Background/Aims: Obesity is associated with several gastrointestinal (GI) disorders and has been identified as a potential risk factor for various GI symptoms. Bowel frequency is an important indicator of bowel function. However, the causal link between obesity and gastrointestinal motility remains uncertain. This study aims to determine the causal effect of overall and central obesity on stool frequency. Methods: Four obesity-related anthropometric indicators–body mass index, body fat percentage, waist circumference (WC), and waist-tohip ratio (WHR)–were investigated. Individual-level baseline information from the UK Biobank was used to explore observational associations between obesity and stool frequency. Additionally, summary-level data from published genome-wide association studies were subjected to two-sample Mendelian randomization (MR) analyses to examine causal associations. Results: For all 4 indicators of obesity, higher levels of obesity were associated with more frequent bowel movements after adjusting for demographic characteristics, lifestyle, and dietary factors. After rigorous screening, 482 body mass index single nucleotide polymorphisms (SNPs), 7 body fat percentage SNPs, 48 WC SNPs, and 287 WHR SNPs were identified as instrument variables for MR analysis. The MR results were generally consistent with observational findings, proving that the associations observed in the overall obesity indicators were causal. For central obesity, the association between WHR and stool frequency remained consistent in both analysis phases, whereas WC showed a multidirectional association. Conclusions Obesity-related anthropometric indicators were causally associated with increased stool frequency in the overall and central obesity groups. Weight loss could be a potential approach to improve gastrointestinal regularity in individuals with obesity.

Background/Aims: Obesity is associated with several gastrointestinal (GI) disorders and has been identified as a potential risk factor for various GI symptoms. Bowel frequency is an important indicator of bowel function. However, the causal link between obesity and gastrointestinal motility remains uncertain. This study aims to determine the causal effect of overall and central obesity on stool frequency. Methods: Four obesity-related anthropometric indicators–body mass index, body fat percentage, waist circumference (WC), and waist-tohip ratio (WHR)–were investigated. Individual-level baseline information from the UK Biobank was used to explore observational associations between obesity and stool frequency. Additionally, summary-level data from published genome-wide association studies were subjected to two-sample Mendelian randomization (MR) analyses to examine causal associations. Results: For all 4 indicators of obesity, higher levels of obesity were associated with more frequent bowel movements after adjusting for demographic characteristics, lifestyle, and dietary factors. After rigorous screening, 482 body mass index single nucleotide polymorphisms (SNPs), 7 body fat percentage SNPs, 48 WC SNPs, and 287 WHR SNPs were identified as instrument variables for MR analysis. The MR results were generally consistent with observational findings, proving that the associations observed in the overall obesity indicators were causal. For central obesity, the association between WHR and stool frequency remained consistent in both analysis phases, whereas WC showed a multidirectional association. Conclusions Obesity-related anthropometric indicators were causally associated with increased stool frequency in the overall and central obesity groups. Weight loss could be a potential approach to improve gastrointestinal regularity in individuals with obesity.

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.

With the rapid development of mobile internet technology, mobile health application (mHealth APP) are increasingly widely used in the field of health management and have been proven to play an important role in the management of chronic diseases. Solid organ transplant recipients face complex health management needs after surgery, including postoperative follow-up, medication management, prevention and treatment of complications and comorbidities, and lifestyle adjustment. mHealth APP can provide solid organ transplant recipients with convenient self-management tools. Although some progress has been made in this field, there are still many challenges, such as insufficient user experience, technological dependence, and data security risks. Therefore, this article discusses the development process, main functions and current application status of mHealth APP, and analyzes its advantages in improving the self-management ability of solid organ transplant recipients, promoting doctor-patient communication and reducing the incidence of complications. At the same time, based on the practical experience of author’s team in developing the “TransMate” mHealth APP, we propose the directions that mHealth APPs should focus on in the future, in order to provide more effective support and services for the health management of solid organ transplant recipients.

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.

Background/Aims: Obesity is associated with several gastrointestinal (GI) disorders and has been identified as a potential risk factor for various GI symptoms. Bowel frequency is an important indicator of bowel function. However, the causal link between obesity and gastrointestinal motility remains uncertain. This study aims to determine the causal effect of overall and central obesity on stool frequency. Methods: Four obesity-related anthropometric indicators–body mass index, body fat percentage, waist circumference (WC), and waist-tohip ratio (WHR)–were investigated. Individual-level baseline information from the UK Biobank was used to explore observational associations between obesity and stool frequency. Additionally, summary-level data from published genome-wide association studies were subjected to two-sample Mendelian randomization (MR) analyses to examine causal associations. Results: For all 4 indicators of obesity, higher levels of obesity were associated with more frequent bowel movements after adjusting for demographic characteristics, lifestyle, and dietary factors. After rigorous screening, 482 body mass index single nucleotide polymorphisms (SNPs), 7 body fat percentage SNPs, 48 WC SNPs, and 287 WHR SNPs were identified as instrument variables for MR analysis. The MR results were generally consistent with observational findings, proving that the associations observed in the overall obesity indicators were causal. For central obesity, the association between WHR and stool frequency remained consistent in both analysis phases, whereas WC showed a multidirectional association. Conclusions Obesity-related anthropometric indicators were causally associated with increased stool frequency in the overall and central obesity groups. Weight loss could be a potential approach to improve gastrointestinal regularity in individuals with obesity.

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.

In recent years, there has been a growing interest in the research on NOD-like receptor thermal protein domain associated protein 3(NLRP3) inflammasome inhibitors in the treatment of inflammatory diseases. The NLRP3 inflammasome is integral to the innate immune response, and its abnormal activation can lead to the release of pro-inflammatory cytokine, consequently facilitating the progression of various pathological conditions. Therefore, investigating the pharmacological inhibition pathway of the NLRP3 inflammasome represents a promising strategy for the treatment of inflammation-related diseases. Currently, the Food and Drug Administration(FDA) has not approved drugs targeting the NLRP3 inflammasome for clinical use due to concerns regarding liver toxicity and gastrointestinal side effects associated with chemical small molecule inhibitors in clinical trials. Natural small molecule compounds such as polyphenols, flavonoids, and alkaloids are ubiquitously found in animals, plants, and other natural substances exhibiting pharmacological activities. Their abundant sources, intricate and diverse structures, high biocompatibility, minimal adverse reactions, and superior biochemical potency in comparison to synthetic compounds have attracted the attention of extensive scholars. Currently, certain natural small molecule compounds have been demonstrated to impede the activation of the NLRP3 inflammasome via various action mechanisms, so they are viewed as the innovative, feasible, and minimally toxic therapeutic agents for inhibiting NLRP3 inflammasome activation in the treatment of both acute and chronic inflammatory diseases. Hence, this study systematically examined the effects and potential mechanisms of natural small molecule compounds derived from traditional Chinese medicine on the activation of NLRP3 inflammasomes at their initiation, assembly, and activation stages. The objection is to furnish theoretical support and practical guidance for the effective clinical application of these natural small molecule inhibitors.
NLR Family, Pyrin Domain-Containing 3 Protein/metabolism* ; Inflammasomes/metabolism* ; Inflammation/drug therapy* ; Anti-Inflammatory Agents/therapeutic use* ; Humans ; Animals ; Disease Models, Animal ; Biological Products/therapeutic use* ; Drug Discovery ; Medicine, Chinese Traditional/methods*