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.

ObjectiveTo investigate the effect of Danggui Shaoyaosan on ferroptosis in the rat model of non-alcoholic fatty liver disease （NAFLD） and explore the underlying mechanism based on the nuclear factor E₂-related factor 2 （Nrf2）/solute carrier family 7 member 11 （SLC7A11）/glutathione peroxidase 4 （GPX4） signaling pathway. MethodsThe sixty SD rats were randomly grouped as follows： control， model， Yishanfu （0.144 g·kg^-1）， and low-， medium-， and high-dose （2.44， 4.88， and 9.76 g·kg^-1， respectively） Danggui Shaoyaosan. A high-fat diet was used to establish the rat model of NAFLD. After 12 weeks of modeling， rats were treated with corresponding agents for 4 weeks. Then， the body weight and liver weight were measured， and the liver index was calculated. At the same time， serum and liver samples were collected. The levels or activities of total cholesterol （TC）， triglycerides （TG）， alanine aminotransferase （ALT）， aspartate aminotransferase （AST）， and Fe²⁺ in the serum and TC， TG， free fatty acids （FFA）， malondialdehyde （MDA）， superoxide dismutase （SOD）， glutathione peroxidase （GPX）， and Fe²⁺ in the liver were measured. Hematoxylin-eosin staining and oil red O staining were employed to observe the pathological changes in the liver. Immunofluorescence was used to assess the reactive oxygen species （ROS） content in the liver. Mitochondrial morphology was observed by transmission electron microscopy. The protein levels of Nrf2， SLC7A11， GPX4， transferrin receptor 1 （TFR1）， and divalent metal transporter 1 （DMT1） in the liver were determined by Western blot. ResultsCompared with the control group， the model group showed increases in the body weight， liver weight， liver index， levels or activities of TC， TG， ALT， AST， and Fe²⁺ in the serum， levels of TC， TG， FFA， MDA， Fe²⁺， and ROS in the liver， and protein levels of TFR1 and DMT1 in the liver （P<0.01）， and decreases in the activities of SOD， GPX and the protein levels of Nrf2， SLC7A11， and GPX4 in the liver （P<0.05， P<0.01）. Meanwhile， the liver tissue in the model group presented steatosis， iron deposition， mitochondrial shrinkage， and blurred or swollen mitochondrial cristae. Compared with the model group， all doses of Danggui Shaoyaosan reduced the body weight， liver weight， liver index， levels or activities of TC， TG， ALT， AST， and Fe²⁺ in the serum， levels of TC， TG， FFA， MDA， Fe²⁺， and ROS in the liver， and protein levels of TFR1 and DMT1 in the liver （P<0.01）， while increasing the activities of SOD and GPX and the protein levels of Nrf2， SLC7A11， and GPX4 in the liver （P<0.01）. Furthermore， Danggui Shaoyaosan alleviated steatosis， iron deposition， and mitochondrial damage in the liver. ConclusionDanggui Shaoyaosan may inhibit lipid peroxidation and ferroptosis by activating the Nrf2/SLC7A11/GPX4 signaling pathway to treat NAFLD.

ObjectiveTo observe and analyze the plasma metabolite differences among colorectal cancer patients with spleen-qi deficiency， damp-heat stasis-toxin syndrome（SRYD）， non-spleen-qi deficiency， damp-heat stasis-toxin syndrome（non-SRYD）， and normal human beings（Normal）， aiming to identify unique metabolites specific to SRYD colorectal cancer patients and their potential biomarkers. MethodsBased on the diagnostic criteria of SRYD and non-SRYD colorectal cancer， 30 patients were included， including 10 patients with SRYD colorectal cancer and 20 patients with non-SRYD colorectal cancer， while 10 individuals were recruited for the Normal group. Metabolome sequencing of plasma from the three groups was performed by ultra-performance liquid chromatography-quadrupole-electrostatic field orbitrap mass spectrometry（UPLC-Q-Exactive-Orbitrap-MS）. Multivariate statistical analysis were performed by principal component analysis（PCA） and partial least squares-discriminant analysis（PLS-DA）， and the intergroup differential metabolites were identified based on variable importance in the projection（VIP） value>1 and t-test P<0.05. And pathway enrichment analysis based on Kyoto Encyclopedia of Genes and Genomes（KEGG） was performed to explore the metabolites and metabolic pathways specific to SRYD colorectal cancer patients. ResultsMetabolome sequencing results showed some differences in metabolic profiles between the groups. A total of 111 plasma differential metabolites were found in the SRYD group and the Normal group， of which 31 were up-regulated and 80 were down-regulated， mainly including stearoyl lysophosphatidylcholine， indole-3-acrylic acid， and dehydroepiandrosterone sulfate（P<0.05）. The non-SRYD group exhibited 97 differentially expressed metabolites compared to the Normal group， with 36 up-regulated and 61 down-regulated， mainly including stearoyl lysophosphatidylcholine， sphingosine， and palmitoyl lysophosphatidylcholine（P<0.05）. And the SRYD group exhibited 19 differentially expressed metabolites compared to the non-SRYD group， of which 5 were up-regulated and 14 were down-regulated， mainly including dihydrosphingosine， palmitic acid， and linoleoylethanolamide（P<0.05）. The significant differential metabolites were subjected to KEGG analysis to obtain significantly enriched metabolic pathways in each group， and the results showed that 11 metabolic pathways such as primary bile acid synthesis， cholesterol metabolism and bile secretion were differential signaling pathways specific to SRYD colorectal cancer. Further retrieval of the above key signaling pathways showed that bile acids were up-regulated in both bile secretion and primary bile acid synthesis pathways， and there was a trend of up-regulation of glycochenodeoxycholic acid， taurochenodeoxycholic acid， and chenodeoxycholic acid. ConclusionPrimary bile acid synthesis， cholesterol metabolism， and bile secretion-related pathways may be differential signaling pathways specific to SRYD colorectal cancer， and bile acid is a core molecule in the metabolic pathway， which can serve as potential biomarkers closely related to the development and progression of SRYD colorectal cancer.

ObjectiveTo observe and analyze the plasma metabolite differences among colorectal cancer patients with spleen-qi deficiency， damp-heat stasis-toxin syndrome（SRYD）， non-spleen-qi deficiency， damp-heat stasis-toxin syndrome（non-SRYD）， and normal human beings（Normal）， aiming to identify unique metabolites specific to SRYD colorectal cancer patients and their potential biomarkers. MethodsBased on the diagnostic criteria of SRYD and non-SRYD colorectal cancer， 30 patients were included， including 10 patients with SRYD colorectal cancer and 20 patients with non-SRYD colorectal cancer， while 10 individuals were recruited for the Normal group. Metabolome sequencing of plasma from the three groups was performed by ultra-performance liquid chromatography-quadrupole-electrostatic field orbitrap mass spectrometry（UPLC-Q-Exactive-Orbitrap-MS）. Multivariate statistical analysis were performed by principal component analysis（PCA） and partial least squares-discriminant analysis（PLS-DA）， and the intergroup differential metabolites were identified based on variable importance in the projection（VIP） value>1 and t-test P<0.05. And pathway enrichment analysis based on Kyoto Encyclopedia of Genes and Genomes（KEGG） was performed to explore the metabolites and metabolic pathways specific to SRYD colorectal cancer patients. ResultsMetabolome sequencing results showed some differences in metabolic profiles between the groups. A total of 111 plasma differential metabolites were found in the SRYD group and the Normal group， of which 31 were up-regulated and 80 were down-regulated， mainly including stearoyl lysophosphatidylcholine， indole-3-acrylic acid， and dehydroepiandrosterone sulfate（P<0.05）. The non-SRYD group exhibited 97 differentially expressed metabolites compared to the Normal group， with 36 up-regulated and 61 down-regulated， mainly including stearoyl lysophosphatidylcholine， sphingosine， and palmitoyl lysophosphatidylcholine（P<0.05）. And the SRYD group exhibited 19 differentially expressed metabolites compared to the non-SRYD group， of which 5 were up-regulated and 14 were down-regulated， mainly including dihydrosphingosine， palmitic acid， and linoleoylethanolamide（P<0.05）. The significant differential metabolites were subjected to KEGG analysis to obtain significantly enriched metabolic pathways in each group， and the results showed that 11 metabolic pathways such as primary bile acid synthesis， cholesterol metabolism and bile secretion were differential signaling pathways specific to SRYD colorectal cancer. Further retrieval of the above key signaling pathways showed that bile acids were up-regulated in both bile secretion and primary bile acid synthesis pathways， and there was a trend of up-regulation of glycochenodeoxycholic acid， taurochenodeoxycholic acid， and chenodeoxycholic acid. ConclusionPrimary bile acid synthesis， cholesterol metabolism， and bile secretion-related pathways may be differential signaling pathways specific to SRYD colorectal cancer， and bile acid is a core molecule in the metabolic pathway， which can serve as potential biomarkers closely related to the development and progression of SRYD colorectal cancer.

AIM: To investigate the pharmacokinetic properties of the main active components of Dalitong extract in SD rats after oral administration using UPLC-MS / MS. METHODS: An UPLC-MS / MS method was established to simultaneously detect tetrahydropalmatine, nobiletin and costunolide in the plasma and tissues of SD rats. The method was applied to investigate the pharmacokinetic characteristics and tissue distribution. RESULTS: After a single oral administration, the three active components were rapidly absorbed into the body, with a peak concentration (Cmax) of (13.73 ± 7.50), (27.01 ± 17.69) and (6.73 ± 29.94) ng / mL for tetrahydropalmatine, nobiletin, and costunolide, respectively. The time to reach the peak concentration (Tmax) was (1.40 ± 0.93), (0.63 ± 0.28) and (2.38 ± 8.81) h, respectively. The area under the curve (AUC) was (80.43±40.03), (41.30±28.69) and (303.90 ± 136.69) ng · h · mL

Six compounds were isolated from the roots of Ephedra sinica Stapf using various chromatographic techniques such as silica gel column chromatography, thin layer chromatography and semi-preparative HPLC. Their chemical structures were identified by analysis of physicochemical properties and spectral data, and determined as (Z)-docosanylferulate (1), (E)-docosanylferulate (2), bis (2-ethylheptyl) phythalate (3), 2,2′-oxybis (1,4-di-tert-butylbenzene) (4), diisobutyl phthalate (5), bis (2-ethylhexyl) phthalate (6). Among them, compound 1 is a new compound, compounds 2-4 were first isolated from Ephedra. A corticosterone-induced PC-12 cell injury model was used for compound activity screening. The results showed that compounds 1 and 5 significantly improved corticosterone-induced PC-12 cell injury and significantly increased 5-HT₇ receptor protein expression in the cells, indicating potential antidepressant activity.