Suppr超能文献

植物化合物通过神经内分泌调节饥饿治疗肥胖:系统评价。

Plant compounds for obesity treatment through neuroendocrine regulation of hunger: A systematic review.

机构信息

Institute of Research, Development and Innovation in Health Biotechnology of Elche (IDiBE), Universitas Miguel Hernández (UMH), 03202, Elche, Spain.

Institute of Bioengineering, Applied Biology Department-Nutrition, University Miguel-Hernández, 03202, Elche, Spain; Instituto de Investigación Sanitaria y Biomédica de Alicante (ISABIAL), 03010, Alicante, Spain; CIBER Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029, Madrid, Spain.

出版信息

Phytomedicine. 2023 May;113:154735. doi: 10.1016/j.phymed.2023.154735. Epub 2023 Feb 26.

Abstract

BACKGROUND

Food intake behavior is influenced by both physiological and psychological complex processes, such as appetite, satiety, and hunger. The neuroendocrine regulation of food intake integrates short- and long-term acting signals that modulate the moment of intake and energy storage/expenditure, respectively. These signals are classified as orexigenic, those that activate anabolic pathways and the desire of eating, and anorexigenic, those that activate the catabolic pathways and a sensation of satiety. Appetite control by natural vegetal compounds is an intense area of research and new pharmacological interventions have been emerging based on an understanding of appetite regulation pathways. Several validated psychometric tools are used to assess the efficacy of these plant ingredients. However, these data are not conclusive if they are not complemented with physiological parameters, such as anthropometric evaluations (body weight and composition) and the analysis of hormones related to adipose tissue and appetite in blood.

PURPOSE

The purpose of this manuscript is the critical analysis of the plant compounds studied to date in the literature with potential for the neuroendocrine regulation of hunger in order to determine if the use of phytochemicals for the treatment of obesity constitutes an effective and/or promising therapeutic tool.

METHODS

Relevant information on neuroendocrine regulation of hunger and satiety for the treatment of obesity by plant compounds up to 2022 in English and/or Spanish were derived from online databases using the PubMed search engine and Google Scholar with relevant keywords and operators.

RESULTS

Accordingly, the comparison performed in this review between previous studies showed a high degree of experimental heterogeneity. Among the studies reviewed here, only a few of them establish comprehensively a potential correlation between the effect of the ingredient on hunger or satiety, body changes and a physiological response.

CONCLUSIONS

More systematic clinical studies are required in future research. The first approach should be to decode the pattern of circulating hormones regulating hunger, satiety, and appetite in overweight/obese subjects. Thereafter, studies should correlate brain connectivity at the level of the hypothalamus, gut and adipose tissue with the hormone patterns modulating appetite and satiety. Extracts whose mode of action have been well characterized and that are safe, can be used clinically to perform a moderate, but continuous, caloric restriction in overweight patients to lose weight excess into a controlled protocol.

摘要

背景

食物摄入行为受生理和心理复杂过程的影响,如食欲、饱腹感和饥饿感。食物摄入的神经内分泌调节整合了短期和长期作用的信号,分别调节摄入时刻和能量储存/消耗。这些信号分为食欲刺激物,即激活合成代谢途径和进食欲望的信号,以及食欲抑制剂,即激活分解代谢途径和饱腹感的信号。天然植物化合物对食欲的控制是一个研究热点,新的药理学干预措施已经基于对食欲调节途径的理解而出现。有几种经过验证的心理计量工具用于评估这些植物成分的功效。然而,如果这些数据不辅以生理参数,如人体测量评估(体重和成分)以及分析与脂肪组织和血液中食欲相关的激素,那么这些数据就没有结论性。

目的

本文旨在对迄今为止文献中研究的具有神经内分泌调节饥饿潜力的植物化合物进行批判性分析,以确定植物化学物质治疗肥胖是否构成有效和/或有前途的治疗工具。

方法

使用 PubMed 搜索引擎和 Google Scholar 在线数据库,使用相关关键词和运算符,检索截至 2022 年有关植物化合物对饥饿和饱腹感的神经内分泌调节以治疗肥胖的相关信息。

结果

因此,本文对之前研究进行了比较,结果显示实验的异质性很高。在本文综述的研究中,只有少数研究全面地建立了成分对饥饿或饱腹感、身体变化和生理反应的潜在相关性。

结论

未来研究需要进行更系统的临床研究。首先,应该解码调节饥饿、饱腹感和食欲的循环激素模式超重/肥胖受试者。此后,应将下丘脑、肠道和脂肪组织水平的大脑连接与调节食欲和饱腹感的激素模式相关联。作用模式已经得到很好描述且安全的提取物可以在临床上用于超重患者进行适度但持续的热量限制,以在受控方案中减轻多余体重。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验