Hide table of contents

The nose knows:

A short review of scent based e-nose biosensors


 

Sniffer working dogs have been used for drug, explosive and dangerous substance detection in locations such as stowage, storage, airports, transport hubs and more. 

More recent observation also shows superb scent-based detection of certain cancers (prostate, bowel), diseases (Parkinson’s, Covid) and even community detection (UTIs, Pseudomonas in care homes or hospitals). 

Trials with efficient specificity and sensitivity have replicated the training process and found hopeful results, but it is still a small scale operation, rather than a commercial solution.

Scientists are hoping to replicate, iterate and improve on biological systems that allow dogs to understand, 

interpret and distinguish these scent-based molecules for detection of diseases, substances and more, to allow for earlier, quicker and more foolproof detection of health conditions, hazards and contraband.

Dogs are very loyal, hard working, and seem to enjoy working with human companions, including as personal assistance dogs, but the high training costs, relatively limited working lifespan, health and emotional costs, and ethics, means a potential transition to E-nose scent based biosensors in dangerous, busy or simply frequent areas, allows for better ease of use and cost effectiveness.

 

 


 

SCIENCE OF A DOG’S SMELL:

Dogs have a long nasal canal full of turbinates which are folds and corridors to allow smells to be filtered to ‘stereo’, so they can determine relative spatial positions of scent sources, and can also smell with each nostril independently. This allows for better navigation to locate scents, and allows them to find the edge of an odour plume to find the strongest source, allowing for more accurate location of a desired scent. They also have 300 million scent receptors (60 times more than humans!) and an olfactory bulb right above the nose which sends smell information to the brain. Dogs greatly outperform humans or other closely related species in terms of distance and accuracy to tracking scents. 

Work to utilise the dog’s sense of smell has also shifted to biological devices, with a MIT team working on developing biosensors that detect scent and utilise some of the anatomical, mechanical and adapted assets that dogs have, to better improve our ability to detect scent from diseases to substances.

In a team lead by Andreas Mershin, and collaborating with many organisations such as Medical Detection Dogs and Prostate Cancer UK, the initial designs for dog based E-noses showed promise.

To imitate the movement of nostrils, a pump was used to bring scent molecules close to reactive surfaces that then sent signals to an interpretive computer.

Raw data with machine learning algorithms allowed them to refine the different signals to names and concentrations of compounds, such as indicators of cancer, Covid, drugs, bombs and more.

Electronic noses can interpret biological and chemical information with more sensitive equipment, but dogs are (for now) still outperforming them, not due to innate sensitivity to gather scent data, but their ability to interpret and build up a picture of scent indicators.

Outside of controlled labs, the extra background scents (such as body odour, perfumes, clothes, dyes) makes it harder to distinguish the target scent, and for now, E-noses are still less accurate than a trained sniffer dog in real world applications. 

 

AIR MOVEMENT MECHANISMS:

Dogs do not just passively inhale to collect scent particles, but rather intentionally breathe in and out rapidly around 5 times a second when they intentionally sniff a substance. The pulsating motion creates turbulent air jets during the exhale which pushes air backwards and therefore pulls air in from far away towards itself. This allows the dogs to sample a large region effectively and quickly.

Breeds of dogs don’t seem to show different patterns or frequencies of inhales and exhales (though breeds do show behavioural, health and anatomical differences which are considered when working with a live dog).

The bellow effect allows for a much more efficient volume of air to pass through the dog’s nose, and a mechanistic model utilising the dog’s method outperformed typical vapour sample detectors by a factor of 16 to 18!

Schlieren imaging can be used to visualise the movement of air molecules, to compare the reach and volume of air movement by different scent-sampling systems.

 

FUTURE HOPES:

Many organisations and scientific research teams are continuing the work on utilising the power of dogs to improve scent based sampling and analysis. Capturing real time data, monitoring pollution or chemical leaks, detecting hazardous substances, diagnosing disease before clinical signs, and non invasively screening for new pathogens can create a hope for the future applications beyond the lab for these devices. However, some controversies still remain.

 

ETHICS AND LIMITATIONS:

Unlike sniffer dogs, E-noses could be (if developed enough) a far superior commercial alternative, due to their more reliable schedule, easier transport, lower up front training (compared to dog and handler), lower costs, and reduction of animal welfare and wellbeing issues. However, they can bring their own ethical and moral questions. 

Teams are considering incorporating scent-based passive detection to public areas or devices. For example, installing these sensors into smartphones. 

What issues may arise from passively deciphering unique and personal biological information, such as if those you come in contact with are fertile, if they are ill, or if they smoke, could bring are still to appear. But when the time comes that we can create this- should we?

 

Scent based data is usually involuntary and personal, and can provide information on mood, anxiety, affection, health and more. Unlike surveillance through actions, words, cameras or audio, the scent we give off to the world is typically outside our control, and can be used for identification far wider than just hazardous substances or life threatening diseases.

 

The future of scent-based sensors in our smartphones is not yet a reality, but it is also getting closer. The benefits and costs of these sensors can be great, and so we must ensure we continue discussing how to safely, fairly and accessibly develop and utilise these technologies.

 

For now, I can’t wait to see the day that invasive biopsies can be replaced with a sniff from a dog or an external scent sample, especially if it can detect diseases earlier to allow for better treatment and health outcomes. But I also stay wary of the potential misuses of such a technology, and will be following it closely, and hoping that discussions of the role scientific developments should play in our society remain open to many perspectives to create a better future for all.

 

I wrote a short paper on Enoses and scent based biosensors including the ethics of passive scent surveillance.

https://drive.google.com/file/d/1GZrlgUmFhabjcSHWZ7rXBuyZEVe_ieoA/view?usp=sharing

https://linktr.ee/sofiiaf

Comments1


Sorted by Click to highlight new comments since:
[comment deleted]0
0
0
Curated and popular this week
Sam Anschell
 ·  · 6m read
 · 
*Disclaimer* I am writing this post in a personal capacity; the opinions I express are my own and do not represent my employer. I think that more people and orgs (especially nonprofits) should consider negotiating the cost of sizable expenses. In my experience, there is usually nothing to lose by respectfully asking to pay less, and doing so can sometimes save thousands or tens of thousands of dollars per hour. This is because negotiating doesn’t take very much time[1], savings can persist across multiple years, and counterparties can be surprisingly generous with discounts. Here are a few examples of expenses that may be negotiable: For organizations * Software or news subscriptions * Of 35 corporate software and news providers I’ve negotiated with, 30 have been willing to provide discounts. These discounts range from 10% to 80%, with an average of around 40%. * Leases * A friend was able to negotiate a 22% reduction in the price per square foot on a corporate lease and secured a couple months of free rent. This led to >$480,000 in savings for their nonprofit. Other negotiable parameters include: * Square footage counted towards rent costs * Lease length * A tenant improvement allowance * Certain physical goods (e.g., smart TVs) * Buying in bulk can be a great lever for negotiating smaller items like covid tests, and can reduce costs by 50% or more. * Event/retreat venues (both venue price and smaller items like food and AV) * Hotel blocks * A quick email with the rates of comparable but more affordable hotel blocks can often save ~10%. * Professional service contracts with large for-profit firms (e.g., IT contracts, office internet coverage) * Insurance premiums (though I am less confident that this is negotiable) For many products and services, a nonprofit can qualify for a discount simply by providing their IRS determination letter or getting verified on platforms like TechSoup. In my experience, most vendors and companies
 ·  · 4m read
 · 
Forethought[1] is a new AI macrostrategy research group cofounded by Max Dalton, Will MacAskill, Tom Davidson, and Amrit Sidhu-Brar. We are trying to figure out how to navigate the (potentially rapid) transition to a world with superintelligent AI systems. We aim to tackle the most important questions we can find, unrestricted by the current Overton window. More details on our website. Why we exist We think that AGI might come soon (say, modal timelines to mostly-automated AI R&D in the next 2-8 years), and might significantly accelerate technological progress, leading to many different challenges. We don’t yet have a good understanding of what this change might look like or how to navigate it. Society is not prepared. Moreover, we want the world to not just avoid catastrophe: we want to reach a really great future. We think about what this might be like (incorporating moral uncertainty), and what we can do, now, to build towards a good future. Like all projects, this started out with a plethora of Google docs. We ran a series of seminars to explore the ideas further, and that cascaded into an organization. This area of work feels to us like the early days of EA: we’re exploring unusual, neglected ideas, and finding research progress surprisingly tractable. And while we start out with (literally) galaxy-brained schemes, they often ground out into fairly specific and concrete ideas about what should happen next. Of course, we’re bringing principles like scope sensitivity, impartiality, etc to our thinking, and we think that these issues urgently need more morally dedicated and thoughtful people working on them. Research Research agendas We are currently pursuing the following perspectives: * Preparing for the intelligence explosion: If AI drives explosive growth there will be an enormous number of challenges we have to face. In addition to misalignment risk and biorisk, this potentially includes: how to govern the development of new weapons of mass destr
Dr Kassim
 ·  · 4m read
 · 
Hey everyone, I’ve been going through the EA Introductory Program, and I have to admit some of these ideas make sense, but others leave me with more questions than answers. I’m trying to wrap my head around certain core EA principles, and the more I think about them, the more I wonder: Am I misunderstanding, or are there blind spots in EA’s approach? I’d really love to hear what others think. Maybe you can help me clarify some of my doubts. Or maybe you share the same reservations? Let’s talk. Cause Prioritization. Does It Ignore Political and Social Reality? EA focuses on doing the most good per dollar, which makes sense in theory. But does it hold up when you apply it to real world contexts especially in countries like Uganda? Take malaria prevention. It’s a top EA cause because it’s highly cost effective $5,000 can save a life through bed nets (GiveWell, 2023). But what happens when government corruption or instability disrupts these programs? The Global Fund scandal in Uganda saw $1.6 million in malaria aid mismanaged (Global Fund Audit Report, 2016). If money isn’t reaching the people it’s meant to help, is it really the best use of resources? And what about leadership changes? Policies shift unpredictably here. A national animal welfare initiative I supported lost momentum when political priorities changed. How does EA factor in these uncertainties when prioritizing causes? It feels like EA assumes a stable world where money always achieves the intended impact. But what if that’s not the world we live in? Long termism. A Luxury When the Present Is in Crisis? I get why long termists argue that future people matter. But should we really prioritize them over people suffering today? Long termism tells us that existential risks like AI could wipe out trillions of future lives. But in Uganda, we’re losing lives now—1,500+ die from rabies annually (WHO, 2021), and 41% of children suffer from stunting due to malnutrition (UNICEF, 2022). These are preventable d