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

Molecular Spectroscopy for the Biochemical Composition Analysis of Patient-Derived Pancreatic Cancer Organoids

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) continues to pose profound challenges within the field of oncology due to its notorious resistance to existing therapies and constant high mortality rates. The recent emergence of three-dimensional patient-derived organoid (PDO) models marks a significant advancement, opening new avenues for exploring cancer biology and assessing therapeutic approaches.

AIMS

The aim of this study focuses on the innovative use of Fourier-transform infrared (FT-IR) spectroscopy to analyze PDAC organoids, thus illuminating their biochemical intricacies.

MATERIALS AND METHODS

In this study, PDAC organoids, cultivated from specimens sourced from cancer patients, were subjected to FT-IR spectroscopic imaging. By examining the spectral data within the critical fingerprint region (950-1800 cm-1), and employing principal component analysis (PCA), biochemical disparities were detected and analyzed.

RESULTS

The results revealed distinct spectral profiles corresponding to different sample preparation techniques, which in turn highlighted variations in protein content and structure. PCA revealed a high homogeneity within classes and minimal passage number influence on spectral profiles, with variations in lipid content and protein profiles. Significantly, the biochemical fingerprint of these PDOs closely mirrored that of the original human tissue samples.

CONCLUSION

This investigation underscores the efficacy of molecular spectroscopy as a non-invasive method for profound characterization of PDAC organoids, enhancing our comprehension of tumor biochemistry. The capacity for swift and precise biochemical profiling of PDOs via molecular spectroscopy heralds a promising future for this technique in the realms of cancer diagnostics and personalized medicine.

Advancements in Hyperspectral Imaging and Computer-Aided Diagnostic Methods for the Enhanced Detection and Diagnosis of Head and Neck Cancer

Background/Objectives: Head and neck cancer (HNC), predominantly squamous cell carcinoma (SCC), presents a significant global health burden. Conventional diagnostic approaches often face challenges in terms of achieving early detection and accurate diagnosis. This review examines recent advancements in hyperspectral imaging (HSI), integrated with computer-aided diagnostic (CAD) techniques, to enhance HNC detection and diagnosis. Methods: A systematic review of seven rigorously selected studies was performed. We focused on CAD algorithms, such as convolutional neural networks (CNNs), support vector machines (SVMs), and linear discriminant analysis (LDA). These are applicable to the hyperspectral imaging of HNC tissues. Results: The meta-analysis findings indicate that LDA surpasses other algorithms, achieving an accuracy of 92%, sensitivity of 91%, and specificity of 93%. CNNs exhibit moderate performance, with an accuracy of 82%, sensitivity of 77%, and specificity of 86%. SVMs demonstrate the lowest performance, with an accuracy of 76% and sensitivity of 48%, but maintain a high specificity level at 89%. Additionally, in vivo studies demonstrate superior performance when compared to ex vivo studies, reporting higher accuracy (81%), sensitivity (83%), and specificity (79%). Conclusion: Despite these promising findings, challenges persist, such as HSI's sensitivity to external conditions, the need for high-resolution and high-speed imaging, and the lack of comprehensive spectral databases. Future research should emphasize dimensionality reduction techniques, the integration of multiple machine learning models, and the development of extensive spectral libraries to enhance HSI's clinical utility in HNC diagnostics. This review underscores the transformative potential of HSI and CAD techniques in revolutionizing HNC diagnostics, facilitating more accurate and earlier detection, and improving patient outcomes.

Sensing Biomolecules Associated with Cells' Radiosusceptibility by Advanced Micro- and Nanospectroscopy Techniques

Radiotherapy is one of the most common approaches for cancer treatment, especially in the case of peripheral nervous system tumors. As it requires exposure to high doses of ionizing radiation, it is important to look for substances that support efficient reduction of the tumor volume with simultaneous prevention of the surrounding noncancerous cells. Cannabidiol (CBD), which exhibits both anticancer and neuroprotective properties, was applied as a potential modulator of radiological response; however, its influence on cells undergoing irradiation remains elusive. Here, we have applied high-resolution optical spectroscopy techniques to capture biomolecules associated with CBD shielding of normal and damaging cancerous cells upon X-ray exposure. Conventional Raman (RS) and Fourier transformed infrared (FT-IR) spectroscopies provided semiquantitative information mainly about changes in the concentration of total lipids, DNA, cholesteryl esters, and phospholipids in cells. A through assessment of the single cells by atomic force microscopy coupled with infrared spectroscopy (AFM-IR) allowed us to determine not only the alterations in DNA content but also in its conformation due to cell treatment. Pronounced nanoscale changes in cholesteryl ester metabolites, associated with CBD treatment and radiation, were also observed. AFM-IR chemoselective maps of the single cells indicate the modified distribution of cholesteryl esters with 40 nm spatial resolution. Based on the obtained results, we propose a label-free and fast analytical method engaging optical spectroscopy to assess the mechanism of normal and cancerous cell susceptibility to ionizing radiation when pretreated with CBD.

Complementary techniques for the reliable characterisation of tissue samples: A case study on pancreatic tumours analysed by means of X-ray fluorescence analysis and IR spectroscopy

An improvement in the reliability and comparability of tissue characterization results is crucial for enabling further progress in cancer detection and the assessment of therapeutic effects. This can only be achieved by integrating quantitative methods into well-established qualitative characterization routines. This case study presents a hybrid metrological approach for tissue characterisation including vibrational Fourier Transform InfraRed (FTIR) spectroscopy and traceable reference-free X-Ray Fluorescence analysis (XRF). Through the combination of spatially resolved qualitative molecular information with quantitative elemental concentrations an all-encompassing sample characterisation can be provided. The study was performed on tissue sections of syngeneic murine pancreatic ductal adenocarcinoma KPC (KrasG12D/+; Trp53R172H/+; Pdx-1-Cre) tumours ex-vivo. Sections from healthy pancreatic tissues, sham-exposed tumours and tumours subjected to low dose radiotherapy treatment (2 Gray and 6 Gray) were analysed using both methods. Additional sample integrity studies using Near Edge X-ray Absorption Fine Structure (NEXAFS) spectroscopy at the carbon and nitrogen K-edges were performed to assess the effect of sample aging and XRF investigations on the samples. Results showed an increase in the concentrations of elemental biomarkers, including S, K and amide I structures in malignant pancreatic tissue compared to healthy pancreatic tissue. The exposure of tumours to 6 Gy radiation decreases the levels of these elements towards a phenotype seen in the healthy pancreas. A protocol for hybrid investigations is presented, with emphasis on the sample preparation, minimizing the impact of consecutive applied methods on their measurands, and ensuring the compatibility and reliability of achieved results. The study demonstrates the cancer recognition capabilities, and the sensitivity for low dosage radiotherapy treatment monitoring for each method individually and assesses the potential of combining molecular fingerprinting with non-destructive quantitative elemental information for tissue sample characterization.

PTGES2 and RNASET2 identified as novel potential biomarkers and therapeutic targets for basal cell carcinoma: insights from proteome-wide mendelian randomization, colocalization, and MR-PheWAS analyses

Introduction

Basal cell carcinoma (BCC) is the most common skin cancer, lacking reliable biomarkers or therapeutic targets for effective treatment. Genome-wide association studies (GWAS) can aid in identifying drug targets, repurposing existing drugs, predicting clinical trial side effects, and reclassifying patients in clinical utility. Hence, the present study investigates the association between plasma proteins and skin cancer to identify effective biomarkers and therapeutic targets for BCC.

Methods

Proteome-wide mendelian randomization was performed using inverse-variance-weight and Wald Ratio methods, leveraging 1 Mb cis protein quantitative trait loci (cis-pQTLs) in the UK Biobank Pharma Proteomics Project (UKB-PPP) and the deCODE Health Study, to determine the causal relationship between plasma proteins and skin cancer and its subtypes in the FinnGen R10 study and the SAIGE database of Lee lab. Significant association with skin cancer and its subtypes was defined as a false discovery rate (FDR) < 0.05. pQTL to GWAS colocalization analysis was executed using a Bayesian model to evaluate five exclusive hypotheses. Strong colocalization evidence was defined as a posterior probability for shared causal variants (PP.H4) of ≥0.85. Mendelian randomization-Phenome-wide association studies (MR-PheWAS) were used to evaluate potential biomarkers and therapeutic targets for skin cancer and its subtypes within a phenome-wide human disease category.

Results

PTGES2, RNASET2, SF3B4, STX8, ENO2, and HS3ST3B1 (besides RNASET2, five other plasma proteins were previously unknown in expression quantitative trait loci (eQTL) and methylation quantitative trait loci (mQTL)) were significantly associated with BCC after FDR correction in the UKB-PPP and deCODE studies. Reverse MR showed no association between BCC and these proteins. PTGES2 and RNASET2 exhibited strong evidence of colocalization with BCC based on a posterior probability PP.H4 >0.92. Furthermore, MR-PheWAS analysis showed that BCC was the most significant phenotype associated with PTGES2 and RNASET2 among 2,408 phenotypes in the FinnGen R10 study. Therefore, PTGES2 and RNASET2 are highlighted as effective biomarkers and therapeutic targets for BCC within the phenome-wide human disease category.

Conclusion

The study identifies PTGES2 and RNASET2 plasma proteins as novel, reliable biomarkers and therapeutic targets for BCC, suggesting more effective clinical application strategies for patients.

A Modern Multidisciplinary Method to Characterize Natural White Spot Lesions with 2D and 3D Assessments: A Preliminary Study

In this preliminary study, a multidisciplinary method based on high-resolution analytical techniques (such as microcomputed tomography, Raman Microspectroscopy, scanning electron microscopy, and Vickers microhardness test) was exploited to evaluate the alterations that occur in human teeth at the initial stage of the carious lesion. To this purpose, six extracted molars displaying a natural white spot lesion (WSL) were investigated. Specific morphological, structural, and chemical parameters, such as the mineral density, indentation hardness, molecular and elemental composition, and surface micromorphology were obtained on the WSL, and the results were statistically compared (t-test, p < 0.05) to those of the sound enamel on the same tooth. In the WSL, with respect to the sound area, a decrease in the mineral density and crystallinity was detected together with differences in the molecular composition and surface microstructure, such as the occurrence of micropores and irregularities. Moreover, the elemental analysis highlighted in WSL showed a statistically significant decrease in Ca and P percentages. In conclusion, this multidisciplinary approach allows us to fully characterize the area of interest, providing a deeper knowledge of these enamel lesions, which could have important clinical implications.

Exposure to environmental pharmaceuticals affects the macromolecular composition of mussels digestive glands

Human pharmaceuticals represent a major challenge in natural environment. A better knowledge on their mechanisms of action and adverse effects on cellular pathways is fundamental to predict long-term consequences for marine wildlife. The FTIRI Imaging (FTIRI) spectroscopy represents a vibrational technique allowing to map specific areas of non-homogeneous biological samples, providing a unique biochemical and ultrastructural fingerprint of the tissue. In this study, FTIRI technique has been applied, for the first time, to characterize (i) the chemical building blocks of digestive glands of Mytilus galloprovincialis, (ii) alterations and (iii) resilience of macromolecular composition, after a 14-days exposure to 0.5 µg/L of carbamazepine (CBZ), valsartan (VAL) and their mixture, followed by a 14-days recovery period. Spectral features of mussels digestive glands provided insights on composition and topographical distribution of main groups of biological macromolecules, such as proteins, lipids, and glycosylated compounds. Pharmaceuticals caused an increase in the total amount of protein and a significant decrease of lipids levels. Changes in macromolecular features reflected the modulation of specific molecular and biochemical pathways thus supporting our knowledge on mechanisms of action of such emerging pollutants. Overall, the applied approach could represent an added value within integrated strategies for the effects-based evaluation of environmental contaminants.

FTIR Microspectroscopy as a new probe to study human uterine lesions: Characterization of tumor cell lines from uterine smooth muscle cells and evaluation of EPA and DHA in vitro treatments

During their life, women are likely to develop uterine diseases, which often compromise their fertile and perimenopausal age. Besides benign lesions like leiomyomas, several malignant neoplasms can occur, such as the uterine leiomyosarcoma, which represents the most frequent malignancy among the rarest uterine cancers. It presents several variants similar to both benign and malignant neoplasms, and sometimes it shares symptoms with the benign counterpart. In this scenario, for a correct diagnosis and a successful prognosis, it is mandatory to detect new reliable markers which strengthen histopathological outcomes and let define a more appropriate and less harmful therapy. Based on this concerning evidence, in the present study, Fourier Transform Infrared Microspectroscopy has been exploited at a cellular level on uterine leiomyoma and leiomyosarcoma cell lines to (1) identify specific spectral biomarkers able to distinguish between benign and malignant lesions, and (2) evaluate the efficacy of eicosapentaenoic and docosahexaenoic acids (respectively EPA and DHA), already successfully tested. Results evidenced reliable differences in the spectral signature of benign and malignant cells, mainly in terms of lipids and nucleic acids composition. Moreover, even if EPA and DHA seemed to exert different effects on the tested cell lines, no cytotoxic and/or anti-apoptotic actions were observed after omega-3 based treatments.

Hyperspectral imaging of lipids in biological tissues using near-infrared and shortwave infrared transmission mode: A pilot study

Label-free hyperspectral imaging (HSI) of lipids was demonstrated in the near-infrared (NIR) and shortwave infrared (SWIR) regions (950-1800 nm) using porcine tissue. HSI was performed in the transmission light-pass configuration, using a NIR-SWIR camera coupled with a liquid crystal tunable filter. The transmittance spectra of the regions of interest (ROIs), which correspond to the lipid and muscle areas in the specimen, were utilized for the spectrum unmixing. The transmittance spectra in ROIs were compared with those recorded by a spectrophotometer using samples of adipose and muscle. The lipid optical absorption bands at 1210 and 1730 nm were first used for the unmixing and mapping. Then, we performed the continuous multiband unmixing over the entire available spectral range, thereby, considering a combination of characteristic absorption bands of lipids, proteins, and water. The enhanced protocol demonstrates the ability to visualize small adipose inclusions of 1-10 μm size.

A one-dimensional convolutional neural network based deep learning for high accuracy classification of transformation stages in esophageal squamous cell carcinoma tissue using micro-FTIR

Among the most frequently diagnosed cancers in developing countries, esophageal squamous cell carcinoma (ESCC) ranks among the top six causes of death. It would be beneficial if a rapid, accurate, and automatic ESCC diagnostic method could be developed to reduce the workload of pathologists and improve the effectiveness of cancer treatments. Using micro-FTIR spectroscopy, this study classified the transformation stages of ESCC tissues. Based on 6,352 raw micro-FTIR spectra, a one-dimensional convolutional neural network (1D-CNN) model was constructed to classify-five stages. Based on the established model, more than 93% accuracy was achieved at each stage, and the accuracy of identifying proliferation, low grade neoplasia, and ESCC cancer groups was achieved 99% for the test dataset. In this proof-of-concept study, the developed method can be applied to other diseases in order to promote the use of FTIR spectroscopy in cancer pathology.

Variabilities in global DNA methylation and β-sheet richness establish spectroscopic landscapes among subtypes of pancreatic cancer

PURPOSE

Knowledge about pancreatic cancer (PC) biology has been growing rapidly in recent decades. Nevertheless, the survival of PC patients has not greatly improved. The development of a novel methodology suitable for deep investigation of the nature of PC tumors is of great importance. Molecular imaging techniques, such as Fourier transform infrared (FTIR) spectroscopy and Raman hyperspectral mapping (RHM) combined with advanced multivariate data analysis, were useful in studying the biochemical composition of PC tissue.

METHODS

Here, we evaluated the potential of molecular imaging in differentiating three groups of PC tumors, which originate from different precursor lesions. Specifically, we comprehensively investigated adenocarcinomas (ACs): conventional ductal AC, intraductal papillary mucinous carcinoma, and ampulla of Vater AC. FTIR microspectroscopy and RHM maps of 24 PC tissue slides were obtained, and comprehensive advanced statistical analyses, such as hierarchical clustering and nonnegative matrix factorization, were performed on a total of 211,355 Raman spectra. Additionally, we employed deep learning technology for the same task of PC subtyping to enable automation. The so-called convolutional neural network (CNN) was trained to recognize spectra specific to each PC group and then employed to generate CNN-prediction-based tissue maps. To identify the DNA methylation spectral markers, we used differently methylated, isolated DNA and compared the observed spectral differences with the results obtained from cellular nuclei regions of PC tissues.

RESULTS

The results showed significant differences among cancer tissues of the studied PC groups. The main findings are the varying content of β-sheet-rich proteins within the PC cells and alterations in the relative DNA methylation level. Our CNN model efficiently differentiated PC groups with 94% accuracy. The usage of CNN in the classification task did not require Raman spectral data preprocessing and eliminated the need for extensive knowledge of statistical methodologies.

CONCLUSIONS

Molecular spectroscopy combined with CNN technology is a powerful tool for PC detection and subtyping. The molecular fingerprint of DNA methylation and β-sheet cytoplasmic proteins established by our results is different for the main PC groups and allowed the subtyping of pancreatic tumors, which can improve patient management and increase their survival. Our observations are of key importance in understanding the variability of PC and allow translation of the methodology into clinical practice by utilizing liquid biopsy testing.

Gestational Diabetes Mellitus and Small-for-Gestational-Age: An Insight into the Placental Molecular Biomarkers

Gestational diabetes mellitus (GDM) and small-for-gestational-age (SGA) are two metabolic-related diseases that could affect women during pregnancy. Considering that the chorionic villi (CVs) are crucial structures for the feto-maternal exchange, the alterations in their conformation have been linked to an imbalanced metabolic environment of placenta. In this study, a multidisciplinary approach has been carried out to describe the changes occurring in the placental CVs of GDM and SGA patients. The results revealed higher levels of superoxide dismutase 1 (SOD-1) and catalase (CAT), especially in the GDM placentae, which could be correlated with the hyperglycemic environment characteristic of this pathology. Furthermore, spectroscopy and histologic analyses revealed that both pathologies modify the placental lipid composition altering its structure. However, SGA induces lipid peroxidation and reduces collagen deposition within the CVs. Since the endocannabinoid system (ECS) is involved in placentation and different metabolic activities, the cannabinoid receptor 1 (CB1) and transient receptor potential cation channel subfamily V member 1 (TRPV-1) were analyzed. No changes have been observed either at general or specific levels in the CVs comparing control and pathological samples, suggesting the non-involvement of the cannabinoid system in these two pathologies.

Pd-Based Hybrid Nanoparticles As Multimodal Theranostic Nanomedicine

A nanodelivery system based on palladium nanoparticles (PdNP) and cisplatin (CisPt) was developed by physisorption of the drug onto the PdNP synthesized via a green redox process, using d-glucose and polyvinylpyrrolidone (PVP) as reducing and stabilizing/capping agents, respectively. UV-vis analysis and H₂-evolution measurements were carried out to prove the nanoparticles' capability to act as bimodal theranostic nanomedicine, i.e., having both plasmonic and photocatalytic properties. XPS, XRD, and TEM allowed light to be shed on the chemical composition and morphology of the PdNP. The analysis of the UV-visible spectra evidenced plasmonic peak changes for the hybrid nanoparticle-drug assembly (Pd@CisPt), which pointed to a significant interaction of CisPt with the NP surface. The drug loading was quantitatively estimated by ICP-OES measurements, while DLS and AFM confirmed the strong association of the drug with the nanoparticle surface. The test of SOD-like activity in a cell-free environment proved the maintenance of the antioxidant capability of PdNP also in the Pd@CisPt systems. Finally, Pd@CisPt tested in prostate cancer cells (PC-3 line) unveiled the antitumoral action of the developed nanomedicine, related to reactive oxygen species (ROS) generation, with a condition of protein misfolding/unfolding and DNA damage, as evidenced by cytotoxicity and MitoSOX assays, as well as Raman microspectroscopy, respectively. Cell imaging by confocal microscopy evidenced cellular uptake of the nanoparticles, as well as dynamic processes of copper ion accumulation at the level of subcellular compartments. Finally, cell migration studies upon treatment with Pd@CisPt evidenced a tunable response between the inhibitory effect of CisPt and the enhanced rate of cell migration for the metal NP alone, which pointed out the promising potential of the developed theranostic nanomedicine in tissue regeneration.

Differentiation of Urothelial Carcinoma and Normal Bladder Tissues by Means of Fiber-Based ATR IR Spectroscopy

Surgical treatment is widely applied curative approach for bladder cancer. White light cystoscopy (WLC) is currently used for intraoperative diagnostics of malignant lesions but has relatively high false-negative rate. Here we represent an application of label free fiber-based attenuated total reflection infrared spectroscopy (ATR IR) for freshly resected human bladder tissue examination for 54 patients. Defined molecular spectral markers allow to identify normal and urothelial carcinoma tissues. While methods of statistical analysis (Hierarchical cluster analysis (HCA) and Principal component analysis (PCA)) used for spectral data treatment allow to discriminate tissue types with 91% sensitivity and 96-98% specificity. In the present study the described method was applied for tissue examination under ex vivo conditions. However, after method validation the equipment could be translated from laboratory studies to in situ or even in vivo studies in operating room.

Vibrational spectroscopy – are we close to finding a solution for early pancreatic cancer diagnosis?

Pancreatic cancer (PC) is an aggressive and lethal neoplasm, ranking seventh in the world for cancer deaths, with an overall 5-year survival rate of below 10%. The knowledge about PC pathogenesis is rapidly expanding. New aspects of tumor biology, including its molecular and morphological heterogeneity, have been reported to explain the complicated “cross-talk” that occurs between the cancer cells and the tumor stroma or the nature of pancreatic ductal adenocarcinoma-associated neural remodeling. Nevertheless, currently, there are no specific and sensitive diagnosis options for PC. Vibrational spectroscopy (VS) shows a promising role in the development of early diagnosis technology. In this review, we summarize recent reports about improvements in spectroscopic methodologies, briefly explain and highlight the drawbacks of each of them, and discuss available solutions. The important aspects of spectroscopic data evaluation with multivariate analysis and a convolutional neural network methodology are depicted. We conclude by presenting a study design for systemic verification of the VS-based methods in the diagnosis of PC.

Spirulina-enriched Substrate to Rear Black Soldier Fly (Hermetia illucens) Prepupae as Alternative Aquafeed Ingredient for Rainbow Trout (Oncorhynchus mykiss) Diets: Possible Effects on Zootechnical Performances, Gut and Liver Health Status, and Fillet Quality

In the present study, an organic substrate (coffee silverskin) enriched with spirulina (Arthrospira platensis; 15% w/w), as a source of lipids and bioactive molecules, was used to rear the black soldier fly (Hermetia illucens) prepupae. Three grossly isonitrogenous, isoproteic, isolipidic and isoenergetic experimental diets for rainbow trout (Oncorhynchus mykiss) juveniles were then produced: a control diet (HM0) mostly including fish meal and fish oil, and two other test diets named HM3 and HM20, in which 3 or 20% of the marine ingredients were substituted with full fat black soldier fly prepupae meal (HM), respectively. Experimental diets were provided for 6 weeks, and at the end of the trial the physiological responses and marketable traits of the fish were investigated using a multidisciplinary approach. Generally, all test diets were well accepted, and fish growth, gut and liver health status, and marketable characteristics were not impaired by the experimental diets. However, an increased immuno-related gene expression along with a slight reduction of fillet redness and yellowness was evident in fish from the HM20 group.

Preeclampsia Correlates with an Increase in Cannabinoid Receptor 1 Levels Leading to Macromolecular Alterations in Chorionic Villi of Term Placenta

Preeclampsia is a human pregnancy-specific disease characterized by abnormal placentation that usually presents with maternal hypertension and proteinuria. The main hallmark of preeclampsia, impaired trophoblast migration, and the subsequent disruption of uterine arteries remodeling lead to several molecular alterations in the placental compartments with those occurring in the chorionic villi being of the utmost importance. Given the essential role of the endocannabinoid system during preimplantation and trophoblast migration, we have combined the histological and hyperspectral imaging analyses to shed light on the involvement of two cannabinoid receptors in the macromolecular alterations related to preeclampsia. The results obtained by immunohistochemistry showed a significant increase in the protein levels of cannabinoid receptor 1 (CB1) in the preeclamptic chorionic villi. However, no changes were reported regarding transient receptor potential vanilloid 1 (TRPV-1) levels either in the bulk placental samples or chorionic villi when comparing control and preeclamptic patients. Histological analysis and Fourier-transform infrared spectroscopy (FTIRI) showed an increase in collagen deposition together with higher levels of lipid peroxidation and phosphorylated compounds in the pathological villi. Since CB1 enhancement has been described as promoting fibrosis and oxidative stress in several tissues, we proposed that the higher receptor abundance in preeclampsia could be triggering similar molecular effects in preeclamptic term placentas.

Staging of Skin Cancer Based on Hyperspectral Microscopic Imaging and Machine Learning

Skin cancer, a common type of cancer, is generally divided into basal cell carcinoma (BCC), squamous cell carcinoma (SCC) and malignant melanoma (MM). The incidence of skin cancer has continued to increase worldwide in recent years. Early detection can greatly reduce its morbidity and mortality. Hyperspectral microscopic imaging (HMI) technology can be used as a powerful tool for skin cancer diagnosis by reflecting the changes in the physical structure and microenvironment of the sample through the differences in the HMI data cube. Based on spectral data, this work studied the staging identification of SCC and the influence of the selected region of interest (ROI) on the staging results. In the SCC staging identification process, the optimal result corresponded to the standard normal variate transformation (SNV) for spectra preprocessing, the partial least squares (PLS) for dimensionality reduction, the hold-out method for dataset partition and the random forest (RF) model for staging identification, with the highest staging accuracy of 0.952 ± 0.014, and a kappa value of 0.928 ± 0.022. By comparing the staging results based on spectral characteristics from the nuclear compartments and peripheral regions, the spectral data of the nuclear compartments were found to contribute more to the accurate staging of SCC.

Altered type I collagen networking in osteoporotic human femoral head revealed by histomorphometric and Fourier transform infrared imaging correlated analyses

Bone homeostasis is the equilibrium between organic and inorganic components of the extracellular matrix (ECM) and cells. Alteration of this balance has consequences on bone mass and architecture, resulting in conditions such as osteoporosis (OP). Given ECM protein mutual regulation and their effects on bone structure and mineralization, further insight into their expression is crucial to understanding bone biology under normal and pathological conditions. This study focused on Type I Collagen, which is mainly responsible for structural properties and mineralization of bone, and selected proteins implicated in matrix composition, mineral deposition, and cell-matrix interaction such as Decorin, Osteocalcin, Osteopontin, Bone Sialoprotein 2, Osteonectin and Transforming Growth Factor beta. We developed a novel multidisciplinary approach in order to assess bone matrix in healthy and OP conditions more comprehensively by exploiting the Fourier Transform Infrared Imaging (FTIRI) technique combined with histomorphometry, Sirius Red staining, immunohistochemistry, and Western Blotting. This innovatory procedure allowed for the analysis of superimposed tissue sections and revealed that the alterations in OP bone tissue architecture were associated with warped Type I Collagen structure and deposition but not with changes in the total protein amount. The detected changes in the expression and/or cooperative or antagonist role of Decorin, Osteocalcin, Osteopontin, and Bone Sialoprotein-2 indicate the deep impact of these NCPs on collagen features of OP bone. Overall, our strategy may represent a starting point for designing targeted clinical strategies aimed at bone mass preservation and sustain the FTIRI translational capability as upcoming support for traditional diagnostic methods.

Label-free differentiation of human pancreatic cancer, pancreatitis, and normal pancreatic tissue by molecular spectroscopy

SIGNIFICANCE

Pancreatic ductal adenocarcinoma (PDAC) is one of the leading causes of cancer deaths with a best median survival of only 40 to 50 months for localized disease despite multimodal treatment. The standard tissue differentiation method continues to be pathology with histological staining analysis. Microscopic discrimination between inflammatory pancreatitis and malignancies is demanding.

AIM

We aim to accurately distinguish native pancreatic tissue using infrared (IR) spectroscopy in a fast and label-free manner.

APPROACH

Twenty cryopreserved human pancreatic tissue samples were collected from surgical resections. In total, more than 980,000 IR spectra were collected and analyzed using aMATLAB package. For differentiation of PDAC, pancreatitis, and normal tissue, a three-class training set for supervised classification was created with 25,000 spectra and the principal component analysis (PCA) score values for each cohort. Cross-validation was performed using the leaveone- out method. Validation of the algorithm was accomplished with 13 independent test samples.

RESULTS

Reclassification of the training set and the independent test samples revealed an overall accuracy of more than 90% using a discrimination algorithm.

CONCLUSION

IR spectroscopy in combination with PCA and supervised classification is an efficient analytical method to reliably distinguish between benign and malignant pancreatic tissues. It opens up a wide research field for oncological and surgical applications.

Uterine leiomyoma as useful model to unveil morphometric and macromolecular collagen state and impairment in fibrotic diseases: An ex-vivo human study

Collagen is one of the main components of the extracellular matrix (ECM), involved, among all, in the maintenance of the structural support of tissues. In fibrotic diseases, collagen is overexpressed, and its production determines the formation of a significantly stiffer ECM. The cross-linking of high-resolution analytical tools, able to investigate both the tridimensional organization and the secondary structure of collagen in fibrotic diseases, could be useful to identify defined markers correlating the status of this protein with specific pathological conditions. To this purpose, an innovative multidisciplinary approach based on Phase-Contrast MicroComputed Tomography, Transmission Electron Microscopy, and Fourier Transform Infrared Imaging Spectroscopy was exploited on leiomyoma samples and adjacent myometrium to characterize microstructural collagen features. Uterine leiomyoma is a common gynecological disorder affecting women in fertile age. It is characterized by a massive collagen production due to the repairing processes occurring at myometrium level, and, hence, it represents a valuable model to investigate collagen self-organization in a pathological condition. Moreover, to evaluate the sensitivity of this multidisciplinary approach, the effects of eicosapentaenoic (EPA) and docosahexaenoic (DHA) omega-3 fatty acids in collagen reduction were also investigated.

Current Pathology Model of Pancreatic Cancer

Pancreatic cancer (PC) is one of the most aggressive and lethal malignant neoplasms, ranking in seventh place in the world in terms of the incidence of death, with overall 5-year survival rates still below 10%. The knowledge about PC pathomechanisms is rapidly expanding. Daily reports reveal new aspects of tumor biology, including its molecular and morphological heterogeneity, explain complicated "cross-talk" that happens between the cancer cells and tumor stroma, or the nature of the PC-associated neural remodeling (PANR). Staying up-to-date is hard and crucial at the same time. In this review, we are focusing on a comprehensive summary of PC aspects that are important in pathologic reporting, impact patients' outcomes, and bring meaningful information for clinicians. Finally, we show promising new trends in diagnostic technologies that might bring a difference in PC early diagnosis.

A vibrational in vitro approach to evaluate the potential of monoolein nanoparticles as isofuranodiene carrier in MDA-MB 231 breast cancer cell line: New insights from Infrared and Raman microspectroscopies

Isofuranodiene (IFD) is a sesquiterpene occurring in several plant species, which proved to have multiple anticancer activities. IFD has a lipophilic nature and, hence, a very low water solubility and a poor bioavailability; moreover, it is not stable, undergoing the "Cope rearrangement" to the less active curzerene. The use of appropriate delivery systems can thus be considered as a valid tool to enhance IFD bioavailability, solubility, stability and at the same time also to improve its intracellular uptake and pharmacological activity. Within this frame, monoolein (GMO) nanoparticles loaded with IFD were prepared and their enhanced anticancer activity, compared to pristine IFD, was assessed. In this study, for the first time, an in vitro Fourier Transform Infrared and Raman Microspectroscopy approaches were exploited to evaluate the effects of IFD, alone and loaded in GMO nanoparticles, on MDA-MB 231 breast cancer cell line. The anti-cancer effects of IFD were evidenced by both the spectroscopic techniques and discriminated from the GMO-induced changes in the culture environment; moreover, a synergistic effect of IFD and GMO administration can be envisaged by the experimental results.

Evaluation of Controlled Ovarian Stimulation Protocols in Patients with Normal and Low Ovarian Reserve: Analyses of miRNAs and Selected Target Genes Involved in the Proliferation of Human Cumulus Cells and Oocyte Quality

The oocyte and the surrounding cumulus cells (CCs) are deeply linked by a complex bidirectional cross-talk. In this light, the molecular analysis of the CCs is nowadays considered to be precious in providing information on oocyte quality. It is now clear that miRNAs play a key role in several ovarian functions, such as folliculogenesis, steroidogenesis, and ovulation. Thus, in this study, specific miRNAs, together with their target genes, were selected and investigated in CCs to assess the response of patients with normal (NR) and low (LR) ovarian reserve to two different controlled ovarian stimulation (COS) protocols, based on rFSH and hMG. Moreover, a Fourier transform infrared microspectroscopy (FTIRM) analysis was performed to evaluate DNA conformational changes in CCs and to relate them with the two COS protocols. The results evidenced a modulation of the expression of miRNAs and related target genes involved in CCs' proliferation, in vasculogenesis, angiogenesis, genomic integrity, and oocyte quality, with different effects according to the ovarian reserve of patients. Moreover, the COS protocols determined differences in DNA conformation and the methylation state. In particular, the results clearly showed that treatment with rFSH is the most appropriate in NR patients with normal ovarian reserve, while treatment with hMG appears to be the most suitable in LR patients with low ovarian reserve.

Vibrational Imaging Techniques for the Characterization of Hard Dental Tissues: From Bench-Top to Chair-Side

Currently, various analytical techniques, including scanning electron microscopy, X-Ray diffraction, microcomputed tomography, and energy dispersive X-ray spectroscopy, are available to study the structural or elemental features of hard dental tissues. In contrast to these approaches, Raman Microspectroscopy (RMS) has the great advantage of simultaneously providing, at the same time and on the same sample, a morpho-chemical correlation between the microscopic information from the visual analysis of the sample and its chemical and macromolecular composition. Hence, RMS represents an innovative and non-invasive technique to study both inorganic and organic teeth components in vitro. The aim of this narrative review is to shed new light on the applicative potential of Raman Microspectroscopy in the dental field. Specific Raman markers representative of sound and pathological hard dental tissues will be discussed, and the future diagnostic application of this technique will be outlined. The objective and detailed information provided by this technique in terms of the structure and chemical/macromolecular components of sound and pathological hard dental tissues could be useful for improving knowledge of several dental pathologies. Scientific articles regarding RMS studies of human hard dental tissues were retrieved from the principal databases by following specific inclusion and exclusion criteria.

New insights from Raman MicroSpectroscopy and Scanning Electron Microscopy on the microstructure and chemical composition of vestibular and lingual surfaces in permanent and deciduous human teeth

Teeth are characterized by a specific chemical composition and microstructure, which are related to their nature, permanent and deciduous, and to the sides, lingual and vestibular. Deeper knowledge in this topic could be useful in clinical practice to develop new strategies in restorative dentistry and in the choice of materials with the best performances. In this study, Raman MicroSpectroscopy (RMS), Scanning Electron Microscopy (SEM), Energy Dispersive X-ray Spectrometry (EDS), and Vickers MicroHardness (VMH) were exploited to: (1) identify the microstructure and the chemical/elemental composition of permanent and deciduous human teeth, also characterizing their lingual and vestibular sides, and (2) validate a new multidisciplinary analytical approach, for obtaining multiple information on calcified tissues. All applied techniques evidenced differences between permanent and deciduous teeth both in the lingual and vestibular sides. In particular, scanning electron micrographs identified areas with an irregular appearance in the vestibular and lingual sides, which presented also different VMH values. Moreover, RMS and EDS displayed a different chemical/elemental composition in outer and inner enamel and dentin, in terms of Mineral/Matrix, Crystallinity, Carbonates/phosphates, and concentrations by weight (%) of calcium, phosphorous, carbon, magnesium, and sodium. A good linear correlation was found between RMS spectral profiles and EDS and VMH measurements, suggesting that RMS may be considered a useful and non-destructive diagnostic tool for obtaining multiple information on calcified tissues.

Detection of Human Cholangiocarcinoma Markers in Serum Using Infrared Spectroscopy

Simple Summary

Cholangiocarcinoma is a form of liver cancer that is found, predominantly, in Thailand. Due to the non-specific symptoms and laboratory investigation, it is difficult to rule out cholangiocarcinoma from other liver conditions. Here, we demonstrate the development of a diagnostic tool for cholangiocarcinoma, based on the ATR-FTIR analyses of sera, coupled with multivariate analyses and machine learning tools to obtain a better specificity. The innovative approach that shows highly promising results for this otherwise difficult to diagnose cancer.

Abstract

Cholangiocarcinoma (CCA) is a malignancy of the bile duct epithelium. Opisthorchis viverrini infection is a known high-risk factor for CCA and in found, predominantly, in Northeast Thailand. The silent disease development and ineffective diagnosis have led to late-stage detection and reduction in the survival rate. Attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR) is currently being explored as a diagnostic tool in medicine. In this study, we apply ATR-FTIR to discriminate CCA sera from hepatocellular carcinoma (HCC), biliary disease (BD) and healthy donors using a multivariate analysis. Spectral markers differing from healthy ones are observed in the collagen band at 1284, 1339 and 1035 cm⁻¹, the phosphate band (vsPO2−) at 1073 cm⁻¹, the polysaccharides band at 1152 cm⁻¹ and 1747 cm⁻¹ of lipid ester carbonyl. A Principal Component Analysis (PCA) shows discrimination between CCA and healthy sera using the 1400–1000 cm⁻¹ region and the combined 1800—1700 + 1400–1000 cm⁻¹ region. Partial Least Square-Discriminant Analysis (PLS-DA) scores plots in four of five regions investigated, namely, the 1400–1000 cm⁻¹, 1800–1000 cm⁻¹, 3000–2800 + 1800–1000 cm⁻¹ and 1800–1700 + 1400–1000 cm⁻¹ regions, show discrimination between sera from CCA and healthy volunteers. It was not possible to separate CCA from HCC and BD by PCA and PLS-DA. CCA spectral modelling is established using the PLS-DA, Support Vector Machine (SVM), Random Forest (RF) and Neural Network (NN). The best model is the NN, which achieved a sensitivity of 80–100% and a specificity between 83 and 100% for CCA, depending on the spectral window used to model the spectra. This study demonstrates the potential of ATR-FTIR spectroscopy and spectral modelling as an additional tool to discriminate CCA from other conditions.

Cytotoxic Effects of 5-Azacytidine on Primary Tumour Cells and Cancer Stem Cells from Oral Squamous Cell Carcinoma: An In Vitro FTIRM Analysis

In the present study, the cytotoxic effects of 5-azacytidine on primary Oral Squamous Cell Carcinoma cells (OSCCs) from human biopsies, and on Cancer Stem Cells (CSCs) from the same samples, were investigated by an in vitro Fourier Transform InfraRed Microscospectroscopy (FTIRM) approach coupled with multivariate analysis. OSCC is an aggressive tumoral lesion of the epithelium, accounting for ~90% of all oral cancers. It is usually diagnosed in advanced stages, and this causes a poor prognosis with low success rates of surgical, as well as radiation and chemotherapy treatments. OSCC is frequently characterised by recurrence after chemotherapy and by the development of a refractoriness to some employed drugs, which is probably ascribable to the presence of CSCs niches, responsible for cancer growth, chemoresistance and metastasis. The spectral information from FTIRM was correlated with the outcomes of cytotoxicity tests and image-based cytometry, and specific spectral signatures attributable to 5-azacytidine treatment were identified, allowing us to hypothesise the demethylation of DNA and, hence, an increase in the transcriptional activity, together with a conformational transition of DNA, and a triggering of cell death by an apoptosis mechanism. Moreover, a different mechanism of action between OSSC and CSC cells was highlighted, probably due to possible differences between OSCCs and CSCs response.

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.

A Spectroscopic Approach to Evaluate the Effects of Different Soil Tillage Methods and Nitrogen Fertilization Levels on the Biochemical Composition of Durum Wheat (Triticum turgidum subsp. durum) Leaves and Caryopses

The agricultural sector is required to produce food at the same pace as population growth, while accounting for pollution and costs. For this reason, conservative agricultural practices have been employed worldwide. Attenuated Total Reflectance–Fourier Transform Infrared (ATR-FTIR) spectroscopy has the ability to provide a snapshot of the macromolecular composition of a sample in a timely and cost-effective way and it has been widely applied in the field of agriculture to assess food quality. The aim of this study was to exploit ATR-FTIR spectroscopy to assess the impact of different soil tillage methods (conventional tillage, CT; minimum tillage, MT, and no tillage, NT) and nitrogen fertilization levels (0, 90 and 180 kg N ha−1) on the macromolecular composition of leaves and caryopses of durum wheat (Triticum turgidum subsp. durum). The analysis of the spectral data revealed that the quality of durum wheat, in terms of protein content, grown on soil with no tillage was not reduced. Indeed, with regards to caryopses, the different tillage methods influenced only the lipid and hemicellulose content, whereas the macromolecular composition of leaves was sensitive to tillage methods mostly during the early stage of growth. Moreover, no relevant effects were found in leaves and caryopses when different fertilizer concentrations were used. These results provide important knowledge supporting the adoption of both no-tillage soil treatments and reduced fertilization dosage for the development of durum wheat management strategies and support the use of spectroscopy for conservative agriculture practices.

Hermetia illucens and Poultry by-Product Meals as Alternatives to Plant Protein Sources in Gilthead Seabream (Sparus aurata) Diet: A Multidisciplinary Study on Fish Gut Status

Simple Summary

Sustainability and fish welfare have been receiving increasing attention in the aquaculture sector, with an emphasis on the search for new, sustainable, and healthy aquafeed ingredients. For many years, plant ingredients have been widely used in aquafeed formulation; however, negative side effects on gut welfare have often been reported in several carnivorous fish species. From this perspective, alternative ingredients such as poultry by-products and insect meal are receiving attention due to their low ecological footprint and high nutritional value. In the present study, these two ingredients were used, singly or in combination, to formulate practical diets for gilthead seabream (Sparus aurata). After a twelve-week feeding trial, a multidisciplinary laboratory approach including histological, molecular, and spectroscopic techniques was adopted in order to investigate fish physiological responses to the new test diets. The results obtained showed excellent zootechnical performances and ameliorated gut health in fish fed dietary inclusions of poultry by-products and insect meal compared to those fed a vegetable-based diet. In addition, the modulation of nutrient absorption in relation to the ingredients used was highlighted by means of spectroscopic tools. The results obtained demonstrated that poultry by-products and insect meal can be successfully used to replace plant-derived ingredients in diets for gilthead seabream without negatively affecting fish welfare.

Abstract

The attempt to replace marine-derived ingredients for aquafeed formulation with plant-derived ones has met some limitations due to their negative side effects on many fish species. In this context, finding new, sustainable ingredients able to promote fish welfare is currently under exploration. In the present study, poultry by-products and Hermetia illucens meal were used to replace the vegetable protein fraction in diets totally deprived of fish meal intended for gilthead seabream (Sparus aurata). After a 12-week feeding trial, a multidisciplinary approach including histological, molecular, and spectroscopic techniques was adopted to investigate intestine and liver responses to the different dietary formulations. Regardless of the alternative ingredient used, the reduction in dietary vegetable proteins resulted in a lower incidence of intestine histological alterations and inflammatory responses. In addition, the dietary inclusion of insect meal positively affected the reduction in the molecular inflammatory markers analyzed. Spectroscopic analyses showed that poultry by-product meal improved lipid absorption in the intestine, while insect meal induced increased liver lipid deposition in fish. The results obtained demonstrated that both poultry by-products and H. illucens meal can successfully be used to replace plant-derived ingredients in diets for gilthead seabream, promoting healthy aquaculture.

Physiological responses of Siberian sturgeon (Acipenser baerii) juveniles fed on full-fat insect-based diet in an aquaponic system

Over the last years, the potential use of Black Soldier Fly meal (BSF) as a new and sustainable aquafeed ingredient has been largely explored in several fish species. However, only fragmentary information is available about the use of BSF meal-based diets in sturgeon nutrition. In consideration of a circular economy concept and a more sustainable aquaculture development, the present research represents the first comprehensive multidisciplinary study on the physiological effects of a BSF diet during sturgeon culture in an aquaponic system. Siberian sturgeon (Acipenser baerii) juveniles were fed over a 60-days feeding trial on a control diet (Hi0) and a diet containing 50% of full-fat BSF meal respect to fish meal (Hi50). Physiological responses of fish were investigated using several analytical approaches, such as gas chromatography-mass spectrometry, histology, Fourier Transformed Infrared Spectroscopy (FTIR), microbiome sequencing and Real-time PCR. While aquaponic systems performed optimally during the trial, Hi50 group fish showed lower diet acceptance that resulted in growth and survival reduction, a decrease in hepatic lipids and glycogen content (FTIR), a higher hepatic hsp70.1 gene expression and a worsening in gut histological morphometric parameters. The low feed acceptance showed by Hi50 group sturgeon highlighted the necessity to improve the palatability of BSF-based diet designed for sturgeon culture.

Use of Fourier-Transform Infrared Spectroscopy (FT-IR) for Monitoring Experimental Helicobacter pylori Infection and Related Inflammatory Response in Guinea Pig Model

Infections due to Gram-negative bacteria Helicobacter pylori may result in humans having gastritis, gastric or duodenal ulcer, and even gastric cancer. Investigation of quantitative changes of soluble biomarkers, correlating with H. pylori infection, is a promising tool for monitoring the course of infection and inflammatory response. The aim of this study was to determine, using an experimental model of H. pylori infection in guinea pigs, the specific characteristics of infrared spectra (IR) of sera from H. pylori infected (40) vs. uninfected (20) guinea pigs. The H. pylori status was confirmed by histological, molecular, and serological examination. The IR spectra were measured using a Fourier-transform (FT)-IR spectrometer Spectrum 400 (PerkinElmer) within the range of wavenumbers 3000–750 cm⁻¹ and converted to first derivative spectra. Ten wavenumbers correlated with H. pylori infection, based on the chi-square test, were selected for a K-nearest neighbors (k-NN) algorithm. The wavenumbers correlating with infection were identified in the W2 and W3 windows associated mainly with proteins and in the W4 window related to nucleic acids and hydrocarbons. The k-NN for detection of H. pylori infection has been developed based on chemometric data. Using this model, animals were classified as infected with H. pylori with 100% specificity and 97% sensitivity. To summarize, the IR spectroscopy and k-NN algorithm are useful for monitoring experimental H. pylori infection and related inflammatory response in guinea pig model and may be considered for application in humans.

Knockout of the Glucocorticoid Receptor Impairs Reproduction in Female Zebrafish

The pleiotropic effects of glucocorticoids in metabolic, developmental, immune and stress response processes have been extensively investigated; conversely, their roles in reproduction are still less documented. It is well known that stress or long-lasting therapies can cause a strong increase in these hormones, negatively affecting reproduction. Moreover, the need of glucocorticoid (GC) homeostatic levels is highlighted by the reduced fertility reported in the zebrafish glucocorticoid receptor mutant (nr3c1ia30/ia30) line (hereafter named gr-/-). Starting from such evidence, in this study, we have investigated the role of glucocorticoid receptor (Gr) in the reproduction of female zebrafish. Key signals orchestrating the reproductive process at the brain, liver, and ovarian levels were analyzed using a multidisciplinary approach. An impairment of the kiss-GnRH system was observed at the central level in (gr-/-) mutants as compared to wild-type (wt) females while, in the liver, vitellogenin (vtg) mRNA transcription was not affected. Changes were instead observed in the ovary, particularly in maturing and fully grown follicles (classes III and IV), as documented by the mRNA levels of signals involved in oocyte maturation and ovulation. Follicles isolated from gr-/- females displayed a decreased level of signals involved in the acquisition of competence and maturation, causing a reduction in ovulation with respect to wt females. Fourier transform infrared imaging (FTIRI) analysis of gr-/- follicle cytoplasm showed major changes in macromolecule abundance and distribution with a clear alteration of oocyte composition. Finally, differences in the molecular structure of the zona radiata layer of gr-/- follicles are likely to contribute to the reduced fertilization rate observed in mutants.

The Impact of Controlled Ovarian Stimulation Hormones on the Metabolic State and Endocannabinoid System of Human Cumulus Cells

Different Follicle Stimulating Hormone (FSH) formulation and Luteinizing Hormone (LH) are used in Assisted Reproductive Technology (ART) to induce follicles development and oocytes maturation, but it is still under debate which protocol is to be preferred. In the present study, the different effects on cumulus cells (CCs) of three controlled ovarian stimulation (COS) protocols, based on urinary FSH, recombinant FSH, or human Menopausal Gonadotropin (hMG) administration, were assessed. CCs were obtained from 42 normal-responders women undergoing COS, randomly divided into three groups according to the used gonadotropin formulation. Differences were found in the expression of genes belonging to the endocannabinoid system (the receptors CNR1, CNR2 and TRPV1, and the enzymes involved in the metabolisms of anandamide, NAPE-PLD and FAAH, and 2-acylglycerol, DAGL and MAGL); consistently, changes in lipid (PPARα, and FASN) and carbohydrate (GLUT1 and GLUT9) metabolisms, in CCs’ macromolecules composition (highlighted by Fourier Transform Infrared Microspectroscopy, FTIRM), and in the number of retrieved oocytes were found. For the first time, statistically significant evidence on the differences related to each COS protocol on the endocannabinoid system, metabolism and macromolecular composition of CCs was found, representing a proof of concept to be further confirmed in a larger cohort of patients.

Evaluation of Melanoma (SK-MEL-2) Cell Growth between Three-Dimensional (3D) and Two-Dimensional (2D) Cell Cultures with Fourier Transform Infrared (FTIR) Microspectroscopy

Fourier transform infrared (FTIR) microspectroscopy was used to evaluate the growth of human melanoma cells (SK-MEL-2) in two-dimensional (2D) versus three-dimensional (3D) spheroid culture systems. FTIR microspectroscopy, coupled with multivariate analysis, could be used to monitor the variability of spheroid morphologies prepared from different cell densities. The characteristic shift in absorbance bands of the 2D cells were different from the spectra of cells from 3D spheroids. FTIR microspectroscopy can also be used to monitor cell death similar to fluorescence cell staining in 3D spheroids. A change in the secondary structure of protein was observed in cells from the 3D spheroid versus the 2D culture system. FTIR microspectroscopy can detect specific alterations in the biological components inside the spheroid, which cannot be detected using fluorescence cell death staining. In the cells from 3D spheroids, the respective lipid, DNA, and RNA region content represent specific markers directly proportional to the spheroid size and central area of necrotic cell death, which can be confirmed using unsupervised PCA and hierarchical cluster analysis. FTIR microspectroscopy could be used as an alternative tool for spheroid cell culture discrimination, and validation of the usual biochemical technique.