Obesity alters upper aerodigestive physiology through changes in respiratory mechanics, upper airway stability, reflux burden, esophageal clearance, gastric emptying, and systemic inflammation. These changes may contribute to a myriad of voice, swallowing, and airway pathologies. This article examines the relationship between obesity and upper aerodigestive tract disorders, focusing on voice, swallowing, reflux, airway mechanics, perioperative/postoperative risks, and management relevant to laryngologists and comprehensive otolaryngologists alike.
The aim of this study was to assess the potential of FTIR spectroscopy for monitoring biochemical changes in serum samples of individuals with carotid atherosclerosis following surgical intervention. Principal Component Analysis (PCA) of FTIR spectra from serum samples reveals distinct biochemical patterns at different time points: pre-surgery, 24 h post-surgery, and 48 h post-surgery. Two spectral ranges, 800–1800 cm−1 and 2800–3000 cm−1, were analyzed. PCA demonstrated that pre-surgery samples can be clearly differentiated from those taken 24 and 48 h post-surgery. However, no significant distinction was found between the 24-hour and 48-hour post-surgery samples. For the 800–1800 cm−1 range, the first principal component (PC1) explained 77.49% of the variance, highlighting the molecular vibrations of lipids, proteins, and carbohydrates. In the 2800–3000 cm−1 range, PC1 accounted for 94.89% of the variance, primarily reflecting lipid-related vibrations. These findings indicate a clear separation between pre-surgery and post-surgery samples, with the most significant variance explained by PC1. Additionally, the Boruta algorithm identified a key spectral range between 1506 cm−1 and 1673 cm−1, critical for distinguishing the samples. Classification models, including k-Nearest Neighbors, Gradient Boosting, Support Vector Machine, and Neural Network, demonstrated excellent performance in differentiating pre-surgery and post-surgery samples. However, the models struggled to distinguish between the 24-hour and 48-hour post-surgery time points. This suggests that FTIR spectroscopy may be useful for monitoring post-surgery recovery in carotid artery atherosclerosis, although subtle changes in the biochemical profile are challenging to detect between 24 and 48 h post-surgery.
Attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR) provides information on the molecular composition and structure of samples. The use of ATR-FTIR was evaluated for biochemical analysis and taxonomic differentiation of entomopathogenic nematodes (EPNs). Spectra were obtained from a small sample (pellet) of a nematode population recovered from commercial EPN packages, which was placed directly on the ATR plate. Differences in signal intensity at multiple peaks associated with biomolecules critical to the survival of EPN (trehalose, glycogen, and triglyceride) were measured and visualized using Non-Metric Multidimensional Scaling (nMDS) and Principal Component Analysis (PCA). Statistically significant differences in peak signal intensity were observed between EPN species for each biochemical parameter, providing a basis for assessing the likelihood of their performance success in the field conditions. The present study also evaluated FTIR analysis of EPN for taxonomic differentiation. Results demonstrate that FTIR can be used to identify and differentiate Steinernema and Heterorhabditis genera/species, offering a potentially faster, less expensive alternative to molecular identification techniques. Ultimately, this study demonstrates the efficacy of ATR-FTIR as a reliable method for assessing the biochemical suitability of EPN products for field applications and differentiating between EPNs.
Endometrial cancer (EC) is increasingly prevalent worldwide, highlighting the need for non-invasive blood-based diagnostic triage tools. ATR-FTIR spectroscopy enables rapid, label-free biochemical profiling of plasma or serum for experimental cancer detection. To date, no systematic review or meta-analysis has evaluated the experimental performance of infrared spectroscopy for discriminating EC from non-cancer in blood-based samples. This study synthesizes available evidence to characterize the strength, consistency, and heterogeneity of the underlying spectroscopic signal across preclinical and proof-of-concept studies. MEDLINE, Web of Science, EMBASE, Scopus, Google Scholar, and CENTRAL were searched without language restrictions. Eligible studies evaluated ATR-FTIR spectroscopy of plasma or serum using histopathology as the reference standard. Pooled sensitivity, specificity, likelihood ratios, and diagnostic odds ratios were estimated using a bivariate random-effects model, with assessment of heterogeneity, threshold effects, and publication bias. Five case–control studies comprising 1376 participants were included. For plasma-based analyses, pooled sensitivity was 0.61 (95% CI: 0.59–0.68) and specificity was 0.73 (95% CI: 0.69–0.76), with a diagnostic odds ratio of 4.23 (95% CI: 3.33–5.37). For serum-based analyses, pooled sensitivity and specificity were both 0.62 (95% CI: 0.59–0.65), with a diagnostic odds ratio of 2.65 (95% CI: 2.16–3.25). Substantial heterogeneity and significant threshold effects were observed. Current evidence supports reproducible spectroscopic differences between EC and non-cancer blood samples under experimental conditions. However, methodological heterogeneity and retrospective case–control study designs limit clinical interpretability. These findings provide a benchmark for future prospective validation rather than immediate clinical application.
Innovations in Eustachian tube dysfunction (ETD) management are shifting care from symptom-based approaches toward precision, technology-integrated strategies. Advances in computational modeling, drug delivery systems (including hydrogels and nanoparticles), intranasal surfactants, and drug-eluting devices are expanding medical options. The potential role of biologics in type 2 inflammation and the effects of radiation and GLP-1 receptor agonists on ET function are under investigation. Emerging surgical approaches-such as permanent and biodegradable stents, shims, and injectable fillers-show promise but require validation. Artificial intelligence, robotics, telehealth, and remote monitoring are enhancing diagnosis, treatment precision, and longitudinal care, with significant progress anticipated in the coming decade.
Cancer diagnostic methods based on Raman spectroscopy are being actively investigated, and there is a strong need for simple approaches to amplify the intensity of Raman scattered light from biological fluids such as serum and urine, which contain only trace amounts of nucleic acids, proteins, amino acids, and other analytes together with highly autofluorescent background components. We evaluated two measurement methods. One was the needle method (NM), in which a laser irradiates a droplet of liquid sample held at the tip of a fine-diameter stainless-steel needle. The other was the quartz glass fiber sheet method (QSM), in which a quartz glass fiber sheet is imbued with a liquid sample, allowed to dry, and then irradiated at the sheet surface. Raman spectra of sodium benzoate, sodium sulfate, human serum, and human urine were recorded. For the model compounds, spectra obtained by QSM reproduced the Raman shifts of the solid state, whereas spectra of aqueous solutions measured by NM showed clear peak shifts, and the scattered-light intensity increased monotonically with the number of drops on the sheet. Based on these findings, we infer that the samples crystallize and become concentrated within the quartz glass fiber sheet, enabling acquisition of spectra with high scattered-light intensity even from low-concentration solutions. For human serum and urine, QSM increased the intensity of characteristic bands by up to about seven-fold compared with NM while preserving the spectral fingerprints. Our results indicate that a quartz glass fiber sheet is a practical low-background substrate for obtaining FT-Raman spectra of liquid biological samples whose components are present at low concentrations.
Surface-enhanced Raman spectroscopy (SERS) enables rapid, label-free bacterial fingerprinting, yet many machine-learning studies lack transparent evaluation protocols and interpretable feature analysis. This study presents a SERS-machine-learning evaluation framework for bacterial classification using a fixed-concentration ten-class Staphylococcus aureus dataset (100 spectra) and leak-free 60/20/20 train/validation/test partitions repeated across 15 random seeds. After Savitzky-Golay smoothing and standard normal variate normalization, spectra were analyzed in both full (384 variables) and cropped (400–1200 cm−1; 298 variables) representations. Linear discriminant analysis (LDA) served as the primary dense classifier, while stability-selection-based feature selection combined with LDA (StabSel-LDA) was evaluated as a sparse companion model with validation-tuned feature count K. LDA achieved near-ceiling clean performance (mean accuracy 0.970–0.973; macro-F1 0.966–0.969) and remained stable under additive noise, drift, and ±5 cm−1 spectral shifts (accuracy 0.953). StabSel-LDA reduced the feature set to 124–228 bands and produced reproducible band-selection profiles across seeds, but showed lower clean accuracy (0.940–0.943) and pronounced degradation under ±5 cm−1 shifts (0.760–0.783). These results support a role-separated deployment strategy in which LDA functions as the primary decision model, while StabSel-LDA provides a sparse companion for feature compression and interpretable spectral-band identification. The proposed framework offers a transparent approach for balancing classification performance, robustness assessment, and spectral interpretability in small SERS datasets.
Metabolic syndrome (MetS) is characterized by central adiposity, hypertension, dyslipidemia, insulin resistance, and chronic inflammation, conditions that alter lipid regulation in multiple tissues, including skin. Fatty acidbinding proteins, particularly epidermal fatty acid-binding protein (E-FABP, FABP5), have been proposed as potential biomarkers of these metabolic and cardiovascular alterations; however, their contribution in skin has not been studied using vibrational spectroscopy. This work aimed to evaluate whether Raman spectroscopy can detect epidermal FABP-associated molecular changes in skin during the development of MetS. Male Wistar rats were fed a high-fat diet for up to 52 weeks, and in vivo Raman spectra of abdominal skin were acquired at several time points. Raman band-intensity analysis, principal component analysis, and logistic regression classification were applied to identify biochemical differences between the control and metabolic syndrome groups. The Raman bands at 1002 cm 1 , 1050 cm-1 , and 1377 cm 1 , associated with E-FABP, showed time-dependent differences, with the most significant increase at 18 weeks and convergence between groups by 52 weeks. Based on this unique spectral feature, we developed a noninvasive Raman workflow capable of detecting E-FAPB directly in living tissue, as a potential Raman biomarker of MetS. The classification model achieved 79% accuracy with an area under the curve of 0.85. In summary, our findings indicate that Raman spectroscopy can detect E-FABP alterations in skin associated with MetS, supporting its potential as a non-invasive tool for early metabolic assessment.
Balloon dilation of the Eustachian tube has moved from an experimental concept to a mainstream option for selected adults with chronic obstructive Eustachian tube dysfunction that persists despite optimized medical management. Contemporary practice emphasizes careful phenotyping (obstructive vs patulous vs baro-challenge induced disease), correlation of symptoms with objective middle ear findings, and endoscopic evaluation of the nasopharyngeal orifice before intervention. Randomized trials and subsequent long-term follow-up demonstrate meaningful improvements in patient-reported symptoms and selected objective measures for appropriately chosen patients, with low rates of serious adverse events.
