Miracle-dz/UniFAR-FTUs huggingface dataset:
Achievable agricultural soil carbon sequestration across Europe from country‐specific estimates

The role of soils in the global carbon cycle and in reducing GHG emissions from agriculture has been increasingly acknowledged. The ‘4 per 1000’ (4p1000) initiative has become a prominent action plan for climate change mitigation and achieve food security through an annual increase in soil organic carbon (SOC) stocks by 0.4%, (i.e. 4‰ per year). However, the feasibility of the 4p1000 scenario and, more generally, the capacity of individual countries to implement soil carbon sequestration (SCS) measures remain highly uncertain. Here, we evaluated country‐specific SCS potentials of agricultural land for 24 countries in Europe. Based on a detailed survey of available literature, we estimate that between 0.1% and 27% of the agricultural greenhouse gas (GHG) emissions can potentially be compensated by SCS annually within the next decades. Measures varied widely across countries, indicating differences in country‐specific environmental conditions and agricultural practices. None of the countries' SCS potential reached the aspirational goal of the 4p1000 initiative, suggesting that in order to achieve this goal, a wider range of measures and implementation pathways need to be explored. Yet, SCS potentials exceeded those from previous pan‐European modelling scenarios, underpinning the general need to include national/regional knowledge and expertise to improve estimates of SCS potentials. The complexity of the chosen SCS measurement approaches between countries ranked from tier 1 to tier 3 and included the effect of different controlling factors, suggesting that methodological improvements and standardization of SCS accounting are urgently required. Standardization should include the assessment of key controlling factors such as realistic areas, technical and practical feasibility, trade‐offs with other GHG and climate change. Our analysis suggests that country‐specific knowledge and SCS estimates together with improved data sharing and harmonization are crucial to better quantify the role of soils in offsetting anthropogenic GHG emissions at global level.
Low‐affinity immunoglobulin gamma Fc region receptor III‐B (FcγRIIIB, CD16B) deficiency in patients with blood and immune system disorders

Low‐affinity immunoglobulin gamma Fc region receptor III‐B (FcγRIIIB) deficiency is present in ˜0·05% of the general population. Among our patients, FcγRIIIB deficiency was less frequent in those with immune‐system disorders (one of 1815 patients, 0·05%) than in those with blood disorders (nine of 2147 patients, 0·42%, P = 0·023): mainly primary immune thrombocytopenia (4·34%), therapy related myeloid neoplasms (1·16%) and myelodysplastic syndrome with excess blasts (1·28%). Four of the nine (44·4%) patients with blood disorders were diagnosed with or quickly evolved to acute myeloid leukaemia (AML), suggesting that FcγRIIIB deficiency could be an adverse prognostic factor for progression to AML that should be confirmed in large multicentre studies.
Spin evolution of two valence electrons in two separated ions

The spin evolution of two spin-1/2 valence electrons, located at two separated ions, is investigated with the help of Breit equation. This evolution that arise solely depends on their dipole-dipole magnetic interaction. Special attention is paid to the effects beyond the leading order of the dipole-dipole magnetic interaction. In contrast to just including the leading order, it is found that the spin-spin interactions flips the spin of both electrons together, while the spin-orbit interactions typically changes the spin of just single electron. As a consequence, different behaviour is observed in the time evolution of two different entangled Bell states.
The impact of growth hormone replacement therapy on adipokines, but not upon Ghrelin.

BACKGROUND Besides growth acceleration, growth hormone (GH) therapy of GH deficient (GHD) children improves body composition by decreasing body fat. This effect is due to GH interaction with lipid and carbohydrate metabolism, possibly also mediated by adipokines secreted by adipose tissue, and ghrelin. This study aimed to assess the impact of oneyear GH replacement therapy on the metabolic profile, adipokines, and acylated/ unacylated ghrelin of prepubertal children with GHD. METHODS Prospective observational study of 42 non-obese, prepubertal children with GHD followed up for twelve months. Mean lipid, carbohydrate, adipokine profiles, acylated/unacylated ghrelin, and body composition data before therapy onset were compared with measurements obtained after 6 and 12 months of GH therapy. RESULTS Total body fat content and body fat percentage decreased significantly, while the lipid profile improved over the study period in the 42 GHD children with a mean age of 9.2 ±2.6 years. The levels of leptin and unacylated ghrelin decreased significantly, whereas adiponectin and acylated ghrelin values increased after GH therapy. In regression analysis models, GH treatment (reflected by increased absolute values or standard deviations of IGF1) influences the variation of leptin and adiponectin, but not ghrelin, independently of body composition - lean or fat mass. CONCLUSIONS GH replacement therapy improves body composition, lipid, and adipokine profile in GHD children. Also, GH replacement therapy directly impacts leptin and adiponectin concentrations, independently of body composition. Further research is needed to identify the molecular mechanisms and metabolic pathways by which the GH/IGF1 axis influences adipokines secretion.
Acetylcholine-gated current translates wake neuronal firing rate information into a spike timing-based code in Non-REM sleep, stabilizing neural network dynamics during memory consolidation

Sleep is critical for memory consolidation, although the exact mechanisms mediating this process are unknown. Combining reduced network models and analysis of in vivo recordings, we tested the hypothesis that neuromodulatory changes in acetylcholine (ACh) levels during non-rapid eye movement (NREM) sleep mediate stabilization of network-wide firing patterns, with temporal order of neurons’ firing dependent on their mean firing rate during wake. In both reduced models and in vivo recordings from mouse hippocampus, we find that the relative order of firing among neurons during NREM sleep reflects their relative firing rates during prior wake. Our modeling results show that this remapping of wake-associated, firing frequency-based representations is based on NREM-associated changes in neuronal excitability mediated by ACh-gated potassium current. We also show that learning-dependent reordering of sequential firing during NREM sleep, together with spike timing-dependent plasticity (STDP), reconfigures neuronal firing rates across the network. This rescaling of firing rates has been reported in multiple brain circuits across periods of sleep. Our model and experimental data both suggest that this effect is amplified in neural circuits following learning. Together our data suggest that sleep may bias neural networks from firing rate-based towards phase-based information encoding to consolidate memories.
Impacts of Systemic Hypertension on the Macular Microvasculature in Diabetic Patients Without Clinical Diabetic Retinopathy

Purpose To identify the impact of hypertension (HTN) on macular microvasculature in type 2 diabetes (T2DM) patients without clinical diabetic retinopathy. Methods In this retrospective cross-sectional study, subjects were divided into three groups: controls (control group), patients with T2DM (DM group), and patients with both T2DM and HTN (DM + HTN group). The vessel length density (VD) was compared among the groups. Linear regression analyses were performed to identify factors associated with VD. Results The VD in the control, DM, and DM + HTN groups was 20.43 ± 1.16, 19.50 ± 1.45, and 18.19 ± 2.06 mm−1, respectively (P < 0.001). The best-corrected visual acuity (B = −9.30; P = 0.002), duration of T2DM (B = −0.04; P = 0.020), HTN (B = −0.51; P = 0.016), signal strength (B = 1.12; P < 0.001), and ganglion cell–inner plexiform layer thickness (B = 0.06; P < 0.001) were significant factors affecting VD in patients with T2DM. Additionally, the hemoglobin A1c (HbA1c) (B = −0.49; P = 0.016) was significantly associated with VD in patients with both T2DM and HTN. Conclusions Patients with T2DM had impaired macular microvasculature, and patients with T2DM with HTN exhibited greater impairment of the microvasculature than did patients with T2DM only. Additionally, physicians should be aware that the macular microvasculature would be more vulnerable to hyperglycemic damage under ischemic conditions by HTN.
A critical review of the ecological status of lakes and rivers from Canada's oil sands region

We synthesize the information available from the peer‐reviewed literature on the ecological status of lakes and rivers in the oil sands region (OSR) of Canada. The majority of the research from the OSR has been performed in or near the minable region and examines the concentrations, flux, or enrichment of contaminants of concern (CoCs). Proximity to oil sands facilities and the beginning of commercial activities tend to be associated with greater estimates of CoCs across studies. Research suggests the higher measurements of CoCs are typically associated with wind‐blown dust, but other sources also contribute. Exploratory analyses further suggest relationships with facility production and fuel use data. Exceedances of environmental quality guidelines for CoCs are also reported in lake sediments, but there are no indications of toxicity including those within the areas of the greatest atmospheric deposition. Instead, primary production has increased in most lakes over time. Spatial differences are observed in streams, but causal relationships with industrial activity are often confounded by substantial natural influences. Despite this, there may be signals associated with site preparation for new mines, potential persistent differences, and a potential effect of petroleum coke used as fuel on some indices of health in fish captured in the Steepbank River. There is also evidence of improvements in the ecological condition of some rivers. Despite the volume of material available, much of the work remains temporally, spatially, or technically isolated. Overcoming the isolation of studies would enhance the utility of information available for the region, but additional recommendations for improving monitoring can be made, such as a shift to site‐specific analyses in streams and further use of industry‐reported data. Integr Environ Assess Manag 2022;18:361–387. © 2021 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).
TRAIL signaling promotes entosis in colorectal cancer

Bozkurt et al. find that besides activating apoptosis, TRAIL signaling induces entosis in colon cancer cells through TRAIL receptors and structural presence but not catalytic activity of caspase-8. Moreover, they provide evidence for an association of TRAIL signaling, cell-in-cell structures, and clinical outcome in CRC.
Scalability of resonant motor-driven flapping wing propulsion systems

This work aims to develop an integrated conceptual design process to assess the scalability and performance of propulsion systems of resonant motor-driven flapping wing vehicles. The developed process allows designers to explore the interaction between electrical, mechanical and aerodynamic domains in a single transparent design environment. Wings are modelled based on a quasi-steady treatment that evaluates aerodynamics from geometry and kinematic information. System mechanics is modelled as a damped second-order dynamic system operating at resonance with nonlinear aerodynamic damping. Motors are modelled using standard equations that relate operational parameters and AC voltage input. Design scaling laws are developed using available data based on current levels of technology. The design method provides insights into the effects of changing core design variables such as the actuator size, actuator mass fraction and pitching kinematics on the overall design solution. It is shown that system efficiency achieves peak values of 30–36% at motor masses of 0.5–1 g when a constant angle of attack kinematics is employed. While sinusoidal angle of attack kinematics demands more aerodynamic and electric powers compared with the constant angle of attack case, sinusoidal angle of attack kinematics can lead to a maximum difference of around 15% in peak system efficiency.
The demographic history of Madagascan micro-endemics: have rare species always been rare?

Extinction has increased as human activities impact ecosystems, yet relatively few species have conservation assessments. Novel approaches are needed to highlight threatened species that are currently data-deficient. Many Madagascan plant species have extremely narrow ranges, but this may not have always been the case—it is unclear how the island's diverse flora evolved. To assess this, we generated restriction-site associated DNA sequence data for 10 Madagascan plant species, estimated effective population size (Ne) for each species and compared this to census (Nc) sizes. In each case, Ne was an order of magnitude larger than Nc—signifying rapid, recent population decline. We then estimated species' demographic history, tracking changes in Ne over time. We show that it is possible to predict extinction risk, particularly in the most threatened species. Furthermore, simulations showed that our approach has the power to detect population decline during the Anthropocene. Our analyses reveal that Madagascar's micro-endemics were not always rare, having experienced a rapid decline in their recent history. This casts further uncertainty over the processes that generated Madagascar's exceptional biodiversity. Our approach targets data-deficient species in need of conservation assessment, particularly in regions where human modification of the environment has been rapid.
Procedural tools and pension reform in the long run: the case of Sweden

ABSTRACT Welfare state reform is understood to be risky, difficult and still ongoing. As such, there is a need for analytic tools that can aid understanding of how governments are able to overcome the various barriers they face in seeking change, and the challenges of managing complex and hybridised welfare arrangements. This article argues that the policy tools literature provides several promising avenues for doing so. Specifically, it suggests that procedural policy tools – increasingly recognised in policy studies – are often critical for mitigating risk of blame, sustaining coalitions and supporting the ongoing adaptation of social policy systems to changing conditions and information. This is especially critical where policy innovations entail new substantive relationships between states, citizens and markets, as initial assumptions about individual and group behaviour are likely to be flawed. Procedural tools can enable learning and recalibration in the pursuit of public legitimacy for changing arrangements. To demonstrate the argument, this article engages closely with a case study of public pension reform in Sweden in the 1990s. The case study finds that, initially, reformers made use of a politically insulated parliamentary working group to design a new system, one which attempted to automate elements of policymaking and transfer risk from the state to the individual. However, this goal has proved more difficult to realise than imagined, and in the longer-term, the government used procedural tools for the purposes of learning and recalibration, and in doing so has gone some way to re-establishing modified forms of state accountability.
Multi-sensor data fusion of remotely-sensed images with sparse and logarithmic low-rank regularization for shadow removal and denoising

ABSTRACT Hyperspectral images have high spectral resolution but low spatial resolution, which results in a large number of mixed pixels. As an economical and effective means to improve image quality, the fusion of hyperspectral and multispectral data from different sensors can achieve the reconstruction of super-resolution images. As a representative of fusion method, coupled non-negative matrix factorization is an ill-posed problem, in which the number of endmembers was set to be no less than the groundtruth without requiring an accurate value. However, this often results in spectral shadows and spatial information redundancy, especially when the observed images are contaminated by noise. To address these problems above, this article incorporates sparse and low-rank regularization to reformulate a bi-convex fusion problem for the removal of shadows and noise, in which the logarithmic sum function is employed to suppress the small singular components of endmember and abundance matrices. Then, an efficient solver is designed to obtain the closed-form solutions via matrix-vector operators, in which the alternating direction method of multipliers is utilized to split the variables using equality constraints. The experimental results of real datasets demonstrate that the proposed fusion method can effectively enhance the quality of reconstructed super-resolution images especially in high-noise environments, which also verifies the validation of incorporated regularization.
Fish feeds and feed management practices in the Kenyan aquaculture sector: Challenges and opportunities

Feeds and feed management practices are key to the development of the aquaculture sector. To achieve high levels of aquaculture production, fish farmers need nutritionally adequate and cost-effective feeds, which are coupled with good feed management practices. Access to high quality and cost-effective feeds is one of the prerequisites to successful fish farming. This paper reviews the current status of the Kenyan fish feed industry and feed management practices. The review includes constraints and opportunities in fish feeds from a farmer's perspective. The review shows that the fish feed industry has been boosted by the development of fish feed standards, which has ensured access to high-quality fish feeds by all farmers. Feed management practices considerably impact on the economic performance in fish production. Thus, adopting appropriate feed management technologies and feeding strategies is instrumental in maximizing aquaculture productivity. Some of the major challenges faced by fish farmers in the feed sector including limited access to finance, lack of appropriate technical innovations, limited knowledge in feed formulation and processing and poor feed handling and storage are discussed. These challenges pose limitation in investment opportunities for a viable and sustainable fish feed processing and manufacturing to meet the rising demand occasioned by increased demand for fish food in Kenya. There is a huge potential to develop public-private partnerships with farmer groups to improve access to training and information dissemination on feeds availability and quality. Training fish farmers on feed formulation using locally available feed ingredients provide an opportunity to reduce feed costs, increase feeding efficiency and improve profitability. This paper reviews the current status of the Kenyan fish feed industry and feed management practices including constraints and opportunities from a farmer's perspective.
New data and collaborations at the Saccharomyces Genome Database: updated reference genome, alleles, and the Alliance of Genome Resources

Saccharomyces cerevisiae is used to provide fundamental understanding of eukaryotic genetics, gene product function, and cellular biological processes. Saccharomyces Genome Database (SGD) has been supporting the yeast research community since 1993, serving as its de facto hub. Over the years, SGD has maintained the genetic nomenclature, chromosome maps, and functional annotation, and developed various tools and methods for analysis and curation of a variety of emerging data types. More recently, SGD and six other model organism focused knowledgebases have come together to create the Alliance of Genome Resources to develop sustainable genome information resources that promote and support the use of various model organisms to understand the genetic and genomic bases of human biology and disease. Here we describe recent activities at SGD, including the latest reference genome annotation update, the development of a curation system for mutant alleles, and new pages addressing homology across model organisms as well as the use of yeast to study human disease.
Ribosomal RNA 2′-O-methylations regulate translation by impacting ribosome dynamics

Protein synthesis by ribosomes is critically important for gene expression in all cells. The ribosomal RNAs (rRNAs) are marked by numerous chemical modifications. An abundant group of rRNA modifications, present in all domains of life, is 2’-O-methylation guided by box C/D small nucleolar RNAs (snoRNAs) which are part of small ribonucleoprotein complexes (snoRNPs). Although 2’-O-methylations are required for proper production of ribosomes, the mechanisms by which these modifications contribute to translation have remained elusive. Here, we show that a change in box C/D snoRNP biogenesis in actively growing yeast cells results in the production of hypo 2’-O-methylated ribosomes with distinct translational properties. Using RiboMeth-Seq for the quantitative analysis of 2’-O methylations, we identify site-specific perturbations of the rRNA 2’-O-methylation pattern and uncover sites that are not required for ribosome production under normal conditions. Characterization of the hypo 2’-O-methylated ribosomes reveals significant translational fidelity defects including frameshifting and near-cognate start codon selection. Using rRNA structural probing, we show that hypo 2’-O-methylation affects the inherent dynamics of the ribosomal subunits and impacts the binding of translation factor eIF1 thereby causing translational defects. Our data reveal an unforeseen spectrum of 2’-O-methylation heterogeneity in yeast rRNA and suggest a significant role for rRNA 2’-O-methylation in regulating cellular translation by controlling ribosome dynamics and ligand binding.
Non-linear archetypal analysis of single-cell RNA-seq data by deep autoencoders

Advances in single-cell RNA sequencing (scRNA-seq) have led to successes in discovering novel cell types and understanding cellular heterogeneity among complex cell populations through cluster analysis. However, cluster analysis is not able to reveal continuous spectrum of states and underlying gene expression programs (GEPs) shared across cell types. We introduce scAAnet, an autoencoder for single-cell non-linear archetypal analysis, to identify GEPs and infer the relative activity of each GEP across cells. We use a count distribution-based loss term to account for the sparsity and overdispersion of the raw count data and add an archetypal constraint to the loss function of scAAnet. We first show that scAAnet outperforms existing methods for archetypal analysis across different metrics through simulations. We then demonstrate the ability of scAAnet to extract biologically meaningful GEPs using publicly available scRNA-seq datasets including a pancreatic islet dataset, a lung idiopathic pulmonary fibrosis dataset and a prefrontal cortex dataset.