1.Expert consensus on evaluation index system construction for new traditional Chinese medicine(TCM) from TCM clinical practice in medical institutions.
Li LIU ; Lei ZHANG ; Wei-An YUAN ; Zhong-Qi YANG ; Jun-Hua ZHANG ; Bao-He WANG ; Si-Yuan HU ; Zu-Guang YE ; Ling HAN ; Yue-Hua ZHOU ; Zi-Feng YANG ; Rui GAO ; Ming YANG ; Ting WANG ; Jie-Lai XIA ; Shi-Shan YU ; Xiao-Hui FAN ; Hua HUA ; Jia HE ; Yin LU ; Zhong WANG ; Jin-Hui DOU ; Geng LI ; Yu DONG ; Hao YU ; Li-Ping QU ; Jian-Yuan TANG
China Journal of Chinese Materia Medica 2025;50(12):3474-3482
Medical institutions, with their clinical practice foundation and abundant human use experience data, have become important carriers for the inheritance and innovation of traditional Chinese medicine(TCM) and the "cradles" of the preparation of new TCM. To effectively promote the transformation of new TCM originating from the TCM clinical practice in medical institutions and establish an effective evaluation index system for the transformation of new TCM conforming to the characteristics of TCM, consensus experts adopted the literature research, questionnaire survey, Delphi method, etc. By focusing on the policy and technical evaluation of new TCM originating from the TCM clinical practice in medical institutions, a comprehensive evaluation from the dimensions of drug safety, efficacy, feasibility, and characteristic advantages was conducted, thus forming a comprehensive evaluation system with four primary indicators and 37 secondary indicators. The expert consensus reached aims to encourage medical institutions at all levels to continuously improve the high-quality research and development and transformation of new TCM originating from the TCM clinical practice in medical institutions and targeted at clinical needs, so as to provide a decision-making basis for the preparation, selection, cultivation, and transformation of new TCM for medical institutions, improve the development efficiency of new TCM, and precisely respond to the public medication needs.
Medicine, Chinese Traditional/standards*
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Humans
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Consensus
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Drugs, Chinese Herbal/therapeutic use*
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Surveys and Questionnaires
2.Prevotella nigrescens exacerbates periodontal inflammation and impairs cognitive function in mice.
Qi CHEN ; Tiantian XIA ; Yongqiang ZHOU ; Mingyang CHANG ; Nan HU ; Yanmei YANG ; Zhong LI ; Yue GAO ; Bin GU
Journal of Southern Medical University 2025;45(3):453-460
OBJECTIVES:
To investigate the effects of periodontitis induced by Prevotella nigrescens (Pn) combined with ligation on cognitive functions in mice.
METHODS:
Twenty-four C57BL/6J mice were randomly divided into control group, ligation group, and ligation + Pn treatment (P+Pn) group. Experimental periodontitis was induced by silk ligation of the first molars followed by topical application of Pn for 6 weeks. After modeling, alveolar bone resorption was assessed using micro-CT and histological analysis. Learning and memory abilities of the mice were evaluated using open field test (OFT), novel object recognition test (NORT), and Morris water maze test (MWM). Seven weeks after the start of modeling, the mice were sacrificed for examining histopathological changes in the hippocampus using HE and Nissl staining.
RESULTS:
After 6 weeks of molar ligation, micro-CT revealed horizontal alveolar bone resorption and furcation exposure in the mice, and histological analysis showed apical migration of the junctional epithelium, epithelial ridge hyperplasia, and lymphocyte infiltration, and these changes were obviously worsened in P+Pn group. Alveolar bone height decreased significantly in both ligation groups compared to the control group. Cognitive tests showed that the mice in both of the ligation groups traveled shorter distances in OFT, showed reduced novel object preference in NORT, and exhibited longer escape latencies in MWM, and the mice in P+Pn group had significantly poorer performances in the tests. Histologically, obvious neuronal cytoplasmic degeneration, necrosis, nuclear pyknosis, vacuolation, and reduced Nissl bodies and viable neurons were observed in the hippocampal regions of the mice in the two ligation groups.
CONCLUSIONS
Pn infection aggravates alveolar bone destruction, accelerates necrosis and causes morphological abnormalities of neuronal cells in the hippocampus to reduce cognitive functions of mice with periodontitis.
Animals
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Periodontitis/microbiology*
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Mice
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Mice, Inbred C57BL
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Cognition
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Alveolar Bone Loss
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Hippocampus/pathology*
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Male
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Inflammation
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Maze Learning
4.Prevotella nigrescens exacerbates periodontal inflammation and impairs cognitive function in mice
Qi CHEN ; Tiantian XIA ; Yongqiang ZHOU ; Mingyang CHANG ; Nan HU ; Yanmei YANG ; Zhong LI ; Yue GAO ; Bin GU
Journal of Southern Medical University 2025;45(3):453-460
Objective To investigate the effects of periodontitis induced by Prevotella nigrescens(Pn)combined with ligation on cognitive functions in mice.Methods Twenty-four C57BL/6J mice were randomly divided into control group,ligation group,and ligation+Pn treatment(P+Pn)group.Experimental periodontitis was induced by silk ligation of the first molars followed by topical application of Pn for 6 weeks.After modeling,alveolar bone resorption was assessed using micro-CT and histological analysis.Learning and memory abilities of the mice were evaluated using open field test(OFT),novel object recognition test(NORT),and Morris water maze test(MWM).Seven weeks after the start of modeling,the mice were sacrificed for examining histopathological changes in the hippocampus using HE and Nissl staining.Results After 6 weeks of molar ligation,micro-CT revealed horizontal alveolar bone resorption and furcation exposure in the mice,and histological analysis showed apical migration of the junctional epithelium,epithelial ridge hyperplasia,and lymphocyte infiltration,and these changes were obviously worsened in P+Pn group.Alveolar bone height decreased significantly in both ligation groups compared to the control group.Cognitive tests showed that the mice in both of the ligation groups traveled shorter distances in OFT,showed reduced novel object preference in NORT,and exhibited longer escape latencies in MWM,and the mice in P+Pn group had significantly poorer performances in the tests.Histologically,obvious neuronal cytoplasmic degeneration,necrosis,nuclear pyknosis,vacuolation,and reduced Nissl bodies and viable neurons were observed in the hippocampal regions of the mice in the two ligation groups.Conclusion Pn infection aggravates alveolar bone destruction,accelerates necrosis and causes morphological abnormalities of neuronal cells in the hippocampus to reduce cognitive functions of mice with periodontitis.
5.Heart-sparing strategy for breast cancer radiotherapy based on nnU-Net: regional optimization and automatic segmentation
Jinghan HUANG ; Maidina BATUER ; Chuanghui ZHOU ; Zhi ZHANG ; Limei DENG ; Yuan XU ; Junyuan ZHONG ; Linghong ZHOU ; Xia LI ; Genggeng QIN
Chinese Journal of Radiation Oncology 2025;34(4):355-362
Objective:To investigate the feasibility and optimal expansion width of replacing the left anterior descending coronary artery (LADCA) with the region of heart sparing (RHS) to reduce cardiac radiation dose during breast cancer radiotherapy.Methods:Retrospective analysis was conducted on data from 88 patients with left-sided breast cancer who underwent radiotherapy at 2 centers: Nanfang Hospital of Southern Medical University (50 cases for the training set, 15 cases for the internal test set) and Ganzhou Hospital of Nanfang Hospital (23 cases for the external test set) from March 2022 to January 2024. All patients had left-sided invasive ductal carcinoma with axillary lymph node metastasis, and had undergone modified radical mastectomy and chemotherapy. Based on simulation CT images, 2 radiation oncologists delineated the LADCA and 8 RHSs. The RHSs were delineated by expanding the LADCA contour by 0.5 cm increments, totaling 8 expansions. The RHS widths were defined as 0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 3.5, and 4.0 cm. The nnU-Net model was trained for 3D automatic segmentation of the LADCA and RHSs. Model performance was evaluated using the Dice similarity coefficient (DSC), relative volume error (RVE), sensitivity, specificity, and 95% Hausdorff distance (HD95). Additionally, the minimum, maximum, and average relative dose variations (RDV) as well as V5% and V20% indicators were calculated for the LADCA and each RHS. Correlation analysis was performed using the least squares regression, with the slope and coefficient of determination ( R2) employed to evaluate the accuracy of the model fitting, the relationship between the LADCA and RHS, and the degree of their correlation, thereby assessing the substitutive effect of the RHS for the LADCA. Results:The DSC for the LADCA was 0.415, while the DSCs for RHS widths of 0.5 cm and 4.0 cm were 0.718 and 0.835, respectively. Overall, the automatic segmentation performance improved with increasing RHS width. The DSC, RVE, sensitivity, specificity, and HD95 for the external test set were largely consistent with those of the internal test set, demonstrating the model's good robustness across different datasets. All RDVmin values were negative, while RDVmax and RDVmean showed a positive correlation with RHS width. RDVmean increased from 39.01% to 75.89% as the RHS width increased. In the correlation analysis, the slopes for RHS widths of 1.5 cm and 2.0 cm were 0.95 and 1.05, respectively, with R2 values and coefficients of variation of 0.79 and 0.73, and 21.11% and 24.03%, respectively. Conclusions:The automatic segmentation model trained on nnU-Net can accurately segment RHSs. Based on geometric and dosimetric indicators, a 1.5 cm-wide RHS is the most suitable substitute for the LADCA, effectively limiting the radiation dose to the LADCA without compromising target dose coverage.
6.Deep learning-based dynamic generation of uterine geometry for cervical cancer radiotherapy
Batuer MAIDINA ; Jinghan HUANG ; Chuanghui ZHOU ; Junyuan ZHONG ; Lei YANG ; Linghong ZHOU ; Xia LI ; Genggeng QIN
Chinese Journal of Radiation Oncology 2025;34(6):585-593
Objective:To propose a semi-supervised learning method for dynamic generation of organ geometric contours, leveraging bladder volume variations and its relative position to the uterus to accurately generate uterine contours in cervical cancer radiotherapy.Methods:A total of 120 sets of pelvic planning CT images (including both full and empty bladder scans) from 60 patients with cervical cancer treated at the Department of Radiation Oncology, Nanfang Hospital of Southern Medical University between January and December 2023 were retrospectively collected. A conditional generative adversarial network (CGAN) based on a squeeze-and-excitation channel attention mechanism was proposed to accurately generate uterine geometric contours under varying bladder filling states. By emphasizing the critical spatial relationships between the bladder and uterus, the model learned the relative anatomical positions of pelvic organs and their motion correlations. The generative performance was quantitatively evaluated using the average Dice similarity coefficient (DSC), intersection over union (IoU), and the 95 th percentile Hausdorff distance (HD95), and was compared with GAN model, CGAN model, and Pix2Pix model. Pairwise comparisons were perfomed by paired-sample t-test. Results:The proposed SE-CGAN model achieved the best performance on the test set, with DSC of 0.83±0.09, IoU of 0.71±0.05, HD95 of (6.74±1.23) mm, improving DSC by 7.5%, 4.9%, and 3.6% compared to the GAN, CGAN, and Pix2Pix models, respectively (all P<0.001), and reducing the mean HD95 by 32.9%-45.3%. Statistical analysis revealed significant differences between SE-CGAN model and the other 3 baseline models, whereas no significant difference was observed between CGAN model and Pix2Pix model. The visualization results further demonstrated that the GAN model produced uterine contours deviated greatly from the real shape, and the edge was fuzzy; CGAN and Pix2Pix model achieved better overlap but lacked of precision in boundary reconstruction. In contrast, the contours generated by SE-CGAN model closely matched the ground truth with clearly defined edges, indicating superior reconstruction accuracy. Conclusions:In this study, we propose a generative adversarial network method that establishes a dynamic modulation mechanism by which the bladder state influences the uterine geometric contour, enabling accurate generation of the uterine contours from the bladder contours of any given localization CT scan. This approach effectively addresses the uncertainty in radiotherapy target delineation caused by pelvic organ motion.
7.Heart-sparing strategy for breast cancer radiotherapy based on nnU-Net: regional optimization and automatic segmentation
Jinghan HUANG ; Maidina BATUER ; Chuanghui ZHOU ; Zhi ZHANG ; Limei DENG ; Yuan XU ; Junyuan ZHONG ; Linghong ZHOU ; Xia LI ; Genggeng QIN
Chinese Journal of Radiation Oncology 2025;34(4):355-362
Objective:To investigate the feasibility and optimal expansion width of replacing the left anterior descending coronary artery (LADCA) with the region of heart sparing (RHS) to reduce cardiac radiation dose during breast cancer radiotherapy.Methods:Retrospective analysis was conducted on data from 88 patients with left-sided breast cancer who underwent radiotherapy at 2 centers: Nanfang Hospital of Southern Medical University (50 cases for the training set, 15 cases for the internal test set) and Ganzhou Hospital of Nanfang Hospital (23 cases for the external test set) from March 2022 to January 2024. All patients had left-sided invasive ductal carcinoma with axillary lymph node metastasis, and had undergone modified radical mastectomy and chemotherapy. Based on simulation CT images, 2 radiation oncologists delineated the LADCA and 8 RHSs. The RHSs were delineated by expanding the LADCA contour by 0.5 cm increments, totaling 8 expansions. The RHS widths were defined as 0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 3.5, and 4.0 cm. The nnU-Net model was trained for 3D automatic segmentation of the LADCA and RHSs. Model performance was evaluated using the Dice similarity coefficient (DSC), relative volume error (RVE), sensitivity, specificity, and 95% Hausdorff distance (HD95). Additionally, the minimum, maximum, and average relative dose variations (RDV) as well as V5% and V20% indicators were calculated for the LADCA and each RHS. Correlation analysis was performed using the least squares regression, with the slope and coefficient of determination ( R2) employed to evaluate the accuracy of the model fitting, the relationship between the LADCA and RHS, and the degree of their correlation, thereby assessing the substitutive effect of the RHS for the LADCA. Results:The DSC for the LADCA was 0.415, while the DSCs for RHS widths of 0.5 cm and 4.0 cm were 0.718 and 0.835, respectively. Overall, the automatic segmentation performance improved with increasing RHS width. The DSC, RVE, sensitivity, specificity, and HD95 for the external test set were largely consistent with those of the internal test set, demonstrating the model's good robustness across different datasets. All RDVmin values were negative, while RDVmax and RDVmean showed a positive correlation with RHS width. RDVmean increased from 39.01% to 75.89% as the RHS width increased. In the correlation analysis, the slopes for RHS widths of 1.5 cm and 2.0 cm were 0.95 and 1.05, respectively, with R2 values and coefficients of variation of 0.79 and 0.73, and 21.11% and 24.03%, respectively. Conclusions:The automatic segmentation model trained on nnU-Net can accurately segment RHSs. Based on geometric and dosimetric indicators, a 1.5 cm-wide RHS is the most suitable substitute for the LADCA, effectively limiting the radiation dose to the LADCA without compromising target dose coverage.
8.Deep learning-based dynamic generation of uterine geometry for cervical cancer radiotherapy
Batuer MAIDINA ; Jinghan HUANG ; Chuanghui ZHOU ; Junyuan ZHONG ; Lei YANG ; Linghong ZHOU ; Xia LI ; Genggeng QIN
Chinese Journal of Radiation Oncology 2025;34(6):585-593
Objective:To propose a semi-supervised learning method for dynamic generation of organ geometric contours, leveraging bladder volume variations and its relative position to the uterus to accurately generate uterine contours in cervical cancer radiotherapy.Methods:A total of 120 sets of pelvic planning CT images (including both full and empty bladder scans) from 60 patients with cervical cancer treated at the Department of Radiation Oncology, Nanfang Hospital of Southern Medical University between January and December 2023 were retrospectively collected. A conditional generative adversarial network (CGAN) based on a squeeze-and-excitation channel attention mechanism was proposed to accurately generate uterine geometric contours under varying bladder filling states. By emphasizing the critical spatial relationships between the bladder and uterus, the model learned the relative anatomical positions of pelvic organs and their motion correlations. The generative performance was quantitatively evaluated using the average Dice similarity coefficient (DSC), intersection over union (IoU), and the 95 th percentile Hausdorff distance (HD95), and was compared with GAN model, CGAN model, and Pix2Pix model. Pairwise comparisons were perfomed by paired-sample t-test. Results:The proposed SE-CGAN model achieved the best performance on the test set, with DSC of 0.83±0.09, IoU of 0.71±0.05, HD95 of (6.74±1.23) mm, improving DSC by 7.5%, 4.9%, and 3.6% compared to the GAN, CGAN, and Pix2Pix models, respectively (all P<0.001), and reducing the mean HD95 by 32.9%-45.3%. Statistical analysis revealed significant differences between SE-CGAN model and the other 3 baseline models, whereas no significant difference was observed between CGAN model and Pix2Pix model. The visualization results further demonstrated that the GAN model produced uterine contours deviated greatly from the real shape, and the edge was fuzzy; CGAN and Pix2Pix model achieved better overlap but lacked of precision in boundary reconstruction. In contrast, the contours generated by SE-CGAN model closely matched the ground truth with clearly defined edges, indicating superior reconstruction accuracy. Conclusions:In this study, we propose a generative adversarial network method that establishes a dynamic modulation mechanism by which the bladder state influences the uterine geometric contour, enabling accurate generation of the uterine contours from the bladder contours of any given localization CT scan. This approach effectively addresses the uncertainty in radiotherapy target delineation caused by pelvic organ motion.
9.Pathogenicity of Escherichia coli causing calf encephalitis to cells and mice
Shirong DANG ; Yiheng CAO ; Kaiwen JIA ; Meiqi JIANG ; Xia ZHOU ; Tongzhong WU ; Xin HUANG ; Fagang ZHONG ; Mengli HAN ; Qian ZHANG ; Xiaolan WANG ; Zijie WANG
Chinese Journal of Veterinary Science 2024;44(9):1948-1956
The purpose of this study was to investigate the damage mechanism of pathogenic E.coli on mouse brain microvascular endothelial cells(BMEC cells)and mouse alveolar macrophages(MH-S cells),as well as the lung and brain of healthy mice.In this study,BMEC cells and MH-S cells were infected with pathogenic E.coli strains,and cell morphological changes were observed.Plate counting method was used to detect the adhesion and invasion ability of the strains to cells and the number of bacteria in the lungs and brains of mice.RT-qPCR was used to detect the ex-pression of TNF-α,IL-1β and IL-6 genes in cells and mouse organs at different time periods.West-ern blot was used to detect the expression of p-NF-κB,p-JAK2 and p-STAT3 proteins related to inflammation in cells and mouse organs after infection.The results showed that the cell culture medium of the infection group was turbid,the cell vision became dark and blurred,some cells shrank and died,and more fragments were produced.The adhesion rate and invasion rate of BMEC cells at 3 h were significantly lower than those at 6 h(P<0.050),and the adhesion rate and inva-sion rate of MH-S cells at 3 h were significantly higher than those at 6 h(P<0.010).Infected mice had a large area of swelling and bleeding in the brain,and the lungs had different degrees of swell-ing and bleeding.The bacterial load in the brain and lung was the highest at 12 h.Compared with the control group,the mRNA expression levels of IL-1β,IL-6 and TNF-α in the infection group were significantly increased at 3 h and 6 h(P<0.050),and the mRNA expression levels of inflam-matory factors in BMEC cells and MH-S cells were the highest at 6 and 3 h,respectively.The mR-NA expression of inflammatory factors in the brain and lung of infected mice showed a trend of in-creasing first and then decreasing with time,with the highest expression at 12 h after infection.The expression levels of p-NF-κB protein in BMEC cells,MH-S cells,lung and brain tissues of mice in the infection group were significantly higher than those in the control group(P<0.001),and the expression levels of p-JAK2 protein and p-STAT3 protein were significantly lower than those in the control group(P<0.050).The above results showed that pathogenic E.coli could adhere and invade BMEC cells and MH-S cells,colonize in lung and brain tissues of mice,promote the expres-sion of NF-κB protein in cells and tissues,inhibit the expression of JAK2 protein and STAT3 pro-tein,and then stimulate cells and tissues to produce inflammatory response.
10.Factors affecting target volume in adaptive radiotherapy for locally advanced nasopharyngeal carcinoma
Shuhui DONG ; Wenyan YAO ; Mengxue HE ; Ziyue ZHONG ; Yupeng ZHOU ; Senkui XU ; Weixiong XIA
Chinese Journal of Medical Physics 2024;41(7):798-802
Objective To investigate the relationships of pre-radiotherapy body weight,gender,age,EBVDNA,hemoglobin,plasma albumin,and induction chemotherapy regimen with the changes of target area and lymph node volume in adaptive radiotherapy,so as to provide a reference for the timing and population selection of adaptive radiotherapy.Methods A retrospective analysis was conducted on 34 patients who received the first course of radiotherapy at Sun Yat-sen University Cancer Center from January 2022 to November 2022.All patients underwent CT scans again after 20 sessions of radiotherapy for developing the secondary radiotherapy plans.The body weight,gender,age,tumor stage,hemoglobin,plasma albumin,induction chemotherapy regimen,and EBVDNA were collected.Results The tumor volume reduction in the primary focus was more evident in patients with pre-treatment plasma albumin≥40 g/L than in those with pre-treatment plasma albumin<40 g/L(t=3.971,P=0.001),and in patients with pretreatment EBVDNA≤4000 copies/mL than in those with pretreatment EBVDNA>4000 copies/mL(t=4.080,P=0.001).Pearson analysis showed that GTVnx volume difference was positively correlated with pre-radiotherapy GTVnx volume(r=0.444,P=0.009),right parotid gland volume difference(r=0.737,P<0.001),left parotid gland volume difference(r=0.435,P=0.010),and hemoglobin(r=0.722,P<0.001).Conclusion The reduction in tumor volume during radiotherapy is more pronounced in nasopharyngeal cancer patients with normal plasma albumin level and those with pretreatment EBVDNA≤4000 copies/mL.The pre-radiotherapy treatment volume of primary focus,parotid gland volume change before and after radiotherapy,and pre-radiotherapy EBVDNA,hemoglobin and plasma albumin levels can be used to predict the degree of tumor volume shrinkage during radiotherapy,providing a reference for the selection of the timing of adaptive radiotherapy for nasopharyngeal carcinoma.

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