Carbon and nitrogen fluxes associated with the cyanobacterium Aphanizomenon sp. in the Baltic Sea

Carbon and nitrogen fluxes in Aphanizomenon sp. colonies in the Baltic Sea were measured using a combination of microsensors, stable isotopes, mass spectrometry, and nanoscale secondary ion mass spectrometry (nanoSIMS). Cell numbers varied between 956 and 33 000 in colonies ranging in volume between 1.4 × 10−4 and 230 × 10−4 mm−3. The high cell content and their productivity resulted in steep O2 gradients at the colony–water interface as measured with an O2 microsensor. Colonies were highly autotrophic communities with few heterotrophic bacteria attached to the filaments. Volumetric gross photosynthesis in colonies was 78 nmol O2 mm−3 h−1. Net photosynthesis was 64 nmol O2 mm−3 h−1, and dark respiration was on average 15 nmol O2 mm−3 h−1 or 16% of gross photosynthesis. These volumetric photosynthesis rates belong to the highest measured in aquatic systems. The average cell-specific net carbon-fixation rate was 38 and 40 fmol C cell−1 h−1 measured by microsensors and by using stable isotopes in combination with mass spectrometry and nanoSIMS, respectively. In light, the net C:N fixation ratio of individual cells was 7.3±3.4. Transfer of fixed N2 from heterocysts to vegetative cells was fast, but up to 35% of the gross N2 fixation in light was released as ammonium into the surrounding water. Calculations based on a daily cycle showed a net C:N fixation ratio of 5.3. Only 16% of the bulk N2 fixation in dark was detected in Aphanizomenon sp. Hence, other organisms appeared to dominate N2 fixation and NH4+ release during darkness

Single‐cell and population level viral infection dynamics revealed by phage FISH , a method to visualize intracellular and free viruses

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/99658/1/emi12100.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/99658/2/emi12100-sup-0001-suppl.pd

efam: an expanded, metaproteome-supported HMM profile database of viral protein families

Motivation: Viruses infect, reprogram and kill microbes, leading to profound ecosystem consequences, from elemental cycling in oceans and soils to microbiome-modulated diseases in plants and animals. Although metagenomic datasets are increasingly available, identifying viruses in them is challenging due to poor representation and annotation of viral sequences in databases. Results: Here, we establish efam, an expanded collection of Hidden Markov Model (HMM) profiles that represent viral protein families conservatively identified from the Global Ocean Virome 2.0 dataset. This resulted in 240 311 HMM profiles, each with at least 2 protein sequences, making efam >7-fold larger than the next largest, panecosystem viral HMM profile database. Adjusting the criteria for viral contig confidence from 'conservative' to 'eXtremely Conservative' resulted in 37 841 HMM profiles in our efam-XC database. To assess the value of this resource, we integrated efam-XC into VirSorter viral discovery software to discover viruses from less-studied, ecologically distinct oxygen minimum zone (OMZ) marine habitats. This expanded database led to an increase in viruses recovered from every tested OMZ virome by similar to 24% on average (up to similar to 42%) and especially improved the recovery of often-missed shorter contigs (<5 kb). Additionally, to help elucidate lesser-known viral protein functions, we annotated the profiles using multiple databases from the DRAM pipeline and virion-associated metaproteomic data, which doubled the number of annotations obtainable by standard, single-database annotation approaches. Together, these marine resources (efam and efam-XC) are provided as searchable, compressed HMM databases that will be updated bi-annually to help maximize viral sequence discovery and study from any ecosystem

Extremely long quasiparticle spin lifetimes in superconducting aluminium using MgO tunnel spin injectors

There has been an intense search in recent years for long-lived spin-polarized carriers for spintronic and quantum-computing devices. Here we report that spin polarized quasi-particles in superconducting aluminum layers have surprisingly long spin-lifetimes, nearly a million times longer than in their normal state. The lifetime is determined from the suppression of the aluminum's superconductivity resulting from the accumulation of spin polarized carriers in the aluminum layer using tunnel spin injectors. A Hanle effect, observed in the presence of small in-plane orthogonal fields, is shown to be quantitatively consistent with the presence of long-lived spin polarized quasi-particles. Our experiments show that the superconducting state can be significantly modified by small electric currents, much smaller than the critical current, which is potentially useful for devices involving superconducting qubits

Annotations for Rule-Based Models

The chapter reviews the syntax to store machine-readable annotations and describes the mapping between rule-based modelling entities (e.g., agents and rules) and these annotations. In particular, we review an annotation framework and the associated guidelines for annotating rule-based models of molecular interactions, encoded in the commonly used Kappa and BioNetGen languages, and present prototypes that can be used to extract and query the annotations. An ontology is used to annotate models and facilitate their description

Efam: an expanded, metaproteome-supported HMM profile database of viral protein families

Motivation: Viruses infect, reprogram and kill microbes, leading to profound ecosystem consequences, from elemental cycling in oceans and soils to microbiome-modulated diseases in plants and animals. Although metagenomic datasets are increasingly available, identifying viruses in them is challenging due to poor representation and annotation of viral sequences in databases. Results: Here, we establish efam, an expanded collection of Hidden Markov Model (HMM) profiles that represent viral protein families conservatively identified from the Global Ocean Virome 2.0 dataset. This resulted in 240 311 HMM profiles, each with at least 2 protein sequences, making efam >7-fold larger than the next largest, pan-ecosystem viral HMM profile database. Adjusting the criteria for viral contig confidence from 'conservative' to 'eXtremely Conservative' resulted in 37 841 HMM profiles in our efam-XC database. To assess the value of this resource, we integrated efam-XC into VirSorter viral discovery software to discover viruses from less-studied, ecologically distinct oxygen minimum zone (OMZ) marine habitats. This expanded database led to an increase in viruses recovered from every tested OMZ virome by ∼24% on average (up to ∼42%) and especially improved the recovery of often-missed shorter contigs (<5 kb). Additionally, to help elucidate lesser-known viral protein functions, we annotated the profiles using multiple databases from the DRAM pipeline and virion-associated metaproteomic data, which doubled the number of annotations obtainable by standard, single-database annotation approaches. Together, these marine resources (efam and efam-XC) are provided as searchable, compressed HMM databases that will be updated bi-annually to help maximize viral sequence discovery and study from any ecosystem

Texture spectrum coupled with entropy and homogeneity image features for myocardium muscle characterization

People in middle/later age often suffer from heart muscle damage due to coronary artery disease associated to myocardial infarction. In young people, the genetic forms of cardiomyopathies (heart muscle disease) are the utmost protuberant cause of myocardial disease. Accurate early detected information regarding the myocardial tissue structure is a key answer for tracking the progress of several myocardial diseases. The present work proposes a new method for myocardium muscle texture classification based on entropy, homogeneity and on the texture unit-based texture spectrum approaches. Entropy and homogeneity are generated in moving windows of size 3x3 and 5x5 to enhance the texture features and to create the premise of differentiation of the myocardium structures. Texture is then statistically analyzed using the texture spectrum approach. Texture classification is achieved based on a fuzzy c–means descriptive classifier. The noise sensitivity of the fuzzy c–means classifier is overcome by using the image features. The proposed method is tested on a dataset of 80 echocardiographic ultrasound images in both short-axis and long-axis in apical two chamber view representations, for normal and infarct pathologies. The results established that the entropy-based features provided superior clustering results compared to homogeneity

UBVRI Light Curves of 44 Type Ia Supernovae

We present UBVRI photometry of 44 type-Ia supernovae (SN Ia) observed from 1997 to 2001 as part of a continuing monitoring campaign at the Fred Lawrence Whipple Observatory of the Harvard-Smithsonian Center for Astrophysics. The data set comprises 2190 observations and is the largest homogeneously observed and reduced sample of SN Ia to date, nearly doubling the number of well-observed, nearby SN Ia with published multicolor CCD light curves. The large sample of U-band photometry is a unique addition, with important connections to SN Ia observed at high redshift. The decline rate of SN Ia U-band light curves correlates well with the decline rate in other bands, as does the U-B color at maximum light. However, the U-band peak magnitudes show an increased dispersion relative to other bands even after accounting for extinction and decline rate, amounting to an additional ~40% intrinsic scatter compared to B-band.Comment: 84 authors, 71 pages, 51 tables, 10 figures. Accepted for publication in the Astronomical Journal. Version with high-res figures and electronic data at http://astron.berkeley.edu/~saurabh/cfa2snIa