Explore the vast range of titles available.

Ascorbic acid is among the most abundant antioxidants in the lung, where it likely plays a key role in the mechanism by which particulate air pollution initiates a biological response. Because ascorbic acid is a highly redox active species, it engages in a far more complex web of reactions than a typical organic molecule, reacting with oxidants such as the hydroxyl radical as well as redox-active transition metals such as iron and copper. The literature provides a solid outline for this chemistry, but there are large disagreements about mechanisms, stoichiometries and reaction rates, particularly for the transition metal reactions. Here we synthesize the literature, develop a chemical kinetics model, and use seven sets of laboratory measurements to constrain mechanisms for the iron and copper reactions and derive key rate constants. We find that micromolar concentrations of iron(III) and copper(II) are more important sinks for ascorbic acid (both AH 2 and AH − ) than reactive oxygen species. The iron and copper reactions are catalytic rather than redox reactions, and have unit stoichiometries: Fe(III)/Cu(II) + AH 2 /AH −  + O 2 → Fe(III)/Cu(II) + H 2 O 2  + products. Rate constants are 5.7 × 10 4 and 4.7 × 10 4  M −2  s −1 for Fe(III) + AH 2 /AH − and 7.7 × 10 4 and 2.8 × 10 6  M −2  s −1 for Cu(II) + AH 2 /AH − , respectively.

To assess the performance of the PPP-B2b service, most existing studies typically store real-time PPP-B2b messages and leverage them to acquire precise satellite orbits and clock offsets. However, they often overlook potential interferences, such as occlusions and receiving delays, that may occur in real-time scenarios. Consequently, these studies fail to fully capture the real-time positioning capabilities of PPP-B2b. This study assesses real-time static and kinematic precise point positioning (PPP) solutions based on BDS-3 and BDS-3/GPS. The findings reveal that both BDS-3 and GPS systems demonstrate high signal matching with PPP-B2b, resulting in quicker convergence in real-time static PPP solutions and maintaining stable positioning accuracy without divergence. Particularly noteworthy is the higher precision observed in the north–south direction. Under BDS-3, the convergence time is approximately 26 min, with horizontal accuracy below 0.2 m, vertical accuracy below 0.4 m. Utilizing BDS-3/GPS reduces the convergence time by roughly 30% while maintaining comparable accuracy (horizontal accuracy below 0.2 m, vertical accuracy below 0.4 m). In real-time kinematic PPP solutions, based on the PPP-B2b algorithm, decimeter-level accuracy is attained, particularly in the north and south directions. The convergence time is approximately 1 h and 28 min, longer than real-time static PPP solutions, due to clock system biases. However, within the time periods after convergence and with no divergence, real-time kinematic PPP solutions achieve horizontal accuracy of 4 cm and vertical accuracy of 8 cm.

Summary Flavonoid accumulation in most fruits is enhanced by ethylene and jasmonate. However, little is known about the hormone functions related to red pear fruit coloration or their combined effects and potential underlying mechanisms. Various treatments were used to investigate the flavonoid metabolite profile and pear transcriptome to verify the effects of ethylene and jasmonate on flavonoid biosynthesis in red pear fruits as well as the mechanism behind this. Ethylene inhibits anthocyanin biosynthesis in red Chinese pear fruits, whereas jasmonate increases anthocyanin and flavone/isoflavone biosyntheses. The branching of the jasmonate‐induced flavonoid biosynthesis pathway is determined by ethylene. Co‐expression network and Mfuzz analyses revealed 4,368 candidate transcripts. Additionally, ethylene suppresses PpMYB10 and PpMYB114 expression via TF repressors, ultimately decreasing anthocyanin biosynthesis. Jasmonate induces anthocyanin accumulation through transcriptional or post‐translational regulation of TFs‐like MYB and bHLH in the absence of ethylene. However, jasmonate induces ethylene biosynthesis and the associated signalling pathway in pear, thereby decreasing anthocyanin production, increasing the availability of the precursors for flavone/isoflavone biosynthesis and enhancing deep yellow fruit coloration. We herein present new phenotypes and fruit coloration regulatory patterns controlled by jasmonate and ethylene, and confirm that the regulation of fruit coloration is complex.

Background Flavonoid biosynthesis is strongly influenced by phytohormones. For example, methyl jasmonate (MeJA) enhances the flavonoid accumulation in pear. However, the molecular mechanism underlying the MeJA-induced flavonoid biosynthesis in pear is largely uncharacterized. Therefore, the transcriptome of pear calli treated with MeJA was analyzed to elucidate the mechanism regulating MeJA-mediated flavonoid biosynthesis. Results The application of exogenous MeJA significantly enhanced flavonoid accumulation, especially anthocyanin, in pear calli. A weighted gene co-expression network analysis identified the differentially expressed genes associated with MeJA-induced flavonoid biosynthesis. The MeJA treatment upregulated the expression of the flavonoid biosynthesis pathway structural genes ( PcCHS , PcCHI , PcF3H , PcDFR , PcANS , PcANR2a , and PcLAR1 ). The MYB family members were the main transcription factors regulating the MeJA-induced flavonoid biosynthesis, but the bHLH, AP2-EREBP, NAC, WRKY, and TIFY families were also involved. In addition to PcMYB10, which is a known positive regulator of anthocyanin biosynthesis in pear, several novel MYB candidates that may regulate flavonol and proanthocyanidin biosynthesis were revealed. Yeast two-hybrid and bimolecular fluorescence complementation assays demonstrated that PcMYB10 and PcMYC2 can directly interact with each other and bind to JAZ repressors (PcJAZ1 and PcJAZ2). Conclusions The PcMYB10–PcMYC2 molecular complex is likely involved in the regulation of jasmonate-mediated flavonoid biosynthesis at the transcript level. The data generated in this study may clarify the transcriptional regulatory network associated with the MeJA-induced flavonoid accumulation in pear calli and provide a solid foundation for future studies.

This study investigated the association between serum chloride levels and mortality risk in critically ill patients with sepsis. This retrospective cohort study utilized data from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database. Patients were stratified into four groups based on serum chloride quartiles. The primary outcome was 365-day mortality, while secondary outcomes included 30-day and 90-day mortality. Kaplan–Meier curves were constructed to compare survival probabilities across serum chloride quartiles. Multivariable Cox proportional hazards regression and restricted cubic spline regression analyses were employed to assess the relationship between serum chloride and mortality in sepsis patients. Subgroup and sensitivity analyses were also performed to validate the findings. A total of 17,743 patients (58.26% male) were included in the study. Kaplan–Meier survival curves revealed that sepsis patients in the lowest serum chloride quartile exhibited the highest mortality (log-rank P  < 0.001). Multivariable Cox regression analysis demonstrated that serum chloride was independently associated with a decreased risk of 365-day mortality (HR 0.95, 95% CI 0.94–0.97). Compared with patients in the lowest quartile, those in the highest quartile of serum chloride had significantly lower 365-day mortality (HR 0.66, 95% CI 0.58–0.75), similar trends were observed for 30-day and 90-day mortality. Restricted cubic spline regression modeling indicated a non-linear relationship between serum chloride and mortality risk, with a threshold effect identified at 105 mmol/L ( P for non-linearity < 0.05). Subgroup analyses further revealed an interaction between acute kidney injury and mortality in sepsis patients. Sensitivity analysis confirmed the stability of the results. Our study demonstrated an L-shaped association between serum chloride levels and 365-day mortality in sepsis patients, with higher serum chloride levels corresponding to a lower mortality risk. However, abnormal chloride levels are often secondary to disease severity, emphasizing the need for targeted interventions addressing the underlying pathology rather than chloride levels alone.

Extensive exposure to estrogen is generally acknowledged as a risk factor for endometrial cancer. Given that the accumulation of adipocytes also contributes to the increased production of estrogen, in the present study, we evaluated the expression of the fat mass and obesity-associated (FTO) gene in endometrial tumor tissues and further explored the mechanism of how estrogen facilitates FTO nuclear localization and promotes endometrial cancer cell proliferation. Immunohistochemical (IHC) staining assay was used to detect the FTO expression in endometrial tumor samples. Western blotting was performed to investigate the mechanism of estrogen-induced FTO nuclear localization. siRNA was used to knock down ERα and further explore its role in FTO nuclear localization. MTT assay was carried out to determine cell proliferation. We found that FTO was overexpressed in endometrial carcinoma tissues and served as a poor prognostic marker. Additionally, estrogen induced FTO nuclear accumulation via the mTOR signaling pathway and the nuclear localization was ERα-dependent, which contributed to enhanced proliferative activity. Therefore, the present study provides new insight into the mechanisms of estrogen-induced proliferation, implying the possibility of using FTO as a potential therapeutic target for the treatment of endometrial cancer.

Accurate recognition of tool state is important for maximizing tool life. However, the tool sensor data collected in real-life scenarios has unbalanced characteristics. Additionally, although graph neural networks (GNNs) show excellent performance in feature extraction in the spatial dimension of data, it is difficult to extract features in the temporal dimension efficiently. Therefore, we propose a tool state recognition method based on the Pruned Optimized Graph Neural Network-Gated Recurrent Unit (POGNN-GRU) under unbalanced data. Firstly, design the Improved-Majority Weighted Minority Oversampling Technique (IMWMOTE) by introducing an adaptive noise removal strategy and improving the MWMOTE to alleviate the unbalanced problem of data. Subsequently, propose a POG graph data construction method based on a multi-scale multi-metric basis and a Gaussian kernel weight function to solve the problem of one-sided description of graph data under a single metric basis. Then, construct the POGNN-GRU model to deeply mine the spatial and temporal features of the data to better identify the state of the tool. Finally, validation and ablation experiments on the PHM 2010 and HMoTP datasets show that the proposed method outperforms the other models in terms of identification, and the highest accuracy improves by 1.62% and 1.86% compared with the corresponding optimal baseline model.

This paper presents a comprehensive time-series analysis framework leveraging the Temporal Fusion Transformer (TFT) architecture to address the challenge of multi-horizon forecasting in complex ecological systems, specifically focusing on global fishery resources. Using global fishery data spanning 70 years (1950–2020), enhanced with key climate indicators, we develop a methodology for predicting time-dependent patterns across three-year, five-year, and extended seven-year horizons. Our approach integrates static metadata with temporal features, including historical catch and climate data, through a specialized architecture incorporating variable selection networks, multi-head attention mechanisms, and bidirectional encoding layers. A comparative analysis demonstrates the TFT model’s robust performance against traditional methods (ARIMA), standard deep learning models (MLP, LSTM), and contemporary architectures (TCN, XGBoost). While competitive across different horizons, TFT excels in the 7-year forecast, achieving a mean absolute percentage error (MAPE) of 13.7%, outperforming the next best model (LSTM, 15.1%). Through a sensitivity analysis, we identify the optimal temporal granularity and historical context length for maximizing prediction accuracy. The variable selection component reveals differential weighting, with recent market observations (past 1-year catch: 31%) and climate signals (ONI index: 15%, SST anomaly: 10%) playing significant roles. A species-specific analysis uncovers variations in predictability patterns. Ablation experiments quantify the contributions of the architectural components. The proposed methodology offers practical applications for resource management and theoretical insights into modeling temporal dependencies in complex ecological data.

In this study, a multi-functional layer was developed based on the commercially available cellulose triacetate (CTA) forward osmosis (FO) membrane to improve its antifouling property. Tannic acid/ferric ion (TA/Fe3+) complexes were firstly coated as a precursor layer on the membrane surface via self-assembly. Afterwards, the tannic acid/diethylenetriamine (TA/DETA) hydrophilic functional layer was further coated, following Ag/polyvinylpyrrolidone (PVP) anti-bacterial layer was formed in situ through the reducibility of TA to obtain TA/Fe3+-TA/DETA-Ag/PVP-modified membrane. The optimized precursor layer was acquired by adjusting the buffer solution pH to 8, TA/Fe3+ ratio to 4 and the number of self-assembled layers to 5. The permeability testing results illustrated that the functional layer had an insignificant effect on the membrane transport parameters. The TA/Fe3+-TA/DETA-Ag/PVP-modified membrane simultaneously exhibited excellent physical and chemical stability. The coated membrane also demonstrated enhanced anti-bacterial properties, achieving 98.63 and 97.30% inhibition against Staphylococcus aureus and Escherichia coli, respectively. Furthermore, the dynamic fouling experiment showed a 12% higher water flux decrease for the TA/Fe3+-TA/DETA-Ag/PVP CTA membrane compared to the nascent CTA membrane, which proved its excellent antifouling performance. This work provides a feasible strategy to heighten the antifouling property of the CTA FO membrane.

When the penetrating warhead penetrates the target, the internal charge is subjected to extremely high overload and impact loads. If the load intensity and duration meet the detonation conditions, the warhead may experience early detonation, compromising both the penetration effect and safety. To study the influence of charge structure on penetration stability, a specific warhead was used as a model reference, and finite element simulation software was employed to numerically simulate the penetration of concrete targets by the warhead. The results showed that stress concentration occurred at the warhead head during the penetration process, with the maximum stress exceeding the critical detonation stress of the charge, indicating a possibility of early detonation. To improve penetration stability while maintaining the original damage performance, different models of penetration warheads with various charge structures were constructed to analyze the influence of baffle position and number on charge stress. The results show that the loading structure with added partitions can effectively reduce the stress on the charge during penetration. The optimal effect is achieved when the partition is located at 1/2 of the interior of the projectile, with a maximum pressure of 3.75 GPa, which is 44.36% lower than that of the structure without partitions, thereby improving the penetration stability of the projectile.