revolutionary in scientific circles is very different than revolutionary in public facing circles.

At it's core, this group is using stem cells to prevent glial scarring. That's huge. Implants like electrodes are an obvious starting point, but there's some recent work - apart from this paper - also looking at using stem cells to manage scarring from actual injury to nervous tissue - so that could be a management strategy for spinal cord injuries or peripheral nervous issues. All sorts of cool avenues to look at next.

Is this something that will be a treatment strategy in the next 6 months? absolutely not. Progress happens slowly, but it does happen, and this is a great track to explore.

>Also title itself says "paralyzed limbs".

Who cares what the title says?

In an ideal world, people would read the actual published journal article. The bare minimum should be reading the entirety of the public facing article because science is all about the details, and headlines are not. Now we can get into the quality of science journalism (generally, it's shit), but this article actually addresses your exact criticisms directly and clearly.

The situation "they" present (if one reads the article, which you clearly didn't) is both restoration of function, AND integration of artificial limbs.

Besides that, the linked article talks quite a bit about the specific problem this is solving (scar tissue development) and other possible uses (prosthetics and BCIs).

Off the top of my head, using a similar strategy may be a benefit to things such as deep brain stimulators or other CNS implants that are upstream of the spinal cord, since glial scarring is a huge problem there too.

So, no - this isn't a "dead end" for the situation they present it, because they present multiple situations and you focused (incorrectly) on one. Turns out, reading past the headline is often helpful when discussing recent developments in cutting edge, detail oriented fields.

>"The challenge with integrating artificial limbs, or restoring function to arms or legs, is extracting the information from the nerve and getting it to the limb so that function is restored."

How does spinal repair help someone who lost the limb in the first place? Be as specific as you can please.

>and not just slap the implant on and say it's done.

It's a good thing that's not what they're doing then.

>know some studies show educated westerners tend to have less kids

This isn't a westerner thing, this is a "literally every economically developed country, and most developing" thing.

Every economically developed country is under replacement rate. A lot of developing countries are dropping dramatically. India went from a rate of 6.something to replacement adjacent over the course of 50 years.

It has absolutely nothing to do with sleep schedules. Birth rate drops as a society becomes more economically developed, and - crucially - women have a greater emphasis on their own education and career.

>Obviously I said "science is about gathering data and doing measurements".

Wow, you don't even know what you said.

No, you didn't say that "science is about gathering data and doing measurements".

You specifically said that

>Well again the problem is thinking that science is about gathering data and doing measurements.

This conversation has run it's course. There is no worthwhile discussion to be had with someone that doesn't even understand their own written claims. Just lead with that next time, and save us all some effort.

That's not what I asked. I'm not saying that hypotheses are not important.

Here is your original statement.

>Well again the problem is thinking that science is about gathering data and doing measurements. That doesn't really help with figuring out how things work.

For this to be true, you must be able to "figure out how things work" without data and measurements.

I'm not the one taking the stance that hypotheses are not important. You are the one taking a stance that data is not important. Defend it.

Explain to me how you validate a hypothesis without any data. Don't use Darwin or Einstein, their contributions were based in explaining previous data, as well as explaining anomalous data. Therefore, you cannot use them as an example here.

Please explain specifically how data collection doesn't help with "figuring out how things work".

I've only asked you several times now. Maybe this time, you'll actually defend your stance. Who knows, I'm an optimist.

Or maybe, you're full of shit and have no way of explaining how data analysis somehow doesn't help with "figuring out how things work". I don't think asking someone to defend their own stance is unreasonable, but well, here we are.

I was just using protein changes as an example, since that's what I'm most familiar with.

My main point was that the research techniques we use for establishing mechanisms and pathways are not compatible with humans, since they tend to be very destructive to the individual.

Prove it. Find me a definition of a scientific theory that explicitly excludes data, or a basis in data. I've provided you with plenty of sources. Put your money where your mouth is.

And can you please describe how this (incorrect) emphasis on theory relates to biomedical sciences and establishing mechanistic causes for neurological pathologies?

Can you explain to me specifically how gathering data doesn't help with figuring out how things work? How do you know your hypothesis is correct without data?

>There is not a single scientific theory that contains “data”, because if it did, then by definition it stops being a theory and it just becomes data.

You have just proven you don't understand what a "theory" is in science.

The dictionary definition of a Scientific Theory notes specifically that it is an explanation that has been repeatedly and thoroughly tested in accordance with the scientific method. YOU CANNOT HAVE A SCIENTIFIC THEORY WITHOUT DATA CORROBORATING IT. A Scientific Theory, BY DEFINITION, must include data supporting a hypothesis. A Scientific theory without supporting data is not a theory - it is a untested, unsubstantiated hypothesis. The single exception is cases where it is entirely impossible to gather data - which is not a situation that applies to life sciences.

You have a dangerous, fundamental misunderstanding of science.

>Of course, we test a theory by data, but the theory itself is not data.

No, you don't. You test a hypothesis. A theory is something that already has a veritable mountain of supporting evidence in the form of data from experiments. If your theory has no data, 99% of the time it is a hypothesis, not a theory.

If you're going to pedant, at least be accurate.

>And how did you exactly come up with that hypothesis? It certainly wasn’t just gathering “data”.

You look at previous literature, and previous data? Science is iterative. No one is coming up with completely original ideas that have no grounding in previous experimentation. Either A) You notice something interesting in previous data and design a experiment as an extension of that idea or B) You notice something anomalous in previous experiments, and design experiments to challenge that data.

Every single funded grant has significant preliminary data. Every hypothesis, every question has data to back it, and data is the ONLY way to test a hypothesis.

>Einstein barely gathered data and instead did a lot of thought experiments to come up with relativity.

What relevance does Einstein have to biomedical and life sciences research? You're right of course, if we ignore all the experimentation to validate the theory of relativity, there really isn't a huge emphasis on data gathering.

How do you establish a mechanistic pathway WITHOUT gathering data and collecting experimental measurements? How do you reject or accept a biomedical hypothesis without data? Be as specific as you can.

>Well again the problem is thinking that science is about gathering data and doing measurements.

It literally fucking is?

You propose a hypothesis: EG - I believe that Schizophrenia is caused by changes in X protein, or alterations in Y function in the brain.

You design experiments to test the hypothesis. You gather data to support or disprove that hypothesis: Maybe you look at western blots to see if there are changes in protein expression. Maybe you collect ephys data to see if there are changes in electrical activity due to changes in this protein. Maybe you analyze biomarkers of particular metabolic processes. You analyze that data and determine if there is a significant change between the control condition and experimental (schizophrenic) condition.

>That doesn't really help with figuring out how things work.

How do you think this works? Because if you go to any graduate school or any academic, research, or medical institution and make the argument that science and research isn't about data collection and experimental design, you will be laughed out of the room.

Explain to me precisely how someone establishes a mechanistic pathway WITHOUT gathering data and collecting experimental measurements please. Be as specific as you can.

>What they need to be doing is to figure out how a disorder works.

And the difficulty with this is that the field is sharply limited on what data we can gather from humans. The highly sensitive research techniques looking at protein function, or electrophysiological data or whatever have 2 things in common. A) They are highly invasive. B) The are either terminal procedures, or highly damaging. For obvious reasons, we don't do these in humans. This research happens in animal models, typically rodents.

But that brings us to problem 2: How do you know that your mouse model of psychosis is actually experiencing psychosis? We can't ask a mouse about it's perception on reality.

And then problem 3 happens: Sure, you may have a reasonable mouse model of psychosis, but treating psychosis in 1 species is exceptionally different than treating it in humans. Protein expression is very different, and what works in a mouse does not work in a human.

Medical research is limited by the measurements we can take, and the model systems we use. Biggest advancements will happen when we can mechanistically define a condition rather than looking at the overlap of subjective symptoms, and THAT requires better measurement techniques.

It doesn't.

Before any sort of experimental drug proceeds to clinical trials, it needs to have robust preclinical data showing A) Safety in animal models and B) some functional data suggesting it would have efficacy in humans. Primary research into neurological conditions and mental pathologies is limited by model systems and the measurements we can take.

The most detailed measurements in neuroscience are terminal, invasive procedures. For obvious reasons, we do not do these in humans. So we have to use a animal model - typically a rodent of some sort. But there are enormous species to species differences that make assessing model systems very difficult.

Consider the primary symptoms of schizophrenia in a human; psychosis, delusions, apathy and others. How do you assess if a mouse or rat is actually experiencing auditory hallucinations? By what criteria can you examine a mouse model, and determine if it is undergoing psychosis? If my hypothesis is that psychosis is caused by X deviation in Y protein, I first need to have an accurate animal model for psychosis. Or I could look at the animal first, and then look at humans after, but that has it's own challenges.

The biggest limits on research in mental pathologies is developing accurate mechanistic causes for conditions such as schizophrenia. Once you have a clear idea on what the problem is - protein expression, inappropriate excitability, etc - you can far more accurately develop new therapeutic drugs, or repurpose old drugs.

It has little to do with emotional bias in research, and far more to do with technical limitations in what data we can actually gather.

>someone without schizophrenia to correctly perceive schizophrenia.

This has little to do with bias, and more to do with the fluid nature and standards we use to diagnose these conditions. If you look at a DSM or similar diagnostic catalog, over the years, you'll notice that the criteria for diagnoses change. This is a result of learning more about the condition - but at the end of the day, there isn't a simple, mechanistic diagnosis for most mental pathologies.

In the case of schizophrenia, we can't say If you have a protein level <X, you have schizophrenia. It comes down to a number of subjective symptoms, and how the patient experiences them. That's not bias, that's simply not having a clear cut definition for a condition.

Combine this with the fact that many conditions that are considered distinct have similar or overlapping symptom profiles, despite having potentially different causes and potentially different responses to therapeutic strategies.

Emotional bias in research is not the biggest problem. The biggest problem is that defining a clear cut mechanistic cause for these conditions is exceptionally difficult.

>with no substance.

Welcome to Futurology.

I don't have a background in AI, but I do have a pretty good grasp on Neuroscience.

The articles and comment sections on anything related to neuro are absolutely atrocious. There is no worthwhile discussion to be had. Most comments are pop culture references, or talking about some 70s dystopian nonsense that has nothing to do with the article. It's abundantly clear that very few people read past the headlines, let alone actually reading the primary research. Most commenters don't understand the absolute basics of the field, and most of the articles that are posted here are utter horseshit anyway. There was one a while back about direct brain to brain communication, that of course, led people down the rabbit hole of big brother listening to your thoughts, etc etc. About 3 people actually read the article, which was simply talking about distinguishing what letter a person looked at, and printing that letter on a different monitor for someone to read. That's not novel, or exciting, or new. But the bullshit rises to the top.

I can only assume that neuro articles and discussion are not unique in their awfulness around here, and that every field is similarly poorly informed - I just don't have the background to identify it in other fields. Given that, I'm fairly confident that all the doom and gloom around AI discussions is completely unsubstantiated. It's just the hot new thing to speculate wildly about.

>The Toyota that famously has avoided EV's as long as they can and don't have ANY right now? Same with Subaru?

If you're going to rant about accuracy, at least be correct. Toyota has the BZ4x, and the Lexus ux300e, and the soon to be released RZ450e.

Subaru has the Solterra.

The Bz4x and Solterra are basically the same vehicle. They aren't brilliant, but their existence is not disputable.

Care to explain why you were trying to equate them then?

targeted electrical/magnetic stimulation and seizures are also two different things.

You're the one equating BCIs with cutting corners, not me.

>Ever have a seizure before?

Ever seen what deep brain stimulators have been doing for Parkinson's patients for the last 2 decades or so?

The biggest problem with Neuralink is that all the marketing and attention goes to a company that isn't particularly remarkable. It's a very exciting field that can make huge improvements to patient quality of life. Neuralink is not the company to pay attention to - look into what the academic labs are doing.

Equating targeted stimulation protocols to having a seizure reeks of ignorance of the field. Especially when brain stimulation has been an approved treatment strategy for Parkinson's and Essential Tremors for, at least 2 decades now.

This is absolutely fascinating. I don't have time to read your article just yet - But I have some questions, and I hope they aren't immediately addressed in the paper, so I'm not wasting everyone's time.

How do you intend to do the reverse operation - writing information to the nerves?

My background is in neuroscience, not biomedical engineering. I'm more familiar with optogenetic schemes, but those rely on modified light sensitive receptor expression in the target neuron. Is your scheme able to stimulate the neuron without changing protein expression within the cell?

Additionally, optogenetic approaches need a fairly intense light source, and that runs the risk of causing damage to the tissue in research settings. Is that a concern for your system?

Thanks again. This is the coolest thing I've read in a while.

I absolutely love how you cut out the paragraph between the 2 you actually quoted. Let me add it back in.

>In fairness, China also leads the world in terms of installed wind and solar power, and investments in energy storage batteries, electric vehicles, and ultra-high transmission lines—all key elements for a clean energy transition. China has also pledged to peak related air emissions by 2030, and the Xi government has said it will drastically cut coal use in 2026 to meet that goal.

I've no idea why you would selectively exclude that section, except to push a biased view of the Chinese energy industry.

China leads the world in most energy metrics. They just need more energy, and they are investing heavily in basically every source.