Search Results (55)

Sinus augmentation provides a well-established model for investigating the three-dimensional morphometry and macromolecular dynamics of bone regeneration, particularly when using biphasic calcium phosphate (BCP) graft substitutes. This case series included six biopsies from patients who underwent maxillary sinus augmentation using BCP granules composed of 30% hydroxyapatite (HA) and 70% β-tricalcium phosphate (β-TCP). Bone core biopsies were obtained at healing times of 6 months, 9 months, and 12 months. Histological evaluation yielded qualitative and quantitative insights into new bone distribution, while micro-computed tomography (micro-CT) and Raman microspectroscopy (RMS) were employed to assess the three-dimensional architecture and macromolecular composition of the regenerated bone. Micro-CT analysis revealed progressive maturation of the regenerated bone microstructure over time. At 6 months, the apical regenerated area exhibited a significantly higher mineralized volume fraction (58 ± 5%) compared to the basal native bone (44 ± 11%; p = 0.0170), as well as significantly reduced trabecular spacing (Tb.Sp: 187 ± 70 µm vs. 325 ± 96 µm; p = 0.0155) and degree of anisotropy (DA: 0.37 ± 0.05 vs. 0.73 ± 0.03; p < 0.0001). By 12 months, the mineralized volume fraction in the regenerated area (53 ± 5%) was statistically comparable to basal bone (44 ± 3%; p > 0.05), while Tb.Sp (211 ± 20 µm) and DA (0.23 ± 0.09) remained significantly lower (Tb.Sp: 395 ± 41 µm, p = 0.0041; DA: 0.46 ± 0.04, p = 0.0001), indicating continued structural remodelling and organization. Raman microspectroscopy further revealed dynamic macromolecular changes during healing. Characteristic β-TCP peaks (e.g., 1315, 1380, 1483 cm⁻¹) progressively diminished over time and were completely absent in the regenerated tissue at 12 months, contrasting with their partial presence at 6 months. Simultaneously, increased intensity of collagen-specific bands (e.g., Amide I at 1661 cm⁻¹, Amide III at 1250 cm⁻¹) and carbonate peaks (1065 cm⁻¹) reflected active matrix formation and mineralization. Overall, this case series provides qualitative and quantitative evidence that bone regeneration and integration of BCP granules in sinus augmentation continues beyond 6 months, with ongoing maturation observed up to 12 months post-grafting. Full article

Cardiac fibrosis following myocardial infarction plays a critical role in the formation of scar tissue and contributes to ventricular arrhythmias, including ventricular tachycardia and sudden cardiac death. Current clinical diagnostics use electrical and structural markers, but lack precision due to low spatial resolution and absence of molecular information. In this paper, we employed line scan Raman microspectroscopy to classify sheep myocardial tissue into muscle, necrotic, granulated, and fibrotic tissue types, using collagen as a molecular biomarker. Three spectral regions were evaluated: region A (600–2960 cm⁻¹), region B (600–1399 cm⁻¹ and 1751–2960 cm⁻¹), and region C (1400–1750 cm⁻¹), which includes the prominent collagen-associated peaks at 1448 cm⁻¹ and 1652 cm⁻¹. Linear and nonlinear principal component analysis (PCA) and support vector machines (SVMs) were applied for dimensionality reduction and classification, with nonlinear models specifically addressing the nonlinearity of collagen formation during fibrogenesis. Histological validation was performed using Masson’s trichrome staining. Raman bands associated with collagen in region C consistently outperformed regions A and B, achieving the highest explained variance and best class separation in both binary and multiclass PCA models for both linear and nonlinear approaches. The ratio of collagen-related peaks enabled stage-dependent tissue characterization, confirming the nonlinear nature of fibrotic remodeling. Our findings highlight the diagnostic potential of collagen-associated Raman bands for characterizing myocardial fibrosis. The proposed PCA-SVM framework demonstrates robust performance even with limited sample size and has the potential to lay the foundation for real-time intraoperative diagnostics. Full article

Vital pulp therapy with calcium hydroxide or mineral trioxide aggregate (MTA) rapidly induces dystrophic calcification and promotes the accumulation of two members of small integrin-binding ligand N-linked glycoproteins: osteopontin (OPN) and dentin matrix protein-1 (DMP1). However, the precise relationship between these initial events and their roles in reparative dentinogenesis remain unclear. This study aimed to clarify the relationship between dystrophic calcification, OPN and DMP1 accumulation, and reparative dentin formation. Pulpotomy was performed on rat molars using MTA or zirconium oxide (ZrO₂). ZrO₂ was used as a control to assess pulp healing in the absence of dystrophic calcification. Pulpal responses were evaluated from 3 h to 7 days postoperatively via elemental mapping, micro-Raman spectroscopy, and histological staining. In the MTA-treated group, a calcium-rich dystrophic calcification zone containing calcite and hydroxyapatite was observed at 3 h after treatment; OPN and DMP1 accumulated under the dystrophic calcification zone by day 3; reparative dentin formed below the region of OPN and DMP1 accumulation by day 7. In contrast, these reactions did not occur in the ZrO₂-treated group. These results suggest that dystrophic calcification serves as a key trigger for OPN and DMP1 accumulation and plays a pivotal role in reparative dentinogenesis. Full article

Colorectal cancer is one of the most commonly diagnosed cancers in developed countries. Although the gold-standard diagnosis technique is the histological analysis of colon biopsies, it is important to investigate different diagnostic tools because the microscope examination of stained tissues provides indications partially depending on the experience of the pathologist. This study reports a Raman-spectroscopy-based analysis of healthy and cancerous colon cells to detect biochemical differences at the subcellular level and discriminate the former from the latter. FHC and CaCo-2 cell lines were used to model healthy and cancerous cells, respectively. The comparison of the Raman spectra measured inside subcellular volumes including the nucleus (nucleus spectra) and excluding it (cytoplasm spectra), as well as principal component analysis and partial least squares analysis of these spectra, suggest that the differences between the spectra of healthy and cancerous cells are very small, and they mainly involve the different relative content of lipids and nucleic acid components. The relative intensity of lipid peaks is higher in the Raman spectra of healthy samples, while nucleic acid peaks show higher relative intensity in the spectra of cancer cells. Linear discriminant analysis of a few principal components and partial least squares components was used to estimate the classification accuracy of a set of Raman spectra measured inside nucleus and cytoplasm. Both methods are able to classify unknown cells with excellent accuracy (100% and 96%, respectively). The findings of this study confirm the general applicability of subcellular Raman analysis in clinical practice for diagnosis of cytological samples. Full article

Three-dimensional (3D) cellular models, such as spheroids, serve as pivotal systems for understanding complex biological phenomena in histology, oncology, and tissue engineering. In response to the growing need for advanced imaging capabilities, we present a novel multi-modal Raman light sheet microscope designed to capture elastic (Rayleigh) and inelastic (Raman) scattering, along with fluorescence signals, in a single platform. By leveraging a shorter excitation wavelength (532 nm) to boost Raman scattering efficiency and incorporating robust fluorescence suppression, the system achieves label-free, high-resolution tomographic imaging without the drawbacks commonly associated with near-infrared modalities. An accompanying Deep Image Prior (DIP) seamlessly integrates with the microscope to provide unsupervised denoising and resolution enhancement, preserving critical molecular details and minimizing extraneous artifacts. Altogether, this synergy of optical and computational strategies underscores the potential for in-depth, 3D imaging of biomolecular and structural features in complex specimens and sets the stage for future advancements in biomedical research, diagnostics, and therapeutics. Full article

Objectives: This study aimed to develop hesperidin solid lipid nanoparticles (HESP-SLNs) to enhance their stability, solubility, and sustained release for wound healing; further enhancement was achieved through prepared nanostructured lipid carriers (HESP-NLCs) using Tea Tree Oil (TTO) to explore their synergistic efficacy. Methods: A factorial design of 2⁴ trials was established to evaluate the influence of lipid type (X1), lipid conc (%) (X2), surfactant type (X3), and sonication amplitude (%) (X4) of prepared HESP-SLNs on the particle size (nm) (Y1), polydispersibility index (Y2), zeta potential (Y3), and encapsulation efficiency (%) (Y4). The optimized HESP-SLNs formula was selected utilizing Design Expert^® software version 13, which was additionally enhanced by preparing TTO-loaded HESP-NLCs. In vitro release, Raman spectroscopy, and transmission electron microscopy were carried out for both lipid nanoparticles. Cytotoxicity, in vivo wound-healing assessments, and skin irritancy tests were performed to evaluate the performance of TTO-incorporated HESP-NLCs compared to HESP-SLNs. Results: The optimized formula demonstrated PS (280 ± 1.35 nm), ZP (−39.4 ± 0.92 mV), PDI (0.239 ± 0.012), and EE% (88.2 ± 2.09%). NLCs enhanced Q6% release, (95.14%) vs. (79.69%), for SLNs and showed superior antimicrobial efficacy. Both lipid nanoparticles exhibited spherical morphology and compatibility between HESP and excipients. NLCs achieved the highest wound closure percentage, supported by histological analysis and inflammatory biomarker outcomes. Cytotoxicity evaluation showed 87% cell viability compared to untreated HSF cells, and the skin irritancy test confirmed the safety of NLCs. Conclusions: TTO-loaded HESP-NLCs are promising candidates exhibiting superior wound-healing capabilities, making them a potential therapeutic option for cutaneous wound management. Full article

This study assessed the biocompatibility and chemical properties of two bioceramic root canal sealers, EndoSequence BC Sealer (EBC) and Nishika Canal Sealer BG (NBG), using a sealer extrusion model. Eight-week-old male Wistar rats were used. The mesial root canals of the upper first molars were pulpectomized and overfilled with EBC, NBG, or, as reference, epoxy resin-based AH Plus (AHP). After 28 days, periapical tissue reactions were assessed using microcomputed tomography and histological staining. The elemental composition and chemical composition of the extruded EBC and NBG were analyzed at Day 1 and 28 using an electron probe microanalyzer and micro-Raman spectroscopy. No periapical lesions were observed with the sealer extrusion. Additionally, inflammation around the extruded EBC and NBG was minimal to mild on Day 28, whereas moderate inflammation was found around the extruded AHP. Silicon concentration in the extruded EBC and NBG decreased significantly from Day 1 to 28, with almost no silicon present on Day 28. Furthermore, the extruded EBC and NBG became calcium- and phosphorus-rich, showing a Raman band for hydroxyapatite on Day 28. In conclusion, EBC and NBG demonstrated favorable biocompatibility and the ability to release silicon elements and produce hydroxyapatite when extruded into the periapical tissues. AHP showed moderate periapical tissue irritancy. Full article

Advancements in Raman light sheet microscopy have provided a powerful, non-invasive, marker-free method for imaging complex 3D biological structures, such as cell cultures and spheroids. By combining 3D tomograms made by Rayleigh scattering, Raman scattering, and fluorescence detection, this modality captures complementary spatial and molecular data, critical for biomedical research, histology, and drug discovery. Despite its capabilities, Raman light sheet microscopy faces inherent limitations, including low signal intensity, high noise levels, and restricted spatial resolution, which impede the visualization of fine subcellular structures. Traditional enhancement techniques like Fourier transform filtering and spectral unmixing require extensive preprocessing and often introduce artifacts. More recently, deep learning techniques, which have shown great promise in enhancing image quality, face their own limitations. Specifically, conventional deep learning models require large quantities of high-quality, manually labeled training data for effective denoising and super-resolution tasks, which is challenging to obtain in multi-modal microscopy. In this study, we address these limitations by exploring advanced zero-shot and self-supervised learning approaches, such as ZS-DeconvNet, Noise2Noise, Noise2Void, Deep Image Prior (DIP), and Self2Self, which enhance image quality without the need for labeled and large datasets. This study offers a comparative evaluation of zero-shot and self-supervised learning methods, evaluating their effectiveness in denoising, resolution enhancement, and preserving biological structures in multi-modal Raman light sheet microscopic images. Our results demonstrate significant improvements in image clarity, offering a reliable solution for visualizing complex biological systems. These methods establish the way for future advancements in high-resolution imaging, with broad potential for enhancing biomedical research and discovery. Full article

Background: Stimulated Raman histology (SRH) is a label-free optical imaging method for rapid intraoperative analysis of fresh tissue samples. Analysis of SRH images using Convolutional Neural Networks (CNN) has shown promising results for predicting the main histopathological classes of neurooncological tumors. Due to the relatively low number of rare tumor representations in CNN training datasets, a valid prediction of rarer entities remains limited. To develop new reliable analysis tools, larger datasets and greater tumor variety are crucial. One way to accomplish this is through research biobanks storing frozen tumor tissue samples. However, there is currently no data available regarding the pertinency of previously frozen tissue samples for SRH analysis. The aim of this study was to assess image quality and perform a comparative reliability analysis of artificial intelligence-based tumor classification using SRH in fresh and frozen tissue samples. Methods: In a monocentric prospective study, tissue samples from 25 patients undergoing brain tumor resection were obtained. SRH was acquired in fresh and defrosted samples of the same specimen after varying storage durations at −80 °C. Image quality was rated by an experienced neuropathologist, and prediction of histopathological diagnosis was performed using two established CNNs. Results: The image quality of SRH in fresh and defrosted tissue samples was high, with a mean image quality score of 1.96 (range 1–5) for both groups. CNN analysis showed high internal consistency for histo-(Cα 0.95) and molecular (Cα 0.83) pathological tumor classification. The results were confirmed using a dataset with samples from the local tumor biobank (Cα 0.91 and 0.53). Conclusions: Our results showed that SRH appears comparably reliable in fresh and frozen tissue samples, enabling the integration of tumor biobank specimens to potentially improve the diagnostic range and reliability of CNN prediction tools. Full article

Frozen section biopsy, introduced in the early 1900s, still remains the gold standard methodology for rapid histologic evaluations. Although a valuable tool, it is labor-, time-, and cost-intensive. Other challenges include visual and diagnostic variability, which may complicate interpretation and potentially compromise the quality of clinical decisions. Raman spectroscopy, with its high specificity and non-invasive nature, can be an effective tool for dependable and quick histopathology. The most promising modality in this context is stimulated Raman histology (SRH), a label-free, non-linear optical process which generates conventional H&E-like images in short time frames. SRH overcomes limitations of conventional Raman scattering by leveraging the qualities of stimulated Raman scattering (SRS), wherein the energy gets transferred from a high-power pump beam to a probe beam, resulting in high-energy, high-intensity scattering. SRH’s high resolution and non-requirement of preprocessing steps make it particularly suitable when it comes to intrasurgical histology. Combining SRH with artificial intelligence (AI) can lead to greater precision and less reliance on manual interpretation, potentially easing the burden of the overburdened global histopathology workforce. We review the recent applications and advances in SRH and how it is tapping into AI to evolve as a revolutionary tool for rapid histologic analysis. Full article

Adipocytes derived from 3T3-L1 cells are a gold standard for analyses of adipogenesis processes and the metabolism of fat cells. A widely used histological and immunohistochemical staining and mass spectrometry lipidomics are mainly aimed for examining lipid droplets (LDs). Visualizing other cellular compartments contributing to the cellular machinery requires additional cell culturing for multiple labeling. Here, we present the localization of the intracellular structure of the 3T3-L1-derived adipocytes utilizing vibrational spectromicroscopy, which simultaneously illustrates the cellular compartments and provides chemical composition without extensive sample preparation and in the naïve state. Both vibrational spectra (FTIR—Fourier transform infrared and RS—Raman scattering spectroscopy) extended the gathered chemical information. We proved that both IR and RS spectra provide distinct chemical information about lipid content and their structure. Despite the expected presence of triacylglycerols and cholesteryl esters in lipid droplets, we also estimated the length and unsaturation degree of the fatty acid acyl chains that were congruent with known MS lipidomics of these cells. In addition, the clustering of spectral images revealed that the direct surroundings around LDs attributed to lipid-associated proteins and a high abundance of mitochondria. Finally, by using quantified markers of biomolecules, we showed that the fixative agents, paraformaldehyde and glutaraldehyde, affected the cellular compartment differently. We concluded that PFA preserves LDs better, while GA fixation is better for cytochromes and unsaturated lipid analysis. The proposed analysis of the spectral images constitutes a complementary tool for investigations into the structural and molecular features of fat cells. Full article

This study presents an advanced integration of Multi-modal Raman Light Sheet Microscopy with zero-shot learning-based computational methods to significantly enhance the resolution and analysis of complex three-dimensional biological structures, such as 3D cell cultures and spheroids. The Multi-modal Raman Light Sheet Microscopy system incorporates Rayleigh scattering, Raman scattering, and fluorescence detection, enabling comprehensive, marker-free imaging of cellular architecture. These diverse modalities offer detailed spatial and molecular insights into cellular organization and interactions, critical for applications in biomedical research, drug discovery, and histological studies. To improve image quality without altering or introducing new biological information, we apply Zero-Shot Deconvolution Networks (ZS-DeconvNet), a deep-learning-based method that enhances resolution in an unsupervised manner. ZS-DeconvNet significantly refines image clarity and sharpness across multiple microscopy modalities without requiring large, labeled datasets, or introducing artifacts. By combining the strengths of multi-modal light sheet microscopy and ZS-DeconvNet, we achieve improved visualization of subcellular structures, offering clearer and more detailed representations of existing data. This approach holds significant potential for advancing high-resolution imaging in biomedical research and other related fields. Full article

Background: Neurosurgery demands exceptional precision due to the brain’s complex and delicate structures, necessitating precise targeting of pathological targets. Achieving optimal outcomes depends on the surgeon’s ability to accurately differentiate between healthy and pathological tissues during operations. Raman spectroscopy (RS) has emerged as a promising innovation, offering real-time, in vivo non-invasive biochemical tissue characterization. This literature review evaluates the current research on RS applications in intraoperative neurosurgery, emphasizing its potential to enhance surgical precision and patient outcomes. Methods: Following PRISMA guidelines, a comprehensive systematic review was conducted using PubMed to extract relevant peer-reviewed articles. The inclusion criteria focused on original research discussing real-time RS applications with human tissue samples in or near the operating room, excluding retrospective studies, reviews, non-human research, and other non-relevant publications. Results: Our findings demonstrate that RS significantly improves tumor margin delineation, with handheld devices achieving high sensitivity and specificity. Stimulated Raman Histology (SRH) provides rapid, high-resolution tissue images comparable to traditional histopathology but with reduced time to diagnosis. Additionally, RS shows promise in identifying tumor types and grades, aiding precise surgical decision-making. RS techniques have been particularly beneficial in enhancing the accuracy of glioma surgeries, where distinguishing between tumor and healthy tissue is critical. By providing real-time molecular data, RS aids neurosurgeons in maximizing the extent of resection (EOR) while minimizing damage to normal brain tissue, potentially improving patient outcomes and reducing recurrence rates. Conclusions: This review underscores the transformative potential of RS in neurosurgery, advocating for continued innovation and research to fully realize its benefits. Despite its substantial potential, further research is needed to validate RS’s clinical utility and cost-effectiveness. Full article

Background: Raman spectroscopy is a well-known tool used in criminology, molecular biology, and histology. It is also applied to diagnose bone mineral disorders by taking advantage of the similarity of the structure of keratin and bone collagen. Raman spectroscopy can also be used in dermatology and diabetology. The purpose of the present review is to critically evaluate the available research about the use of Raman spectroscopy in the mentioned areas of medicine. Methodology: PubMed was searched for peer-reviewed articles on the subject of use of Raman spectroscopy in bone mineral disorders, dermatology, and diabetes mellitus. Results: Nail keratin and bone collagen are related structural proteins that require disulfide bond for structural stability. Therefore, Raman spectroscopy of keratin may have potential as a diagnostic tool for screening bone quality and distinguishing patients at risk of fracture for reasons different from low bone mineral density (BMD) in the adult women population. Raman spectroscopy can also investigate the changes in keratin’s structure in nails affected by onychomycosis and distinguish between healthy and onychomycosis nail samples. It could also reduce the need for nail biopsy by distinguishing between dermatophytic and non-dermatophytic agents of onychomycosis. Additionally, Raman spectroscopy could expedite the diagnostic process in psoriasis (by assessing the secondary structure of keratin) and in diabetes mellitus (by examining the protein glycation level). Conclusions: In adult populations, Raman spectroscopy is a promising and safe method for assessing the structure of fingernails. However, data are scarce in the pediatric population; therefore, more studies are required in children. Full article

In the last few years, an increasing interest has developed regarding the application of different techniques for the identification of pollutants inside the tissues deriving from patients affected by benign or neoplastic diseases. Particular attention was paid to neoplasia linked to particular exposures, e.g., heavy metals, carbon dusts, silica, asbestos. As regards the last pollutant, a wide body of scientific literature has been collected, considering the severe effects caused by mineral fibers on human health. Optical and electronic microscopies were widely applied to identify the fibers in respiratory and extra-respiratory organs to detect the minerals and to link their presence to an exposure source and to understand their role in cancer development. The main advantage of electron microscopy lies in the possibility of coupling the microscopes with energy dispersive spectrometers and also collecting data on the elemental composition of various inorganic phases. In term of sample preparation and time of analysis, the most utilized microscope technique is Scanning Electron Microscopy with an annexed energy dispersive spectrometer (SEM/EDS), allowing for the morphological and chemical characterization of the observed particles/fibers. Moreover, this technique is envisaged by Italian Law for asbestos identification in air and bulk samples. On the other hand, this technique does not allow a reliable identification of the mineral phase in the case of polymorphs with the same chemical formula but different crystal structures. In this work, the coupling of a spectroscopical technique—micro-Raman spectroscopy—to SEM/EDS is proposed for a sure phase identification of particles, showing EDS spectra with ambiguous phase identification, observed in samples of tissues from patients affected by colorectal cancer and living in an asbestos-polluted area. In these tissues, different particles with EDS spectra that do not allow a sure identification of the phase—in particular calcium-rich particles and titanium oxides—were successively analyzed by micro-Raman spectroscopy. Thanks to this last technique, it was possible to ascribe the mineral phases associated to these particles to “aragonite” (a calcium carbonate polymorph) and to “anatase” (a Ti dioxide polymorph). Full article