Major depressive disorder (MDD) is a prevalent psychiatric condition characterized by high rates of prevalence and recurrence. Repetitive transcranial magnetic stimulation (rTMS) has been widely utilized in the acute phase treatment of MDD and has shown potential in maintenance therapy. However, the factors influencing the efficacy of rTMS during the acute phase and the sustainability of its long-term therapeutic effects remain incompletely understood. Additionally, a consensus on the optimal maintenance treatment protocol has yet to be established. This article reviews recent evidence on the application of rTMS in both acute and maintenance treatment of MDD, aiming to summarize current research progress and provide insights for the further promotion and application of rTMS in clinical practice.

ObjectiveTo investigate the ameliorative effect of paeonol on acute alcohol-induced hepatic inflammation in mice via the regulation of the short-chain fatty acids （SCFAs）-specific receptor GPR43/mitogen-activated protein kinase （MAPK） signaling pathway. MethodsC57BL/6 mice were randomly divided into five groups： blank control group， model group， low-dose paeonol group （120 mg·kg^-1）， high-dose paeonol group （480 mg·kg^-1）， and silybin group （36.8 mg·kg^-1）. A mouse model of alcohol-induced liver disease （ALD） was established by ad libitum administration of a Lieber-DeCarli alcohol liquid diet. Serum lipid levels， liver function， inflammatory cytokines， and oxidative stress markers were measured. Liver hematoxylin-eosin （HE） staining and Oil Red O staining were performed to validate successful modeling. Western blot analysis was used to assess the expression levels of zonula occludens-1 （ZO-1）， Claudin-1， and proteins related to the GPR43/MAPK signaling pathway in the colonic tissue. Immunohistochemistry was employed to detect the protein expression of GPR43， ZO-1， and Claudin-1 in the colon. Then 16S rDNA sequencing was performed to analyze differences in intestinal flora between the model group and the high-dose paeonol group. Additionally， fecal microbiota transplantation （FMT） experiments were conducted to validate the regulatory effect of paeonol on ALD via modulation of intestinal flora. ResultsCompared with the blank control group， the model group showed significantly elevated serum lipid levels， oxidative stress， and inflammatory cytokine expression （P<0.01）. Liver histology revealed increased inflammatory infiltration and lipid droplet accumulation. Colonic mucosal injury and impaired intestinal barrier function were observed. Levels of MAPK pathway-related proteins in the colonic tissue were upregulated （P<0.01）， while GPR43， ZO-1， and Claudin-1 protein expression levels were significantly decreased （P<0.01）. The composition and abundance of the intestinal flora were markedly altered， with a reduced Bacteroidetes-to-Firmicutes ratio and decreased relative abundances of Eubacterium， Parabacteroides， Erysipelothrix， and Adlercreutzia， alongside increased abundances of Clostridium butyricum， Enterococcus， and Helicobacter pylori in the model group. Compared with the model group， paeonol significantly reduced serum lipid levels， oxidative stress responses， and the expression of inflammatory cytokines in ALD mice （P<0.05， P<0.01）. It also attenuated hepatic lipid accumulation， restored intestinal barrier function， and repaired the structural integrity of liver and colonic tissues. The protein expression levels of ZO-1， Claudin-1， and GPR43 in the colonic tissue were significantly increased （P<0.05， P<0.01）， while those of MAPK pathway-related proteins were significantly decreased （P<0.05， P<0.01）. The intestinal flora dysbiosis was effectively alleviated， rendering its composition closer to that of normal mice. The efficacy of paeonol in modulating ALD was further confirmed by FMT experiments， supporting its mechanistic involvement in the SCFAs-GPR43/MAPK signaling pathway. ConclusionPaeonol exerts a protective effect against ALD in mice， which may be mediated through regulation of the SCFAs-GPR43/MAPK signaling pathway， thereby achieving anti-inflammatory effects and improving intestinal barrier function.

ObjectiveTo investigate the ameliorative effect of paeonol on acute alcohol-induced hepatic inflammation in mice via the regulation of the short-chain fatty acids （SCFAs）-specific receptor GPR43/mitogen-activated protein kinase （MAPK） signaling pathway. MethodsC57BL/6 mice were randomly divided into five groups： blank control group， model group， low-dose paeonol group （120 mg·kg^-1）， high-dose paeonol group （480 mg·kg^-1）， and silybin group （36.8 mg·kg^-1）. A mouse model of alcohol-induced liver disease （ALD） was established by ad libitum administration of a Lieber-DeCarli alcohol liquid diet. Serum lipid levels， liver function， inflammatory cytokines， and oxidative stress markers were measured. Liver hematoxylin-eosin （HE） staining and Oil Red O staining were performed to validate successful modeling. Western blot analysis was used to assess the expression levels of zonula occludens-1 （ZO-1）， Claudin-1， and proteins related to the GPR43/MAPK signaling pathway in the colonic tissue. Immunohistochemistry was employed to detect the protein expression of GPR43， ZO-1， and Claudin-1 in the colon. Then 16S rDNA sequencing was performed to analyze differences in intestinal flora between the model group and the high-dose paeonol group. Additionally， fecal microbiota transplantation （FMT） experiments were conducted to validate the regulatory effect of paeonol on ALD via modulation of intestinal flora. ResultsCompared with the blank control group， the model group showed significantly elevated serum lipid levels， oxidative stress， and inflammatory cytokine expression （P<0.01）. Liver histology revealed increased inflammatory infiltration and lipid droplet accumulation. Colonic mucosal injury and impaired intestinal barrier function were observed. Levels of MAPK pathway-related proteins in the colonic tissue were upregulated （P<0.01）， while GPR43， ZO-1， and Claudin-1 protein expression levels were significantly decreased （P<0.01）. The composition and abundance of the intestinal flora were markedly altered， with a reduced Bacteroidetes-to-Firmicutes ratio and decreased relative abundances of Eubacterium， Parabacteroides， Erysipelothrix， and Adlercreutzia， alongside increased abundances of Clostridium butyricum， Enterococcus， and Helicobacter pylori in the model group. Compared with the model group， paeonol significantly reduced serum lipid levels， oxidative stress responses， and the expression of inflammatory cytokines in ALD mice （P<0.05， P<0.01）. It also attenuated hepatic lipid accumulation， restored intestinal barrier function， and repaired the structural integrity of liver and colonic tissues. The protein expression levels of ZO-1， Claudin-1， and GPR43 in the colonic tissue were significantly increased （P<0.05， P<0.01）， while those of MAPK pathway-related proteins were significantly decreased （P<0.05， P<0.01）. The intestinal flora dysbiosis was effectively alleviated， rendering its composition closer to that of normal mice. The efficacy of paeonol in modulating ALD was further confirmed by FMT experiments， supporting its mechanistic involvement in the SCFAs-GPR43/MAPK signaling pathway. ConclusionPaeonol exerts a protective effect against ALD in mice， which may be mediated through regulation of the SCFAs-GPR43/MAPK signaling pathway， thereby achieving anti-inflammatory effects and improving intestinal barrier function.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Objective: To evaluate the comprehensive intervention effect of lunch for primary and secondary school students in Minhang District, so as to provide a theoretical and practical basis for lunch intervention in school. Methods: From October to December 2023, a convenience sampling method was used to select 1 937 students from one primary and secondary school in Minhang District.A comprehensive intervention measure focusing on "reducing oil and salt" for lunch recipe optimization and nutrition education was carried out, and a questionnaire survey was conducted to evaluate the intervention effect three months later. Chi square test and Wilcoxon rank test were used to compare the data before and after the intervention. Results: After intervention, the use of cooking oil and salt, the supply of protein and fat in primary and secondary school lunches were reduced, and had no obvious impact on energy and other major nutrients. After intervention, compared to before intervention, the proportion of primary school students who felt that lunch was greasy decreased (8.9%, 6.2%, χ 2=4.35), and the proportion of primary and secondary school students who felt that lunch were delicious decreased significantly (33.2%, 23.2%; 63.9%, 53.5%, χ 2=26.39, 17.52) ( P < 0.05 ). Secondary school students also felt reduced variety of food ingredients (46.9%, 38.3%, χ 2=16.05, P <0.05). In addition, after intervention, the total surplus rate of primary school students meals decreased (7.4%, 4.4%, χ 2=5.73), mainly reflected in the decrease of the surplus rate of staple foods (7.1%, 2.4%, χ 2=17.39), while the surplus rate of vegetable dishes increased ( 16.0 %, 21.2%, χ 2=6.01) ( P <0.05). Although there was no significant change in the total surplus rate of meals for secondary school students, the surplus rate of staple foods decreased (12.9%, 5.4%, χ 2=33.52), while the surplus rates of meat and vegetable dishes increased (11.2%, 26.9%; 17.5%, 33.2%, χ 2=74.26, 61.88) ( P <0.05). After intervention, there was no statistically significant difference in the overweight and obesity rates of primary school students ( χ 2=0.11,0.43) and secondary school students ( χ 2=0.01,0.00) compared to before intervention( P >0.05). After intervention, the lung capacity of primary school students [1 564 (1 269,1 890) mL] and sitting forward flexion [11.3 (7.6, 15.2) cm] increased compared to before intervention [1 522 (1 259, 1 819 ) mL, 10.5 (6.3, 13.5) cm] ( Z =2.20, 4.68, P <0.01), but there was no statistically significant difference in lung capacity and sitting forward flexion of secondary school students before and after intervention ( Z =-0.46, -0.08, P >0.05). Conclusion The comprehensive intervention of school lunch has promoted a significant decrease in the use of oil and salt in lunch and improved the quality of recipes, and has a positive impact on the situation of leftover lunch and the health of students to a certain extent.

With the widespread adoption of low-dose CT screening and the extensive application of high-resolution CT, the detection rate of sub-centimeter lung nodules has significantly increased. How to scientifically manage these nodules while avoiding overtreatment and diagnostic delays has become an important clinical issue. Among them, lung nodules with a consolidation tumor ratio less than 0.25, dominated by ground-glass shadows, are particularly worthy of attention. The therapeutic challenge for this group is how to achieve precise and complete resection of nodules during surgery while maximizing the preservation of the patient's lung function. The "watershed topography map" is a new technology based on big data and artificial intelligence algorithms. This method uses Dicom data from conventional dose CT scans, combined with microscopic (22-24 levels) capillary network anatomical watershed features, to generate high-precision simulated natural segmentation planes of lung sub-segments through specific textures and forms. This technology forms fluorescent watershed boundaries on the lung surface, which highly fit the actual lung anatomical structure. By analyzing the adjacent relationship between the nodule and the watershed boundary, real-time, visually accurate positioning of the nodule can be achieved. This innovative technology provides a new solution for the intraoperative positioning and resection of lung nodules. This consensus was led by four major domestic societies, jointly with expert teams in related fields, oriented to clinical practical needs, referring to domestic and foreign guidelines and consensus, and finally formed after multiple rounds of consultation, discussion, and voting. The main content covers the theoretical basis of the "watershed topography map" technology, indications, operation procedures, surgical planning details, and postoperative evaluation standards, aiming to provide scientific guidance and exploration directions for clinical peers who are currently or plan to carry out lung nodule resection using the fluorescent microscope watershed analysis method.

Objective To explore enteral nutrition support and analyze its influencing factors in elderly patients with ischemic stroke. Methods A total of 328 patients with ischemic stroke in General Hospital of Western Theater Command were enrolled for nutritional screening between July 2020 and February 2024. Corresponding nutritional support plans were selected to investigate the compliance of patients with enteral nutrition support. Patients were divided into a standard group (n=140) and a non-standard group (n=97) based on whether their calorie intake met the standard. The effects of different clinical characteristics on enteral nutrition support were explored, and logistic analysis was used to analyze the influencing factors of non-standard enteral nutrition support. Results In the 328 patients with ischemic stroke, proportions of total parenteral nutrition support, total enteral nutrition support, and parenteral/enteral nutrition support were 25.30%, 27.74% and 46.95%, respectively. The proportions of vomiting or regurgitation, gastric residual volume >100 mL, mechanical ventilation and use of antibiotics >2 in the non-standard group were higher than those in the standard group (P<0.05). Logistic analysis showed that the above clinical characteristics were risk factors influencing patients with enteral nutrition support and parenteral/enteral nutrition support. Conclusion Vomiting or regurgitation , gastric residual volume, mechanical ventilation, and amount of antibiotics used are important influencing factors of enteral nutrition support in patients. Clinicians should pay attention to the above clinical characteristics.

AIM: To investigate the predictive value of serum histone deacetylase 1(HDAC1)and endothelial nitric oxide synthase(eNOS)for infectious endophthalmitis after cataract surgery.METHODS: A total of 362 cataract patients(362 eyes)admitted to our hospital from January 2020 to January 2023 were selected as the research objects. According to the occurrence of postoperative infectious endophthalmitis, they were divided into infection group(15 cases, 15 eyes)and non-infection group(347 cases, 347 eyes). Enzyme linked immunosorbent assay(ELISA)was applied to detect the levels of serum HDAC1 and eNOS in all subjects, and the levels of serum HDAC1 and eNOS in both groups were compared; the influencing factors of infectious endophthalmitis were analyzed by multivariate Logistic regression; the receiver operative curve(ROC)was applied to analyze the predictive value of serum HDAC1 and eNOS levels for postoperative infectious endophthalmitis in cataract patients.RESULTS: The levels of serum HDAC1 and eNOS in the infected group were obviously higher than those in the uninfected group(all P<0.01). Surgical time, vitreous overflow, HDAC1, and eNOS were all risk factors for postoperative infectious endophthalmitis(all P<0.05). ROC results showed that the AUC of HDAC1 and eNOS in predicting postoperative infectious endophthalmitis in cataract patients was 0.878 and 0.877, respectively, with sensitivity of 88.7% and 87.7%, specificity of 70.4% and 7.8%, respectively, while the AUC of the two combination in predicting postoperative infectious endophthalmitis in cataract patients was 0.978, with a sensitivity of 86.7% and a specificity of 85.3%.CONCLUSION:The serum levels of HDAC1 and eNOS in patients with infectious endophthalmitis after cataract surgery are obviously increased, and the combined detection of serum HDAC1 and eNOS can improve the predictive efficacy of infectious endophthalmitis in cataract patients after surgery. Both can provide reference for clinical diagnosis and treatment.

AIM: To investigate the predictive value of serum histone deacetylase 1(HDAC1)and endothelial nitric oxide synthase(eNOS)for infectious endophthalmitis after cataract surgery.METHODS: A total of 362 cataract patients(362 eyes)admitted to our hospital from January 2020 to January 2023 were selected as the research objects. According to the occurrence of postoperative infectious endophthalmitis, they were divided into infection group(15 cases, 15 eyes)and non-infection group(347 cases, 347 eyes). Enzyme linked immunosorbent assay(ELISA)was applied to detect the levels of serum HDAC1 and eNOS in all subjects, and the levels of serum HDAC1 and eNOS in both groups were compared; the influencing factors of infectious endophthalmitis were analyzed by multivariate Logistic regression; the receiver operative curve(ROC)was applied to analyze the predictive value of serum HDAC1 and eNOS levels for postoperative infectious endophthalmitis in cataract patients.RESULTS: The levels of serum HDAC1 and eNOS in the infected group were obviously higher than those in the uninfected group(all P<0.01). Surgical time, vitreous overflow, HDAC1, and eNOS were all risk factors for postoperative infectious endophthalmitis(all P<0.05). ROC results showed that the AUC of HDAC1 and eNOS in predicting postoperative infectious endophthalmitis in cataract patients was 0.878 and 0.877, respectively, with sensitivity of 88.7% and 87.7%, specificity of 70.4% and 7.8%, respectively, while the AUC of the two combination in predicting postoperative infectious endophthalmitis in cataract patients was 0.978, with a sensitivity of 86.7% and a specificity of 85.3%.CONCLUSION:The serum levels of HDAC1 and eNOS in patients with infectious endophthalmitis after cataract surgery are obviously increased, and the combined detection of serum HDAC1 and eNOS can improve the predictive efficacy of infectious endophthalmitis in cataract patients after surgery. Both can provide reference for clinical diagnosis and treatment.

ObjectiveTomatoes are one of the highest-yielding and most widely cultivated economic crops globally, playing a crucial role in agricultural production and providing significant economic benefits to farmers and related industries. However, early blight in tomatoes is known for its rapid infection, widespread transmission, and severe destructiveness, which significantly impacts both the yield and quality of tomatoes, leading to substantial economic losses for farmers. Therefore, accurately identifying early symptoms of tomato early blight is essential for the scientific prevention and control of this disease. Additionally, visualizing affected areas can provide precise guidance for farmers, effectively reducing economic losses. This study combines hyperspectral imaging technology with machine learning algorithms to develop a model for the early identification of symptoms of tomato early blight, facilitating early detection of the disease and visual localization of affected areas. MethodsTo address noise interference present in hyperspectral images, robust principal component analysis (RPCA) is employed for effective denoising, enhancing the accuracy of subsequent analyses. To avoid insufficient information representation caused by the subjective selection of regions of interest, the Otsu’s thresholding method is utilized to extract tomato leaves effectively from the background, with the average spectrum of the entire leaf taken as the primary object of study. Furthermore, a comprehensive spectral preprocessing workflow is established by integrating multivariate scatter correction (MSC) and standardization methods, ensuring the reliability and effectiveness of the data. Based on the processed spectral data, a discriminant model utilizing a linear kernel function support vector machine (SVM) is constructed, focusing on characteristic wavelengths to improve the model's discriminative capability. ResultsCompared to full-spectrum modeling, this approach results in an 8.33% increase in accuracy on the test set. After optimizing the parameters of the SVM model, when C=1.64, the accuracies of the training set and test set reach 91.67% and 94.44%, respectively, demonstrating a 1.19% increase in training set accuracy compared to the unoptimized model, while maintaining the same accuracy on the test set, effectively alleviating issues of underfitting. ConclusionThis study successfully establishes an early discriminant model for tomato early blight using hyperspectral imaging and achieves visualization of early symptoms. Experimental results indicate that the SVM discriminant model based on characteristic wavelengths and a linear kernel function can effectively identify early symptoms of tomato early blight. Visualization of these symptoms in terms of disease probability allows for a more intuitive detection of early diseases and timely implementation of corresponding control measures. This visual analysis not only enhances the efficiency of disease identification but also provides farmers with more straightforward and practical information, aiding them in formulating more reasonable prevention strategies. These research findings provide valuable references for the early identification and visualization of plant diseases, holding significant practical implications for monitoring, identifying, and scientifically preventing crop diseases. Future research could further explore how to apply this model to disease detection in other crops and how to integrate IoT technology to create intelligent disease monitoring systems, enhancing the scientific and efficient management of crops.