Estrogen exposure is a significant risk factor for endometrial cancer, which most commonly occurs in post-menopausal women. It’s a cumulative effect, as are many other things.
Not a comment on the parent post, just highlighting that biology is not so straight forward.
Had the pleasure of taking a course of his in undergrad as a newly decided philosophy major. The material was excellent and right up my alley, but more than anything I was stunned by how fluidly and clearly he communicated. Huge loss
I had the same experience, except I was definitely not a Phil major. He had a "class for every major" where we read chapters of the book he was writing (Toolkit for Thinking) and basically gave him feedback. It was an amazing strategy for him to get reviews on his book that way from totally non-Phil folks. And my name is in the book!
Great teacher, great writer. I took one of his undergrad classes, and one day I went in to his office hours to chat - I still remember how relieved he was that I wasn't there to try to debate with him about God, that I wanted to talk about something else! I think that happened to him quite a lot due to his reputation.
I haven’t read that literature very closely, but will say that I have seen lots of handoffs, and they generally involve someone who has been working 12+ hours, very often 24+ hours, who needs to hand off 10s of patients to 3+ people, all of whom have things to do and can be hard to schedule around, before they can go home.
It is not at all surprising to me that these kind of hand offs result in things being missed, and equally obvious that decreasing the patients per provider and increasing hand off window hours would at least reduce some of those errors, if not outright improve them. Bonus points for putting the peak of handoffs into late morning hours, where much more of the decision making is completed.
Of course, the only way to do that is to either:
1) drag hours out longer, which I think lots of MDs would be fine with if they weren’t expected to turn around and do it again in 18-36 hours, requiring increased staffing
Or 2) increase staffing all around and just maintain more reasonable ratios
Fun thought, we’re kind of all on one right now! Regardless of how you choose to define “human,” we’ve been around for much less time than a single revolution around the Milky Way. We get no say in the route, and our star is feeding us rather than fueling our travel, but still a wild thought.
> While there's no doubt that self-optimization topics seem to attract more men than women, why is it that people who are into gender, equality and "toxic masculinity" topics … always have to put a label on everything, such as "This is male, this is female." They seem to be falling into exactly the trap they are criticizing.
I would disagree pretty strongly that men are more into self-optimization than women. Instead, I’d wager men are more into “Self Optimization,” which is more a unique subculture than a goal or activity, and societal ideas of masculinity get a lot of play in that space. I find it pretty understandable that people interested in gender would have something to say about the way gender interacts with that space as well.
Honestly I don’t think that people are always being deeply normative when they talk about these things, they can just see features of the culture around them they find interesting and may dislike, and say so.
For example, for the bro culture comment - I think most people would agree bro culture exists, that it’s male dominated, and that concepts of masculinity have a lot to do with it. I’ve had lots of discussions with people, men and women, who feel excluded by that culture. It feels counterproductive to take “masculinity” and what comes with it off the table for that discussion in the name of the ideal of equality, especially if that discussion might win you some real equality. An example I’ve encountered in real life was my universities chemical engineering program being know for a “bro” culture, and they had some real conversations about it and the reality that it might exclude some people, and they made changes because of it.
To be fair, I’m not sure what role the gender discussion played in this piece, and I’d probably say it detracted from the point overall, so I can understand your response to it. But I don’t think that makes the practice wrong, and perhaps both a couple of bros not aware of who it is we’re excluding?
> I would disagree pretty strongly that men are more into self-optimization than women.
Sure, it very much depends on how you define "self-optimization". Let's just say there is a group of people interested in certain (selected?) topics related to self-optimization that predominantly attracts men.
> I find it pretty understandable that people interested in gender would have something to say about the way gender interacts with that space as well.
I have no issue if someone says "This and that subculture attracts mostly men [with certain character traits] and here's why this is problematic" and then goes on to explore this topic in detail. But carelessly throwing around stereotypes of masculinity and feminity doesn't help anyone.
> I’d probably say it detracted from the point overall
Yes, I would say so as well.
> It feels counterproductive to take “masculinity” and what comes with it off the table for that discussion in the name of the ideal of equality, especially if that discussion might win you some real equality.
I'm not really sure I subscribe to this idea/desire of "real equality" (which I interpret as "equality of outcome", i.e. in this case a 50-50 representation of genders), at least not on a general basis. Different people have different interests and propensities, and it seems these are controlled by biological factors (e.g. sex) to some degree[0], though it is not clear how much exactly. In any case, not only does achieving a 50-50 gender distribution across all groups seem unrealistic, it would also go against freedom of will of the individual.
Now this is not to say that making a given group (e.g. a university's chemical engineering program) more inclusive and welcoming to all kinds of people (and all genders) doesn't have benefits. It does. But if, at the end of the day, we don't reach a 50-50 gender distribution everywhere, I don't think this is an issue, either.
[0]: See the debates about "systemizing vs. empathizing" and "people vs. things".
Sorry, I was reacting to the The Conversation article linked above, not to the actual Nature paper, which seems much less patronizing to the group under study.
I assumed you were referring to ‘The Conversation’ piece actually. I’m not sure which part of the article you find woke and/or patronizing? I didn’t read it that way personally. One of the authors of the piece, Chapurukha Kusimba, is East African and seems to be a part of a group of self-described “post-colonial” scholars from the region. To me I just read actual pride for the region and its history and a desire to study it from a point of view distinct from western archeology.
I’m not sure why you talked about the pre-colonial slave trade specifically, but it read like you felt this article neglected the point in favor of a rosier image of the region’s history. The article does mention the perpetuation of colonial structures by East Africans after the British left (and cites an article by Kusimba). There’s no specific mention of the pre-colonial slave trade in this piece, but Kusimba has written about the “ancient practices that can be traced back more than two millennia in Africa.”[1] I find it unlikely he meant to gloss over this, and instead probably just focused on another time period.
Just to say so explicitly, I’m genuinely curious about how you perceived this article and why!
I had to look that one up because their interpretation seemed so unlikely to me. Doesn’t necessarily mean there is no other history there, but I found out tarballs are real things.
I had the same initial reaction, but after digging in a little I don’t think “artificial” is the worst description in the world here. I do think the innovation here is much more like an artificial neuron than an artificial synapse though. Fair warning, I’m no neuroscientist and I basically don’t know what neural networks are, but here’s what I’ve gathered.
neuron1 -> neuron2
Neuron1 receives an input signal across a synapse, “processes” that signal, and then either does or does not pass along an output signal to neuron2. I’m sure this is an incredibly deep field of research with a lot of nuance, but I think it remains a reasonable approximation to say that neurons “fire” or not in a binary manner. A lot of the magic takes place within the neuron itself, where unimaginably complex biochemistry dictates how likely a neuron is to fire in response to an input signal. As far as I understand it, this is analogous to the application of a weight to an input in a neural network.
A decent example along these lines is how opiates influence breathing. Neurons exist at a resting negative electrical state, which can be shifted to a sufficiently positive state in response to an input that the signal propagates down the neuron resulting in the passing on of that signal to the next neuron. Opiates drive that resting negative electrical state to be even more negative, and so in response to a normal “we’re running low on oxygen here!” input, a neuron will fail to become sufficiently positive to pass that signal along the chain. In NN parlance, it’s weight has been changed.
This piece describes a memristor that replicates this weighting of inputs to produce outputs through a material that stores these weights in a material that can be adjusted electrically rather than through biochemistry. There was actually a paper[0](released just two days ago!) that uses memristors to meaningfully create an artificial neuron with biochemical synapses. Of course, there’s a lot of extra machinery involved to actually be biologically useful, but nonetheless this tech can be used as a very simplified drop-in. Of course, as you say it’s like step one in a 10 billion step process, but I don’t think it’s totally dishonest to call it an “artificial” neuron, or at least a component of one.
Of course, bragging about how fast and small it is compared to a neuron and synapse is a bit like an elementary school teacher setting up a cool grow-lamp garden to teach kids about sunlight and photosynthesis and then bragging about how they produced an ultra-minutare sun that’s so efficient it runs off an outlet :)
For one, some neurons, when activated, don't just send a signal to specific other neurons, but instead release a chemical in an area, that affects the activation chances of other nearby neurons. I believe there are also other modes of activation, and other consequences of neuron activation, that make the brain far more complex. It should be remembered that the brain can also activate other glands in the body, which in turn change how the brain works - e.g. when releasing adrenaline, testosterone, oxytocin etc.
For another, as far as we know right now, each neuron itself is deciding whether to fire or not based on much more sophisticated logic than "sum(input*weight) > threshold". In fact, it seems that computation happens quite a bit in individual neurons, not only at the NN level. At the very least, the neuron activation function is not fixed, like in an ANN after training, it changes constantly for various reasons.
Oh the number of ways this model doesn’t match reality couldn’t even be counted. I suppose my standard for achieving an “artificial something” in biology is if accurately reflects reality well enough to learn from, and I only meant to imply that this might.
I will say that my mental model does hinge on the idea that the action of a single neuron at a single point in time in a single context can actually be equated to "sum(input*weight) > threshold". Doing the actual computation to figure out a principled measure of weight (and input, context, and maybe even time for that matter) is way outside our ability, but it seems like something that could be approximated in a simple experimental model!
"if accurately reflects reality well enough to learn from" - but are we learning real stuff from that, or only implications from the fake/artificial thing? I mean for sure we can see that as a brainstorming, exciting by itself, but does that get us closer to understanding the real thing, or it's at the maximum a Plato's cave exercise in rationality?
Work in the field myself. The real answer is definitely we don’t know, but for whatever reason a high diversity (lots of different kinds of bacteria) seems to be almost universally good. Fiber is the major carbohydrate source for our gut microbiome, and a fiber-rich and fiber-diverse diet seems to provide lots of niches for various bugs to grow.
Immunology is wildly complicated so my description is going to fall short of reality, but my understanding of the role of the adaptive immune system as it would relate to mRNA therapies is different.
Lymphocytes, or T cells & B cells, are immune cells which have receptors on their surface that recognize a specific, tiny chunk of protein. For any given lymphocyte, the type of receptor on its surface is fixed for its life and that receptor is able to recognize exactly one distinct protein chunk.
Through some very cool mechanisms, very early on in life we all develop a massive number of lymphocytes, each of which recognize different protein chunks. I've not read any research which quantifies the scope here, but it's not unreasonable for the sake of a thought exercise to the assume that at one point we all have a lymphocyte receptor repertoire that's capable of recognizing every conceivable natural protein. Through what I consider one of my top 10 most jaw-dropping biological mechanisms [0], we cull the population of lymphocytes that recognize self, leaving us with a cell population capable of recognizing and responding to every non-self protein conceivable. No training is needed here, each of us at this exact moment has several T cell and B cell populations ready to recognize proteins produced by the next novel pandemic causing virus, whatever future protein mRNA vaccines might make, and whatever proteins these future mRNA therapies might produce.
What you refer to as training is probably more like immunological memory, which allows for a ramping up of the immune response on a quicker timeline. We give vaccines where it's generally not safe (or survivable) to wait out an effective immune response, because the disease causes so much havoc in the meantime. This doesn't really apply for the introduction of novel, useful proteins.
Your point about Onasemnogene abeparvovec is a very interesting one. I'm truly only guessing here, but people with SMA almost universally produce functional protein via SMN2, but very little of it. It's not enough to serve its function, but is perhaps enough for effective self-tolerance. I'm also not entirely sure about the timeline of self-tolerance development, it's possible Onasemnogene abeparvovec is given young enough to allow effective tolerance development!
Not a comment on the parent post, just highlighting that biology is not so straight forward.