Features of the Metabolic Profile of Saliva in Lung Cancer and COPD: The Effect of Smoking Status

Enhanced Peroxidase-Mimic Catalytic Activity via Cerium Doping of Strontium-Based Metal-Organic Frameworks with Design of a Smartphone-Based Sensor for On-Site Salivary Total Antioxidant Capacity Detection in Lung Cancer Patients

The development of artificial nanozymes with superior catalytic performance and excellent stability has been a long-standing objective for chemists. The total antioxidant capacity (TAC) is one of the most important bioanalytical measures of oxidative stress in the body. The present work aims to develop a smartphone-assisted visual detection sensor using cerium-doped strontium-based metal-organic frameworks (Ce-SrMOFs) as peroxidase-like nanozymes for the rapid, low-cost, on-site detection of TAC. The pristine SrMOF functioned as a peroxidase nanozyme, and its enzymatic activity was enhanced after doping it with Ce(IV) ions because of the multivalent nature and synergistic impact of the heteroatoms. The Ce-SrMOFs were sensitive to the single electron transfer and hydrogen atom transfer processes, which implies that the Ce-SrMOFs can serve as an ideal nanozyme candidate for TAC analysis. The investigated mechanism revealed that •OH is the most active oxygen species for the peroxidase-like activity. The Ce-SrMOFs exhibited a strong affinity for 3,3',5,5'-tetramethylbenzidine (TMB) and H₂O₂, with K_m values of 0.082 and 0.427 mM, which are 5.29- and 8.67-fold lower than those of horseradish peroxidase (HRP), respectively. The Ce-SrMOFs were used for the detection of ascorbic acid, cysteine, and glutathione, with limits of detection of 44, 53, and 512 nM, respectively. The proposed method proved effective in measuring the TAC in saliva samples from lung cancer patients, thereby yielding results with satisfactory precision and accuracy.

Drying of bio-colloidal sessile droplets: Advances, applications, and perspectives

Drying of biologically-relevant sessile droplets, including passive systems such as DNA, proteins, plasma, and blood, as well as active microbial systems comprising bacterial and algal dispersions, has garnered considerable attention over the last decades. Distinct morphological patterns emerge when bio-colloids undergo evaporative drying, with significant potential in a wide range of biomedical applications, spanning bio-sensing, medical diagnostics, drug delivery, and antimicrobial resistance. Consequently, the prospects of novel and thrifty bio-medical toolkits based on drying bio-colloids have driven tremendous progress in the science of morphological patterns and advanced quantitative image-based analysis. This review presents a comprehensive overview of bio-colloidal droplets drying on solid substrates, focusing on the experimental progress during the last ten years. We provide a summary of the physical and material properties of relevant bio-colloids and link their native composition (constituent particles, solvent, and concentrations) to the patterns emerging due to drying. We specifically examined the drying patterns generated by passive bio-colloids (e.g., DNA, globular, fibrous, composite proteins, plasma, serum, blood, urine, tears, and saliva). This article highlights how the emerging morphological patterns are influenced by the nature of the biological entities and the solvent, micro- and global environmental conditions (temperature and relative humidity), and substrate attributes like wettability. Crucially, correlations between emergent patterns and the initial droplet compositions enable the detection of potential clinical abnormalities when compared with the patterns of drying droplets of healthy control samples, offering a blueprint for the diagnosis of the type and stage of a specific disease (or disorder). Recent experimental investigations of pattern formation in the bio-mimetic and salivary drying droplets in the context of COVID-19 are also presented. We further summarized the role of biologically active agents in the drying process, including bacteria, algae, spermatozoa, and nematodes, and discussed the coupling between self-propulsion and hydrodynamics during the drying process. We wrap up the review by highlighting the role of cross-scale in situ experimental techniques for quantifying sub-micron to micro-scale features and the critical role of cross-disciplinary approaches (e.g., experimental and image processing techniques with machine learning algorithms) to quantify and predict the drying-induced features. We conclude the review with a perspective on the next generation of research and applications based on drying droplets, ultimately enabling innovative solutions and quantitative tools to investigate this exciting interface of physics, biology, data sciences, and machine learning.

Effect of short-term use of FFP2 (N95) masks on the salivary metabolome of young healthy volunteers: a pilot study

The use of face masks has become an integral part of public life in the post-pandemic era. However, the understanding of the effect of wearing masks on physiology remains incomplete and is required for informing public health policies. For the first time, we report the effects of wearing FFP2 masks on the metabolic composition of saliva, a proximal matrix to breath, along with cardiopulmonary parameters. Un-induced saliva was collected from young (31.2 ± 6.3 years) healthy volunteers (n = 10) before and after wearing FFP2 (N95) masks for 30 minutes and analyzed using GCMS. The results showed that such short-term mask use did not cause any significant change in heart rate, pulse rate or SpO₂. Three independent data normalization approaches were used to analyze the changes in metabolomic signature. The individuality of the overall salivary metabotype was found to be unaffected by mask use. However, a trend of an increase in the salivary abundance of L-fucose, 5-aminovaleric acid, putrescine and phloretic acid was indicated irrespective of the method of data normalization. Quantitative analysis confirmed increases in concentrations of these metabolites in saliva of paired samples amid high inter-individual variability. The results showed that while there was no significant change in measured physiological parameters and individual salivary metabotypes, mask use was associated with correlated changes in these metabolites plausibly originating from altered microbial metabolic activity. These results might also explain the change in odour perception reported to be associated with mask use. Potential implications of these changes on mucosal health and immunity warrants further investigation to evolve more prudent mask use policies.

Salivary Metabolomics for Systemic Cancer Diagnosis: A Systematic Review

Cancers are the leading cause of death worldwide. The most common cancers include breast, lung, and colorectum. Salivary metabolome profiling is a novel non-invasive method in oncological diagnosis. This systematic review was designed to answer the question "Are salivary metabolites reliable for the diagnosis of systemic cancers?". Following the inclusion and exclusion criteria, nineteen studies were included (according to PRISMA statement guidelines). Changes in salivary metabolome were most commonly determined in patients with breast cancer, gastrointestinal cancers, and lung cancer. Most studies involved unstimulated whole saliva as the diagnostic material, evaluated by different spectroscopic methods. Among the found saliva metabolites, the alterations in the metabolic pathways of amino acids and polyamines were most frequently observed, which showed significant predictive values in oncological diagnostics. The most frequently encountered risks of bias were the absence of data regarding blinding, sample size justification, and randomisation. In conclusion, salivary metabolites seem to be potentially reliable for detecting the most common systemic cancers. However, further research is desirable to confirm these outcomes and to detect new potential metabolic biomarkers in saliva.

Effect of smoking on MUC1 expression in oral epithelial dysplasia, oral cancer, and irradiated oral epithelium

OBJECTIVES

The aim of this study was to assess the MUC1 expression in the oral epithelium of normal, oral epithelial dysplasia (OED), oral squamous cell carcinoma (OSCC), and irradiated oral epithelium (IROE) and its association with smoking habits in non-smokers and smokers.

DESIGN

Oral mucosal biopsies from controls, OED, OSCC, and IROE groups were obtained and categorized based on the smoking history as non-smokers, smoker I (25 pack-years), and smoker II (>25 pack-years). Immunohistochemical staining of MUC1 using human milk fat globule 1 (HMFG 1) antibody was performed, and the MUC1 score was calculated. The relation between MUC1 expression and clinicopathological findings was examined.

RESULTS

MUC1 staining of superficial oral epithelial cells with mild MUC1 score was detected in all control samples. The MUC1 staining extended from superficial to basal cell layer of oral epithelium with the increase in MUC1 score from moderate to strong in OED, OSCC, and IROE, and the difference was significant (p < 0.004, p < 0.002 and p < 0.004, respectively) compared to controls. A positive association between smoking and MUC1 score was observed within groups (p < 0.05).

CONCLUSION

The depolarization of MUC1 protein expression is associated with smoking habits in OED and OSCC. In the IROE, the radiation causes subcellular and molecular changes, observed as altered MUC1 expression and accelerated by smoking, furthermore, complicating the oral mucosal adaptation and progress to radiation-induced lesions as a delayed effect.