstract</p> <p>Background</p> <p>Since high-throughput protein-protein interaction (PPI) data has recently become available for humans, there has been a growing interest in combining PPI data with other genome-wide data. In particular, the identification of phenotype-related PPI subnetworks using gene expression data has been of great concern. Successful integration for the identification of significant subnetworks requires the use of a search algorithm with a proper scoring method. Here we propose a multivariate analysis of variance (MANOVA)-based scoring method with a greedy search for identifying differentially expressed PPI subnetworks.</p> <p>Results</p> <p>Given the MANOVA-based scoring method, we performed a greedy search to identify the subnetworks with the maximum scores in the PPI network. Our approach was successfully applied to human microarray datasets. Each identified subnetwork was annotated with the Gene Ontology (GO) term, resulting in the phenotype-related functional pathway or complex. We also compared these results with those of other scoring methods such as <it>t </it>statistic- and mutual information-based scoring methods. The MANOVA-based method produced subnetworks with a larger number of proteins than the other methods. Furthermore, the subnetworks identified by the MANOVA-based method tended to consist of highly correlated proteins.</p> <p>Conclusion</p> <p>This article proposes a MANOVA-based scoring method to combine PPI data with expression data using a greedy search. This method is recommended for the highly sensitive detection of large subnetworks.</p

Confronting chemobrain: an in-depth look at survivors’ reports of impact on work, social networks, and health care response

Mild cognitive impairment following chemotherapy is one of the most commonly reported post treatment symptoms by breast cancer survivors. This deterioration in cognitive function, commonly referred to as “chemobrain” or “chemofog,” was largely unacknowledged by the medical community until recent years. Although chemobrain has now become the subject of more vigorous exploration, little is known about this specific phenomenon’s psychosocial impact on breast cancer survivors. This research documents in-depth the effects that cognitive impairment has on women’s personal and professional lives, and our data suggest that greater attention needs to be focused on this arena of survivorship. The results are based on an in-depth qualitative study of 74 white and African American breast cancer survivors in California who experience post-treatment side effects. The data reported herein were obtained through the use of focus groups and in-depth interviews. Our data indicate that cognitive impairment can be problematic for survivors, with many asserting that it is their most troublesome post treatment symptom. Survivors report diminished quality of life and daily functioning as a result of chemobrain. Respondents detail a range of coping strategies that they are forced to employ in order to manage their social and professional lives. Chemobrain significantly impairs a proportion of cancer survivors, at great cost to them economically, emotionally, and interpersonally. This suggests that more research needs to be conducted on the psychosocial ramifications of post treatment symptoms in order to inform the efforts of the medical and mental health communities as well as the support networks of survivors. A better and broader understanding of the effects of cognitive impairment both in the medical community and among lay people could pave the way for improved social and psychological services for this population

Comparison of multiplex meta analysis techniques for understanding the acute rejection of solid organ transplants

<p>Abstract</p> <p>Background</p> <p>Combining the results of studies using highly parallelized measurements of gene expression such as microarrays and RNAseq offer unique challenges in meta analysis. Motivated by a need for a deeper understanding of organ transplant rejection, we combine the data from five separate studies to compare acute rejection versus stability after solid organ transplantation, and use this data to examine approaches to multiplex meta analysis.</p> <p>Results</p> <p>We demonstrate that a commonly used parametric effect size estimate approach and a commonly used non-parametric method give very different results in prioritizing genes. The parametric method providing a meta effect estimate was superior at ranking genes based on our gold-standard of identifying immune response genes in the transplant rejection datasets.</p> <p>Conclusion</p> <p>Different methods of multiplex analysis can give substantially different results. The method which is best for any given application will likely depend on the particular domain, and it remains for future work to see if any one method is consistently better at identifying important biological signal across gene expression experiments.</p