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.

Japan is one of the main trading partners for the import and export of experimental animals in China,and its quarantine and supervision policies for the import and export of experimental animals are very detailed and strict.This article takes experimental dogs,cats,and monkeys as examples to provide an in-depth analysis of the quarantine and supervision policies for the main experimental animals exported to Japan.At the same time,it reflects on the current laws and regulations,import and export management method,standards,biosafety,breeding and management status,as well as the import and export business status of experimental animals in China.Suggestions are provided in improving the laws and regulations,import and export management method,ensuring national biosafety,improving the management level of experimental animal breeding,and promoting the import and export trade of experimental animals,in order to provide reference for comprehensively improving the production,use,and breeding management level of experimental animals in China and strengthening the trade between China and Japan.

Objective To explore the difference in gut microbiota composition between patients with obstructive sleep apnea(OSA)and healthy individuals and the role of gut microbiota in the pathogenesis of OSA.Methods Thirty-nine patients with OSA admitted to our hospital between May and December,2022 and 20 healthy individuals were enrolled in this study.Stool samples were collected from all the participants for analysis of microbiome composition using 16S rRNA high-throughput sequencing analysis.The alpha diversity,beta diversity,and species difference were determined between the two groups and marker species analysis and metabolic pathway function prediction analysis were performed.Results The species diversity(Shannon and Simpson)indexes,richness(observed species)and evenness(Pielou)of gut microbiota were significantly lower in OSA patients than in the healthy individuals(P<0.05).The OSA patients had also a significantly lowered community diversity(P<0.05)with different gut microbial communities from those of the healthy individuals shown by increased relative abundance of potentially pathogenic bacteria such as Pseudomonas and Monocytogenes(P<0.05).LEfSe analysis showed that the abundance of 23 species of gut microbiota differed significantly between the two groups and the OSA patients had significant increases in the abundance of Pseudomonas,Meganomonas,and Fusobacterium(P<0.05).The differential marker flora affected host homeostasis.Random Forest and ROC curve analyses confirmed that Pseudomonas could be used as important biomarkers for a differential diagnosis.Metabolic pathway function prediction analysis showed that biosynthesis function had the greatest contribution to maintaining gut microbiota homeostasis,and Pseudomonas affected the occurrence and progression of OSA by participating in aromatic bioamine degradation and ketogluconic acid metabolic pathway.Conclusion OSA patients have obvious gut microbiota disturbances,and Pseudomonas may affect the development of OSA by participating in substance metabolism to serve as the potential target gut bacteria for OSA treatment.

Objective To explore the difference in gut microbiota composition between patients with obstructive sleep apnea(OSA)and healthy individuals and the role of gut microbiota in the pathogenesis of OSA.Methods Thirty-nine patients with OSA admitted to our hospital between May and December,2022 and 20 healthy individuals were enrolled in this study.Stool samples were collected from all the participants for analysis of microbiome composition using 16S rRNA high-throughput sequencing analysis.The alpha diversity,beta diversity,and species difference were determined between the two groups and marker species analysis and metabolic pathway function prediction analysis were performed.Results The species diversity(Shannon and Simpson)indexes,richness(observed species)and evenness(Pielou)of gut microbiota were significantly lower in OSA patients than in the healthy individuals(P<0.05).The OSA patients had also a significantly lowered community diversity(P<0.05)with different gut microbial communities from those of the healthy individuals shown by increased relative abundance of potentially pathogenic bacteria such as Pseudomonas and Monocytogenes(P<0.05).LEfSe analysis showed that the abundance of 23 species of gut microbiota differed significantly between the two groups and the OSA patients had significant increases in the abundance of Pseudomonas,Meganomonas,and Fusobacterium(P<0.05).The differential marker flora affected host homeostasis.Random Forest and ROC curve analyses confirmed that Pseudomonas could be used as important biomarkers for a differential diagnosis.Metabolic pathway function prediction analysis showed that biosynthesis function had the greatest contribution to maintaining gut microbiota homeostasis,and Pseudomonas affected the occurrence and progression of OSA by participating in aromatic bioamine degradation and ketogluconic acid metabolic pathway.Conclusion OSA patients have obvious gut microbiota disturbances,and Pseudomonas may affect the development of OSA by participating in substance metabolism to serve as the potential target gut bacteria for OSA treatment.

Bile acids (BAs) are a group of endogenous steroid molecules that regulate lipid, glucose and energy metabolism. They play an important role in maintaining body homeostasis and physiological functions as key signaling molecules for host and gut microbial metabolism. The accurate characterization and quantification of BAs in vivo is of great importance in basic and clinical research. Over the past decades, enzymatic assay, enzyme-linked immunoassay, nuclear magnetic resonance (NMR), chromatography, and other related techniques have been developed and applied to the detection of BAs. The diverse structures of BAs, the existence of isomers and the complex matrix of biological samples pose great challenges for the detection of endogenous BAs. Ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) is a robust analytical technique that combines the rapid separation capacities of UPLC with the powerful structural identification capabilities of MS/MS, facilitating the more rapid separation, characterization and accurate quantitative of target analytes in biological samples. UPLC-MS/MS has been widely used in the quantitative analysis of BAs in recent years for its high selectivity, high sensitivity, and high accuracy. This paper summarized the biosynthetic pathways of BAs, sample pretreatment methods, common analytical detection techniques, and highlights the current status of the application of UPLC-MS/MS technology in the analysis of endogenous BAs over the past five years, to provide a reference for the accurate detection of endogenous BAs and further research development and application.

BACKGROUND: China bears the biggest atrial fibrillation (AF) burden in the world. However, little is known about the incidence and predictors of AF. This study aimed to investigate the current incidence of AF and its electrocardiographic (ECG) predictors in general community individuals aged over 60 years in China. METHODS: This was a prospective cohort study, recruiting subjects who were aged over 60 years and underwent annual health checkups from April to July 2015 in four community health centers in Songjiang District, Shanghai, China. The subjects were then followed up from 2015 to 2019 annually. Data on sociodemographic characteristics, medical history, and the resting 12-lead ECG were collected. Kaplan-Meier curve was used for showing the trends in AF incidence and calculating the predictors of AF. Associations of ECG abnormalities and AF incidence were examined using Cox proportional hazard models. RESULTS: This study recruited 18,738 subjects, and 351 (1.87%) developed AF. The overall incidence rate of AF was 5.2/1000 person-years during an observation period of 67,704 person-years. Multivariable Cox regression analysis indicated age (hazard ratio [HR], 1.07; 95% confidence interval [CI]: 1.06-1.09; P < 0.001), male (HR, 1.30; 95% CI: 1.05-1.62; P = 0.018), a history of hypertension (HR, 1.55; 95% CI: 1.23-1.95; P < 0.001), a history of cardiac diseases (HR, 3.23; 95% CI: 2.34-4.45; P < 0.001), atrial premature complex (APC) (HR, 2.82; 95% CI: 2.17-3.68; P < 0.001), atrial flutter (HR, 18.68; 95% CI: 7.37-47.31; P < 0.001), junctional premature complex (JPC) (HR, 3.57; 95% CI: 1.59-8.02; P = 0.002), junctional rhythm (HR, 18.24; 95% CI: 5.83-57.07; P < 0.001), ventricular premature complex (VPC) (HR, 1.76; 95% CI: 1.13-2.75, P = 0.012), short PR interval (HR, 5.49; 95% CI: 1.36-22.19; P = 0.017), right atrial enlargement (HR, 6.22; 95% CI: 1.54-25.14; P = 0.010), and pacing rhythm (HR, 3.99; 95% CI: 1.57-10.14; P = 0.004) were independently associated with the incidence of AF. CONCLUSIONS The present incidence of AF was 5.2/1000 person-years in the studied population aged over 60 years in China. Among various ECG abnormalities, only APC, atrial flutter, JPC, junctional rhythm, short PR interval, VPC, right atrial enlargement, and pacing rhythm were independently associated with AF incidence.
Humans ; Male ; Middle Aged ; Aged ; Atrial Fibrillation/epidemiology* ; Prospective Studies ; Incidence ; Atrial Flutter/complications* ; Risk Factors ; China/epidemiology* ; Electrocardiography