The antitumor agents

Background: Identification of patients at risk for mortality early in the course of acute pancreatitis (AP) is an important step in improving outcome. Methods: Using Classification and Regression Tree (CART) analysis, a clinical scoring system was developed for prediction of in-hospital mortality in AP. The scoring system was derived on data collected from 17 992 cases of AP from 212 hospitals in 2000-2001. The new scoring system was validated on data collected from 18 256 AP cases from 177 hospitals in 2004-2005. The accuracy of the scoring system for prediction of mortality was measured by the area under the receiver operating characteristic curve (AUC). The performance of the new scoring system was further validated by comparing its predictive accuracy with that of Acute Physiology and Chronic Health Examination (APACHE) II. Results: CART analysis identified five variables for prediction of in-hospital mortality. One point is assigned for the presence of each of the following during the first 24 h: blood urea nitrogen (BUN) >25 mg/dl; impaired mental status; systemic inflammatory response syndrome (SIRS); age >60 years; or the presence of a pleural effusion (BISAP). Mortality ranged from >20% in the highest risk group to <1% in the lowest risk group. In the validation cohort, the BISAP AUC was 0.82 (95% Cl 0.79 to 0.84) versus APACHE II AUC of 0.83 (95% Cl 0.80 to 0.85). Conclusions: A new mortality-based prognostic scoring system for use in AP has been derived and validated. The BISAP is a simple and accurate method for the early identification of patients at increased risk for in-hospital mortality.

The early prediction of mortality in acute pancreatitis : a large population-based study. Commentary

Introduction: Studying changes in the whole set of small molecules, final products of biochemical reactions in living systems or metabolites, is extremely appealing because they represent the best ...

A review of validated biomarkers obtained through metabolomics

Acute pancreatitis (AP) is a severe inflammation of the pancreas presented with sudden onset and severe abdominal pain with a high morbidity and mortality rate, if accompanied by severe local and systemic complications. Numerous studies have been published about the pathogenesis of AP; however, the precise mechanism behind this pathology remains unclear. Extensive research conducted over the last decades has demonstrated that the first 24 h after symptom onset are critical for the identification of patients who are at risk of developing complications or death. The identification of these subgroups of patients is crucial in order to start an aggressive approach to prevent mortality. In this sense and to avoid unnecessary overtreatment, thereby reducing the financial implications, the proper identification of mild disease is also important and necessary. A large number of multifactorial scoring systems and biochemical markers are described to predict the severity. Despite recent progress in understanding the pathophysiology of AP, more research is needed to enable a faster and more accurate prediction of severe AP. This review provides an overview of the available multifactorial scoring systems and biochemical markers for predicting severe AP with a special focus on their advantages and limitations.

https://www.mdpi.com/1422-0067/21/1/338/pdf

Multifactorial Scores and Biomarkers of Prognosis of Acute Pancreatitis: Applications to Research and Practice

Chemometric methods are powerful tools used in analytical sciences and beyond. Their application is continuously increasing due in part to the technological advances that allow exploration of new issues. This review presents the most common chemometric tools utilized in the most recent research articles (2018 to now), which emerge at the interface between several disciplines and instrumental techniques such as vibrational spectroscopy, electrochemistry, and hyphenated mass spectrometry techniques. The review is divided into several sections: statistical design of experiments, signal pre-processing, exploratory data analysis, predictive modelling of the data, and statistical validation. In each section, we review the main mathematical models, then we examine the trends observed in the research articles, and finally discuss the potential pitfalls to avoid during the application of the methods. We believe that bringing together the main mathematical models with the possible experimental challenges will be of great use for non-experts chemometricians.

A guide to good practice in chemometric methods for vibrational spectroscopy, electrochemistry, and hyphenated mass spectrometry

Identification of potential diagnostic biomarkers of acute pancreatitis by serum metabolomic profiles

A new sucrosephenylpropanoid ester from Polygonum pubescens Blume.

Anti-inflammatory and antioxidant activities of chemical constituents from the flower buds of Buddleja officinalis.

Cerebral infarction (CI) is one of the most common cerebrovascular diseases and remains a major health problem worldwide. In this study, we evaluated the potential diagnostic biomarkers and important relevant metabolic pathways associated with CI. Metabolomics based on gas chromatography-mass spectrometry coupled with the multivariate pattern recognition technique were used to characterize the potential serum metabolic profiles of CI. Forty healthy controls and thirty-three cerebral infarction patients were recruited for the nontargeted global metabolites' study and subsequent targeted fatty acid analysis. Overall, thirty-four endogenous metabolites were found in serum from the untargeted global study, four of which were detected to be significantly different between the CI group and healthy controls, including L-lysine, octadecanoic acid (fatty acid), L-tyrosine and lactic acid. Additionally, fourteen free fatty acids were identified by the subsequent targeted fatty acid analysis, and seven of them were detected to be significantly different between the CI group and healthy controls, which were mainly associated with arachidonic acid metabolism and fatty acid metabolism. Our results suggest several potential diagnostic biomarkers, and serum metabolism research is demonstrated as a powerful tool to explore the pathogenesis of CI.

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Qing-hua Peng

Papers

Identification of potential diagnostic biomarkers of acute pancreatitis by serum metabolomic profiles

A new sucrosephenylpropanoid ester from Polygonum pubescens Blume.

Anti-inflammatory and antioxidant activities of chemical constituents from the flower buds of Buddleja officinalis.

Identification of potential diagnostic biomarkers of cerebral infarction using gas chromatography-mass spectrometry and chemometrics