轻松学英语，高中英语单词精讲（1）：senior，务必收藏
senior既是名词也是形容词，作为名词是年长者, 资深者, 毕业班学生，作为形容词是年长的, 高级的, 资深的。既是高中词汇，也是大学英语四级词汇。
这个词实际上是由古印欧语系词根sen-发展而来，sen表示老的，在造词过程中还延伸出高级的意思。当然sen-词根还有其他的单词，例如高龄的，年老的senile，参议院senate，古罗马的元老院senatus等等，总共至少包括10个单词，如下图：
该单词出现在多次六级考试中，例如2008、2010、2012、2017、2018、2019、2021等年份。
作为高级的，我们经常能听到的、用到的有高级管理，高级工程师等等。作为年长的，有年长者，老人等。我在海外工作的时候，不少银行就有专门的老年人服务窗口，或者发放相关卡片senior citizen。
运动会的成人组等等
我们常说的老年痴呆症senile dementia，于1851年首次出现。我们很多了解的老年痴呆症，可能只是阿尔茨海默症AD，实际上，除了AD，还有其他原因，例如中风引起的老年痴呆症。
Alois Alzheimer，1864年6月14日-1915年12月19日，爱罗斯·阿尔茨海默，德国精神科医师及神经病理学家，1906年，他首先发表了“老年痴呆症”的病例，后来并以他的名字命名为阿尔茨海默病（Alzheimer's disease, AD），据国际阿尔茨海默病协会（ADI）发布的《世界阿尔茨海默病2018年报告》显示，目前全世界至少有5000万的痴呆患者，到2050年预计将达到1.52亿，其中约60%-70%为阿尔茨海默病患者。
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来源：香港中文大学
The world’s first AI model using fundus photographs alone to detect Alzheimer’s disease
The world’s first AI model using fundus photographs alone to detect Alzheimer’s disease | CUHK in Focus | The Chinese University of Hong Kong
The retina is an extension of the central nervous system; thus, the eye is therefore a window that can show degenerative changes in the blood vessels and nerves of the brain. An international team led by CUHK’s Faculty of Medicine (CU Medicine) has successfully developed the world’s first AI model that can detect Alzheimer’s disease solely through fundus photographs or images of the retina. The model is more than 80% accurate after validation.
Considering fundus photography is widely accessible, non-invasive and cost-effective, this novel AI model incorporated with fundus photography is expected to become an important tool for screening people at high risk of Alzheimer’s disease in the community. Details have been published in The Lancet Digital Health.
Current methods to detect early Alzheimer’s disease are limited
In Hong Kong, 1 in 10 people aged 70 or above suffers from dementia, with more than half of those cases attributed to Alzheimer’s disease. Alzheimer’s disease is associated with an excessive accumulation of abnormal amyloid plaque and neurofibrillary tangles in the brains, leading to the death of brain cells and resulting in progressive cognitive decline.
Dr Lisa Au Wing-chi of the Division of Neurology says, “Memory complaints are common among middle-aged and elderly people, and often considered a sign of Alzheimer’s disease. It is sometimes difficult to make an accurate diagnosis of Alzheimer’s disease based on cognitive tests and structural brain imaging. However, methods to detect Alzheimer’s pathology, such as an amyloid-PET scan or testing of cerebrospinal fluid collected via lumber puncture, are invasive and less accessible.”
To address the current clinical gap, CU Medicine has led a number of medical centres and institutions from Singapore, the UK and the US to successfully develop an AI model using state-of-the art technologies which can detect Alzheimer’s disease using fundus photographs alone.
The retina is a window to study disorders of the central nervous system
Professor Clement Tham Chee-yung, chairman of the Department of Ophthalmology and Visual Sciences, explains, “The retina is an extension of the brain in terms of embryology, anatomy and physiology. In the entire central nervous system, only the blood vessels and nerves in the retina allow direct visualisation and analysis. Hence, it has long been considered a window to study disorders in the central nervous system. Through non-invasive fundus photography, we can detect a range of changes in the blood vessels and nerves of the retina that are associated with Alzheimer’s disease.”
The team developed and validated their AI model using nearly 13,000 fundus photographs from 648 Alzheimer’s disease patients (included patients from the Prince of Wales Hospital) and 3,240 cognitively normal subjects. Upon validation, the model showed 84% accuracy, 93% sensitivity and 82% specificity in detecting Alzheimer’s disease. In the multi-ethnic, multi-country datasets, the AI model achieved accuracies ranging from 80% to 92%.
Accessibility, non-invasiveness and high cost-effectiveness of the AI model using fundus photography help detection of Alzheimer’s cases both in clinic and the community
Professor Vincent Mok Chung-tong, director of the Therese Pei Fong Chow Research Centre for Prevention of Dementia, says, “In addition to its accessibility and non-invasiveness, the accuracy of the new AI model is comparable to imaging tests such as MRI. It shows potential to become not only a diagnostic test in clinics, but also a screening tool for Alzheimer’s disease in community settings. In the future, we hope to validate its efficacy in identifying high-risk cases of the disease hidden in the community, so that various preventive treatments such as anti-amyloid drugs can be initiated early to slow down cognitive decline and brain damage.”
Dr Carol Cheung Yim-lui of the Department of Ophthalmology and Visual Sciences adds, “In addition to applying novel AI technologies in the model, we also tested it in different scenarios. Notably, our AI model retained a robust ability to differentiate between subjects with and without Alzheimer’s disease, even in the presence of concomitant eye diseases like macular degeneration and glaucoma which are common in city-dwellers and the older population. This further supports the concept that our AI analysis of fundus photographs is an excellent tool for the detection of the memory-depriving Alzheimer’s disease.”
