Approaches for advancing scientific understanding of macrosystems

The emergence of macrosystems ecology (MSE), which focuses on regional- to continental-scale ecological patterns and processes, builds upon a history of long-term and broad-scale studies in ecology. Scientists face the difficulty of integrating the many elements that make up macrosystems, which consist of hierarchical processes at interacting spatial and temporal scales. Researchers must also identify the most relevant scales and variables to be considered, the required data resources, and the appropriate study design to provide the proper inferences. The large volumes of multi-thematic data often associated with macrosystem studies typically require validation, standardization, and assimilation. Finally, analytical approaches need to describe how cross-scale and hierarchical dynamics and interactions relate to macroscale phenomena. Here, we elaborate on some key methodological challenges of MSE research and discuss existing and novel approaches to meet them

Culture dependent and independent analyses of 16S rRNA and ATP citrate lyase genes : a comparison of microbial communities from different black smoker chimneys on the Mid-Atlantic Ridge

Author Posting. © Springer, 2008. This is the author's version of the work. It is posted here by permission of Springer for personal use, not for redistribution. The definitive version was published in Extremophiles 12 (2008): 627-640, doi:10.1007/s00792-008-0167-5.The bacterial and archaeal communities of three deep-sea hydrothermal vent systems located on the Mid-Atlantic Ridge (MAR; Rainbow, Logatchev and Broken Spur) were investigated using an integrated culture-dependent and independent approach. Comparative molecular phylogenetic analyses, using the 16S rRNA gene and the deduced amino acid sequences of the alpha and beta subunits of the ATP citrate lyase encoding genes were carried out on natural microbial communities, on an enrichment culture obtained from the Broken Spur chimney, and on novel chemolithoautotrophic bacteria and reference strains originally isolated from several different deep-sea vents. Our data showed that the three MAR hydrothermal vent chimneys investigated in this study host very different microbial assemblages. The microbial community of the Rainbow chimney was dominated by thermophilic, autotrophic, hydrogen-oxidizing, sulfur- and nitrate reducing Epsilonproteobacteria related to the genus Caminibacter. The detection of sequences related to sulfur-reducing bacteria and archaea (Archaeoglobus) indicated that thermophilic sulfate reduction might also be occurring at this site. The Logatchev bacterial community included several sequences related to mesophilic sulfur-oxidizing bacteria, while the archaeal component of this chimney was dominated by sequences related to the ANME-2 lineage, suggesting that anaerobic oxidation of methane may be occurring at this site. Comparative analyses of the ATP citrate lyase encoding genes from natural microbial communities suggested that Epsilonproteobacteria were the dominant primary producers using the reverse TCA cycle (rTCA) at Rainbow, while Aquificales of the genera Desulfurobacterium and Persephonella were prevalent in the Broken Spur chimney.This research was supported by NSF grants MCB 04-56676 (C.V.), OCE 03-27353 (C.V.), MCB 04-56689 (S.M.S.), a grant from the New Jersey Agricultural Experiment Station to C.V., and a NIH Ph.D. Training Program in Biotechnology Fellowship (NIH NIGMS 5 T32 GM08339) to J.V. M.H. was supported through a postdoctoral scholarship from the Woods Hole Oceanographic Institution

Collateral Quality and Loan Default Risk: The Case of Vietnam

In the transition economy of Vietnam, financial market is dominated by banking sector but commercial banks heavily rely on collateral-based lending. While the relationship between collateral and implied credit risk is still in debate, this paper provides additional empirical evidence regarding the heterogeneous effects and transmission channels of collateral characteristics on loan delinquency. Applying instrumental variable probit analysis on a unique dataset of 2295 internal loan accounts in Vietnam, we find the significantly negative impact of collateral quality on the probability of default of consumer loans, supporting the dominance of borrower selection and risk-shifting over lender selection effects. The finding implies that high-quality collateral not only signals more credible borrower but also fosters good behavior in using loan, enabling bank to mitigate adverse selection and moral hazard problems

Approaches to advance scientific understanding of macrosystems ecology

The emergence of macrosystems ecology (MSE), which focuses on regional- to continental-scale ecological pat- terns and processes, builds upon a history of long-term and broad-scale studies in ecology. Scientists face the difficulty of integrating the many elements that make up macrosystems, which consist of hierarchical processes at interacting spatial and temporal scales. Researchers must also identify the most relevant scales and variables to be considered, the required data resources, and the appropriate study design to provide the proper inferences. The large volumes of multi-thematic data often associated with macrosystem studies typically require valida- tion, standardization, and assimilation. Finally, analytical approaches need to describe how cross-scale and hierarchical dynamics and interactions relate to macroscale phenomena. Here, we elaborate on some key methodological challenges of MSE research and discuss existing and novel approaches to meet them

The genetic architecture of low-temperature adaptation in the wine yeast Saccharomyces cerevisiae

[Background] Low-temperature growth and fermentation of wine yeast can enhance wine aroma and make them highly desirable traits for the industry. Elucidating response to cold in Saccharomyces cerevisiae is, therefore, of paramount importance to select or genetically improve new wine strains. As most enological traits of industrial importance in yeasts, adaptation to low temperature is a polygenic trait regulated by many interacting loci.[Results] In order to unravel the genetic determinants of low-temperature fermentation, we mapped quantitative trait loci (QTLs) by bulk segregant analyses in the F13 offspring of two Saccharomyces cerevisiae industrial strains with divergent performance at low temperature. We detected four genomic regions involved in the adaptation at low temperature, three of them located in the subtelomeric regions (chromosomes XIII, XV and XVI) and one in the chromosome XIV. The QTL analysis revealed that subtelomeric regions play a key role in defining individual variation, which emphasizes the importance of these regions’ adaptive nature.[Conclusions] The reciprocal hemizygosity analysis (RHA), run to validate the genes involved in low-temperature fermentation, showed that genetic variation in mitochondrial proteins, maintenance of correct asymmetry and distribution of phospholipid in the plasma membrane are key determinants of low-temperature adaptation.This work has been financially supported from the Spanish Government through MINECO and FEDER funds (AGL2013-47300-C3-3-R and PCIN-2015-143 grants) and from Generalitat Valenciana through PROMETEOII/2014/042 grant, awarded to JMG. This study has been carried out in the context of the European Project ERA-IB “YeastTempTation” EGR thanks the Spanish government for an FPI grant BES-2011-044498 and MM also thanks the Generalitat Valenciana for a VALi+d ACIF/2015/194 grant. We acknowledge support of the publication fee by the CSIC Open Access Publication Support Initiative through its Unit of Information Resources for Research (URICI).Peer reviewe

Ratios of involved nodes in early breast cancer

INTRODUCTION: The number of lymph nodes found to be involved in an axillary dissection is among the most powerful prognostic factors in breast cancer, but it is confounded by the number of lymph nodes that have been examined. We investigate an idea that has surfaced recently in the literature (since 1999), namely that the proportion of node-positive lymph nodes (or a function thereof) is a much better predictor of survival than the number of excised and node-positive lymph nodes, alone or together. METHODS: The data were abstracted from 83,686 cases registered in the Surveillance, Epidemiology, and End Results (SEER) program of women diagnosed with nonmetastatic T1–T2 primary breast carcinoma between 1988 and 1997, in whom axillary node dissection was performed. The end-point was death from breast cancer. Cox models based on different expressions of nodal involvement were compared using the Nagelkerke R(2 )index (R(2)(N)). Ratios were modeled as percentage and as log odds of involved nodes. Log odds were estimated in a way that avoids singularities (zero values) by using the empirical logistic transform. RESULTS: In node-negative cases both the number of nodes excised and the log odds were significant, with hazard ratios of 0.991 (95% confidence interval 0.986–0.997) and 1.150 (1.058–1.249), respectively, but without improving R(2)(N). In node-positive cases the hazard ratios were 1.003–1.088 for the number of involved nodes, 0.966–1.005 for the number of excised nodes, 1.015–1.017 for the percentage, and 1.344–1.381 for the log odds. R(2)(N )improved from 0.067 (no nodal covariate) to 0.102 (models based on counts only) and to 0.108 (models based on ratios). DISCUSSION: Ratios are simple optimal predictors, in that they provide at least the same prognostic value as the more traditional staging based on counting of involved nodes, without replacing them with a needlessly complicated alternative. They can be viewed as a per patient standardization in which the number of involved nodes is standardized to the number of nodes excised. In an extension to the study, ratios were validated in a comparison with categorized staging measures using blinded data from the San Jose–Monterey cancer registry. A ratio based prognostic index was also derived. It improved the Nottingham Prognostic Index without compromising on simplicity

Predicting new venture survival and growth: does the fog lift?

This paper investigates whether new venture performance becomes easier to predict as the venture ages: does the fog lift? To address this question we primarily draw upon a theoretical framework, initially formulated in a managerial context by Levinthal (Adm Sci Q 36(3):397–420, 1991) that sees new venture sales as a random walk but survival being determined by the stock of available resources (proxied by size). We derive theoretical predictions that are tested with a 10-year cohort of 6579 UK new ventures in the UK. We observe that our ability to predict firm growth deteriorates in the years after entry—in terms of the selection environment, the ‘fog’ seems to thicken. However, our survival predictions improve with time—implying that the ‘fog’ does lift