Background Air pollution exposure has a significant impact on maternal and child health. However, the research on the association between ambient ozone (O₃) exposure during pregnancy and the risk of premature birth in newborns is limited, and the conclusions are inconsistent. Objective To investigate the association of ambient O₃ exposure during pregnancy with the risk of preterm birth in Guangdong Province. Methods Data of pregnant women in Guangzhou from 2013 to 2019 and Foshan from 2018 to 2023 were collected, and O₃ concentrations during different trimesters were assessed according to maternal residential addresses. Bilinear interpolation was used to evaluate the concentrations of air pollution. A cohort study design was adopted in our study. Restricted cubic spline curves were used to evaluate the exposure-response relationship between O₃ exposure and preterm birth risk and explore potential exposure threshold of O₃. Logistic regression models were used to evaluate the association of O₃ exposure with preterm birth. Results A total of 702 924 pregnant women were included in this study, of whom 43 051 (6.12%) were preterm. The average O₃ exposure concentrations of pregnant women during the first, second, third, and whole trimesters were 95.51, 97.51, 100.60, and 97.87 μg·m⁻³, respectively. We observed J-shaped associations between O₃ exposure and preterm birth risk during the second, third, and whole trimesters of pregnancy using restricted cubic spline curves. This study found that there were threshold concentrations between O₃ exposure and preterm birth risk during different gestational periods, and the threshold concentrations in the first, second, third, and whole trimesters were 112.32, 99.83, 111.74, and 112.46 μg·m⁻³, respectively. During the second, third, and whole trimesters of pregnancy, after adjusting for maternal age, baby sex, pre-pregnancy body mass index, mode of delivery, baby birth weight, gestational diabetes, and gestational hypertension, the odds ratios (OR) of preterm birth were 1.02 (95%CI: 1.01, 1.04), 1.02 (95%CI: 1.00, 1.03), and 1.17 (95%CI: 1.13, 1.21) for each 10 μg·m⁻³ increase in O₃ concentration above the O₃ threshold. No significant association was found between O₃ exposure and the risk of preterm birth during the first trimester. Conclusion There is a nonlinear association between the risk of preterm birth and O₃ exposure during pregnancy, and higher concentrations of O₃ exposure during pregnancy are associated with the risk of preterm birth. Above the O₃ threshold concentration during pregnancy, especially during the second, third, and whole trimesters, the risk of preterm birth elevates with the increase of O₃ exposure concentrations.

Linxian County in Henan Province, Northern China is known as the region with the highest incidence and mortality rate of esophageal cancer worldwide. Since 1959, the Henan medical team has conducted field work on esophageal cancer prevention and treatment in Linxian. Through three generations of effort exerted by oncologists over 65 years of research on esophageal cancer prevention and treatment in Linxian, the incidence rate of esophageal squamous cell carcinoma in this area has dropped by nearly 50%, and the 5-year survival rate has increased to 40%, reaching the international leading level. This article aims to summarize the history, present opportunities and new challenges, and explore the experience of esophageal cancer prevention and treatment in Linxian (referred to as the “Linxian experience”), providing reference and guidance to cancer prevention and treatment research in China.

ObjectiveThe rapid advancement of bioanalytical technologies has heightened the demand for high-throughput, label-free, and real-time cellular analysis. Electrochemical impedance spectroscopy (EIS) operating in the GHz frequency range (GHz-EIS) has emerged as a promising tool for characterizing cell suspensions due to its ability to rapidly and non-invasively capture the dielectric properties of cells and their microenvironment. Although GHz-EIS enables rapid and label-free detection of cell suspensions, significant challenges remain in interpreting GHz impedance data for complex samples, limiting the broader application of this technique in cellular research. To address these challenges, this study presents a novel method that integrates GHz-EIS with deep learning algorithms, aiming to improve the precision of cell suspension concentration identification and quantification. This method provides a more efficient and accurate solution for the analysis of GHz impedance data. MethodsThe proposed method comprises two key components: dielectric property dataset construction and backpropagation (BP) neural network modeling. Yeast cell suspensions at varying concentrations were prepared and separately introduced into a coaxial sensor for impedance measurement. The dielectric properties of these suspensions were extracted using a GHz-EIS dielectric property extraction method applied to the measured impedance data. A dielectric properties dataset incorporating concentration labels was subsequently established and divided into training and testing subsets. A BP neural network model employing specific activation functions (ReLU and Leaky ReLU) was then designed. The model was trained and tested using the constructed dataset, and optimal model parameters were obtained through this process. This BP neural network enables automated extraction and analytical processing of dielectric properties, facilitating precise recognition of cell suspension concentrations through data-driven training. ResultsThrough comparative analysis with conventional centrifugal methods, the recognized concentration values of cell suspensions showed high consistency, with relative errors consistently below 5%. Notably, high-concentration samples exhibited even smaller deviations, further validating the precision and reliability of the proposed methodology. To benchmark the recognition performance against different algorithms, two typical approaches—support vector machines (SVM) and K-nearest neighbor (KNN)—were selected for comparison. The proposed method demonstrated superior performance in quantifying cell concentrations. Specifically, the BP neural network achieved a mean absolute percentage error (MAPE) of 2.06% and an R² value of 0.997 across the entire concentration range, demonstrating both high predictive accuracy and excellent model fit. ConclusionThis study demonstrates that the proposed method enables accurate and rapid determination of unknown sample concentrations. By combining GHz-EIS with BP neural network algorithms, efficient identification of cell concentrations is achieved, laying the foundation for the development of a convenient online cell analysis platform and showing significant application prospects. Compared to typical recognition approaches, the proposed method exhibits superior capabilities in recognizing cell suspension concentrations. Furthermore, this methodology not only accelerates research in cell biology and precision medicine but also paves the way for future EIS biosensors capable of intelligent, adaptive analysis in dynamic biological research.

To summarize Professor WANG Jianmin's experience in cathartic colon from "keeping sweet to return liquid". It is believed that the key to the pathogenesis of cathartic colon is fluid consumption and intestinal dryness， including yin depletion of spleen earth， and lack of sources for body fluids production； discordance of water and fire in kidneys， and irregular distribution of body fluids； and closure of the lungs and liver leads to inability of the flow of fluids. The treatment is based on the principle of "keeping sweet to return liquid"， using sweet medicinals mainly， assistant with sour， bland and acrid medicinals， and self-prescribed Lipi Shengjin Decoction （理脾生津汤）， Wenshen Runchang Decoction （温肾润肠汤）， Kaifei Shunchang Decoction （开肺顺肠汤）， Rougan Tongbian Decoction （柔肝通便汤） could be used to regulate spleen yin by the sweet and bland， and establish qi and promote fluid production； the sweet and warm medicinals can replenish water and fire， transform into qi， and distribute body fluids； the acrid and sweet can open lung depression， descend qi， and flow the body fluids； the sour and sweet can emolliate liver， move qi， and transform fluids.

Background/Aims: Liver cirrhosis involves chronic inflammation and progressive fibrosis.Among various immune cells, CD8+ T cells are considered a major contributor to hepatic inflammation and fibrosis. However, the exact molecular pathways governing CD8+ T-cell-mediated effects in cirrhosis remain unclear. Methods: This study analyzed transcriptomic and single-cell sequencing data to elucidate CD8+ T-cell heterogeneity and implications in cirrhosis. Results: Weighted gene co-expression analysis of bulk RNA-seq data revealed an association between cirrhosis severity and activated T-cell markers like HLA and chemokine genes. Furthermore, single-cell profiling uncovered eight CD8+ T-cell subtypes, notably, effector memory (Tem) and exhausted (Tex) T cells. Tex cells, defined by PDCD1, LAG3, and CXCL13 expression, were increased in cirrhosis, while Tem cells were decreased. Lineage tracing and differential analysis highlighted CXCL13+ Tex cells as a terminal, exhausted subtype of cells with roles in PD-1 signaling, glycolysis, and T-cell regulation. CXCL13+ Tex cells displayed T-cell exhaustion markers like PDCD1, HAVCR2, TIGIT, and TNFRSF9. Functional analysis implicated potential roles of these cells in immunosuppression. Finally, a CXCL13+ Tex-cell gene signature was found that correlated with cirrhosis severity and poorer prognosis of liver cancer. Conclusions In summary, this comprehensive study defines specialized CD8+ T-cell subpopulations in cirrhosis, with CXCL13+ Tex cells displaying an exhausted phenotype associated with immune dysregulation and advanced disease. Key genes and pathways regulating these cells present potential therapeutic targets.

Background/Aims: Liver cirrhosis involves chronic inflammation and progressive fibrosis.Among various immune cells, CD8+ T cells are considered a major contributor to hepatic inflammation and fibrosis. However, the exact molecular pathways governing CD8+ T-cell-mediated effects in cirrhosis remain unclear. Methods: This study analyzed transcriptomic and single-cell sequencing data to elucidate CD8+ T-cell heterogeneity and implications in cirrhosis. Results: Weighted gene co-expression analysis of bulk RNA-seq data revealed an association between cirrhosis severity and activated T-cell markers like HLA and chemokine genes. Furthermore, single-cell profiling uncovered eight CD8+ T-cell subtypes, notably, effector memory (Tem) and exhausted (Tex) T cells. Tex cells, defined by PDCD1, LAG3, and CXCL13 expression, were increased in cirrhosis, while Tem cells were decreased. Lineage tracing and differential analysis highlighted CXCL13+ Tex cells as a terminal, exhausted subtype of cells with roles in PD-1 signaling, glycolysis, and T-cell regulation. CXCL13+ Tex cells displayed T-cell exhaustion markers like PDCD1, HAVCR2, TIGIT, and TNFRSF9. Functional analysis implicated potential roles of these cells in immunosuppression. Finally, a CXCL13+ Tex-cell gene signature was found that correlated with cirrhosis severity and poorer prognosis of liver cancer. Conclusions In summary, this comprehensive study defines specialized CD8+ T-cell subpopulations in cirrhosis, with CXCL13+ Tex cells displaying an exhausted phenotype associated with immune dysregulation and advanced disease. Key genes and pathways regulating these cells present potential therapeutic targets.

Background/Aims: Liver cirrhosis involves chronic inflammation and progressive fibrosis.Among various immune cells, CD8+ T cells are considered a major contributor to hepatic inflammation and fibrosis. However, the exact molecular pathways governing CD8+ T-cell-mediated effects in cirrhosis remain unclear. Methods: This study analyzed transcriptomic and single-cell sequencing data to elucidate CD8+ T-cell heterogeneity and implications in cirrhosis. Results: Weighted gene co-expression analysis of bulk RNA-seq data revealed an association between cirrhosis severity and activated T-cell markers like HLA and chemokine genes. Furthermore, single-cell profiling uncovered eight CD8+ T-cell subtypes, notably, effector memory (Tem) and exhausted (Tex) T cells. Tex cells, defined by PDCD1, LAG3, and CXCL13 expression, were increased in cirrhosis, while Tem cells were decreased. Lineage tracing and differential analysis highlighted CXCL13+ Tex cells as a terminal, exhausted subtype of cells with roles in PD-1 signaling, glycolysis, and T-cell regulation. CXCL13+ Tex cells displayed T-cell exhaustion markers like PDCD1, HAVCR2, TIGIT, and TNFRSF9. Functional analysis implicated potential roles of these cells in immunosuppression. Finally, a CXCL13+ Tex-cell gene signature was found that correlated with cirrhosis severity and poorer prognosis of liver cancer. Conclusions In summary, this comprehensive study defines specialized CD8+ T-cell subpopulations in cirrhosis, with CXCL13+ Tex cells displaying an exhausted phenotype associated with immune dysregulation and advanced disease. Key genes and pathways regulating these cells present potential therapeutic targets.