Identifying the geospatial relationship of surface ozone pollution in China: Implications for key pollution control regions.

Surface ozone pollution, as a pressing environmental concern, has garnered widespread attention across China. Due to air mass transport, effective control of ozone pollution is highly dependent on collaborative efforts across neighboring regions. However, specific regions with strong internal interactions of ozone pollution are not yet well identified. Here, we introduced the Geospatial SHapley Additive exPlanation (GeoSHAP) approach, which primarily involves machine learning and geostatistical algorithms. Based on extensive atmospheric environmental monitoring data from 2017 to 2021, machine learning models were employed to train and predict ozone concentrations at the target location. The R2 values on the test sets of different scale regions all reached 0.98 in the overall condition, indicating that the core model has good accuracy and generalization ability. The results highlight key regions with high ozone geospatial relationship (OGR) index, predominantly located in the Northern District (ND), spanning the Fen-Wei Plain, the Loess Plateau, and the North China Plain, as well as within portions of the Yangtze River Delta (YRD) and the Pearl River Delta (PRD). Further investigation indicated that high geospatial relationships stem from a synergy between anthropogenic and natural factors, with anthropogenic factors serving as a pivotal element. This study revealed key regions with the most urgent need for joint control of anthropogenic sources to mitigate ozone pollution.

Origins of formaldehyde in a mountainous background atmosphere of southern China.

Formaldehyde (HCHO) is one of the key indicators of severe photochemical pollution and strong atmospheric oxidation capacity in southern China. However, current information on the origins of regional HCHO and the impacts of polluted air masses remains scarce and unclear. In this study, an intensive observation of HCHO was conducted at a mountainous background site in southern China during typical photochemical pollution episodes. The concentrations of HCHO reached up to 6.14 ppbv and averaged at 2.68 ± 1.11 ppbv. Source appointment using a photochemical age-based parameterization method revealed significant contributions of secondary formation (50 %) and biomass burning (42 %). Meanwhile, under the influence of the East Asian Winter Monsoon, polluted air masses from central and western China can significantly increase the regional HCHO levels. The simulation results adopting the Rapid Adaptive Optimization Model for Atmospheric Chemistry model further demonstrated that the intrusion of active anthropogenic pollutants (e.g., small-molecule alkenes) can accelerate the net production rate of HCHO, particularly through BVOC-oxidation pathways. This study suggests a potential enhanced mechanism of HCHO production resulting from anthropogenic-biogenic interactions. It highlights that polluted air masses carrying abundant HCHO from upwind areas may facilitate severe photochemical pollution in the Greater Bay Area.

Coarse particles compensate for missing daytime sources of nitrous acid and enhance atmospheric oxidation capacity in a coastal atmosphere.

Large missing sources of daytime atmospheric nitrous acid (HONO), a vital source of hydroxyl radicals (OH) through its photolysis, frequently exist in global coastal regions. In this study, ambient HONO and relevant species were measured at a coastal site in the Pearl River Delta (PRD), China, during October 2019. Relatively high concentrations (0.32 ± 0.19 ppbv) and daytime peaks at approximately 13:00 of HONO were observed, and HONO photolysis was found to be the dominant (55.5 %) source of the primary OH production. A budget analysis of HONO based on traditional sources suggested large unknown sources during the daytime (66.4 %), which had a significant correlation with the mass of coarse particles (PM2.5-10) and photolysis frequency (J(NO2)). When incorporating photolysis of the abundant nitrate measured in coarse particles with a reasonable enhancement factor relative to fine particles due to favorable aerosol conditions, the missing daytime sources of HONO could be fully compensated by coarse particles serving as the largest source at this coastal site. Our study revealed great potential of coarse particles as a strong daytime HONO source, which has been ignored before but can efficiently promote NOx recycling and thus significantly enhance atmospheric oxidation capacity.

Comprehensive effects of climate, land use/cover and management practices on runoff and nutrient variations in a rapidly urbanizing watershed.

As non-point source pollution has emerged as a significant global and regional concern, climate change (CC), land use/cover transformation (LUCT), and management practices (MP) play vital roles in addressing nutrient pollution. However, current studies lack comprehensive quantification and consistent conclusions on the response to these factors, especially for management practices. To quantify and elucidate the impact of representative environmental factors on rapidly urbanizing regions, this study focused on the Shenzhen River, which serves as the most typical urbanizing watershed. Using a process-based distributed hydrological model with a factor-controlled simulation method, we identified significant differences in nutrient concentrations and the impacts of climate variability, land use/cover changes, and anthropogenic interventions from 2003 to 2020. Moreover, effective measures greatly improved water quality in the Shenzhen River during study period, as evident from trend and cluster analysis. However, ecological water supplements implemented since 2016 have led to a slight reduction in simulated runoff performance, and CC may amplify the synergistic effects of precipitation and temperature on the river system. While the implemented practices have been effective in reducing total nitrogen (TN) and total phosphorus (TP) loads, strong TN pollution control is still needed in rapidly urbanizing areas due to the results of land use/cover type changes. Our findings emphasize the intricate interplay among CC, LUCT, and MP in shaping water quality and hydrological processes in rapidly urbanizing watersheds, and clarify the independent effects of these factors on nutrients. This study contributes to a better understanding of the complex interactions between multiple factors in watersheds and provides guidance for sustainable watershed management.

Multi-scenario simulation of runoff and nutrient loads in a rapidly urbanizing watershed during China's Dual Carbon periods.

Apprehending the hydrological and nutrient variations in rapidly urbanizing watersheds under changing environments is crucial for pollution control and water resource management. However, existing studies have primarily focused on hydrological processes, neglecting water quality aspects, and comprehensive assessment of future runoff and nutrient loads in these watersheds during China's Dual Carbon periods is limited. This study firstly bridges these gaps by constructing multi-scenario with different levels of "Urban Development - Ecological Conservation" and utilizing latest bias-corrected General Circulation Models or Global Climate Models (GCMs) projections to evaluate future runoff and nutrient loads in the Shenzhen River. The calibrated and validated models display satisfactory performance in simulating runoff, nutrient loads, and land use types. The bias-corrected GCMs projections exhibit enhanced accuracy for temperature variables, particularly during the wet season. Implementing effective ecological protection measures is paramount in mitigating water quantity fluctuations and controlling total nitrogen pollution, which is closely associated with urban development and human activities. Conversely, total phosphorus loads demonstrate greater simulation uncertainty, particularly during the dry season of the Carbon Neutrality period, requiring further exploration. Compared to the baseline period, runoff changes minimally, with notable seasonal variations. The findings highlight the escalating uncertainty in load predictions as time progresses. Additionally, addressing uncertainties in precipitation projections driven by GCMs is imperative, given their substantial influence on runoff and nutrient load simulations, particularly during challenging dry seasons. While further research is needed to reduce simulation uncertainty, our study provides valuable insights into nitrogen-phosphorus pollution control and sustainable water resource management in rapidly urbanizing watersheds, especially during the near-term period.

Assessing water quality in the Pearl River for the last decade based on clustering: Characteristic, evolution and policy implications.

The Pearl River (PR) is China's second-largest river, playing a crucial role in regulating and supplying water in the southeast. However, for the last decade, the PR has been experiencing water quality deterioration due to population growth, rapid economic development, and diverse human activities, particularly in its delta areas. This study analyzed the characteristics and evolution of eight water quality variables, including pH values (pH), water temperature (WT), dissolved oxygen (DO), five-day biochemical oxygen demand (BOD5), permanganate index (PI), total phosphorus (TP), ammonia nitrogen (NH3N), and fluoride (F-), which were monitored monthly at 16 water quality monitoring stations from January 2009 to August 2019. Overall, annual average BOD5 and F- concentrations met Class I water quality standards, while TP and NH3N conformed to lower standards. The cluster results showed noticeable differences for parameter grouping (DO-organic parameters-nutrient and solutes), seasonal variation (wet and dry), and water quality status (contaminated-remediating-fine). The Water Quality Index (WQI) ranged from 8.3 ("very poor") to 91.7 ("excellent") in the entire basin from 2009 to 2019, and NH3N-DO based WQImins were identified using the All-Subsets Linear Regression method. The fitting results of the Generalized Additive Models displayed that the deviance explained by natural factors ranged from 37.2% to 61.3%, while the socioeconomic explanation exceeded 70%. The WQImin component evolution (2003-2019) of Shenzhen River estuary, the most important part of the PR estuary, agreed with key parameter variations in heterogeneous clusters in the entire basin. Moreover, Shenzhen's water quality remediation applications indicated that reasonable-efficient-powerful efforts and support from governments could accelerate recovery. For the management departments, consistent measures should be strictly enforced, and elaborate regionalized management based on clusters could be attempted to maintain excellent water quality.

The evaluation of six genes combined value in glioma diagnosis and prognosis.

PURPOSE: Glioma is the most common and fatal type of brain tumour. Owing to its aggressiveness and lethality, early diagnosis and prediction of patient survival are very important. This study aimed to identify key genes and biomarkers for glioma that can guide clinicians in making rapid diagnosis and prognostication. METHODS: Data mining of The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), Repository of Molecular Brain Neoplasia Data, and Genotype-Tissue Expression Project brain expression data revealed significantly differentially expressed genes (DEGs), and the risk scores of individual patients were calculated. WGCNA was utilized to screen for genes most related to clinical diagnosis. Prognostic genes associated with glioma were selected via combining the LASSO regression with univariate and multivariate Cox regression and protein-protein interaction network analyses. Then, a nomogram was constructed. And CGGA dataset was utilized to validated. The protein expression levels of the signature were detected using the human protein atlas. Drug response prediction was carried out using the package "pRRophetic". RESULTS: A six-gene signature (KLF6, CHI3L1, SERPINE1, ANGPT2, TGFBR1, and PTX3) was identified and used to stratify patients into low- and high-risk groups. Survival, ROC curve, and Cox analyses clarified that the six hub genes were a favourable independent prognostic factor for patients with glioma. A nomogram was set up by integrating clinical parameters with risk signatures, showing high precision for predicting 2-, 3-, 4-, 5-years survival. In addition, the expression of most genes was consistent with protein expression. Furthermore, the sensitivity to the top ten drugs in the GDSC database of the high-risk group was significantly higher than the low-risk group. CONCLUSION: Based on genetic profiles and clinicopathological features, including age, grade, isocitrate dehydrogenase mutation status, we constructed a comprehensive prognostic model for patients with glioma. These signatures can be regarded as biomarkers to predict the prognosis of gliomas, possibly providing more therapeutic strategies for future clinical research.

Ramelteon improves blood-brain barrier of focal cerebral ischemia rats to prevent post-stroke depression via upregulating occludin.

Post-stroke depression (PSD) negatively affects the prognosis of post-stroke animals. Ramelteon has neuroprotection for chronic ischemia animals, but the effect and the biological mechanism of it on PSD is still unclear. This study explored the effects of ramelteon with prophylactic administration on blood-brain barrier in rats with middle cerebral artery occlusion (MCAO) and the oxygen-glucose deprivation/reperfusion (OGD/R) bEnd.3 cells and found that ramelteon pretreatment improved the depressive-like behaviors and decreased infarct area in MCAO rats. Also, this study found ramelteon pretreatment improved viability and inhibited permeability in OGD/R cells. In addition, this study found that MCP-1, TNF-α, and IL-1 levels were raised in the MCAO rats and that occludin protein and mRNA levels were decreased in the MCAO and the OGD/R models, while the Egr-1 level was up-regulated. All of these were antagonized by ramelteon pretreatment. In addition, overexpression of Egr-1 could reverse the effect of 100 nM ramelteon pretreatment on FITC and occludin levels in OGD/R cells. In short, this study has demonstrated that the protective effect on PSD of ramelteon pretreatment on MCAO rats is related to the development of BBB permeability and that ramelteon regulates occludin to protect the BBB by inhibiting Egr-1.

Machine learning-based mRNA signature in early acute myocardial infarction patients: the perspective toward immunological, predictive, and personalized.

Patients diagnosed with stable coronary artery disease (CAD) are at continued risk of experiencing acute myocardial infarction (AMI). This study aims to unravel the pivotal biomarkers and dynamic immune cell changes, from an immunological, predictive, and personalized viewpoint, by implementing a machine-learning approach and a composite bioinformatics strategy. Peripheral blood mRNA data from different datasets were analyzed, and CIBERSORT was used for deconvoluting human immune cell subtype expression matrices. Weighted gene co-expression network analysis (WGCNA) in single-cell and bulk transcriptome levels was conducted to explore possible biomarkers for AMI, with a particular emphasis on examining monocytes and their involvement in cell-cell communication. Unsupervised cluster analysis was performed to categorize AMI patients into different subtypes, and machine learning methods were employed to construct a comprehensive diagnostic model to predict the occurrence of early AMI. Finally, RT-qPCR on peripheral blood samples collected from patients validated the clinical utility of the machine learning-based mRNA signature and hub biomarkers. The study identified potential biomarkers for early AMI, including CLEC2D, TCN2, and CCR1, and found that monocytes may play a vital role in AMI samples. Differential analysis revealed that CCR1 and TCN2 exhibited elevated expression levels in early AMI compared to stable CAD. Machine learning methods showed that the glmBoost+Enet [alpha=0.9] model achieved high predictive accuracy in the training set, external validation sets, and clinical samples in our hospital. The study provided comprehensive insights into potential biomarkers and immune cell populations involved in the pathogenesis of early AMI. The identified biomarkers and the constructed comprehensive diagnostic model hold great promise for predicting the occurrence of early AMI and can serve as auxiliary diagnostic or predictive biomarkers.

Evolution characteristic of atmospheric black carbon particles at a coastal site in the Pearl River Delta, China.

The mixing of black carbon (BC) with secondary materials is a major uncertainty source in assessing its radiative forcing. However, current understanding of the formation and evolution of various BC components is limited, particularly in the Pearl River Delta, China. This study measured submicron BC-associated nonrefractory materials and the total submicron nonrefractory materials using a soot particle aerosol mass spectrometer and a high-resolution time-of-flight aerosol mass spectrometer, respectively, at a coastal site in Shenzhen, China. Two distinct atmospheric conditions were also identified to further explore the distinctive evolution of BC-associated components: polluted period (PP) and clean period (CP). Comparing the components of two particles, we found that more-oxidized organic factor (MO-OOA) prefers to form on BC during PP rather CP. The formation of MO-OOA on BC (MO-OOABC) was affected by both enhanced photochemical processes and nocturnal heterogeneous processes. Enhanced photo-reactivity of BC, photochemistry during the daytime, and heterogeneous reaction at nighttime were potential pathways for MO-OOABC formation during PP. The fresh BC surface was favorable for the formation of MO-OOABC. Our study shows the evolution of BC-associated components under different atmospheric conditions, which should be considered in regional climate models to improve the assessment of the climate effects of BC.

Environmental regulation and green innovation of polluting firms in China.

The main objective of this paper is to study the impact of the Ambient Air Quality Standard (2012) on the green innovation of Chinese firms in polluting industries. The analysis features "leverage effect" of Porter Hypothesis imposed by environmental regulations and exploits exogenous variations caused by the promulgation of the new policy. Based on the exogenous variations, this paper uses the time varying PSM-DID method. The findings of this study suggest that the implementation of the new policy improves firms' green innovation. Increments in R&D investment and environmental protection investment are channels through which the new standard positively affects firms' green innovation. The cross-sectional heterogeneity analysis exhibits that the effect of this environmental regulation is stronger for firms with bigger size and lower financial constraints. The contribution and significance of this study are as follows: our study enriches understanding of the impact of environmental regulation on firms' green innovation by empirically confirming the influencing channels of the impact of environmental regulations on green innovation. In addition, this paper contributes to the firms' green innovation literature by empirically validating the role of corporate characteristics in moderating the effect of environmental regulations.

Progress in quantitative research on the relationship between atmospheric oxidation and air quality.

Atmospheric oxidizing capacity (AOC) is an essential driving force of troposphere chemistry and self-cleaning, but the definition of AOC and its quantitative representation remain uncertain. Driven by national demand for air pollution control in recent years, Chinese scholars have carried out studies on theories of atmospheric chemistry and have made considerable progress in AOC research. This paper will give a brief review of these developments. First, AOC indexes were established that represent apparent atmospheric oxidizing ability (AOIe) and potential atmospheric oxidizing ability (AOIp) based on aspects of macrothermodynamics and microdynamics, respectively. A closed study refined the quantitative contributions of heterogeneous chemistry to AOC in Beijing, and these AOC methods were further applied in Beijing-Tianjin-Hebei and key areas across the country. In addition, the detection of ground or vertical profiles for atmospheric OH·, HO2·, NO3· radicals and reservoir molecules can now be obtained with domestic instruments in diverse environments. Moreover, laboratory smoke chamber simulations revealed heterogeneous processes involving reactions of O3 and NO2, which are typical oxidants in the surface/interface atmosphere, and the evolutionary and budgetary implications of atmospheric oxidants reacting under multispecies, multiphase and multi-interface conditions were obtained. Finally, based on the GRAPES-CUACE adjoint model improved by Chinese scholars, simulations of key substances affecting atmospheric oxidation and secondary organic and inorganic aerosol formation have been optimized. Normalized numerical simulations of AOIe and AOIp were performed, and regional coordination of AOC was adjusted. An optimized plan for controlling O3 and PM2.5 was analyzed by scenario simulation.

Characterizing formation mechanisms of secondary aerosols on black carbon in a megacity in South China.

Refractory black carbon (rBC) aerosols emitted from incomplete combustion are important climate forcers. Understanding the chemical characteristics and evolution of rBC-related components is particularly crucial to assess rBC environmental impacts. Here, we explored the chemical components of rBC in Shenzhen, China, using a soot-particle aerosol mass spectrometer (SP-AMS). The observations showed that the rBC coating was mainly composed of secondary aerosols with an average mass contribution of 84.7 %. Among them, secondary organic coating occupied ∼57.7 % of the total coating mass. Exploration of the relationship between secondary organic aerosol (SOA) coating and Ox (=NO2 + O3, an indicator of the extent of photochemical processing) showed that SOA coating was generated mainly through photochemical oxidation during the day. Similarly, sulfate coating, with a small mass fraction of 0.9 %, was also dominated by photochemical oxidation. In contrast, nitrate coating responded positively to ambient relative humidity, especially at night, indicating that it was driven by heterogeneous reactions. In addition, the increased ratio of nitrate on rBC to bulk nitrate at night suggested that black carbon surface could facilitate nocturnal nitrate formation.

A novel machine learning method for evaluating the impact of emission sources on ozone formation.

Ambient ozone air pollution is one of the most important environmental challenges in China today, and it is particularly significant to identify pollution sources and formulate control strategies. In present study, we proposed a novel method of positive matrix factorization-SHapley Additive explanation (PMF-SHAP) for evaluating the impact of emission sources on ozone formation, which can quantify the main emission sources of ozone pollution. In this method, we first used the PMF model to identify the source of volatile organic compounds (VOCs), and then quantified various emission sources using a combination of machine learning (ML) models and the SHAP algorithm. The R2 of the optimal ML model in this method was as high as 0.96, indicating that the prediction performance was excellent. Furthermore, we explored the impact of different emission sources on ozone formation, and found that ozone formation in Shenzhen was more affected by VOCs, of which vehicle emission sources may have the greatest impact. Our results suggest that the appropriate combination of traditional models with ML models can well address environmental pollution problems. Moreover, the conclusions obtained based on the PMF-SHAP method were different from the traditional ozone formation potential (OFP) results, providing valuable clues for related mechanism studies.

Multiple Impacts of Aerosols on O3 Production Are Largely Compensated: A Case Study Shenzhen, China.

Tropospheric ozone (O3) is a harmful gas compound to humans and vegetation, and it also serves as a climate change forcer. O3 is formed in the reactions of nitrogen oxides and volatile organic compounds (VOCs) with light. In this study, an O3 pollution episode encountered in Shenzhen, South China in 2018 was investigated to illustrate the influence of aerosols on local O3 production. We used a box model with comprehensive heterogeneous mechanisms and empirical prediction of photolysis rates to reproduce the O3 episode. Results demonstrate that the aerosol light extinction and NO2 heterogeneous reactions showed comparable influence but opposite signs on the O3 production. Hence, the influence of aerosols from different processes is largely counteracted. Sensitivity tests suggest that O3 production increases with further reduction in aerosols in this study, while the continued NOx reduction finally shifts O3 production to an NOx-limited regime with respect to traditional O3-NOx-VOC sensitivity. Our results shed light on the role of NOx reduction on O3 production and highlight further mitigation in NOx not only limiting the production of O3 but also helping to ease particulate nitrate, as a path for cocontrol of O3 and fine particle pollution.

Spectral control of nonclassical light pulses using an integrated thin-film lithium niobate modulator.

Manipulating the frequency and bandwidth of nonclassical light is essential for implementing frequency-encoded/multiplexed quantum computation, communication, and networking protocols, and for bridging spectral mismatch among various quantum systems. However, quantum spectral control requires a strong nonlinearity mediated by light, microwave, or acoustics, which is challenging to realize with high efficiency, low noise, and on an integrated chip. Here, we demonstrate both frequency shifting and bandwidth compression of heralded single-photon pulses using an integrated thin-film lithium niobate (TFLN) phase modulator. We achieve record-high electro-optic frequency shearing of telecom single photons over terahertz range (±641 GHz or ±5.2 nm), enabling high visibility quantum interference between frequency-nondegenerate photon pairs. We further operate the modulator as a time lens and demonstrate over eighteen-fold (6.55 nm to 0.35 nm) bandwidth compression of single photons. Our results showcase the viability and promise of on-chip quantum spectral control for scalable photonic quantum information processing.

Integrated femtosecond pulse generator on thin-film lithium niobate.

Integrated femtosecond pulse and frequency comb sources are critical components for a wide range of applications, including optical atomic clocks1, microwave photonics2, spectroscopy3, optical wave synthesis4, frequency conversion5, communications6, lidar7, optical computing8 and astronomy9. The leading approaches for on-chip pulse generation rely on mode-locking inside microresonators with either third-order nonlinearity10 or with semiconductor gain11,12. These approaches, however, are limited in noise performance, wavelength and repetition rate tunability 10,13. Alternatively, subpicosecond pulses can be synthesized without mode-locking, by modulating a continuous-wave single-frequency laser using electro-optic modulators1,14-17. Here we demonstrate a chip-scale femtosecond pulse source implemented on an integrated lithium niobate photonic platform18, using cascaded low-loss electro-optic amplitude and phase modulators and chirped Bragg grating, forming a time-lens system19. The device is driven by a continuous-wave distributed feedback laser chip and controlled by a single continuous-wave microwave source without the need for any stabilization or locking. We measure femtosecond pulse trains (520-femtosecond duration) with a 30-gigahertz repetition rate, flat-top optical spectra with a 10-decibel optical bandwidth of 12.6 nanometres, individual comb-line powers above 0.1 milliwatts, and pulse energies of 0.54 picojoules. Our results represent a tunable, robust and low-cost integrated pulsed light source with continuous-wave-to-pulse conversion efficiencies an order of magnitude higher than those achieved with previous integrated sources. Our pulse generator may find applications in fields such as ultrafast optical measurement19,20 or networks of distributed quantum computers21,22.

Secondary organic aerosol formation from straw burning using an oxidation flow reactor.

Herein, we use an oxidation flow reactor, Gothenburg: Potential Aerosol Mass (Go: PAM) reactor, to investigate the secondary organic aerosol (SOA) formation from wheat straw burning. Biomass burning emissions are exposed to high concentrations of hydroxyl radicals (OH) to simulate processes equivalent to atmospheric oxidation of 0-2.55 days. Primary volatile organic compounds (VOCs) were investigated, and particles were measured before and after the Go: PAM reactor. The influence of water content (i.e. 5% and 11%) in wheat straw was also explored. Two burning stages, the flaming stage, and non-flaming stages, were identified. Primary particle emission factors (EFs) at a water content of 11% (∼3.89 g/kg-fuel) are significantly higher than those at a water content of 5% (∼2.26 g/kg-fuel) during the flaming stage. However, the water content showed no significant influence at the non-flaming stage. EFs of aromatics at a non-flaming stage (321.8±46.2 mg/kg-fuel) are larger than that at a flaming stage (130.9±37.1 mg/kg-fuel). The OA enhancement ratios increased with the increase in OH exposure at first and decreased with the additional increment of OH exposure. The maximum OA enhancement ratio is ∼12 during the non-flaming stages, which is much higher than ∼ 1.7 during the flaming stages. The mass spectrum of the primary wheat burning organic aerosols closely resembles that of resolved biomass burning organic aerosols (BBOA) based on measurements in ambient air. Our results show that large gap (∼60%-90%) still remains to estimate biomass burning SOA if only the oxidation of VOCs were included.

Ambra1 regulates apoptosis and chemosensitivity in breast cancer cells through the Akt-FoxO1-Bim pathway.

The sensitivity of cells to chemotherapeutic agents has a major effect on disease outcome in breast cancer patients. Unfortunately, there are numerous factors involved in the regulation of chemosensitivity, and the mechanisms need to be further investigated. Autophagy/Beclin 1 regulator 1 (Ambra1) is a key protein in the crosstalk between autophagy and apoptosis. It controls the switch between these two processes, which determines whether cells survive or die. Induction of apoptosis is the primary mechanism by which most chemotherapeutic drugs eliminate cancer cells. Recently, Ambra1 has been shown to modulate paclitaxel-induced apoptosis in breast cancer cells via the Bim/mitochondrial pathway, thereby modifying the sensitivity of cells to paclitaxel. However, how Ambra1 regulates Bim expression remains unclear. Here, we further confirmed that Bim plays an indispensable role in Ambra1's regulation of apoptosis and chemosensitivity in breast cancer cells. Furthermore, Ambra1 was found to regulate Bim expression at the transcriptional level through the Akt-FoxO1 pathway. Therefore, we propose a novel pathway, Ambra1-Akt-FoxO1-Bim, which regulates apoptosis and chemosensitivity in breast cancer cells. Thus, Ambra1 may represent a potential target for breast cancer treatment.

Decisive role of ozone formation control in winter PM2.5 mitigation in Shenzhen, China.

During the COVID-19 lockdown, atmospheric PM2.5 in the Pearl River Delta (PRD) showed the highest reduction in China, but the reasons, being a critical question for future air quality policy design, are not yet clear. In this study, we analyzed the relationships among gaseous precursors, secondary aerosols and atmospheric oxidation capacity in Shenzhen, a megacity in the PRD, during the lockdown period in 2020 and the same period in 2021. The comprehensive observational datasets showed large lockdown declines in all primary and secondary pollutants (including O3). We found that, however, the daytime concentrations of secondary aerosols during the lockdown period and normal period were rather similar when the corresponding odd oxygen (Ox≡O3+NO2, an indicator of photochemical processing avoiding the titration effect of O3 by freshly emitted NO) were at similar levels. Therefore, reduced Ox, rather than the large reduction in precursors, was a direct driver to achieve the decline in secondary aerosols. Moreover, Ox was also found to determine the spatial distribution of intercity PM2.5 levels in winter PRD. Thus, an effective strategy for winter PM2.5 mitigation should emphasize on control of winter O3 formation in the PRD and other regions with similar conditions.