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.

Objective To investigate the effective components and therapeutic mechanism of Chaihu-Guizhi-Ganjiang decoction in treating chronic non-atrophic gastritis. Methods The primary and secondary ion fragments of chemical components of Chaihu-Guizhi-Ganjiang decoction were obtained by UHPLC-Q-TOF/MS. Comparing with reference standards and literature information, a comprehensive characterization of the chemical constituents of Chaihu-Guizhi-Ganjiang decoction was conducted. Then, the network pharmacology approach was applied to explore the therapeutic mechanism of Chaihu-Guizhi-Ganjiang decoction in treatment of chronic non-atrophic gastritis based on the components in plasma and verified by immunohistochemical results. Results A total of 24 absorbed components of Chaihu-Guizhi-Ganjiang decoction were characterized, including 11 flavonoid glycosides, 3 fatty acids, 3organic acids, 2 gingerols, 2 flavonoids and, 1 each of fatty aldehydes, triterpenoids and amino acids, which mainly acted on TNF-α, IL-6, STAT3, and PTGS2. It exerted therapeutic effects by modulating signaling pathways, including the IL-17 signaling pathway and the AGE-RAGE signaling pathway, etc. Conclusion This study provided the first exploration of the effective components and therapeutic mechanism of Chaihu-Guizhi-Ganjiang decoction in treatment of chronic non-atrophic gastritis by UHPLC-Q-TOF/MS, which could offer scientific references for its further research.

Image 1.

OBJECTIVE: To investigate the association between ABO blood types and gestational diabetes mellitus (GDM) risk. METHODS: A prospective birth cohort study was conducted. ABO blood types were determined using the slide method. GDM diagnosis was based on a 75-g, 2-h oral glucose tolerance test (OGTT) according to the criteria of the International Association of Diabetes and Pregnancy Study Groups. Logistic regression was applied to calculate the odds ratios ( ORs) and 95% confidence intervals ( CIs) between ABO blood types and GDM risk. RESULTS: A total of 30,740 pregnant women with a mean age of 31.81 years were enrolled in this study. The ABO blood types distribution was: type O (30.99%), type A (26.58%), type B (32.20%), and type AB (10.23%). GDM was identified in 14.44% of participants. Using blood type O as a reference, GDM risk was not significantly higher for types A ( OR = 1.05) or B ( OR = 1.04). However, women with type AB had a 19% increased risk of GDM ( OR = 1.19, 95% CI = 1.05-1.34; P < 0.05), even after adjusting for various factors. This increased risk for type AB was consistent across subgroup and sensitivity analyses. CONCLUSION The ABO blood types may influence GDM risk, with type AB associated with a higher risk. Incorporating it-either as a single risk factor or in combination with other known factors-could help identify individuals at risk for GDM before or during early pregnancy.
Humans ; Female ; Pregnancy ; Diabetes, Gestational/etiology* ; ABO Blood-Group System ; Adult ; Prospective Studies ; Risk Factors ; Young Adult

Helicobacter pylori(HP)infection is a Class Ⅰ carcinogen in gastric cancer,closely related to the occurrence of gastric cancer.Many studies have shown that HP eradication has a preventive effect on gastric cancer.However,2.7%-6.1%of patients with early gastric cancer who have been eradicated after endoscopic submucosal dissection(ESD)can still develop metachronous gastric cancer(MGC),and the mechanism of its occurrence is still unclear.In this review,the atrophy of gastric mucosa and intestinal metaplasia cannot be completely reversed after HP eradication,the excessive proliferation of gastric mucosa epithelial cells,the accumulation of genetic abnormalities,the homeostasis imbalance of the epigenetic group,changes in immune microenvironment,the abnormality of stem cells in gastric mucosa,chromatin accessibility,and changes in chromosome remodeling were discussed in the mechanism of carcinogenesis caused by the above molecular changes after ESD and HP eradication in early gastric cancer.

Objective To investigate the role of pulmonary neuroendocrine cells(PNEC)and γ-aminobutyric acid(GABA)in patients with pulmonary neuroendocrine tumors(PNET).Methods The pathological specimens of 29 cases of PNET treated in the eighth Medical Center of Chinese PLA General Hospital from October 2018 to January 2022 were collected.The morphological characteristics were observed by HE staining,and the expression levels of synaptophysin(Syn),chromogranin A(CgA),CD56,Ki-67,CD86 and CD163 were observed by immunohistochemical staining.Calcitonin gene-related peptide(CGRP)and glutamic acid decarboxylase(GAD)65/67 in different types of PNETs were detected by double antibody immunofluorescence co-staining,and the correlation between GAD65/67 positive PNEC and macrophage polarization was analyzed.Results The results of HE staining showed that all four types of PNET tissues had neuroendocrine(NE)characteristics:rosette structure and organ nesting or palisade pattern,but they were different,and the proportion of mitotic cells from low to high was typical carcinoid(TC),atypical carcinoid(AC),large cell neuroendocrine carcinoma(LCNEC)and small cell lung cancer(SCLC).The results of immunohistochemical staining showed that the positive expression rate of Syn and CgA and the positive degree of Syn,CgA and CD56 in carcinoid(TC and AC)were significantly higher than those in LCNEC and SCLC(P＜0.05).The Ki-67 indices of the four types of PNET are:TC＜5%,AC 5%-20%,LCNEC and SCLC＞75%respectively.The number of PNEC in carcinoid was significantly higher than that in LCNEC,SCLC and paratumoral tissues(P＜0.05),but there was no significant difference in the number of PNEC between LCNEC and SCLC and para-tumor tissues(P＞0.05).The results of immunofluorescence staining showed that the number of GAD65/67 positive cells co-expressing GAD65/67 in 95%PNEC was significantly higher than that in LCNEC,SCLC and para-tumor tissues(P＜0.05),but there was no significant difference between LCNEC and SCLC GAD65/67 positive cells and para-tumor tissues(P＞0.05).The results of immunohistochemical staining also showed that the number of CD86 positive M1 macrophages was significantly higher than that of CD163 positive M2 macrophages in para-tumor tissues(P＜0.05),while M2 macrophages were significantly more than M1 macrophages in AC,LCNEC and SCLC(P＜0.01).Correlation analysis showed that the number of GAD65/67 positive PNEC cells in PNET was negatively correlated with the number of CD163 positive M2 macrophages in tumor stroma(r=-0.6336,P=0.0174).Conclusions PNEC is the main source of GABA in lung tissue and plays an immunomodulatory role in the lung,which may be involved in the progression of PNET.