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Hu W, Yan G, Ding Q, Cai J, Zhang Z, Zhao Z, Lei H, Zhu YZ. Update of Indoles: Promising molecules for ameliorating metabolic diseases. Biomed Pharmacother 2022; 150:112957. [PMID: 35462330 DOI: 10.1016/j.biopha.2022.112957] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Revised: 03/30/2022] [Accepted: 04/11/2022] [Indexed: 11/15/2022] Open
Abstract
Obesity and metabolic disorders have gradually become public health-threatening problems. The metabolic disorder is a cluster of complex metabolic abnormalities which are featured by dysfunction in glucose and lipid metabolism, and results from the increasing prevalence of visceral obesity. With the core driving factor of insulin resistance, metabolic disorder mainly includes type 2 diabetes mellitus (T2DM), micro and macro-vascular diseases, non-alcoholic fatty liver disease (NAFLD), dyslipidemia, and the dysfunction of gut microbiota. Strategies and therapeutic attention are demanded to decrease the high risk of metabolic diseases, from lifestyle changes to drug treatment, especially herbal medicines. Indole is a parent substance of numerous bioactive compounds, and itself can be produced by tryptophan catabolism to stimulate glucagon-like peptide-1 (GLP-1) secretion and inhibit the development of obesity. In addition, in heterocycles drug discovery, the indole scaffold is primarily found in natural compounds with versatile biological activity and plays a prominent role in drug molecules synthesis. In recent decades, plenty of natural or synthesized indole deriviatives have been investigated and elucidated to exert effects on regulating glucose hemeostasis and lipd metabolism. The aim of this review is to trace and emphasize the compounds containing indole scaffold that possess immense potency on preventing metabolic disorders, particularly T2DM, obesity and NAFLD, along with the underlying molecular mechanisms, therefore facilitate a better comprehension of their druggability and application in metabolic diseases.
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Affiliation(s)
- Wei Hu
- State Key Laboratory of Quality Research in Chinese Medicine, Faculty of Chinese Medicine and School of Pharmacy, Macau University of Science and Technology, Macau, China
| | - Guanyu Yan
- Department of Allergy and Clinical Immunology, National Center for Respiratory Medicine, The First Affiliated Hospital of Guangzhou Medical University, National Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, Guangzhou, China
| | - Qian Ding
- State Key Laboratory of Quality Research in Chinese Medicine, Faculty of Chinese Medicine and School of Pharmacy, Macau University of Science and Technology, Macau, China
| | - Jianghong Cai
- State Key Laboratory of Quality Research in Chinese Medicine, Faculty of Chinese Medicine and School of Pharmacy, Macau University of Science and Technology, Macau, China
| | - Zhongyi Zhang
- State Key Laboratory of Quality Research in Chinese Medicine, Faculty of Chinese Medicine and School of Pharmacy, Macau University of Science and Technology, Macau, China
| | - Ziming Zhao
- State Key Laboratory of Quality Research in Chinese Medicine, Faculty of Chinese Medicine and School of Pharmacy, Macau University of Science and Technology, Macau, China
| | - Heping Lei
- Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China.
| | - Yi Zhun Zhu
- State Key Laboratory of Quality Research in Chinese Medicine, Faculty of Chinese Medicine and School of Pharmacy, Macau University of Science and Technology, Macau, China; Shanghai Key Laboratory of Bioactive Small Molecules, School of Pharmacy, Fudan University, Shanghai, China.
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Hemodynamic Impact of Cardiovascular Antihypertensive Medications in Patients With Sepsis-Related Acute Circulatory Failure. Shock 2021; 54:315-320. [PMID: 32080062 DOI: 10.1097/shk.0000000000001524] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
BACKGROUND Impact of prior cardiovascular antihypertensive medication during the initial phase of septic shock in terms of catecholamine requirements and mortality has been poorly investigated and remains unclear. OBJECTIVES To investigate the association between chronic prescription of cardiovascular antihypertensive medication prior to intensive care unit (ICU) admission, catecholamine requirement, and mortality in patients with septic shock. METHODS We included all consecutive patients diagnosed with septic shock within the first 24 h of ICU admission, defined as a microbiologically proven or clinically suspected infection, associated with acute circulatory failure requiring vasopressors despite adequate fluid filling. Prior cardiovascular antihypertensive medication was defined as the chronic use of betablockers (BB), calcium channel blockers (CCB), angiotensin converting enzyme inhibitor (ACEi)/angiotensin receptor blockers (ARB). ICU mortality was investigated using multivariate competitive risk analysis. RESULTS Among 735 patients admitted for septic shock between 2008 and 2016, 46.9% received prior cardiovascular antihypertensive medication. Prior cardiovascular antihypertensive therapy was not associated with increased norepinephrine requirements during the first 24 h (median = 0.28 μg/kg/min in patients previously treated vs. 0.26 μg/kg/min). Prior cardiovascular antihypertensive medication was not associated with a higher risk of ICU mortality after adjustment (cause-specific hazard = 1.28, 95% confidence interval [0.98-1.66], P = 0.06). Subgroups analyses for BB, CCB, and ACEi/ARB using propensity score analyses retrieved similar results. CONCLUSION In patients admitted with septic shock, prior cardiovascular antihypertensive medication seems to have limited impact on initial hemodynamic failure and catecholamine requirement.
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Min L, Ha JK, Aubert CE, Hofer TP, Sussman JB, Langa KM, Tinetti M, Kim HM, Maciejewski ML, Gillon L, Larkin A, Chan CL, Kerr EA, Bravata D, Cushman WC. A Method to Quantify Mean Hypertension Treatment Daily Dose Intensity Using Health Care System Data. JAMA Netw Open 2021; 4:e2034059. [PMID: 33449097 PMCID: PMC7811181 DOI: 10.1001/jamanetworkopen.2020.34059] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/26/2020] [Accepted: 11/28/2020] [Indexed: 12/27/2022] Open
Abstract
Importance Simple measures of hypertension treatment, such as achievement of blood pressure (BP) targets, ignore the intensity of treatment once the BP target is met. High-intensity treatment involves increased treatment burden and can be associated with potential adverse effects in older adults. A method was previously developed to identify older patients receiving intense hypertension treatment by low BP and number of BP medications using national Veterans Health Administration and Medicare Part D administrative pharmacy data to evaluate which BP medications a patient is likely taking on any given day. Objective To further develop and validate a method to more precisely quantify dose intensity of hypertension treatment using only health system administrative pharmacy fill data. Design, Setting, and Participants Observational, cross-sectional study of 319 randomly selected older veterans in the national Veterans Health Administration health care system who were taking multiple BP-lowering medications and had a total of 3625 ambulatory care visits from July 1, 2011, to June 30, 2013. Measure development and medical record review occurred January 1, 2017, through November 30, 2018, and data analysis was conducted from December 1, 2019, to August 31, 2020. Main Outcomes and Measures For each BP-lowering medication, a moderate hypertension daily dose (HDD) was defined as half the maximum dose above which no further clinical benefit has been demonstrated by that medication in hypertension trials. Patients' total HDD was calculated using pharmacy data (pharmacy HDDs), accounting for substantial delays in refills (>30 days) when a patient's pill supply was stretched (eg, cutting existing pills in half). As an external comparison, the pharmacy HDDs were correlated with doses manually extracted from clinicians' visit notes (clinically noted HDDs). How well the pharmacy HDDs correlated with clinically noted HDDs was calculated (using C statistics). To facilitate interpretation, HDDs were described in association with the number of medications. Results A total of 316 patients (99.1%) were male; the mean (SD) age was 75.6 (7.2) years. Pharmacy HDDs were highly correlated (r = 0.92) with clinically noted HDDs, with a mean (SD) of 2.7 (1.8) for pharmacy HDDs and 2.8 (1.8) for clinically noted HDDs. Pharmacy HDDs correlated with high-intensity, clinically noted HDDs ranging from a C statistic of 92.8% (95% CI, 92.0%-93.7%) for 2 or more clinically noted HDDs to 88.1% (95% CI, 85.5%-90.6%) for 6 or more clinically noted HDDs. Conclusions and Relevance This study suggests that health system pharmacy data may be used to accurately quantify hypertension regimen dose intensity. Together with clinic-measured BP, this tool can be used in future health system-based research or quality improvement efforts to fine-tune, manage, and optimize hypertension treatment in older adults.
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Affiliation(s)
- Lillian Min
- Veterans Affairs Geriatric Research, Education, and Clinical Center, Veterans Affairs Ann Arbor Medical Center, Ann Arbor, Michigan
- Division of Geriatric and Palliative Medicine, Department of Medicine, University of Michigan, Ann Arbor
- Veterans Affairs Center for Clinical Management Research, Health Services Research and Development Center of Innovation, Ann Arbor, Michigan
- Institute of Healthcare Policy and Innovation, University of Michigan, Ann Arbor
| | - Jin-Kyung Ha
- Division of Geriatric and Palliative Medicine, Department of Medicine, University of Michigan, Ann Arbor
| | - Carole E. Aubert
- Veterans Affairs Center for Clinical Management Research, Health Services Research and Development Center of Innovation, Ann Arbor, Michigan
- Institute of Healthcare Policy and Innovation, University of Michigan, Ann Arbor
- Department of General Internal Medicine, Bern University Hospital, University of Bern, Bern, Switzerland
- Institute of Primary Healthcare, University of Bern, Bern, Switzerland
| | - Timothy P. Hofer
- Veterans Affairs Center for Clinical Management Research, Health Services Research and Development Center of Innovation, Ann Arbor, Michigan
- Institute of Healthcare Policy and Innovation, University of Michigan, Ann Arbor
- Division of General Internal Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor
| | - Jeremy B. Sussman
- Veterans Affairs Center for Clinical Management Research, Health Services Research and Development Center of Innovation, Ann Arbor, Michigan
- Institute of Healthcare Policy and Innovation, University of Michigan, Ann Arbor
- Division of General Internal Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor
| | - Kenneth M. Langa
- Veterans Affairs Geriatric Research, Education, and Clinical Center, Veterans Affairs Ann Arbor Medical Center, Ann Arbor, Michigan
- Institute of Healthcare Policy and Innovation, University of Michigan, Ann Arbor
- Division of General Internal Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor
- Institute for Social Research, University of Michigan, Ann Arbor
| | - Mary Tinetti
- Section of Geriatrics, Department of Medicine, Yale School of Medicine, New Haven, Connecticut
| | - Hyungjin Myra Kim
- Consulting for Statistics, Computing & Analytics Research, University of Michigan, Ann Arbor
- Department of Biostatistics, University of Michigan Medical School, Ann Arbor
| | - Matthew L. Maciejewski
- Center of Innovation to Accelerate Discovery and Practice Transformation, Veterans Affairs Healthcare System, Durham, North Carolina
- Department of Population Health Sciences, Duke University, Durham, North Carolina
| | - Leah Gillon
- Veterans Affairs Center for Clinical Management Research, Health Services Research and Development Center of Innovation, Ann Arbor, Michigan
| | - Angela Larkin
- Veterans Affairs Center for Clinical Management Research, Health Services Research and Development Center of Innovation, Ann Arbor, Michigan
| | - Chiao-Li Chan
- Division of Geriatric and Palliative Medicine, Department of Medicine, University of Michigan, Ann Arbor
| | - Eve A. Kerr
- Veterans Affairs Center for Clinical Management Research, Health Services Research and Development Center of Innovation, Ann Arbor, Michigan
- Institute of Healthcare Policy and Innovation, University of Michigan, Ann Arbor
- Division of General Internal Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor
| | - Dawn Bravata
- Veterans Affairs Health Services Research and Development Center for Health Information and Communication, Richard L. Roudebush Veterans Affairs Medical Center, Indianapolis, Indiana
- Department of Medicine, Indiana University School of Medicine, Indianapolis
- Department of Neurology, Indiana University School of Medicine, Indianapolis
- Center for Health Services Research, Regenstrief Institute, Indianapolis, Indiana
| | - William C. Cushman
- Department of Preventive Medicine, University of Tennessee Health Science Center, Memphis
- Medical Service, Memphis Veterans Affairs Medical Center, Memphis, Tennessee
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