Heart failure is common in adult population,accounting for substantial morbidity and mortality worldwide.The main risk factors for heart failure are coronary artery disease,hypertension,obesity,diabetes mellitus,chron...Heart failure is common in adult population,accounting for substantial morbidity and mortality worldwide.The main risk factors for heart failure are coronary artery disease,hypertension,obesity,diabetes mellitus,chronic pulmonary diseases,family history of cardiovascular diseases,cardiotoxic therapy.The main factor associated with poor outcome of these patients is constant progression of heart failure.In the current review we present evidence on the role of established and candidate neurohumoral biomarkers for heart failure progression management and diagnostics.A growing number of biomarkers have been proposed as potentially useful in heart failure patients,but not one of them still resembles the characteristics of the"ideal biomarker."A single marker will hardly perform well for screening,diagnostic,prognostic,and therapeutic management purposes.Moreover,the pathophysiological and clinical significance of biomarkers may depend on the presentation,stage,and severity of the disease.The authors cover main classification of heart failure phenotypes,based on the measurement of left ventricular ejection fraction,including heart failure with preserved ejection fraction,heart failure with reduced ejection fraction,and the recently proposed category heart failure with mid-range ejection fraction.One could envisage specific sets of biomarker with different performances in heart failure progression with different left ventricular ejection fraction especially as concerns prediction of the future course of the disease and of left ventricular adverse/reverse remodeling.This article is intended to provide an overview of basic and additional mechanisms of heart failure progression will contribute to a more comprehensive knowledge of the disease pathogenesis.展开更多
Objective To identify the quality markers of Moutan Cortex（MC） and establish the quality evaluation methods for multi-component assay and fingerprinting of MC. Methods The chemical constituents in MC were identified...Objective To identify the quality markers of Moutan Cortex（MC） and establish the quality evaluation methods for multi-component assay and fingerprinting of MC. Methods The chemical constituents in MC were identified by HPLC-QTOF-MS. UPLC was employed for the multi-component assay and fingerprinting of MC. Furthermore, text mining was carried out to review the biosynthesis pathways and pharmacological and pharmacokinetic studies related to MC, and in silico target fishing was conducted to construct compound-target networks for MC. Results Sixteen compounds were clearly identified in MC and their structures were confirmed through comparison with literature data. In addition, the biosynthetic pathways and component specificities of the identified compounds were summarized and confirmed by text mining.Pharmacological activities, including traditional usage and modern pharmacological studies were summarized. A total of 282 targets from Homo sapiens were fished for 13 compounds. In addition, pharmacokinetic studies of different compounds were synopsized. Finally, multi-component assay and fingerprint of MC were established. Conclusion Eight major components are selected as quality markers of MC, such as oxypaeoniflorin, apiopaeonoside, albiflorin, paeonolide, paeoniflorin, 1,2,3,4,6-penta-O-galloyl-β-D-glucose, mudanpioside C and paeonol. These eight quality markers are successfully applied to the quality evaluation of MC, and could be useful in improving the current quality standards of MC.展开更多
We provide a detailed review for the statistical analysis of diagnostic accuracy in a multi-category classification task.For qualitative response variables with more than two categories,many traditional accuracy measu...We provide a detailed review for the statistical analysis of diagnostic accuracy in a multi-category classification task.For qualitative response variables with more than two categories,many traditional accuracy measures such as sensitivity,specificity and area under the ROC curve are no longer applicable.In recent literature,new diagnostic accuracy measures are introduced in medical research studies.In this paper,important statistical concepts for multi-category classification accuracy are reviewed and their utilities are demonstrated with real medical examples.We offer problem-based R code to illustrate how to perform these statistical computations step by step.We expect such analysis tools will become more familiar to practitioners and receive broader applications in biostatistics.Our program can be adapted to many classifiers among which logistic regression may be the most popular approach.We thus base our discussion and illustration completely on the logistic regression in this paper.展开更多
基金supported by the grant from the Ministry of Science and Higher Education of the Russian Federation(agreement 075-15-2020-800)。
文摘Heart failure is common in adult population,accounting for substantial morbidity and mortality worldwide.The main risk factors for heart failure are coronary artery disease,hypertension,obesity,diabetes mellitus,chronic pulmonary diseases,family history of cardiovascular diseases,cardiotoxic therapy.The main factor associated with poor outcome of these patients is constant progression of heart failure.In the current review we present evidence on the role of established and candidate neurohumoral biomarkers for heart failure progression management and diagnostics.A growing number of biomarkers have been proposed as potentially useful in heart failure patients,but not one of them still resembles the characteristics of the"ideal biomarker."A single marker will hardly perform well for screening,diagnostic,prognostic,and therapeutic management purposes.Moreover,the pathophysiological and clinical significance of biomarkers may depend on the presentation,stage,and severity of the disease.The authors cover main classification of heart failure phenotypes,based on the measurement of left ventricular ejection fraction,including heart failure with preserved ejection fraction,heart failure with reduced ejection fraction,and the recently proposed category heart failure with mid-range ejection fraction.One could envisage specific sets of biomarker with different performances in heart failure progression with different left ventricular ejection fraction especially as concerns prediction of the future course of the disease and of left ventricular adverse/reverse remodeling.This article is intended to provide an overview of basic and additional mechanisms of heart failure progression will contribute to a more comprehensive knowledge of the disease pathogenesis.
基金Special Fund for TCM by State Administration of Traditional Chinese Medicine of China(No.201507002-10)CAMS Innovation Fund for Medical Sciences(CIFMS)(No.2016-I2M-1-012)Construction of Liuwei Dihuang Capsule Standard(No.ZYBZH-C-JL-24-03)
文摘Objective To identify the quality markers of Moutan Cortex（MC） and establish the quality evaluation methods for multi-component assay and fingerprinting of MC. Methods The chemical constituents in MC were identified by HPLC-QTOF-MS. UPLC was employed for the multi-component assay and fingerprinting of MC. Furthermore, text mining was carried out to review the biosynthesis pathways and pharmacological and pharmacokinetic studies related to MC, and in silico target fishing was conducted to construct compound-target networks for MC. Results Sixteen compounds were clearly identified in MC and their structures were confirmed through comparison with literature data. In addition, the biosynthetic pathways and component specificities of the identified compounds were summarized and confirmed by text mining.Pharmacological activities, including traditional usage and modern pharmacological studies were summarized. A total of 282 targets from Homo sapiens were fished for 13 compounds. In addition, pharmacokinetic studies of different compounds were synopsized. Finally, multi-component assay and fingerprint of MC were established. Conclusion Eight major components are selected as quality markers of MC, such as oxypaeoniflorin, apiopaeonoside, albiflorin, paeonolide, paeoniflorin, 1,2,3,4,6-penta-O-galloyl-β-D-glucose, mudanpioside C and paeonol. These eight quality markers are successfully applied to the quality evaluation of MC, and could be useful in improving the current quality standards of MC.
基金Li’s work was partially supported by National Medical Research Council in Singapore and AcRF R-155-000-174-114.NNSF[grant number 11371142].
文摘We provide a detailed review for the statistical analysis of diagnostic accuracy in a multi-category classification task.For qualitative response variables with more than two categories,many traditional accuracy measures such as sensitivity,specificity and area under the ROC curve are no longer applicable.In recent literature,new diagnostic accuracy measures are introduced in medical research studies.In this paper,important statistical concepts for multi-category classification accuracy are reviewed and their utilities are demonstrated with real medical examples.We offer problem-based R code to illustrate how to perform these statistical computations step by step.We expect such analysis tools will become more familiar to practitioners and receive broader applications in biostatistics.Our program can be adapted to many classifiers among which logistic regression may be the most popular approach.We thus base our discussion and illustration completely on the logistic regression in this paper.
