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 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.

The therapeutic effects of Yueju Pills on depression and cardiovascular diseases have been widely recognized. Previous studies have shown that the drug can significantly improve depressive-like behaviors induced by chronic unpredictable mild stress(CUMS) combined with atherosclerosis(AS). Given the complex pathogenesis of psychocardiac diseases, this study integrated metabolomics and network pharmacology to systematically elucidate the mechanism of Yueju Pills in alleviating depressive symptoms in psychocardiac diseases. The results demonstrate that, after Yueju Pill intervention, the levels of 9 abnormal metabolites in the hippocampus restore to normal ranges, primarily involving key pathways or signaling pathways, including the cyclic adenosine monophosphate(cAMP), mammalian target of rapamycin(mTOR), glycine/serine/threonine metabolism, and aminoacyl-tRNA biosynthesis. In a high-fat diet-induced CUMS ApoE~(-/-) mouse model, Yueju Pills significantly increases adenosine monophosphate(AMP) levels and decreases L-alanine and D-glyceric acid levels in the hippocampus. In conclusion, Yueju Pills exert antidepressant effects by regulating multiple metabolic axes, including glycine/serine/threonine metabolism and the cAMP, mTOR signaling pathways. Network pharmacology predictions reveal that the treatment of CUMS combined with AS by its core active components may be realized through modulating pathways concerning neuroinflammation and synaptic plasticity, including serine/threonine-protein kinase 1(AKT1), mitogen-activated protein kinase 1(MAPK1), and prostaglandin-endoperoxide synthase 2(PTGS2). This study provides a theoretical reference for the clinical application of Yueju Pills in alleviating the depressive symptoms of psychocardiac diseases.
Animals ; Network Pharmacology ; Mice ; Drugs, Chinese Herbal/administration & dosage* ; Metabolomics ; Male ; Depression/genetics* ; Humans ; Hippocampus/drug effects* ; Mice, Inbred C57BL ; Signal Transduction/drug effects*

Purpose::Vibrio vulnificus ( V. Vulnificus) infection is characterized by rapid onset, aggressive progression, and challenging treatment. Bacterial resistance poses a significant challenge for clinical anti-infection treatment and is thus the subject of research. Enhancing host infection tolerance represents a novel infection prevention strategy to improve patient survival. Our team initially identified cytochrome P4501A1 (CYP1A1) as an important target owing to its negative modulation of the body's infection tolerance. This study explored the superior effects of the CYP1A1 inhibitor bergamottin compared to antibiotic combination therapy on the survival of mice infected with multidrug-resistant V. Vulnificus and the protection of their vital organs. Methods::An increasing concentration gradient method was used to induce multidrug-resistant V. Vulnificus development. We established a lethal infection model in C57BL/6J male mice and evaluated the effect of bergamottin on mouse survival. A mild infection model was established in C57BL/6J male mice, and the serum levels of creatinine, urea nitrogen, aspartate aminotransferase, and alanine aminotransferase were determined using enzyme-linked immunosorbent assay to evaluate the effect of bergamottin on liver and kidney function. The morphological changes induced in the presence of bergamottin in mouse organs were evaluated by hematoxylin and eosin staining of liver and kidney tissues. The bacterial growth curve and organ load determination were used to evaluate whether bergamottin has a direct antibacterial effect on multidrug-resistant V. Vulnificus. Quantification of inflammatory factors in serum by enzyme-linked immunosorbent assay and the expression levels of inflammatory factors in liver and kidney tissues by real-time quantitative polymerase chain reaction were performed to evaluate the effect of bergamottin on inflammatory factor levels. Western blot analysis of IκBα, phosphorylated IκBα, p65, and phosphorylated p65 protein expression in liver and kidney tissues and in human hepatocellular carcinomas-2 and human kidney-2 cell lines was used to evaluate the effect of bergamottin on the nuclear factor kappa-B signaling pathway. One-way ANOVA and Kaplan-Meier analysis were used for statistical analysis. Results::In mice infected with multidrug-resistant V. Vulnificus, bergamottin prolonged survival ( p = 0.014), reduced the serum creatinine ( p = 0.002), urea nitrogen ( p = 0.030), aspartate aminotransferase ( p = 0.029), and alanine aminotransferase ( p = 0.003) levels, and protected the cellular morphology of liver and kidney tissues. Bergamottin inhibited interleukin (IL)-1β, IL-6, and tumor necrosis factor (TNF)-α expression in serum (IL-1β: p = 0.010, IL-6: p = 0.029, TNF-α: p = 0.025) and inhibited the protein expression of the inflammatory factors IL-1β, IL-6, TNF-α in liver (IL-1β: p = 0.010, IL-6: p = 0.011, TNF-α: p = 0.037) and kidney (IL-1β: p = 0.016, IL-6: p = 0.011, TNF-α: p = 0.008) tissues. Bergamottin did not affect the proliferation of multidrug-resistant V. Vulnificus or the bacterial load in the mouse peritoneal lavage fluid ( p = 0.225), liver ( p = 0.186), or kidney ( p = 0.637). Conclusion::Bergamottin enhances the tolerance of mice to multidrug-resistant V. Vulnificus infection. This study can serve as a reference and guide the development of novel clinical treatment strategies for V. Vulnificus.