Resolving Ultraviolet-Visible Spectra for Complex Dissolved Mixtures of Multitudinous Organic Matters in Aerosols.

Light-absorbing organic aerosols, referred to as brown carbon (BrC), play a vital role in the global climate and air quality. Due to the complexity of BrC chromophores, the identified absorbing substances in the ambient atmosphere are very limited. However, without comprehensive knowledge of the complex absorbing compounds in BrC, our understanding of its sources, formation, and evolution mechanisms remains superficial, leading to great uncertainty in climatic and atmospheric models. To address this gap, we developed a constrained non-negative matrix factorization (NMF) model to resolve the individual ultraviolet-visible spectrum for each substance in dissolved organic aerosols, with the power of ultrahigh-performance liquid chromatography-diode array detector-ultrahigh-resolution mass spectrometry (UHPLC-DAD-UHRMS). The resolved spectra were validated by selected standard substances and validation samples. Approximately 40,000 light-absorbing substances were recognized at the MS1 level. It turns out that BrC is composed of a vast number of substances rather than a few prominent chromophores in the urban atmosphere. Previous understanding of the absorbing feature of BrC based on a few identified compounds could be biased. Weak-absorbing substances missed previously play an important role in BrC absorption when they are integrated due to their overwhelming number. This model brings the property exploration of complex dissolved organic mixtures to a molecular level, laying a foundation for identifying potentially significant compositions and obtaining a comprehensive chemical picture.

Implication of lncRNA MSTRG.81401 in Hippocampal Pyroptosis Induced by P2X7 Receptor in Type 2 Diabetic Rats with Neuropathic Pain Combined with Depression.

Major depressive disorder (MDD) is a common complication of diabetes and is often observed alongside diabetic neuropathic pain (DNP) as a comorbidity in diabetic patients. Long non-coding RNA (lncRNA) plays an important role in various pathophysiological processes. The P2X7 receptor is responsible for triggering inflammatory responses, such as pyroptosis, linked to pain and depression. The aim of this study was to investigate the effect of lncRNA MSTRG.81401 on hippocampal pyroptosis induced by the P2X7 receptor in diabetic rats with DNP combined with MDD (DNP + MDD). Our results showed that the expression of lncRNA MSTRG.81401 was significantly elevated in the hippocampus of DNP + MDD rats compared with the control group. Following the administration of shRNA targeting lncRNA MSTRG.81401, a notable elevation in mechanical and thermal pain thresholds was observed in rats with comorbid DNP and MDD. Additionally, significant improvements in depression-like behaviors were evident in the open-field test (OFT), sucrose preference test (SPT), and forced swim test (FST). In the DNP + MDD rats, elevated levels in hippocampal P2X7 receptor mRNA and protein were observed, along with increased co-expression of P2X7 and the astrocytic marker glial fibrillary acidic protein (GFAP). Meanwhile, in DNP + MDD rats, the heightened mRNA expression of NOD-like receptor protein 3 (NLRP3), apoptosis-associated speck-like protein (ASC), pyroptosis-related protein Gasdermin D (GSDMD), caspase-1, IL-1ß, IL-18, and TNF-α was detected, in addition to increased serum levels of IL-1ß, IL-18 and TNF-α. After shRNA treatment with lncRNA MSTRG.81401, the above abnormal changes in indicators for pyroptosis and inflammation were improved. Therefore, our study demonstrates that shRNA of lncRNA MSTRG.81401 can alleviate the pain and depression-like behaviors in diabetic rats associated with the comorbidity of DNP and MDD by inhibiting the hippocampal P2X7 receptor-mediated pyroptosis pathway and pro-inflammatory responses. This suggests that the P2X7R/NLRP3/caspase-1 implicated pyroptosis and inflammatory scenario may serve as a potential target for the management of comorbid DNP and MDD in diabetes.

Predicting Atmospheric Particle Phase State Using an Explainable Machine Learning Approach Based on Particle Rebound Measurements.

The particle phase state plays a vital role in the gas-particle partitioning, multiphase reactions, ice nucleation activity, and particle growth in the atmosphere. However, the characterization of the atmospheric phase state remains challenging. Herein, based on measured aerosol chemical composition and ambient relative humidity (RH), a machine learning (ML) model with high accuracy (R2 = 0.952) and robustness (RMSE = 0.078) was developed to predict the particle rebound fraction, f, which is an indicator of the particle phase state. Using this ML model, the f of particles in the urban atmosphere was predicted based on seasonal average aerosol chemical composition and RH. Regardless of seasons, aerosols remain in the liquid state of mid-high latitude cities in the northern hemisphere and in the semisolid state over semiarid regions. In the East Asian megacities, the particles remain in the liquid state in spring and summer and in the semisolid state in other seasons. The effects of nitrate, which is becoming dominant in fine particles in several urban areas, on the particle phase state were evaluated. More nitrate led the particles to remain in the liquid state at an even lower RH. This study proposed a new approach to predict the particle phase state in the atmosphere based on RH and aerosol chemical composition.

Observational evidence for the non-suppression effect of atmospheric chemical modification on the ice nucleation activity of East Asian dust.

Airborne mineral dust triggers ice formation in clouds and alters cloud microphysical properties by acting as ice-nucleating particles (INPs), potentially influencing weather and climate at regional and global scales. Anthropogenic pollution would modify natural mineral dust during the atmospheric transport process. However, the effects of anthropogenic pollution aging on the ice nucleation activity (INA) of mineral dust remain not well-understood. In this study, we investigated the immersion mode ice nucleation properties and particle chemical characterizations of collected size-resolved Asian dust samples (eight particle size classes ranging from 0.18 to 10.0 µm), and testified the chemical modification of aged dust particles via particle chemistry and morphology analyses including the mass concentrations of particulate matter, the water-soluble ion concentrations, the mental element concentrations, and single-particle morphology. The mass fraction of Ca2+ in element Ca and the mean relative mass proportions of supermicron Ca2+ increased by 67.0 % and 3.5-11.2 % in aged Asian dust particles, respectively, suggesting the occurrence of heterogeneous reactions. On the other hand, the total INP concentrations (total NINP) and total ice nucleation active site densities (total ns(T)) were consistent between aged and normal dust particles (0.62-1.18 times) without a statistically significant difference. And the NINP and ns(T) of chemically aged supermicron dust (1.0-10.0 µm) in each particle size class were nearly equal to or slightly higher than those of normal Asian dust, which were 0.70-2.45 times and 0.64-4.34 times at -18 °C, respectively. These results reveal that anthropogenic air pollution does not notably change the INP concentrations and does not impair the INA of Asian dust. Our work provides direct observational evidence and clarifies the non-suppression effect of anthropogenic air pollution on the INA of East Asian dust, advancing the understanding of the ice nucleation of airborne aged mineral dust.

Comparison of Phase States of PM2.5 over Megacities, Seoul and Beijing, and Their Implications on Particle Size Distribution.

Although the particle phase state is an important property, there is scant information on it, especially, for real-world aerosols. To explore the phase state of fine mode aerosols (PM2.5) in two megacities, Seoul and Beijing, we collected PM2.5 filter samples daily from Dec 2020 to Jan 2021. Using optical microscopy combined with the poke-and-flow technique, the phase states of the bulk of PM2.5 as a function of relative humidity (RH) were determined and compared to the ambient RH ranges in the two cities. PM2.5 was found to be liquid to semisolid in Seoul but mostly semisolid to solid in Beijing. The liquid state was dominant on polluted days, while a semisolid state was dominant on clean days in Seoul. These findings can be explained by the aerosol liquid water content related to the chemical compositions of the aerosols at ambient RH; the water content of PM2.5 was much higher in Seoul than in Beijing. Furthermore, the overall phase states of PM2.5 observed in Seoul and Beijing were interrelated with the particle size distribution. The results of this study aid in a better understanding of the fundamental physical properties of aerosols and in examining how these are linked to PM2.5 in polluted urban atmospheres.

[Characteristics of PM2.5 Pollution in Beijing During the Historical Period of the 2022 Olympic Winter Games].

Based on the dataset derived from January to March between 2015 and 2021 in Beijing, the PM2.5 pollution characteristics and its potential source regions during the historical period of the Beijing 2022 Olympic Winter Games and Paralympic Winter Games were investigated. From 2015 to 2018, both the number of severely polluted days (daily average ρ(PM2.5)>75 µg·m-3) and the average PM2.5 concentrations during severe pollution episodes decreased significantly in the period of January to March. While, neither variable has changed obviously since 2018. On average, severely polluted days occurred 23 times in each year between 2018 and 2021 during the period of January to March, and the average of ρ(PM2.5) was approximately 120.0 µg·m-3 during such polluted days. From January to March in 2015-2021, the severely polluted event with more than 5 consecutive polluted days occurred 2-3 times in each year, and the severest one lasted 8 d. During the historical period of the Beijing 2022 Olympic Winter Games, severely polluted days took place 2-9 d every year. The large quantities of fireworks during the Spring Festival maybe one of important primary sources of the PM2.5. The number of severely polluted days during the historical period of the Paralympic Winter Games ranged from 1 to 5 d, except for 2021 with 9 d owing to the frequent stagnant weather condition. The PM2.5 chemical composition was dominated by secondary species on severely polluted days during the historical period of the Beijing 2022 Olympic Winter Games and Paralympic Winter Games. Nitrate accounted for 46% of the measurable chemical components of PM2.5 during severe pollution events in 2020, which was remarkably higher than that during clean days in the same year (11%). The mass fraction of SO42- ranged from 12% to 19% in 2018-2020, indicating that the contribution of sulfate was much less, but cannot be ignored. The main potential source regions of PM2.5 in Beijing during the period concerned in this study were central and western Inner Mongolia, Hebei Province, Tianjin City, Shanxi Province, Shaanxi Province, central and western Shandong Province, and northern Henan Province.

Recent Developments in the Determination of PM2.5 Chemical Composition.

Fine particulate matter (named PM2.5) has become a prominent and dangerous form of air pollution. The chemical composition of PM2.5 mainly includes inorganic elements, water soluble ions, elemental carbon (EC), organic carbon (OC), and organic compounds. The detection method for inorganic elements mainly includes X ray fluorescence, inductively coupled plasma-atomic emission spectrometry, and inductively coupled plasma mass spectrometry. As for water soluble ions, ion chromatography is the most common detection method. EC and OC are usually detected by carbon analyzer. The organic compounds are determined by gas chromatography-mass spectrometry and liquid chromatography-mass spectrometry. In this paper, the merits and drawbacks of each analytical methods for the determination of PM2.5 chemical composition are summarized. This review also includes our discussion on the improvement of the analytical accuracy for the determination of PM2.5 chemical composition owing to the development of reference materials.

5-Hydroxymethylfurfural Exerts Negative Effects on Gastric Mucosal Epithelial Cells by Inducing Oxidative Stress, Apoptosis, and Tight Junction Disruption.

5-Hydroxymethylfurfural (5-HMF) is a processing byproduct present in foods that are consumed daily by humans, and the diet is the principal route for human exposure to it. However, its adverse effects on gastric epithelial cells are not fully understood. Based on the half inhibitory concentration value, concentrations of HMF of 2, 4, 8, and 16 mM were selected for this study. After 5-HMF treatment for 24 h, the number of living cells decreased to 89.61 ± 0.48, 77.30 ± 0.57, 58.75 ± 0.36, and 19.61 ± 0.40% of the control, respectively. Apoptosis activated through both the death receptor and mitochondrial pathways was confirmed to be the primary mode of HMF-induced cell death. Further analysis revealed that the reactive oxygen species (ROS) levels in GES-1 cells increased 1.7-6.5 fold after exposure to 5-HMF. Moreover, the inhibition of ROS by N-acetylcysteine blocked HMF-induced apoptosis and cell proliferation suppression, indicating that oxidative stress was important in HMF-induced apoptosis. Besides, after 5-HMF treatment, the gene expressions of occludin and ZO-1 were reduced by 1.1-3.4 fold and 2.0-9.4 fold, respectively. The cell surface morphology and tight junction-related protein expression analysis also revealed the destructive effect of 5-HMF on tight junction integrity. Our research highlights a potential mechanism of HMF-induced toxicity in GES-1 cells and provides additional information on the health risks of 5-HMF exposure to the human gastric epithelium.

Historically understanding the spatial distributions of particle surface area concentrations over China estimated using a non-parametric machine learning method.

A non-parametric ensemble model was proposed to estimate the long-term (2015-2019) particle surface area concentrations (SA) over China for the first time on basis of a vilification dataset of measured particle number size distribution. This ensemble model showed excellent cross-validation R2 value (CV R2 = 0.83) as well as a relatively low root-mean-square error (RMSE = 195.0 µm2/cm3). No matter in which year, considerable spatial heterogeneity of SA was found over China with higher SA in Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD), and Middle Lower Reaches of Yangtze River (MLYR). From 2015 to 2019, SA significantly decreased in representative city clusters. The reduction rates were 140.1 µm2·cm-3·a-1 in BTH, 110.7 µm2·cm-3·a-1 in Pearl River Delta (PRD), 105.2 µm2·cm-3·a-1 in YRD, and 92.4 µm2·cm-3·a-1 in Sichuan Basin (SCB), respectively. Even though such quick reduction, high SA (ranged from ~800 µm2/cm3 to ~1750 µm2/cm3) during the heavy pollution period (PM2.5 > 75 µg/m3) still existed in the above-mentioned city clusters and may provide rich reaction vessels for multiphase chemistry. A dichotomy of enhanced annual 4th maximum daily 8-h average O3 concentrations (4MDA8 O3) and decreased SA during summertime was found in Shanghai, a representative city of YRD. In Chengdu (SCB), increased 4MDA8 O3 concentration was associated with a synchronous increase of SA from 2017 to 2019. Differently, 4MDA8 O3 concentrations enhanced in Beijing (BTH) and Guangzhou (PRD), while not significant for SA before 2018. This work will greatly deepen our understanding of the historical variation and spatial distributions of SA over China.

More Significant Impacts From New Particle Formation on Haze Formation During COVID-19 Lockdown.

During the COVID-19 lockdown in 2020, large-scale industrial and transportation emissions were reduced, but high PM2.5 concentration still occurred. This study investigated the variation of particle number size distribution during the lockdown, and analyzed the characteristics of new particle formation (NPF) events and its potential impact on haze formation. Through measurement conducted in urban Beijing during the first 3 months of 2020, and comparison with year-over-year data, the decrease of primary Aitken-mode particles was observed. However, frequencies, formation rates and growth rates of NPF events remained stable between 2020 and 2019 in the same period. As a result, >25 nm particles produced by NPF events, would play a more important role in serving as the haze formation "seeds" compared to those produced by primary emissions. This finding emphasizes the significance on the understanding of NPF mechanisms when making pollution mitigation policy in the future.

Critical biodegradation process of a widely used surfactant in the water environment: dodecyl benzene sulfonate (DBS).

Sodium dodecyl benzene sulfonate (DBS) is a widely used surfactant that is now found extensively in water bodies because of anthropogenic emissions. Since the degradation of DBS in the environment mainly relies on microorganisms, it is essential to study the mechanism by which DBS is biodegraded. In this study, Chlorella vulgaris was used to research the biodegradation process of DBS. The C. vulgaris suspension was centrifuged to remove the supernatant, then secondary deionized water and DBS were added to the C. vulgaris. And the intermediate products were detected in real time by electrospray ionization mass spectrometry (ESI-MS). Some novel intermediate products, including 4-sodium sulfophenyldodecanoate acid and its homologs, were detected that had not been mentioned in previous studies. In this work, the process of DBS degradation was indicated, which consisted of three main steps: chain-shorting oxidation, ring-opening oxidation of benzene rings, and degradation of small molecules. By investigating the process of DBS degradation by C. vulgaris, we were able to propose a preliminary mechanism of DBS biodegradation, which is of great significance for research on the migration and conversion of surfactants in the environment.

Altered Salivary Alpha-Amylase Secretion in Patients with Ulcerative Colitis.

PURPOSE: Patients with ulcerative colitis (UC) frequently present with psychological disturbances as well as dysfunctions of autonomic nervous system (ANS). Salivary alpha-amylase (sAA) secretion is predominantly controlled by sympathetic nervous activity, while salivary fluid secretion is by parasympathetic nervous activity. Thus, it is speculated that alterations of salivary secretion may be addressed in UC populations. METHODS: Thirty-five UC patients as well as 32 age- and sex-matched healthy controls were enrolled. Saliva samples before and after citric acid stimulation were collected from each participant, and salivary flow rate (SFR) was calculated accordingly. Western blotting and quantitative PCR were applied to measure the sAA level and sAA gene (AMY1) copy number, respectively. The psychological disorders, anxiety and depression, were evaluated by the scoring system of Hospital Anxiety and Depression Scale (HADS) for each participant. RESULTS: We observed robustly increased prevalence of anxiety (p < 0.001) as well as depression (p < 0.001) in UC patients relative to controls. Interestingly, we detected elevated basal (p = 0.015) and stimulated (p = 0.021) sAA levels in the UC populations compared to controls. However, no differences were found for basal (p = 0.643) or stimulated (p = 0.402) SFR between the two study groups. Besides, AMY1 gene copy number was comparable between UC patients and controls. CONCLUSIONS: Our results reveal an overactivity of the sympathetic nervous system and a normal activity of the parasympathetic nervous system in the UC population.