Correlations of Salivary and Blood Glucose Levels among Six Saliva Collection Methods

Recent advancements in non-invasive wearable electrochemical biosensors for biomarker analysis - A review

A biomarker is a molecular indicator that can be used to identify the presence or severity of a disease. It may be produced due to biochemical or molecular changes in normal biological processes. In some cases, the presence of a biomarker itself is an indication of the disease, while in other cases, the elevated or depleted level of a particular protein or chemical substance aids in identifying a disease. Biomarkers indicate the progression of the disease in response to therapeutic interventions. Identifying these biomarkers can assist in diagnosing the disease early and providing proper therapeutic treatment. In recent years, wearable electrochemical (EC) biosensors have emerged as an important tool for early detection due to their excellent selectivity, low cost, ease of fabrication, and improved sensitivity. There are several challenges in developing a fully integrated wearable sensor, such as device miniaturization, high power consumption, incorporation of a power source, and maintaining the integrity and durability of the biomarker for long-term continuous monitoring. This review covers the recent advancements in the fabrication techniques involved in device development, the types of sensing platforms utilized, different materials used, challenges, and future developments in the field of wearable biosensors.

Recent Advances in Wearable Healthcare Devices: From Material to Application

In recent years, the proliferation of wearable healthcare devices has marked a revolutionary shift in the personal health monitoring and management paradigm. These devices, ranging from fitness trackers to advanced biosensors, have not only made healthcare more accessible, but have also transformed the way individuals engage with their health data. By continuously monitoring health signs, from physical-based to biochemical-based such as heart rate and blood glucose levels, wearable technology offers insights into human health, enabling a proactive rather than a reactive approach to healthcare. This shift towards personalized health monitoring empowers individuals with the knowledge and tools to make informed decisions about their lifestyle and medical care, potentially leading to the earlier detection of health issues and more tailored treatment plans. This review presents the fabrication methods of flexible wearable healthcare devices and their applications in medical care. The potential challenges and future prospectives are also discussed.

Extensive comparison of salivary collection, transportation, preparation, and storage methods: a systematic review

BACKGROUND

Human saliva as a bodily fluid-similar to blood-is utilized for diagnostic purposes. Unlike blood sampling, collecting saliva is non-invasive, inexpensive, and readily accessible. There are no previously published systematic reviews regarding different collection, transportation, preparation, and storage methods for human saliva.

DESIGN

This study has been prepared and organized according to the preferred reporting items for systematic reviews and meta-analyses (PRISMA) 2020 guidelines. This systematic review has been registered at PROSPERO (Registration ID: CRD42023415384). The study question according to the PICO format was as followed: Comparison of the performance (C) of different saliva sampling, handling, transportation, and storage techniques and methods (I) assessed for analyzing stimulated or unstimulated human saliva (P and O). An electronic search was executed in Scopus, Google Scholar, and PubMed.

RESULTS

Twenty-three descriptive human clinical studies published between 1995 and 2022 were included. Eight categories of salivary features and biomarkers were investigated (i.e., salivary flow rate, total saliva quantity, total protein, cortisol, testosterone, DNA quality and quantity, pH and buffering pH). Twenty-two saliva sampling methods/devices were utilized. Passive drooling, Salivette®, and spitting were the most utilized methods. Sampling times with optimum capabilities for cortisol, iodine, and oral cancer metabolites are suggested to be 7:30 AM to 9:00 AM, 10:30 AM to 11:00 AM, and 14:00 PM to 20:00 PM, respectively. There were 6 storage methods. Centrifuging samples and storing them at -70 °C to -80 °C was the most utilized storage method. For DNA quantity and quality, analyzing samples immediately after collection without centrifuging or storage, outperformed centrifuging samples and storing them at -70 °C to -80 °C. Non-coated Salivette® was the most successful method/device for analyzing salivary flow rate.

CONCLUSION

It is highly suggested that scientists take aid from the reported categorized outcomes, and design their study questions based on the current voids for each method/device.

The Application of Fluorescence Anisotropy for Viscosity Measurements of Small Volume Biological Analytes

Time-resolved fluorescence anisotropy has been extensively used to detect changes in bimolecular rotation associated with viscosity levels within cells and other solutions. Physiological alterations of the viscosity of biological fluids have been associated with numerous pathological causes. This current work serves as proof of concept for a method to measure viscosity changes in small analyte volumes representative of biological fluids. The fluorophores used in this study were fluorescein disodium salt and Enhanced Green Fluorescent Protein (EGFP). To assess the ability of the method to accurately detect viscosity values in small volume samples, we conducted measurements with 12 μL and 100 μL samples. No statistically significant changes in determined viscosities were recorded as a function of sample volume for either fluorescent probe. The anisotropy of both fluorescence probes was measured in low viscosity standards ranging from 1.02 to 1.31 cP, representative of physiological fluid values, and showed increasing rotational correlation times in response to increasing viscosity. We also showed that smaller fluid volumes can be diluted to accommodate available cuvette volume requirements without a loss in the accuracy of detecting discrete viscosity variations. Moreover, the ability of this technique to detect subtle viscosity changes in complex fluids similar to physiological ones was assessed by using fetal bovine serum (FBS) containing samples. The presence of FBS in the analytes did not alter the viscosity specific rotational correlation time of EGFP, indicating that this probe does not interact with the tested analyte components and is able to accurately reflect sample viscosity. We also showed that freeze-thaw cycles, reflective of the temperature-dependent processes that biological samples of interest could undergo from the time of collection to analyses, did not impact the viscosity measurements' accuracy. Overall, our data highlight the feasibility of using time-resolved fluorescence anisotropy for precise viscosity measurements in biological samples. This finding is relevant as it could potentially expand the use of this technique for in vitro diagnostic systems.

A Narrative Review on Strategies for the Reversion of Prediabetes to Normoglycemia: Food Pyramid, Physical Activity, and Self-Monitoring Innovative Glucose Devices

In 2019, "Nutrition Therapy for Adults with Diabetes or Prediabetes: A Consensus Report" was published. This consensus report, however, did not provide an easy way to illustrate to subjects with prediabetes (SwPs) how to follow a correct dietary approach. The purpose of this review is to evaluate current evidence on optimum dietary treatment of SwPs and to provide a food pyramid for this population. The pyramid built shows that everyday consumption should consist of: whole-grain bread or potatoes eaten with their skins (for fiber and magnesium) and low glycemic index carbohydrates (GI < 55%) (three portions); fruit and vegetables (5 portions), in particular, green leafy vegetables (for fiber, magnesium, and polyphenols); EVO oil (almost 8 g); nuts (30 g, in particular, pistachios and almonds); three portions of dairy products (milk/yogurt: 300-400 g/day); mineral water (almost 1, 5 L/day for calcium intake); one glass of wine (125 mL); and three cups of coffee. Weekly portions should include fish (four portions), white meat (two portions), protein plant-based food (four portions), eggs (egg portions), and red/processed meats (once/week). At the top of the pyramid, there are two pennants: a green one means that SwPs need some personalized supplementation (if daily requirements cannot be satisfied through diet, vitamin D, omega-3, and vitamin B supplements), and a red one means there are some foods and factors that are banned (simple sugar, refined carbohydrates, and a sedentary lifestyle). Three to four times a week of aerobic and resistance exercises must be performed for 30-40 min. Finally, self-monitoring innovative salivary glucose devices could contribute to the reversion of prediabetes to normoglycemia.

Human Serum and Salivary Metabolomes: Diversity and Closeness

Saliva, which contains molecular information that may reflect an individual's health status, has become a valuable tool for discovering biomarkers of oral and general diseases. Due to the high vascularization of the salivary glands, there is a molecular exchange between blood and saliva. However, the composition of saliva is complex and influenced by multiple factors. This study aimed to investigate the possible relationships between the salivary and serum metabolomes to gain a comprehensive view of the metabolic phenotype under physiological conditions. Using 1H-NMR spectroscopy, we obtained the serum metabolite profiles of 20 healthy young individuals and compared them with the metabolomes of parotid, submandibular/sublingual, and whole-saliva samples collected concurrently from the same individuals using multivariate and univariate statistical analysis. Our results show that serum is more concentrated and less variable for most of the shared metabolites than the three saliva types. While we found moderate to strong correlations between serum and saliva concentrations of specific metabolites, saliva is not simply an ultrafiltrate of blood. The intense oral metabolism prevents very strong correlations between serum and salivary concentrations. This study contributes to a better understanding of salivary metabolic composition, which is crucial for utilizing saliva in laboratory diagnostics.

Review of Noninvasive Continuous Glucose Monitoring in Diabetics

For diabetics, taking regular blood glucose measurements is crucial. However, traditional blood glucose monitoring methods are invasive and unfriendly to diabetics. Recent studies have proposed a biofluid-based glucose sensing technique that creatively combines wearable devices with noninvasive glucose monitoring technology to enhance diabetes management. This is a revolutionary advance in the diagnosis and management of diabetes, reflects the thoughtful modernization of medicine, and promotes the development of digital medicine. This paper reviews the research progress of noninvasive continuous blood glucose monitoring (CGM), with a focus on the biological liquids that replace blood in monitoring systems, the technical principles of continuous noninvasive glucose detection, and the output and calibration of sensor signals. In addition, the existing limits of noninvasive CGM systems and prospects for the future are discussed. This work serves as a resource for further promoting the development of noninvasive CGM systems.

Monitoring saliva compositions for non-invasive detection of diabetes using a colorimetric-based multiple sensor

The increasing population of diabetic patients, especially in developing countries, has posed a serious risk to the health sector, so that the lack of timely diagnosis and treatment process of diabetes can lead to threatening complications for the human lifestyle. Here, a multiple sensor was fabricated on a paper substrate for rapid detection and controlling the progress of the diabetes disease. The proposed sensor utilized the sensing ability of porphyrazines, pH-sensitive dyes and silver nanoparticles in order to detect the differences in saliva composition of diabetic and non-diabetic patients. A unique color map (sensor response) was obtained for each studied group, which can be monitored by a scanner. Moreover, a good correlation was observed between the colorimetric response resulting from the analysis of salivary composition and the fasting blood glucose (FBG) value measured by standard laboratory instruments. It was also possible to classify participants into two groups, including patients caused by diabetes and those were non-diabetic persons with a total accuracy of 88.9%. Statistical evaluations show that the multiple sensor can be employed as an effective and non-invasive device for continuous monitoring of diabetes, substantially in the elderly.

Saliva sampling strategies affecting the salivary glucose measurement

Characterized by sustained elevated blood glucose levels, diabetes mellitus has become one of the largest global public health concerns by imposing a heavy global burden on socio-economic development. To date, regular blood glucose level check by performing a finger-prick test has been a routine strategy to monitor diabetes. However, the intrusive nature of finger blood prick tests makes it challenging for individuals to maintain consistent testing routines. Recently, salivary glucose measurement (SGM) has increasingly become a non-invasive alternative to traditional blood glucose testing for diabetes. Despite that, further research is needed to standardize the collection methods and address the issues of variability to ensure accurate and reliable SGM. To resolve possible remaining issues in SGM, we here thoroughly explored saliva sampling strategies that could impact the measurement results. Additionally, the effects of supplements taken, mouth washing, gum chewing, and smoking were collectively analyzed, followed by a continuous SGM over a long period, forming the stepping stone for the practical transitional development of SGM in non-invasive diabetes monitoring.

Saliva as Biomarker for Oral and Chronic Degenerative Non-Communicable Diseases

Saliva is a very complex fluid and it is essential to maintain several physiological processes and functions, including oral health, taste, digestion and immunological defenses. Saliva composition and the oral microbiome can be influenced by several factors, like diet and smoking habits, and their alteration can represent an important access point for pathogens and, thus, for systemic illness onset. In this review, we explore the potentiality of saliva as a new tool for the early detection of some pathological conditions, such as oral diseases, chronic degenerative non-communicable diseases, among these chronic kidney disease (CKD). We also examined the possible correlation between oral and systemic diseases and oral and gut microbiota dysbiosis. In particular, we deeply analyzed the relationship between oral diseases and CKD. In this context, some salivary parameters can represent a new device to detect either oral or systemic pathologies. Moreover, the positive modulation of oral and gut microbiota induced by prebiotics, postbiotics, or symbiotics could represent a new possible adjuvant therapy in the clinical management of oral diseases and CKD.

Insight into continuous glucose monitoring: from medical basics to commercialized devices

According to the latest statistics, more than 537 million people around the world struggle with diabetes and its adverse consequences. As well as acute risks of hypo- or hyper- glycemia, long-term vascular complications may occur, including coronary heart disease or stroke, as well as diabetic nephropathy leading to end-stage disease, neuropathy or retinopathy. Therefore, there is an urgent need to improve diabetes management to reduce the risk of complications but also to improve patient's quality life. The impact of continuous glucose monitoring (CGM) is well recognized, in this regard. The current review aims at introducing the basic principles of glucose sensing, including electrochemical and optical detection, summarizing CGM technology, its requirements, advantages, and disadvantages. The role of CGM systems in the clinical diagnostics/personal testing, difficulties in their utilization, and recommendations are also discussed. In the end, challenges and prospects in future CGM systems are discussed and non-invasive, wearable glucose biosensors are introduced. Though the scope of this review is CGMs and provides information about medical issues and analytical principles, consideration of broader use will be critical in future if the right systems are to be selected for effective diabetes management.

Promising applications of human-derived saliva biomarker testing in clinical diagnostics

Saliva testing is a vital method for clinical applications, for its noninvasive features, richness in substances, and the huge amount. Due to its direct anatomical connection with oral, digestive, and endocrine systems, clinical usage of saliva testing for these diseases is promising. Furthermore, for other diseases that seeming to have no correlations with saliva, such as neurodegenerative diseases and psychological diseases, researchers also reckon saliva informative. Tremendous papers are being produced in this field. Updated summaries of recent literature give newcomers a shortcut to have a grasp of this topic. Here, we focused on recent research about saliva biomarkers that are derived from humans, not from other organisms. The review mostly addresses the proceedings from 2016 to 2022, to shed light on the promising usage of saliva testing in clinical diagnostics. We recap the recent advances following the category of different types of biomarkers, such as intracellular DNA, RNA, proteins and intercellular exosomes, cell-free DNA, to give a comprehensive impression of saliva biomarker testing.

A Comparative Study of Forehead Temperature and Core Body Temperature under Varying Ambient Temperature Conditions

When the ambient temperature, in which a person is situated, fluctuates, the body's surface temperature will alter proportionally. However, the body's core temperature will remain relatively steady. Consequently, using body surface temperature to characterize the core body temperature of the human body in varied situations is still highly inaccurate. This research aims to investigate and establish the link between human body surface temperature and core body temperature in a variety of ambient conditions, as well as the associated conversion curves.

METHODS

Plan an experiment to measure temperature over a thousand times in order to get the corresponding data for human forehead, axillary, and oral temperatures at varying ambient temperatures (14-32 °C). Utilize the axillary and oral temperatures as the core body temperature standards or the control group to investigate the new approach's accuracy, sensitivity, and specificity for detecting fever/non-fever conditions and the forehead temperature as the experimental group. Analyze the statistical connection, data correlation, and agreement between the forehead temperature and the core body temperature.

RESULTS

A total of 1080 tests measuring body temperature were conducted on healthy adults. The average axillary temperature was (36.7 ± 0.41) °C, the average oral temperature was (36.7 ± 0.33) °C, and the average forehead temperature was (36.2 ± 0.30) °C as a result of the shift in ambient temperature. The forehead temperature was 0.5 °C lower than the average of the axillary and oral temperatures. The Pearson correlation coefficient between axillary and oral temperatures was 0.41 (95% CI, 0.28-0.52), between axillary and forehead temperatures was 0.07 (95% CI, -0.07-0.22), and between oral and forehead temperatures was 0.26 (95% CI, 0.11-0.39). The mean differences between the axillary temperature and the oral temperature, the oral temperature and the forehead temperature, and the axillary temperature and the forehead temperature were -0.08 °C, 0.49 °C, and 0.42 °C, respectively, according to a Bland-Altman analysis. Finally, the regression analysis revealed that there was a linear association between the axillary temperature and the forehead temperature, as well as the oral temperature and the forehead temperature due to the change in ambient temperature.

CONCLUSION

The changes in ambient temperature have a substantial impact on the temperature of the forehead. There are significant differences between the forehead and axillary temperatures, as well as the forehead and oral temperatures, when the ambient temperature is low. As the ambient temperature rises, the forehead temperature tends to progressively converge with the axillary and oral temperatures. In clinical or daily applications, it is not advised to utilize the forehead temperature derived from an uncorrected infrared thermometer as the foundation for a body temperature screening in public venues such as hospital outpatient clinics, shopping malls, airports, and train stations.

Solving the inverse problem in electrocardiography imaging for atrial fibrillation using various time-frequency decomposition techniques based on empirical mode decomposition: A comparative study

Electrocardiographic imaging (ECGI) can aid in identifying the driving sources that cause and sustain atrial fibrillation (AF). Traditional regularization strategies for addressing the ECGI inverse problem are not currently concerned about the multi-scale analysis of the inverse problem, and these techniques are not clinically reliable. We have previously investigated the solution based on uniform phase mode decomposition (UPEMD-based) to the ECGI inverse problem. Numerous other methods for the time-frequency analysis derived from empirical mode decomposition (EMD-based) have not been applied to the inverse problem in ECGI. By applying many EMD-based solutions to the ECGI inverse problem and evaluating the performance of these solutions, we hope to find a more efficient EMD-based solution to the ECGI inverse problem. In this study, five AF simulation datasets and two real datasets from AF patients derived from a clinical ablation procedure are employed to evaluate the operating efficiency of several EMD-based solutions. The Pearson's correlation coefficient (CC), the relative difference measurement star (RDMS) of the computed epicardial dominant frequency (DF) map and driver probability (DP) map, and the distance (Dis) between the estimated and referenced most probable driving sources are used to evaluate the application of various EMD-based solutions in ECGI. The results show that for DF maps on all simulation datasets, the CC of UPEMD-based and improved UPEMD (IUPEMD)-based techniques are both greater than 0.95 and the CC of the empirical wavelet transform (EWT)-based solution is greater than 0.889, and the RDMS of UPEMD-based and IUPEMD-based approaches is less than 0.3 overall and the RDMS of EWT-based method is less than 0.48, performing better than other EMD-based solutions; for DP maps, the CC of UPEMD-based and IUPEMD-based techniques are close to 0.5, the CC of EWT-based is 0.449, and the CC of the remaining EMD-based techniques on the SAF and CAF is all below 0.1; the RDMS of UPEMD-based and IUPEMD-based are 0.06∼0.9 less than that of other EMD-based methods for all the simulation datasets overall. On two authentic AF datasets, the Dis between the first 10 real and estimated maximum DF positions of UPEMD-based and EWT-based methods are 212∼1440 less than that of others, demonstrating these two EMD-based solutions are superior and are suggested for clinical application in solving the ECGI inverse problem. On all datasets, EWT-based algorithms deconstruct the signal in the shortest time (no more than 0.12s), followed by UPEMD-based solutions (less than 0.81s), showing that these two schemes are more efficient than others.

Obtaining a Reliable Diagnostic Biomarker for Diabetes Mellitus by Standardizing Salivary Glucose Measurements

Salivary glucose is frequently utilized in diabetes mellitus (DM), and it might be proposed as a potential biomarker candidate for DM, as it is non-invasive and cost-effective and achieves adequate diagnostic performance for DM patients. However, salivary glucose levels may change under specific conditions. It is consequently essential to maintain a consistent strategy for measuring saliva, taking into account the possibility of external factors influencing salivary glucose levels. In this study, we analyzed salivary glucose levels under different handling conditions and donor-dependent factors, including age, interdiurnal variations, and collection and processing methods. A structured questionnaire was used to determine the symptoms and predisposing factors of DM. The glucose oxidase peroxidase method was used to estimate glucose levels in the blood and saliva of people in a fasting state. The aim of this study is to investigate the effect of such conditions on salivary glucose levels. We found that these extraneous variables should be taken into account in the future when salivary glucose is used as a predictive biomarker for DM.

Artificial Intelligence in Spinal Imaging: Current Status and Future Directions

Spinal maladies are among the most common causes of pain and disability worldwide. Imaging represents an important diagnostic procedure in spinal care. Imaging investigations can provide information and insights that are not visible through ordinary visual inspection. Multiscale in vivo interrogation has the potential to improve the assessment and monitoring of pathologies thanks to the convergence of imaging, artificial intelligence (AI), and radiomic techniques. AI is revolutionizing computer vision, autonomous driving, natural language processing, and speech recognition. These revolutionary technologies are already impacting radiology, diagnostics, and other fields, where automated solutions can increase precision and reproducibility. In the first section of this narrative review, we provide a brief explanation of the many approaches currently being developed, with a particular emphasis on those employed in spinal imaging studies. The previously documented uses of AI for challenges involving spinal imaging, including imaging appropriateness and protocoling, image acquisition and reconstruction, image presentation, image interpretation, and quantitative image analysis, are then detailed. Finally, the future applications of AI to imaging of the spine are discussed. AI has the potential to significantly affect every step in spinal imaging. AI can make images of the spine more useful to patients and doctors by improving image quality, imaging efficiency, and diagnostic accuracy.

Stimulated Parotid Saliva Is a Better Method for Depression Prediction

Background: Saliva cortisol is considered to be a biomarker of depression prediction. However, saliva collection methods can affect the saliva cortisol level. Objective: This study aims to determine the ideal saliva collection method and explore the application value of saliva cortisol in depression prediction. Methods: 30 depressed patients and 30 healthy controls were instructed to collect saliva samples in the morning with six collection methods. Simultaneous venous blood was collected. Enzyme-linked immunosorbent assay was used to determine the cortisol level. The 24-observerrated Hamilton depression rating scale (HAMD-24) was used to assess the severity of depression. Results: The significant differences in saliva cortisol levels depend on the saliva collection methods. The level of unstimulated whole saliva cortisol was most correlated with blood (r = 0.91). The stimulated parotid saliva cortisol can better predict depression. The area under the curve was 0.89. In addition, the saliva cortisol level of the depression patients was significantly higher than the healthy controls. The correlation between the cortisol level and the HAMD-24 score was highly significant. The higher the saliva cortisol level, the higher the HAMD-24 score. Conclusions: All the above findings point to an exciting opportunity for non-invasive monitoring of cortisol through saliva.

Investigation of Whole and Glandular Saliva as a Biomarker for Alzheimer’s Disease Diagnosis

Salivary Aβ40, Aβ42, t-tau, and p-tau 181 are commonly employed in Alzheimer’s disease (AD) investigations. However, the collection method of these biomarkers can affect their levels. To assess the impact of saliva collection methods on biomarkers in this study, 15 healthy people were employed in the morning with six saliva collection methods. The chosen methods were then applied in 30 AD patients and 30 non-AD controls. The levels of salivary biomarkers were calculated by a specific enzyme-linked immunosorbent assay. The receiver operating characteristic was utilized to assess salivary biomarkers in AD patients. The results demonstrated that the highest levels of salivary Aβ40, Aβ42, t-tau, and p-tau were in different saliva collection methods. The correlations between different saliva biomarkers in the same collection method were different. Salivary Aβ40, Aβ42, t-tau, and p-tau had no significant association. Salivary Aβ42 was higher in AD than in non-AD controls. However, p-tau/t-tau and Aβ42/Aβ40 had some relevance. The area under the curve for four biomarkers combined in AD diagnosis was 92.11%. An alternate saliva collection method (e.g., USS in Aβ40, UPS in Aβ42, t-tau, SSS in p-tau 181) was demonstrated in this study. Moreover, combining numerous biomarkers improves AD diagnosis.