Broadening the mission of an RNA enzyme

The “RNA World” hypothesis suggests that life developed from RNA enzymes termed ribozymes, which carry out reactions without assistance from proteins. Ribonuclease (RNase) P is one ribozyme that appears to have adapted these origins to modern cellular life by adding protein to the RNA core in order to broaden the potential functions. This RNA-protein complex plays diverse roles in processing RNA, but its best-understood reaction is pre-tRNA maturation, resulting in mature 5' ends of tRNAs. The core catalytic activity resides in the RNA subunit of almost all RNase P enzymes but broader substrate tolerance is required for recognizing not only the diverse sequences of tRNAs, but also additional cellular RNA substrates. This broader substrate tolerance is provided by the addition of protein to the RNA core and allows RNase P to selectively recognize different RNAs, and possibly ribonucleoprotein (RNP) substrates. Thus, increased protein content correlated with evolution from bacteria to eukaryotes has further enhanced substrate potential enabling the enzyme to function in a complex cellular environment. J. Cell. Biochem. 108: 1244–1251, 2009. © 2009 Wiley-Liss, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/64531/1/22367_ftp.pd

Visual Analysis of Spatio-Temporal Event Predictions: Investigating the Spread Dynamics of Invasive Species

Invasive species are a major cause of ecological damage and commercial losses. A current problem spreading in North America and Europe is the vinegar fly Drosophila suzukii. Unlike other Drosophila, it infests non-rotting and healthy fruits and is therefore of concern to fruit growers, such as vintners. Consequently, large amounts of data about infestations have been collected in recent years. However, there is a lack of interactive methods to investigate this data. We employ ensemble-based classification to predict areas susceptible to infestation by D. suzukii and bring them into a spatio-temporal context using maps and glyph-based visualizations. Following the information-seeking mantra, we provide a visual analysis system Drosophigator for spatio-temporal event prediction, enabling the investigation of the spread dynamics of invasive species. We demonstrate the usefulness of this approach in two use cases

Anisotropic Carbon Nanotube Structures with High Aspect Ratio Nanopores for Li-Ion Battery Anodes.

Technological advances in membrane technology, catalysis, and electrochemical energy storage require the fabrication of controlled pore structures at ever smaller length scales. It is therefore important to develop processes allowing for the fabrication of materials with controlled submicron porous structures. We propose a combination of colloidal lithography and chemical vapor deposition of carbon nanotubes to create continuous straight pores with diameters down to 100 nm in structures with thicknesses of more than 300 μm. These structures offer unique features, including continuous and parallel pores with aspect ratios in excess of 3000, a low pore tortuosity, good electrical conductivity, and electrochemical stability. We demonstrate that these structures can be used in Li-ion batteries by coating the carbon nanotubes with Si as an active anode material

Milk fatty acids estimated by mid-infrared spectroscopy and milk yield can predict methane emissions in dairy cows

Ruminant enteric methane emission contributes to global warming. Although breeding low methane-emitting cows appears to be possible through genetic selection, doing so requires methane emission quantification by using elaborate instrumentation (respiration chambers, SF6 technique, GreenFeed) not feasible on a large scale. It has been suggested that milk fatty acids are promising markers of methane production. We hypothesized that methane emission can be predicted from the milk fatty acid concentrations determined by mid-infrared spectroscopy, and the integration of energy-corrected milk yield would improve the prediction. Therefore, we examined relationships between methane emission of cows measured in respiration chambers and milk fatty acids, predicted by mid-infrared spectroscopy, to derive diet-specific and general prediction equations based on milk fatty acid concentrations alone and with the additional consideration of energy-corrected milk yield. Cows were fed diets differing in forage type and linseed supplementation to generate a large variation in both CH4 emission and milk fatty acids. Depending on the diet, equations derived from regression analysis explained 61 to 96% of variation of methane emission, implying the potential of milk fatty acid data predicted by mid-infrared spectroscopy as novel proxy for direct methane emission measurements. When data from all diets were analyzed collectively, the equation with energy-corrected milk yield (CH4 (L/day) = − 1364 + 9.58 × energy-corrected milk yield + 18.5 × saturated fatty acids + 32.4 × C18:0) showed an improved coefficient of determination of cross-validation R2 CV = 0.72 compared to an equation without energy-corrected milk yield (R2 CV = 0.61). Equations developed for diets supplemented by linseed showed a lower R2 CV as compared to diets without linseed (0.39 to 0.58 vs. 0.50 to 0.91). We demonstrate for the first time that milk fatty acid concentrations predicted by mid-infrared spectroscopy together with energy-corrected milk yield can be used to estimate enteric methane emission in dairy cows. © 2018, The Author(s)

Methane prediction based on individual or groups of milk fatty acids for dairy cows fed rations with or without linseed

Milk fatty acids (MFA) are a proxy for the prediction of CH4 emission from cows, and prediction differs with diet. Our objectives were (1) to compare the effect of diets on the relation between MFA profile and measured CH4 production, (2) to predict CH4 production based on 6 data sets differing in the number and type of MFA, and (3) to test whether additional inclusion of energy-corrected milk (ECM) yield or dry matter intake (DMI) as explanatory variables improves predictions. Twenty dairy cows were used. Four diets were used based on corn silage (CS) or grass silage (GS) without (L0) or with linseed (LS) supplementation. Ten cows were fed CS-L0 and CS-LS and the other 10 cows were fed GS-L0 and GS-LS in random order. In feeding wk 5 of each diet, CH4 production (L/d) was measured in respiration chambers for 48 h and milk was analyzed for MFA concentrations by gas chromatography. Specific CH4 prediction equations were obtained for L0-, LS-, GS-, and CS-based diets and for all 4 diets collectively and validated by an internal cross-validation. Models were developed containing either 43 identified MFA or a reduced set of 7 groups of biochemically related MFA plus C16:0 and C18:0. The CS and LS diets reduced CH4 production compared with GS and L0 diets, respectively. Methane yield (L/kg of DMI) reduction by LS was higher with CS than GS diets. The concentrations of C18:1 trans and n-3 MFA differed among GS and CS diets. The LS diets resulted in a higher proportion of unsaturated MFA at the expense of saturated MFA. When using the data set of 43 individual MFA to predict CH4 production (L/d), the cross-validation coefficient of determination (R2 CV) ranged from 0.47 to 0.92. When using groups of MFA variables, the R2 CV ranged from 0.31 to 0.84. The fit parameters of the latter models were improved by inclusion of ECM or DMI, but not when added to the data set of 43 MFA for all diets pooled. Models based on GS diets always had a lower prediction potential (R2 CV = 0.31 to 0.71) compared with data from CS diets (R2 CV = 0.56 to 0.92). Models based on LS diets produced lower prediction with data sets with reduced MFA variables (R2 CV = 0.62 to 0.68) compared with L0 diets (R2 CV = 0.67 to 0.80). The MFA C18:1 cis-9 and C24:0 and the monounsaturated FA occurred most often in models. In conclusion, models with a reduced number of MFA variables and ECM or DMI are suitable for CH4 prediction, and CH4 prediction equations based on diets containing linseed resulted in lower prediction accuracy. © 2019 American Dairy Science Associatio

Nutzen der Digitalisierung auf eine nachhaltige Landschafts- und Raumentwicklung: Ergebnisse einer breit angelegten Delphi-Umfrage in der Schweiz

Digitalisierung verändert die Anforderungen an den Raum, dessen Nutzungen und damit Raum und Landschaft selbst. Für Technik und Fachplanungen kristallisieren sich die Entwicklungstrends allmählich heraus. Doch wie sich die Digitalisierung auf den Raum und die Planung konkret auswirkt, ist momentan noch kaum erforscht. Auswirkungen der Digitalisierung werden in den Bereichen Mobilität, Energie und Versorgung besonders deutlich, aber auch in Bezug auf Freizeit und Erholung und die flächenhaften Nutzungen werden Trends in der Fachwelt diskutiert.Hier erste Antworten und Hilfestellungen für die Planung in den Gemeinden und Regionen zu finden, um deren Handlungsfähigkeit im Zeitalter der Digitalisierung zu erhöhen, ist Ziel des Forschungsprojekts „NUDIG – Nutzen der Digitalisierung für eine nachhaltige Landschafts- und Raumentwicklung“ der HSR Hochschule für Technik Rapperswil / Schweiz. Als Grundlage werden im ersten Schritt aus der Literatur und aus beschriebene Auswirkungen der Digitalisierung vom Forschungsteam systematisiert und bewertet. Als Ergebnis der Desktoprecherche kann die Raumwirksamkeit der Digitalisierung und mögliche Steuerungsansätze phänomenologisch beschrieben werden, eine Evidenz oder sogar Empirie über die Raumwirksamkeit lässt sich hingegen nicht ableiten. Eine empirische Untersuchung der Raumwirksamkeit der Digitalisierung, die sich mit mehreren Disziplinen der räumlichen Planung und deren Wechselwirkungen befasst, scheint zumindest zum jetzigen Zeitpunkt nicht möglich. Um die Ergebnisse und die darausfolgenden Thesen der Literaturrecherche dennoch zu plausibilisieren wurde eine zweifstufige Delphi-Umfrage gestartet, wo Fachexpertinnen und Fachexperten der einzelnen Planungsdisziplinen gefragt sind,ihre Einschätzungen zu den Auswirkungen und dem Nutzen der Digitalisierung auf die Planung abzugeben. Das zentrale Ergebnis der Umfrage ist, dass sich die Fachdisziplinen der Digitalisierung nicht verweigern können und die Raumnutzungen und die Wahrnehmung von Raum beeinflusst und verändert werden. Die Digitalisierung eröffnet für alle Raumkategorien und die unterschiedlichen Fachdisziplinen Potenziale für eine nachhaltige Entwicklung, wenngleich die einzelnen positiven und auch negativen Einschätzungen derFachdisziplinen variieren. Dieser Beitrag soll daher einerseits die Vorgehensweise der Delphi-Umfrage beleuchten sowie die relevantesten Ergebnisse und Schlussfolgerungen aus der Umfrage erläutern. Andererseits liegt der Fokus auf der Frage ob mithilfe der Digitalisierung und der dadurch entstehenden neuen planerischen Perspektiven, eine Trendumkehr, eine umweltverträglichere und ressourceneffizientere Raum-, Verkehrs- und Landschaftsplanung, unterstützt und wie dieser Aspekt von der Fachwelt beurteilt wird

Intra-oral compartment pressures: a biofunctional model and experimental measurements under different conditions of posture

Oral posture is considered to have a major influence on the development and reoccurrence of malocclusion. A biofunctional model was tested with the null hypotheses that (1) there are no significant differences between pressures during different oral functions and (2) between pressure measurements in different oral compartments in order to substantiate various postural conditions at rest by intra-oral pressure dynamics. Atmospheric pressure monitoring was simultaneously carried out with a digital manometer in the vestibular inter-occlusal space (IOS) and at the palatal vault (sub-palatal space, SPS). Twenty subjects with normal occlusion were evaluated during the open-mouth condition (OC), gently closed lips (semi-open compartment condition, SC), with closed compartments after the generation of a negative pressure (CCN) and swallowing (SW). Pressure curve characteristics were compared between the different measurement phases (OC, SC, CCN, SW) as well as between the two compartments (IOS, SPS) using analysis of variance and Wilcoxon matched-pairs tests adopting a significance level of α = 0.05. Both null hypotheses were rejected. Average pressures (IOS, SPS) in the experimental phases were 0.0, −0.08 (OC); −0.16, −1.0 (SC); −48.79, −81.86 (CCN); and −29.25, −62.51 (SW) mbar. CCN plateau and peak characteristics significantly differed between the two compartments SPS and IOS. These results indicate the formation of two different intra-oral functional anatomical compartments which provide a deeper understanding of orofacial biofunctions and explain previous observations of negative intra-oral pressures at rest

Plasma production of nanomaterials for energy storage: continuous gas-phase synthesis of metal oxide CNT materials via a microwave plasma.

In this work we show for the first time that a continuous plasma process can synthesize materials from bulk industrial powders to produce hierarchical structures for energy storage applications. The plasma production process's unique advantages are that it is fast, inexpensive, and scalable due to its high energy density that enables low-cost precursors. The synthesized hierarchical material is comprised of iron oxide and aluminum oxide aggregate particles and carbon nanotubes grown in situ from the iron particles. New aerosol-based methods were used for the first time on a battery material to characterize aggregate and primary particle morphologies, while showing good agreement with observations from TEM measurements. As an anode for lithium ion batteries, a reversible capacity of 870 mA h g-1 based on metal oxide mass was observed and the material showed good recovery from high rate cycling. The high rate of material synthesis (∼10 s residence time) enables this plasma hierarchical material synthesis platform to be optimized as a means for energetic material production for the global energy storage material supply chain

Segmentation of the fascia lata and reproducible quantification of intermuscular adipose tissue (IMAT) of the thigh

Abstract Objective To develop a precise semi-automated segmentation of the fascia lata (FL) of the thigh to quantify IMAT volume in T1w MR images and fat fraction (FF) in Dixon MR images. Materials and methods A multi-step segmentation approach was developed to identify fibrous structures of the FL and combining them into a closed 3D surface. 23 healthy young men with low and 50 elderly sarcopenic men with moderate levels of IMAT were measured by T1w and 6pt Dixon MRI at 3T. 20 datasets were used to determine reanalysis precision errors. IMAT volume was compared using the new FL segmentation versus an easier to segment but less accurate, tightly fitting envelope of the thigh muscle ensemble. Results The segmentation was successfully applied to all 73 datasets and took about 7 min per 28 slices. In particular, in elderly subjects, it includes a large amount of adipose tissue below the FL typically not accounted for in other segmentation approaches. Inter- and intra-operator RMS-CVs were 0.33% and 0.14%, respectively, for IMAT volume and 0.04% and 0.02%, respectively, for FFMT. Discussion The FL segmentation is an important step to quantify IMAT with high precision and may be useful to investigate effects of aging and treatment on changes of IMAT and FF. ClinicalTrials.gov identifier NCT2857660, August 5, 2016. Trial registration ClinicalTrials.gov identifier NCT2857660, August 5, 2016