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Soil organic matter can release carbon dioxide to the atmosphere as the climate warms. Organic matter sorbed to reactive (iron- and aluminium-bearing) soil minerals is an important mechanism for long-term carbon storage. However, the global distribution of mineral-stored carbon across climate zones and consequently its overall contribution to the global soil carbon pool is poorly known. We measured carbon held by reactive minerals across a broad range of climates. Carbon retained by reactive minerals was found to contribute between 3 and 72% of organic carbon found in mineral soil, depending on mean annual precipitation and potential evapotranspiration. Globally, we estimate ~600 Gt of soil carbon is retained by reactive minerals, with most occurring in wet forested biomes. For many biomes, the fraction of organic carbon retained by reactive minerals is responsive to slight shifts in effective moisture, suggesting high sensitivity to future changes in climate.

Soil organic matter (SOM) anchors global terrestrial productivity and food and fiber supply. SOM retains water and soil nutrients and stores more global carbon than do plants and the atmosphere combined. SOM is also decomposed by microbes, returning CO 2 , a greenhouse gas, to the atmosphere. Unfortunately, soil carbon stocks have been widely lost or degraded through land use changes and unsustainable forest and agricultural practices. To understand its structure and function and to maintain and restore SOM, we need a better appreciation of soil organic carbon (SOC) saturation capacity and the retention of above- and belowground inputs in SOM. Our analysis suggests root inputs are approximately five times more likely than an equivalent mass of aboveground litter to be stabilized as SOM. Microbes, particularly fungi and bacteria, and soil faunal food webs strongly influence SOM decomposition at shallower depths, whereas mineral associations drive stabilization at depths greater than ∼30 cm. Global uncertainties in the amounts and locations of SOM include the extent of wetland, peatland, and permafrost systems and factors that constrain soil depths, such as shallow bedrock. In consideration of these uncertainties, we estimate global SOC stocks at depths of 2 and 3 m to be between 2,270 and 2,770 Pg, respectively, but could be as much as 700 Pg smaller. Sedimentary deposits deeper than 3 m likely contain >500 Pg of additional SOC. Soils hold the largest biogeochemically active terrestrial carbon pool on Earth and are critical for stabilizing atmospheric CO 2 concentrations. Nonetheless, global pressures on soils continue from changes in land management, including the need for increasing bioenergy and food production.

The SPARC tokamak is a critical next step towards commercial fusion energy. SPARC is designed as a high-field ($B_0 = 12.2$ T), compact ($R_0 = 1.85$ m, $a = 0.57$ m), superconducting, D-T tokamak with the goal of producing fusion gain $Q>2$ from a magnetically confined fusion plasma for the first time. Currently under design, SPARC will continue the high-field path of the Alcator series of tokamaks, utilizing new magnets based on rare earth barium copper oxide high-temperature superconductors to achieve high performance in a compact device. The goal of $Q>2$ is achievable with conservative physics assumptions ($H_{98,y2} = 0.7$) and, with the nominal assumption of $H_{98,y2} = 1$, SPARC is projected to attain $Q \\approx 11$ and $P_{\\textrm {fusion}} \\approx 140$ MW. SPARC will therefore constitute a unique platform for burning plasma physics research with high density ($\\langle n_{e} \\rangle \\approx 3 \\times 10^{20}\\ \\textrm {m}^{-3}$), high temperature ($\\langle T_e \\rangle \\approx 7$ keV) and high power density ($P_{\\textrm {fusion}}/V_{\\textrm {plasma}} \\approx 7\\ \\textrm {MW}\\,\\textrm {m}^{-3}$) relevant to fusion power plants. SPARC's place in the path to commercial fusion energy, its parameters and the current status of SPARC design work are presented. This work also describes the basis for global performance projections and summarizes some of the physics analysis that is presented in greater detail in the companion articles of this collection.

A bstract We present predictions for the prompt-neutrino flux arising from the decay of charmed mesons and baryons produced by the interactions of high-energy cosmic rays in the Earth’s atmosphere, making use of a QCD approach on the basis of the general-mass variable-flavor-number scheme for the description of charm hadroproduction at NLO, complemented by a consistent set of fragmentation functions. We compare the theoretical results to those already obtained by our and other groups with different theoretical approaches. We provide comparisons with the experimental results obtained by the IceCube Collaboration in two different analyses and we discuss the implications for parton distribution functions.

PurposeRisk classification of primary prostate cancer in clinical routine is mainly based on prostate-specific antigen (PSA) levels, Gleason scores from biopsy samples, and tumor-nodes-metastasis (TNM) staging. This study aimed to investigate the diagnostic performance of positron emission tomography/magnetic resonance imaging (PET/MRI) in vivo models for predicting low-vs-high lesion risk (LH) as well as biochemical recurrence (BCR) and overall patient risk (OPR) with machine learning.MethodsFifty-two patients who underwent multi-parametric dual-tracer [18F]FMC and [68Ga]Ga-PSMA-11 PET/MRI as well as radical prostatectomy between 2014 and 2015 were included as part of a single-center pilot to a randomized prospective trial (NCT02659527). Radiomics in combination with ensemble machine learning was applied including the [68Ga]Ga-PSMA-11 PET, the apparent diffusion coefficient, and the transverse relaxation time-weighted MRI scans of each patient to establish a low-vs-high risk lesion prediction model (MLH). Furthermore, MBCR and MOPR predictive model schemes were built by combining MLH, PSA, and clinical stage values of patients. Performance evaluation of the established models was performed with 1000-fold Monte Carlo (MC) cross-validation. Results were additionally compared to conventional [68Ga]Ga-PSMA-11 standardized uptake value (SUV) analyses.ResultsThe area under the receiver operator characteristic curve (AUC) of the MLH model (0.86) was higher than the AUC of the [68Ga]Ga-PSMA-11 SUVmax analysis (0.80). MC cross-validation revealed 89% and 91% accuracies with 0.90 and 0.94 AUCs for the MBCR and MOPR models respectively, while standard routine analysis based on PSA, biopsy Gleason score, and TNM staging resulted in 69% and 70% accuracies to predict BCR and OPR respectively.ConclusionOur results demonstrate the potential to enhance risk classification in primary prostate cancer patients built on PET/MRI radiomics and machine learning without biopsy sampling.

Models of ecosystem carbon (C) balance generally assume a strong relationship between NPP, litter inputs, and soil C accumulation, but there is little direct evidence for such a coupled relationship. Using a unique 50-year detrital manipulation experiment in a mixed deciduous forest and in restored prairie grasslands in Wisconsin, combined with sequential density fractionation, isotopic analysis, and short-term incubation, we examined the effects of detrital inputs and removals on soil C stabilization, destabilization, and quality. Both forested sites showed greater decline in bulk soil C content in litter removal plots (55 and 66 %) compared to increases in litter addition plots (27 and 38 % increase in surface soils compared to controls). No accumulation in the mineral fraction C was observed after 50 years of litter addition of the two forested plots, thus increases in the light density fraction pool drove patterns in total C content. Litter removal across both ecosystem types resulted in a decline in both free light fraction and mineral C content, with an overall 51 % decline in mineral-associated carbon in the intermediate (1.85–2.4 g cm⁻³) density pool; isotopic data suggest that it was preferentially younger C that was lost. In contrast to results from other, but younger litter manipulation sites, there was with no evidence of priming even in soils collected after 28 years of treatment. In prairie soils, aboveground litter exclusion had an effect on C levels similar to that of root exclusion, thus we did not see evidence that root-derived C is more critical to soil C sequestration. There was no clear evidence that soil C quality changed in litter addition plots in the forested sites; δ¹³C and Δ¹⁴C values, and incubation estimates of labile C were similar between control and litter addition soils. C quality appeared to change in litter removal plots; soils with litter excluded had Δ¹⁴C values indicative of longer mean residence times, δ¹³C values indicative of loss of fresh plant-derived C, and decreases in all light fraction C pools, although incubation estimates of labile C did not change. In prairie soils, δ¹³C values suggest a loss of recent C4-derived soil C in litter removal plots along with significant increases in mean residence time, especially in plots with removal of roots. Our results suggest surface mineral soils may be vulnerable to significant C loss in association with disturbance, land use change, or perhaps even climate change over century–decadal timescales, and also highlight the need for longer-term experimental manipulations to study soil organic matter dynamics.

A new, rapid Fourier transform near infrared (FT-NIR) spectroscopic procedure is described to screen for the authenticity of extra virgin olive oils (EVOO) and to determine the kind and amount of an adulterant in EVOO. To screen EVOO, a partial least squares (PLS1) calibration model was developed to estimate a newly created FT-NIR index based mainly on the relative intensities of two unique carbonyl overtone absorptions in the FT-NIR spectra of EVOO and other mixtures attributed to volatile (5280 cm⁻¹) and non-volatile (5180 cm⁻¹) components. Spectra were also used to predict the fatty acid (FA) composition of EVOO or samples spiked with an adulterant using previously developed PLS1 calibration models. Some adulterated mixtures could be identified provided the FA profile was sufficiently different from those of EVOO. To identify the type and determine the quantity of an adulterant, gravimetric mixtures were prepared by spiking EVOO with different concentrations of each adulterant. Based on FT-NIR spectra, four PLS1 calibration models were developed for four specific groups of adulterants, each with a characteristic FA composition. Using these different PLS1 calibration models for prediction, plots of predicted vs. gravimetric concentrations of an adulterant in EVOO yielded linear regression functions with four unique sets of slopes, one for each group of adulterants. Four corresponding slope rules were defined that allowed for the determination of the nature and concentration of an adulterant in EVOO products by applying these four calibration models. The standard addition technique was used for confirmation.

Activation of the Hippo pathway effector Yap underlies many liver cancers, however no germline or somatic mutations have been identified. Autophagy maintains essential metabolic functions of the liver, and autophagy-deficient murine models develop benign adenomas and hepatomegaly, which have been attributed to activation of the p62/Sqstm1-Nrf2 axis. Here, we show that Yap is an autophagy substrate and mediator of tissue remodeling and hepatocarcinogenesis independent of the p62/Sqstm1-Nrf2 axis. Hepatocyte-specific deletion of Atg7 promotes liver size, fibrosis, progenitor cell expansion, and hepatocarcinogenesis, which is rescued by concurrent deletion of Yap. Our results shed new light on mechanisms of Yap degradation and the sequence of events that follow disruption of autophagy, which is impaired in chronic liver disease. Increased levels of the Yap oncoprotein stimulate liver growth and promote hepatocarcinogenesis. Here the authors show that hepatocyte-specific loss of Atg7 in mice leads to decreased autophagic degradation of Yap and liver overgrowth, and further establish this association in human liver cancer tissues.

A heatwave in June 2021 exposed Pacific Northwest (PNW) snowpack to record temperatures, allowing us to probe seasonal snowpack response to short-term heat extremes. Using high-resolution contiguous snowpack and temperature datasets (daily 1 km 2 SNODAS, 4 km 2 PRISM), we examined daily snowmelt in cooler, higher-elevation zones during this event, contrasted with the prior 18 years (2004–2021). We found that multiple early season (spring) heatwaves, concluding with the 2021 heat dome itself, resulted in dramatic early season melt including the most persistent fraction of PNW snowpack. Using longer-term station records (1940–2021), we show that springtime +5 °C daily anomalies were historically rare but since the mid-1990s have doubled in frequency and/or intensity, now potentially affecting typically cool La Niña periods (2021). Collectively, these results indicate that successive heat extremes drive rapid snowmelt, and these extremes may increasingly threaten previously resilient fractions of seasonal snowpack.

We study inclusive B-meson production in pp collisions at the LHC and compare experimental data with predictions of the general-mass variable-flavour-number scheme at next-to-leading order of perturbative QCD. We find almost perfect agreement provided that the factorization scale parameters and the parton distribution functions are chosen appropriately.