Objective To investigate the perioperative safety of patients with myasthenia gravis who take high doses of oral glucocorticoids. Methods A retrospective analysis was conducted on the clinical data of patients with myasthenia gravis who received oral glucocorticoids and underwent thoracoscopic thymectomy at the Department of Thoracic Surgery, the University of Hong Kong-Shenzhen Hospital from April 2013 to October 2019. Patients were divided into a high-dose steroid group and a medium-to-low dose steroid group based on the dosage of oral steroids, and the clinical data of the two groups were compared. Results A total of 102 patients were included, including 19 (18.62%) males and 83 (81.37%) females, with an average age of (32.25±9.83) years. There were 75 patients in the medium-to-low dose steroid group and 27 patients in the high-dose steroid group. All patients in both groups successfully completed the surgery without major intraoperative bleeding, conversion to open chest surgery, delayed extubation, severe infection, or perioperative death. The daily oral steroid dose for the high-dose steroid group was (35.81±4.29) mg, and for the medium-to-low dose steroid group it was (15.29±2.17) mg. There was no statistical difference in the operation time [(124.69±23.51) min vs. (117.89±21.46) min, P=0.172] and intraoperative blood loss [(21.19±3.48) mL vs. (20.56±3.41) mL, P=0.419] between the two groups. Postoperatively, 12 (11.76%) patients developed complications: one patient of myasthenic crisis (the medium-to-low dose steroid group), which was improved after short-term respiratory support and intravenous immunoglobulin treatment; 11 patients of respiratory/swallowing difficulties (9 in the medium-to-low dose steroid group and 2 in the high-dose steroid group), which were improved after anticholinergic treatment to reduce oral secretions and sputum suction, and the patients were discharged smoothly. There was no statistical difference in the incidence of postoperative complications between the two groups (P=0.637). Conclusion On the basis of good perioperative management, it is safe and feasible for patients with myasthenia gravis who take high dose of oral steroids to undergo thymectomy, and they have the same perioperative safety as patients with medium-to-low dose steroids.

This paper discussed the differentiation and treatment of chemotherapy-induced nausea and vomiting （CINV） in traditional Chinese medicine， based on the theory of "yin qi descends， while all yang qi ascends” from Inner Canon of Yellow Emperor （《黄帝内经》）. The core pathogenesis of CINV is attributed to chemotherapy-induced injury to the middle jiao （焦）， resulting in the separation of yin and yang and loss of their mutual communication. Acute and explosive CINV is often characterized by "all yang qi ascends"， with stomach yang constraint transforming into fire， and qi counterflow leading to vomiting， which can be treated by unblocking stomach yang， draining fire and scattering the counterflow， with Huoxiang Zhengqi Powder （藿香正气散） and medicinals of clearing function. For delayed cases， which are often due to "yin qi descends"， and the accumulation of turbid yin obstructs and constrains the deficient yang， the treatment should focus on promoting qi flow to eliminate turbidity， unblocking and boosting yang qi， and Chengqi-series Formulas （承气类方） or Xiao Banxia Decoction （小半夏汤） can be considered. Refractory and anticipated cases usually involve stomach-kidney deficiency and zang-fu （脏腑） organs disharmony， making yin and yang difficult to restore balance， for which the treatment should focus on nourishing both the stomach and kidneys and harmonize the zang-fu organs， with formulas such as Fuzi Lizhong Decoction （附子理中汤） or Xiaoyao Powder （逍遥散） modified as appropriate.

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.

ObjectiveEarly detection of crop diseases is crucial for effective agricultural management and yield protection. While visible light imaging has been widely applied for disease detection due to its accessibility and non-destructive nature, most existing methods primarily focus on identifying diseases during the symptomatic phase, when visual symptoms are already prominent. However, detecting plant diseases during the incubation period—when symptoms are still subtle or invisible—remains a major challenge due to the lack of distinctive visual cues and limited research methodologies. This study aims to address this gap by proposing a novel three-channel recognition model to accurately identify early blight symptoms during the incubation stage in Solanaceae crops, particularly in chili and tomato, using only visible light images. MethodsWe established a controlled experimental setup in which healthy leaves and leaves inoculated with early blight pathogens were photographed continuously over time. A total of 1 258 visible light images were collected, capturing various stages of disease progression. From these images, lesion regions were manually annotated. To quantitatively characterize early and subtle color changes within the lesion areas, we extracted color moments—first-order (mean), second-order (standard deviation), and third-order (skewness)—from multiple color spaces, including Lab and HSV. By analyzing the temporal variation of these color moments across disease progression stages, we identified the first-order moment of the saturation (S) channel in the HSV color space as the most sensitive indicator of lesion development on inoculated leaves. Using this insight, we defined four disease categories: healthy, incubation stage, early stage, and late stage. Subsequently, a three-channel classification model was constructed by integrating features from three color channels that provided complementary information. Three-channel models were constructed based on R-G-B, L-a-b, and H-S-V color spaces, respectively, to evaluate performance across different crops and to determine which color representation provides the most discriminative power for identifying disease symptoms during the incubation period. ResultsThe proposed models demonstrated strong classification performance. The three-channel model built using the Lab color space achieved a 94.44% accuracy in recognizing the incubation stage of early blight in pepper, effectively distinguishing subtle pre-symptomatic features from healthy tissue. The model based on the HSV color space achieved 100% accuracy in detecting incubation-stage symptoms in tomato, underscoring the discriminative power of S-channel variations in this context. These results confirm the model’s capability to identify early blight before visible lesions become pronounced, which is essential for timely disease intervention. ConclusionThis study presents a new technical pathway for early-stage disease detection using visible light images by focusing on subtle color feature changes during the incubation period. The proposed three-channel recognition model effectively identifies early blight in both chili and tomato, offering a non-destructive, low-cost, and easily deployable solution for early warning and precision agriculture. Furthermore, this framework can be generalized to other crops and diseases where early detection plays a critical role in minimizing yield losses and ensuring sustainable production. The method lays a solid foundation for future research in pre-symptomatic plant disease recognition and provides valuable tools for intelligent crop monitoring and precision management systems.

AIM: To investigate the expression changes and significance of serum microRNA-34a-5p(miR-34a-5p)and silent information regulator T1(SIRT1)in patients with endophthalmitis after cataract surgery.METHODS: Patients with endophthalmitis after cataract surgery from May 2020 to May 2024 were selected as infection group(20 cases), and patients without endophthalmitis were selected as control group(74 cases). Serum SIRT1 levels were detected by ELISA; the serum level of serum miR-34a-5p was detected by qRT-PCR; the correlation between miR-34a-5p and SIRT1 was analyzed by Pearson method; Logistic regression was used to analyze the influencing factors of endophthalmitis after cataract operation. Receiver operating characteristic(ROC)curve was drawn to analyze the diagnostic value of serum miR-34a-5p and SIRT1 levels in postoperative endophthalmitis.RESULTS: Compared with the control group, the serum level of miR-34a-5p in the infected group was significantly increased(P<0.001), and the serum level of SIRT1 was significantly decreased(P<0.001). Correlation analysis showed that miR-34a-5p was negatively correlated with SIRT1(r=-0.421, P<0.001). Logistic multivariate regression analysis showed that miR-34a-5p was an independent risk factor affecting endophthalmitis infection after cataract surgery(OR=3.532, P<0.05), and SIRT1 was a protective factor affecting endophthalmitis infection after cataract surgery(OR=0.875, P<0.05). The ROC curve showed that the area under curve(AUC)of serum miR-34a-5p combined with SIRT1 in the diagnosis of postoperative endophthalmitis was 0.933(95%CI: 0.861-0.975).CONCLUSION:Serum levels of miR-34a-5p are highly expressed and SIRT1 is lowly expressed in postoperative endophthalmitis, they are closely related to the occurrence and development of endophthalmitis after cataract surgery.

AIM: To explore the value of changes in the serum expression levels of triggering receptor expressed on myeloid cells-1(TREM-1)and matrix metalloproteinase-9(MMP-9)in early clinical diagnosis of postoperative endophthalmitis in patients with cataract surgery.METHODS: A total of 21 patients who underwent cataract surgery with infectious endophthalmitis in our hospital from May 2021 to May 2023 were selected as the study subjects(endophthalmitis group), and another 100 patients who underwent cataract surgery without endophthalmitis were selected as the non-endophthalmitis group. The serum levels of TREM-1, MMP-9, and the expression levels of inflammatory factors such as interleukin-1β(IL-1β), IL-17, and tumor necrosis factors-α(TNF-α)were detected and compared between the endophthalmitis group and the non-endophthalmitis group. The correlation between TREM-1 and MMP-9 was analyzed by Pearson method. Logistic regression was applied to analyze the factors that affected the occurrence of endophthalmitis in cataract patients after surgery. Receiver operating characteristic(ROC)curve was applied to analyze the early clinical diagnostic efficacy of TREM-1 and MMP-9 levels for postoperative endophthalmitis in cataract patients.RESULTS: Compared with the non-endophthalmitis group after cataract surgery, the expression levels of serum TREM-1, MMP-9, and inflammatory factors IL-1β, IL-17, and TNF-α in the endophthalmitis group were obviously increased(all P<0.05), and the TREM-1 was positively correlated with MMP-9(r=0.389, P<0.001). Logistic regression results showed that elevated levels of serum TREM-1 and MMP-9 expression, and vitreous overflow were independent risk factors for postoperative endophthalmitis in cataract patients(all P<0.05). ROC curve showed that the area under the curve(AUC)of TREM-1, MMP-9, and their combination in diagnosing postoperative endophthalmitis in cataract patients was 0.845, 0.844, and 0.935, respectively, and the clinical efficacy of the combination of the two in early diagnosis of postoperative endophthalmitis in cataract patients was better than that of serum TREM-1 and MMP-9 alone(all P<0.05).CONCLUSION: The expression levels of serum TREM-1 and MMP-9 in patients with endophthalmitis after cataract surgery are abnormally elevated, and the combination of the two has high clinical application value in early diagnosis of endophthalmitis after cataract surgery.

Objective:To analyze the interference of an exogenous glucose test on urinary creatinine-related renal injury biomarkers in patients with chronic kidney disease (CKD).Methods:This cross-sectional study enrolled CKD patients who visited Peking University First Hospital between October 2023 and March 2024. The patients (age: 50±18 years) included 90 males and 70 females. Fresh morning urine samples were collected, totaling 160 samples. Each urine sample was divided into 5 aliquots,each containing 225 μl. One aliquot received 75 μl of deionized water as the control. The other aliquots received 75 μl of glucose solutions at concentrations of 120, 480, 960, and 1200 mmol/L, resulting in final glucose concentrations of 30, 120, 240, and 300 mmol/L in the urine samples, respectively. Urinary creatinine in each sample was measured using both the enzymatic method and the picric acid (Jaffe) method. The following ratios were calculated: urinary albumin-to-creatinine ratio (uACR), urinary protein-to-creatinine ratio (uPCR), urinary transferrin-to-creatinine ratio (uTRF/uCr), urinary α1-microglobulin-to-creatinine ratio (uA1M/uCr), urinary immunoglobulin G-to-creatinine ratio (uIgG/uCr), and urinary N-acetyl-β-D-glucosaminidase-to-creatinine ratio (uNAG/uCr).Results:Under high glucose concentrations, significant differences ( P<0.05) were observed between the enzymatic method and the picric acid method in measuring urinary creatinine-related renal injury biomarkers. At glucose concentrations of 30, 120, 240, and 300 mmol/L, the mean percentage biases for creatinine measured by the enzymatic method were -0.19%, -0.27%, -0.20%, and -0.21%, respectively. The mean percentage biases for creatinine measured by the picric acid method were 0.78%, 1.26%, 1.35%, and 1.38%, respectively, showing an increasing deviation between the results before and after glucose addition as the glucose concentration rose. For uACR measurement, the mean absolute biases using the enzymatic method were -0.01, 1.27, 0.95, and 1.10 mg/g at the respective glucose concentrations. Using the picric acid method, the mean absolute biases for uACR were -11.69, -14.98, -16.91, and-18.51 mg/g. The biases of the picric acid method were significantly higher than the those of the enzymatic method, and the absolute value of the mean biases increased with rising glucose concentration. For uPCR, uTRF/uCr, uA1M/uCr, uNAG/uCr, and uIgG/uCr, the deviations measured by the enzymatic method were consistently smaller than those measured by the picric acid method. Conclusions:The measurement of creatinine and related renal injury biomarkers by the enzymatic method is less affected by glucose concentration. In contrast, the measurement results obtained using the picric acid method are significantly affected by glucose concentration.

Objective In order to understand the current status and influencing factors of perioperative pulmonary rehabilitation knowledge,attitude,and practice among Chinese thoracic surgery nurses,and to provide references for managers to take targeted measures to improve their pulmonary rehabilitation knowledge,attitude,and practice level.Methods From August to October 2023,a convenience sampling method and cross-sectional descriptive survey were used to anonymously survey 1 167 thoracic surgery nurses from tertiary-level A cancer specialty hospitals and tertiary-level A general hospitals in 24 provinces through the Wenjuanxing platform.A general information questionnaire and a knowledge,attitude and practice questionnaire for lung cancer perioperative pulmonary rehabilitation nurses were used,including knowledge dimension(14 items),belief dimension(6 items),and behavior dimension(14 items),totaling 34 items.Univariate analysis and linear regression multivariate analysis were used to determine the influencing factors of the knowledge,attitude and practice level of thoracic surgery nurses in perioperative pulmonary rehabilitation.Results 1 089 nurses completed the investigation.The total standard score and the dimension scores on knowledge,attitude,and behavior of the perioperative pulmonary rehabilitation questionnaire for thoracic surgery nurses were(80.45±11.84)(73.72±14.68)(89.61±11.38)and(83.46±14.48),respectively.The nature of the hospital,whether there is an administrative position,whether the department carries out ERAS,and whether they have received pulmonary rehabilitation training are the influencing factors of the perioperative pulmonary rehabilitation knowledge,attitude,and practice level of thoracic surgery nurses(P＜0.05).Conclusion The knowledge,attitude,and practice of perioperative lung rehabilitation among thoracic surgery nurses are generally at a moderate level.However,their knowledge of perioperative lung rehabilitation is relatively insufficient,and there are many influencing factors.Managers should strengthen pulmonary rehabilitation training for thoracic surgery nurses,improve their knowledge reserves and evidence conversion capabilities,and coordinate cross-integration among multidisciplinary teams to improve their knowledge,attitude and practice in perioperative pulmonary rehabilitation.