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Abstract Targeted immunomodulation for reactivating innate cells, especially macrophages, holds great promise to complement current adaptive immunotherapy. Nevertheless, there is still a lack of high-performance therapeutics for blocking macrophage phagocytosis checkpoint inhibitors in solid tumors. Herein, a peptide-antibody combo-supramolecular in situ assembled CD47 and CD24 bi-target inhibitor (PAC-SABI) is described, which undergoes biomimetic surface propagation on cancer cell membranes through ligand-receptor binding and enzyme-triggered reactions. By simultaneously blocking CD47 and CD24 signaling, PAC-SABI enhances the phagocytic ability of macrophages in vitro and in vivo, promoting anti-tumor responses in breast and pancreatic cancer mouse models. Moreover, building on the foundation of PAC-SABI-induced macrophage repolarization and increased CD8+ T cell tumor infiltration, sequential anti-PD-1 therapy further suppresses 4T1 tumor progression, prolonging survival rate. The in vivo construction of PAC-SABI-based nano-architectonics provides an efficient platform for bridging innate and adaptive immunity to maximize therapeutic potency.

Equal access to social infrastructures is a fundamental prerequisite for sustainable development, but has long been a great challenge worldwide. Previous studies have primarily focused on the accessibility to social infrastructures in urban areas across various scales, with less attention to rural areas, where inequality can be more severe. Particularly, few have investigated the disparities of accessibility to social infrastructures between urban and rural areas. Here, using the Changsha–Zhuzhou–Xiangtan urban agglomeration, China, as an example, we investigated the inequality of accessibility in both urban and rural areas, and further compared the urban-rural difference. Accessibility was measured by travel time of residents to infrastructures. We selected four types of social infrastructures including supermarkets, bus stops, primary schools, and health care, which were fundamentally important to both urban and rural residents. We found large disparities in accessibility between urban and rural areas, ranging from 20 min to 2 h. Rural residents had to spend one to two more hours to bus stops than urban residents, and 20 min more to the other three types of infrastructures. Furthermore, accessibility to multiple infrastructures showed greater urban-rural differences. Rural residents in more than half of the towns had no access to any infrastructure within 15 min, while more than 60% of the urban residents could access to all infrastructures within 15 min. Our results revealed quantitative accessibility gap between urban and rural areas and underscored the necessity of social infrastructures planning to address such disparities.

Insufficient density of red deer has affected the stability of forest ecosystems and the recovery of large carnivores (represented by Amur tiger). Conservation translocations from captivity to the wild has become an important way to restore the red deer populations. However, the difference in gut microbes between pre-release and wild red deer may affect the feeding adaptability of red deer after release. In this study, we clarified the differences in gut microbes between pre-released and wild red deer and screened the key gut microbes of the red deer involved in feeding by using metagenomic sequencing and feeding analysis. The results showed that the microbial difference between pre-released and wild red deer was mainly related to Firmicutes represented by Eubacteriales and Clostridia, and Firmicutes abundance in pre-released red deer (68.23%) was significantly lower than that of wild red deer (74.91%, p 1), showing a significant positive correlation (p

Abstract Targeting tumor-infiltrating regulatory T cells (Tregs) is an efficient way to evoke an anti-tumor immune response. However, how Tregs maintain their fragility and stability remains largely unknown. IFITM3 and STAT1 are interferon-induced genes that play a positive role in the progression of tumors. Here, we showed that IFITM3-deficient Tregs blunted tumor growth by strengthening the tumor-killing response and displayed the Th1-like Treg phenotype with higher secretion of IFNγ. Mechanistically, depletion of IFITM3 enhances the translation and phosphorylation of STAT1. On the contrary, the decreased IFITM3 expression in STAT1-deficient Tregs indicates that STAT1 conversely regulates the expression of IFITM3 to form a feedback loop. Blocking the inflammatory cytokine IFNγ or directly depleting STAT1-IFITM3 axis phenocopies the restored suppressive function of tumor-infiltrating Tregs in the tumor model. Overall, our study demonstrates that the perturbation of tumor-infiltrating Tregs through the IFNγ-IFITM3-STAT1 feedback loop is essential for anti-tumor immunity and constitutes a targetable vulnerability of cancer immunotherapy.

Abstract Anion exchanger 2 (AE2) is an electroneutral Na+-independent Cl-/HCO3 - exchanger belongs to the SLC4 transporter family. The widely expressed AE2 participates in a variety of physiological processes, including transepithelial acid-base secretion and osteoclastogenesis. Both the transmembrane domains (TMDs) and the N-terminal cytoplasmic domain (NTD) are involved in regulation of AE2 activity. However, the regulatory mechanism remains unclear. Here, we report a 3.2 Å cryo-EM structure of the AE2 TMDs in complex with PIP2 and a 3.3 Å full-length mutant AE2 structure in the resting state without PIP2. We demonstrate that PIP2 at the TMD dimer interface is involved in the substrate exchange process. Mutation in the PIP2 binding site leads to the displacement of TM7 and further stabilizes the interaction between the TMD and the NTD. Reduced substrate transport activity and conformation similar to AE2 in acidic pH indicating the central contribution of PIP2 to the function of AE2.

Abstract Phase separation, a biophysical segregation of subcellular milieus referred as condensates, is known to regulate transcription, but its impacts on physiological processes are less clear. Here, we demonstrate the formation of liquid-like nuclear condensates by SGF29, a component of the SAGA transcriptional coactivator complex, during cellular senescence in human mesenchymal progenitor cells (hMPCs) and fibroblasts. The Arg 207 within the intrinsically disordered region is identified as the key amino acid residue for SGF29 to form phase separation. Through epigenomic and transcriptomic analysis, our data indicated that both condensate formation and H3K4me3 binding of SGF29 are essential for establishing its precise chromatin location, recruiting transcriptional factors and co-activators to target specific genomic loci, and initiating the expression of genes associated with senescence, such as CDKN1A. The formation of SGF29 condensates alone, however, may not be sufficient to drive H3K4me3 binding or achieve transactivation functions. Our study establishes a link between phase separation and aging regulation, highlighting nuclear condensates as a functional unit that facilitate shaping transcriptional landscapes in aging.

Motor dysfunction is increasingly being viewed as a core characteristic of autism spectrum disorder (ASD) in children. In particular, children with ASD have difficulty in learning new motor skills and there is a need to develop effective methods to improve this. Previous research has found that children with ASD may retain the ability to implicitly learn motor skills in comparison to their explicit learning of motor skills, which is typically impaired. This literature mini review focuses on summarizing the study of implicit learning in the acquisition of motor skills in children with ASD. First, we briefly introduce several common implicit learning methods in children’s motor skill learning. Second, we focus on the role of two important implicit learning approaches in motor skill learning, namely, an external focus of attention and analogy learning. Finally, based on our review of the existing studies, we present an outlook for future research and the areas that need to be improved in the practical teaching of implicit learning in the acquisition of motor skills in children with ASD.

This paper introduces a design of an annular water-cooled automotive exhaust-based thermoelectric generator (TEG). A comprehensive numerical model of TEG system is established to investigate the relationship between automotive exhaust temperature and coolant flow rate. Through numerical simulations, it is demonstrated that the implementation of this device can effectively enhance the temperature uniformity at the hot side of the heat exchanger, consequently increasing the TEG's power output. After introducing the annular water-cooled radiator, the temperature uniformity of the thermoelectric module increased by 18.8%. By utilizing the numerical simulation outcomes alongside empirical formulas, calculations for the pump power consumption, maximum output power, and maximum net output power of the thermoelectric module (TEM) are conducted. The maximum net output power can be increased by 3.30%–53.24% by controlling the coolant flow rate. As a result, a relationship curve depicting the average temperature difference between the hot and cold ends of the TEM, in relation to the optimum coolant flow rate, is obtained. This relationship curve serves as a valuable tool for adjusting the radiator's coolant flow rate and augmenting the TEG's net output power, ultimately achieving the objective of heightening the power generation efficiency of the TEG.

After the service provider temporarily selects the required edge nodes based on social and storage capabilities, application execution causes the edge nodes to cache part of the application data. Therefore, offloading part of the application computing tasks to the selected edge nodes can effectively improve application execution performance. However, in cases where the resources of user’s IoT devices are insufficient, tasks can be further offloaded to traditional edge servers or even to the cloud to maximize application execution efficiency. In this paper, the entire uninstall utility is modeled as a weighted sum of task completion time and energy consumption. Under the premise of considering users’ preferences for completion time and energy consumption, a game-based uninstallation algorithm is proposed. The algorithm performs uninstallation by optimizing the uninstallation decision. Based on user preferences, the total system overhead is relatively small. The subsequent simulation experiments show that the algorithm can reduce system overhead on the basis of satisfying user preferences and has relatively good adaptability.

Ecosystem services (ESs) have been changed significantly due to human and natural interference, especially in urban megaregions. Numerous studies have revealed the impact of urbanization on regional ecosystem service(ES). However, the research on whether urban expansion has sacrificed the areas providing high ESs, which played a crucial role in sustainable development, was poorly understood. This study analyzed the spatial variation of ES supply from 2000 to 2020 under the influence of urban expansion in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA). The result showed that GBA has witnessed high-seeped urban development, and nearly 50% of urban expansion encroached on cropland, 25% on forestland, and 25% on waterbody from 2000 to 2020. Secondly, The ESs changed significantly due to urban expansion. Importantly, nearly 74.48% and 59.74% of areas that urban expansion encroached on were the ecological lands that provided a very high level of ESs from 2000 to 2010 and from 2010 to 2020, respectively. However, the direct impact of urban expansion on the ecological lands providing a very high level of ESs has been decreased. Additionally, the increase in ESs in old urban areas also has a positive role in the regional ES. This study expects to systematically assess the direct impact of urbanization on regional ES and provide scientific information on land use planning for sustainable development.

Accurate energy consumption prediction is essential for improving the driving experience. In the urban road scenario, we discussed the influencing factors of energy consumption and divided the modes from various perspectives. The differences in energy consumption characteristics and distribution laws for electric vehicles using the IDM and CACC car-following models under different traffic flows are compared. An energy consumption prediction framework based on the LightGBM model is proposed. According to the study, driving range, acceleration, accelerating time, decelerating time and cruising time all significantly impact the overall energy consumption of electric vehicles. There are apparent differences in energy consumption characteristics and distribution laws under different traffic flows: average energy consumption is lower under low flow and increased under high flow. The CACC-electric vehicles consume more energy in low flow than IDM-electric vehicles. Under high flow, the opposite is true. The results show that the proposed framework has a high accuracy: the MAPE based on IDM datasets is 3.45% and the RMSE is 0.039 kWh; the MAPE based on CACC datasets is 5.57% and the RMSE is 0.042 kWh. The MAPE and RMSE are reduced by 33.7% and 50.6% (maximum extent) compared to the best comparison algorithm.

Abstract Cyclic GMP-AMP synthase (cGAS) is an essential sensor of aberrant cytosolic DNA for initiating innate immunity upon invading pathogens and cellular stress, which is considered as a potential drug target for autoimmune and autoinflammatory diseases. Here, we report the discovery of a class of cyclopeptide inhibitors of cGAS identified by an in vitro screening assay from a focused library of cyclic peptides. These cyclopeptides specifically bind to the DNA binding site of cGAS and block the binding of dsDNA with cGAS, subsequently inhibit dsDNA-induced liquid phase condensation and activation of cGAS. The specificity and potency of one optimal lead XQ2B were characterized in cellular assays. Concordantly, XQ2B inhibited herpes simplex virus-1 (HSV-1)-induced antiviral immune responses and enhanced HSV-1 infection in vitro and in vivo. Furthermore, XQ2B significantly suppressed the elevated levels of type I interferon and proinflammatory cytokines in primary macrophages from Trex1 -/- mice and systemic inflammation in Trex1 -/- mice. XQ2B represents the specific cGAS inhibitor targeting protein-DNA interaction and phase separation and serves as a scaffold for the development of therapies in the treatment of cGAS-dependent inflammatory diseases.

Abstract Sports have traditionally had gendered connotations in society and culture, resulting in solidified gender stereotypes that influence impression evaluations. China has a special gender social culture; however, how sport–gender stereotypes (SGS) influence the gender evaluation of people in China in the Global South is still unknown. This study obtained gender-typed sports and attribute adjectives and proved the existence of SGS through a pilot study (392 college students, n 1 = 207, n 2 = 185) and then used two studies to explore the influence of both explicit and implicit SGS on evaluations and compared the differences between these stereotypes and general gender stereotypes. Study 1 (395 college students, n 1a = 192, n 1b = 203) examined the explicit level using a questionnaire experiment. The results of two experiments showed that (1) stereotype-consistent targets were more masculine or feminine in correspondence with their gender, while stereotype-inconsistent targets had higher anti-gender traits; and (2) the inclusion of stereotype-consistent sports activities led targets to be evaluated as more masculine, while stereotype-inconsistent sport activities showed gender evaluation reversal, especially for women. Study 2 (103 college students, n 2a = 61, n 2b = 42) measured the implicit attitudes using the Implicit Association Test. The results of two experiments showed that (1) implicit evaluations of stereotype-consistent targets were associated faster than stereotype-inconsistent targets and (2) the inclusion of gender-typed sports weakened implicit gender evaluations. In conclusion, this is the first quantitative study to explore the unique effect of SGS on individual evaluations and how they differ from general gender stereotypes in the Chinese context. These findings could provide valuable insights for research and the application of sports social science and physical education.

Collective movement has emerged as a key area of interest in animal behavior. While individual differences are often viewed as a potential threat to group cohesion, growing evidence suggests that these differences can actually influence an animal’s behavior as an initiator or follower during collective movements, thereby driving the group‘s movement and decision-making processes. To resolve the divergence, we asked how personality can affect the dynamics of collective movements in one group of free-ranging Tibetan macaques (Macaca thibetana) in Huangshan, China. We assessed individual personality using principal component analysis and applied the generalized linear mixed model and linear mixed model to examine the influence of personality on decision making during collective movements. Our findings reveled three distinct personality types among Tibetan macaques: sociability, boldness, and anxiousness. Individuals with higher sociability scores and rank, or those with lower anxiousness scores, were more likely to initiate successful collective movements. Older individuals were less successful in initiating movements compared to young adults. Leaders with lower anxiousness scores or higher rank attracted more followers, with females attracting larger groups than males. As for followers, individuals with higher rank tended to join the collective movement earlier. Additionally, individuals with higher sociability or boldness scores had shorter joining latency in collective movement. Finally, there was a longer joining latency for middle-aged adults compared to young adults. These results suggest that individual differences are a potential driver of collective movements. We provide some insights into the relationships between personality and decision making in Tibetan macaques.

Lithium metal batteries based on solid electrolytes are considered as promising candidates with high energy density and safety. However, the weak solid-solid contact between electrolyte and electrode can easily lead to interface instability and lithium ions discontinuous migration, which seriously reduces the electrochemical performance of the battery. Herein, we construct a soft gel interfacial layer to improve the stability of the solid-solid interface between electrolyte and electrode by means of polyester-based monomers and imidazole-based ionic liquids. Based on this, garnet-type Li6.4La3Zr1.4Ta0.6O12 (LLZTO) particles as inorganic ceramic filler were introduced in the layer to obtain composite electrolytes with high ionic conductivity (up to 1.1 × 10−3 S/cm at 25 °C). As a result, the assembled lithium symmetric battery of Li|THCE-15%LLZTO|Li suggests excellent cycling stability with 700 h at 0.1 mA/cm2 at 50 °C, and the lithium metal batteries of LFP|THCE-15%LLZTO|Li delivers high initial discharge capacity of 128.2 mA ·h/g with capacity retain of 75.48% after 150 cycles at 2 C. This work paves a new route to build safe and stable lithium metal batteries with synergistic introduction of composite electrolytes between electrolyte and electrode using soft gel interfacial layer and inorganic filler.

Africa has a lower proportion of urban areas compared to other continents, yet it is experiencing rapid urbanization, which is posing a significant threat to the urban ecosystem. This study presents the results of a bibliometric analysis from publications on urban green spaces (UGS) research in African cities. From the Web of Science, Science Direct, Google Scholar, and PubMed databases, 264 articles on UGS research in Africa were included in this study. This research topic experienced rapid growth, as more than 68% of all the articles were produced in the past five years, where about 63% of the studies included in this analysis were carried out in only four countries. Most of the studies were carried out at the intracity scale, with the main focus being on the ecosystem services provided by UGS. Change detection and overall UGS mapping studies show that high-income cities have a high percentage of UGS, while many African cities exhibited lower green coverage. We commend the work from researchers; however, there is still a gap to fill both in terms of high-quality datasets and state-of-the-art technology usage, and there is also a need for more comparative studies among cities and countries at the continental scale.

The phase circulating current (PCC) of the parallel three-phase inverter systems dramatically affects the power quality and conversion efficiency of the power grid. In this paper, a composite suppression strategy is proposed to solve the PCC issue by using the sliding mode control (SMC) approach and improved virtual impedance droop control. Taking the commonly used 2-group parallel three-phase inverter as an example, an inter- and intra-classification model is established by analyzing the sources of PCC. In order to suppress the inter-PCC, the traditional virtual impedance droop control is given, following the improved substitute by combining SMC. And the variables of the bus voltage, Q-U loop, P-f loop, and the virtual-induced reactance are also introduced for the robust control of the impedance droop. On the other side, a SMC-based suppression approach is designed to solve the issue of the intra-PCC. Its idea is to introduce a regulation factor for the space vector pulse width modulation (SVPWM) so that the zero-sequence voltage can be eliminated and the influence of the intra-PCC can be relieved. Comparative simulations and experiments validate the effectiveness of the methods proposed in this paper.

Abstract Lumbar disc herniation is a common disease that causes low back pain. Due to the high cost of medical diagnosis, as well as a shortage and uneven distribution of medical resources, a system that can automatically analyze and diagnose lumbar spine Magnetic Resonance Imaging (MRI) is becoming an urgent need. This study uses deep learning methods to establish a classifier to diagnose lumbar disc herniation. An MRI classification dataset of lumbar disc herniation consisting of public MRI images is presented and is used to train the proposed classifier. Because a common difficulty in applying computer vision technology to medical images is labeling training data, we use a semi-supervised model training method, while multilayer transverse axial MRI images are used as the model input. In this method, we first use unlabelled MRI images for random self-supervised pre-training and the pre-trained model as a feature extractor for MRI images. Then, all marked cross-sections of each intervertebral disc are used to calculate the feature vector through the feature extractor. The information of all feature vectors is integrated, while a multilayer perceptron is used for classification training. After training, the model achieved 87.11 $$\%$$ % accuracy, 87.50 $$\%$$ % sensitivity, 86.72 $$\%$$ % specificity and 0.9487 AUC (Area Under the ROC Curve) index on the test set. To analyze the rationality of the diagnostic results more quickly, we output the severity of degenerative changes in each region using a heatmap.

Aging research has shifted from studying phenotypes to studying in-depth mechanisms in recent decades. However, extrapolating cellular and molecular bases of aging from studying traditional model systems to humans has been challenging. The advent of organoids holds promise for overcoming the limitations of monolayer cell culture and bridging the gap between animal models and humans. Here, we mainly discuss recent paradigms for using organoid models in studying organ aging. Pluripotent stem cells–derived organoid provides a promising platform for simulating the pathophysiology of several aging-related diseases, especially neurodegenerative diseases, and adult stem cells organoids derived from different age groups have been applied to detect aging-related functional changes. We also assess the value of organoid model systems in understanding human aging and aging-related diseases, and identify challenges to be addressed in the future, such as the immaturity of organoids, and effective methods of inducing aging.

Villages around the world are gradually disappearing. Their cultural heritage needs to be not only protected but also transformed into an opportunity to develop historic villages. With the support of national policies, the conservation and development of historic villages have improved in China. In this study, a resource potential evaluation system and the associated criteria for the conservation of historic villages are established. Fourteen historic villages with different rates of development in the Guangzhou and Foshan Area, Guangdong province, China, are quantitatively evaluated, and the resource advantages and deficiencies of each village are analyzed. Furthermore, to identify a suitable development direction for historic villages, the various types of historic villages and their resource potentials are summarized, and corresponding development guidelines are posited.

IntroductionThe lower respiratory tract microbiome is widely studied to pinpoint microbial dysbiosis of diversity or abundance that is linked to a number of chronic respiratory illnesses. However, it is vital to clarify how the microbiome, through the release of microbial metabolites, impacts lung health and oncogenesis.MethodsIn order to discover the powerful correlations between microbial metabolites and disease, we collected, under electronic bronchoscopy examinations, samples of paired bronchoalveolar lavage fluids (BALFs) from tumor-burden lung segments and ipsilateral non-tumor sites from 28 lung cancer participants, further performing metagenomic sequencing, short-chain fatty acid (SCFA) metabolomics, and multiomics analysis to uncover the potential correlations of the microbiome and SCFAs in lung cancer.ResultsIn comparison to BALFs from normal lung segments of the same participant, those from lung cancer burden lung segments had slightly decreased microbial diversity in the lower respiratory tract. With 18 differentially prevalent microbial species, including the well-known carcinogens Campylobacter jejuni and Nesseria polysaccharea, the relative species abundance in the lower respiratory tract microbiome did not significantly differ between the two groups. Additionally, a collection of commonly recognized probiotic metabolites called short-chain fatty acids showed little significance in either group independently but revealed a strong predictive value when using an integrated model by machine learning. Multiomics also discovered particular species related to SCFAs, showing a positive correlation with Brachyspira hydrosenteriae and a negative one with Pseudomonas at the genus level, despite limited detection in lower airways. Of note, these distinct microbiota and metabolites corresponded with clinical traits that still required confirmation.ConclusionsFurther analysis of metagenome functional capacity revealed that genes encoding environmental information processing and metabolism pathways were enriched in the lower respiratory tract metagenomes of lung cancer patients, further supporting the oncogenesis function of various microbial species by different metabolites. These findings point to a potent relationship between particular components of the integrated microbiota-metabolites network and lung cancer, with implications for screening and diagnosis in clinical settings.

With intelligent terminal devices’ widespread adoption and global positioning systems’ advancement, Location-based Social Networking Services (LbSNs) have gained considerable attention. The recommendation mechanism, which revolves around identifying similar users, holds significant importance in LbSNs. In order to enhance user experience, LbSNs heavily rely on accurate data. By mining and analyzing users who exhibit similar behavioral patterns to the target user, LbSNs can offer personalized services that cater to individual preferences. However, trajectory data, a form encompassing various sensitive attributes, pose privacy concerns. Unauthorized disclosure of users’ precise trajectory information can have severe consequences, potentially impacting their daily lives. Thus, this paper proposes the Similar User Discovery Method based on Semantic Privacy (SUDM-SP) for trajectory analysis. The approach involves employing a model that generates noise trajectories, maximizing expected noise to preserve the privacy of the original trajectories. Similar users are then identified based on the published noise trajectory data. SUDM-SP consists of two key components. Firstly, a puppet noise location, exhibiting the highest semantic expectation with the original location, is generated to derive noise-suppressed trajectory data. Secondly, a mechanism based on semantic and geographical distance is employed to cluster highly similar users into communities, facilitating the discovery of noise trajectory similarity among users. Through trials conducted using real datasets, the effectiveness of SUDM-SP, as a recommendation service ensuring user privacy protection is substantiated.

In this paper, a uniform quantization design method for the parallel text DC-DC converter network control system (NCS) is proposed in combination with the sliding mode control (SMC) strategy to solve the problem that performing the system is poor because of the inability to process long signals in time. Taking the parallel buck converter as an example, first, the master-slave current sharing SM controller of the parallel buck converter is designed. Then, the NCS containing the designed SM controller is uniformly quantized in the continuous domain, and the stability performance of the system is analyzed according to the quantization error. Considering the parallel buck converter’s application in the digital control system, the discretization effect of the uniform quantization SMC system is studied using a text zero-order hold (ZOH), and the stability conditions of the discrete quantization system are given. Finally, the system’s state trajectories and output performances under different parameters in the continuous domain and discrete domain are analyzed by simulations, and the correctness and reliability of the uniform quantization SMC system designed in this paper are further verified by experiments.

The network security status assessment (NSSA) method can evaluate the network security status of cloud manufacturing systems (CMSs), which is of great significance to reduce the network security risk and loss of CMSs. At present, the NSSA of CMSs suitable for semiquantitative and uncertain information conditions is commonly used, which has certain limitations and low accuracy. This paper proposes an NSSA method for CMSs based on semiquantitative information. First, through the detailed analysis of the influencing factors of the network security status of the CMSs, the security evaluation indicators are selected, and the evaluation framework containing multilevel indicators is established by combining semiquantitative information. Second, the evaluation level is established according to the data distribution and the properties of the indicators. Third, a process of data fusion reasoning based on an evidential reasoning algorithm is designed, and a strong reference fusion case is given. Finally, the effectiveness of the proposed security state assessment algorithm in the NSSA of CMSs is verified and analyzed by simulation experiments. The experimental results show that the proposed method can make full use of semiquantitative information and uncertain information to evaluate the network security status of CMSs, and the evaluation results can reflect the actual security status of CMSs.

The internal mechanism of the high hydrophobicity of the coal samples from the Pingdingshan mining area was studied through industrial, element, and surface functional group analysis. Laboratory testing and molecular dynamics simulations were employed to study the impact of three types of surfactants on the surface adsorption properties and wettability of highly hydrophobic bituminous coal. The results show that the surface of highly hydrophobic bituminous coal is compact, rich in inorganic minerals, and poorly wettable and that coal molecules are dominated by hydrophobic functional groups of aromatic rings and aliphatic structures. The wetting performance of surfactants as the intermediate carrier to connect coal and water molecules is largely determined by the interaction force between surfactants and coal (Fs-c) and the interaction force between surfactants and water (Fs-w), which effectively improve the wettability of modified coal dust via modifying its surface electrical properties and surface energy. A new type of wetting agent with a dust removal rate of 89% has been developed through discovery of a compound wetting agent solution with optimal wetting and settling performance. This paper provides theoretical and technical support for removing highly hydrophobic bituminous coal dust in underground mining.

Abstract Aging is accompanied by the decline of organismal functions and a series of prominent hallmarks, including genetic and epigenetic alterations. These aging-associated epigenetic changes include DNA methylation, histone modification, chromatin remodeling, non-coding RNA (ncRNA) regulation, and RNA modification, all of which participate in the regulation of the aging process, and hence contribute to aging-related diseases. Therefore, understanding the epigenetic mechanisms in aging will provide new avenues to develop strategies to delay aging. Indeed, aging interventions based on manipulating epigenetic mechanisms have led to the alleviation of aging or the extension of the lifespan in animal models. Small molecule-based therapies and reprogramming strategies that enable epigenetic rejuvenation have been developed for ameliorating or reversing aging-related conditions. In addition, adopting health-promoting activities, such as caloric restriction, exercise, and calibrating circadian rhythm, has been demonstrated to delay aging. Furthermore, various clinical trials for aging intervention are ongoing, providing more evidence of the safety and efficacy of these therapies. Here, we review recent work on the epigenetic regulation of aging and outline the advances in intervention strategies for aging and age-associated diseases. A better understanding of the critical roles of epigenetics in the aging process will lead to more clinical advances in the prevention of human aging and therapy of aging-related diseases.

Urban heat islands (UHIs) aggravate urban heat stress and, therefore, exacerbate heat-related morbidity and mortality as global warming continues. Numerous studies used surface urban heat island intensity (SUHII) to quantify the change in the UHI effect and its drivers for heat mitigation. However, whether the variations in SUHII among cities can demonstrate the physical difference and fluctuation of the urban thermal environment is poorly understood. Here, we present a comparison study on the temporal trends of SUHII and LST in urban and nonurban areas in 13 cities of the Beijing–Tianjin–Hebei (BTH) megaregion in China and further identify different types of changes in SUHII based on the temporal trends of land surface temperature (LST) in urban and nonurban areas from 2000 to 2020. We also measured the effect of the changes in four socioecological factors (i.e., population density, vegetation greenness (EVI), GDP, and built-up area) on the trends of SUHII to understand the dynamic interaction between the UHI effect and socioecological development. We found the following. (1) Nine out of thirteen cities showed a significant increasing trend in SUHII, indicating that the SUHI effects have been intensified in most of the cities in the BTH megaregion. (2) The spatial pattern of summer mean SUHII and LST in urban areas varied greatly. Among the 13 cities, Beijing had the highest mean SUHII, but Handan had the highest urban temperature, which suggests that a city with stronger SUHII does not necessarily have a higher urban temperature or hazardous urban thermal environment. (3) Four types of changes in SUHII were identified in the 13 cities, which resulted from different temporal trends of LST in urban areas and nonurban areas. In particular, one type of increasing trend of SUHII in seven cities resulted from a greater warming trend (increasing LST) in urban than nonurban areas (SUHII↑1), and another type of increasing trend of SUHII in Beijing and Chengde was attributed to the warming trends (increasing LST) in urban areas and the cooling trends (decreasing LST) in nonurban areas (SUHII↑2). Meanwhile, the third type of increasing trend of SUHII in Zhangjiakou was due to a greater cooling (decreasing LST) trend in nonurban areas than in urban areas (SUHII↑3). In contrast, three cities with a decreasing trend of SUHII were caused by the increase in LST in urban and nonurban areas, but the warming trend in nonurban areas was greater than in urban areas (SUHII↓1). (4) Among the relationship between the trend of SUHII (TrendSUHII) and the changes in socioecological factors (Trendpopulation density, TrendGDP per captica, TrendEVI, and Trendbuild-up area), a significantly positive correlation between TrendSUHII and TrendEVI indicated that the change in SUHII was significantly related to an increased rate of EVI. This is mainly because increased vegetation in nonurban areas would result in lower temperatures in nonurban areas.

Phase-change nanodroplets (PCND;NDs) are emulsions with a perfluorocarbon (PFC) core that undergo acoustic vaporisation as a response to ultrasound (US). Nanodroplets change to microbubbles and cavitate while under the effect of US. This cavitation can apply forces on cell connections in biological barrier membranes, such as the blood–brain barrier (BBB), and trigger a transient and reversible increased permeability to molecules and matter. This study aims to present the preparation of lipid-based NDs and investigate their effects on the brain endothelial cell barrier in vitro. The NDs were prepared using the thin-film hydration method, followed by the PFC addition. They were characterised for size, cavitation (using a high-speed camera), and PFC encapsulation (using FTIR). The bEnd.3 (mouse brain endothelial) cells were seeded onto transwell inserts. Fluorescein with NDs and/or microbubbles were applied on the bEND3 cells and the effect of US on fluorescein permeability was measured. The Live/Dead assay was used to assess the BBB integrity after the treatments. Size and PFC content analysis indicated that the NDs were stable while stored. High-speed camera imaging confirmed that the NDs cavitate after US exposure of 0.12 MPa. The BBB cell model experiments revealed a 4-fold increase in cell membrane permeation after the combined application of US and NDs. The Live/Dead assay results indicated damage to the BBB membrane integrity, but this damage was less when compared to the one caused by microbubbles. This in vitro study shows that nanodroplets have the potential to cause BBB opening in a similar manner to microbubbles. Both cavitation agents caused damage on the endothelial cells. It appears that NDs cause less cell damage compared to microbubbles.

The generalized Maxwell (GM) constitutive model has been widely applied to characterize the viscoelastic properties of asphalt mixtures. The parameters (Prony series) of the GM are usually obtained via interconversion between a dynamic modulus and relaxation modulus, and they are then input to a finite element model (FEM) as viscoelastic parameters. However, the dynamic modulus obtained with the common loading mode only provides the compressive and tensile properties of materials. Whether the compression or tensile modulus can represent the shear properties of materials related to flow rutting is still open to discussion. Therefore, this study introduced a novel method that integrates the Kriging model into the genetic algorithm as a surrogate model to determine the viscoelastic parameters of an asphalt mixture in rutting research. Firstly, a wheel tracking test (WTT) for AC-13 was conducted to clarify the flow rutting development mechanism. Secondly, two sets of the AC-13 viscoelastic parameters obtained through the optimization method and the dynamic modulus were used as inputs into the FEM simulation of the WTT to compare the simulation results. Finally, a sensitivity analysis of viscoelastic parameters was performed to improve the efficiency of parameter optimization. The results indicating the viscoelastic parameters obtained by this method could precisely characterize the development law of flow rutting in asphalt mixtures.

In order to explore the applicability of different cementitious paste systems used for massive concrete structures, the hydration characteristics and mechanism of the binary and ternary cementitious paste systems in Portland cement pastes containing fly ash and slag were investigated in this work. The hydration heat release rate and cumulative heat release of each cementitious paste system at 20 ℃ and 60 ℃ were measured by an isothermal calorimeter. The characteristic parameters of each cementitious paste system hydration process were calculated and analyzed using the Knudsen equation and Krstulović-Dabić hydration kinetic model. Besides, the hydration mechanism was analyzed. It was obtained that the cement-fly ash (C-F) binary system is not effective in reducing the early reaction rate but its overall heat release is lower; while, the cement-slag (C-S) binary system is more effective in reducing the reaction rate but its overall heat release is higher, and the cement-fly ash-slag (C-F-S) ternary system has the advantages of both above binary systems. Probably, the C-F-S ternary system is more consistent with the heating characteristics of massive concrete structures, and it is more applicable. There are few studies on the hydration characteristics of C-F-S ternary systems from the perspective of hydration kinetic, and this work provides theoretical basis for the selection of cementitious paste systems for massive concrete structures.

Phase-change nanodroplets have attracted increasing interest in recent years as ultrasound theranostic nanoparticles. They are smaller compared to microbubbles and they may distribute better in tissues (e.g. in tumours). They are composed of a stabilising shell and a perfluorocarbon core. Nanodroplets can vaporise into echogenic microbubbles forming cavitation nuclei when exposed to ultrasound. Their perfluorocarbon core phase-change is responsible for the acoustic droplet vaporisation. However, methods to quantify the perfluorocarbon core in nanodroplets are lacking. This is an important feature that can help explain nanodroplet phase change characteristics. In this study, we fabricated nanodroplets using lipids shell and perfluorocarbons. To assess the amount of perfluorocarbon in the core we used two methods, 19F NMR and FTIR. To assess the cavitation after vaporisation we used an ultrasound transducer (1.1 MHz) and a high-speed camera. The 19F NMR based method showed that the fluorine signal correlated accurately with the perfluorocarbon concentration. Using this correlation, we were able to quantify the perfluorocarbon core of nanodroplets. This method was used to assess the content of the perfluorocarbon of the nanodroplets in solutions over time. It was found that perfluoropentane nanodroplets lost their content faster and at higher ratio compared to perfluorohexane nanodroplets. The high-speed imaging indicates that the nanodroplets generate cavitation comparable to that from commercial contrast agent microbubbles. Nanodroplet characterisation should include perfluorocarbon concentration assessment as critical information for their development.

To investigate the fatigue and freeze-thaw properties of the geotextile isolation layer in CRTS III ballastless track, a new type of disc multi-point load distribution device was manufactured. The experimental study was carried out on the geotextile isolation layer subjected to the fatigue load and freeze-thaw cycles. The results showed that the mechanical properties of the geotextile isolation layers were affected by the harsh environment and cyclic load. With the increase of fatigue loading cycles, the dynamic stiffness of the geotextile isolation layers increased and tended to be stable, and the nonlinear performance of the geotextile isolation layer gradually weakened. The freeze-thaw cycle greatly influenced the dynamic stiffness of the geotextile isolation layer compared with the fatigue loadings, and the freeze-thaw cycle action could accelerate the elastic loss of the geotextile isolation layer. Under the fatigue load and freeze-thaw cycles, the tensile strength of the geotextile isolation layer decreased and caused damage to the geotextile isolation layers, which should be paid attention to in long-term service.

The concrete hydration heat and different construction methods directly affects the early crack resistance of massive concrete structures and may lead to concrete cracks. In this work, the hydration heat test and finite element simulation were conducted to investigate the early cracking resistance and the main influencing factors of the massive concrete bridge pier. The size of the bridge pier was 8 m (length) × 4 m (width) × 22.5 m (height), and the pier was poured in two layers (8.5 m/14 m) with an interval of 37 h. The internal temperature of the pier was tested 16 days after the concrete pouring using pre-buried temperature sensors, and the crack expansion on the surface of the pier was continuously observed during the test period. The test obtained a maximum concrete temperature of 64.25 °C after 100 h after the concrete pouring, and 3 cracks were found on the surface of the pier. The pier simulation model is established according to the actual situation in the test, The maximum temperature inside the bridge pier obtained from the simulation is 61.73 ℃, and the temperature field development pattern and the crack expansion on the pier surface were basically consistent with the test, which confirmed the reliability of the simulation method. Besides, the simulation process found that the maximum main tensile stress on the surface of the bridge pier was 2.77 MPa, which was mainly distributed near the interface of the 2 layers, indicating that the layered pouring scheme adopted in the test was improper. The effect of layered casting schemes on the early cracking resistance of massive concrete has rarely been discussed, and further simulations revealed that: the maximum main tensile stress can be reduced by gradually improving the number of layers, layer height and interval between each layer. By changing the original layered pouring scheme to 3 layers with an interval of 3 days between each layer, the maximum principal tensile stress is reduced to 1.50 MPa, and early cracking of the bridge pier can be avoided. This work provides a general numerical analysis method with high accuracy, parameterization and quantification for early crack control of massive concrete structures in a multi-factor complex environment.

With the rapid development of high-speed mobile network technology and high-precision positioning technology, the trajectory information of mobile users has received extensive attention from academia and industry in the field of Location-based Social Networks. Researchers can mine users’ trajectories in Location-based Social Networks to obtain sensitive information, such as friendship groups, activity patterns, and consumption habits. Therefore, mobile users’ privacy and security issues have received growing attention in Location-based Social networks. It is crucial to strike a balance between privacy protection and data availability. This paper proposes a differential privacy trajectory protection method based on latent interest community detection (DPTP-LICD), ensuring strict privacy protection standards and user data availability. Firstly, based on the historical trajectory information of users, spatiotemporal constraint information is extracted to construct a potential community strength model for mobile users. Secondly, the latent interest community obtained from the analysis is used to identify preferred hot spots on the user’s trajectory, and their priorities are assigned based on a popularity model. A reasonable privacy budget is allocated to prevent excessive noise from being added and rendering the protected trajectory data unusable. Finally, to prevent privacy leakage, we add Laplace and exponential noise in generating preferred hot spots and recommending user interest points. Security and effectiveness analysis shows that our mechanism provides effective points of interest recommendations and protects users’ privacy from disclosure.

Abstract We study a “conjugate” transform on matrix spaces. For Laurent/Toeplitz operators such a transform is a way of realizing the Hilbert transform on the torus. We establish its operator norm on Schatten classes and discuss the possibility of its boundedness upon permutations. Applications in the Rademacher–Menshov inequality and iterative methods are also included.

Due to the high reactivity between the lithium metal and traditional organic liquid electrolyte, the reaction of lithium metal electrode is usually uneven and there are also unexpected side reactions. Therefore, construction of a stable solid electrolyte interface (SEI) is highly essential to improve the performance of lithium metal anode. Herein, a sandwich-like gel polymer electrolyte (GPE) is accurately prepared by in-situ polymerization of Polyacrylonitrile (PAN) nanofiber membrane with trihydroxymethylpropyl trimethylacrylate (TMPTMA) and 1,6-hexanediol diacrylate (HDDA). The resulting GPE with a tightly cross-linked gel skeleton exhibits high ionic conductivity and electrochemical window of 5.6 V versus Li/Li+. In particular, the pretreatment of Li metal anode can improve the interfacial wettability, and the synergy of the chemically pretreated Li metal anode surface and the GPE can electrochemically in situ generate SEI with compositionally stable and fluorine-rich inorganic components. Owing to these unique advantages, the interfacial compatibility between the GPE and lithium metal is greatly improved. Meanwhile, the formed SEI can inhibit the formation of lithium dendrites, and decomposition of GPE would be alleviated. The assembled Li-FEC|GPE|LiFePO4 full cell shows a high initial discharge capacity of 157.1 mA h g−1, and maintains a capacity retention of 92.3% after 100 cycles at 0.2C.

Abstract Purpose We develop a new risk score to predict patients with stroke-associated pneumonia (SAP) who have an acute intracranial hemorrhage (ICH). Method We applied logistic regression to develop a new risk score called ICH-LR2S2. It was derived from examining a dataset of 70,540 ICH patients between 2015 and 2018 from the Chinese Stroke Center Alliance (CSCA). During the training of ICH-LR2S2, patients were randomly divided into two groups – 80% for the training set and 20% for model validation. A prospective test set was developed using 12,523 patients recruited in 2019. To further verify its effectiveness, we tested ICH-LR2S2 on an external dataset of 24,860 patients from the China National Stroke Registration Management System II (CNSR II). The performance of ICH-LR2S2 was measured by the area under the receiver operating characteristic curve (AUROC). Results The incidence of SAP in the dataset was 25.52%. A 24-point ICH-LR2S2 was developed from independent predictors, including age, modified Rankin Scale, fasting blood glucose, National Institutes of Health Stroke Scale admission score, Glasgow Coma Scale score, C-reactive protein, dysphagia, Chronic Obstructive Pulmonary Disease, and current smoking. The results showed that ICH-LR2S2 achieved an AUC = 0.749 [95% CI 0.739–0.759], which outperforms the best baseline ICH-APS (AUC = 0.704) [95% CI 0.694–0.714]. Compared with the previous ICH risk scores, ICH-LR2S2 incorporates fasting blood glucose and C-reactive protein, improving its discriminative ability. Machine learning methods such as XGboost (AUC = 0.772) [95% CI 0.762–0.782] can further improve our prediction performance. It also performed well when further validated by the external independent cohort of patients (n = 24,860), ICH-LR2S2 AUC = 0.784 [95% CI 0.774–0.794]. Conclusion ICH-LR2S2 accurately distinguishes SAP patients based on easily available clinical features. It can help identify high-risk patients in the early stages of diseases.

BackgroundLiver transplantation (LT) is one of the most effective treatment modalities for hepatocellular carcinoma (HCC), but patients with HCC recurrence after LT always have poor prognosis. This study aimed to evaluate the predictive value of the gamma-glutamyl transpeptidase-to-lymphocyte ratio (GLR) and systemic immune-inflammation index (SII) in terms of HCC recurrence after LT, based on which we developed a more effective predictive model.MethodsThe clinical data of 325 HCC patients who had undergone LT were collected and analyzed retrospectively. The patients were randomly divided into a development cohort (n = 215) and a validation cohort (n = 110). Cox regression analysis was used to screen the independent risk factors affecting postoperative recurrence in the development cohort, and a predictive model was established based on the results of the multivariate analysis. The predictive values of GLR, SII and the model were evaluated by receiver operating characteristic (ROC) curve analysis, which determined the cut-off value for indicating patients’ risk levels. The Kaplan-Meier survival analysis and the competing-risk regression analysis were used to evaluate the predictive performance of the model, and the effectiveness of the model was verified further in the validation cohort.ResultsThe recurrence-free survival of HCC patients after LT with high GLR and SII was significantly worse than that of patients with low GLR and SII (P

Photodynamic therapy (PDT) provides an effective therapeutic option for different types of cancer in addition to surgery, radiation, and chemotherapy. The treatment outcome of PDT is largely determined by both the light and dark toxicity of photosensitizers (PSs), which can be technically improved with the assistance of a drug delivery system, especially the nanocarriers. Toluidine blue (TB) is a representative PS that demonstrates high PDT efficacy; however, its application is largely limited by the associated dark toxicity. Inspired by TB’s noncovalent binding with nucleic acids, in this study, we demonstrated that DNA nanogel (NG) could serve as an effective TB delivery vehicle to facilitate anticancer PDT. The DNA/TB NG was constructed by the simple self-assembly between TB and short DNA segments using cisplatin as a crosslinker. Compared with TB alone, DNA/TB NG displayed a controlled TB-releasing behavior, effective cellular uptake, and phototoxicity while reducing the dark toxicity in breast cancer cells MCF-7. This DNA/TB NG represented a promising strategy to improve TB-mediated PDT for cancer treatments.

Characterizing the optimal fMRI paradigms for detecting behaviorally relevant functional connectivity (FC) patterns is a critical step to furthering our knowledge of the neural basis of behavior. Previous studies suggested that FC patterns derived from task fMRI paradigms, which we refer to as task-based FC, are better correlated with individual differences in behavior than resting-state FC, but the consistency and generalizability of this advantage across task conditions was not fully explored. Using data from resting-state fMRI and three fMRI tasks from the Adolescent Brain Cognitive Development Study ® (ABCD), we tested whether the observed improvement in behavioral prediction power of task-based FC can be attributed to changes in brain activity induced by the task design. We decomposed the task fMRI time course of each task into the task model fit (the fitted time course of the task condition regressors from the single-subject general linear model) and the task model residuals, calculated their respective FC, and compared the behavioral prediction performance of these FC estimates to resting-state FC and the original task-based FC. The FC of the task model fit was better than the FC of the task model residual and resting-state FC at predicting a measure of general cognitive ability or two measures of performance on the fMRI tasks. The superior behavioral prediction performance of the FC of the task model fit was content-specific insofar as it was only observed for fMRI tasks that probed similar cognitive constructs to the predicted behavior of interest. To our surprise, the task model parameters, the beta estimates of the task condition regressors, were equally if not more predictive of behavioral differences than all FC measures. These results showed that the observed improvement of behavioral prediction afforded by task-based FC was largely driven by the FC patterns associated with the task design. Together with previous studies, our findings highlighted the importance of task design in eliciting behaviorally meaningful brain activation and FC patterns.

Aiming to investigate the non-uniform temperature distribution of the steel-concrete composite box girder-ballastless track system induced by the time-varying solar radiation, the ray-tracing algorithm was used to calculate the environmental parameters. The segment finite element model (SFEM) for spatial interaction between the bridge and the ballastless track was used to perform several numerical simulations. The temperature variation induced by solar radiation was evaluated based on the numerical simulations. The results showed that the peak temperature of the system (on the western side of the steel web) was 49.59 Co (at 16:00). Regarding time-varying solar temperature distribution of the steel-concrete composite box girder-ballastless track system, a difference was found between the western and eastern sides of the steel webs. Finally, the vertical temperature gradient model of the steel-concrete composite box girder-ballastless track system was established according to the most unfavorable temperature. The results provided a reference for constructing and maintaining a steel-concrete composite box girder equipped with the ballastless track.

This paper proposes a method called Grouped Contrastive Learning of self-supervised Sentence Representation (GCLSR), which can learn an effective and meaningful representation of sentences. Previous works maximize the similarity between two vectors to be the objective of contrastive learning, suffering from the high-dimensionality of the vectors. In addition, most previous works have adopted discrete data augmentation to obtain positive samples and have directly employed a contrastive framework from computer vision to perform contrastive training, which could hamper contrastive training because text data are discrete and sparse compared with image data. To solve these issues, we design a novel framework of contrastive learning, i.e., GCLSR, which divides the high-dimensional feature vector into several groups and respectively computes the groups’ contrastive losses to make use of more local information, eventually obtaining a more fine-grained sentence representation. In addition, in GCLSR, we design a new self-attention mechanism and both a continuous and a partial-word vector augmentation (PWVA). For the discrete and sparse text data, the use of self-attention could help the model focus on the informative words by measuring the importance of every word in a sentence. By using the PWVA, GCLSR can obtain high-quality positive samples used for contrastive learning. Experimental results demonstrate that our proposed GCLSR achieves an encouraging result on the challenging datasets of the semantic textual similarity (STS) task and transfer task.

Wildfire is one of the main hazards affecting large areas and causes great damage all over the world, and the rapid development of the wildland-urban interface (WUI) increases the threat of wildfires that have ecological, social, and economic consequences. As one of the most widely used methods for tracking fire, remote sensing can provide valuable information about fires, but it is not always available, and needs to be supplemented by data from other sources. Social media is an emerging but underutilized data source for emergency management, contains a wealth of disaster information, and reflects the public’s real-time witness and feedback to fires. In this paper, we propose a fusion framework of multi-source data analysis, including social media data and remote sensing data, cellphone signaling data, terrain data, and meteorological data to track WUI fires. Using semantic web technology, the framework has been implemented as a Knowledge Base Service and runs on top of WUIFire ontology. WUIFire ontology represents WUI fire–related knowledge and consists of three modules: system, monitoring, and spread, and tracks wildfires happening in WUIs. It provides a basis for tracking and analyzing a WUI fire by fusing multi-source data. To showcase the utility of our approach in a real-world scenario, we take the fire in the Yaji Mountain Scenic Area, Beijing, China, in 2019 as a case study. With object information identified from remote sensing, fire situation information extracted from Weibo, and fire perimeters constructed through fire spread simulation, a knowledge graph is constructed and an analysis using a semantic query is carried out to realize situational awareness and determine countermeasures. The experimental results demonstrate the benefits of using a semantically improved multi-source data fusion framework for tracking WUI fire.

Abstract Regenerative capacity declines throughout evolution and with age. In this study, we asked whether metabolic programs underlying regenerative capability might be conserved across species, and if so, whether such metabolic drivers might be harnessed to promote tissue repair. To this end, we conducted metabolomic analyses in two vertebrate organ regeneration models: the axolotl limb blastema and antler stem cells. To further reveal why young individuals have higher regenerative capacity than the elderly, we also constructed metabolic profiles for primate juvenile and aged tissues, as well as young and aged human stem cells. In joint analyses, we uncovered that active pyrimidine metabolism and fatty acid metabolism correlated with higher regenerative capacity. Furthermore, we identified a set of regeneration-related metabolite effectors conserved across species. One such metabolite is uridine, a pyrimidine nucleoside, which can rejuvenate aged human stem cells and promote regeneration of various tissues in vivo. These observations will open new avenues for metabolic intervention in tissue repair and regeneration.

Mitochondrial dysfunction is a hallmark feature of cellular senescence and organ aging. Here, we asked whether the mitochondrial antiviral signaling protein (MAVS), which is essential for driving antiviral response, also regulates human stem cell senescence. To answer this question, we used CRISPR/Cas9-mediated gene editing and directed differentiation techniques to generate various MAVS-knockout human stem cell models. We found that human mesenchymal stem cells (hMSCs) were sensitive to MAVS deficiency, as manifested by accelerated senescence phenotypes. We uncovered that the role of MAVS in maintaining mitochondrial structural integrity and functional homeostasis depends on its interaction with the guanosine triphosphatase optic atrophy type 1 (OPA1). Depletion of MAVS or OPA1 led to the dysfunction of mitochondria and cellular senescence, whereas replenishment of MAVS or OPA1 in MAVS-knockout hMSCs alleviated mitochondrial defects and premature senescence phenotypes. Taken together, our data underscore an uncanonical role of MAVS in safeguarding mitochondrial homeostasis and antagonizing human stem cell senescence.

Exercise benefits the whole organism, yet, how tissues across the body orchestrally respond to exercise remains enigmatic. Here, in young and old mice, with or without exercise, and exposed to infectious injury, we characterized the phenotypic and molecular adaptations to a 12-month exercise across 14 tissues/organs at single-cell resolution. Overall, exercise protects tissues from infectious injury, although more effectively in young animals, and benefits aged individuals in terms of inflammaging suppression and tissue rejuvenation, with structural improvement in the central nervous system and systemic vasculature being the most prominent. In vascular endothelial cells, we found that readjusting the rhythmic machinery via the core circadian clock protein BMAL1 delayed senescence and facilitated recovery from infectious damage, recapitulating the beneficial effects of exercise. Our study underscores the effect of exercise in reconstituting the youthful circadian clock network and provides a foundation for further investigating the interplay between exercise, aging, and immune challenges across the whole organism.

Urban forests can provide temperature regulation service (TRS) by lowering the local temperature and further mitigating the urban heat island effect. Numerous studies have focused on how to better realize or enhance the cooling function of urban forests, but have not considered that from the perspective of supply and demand. Here, we develop a framework to quantify the supply and demand of temperature regulation service provided by urban forests, using remote sensing, meteorological and socio-economic data. Taking Shenzhen city as a case study, we analyzed the spatial distribution of both TRS supply and demand as well as their relationship in Shenzhen. We found: 1) TRS supply varied greatly in space, with areas of high supply generally located in the southeast of Shenzhen, which is mainly covered by forests, and around the boundaries of administrative districts that are distant from the urban centers. 2) TRS demand had even more significant spatial heterogeneity, showing that high-demand areas were primarily distributed in the southwest but occupied a relatively small amount of land in Shenzhen. We then categorized the spatial relationship between TRS supply and demand into four types, and identified the hotspots of highly mismatched supply and demand of TRS. Targeted urban forests planning and management measures were further proposed for each type of region. This study provides spatial tools and insights for urban forests design and planning towards better urban heat mitigation and adaptation.

Natural habitats transformed to city or countryside with human activities of different intensities have reshaped regional and global landscapes, especially in those rapid developed low- and mid-income countries, like China. China’s rapid shift in urban and rural expansion, which are greater than and equal to, and below county-level’s artificial land expansion, and reduction in farmland and ecological land are important for determining future urban and rural development under the conservation and protection of farmland and ecosystems; however, such an understanding is still inadequate. Here, we show that both urban and rural expansions have encroached on farmland and ecological land since 1980; rural areas, with 1.33 km2 × 105 km2 in 2020, remain larger than urban areas, with 0.97 km2 × 105 km2 in 2020. However, urban areas (1857.5 km2/year) increased faster than rural areas (695.0 km2/year) during 1980–2020, rural expansion primarily occurred in the 1980s and 1990s, and urban expansion primarily occurred after 2000 especially 2000s. Farmland is the major land cover that has been occupied by urban and rural expansion for 53.7 and 39.1 thousand km2, especially in East China’s densely populated areas. And, both farmland and ecological land were primarily encroached during 2000s. Our results demonstrate imbalanced urban and rural expansion and encroachment on farmland and ecological land; thus, both forms of encroachment should be optimized at the regional scale based on the socioeconomic needs and natural conditions, and diverse policies can be designed to support local sustainable development.