Bespoke Biomolecular Wires for Transmembrane Electron Transfer: Spontaneous Assembly of a Functionalized Multiheme Electron Conduit.

Shewanella oneidensis exchanges electrons between cellular metabolism and external redox partners in a process that attracts much attention for production of green electricity (microbial fuel cells) and chemicals (microbial electrosynthesis). A critical component of this pathway is the outer membrane spanning MTR complex, a biomolecular wire formed of the MtrA, MtrB, and MtrC proteins. MtrA and MtrC are decaheme cytochromes that form a chain of close-packed hemes to define an electron transfer pathway of 185 Å. MtrA is wrapped inside MtrB for solubility across the outer membrane lipid bilayer; MtrC sits outside the cell for electron exchange with external redox partners. Here, we demonstrate tight and spontaneous in vitro association of MtrAB with separately purified MtrC. The resulting complex is comparable with the MTR complex naturally assembled by Shewanella in terms of both its structure and rates of electron transfer across a lipid bilayer. Our findings reveal the potential for building bespoke electron conduits where MtrAB combines with chemically modified MtrC, in this case, labeled with a Ru-dye that enables light-triggered electron injection into the MtrC heme chain

Structural modeling of an outer membrane electron conduit from a metal-reducing bacterium suggests electron transfer via periplasmic redox partners

Many subsurface microorganisms couple their metabolism to the reduction or oxidation of extracellular substrates. For example, anaerobic mineral-respiring bacteria can use external metal oxides as terminal electron acceptors during respiration. Porin–cytochrome complexes facilitate the movement of electrons generated through intracellular catabolic processes across the bacterial outer membrane to these terminal electron acceptors. In the mineral-reducing model bacterium Shewanella oneidensis MR-1, this complex is composed of two decaheme cytochromes (MtrA and MtrC) and an outer-membrane β-barrel (MtrB). However, the structures and mechanisms by which porin–cytochrome complexes transfer electrons are unknown. Here, we used small-angle neutron scattering (SANS) to study the molecular structure of the transmembrane complexes MtrAB and MtrCAB. Ab initio modeling of the scattering data yielded a molecular envelope with dimensions of ∼105 × 60 × 35 Å for MtrAB and ∼170 × 60 × 45 Å for MtrCAB. The shapes of these molecular envelopes suggested that MtrC interacts with the surface of MtrAB, extending ∼70 Å from the membrane surface and allowing the terminal hemes to interact with both MtrAB and an extracellular acceptor. The data also reveal that MtrA fully extends through the length of MtrB, with ∼30 Å being exposed into the periplasm. Proteoliposome models containing membrane-associated MtrCAB and internalized small tetraheme cytochrome (STC) indicate that MtrCAB could reduce Fe(III) citrate with STC as an electron donor, disclosing a direct interaction between MtrCAB and STC. Taken together, both structural and proteoliposome experiments support porin–cytochrome–mediated electron transfer via periplasmic cytochromes such as STC

The low-order wavefront sensor for the PICTURE-C mission

The PICTURE-C mission will fly a 60 cm off-axis unobscured telescope and two high-contrast coronagraphs in successive high-altitude balloon flights with the goal of directly imaging and spectrally characterizing visible scattered light from exozodiacal dust in the interior 1-10 AU of nearby exoplanetary systems. The first flight in 2017 will use a 10[superscript -4] visible nulling coronagraph (previously flown on the PICTURE sounding rocket) and the second flight in 2019 will use a 10[superscript -7] vector vortex coronagraph. A low-order wavefront corrector (LOWC) will be used in both flights to remove time-varying aberrations from the coronagraph wavefront. The LOWC actuator is a 76-channel high-stroke deformable mirror packaged on top of a tip-tilt stage. This paper will detail the selection of a complementary high-speed, low-order wavefront sensor (LOWFS) for the mission. The relative performance and feasibility of several LOWFS designs will be compared including the Shack-Hartmann, Lyot LOWFS, and the curvature sensor. To test the different sensors, a model of the time-varying wavefront is constructed using measured pointing data and inertial dynamics models to simulate optical alignment perturbations and surface deformation in the balloon environment.United States. National Aeronautics and Space Administration (Grant NNX15AG23G S01

The low-order wavefront sensor for the PICTURE-C mission

The PICTURE-C mission will fly a 60 cm off-axis unobscured telescope and two high-contrast coronagraphs in successive high-altitude balloon flights with the goal of directly imaging and spectrally characterizing visible scattered light from exozodiacal dust in the interior 1-10 AU of nearby exoplanetary systems. The first flight in 2017 will use a 10^(-4) visible nulling coronagraph (previously flown on the PICTURE sounding rocket) and the second flight in 2019 will use a 10^(-7) vector vortex coronagraph. A low-order wavefront corrector (LOWC) will be used in both flights to remove time-varying aberrations from the coronagraph wavefront. The LOWC actuator is a 76-channel high-stroke deformable mirror packaged on top of a tip-tilt stage. This paper will detail the selection of a complementary high-speed, low-order wavefront sensor (LOWFS) for the mission. The relative performance and feasibility of several LOWFS designs will be compared including the Shack-Hartmann, Lyot LOWFS, and the curvature sensor. To test the different sensors, a model of the time-varying wavefront is constructed using measured pointing data and inertial dynamics models to simulate optical alignment perturbations and surface deformation in the balloon environment

BIAS: Transparent reporting of biomedical image analysis challenges

The number of biomedical image analysis challenges organized per year is steadily increasing. These international competitions have the purpose of benchmarking algorithms on common data sets, typically to identify the best method for a given problem. Recent research, however, revealed that common practice related to challenge reporting does not allow for adequate interpretation and reproducibility of results. To address the discrepancy between the impact of challenges and the quality (control), the Biomedical Image Analysis ChallengeS (BIAS) initiative developed a set of recommendations for the reporting of challenges. The BIAS statement aims to improve the transparency of the reporting of a biomedical image analysis challenge regardless of field of application, image modality or task category assessed. This article describes how the BIAS statement was developed and presents a checklist which authors of biomedical image analysis challenges are encouraged to include in their submission when giving a paper on a challenge into review. The purpose of the checklist is to standardize and facilitate the review process and raise interpretability and reproducibility of challenge results by making relevant information explicit

Crossing the Dripline to 11N Using Elastic Resonance Scattering

The level structure of the unbound nucleus 11N has been studied by 10C+p elastic resonance scattering in inverse geometry with the LISE3 spectrometer at GANIL, using a 10C beam with an energy of 9.0 MeV/u. An additional measurement was done at the A1200 spectrometer at MSU. The excitation function above the 10C+p threshold has been determined up to 5 MeV. A potential-model analysis revealed three resonance states at energies 1.27 (+0.18-0.05) MeV (Gamma=1.44 +-0.2 MeV), 2.01(+0.15-0.05) MeV, (Gamma=0.84 +-$0.2 MeV) and 3.75(+-0.05) MeV, (Gamma=0.60 +-0.05 MeV) with the spin-parity assignments I(pi) =1/2+, 1/2- and 5/2+, respectively. Hence, 11N is shown to have a ground state parity inversion completely analogous to its mirror partner, 11Be. A narrow resonance in the excitation function at 4.33 (+-0.05) MeV was also observed and assigned spin-parity 3/2-.Comment: 14 pages, 9 figures, twocolumn Accepted for publication in PR

Diffraction evidence for the structure of cellulose microfibrils in bamboo, a model for grass and cereal celluloses

Background: Cellulose from grasses and cereals makes up much of the potential raw material for biofuel production. It is not clear if cellulose microfibrils from grasses and cereals differ in structure from those of other plants. The structures of the highly oriented cellulose microfibrils in the cell walls of the internodes of the bamboo Pseudosasa amabilis are reported. Strong orientation facilitated the use of a range of scattering techniques. Results: Small-angle neutron scattering provided evidence of extensive aggregation by hydrogen bonding through the hydrophilic edges of the sheets of chains. The microfibrils had a mean centre-to-centre distance of 3.0 nm in the dry state, expanding on hydration. The expansion on hydration suggests that this distance between centres was through the hydrophilic faces of adjacent microfibrils. However in the other direction, perpendicular to the sheets of chains, the mean, disorder-corrected Scherrer dimension from wide-angle X-ray scattering was 3.8 nm. It is possible that this dimension is increased by twinning (crystallographic coalescence) of thinner microfibrils over part of their length, through the hydrophobic faces. The wide-angle scattering data also showed that the microfibrils had a relatively large intersheet d-spacing and small monoclinic angle, features normally considered characteristic of primary-wall cellulose. Conclusions: Bamboo microfibrils have features found in both primary-wall and secondary-wall cellulose, but are crystallographically coalescent to a greater extent than is common in celluloses from other plants. The extensive aggregation and local coalescence of the microfibrils are likely to have parallels in other grass and cereal species and to influence the accessibility of cellulose to degradative enzymes during conversion to liquid biofuel

Metrics reloaded: Pitfalls and recommendations for image analysis validation

Increasing evidence shows that flaws in machine learning (ML) algorithm validation are an underestimated global problem. Particularly in automatic biomedical image analysis, chosen performance metrics often do not reflect the domain interest, thus failing to adequately measure scientific progress and hindering translation of ML techniques into practice. To overcome this, our large international expert consortium created Metrics Reloaded, a comprehensive framework guiding researchers in the problem-aware selection of metrics. Following the convergence of ML methodology across application domains, Metrics Reloaded fosters the convergence of validation methodology. The framework was developed in a multi-stage Delphi process and is based on the novel concept of a problem fingerprint - a structured representation of the given problem that captures all aspects that are relevant for metric selection, from the domain interest to the properties of the target structure(s), data set and algorithm output. Based on the problem fingerprint, users are guided through the process of choosing and applying appropriate validation metrics while being made aware of potential pitfalls. Metrics Reloaded targets image analysis problems that can be interpreted as a classification task at image, object or pixel level, namely image-level classification, object detection, semantic segmentation, and instance segmentation tasks. To improve the user experience, we implemented the framework in the Metrics Reloaded online tool, which also provides a point of access to explore weaknesses, strengths and specific recommendations for the most common validation metrics. The broad applicability of our framework across domains is demonstrated by an instantiation for various biological and medical image analysis use cases

Serum Neurotrophin Profile in Systemic Sclerosis

International audienceBACKGROUND: Neurotrophins (NTs) are able to activate lymphocytes and fibroblasts; they can modulate angiogenesis and sympathic vascular function. Thus, they can be implicated in the three pathogenic processes of systemic sclerosis (SSc). The aims of this study are to determine blood levels of Nerve Growth Factor (NGF), Brain-Derived Neurotrophic Factor (BDNF) and Neurotrophin-3 (NT-3) in SSc and to correlate them with clinical and biological data.METHODS: Serum samples were obtained from 55 SSc patients and 32 control subjects to measure NTs levels by ELISA and to determine their relationships with SSc profiles. FINDINGS: Serum NGF levels were higher in SSc patients (288.26 ± 170.34 pg/mL) than in control subjects (170.34 ± 50.8 pg/mL, p<0.001) and correlated with gammaglobulins levels and the presence of both anti-cardiolipin and anti-Scl-70 antibodies (p<0.05). In contrast, BDNF levels were lower in SSc patients than in controls (1121.9 ± 158.1 vs 1372.9 ± 190.9 pg/mL, p<0.0001), especially in pulmonary arterial hypertension and diffuse SSc as compared to limited forms (all p<0.05). NT-3 levels were similar in SSc and in the control group (2657.2 ± 2296 vs 2959.3 ± 2555 pg/mL, NS). BDNF levels correlated negatively with increased NGF levels in the SSc group (and not in controls). CONCLUSION: Low BDNF serum levels were not previously documented in SSc, particularly in the diffuse SSc subset and in patients with pulmonary hypertension or anti-Scl-70 antibodies. The negative correlation between NGF and BDNF levels observed in SSc and not in healthy controls could be implicated in sympathic vascular dysfunction in SSc

Understanding metric-related pitfalls in image analysis validation

Validation metrics are key for the reliable tracking of scientific progress and for bridging the current chasm between artificial intelligence (AI) research and its translation into practice. However, increasing evidence shows that particularly in image analysis, metrics are often chosen inadequately in relation to the underlying research problem. This could be attributed to a lack of accessibility of metric-related knowledge: While taking into account the individual strengths, weaknesses, and limitations of validation metrics is a critical prerequisite to making educated choices, the relevant knowledge is currently scattered and poorly accessible to individual researchers. Based on a multi-stage Delphi process conducted by a multidisciplinary expert consortium as well as extensive community feedback, the present work provides the first reliable and comprehensive common point of access to information on pitfalls related to validation metrics in image analysis. Focusing on biomedical image analysis but with the potential of transfer to other fields, the addressed pitfalls generalize across application domains and are categorized according to a newly created, domain-agnostic taxonomy. To facilitate comprehension, illustrations and specific examples accompany each pitfall. As a structured body of information accessible to researchers of all levels of expertise, this work enhances global comprehension of a key topic in image analysis validation.Comment: Shared first authors: Annika Reinke, Minu D. Tizabi; shared senior authors: Paul F. J\"ager, Lena Maier-Hei