Exposure to 6-PPD quinone causes ferroptosis activation associated with induction of reproductive toxicity in Caenorhabditis elegans.

Exposure to N-(1,3-dimethylbutyl)-N'-phenyl-p-phenylenediamine quinone (6-PPDQ) caused toxicity on Caenorhabditis elegans, including reproductive toxicity. However, the underlying mechanisms for this induced reproductive toxicity by 6-PPDQ remain largely unclear. We examined possible association of ferroptosis activation with reproductive toxicity of 6-PPDQ. In 1-100 µg/L 6-PPDQ exposed nematodes, Fe2+ content was increased, which was accompanied with enhanced lipid peroxidation, increased malonydialdehyde (MDA) content, and decreased L-glutathione (GSH) content. Exposure to 1-100 µg/L 6-PPDQ decreased expressions of ftn-1 encoding ferritin, ads-1 encoding AGPS, and gpx-6 encoding GPX4 and increased expression of bli-3 encoding dual oxidase. After 6-PPDQ exposure, RNAi of ftn-1 decreased ads-1 and gpx-6 expressions and increased bli-3 expression. RNAi of ftn-1, ads-1, and gpx-6 strengthened alterations in ferroptosis related indicators, and RNAi of bli-3 suppressed changes of ferroptosis related indicators in 6-PPDQ exposed nematodes. Meanwhile, RNAi of ftn-1, ads-1, and gpx-6 induced susceptibility, and RNAi of bli-3 caused resistance to 6-PPDQ reproductive toxicity. Moreover, expressions of DNA damage checkpoint genes (clk-2, mrt-2, and hus-1) could be increased by RNAi of ftn-1, ads-1, and gpx-6 in 6-PPDQ exposed nematodes. Therefore, our results demonstrated activation of ferroptosis in nematodes exposed to 6-PPDQ at environmentally relevant concentrations, and this ferroptosis activation was related to reproductive toxicity of 6-PPDQ.

Optimization of the Thermally Conductive Low-k Polymer Dielectrics Based on Multisource Free-Volume Effects.

Polymers/polymer matrix composites possessing low dielectric constants (low-k polymer dielectrics) contribute to the advance of electronics, for instance, microprocessor chips, mobile phone antennas, and data communication terminals. However, the intrinsic long-chain structural characteristic results in poor thermal conductivities, which draw heat accumulation and undermine the outstanding low-k performance of polymers. Herein, multisource free-volume effects that combine two novel kinds of extra free volume with the known in-cage free volume of polyhedral oligomeric silsesquioxanes (POSSs) are discussed to reduce the capacity for dielectric constant reduction. The multisource free-volume effects of POSSs are associated with the thermal conductive network formed by the hexagonal boron nitride (BN) in the polymer matrix. The results show a decent balance between low-k performance (dielectric constant is 2.08 at 1 MHz and 1.98 at 10 GHz) and thermal conductivity (0.555 W m-1 K-1, 4.91 times the matrix). The results provide a new idea to maximize the free-volume effects of POSSs to optimize dielectric properties together with other desired performances for the dielectrics.

Polystyrene nanoparticles strengthen high glucose toxicity associated with alteration in insulin signaling pathway in C. elegans.

Using Caenorhabditis elegans as animal model, we investigated the effect of exposure to polystyrene nanoparticles (PS-NPs) in the range of µg/L on high glucose toxicity induction. With lifespan and locomotion behavior as endpoints, we observed that PS-NP (10 and 100 µg/L) enhanced toxicity in 50 mM glucose treated animals. In insulin signaling pathway, expressions of genes encoding insulin receptor (daf-2), kinases (age-1 and akt-1/2), and insulin peptides (ins-9, ins-6, and daf-28) were increased, and expressions of daf-16 and its target of sod-3 were decreased in high glucose treated nematodes followed by PS-NP exposure. Toxicity enhancement in high glucose treated nematodes by PS-NP exposure was inhibited by RNAi of daf-2, age-1, akt-2, akt-1, and 3 insulin peptides genes, but increased by RNAi of daf-16 and sod-3. The resistance of animals with RNAi of daf-2 to toxicity in high glucose treated nematodes followed by PS-NP exposure could be suppressed by RNAi of daf-16. Moreover, in high glucose treated animals followed by PS-NP exposure, daf-2 expression was inhibited by RNAi of ins-6, ins-9, and daf-28. Our data demonstrated the risk of PS-NP exposure in enhancing the high glucose toxicity. More importantly, alteration in expression of genes in insulin signaling pathway was associated with the toxicity enhancement in high glucose treated nematodes followed by PS-NP exposure.

Achieving a Wide-Range Linear Piezoresistive Response in Electrowritten Soft-Hard Polymer Blends via Salami-Inspired Heterostructure Design.

Flexible electronics capable of acquiring high-precision signals are in great demand for the development of the internet of things and intelligent artificial. However, it is currently a challenge to simultaneously achieve high signal linearity and sensitivity for stretchable resistive sensors over a wide strain range toward advanced application scenarios requiring high signal accuracy, e.g., sophisticated physiological signal discrimination and displacement measurement. Herein, a film strain sensor, which has an electrical and mechanical dual heterostructure, was fabricated via a direct near-field electrowriting and molecule-guided in situ growth of silver nanoparticles with different concentrations on high-modulus polystyrene domains and low-modulus styrene-butadiene copolymers with a salami-like morphology. Mechanism analyses from both theoretical and experimental investigations reveal that the salami-like heteromodulus microstructure regulates microcrack propagation routes, while the heteroconductivity changes the electron transport paths and amplifies the resistance increase during crack propagation. Therefore, the as-designed strain sensor shows a linear resistive response within ca. 70% strain with a gauge factor of 25, unveiling a simple and scalable strategy for trading off signal linearity and sensitivity over a wide strain range for the fabrication of high-performance linear strain sensors.

Thermally Conductive Magnetic Composite Phase Change Materials for Anisotropic Photo/Magnetic-to-Thermal Energy Conversion.

The distinctive thermal energy storage properties of phase change materials (PCMs) are critical for solving energy issues. However, their inherently low thermal conductivity and limited energy conversion capability impede their applications in advanced thermal energy harvesting and storage systems. Herein, we developed magnetic composite PCMs with enhanced thermal conductivity for anisotropic photothermal and magnetic-to-thermal energy conversions. The hierarchically interconnected ferroferric oxide-coated boron nitride/poly(vinyl alcohol) (BN@Fe3O4/PVA) porous scaffolds were constructed by a unidirectional freeze-casting method to enhance the directional heat transfer capability of the composite PCMs with a through-plane thermal conductivity of 1.84 W m-1 K-1 at a BN@Fe3O4 loading of 25.4 wt %. The superparamagnetic Fe3O4 nanoparticles endow the composite PCMs with unique solar absorption and magnetic response properties, and the energy conversion efficiency can be regulated by controlling the orientation of the synthesized magnetic particles in the composite PCMs. As a consequence, the resulting composite PCMs exhibit superior photo/magnetic-to-thermal energy conversion efficiency along the direction of orientation of magnetic particles. These novel findings provide an instructive guide to yield composite PCMs for efficient energy conversion.

Policy instruments facilitate China's COVID-19 work resumption.

Governments worldwide have announced stimulus packages to remobilize the labor force after COVID-19 and therefore to cope with the COVID-19-related recession. However, it is still unclear how to facilitate large-scale work resumption. This paper aims to clarify the issue by analyzing the large-scale prefecture-level dataset of human mobility trajectory information for 320 million workers and about 500,000 policy documents in China. We model work resumption as a collective behavioral change due to configurations of capacity, motivation, and policy instruments by using qualitative comparative analysis. We find that the effectiveness of post-COVID-19 recovery stimulus varied across China depending on the fiscal and administrative capacity and the policy motivation of the prefecture. Subnational fiscal and procurement policies were more effective for the wholesale and retail sector and the hotel and catering sector, whereas the manufacturing and business services sectors required more effort regarding employment policies. Due to limited prefectural capacity and wavering policy motivation, the simultaneous adoption of fiscal, employment, and procurement policy interventions endangered post-COVID-19 work resumption. We highlight the necessity of tailored postcrisis recovery strategies based on local fiscal and administrative capacity and the sectoral structure.

Uncovering spatial and social gaps in rural mobility via mobile phone big data.

Rural mobility inequality is an important aspect of inequality-focused Sustainable Development Goals. To reduce inequality and promote global sustainable development, more insight is needed into human mobility patterns in rural areas. However, studies on rural human mobility are scarce, limiting our understanding of the spatial and social gaps in rural human mobility and our ability to design policies for social equality and global sustainable development. This study, therefore, explores human mobility patterns in rural China using mobile phone data. Mapping the relative frequency of short-distance trips across rural towns, we observed that geographically peripheral populations tend to have a low percentage of short-distance flows. We further revealed social gaps in mobility by fitting statistical models: as travel distances increased, human movements declined more rapidly among vulnerable groups, including children, older people, women, and low-income people. In addition, we found that people living with low street density, or in rural towns in peripheral cities with long distances to city borders, are more likely to have low intercity movement. Our results show that children, older adults, women, low-income individuals, and geographically peripheral populations in rural areas are mobility-disadvantaged, providing insights for policymakers and rural planners for achieving social equality by targeting the right groups.

Reducing COVID-19 diagnostic errors with dNTPαSe supplementation.

Timely and accurate diagnosis of COVID-19 is critical for controlling the pandemic. As the standard method to diagnose SARS-CoV-2, the real-time reverse transcription polymerase chain reaction (RT-qPCR) has good convenience. However, RT-qPCR still has a relatively high false-negative rate, particularly in the case of detecting low viral loads. In this study, using selenium-modified nucleoside triphosphates (dNTPαSe) in the RT-PCR reactions, we successfully increased the detection sensitivity and reduced the false-negative rate in COVID-19 diagnosis. By detecting positive controls, pseudovirus, and clinical samples with the commercial kits, we found that the dNTPαSe supplementation to these kits could generally offer smaller Ct values, permit the viral detection even in single-digit copies, and increase the detection specificity, sensitivity, and accuracy, thereby reducing the false-negative rate. Our experimental results demonstrated that dNTPαSe supplementation can make the commercial kits more specific, sensitive, and accurate, and this method is a convenient and efficient strategy for the disease detection and diagnosis.

The effects of urban land use on energy-related CO2 emissions in China.

Land use change caused by urbanization is widely believed to be the primary way human activities affect energy use and, thus, CO2 emissions (CEs) in China. However, there is a limited understanding of the role of land use with detailed categories in energy-related CEs is still absent. This paper aims to narrow the knowledge gap using multi-dimension metrics, including land use scale, mixture, and intensity. These metrics were derived from three years of sequential POI data. A GWR analysis was carried out to examine the associations between land use change and energy-related CEs. Our results show that (1) the scale of most land use types exerted a bidirectional effect on CEs, demonstrating apparent spatiotemporal heterogeneity; (2) land use mixture of mature city agglomerations had a significant suppressive effect on CEs, suggesting mixed land use be advocated in the urbanization process; (3) Land use intensity had a bi-directional association with CEs in most cities, but its adverse effect gradually spread from the west to the northeast. Therefore, systematically regulating land transaction to control land scale, appropriately interplanting biofuel plants, and utilizing renewable energy are encouraged to reduce energy footprints and mitigate CEs in China. The findings and conclusions of this paper enhance our knowledge on the relationship between land use and CEs and present the scientific basis for policy-making in building low-carbon cities in the context of rapidly urbanizing China.

Measuring Accessibility to Healthcare Using Taxi Trajectories Data: A Case Study of Acute Myocardial Infarction Cases in Beijing.

Several methods have been applied to measure healthcare accessibility, ie, the Euclidean distance, the network distance, and the transport time based on speed limits. However, these methods generally produce less accurate estimates than actual measurements. This research proposed a method to estimate historical healthcare accessibility more accurately by using taxi Global Positioning System (GPS) traces. The proposed method's advantages were evaluated vis a case study using acute myocardial infarction (AMI) cases in Beijing in 2008. Comparative analyses of the new measure and three conventionally used measures suggested that the median estimated transport time to the closest hospital with percutaneous coronary intervention (PCI) capability for AMI patients was 5.72 minutes by the taxi GPS trace-based measure, 2.42 minutes by the network distance-based measure, 2.28 minutes by the speed limit-based measure, 1.73 minutes by the Euclidean distance-based measure; and the estimated proportion of patients who lived within 5 minutes of a PCI-capable hospital was 38.17%, 89.20%, 92.52%, 95.05%, respectively. The three conventionally used measures underestimated the travel time cost and overestimated the percentage of patients with timely access to healthcare facilities. In addition, the new measure more accurately identifies the areas with low or high access to healthcare facilities. The taxi GPS trace-based accessibility measure provides a promising start for more accurately estimating accessibility to healthcare facilities, increasing the use of medical records in studying the effects of historical healthcare accessibility on health outcomes, and evaluating how accessibility to healthcare changes over time.

Leakage-Proof Flexible Phase Change Gels with Salient Thermal Conductivity for Efficient Thermal Management.

Phase change materials (PCMs) as one of the most potential latent heat storage techniques have been widely used for thermal management and energy storage. However, simultaneously imparting flexibility, high thermal conductivity, and considerable energy storage density to organic PCMs remains challenging. In this work, a coupling strategy combining substance exchange and magnetic orientation has been proposed to fabricate phase change gels (PCGs) with thermally induced flexibility and high through-plane thermal conductivity. In the PCGs, synthesized boron nitride/ferroferric oxide (BN@Fe3O4) particles and polyacrylic acid (PAA) precursor liquid are introduced to polyethylene glycol (PEG) aqueous solution, and a magnetic field is applied in the process of PAA network construction to promote ordered arrangement of BN@Fe3O4 along the direction of the magnetic field. Consequently, PEG is wrapped by the cross-linked PAA supporting network, forming PCGs with excellent shape stability and thermally induced flexibility. The vertical orientation structure of BN@Fe3O4 endows the PCGs with an enhanced through-plane thermal conductivity of up to 1.07 W m-1 K-1 at a BN@Fe3O4 loading of 25.6 wt % with an additional enhancement of 215% compared to the composite without BN. The thermally conductive leakage-proof PCGs present great application potential in heat storage and management.

Janus and Heteromodulus Elastomeric Fiber Mats Feature Regulable Stress Redistribution for Boosted Strain Sensing Performance.

Wearable strain sensors have huge potential for applications in healthcare, human-machine interfacing, and augmented reality systems. However, the nonlinear response of the resistance signal to strain has caused considerable difficulty and complexity in data processing and signal transformation, thus impeding their practical applications severely. Herein, we propose a simple way to achieve linear and reproducible resistive signals responding to strain in a relatively wide strain range for flexible strain sensors, which is achieved via the fabrication of Janus and heteromodulus elastomeric fiber mats with micropatterns using microimprinting second processing technology. In detail, both isotropic and anisotropic fiber mats can turn into Janus fiber mats with periodical and heteromodulus micropatterns via controlling the fiber fusion and the diffusion of local macromolecular chains of thermoplastic elastomers. The Janus heterogeneous microstructure allows for stress redistribution upon stretching, thus leading to lower strain hysteresis and improved linearity of resistive signal. Moreover, tunable sensing performance can be achieved by tailoring the size of the micropatterns on the fiber mat surface and the fiber anisotropy. The Janus mat strain sensors with high signal linearity and good reproducibility have a very low strain detection limit, enabling potential applications in human-machine interfacing and intelligent control fields if combined with a wireless communication module.

Soil Heavy Metal Content Prediction Based on a Deep Belief Network and Random Forest Model.

In order to extract useful information from X-ray fluorescence (XRF) spectra and establish a high-accuracy prediction model of soil heavy metal contents, a hybrid model combining a deep belief network (DBN) with a tree-based model was proposed. The DBN was first introduced into feature extraction of XRF spectral data, which can obtain deep layer features of spectra. Owing to the strong regression ability of the tree-based model, it can offset the deficiency of DBN in prediction ability so it was used for predicting heavy metal contents based on the extracted features. In order to further improve the performance of the model, the parameters of model can be optimized according to the prediction error, which was completed by sparrow search algorithm and the gird search. The hybrid model was applied to predict the contents of As and Pb based on spectral data of overlapping peaks. It can be obtained that R2 of As and Pb reached 0.9884 and 0.9358, the mean square error of As and Pb are as low as 0.0011 and 0.0058, which outperform other commonly used models. That proved the combination of DBN and tree-based model can obtain more accurate prediction results.

Perceived accessibility and mental health consequences of COVID-19 containment policies.

BACKGROUND: Individuals have experienced various degrees of accessibility loss during the COVID-19 pandemic, which may consequently have influenced their mental health. Although efforts have been made to understand the mental health consequences of the pandemic and corresponding containment measures, the impacts of accessibility loss remain underexplored. METHODS: Based on 186 family interviews, a 569-respondent panel survey was designed and distributed monthly from February to October 2020 in Kunming, China. A 3-wave cross-lagged panel model was developed to understand the causal relationship between mental health and perceived accessibility of daily necessities, key services, and social activities. RESULTS: Goodness-of-fit indicators imply that the hypothesised model fits the observed data well: χ2/df = 2.221, AGFI = 0.910, NFI = 0.907, CFI = 0.933, RMSEA = 0.052. The results indicate that perceived accessibility of daily necessities and social activities had lagged effects on mental health status. The within-wave effects show that perceived accessibility of daily necessities (0.619, p < 0.01) and social activities (0.545, p < 0.01) significantly influenced respondents' mental health during the peak of the pandemic whilst perceived accessibility of social activities dominantly influenced their mental health after restrictions were lifted (0.779, p < 0.01). Perceived accessibility of public services such as healthcare did not significantly influence respondents' mental health in any wave. COVID-19 containment policies had different mental outcomes across population groups. Disadvantaged people experienced mental health issues due to accessibility loss for daily necessities and social activities until the lifting of compulsory QR-code-for-buses, whilst better-off populations had better mental health during the early phase of the outbreak and rapidly recovered their mental health after mobility restrictions eased. CONCLUSION: Reduced perceived accessibility of daily necessities and social activities may be an underlying cause of mental health problems. Relative accessibility deprivation exacerbated mental health inequities during the COVID-19 pandemic.

Recent Advances in Multiresponsive Flexible Sensors towards E-skin: A Delicate Design for Versatile Sensing.

Multiresponsive flexile sensors with strain, temperature, humidity, and other sensing abilities serving as real electronic skin (e-skin) have manifested great application potential in flexible electronics, artificial intelligence (AI), and Internet of Things (IoT). Although numerous flexible sensors with sole sensing function have already been reported since the concept of e-skin, that mimics the sensing features of human skin, was proposed about a decade ago, the ones with more sensing capacities as new emergences are urgently demanded. However, highly integrated and highly sensitive flexible sensors with multiresponsive functions are becoming a big thrust for the detection of human body motions, physiological signals (e.g., skin temperature, blood pressure, electrocardiograms (ECG), electromyograms (EMG), sweat, etc.) and environmental stimuli (e.g., light, magnetic field, volatile organic compounds (VOCs)), which are vital to real-time and all-round human health monitoring and management. Herein, this review summarizes the design, manufacturing, and application of multiresponsive flexible sensors and presents the future challenges of fabricating these sensors for the next-generation e-skin and wearable electronics.

Influence of Neighborhood Characteristics on Physical Activity, Health, and Quality of Life of Older Adults: A Path Analysis.

Background: As life expectancy and health expenditure consumed by older people increase, maintaining a better health and quality of life for older adults has become an important social issue. Research indicates that physical activity may help address this challenge. Moreover, it is believed that improved quality of life and health benefits from physical activity can be achieved through interventions in the neighborhood environments. However, existing knowledge has often been based on bivariate relationships between these factors, and few studies have formally examined the extent to which any association between neighborhood environments, health, and quality of life may be mediated by the level of physical activity. This paper aims to investigate the direct and indirect influence of neighborhood characteristics on the health and quality of life of older adults, taking into account physical activity behavior and socio-demographic characteristics in a more comprehensive framework. Methods: Data were collected using a survey among 363 older adults aged 60 years and over in China. A path analysis was used that derives all direct and indirect relationships between the variables. Results: Leisure-time physical activity levels played a mediating role in the relation between social capital and health as well as quality of life. Moreover, the study confirmed direct relationships between neighborhood characteristics such as neighborhood aesthetics and traffic safety and health as well as quality of life. However, the effect of neighborhood characteristics on health and quality of life through transport-related physical activity levels was not found. Conclusions: Leisure-time physical activity instead of transport-related physical activity should be considered a priority when developing interventions aiming to promote healthy aging. Additionally, neighborhood characteristics are important in promoting healthy aging, even though they have no or less impacts on older adults' health and quality of life through physical activity.

Scalable Flexible Phase Change Materials with a Swollen Polymer Network Structure for Thermal Energy Storage.

3D porous structural materials are proved to be enticing candidates for the fabrication of high-performance organic phase change materials (PCMs), but the stringent fabrication process and poor processability greatly hampered their commercialization. Herein, flexible leakage-proof composite PCMs with pronounced comprehensive performance are fabricated by a scalable polymer swelling strategy without using any solvent, in which the paraffin wax (PW) segment is confined in a robust flexible 3D polymer network, giving rise to the composite PCMs with excellent form stability even at 160 °C, a high latent heat energy storage density of 133.6 J/g, and an outstanding thermal conductivity of up to ∼5.11 W/mK. More importantly, the mass production of the flexible composite phase change fiber, film, and bulk products can be achieved by adopting mature processing technologies. These resultant composite PCMs exhibit promising thermal management ability to solve the overheating problem of electronics and high-efficiency solar-thermal energy conversion capacity.

Older Adults' Choice of Patterns of Outdoor Physical Activity Duration: A Mixed Multinomial Logit Model.

Outdoor physical activity duration is a key component of outdoor physical activity behavior of older adults, and therefore, an important determinant of their total physical activity levels. In order to develop a successful outdoor physical activity program, it is important to identify any heterogeneity in preferences for outdoor physical activity duration patterns among older adults. In addition, more insight is needed in the influence of environmental characteristics on duration choice for creating supportive neighborhood environments matching individuals' preferences. To this end, a mixed multinomial logit model is estimated based on one-week data collected among 336 respondents aged 60 or over in 2017 in Dalian, China. The present model formulation accounts for heterogeneity in individuals' preferences and allows for the analysis of substitution and complementary relationships between the different patterns of outdoor physical activity duration. Results indicate that older adults vary significantly in their preferences for each outdoor physical activity duration pattern. Moreover, short walking duration, short exercise duration and medium exercise duration are substitutes for medium walking duration while short walking duration and short exercise duration are complements for medium exercise duration in terms of individuals' outdoor physical activity duration preferences. In addition, we find that distance to the nearest park, footpath conditions and neighborhood aesthetics are associated with older adults' outdoor physical activity duration choice.

Winning Solutions and Post-Challenge Analyses of the ChaLearn AutoDL Challenge 2019.

This paper reports the results and post-challenge analyses of ChaLearn's AutoDL challenge series, which helped sorting out a profusion of AutoML solutions for Deep Learning (DL) that had been introduced in a variety of settings, but lacked fair comparisons. All input data modalities (time series, images, videos, text, tabular) were formatted as tensors and all tasks were multi-label classification problems. Code submissions were executed on hidden tasks, with limited time and computational resources, pushing solutions that get results quickly. In this setting, DL methods dominated, though popular Neural Architecture Search (NAS) was impractical. Solutions relied on fine-tuned pre-trained networks, with architectures matching data modality. Post-challenge tests did not reveal improvements beyond the imposed time limit. While no component is particularly original or novel, a high level modular organization emerged featuring a "meta-learner", "data ingestor", "model selector", "model/learner", and "evaluator". This modularity enabled ablation studies, which revealed the importance of (off-platform) meta-learning, ensembling, and efficient data management. Experiments on heterogeneous module combinations further confirm the (local) optimality of the winning solutions. Our challenge legacy includes an ever-lasting benchmark (http://autodl.chalearn.org), the open-sourced code of the winners, and a free "AutoDL self-service."

Location Choice in the Context of Older Adults' Leisure-Time Walking.

Leisure-time walking is the most prevalent and preferred form of physical activity of older adults. In order to promote leisure-time walking and enhance the efficiency of using outdoor open spaces, the supply of different types of walking locations should match the needs, interests and preferences of older adults. However, there is limited knowledge on which location types are chosen by which groups of individuals under which conditions. This study therefore examines the effects of socio-demographics, episode participation attributes and neighborhood characteristics on the location choice of older adults for leisure-time walking. A multinomial logit model is estimated based on data collected among 316 respondents aged 60 or older in Dalian, China. The results indicate that older people's location choices for walking are associated with their socio-demographics, episode participation attributes and neighborhood characteristics. Finally, implications of the results for the planning, design and management of open spaces are identified.