Unique immunohistochemical profiles of MUC5AC, MUC6, P53, and Ki67 in gastric atypical hyperplasia and dysplasia.

OBJECTIVES: Differentiating gastric atypical hyperplasia (AH) from dysplasia, including low-grade dysplasia (LGD) and high-grade dysplasia (HGD), poses significant challenges in small biopsies and specimens with technical artifacts. This study aims to establish objective diagnostic criteria for these conditions through combined morphologic and immunohistochemical (IHC) analyses. METHODS: Between January 2018 and September 2020, a total of 123 gastric mucosa biopsy specimens were collected at Anyang Tumor Hospital. According to the WHO Classification of Digestive System Tumors (5th edition), specimens were categorized into three groups: AH (n=48), LGD (n=30), and HGD (n=45). Morphologic characteristics were assessed, and IHC staining for MUC5AC, MUC6, MUC2, CD10, P53, and Ki67 was performed, followed by statistical analysis. RESULTS: Histologically, AH was predominantly marked by a pronounced inflammatory background (60.42%), intestinal metaplasia (64.58%), indistinct boundaries (83.33%), and a distinct maturation gradient (97.72%). AH nuclei were typically circular (97.92%), with a high nucleus-to-cytoplasm ratio (64.58%), prominent nucleoli (47.92%), and preserved polarity (89.58%). In contrast, LGD and HGD typically exhibited well-defined boundaries with an absent maturation gradient. LGD nuclei were rod-shaped (96.67%), with a low nucleus-to-cytoplasm ratio (96.67%) and preserved polarity (100%), whereas HGD demonstrated a loss of cellular polarity (77.78%). IHC findings revealed a consistent maturation gradient in AH, with polarized MUC5AC and MUC6 expression, significantly reduced in LGD (86.67%), and absent in HGD. P53 expression in HGD showed a predominant 'mutation-type pattern' (66.67%), contrasting with 'wild-type pattern' expression in AH and LGD (100%, 93.33%). Ki67 expression patterns varied from a 'pit neck pattern' in AH (95.83%) to a 'polarity pattern' in LGD (76.67%) and a 'diffuse pattern' in HGD (57.78%). The expression patterns of MUC5AC, MUC6, CD10, P53, and Ki67 varied significantly across the three groups (P<0.001). CONCLUSIONS: The integration of histomorphological features and expression profiles of MUC5AC, MUC6, P53, and Ki67 is instrumental in diagnosing gastric atypical hyperplasia and dysplasia.

What Factors Dominate the Change of PM2.5 in the World from 2000 to 2019? A Study from Multi-Source Data.

As the threat to human life and health from fine particulate matter (PM2.5) increases globally, the life and health problems caused by environmental pollution are also of increasing concern. Understanding past trends in PM2.5 and exploring the drivers of PM2.5 are important tools for addressing the life-threatening health problems caused by PM2.5. In this study, we calculated the change in annual average global PM2.5 concentrations from 2000 to 2020 using the Theil-Sen median trend analysis method and reveal spatial and temporal trends in PM2.5 concentrations over twenty-one years. The qualitative and quantitative effects of different drivers on PM2.5 concentrations in 2020 were explored from natural and socioeconomic perspectives using a multi-scale geographically weighted regression model. The results show that there is significant spatial heterogeneity in trends in PM2.5 concentration, with significant decreases in PM2.5 concentrations mainly in developed regions, such as the United States, Canada, Japan and the European Union countries, and conversely, significant increases in PM2.5 in developing regions, such as Africa, the Middle East and India. In addition, in regions with more advanced science and technology and urban management, PM2.5 concentrations are more evenly influenced by various factors, with a more negative influence. In contrast, regions at the rapid development stage usually continue their economic development at the cost of the environment, and under a high intensity of human activity. Increased temperature is known as the most important factor for the increase in PM2.5 concentration, while an increase in NDVI can play an important role in the reduction in PM2.5 concentration. This suggests that countries can achieve good air quality goals by setting a reasonable development path.

A one-dimensional convolutional neural network based deep learning for high accuracy classification of transformation stages in esophageal squamous cell carcinoma tissue using micro-FTIR.

Among the most frequently diagnosed cancers in developing countries, esophageal squamous cell carcinoma (ESCC) ranks among the top six causes of death. It would be beneficial if a rapid, accurate, and automatic ESCC diagnostic method could be developed to reduce the workload of pathologists and improve the effectiveness of cancer treatments. Using micro-FTIR spectroscopy, this study classified the transformation stages of ESCC tissues. Based on 6,352 raw micro-FTIR spectra, a one-dimensional convolutional neural network (1D-CNN) model was constructed to classify-five stages. Based on the established model, more than 93% accuracy was achieved at each stage, and the accuracy of identifying proliferation, low grade neoplasia, and ESCC cancer groups was achieved 99% for the test dataset. In this proof-of-concept study, the developed method can be applied to other diseases in order to promote the use of FTIR spectroscopy in cancer pathology.

Assessment of NO2 population exposure from 2005 to 2020 in China.

Nitrogen dioxide (NO2) is a major air pollutant with serious environmental and human health impacts. A random forest model was developed to estimate ground-level NO2 concentrations in China at a monthly time scale based on ground-level observed NO2 concentrations, tropospheric NO2 column concentration data from the Ozone Monitoring Instrument (OMI), and meteorological covariates (the MAE, RMSE, and R2 of the model were 4.16 µg/m3, 5.79 µg/m3, and 0.79, respectively, and the MAE, RMSE, and R2 of the cross-validation were 4.3 µg/m3, 5.82 µg/m3, and 0.77, respectively). On this basis, this article analyzed the spatial and temporal variation in NO2 population exposure in China from 2005 to 2020, which effectively filled the gap in the long-term NO2 population exposure assessment in China. NO2 population exposure over China has significant spatial aggregation, with high values mainly distributed in large urban clusters in the north, east, south, and provincial capitals in the west. The NO2 population exposure in China shows a continuous increasing trend before 2012 and a continuous decreasing trend after 2012. The change in NO2 population exposure in western and southern cities is more influenced by population density compared to northern cities. NO2 pollution in China has substantially improved from 2013 to 2020, but Urumqi, Lanzhou, and Chengdu still maintain high NO2 population exposure. In these cities, the Environmental Protection Agency (EPA) could reduce NO2 population exposure through more monitoring instruments and limiting factory emissions.

A long short-term memory-fully connected (LSTM-FC) neural network for predicting the incidence of bronchopneumonia in children.

Bronchopneumonia is the most common infectious disease in children, and it seriously endangers children's health. In this paper, a deep neural network combining long short-term memory (LSTM) layers and fully connected layers was proposed to predict the prevalence of bronchopneumonia in children in Chengdu based on environmental factors and previous prevalence rates. The mean square error (MSE), mean absolute error (MAE), and Pearson correlation coefficient (R) were used to detect the performance of the deep learning model. The values of MSE, MAE, and R in the test dataset are 0.0051, 0.053, and 0.846, respectively. The results show that the proposed model can accurately predict the prevalence of bronchopneumonia in children. We also compared the proposed model with three other models, namely, a fully connected (FC) layer neural network, a random forest model, and a support vector machine. The results show that the proposed model achieves better performance than the three other models by capturing time series and mitigating the lag effect.

Mg storage properties of hollow copper selenide nanocubes.

Rechargeable Mg batteries are thought to be suitable for scalable energy-storage applications because of their high safety and low cost. However, the bivalent Mg2+ cations suffer from sluggish solid-state diffusion kinetics. Herein, a hollow morphological approach is introduced to design copper selenide cathodes for rechargeable Mg batteries. Hollow Cu2-xSe nanocubes are fabricated via a solution reaction and their Mg-storage properties are investigated in comparison to simple nanoparticles. The hollow structures accommodate the volume change during magnesiation/demagnesiation and maintain material integrity, and thus a remarkable cycling stability of over 200 cycles is achieved. A kinetic study demonstrates that a hollow structure favors solid-phase Mg2+ diffusion, and therefore the hollow Cu2-xSe nanocubes exhibit a high capacity of 250 mA h g-1 at 100 mA g-1 as well as a superior rate capability. Mechanism investigation indicates that Cu2-xSe experiences a structure conversion during which a phase transformation occurs. This work develops a facile method for the preparation of hollow copper selenides and highlights the advantages of hollow structures in the design of high-performance Mg-storage materials.

CoSe2 hollow microspheres, nano-polyhedra and nanorods as pseudocapacitive Mg-storage materials with fast solid-state Mg2+ diffusion kinetics.

CoSe2 materials with different nanostructures are used as pseudocapacitive Mg-storage cathodes, which exhibit fast solid-state Mg2+ ions diffusion kinetics. In this work, CoSe2 with different nanostructures including hollow microspheres (H-CoSe2), nano-polyhedra (P-CoSe2) and nanorods (R-CoSe2) are fabricated by using facile one-step hydrothermal methods, and used as pseudocapacitive electrodes for rechargeable Mg batteries. It is observed that R-CoSe2 exhibits the highest reversible capacity of 233 mA h g-1 at 50 mA g-1 and an excellent rate capability of 116 mA h g-1 at 500 mA g-1, ascribing to the 1D nanorod structure which facilitates the solid-state Mg2+ diffusion. Benefitting from the stable hierarchical structure, H-CoSe2 exhibits a superior long-term cycling stability of 350 cycles. A mechanism study indicates that the redox reaction reversibly occurs between CoSe2 and metallic Co0. Further investigation demonstrates that the fast solid-state Mg2+ diffusion kinetics and surface-controlled pseudocapacitive behavior enhance the electrochemical performance. This work highlights a novel and efficient Mg-storage strategy of using pseudocapacitive materials, and the performance and solid-state Mg2+ diffusion kinetics of CoSe2 could be optimized by rational structural tailoring.

Facile synthesis and electrochemical Mg-storage performance of Sb2Se3 nanowires and Bi2Se3 nanosheets.

Rechargeable Mg batteries are considered as low-cost and reliable candidates for efficient energy storage, but their development is blocked by the lack of suitable cathode materials. In this work, Sb2Se3 nanowires and Bi2Se3 nanosheets are fabricated by facile one-step hydrothermal methods and their Mg-storage performances are systematically investigated. The results show that the Bi2Se3 nanosheets with stable hierarchical 2D structure exhibit a better performance. Because of its thin nanosheet structure, Bi2Se3 provides a high Mg-storage capacity of 144 mA h g-1 and a remarkable rate capability with 65 mA h g-1 delivered at 1000 mA g-1. Bi2Se3 also exhibits an outstanding cyclability over 350 cycles owing to its hierarchical structure. Furthermore, this study reveals that the electrochemical charge/discharge cycling is a typical conversion reaction occurring between Bi3+ and metallic Bi0. Kinetic investigation suggests that the high performance of Bi2Se3 is attributed to both its intrinsic nature and its thin nanosheet structure facilitating solid-state Mg2+ diffusion. The present work highlights the selection principle of conversion cathodes for rechargeable Mg batteries, namely matching a soft anion with a quasi-soft metal cation. Moreover, the facile synthesis approach is also used for low-dimensional main-group VI metal chalcogenides to improve the Mg-storage performance.

Rechargeable Mg batteries based on a Ag2S conversion cathode with fast solid-state Mg2+ diffusion kinetics.

Rechargeable Mg batteries are promising candidates for highly safe, large-scale energy storage batteries due to the low-cost and non-dendritic metallic Mg anode. However, exploring high-performance cathodes remains a great challenge blocking their development. Herein, a rechargeable Mg battery is established with a Ag2S conversion cathode, providing a highly reversible capacity of 120 mA h g-1 at 50 mA g-1, a superior rate capability of 70 mA h g-1 at 500 mA g-1, and an outstanding long-term cyclability over 400 cycles. The mechanism was investigated using XRD, TEM and XPS in addition to electrochemical measurements, and indicated a two-stage magnesiation: first, Mg2+ intercalation into Ag2S and then a conversion reaction to form metallic Ag0 and MgS. The solid-state Mg2+ diffusion coefficients are as high as 3.6 × 10-9 and 3.1 × 10-10 cm2 s-1 for the intercalation and conversion reactions, respectively, which explains the high performance of the Ag2S cathode. This work provides scientific insights for the selection of a promising conversion cathode by the combination of soft anions and soft transition metal cations.

Rechargeable Mg-M (M = Li, Na and K) dual-metal-ion batteries based on a Berlin green cathode and a metallic Mg anode.

Mg-M (M = Li, Na and K) dual-metal-ion batteries featuring a dendrite-free Mg anode and an alkali-metal-ion storage cathode are promising safe energy storage systems. However, the compatibility between cathode materials and insertion cations might largely limit the electrochemical performance of the cathodes. In this work, three types of Mg-M (M = Li, Na and K) dual-metal-ion batteries are constructed with a Berlin green (FeFe(CN)6) cathode. The FeFe(CN)6 cathode is compatible with the dual-salt Mg2+/M+ (M = Li, Na and K) electrolytes, and delivers a high reversible capacity of 120 mA h g-1 at 50 mA g-1, with no capacity fading over 50 cycles in Mg-Na batteries. The Mg-Na battery also shows an outstanding rate capability, providing 85 mA h g-1 at 1000 mA g-1 and superior long-term cyclability over 800 cycles. The electrochemical performance comparison between Mg-Li, Mg-Na and Mg-K dual-metal-ion batteries demonstrates the significance of the appropriate hydrated ionic radius and dehydrated ionic radius for the insertion of cations with the FeFe(CN)6 cathode. This work provides new design strategies for stable and high energy density cathodes, and opens a new avenue for building safe and high-performance Mg-M (M = Li, Na and K) dual-metal-ion batteries for practical applications.

a-MoS3@CNT nanowire cathode for rechargeable Mg batteries: a pseudocapacitive approach for efficient Mg-storage.

Rechargeable Mg batteries are promising candidates for highly safe large-scale energy storage batteries owing to their low-cost and non-dendritic metallic Mg anode. However, exploration of high-performance cathodes remains a great challenge hindering their development. Herein, a new pseudocapacitive Mg-storage nanowire material (a-MoS3@CNT) is constructed with a carbon nanotube (CNT) core and an amorphous MoS3 (a-MoS3) outer layer (15 nm thick). The nanowire cathode exhibits a high reversible capacity of 175 mA h g-1 at 100 mA g-1, a good rate performance of 50 mA h g-1 at 1000 mA g-1, and an outstanding long-term cyclability over 500 cycles. Further investigation of the mechanism demonstrates that the Mg-storage of a-MoS3@CNT is mainly achieved by the pseudocapacitance of a-MoS3, in which Mg2+ ions show fast solid-state diffusion kinetics. The present results demonstrate a new approach for efficient Mg-storage using pseudocapacitive materials, and the performance and solid-state Mg2+ diffusion kinetics could be optimized by delicate morphology tailoring.