Development and validation of a nomogram to predict non-response to 5-aminosalicylic acid in patients with ulcerative colitis.

BACKGROUND: there are some patients with ulcerative colitis (UC) who have non-response (NR) to 5-aminosalicylic acid (5-ASA). To promote individualized treatment in UC patients, it is crucial to identify valid predictors to estimate NR to 5-ASA. Therefore, this study aimed to identify the predictive value of clinical and biochemical markers and to construct a nomogram model predicting NR to 5-ASA in patients with UC. METHODS: data of patients diagnosed with UC in the First Hospital of China Medical University between January 2012 and December 2020 were retrospectively analyzed. Primary outcome was the proportion of NR to 5-ASA. Multivariable logistic regression was used to construct prediction models. Area under the curve (AUC), calibration and decision curve analyses (DCA) were assessed in the validation cohort. RESULTS: of 284 UC patients who were treatment-naive, 86 (30.3 %) had NR to 5-ASA. Univariate regression analysis showed that disease classification (DC) (p = 0.008), monocytes (MONO) (p = 0.041), platelet distribution width (PDW) (p = 0.027), serum total cholesterol (TC) (p = 0.031) and α1 globulin (p < 0.001) were strongly associated with NR to 5-ASA. Receiver operating characteristics (ROC) analysis indicated the AUC was 0.852, it showed that this model has a good degree of discrimination. The DCA curve showed that the predicted probability is 0.0-96.0 %. CONCLUSION: this study developed a predictive model with good discrimination and calibration, and high clinical validity, which can effectively estimate the risk of NR to 5-ASA. DC, MONO, PDW, TC and α1 globulin can be used as predictors for NR to 5-ASA in UC patients.

Development and validation of a nomogram to predict non-response to 5-aminosalicylic acid in patients with ulcerative colitis

Background: there are some patients with ulcerative colitis (UC) who have non-response (NR) to 5-aminosalicylic acid (5-ASA). To promote individualized treatment in UC patients, it is crucial to identify valid predictors to estimate NR to 5-ASA. Therefore, this study aimed to identify the predictive value of clinical and biochemical markers and to construct a nomogram model predicting NR to 5-ASA in patients with UC. Methods: data of patients diagnosed with UC in the First Hospital of China Medical University between January 2012 and December 2020 were retrospectively analyzed. Primary outcome was the proportion of NR to 5-ASA. Multivariable logistic regression was used to construct prediction models. Area under the curve (AUC), calibration and decision curve analyses (DCA) were assessed in the validation cohort. Results: of 284 UC patients who were treatment-naive, 86 (30.3 %) had NR to 5-ASA. Univariate regression analysis showed that disease classification (DC) (p = 0.008), monocytes (MONO) (p = 0.041), platelet distribution width (PDW) (p = 0.027), serum total cholesterol (TC) (p = 0.031) and α1 globulin (p < 0.001) were strongly associated with NR to 5-ASA. Receiver operating characteristics (ROC) analysis indicated the AUC was 0.852, it showed that this model has a good degree of discrimination. The DCA curve showed that the predicted probability is 0.0-96.0 %. Conclusion: this study developed a predictive model with good discrimination and calibration, and high clinical validity, which can effectively estimate the risk of NR to 5-ASA. DC, MONO, PDW, TC and α1 globulin can be used as predictors for NR to 5-ASA in UC patients. (AU)

Advances of mesenchymal stem cells and their derived extracellular vesicles as a promising therapy for acute respiratory distress syndrome: from bench to clinic.

Acute respiratory distress syndrome (ARDS) is an acute inflammatory lung injury characterized by diffuse alveolar damage. The period prevalence of ARDS was 10.4% of ICU admissions in 50 countries. Although great progress has been made in supportive care, the hospital mortality rate of severe ARDS is still up to 46.1%. Moreover, up to now, there is no effective pharmacotherapy for ARDS and most clinical trials focusing on consistently effective drugs have met disappointing results. Mesenchymal stem cells (MSCs) and their derived extracellular vesicles (EVs) have spawned intense interest of a wide range of researchers and clinicians due to their robust anti-inflammatory, anti-apoptotic and tissue regeneration properties. A growing body of evidence from preclinical studies confirmed the promising therapeutic potential of MSCs and their EVs in the treatment of ARDS. Based on the inspiring experimental results, clinical trials have been designed to evaluate safety and efficacy of MSCs and their EVs in ARDS patients. Moreover, trials exploring their optimal time window and regimen of drug administration are ongoing. Therefore, this review aims to present an overview of the characteristics of mesenchymal stem cells and their derived EVs, therapeutic mechanisms for ARDS and research progress that has been made over the past 5 years.

Reply: SARS-CoV-2 vaccination in inflammatory bowel disease patients with different biological agents.

We thank Dr Mungmunpuntipantip and colleague for their interest and thoughtful comments on our publication. The authors have highlighted several important considerations for the impact of SARS-CoV-2 vaccination in inflammatory bowel disease (IBD) patients with different biological agents. We fully agree with the author's point of view, and we also point out the limitations in our meta-analysis.

Impact of SARS-CoV-2 vaccination in inflammatory bowel disease patients with different biological agents: a systematic review and meta-analysis.

BACKGROUND: There are concerns regarding the effect of biological agents on SARS-CoV-2 vaccination in patients with inflammatory bowel disease (IBD). A systematic review and meta-analysis was performed about the serological responses, breakthrough infections and clinical relapse of IBD patients treated with biological agents following SARS-CoV-2 vaccination. METHODS: Electronic databases were searched to identify relevant studies. Primary outcomes were the pooled seroconversion rates, breakthrough infection rates and clinical relapse rates after SARS-CoV-2 vaccination in IBD patients treated with biological agents. Secondary outcomes were the comparison of seroconversion rates, breakthrough infection rates and clinical relapse rates in IBD patients treated with biological agents and control cohort after SARS-CoV-2 vaccination. RESULTS: Thirty-five studies were included in this meta-analysis. A high percentage of seroconversion (96.6%, 99% and 99.2%) was achieved in IBD patients treated with anti-TNF-α therapy, vedolizumab and ustekinumab after SARS-CoV-2 vaccination, respectively. The pooled breakthrough infection rate was 2.5% and 3.9% in IBD patients treated with anti-TNF-α therapy and vedolizumab, respectively. The breakthrough infection rate in IBD patients treated with anti-TNF-α therapy was significantly lower than control cohort (RR 0.178, 95% CI 0.084-0.378). The pooled clinical relapse rate in IBD patients treated with anti-TNF-α therapy, vedolizumab and ustekinumab was 6.9%, 5.4% and 5.3%, respectively. CONCLUSION: The overall seroconversion rate after SARS-CoV-2 vaccination in IBD patients treated with biological agents is high. The overall breakthrough infection rate and clinical relapse rate in IBD patients treated with biological agents were low.

Impact of SARS-CoV-2 vaccination in inflammatory bowel disease patients with different biological agents: a systematic review and meta-analysis

Background: There are concerns regarding the effect of biological agents on SARS-CoV-2 vaccination in patients with inflammatory bowel disease (IBD). A systematic review and meta-analysis was performed about the serological responses, breakthrough infections and clinical relapse of IBD patients treated with biological agents following SARS-CoV-2 vaccination. Methods: Electronic databases were searched to identify relevant studies. Primary outcomes were the pooled seroconversion rates, breakthrough infection rates and clinical relapse rates after SARS-CoV-2 vaccination in IBD patients treated with biological agents. Secondary outcomes were the comparison of seroconversion rates, breakthrough infection rates and clinical relapse rates in IBD patients treated with biological agents and control cohort after SARS-CoV-2 vaccination. Results: Thirty-five studies were included in this meta-analysis. A high percentage of seroconversion (96.6%, 99% and 99.2%) was achieved in IBD patients treated with anti-TNF-α therapy, vedolizumab and ustekinumab after SARS-CoV-2 vaccination, respectively. The pooled breakthrough infection rate was 2.5% and 3.9% in IBD patients treated with anti-TNF-α therapy and vedolizumab, respectively. The breakthrough infection rate in IBD patients treated with anti-TNF-α therapy was significantly lower than control cohort (RR 0.178, 95% CI 0.084–0.378). The pooled clinical relapse rate in IBD patients treated with anti-TNF-α therapy, vedolizumab and ustekinumab was 6.9%, 5.4% and 5.3%, respectively. Conclusion: The overall seroconversion rate after SARS-CoV-2 vaccination in IBD patients treated with biological agents is high. The overall breakthrough infection rate and clinical relapse rate in IBD patients treated with biological agents were low (AU)

The diagnostic and predictive value of fecal calprotectin and capsule endoscopy for small-bowel Crohn's disease: a systematic review and meta-analysis.

BACKGROUND: there are no clarified non-invasive methods to evaluate small bowel inflammation in Crohn's disease. AIMS: to evaluate the accuracy of fecal calprotectin and capsule endoscopy for the diagnosis of small bowel Crohn's disease and to predict relapse. METHODS: a systematic literature search was performed for studies to diagnose and predict relapse of the disease with fecal calprotectin and capsule endoscopy. The relevant pooled data including sensitivity, specificity, diagnostic odds ratio, positive likelihood ratio, negative likelihood ratio and area under curve were calculated using Stata 14.0. RESULTS: twenty-one studies were included in the final analyses. The diagnostic accuracy of the disease and relapse were obtained for capsule endoscopy, with a pooled sensitivity of 0.90 and 0.82, specificity of 0.76 and 0.56, diagnostic odds ratio of 33 and 6, and area under curve of 0.92 and 0.82, respectively. Diagnostic accuracy of the disease was calculated for fecal calprotectin values of 50, 100 and 200 ug/g; the sensitivity values were 0.84, 0.66 and 0.45; specificity values were 0.49, 0.74 and 0.87; diagnostic odds ratio were 5, 5 and 5; and area under curve were 0.74, 0.76 and 0.75, respectively. A fecal calprotectin level of 100-140 ug/g for the prediction of relapse had a pooled sensitivity of 0.68, specificity of 0.91, diagnostic odds ratio of 21, and area under curve of 0.77. CONCLUSION: capsule endoscopy is effective in diagnosing small bowel Crohn's disease and predicting relapse. Fecal calprotectin is an accurate surrogate technique to diagnose small bowel inflammation in Crohn's disease. Furthermore, the best scenario for fecal calprotectin is the prediction of relapse.

The Prevalence of Gastrointestinal Symptoms, Abnormal Liver Function, Digestive System Disease and Liver Disease in COVID-19 Infection: A Systematic Review and Meta-Analysis.

BACKGROUND: The worldwide outbreak of COVID-19 infected millions of people. Some patients had gastrointestinal (GI) symptoms, abnormal liver function, digestive system disease and liver disease. AIM: To investigate the prevalence of GI symptoms, abnormal liver function, digestive system disease and liver disease in patients with COVID-19 by a systematic review and meta-analysis. METHODS: We searched PubMed, Ovid Embase, Medline, and 2 Chinese databases. Primary outcomes were the prevalence of GI symptoms, abnormal liver function, digestive system disease, and liver disease. Different studies were included in different subset analysis. These outcomes were estimated with proportions, odds ratio, 95% confidence interval (CI) and P-value by Stata SE 15.1. RESULTS: Thirty-one studies involving 4682 patients were included. The most significant GI symptoms were diarrhea (0.08, 95% CI: 0.06-0.11) and anorexia (0.17, 95% CI: 0.06-0.27). The most significant abnormal liver function was increased alanine aminotransferase (ALT) (0.25, 95% CI: 0.16-0.33). A total of 5% of the patients had digestive system disease (95% CI: 0.02-0.08). A total of 3% of the patients had liver disease (95% CI: 0.02-0.05). The prevalence of nausea and vomiting, diarrhea, abnormal liver function, digestive system disease, and liver disease was higher in Wuhan group. The prevalence of diarrhea was higher in non-China group. Patients in severe/intensive care unit group were more likely to have diarrhea, anorexia, abdominal pain increased aspartate aminotransferase, and increased ALT. CONCLUSION: The most significant GI symptoms were anorexia and diarrhea. The most significant abnormal liver function was increased ALT. Severe patients were more likely to have GI symptoms and abnormal liver function.

The integration of multi-platform MS-based metabolomics and multivariate analysis for the geographical origin discrimination of Oryza sativa L.

For the authentication of white rice from different geographical origins, the selection of outstanding discrimination markers is essential. In this study, 80 commercial white rice samples were collected from local markets of Korea and China and discriminated by mass spectrometry-based untargeted metabolomics approaches. Additionally, the potential markers that belong to sugars & sugar alcohols, fatty acids, and phospholipids were examined using several multivariate analyses to measure their discrimination efficiencies. Unsupervised analyses, including principal component analysis and k-means clustering demonstrated the potential of the geographical classification of white rice between Korea and China by fatty acids and phospholipids. In addition, the accuracy, goodness-of-fit (R2), goodness-of-prediction (Q2), and permutation test p-value derived from phospholipid-based partial least squares-discriminant analysis were 1.000, 0.902, 0.870, and 0.001, respectively. Random Forests further consolidated the discrimination ability of phospholipids. Furthermore, an independent validation set containing 20 white rice samples also confirmed that phospholipids were the excellent discrimination markers for white rice between two countries. In conclusion, the proposed approach successfully highlighted phospholipids as the better discrimination markers than sugars & sugar alcohols and fatty acids in differentiating white rice between Korea and China.

Optimized Mass Spectrometry-Based Metabolite Extraction and Analysis for the Geographical Discrimination of White Rice (Oryza sativa L.): A Method Comparison Study.

In this study, we examined the effects of different extraction methods for the GC-MS- and LC-MS-based metabolite profiling of white rice (Oryza sativa L.). In addition, the metabolite divergence of white rice cultivated in either Korea or China was also evaluated. The discrimination analysis of each extraction method for white rice from Korea and China and the corresponding discriminatory markers were estimated by unpaired t-test, principal component analysis, k-means cluster analysis, partial least-squares discriminant analysis (PLS-DA), and random forest (RF). According to the prediction parameters obtained from PLS-DA and RF classifiers as well as features that could be identified, the extraction method using 75% isopropanol heated at 100°C coupled with LC-MS analysis was confirmed to be superior to the other extraction methods. Noticeably, lysophospholipid concentrations were significantly different in white rice between Korea and China, and they are novel markers for geographical discrimination. In conclusion, our study suggests an optimized extraction and analysis method as well as novel markers for the geographical discrimination of white rice.

Combination of mass spectrometry-based targeted lipidomics and supervised machine learning algorithms in detecting adulterated admixtures of white rice.

The mixing of extraneous ingredients with original products is a common adulteration practice in food and herbal medicines. In particular, authenticity of white rice and its corresponding blended products has become a key issue in food industry. Accordingly, our current study aimed to develop and evaluate a novel discrimination method by combining targeted lipidomics with powerful supervised learning methods, and eventually introduce a platform to verify the authenticity of white rice. A total of 30 cultivars were collected, and 330 representative samples of white rice from Korea and China as well as seven mixing ratios were examined. Random forests (RF), support vector machines (SVM) with a radial basis function kernel, C5.0, model averaged neural network, and k-nearest neighbor classifiers were used for the classification. We achieved desired results, and the classifiers effectively differentiated white rice from Korea to blended samples with high prediction accuracy for the contamination ratio as low as five percent. In addition, RF and SVM classifiers were generally superior to and more robust than the other techniques. Our approach demonstrated that the relative differences in lysoGPLs can be successfully utilized to detect the adulterated mixing of white rice originating from different countries. In conclusion, the present study introduces a novel and high-throughput platform that can be applied to authenticate adulterated admixtures from original white rice samples.