Performance Evaluation of a Salivary Amylase Biosensor for Stress Assessment in Military Field Research

Fluorometric biosensing of α-amylase using an artificial allosteric biosensor immobilized on nanostructured interface

Protein biosensors hold a promise to transform the way we collect physiological data by enabling quantification of biomarkers outside of specialized laboratory environment. However, achieving high specificity and sensitivity in homogeneous assay format remains challenging. Here we report construction of fluorescent biosensor arrays based on artificial allosteric α-amylase-activated PQQ-dependent glucose dehydrogenase (Amy-GDH). Amy-GDH was covalently immobilized on silica nanoparticles that were then arrayed on fiberglass sheets. The activity of the biosensor was monitored using a smartphone camera via emergence of bright fluorescence (λ_ex 365 nm) originating from reduced phenazine methosulfate upon glucose oxidation by Amy-GDH. We show that such biosensor arrays demonstrate an apparent K_d of 115 pM for α-amylase with a detection limit of 2 pM. Using the developed biosensor arrays, we were able to specifically and accurately quantify the concentration of α-amylase in biological fluids such as serum and saliva. We propose that the presented approach can enable construction of ultrasensitive point-of-care diagnostic arrays.

EEG Mental Stress Assessment Using Hybrid Multi-Domain Feature Sets of Functional Connectivity Network and Time-Frequency Features

Exposure to mental stress for long period leads to serious accidents and health problems. To avoid negative consequences on health and safety, it is very important to detect mental stress at its early stages, i.e., when it is still limited to acute or episodic stress. In this study, we developed an experimental protocol to induce two different levels of stress by utilizing a mental arithmetic task with time pressure and negative feedback as the stressors. We assessed the levels of stress on 22 healthy subjects using frontal electroencephalogram (EEG) signals, salivary alpha-amylase level (AAL), and multiple machine learning (ML) classifiers. The EEG signals were analyzed using a fusion of functional connectivity networks estimated by the Phase Locking Value (PLV) and temporal and spectral domain features. A total of 210 different features were extracted from all domains. Only the optimum multi-domain features were used for classification. We then quantified stress levels using statistical analysis and seven ML classifiers. Our result showed that the AAL level was significantly increased (p < 0.01) under stress condition in all subjects. Likewise, the functional connectivity network demonstrated a significant decrease under stress, p < 0.05. Moreover, we achieved the highest stress classification accuracy of 93.2% using the Support Vector Machine (SVM) classifier. Other classifiers produced relatively similar results.

The calming effect of roasted coffee aroma in patients undergoing dental procedures

Coffee beverage consumption is well-known to exert various health benefits; however, the effects of coffee aroma are rarely explored. This study aimed to investigate the calming effect of inhaling coffee aroma while the patients underwent dental procedures (probing and scaling). Salivary α-amylase (sAA) and cortisol (sCort) levels were measured as proxies of sympathetic nervous system and hypothalamic–pituitary–adrenal axis responses to stress respectively. Blood pressures and pulse rates were recorded. The results showed that undergoing dental procedures could increase sAA and sCort levels of the patients inhaling sham aroma while those inhaling coffee aroma had significantly decreased sAA and sCort levels (40% and 25% differences, respectively). The pulse rates of those inhaling coffee aroma were also lower. Subjective assessment using visual analog scale was in line with objective measures as well. The preference for coffee aroma or the frequency of coffee drinking had no effect on the sAA and sCort responses. This is the first study to provide evidence on the effect of coffee aroma on sAA and sCort levels in patients undergoing dental procedures.

Portable Biosensors for Psychophysiological Stress Monitoring of a Helicopter Crew

This study aims to analyze the psychophysiological stress response of a helicopter crew using portable biosensors, and to analyze the psychophysiological stress response differences of experienced and non-experienced crew members. We analyzed 27 participants (33.89 ± 5.93 years) divided into two different flight maneuvers: a crane rescue maneuver: 15 participants (three control and 12 military) and a low-altitude maneuver: 12 participants (five control and seven military). Anxiety, rating of perceived exertion, subjective perception of stress, heart rate, blood oxygen saturation, skin temperature, blood lactate, cortical arousal, autonomic modulation, leg and hand strength, leg flexibility, spirometry, urine, and short-term memory were analyzed before and after both helicopter flight maneuvers. The maneuvers produced a significant increase in stress and effort perception, state of anxiety, and sympathetic modulation, as well as a significant decrease in heart rate, blood oxygen saturation, leg and inspiratory muscle strength, and urine proteins. The use of biosensors showed how a crane rescue and low-altitude helicopter maneuvers produced an anticipatory anxiety response, showing an increased sympathetic autonomic modulation prior to the maneuvers, which was maintained during the maneuvers in both experienced and non-experienced participants. The crane rescue maneuver produced a higher maximal heart rate and decreased pulmonary capacity and strength than the low-altitude maneuver. The psychophysiological stress response was higher in the experienced than in non-experienced participants, but both presented an anticipatory stress response before the maneuver.

Factors affecting salivary α-amylase levels measured with a handheld biosensor and a standard laboratory assay

OBJECTIVES

A handheld biosensor for measuring salivary α-amylase (sAA) was developed for convenient on-site measurement. Previous studies reported some discrepancies in sAA levels measured with a biosensor and a standard assay. This study aimed to compare sAA levels measured with three different methods and the factors affecting its levels.

METHODS

Thirty-eight participants collected saliva two times for three measurements. First, the collector strip was placed under the tongue for 2 minutes, then the strip was used to measure sAA level on-site immediately (intraoral biosensor; method 1). Then, a participant pooled the saliva for 4 minutes and collected the saliva into the tube which was aliquoted to measure in a laboratory with a handheld biosensor (extraoral biosensor; method 2) and with a standard enzyme kinetic assay (EKA; method 3). Additional experiments were carried out to compare the levels of sAA measured with differences in pooling time and positioning of the collector strip.

RESULTS

A high correlation of sAA levels between an extraoral and an EKA measurement (r = 0.989) was observed, while sAA levels measured with an intraoral method showed a significant but weaker correlation with either an EKA (r = 0.475) or an extraoral method (r = 0.436). Saliva pooling time and positioning of the collector strip significantly affected sAA levels.

CONCLUSIONS

A handheld biosensor is valid to measure sAA levels extraorally. For an intraoral measurement, pooling time and positioning of the collector strip need to be taken into account.

Evaluation of an Integrated System of Wearable Physiological Sensors for Stress Monitoring in Working Environments by Using Biological Markers

OBJECTIVE

The objectives of this paper are to develop and test the ability of a wearable physiological sensors system, based on ECG, EDA, and EEG, to capture human stress and to assess whether the detected changes in physiological signals correlate with changes in salivary cortisol level, which is a reliable, objective biomarker of stress.

METHODS

15 healthy participants, eight males and seven females, mean age 40.8 ± 9.5 years, wore a set of three commercial sensors to record physiological signals during the Maastricht Acute Stress Test, an experimental protocol known to elicit robust physical and mental stress in humans. Salivary samples were collected throughout the different phases of the test. Statistical analysis was performed using a support vector machine (SVM) classification algorithm. A correlation analysis between extracted physiological features and salivary cortisol levels was also performed.

RESULTS

15 features extracted from heart rate variability, electrodermal, and electroencephalography signals showed a high degree of significance in disentangling stress from a relaxed state. The classification algorithm, based on significant features, provided satisfactory outcomes with 86% accuracy. Furthermore, correlation analysis showed that the observed changes in physiological features were consistent with the trend of salivary cortisol levels (R² = 0.714).

CONCLUSION

The tested set of wearable sensors was able to successfully capture human stress and quantify stress level.

SIGNIFICANCE

The results of this pilot study may be useful in designing portable and remote control systems, such as medical devices used to turn on interventions and prevent stress consequences.