FTIR and Raman Spectroscopy Applied to Dementia Diagnosis Through Analysis of Biological Fluids

Evaluation of Peri-Implantitis through Fourier-Transform Infrared Spectroscopy on Saliva

BACKGROUND

Peri-implantitis is characterized as a pathological change in the tissues around dental implants. Fourier-transform infrared spectroscopy (FTIR) provides molecular information from optical phenomena observed by the vibration of molecules, which is used in biological studies to characterize changes and serves as a form of diagnosis.

AIMS

this case-control study evaluated the peri-implant disease by using FTIR spectroscopy with attenuated total reflectance in the fingerprint region.

METHODS

38 saliva samples were evaluated, 17 from the control group and 21 from the peri-implantitis group. Clinical data such as plaque index (PI), gingival index, probing depth (PS), and attachment level were assessed.

RESULTS

The results of clinical parameters showed a statistical difference between the two groups regarding an excess of the PI. In the FTIR-ATR analysis, the main components revealed vibrational modes of fatty acids, histidine, lipid esters, nucleic acids, and tryptophan, with the main molecules contributing to spectral discrimination. The five-component partial least-squares discriminant analysis classification model had an accuracy of 81%, showing differences between healthy and diseased implants.

CONCLUSION

the FTIR spectroscopy provides important molecular characteristics of the samples and the results in association with clinical data show the effectiveness of using this tool for diagnosing the disease.

C. Calado C. Early Mortality Prediction in Intensive Care Unit Patients Based on Serum Metabolomic Fingerprint

Predicting mortality in intensive care units (ICUs) is essential for timely interventions and efficient resource use, especially during pandemics like COVID-19, where high mortality persisted even after the state of emergency ended. Current mortality prediction methods remain limited, especially for critically ill ICU patients, due to their dynamic metabolic changes and heterogeneous pathophysiological processes. This study evaluated how the serum metabolomic fingerprint, acquired through Fourier-Transform Infrared (FTIR) spectroscopy, could support mortality prediction models in COVID-19 ICU patients. A preliminary univariate analysis of serum FTIR spectra revealed significant spectral differences between 21 discharged and 23 deceased patients; however, the most significant spectral bands did not yield high-performing predictive models. By applying a Fast-Correlation-Based Filter (FCBF) for feature selection of the spectra, a set of spectral bands spanning a broader range of molecular functional groups was identified, which enabled Naïve Bayes models with AUCs of 0.79, 0.97, and 0.98 for the first 48 h of ICU admission, seven days prior, and the day of the outcome, respectively, which are, in turn, defined as either death or discharge from the ICU. These findings suggest FTIR spectroscopy as a rapid, economical, and minimally invasive diagnostic tool, but further validation is needed in larger, more diverse cohorts.

Development of SERS Active Nanoprobe for Selective Adsorption and Detection of Alzheimer's Disease Biomarkers Based on Molecular Docking

Purpose

Development of SERS-based Raman nanoprobes can detect the misfolding of Amyloid beta (Aβ) 42 peptides, making them a viable diagnostic technique for Alzheimer's disease (AD). The detection and imaging of amyloid peptides and fibrils are expected to help in the early identification of AD.

Methods

Here, we propose a fast, easy-to-use, and simple scheme based on the selective adsorption of Aβ42 molecules on SERS active gold nanoprobe (RB-AuNPs) of diameter 29 ± 3 nm for Detection of Alzheimer's Disease Biomarkers. Binding with the peptides results in a spectrum shift, which correlates with the target peptide. We also demonstrated the possibility of using silver nanoparticles (AgNPs) as precursors for the preparation of a SERS active nanoprobe with carbocyanine (CC) dye and AgNPs known as silver nanoprobe (CC-AgNPs) of diameter 25 ± 4 nm.

Results

RB-AuNPs probe binding with the peptides results in a spectrum shift, which correlates with the target peptide. Arginine peak appears after the conjugation confirms the binding of Aβ 42 with the nanoprobe. Tyrosine peaks appear after conjugated Aβ42 with CC-AgNPs providing binding of the peptide with the probe. The nanoprobe produced a strong, stable SERS signal. Further molecular docking was utilized to analyse the interaction and propose a structural hypothesis for the process of binding the nanoprobe to Aβ42 and Tau protein.

Conclusion

This peptide-probe interaction provides a general enhancement factor and the molecular structure of the misfolded peptides. Secondary structural information may be obtained at the molecular level for specific residues owing to isotope shifts in the Raman spectra. Conjugation of the nanoprobe with Aβ42 selectively detected AD in bodily fluids. The proposed nanoprobes can be easily applied to the detection of Aβ plaques in blood, saliva, and sweat samples.

A Study of the Association between Primary Oral Pathologies (Dental Caries and Periodontal Diseases) Using Synchrotron Molecular FTIR Spectroscopy in View of the Patient's Personalized Clinical Picture (Demographics and Anamnesis)

In this exploratory study, we searched for associations between the two most common diseases of the oral cavity-dental caries and periodontal diseases-taking into account additional factors, such as personalized clinical pictures (the individual risk factors of the patient), based on the method of a multivariate data analysis of the molecular changes in the composition of human gingival crevicular fluid (GCF). For this purpose, a set of synchrotron Fourier-transform infrared spectroscopy (FTIR) spectra of gingival crevicular fluid samples from patients with different demographics, levels of dental caries development and periodontal diseases, and the presence/absence of concomitant chronic diseases were obtained and analyzed. Using a set of techniques (v-, F-, Chi-square tests; a principal component analysis (PCA); and the hierarchical clustering of principal components (HCPCs)) implemented in the R package FactoMineR allowed us to assess the relationship between the principal components (PCs) and characteristics of the respondents. By identifying the features (vibrational modes in the FTIR spectra) that contribute most to the differentiation of the spectral dataset, and by taking into account the interrelationships between the patients' characteristics, we were able to match specific biological markers (specific molecular groups) to the two factors of interest-two types of oral pathologies. The results obtained show that the observed changes in the quantitative and qualitative composition of the modes in the infrared (IR) spectra of the GCF samples from patients with different dental caries developments and periodontal diseases present confirm the difficulty of identifying patient-specific spectral information. At the same time, different periodontal pathologies are more closely associated with other characteristics of the patients than the level of their caries development. The multivariate analysis performed on the spectral dataset indicates the need to take into account not only the co-occurrence of oral diseases, but also some other factors. The lack of this consideration (typical in lots of studies in this area) may lead to misinterpretations and consequently to a loss of data when searching for biological markers of certain oral diseases.

FTIR Spectroscopy and Blood-Derived Extracellular Vesicles Duo in Alzheimer's Disease

Background

Alzheimer's disease (AD) diagnosis is difficult, and new accurate tools based on peripheral biofluids are urgently needed. Extracellular vesicles (EVs) emerged as a valuable source of biomarker profiles for AD, since their cargo is disease-specific and these can be easily isolated from easily accessible biofluids, as blood. Fourier Transform Infrared (FTIR) spectroscopy can be employed to analyze EVs and obtain the spectroscopic profiles from different regions of the spectra, simultaneously characterizing carbohydrates, nucleic acids, proteins, and lipids.

Objective

The aim of this study was to identify blood-derived EVs (bdEVs) spectroscopic signatures with AD discriminatory potential.

Methods

Herein, FTIR spectra of bdEVs from two biofluids (serum and plasma) and distinct sets of Controls and AD cases were acquired, and EVs' spectra analyzed.

Results

Analysis of bdEVs second derivative peaks area revealed differences between Controls and AD cases in distinct spectra regions, assigned to carbohydrates and nucleic acids, amides, and lipids.

Conclusions

EVs' spectroscopic profiles presented AD discriminatory value, supporting the use of bdEVs combined with FTIR as a screening or complementary tool for AD diagnosis.

Toward Reagent-Free Discrimination of Alzheimer's Disease Using Blood Plasma Spectral Digital Biomarkers and Machine Learning

BACKGROUND

Alzheimer's disease (AD) is the most prevalent neurodegenerative disease. The detection of early-stage AD is particularly desirable because it would allow early intervention. However, a minimally invasive, low-cost, and accurate discrimination or diagnostic method for AD is especially difficult in the earliest stage of AD.

OBJECTIVE

The aim of this research is to discover blood plasma spectral digital biomarkers of AD, develop a novel intelligent method for the discrimination of AD and accelerate the translation of Fourier transform infrared (FTIR) spectral-based disease discrimination methods from the laboratory to clinical practice.

METHODS

Since vibration spectroscopy can provide the structure and chemical composition information of biological samples at the molecular level, we investigated the potential of FTIR spectral biomarkers of blood plasma to differentiate between AD patients and healthy controls. Combined with machine learning technology, we designed a hierarchical discrimination system that provides reagent-free and accurate AD discrimination based on blood plasma spectral digital biomarkers of AD.

RESULTS

Accurate segregation between AD patients and healthy controls was achieved with 89.3% sensitivity and 85.7% specificity for early-stage AD patients, 92.8% sensitivity and 87.5% specificity for middle-stage AD patients, and 100% sensitivity and 100% specificity for late-stage AD patients.

CONCLUSIONS

Our results show that blood plasma spectral digital biomarkers hold great promise as discrimination markers of AD, indicating the potential for the development of an inexpensive, reagent-free, and less laborious clinical test. As a result, our research outcome will accelerate the clinical application of spectral digital biomarkers and machine learning.

Raman Spectroscopy on Brain Disorders: Transition from Fundamental Research to Clinical Applications

Brain disorders such as brain tumors and neurodegenerative diseases (NDs) are accompanied by chemical alterations in the tissues. Early diagnosis of these diseases will provide key benefits for patients and opportunities for preventive treatments. To detect these sophisticated diseases, various imaging modalities have been developed such as computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET). However, they provide inadequate molecule-specific information. In comparison, Raman spectroscopy (RS) is an analytical tool that provides rich information about molecular fingerprints. It is also inexpensive and rapid compared to CT, MRI, and PET. While intrinsic RS suffers from low yield, in recent years, through the adoption of Raman enhancement technologies and advanced data analysis approaches, RS has undergone significant advancements in its ability to probe biological tissues, including the brain. This review discusses recent clinical and biomedical applications of RS and related techniques applicable to brain tumors and NDs.

Plasma versus Serum Analysis by FTIR Spectroscopy to Capture the Human Physiological State

Fourier Transform InfraRed spectroscopy of serum and plasma has been highly explored for medical diagnosis, due to its general simplicity, and high sensitivity and specificity. To evaluate the plasma and serum molecular fingerprint, as obtained by FTIR spectroscopy, to acquire the system metabolic state, serum and plasma spectra were compared to characterize the metabolic state of 30 human volunteers, between 90 days consumption of green tea extract rich in Epigallocatechin-3-gallate (EGCG). Both plasma and serum spectra enabled the high impact of EGCG consumption on the biofluid spectra to be observed, as analyzed by the spectra principal component analysis, hierarchical-cluster analysis, and univariate data analysis. Plasma spectra resulted in the prediction of EGCG consumption with a slightly higher specificity, accuracy, and precision, also pointing to a higher number of significant spectral bands that were different between the 90 days period. Despite this, the lipid regions of the serum spectra were more affected by EGCG consumption than the corresponding plasma spectra. Therefore, in general, if no specific compound analysis is highlighted, plasma is in general the advised biofluid to capture by FTIR spectroscopy the general metabolic state. If the lipid content of the biofluid is relevant, serum spectra could present some advantages over plasma spectra.

An Emerging Strategy for Muscle Evanescent Trauma Discrimination by Spectroscopy and Chemometrics

Trauma is one of the most common conditions in the biomedical field. It is important to identify it quickly and accurately. However, when evanescent trauma occurs, it presents a great challenge to professionals. There are few reports on the establishment of a rapid and accurate trauma identification and prediction model. In this study, Fourier transform infrared spectroscopy (FTIR) and microscopic spectroscopy (micro-IR) combined with chemometrics were used to establish prediction models for the rapid identification of muscle trauma in humans and rats. The results of the average spectrum, principal component analysis (PCA) and loading maps showed that the differences between the rat muscle trauma group and the rat control group were mainly related to biological macromolecules, such as proteins, nucleic acids and carbohydrates. The differences between the human muscle trauma group and the human control group were mainly related to proteins, polysaccharides, phospholipids and phosphates. Then, a partial least squares discriminant analysis (PLS-DA) was used to evaluate the classification ability of the training and test datasets. The classification accuracies were 99.10% and 93.69%, respectively. Moreover, a trauma classification and recognition model of human muscle tissue was constructed, and a good classification effect was obtained. The classification accuracies were 99.52% and 91.95%. In conclusion, spectroscopy and stoichiometry have the advantages of being rapid, accurate and objective and of having high resolution and a strong recognition ability, and they are emerging strategies for the identification of evanescent trauma. In addition, the combination of spectroscopy and stoichiometry has great potential in the application of medicine and criminal law under practical conditions.

Design and Development of a Bimodal Optical Instrument for Simultaneous Vibrational Spectroscopy Measurements

Vibrational spectroscopy techniques are widely used in analytical chemistry, physics and biology. The most prominent techniques are Raman and Fourier-transform infrared spectroscopy (FTIR). Combining both techniques delivers complementary information of the test sample. We present the design, construction, and calibration of a novel bimodal spectroscopy system featuring both Raman and infrared measurements simultaneously on the same sample without mutual interference. The optomechanical design provides a modular flexible system for solid and liquid samples and different configurations for Raman. As a novel feature, the Raman module can be operated off-axis for optical sectioning. The calibrated system demonstrates high sensitivity, precision, and resolution for simultaneous operation of both techniques and shows excellent calibration curves with coefficients of determination greater than 0.96. We demonstrate the ability to simultaneously measure Raman and infrared spectra of complex biological material using bovine serum albumin. The performance competes with commercial systems; moreover, it presents the additional advantage of simultaneously operating Raman and infrared techniques. To the best of our knowledge, it is the first demonstration of a combined Raman-infrared system that can analyze the same sample volume and obtain optically sectioned Raman signals. Additionally, quantitative comparison of confocality of backscattering micro-Raman and off-axis Raman was performed for the first time.

High Resolution Magic Angle Spinning Proton NMR Study of Alzheimer's Disease with Mouse Models

Alzheimer's disease (AD) is a crippling condition that affects millions of elderly adults each year, yet there remains a serious need for improved methods of diagnosis. Metabolomic analysis has been proposed as a potential methodology to better investigate and understand the progression of this disease; however, studies of human brain tissue metabolomics are challenging, due to sample limitations and ethical considerations. Comprehensive comparisons of imaging measurements in animal models to identify similarities and differences between aging- and AD-associated metabolic changes should thus be tested and validated for future human non-invasive studies. In this paper, we present the results of our highresolution magic angle spinning (HRMAS) nuclear magnetic resonance (NMR) studies of AD and wild-type (WT) mouse models, based on animal age, brain regions, including cortex vs. hippocampus, and disease status. Our findings suggest the ability of HRMAS NMR to differentiate between AD and WT mice using brain metabolomics, which potentially can be implemented in in vivo evaluations.

Novel fusion peptides deliver exosomes to modify injectable thermo-sensitive hydrogels for bone regeneration

Injectable thermo-sensitive hydrogels composed of small intestinal submucosa (SIS) with exosomes derived from bone marrow mesenchymal stem cells (BMSCs) are desired for bone regeneration. However, poor mechanical properties limit the clinical application of SIS hydrogels. Herein, the mechanical properties of SIS hydrogels incorporated with 3-(3,4-dihydroxyphenyl) propionic acid (CA) are assessed. The results show that the mechanical properties of SIS hydrogels are improved. In addition, the retention and stability of exosomes over time at the defect site are also challenges. Fusion peptides are designed by connecting collagen-binding domines (CBDs) of collagen type I/III with exosomal capture peptides CP05 (CRHSQMTVTSRL) directly or via rigid linkers (EAAAK). In vitro experiments demonstrate that fusion peptides are contribute to promoting the positive effect of exosomes on osteogenic differentiation of BMSCs. Meanwhile, the results of hydrogels combining exosomes and fusion peptides in the treatment of rat skull defect models reveal that fusion peptides could enhance the retention and stability of exosomes, thereby strengthen the therapeutic effect for skull defects. Therefore, SIS hydrogels with CA modified by fusion peptides and exosomes appear to be a promising strategy in bone regenerative medicine.

A New Look into Cancer-A Review on the Contribution of Vibrational Spectroscopy on Early Diagnosis and Surgery Guidance

Simple Summary

Cancer is a leading cause of death worldwide, with the detection of the disease in its early stages, as well as a correct assessment of the tumour margins, being paramount for a successful recovery. While breast cancer is one of most common types of cancer, head and neck cancer is one of the types of cancer with a lower prognosis and poor aesthetic results. Vibrational spectroscopy detects molecular vibrations, being sensitive to different sample compositions, even when the difference was slight. The use of spectroscopy in biomedicine has been extensively explored, since it allows a broader assessment of the biochemical fingerprint of several diseases. This literature review covers the most recent advances in breast and head and neck cancer early diagnosis and intraoperative margin assessment, through Raman and Fourier transform infrared spectroscopies. The rising field of spectral histopathology was also approached. The authors aimed at expounding in a more concise and simple way the challenges faced by clinicians and how vibrational spectroscopy has evolved to respond to those needs for the two types of cancer with the highest potential for improvement regarding an early diagnosis, surgical margin assessment and histopathology.

Abstract

In 2020, approximately 10 million people died of cancer, rendering this disease the second leading cause of death worldwide. Detecting cancer in its early stages is paramount for patients’ prognosis and survival. Hence, the scientific and medical communities are engaged in improving both therapeutic strategies and diagnostic methodologies, beyond prevention. Optical vibrational spectroscopy has been shown to be an ideal diagnostic method for early cancer diagnosis and surgical margins assessment, as a complement to histopathological analysis. Being highly sensitive, non-invasive and capable of real-time molecular imaging, Raman and Fourier transform infrared (FTIR) spectroscopies give information on the biochemical profile of the tissue under analysis, detecting the metabolic differences between healthy and cancerous portions of the same sample. This constitutes tremendous progress in the field, since the cancer-prompted morphological alterations often occur after the biochemical imbalances in the oncogenic process. Therefore, the early cancer-associated metabolic changes are unnoticed by the histopathologist. Additionally, Raman and FTIR spectroscopies significantly reduce the subjectivity linked to cancer diagnosis. This review focuses on breast and head and neck cancers, their clinical needs and the progress made to date using vibrational spectroscopy as a diagnostic technique prior to surgical intervention and intraoperative margin assessment.

The Progress of Label-Free Optical Imaging in Alzheimer's Disease Screening and Diagnosis

As the major neurodegenerative disease of dementia, Alzheimer's disease (AD) has caused an enormous social and economic burden on society. Currently, AD has neither clear pathogenesis nor effective treatments. Positron emission tomography (PET) and magnetic resonance imaging (MRI) have been verified as potential tools for diagnosing and monitoring Alzheimer's disease. However, the high costs, low spatial resolution, and long acquisition time limit their broad clinical utilization. The gold standard of AD diagnosis routinely used in research is imaging AD biomarkers with dyes or other reagents, which are unsuitable for in vivo studies owing to their potential toxicity and prolonged and costly process of the U.S. Food and Drug Administration (FDA) approval for human use. Furthermore, these exogenous reagents might bring unwarranted interference to mechanistic studies, causing unreliable results. Several label-free optical imaging techniques, such as infrared spectroscopic imaging (IRSI), Raman spectroscopic imaging (RSI), optical coherence tomography (OCT), autofluorescence imaging (AFI), optical harmonic generation imaging (OHGI), etc., have been developed to circumvent this issue and made it possible to offer an accurate and detailed analysis of AD biomarkers. In this review, we present the emerging label-free optical imaging techniques and their applications in AD, along with their potential and challenges in AD diagnosis.

Isotope-Edited Amide II Mode: A New Label for Site-Specific Vibrational Spectroscopy

Vibrational spectroscopy is a powerful tool used to analyze biological and chemical samples. However, in proteins, the most predominant peaks that arise from the backbone amide groups overlap one another, hampering site-specific analyses. Isotope editing has provided a robust, noninvasive approach to overcome this hurdle. In particular, the 1-¹³C═¹⁶O and 1-¹³C═¹⁸O labels that shift the amide I vibrational mode have enabled 1D- and 2D-IR spectroscopy to characterize proteins with excellent site-specific resolution. Herein, we expand the vibrational spectroscopy toolkit appreciably by introducing the 1-¹³C[Formula: see text]¹⁵N probe at specific locations along the protein backbone. A new, isotopically edited amide II peak is observed clearly in the spectra despite the presence of unlabeled modes arising from the rest of the protein. The experimentally determined shift of -30 cm^-1 is reproduced by DFT calculations providing further credence to the mode assignment. Since the amide II mode arises from different elements than the amide I mode, it affords molecular insights that are both distinct and complementary. Moreover, multiple labeling schemes may be used simultaneously, enhancing vibrational spectroscopy's ability to provide detailed molecular insights.

Potential of FTIR Spectroscopy Applied to Exosomes for Alzheimer's Disease Discrimination: A Pilot Study

Alzheimer's disease (AD) diagnosis is based on psychological and imaging tests but can also include monitoring cerebrospinal fluid (CSF) biomarkers. However, CSF based-neurochemical approaches are expensive and invasive, limiting their use to well-equipped settings. In contrast, blood-based biomarkers are minimally invasive, cost-effective, and a widely accessible alternative. Blood-derived exosomes have recently emerged as a reliable AD biomarker source, carrying disease-specific cargo. Fourier-transformed infrared (FTIR) spectroscopy meets the criteria for an ideal diagnostic methodology since it is rapid, easy to implement, and has high reproducibility. This metabolome-based technique is useful for diagnosing a broad range of diseases, although to our knowledge, no reports for FTIR spectroscopy applied to exosomes in AD exist. In this ground-breaking pilot study, FTIR spectra of serum and serum-derived exosomes from two independent cohorts were acquired and analyzed using multivariate analysis. The regional UA-cohort includes 9 individuals, clinically diagnosed with AD, mean age of 78.7 years old; and the UMG-cohort comprises 12 individuals, clinically diagnosed with AD (based on molecular and/or imaging data), mean age of 73.2 years old. Unsupervised principal component analysis of FTIR spectra of serum-derived exosomes revealed higher discriminatory value for AD cases when compared to serum as a whole. Consistently, the partial least-squares analysis revealed that serum-derived exosomes present higher correlations than serum. In addition, the second derivative peak area calculation also revealed significant differences among Controls and AD cases. The results obtained suggest that this methodology can discriminate cases from Controls and thus be potential useful to assist in AD clinical diagnosis.

Fourier-Transform Infrared Spectroscopy as a Discriminatory Tool for Myotonic Dystrophy Type 1 Metabolism: A Pilot Study

Myotonic dystrophy type 1 (DM1) is a hereditary disease characterized by progressive distal muscle weakness and myotonia. Patients with DM1 have abnormal lipid metabolism and a high propensity to develop a metabolic syndrome in comparison to the general population. It follows that metabolome evaluation in these patients is crucial and may contribute to a better characterization and discrimination between DM1 disease phenotypes and severities. Several experimental approaches are possible to carry out such an analysis; among them is Fourier-transform infrared spectroscopy (FTIR) which evaluates metabolic profiles by categorizing samples through their biochemical composition. In this study, FTIR spectra were acquired and analyzed using multivariate analysis (Principal Component Analysis) using skin DM1 patient-derived fibroblasts and controls. The results obtained showed a clear discrimination between both DM1-derived fibroblasts with different CTG repeat length and with the age of disease onset; this was evident given the distinct metabolic profiles obtained for the two groups. Discrimination could be attributed mainly to the altered lipid metabolism and proteins in the 1800–1500 cm⁻¹ region. These results suggest that FTIR spectroscopy is a valuable tool to discriminate both DM1-derived fibroblasts with different CTG length and age of onset and to study the metabolomic profile of patients with DM1.

[Spectroscopic studies of the molecular composition of the dentinal and gingival fluids and their diagnostic potential for preventive screening of dentin caries]

PURPOSE OF THE STUDY

The aim of the work is a spectroscopic investigation and comparison of the molecular composition of dentine and gingival fluids as well as of their diagnostic potential for the preventive screening of dentin caries.

MATERIAL AND METHODS

Applying infrared spectroscopy including synchrotron radiation the samples of biological fluids taken from the oral cavity (dentine fluid, fluid from the gingival sulcus and blood) were studied for the patients with the progressive dentine caries. The part of this research was undertaken with the infrared microspectroscopy beamline at the Australian Synchrotron.

RESULTS

Dentine and gingival fluids were shown to have no less complicated composition than the blood serum. Having all this in mind, in spite that these two fluids are derivatives of the blood serum, and a majority of the molecular groups observed in all of the three fluids can be detected in their IR-spectra, it follows that there is a number of signature modes that are in fact present in the IR spectra of only dentine and gingival fluids. This fact indicates at the molecular exchange between them under certain conditions. It means the high diagnostic potential in the study of the pathologic processes occurring in the oral fluid of a human. We have observed and fixed an increase of thiocyanates and esters in the samples of both dentine and gingival fluids under the development of dentin caries.

CONCLUSION

Utilization of the gingival fluid for screening taking into account that its sampling is not such a complicated challenge as dentine fluid sampling will promote a transition to the personalized medicine, the development of high-technology healthcare and technology of the health preservation as a whole.

Changes in γH2AX and H4K16ac levels are involved in the biochemical response to a competitive soccer match in adolescent players

The aim of this study was to examine novel putative markers of the response to the competitive soccer match in adolescent players, such as changes in global levels of γH2AX and H4K16ac in the chromatin of peripheral mononuclear blood cells (PMBCs) and a Fourier-transform infrared spectroscopy (FTIR)-based biochemical fingerprint of serum. These characteristics were examined with reference to the physiological and metabolic aspects of this response. Immediately post-match we noticed: (1) a systemic inflammatory response, manifesting as peaks in leukocyte count and changes in concentrations of IL-6, TNFα, and cortisol; (2) a peak in plasma lactate; (3) onset of oxidative stress, manifesting as a decline in GSH/GSSG; (4) onset of muscle injury, reflected in an increase in CK activity. Twenty-four hours post-match the decrease in GSH/GSSG was accompanied by accumulation of MDA and 8-OHdG, macromolecule oxidation end-products, and an increase in CK activity. No changes in SOD1 or GPX1 levels were found. Repeated measures correlation revealed several associations between the investigated biomarkers. The FTIR analysis revealed that the match had the greatest impact on serum lipid profile immediately post-game. In turn, increases in γH2AX and H4K16ac levels at 24 h post-match indicated activation of a DNA repair pathway.

Potential of infrared microscopy to differentiate between dementia with Lewy bodies and Alzheimer's diseases using peripheral blood samples and machine learning algorithms

SIGNIFICANCE

Accurate and objective identification of Alzheimer's disease (AD) and dementia with Lewy bodies (DLB) is of major clinical importance due to the current lack of low-cost and noninvasive diagnostic tools to differentiate between the two. Developing an approach for such identification can have a great impact in the field of dementia diseases as it would offer physicians a routine objective test to support their diagnoses. The problem is especially acute because these two dementias have some common symptoms and characteristics, which can lead to misdiagnosis of DLB as AD and vice versa, mainly at their early stages.

AIM

The aim is to evaluate the potential of mid-infrared (IR) spectroscopy in tandem with machine learning algorithms as a sensitive method to detect minor changes in the biochemical structures that accompany the development of AD and DLB based on a simple peripheral blood test, thus improving the diagnostic accuracy of differentiation between DLB and AD.

APPROACH

IR microspectroscopy was used to examine white blood cells and plasma isolated from 56 individuals: 26 controls, 20 AD patients, and 10 DLB patients. The measured spectra were analyzed via machine learning.

RESULTS

Our encouraging results show that it is possible to differentiate between dementia (AD and DLB) and controls with an ∼86  %   success rate and between DLB and AD patients with a success rate of better than 93%.

CONCLUSIONS

The success of this method makes it possible to suggest a new, simple, and powerful tool for the mental health professional, with the potential to improve the reliability and objectivity of diagnoses of both AD and DLB.

Identification of new spectral signatures from hepatitis C virus infected human sera

Hepatitis C virus (HCV) infection is one of the leading causes of morbidity and mortality worldwide. Mortality linked with HCV infection can be lowered with effective and prompt diagnosis in early stages of infection. In this study potential of Raman spectroscopy to differentiate between healthy and HCV infected serum samples was investigated. Clear differences were observed in the Raman spectra of HCV infected and healthy sera samples. Using the analysis of variance (ANOVA) and t-test (p < 0.001) on Raman spectra of diseased and healthy samples, we observed eleven unique Raman bands at 676, 825, 853, 936, 1029, 1105, 1155, 1305, 1620, 1654 and 1757 cm^-1 associated with only HCV infected sera and have not been reported in earlier studies. In addition, six Raman bands at 556, 585, 716, 815, 1273 and 1142 cm^-1were observed in healthy sera only. Three Raman bands at 1330, 1526 and 1572 cm^-1 were observed in both type of samples but their intensity was drastically reduced in diseased samples. Various multivariate analysis techniques were employed to demonstrate the robustness of the results. We employed multivariate and unsupervised principal component analysis (PCA) in conjunction with supervised classification linear discriminant analysis (LDA), using ten-fold jackknife cross-validation, in order to develop effective diagnostic algorithm technique (PCA-LDA). Our PCA-LDA model yielded sufficient sensitivity and specificity i.e. correctly identified all infected samples included in this study. Ours results indicate that these unique Raman bands have the potential to be used as biomarkers for optical diagnosis of HCV infection.

Differential Molecular Signature of Human Saliva Using ATR-FTIR Spectroscopy for Chronic Kidney Disease Diagnosis

Abstract The symptoms of chronic kidney disease (CKD) are often not specific or absent in the early stages of this illness. Therefore, there is a demand for developing low cost, non-invasive and highly accurate platforms for CKD diagnostics. We hypothesized that the level of specifics salivary components changes when CKD is emplace, which could be clinically used to discriminate CKD patients from healthy subjects. The present study aimed to compare salivary components between CKD patients and matched control subjects by using attenuated total reflection-Fourier Transform Infrared (ATR-FTIR) spectroscopy. The predictive power of salivary components was evaluated by receiver operating characteristic (ROC) curves. Several components were identified, and 4 of them showed different expression (p<0.05) between CKD and control subjects. Thiocyanate (SCN-, 2052 cm-1) and phospholipids/carbohydrates (924 cm-1) vibrational modes using original and second-derivative spectra by ATR-FTIR could potentially be used as salivary biomarkers to differentiate CKD than control subjects. The combination of original and second-derivative spectra by ATR-FTIR of 924 cm-1 vibrational modes could reach 92.8% sensitivity and 85.7% specificity for CKD detection. Despite, the limitation of our investigation, the acquired data indicates that salivary vibrational modes by ATR-FTIR platform should be further explored as an auxiliary diagnostic tool for CKD.

Mechanism investigation of ethosomes transdermal permeation

Ethosomes are widely used to promote transdermal permeation of both lipophilic and hydrophilic drugs, but the mechanism of interaction between the ethosomes and the skin remains unclear. In this work, it was exploded with several technologies and facilities. Firstly, physical techniques such as attenuated total reflectance fourier-transform infrared and laser confocal Raman were used and the results indicated that the phospholipids configuration of stratum corneum changes from steady state to unstable state with the treatment of ethosomes. Differential scanning calorimetry reflected the thermodynamics change in stratum corneum after treatment with ethosomes. The results revealed that the skin of Bama mini-pigs, which is similar to human skin, treated by ethosomes had a relatively low T_m and enthalpy. Scanning electron microscopy and transmission electron microscopy showed that the microstructure and ultrastructure of stratum corneum was not damaged by ethosomes treatment. Furthermore, confocal laser scanning microscopy revealed that lipid labeled ethosomes could penetrate the skin via stratum corneum mainly through intercellular route, while during the process of penetration, phospholipids were retained in the upper epidermis. Cell experiments confirmed that ethosomes were distributed mainly on the cell membrane. Further study showed that only the drug-loaded ethosomes increased the amount of permeated drug. The current study, for the first time, elucidated the mechanistic behavior of ethosomes in transdermal application from molecular configuration, thermodynamic properties, ultrastructure, fluorescent labeling and cellular study. It is anticipated that the approaches and results described in the present study will benefit for better design of drug-loaded ethosomes.

Spectroscopic signature of the pathological processes of carious dentine based on FTIR investigations of the oral biological fluids

The aim of our work is to find a spectroscopic signature of the pathological processes of carious dentine based on the investigations of the molecular composition of the oral biological fluids with the use of FTIR synchrotron techniques. This complex analysis of the obtained data shows that a number of signatures are present only in the spectra of dentine and gingival fluids from the patients developing caries of the deep dentine tissues. The detected features and complex analysis of the quantitative and qualitative data representing signatures of the development of oral cavity pathologies can enhance the quality of dental screening.

Blood-based molecular signature of Alzheimer's disease via spectroscopy and metabolomics

OBJECTIVES

With over 35 million cases worldwide, Alzheimer's disease (AD) represents the main cause of dementia. The differentiation of AD from other types of dementia is challenging and its early diagnosis is complicated. The established biomarkers are not only based on the invasive collection of cerebrospinal fluid, but also lack sufficient sensitivity and specificity. Therefore, much current effort is aimed at the identification of new biomarkers of AD in peripheral blood.

DESIGN AND METHODS

We focused on blood-based analyses using chiroptical spectroscopy (Raman optical activity, electronic circular dichroism) supplemented with conventional vibrational spectroscopy (infrared, Raman) and metabolomics (high-performance liquid chromatography with a high-resolution mass detection).

RESULTS

This unique approach enabled us to identify the spectral pattern of AD and variations in metabolite levels. Subsequent linear discriminant analysis of the spectral data resulted in differentiation between the AD patients and control subjects.

CONCLUSIONS

It may be stated that this less invasive approach has strong potential for the identification of disease-related changes within essential plasmatic biomolecules and metabolites.

Screening Younger Individuals in a Primary Care Setting Flags Putative Dementia Cases and Correlates Gastrointestinal Diseases with Poor Cognitive Performance

BACKGROUND/AIMS

Diagnosing dementia is challenging in many primary care settings, given the limited human resources and the lack of current diagnostic tools. With this in mind, a primary care-based cohort was established in the Aveiro district of Portugal.

METHODS

A total of 568 participants were evaluated using cognitive tests and APOE genotyping.

RESULTS

The findings revealed a dementia prevalence of 12%. A strong correlation between increasing Clinical Dementia Rating (CDR) scores and education was clearly evident. Other highly relevant risk factors were activities of daily living (ADL), instrumental ADL, aging, depression, gender, the APOE ε4 allele, and comorbidities (depression as well as gastrointestinal, osteoarticular, and neurodegenerative diseases). A hitherto unreported, significant correlation between gastrointestinal disease and high CDR score was clearly observable.

CONCLUSIONS

This study shows the merit of carrying out a dementia screening on younger subjects. Significantly, 71 subjects in the age group of 50-65 years were flagged for follow-up studies; furthermore, these cases with a potentially early onset of dementia were identified in a primary care setting.

Pathology-specific molecular profiles of saliva in patients with multiple dental caries-potential application for predictive, preventive and personalised medical services

BACKGROUND

Improving the quality of life is part of the global agenda. The focus is predominantly on prevention of socially significant diseases. Combating dental caries-related diseases is a top priority as it has a huge impact on people's social lives. Therefore, the purpose of the work was to study the changes in the molecular composition of saliva from subjects with multiple caries lesions using spectroscopic methods of analysis to identify potential tissue markers of caries development for predictive, preventive and personalised medical services.

OBJECTIVES AND METHODS

The molecular composition of mixed saliva (oral fluid) from subjects with and without multiple caries was analysed with the use of spectroscopic techniques, FTIR with synchrotron radiation for the excitation. The IR spectra of the oral fluid as well as the calculated mineral-organic, carbon-phosphate, Amide II/Amide I and protein/thiocyanate ratios were compared between subjects with and without multiple caries.

RESULTS

This complex analysis of the obtained experimental data determined that the molecular composition of the oral fluid from those with multiple caries differed from those without caries; the organic-mineral balance in the oral fluid of those with multiple caries shifted towards a reduction in the mineral complexes, accompanied by an increase in the organic component. The thiocyanate content increased more than twofold, accompanied by increased carboxyl groups of esters, lipids and carbohydrates.

CONCLUSION

The detected features in the IR spectra of mixed saliva as well as the calculated changes in the ratios between organic and inorganic components can be used as biomarkers of cariogenesis in the oral cavity, as a diagnostic criterion in the analysis of the oral fluid samples.

Application of Fourier transform infrared spectroscopy with chemometrics on postmortem interval estimation based on pericardial fluids

Postmortem interval (PMI) evaluation remains a challenge in the forensic community due to the lack of efficient methods. Studies have focused on chemical analysis of biofluids for PMI estimation; however, no reports using spectroscopic methods in pericardial fluid (PF) are available. In this study, Fourier transform infrared (FTIR) spectroscopy with attenuated total reflectance (ATR) accessory was applied to collect comprehensive biochemical information from rabbit PF at different PMIs. The PMI-dependent spectral signature was determined by two-dimensional (2D) correlation analysis. The partial least square (PLS) and nu-support vector machine (nu-SVM) models were then established based on the acquired spectral dataset. Spectral variables associated with amide I, amide II, COO-, C-H bending, and C-O or C-OH vibrations arising from proteins, polypeptides, amino acids and carbohydrates, respectively, were susceptible to PMI in 2D correlation analysis. Moreover, the nu-SVM model appeared to achieve a more satisfactory prediction than the PLS model in calibration; the reliability of both models was determined in an external validation set. The study shows the possibility of application of ATR-FTIR methods in postmortem interval estimation using PF samples.