Attention mechanism-enhanced graph convolutional neural network for unbalanced lithology identification.

In this study, we propose a novel method for identifying lithology using an attention mechanism-enhanced graph convolutional neural network (AGCN). The aim of this method is to address the limitations of traditional approaches that evaluate unbalanced lithology by improving the identification of thin layers and small samples, while providing reliable data support for reservoir evaluation. To achieve this goal, we begin by using Principal Component Analysis (PCA) with maximum and minimum distance clustering (Max-min-distance) to correct the logging curves, which compensates for the low resolution of thin layers and enhances the accuracy of stratigraphic representation. Subsequently, we transform the logging data into graph-structured data by connecting distance similarity points and feature similarity points of the logging samples. We then use the graph convolutional network (GCN) to identify lithology, leveraging both labeled and unlabeled data to enhance the ability to identify lithology in small sample datasets. Additionally, our model incorporates a channel and spatial attention mechanism that assigns weights to the graph structure during lithology identification, improving the model's capability to discern differences across samples. To evaluate the performance of our model, we constructed a lithology dataset comprising five wells and conducted experiments. The results indicate that our approach achieves a maximum accuracy of 97.67%, surpassing the performance of a singlestructure model in lithology identification. In conclusion, our proposed method provides a promising and effective approach for unbalanced lithology identification, significantly improving accuracy levels.

Jinlida for Diabetes Prevention in Impaired Glucose Tolerance and Multiple Metabolic Abnormalities: The FOCUS Randomized Clinical Trial.

Importance: Previous studies have shown that Jinlida (JLD) granules, an approved treatment for type 2 diabetes in China, can reduce blood glucose level, reduce glycated hemoglobin (HbA1c), and improve insulin resistance in people with type 2 diabetes. Objective: To evaluate the effect of long-term administration of JLD vs placebo on the incidence of diabetes in participants with impaired glucose tolerance (IGT) and multiple metabolic abnormalities. Design, Setting, and Participants: This multicenter, double-blind, placebo-controlled randomized clinical trial (FOCUS) was conducted across 35 centers in 21 cities in China from June 2019 to February 2023. Individuals aged 18 to 70 years with IGT and multiple metabolic abnormalities were enrolled. Intervention: Participants were randomly allocated 1:1 to receive JLD or placebo (9 g, 3 times per day, orally). They continued this regimen until they developed diabetes, withdrew from the study, were lost to follow-up, or died. Main Outcomes and Measures: The primary outcome was the occurrence of diabetes, which was determined by 2 consecutive oral glucose tolerance tests. Secondary outcomes included waist circumference; fasting and 2-hour postprandial plasma glucose levels; HbA1c; fasting insulin level; homeostatic model assessment for insulin resistance (HOMA-IR); total cholesterol, low-density lipoprotein cholesterol, and triglyceride levels; ankle-brachial index; and carotid intima-media thickness. Results: A total of 889 participants were randomized, of whom 885 were in the full analysis set (442 in the JLD group; 443 in the placebo group; mean [SD] age, 52.57 [10.33] years; 463 [52.32%] female). Following a median observation period of 2.20 years (IQR, 1.27-2.64 years), participants in the JLD group had a lower risk of developing diabetes compared with those in the placebo group (hazard ratio, 0.59; 95% CI, 0.46-0.74; P < .001). During the follow-up period, the JLD group had a between-group difference of 0.95 cm (95% CI, 0.36-1.55 cm) in waist circumference, 9.2 mg/dL (95% CI, 5.4-13.0 mg/dL) in 2-hour postprandial blood glucose level, 3.8 mg/dL (95% CI, 2.2-5.6 mg/dL) in fasting blood glucose level, 0.20% (95% CI, 0.13%-0.27%) in HbA1c, 6.6 mg/dL (95% CI, 1.9-11.2) in total cholesterol level, 4.3 mg/dL (95% CI, 0.8-7.7 mg/dL) in low-density lipoprotein cholesterol level, 25.7 mg/dL (95% CI, 15.9-35.4 mg/dL) in triglyceride levels, and 0.47 (95% CI, 0.12-0.83) in HOMA-IR compared with the placebo group. After 24 months of follow-up, the JLD group had a significant improvement in ankle-brachial index and waist circumference compared with the placebo group. Conclusions and Relevance: The findings suggest that JLD can reduce the risk of diabetes in participants with IGT and multiple metabolic abnormalities. Trial Registration: Chinese Clinical Trial Register: ChiCTR1900023241.

Simulations of water pollutants in the Hangzhou Bay, China: Hydrodynamics, characteristics, and sources.

China's coastal waters are confronting serious water quality problems, particularly the Hangzhou Bay in the Yangtze River Delta. To find out the underlying cause, we use the Regional Ocean Modeling System (ROMS) to simulate the hydrodynamic characteristics and the evolution of water pollutants. The results show that the hydrodynamic conditions are complicated and the semi-exchange time is 46 days, significantly hindering the dilution and diffusion of water pollutants. Concentrations of each typical pollutant as chemical oxygen demand (COD), dissolved inorganic nitrogen (DIN), and phosphate (PO4) decrease from west to east, showing an obvious enrichment in the coastal region. Source-oriented results show that the inland water pollution of the Yangtze River and the Qiantang River is the key contributor, and the sewage outfalls on the coast near the bay worsen the pollution. This suggests that the government needs to strengthen the management of sources that affect water security.

Analysis of the Formation Mechanism of Hydrogen Sulfide in the 13# Coal Seam of Shaping Coal Mine.

In order to accurately predict the law of occurrence and migration of hydrogen sulfide (H2S) in the underground and effectively solve the problem of excessive concentration of H2S gas, laboratory experiments on the content of various forms of sulfur in coal, sulfur isotopes, thermal evolution history, and coal seam water samples were carried out by applying the theories of coal mine geology, microbiology, and analytical chemistry, and based on the experimental results, the cause of H2S gas was explored. Through the analysis of the geological conditions of the coal seam mined, it can be seen that the coal mine experienced the alternation of marine and continental phases in the process of coal formation and that there was no magma intrusion. The experimental results showed that iron sulfide in coal accounts for 73.25% of the total sulfur, indicating that the coal seam was rich in pyrite. The results of the isotope test showed that the sulfur isotopes in coal samples were all negative, indicating that the sulfur isotope fractionation in coal was large, the loss was serious, and the coal seam was greatly affected by seawater. According to the experimental results of vitrinite reflectance, it can be concluded that the highest temperature during the thermal evolution of the coal seam is 108.12 °C, which has not reached the temperature condition of sulfate thermochemical reduction. Comparing the concentration of acid ions in coal seam water and tap water, it was found that the concentration of SO42- in coal seam water is low, while the concentration of HCO3- is high. According to the experimental results and theoretical analysis, the H2S gas in the high-sulfur coal mine was caused by microbial sulfate reduction. Finally, the transformation path of sulfur in the coal seam was deduced and analyzed. The results showed that sulfur in coal is positively correlated with H2S gas concentration.

Impacts of haze and nitrogen oxide alleviation on summertime ozone formation: A modeling study over the Yangtze River Delta, China.

The strict emission control measures have profoundly changed the air pollution in the Yangtze River Delta (YRD) region, China. However, the impacts of decreasing fine particulates (PM2.5) and nitrogen oxide (NOx) on summer ozone (O3) formation still remain disputable. We perform simulations in the 2018 summer over the YRD using the WRF-Chem model that considers the aerosol radiative forcing (ARF) and HO2 heterogeneous loss on aerosol surface. The model reasonably reproduces the measured spatiotemporal surface O3 and PM2.5 concentrations and aerosol compositions. Model sensitivity experiments show that the NOx mitigation during recent years changes daytime O3 formation in summer from the transition regime to the NOx-sensitive regime in the YRD. The decreasing NOx emission generally weakens O3 formation and lowers ambient O3 levels in summer during recent years, except for some urban centers of megacities. While, the haze alleviation characterized by a decline in ambient PM2.5 concentration in the past years largely counteracts the daytime O3 decrease caused by NOx mitigation, largely contributing to the persistently high levels of summertime O3. The counteracting effect is dominantly attributed to the attenuated ARF and minorly contributed by the suppressed HO2 uptake and heterogeneous loss on aerosol surface. These results highlight that the repeated O3 pollution in the YRD is closely associated with NOx and haze alleviation and more efforts must be taken to achieve lower O3 levels.

Expanded field of view frequency-selective incoherent holography by using a triple-beam setup.

We propose a new, to the best of our knowledge, method of incoherent optical frequency selection called three-pack frequency-selective incoherent holography. Compressed holography is reconstructed using phase shift intercepts and spatial transfer function convolution in the form of separation without loss of magnification or resolution. The frequency-selective reconstruction process removes the conjugate and DC terms along with the interception of the object wave. This work attempts three-dimensional reconstruction and selected-frequency phase extraction of axial slices in submicron steps, and the experimental results show the potential of the proposed method in areas such as compressed holography, extended field of view, and slice tomography.

Gallium nitride-based resonant cavity light-emitting diode with single-longitudinal-mode emission.

A novel, to the best of our knowledge, gallium nitride (GaN)-based resonant cavity light-emitting diode (RCLED) with single-longitudinal-mode light emission was demonstrated. A Ta2O5/SiO2 dielectric distributed Bragg reflector (DBR) with a filter-film structure was adopted as the top mirror. In contrast to the flat-topped reflectivity spectrum of the conventional high-reflective-structure DBR, for this filter-film-structure DBR, there is a light-transmitting concave band on the reflectivity spectrum. Owing to the modulation effect of this band on the output light, a single-longitudinal-mode light emission with a full width at half maximum as low as 0.63 nm was realized. Furthermore, the novel RCLED exhibited better wavelength stability. With an increase in the injection current from 50 to 500 mA, the redshift of the emission peak was only 0.2 nm. This novel RCLED with ultra-narrowband emission has a high potential for application in optical communication systems and optical fiber sensing applications.

Identification of a hippocampal lncRNA-regulating network in a natural aging rat model.

BACKGROUND: Dysregulation of long noncoding RNA (lncRNA) expression is related to aging and age-associated neurodegenerative diseases, and the lncRNA expression profile in the aging hippocampus is not well characterized. In the present investigation, the changed mRNAs and lncRNAs were confirmed via deep RNA sequencing. GO and KEGG pathway analyses were conducted to investigate the principal roles of the clearly dysregulated mRNAs and lncRNAs. Subsequently, through the prediction of miRNAs via which mRNAs and lncRNAs bind together, a competitive endogenous RNA network was constructed. RESULTS: A total of 447 lncRNAs and 182 mRNAs were upregulated, and 385 lncRNAs and 144 mRNAs were downregulated. Real-time reverse transcription-polymerase chain reaction validated the reliability of mRNA and lncRNA sequencing. KEGG pathway and GO analyses revealed that differentially expressed (DE) mRNAs were associated with cell adhesion molecules (CAMs), the p53 signaling pathway (SP), phagosomes, PPAR SP and ECM-receptor interactions. KEGG pathway and GO analyses showed that the target genes of the DE lncRNAs were related to cellular senescence, the p53 signaling pathway, leukocyte transendothelial migration and tyrosine metabolism. Coexpression analyses showed that 561 DE lncRNAs were associated with DE mRNAs. A total of 58 lncRNA-miRNA-mRNA target pairs were confirmed in this lncRNA‒miRNA‒mRNA network, comprising 10 mRNAs, 13 miRNAs and 38 lncRNAs. CONCLUSIONS: We found specific lncRNAs and mRNAs in the hippocampus of natural aging model rats, as well as abnormal regulatory ceRNA networks. Our outcomes help explain the pathogenesis of brain aging and provide direction for further research.

Nitrous acid emission from soil bacteria and related environmental effect over the North China Plain.

Soil bacteria could be one of the important sources for ambient HONO. However, the HONO emission from soil bacteria over North China Plain (NCP) with vast croplands has not yet been evaluated. In this study, high-resolution simulations are created to explore the HONO emission from soil bacteria over NCP and related influences on atmospheric chemistry. Ground measurements of critical air pollutants including O3, HONO, and PM2.5 compositions are incorporated to constrain the model simulations. Results show that abundant HONO is emitted from soil bacteria over NCP during summertime and the emission rate varies dramatically for different areas (about 0.2 kg km-2 d-1 - 2.0 kg km-2 d-1). The HONO emission rate presents clear diurnal cycles with peaks of 1.5 kg km-2 d-1 in the afternoon and valleys of 0.4 kg km-2 d-1 during the early morning hours. The resulting HONO concentration ranges from 0.2 µg m-3 to 1.4 µg m-3, which predominates the total HONO concentration in ambient air, particularly in western NCP. The soil bacteria source can significantly alter the diurnal cycles of ambient HONO and OH concentrations over NCP, but only slightly change O3 and PM2.5 concentrations via participating photochemistry and secondary aerosol formations. These results highlight the pressing need for the involvement of HONO emission from soil bacteria in modeling studies regarding atmospheric chemistry, particularly in rural areas.

Weather-Climate Anomalies and Regional Transport Contribute to Air Pollution in Northern China During the COVID-19 Lockdown.

Two persistent and heavy haze episodes during the COVID-19 lockdown (from 20 Jan to 22 Feb 2020) still occur in northern China, when anthropogenic emissions, particularly from transportation sources, are greatly reduced. To investigate the underlying cause, this study comprehensively uses in-situ measurements for ambient surface pollutants, reanalysis meteorological data and the WRF-Chem model to calculate the contribution of NOx emission change and weather-climate change to the "unexpectedly heavy" haze. Results show that a substantial NOx reduction has slightly decreased PM2.5 concentration. By contrast, the weakest East Asian winter monsoon (EAWM) in the 2019-2020 winter relative to the past decade is particularly important for haze occurrence. A warmer and moister climate is also favorable. Model results suggest that climate anomalies lead to a 25-50 µg m-3 increase of PM2.5 concentration, and atmospheric transport is also an important contributor to two haze episodes. The first haze is closely related to the atmospheric transport of pollutants from NEC to the south, and fireworks emissions in NEC are a possible amplifying factor that warrants future studies. The second one is caused by the convergence of a southerly wind and a mountain wind, resulting in an intra-regional transport within BTH, with a maximal PM2.5 increment of 50-100 µg m-3. These results suggest that climate change and regional transport are of great importance to haze occurrence in China, even with significant emission reductions of pollutants.

Elucidating the impacts of rapid urban expansion on air quality in the Yangtze River Delta, China.

Urban expansion not only results in land use transformation, but also introduces extra anthropogenic emissions over the expanded urban areas, which is usually neglected in existing studies. In this study, we consider both the changes in land use categories and added anthropogenic emissions from 2001 to 2018 in the Yangtze River Delta (YRD) which we define as the city of Shanghai and the nearby provinces of Zhejiang, Jiangsu, and Anhui, China and explore the individual and combined impacts of these factors on air pollution using the WRF-Chem model. Calibrated by available observations, the model performs well (IOA (index of agreement) > 0.8) in reproducing the meteorological fields and ambient PM2.5 and O3 concentrations in September 2018. We show that the land use transformation from non-urban to urban and the introduced anthropogenic emissions over new urban areas exert opposite influences on ambient PM2.5 concentrations over YRD, particularly in the expanded urban areas, and the PM2.5 decrease due to land use changes is significantly offset by the increase due to added emissions. The response of ambient O3 concentration to these two factors is highly variable in space, which is dependent on the chemical regime of tropospheric O3 formation and influenced by the chemistry-meteorology feedback. As the total effect, strong increases in O3 concentration occur over the central areas of YRD. These results highlight that it is essential to take into account the additional anthropogenic emissions over expanded urban areas in the assessment of environmental impacts of urban expansion.

Increasing atmospheric oxidizing capacity weakens emission mitigation effort in Beijing during autumn haze events.

Although strict mitigation measures have been implemented since 2013 in Beijing-Tianjin-Hebei (BTH), China, air pollution still frequently occurs. Observations reveal that during pollution episodes in autumn, fine particulate matter (PM2.5) concentrations have not decreased, and particularly, ozone (O3) concentrations have increased remarkably from 2013 to 2015 in Beijing. Additionally, a concurrence of O3 and particulate pollution with high secondary aerosol contributions has been observed frequently, indicating high atmospheric oxidizing capacity (AOC) during particulate pollution. The WRF-Chem model simulations show elevated O3 concentrations and high fractions of oxygenated secondary aerosols (OSA) in PM2.5 (0.53-0.73) during the severe pollution period. During daytime there exhibits an AOC-sufficient regime with the persistently high OSA fraction and an AOC-deficient regime with varied OSA fractions, separated by the O3 level of 80 µg m-3. Our results suggest that increasing AOC can considerably weaken the emission mitigation effort by enhancing the secondary aerosol formation.

Case Report: Next-Generation Sequencing Reveals Tumor Origin in a Female Patient With Brain Metastases.

BACKGROUND: Brain metastasis mainly originates from lung cancer. Napsin A and TTF-1 factors have frequently been detected in lung adenocarcinoma cases. Brain metastasis tumors with napsin A and TTF-1 positive are easily classified as lung adenocarcinoma origin. However, some thyroid cancers also exhibit these clinical features. Besides, lung is the most common metastasis of undifferential thyroid cancer. Therefore, it requires development of novel diagnostic tools to aid in distinguishing between pulmonary and thyroid origin. PATIENT FINDINGS: We reported a case that was initially diagnosed as brain metastatic lung cancer based on immunohistochemistry results. Analysis of next-generation sequencing (NGS) data from the brain lesion revealed that the cancer may have originated from the thyroid. We detected combo mutations in TERT promoter mutation, RET fusion and TP53, which are common in undifferential thyroid cancer (UTC), but rare for lung cancer. These results, coupled with identification of PAX8, indicated that this patient had UTC. Additionally, her three sons, despite being asymptomatic, were all diagnosed with papillary thyroid carcinoma. SUMMARY: The patient received anlotinib treatment and showed good clinical outcomes. One month after anlotinib treatment, the pulmonary nodules were found to be controlled, and the thyroid tumor drastically reduced, and tracheal compression relieved. She continued anlotinib treatment for the following two months, but died one month later because the treatment stopped owing to financial reasons. All her sons underwent total thyroidectomy with lymph node dissection. CONCLUSIONS: Although NGS has been reported to assist in diagnosis of the origin of some tumors, this is the first evidence of NGS for the determination of the origin of thyroid tumors. To our knowledge, this is the first time that a combination of multiple mutations has been used to help determine the origin of a tumor, compared with the previous single mutant gene. Moreover, this is the first evidence on the use of anlotinib for treatment of UTC with distant metastasis. Besides, all three sons of the patient had thyroid carcinoma in subsequent examinations, indicating high-risk for familial non-medullary thyroid cancer in UTC patients and necessity for performing thyroid ultrasound testing in other family members.

Genetic Basis of Tiller Dynamics of Rice Revealed by Genome-Wide Association Studies.

A tiller number is the key determinant of rice plant architecture and panicle number and consequently controls grain yield. Thus, it is necessary to optimize the tiller number to achieve the maximum yield in rice. However, comprehensive analyses of the genetic basis of the tiller number, considering the development stage, tiller type, and related traits, are lacking. In this study, we sequence 219 Korean rice accessions and construct a high-quality single nucleotide polymorphism (SNP) dataset. We also evaluate the tiller number at different development stages and heading traits involved in phase transitions. By genome-wide association studies (GWASs), we detected 20 significant association signals for all traits. Five signals were detected in genomic regions near known candidate genes. Most of the candidate genes were involved in the phase transition from vegetative to reproductive growth. In particular, HD1 was simultaneously associated with the productive tiller ratio and heading date, indicating that the photoperiodic heading gene directly controls the productive tiller ratio. Multiple linear regression models of lead SNPs showed coefficients of determination (R2) of 0.49, 0.22, and 0.41 for the tiller number at the maximum tillering stage, productive tiller number, and productive tiller ratio, respectively. Furthermore, the model was validated using independent japonica rice collections, implying that the lead SNPs included in the linear regression model were generally applicable to the tiller number prediction. We revealed the genetic basis of the tiller number in rice plants during growth, By GWASs, and formulated a prediction model by linear regression. Our results improve our understanding of tillering in rice plants and provide a basis for breeding high-yield rice varieties with the optimum the tiller number.

Increasing wintertime ozone levels and secondary aerosol formation in the Guanzhong basin, central China.

The observed near-surface ozone (O3) concentration has been remarkably increasing during recent years in winter in the Guanzhong basin, central China, showing a continuous enhancement of the atmospheric oxidizing capacity (AOC). The impact of such a change in the AOC on secondary aerosol formation, however, has not yet been assessed. In this study, we simulate the formation of O3 and airborne particles in the atmosphere using the WRF-Chem model, in which the AOC is calculated quantitatively, to understand the responses of secondary aerosols to the AOC increase. Meteorological observations, air pollutants including O3, NO2, SO2, CO, and PM2.5 concentrations at ambient monitoring sites, and the main compositions of submicron particulates measured using ACSM are used to constrain the model simulation. The model result shows that the population hourly and postmeridian Ox (=O3 + NO2) concentrations are good indicators for the wintertime AOC in the basin, suggested by the significantly positive correlations between them. Sensitivity experiments present that the AOC changes may exert important influences on fine particle (PM2.5) concentration with an average rate of 1.94 (µg m-3)/(106 cm-3 s-1) for Δ(PM2.5)/Δ(AOC), which is mostly caused by the mass changes in secondary organic aerosol (43%) and nitrate aerosol (40%) and less attributed to the ammonium (11%) and sulfate (6%) components.

Construction of Glycometabolism- and Hormone-Related lncRNA-Mediated Feedforward Loop Networks Reveals Global Patterns of lncRNAs and Drug Repurposing in Gestational Diabetes.

Gestational diabetes mellitus (GDM) is a condition associated with the onset of abnormal glucose tolerance during pregnancy. Long non-coding RNAs (lncRNAs), microRNAs (miRNAs), and genes can form lncRNA-mediated feedforward loops (lnc-FFLs), which are functional network motifs that regulate a wide range of biological processes and diseases. However, lnc-FFL network motifs have not been systematically investigated in GDM, and their role in the disease remains largely unknown. In the present study, a global lnc-FFL network was constructed and analyzed. Glycometabolism- and hormone-related lnc-FFL networks were extracted from the global network. An integrated algorithm was designed to identify dysregulated glycometabolism- and hormone-related lnc-FFLs in GDM. The patterns of dysregulated lnc-FFLs in GDM were complex. Moreover, there were strong associations between dysregulated glycometabolism- and hormone-related lnc-FFLs in GDM. Core modules were extracted from the dysregulated lnc-FFL networks in GDM and showed specific and essential functions. In addition, dysregulated lnc-FFLs could combine with ceRNAs and form more complex modules, which could play novel roles in GDM. Notably, we discovered that the dysregulated lnc-FFLs were enriched in the thyroid hormone signaling pathway. Some drug-repurposing candidates, such as hormonal drugs, could be identified based on lnc-FFLs in GDM. In summary, the present study highlighted the effect of dysregulated glycometabolism- and hormone-related lnc-FFLs in GDM and revealed their potential for the discovery of novel biomarkers and therapeutic targets for GDM.

Identification and characterization of methylation-mediated transcriptional dysregulation dictate methylation roles in preeclampsia.

BACKGROUND: Preeclampsia (PE) is a heterogeneous, hypertensive disorder of pregnancy, with no robust biomarkers or effective treatments. PE increases the risk of poor outcomes for both the mother and the baby. Methylation-mediated transcriptional dysregulation motifs (methTDMs) could contribute the PE development. However, precise functional roles of methTDMs in PE have not been globally described. METHODS: Here, we develop a comprehensive and computational pipeline to identify PE-specific methTDMs following TF, gene, methylation expression profile, and experimentally verified TF-gene interactions. RESULTS: The regulation patterns of methTDMs are multiple and complex in PE and contain relax inhibition, intensify inhibition, relax activation, intensify activation, reverse activation, and reverse inhibition. A core module is extracted from global methTDM network to further depict the mechanism of methTDMs in PE. The common and specific features of any two kinds of regulation pattern are also analyzed in PE. Some key methylation sites, TFs, and genes such as IL2RG are identified in PE. Functional analysis shows that methTDMs are associated with immune-, insulin-, and NK cell-related functions. Drug-related network identifies some key drug repurposing candidates such as NADH. CONCLUSION: Collectively, the study highlighted the effect of methylation on the transcription process in PE. MethTDMs could contribute to identify specific biomarkers and drug repurposing candidates for PE.

Effect of ship emissions on O3 in the Yangtze River Delta region of China: Analysis of WRF-Chem modeling.

The Yangtze River Delta (YRD) region locates on the eastern coast of China, and it has suffered severe O3 pollutions due to high and mixed emissions of air pollutants. There are 3 different emission sectors for O3 precursors in the region, including anthropogenic VOCS and NOX emissions, ship emissions (mainly NOX), and biogenic emissions from a large forest (biogenic VOCS). This unique emission mixture produces complicated chemical processes in studying the O3 pollutions in the region. This study aims to identify the contribution of the ship emissions to O3 pollutions, as well as the effect of mixing emissions on O3 pollutions in YRD. To identify the individual emission effect, the WRF-Chem model is used in this study. The model generally performs well in simulating meteorological parameters and air pollutants against observations in YRD. Sensitive study suggests that the ship emissions have important effects on the O3 concentrations over ocean and inland, with a maximum increase of 30-50 µg m-3 occurred mainly in the ship track regions. However, the ship emissions have a very complicated effect on the in-land O3 concentrations. In the north of Shanghai, the NOX concentrations are high due to high anthropogenic emissions, and a further increase in NOX emissions from ship results in depressing O3 chemical production. In contrast, in the south of Shanghai, there are high biogenic VOC emissions (mainly isoprene) and low NOx concentrations. As a result, the O3 concentrations are enhanced by 30-50 µg m-3, due to the mixing between ship and forest emissions. This study suggests that ship emissions play important roles in controlling O3 pollutions in YRD. Furthermore, the mixing emissions between ship, anthropogenic, and biogenic emissions in YRD produce a complicated O3 chemical production and need to be carefully considered in controlling strategy of O3 pollution in the region.

Circulating lncRNA BC030099 Increases in Preeclampsia Patients.

Long noncoding RNAs (lncRNAs) have increasingly been shown to be important biological regulators involved in numerous diseases. Further, increasing evidence demonstrates that circulating lncRNAs can be used as diagnostic biomarkers. Therefore, the purpose of this study was to evaluate the potential for circulating lncRNAs as novel biomarkers for the diagnosis of preeclampsia. In the present study, we measured the expression of five lncRNAs known to be relevant to the uterus in whole blood samples from 48 preeclampsia patients and 24 non-preeclampsia healthy subjects using qRT-PCR. We found that circulating levels of lncRNA BC030099 were significantly higher in patients with preeclampsia (1.232 ± 0.4870) than in non-preeclampsia healthy subjects (0.9928 ± 0.2008, p < 0.05). The area under the receiver operating characteristic (ROC) curve for lncRNA BC030099 was 0.713. Univariate and multivariate analyses identified lncRNA BC030099 as an independent predictor for preeclampsia. In brief, our results suggest that increased plasma levels of lncRNA BC030099 are associated with an increased risk of preeclampsia and may be considered a novel biomarker.

A Dual-Salt Gel Polymer Electrolyte with 3D Cross-Linked Polymer Network for Dendrite-Free Lithium Metal Batteries.

Lithium metal batteries show great potential in energy storage because of their high energy density. Nevertheless, building a stable solid electrolyte interphase (SEI) and restraining the dendrite growth are difficult to realize with traditional liquid electrolytes. Solid and gel electrolytes are considered promising candidates to restrain the dendrites growth, while they are still limited by low ionic conductivity and incompatible interphases. Herein, a dual-salt (LiTFSI-LiPF6) gel polymer electrolyte (GPE) with 3D cross-linked polymer network is designed to address these issues. By introducing a dual salt in 3D structure fabricated using an in situ polymerization method, the 3D-GPE exhibits a high ionic conductivity (0.56 mS cm-1 at room temperature) and builds a robust and conductive SEI on the lithium metal surface. Consequently, the Li metal batteries using 3D-GPE can markedly reduce the dendrite growth and achieve 87.93% capacity retention after cycling for 300 cycles. This work demonstrates a promising method to design electrolytes for lithium metal batteries.