OBJECTIVE To optimize the management model of drugs used in investigator-initiated trial （IIT）. METHODS With benchmarking analysis， based on the practical work experience of a tertiary specialized hospital in the field of IIT drug management in Shanghai， a thorough review was conducted， involving relevant laws， regulations， and academic literature to establish benchmark criteria and the evaluation standards. Starting from the initiation of IIT projects， a detailed comparative analysis of key processes was carried out， such as the receipt， storage， distribution， use and recycling of drugs for trial. The deficiencies in the current management of IIT drugs were reviewed in detail and a series of optimization suggestions were put forward. RESULTS It was found that the authorized records of drug management were missing， the training before project implementation was insufficient， and the records of receipt and acceptance of IIT drugs were incomplete. In light of these existing problems， improvement measures were put forward， including strengthening the training of drug administrators and stipulating that only drug administrators with pharmacist qualifications be eligible to inspect and accept drugs， etc. The related systems were improved， and 17 key points of quality control for the management of IIT drugs were developed. CONCLUSIONS A preliminary IIT drug management system for medical institutions has been established， which helps to improve the institutional X2023076） framework of medical institutions in this field.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Based on the theory of "spleen functions as wei qi"， this paper believes that the disease mechanism of allergic rhinitis （AR） in children is the nasal dysfunction caused by the loss of spleen's wei qi. The root cause of AR is the failure of splenic transportation as well as its inability to properly distribute nutrients. The inducement of AR is the invasion of pathogenic qi coupled with insecurity of the wei exterior. The key to AR recurrence lies in the deficiency of healthy qi and lingering of pathogenic qi， with pathogenic qi lodging inside the body. The treatment should adhere to the principle of helping the spleen restore wei qi. During the acute phase， the treatment should dispel wind， conso-lidate the wei qi， and relieve stuffy orifices， and the modified Qufeng Tongqiao Decoction （祛风通窍汤） is used. During the remission phase， the treatment should fortify the spleen， raise the clear， and harmonize the wei qi， and the modified Yuhan Decoction （御寒汤） is applied. During the recovery phase， the treatment should reinforce the healthy qi， consolidate the constitution， and strengthen the wei qi， and the modified Huangqi Jianzhong Decoction （黄芪建中汤） is employed.

Objective To explore the efficiency improvement in segmenting neural network with the application of Transformer + U-Net artificial intelligence (AI) and modeling with the application of Python scripts in three-dimensional (3D) printing brachytherapy. Methods A Transformer + U-Net AI neural network model was constructed, and Adam optimizer was used to ensure rapid gradient descent. Computed tomography or magnetic resonance imaging data of patients were standardized and processed as self-made data sets. The training set was used to train AI and the optimal result weight parameters were saved. The test set was used to evaluate the AI ability. Python programming language was used to write an automated script to obtain the output segmentation image and convert it to the STL file for import. The source applicator and needle could be automatically modeled. The time of automatic segmentation and modeling and the time of manual segmentation and modeling were entered by two people, and the difference was verified by paired t-test. Results Dice similarity coefficient (DSC), mean intersection over union (MIOU), and Hausdorff distance (HD95) were used for evaluation. DSC was 0.9341, MIOU was 0.8762, and mean HD95 was 2.516. The mean time of manual segmentation was 1187 s, and the mean time of AI segmentation was 145 s (P < 0.01). The mean time of manual modeling was 321 s, and the mean time of modeling with Python automated scripts was 18 s (P < 0.01). Conclusion The application of Transformer + U-Net automatic segmentation and Python automated scripts can effectively improve work efficiency in the 3D printing brachytherapy for cervical cancer.

Objective To study the antioxidant activity and organ protection of different components of Panax notoginseng polysaccharide(PNPS)in D-galactose-induced oxidative damage aging model mice.Methods KM mice were randomly divided into normal group,model group,vitamin C(VC)group(given 200 mg·kg-1 VC),crude polysaccharide from Panax notoginseng(CPPN)group,neutral polysaccharide from Panax notoginseng(NPPN)group and acidic polysaccharide from Panax notoginseng(APPN-Ⅰ,APPN-Ⅱ,APPN-Ⅲ)group(given 400 mg·kg-1 CPPN,NPPN,APPN-Ⅰ,APPN-Ⅱ,APPN-Ⅲ,respectively).Except for the normal group,oxidative injury aging mouse models were established by intraperitoneal injection of 1 g·kg-1 D-galactose.The mice were sacrificed after continuous administration for 42 days,and serum and liver homogenate were prepared.Malondialdehyde(MDA)was determined by thiobarbituric acid method;superoxide dismutase(SOD)was determined by tetrazole salt method;glutathione peroxidase(GSH-Px)was determined by double antibody sandwich method.Results Serum SOD in the normal group,model group,VC group,CPPN group,NPPN group and APPN-Ⅰ,APPN-Ⅱ,APPN-Ⅲ groups were(15.07±0.69),(12.79±1.51),(15.56±1.01),(13.69±0.96),(14.27±0.64),(14.31±0.99),(14.18±0.79)and(15.85±0.89)U·mL-1;serum GSH-Px were(105.35±4.97),(90.36±4.31),(111.51±7.00),(113.03±8.06),(118.77±5.19),(123.60±8.08),(131.65±3.60)and(149.22±13.32)ng·L-1;serum MDA were(1.72±0.26),(4.16±0.92),(2.26±0.59),(2.82±0.47),(2.46±0.50),(1.98±0.41),(2.39±0.39)and(2.07±0.24)nmol·mL-1;the liver SOD were(234.22±3.84),(205.04±7.28),(234.63±6.37),(214.99±17.66),(234.13±3.63),(234.63±3.44),(233.87±5.63)and(235.42±2.33)U·mgprot-1;liver GSH-Px were(274.27±23.72),(207.00±15.22),(257.68±16.39),(249.79±18.78),(252.62±10.92),(256.25±21.83),(261.20±17.52)and(263.16±17.98)ng·L-1;liver MDA were(35.70±3.52),(49.65±6.32),(36.15±2.48),(39.17±4.29),(37.40±6.19),(35.34±4.06)and(35.90±5.36),(33.31±7.64)nmol·mgprot-1.Compared with the normal group,SOD,GSH-Px in serum and liver of mice in the model group were significantly reduced,and the content of MDA was significantly increased(all P＜0.01).After treatment with different components of Panax notoginseng polysaccharide,the oxidative indicators in mice were significantly improved,among which APPN-Ⅲ have the best antioxidant activity,which could significantly increase the activities of SOD,GSH-Px in serum and liver,and reduce the content of MDA(all P＜0.01).Conclusion Different components of Panax notoginseng polysaccharide have antioxidant activity and organ protection in vivo,among which APPN-Ⅲ has the best antioxidant activity and has a good organ protection effect.

Quercetin can mediate the activation of mitogen-activated protein kinase(MAPK)signaling pathways to prevent osteoporosis(OP).This paper comprehensively discusses the interrelationship between MAPK and osteoporosis-related cells based on the latest domestic and international research.Additionally,it elucidates the research progress of quercetin in mediating the MAPK signaling pathway for OP prevention.The aim is to provide an effective foundation for the clinical prevention and treatment of OP and the in-depth development of quercetin.