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Common solar wind drivers behind magnetic storm–magnetospheric substorm dependency
The dynamical relationship between magnetic storms and magnetospheric substorms is one of the most controversial issues of contemporary space research. Here, we address this issue through a causal inference approach to two corresponding indices in conjunction with several relevant solar wind variables. We find that the vertical component of the interplanetary magnetic field is the strongest and common driver of both storms and substorms. Further, our results suggest, at least based on the analyzed indices, that there is no statistical evidence for a direct or indirect dependency between substorms and storms and their statistical association can be explained by the common solar drivers. Given the powerful statistical tests we performed (by simultaneously taking into account time series of indices and solar wind variables), a physical mechanism through which substorms directly or indirectly drive storms or vice versa is, therefore, unlikely.
Phenotypic, Morphological and Adhesive Differences of Human Hematopoietic Progenitor Cells Cultured on Murine versus Human Mesenchymal Stromal Cells
Xenogenic transplantation models have been developed to study human hematopoiesis in immunocompromised murine recipients. They still have limitations and therefore it is important to delineate all players within the bone marrow that could account for species-specific differences. Here, we evaluated the proliferative capacity, morphological and physical characteristics of human CD34+ hematopoietic stem and progenitor cells (HSPCs) after co-culture on murine or human bone marrow-derived mesenchymal stromal cells (MSCs). After seven days, human CD34+CD133– HSPCs expanded to similar extents on both feeder layers while cellular subsets comprising primitive CD34+CD133+ and CD133+CD34– phenotypes are reduced fivefold on murine MSCs. The number of migrating HSPCs was also reduced on murine cells suggesting that MSC adhesion influences cellular polarization of HSPC. We used atomic force microscopy-based single-cell force spectroscopy to quantify their adhesive interactions. We found threefold higher detachment forces of human HSPCs from murine MSCs compared to human ones. This difference is related to the N-cadherin expression level on murine MSCs since its knockdown abolished their differential adhesion properties with human HSPCs. Our observations highlight phenotypic, morphological and adhesive differences of human HSPCs when cultured on murine or human MSCs, which raise some caution in data interpretation when xenogenic transplantation models are used.
Monoclonal Antibodies 13A4 and AC133 Do Not Recognize the Canine Ortholog of Mouse and Human Stem Cell Antigen Prominin-1 (CD133)
The pentaspan membrane glycoprotein prominin-1 (CD133) is widely used in medicine as a cell surface marker of stem and cancer stem cells. It has opened new avenues in stem cell-based regenerative therapy and oncology. This molecule is largely used with human samples or the mouse model, and consequently most biological tools including antibodies are directed against human and murine prominin-1. Although the general structure of prominin-1 including its membrane topology is conserved throughout the animal kingdom, its primary sequence is poorly conserved. Thus, it is unclear if anti-human and -mouse prominin-1 antibodies cross-react with their orthologs in other species, especially dog. Answering this issue is imperative in light of the growing number of studies using canine prominin-1 as an antigenic marker. Here, we address this issue by cloning the canine prominin-1 and use its overexpression as a green fluorescent protein fusion protein in Madin-Darby canine kidney cells to determine its immunoreactivity with antibodies against human or mouse prominin-1. We used immunocytochemistry, flow cytometry and immunoblotting techniques and surprisingly found no cross-species immunoreactivity. These results raise some caution in data interpretation when anti-prominin-1 antibodies are used in interspecies studies.
Environmental co-benefits and adverse side-effects of alternative power sector decarbonization strategies
A rapid and deep decarbonization of power supply worldwide is required to limit global warming to well below 2 °C. Beyond greenhouse gas emissions, the power sector is also responsible for numerous other environmental impacts. Here we combine scenarios from integrated assessment models with a forward-looking life-cycle assessment to explore how alternative technology choices in power sector decarbonization pathways compare in terms of non-climate environmental impacts at the system level. While all decarbonization pathways yield major environmental co-benefits, we find that the scale of co-benefits as well as profiles of adverse side-effects depend strongly on technology choice. Mitigation scenarios focusing on wind and solar power are more effective in reducing human health impacts compared to those with low renewable energy, while inducing a more pronounced shift away from fossil and toward mineral resource depletion. Conversely, non-climate ecosystem damages are highly uncertain but tend to increase, chiefly due to land requirements for bioenergy.
Elucidation of Plasma-induced Chemical Modifications on Glutathione and Glutathione Disulphide
Cold atmospheric pressure plasmas are gaining increased interest in the medical sector and clinical trials to treat skin diseases are underway. Plasmas are capable of producing several reactive oxygen and nitrogen species (RONS). However, there are open questions how plasma-generated RONS interact on a molecular level in a biological environment, e.g. cells or cell components. The redox pair glutathione (GSH) and glutathione disulphide (GSSG) forms the most important redox buffer in organisms responsible for detoxification of intracellular reactive species. We apply Raman spectroscopy, mass spectrometry, and molecular dynamics simulations to identify the time-dependent chemical modifications on GSH and GSSG that are caused by dielectric barrier discharge under ambient conditions. We find GSSG, S-oxidised glutathione species, and S-nitrosoglutathione as oxidation products with the latter two being the final products, while glutathione sulphenic acid, glutathione sulphinic acid, and GSSG are rather reaction intermediates. Experiments using stabilized pH conditions revealed the same main oxidation products as were found in unbuffered solution, indicating that the dominant oxidative or nitrosative reactions are not influenced by acidic pH. For more complex systems these results indicate that too long treatment times can cause difficult-to-handle modifications to the cellular redox buffer which can impair proper cellular function.
Farmer typology to understand differentiated climate change adaptation in Himalaya
Smallholder farmers’ responses to the climate-induced agricultural changes are not uniform but rather diverse, as response adaptation strategies are embedded in the heterogonous agronomic, social, economic, and institutional conditions. There is an urgent need to understand the diversity within the farming households, identify the main drivers and understand its relationship with household adaptation strategies. Typology construction provides an efficient method to understand farmer diversity by delineating groups with common characteristics. In the present study, based in the Uttarakhand state of Indian Western Himalayas, five farmer types were identified on the basis of resource endowment and agriculture orientation characteristics. Factor analysis followed by sequential agglomerative hierarchial and K-means clustering was use to delineate farmer types. Examination of adaptation strategies across the identified farmer types revealed that mostly contrasting and type-specific bundle of strategies are adopted by farmers to ensure livelihood security. Our findings show that strategies that incurred high investment, such as infrastructural development, are limited to high resource-endowed farmers. In contrast, the low resourced farmers reported being progressively disengaging with farming as a livelihood option. Our results suggest that the proponents of effective adaptation policies in the Himalayan region need to be cognizant of the nuances within the farming communities to capture the diverse and multiple adaptation needs and constraints of the farming households. © 2019, The Author(s).
Effect on healthcare utilization and costs of spinal manual therapy for acute low back pain in routine care: A propensity score matched cohort study
Spinal manual therapy (SMT) is a popular treatment option for low back pain (LBP). The aim of our analysis was to evaluate the effects of manual therapy delivered by general practitioners and ambulatory orthopedic surgeons in routine care on follow up consultations, sick leave, health service utilization and costs for acute LBP compared to matched patients not receiving manual therapy. This is a propensity score matched cohort study based on health claims data. We identified a total of 113.652 adult patients with acute LBP and no coded red flags of whom 21.021 (18%) received SMT by physicians. In the final analysis 17.965 patients in each group could be matched. Balance on patients' coded characteristics, comorbidity and prior health service utilization was achieved. The provision of SMT for acute LBP had no relevant impact on follow up visits and days of sick leave for LBP in the index billing period and the following year. SMT was associated with a higher proportion of imaging studies for LBP (30.6% vs. 23%, SMD: 0.164 [95% CI 0.143-0.185]). SMT did not lead to meaningful savings by replacing other health services for LBP. SMT for acute non-specific LBP in routine care was not clinically meaningful effective to reduce sick leave and reconsultation rates compared to no SMT and did not lead to meaningful savings by replacing other health services from the perspective of health insurance. This does not imply that SMT is ineffective but might reflect a problem with selection of suitable patients and the quality and quantity of SMT in routine care. National Manual Medicine societies should state clearly that imaging is not routinely needed prior to SMT in patients with low suspicion of presence of red flags and monitor the quality of provided services.
Distinguishing autocrine and paracrine signals in hematopoietic stem cell culture using a biofunctional microcavity platform
Homeostasis of hematopoietic stem cells (HSC) in the mammalian bone marrow stem cell niche is regulated by signals of the local microenvironment. Besides juxtacrine, endocrine and metabolic cues, paracrine and autocrine signals are involved in controlling quiescence, proliferation and differentiation of HSC with strong implications on expansion and differentiation ex vivo as well as in vivo transplantation. Towards this aim, a cell culture analysis on a polymer microcavity carrier platform was combined with a partial least square analysis of a mechanistic model of cell proliferation. We could demonstrate the discrimination of specific autocrine and paracrine signals from soluble factors as stimulating and inhibitory effectors in hematopoietic stem and progenitor cell culture. From that we hypothesize autocrine signals to be predominantly involved in maintaining the quiescent state of HSC in single-cell niches and advocate our analysis platform as an unprecedented option for untangling convoluted signaling mechanisms in complex cell systems being it of juxtacrine, paracrine or autocrine origin.
Improving Accuracy and Temporal Resolution of Learning Curve Estimation for within- and across-Session Analysis
Estimation of learning curves is ubiquitously based on proportions of correct responses within moving trial windows. Thereby, it is tacitly assumed that learning performance is constant within the moving windows, which, however, is often not the case. In the present study we demonstrate that violations of this assumption lead to systematic errors in the analysis of learning curves, and we explored the dependency of these errors on window size, different statistical models, and learning phase. To reduce these errors in the analysis of single-subject data as well as on the population level, we propose adequate statistical methods for the estimation of learning curves and the construction of confidence intervals, trial by trial. Applied to data from an avoidance learning experiment with rodents, these methods revealed performance changes occurring at multiple time scales within and across training sessions which were otherwise obscured in the conventional analysis. Our work shows that the proper assessment of the behavioral dynamics of learning at high temporal resolution can shed new light on specific learning processes, and, thus, allows to refine existing learning concepts. It further disambiguates the interpretation of neurophysiological signal changes recorded during training in relation to learning.
State-of-the-art global models underestimate impacts from climate extremes
Global impact models represent process-level understanding of how natural and human systems may be affected by climate change. Their projections are used in integrated assessments of climate change. Here we test, for the first time, systematically across many important systems, how well such impact models capture the impacts of extreme climate conditions. Using the 2003 European heat wave and drought as a historical analogue for comparable events in the future, we find that a majority of models underestimate the extremeness of impacts in important sectors such as agriculture, terrestrial ecosystems, and heat-related human mortality, while impacts on water resources and hydropower are overestimated in some river basins; and the spread across models is often large. This has important implications for economic assessments of climate change impacts that rely on these models. It also means that societal risks from future extreme events may be greater than previously thought.