Multiple constraints cause positive and negative feedbacks limiting grassland soil CO2efflux under CO2enrichment

Terrestrial ecosystems are increasingly enriched with resources such as atmospheric CO2that limit ecosystem processes. The consequences for ecosystem carbon cycling depend on the feedbacks from other limiting resources and plant community change, which remain poorly understood for soil CO2efflux, JCO2, a primary carbon flux from the biosphere to the atmosphere. We applied a unique CO2enrichment gradient (250 to 500 μL L-1) for eight years to grassland plant communities on soils from different landscape positions. We identified the trajectory of JCO2responses and feedbacks from other resources, plant diversity [effective species richness, exp(H)], and community change (plant species turnover). We found linear increases in JCO2on an alluvial sandy loam and a lowland clay soil, and an asymptotic increase on an upland silty clay soil. Structural equation modeling identified CO2as the dominant limitation on JCO2on the clay soil. In contrast with theory predicting limitation from a single limiting factor, the linear JCO2response on the sandy loam was reinforced by positive feedbacks from aboveground net primary productivity and exp(H), while the asymptotic JCO2response on the silty clay arose from a net negative feedback among exp(H), species turnover, and soil water potential. These findings support a multiple resource limitation view of the effects of global change drivers on grassland ecosystem carbon cycling and highlight a crucial role for positive or negative feedbacks between limiting resources and plant community structure. Incorporating these feedbacks will improve models of terrestrial carbon sequestration and ecosystem services

Multiple constraints cause positive and negative feedbacks limiting grassland soil CO2efflux under CO2enrichment

Terrestrial ecosystems are increasingly enriched with resources such as atmospheric CO2that limit ecosystem processes. The consequences for ecosystem carbon cycling depend on the feedbacks from other limiting resources and plant community change, which remain poorly understood for soil CO2efflux, JCO2, a primary carbon flux from the biosphere to the atmosphere. We applied a unique CO2enrichment gradient (250 to 500 μL L-1) for eight years to grassland plant communities on soils from different landscape positions. We identified the trajectory of JCO2responses and feedbacks from other resources, plant diversity [effective species richness, exp(H)], and community change (plant species turnover). We found linear increases in JCO2on an alluvial sandy loam and a lowland clay soil, and an asymptotic increase on an upland silty clay soil. Structural equation modeling identified CO2as the dominant limitation on JCO2on the clay soil. In contrast with theory predicting limitation from a single limiting factor, the linear JCO2response on the sandy loam was reinforced by positive feedbacks from aboveground net primary productivity and exp(H), while the asymptotic JCO2response on the silty clay arose from a net negative feedback among exp(H), species turnover, and soil water potential. These findings support a multiple resource limitation view of the effects of global change drivers on grassland ecosystem carbon cycling and highlight a crucial role for positive or negative feedbacks between limiting resources and plant community structure. Incorporating these feedbacks will improve models of terrestrial carbon sequestration and ecosystem services

CO2 enrichment and soil type additively regulate grassland productivity

The development of a predictive understanding of how atmospheric CO2 enrichment is affecting the primary productivity of the terrestrial biosphere is among the most pressing of ecological challenges. The terrestrial biosphere absorbs c. 25% of anthropogenic carbon (C) emissions (Le Quere et al., 2018). Uncertainty in CO2 effects on ecosystem C uptake is a major constraint in the prediction of C cycling and the provisioning of productivity- related ecosystem services. Grasslands cover c. 25% of the terrestrial area and are an important contributor to the global C balance (Sala et al., 1996). CO2 enrichment stimulates the aboveground net primary productivity (ANPP) of most water-limited grasslands by increasing plant water use efficiency (WUE; productivity per unit of transpiration; Morgan et al., 2004; Nowak et al., 2004; Fatichi et al., 2016), but grassland ANPP, as other ecosystem functions, is determined by drivers in addition to water availability which act simultaneously and often interactively with CO2 (Polley et al., 2011). CO2 enrichment usually shows greater stimulation of plant productivity when nitrogen (N) availability is relatively high (Owensby et al., 1994; Reich & Hobbie, 2013; Mueller et al., 2016), for example. Other drivers include precipitation timing (Hovenden et al., 2014), disturbance regimes (Newton et al., 2014), plant species composition (Langley & Megonigal, 2010; Fay et al., 2012; Polley et al., 2012) and soil properties (Epstein et al., 1997, 1998), including soil texture, which influences water availability to plants (Tor-Ngern et al., 2017)

CO2 enrichment and soil type additively regulate grassland productivity

The development of a predictive understanding of how atmospheric CO2 enrichment is affecting the primary productivity of the terrestrial biosphere is among the most pressing of ecological challenges. The terrestrial biosphere absorbs c. 25% of anthropogenic carbon (C) emissions (Le Quere et al., 2018). Uncertainty in CO2 effects on ecosystem C uptake is a major constraint in the prediction of C cycling and the provisioning of productivity- related ecosystem services. Grasslands cover c. 25% of the terrestrial area and are an important contributor to the global C balance (Sala et al., 1996). CO2 enrichment stimulates the aboveground net primary productivity (ANPP) of most water-limited grasslands by increasing plant water use efficiency (WUE; productivity per unit of transpiration; Morgan et al., 2004; Nowak et al., 2004; Fatichi et al., 2016), but grassland ANPP, as other ecosystem functions, is determined by drivers in addition to water availability which act simultaneously and often interactively with CO2 (Polley et al., 2011). CO2 enrichment usually shows greater stimulation of plant productivity when nitrogen (N) availability is relatively high (Owensby et al., 1994; Reich & Hobbie, 2013; Mueller et al., 2016), for example. Other drivers include precipitation timing (Hovenden et al., 2014), disturbance regimes (Newton et al., 2014), plant species composition (Langley & Megonigal, 2010; Fay et al., 2012; Polley et al., 2012) and soil properties (Epstein et al., 1997, 1998), including soil texture, which influences water availability to plants (Tor-Ngern et al., 2017)

Serum microRNA array analysis identifies miR-140-3p, miR-33b-3p and miR-671-3p as potential osteoarthritis biomarkers involved in metabolic processes.

Background: MicroRNAs (miRNAs) in circulation have emerged as promising biomarkers. In this study, we aimed to identify a circulating miRNA signature for osteoarthritis (OA) patients and in combination with bioinformatics analysis to evaluate the utility of selected differentially expressed miRNAs in the serum as potential OA biomarkers. Methods: Serum samples were collected from 12 primary OA patients, and 12 healthy individuals were screened using the Agilent Human miRNA Microarray platform interrogating 2549 miRNAs. Receiver Operating Characteristic (ROC) curves were constructed to evaluate the diagnostic performance of the deregulated miRNAs. Expression levels of selected miRNAs were validated by quantitative real-time PCR (qRT-PCR) in all serum and in articular cartilage samples from OA patients (n = 12) and healthy individuals (n = 7). Bioinformatics analysis was used to investigate the involved pathways and target genes for the above miRNAs. Results: We identified 279 differentially expressed miRNAs in the serum of OA patients compared to controls. Two hundred and five miRNAs (73.5%) were upregulated and 74 (26.5%) downregulated. ROC analysis revealed that 77 miRNAs had area under the curve (AUC) > 0.8 and p < 0.05. Bioinformatics analysis in the 77 miRNAs revealed that their target genes were involved in multiple signaling pathways associated with OA, among which FoxO, mTOR, Wnt, pI3K/akt, TGF-β signaling pathways, ECM-receptor interaction, and fatty acid biosynthesis. qRT-PCR validation in seven selected out of the 77 miRNAs revealed 3 significantly downregulated miRNAs (hsa-miR-33b-3p, hsa-miR-671-3p, and hsa-miR-140-3p) in the serum of OA patients, which were in silico predicted to be enriched in pathways involved in metabolic processes. Target-gene analysis of hsa-miR-140-3p, hsa-miR-33b-3p, and hsa-miR-671-3p revealed that InsR and IGFR1 were common targets of all three miRNAs, highlighting their involvement in regulation of metabolic processes that contribute to OA pathology. Hsa-miR-140-3p and hsa-miR-671-3p expression levels were consistently downregulated in articular cartilage of OA patients compared to healthy individuals. Conclusions: A serum miRNA signature was established for the first time using high density resolution miR-arrays in OA patients. We identified a three-miRNA signature, hsa-miR-140-3p, hsa-miR-671-3p, and hsa-miR-33b-3p, in the serum of OA patients, predicted to regulate metabolic processes, which could serve as a potential biomarker for the evaluation of OA risk and progression.Peer reviewedFinal Published versio

Herd-level animal management factors associated with the occurrence of bovine neonatal pancytopenia in calves in a multicountry study

Since 2007, mortality associated with a previously unreported haemorrhagic disease has been observed in young calves in several European countries. The syndrome, which has been named ‘bovine neonatal pancytopenia’ (BNP), is characterised by thrombocytopenia, leukocytopenia and a panmyelophthisis. A herd-level case-control study was conducted in four BNP affected countries (Belgium, France, Germany and the Netherlands) to identify herd management risk factors for BNP occurrence. Data were collected using structured face-to-face and telephone interviews of farm managers and their local veterinarians. In total, 363 case farms and 887 control farms were included in a matched multivariable conditional logistic regression analysis. Case-control status was strongly associated with the odds of herd level use of the vaccine PregSure® BVD (PregSure, Pfizer Animal Health) (matched adjusted odds ratio (OR) 107.2; 95% CI: 41.0–280.1). This was also the case for the practices of feeding calves colostrum from the calf’s own dam (OR 2.0; 95% CI: 1.1–3.4) or feeding pooled colostrum (OR 4.1; 95% CI: 1.9–8.8). Given that the study had relatively high statistical power and represented a variety of cattle production and husbandry systems, it can be concluded with some confidence that no other herd level management factors are competent causes for a sufficient cause of BNP occurrence on herd level. It is suggested that genetic characteristics of the dams and BNP calves should be the focus of further investigations aimed at identifying the currently missing component causes that together with PregSure vaccination and colostrum feeding represent a sufficient cause for occurrence of BNP in calves

Bulk Damage Effects in Irradiated Silicon Detectors due to Clustered Divacancies

High resistivity silicon particle detectors will be used extensively in experiments at the future CERN Large Hadron Collider where the enormous particle fluences give rise to significant atomic displacement damage. A model has been developed to estimate the evolution of defect concentrations during irradiation and their electrical behaviour according to Shockley-Read-Hall (SRH) semiconductor statistics. The observed increases in leakage current and doping concentration changes can be described well after gamma irradiation but less well after fast neutron irradiation. A possible non-SRH mechanism is considered, based on the hypothesis of charge transfer between clustered divacancy defects in neutron damaged silicon detectors. This leads to a large enhancement over the SRH prediction for V2 acceptor state occupancy and carrier generation rate which may resolve the discrepancy

Primary skin fibroblasts as a model of Parkinson's disease

Parkinson's disease is the second most frequent neurodegenerative disorder. While most cases occur sporadic mutations in a growing number of genes including Parkin (PARK2) and PINK1 (PARK6) have been associated with the disease. Different animal models and cell models like patient skin fibroblasts and recombinant cell lines can be used as model systems for Parkinson's disease. Skin fibroblasts present a system with defined mutations and the cumulative cellular damage of the patients. PINK1 and Parkin genes show relevant expression levels in human fibroblasts and since both genes participate in stress response pathways, we believe fibroblasts advantageous in order to assess, e.g. the effect of stressors. Furthermore, since a bioenergetic deficit underlies early stage Parkinson's disease, while atrophy underlies later stages, the use of primary cells seems preferable over the use of tumor cell lines. The new option to use fibroblast-derived induced pluripotent stem cells redifferentiated into dopaminergic neurons is an additional benefit. However, the use of fibroblast has also some drawbacks. We have investigated PARK6 fibroblasts and they mirror closely the respiratory alterations, the expression profiles, the mitochondrial dynamics pathology and the vulnerability to proteasomal stress that has been documented in other model systems. Fibroblasts from patients with PARK2, PARK6, idiopathic Parkinson's disease, Alzheimer's disease, and spinocerebellar ataxia type 2 demonstrated a distinct and unique mRNA expression pattern of key genes in neurodegeneration. Thus, primary skin fibroblasts are a useful Parkinson's disease model, able to serve as a complement to animal mutants, transformed cell lines and patient tissues

Roles of residues in the interface of transient protein-protein complexes before complexation

Transient protein-protein interactions play crucial roles in all facets of cellular physiology. Here, using an analysis on known 3-D structures of transient protein-protein complexes, their corresponding uncomplexed forms and energy calculations we seek to understand the roles of protein-protein interfacial residues in the unbound forms. We show that there are conformationally near invariant and evolutionarily conserved interfacial residues which are rigid and they account for ∼65% of the core interface. Interestingly, some of these residues contribute significantly to the stabilization of the interface structure in the uncomplexed form. Such residues have strong energetic basis to perform dual roles of stabilizing the structure of the uncomplexed form as well as the complex once formed while they maintain their rigid nature throughout. This feature is evolutionarily well conserved at both the structural and sequence levels. We believe this analysis has general bearing in the prediction of interfaces and understanding molecular recognition