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Pelvic organ prolapse (POP) represents a major health care burden in women, but its underlying pathophysiological mechanisms have not been elucidated. We first used a case-control design to perform an exome chip study in 526 women with POP and 960 control women to identify single nucleotide variants (SNVs) associated with the disease. We then integrated the functional interactions between the POP candidate proteins derived from the exome chip study and other POP candidate molecules into a molecular landscape. We found significant associations between POP and SNVs in 54 genes. The proteins encoded by 26 of these genes fit into the molecular landscape, together with 43 other POP candidate molecules. The POP landscape is located in and around epithelial cells and fibroblasts of the urogenital tract and harbors four interacting biological processes-epithelial-mesenchymal transition, immune response, modulation of the extracellular matrix, and fibroblast function-that are regulated by sex hormones and TGFB1. Our findings were corroborated by enrichment analyses of differential gene expression data from an independent POP cohort. Lastly, based on the landscape and using vaginal fibroblasts from women with POP, we predicted and showed that metformin alters gene expression in these fibroblasts in a beneficial direction. In conclusion, our integrated molecular landscape of POP provides insights into the biological processes underlying the disease and clues towards novel treatments.

Stress urinary incontinence (SUI) is a common and burdensome condition. Because of the large knowledge gap around the molecular processes involved in its pathophysiology, the aim of this review was to provide a systematic overview of genetic variants, gene and protein expression changes related to SUI in human and animal studies. On 5 January 2021, a systematic search was performed in Pubmed, Embase, Web of Science, and the Cochrane library. The screening process and quality assessment were performed in duplicate, using predefined inclusion criteria and different quality assessment tools for human and animal studies respectively. The extracted data were grouped in themes per outcome measure, according to their functions in cellular processes, and synthesized in a narrative review. Finally, 107 studies were included, of which 35 used animal models (rats and mice). Resulting from the most examined processes, the evidence suggests that SUI is associated with altered extracellular matrix metabolism, estrogen receptors, oxidative stress, apoptosis, inflammation, neurodegenerative processes, and muscle cell differentiation and contractility. Due to heterogeneity in the studies (e.g., in examined tissues), the precise contribution of the associated genes and proteins in relation to SUI pathophysiology remained unclear. Future research should focus on possible contributors to these alterations.

Purpose: Genome-wide association studies have not identified replicable genetic risk loci for stress or urgency urinary incontinence., Materials and Methods: We carried out a discovery stage, case control, genome-wide association study in 3 independent discovery cohorts of European women (8,979) for stress incontinence, urgency incontinence, and any incontinence phenotypes. We conducted replication in 6 additional studies of European ancestry (4,069). We collected bladder biopsies from women with incontinence (50) to further investigate bladder expression of implicated genes and pathways and used symptom questionnaires for phenotyping. We conducted meta-analyses using inverse variance fixed effects models and whole transcriptome analyses using Affymetrix® arrays with replication with TaqMan® polymerase chain reaction., Results: In the discovery stage, we identified 16 single nucleotide polymorphisms genotyped or imputed at 5 loci that reached genome-wide significance (p <5×10 -8 ). In replication, rs138724718 on chromosome 2 near the macrophage receptor with collagenous structure ( MARCO ) gene (replication p=0.003) was associated with stress incontinence. In addition, rs34998271 on chromosome 6 near the endothelin 1 ( EDN1 ) gene (replication p=0.0008) was associated with urgency incontinence. In combined meta-analyses of discovery and replication cohorts, associations with genome-wide significance for these 2 single nucleotide polymorphisms were confirmed. Transcriptomics analyses showed differential expression of 7 of 19 genes in the endothelin pathway between stress and urgency incontinence (p <0.0001)., Conclusions: We uncovered 2 new risk loci near the genes endothelin 1 ( EDN1 ), associated with urgency incontinence, and macrophage receptor with collagenous structure ( MARCO ), associated with stress incontinence. These loci are biologically plausible given their roles in smooth muscle contraction and innate host defense, respectively.

Aim: To perform a systematic review summarizing the knowledge of genetic variants, gene, and protein expression changes in humans and animals associated with urgency urinary incontinence (UUI) and to provide an overview of the known molecular mechanisms related to UUI., Methods: A systematic search was performed on March 2, 2020, in PubMed, Embase, Web of Science, and the Cochrane library. Retrieved studies were screened for eligibility. The risk of bias was assessed using the ROBINS-I (human) and SYRCLE (animal) tool. Data were presented in a structured manner and in the case of greater than five studies on a homogeneous outcome, a meta-analysis was performed., Results: Altogether, a total of 10,785 records were screened of which 37 studies met the inclusion criteria. Notably, 24/37 studies scored medium-high to high on risk of bias, affecting the value of the included studies. The analysis of 70 unique genes and proteins and three genome-wide association studies showed that specific signal transduction pathways and inflammation are associated with UUI. A meta-analysis on the predictive value of urinary nerve growth factor (NGF) levels showed that increased urinary NGF levels correlate with UUI., Conclusion: The collective evidence showed the involvement of two molecular mechanisms (signal transduction and inflammation) and NGF in UUI, enhancing our understanding of the pathophysiology of UUI. Unfortunately, the risk of bias was medium-high to high for most studies and the value of many observations remains unclear. Future studies should focus on elucidating how deficits in the two identified molecular mechanisms contribute to UUI and should avoid bias., (© 2020 The Authors. Neurourology and Urodynamics published by Wiley Periodicals LLC.)

Objective: Since publication of the Term Breech Trial in 2000 only 15% of term breech presentations is delivered vaginally in the Netherlands. This declined exposure to vaginal breech deliveries (VBD) is a problem for those who still need to be trained. The aim of this study was to evaluate the level of training of the Dutch gynecological residents, and their intentions on guiding VBDs during their careers., Study Design: Via an online questionnaire Dutch residents and starting gynecologists, were asked about their training, exposure and confidence in guiding VBDs during their residency., Main Outcome Measures: Number of VBDs performed, level of entrustment of independent practice in guiding VBDs, courses in guiding VBDs, confidence in guiding VBDs after finishing their residency., Results: The response rate was 64% (N = 294). Thirteen per cent performed less than three VBDs, 15% more than 15. Of sixth year residents 65% has not yet obtained entrustment for personally guiding VBDs. The residents are trained in VBDs at least once during a national mandatory course. Further training is strongly dependent on local hospital policy: 34% are trained every quarter versus 29% who never receive a local training., Conclusion: Our survey showed that more than half of the respondents judge the current residency program to be insufficient for guiding VBDs. This seems to be related to the low overall exposure to VBDs and the lack of quantity and quality of attended courses., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Soil is the largest organic carbon (C) pool of terrestrial ecosystems, and C loss from soil accounts for a large proportion of land-atmosphere C exchange. Therefore, a small change in soil organic C (SOC) can affect atmospheric carbon dioxide (CO 2 ) concentration and climate change. In the past decades, a wide variety of studies have been conducted to quantify global SOC stocks and soil C exchange with the atmosphere through site measurements, inventories, and empirical/process-based modeling. However, these estimates are highly uncertain, and identifying major driving forces controlling soil C dynamics remains a key research challenge. This study has compiled century-long (1901-2010) estimates of SOC storage and heterotrophic respiration (Rh) from 10 terrestrial biosphere models (TBMs) in the Multi-scale Synthesis and Terrestrial Model Intercomparison Project and two observation-based data sets. The 10 TBM ensemble shows that global SOC estimate ranges from 425 to 2111 Pg C (1 Pg = 10 15  g) with a median value of 1158 Pg C in 2010. The models estimate a broad range of Rh from 35 to 69 Pg C yr -1 with a median value of 51 Pg C yr -1 during 2001-2010. The largest uncertainty in SOC stocks exists in the 40-65°N latitude whereas the largest cross-model divergence in Rh are in the tropics. The modeled SOC change during 1901-2010 ranges from -70 Pg C to 86 Pg C, but in some models the SOC change has a different sign from the change of total C stock, implying very different contribution of vegetation and soil pools in determining the terrestrial C budget among models. The model ensemble-estimated mean residence time of SOC shows a reduction of 3.4 years over the past century, which accelerate C cycling through the land biosphere. All the models agreed that climate and land use changes decreased SOC stocks, while elevated atmospheric CO 2 and nitrogen deposition over intact ecosystems increased SOC stocks-even though the responses varied significantly among models. Model representations of temperature and moisture sensitivity, nutrient limitation, and land use partially explain the divergent estimates of global SOC stocks and soil C fluxes in this study. In addition, a major source of systematic error in model estimations relates to nonmodeled SOC storage in wetlands and peatlands, as well as to old C storage in deep soil layers.

Climate feedbacks from soils can result from environmental change followed by response of plant and microbial communities, and/or associated changes in nutrient cycling. Explicit consideration of microbial life-history traits and functions may be necessary to predict climate feedbacks owing to changes in the physiology and community composition of microbes and their associated effect on carbon cycling. Here we developed the microbial enzyme-mediated decomposition (MEND) model by incorporating microbial dormancy and the ability to track multiple isotopes of carbon. We tested two versions of MEND, that is, MEND with dormancy (MEND) and MEND without dormancy (MEND&#95;wod), against long-term (270 days) carbon decomposition data from laboratory incubations of four soils with isotopically labeled substrates. MEND&#95;wod adequately fitted multiple observations (total C-CO2 and (14)C-CO2 respiration, and dissolved organic carbon), but at the cost of significantly underestimating the total microbial biomass. MEND improved estimates of microbial biomass by 20-71% over MEND&#95;wod. We also quantified uncertainties in parameters and model simulations using the Critical Objective Function Index method, which is based on a global stochastic optimization algorithm, as well as model complexity and observational data availability. Together our model extrapolations of the incubation study show that long-term soil incubations with experimental data for multiple carbon pools are conducive to estimate both decomposition and microbial parameters. These efforts should provide essential support to future field- and global-scale simulations, and enable more confident predictions of feedbacks between environmental change and carbon cycling.

The development of effective measures to stabilize atmospheric CO2 concentration and mitigate negative impacts of climate change requires accurate quantification of the spatial variation and magnitude of the terrestrial carbon (C) flux. However, the spatial pattern and strength of terrestrial C sinks and sources remain uncertain. In this study, we designed a spatially-explicit agroecosystem modeling system by integrating the Environmental Policy Integrated Climate (EPIC) model with multiple sources of geospatial and surveyed datasets (including crop type map, elevation, climate forcing, fertilizer application, tillage type and distribution, and crop planting and harvesting date), and applied it to examine the sensitivity of cropland C flux simulations to two widely used soil databases (i.e. State Soil Geographic-STATSGO of a scale of 1:250,000 and Soil Survey Geographic-SSURGO of a scale of 1:24,000) in Iowa, USA. To efficiently execute numerous EPIC runs resulting from the use of high resolution spatial data (56m), we developed a parallelized version of EPIC. Both STATSGO and SSURGO led to similar simulations of crop yields and Net Ecosystem Production (NEP) estimates at the State level. However, substantial differences were observed at the county and sub-county (grid) levels. In general, the fine resolution SSURGO data outperformed the coarse resolution STATSGO data for county-scale crop-yield simulation, and within STATSGO, the area-weighted approach provided more accurate results. Further analysis showed that spatial distribution and magnitude of simulated NEP were more sensitive to the resolution difference between SSURGO and STATSGO at the county or grid scale. For over 60% of the cropland areas in Iowa, the deviations between STATSGO- and SSURGO-derived NEP were larger than 1MgCha(-1)yr(-1), or about half of the average cropland NEP, highlighting the significant uncertainty in spatial distribution and magnitude of simulated C fluxes resulting from differences in soil data resolution., (Copyright © 2014 Elsevier B.V. All rights reserved.)

The use of marginal lands for biofuel production has been proposed as a promising solution for meeting biofuel demands while avoiding food-feed-fuel conflicts. However, uncertainty surrounds whether marginal lands can be reliably located, as well as their inherent biofuel potential and the possible environmental impacts. We developed a quantitative approach that integrates high-resolution land cover and land productivity to classify productive croplands and nonarable marginal lands in a nine-county region in southern Michigan. The classified lands were then examined with the spatially explicit modeling framework using the Environmental Policy Integrated Climate (EPIC) model to estimate net energy (NE) and soil organic carbon (SOC) changes associated with the cultivation of different annual and perennial production systems. Simulation results suggest that biofuel production systems underperform on marginal lands when compared to productive croplands. However, we found perennial grasses could perform better than annual crops. Hence, when growing perennial bioenergy crops on marginal lands instead of productive croplands, less additional land (about 0.09 ha per each hectare planted) would be needed to achieve the same NE than if growing annual bioenergy crops (additional 0.17 ha per hectare planted). Miscanthus ( × ) and switchgrass ( L.) can produce 112.43 and 74.61 GJ ha yr NE, respectively, and have the potential to sequester, on average, 0.59 and 0.23 Mg C ha yr SOC, respectively. Notably, simulation results indicate substantial variability of the NE and SOC storage potential across the study region. Thus, although perennial energy crops are promising options for biofuel production on marginal lands, given the large spatial variability, regional- and site-specific management strategies are required for sustainable biofuel production., (Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.)

We developed a microbial-enzyme-mediated decomposition (MEND) model, based on the Michaelis-Menten kinetics, that describes the dynamics of physically defined pools of soil organic matter (SOC). These include particulate, mineral-associated, dissolved organic matter (POC, MOC, and DOC, respectively), microbial biomass, and associated exoenzymes. The ranges and/or distributions of parameters were determined by both analytical steady-state and dynamic analyses with SOC data from the literature. We used an improved multi-objective parameter sensitivity analysis (MOPSA) to identify the most important parameters for the full model: maintenance of microbial biomass, turnover and synthesis of enzymes, and carbon use efficiency (CUE). The model predicted that an increase of 2 degrees C (baseline temperature 12 degrees C) caused the pools of POC-cellulose, MOC, and total SOC to increase with dynamic CUE and decrease with constant CUE, as indicated by the 50% confidence intervals. Regardless of dynamic or constant CUE, the changes in pool size of POC, MOC, and total SOC varied from -8% to 8% under +2 degrees C. The scenario analysis using a single parameter set indicates that higher temperature with dynamic CUE might result in greater net increases in both POC-cellulose and MOC pools. Different dynamics of various SOC pools reflected the catalytic functions of specific enzymes targeting specific substrates and the interactions between microbes, enzymes, and SOC. With the feasible parameter values estimated in this study, models incorporating fundamental principles of microbial-enzyme dynamics can lead to simulation results qualitatively different from traditional models with fast/slow/passive pools.

We attempted to reconcile three microbial maintenance models (Herbert, Pirt, and Compromise) through a theoretical reassessment. We provided a rigorous proof that the true growth yield coefficient (Y(G)) is the ratio of the specific maintenance rate (a in Herbert) to the maintenance coefficient (m in Pirt). Other findings from this study include: (1) the Compromise model is identical to the Herbert for computing microbial growth and substrate consumption, but it expresses the dependence of maintenance on both microbial biomass and substrate; (2) the maximum specific growth rate in the Herbert (μ(max,H)) is higher than those in the other two models (μ(max,P) and μ(max,C)), and the difference is the physiological maintenance factor (m(q) = a); and (3) the overall maintenance coefficient (m(T)) is more sensitive to m(q) than to the specific growth rate (μ(G)) and Y(G). Our critical reassessment of microbial maintenance provides a new approach for quantifying some important components in soil microbial ecology models., (© This article is a US government work and is in the public domain in the USA.)

Net annual soil carbon change, fossil fuel emissions from cropland production, and cropland net primary production were estimated and spatially distributed using land cover defined by NASA's moderate resolution imaging spectroradiometer (MODIS) and by the USDA National Agricultural Statistics Service (NASS) cropland data layer (CDL). Spatially resolved estimates of net ecosystem exchange (NEE) and net ecosystem carbon balance (NECB) were developed. The purpose of generating spatial estimates of carbon fluxes, and the primary objective of this research, was to develop a method of carbon accounting that is consistent from field to national scales. NEE represents net on-site vertical fluxes of carbon. NECB represents all on-site and off-site carbon fluxes associated with crop production. Estimates of cropland NEE using moderate resolution (approximately 1 km2) land cover data were generated for the conterminous United States and compared with higher resolution (30-m) estimates of NEE and with direct measurements of CO2 flux from croplands in Illinois and Nebraska, USA. Estimates of NEE using the CDL (30-m resolution) had a higher correlation with eddy covariance flux tower estimates compared with estimates of NEE using MODIS. Estimates of NECB are primarily driven by net soil carbon change, fossil fuel emissions associated with crop production, and CO2 emissions from the application of agricultural lime. NEE and NECB for U.S. croplands were -274 and 7 Tg C/yr for 2004, respectively. Use of moderate- to high-resolution satellite-based land cover data enables improved estimates of cropland carbon dynamics.

Background: Soil organic carbon (SOC) represents a significant pool of carbon within the biosphere. Climatic shifts in temperature and precipitation have a major influence on the decomposition and amount of SOC stored within an ecosystem and that released into the atmosphere. We have linked net primary production (NPP) algorithms, which include the impact of enhanced atmospheric CO2 on plant growth, to the SOCRATES terrestrial carbon model to estimate changes in SOC for the Australia continent between the years 1990 and 2100 in response to climate changes generated by the CSIRO Mark 2 Global Circulation Model (GCM)., Results: We estimate organic carbon storage in the topsoil (0-10 cm) of the Australian continent in 1990 to be 8.1 Gt. This equates to 19 and 34 Gt in the top 30 and 100 cm of soil, respectively. By the year 2100, under a low emissions scenario, topsoil organic carbon stores of the continent will have increased by 0.6% (49 Mt C). Under a high emissions scenario, the Australian continent becomes a source of CO2 with a net reduction of 6.4% (518 Mt) in topsoil carbon, when compared to no climate change. This is partially offset by the predicted increase in NPP of 20.3%, Conclusion: Climate change impacts must be studied holistically, requiring integration of climate, plant, ecosystem and soil sciences. The SOCRATES terrestrial carbon cycling model provides realistic estimates of changes in SOC storage in response to climate change over the next century, and confirms the need for greater consideration of soils in assessing the full impact of climate change and the development of quantifiable mitigation strategies.

Soil organic matter (SOM) often increases when agricultural fields are converted to perennial vegetation, yet decadal scale rates and the mechanisms that underlie SOM accumulation are not clear. We measured SOM accumulation and changes in soil properties on a replicated chronosequence of former agricultural fields in the midwestern United States that spanned 40 years after perennial-grassland establishment. Over this time period, soil organic carbon (SOC) in the top 10 cm of soil accumulated at a constant rate of 62.0 g x m(-2) x yr(-1), regardless of whether the vegetation type was dominated by C3 or C4 grasses. At this rate, SOC contents will be equivalent to unplowed native prairie sites within 55-75 years after cultivation ceased. Both labile (short turnover time) and recalcitrant (long turnover time) carbon pools increased linearly for 40 years, with recalcitrant pools increasing more rapidly than expected. This result was consistent across several different methods of measuring labile SOC. A model that investigates the mechanisms of SOM formation suggests that rapid formation of stable carbon resulted from biochemically resistant microbial products and plant material. Former agricultural soils of the Great Plains may function as carbon sinks for less than a century, although much of the carbon stored is stable.

Measurement of the change in soil carbon that accompanies a change in land use (e.g., forest to agriculture) or management (e.g., conventional tillage to no-till) can be complex and expensive, may require reference plots, and is subject to the variability of statistical sampling and short-term variability in weather. In this paper, we develop Carbon Management Response (CMR) curves that could be used as an alternative to in situ measurements. The CMR curves developed here are based on quantitative reviews of existing global analyses and field observations of changes in soil carbon. The curves show mean annual rates of soil carbon change, estimated time to maximum rates of change, and estimated time to a new soil carbon steady state following the initial change in management. We illustrate how CMR curves could be used in a carbon accounting framework while effectively addressing a number of potential policy issues commonly associated with carbon accounting. We find that CMR curves provide a transparent means to account for changes in soil carbon accumulation and loss rates over time, and also provide empirical relationships that might be used in the development or validation of ecological or Earth systems models.

In two studies, the effect of two types of intra-team feedback on developing a shared mental model in Command & Control teams was investigated. A distinction is made between performance monitoring and team self-correction. Performance monitoring is the ability of team members to monitor each other's task execution and give feedback during task execution. Team self-correction is the process in which team members engage in evaluating their performance and in determining their strategies after task execution. In two experiments the opportunity to engage in performance monitoring, respectively team self-correction, was varied systematically. Both performance monitoring as well as team self-correction appeared beneficial in the improvement of team performance. Teams that had the opportunity to engage in performance monitoring, however, performed better than teams that had the opportunity to engage in team self-correction.

This article describes a system for the optimization of the prehospital assessment of emergency, in cases involving thoraco-abdominal complaints and consciousness problems. This assessment is performed by nurses on the basis of a telephone interview at ambulance dispatch centers. The system has a body of biomedical and policy knowledge available to guide the interview and to provide advice.