An approximate introduction to how zk-SNARKs are possible (part 1)
You can make a proof for the statement "I know a secret number such that if you take the word ‘cow', add the number to the end, and SHA256 hash it 100 million times, the output starts with 0x57d00485aa". The verifier can verify the proof far more quickly than it would take for them to run 100 million hashes themselves, and the proof would also not reveal what the secret number is.
In the context of blockchains, this has 2 very powerful applications: Perhaps the most powerful cryptographic technology to come out of the last decade is general-purpose succinct zero knowledge proofs, usually called zk-SNARKs ("zero knowledge succinct arguments of knowledge"). A zk-SNARK allows you to generate a proof that some computation has some particular output, in such a way that the proof can be verified extremely quickly even if the underlying computation takes a very long time to run. The "ZK" part adds an additional feature: the proof can keep some of the inputs to the computation hidden.
You can make a proof for the statement "I know a secret number such that if you take the word ‘cow', add the number to the end, and SHA256 hash it 100 million times, the output starts with 0x57d00485aa". The verifier can verify the proof far more quickly than it would take for them to run 100 million hashes themselves, and the proof would also not reveal what the secret number is.
In the context of blockchains, this has two very powerful applications:
- Scalability: if a block takes a long time to verify, one person can verify it and generate a proof, and everyone else can just quickly verify the proof instead
- Privacy: you can prove that you have the right to transfer some asset (you received it, and you didn't already transfer it) without revealing the link to which asset you received. This ensures security without unduly leaking information about who is transacting with whom to the public.
But zk-SNARKs are quite complex; indeed, as recently as in 2014-17 they were still frequently called "moon math". The good news is that since then, the protocols have become simpler and our understanding of them has become much better. This post will try to explain how ZK-SNARKs work, in a way that should be understandable to someone with a medium level of understanding of mathematics.
Why ZK-SNARKs "should" be hard
Let us take the example that we started with: we have a number (we can encode "cow" followed by the secret input as an integer), we take the SHA256 hash of that number, then we do that again another 99,999,999 times, we get the output, and we check what its starting digits are. This is a huge computation.
A "succinct" proof is one where both the size of the proof and the time required to verify it grow much more slowly than the computation to be verified. If we want a "succinct" proof, we cannot require the verifier to do some work per round of hashing (because then the verification time would be proportional to the computation). Instead, the verifier must somehow check the whole computation without peeking into each individual piece of the computation.
One natural technique is random sampling: how about we just have the verifier peek into the computation in 500 different places, check that those parts are correct, and if all 500 checks pass then assume that the rest of the computation must with high probability be fine, too?
Such a procedure could even be turned into a non-interactive proof using the Fiat-Shamir heuristic: the prover computes a Merkle root of the computation, uses the Merkle root to pseudorandomly choose 500 indices, and provides the 500 corresponding Merkle branches of the data. The key idea is that the prover does not know which branches they will need to reveal until they have already "committed to" the data. If a malicious prover tries to fudge the data after learning which indices are going to be checked, that would change the Merkle root, which would result in a new set of random indices, which would require fudging the data again... trapping the malicious prover in an endless cycle.
But unfortunately there is a fatal flaw in naively applying random sampling to spot-check a computation in this way: computation is inherently fragile. If a malicious prover flips one bit somewhere in the middle of a computation, they can make it give a completely different result, and a random sampling verifier would almost never find out.
It only takes one deliberately inserted error, that a random check would almost never catch, to make a computation give a completely incorrect result.
If tasked with the problem of coming up with a zk-SNARK protocol, many people would make their way to this point and then get stuck and give up. How can a verifier possibly check every single piece of the computation, without looking at each piece of the computation individually? There is a clever solution.
see part 2
(Edited)
More on Web3 & Crypto
CyberPunkMetalHead
3 years ago
It's all about the ego with Terra 2.0.
UST depegs and LUNA crashes 99.999% in a fraction of the time it takes the Moon to orbit the Earth.
Fat Man, a Terra whistle-blower, promises to expose Do Kwon's dirty secrets and shady deals.
The Terra community has voted to relaunch Terra LUNA on a new blockchain. The Terra 2.0 Pheonix-1 blockchain went live on May 28, 2022, and people were airdropped the new LUNA, now called LUNA, while the old LUNA became LUNA Classic.
Does LUNA deserve another chance? To answer this, or at least start a conversation about the Terra 2.0 chain's advantages and limitations, we must assess its fundamentals, ideology, and long-term vision.
Whatever the result, our analysis must be thorough and ruthless. A failure of this magnitude cannot happen again, so we must magnify every potential breaking point by 10.
Will UST and LUNA holders be compensated in full?
The obvious. First, and arguably most important, is to restore previous UST and LUNA holders' bags.
Terra 2.0 has 1,000,000,000,000 tokens to distribute.
25% of a community pool
Holders of pre-attack LUNA: 35%
10% of aUST holders prior to attack
Holders of LUNA after an attack: 10%
UST holders as of the attack: 20%
Every LUNA and UST holder has been compensated according to the above proposal.
According to self-reported data, the new chain has 210.000.000 tokens and a $1.3bn marketcap. LUNC and UST alone lost $40bn. The new token must fill this gap. Since launch:
LUNA holders collectively own $1b worth of LUNA if we subtract the 25% community pool airdrop from the current market cap and assume airdropped LUNA was never sold.
At the current supply, the chain must grow 40 times to compensate holders. At the current supply, LUNA must reach $240.
LUNA needs a full-on Bull Market to make LUNC and UST holders whole.
Who knows if you'll be whole? From the time you bought to the amount and price, there are too many variables to determine if Terra can cover individual losses.
The above distribution doesn't consider individual cases. Terra didn't solve individual cases. It would have been huge.
What does LUNA offer in terms of value?
UST's marketcap peaked at $18bn, while LUNC's was $41bn. LUNC and UST drove the Terra chain's value.
After it was confirmed (again) that algorithmic stablecoins are bad, Terra 2.0 will no longer support them.
Algorithmic stablecoins contributed greatly to Terra's growth and value proposition. Terra 2.0 has no product without algorithmic stablecoins.
Terra 2.0 has an identity crisis because it has no actual product. It's like Volkswagen faking carbon emission results and then stopping car production.
A project that has already lost the trust of its users and nearly all of its value cannot survive without a clear and in-demand use case.
Do Kwon, how about him?
Oh, the Twitter-caller-poor? Who challenges crypto billionaires to break his LUNA chain? Who dissolved Terra Labs South Korea before depeg? Arrogant guy?
That's not a good image for LUNA, especially when making amends. I think he should step down and let a nicer person be Terra 2.0's frontman.
The verdict
Terra has a terrific community with an arrogant, unlikeable leader. The new LUNA chain must grow 40 times before it can start making up its losses, and even then, not everyone's losses will be covered.
I won't invest in Terra 2.0 or other algorithmic stablecoins in the near future. I won't be near any Do Kwon-related project within 100 miles. My opinion.
Can Terra 2.0 be saved? Comment below.
Vivek Singh
3 years ago
A Warm Welcome to Web3 and the Future of the Internet
Let's take a look back at the internet's history and see where we're going — and why.
Tim Berners Lee had a problem. He was at CERN, the world's largest particle physics factory, at the time. The institute's stated goal was to study the simplest particles with the most sophisticated scientific instruments. The institute completed the LEP Tunnel in 1988, a 27 kilometer ring. This was Europe's largest civil engineering project (to study smaller particles — electrons).
The problem Tim Berners Lee found was information loss, not particle physics. CERN employed a thousand people in 1989. Due to team size and complexity, people often struggled to recall past project information. While these obstacles could be overcome, high turnover was nearly impossible. Berners Lee addressed the issue in a proposal titled ‘Information Management'.
When a typical stay is two years, data is constantly lost. The introduction of new people takes a lot of time from them and others before they understand what is going on. An emergency situation may require a detective investigation to recover technical details of past projects. Often, the data is recorded but cannot be found. — Information Management: A Proposal
He had an idea. Create an information management system that allowed users to access data in a decentralized manner using a new technology called ‘hypertext'.
To quote Berners Lee, his proposal was “vague but exciting...”. The paper eventually evolved into the internet we know today. Here are three popular W3C standards used by billions of people today:
(credit: CERN)
HTML (Hypertext Markup)
A web formatting language.
URI (Unique Resource Identifier)
Each web resource has its own “address”. Known as ‘a URL'.
HTTP (Hypertext Transfer Protocol)
Retrieves linked resources from across the web.
These technologies underpin all computer work. They were the seeds of our quest to reorganize information, a task as fruitful as particle physics.
Tim Berners-Lee would probably think the three decades from 1989 to 2018 were eventful. He'd be amazed by the billions, the inspiring, the novel. Unlocking innovation at CERN through ‘Information Management'.
The fictional character would probably need a drink, walk, and a few deep breaths to fully grasp the internet's impact. He'd be surprised to see a few big names in the mix.
Then he'd say, "Something's wrong here."
We should review the web's history before going there. Was it a success after Berners Lee made it public? Web1 and Web2: What is it about what we are doing now that so many believe we need a new one, web3?
Per Outlier Ventures' Jamie Burke:
Web 1.0 was read-only.
Web 2.0 was the writable
Web 3.0 is a direct-write web.
Let's explore.
Web1: The Read-Only Web
Web1 was the digital age. We put our books, research, and lives ‘online'. The web made information retrieval easier than any filing cabinet ever. Massive amounts of data were stored online. Encyclopedias, medical records, and entire libraries were put away into floppy disks and hard drives.
In 2015, the web had around 305,500,000,000 pages of content (280 million copies of Atlas Shrugged).
Initially, one didn't expect to contribute much to this database. Web1 was an online version of the real world, but not yet a new way of using the invention.
One gets the impression that the web has been underutilized by historians if all we can say about it is that it has become a giant global fax machine. — Daniel Cohen, The Web's Second Decade (2004)
That doesn't mean developers weren't building. The web was being advanced by great minds. Web2 was born as technology advanced.
Web2: Read-Write Web
Remember when you clicked something on a website and the whole page refreshed? Is it too early to call the mid-2000s ‘the good old days'?
Browsers improved gradually, then suddenly. AJAX calls augmented CGI scripts, and applications began sending data back and forth without disrupting the entire web page. One button to ‘digg' a post (see below). Web experiences blossomed.
In 2006, Digg was the most active ‘Web 2.0' site. (Photo: Ethereum Foundation Taylor Gerring)
Interaction was the focus of new applications. Posting, upvoting, hearting, pinning, tweeting, liking, commenting, and clapping became a lexicon of their own. It exploded in 2004. Easy ways to ‘write' on the internet grew, and continue to grow.
Facebook became a Web2 icon, where users created trillions of rows of data. Google and Amazon moved from Web1 to Web2 by better understanding users and building products and services that met their needs.
Business models based on Software-as-a-Service and then managing consumer data within them for a fee have exploded.
Web2 Emerging Issues
Unbelievably, an intriguing dilemma arose. When creating this read-write web, a non-trivial question skirted underneath the covers. Who owns it all?
You have no control over [Web 2] online SaaS. People didn't realize this because SaaS was so new. People have realized this is the real issue in recent years.
Even if these organizations have good intentions, their incentive is not on the users' side.
“You are not their customer, therefore you are their product,” they say. With Laura Shin, Vitalik Buterin, Unchained
A good plot line emerges. Many amazing, world-changing software products quietly lost users' data control.
For example: Facebook owns much of your social graph data. Even if you hate Facebook, you can't leave without giving up that data. There is no ‘export' or ‘exit'. The platform owns ownership.
While many companies can pull data on you, you cannot do so.
On the surface, this isn't an issue. These companies use my data better than I do! A complex group of stakeholders, each with their own goals. One is maximizing shareholder value for public companies. Tim Berners-Lee (and others) dislike the incentives created.
“Show me the incentive and I will show you the outcome.” — Berkshire Hathaway's CEO
It's easy to see what the read-write web has allowed in retrospect. We've been given the keys to create content instead of just consume it. On Facebook and Twitter, anyone with a laptop and internet can participate. But the engagement isn't ours. Platforms own themselves.
Web3: The ‘Unmediated’ Read-Write Web
Tim Berners Lee proposed a decade ago that ‘linked data' could solve the internet's data problem.
However, until recently, the same principles that allowed the Web of documents to thrive were not applied to data...
The Web of Data also allows for new domain-specific applications. Unlike Web 2.0 mashups, Linked Data applications work with an unbound global data space. As new data sources appear on the Web, they can provide more complete answers.
At around the same time as linked data research began, Satoshi Nakamoto created Bitcoin. After ten years, it appears that Berners Lee's ideas ‘link' spiritually with cryptocurrencies.
What should Web 3 do?
Here are some quick predictions for the web's future.
Users' data:
Users own information and provide it to corporations, businesses, or services that will benefit them.
Defying censorship:
No government, company, or institution should control your access to information (1, 2, 3)
Connect users and platforms:
Create symbiotic rather than competitive relationships between users and platform creators.
Open networks:
“First, the cryptonetwork-participant contract is enforced in open source code. Their voices and exits are used to keep them in check.” Dixon, Chris (4)
Global interactivity:
Transacting value, information, or assets with anyone with internet access, anywhere, at low cost
Self-determination:
Giving you the ability to own, see, and understand your entire digital identity.
Not pull, push:
‘Push' your data to trusted sources instead of ‘pulling' it from others.
Where Does This Leave Us?
Change incentives, change the world. Nick Babalola
People believe web3 can help build a better, fairer system. This is not the same as equal pay or outcomes, but more equal opportunity.
It should be noted that some of these advantages have been discussed previously. Will the changes work? Will they make a difference? These unanswered questions are technical, economic, political, and philosophical. Unintended consequences are likely.
We hope Web3 is a more democratic web. And we think incentives help the user. If there’s one thing that’s on our side, it’s that open has always beaten closed, given a long enough timescale.
We are at the start.
Elnaz Sarraf
3 years ago
Why Bitcoin's Crash Could Be Good for Investors
The crypto market crashed in June 2022. Bitcoin and other cryptocurrencies hit their lowest prices in over a year, causing market panic. Some believe this crash will benefit future investors.
Before I discuss how this crash might help investors, let's examine why it happened. Inflation in the U.S. reached a 30-year high in 2022 after Russia invaded Ukraine. In response, the U.S. Federal Reserve raised interest rates by 0.5%, the most in almost 20 years. This hurts cryptocurrencies like Bitcoin. Higher interest rates make people less likely to invest in volatile assets like crypto, so many investors sold quickly.
The crypto market collapsed. Bitcoin, Ethereum, and Binance dropped 40%. Other cryptos crashed so hard they were delisted from almost every exchange. Bitcoin peaked in April 2022 at $41,000, but after the May interest rate hike, it crashed to $28,000. Bitcoin investors were worried. Even in bad times, this crash is unprecedented.
Bitcoin wasn't "doomed." Before the crash, LUNA was one of the top 5 cryptos by market cap. LUNA was trading around $80 at the start of May 2022, but after the rate hike?
Less than 1 cent. LUNA lost 99.99% of its value in days and was removed from every crypto exchange. Bitcoin's "crash" isn't as devastating when compared to LUNA.
Many people said Bitcoin is "due" for a LUNA-like crash and that the only reason it hasn't crashed is because it's bigger. Still false. If so, Bitcoin should be worth zero by now. We didn't. Instead, Bitcoin reached 28,000, then 29k, 30k, and 31k before falling to 18k. That's not the world's greatest recovery, but it shows Bitcoin's safety.
Bitcoin isn't falling constantly. It fell because of the initial shock of interest rates, but not further. Now, Bitcoin's value is more likely to rise than fall. Bitcoin's low price also attracts investors. They know what prices Bitcoin can reach with enough hype, and they want to capitalize on low prices before it's too late.
Bitcoin's crash was bad, but in a way it wasn't. To understand, consider 2021. In March 2021, Bitcoin surpassed $60k for the first time. Elon Musk's announcement in May that he would no longer support Bitcoin caused a massive crash in the crypto market. In May 2017, Bitcoin's price hit $29,000. Elon Musk's statement isn't worth more than the Fed raising rates. Many expected this big announcement to kill Bitcoin.
Not so. Bitcoin crashed from $58k to $31k in 2021. Bitcoin fell from $41k to $28k in 2022. This crash is smaller. Bitcoin's price held up despite tensions and stress, proving investors still believe in it. What happened after the initial crash in the past?
Bitcoin fell until mid-July. This is also something we’re not seeing today. After a week, Bitcoin began to improve daily. Bitcoin's price rose after mid-July. Bitcoin's price fluctuated throughout the rest of 2021, but it topped $67k in November. Despite no major changes, the peak occurred after the crash. Elon Musk seemed uninterested in crypto and wasn't likely to change his mind soon. What triggered this peak? Nothing, really. What really happened is that people got over the initial statement. They forgot.
Internet users have goldfish-like attention spans. People quickly forgot the crash's cause and were back investing in crypto months later. Despite the market's setbacks, more crypto investors emerged by the end of 2017. Who gained from these peaks? Bitcoin investors who bought low. Bitcoin not only recovered but also doubled its ROI. It was like a movie, and it shows us what to expect from Bitcoin in the coming months.
The current Bitcoin crash isn't as bad as the last one. LUNA is causing market panic. LUNA and Bitcoin are different cryptocurrencies. LUNA crashed because Terra wasn’t able to keep its peg with the USD. Bitcoin is unanchored. It's one of the most decentralized investments available. LUNA's distrust affected crypto prices, including Bitcoin, but it won't last forever.
This is why Bitcoin will likely rebound in the coming months. In 2022, people will get over the rise in interest rates and the crash of LUNA, just as they did with Elon Musk's crypto stance in 2021. When the world moves on to the next big controversy, Bitcoin's price will soar.
Bitcoin may recover for another reason. Like controversy, interest rates fluctuate. The Russian invasion caused this inflation. World markets will stabilize, prices will fall, and interest rates will drop.
Next, lower interest rates could boost Bitcoin's price. Eventually, it will happen. The U.S. economy can't sustain such high interest rates. Investors will put every last dollar into Bitcoin if interest rates fall again.
Bitcoin has proven to be a stable investment. This boosts its investment reputation. Even if Ethereum dethrones Bitcoin as crypto king one day (or any other crypto, for that matter). Bitcoin may stay on top of the crypto ladder for a while. We'll have to wait a few months to see if any of this is true.
This post is a summary. Read the full article here.
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Maria Stepanova
3 years ago
How Elon Musk Picks Things Up Quicker Than Anyone Else
Adopt Elon Musk's learning strategy to succeed.
Medium writers rank first and second when you Google “Elon Musk's learning approach”.
My article idea seems unoriginal. Lol
Musk is brilliant.
No doubt here.
His name connotes success and intelligence.
He knows rocket science, engineering, AI, and solar power.
Musk is a Unicorn, but his skills aren't special.
How does he manage it?
Elon Musk has two learning rules that anyone may use.
You can apply these rules and become anyone you want.
You can become a rocket scientist or a surgeon. If you want, of course.
The learning process is key.
Make sure you are creating a Tree of Knowledge according to Rule #1.
Musk told Reddit how he learns:
“It is important to view knowledge as sort of a semantic tree — make sure you understand the fundamental principles, i.e. the trunk and big branches, before you get into the leaves/details or there is nothing for them to hang onto.”
Musk understands the essential ideas and mental models of each of his business sectors.
He starts with the tree's trunk, making sure he learns the basics before going on to branches and leaves.
We often act otherwise. We memorize small details without understanding how they relate to the whole. Our minds are stuffed with useless data.
Cramming isn't learning.
Start with the basics to learn faster. Before diving into minutiae, grasp the big picture.
Rule #2: You can't connect what you can't remember.
Elon Musk transformed industries this way. As his expertise grew, he connected branches and leaves from different trees.
Musk read two books a day as a child. He didn't specialize like most people. He gained from his multidisciplinary education. It helped him stand out and develop billion-dollar firms.
He gained skills in several domains and began connecting them. World-class performances resulted.
Most of us never learn the basics and only collect knowledge. We never really comprehend information, thus it's hard to apply it.
Learn the basics initially to maximize your chances of success. Then start learning.
Learn across fields and connect them.
This method enabled Elon Musk to enter and revolutionize a century-old industry.
Matthew Royse
3 years ago
5 Tips for Concise Writing
Here's how to be clear.
“I have only made this letter longer because I have not had the time to make it shorter.” — French mathematician, physicist, inventor, philosopher, and writer Blaise Pascal
Concise.
People want this. We tend to repeat ourselves and use unnecessary words.
Being vague frustrates readers. It focuses their limited attention span on figuring out what you're saying rather than your message.
Edit carefully.
“Examine every word you put on paper. You’ll find a surprising number that don’t serve any purpose.” — American writer, editor, literary critic, and teacher William Zinsser
How do you write succinctly?
Here are three ways to polish your writing.
1. Delete
Your readers will appreciate it if you delete unnecessary words. If a word or phrase is essential, keep it. Don't force it.
Many readers dislike bloated sentences. Ask yourself if cutting a word or phrase will change the meaning or dilute your message.
For example, you could say, “It’s absolutely essential that I attend this meeting today, so I know the final outcome.” It’s better to say, “It’s critical I attend the meeting today, so I know the results.”
Key takeaway
Delete actually, completely, just, full, kind of, really, and totally. Keep the necessary words, cut the rest.
2. Just Do It
Don't tell readers your plans. Your readers don't need to know your plans. Who are you?
Don't say, "I want to highlight our marketing's problems." Our marketing issues are A, B, and C. This cuts 5–7 words per sentence.
Keep your reader's attention on the essentials, not the fluff. What are you doing? You won't lose readers because you get to the point quickly and don't build up.
Key takeaway
Delete words that don't add to your message. Do something, don't tell readers you will.
3. Cut Overlap
You probably repeat yourself unintentionally. You may add redundant sentences when brainstorming. Read aloud to detect overlap.
Remove repetition from your writing. It's important to edit our writing and thinking to avoid repetition.
Key Takeaway
If you're repeating yourself, combine sentences to avoid overlap.
4. Simplify
Write as you would to family or friends. Communicate clearly. Don't use jargon. These words confuse readers.
Readers want specifics, not jargon. Write simply. Done.
Most adults read at 8th-grade level. Jargon and buzzwords make speech fluffy. This confuses readers who want simple language.
Key takeaway
Ensure all audiences can understand you. USA Today's 5th-grade reading level is intentional. They want everyone to understand.
5. Active voice
Subjects perform actions in active voice. When you write in passive voice, the subject receives the action.
For example, “the board of directors decided to vote on the topic” is an active voice, while “a decision to vote on the topic was made by the board of directors” is a passive voice.
Key takeaway
Active voice clarifies sentences. Active voice is simple and concise.
Bringing It All Together
Five tips help you write clearly. Delete, just do it, cut overlap, use simple language, and write in an active voice.
Clear writing is effective. It's okay to occasionally use unnecessary words or phrases. Realizing it is key. Check your writing.
Adding words costs.
Write more concisely. People will appreciate it and read your future articles, emails, and messages. Spending extra time will increase trust and influence.
“Not that the story need be long, but it will take a long while to make it short.” — Naturalist, essayist, poet, and philosopher Henry David Thoreau
Michael Hunter, MD
3 years ago
5 Drugs That May Increase Your Risk of Dementia
While our genes can't be changed easily, you can avoid some dementia risk factors. Today we discuss dementia and five drugs that may increase risk.
Memory loss appears to come with age, but we're not talking about forgetfulness. Sometimes losing your car keys isn't an indication of dementia. Dementia impairs the capacity to think, remember, or make judgments. Dementia hinders daily tasks.
Alzheimers is the most common dementia. Dementia is not normal aging, unlike forgetfulness. Aging increases the risk of Alzheimer's and other dementias. A family history of the illness increases your risk, according to the Mayo Clinic (USA).
Given that our genes are difficult to change (I won't get into epigenetics), what are some avoidable dementia risk factors? Certain drugs may cause cognitive deterioration.
Today we look at four drugs that may cause cognitive decline.
Dementia and benzodiazepines
Benzodiazepine sedatives increase brain GABA levels. Example benzodiazepines:
Diazepam (Valium) (Valium)
Alprazolam (Xanax) (Xanax)
Clonazepam (Klonopin) (Klonopin)
Addiction and overdose are benzodiazepine risks. Yes! These medications don't raise dementia risk.
USC study: Benzodiazepines don't increase dementia risk in older adults.
Benzodiazepines can produce short- and long-term amnesia. This memory loss hinders memory formation. Extreme cases can permanently impair learning and memory. Anterograde amnesia is uncommon.
2. Statins and dementia
Statins reduce cholesterol. They prevent a cholesterol-making chemical. Examples:
Atorvastatin (Lipitor) (Lipitor)
Fluvastatin (Lescol XL) (Lescol XL)
Lovastatin (Altoprev) (Altoprev)
Pitavastatin (Livalo, Zypitamag) (Livalo, Zypitamag)
Pravastatin (Pravachol) (Pravachol)
Rosuvastatin (Crestor, Ezallor) (Crestor, Ezallor)
Simvastatin (Zocor) (Zocor)
This finding is contentious. Harvard's Brigham and Womens Hospital's Dr. Joann Manson says:
“I think that the relationship between statins and cognitive function remains controversial. There’s still not a clear conclusion whether they help to prevent dementia or Alzheimer’s disease, have neutral effects, or increase risk.”
This one's off the dementia list.
3. Dementia and anticholinergic drugs
Anticholinergic drugs treat many conditions, including urine incontinence. Drugs inhibit acetylcholine (a brain chemical that helps send messages between cells). Acetylcholine blockers cause drowsiness, disorientation, and memory loss.
First-generation antihistamines, tricyclic antidepressants, and overactive bladder antimuscarinics are common anticholinergics among the elderly.
Anticholinergic drugs may cause dementia. One study found that taking anticholinergics for three years or more increased the risk of dementia by 1.54 times compared to three months or less. After stopping the medicine, the danger may continue.
4. Drugs for Parkinson's disease and dementia
Cleveland Clinic (USA) on Parkinson's:
Parkinson's disease causes age-related brain degeneration. It causes delayed movements, tremors, and balance issues. Some are inherited, but most are unknown. There are various treatment options, but no cure.
Parkinson's medications can cause memory loss, confusion, delusions, and obsessive behaviors. The drug's effects on dopamine cause these issues.
A 2019 JAMA Internal Medicine study found powerful anticholinergic medications enhance dementia risk.
Those who took anticholinergics had a 1.5 times higher chance of dementia. Individuals taking antidepressants, antipsychotic drugs, anti-Parkinson’s drugs, overactive bladder drugs, and anti-epileptic drugs had the greatest risk of dementia.
Anticholinergic medicines can lessen Parkinson's-related tremors, but they slow cognitive ability. Anticholinergics can cause disorientation and hallucinations in those over 70.
5. Antiepileptic drugs and dementia
The risk of dementia from anti-seizure drugs varies with drugs. Levetiracetam (Keppra) improves Alzheimer's cognition.
One study linked different anti-seizure medications to dementia. Anti-epileptic medicines increased the risk of Alzheimer's disease by 1.15 times in the Finnish sample and 1.3 times in the German population. Depakote, Topamax are drugs.