Lakes act as one of the reservoirs and dispersal routes of antibiotic resistance genes (ARGs) and pathogenic resistant bacteria in aquatic environments. Previous studies reported the occurrence and distribution of ARGs in lakes worldwide; however, few investigated the biogeography and diversity patterns of antibiotic resistome in the environment. To fill this gap, a large-scale data set of sediment metagenomes was collected from globally distributed lakes and characterized comprehensively using metagenomic assembly-based analysis, aiming to shed light on the biogeography and diversity patterns of ARGs in lake ecosystems from a global perspective. Our analyses showed that abundant and diverse ARGs were found in the global lake sediments, including a set of emerging ARGs such as mcr-type and carbapenem-resistant Enterobacteriaceae related genes. Most of the identified ARGs were generally associated with the commonly used antibiotics, suggesting the role of increasing antibiotic consumptions on the resistome prevalence. Spatially, the composition and diversity of ARGs varied across geographical distances and exhibited a scale-dependent distance-decay relationship. Notably, the composition of ARGs was largely shaped by bacterial community structure, and their diversities were co-governed by stochastic process (∼48%) and deterministic process (∼52%). Findings provide a valuable insight to better understand ecological mechanisms of ARGs in lake ecosystems and have important implication for the prevention and control of resistome risk.
Anodes based on silicon/carbon composites promise their commercial prospects for next-generation lithium ion batteries owing to their merits of high specific capacity, enhanced ionic and electronic conductivity, and excellent compatibility. Herein, a series of carbonaceous framework/Si composites are designed and prepared by rational waste utilization. N, P codoped foam-like porous carbon/Si composites (FPC@Si) and N, P codoped carbon coated Si composites (NPC@Si) are fabricated by utilizing expired milk powder as a carbon source with facile treatment methods. The results indicate that the porous carbon skeleton and carbon shell can improve the conductivity of Si and stabilize the solid electrolyte interfaces to avoid direct contact between active material and electrolyte. Moreover, the influence of drastic volume expansion of Si on the anode can be efficiently alleviated during charge/discharge processes. Therefore, the Si/C composite electrodes present excellent long-term cycling stability and rate capability. The electrochemical performance shows that the reversible capacity of FPC@Si and NPC@Si can be respectively maintained at 587.3 and 731.2 mAh g-1 after 1000 charge/discharge cycles under 400 mA g-1. Most significantly, the optimized Si/C composite electrodes exhibit outstanding performance in the full cell tests, promising them great potential for practical applications. This study not only provides a valuable guidance for recycling of waste resources, but also supports a rational design strategy of advanced composite materials for high-performance energy storage devices.
Multivariate time series data (Mv-TSD) portray the evolving processes of the system(s) under examination in a multi-view manner. Factorization methods are salient for Mv-TSD analysis with the potentials of structural feature construction. However, research challenges remain in the derivation of factors due to scattered data distribution of Mv-TSD and intensive interferences/outliers embedded in the source data. The proposed Enhanced Bayesian Factorization approach (Enhanced-BF) addresses the challenges in three phases: (1) variant scale partitioning applies to Mv-TSD according to degree of amplitude and obtains the blocks of variant scales; (2) hierarchical Bayesian model for tensor factorization automatically derives the factors of each block with interferences suppressed; (3) Bayesian unification model merges those block factors to construct the final structural features. Enhanced-BF has been evaluated using a case study of brain data engineering with multivariate electroencephalogram (EEG). Experimental results indicate that the proposed method manifests robustness to the interferences and outperforms the counterparts in terms of operation efficiency and error when factorizing EEG tensor. Besides, Enhanced-BF excels in factorization-based analysis of ongoing autism spectrum disorder (ASD) EEG: 3 times speed-up in factorization and 87.35% accuracy in ASD discrimination. The latent factors can distinctly interpret the typical EEG characteristics of ASD subjects.
Exploring highly efficient electromagnetic interference (EMI) shielding filler is urgently desired for next-generation wireless communication and integrated electronics. In this regard, a series of heterogeneous MoO2/N-doped carbon (MoO2/NC) nanorods with tunable conductivity have been successfully synthesized by regulating the pyrolysis temperature within 600, 700 and 800 °C. Profiting from the rational design of heterointerface and low-dimensional structure, the MoO2/NC powder achieves stronger EMI shielding capacity with the incremental temperature. It is found that the MoO2/NC-800 nanorods exhibit the optimal average EMI shielding effectiveness (SE) of 57.2 dB at a thickness of ∼0.3 mm in the X band. Meanwhile, the corresponding shielding mechanisms of MoO2/NC nanorods are also elaborately explained. More interestingly, the increase of sintering temperature makes an obvious effect on absorption loss but has little influence on reflection loss, demonstrating that adjusting the pyrolysis temperature is an effective strategy to strengthen the electromagnetic energy dissipation.
Three-dimensional (3D) deformable image registration is a fundamental technique in medical image analysis tasks. Although it has been extensively investigated, current deep-learning-based registration models may face the challenges posed by deformations with various degrees of complexity. This paper proposes an adaptive multi-level registration network (AMNet) to retain the continuity of the deformation field and to achieve high-performance registration for 3D brain MR images. First, we design a lightweight registration network with an adaptive growth strategy to learn deformation field from multi-level wavelet sub-bands, which facilitates both global and local optimization and achieves registration with high performance. Second, our AMNet is designed for image-wise registration, which adapts the local importance of a region in accordance with the complexity degrees of its deformation, and thereafter improves the registration efficiency and maintains the continuity of the deformation field. Experimental results from five publicly-available brain MR datasets and a synthetic brain MR dataset show that our method achieves superior performance against state-of-the-art medical image registration approaches.
Leakage of light non-aqueous phase liquid (LNAPL) into soil can cause serious environmental issues. In this study, a two-dimensional device with adjustable dip angles was designed to investigate the migration and redistribution of LNAPL in natural inclined stratified soil media by the light transmission visualization (LTV) technology. The captured experimental images were processed to obtain the diesel distribution based on gray value which could represent the LNAPL saturation distribution. LNAPL may not be able to penetrate through the fine-coarse interface due to the capillary barrier effects. In this case, the vertical and horizontal migration distances (V and H), contaminated area (S), as well as deviation angle (γ) of centroid increased with the dip angle. Increasing the leakage amount to more than 30 mL would result in LNAPL breakthrough at the 10°-inclined interface, leading to much larger V, H, S, and γ than those at 10 mL, while 20-mL LNAPL failed to break through. In the latter case, a lower leakage rate than 10 mL/min would cause larger H and γ but similar V or S in the long term. This study could enrich the understanding of LNAPL contamination in vadose zone, providing reference for the prediction and treatment in realistic inclined contaminated sites.
Background: To investigate clinical manifestations and factors of perioperative brain injury (PBI) after surgical repair of coarctation of the aorta (CoA) combined with other heart malformations under cardiopulmonary bypass (CPB) in children under two years. Methods: The clinical data of 100 children undergoing CoA repair were retrospectively reviewed between January 2010 and September 2021. Univariate and multivariate analyses were performed to identify factors of PBI development. Hierarchical and K-means cluster analyses were conducted to evaluate the association between hemodynamic instability and PBI. Results: Eight children developed postoperative complications, and all of them had a favorable neurological outcome one year after surgery. Univariate analysis revealed eight risk factors associated with PBI. Multivariate analysis indicated operation duration (P = 0.04, odds ratio [OR], 2.93; 95% confidence interval [CI], 1.04 to 8.28) and pulse pressure (PP) minimum (P = 0.01; OR, 0.22; 95% CI, 0.06 to 0.76) were independently associated with PBI. The following three parameters emerged for cluster analysis: PP minimum, mean arterial pressure (MAP) dispersion, and systemic vascular resistance (SVR) average. Using cluster analysis, PBI mainly occurred in subgroups 1 (12%, three of 26) and 2 (10%, five of 48). The mean value of PP and MAP in subgroup 1 was significantly higher than in subgroup 2. The mean SVR in subgroup 1 was the highest. The lowest PP minimum, MAP, and SVR were observed in subgroup 2. Conclusion: Lower PP minimum and longer operation duration were independent risk factors for developing PBI in children under two years during CoA repair. Unstable hemodynamics should be avoided during CPB.
Esophageal cancer is a malignant tumor with two-thirds of patients having a local recurrence or distant metastasis. To date, diagnostic biomarkers with high sensitivity and specificity are lacking. Extracellular vesicles (EVs) have shown their potential values as disease biomarkers as they carry specific proteins and RNAs derived from cancer cells. In this study, we investigate ESCC precision diagnostics from the insights of circulating EVs, and integrate the ultrafast EV isolation approach (EXODUS) and ELISA for fast detection and screening of ESCC patients. First, we isolate and characterize the high-purity plasma EVs with EXODUS and identify 401 proteins and 372 proteins from ESCC patient and healthy individuals, respectively. Further looking into the differentially expressed proteins (DEPs) of ESCC patients and enriched KEGG pathways, we discover EV-CD14 as a potential diagnostic biomarker for ESCC, which has been further validated as a significantly differentially expressed protein by Western Blot and immunogold labelling TEM. For fast screening and detection of ESCC towards clinical applications, we apply ELISA method to diagnose ESCC from 60 clinical samples based on circulating EV-CD14, which shows a high AUC value up to 96.0% for detection of ESCC in a test set (30 samples), and displays a high accuracy rate up to 90% for prediction of ESCC in a screening test (30 samples). Our results suggest that the circulating EV-CD14 may highly be related to the initiation and progression of ESCC, providing a novel method for the diagnosis and prognosis of ESCC towards clinical translations.
This study aimed to systematically investigate the relationship between children exposure possibility, metal concentration, metal bioaccessibility and soil particle size. fifty Children aged 3-8 years were recruited for the collection of hand-adhered soil, environmental soil, and blood samples. The mass distribution of hand-adhered soil with particle size were analyzed. Based on it, environmental soil samples were divided into five fractions to evaluate the effect of soil particle size on the total contents and bioaccessibilities of toxic metals. Then, a refined soil oral exposure model based on the particle size distribution of hand-adhered soil was established, and the estimation was compared with the typical traditional method. We found that finer particles were preferentially adhered to hand. The highest metal concentrations and bioaccessibilities occurred in the finest fraction, with values decreasing with increasing particle size. The exposure levels using the refined model were 2.0-3.4 times higher than those with the traditional method. In addition, Pb exposure level calculated using the refined model exhibited stronger and more significant correlation with blood Pb than those of the traditional soil. The construction of a refined exposure scenario based on hand-adhered soil could more exactly reflect the real exposure level and the difference among individuals.
Urbanization is transforming ecosystems at a global scale and at an increasing rate, and its profound consequences for wildlife have been well documented. Understanding how animals thrive in the urban environment and how this environment affects (co-)evolutionary processes remains an important challenge. Urban environments can provide resources such as food or nest sites (e.g., cavities) and also reduce exposure to predators. For some species, urban environments may also affect susceptibility to brood parasitism, but this has never been tested experimentally. Here, we use a combination of field observations and experimental manipulations to show that Daurian redstarts, Phoenicurus auroreus, a common host of the common cuckoo, Cuculus canorus, nest in proximity to humans to avoid brood parasitism. First, redstarts were more likely to be parasitized with increasing distance to the nearest building. Second, redstarts adjusted their nesting location in response to a seasonally predictable change in the risk of brood parasitism. Third, experimentally simulating the presence of cuckoos during a period when they are naturally absent increased the likelihood that redstarts nested indoors or closer to human settlements. These findings suggest that redstarts actively choose to place their nest in the vicinity of a human residence as a defense against cuckoos. Our study exemplifies how animals take advantage of the urban environment by using it as a novel line of defense against detrimental interspecific interactions.
One landmark application of evolutionary game theory is the study of social dilemmas. This literature explores why people cooperate even when there are strong incentives to defect. Much of this literature, however, assumes that interactions are symmetric. Individuals are assumed to have the same strategic options and the same potential pay-offs. Yet many interesting questions arise once individuals are allowed to differ. Here, we study asymmetry in simple coordination games. In our set-up, human participants need to decide how much of their endowment to contribute to a public good. If a group’s collective contribution reaches a pre-defined threshold, all group members receive a reward. To account for possible asymmetries, individuals either differ in their endowments or their productivities. According to a theoretical equilibrium analysis, such games tend to have many possible solutions. In equilibrium, group members may contribute the same amount, different amounts or nothing at all. According to our behavioural experiment, however, humans favour the equilibrium in which everyone contributes the same proportion of their endowment. We use these experimental results to highlight the non-trivial effects of inequality on cooperation, and we discuss to which extent models of evolutionary game theory can account for these effects. This article is part of the theme issue ‘Half a century of evolutionary games: a synthesis of theory, application and future directions’.
The heterogeneity of extracellular matrix (ECM) topology, stiffness and architecture is a key factor modulating cellular behavior and osteogenesis. However, the effects of heterogeneous ECM electric potential at the micro- and nanoscale on cellular behavior and osteogenesis remain to be elucidated. Here, the heterogeneous distributions of surface electrical potential is established by incorporating ferroelectric BaTiO3 nanofibers (BTNF) into poly(vinylidene fluoridetrifluoroethylene) (P(VDF-TrFE)) matrix based on phase-field simulation and first-principles simulation. By optimizing the aspect ratios of BTNF fillers, the anisotropic distribution of surface potential on BTNF/P(VDF-TrFE) nanocomposite membranes can be achieved by strong spontaneous electric polarization of BTNF fillers. Our results indicate that heterogeneous surface potential distribution leads to a meshwork pattern of fibronectin (FN) aggregation, which increased FN-III7-10 (FN fragment) focal flexibility and anchor points as predicted by molecular dynamics simulation. Furthermore, integrin clustering, focal adhesion formation, cell spreading and adhesion were enhanced sequentially. Increased traction of actin fibers amplifies mechanotransduction by promoting nuclear translocation of YAP/Runx2, which enhances osteogenesis in vitro and bone regeneration in vivo. Our work thus provides fundamental insights into the biological effects of surface potential heterogeneity at the micro- and nanoscale on osteogenesis, and also develops a new strategy to optimize the performance of electroactive biomaterials for tissue regenerative therapies. This article is protected by copyright. All rights reserved.
Incorporating seasonality into livestock spatial distribution is of great significance for studying the complex system interaction between climate, vegetation, water, and herder activities, associated with livestock. the Qinghai-tibet Plateau (QtP) has the world’s most elevated pastoral area and is a hot spot for global environmental change. This study provides the spatial distribution of cattle, sheep, and livestock grazing on the warm-season and cold-season pastures at a 15 arc-second spatial resolution on the QTP. Warm/cold-season pastures were delineated by identifying the key elements that affect the seasonal distribution of grazing and combining the random forest classification model, and the average area under the receiver operating characteristic curve of the model is 0.98. Spatial disaggregation weights were derived using the prediction from a random forest model that linked county-level census livestock numbers to topography, climate, vegetation, and socioeconomic predictors. The coefficients of determination of external cross-scale validations between dasymetric mapping results and township census data range from 0.52 to 0.70. The data could provide important information for further modeling of human-environment interaction under climate change for this region
The deposition of β-amyloid (Aβ) in the brain is a pathologic hallmark of Alzheimer's disease (AD), appearing years before the onset of symptoms, and its detection is incorporated into clinical diagnosis. Here, we have discovered and developed a class of diaryl-azine derivatives for detecting Aβ plaques in the AD brain using PET imaging. After a set of comprehensive preclinical assessments, we screened out a promising Aβ-PET tracer, [18F]92, with a high binding affinity to the Aβ aggregates, significant binding ability with the AD brain sections, and optimal brain pharmacokinetic properties in rodents and non-human primates. The first-in-human PET study declared that [18F]92 displayed low white matter uptake and could bind to Aβ pathology for distinguishing AD from healthy control subjects. All these results support that [18F]92 might become a promising PET tracer for visualizing Aβ pathology in AD patients.
Life satisfaction (LS) is a core dimension of subjective well-being and is linked to many life outcomes in adolescents. Among other indicators of optimal functioning in youth, LS has been understudied; not until the last decade did research on adolescent LS show a resurgence. Parent–child attachment relationships are considered a vital factor contributing to adolescent LS. However, extant studies are predominantly cross-sectional, and few studies have examined its underlying mechanisms. This study is designed to bridge those gaps. Drawing on ecological system theories, it examines the association between parent–child attachment relationships and adolescent LS. It also investigates resilience as a mediator and teacher-student relationships (TSR) as a moderator using a three-wave longitudinal design, with a 6-month interval between each wave. Participants were 815 Chinese adolescents (53.9% boys, Mage = 11.53 years) and one of their parents (65.28% mothers). Adolescents reported on TSR at T1, resilience at T2, and LS at T1 and T3, whereas their parents reported on parent–child attachment relationships at T1. Overall, results of the moderated mediation model indicate that after controlling for T1 LS and covariates, T1 parent–child attachment relationships predicted T3 LS via T2 resilience only for adolescents with a high-quality TSR but not for those with a low or medium quality of TSR. This research contributes to the literature on the synergistic interplay between interpersonal and intrapersonal resources in predicting resilience and LS in adolescents. The findings have implications for well-being interventions for adolescents with diverse qualities of connections with teachers
How infectious diseases shape individual minds and behaviors has been of interest to researchers. We conducted four studies to examine whether the threat perception of the COVID-19 pandemic was positively related to pro-environmentalism. Study 1 (N = 1,508) showed that individuals’ threat perception of the pandemic was correlated with their pro-environmental behaviors. Study 2 (N = 241) clarified the causality by manipulating threat perception and found that individuals with high (vs. low) threat perception reported higher pro-environmental willingness. Study 3 (N = 406) revealed that awe for nature mediated this relationship. Study 4 (N = 405) replicated Study 3 more than two years after the outbreak and demonstrated the findings were robust regardless of decreases in infection fear. These findings suggest that the COVID-19 pandemic provides individuals with an opportunity to reconsider the way they treat nature.
Agriculture is responsible for about one third of global greenhouse gas emissions and it is the primary driver of habitat destruction. A paradigm shift embracing changes in lifestyles, agricultural practices, and policies is required to realize a sustainable transition in the agri-food sector.
Lithium’s (Li) ubiquitous distribution in the environment is a rising concern due to its rapid proliferation in the modern electronic industry. Li enigmatic entry into the terrestrial food chain raises many questions and uncertainties that may pose a grave threat to living biota. We examined the leverage existing published articles regarding advances in global Li resources, interplay with plants, and possible involvement with living organisms, especially humans and animals. Globally, Li concentration (<10–300 mg kg−1) is detected in agricultural soil, and their pollutant levels vary with space and time. High mobility of Li results in higher accumulation in plants, but the clear mechanisms and specific functions remain unknown. Our assessment reveals the causal relationship between Li level and biota health. For example, lower Li intake (<0.6 mM in serum) leads to mental disorders, while higher intake (>1.5 mM in serum) induces thyroid, stomach, kidney, and reproductive system dysfunctions in humans and animals. However, there is a serious knowledge gap regarding Li regulatory standards in environmental compartments, and mechanistic approaches to unveil its consequences are needed. Furthermore, aggressive efforts are required to define optimum levels of Li for the normal functioning of animals, plants, and humans. This review is designed to revitalize the current status of Li research and identify the key knowledge gaps to fight back against the mountainous challenges of Li during the recent digital revolution. Additionally, we propose pathways to overcome Li problems and develop a strategy for effective, safe, and acceptable applications.
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