Salivary factor LTRIN from Aedes aegypti facilitates the transmission of Zika virus by interfering with the lymphotoxin-ß receptor.

Pathogens have co-evolved with mosquitoes to optimize transmission to hosts. Mosquito salivary-gland extract is known to modulate host immune responses and facilitate pathogen transmission, but the underlying molecular mechanisms of this have remained unknown. In this study, we identified and characterized a prominent 15-kilodalton protein, LTRIN, obtained from the salivary glands of the mosquito Aedes aegypti. LTRIN expression was upregulated in blood-fed mosquitoes, and LTRIN facilitated the transmission of Zika virus (ZIKV) and exacerbated its pathogenicity by interfering with signaling through the lymphotoxin-ß receptor (LTßR). Mechanically, LTRIN bound to LTßR and 'preferentially' inhibited signaling via the transcription factor NF-κB and the production of inflammatory cytokines by interfering with the dimerization of LTßR during infection with ZIKV. Furthermore, treatment with antibody to LTRIN inhibited mosquito-mediated infection with ZIKV, and abolishing LTßR potentiated the infectivity of ZIKV both in vitro and in vivo. This study provides deeper insight into the transmission of mosquito-borne diseases in nature and supports the therapeutic potential of inhibiting the action of LTRIN to disrupt ZIKV transmission.

The researcher's guide to selecting biomarkers in mental health studies.

Clinical mental health researchers may understandably struggle with how to incorporate biological assessments in clinical research. The options are numerous and are described in a vast and complex body of literature. Here we provide guidelines to assist mental health researchers seeking to include biological measures in their studies. Apart from a focus on behavioral outcomes as measured via interviews or questionnaires, we advocate for a focus on biological pathways in clinical trials and epidemiological studies that may help clarify pathophysiology and mechanisms of action, delineate biological subgroups of participants, mediate treatment effects, and inform personalized treatment strategies. With this paper we aim to bridge the gap between clinical and biological mental health research by (1) discussing the clinical relevance, measurement reliability, and feasibility of relevant peripheral biomarkers; (2) addressing five types of biological tissues, namely blood, saliva, urine, stool and hair; and (3) providing information on how to control sources of measurement variability.

Quantitative detection of hydrogen peroxide in rain, air, exhaled breath, and biological fluids by NMR spectroscopy.

Hydrogen peroxide (H2O2) plays a key role in environmental chemistry, biology, and medicine. H2O2 concentrations typically are 6 to 10 orders of magnitude lower than that of water, making its quantitative detection challenging. We demonstrate that optimized NMR spectroscopy allows direct, interference-free, quantitative measurements of H2O2 down to submicromolar levels in a wide range of fluids, ranging from exhaled breath and air condensate to rain, blood, urine, and saliva. NMR measurements confirm the previously reported spontaneous generation of H2O2 in microdroplets that form when condensing water vapor on a hydrophobic surface, which can interfere with atmospheric H2O2 measurements. Its antimicrobial activity and strong seasonal variation speculatively could be linked to the seasonality of respiratory viral diseases.

A top-down proteomic approach reveals a salivary protein profile able to classify Parkinson's disease with respect to Alzheimer's disease patients and to healthy controls.

Parkinson's disease (PD) is a complex neurodegenerative disease with motor and non-motor symptoms. Diagnosis is complicated by lack of reliable biomarkers. To individuate peptides and/or proteins with diagnostic potential for early diagnosis, severity and discrimination from similar pathologies, the salivary proteome in 36 PD patients was investigated in comparison with 36 healthy controls (HC) and 35 Alzheimer's disease (AD) patients. A top-down platform based on HPLC-ESI-IT-MS allowed characterizing and quantifying intact peptides, small proteins and their PTMs (overall 51). The three groups showed significantly different protein profiles, PD showed the highest levels of cystatin SA and antileukoproteinase and the lowest of cystatin SN and some statherin proteoforms. HC exhibited the lowest abundance of thymosin ß4, short S100A9, cystatin A, and dimeric cystatin B. AD patients showed the highest abundance of α-defensins and short oxidized S100A9. Moreover, different proteoforms of the same protein, as S-cysteinylated and S-glutathionylated cystatin B, showed opposite trends in the two pathological groups. Statherin, cystatins SA and SN classified accurately PD from HC and AD subjects. α-defensins, histatin 1, oxidized S100A9, and P-B fragments were the best classifying factors between PD and AD patients. Interestingly statherin and thymosin ß4 correlated with defective olfactory functions in PD patients. All these outcomes highlighted implications of specific proteoforms involved in the innate-immune response and inflammation regulation at oral and systemic level, suggesting a possible panel of molecular and clinical markers suitable to recognize subjects affected by PD.

Unrevealing the connection between real sample analysis and analytical method. The case of cytokines.

Cytokines are compounds that belong to a special class of signaling biomolecules that are responsible for several functions in the human body, being involved in cell growth, inflammatory, and neoplastic processes. Thus, they represent valuable biomarkers for diagnosing and drug therapy monitoring certain medical conditions. Because cytokines are secreted in the human body, they can be detected in both conventional samples, such as blood or urine, but also in samples less used in medical practice such as sweat or saliva. As the importance of cytokines was identified, various analytical methods for their determination in biological fluids were reported. The gold standard in cytokine detection is considered the enzyme-linked immunosorbent assay method and the most recent ones have been considered and compared in this study. It is known that the conventional methods are accompanied by a few disadvantages that new methods of analysis, especially electrochemical sensors, are trying to overcome. Electrochemical sensors proved to be suited for the elaboration of integrated, portable, and wearable sensing devices, which could also facilitate cytokines determination in medical practice.

Mapping Conformational Changes in the Saliva Proteome Potentially Associated with Oral Cancer Aggressiveness.

Diverse proteomics-based strategies have been applied to saliva to quantitatively identify diagnostic and prognostic targets for oral cancer. Considering that these targets may be regulated by events that do not imply variation in protein abundance levels, we hypothesized that changes in protein conformation can be associated with diagnosis and prognosis, revealing biological processes and novel targets of clinical relevance. For this, we employed limited proteolysis-mass spectrometry in saliva samples to explore structural alterations, comparing the proteome of healthy control and oral squamous cell carcinoma (OSCC) patients with and without lymph node metastasis. Thirty-six proteins with potential structural rearrangements were associated with clinical patient features including transketolase and its interacting partners. Moreover, N-glycosylated peptides contribute to structural rearrangements of potential diagnostic and prognostic markers. Altogether, this approach utilizes saliva proteins to search for targets for diagnosing and prognosing oral cancer and can guide the discovery of potential regulated sites beyond protein-level abundance.

Discovery and validation of plasma, saliva and multi-fluid plasma-saliva metabolomic scores predicting insulin resistance and diabetes progression or regression among Puerto Rican adults.

AIMS/HYPOTHESIS: Many studies have examined the relationship between plasma metabolites and type 2 diabetes progression, but few have explored saliva and multi-fluid metabolites. METHODS: We used LC/MS to measure plasma (n=1051) and saliva (n=635) metabolites among Puerto Rican adults from the San Juan Overweight Adults Longitudinal Study. We used elastic net regression to identify plasma, saliva and multi-fluid plasma-saliva metabolomic scores predicting baseline HOMA-IR in a training set (n=509) and validated these scores in a testing set (n=340). We used multivariable Cox proportional hazards models to estimate HRs for the association of baseline metabolomic scores predicting insulin resistance with incident type 2 diabetes (n=54) and prediabetes (characterised by impaired glucose tolerance, impaired fasting glucose and/or high HbA1c) (n=130) at 3 years, along with regression from prediabetes to normoglycaemia (n=122), adjusting for traditional diabetes-related risk factors. RESULTS: Plasma, saliva and multi-fluid plasma-saliva metabolomic scores predicting insulin resistance included highly weighted metabolites from fructose, tyrosine, lipid and amino acid metabolism. Each SD increase in the plasma (HR 1.99 [95% CI 1.18, 3.38]; p=0.01) and multi-fluid (1.80 [1.06, 3.07]; p=0.03) metabolomic scores was associated with higher risk of type 2 diabetes. The saliva metabolomic score was associated with incident prediabetes (1.48 [1.17, 1.86]; p=0.001). All three metabolomic scores were significantly associated with lower likelihood of regressing from prediabetes to normoglycaemia in models adjusting for adiposity (HRs 0.72 for plasma, 0.78 for saliva and 0.72 for multi-fluid), but associations were attenuated when adjusting for lipid and glycaemic measures. CONCLUSIONS/INTERPRETATION: The plasma metabolomic score predicting insulin resistance was more strongly associated with incident type 2 diabetes than the saliva metabolomic score. Only the saliva metabolomic score was associated with incident prediabetes.

Temporal Characterization of Prion Shedding in Secreta of White-Tailed Deer in Longitudinal Study of Chronic Wasting Disease, United States.

Chronic wasting disease (CWD) affects cervids in North America, Asia, and Scandinavia. CWD is unique in its efficient spread, partially because of contact with infectious prions shed in secreta. To assess temporal profiles of CWD prion shedding, we collected saliva, urine, and feces from white-tailed deer for 66 months after exposure to low oral doses of CWD-positive brain tissue or saliva. We analyzed prion seeding activity by using modified amyloid amplification assays incorporating iron oxide bead extraction, which improved CWD detection and reduced false positives. CWD prions were detected in feces, urine, and saliva as early as 6 months postinfection. More frequent and consistent shedding was observed in deer homozygous for glycine at prion protein gene codon 96 than in deer expressing alternate genotypes. Our findings demonstrate that improved amplification methods can be used to identify early antemortem CWD prion shedding, which might aid in disease surveillance of cervids.

Nociception related biomolecules in the adult human saliva: A scoping review with additional quantitative focus on cortisol.

Nociception related salivary biomolecules can be useful patients who are not able to self-report pain. We present the existing evidence on this topic using the PRISMA-ScR guidelines and a more focused analysis of cortisol change after cold pain induction using the direction of effect analysis combined with risk of bias analysis using ROBINS-I. Five data bases were searched systematically for articles on adults with acute pain secondary to disease, injury, or experimentally induced pain. Forty three articles met the inclusion criteria for the general review and 11 of these were included in the cortisol-cold pain analysis. Salivary melatonin, kallikreins, pro-inflammatory cytokines, soluable TNF-α receptor II, secretory IgA, testosterone, salivary α-amylase (sAA) and, most commonly, cortisol have been studied in relation to acute pain. There is greatest information about cortisol and sAA which both rise after cold pain when compared with other modalities. Where participants have been subjected to both pain and stress, stress is consistently a more reliable predictor of salivary biomarker change than pain. There remain considerable challenges in identifying biomarkers that can be used in clinical practice to guide the measurement of nociception and treatment of pain. Standardization of methodology and researchers' greater awareness of the factors that affect salivary biomolecule concentrations are needed to improve our understanding of this field towards creating a clinically relevant body of evidence.

Salivary metabolomic biomarkers for non-invasive lung cancer detection.

Identifying novel biomarkers for early detection of lung cancer is crucial. Non-invasively available saliva is an ideal biofluid for biomarker exploration; however, the rationale underlying biomarker detection from organs distal to the oral cavity in saliva requires clarification. Therefore, we analyzed metabolomic profiles of cancer tissues compared with those of adjacent non-cancerous tissues, as well as plasma and saliva samples collected from patients with lung cancer (n = 109 pairs). Additionally, we analyzed plasma and saliva samples collected from control participants (n = 83 and 71, respectively). Capillary electrophoresis-mass spectrometry and liquid chromatography-mass spectrometry were performed to comprehensively quantify hydrophilic metabolites. Paired tissues were compared, revealing 53 significantly different metabolites. Plasma and saliva showed 44 and 40 significantly different metabolites, respectively, between patients and controls. Of these, 12 metabolites exhibited significant differences in all three comparisons and primarily belonged to the polyamine and amino acid pathways; N1-acetylspermidine exhibited the highest discrimination ability. A combination of 12 salivary metabolites was evaluated using a machine learning method to differentiate patients with lung cancer from controls. Salivary data were randomly split into training and validation datasets. Areas under the receiver operating characteristic curve were 0.744 for cross-validation using training data and 0.792 for validation data. This model exhibited a higher discrimination ability for N1-acetylspermidine than that for other metabolites. The probability of lung cancer calculated using this model was independent of most patient characteristics. These results suggest that consistently different salivary biomarkers in both plasma and lung tissues might facilitate non-invasive lung cancer screening.

Methylation analysis of DCC gene in saliva samples is an efficient method for non-invasive detection of superficial hypopharyngeal cancer.

BACKGROUND: Advances in upper gastrointestinal endoscopic technology have enabled early detection and treatment of hypopharyngeal cancer. However, in-depth pharyngeal observations require sedation and are invasive. It is important to establish a minimally invasive and simple evaluation method to identify high-risk patients. METHODS: Eighty-seven patients with superficial hypopharyngeal cancer and 51 healthy controls were recruited. We assessed the methylation status of DCC, PTGDR1, EDNRB, and ECAD, in tissue and saliva samples and verified the diagnostic accuracy by methylation analyses of their promoter regions using quantitative methylation-specific PCR. RESULTS: Significant differences between cancer and their surrounding non-cancerous tissues were observed in the methylation values of DCC (p = 0.003), EDNRB (p = 0.001), and ECAD (p = 0.043). Using receiver operating characteristic analyses of the methylation values in saliva samples, DCC showed the highest area under the curve values for the detection of superficial hypopharyngeal cancer (0.917, 95% confidence interval = 0.864-0.970), compared with those for EDNRB (0.680) and ECAD (0.639). When the cutoff for the methylation values of DCC was set at ≥0.163, the sensitivity to detect hypopharyngeal cancer was 82.8% and the specificity was 90.2%. CONCLUSIONS: DCC methylation in saliva samples could be a non-invasive and efficient tool for early detection of hypopharyngeal cancer in high-risk patients.

Coupling Miniaturized Stir Bar Sorptive Dispersive Microextraction to Needle-Based Electrospray Ionization Emitters for Mass Spectrometry: Determination of Tetrahydrocannabinol in Human Saliva as a Proof of Concept.

Direct coupling of sample preparation with mass spectrometry (MS) can speed up analysis, enabling faster decision-making. In such combinations, where the analysis time is mainly defined by the extraction procedure, magnetic dispersive solid-phase extraction emerges as a relevant technique because of its rapid workflow. The dispersion and retrieval of the magnetic sorbent are typically uncoupled stages, thus reducing the potential simplicity. Stir bar sorptive dispersive microextraction (SBSDME) is a novel technique that integrates both stages into a single device. Its miniaturization (mSBSDME) makes it more portable and compatible with low-availability samples. This article reports the direct combination of mSBSDME and MS using a needle-based electrospray ionization (NESI) emitter as the interface. This combination is applied to determine tetrahydrocannabinol in saliva samples, a relevant societal problem if the global consumption rates of cannabis are considered. The coupling requires only the transference of the magnet (containing the sorbent and the isolated analyte) from the mSBSDME to the hub of a hypodermic needle, where the online elution occurs. The application of 5 kV on the needle forms an electrospray on its tip, transferring the ionized analyte to the MS inlet. The excellent performance of mSBSDME-NESI-MS/MS relies on the sensitivity (limits of detection as low as 2.25 ng mL-1), the precision (relative standard deviation lower than 15%), and the accuracy (relative recoveries ranged from 87 to 127%) obtained. According to the results, the mSBSDME-NESI-MS/MS technique promises faster and more efficient chemical analysis in MS-based applications.

Proteomic Analysis of Human Saliva via Solid-Phase Microextraction Coupled with Liquid Chromatography-Mass Spectrometry.

Proteomics of human saliva samples was achieved for the first time via biocompatible solid-phase microextraction (bio-SPME) devices. Upon introduction of a porogen to a conventional C18 coating, porous C18/polyacrylonitrile (PAN) SPME blades were able to extract peptides up to 3.0 kDa and more peptides than commercial SPME blades. Following Trypsin digestion, salivary proteomic analysis was achieved via SPME-LC-MS/MS. Seven endogenous proteins were consistently identified in all saliva samples via bio-SPME. Taking advantage of this strategy, untargeted peptidomics was applied for the comparison of saliva samples between healthy and SARS-CoV-2 positive individuals. The results showed clear peptidomic differences between the viral and healthy saliva samples. This proof-of-concept study demonstrates the potential of bio-SPME-LC-MS/MS for peptidomics and proteomics in biomedical applications.

Microfluidic Electrochemical Integrated Sensor for Efficient and Sensitive Detection of Candida albicans.

Traditional methods for the detection of pathogenic bacteria are time-consuming, less efficient, and sensitive, which affects infection control and bungles illness. Therefore, developing a method to remedy these problems is very important in the clinic to diagnose the pathogenic diseases and guide the rational use of antibiotics. Here, microfluidic electrochemical integrated sensor (MEIS) has been investigated, functionally for rapid, efficient separation and sensitive detection of pathogenic bacteria. Three-dimensional macroporous PDMS and Au nanotube-based electrode are successfully assembled into the modeling microchip, playing the functions of "3D chaotic flow separator" and "electrochemical detector," respectively. The 3D chaotic flow separator enhances the turbulence of the fluid, achieving an excellent bacteria capture efficiency. Meanwhile, the electrochemical detector provides a quantitative signal through enzyme-linked immunoelectrochemistry with improved sensitivity. The microfluidic electrochemical integrated sensor could successfully isolate Candida albicans (C. albicans) in the range of 30-3,000,000 CFU in the saliva matrix with over 95% capture efficiency and sensitively detect C. albicans in 1 h in oral saliva samples. The integrated device demonstrates great potential in the diagnosis of oral candidiasis and is also applicable in the detection of other pathogenic bacteria.

Light-Controlled Regulation of Dual-Enzyme Properties in YbGd-Carbon Quantum Dots Nano-Hybrid for Advanced Biosensing.

Compared to nanozymes with single enzyme activity, those with multiple enzyme activities possess broader application potential due to their diversified enzymatic functionalities. However, the multienzyme nanozymes currently face challenges of interference among different enzymatic activities during practical applications. In this study, we report the synthesis of a light-responsive YbGd-carbon quantum dots nano-hybrid, termed YbGd-CDs, which exhibits controllable enzyme-mimicking activities. This light-responsive behavior enables selective control of the enzymatic activities. Under visible light irradiation, YbGd-CDs demonstrate robust oxidase-like activity. Conversely, under dark conditions, they primarily exhibit peroxidase-like activity. Leveraging the dual-enzyme-mimicking capabilities of YbGd-CDs, we developed colorimetric assays for sensitive detection of total antioxidant capacity (TAC) in both normal and cancer cells as well as d-amino acids in human saliva. This study not only advances the synthesis of carbon-based nanozymes but also highlights their potential in biosensing applications.

Portable Saliva Sensor Based on Dual Recognition Elements for Detection of Caries Pathogenic Bacteria.

Dental caries is one of the most common diseases affecting more than 2 billion people's health worldwide. In a clinical setting, it is challenging to predict and proactively guard against dental cavities prior to receiving a confirmed diagnosis. Streptococcus mutans (S. mutans) in saliva has been recognized as the main causative bacterial agent that causes dental caries. High sensitivity, good selectivity, and a wide detection range are incredibly important factors to affect S. mutans detection in practical applications. In this study, we present a portable saliva biosensor designed for the early detection of S. mutans with the potential to predict the occurrence of dental cavities. The biosensor was fabricated using a S. mutans-specific DNA aptamer and S. mutans-imprinted polymers. Methylene blue was utilized as a redox probe in the sensor to generate current signals for analysis. When S. mutans enters complementarily S. mutans cavities, it blocks electron transfer between methylene blue and the electrode, resulting in decreases in the reduction current signal. The signal variations are associated with S. mutans concentrations that are useful for quantitative analysis. The linear detection range of S. mutans is 102-109 cfu mL-1, which covers the critical concentration of high caries risk. The biosensor exhibited excellent selectivity toward S. mutans in the presence of other common oral bacteria. The biosensor's wide detection range, excellent selectivity, and low limit of detection (2.6 cfu mL-1) are attributed to the synergistic effect of aptamer and S. mutans-imprinted polymers. The sensor demonstrates the potential to prevent dental caries.

Surface Sialic Acid Detection of Small Extracellular Vesicles at the Single-Particle Level by Nano-Flow Cytometry.

Glycans, particularly sialic acids (SAs), play crucial roles in diverse biological processes. Despite their significance, analyzing specific glycans, such as sialic acids, on individual small extracellular vesicles (sEVs) has remained challenging due to the limited glycan capacity and substantial heterogeneity of sEVs. To tackle this issue, we introduce a chemical modification method of surface SAs on sEVs named PALEV-nFCM, which involves periodate oxidation and aniline-catalyzed oxime ligation (PAL), in conjunction with single-particle analysis using a laboratory-built nano-flow cytometer (nFCM). The specificity of the PALEV labeling method was validated using SA-decorated liposomes, enzymatic removal of terminal SA residues, lectin preblocking, and cellular treatment with an endogenous sialyltransferase inhibitor. Comprehensive mapping of SA distributions was conducted for sEVs derived from different sources, including conditioned cell culture medium (CCCM) of various cell lines, human saliva, and human red blood cells (RBCs). Notably, treatment with the calcium ionophore substantially increases the population of SA-positive RBC sEVs and enhances the SA content on individual RBC sEVs as well. nFCM provides a sensitive and versatile platform for mapping SAs of individual sEVs, which could significantly contribute to resolving the heterogeneity of sEVs and advancing the understanding of their glycosignature.

Targeted Phosphoproteomics of Human Saliva Extracellular Vesicles via Multiple Reaction Monitoring Cubed (MRM3).

Oral squamous cell carcinoma (OSCC) has become a global health problem due to its increasing incidence and high mortality rate. Early intervention through monitoring of the diagnostic biomarker levels during OSCC treatment is critical. Extracellular vesicles (EVs) are emerging surrogates in intercellular communication through transporting biomolecule cargo and have recently been identified as a potential source of biomarkers such as phosphoproteins for many diseases. Here, we developed a multiple reaction monitoring cubed (MRM3) method coupled with a novel sample preparation strategy, extracellular vesicles to phosphoproteins (EVTOP), to quantify phosphoproteins using a minimal amount of saliva (50 µL) samples from OSCC patients with high specificity and sensitivity. Our results established differential patterns in the phosphopeptide content of healthy, presurgery, and postsurgery OSCC patient groups. Notably, we discovered significantly increased salivary phosphorylated alpha-amylase (AMY) in the postsurgery group compared to the presurgery group. We hereby present the first targeted MS method with extremely high sensitivity for measuring endogenous phosphoproteins in human saliva EVs.

Predictive Analysis in Oral Cancer Immunotherapy: Profiling Dual PD-L1-Positive Extracellular Vesicle Subtypes with Step-Wedge Microfluidic Chips.

PD-L1-positive extracellular vesicles (PD-L1+ EVs) play a pivotal role as predictive biomarkers in cancer immunotherapy. These vesicles, originating from immune cells (I-PD-L1+ EVs) and tumor cells (T-PD-L1+ EVs), hold distinct clinical predictive values, emphasizing the importance of deeply differentiating the PD-L1+ EV subtypes for effective liquid biopsy analyses. However, current methods such as ELISA lack the ability to differentiate their cellular sources. In this study, a novel step-wedge microfluidic chip that combines magnetic microsphere separation with single-layer fluorescence counting is developed. This chip integrates magnetic microspheres modified with anti-PD-L1 antibodies and fluorescent nanoparticles targeting EpCAM (tumor cell marker) or CD45 (immunocyte marker), enabling simultaneous quantification and sensitive analysis of PD-L1+ EV subpopulations in oral squamous cell carcinoma (OSCC) patients' saliva without background interference. Analysis results indicate reduced levels of I-PD-L1+ EVs in OSCC patients compared to those in healthy individuals, with varying levels of heterogeneous PD-L1+ EVs observed among different patient groups. During immunotherapy, responders exhibit decreased levels of total PD-L1+ EVs and T-PD-L1+ EVs, accompanied by reduced levels of I-PD-L1+ EVs. Conversely, nonresponders show increased levels of I-PD-L1+ EVs. Utilizing the step-wedge microfluidic chip allows for simultaneous detection of PD-L1+ EV subtypes, facilitating the precise prediction of oral cancer immunotherapy outcomes.

Is Salivary Α-Amylase a Reliable Indicator of Psychological Status and Quality of Life in Patients with Oral Lichen Planus: a Case-Control Study.

BACKGROUND/AIMS: The objectives of our study were to determine salivary α-amylase activity (stress biomarker) and its association with psychological status and quality of life (QoL), disease duration and intensity of symptoms (pain/burning) in patients with OLP. METHODS: A total of 50 subjects participated in this case-control study: 30 patients with oral lichen planus (OLP); 20 control subjects. Unstimulated whole saliva (UWS) was collected between 9 and 10 am to avoid diurnal fluctuations. Psychological status was assessed using the Croatian validated version of the original Depression, Anxiety and Stress Scale (DASS-21). The impact of oral health on QoL was assessed using the Croatian version of the Oral Health Impact Profile Questionnaire (OHIP-CRO14). RESULTS: There was no statistically significant difference in salivary α-amylase activity between patients with OLP (N=30) and control subjects (N=20) (133813.3 vs. 166815.5 U/L, p=0.314; t-test). Depression, anxiety and stress showed no statistically significant difference between patients with OLP and control subjects (p=0.076, p=0.111, p=0.209; t-test). The patients with OLP had statistically significantly poorer QoL (total) compared to control subjects (p=0.004, t-test). There was a moderate positive correlation between symptom intensity (pain/burning) and poor QoL (total) (r=0.584, p<0.001), the OHIP-CRO14 dimension "physical pain" (r=0.661, p<0.001), "psychological impossibility" (r=0.555, p<0.01), "handicap" (r=0.546, p<0.01). CONCLUSION: Although salivary α-amylase showed no statistically significant difference between patients with OLP and control subjects, the patients with OLP had poorer psychological status (three times higher scores for depression and two times higher scores for anxiety) and poorer QoL compared to the control subjects. Recognising and treating mental disorders in patients with OLP is important in order to break the "vicious circle" and achieve a better QoL in these patients.