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Abstract Background Heterotopic ossification (HO) is a frequent complication of joint trauma or surgery, commonly occurring after hip replacements, acetabular or other joint injuries, or surgeries. Indomethacin has long been used to prevent HO and is considered the first-line therapy. However, its effectiveness and necessity for HO prevention are still debated due to mixed evidence about its efficacy and potential side effects. Methods Following PRISMA guidelines, this systematic review and meta-analysis evaluated randomized controlled trials using the PICO framework. Searches were conducted across PubMed, Embase, Cochrane Library, and Web of Science. Data were extracted and assessed based on the evidence levels of the selected articles. This study was registered with the International Platform of Registered Systematic Review and Meta-analysis Protocols (INPLASY). Results This analysis included 665 patients, with 347 in the Indomethacin group and 318 in the No Indomethacin group. The outcomes analyzed—HO, Gastrointestinal Side Effects, and Bone Ununion—indicated that indomethacin effectively prevents HO. The meta-analysis revealed that the Indomethacin group experienced a significant reduction in the occurrence of grade I-II HO compared to the No Indomethacin group, but not for grade III-IV HO. Gastrointestinal side effects were notably higher in the Indomethacin group. The incidence of bone nonunion was higher in the Indomethacin group, although not statistically significant. Conclusions The meta-analysis suggests that indomethacin is effective in preventing HO, particularly for Brooker grade I-II, rather than Brooker grade III-IV. Special attention should be given to gastrointestinal complications when using indomethacin. Further prospective randomized controlled studies are required to confirm these findings.

Abstract Background Invertases (INVs) are key enzymes in sugar metabolism, cleaving sucrose into glucose and fructose and playing an important role in plant development and the stress response, however, the INV gene family in passion fruit has not been systematically reported. Results In this study, a total of 16 PeINV genes were identified from the passion fruit genome and named according to their subcellular location and chromosome position. These include six cell wall invertase (CWINV) genes, two vacuolar invertase (VINV) genes, and eight neutral/alkaline invertase (N/AINV) genes. The gene structures, phylogenetic tree, and cis-acting elements of PeINV gene family were predicted using bioinformatics methods. Results showed that the upstream promoter region of the PeINV genes contained various response elements; particularly, PeVINV2, PeN/AINV3, PeN/AINV5, PeN/AINV6, PeN/AINV7, and PeN/AINV8 had more response elements. Additionally, the expression profiles of PeINV genes under different abiotic stresses (drought, salt, cold temperature, and high temperature) indicated that PeCWINV5, PeCWINV6, PeVINV1, PeVINV2, PeN/AINV2, PeN/AINV3, PeN/AINV6, and PeN/AINV7 responded significantly to these abiotic stresses, which was consistent with cis-acting element prediction results. Sucrose, glucose, and fructose are main soluble components in passion fruit pulp. The contents of total soluble sugar, hexoses, and sweetness index increased significantly at early stages during fruit ripening. Transcriptome data showed that with an increase in fruit development and maturity, the expression levels of PeCWINV2, PeCWINV5, and PeN/AINV3 exhibited an up-regulated trend, especially for PeCWINV5 which showed highest abundance, this correlated with the accumulation of soluble sugar and sweetness index. Transient overexpression results demonstrated that the contents of fructose, glucose and sucrose increased in the pulp of PeCWINV5 overexpressing fruit. It is speculated that this cell wall invertase gene, PeCWINV5, may play an important role in sucrose unloading and hexose accumulation. Conclusion In this study, we systematically identified INV genes in passion fruit for the first time and further investigated their physicochemical properties, evolution, and expression patterns. Furthermore, we screened out a key candidate gene involved in hexose accumulation. This study lays a foundation for further study on INV genes and will be beneficial on the genetic improvement of passion fruit breeding.

Abstract The static properties and dynamic evolution of bottomonium states in a hot QCD medium are investigated through the Schrödinger equation with complex heavy quark potentials, which have been presented recently in a lattice QCD study and with three different extractions. This approach builds a direct connection between the in-medium heavy quark potentials from the lattice QCD to the experimental observables. The yields and nuclear modification factors $$R_{AA}$$ R AA of bottomonium in Pb–Pb collisions at $$\sqrt{s_\textrm{NN}}=5.02$$ s NN = 5.02 TeV are calculated in this work. Our results show a large suppression of the bottomonium yield in heavy ion collisions due to the large imaginary potential. To understand bottomonium $$R_{AA}$$ R AA based on lattice QCD potentials, we propose a formation time for bottomonium states and find that experimental data can be well explained with the heavy quark potential extracted by the Padé fit, which shows no color screening in the real part potential.

High‐entropy spinel‐type oxides are synthesized by a modified Pechini process, wet chemistry approach, and solid‐state synthesis method and characterized as anode materials for Li‐ion batteries. The Pechini process that involves chelation and polyesterification reactions facilitates the formation of high‐entropy spinel‐type oxides without compositional segregation at ≈600 °C as confirmed by in situ and ex situ XRD. XAFS analysis and the Rietveld refinement of room‐temperature neutron diffraction data suggest the composition (Mn0.05Fe0.48Co0.47, tetrahedral)(Cr0.61Mn0.52Fe0.11Co0.09Ni0.68, octahedral)O4 for phase‐pure specimens. Compared to high‐entropy spinel‐type oxides synthesized by the solid‐state method, the precursor‐derived materials demonstrate higher specific capacity as anodes, in which the materials without citric acid addition exhibit low capacity fading at high current densities and maintained a capacity of ≈200 mAh g−1 after 1000 cycles. The generation of a rock‐salt‐type phase during cycling is confirmed for the first time by in situ charging–discharging XRD. The charging–discharging of this anode material is achieved mainly through the embedding–disembedding of lithium ions in the lattice of the generated rock‐salt‐type phase.

Sea state bias (SSB) is a crucial error of satellite radar altimetry over the ocean surface. For operational nonparametric SSB (NPSSB) models, such as two-dimensional (2D) or three-dimensional (3D) NPSSB, the solution process becomes increasingly complex and the construction of their regression functions pose challenges as the dimensionality of relevant variables increases. And most current SSB correction models for altimeters still follow those of traditional nadir radar altimeters, which limits their applicability to Synthetic Aperture Radar altimeters. Therefore, to improve this situation, this study has explored the influence of multi-dimensional SSB models on Synthetic Aperture Radar altimeters. This paper proposes a deep learning-based SSB estimation model called SNSSB, which employs a Siamese network framework, takes various multi-dimensional variables related to sea state as inputs, and uses the difference in sea surface height (SSH) at self-crossover points as the label. Experiments were conducted using Sentinel-6 self-crossover data from 2021 to 2023, and the model is evaluated using three main metrics: the variance of the SSH difference, the explained variance, and the SSH difference variance index (SVDI). The experimental results demonstrate that the proposed SNSSB model can further improve the accuracy of SSB estimation. On a global scale, compared to the traditional NPSSB, the multi-dimensional SNSSB not only decreases the variance of the SSH difference by over 11%, but also improves the explained variance by 5-10 cm2 in mid- and low-latitude regions. And the regional SNSSB also performs well, reducing the variance of the SSH difference by over 10% compared to the NPSSB. Additionally, the SNSSB model improves the computational efficiency by approximately 100 times. The favorable results highlight the potential of the multi-dimensional SNSSB in constructing SSB models, particularly the five-dimensional (5D) SNSSB, representing a breakthrough in overcoming the limitations of traditional NPSSB for constructing high-dimensional models. This study provides a novel approach to exploring the multiple influencing factors of SSB.

The formation and evolution mechanisms of coal mine water quality are intricate, significantly influenced by multiple processes such as hydrodynamics, hydrochemistry, and biodegradation. A comprehensive investigation and elucidation of the mechanisms is theoretically crucial for the prevention and remediation of coal mine water pollution. The hydrogeological prototype of a goaf in a coal mine in the Ordos Basin is choosen, and a laboratorial physical model and a coupled hydrodynamic-chemical-biodegradation (HCB) milti-field numerical model for the goaf are established, focusing the water level rises and biogeochemistry processes. The research results demonstrate the significance of multi-field coupling effects on mine water quality. The water level filling up results shows that the matrix-fracture dual-porosity model effectively matches the water level in the goaf with a simulation error of 9.9%, which is much more accurate than the theoretical and the single-porosity model predictions. The simulation results of the hydrochemical field are relatively consistent with the experiments, with relative errors of 3.0%, 21.0%, and 6.2% for \begin{document}${\mathrm{SO}}_4^{2-} $\end{document}, \begin{document}${\mathrm{HCO}}_3^- $\end{document}, and pH, respectively. Results from different time periods indicate that water-rock reactions and microbial activities are not significant during the water storage process. After the goaf is filled up, the hydrodynamics almost stagnate, but the hydrochemical and microbial fields are relatively active. The pyrite oxidation reactions in the No.2 and No.3 coal seams increase the concentration of \begin{document}${\mathrm{SO}}_4^{2-} $\end{document} by about 24.6%. In the later stage, the water environment in the goaf evolves into weakly acidic and anaerobic reducing conditions, and the microbial degradation becomes prominent, reducing the \begin{document}${\mathrm{SO}}_4^{2-} $\end{document} concentration from its peak by 6.1%. A certain “self-purification” ability of mine water in the goaf after closure has been confirmed. By adjusting the microbial metabolic rate constant, the proportion of \begin{document}${\mathrm{SO}}_4^{2-} $\end{document} degradation can be induced up to 61.6%. In actual engineering scenarios, this target can be achieved through some strategies such as supplementing enough dissolved carbon nutrient substance and artificially establishing a closed anaerobic environment. This study expands the multi-field coupling laboratorial experiments and numerical modeling techniques to the formation and evolution of water quality in coal mine water in a goaf, and the constructive conclusions can provide theoretical guidance for the prevention and remediation of coal mine water pollution.

In coastal regions, the formation of submesoscale eddies is frequently influenced by factors including topography, tidal forces, and ocean currents. These eddies are often challenging to detect owing to the limited spatial resolution of altimeters and restricted observation areas. Equipped with a multispectral imager (MSI) specialized in coastal and offshore environments, SDGSAT-1 supports the sustainable development goals. It generates extensive data concerning nearshore resources. However, the multispectral data from SDGSAT-1 exhibit image blurring and indistinct eddy boundaries due to the imaging conditions of remote sensing satellites. This challenge impedes conventional deep learning models from directly identifying these features. Consequently, we developed a multispectral eddy detection network (MEDNet). Given the characteristics of remote sensing images, we employ a linear stretching technique to enhance eddy information in SDGSAT-1 images. Additionally, we propose a multispectral eddy horizontal flip technique (MEHFT) to address the imbalance between cyclonic and anticyclonic eddies in remote sensing imagery. To direct the network’s focus towards critical areas, we incorporate a multi-branch stacking construct and an SPPCSPC module to enhance eddy feature extraction. Experimental results demonstrate that our method achieves high accuracy (mAP of 90.42%) in the dataset, surpassing competing object detection models.

ABSTRACTThe capability of continuous eddy tracking has been significantly advanced over the past decades, thanks to the availability of sea surface height measurements routinely collected by satellite altimeters. However, due to the complexity of eddy kinematic mechanisms and underlying oceanic processes, a medium-range forecast of individual eddy trajectories is a challenging task. This study develops an algorithm to effectively achieve a precise prediction of eddy propagation with a ten-day lead time by building a physics-embedded temporal evolution model. The theoretical eddy phase speed, current field, and eddy properties are incorporated as physical constraints. Compared to only considering eddy past/climatological velocities, the forecast accuracy of embedded physics constraints is improved by 21%. Forecasting of 2.3 million altimeter-derived eddy tracks globally shows that trajectory predictions are valid for eddies moving towards any direction, and the forecast error achieves 9.9 km on a ten-day average. After systematically evaluating the global forecast error, we conclude that the forecasting accuracy is geographically correlated and affected by external forcings (topography and wind) and eddy properties (geostrophy and life stage). Achieving accurate eddy trajectory prediction is expected to provide critical guidance for in-situ eddy observations, and bring substantial improvements for understanding oceanic substance transportations and biogeochemical processes.

Abstract The Surface Water and Ocean Topography (SWOT) mission provides a good opportunity to study fine‐scale processes in the global ocean but whether it can detect balanced submesoscale eddies is uncertain due to the “contamination” by unbalanced inertial gravity waves. Here, based on concurrent observations from SWOT and a mooring array in the northwestern Pacific, we successfully captured two submesoscale cyclonic eddies with negative sea level anomalies (SLAs) in spring 2023. We find that the SLA amplitude and equivalent radius of the first (second) eddy are 2.5 cm and 16.0 km (2.0 cm and 18.8 km), respectively. For both eddies, their vertical scales are around 150 m and their horizontal velocities and Rossby numbers exceed 15.0 cm/s and 0.4, respectively. Further analysis suggests that similar submesoscale eddies can commonly occur in the northwestern Pacific and that SWOT is capable to detect larger submesoscale eddies with scales greater than ∼10 km.

Objective To examine the effects of fish oil supplements on the clinical course of cardiovascular disease, from a healthy state to atrial fibrillation, major adverse cardiovascular events, and subsequently death.Design Prospective cohort study.Setting UK Biobank study, 1 January 2006 to 31 December 2010, with follow-up to 31 March 2021 (median follow-up 11.9 years).Participants 415 737 participants, aged 40-69 years, enrolled in the UK Biobank study.Main outcome measures Incident cases of atrial fibrillation, major adverse cardiovascular events, and death, identified by linkage to hospital inpatient records and death registries. Role of fish oil supplements in different progressive stages of cardiovascular diseases, from healthy status (primary stage), to atrial fibrillation (secondary stage), major adverse cardiovascular events (tertiary stage), and death (end stage).Results Among 415 737 participants free of cardiovascular diseases, 18 367 patients with incident atrial fibrillation, 22 636 with major adverse cardiovascular events, and 22 140 deaths during follow-up were identified. Regular use of fish oil supplements had different roles in the transitions from healthy status to atrial fibrillation, to major adverse cardiovascular events, and then to death. For people without cardiovascular disease, hazard ratios were 1.13 (95% confidence interval 1.10 to 1.17) for the transition from healthy status to atrial fibrillation and 1.05 (1.00 to 1.11) from healthy status to stroke. For participants with a diagnosis of a known cardiovascular disease, regular use of fish oil supplements was beneficial for transitions from atrial fibrillation to major adverse cardiovascular events (hazard ratio 0.92, 0.87 to 0.98), atrial fibrillation to myocardial infarction (0.85, 0.76 to 0.96), and heart failure to death (0.91, 0.84 to 0.99).Conclusions Regular use of fish oil supplements might be a risk factor for atrial fibrillation and stroke among the general population but could be beneficial for progression of cardiovascular disease from atrial fibrillation to major adverse cardiovascular events, and from atrial fibrillation to death. Further studies are needed to determine the precise mechanisms for the development and prognosis of cardiovascular disease events with regular use of fish oil supplements.

Although clinical outcomes in chronic lymphocytic leukemia (CLL) have greatly improved with several approved small molecular inhibitors, acquired resistance does occur, leading to disease progression and eventual death. Thus, the effort to explore novel inhibitors and combination therapeutic regimens is needed. The inhibition of MDM2-p53 interaction to restore p53 function has been regarded as a potential strategy for treating different cancers. We investigated the effects of novel MDM2 inhibitor APG-115 in CLL. We found that APG-115 treatment upregulated the expression of p53, MDM2, and p21 at the mRNA and protein level. APG-115 inhibited cell proliferation, induced apoptosis, and arrested the cell cycle at G0/G1 stage. Moreover, APG-115 inhibited the expression of BCL-2, BCL-xL, and MCL-1, and suppressed the activation of AKT and ERK signaling pathways. APG-115 combined with the BCL2 inhibitor, ABT-199 (venetoclax), led to further inhibition of the expression of BCL-2 family anti-apoptotic proteins and consequently enhanced cell death. Collectively, this study demonstrates that APG-115 activates p53 and thus inhibits multiple pro-survival mechanisms, which provides a rational explanation for APG-115 efficiency in inducing cell apoptosis in CLL. The synergistic effect of APG-115 with ABT-199 suggested a potential combination application in CLL therapy.

Abstract Osteoarthritis (OA) is a degenerative disease that significantly impairs quality of life. There is a pressing need for innovative OA therapies. While small extracellular vesicles (sEVs) show promising therapeutic effects against OA, their limited yield restricts clinical translation. Here, we devised a novel production system for sEVs that enhances both their yield and therapeutic properties. By stimulating mesenchymal stem cells (MSCs) using electromagnetic field (EMF) combined with ultrasmall superparamagnetic iron oxide (USPIO) particles, we procured an augmented yield of EMF-USPIO-sEVs. These vesicles not only activate anabolic pathways but also inhibit catabolic activities, and crucially, they promote M2 macrophage polarization, aiding cartilage regeneration. In an OA mouse model triggered by anterior cruciate ligament transection surgery, EMF-USPIO-sEVs reduced OA severity, and augmented matrix synthesis. Moreover, they decelerated OA progression through the microRNA-99b/MFG-E8/NF-κB signaling axis. Consequently, EMF-USPIO-sEVs present a potential therapeutic option for OA, acting by modulating matrix homeostasis and macrophage polarization.

Ocean eddies have a significant impact on marine ecosystems and the climate because they transport essential substances in the ocean. Detection of ocean eddies has become one of the most active topics in physical ocean research. In recent years, research based on deep learning has mainly focused on regional oceans, with small and specific data and relatively general detection results. This study processes the global eddy by pixel-by-pixel classification and generates a global eddy classification map with a resolution of 720 × 1440, which expands the data volume and improves the generality of the data. Moreover, a high-precision attention residual U$^{2}$-Net model, referred to as ARU$^{2}$-Net, is proposed, which is suitable for mining eddy surface features from sea level anomaly (SLA) and sea surface temperature (SST) data in the global ocean. ARU$^{2}$-Net integrates the convolutional block attention module (CBAM). The channel attention of the CBAM module is used to learn the correlation features between the SST and SLA dual channels; the spatial attention mechanism of the CBAM module is used to learn the importance of the spatial location of the eddy, focusing on the locally important regions, which further improves the detection ability of ARU$^{2}$-Net for eddies, and helps ARU$^{2}$-Net to better identify the eddy categories. Finally, we demonstrate the effectiveness of our approach on the global eddy dataset, achieving a test performance of 94.926%, significantly exceeding previous detection in some areas.

Transition towards carbon-neutral power systems has necessitated optimization of power dispatch in active distribution networks (ADNs) to facilitate integration of distributed renewable generation. Due to unavailability of network topology and line impedance in many distribution networks, physical model-based methods may not be applicable to their operations. To tackle this challenge, some studies have proposed constraint learning, which replicates physical models by training a neural network to evaluate feasibility of a decision (i.e., whether a decision satisfies all critical constraints or not). To ensure accuracy of this trained neural network, training set should contain sufficient feasible and infeasible samples. However, since ADNs are mostly operated in a normal status, only very few historical samples are infeasible. Thus, the historical dataset is highly imbalanced, which poses a significant obstacle to neural network training. To address this issue, we propose an enhanced constraint learning method. First, it leverages constraint learning to train a neural network as surrogate of ADN's model. Then, it introduces Synthetic Minority Oversampling Technique to generate infeasible samples to mitigate imbalance of historical dataset. By incorporating historical and synthetic samples into the training set, we can significantly improve accuracy of neural network. Furthermore, we establish a trust region to constrain and thereafter enhance reliability of the solution. Simulations confirm the benefits of the proposed method in achieving desirable optimality and feasibility while maintaining low computational complexity.

AbstractVischeria punctata, as first described by Vischer in 1945, is a member of the family Chlorobotryaceae, within the order Eustigmatales. This species is recognized for its potential as a source of biofuels and other high-value products. In the present investigation, the whole genome of V. punctata was sequenced utilizing the Illumina HiSeq 4000 platform, enabling the assembly and annotation of its complete mitochondrial genome. The resulting circular genome spans 41,528 base pairs (bp) with a guanine-cytosine (GC) content of 27.3%. This genome encompasses 36 protein-coding genes, alongside 28 transfer RNA (tRNA), and three ribosomal RNA (rRNA) genes. The evolutionary trajectory of V. punctata was further explored by constructing a phylogenetic tree derived from the mitochondrial 33 gene dataset of 16 Ochrophyta species. Comparative analysis reveals that V. punctata bears closer ties to Vischeria sp. CAUP Q202 than to Vischeria stellata strain SAG 33.83, suggesting shared evolutionary pathways and phenotypic traits. This investigation constitutes the inaugural study into the mitochondrial evolution and phylogenetic patterning of the mitogenome in V. punctata. The outcomes from this research bolster our understanding of the genetic diversity and evolutionary processes within the class Eustigmatophyceae. In particular, the mitochondrial genome of V. punctata serves as a valuable resource in elucidating these aspects.

Reconstructing the three-dimensional thermal structure of the ocean under typhoon conditions presents significant challenges due to the scarcity of observational data, particularly in subsurface regions, and the limitations of existing observation methods in terms of spatial and temporal resolution. Accurate reconstruction of these structures is crucial for understanding the energy exchange between the ocean and typhoons, as this exchange directly influences typhoon intensity and trajectory. To address these challenges, this study introduces a fully connected transformer network (FCT), which integrates fully connected layers with a transformer model. The FCT model leverages the attention mechanisms inherent in the transformer architecture to effectively extract and integrate multi-scale ocean dynamical features. Using data from Typhoon Lekima in 2019, this study reconstructs ocean thermal structures at various depths and achieves an RMSE of 1.03 °C and an MAE of 0.83 °C when validated against Argo data. Furthermore, the model’s robustness was demonstrated through five-fold cross-validation, with the validation loss exhibiting minor fluctuations across folds but remaining stable overall, with an average validation loss of 0.986 °C, indicating the model’s generalizability. Sensitivity analysis also revealed the model’s resilience to variations in key input variables, showing minimal impact on output even with perturbations of up to 10% in input data. In addition, the study incorporates content analysis of typhoon-related news reports from 2011 to 2020, revealing a predominance of political topics, which underscores the central role of government in disaster response, with economic and ecological topics following. This integrated approach not only enhances our understanding of the interactions between ocean thermal structures and typhoon dynamics but also provides valuable insights into the societal impacts of typhoons, as reflected in media coverage, contributing to improved disaster management strategies.

Abstract Extracting balanced geostrophic motions (BM) from sea surface height (SSH) observations obtained by wide‐swath altimetry holds great significance in enhancing our understanding of oceanic dynamic processes at submesoscale wavelength. However, SSH observations derived from wide‐swath altimetry are characterized by high spatial resolution while relatively low temporal resolution, thereby posing challenges to extract the BM from a single SSH snapshot. To address this issue, this paper proposes a deep learning model called the BM‐UBM Network, which takes an instantaneous SSH snapshot as input and outputs the projection corresponding to the BM. Training experiments are conducted both in the Gulf Stream and South China Sea, and three metrics are considered to diagnose model's outputs. The favorable results highlight the potential capability of the BM‐UBM Network to process SSH measurements obtained by wide‐swath altimetry.

Tenghuang Jiangu Wan (THJGW) is a commonly utilized treatment for osteoarthritis (OA), yet its pharmacodynamic material basis and molecular mechanism remain inadequately understood. This study systematically characterized the in vitro and in vivo chemical components of THJGW using ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS). The pharmacodynamic material basis of THJGW in the treatment of OA was explored through a target network pharmacology approach and molecular docking technology. Cellular experiments were subsequently employed to validate the molecular mechanisms. Consequently, a total of 134 components from THJGW were identified in vitro, comprising 45 flavonoids, 10 iridoid glycosides, 39 phenylethanoid glycosides, 9 phenylpropanoids, 11 organic acids, 4 phenolics, and 16 other compounds. Additionally, 38 prototype absorbed components in serum were characterized for the purpose of network construction. 11 key components and 10 core targets (VEGFA, STAT3, RELA/NF-κB p65, PIK3R1, PIK3CA, MMP9, MMP1, IL-6, HDAC1, and FGF2) were determined by the target network pharmacology. Through Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, it was found that these intersection targets are associated with various signaling pathways such as pathways in cancer, lipid and atherosclerosis, and prostate cancer. Notably, the lipid and atherosclerosis pathway was closely linked to OA. The molecular docking results demonstrated strong binding affinities of the three core targets: IL-6, STAT3, and RELA/NF-κB p65. These results suggest that these targets may play a significant role for THJGW in treating OA. In vitro experiments showed that THJGW had notable protective effects on LPS-induced RAW264.7 macrophages by reducing levels of TNF-α and IL-6, and inhibiting phosphorylation expression of STAT3 and NF-κB p65 proteins related to the lipid and atherosclerosis pathway. This study provides insight into the pharmacodynamic material basis and mechanism of action for THJGW in the treatment of OA, which provide scientific evidence for the scientific application and improvement of quality standards for THJGW.

Global climate change can significantly affect lake systems. However, our understanding of extreme events in lake water levels on a global scale remains relatively limited. In this study, we conducted a quantitative analysis of extreme water level events in 245 lakes worldwide over the past three decades utilising altimetry satellite-derived water level records. These lakes are broadly categorised as reservoir, endorheic, or permafrost-fed lakes. Moreover, we assessed the spatiotemporal differences in extreme water level events among the different lake types. We then conducted a preliminary analysis of the relationship between extreme events in lake water levels and meteorological variables, as well as large-scale climate oscillations, to understand the driving forces behind their occurrence. Our findings revealed that in the past two decades and under the definition of extreme events employed in this study, the proportion of lakes experiencing extreme water level events annually exhibited a cyclic fluctuation of approximately ten years, rather than the anticipated increase. Moreover, the spatiotemporal distribution of extreme water-level events varied among the different types of lakes. Extreme events in lake water levels were closely related to evaporation and temperature. The implications of this study are potentially profound, and include forecasting lake ecology, understanding the ramifications of climate change, and facilitating sustainable water resource management.

The change of regional hydrodynamic field caused by coal mining process affects the multi-field process of the formation and evolution of mine water quality, which may lead to the pollution of the water environment in the coal mining area. Research on the driving mechanism of the hydrodynamic field and the method of quantitative calculation of key parameters is the premise of quantitative description on the multi-field effects of site pollution in the coal mining areas and its corresponding pollution control. Taking the Menkeqing Coal Mine as the geological background, this paper clarifies the evolution mechanism of the hydrodynamic field of goaf water. According to the difference in the flow path of the hydrodynamic field, it is divided into the stages of water level recovery and filling-up. It reveals the complex process of the formation and evolution of water quality in the goaf, with the hydrodynamic field as the main driving force, and the synergistic effects of multiple fields such as the hydrochemical field and the microbial field. Then the concept model of the water level recovery stage and filling-up stage and the theoretical calculation model of the analytical solution of the key parameters (permeability coefficient, water level, and water volume) of the hydrodynamic field are proposed. The measured data of the similar material simulation test and the three-dimensional box simulation test are compared with the model calculation results. The theoretical calculation of the permeability coefficient and the curve of goaf water level with time and the experimental measurement error are about 13.2% and 22.5%, respectively. The reliability of the theoretical calculation model is verified. Finally, on the basis of the equations of the hydrodynamic field, and the hydrochemical field and the microbial field under the influence of the hydrodynamic field in the goaf, a multi-field coupling effect model dominated by the hydrodynamic field is constructed. The constitutive model provides an inspiration for exploring the formation and evolution of coal mine water quality driven by the coupling of hydrodynamic field. This study supplements and expands the theory of coal mine water pollution prevention and control.

District cooling systems (DCS) can effectively satisfy the cooling demands of multiple buildings. However, since the peak cooling demands usually appear in working hours, DCS may further increase the load peak and off-peak difference in power systems. An ice storage system (ISS) can be combined with DCS to achieve peak-load shaving and reduce the operational cost of DCS. However, finding the optimal operational strategy for DCS with an ISS is challenging since the system involves many complex physical processes that are hard to describe explicitly. To address this issue, this paper proposes a learning-based approach to optimize the operation of the DCS and ISS. Based on historical operational data, the proposed approach first trains multiple neural networks to approximate the complex mappings from decision variables and environment parameters to critical variables. With these trained neural networks, the dynamics of the system can be explicitly described with no need for establishing physical models. Then, the optimization problem can be formulated by using these neural networks to replicate objectives and constraints. A projected gradient descent algorithm is further employed to solve the previous optimization problem. Simulation results based on an actual DCS show that the proposed learning-based method can achieve excellent energy efficiency while maintaining the quality of services.

Reducing fruit and vegetable waste and maintaining quality has become challenging for everyone. Nanotechnology is a new and intriguing technology that is currently being implemented in fruit and vegetable preservation. Silver nanomaterials provide superior antibacterial qualities, biodegradability, and biocompatibility, which expands their potential applications in fruit and vegetable preservation. Silver nanomaterials include silver nanocomposites and Ag-MOF, of which silver nanocomposites are mainly composed of silver nanoparticles. Notably, not all kinds of silver nanoparticles utilized in the preservation of fruits and vegetables are thoroughly described. Therefore, the synthesis, mechanism of action, and advancements in research on silver nanocomposites for fruit and vegetable preservation were discussed in this study.

Many studies have consistently demonstrated that the near-surface phytoplankton chlorophyll (Chl) levels in anticyclonic eddies (AEs) are higher than in cyclonic eddies (CEs) in the South Pacific Ocean (SPO), using remote sensing data, which is attributed to higher phytoplankton biomass or physiological adjustments in AEs. However, the characteristics of the Chl profile induced by mesoscale eddies and their underlying dynamic mechanism have not been comprehensively studied by means of field measurement, and the influence mechanism of environmental factors at different depths on Chl has not been investigated. To fill this gap, we utilized Biogeochemical-Argo (BGC-Argo) data to investigate the relationships between Chl concentration and environmental factors at different water layers and the underlying dynamic mechanisms of mesoscale eddies in the SPO. Our findings indicate that the same environmental factor can have different effects on Chl at different depths. Within a mixed layer (ML), the elevated Chl levels in AEs result from both physiological adjustments and increased phytoplankton biomass, and the former plays a more dominant role, which is induced by enhanced nutrient availability and weakened light, due to the deepening ML in AEs. At depths ranging from 50 m to 110 m, and between 110 m and 150 m (near the depth of pycnocline or the bottom of the euphotic zone), the dominant factor contributing to higher Chl levels in CEs is phytoplankton physiological adaptation driven by reduced temperature and light. At depths exceeding 150 m (beyond the euphotic zone), higher Chl in AEs is primarily caused by high phytoplankton biomass as a result of downwelling by eddy pumping. This work should advance our comprehensive understanding of the physical–biological interactions of mesoscale eddies and their impacts on primary productivity throughout the water column, and it should provide some implications for understanding the biogeochemical processes.

Using dense global navigation satellite system data and brightness temperature data across the New Zealand and Australia regions, we tracked the propagation of traveling ionospheric disturbances (TIDs) associated with the 15 January 2022 Tonga volcanic eruptions. We identified two shock wave-related TIDs and two Lamb wave-related TIDs following the eruptions. The two shock wave-related TIDs, propagating with velocities of 724–750 and 445–471 m/s, respectively, were observed around New Zealand and Australia within a distance of 3500–6500 km from the eruptive center. These shock wave-related TIDs suffered severe attenuation during the propagation and disappeared more than 6500 km from the eruptive center. Based on the TEC data from the nearest ground-based receivers, we estimated the onset times of two main volcanic explosions at 04:20:54 UT ± 116 s and 04:24:37 UT ± 141 s, respectively. The two shock wave-related TIDs were most likely generated by these two main volcanic eruptions. The two Lamb wave-related TIDs propagated with velocities of 300–370 and 250 m/s in the near-field region. The Lamb wave-related TIDs experienced minimal attenuation during their long-distance propagation, with only a 0.17% decrease observed in the relative amplitudes of the Lamb wave-related TIDs from the near-field to far-field regions.

Abstract Furfural content in oil is considered as an effective parameter to evaluate the ageing state of oil‐immersed transformers. In previous thermal ageing experiments at 130°C, we found that moisture increment in oil‐paper system makes more furfural distribute in oil. However, the microcosmic mechanism of moisture effect on furfural diffusion from paper to oil is still unknown, and the furfural equilibrium law at transformers' typical operating temperatures is also unclear, resulting in the unreliability of the existed furfural evaluation model. To elucidate the above problems, molecular dynamics simulation and furfural equilibrium experiments at 60°C were carried out at different moisture contents. The results show that high moisture content makes part of furfural diffuse from paper to oil indeed. Supposing moisture content increases from 1% to 2%, mass fraction of furfural in oil may increase from 32.98% to 49.83%, leading to furfural content in oil increases from 0.76 mg/L to 1.06 mg/L when the degree of polymerisation of insulation paper is about 524, which increased by 39.5%. The increase in moisture content makes cellulose form hydrogen bonds with H2O preferentially, decreasing the hydrogen bonds interaction between cellulose and furfural. Thus, partial furfural falls off cellulose and diffuses into oil, leading to an increase in furfural content in oil. To eliminate the moisture interference, a corrected furfural assessment model based on the moisture equilibrium curve has been constructed, which can accurately evaluate the ageing state of insulation paper regardless of the moisture influence.

Cumin (Cuminum cyminum L). belongs to the family Apiaceae and the order Apiales, which is a widely grown spice and medicinal plant in Xinjiang province, China. In the current study, whole genome sequencing of C. cyminum was performed using the Illumina HiSeq 4000 platform, and the complete mitogenome sequence was assembled and annotated. We found that the single circular mitogenome of C. cyminum was 246,721 bp in length, and has about 45.5% GC content. It comprised 73 genes in the coding region (35 protein-coding genes, 18 tRNA genes, 3 rRNA genes, and 15 open-reading frames) and a non-coding region. Phylogenetic analysis indicated that C. cyminum is closely related to Daucus carota and the subtribes Daucinae. The mitogenome of C. cyminum revealed its phylogenetic relationships with other species in the Apiaceae family, which would further help in understanding its evolution.

Formaldehyde (HCHO) has been identified as one of the most common indoor pollutions nowadays. Manganese oxides (MnOx) are considered to be a promising catalytic material used in indoor HCHO oxidation removal due to their high catalytic activity, low-cost, and environmentally friendly. In this paper, the progress in developing MnOx-based catalysts for HCHO removal is comprehensively reviewed for exploring the mechanisms of catalytic oxidation and catalytic deactivation. The catalytic oxidation mechanisms based on three typical theory models (Mars-van-Krevelen, Eley-Rideal and Langmuir–Hinshelwood) are discussed and summarized. Furthermore, the research status of catalytic deactivation, catalysts’ regeneration and integrated application of MnOx-based catalysts for indoor HCHO removal are detailed in the review. Finally, the technical challenges in developing MnOx-based catalysts for indoor HCHO removal are analyzed and the possible research direction is also proposed for overcoming the challenges toward practical application of such catalysts.

Objective: This study explored the potential association between the Prognostic Nutritional Index (PNI) and the incidence of non-alcoholic fatty liver disease (NAFLD) and advanced liver fibrosis (AF) in the adult population of the United States. Methods: Information on 6409 participants ≥18 years old was downloaded from the U.S. National Health and Nutrition Examination Survey (NHANES) from 2017 to 2020. Multivariate analysis was combined with demographic factors to assess the relationships between PNI, NAFLD, and AF. A restricted cubic spline (RCS) was used to characterise the nonlinear association between the PNI and NAFLD and AF. Results: Patients without NAFLD had substantially lower mean values for parameters such as age, lymphocyte count, neutrophil count, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammatory index (SII), total cholesterol, triglycerides, HbA1c, aspartate aminotransferase (AST), and alanine aminotransferase (ALT) than patients with NAFLD. Interestingly, non-NAFLD patients showed a pronounced increase in serum albumin levels compared to their NAFLD counterparts. In the subset without AF, there were discernibly lower measures of NLR, age, AST, ALT, γ-glutamyl transferase, triglycerides, neutrophil count, and body mass index (BMI) than in patients with AF. It was evident that those without AF had markedly elevated mean albumin and PNI levels in comparison to AF-affected individuals. In the comprehensive multivariable framework, a direct correlation was observed between PNI and NAFLD (adjusted odds ratio[aOR] = 1.07, 95% confidence interval [CI]: 1.05–1.09; p

IntroductionUnderstanding the immune status of an individual using neutralizing antibody testing is complicated by the continued evolution of the SARS-CoV-2 virus. Previous work showed that assays developed against the wildtype strain of SARS-CoV-2 were insufficient predictors of neutralization of omicron variants, thus we developed an omicron-specific flow cytometry-based neutralizing antibody test and performed experiments to assess how well it compared to an omicron-specific PRNT assay (gold standard) and whether it could predict neutralizing activity to more recent omicron subvariants such as XBB.1.5.MethodsAccuracy of a novel flow cytometry-based neutralizing antibody (FC-NAb) assay was determined by comparison with an omicron-specific PRNT assay. A series of samples were evaluated in both the omicron FC-NAb assay and a second test was designed to assess neutralization of XBB.1.5.ResultsGood concordance between the omicron FC-NAb test and the omicron PRNT was demonstrated (AUC = 0.97, p

Background Information about orthopedics diseases on the Internet has not been extensively assessed. Our purpose was to evaluate the quality of online information of osteosarcoma on current video-sharing platforms in mainland China. Method TikTok and Bilibili were independently queried from June to July 2023 by four independent researchers using the Microsoft Edge web browser. Information about the videos and creators was recorded, and descriptive analyses were conducted. Results After data extraction, a total of 95 videos were included, in which 43 videos were uploaded by certified doctors (45.3%), with 35 videos (36.8%) uploaded by certified orthopedic surgeons. Of the content of these videos, 78.9% were introduction ( n = 75), 64.2% were on professional knowledge ( n = 61), 28.4% were on treatment ( n = 27), while 5.3% were on surgical techniques ( n = 5). The mean DISCERN total score was 43.8 ± 13.4, and the mean JAMA score was 3.8 ± 0.3. Conclusions Videos about osteosarcoma on current video-sharing platforms were extensive, but were not comprehensive and professional. Although current online videos have the potential to improve public awareness on osteosarcoma, due to their quality and content, were not assessed to be good sources for medical education.

Purpose To investigate whether mutations in the minichromosome maintenance complex component (MCM) family genes were present in patients with polycystic ovary syndrome (PCOS) of Chinese descent.Methods A total of 365 Chinese patients with PCOS and 860 women without PCOS as control who underwent with assisted reproductive technology were enrolled. Genomic DNA was extracted from the peripheral blood of these patients for PCR and Sanger sequencing. The potential damage of these mutations/rare variants was analyzed through evolutionary conservation analysis and bioinformatic programs.Results Twenty-nine missense or nonsense mutations/rare variants in the MCM genes were identified in 365 patients with PCOS (7.9%, 29/365), all these mutations/rare variants were predicted to be ‘disease causing’ by SIFT and PolyPhen2 programs. Among those, four mutations were reported here for the first time, p.S7C (c.20C > G) in MCM2 (NM_004526.3), p.K350R (c.1049A > G) in MCM5 (NM_006739.3), p.K283N (c.849G > T) in MCM10 (NM_182751.2), and p.S1708F (c.5123C > T) in MCM3AP (NM_003906.4). All of these novel mutations were not found in our 860 control women, or also absent in public databases. In addition, the evolutionary conservation analysis results suggested that these novel mutations caused highly conserved amino acid substitutions among 10 vertebrate species.Conclusion This study identified a high frequency of potential pathogenic rare variants/mutations in MCM family genes in Chinese women with PCOS, which further expands the genotype spectrum in PCOS.

Abstract Background Thyrotropin-secreting adenoma (TSHoma) is the least common type of pituitary adenoma, these patients often present with symptoms of hyperthyroidism. When TSHoma patients combined with autoimmune hypothyroidism, it is critically difficult to diagnose for the specific confusion in the results of thyroid function test. Case presentation One middle-aged male patient was presented with a sellar tumor on cranial MRI for headache symptoms. After hospitalization, a significant increase in thyrotropin (TSH) was revealed by the endocrine tests, while free thyronine (FT3) and free thyroxine (FT4) decreased, and the diffuse destruction of thyroid gland was revealed by thyroid ultrasound. Based on the endocrine test results, the patient was diagnosed as autoimmune hypothyroidism. After the multidisciplinary discussion, the pituitary adenoma was removed by endoscopic transnasal surgery, until the tumor was completely excised, for which TSHoma was revealed by postoperative pathology. A significant decrease of TSH was revealed by the postoperative thyroid function tests, the treatment for autoimmune hypothyroidism was conducted. After 20 months of follow-up, the thyroid function of patient had been improved significantly. Conclusion When the thyroid function test results of patients with TSHoma are difficult to interpret, the possibility of combined primary thyroid disease should be considered. TSHoma combined with autoimmune hypothyroidism is rare, which is difficult to diagnose. The multidisciplinary collaborative treatment could help to improve the outcomes of treatment.

Abstract Background Understanding the effects of risk factor burden and genetic predisposition on the long-term risk of atrial fibrillation (AF) is important to improve public health initiatives. However, the 10-year risk of AF considering risk factor burden and genetic predisposition is unknown. Methods A total of 348,904 genetically unrelated participants without AF at baseline from the UK were categorized into three groups: index ages 45 years (n = 84,206), 55 years (n=117,520), and 65 years (n=147,178). Optimal, borderline, or elevated risk factor burden was determined by body mass index, blood pressure, diabetes mellitus, alcohol consumption, smoking status, and history of myocardial infarction or heart failure. Genetic predisposition was estimated using the polygenic risk score (PRS), constructed using 165 predefined genetic risk variants. The combined effects of risk factor burden and PRS on the risk of incident AF in 10 years were estimated for each index age. Fine and Gray models were developed to predict the 10-year risk of AF. Results The overall 10-year risk of AF was 0.67% (95% CI: 0.61–0.73%) for index age 45 years, 2.05% (95% CI: 1.96–2.13%) for index age 55 years, and 6.34% (95% CI: 6.21–6.46%) for index age 65 years, respectively. An optimal risk factor burden was associated with later AF onset regardless of genetic predisposition and sex (P < 0.001). Significant synergistic interactions were observed for risk factor burden with PRS at each index age (P < 0.05). Participants with an elevated risk factor burden and high PRS had the highest 10-year risk of AF in reference to those who had both an optimal risk factor burden and a low PRS. At younger ages, optimal risk burden and high PRS might also lead to later onset of AF, compared to the joint effect of elevated risk burden and low/intermediate PRS. Conclusions Risk factor burden together with a genetic predisposition is associated with the 10-year risk of AF. Our results may be helpful in selecting high-risk individuals for primary prevention of AF and facilitating subsequent health interventions.

To reduce platinum usage, ultrathin MXene sheets with little restacking effect were prepared. The ultrathin MXene was prepared by a two-step etching process, which showed high specific surface area with low charge transfer resistance. The sample showed a double layer capacity of 64.98 mF cm−2, which is 14 times as large as that of ordinary HF prepared MXene, indicating a larger electrochemically active surface area. It showed a much better HER performance of ∼190 mV at 10 mA cm−2. The better performance attributes to 0.4 wt% Pt loaded. The Pt loaded MXene exhibited a better HER performance of ∼75 mV at 10 mA cm−2 and a Tafel slope of 61.7 mV·dec−1 close to 40 wt% commercial Pt/C. The sample performed better than Pt/C in a 3 h chronopotentiometry test and hardly changed in ECSA after the cyclic experiment. With more Pt loading, the sample delivered better HER performance than Pt/C in the LSV test (∼51 mV at 10 mA cm−2). This work provides an effective route for the preparation of ultrathin MXene sheets with larger electrochemically active area and more active sites for Pt loading, leading to superior HER performance.

Background: With rapid development in agriculture and industry, water polluted with heavy metallic ions has come to be a serious problem. Adsorption-based methods are simple, efficient, and broadly used to eliminate heavy metals. Conventional adsorption materials have the problems of secondary environmental contamination. Hydrogels are considered effective adsorbents, and those prepared from biopolymers are biocompatible, biodegradable, non-toxic, safe to handle, and increasingly used to adsorb heavy metal ions. Aim of review: The natural origin and easy degradability of biopolymer hydrogels make them potential for development in environmental remediation. Its water absorption capacity enables it to efficiently adsorb various pollutants in the aqueous environment, and its internal pore channels increase the specific surface area for adsorption, which can provide abundant active binding sites for heavy metal ions through chemical modification. Key scientific concept of review: As the most representative of biopolymer hydrogels, polysaccharide-based hydrogels are diverse, physically and chemically stable, and can undergo complex chemical modifications to enhance their performance, thus exhibiting superior ability to remove contaminants. This review summarizes the preparation methods of hydrogels, followed by a discussion of the main categories and applications of polysaccharide-based biopolymer hydrogels.

A subsurface chlorophyll maximum is an important ecological feature of planktonic ecosystems. Although the vertical profiles can be determined through the implementation of biogeochemical (BGC)-Argo buoy, this method is not compatible with the ocean observation requirements of high-resolution spatiotemporal measurements. Here, we demonstrate that deep learning can proficiently fill in these observational gaps when combined with sea surface data from ocean color radiometry. First, the sparse vertical profile data of BGC-Argo is fused with sea surface data to construct the benchmark dataset for deep learning. Second, encouraged by the idea of dense numerical representations, the comprehensive model combined with coupled embedding and bidirectional gated recurrent unit is proposed to inverse the vertical profile with BGC-Argo and satellite data. Then, the in-depth spatiotemporal analysis of the subsurface chlorophyll maxima phenomenon is performed by the parametric equation method and deep learning method as well. Finally, extensive experiments in the Northwest Pacific were conducted to demonstrate the effectiveness of the proposed methodology. The impressive results indicate that the proposed method can compensate for the lack of sparse in situ observations of chlorophyll concentration, the determination coefficient is increased by more than 20%. This study is of great significance to marine ecology and provides important insight into artificial intelligence in the study of subsurface oceanic phenomena.

Wild fish recognition is a fundamental problem of ocean ecology research and contributes to the understanding of biodiversity. Given the huge number of wild fish species and unrecognized category, the essence of the problem is an open set fine-grained recognition. Moreover, the unrestricted marine environment makes the problem even more challenging. Deep learning has been demonstrated as a powerful paradigm in image classification tasks. In this article, the wild fish recognition deep neural network (termed WildFishNet) is proposed. Specifically, an open set fine-grained recognition neural network with a fused activation pattern is constructed to implement wild fish recognition. First, three different reciprocal inverted residual structural modules are combined by neural structure search to obtain the best feature extraction performance for fine-grained recognition; next, a new fusion activation pattern of softmax and openmax functions is designed to improve the recognition ability of open set. Then, the experiments are implemented on the WildFish dataset that consists of 54 459 unconstrained images, which includes 685 known classes and 1 open set unrecognized category. Finally, the experimental results are analyzed comprehensively to demonstrate the effectiveness of the proposed method. The in-depth study also shows that artificial intelligence can empower marine ecosystem research.

Abstract Background Total removal of the vestibular schwannoma when preserving the function of the facial nerve is difficult. The objective of the current study was to investigate the short-term clinical outcome of vestibular schwannoma removal via retro-sigmoid approach. Methods One-hundred consecutive patients diagnosed with vestibular schwannoma were surgically treated between December 2018 and August 2019 in Xuanwu Hospital, Capital Medical University. The clinical classification, surgical position, gross total removal rate, the anatomical and functional preservation rates of facial nerve, and the postoperative complications were retrospectively analyzed. Results All 100 patients including 34 males and 66 females were operated on via retro-sigmoid approach. According to Koos vestibular schwannoma grading system, 18 cases were grade 2, 34 cases were grade 3, and 48 cases were grade 4. According to Hannover vestibular schwannoma grading system, 5 cases were T2, 6 cases were T3a, 8 cases were T3b, 30 cases were T4a, and 51 cases were T4b. Seventy-three surgeries were performed under lateral position, and 27 cases were operated under semi-sitting position. The gross total removal rate was 90.0%; the anatomic reservation rate of the facial nerve was 96.0%. According to the House-Brackman system, the facial nerve function was grades 1–2 in 78.0% cases, grade 3 in 7.0% cases, and grades 4–5 in 15% cases. For patients with effective hearing before operation, the hearing reservation rate was 19.0%. Two patients (2.0%) developed intracranial hematoma after operation. Conclusion Most vestibular schwannoma could be completely removed with good postoperative facial nerve function. If total removal of tumor is difficult, we should give priority to the functional preservation of the nerve function.

Abstract Mixed insulation oil is considered as a desired substitute for traditional mineral oil. A novel 3‐element mixed insulation oil has been developed in our previous works, whose parameters satisfy the mineral oil standard (IEC 60296:2012). In the application of transformer oil, dissolved gas analysis is an effective method for insulation fault diagnosis. Thermal fault is a common and typical fault in transformers; however, the pyrolysis process and gas production characteristics of mixed insulation oil under thermal fault remain unknown. In this study, the pyrolysis process and gas production characteristics of 3‐element mixed insulation oil have been studied through simulation and experiments, and mineral oil is equally treated for comparison. Results show that the gas production characteristics of mixed oil are closely related to its base oils, and 3‐element mixed insulation oil generates more H2 and C2H6 under thermal fault, in which the percentage of H2 in the mixed oil is always three times that in the mineral oil. More CO2 is produced in mixed oil under thermal fault because of ester bonds; C2H4 is also a main characteristic gas for mixed insulation oil under thermal fault, and its proportion increases continuously with the increase of temperature. For mineral oil, the weight loss temperature in thermo‐gravimetric (TG) curve corresponds to evaporation rather than decomposition. Natural esters have poor thermal stability according to simulation results, but they possess high flash point and weight loss temperature in the TG curve primarily because of their large average molecular weight.

Abstract Background Polycystic ovary syndrome (PCOS) is a complex reproductive disorder, that affects approximately 5–10% of women of reproductive age. The disease is complex because its evolution may be impacted by genetic, lifestyle and environmental factors. Previous studies have emphasized the important roles of estrogen receptors in the pathogenesis of PCOS. Objective To use whole exome sequencing (WES) to assess possible pathogenic factors in a PCOS patient who exhibited estrogen insensitivity during hormone replacement therapy (HRT) treatment. Methods Genome sequencing and variant filtering via WES were performed in a patient with PCOS. DNA extraction from 364 unrelated female controls without PCOS was followed by PCR amplification, Sanger sequencing and sequence alignment. Evolutionary conservation analysis, protein structural modelling and in silico prediction were applied to analyse the potential pathogenicity of the novel ESR1 mutation. Result(s) During the controlled ovarian hyperstimulation (COH) period of an IVF cycle, the patient experienced markedly prolonged ovarian stimulation due to a poor response to gonadotropins (Gn) and elevated serum FSH. A novel heterozygous ESR1 mutation, c.619G > A/p.A207T, leading to the replacement of a highly conserved alanine with a threonine, was identified in this patient, via WES analysis. This novel variant was not identified in 364 unrelated female controls without PCOS, or in the Exome Aggregation Consortium (ExAC) or 1000 Genome Project. Conclusion(s) We identified a novel heterozygous ESR1 mutation in a Han Chinese PCOS woman exhibiting clinical signs of estrogen insensitivity. This study may provide new strategies for IVF therapy, especially for patients who exhibit estrogen insensitivity during IVF cycle.

ObjectivePostoperative epistaxis is a very rare but severe complication after endoscopic endonasal transsphenoidal surgery (EETS) that can lead to catastrophic consequences. However, the incidence, risk factors, management and prevention of postoperative epistaxis remain unclear.Patients and methodsConsecutive patients with pituitary adenoma (PA), Rathke's cleft cyst, craniopharyngioma, or clival chordoma who received EETS in our department between September 2020 and November 2022 were retrospectively analyzed. The incidence, risk factors, management and prevention of postoperative epistaxis were investigated and analyzed.ResultsA total of 557 consecutive patients who received EETS were included in this study. Eight patients (1.4%) (7 PAs and 1 Rathke's cleft cyst) experienced severe postoperative epistaxis. The size of the PAs was 9.6 mm–46.2 mm, with a median size of 22.1 mm. Epistaxis occurred 4 h to 30 days (median 14.5 days) postoperatively. Bleeding was stopped in 3 patients after nasal packing with iodoform gauze. The remaining 5 patients for whom nasal packing was insufficient were all sent to the operating room, and posterior nasal septal artery (PNSA) bleeding was identified and successfully treated with endoscopic bleeding artery electrocauterization under general anesthesia. In the EETS, all 8 patients had downward extension of the septal mucosal incision, in which 6 had intraoperative bleeding of PNSA that were cauterized by bipolar diathermy. Four patients had causative factors, including administration of antiplatelet agents, Valsalva-like manoeuvre, nose blowing and removal of nasal packing, respectively. No patients had recurrent epistaxis during the follow-up period.ConclusionPost-EETS epistaxis is a rare but severe complication that could lead to catastrophic consequences, and one of the most common bleeding sources is the PNSA. Endoscopic bleeding artery electrocauterization under general anesthesia may be a safe, economic and effective measure for epistaxis refractory to nasal packing. Avoiding excessive downward extension of the septal mucosal incision could contribute to the prevention of postoperative epistaxis.

Abstract Objective This study aimed to explore the correlation between T1 and T2 relaxation times of synthetic MRI (SyMRI) and gestational age (GA) in each hemisphere of preterm and term newborns at the initial 28 days of birth. Methods Seventy preterm and full‐term infants were prospectively included in this study. All subjects completed 3.0 T routine MRI and SyMRI (MAGiC) one‐stop scanning within 28 days of birth (aged 34–42 W at examination). The SyMRI postprocessing software (v8.0.4) was used to measure the T1 and T2 relaxation values of each brain region. The linear regression equations of quantitative relaxation values with GA were established to compare the variation speed in each brain region. Results A significant linear and negative correlation was found between relaxation times and GA in the neonate cerebral cortex and subcortical gray and white matter regions (All p

In the Southwestern Atlantic, the Falkland Current intrudes onto the South American shelf, resulting in the meeting of two water masses which are completely different in temperature and dynamic characteristics, thus generating the Southwestern Atlantic Front (SAF). Therefore, the SAF has prominent characteristics of thermal and dynamics. The current ocean front detection is mainly by performing gradient operations on sea surface temperature (SST) data, where regions with large temperature gradients are considered as ocean fronts. The thermal gradient method largely ignores the dynamical features, leading to inaccurate manifestation of SAF. This study develops a deep learning model, SAFNet, to detect the SAF through the synergy of 10-year (2010-2019) satellite-derived SST and sea surface height (SSH) observations to achieve high accuracy detection of SAF with fused thermal and dynamic characteristics. The comparative experimental results show that the detection accuracy of SAFNet reaches 99.45%, which is significantly better than other models. By comparing the frontal probability (FP) obtained by SST, SSH and SST-SSH fusion data respectively, it is proved that the necessity of fusion multi-source remote sensing data for SAF detection. The detection results of fusion data can reflect the spatial distribution of SAF more comprehensively and accurately. According to the meridional variation of FP, the main reason for the seasonal variation of the SAF is the change in its thermal characteristics, and the SAF has stable dynamic characteristics.

The influence of mesoscale eddies on chlorophyll (Chl) has received significant attention due to Chl being a proxy for phytoplankton, which plays a crucial role in marine ecosystems. Solely relying on the analysis of satellite-observed Chl poses challenges in determining the phytoplankton response to mesoscale eddies. To address this, our study takes a collaborative approach, utilizing satellite-derived sea surface temperature anomalies (SSTA) and chlorophyll anomalies (CHLA) to comprehensively investigate the dynamical-biological processes associated with eddies in the subtropical and mid-latitude North Atlantic. In the subtropics, the patterns in CHLA and SSTA predominantly exhibit a dipole nature, with the dipole component providing more than 70% of the explained variance (EV). This suggests that eddy stirring is the dominant mechanism driving the observed anomaly patterns. Conversely, in the mid-latitudes, the monopole components ( T _M ) explain more than 60% of the EV, implying a more influential role for eddy trapping and vertical modulations. The signs of the T _M of eddy SSTA persist throughout their lifetime, being consistent with the lowering (raising) of isopycnals within AEs (CEs). However, the subtropical CHLA response is higher in AEs than CEs, indicating additional factors, such as eddy-induced Ekman pumping and/or mixing to a deeper level may be important. This finding is also corroborated by subsurface observations from Argo floats. At mid-latitudes, there is a clear inverse correspondence between the CHLA and mixed layer depth. In contrast, no significant correlation is observed in the subtropics, except during winter when a positive relationship emerges. These patterns suggest that phytoplankton exhibit highly diverse responses to the physical dynamics associated with eddies. Our work offers a method to estimate eddy dynamical-biological impacts on phytoplankton using satellite products, compensating for the limitations of in-situ observations. It also reveals potential contributions to marine primary production, global carbon cycles, and the development of biogeochemical models.

Fast radio bursts (FRBs) are a powerful and mysterious new class of transients that are luminous enough to be detected at cosmological distances. By associating FRBs to host galaxies, we can measure intrinsic and environmental properties that test FRB origin models, in addition to using them as precise probes of distant cosmic gas. The Deep Synoptic Array (DSA-110) is a radio interferometer built to maximize the rate at which it can simultaneously detect and localize FRBs. Here, we present the first sample of FRBs and host galaxies discovered by the DSA-110. This sample of 11 FRBs is the largest, most uniform sample of localized FRBs to date, as it is selected based on association with host galaxies identified in optical imaging by Pan-STARRS1. These FRBs have not been observed to repeat, and their radio properties (dispersion, temporal scattering, energy) are similar to that of the known nonrepeating FRB population. Most host galaxies have ongoing star formation, as has been identified before for FRB hosts. Two hosts of the new sample are massive, quiescent galaxies. The distribution of star formation history across this host-galaxy sample shows that the delay time distribution is wide, with a power-law model that spans from ∼100 Myr to ≳2 Gyr. This requires the existence of one or more progenitor formation channels associated with old stellar populations, such as the binary evolution of compact objects.

We report on a full-polarization analysis of the first 25 as yet nonrepeating fast radio bursts (FRBs) detected at 1.4 GHz by the 110-antenna Deep Synoptic Array (DSA-110) during commissioning observations. We present details of the data-reduction, calibration, and analysis procedures developed for this novel instrument. Faraday rotation measures (RMs) are searched between ±10 ^6 rad m ^−2 and detected for 20 FRBs, with magnitudes ranging from 4 to 4670 rad m ^−2 . Fifteen out of 25 FRBs are consistent with 100% polarization, 10 of which have high (≥70%) linear-polarization fractions and two of which have high (≥30%) circular-polarization fractions. Our results disfavor multipath RM scattering as a dominant depolarization mechanism. Polarization-state and possible RM variations are observed in the four FRBs with multiple subcomponents. We combine the DSA-110 sample with polarimetry of previously published FRBs, and compare the polarization properties of FRB subpopulations and FRBs with Galactic pulsars. Although FRB polarization fractions are typically higher than those of Galactic pulsars, and cover a wider range than those of pulsar single pulses, they resemble those of the youngest (characteristic ages

Nanosized Pd-based catalysts are widely used in the direct hydrogen peroxide (H2O2) synthesis from H2 and O2, while the selectivity and yield of H2O2 remain inferior. Here, a remarkable H2O2 yield of 115 mol/gPd/h and H2O2 selectivity higher than 99% are reported using a Pd single-atom catalyst for the direct synthesis of H2O2.

Abstract Rheumatoid arthritis (RA) is a chronic and inflammatory autoimmune disease. Macrophage pyroptosis, a proinflammatory form of cell death, is critically important in RA; however, the detailed mechanism underlying pyroptosis induction is not yet well understood. Here, we report that DNA polymerase β (Pol β), a key enzyme in base excision repair, plays a pivotal role in RA pathogenesis. Our data shows that Pol β expression is significantly decreased in peripheral blood mononuclear cells (PBMCs) from active RA patients and collagen-induced arthritis (CIA) mice, and Pol β deficiency increases the incidence of RA, macrophage infiltration, and bone destruction in CIA mouse models. In vitro, experiments showed that Pol β deficiency exacerbated macrophage pyroptosis induced by LPS plus ATP, while overexpression of Pol β inhibited macrophage pyroptosis. Further characterization revealed that Pol β knockout resulted in DNA damage accumulation and cytosolic dsDNA leakage, which activated the cGAS-STING-NF-κB signaling pathway and upregulated the expression of NLRP3, IL-1 β, and IL-18. In conclusion, our findings clarify the influence of Pol β on the development of RA and provide a detailed explanation for the STING-NF-κB pathway to induce macrophage pyroptosis.

Abstract Background There is an ongoing discussion about the advantages and disadvantages of different surgical positions (semi-sitting and lateral position) for vestibular schwannoma surgery. Each position has its advantages, disadvantages, challenges, and risk profiles. The objectives of this study are to compare the effects of different surgical positions (semi-sitting and lateral position) on the outcomes of large vestibular schwannoma, primarily including effectiveness and safety. Methods In this single-centre, open, randomized controlled trial, we will recruit a total of 116 participants according to the inclusion and exclusion criteria who will be randomized to an experimental group or control group. Patients will undergo operations in semi-sitting and lateral positions. The primary endpoint will be the percentage of gross total resection. The secondary endpoints will include the facial nerve function, hearing preservation, surgical position placement time, time of operation (skin-to-skin surgical time), hospital stay, total hospitalization fee, and complications. The follow-up period will be at least 12 months, during which time patients will be evaluated both clinically and radiologically. Discussion This issue is still debated after 30 years since the first large comparative study was published in 1989, so the study will be useful. Therefore, more high-quality studies are required to compare clinical outcomes, complications, and other factors associated with these two positions. Trial registration Chinese Clinical Trial Registry ChiCTR1900027550 . Registered on 17 November 2019