The application of Fourier transform infrared microspectroscopy for the study of diseased central nervous system tissue

Exploration of macromolecular phenotype of human skeletal muscle in diabetes using infrared spectroscopy

Introduction

The global burden of diabetes mellitus is escalating, and more efficient investigative strategies are needed for a deeper understanding of underlying pathophysiological mechanisms. The crucial role of skeletal muscle in carbohydrate and lipid metabolism makes it one of the most susceptible tissues to diabetes-related metabolic disorders. In tissue studies, conventional histochemical methods have several technical limitations and have been shown to inadequately characterise the biomolecular phenotype of skeletal muscle to provide a holistic view of the pathologically altered proportions of macromolecular constituents.

Materials and methods

In this pilot study, we examined the composition of five different human skeletal muscles from male donors diagnosed with type 2 diabetes and non-diabetic controls. We analysed the lipid, glycogen, and collagen content in the muscles in a traditional manner with histochemical assays using different staining techniques. This served as a reference for comparison with the unconventional analysis of tissue composition using Fourier-transform infrared spectroscopy as an alternative methodological approach.

Results

A thorough chemometric post-processing of the infrared spectra using a multi-stage spectral decomposition allowed the simultaneous identification of various compositional details from a vibrational spectrum measured in a single experiment. We obtained multifaceted information about the proportions of the different macromolecular constituents of skeletal muscle, which even allowed us to distinguish protein constituents with different structural properties. The most important methodological steps for a comprehensive insight into muscle composition have thus been set and parameters identified that can be used for the comparison between healthy and diabetic muscles.

Conclusion

We have established a methodological framework based on vibrational spectroscopy for the detailed macromolecular analysis of human skeletal muscle that can effectively complement or may even serve as an alternative to histochemical assays. As this is a pilot study with relatively small sample sets, we remain cautious at this stage in drawing definitive conclusions about diabetes-related changes in skeletal muscle composition. However, the main focus and contribution of our work has been to provide an alternative, simple and efficient approach for this purpose. We are confident that we have achieved this goal and have brought our methodology to a level from which it can be successfully transferred to a large-scale study that allows the effects of diabetes on skeletal muscle composition and the interrelationships between the macromolecular tissue alterations due to diabetes to be investigated.

Prediction of type 1 diabetes with machine learning algorithms based on FTIR spectral data in peripheral blood mononuclear cells

The incidence of autoimmunity is increasing, to ensure timely and comprehensive treatment, there must be a diagnostic method or markers that would be available to the general public. Fourier-transform infrared spectroscopy (FTIR) is a relatively inexpensive and accurate method for determining metabolic fingerprint. The metabolism, molecular composition and function of blood cells vary according to individual physiological and pathological conditions. Thus, by obtaining autoimmune disease-specific metabolic fingerprint markers in peripheral blood mononuclear cells (PBMC) and subsequently using machine learning algorithms, it might be possible to create a tool that will allow the diagnosis of autoimmune diseases. In this preliminary study, it was found that the peak shift at 1545 cm-1 could be considered specific for autoimmune disease type 1 diabetes (T1D), while the shifts at 1070 and 1417 cm-1 could be more attributed to the autoimmune condition per se. The prediction of T1D, despite the small number of participants in the study, showed an inverse AUC = 0.33 ± 0.096, n = 15, indicating a stable trend in the prediction of T1D based on FTIR metabolic fingerprint data in the PBMC.

Roadmap for Postnatal Brain Maturation: Changes in Gray and White Matter Composition during Development Measured by Fourier Transformed Infrared Microspectroscopy

Key events in postnatal brain development, such as neuronal migration, synaptogenesis, and myelination, shape the adult brain. These events are reflected in changes in gray and white matter (GM and WM) occurring during this period. Therefore, precise knowledge of GM and WM composition in perinatal brain development is crucial to characterizing brain formation as well as the neurodevelopmental disruption observed in diseases such as autism and schizophrenia. In this study, we combined histochemical and immunohistochemical staining with biochemical and biophysical analyses using Fourier transform infrared (IR) microspectroscopy (μFTIR) to better understand the chemical changes during postnatal developmental myelination. For this purpose, we analyzed the GM and WM in the mouse brain and cerebellum (strain C57BL/6) from postnatal day 0 (P0) to day P28 and established presumed correlations between staining and IR data. IR spectra allowed the (i) quantification of lipid and protein content through the CH2/amide I ratio, (ii) determination of chemical characteristics of lipids, such as the presence of unsaturated bonds in the carbonate chain or carbonyls from ester groups in the polar head, and (iii) determination of the protein secondary structure (α-helix and intramolecular β-sheets). The results indicate that the increase in the CH2/amide I ratio calculated from the μFTIR data correlates well with lipid histochemical staining. IR data indicated a change in the lipid composition in WM since carbonyl and unsaturated olefinic groups do not increase when lipids accumulate during myelination. Our correlation analysis between IR data and immunohistochemical staining of myelin-associated proteins revealed that myelin oligodendrocyte protein correlated well with lipid accumulation, while myelin basic protein appeared before lipid modifications, which indicated that myelin-associated proteins and lipid deposition were not synchronic. These events were related to a decrease in the intramolecular β/α protein ratio. Our results indicate that lipids and proteins in WM substantially change their composition due to primary myelination, and according to results obtained from staining, these modifications are better described by lipid histochemical staining than by immunohistochemistry against myelin-related proteins. In conclusion, μFTIR can be a useful technique to study WM during perinatal development and provide detailed information about alterations in the chemical composition related to neurodevelopmental diseases.

Biomolecular alterations detected in multiple sclerosis skin fibroblasts using Fourier transform infrared spectroscopy

Multiple sclerosis (MS) is the leading cause of non-traumatic disability in young adults. New avenues are needed to help predict individuals at risk for developing MS and aid in diagnosis, prognosis, and outcome of therapeutic treatments. Previously, we showed that skin fibroblasts derived from patients with MS have altered signatures of cell stress and bioenergetics, which likely reflects changes in their protein, lipid, and biochemical profiles. Here, we used Fourier transform infrared (FTIR) spectroscopy to determine if the biochemical landscape of MS skin fibroblasts were altered when compared to age- and sex-matched controls (CTRL). More so, we sought to determine if FTIR spectroscopic signatures detected in MS skin fibroblasts are disease specific by comparing them to amyotrophic lateral sclerosis (ALS) skin fibroblasts. Spectral profiling of skin fibroblasts from MS individuals suggests significant alterations in lipid and protein organization and homeostasis, which may be affecting metabolic processes, cellular organization, and oxidation status. Sparse partial least squares-discriminant analysis of spectral profiles show that CTRL skin fibroblasts segregate well from diseased cells and that changes in MS and ALS may be unique. Differential changes in the spectral profile of CTRL, MS, and ALS cells support the development of FTIR spectroscopy to detect biomolecular modifications in patient-derived skin fibroblasts, which may eventually help establish novel peripheral biomarkers.

Rapid and accurate screening of cystic echinococcosis in sheep based on serum Fourier-transform infrared spectroscopy combined with machine learning algorithms

Cystic echinococcosis (CE) in sheep is a serious zoonotic parasitic disease caused by Echinococcus granulosus sensu stricto (s.s.). Presently, the screening technology for CE in sheep is time-consuming and inaccurate, and novel screening technology is urgently needed. In this work, we combined machine-learning algorithms with Fourier transform infrared (FT-IR) spectroscopy of serum to establish a quick and accurate screening approach for CE in sheep. Serum samples from 77 E. granulosus s.s.-infected sheep to 121 healthy control sheep were measured by FT-IR spectrometer. To optimize the classification accuracy of the serum FI-TR method for the E. granulosus s.s.-infected sheep and healthy control sheep, principal component analysis (PCA), linear discriminant analysis, and support vector machine (SVM) algorithms were used to analyze the data. Among all the bands, 1500-1700 cm^-1 band has the best classification effect; its diagnostic sensitivity, specificity, and accuracy of PCA-SVM were 100%, 95.74%, and 96.66%, respectively. The study showed that serum FT-IR spectroscopy combined with machine learning algorithms has great potential for rapid and accurate screening methods for the CE in sheep.

Accurate identification of traumatic lung injury (TLI) by ATR-FTIR spectroscopy combined with chemometrics

Traumatic lung injury (TLI), which is a common mechanical injury, is receiving increasing attention because of its serious hazards. In forensic practices, accurately identifying TLI is of great importance for investigations and case trials. The main goal of this research was to identify TLI utilizing attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy in combination with chemometrics. The macroscopic appearance of lung tissue showed that identifying TLI in lung tissue at the decomposition stage is not feasible by only visualization, and significant pulmonary hypostasis was observed in the lungs regardless of whether the lung tissue was injured. Average spectra and principal component analysis (PCA) suggested that the biochemical difference between injured lung tissue samples from the TLI group and noninjured lung tissue samples from the negative control group was mainly attributed to the different structures and contents of proteins. Partial least squares discriminant analysis (PLS-DA) was then utilized to identify TLI with an accuracy of 96.4% and 98.6% based on the training set and the test set, respectively. Next, we focused on samples that were misclassified in the model and proposed that the misclassification could be caused by the pulmonary hypostasis effect. Therefore, two additional PCA and PLS-DA models were created to identify the pulmonary hypostatic areas between the TLI group and the negative control group and the nonpulmonary hypostatic areas between the TLI group and the negative control group. The PCA results indicated that the biochemical difference between the two groups was still associated with proteins, and the two PLS-DA models achieved 100% accuracy based on both the training and test sets. This result indicated that when pulmonary hypostasis was considered and the lung tissue was divided into pulmonary hypostatic areas and nonpulmonary hypostatic areas for separate comparisons, TLI identification was achieved with a greater accuracy than that obtained when the two areas were combined. This research confirms that the combined application of ATR-FTIR spectroscopy and chemometrics can be utilized to accurately identify TLI.

Terahertz Waves Enhance the Permeability of Sodium Channels

With the help of molecular dynamics simulations and an artificial sodium channel model, we corroborated that the application of terahertz stimulation at a characteristic frequency can largely increase the permeability of the sodium channel by a factor of 33.6. The mechanism is that the carboxylate groups in the filter region transfer the absorbed terahertz photon energy to the sodium ions, which increase the ions’ kinetic energy; this results in breaking the hydrated hydrogen bonding network between the hydrosphere layer of the ions and the carboxylate groups, thereby increasing their diffusion and reducing the energy barrier for them to cross the channel. This study on terahertz-driven particle transmembrane transport offers new ideas for targeted therapy of channel diseases and for developing novel integrated engineering systems in energy conversion and storage.

Distinguishing Asphyxia from Sudden Cardiac Death as the Cause of Death from the Lung Tissues of Rats and Humans Using Fourier Transform Infrared Spectroscopy

The ability to determine asphyxia as a cause of death is important in forensic practice and helps us to judge whether a case is criminal. However, in some cases where the deceased has underlying heart disease, death by asphyxia cannot be determined by traditional autopsy and morphological observation under a microscope because there are no specific morphological features for either asphyxia or sudden cardiac death (SCD). Here, Fourier transform infrared (FTIR) spectroscopy was employed to distinguish asphyxia from SCD. A total of 40 lung tissues (collected at 0 h and 24 h postmortem) from 20 rats (10 died from asphyxia and 10 died from SCD) and 16 human lung tissues from 16 real cases were used for spectral data acquisition. After data preprocessing, 2675 spectra from rat lung tissues and 1526 spectra from human lung tissues were obtained for subsequent analysis. First, we found that there were biochemical differences in the rat lung tissues between the two causes of death by principal component analysis and partial least-squares discriminant analysis (PLS-DA), which were related to alterations in lipids, proteins, and nucleic acids. In addition, a PLS-DA classification model can be built to distinguish asphyxia from SCD. Second, based on the spectral data obtained from lung tissues allowed to decompose for 24 h, we could still distinguish asphyxia from SCD even when decomposition occurred in animal models. Nine important spectral features that contributed to the discrimination in the animal experiment were selected and further analyzed. Third, 7 of the 9 differential spectral features were also found to be significantly different in human lung tissues from 16 real cases. A support vector machine model was finally built by using the seven variables to distinguish asphyxia from SCD in the human samples. Compared with the linear PLS-DA model, its accuracy was significantly improved to 0.798, and the correct rate of determining the cause of death was 100%. This study shows the application potential of FTIR spectroscopy for exploring the subtle biochemical differences resulting from different death processes and determining the cause of death even after decomposition.

Investigation of bactericidal effect of a mid-infrared free electron laser on Escherichia coli

The rapid increase in the number of bacteria that are resistant to many commonly used antimicrobial agents and their global spread have become a major problem worldwide. In particular, for periodontal disease, which is a localized infection, there is a growing need for treatment methods that do not primarily involve antimicrobial agents, and antimicrobial photodynamic therapy (aPDT) is attracting attention. In this study, the bactericidal effects of a mid-infrared free electron laser (MIR-FEL) on E. coli were investigated as a basic study to examine the applicability of MIR-FELs, which can selectively excite molecular vibrations due to their wavelength tunability, to aPDT. The optimal irradiation wavelengths to be examined in this study were determined from the infrared spectrum of the bacteria, which was obtained using Fourier transform infrared spectroscopy. Five irradiation wavelengths (6.62, 6.88, 7.14, 8.09 and 9.26 µm) were selected from the FT-IR spectrum, and we found that the bactericidal effects at a wavelength of 6.62 µm were markedly stronger than those observed at the other wavelengths. At this wavelength corresponding to the Amide II band, the bacterial survival rate decreased significantly as the irradiation time increased. On the contrary, irradiation of a neodymium-doped yttrium aluminum garnet (Nd: YAG) laser at 1.06 µm exhibited no distinct bactericidal effect. No morphological changes were observed after MIR-FEL irradiation, suggesting that a bacterial organelle molecule may be the target of MIR-FEL irradiation, but the exact target was not identified. Furthermore, the temperature change induced in the culture medium by the laser irradiation was ± 1.5 °C at room temperature. These results suggest that the bactericidal effects of MIR-FEL are derived from photochemical reactions involving infrared photons, since E. coli is usually killed by heating it to 75 °C for 1 min or longer.

Application of FTIR Spectroscopy to Detect Changes in Skeletal Muscle Composition Due to Obesity with Insulin Resistance and STZ-Induced Diabetes

Age, obesity, and diabetes mellitus are pathophysiologically interconnected factors that significantly contribute to the global burden of non-communicable diseases. These metabolic conditions are associated with impaired insulin function, which disrupts the metabolism of carbohydrates, lipids, and proteins and can lead to structural and functional changes in skeletal muscle. Therefore, the alterations in the macromolecular composition of skeletal muscle may provide an indication of the underlying mechanisms of insulin-related disorders. The aim of this study was to investigate the potential of Fourier transform infrared (FTIR) spectroscopy to reveal the changes in macromolecular composition in weight-bearing and non-weight-bearing muscles of old, obese, insulin-resistant, and young streptozotocin (STZ)-induced diabetic mice. The efficiency of FTIR spectroscopy was evaluated by comparison with the results of gold-standard histochemical techniques. The differences in biomolecular phenotypes and the alterations in muscle composition in relation to their functional properties observed from FTIR spectra suggest that FTIR spectroscopy can detect most of the changes observed in muscle tissue by histochemical analyses and more. Therefore, it could be used as an effective alternative because it allows for the complete characterization of macromolecular composition in a single, relatively simple experiment, avoiding some obvious drawbacks of histochemical methods.

High-sensitivity hyperspectral vibrational imaging of heart tissues by mid-infrared photothermal microscopy

Visualizing the spatial distribution of chemical compositions in biological tissues is of great importance to study fundamental biological processes and origin of diseases. Raman microscopy, one of the label-free vibrational imaging techniques, has been employed for chemical characterization of tissues. However, the low sensitivity of Raman spectroscopy often requires a long acquisition time of Raman measurement or a high laser power, or both, which prevents one from investigating large-area tissues in a nondestructive manner. In this work, we demonstrated chemical imaging of heart tissues using mid-infrared photothermal (MIP) microscopy that simultaneously achieves the high sensitivity benefited from IR absorption of molecules and the high spatial resolution down to a few micrometers. We successfully visualized the distributions of different biomolecules, including proteins, phosphate-including proteins, and lipids/carbohydrates/amino acids. Further, we experimentally compared MIP microscopy with Raman microscopy to evaluate the sensitivity and photodamage to tissues. We proved that MIP microscopy is a highly sensitive technique for obtaining vibrational information of molecules in a broad fingerprint region, thereby it could be employed for biological and diagnostic applications, such as live-tissue imaging.

Investigation of early biochemical alterations in myocardia of the diabetic db/db mice by FTIR microspectroscopy combined with machine learning

Diabetic cardiomyopathy (DbCM) is a serious complication of diabetes that affects about 12% of the diabetic population. Sensitive detection of diabetes-induced biochemical changes in the heart before symptoms appear can assist clinicians in developing targeted treatment plans and forensic pathologists in making accurate postmortem diagnoses. The Fourier transform infrared (FTIR) spectroscopy-based approach allows for the analysis of the sample biomolecular composition and variations. In the current study, the myocardial tissues of mouse models of type 2 diabetes mellitus (T2DM) at various ages (7, 12, and 21 weeks) were analyzed using FTIR microspectroscopy (FTIRM) in combination with machine learning algorithms. The carbonyl esters, olefinic=CH and CH₂ groups of lipids, total lipids, saccharides, and β-sheet to α-helix conformational transition in proteins increased significantly in diabetic mice myocardial tissues compared to healthy mice. Furthermore, partial least-squares discriminant analysis and random forest-guided partial least-squares discriminant analysis revealed the time-dependent progression of the spectral lipidomic profiles during the development of DbCM. Finally, a random forest classifier was developed for diagnosing DbCM, with 97.1% accuracy. This study demonstrates that FTIRM is a novel method for monitoring early biochemical changes in the myocardia of mice with T2DM.

Different Types of Meatballs Enriched with Wild Thyme/Lemon Balm Aqueous Extract-Complex Characterization

In the context of the increasing lactation problems among breastfeeding women, the development of a healthy lifestyle is needed. Different variants of pork, turkey, and beef meatballs, with added lemon balm (Melissa officinalis L.) and wild thyme (Thymus serpyllum L.) aqueous extract (6%), were obtained. These herbs were selected and used due to their antioxidant, antimicrobial, and lactogenic potential. Two thermal treatments, hot air convection (180 °C) and steam convection (94 °C), were applied for meatballs processing. The obtained meatballs were further subjected to a complex characterization. The functionality of the plant extracts was proved by the values of total content of polyphenols (2.69 ± 0.02 mg AG/g dw) and flavonoids (3.03 ± 0.24 mg EQ/g dw). FT-IR analysis confirmed the presence of trans-anethole and estragole at 1507–1508 cm⁻¹ and 1635–1638 cm⁻¹, respectively. Costumers’ overall acceptance had a score above 5.5 for all samples, on a scale of 1 to 9. Further analysis and human trials should be considered regarding the use of lactogenic herbs, given their health benefits and availability.

Non/mini-invasive monitoring of diabetes-induced myocardial damage by Fourier transform infrared spectroscopy: Evidence from biofluids

Early identification of diabetic cardiomyopathy (DCM) can help clinicians develop targeted treatment plans and forensic pathologists make accurate postmortem diagnoses. In the present study, diabetes-induced metabolic abnormalities in the myocardium and biofluids (plasma, urine, and saliva) of db/db mice of various ages (7, 12, and 21 weeks) were investigated by attenuated total reflection (ATR)-Fourier transform infrared (FTIR) spectroscopy. The results indicated that the diabetic and control groups had significantly different changes in the function groups of lipids, phosphate macromolecules (mostly nucleic acids), protein compositions and conformations, and carbohydrates (primarily glucose) in the myocardium and biofluids. The prediction model for quantifying DCM severity was developed on db/db mice's myocardial spectra using a genetic algorithm (GA)-partial least squares (PLS) regression method. Following that, the linear correlations between the predicted values for DCM severity and spectra for db/db biofluids were evaluated using the GA-PLS regression algorithm. The results showed there were good linear correlations between the predicted values for DCM severity and spectra for plasma (R² = 0.929), saliva (R² = 0.967), urine (R² = 0.954), and combination of plasma and saliva (R² = 0.980). This study provides a novel perspective on detecting diabetes-related biofluid and cardiac metabolic abnormalities and demonstrates the potential of biofluid infrared spectro-diagnostic models for non/mini-invasive assessment of DCM.

From Dynamic Superwettability to Ionic/Molecular Superfluidity

Life systems present ultralow energy consumption in high-efficiency energy conversion, information transmission, and biosynthesis. The total energy intake of the human body is about 2000 kcal/day to maintain all of our activities, which is comparable to a power of ∼100 W. The energy required for the brain to work is equivalent to ∼20 W, and the rest of the energy (∼80 W) is used for other activities. All in vivo biosyntheses take place only at body temperature, which is much lower than that of in vitro reactions. To achieve these ultralow energy-consumption processes, there should be a kind of ultralow-resistivity matter transport in nanochannels (e.g., ionic and molecular channels), in which the directional collective motion of ions or molecules is a necessary condition rather than traditional Newton diffusion. The directional collective motion of ions and molecules is considered to be ionic/molecular superfluidity. The driving force of ionic/molecular superfluidity formation requires two necessary conditions: (1) Ions or molecules are confined at a certain distance (e.g., approximately twice Debye length (2λ_D) for ions or twice the van der Waals equilibrium distance (2d₀) for molecules). (2) When the attractive potential energy (E₀) is stronger than the thermal noise (k_BT_c), ionic/molecular superfluidity can be formed. The concept of ionic/molecular superfluidity will promote the understanding of energy conversion with ultralow energy consumption in biological systems. The swing of an eel's body generating electricity and cardiac resuscitation denote the conversion from mechanical energy to electrical energy, and mechanical modulation might result in a coherent resonance of ionic motion. The coherent resonance of Ca²⁺ in myocardium cells can induce a heartbeat, realizing the conversion from the electrical energy to the mechanical energy of a biological system. The macroscopic quantum state of ion channels is considered to be a carrier of neural information, and the environment field might play a significant role in regulating the macroscopic quantum states of various ion channels. In the biological ion channels system, the coupling of ion channels and their released photons might induce an environment wave which in turn regulates the ion oscillations in the channels to a coherent state. The states of decoherence and coherence might correspond to the states of sleep and action. We also demonstrated the decomposition of ATP to ADP released photons with a frequency of ∼34 THz, which could further drive DNA polymerization in the nanocavity of DNA polymerase. The photochemical (mid- and far-IR) reaction might be the driving force in high-efficiency biosynthesis. Quantized syntheses resonantly driven by multiple mid- and far-IR photons could be further designed in a tubular reactor with membranes of different microporous structures to achieve a high-efficiency synthesis with a low energy consumption. Finally, we point out that the Bose-Einstein condensate potentially widely exists. We expect that this Account will provide new ideas for the key problem in life science: how can life systems present ultralow energy consumption in high-efficiency energy conversion, information transmission, and biosynthesis?

A resonance Rayleigh scattering method for sensitive detection of chitosan based on supramolecular complex and mechanism study

A convenient and sensitive resonance Rayleigh scattering (RRS) method for the detection of chitosan (CTS) has been developed via forming Cu-Zn supramolecular complex by complexation reaction, hydrophobic force and electrostatic attraction. The microstructure of the complex was characterized by FT-IR, zeta potential, scanning electron microscope (SEM), UV-vis and RRS. Furthermore, the interaction mechanism among Cu(II), Zn(II), CTS and sodium dodecyl benzene sulfonate (SDBS) was studied. The results revealed that CTS and Cu(II) or Zn(II) formed a supramolecular complex with RRS enhancement in weak acid condition. In the presence of SDBS, the RRS intensity of CTS-Cu(II)-SDBS or CTS-Zn(II)-SDBS was significantly higher than that of the binary system without SDBS at the same CTS concentration. The RRS intensity of CTS-Cu(II)-Zn(II)-SDBS was higher than that of CTS-Cu(II)-SDBS and CTS-Zn(II)-SDBS. The RRS intensity increased linearly with the increase of CTS concentration made it possible to determine CTS quantitatively. In the range extending from 0.10 to 5.00 μg/mL, the equation of linear regression was ΔI=1848.8c-138.3 with a correlation coefficient 0.9996, and the detection limit was estimated to be 37.96 ng/mL. The study was successfully applied for the determination of CTS in health food samples, suggesting its great potential toward CTS analysis.

In situ analysis of acupuncture protecting dopaminergic neurons from lipid peroxidative damage in mice of Parkinson's disease

Objectives

Acupuncture stimulation has proven to protect dopaminergic neurons from oxidative damage in animal models of Parkinson's disease (PD), but it remains unclear about the in situ information of biochemical components in dopaminergic neurons. Here, we aimed to analyse in situ changes of biochemical components and lipid peroxidation levels in dopaminergic neurons in PD mice treated with acupuncture by synchrotron FTIR micro‐spectroscopy technique.

Materials and Methods

About 9–10‐week‐old C57BL/6 mice were used to establish PD model by intraperitoneal injection of 1‐methyl‐4‐phenyl‐1,2,3,6‐tetrahydropyridine (MPTP, 30 mg/kg for 5 days). Acupuncture stimulation was performed once a day for 12 days. Behaviour test was determined using the rotarod instrument. Biochemical compositions of dopaminergic neurons in substantia nigra pars compacta were analysed by synchrotron FTIR micro‐spectroscopy technique. The number and ultrastructure of dopaminergic neurons were respectively observed by immunofluorescence and transmission electron microscopy (TEM).

Results

We found that the number and protein expression of dopaminergic neurons in MPTP‐treated mice were reduced by about half, while that in the mice treated by acupuncture were significantly restored. Acupuncture treatment also restored the motor ability of PD mice. The results of single cell imaging with synchrotron FTIR micro‐spectroscopy technique showed that the proportion of lipid in MPTP treated mice increased significantly. Especially the ratio of CH₂ asymmetric stretching and CH₃ asymmetric stretching increased significantly, suggesting that MPTP induced lipid peroxidation damage of dopaminergic neurons. It is also supported by the result of TEM, such as mitochondrial swelling or atrophy, loss of mitochondrial crests and mitochondrial vacuolization. Compared with MPTP treated mice, the proportion of lipid in acupuncture treated mice decreased and the mitochondrial structure was restored.

Conclusions

Acupuncture can inhibit the level of lipid peroxides in dopaminergic neurons and protect neurons from oxidative damage. The study provides a promising method for in situ analysis of biochemical compositions in PD mice and reveals the mechanism of acupuncture in treating neurodegenerative diseases.

Cellulose-based hydrogel on quantum dots with molecularly imprinted polymers for the detection of CA19-9 protein cancer biomarker

Molecularly imprinted polymers MIPs were successfully assembled around quantum dots (QDs), for the detection of the protein biomarker CA19-9 associated to pancreatic cancer (PC). These imprinted materials MIP@QDs were incorporated within the cellulose hydrogel with retention of its conformational structure inside the binding cavities. The concept is to use MIPs which function as the biorecognition elements, conjugated to cadmium telluride QDs as the sensing system. The excitation wavelength was set to 477 nm and the fluorescence signal was measured at its maximum intensity, with an emission range between 530 and 780 nm. The fluorescence quenching of the imprinted cellulose hydrogels occurred with increasing concentrations of CA19-9, showing linearity in the range 2.76 × 10 ^-2 - 5.23 × 10 ² U/ml, in a 1000-fold diluted human serum. Replicates of the imprinted hydrogel show a linear response below the cut-off values for pancreatic cancer diagnosis (< 23 U/ml), a limit of detection of 1.58 × 10 ^-3 U/ml and an imprinting factor (IF) of 1.76. In addition to the fact that the imprinted cellulose hydrogel displays good stability and selectivity towards CA19-9 when compared with the non-imprinted controls, the conjugation of MIPs to QDs increases the sensitivity of the system for an optical detection method towards ranges within clinical significance. This fact shows potential for the imprinted hydrogel to be applied as a sensitive, low-cost format for point-of-care tests (PoCTs).

Biochemical Alterations in White Matter Tracts of the Aging Mouse Brain Revealed by FTIR Spectroscopy Imaging

White matter degeneration in the central nervous system (CNS) has been correlated with a decline in cognitive function during aging. Ultrastructural examination of the aging human brain shows a loss of myelin, yet little is known about molecular and biochemical changes that lead to myelin degeneration. In this study, we investigate myelination across the lifespan in C57BL/6 mice using electron microscopy and Fourier transform infrared (FTIR) spectroscopic imaging to better understand the relationship between structural and biochemical changes in CNS white matter tracts. A decrease in the number of myelinated axons was associated with altered lipid profiles in the corpus callosum of aged mice. FTIR spectroscopic imaging revealed alterations in functional groups associated with phospholipids, including the lipid acyl, lipid ester and phosphate vibrations. Biochemical changes in white matter were observed prior to structural changes and most predominant in the anterior regions of the corpus callosum. This was supported by biochemical analysis of fatty acid composition that demonstrated an overall trend towards increased monounsaturated fatty acids and decreased polyunsaturated fatty acids with age. To further explore the molecular mechanisms underlying these biochemical alterations, gene expression profiles of lipid metabolism and oxidative stress pathways were investigated. A decrease in the expression of several genes involved in glutathione metabolism suggests that oxidative damage to lipids may contribute to age-related white matter degeneration.

A bimodal probe for fluorescence and synchrotron X-ray fluorescence imaging of dopaminergic neurons in the brain

A bimodal probe, the erythrosine B (EB) conjugated immunoglobulin G complex (EB/IgG), has been developed for the fluorescence and synchrotron X-ray fluorescence (SXRF) imaging of dopaminergic neurons in the brain.

The Use of Fourier Transform Infrared Microspectroscopy for the Determination of Biochemical Anomalies of the Hippocampal Formation Characteristic for the Kindling Model of Seizures

The animal models of seizures and/or epilepsy are widely used to identify the pathomechanisms of the disease as well as to look for and test the new antiseizure therapies. The understanding of the mechanisms of action of new drugs and evaluation of their safety in animals require previous knowledge concerning the biomolecular anomalies characteristic for the particular model. Among different models of seizures, one of the most widely used is the kindling model that was also applied in our study. To examine the influence of multiple transauricular electroshocks on the biochemical composition of rat hippocampal formation, Fourier transform infrared (FT-IR) microspectrosopy was utilized. The chemical mapping of the main absorption bands and their ratios allowed us to detect significant anomalies in both the distribution and structure of main biomolecules for electrically stimulated rats. They included an increased relative content of proteins with β-sheet conformation (an increased ratio of the absorbance at the wavenumbers of 1635 and 1658 cm^–1), a decreased level of cholesterol and/or its esters and compounds containing phosphate groups (a diminished intensity of the massif of 1360–1480 cm^–1 and the band at 1240 cm^–1), as well as increased accumulation of carbohydrates and the compounds containing carbonyl groups (increased intensity of the bands at 1080 and 1740 cm^–1, respectively). The observed biomolecular abnormalities seem to be the consequence of lipid peroxidation promoted by reactive oxygen species as well as the mobilization of glucose that resulted from the increased demand to energy during postelectroshock seizures.

Anti-damage effect of theaflavin-3'-gallate from black tea on UVB-irradiated HaCaT cells by photoprotection and maintaining cell homeostasis

Keratinocytes are rich in lipids and are the main sensitive cells to ultraviolet (UV) rays. Theaflavins are the core functional components of black tea and are known as the "soft gold" in tea. In this study, ultraviolet-B (UVB) irradiation caused apoptosis and necrosis of human epidermal keratinocytes (HaCaT). EGCG and the four theaflavins had anti-UVB damage activity, among which theaflavin-3'-gallate (TF3'G) had the best activity. The results of biophysical and molecular biology experiments showed that TF3'G has anti-damage effects on UVB-irradiated HaCaT cells through the dual effects of photoprotection and maintenance of cell homeostasis. That is, TF3'G preincubation could absorb UV rays, reduce the accumulation of aging-related heterochromatin (SAHF) formation, increase mitochondrial membrane potential, downregulate NF-κB inflammation pathways, inhibit the formation of cytotoxic aggregates, and protect biological macromolecules Structure, etc. The accumulation of conjugated π bonds and the balance benzoquinone are the core functional structure of TF3'G with high efficiency and low toxicity. The study indicates that TF3'G has the potential to inhibit the photoaging and intrinsic aging of skin cells.

Fourier-transform infrared microspectroscopy of pulmonary edema fluid for postmortem diagnosis of diabetic ketoacidosis

Determination of the cause of death for diabetic ketoacidosis (DKA), a common and fatal acute complication of diabetes mellitus, is a challenging forensic task owing to the lack of characteristic morphological findings at autopsy. In this study, Fourier-transform infrared (FTIR) microspectroscopy coupled with chemometrics was employed to characterize biochemical differences in pulmonary edema fluid from different causes of death to supplement conventional methods and provide an efficient postmortem diagnosis of DKA. With this aim, FTIR spectra in three different situations (DKA-caused death, other causes of death with diabetes history, and other causes of death without diabetes history) were measured. The results of principal component analysis indicated different spectral profiles between these three groups, which mainly exhibited variations in proteins. Subsequently, two binary classification models were established using an algorithm of partial least squares discriminant analysis (PLS-DA) to determine whether decedents had diabetes and whether the diabetic patients died from DKA. Satisfactory prediction results of PLS-DA models demonstrated good differentiation among these three groups. Therefore, it is feasible to make a postmortem diagnosis of DKA and detect diabetes history via FTIR microspectroscopic analysis of the pulmonary edema fluid.

Nonthermal and reversible control of neuronal signaling and behavior by midinfrared stimulation

Various neuromodulation approaches have been employed to alter neuronal spiking activity and thus regulate brain functions and alleviate neurological disorders. Infrared neural stimulation (INS) could be a potential approach for neuromodulation because it requires no tissue contact and possesses a high spatial resolution. However, the risk of overheating and an unclear mechanism hamper its application. Here we show that midinfrared stimulation (MIRS) with a specific wavelength exerts nonthermal, long-distance, and reversible modulatory effects on ion channel activity, neuronal signaling, and sensorimotor behavior. Patch-clamp recording from mouse neocortical pyramidal cells revealed that MIRS readily provides gain control over spiking activities, inhibiting spiking responses to weak inputs but enhancing those to strong inputs. MIRS also shortens action potential (AP) waveforms by accelerating its repolarization, through an increase in voltage-gated K⁺ (but not Na⁺) currents. Molecular dynamics simulations further revealed that MIRS-induced resonance vibration of -C=O bonds at the K⁺ channel ion selectivity filter contributes to the K⁺ current increase. Importantly, these effects are readily reversible and independent of temperature increase. At the behavioral level in larval zebrafish, MIRS modulates startle responses by sharply increasing the slope of the sensorimotor input-output curve. Therefore, MIRS represents a promising neuromodulation approach suitable for clinical application.

Fourier Transform Infrared Imaging-A Novel Approach to Monitor Bio Molecular Changes in Subacute Mild Traumatic Brain Injury

Traumatic brain injury (TBI) can be defined as a disorder in the function of the brain after a bump, blow, or jolt to the head, or penetrating head injury. Mild traumatic brain injury (mTBI) can cause devastating effects, such as the initiation of long-term neurodegeneration in brain tissue. In the current study, the effects of mTBI were investigated on rat brain regions; cortex (Co) and corpus callosum (CC) after 24 h (subacute trauma) by Fourier transform infrared (FTIR) imaging and immunohistochemistry (IHC). IHC studies showed the formation of amyloid-β (Aβ) plaques in the cortex brain region of mTBI rats. Moreover, staining of myelin basic protein presented the shearing of axons in CC region in the same group of animals. According to FTIR imaging results, total protein and lipid content significantly decreased in both Co and CC regions in mTBI group compared to the control. Due to this significant decrease in both lipid and protein content, remarkable consistency in lipid/protein band ratio in mTBI and control group, was observed. Significant decrease in methyl content and a significant increase in olefinic content were observed in Co and CC regions of mTBI rat brain tissues. Classification amongst distinguishable groups was performed using principal component analysis (PCA) and hierarchical clustering (HCA). This study established the prospective of FTIR imaging for assessing biochemical changes due to mTBI with high sensitivity, precision and high-resolution.

Biomolecular alterations in acute traumatic brain injury (TBI) using Fourier transform infrared (FTIR) imaging spectroscopy

Acute injury is one of the substantial stage post-traumatic brain injury (TBI) occurring at the moment of impact. Decreased metabolism, unregulated cerebral blood flow and direct tissue damage are triggered by acute injury. Understating the biochemical alterations associated with acute TBI is critical for brain plasticity and recovery. The objective of this study was to investigate the biochemical and molecular changes in hippocampus, corpus callosum and thalamus brain regions post-acute TBI in rats. Fourier Transform Infrared (FTIR) imaging spectroscopy were used to collect chemical images from control and 3 hrs post-TBI (Marmarou model was used for the TBI induction) rat brains and adjacent sections were treated by hematoxylin and eosin (H&E) staining to correlate with the disruption in tissue morphology and injured brain biochemistry. Our results revealed that the total lipid and total protein content decreased significantly in the hippocampus, corpus callosum and thalamus after brain injury. Reduction in lipid acyl chains (-CH₂) associated with an increase in methyl (-CH₃) and unsaturated lipids olefin = CH concentrations is observed. Furthermore, there is a decrease in the lipid order (disorder), which leads to an increase in acyl chain fluidity in injured rats. The results suggest acute TBI damages brain tissues mechanically rather than chemical alterations. This will help in assessing successful therapeutic strategy in order to mitigate tissue damage in acute TBI period.

Synchrotron Radiation-Based FTIR Microspectroscopic Imaging of Traumatically Injured Mouse Brain Tissue Slices

Traumatic brain injury (TBI) is a health problem of global concern because of its serious adverse effects on public health and social economy. A technique that can be used to precisely detect TBI is highly demanded. Here, we report on a synchrotron radiation-based Fourier transform infrared (SR-FTIR) microspectroscopic imaging technique that can be exploited to identify TBI-induced injury by examining model mouse brain tissue slices. The samples were first examined by conventional histopathological techniques including hematoxylin and eosin (H&E) staining and 2,3,5-triphenyltetrazolium chloride staining and then spectroscopically imaged by SR-FTIR. SR-FTIR results show that the contents of protein and nucleic acid in the injured region are lower than their counterparts in the normal region. The injured and normal regions can be unambiguously distinguished from each other by the principle component analysis of the SR-FTIR spectral data corresponding to protein or nucleic acid. The images built from the spectral data of protein or nucleic acid clearly present the injured region of the brain tissue, which is in good agreement with the H&E staining image and optical image of the sample. Given the label-free and fingerprint features, the demonstrated method suggests potential application of SR-FTIR spectroscopic mapping for the digital and intelligent diagnosis of TBI by providing spatial and chemical information of the sample simultaneously.

ATR-FTIR spectroscopy as adjunct method to the microscopic examination of hematoxylin and eosin-stained tissues in diagnosing lung cancer

Lung cancer remains the leading cause of cancer-related death worldwide. Since prognosis and treatment outcomes rely on fast and accurate diagnosis, there is a need for more cost-effective, sensitive, and specific method for lung cancer detection. Thus, this study aimed to determine the ability of ATR-FTIR in discriminating malignant from benign lung tissues and evaluate its concordance with H&E staining. Three (3) 5μm-thick sections were cut from formalin fixed paraffin embedded (FFPE) cell or tissue blocks from patients with lung lesions. The outer sections were H&E-stained and sent to two (2) pathologists to confirm the histopathologic diagnosis. The inner section was deparaffinized by standard xylene method and then subjected to ATR-FTIR analysis. Distinct spectral profiles that distinguished (p<0.05) one sample from another, called the "fingerprint region", were observed in five (5) peak patterns representing the amides, lipids, and nucleic acids. Principal component analysis and hierarchical cluster analysis evidently clustered the benign from malignant tissues. ATR-FTIR showed 97.73% sensitivity, 92.45% specificity, 94.85% accuracy, 91.49% positive predictive value and 98.00% negative predictive value in discriminating benign from malignant lung tissue. Further, strong agreement was observed between histopathologic readings and ATR-FTIR analysis. This study shows the potential of ATR-FTIR spectroscopy as a potential adjunct method to the gold standard, the microscopic examination of hematoxylin and eosin (H&E)-stained tissues, in diagnosing lung cancer.

Diagnosis of idiopathic amyotrophic lateral sclerosis using Fourier-transform infrared spectroscopic analysis of patient-derived skin

One of the great challenges in identifying effective therapy in many neurodegenerative diseases, such as amyotrophic lateral sclerosis (ALS), is the lack of reliable biomarkers. In this study, we applied infrared imaging microspectroscopy, a valuable technique to investigate biomolecule fingerprints and secondary structure of proteins within biological tissue. We hypothesized that, since skin and CNS have the same embryonic origin, spectral differences associated with ALS-specific pathological events will be readily detectable through skin testing using this technique. Cells from healthy individuals and ALS patients were isolated from skin biopsies in order to generate tissue-engineered in vitro skin (TES). Infrared spectra of the generated TES were recorded using a focal-plane-array Fourier transform infrared (FPA-FTIR) spectrometer, and hierarchical cluster analysis of the spectral data was performed in order to establish clear differences between the tested TES specimens. Interestingly, our analyses showed that it was readily possible to discriminate ALS- and control-TES solely based on differences in associated FTIR spectra, mainly located between 1149 and 1473 cm^-1, attributed to disruption of phospholipid cell membranes, extracellular matrix remodeling or cholesterol accumulation. Spectral differences within the TES samples may therefore be associated with disease state, paving the way for the identification of biomarkers in ALS.

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.

Investigation of human pancreatic cancer tissues by Fourier Transform Infrared Hyperspectral Imaging

Fourier-transform infrared hyperspectral imaging (FTIR-HSI) provides hyperspectral images containing both morphological and chemical information. It is widely applied in the biomedical field to detect tumor lesions, even at the early stage, by identifying specific spectral biomarkers. Pancreatic neoplasms present different prognoses and are not always easily classified by conventional analyses. In this study, tissue samples with diagnosis of pancreatic ductal adenocarcinoma and pancreatic neuroendocrine tumor were analyzed by FTIR-HSI and the spectral data compared with those from healthy and dysplastic samples. Multivariate/univariate approaches were complemented to hyperspectral images, and definite spectral markers of the different lesions identified. The malignant lesions were recognizable both from healthy/dysplastic pancreatic tissues (high values of phospholipids and triglycerides with shorter, more branched and less unsaturated alkyl chains) and between each other (different amounts of total lipids, phosphates and carbohydrates). These findings highlight different metabolic pathways characterizing the different samples, well detectable by FTIR-HSI.

Applications of Fourier transform infrared spectroscopy to pharmaceutical preparations

Introduction: Various pharmaceutical preparations are widely used for clinical treatment. Elucidation of the mechanisms of drug release and evaluation of drug efficacy in biological samples are important in drug design and drug quality control.Areas covered: This review classifies recent applications of Fourier transform infrared (FTIR) spectroscopy in the field of medicine to comprehend drug release and diffusion. Drug release is affected by many factors of preparations, such as drug delivery system and microstructure polymorphism. The applications of FTIR imaging and nano-FTIR technique in biological samples lay a foundation for studying drug mechanism in vivo.Expert opinion: FTIR spectroscopy meets the research needs on preparations to understand the processes and mechanisms underlying drug release. The combination of attenuated total reflectance-FTIR imaging and nano-FTIR accompanied by chemometrics is a potent tool to overcome the deficiency of conventional infrared detection. FTIR shows an enormous potential in drug characterization, drug quality control, and bio-sample detection.

Infrared biomarkers of impaired cystic fibrosis transmembrane regulator protein biogenesis

The mid-infrared (IR) spectra of human cystic fibrosis (CF) cells acquired by Fourier transform infrared microspectroscopy were compared with those of non-CF cells. Within the 1700 to 1480 cm^-1 spectral domain of amides, unsupervised explorative principal component analysis identified a few variables reflecting quantitative and qualitative vibrations arising from protein secondary structures and amino acid side chains. Their pattern reflected α-helix to β-sheet transitions in bronchial epithelial cells and in immortalized peripheral blood mononuclear cells from patients with R1162X missense or in-frame F508del mutations in the cystic fibrosis transmembrane regulator gene (Cftr). Similar transitions have been described in IR spectra of cells, tissues and body fluids of patients affected with some neurodegenerative diseases characterized by the accumulation of misfolded protein aggregates. The variables pattern was able to distinguish CF cells from non-CF cells and was modified by molecular compounds used to rescue the unbalanced folding process of mutated cystic fibrosis transmembrane regulator (CFTR) anion channel. To our knowledge, this is the first experimental evidence of spectroscopic biomarkers of the impaired biogenesis of CFTR by IR microanalysis in the spectra of human CF bronchial epithelial and lymphoblastoid cells.

Fourier Transform Infrared Spectroscopy as a Cancer Screening and Diagnostic Tool: A Review and Prospects

Infrared spectroscopy has long been used to characterize chemical compounds, but the applicability of this technique to the analysis of biological materials containing highly complex chemical components is arguable. However, recent advances in the development of infrared spectroscopy have significantly enhanced the capacity of this technique in analyzing various types of biological specimens. Consequently, there is an increased number of studies investigating the application of infrared spectroscopy in screening and diagnosis of various diseases. The lack of highly sensitive and specific methods for early detection of cancer has warranted the search for novel approaches. Being more simple, rapid, accurate, inexpensive, non-destructive and suitable for automation compared to existing screening, diagnosis, management and monitoring methods, Fourier transform infrared spectroscopy can potentially improve clinical decision-making and patient outcomes by detecting biochemical changes in cancer patients at the molecular level. Besides the commonly analyzed blood and tissue samples, extracellular vesicle-based method has been gaining popularity as a non-invasive approach. Therefore, infrared spectroscopic analysis of extracellular vesicles could be a useful technique in the future for biomedical applications. In this review, we discuss the potential clinical applications of Fourier transform infrared spectroscopic analysis using various types of biological materials for cancer. Additionally, the rationale and advantages of using extracellular vesicles in the spectroscopic analysis for cancer diagnostics are discussed. Furthermore, we highlight the challenges and future directions of clinical translation of the technique for cancer.

Postmortem Diagnosis of Fatal Hypothermia by Fourier Transform Infrared Spectroscopic Analysis of Edema Fluid in Formalin-Fixed, Paraffin-Embedded Lung Tissues

The goal of this study was to investigate whether pulmonary edema could become a specific diagnostic marker for fatal hypothermia using Fourier transform infrared (FTIR) spectroscopy in combination with chemometrics. The spectral profile analysis indicated that hypothermia fatalities associated with pulmonary edema fluid contained more β-sheet protein conformational structures than the control causes of death, which included sudden cardiac death, brain injury, cerebrovascular disease, mechanical asphyxiation, intoxication, and drowning. Subsequently, the results of principal component analysis (PCA) further revealed that the content of β-sheet protein conformational structures in the pulmonary edema fluid was the main discriminatory marker between fatal hypothermia and the other causes of death. Ultimately, a robust postmortem diagnostic model for fatal hypothermia using a partial least-squares discriminant analysis (PLS-DA) algorithm was constructed. Pulmonary edema fluid spectra collected from eight new forensic autopsy cases that did not participate in the construction of the diagnostic model were predicted using the model. The results showed the causes of death of all these eight cases were correctly classified. In conclusion, this preliminary study demonstrates that FTIR spectroscopy in combination with chemometrics could be a promising approach for the postmortem diagnosis of fatal hypothermia.

Investigation of the Effect of PD-L1 Blockade on Triple Negative Breast Cancer Cells Using Fourier Transform Infrared Spectroscopy

Interactions between programmed death-1 (PD-1) with its ligand PD-L1 on tumor cells can antagonize T cell responses. Inhibiting these interactions using immune checkpoint inhibitors has shown promise in cancer immunotherapy. MDA-MB-231 is a triple negative breast cancer cell line that expresses PD-L1. In this study, we investigated the biochemical changes in MDA-MB-231 cells following treatment with atezolizumab, a specific PD-L1 blocker. Our readouts were Fourier Transform Infrared (FTIR) spectroscopy and flow cytometric analyses. Chemometrical analysis, such as principal component analysis (PCA), was applied to delineate the spectral differences. We were able to identify the chemical alterations in both protein and lipid structure of the treated cells. We found that there was a shift from random coil and α-helical structure to β-sheet conformation of PD-L1 on tumor cells due to atezolizumab treatment, which could hinder binding with its receptors on immune cells, ensuring sustained T cell activation for potent immune responses. This work provides novel information about the effects of atezolizumab at molecular and cellular levels. FTIR bio-spectroscopy, in combination with chemometric analyses, may expedite research and offer new approaches for cancer immunology.

Vibrational Spectroscopy Fingerprinting in Medicine: from Molecular to Clinical Practice

In the last two decades, Fourier Transform Infrared (FTIR) and Raman spectroscopies turn out to be valuable tools, capable of providing fingerprint-type information on the composition and structural conformation of specific molecular species. Vibrational spectroscopy's multiple features, namely highly sensitive to changes at the molecular level, noninvasive, nondestructive, reagent-free, and waste-free analysis, illustrate the potential in biomedical field. In light of this, the current work features recent data and major trends in spectroscopic analyses going from in vivo measurements up to ex vivo extracted and processed materials. The ability to offer insights into the structural variations underpinning pathogenesis of diseases could provide a platform for disease diagnosis and therapy effectiveness evaluation as a future standard clinical tool.

Role of quercetin and caloric restriction on the biomolecular composition of aged rat cerebral cortex: An FTIR study

Aging brain is characterized by a change in biomolecular composition leading to a diverse range of neurological diseases. Anti-aging research is of current interest, to lessen the burden of age-related macromolecular damage through antioxidant supplementation and caloric restriction. However, data concerning the effect of these anti-aging regimens on age-related biomolecular changes in rat brain is still lacking. In the present study, for the first time, we employed Fourier transform infrared (FTIR) spectroscopy, to investigate the effect of quercetin, caloric restriction (CR) and combination of both on alterations in the composition of lipids and proteins of aged rat brain cerebral cortex. Aged male Wistar rats (21 months old) were divided into four groups: Control (CONT), fed pellet diet; Quercetin (QUER), fed quercetin (50 mg/kg/day); CR (caloric restriction) (fed 40% reduced CONT), and CRQ (40% CR and 50 mg/kg/day QUER). Three-month-old rats served as young control (YOUNG). Our short-term study (45 days) shows decreased band area of unsaturated lipids, decreased area ratios of olefinic/lipid and CH₂ antisymmetric stretching (2925 cm^-1)/lipids in CONT group compared to young rats, suggesting age-associated lipid peroxidation in aged rats. A slight decrease in the frequency of CH₂ antisymmetric mode of lipids (whereas no change in CH₂ symmetric mode), but a decrease in bandwidths of both CH₂ antisymmetric and symmetric modes of lipids was observed for CONT group compared to YOUNG. Further, a significant decrease in the peak area of infrared bands of proteins and an increase in the peak area of the CO band of lipids was observed in the CONT group. Our data also show that lower levels of α-helical structures and higher levels of random coils, representing altered protein secondary structure composition in the CONT group compared to YOUNG group. Reduction in neuronal cell density and shrinked nucleus was also observed in aged rats. Increase in the accumulation of oxidative mediated damage to macromolecules and diminished antioxidant levels, could be the possible reason for the age-related alterations in the composition of lipids and proteins. However, the combination of quercetin and CR, but not either treatment alone, significantly prevented the age associated alterations in the lipid and protein profiles in the rat cerebral cortex. Further, our results help to understand the mechanism of action of antioxidants under non-restriction and CR conditions, this might help in the development of novel anti-aging treatments to ameliorate oxidative stress in age-related disorders.

Does the molecular and metabolic profile of human granulosa cells correlate with oocyte fate? New insights by Fourier transform infrared microspectroscopy analysis

STUDY QUESTION

Does the molecular and metabolic profile of human mural granulosa cells (GCs) correlate with oocyte fate?

SUMMARY ANSWER

A close relation between the metabolic profile of mural GCs and the fate of the corresponding oocyte was revealed by the analysis of selected biomarkers defined by GC Fourier transform infrared microspectroscopy (FTIRM) analysis.

WHAT IS KNOWN ALREADY

In ART, oocyte selection is mainly based on the subjective observation of its morphological features; despite recent efforts, the success rate of this practice is still unsatisfactory. FTIRM is a well-established vibrational technique recently applied to evaluate oocytes quality in several experimental models, including human.

STUDY DESIGN, SIZE, DURATION

GCs retrieved from single-follicle aspirates were obtained with informed consent from 55 women undergoing controlled ovarian stimulation for IVF treatment. GCs were analysed by FTIRM to retrospectively correlate their spectral features with the fate of the companion oocytes. The study has been conducted between March 2016 and September 2017.

PARTICIPANTS/MATERIALS, SETTING, METHODS

Patients were selected according to the following inclusion criteria: age <40 years; non-smokers; no ovarian infertility diagnosis (only tubal, idiopathic and male infertility); regular ovulatory menstrual cycles (25-30 days) with FSH < 10 IU/I on Day 3 of the menstrual cycle; sperm sample with a total motility count after treatment ≥300.000; number of retrieved oocytes ≥8. Based on the clinical outcome of the corresponding oocyte, GCs were retrospectively classified into the following experimental groups: clinical pregnancy (CP), fertilization failure (FF), embryo development failure (EDF) and implantation failure (IF). All samples were analysed by the FTIRM technique. The spectral biomarker signature of different oocyte fates was derived by several feature selection procedures ('Leave-one-out' method on factorial discriminant analysis (FDA), variable characterization method and logistic regression method with the multinomial Logit model). ANOVA, permutational multivariate ANOVA, FDA and canonical analysis of principal co-ordinates statistical tools were also applied to validate the identified spectral biomarkers.

MAIN RESULTS AND THE ROLE OF CHANCE

In total, 284 GCs samples were retrieved and retrospectively classified as FF: (N = 92), EDF (N = 113), IF (N = 56) and CP (N = 23). From the spectral profiles of GCs belonging to CP, FF, EDF and IF experimental groups, 17 spectral biomarkers, were identified by several feature selection procedures (P < 0.0001). These biomarkers were then validated by applying multivariate tools, to evaluate their ability to segregate GCs samples into the four experimental groups. FDA showed a clear separation along the F1-axis (62.75% of discrimination) between GCs from oocytes able (CP, IF groups) or not (FF, EDF groups) to develop into embryos; the F2-axis (24.14% of discrimination) segregated the embryos that gave pregnancy (CP) from those that failed implantation (IF). The confusion matrix (total percentage of correctness = 80.25%) obtained from this analysis pinpointed that GCs from oocytes unable to develop into embryos (FF, EDF) were better characterized than those from oocytes able to give viable embryos (CP, IF). ANOVA (P < 0.05) analysis pinpointed that: each experimental group showed specific macromolecular traits, ascribable to different biological and metabolic characteristics of GCs; these metabolic features were likely associated with different oocytes fates, but not to patient characteristics, since from the same patient we obtained GCs with different metabolic profiles.

LIMITATIONS, REASONS FOR CAUTION

The study is based on a small sample size but provides proof of concept that the GCs' metabolic profile is associated with the companion oocyte fate. The generated model should be further tested on a larger cohort of patients, classified in a similar manner, to assess the potential predictive value of this approach. Ultimately, validity of the proposed approach should be tested in a RCT.

WIDER IMPLICATIONS OF THE FINDINGS

For the first time, the FTIRM analysis of human GCs has demonstrated an approach to better understand the molecular crosstalk between follicular cells and oocytes and has identified potential spectral biomarkers for improving human IVF success rate.

STUDY FUNDING/COMPETING INTEREST(S)

The study was funded by GFI 2014 grant. The authors declare that there is no conflict of interest.

New approach to investigate Common Variable Immunodeficiency patients using spectrochemical analysis of blood

Common variable immune deficiency (CVID) is a primary immunodeficiency disease, characterized by hypogammaglobulinemia, recurrent infections and various complications. The clinical heterogeneity of CVID has hindered identification of an underlying immune defect; diagnosis relies on clinical judgement, alongside evidence-based criteria. The lack of pathognomonic clinical or laboratory features leads to average diagnostic delays of 5 years or more from the onset. Vibrational spectroscopic techniques such as Fourier-transform infrared (FTIR) spectroscopy have recently gained increasing clinical importance, being rapid-, non-invasive and inexpensive methods to obtain information on the content of biological samples. This has led us to apply FTIR spectroscopy to the investigation of blood samples from a cohort of CVID patients; revealing spectral features capable of stratifying CVID patients from healthy controls with sensitivities and specificities of 97% and 93%, respectively for serum, and 94% and 95%, respectively for plasma. Furthermore we identified several discriminating spectral biomarkers; wavenumbers in regions indicative of nucleic acids (984 cm⁻¹, 1053 cm⁻¹, 1084 cm⁻¹, 1115 cm⁻¹, 1528 cm⁻¹, 1639 cm⁻¹), and a collagen-associated biomarker (1528 cm⁻¹), which may represent future candidate biomarkers and provide new knowledge on the aetiology of CVID. This proof-of-concept study provides a basis for developing a novel diagnostic tool for CVID.

Postmortem diagnosis of fatal hypothermia/hyperthermia by spectrochemical analysis of plasma

Postmortem diagnosis of extreme-weather-related deaths is a challenging forensic task. Here, we present a state-of-the-art study that employed attenuated total reflection (ATR) Fourier transform infrared (FTIR) spectroscopy in combination with Chemometrics for postmortem diagnosis of fatal hypothermia/hyperthermia by biochemical investigation of plasma in rats. The results of principal component analysis (PCA) and spectral analysis revealed that plasma samples from the fatal hypothermia, fatal hyperthermia, and control groups, are substantially different from each other based on the spectral variations associated with the lipid, carbohydrate and nucleic acid components. Two partial least squares-discriminant analysis (PLS-DA) classification models (hypothermia-nonhypothermia and hyperthermia-nonhyperthermia binary models) with a 100% accuracy rate were constructed. Subsequently, internal cross-validation was performed to assess the robustness of these two models, which resulted in 98.1 and 100% accuracy. Ultimately, classification predictions of 42 unknown plasma samples were performed by these two models, and both models achieved 100% accuracy. Additionally, our results demonstrated that hemolysis and postmortem hypothermic/hyperthermic effects did not weaken the prediction ability of these two classification models. In summary, this work demonstrates ATR-FTIR spectroscopy's great potential for postmortem diagnosis of fatal hypothermia/hyperthermia.

Direct label-free imaging of brain tissue using synchrotron light: a review of new spectroscopic tools for the modern neuroscientist

The incidence of brain disease and brain disorders is increasing on a global scale. Unfortunately, development of new therapeutic strategies has not increased at the same rate, and brain diseases and brain disorders now inflict substantial health and economic impacts. A greater understanding of the fundamental neurochemistry that underlies healthy brain function, and the chemical pathways that manifest in brain damage or malfunction, are required to enable and accelerate therapeutic development. A previous limitation to the study of brain function and malfunction has been the limited number of techniques that provide both a wealth of biochemical information, and spatially resolved information (i.e., there was a previous lack of techniques that provided direct biochemical or elemental imaging at the cellular level). In recent times, a suite of direct spectroscopic imaging techniques, such as Fourier transform infrared spectroscopy (FTIR), X-ray fluorescence microscopy (XFM), and X-ray absorption spectroscopy (XAS) have been adapted, optimized and integrated into the field of neuroscience, to fill the above mentioned capability-gap. Advancements at synchrotron light sources, such as improved light intensity/flux, increased detector sensitivities and new capabilities of imaging/optics, has pushed the above suite of techniques beyond "proof-of-concept" studies, to routine application to study complex research problems in the field of neuroscience (and other scientific disciplines). This review examines several of the major advancements that have occurred over the last several years, with respect to FTIR, XFM and XAS capabilities at synchrotron facilities, and how the increases in technical capabilities have being integrated and used in the field of neuroscience.

Biochemical detection of fatal hypothermia and hyperthermia in affected rat hypothalamus tissues by Fourier transform infrared spectroscopy

It is difficult to determinate the cause of death from exposure to fatal hypothermia and hyperthermia in forensic casework. Here, we present a state-of-the-art study that employs Fourier-transform infrared (FTIR) spectroscopy to investigate the hypothalamus tissues of fatal hypothermic, fatal hyperthermic and normothermic rats to determine forensically significant biomarkers related to fatal hypothermia and hyperthermia. Our results revealed that the spectral variations in the lipid, protein, carbohydrate and nucleic acid components are highly different for hypothalamuses after exposure to fatal hypothermic, fatal hyperthermic and normothermic conditions. In comparison with the normothermia group, the fatal hypothermia and hyperthermia groups contained higher total lipid amounts but were lower in unsaturated lipids. Additionally, their cell membranes were found to have less motional freedom. Among these three groups, the fatal hyperthermia group contained the lowest total proteins and carbohydrates and the highest aggregated and dysfunctional proteins, while the fatal hypothermia group contained the highest level of nucleic acids. In conclusion, this study demonstrates that FTIR spectroscopy has the potential to become a reliable method for the biochemical characterization of fatal hypothermia and hyperthermia hypothalamus tissues, and this could be used as a postmortem diagnostic feature in fatal hypothermia and hyperthermia deaths.

Application of FTIR and LA-ICPMS Spectroscopies as a Possible Approach for Biochemical Analyses of Different Rat Brain Regions

Fourier Transform Infrared Spectroscopy (FTIR) is a non-destructive analytical technique that has been employed in this research to characterize the biochemical make-up of various rat brain regions. The sensorimotor cortex, caudate putamen, thalamus, and the hippocampus were found to have higher olefinic content—an indicator of a higher degree of unsaturated fatty acids—rich in short-chain fatty acids, and low in ester and lipid contents. While the regions of the corpus callosum, internal, and external capsule were found to contain long-chained and higher-esterified saturated fatty acids. These molecular differences may reflect the roles of the specific regions in information processing and can provide a unique biochemical platform for future studies on the earlier detection of pathology development in the brain, as a consequence of disease or injury. Laser Ablation Inductively Coupled Plasma Mass Spectroscopy (LA-ICP-MS) is another vital analytical technique that was used in this work to analyze the elements’ distribution patterns in various regions of the brain. The complementary data sets allowed the characterization of the brain regions, the chemical dominating groups, and the elemental composition. This set-up may be used for the investigation of changes in the brain caused by diseases and help create a deeper understanding of the interactions between the organic and elemental composition.

Early diagnosis of Alzheimer's disease using infrared spectroscopy of isolated blood samples followed by multivariate analyses

Alzheimer's disease (AD) is the most common cause of dementia, particularly in the elderly. The disease is characterized by cognitive decline that typically starts with insidious memory loss and progresses relentlessly to produce global impairment of all higher cortical functions. Due to better living conditions and health facilities in developed countries, which result in higher overall life spans, these countries report upward trends of AD among their populations. There are, however, no specific diagnostic tests for AD and clinical diagnosis is especially difficult in the earliest stages of the disease. Early diagnosis of AD is frequently subjective and is determined by physicians (generally neurologists, geriatricians, and psychiatrists) depending on their experience. Diagnosing AD requires both medical history and mental status testing. Having trouble with memory does not mean you have AD. AD has no current cure, but treatments for symptoms are available and research continues. In this study, we investigated the potential of infrared microscopy to differentiate between AD patients and controls, using Fourier transform infrared (FTIR) spectroscopy of isolated blood components. FTIR is known as a quick, safe, and minimally invasive method to investigate biological samples. For this goal, we measured infrared spectra from white blood cells (WBCs) and plasma taken from AD patients and controls, with the consent of the patients or their guardians. Applying multivariate analysis, principal component analysis (PCA) followed by linear discriminant analysis (LDA), it was possible to differentiate among the different types of mild, moderate, and severe AD, and the controls, with 85% accuracy when using the WBC spectra and about 77% when using the plasma spectra. When only the moderate and severe stages were included, an 83% accuracy was obtained using the WBC spectra and about 89% when using the plasma spectra.

Differential Diagnosis of the Etiologies of Bacterial and Viral Infections Using Infrared Microscopy of Peripheral Human Blood Samples and Multivariate Analysis

Human viral and bacterial infections are responsible for a variety of diseases that are still the main causes of death and economic burden for society across the globe. Despite the different responses of the immune system to these infections, some of them have similar symptoms, such as fever, sneezing, inflammation, vomiting, diarrhea, and fatigue. Thus, physicians usually encounter difficulties in distinguishing between viral and bacterial infections on the basis of these symptoms. Rapid identification of the etiology of infection is highly important for effective treatment and can save lives in some cases. The current methods used for the identification of the nature of the infection are mainly based on growing the infective agent in culture, which is a time-consuming (over 24 h) and usually expensive process. The main objective of this study was to evaluate the potential of the mid-infrared spectroscopic method for rapid and reliable identification of bacterial and viral infections based on simple peripheral blood samples. For this purpose, white blood cells (WBCs) and plasma were isolated from the peripheral blood samples of patients with confirmed viral or bacterial infections. The obtained spectra were analyzed by multivariate analysis: principle component analysis (PCA) followed by linear discriminant analysis (LDA), to identify the infectious agent type as bacterial or viral in a time span of about 1 h after the collection of the blood sample. Our preliminary results showed that it is possible to determine the infectious agent with high success rates of 82% for sensitivity and 80% for specificity, based on the WBC data.

Relapsing-Remitting Multiple Sclerosis diagnosis from cerebrospinal fluids via Fourier transform infrared spectroscopy coupled with multivariate analysis

Multiple sclerosis (MS) is a chronic, progressive, inflammatory and degenerative disease of central nervous system. Here, we aimed to develop a method for differential diagnosis of Relapsing-Remitting MS (RRMS) and clinically isolated syndrome (CIS) patients, as well as to identify CIS patients who will progress to RRMS, from cerebrospinal fluid (CSF) by infrared (IR) spectroscopy and multivariate analysis. Spectral analyses demonstrated significant differences in the molecular contents, especially in the lipids and Z conformation of DNA of CSF from CIS, CIS to RRMS transformed (TCIS) and RRMS groups. These changes enables the discrimination of diseased groups and controls (individuals with no neurological disease) from each other using hierarchical cluster and principal component analysis. Some CIS samples were consistently clustered in RRMS class, which may indicate that these CIS patients potentially will transform to RRMS over time. Z-DNA band at 795 cm⁻¹ that is existent only in diseased groups and significant increase in carbonyl amount, decrease in amideI/amide II and lipid/protein ratios observed only for RRMS groups can be used as diagnostic biomarkers. The results of the present study shed light on the early diagnosis of RRMS by IR spectroscopy complemented with multivariate analysis tools.

Estimation of the age of human bloodstains under the simulated indoor and outdoor crime scene conditions by ATR-FTIR spectroscopy

Estimation of the age of human bloodstains is of great importance in forensic practices, but it is a challenging task because of the lack of a well-accepted, reliable, and established method. Here, the attenuated total reflection (ATR)-Fourier transform infrared (FTIR) technique combined with advanced chemometric methods was utilized to determine the age of indoor and outdoor bloodstains up to 107 days. The bloodstain storage conditions mimicked crime scene scenarios as closely as possible. Two partial least squares regression models—indoor and outdoor models with 7–85 days—exhibited good performance for external validation, with low values of predictive root mean squared error (5.83 and 4.77) and high R² values (0.94 and 0.96) and residual predictive deviation (4.08 and 5.14), respectively. Two partial least squares–discriminant analysis classification models were built and demonstrated excellent distinction between fresh (age ≤1 d) and older (age >1 d) bloodstains, which is highly valuable for forensic investigations. These findings demonstrate that ATR-FTIR spectroscopy coupled with advanced chemometric methods can be employed as a rapid and non-destructive tool for age estimation of bloodstains in real-world forensic investigation.