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The ecosystem and societal development over arid Central Asia, the core connecting region of the Silk Road Economic Belt, are highly sensitive to climate change. The results derived from multiobservational datasets show that summer precipitation over Central Asia has significantly increased by 20.78% from 1961 to 2013. It remains unclear whether anthropogenic forcing has contributed to the summer wetting trend or not. In this study, the corresponding physical processes and contributions of anthropogenic forcing are investigated by comparing reanalysis and experiments of the Community Atmosphere Model, version 5.1 (CAM5.1), from the CLIVAR Climate of the Twentieth Century Plus (C20C+) Project. The observed wetting trend is well reproduced in the simulation driven by all radiative forcings (CAM5-All), but poorly reproduced in the simulation with natural forcings only (CAM5-Nat), confirming the important role of human contribution in the observed wetting trend. Moisture budget analysis shows that the observed wetting trend is dominated by the increasing vertical moisture advection term and results from enhanced vertical motion over nearly all of Central Asia. The observed contributions of moisture budget components to the wetting trend are only captured by CAM5-All experiments. The dynamic contribution is determined by the warm advection anomalies in association with a human-induced meridional uneven warm pattern. Human-induced warming increases the specific humidity over all of Central Asia, increasing (decreasing) the precipitation over the climatological ascent (descent) region in eastern (western) Central Asia.

Arid Central Asia is highly vulnerable to extreme climate events. Information on potential future changes in extreme climate events in Central Asia is limited. In this study, the performances of models from the Coupled Model Intercomparison Project phase 5 (CMIP5) in simulating climatological extremes in Central Asia are first evaluated, and a bias correction method is employed to constrain future projections. The responses of extreme climate events over Central Asia to future warming and, in particular, the impact of 1.5 and 2 °C global warming scenarios are then assessed based on the observationally constrained projections. During the twenty-first century, coldest night (TNn), coldest day (TXn), warmest night (TNx), warmest day (TXx), 1-day maximum precipitation (RX1 day), 5-day maximum precipitation (RX5 day), and precipitation intensity (SDII) in Central Asia would robustly increase at best estimated rates of 1.93 °C, 1.71 °C, 1.18 °C, 1.25 °C, 6.30%, 5.71%, and 4.99% per degree of global warming, respectively, under Representative Concentration Pathway (RCP) 8.5. Compared with the 2 °C warming scenario, limiting global warming to 1.5 °C could reduce the intensification (relative to 1986–2005) of TNn, TNx, TXn, TXx, RX1 day, RX5 day, and SDII by 33%, 24%, 32%, 29%, 39%, 42%, and 53% from the best estimates under RCP8.5, respectively. The avoided intensification of TNn, TNx, TXn and TXx (RX1 day and SDII) would be larger (smaller) under RCP4.5. This suggests that a low warming target is necessary for avoiding the dangerous risk of extremes in this arid region.

It has been of interest in seeking electrocatalysts that could exercise equally high-efficient and durable hydrogen evolution upon nonselective electrolytes in both acidic and alkaline environments. Herein, we report a facile strategy to fabricate cobalt tungsten phosphides (Co x W 2− x P 2 /C) hollow polyhedrons with tunable composition based on metal-organic frameworks (MOFs) template method. By the deliberate control of W doping, the synthesized catalyst with the composition of Co 0.9 W 1.1 P 2 /C is found to be able to achieve a current density of 10 mA·cm −2 at overpotentials of 35 and 54 mV in acidic and alkaline media, respectively. This combined electrochemical property stands atop the state-of-the-art electrocatalyst counterparts. To unveil the peculiar behavior of the structure, density functional theory (DFT) calculation was implemented and reveals that the surface W-doping facilitates the optimization of hydrogen absorption free energy (Δ G H* ) as well as the thermodynamic and kinetics barriers for water dissociation, which is coupled with the hollow structure of Co-W phosphides, leading to the prominent HER catalytic performance.

Changes in monsoon precipitation have profound social and economic impacts as more than two-thirds of the world’s population lives in monsoon regions. Observations show a significant reduction in global land monsoon precipitation during the second half of the 20th century. Understanding the cause of this change, especially possible anthropogenic origins, is important. Here, we compare observed changes in global land monsoon precipitation during 1948–2005 with those simulated by 5 global climate models participating in the Coupled Model Inter-comparison Project-phase 5 (CMIP5) under different external forcings. We show that the observed drying trend is consistent with the model simulated response to anthropogenic forcing and to anthropogenic aerosol forcing in particular. We apply the optimal fingerprinting method to quantify anthropogenic influences on precipitation and find that anthropogenic aerosols may have contributed to 102% (62–144% for the 5–95% confidence interval) of the observed decrease in global land monsoon precipitation. A moisture budget analysis indicates that the reduction in precipitation results from reduced vertical moisture advection in response to aerosol forcing. Since much of the monsoon regions, such as India and China, have been experiencing rapid developments with increasing aerosol emissions in the past decedes, our results imply a further reduction in monsoon precipitation in these regions in the future if effective mitigations to reduce aerosol emissions are not deployed. The observed decline of aerosol emission in China since 2006 helps to alleviate the reducing trend of monsoon precipiptaion.

The identification of drug–drug interactions (DDIs) plays a crucial role in various areas of drug development. In this study, a deep learning framework (KGCN_NFM) is presented to recognize DDIs using coupling knowledge graph convolutional networks (KGCNs) with neural factorization machines (NFMs). A KGCN is used to learn the embedding representation containing high-order structural information and semantic information in the knowledge graph (KG). The embedding and the Morgan molecular fingerprint of drugs are then used as input of NFMs to predict DDIs. The performance and effectiveness of the current method have been evaluated and confirmed based on the two real-world datasets with different sizes, and the results demonstrate that KGCN_NFM outperforms the state-of-the-art algorithms. Moreover, the identified interactions between topotecan and dantron by KGCN_NFM were validated through MTT assays, apoptosis experiments, cell cycle analysis, and molecular docking. Our study shows that the combination therapy of the two drugs exerts a synergistic anticancer effect, which provides an effective treatment strategy against lung carcinoma. These results reveal that KGCN_NFM is a valuable tool for integrating heterogeneous information to identify potential DDIs.

The Yangtze River Valley (YRV) experienced an unprecedented heatwave in midsummer of 2022. Still, the detailed physical processes involved in the influence of abnormal large-scale atmospheric circulation on the heatwave remain unexplored. Here, we show that the positive meridional gradient of anomalous atmospheric moisture at the middle-lower troposphere and associated extreme dry air advection over the YRV are vital prerequisites for forming the 2022 YRV heatwave. The 2022 YRV heatwave is dominated by interannual variability, contributing 72.7% to the total temperature anomalies. Diagnosis of the surface heat budget equation indicates that the surface cloud radiative forcing is the most critical process in driving the 2022 YRV heatwave, which is dominated by the positive surface short-wave cloud radiative forcing associated with the suppressed precipitation and the middle-low clouds. The suppressed precipitation is induced by the vertical dynamical processes of anomalous moisture advection caused by the abnormal descending flows over the YRV, which are driven by the negative advection of anomalous latent heat energy by climatological meridional wind (anomalous dry air advection) according to the atmospheric moist static energy equation. Simulations from the Lagrangian model FLEXPART further indicate that the moisture anomaly over the north of YRV mainly originated from the surface evaporation in the YRV, implying that there is a positive land-air feedback during the life cycle of the YRV heatwave. Our study enriches the mechanism understanding of the 2022 YRV heatwave from the perspective of surface energy budget and land-air feedback.

   This study investigates the physical mechanisms for the persistent heavy rainfall (PHR) events over South China (SC) associated with the 10–30-day intraseasonal oscillation (ISO) before the South China Sea Summer Monsoon (SCSSM) onset (SCSSM-I) and after the SCSSM onset (SCSSM-II) in the first rainy season (April–June). About 25.0% and 65.3% of the total PHR events over SC occur during SCSSM-I and SCSSM-II, respectively. A PHR process usually experiences a suppressed phase, a developing phase, an active phase, a decaying phase, and an ending phase. At the active phase of PHR events during SCSSM-I (SCSSM-II), a northwest–southeast (southeast-northwest)-oriented wavetrain emanated from northwestern Mongolia (the Philippines) migrates southeastward (northwestward) at the lower troposphere; and meanwhile, a circumglobal teleconnection with the positive (negative) phase propagates eastward along the westerly jet, forming a shallower (deeper) convective system over SC. Specifically during SCSSM-II, a positive Pacific–Japan-like teleconnection also makes a contribution to the PHR events over SC. Further planetary boundary layer (PBL) integrated moisture budget diagnosis suggests that the vertical moisture advection dominates the lower-tropospheric moistening for the PHR events at the developing and active phases, in which the leading term is the advection of the background mean moisture by the ISO ascending flow associated with PBL moisture convergence. The magnitude of the horizontal moisture advection is five times smaller than the vertical moisture advection, which is mainly contributed by the advection across the background mean moisture gradient by the ISO flow. We also present further discussions regarding the factors dominating the low-frequency ascending motions over SC and the role of low-frequency sea surface temperature anomalies before and after the SCSSM onset, which may deepen the understanding of the effects of atmospheric internal dynamical processes and the external forcing factors on the formation, strengthening, and demise of the SC PHR events.

Parkinson’s disease (PD) is a serious neurodegenerative disease. Most of the current treatment can only alleviate symptoms, but not stop the progress of the disease. Therefore, it is crucial to find medicines to completely cure PD. Finding new indications of existing drugs through drug repositioning can not only reduce risk and cost, but also improve research and development efficiently. A drug repurposing method was proposed to identify potential Parkinson’s disease-related drugs based on multi-source data integration and convolutional neural network. Multi-source data were used to construct similarity networks, and topology information were utilized to characterize drugs and PD-associated proteins. Then, diffusion component analysis method was employed to reduce the feature dimension. Finally, a convolutional neural network model was constructed to identify potential associations between existing drugs and LProts (PD-associated proteins). Based on 10-fold cross-validation, the developed method achieved an accuracy of 91.57%, specificity of 87.24%, sensitivity of 95.27%, Matthews correlation coefficient of 0.8304, area under the receiver operating characteristic curve of 0.9731 and area under the precision–recall curve of 0.9727, respectively. Compared with the state-of-the-art approaches, the current method demonstrates superiority in some aspects, such as sensitivity, accuracy, robustness, etc. In addition, some of the predicted potential PD therapeutics through molecular docking further proved that they can exert their efficacy by acting on the known targets of PD, and may be potential PD therapeutic drugs for further experimental research. It is anticipated that the current method may be considered as a powerful tool for drug repurposing and pathological mechanism studies.

A persistent heavy rainfall (PHR) process usually undergoes a suppressed phase, a developing phase, an active phase, a decaying phase, and an ending phase. This study tries to determine the PHR phase related to 10–30-day (high-frequency) intraseasonal oscillation (HF-ISO) over Southeastern China (including South China (SC) and the Yangtze River Basin (YRB)), by using the daily precipitation from the China Meteorological Administration (CMA) surface stations in China. We found that the HF-ISO associated with the PHR has a larger amplitude in the positive phase relative to that in the negative phase. Considering the asymmetry of the PHR process, we divide the PHR process into 5 phases with 1std in the positive phase and − 0.75std in the negative one as the threshold, that is, the suppressed phase, developing phase, active phase, decaying phase, and ending phase. During the different phases, the variables are in a wave-train-like pattern and strike from southeast to northwest. In addition to water vapor, convective instability (CI), and moisture static energy (MSE), the anomalies of other variables are not evident in the developing phase and decaying phase. Furthermore, the extremes of moisture, CI, and MSE are found ahead of the peak precipitation. In this study, we found that the moisture tendency is much larger in the suppressed phase than in the ending phase over both SC and the YRB. Thus, in the following phase, more (less) moisture leads to a stronger (weaker) convective instability and a more (less) recharge of MSE, and favoring (unfavoring) for the development of PHR. Over SC, the main reason for the difference of the moisture tendency during the suppressed phase and the ending phase is the meridional advection based on the mean state and eddy-eddy flow interactions. Over the YRB, the difference of the moisture tendency is due to the advection by the anomalous zonal wind across the mean moisture gradient.

Sea surface temperature (SST) anomalies profoundly shape regional precipitation variability, yet their pathways are often obscured by seasonal/monthly mean-state analyses overlooking daily atmospheric dynamics. Focusing on monsoon-affected South China, we show that the rainy-season rainfall interannual variability is primarily driven by shifts in daily circulation regimes rather than rainfall intensity. Objective classification identifies four dominant regimes: two low-pressure system–related types, a pre-onset monsoon regime, and a South China Sea monsoon–dominated regime. Moisture tracking and precipitation decomposition confirm that regime frequency dominates year-to-year rainfall variations. SST anomalies in the Indian, Pacific, and Atlantic Oceans modulate these frequencies by triggering large-scale atmospheric responses, particularly anomalous cyclones/anticyclones over the western North Pacific. These atmospheric changes alter convection and instability, driving low-pressure activity and monsoon onset. Our findings reveal a regime-mediated mechanism linking remote ocean variability to regional hydroclimate extremes, offering new insights for improving climate prediction and projection under global warming.