Challenges for Coring Deep Permafrost on Earth and Mars

This is the published version. Final publication is available from Mary Ann Liebert, Inc., publishers http://www.dx.doi.org/10.1089/ast.2007.0159.A scientific drilling expedition to the High Lake region of Nunavut, Canada, was recently completed with the goals of collecting samples and delineating gradients in salinity, gas composition, pH, pe, and microbial abundance in a 400 m thick permafrost zone and accessing the underlying pristine subpermafrost brine. With a triple-barrel wireline tool and the use of stringent quality assurance and quality control (QA/QC) protocols, 200 m of frozen, Archean, mafic volcanic rock was collected from the lower boundary that separates the permafrost layer and subpermafrost saline water. Hot water was used to remove cuttings and prevent the drill rods from freezing in place. No cryopegs were detected during penetration through the permafrost. Coring stopped at the 535 m depth, and the drill water was bailed from the hole while saline water replaced it. Within 24 hours, the borehole iced closed at 125 m depth due to vapor condensation from atmospheric moisture and, initially, warm water leaking through the casing, which blocked further access. Preliminary data suggest that the recovered cores contain viable anaerobic microorganisms that are not contaminants even though isotopic analyses of the saline borehole water suggests that it is a residue of the drilling brine used to remove the ice from the upper, older portion of the borehole. Any proposed coring mission to Mars that seeks to access subpermafrost brine will not only require borehole stability but also a means by which to generate substantial heating along the borehole string to prevent closure of the borehole from condensation of water vapor generated by drilling. Astrobiology 8, 623–638

Enhancement of COPD biological networks using a web-based collaboration interface

The construction and application of biological network models is an approach that offers a holistic way to understand biological processes involved in disease. Chronic obstructive pulmonary disease (COPD) is a progressive inflammatory disease of the airways for which therapeutic options currently are limited after diagnosis, even in its earliest stage. COPD network models are important tools to better understand the biological components and processes underlying initial disease development. With the increasing amounts of literature that are now available, crowdsourcing approaches offer new forms of collaboration for researchers to review biological findings, which can be applied to the construction and verification of complex biological networks. We report the construction of 50 biological network models relevant to lung biology and early COPD using an integrative systems biology and collaborative crowd-verification approach. By combining traditional literature curation with a data-driven approach that predicts molecular activities from transcriptomics data, we constructed an initial COPD network model set based on a previously published non-diseased lung-relevant model set. The crowd was given the opportunity to enhance and refine the networks on a website ( https://bionet.sbvimprover.com/) and to add mechanistic detail, as well as critically review existing evidence and evidence added by other users, so as to enhance the accuracy of the biological representation of the processes captured in the networks. Finally, scientists and experts in the field discussed and refined the networks during an in-person jamboree meeting. Here, we describe examples of the changes made to three of these networks: Neutrophil Signaling, Macrophage Signaling, and Th1-Th2 Signaling. We describe an innovative approach to biological network construction that combines literature and data mining and a crowdsourcing approach to generate a comprehensive set of COPD-relevant models that can be used to help understand the mechanisms related to lung pathobiology. Registered users of the website can freely browse and download the networks

Geochemical and boron isotopic compositions of tourmalines from selected gold-mineralised and barren rocks in SW Finland

Tourmaline-bearing rocks and a number of gold occurrences coexist in southwestern Finland, in a region where extensive magmatism and hydrothermal systems occurred during the Svecofennian orogeny, 1.9-1.8 Ga ago. Tourmalines investigated for this study were sampled from late-orogenic granite pegmatites (Eräjärvi, Kietyönmäki), quartztourmaline veins from gold occurrences (Kutemajärvi, Riukka), and the tourmalinised contact between a synorogenic intrusion and supracrustal rocks (Lepomäki Au occurrence, Ylöjärvi Cu-W-As-Ag-Au deposit). Major element compositions of the tourmalines are controlled by their host lithologies, whereas their boron isotopic compositions reflect the B reservoir(s) and the magmatichydrothermal processes of the B-bearing systems. The obtained δ11B values for granite pegmatite, vein, and intrusion-country rock contact-related tourmalines range between -10.2‰ and -13.2‰, -10.2‰ and -11.6‰, and -9.6‰ and -8.7‰, respectively, and are similar to tourmalines worldwide. The lighter B isotopic composition at Lepomäki gold and Ylöjärvi polymetallic occurrences indicate different B reservoirs and magmatic-hydrothermal processes between synand late-orogenic tourmalines. Geological observations and geochemical data on tourmalines also suggest that B was a constituent in hydrothermal fluids at all localities, including the gold-mineralising fluids at Lepomäki, Ylöjärvi and Riukka

Pukala intrusion, its age and connection to hydrothermal alteration in Orivesi, southwestern Finland

The Pukala intrusion is situated in the Paleoproterozoic Svecofennian domain of the Fennoscandian Shield in the contact region between the Central Finland Granitoid Complex and the Tampere Belt. The acid subvolcanic intrusion, which is in contact or close to several altered domains, mainly consists of porphyritic granodiorite and trondhjemite. The Pukala intrusion was emplaced into volcanic sequence in an island-arc or fore-arc setting before or during the early stages of the main regional deformation phase of the Svecofennian orogeny. On the basis of the geochemical data, the Pukala intrusion is a peraluminous volcanic-arc granitoid. After crystallisation at 1896 ±3 Ma, multiphase deformation and metamorphism caused alteration, recrystallisation, and orientation of the minerals, and tilted the intrusion steeply towards south. The 1851 ±5 Ma U-Pb age for titanite is connected to the late stages of the Svecofennian tectonometamorphic evolution of the region. Several hydrothermally altered domains are located in the felsic and intermediate metavolcanic rocks of the Tampere Belt within less than one kilometre south of the Pukala intrusion. Alteration is divided into three basic types: partial silica alteration, chlorite-sericite±silica alteration, and sericite alteration in shear zones. The first two types probably formed during the emplacement and crystallisation of the Pukala intrusion, and the third is linked to late shearing. Intense sericitisation and comb quartz bands in the contact of the intrusion and the altered domain at Kutemajärvi suggest that the hydrothermal system was driven by the Pukala intrusion

Geochemical signatures of mineralizing events in the Juomasuo Au–Co deposit, Kuusamo belt, northeastern Finland

Abstract The Juomasuo Au–Co deposit, currently classified as an orogenic gold deposit with atypical metal association, is located in the Paleoproterozoic Kuusamo belt in northeastern Finland. The volcano-sedimentary sequence that hosts the deposit was intensely altered, deformed, and metamorphosed to greenschist facies during the 1.93–1.76 Ga Svecofennian orogeny. In this study, we investigate the temporal relationship between Co and Au deposition and the relationship of metal enrichment with protolith composition and alteration mineralogy by utilizing lithogeochemical data and petrographic observations. We also investigate the nature of fluids involved in deposit formation based on sulfide trace element and sulfur isotope LA-ICP-MS data together with tourmaline mineral chemistry and boron isotopes. Classification of original protoliths was made on the basis of geochemically immobile elements; recognized lithologies are metasedimentary rocks, mafic, intermediate-composition, and felsic metavolcanic rocks, and an ultramafic sill. The composition of the host rocks does not control the type or intensity of mineralization. Sulfur isotope values (δ³⁴S − 2.6 to + 7.1‰) and trace element data obtained for pyrite, chalcopyrite, and pyrrhotite indicate that the two geochemically distinct Au–Co and Co ore types formed from fluids of different compositions and origins. A reduced, metamorphic fluid was responsible for deposition of the pyrrhotite-dominant, Co-rich ore, whereas a relatively oxidized fluid deposited the pyrite-dominant Au–Co ore. The main alteration and mineralization stages at Juomasuo are as follows: (1) widespread albitization that predates both types of mineralization; (2) stage 1, Co-rich mineralization associated with chlorite (± biotite ± amphibole) alteration; (3) stage 2, Au–Co mineralization related to sericitization. Crystal-chemical compositions for tourmaline suggest the involvement of evaporite-related fluids in formation of the deposit; boron isotope data also allow for this conclusion. Results of our research indicate that the metal association in the Juomasuo Au–Co deposit was formed by spatially coincident and multiple hydrothermal processes

Strengths and limitations of microarray-based phenotype prediction: lessons learned from the IMPROVER Diagnostic Signature Challenge.

MOTIVATION: After more than a decade since microarrays were used to predict phenotype of biological samples, real-life applications for disease screening and identification of patients who would best benefit from treatment are still emerging. The interest of the scientific community in identifying best approaches to develop such prediction models was reaffirmed in a competition style international collaboration called IMPROVER Diagnostic Signature Challenge whose results we describe herein. RESULTS: Fifty-four teams used public data to develop prediction models in four disease areas including multiple sclerosis, lung cancer, psoriasis and chronic obstructive pulmonary disease, and made predictions on blinded new data that we generated. Teams were scored using three metrics that captured various aspects of the quality of predictions, and best performers were awarded. This article presents the challenge results and introduces to the community the approaches of the best overall three performers, as well as an R package that implements the approach of the best overall team. The analyses of model performance data submitted in the challenge as well as additional simulations that we have performed revealed that (i) the quality of predictions depends more on the disease endpoint than on the particular approaches used in the challenge; (ii) the most important modeling factor (e.g. data preprocessing, feature selection and classifier type) is problem dependent; and (iii) for optimal results datasets and methods have to be carefully matched. Biomedical factors such as the disease severity and confidence in diagnostic were found to be associated with the misclassification rates across the different teams. AVAILABILITY: The lung cancer dataset is available from Gene Expression Omnibus (accession, GSE43580). The maPredictDSC R package implementing the approach of the best overall team is available at www.bioconductor.org or http://bioinformaticsprb.med.wayne.edu/