Testing the Posterior Chain: Diagnostic Accuracy of the Bunkie Test versus the Isokinetic Hamstrings/Quadriceps Measurement in Patients with Self-Reported Knee Pain and Healthy Controls.

(1) Background: The isokinetic measurement (IM) of the leg muscles is well established but costly, whereas the Bunkie Test (BT) is a rarely investigated but easy-to-conduct functional test to evaluate the total posterior chain. Although the tests differ in aim and test structures, both have their justification in the assessment process. Therefore, this study evaluated the diagnostic accuracy of the BT and the IM. (2) Methods: 21 participants (9 female, 12 male; age, 26.2 ± 5.26 years; weight 73.8 ± 14.6 kg; height 176.0 ± 9.91 cm) and 21 patients (9 female, 12 male; age, 26.5 ± 5.56 years; weight, 72.6 ± 16.9 kg; height 177.0 ± 10.1 cm) with self-reported pain in the knee performed the IM and the BT. For IM, we calculated the ratio of the knee mean flexor/extensor peak torque (H/Q ratio) for 60°/s and 120°/s, and BT performance was measured in seconds. We classified the IM (<0.6 H/Q ratio) and the BT (leg difference ≥4 s) as binary results according to the literature. We calculated the sensitivity and specificity, which we compared with the Chi-Square test, and the 95% confidence intervals (CI). A p-value of ≤0.05 is considered significant. (3) Results: The sensitivity for the BT was 0.89, 95% CI [0.67, 0.99], and the specificity was 0.52 [0.30, 0.74]. For the IM, the sensitivity was 0.14 [0.03, 0.36] for 60°/s and 0.05 [0.00, 0.24] for 120°/s, and the specificity was 0.70 [0.46, 0.88] for 60°/s and 0.90 [0.68, 0.99] for 120°/s. The results of the Chi-Square tests were significant for the BT (χ2 (1) = 6.17, p = 0.01) but not for the IM (60°/s: χ2 (1) = 0.70, p = 0.40; 120°/s: χ2 (1) = 0.00, p = 0.97). (4) Conclusions: Patients were more likely to obtain a positive test result for the BT but not for the IM.

An expert system model for mapping tropical wetlands and peatlands reveals South America as the largest contributor.

Wetlands are important providers of ecosystem services and key regulators of climate change. They positively contribute to global warming through their greenhouse gas emissions, and negatively through the accumulation of organic material in histosols, particularly in peatlands. Our understanding of wetlands' services is currently constrained by limited knowledge on their distribution, extent, volume, interannual flood variability and disturbance levels. We present an expert system approach to estimate wetland and peatland areas, depths and volumes, which relies on three biophysical indices related to wetland and peat formation: (1) long-term water supply exceeding atmospheric water demand; (2) annually or seasonally water-logged soils; and (3) a geomorphological position where water is supplied and retained. Tropical and subtropical wetlands estimates reach 4.7 million km2 (Mkm2 ). In line with current understanding, the American continent is the major contributor (45%), and Brazil, with its Amazonian interfluvial region, contains the largest tropical wetland area (800,720 km2 ). Our model suggests, however, unprecedented extents and volumes of peatland in the tropics (1.7 Mkm2 and 7,268 (6,076-7,368) km3 ), which more than threefold current estimates. Unlike current understanding, our estimates suggest that South America and not Asia contributes the most to tropical peatland area and volume (ca. 44% for both) partly related to some yet unaccounted extended deep deposits but mainly to extended but shallow peat in the Amazon Basin. Brazil leads the peatland area and volume contribution. Asia hosts 38% of both tropical peat area and volume with Indonesia as the main regional contributor and still the holder of the deepest and most extended peat areas in the tropics. Africa hosts more peat than previously reported but climatic and topographic contexts leave it as the least peat-forming continent. Our results suggest large biases in our current understanding of the distribution, area and volumes of tropical peat and their continental contributions.

General relationships between abiotic soil properties and soil biota across spatial scales and different land-use types.

Very few principles have been unraveled that explain the relationship between soil properties and soil biota across large spatial scales and different land-use types. Here, we seek these general relationships using data from 52 differently managed grassland and forest soils in three study regions spanning a latitudinal gradient in Germany. We hypothesize that, after extraction of variation that is explained by location and land-use type, soil properties still explain significant proportions of variation in the abundance and diversity of soil biota. If the relationships between predictors and soil organisms were analyzed individually for each predictor group, soil properties explained the highest amount of variation in soil biota abundance and diversity, followed by land-use type and sampling location. After extraction of variation that originated from location or land-use, abiotic soil properties explained significant amounts of variation in fungal, meso- and macrofauna, but not in yeast or bacterial biomass or diversity. Nitrate or nitrogen concentration and fungal biomass were positively related, but nitrate concentration was negatively related to the abundances of Collembola and mites and to the myriapod species richness across a range of forest and grassland soils. The species richness of earthworms was positively correlated with clay content of soils independent of sample location and land-use type. Our study indicates that after accounting for heterogeneity resulting from large scale differences among sampling locations and land-use types, soil properties still explain significant proportions of variation in fungal and soil fauna abundance or diversity. However, soil biota was also related to processes that act at larger spatial scales and bacteria or soil yeasts only showed weak relationships to soil properties. We therefore argue that more general relationships between soil properties and soil biota can only be derived from future studies that consider larger spatial scales and different land-use types.

Pyrosequencing-based assessment of bacterial community structure along different management types in German forest and grassland soils.

BACKGROUND: Soil bacteria are important drivers for nearly all biogeochemical cycles in terrestrial ecosystems and participate in most nutrient transformations in soil. In contrast to the importance of soil bacteria for ecosystem functioning, we understand little how different management types affect the soil bacterial community composition. METHODOLOGY/PRINCIPAL FINDINGS: We used pyrosequencing-based analysis of the V2-V3 16S rRNA gene region to identify changes in bacterial diversity and community structure in nine forest and nine grassland soils from the Schwäbische Alb that covered six different management types. The dataset comprised 598,962 sequences that were affiliated to the domain Bacteria. The number of classified sequences per sample ranged from 23,515 to 39,259. Bacterial diversity was more phylum rich in grassland soils than in forest soils. The dominant taxonomic groups across all samples (>1% of all sequences) were Acidobacteria, Alphaproteobacteria, Actinobacteria, Betaproteobacteria, Deltaproteobacteria, Gammaproteobacteria, and Firmicutes. Significant variations in relative abundances of bacterial phyla and proteobacterial classes, including Actinobacteria, Firmicutes, Verrucomicrobia, Cyanobacteria, Gemmatimonadetes and Alphaproteobacteria, between the land use types forest and grassland were observed. At the genus level, significant differences were also recorded for the dominant genera Phenylobacter, Bacillus, Kribbella, Streptomyces, Agromyces, and Defluviicoccus. In addition, soil bacterial community structure showed significant differences between beech and spruce forest soils. The relative abundances of bacterial groups at different taxonomic levels correlated with soil pH, but little or no relationships to management type and other soil properties were found. CONCLUSIONS/SIGNIFICANCE: Soil bacterial community composition and diversity of the six analyzed management types showed significant differences between the land use types grassland and forest. Furthermore, bacterial community structure was largely driven by tree species and soil pH.

Horizon-specific bacterial community composition of German grassland soils, as revealed by pyrosequencing-based analysis of 16S rRNA genes.

The diversity of bacteria in soil is enormous, and soil bacterial communities can vary greatly in structure. Here, we employed a pyrosequencing-based analysis of the V2-V3 16S rRNA gene region to characterize the overall and horizon-specific (A and B horizons) bacterial community compositions in nine grassland soils, which covered three different land use types. The entire data set comprised 752,838 sequences, 600,544 of which could be classified below the domain level. The average number of sequences per horizon was 41,824. The dominant taxonomic groups present in all samples and horizons were the Acidobacteria, Betaproteobacteria, Actinobacteria, Gammaproteobacteria, Alphaproteobacteria, Deltaproteobacteria, Chloroflexi, Firmicutes, and Bacteroidetes. Despite these overarching dominant taxa, the abundance, diversity, and composition of bacterial communities were horizon specific. In almost all cases, the estimated bacterial diversity (H') was higher in the A horizons than in the corresponding B horizons. In addition, the H' was positively correlated with the organic carbon content, the total nitrogen content, and the C-to-N ratio, which decreased with soil depth. It appeared that lower land use intensity results in higher bacterial diversity. The majority of sequences affiliated with the Actinobacteria, Bacteroidetes, Cyanobacteria, Fibrobacteres, Firmicutes, Spirochaetes, Verrucomicrobia, Alphaproteobacteria, Betaproteobacteria, and Gammaproteobacteria were derived from A horizons, whereas the majority of the sequences related to Acidobacteria, Chloroflexi, Gemmatimonadetes, Nitrospira, TM7, and WS3 originated from B horizons. The distribution of some bacterial phylogenetic groups and subgroups in the different horizons correlated with soil properties such as organic carbon content, total nitrogen content, or microbial biomass.

Conservation of the protein composition and electron microscopy structure of Drosophila melanogaster and human spliceosomal complexes.

Comprehensive proteomics analyses of spliceosomal complexes are currently limited to those in humans, and thus, it is unclear to what extent the spliceosome's highly complex composition and compositional dynamics are conserved among metazoans. Here we affinity purified Drosophila melanogaster spliceosomal B and C complexes formed in Kc cell nuclear extract. Mass spectrometry revealed that their composition is highly similar to that of human B and C complexes. Nonetheless, a number of Drosophila-specific proteins were identified, suggesting that there may be novel factors contributing specifically to splicing in flies. Protein recruitment and release events during the B-to-C transition were also very similar in both organisms. Electron microscopy of Drosophila B complexes revealed a high degree of structural similarity with human B complexes, indicating that higher-order interactions are also largely conserved. A comparison of Drosophila spliceosomes formed on a short versus long intron revealed only small differences in protein composition but, nonetheless, clear structural differences under the electron microscope. Finally, the characterization of affinity-purified Drosophila mRNPs indicated that exon junction complex proteins are recruited in a splicing-dependent manner during C complex formation. These studies provide insights into the evolutionarily conserved composition and structure of the metazoan spliceosome, as well as its compositional dynamics during catalytic activation.