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Atmospheric organic aerosols consist of both gas-phase organic compounds and particle-phase organic compounds. The components of aerosol particles (solid or liquid droplets) can undergo exchange or chemical reactions with gas-phase components, influencing atmospheric physical and chemical processes and potentially impacting atmospheric environment, climate, and human health. Methods for detecting organic compounds in aerosol particle phase are classified into offline and online detection. Offline detection methods involve collecting aerosol samples for analysis using chromatography-mass spectrometry, which is time-consuming and limited sensitivity. Online detection methods involve enriching aerosols through aerodynamic lens and then detecting them using laser ablation or electron impact ionization techniques. However, these methods usually generate a large number of ion fragments, making mass spectrum analysis difficult. Therefore, it is necessary to develop an online detection method for aerosol particle-phase organic compounds with soft ionization and high sampling efficiency. In the present work, a set of aerodynamic lens sampling systems was designed and developed for online detection and analysis of organic compounds in aerosol particle phase. This sampling system consists of a gas-phase stripping module for removing gas-phase organic compounds, an aerodynamic lens module for particle focusing and enrichment, and a thermal desorption module for extracting particle-phase organic compounds. The efficiency of gas-phase organic compound removal and the particle transmission rate of the gas-phase stripping module were firstly investigated. The results showed that gas-phase stripping module achieves a removal efficiency of 98.89% for gas-phase organic compounds, and the particle transmission rate ranges from 75.16% to 91.15% for particles with the diameters between 295 and 375 nm. Subsequently, the effectiveness of the aerodynamic lens was studied through theoretical simulations. The simulation results indicated that the transmission rate of particles in the diameters of 0.36-6.0 μm is above 90% in the designed aerodynamic lens. Finally, The designed aerodynamic lens sampling system with a homemade proton transfer reaction mass spectrometer (PTR-MS) was integrated to develop an aerodynamic lens-PTR-MS device. This device was tested by detecting simulated aerosol samples containing reaction products of α-pinene and ozone. The mass spectrometry results demonstrated that the intensity changes of the examined ten ions are closely related to the presence of α-pinene, confirming that the device can achieve online detection of organic compounds in aerosols ranging from submicron to several micrometers.

Abstract Non-alcoholic fatty liver disease is associated with an irregular serine metabolism. Serine hydroxymethyltransferase 2 (SHMT2) is a liver enzyme that breaks down serine into glycine and one-carbon (1C) units critical for liver methylation reactions and overall health. However, the contribution of SHMT2 to hepatic 1C homeostasis and biological functions has yet to be defined in genetically modified animal models. We created a mouse strain with targeted SHMT2 knockout in hepatocytes to investigate this. The absence of SHMT2 increased serine and glycine levels in circulation, decreased liver methylation potential, and increased susceptibility to fatty liver disease. Interestingly, SHMT2-deficient mice developed simultaneous fatty liver, but when fed a diet high in fat, fructose, and cholesterol, they had significantly less inflammation and fibrosis. This study highlights the critical role of SHMT2 in maintaining hepatic 1C homeostasis and its stage-specific functions in the pathogenesis of NAFLD.

Tibetan script possesses a distinctive artistic form of writing, intricate glyph structures, and diverse stylistic variations. In the task of text recognition, effectively handling the recognition of Tibetan script with significantly different stylistic fonts remains a challenge. Existing research has made considerable progress in recognizing Tibetan script within a single style using techniques such as convolutional neural networks and convolutional recurrent neural networks. However, when dealing with multi-style Tibetan script recognition, the standard approach involves training models using a multi-label joint training method. This approach annotates the style and class of different font style samples and merges them into a single dataset for model training. Nevertheless, as the amount of data and performance requirements increase, this approach gradually faces issues such as decreasing accuracy, insufficient generalization capability, and poor adaptability to new style samples. In this paper, we propose a transfer learning-based method for incremental recognition of multi-style Tibetan script, referred to as “multi-style Tibetan script incremental recognition.” In the style recognition stage, we employ a convolutional neural network (CNN) to accurately differentiate between style categories. During the pre-training stage, we train a residual network on the Tibetan Uchen standard style and utilize it as the baseline model. In the multi-style Tibetan script recognition stage, we integrate transfer learning into the model training process to reduce the training time. These three stages collectively accomplish the task of multi-style Tibetan script incremental recognition. The experimental results demonstrate that our approach achieves a significant improvement in overall recognition accuracy, from 90.14% to 98.40%, when utilizing the TCDB and HUTD datasets compared to traditional multi- task recognition methods. This method exhibits high accuracy, strong generalization capability, and good adaptability to new style samples in multi-style Tibetan script character recognition. Furthermore, it can be applied to other tasks involving multi-style, multi-font, and multi-script recognition.

Few-shot classification aims to classify unseen classes (query instances) with few labeled samples from each class (support instances). However, current few-shot learning methods assume that the training and testing sets obey the same distribution. When there exists a huge domain gap between the training and testing sets, they fail to generalize well across domains. In this work, we tackle the cross-domain few-shot learning (CD-FSL) problem in Tibetan characters from two perspectives. In the meta-training phase, we seamlessly introduce contrastive learning into the episodic training paradigm and apply a data augmentation strategy to seek better feature representations thereby improving the ability to recognize unseen categories. In the meta-finetuning phase, we then integrate the above algorithm into transfer learning and propose a fine-tuning method that generates episodic synthetic query sets to enhance generalization capability across domains. These two stages force the model to overcome the domain shift between training and testing sets. Extensive experiments show that our simple approach allows us to establish competitive results on the well-known few-shot learning dataset Omniglot and state-of-the-art results on our Tibetan character datasets. The code will be publicly available in this repository: https://github.com/coder-bossin/fs-TCR.

Abstract The Vajrasana pagoda is the only stone overturned-bowl pagoda among the 12 existing Vajrasana pagodas built during the Ming Dynasty in the Guandu District, Kunming City, Yunnan Province, China. The location of the Vajrasana pagoda is in an earthquake-active zone with high rainfall. The small towers on the upper side were damaged by an earthquake in 1696 AD. All the stone statues representing religious figures have blistered and may peel further due to external factors, such as sunshine and rainfall. To assess the structural stability of the blistering, we employed 3D laser scanning to record the building’s geometry over time. Subsequently, X-ray diffraction, thin section identification, and uniaxial compressive strength tests were conducted on the pagoda stone to reveal physical–mechanical properties. Finally, a finite element model was constructed to analyze stress and displacement in various scenarios. The results revealed: (1) Blistering on the pagoda stone is secure under self-gravity and heavy rainfall. (2) In an earthquake, the upper blistering near the junction of two sides may break. (3) A 3D color deviation model of blistering over 8 months showed peeling and bursting within the finite element simulation's predicted range. This research offers a fresh approach to stone tower preservation, shifting from reactive measures to proactive prevention and prediction. These methods and concepts hold relevance for stone towers in similar high-rainfall and earthquake-prone regions.

Abstract Many degradation processes of cultural heritage objects are associated with unsuitable microclimatic conditions. One of the most ubiquitous deteriorations is the crystallization of salts in pores, which can accelerate the erosion rate of masonry historical relics. In this study, the microclimate of the burial tomb and exfoliation of sandstone in the Yongling Mausoleum of the Former Shu Dynasty in Chengdu were monitored for 1 year to determine the development of the degradation. We established a connection between the monitoring data and exfoliation variations of the stone with time. To predict the deterioration of the stone, a three-dimensional computational finite element model was used to simulate the detailed process of the thermo-hygrometric performance that led to salt crystallization and artwork deterioration. Two results were obtained. In the simulation of the microclimate, the temperature ranged from 15 to 22.6 °C, and the relative humidity was heterogeneous and varied between 60 and 100%. The other was the relationship between the microclimate and exfoliation. It was found that the exfoliation was more severe in the higher relative humidity areas where the water vapor frequently interacted with the relics. The crystallization and hydration of sulfate produced stress, which damaged the stone relics. These results provide a rationale analysis and a reference for better management of the environmental interactions and reduction of the environmental impacts in the subsequent scientific conservation of ancient Chinese cultural relics in tombs.

Abstract Age-related macular degeneration (AMD), a progressive chronic disease of the central retina, is a leading cause of blindness worldwide. Activated macrophages recruited to the injured eyes greatly contribute to the pathogenesis of choroidal neovascularization (CNV) in exudative AMD (wet AMD). This study describes the effects of cyclooxygenase-2 (COX2)/prostaglandin E2 (PGE2) signalling on the macrophage activation and CNV formation of wet AMD. In a mouse model of laser-induced wet AMD, the mice received an intravitreal injection of celecoxib (a selective COX2 inhibitor). Optical coherence tomography (OCT), fundus fluorescein angiography (FFA), choroidal histology of the CNV lesions, and biochemical markers were assessed. The level of PGE2 expression was high in the laser-induced CNV lesions. Macrophage recruitment and CNV development were significantly less after celecoxib treatment. E-prostanoid1 receptor (EP1R)/protein kinase C (PKC) signalling was involved in M2 macrophage activation and interleukin-10 (IL-10) production of bone marrow-derived macrophages (BMDMs) in vitro. In addition, IL-10 was found to induce the proliferation and migration of human choroidal microvascular endothelial cells (HCECs). Thus, the PGE2/EP1R signalling network serves as a potential therapeutic target for CNV of the wet-type AMD. Graphical Abstract Video abstract

Abstract This study determined absolute transporter protein abundances in isolated microvessels of human noncancerous cerebral cortex as well as brain metastases of patients with lung and breast cancer, using a validated targeted proteomics approach. As compared with those in microvessels of noncancerous cerebral cortex, the median protein abundances of glucose transporter 1 (a brain endothelial marker) and sodium‐potassium pump (Na/K ATPase, a plasma membrane marker) were decreased by ~ 80% in brain metastasis microvessels. The major efflux transporters (ABCB1 and ABCG2) fell to undetectable in microvessels of more than 80% of brain metastasis specimens. Monocarboxylate transporter 1 was undetectable in microvessels of more than 80% of brain metastases, whereas large neutral amino acid transporter 1 levels remained unchanged. In conclusion, the integrity of the physical and biochemical barrier with respect to transporter protein expression is largely disrupted in brain metastasis tumor vasculatures. Differential transporter protein abundances at the blood‐brain barrier and blood‐brain tumor barrier provided mechanistic and quantitative basis for prediction of heterogeneous drug penetration into human brain and brain tumors, which is critical not only to the understanding of the success or failure of systemic chemotherapy in the treatment of brain tumors but also to the development of more effective therapeutic strategies.

The resurrection of landslides often occurs in complex strata, where there are often multiple water-resisting zones and weak interlayers. The groundwater level has a significant influence on landslide stability and can lead to the formation of composite landslides and increase the probability of landslide resurrection. In a field investigation of the K39 +400 composite landslide of Wenma Expressway, the deformation characteristics of the landslide surface were obtained by analyzing 34 cracks on the landslide surface. The deep deformation characteristics of the landslide were analyzed by studying the deformation data obtained from deep borehole monitoring. The deformation zone characteristics of landslides were assessed by integrating surface and deep deformation data in the landslide area. The resurrections of shallow landslides in Area I and deep landslides in Area III were due mainly to the long-term high underground water level in the landslide. The stability of the landslide was calculated under various depths of drainage tunnel, and the results showed that the slope was in critical condition when the depth of the drainage tunnel was 15 m; the slope was basically stable when the depth of the drainage tunnel was 20 m and 25 m. When the depth of the drainage tunnel reached more than 30 m, the slope was in a stable state. Groundwater level was found to be the main factor affecting landslide deformation. This case study shows the importance of zoning the deformation characteristics of composite landslides, and the important influence of the groundwater level on landslide resurrection.

The reservoir water level in the Three Gorges Reservoir (TGR) of the Yangtze River is adjusted between 145 m and 175 m throughout the year. The landslide below the reservoir water level bears periodic dynamic seepage pressure on the basis of the original steady-state water pressure. In the process of rising reservoir water levels in particular, the effective stress on the sliding zone soil below the reservoir water level line is reduced, and the sliding zone soil shows an unloading state. In order to study the creep characteristics of landslides in a reservoir area, direct shear creep tests of the sliding zone soil in the Huangtupo landslide in an unloading state were carried out in this study. The test results show that the creep characteristics of the sliding zone soil are obvious. The creep curve of the sliding zone soil presents an attenuation creep stage with low shear stress, which is mainly manifested as an elastic creep. However, with the increase in the shear stress, the creep curve of the sliding zone soil presents a steady creep stage, which is mainly manifested as viscoelastic creep. The nonlinear creep characteristics of the sliding zone soil are related to the creep time, stress level, and soil porosity. The longer the creep time, the greater the stress level and the denser the soil, the more obvious the nonlinear creep characteristics of the sliding zone soil. In this study, the Burgers model was used to fit the creep curve of the sliding zone soil, and the fitting effect was good, which indicates that the Burgers model can sufficiently describe the unloading state creep characteristics of the sliding zone soil in the Huangtupo landslide.

A rapid, sensitive, and robust reversed-phase liquid chromatography with tandem mass spectrometry method was developed and validated for the determination of total and unbound ceritinib, a second-generation ALK inhibitor, in patient plasma and brain tumor tissue samples. Sample preparation involved simple protein precipitation with acetonitrile. Chromatographic separation was achieved on a Waters ACQUITY UPLC BEH C18 column using a 4-min gradient elution consisting of mobile phase A (0.1% formic acid in water) and mobile phase B (0.1% formic acid in acetonitrile), at a flow rate of 0.4 mL/min. Ceritinib and the internal standard ([13C6]ceritinib) were monitored using multiple reaction monitoring mode under positive electrospray ionization. The lower limit of quantitation (LLOQ) was 1 nM of ceritinib in plasma. The calibration curve was linear over ceritinib concentration range of 1–2000 nM in plasma. The intra- and inter-day precision and accuracy were within the generally accepted criteria for bioanalytical method (