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.

Rheumatic diseases are chronic inflammatory autoimmune diseases that can affect multiple organs and systems. In clinical practice， most patients with rheumatic diseases present with asymptomatic liver function abnormalities during the course of the disease， and the etiology of such diseases may be associated with the rheumatic disease itself， medications， metabolism， viruses， or the presence of other chronic liver diseases. Immune-mediated inflammatory responses play a significant role in liver involvement （including hepatocyte injury， intrahepatic vascular lesions， and hepatic fibrosis） in rheumatic diseases. This article discusses the clinical features and management of liver involvement secondary to rheumatic diseases， in order to enhance the understanding of this condition among specialists in related fields.

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 explore the mechanism of modified maimendong decoction (MMD) in inhibiting lung cancer metastasis from the perspective of immune regulation. Methods CTC-TJH-01 and LLC cells were intervened with different concentrations of modified maimendong decoction. The cell proliferation was detected with a CCK-8 kit, apoptosis was detected with an Annexin V-FITC/PI kit, and cell migration was detected through Transwell assays. A lung metastasis model was established through the tail vein injection of LLC cells into C57BL/6 mice, and body weight change and lung tumor metastasis in the mice were evaluated after continuous gavage intervention with MMD. HE staining, immunohistochemistry, and immunofluorescence were employed to observe the histomorphology, Ki-67 protein level, and NK and T cell levels of metastatic lesions. The levels of NK and T cells in the peripheral blood of mice were detected throughflow cytometry. Results MMD had no significant inhibitory effect on the proliferation, apoptosis, and migration of CTC-TJH-01 and LLC cells in vitro. In mice, MMD could significantly inhibit the lung metastasis of LLC cells, increase the proportion of NK and CD8⁺ T cells in peripheral blood and tumor microenvironment (P<0.05), and reduce the expression of Ki-67 protein in metastatic tumor tissues (P<0.05). Conclusion MMD may inhibit the growth of metastatic tumors by upregulating the expression levels of NK and CD8⁺ T cells in peripheral blood to promote the elimination of circulating tumor cells, and regulating the infiltration of NK and CD8⁺ T cells in the immune microenvironment of metastatic tumors, then play an antimetastatic role in lung cancer.

Objective:To study the current status of longitudinal extrauterine growth restriction (EUGR) in extremely preterm infants (EPIs) and to develop a prediction model based on clinical data from multiple NICUs.Methods:From January 2017 to December 2018, EPIs admitted to 32 NICUs in North China were retrospectively studied. Their general conditions, nutritional support, complications during hospitalization and weight changes were reviewed. Weight loss between birth and discharge > 1SD was defined as longitudinal EUGR. The EPIs were assigned into longitudinal EUGR group and non-EUGR group and their nutritional support and weight changes were compared. The EPIs were randomly assigned into the training dataset and the validation dataset with a ratio of 7∶3. Univariate Cox regression analysis and multiple regression analysis were used in the training dataset to select the independent predictive factors. The best-fitting Nomogram model predicting longitudinal EUGR was established based on Akaike Information Criterion. The model was evaluated for discrimination efficacy, calibration and clinical decision curve analysis.Results:A total of 436 EPIs were included in this study, with a mean gestational age of (26.9±0.9) weeks and a birth weight of (989±171) g. The incidence of longitudinal EUGR was 82.3%(359/436). Seven variables (birth weight Z-score, weight loss, weight growth velocity, the proportion of breast milk ≥75% within 3 d before discharge, invasive mechanical ventilation ≥7 d, maternal antenatal corticosteroids use and bronchopulmonary dysplasia) were selected to establish the prediction model. The area under the receiver operating characteristic curve of the training dataset and the validation dataset were 0.870 (95% CI 0.820-0.920) and 0.879 (95% CI 0.815-0.942), suggesting good discrimination efficacy. The calibration curve indicated a good fit of the model ( P>0.05). The decision curve analysis showed positive net benefits at all thresholds. Conclusions:Currently, EPIs have a high incidence of longitudinal EUGR. The prediction model is helpful for early identification and intervention for EPIs with higher risks of longitudinal EUGR. It is necessary to expand the sample size and conduct prospective studies to optimize and validate the prediction model in the future.

ObjectiveTo determine the drug sensitivity and molecular typing characteristics of Klebsiella pneumoniae isolated from meat and diarrhea samples in a local area. MethodsSeventy-one strains of K.pneumoniae were isolated from 118 meat food （chicken and pork） randomly sampled in the markets in Jinshan District， Shanghai， 2020‒2021， and 1 499 diarrhea samples from outpatient diarrhoea patients in hospitals in the same district. Then drug susceptibility testing was conducted by micro-broth dilution method， and sequence identity was determined by pulsed field gel electrophoresis（PFGE）. ResultsThe overall detection rate of K.pneumoniae in meat was 11.86% （14/118）， with detection rate 20.93% （9/43） in chicken and 6.67% （5/75） in pork. The difference in detection between meats was statistically significant （χ²=5.317，P<0.05）. The detection rate of K.pneumoniae in diarrhea samples was 3.80% （57/1 499）. Furthermore， the isolated strains showed the highest resistance to ampicillin at 76.06%. The multi-drug resistant strains included 5 of human origin （8.77%） and 2 of foodborne origin （14.28%）. Additionally， 1 foodborne imipenem-resistant strain was detected. A total of 71 strains of K.pneumoniae were found to have 70 banding types， with similarity ranging from 39.4% to 100%， suggesting genetic diversity. ConclusionK.pneumoniae isolated from foodborne and diarrhea samples showed multi-drug resistance in Jinshan District， . with scattered PFGE banding patterns. It is recommended to strengthen the monitoring of this pathogen in the population and animal food， and be alert to the emerging multi-drug resistant strains and risk of food chain transmission.

ObjectiveTo understand the current drug resistance status and bacterial multilocus sequence typing （MLST） of human and avian Campylobacter jejuni in Jinshan District， Shanghai. MethodsFecal samples were collected from diarrhea patients in the annuity mountainous area from 2021 to 2022， and poultry and related samples were collected from 2 poultry farms in the Jinshan area for detection of C. jejuni. Minimal inhibitory concentration （MIC） drug sensitivity test was performed on the detected C. jejuni， and some strains were selected for whole genome sequencing and MLST analysis. ResultsA total of 823 samples of diarrhea disease were collected， and 32 strains of C. jejuni were detected， with a detection rate of 3.89%. Out of 600 poultry related samples， 62 strains of C. jejuni were detected， with a detection rate of 10.33%. Human multidrug resistance reached 93.75% （30/32）， while avian multidrug resistance reached 100.00%（62/62）. The top four drug resistance rates of human and avian C. jejuni were azithromycin （100.00% from humans and 100.00% from birds）， naphthoic acid （93.75% from humans and 87.10% from birds）， ciprofloxacin （90.63% from humans and 98.39% from birds）， and tetracycline （84.38% from humans and 98.39% from birds）. The relatively low resistance strains of human derived C. were erythromycin， chloramphenicol， and thalithromycin. The relatively low resistance strains of avian C. jejuni were erythromycin， clindamycin， and flufenicol. MLST analysis showed that the selected 16 strains of bacteria were divided into 9 ST types， among which the evolutionary relationship of avian C. jejuni was relatively concentrated， while human C. jejuni was relatively dispersed. It was found that one strain of avian C. jejuni was closely related to two strains of human C. jejuni. ConclusionsC. jejuni infection is severe in patients with diarrhea in this region， with a detection rate second only to salmonella and Vibrio parahaemolyticus. C. jejuni infection in poultry is relatively common， and both are highly resistant. Therefore， monitoring and control should be strengthened. MLST analysis shows new ST types in both avian and human sources of C. jejuni， indicating the emergence of new mutations that require continuous monitoring to avoid the epidemics caused by new strains. The isolated strains with close genetic relationships between avian and human sources reveal the evidence of the spread of C. jejuni from poultry to humans. Therefore it is necessary to strengthen the monitoring of C. jejuni in relevant samples from breeding farms.