After I finish my postgraduate entrance exam on December 22, 2024, I will immediately start working on conquering ALS !
1999年，蔡磊大学毕业，因为考研失利，且父亲刚过世，于是回到老家陪伴母亲，并在基层税务机关任职。2001年(23岁)，在保证本职工作的前提下，他再次参加全国研究生统一考试，以系内前三名的成绩考取中央财经大学财税学院的公费研究生，师从郝如玉教授。研究生期间，他发表多篇学术论文，并以每年多本的速度参编出版专业书籍。2003年，研究生毕业后，加入三星集团中国总部任税务经理。此后，又相继在安利（中国）、万科集团担任税务经理、集团总税务师。
2024/3/28: Unfortunately, I saw this news, so I absolutely cannot stand by and watch them die in front of me !
2024/3/28: 蔡磊你书读得这么好, 考研成绩这么优秀, 职业生涯如此完美, 甚至连 "去死" 都要赶在我们前面, 这让我们无地自容啊 ! 给我们留点面子吧, 你可不能就这么死了 ! AlphaFold正在重塑整个生命科学, 我在 2025/10/1 之前必将消灭渐冻症, 撑住 !
2024/3/28: Race against time, use the tremendous power of AI to accelerate scientific research, save countless terminally ill patients like Cai Lei, and snatch them back from the hands of the god of death ! This is a war with the god of death !
2024/10/19: Cai Lei's team: The new drug has no effect on Cai Lei, and is not suitable for Cai Lei and most ALS patients
Don't begin by reading textbooks. Instead, start by asking ChatGPT about ALS and searching for ALS information on Google to get a general overview of this disease.
How to eliminate ALS ? What do I need to learn ? Recommend some textbooks or courses to help me get started.
Eliminating ALS is a complex, multidisciplinary challenge involving neuroscience, molecular biology, genetics, and therapeutic sciences. Here’s a breakdown of key areas to understand and recommended resources to get started:
- Neuroscience: Understand the nervous system's structure and function, especially motor neuron biology.
- Molecular Biology: Learn about genetic mutations linked to ALS, protein misfolding, and cellular mechanisms.
- Genetics: Study gene editing technologies (like CRISPR) and how specific genetic mutations contribute to ALS.
- Pharmacology and Drug Development: Explore current therapeutic approaches and the process of creating effective drugs.
- Clinical Research Methods: Learn about clinical trials and how to evaluate treatments’ safety and effectiveness.
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Neuroscience
- Textbook: Principles of Neural Science by Eric R. Kandel et al. — A comprehensive introduction to neuroscience.
- Course: Fundamentals of Neuroscience (Harvard University, free on edX).
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Molecular Biology
- Textbook: Molecular Biology of the Cell by Alberts et al. — For understanding cellular mechanisms relevant to ALS.
- Course: Introduction to Molecular Biology (MIT OpenCourseWare).
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Genetics and Gene Therapy
- Textbook: Human Molecular Genetics by Tom Strachan and Andrew Read — Covers genetics and disease mechanisms.
- Course: Genetics and Genomics (Coursera - University of California, Davis).
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Pharmacology and Therapeutics
- Textbook: Goodman & Gilman's: The Pharmacological Basis of Therapeutics — Detailed insights into drug mechanisms and therapeutic strategies.
- Course: Drug Discovery and Development (Coursera - UC San Diego).
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Clinical Research
- Textbook: Designing Clinical Research by Hulley et al. — Helps you understand clinical trials, which is critical for developing treatments.
- Course: Clinical Trials (Coursera - Johns Hopkins University).
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ALS-Specific Resources
- Research Papers: Reading ALS-specific research papers will keep you updated on recent advancements. Journals like Nature Neuroscience and Brain regularly publish ALS research.
- Courses on Rare Neurological Diseases: Check ALS Association webinars or workshops.
Building a strong foundational knowledge in these fields will put you in a great position to understand and contribute to ALS research. If you’re interested, I can help guide your study path further based on any specific area you want to focus on.
AlphaFold and quantum computing could significantly impact ALS research, especially in understanding the molecular mechanisms and accelerating the drug discovery process. Here’s how they can contribute:
- Protein Misfolding and Aggregation: ALS is often associated with misfolded proteins, such as TDP-43 and SOD1, which form toxic aggregates in neurons. AlphaFold, developed by DeepMind, can predict protein structures with high accuracy, allowing researchers to model these ALS-associated proteins precisely. Understanding these proteins' structures provides insight into how they fold and misfold, a critical step in developing therapies to prevent or reverse these processes.
- Target Identification: AlphaFold can help identify binding sites and target regions on problematic proteins. This information is crucial for designing drugs or molecular therapies that can specifically interact with ALS-associated proteins.
- Accelerating Drug Discovery: Protein structure prediction speeds up the identification of potential drug compounds by providing a clear target. Pharmaceutical companies and researchers can use AlphaFold-predicted structures to perform in silico screening, reducing the need for time-intensive experimental methods.
- Quantum Simulations of Molecular Interactions: Quantum computing is particularly promising in simulating molecular interactions at an atomic level, providing insights into how ALS-related proteins interact with each other and with potential drugs. Classical computers struggle with these calculations due to the sheer complexity, but quantum computers, especially those employing qubits, can model these interactions more precisely and quickly.
- Optimization in Drug Discovery: Quantum computing can improve optimization algorithms used in drug discovery by simulating how thousands of drug molecules could interact with ALS-associated targets. This makes it faster to find compounds that can, for instance, prevent protein aggregation or reduce neurotoxicity.
- Genetic Data Analysis: Since genetics play a significant role in ALS, quantum computing could be used to analyze large-scale genomic data to identify genetic mutations linked to ALS. This can help stratify patients based on genetic risk, which is essential for developing personalized treatments.
Together, AlphaFold and quantum computing could form a powerful toolkit for ALS research by accelerating drug discovery, identifying and validating therapeutic targets, and understanding disease mechanisms at a molecular level. Quantum-enhanced simulations combined with accurate protein structure predictions could reduce the typical drug development timeline significantly, potentially bringing effective treatments to ALS patients faster.
If you’re interested in the technical aspects of these approaches, diving into molecular simulation methods and quantum algorithms like the Variational Quantum Eigensolver (VQE) can provide a deeper understanding of how these technologies can be applied to ALS research.