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Anaerobic methane oxidation is coupled to the reduction of electron acceptors, such as sulfate, and contributes to their biogeochemical cycling in the environment. However, whether arsenate acts as an alternative electron acceptor of anaerobic methane oxidation and how this influences global arsenic transformations remains elusive. Here, we present incubations of arsenate-contaminated wetland soils from seven provinces in China. Using isotopically labelled methane, we find that anaerobic methane oxidation was linked to arsenate reduction at a rate approaching the theoretical arsenic/methane stoichiometric ratio of 4. In microcosm incubations with natural wetland soils, we find that the coupled pathway of anaerobic methane oxidation and arsenate reduction contributed 26 to 49% of total arsenic release from soils, with arsenic in the more soluble and toxic form arsenite. Comparative gene quantification and metagenomic sequencing suggest that the coupled pathway was facilitated by anaerobic methanotrophs, either independently or synergistically with arsenate-reducing bacteria through reverse methanogenesis and respiratory arsenate reduction. Further bioinformatic analyses show that genes coding for reverse methanogenesis and respiratory arsenate reduction are universally co-distributed in nature. This suggests that coupling of anaerobic methane oxidation and arsenate reduction is a potentially global but previously overlooked process, with implications for arsenic mobilization and environmental contamination.The coupling of anaerobic oxidation of methane and arsenate reduction is an important pathway of releasing arsenic from soils, according to incubation experiments of arsenate-contaminated wetland soils.

In tokamak disruptions where the magnetic connection length becomes comparable to or even shorter than the plasma mean-free-path, parallel transport can dominate the energy loss and the thermal quench of the core plasma goes through four phases (stages) that have distinct temperature ranges and durations. The main temperature drop occurs while the core plasma remains nearly collisionless, with the parallel electron temperature T e ∥ dropping in time t as T e ∥ ∝ t − 2 and a cooling time that scales with the ion sound wave transit time over the length of the open magnetic field line. These surprising physics scalings are the result of effective suppression of parallel electron thermal conduction in an otherwise bounded, quasineutral, and collisionless plasma, which is different from what are known to date on electron thermal conduction along the magnetic field in a nearly collisionless and quasineural plasma.

Background Adrenocortical carcinoma (ACC) is an aggressive and rare malignant tumor and is prone to local invasion and metastasis. And, overexpressed Centromere Protein F (CENPF) is closely related to the oncogenesis of various neoplasms, including ACC. However, the prognosis and exact biological function of CENPF in ACC remains largely unclear. Methods In the present essay, the expression patterns and prognostic value of CENPF in ACC were investigated in clinical specimens and public cancer databases, including GEO and TCGA. The potential signaling mechanism of CENPF in ACC was studied based on gene-set enrichment analysis (GSEA). Furthermore, a small RNA interference experiment was conducted to probe the underlying biological function of CENPF in the human ACC cell line, SW13 cells. Lastly, two available therapeutic strategies, including immunotherapy and chemotherapy, have been further explored. Results The expression of CENPF in human ACC samples, GEO, and TCGA databases depicted that CENPF was overtly hyper-expressed in ACC patients and positively correlated with tumor stage. The aberrant expression of CENPF was significantly correlated with unfavorable overall survival (OS) in ACC patients. Then, the GSEA analysis declared that CENPF was mainly involved in the G2/M-phase mediated cell cycle and p53 signaling pathway. Further, the in vitro experiment demonstrated that the interaction between CENPF and CDK1 augmented the G2/M-phase transition of mitosis, cell proliferation and might induce p53 mediated anti-tumor effect in human ACC cell line, SW13 cells. Lastly, immune infiltration analysis highlighted that ACC patients with high CENPF expression harbored significantly different immune cell populations, and high TMB/MSI score. The gene-drug interaction network stated that CENPF inhibitors, such as Cisplatin, Sunitinib, and Etoposide, might serve as potential drugs for the therapy of ACC. Conclusion The result points out that CENPF is significantly overexpressed in ACC patients. The overexpressed CENPF predicts a poor prognosis of ACC and might augment the progress of ACC. Thus, CENPF and related genes might serve as a novel prognostic biomarker or latent therapeutic target for ACC patients.

Thermal quench of a nearly collisionless plasma against an isolated cooling boundary or region is an undesirable off-normal event in magnetic fusion experiments, but an ubiquitous process of cosmological importance in astrophysical plasmas. Parallel transport theory of ambipolar-constrained tail electron loss is known to predict rapid cooling of the parallel electron temperature although is difficult to diagnose in actual experiments. Instead direct experimental measurements can readily track the perpendicular electron temperature via electron cyclotron emission. The physics underlying the observed fast drop in requires a resolution. Here two collisionless mechanisms, dilutional cooling by infalling cold electrons and wave-particle interaction by two families of whistler instabilities, are shown to enable fast cooling that closely tracks the mostly collisionless crash of These findings motivate both experimental validation and reexamination of a broad class of plasma cooling problems in laboratory, space, and astrophysical settings.

The edge plasma turbulence and transport dynamics, as well as the divertor power loads during the thermal-quench phase of tokamak disruptions, are numerically investigated with BOUT++’s flux-driven six-field electromagnetic turbulence model. Here, transient yet intense particle and energy sources are applied at the pedestal top to mimic the plasma power drive at the edge induced by a core thermal collapse, which flattens the core temperature profile. Interesting features, such as surging of divertor heat load (up to 50 times) and broadening of heat-flux width (up to four times) on the outer-divertor target plate, are observed in the simulation, in qualitative agreement with experimental observations. The dramatic changes in divertor heat load and width are due to the enhanced plasma turbulence activities inside the separatrix. Two cross-field transport mechanisms, namely, the E  ×  B turbulent convection and the stochastic parallel advection/conduction, are identified to play important roles in this process. First, an elevated edge pressure gradient drives instabilities and subsequent turbulence in the entire pedestal region. The enhanced turbulence not only transports particles and energy radially across the separatrix via the E  ×  B convection, which causes the initial divertor heat-load burst, but it also induces amplified magnetic fluctuation B ˜ . Once themagnetic fluctuation is large enough to break the magnetic flux surface, magnetic flutter effect provides an additional radial transport channel. In the late stage of our simulation, | B ˜ r / B 0 | reaches to 10 −4 level that completely breaks magnetic flux surfaces such that stochastic field lines are directly connecting pedestal top plasma to the divertor target plates or first wall, further contributing to the divertor heat-flux width broadening.

A physics-constrained deep learning surrogate that predicts the exponential ‘avalanche’ growth rate of runaway electrons (REs) for a plasma containing partially ionized impurities is developed. Specifically, a physics-informed neural network (PINN) that learns the adjoint of the relativistic Fokker–Planck equation in steady-state is derived, enabling a rapid surrogate of the RE avalanche for a broad range of plasma parameters, motivating a path towards an machine learning-accelerated integrated description of a tokamak disruption. A steady-state power balance equation together with atomic physics data is embedded directly into the PINN, thus limiting the PINN to train across physically consistent temperatures and charge state distributions. This restricted training domain enables accurate predictions of the PINN while drastically reducing the computational cost of training the model. In addition, a novel closure for the relativistic electron population used when evaluating the secondary source of REs is developed that enables improved accuracy compared to a Rosenbluth–Putvinski source. The avalanche surrogate is verified against Monte Carlo simulations, where it is shown to accurately predict the RE avalanche growth rate across a broad range of plasma parameters encompassing distinct tokamak disruption scenarios.

The corrosion behavior of environmental barrier coatings (EBCs) directly affects the service life and stability of ceramic matrix composite (CMC) structural parts in the aero-engines. The silicon carbide (SiC) whisker toughening phase and c-AlPO 4 bonding phase are firstly used to improve the service life of novel tri-layer Yb 2 Si 2 O 7 /mullite/SiC EBCs in the burner rig test. The formation of penetrating cracks in Yb 2 Si 2 O 7 /mullite/SiC coating caused the failure of coating at 1673 K. The SiC whiskers in mullite middle coating significantly inhibited the formation of penetrating cracks in Yb 2 Si 2 O 7 /mullite/SiC coating, and efficiently prevented the oxidation of carbon fiber reinforced silicon carbide (C f /SiC) samples for 360-min thermal cycles (24 times) with a weight loss of 6.19×10 −3 g·cm −2 . Although c-AlPO 4 particles further improved the service life of SiC w -mullite (SM) coating, the overflow of PO x gas aggravated the formation and expansion of cracks in the Yb 2 Si 2 O 7 outer coating, and caused the service life of overall Yb 2 Si 2 O 7 /c-AlPO 4 -SiC w -mullite (ASM)/SiC coating to be slightly lower than that of Yb 2 Si 2 O 7 /SM/SiC coating. This study guides the design of modified tri-layer EBCs with long service life in high-temperature and high-speed gas environment.

The conventional approach for thermal quench (TQ) mitigation in a tokamak disruption is through a high-Z impurity injection that radiates away the plasma’s thermal energy before it reaches the wall. The downside is a robust Ohmic-to-runaway current conversion due to the radiatively clamped low post-thermal-quench electron temperature. An alternative approach is to deploy a low-Z (either deuterium or hydrogen) injection that aims to slow down the TQ, and ideally aligns it with the current quench (CQ). This approach has been investigated here via 3D MHD simulations using the PIXIE3D code. By boosting the hydrogen density, a fusion-grade plasma is dilutionally cooled at approximately the original pressure. Energy loss to the wall is controlled by a Bohm outflow condition at the boundary where the magnetic field intercepts a thin plasma sheath at the wall, in addition to Bremsstrahlung bulk losses. Robust MHD instabilities proceed as usual, while the collisionality of the plasma has been greatly increased and parallel transport is now in the Braginskii regime. The main conclusion of this study is that the decreased transport loss along open field lines due to a sufficient low-Z injection slows down the TQ rate to the order of 20 ms, aligned with the CQ timescale for a 15 MA ITER plasma.

Caused by multiple risk factors, heavy burden of major depressive disorder (MDD) poses serious challenges to public health worldwide over the past 30 years. Yet the burden and attributable risk factors of MDD were not systematically known. We aimed to reveal the long-term spatio-temporal trends in the burden and attributable risk factors of MDD at global, regional and national levels during 1990-2019. We obtained MDD and attributable risk factors data from Global Burden of Disease Study 2019. We used joinpoint regression model to assess the temporal trend in MDD burden, and age-period-cohort model to measure the effects of age, period and birth cohort on MDD incidence rate. We utilized population attributable fractions (PAFs) to estimate the specific proportions of MDD burden attributed to given risk factors. During 1990-2019, the global number of MDD incident cases, prevalent cases and disability-adjusted life years (DALYs) increased by 59.10%, 59.57% and 58.57%, respectively. Whereas the global age-standardized incidence rate (ASIR), age-standardized prevalence rate (ASPR) and age-standardized DALYs rate (ASDR) of MDD decreased during 1990-2019. The ASIR, ASPR and ASDR in women were 1.62, 1.62 and 1.60 times as that in men in 2019, respectively. The highest age-specific incidence, prevalence and DALYs rate occurred at the age of 60-64 in women, and at the age of 75-84 in men, but the maximum increasing trends in these age-specific rates occurred at the age of 5-9. Population living during 2000-2004 had higher risk of MDD. MDD burden varied by socio-demographic index (SDI), regions and nations. In 2019, low-SDI region, Central sub-Saharan Africa and Uganda had the highest ASIR, ASPR and ASDR. The global PAFs of intimate partner violence (IPV), childhood sexual abuse (CSA) and bullying victimization (BV) were 8.43%, 5.46% and 4.86% in 2019, respectively. Over the past 30 years, the global ASIR, ASPR and ASDR of MDD had decreased trends, while the burden of MDD was still serious, and multiple disparities in MDD burden remarkably existed. Women, elderly and populations living during 2000-2004 and in low-SDI regions, had more severe burden of MDD. Children were more susceptible to MDD. Up to 18.75% of global MDD burden would be eliminated through early preventing against IPV, CSA and BV. Tailored strategies-and-measures in different regions and demographic groups based on findings in this studywould be urgently needed to eliminate the impacts of modifiable risk factors on MDD, and then mitigate the burden of MDD.

Despite recent advances in the assembly of organic nanotubes, conferral of sequence-defined engineering and dynamic response characteristics to the tubules remains a challenge. Here we report a new family of highly designable and dynamic nanotubes assembled from sequence-defined peptoids through a unique “rolling-up and closure of nanosheet” mechanism. During the assembly process, amorphous spherical particles of amphiphilic peptoid oligomers crystallize to form well-defined nanosheets before folding to form single-walled nanotubes. These nanotubes undergo a pH-triggered, reversible contraction–expansion motion. By varying the number of hydrophobic residues of peptoids, we demonstrate tuning of nanotube wall thickness, diameter, and mechanical properties. Atomic force microscopy-based mechanical measurements show peptoid nanotubes are highly stiff (Young’s Modulus ~13–17 GPa). We further demonstrate the precise incorporation of functional groups within nanotubes and their applications in water decontamination and cellular adhesion and uptake. These nanotubes provide a robust platform for developing biomimetic materials tailored to specific applications. The application potential of organic nanotubes is currently limited by their lack of designable or dynamic properties. Here, Chen et al. use sequence-defined peptoids to assemble a new family of pH-responsive stiff nanotubes whose dimensions, components and functions can be easily tailored.