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 identify the active constituents of Kaixuan Jiedu core prescription （KXJD） and investigate its effective components and therapeutic targets in the treatment of common psoriasis. MethodsUltra-performance liquid chromatography-high resolution mass spectrometry （UPLC-Q-TOF MS） was used to identify and analyze the chemical components of KXJD and its blood-entering chemical components. The chemical components of the single decoction were further identified to clarify the source of the chemical components in KXJD. Then， all identified blood-entering compounds were screened for effective active ingredients through the Swiss ADME database. The active ingredient targets of KXJD were searched on the Swiss Target Prediction platform. The targets of common psoriasis were searched in OMIM， GEO， GeneCards， and DISGNET databases to obtain drug-disease intersection targets. The protein-protein interaction network of intersection targets was constructed using STRING， and then the core blood-entering component-intersection target network of KXJD was constructed. The core target proteins in the network were selected for molecular docking with the core components of KXJD. Small molecules and proteins were pretreated， and appropriate docking sites were selected. AutoDock Vina software was used for continuous local search and repeated iterations to find molecular docking conformations. PyMOL software and LigPlot+ software were used for analysis and visualization. Subsequently， the verification was carried out through animal experiments. SPF-grade male C57 mice were randomly divided into a blank group， a model group， a positive drug methotrexate group， and a KXJD group. In the model group， the methotrexate group， and the KXJD group， imiquimod was applied to the backs of the mice for modeling. The blank group and the model group were administered normal saline by gavage， while the methotrexate group and the KXJD group were respectively administered 1 mg·kg^-1 suspension and 30.42 g·kg^-1 decoction of traditional Chinese medicine by gavage. Five days after administration， the mice were sacrificed， and samples were collected. Hematoxylin-eosin （HE） staining was used to observe the skin tissue samples of mice， and the effect of KXJD on the pathological manifestations of psoriasis mice was analyzed. The expression areas of tumor necrosis factor-α （TNF-α）， cyclooxygenase 2 （PTGS2）， interleukin （IL）-1β， and IL-6 in the skin tissue of mice were detected by immunohistochemistry （IHC）. The mRNA expressions of TNF-α， IL-1β， IL-6， and PTGS2 in the skin tissue of mice were detected by real-time fluorescent quantitative polymerase chain reaction （Real-time PCR）. ResultsIn this study， 208 compounds in KXJD were identified by UPLC-Q-TOF MS， and 44 compounds were detected in serum， including 28 prototype components and 16 metabolites. 12 blood-entering active components were screened， and 1 153 active component targets and 1 076 psoriasis-related targets were identified. Eighty-five targets in the intersection set were drug-disease common targets. PPI network analysis showed that TNF-α， IL-1β， IL-6， PTGS2， and ALB were the key target proteins. The results of molecular docking showed that the binding ability of （+）-hexylphenylglycolic acid to key target proteins such as PTGS2 was stable， and PTGS2 showed high stability with a variety of core compounds. Compared with those in the blank group， the stratum corneum and epidermis in the model group mice were significantly thickened， and the pathological Baker score of the mice's skin in the model group was significantly higher than that of the blank group （P<0.01）. The expression areas of PTGS2， TNF-α， IL-1β， and IL-6 proteins in the skin tissue of the model group mice were significantly increased （P<0.01）， and the expression levels of PTGS2， TNF-α， IL-1β， and IL-6 mRNA in the skin tissue of the model group mice were significantly elevated （P<0.01）. Compared with the model group， the pathological Baker scores of the methotrexate group and the KXJD group were both decreased （P<0.01）， and the expression areas in the skin tissue of the methotrexate group and the KXJD group were significantly reduced （P<0.05， P<0.01）. The expression levels of PTGS2， TNF-α， IL-1β， and IL-6 mRNA in the skin tissue of the methotrexate group and the KXJD group were significantly decreased （P<0.01）. ConclusionKXJD can effectively improve the skin lesions of psoriasis model mice and reduce the expression of TNF-α， IL-1β， IL-6， and PTGS2 in the skin tissue of psoriasis model mice. PTGS2 has a stable binding ability with a variety of compounds in the decoction， which may be a key target for the treatment of psoriasis. The compound （+）-hexylphenylglycolic acid may play a key role.

ObjectiveTo use bioinformatics technology to screen the molecular patterns and diagnostic biomarkers of ferroptosis closely related to psoriasis， observe the therapeutic effect of Kaixuan Jiedu core prescription on psoriasis and explore its potential mechanism through animal experiments. MethodsPsoriasis microarray data from GEO were analyzed to identify differentially expressed genes （DEGs）. Intersection with a ferroptosis gene set yielded psoriasis ferroptosis-related genes （FRGs）， which underwent correlation， consensus clustering， enrichment， and immune infiltration analyses. Core diagnostic FRGs （Hub-FRGs） were identified using random forest （RF）， support vector machine （SVM）， LASSO regression， Nomogram， and ROC analyses. In vivo， imiquimod （5% cream） induced psoriasis in mice （except controls）. Drug treatment groups received respective doses， while control and model groups received saline via daily gavage for 7 days. Back skin changes were recorded and PASI scored. Hematoxylin-eosin （HE） staining assessed histopathology. The levels of ferrous ion （Fe²⁺）， malondialdehyde （MDA）， 4-hydroxynonenal （4-HNE） and free fatty acid （FFA） in skin tissue were detected. The level of reactive oxygen species （ROS） in skin tissue was detected by immunofluorescence. Immunohistochemistry was used to detect the expression of ChaC glutathione-specific γ-glutamyl transferase 1 （CHAC1）， arachidonic acid 12-lipoxygenase β （ALOX12B）， trimotif protein 21 （TRIM21）， proliferation marker （Ki67） and nuclear transcription factor-κB （NF-κB） protein. ResultsAnalysis of GSE30999 identified 2 100 DEGs and 24 FRGs. Gene Ontology （GO） and Kyoto Encyclopedia of Genes and Genomes （KEGG） enrichment revealed 1 000 biological functions and 75 pathways. After cluster analysis， combined with three machine learning algorithms， Nomogram and ROC curve analysis， the core Hub-FRGs （CHAC1， ALOX12 B， TRIM21） were obtained. Immunoinfiltration showed inactive memory CD4⁺T cells and activated dendritic cells abundance significantly correlated with Hub-FRGs. In vivo， model group vs. control showed significantly increased PASI/Baker scores （P<0.05）， epidermal hyperkeratosis， inflammatory infiltration， and elevated levels of Fe²⁺， MDA， 4-HNE， FFA， ROS， CHAC1， ALOX12B， TRIM21， Ki67， and NF-κB （P<0.05）. Drug groups vs. model group exhibited significantly reduced scores （P<0.05）， alleviated skin lesions， and decreased levels of Fe²⁺， MDA， 4-HNE， FFA， ROS， Hub-FRGs， Ki67， and NF-κB （P<0.05）. ConclusionKaixuan Jiedu core prescription can significantly improve the skin pathological injury of psoriasis mice， showing good therapeutic and repair effects， and its mechanism may be related to regulating the expression of ferroptosis genes CHAC1， ALOX12B and TRIM21， which are closely related to the pathogenesis of psoriasis.

ObjectiveTo identify the active constituents of Kaixuan Jiedu core prescription （KXJD） and investigate its effective components and therapeutic targets in the treatment of common psoriasis. MethodsUltra-performance liquid chromatography-high resolution mass spectrometry （UPLC-Q-TOF MS） was used to identify and analyze the chemical components of KXJD and its blood-entering chemical components. The chemical components of the single decoction were further identified to clarify the source of the chemical components in KXJD. Then， all identified blood-entering compounds were screened for effective active ingredients through the Swiss ADME database. The active ingredient targets of KXJD were searched on the Swiss Target Prediction platform. The targets of common psoriasis were searched in OMIM， GEO， GeneCards， and DISGNET databases to obtain drug-disease intersection targets. The protein-protein interaction network of intersection targets was constructed using STRING， and then the core blood-entering component-intersection target network of KXJD was constructed. The core target proteins in the network were selected for molecular docking with the core components of KXJD. Small molecules and proteins were pretreated， and appropriate docking sites were selected. AutoDock Vina software was used for continuous local search and repeated iterations to find molecular docking conformations. PyMOL software and LigPlot+ software were used for analysis and visualization. Subsequently， the verification was carried out through animal experiments. SPF-grade male C57 mice were randomly divided into a blank group， a model group， a positive drug methotrexate group， and a KXJD group. In the model group， the methotrexate group， and the KXJD group， imiquimod was applied to the backs of the mice for modeling. The blank group and the model group were administered normal saline by gavage， while the methotrexate group and the KXJD group were respectively administered 1 mg·kg^-1 suspension and 30.42 g·kg^-1 decoction of traditional Chinese medicine by gavage. Five days after administration， the mice were sacrificed， and samples were collected. Hematoxylin-eosin （HE） staining was used to observe the skin tissue samples of mice， and the effect of KXJD on the pathological manifestations of psoriasis mice was analyzed. The expression areas of tumor necrosis factor-α （TNF-α）， cyclooxygenase 2 （PTGS2）， interleukin （IL）-1β， and IL-6 in the skin tissue of mice were detected by immunohistochemistry （IHC）. The mRNA expressions of TNF-α， IL-1β， IL-6， and PTGS2 in the skin tissue of mice were detected by real-time fluorescent quantitative polymerase chain reaction （Real-time PCR）. ResultsIn this study， 208 compounds in KXJD were identified by UPLC-Q-TOF MS， and 44 compounds were detected in serum， including 28 prototype components and 16 metabolites. 12 blood-entering active components were screened， and 1 153 active component targets and 1 076 psoriasis-related targets were identified. Eighty-five targets in the intersection set were drug-disease common targets. PPI network analysis showed that TNF-α， IL-1β， IL-6， PTGS2， and ALB were the key target proteins. The results of molecular docking showed that the binding ability of （+）-hexylphenylglycolic acid to key target proteins such as PTGS2 was stable， and PTGS2 showed high stability with a variety of core compounds. Compared with those in the blank group， the stratum corneum and epidermis in the model group mice were significantly thickened， and the pathological Baker score of the mice's skin in the model group was significantly higher than that of the blank group （P<0.01）. The expression areas of PTGS2， TNF-α， IL-1β， and IL-6 proteins in the skin tissue of the model group mice were significantly increased （P<0.01）， and the expression levels of PTGS2， TNF-α， IL-1β， and IL-6 mRNA in the skin tissue of the model group mice were significantly elevated （P<0.01）. Compared with the model group， the pathological Baker scores of the methotrexate group and the KXJD group were both decreased （P<0.01）， and the expression areas in the skin tissue of the methotrexate group and the KXJD group were significantly reduced （P<0.05， P<0.01）. The expression levels of PTGS2， TNF-α， IL-1β， and IL-6 mRNA in the skin tissue of the methotrexate group and the KXJD group were significantly decreased （P<0.01）. ConclusionKXJD can effectively improve the skin lesions of psoriasis model mice and reduce the expression of TNF-α， IL-1β， IL-6， and PTGS2 in the skin tissue of psoriasis model mice. PTGS2 has a stable binding ability with a variety of compounds in the decoction， which may be a key target for the treatment of psoriasis. The compound （+）-hexylphenylglycolic acid may play a key role.

ObjectiveTo use bioinformatics technology to screen the molecular patterns and diagnostic biomarkers of ferroptosis closely related to psoriasis， observe the therapeutic effect of Kaixuan Jiedu core prescription on psoriasis and explore its potential mechanism through animal experiments. MethodsPsoriasis microarray data from GEO were analyzed to identify differentially expressed genes （DEGs）. Intersection with a ferroptosis gene set yielded psoriasis ferroptosis-related genes （FRGs）， which underwent correlation， consensus clustering， enrichment， and immune infiltration analyses. Core diagnostic FRGs （Hub-FRGs） were identified using random forest （RF）， support vector machine （SVM）， LASSO regression， Nomogram， and ROC analyses. In vivo， imiquimod （5% cream） induced psoriasis in mice （except controls）. Drug treatment groups received respective doses， while control and model groups received saline via daily gavage for 7 days. Back skin changes were recorded and PASI scored. Hematoxylin-eosin （HE） staining assessed histopathology. The levels of ferrous ion （Fe²⁺）， malondialdehyde （MDA）， 4-hydroxynonenal （4-HNE） and free fatty acid （FFA） in skin tissue were detected. The level of reactive oxygen species （ROS） in skin tissue was detected by immunofluorescence. Immunohistochemistry was used to detect the expression of ChaC glutathione-specific γ-glutamyl transferase 1 （CHAC1）， arachidonic acid 12-lipoxygenase β （ALOX12B）， trimotif protein 21 （TRIM21）， proliferation marker （Ki67） and nuclear transcription factor-κB （NF-κB） protein. ResultsAnalysis of GSE30999 identified 2 100 DEGs and 24 FRGs. Gene Ontology （GO） and Kyoto Encyclopedia of Genes and Genomes （KEGG） enrichment revealed 1 000 biological functions and 75 pathways. After cluster analysis， combined with three machine learning algorithms， Nomogram and ROC curve analysis， the core Hub-FRGs （CHAC1， ALOX12 B， TRIM21） were obtained. Immunoinfiltration showed inactive memory CD4⁺T cells and activated dendritic cells abundance significantly correlated with Hub-FRGs. In vivo， model group vs. control showed significantly increased PASI/Baker scores （P<0.05）， epidermal hyperkeratosis， inflammatory infiltration， and elevated levels of Fe²⁺， MDA， 4-HNE， FFA， ROS， CHAC1， ALOX12B， TRIM21， Ki67， and NF-κB （P<0.05）. Drug groups vs. model group exhibited significantly reduced scores （P<0.05）， alleviated skin lesions， and decreased levels of Fe²⁺， MDA， 4-HNE， FFA， ROS， Hub-FRGs， Ki67， and NF-κB （P<0.05）. ConclusionKaixuan Jiedu core prescription can significantly improve the skin pathological injury of psoriasis mice， showing good therapeutic and repair effects， and its mechanism may be related to regulating the expression of ferroptosis genes CHAC1， ALOX12B and TRIM21， which are closely related to the pathogenesis of psoriasis.

ObjectiveTo explore the impact of Gegen Qinliantang（GQT） on the fecal short-chain fatty acids（SCFAs） metabolism in antibiotic-associated diarrhea（AAD） through targeted metabolomics. MethodA total of 240 SD rats were randomly divided into six groups（n=40， half male and half female）， including blank group， model group， bifidobiogen group（0.15 g·kg^-1）， and GQT high-， medium-， and low-dose groups（10.08， 5.04， 2.52 g·kg^-1）， except for the blank group， clindamycin（250 mg·kg^-1） was given to all groups by gavage for modeling every day for 7 d. After successful modeling， each administered group was gavaged with the corresponding dose of the drug， and the blank and model groups were gavaged with an equal volume of normal saline solution， 1 time/d， for 14 d. At 0， 3， 7， 14 d after the drug intervention， eight rats were randomly selected from each group， respectively. Gas chromatography-time-of-flight mass spectrometry（GC-TOF-MS） was used to perform targeted metabolomic analysis of SCFAs in the feces of rats， and partial least squares-discriminant analysis（PLS-DA） was applied to compare the differences in metabolic profiles between groups at different treatment times， and to compare the changes in the contents of SCFAs in rat feces between groups. ResultPLS-DA results showed that the blank group could be clearly distinguishable from the model group， with GQT exhibiting a closer proximity to the blank group after 7 d of treatment. After further analyzing the composition of SCFAs， it was found that the proportion of acetic acid increased and the proportions of butyric acid， valeric acid， hexanoic acid and isovaleric acid decreased in the model group compared with the blank group. After the treatment with GQT， the proportions of butyric acid， isobutyric acid， valeric acid， and isovaleric acid increased， and the proportions of acetic acid， propionic acid and caproic acid decreased. Subsequent differential analysis revealed that GQT could significantly improve the content of butyric acid， and had a certain retrogressive effect on the contents of valeric acid and hexanoic acid. ConclusionThe medium dose group of GQT can improve the contents of SCFAs in AAD feces after 7 days of treatment， which may be related to the improvement of the composition ratio of SCFAs and the contents of butyric acid， valeric acid and caproic acid.