Brain endothelial GSDMD activation mediates inflammatory BBB breakdown.

The blood-brain barrier (BBB) protects the central nervous system from infections or harmful substances1; its impairment can lead to or exacerbate various diseases of the central nervous system2-4. However, the mechanisms of BBB disruption during infection and inflammatory conditions5,6 remain poorly defined. Here we find that activation of the pore-forming protein GSDMD by the cytosolic lipopolysaccharide (LPS) sensor caspase-11 (refs. 7-9), but not by TLR4-induced cytokines, mediates BBB breakdown in response to circulating LPS or during LPS-induced sepsis. Mice deficient in the LBP-CD14 LPS transfer and internalization pathway10-12 resist BBB disruption. Single-cell RNA-sequencing analysis reveals that brain endothelial cells (bECs), which express high levels of GSDMD, have a prominent response to circulating LPS. LPS acting on bECs primes Casp11 and Cd14 expression and induces GSDMD-mediated plasma membrane permeabilization and pyroptosis in vitro and in mice. Electron microscopy shows that this features ultrastructural changes in the disrupted BBB, including pyroptotic endothelia, abnormal appearance of tight junctions and vasculature detachment from the basement membrane. Comprehensive mouse genetic analyses, combined with a bEC-targeting adeno-associated virus system, establish that GSDMD activation in bECs underlies BBB disruption by LPS. Delivery of active GSDMD into bECs bypasses LPS stimulation and opens the BBB. In CASP4-humanized mice, Gram-negative Klebsiella pneumoniae infection disrupts the BBB; this is blocked by expression of a GSDMD-neutralizing nanobody in bECs. Our findings outline a mechanism for inflammatory BBB breakdown, and suggest potential therapies for diseases of the central nervous system associated with BBB impairment.

Cannabidiol ameliorates PTSD-like symptoms by inhibiting neuroinflammation through its action on CB2 receptors in the brain of male mice.

Post-traumatic stress disorder (PTSD) is a debilitating mental health disease related to traumatic experience, and its treatment outcomes are unsatisfactory. Accumulating research has indicated that cannabidiol (CBD) exhibits anti-PTSD effects, however, the underlying mechanism of CBD remains inadequately investigated. Although many studies pertaining to PTSD have primarily focused on aberrations in neuronal functioning, the present study aimed to elucidate the involvement and functionality of microglia/macrophages in PTSD while also investigated the modulatory effects of CBD on neuroinflammation associated with this condition. We constructed a modified single-prolonged stress (SPS) mice PTSD model and verified the PTSD-related behaviors by various behavioral tests (contextual freezing test, elevated plus maze test, tail suspension test and novel object recognition test). We observed a significant upregulation of Iba-1 and alteration of microglial/macrophage morphology within the prefrontal cortex and hippocampus, but not the amygdala, two weeks after the PTSD-related stress, suggesting a persistent neuroinflammatory phenotype in the PTSD-modeled group. CBD (10 mg/kg, i.p.) inhibited all PTSD-related behaviors and reversed the alterations in both microglial/macrophage quantity and morphology when administered prior to behavioral assessments. We further found increased pro-inflammatory factors, decreased PSD95 expression, and impaired synaptic density in the hippocampus of the modeled group, all of which were also restored by CBD treatment. CBD dramatically increased the level of anandamide, one of the endocannabinoids, and cannabinoid type 2 receptors (CB2Rs) transcripts in the hippocampus compared with PTSD-modeled group. Importantly, we discovered the expression of CB2Rs mRNA in Arg-1-positive cells in vivo and found that the behavioral effects of CBD were diminished by CB2Rs antagonist AM630 (1 mg/kg, i.p.) and both the behavioral and molecular effects of CBD were abolished in CB2Rs knockout mice. These findings suggest that CBD would alleviate PTSD-like behaviors in mice by suppressing PTSD-related neuroinflammation and upregulation and activation of CB2Rs may serve as one of the underlying mechanisms for this therapeutic effect. The present study offers innovative experimental evidence supporting the utilization of CBD in PTSD treatment from the perspective of its regulation of neuroinflammation, and paves the way for leveraging the endocannabinoid system to regulate neuroinflammation as a potential therapeutic approach for psychiatric disorders.

Associations between phthalate metabolites and cytokines in the follicular fluid of women undergoing in vitro fertilization.

Many studies have showed that phthalates have reproductive and embryonic toxicity, while the potential mechanisms are mostly unknown. Inflammation may play a mediating part in phthalate exposure and adverse reproductive endpoints. A cross-sectional survey was conducted to investigate the associations of phthalate metabolites with inflammatory cytokines in the follicular fluid (FF) of women undergoing in vitro fertilization (IVF). We determined the levels of eight phthalate metabolites and five cytokines in the FF of 76 women, including interleukin (IL)- 6, IL-8, IL-10, monocyte chemoattractant protein-1 (MCP-1) and tumor necrosis factor-α (TNF-α). The associations of individual phthalate exposure with cytokines in FF samples were explored by multiple linear regression. We further evaluated the combined effects of multiple phthalate exposures on FF levels of cytokines by using Bayesian kernel machine regression (BKMR) models. We found that there was a positive relationship between mono-ethyl phthalate (MEP) and IL-6 in the FF (percent change:12.4%; 95% CI: 1.3%, 24.9%). In contrast, elevated mono-benzyl phthalate (MBzP), mono(2-ethylhexyl) phthalate (MEHP) and %MEHP levels were associated with decreased MCP-1. In the BKMR models, phthalate metabolite mixtures were positively associated with TNF-α when the mixtures were lower than 65th percentile compared with their medians. In the stratified analyses, MEHP was inversely associated with MCP-1 among women with BMI ≥ 23 kg/m2 (test for interaction <0.05). Our results suggest that certain phthalate metabolites or their mixtures may alter levels of inflammatory cytokines in the FF, and further research is necessary to elucidate the mechanisms underlying the relationship between phthalates exposure, ovarian dysfunction and adverse pregnancy outcomes.

DeepS: a web server for image optical sectioning and super resolution microscopy based on a deep learning framework.

MOTIVATION: Microscopy technology plays important roles in many biological research fields. Solvent-cleared brain high-resolution (HR) 3D image reconstruction is an important microscopy application. However, 3D microscopy image generation is time-consuming and expensive. Therefore, we have developed a deep learning framework (DeepS) for both image optical sectioning and super resolution microscopy. RESULTS: Using DeepS to perform super resolution solvent-cleared mouse brain microscopy 3D image yields improved performance in comparison with the standard image processing workflow. We have also developed a web server to allow online usage of DeepS. Users can train their own models with only one pair of training images using the transfer learning function of the web server. AVAILABILITYAND IMPLEMENTATION: http://deeps.cibr.ac.cn. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Chronic exposure to propylparaben at the humanly relevant dose triggers ovarian aging in adult mice.

Parabens, a type of endocrine-disrupting chemicals, are widely used as antibacterial preservatives in food and cosmetics in daily life. Paraben exposure has gained particular attention in the past decades, owing to its harmful effects on reproductive function. Whether low-dose paraben exposure may cause ovarian damage has been ignored recently. Here, we investigated the effects of chronic low-dose propylparaben (PrPB) exposure on ovarian function. Female C57BL/6J mice were exposed to PrPB at a humanly relevant dose for 8 months. Our results showed that chronic exposure to PrPB at a humanly relevant dose significantly altered the estrus cycle, hormone levels, and ovarian reserve, accelerating ovarian aging in adult mice. These effects are accompanied by oxidative stress enrichment, leading to steroidogenesis dysfunction and acceleration of primordial follicle recruitment. Notably, melatonin supplementation has been shown to protect against PrPB-induced steroidogenesis dysfunction in granulosa cells. Here, we report that daily chronic PrPB exposure may contribute to ovarian aging by altering oxidative stress-mediated JNK and PI3K-AKT signaling regulation, and that melatonin may serve as a pharmaceutical candidate for PrPB-associated ovarian dysfunction.

Integrated neural tracing and in-situ barcoded sequencing reveals the logic of SCN efferent circuits in regulating circadian behaviors.

The circadian clock coordinates rhythms in numerous physiological processes to maintain organismal homeostasis. Since the suprachiasmatic nucleus (SCN) is widely accepted as the circadian pacemaker, it is critical to understand the neural mechanisms by which rhythmic information is transferred from the SCN to peripheral clocks. Here, we present the first comprehensive map of SCN efferent connections and suggest a molecular logic underlying these projections. The SCN projects broadly to most major regions of the brain, rather than solely to the hypothalamus and thalamus. The efferent projections from different subtypes of SCN neurons vary in distance and intensity, and blocking synaptic transmission of these circuits affects circadian rhythms in locomotion and feeding to different extents. We also developed a barcoding system to integrate retrograde tracing with in-situ sequencing, allowing us to link circuit anatomy and spatial patterns of gene expression. Analyses using this system revealed that brain regions functioning downstream of the SCN receive input from multiple neuropeptidergic cell types within the SCN, and that individual SCN neurons generally project to a single downstream brain region. This map of SCN efferent connections provides a critical foundation for future investigations into the neural circuits underlying SCN-mediated rhythms in physiology. Further, our new barcoded tracing method provides a tool for revealing the molecular logic of neuronal circuits within heterogeneous brain regions.

Phthalate metabolites in urine and follicular fluid in relation to menstrual cycle characteristics in women seeking fertility assistance.

BACKGROUND: Phthalates have been shown to disrupt the estrous cycle in animal studies. However, epidemiological research investigating their associations with menstrual cycle characteristics is limited. OBJECTIVE: To explore the relationships between phthalate exposure and menstrual cycle characteristics among women seeking fertility assistance. METHODS: We determined the levels of eight phthalate metabolites in both follicular fluid (FF) and urine specimens collected from 441 women in the Tongji Reproductive and Environmental (TREE) cohort, using high-performance liquid chromatography and tandem mass spectrometry. Information about menstrual cycle parameters was obtained through a questionnaire. The impacts of individual and joint exposure to phthalates on menstrual cycle characteristics were assessed using multivariable linear regression, Poisson regression, and quantile g-computation approaches. RESULTS: After adjusting for relevant covariates, we found that per log10-unit increase in mono(2-ethylhexyl) phthalate (MEHP) level in urine specimens was associated with a decrease of 0.20 days (95 % CI: -0.37, -0.03) in bleeding duration. We also observed that mono(2-ethyl-5-carboxypentyl) phthalate (MECPP) and the sum of di(2-ethylhexyl) phthalate (DEHP) metabolites (∑DEHP) concentrations in FF samples were inversely related to cycle length [ß = -1.92 (95 % CI: -3.10, -0.75) and -1.87 (95 % CI: -3.56, -0.19), respectively]. However, we generally observed null associations between phthalate metabolites and irregular cycle, dysmenorrhea, hypomenorrhea, or cycle length variation. Furthermore, we also found that phthalate metabolite mixtures in FF and urine were generally unrelated to menstrual cycle characteristics. CONCLUSION: Our findings suggest that some DEHP metabolites in FF and urine are inversely associated with menstrual cycle length and menstrual bleeding duration in women attending a fertility center.

DBP Exposure Affects Oocyte Fertilization Via Extracellular Vesicles-Derived miR-116-5p in Ovarian Granulosa Cells Through Downregulating FOXO3a Expression.

Mono-butyl phthalate (MBP), the metabolite of dibutyl phthalate (DBP), is the most abundant phthalate metabolite found in Chinese women. Extracellular vesicles (EVs) are nanoscale lipid bilayer particles produced by extensive kinds of cells, serving a key role in intercellular communication. Extracellular vesicle miRNAs (EV-miRNAs) in follicular fluid (FF) have been evidenced to be associated with female reproductive health. The objective of this study was to investigate the associations of EV-miRNAs expressed profile with DBP exposure in FF of female participants and expose its potential mechanism in impaired oocyte development. Based on participants' FF MBP concentrations and fertilization status, we compared the miRNA expression between the FF-EVs of group A (high DBP exposure and impaired fertilization) and group B (low DBP exposure and normal fertilization). Compared with group B, miR-1246, miR-3679-5p, miR-423-5p, miR-5585-3p, miR-116-5p, miR-172-5p were upregulated, while miR-34b-3p was downregulated in group A. Target genes of the differently expressed miRNAs were predicted, and the functional analysis was performed. Furthermore, we exposed human ovarian granulosa tumor cell line (KGN) to MBP (4ug/L) to isolate the EVs from the culture medium and validated the expression levels of different miRNAs. We found that MBP exposure was significantly associated with increased levels of miR-116-5p (P = 0.01). In addition, we demonstrated that the most different miRNA, miR-116-5p regulated oocyte fertilization by inhibiting FOXO3a. Our findings suggested that EV-miRNAs in the FF might mediate MBP toxicity in oocytes.

Associations between exposure to phthalates and liver function among women undergoing assisted reproductive technology.

Phthalates can induce hepatotoxicity in animal studies. We aimed to assess the associations of individual and mixture of urinary phthalate metabolites with serum liver function indicators among 764 women undergoing assisted reproductive technology (ART). In linear models, we observed inverse correlations between urinary mono-benzyl phthalate and serum total protein (TP) as well as globulin (ß=-0.27 and -0.23, respectively, P<0.05). Additionally, negative associations were identified between mono-isobutyl phthalate and mono-butyl phthalate (MBP) and aspartate aminotransferase-to-alanine transaminase ratio (AST/ALT) (P<0.05). MBP and the sum of all phthalate metabolites (∑all.phth.m) were positively associated with bilirubin, with ß ranging from 0.14 to 0.47. Most phthalate metabolites were also positively related to gamma-glutamyl transferase (GGT) (all P<0.05). In Bayesian kernel machine regression models, phthalate mixture was positively associated with bilirubin and GGT, whereas inversely associated with AST/ALT and TP. Our results suggest that phthalate exposure may impair liver function among women undergoing ART.

Simulating daily PM2.5 concentrations using wavelet analysis and artificial neural network with remote sensing and surface observation data.

Accurate PM2.5 concentrations predicting is critical for public health and wellness as well as pollution control. However, traditional methods are difficult to accurately predict PM2.5. An adaptive model coupled with artificial neural network (ANN) and wavelet analysis (WANN) is utilized to predict daily PM2.5 concentrations with remote sensing and surface observation data. The four evaluation metrics, namely Pearson correlation coefficient (R), mean absolute percentage error (MAPE), root mean square error (RMSE), and mean absolute error (MAE), are utilized to evaluate the performances of the artificial neural network (ANN) and WANN methods. From the predicting results, The WANN model has a higher R (R = 0.9990) during the testing period compared with R (R = 0.6844) based on the ANN model. Similarly, the WANN model has a lower MAPE (3.6988%), RMSE (1.0145 µg/m3), MAE (1.3864 µg/m3), compared with MAPE (80.0086%), RMSE (16.5838 µg/m3), MAE (12.2420 µg/m3) of the ANN. In addition, comparing the outcomes of the proposed WANN method with the ANN method, it was observed that the error during the training and verification period has decreased significantly. Furthermore, the statistical methods are used to analyze WANN and ANN, showing that WANN has higher training accuracy and better stability. Therefore, it is feasible to establish WANN to predict PM2.5 concentrations (1 day in advance) by using remote sensing and surface observation data.

Long-term projection of future climate change over the twenty-first century in the Sahara region in Africa under four Shared Socio-Economic Pathways scenarios.

Climate change affects air quality and people's health. Therefore, accurate prediction of future climate change is of great significance for human beings to better adapt and mitigate climate change. Using the projection simulation dataset of the CMIP6 multi-model ensemble, the future climate change in the Sahara region under the four scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) is analyzed. The results show that annual and seasonal average surface air temperature in the Sahara region will continue to rise throughout the twenty-first century relative to the baseline period 1995-2014 if greenhouse gas (GHG) concentrations continue increasing. Under the four SSPs scenarios, the warming in the Sahara region will be more pronounced than in the whole world through the twenty-first century. The annual maximum temperature (TX), the annual minimum temperature (TN), the annual count of days with maximum temperature above 35 °C (TX 35), and the annual count of days with maximum temperature above 40 °C (TX 40) in the Sahara region will continue to increase until the end of the twenty-first century under the four scenarios. The results of climate change prediction can provide scientific reference for climate policy-making.

Change in Air Quality during 2014-2021 in Jinan City in China and Its Influencing Factors.

Air pollution affects climate change, food production, traffic safety, and human health. In this paper, we analyze the changes in air quality index (AQI) and concentrations of six air pollutants in Jinan during 2014-2021. The results indicate that the annual average concentrations of PM10, PM2.5, NO2, SO2, CO, and O3 and AQI values all declined year after year during 2014-2021. Compared with 2014, AQI in Jinan City fell by 27.3% in 2021. Air quality in the four seasons of 2021 was obviously better than that in 2014. PM2.5 concentration was the highest in winter and PM2.5 concentration was the lowest in summer, while it was the opposite for O3 concentration. AQI in Jinan during the COVID epoch in 2020 was remarkably lower compared with that during the same epoch in 2021. Nevertheless, air quality during the post-COVID epoch in 2020 conspicuously deteriorated compared with that in 2021. Socioeconomic elements were the main reasons for the changes in air quality. AQI in Jinan was majorly influenced by energy consumption per 10,000-yuan GDP (ECPGDP), SO2 emissions (SDE), NOx emissions (NOE), particulate emissions (PE), PM2.5, and PM10. Clean policies in Jinan City played a key role in improving air quality. Unfavorable meteorological conditions led to heavy pollution weather in the winter. These results could provide a scientific reference for the control of air pollution in Jinan City.

Predicting of Daily PM2.5 Concentration Employing Wavelet Artificial Neural Networks Based on Meteorological Elements in Shanghai, China.

Anthropogenic sources of fine particulate matter (PM2.5) threaten ecosystem security, human health and sustainable development. The accuracy prediction of daily PM2.5 concentration can give important information for people to reduce their exposure. Artificial neural networks (ANNs) and wavelet-ANNs (WANNs) are used to predict daily PM2.5 concentration in Shanghai. The PM2.5 concentration in Shanghai from 2014 to 2020 decreased by 39.3%. The serious COVID-19 epidemic had an unprecedented effect on PM2.5 concentration in Shanghai. The PM2.5 concentration during the lockdown in 2020 of Shanghai is significantly reduced compared to the period before the lockdown. First, the correlation analysis is utilized to identify the associations between PM2.5 and meteorological elements in Shanghai. Second, by estimating twelve training algorithms and twenty-one network structures for these models, the results show that the optimal input elements for daily PM2.5 concentration predicting models were the PM2.5 from the 3 previous days and fourteen meteorological elements. Finally, the activation function (tansig-purelin) for ANNs and WANNs in Shanghai is better than others in the training, validation and forecasting stages. Considering the correlation coefficients (R) between the PM2.5 in the next day and the input influence factors, the PM2.5 showed the closest relation with the PM2.5 1 day lag and closer relationships with minimum atmospheric temperature, maximum atmospheric pressure, maximum atmospheric temperature, and PM2.5 2 days lag. When Bayesian regularization (trainbr) was used to train, the ANN and WANN models precisely simulated the daily PM2.5 concentration in Shanghai during the training, calibration and predicting stages. It is emphasized that the WANN1 model obtained optimal predicting results in terms of R (0.9316). These results prove that WANNs are adept in daily PM2.5 concentration prediction because they can identify relationships between the input and output factors. Therefore, our research can offer a theoretical basis for air pollution control.

Morphological and transcriptomic responses/acclimations of erect-type submerged macrophyte Hydrilla verticillata both at low-light exposure and light recovery phases.

Light intensity is a determinant for submerged macrophytes. Little is known about their molecular responses to low-light exposure, despite more informative and responsive than morphological traits. For erect-type submerged macrophytes, the stem is more crucial relative to the leaf in acclimation to low-light stress, but receives less attention. We determined morphological and stem transcriptomic responses/acclimations of Hydrilla verticillata to extremely and mildly low light (7.2 and 36 µmol photons m-2 s-1, respectively), that is, EL and ML, with the radiation intensity of 180 µmol photons m-2 s-1 as the control. Low-light exposure continued for 9 days, followed by a 7-day recovery phase (180 µmol photons m-2 s-1). At the exposure phase, the low-light treatments, in particular the EL, decreased the relative growth ratio, but induced greater height and longer stem internode distance and epidermal cell. Such responses/acclimations continued into the recovery phase, despite more or less changes in the magnitude. Transcriptome showed that the photosynthetic system was inhibited at the exposure phase, but the macrophyte adjusted hormone synthesis relating to cell division and elongation. Moreover, the EL activated cell stress responses such as DNA repair. Following light recovery, the macrophyte exhibited a strong-light response, although energy metabolism enhanced. Especially, the EL enriched the pathways relating to anthocyanin synthesis at such phase, indicating an activation of photoprotective mechanism. Our findings suggest that negative influences of low light occur at both low-light exposure and recovery phases, but submerged macrophytes would acclimate to light environments. Transcriptome can show molecular basis of plant responses/acclimations, including but not limited to morphology. This study establishes a bridge connecting morphological and molecular responses/acclimations.

Learning ensembles of process-based models for high accurately evaluating the one-hundred-year carbon sink potential of China's forest ecosystem.

China's forests play a vital role in the global carbon cycle through the absorption of atmospheric CO2 to mitigate climate change caused by the increase of anthropogenic CO2. It is essential to evaluate the carbon sink potential (CSP) of China's forest ecosystem. Combining NDVI, field-investigated, and vegetation and soil carbon density data modeled by process-based models, we developed the state-of-the-art learning ensembles model of process-based models (the multi-model random forest ensemble (MMRFE) model) to evaluate the carbon stocks of China's forest ecosystem in historical (1982-2021) and future (2022-2081, without NDVI-driven data) periods. Meanwhile, we proposed a new carbon sink index (CSindex) to scientifically and accurately evaluate carbon sink status and identify carbon sink intensity zones, reducing the probability of random misjudgments as a carbon sink. The new MMRFE models showed good simulation results in simulating forest vegetation and soil carbon density in China (significant positive correlation with the observed values, r = 0.94, P < 0.001). The modeled results show that a cumulative increase of 1.33 Pg C in historical carbon stocks of forest ecosystem is equivalent to 48.62 Bt CO2, which is approximately 52.03% of the cumulative increased CO2 emissions in China from 1959 to 2018. In the next 60 years, China's forest ecosystem will absorb annually 1.69 (RCP45 scenario) to 1.85 (RCP85 scenario) Bt CO2. Compared with the carbon stock in the historical period, the cumulative absorption of CO2 by China's forest ecosystem in 2032-2036, 2062-2066, and 2077-2081 are approximately 11.25-39.68, 110.66-121.49 and 101.31-111.11 Bt CO2, respectively. In historical and future periods, the medium and strong carbon sink intensity regions identified by the historical CSindex covered 65% of the total forest area, cumulative absorbing approximately 31.60 and 65.83-72.22 Bt CO2, respectively. In the future, China's forest ecosystem has a large CSP with a non-continuous increasing trend. However, the CSP should not be underestimated. Notably, the medium carbon sink intensity region should be the priority for natural carbon sequestration action. This study not only provides an important methodological basis for accurately estimating the future CSP of forest ecosystem but also provides important decision support for future forest ecosystem carbon sequestration action.

Contrasting molecular characteristics and formation mechanisms of biogenic and anthropogenic secondary organic aerosols at the summit and foot of Mt. Huang, East China.

Secondary organic aerosol (SOA) exerts a considerable influence on atmospheric chemistry. However, little information about the vertical distribution of SOA in the alpine setting is available, which limited the simulation of SOA using chemical transport models. Here, a total of 15 biogenic and anthropogenic SOA tracers were measured in PM2.5 aerosols at both the summit (1840 m a.s.l.) and foot (480 m a.s.l.) of Mt. Huang during the winter of 2020 to explore their vertical distribution and formation mechanism. Most of the determined chemical species (e.g., BSOA and ASOA tracers, carbonaceous components, major inorganic ions) and gaseous pollutants at the foot of Mt. Huang were 1.7-3.2 times higher concentrations than those at the summit, suggesting the relatively more significant effect of anthropogenic emissions at the ground level. The ISORROPIA-II model showed that aerosol acidity increases as altitude decreases. Air mass trajectories, potential source contribution function (PSCF), and correlation analysis of BSOA tracers with temperature revealed that SOA at the foot of Mt. Huang was mostly derived from the local oxidation of volatile organic compounds (VOCs), while SOA at the summit was mainly influenced by long-distance transport. The robust correlations of BSOA tracers with anthropogenic pollutants (e.g., NH3, NO2, and SO2) (r = 0.54-0.91, p < 0.05) indicated that anthropogenic emissions could promote BSOA productions in the mountainous background atmosphere. Moreover, most of SOA tracers (r = 0.63-0.96, p < 0.01) and carbonaceous species (r = 0.58-0.81, p < 0.01) were correlated well with levoglucosan in all samples, suggesting that biomass burning played an important role in the mountain troposphere. This work demonstrated that daytime SOA at the summit of Mt. Huang was significantly influenced by the valley breeze in winter. Our results provide new insights into the vertical distributions and provenance of SOA in the free troposphere over East China.

Associations of personal care products use with reproductive outcomes of IVF/ICSI treatment.

Introduction: Personal care products (PCPs) contain a number of endocrine-disrupting chemicals (EDCs) that could potentially affect the reproductive function in women of childbearing age. However, studies focused on the effects of PCPs use on reproductive outcomes are very limited. The current study aimed to explore the relationships between PCPs use patterns and reproductive outcomes in women undergoing in vitro fertilization/intracytoplasmic sperm injection (IVF/ICSI) treatment. Methods: A total of 1500 women from the Tongji Reproductive and Environmental (TREE) study between December 2018 and January 2020 were included in this study. Participants provided characteristics of PCPs use within the previous three months. Retrieved oocyte number, mature oocyte number, two distinct pronuclei (2PN) zygote number, fertilization rate, cleavage rate, blastocyst formation rate, implantation, clinical pregnancy, miscarriage, and live birth were followed up as reproductive endpoints. Generalized linear regression model was utilized to assess the associations between various categories of PCPs use and reproductive endpoints of IVF/ICSI. Results: After adjusting for relevant covariates, women who used skin care products ≥14 times per week had a reduction of 22.4% in the maturation rate (95% CI: -39.2%, -1.6%) compared to participants who did not use skin care products. After transferring fresh embryos, women who used cosmetics 1-2 times per week (adjusted OR = 2.2, 95% CI: 1.0, 4.8) or 3-7 times per week (adjusted OR = 2.5, 95% CI: 1.2, 5.2) had a higher possibility of miscarriage than those who did not use cosmetics. There was negative association between the use of gel or soap and the cleavage rate among women aged < 30 years old (P for interaction = 0.01). Among women with BMI ≥ 24 kg/m2, the use of gel or soap was negatively associated with the blastocyst formation rate (P for interaction = 0.04), while cosmetics use was negatively associated with the maturation rate (P for interaction = 0.001). Conclusion: Our findings suggest that the use of PCPs in women of reproductive age have a potential adverse impact on IVF/ICSI outcomes, particularly skin care and cosmetic products.

Synergistic toxicity to the toxigenic Microcystis and enhanced microcystin release exposed to polycyclic aromatic hydrocarbon mixtures.

With the continued influx and accumulation of polycyclic aromatic hydrocarbons (PAHs) in eutrophic waters, the effects of PAHs on cyanobacteria bloom need to be clarified. PAHs usually existed as mixtures in aquatic environments, but the combined toxicity of PAH mixtures to toxigenic cyanobacteria remained unknown. This study investigated the effects of phenanthrene (Phe) and benzo [a]pyrene (BaP), alone or in combination, on the growth and physiology of Microcystis aeruginosa. The results showed that a hormesis effect on growth at low doses of the single Phe (≤1 mg/L) or PAH mixtures (≤0.279 mg/L) was observed, whereas the single BaP induced significant growth inhibitions at all concentrations (≥0.2 mg/L). The median effective concentrations (96 h) for Phe, BaP and their mixtures were 4.29, 1.29 and 1.07 mg/L, respectively. Mixture toxicity models showed that Phe and BaP elicited a synergistic interaction on M. aeruginosa. The synergy may be ascribed to the excessive oxidative stress induced by PAH mixtures, which further led to membrane structure damages, photosynthesis inhibitions and decreased metabolic activity. Moreover, the microcystins (MCs) release significantly increased by 25.3% and 31.9% upon exposure to 0.558 and 1.116 mg/L of PAH mixtures. In all, this study suggested that the enhanced release of MCs by PAH mixtures might exacerbate potential risks to the aquatic environment.

A neuropsin-based optogenetic tool for precise control of Gq signaling.

Gq-coupled receptors regulate numerous physiological processes by activating enzymes and inducing intracellular Ca2+ signals. There is a strong need for an optogenetic tool that enables powerful experimental control over Gq signaling. Here, we present chicken opsin 5 (cOpn5) as the long sought-after, single-component optogenetic tool that mediates ultra-sensitive optical control of intracellular Gq signaling with high temporal and spatial resolution. Expressing cOpn5 in HEK 293T cells and primary mouse astrocytes enables blue light-triggered, Gq-dependent Ca2+ release from intracellular stores and protein kinase C activation. Strong Ca2+ transients were evoked by brief light pulses of merely 10 ms duration and at 3 orders lower light intensity of that for common optogenetic tools. Photostimulation of cOpn5-expressing cells at the subcellular and single-cell levels generated fast intracellular Ca2+ transition, thus demonstrating the high spatial precision of cOpn5 optogenetics. The cOpn5-mediated optogenetics could also be applied to activate neurons and control animal behavior in a circuit-dependent manner. cOpn5 optogenetics may find broad applications in studying the mechanisms and functional relevance of Gq signaling in both non-excitable cells and excitable cells in all major organ systems.

Fluorescence ghost imaging with pseudothermal light.

We extend classical light ghost imaging to the area of fluorescence imaging and propose a new fluorescence imaging method. For the first time, we demonstrate both theoretically and experimentally that fluorescence ghost imaging can be realized with pseudothermal light. Important factors influencing the visibility and resolution of the images are discussed to improve the quality of the fluorescence ghost imaging. We hope that this work may pave the road for ghost imaging to biomedical applications.