Confocal raman microspectral imaging of ex vivo human spinal cord tissue

Studying the pathological and biochemical features in breast cancer progression by confocal Raman microspectral imaging of excised tissue samples

Confocal Raman microspectral imaging (CRMI) has been used to detect the spectra-pathological features of ductal carcinoma in situ (DCIS) and lobular hyperplasia (LH) compared with the heathy (H) breast tissue. A total of 15-20 spectra were measured from healthy tissue, LH tissue, and DCIS tissue. One-way ANOVA and Tukey's honest significant difference (HSD) post hoc multiple tests were used to evaluate the peak intensity variations in all three tissue types. Besides that, linear discrimination analysis (LDA) algorithm was adopted in combination with principal component analysis (PCA) to classify the spectral features from tissues at different stages along the continuum to breast cancer. Moreover, by using the point-by-point scanning methodology, spectral datasets were obtained and reconstructed for further pathologic visualization by multivariate imaging methods, including K-mean clustering analysis (KCA) and PCA. Univariate imaging of individual Raman bands was also used to describe the differences in the distribution of specific molecular components in the scanning area. After a detailed spectral feature analysis from 800 to 1800 cm^-1 and 2800 to 3000 cm^-1 for all the three tissue types, the histopathological features were visualized based on the content and structural variations of lipids, proteins, phenylalanine, carotenoids and collagen, as well as the calcification phenomena. The results obtained not only allowed a detailed Raman spectroscopy-based understanding of the malignant transformation process of breast cancer, but also provided a solid spectral data support for developing Raman based breast cancer clinical diagnostic techniques.

Design of a Multimodal Imaging System and Its First Application to Distinguish Grey and White Matter of Brain Tissue. A Proof-of-Concept-Study

Multimodal imaging gains increasing popularity for biomedical applications. This article presents the design of a novel multimodal imaging system. The centerpiece is a light microscope operating in the incident and transmitted light mode. Additionally, Raman spectroscopy and VIS/NIR reflectance spectroscopy are adapted. The proof-of-concept is realized to distinguish between grey matter (GM) and white matter (WM) of normal mouse brain tissue. Besides Raman and VIS/NIR spectroscopy, the following optical microscopy techniques are applied in the incident light mode: brightfield, darkfield, and polarization microscopy. To complement the study, brightfield images of a hematoxylin and eosin (H&E) stained cryosection in the transmitted light mode are recorded using the same imaging system. Data acquisition based on polarization microscopy and Raman spectroscopy gives the best results regarding the tissue differentiation of the unstained section. In addition to the discrimination of GM and WM, both modalities are suited to highlight differences in the density of myelinated axons. For Raman spectroscopy, this is achieved by calculating the sum of two intensity peak ratios (I2857 + I2888)/I2930 in the high-wavenumber region. For an optimum combination of the modalities, it is recommended to apply the molecule-specific but time-consuming Raman spectroscopy to smaller regions of interest, which have previously been identified by the microscopic modes.

Raman Microspectroscopic Investigation and Classification of Breast Cancer Pathological Characteristics

Breast cancer is one of the major cancers of women in the world. Despite significant progress in its treatment, an early diagnosis can effectively reduce its incidence rate and mortality. To improve the reliability of Raman-based tumor detection and analysis methods, we conducted an ex vivo study to unveil the compositional features of healthy control (HC), solid papillary carcinoma (SPC), mucinous carcinoma (MC), ductal carcinoma in situ (DCIS), and invasive ductal carcinoma (IDC) tissue samples. Following the identification of biological variations occurring as a result of cancer invasion, principal component analysis followed by linear discriminate analysis (PCA-LDA) algorithm were adopted to distinguish spectral variations among different breast tissue groups. The achieved results confirmed that after training, the constructed classification model combined with the leave-one-out cross-validation (LOOCV) method was able to distinguish the different breast tissue types with 100% overall accuracy. The present study demonstrates that Raman spectroscopy combined with multivariate analysis technology has considerable potential for improving the efficiency and performance of breast cancer diagnosis.

Study on the biochemical mechanisms of the micro-wave ablation treatment of lung cancer by ex vivo confocal Raman microspectral imaging

As a highly invasive and the most prevalent malignancy, lung cancer remains the leading cause of cancer-associated mortality worldwide, especially in China. Microwave ablation (MWA) is an effective, safe, and the least invasive ablative treatment modality, which has been increasingly used for the management of unrespectable lung tumors. However, the underlying biochemical mechanisms of MWA treatment remain to be incompletely elucidated. Therefore, to illustrate the complex biochemical responses of lung squamous cell carcinoma (LSCC) to MWA treatment, confocal Raman micro-spectral imaging (CRMI) was applied in combination with multivariate analysis. A total of twelve LSCC tissues were acquired from patients undergoing clinical treatment, and their spectral characteristics were analyzed to determine significant spectral variations following cancer progression and MWA treatment in comparison with healthy lung tissues. Point-scanned Raman datasets were acquired from sectioned tissue samples in both pre-therapy (Pre-MWA group) and post-therapy groups (Post-MWA group) and further analyzed using K-means cluster analysis (KCA) and principal component analysis (PCA) to highlight the detailed compositional variations of the biochemical constituents. The spectral variations of essential amino acids (such as phenylalanine and tryptophan), collagen, and nucleic acids in the cancerous tissues of the Post-MWA group were significantly enhanced compared to those in the Pre-MWA group. The acquired information further confirmed a remarkable increase in the content of nucleic acid, protein, and lipid in the cancerous tissue following MWA treatment and, a comparative spectral imaging investigation indicated that MWA had no noticeable adverse effects on the paracancerous tissues. Thus, the findings not only illustrated the underlying biochemical variability in lung cancer during MWA treatment but also further confirmed the feasibility of a combined analytical procedure for assessing the biochemical responses during thermal ablation, which could be applied to prominently enhance the effectiveness of MWA in lung cancer treatment in clinical settings.

Myelination and Node of Ranvier Formation in a Human Motoneuron-Schwann Cell Serum-Free Coculture

Myelination and node of Ranvier formation play an important role in the rapid conduction of nerve impulses, referred to as saltatory conduction, along axons in the peripheral nervous system. We report a human-human myelination model using human primary Schwann cells (SCs) and human-induced pluripotent stem-cell-derived motoneurons utilizing a serum-free medium supplemented with ascorbate to induce myelination, where 41.6% of SCs expressed the master transcription factor for myelination, early growth response protein 2. After 30 days in coculture, myelin segments were visualized using immunocytochemistry for myelin basic protein surrounding neurofilament-stained motor neuron axons, which was confirmed via 3D confocal Raman microscopy, a viable alternative for transmission electron microscopy analysis. The myelination efficiency was 65%, and clusters of voltage-gated sodium channels and the paranodal protein contactin-associated protein 1 indicated node of Ranvier formation. This model has applications to study remyelination and demyelinating diseases, including Charcot-Marie Tooth disorder, Guillian-Barre syndrome, and anti-myelin-associated glycoprotein peripheral neuropathy.

Coupled Turbidity and Spectroscopy Problems: A Simple Algorithm for Volumetric Analysis of Optically Thin or Dilute, In Vitro Bacterial Cultures in Various Media

An approach binary spectronephelometry (BSN) to perform real-time simultaneous noninvasive in situ physical and chemical analysis of bacterial cultures in fluid media is described. We choose to characterize cultures of Escherichia coli (NC), Pseudomonas aeruginosa (PA), and Shewanella oneidensis (SO) in the specific case of complex media whose Raman spectrum cannot be unambiguously assigned. Nevertheless, organism number density and a measure of the chemical makeup of the fluid medium can be monitored noninvasively, simultaneously, and continuously, despite changing turbidity and medium chemistry. The method involves irradiating a culture in fluid medium in an appropriate vessel (in this case a standard 1 cm cuvette) using a near infrared laser and collecting all the backscattered light from the cuvette, i.e., the Rayleigh-Mie line and the inelastically emitted light which includes unresolved Raman scattered light and fluorescence. Complex "legacy" media contain materials of biological origin whose chemical composition cannot be fully delineated. We independently calibrate this approach to a commonly used reference, optical density at 600 nm (OD600) for characterizing the number density of organisms. We suggest that the total inelastically emitted light could be a measure of the chemical state of a biologically based medium, e.g., lysogeny broth (LB). This approach may be useful in a broad range of basic and applied studies and enterprises that utilize bacterial cultures in any medium or container that permits optical probing in the single scattering limit.

Raman spectroscopy combined with multivariate analysis to study the biochemical mechanism of lung cancer microwave ablation

Lung cancer is the leading cause of death in cancer patients, and microwave ablation (MWA) has been extensively used in clinical treatment. In this study, we characterized the spectra of MWA-treated and untreated lung squamous cell carcinoma (LSCC) tissues, as well as healthy lung tissue, and conducted a preliminary analysis of spectral variations associated with MWA treatment. The results of characteristic spectral analysis of different types of tissues indicated that MWA treatment induces an increase in the content of nucleic acids, proteins, and lipid components in lung cancer tissues. The discriminant model based on the principal component analysis - linear discriminant analysis (PCA-LDA) algorithm together with leave-one-out cross validation (LOOCV) method yield the sensitivities of 90%, 80%, and 96%, and specificities of 86.2%, 93.8%, and 100% among untreated and MWA-treated cancerous tissue, and healthy lung tissue, respectively. These results indicate that Raman spectroscopy combined with multivariate analysis techniques can be used to explore the biochemical response mechanism of cancerous tissue to MWA therapy.

Study on the pathological and biomedical characteristics of spinal cord injury by confocal Raman microspectral imaging

Confocal Raman microspectral imaging (CRMI) in combination with multivariate analysis was used to study pathological progression after spinal cord injury (SCI). By establishing moderate contusion in rat models, ex vivo longitudinal spinal cord tissue sections were prepared for microspectroscopic analysis. Comparative studies were then performed to determine the pathological distinctions among before injury (BI), one day post-injury (1 DPI), seven days post-injury (7 DPI), and 14 days post-injury (14 DPI) groups. Multivariate analysis algorithms, including K-mean cluster analysis (KCA) and principal component analysis (PCA), were conducted to highlight biochemical and structural variations after tissue damage. It is confirmed that typical spectral features and profiles can illustrate some fundamental and significant pathological processes post-injury, such as neuron apoptosis, hemorrhage, demyelination, and chondroitin sulfate proteoglycans (CSPGs) upregulation. Further, by establishing spectra-structure correlations, the reconstructed spectral images revealed some minute and important morphological characteristics following tissue injury, such as glial scar formation surrounding the cavity structure. The observed spectral phenomena also provide a detailed view on relevant pathobiological factors, which are involved in the spread of secondary damage after traumatic spinal cord injury. Our findings not only provide a spectral perspective to the well-known cellular mechanisms underlying SCI, but further provide a sound basis for developing real-time Raman methodologies to evaluate the prognostic factors and therapeutic results of SCI.

Tissue degeneration in ALS affected spinal cord evaluated by Raman spectroscopy

The Raman spectral features from spinal cord tissue sections of transgenic, ALS model mice and non-transgenic mice were compared using 457 nm excitation line, profiting from the favourable signal intensity obtained in the molecular fingerprint region at this wavelength. Transverse sections from four SOD1G93A mice at 75 days and from two at 90 days after birth were analysed and compared with sections of similarly aged control mice. The spectra acquired within the grey matter of tissue sections from the diseased mice is markedly different from the grey matter signature of healthy mice. In particular, we observe an intensity increase in the spectral windows 450-650 cm-1 and 1050-1200 cm-1, accompanied by an intensity decrease in the lipid contributions at ~1660 cm-1, ~1440 cm-1 and ~1300 cm-1. Axons demyelination, loss of lipid structural order and the proliferation and aggregation of branched proteoglycans are related to the observed spectral modifications. Furthermore, the grey and white matter components of the spinal cord sections could also be spectrally distinguished, based on the relative intensity of characteristic lipid and protein bands. Raman spectra acquired from the white matter regions of the SOD1G93A mice closely resembles those from control mice.