ObjectiveTo characterize the systemically absorbed components of Zhengqi prescription （ZQP） and investigate its therapeutic effects and mechanisms against cancer-related fatigue （CRF） through an integrated approach of network pharmacology and animal experiments. MethodsThe systemically absorbed components of ZQP were identified by ultra-performance liquid chromatography coupled with quadrupole-Orbitrap mass spectrometry （UPLC-Q-Exactive Orbitrap MS）. Network pharmacology was employed to predict the potential targets and signaling pathways involved in the anti-CRF effects of ZQP. A mouse model of paclitaxel-induced CRF， mimicking breast cancer-related fatigue， was established. Mice were administered different doses of ZQP extract. The therapeutic efficacy was evaluated based on fatigue-related indicators， behavioral test results， and energy metabolism parameters. Western blot analysis was conducted to validate the regulation of core signaling pathways. ResultsA total of 48 systemically absorbed components were identified. Network pharmacology analysis revealed 124 intersecting targets （including Akt1） and implicated signaling pathways such as phosphatidylinositol 3-kinase/protein kinase （PI3K/Akt）. Pharmacodynamic studies with the established CRF model demonstrated that ZQP alleviated fatigue symptoms. Specifically， ZQP-treated mice exhibited increased exhaustive swimming time （P<0.05）， prolonged struggling time in the tail suspension test， and enhanced movement duration and distance in the open field test （P<0.05， P<0.01）. Furthermore， ZQP treatment decreased serum lactate and blood urea nitrogen levels （P<0.05， P<0.01）， increased liver and muscle glycogen content （P<0.05， P<0.01）， and upregulated the expression of phosphorylated （p）-Akt and p-PI3K in the gastrocnemius muscle （P<0.05， P<0.01）. ConclusionZQP exerts significant therapeutic effects on paclitaxel-induced breast cancer-related fatigue by regulating the PI3K/Akt signaling pathway. Furthermore， this study provides a preliminary foundation for subsequent quality control of the formula and further investigation into its mechanism against CRF.

ObjectiveTo investigate the effects of Congrong Zonggan capsules （CRZG） on cognitive impairment in the Alzheimer's disease （AD） model of mice and its related mechanisms. MethodsSPF grade 4-week-old 5×FAD mice were divided into a model group， low-dose CRZG （0.819 g·kg^-1） and high-dose CRZG （1.638 g·kg^-1） groups， and Donepezilepezil hydrochloride group （2 mg·kg^-1）， with eight mice in each group. Eight C57 mice with the same background were set as the normal group. After one week of adaptive feeding， mice were orally administered continuously for six months. On the 5th month of drug administration， Y maze， new object recognition， and Morris water maze tests were conducted separately. After administration， mouse brain tissue was taken， and the levels of tumor necrosis factor-α （TNF-α） and interleukin-6 （IL-6） in brain tissue were detected by enzyme-linked immunosorbent assay （ELISA）. Immunofluorescence （IF） was used to detect the expression of small glial cell markers Iba1， astrocyte markers GFAP， and amyloid protein 1-42 （Aβ_1-42） in the hippocampus of the brain tissue. The hematoxylin-eosin （HE） staining was used to detect pathological changes in the hippocampus of brain tissue. Western blot was used to detect the expression of nuclear factor-κB （NF-κB） p65， NOD-like receptor protein 3 （NLRP3）， cleaved Caspase-1， apoptosis-associated speck-like protein containing a CARD （ASC）， and other proteins in the brain tissue. ResultsCompared with those in the normal group， the mice in the model group had obvious cognitive impairment. The spontaneous alternation rate of the Y maze was decreased， and the discrimination index of novel object recognition was decreased significantly （P<0.01）. The escape latency in the water maze was shortened significantly （P<0.01）. The contents of IL-6 and TNF-α in brain tissue were increased. The fluorescence levels of Iba1 and Aβ_1-42 in the hippocampus were significantly increased （P<0.01）. There was a significant increase in neuronal lesions， neuronal atrophy， loose arrangement of tissue structure， and abnormal erythrocyte aggregation in the hippocampus. The protein expressions of p-NF-κB p65/NF-κB p65， cleaved Caspase-1， ASC， IL-6， and IL-1β were significantly increased （P<0.05， P<0.01）. Compared with the model group， the spontaneous alternation rate and discrimination index of the high-dose CRZG group were increased significantly （P<0.01）， and the escape latency was shortened significantly （P<0.05， P<0.01）. The content of IL-6 decreased in the brain， and that of TNF-α dropped significantly （P<0.01）. The expression of Iba1 protein and Aβ_1-42 in the hippocampus decreased significantly （P<0.05， P<0.01）. The hippocampal neurons were densely arranged， and the pyramidal nuclei were clear and centered. The abnormal aggregation of red blood cells was alleviated. The value of p-NF-κB/NF-κB proteins and the expression of ASC， cleaved Caspase-1， IL-6， and IL-1β were significantly decreased （P<0.05， P<0.01）. ConclusionCRZG can effectively improve cognitive impairment in 5×FAD mice with Alzheimer's disease， and its mechanism may be related to the regulation of the NF-κB/NLRP3 pathway to reduce the abnormal activation of microglia and inhibit neuroinflammation.

Objective To develop a method for accurate identification of multiscale carotid plaques in ultrasound images.Methods We proposed a two-stage carotid plaque detection method based on deep convolutional neural network(SM-YOLO).A series of algorithms such as median filtering,histogram equalization,and Gamma transformation were used to preprocess the dataset to improve image quality.In the first stage of the model construction,a candidate plaque set was built based on the YOLOX_l target detection network,using multiscale image training and multiscale image prediction strategies to accommodate carotid artery plaques of different shapes and sizes.In the second stage,the Histogram of Oriented Gradient(HOG)features and Local Binary Pattern(LBP)features were extracted and fused,and a Support Vector Machine(SVM)classifier was used to screen the candidate plaque set to obtain the final detection results.This model was compared quantitatively and visually with several target detection models(YOLOX_l,SSD,EfficientDet,YOLOV5_l,Faster R-CNN).Results SM-YOLO achieved a recall of 89.44%,an accuracy of 90.96%,a F1-Score of 90.19%,and an AP of 92.70%on the test set,outperforming other models in all performance indicators and visual effects.The constructed model had a much shorter detection time than the Faster R-CNN model(only one third of that of the latter),thus meeting the requirements of real-time detection.Conclusion The proposed carotid artery plaque detection method has good performance for accurate identification of carotid plaques in ultrasound images.

Objective To develop a method for accurate identification of multiscale carotid plaques in ultrasound images.Methods We proposed a two-stage carotid plaque detection method based on deep convolutional neural network(SM-YOLO).A series of algorithms such as median filtering,histogram equalization,and Gamma transformation were used to preprocess the dataset to improve image quality.In the first stage of the model construction,a candidate plaque set was built based on the YOLOX_l target detection network,using multiscale image training and multiscale image prediction strategies to accommodate carotid artery plaques of different shapes and sizes.In the second stage,the Histogram of Oriented Gradient(HOG)features and Local Binary Pattern(LBP)features were extracted and fused,and a Support Vector Machine(SVM)classifier was used to screen the candidate plaque set to obtain the final detection results.This model was compared quantitatively and visually with several target detection models(YOLOX_l,SSD,EfficientDet,YOLOV5_l,Faster R-CNN).Results SM-YOLO achieved a recall of 89.44%,an accuracy of 90.96%,a F1-Score of 90.19%,and an AP of 92.70%on the test set,outperforming other models in all performance indicators and visual effects.The constructed model had a much shorter detection time than the Faster R-CNN model(only one third of that of the latter),thus meeting the requirements of real-time detection.Conclusion The proposed carotid artery plaque detection method has good performance for accurate identification of carotid plaques in ultrasound images.

OBJECTIVE To predict the amount of colorants used in the preparation of placebo of Chinese medicine by construc-ting particle swarm optimization-back propagation neural network PSO-BPNN compound granules,and to provide a new idea for the simulation of placebo color of Chinese medicine compound granules.METHODS The BP neural network was used to establish the model of sample color parameters L,a?,b?and pigment mass fraction.The global search ability of particle swarm optimization algo-rithm was used to optimize the weight and bias of BP neural network to prevent the local minimum value of the model.The linear reduc-tion weight coefficient method and the introduction of mutation operator were used to improve the global optimization ability of particle swarm optimization algorithm.The color comprehensive evaluation index(ΔE)was used as the objective evaluation standard to verify the test results.RESULTS The training results show that the fitting accuracy of the improved PSO-BP neural network was up to 98.31%.The prediction results show that the prediction error of the improved PSO-BP neural network was the smallest,and the mean absolute percentage error(MAPE),root mean square error(RMSE)and mean color difference(ΔE)were 0.411 5,2.164 6 and 2.56,respectively.The verification samples of three kinds of particles were prepared for verification.The ΔE of the verification sample and the model drug were 1.73,2.63 and 4.11,respectively.The color difference between the two groups and the model drug was small by visual evaluation.CONCLUSION The BP neural network based on the improved particle swarm optimization algorithm can simulate the prediction of the amount of colorants used in the preparation of Chinese medicine compound granules,and can be used as a recommended optimization model for placebo color matching research.

As a commonly used traditional Chinese medicine,Alpinia oxyphylla is widely used as both medicine and edible resources.A.oxyphylla has the effects of warming the kidney,consolidating essence,contracting urine,warming the spleen,stopping diarrhea and absorbing saliva,which mainly treated diseases caused by kidney deficiency and spleen cold.A.oxyphylla is rich in chemical components,mainly including 194 volatile oil,121 terpenoids(including 111 sesquiterpenoids),19 diphenylheptanes,ten flavonoids,ten bases and nucleosides,four steroids,eight glycosides and 13 organic acids.It has a wide range of pharmacological effects such as anti-AD/PD,anti-tumor,anti-inflammatory,antioxidant,etc.This article reviews the chemical components and pharmacological effects of A.oxyphylla,in order to provide reference for its further development and rational application.

Objective:To provide references for the health management of thyroid nodules in naval flying personnel by analyzing the ultrasound characteristics of naval flying personnel with thyroid nodules.Methods:A total of 306 naval flying personnel, who were diagnosed as thyroid nodules in yearly health examination in the Third Sanatorium of Air Force Healthcare Center for Special Services Hangzhou from January of 2019 to December of 2021, were selected as the research subjects. They were divided into 3 groups by age (20-29 years, 30-39 years, ≥40 years), 2 groups by flying hours (<3 000 h, ≥3 000 h) and 3 groups by aircraft types (helicopter, transporter, fighter). The characteristics of thyroid nodule ultrasound images were retrospectively analyzed and the size, quantity and classification which defined in Chinese-thyroid imaging reporting and data system (C-TIRADS) of thyroid nodule were compared among the groups of different ages, flying hours, and aircraft types.Results:Among 306 naval flying personnel with thyroid noedules, 280 cases (91.50%) were small nodules (diameter <1 cm), 26 cases (8.50%) were large nodules (diameter ≥1 cm). One hundred and fifty-one cases (49.35%) were single nodules and 155 cases (50.65%) were multiple nodules. There were 135 cases (44.12%) with C-TIRADS grade 2 thyroid nodules, 158 cases (51.63%) with C-TIRADS grade 3 nodules, and 13 cases (4.25%) with C-TIRADS grade 4 nodules. There were significant differences in the size, number, classification of composition ratio of thyroid nodules among different age groups ( χ2=8.86, 5.94, 46.20, P=0.013, 0.051,<0.001). There were significant differences in the size and classification of composition ratio of thyroid nodules between different flying hours groups ( χ2=16.91, 24.35, both P<0.001). The proportion of C-TIRADS grade 4 nodules in the flying hours ≥3 000 h group was higher than that in the <3 000 h group, with a significant difference ( χ2=4.77, P=0.029).There were no significant differences in the size, number, classification of composition ratio of thyroid nodules among different aircraft types groups (all P>0.05). Conclusions:Age and flying hours have effects on size and classification of composition ratio of thyroid nodules in flying personnel, and age also has the effect on quantity. A scientific and systematic follow-up mechanism would be helpful to assess the risk of thyroid cancer and give early warning for the timely intervention.

Objective:To provide references for the health management of thyroid nodules in naval flying personnel by analyzing the ultrasound characteristics of naval flying personnel with thyroid nodules.Methods:A total of 306 naval flying personnel, who were diagnosed as thyroid nodules in yearly health examination in the Third Sanatorium of Air Force Healthcare Center for Special Services Hangzhou from January of 2019 to December of 2021, were selected as the research subjects. They were divided into 3 groups by age (20-29 years, 30-39 years, ≥40 years), 2 groups by flying hours (<3 000 h, ≥3 000 h) and 3 groups by aircraft types (helicopter, transporter, fighter). The characteristics of thyroid nodule ultrasound images were retrospectively analyzed and the size, quantity and classification which defined in Chinese-thyroid imaging reporting and data system (C-TIRADS) of thyroid nodule were compared among the groups of different ages, flying hours, and aircraft types.Results:Among 306 naval flying personnel with thyroid noedules, 280 cases (91.50%) were small nodules (diameter <1 cm), 26 cases (8.50%) were large nodules (diameter ≥1 cm). One hundred and fifty-one cases (49.35%) were single nodules and 155 cases (50.65%) were multiple nodules. There were 135 cases (44.12%) with C-TIRADS grade 2 thyroid nodules, 158 cases (51.63%) with C-TIRADS grade 3 nodules, and 13 cases (4.25%) with C-TIRADS grade 4 nodules. There were significant differences in the size, number, classification of composition ratio of thyroid nodules among different age groups ( χ2=8.86, 5.94, 46.20, P=0.013, 0.051,<0.001). There were significant differences in the size and classification of composition ratio of thyroid nodules between different flying hours groups ( χ2=16.91, 24.35, both P<0.001). The proportion of C-TIRADS grade 4 nodules in the flying hours ≥3 000 h group was higher than that in the <3 000 h group, with a significant difference ( χ2=4.77, P=0.029).There were no significant differences in the size, number, classification of composition ratio of thyroid nodules among different aircraft types groups (all P>0.05). Conclusions:Age and flying hours have effects on size and classification of composition ratio of thyroid nodules in flying personnel, and age also has the effect on quantity. A scientific and systematic follow-up mechanism would be helpful to assess the risk of thyroid cancer and give early warning for the timely intervention.

Objective    To investigate the predictive value of right atrial myocardial fibrosis in the prognosis of isolated tricuspid regurgitation surgery after left heart valve surgery. Methods    The patients who underwent tricuspid valvuloplasty by the same operator in Guangdong Provincial People's Hospital from April 2016 to August 2021 due to long-term isolated severe tricuspid regurgitation after left heart valve surgery were included in the study. According to the degree of right atrial myocardial fibrosis, the patients were divided into three groups: a mild group, a moderate group, and a severe group. The clinical data of these patients were compared and analyzed. Results    A total of 75 patients were enrolled, including 16 males and 59 females with an average age of 57.0±8.4 years. There were 30 patients in the mild group, 29 patients in the moderate group and 16 patients in the severe group. In terms of the preoperative data, there were statistical differences in cardiac function grade, right atrial diameter, tricuspid incompetence area among the three groups (P<0.05). In terms of the postoperative data, there were statistical differences among the three groups in the cardiopulmonary bypass time, mechanical ventilation time, ICU monitoring time, complication rate and mortality (P<0.05). Further pairwise comparison showed that, compared with the mild group, the severe group had longer mechanical ventilation time (P=0.024), longer ICU monitoring time (P=0.003) and higher incidence of postoperative complications (P=0.024), while the moderate group had no statistical difference in all aspects (P>0.05); compared with the moderate group, the severe group had longer ICU monitoring time (P=0.021) and higher incidence of complications (P=0.006). Conclusion    The early outcome of tricuspid valvuloplasty in patients with isolated tricuspid regurgitation after left heart valve surgery with severe right atrial myocardial fibrosis is worse than that in the patients with mild and moderate fibrosis, suggesting that the degree of myocardial fibrosis in the right atrium can be a predictor of the effect of tricuspid regurgitation surgery and a judgement indicator of the surgery timing.

Objective:To analyze students' learning behavior in the teaching practice of the presentation-assimilation-discussion (PAD) class based on Xuexitong platform.Methods:The PAD class based on Xuexitong platform was applied to the course of child and adolescent health in the specialty of preventive medicine. And the data were collected from the platform to analyze students' learning behavior, including the number of visits and its rules, the completion rate and duration of homework submission, the completion rate of task points, and the number of students participating in discussions. Questionnaires were used to investigate students' evaluation of the learning effect. SPSS 17.0 was used for Mann-Whitney U test, Kruskal Wallis H, and Chi-square test. Results:A total of 99 students visited the platform 40 322 times over 84 days, with a peak on the day of the discussion class, with the highest number of visits from 16:00 to 20:00, and 29.3% (29/99) of them visited the platform for less than 40 days. The completion rate of homework submission was 98.0% (582/594), with 31.1% (181/582) of the person-times less than 6 hours of homework submission duration. The completion rate of task points was 99.0% (3 919/3 960), and the number of students participating in discussions was 3 (2,7). In total, 86.9% to 90.9% of the students thought that the five aspects of learning effect were partly or basically achieved.Conclusion:Students' learning behavior is good on the whole, but their participation in discussion is few, and some of them learn passively, which needs to be further improved.