> When dried and frozen, Deinococcus radiodurans could survive 140,000 grays, or units of X-and gamma-ray radiation, which is 28,000 times greater than the amount of radiation that could kill a person.
I would love also if they called it Hulk the Bacterium
According to Thomas Seyfried, cancer is indeed one disease, fundamentally a metabolic disease [0]. Seyfried's theory suggests that cancer stems from mitochondrial dysfunction, which disrupts cellular metabolism and leads to abnormal cell growth. He argues that the root cause of cancer is not genetic mutations, as commonly believed, but rather metabolic disturbances that alter how cells process energy. Basically returning the damaged cells to "old pathways" of energy generation, without oxygen: fermentation.
This process, known as the Warburg Effect (named after Otto Warburg who first described it in the 1920s), shows that cancer cells primarily rely on fermentation for energy production even in the presence of oxygen - a phenomenon called "aerobic glycolysis." However, glucose fermentation is only part of the story. Cancer cells also heavily depend on glutamine, an amino acid that serves as another crucial fuel source. Through a process called glutaminolysis, cancer cells convert glutamine into both energy and building blocks for rapid cell division. This dual dependency on glucose and glutamine makes cancer cells metabolically distinct from normal cells.
This metabolic theory challenges the traditional somatic mutation theory, which views cancer as a result of DNA mutations accumulating in cells. Seyfried proposes that targeting the metabolism of cancer cells—primarily through dietary interventions like ketogenic diets or therapies that restrict glucose—could effectively "starve" cancer cells while leaving healthy cells less affected. His approach implies that a general strategy for treating cancer could involve targeting this metabolic vulnerability shared across many cancer types.
Furthermore, this theory suggests that combination approaches targeting both glucose and glutamine metabolism might be particularly effective, as they would address both major fuel sources that cancer cells rely on. This could include strategies such as ketogenic diets (to restrict glucose), glutamine inhibitors, and other metabolic therapies that work together to compromise cancer cell energy production while preserving normal cell function.
One heuristic I like is a kind of reverse Occam's Razor: When no clear solution doesn't emerge even after a huge amount of searching, it's probably because the problem actually is complex, not because it's simple.
For example, maybe cancer does have a single unifying cause that can be fixed very easily. But the millions of hours put into studying it suggests otherwise.
This seems to be generally true about most things. Only very rarely do we get something super simple like goiter being caused by the lack of iodine, or stomach ulcers being caused by H. pylori.
Interesting point, though I think we should also consider that our ability to understand diseases like cancer has historically been limited by the observational and analytical technology available. For example, it was recently suggested that Alzheimer’s might be linked to Candida albicans, a fungus that naturally inhabits our bodies but could play a role in the disease. Just as it took time to discover that iodine deficiency causes goiter or that H. pylori produces ulcers, the complexity of cancer might partly stem from the fact that we don’t yet have the necessary technology to closely observe the cells and underlying mechanisms. It’s not necessarily the inherent complexity of the problem but our technological limitations that delay understanding—and possibly a cure.
The Candida link is interesting but not proven — so in that sense it's equivalent to your cancer guy.
The other discoveries predate a lot of advanced medical technology, though. They were the low-hanging fruit in that sense. The only semi-recent discovery I can think of is that the Epstein-Barr virus causes cancer, though that does not necessarily qualify as "simple". EBV is also implicated in MS. EBV could ultimately be one of those "unifiers" that could explain multiple diseases.
> Seyfried, in my readings, appears all too often to speak of “cancer” as if it were a monolithic single disease. As I’ve pointed out many times before, it’s not. Indeed, only approximately 60-90% of cancers demonstrate the Warburg effect.
> Dr. Seyfried presents mouse studies that are interesting and suggestive that there might be something to this whole ketogenic diet thing, at least in brain tumors, such as this one. However, this is what we in the oncology biz would call pretty preliminary data, worthy of further investigation but not supporting the grandiose claims that Dr. Seyfried makes.
> Irritatingly, during the same talk, Dr. Seyfried refers to having done a “biopsy” on the GBM when the case report clearly says that the patient underwent a partial excision of the temporal pole with incomplete debulking of the tumor, which is a different thing.
> ...
> He also heaps scorn on the hospital for insisting that the patient undergo standard of care therapy, clearly demonstrating that he has no understanding of clinical trial ethics.
> This brings me back to the question of whether cancer is a metabolic disease or a genetic disease, the answer to which I promised early on. The likely answer? It’s both! Indeed, a “chicken or the egg” argument continues about whether it is the metabolic abnormalities that cause the mutations observed in cancer cells or whether it is the mutations that produce the metabolic abnormalities. Most likely, it’s a little of both, the exact proportion of which depending upon the tumor cell, that combine in an unholy synergistic circle to drive cancer cells to be more and more abnormal and aggressive. Moreover, cancer is about far more than just the genomics or the metabolism of cancer cells. It’s also the immune system and the tumor microenvironment (the cells and connective tissue in which tumors arise and grow). As I’ve said time and time and time again, cancer is complicated, real complicated. The relative contributions of genetic mutations, metabolic derangements, immune cell dysfunction, and influences of the microenvironment are likely to vary depending upon the type of tumor and, as a consequence, require different treatments. In the end, as with many hyped cancer cures, the ketogenic diet might be helpful for some tumors and almost certainly won’t be helpful for others. Dr. Seyfried might be on to something, but he’s gone a bit off the deep end in apparently thinking that he’s found out something about cancer that no one else takes seriously—or has even thought of before.
BTW, saying that someone "is a bit of a quack" is an ad hominem fallacy. The article linked talks about the "keto" part of the protocol, it does not discuss the glutamine portion of the treatment. I'm not sure who is right, but I would love to see, someone debunking it with data.
Protocol: https://www.nature.com/articles/s42003-019-0455-x
No it is not. If you want to consider informal logical fallacies, it is closest to "poisoning the well", as I am tarnishing his name in an effort to make you not believe is claims. I am not saying he is wrong because he is a quack, I am saying he is a quack, and here is an article going into why he is wrong.
> but I would love to see, someone debunking it with data
The problem is Seyfried doesn't have data. His science is bad and extrapolating from marginal results. Some parts of these ideas might pan out, but all I've seen indicates he's made this his hobby horse is riding it.
Speaking of fallacies, dismissing an argument because you found a single fallacy within it without addressing the main substance of the argument is known as the fallacy fallacy.
There is a lot chew on in that comment and that article beyond "a bit of a quack"
The fallacy fallacy is when you dismiss a conclusion based on a faulty argument. Him not addressing the argument isn't that. Him dismissing the conclusion of the argument is that.
Speaking of the fallacy fallacy, calling out someone for calling out someone for a fallacy using the fallacy fallacy is the fallacy fallacy fallacy — as an initial fallacious fumble may indeed foretell further fallacious findings in a given figure.
Oh nice to learn that. I knew a less formal version in my country which we call "the fat virgin fallacy" which is when you denounce a fallacy in a somewhat informal less strict conversation. Made popular because libertarian argie president liked to tweet and denounce fallacies like so.
Innovation comes in two flavors: incremental, which is what you'll mostly get from your establishment, and paradigm shifts, which you're more likely to get from your cranks.
That's not to say all (or even many) cranks are secretly geniuses. But they're able to explore parts of the search space that the establishment can't for all sorts of reasons.
In other words, your establishment has all the resources and can incrementally make its way to local maxima better than any crank could. But any members that start making bold claims that might threaten that establishment will be punished, out of a simple survival instinct.
Here are five of the best historical examples of individuals who were considered cranks or fringe by their peers but ultimately brought about a paradigm shift in their respective fields. Each faced intense skepticism and mockery, yet their ideas transformed our understanding of the world:
### 1. *Ignaz Semmelweis (Medicine)*
- *Contribution*: In the 1840s, Semmelweis discovered that hand-washing drastically reduced maternal deaths in maternity wards.
- *Why He Was Considered a Crank*: His idea that "invisible particles" (what we now know as germs) could cause infection was ridiculed. At the time, the concept of doctors themselves transmitting disease was unthinkable, and many in the medical community were deeply offended.
- *Impact*: Although he was dismissed and ultimately died in an asylum, his insights laid the groundwork for antiseptic practices. Today, Semmelweis is honored as a pioneer of infection control, and hand-washing is a cornerstone of medical hygiene.
### 2. *Alfred Wegener (Geology)*
- *Contribution*: In 1912, Wegener proposed the theory of continental drift, suggesting that continents moved across the Earth’s surface.
- *Why He Was Considered a Crank*: Geologists at the time thought his theory was absurd because Wegener couldn't explain how continents could move. He faced widespread ridicule, with critics dismissing his ideas as pseudoscientific.
- *Impact*: Decades later, with the discovery of plate tectonics, his theory became foundational to modern geology. Wegener is now recognized as a visionary, and his ideas radically changed our understanding of Earth's structure and history.
### 3. *Louis Pasteur (Microbiology)*
- *Contribution*: Pasteur’s germ theory of disease in the 1860s revolutionized medicine, suggesting that microorganisms were responsible for causing many diseases.
- *Why He Was Considered a Crank*: The prevailing "miasma" theory held that diseases were caused by "bad air," not germs. Many in the scientific and medical communities mocked Pasteur’s ideas, calling them "preposterous" and even "dangerous."
- *Impact*: Pasteur’s work ultimately led to sterilization techniques, vaccines, and pasteurization, transforming medicine and public health. Germ theory is now a foundational concept in microbiology, and Pasteur is one of the most celebrated figures in medical history.
### 4. *Nikola Tesla (Electrical Engineering and Physics)*
- *Contribution*: Tesla developed and promoted the use of alternating current (AC) electricity, which ultimately became the standard for power transmission worldwide.
- *Why He Was Considered a Crank*: Tesla’s ideas about AC were met with hostility from proponents of direct current (DC), most notably Thomas Edison. Tesla’s later ideas, including wireless energy transmission, were seen as wildly impractical and even "insane" by many of his contemporaries.
- *Impact*: Despite the ridicule, Tesla’s AC power systems are now the global standard, and his ideas on wireless communication foreshadowed modern radio and telecommunications. Today, he’s recognized as a visionary inventor who changed the course of technology.
### 5. *Barbara McClintock (Genetics)*
- *Contribution*: In the 1940s, McClintock discovered "jumping genes" (transposons), showing that genes could move within and between chromosomes.
- *Why She Was Considered a Crank*: Her findings were so radical that her peers couldn’t accept them, with many scientists dismissing her ideas as highly unlikely or even bizarre.
- *Impact*: Her work was eventually recognized as groundbreaking, earning her a Nobel Prize in 1983. McClintock’s discovery of transposable elements opened new avenues in genetics, shaping our understanding of genetic variation and evolution.
---
These five individuals were openly mocked, ignored, or dismissed by the scientific communities of their time. However, they each persevered and eventually brought about paradigm shifts that redefined their fields. Their stories highlight the importance of challenging conventional wisdom and illustrate how transformative ideas often come from those who are willing to go against the mainstream.
I think what your initial comment was missing is it implied just being a quack was somehow a path to new ideas.
What his is missing, in the context of Seyfreid, is that what Seyfreid is promoting:
1. Has been studied quite extensively.
2. The results of said studies do not match his claims.
3. He can't even get the details right on the data he's trying to present.
The examples you gave are different in that while the action was not understood, they explained existing data.
In particular, I think the challenge with your initial comment is that spouting bullshit is an entirely free enterprise. Testing bullshit is an expensive enterprise. So your system provides no meaningful actionable way to get to a new, coherent, understanding of the world.
And, let's be honest, Tesla is a mixed bag. He was a total crank in a lot of ways. But also a genius in other ways. Linus Pauling is similar. Complete crank around vitamin C.
A less quackish way to say the same thing is that a scientific paradigm tells people along which lines to look for answers. Looking at areas the paradigm doesn't recommend are generally not worthwhile, but occasionally you get something important, which doesn't fit in the current paradigm but will eventually help form the new paradigm.
A good heuristic could be "seems like a solid scientist in general, but this niche where he was a top level researcher led him to a split with the main stream" vs "consistently takes anti-mainstream views and has no contributions within the paradigm "
You could skip to a better heuristic: they (provably) did a thing that the mainstream people said was impossible. That other stuff is part of the blind spot.
I normally work with a 40", I'm using a a hammerspoon to divide the screen, but normally I end using one main window, with some smaller window at the side and cmd-tabbing between info. How do you manage the distraction of so many information at the same time? Do you switch between apps? use the mouse? don't you loose track of where the focused window is?
a variation of this problem is carrying your shopping cart around. A shopping list that you can buy in place A or B. Also splitting shopping wisely in both.
I use runpod or vast for training my (small) models (a few million parameters) mostly using RTX4090 up to 4 GPUs. Training is a sporadic task. Is not worth it for me to book it monthly (at these prices)
That's the second time I read this comment and I still don't believe it: it's listed as a "dedicated root server" (usually billed by the month) with no mention of typical cloud offers.
> Swift UI makes simple UIs easier, moderately complex UIs harder, and very complex UIs impossible. The moment your UI is more complex than a stack of stacks, the elegance and comprehensibly falls apart compared to autolayout. It starts to feel like CSS all over again, using trial and error to try out combinations of elements and properties with unclear interactions.
Sadly, this has been my experience. I built a moderately complex app, only to bump into more and more problems, and I find myself fighting the framework, building hacks, and implementing workarounds. When you venture into more advanced UIs, the leaky abstraction comes back to haunt you.
Have in mind that instead of training a GPT-2 model from scratch, you can opt for fine-tuning. Fine-tuning allows you to take a pre-trained model and adapt it to your specific task with much less computational resources and time. It leverages the existing knowledge of the model, resulting in better performance and faster development cycles.
I would love also if they called it Hulk the Bacterium