two more organizations that seem worthy of consideration
Investing in Eon Systems looks much more promising than donating to Carbon Copies.
I see maybe a 3% chance that they’ll succeed at WBE soon enough to provide help with AI x-risk.
PeterMcCluskey
Karma: 3,879
The Invention of Lying provides a mostly accurate portrayal of a world where everyone is honest. It feels fairly Hansonian.
No, I don’t recall any ethical concerns. Just basic concerns such as the difficulty of finding a boss that I’m comfortable with, having control over my hours, etc.
Oura also has heart rate and VO2 max tracking. Does anyone know of problems with Oura’s data?
The primary motive for funding NASA was definitely related to competing with the USSR, but I doubt that it was heavily focused on military applications. It was more along the lines of demonstrating the general superiority of the US system, in order to get neutral countries to side with us because we were on track to win the cold war.
Manifold estimates an 81% chance of ASI by 2036, using a definition that looks fairly weak and subjective to me.
I’ve bid the brain emulation market back up a bit.
Brain emulation looks closer than your summary table indicates.
Manifold estimates a 48% chance by 2039.
Eon Systems is hiring for work on brain emulation.
We can only value lives at $10 million when we have limited opportunities to make that trade, or we’d go bankrupt.
I’m suspicious of the implication that we have many such opportunities. But a quick check suggests says it’s very dependent on guesses as to how many lives are saved be treatments.
I did a crude check for lives saved by cancer treatments. Optimistic estimates suggest that lives are being saved at less than $1 million per life. Robin Hanson’s writings have implied that the average medical treatments is orders of magnitude less effective than that.
Could last year’s revamping of OpenAI’s board have been influenced by government pressure to accept some government-approved board members? Nakasone’s appointment is looking more interesting after reading this post.
Soaking seeds overnight seems to be a good way to reduce phytic acid.
oral probiotics in general might just all be temporary.
The solution to concerns about it being temporary is to take them daily. I take Seed Daily Synbiotic. My gut is probably better as a result, but I don’t have evidence that is at all rigorous.
The beginning of this comment is how Lintern expands on that claim. But it sounds like you have an objection that isn’t well addressed there.
If cancer merely involved one bad feature, I could imagine software analogies that involved a large variety of mistakes producing that one bad feature.
The hallmarks of cancer indicate that all cancers have a number of bad features in common that look sufficiently unrelated to each other that it seems hard to imagine large sets of unrelated mutations all producing those same hallmarks. Lintern lists many other features that could be considered additional hallmarks.
When I try to imagine software problems that seem analogous to cancer, I come up with problems such as spam where there’s an optimizer that’s generating the problems.
I’m unclear whether you’re imagining software problems that I haven’t thought of, or whether you’re modeling cancer differently from me.
Maybe? It doesn’t seem very common for infectious diseases to remain in one area. It depends a lot on how they are transmitted. It’s also not unusual for a non-infectious disease to have significant geographical patterns. There are cancers which are concentrated in particular areas, but there seem to be guesses for those patterns that don’t depend on fungal infections.
Thanks. You’ve convinced me that Lintern overstates the evidence of mutation-free cancer cells.
But you seem to have missed really obvious consequences of the fungi theory, like, “wouldn’t it be infectious then”,
I very much did not miss that.
containing some potentially pretty dangerous advice like “don’t do chemotherapy”.
Where did I say that?
Enough that it should have been noticed.
My guess is that almost nobody looks for this kind of connection.
Even if they do notice it, they likely conclude that pathogens are just another small influence on cancer risk.
Because radiation cannot spread a fungus
Anything that causes cell damage and inflammation has effects that sometimes make cells more vulnerable to pathogens.
How would transmission be detected? It probably takes years before a tumor grows big enough for normal methods to detect it.
I assume that transmission is common, mild infections are common, and they rarely become harmful tumors.
Here are some conversations that I had with AIs, mainly Claude 3.5 Sonnet:
Perplexity, in response to “arguments against Mark Lintern’s theory that fungal infections are the primary cause of cancer?”:
Effectiveness of current treatments: Many existing cancer treatments that do not specifically target fungal infections have shown efficacy in treating various types of cancer, which may contradict the theory that fungi are the primary cause [1].
That stands out as strange. The “effectiveness” of current cancer treatments is what led me to search for what is wrong with cancer research.
me: What are the strongest arguments against Mark Lintern’s claim that fungal infections are the primary cause of cancer?
Claude:
Mark Lintern’s claim that fungal infections are the primary cause of cancer is not widely accepted in the scientific community. While it’s important to consider alternative hypotheses, there are several strong arguments against this claim:
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Lack of robust scientific evidence: - There is a scarcity of peer-reviewed, well-designed studies supporting the fungal infection hypothesis as a primary cause of cancer. - The vast majority of cancer research points to genetic mutations, environmental factors, and other well-established risk factors.
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Inconsistency with epidemiological data: - Cancer incidence patterns and risk factors observed in large-scale population studies don’t align well with patterns of fungal infections. - Known risk factors like smoking, UV radiation, and certain chemicals have much stronger correlations with cancer incidence.
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Cancer genomics: - Extensive genomic studies, such as The Cancer Genome Atlas, have identified numerous genetic mutations and alterations in cancer cells that are not explained by fungal infections. - These genetic changes are often directly linked to cancer-related processes.
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Mechanism of action: - While some fungi can produce carcinogenic compounds, there’s no clear mechanism by which fungi could consistently cause the specific genetic alterations observed in various types of cancer.
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Immunocompromised patients: - Patients with compromised immune systems are highly susceptible to fungal infections. If fungi were the primary cause of cancer, we would expect to see much higher cancer rates in these populations, which is not the case.
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Treatment efficacy: - Cancer treatments targeting cellular mechanisms and genetic alterations have shown significant efficacy, which would be unlikely if fungi were the primary cause.
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Experimental evidence: - Laboratory studies inducing cancer in animal models through genetic alterations or carcinogen exposure don’t require fungal involvement.
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Tissue culture studies: - Cancer cells can be grown and studied in sterile laboratory conditions without any fungal presence, demonstrating that fungi are not necessary for cancer cell survival or proliferation.
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Hereditary cancers: - The existence of hereditary cancer syndromes, where specific genetic mutations dramatically increase cancer risk, is difficult to explain with a fungal infection hypothesis.
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Cellular and molecular biology: - Our understanding of cancer at the cellular and molecular level, including oncogene activation and tumor suppressor inactivation, doesn’t require fungal involvement to explain cancer development.
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Inconsistency across cancer types: - Different cancers have distinct molecular profiles and risk factors. A single cause (fungi) is unlikely to explain this diversity.
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Successful prevention strategies: - Many cancer prevention strategies (e.g., smoking cessation, sun protection) are effective without addressing fungal infections.
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Lack of fungal signatures: - Sophisticated genomic analyses of tumors have not revealed consistent fungal genetic material or signatures across cancer types.
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Evolutionary perspective: - Cancer is observed across many animal species, including those with very different susceptibilities to fungal infections than humans.
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Clinical observations: - Clinicians and pathologists routinely examine cancer tissues and rarely report finding evidence of widespread fungal involvement.
While it’s true that some fungi can produce carcinogenic compounds and that certain fungal infections (like chronic candidiasis) have been associated with slightly increased risk of specific cancers, the evidence overwhelmingly suggests that fungi are not the primary cause of most cancers. The scientific consensus supports a multifactorial model of cancer causation, involving genetic, environmental, and lifestyle factors, with somatic mutations playing a central role in most cases.
It’s important to approach such claims critically and rely on well-established scientific evidence and consensus when considering cancer causes and treatments.
Most of Claude’s points seem weak, often assuming a rather controversial belief that fungi are reliably detected when they’re present. The point that looks strongest to me is the one about Immunocompromised patients.
me: What’s the best source of evidence for cancer rates in immunocompromised patients?
Claude:
To find the best evidence for cancer rates in immunocompromised patients, we should look at large-scale epidemiological studies, systematic reviews, and meta-analyses. Some of the most reliable sources include:
HIV/AIDS patient cohorts: The HIV/AIDS Cancer Match Study, conducted by the National Cancer Institute, is one of the most comprehensive sources. It links HIV/AIDS and cancer registry data in the United States.
Key resource: Engels, E. A., et al. (2008). Trends in cancer risk among people with AIDS in the United States 1980--2002. AIDS, 22(16), 2101-2108.
Transplant recipient studies: The Transplant Cancer Match Study, also by the National Cancer Institute, is an authoritative source for cancer incidence in organ transplant recipients.
Key resource: Engels, E. A., et al. (2011). Spectrum of cancer risk among US solid organ transplant recipients. JAMA, 306(17), 1891-1901.
Systematic reviews and meta-analyses: These provide comprehensive overviews of multiple studies.
Example: Grulich, A. E., et al. (2007). Incidence of cancers in people with HIV/AIDS compared with immunosuppressed transplant recipients: a meta-analysis. The Lancet, 370(9581), 59-67.
Large national databases: Countries with comprehensive health registries, like the Nordic countries, often provide valuable data.
Example: Vajdic, C. M., & van Leeuwen, M. T. (2009). Cancer incidence and risk factors after solid organ transplantation. International Journal of Cancer, 125(8), 1747-1754.
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Collaborative international studies: The International Immunocompromised Host Society (ICHS) often publishes comprehensive data.
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Specific immunodeficiency disorder studies: For rare immunodeficiency disorders, studies like the USIDNET (United States Immunodeficiency Network) can be valuable.
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World Health Organization (WHO) reports: The WHO occasionally publishes comprehensive reports on cancer in immunocompromised populations.
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Centers for Disease Control and Prevention (CDC): The CDC maintains databases and publishes reports on cancer incidence in HIV-infected individuals.
When evaluating these sources, consider: - Sample size—Duration of follow-up—Methodology for cancer detection and classification - Adjustment for confounding factors—Recency of the data
It’s important to note that cancer rates can vary depending on the specific cause and nature of immunosuppression, so looking at multiple sources covering different immunocompromised populations can provide a more comprehensive picture.
me: What does the Somatic Mutation Theory of cancer predict about the kinds of mutations seen in the DNA of cancer cells? What kind of evidence concerning those mutations would falsify the theory?
Claude:
The Somatic Mutation Theory (SMT) of cancer makes several predictions about the kinds of mutations seen in the DNA of cancer cells. Here are the key predictions and the types of evidence that could potentially falsify the theory:
Predictions of the Somatic Mutation Theory:
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Accumulation of mutations: SMT predicts that cancer cells will have accumulated multiple mutations over time.
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Driver mutations: Some mutations (called driver mutations) will be causally implicated in cancer development, affecting genes that control cell growth, division, or death.
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Passenger mutations: Other mutations (called passenger mutations) will be present but not directly contributing to cancer development.
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Clonal expansion: Cells with advantageous mutations will undergo clonal expansion, leading to a population of cancer cells with shared mutations.
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Heterogeneity: Different areas of a tumor may have different sets of mutations due to ongoing mutation and selection processes.
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Specific gene types: Mutations will often affect proto-oncogenes (promoting cell growth) and tumor suppressor genes (inhibiting cell growth).
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Functional changes: Mutations will lead to functional changes in proteins that drive cancer-related processes (e.g., increased proliferation, evading apoptosis).
Evidence that could potentially falsify the theory:
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Lack of mutations: If cancer cells consistently showed no increase in mutations compared to normal cells, this would challenge SMT.
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Random distribution: If mutations in cancer cells were completely random and showed no enrichment in cancer-related genes, this would be contrary to SMT predictions.
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Reversibility without genetic changes: If advanced cancers could be consistently and permanently reversed to normal cells without altering their genetic material, this would challenge SMT.
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Lack of clonality: If cancer cells within a tumor showed no evidence of clonal relationships, this would be inconsistent with SMT.
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Identical mutations across cancer types: If all cancers, regardless of tissue origin or type, always had the exact same set of mutations, this would be difficult to explain with SMT.
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Non-genetic transmission: If cancer could be reliably transmitted between individuals or cells without any transfer of genetic material or induction of new mutations, this would challenge SMT.
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Perfect correlation with environmental factors: If cancer incidence was perfectly explained by environmental factors alone, with no role for random mutations or genetic susceptibility, this would be inconsistent with SMT.
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Lack of genomic instability: If cancer cells showed no signs of genomic instability or increased mutation rates compared to normal cells, this would be contrary to many versions of SMT.
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Mutations without consequences: If the identified mutations in cancer cells could be shown to have no functional consequences at all, this would challenge a key aspect of SMT.
It’s important to note that while these findings would challenge SMT, they would need to be consistently replicated and thoroughly verified before the theory would be considered falsified. Many of these potential falsifying observations have not been seen; instead, the accumulating evidence has generally supported the main tenets of the Somatic Mutation Theory, though it has also led to refinements and expansions of the theory over time.
me: What does the Cancer Genome Atlas say about whether mutations in cancer cells tend to be in cancer-related genes?
Claude:
The Cancer Genome Atlas (TCGA) has provided extensive data on the genomic characteristics of various cancer types, offering significant insights into the patterns of mutations in cancer cells. Regarding your specific question about whether mutations in cancer cells tend to be in cancer-related genes, TCGA data strongly supports this notion. Here’s a summary of key findings:
Enrichment in cancer-related genes: TCGA data shows that mutations in cancer cells are indeed enriched in cancer-related genes. These include:
Oncogenes (e.g., KRAS, BRAF) - Tumor suppressor genes (e.g., TP53, PTEN) - DNA repair genes (e.g., BRCA1, BRCA2) - Cell cycle regulators (e.g., RB1, CDKN2A)
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Recurrent mutations: Certain genes are found to be recurrently mutated across multiple cancer types, suggesting their importance in cancer development. For example, TP53 is mutated in a high percentage of various cancers.
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Cancer-type specific patterns: While some genes are commonly mutated across cancer types, TCGA has also revealed cancer-type specific mutation patterns. For instance: - BRAF mutations are common in melanoma
APC mutations are frequent in colorectal cancer—EGFR mutations are often seen in certain lung cancers
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Pathway-level alterations: TCGA data shows that even when specific genes are not mutated, the pathways they belong to are often altered. This supports the idea that cancer-related processes are being targeted by mutations.
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Driver vs. passenger mutations: TCGA analyses have helped distinguish between driver mutations (in cancer-related genes) and passenger mutations. Driver mutations are less common but more impactful, often occurring in cancer-related genes.
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Mutational signatures: TCGA has revealed mutational signatures that are associated with specific cancer types or carcinogenic exposures, many of which affect cancer-related genes more frequently.
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Fusion genes: TCGA has identified numerous fusion genes in various cancers, often involving known cancer-related genes, further supporting the concentration of impactful mutations in cancer-relevant genomic regions.
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Copy number alterations: Beyond point mutations, TCGA data shows that copy number alterations (amplifications and deletions) also frequently affect cancer-related genes.
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Epigenetic alterations: While not mutations per se, TCGA has shown that epigenetic changes (like DNA methylation) often affect the expression of cancer-related genes.
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Mutual exclusivity: TCGA data has revealed patterns of mutual exclusivity among mutations in certain cancer-related genes, suggesting that altering one component of a pathway is often sufficient for cancer development.
It’s important to note that while TCGA data strongly supports the concentration of mutations in cancer-related genes, it also reveals the complexity of cancer genomics:
Not all mutations in cancer cells are in known cancer-related genes. - The functional impact of many mutations is still not fully understood. - There’s significant heterogeneity both within and between cancer types. - Some cancers show a high mutational burden across the genome, while others have fewer, more specific alterations.
In conclusion, TCGA data provides robust evidence that mutations in cancer cells tend to be enriched in cancer-related genes, supporting key aspects of the Somatic Mutation Theory of cancer. However, it also highlights the complexity of cancer genomics and the need for continued research to fully understand the role of various genetic alterations in cancer development and progression.
me: I’ve seen reports (via Mark Lintern) that a number of cancers involve no mutations. How do supporters of the Somatic Mutation Theory respond to such claims?
Claude:
The claim that some cancers involve no mutations is indeed a challenge to the Somatic Mutation Theory (SMT) of cancer. This topic has been a subject of debate in the cancer research community. Here’s how supporters of SMT typically respond to such claims:
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Questioning the methodology: - SMT supporters often argue that the studies claiming “mutation-free” cancers may have limitations in their detection methods. - They suggest that more sensitive techniques or broader genomic analyses might reveal mutations that were initially missed.
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Epigenetic alterations: - Some SMT proponents argue that while there might not be detectable DNA sequence mutations, epigenetic changes (which can alter gene expression without changing the DNA sequence) could be present. - They consider epigenetic alterations as an extension of the mutation concept, still fitting within a broader interpretation of SMT.
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Inherited genetic factors: - In some cases, cancer might develop due to inherited genetic factors rather than new somatic mutations. SMT supporters argue this still fits within the genetic basis of cancer.
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Chromosomal abnormalities: - Some cancers might have large-scale chromosomal abnormalities (like aneuploidy) rather than point mutations. These are still genetic changes consistent with SMT.
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Viral oncogenesis: - In cancers caused by viruses, the viral genes might drive cancer development without new mutations in the host genome. SMT supporters argue this still involves genetic alterations, albeit from an external source.
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Rare exceptions: - SMT proponents often argue that even if some cancers truly lack mutations, these are likely rare exceptions that don’t invalidate the theory for the vast majority of cancers.
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Limitations of current knowledge: - They might argue that our current understanding of cancer-related genes is incomplete, and mutations in yet-unknown cancer-related genes might be present.
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Challenging the “mutation-free” claim: - Some supporters question whether truly “mutation-free” cancers exist, suggesting that more comprehensive analyses would likely reveal some level of genetic alteration.
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Fusion genes and other structural variations: - Some genetic alterations, like gene fusions, might not be detected by methods looking for point mutations but still represent genetic changes consistent with SMT.
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Mosaicism and low-frequency mutations: - They argue that some mutations might be present in only a small subset of cells or at very low frequencies, making them difficult to detect with standard methods.
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Expanding the definition of “mutation”: - Some researchers propose broadening the definition of mutations to include other types of genetic and epigenetic alterations, thus maintaining the core of SMT while accommodating new findings.
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Integrating with other theories: - Many SMT supporters advocate for an integrated view of cancer development, incorporating aspects of other theories (like the metabolic theory or tissue organization field theory) while maintaining the central role of genetic alterations.
It’s worth noting that the cancer research community continues to debate and refine theories based on new evidence. While SMT remains a dominant paradigm, many researchers acknowledge that it may not fully explain all aspects of cancer development and progression. The field is moving towards more nuanced and integrated models of cancer biology that can account for the complex and diverse nature of the disease.
I just published a post on Drexler’s MSEP software that is relevant to whether people should donate to his project.