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Abstract Background Theoretically, artificial intelligence can provide an accurate automatic solution to measure right ventricular (RV) ejection fraction (RVEF) from cardiovascular magnetic resonance (CMR) images, despite the complex RV geometry. However, in our recent study, commercially available deep learning (DL) algorithms for RVEF quantification performed poorly in some patients. The current study was designed to test the hypothesis that quantification of RV function could be improved in these patients by using more diverse CMR datasets in addition to domain-specific quantitative performance evaluation metrics during the cross-validation phase of DL algorithm development. Methods We identified 100 patients from our prior study who had the largest differences between manually measured and automated RVEF values. Automated RVEF measurements were performed using the original version of the algorithm (DL1), an updated version (DL2) developed from a dataset that included a wider range of RV pathology and validated using multiple domain-specific quantitative performance evaluation metrics, and conventional methodology performed by a core laboratory (CORE). Each of the DL-RVEF approaches was compared against CORE-RVEF reference values using linear regression and Bland–Altman analyses. Additionally, RVEF values were classified into 3 categories: ≤ 35%, 35–50%, and ≥ 50%. Agreement between RVEF classifications made by the DL approaches and the CORE measurements was tested. Results CORE-RVEF and DL-RVEFs were obtained in all patients (feasibility of 100%). DL2-RVEF correlated with CORE-RVEF better than DL1-RVEF (r = 0.87 vs. r = 0.42), with narrower limits of agreement. As a result, DL2 algorithm also showed increasing accuracy from 0.53 to 0.80 for categorizing RV function. Conclusions The use of a new DL algorithm cross-validated on a dataset with a wide range of RV pathology using multiple domain-specific metrics resulted in a considerable improvement in the accuracy of automated RVEF measurements. This improvement was demonstrated in patients whose images were the most challenging and resulted in the largest RVEF errors. These findings underscore the critical importance of this strategy in the development of DL approaches for automated CMR measurements.

Introduction: Currently there is no standardization of variable taper endodontic files and corresponding gutta-percha (GP) cones. The aim of this study was to evaluate intramanufacturer and intermanufacturer variability of diameter and taper in the apical third of GP master cones and finishing files from 3 commercially available variable taper endodontic systems., Methods: Diameter measurements were recorded using digital microscopy at 1-mm increments (D1-D4) for F2 files and corresponding GP cones (n = 20 per system) from ProTaper Gold (Dentsply Tulsa Dental Specialties, Johnson City, TN), EdgeTaper Platinum (EdgeEndo, Albuquerque, NM), and ExactTaper H (SS White, Lakewood, NJ). Taper was defined as the rate of change in diameter per 1-mm increment. Mean differences in diameter were assessed using repeated measures of analysis of variance for D1 to D4 and the Wilks test for differences in taper., Results: In the apical third, ProTaper and EdgeEndo mean file diameters were significantly smaller than corresponding GP cone diameters (P < .01, P < .01, respectively). Contrastingly, SS White file diameters were significantly larger than their corresponding GP cones (P = .02). Files from all manufacturers had significantly smaller diameters than advertised (nominal) values (P < .01). ProTaper GP cones had similar diameters to nominal values (P = .30), while EdgeEndo and SS White GP cones were significantly smaller (P < .01). Amongst files and corresponding GP cones from all systems, taper was nonstandardized., Conclusions: Size discrepancies between finishing files and corresponding GP cones can be expected amongst variable taper endodontic systems. Therefore, clinicians should be prepared to make intraoperative adjustments when obturating., (Published by Elsevier Inc.)

Perennial bioenergy crops are a key tool in decarbonizing global energy systems, but to ensure the efficient use of land resources, it is essential that yields and crop longevity are maximized. Remedial shallow surface tillage is being explored in commercial Miscanthus plantations as an approach to reinvigorate older crops and to rectify poor establishment, improving yields. There are posited links, however, between tillage and losses in soil carbon (C) via increased ecosystem C fluxes to the atmosphere. As Miscanthus is utilized as an energy crop, changes in field C fluxes need to be assessed as part of the C balance of the crop. Here, for the first time, we quantify the C impacts of remedial tillage at a mature commercial Miscanthus plantation in Lincolnshire, United Kingdom. Net ecosystem C production based on eddy covariance flux observations and exported yield totalled 12.16 Mg C ha -1 over the 4.6 year period after tillage, showing the site functioned as a net sink for atmospheric carbon dioxide (CO 2 ). There was no indication of negative tillage induced impacts on soil C stocks, with no difference 3 years post tillage in the surface (0-30 cm) or deep (0-70 cm) soil C stocks between the tilled Miscanthus field and an adjacent paired untilled Miscanthus field. Comparison to historic samples showed surface soil C stocks increased by 11.16 ± 3.91 Mg C ha -1 between pre (October 2011) and post tillage sampling (November 2016). Within the period of the study, however, the tillage did not result in the increased yields necessary to "pay back" the tillage induced yield loss. Rather the crop was effectively re-established, with progressive yield increases over the study period, mirroring expectations of newly planted sites. The overall impacts of remedial tillage will depend therefore, on the longer-term impacts on crop longevity and yields., Competing Interests: The authors declare no conflicts of interest., (© 2023 The Authors. GCB Bioenergy published by John Wiley & Sons Ltd.)

Transmembrane proteins have unique requirements to fold and integrate into the endoplasmic reticulum (ER) membrane. Most notably, transmembrane proteins must fold in three separate environments: extracellular domains fold in the oxidizing environment of the ER lumen, transmembrane domains (TMDs) fold within the lipid bilayer, and cytosolic domains fold in the reducing environment of the cytosol. Moreover, each region is acted upon by a unique set of chaperones and monitored by components of the ER associated quality control machinery that identify misfolded domains in each compartment. One factor is the ER lumenal Hsp70-like chaperone, Lhs1. Our previous work established that Lhs1 is required for the degradation of the unassembled α-subunit of the epithelial sodium channel (αENaC), but not the homologous β- and γENaC subunits. However, assembly of the ENaC heterotrimer blocked the Lhs1-dependent ER associated degradation (ERAD) of the α-subunit, yet the characteristics that dictate the specificity of Lhs1-dependent ERAD substrates remained unclear. We now report that Lhs1-dependent substrates share a unique set of features. First, all Lhs1 substrates appear to be unglycosylated, and second they contain two TMDs. Each substrate also contains orphaned or unassembled TMDs. Additionally, interfering with inter-subunit assembly of the ENaC trimer results in Lhs1-dependent degradation of the entire complex. Finally, our work suggests that Lhs1 is required for a subset of ERAD substrates that also require the Hrd1 ubiquitin ligase. Together, these data provide hints as to the identities of as-yet unconfirmed substrates of Lhs1 and potentially of the Lhs1 homolog in mammals, GRP170., (© 2023 The Author(s). Published by Portland Press Limited on behalf of the Biochemical Society.)

Efforts to improve soil health require that target values of key soil properties are established. No agreed targets exist but providing population data as benchmarks is a useful step to standardise soil health comparison between landscapes. We exploited nationally representative topsoil (0-15 cm) measurements to derive soil health benchmarks for managed and semi-natural environments across Great Britain. In total, 4587 soil organic matter (SOM), 3860 pH, 2908 bulk density (BD), and 465 earthworm abundance (EA) datapoints were used. As soil properties are sensitive to site-specific characteristics, data were stratified by habitat, soil type, and mean annual precipitation, with benchmarks defined as the middle 80 % of values in each distribution - yielding 135 benchmarks. BD and pH decreased with land management intensity (agriculture > semi-natural grasslands > woodlands > heathlands > wetlands), and vice versa for SOM and EA. Normalising benchmark ranges by medians revealed soil health indicator benchmark widths increased in the order: pH < BD < SOM < EA, while width increased with decreasing land management intensity. Arable and horticulture and improved grassland exhibited narrow benchmarks for SOM, pH and BD, yet the widest EA benchmark, suggesting additional drivers impact EA patterns. Upland wetlands had the widest BD benchmarks, important when determining carbon stocks. East Anglia currently possesses the largest proportions of atypical soils, including below typical SOM (19.2 %), above typical BD (17.4 %) and pH (39.1 %), and the smallest proportions of above typical SOM (2.4 %), and below typical BD (5.8 %) and pH (2.3 %). This is found even after land use, soil type and rainfall have been considered, underscoring how urgently soil health should be addressed here. Our benchmarking framework allows landowners to compare where their measured soil health indicators fall within expected ranges and is applicable to other biomes, national and multinational contexts., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

Global land use change has resulted in more pasture and cropland, largely at the expense of woodlands, over the last 300 years. How this change affects soil hydraulic function with regard to feedbacks to the hydrological cycle is unclear for earth system modelling (ESM). Pedotransfer functions (PTFs) used to predict soil hydraulic conductivity (K) take no account of land use. Here, we synthesize >800 measurements from around the globe from sites that measured near-saturated soil hydraulic conductivity, or infiltration, at the soil surface, on the same soil type at each location, but with differing land use, woodland (W), grassland (G) and cropland (C). We found that texture based PTFs predict K reasonably well for cropland giving unbiased results, but increasingly underestimate K in grassland and woodland. In native woodland and grassland differences in K can usually be accounted for by differences in bulk density. However, heavy grazing K responses can be much lower indicating compaction likely reduces connectivity. We show that the K response ratios (RR) between land uses vary with cropland (C/W = 0.45 [W/C = 2.2]) and grassland (G/W = 0.63 [W/G = 1.6]) having about half the K of woodland., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 UK Centre for Ecology & Hydrology. Published by Elsevier B.V. All rights reserved.)

Earthworms are an important soil taxon as ecosystem engineers, providing a variety of crucial ecosystem functions and services. Little is known about their diversity and distribution at large spatial scales, despite the availability of considerable amounts of local-scale data. Earthworm diversity data, obtained from the primary literature or provided directly by authors, were collated with information on site locations, including coordinates, habitat cover, and soil properties. Datasets were required, at a minimum, to include abundance or biomass of earthworms at a site. Where possible, site-level species lists were included, as well as the abundance and biomass of individual species and ecological groups. This global dataset contains 10,840 sites, with 184 species, from 60 countries and all continents except Antarctica. The data were obtained from 182 published articles, published between 1973 and 2017, and 17 unpublished datasets. Amalgamating data into a single global database will assist researchers in investigating and answering a wide variety of pressing questions, for example, jointly assessing aboveground and belowground biodiversity distributions and drivers of biodiversity change.

As the most abundant animals on earth, nematodes are a dominant component of the soil community. They play critical roles in regulating biogeochemical cycles and vegetation dynamics within and across landscapes and are an indicator of soil biological activity. Here, we present a comprehensive global dataset of soil nematode abundance and functional group composition. This dataset includes 6,825 georeferenced soil samples from all continents and biomes. For geospatial mapping purposes these samples are aggregated into 1,933 unique 1-km pixels, each of which is linked to 73 global environmental covariate data layers. Altogether, this dataset can help to gain insight into the spatial distribution patterns of soil nematode abundance and community composition, and the environmental drivers shaping these patterns.

Soil organisms, including earthworms, are a key component of terrestrial ecosystems. However, little is known about their diversity, their distribution, and the threats affecting them. We compiled a global dataset of sampled earthworm communities from 6928 sites in 57 countries as a basis for predicting patterns in earthworm diversity, abundance, and biomass. We found that local species richness and abundance typically peaked at higher latitudes, displaying patterns opposite to those observed in aboveground organisms. However, high species dissimilarity across tropical locations may cause diversity across the entirety of the tropics to be higher than elsewhere. Climate variables were found to be more important in shaping earthworm communities than soil properties or habitat cover. These findings suggest that climate change may have serious implications for earthworm communities and for the functions they provide., (Copyright © 2019 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)

Developing a holistic understanding of the ecosystem impacts of global change requires methods that can quantify the interactions among multiple response variables. One approach is to generate high dimensional spaces, or hypervolumes, to answer ecological questions in a multivariate context. A range of statistical methods has been applied to construct hypervolumes but have not yet been applied in the context of ecological data sets with spatial or temporal structure, for example, where the data are nested or demonstrate temporal autocorrelation. We outline an approach to account for data structure in quantifying hypervolumes based on the multivariate normal distribution by including random effects. Using simulated data, we show that failing to account for structure in data can lead to biased estimates of hypervolume properties in certain contexts. We then illustrate the utility of these "model-based hypervolumes" in providing new insights into a case study of afforestation effects on ecosystem properties where the data has a nested structure. We demonstrate that the model-based generalization allows hypervolumes to be applied to a wide range of ecological data sets and questions., (© 2019 The Authors. Ecology published by Wiley Periodicals, Inc. on behalf of Ecological Society of America.)

Bioenergy crops, such as sugarcane, have the potential to mitigate greenhouse gas emissions through fossil fuel substitution. However, increased sugarcane propagation and recent management changes have raised concerns that these practices may deplete soil carbon (C) stocks, thereby limiting the net greenhouse gas benefit. In this study, we use both a measured and modelled approach to evaluate the impacts of two common sugarcane management practices on soil C sequestration potential in Brazil. We explore how transitions from conventional (mineral fertiliser/burning) to improved (vinasse application/unburned) practices influence soil C stocks in total and in physically fractionated soil down to one metre. Results suggest that vinasse application leads to an accumulation of soil C of 0.55 Mg ha -1 yr -1 at 0-30 cm depth and applying unburned management led to gains of ∼0.7 Mg ha -1 yr -1 at 30-60 cm depth. Soil C concentration in the Silt+Clay fraction of topsoil (0-20 cm) showed higher C content in unburned management but it did not differ under vinasse application. The CENTURY model was used to simulate the consequences of management changes beyond the temporal extent of the measurements. Simulations indicated that vinasse was not the key factor driving increases in soil C stocks but its application may be the most readily available practice to prevent the soil C losses under burned management. Furthermore, cessation of burning may increase topsoil C by 40% after ∼50 years. These are the first data comparing different sugarcane management transitions within a single area. Our findings indicate that both vinasse application and the cessation of burning can play an important role in reducing the time required for sugarcane ethanol production to reach a net C benefit (payback time)., Competing Interests: The authors declare there are no competing interests.

Soil microbial communities play a crucial role in ecosystem functioning, but it is unknown how co-occurrence networks within these communities respond to disturbances such as climate extremes. This represents an important knowledge gap because changes in microbial networks could have implications for their functioning and vulnerability to future disturbances. Here, we show in grassland mesocosms that drought promotes destabilising properties in soil bacterial, but not fungal, co-occurrence networks, and that changes in bacterial communities link more strongly to soil functioning during recovery than do changes in fungal communities. Moreover, we reveal that drought has a prolonged effect on bacterial communities and their co-occurrence networks via changes in vegetation composition and resultant reductions in soil moisture. Our results provide new insight in the mechanisms through which drought alters soil microbial communities with potential long-term consequences, including future plant community composition and the ability of aboveground and belowground communities to withstand future disturbances.

Background: Change in land use and management can impact massively on soil ecosystems. Ecosystem engineers and other functional biodiversity in soils can be influenced directly by such change and this in turn can affect key soil functions. Here, we employ meta-analysis to provide a quantitative assessment of the effects of changes in land use and land management across a range of successional/extensification transitions (conventional arable → no or reduced tillage → grassland → wooded land) on community metrics for two functionally important soil taxa, earthworms and fungi. An analysis of the relationships between community change and soil structural properties was also included., Results: Meta-analysis highlighted a consistent trend of increased earthworm and fungal community abundances and complexity following transitions to lower intensity and later successional land uses. The greatest changes were seen for early stage transitions, such as introduction of reduced tillage regimes and conversion to grassland from arable land. Not all changes, however, result in positive effects on the assessed community metrics. For example, whether woodland conversion positively or negatively affects community size and complexity depends on woodland type and, potentially, the changes in soil properties, such as pH, that may occur during conversion. Alterations in soil communities tended to facilitate subsequent changes in soil structure and hydrology. For example, increasing earthworm abundances and functional group composition were shown to be positively correlated with water infiltration rate (dependent on tillage regime and habitat characteristics); while positive changes in fungal biomass measures were positively associated with soil microaggregate stability., Conclusions: These findings raise the potential to manage landscapes to increase ecosystem service provision from soil biota in relation to regulation of soil structure and water flow.

Background: Medical treatment with trilostane improves clinical signs, causes unclear insulin requirement changes, and variable survival times in cats., Objectives/hypothesis: To characterize the long-term efficacy of trilostane in treating cats with hyperadrenocorticism (HAC)., Animals: Fifteen client-owned cats with spontaneous HAC., Methods: Multicenter descriptive retrospective study with a search performed on all medical records for cats diagnosed with spontaneous HAC., Results: Clinical signs (13 of 15 cats) and ACTH stimulation testing results (13 of 15) improved with trilostane therapy. Diabetes mellitus was reported in 9/15 cases. Insulin requirements decreased by 36% within 2 months in 6/9 diabetic cats. Median survival time was 617 days for all cats (range 80-1,278 days). Complications included weight loss, urinary tract infections, chronic kidney disease, seizures, and recurrent pancreatitis. Hypocortisolemia was documented in 1 case. Cause of death occurred as a result of nonadrenal or nondiabetic illnesses (renal failure, seizures [caused by hypoglycemia or unknown]), or lymphoma., Conclusions and Clinical Importance: Trilostane ameliorates clinical signs of HAC in cats, is tolerated well in the long term, and can lead to improved regulation of diabetes., (Copyright © 2013 by the American College of Veterinary Internal Medicine.)

Debate on the relationship between diversity and stability has been driven by the recognition that species loss may influence ecosystem properties and processes. We conducted a litterbag experiment in the Scottish Highlands, United Kingdom, to examine the effects of altering plant litter diversity on decomposition, microbial biomass, and microfaunal abundance. The design of treatments was fully factorial and included five species from an upland plant community (silver birch, Betula pendula; Scots' pine, Pinus sylvestris; heather, Calluna vulgaris; bilberry, Vaccinium myrtillus; wavy-hair grass, Deschampsia flexuosa); species richness ranged from one to five species. We tested the effects of litter species richness and composition on variable means, whether increasing litter species richness reduced variability in the decomposer system, and whether any richness-variability relationships were maintained over time (196 vs. 564 days). While litter species composition effects controlled variable means, we revealed reductions in variability with increasing litter species richness, even after accounting for differences between litter types. These findings suggest that higher plant species richness per se may result in more stable ecosystem processes (e.g., decomposition) and decomposer communities. Negative richness-variation relationships generally relaxed over time, presumably because properties of litter mixtures became more homogeneous. However, given that plant litter inputs continue to enter the belowground system over time, we conclude that variation in ecosystem properties may be buffered by greater litter species richness.