A two-minute assay for electronic quantification of antibodies in saliva enabled through a reusable microfluidic multi-frequency impedance cytometer and machine learning analysis.

The use of saliva as a diagnostic fluid has always been appealing due to the ability for rapid and non-invasive sampling for monitoring health status and the onset and progression of disease and treatment progress. Saliva is rich in protein biomarkers and provides a wealth of information for diagnosis and prognosis of various disease conditions. Portable electronic tools which rapidly monitor protein biomarkers would facilitate point-of-care diagnosis and monitoring of various health conditions. For example, the detection of antibodies in saliva can enable rapid diagnosis and tracking disease pathogenesis of various auto-immune diseases like sepsis. Here, we present a novel method involving immuno-capture of proteins on antibody coated beads and electrical detection of dielectric properties of the beads. The changes in electrical properties of a bead when capturing proteins are extremely complex and difficult to model physically in an accurate manner. The ability to measure impedance of thousands of beads at multiple frequencies, however, allows for a data-driven approach for protein quantification. By moving from a physics driven approach to a data driven approach, we have developed, for the first time ever to the best of our knowledge, an electronic assay using a reusable microfluidic impedance cytometer chip in conjunction with supervised machine learning to quantifying immunoglobulins G (IgG) and immunoglobulins A (IgA) in saliva within two minutes.

Does saliva contamination interfere or stimulate regenerative processes applying current biomaterials on oral surgical sites?

Innovative dental biomaterials have been developed in order to stimulate higher biocompatibility and faster healing times using responsive surfaces for regenerative procedures. However, saliva is one of the fluids to interact with these biomaterials in the first instance. Studies have revealed significant negative effects on the biomaterials' properties, biocompatibility and bacterial colonisation after saliva contact. Nevertheless, the current literature is unclear about the profound effects of saliva on regenerative procedures. The scientific community urges further detailed studies associating innovative biomaterials/saliva/microbiology/immunology in order to clarify clinical outcomes. This paper discusses and provides information about the challenges of research using human saliva, the lack of standardisation in protocols applying saliva, and tentative applications of saliva proteins associated with innovative dental biomaterials.

Comparative evaluation of saliva and nasopharyngeal swab for SARS-CoV-2 detection using RT-qPCR among COVID-19 suspected patients at Jigjiga, Eastern Ethiopia.

BACKGROUND: Nasopharyngeal swab (NPS) remains the recommended sample type for Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) diagnosis. However, the collection procedure causes discomfort and irritation to the patients, lowering the quality of the sample and exposing healthcare workers to risk. Furthermore, there is also a shortage of flocked swabs and personnel protective equipment in low-income settings. Therefore, this necessitates an alternative diagnostic specimen. The purpose of this study was to evaluate the performance of saliva against NPS for SARS-CoV-2 detection using RT-qPCR among COVID-19 suspected patients at Jigjiga, Eastern Ethiopia. METHODS: Comparative cross-sectional study was conducted from June 28 to July 30, 2022. A total of 227 paired saliva and NPS samples were collected from 227 COVID-19 suspected patients. Saliva and NPS samples were collected and transported to the Somali Regional Molecular Laboratory. Extraction was conducted using DaAn kit (DaAn Gene Co., Ltd China). Veri-Q RT-qPCR was used for amplification and detection (Mico BioMed Co, Ltd, Republic of Korea). The data were entered into Epi-data version 4.6 and analyzed using SPSS 25. McNemar's test was used to compare the detection rate. Agreement between NPS and saliva was performed using Cohen's Kappa. The mean and median of cycle threshold values were compared using paired t-tests and the correlation between cycle threshold values was measured using Pearson correlation coefficient. P value < 0.05 was considered statistically significant. RESULTS: The overall positivity rate of SARS-CoV-2 RNA was 22.5% (95% CI 17-28%). Saliva showed higher sensitivity (83.8%, 95% CI, 73-94.5%) than NPS (68.9%, 95% CI 60.8-76.8%). The specificity of saliva was 92.6% (95% CI, 80.6% - 100%) compared to NPS (96.7%, 95% CI, 87% - 100%). The positive, negative, and overall percent agreement between NPS and saliva was 83.8%, 92.6%, and 91.2% respectively (κ = 0.703, 95% CI 0.58-0.825, P = 0.00). The concordance rate between the two samples was 60.8%. NPS showed a higher viral load than saliva. There was low positive correlation between the cycle threshold values of the two samples (r = 0.41, 95% CI -1.69 to -0.98, P >0.05). CONCLUSION: Saliva showed a higher detection rate for SARS-CoV-2 molecular diagnosis than NPS and there was significant agreement between the two specimens. Therefore, saliva could be suitable and easily obtainable alternative diagnostic specimen for SARS-CoV-2 molecular diagnosis.

Modeling in higher dimensions to improve diagnostic testing accuracy: Theory and examples for multiplex saliva-based SARS-CoV-2 antibody assays.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has emphasized the importance and challenges of correctly interpreting antibody test results. Identification of positive and negative samples requires a classification strategy with low error rates, which is hard to achieve when the corresponding measurement values overlap. Additional uncertainty arises when classification schemes fail to account for complicated structure in data. We address these problems through a mathematical framework that combines high dimensional data modeling and optimal decision theory. Specifically, we show that appropriately increasing the dimension of data better separates positive and negative populations and reveals nuanced structure that can be described in terms of mathematical models. We combine these models with optimal decision theory to yield a classification scheme that better separates positive and negative samples relative to traditional methods such as confidence intervals (CIs) and receiver operating characteristics. We validate the usefulness of this approach in the context of a multiplex salivary SARS-CoV-2 immunoglobulin G assay dataset. This example illustrates how our analysis: (i) improves the assay accuracy, (e.g. lowers classification errors by up to 42% compared to CI methods); (ii) reduces the number of indeterminate samples when an inconclusive class is permissible, (e.g. by 40% compared to the original analysis of the example multiplex dataset) and (iii) decreases the number of antigens needed to classify samples. Our work showcases the power of mathematical modeling in diagnostic classification and highlights a method that can be adopted broadly in public health and clinical settings.

Bioluminescent-Triple-Enzyme-Based Biosensor with Lactate Dehydrogenase for Non-Invasive Training Load Monitoring.

Saliva is one of the most significant biological liquids for the development of a simple, rapid, and non-invasive biosensor for training load diagnostics. There is an opinion that enzymatic bioassays are more relevant in terms of biology. The present paper is aimed at investigating the effects of saliva samples, upon altering the lactate content, on the activity of a multi-enzyme, namely lactate dehydrogenase + NAD(P)H:FMN-oxidoreductase + luciferase (LDH + Red + Luc). Optimal enzymes and their substrate composition of the proposed multi-enzyme system were chosen. During the tests of the lactate dependence, the enzymatic bioassay showed good linearity to lactate in the range from 0.05 mM to 0.25 mM. The activity of the LDH + Red + Luc enzyme system was tested in the presence of 20 saliva samples taken from students whose lactate levels were compared by the Barker and Summerson colorimetric method. The results showed a good correlation. The proposed LDH + Red + Luc enzyme system could be a useful, competitive, and non-invasive tool for correct and rapid monitoring of lactate in saliva. This enzyme-based bioassay is easy to use, rapid, and has the potential to deliver point-of-care diagnostics in a cost-effective manner.

What is the food like that people choke on? A study on food bolus physical properties under different in vitro oral capacities.

People with oral impairments, such as poor denture status, poor muscle strength, and poor salivary secretion, have more difficulties performing oral processes, which results in the risk of choking. In this study, we aimed to understand, in vitro, how different oral impairments can affect the oral processing of food reported as a choking hazard. Six foods that frequently cause choking were selected and studied, varying three in vitro factors at two levels-saliva incorporation amount, cutting activity, and compression action. The median particle size (a50) and the particle size heterogeneity (a75/25) of the food fragmentation, the hardness, and adhesiveness of the bolus formation, and the final cohesiveness of the bolus were studied. The results showed that all the parameters studied varied depending on the food product. High compression reduced a50 (except in mochi that increased) and a75/25 (except in eggs and fish) but increased bolus adhesion and particle aggregation (except for mochi). Regarding cutting activity, when performing a greater number of strokes, the particle size for sausage and egg, and the hardness of the bolus for mochi and sausage were lower. In contrast, for some food products, the bolus adhesiveness (bread) and particle aggregation (pineapple) were higher at a high number of strokes. The amount of saliva also played an important role in the creation of the bolus. When high amounts of saliva were added, the a50 values (mochi) and hardness (mochi, egg, and fish) decreased; and increased the adhesiveness (mochi) and particle aggregation (bread, pineapple, and sausage). When all oral factors are compromised (lack of muscle strength, denture status, and saliva secretion), some food products create a choking hazard as individuals cannot achieve the right particle size, bolus cohesiveness, and mechanical properties of the bolus to be safe to swallow, there is still a need to elaborate a guide, considering all the safety parameters.

Immuno field-effect transistor (ImmunoFET) for detection of salivary cortisol using potentiometric and impedance spectroscopy for monitoring heart failure.

Cortisol, a steroid hormone mostly known as "the stress hormone," plays many essential functions in humans due its involvement in several metabolic pathways. It is well-known that cortisol dysregulation is implied in evolution and progression of several chronic pathologies, including cardiac diseases such as heart failure (HF). However, although several sensors have been proposed to date for the determination of cortisol, none of them has been designed for its determination in saliva in order to monitor HF progression. In this work, a silicon nitride based Immuno field-effect transistor (ImmunoFET) has been proposed to quantify salivary cortisol for HF monitoring. Sensitive biological element was represented by anti-cortisol antibody bound onto the ISFET gate via 11-triethoxysilyl undecanal (TESUD) by vapor-phase method. Potentiometric and electrochemical impedance spectroscopy (EIS) measurements were carried out for preliminary investigations on device responsiveness. Subsequently, a more sensitive detection was obtained using electrochemical EIS. The proposed device has proven to have a linear response (R2 always >0.99), to be sensitive (with a limit of detection, LoD, of 0.005 ± 0.002 ng/mL), selective in case of other HF biomarkers (e.g. N-terminal pro B-type natriuretic peptide (NT-proBNP), tumor necrosis factor-alpha (TNF-α), and interleukin 10 (IL-10)), and accurate in cortisol quantification in saliva sample by performing the standard addition method.

Composition and Properties of Saliva in Patients with Osteoporosis Taking Antiresorptive Drugs.

The aim of this study was to examine how the composition and properties of saliva change in people with osteoporosis who have received antiresorptive (AR) treatment, compared to patients with osteoporosis who have not yet received this treatment. METHODS: The study population consisted of 38 patients with osteoporosis using AR drugs (Group I) and 16 patients with osteoporosis who had never used AR drugs (Group II). The control group consisted of 32 people without osteoporosis. Laboratory tests included determination of pH and concentrations of Ca, PO4, total protein, lactoferrin, lysozyme, sIgA, IgA, cortisol, neopterin, activity of amylase at rest, and stimulated saliva. The buffering capacity of stimulated saliva was also determined. RESULTS: There were no statistically significant differences between the saliva of Group I and Group II. No statistically significant correlation was found between the amount of time using AR therapy (Group I) and the tested parameters of the saliva. Significant differences were found between Group I and the control group. The concentrations of PO4, lysozyme, and cortisol were higher, while concentrations of Ca ions, sIgA, and neopterin were lower, in comparison to the control group. The significant differences between Group II and the control group were smaller, and they concerned only the concentrations of lysozyme, cortisol, and neopterin. CONCLUSIONS: The saliva of people with osteoporosis subjected to AR therapy and those not subjected to AR therapy did not show statistically significant differences in terms of the examined parameters of the saliva. However, the saliva of patients with osteoporosis taking and not taking AR drugs was significantly different compared to the saliva of the control group.

Biosensors for saliva biomarkers.

The analysis of salivary biomarkers has gained interest and is advantageous for simple, safe, and non-invasive testing in diagnosis as well as treatment. This chapter explores the importance of saliva biomarkers and summarizes recent advances in biosensor fabrication. The identification of diagnostic, prognostic and therapeutic markers in this matrix enables more rapid and frequent testing when combined with the use of biosensor technology. Challenges and future goals are highlighted and examined.

Cortisol: Analytical and clinical determinants.

Cortisol, the main human glucocorticoid, is synthesized from cholesterol in the adrenal cortex and predominantly metabolized by the liver. Interpretation of quantitative results from the analysis of serum, urine and saliva is complicated by variation in circadian rhythm, response to stress as well as the presence of protein-bound and free forms. Interestingly, cortisol is the only hormone routinely measured in serum, urine, and saliva. Preanalytical and analytical challenges arise in each matrix and are further compounded by the use of various stimulation and suppression tests commonly employed in clinical practice. Although not yet included in clinical guidelines, measurement of cortisol in hair may be of interest in specific situations. Immunoassays are the most widely used methods in clinical laboratories to measure cortisol, but they are susceptible to interference from synthetic and endogenous steroids, generally producing a variable overestimation of true cortisol results, especially in urine. Analysis by mass spectrometry provides higher specificity and allows simultaneous measurement of multiple steroids including synthetic steroids, thus reducing diagnostic uncertainty. An integrated review of cortisol in various disease states is also addressed.

Ecological shifts of salivary microbiota associated with metabolic-associated fatty liver disease.

Introduction: Metabolic-associated fatty liver disease (MAFLD) is the most common chronic liver disease related to metabolic syndrome. However, ecological shifts in the saliva microbiome in patients with MAFLD remain unknown. This study aimed to investigate the changes to the salivary microbial community in patients with MAFLD and explore the potential function of microbiota. Methods: Salivary microbiomes from ten MAFLD patients and ten healthy participants were analyzed by 16S rRNA amplicon sequencing and bioinformatics analysis. Body composition, plasma enzymes, hormones, and blood lipid profiles were assessed with physical examinations and laboratory tests. Results: The salivary microbiome of MAFLD patients was characterized by increased α-diversity and distinct ß-diversity clustering compared with control subjects. Linear discriminant analysis effect size analysis showed a total of 44 taxa significantly differed between the two groups. Genera Neisseria, Filifactor, and Capnocytophaga were identified as differentially enriched genera for comparison of the two groups. Co-occurrence networks suggested that the salivary microbiota from MAFLD patients exhibited more intricate and robust interrelationships. The diagnostic model based on the salivary microbiome achieved a good diagnostic power with an area under the curve of 0.82(95% CI: 0.61-1). Redundancy analysis and spearman correlation analysis revealed that clinical variables related to insulin resistance and obesity were strongly associated with the microbial community. Metagenomic predictions based on Phylogenetic Investigation of Communities by Reconstruction of Unobserved States revealed that pathways related to metabolism were more prevalent in the two groups. Conclusions: Patients with MAFLD manifested ecological shifts in the salivary microbiome, and the saliva microbiome-based diagnostic model provides a promising approach for auxiliary MAFLD diagnosis.

Persistence of SARS-CoV-2 in saliva: Implications for late-stage diagnosis and infectious duration.

Saliva has been a COVID-19 diagnostic specimen of interest due to its simple collection, scalability, and yield. Yet COVID-19 testing and estimates of the infectious period remain largely based on nasopharyngeal and nasal swabs. We sought to evaluate whether saliva testing captured prolonged presence of SARS-CoV-2 and potential infectiousness later in the disease course. We conducted an observational study of symptomatic COVID-19 patients at University Hospital in Newark, NJ. Paired saliva and nasal specimens from 96 patients were analyzed, including longitudinal analysis of paired observations from 28 of these patients who had multiple time-points. Saliva detected significantly more cases of COVID-19 beyond 5 days (86.1% [99/115] saliva vs 48.7% [56/115] nasal, p-value < 0.001), 9 days (79.4% [50/63] saliva vs 36.5% [23/63] nasal, p-value < 0.001) and 14 days (71.4% [20/28] saliva vs 32.1% [9/28] nasal, p-value = 0.010) of symptoms. Additionally, saliva yielded lower cycle thresholds across all time periods, indicative of higher viral loads in saliva. In the longitudinal analysis, a log-rank analysis indicated that the survival curve for saliva was significantly different from the curve for nasal swabs (p<0.001) with a median survival time for saliva of 18 days compared to 13 days for nasal swabs. We additionally performed saliva viral cultures among a similar COVID-19 patient cohort and noted patients with positive saliva viral cultures between 7 to 28 days of symptoms. Findings from this study suggest that SARS-CoV-2 RNA persists longer and in higher abundance in saliva compared to nasal swabs, with potential of prolonged propagating virus. Testing saliva may thus increase yield for detecting potentially infectious virus even beyond the first five days of symptomatic COVID-19.

Structural properties and binding mechanism of DNA aptamers sensing saliva melatonin for diagnosis and monitoring of circadian clock and sleep disorders.

Circadian desynchrony with the external light-dark cycle influences the rhythmic secretion of melatonin which is among the first signs of circadian rhythm sleep disorders. An accurate dim light melatonin onset (established indicator of circadian rhythm sleep disorders) measurement requires lengthy assays, and antibody affinities alterations, especially in patients with circadian rhythm disorders whose melatonin salivary levels vary significantly, making antibodies detection mostly inadequate. In contrast, aptamers with their numerous advantages (e.g., target selectivity, structural flexibility in tuning binding affinities, small size, etc.) can become preferable biorecognition molecules for salivary melatonin detection with high sensitivity and specificity. This study thoroughly characterizes the structural property and binding mechanism of a single-stranded DNA aptamer full sequence (MLT-C-1) and its truncated versions (MLT-A-2, MLT-A-4) to decipher its optimal characteristics for saliva melatonin detection. We use circular dichroism spectroscopy to determine aptamers' conformational changes under different ionic strengths and showed that aptamers display a hairpin loop structure where few base pairs in the stem play a significant role in melatonin binding and formation of aptamer stabilized structure. Through microscale thermophoresis, aptamers demonstrated a high binding affinity in saliva samples (MLT-C-1F Kd = 12.5 ± 1.7 nM; MLT-A-4F Kd = 11.2 ± 1.6 nM; MLT-A-2F Kd = 2.4 ± 2.8 nM; limit-of-detection achieved in pM, highest sensitivity attained for MLT-A-2F aptamer with the lowest detection limit of 1.35 pM). Our data suggest that aptamers are promising as biorecognition molecules and provide the baseline parameters for the development of an aptamer-based point-of-care diagnostic system for melatonin detection and accurate profiling of its fluctuations in saliva.

SPECIFIC FEATURES OF THE ORAL MICROBIOME IN YOUNG CHILDREN WITH ARYNGOPHARYNGEAL REFLUX AND ITS ROLE THE DEVELOPMENT OF RECURRENT RESPIRATORY DISEASES.

OBJECTIVE: The aim: To examine the composition of the oral microbiome in young children with laryngopharyngeal reflux (LPR) and its role the development of recurrent respiratory diseases. PATIENTS AND METHODS: Materials and methods: There were examined 38 children with physiological gastroesophageal reflux (GER), 18 children with LPR who had a medical history of recurrent bronchitis and 17 healthy children (control group). The study included the collection of anamnesis, objective examination. The qualitative and quantitative microbial composition of the upper respiratory tract was performed obtained by oropharyngeal deep swab. Salivary pepsin level and IL-8 were determined by enzyme-linked immunosorbent assay. RESULTS: Results: This research showed significant alterations in the oral microbiome of patients with GER and LPR as compared to healthy control. We found that gram-negative microbiota such as Klebsiella pneumoniae, Escherichia coli, Proteus vulgaris, Proteus spp. and Candida albicans were identified in children with GER and LPR compared to the healthy control. At the same time, the amount of such a representative of the normal microbiome as Streptococcus viridans in children with LPR was sharply reduced. There were established a much higher mean salivary pepsin level of the patients with LPR than in the GER and control group. We found the association between high pepsin levels, saliva IL-8 levels and frequency of respiratory pathology in children with LPR. CONCLUSION: Conclusions: Our study confirms that increased levels of pepsin in saliva are a risk factor for recurrent respiratory diseases in children with LPR.

Highly Specific Detection of Oxytocin in Saliva.

Oxytocin is a peptide neurophysin hormone made up of nine amino acids and is used in induction of one in four births worldwide (more than 13 percent in the United States). Herein, we have developed an antibody alternative aptamer-based electrochemical assay for real-time and point-of-care detection of oxytocin in non-invasive saliva samples. This assay approach is rapid, highly sensitive, specific, and cost-effective. Our aptamer-based electrochemical assay can detect as little as 1 pg/mL of oxytocin in less than 2 min in commercially available pooled saliva samples. Additionally, we did not observe any false positive or false negative signals. This electrochemical assay has the potential to be utilized as a point-of-care monitor for rapid and real-time oxytocin detection in various biological samples such as saliva, blood, and hair extracts.

Comparison of SARS-CoV-2 Detection in Nasopharyngeal Swab and Saliva Samples from Patients Infected with Omicron Variant.

To compare the detection of the SARS-CoV-2 Omicron variant in nasopharyngeal-swab (NPS) and oral saliva samples. 255 samples were obtained from 85 Omicron-infected patients. SARS-CoV-2 load was measured in the NPS and saliva samples by using Simplexa™ COVID-19 direct and Alinity m SARS-CoV-2 AMP assays. Results obtained with the two diagnostic platforms showed very good inter-assay concordance (91.4 and 82.4% for saliva and NPS samples, respectively) and a significant correlation among cycle threshold (Ct) values. Both platforms revealed a highly significant correlation among Ct obtained in the two matrices. Although the median Ct value was lower in NPS than in saliva samples, the Ct drop was comparable in size for both types of samples after 7 days of antiviral treatment of the Omicron-infected patients. Our result demonstrates that the detection of the SARS-CoV-2 Omicron variant is not influenced by the type of sample used for PCR analysis, and that saliva can be used as an alternative specimen for detection and follow-up of Omicron-infected patients.

Participants in the Trans-Antarctic Winter Traverse Expedition Showed Increased Bacterial Load and Diversity in Saliva but Maintained Individual Differences within Stool Microbiota and Across Metabolite Fingerprints.

Understanding the impact of long-term physiological and environmental stress on the human microbiota and metabolome may be important for the success of space flight. This work is logistically difficult and has a limited number of available participants. Terrestrial analogies present important opportunities to understand changes in the microbiota and metabolome and how this may impact participant health and fitness. Here, we present work from one such analogy: the Transarctic Winter Traverse expedition, which we believe is the first assessment of the microbiota and metabolome from different bodily locations during prolonged environmental and physiological stress. Bacterial load and diversity were significantly higher during the expedition when compared with baseline levels (p < 0.001) in saliva but not stool, and only a single operational taxonomic unit assigned to the Ruminococcaceae family shows significantly altered levels in stool (p < 0.001). Metabolite fingerprints show the maintenance of individual differences across saliva, stool, and plasma samples when analysed using flow infusion electrospray mass spectrometry and Fourier transform infrared spectroscopy. Significant activity-associated changes in terms of both bacterial diversity and load are seen in saliva but not in stool, and participant differences in metabolite fingerprints persist across all three sample types.

Analysis of Drugs in Saliva of US Military Veterans Treated for Substance Use Disorders Using Supported Liquid Extraction and Surface-Enhanced Raman Spectral Analysis.

According to the Center for Disease Control, there were more than 107,000 US drug overdose deaths in 2021, over 80,000 of which due to opioids. One of the more vulnerable populations is US military veterans. Nearly 250,000 military veterans suffer from substance-related disorders (SRD). For those seeking treatment, buprenorphine is prescribed to help treat opioid use disorder (OUD). Urinalysis is currently used to monitor buprenorphine adherence as well as to detect illicit drug use during treatment. Sometimes sample tampering occurs if patients seek to generate a false positive buprenorphine urine test or mask illicit drugs, both of which can compromise treatment. To address this problem, we have been developing a point-of-care (POC) analyzer that can rapidly measure both medications used for treatment and illicit drugs in patient saliva, ideally in the physi-cian's office. The two-step analyzer employs (1) supported liquid extraction (SLE) to isolate the drugs from the saliva and (2) surface-enhanced Raman spectroscopy (SERS) to detect the drugs. A prototype SLE-SERS-POC analyzer was used to quantify buprenorphine at ng/mL concentrations and identify illicit drugs in less than 1 mL of saliva collected from 20 SRD veterans in less than 20 min. It correctly detected buprenorphine in 19 of 20 samples (18 true positives, 1 true negative and 1 false negative). It also identified 10 other drugs in patient samples: acetaminophen, amphetamine, cannabidiol, cocaethylene, codeine, ibuprofen, methamphetamine, methadone, nicotine, and norbuprenorphine. The prototype analyzer shows evidence of accuracy in measuring treatment medications and relapse to drug use. Further study and development of the system is warranted.

Use of Streptococcus salivarius K12 in supporting the mucosal immune function of active young subjects: A randomised double-blind study.

Introduction: Upper respiratory tract infections (URTI) are the most common illnesses affecting athletes, causing absences from training and competition. Salivary immunoglobulin A (sIgA) is the main immune factor in saliva, and a consistent association between low concentrations of sIgA and an increased incidence of URTIs has been reported. The oral probiotic Streptococcus salivarius K12 has been suggested to have the potential to improve oral diseases and mucosal barrier function. However, the effects of this probiotic on active young subjects performing a high-intensity training (HIT) program have not been investigated. Methods: Active young students were randomised into a treated group (S. salivarius K12) and a control (placebo) group and asked to take the product daily for 30 days. After this period, participants performed a graded exercise test and five HIT sessions, all within 3 days. They were also asked to complete the Wisconsin Upper Respiratory Symptom Survey daily to monitor URTI's presence. Before and after the 30 days, and at 0h, 24h and 72h after the last training session, saliva samples were collected to quantify sIgA level, secretion rate, and flow. The effect of S. salivarius K12 intake on these parameters was tested using an ANOVA for repeated measures. Results: Twenty (M = 14, F = 6) young subjects (23.5 ± 2.3 years old) participated in the study. The total accumulated training load (sRPE) in the supplementation period was similar in the two groups (treated: 4345 ± 3441 AU; control: 4969 ± 4165 AU; p > 0.05). Considering both sIgA level and secretion rate, significant time (F(4,15) = 3.38; p = 0.037; F(4,15) = 6.00; p = 0.004) and time×group interactions (F(4,15) = 2.49; p = 0.049; F(4,15) = 5.01; p = 0.009) were reported, with the treated group showing higher sIgA levels at 72h post-exercise and increased secretion rate both at 0h and 72h. The number of URTI episodes was similar in the treated and control groups (χ² = 1.83; p > 0.05). Conclusion: This study demonstrates that relatively short-term S. salivarius K12 supplementation increased sIgA level and secretion in healthy subjects performing a demanding exercise-training programme composed of HIT sessions.

Saliva-based microfluidic point-of-care diagnostic.

There has been a long-standing interest in point-of-care (POC) diagnostics as a tool to improve patient care because it can provide rapid, actionable results near the patient. Some of the successful examples of POC testing include lateral flow assays, urine dipsticks, and glucometers. Unfortunately, POC analysis is somewhat limited by the ability to manufacture simple devices to selectively measure disease specific biomarkers and the need for invasive biological sampling. Next generation POCs are being developed that make use of microfluidic devices to detect biomarkers in biological fluids in a non-invasive manner, addressing the above-mentioned limitations. Microfluidic devices are desirable because they can provide the ability to perform additional sample processing steps not available in existing commercial diagnostics. As a result, they can provide more sensitive and selective analysis. While most POC methods make use of blood or urine as a sample matrix, there has been a growing push to use saliva as a diagnostic medium. Saliva represents an ideal non-invasive biofluid for detecting biomarkers because it is readily available in large quantities and analyte levels reflect those in blood. However, using saliva in microfluidic devices for POC diagnostics is a relatively new and an emerging field. The overarching aim of this review is to provide an update on recent literature focused on the use of saliva as a biological sample matrix in microfluidic devices. We will first cover the characteristics of saliva as a sample medium and then review microfluidic devices that are developed for the analysis of salivary biomarkers.