Today, tomorrow, learn English naturally. 天天自然学英语
Machine learning algorithm identifies 3 natural anti-aging chemicals
Researchers have used a machine learning model to identify three compounds that could combat aging. They say their approach could be an effective way of identifying new drugs, especially for complex diseases.
Cell division is necessary for our body to grow and for tissues to renew themselves. Cellular senescence describes the phenomenon where cells permanently stop dividing but remain in the body, causing tissue damage and aging across body organs and systems.
Ordinarily, senescent cells are cleared from the body by our immune system. But, as we age, our immune system is less effective at clearing out these cells and their number increases. An increase in senescent cells has been associated with diseases such as cancer, Alzheimer’s disease and the hallmarks of aging such as worsening eyesight and reduced mobility. Given the potentially deleterious effects on the body, there has been a push to develop effective senolytics, compounds that clear out senescent cells.
Previous studies have identified some promising senolytics, but they’re often toxic to healthy cells. Now, a study led by researchers from the University of Edinburgh in Scotland has used a pioneering method to seek out chemicals that can safely and effectively eliminate these defective cells.
They developed a machine learning model and trained it to recognize the key features of chemicals with senolytic properties. The model training data came from multiple sources, including academic papers and commercial patents, and was integrated with compounds from two existing chemical libraries that contain a wide range of FDA-approved or clinical-stage compounds.
The full dataset contained 2,523 compounds and included compounds with both senolytic and non-senolytic properties so as not to bias the machine-learning algorithm. The algorithm was then used to screen more than 4,000 chemicals from which 21 potential candidates were identified.
Testing these candidates, the researchers found that three chemicals – ginkgetin, periplocin, and oleandrin – removed senescent cells without harming healthy cells. Of the three, oleandrin was found to be the most effective. All three are natural products found in traditional herbal medicines.
Oleandrin is extracted from the oleander plant (Nerium oleander) and has properties similar to the drug digoxin used to treat heart failure and certain abnormal heart rhythms (arrhythmias). Studies have shown that oleandrin possesses anticancer, anti-inflammatory, anti-HIV, antimicrobial and antioxidant properties. Oleandrin is highly toxic beyond therapeutic levels, which in humans is a very narrow window, hindering its clinical application. As such, it hasn’t been approved by regulatory agencies as a prescription drug or dietary supplement.
Like oleandrin, ginkgetin has been shown to exhibit anticancer, anti-inflammatory, antimicrobial, antioxidant and neuroprotective properties. Ginkgetin is extracted from the Gingko (Ginkgo biloba) tree, the oldest living tree species whose leaves and seeds have been used in Chinese herbal medicine for thousands of years. A highly concentrated Ginkgo biloba extract made from the tree’s dried leaves is available over the counter. It’s one of the best-selling herbal supplements throughout the US and Europe.
Periplocin is isolated from the root bark of the Chinese silk vine (Periploca sepium). Studies have shown that it can improve heart function as well as block cell growth and cause cell death in cancer cells.
The researchers say their findings demonstrate that these compounds have a potency comparable to or higher than senolytics described in previous studies. More importantly, they say, their machine-learning-based method was extremely efficient, reducing the number of compounds that needed to be screened by more than 200-fold.
The researchers say their AI-based approach represents a milestone in identifying new drugs, particularly for complex diseases.
“This study demonstrates that AI can be incredibly effective in helping us identify new drug candidates, particularly at early stages of drug discovery and for diseases with complex biology or few known molecular targets,” said Diego Oyarzún, corresponding author of the study.
They also say the approach is more cost-effective than standard drug screening methods, such as preclinical and clinical trials.
“This work was borne out of intensive collaboration between data scientists, chemists and biologists,” said Vanessa Smer-Barreto, lead author of the study. “Harnessing the strengths of this interdisciplinary mix, we were able to build robust models and save screening costs by using only published data for model training. I hope this work will open new opportunities to accelerate the application of this exciting technology.”
注释：
algorithm: n
表示"算法"，means "a precise rule (or set of rules) specifying how to solve some problem"，如：The compare algorithm is used to do the comparison.比较算法是用来比较属性值的。
senescence: n
表示"衰老；老年期"，means "the organic process of growing older and showing the effects of increasing age; the property characteristic of old age"，如：Senescence is the key problem of cucumber storage. 衰老是黄瓜贮藏中的主要问题。
hallmark: n
表示"标志；特征"，means "a distinctive characteristic or attribute"，如：One hallmark of a good politician is his ability to influence people. 衡量一个优秀政治家的标志之一就是他影响大众的能力。
deleterious: adj
表示"有害的"，means "harmful to living things;"，如：Such weather is deleterious on plants. 这种天气对植物有害。
senolytics: n
表示" 衰老细胞裂解法,衰老细胞靶向清除",用来去除衰老细胞，通常使用达沙替尼、槲皮素和Fisetin。
defective：adj
表示"有缺陷的；"，means "having a defect"，如：He is mentally defective. 他智力不健全。
ginkgetin: n
表示"银杏亭, 银杏黄素"，如：We recorded the changes of the heart rate the blood pressure, and the left ventricle pressure, and observed Ginkgetin effect on reducing the myocardial infarct death rate of AMI - reperfused rabbits. 记录心率、血压、左心室内压、左心室内压微分变化。同时观察银杏黄酮对家兔急性心肌缺血／再灌注治疗后减轻心肌梗死的情况。
periplocin: n
表示"杠柳素,萝蘑苷"，如：Determination of Periplocin in Different Parts of Periploca sepium 杠柳不同部位的杠柳毒苷含量
oleandrin: n
表示"夹竹桃甙"
oleander: n
表示" 夹竹桃"，如：Many people happily recognize oleander. 许多人高兴地承认夹竹桃。
digoxin: n
表示"地高辛（一种强心剂）"，如：There is no evidence that regular digoxin concentration measurements confer better outcomes. 没有任何证据表明，高辛浓度经常性地测量获得更好的结果。
arrhythmia: n
表示"心律失常"，means ""，如：The doctor found that he was born with arrhythmia.医生发现他天生心律不齐。
antimicrobial: adj; n
1. adj表示" 抗菌的；抗微生物的"，means "capable of destroying or inhibiting the growth of disease-causing microorganisms"，如：Antimicrobial coated steel is a new material. 抗菌钢是一种新型抗菌材料。
2. n表示" 抗菌剂；抗菌药"，means "an agent (as heat or radiation or a chemical) that destroys microorganisms that might carry disease"，如：How do you describe Cupron＇s antimicrobial product protection? 能描述一下卡普龙抗菌防护的功效吗？
antioxidant: n
表示" 抗氧化剂"，means "substance that inhibits oxidation or inhibits reactions promoted by oxygen or peroxides"，如：Antioxidant represses the cancer metastasis through scavenging ROS. 抗氧化剂可以通过清除活性氧化物而抑制癌转移的发生。
therapeutic: adj
表示"治疗的"，means "tending to cure or restore to health;"，如：Mourning can have a therapeutic function that we ignore at our peril. 悲痛可以有一种治疗的功能，即让我们忽略我们的风险。
neuroprotective: n
表示"保护神经"，如：It has powerful neurotrophic and neuroprotective activity. 它具有强大的营养和保护神经作用。
gingko: n
表示" 银杏"，means "ginkgo"，如：Gingko also performs a cleansing antioxidant function.银杏还有抗氧化功能。
Biloba: n
表示"银杏果;凹叶厚朴"，如：One of the side effects of ginkgo biloba is an increased risk of bleeding. 白果的副作用之一是增加出血的几率，他没有意识到这一点。
Periploca sepium: n
表示"杠柳；香加皮;山五加皮"，如：Crude extract from Periploca sepium Bunge 杠柳根皮提取物
preclinical：adj
表示"临床前的；临床前期的"，means "of or relating to the early phases of a disease when accurate diagnosis is not possible because symptoms of the disease have not yet appeared"，如：Hydrophobic preclinical passed, still have a thing? 狂犬病潜伏期过了，还有没有事？
Interdisciplinary: adj
表示"跨学科的"，means "drawing from or characterized by participation of two or more fields of study;"，如：Interdisciplinary research on climate change in the Massachusetts Institute of Technology's science and engineering schools.马萨诸塞州科学工程部技术研究所有关气候变化的学科间研究。
中文简要说明：
AI人工智能该怎么应用?如果只是ChatGPT帮写论文那种程度就太简单了，生化学家现在是由AI寻找「不老药」的配方。它们还真的提出3种抗衰老的天然化合物，刚好是3种传统医学的中草药。这是AI的生化应用的第一步，可能是识别新药、新抗生素的有效方法，特别是面对复杂的疾病。
新阿特拉斯(NewAtlas)报导，大家都知道，细胞分裂是我们身体生长和组织自我更新所必需的，但是细胞运作久了以后就会功能衰退，也就是老化的细胞，它们会停止分裂与自我凋亡，以维持整个身体系统的活力。
通常，衰老细胞会被我们的免疫系统清除。但是，随着年龄的增长，我们的免疫系统也会出现效率降低的问题。一般认为大约在27岁左右， 胸腺(免疫细胞的生产基地)功能就开始衰退，人类的衰老似乎也是从那时候开始。
人们一直在尝试开发有效的抗衰老药物，也就是即清除衰老细胞的化合物。然而，生理系统极其复杂，就如前途，为了保持系统的活力，需要消除衰老的细胞，有时被简称为「对抗慢性发炎」。但是我们很难找到一种只针对衰老细胞破坏的「精准子弹」，抗发炎药物不只消除衰老细胞，通常也对健康细胞有毒。
这种「寻百草」的过程极为困难，现在苏格兰爱丁堡大学的研究团队，希望由AI来帮忙寻找有效的抗衰老药。
他们开发了一套仿真系统并持续训练，数据来自多种来源，包括学术论文、商业专利等等已知的研究成果，总共收集了2,523 种化合物，其中包括具有抗衰老和非抗衰老特性的化合物，以免机器学习算法产生偏差。然后使用该算法，筛选其中的 4,000 多种化学品，终于确定了21种潜在候选物。
在对这些候选物进行测试后，研究人员发现3种化学物质：银杏黄酮(Ginkgetin)、环丙沙星(Periplocin)和夹竹桃苷(Oleandrin)似乎最为可能，它们可以在不伤害健康细胞的情况下，除去衰老细胞。在这三者都是传统草药中的天然产牾，又以夹竹桃苷被认为是最有效的。
夹竹桃苷是从夹竹桃植物 ( Nerium oleander ) 中提取的，这是一种全株有毒的植物，所以千万不要自己拔来吃。但是它有明确的药理效果，是治疗心力衰竭、心律失常的药物「地高辛」(Digoxin)的原材料。另外，夹竹桃苷也具有抗癌、抗炎、抗HIV、抗菌和抗氧化的效果。
另外，从银杏中提炼的银杏黄素，也已被证明具有抗癌、抗炎、抗菌、抗氧化和神经保护效果。银杏在华人世界几乎不用多介绍，它是树木界的活化石，首先出现在二纪，是现存最古老的裸子植物。另外，它的叶子和种子被做中国传统草药材已有数千年的历史。事实上，银杏也不只在东亚受欢迎，在美国和欧洲也是最畅销的草药补品之一。
环丙沙星是从北五加皮 ( 学名Periploca sepium, 别名杠柳、香加皮 )的根皮中分离出来的。它也是中国传统医学的草药，研究表明，它可以改善心脏功能，并有抗癌的效果，能够阻止癌细胞分裂而凋亡。
研究人员表示，AI的学习效率非常高，立即就将需要筛选的化合物，数量立即减少了 200 多倍。该研究的通讯作者 Diego Oyarzún 说：「人工智能可以非常有效地帮助我们识别新的候选药物，甚至可以帮我们对付原因复杂的多因型疾病，比如癌症、失智症、老化问题等等。」
留言微信公众号《自然学英语LearnNaturally》，可咨询更多！