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.

Outer membrane vesicles (OMVs) are nanoscale vesicles secreted by Gram-negative bacteria. As a unique bacterial secretion, OMV secretion can help bacteria maintain the outer membrane stability or remove harmful substances. Studies have shown that local separation of outer membrane and peptidoglycan layers led by abnormalities in outer membrane protein function, abnormal structure or excessive accumulation of LPS, and erroneous accumulation of phospholipids in the outer leaflet, which can all lead to bacterial outer membrane protrusion and eventually bud formation of OMVs. Since OMVs are mainly composed of bacterial outer membrane and periplasmic components, the pathogen associated molecular patterns (PAMPs) on their surface can trigger strong immune responses. For example, OMVs can recruit and activate neutrophils, polarize macrophages to secrete large amounts of inflammatory factors. More importantly, OMVs can act as adjuvants to induce dendritic cell (DC) maturation to enhance adaptive immune response in the body. At the same time, OMVs are derived from bacteria, which make it easy to modify. The methods by genetic engineering and others can improve their tumor targeting, give them new functions, or reduce their immunotoxicity, which is conducive to their application in tumor therapy. OMVs not only induce apoptosis or pyroptosis of tumor cells, but also regulate the host immune system, which makes OMVs themselves have a certain killing effect on tumors. In addition, the tendency of neutrophils to inflammatory tumor sites and the formation of neutrophil extracellular traps enable OMVs to target tumor sites, and the suitable size and the characteristic that they are easily taken up by DCs give OMVs a certain lymphatic targeting ability. Therefore, OMVs are often employed as excellent drug or vaccine carriers in tumor therapy. This review mainly discusses the biological mechanism of OMVs, the regulatory effects of OMVs on immune cells, the functional modification strategies of OMVs, and their research progress in tumor therapy.

Objective: To explore the application of up-conversing phosphor technology (UPT) to detect pathogenic organisms in the air. Methods: The performance of UPT was verified with Staphylococcus aureus, Yersinia pestis and Escherichia coli O157 as simulated strains, including stability, specificity, sensitivity and response time tests; Air particle sampler is used to collect air samples in the field microenvironment test chamber, and UPT is used for detection. At the same time, compared with the traditional culture method, the practicability of UPT is verified. Results: The coefficient of variation in laboratory was 9.62% and 8.02% when the concentration of 10⁷ CFU/ml and 10⁸ CFU/ml were detected by UPT. The results were less than the allowable target, and the detection system had good stability. The specificity of UPT was verified by Staphylococcus aureus. The results showed that no non-Staphylococcus aureus was detected, and the positive detection rate of different kinds of Staphylococcus aureus was 100%. The specificity of the detection system was good. The sensitivity of UPT for detecting Staphylococcus aureus was 10⁴ CFU/ml. Detection sensitivity of Yersinia pestis ≥10³ CFU/ml; The detection sensitivity of Escherichia coli O157 is ≥10³ CFU/ml, and the response time of UPT to bacteria is within 15 min (all 10 min 15 s). The detection results of bacteria contentration in the air of the on-site microenvironment test cabin by UPT showed that when the concentration of Escherichia coli O157 in the air reached above 10⁴ CFU/m³, the detection results of UPT were positive, and with the increase of air concentration, the numerical concentration measured by UPT showed an upward trend, which was positively correlated with the concentration of bacteria in the air. Conclusion: UPT may be feasible as a rapid method to evaluate the species and contentration of pathogenic organisms in the air.
Humans ; Sensitivity and Specificity ; Technology

Objective: To analyze the drug resistance and multilocus sequence typing of five types of diarrheagenic Escherichia coli (DEC) isolated from diarrhea outpatients of diarrhea comprehensive monitoring designated hospital in Qingpu District, Shanghai from 2015 to 2019. Methods: From January 2015 to December 2019, five types of DEC, isolated and identified from diarrhea outpatient cases' anal swabs of the Qingpu branch of Zhongshan Hospital were collected to determine the minimal inhibitory concentration by using the micro broth dilution susceptibility test. The strains, resistant to the third-generation cephalosporins or carbapenems, or producing ESBLs, were selected based on the results of sensitivity tests and determined by WGS. The MLST typing of DEC was analyzed based on the WGS technology and the minimum spanning tree was constructed by BioNumerics 7.6 software to analyze the local dominant flora. Results: A total of 513 strains of DEC were detected and isolated from 4 494 anal swabs, with a detection rate of 11.42%. About 500 strains were tested for drug sensitivity to nine antibiotics in four classes, including 330 strains of enterotoxigenic E.coli (ETEC), 72 strains of enteroaggregative E.coli (EAEC), 95 strains of enteropathogenic E.coli (EPEC), 1 strain of enterohemorrhagic E.coli (EHEC), and 2 strains of enteroinvasive E.coli (EIEC). From 2015 to 2019, the resistance rate of cefotaxime-clavulanic acid was significantly different (P<0.05). The resistance rate of virulence types of DEC to nalixic acid was significantly different (P<0.05). About 71 strains of DEC were determined by WGS, and 77 drug-resistant genes were detected. Strains were classified into 32 ST subtypes, with the dominant genotypes being ST-1491 (29.6%, 21/71) and ST-10 Complex (23.9%, 17/71). All ST-1491 produced ESBLs, which were bla_CTX-M gene mutant strains. The dominant type of ST-10 complex was ST-218 (35.3%, 6/17). In addition, 8 strains of EAEC, 14 strains of EPEC and 49 strains of ETEC were classified into 7, 14 and 18 ST subtypes, respectively. Conclusion: The drug resistance of DEC strains from the diarrhea outpatient case of Qingpu District is serious. The ST types of EAEC and EPEC are highly polymorphic. The dominant ST types of DEC are basically consistent with the common genotypes in southeast China.

Objective: To analyze the drug resistance and multilocus sequence typing of five types of diarrheagenic Escherichia coli (DEC) isolated from diarrhea outpatients of diarrhea comprehensive monitoring designated hospital in Qingpu District, Shanghai City from 2015 to 2019. Methods: From January 2015 to December 2019, five types of DEC, isolated and identified from diarrhea outpatient cases' anal swabs of the Qingpu branch of Zhongshan Hospital were collected to determine the minimal inhibitory concentration by using the micro broth dilution susceptibility test. The strains, resistant to the third-generation cephalosporins or carbapenems, or producing ESBLs, were selected based on the results of sensitivity tests and determined by WGS. The MLST typing of DEC was analyzed based on the WGS technology and the minimum spanning tree was constructed by BioNumerics 7.6 software to analyze the local dominant flora. Results: A total of 513 strains of DEC were detected and isolated from 4 494 anal swabs, with a detection rate of 11.42%. About 500 strains were tested for drug sensitivity to nine antibiotics in four classes, including 330 strains of enterotoxigenic E.coli (ETEC), 72 strains of enteroaggregative E.coli (EAEC), 95 strains of enteropathogenic E.coli (EPEC), 1 strain of enterohemorrhagic E.coli (EHEC), and 2 strains of enteroinvasive E.coli (EIEC). From 2015 to 2019, the resistance rate of cefotaxime-clavulanic acid was significantly different (P<0.05). The resistance rate of virulence types of DEC to nalixic acid was significantly different (P<0.05). About 71 strains of DEC were determined by WGS, and 77 drug-resistant genes were detected. Strains were classified into 32 ST subtypes, with the dominant genotypes being ST-1491 (29.6%, 21/71) and ST-10 Complex (23.9%, 17/71). All ST-1491 produced ESBLs, which were bla_CTX-M gene mutant strains. The dominant type of ST-10 complex was ST-218 (35.3%, 6/17). In addition, 8 strains of EAEC, 14 strains of EPEC and 49 strains of ETEC were classified into 7, 14 and 18 ST subtypes, respectively. Conclusion: The drug resistance of DEC strains from the diarrhea outpatient case of Qingpu District is serious. The ST types of EAEC and EPEC are highly polymorphic. The dominant ST types of DEC are basically consistent with the common genotypes in southeast China.

Objective: To analyze the drug resistance and multilocus sequence typing of five types of diarrheagenic Escherichia coli (DEC) isolated from diarrhea outpatients of diarrhea comprehensive monitoring designated hospital in Qingpu District, Shanghai City from 2015 to 2019. Methods: From January 2015 to December 2019, five types of DEC, isolated and identified from diarrhea outpatient cases' anal swabs of the Qingpu branch of Zhongshan Hospital were collected to determine the minimal inhibitory concentration by using the micro broth dilution susceptibility test. The strains, resistant to the third-generation cephalosporins or carbapenems, or producing ESBLs, were selected based on the results of sensitivity tests and determined by WGS. The MLST typing of DEC was analyzed based on the WGS technology and the minimum spanning tree was constructed by BioNumerics 7.6 software to analyze the local dominant flora. Results: A total of 513 strains of DEC were detected and isolated from 4 494 anal swabs, with a detection rate of 11.42%. About 500 strains were tested for drug sensitivity to nine antibiotics in four classes, including 330 strains of enterotoxigenic E.coli (ETEC), 72 strains of enteroaggregative E.coli (EAEC), 95 strains of enteropathogenic E.coli (EPEC), 1 strain of enterohemorrhagic E.coli (EHEC), and 2 strains of enteroinvasive E.coli (EIEC). From 2015 to 2019, the resistance rate of cefotaxime-clavulanic acid was significantly different (P<0.05). The resistance rate of virulence types of DEC to nalixic acid was significantly different (P<0.05). About 71 strains of DEC were determined by WGS, and 77 drug-resistant genes were detected. Strains were classified into 32 ST subtypes, with the dominant genotypes being ST-1491 (29.6%, 21/71) and ST-10 Complex (23.9%, 17/71). All ST-1491 produced ESBLs, which were bla_CTX-M gene mutant strains. The dominant type of ST-10 complex was ST-218 (35.3%, 6/17). In addition, 8 strains of EAEC, 14 strains of EPEC and 49 strains of ETEC were classified into 7, 14 and 18 ST subtypes, respectively. Conclusion: The drug resistance of DEC strains from the diarrhea outpatient case of Qingpu District is serious. The ST types of EAEC and EPEC are highly polymorphic. The dominant ST types of DEC are basically consistent with the common genotypes in southeast China.