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Extreme habitats often harbor specific communities that differ substantially from non-extreme habitats. In many cases, these communities are characterized by archaea, bacteria and protists, whereas the number of species of metazoa and higher plants is relatively low. In extremely acidic habitats, mostly prokaryotes and protists thrive, and only very few metazoa thrive, for example, rotifers. Since many studies have investigated the physiology and ecology of individual species, there is still a gap in research on direct, trophic interactions among extremophiles. To fill this gap, we experimentally studied the trophic interactions between a predatory protist (Actinophrys sol, Heliozoa) and its prey, the rotifers Elosa woralli and Cephalodella sp., the ciliate Urosomoida sp. and the mixotrophic protist Chlamydomonas acidophila (a green phytoflagellate, Chlorophyta). We found substantial predation pressure on all animal prey. High densities of Chlamydomonas acidophila reduced the predation impact on the rotifers by interfering with the feeding behaviour of A. sol. These trophic relations represent a natural case of intraguild predation, with Chlamydomonas acidophila being the common prey and the rotifers/ciliate and A. sol being the intraguild prey and predator, respectively. We further studied this intraguild predation along a resource gradient using Cephalodella sp. as the intraguild prey. The interactions among the three species led to an increase in relative rotifer abundance with increasing resource (Chlamydomonas) densities. By applying a series of laboratory experiments, we revealed the complexity of trophic interactions within a natural extremophilic community.
The Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) with its land and vegetation height data product (ATL08), and Global Ecosystem Dynamics Investigation (GEDI) with its terrain elevation and height metrics data product (GEDI Level 2A) missions have great potential to globally map ground and canopy heights. Canopy height is a key factor in estimating above-ground biomass and its seasonal changes; these satellite missions can also improve estimated above-ground carbon stocks. This study presents a novel Sparse Vegetation Detection Algorithm (SVDA) which uses ICESat-2 (ATL03, geolocated photons) data to map tree and vegetation heights in a sparsely vegetated savanna ecosystem. The SVDA consists of three main steps: First, noise photons are filtered using the signal confidence flag from ATL03 data and local point statistics. Second, we classify ground photons based on photon height percentiles. Third, tree and grass photons are classified based on the number of neighbors. We validated tree heights with field measurements (n = 55), finding a root-mean-square error (RMSE) of 1.82 m using SVDA, GEDI Level 2A (Geolocated Elevation and Height Metrics product): 1.33 m, and ATL08: 5.59 m. Our results indicate that the SVDA is effective in identifying canopy photons in savanna ecosystems, where ATL08 performs poorly. We further identify seasonal vegetation height changes with an emphasis on vegetation below 3 m; widespread height changes in this class from two wet-dry cycles show maximum seasonal changes of 1 m, possibly related to seasonal grass-height differences. Our study shows the difficulties of vegetation measurements in savanna ecosystems but provides the first estimates of seasonal biomass changes.
The discovery that certain diseases have specific miRNA signatures which correspond to disease progression opens a new biomarker category. The detection of these small non-coding RNAs is performed routinely using body fluids or tissues with real-time PCR, next-generation sequencing, or amplification-based miRNA assays. Antibody-based detection systems allow an easy onset handling compared to PCR or sequencing and can be considered as alternative methods to support miRNA diagnostic in the future. In this study, we describe the generation of a camelid heavy-chain-only antibody specifically recognizing miRNAs to establish an antibody-based detection method. The generation of nucleic acid-specific binders is a challenge. We selected camelid binders via phage display, expressed them as VHH as well as full-length antibodies, and characterized the binding to several miRNAs from a signature specific for dilated cardiomyopathy. The described workflow can be used to create miRNA-specific binders and establish antibody-based detection methods to provide an additional way to analyze disease-specific miRNA signatures.
Science education researchers have developed a refined understanding of the structure of science teachers’ pedagogical content knowledge (PCK), but how to develop applicable and situation-adequate PCK remains largely unclear. A potential problem lies in the diverse conceptualisations of the PCK used in PCK research. This study sought to systematize existing science education research on PCK through the lens of the recently proposed refined consensus model (RCM) of PCK. In this review, the studies’ approaches to investigating PCK and selected findings were characterised and synthesised as an overview comparing research before and after the publication of the RCM. We found that the studies largely employed a qualitative case-study methodology that included specific PCK models and tools. However, in recent years, the studies focused increasingly on quantitative aspects. Furthermore, results of the reviewed studies can mostly be integrated into the RCM. We argue that the RCM can function as a meaningful theoretical lens for conceptualizing links between teaching practice and PCK development by proposing pedagogical reasoning as a mechanism and/or explanation for PCK development in the context of teaching practice.
Bayesian geomorphology
(2020)
The rapidly growing amount and diversity of data are confronting us more than ever with the need to make informed predictions under uncertainty. The adverse impacts of climate change and natural hazards also motivate our search for reliable predictions. The range of statistical techniques that geomorphologists use to tackle this challenge has been growing, but rarely involves Bayesian methods. Instead, many geomorphic models rely on estimated averages that largely miss out on the variability of form and process. Yet seemingly fixed estimates of channel heads, sediment rating curves or glacier equilibrium lines, for example, are all prone to uncertainties. Neighbouring scientific disciplines such as physics, hydrology or ecology have readily embraced Bayesian methods to fully capture and better explain such uncertainties, as the necessary computational tools have advanced greatly. The aim of this article is to introduce the Bayesian toolkit to scientists concerned with Earth surface processes and landforms, and to show how geomorphic models might benefit from probabilistic concepts. I briefly review the use of Bayesian reasoning in geomorphology, and outline the corresponding variants of regression and classification in several worked examples.
This article explores the structural diversity of intraministerial organization over time. Based on organization theory, it proposes a generic typology for intraministerial units applicable to any hierarchically structured government organization. We empirically investigate the critical case of the German federal bureaucracy. By classifying its subunits, we analyze the longitudinal development of structural differentiation and its correspondence to denominational variety. The data stem from a novel international dataset, covering all ministries between 1980 and 2015. We find that intraministerial structure differentiates over time, across and within ministries. A stable core of traditional Weberian structure is complemented by structurally innovative intraministerial units. We conclude that the German federal bureaucracy is more diverse than suggested in previous literature. Our findings indicate that less Weberian bureaucracies are at least as structurally diverse and that more reform-driven bureaucracies will have experienced at least as many changes in structural diversity.
Cosmic-ray neutron sensing (CRNS) has become an effective method to measure soil moisture at a horizontal scale of hundreds of metres and a depth of decimetres. Recent studies proposed operating CRNS in a network with overlapping footprints in order to cover root-zone water dynamics at the small catchment scale and, at the same time, to represent spatial heterogeneity. In a joint field campaign from September to November 2020 (JFC-2020), five German research institutions deployed 15 CRNS sensors in the 0.4 km2 Wüstebach catchment (Eifel mountains, Germany). The catchment is dominantly forested (but includes a substantial fraction of open vegetation) and features a topographically distinct catchment boundary. In addition to the dense CRNS coverage, the campaign featured a unique combination of additional instruments and techniques: hydro-gravimetry (to detect water storage dynamics also below the root zone); ground-based and, for the first time, airborne CRNS roving; an extensive wireless soil sensor network, supplemented by manual measurements; and six weighable lysimeters. Together with comprehensive data from the long-term local research infrastructure, the published data set (available at https://doi.org/10.23728/b2share.756ca0485800474e9dc7f5949c63b872; Heistermann et al., 2022) will be a valuable asset in various research contexts: to advance the retrieval of landscape water storage from CRNS, wireless soil sensor networks, or hydrogravimetry; to identify scale-specific combinations of sensors and methods to represent soil moisture variability; to improve the understanding and simulation of land–atmosphere exchange as well as hydrological and hydrogeological processes at the hillslope and the catchment scale; and to support the retrieval of soil water content from airborne and spaceborne remote sensing platforms.
Objective
To improve consumer decision making, the results of risk assessments on food, feed, consumer products or chemicals need to be communicated not only to experts but also to non-expert audiences. The present study draws on evidence from literature reviews and focus groups with diverse stakeholders to identify content to integrate into an existing risk assessment communication (Risk Profile).
Methods
A combination of rapid literature reviews and focus groups with experts (risk assessors (n = 15), risk managers (n = 8)), and non-experts (general public (n = 18)) were used to identify content and strategies for including information about risk assessment results in the “Risk Profile” from the German Federal Institute for Risk Assessment. Feedback from initial focus groups was used to develop communication prototypes that informed subsequent feedback rounds in an iterative process. A final prototype was validated in usability tests with experts.
Results
Focus group feedback and suggestions from risk assessors were largely in line with findings from the literature. Risk managers and lay persons offered similar suggestions on how to improve the existing communication of risk assessment results (e.g., including more explanatory detail, reporting probabilities for individual health impairments, and specifying risks for subgroups in additional sections). Risk managers found information about quality of evidence important to communicate, whereas people from the general public found this information less relevant. Participants from lower educational backgrounds had difficulties understanding the purpose of risk assessments. User tests found that the final prototype was appropriate and feasible to implement by risk assessors.
Conclusion
An iterative and evidence-based process was used to develop content to improve the communication of risk assessments to the general public while being feasible to use by risk assessors. Remaining challenges include how to communicate dose-response relationships and standardise quality of evidence ratings across disciplines.
Background
The aim of this study was to analyze the shoulder functional profile (rotation range of motion [ROM] and strength), upper and lower body performance, and throwing speed of U13 versus U15 male handball players, and to establish the relationship between these measures of physical fitness and throwing speed.
Methods
One-hundred and nineteen young male handball players (under (U)-13 (U13) [n = 85]) and U15 [n = 34]) volunteered to participate in this study. The participating athletes had a mean background of sytematic handball training of 5.5 ± 2.8 years and they exercised on average 540 ± 10.1 min per week including sport-specific team handball training and strength and conditioning programs. Players were tested for passive shoulder range-of-motion (ROM) for both internal (IR) and external rotation (ER) and isometric strength (i.e., IR and ER) of the dominant/non-dominant shoulders, overhead medicine ball throw (OMB), hip isometric abductor (ABD) and adductor (ADD) strength, hip ROM, jumps (countermovement jump [CMJ] and triple leg-hop [3H] for distance), linear sprint test, modified 505 change-of-direction (COD) test and handball throwing speed (7 m [HT7] and 9 m [HT9]).
Results
U15 players outperformed U13 in upper (i.e., HT7 and HT9 speed, OMB, absolute IR and ER strength of the dominant and non-dominant sides; Cohen’s d: 0.76–2.13) and lower body (i.e., CMJ, 3H, 20-m sprint and COD, hip ABD and ADD; d: 0.70–2.33) performance measures. Regarding shoulder ROM outcomes, a lower IR ROM was found of the dominant side in the U15 group compared to the U13 and a higher ER ROM on both sides in U15 (d: 0.76–1.04). It seems that primarily anthropometric characteristics (i.e., body height, body mass) and upper body strength/power (OMB distance) are the most important factors that explain the throw speed variance in male handball players, particularly in U13.
Conclusions
Findings from this study imply that regular performance monitoring is important for performance development and for minimizing injury risk of the shoulder in both age categories of young male handball players. Besides measures of physical fitness, anthropometric data should be recorded because handball throwing performance is related to these measures.
Objective: A role for microRNAs is implicated in several biological and pathological processes. We investigated the effects of high-intensity interval training (HIIT) and moderate-intensity continuous training (MICT) on molecular markers of diabetic cardiomyopathy in rats.
Methods: Eighteen male Wistar rats (260 ± 10 g; aged 8 weeks) with streptozotocin (STZ)-induced type 1 diabetes mellitus (55 mg/kg, IP) were randomly allocated to three groups: control, MICT, and HIIT. The two different training protocols were performed 5 days each week for 5 weeks. Cardiac performance (end-systolic and end-diastolic dimensions, ejection fraction), the expression of miR-206, HSP60, and markers of apoptosis (cleaved PARP and cytochrome C) were determined at the end of the exercise interventions.
Results: Both exercise interventions (HIIT and MICT) decreased blood glucose levels and improved cardiac performance, with greater changes in the HIIT group (p < 0.001, η2: 0.909). While the expressions of miR-206 and apoptotic markers decreased in both training protocols (p < 0.001, η2: 0.967), HIIT caused greater reductions in apoptotic markers and produced a 20% greater reduction in miR-206 compared with the MICT protocol (p < 0.001). Furthermore, both training protocols enhanced the expression of HSP60 (p < 0.001, η2: 0.976), with a nearly 50% greater increase in the HIIT group compared with MICT.
Conclusions: Our results indicate that both exercise protocols, HIIT and MICT, have the potential to reduce diabetic cardiomyopathy by modifying the expression of miR-206 and its downstream targets of apoptosis. It seems however that HIIT is even more effective than MICT to modulate these molecular markers.