Osteoderm histology of the Pampatheriidae (Cingulata,Xenarthra, Mammalia): Implications for systematics,osteoderm growth,and biomechanical adaptation

Pampatheres are extinct, large‐bodied cingulates, which share morphological characters with both armadillos and glyptodonts but are considered to be more closely related to the latter. The osteoderm histology of six pampathere taxa was examined and compared to the histology of other cingulate osteoderms. This study investigates the development and functional adaptation of pampathere osteoderms as well as the phylogenetic relationships of the Pampatheriidae within the Cingulata. We found that pampathere osteoderms share a uniform histological organization based on a basic diploe‐like structure. After initial stages of intramembranous growth, metaplastic ossification, that is, the direct incorporation and mineralization of pre‐existing protein fibers, plays an important role in osteoderm development and provides information on various kinds of soft tissue otherwise not preserved. The latest stages of osteoderm growth are dominated by periosteal bone formation especially in the superficial cortex. Movable band osteoderms show regular arrangements of incorporated fibers that may increase the resistance of particularly weak areas against strain. The histological composition of pampathere osteoderms is plesiomorphic in its basic structure but shows a number of derived features. A unique array of Sharpey's fibers that are incorporated into the bone matrix at sutured osteoderm margins is interpreted as a synapomorphy of pampatheres. The arrangement of dermal fibers in the deep and superficial cortexes supports the close relationship between pampatheres and glyptodonts. J. Morphol., 2012. © 2011 Wiley Periodicals, Inc.     

Development of Eye Position Dependency of Slow Phase Velocity during Caloric Stimulation

The nystagmus in patients with vestibular disorders often has an eye position dependency, called Alexander’s law, where the slow phase velocity is higher with gaze in the fast phase direction compared with gaze in the slow phase direction. Alexander’s law has been hypothesized to arise either due to adaptive changes in the velocity-to-position neural integrator, or as a consequence of processing of the vestibular-ocular reflex. We tested whether Alexander’s law arises only as a consequence of non-physiologic vestibular stimulation. We measured the time course of the development of Alexander’s law in healthy humans with nystagmus caused by three types of caloric vestibular stimulation: cold (unilateral inhibition), warm (unilateral excitation), and simultaneous bilateral bithermal (one side cold, the other warm) stimulation, mimicking the normal push-pull pattern of vestibular stimulation. Alexander’s law, measured as a negative slope of the velocity versus position curve, was observed in all conditions. A reversed pattern of eye position dependency (positive slope) was found <10% of the time. The slope often changed with nystagmus velocity (cross-correlation of nystagmus speed and slope was significant in 50% of cases), and the average lag of the slope with the speed was not significantly different from zero. Our results do not support the hypothesis that Alexander’s law can only be observed with non-physiologic vestibular stimulation. Further, the rapid development of Alexander’s law, while possible for an adaptive mechanism, is nonetheless quite fast compared to most other ocular motor adaptations. These results suggest that Alexander’s law may not be a consequence of a true adaptive mechanism.     

Metallothionein induction by nonsteroidal antiinflammatory drugs

In the present study we report on the effects of commonly used nonsteroidal antiinflammatory drugs on metallothionein (MT) and MT-I mRNA levels. A single dose of chloroquine (100 mg/kg), diclofenac (100 mg/kg), indomethacin (10 mg/kg), or piroxicam (100 mg/kg) was administered ip to C57B1 mice. After 18 h, MT levels were determined with a Cd-saturation radioassay. MT-I mRNA levels were measured by Northern Blot analyses using a probe containing the mouse MT-I gene. All drugs tested caused an increase in the MT content of the liver but not of the kidneys and lung. The lowest and highest effects were observed with chloroquine (8 times the control value) and diclofenac (18 times), respectively. In accordance with the stimulation of MT synthesis, increased accumulation of hepatic MT-I mRNA could be demonstrated. These results indicate that elevated MT levels may contribute to the effectiveness of nonsteroidal antiinflammatory drugs in the treatment of rheumatoid arthritis (RA).     

Conversion of 2-chloromaleylacetate in Alcaligenes eutrophus JMP134

2,4-Dichlorophenoxyacetate (2,4-D) in Alcaligenes eutrophus JMP134 (pJP4) is degraded via 2-chloromaleylacetate as an intermediate. The latter compound was found to be reduced by NADH in a maleylacetate reductase catalyzed reaction. Maleylacetate and chloride were formed as products of 2-chloromaleylacetate reduction, the former being funnelled into the 3-oxoadipate pathway by a second reductive step. There was no indication for an involvement of a pJP4-encoded enzyme in either the reduction or the dechlorination reaction.Abbreviations 2,4-D 2,4-dichlorophenoxyacetate     

The unexpected long period of elevated CH4 emissions from an inundated fen meadow ended only with the occurrence of cattail (Typha latifolia)

Drainage and agricultural use transform natural peatlands from a net carbon (C) sink to a net C source. Rewetting of peatlands, despite of high methane (CH₄) emissions, holds the potential to mitigate climate change by greatly reducing CO₂ emissions. However, the time span for this transition is unknown because most studies are limited to a few years. Especially, nonpermanent open water areas often created after rewetting, are highly productive. Here, we present 14 consecutive years of CH₄ flux measurements following rewetting of a formerly long-term drained peatland in the Peene valley. Measurements were made at two rewetted sites (non-inundated vs. inundated) using manual chambers. During the study period, significant differences in measured CH₄ emissions occurred. In general, these differences overlapped with stages of ecosystem transition from a cultivated grassland to a polytrophic lake dominated by emergent helophytes, but could also be additionally explained by other variables. This transition started with a rapid vegetation shift from dying cultivated grasses to open water floating and submerged hydrophytes and significantly increased CH₄ emissions. Since 2008, helophytes have gradually spread from the shoreline into the open water area, especially in drier years. This process was periodically delayed by exceptional inundation and eventually resulted in the inundated site being covered by emergent helophytes. While the period between 2009 and 2015 showed exceptionally high CH₄ emissions, these decreased significantly after cattail and other emergent helophytes became dominant at the inundated site. Therefore, CH₄ emissions declined only after 10 years of transition following rewetting, potentially reaching a new steady state. Overall, this study highlights the importance of an integrative approach to understand the shallow lakes CH₄ biogeochemistry, encompassing the entire area with its mosaic of different vegetation forms. This should be ideally done through a study design including proper measurement site allocation as well as long-term measurements.     

Combining industrial ecology tools to assess potential greenhouse gas reductions of a circular economy: Method development and application to Switzerland

Industrial ecology (IE) methodologies, such as input/output or material flow analysis and life cycle assessment (LCA), are often used for the environmental evaluation of circular economy strategies. Up to now, an approach that utilizes these methods in a systematic, integrated framework for a holistic assessment of a geographic region's sustainable circular economy potential has been lacking. The approach developed in this study (IE4CE approach) combines IE methodologies to determine the environmental impact mitigation potential of circular economy strategies for a defined geographic region. The approach foresees five steps. First, input/output analysis helps identify sectors with high environmental impacts. Second, a refined analysis is conducted using material flow and LCA. In step 3, circular strategies are used for scenario design and evaluated in step 4. In step 5, the assessment results are compiled and compared across sectors. The approach was applied to a case study of Switzerland, analyzing 8 sectors and more than 30 scenarios in depth. Carbon capture and storage (CCS) from waste incineration, biogas and cement production, food waste prevention in households, hospitality and production, and the increased recycling of plastics had the highest mitigation potential. Most of the scenarios do not influence each other. One exception is the CCS scenarios: waste avoidance scenarios decrease the reduction potential of CCS. A combination of scenarios from different sectors, including their impact on the CCS scenario potential, led to an environmental impact mitigation potential of 11.9 Mt CO₂-eq for 2050, which equals 14% of Switzerland's current consumption-based impacts.     

A review of methods to trace material flows into final products in dynamic material flow analysis: From industry shipments in physical units to monetary input–output tables,Part 1

Dynamic material flow analysis (dMFA) is widely used to model stock-flow dynamics. To appropriately represent material lifetimes, recycling potentials, and service provision, dMFA requires data about the allocation of economy-wide material consumption to different end-use products or sectors, that is, the different product stocks, in which material consumption accumulates. Previous estimates of this allocation only cover few years, countries, and product groups. Recently, several new methods for estimating end-use product allocation in dMFA were proposed, which so far lack systematic comparison. We review and systematize five methods for tracing material consumption into end-use products in inflow-driven dMFA and discuss their strengths and limitations. Widely used data on industry shipments in physical units have low spatio-temporal coverage, which limits their applicability across countries and years. Monetary input–output tables (MIOTs) are widely available and their economy-wide coverage makes them a valuable source to approximate material end-uses. We find four distinct MIOT-based methods: consumption-based, waste input–output MFA (WIO-MFA), Ghosh absorbing Markov chain, and partial Ghosh. We show that when applied to a given MIOT, the methods’ underlying input–output models yield the same results, with the exception of the partial Ghosh method, which involves simplifications. For practical applications, the MIOT system boundary must be aligned to those of dMFA, which involves the removal of service flows, sector (dis)aggregation, and re-defining specific intermediate outputs as final demand. Theoretically, WIO-MFA, applied to a modified MIOT, produces the most accurate results as it excludes massless and waste transactions. In part 2 of this work, we compare methods empirically and suggest improvements for aligning MIOT-dMFA system boundaries.     

PocketOptimizer 2.0: A modular framework for computer-aided ligand-binding design

The ability to design customized proteins to perform specific tasks is of great interest. We are particularly interested in the design of sensitive and specific small molecule ligand-binding proteins for biotechnological or biomedical applications. Computational methods can narrow down the immense combinatorial space to find the best solution and thus provide starting points for experimental procedures. However, success rates strongly depend on accurate modeling and energetic evaluation. Not only intra- but also intermolecular interactions have to be considered. To address this problem, we developed PocketOptimizer, a modular computational protein design pipeline, that predicts mutations in the binding pockets of proteins to increase affinity for a specific ligand. Its modularity enables users to compare different combinations of force fields, rotamer libraries, and scoring functions. Here, we present a much-improved version––PocketOptimizer 2.0. We implemented a cleaner user interface, an extended architecture with more supported tools, such as force fields and scoring functions, a backbone-dependent rotamer library, as well as different improvements in the underlying algorithms. Version 2.0 was tested against a benchmark of design cases and assessed in comparison to the first version. Our results show how newly implemented features such as the new rotamer library can lead to improved prediction accuracy. Therefore, we believe that PocketOptimizer 2.0, with its many new and improved functionalities, provides a robust and versatile environment for the design of small molecule-binding pockets in proteins. It is widely applicable and extendible due to its modular framework. PocketOptimizer 2.0 can be downloaded at https://github.com/Hoecker-Lab/pocketoptimizer .