Smoker or Non-Smoker? Donor Characteristics from Saliva

Smoker or Non-Smoker? Donor Characteristics from Saliva

The discovery of body fluids during forensic investigation can provide countless clues to a crime. Saliva is often countered during certain investigations, particularly in the investigation of sexual assaults and other violent crimes. The wealth of chemical information housed in the complex matrix could provide clues as to who might have left the substance behind. One example of this is whether or not the donor is a smoker.

A team of researchers at the University at Albany have hit the news multiple times in recent years with their rapid, on-site tools for body fluid analysis. Using Raman spectroscopy, the group have successfully developed methods to identify body fluids, estimate body fluid age, and determine characteristics of the donor, such as race and sex. In the latest paper by Igor Lednev and his colleagues, published in Journal of Biophotonics, Raman spectroscopy has been shown to differentiate between smokers and non-smokers.

Working in collaboration with researchers at Kuwait University, the team applied Raman spectroscopy to dried saliva from smokers and non-smokers, aiming to use chemical differences in the samples to determine whether or not the donor smokes. Raman spectroscopy is a non-destructive technique that enables the rapid, on-site analysis of samples, producing distinctive chemical fingerprints consisting of bands produced by the interaction of light with molecular structures.

One might assume the test would target nicotine, a major chemical component in tobacco. However, nicotine is relatively short-lived in the body, thus is not a suitable target for analytical tests. Instead, the researchers focused on cotinine, a primary metabolite of nicotine with a notably longer half-life. Saliva samples from 32 donors were analysed by Raman spectroscopy and the chemical profiles produced studied for differences. Researchers soon encountered a problem. Raman bands indicative of cotinine overlapped with typical Raman bands produced by saliva, making the detection of cotinine in saliva challenging. The team used machine learning to solve this problem.

First, they identified eight spectral regions that contributed the most variation between the saliva of smokers and non-smokers. Using an artificial neural network, a classification model was constructed for the prediction of smoking habits of a donor. By inputting chemical data from known samples, the network is able to learn from the data in order to predict an output (in this case, whether or not the donor of a saliva sample was a smoker). In laboratory-based studies, the model constructed achieved an impressive accuracy of 100%.

Although this pilot study was based on a very limited sample size, the technique shows great promise in the determination of donor characteristics from dried body fluids.

 

Al-Hetlani et al. Differentiating smokers and nonsmokers based on Raman spectroscopy of oral fluid and advanced statistics for forensic applications. Journal of Biophotonics, 2019, DOI: 10.1002/jbio.201960123  https://onlinelibrary.wiley.com/doi/abs/10.1002/jbio.201960123

Sweat Security: Using Skin Secretions for Authentication

Sweat Security: Using Skin Secretions for Authentication

The use of passwords and pin numbers is part of our daily lives, being a necessity in ensuring our data and money doesn’t fall into the wrong hands. However passwords and pattern-based pins have their obvious limitations, and they are only as secure as the user is cautious.  One method of improving security utilises biometric technology, which is based on the biological or behavioural characteristics of an individual. Biometric-based security systems are certainly nothing new. The concept of using fingerprints, retinal scans and voice recognition as security measures materialised decades ago, and such techniques are frequently used for authentication purposes. Despite these technological developments, ongoing research is attempting to develop more robust and secure methods of identification.

Researchers at the University of Albany are developing a unique new technique of biometric identification using only a person’s sweat. Human sweat, and all body fluids for that matter, contains a plethora of chemical compounds, ranging from small weight molecules to large proteins. These compounds originate from a variety of sources, with some resulting from endogenous metabolic processes within the body, and others being introduced through diet and environmental exposure. Metabolite levels can be affected by an endless array of factors, including sex, ethnicity, age and lifestyle. Interestingly, it is now known that the presence and amount of some of these compounds can vary greatly between different people, thus in theory unique metabolome profiles could be harnessed for identification purposes.

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The compounds the technique will focus on is vital, as certain chemical levels can fluctuate wildly throughout the day depending on what we have eaten, for instance. However levels of certain chemicals have been found to be relatively stable or at least only vary gradually. In this research, Assistant Professor Jan Halámek and his team focused on using amino acid profiles of sweat to offer a unique means of authentication.

By first establishing which amino acids are present in a person’s skin secretions, a wearable device can then be constructed which will monitor the levels of these compounds. The device would initially require a kind of enrolment period, during which time the user’s skin secretions would be constantly measured in order to develop a unique profile of metabolites. It is already known that the metabolites released by the body vary throughout the day, so such a monitoring period would be necessary to take into account these changes.

Over time a profile of the user’s skin secretions would be built up and stored within the device, acting as a kind of standard for comparison. When future skin secretions are analysed by the device, the profiles will be compared with the known user profile and used to confirm the identity of the user. In the event of anyone else picking up the device, the instrument would detect a different skin secretion profile and lock the device or turn it off, thus ensuring security of the smartphone or computer.

If successful, the technology could offer an improved active authentication system, either as a standalone system or supplementing existing technology. However the technique is very much in its infancy and a great deal more research will be required before this kind of technology is rolled out commercially, if it ever is possible. It is likely that such a technique will be affected by contamination, for instance as the user’s hands become dirty throughout the day or if cleaning or cosmetic products are applied to the skin. Furthermore, if authentication is based on comparison with an electronically stored profile, the device may still be susceptible to hacking in order to bypass the security system. But if this technique could reach a sufficient level of robustness, the days of struggling to remember your password could be eliminated.

 

Agudelo, J. Privman, V. Halamek, J. Promises and Challenges in Continuous Tracking Utilizing Amino Acids in Skin Secretions for Active Multi-Factor Biometric Authentication for Cybersecurity. ChemPhysChem. 18, 1714-1720 (2017).