Importance of tissue preparation methods in FTIR micro-spectroscopical analysis of biological tissues: 'traps for new users'

Fourier transform InfraRed spectra analyzed by multivariate and machine learning methods in determination spectroscopy marker of prostate cancer in dried serum

Prostate cancer represents the second most prevalent form of cancer in males globally. In the diagnosis of prostate cancer, the most commonly utilised biomarker is prostate-specific antigen (PSA). It is unfortunate that approximately 25 % of men with elevated PSA levels do not have cancer, and that approximately 20 % of patients with prostate cancer have normal serum PSA levels. Accordingly, a more sensitive methodology must still be identified. It is imperative that new diagnostic methods should be non-invasive, cost-effective, rapid, and highly sensitive. Fourier transform infrared spectroscopy (FTIR) is a technique that fulfils all of the aforementioned criteria. Consequently, the present study used FTIR to assess dried serum samples obtained from a cohort of prostate cancer patients (n = 53) and a control group of healthy individuals (n = 40). Furthermore, this study proposes FTIR markers of prostate cancer obtained from serum. For this purpose, FTIR spectra of dried serum were measured and analysed using statistical, chemometric and machine learning (ML) algorithms including decision trees C5.0, Random Forest (RF), k-Nearest Neighbours (kNN) and Support Vector Machine (SVM). The FTIR spectra of serum collected from patients suffering from prostate cancer exhibited a reduced absorbance values of peaks derived from phospholipids, amides, and lipids. However, these differences were not statistically significant. Furthermore, principal component analysis (PCA) demonstrated that it is challenging to distinguish serum samples from healthy and non-healthy patients. The ML algorithms demonstrated that FTIR was capable of differentiating serum collected from both analysed groups of patients with high accuracy (values between 0.74 and 0.93 for the range from 800 cm-1 to 1800 cm-1 and around 0.70 and 1 for the range from 2800 cm-1 to 3000 cm-1), depending on the ML algorithms used. The results demonstrated that the peaks at 1637 cm-1 and 2851 cm-1 could serve as a FTIR marker for prostate cancer in serum samples. Furthermore, the correlation test indicated a clear correlation between these two wavenumbers and four of the five clinical parameters associated with prostate cancer. However, the relatively small number of samples collected only from patients over the age of 60 indicated that the results should be further investigated using a larger number of serum samples collected from a mean age range. In conclusion, this study demonstrated the potential of FTIR for the detection of prostate cancer in serum samples, highlighting the presence of distinctive spectroscopic markers associated with the analysed cancer type.

Infrared imaging with visible light in microfluidic devices: the water absorption barrier

Infrared spectro-microscopy is a powerful technique for analysing chemical maps of cells and tissues for biomedical and clinical applications, yet the strong water absorption in the mid-infrared region is a challenge to overcome, as it overlaps with the spectral fingerprints of biological components. Microfluidic chips offer ultimate control over the water layer thickness and are increasingly used in infrared spectro-microscopy. However, the actual impact of the water layer thickness on the instrument's performance is often left to the experimentalist's intuition and the peculiarities of specific instruments. Aiming to experimentally test the amount of absorption introduced by water with varying layer thicknesses, we fabricated a set of microfluidic devices with three controlled chamber thicknesses, each comprising a simple test pattern made of a well-known photoresist SU-8. We employed two infrared spectro-microscopy methods for measurements. The first method involves using a standard FTIR microscope with a benchtop infrared light source. The second method is a quantum infrared microscopy technique, where infrared imaging is achieved by detecting correlated photons in the visible range. We demonstrated that both methods enable the measurement of the absorption spectrum in the mid-IR region, even in the presence of up to a 30 μm thick water layer on top of a sample pattern. Additionally, the Q-IR technique offers practical advantages over synchrotron-based FTIR, such as reduced complexity, cost, and ease of operation.

Urine Analysed by FTIR, Chemometrics and Machine Learning Methods in Determination Spectroscopy Marker of Prostate Cancer in Urine

Prostate-specific antigen (PSA) is the most commonly used marker of prostate cancer. However, nearly 25% of men with elevated PSA levels do not have cancer and nearly 20% of patients with prostate cancer have normal serum PSA levels. Therefore, in this study, Fourier transform infrared (FTIR) spectroscopy was investigated as a new tool for detection of prostate cancer from urine. Obtained results showed higher levels of glucose, urea and creatinine in urine collected from patients with prostate cancer than that in control. Principal component analysis (PCA) was not noticed possibility of differentiation urine collected from healthy and nonhealthy patients. However, machine learning algorithms showed 0.90 accuracy and precision of FTIR in detection of prostate cancer from urine. We showed that wavenumbers at 1614 cm-1 and 2972 cm-1 were candidates for prostate cancer spectroscopy markers. Importantly, these FTIR markers correlated with Gleason score, PSA and mpMRI PI-RADS category.

Serum and plasma as a good candidates of body fluids for detection lung cancer by FTIR liquid biopsy

Using Fourier Transform Infrared spectroscopy (FTIR), it is possible to show chemical composition of materials and / or profile chemical changes occurring in tissues, cells, and body fluids during onset and progression of diseases. For diagnostic application, the use of blood would be the most appropriate in biospectroscopy studies since, (i) it is easily accessible and, (ii) enables frequent analyses of biochemical changes occurring in pathological states. At present, different studies have investigated potential of serum, plasma and sputum being alternative biofluids for lung cancer detection using FTIR. However, until now, it has not been shown which biofluid; among serum and plasma, that can serve as the best material medium for detecting lung cancer with highest levels of accuracy. In this study, plasma and serum isolated from blood consenting participants without lung cancer symptoms (controls) and lung cancer patients. The samples were measured using FTIR and subsequently analyzed by machine learning (ML) algorithms in order to show which fluids (serum or plasma) would better enhance detection of lung cancer. Higher absorbances values of PO2-, CH2, CH3 and amides vibrations in FTIR spectra of both serum and plasma samples, collected from lung cancer patients were observed in comparison to individuals without lung cancer symptoms (controls). Principal component analysis (PCA) of FTIR spectra showed plasma and serum samples collected from lung cancer patients and individuals without lung cancer symptoms were better differentiated in fingerprinting region (from 800 to 1800 cm- 1) when compared to lipid region (2800-3000 cm- 1). Moreover, also sensitivity specificity and accuracy calculated by logistic regression (LR) and receive operating characteristic (ROC) showed higher values for fingerprint range (800-1800 cm- 1) in comparison with lipids (2800-3000 cm- 1) one for both, serum and plasma. However, using these methods differences between serum and plasma were not existed. From the all obtained results, it was visible, that both fluids could be used in detected lung cancer using FTIR. Moreover, it was also showed that fingerprint range gave a better distinction between the studied patient groups than the lipid range. This was noticeable for both serum and plasma.

Knockout of the Muscle-Specific E3 Ligase MuRF1 Affects Liver Lipid Metabolism upon Dexamethasone Treatment in Mice

In order to preserve muscle mass during catabolic states, investigators are actively searching for a specific inhibitor of MuRF1, the only known E3 ligase that can target muscle contractile proteins for their degradation. However, what would be the consequences of such inhibitors on other organs, both in the short and long term? Indeed, skeletal muscles can provide amino acids for liver gluconeogenesis, which is a crucial adaptation for maintaining glucose homeostasis upon elevated energy demands (e.g., during prolonged starvation). Comparing 3-month-old wild-type and MuRF1-KO mice, we measured tissue weights, liver glycogen, lipid and protein content, and liver biochemical composition using Fourier transform infrared (FTIR) spectrometry in control animals and in dexamethasone (Dex)-treated animals. Dex induces a catabolic situation with muscle atrophy and lipid deposits in the liver. In response to Dex treatment, liver glycogen, lipid, and protein content increased in wild type (WT) and MuRF1-KO mice. We found that MuRF1 deletion differentially affected organ weights, the liver of KO mice being hypertrophied upon Dex treatment when compared to WT mice. Upon Dex treatment, muscle mass was preserved in MuRF1-KO mice, and by contrast, liver lipid content increased more in these animals than in WT mice. PLS-DA analysis of FTIR showed that the levels of 13 markers were significantly altered in KO vs WT mice, witnessing profound alterations of lipid, protein, and glycogen content in the liver due to the absence of MuRF1. Using Nile red and oil red lipid staining, we also found that both membrane-linked lipids and intracellular lipid droplets were altered due to the absence of MuRF1. Altogether, it seems that when the liver is deprived of the possibility of obtaining amino acids from muscle upon Dex treatment, there is a concomitant increase in tissue weight and anabolic activity.

Investigating the influence of molybdenum disulfide quantum dots coated with DSPE-PEG-TPP on molecular structures of liver lipids and proteins: An in vivo study

Molybdenum disulfide (MoS2) quantum dots (QDs) based therapeutic approaches hold great promise for biomedical applications, necessitating a thorough evaluation of their potential effects on biological systems. In this study, we systematically investigated the impact of MoS2 QDs coated with 1,2-distearoyl-sn-glycero-3-phosphoethanolamine-N-[amino(polyethyleneglycol)-2000](DPSE-PEG) linked with (3-carboxypropyl)triphenyl-phosphonium-bromide (TPP) on molecular structures of hepatic tissue lipids and proteins through a multifaceted analysis. The DSPE-PEG-TPP-MoS2 QDs were prepared and administered to the mice daily for 7 weeks. Liver tissues were subjected to a comprehensive examination using various techniques, including Fourier-transform infrared (FTIR) spectroscopy, UV-vis spectroscopy, and liver function tests. FTIR revealed subtle changes in the lipid composition of liver tissues, indicating potential modifications in the cell membrane structure. Also, the (CH stretching and amides I and II regions) analysis unveiled tiny alterations in lipid chain length and fluidity without changes in the protein structures, suggesting a minor influence of DSPE-PEG-TPP-MoS2 QDs on the liver's cellular membrane and no effect on the protein structures. Further scrutiny using UV-vis spectroscopy demonstrated that DSPE-PEG-TPP-MoS2 QDs had no discernible impact on the absorbance intensities of aromatic amino acids and the Soret band. This observation implies that the treatment with SPE-PEG-TPP-MoS2 QDs did not induce significant alterations in helical conformation or the microenvironment surrounding prosthetic groups in liver tissues. The liver function tests, including ALP, ALT, AST, and BIL levels, revealed no statistically significant changes in these key biomarkers despite minor fluctuations in their values, indicating a lack of significant liver dysfunction. This study provides a detailed understanding of the effects of DSPE-PEG-TPP-MoS2 QDs on hepatic lipids and proteins, offering valuable insights into the biocompatibility and limited impact on the molecular and functional aspects of the liver tissue. These findings could be essential for the application of MoS2 QDs-based therapies.

Optimizing near infrared laser irradiation and photosensitizer accumulation period for indocyanine green-mediated photodynamic therapy in breast cancer xenografts: a focus on treatment and characterization

Photodynamic therapy (PDT) is a promising cancer treatment approach. Indocyanine green (ICG) is a water-soluble tricarbocyanine dye with a peak absorption wavelength of around 800 nm and possesses the capacity to produce reactive oxygen species. FTIR spectroscopy is rarely used and offers insights into molecular changes in cancer studies. MCF-7 cells were injected into Nude mouse. Once the tumor had grown to a size of 3-4 mm, mice were randomized into the 12 PDT groups. After each mouse received 5 mg/kg of ICG, they were photo-irradiated with a diode laser emitting light at 809 nm, followed by waiting intervals of 0, 30, 60, and 90 min. Laser irradiation parameters were 150, 250, 500 mW/cm2 and irradiation duration was 1200s. The tumor size was measured every day for four days. The FTIR spectroscopy was used to perform spectral analysis on tumor tissue samples. Four distinct regions (3600-2800 cm-1, 1750-1550 cm-1, 1540-1450 cm-1, and 1700-1100 cm-1) were analyzed, and Hierarchical Cluster study was carried out. A decrease in tumor volume was observed with all PDT applications, except, increases in tumor volume was observed at 150mW 90-minute group. PDT administered after 90 min revealed variations in 150mW and 250mW laser powers in the 3600 cm-1-2800 cm-1 range. The 250mW and 500mW applications resulted in a considerable reduction in fibroadenoma and carcinoma tissues, according to an analysis comparing the A1695 / A1635 ratio. It is proposed that the ideal treatments for further investigation have a power output of 250 mW.

Rapid Hyperspectral Photothermal Mid-Infrared Spectroscopic Imaging from Sparse Data for Gynecologic Cancer Tissue Subtyping

Ovarian cancer detection has traditionally relied on a multistep process that includes biopsy, tissue staining, and morphological analysis by experienced pathologists. While widely practiced, this conventional approach suffers from several drawbacks: it is qualitative, time-intensive, and heavily dependent on the quality of staining. Mid-infrared (MIR) hyperspectral photothermal imaging is a label-free, biochemically quantitative technology that, when combined with machine learning algorithms, can eliminate the need for staining and provide quantitative results comparable to traditional histology. However, this technology is slow. This work presents a novel approach to MIR photothermal imaging that enhances its speed by an order of magnitude. This method resolves the longstanding trade-off between imaging resolution and data collection speed, enabling the reconstruction of high-quality, high-resolution images from undersampled data sets and achieving a 10X improvement in data acquisition time. We assessed the performance of our sparse imaging methodology using a variety of quantitative metrics, including mean squared error (MSE), structural similarity index (SSIM), and tissue subtype classification accuracies, employing both random forest and convolutional neural network (CNN) models, accompanied by Receiver Operating Characteristic (ROC) curves. Our statistically robust analysis, based on data from 100 ovarian cancer patient samples and over 65 million data points, demonstrates the method's capability to produce superior image quality and accurately distinguish between different gynecological tissue types with segmentation accuracy exceeding 95%. Our work demonstrates the feasibility of integrating rapid MIR hyperspectral photothermal imaging with machine learning in enhancing ovarian cancer tissue characterization, paving the way for quantitative, label-free, automated histopathology.

Characterization of sub-micrometre-sized voids in fixed human brain tissue using scanning X-ray microdiffraction

Using a 5 µm-diameter X-ray beam, we collected scanning X-ray microdiffraction in both the small-angle (SAXS) and the wide-angle (WAXS) regimes from thin sections of fixed human brain tissue from Alzheimer's subjects. The intensity of scattering in the SAXS regime of these patterns exhibits essentially no correlation with the observed intensity in the WAXS regime, indicating that the structures responsible for these two portions of the diffraction patterns, which reflect different length scales, are distinct. SAXS scattering exhibits a power-law behavior in which the log of intensity decreases linearly with the log of the scattering angle. The slope of the log-log curve is roughly proportional to the intensity in the SAXS regime and, surprisingly, inversely proportional to the intensity in the WAXS regime. We interpret these observations as being due to the presence of sub-micrometre-sized voids formed during dehydration of the fixed tissue. The SAXS intensity is due largely to scattering from these voids, while the WAXS intensity derives from the secondary structures of macromolecular material surrounding the voids. The ability to detect and map the presence of voids within thin sections of fixed tissue has the potential to provide novel information on the degradation of human brain tissue in neurodegenerative diseases.

Structural Mapping of Protein Aggregates in Live Cells Modeling Huntington's Disease

While protein aggregation is a hallmark of many neurodegenerative diseases, acquiring structural information on protein aggregates inside live cells remains challenging. Traditional microscopy does not provide structural information on protein systems. Routinely used fluorescent protein tags, such as Green Fluorescent Protein (GFP), might perturb native structures. Here, we report a counter-propagating mid-infrared photothermal imaging approach enabling mapping of secondary structure of protein aggregates in live cells modeling Huntington's disease. By comparing mid-infrared photothermal spectra of label-free and GFP-tagged huntingtin inclusions, we demonstrate that GFP fusions indeed perturb the secondary structure of aggregates. By implementing spectra with small spatial step for dissecting spectral features within sub-micrometer distances, we reveal that huntingtin inclusions partition into a β-sheet-rich core and a ɑ-helix-rich shell. We further demonstrate that this structural partition exists only in cells with the [RNQ+] prion state, while [rnq-] cells only carry smaller β-rich non-toxic aggregates. Collectively, our methodology has the potential to unveil detailed structural information on protein assemblies in live cells, enabling high-throughput structural screenings of macromolecular assemblies.

Diagnosis of common intraosseous lesions of the dentomaxillofacial region by chemometry-assisted FT-IR spectroscopy in dental tissue samples

PURPOSES

This study aimed to determine the differential diagnosis of three intraosseous lesions (odontogenic keratocyst (OKC), central giant cell granuloma (CGCG), and dentigerous cyst (DC)) of the dentomaxillofacial region with very similar radiological and clinical features by using chemometrics assisted FT-IR (Fourier transform infrared) spectroscopy in tissue samples.

METHODS

Tissue samples (exposed to formaldehyde for a similar time) of 20-micron thickness belonging to 19 intraosseous lesions diagnosed histopathologically were obtained from the pathology laboratory. The samples were analyzed by FT-IR spectroscopic method using the 400-4000 cm-1 wavenumber range, and the obtained spectra of the samples were evaluated using the orthogonal partial least squares discriminant analysis (OPLS-DA) algorithm.

RESULTS

The intraosseous lesions with different histopathological diagnoses were accurately and precisely clustered with different FT-IR bands corresponding to the main molecular vibrations, especially the phosphodiester region, of the tissue components using the proposed model with 3 latent variables.

CONCLUSIONS

The model showed high sensitivity and specificity. The present study is the first to report the elucidation of clear spectral differences between similar lesions in the maxillofacial region. In the future, the FT-IR method may be used in the non-destructive classification of similar lesions in the maxillofacial region as an alternative to histopathological evaluation.

Metastasis diagnosis using attenuated total reflection-Fourier transform infra-red (ATR-FTIR) spectroscopy

The suitability of Fourier transform infrared spectroscopy as a metastasis prognostic tool has not been reported for some cancer types. Our main aim was to show spectroscopic differences between live un-preprocessed cancer cells of different metastatic levels. Spectra of four cancer cell pairs, including colon cancer (SW480, SW620); human melanoma (WM115, WM266.4); murine melanoma (B16F01, B16F10); and breast cancer (MCF7, MDA-MB-231); each pair having the same genetic background, but different metastatic level were analyzed in the regions 1400-1700 cm-1 and 3100-3500 cm-1 using Principal Component Analysis, curve fitting, multifractal dimension and receiver operating characteristic (ROC) curves. The results show spectral markers I1540/I1473, I1652/I1473, [Formula: see text], and multifractal dimension of the spectral images are significantly different for the cells based on their metastatic levels. ROC curve analysis showed good diagnostic performance of the spectral markers in separating cells based on metastatic degree, with areas under the ROC curves having 95% confidence interval lower limits greater than 0.5 for most instances. These spectral features can be important in predicting the probability of metastasis in primary tumors, providing useful guidance for treatment planning. Our markers are effective in differentiating metastatic levels without sample fixation or drying and therefore could be compactible for future use in in-vivo procedures involving spectroscopic cancer diagnosis.

Biochemical analysis of Hyalomma dromedarii salivary glands and gut tissues using SR-FTIR micro-spectroscopy

Ticks are obligatory voracious blood feeders infesting diverse vertebrate hosts, that have a crucial role in the transmission of diverse pathogens that threaten human and animal health. The continuous emergence of tick-borne diseases due to combined worldwide climatic changes, human activities, and acaricide-resistant tick strains, necessitates the development of novel ameliorative tick control strategies such as vaccines. The synchrotron-based Fourier transform infrared micro-spectroscopy (SR-FTIR) is a bioanalytical microprobe capable of exploring the molecular chemistry within microstructures at a cellular or subcellular level and is considered as a nondestructive analytical approach for biological specimens. In this study, SR-FTIR analysis was able to explore a qualitative and semi-quantitative biochemical composition of gut and salivary glands of Hyalomma dromedarii (H. dromedarii) tick detecting differences in the biochemical composition of both tissues. A notable observation regarding Amide I secondary structure protein profile was the higher ratio of aggregated strands in salivary gland and beta turns in gut tissues. Regarding the lipid profile, there was a higher intensity of lipid regions in gut tissue when compared to salivary glands. This detailed information on the biochemical compositions of tick tissues could assist in selecting vaccine and/or control candidates. Altogether, these findings confirmed SR-FTIR spectroscopy as a tool for detecting differences in the biochemical composition of H. dromedarii salivary glands and gut tissues. This approach could potentially be extended to the analysis of other ticks that are vectors of important diseases such as babesiosis and theileriosis.

Rapid hyperspectral photothermal mid-infrared spectroscopic imaging from sparse data for gynecologic cancer tissue subtyping

Ovarian cancer detection has traditionally relied on a multi-step process that includes biopsy, tissue staining, and morphological analysis by experienced pathologists. While widely practiced, this conventional approach suffers from several drawbacks: it is qualitative, time-intensive, and heavily dependent on the quality of staining. Mid-infrared (MIR) hyperspectral photothermal imaging is a label-free, biochemically quantitative technology that, when combined with machine learning algorithms, can eliminate the need for staining and provide quantitative results comparable to traditional histology. However, this technology is slow. This work presents a novel approach to MIR photothermal imaging that enhances its speed by an order of magnitude. Our method significantly accelerates data collection by capturing a combination of highresolution and interleaved, lower-resolution infrared band images and applying computational techniques for data interpolation. We effectively minimize data collection requirements by leveraging sparse data acquisition and employing curvelet-based reconstruction algorithms. This approach enhances imaging speed without compromising image quality and ensures robust tissue segmentation. This method resolves the longstanding trade-off between imaging resolution and data collection speed, enabling the reconstruction of high-quality, high-resolution images from undersampled datasets and achieving a 10X improvement in data acquisition time. We assessed the performance of our sparse imaging methodology using a variety of quantitative metrics, including mean squared error (MSE), structural similarity index (SSIM), and tissue subtype classification accuracies, employing both random forest and convolutional neural network (CNN) models, accompanied by Receiver Operating Characteristic (ROC) curves. Our statistically robust analysis, based on data from 100 ovarian cancer patient samples and over 65 million data points, demonstrates the method's capability to produce superior image quality and accurately distinguish between different gynecological tissue types with segmentation accuracy exceeding 95%. Our work demonstrates the feasibility of integrating rapid MIR hyperspectral photothermal imaging with machine learning in enhancing ovarian cancer tissue characterization, paving the way for quantitative, label-free, automated histopathology. It represents a significant leap forward from traditional histopathological methods, offering profound implications for cancer diagnostics and treatment decision-making.

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.

Vibrational spectroscopy identifies myocardial chemical modifications in heart failure with preserved ejection fraction

BACKGROUND

Vibrational spectroscopy can be a valuable tool to monitor the markers of cardiovascular diseases. In the present work, we explored the vibrational spectroscopy characteristics of the cardiac tissue in an experimental model of heart failure with preserved ejection fraction (HFpEF). The goal was to detect early cardiac chemical modifications associated with the development of HFpEF.

METHODS

We used the Fourier-transform infrared (FTIR) and Raman micro-spectroscopic techniques to provide complementary and objective tools for the histological assessment of heart tissues from an animal model of HFpEF. A new sampling technique was adopted (tissue print on a CaF2 disk) to characterize the extracellular matrix.

RESULTS

Several spectroscopic markers (lipids, carbohydrates, and glutamate bands) were recognized in the cardiac ventricles due to the comorbidities associated with the pathology, such as obesity and diabetes. Besides, abnormal collagen cross-linking and a decrease in tryptophan content were observed and related to the stiffening of ventricles and to the inflammatory state which is a favourable condition for HFpEF.

CONCLUSIONS

By the analyses of tissues and tissue prints, FTIR and Raman techniques were shown to be highly sensitive and selective in detecting changes in the chemistry of the heart in experimental HFpEF and its related comorbidities. Vibrational spectroscopy is a new approach that can identify novel biomarkers for early detection of HFpEF.

Linearly Polarized Infrared Spectroscopy for the Analysis of Biological Materials

The analysis of biological samples with polarized infrared spectroscopy (p-IR) has long been a widely practiced method for the determination of sample orientation and structural properties. In contrast to earlier works, which employed this method to investigate the fundamental chemistry of biological systems, recent interests are moving toward "real-world" applications for the evaluation and diagnosis of pathological states. This focal point review provides an up-to-date synopsis of the knowledge of biological materials garnered through linearly p-IR on biomolecules, cells, and tissues. An overview of the theory with special consideration to biological samples is provided. Different modalities which can be employed along with their capabilities and limitations are outlined. Furthermore, an in-depth discussion of factors regarding sample preparation, sample properties, and instrumentation, which can affect p-IR analysis is provided. Additionally, attention is drawn to the potential impacts of analysis of biological samples with inherently polarized light sources, such as synchrotron light and quantum cascade lasers. The vast applications of p-IR for the determination of the structure and orientation of biological samples are given. In conclusion, with considerations to emerging instrumentation, findings by other techniques, and the shift of focus toward clinical applications, we speculate on the future directions of this methodology.

In vitro cholesterol lowering activity of Ganoderma australe mycelia based on mass spectrometry, synchrotron Fourier-transform infrared analysis and liver-spheroid bioactivity

Mycelia were cultivated from a Thai wild mushroom identified as Ganoderma australe based on polymerase chain reaction (PCR) and morphological analyses. The mycelial extracts were examined for their active ingredients using a liquid chromatography-tandem mass spectrometry (LC‒MS/MS) method. This revealed the presence of lovastatin and tentative compounds including p-coumaric, nicotinamide, gamma-aminobutyric acid, choline, nucleosides, amino acids, and saccharides. The extracts had an inhibitory effect on the activity of HMG-CoA reductase in a concentration-dependent manner. At 2.5 mg/mL, the G. australe extracts did not interfere with the viability of HepG2 spheroids, but their biochemical composition was altered as determined by Fourier-transform infrared (FTIR) spectroscopy. The lipid profile of the spheroids treated with the mycelial extract was distinct from that of the control and the 5 µM lovastatin treatment, corresponding with the production of cholesterol by the spheroids. The mycelia of G. australe increased the percentage of high-density lipoprotein (HDL) production to 71.35 ± 2.74%, compared to the control and lovastatin-treated spheroids (33.26 ± 3.15% and 32.13 ± 3.24%, respectively). This study revealed the superior effect of natural compound mixtures to pure lovastatin, and the potential use of Thailand's wild G. australe as a functional food to prevent or alleviate hypercholesterolemia.

Interactions of N-Mannich Bases of Pyrrolo[3,4-c]pyrrole with Artificial Models of Cell Membranes and Plasma Proteins, Evaluation of Anti-Inflammatory and Antioxidant Activity

Despite the widespread and easy access to NSAIDs, effective and safe treatment of various inflammatory disorders is still a serious challenge because of the severe adverse effects distinctive to these drugs. The Mannich base derivatives of pyrrolo[3,4-c]pyrrole are potent, preferential COX-2 inhibitors with a COX-2/COX-1 inhibitory ratio better than meloxicam. Therefore, we chose the six most promising molecules and subjected them to further in-depth research. The current study presents the extensive biological, spectroscopic and in silico evaluation of the activity and physicochemical properties of pyrrolo[3,4-c]pyrrole derivatives. Aware of the advantages of dual COX-LOX inhibition, we investigated the 15-LOX inhibitory activity of these molecules. We also examined their antioxidant effect in several in vitro experiments in a protection and regeneration model. Furthermore, we defined how studied compounds interact with artificial models of cell membranes, which is extremely important for drugs administered orally with an intracellular target. The interactions and binding mode of the derivatives with the most abundant plasma proteins-human serum albumin and alpha-1-acid glycoprotein-are also described. Finally, we used computational techniques to evaluate their pharmacokinetic properties. According to the obtained results, we can state that pyrrolo[3,4-c]pyrrole derivatives are promising anti-inflammatory and antioxidant agents with potentially good membrane permeability.

Characterization of Different Types of Epiretinal Proliferations by Synchrotron Radiation-Based Fourier Transform Infrared Micro-Spectroscopy

Pathological tissue on the surface of the retina that can be of different etiology and pathogenesis can cause changes in the retina that have a direct consequence on vision. Tissues of different etiology and pathogenesis have different morphological structures and also different macromolecule compositions usually characteristic of specific diseases. In this study, we evaluated and compared biochemical differences among samples of three different types of epiretinal proliferations: idiopathic epiretinal membrane (ERMi), membranes in proliferative vitreoretinopathy (PVRm), and proliferative diabetic retinopathy (PDRm). The membranes were analyzed by using synchrotron radiation-based Fourier transform infrared micro-spectroscopy (SR-FTIR). We used the SR-FTIR micro-spectroscopy setup, where measurements were set to achieve a high resolution that was capable of showing clear biochemical spectra in biological tissue. We were able to identify differences between PVRm, PDRm, and ERMi in protein and lipid structure; collagen content and collagen maturity; differences in proteoglycan presence; protein phosphorylation; and DNA expression. Collagen showed the strongest expression in PDRm, lower expression in ERMi, and very low expression in PVRm. We also demonstrated the presence of silicone oil (SO) or polydimethylsiloxane in the structure of PVRm after SO endotamponade. This finding suggests that SO, in addition to its many benefits as an important tool in vitreoretinal surgery, could be involved in PVRm formation.

Melatonin ameliorates chronic copper-induced lung injury

Copper (Cu) is an important trace element required for several biological processes. The use of copper is increasing gradually in several applications. Previous studies suggest that excess levels of copper are attributed to induce oxidative stress and inflammation, mediating tissue damage. Inline, melatonin the hormone of darkness has been reported to exhibit various therapeutic effects including strong free radical scavenging properties and anti-inflammatory effects. However, its effects against pulmonary injury promoted by copper are not explored and remain unclear so far. Therefore, the present study was aimed to investigate the protective effect of melatonin against copper-induced lung damage. Female Sprague Dawley (SD) rats were exposed to 250 ppm of copper in drinking water for 16 weeks and treated with melatonin (i.p.) 5 and 10 mg/kg from the week (13-16th). The extent of tissue damage was assessed by tissue oxidative stress parameters, metal estimation and histological analysis. Copper-challenged rats showed altered oxidative stress variables. In addition, metal analysis revealed increased copper accumulation in the lungs and histological staining results further indicated severe tissue injury and inflammatory cell infiltration in copper-exposed rats. To this side, treatment with melatonin showed antioxidant and anti-inflammatory activities evidenced by reduced oxidative stress, tissue inflammation and collagen deposition as compared to copper-exposed animals. Moreover, spectral findings suggested melatonin treatment modulated the frequency sift, as compared to copper-challenged animals. Altogether, the present results suggest that melatonin might play a potential role in preventing copper-induced lung aberrations via inhibiting the ROS-mediated oxidative stress and inflammation.

The Impact of Tissue Preparation on Salivary Gland Tumors Investigated by Fourier-Transform Infrared Microspectroscopy

Due to the wide variety of benign and malignant salivary gland tumors, classification and malignant behavior determination based on histomorphological criteria can be difficult and sometimes impossible. Spectroscopical procedures can acquire molecular biological information without destroying the tissue within the measurement processes. Since several tissue preparation procedures exist, our study investigated the impact of these preparations on the chemical composition of healthy and tumorous salivary gland tissue by Fourier-transform infrared (FTIR) microspectroscopy. Sequential tissue cross-sections were prepared from native, formalin-fixed and formalin-fixed paraffin-embedded (FFPE) tissue and analyzed. The FFPE cross-sections were dewaxed and remeasured. By using principal component analysis (PCA) combined with a discriminant analysis (DA), robust models for the distinction of sample preparations were built individually for each parotid tissue type. As a result, the PCA-DA model evaluation showed a high similarity between native and formalin-fixed tissues based on their chemical composition. Thus, formalin-fixed tissues are highly representative of the native samples and facilitate a transfer from scientific laboratory analysis into the clinical routine due to their robust nature. Furthermore, the dewaxing of the cross-sections entails the loss of molecular information. Our study successfully demonstrated how FTIR microspectroscopy can be used as a powerful tool within existing clinical workflows.

Bioengineering strategies for 3D bioprinting of tubular construct using tissue-specific decellularized extracellular matrix

The goal of the current study is to develop an extracellular matrix bioink that could mimic the biochemical components present in natural blood vessels. Here, we have used an innovative approach to recycle the discarded varicose vein for isolation of endothelial cells and decellularization of the same sample to formulate the decellularized extracellular matrix (dECM) bioink. The shift towards dECM bioink observed as varicose vein dECM provides the tissue-specific biochemical factors that will enhance the regeneration capability. Interestingly, the encapsulated umbilical cord mesenchymal stem cells expressed the markers of vascular smooth muscle cells because of the cues present in the vein dECM. Further, in vitro immunological investigation of dECM revealed a predominant M2 polarization which could further aid in tissue remodeling. A novel approach was used to fabricate vascular construct using 3D bioprinting without secondary support. The outcomes suggest that this could be a potential approach for patient- and tissue-specific blood vessel regeneration.

The Convergence of FTIR and EVs: Emergence Strategy for Non-Invasive Cancer Markers Discovery

In conjunction with imaging analysis, pathology-based assessments of biopsied tissue are the gold standard for diagnosing solid tumors. However, the disadvantages of tissue biopsies, such as being invasive, time-consuming, and labor-intensive, have urged the development of an alternate method, liquid biopsy, that involves sampling and clinical assessment of various bodily fluids for cancer diagnosis. Meanwhile, extracellular vesicles (EVs) are circulating biomarkers that carry molecular profiles of their cell or tissue origins and have emerged as one of the most promising biomarkers for cancer. Owing to the biological information that can be obtained through EVs' membrane surface markers and their cargo loaded with biomolecules such as nucleic acids, proteins, and lipids, EVs have become useful in cancer diagnosis and therapeutic applications. Fourier-transform infrared spectroscopy (FTIR) allows rapid, non-destructive, label-free molecular profiling of EVs with minimal sample preparation. Since the heterogeneity of EV subpopulations may result in complicated FTIR spectra that are highly diverse, computational-assisted FTIR spectroscopy is employed in many studies to provide fingerprint spectra of malignant and non-malignant samples, allowing classification with high accuracy, specificity, and sensitivity. In view of this, FTIR-EV approach carries a great potential in cancer detection. The progression of FTIR-based biomarker identification in EV research, the rationale of the integration of a computationally assisted approach, along with the challenges of clinical translation are the focus of this review.

Evaluating Subtle Pathological Changes in Early Myocardial Ischemia Using Spectral Histopathology

Early myocardial ischemia (EMI) is morphologically challenging, and the results from conventional histological staining may be subjective, imprecise, or even silent. The size of myocardial necrosis determines the acute and long-term mortality of EMI. The precise diagnosis of myocardial ischemia is critical for both clinical management and forensic investigation. Fourier transform infrared (FTIR) spectroscopic imaging is a highly sensitive tool for detecting protein conformations and imaging protein profiles. The aim of this study was to evaluate the application of FTIR imaging with multivariate analysis to detect biochemical changes in the protein conformation in the early phase of myocardial ischemia and to visually classify different disease states. The spectra and curve fitting results revealed that the total protein content decreased significantly in the EMI group and that the α-helix content of the secondary protein structure continuously decreased as ischemia progressed, while the β-sheet content increased. Differences in the control and EMI groups and perfused and ischemic myocardium were confirmed using principal component analysis and partial least squares discriminant analysis. Next, two support vector machine classifiers were effectively created. The accuracy, recall, and precision were 99.98, 99.96, and 100.00%, respectively, to differentiate the EMI group from the control group and 99.25, 98.95, and 99.54%, respectively, to differentiate perfused and ischemic myocardium. Ultimately, high EMI diagnostic accuracy was achieved with 100.00% recall and 100.00% precision, and ischemic myocardium diagnostic accuracy was achieved with 99.30% recall and 99.53% precision for the test set. This pilot study demonstrated that FTIR imaging is a powerful automated quantitative analysis tool to detect EMI without morphological changes and will improve diagnostic accuracy and patient prognosis.

Possible use of corneal lenticule in surgery of corneal diseases (literature review)

In this review, we analyzed the domestic and foreign literature on the use of corneal lenticula obtained by keratorefractive surgery using the SMILE technology (SMall Incision Lenticula Extraction). Research is being actively carried out on the use of a lenticular tissue for refractive purposes: for the correction of hyperopia (LIKE – Lenticular Intrastromal Keratoplasty), for the correction of presbyopia (PEARL – PrEsbyopic Allogenic Refractive Lenticule). A significant amount of works are devoted to the use of lenticular tissue for the treatment of keratectasias of various origins. For example, a number of authors for the treatment of keratoconus suggest implantation of a lenticule into the recipient’s corneal pocket formed by a femtolaser (SLAK – Stromal lenticule addition keratoplasty). Clinical cases of combined treatment are described: implantation of a lenticule and corneal intrastromal segments for the treatment of corneal pellucid degeneration. A large number of works are devoted to the use of lenticules for tectonic coverage of ulcerative defects, marginal thinning in Mooren’s ulcer. Several clinical cases of the use of a corneal lenticule to cover a deep corneal defect in recurrent pterygium are described. This review also included articles on the storage and decellularization of corneal lenticules. The analyzed articles show a wide area of application of the corneal lenticule; however, more research is required in each of the areas of application, and it is also necessary to solve the problem of procurement and storage of lenticular tissue.

Small-angle X-ray microdiffraction from fibrils embedded in tissue thin sections

Small-angle X-ray scattering (SAXS) from fibrils embedded in a fixed, thin section of tissue includes contributions from the fibrils, the polymeric matrix surrounding the fibrils, other constituents of the tissue, and cross-terms due to the spatial correlation between fibrils and neighboring molecules. This complex mixture severely limits the amount of information that can be extracted from scattering studies. However, availability of micro- and nano-beams has made the measurement of scattering from very small volumes possible, which, in some cases, may be dominated by a single fibrillar constituent. In such cases, information about the predominant species may be accessible. Nevertheless, even in these cases, the correlations between the positions of fibrils and other constituents have a significant impact on the observed scattering. Here, strategies are proposed to extract partial information about fibril structure and tissue organization on the basis of SAXS from samples of this type. It is shown that the spatial correlation function of the fibril in the direction perpendicular to the fibril axis can be computed and contains information about the predominant fibril structure and the organization of the surrounding tissue matrix. This has significant advantages over approaches based on techniques developed for X-ray solution scattering. Examples of correlation calculations in different types of samples are given to demonstrate the information that can be obtained from these measurements.

Performance Evaluation of Focal Plane Array (FPA)-FTIR and Synchrotron Radiation (SR)-FTIR Microspectroscopy to Classify Rice Components

The development of biochemical analysis techniques to study heterogeneous biological samples is increasing. These techniques include synchrotron radiation Fourier transform infrared (SR-FTIR) microspectroscopy. This method has been applied to analyze biological tissue with multivariate statistical analysis to classify the components revealed by the spectral data. This study aims to compare the efficiencies of SR-FTIR microspectroscopy and focal plane array (FPA)-FTIR microspectroscopy when classifying rice tissue components. Spectral data were acquired for mapping the same sample areas from both techniques. Principal component analysis and cluster imaging were used to investigate the biochemical variations of the tissue types. The classification was based on the functional groups of pectin, protein, and polysaccharide. Four layers from SR-FTIR microspectroscopy including pericarp, aleurone layer, sub-aleurone layer, and endosperm were classified using cluster imaging, while FPA-FTIR microspectroscopy could classify only three layers of pericarp, aleurone layer, and endosperm. Moreover, SR-FTIR microspectroscopy increased the image contrast of the biochemical distribution in rice tissue more efficiently than FPA-FTIR microspectroscopy. We have demonstrated the capability of the high-resolution synchrotron technique and its ability to clarify small structures in rice tissue. The use of this technique might increase in future studies of tissue characterization.

Mid-Infrared Imaging Characterization to Differentiate Lung Cancer Subtypes

Introduction: Lung cancer is the most common malignancy worldwide. Squamous cell carcinoma (SQ) and adenocarcinoma (LUAD) are the two most frequent histological subtypes. Small cell carcinoma (SCLC) subtype has the worst prognosis. Differential diagnosis is essential for proper oncological treatment. Life science associated mid- and near-infrared based microscopic techniques have been developed exponentially, especially in the past decade. Vibrational spectroscopy is a potential non-destructive approach to investigate malignancies.

Aims: Our goal was to differentiate lung cancer subtypes by their label-free mid-infrared spectra using supervised multivariate analyses.

Material and Methods: Formalin-fixed paraffin-embedded (FFPE) samples were selected from the archives. Three subtypes were selected for each group: 10-10 cases SQ, LUAD and SCLC. 2 μm thick sections were cut and laid on aluminium coated glass slides. Transflection optical setup was applied on Perkin-Elmer infrared microscope. 250 × 600 μm areas were imaged and the so-called mid-infrared fingerprint region (1800-648cm⁻¹) was further analysed with linear discriminant analysis (LDA) and support vector machine (SVM) methods.

Results: Both “patient-based” and “pixel-based” approaches were examined. Patient-based analysis by using 3 LDA models and 2 SVM models resulted in different separations. The higher the cut-off value the lower is the accuracy. The linear C-support vector classification (C-SVC) SVM resulted in the best (100%) accuracy for the three subtypes using a 50% cut-off value. The pixel-based analysis gave, similarly, the linear C-SVC SVM model to be the most efficient in the statistical indicators (SQ sensitivity 81.65%, LUAD sensitivity 82.89% and SCLC sensitivity 88.89%). The spectra cut-off, the kernel function and the algorithm function influence the accuracy.

Conclusion: Mid-Infrared imaging could be used to differentiate FFPE lung cancer subtypes. Supervised multivariate tools are promising to accurately separate lung tumor subtypes. The long-term perspective is to develop a spectroscopy-based diagnostic tool, revolutionizing medical differential diagnostics, especially cancer identification.

Scanning x-ray microdiffraction: In situ molecular imaging of tissue and materials

Scanning x-ray microdiffraction of complex tissues and materials is an emerging method for the study of macromolecular structures in situ, providing information on the way molecular constituents are arranged and interact with their microenvironment. Acting as a bridge between high-resolution images of individual constituents and lower resolution microscopies that generate global views of material, scanning microdiffraction provides an approach to study the functioning of complex tissues across multiple length scales. Here, we discuss the methodology, summarize results from recent studies, and discuss the potential of the technique for future studies coordinated with other biophysical techniques.

Mapping the Spatial Distribution of Fibrillar Polymorphs in Human Brain Tissue

Alzheimer's disease (AD) is a neurodegenerative disorder defined by the progressive formation and spread of fibrillar aggregates of Aβ peptide and tau protein. Polymorphic forms of these aggregates may contribute to disease in varying ways since different neuropathologies appear to be associated with different sets of fibrillar structures and follow distinct pathological trajectories that elicit characteristic clinical phenotypes. The molecular mechanisms underlying the spread of these aggregates in disease may include nucleation, replication, and migration all of which could vary with polymorphic form, stage of disease, and region of brain. Given the linkage between mechanisms of progression and distribution of polymorphs, mapping the distribution of fibrillar structures in situ has the potential to discriminate between mechanisms of progression. However, the means of carrying out this mapping are limited. Optical microscopy lacks the resolution to discriminate between polymorphs in situ, and higher resolution tools such as ssNMR and cryoEM require the isolation of fibrils from tissue, destroying relevant spatial information. Here, we demonstrate the use of scanning x-ray microdiffraction (XMD) to map the locations of fibrillar polymorphs of Aβ peptides and tau protein in histological thin sections of human brain tissue. Coordinated examination of serial sections by immunohistochemistry was used to aid in the interpretation of scattering patterns and to put the observations in a broader anatomical context. Scattering from lesions in tissue shown to be rich in Aβ fibrils by immunohistochemistry exhibited scattering patterns with a prototypical 4.7 Å cross-β peak, and overall intensity distribution that compared well with that predicted from high resolution structures. Scattering from lesions in tissue with extensive tau pathology also exhibited a 4.7 Å cross-β peak but with intensity distributions that were distinct from those seen in Aβ-rich regions. In summary, these observations demonstrate that XMD is a rich source of information on the distribution of fibrillar polymorphs in diseased human brain tissue. When used in coordination with neuropathological examination it has the potential to provide novel insights into the molecular mechanisms underlying disease.

Contribution of Infrared Spectroscopy to the Understanding of Amyloid Protein Aggregation in Complex Systems

Infrared (IR) spectroscopy is a label-free and non-invasive technique that probes the vibrational modes of molecules, thus providing a structure-specific spectrum. The development of infrared spectroscopic approaches that enable the collection of the IR spectrum from a selected sample area, from micro- to nano-scale lateral resolutions, allowed to extend their application to more complex biological systems, such as intact cells and tissues, thus exerting an enormous attraction in biology and medicine. Here, we will present recent works that illustrate in particular the applications of IR spectroscopy to the in situ characterization of the conformational properties of protein aggregates and to the investigation of the other biomolecules surrounding the amyloids. Moreover, we will discuss the potential of IR spectroscopy to the monitoring of cell perturbations induced by protein aggregates. The essential support of multivariate analyses to objectively pull out the significant and non-redundant information from the spectra of highly complex systems will be also outlined.

Identification of myocardial fibrosis by ATR-FTIR spectroscopy combined with chemometrics

Different degrees of myocardial fibrosis can often be observed in sudden cardiac death cases, so that the identification of myocardial fibrosis is an important step in forensics to identify cardiac death. Previous methods are restricted by complex algorithms, high cost, low sensitivity and high requirements. Attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy is an efficient and rapid method to identify tissue types, which has been used increasingly in forensics. This study aims to identify novel biophysical biomarkers of myocardial fibrosis and establish a prediction model by using ATR-FTIR analysis combined with chemometrics. A total of 129 tissue blocks taken from human hearts were cut into slices, and then ATR-FTIR spectroscopy and hematoxylin and eosin (HE) staining were performed. By using HE staining, the samples were divided into the experimental group (with myocardial fibrosis) and the control group (without myocardial fibrosis). The chemometrics classification results showed that the sensitivity and specificity of the training dataset were 0.91 and 1.0 respectively, and the sensitivity and specificity of the predictive dataset were 0.862 and 0.900. This study demonstrated that ATR-FTIR spectroscopy combined with chemometrics is a novel method for identifying myocardial fibrosis.

Acid-Catalyzed Liquefaction of Biomasses from Poplar Clones for Short Rotation Coppice Cultivations

Liquefaction of biomass delivers a liquid bio-oil with relevant chemical and energetic applications. In this study we coupled it with short rotation coppice (SRC) intensively managed poplar cultivations aimed at biomass production while safeguarding environmental principles of soil quality and biodiversity. We carried out acid-catalyzed liquefaction, at 160 °C and atmospheric pressure, with eight poplar clones from SRC cultivations. The bio-oil yields were high, ranging between 70.7 and 81.5%. Average gains of bio-oil, by comparison of raw biomasses, in elementary carbon and hydrogen and high heating, were 25.6, 67, and 74%, respectively. Loss of oxygen and O/C ratios averaged 38 and 51%, respectively. Amounts of elementary carbon, oxygen, and hydrogen in bio-oil were 65, 26, and 8.7%, and HHV averaged 30.5 MJkg⁻¹. Correlation analysis showed the interrelation between elementary carbon with HHV in bio-oil or with oxygen loss. Overall, from 55 correlations, 21 significant and high correlations among a set of 11 variables were found. Among the most relevant ones, the percentage of elementary carbon presented five significant correlations with the percentage of O (−0.980), percentage of C gain (0.902), percentage of O loss (0.973), HHV gain (0.917), and O/C loss (0.943). The amount of carbon is directly correlated with the amount of oxygen, conversely, the decrease in oxygen content increases the elementary carbon and hydrogen concentration, which leads to an improvement in HHV. HHV gain showed a strong positive dependence on the percentage of C (0.917) and percentage of C gain (0.943), while the elementary oxygen (−0.885) and its percentage of O loss (0.978) adversely affect the HHV gain. Consequently, the O/C loss (0.970) increases the HHV positively. van Krevelen’s analysis indicated that bio-oils are chemically compatible with liquid fossil fuels. FTIR-ATR evidenced the presence of derivatives of depolymerization of lignin and cellulose in raw biomasses in bio-oil. TGA/DTG confirmed the bio-oil burning aptitude by the high average 53% mass loss of volatiles associated with lowered peaking decomposition temperatures by 100 °C than raw biomasses. Overall, this research shows the potential of bio-oil from liquefaction of SRC biomasses for the contribution of renewable energy and chemical deliverables, and thereby, to a greener global economy.

Breast cancer or surrounding normal tissue? A successful discrimination by FTIR or Raman microspectroscopy

Breast cancer is a type of cancer with the highest incidence worldwide in 2021, with early diagnosis and rapid treatment intervention being the reasons for the decreasing mortality rate associated with the disease.

Detection of lipid efflux from foam cell models using a label-free infrared method

Synchrotron-based microFTIR spectroscopy was used to study the process of lipid efflux in a foam cell model. The anti-atherosclerotic drug, atorvastatin, removed low-density lipoprotein from the foam cells in a dose, and time dependent manner.

Characterization of the Conformational Properties of Soluble and Insoluble Proteins by Fourier Transform Infrared Spectroscopy

The FTIR (micro-)spectroscopy method applied to the study of the structural properties of different soluble and insoluble proteins will be illustrated. In particular, we will discuss the procedure to analyze proteins in form of hydrated films and in solution by means of attenuated total reflection (ATR) measurements. Moreover, we will describe the procedure to characterize bacterial inclusion bodies (IBs) and amyloid deposits within human tissues by means of FTIR microspectroscopy.

Challenges in Experimental Methods

Experimental studies of amyloids encounter many challenges. There are many methods available for studying proteins, which can be applied to amyloids: from basic staining techniques, allowing visualization of fibers, to complex methods, e.g., AFM-IR used to their detailed biochemical and structural characterization in nanoscale. Which method is appropriate depends on the goal of an experiment: verification of aggregational properties of a peptide, distinguishing oligomers from mature fibers, or kinetic studies. Insolubility, rapid aggregation, and the need of using a high-purity peptide may be a limiting factor in studies involving amyloids. Moreover, the results obtained by various experimental methods often differ significantly, which may lead to misclassification of amyloid peptides. Due to ambiguity of experimental results, laborious and time-consuming analysis, bioinformatical methods become more widely used for amyloids.

The fractal and textural analysis of glomeruli in obese and non-obese patients

Background

Fractal dimension is an indirect indicator of signal complexity. The aim was to evaluate the fractal and textural analysis parameters of glomeruli in obese and non-obese patients with glomerular diseases and association of these parameters with clinical features.

Methods

The study included 125 patients mean age 46 ± 15.2 years: obese (BMI ≥ 27 kg/m²—63 patients) and non-obese (BMI < 27 kg/m²—62 patients). Serum concentration of creatinine, protein, albumin, cholesterol, trygliceride, and daily proteinuria were measured. Formula Chronic Kidney Disease Epidemiology Colaboration (CKD-EPI) equation was calculated. Fractal (fractal dimension, lacunarity) and textural (angular second moment (ASM), textural correlation (COR), inverse difference moment (IDM), textural contrast (CON), variance) analysis parameters were compared between two groups.

Results

Obese patients had higher mean value of variance (t = 1.867), ASM (t = 1.532) and CON (t = 0.394) but without significant difference (P > 0.05) compared to non-obese. Mean value of COR (t = 0.108) and IDM (t = 0.185) were almost the same in two patient groups. Obese patients had higher value of lacunarity (t = 0.499) in comparison with non-obese, the mean value of fractal dimension (t = 0.225) was almost the same in two groups. Significantly positive association between variance and creatinine concentration (r = 0.499, P < 0.01), significantly negative association between variance and CKD-EPI (r = -0.448, P < 0.01), variance and sex (r = -0.339, P < 0.05) were found.

Conclusions

Variance showed significant correlation with serum creatinine concentration, CKD-EPI and sex. CON and IDM were significantly related to sex. Fractal and textural analysis parameters of glomeruli could become a supplement to histopathologic analysis of kidney tissue.

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Variance showed significant correlation with eGFR calculated by CKD- EPI formula.

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Significant correlation between variance and serum creatinine was found.

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Textural contrast and inverse difference moment were significantly related to sex.

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Fractal analysis of glomeruli could become supplement to histopathologic analysis.

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Textural analyses of kidney tissue should become useful to histopathologic analysis.

Thermochemical Liquefaction as a Cleaner and Efficient Route for Valuing Pinewood Residues from Forest Fires

Biomass thermochemical liquefaction is a chemical process with multifunctional bio-oil as its main product. Under this process, the complex structure of lignocellulosic components can be hydrolysed into smaller molecules at atmospheric pressure. This work demonstrates that the liquefaction of burned pinewood from forest fires delivers similar conversion rates into bio-oil as non-burned wood does. The bio-oils from four burned biomass fractions (heartwood, sapwood, branches, and bark) showed lower moisture content and higher HHV (ranging between 32.96 and 35.85 MJ/kg) than the initial biomasses. The increased HHV resulted from the loss of oxygen, whereas the carbon and hydrogen mass fractions increased. The highest conversion of bark and heartwood was achieved after 60 min of liquefaction. Sapwood, pinewood, and branches reached a slightly higher conversion, with yields about 8% greater, but with longer liquefaction time resulting in higher energy consumption. Additionally, the van Krevelen diagram indicated that the produced bio-oils were closer and chemically more compatible (in terms of hydrogen and oxygen content) to the hydrocarbon fuels than the initial biomass counterparts. In addition, bio-oil from burned pinewood was shown to be a viable alternative biofuel for heavy industrial applications. Overall, biomass from forest fires can be used for the liquefaction process without compromising its efficiency and performance. By doing so, it recovers part of the lost value caused by wildfires, mitigating their negative effects.

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.

On 2D-FTIR-XRF microscopy - A step forward correlative tissue studies by infrared and hard X-ray radiation

Correlative Fourier Transform Infra-Red (FTIR) and hard X-Ray Fluorescence (XRF) microscopy studies of thin biological samples have recently evolved as complementary methods for biochemical fingerprinting of animal/human tissues. These are seen particularly useful for tracking the mechanisms of neurological diseases, i.e., in Alzheimer/Parkinson disease, in the brain where mishandling of trace metals (Fe, Cu, Zn) seems to be often associated with ongoing damage to molecular components via, among others, oxidative/reductive stress neurotoxicity. Despite substantial progress in state-of-the-art detection and data analysis methods, combined FTIR-XRF experiments have never benefited from correlation and co-localization analysis of molecular moieties and chemical elements, respectively. We here propose for the first time a completely novel data analysis pipeline, utilizing the idea of 2D correlation spectrometry for brain tissue analysis. In this paper, we utilized combined benchtop FTIR - synchrotron XRF mapping experiments on thin brain samples mounted on polypropylene membranes. By implementing our recently developed Multiple Linear Regression Multi-Reference (MLR-MR) algorithm, along with advanced image processing, artifact-free 2D FTIR-XRF spectra could be obtained by mitigating the impact of spectral artifacts, such as Etalon fringes and mild scattering Mie-like signatures, in the FTIR data. We demonstrated that the method is a powerful tool for co-localizing and correlating molecular arrangements and chemical elements (and vice versa) using visually attractive 2D correlograms. Moreover, the methods' applicability for fostering the identification of distinct (biological) materials, involving chemical elements and molecular arrangements, is also shown. Taken together, the 2D FTIR-XRF method opens up for new measures for in-situ investigating hidden complex biochemical correlations, and yet unraveled mechanisms in a biological sample. This step seems crucial for developing new strategies for facilitating the research on the interaction of metals/nonmetals with organic components. This is particularly important for enhancing our understanding of the diseases associated with metal/nonmetal mishandling.

Addressing Delicate and Variable Cancer Morphology in Spectral Histopathology Using Canine Visceral Hemangiosarcoma

Spectral histopathology has shown promise for the classification and diagnosis of tumors with defined morphology, but application in tumors with variable or diffuse morphologies is yet to be investigated. To address this gap, we evaluated the application of Fourier transform infrared (FTIR) imaging as an accessory diagnostic tool for canine hemangiosarcoma (HSA), a vascular endothelial cell cancer that is difficult to diagnose. To preserve the delicate vascular tumor tissue structure, and potential classification of single endothelial cells, paraffin removal was not performed, and a partial least square discrimination analysis (PLSDA) and Random Forest (RF) models to classify different tissue types at individual pixel level were established using a calibration set (24 FTIR images from 13 spleen specimens). Next, the prediction capability of the PLSDA model was tested with an independent test set (n = 11), resulting in 74% correct classification of different tissue types at an individual pixel level. Finally, the performance of the FTIR spectropathology and chemometric algorithm for diagnosis of HSA was established in a blinded set of tissue samples (n = 24), with sensitivity and specificity of 80 and 81%, respectively. Taken together, these results show that FTIR imaging without paraffin removal can be applied to tumors with diffuse morphology, and this technique is a promising tool to assist in canine splenic HSA differential diagnosis.

Application of 2D IR Bioimaging: Hyperspectral Images of Formalin-Fixed Pancreatic Tissues and Observation of Slow Protein Degradation

We used two-dimensional IR bioimaging to study the structural heterogeneity of formalin-fixed mouse pancreas. Images were generated from the hyperspectral data sets by plotting quantities associated with the amide I vibrational mode, which is created by the backbone carbonyl stretch. Images that measure the fundamental vibrational frequencies, cross peaks, and anharmonic shifts are presented. Histograms are generated for each quantity, providing averaged values and distributions around the mean that serve as metrics for protein structures. Images were generated from tissue that had been stored in a formalin fixation for 3, 8, and 48 weeks. Over this period, all three metrics show that that the β-sheet content of the samples increased, consistent with protein aggregation. Our results indicate that formalin fixation does not entirely arrest the degradation of a protein structure in pancreas tissue.

Microplastic fibers influence Ag toxicity and bioaccumulation in Eisenia andrei but not in Enchytraeus crypticus

Microplastic fibers (MF) are released from synthetic textiles during washing and end up in the wastewater. Similarly, silver nanoparticles (AgNP), incorporated in textiles as antimicrobial agents, are released in washing machines, also reaching the wastewater treatment plants. Therefore, both MF and AgNP co-exist in the environment and enter the soil compartment mainly via the application of biosolids. Yet, the combined effect of MF and AgNP has not been studied. Here, we assessed the effects of polyester MF on the toxicity of AgNP and AgNO₃ to the earthworm Eisenia andrei and the enchytraeid Enchytraeus crypticus. The organisms were exposed to a range of concentration of AgNP (32, 100, 320, 1000, 3200 mg Ag/kg) and AgNO₃ (12.8, 32, 80, 200, 500 mg Ag/kg) in LUFA 2.2 soil in the absence or presence of MF (0.01% DW). Reproduction tests were conducted and the toxicity outcomes compared between soils with and without MF. The exposure to MF caused a decrease in the number of juveniles and changed the biochemical composition of earthworms. Moreover, the presence of MF increased the toxicity of AgNP to earthworm reproduction (EC50 = 165 mg Ag/kg) when compared to AgNP exposure alone (EC50 = 450 mg Ag/kg), but did not alter the toxicity of AgNO₃ (EC50 = 40 mg Ag/kg). For enchytraeids, no significant difference in Ag toxicity could be detected when MF was added to the soil for both AgNP and AgNO₃. Overall, Ag bioaccumulation was not affected by MF, except for a decrease in earthworm body concentration at the highest Ag soil concentration (3200 mg Ag/kg). Our results suggest that the presence of MF in the soil compartment may be a cause of concern, and that the joint exposure to Ag may be deleterious depending on the Ag form, organism, and endpoint. The present work provides the first evidence that a realistic MF concentration in soil lowers AgNP concentration necessary to provoke reproductive impairment in earthworms. The influence of MF on the risk assessment of AgNP should be considered.

The effect of universal adhesives on dentine collagen

OBJECTIVES

The purpose of the study was to evaluate the integrity of dentine type I collagen after self-etching (SE) treatments with strong and mild universal adhesives.

METHODS

Coronal dentine specimens (n=10/product) were imaged by optical microscopy and analyzed by ATR-FTIR spectroscopy before and after treatment with 32% phosphoric acid gel (PA-negative control), 17% neutral EDTA (ED-positive control) conditioners and Adhese Universal (AD), Clearfil Universal Bond Quick (CQ), G-Premio Bond (GP), Prelude One (PR) and Scotchbond Universal (SB) adhesives. From the spectroscopic analysis the following parameters were determined: a) Extent of dentine demineralization (DM%) and b) percentage area of the Amide I curve-fitted components of β-turns, 3₁₀-helix/β-turns, α-helix, random coils, β-sheets and collagen maturation (R) index. Statistical analysis was performed by one-way ANOVA (DM%), paired t-test/Wilcoxon test (Amide I components) and Spearman correlation coefficient (DM% vs Amide I components) at an a=0.05 level.

RESULTS

PA, ED and GP removed the smear-layer and opened tubule orifices, whereas all other treatments removed only the intratubular smear-layer fraction. The ranking of the statistically significant differences in DM% was PA>GP>ED>AD, SB, CQ, PR, with AD being significantly different from PR. Regarding the Amide I components, PA demonstrated a significant reduction in β-turns, α-helices and an increase in β-sheets, GP a reduction in β-turns, AD an increase in β-turns and random coils, and CQ an increase in β-turns. PR, SB and ED showed insignificant differences in all the Amide I components. Significant correlations were found between DM%-random coils and DM%-R.

SIGNIFICANCE

The universal adhesives used in the SE mode induced none to minimal changes in dentine collagen structure, without evidence of the destabilization pattern observed after conventional phosphoric acid treatments.

Saliva based non invasive screening of Oral Submucous Fibrosis using ATR-FTIR spectroscopy

Oral Submucous Fibrosis (OSMF) is a type of precancerous condition of Oral cancer and considered to have the greatest malignant potential. Biopsy is an ultimate option for the conformation of the malignancy. But the invasiveness of the procedure makes it interdict. Therefore, there is an urgent need to identify effective screening and diagnostic methods which would be less invasive, rapid, more accurate and cost effective. Here, we used Attenuated Total Reflection- Fourier transform infrared spectroscopy (ATR-FTIR) with Chemometric analysis coupled with estimation of total salivary protein to discriminate OSMF and Healthy Control (HC). The present study showed the specific Infrared spectrum for OSMF patients, which was specifically differentiated from HC based on the spectral shift of proteins/amide II, carbohydrate and nucleic acid using Principal Component Analysis (PCA) and Hierarchical Clustering Analysis (HCA) with small data sets. ATR-FTIR spectroscopy of saliva coupled with total protein estimation can be used to discriminate between OSMF and HC. However, large sample size should be needed to evaluate the ATR-FTIR for consideration as a screening tool for an early diagnosis OSMF.

Infrared Spectroscopy of Blood

The magnitude of infectious diseases in the twenty-first century created an urgent need for point-of-care diagnostics. Critical shortages in reagents and testing kits have had a large impact on the ability to test patients with a suspected parasitic, bacteria, fungal, and viral infections. New point-of-care tests need to be highly sensitive, specific, and easy to use and provide results in rapid time. Infrared spectroscopy, coupled to multivariate and machine learning algorithms, has the potential to meet this unmet demand requiring minimal sample preparation to detect both pathogenic infectious agents and chronic disease markers in blood. This focal point article will highlight the application of Fourier transform infrared spectroscopy to detect disease markers in blood focusing principally on parasites, bacteria, viruses, cancer markers, and important analytes indicative of disease. Methodologies and state-of-the-art approaches will be reported and potential confounding variables in blood analysis identified. The article provides an up to date review of the literature on blood diagnosis using infrared spectroscopy highlighting the recent advances in this burgeoning field.

Mid-infrared absorption by soft tissue sarcoma and cell ablation utilizing a mid-infrared interband cascade laser

SIGNIFICANCE

Mid-infrared (MIR) light refers to wavelengths ranging from 3 to 30  μm and is the most attractive spectral region for ablation of soft and hard tissues. This is because building blocks of biological tissue, such as water, proteins, and lipids, exhibit molecular vibrational modes in the MIR wavelengths that result in strong MIR light absorption. To date, researchers investigating MIR lasers for surgical applications have used bulky light sources, such as free electron lasers, nonlinear light generators, and carbon dioxide lasers. We demonstrate the use of a tiny (a few microns wide, a few millimeters long) MIR interband cascade laser (ICL) for surgical thermal ablation applications.

AIM

Our goal is to demonstrate the use of an ICL for surgical thermal ablation and demonstrate its efficacy in ablating normal fibroblasts and primary undifferentiated pleomorphic sarcoma tumor cells (C1619).

APPROACH

We conducted Fourier transform infrared spectroscopy analysis of healthy and cancerous tissue samples, which indicated that the absorption of tumor tissue is higher than healthy tissue around 3.3-μm wavelength. These results enabled us to select an ICL emission wavelength, λ, of 3.3  μm to probe normal fibroblast and primary undifferentiated pleomorphic sarcoma cell survival after ICL exposure.

RESULTS

We show that the absorption of tumorous tissue is higher than that of healthy tissues around the 3-μm MIR wavelength. We demonstrate that the ICL is able to ablate cancer cells at very low-power levels that can be clinically implemented but that this effect does not appear to be specific to C1619 when compared to normal fibroblasts.

CONCLUSIONS

Our study demonstrates that ICLs may represent an exciting new avenue toward precise laser-based thermal ablation.