In order to explore the possible role and molecular mechanism of the combined action of leech and bear bile in liver and gallbladder diseases, this study first used network pharmacology methods to screen the components and targets of leech and bear bile, as well as the related target genes of liver and gallbladder diseases. The selected key genes were subjected to interaction network and GO/KEGG enrichment analysis. Then, using sodium oleate induced HepG2 cell lipid deposition model and DL-ethionine induced mouse fatty liver model, the activity of leech and bear bile alone and in combination in reducing liver fat was evaluated in vitro and in vivo, and the expression of key pathway related proteins suggested by network pharmacology was detected by Western blot. The results of network pharmacology analysis showed that the active ingredients of leech and bear bile have 295 intersecting targets with liver and gallbladder related diseases, involving more than 200 signaling pathways, including the PI3K/Akt signaling pathway and phospholipase D signaling pathway closely related to glucose and lipid metabolism. The results of in vitro validation experiments showed that both leech and bear bile, alone and in combination, can significantly inhibit the lipid deposition induced by sodium oleate in human liver cells, reduce the triacylglycerol level in cell culture supernatant, and inhibit the lipid content in liver cells. The observation results of Nile red staining confocal microscopy showed that the combination of leech and bear bile had better activity in reducing lipid deposition in liver cells compared to using them alone. In a mouse fatty liver model, the combination of leech and bear bile can better reduce elevated organ indices, blood lipids, and liver lipid levels, as well as lower the levels of serum liver injury biomarkers. The animals used in this experiment and related disposal meet the requirements of animal welfare. Before the experiment, it was reviewed and approved by IACUC, Institute of Materia Medica, Chinese Academy of Medical Sciences. The Western blot experiment results showed that the combination of leech and bear bile can significantly upregulate the expression levels of p-PI3K and p-Akt proteins, and increase the p-PI3K/PI3K and p-Akt/Akt ratios, which is consistent with the predicted results of network pharmacology. The combination of leech and bear bile has great potential for treating fatty liver disease, and activating the PI3K/Akt pathway may be one of the important mechanisms for reducing lipid deposition in liver cells.

BACKGROUND:How to repair bone defect has been a clinical problem for a long time.The effective ingredients of traditional Chinese medicine have good biological activity and therapeutic effect,and the combination of effective ingredients of traditional Chinese medicine and tissue engineering materials has a broad prospect in the field of bone repair.The combination of different effective ingredients of traditional Chinese medicine and scaffolds has similarities in their functional relationships. OBJECTIVE:To collect the cases of the combinations of effective ingredients of traditional Chinese medicine and scaffolds,then analogize tissue engineering scaffolds and effective ingredients of traditional Chinese medicine into two types of traditional Chinese medicine that generate compatibility relationships based on the inspiration of the compatibility of seven emotions and summarize the relationship between the two based on their functional relationships. METHODS:Relevant articles from January 1998 to January 2024 were searched in PubMed and China National Knowledge Infrastructure(CNKI),using English search terms"traditional Chinese medicine,Chinese medicine,traditional Chinese medicine monomers,bone defect,bone repair,bone tissue engineering,tissue engineering,scaffold"and Chinese search terms"traditional Chinese medicine,effective ingredients of traditional Chinese medicine,traditional Chinese medicine monomers,bone tissue engineering,bone tissue engineering scaffold,scaffold,tissue engineering,bone defect,bone repair."A total of 88 articles were included for review and analysis. RESULTS AND CONCLUSION:(1)Both tissue engineering scaffold materials and active ingredients of traditional Chinese medicine have been widely used in the field of bone repair.Although they have obvious advantages in osteogenesis,there are still many shortcomings.Many studies are dedicated to preparing composite materials from the two,hoping to exert a detoxification and synergism through the interaction between the two.(2)Some drugs and materials can promote each other in osteogenesis,antibacterial,and promoting angiogenesis,enhancing their original effects.Inspired by the traditional concept of prescription compatibility,this article summarized it as a"Mutual promotion"relationship and provided examples to support it.(3)Some drugs can enhance the strength of materials,while some materials can achieve sustained release and controlled release effects,increase drug loading and stability,or achieve targeted delivery of drugs loaded on them.The article summarized this unilateral enhancement effect as a"Mutual assistance"relationship.(4)The combination of some traditional Chinese medicine and materials can reduce the toxic side effects of the other party.The article summarizes this detoxification relationship as"Mutual restraint and detoxification."(5)The article provided a new perspective on traditional Chinese medicine composite scaffolds,inspired by the seven emotions compatibility relationship and based on the classification of action relationships.It introduced traditional Chinese medicine concepts into the field of tissue engineering,providing new research ideas for subsequent researchers of composite scaffolds,and providing certain convenience in material selection and matching.

[Objective] To investigate the factors associated with alanine aminotransferase (ALT) abnormalities in multi-ethnic blood donors across five Zang autonomous prefectures in the plateau regions of Qinghai Province, and to provide evidence for ensuring blood safety and formulating screening strategies. [Methods] A retrospective analysis was performed on the ALT abnormal test results of blood donors in the Zang autonomous prefectures of Qinghai from 2022 to 2024. The correlations between ALT levels and factors including gender, age, altitude, and infectious markers were investigated. [Results] The overall ALT unqualified rate among blood donors in this region was 9.01%. Significant differences in ALT levels were observed across genders and age groups (P<0.05). Variations in ALT abnormality rates were also noted among different plateau regions (P<0.05). Overall, ALT values exhibited an increasing trend with rising altitude. The average ALT unqualified rates were 11.19% in Zang donors, 7.96% in Han donors, and 4.79% in donors from other ethnic groups (P<0.05). No statistically significant association was observed between ALT abnormality and the presence of HBV/HCV infectious markers (P>0.05). [Conclusion] In the plateau areas of Qinghai, multi-ethnic blood donors have a relatively high ALT levels and ALT unqualified rates, showing distinct regional characteristics. ALT elevation in voluntary blood donors is related to non-pathological factors such as gender, age, and dietary habits, but not to infectious indicators.

Objective: To explore the prospective association between multidimensional sleep indicators and the risk of newlyonset dental caries, providing a reference for childrens oral healthrelated sleep intervention. Methods: In October 2021, 1 417 students in grades 1 to 4 (aged 6 to 11) from two elementary schools in Bengbu, Anhui Province, were selected by cluster sampling method. Surveys and followup visits were conducted at baseline (T1), November 2022 (T2), May 2023 (T3), and November 2023 (T4), respectively, including parental questionnaires, oral health and physical examination. Bedtime, sleep duration, sleep midpoint, social jet lag, weekend catchup sleep, and sleep habits were collected and calculated. A multifactorial Cox proportional risk regression model was used to analyze the association between multidimensional sleep indicators and newlyonset caries in schoolaged children after 2 years. Results: The prevalence of dental caries in children was 65.1% at baseline, and the prevalence was 59.0% at the end of the 2year followup. Cox proportional risk regression model showed that for every 1point increase in the childrens bedtime resistance, nocturnal awakenings, parasomnias, and daytime sleepiness scores, the risk of newlyonset caries increased by 12% (HR=1.12, 95%CI=1.08-1.15), 22% (HR=1.22, 95%CI=1.15-1.29), 12% (HR=1.12, 95%CI=1.08-1.17), and 15% (HR=1.15, 95%CI=1.12-1.19), respectively; the risk of newlyonset caries increased by 23% for each 1 h increase in the length of weekend catchup sleep (HR=1.23, 95%CI=1.14 -1.33); compared with children who went to bed before 21:00 on school days, those who went to bed later than 22:00 had a 57% higher risk of newlyonset caries (HR=1.57, 95%CI=1.22-2.03). Compared to children who slept adequately (≥9 h/d), those with insufficient sleep had a 67% higher risk of new caries (HR=1.67, 95%CI=1.43-1.95) (P<0.01). Conclusions These findings suggest a significant association between sleep patterns/sleep disorders and the development of childhood dental caries. Incorporating sleep behavior optimization and sleep quality improvement into comprehensive caries prevention and oral health management protocols may represent a promising intervention strategy to enhance childrens oral health outcomes.

Objective: This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy. Materials and Methods: Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP. Results: The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001). Conclusion Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.

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: This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy. Materials and Methods: Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP. Results: The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001). Conclusion Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.

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: This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy. Materials and Methods: Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP. Results: The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001). Conclusion Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.

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.