Integrated Analysis of Pollution Characteristic and Ecotoxicological Effect Reveals the Fate of Lithium in Soil-Plant Systems: A Challenge to Global Sustainability.

Lithium, as an emerging contaminant, lacks sufficient information regarding its environmental and ecotoxicological implications within soil-plant systems. Employing maize, wheat, pea, and water spinach, we conducted a thorough investigation utilizing a multispecies, multiparameter, and multitechnique approach to assess the pollution characteristics and ecotoxicological effects of lithium. The findings suggested that lithium might persist in an amorphous state, altering surface functional groups and chemical bonds, although semiquantitative analysis was unattainable. Notably, lithium demonstrated high mobility, with a mild acid-soluble fraction accounting for 29.66-97.02% of the total, while a minor quantity of exogenous lithium tended to be a residual fraction. Plant analysis revealed that in 10-80 mg Li/kg soils lithium significantly enhanced certain growth parameters of maize and pea, and the calculated LC50 values for aerial part length across the four plant species varied from 173.58 to 315.63 mg Li/kg. Lithium accumulation in the leaves was up to 1127.61-4719.22 mg/kg, with its inorganic form accounting for 18.60-94.59%, and the cytoplasm fraction (38.24-89.70%) predominantly harbored lithium. Furthermore, the model displayed that growth stimulation might be attributed to the influence of lithium on phytohormone levels. Water spinach exhibited superior accumulation capacity and tolerance to lithium stress and was a promising candidate for phytoremediation strategies. Our findings contribute to a more comprehensive understanding of lithium's environmental behavior within soil-plant systems, particularly within the context of global initiatives toward carbon neutrality.

Recent advances in wearable flexible electronic skin: types, power supply methods, and development prospects.

In recent years, wearable e-skin has emerged as a prominent technology with a wide range of applications in healthcare, health surveillance, human-machine interface, and virtual reality. Inspired by the properties of human skin, arrayed wearable e-skin is a novel technology that offers multifunctional sensing capabilities. It can detect and quantify various stimuli, mimicking the human somatosensory system, and record a wide range of physical and physiological parameters in real time. By combining flexible electronic device units with a data acquisition system, specific functional sensors can be distributed in targeted areas to achieve high sensitivity, resolution, adjustable sensing range, and large-area expandability. This review provides a comprehensive overview of recent advances in wearable e-skin technology, including its development status, types of applications, power supply methods, and prospects for future development. The emphasis of current research is on enhancing the sensitivity and stability of sensors, improving the comfort and reliability of wearable devices, and developing intelligent data processing and application algorithms. This review aims to serve as a scientific reference for the intelligent development of wearable e-skin technology.

Highly efficient field-free switching of perpendicular yttrium iron garnet with collinear spin current.

Yttrium iron garnet, a material possessing ultralow magnetic damping and extraordinarily long magnon diffusion length, is the most widely studied magnetic insulator in spintronics and magnonics. Field-free electrical control of perpendicular yttrium iron garnet magnetization with considerable efficiency is highly desired for excellent device performance. Here, we demonstrate such an accomplishment with a collinear spin current, whose spin polarization and propagation direction are both perpendicular to the interface. Remarkably, the field-free magnetization switching is achieved not only with a heavy-metal-free material, Permalloy, but also with a higher efficiency as compared with a typical heavy metal, Pt. Combined with the direct and inverse effect measurements, we ascribe the collinear spin current to the anomalous spin Hall effect in Permalloy. Our findings provide a new insight into spin current generation in Permalloy and open an avenue in spintronic devices.

Preparation of polyphenol-structural colored silk fabrics with bright colors.

Conventional textile dyeing relies on the use of dyes and pigments, which can cause severe environmental contamination and waste a large amount of water. Structural coloring is one of the effective ways to achieve environmentally friendly coloring of textiles. In this work, three plant polyphenols with the same o-benzenetriol structure (tannic acid (TA), gallic acid (GA), and tea polyphenol (TP)) were selected as raw materials. Three plant polyphenols can quickly form nanofilms at the gas-liquid interface through a Schiff base reaction with polyethyleneimine (PEI) under mildly alkaline conditions, which were deposited to the surface of silk fabric, allowing precise control over the thickness of film by adjusting the time, resulting in various structurally colored silk fabric. This method for creating structural colors is not substrate-specific and enables the quick production of structural colors on various textile substrates. Furthermore, the structural color silk fabric based on plant polyphenol has antibacterial performance. This textile coloring method is simple, cost-effective and environmentally friendly, providing a new approach to eco-friendly textile dyeing.

LRRK2 regulates ferroptosis through the system Xc-GSH-GPX4 pathway in the neuroinflammatory mechanism of Parkinson's disease.

Parkinson's disease (PD) is the most prevalent neurodegenerative disorder. Neuroinflammation mediated by activated microglia and apoptosis of dopaminergic (DA) neurons in the midbrain are its primary pathological manifestations. Leucine-rich repeat protein kinase 2 (LRRK2) kinase has been observed to increase expression during neuroinflammation, however, the effect of LRRK2 on microglia activation remains poorly understood. In this study, we have established lipopolysaccharide (LPS) treated BV2 cells and 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) models for both in vivo and in vitro investigation. Our data in vivo reveal that LRRK2 can promote microglia activation by regulating ferroptosis and activating nuclear factor-κB. Inhibition of LRRK2 expression effectively suppressed the LPS-induced pro-inflammatory cytokines and facilitated the secretion of neuroprotective factors. Importantly, by co-overexpressing LRRK2 and glutathione peroxidase 4 (GPX4), we identified the system Xc-GSH-GPX4 pathway as a crucial component in LRRK2-mediated microglial ferroptosis and inflammatory responses. Using a microglial culture supernatant (MCS) transfer model, we found that inhibiting LRRK2 or downregulating ferroptosis in BV2 cells prevented SH-SY5Y cell apoptosis. Additionally, we observed abundant expression of LRRK2 and P-P65 in the midbrain, which was elevated in the MPTP-induced PD model, along with microglia activation. LRRK2 and P-P65 expression inhibition with PF-06447475 attenuated microglia activation in the nigrostriatal dense part of MPTP-treated mice. Based on our findings, it is evident that LRRK2 plays a critical role in promoting the neuroinflammatory response during the pathogenesis of PD by regulating the system Xc-GSH-GPX4 pathway. Taken together, our data highlights the potential research and therapeutic value of targeting LRRK2 to regulate neuroinflammatory response in PD through ferroptosis.

Exploring the biotic and abiotic drivers influencing nata de coco production by Komagataeibacter nataicola in pre-fermented coconut water.

In China and Southeast Asia, pre-fermented coconut water is commonly used for the production of nata de coco, a jelly-like fermented food that consists of bacterial cellulose (BC). The inherent natural fermentation process of coconut water introduces uncontrollable variables, which can lead to unstable yields during BC production. This study involved the collection of spontaneously pre-fermented coconut water over a five-month production cycle. The aim was to evaluate the microbiota and metabolite profile, as well as determine its impact on BC synthesis by Komagataeibacter nataicola. Significant variations in the microbial community structure and metabolite profile of pre-fermented coconut water were observed across different production months, these variations had significant effects on BC synthesis by K. nataicola. A total of 52 different bacterial genera and 32 different fungal genera were identified as potential biotic factors that can influence BC production. Additionally, several abiotic factors, including lactate (VIP = 4.92), mannitol (VIP = 4.22), ethanol (VIP = 2.67), and ascorbate (VIP = 1.61), were found to be potential driving forces affecting BC synthesis by K. nataicola. Upon further analysis, the correlation network indicated that 14 biotic factors had a significant contribution to BC production in three strains of K. nataicola. These factors included 8 bacterial genera, such as Limosilactobacillus and Lactiplantibacillus, and 6 fungal genera, such as Meyerozyma and Ogataea. The abiotic factors lactate, mannitol, and ethanol showed a positive correlation with the BC yield. This study provides significant insights into controlling the fermentation processes of pre-fermented coconut water in industrial settings.

Preparation of Natural Plant Polyphenol Catechin Film for Structural Coloration of Silk Fabrics.

Traditional textile dyeing uses chemical pigments and dyes, which consumes a large amount of water and causes serious environmental pollution. Structural color is an essential means of achieving green dyeing of textiles, and thin-film interference is one of the principles of structural coloring. In the assembly of structural color films, it is necessary to introduce dark materials to suppress light scattering and improve the brightness of the fabric. In this study, the conditions for the generation of nanofilms of catechin (CC) at the gas-liquid interface were successfully investigated. At the same time, environmentally friendly colored silk fabrics were novelly prepared using polycatechin (PCC) structural color films. In addition, it was found that various structural colors were obtained on the surface of silk fabrics by adjusting the time. Meanwhile, the color fastness of the structural colored fabrics was improved by introducing polyvinylpyrrolidone (PVP) to form a strong hydrogen bond between the fabric and catechin. PCC film is uniform and smooth, with a special double-layer structure, and can be attached to the surface of silk fabrics, giving the fabrics special structural colors. Through the thin-film interference formed between the visible light and the PCC film, the silk fabrics obtain bright, controllable, and uniform structural colors. This method is easy to operate and provides a new way of thinking for environmental-protection-oriented coloring of fabrics.

Combined exposure to lead and microplastics increased risk of glucose metabolism in mice via the Nrf2/NF-κB pathway.

The purpose of this study was to explore the effects of combined lead (Pb) and two types of microplastic (MP) (polyvinyl chloride [PVC] and polyethylene [PE]) exposure on glucose metabolism and investigate the role of the nuclear factor erythroid 2-related factor 2 (Nrf2)/nuclear factor-kappa B (NF-κB) signaling pathway in mediating these effects in mice. Adult C57BL/6J mice were randomly divided into four groups: control, Pb (100 mg/L), MPs (containing 10 mg/L PE and PVC), and Pb + MPs, each of which was treated with drinking water. Treatments were conducted for 6 weeks. Co-exposure to Pb + MPs exhibited increase glycosylated serum protein levels, insulin resistance, and damaged glucose tolerance compared with the control mice. Additionally, treatment with Pb + MPs caused more severe damage to hepatocytes than when exposed to them alone concomitantly, exposed to Pb + MPs exhibited improved the levels of interleukin-6, tumor necrosis factor-alpha, and malondialdehyde, but reduced superoxide dismutase, glutathione peroxidase, and catalase assay in livers. Furthermore, they increase the Kelch-like ECH-associated protein 1 (Keap1) and phosphorylated p-NF-κB protein levels but reduced the protein levels of heme oxygenase-1 and Nrf2, as well as increased Keap1 mRNA and Nrf2 mRNA. Co-exposure to Pb + MP impacts glucose metabolism via the Nrf2 /NF-κB pathway.

Metabolomic analysis reveals the toxicity mechanisms of bisphenol A on the Microcystis aeruginosa under different phosphorus levels.

Harmful cyanobacterial blooms have been a global environmental problem. Discharge of anthropogenic pollutants and excess nutrient import into the freshwater bodies may be the biggest drivers of bloom. Bisphenol A (BPA), a typical endocrine-disrupting compound, is frequently detected in different natural waters, which was a threat to the balance of aquatic ecosystem. Yet mechanistic understanding of the bloom and microcystin generation under combined pollution conditions is still a mystery. Herein, the cellular and metabolomic responses to BPA exposure and phosphorus (P) levels in Microcystis aeruginosa were investigated throughout its growth period. The results showed that the stress response of M. aeruginosa to BPA was characterized by a decrease in growth density, an increase in P utilization, an increase in ATPase activity, a disruption of the photosynthetic system, and an increase in the production and release of microcystins (MCs). However, these effects are highly dependent on the growth stage of the cyanobacterial cell and the magnitude of the added P concentration. In addition, exposure to a high concentration (10 µM) of BPA significantly stimulated the production of 20.7% more and the release of 29.2% more MCs from M. aeruginosa cells at a low P level. The responses of reactive oxygen species (ROS), superoxide dismutase (SOD) and malondialdehyde (MDA) suggested that exposure to BPA exposure at a low P level can lead to oxidative stress in M. aeruginosa. In addition, the differentially expressed 63 metabolites showed that cell growth, energy generation and photosynthesis were mainly regulated by the metabolic network of 3-phosphoglyceric acid (3-PGA), D-glucose 6-phosphate, UDP-α-D-galactose and UDP-N-acetyl-D-galactosamine (UDP-GalNAc) metabolism. Amino acids and lipid metabolism collectively mediated MCs production and release. These findings will provide important references for the control of harmful cyanobacterial blooms under combined pollution.

Chain mediations of perceived social support and emotional regulation efficacy between role stress and compassion fatigue: insights from the COVID-19 pandemic.

Background: Nurses at the frontline faced high risks of the COVID-19 infection, undertook heavy workloads of patient care, and experienced tremendous stress that often led to compassion fatigue. Aim: This study was to explore the role of positive psychosocial resources (i.e., perceived social support and emotional regulation efficacy) in the relationship between role stress and compassion fatigue. Methods: A cross-sectional design was conducted in Hubei Province, China between May and September 2021. The Role Stress Questionnaire, the Perceived Social Support Scale, the Emotional Regulation Efficacy Scale, and the Professional Quality of Life Scale were used to measure key variables of interest. Nurse socio-demographic data were also collected. Structural equation modeling was used to explore the relationships, including potential mediating effect, among role stress, perceived social support, emotional regulation efficacy, and compassion fatigue. Results: A total of 542 nurses participated in this investigation, and 500 were eventually enrolled in the analysis. The incidence of compassion fatigue among nurses was 94.2%, including 65.8% of nurses reporting at least moderate compassion fatigue. Univariate analysis showed that educational level, marital status, hospital rank, sleep time were the factors affecting compassion fatigue of the nurses. The structural equation modeling revealed that: Role stress had a direct positive effect on compassion fatigue; Perceived social support and emotional regulation efficacy partially mediated the link between role stress and compassion fatigue respectively; And there was a chain mediating role of perceived social support and emotional regulation efficacy between role stress and compassion fatigue. Conclusion: The incidence of compassion fatigue was high during the COVID-19 pandemic among bedside nurses in China. Improving social support and enhancing the efficacy of emotion regulation may help alleviate compassion fatigue directly and/or via buffering the impact of role stress.

Effect and mechanism of microplastics exposure against microalgae: Photosynthesis and oxidative stress.

The occurrence of microplastics (MPs) within aquatic ecosystems attracts a major environmental concern. It was demonstrated MPs could cause various ecotoxicological effects on microalgae. However, existing data on the effects of MPs on microalgae showed great variability among studies. Here, we performed a meta-analysis of the latest studies on the effects of MPs on photosynthesis and oxidative stress in microalgae. A total of 835 biological endpoints were investigated from 55 studies extracted, and 37 % of them were significantly affected by MPs. In this study, the impact of MPs against microalgae was concentration-dependent and size-dependent, and microalgae were more susceptible to MPs stress in freshwater than marine. Additionally, we summarized the biological functions of microalgae that are primarily affected by MPs. Under MPs exposure, the content of chlorophyll a (Chl-a) was reduced and electron transfer in the photosynthetic system was hindered, causing electron accumulation and oxidative stress damage, which may also affect biological processes such as energy production, carbon fixation, lipid metabolism, and nucleic acid metabolism. Finally, our findings provide important insights into the effects of MPs stress on photosynthesis and oxidative stress in microalga and enhance the current understanding of the potential risk of MPs pollution on aquatic organisms.

Ecotoxicological effects of soil lithium on earthworm Eisenia fetida: Lethality, bioaccumulation, biomarker responses, and histopathological changes.

Lithium is an emerging environmental contaminant in the current low-carbon economy, but little is known about its influences on soil invertebrates. In this work, earthworm Eisenia fetida was exposed to soils treated with different levels of lithium for 7 d, and multiple ecotoxicological parameters were evaluated. The results showed that mortality was dose-dependent and lithium's median lethal content (LC50) to earthworm was respectively 865.08, 361.01, 139.36, and 94.95 mg/kg after 1 d, 2 d, 4 d, and 7 d exposure. The bioaccumulation factor based on measured exogenous lithium content (BFexog) respectively reached 0.79, 1.01, 1.57, and 1.27 with the increasing lithium levels, suggesting that lithium accumulation was averagely 1.16-fold to the exogenous content, and 74.42%∼81.19%, 14.54%∼18.23%, and 2.26%∼8.02% of the lithium in exposed earthworms were respectively retained in the cytosol, debris, and granule. Then, lithium stress stimulated the activity of superoxide dismutase, peroxidase, catalase, acetylcholinesterase, and glutathione S-transferase as well as the content of 8-hydroxy-2-deoxyguanosine and metallothionein, indicating the generation of oxidative damage, while the content of reactive oxygen species and malondialdehyde decreased. Finally, lithium introduced histopathological changes, including the degenerated seminal vesicle and muscle hyperplasia, as well as high or extreme nuclear DNA damage. This study confirmed the obvious bioaccumulation and toxic effects caused by soil lithium via ecotoxicological data, providing new theoretical insights into understanding the ecological risks of lithium to soil invertebrates.

Application of machine learning algorithm in prediction of lymph node metastasis in patients with intermediate and high-risk prostate cancer.

PURPOSE: This study aims to establish the best prediction model of lymph node metastasis (LNM) in patients with intermediate- and high-risk prostate cancer (PCa) through machine learning (ML), and provide the guideline of accurate clinical diagnosis and precise treatment for clinicals. METHODS: A total of 24,470 patients with intermediate- and high-risk PCa were included in this study. Multivariate logistic regression model was used to screen the independent risk factors of LNM. At the same time, six algorithms, namely random forest (RF), naive Bayesian classifier (NBC), xgboost (XGB), gradient boosting machine (GBM), logistic regression (LR) and decision tree (DT) are used to establish risk prediction models. Based on the best prediction performance of ML algorithm, a prediction model is established, and the performance of the model is evaluated from three aspects: area under curve (AUC), sensitivity and specificity. RESULTS: In multivariate logistic regression analysis, T stage, PSA, Gleason score and bone metastasis were independent predictors of LNM in patients with intermediate- and high-risk PCa. By comprehensively comparing the prediction model performance of training set and test set, GBM model has the best prediction performance (F1 score = 0.838, AUROC = 0.804). Finally, we developed a preliminary calculator model that can quickly and accurately calculate the regional LNM in patients with intermediate- and high-risk PCa. CONCLUSION: T stage, PSA, Gleason and bone metastasis were independent risk factors for predicting LNM in patients with intermediate- and high-risk PCa. The prediction model established in this study performs well; however, the GBM model is the best one.

Toxic effects of three perfluorinated or polyfluorinated compounds (PFCs) on two strains of freshwater algae: Implications for ecological risk assessments.

Perfluorinated or polyfluorinated compounds (PFCs) continue entering to the environmental as individuals or mixtures, but their toxicological information remains largely unknown. Here, we investigated the toxic effects and ecological risks of Perfluorooctane sulfonic acid (PFOS) and its substitutes on prokaryotes (Chlorella vulgaris) and eukaryotes (Microcystis aeruginosa). Based on the calculated EC50 values, the results showed that PFOS was significantly more toxic to both algae than its alternatives including Perfluorobutane sulfonic acid (PFBS) and 6:2 Fluoromodulated sulfonates (6:2 FTS), and the PFOS-PFBS mixture was more toxic to both algae than the other two PFC mixtures. The action mode of binary PFC mixtures on Chlorella vulgaris was mainly shown as antagonistic and on Microcystis aeruginosa as synergistic, by using Combination index (CI) model coupled with Monte Carlo simulation. The mean risk quotient (RQ) value of three individual PFCs and their mixtures were all below the threshold of 10-1, but the risk of those binary mixtures were higher than that of PFCs individually because of their synergistic effect. Our findings contribute to enhance the understanding of the toxicological information and ecological risks of emerging PFCs and provide a scientific basis for their pollution control.

The greenhouse effect of antibiotics: The influence pathways of antibiotics on methane release from freshwater sediment.

The impact of antibiotics on methane (CH4) release from sediment involves both CH4 production and consumption processes. However, most relevant studies lack a discussion of the pathways by which antibiotics affect CH4 release and do not highlight the role played by the sediment chemical environment in this influence mechanism. Here, we collected field surface sediments and grouped them with various antibiotic combination concentration gradients (50, 100, 500, 1000 ng g-1) under a 35-day indoor anaerobic constant temperature incubation. We found that the positive effect of antibiotics on sediment CH4 release potential appeared later than the positive effect on sediment CH4 release flux. Still, the positive effect of high-concentration antibiotics (500, 1000 ng g-1) occurred with a lag in both processes. Also, the positive effect of high-concentration antibiotics was significantly higher than low-concentration antibiotics (50, 100 ng g-1) in the later incubation period (p < 0.05). We performed a multi-collinearity assessment of sediment biochemical indicators, followed by a generalized linear model with negative binomial regression (GLM-NB) to obtain essential variables. In particular, we conducted the interaction analysis on CH4 release potential and flux regression for the influence pathways construction. The partial least-squares path modeling (PLS-PM) demonstrated that the positive effect of antibiotics on CH4 release (Total effect = 0.2579) was primarily attributed to their effect on the sediment chemical environment (Direct effect = 0.5107). These findings greatly expand our understanding of the antibiotic greenhouse effect in freshwater sediment. Further studies should more carefully consider the effects of antibiotics on the sediment chemical environment, and continuously improve the mechanistic studies of antibiotics on sediment CH4 release.

The Human Activity Radar Challenge: benchmarking based on the 'Radar signatures of human activities' dataset from Glasgow University.

Radar is an extremely valuable sensing technology for detecting moving targets and measuring their range, velocity, and angular positions. When people are monitored at home, radar is more likely to be accepted by end-users, as they already use WiFi, is perceived as privacy-preserving compared to cameras, and does not require user compliance as wearable sensors do. Furthermore, it is not affected by lighting condi-tions nor requires artificial lights that could cause discomfort in the home environment. So, radar-based human activities classification in the context of assisted living can empower an aging society to live at home independently longer. However, challenges remain as to the formulation of the most effective algorithms for radar-based human activities classification and their validation. To promote the exploration and cross-evaluation of different algorithms, our dataset released in 2019 was used to benchmark various classification approaches. The challenge was open from February 2020 to December 2020. A total of 23 organizations worldwide, forming 12 teams from academia and industry, participated in the inaugural Radar Challenge, and submitted 188 valid entries to the challenge. This paper presents an overview and evaluation of the approaches used for all primary contributions in this inaugural challenge. The proposed algorithms are summarized, and the main parameters affecting their performances are analyzed.

Source Apportionment and Health Risk Assessment of Heavy Metals in Soils of Old Industrial Areas-A Case Study of Shanghai, China.

Heavy metals in the soil of industrial areas pose severe health risks to humans after land-use properties are transformed into residential land. The public exposure time and frequency will soar significantly under residential land. However, much uncertainty still exists about the relationship between soil heavy metal pollution and-human health risks in an old industrial zone in Shanghai, China. Principal component analysis-(PCA) was used to explore the main sources of these heavy metals. Kriging interpolation was u-sed to identify their spatial distribution and high-risk areas, and the Human Health risk model was used to measure health risk. The results illustrate that the pollution levels of Cd, Hg, and Pb in industrial land are more serious than those in irrigation cropland. Meanwhile, the results of PCA showed that there were two main pollution sources under irrigated cropland, a natural source and a traffic source, accounting for 44.1% and 31.0%, respectively, and there were three main pollution sources under industrial land, with natural sources accounting for 28.5%, traffic sources accounting for 25.7%, and industrial sources accounting for 13.1%. In addition, the health risk assessment results indicated that the priority control pollutants of non-carcinogenic risk and carcinogenic risk were Zn and Cr, respectively. The high-risk area was mainly located in the middle of the study area. These results indicate that eliminating heavy metal pollution in the soil of the industrial area is so important to decrease health risks. The results of this study provide theoretical contributions to early warning of health risks related to heavy metal pollution in industrial area soil and serve as a practical reference for speeding up the formulation of industrial land pollution management policies.