{"id":472,"date":"2025-09-06T19:05:09","date_gmt":"2025-09-06T13:35:09","guid":{"rendered":"https:\/\/www.najao.com\/learn\/?p=472"},"modified":"2026-04-01T19:25:51","modified_gmt":"2026-04-01T13:55:51","slug":"spectroscopy-and-imaging","status":"publish","type":"post","link":"https:\/\/www.najao.com\/learn\/spectroscopy-and-imaging\/","title":{"rendered":"Spectroscopy and Imaging in Biology: Unveiling the Hidden Complexity of Life"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\">To understand the intricate architecture and dynamic processes of living systems, we need powerful methods that explore beyond what is visible. Spectroscopy and imaging techniques form the backbone of this exploration<strong><sup>1<\/sup><\/strong>. They involve studying electromagnetic (EM) radiation interactions with matter and translating them into spatial visualizations. These techniques allow us to know not only &#8220;where&#8221; structures exist but also &#8220;what&#8221; molecules are present and &#8220;how much&#8221; of them exist. Therefore, they offer us an unparalleled insight into molecular composition, structure, and function across all biological scales. Evidently, these techniques have been playing transformative roles in foundational biology and clinical medicine<strong><sup>2, 3<\/sup><\/strong>.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">EM spectrum and interaction modes<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">The EM spectrum <a href=\"https:\/\/imagine.gsfc.nasa.gov\/science\/toolbox\/emspectrum1.html\" target=\"_blank\" rel=\"noreferrer noopener\">spans from<\/a> long radio waves to short gamma rays. Biological applications exploit distinct regions based on the energy of the photons and their interaction mechanisms with matter.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Following are the main types of interaction phenomena that underpin the various techniques:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Absorption:<\/strong> Molecules absorb photons, leading to electronic or vibrational (IR) transitions<strong><sup>4<\/sup><\/strong>. This helps to reveal molecular composition and concentration.<\/li>\n\n\n\n<li><strong>Emission:<\/strong> Electronically excited molecules return to the ground state by releasing energy as light (fluorescence, phosphorescence). This offers high sensitivity and molecular specificity.<\/li>\n\n\n\n<li><strong>Scattering:<\/strong> Incident light deviates in direction<strong><sup>5<\/sup><\/strong>. Inelastic scattering (Raman) involves a small energy shift corresponding to molecular vibrations.<\/li>\n\n\n\n<li><strong>Diffraction:<\/strong> Used in X-ray techniques, such as X-ray crystallography, to reveal precise atomic structure based on predictable interference patterns from ordered materials<strong><sup>6<\/sup><\/strong>.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Differentiating Spectroscopy and Imaging<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Many cutting-edge biological methods have integrated spectroscopic principles into imaging modalities. However, the fundamental distinction between spectroscopy and imaging lies in their primary data output and informational focus. Spectroscopy primarily measures the interaction of EM radiation with a sample as a function of wavelength or energy, and this results in a spectrum. This spectrum is a molecular fingerprint that identifies the chemical components, concentration, and molecular structure of the analyzed sample (the &#8220;what&#8221;). Conversely, Imaging focuses on measuring the spatial distribution of a signal to produce a map or image. It aids in revealing the location, morphology, and spatial arrangement of biological features (the &#8220;where&#8221;).<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The most powerful current technologies, referred to as spectroscopic imaging (e.g., FTIR Imaging, Raman Microscopy, and Mass spectrometry imaging (MSI)), combines both spectroscopy and imaging<strong><sup>7-9<\/sup><\/strong>. They collect a full spectrum for every spatial point in an image, generating a data cube. In this way, these techniques simultaneously provide high-resolution positional information (the image) and detailed chemical identification (the spectrum) at every location.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">UV-Visible (UV-Vis) spectroscopy and imaging<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">UV-Vis spectroscopy measures the absorption of ultraviolet and visible light by chromophores<strong><sup>10<\/sup><\/strong>. It is a fundamental quantitative tool, as absorption is proportional to concentration. It is routinely used in biochemistry for nucleic acid and protein quantification, enzyme assay monitoring, and cell viability assessments <em>in vitro<\/em><strong><sup>11-14<\/sup><\/strong>.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Absorption microscopy spatially maps this principle, helping to visualize the distribution of naturally absorbing molecules like hemoglobin or artificially stained components within cells and tissues<strong><sup>15<\/sup><\/strong>. This process thus links the molecular presence to its exact location.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Fluorescence spectroscopy and microscopy<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Fluorescence is characterized by the Stokes shift, which is longer emission wavelength than excitation<strong><sup>16<\/sup><\/strong>. It is vital for its exceptional sensitivity (often single-molecule level) and specificity, which is often enabled by external fluorophores or genetically encoded fluorescent proteins.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Microscopic modalities are key to dynamic biological imaging:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Confocal microscopy<\/strong> uses a pinhole to achieve 3D optical sectioning and high-contrast imaging<strong><sup>17<\/sup><\/strong>.<\/li>\n\n\n\n<li><strong>Multi-photon microscopy<\/strong> uses lower-energy photons for deep tissue imaging with reduced phototoxicity, which is essential for <em>in vivo<\/em> studies<strong><sup>18<\/sup><\/strong>.<\/li>\n\n\n\n<li><strong>Super-resolution techniques<\/strong> (e.g., STORM, PALM, STED) bypass the classical diffraction limit<strong><sup>19-21<\/sup><\/strong>. This allows the visualization of organelles and protein complexes at the nanometer scale.<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">The applications are wide-ranging, such as gene expression, protein-protein interactions (eg, FRET), and tracking ion fluxes in live cells<strong><sup>22-24<\/sup><\/strong>. It helps to profoundly impact drug discovery and disease mechanism studies.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Infrared (IR) spectroscopy and imaging<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">IR spectroscopy is used to probe the vibrational modes of functional groups like C=O and N-H, to generate a detailed &#8220;chemical fingerprint&#8221; that characterizes the macromolecular composition (proteins, lipids, nucleic acids etc.)<strong><sup> 25<\/sup><\/strong>.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Fourier-transform infrared (FTIR) imaging<\/strong> combines the spectral richness of IR with microscopy to generate spatially-resolved biochemical maps<strong><sup>26<\/sup><\/strong>. This label-free technique can discriminate tissues based on subtle changes in their biochemical profiles. They can help detecting cancerous changes or fibrosis by mapping lipid-to-protein ratios or shifts in protein secondary structure, helping to complement molecular pathology<strong><sup>27<\/sup><\/strong>.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Raman spectroscopy and imaging<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Raman spectroscopy<\/strong> relies on inelastic scattering, thus providing complementary vibrational information to IR<strong><sup>28<\/sup><\/strong>. This technique is minimally sensitive to water, which makes it highly advantageous for biological samples. It is also uniquely sensitive to non-polar bonds.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Raman microscopy<\/strong> creates high-resolution chemical maps of cells and tissues <em>in situ<\/em> without exogenous labels<strong><sup>29<\/sup><\/strong>. Key applications include:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Intraoperative tumor margin identification<\/strong> for rapid surgical guidance<strong><sup>30<\/sup><\/strong>.<\/li>\n\n\n\n<li><strong>Single-cell molecular profiling<\/strong> to characterize cellular heterogeneity<strong><sup>31<\/sup><\/strong>.<\/li>\n\n\n\n<li><strong>Drug distribution studies<\/strong> within tissue samples<strong><sup>32<\/sup><\/strong>.<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">Advanced techniques like <strong>surface-enhanced Raman spectroscopy (SERS)<\/strong> utilize metallic nanoparticles to amplify the typically weak Raman signal, thereby achieving higher sensitivity<strong><sup>33<\/sup><\/strong>.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Nuclear magnetic resonance (NMR) spectroscopy and magnetic resonance imaging (MRI)<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">NMR spectroscopy utilizes the magnetic properties of atomic nuclei (eg, H, C) in a strong external magnetic field<strong><sup>34<\/sup><\/strong>. It analyzes the absorption and re-emission of radiofrequency energy. This helps to provide precise data on molecular structure and dynamics in solutions, which is crucial for understanding protein folding and detailed metabolomic analysis.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">MRI is the <a href=\"https:\/\/www.nibib.nih.gov\/science-education\/science-topics\/magnetic-resonance-imaging-mri\" target=\"_blank\" rel=\"noreferrer noopener\">clinical extension<\/a> of the above technique. It helps to generate non-invasive, high-resolution <strong>soft tissue images<\/strong>. Specialized MRI techniques include:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Functional MRI (fMRI)<\/strong>: It is used to monitor blood oxygenation level changes (BOLD contrast) to map brain activity<strong><sup>35<\/sup><\/strong>.<\/li>\n\n\n\n<li><strong>Diffusion tensor imaging (DTI)<\/strong>: It helps to visualize the directionality of water diffusion to map neural white matter tracts<strong><sup>36<\/sup><\/strong>.<\/li>\n\n\n\n<li><strong>Magnetic resonance spectroscopy (MRS)<\/strong>: It is utilized for quantifying regional metabolite concentrations <em>in vivo<\/em> for clinical assessment of tumors or neurological disorders<strong><sup>37<\/sup><\/strong>.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Mass spectrometry and mass spectrometry imaging<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Mass spectrometry<\/strong> ionizes molecules and separates them based on their <strong>mass-to-charge ratio (m\/z)<\/strong><strong><sup> 38<\/sup><\/strong>. It offers ultra-high sensitivity for the identification and quantification of thousands of biomolecules. It is the core technology that drives <strong>proteomics<\/strong> and <strong>metabolomics<\/strong>.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>MSI<\/strong> is used to spatially map molecular species directly from a tissue surface. Techniques like <strong>MALDI-MSI<\/strong> and <strong>DESI-MSI<\/strong> ionize molecules layer by layer, helping to offer an unprecedented view of<strong><sup>39-40<\/sup><\/strong>:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Drug pharmacokinetics<\/strong> by tracing compound distribution in tissues<strong><sup>41<\/sup><\/strong>.<\/li>\n\n\n\n<li><strong>Tumor heterogeneity<\/strong> based on localized lipid and metabolite profiles<strong><sup>42<\/sup><\/strong>.<\/li>\n\n\n\n<li><strong>Biomarker mapping<\/strong> for fundamental disease research<strong><sup>43<\/sup><\/strong>.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">X-ray diffraction (XRD) and X-ray imaging<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>XRD<\/strong> is used to study the atomic structure of ordered materials, primarily <strong>crystallized proteins and nucleic acids<\/strong><strong><sup>44<\/sup><\/strong>. Analyzing the diffraction patterns allows scientists to determine the precise 3D arrangement of atoms, which is a foundational pillar of structural biology.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>X-ray imaging<\/strong> techniques are widely used in the clinic:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Computed tomography (CT)<\/strong> is used to generate 3D cross-sectional images by rotating an X-ray source and detectors around the patient<strong><sup>45<\/sup><\/strong>. This technique excels in high-contrast imaging of bone and dense structures.<\/li>\n\n\n\n<li><strong>X-ray Microscopy<\/strong> offers high-resolution imaging of cellular ultrastructure in thick, prepared samples<strong><sup>46<\/sup><\/strong>.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Challenges<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Despite their utility, these sophisticated methods face critical challenges:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Continuous innovation is paramount to improving spatial and temporal resolutions to capture ultrafast biological events at the nanoscale.<\/li>\n\n\n\n<li>Minimizing artifacts and maintaining the native, physiological state of the sample during preparation and measurement is difficult<strong><sup>47<\/sup><\/strong>.<\/li>\n\n\n\n<li>Generating massive, multi-dimensional datasets requires investment in specialized infrastructure and advanced computational tools, including <a href=\"https:\/\/www.najao.com\/learn\/artificial-intelligence-applications-in-healthcare\/\" target=\"_blank\" rel=\"noreferrer noopener\">artificial intelligence<\/a>, for effective interpretation and biomarker extraction<strong><sup>48<\/sup><\/strong>.<\/li>\n\n\n\n<li>High costs, specialized instrumentation, and training limit the broad deployment of many cutting-edge techniques in research and clinical settings<strong><sup>49<\/sup><\/strong>.<\/li>\n\n\n\n<li>Bridging insights from simplified <em>in vitro<\/em> or fixed samples to the complex, dynamic environment of a living organism (<em>in vivo<\/em>) remains a significant hurdle<strong><sup>50<\/sup><\/strong>.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Future directions: innovation and integration<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">The future of biological imaging and spectroscopy is focused on integration and intelligence:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Multimodal Imaging Platforms leverage the integration of complementary techniques (eg, PET-MRI, fluorescence-Raman) within a single system to maximize the information gathered about a biological system<strong><sup>51-52<\/sup><\/strong>.<\/li>\n\n\n\n<li>Artificial Intelligence and machine learning are crucial for automating complex image analysis, identifying subtle patterns invisible to the human eye, and optimizing experimental design<strong><sup>53<\/sup><\/strong>.<\/li>\n\n\n\n<li>There is a growing need for developing smaller, more robust, and lower-cost devices that can enable point-of-care diagnostics and be used for fieldwork applications<strong><sup>54<\/sup><\/strong>.<\/li>\n\n\n\n<li>Continuous development of non-linear optical methods is enabling the dynamic, native imaging of processes which allows us to do away with the perturbation caused by fluorescent markers<strong><sup>55<\/sup><\/strong>.<\/li>\n\n\n\n<li><a href=\"https:\/\/www.najao.com\/learn\/theranostics\/\" target=\"_blank\" rel=\"noreferrer noopener\">Theranostics<\/a> is no longer a buzzword as combining diagnostic imaging with targeted therapeutic delivery mechanisms helps us to create integrated systems for personalized treatment and simultaneous monitoring of patient responses<strong><sup>56<\/sup><\/strong>.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Conclusion<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Spectroscopy and imaging have fundamentally revolutionized life sciences by allowing us to observe and measure biological processes with molecular precision. This evolving technological landscape is driven by intelligent computation, and it continues to expand our understanding of disease mechanisms and physiological processes. They also serve as the essential enablers of <a href=\"https:\/\/www.najao.com\/learn\/precision-medicine\/\" target=\"_blank\" rel=\"noreferrer noopener\">precision medicine<\/a> and by doing so these methods promise to deliver increasingly clearer, richer, and more detailed insights into the complex fabric of life<strong><sup>57<\/sup><\/strong>.<\/p>\n\n\n\n<!--nextpage-->\n\n\n\n<h2 class=\"wp-block-heading\">FAQs<\/h2>\n\n\n\n<h4 class=\"wp-block-heading\">1. How is Mass spectrometry imaging (MSI) used in pharmaceutical development to track drug distribution?<\/h4>\n\n\n\n<p class=\"wp-block-paragraph\">MSI allows researchers to label-free map the precise spatial distribution and concentration of an administered drug and its various metabolites directly within a tissue section. This is vital for pharmacokinetics, as it reveals how a compound penetrates tumors, crosses the blood-brain barrier, or accumulates in organs.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">2. What is the fundamental difference in the information provided by FTIR and Raman spectroscopy in biological samples?<\/h4>\n\n\n\n<p class=\"wp-block-paragraph\">FTIR measures light absorption caused by changes in the molecule&#8217;s dipole moment (e.g., polar bonds like C=O, N-H). Raman measures inelastic scattering based on changes in molecular polarizability (e.g., non-polar C-C, C=C bonds). This makes Raman highly advantageous for aqueous samples as it is minimally sensitive to water, whereas water strongly absorbs in FTIR.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">3. How does Functional MRI (fMRI) use the BOLD contrast to map brain activity in cognitive neuroscience?<\/h4>\n\n\n\n<p class=\"wp-block-paragraph\">fMRI maps brain activity by detecting changes in blood oxygenation, known as the blood-oxygenation-level dependent (BOLD) contrast. When a brain region becomes active, blood flow to that area increases, delivering more oxygenated blood than the local neurons consume. Oxygenated and deoxygenated hemoglobin have different magnetic properties, which the MRI scanner detects to indirectly map the areas of increased neural activity.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Reference<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">1. Zahra, A., Qureshi, R., Sajjad, M., <em>et al<\/em>. (2024). Current advances in imaging spectroscopy and its state-of-the-art applications.&nbsp;<em>Expert Systems with Applications<\/em>,&nbsp;<em>238<\/em>, 122172.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">2. Ferr\u00e9, G., &amp; Eddy, M. T. (2020). 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A review of basic crystallography and x-ray diffraction applications.&nbsp;<em>The international journal of advanced manufacturing technology<\/em>,&nbsp;<em>105<\/em>(7), 3289-3302.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">7. Tiernan, H., Byrne, B., &amp; Kazarian, S. G. (2020). ATR-FTIR spectroscopy and spectroscopic imaging for the analysis of biopharmaceuticals.&nbsp;<em>Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy<\/em>,&nbsp;<em>241<\/em>, 118636.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">8. Krishna, R., &amp; Colak, I. (2023). Advances in biomedical applications of Raman microscopy and data processing: a mini review.&nbsp;<em>Analytical Letters<\/em>,&nbsp;<em>56<\/em>(4), 576-617.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">9. Van Velzen, M. J. M., Derks, S., Van Grieken, N. C. T., <em>et al<\/em>. (2020). 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Deep Learning\u2013Assisted Multiphoton Microscopy to Reduce Light Exposure and Expedite Imaging in Tissues With High and Low Light Sensitivity.&nbsp;<em>Translational Vision Science &amp; Technology<\/em>,&nbsp;<em>10<\/em>(12), 30.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">19. Codron, P., Letournel, F., Marty, S., <em>et al<\/em>. (2021). STochastic Optical Reconstruction Microscopy (STORM) reveals the nanoscale organization of pathological aggregates in human brain.&nbsp;<em>Neuropathology and applied neurobiology<\/em>,&nbsp;<em>47<\/em>(1), 127-142.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">20. Xie, L., Dong, P., Chen, X., <em>et al<\/em>. (2020). 3D ATAC-PALM: super-resolution imaging of the accessible genome.&nbsp;<em>Nature methods<\/em>,&nbsp;<em>17<\/em>(4), 430-436.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">21. Calovi, S., Soria, F. N., &amp; T\u00f8nnesen, J. (2021). Super-resolution STED microscopy in live brain tissue.&nbsp;<em>Neurobiology of Disease<\/em>,&nbsp;<em>156<\/em>, 105420.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">22. Zou, F., &amp; Bai, L. (2019). Using time-lapse fluorescence microscopy to study gene regulation.&nbsp;<em>Methods<\/em>,&nbsp;<em>159<\/em>, 138-145.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">23. Sekar, R. B., &amp; Periasamy, A. (2003). Fluorescence resonance energy transfer (FRET) microscopy imaging of live cell protein localizations.&nbsp;<em>The Journal of cell biology<\/em>,&nbsp;<em>160<\/em>(5), 629.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">24. Peled\u2010Zehavi, H., &amp; Gal, A. (2021). Exploring intracellular ion pools in coccolithophores using live\u2010cell imaging.&nbsp;<em>Advanced biology<\/em>,&nbsp;<em>5<\/em>(6), 2000296.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">25. Ozaki, Y. (2021). Infrared spectroscopy\u2014Mid-infrared, near-infrared, and far-infrared\/terahertz spectroscopy.&nbsp;<em>Analytical Sciences<\/em>,&nbsp;<em>37<\/em>(9), 1193-1212.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">26. Levin, I. W., &amp; Bhargava, R. (2005). Fourier transform infrared vibrational spectroscopic imaging: integrating microscopy and molecular recognition.&nbsp;<em>Annu. Rev. Phys. Chem.<\/em>,&nbsp;<em>56<\/em>(1), 429-474.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">27. Lewis, P. D., Lewis, K. E., Ghosal, R., <em>et al<\/em>. (2010). Evaluation of FTIR spectroscopy as a diagnostic tool for lung cancer using sputum.&nbsp;<em>BMC cancer<\/em>,&nbsp;<em>10<\/em>(1), 640.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">28. Krishna, R., &amp; Colak, I. (2023). Advances in biomedical applications of Raman microscopy and data processing: a mini review.&nbsp;<em>Analytical Letters<\/em>,&nbsp;<em>56<\/em>(4), 576-617.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">29. Antonio, K. A., &amp; Schultz, Z. D. (2014). Advances in biomedical Raman microscopy.&nbsp;<em>Analytical chemistry<\/em>,&nbsp;<em>86<\/em>(1), 30-46.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">30. Aaboubout, Y., Soares, M. R. N., Schut, T. C. B., <em>et al<\/em>. (2023). Intraoperative assessment of resection margins by Raman spectroscopy to guide oral cancer surgery.&nbsp;<em>Analyst<\/em>,&nbsp;<em>148<\/em>(17), 4116-4126.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">31. Ando, M., Sugiyama, K., Kubo, K., <em>et al<\/em>. (2023). Single-Cell Level Raman Molecular Profiling Reveals the Classification of Growth Phases of Chaetoceros tenuissimus.&nbsp;<em>The Journal of Physical Chemistry B<\/em>,&nbsp;<em>127<\/em>(22), 5027-5033.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">32. LaLone, V., Smith, D., Diaz-Espinosa, J., <em>et al<\/em>. (2023). Quantitative Raman Chemical Imaging of Intracellular Drug-Membrane Aggregates and Small Molecule Drug Precipitates In Cytoplasmic Organelles.&nbsp;<em>Advanced drug delivery reviews<\/em>,&nbsp;<em>202<\/em>, 115107.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">33. Schl\u00fccker, S. (2014). Surface\u2010enhanced Raman spectroscopy: concepts and chemical applications.&nbsp;<em>Angewandte Chemie International Edition<\/em>,&nbsp;<em>53<\/em>(19), 4756-4795.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">34. Marion, D. (2013). An introduction to biological NMR spectroscopy.&nbsp;<em>Molecular &amp; Cellular Proteomics<\/em>,&nbsp;<em>12<\/em>(11), 3006-3025.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">35. Logothetis, N. K. (2008). What we can do and what we cannot do with fMRI.&nbsp;<em>Nature<\/em>,&nbsp;<em>453<\/em>(7197), 869-878.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">36. Ranzenberger, L. R., Das, J. M., &amp; Snyder, T. (2023). Diffusion tensor imaging. In&nbsp;<em>StatPearls [Internet]<\/em>. StatPearls Publishing.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">37. Tognarelli, J. M., Dawood, M., Shariff, M. I., <em>et al<\/em>. (2015). Magnetic resonance spectroscopy: principles and techniques: lessons for clinicians.&nbsp;<em>Journal of clinical and experimental hepatology<\/em>,&nbsp;<em>5<\/em>(4), 320-328.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">38. Gross, J. H. (2006).&nbsp;<em>Mass spectrometry: a textbook<\/em>. Springer Science &amp; Business Media.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">39. Aichler, M., &amp; Walch, A. (2015). MALDI Imaging mass spectrometry: current frontiers and perspectives in pathology research and practice.&nbsp;<em>Laboratory investigation<\/em>,&nbsp;<em>95<\/em>(4), 422-431.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">40. Garza, K. Y., Feider, C. L., Klein, D. R., <em>et al<\/em>. (2018). Desorption electrospray ionization mass spectrometry imaging of proteins directly from biological tissue sections.&nbsp;<em>Analytical chemistry<\/em>,&nbsp;<em>90<\/em>(13), 7785-7789.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">41. Spruill, M. L., Maletic-Savatic, M., Martin, H., <em>et al<\/em>. (2022). Spatial analysis of drug absorption, distribution, metabolism, and toxicology using mass spectrometry imaging.&nbsp;<em>Biochemical pharmacology<\/em>,&nbsp;<em>201<\/em>, 115080.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">42. Duncan, K. D., P\u011btro\u0161ov\u00e1, H., Lum, J. J., <em>et al<\/em>. (2024). Mass spectrometry imaging methods for visualizing tumor heterogeneity.&nbsp;<em>Current opinion in biotechnology<\/em>,&nbsp;<em>86<\/em>, 103068.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">43. Scott, A. J., Jones, J. W., Orschell, C. M., <em>et al<\/em>. (2014). Mass Spectrometry Imaging Enriches Biomarker Discovery Approaches with Candidate Mapping.&nbsp;<em>Health physics<\/em>,&nbsp;<em>106<\/em>(1), 120.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">44. Bunaciu, A. A., Udri\u015eTioiu, E. G., &amp; Aboul-Enein, H. Y. (2015). X-ray diffraction: instrumentation and applications.&nbsp;<em>Critical reviews in analytical chemistry<\/em>,&nbsp;<em>45<\/em>(4), 289-299.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">45. Yasaka, K., Akai, H., Kunimatsu, A., <em>et al<\/em>. (2020). Prediction of bone mineral density from computed tomography: application of deep learning with a convolutional neural network.&nbsp;<em>European radiology<\/em>,&nbsp;<em>30<\/em>(6), 3549-3557.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">46. Duncan, K. E., Czymmek, K. J., Jiang, N., <em>et al<\/em>. (2021). X-ray microscopy enables multiscale high-resolution 3D imaging of plant cells, tissues, and organs.&nbsp;<em>Plant Physiology<\/em>,&nbsp;<em>188<\/em>(2), 831.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">47. Triche, B. L., Nelson Jr, J. T., McGill, N. S., <em>et al<\/em>. (2019). Recognizing and minimizing artifacts at CT, MRI, US, and molecular imaging.&nbsp;<em>RadioGraphics<\/em>,&nbsp;<em>39<\/em>(4), 1017-1018.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">48. Zhang, H., Zhang, J., Yuan, C., <em>et al<\/em>. (2024). Recent advances in mass spectrometry imaging combined with artificial intelligence for spatially clarifying molecular profiles: Toward biomedical applications.&nbsp;<em>TrAC Trends in Analytical Chemistry<\/em>,&nbsp;<em>178<\/em>, 117834.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">49. Saba, L., &amp; d\u2019Aloja, E. (2025). Predictive techniques in medical imaging: opportunities, limitations, and ethical-economic challenges.&nbsp;<em>npj Digital Medicine<\/em>,&nbsp;<em>8<\/em>(1), 392.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">50. Smith, R., Wright, K. L., &amp; Ashton, L. (2016). Raman spectroscopy: an evolving technique for live cell studies.&nbsp;<em>Analyst<\/em>,&nbsp;<em>141<\/em>(12), 3590-3600.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">51. Jung, J. H., Choi, Y., &amp; Im, K. C. (2016). PET\/MRI: technical challenges and recent advances.&nbsp;<em>Nuclear medicine and molecular imaging<\/em>,&nbsp;<em>50<\/em>(1), 3-12.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">52. Jeong, S., Kim, Y. I., Kang, H., <em>et al<\/em>. (2015). Fluorescence-Raman dual modal endoscopic system for multiplexed molecular diagnostics.&nbsp;<em>Scientific reports<\/em>,&nbsp;<em>5<\/em>(1), 9455.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">53. Liu, Y., Chen, S., Xiong, X., <em>et al<\/em>. (2025). Artificial intelligence guided Raman spectroscopy in biomedicine: Applications and prospects.&nbsp;<em>Journal of Pharmaceutical Analysis<\/em>, <em>15<\/em>(11), 101271.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">54. Frija, G., Salama, D. H., Kawooya, M. G., <em>et al<\/em>. (2023). A paradigm shift in point-of-care imaging in low-income and middle-income countries.&nbsp;<em>EClinicalMedicine<\/em>,&nbsp;<em>62<\/em>.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">55. Kang, D., Li, R., Cao, S., <em>et al<\/em>. (2021). Nonlinear optical microscopies: Physical principle and applications.&nbsp;<em>Applied Spectroscopy Reviews<\/em>,&nbsp;<em>56<\/em>(1), 52-66.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">56. Kelkar, S. S., &amp; Reineke, T. M. (2011). Theranostics: combining imaging and therapy.&nbsp;<em>Bioconjugate chemistry<\/em>,&nbsp;<em>22<\/em>(10), 1879-1903.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">57. Ghasemi, M., Nabipour, I., Omrani, A., <em>et al<\/em>. (2016). Precision medicine and molecular imaging: new targeted approaches toward cancer therapeutic and diagnosis.&nbsp;<em>American journal of nuclear medicine and molecular imaging<\/em>,&nbsp;<em>6<\/em>(6), 310.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Spectroscopy and imaging techniques unveil life&#8217;s complexity by studying electromagnetic radiation interactions with matter. 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