A nanostructured lithium‐metal anode employing an unstacked graphene “drum” and dual‐salt electrolyte brings about a dendrite‐free lithium depositing morphology. On the one hand, the unstacked ...graphene framework with ultrahigh specific surface area guarantees an ultralow local current density that prevents the growth of lithium dendrites. On the other hand, the stable, flexible, and compact solid electrolyte interphase layer induced by the dual‐salt electrolyte protects the deposited lithium layers.
A cooperative interface constructed by “lithiophilic” nitrogen‐doped graphene frameworks and “sulfiphilic” nickel–iron layered double hydroxides (LDH@NG) is proposed to synergistically afford ...bifunctional Li and S binding to polysulfides, suppression of polysulfide shuttles, and electrocatalytic activity toward formation of lithium sulfides for high‐performance lithium–sulfur batteries. LDH@NG enables high rate capability, long lifespan, and efficient stabilization of both sulfur and lithium electrodes.
Solid/liquid interfaces are ubiquitous in nature and knowledge of their atomic-level structure is essential in elucidating many phenomena in chemistry, physics, materials science and Earth science
. ...In electrochemistry, in particular, the detailed structure of interfacial water, such as the orientation and hydrogen-bonding network in electric double layers under bias potentials, has a significant impact on the electrochemical performances of electrode materials
. To elucidate the structures of electric double layers at electrochemical interfaces, we combine in situ Raman spectroscopy and ab initio molecular dynamics and distinguish two structural transitions of interfacial water at electrified Au single-crystal electrode surfaces. Towards negative potentials, the interfacial water molecules evolve from structurally 'parallel' to 'one-H-down' and then to 'two-H-down'. Concurrently, the number of hydrogen bonds in the interfacial water also undergoes two transitions. Our findings shed light on the fundamental understanding of electric double layers and electrochemical processes at the interfaces.
Antibiotic resistance genes (ARGs) are emerging micropollutants with environmental persistence. Aquaculture environments are considered as potential reservoirs for ARGs pollution and horizontal gene ...transfer (HGT). This study analyzed water and sediment from eight culture ponds (integrated culture: duck-fish pond; monoculture: duck pond and fish pond) and a control pond (without any aquaculture activity) in Zhongshan, South China. Seventeen types of ARGs were detected in all ponds, which conferring resistance to four classes of antibiotics including tetracycline (tetA, tetB, tetC, tetE, tetG, tetL, tetA-P, tetM, tetO, tetS, tetW and tetX), AmpC beta-lactamase products (EBC and FOX), sulfonamide (sul1 and sul2) and erythromycin (ermA), with class 1 integron (intI1) as motility gene. The total concentrations of detected ARGs in culture pond water were much higher than control (about 1.6–4.0 times). Integrated culture showed lowest absolute abundance of ∑ARGs in water (3.686 × 107 copies mL−1) and the highest in sediment (4.574 × 108 copies g−1). Monoculture ponds showed higher relative abundance of ∑ARGs both in water (fish pond: 0.5149) and sediment (duck pond: 0.4919). As the main contributor to the ARGs abundance and significant correlations with ∑tet, ∑ARGs and intI1 (P < 0.01), tetA was suggested to be a potential indicator for the abundance of tetracycline resistance genes in these classes of aquaculture modes in the Pearl River Delta. This study provides a case for the ARGs abundance in aquaculture and as a reference for the upcoming health risk assessment in aquatic environment.
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•Lower abundance of ARGs was detected in water of integrated culture than monoculture.•AmpC beta-lactamase genes were detected in pond water and sediment.•ARGs accumulated and persisted in sediments even in case of antibiotics undetectable.•TetA could be potential indicator to tetracycline resistance genes in aquaculture.
Silicon carbide (SiC) fiber‐reinforced SiC matrix (SiC/SiC) composites have emerged as a new material candidate for fuel claddings in light water reactors. Recent studies showed that the load ...capacity of SiC/SiC materials exhibits a considerable statistical variation. Therefore, reliability analysis plays a critical role in design of SiC/SiC composite claddings. This paper presents a probabilistic model for the lifetime distribution of SiC/SiC composites. The model is anchored by a multiaxial stress‐based failure criterion and subcritical damage accumulation mechanism. Based on the kinetics of subcritical damage growth, the lifetime distribution of a laboratory test specimen for any given loading history can be calculated. A finite weakest‐link model is used to extrapolate the lifetime distribution of test specimens to full‐length claddings. It is shown that the damage accumulation mechanism has a strong influence on the lifetime distribution of the cladding. This finding highlights the importance of understanding the static fatigue behavior of SiC/SiC composites. The present analysis also demonstrates an intricate length effect on the failure probability of the cladding, which is expected to play a crucial role in design extrapolation.
AgNPs are nanomaterials with many potential biomedical applications. In this study, the two novel yeast strains HX-YS and LPP-12Y capable of producing biological silver nanoparticles were isolated. ...Sequencing of ribosomal DNA-ITS fragments, as well as partial D1/D2 regions of 26S rDNA indicated that the strains are related to species from the genus Metschnikowia. The BioAgNPs produced by HX-YS and LPP-12Y at pH 5.0-6.0 and 26 °C ranged in size from 50 to 500 nm. The antibacterial activities of yeast BioAgNPs against five pathogenic bacteria were determined. The highest antibacterial effect was observed on P. aeruginosa, with additional obvious effects on E. coli ATCC8099 and S. aureus ATCC10231. Additionally, the BioAgNPs showed antiproliferative effects on lung cancer cell lines H1975 and A579, with low toxicity in Beas 2B normal lung cells. Therefore, the AgNPs biosynthesized by HX-YS and LPP-12Y may have potential applications in the treatment of bacterial infections and cancer.
TP53 is the most frequently mutated gene in cancer, yet these mutations remain therapeutically non-actionable. Major challenges in drugging p53 mutations include heterogeneous mechanisms of ...inactivation and the absence of broadly applicable allosteric sites. Here we report the identification of small molecules, including arsenic trioxide (ATO), an established agent in treating acute promyelocytic leukemia, as cysteine-reactive compounds that rescue structural p53 mutations. Crystal structures of arsenic-bound p53 mutants reveal a cryptic allosteric site involving three arsenic-coordinating cysteines within the DNA-binding domain, distal to the zinc-binding site. Arsenic binding stabilizes the DNA-binding loop-sheet-helix motif alongside the overall β-sandwich fold, endowing p53 mutants with thermostability and transcriptional activity. In cellular and mouse xenograft models, ATO reactivates mutant p53 for tumor suppression. Investigation of the 25 most frequent p53 mutations informs patient stratification for clinical exploration. Our results provide a mechanistic basis for repurposing ATO to target p53 mutations for widely applicable yet personalized cancer therapies.
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•ATO rescues multiple p53 mutants effectively in various assays•The structural mechanism of how mutant p53 function is restored by ATO is described•Most p53 mutants are stabilized structurally but only some are transcriptionally rescued•Widely applicable, yet has individual p53 mutation-based therapeutic potential
Chen et al. show that ATO, an FDA-approved drug, robustly rescues mutant p53, uncover the underlying molecular mechanism, and report the rescue pattern among frequent p53 mutants.
Abstract
Background
Fertility awareness and menses prediction are important for improving fecundability and health management. Previous studies have used physiological parameters, such as basal body ...temperature (BBT) and heart rate (HR), to predict the fertile window and menses. However, their accuracy is far from satisfactory. Additionally, few researchers have examined irregular menstruators. Thus, we aimed to develop fertile window and menstruation prediction algorithms for both regular and irregular menstruators.
Methods
This was a prospective observational cohort study conducted at the International Peace Maternity and Child Health Hospital in Shanghai, China. Participants were recruited from August 2020 to November 2020 and followed up for at least four menstrual cycles. Participants used an ear thermometer to assess BBT and wore the Huawei Band 5 to record HR. Ovarian ultrasound and serum hormone levels were used to determine the ovulation day. Menstruation was self-reported by women. We used linear mixed models to assess changes in physiological parameters and developed probability function estimation models to predict the fertile window and menses with machine learning.
Results
We included data from 305 and 77 qualified cycles with confirmed ovulations from 89 regular menstruators and 25 irregular menstruators, respectively. For regular menstruators, BBT and HR were significantly higher during fertile phase than follicular phase and peaked in the luteal phase (all
P
< 0.001). The physiological parameters of irregular menstruators followed a similar trend. Based on BBT and HR, we developed algorithms that predicted the fertile window with an accuracy of 87.46%, sensitivity of 69.30%, specificity of 92.00%, and AUC of 0.8993 and menses with an accuracy of 89.60%, sensitivity of 70.70%, and specificity of 94.30%, and AUC of 0.7849 among regular menstruators. For irregular menstruators, the accuracy, sensitivity, specificity and AUC were 72.51%, 21.00%, 82.90%, and 0.5808 respectively, for fertile window prediction and 75.90%, 36.30%, 84.40%, and 0.6759 for menses prediction.
Conclusions
By combining BBT and HR recorded by the Huawei Band 5, our algorithms achieved relatively ideal performance for predicting the fertile window and menses among regular menstruators. For irregular menstruators, the algorithms showed potential feasibility but still need further investigation.
Trial registration
ChiCTR2000036556. Registered 24 August 2020.
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