julilili42/papers huggingface dataset:
Bayesian network modeling of risk and prodromal markers of Parkinson’s disease
2023-02-24

Parkinson’s disease (PD) is characterized by a long prodromal phase with a multitude of markers indicating an increased PD risk prior to clinical diagnosis based on motor symptoms. Current PD prediction models do not consider interdependencies of single predictors, lack differentiation by subtypes of prodromal PD, and may be limited and potentially biased by confounding factors, unspecific assessment methods and restricted access to comprehensive marker data of prospective cohorts. We used prospective data of 18 established risk and prodromal markers of PD in 1178 healthy, PD-free individuals and 24 incident PD cases collected longitudinally in the Tübingen evaluation of Risk factors for Early detection of NeuroDegeneration (TREND) study at 4 visits over up to 10 years. We employed artificial intelligence (AI) to learn and quantify PD marker interdependencies via a Bayesian network (BN) with probabilistic confidence estimation using bootstrapping. The BN was employed to generate a synthetic cohort and individual marker profiles. Robust interdependencies were observed for BN edges from age to subthreshold parkinsonism and urinary dysfunction, sex to substantia nigra hyperechogenicity, depression, non-smoking and to constipation; depression to symptomatic hypotension and excessive daytime somnolence; solvent exposure to cognitive deficits and to physical inactivity; and non-smoking to physical inactivity. Conversion to PD was interdependent with prior subthreshold parkinsonism, sex and substantia nigra hyperechogenicity. Several additional interdependencies with lower probabilistic confidence were identified. Synthetic subjects generated via the BN based representation of the TREND study were realistic as assessed through multiple comparison approaches of real and synthetic data. Altogether our work demonstrates the potential of modern AI approaches (specifically BNs) both for modelling and understanding interdependencies between PD risk and prodromal markers, which are so far not accounted for in PD prediction models, as well as for generating realistic synthetic data.
In vitroandin vivoeffects of zoledronate on senescence and senescence-associated secretory phenotype markers
2023-02-24

ABSTRACT In addition to reducing fracture risk, zoledronate has been found in some studies to decrease mortality in humans and extend lifespan and healthspan in animals. Because senescent cells accumulate with aging and contribute to multiple co-morbidities, the non-skeletal actions of zoledronate could be due to senolytic (killing of senescent cells) or senomorphic (inhibition of the secretion of the senescence-associated secretory phenotype [SASP]) actions. To test this, we first performed in vitro senescence assays using human lung fibroblasts and DNA repair-deficient mouse embryonic fibroblasts, which demonstrated that zoledronate killed senescent cells with minimal effects on non-senescent cells. Next, in aged mice treated with zoledronate or vehicle for 8 weeks, zoledronate significantly reduced circulating SASP factors, including CCL7, IL-1β, TNFRSF1A, and TGFβ1 and improved grip strength. Analysis of publicly available RNAseq data from CD115+ (CSF1R/c-fms+) pre-osteoclastic cells isolated from mice treated with zoledronate demonstrated a significant downregulation of senescence/SASP genes (SenMayo). To establish that these cells are potential senolytic/senomorphic targets of zoledronate, we used single cell proteomic analysis (cytometry by time of flight [CyTOF]) and demonstrated that zoledronate significantly reduced the number of pre-osteoclastic (CD115+/CD3e-/Ly6G-/CD45R-) cells and decreased protein levels of p16, p21, and SASP markers in these cells without affecting other immune cell populations. Collectively, our findings demonstrate that zoledronate has senolytic effects in vitro and modulates senescence/SASP biomarkers in vivo . These data point to the need for additional studies testing zoledronate and/or other bisphosphonate derivatives for senotherapeutic efficacy.
Persistence and Structure
2023-02-25

Abstract Perdurance is a mode of persistence. The heart of perdurance is a space-time analogy: a perduring object is extended in time in a way that is analogous to how a composite object is extended in space. This paper is a discussion of perdurance in light of the distinction between mereologically structured and unstructured objects. I show that while the standard formulation of perdurance captures the space-time analogy for unstructured objects, it fails to capture the space-time analogy for temporally and spatially structured objects. I conclude that there are substantially different ways for an object to be space-like temporally extended.
FaMYB123 interacts with FabHLH3 to regulate the late steps of anthocyanin and flavonol biosynthesis during ripening
2023-02-25

SUMMARY In this work, we identified and functionally characterized the strawberry ( Fragaria × ananassa ) R2R3 MYB transcription factor FaMYB123. As in most genes associated with organoleptic properties of ripe fruit, FaMYB123 expression is ripening‐related, receptacle‐specific, and antagonistically regulated by ABA and auxin. Knockdown of FaMYB123 expression by RNAi in ripe strawberry fruit receptacles downregulated the expression of enzymes involved in the late steps of anthocyanin/flavonoid biosynthesis. Transgenic fruits showed a parallel decrease in the contents of total anthocyanin and flavonoid, especially malonyl derivatives of pelargonidin and cyanidins. The decrease was concomitant with accumulation of proanthocyanin, propelargonidins, and other condensed tannins associated mainly with green receptacles. Potential coregulation between FaMYB123 and FaMYB10, which may act on different sets of genes for the enzymes involved in anthocyanin production, was explored. FaMYB123 and FabHLH3 were found to interact and to be involved in the transcriptional activation of FaMT1 , a gene responsible for the malonylation of anthocyanin components during ripening. Taken together, these results demonstrate that FaMYB123 regulates the late steps of the flavonoid pathway in a specific manner. In this study, a new function for an R2R3 MYB transcription factor, regulating the expression of a gene that encodes a malonyltransferase, has been elucidated.
Climatic imprint in the mechanical properties of ice sheets and its effect on ice flow: Observations fromSouth Pole and EPICA Dome C ice cores
2023-02-25

The climatic conditions over ice sheets at the time of snow deposition and compaction imprint distinctive crystallographic properties to the resulting ice. As it gets buried, its macroscopic structure evolves due to vertical compression but retains traces of the climatic imprint that generate distinctive mechanical, thermal and optical properties. Because climate alternates between glacial periods, that are colder and dustier, and interglacial periods, the ice sheets are composed from layers with alternating mechanical properties. Here we compare ice core dust content, crystal orientation fabrics and englacial vertical strain-rates, measured with a phase-sensitive radar (ApRES), at the South Pole and EPICA Dome C ice cores. In agreement with previous observations, we show that ice deposited during glacial periods develops stronger crystal orientation fabrics. In addition, we show that ice deposited during glacial periods is harder in vertical compression and horizontal extension, up to about three times, but softer in shear. These variations in mechanical properties are ignored in ice-flow models but they could be critical for the interpretation of ice core records. Also, we show that the changes in crystal orientation fabrics due to transitions from interglacial to glacial conditions can be detected by radar. This information can be used to constrain age-depth at future ice-core locations.
Oral Zinc Supplementation in Chronically HEV-Infected Patients Not Responding to Ribavirin Monotherapy
2023-02-25

Background: Chronic hepatitis E virus (HEV) infection may progress to end-stage liver disease in immunosuppressed individuals. Ribavirin therapy is efficient in most chronic HEV patients, but 10% remain without a sustained virological response (SVR). Objectives: We aimed to study whether zinc supplementation could represent a therapeutic approach in these patients. Methods: Antiviral properties of zinc salts were studied in vitro (subgenomic-replicon system), in vivo (rabbit model), and retrospectively in patients with chronic hepatitis E who did not achieve SVR under ribavirin monotherapy. Results: Zinc inhibited HEV genotype 3 replication in vitro. In a model of acute HEV infection in immunocompetent rabbits, zinc + ribavirin did not improve viral clearance compared to ribavirin monotherapy. In chronically HEV-infected patients not responding to ribavirin (n = 12), viral clearance was observed in 4/12 (33%) patients receiving additional zinc supplementation. Conclusions: Oral zinc, an inexpensive, harmless dietary supplement, could potentially represent a rescue treatment option for a few patients with chronic hepatitis E without SVR under ribavirin monotherapy. Further studies are needed to elucidate the role of zinc in HEV.
Granulated biochar-based NPK fertilizer and its impact on nutrient leaching, plant growth and soil-borne N2O emissions
2023-02-25

Biochar amendments to fertilized soils are an important step towards more resource-efficient practices in agriculture by limiting the amounts of nutrients being leached to water bodies or transformed to the potent greenhouse gas (GHG) nitrous oxide (N2O). Biochar was often amended to the soil separately to the fertilizer application. Alternatively, biochar and nutrient bearing salts or minerals can be blended and aggregated, e.g., granulated prior to soil application. However, the impact of this practice on biochar effects on nutrient availability, leachability and soil-borne N2O emissions is so far largely unexplored. Here, we present data on the effects of a granulated, biochar-blended mineral NPK fertilizer applied to a sandy soil in two different greenhouse pot trials on white cabbage and spinach, respectively.&amp;#160;In the white cabbage (Brassica oleracea convar. Capitata var. Alba) experiment, the biochar blended NPK fertilizer reduced nitrogen leaching by 30 to 45% compared to the pure NPK fertilized control following two simulated heavy precipitation events. Results in a similar range were obtained when pure, milled biochar was homogeneously mixed with pure NPK fertilizer in the soil as a further control. The reduced nutrient loss in biochar-amended pots may have contributed to increases in cabbage head biomass of 14% for the granulated biochar NPK fertilizer and 34% for the loose mix of milled biochar with pure NPK fertilizer, when compared to the NPK fertilizer control without biochar.&amp;#160;In the spinach (Spinacia oleracea, no precipitation events) experiment, the biochar-blended granulated fertilizer increased the marketable fresh spinach yields by 5% while the mixture of milled biochar and pure NPK fertilizer in the soil increased yields by 13% compared to the control without biochar, respectively. The analyses of GHG emissions that were measured during this experiment allows to comprehend whether these yield increases were also caused by a lower volatilization of fertilized nitrogen as N2O-N.&amp;#160;With these two experiments, we provide insights on how biochar-blended fertilizers interact with plants and the soil system and how biochar could be used in agricultural practices to increase nutrient use efficiencies, i.e., the environmental costs per unit of yield produced, by reducing the undesired loss of nutrients from soil in combination with yield increase.
Greenland ice-stream dynamics: short-lived and agile?
2023-02-25

Reliable knowledge of ice discharge dynamics for the Greenland ice sheet via its ice streams is essential if we are to understand its stability under future climate scenarios as well as their dynamics in the past, especially when using numerical models for diagnosis and prediction. Currently active ice streams in Greenland have been well mapped using remote-sensing data while past ice-stream paths in what are now deglaciated regions can be reconstructed from the landforms they left behind. However, little is known about possible former and now defunct ice streams in areas still covered by ice. Here we use radio-echo sounding data to decipher the regional ice-flow history of the northeastern Greenland ice sheet on the basis of its internal stratigraphy. By creating a three-dimensional reconstruction of time-equivalent horizons, we map folds deep below the surface that we then attribute to the deformation caused by now-extinct ice streams. We propose that locally this ancient ice-!ow regime was much more focused and reached much farther inland than today&amp;#8217;s and was deactivated when the main drainage system was reconfigured and relocated southwards. The insight that major ice streams in Greenland might start, shift or abruptly disappear will affect our approaches to understanding and modelling the past or future response of Earth&amp;#8217;s ice sheets to global warming. Such behaviour has to be sufficiently reproduced by numerical models operating on the mid- to longer-term timescales to be considered adequate physical representations of the naturally occuring dynamic behaviour of ice streams.
pyESD: An open-source Python framework for empirical-statistical downscaling of climate information
2023-02-25

The nature and severity of climate change impacts varies significantly from region to region. Consequently, high-resolution climate information is needed for meaningful impact assessments and the design of mitigation strategies. This demand has lead to an increase in the coupling of Empirical Statistical Downscaling (ESD) models to General Circulation Model (GCM) simulations of future climate. Here, we present a new open-source Python package (pyESD; github.com/Dan-Boat/PyESD) that implements several Perfect Prognosis ESD (PP-ESD) methods and the whole downscaling cycle. The latter includes routines for data preparation, predictor selection and construction, model selection and training, evaluation, utility tools for relevant statistical tests, visualisation, and more. The package includes a collection of well-established Machine Learning algorithms and allows the user to choose a variety of estimators, cross-validation schemes, objective function measures, hyperparameter optimization, etc., in relatively few lines of codes. The package is highly modular and flexible, and allows quick and reproducible downscaling of any climate information, such as precipitation, temperature, wind speed or even glacial retreat. We demonstrate the effectiveness of the new PP-ESD framework by generating station-based downscaling products of precipitation and temperature for complex mountainous terrain in Southwest Germany.
Consequences of the spatial configuration of Carbon Dioxide Removal for its potential to withdraw atmospheric CO2
2023-02-25

At the current decarbonization rate, we are set on a path towards re-shaping a substantial share of land for carbon dioxide removal (CDR) over the following decades. However, existing Earth system models which could help to quantify the character of resulting CDR side effects and their consequences for the cumulative CO2 removal do not yet resolve dynamic CDR cover in space. Here, we embark on shedding light on this CDR uncertainty space, scrutinizing CDR impacts in spatial simulations with a comprehensive Earth system model. Assuming CDR to be driven by solar irradiation in the style of photovoltaics, our model is the first to simulate an idealized approach to land-based CDR with its physical, biospheric, and land use couplings on a grid box scale. We analyze dynamic CDR simulations for spatial deployment scenarios according to the country-wise burden of past CO2 emissions, to livelihood constraints, and to optimal irradiation conditions. Shared socio-economic pathways drive the overall global CDR use for a range of potential future emission scenarios. Aside from these spatio-temporal scenarios, the simulations also cover different ways of releasing excess energy from the solar-to-carbon conversion, permitting either local cooling through carbon storage, heat dissipation resulting from system losses or co-benefits for energy production. Based on simulation ensembles for the different scenarios, we quantify Earth system impacts of CDR and their consequences for CO2 removal if grid-scale feedbacks are properly resolved. With new spatially resolved CDR representations in Earth system models we will be able to test CDR-induced Earth system dynamics and CDR promises in greater detail than with existing globally forced projections. This spatially explicit modeling strategy could also open a way toward more comprehensive modeling strategies which include consequences for land use decisions on CDR.
Determining Basal Mass Balance of Ice Shelves Using Simulation-Based Inference
2023-02-25

The ice shelves buttressing the Antarctic ice sheet determine its stability. Over half of all mass loss in Antarctica occurs due to ice melting at the water-ice boundary at the base of ice shelves. Different contemporary methods of estimating the spatial distribution of the melting rates do not produce consistent results, and provide no information about decadal to centennial timescales. We explore a new method to infer the spatial distribution of the basal mass balance (BMB) using the internal stratigraphy which may contain additional information not present in other sources such as ice thickness and surface velocities alone. The method estimates the Bayesian posterior distribution of the BMB,&amp;#160; and provides us with a principled measure of uncertainty in our estimates.&amp;#160;&amp;#160;Our inference procedure is based on simulation-based inference (SBI) [1], a novel machine learning inference method. SBI utilizes artificial neural networks to approximate probability distributions which characterize those parameters that yield data-compatible simulations, without the need of an explicit likelihood function. We demonstrate the validity of our method on a synthetic ice shelf example, and then apply it to Ekstr&amp;#246;m ice shelf, East Antarctica, where we have radar measurements of the internal stratigraphy. The inference procedure relies on a simulator of the dynamics of the ice shelves. For this we use the Shallow Shelf Approximation (SSA) implemented in the Python library Icepack [2], and a time-discretized layer tracing scheme [3].&amp;#160; These detailed simulations, along with available stratigraphic data and the SBI methodology, allows us to compute a spatially-varying posterior distribution of the melting rate. This distribution corroborates existing estimates and extends upon them by quantifying the uncertainty in our inference. This uncertainty should be incorporated in future forecasting of ice shelf dynamics and stability analysis.&amp;#160;[1] Lueckmann et al.: Benchmarking simulation-based inference (2020).[2] Shapero et al.: icepack: a new glacier flow modeling package in Python, version 1.0. (2021).[3] Born: Tracer transport in an isochronal ice-sheet model (2017).
Mechanisms of migration of bacteria the pore space
2023-02-25

The establishment of microbes in the rhizosphere requires a complex sequence of mobility, proliferation, and attachment/detachment from the root as well as soil surfaces. Most research has focused on proliferation and biofilm formation while the mobility and attachment of microbes in soil has remained mysterious and hidden. We combined novel microscopy technologies and mathematical models to capture and characterise the dynamic movement of bacteria through soil during the early stages of root colonisation. The study revealed how bacteria behave as a flock to exploit the pore space and move towards plant roots where they collectively interact with the root tip before forming biofilms on more mature root zones. Results in this study add significantly to our understanding of the biophysical mechanisms enabling microbial colonisation dynamics in soil.ReferencesLiu Y., Patko D, Engelhardt I.C, George T.S., Stanley-Wall N.P., Ladmiral V., Ameduri B., Daniell T.J., Holden N., MacDonald M.P., Dupuy L.X. (2021). Whole plant-environment microscopy reveals how Bacillus subtilis utilises the soil pore space to colonise plant roots. 118 (48) e2109176118Engelhardt I. C., Patko D., Liu Y., Mimault M., de las Heras Martinez G., George T. S., MacDonald M., Ptashnyk M., Sukhodub T., Stanley-Wall N. R., Holden N., Daniell T. J. &amp; Dupuy &amp;#160;L. X. The ISME Journal volume 16, pages2337&amp;#8211;2347 (2022)&amp;#160;
Improving efficiency of citizen science projects by targeted activation of selected stakeholder groups
2023-02-25

As citizen science is becoming a widely accepted research approach across multiple disciplines, it is essential to explore methods for effective recruitment, involvement, and retention of participants for these programs. An effective recruitment strategy results in motivated and engaged contributors, longer-term participation, and better communication exchange.In this research, we present two marketing approaches adapted from best practice in customer-facing fields in order to identify appropriate stakeholder groups for citizen science and keep motivation and retention of the participants high. Firstly, stakeholder analysis is a major tool within the frame of stakeholder management and includes the systematic identification of stakeholders and their relevance and influence on a project. Thus, efficiency of citizen science projects can be improved significantly by targeted identification and selection of participants and groups through stakeholder analysis, which are suited to generate the data needed to reach the project and research goals. Secondly, the value proposition canvas approach is based on business strategies to match products and services to the market or customer. The value proposition canvas can be adapted to scientific processes and the data generated can help citizen science groups to build a communication strategy that can clearly communicate the value of their message and shared goals to the participants.The application of stakeholder analysis and value proposition canvas is demonstrated using the case study of the project "Next Generation City Climate Services Using Advanced Weather Models and Emerging Data Sources" (CityCLIM, a European Union Horizon 2020 funded project), where the focus is to develop next-generation City Climate Services based on advanced weather forecast models enhanced with data from emerging data sources such as Citizen Science approaches for urban climate monitoring. Before meetings with citizens in pilot cities, stakeholder groups involved in the CityCLIM project were examined and their profiles were analysed using the value proposition canvas. Lessons learned from the use of these tools for engagement with citizens in pilot cities will be presented. Findings also provide an approach that can be used by citizen science groups in environmental observation to strategically target participants and tailor key communication messages, towards the goal of a focused and sustained monitoring of environmental processes.