OBJECTIVE To investigate the mechanism of Shenling baizhu san （SLBZS） in ameliorating ulcerative colitis （UC）. METHODS Mice were randomly divided into normal group， model group， and low-， medium-， high-dose SLBZS groups （3， 6， 12 g/kg）， with 10 mice in each group. Except for the normal group， mice in other groups were given free access to 3% dextran sulfate sodium solution for 7 days to establish UC models. Simultaneously， mice in each group were intragastrically administered corresponding medicinal liquid or double-distilled water once a day for consecutive 7 days. After the last administration， the histopathological morphology of colon tissues was observed； the serum levels of inflammatory factors including tumor necrosis factor-α （TNF-α）， interleukin-1β （IL-1β） and IL-18 were detected； the total bile acid contents in liver， gallbladder and colon tissues were determined； the expression level of NOD-like receptor family pyrin domain-containing protein 3 （NLRP3） in colon tissues was tested. The expression levels of flora metabolism-related proteins [G protein-coupled receptor 41（GPR41），GPR43，farnesoid X receptor （FXR）， G protein-coupled bile acid receptor 1 （TGR5）， flavin-containing monooxygenase 3 （FMO3）， cytochrome P450 family 27 subfamily A member 1 （CYP27A1）， CYP7A1] in liver or colon tissues， as well as the proteins related to Toll-like receptor 4 （TLR4）/nuclear factor-κB （NF-κB）/NLRP3 inflammatory axis [TLR4， NF-κB， phosphorylated NF-κB （p-NF-κB）， myeloid differentiation factor 88 （MyD88）， NLRP3， apoptosis-associated speck-like protein containing a CARD （ASC）， caspase-1] in colon tissues were measured. RESULTS Compared with the model group， the colon tissue injury and inflammatory cell infiltration were alleviated in medium- and high-dose SLBZS groups. The serum levels of TNF-α， IL-1β and IL-18， total bile acid contents in liver and colon tissues， as well as the protein expression levels of FMO3 and CYP7A1 in liver tissues， TLR4， p-NF-κB， NF-κB， MyD88， NLRP3， ASC and caspase-1 in colon tissues were significantly decreased （P＜0.05）. Meanwhile， the total bile acid content in gallbladder， the protein expression levels of GPR41 and GPR43 in colon tissues， along with CYP27A1， FXR and TGR5 in liver tissues were significantly increased （P＜0.05）. CONCLUSIONS SLBZS may relieve colonic inflammatory injury and ameliorate UC by regulating the expression of flora metabolism-related proteins and inhibiting the abnormal activation of TLR4/NF-κB/NLRP3 inflammatory axis.

Aim To investigate the effect of Huangqi injection(HI)and Huangqi oral solution(HO)on cisplatin-induced nephrotoxicity(CIN)based on un-targeted metabolomics technology and the underlying mechanisms.Methods Sprague Dawley(SD)rats were randomly divided into the blank group,cisplatin(CDDP)model group,HI treatment group,and HO treatment group,then the CIN model was built with low dose multiple intraperitoneal injections of CDDP.Pre-liminary evaluation of the renal protective efficacy of HI and HO was performed by measuring serum creatinine(Scr),blood urea nitrogen(BUN),and organ indi-ces.Further screening and identification of potential biomarkers(PBs)related to CIN and HI/HO pharma-cological effects were attained through metabolomics studies of renal tissues,and pathway enrichment analy-sis was conducted.Results HI and HO significantly restored the abnormal increase in renal function indica-tors and abnormal decrease in organ indices caused by CDDP,as well as significantly improved the abnormal renal metabolic profile induced by CDDP,indicating that both HI and HO had good alleviating effects on CIN.HI significantly reversed 47 out of 54 CIN related PBs,mainly involving metabolic pathways such as glycerophospholipid metabolism,tryptophan metabo-lism,pantothenate and CoA biosynthesis;HO signifi-cantly reversed 18 out of 54 CIN related PBs,mainly involving metabolic pathways such as taurine and hypo-taurine metabolism,ascorbate and aldarate metabo-lism,pentose and glucuronate interconversions.Con-clusions Both HI and HO have significant alleviating effects on CIN.In the short term,HI salleviating effect is superior to that of HO.Overall,the mechanisms by which both alleviate CIN are mainly related to regula-ting lipid metabolism,amino acid metabolism.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Aim To investigate the effect of Huangqi injection(HI)and Huangqi oral solution(HO)on cisplatin-induced nephrotoxicity(CIN)based on un-targeted metabolomics technology and the underlying mechanisms.Methods Sprague Dawley(SD)rats were randomly divided into the blank group,cisplatin(CDDP)model group,HI treatment group,and HO treatment group,then the CIN model was built with low dose multiple intraperitoneal injections of CDDP.Pre-liminary evaluation of the renal protective efficacy of HI and HO was performed by measuring serum creatinine(Scr),blood urea nitrogen(BUN),and organ indi-ces.Further screening and identification of potential biomarkers(PBs)related to CIN and HI/HO pharma-cological effects were attained through metabolomics studies of renal tissues,and pathway enrichment analy-sis was conducted.Results HI and HO significantly restored the abnormal increase in renal function indica-tors and abnormal decrease in organ indices caused by CDDP,as well as significantly improved the abnormal renal metabolic profile induced by CDDP,indicating that both HI and HO had good alleviating effects on CIN.HI significantly reversed 47 out of 54 CIN related PBs,mainly involving metabolic pathways such as glycerophospholipid metabolism,tryptophan metabo-lism,pantothenate and CoA biosynthesis;HO signifi-cantly reversed 18 out of 54 CIN related PBs,mainly involving metabolic pathways such as taurine and hypo-taurine metabolism,ascorbate and aldarate metabo-lism,pentose and glucuronate interconversions.Con-clusions Both HI and HO have significant alleviating effects on CIN.In the short term,HI salleviating effect is superior to that of HO.Overall,the mechanisms by which both alleviate CIN are mainly related to regula-ting lipid metabolism,amino acid metabolism.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. Methods: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. Results: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. Conclusion Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.

Objective: : Blood-blister aneurysms (BBAs) of the internal carotid artery (ICA) are challenging lesions with high morbidity and mortality rates. Although research on BBAs is well documented in different populations, the study of BBAs in the Tibetan population is extremely rare. This study aimed to evaluate the characteristics of BBAs and analyze the treatment modalities and long-term outcomes in the Tibetan population in comparison with the Han population. Methods: : The characteristics of patients with BBAs of the ICA from January 2009 to January 2021 at our institution were reviewed. The features of aneurysms, treatment modalities, complications, and follow-up outcomes were retrospectively analyzed. Results: : A total of 130 patients (41 Tibetan and 89 Han patients) with BBAs of the ICA who underwent treatment were enrolled. Compared with the Han group, the Tibetan group significantly demonstrated a high ratio of BBAs among ICAs (8.6%, 41/477 vs. 1.6%, 89/5563; p<0.05), a high ratio of vasospasm (34.1%, 14/41 vs. 6.7%, 6/89; p=0.001), a high risk of ischemic events (43.9%, 18/41 vs. 22.5%, 20/89; p<0.05), and a low ratio of good outcomes (modified Rankin scale, 0–2) at the 1-year follow-up (51.2%, 21/41 vs. 74.2%, 66/89; p<0.05). The multivariate regression model showed that ischemic events significantly contributed to the prediction of outcomes at 1 year. Further analysis revealed that microsurgery and vasospasm were associated with ischemic events. Conclusion : In comparison with Han patients, the Tibetan population had a high ratio of BBA occurrence, a high incidence of ischemic events, and a high ratio of poor outcomes. The endovascular approach showed more benefits in BBA patients.

Objective To explore the potential value of three-dimensional fast spin echo(3D-SPACE)combined with multilayer spiral CT(MSCT)in the diagnosis of knee cruciate ligament injury,to provide a new direction for the optimization of subsequent clinical diagnosis.Methods A total of 120 patients with knee cruciate ligament injury were treated from April 2020 to April 2021,aged from 21 to 68 with an average of(41.52±4.13)years old.For all patients,separate MSCT scanner scans,3D-SPACE sequence scans alone and 3D-SPACE sequence combined with MSCT scans were used.The injury and classifica-tion of the anterior and posterior cruciate ligament of the knee were compared,the length of the anterior-medial bundle and posterolateral bundle and its angle of the knee with the horizontal plane were observed,the diagnostic value of 3 diagnostic methods in knee cruciate ligament injury were determined.Results There was no significant difference between the 3D-SPACE sequence scan alone and the MSCT test alone on the total diagnostic rate and grading total diagnostic rate(P＞0.05).The total diagnostic rate and grading total diagnostic rate of 3D-SPACE scan combined with MSCT were significantly higher than those of 3D-SPACE scan or MSCT alone(P＜0.05).The 3D-SPACE sequence scan alone and the MSCT detection alone had no signifi-cant difference in the measurement values related to the anterior and posterior cruciate ligaments of the knee joint(P＞0.05).3D-SPACE sequence scanning combined with MSCT detection on the knee joint anterior and posterior cruciate ligament related mea-surements were significantly higher than the 3D-SPACE sequence scan or MSCT detection alone(P＜0.05).The area under the ROC curve estimated by 3D-SPACE sequence scanning combined with MSCT was 0.960,which was significantly higher than that of 3D-SPACE sequence scanning and MSCT alone evaluating the area under the ROC curve line of 0.756 and 0.795.The com-bined 3D-SPACE sequence scanning and 3D-SPACE sequence scanning MSCT analysis and prediction models were statistically different(Z=2.236,P＜0.05),and MSCT alone and 3D-SPACE sequence scanning combined with MSCT analysis and prediction models were statistically different(Z=2.653,P＜0.05).Conclusion The application of 3D-SPACE sequence combined with MSCT scanning for knee cruciate ligament injury can improve the diagnosis rate of patients with knee cruciate ligament injury.It can be used as a diagnostic tool for patients with knee cruciate ligament injury and is worthy of clinical application.

Objective: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. Methods: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. Results: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. Conclusion Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.