AIM: To evaluate the surgical outcomes and changes in the ocular surface microenvironment following radiofrequency minimally invasive treatment for conjunctivochalasis-induced epiphora.METHODS: Patients with epiphora primarily caused by conjunctivochalasis were enrolled. All patients had conjunctivochalasis of ≥grade II, and their symptoms showed no significant improvement after previous pharmacological treatment. All patients underwent radiofrequency minimally invasive correction of conjunctivochalasis, supplemented with artificial tears, anti-inflammatory therapy, and ocular surface repair treatment postoperatively. At 8 wk post-surgery, the ocular surface disease index(OSDI), eye redness, tear secretion, non-invasive tear break-up time, lipid layer thickness, tear ferning test, and conjunctival impression cytology were assessed to compare treatment efficacy and observe changes in the ocular surface microenvironment.RESULTS: A total of 43 cases(43 eyes)of conjunctivochalasis and with a main complaint of epiphora were included, including 23 males and 20 males, with a mean age of 64.69±3.36 years. The total effective rate of surgery was 91% at 8 wk postoperatively. Compared with preoperative values, the OSDI scores significantly decreased and the non-invasive tear break-up time was prolonged at 8 wk post-surgery(all P<0.05). No statistically significant differences were observed in lipid layer thickness or tear secretion at 8 wk postoperatively(all P>0.05). The normal rate of chloramphenicol taste test increased from 21% preoperatively to 63% postoperatively; the normal rate of eye redness increased from 40% to 70%; normal rate of tear ferning grading improved from 30% to 63%; and normal conjunctival impression cytology grading increased from 21% to 74%.CONCLUSION: Radiofrequency minimally invasive treatment is effective for conjunctivochalasis and is straightforward to perform. Patients with conjunctivochalasis often present with other ocular surface issues beyond conjunctivochalasis itself, such as insufficient tear secretion, reduced lipid layer thickness, and other dry eye-related problems. Therefore, a comprehensive approach emphasizing tear dynamics should be adopted during treatment.

The auxin/indole-3-acetic acid (Aux/IAA) gene family is an important regulator for plant growth hormone signaling, involved in plant growth, development, as well as response to environmental stresses. In the present study, we identified SmIAA7 which is potentially associated with Salvia miltiorrhiza leaf development through comparatively analyzed the transcriptome data from different pinnate leaves. SmIAA7 was successfully isolated from S. miltiorrhiza using the specific primers. Then subsequent bioinformatic analysis, prokaryotic expression and purification, subcellular localization, and induction expression analysis under auxin and abiotic stress were performed. The full-length of SmIAA7 contained an ORF of 684 bp encoding a protein of 227 amino acid with a molecular weight of 25.3 kD. Conserved domain analysis showed that SmIAA7 contains the conserved Aux_IAA domain (pfam02309). Sequence analysis and phylogenetic tree analysis results indicated SmIAA7 was phylogenetically close to IAA7 and IAA14 from other plants, suggesting SmIAA7 involved in plant growth and development as well as response to environmental stresses. The prokaryotic expression vector pET28a-SmIAA7 was constructed and SmIAA7 recombinant protein was successfully expressed in E. coli Rosetta (DE3) strain. Subcellular localization experiment demonstrated that SmIAA7 localized in the nucleus of plant cells. Real-time fluorescence quantitative PCR results showed that the expression level of SmIAA7 was upregulated in response to auxin. Drought, low temperature, and salt stress significantly increased the transcript level of SmIAA7 gene. This study lays a foundation for further elucidating the role of SmIAA7 in leaf development, signal transduction, and stress defense in S. miltiorrhiza.

Background/Aims: Dexamethasone (DEX) is a widely used exogenous therapeutic glucocorticoid in clinical settings. Its long-term use leads to many side effects. However, its effect on metabolic disorders in individuals on a high-fat diet (HFD) remains poorly understood. Methods: In this study, HFD-fed mice were intraperitoneally injected with DEX 2.5 mg/kg/day for 30 days. Lipid metabolism, adipocyte proliferation, and inflammation were assayed using typical approaches. Results: DEX increased the epididymal fat index and epididymal adipocyte size in HFD-fed mice. The number of epididymal adipocytes with diameters > 70 μm accounted for 0.5% of the cells in the control group, 30% of the cells in the DEX group, 19% of the cells in the HFD group, and 38% of all the cells in the D+H group. Adipocyte proliferation in the D+H group was inhibited by DEX treatment. Adipocyte enlargement in the D+H group was associated with increased the lipid accumulation but not the adipocyte proliferation. In contrast, the liver triglyceride and total cholesterol levels and their metabolism were downregulated by the same treatment, indicating the therapeutic potential of DEX for nonalcoholic fatty liver disease. Conclusions DEX synergizes with HFD to promote lipid deposition in adipose tissues. A high risk of obesity development in patients receiving HFD and DEX treatment is suggested.

Background/Aims: Dexamethasone (DEX) is a widely used exogenous therapeutic glucocorticoid in clinical settings. Its long-term use leads to many side effects. However, its effect on metabolic disorders in individuals on a high-fat diet (HFD) remains poorly understood. Methods: In this study, HFD-fed mice were intraperitoneally injected with DEX 2.5 mg/kg/day for 30 days. Lipid metabolism, adipocyte proliferation, and inflammation were assayed using typical approaches. Results: DEX increased the epididymal fat index and epididymal adipocyte size in HFD-fed mice. The number of epididymal adipocytes with diameters > 70 μm accounted for 0.5% of the cells in the control group, 30% of the cells in the DEX group, 19% of the cells in the HFD group, and 38% of all the cells in the D+H group. Adipocyte proliferation in the D+H group was inhibited by DEX treatment. Adipocyte enlargement in the D+H group was associated with increased the lipid accumulation but not the adipocyte proliferation. In contrast, the liver triglyceride and total cholesterol levels and their metabolism were downregulated by the same treatment, indicating the therapeutic potential of DEX for nonalcoholic fatty liver disease. Conclusions DEX synergizes with HFD to promote lipid deposition in adipose tissues. A high risk of obesity development in patients receiving HFD and DEX treatment is suggested.

Background/Aims: Dexamethasone (DEX) is a widely used exogenous therapeutic glucocorticoid in clinical settings. Its long-term use leads to many side effects. However, its effect on metabolic disorders in individuals on a high-fat diet (HFD) remains poorly understood. Methods: In this study, HFD-fed mice were intraperitoneally injected with DEX 2.5 mg/kg/day for 30 days. Lipid metabolism, adipocyte proliferation, and inflammation were assayed using typical approaches. Results: DEX increased the epididymal fat index and epididymal adipocyte size in HFD-fed mice. The number of epididymal adipocytes with diameters > 70 μm accounted for 0.5% of the cells in the control group, 30% of the cells in the DEX group, 19% of the cells in the HFD group, and 38% of all the cells in the D+H group. Adipocyte proliferation in the D+H group was inhibited by DEX treatment. Adipocyte enlargement in the D+H group was associated with increased the lipid accumulation but not the adipocyte proliferation. In contrast, the liver triglyceride and total cholesterol levels and their metabolism were downregulated by the same treatment, indicating the therapeutic potential of DEX for nonalcoholic fatty liver disease. Conclusions DEX synergizes with HFD to promote lipid deposition in adipose tissues. A high risk of obesity development in patients receiving HFD and DEX treatment is suggested.

Background/Aims: Dexamethasone (DEX) is a widely used exogenous therapeutic glucocorticoid in clinical settings. Its long-term use leads to many side effects. However, its effect on metabolic disorders in individuals on a high-fat diet (HFD) remains poorly understood. Methods: In this study, HFD-fed mice were intraperitoneally injected with DEX 2.5 mg/kg/day for 30 days. Lipid metabolism, adipocyte proliferation, and inflammation were assayed using typical approaches. Results: DEX increased the epididymal fat index and epididymal adipocyte size in HFD-fed mice. The number of epididymal adipocytes with diameters > 70 μm accounted for 0.5% of the cells in the control group, 30% of the cells in the DEX group, 19% of the cells in the HFD group, and 38% of all the cells in the D+H group. Adipocyte proliferation in the D+H group was inhibited by DEX treatment. Adipocyte enlargement in the D+H group was associated with increased the lipid accumulation but not the adipocyte proliferation. In contrast, the liver triglyceride and total cholesterol levels and their metabolism were downregulated by the same treatment, indicating the therapeutic potential of DEX for nonalcoholic fatty liver disease. Conclusions DEX synergizes with HFD to promote lipid deposition in adipose tissues. A high risk of obesity development in patients receiving HFD and DEX treatment is suggested.

Background/Aims: Dexamethasone (DEX) is a widely used exogenous therapeutic glucocorticoid in clinical settings. Its long-term use leads to many side effects. However, its effect on metabolic disorders in individuals on a high-fat diet (HFD) remains poorly understood. Methods: In this study, HFD-fed mice were intraperitoneally injected with DEX 2.5 mg/kg/day for 30 days. Lipid metabolism, adipocyte proliferation, and inflammation were assayed using typical approaches. Results: DEX increased the epididymal fat index and epididymal adipocyte size in HFD-fed mice. The number of epididymal adipocytes with diameters > 70 μm accounted for 0.5% of the cells in the control group, 30% of the cells in the DEX group, 19% of the cells in the HFD group, and 38% of all the cells in the D+H group. Adipocyte proliferation in the D+H group was inhibited by DEX treatment. Adipocyte enlargement in the D+H group was associated with increased the lipid accumulation but not the adipocyte proliferation. In contrast, the liver triglyceride and total cholesterol levels and their metabolism were downregulated by the same treatment, indicating the therapeutic potential of DEX for nonalcoholic fatty liver disease. Conclusions DEX synergizes with HFD to promote lipid deposition in adipose tissues. A high risk of obesity development in patients receiving HFD and DEX treatment is suggested.

ObjectiveTo analyze the changes in the degree of coordination of China's major epidemic prevention and control efforts before and after the outbreak of the Corona Virus Disease 2019 (COVID-19), so as to explore the impact of epidemic prevention and control measures on coordination dynamics. MethodsA total of 3 864 policy documents related to epidemic prevention and control from January 2000 to December 2020 across 31 provinces (autonomous regions, and municipalities) in China were systematically collected. Contents specific to collaborative and cooperative efforts were extracted, and the extent of interdepartmental coordination were quantified to assess the effectiveness of epidemic prevention and control efforts. Wilcoxon signed-rank test was adopted to statistically analyze the differences between the indicators before and after the epidemic. ResultsThe average overall coordination level for major epidemic prevention and control in 31 provinces (autonomous regions, and municipalities) increased from 43.06% to 97.62%, and the average coordination levels in the eastern, central, and western China soared from 42.29%, 37.50%, and 47.46%, to 98.81%, 96.20%, and 97.46%, respectively, with statistically significant differences (all P<0.05). In terms of department categorization, coordination levels in the professional departments and the key support departments peaked at 100.00%, while other support departments rose to 95.43%, with an increase of 77.15%, 181.85%, and 139.89%, respectively, exhibiting noteworthy statistically significant differences (all P<0.001). ConclusionThe scope of coordination departments of China’s major epidemic prevention and control exists a remarkable surge following the COVID-19 outbreak, notable heightened coordination is particularly observed among the key support departments. Future endeavors should prioritize the roles played by diverse departments in epidemic prevention and control, enhancing both the clarity of departmental responsibilities and the effectiveness of interdepartmental coordination.

ObjectiveTo systematically evaluate the public health governance capacity of 40 cities in Jiangsu, Zhejiang, and Anhui Provinces, providing a scientific evaluation basis for building a "Healthy Yangtze River Delta". MethodsA comprehensive collection of policy documents, public information reports, and research literature related to public health governance capacity in Jiangsu, Zhejiang, and Anhui Provinces was conducted, totaling 6 920 policy documents, 1 720 information reports, and 1 200 literature pieces. Based on the evaluation standards for an appropriate public health system established by the research team, the basic status of public health governance capacity was assessed to identify the strengths and weaknesses of the 40 cities. ResultsIn 2022, the public health governance capacity score for the 40 cities in Jiangsu, Zhejiang, and Anhui Provinces was (562.5±38.0) points. In terms of specific areas, the emergency response field received the highest score of (791.4±49.7) points, while the chronic disease prevention and control field received the lowest score of (368.2±29.6) points. The Jiangsu-Zhejiang-Anhui region has largely achieved the strategic priority of health, gradually improved public health legal regulations, and established a basic organizational framework with a solid foundation for information and data infrastructure. However, challenges still need to be addressed, such as unstable government funding for public health, unclear departmental responsibilities, and barriers to information interoperability. ConclusionThe public health governance capacity of the 40 cities in Jiangsu, Zhejiang, and Anhui Province has been at a moderate level, but disparities have still existed across regions and fields. In the future, while continuing to deepen existing advantages, it is essential to accurately identify the causes of problems, establish a long-term and stable investment mechanism, enhance information connectivity mechanisms, further clarify departmental responsibilities, and promote the achievement of the "Healthy Yangtze River Delta" goal.

ObjectivePrimary liver cancer, predominantly hepatocellular carcinoma (HCC), is a significant global health issue, ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality. Accurate and early diagnosis of HCC is crucial for effective treatment, as HCC and non-HCC malignancies like intrahepatic cholangiocarcinoma (ICC) exhibit different prognoses and treatment responses. Traditional diagnostic methods, including liver biopsy and contrast-enhanced ultrasound (CEUS), face limitations in applicability and objectivity. The primary objective of this study was to develop an advanced, light-weighted classification network capable of distinguishing HCC from other non-HCC malignancies by leveraging the automatic analysis of brightness changes in CEUS images. The ultimate goal was to create a user-friendly and cost-efficient computer-aided diagnostic tool that could assist radiologists in making more accurate and efficient clinical decisions. MethodsThis retrospective study encompassed a total of 161 patients, comprising 131 diagnosed with HCC and 30 with non-HCC malignancies. To achieve accurate tumor detection, the YOLOX network was employed to identify the region of interest (ROI) on both B-mode ultrasound and CEUS images. A custom-developed algorithm was then utilized to extract brightness change curves from the tumor and adjacent liver parenchyma regions within the CEUS images. These curves provided critical data for the subsequent analysis and classification process. To analyze the extracted brightness change curves and classify the malignancies, we developed and compared several models. These included one-dimensional convolutional neural networks (1D-ResNet, 1D-ConvNeXt, and 1D-CNN), as well as traditional machine-learning methods such as support vector machine (SVM), ensemble learning (EL), k-nearest neighbor (KNN), and decision tree (DT). The diagnostic performance of each method in distinguishing HCC from non-HCC malignancies was rigorously evaluated using four key metrics: area under the receiver operating characteristic (AUC), accuracy (ACC), sensitivity (SE), and specificity (SP). ResultsThe evaluation of the machine-learning methods revealed AUC values of 0.70 for SVM, 0.56 for ensemble learning, 0.63 for KNN, and 0.72 for the decision tree. These results indicated moderate to fair performance in classifying the malignancies based on the brightness change curves. In contrast, the deep learning models demonstrated significantly higher AUCs, with 1D-ResNet achieving an AUC of 0.72, 1D-ConvNeXt reaching 0.82, and 1D-CNN obtaining the highest AUC of 0.84. Moreover, under the five-fold cross-validation scheme, the 1D-CNN model outperformed other models in both accuracy and specificity. Specifically, it achieved accuracy improvements of 3.8% to 10.0% and specificity enhancements of 6.6% to 43.3% over competing approaches. The superior performance of the 1D-CNN model highlighted its potential as a powerful tool for accurate classification. ConclusionThe 1D-CNN model proved to be the most effective in differentiating HCC from non-HCC malignancies, surpassing both traditional machine-learning methods and other deep learning models. This study successfully developed a user-friendly and cost-efficient computer-aided diagnostic solution that would significantly enhances radiologists’ diagnostic capabilities. By improving the accuracy and efficiency of clinical decision-making, this tool has the potential to positively impact patient care and outcomes. Future work may focus on further refining the model and exploring its integration with multimodal ultrasound data to maximize its accuracy and applicability.