Thursday, March 3, 2022

Organoids of the Nasal Persuasion


Model of the human nose reveals first steps of SARS-CoV-2 and RSV infection
Feb 2022, phys.org

I used to think it was a big deal that we knew how to grow diamonds in a laboratory. But then we started to grow organs. Intestines, kidneys, lungs,  brains (pictured above) and now noses.

They made a nose from scratch, using nose epithelial cells swabbed from somebody's nose, and placed on a substrate designed to enable them to interact as they normally would with the environment. (For this study, they were adding to that environment SARS-CoV-2 and RSV virions.) We could then call this an artificial nose, although that might be misleading. It's not full-blown olfaction, but it's a step. 

via Baylor College of Medicine: Anubama Rajan et al, The Human Nose Organoid Respiratory Virus Model: an Ex Vivo Human Challenge Model To Study Respiratory Syncytial Virus (RSV) and Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Pathogenesis and Evaluate Therapeutics, mBio (2022). DOI: 10.1128/mbio.03511-21

Image credit: This is a human brain organoid, from the National Institutes of Health, circa 2021.

Wednesday, February 16, 2022

Deep Nose


Artificial networks learn to smell like the brain
Oct 2021, phys.org

We now have an artificial neural network that works like the nose. It's not an electronic nose; that's not the big deal part. 

What's important here is that, first of all, this is from the lab that brought us olfactory receptors. Next, these scientists didn't even model the network on evolution. They made an algorithm to solve an odor categorization task, and let the network run with it. Some might call that artificial evolution, but scientists will call it machine learning. After several iterations, the network found an optimized structure for solving this task -- the network ended up looking just like our olfactory system. Go figure.

The "brains" of a neural network lies in its ability to reduce the dimensionality of the information thereby optimizing computation. This is done using compression layers that learn to accept information from some neurons and not from others. After enough iterations, a pattern emerges between the layers of neurons.

Talking about this pattern, and the number of neurons connected to by each neuron on the compression layer:
"It could have been one, it could have been 50. It could have been anywhere in between," Yang says. "Biology finds six, and our network finds about six as well."

The first part of our nose where the hundreds of olfactory receptors collapse into far less neural nodes, one layer up the network, is very similar to the type of artificial neural network used in this study. It is, apparently now supported by these findings, a very effective way to condense a multi-dimensional information-space of chemical signals. Would it work for other information-spaces? What other Big Data can this deep nose model compute?

The side story: Evolution found this organization through random mutation and natural selection over eons; the artificial network found it through standard machine learning algorithms, in under one minute. 

via  Massachusetts Institute of Technology: Peter Y. Wang et al, Evolving the olfactory system with machine learning, Neuron (2021). DOI: 10.1016/j.neuron.2021.09.010

Image credit: Google's quantum computer, totally unrelated, just for looks

Post Script:
Neural network reveals new insights into how the brain functions
Dec 2021, phys.org

"The neural network model approach we have developed in this work presents an 'instruction manual' for other researchers to use to study other areas of the brain or other organs"
-co-author Dr. James Martin, co-author and professor of molecular physiology and biophysics at Baylor College
Their model is called Spatial Transcriptomics cell-types Assignment using Neural Networks (STANN).

via Baylor College of Medicine: Francisco Jose Grisanti Canozo et al, Cell-type modeling in spatial transcriptomics data elucidates spatially variable colocalization and communication between cell-types in mouse brain, Cell Systems (2021). DOI: 10.1016/j.cels.2021.09.004

I'm not certain about this, but I think the reason they chose the olfactory system is because they were looking at the interaction of transcription genes and brain cell types, and the olfactory receptor brain cells are the only one's that each get their own gene. So that would make the olfactory bulb an ideal nexus for investigation of this kind. See studies below for further reference:

Marei H.E.S. et. al. Gene expression profile of adult human olfactory bulb and embryonic neural stem cell suggests distinct signaling pathways and epigenetic control. PLoS One. 2012; 7: e33542. https://doi.org/10.1371/journal.pone.0033542

Nagayama S. et. al.  Neuronal organization of olfactory bulb circuits. Front. Neural Circuits. 2014; 8: 98. https://pubmed.ncbi.nlm.nih.gov/25232305/


Social Deodorization


AKA Life Without Body Odor, Coming Soon

Life in the pits - Scientists identify the key enzyme behind body odor
Aug 2020, phys.org

We already knew the bacterium Staphylococcus hominis was the culprit, but these researchers have identified the specific enzyme (C-T lyase) in the bacteria that turns our odorless sweat into body odor, or what scientists call thiolalcohol. So now we can create a model of that enzyme, and figure out how to deactivate it. 

There's not enough science fiction out there looking at a society without body odor. Just kidding, this is already reality. And what happens is, the people who don't smell still use deodorant, because the people who do smell have just enough spending power to sustain a global corporate personal hygiene complex so powerful it can influence you to deodorize yourself even if you have no odor in the first place. 

If you're interested in this sort of thing, soft paywall to the New York Times about Unilever's attempts to sell deodorant in China, "a market with 2.6 billion armpits" (2018).

via University of York and Unilever: The molecular basis of thioalcohol production in human body odour, Scientific Reports (2020). DOI: 10.1038/s41598-020-68860-z

Post Script:
The smell of your breath is a subset of body odor. 
Research reveals details of how salivary glands collectively produce constellation of proteins found in saliva
Nov 2020, phys.org

What's in your saliva? Here you go. They don't tell you what it smells like, but with this info you'll be halfway there. Also, "oral biofluid" is science for saliva.

Also, in case you were wondering, "cysteine-rich secretory protein 3 (CRISP3) ... is expressed by human labial glands."

via University at Buffalo: Marie Saitou et al. Functional Specialization of Human Salivary Glands and Origins of Proteins Intrinsic to Human Saliva. Cell Reports Volume 33 Issue 7, 108402, Nov 17, 2020. DOI: 10.1016/j.celrep.2020.108402


Tuesday, February 1, 2022

You Don't Know What You're Missing


Attention and memory deficits persist for months after recovery from mild Covid
University of Oxford News, Jan 2022

"Although our Covid-19 survivors did not feel any more symptomatic at the time of testing, they showed degraded attention and memory."
-Dr Sijia Zhao of the Department of Experimental Psychology, University of Oxford
Repasted from above article:
All the participants had previously suffered from Covid-19 but were not significantly different from a control group at the time of testing on factors such as fatigue, forgetfulness, sleep patterns or anxiety.

But, they displayed significantly worse episodic memory and a greater decline in the ability to sustain attention over time than uninfected individuals for 6-9 months.

Note, the COVID-19 survivors in this study were young, mean age around 28, n=136.

How bad was it? Here is a measurements for context: Over the course of the 9-minute experiment, control participants’ accuracy dropped from 78.5% to 75.4%, whilst COVID survivors started with a similar baseline at 75.5%, reducing to 67.8% ... For a 30-minute memory test, COVID-19 survivors showed a significant memory decrement which was larger than in controls by 9.2%.

And to be specific: The larger episodic memory decrement amongst COVID-19 survivors was driven by errors in which the wrong orientation was chosen for a correct item. This difference suggests that the deficit in episodic memory in the COVID group might be associated with a deficit in binding information in memory. 

Interesting: word-memory tasks showed no change. 

How it might happen, if you're interested: One investigation of COVID-19 survivors demonstrated that the most severely cognitively affected patients demonstrated a degree of cognitive impairment accompanied by hypometabolism in the frontoparietal regions. These brain regions are implicated in sustained attention as well as in episodic memory. Reassuringly, the follow-up study of Hosp et al. showed slow but evident improvement after 6 months.

Last thing: The good news is that COVID-19 survivors performed well in most cognitive abilities tested, including working memory, executive function, planning and mental rotation. 

via University of Oxford: Rapid vigilance and episodic memory decrements in COVID-19 survivors. Zhao et al. Brain Communications. Jan 2022. https://academic.oup.com/braincomms/article/4/1/fcab295/6511053


How Is This Related to Smell?
We already know that changes in our ability to smell were the primary symptom of the initial varieties of covid. Some of us still deal with these changes. But something we also know, regardless of any pandemic, is that smell is tightly linked to episodic memory -- "grandma's attic" or "first boyfriend's cologne" -- and a subset called autobiographical memory. These type of memories tie together people, places, feelings and smells into the olfactory cluster. Chemosensation enabled the first navigation, as primordial protists sniffed their way through the soup of early Earth. Chemosensation enabled the first social experience, when you detected your mother's immunity profile via her amniotic fluid. And chemosensation enabled your primate ancestors to remember where that really ripe fruit tree was. 

So it does seem appropriate that a virus attacking your olfactory neurons would also affect your episodic memory.

Image credit: Just astrocytes, upsplash

Post Script:
For those who haven't heard about this enough already, here's a good reminder of what Long Covid is: People who survive COVID-19 infection present a significantly higher risk of major neurological and psychiatric conditions, particularly if they were hospitalized. These include acute cerebrovascular events such as ischaemic stroke and intracerebral haemorrhage. In addition to severe neurological conditions, there can also be more chronic, longer-term consequences such as fatigue, low motivation, disturbed mood and poor sleep—all commonly reported symptoms amongst survivors, the so-called long-COVID (see recent review). -source

Tuesday, December 21, 2021

Trans-Epistemological Etymologues - VOC vs VOC


Violating Organic Content - The new VOCs!

For years we have been both addicted to and suspicious of VOCs -- volatile organic compounds. They smell great, like gasoline, baked bread, or bergamot. They can also get into our bloodstream and cause health problems. They evaporate from all kinds of things, and we can measure them with special "VOC meters," although the human nose is by far the most sensitive all-purpose VOC-detector on the market. (Don't forget there are plenty of things that are bad for you that you CAN'T smell at all; and then there's anosmia too.)

But now, a new VOC is on the scene, one potentially far more serious to the survival of our cultural species. They're called "violating organic contents," and they're like little diseases floating around our collective neural network.

Perhaps "floating" is the wrong word. They're jamming your brain via high-frequency algorithms, engineered to reprogram your hardwired hormone circuits of reward and control. Like spores of a Cordyceps mushroom, they invade your neural system, changing the way you think, and using you to propagate itself throughout the network of other-people's-brains. 

You can't smell these VOCs; in fact, even the digital social networks themselves can't seem to detect them very well. We need a better detector for violating organic content (and a better immune system for our collective brain, perhaps some memetic inoculations?). 

Apple threatened Facebook ban over slavery posts on Instagram
Sep 2021, BBC News

Apple threatened to remove Facebook's products from its App Store, after the BBC found domestic "slaves" for sale on apps, including Instagram, in 2019.

"We removed 700 Instagram accounts within 24 hours, and simultaneously blocked several violating hashtags."

It added that it had also developed technology that can proactively find and take action on content related to domestic servitude - enabling it to "remove over 4,000 pieces of violating organic content in Arabic and English from January 2020 to date".

Image credit: That's not a VOC-detector, it's a radiation detector, used by NASA JPL for Mars research.

Partially Related Post Script:
Why cannabis smells skunky
Dec 2021, phys.org

Now, researchers reporting in ACS Omega have discovered a new family of prenylated volatile sulfur compounds (VSCs) that give cannabis its characteristic skunky aroma. 

Prior studies have focused mainly on terpenoids—molecules that range in odor from fuel-like to woody, citrusy or floral.

However, although terpenoids are the most abundant aroma compounds in cannabis, there is little evidence that they provide the underlying skunk-like smell of many cultivars. Skunks use several VSCs in their smelly defense sprays, so Iain Oswald and colleagues suspected that there could be similar molecules in cannabis.

One compound in particular, 3-methyl-2-butene-1-thiol, referred to as VSC3, was the most abundant VSC in the cultivars that the panel reported to be most pungent. This compound has previously been implicated in the flavor and aroma of "skunked beer"—beer that goes bad after being exposed to UV light.

via American Chemical Society: Iain W. H. Oswald et al, Identification of a New Family of Prenylated Volatile Sulfur Compounds in Cannabis Revealed by Comprehensive Two-Dimensional Gas Chromatography, ACS Omega (2021). DOI: 10.1021/acsomega.1c04196


Monday, November 29, 2021

Signal to Noise for the Win


A new model for how the brain perceives unique odors
Oct 2021, phys.org

So here is a scientist, a physicist by name, with an interest in the information-processing abilities of biological, and neurological systems. It didn't take him long, I would imagine, to realize that olfaction is a prime model for complex information-processing systems; it was the first sense, used by the first bacteria to detect chemicals in the primordial soup, later used by animals to make a big, complex mammal brain. If you want to look at how information processing happens in biological systems, this would be the ideal place to look.

But first, you have to throw into the garbage everything you know about olfaction already, which should be easy for a computational information scientist. What they did here was to look far out, all the way out -- beyond molecules and their myriad physico-chemical characteristics, of which the molecules themselves number in the billions; beyond genetics and their 30% variation across the global population; beyond cultural effects that are almost too surreal to quantify for methodical research purposes, like where Americans prefer peppermint since it's associated with candy, yet older folks from England don't like mint since it's associated with pain-relief products of their era, or the easier comparison of preference for durian fruit or Époisses de Bourgogne cheese.

Too messy, said the computational information scientist. And so they put it all in the blender, all those variables together. And they called it noise. Boil it all down, cancel it all out, all that dirty data of molecules and genes and cultural and personal association. Throw it all in the same bin, and call it noise. That's what they did.

Actually, they didn't call it noise, they called it "context" --

 "If you experience odors in a similar context, even if they were initially rather different in the responses they evoked in the nose, they begin to be represented by similar neural responses so they become the same in your head," Balasubramanian says.

The researchers found that their simplified model could be used to reproduce the same types of results seen in olfaction experiments. It's something that Balasubramanian did not expect to see, as he thought that such a complex process would require "learning and plasticity" in order to adapt and change neural synapses to modify the brain's representation of smells. "We may have found a general strategy of using certain kinds of randomized signals to entrain those effects," he says about their results. "It doesn't have to be just olfaction; it can be elsewhere, too." -medicalexpress

Did you see that? "It doesn't have to be olfaction; it can be elsewhere too." Olfactively-piqued, computational information neuroscientist, where have you been? Proving that the nose-brain is the neural model par excellence, while showing us how it actually works, both at the same time.

*If you want to know more about why olfaction is the ideal model for growing an artificial brain from scratch, it's a constant theme in Hidden Scents.

via University of Pennsylvania: Gaia Tavoni et al, Cortical feedback and gating in odor discrimination and generalization, PLOS Computational Biology (2021). DOI: 10.1371/journal.pcbi.1009479

Post Script:
This study shouldn't be mentioned without this other study, where they taught an artificial network how to smell, via Massachusetts Institute of Technology's McGovern Institute for Brain Research: Peter Y. Wang et al, Evolving the olfactory system with machine learning, Neuron (2021). DOI: 10.1016/j.neuron.2021.09.010. http://dx.doi.org/10.1016/j.neuron.2021.09.010

Post Post Script:
Might as well put this here, since it has to go somewhere -- what happens when you take an information scientist and give them an olfactory science problem? This is what happens. They come up with an answer that is so simple it just makes you look stupid. This is an example, although not a true example, of the other half of the coming dark ages. After a global pandemic, it's inevitable to experience a kind of dark ages, where lots of people died, but way more people got sick, and also a lot of people retired. That's a post-pandemic-pandemic of institutional knowledge loss, like a collective long covid brain fog on our culture -- we forget how to do stuff, because the guy who did it for the past 30 years isn't doing it anymore. That guy either died, got too sick to work, or retired for a million other reasons, of which many of them could be pandemic-related. And there's lots of those guys (and even more of them gals). Who knows what that will look like for us today or tomorrow, but it's happening as we speak, and years from now we might notice, we might even call it the great forgetting. The flip side to the dark ages is the renaissance, which comes from all the new people in new roles and at new jobs. These people are coming in new, with nobody around to teach them how to do things "right," and although that makes for a bumpy road ahead, it also gets you things like this discovery, one of the hardest problems of olfaction taken on by someone who has not much at all to do with olfaction (although he should, because olfaction has been an information science problem all along).

Wednesday, November 24, 2021

Olfaction In Silico


Artificial networks learn to smell like the brain
Nov 2021, phys.org

No kidding, the sensory apparatus that resembles a deep learning neural network can be simulated with a deep learning neural network -- "Artificial networks trained to classify odor identity recapitulate the connectivity inherent in the olfactory system."

The part of our brain that smells is also the most primitive. Before brains were a thing, bacteria performed chemosensory calculations on the primordial soup. As the soup became more complex, so did sensory equipment. Chemosensitive receptors on the surface of a bacterium became antennae, and then became noses, and those noses became seeing, hearing, even speaking brains. But the first version is the one used for smelling. So it shouldn't be a surprise that the first place we see a direct link between the mammalian brain and our artificial instantiation is via olfaction. Nonetheless, the scientists were "surprised to see it replicate biology's strategy so faithfully."

"By showing that we can match the architecture very precisely, I think that gives more confidence that these neural networks can continue to be useful tools for modeling the brain," says Robert Yang, assistant professor in MIT's departments of Brain and Cognitive Sciences and Electrical Engineering and Computer Science [and who collaborated on this project with Columbia neuroscientists Richard Axel and Larry Abbott, btw].

They use an antennae model, and the indispensable fruit fly, but it's all close enough to humans, I mean that's why we use the fruit fly in the first place. They started with some artificial neurons, of the same amount found in a fruit fly. They programmed the neurons to identify odors, and to assign valence (pleasant or unpleasant) to odors. They didn't give the neurons any structure, no information about how to talk to each other, no blueprint on how to process information. Just pre-programmed neurons, thrown into a simulated universe of chemosensation.

In minutes, and in silico, a network emerged to look just like the nose-brain of a fruit fly. All on its own, "an initially homogeneous population of neurons segregated into two populations with distinct input and output connections, resembling learned and innate pathways." 

In other words, it learned how to smell. It took evolution some billions of years to get the fruit fly olfactory system just right. The artificial network did it in minutes. Extrapolations from the study abstract: "This implies that convergent evolution reflects an underlying logic rather than shared developmental principles."


*Their structure used expansion and compression layers, similar to the pyramidal-structure of the nose-brain, and the number of inter-connections was also the exact same number as in the fruit fly, and it worked with both feedforward and recurrent network models, and the networks are plastic, meaning they can learn new odor associations over time.  

via Massachusetts Institute of Technology's McGovern Institute for Brain Research: Peter Y. Wang et al, Evolving the olfactory system with machine learning, Neuron (2021). DOI: 10.1016/j.neuron.2021.09.010

Post Script:
The book Hidden Scents talks about how olfaction is an ideal model for understanding an artificial brain, for an artificial human. 

Although artificial neural networks resemble natural neural activity patterns, like those used by the visual cortex for object recognition, we still don't understand how the visual cortex, or most mammalian neural circuits, are inter-connected. This time, we see how they connect, a connectome of the olfactory cortex.

Post Post Script:
And this study should be kept alongside this other one, where a physics-based computational neuroscientist came up with a pretty simple way to mimic the olfactory cortex, via University of Pennsylvania: Gaia Tavoni et al, Cortical feedback and gating in odor discrimination and generalization, PLOS Computational Biology (2021). DOI: 10.1371/journal.pcbi.1009479