Formaldehyde: An Essential Intermediate for C1 Metabolism and Bioconversion.

Formaldehyde is an intermediate metabolite of methylotrophic microorganisms that can be obtained from formate and methanol through oxidation-reduction reactions. Formaldehyde is also a one-carbon (C1) compound with high uniquely reactive activity and versatility, which is more amenable to further biocatalysis. Biosynthesis of high-value-added chemicals using formaldehyde as an intermediate is theoretically feasible and promising. This review focuses on the design of the biosynthesis of high-value-added chemicals using formaldehyde as an essential intermediate. The upstream biosynthesis and downstream bioconversion pathways of formaldehyde as an intermediate metabolite are described in detail, aiming to highlight the important role of formaldehyde in the transition from inorganic to organic carbon and carbon chain elongation. In addition, challenges and future directions of formaldehyde as an intermediate for the chemicals are discussed, with the expectation of providing ideas for the utilization of C1.

Stable Halide Perovskite CsPbBr3 Nanocrystals Assisted by Covalent-Organic Frameworks for Electrochemiluminescence Analysis in an Aqueous Medium.

Lead halide perovskites have garnered attention as promising electrochemiluminescence (ECL) emitters owing to their superior photophysical characteristics. However, their poor water stability severely restricts their application in aqueous media for ECL. In this study, inorganic perovskite CsPbBr3 was assembled in situ in the imine-linked covalent-organic framework (COF-LZU1) as a novel ECL emitter. The expansive surface area and robust hydrophobic architecture of COF-LZU1 not only improved the water stability of CsPbBr3 but also guaranteed its exceptional ECL performance. The novel composite nanoluminescent material was coated onto an indium tin oxide (ITO) electrode via spin-coating and calcination processes to serve as an electrochemiluminescence (ECL) platform. A sensor was developed by combining a DNA hydrogel target-induced release system with a platform using ascorbic acid (AA) as a coreactant and T-2 toxin as the target analyte model. This method achieved a detection limit as low as 3.56 fg·mL-1 and was successfully applied to the analysis of the T-2 toxin content in corn samples. This study offers a novel path for the advancement of perovskite-based ECL emitters and their utilization in aqueous environments within the ECL field.

Nonlinear biomechanical behaviour of extracranial carotid artery aneurysms in the framework of Windkessel effect via FSI technique.

Extracranial carotid artery aneurysms (ECCA) lead to rupture and neurologic symptoms from embolisation, with potentially fatal outcomes. Investigating the biomechanical behaviour of EECA with blood flow dynamics is crucial for identifying regions more susceptible to rupture. A coupled three-dimensional (3D) Windkessel-framework and hyperelastic fluid-structure interaction (FSI) analysis of ECCAs with patient-specific geometries, was developed in this paper with a particular focus on hemodynamic parameters and the arterial wall's biomechanical response. The blood flow has been modelled as non-Newtonian, pulsatile, and turbulent. The biomechanical characteristics of the aneurysm and artery are characterised employing a 5-parameter Mooney-Rivlin hyperelasticity model. The Windkessel effect is also considered to efficiently simulate pressure profile of the outlets and to capture the dynamic changes over the cardiac cycle. The study found the aneurysm carotid artery exhibited the high levels of pressure, wall shear stress (WSS), oscillatory shear index (OSI), and relative residence time (RRT) compared to the healthy one. The deformation of the arterial wall and the corresponding von Mises (VM) stress were found significantly increased in aneurysm cases, in comparison to that of no aneurysm cases, which strongly correlated with the hemodynamic characteristics of the blood flow and the geometric features of the aneurysms. This escalation would intensify the risk of aneurysm wall rupture. These findings have critical implications for enhancing treatment strategies for patients with extracranial aneurysms.

A bimetallic PtAu-modified carbon fiber electrochemical sensor for simultaneous and highly sensitive detection of catechol and hydroquinone in environmental water.

In this study, we report the development of a novel electrochemical sensor capable of the simultaneous detection of catechol (CC) and hydroquinone (HQ) through differential pulse voltammetry. The sensor is constructed using carbon fiber (CF) that has been intricately modified with bimetallic PtAu nanoparticles. The fabrication process involves subjecting CF to ultrasound treatment in an acidic mixture, resulting in the formation of activated carbon fiber (ACF). This activation step not only enhances surface roughness but also facilitates subsequent modification, ensuring the stability of the material. Bimetallic PtAu nanoparticles are then uniformly deposited onto the ACF surface through co-deposition from a metal precursor solution. The modified ACF, adorned with bimetallic PtAu nanoparticles, exhibits excellent conductivity and efficiently catalyzes both CC and HQ in a 10 mM phosphate-buffered saline solution at pH 7.0, thereby enabling their simultaneous detection. Under optimized experimental conditions, this electrochemical sensor achieves impressive detection limits of 0.019 µM for CC and 0.28 µM for HQ within the same concentration range of 0.5-50 µM, respectively. The practicality of the sensor is further demonstrated through recovery experiments using real water samples. This electrochemical sensor, with its superior performance and versatility, shows great potential for applications in analytical chemistry and environmental monitoring.

A deep learning method for predicting the origins of cervical lymph node metastatic cancer on digital pathological images.

The metastatic cancer of cervical lymph nodes presents complex shapes and poses significant challenges for doctors in determining its origin. We established a deep learning framework to predict the status of lymph nodes in patients with cervical lymphadenopathy (CLA) by hematoxylin and eosin (H&E) stained slides. This retrospective study utilized 1,036 cervical lymph node biopsy specimens at the First Affiliated Hospital of Sun Yat-Sen University (FAHSYSU). A multiple-instance learning algorithm designed for key region identification was applied, and cross-validation experiments were conducted in the dataset. Additionally, the model distinguished between primary lymphoma and metastatic cancer with high prediction accuracy. We also validated our model and other models on an external dataset. Our model showed better generalization and achieved the best results on both internal and external datasets. This algorithm offers an approach for evaluating cervical lymph node status before surgery, significantly aiding physicians in preoperative diagnosis and treatment planning.

Gas6/Axl signaling promotes hematoma resolution and motivates protective microglial responses after intracerebral hemorrhage in mice.

BACKGROUND: Intracerebral hemorrhage (ICH) stands out as the most fatal subtype of stroke, currently devoid of effective therapy. Recent research underscores the significance of Axl and its ligand growth arrest-specific 6 (Gas6) in normal brain function and a spectrum of neurological disorders, including ICH. This study is designed to delve into the role of Gas6/Axl signaling in facilitating hematoma clearance and neuroinflammation resolution following ICH. METHODS: Adult male C57BL/6 mice were randomly assigned to sham and ICH groups. ICH was induced by intrastriatal injection of autologous arterial blood. Recombinant mouse Gas6 (rmGas6) was administered intracerebroventricularly 30 min after ICH. Virus-induced knockdown of Axl or R428 (a selective inhibitor of Axl) treatment was administrated before ICH induction to investigate the protective mechanisms. Molecular changes were assessed using western blot, enzyme-linked immunosorbent assay and immunohistochemistry. Coronal brain slices, brain water content and neurobehavioral tests were employed to evaluate histological and neurofunctional outcomes, respectively. Primary glia cultures and erythrophagocytosis assays were applied for mechanistic studies. RESULTS: The expression of Axl increased at 12 h after ICH, peaking on day 3. Gas6 expression did not remarkably changed until day 3 post-ICH. Early administration of rmGas6 following ICH significantly reduced hematoma volume, mitigated brain edema, and restored neurological function. Both Axl-knockdown and Axl inhibitor treatment abolished the neuroprotection of exogenous Gas6 in ICH. In vitro studies demonstrated that microglia exhibited higher capacity for phagocytosing eryptotic erythrocytes compared to normal erythrocytes, a process reversed by blocking the externalized phosphatidylserine on eryptotic erythrocytes. The erythrophagocytosis by microglia was Axl-mediated and Gas6-dependent. Augmentation of Gas6/Axl signaling attenuated neuroinflammation and drove microglia towards pro-resolving phenotype. CONCLUSIONS: This study demonstrated the beneficial effects of recombinant Gas6 on hematoma resolution, alleviation of neuroinflammation, and neurofunctional recovery in an animal model of ICH. These effects were primarily mediated by the phagocytotic role of Axl expressed on microglia.

Elevated High-Sensitivity C-Reactive Protein Level Enhances the Impact of Lipoprotein(a) on Platelet Reactivity in PCI Patients Treated with Clopidogrel.

BACKGROUND: Recently, the effect of Lipoprotein(a) [Lp(a)] on thrombogenesis has aroused great interest, while inflammation has been reported to modify the Lp(a)-associated risks through an unidentified mechanism. PURPOSE: This study aimed to evaluate the association between platelet reactivity with Lp(a) and high-sensitivity C-reactive protein (hs-CRP) levels in percutaneous intervention (PCI) patients treated with clopidogrel. METHODS: Data were collected from 10,724 consecutive PCI patients throughout the year 2013 in Fuwai Hospital. High on-treatment platelet reactivity (HTPR) and low on-treatment platelet reactivity (LTPR) were defined as thrombelastography (TEG) maximum amplitude of adenosine diphosphate-induced platelet (MAADP) > 47 mm and < 31 mm, respectively. RESULTS: 6615 patients with TEG results were finally enrolled. The mean age was 58.24 ± 10.28 years and 5131 (77.6%) were male. Multivariable logistic regression showed that taking Lp(a) < 30 mg/dL and hs-CRP < 2 mg/L as the reference, isolated Lp(a) elevation [Lp(a) ≥ 30 mg/dL and hs-CRP < 2 mg/L] was not significantly associated with HTPR (P = 0.153) or LTPR (P = 0.312). However, the joint elevation of Lp(a) and hs-CRP [Lp(a) ≥ 30 mg/dL and hs-CRP ≥ 2 mg/L] exhibited enhanced association with both HTPR (OR:1.976, 95% CI 1.677-2.329) and LTPR (OR:0.533, 95% CI 0.454-0.627). CONCLUSIONS: The isolated elevation of Lp(a) level was not an independent indicator for platelet reactivity, yet the concomitant elevation of Lp(a) and hs-CRP levels was significantly associated with increased platelet reactivity. Whether intensified antiplatelet therapy or anti-inflammatory strategies could mitigate the risks in patients presenting combined Lp(a) and hs-CRP elevation requires future investigation.

MelTrans: Mel-Spectrogram Relationship-Learning for Speech Emotion Recognition via Transformers.

Speech emotion recognition (SER) is not only a ubiquitous aspect of everyday communication, but also a central focus in the field of human-computer interaction. However, SER faces several challenges, including difficulties in detecting subtle emotional nuances and the complicated task of recognizing speech emotions in noisy environments. To effectively address these challenges, we introduce a Transformer-based model called MelTrans, which is designed to distill critical clues from speech data by learning core features and long-range dependencies. At the heart of our approach is a dual-stream framework. Using the Transformer architecture as its foundation, MelTrans deciphers broad dependencies within speech mel-spectrograms, facilitating a nuanced understanding of emotional cues embedded in speech signals. Comprehensive experimental evaluations on the EmoDB (92.52%) and IEMOCAP (76.54%) datasets demonstrate the effectiveness of MelTrans. These results highlight MelTrans's ability to capture critical cues and long-range dependencies in speech data, setting a new benchmark within the context of these specific datasets. These results highlight the effectiveness of the proposed model in addressing the complex challenges posed by SER tasks.

Prognostic value of Glasgow Prognostic Score and its modified scores on 5-year outcome in patients with coronary heart disease undergoing percutaneous coronary intervention.

Background: Glasgow Prognostic Score (GPS) and its modified counterparts, including the modified GPS (mGPS) and hsCRP-modified GPS (hs-mGPS), are widely used inflammatory indices in clinical settings. Inflammation has gained increased attention in the context of coronary heart disease (CHD); however, its long-term predictive value in patients with CHD remains uncertain. Objective: This study aimed to assess the predictive values of GPS, mGPS, and hs-mGPS for long-term survival in patients following percutaneous coronary intervention (PCI). Methods: Consecutive 10,724 PCI patients were enrolled in 2013. The primary endpoint was 5-year all-cause death. Results: This study included 8,909 patients. Individuals with high GPS, mGPS, and hs-mGPS scores exhibited a significantly higher risk of all-cause death compared to those with low scores (all P < 0.05). All three indices (GPS, mGPS, and hs-mGPS) demonstrated predictive values for all-cause death, albeit with relatively low area under the curve values of 0.534, 0.522, and 0.545, respectively. Furthermore, we refined the hs-mGPS using cutoffs (hsCRP at 2 mg/L and albumin at 40 g/L) which are better suited for these patients, to establish the CHD-hs-mGPS. This modification significantly improved the prediction of all-cause death, outperformed the mGPS and demonstrated numerical superiority over both the GPS and hs-mGPS. Notably, only CHD-hs-mGPS exhibited a predictive value for both the ACS and non-ACS subgroups. Conclusion: In patients with CHD who underwent PCI, GPS, mGPS, and hs-mGPS demonstrated significant long-term predictive values for all-cause death. Our parameter-adjusted score, the CHD-hs-mGPS, is applicable to a broad population and moderately enhances the predictive accuracy, facilitating the early identification of patients at high risk of long-term death.

Research on a Transformer Vibration Fault Diagnosis Method Based on Time-Shift Multiscale Increment Entropy and CatBoost.

A mechanical vibration fault diagnosis is a key means of ensuring the safe and stable operation of transformers. To achieve an accurate diagnosis of transformer vibration faults, this paper proposes a novel fault diagnosis method based on time-shift multiscale increment entropy (TSMIE) combined with CatBoost. Firstly, inspired by the concept of a time shift, TSMIE was proposed. TSMIE effectively solves the problem of the information loss caused by the coarse-graining process of traditional multiscale entropy. Secondly, the TSMIE of transformer vibration signals under different operating conditions was extracted as fault features. Finally, the features were sent into the CatBoost model for pattern recognition. Compared with different models, the simulation and experimental results showed that the proposed model had a higher diagnostic accuracy and stability, and this provides a new tool for transformer vibration fault diagnoses.

Synergy between Nitrogen Removal and Fermentation Bacteria Ensured Efficient Nitrogen Removal of a Mainstream Anammox System at Low Temperatures.

Simultaneous partial nitrification, anammox, denitrification, and fermentation (SNADF) is a novel process achieving simultaneous advanced sludge reduction and nitrogen removal. The influence of low temperatures on the SNADF reactor was explored to facilitate the application of mainstream anammox. When temperature decreased from 32 to 16 °C, efficient nitrogen removal was achieved, with a nitrogen removal efficiency of 81.9-94.9%. Microbial community structure analysis indicated that the abundance of Candidatus Brocadia (dominant anaerobic ammonia oxidizing bacteria (AnAOB) in the system) increased from 0.03% to 0.18%. The abundances of Nitrospira and Nitrosomonas increased from 1.6% and 0.16% to 2.5% and 1.63%, respectively, resulting in an increase in the ammonia-oxidizing bacteria (AOB) to nitrite-oxidizing bacteria (NOB) abundance ratio from 0.1 to 0.64. This ensured sufficient nitrite for AnAOB, promoting nitrogen removal. In addition, Candidatus Competibacter, which plays a role in partial denitrification, was the dominant denitrification bacteria (DNB) and provided more nitrite for AnAOB, facilitating AnAOB enrichment. Based on the findings from microbial correlation network analysis, Nitrosomonas (AOB), Thauera, and Haliangium (DNB), and A4b and Saprospiraceae (fermentation bacteria), were center nodes in the networks and therefore essential for the stability of the SNADF system. Moreover, fermentation bacteria, DNB, and AOB had close connections in substrate cooperation and resistance to adverse environments; therefore, they also played important roles in maintaining stable nitrogen removal at low temperatures. This study provided new suggestions for mainstream anammox application.

Increasing biomass concentration facilitates simultaneous nitrogen removal and sludge reduction under low C/N conditions.

To overcome the issues of limited carbon source and high sludge production in partial denitrification/anammox (PD/A) process, the effects of mixed liquor suspended solids (MLSS) and carbon/nitrogen ratio (C/N) on PD/A were investigated through parallel experiments. Nitrogen removal efficiencies decreased significantly when C/N was reduced (1.5 â†’ 0.75). When MLSS was doubled, the nitrogen removal efficiencies in the two parallel reactors increased from 75.3 %, 72.9 % to 86.9 %, 89.7 %, respectively, and sludge yields decreased obviously. Combining with in-situ test, it was speculated when MLSS increased, fermentation was enhanced, providing substrate for partial denitrification. Thauera, involved in partial denitrification, decreased obviously with reduced C/N, but increased from 9.93 % to 38.16 % when MLSS doubled, which could promote the PD/A process. Terrimonas and Ignavibacterium (fermentative bacteria) increased from 1.26 %, 5.22 % to 6.62 %, 6.30 %, respectively. These results proved that increasing MLSS under low C/N ratios promoted fermentation in PD/A system, facilitating efficient nitrogen removal and sludge reduction.

A Hierarchical RF-XGBoost Model for Short-Cycle Agricultural Product Sales Forecasting.

Short-cycle agricultural product sales forecasting significantly reduces food waste by accurately predicting demand, ensuring producers match supply with consumer needs. However, the forecasting is often subject to uncertain factors, resulting in highly volatile and discontinuous data. To address this, a hierarchical prediction model that combines RF-XGBoost is proposed in this work. It adopts the Random Forest (RF) in the first layer to extract residuals and achieve initial prediction results based on correlation features from Grey Relation Analysis (GRA). Then, a new feature set based on residual clustering features is generated after the hierarchical clustering is applied to classify the characteristics of the residuals. Subsequently, Extreme Gradient Boosting (XGBoost) acts as the second layer that utilizes those residual clustering features to yield the prediction results. The final prediction is by incorporating the results from the first layer and second layer correspondingly. As for the performance evaluation, using agricultural product sales data from a supermarket in China from 1 July 2020 to 30 June 2023, the results demonstrate superiority over standalone RF and XGBoost, with a Mean Absolute Percentage Error (MAPE) reduction of 10% and 12%, respectively, and a coefficient of determination (R2) increase of 22% and 24%, respectively. Additionally, its generalization is validated across 42 types of agricultural products from six vegetable categories, showing its extensive practical ability. Such performances reveal that the proposed model beneficially enhances the precision of short-term agricultural product sales forecasting, with the advantages of optimizing the supply chain from producers to consumers and minimizing food waste accordingly.

Ultrasound-assisted extraction of polyphenols from Phyllanthi Fructus: Comprehensive insights from extraction optimization and antioxidant activity.

Phyllanthi Fructus (PF) is a valuable botanical resource with a long history of traditional use, known for potent antioxidant and anti-inflammatory effects attributed to its rich contents of bioactive compounds, particularly polyphenols. However, current extraction techniques limit the utilization of polyphenols from PF. This study aimed to achieve the maximum polyphenol yield and improve the antioxidant activity of PF extracts to promise PF's prospects for modern healthcare. Firstly, ultrasonic-assisted extraction (UAE) was employed to extract the polyphenols in PF and a combination of Plackett-Burman designs (PBD) and response surface methodology (RSM) was applied to optimize UAE's conditions. Next, cellular superoxide dismutase (SOD) and malondialdehyde (MDA) were used to assess the antioxidant activity of extracted polyphenols. Ultra-Performance Liquid Chromatography coupled with Quadrupole Time-of-Flight Mass Spectrometry (UPLC-Q-TOF MS) was utilized to characterize polyphenol components in the PF extracts. Finally, network pharmacology and molecular docking analysis were performed to screen the potential target proteins of polyphenols from PF. As a result, the optimized polyphenol yield was 213.49 mg/g, and the antioxidant activities, measured by ability of DPPH scavenging, ABTS+ scavenging, and FRAP were 76.95 %, 2.24 mmol/g, 2.34 mmol/g, respectively. PF extracts also showed good antioxidant capabilities at cellular level. 26 polyphenol components were identified in the PF extracts. Among these, ellagic acid, myricetin, and eriodictyol may exert antioxidant effects by interacting with AKT serine/threonine kinase 1 (AKT1). In conclusion, our study provides valuable insights into the optimizing PF extraction and underscores its potential applications in enhancing natural polyphenols extraction using UAE with a combination of PBD and RSM. These findings offer a promising avenue for the development and utilization of PF, and could serve as a reference for similar extraction processes in the future.

Silicon Nanowires via Metal-Assisted Chemical Etching for Energy Storage Applications.

Silicon nanowires (SiNWs) have demonstrated great potential for energy storage due to their exceptional electrical conductivity, large surface area, and wide compositional range. Metal-assisted chemical etching (MACE) is a widely used top-down technique for fabricating silicon micro/nanostructures. SiNWs fabricated by MACE exhibit significant surface areas and diverse surface chemistry. Since the material composition and surface chemistry have a significant impact on the electrochemical energy storage performance, integrating SiNWs with diverse materials like porous carbon, metal oxides/sulfides, and polymers, can establish composites with excellent properties. Hence, it is imperative to meticulously fabricate SiNW-based materials with customizable morphologies and enhanced electrochemical energy-storage performance. This review provides an in-depth study of recent advancements in SiNW-based materials with enhanced performance for energy storage systems, such as supercapacitors (SCs) and lithium-ion batteries (LIBs). It includes a concise overview of the history, MACE synthesis, and characteristics of SiNWs. Further, it also explores the key elements that influence the MACE process of SiNWs and delves into structural engineering. Additionally, we introduce recent advances in SiNW-based materials for the design of high-performance energy-storage devices, namely SCs and LIBs. Finally, we present the crucial future prospects of SiNW-based materials for energy-storage applications.

Fabrication and characterization of oleic acid/sesame protein isolate/ poly (vinyl) alcohol core-shell nanofibers: Mitigating lipid oxidation by emulsion electrospinning.

Formulated oil-in-water (O/W) emulsions of oleic acid (OA) using sesame protein isolate (SPI) were processed via emulsion electrospinning with poly (vinyl) alcohol (PVA) to fabricate core-shell nanofibers for lipid oxidation prevention. The emulsion droplet size and viscosity increased as the oil volume fraction rose from 5 % to 30 %. The morphology tests and Fourier transform infrared spectroscopy (FTIR) confirmed the uniformity of nanofibers and OA encapsulation with hydrogen bonding. The thermal stability, mechanical properties, and water contact angle (WCA) of the nanofiber films improved with increased OA content. Encapsulation efficiency was 94.76 % and storage stability was maintained for 7 days in 5 % oil fraction nanofibers. The nanofibers showed lower oxidation and superior oxidative resistance to free OA, with the lowest peroxide value (POV, 2.14 mmol/L) and thiobarbituric acid-reactive substances (TBARS, 36.75 µmol/L). In conclusion, the OA/SPI/PVA (PE) core-shell nanofibers via emulsion electrospinning are efficient for fatty acid encapsulation in functional foods.

Treatment of secondary uterine malignancy following radiotherapy for cervical cancer: a study based on the SEER database.

BACKGROUND: Radiotherapy is one of the main treatments for cervical cancer. Long-term complications of radiation exposure include the emergence of secondary tumors. This is a retrospective study based on an American population. We discuss the optimal treatment modality for patients with radiation-induced secondary uterine malignancy based on the Surveillance, Epidemiology, and End Results database. METHODS: The study included patients with a definitive pathological diagnosis of cervical cancer who were diagnosed with a uterine malignant tumor ≥ 1 year later. Patients in whom cervical cancer was not the first tumor or patients with missing data were excluded. Univariate and multivariate analyses were performed using the COX regression model to screen independent prognostic factors affecting overall survival. Kaplan-Meier survival curves were analyzed using the R software package. RESULTS: We screened 142 patients with a secondary uterine malignancy after cervical cancer treatment, 115 patients with a secondary uterine malignancy after radiotherapy, and 27 patients with a secondary uterine malignancy who did not receive radiotherapy. The average latency period for developing a secondary tumor was 8 years, and 57.04% of the patients had a second tumor at ≥ 60 years of age. In patients with a secondary uterine malignancy after radiotherapy, surgery improved the prognosis [hazard ratio (HR), 0.374; 95% confidence interval (CI), 0.229-0.612], whereas radiotherapy and chemotherapy did not reduce the risk of death. In the subgroup analysis, the surgery plus chemotherapy group had a significantly better survival prognosis than the other groups (HR, 0.251; 95% CI, 0.122-0.515). CONCLUSIONS: The results suggest that the treatment modality in patients with secondary uterine malignancy after radiotherapy for cervical cancer has a significant impact on survival. The survival outcomes of patients receiving surgery combined with chemotherapy are superior to those of patients receiving other treatments.

Oil-droplet anchors accelerate the gelation of regenerated silk fibroin-based emulsion gels.

The oil fraction will affect the aggregation behavior and structural strength of emulsion gels. In this study, the effect of the camellia oil (CO) fraction on the properties of emulsion gels stabilized by regenerated silk fibroin (RSF) was studied. The results showed that CO was essential for gel formation, with oil droplets incorporated into the RSF matrix as anchors to achieve rapid gelation of RSF. The gel hardness significantly increased from 20.03 to 53.35 g as the fraction of CO increased from 5 % to 25 %. The oxidation stability of the emulsion gels was also improved, and the peroxide value (POV) decreased from 2419.3 to 839.9 µmol/kg. As the oil fraction rose from 5 % to 25 %, the percentage of released free fatty acids decreased from 73.24 % to 59.49 % due to forming a more compact gel structure. In addition, the rheological results revealed that all emulsion gels had a shear-thinning behavior and good temperature stability in the range of 5 to 90 °C. This study provided a theoretical basis for preparing RSF-based emulsion gels, helps in the recycling of silk protein resources, and promotes the development of emulsion gel applications in the food industry.

Nitrogen isotope characteristics and importance of NOx from biomass burning in China.

Biomass burning is a primary source of atmospheric nitrogen oxide (NOx), however, the lack of isotopic fingerprints from biomass burning limits their use in tracing atmospheric nitrate (NO3-) and NOx. A total of 25 biomass fuels from 10 provinces and regions in China were collected, and the δ15N values of biomass fuels (δ15N-biomass) and δ15N-NOx values of biomass burning (δ15N-NOx values of BB, open burning, and rural cooking stove burning) were determined. The δ15N-NOx values of open burning and rural cooking stove burning ranged from -0.8 ‰ to 11.6 ‰ and 0.8 ‰ to 9.5 ‰, respectively, indicating a significant linear relation with δ15N-biomass. Based on the measured δ15N-NOx values of BB and biomass burning emission inventory data, the δ15N-NOx values of BB in different provinces and regions of China were calculated using the δ15N-NOx model, with a mean value of 5.0 ± 1.8 ‰. The spatial variations in the estimated δ15N-NOx values of BB in China were mainly controlled by the differences in the δ15N-NOx values and the proportions of NOx emissions from various straw burning activities in provinces and regions of China. Furthermore, by using the combined local emissions of biomass burning with regional transportations of NOx based on air-mass backward trajectories, we established an improved δ15N-NOx model and obtained more accurate δ15N-NOx values of BB in regions (2.3 ‰ to 8.4 ‰). By utilising the reported δ15N-NOx values of precipitation and particulate matter from 21 cities in China and the more accurate δ15N-NOx values of BB, the NOx contributions from four sources (mobile sources, coal combustion, biomass burning, and microbial N cycle) at the national scale were estimated using a Bayesian model. The significant contributions of biomass burning (20.9 % to 44.3 %) to NOx emissions were revealed, which is vital for controlling NOx emissions in China.

A rice amino acid transporter OsMP1 acts as a quantitative trait locus against blast fungus and leaf-blight bacterium.

Amino acid homeostasis is interconnected with the immune network of plants. During plant-pathogen interaction, amino acid transporters (AATs) have been shown to be involved in plant immune responses. However, the molecular mechanism by which how AATs function in this process remains elusive. In this study, we identify OsMP1 that acts as a quantitative trait locus against blast fungus from a joint analysis of GWAS and QTL mapping in rice. Heterogeneous expression of OsMP1 in yeast supports its function in transporting a wide range of amino acids, including Thr, Ser, Phe, His and Glu. OsMP1 could also mediate 15N-Glu efflux and influx in Xenopus oocyte cells. The expression of OsMP1 is dramatically induced by Magnaporthe oryzae in the resistant landrace Heikezijing, while remaining unresponsive in the susceptible landrace Suyunuo. Overexpressing OsMP1 in Suyunuo enhances disease resistance to blast fungus and leaf-blight bacterium without yield penalty. Furthermore, the overexpression of OsMP1 leads to increased accumulation of Thr, Ser, Phe and His in the leaves. And the heightened levels of these amino acids contribute to reduced disease susceptibility, which is associated with upregulated jasmonic acid pathway. Thus, our results elucidate the pivotal role of OsMP1 in disease resistance and provide a potential target for breeding more resistant rice cultivars without compromising yield.