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Vegetation greening has long been acknowledged, but recent studies have pointed out that vegetation greening is possibly stalled or even reversed. However, detailed analyses about greening reversal or increased browning of vegetation remain scarce. In this study, we utilized the normalized difference vegetation index (NDVI) as an indicator of vegetation to investigate the trends of vegetation greening and browning (monotonic, interruption, and reversal) through the breaks for the additive season and trend (BFAST) method across China’s drylands from 1982 to 2022. It also reveals the impacts of ecological restoration programs (ERPs) and climate change on these vegetation trends. We find that the vegetation displays an obvious pattern of east-greening and west-browning in China’s drylands. Greening trends mainly exhibits monotonic greening (29.8 %) and greening with setback (36.8 %), whereas browning shows a greening to browning reversal (19.2 %). The increase rate of greening to browning reversal is 0.0342/yr, which is apparently greater than that of greening with setback, 0.0078/yr. This research highlights that, under the background of widespread vegetation greening, vegetation browning is progressively increasing due to the effects of climate change. Furthermore, the ERPs have significantly increased vegetation coverage, with the increase rate in 2000–2022 being twice as much as that of 1982–1999 in revegetation regions. Vegetation browning in southwestern Qingzang Plateau is primarily driven by adverse climatic factors and anthropogenic disturbances, which offset the efforts of ERPs.

Abstract The world’s oceans are under threat from the prevalence of heatwaves caused by climate change. Despite this, there is a lack of understanding regarding their impact on seawater oxygen levels - a crucial element in sustaining biological survival. Here, we find that heatwaves can trigger low-oxygen extreme events, thereby amplifying the signal of deoxygenation. By utilizing in situ observations and state-of-the-art climate model simulations, we provide a global assessment of the relationship between the two types of extreme events in the surface ocean (0–10 m). Our results show compelling evidence of a remarkable surge in the co-occurrence of marine heatwaves and low-oxygen extreme events. Hotspots of these concurrent stressors are identified in the study, indicating that this intensification is more pronounced in high-biomass regions than in those with relatively low biomass. The rise in the compound events is primarily attributable to long-term warming primarily induced by anthropogenic forcing, in tandem with natural internal variability modulating their spatial distribution. Our findings suggest the ocean is losing its breath under the influence of heatwaves, potentially experiencing more severe damage than previously anticipated.

The global COVID-19 pandemic has severely impacted human health and socioeconomic development, posing an enormous public health challenge. Extensive research has been conducted into the relationship between environmental factors and the transmission of COVID-19. However, numerous factors influence the development of pandemic outbreaks, and the presence of confounding effects on the mechanism of action complicates the assessment of the role of environmental factors in the spread of COVID-19. Direct estimation of the role of environmental factors without removing the confounding effects will be biased. To overcome this critical problem, we developed a Double Machine Learning (DML) causal model to estimate the debiased causal effects of the influencing factors in the COVID-19 outbreaks in Chinese cities. Comparative experiments revealed that the traditional multiple linear regression model overestimated the impact of environmental factors. Environmental factors are not the dominant cause of widespread outbreaks in China in 2022. In addition, by further analyzing the causal effects of environmental factors, it was verified that there is significant heterogeneity in the role of environmental factors. The causal effect of environmental factors on COVID-19 changes with the regional environment. It is therefore recommended that when exploring the mechanisms by which environmental factors influence the spread of epidemics, confounding factors must be handled carefully in order to obtain clean quantitative results. This study offers a more precise representation of the impact of environmental factors on the spread of the COVID-19 pandemic, as well as a framework for more accurately quantifying the factors influencing the outbreak.

At the altitude of low-Earth-orbiting satellites, most details of lithospheric magnetic anomalies observed near surface are attenuated, and only slowly decaying long-wavelength magnetic anomalies can be detected. Long-wavelength magnetic anomalies are generated by large-scale magnetized rocks in the Earth's crust and uppermost mantle at depths shallower than the Curie depth. Interpretation of such lithospheric magnetic anomalies has been used in geological mapping, crustal composition and structure studies, plate tectonic reconstruction, and geodynamics. To introduce the origin of long-wavelength magnetic anomalies at a global scale, we first reviewed satellite magnetic anomaly maps in early periods and calculated anomaly maps using four main lithospheric magnetic field models, including the CHAOS-7, CM6, MF7, and CSES models. Then, based on the result of the CHAOS-7 model at 500 km altitude, 29 long-wavelength magnetic anomalies with amplitudes greater than 4 nT were identified and their geological origins were reviewed. Among these, there were twenty magnetic anomalies over continents and nine over the ocean. The long-wavelength magnetic anomalies over continental areas were mostly located in Precambrian basements related to the Archean nuclei, Proterozoic terrane, and iron-rich formations, with a few located in the orogenic background. The long-wavelength magnetic anomalies in the ocean region were all located in oceanic plateau, generally related to the breakup of Gondwana during the Cretaceous Period, and have the characteristics of thickened crust. Hence, the long-wavelength magnetic anomalies reveal a significant magnetization difference in the deep crust during crustal growth, a key issue that requires further study. Compared to satellite magnetic surveys in some other nations, detecting lithospheric magnetic anomalies by satellite started relatively late in China. The China Seismo-Electromagnetic Satellite (CSES) was launched in February 2018. It was China's first satellite designed to monitor earthquakes with multiple geophysical payloads, including magnetometers capable of measuring weak signals from the lithosphere. The Macau Science Satellite-1 (MSS-1) was launched in 2023 and is specially used for monitoring the geomagnetic field in low latitudes. Furthermore, a subsequent CSES-02 satellite is planned to be launched in 2024. With the vigorous development of satellite magnetic surveys in China, it is expected that progressively more Chinese researchers will pay attention to long-wavelength magnetic anomalies and promote the study of their origin.

Abstract The architecture of magma plumbing systems plays a fundamental role in volcano eruption and evolution. However, the precise configuration of crustal magma reservoirs and conduits responsible for supplying eruptions are difficult to explore across most active volcanic systems. Consequently, our understanding of their correlation with eruption dynamics is limited. Axial Seamount is an active submarine volcano located along the Juan de Fuca Ridge, with known eruptions in 1998, 2011, and 2015. Here we present high-resolution images of P-wave velocity, attenuation, and estimates of temperature and partial melt beneath the summit of Axial Seamount, derived from multi-parameter full waveform inversion of a 2D multi-channel seismic line. Multiple magma reservoirs, including a newly discovered western magma reservoir, are identified in the upper crust, with the maximum melt fraction of ~15–32% in the upper main magma reservoir (MMR) and lower fractions of 10% to 26% in other satellite reservoirs. In addition, a feeding conduit below the MMR with a melt fraction of ~4–11% and a low-velocity throat beneath the eastern caldera wall connecting the MMR roof with eruptive fissures are imaged. These findings delineate an asymmetric shallow plumbing system beneath Axial Seamount, providing insights into the magma pathways that fed recent eruptions.

Coronavirus disease 2019 (COVID-19) is a severe global public health emergency that has caused a major crisis in the safety of human life, health, global economy, and social order. Moreover, COVID-19 poses significant challenges to healthcare systems worldwide. The prediction and early warning of infectious diseases on a global scale are the premise and basis for countries to jointly fight epidemics. However, because of the complexity of epidemics, predicting infectious diseases on a global scale faces significant challenges. In this study, we developed the second version of Global Prediction System for Epidemiological Pandemic (GPEP-2), which combines statistical methods with a modified epidemiological model. The GPEP-2 introduces various parameterization schemes for both impacts of natural factors (seasonal variations in weather and environmental impacts) and human social behaviors (government control and isolation, personnel gathered, indoor propagation, virus mutation, and vaccination). The GPEP-2 successfully predicted the COVID-19 pandemic in over 180 countries with an average accuracy rate of 82.7%. It also provided prediction and decision-making bases for several regional-scale COVID-19 pandemic outbreaks in China, with an average accuracy rate of 89.3%. Results showed that both anthropogenic and natural factors can affect virus spread and control measures in the early stages of an epidemic can effectively control the spread. The predicted results could serve as a reference for public health planning and policymaking.

Corona virus disease 2019 (COVID-19) has exerted a profound adverse impact on human health. Studies have demonstrated that aerosol transmission is one of the major transmission routes of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Pathogenic microorganisms such as SARS-CoV-2 can survive in the air and cause widespread infection among people. Early monitoring of pathogenic microorganism transmission in the atmosphere and accurate epidemic prediction are the frontier guarantee for preventing large-scale epidemic outbreaks. Monitoring of pathogenic microorganisms in the air, especially in densely populated areas, may raise the possibility to detect viruses before people are widely infected and contain the epidemic at an earlier stage. The multi-scale coupled accurate epidemic prediction system can provide support for governments to analyze the epidemic situation, allocate health resources, and formulate epidemic response policies. This review first elaborates on the effects of the atmospheric environment on pathogenic microorganism transmission, which lays a theoretical foundation for the monitoring and prediction of epidemic development. Secondly, the monitoring technique development and the necessity of monitoring pathogenic microorganisms in the atmosphere are summarized and emphasized. Subsequently, this review introduces the major epidemic prediction methods and highlights the significance to realize a multi-scale coupled epidemic prediction system by strengthening the multidisciplinary cooperation of epidemiology, atmospheric sciences, environmental sciences, sociology, demography, etc. By summarizing the achievements and challenges in monitoring and prediction of pathogenic microorganism transmission in the atmosphere, this review proposes suggestions for epidemic response, namely, the establishment of an integrated monitoring and prediction platform for pathogenic microorganism transmission in the atmosphere.

Abstract Background Osteoporosis is characterized by an imbalance in bone homeostasis, resulting in the excessive dissolution of bone minerals due to the acidified microenvironment mediated by overactive osteoclasts. Oroxylin A (ORO), a natural flavonoid, has shown potential in reversing osteoporosis by inhibiting osteoclast-mediated bone resorption. The limited water solubility and lack of targeting specificity hinder the effective accumulation of Oroxylin A within the pathological environment of osteoporosis. Results Osteoclasts’ microenvironment-responsive nanoparticles are prepared by incorporating Oroxylin A with amorphous calcium carbonate (ACC) and coated with glutamic acid hexapeptide-modified phospholipids, aiming at reinforcing the drug delivery efficiency as well as therapeutic effect. The obtained smart nanoparticles, coined as OAPLG, could instantly neutralize acid and release Oroxylin A in the extracellular microenvironment of osteoclasts. The combination of Oroxylin A and ACC synergistically inhibits osteoclast formation and activity, leading to a significant reversal of systemic bone loss in the ovariectomized mice model. Conclusion The work highlights an intelligent nanoplatform based on ACC for spatiotemporally controlled release of lipophilic drugs, and illustrates prominent therapeutic promise against osteoporosis.

As one of the main seismic imaging methods, conventional reverse time migration (RTM) may not produce high-quality images in areas with non-flat surfaces and anisotropy because the complex surfaces have a great impact on seismic wave simulation, resulting in strong scattering waves. In addition, in isotropic acoustic (ISO) RTM, the neglection of the anisotropic effects will lead to incorrect travel times during source and receiver wavefield extrapolation. To overcome these problems, we develop a topographic pseudo-acoustic vertical transverse isotropic (VTI) RTM algorithm based on the body-fitted grid. In this method, we first derive anisotropic pseudo-acoustic wave equations in the curvilinear coordinate system. Then, the Lebedev grid finite-difference scheme is used to update these equations to simulate wavefields. Finally, we use the source-normalized cross-correlation imaging condition to realize RTM. Numerical tests are performed to evaluate the feasibility and applicability of the proposed method. The imaging results show that the proposed method can remove the effect of surface topography and anisotropy on seismic wave propagation and improve migration imaging precision.

Abstract Climate change is creating a new era of infectious disease crises, further exacerbated by extreme weather. However, the relationship between extreme weather and infectious disease remain unclear. Here, we provide a new quantitative study on the impact of cold wave on COVID‐19 as an example. We found that during cold waves, extreme cold temperatures coupled with rapid aerosol transport accelerated COVID‐19 outbreaks. It directly increased the number of COVID‐19 cases in Beijing by 28.1% in the winter of year 2022. More urgently, cold temperatures led to a higher risk of death during infectious disease outbreaks, with a 7.07% increase in confirmed deaths and a 16.61% increase in excess mortality. Our findings emphasize the urgent need to promote a synergistic policy for responding to infectious diseases during cold wave disasters in order to minimize the risk of death among the elderly and those with underlying diseases.

Located in Douala V (Cameroon), Makepé Missoké is a lowland area that is influenced by the Tongo Bassa and Ngongué rivers. The site has a closed dumpsite, that operated from the 1975’s to 2003 for the disposal and storage of domestic waste produced in Douala. Geoelectric profiling (ERT) coupled with seismo-electric imaging was used to characterize the shallow aquifer of the Douala subbasin and map subsurface pollution. Fourteen geoelectrical profiles were deployed between June and August 2018 and March 2019. Along these lines, 49 sets of seismo-electric point data were collected in December 2021. A total of 118 wells drilled (2018) were used to obtain water level and topographic data. The aquifer geometry, hydraulic characteristics, permeability, lithology and leachate plume extent were determined. This survey enables us to visualize waste infiltration and migration within Makepé. The drilled wells indicate that the main lithologies observed are clay, sandy clay, sand, clayey sand and gravel. The leachate plume observed after processing the electric profiles had a resistivity signature of ≤ 10 Ωm, and high electrical conductivity are observed in some wells. The leachate migrates within the subsurface along a northwest‒southwest trend, where ground water pollution is observed due to leachate infiltration. This infiltration resulted in poor water quality indices in some collected samples. Such pollution is common in unconfined aquifers (< 50 m) due to the absence of a confining layer at the landfill. An increase in resistivity values with depth toward the northeast direction indicates progressive vertical dilution during leachate mineralization. This study integrated geoelectric and seismo-electric tomography with basic water chemistry analysis to effectively characterize the groundwater within the phreatic Quaternary/Mio-Pliocene aquifers of the Douala basin.

Abstract As a precursor process to cloud formation, aerosol activation over the Tibetan Plateau (TP) plays a pivotal role in regional cloud-precipitation and global climate. However, its characteristics remain unclear due to the absence of targeted observations in the TP. We conducted a ground in-situ aerosol-cloud-precipitation experiment in the southern TP (GACPE-STP), thereby unveiling the aerosol activation characteristics in this crucial region. Our findings reveal a weak aerosol activation capacity with low hygroscopicity (κ) values of less than 0.1 through multi-method κ measurements, contrasting starkly with the widely recommended κ value of 0.3 for continental regions. A κ parameterization is developed for predicting aerosol activation in this region, which can significantly reduce the overestimations of cloud droplet number concentration and hence aerosol indirect effects caused by using the recommended κ of 0.3. These findings address the unclear characteristics of aerosol activation in the TP region, contributing to the enhancement of regional cloud precipitation and global climate simulations.

Abstract The meridional overturning circulation (MOC) in the ocean is a key player in the global climate system, while continental topography provides an essential backdrop to the system. In this study, we design a series of coupled model sensitivity experiments to investigate the influence of various mountain ranges on the global thermohaline circulation. The results highlight the influence of the Tibetan Plateau (TP) on the global thermohaline circulation. It emerges as a requisite for establishing the Atlantic MOC (AMOC) and a determining factor for the cessation of the Pacific MOC (PMOC). Additionally, the Antarctic continent plays a vital role in facilitating the TP to form the AMOC. While the formation of the AMOC cannot be attributed to any single mountain range, the TP alone can inhibit the PMOC’s development. By modifying the global hydrological cycle, the TP is likely to have been crucial in molding the global thermohaline circulation.

High penetration level of renewable energy has brought great challenges to operation of power systems, and use of flexible resources (FRs) is becoming increasingly important. Flexibility of power systems can be improved by changing generation arrangements, but the interests of some market participants may be harmed in the process. This study proposes a stochastic economic dispatch model with trading of flexible ramping products (FRPs). To calculate changes in revenue and reasonably compensate units that provide FRs, multisegmented marginal bidding for energy is simulated by linearizing generation cost, and an optimal market clearing strategy for FRPs is developed according to changes in clearing energy and marginal clearing price. Then, the correlation between prediction errors of wind speeds among different wind farms is determined based on a joint distribution function modeled by the copula function, and quasi-Monte Carlo simulation (QMC) is used to generate wind power scenarios. Finally, numerical simulations of modified IEEE-30 and IEEE-118 bus systems is performed with minimum comprehensive cost as the objective function. This verifies the proposed model could effectively deal with wind variability and uncertainty, stabilize the marginal clearing price of the electricity market, and ensure fairness in the market.

Electrophysiological recordings are vital in assessing biological functions, diagnosing diseases, and facilitating biofeedback and rehabilitation. The applications of conventional wet (gel) electrodes often come with some limitations. Microneedle array electrodes (MAEs) present a possible solution for high-quality electrophysiological acquisition, while the prior technologies for MAE fabrication have been either complex, expensive, or incapable of producing microneedles with uniform dimensions. This work employed a projection stereolithography (P $\mu $ SL) 3D printing technology to fabricate MAEs with micrometer-level precision. The MAEs were compared with gel and flat electrodes on electrode-skin interface impedance (EII) and performances of EMG and ECG acquisition. The experimental results indicate that the P $\mu $ SL 3D printing technology contributed to an easy-to-perform and low-cost fabrication approach for MAEs. The developed MAEs exhibited promising EII and enabled a stable EMG and ECG acquisition in different conditions without inducing skin allergies, inflammation, or injuries. This research lies in the development of a type of customizable MAE with considerable biomedical application potentials for ultra-minimally invasive or non-invasive electrophysiological acquisition.

This paper presents a robust interval economic dispatch (RIED) model for power systems with large-scale wind power integration. Differing from existing interval optimization (IO) approaches that merely rely on the upper and lower boundaries of random variables, the distribution information retained in the historical data is introduced to the IO method in this paper. Based on the available probability distribution function (PDF), wind power curtailment and load shedding are quantified as the operational risk and incorporated into the decision-making process. In this model, we need not rely on the forecasted value of wind power, which is randomly fluctuating and quite unpredictable. Furthermore, when the PDFs of wind power are taken into account, the resulting dispatch solution makes a good tradeoff between the generation cost and the operational risk. Finally, the RIED model yields an optimal dispatch solution for thermal units and the allowable intervals of wind power for the wind farms, which efficiently mitigates the uncertainty in wind power generation and provides more practical suggestions for system operators. Simulation studies are conducted on a modified IEEE-118 bus system and the results verify the effectiveness of the proposed RIED model.

Optimizing the configuration of acquisition terminals can maximize the observability and state estimation accuracy of the distribution grid achieving comprehensive perception of the distribution grid. However, the existing optimization configuration methods typically target a single topology structure. For regional distribution grids with dynamic topology changes, it cannot meet the observability requirements of all their topologies. In this regard, this paper proposes an optimal configuration scheme for regional distribution grid acquisition terminals considering dynamic observability. Firstly, the regional distribution grid considering the change of contact switch is modeled. Based on the observation redundancy and state estimation accuracy, the dynamic observability index of regional distribution grid is proposed. Then, a multi-objective optimal configuration model of acquisition terminal is constructed with the objective function of maximizing dynamic observability and minimizing configuration cost. Finally, the effectiveness of the proposed approach is validated with the simulation model.

Abstract Climate change exacerbates the threat of water scarcity over the drylands in East Asia (DEA), the world's most densely populated arid region. The water cycle continuously supplies water to support all life. Previous studies have focused on the change in individual hydrological components over DEA; however, how the projected water cycle changes under climate warming remains unclear. We demonstrate the projected response of the water cycle to global warming in different seasons utilizing the Coupled Model Intercomparison Project Phase 6. Winter in the DEA presents an intensification of the water cycle, reflected in coherent increases in evapotranspiration (E), precipitation (P), runoff, and surface soil moisture. In contrast, summer will experience a weakened water cycle in the northwestern DEA, while the southeastern part exhibits the opposite trend. From the surface and atmospheric water balance perspective, we further attribute the changes in E and P to gain a more comprehensive understanding. The increasing E is attributed to the combined effects of P and the vapor pressure deficit during summer, whereas it is dominated by P in winter. The increased P in summer is primarily attributed to the horizontal dynamic and vertical thermodynamic components associated with the strengthening and westward expansion of East Asia summer monsoon in the future. During winter, the increased P is mainly due to the vertical dynamic and horizontal thermodynamic components associated with the enhancement of vertical ascending motion and increased moisture.

COVID-19 has posed formidable challenges as a significant global health crisis. Its complexity stems from factors like viral contagiousness, population density, social behaviors, governmental regulations, and environmental conditions, with interpersonal interactions and large-scale activities being particularly pivotal. To unravel these complexities, we used a modified SEIR epidemiological model to simulate various outbreak scenarios during the holiday season, incorporating both inter-regional and intra-regional human mobility effects into the parameterization scheme. In addition, evaluation metrics were used to evaluate the accuracy of the model simulation by comparing the congruence between simulated results and recorded confirmed cases. The findings suggested that intra-city mobility led to an average surge of 57.35% in confirmed cases of China, while inter-city mobility contributed to an average increase of 15.18%. In the simulation for Tianjin, China, a one-week delay in human mobility attenuated the peak number of cases by 34.47% and postponed the peak time by 6 days. The simulation for the United States revealed that human mobility played a more pronounced part in the outbreak, with a notable disparity in peak cases when mobility was considered. This study highlights that while inter-regional mobility acted as a trigger for the epidemic spread, the diffusion effect of intra-regional mobility was primarily responsible for the outbreak. We have a better understanding on how human mobility and infectious disease epidemics interact, and provide empirical evidence that could contribute to disease prevention and control measures.

Abstract How convective boundary‐layer (CBL) processes modify fluxes of sensible (SH) and latent (LH) heat and CO2 (Fc) in the atmospheric surface layer (ASL) remains a recalcitrant problem. Here, large eddy simulations for the CBL show that while SH in the ASL decreases linearly with height regardless of soil moisture conditions, LH and Fc decrease linearly with height over wet soils but increase with height over dry soils. This varying flux divergence/convergence is regulated by changes in asymmetric flux transport between top‐down and bottom‐up processes. Such flux divergence and convergence indicate that turbulent fluxes measured in the ASL underestimate and overestimate the “true” surface interfacial fluxes, respectively. While the non‐closure of the surface energy balance persists across all soil moisture states, it improves over drier soils due to overestimated LH. The non‐closure does not imply that Fc is always underestimated; Fc can be overestimated over dry soils despite the non‐closure issue.

The Zhangheng-1 electromagnetic satellite is the space-based observation platform of China's stereoscopic earthquake observation system. Its scientific objective is to obtain the global geomagnetic field, electromagnetic field (waves), ionospheric plasma parameters, and high-energy particles for monitoring the dynamic variation of the ionosphere and the seismo-ionospheric disturbances over China and its surrounding areas to compensate for the deficiency of the ground-based observation system. The project explores new ways of earthquake monitoring and prediction by using space science. The first test probe of the Zhangheng-1 electromagnetic satellite series was successfully launched in February 2018, and has been stably operating in orbit for more than four years. The second is an operational probe that will be launched in early 2023. The in-flight commissioning test and cross-calibration work show that the Zhangheng-1 electromagnetic satellite can provide good data quality to support geophysics and space physics studies, and has obtained valuable scientific results in recent years. The global geomagnetic reference model built by Zhenghang-1 data is the first global geomagnetic field model built using only Chinese satellite data, allowing Chinese scientists to take an important role in the computation of the global geomagnetic reference model (IGRF) for the first time in over a century. The ionospheric electron density 3D model based on Zhangheng-1 satellite data can present the ionospheric structure characteristics. In natural hazards monitoring, Zhangheng-1 has shown good response ability to disturbances related to earthquakes, volcano eruptions, and geomagnetic storms. In terms of the lithosphere-atmosphere-ionosphere coupling mechanism study, the full-wave calculation method can provide the electromagnetic field changes between the lithosphere-ionosphere waveguide and the ionospheric wave propagation feature. The results from the full-wave model prove the capability of the Zhangheng-1 satellite's electromagnetic payloads to detect low-frequency electromagnetic emissions induced from the earthquake epicenter. The simulation and observation studies suggest that the Zhangheng-1 satellite can reflect seismic activities, very low frequency (VLF) transmitter, magnetic anomalies in the lithosphere, and lightning activities in the atmosphere. These recent scientific results show that the Zhangheng-1 electromagnetic satellite is consistent with other similar types of electromagnetic satellites worldwide, indicating its great potential in scientific application.

Glioblastoma (GBM) poses a significant challenge in clinical oncology due to its aggressive nature, heterogeneity, and resistance to therapies. Cancer stem cells (CSCs) play a critical role in GBM, particularly in treatment resistance and tumor relapse, emphasizing the need to comprehend the mechanisms regulating these cells. Also, their multifaceted contributions to the tumor microenvironment (TME) underline their significance, driven by their unique properties. This study aimed to characterize glioblastoma stem cells (GSCs), specifically slow-cycling cells (SCCs), in an immunocompetent murine GBM model to explore their similarities with their human counterparts. Using the KR158 mouse model, we confirmed that SCCs isolated from this model exhibited key traits and functional properties akin to human SCCs. KR158 murine SCCs, expanded in the gliomasphere assay, demonstrated sphere forming ability, self-renewing capacity, positive tumorigenicity, enhanced stemness and resistance to chemotherapy. Together, our findings validate the KR158 murine model as a framework to investigate GSCs and SCCs in GBM pathology, and explore specifically the SCC–immune system communications, understand their role in disease progression, and evaluate the effect of therapeutic strategies targeting these specific connections.

Abstract The single-scattering albedo (SSA) of atmospheric aerosols is a key parameter that controls aerosol radiative effects. The variation of SSA is thought to be mainly regulated by aerosol absorption in the Himalayas and South Asia, but observations contradict this idea. In situ field campaigns conducted over two Himalayan sites revealed that SSA was strongly dependent on scattering but weakly correlated with absorption. Observational results combined with the Mie theory further illustrated that SSA was primarily modulated by size distribution rather than absorption. Aerosol Robotic Network (AERONET) data showed similar impacts of size distribution on SSA and that aerosol radiative forcing efficiencies were significantly dependent on SSA. Aerosol size distribution therefore considerably affects radiative forcing by modulating aerosol SSA over the Himalayas. This study highlighted the influence of aerosol size distribution on radiative forcing over the Himalayas, which has important implications for understanding aerosol radiative effects globally.

Abstract Licorice, a traditional Chinese medicine, has been widely used for the treatment of COVID-19, but all active compounds and corresponding targets are still not clear. Therefore, this study proposed a deep learning-based network pharmacology approach to identify more potential active compounds and targets of licorice. 4 compounds (quercetin, naringenin, liquiritigenin, and licoisoflavanone), 2 targets (SYK and JAK2) and the relevant pathways (P53, cAMP, and NF-kB) were predicted, which were confirmed by previous studies to be associated with SARS-CoV-2-infection. In addition, 2 new active compounds (glabrone and vestitol) and 2 new targets (PTEN and MAP3K8) were further validated by molecular docking and molecular dynamics simulations (simultaneous molecular dynamics), as well as the results showed that these active compounds bound well to COVID-19 related targets, including the main protease (Mpro), the spike protein (S-protein) and the angiotensin-converting enzyme 2 (ACE2). Overall, in this study, glabrone and vestitol from licorice were found to inhibit viral replication by inhibiting the activation of Mpro, S-protein and ACE2; related compounds in licorice may reduce the inflammatory response and inhibit apoptosis by acting on PTEN and MAP3K8. Therefore, licorice has been proposed as an effective candidate for the treatment of COVID-19 through PTEN, MAP3K8, Mpro, S-protein and ACE2.

Introduction: Synthetic hydroxyapatite (HAp) scaffolds have shown promising therapeutic outcomes in both animals and patients. In this study, we aim to evaluate the chemical and physical phenotype, biocompatibility, and bone repair effects of hydrothermally treated coral with natural coral and synthetic HAp.Methods: The phase composition, surface pattern, 3D structures, and porosity of the scaffolds were characterized, and cell viability, proliferation, and osteogenic differentiation of mesenchymal stem cells (MSCs) after seeding onto the scaffold were determined. The scaffolds were implanted into rats to assess their bone repair effects using micro-CT analysis, mechanical testing, and histological staining.Results: The results showed that the phase composition, porous structure, and porosity of hydrothermally treated coral were comparable to pure HAp scaffold. While only the natural coral happens to be dominantly calcium carbonate. Higher cell proliferation and osteogenic differentiation potential were observed in the hydrothermally treated coral scaffold compared to natural coral and pure HAp. Histological results also showed increased new bone formation in the hydrothermally treated coral group.Discussion: Overall, our study suggests that hydrothermal modification enhances the cytocompatibility and therapeutic capacity of coral without altering its physical properties, showing superior effectiveness in bone repair to synthetic HAp.

The accurate simulation of anisotropic media is critical in seismic imaging and inversion. In recent years, some scholars have dedicated efforts to the study of precise elastic waves in anisotropic media; however, it is easy to separate P-wave and S-wave from elastic wave fields in isotropic media but difficult to separate them in anisotropic media. To address this issue, others have proposed pseudo-pure-wave equations based on the theory of wave-mode separation, but shear wave interference still exists. Therefore, we derived the first-order pure quasi-P-wave equation with no shear wave component in orthorhombic anisotropic media (ORT) which is common in the Earth’s crust and has very important research value. The presence of a pseudodifferential operator in the equation poses a challenge for solving. In order to solve the pure wave equation, we decomposed the original pseudodifferential operator into an elliptic differential operator and a scalar operator, both of which are easily solvable. In addition, we extended the equation from ORT media to tilted ORT (TORT) media. The example results indicate that our pure quasi-P-wave equation can yield a more stable and accurate P-wave field. The pure wave equation we propose can be applied in reverse time migration (RTM), the least squares RTM (LSRTM), and even the full waveform inversion (FWI).

On May 21, a Ms6.4 earthquake occurred in Yangbi, Yunnan Province. Less than 5 ​h later, on May 21, follows a Ms7.4 earthquake in Madoi, Qinghai Province. In this study, multiple parameters are studied from CSES-01 satellite and GNSS. The parameters include the electron density from LAP, energetic particle flux from HEPP, electric field spectrum from EFD, induced magnetic field spectrum from SCM, and global TEC from ground-based GNSS receivers. In the time scale, all parameters changed on May 15, 17 and 18. The relative amplitude of Ne is more than 200%. In space scale, the clear enhancement focus on the southeast of the epicenter of Madoi, Qinghai, and the shape of the focus region is like a clockwise-30°-rotated rectangle, which is about 45° in length and 20° in width. Moreover, there appeared enhancement in the conjugated region. According to the day-to-day analysis of the low-frequency (75–90 Hz) spectrum of EFD and SCM payloads, the relationship of the increment on May 18 could be confirmed with the successive two earthquakes. The energetic particle fluxes enhanced on May 20. All those changes are located in the east of the following epicenter and appeared just several days before, which could be well explained by the Lithosphere-Atmosphere-Ionosphere theory.

In seismic modeling and reverse time migration (RTM), incorporating anisotropy is crucial for accurate wavefield modeling and high-quality images. Due to the trade-off between computational cost and simulation accuracy, the pure quasi-P-wave equation has good accuracy to describe wave propagation in tilted transverse isotropic (TTI) media. However, it involves a fractional pseudo-differential operator that depends on the anisotropy parameters, making it unsuitable for resolution using conventional solvers for fractional operators. To address this issue, we propose a novel pure quasi-P-wave equation with a generalized fractional convolution operator in TTI media. First, we decompose the conventional pure quasi-P-wave equation into an elliptical anisotropy equation and a fractional pseudo-differential correction term. Then, we use a generalized fractional convolution stencil to approximate the spatial-domain pseudo-differential term through the solution of an inverse problem. The proposed approximation method is accurate, and the wavefield modeling method based on it also accurately describes quasi-P-wave propagation in TTI media. Moreover, it only increases the computational cost for calculating mixed partial derivatives compared to those in vertical transverse isotropic (VTI) media. Finally, the proposed wavefield modeling method is utilized in RTM to correct the anisotropic effects in seismic imaging. Numerical RTM experiments demonstrate the flexibility and viability of the proposed method.

It is found that there are some anomalous high-energy nuclear-shaped regions in the VLF frequency band of the space electric field. To detect and statistically analyze these nuclear-shaped anomaly areas, this paper proposes a nuclear-shaped anomaly area detection method based on the electric field power spectrum image data of the China Seismo Electromagnetic Satellite (CSES-01). First, the logarithm of VLF frequency band data was calculated and rotated counterclockwise to create power spectrum images and label them to form a sample image dataset; then, images were enhanced (which involved resizing, scaling, rotation, gaussian denoising, etc.) to solve the problems of the model overfitting and sample imbalance. Finally, the U-net network model based on the ResNet50 encoder was trained to obtain the optimal kernel anomaly detection model ResNet50_Unet. Comparative experiments with various semantic segmentation algorithms show that the ResNet50_Unet model has the best performance. Applying this model to detect the electric field power spectrum images from November 2021 to February 2022, a total of 101 nuclear-shaped anomaly areas were found, distributed between 45° and 70° of the north–south latitude. This model can quickly detect nuclear-shaped anomaly regions from massive data, providing reference significance for the detection of other types of ionospheric spatial disturbances. At the same time, it has important scientific significance and practical value for understanding the ionosphere and space communication.

There is a growing body of research on the factors influencing individual knowledge-sharing behavior, but the exploration of knowledge sharing in the construction industry is still in its infancy. Based on the theory of planned behavior (TPB), this paper introduced factors from the social exchange theory (SET) to develop a comprehensive model for exploring the intention of construction workers to share their safety knowledge. Data were collected from a total of 329 construction workers at five sites. Using the structural equation model method, the research model and path hypotheses of this study were analyzed. The results showed that altruism, trust, and reputation positively influenced the construction workers’ attitude towards sharing safety knowledge. Attitude, safety training, organizational climate, and knowledge-sharing self-efficacy could increase the construction workers’ intention to share their safety knowledge. However, the relationship between workers’ attitudes towards safety knowledge sharing and anticipated extrinsic rewards was not significant. Through identifying the factors underlying workers’ intention to share safety knowledge in the construction industry, the study helps to further understand the influencing factors and mechanisms of safety knowledge sharing willingness among the special group of construction workers and provides practical implications for engineering managers to strengthen construction safety management from the perspective of knowledge sharing.

Abstract The Tibetan Plateau (TP) precipitation is experiencing the north‐south dipole tendency pattern since 1979. In this study, we identify four primary seasonally evolving patterns (SEPs) that explain approximately 50% of the total variance in precipitation variability over the TP. These SEPs contribute 60%–90% of the spatial mean amplitude of precipitation trends across seasons. In particular, the second SEP that features a north‐south dipole pattern dominates the annual mean trend of the precipitation over the TP. The interdecadal variability of the seasonally evolving north‐south dipole pattern is linked to the interdecadal variations of summer Silk Road Pattern and Indian monsoon. These findings suggest that the climate variability expressed through SEPs could potentially serve as a significant source for the interdecadal rainfall prediction.

ObjectiveThis study aimed to evaluate the effectiveness of total contact casts (TCCs) versus removable offloading interventions among patients with diabetic foot ulcers (DFUs).MethodsA comprehensive search was done in databases Embase, Cochrane Library, and, PubMed. The references of retrieved articles were reviewed, up until February 2023. Controlled trials comparing the effects of TCCs with removable offloading interventions (removable walking casts and footwear) in patients with DFUs were eligible for review.ResultsTwelve studies were included in the meta-analysis, involving 591 patients with DFUs. Among them, 269 patients were in the intervention group (TCC), and 322 in the control group (removable walking casts/footwear). The analysis revealed that the TCC group had higher healing rates (Risk Ratio(RR)=1.22; 95% confidence interval(CI):1.11 to 1.34, p

Abstract The amount, frequency and intensity of extreme precipitation over Xinjiang have increased dramatically under the wetting trend in Northwest China, but long‐term trends in the precipitation‐recycling process remain largely unexplored. Based on dynamic recycling model and MERRA2 reanalysis, we revealed a mean recycling ratio for extreme precipitation in Xinjiang of 42.3% with a growth rate of 2.3% decade−1 during 1982–2019. The increasing trend of extreme precipitation was almost equally attributed to increased recycling precipitation (49%) and external precipitation (51%). The extreme precipitation in Xinjiang exhibited two peak centers, the Tianshan Mountains region (TS) and Kunlun Mountains region (KL), highlighting variations in the water cycle. Specifically, the external cycle predominated the increased extreme precipitation in TS (61%), while the recycling process mainly influenced the increase in KL (67%) due to markedly enhanced evapotranspiration. Moisture source attribution further proved the crucial role of evapotranspiration from Xinjiang and its vicinity in extreme precipitation.

Objective: Breast cancer is one of the most prevalent cancers in females worldwide and is one of the leading causes of cancer death and disability in women. Multiple therapies have been applied to breast cancer treatment; however, the long-term survival rate remains low. Although cisplatin has been widely utilized for cancer therapy, chemoresistance still influences the outcome. Methods: After collecting the breast cancer cell line MDA-MB-231 treated with or without cisplatin and sample information from The Cancer Genome Atlas Program (TCGA), we screened out their common parameters and influences on the prognoses of patients' potential targets. Surgical excisional tissue sections of patients with breast cancer who were admitted and treated in the Department of Breast and Thyroid Surgery, Liuzhou People's Hospital from 2017 to 2020 was collected and follow up. After a series of assays combined with clinical information, we tested the reliability of the target. Results: We found that a high expression level of ZNF268 in breast cancer cell lines significantly enhances the sensitivity to cisplatin, contrary to the effects of low expression. Furthermore, a significantly worse prognosis was observed in patients with a high expression of ZNF268 after cisplatin chemotherapy. Conclusion: The expression level of ZNF268 in breast cancer patients after cisplatin chemotherapy may become a potential target to predict the chemoresistance of patients to cisplatin. This study provides a novel idea for improving breast cancer treatment and survival rates.

Under global warming, seasonal snow takes faster melting rate than before, which greatly changes the hydrological cycle. In this study, by targeting three typical seasonal snow-covered land types (i.e., open shrubland, evergreen needleleaf forest and mixed forest) in the Northern Hemisphere, the start of growing season (SGS) has been found obviously advanced in the past years, greatly contributed by the faster melting rate of seasonal snow. It is manifested that significantly positive correlation has been found between SGS and May snow depth for open shrubs, March and April snow depth for evergreen needleleaf forests and March snow depth for mixed forests. However, such close association is not appeared in all the climate conditions of same vegetation. In the future, as the rate of melting snow becomes faster in the high emission of greenhouse gasses than the current situation, continuously advanced SGS will accelerate the change of vegetation distribution in the Northern Hemisphere. These findings offer insights into understanding the effect from seasonal snow on vegetation and promote the sustainable utilization of regional vegetation in the Northern Hemisphere.

Abstract Little is known regarding why a subset of COVID-19 patients exhibited prolonged positivity of SARS-CoV-2 infection. Here, we found that patients with long viral RNA course (LC) exhibited prolonged high-level IgG antibodies and higher regulatory T (Treg) cell counts compared to those with short viral RNA course (SC) in terms of viral load. Longitudinal proteomics and metabolomics analyses of the patient sera uncovered that prolonged viral RNA shedding was associated with inhibition of the liver X receptor/retinoid X receptor (LXR/RXR) pathway, substantial suppression of diverse metabolites, activation of the complement system, suppressed cell migration, and enhanced viral replication. Furthermore, a ten-molecule learning model was established which could potentially predict viral RNA shedding period. In summary, this study uncovered enhanced inflammation and suppressed adaptive immunity in COVID-19 patients with prolonged viral RNA shedding, and proposed a multi-omic classifier for viral RNA shedding prediction.

Rain-induced loess landslides are especially prevalent in the Chinese Loess Plateau (CLP). Some became fatal landslide disasters, leading to numerous casualties and significant socioeconomic losses. Extreme precipitation is the main cause of landslide occurrence. Therefore, in this study we discuss the correlation between seven extreme precipitation indices, single continuous precipitation events and fatal landslides in the CLP using Pearson correlation analysis. We also predict future precipitation under climate changes using five optimal CMIP6 models. During the period 2004–2016, fatal landslides in the CLP increased at a rate of 0.6 per year, with frequent landslide events occurring especially in the central and southwestern parts of the CLP. We find that SDII (simple daily intensity precipitation index) and R×5day (max 5-day precipitation amount) show spatial distribution that are consistent with fatal landslides. Extreme precipitation events were frequent after year 2000; and several extreme precipitation indices show an increasing trend with a higher magnitude since 2000 than before 2000. In particular, in 2013 when the number of fatal landslides was as high as 17, SDII, R95pTOT (extremely wet days), R25mm (very heavy precipitation days), and R×5day all showed abrupt increases. Single continuous precipitation events have profound effects on fatal landslides. We show that single continuous precipitation events with cumulative precipitation of 185–235 mm and duration of 6 days or longer have the highest correlation with fatal landslides. As the increasing occurrence of extreme rainfall events by the global warming, the CLP may face more fatal landslides in the future, especially in the high emission scenario of greenhouse gases (GHGs).

Long-term or supra-physiological dose of glucocorticoid (GC) application in clinic can lead to impaired bone growth and osteoporosis. The side effects of GC on the skeletal system are particularly serious in growing children, potentially causing growth retardation or even osteoporotic fractures. Children’s bone growth is dependent on endochondral ossification of growth plate chondrocytes, and excessive GC can hinder the development of growth plate and longitudinal bone growth. Despite the availability of drugs for treating osteoporosis, they have failed to effectively prevent or treat longitudinal bone growth and development disorders caused by GCs. As of now, there is no specific drug to mitigate these severe side effects. Traditional Chinese Medicine shows potential as an alternative to the current treatments by eliminating the side effects of GC. In summary, this article comprehensively reviews the research frontiers concerning growth and development disorders resulting from supra-physiological levels of GC and discusses the future research and treatment directions for optimizing steroid therapy. This article may also provide theoretical and experimental insight into the research and development of novel drugs to prevent GC-related side effects.

Long Island Sound (LIS) frequently experiences ozone (O3) exceedance events that surpass national ambient air quality standards (NAAQS) due to complex driving factors. The underlying mechanisms governing summertime O3 pollution are investigated through collaborative observations from lidar remote sensing and ground samplers during the 2018 LIS Tropospheric O3 Study (LISTOS). Regional transport and local chemical reactions are identified as the two key driving factors behind the observed O3 episodes in LIS. An enhanced laminar structure is observed in the O3 vertical structure in the atmospheric boundary layer (i.e., 0–2 km layer) for the case dominated by regional transport. An O3 formation regime shift is found in ozone-precursor sensitivity (OPS) for the O3 exceedance event dominated by regional transport with NOx-enriched air mass transport from the New York City (NYC) urban area to LIS. Furthermore, the Integrated Process Rate (IPR) analysis demonstrates that transport from the NYC urban area contributed 40% and 27.1% of surface O3 enhancement to the cases dominated by regional transport and local production, respectively. This study provides scientific evidence to uncovers two key processes that govern summertime O3 pollution over LIS and can help to improve emission control strategies to meet the attainment standards for ambient O3 levels over LIS and other similar coastal areas.

Introduction“Sonic seasoning” is when music influences the real taste experiences of consumers. “Self-construal” is how individuals perceive, understand, and interpret themselves. Numerous studies have shown that independent and interdependent self-construal priming can affect a person's cognition and behavior; however, their moderating effect on the sonic seasoning effect remains unclear.MethodsThis experiment was a 2 (self-construal priming: independent self-construal or interdependent self-construal) × 2 (chocolate: milk chocolate or dark chocolate) × 2 (emotional music: positive emotional music or negative emotional music) mixed design, and explored the moderating role of self-construal priming and the effect of emotional music on taste by comparing participants' evaluations of chocolates while listening to positive or negative music after different levels of self-construal priming.ResultsAfter initiating independent self-construal, participants increased their ratings of milk chocolate sweetness when listening to music that elicited positive emotions, t(32) = 3.11, p = 0.004, Cohen's d = 0.54, 95% CI = [0.33, 1.61]. In contrast, interdependent self-construal priming led participants to perceive dark chocolate as sweeter when they heard positive music, t(29) = 3.63, p = 0.001, Cohen's d = 0.66, 95%CI = [0.44, 1.56].DiscussionThis study provides evidence for improving people's individual eating experience and enjoyment of food.

The successive tidal force (TF) at the epicenter of the Jiashi M6.6 earthquake in Xinjiang, China, was calculated for the period from 13 December 2019 to 10 February 2020. With periodic changes in tide-generating forces, the variations in the electron density (Ne) data recorded by the China Seismo-Electromagnetic Satellite (CSES) and outgoing longwave radiation (OLR) data provided by NOAA on a large scale at N25°–N55°, E65°–E135° were studied. The results show that (1) in the four cycles during which the TF changes from trough to peak, the earthquake occurred during one peak time when the OLR changed around the epicenter via calm–rise processions and in other similar TF phases, and neither an increase in the OLR nor earthquake occurred. (2) With a change in the TF, the spatiotemporal evolution of the OLR from seismogenic processes to its occurrence was as follows: microenhancement–enhancement–microattenuation–enhancement–calmness; this is consistent with the evolution of outward infrared radiation when rocks break under stress loading: microrupture–rupture–locking–accelerated rupture–rupture. (3) Ne increased significantly during the seismogenic period and was basically consistent with OLR enhancement. The results indicate that as the TF increases, the Earth’s stress accumulates at a critical point, and the OLR increases and transfers upward. The theoretical hypothesis underlying the conducted study is that the accumulated electrons on the surface cause negatively charged electrons in the atmosphere to move upward, resulting in an increase in ionospheric Ne near the epicenter, which reveals the homology of seismic stress variations in the spatial coupling process. The quasi-synchronous change process of these three factors suggests that the TF changed the process of the stress accumulation–imbalance in the interior structure of this earthquake and has the effect of triggering the earthquake, and the spatiotemporal variations in the OLR and ionospheric Ne could be indirect reflections of in situ stress.

The spaceborne Electric Field Detector (EFD) is one of the payloads of the China Seismo-Electromagnetic Satellite (CSES-01), which can measure electric field data at near-Earth orbit for investigating fundamental scientific topics such as the dynamics of the top-side ionosphere, lithosphere–atmosphere–ionosphere coupling, and electromagnetic field emissions possibly associated with earthquake occurrence. The Extremely Low-Frequency (ELF) waveform shows anomalous step variations, and this work proposes an automatic detection algorithm to identify steps and analyze their characteristics using a convolutional neural network. The experimental results show that the developed detection method is effective, and the identification performance reaches over 90% in terms of both accuracy and area under the curve index. We also analyze the rate of the occurrence of steps in the three components of the electric field. Finally, we discuss the stability of the statistical results on steps and their relevance to the probe’s function. The research results provide a guideline for improving the quality of EFD data, and further applications in monitoring the low-Earth electromagnetic environment.

In order to explore the correlation between earthquakes and ionospheric very low-frequency (VLF) electric field disturbances, this article uses VLF data observed by the China Earthquake Electromagnetic Satellite (CSES) to analyze very low-frequency signals before and after earthquakes from January 2019 to March 2023 in terms of the amplitude and signal-to-noise ratio of electric field power spectrum disturbances. Taking 73 earthquakes with a magnitude of 6.0 or higher occurring in the Circum-Pacific seismic belt as an example, comprehensive research on the VLF electric field disturbance phenomenon caused by strong earthquakes is conducted, considering both the earthquake location and source mechanism. The research results indicate the following: (1) there is a strong correlation between earthquakes with a magnitude of 6.0 or above and abnormal disturbances in the VLF electric field, which often occur within 20 days before the earthquake and within 800 km from the epicenter. (2) From the perspective of earthquake-prone areas, the VLF electric field anomalies observed before earthquakes in the Ryukyu Islands of the Taiwan region exhibit small and concentrated field fluctuations, while the Taiwan Philippines region exhibits larger field fluctuations and more dispersed fluctuations. The discovery of this correlation between seismic ionospheric phenomena and seismic activity provides a new and effective approach to earthquake monitoring, which can be used for earthquake prediction, early warning, and disaster prevention and reduction work.

The electric field detector of the CSES satellite has captured a vast number of lightning whistler events. To recognize them effectively from the massive amount of electric field detector data, a recognition algorithm based on speech technology has attracted attention. However, this approach has failed to recognize the lightning whistler events which are contaminated by other low-frequency electromagnetic disturbances. To overcome this limitation, we apply the single-channel blind source separation method and audio recognition approach to develop a novel model, which consists of two stages. (1) The training stage: Firstly, we preprocess the electric field detector wave data into the audio fragment. Then, for each audio fragment, mel-frequency cepstral coefficients are extracted and input into the long short-term memory network for training the novel lightning whistler recognition model. (2) The inference stage: Firstly, we process each audio fragment with the single-channel blind source to generate two different sub-signals. Then, for each sub-signal, the mel-frequency cepstral coefficient features are extracted and input into the lightning whistler recognition model to recognize the lightning whistler. Finally, the two results above are processed by decision fusion to obtain the final recognition result. Experimental results based on the electric field detector data of the CSES satellite demonstrate the effectiveness of the algorithm. Compared with classical methods, the accuracy, recall, and F1-score of this algorithm can be increased by 17%, 62.2%, and 50%, respectively. However, the time cost only increases by 0.41 s.

Abstract Temperature variations across the continental northern hemisphere at the interdecadal scale are thought to be remotely modulated by oceanic internal climate variability and the Arctic. Nevertheless, further elucidating the dynamics is essential for clarifying ongoing debates. We show that potential vorticity (PV) dynamics provide a concise explanation for these teleconnections. Our findings demonstrate that extratropical oceans and the Arctic can remotely modulate the wintertime continental temperature variations by stimulating PV anomalies, which are constrained by climatological PV gradients and jet streams. A causal explanation includes anomalous temperature and precipitation over oceans and the Arctic inducing local PV anomalies via diabatic heating. Subsequently, meridional and downstream advection distributes the anomalous PV to remote land regions where the climatological PV gradients are strong, that is, involving PV fronts, as well as jet streams; therefore, PV fronts and jet streams jointly indicate land regions that are largely and frequently impacted. However, land can also modulate other regions through the same mechanism when variations over land occur in advance. Clear causality depends on which factor is independent, while interactions among those regions may convolute the causality, thereby causing further debates.