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Fluorescence imaging

Fluorescence imaging is a powerful optical technique that utilizes the phenomenon of fluorescence to visualize and analyze structures and processes at the molecular and cellular scales with high specificity and contrast. In this method, fluorophores—molecules capable of absorbing light at a specific excitation wavelength and re-emitting it at a longer emission wavelength (known as the Stokes shift)—are used to label targets of interest, allowing researchers to generate detailed images by detecting the emitted light while filtering out the excitation light.^[1] This approach enables the study of dynamic events in living cells, such as protein localization, ion transport, and cellular motility, far surpassing the capabilities of traditional bright-field microscopy.^[2] The core principles of fluorescence imaging rely on precise control of light interaction with fluorophores, typically involving a light source (such as lasers or LEDs), excitation and emission filters, dichroic mirrors to separate wavelengths, and detectors like cameras or photomultiplier tubes.^[2] Excitation occurs when a fluorophore absorbs a photon, elevating an electron to a higher energy state, followed by rapid relaxation and emission of a lower-energy photon, producing the characteristic glow.^[1] Resolution is fundamentally limited by diffraction to approximately 200 nm laterally and 500 nm axially in standard setups, though this can be enhanced through optical sectioning techniques that reduce out-of-focus light.^[3] Common fluorophores include genetically encoded proteins like green fluorescent protein (GFP) and synthetic dyes, chosen for their brightness, photostability, and minimal toxicity to enable live-cell imaging.^[3] Historical developments trace back to the early 20th century, but fluorescence imaging gained prominence in the 1970s with improved fluorophores and filters, evolving into wide-field epifluorescence microscopy as a foundational tool.^[1] Major advances in the 1980s introduced confocal microscopy, which uses a pinhole to achieve optical sectioning for three-dimensional imaging, while the 1990s saw the integration of GFP for genetic labeling.^[3] The 21st century brought super-resolution techniques, such as stimulated emission depletion (STED) achieving resolutions below 30 nm and two-photon excitation for deeper tissue penetration up to hundreds of micrometers, revolutionizing the field.^[1] These innovations, including total internal reflection fluorescence (TIRF) for surface imaging and light-sheet microscopy for rapid 3D volumes, have addressed limitations like photobleaching and shallow penetration depth.^[3] Applications of fluorescence imaging are diverse, spanning cell biology, neuroscience, biomedical research, materials and environmental science, industrial quality control, and forensic analysis, enabling real-time observation of processes like synaptic transmission, tumor metastasis, and organelle dynamics in both cultured cells and living organisms.^[1]^[4] In intravital imaging, it facilitates non-invasive studies in animal models, such as tracking immune responses or vascular changes, while in clinical contexts, it supports intraoperative guidance and disease diagnostics through targeted probes.^[3] Its versatility, combined with quantitative capabilities like fluorescence lifetime imaging (FLIM) for environmental sensing, underscores its indispensable role in advancing understanding of complex biological systems.^[2]

Fundamentals

Fluorescence mechanism

Fluorescence is the emission of light from a substance that has absorbed photons or other electromagnetic radiation, occurring after the substance is excited to a higher electronic energy state and subsequently relaxes to the ground state, typically with a delay on the order of nanoseconds. This process involves the absorption of light at a shorter wavelength (higher energy) and re-emission at a longer wavelength (lower energy), known as the Stokes shift, which arises from non-radiative relaxation processes that dissipate excess vibrational energy before emission. The phenomenon was first systematically described in 1852 by British physicist George Gabriel Stokes, who observed it in fluorspar and coined the term "fluorescence" in reference to the mineral's blue-white glow under ultraviolet excitation.^[5]^[6] The underlying quantum mechanical principles of fluorescence were developed in the 1920s, building on early quantum theory to explain electronic transitions in molecules, including the Franck-Condon principle that governs the vertical nature of absorption and emission due to nuclear motion constraints. These principles are illustrated by the Jablonski diagram, which depicts the energy levels of a molecule: the ground singlet state (S₀) with its vibrational sublevels, absorption to higher vibrational levels of the first excited singlet state (S₁), followed by rapid vibrational relaxation to the lowest S₁ level. From S₁, the molecule can return to S₀ via radiative fluorescence or non-radiative internal conversion (vibronic relaxation within the same spin multiplicity); alternatively, intersystem crossing to the triplet state (T₁) can occur, leading to delayed phosphorescence upon return to S₀, distinguishing fluorescence (fast, spin-allowed) from phosphorescence (slower, spin-forbidden).^[7] The efficiency of fluorescence is quantified by the quantum yield, Φ, defined as the ratio of the number of photons emitted to the number of photons absorbed:

\Phi = \frac{k_f}{k_f + k_{nr}}

where k_f is the rate constant for radiative decay and k_{nr} encompasses non-radiative processes. Quantum yield values range from 0 (no emission) to 1 (perfect efficiency), and it is influenced by environmental factors such as solvent polarity, pH, and quenching agents that enhance k_{nr}. Similarly, the fluorescence lifetime, τ, represents the average time a molecule spends in the excited state before emission, given by:

\tau = \frac{1}{k_f + k_{nr}}

Quenching, a key factor reducing both Φ and τ, includes collisional (dynamic) interactions with quenchers like oxygen or ions, and static quenching via complex formation, often described by the Stern-Volmer relation for dynamic cases.^[8]^[9]^[10] Fluorescence can be characterized in steady-state measurements, which provide average emission properties under continuous excitation, or time-resolved modes, which capture the temporal decay dynamics to reveal excited-state kinetics and environmental interactions.^[11]

Principles of fluorescence imaging

Fluorescence imaging exploits the excitation-emission process to generate contrast by selectively illuminating samples with monochromatic light sources, such as lasers or light-emitting diodes (LEDs), which match the absorption spectrum of target fluorophores, followed by the collection of emitted light at longer wavelengths using emission filters to isolate the signal from excitation light and background noise.^[12]^[4] This selective excitation ensures that only specific molecules are activated, while dichroic mirrors and bandpass filters further enhance signal specificity by reflecting excitation wavelengths and transmitting emission ones, enabling high-contrast visualization of labeled structures.^[13] Image formation in fluorescence imaging is fundamentally limited by diffraction, resulting in a point spread function (PSF) that blurs the emitted light from individual fluorophores into an Airy disk pattern, with the lateral resolution governed by the Abbe diffraction limit expressed as d = \frac{\lambda}{2 \mathrm{NA}}, where \lambda is the emission wavelength and NA is the numerical aperture of the objective lens.^[14]^[15] The PSF determines the minimum resolvable distance between points, typically around 200-300 nm for visible light, as overlapping diffraction patterns from adjacent emitters degrade spatial fidelity, though axial resolution is poorer due to the elongated PSF shape along the optical axis.^[16] Signal-to-noise ratio (SNR) is a critical factor in fluorescence imaging quality, influenced by the desired signal from specific fluorophore emission relative to noise sources such as autofluorescence from endogenous molecules like NADH or collagen, which can obscure weak signals and reduce contrast.^[1] Photobleaching, the irreversible loss of fluorescence due to repeated excitation cycles, further degrades SNR over time by diminishing the signal while background noise persists, necessitating strategies like pulsed illumination or antioxidants to mitigate these effects.^[17] Optimizing SNR often involves balancing excitation intensity to maximize photon collection without excessive bleaching or autofluorescence excitation.^[18] Detection in fluorescence imaging typically employs photomultiplier tubes (PMTs) for their high sensitivity and low noise in scanning systems, where they convert emitted photons into electrical currents via photoelectric effect and electron multiplication, or charge-coupled device (CCD) and complementary metal-oxide-semiconductor (CMOS) cameras for widefield imaging, which capture spatial intensity distributions across the entire field of view.^[1] Signal processing then maps these detections to intensity values, often using analog-to-digital conversion and software algorithms for background subtraction and deconvolution to reconstruct sharper images from the raw data.^[19] PMTs excel in real-time applications due to their single-photon sensitivity, while CCD/CMOS sensors provide higher dynamic range for quantitative mapping but may introduce read noise.^[20] Contrast in fluorescence imaging arises primarily from specific labeling, where exogenous fluorophores are conjugated to antibodies or other targeting agents to highlight particular biomolecules against a dark background, offering molecular specificity unattainable with endogenous fluorescence alone.^[21] In contrast, endogenous fluorescence, or autofluorescence from native chromophores like flavins or porphyrins, provides label-free contrast but suffers from lower specificity and intensity, often requiring spectral unmixing to separate it from labeled signals and improve overall image interpretability.^[22]

Fluorophores

Organic dyes

Organic dyes represent a cornerstone of fluorescence imaging as synthetic small-molecule fluorophores, prized for their customizable spectral properties spanning the visible to near-infrared range (400-900 nm) and straightforward chemical derivatization for targeted labeling.^[23] These carbon-based compounds enable high-resolution visualization in biological and material contexts through their strong absorption and emission characteristics.^[24] Key classes include xanthene dyes, such as fluorescein and rhodamine, which dominate visible-light applications with excitation/emission peaks typically between 400-600 nm. Fluorescein, for instance, absorbs maximally at 494 nm and emits at 518 nm, while rhodamine derivatives like rhodamine B feature excitation around 550 nm and emission near 575 nm, providing bright green-to-orange fluorescence.^[25]^[26] Cyanine dyes extend utility into the near-infrared, exemplified by Cy3 (excitation 550 nm, emission 570 nm) and Cy5 (excitation 650 nm, emission 670 nm), with longer polymethine chains shifting spectra up to 900 nm for deeper tissue penetration.^[27] Squaraine dyes further complement this palette, absorbing and emitting in the 600-800 nm range with narrow, intense bands ideal for multiplexing.^[28] Synthesis of organic dyes often employs condensation or cyclization reactions tailored to each class—for xanthene dyes, phthalic anhydride reacts with resorcinol derivatives—followed by activation for bioconjugation. Amine-reactive N-hydroxysuccinimide (NHS) esters are commonly appended to enable covalent attachment to proteins, antibodies, or nucleic acids via primary amine groups. The Alexa Fluor series exemplifies this approach, offering sulfonated variants with superior aqueous solubility, reduced pH sensitivity, and photostability over classical dyes like fluorescein.^[29]^[30] These dyes boast high fluorescence quantum yields, reaching up to 0.9 for optimized rhodamines and cyanines, facilitating sensitive detection even at low concentrations. However, they remain prone to photobleaching under prolonged illumination, where irreversible chemical degradation quenches emission. Certain variants, notably fluorescein, exhibit pH-dependent fluorescence, with quantum yield dropping below pH 7 due to protonation of the xanthene core.^[31]^[30]^[32] BODIPY (boron-dipyrromethene) dyes, initially synthesized in 1968 and refined through the 1980s, stand out for their rigid structure yielding sharp absorption/emission spectra (typically 500-600 nm, tunable to NIR), quantum yields near 1.0, minimal photobleaching, low cellular toxicity, and insensitivity to environmental factors like pH or solvents.^[33]^[34] In contrast to genetically encoded fluorescent proteins, organic dyes permit precise synthetic tuning and conjugation for diverse imaging probes.^[35]

Fluorescent proteins

Fluorescent proteins (FPs) are genetically encoded biomolecules that emit light upon excitation, enabling non-invasive visualization of cellular processes. The prototypical green fluorescent protein (GFP) was first isolated from the bioluminescent jellyfish Aequorea victoria in 1962 by Osamu Shimomura during purification of the calcium-activated photoprotein aequorin, revealing a protein with intrinsic green fluorescence independent of the jellyfish's bioluminescence system. The GFP gene was cloned in 1992 by Douglas Prasher, and its expression in non-jellyfish organisms was demonstrated in 1994 by Martin Chalfie, who fused it to β-galactosidase and myosin in Escherichia coli and Caenorhabditis elegans, respectively, to track protein localization. Commercialization began in the mid-1990s when Clontech Laboratories optimized and marketed enhanced GFP (eGFP) variants with improved folding and brightness for broader research use. The fluorescence arises from an autocatalytic chromophore formed post-translationally within the protein's β-barrel structure through cyclization, dehydration, and oxidation of residues Ser65-Tyr66-Gly67, requiring no external cofactors. To expand the spectral range beyond green emission (excitation ~488 nm, emission ~509 nm), researchers engineered variants via site-directed and random mutagenesis, tuning the chromophore environment to shift absorption and emission wavelengths. Cyan fluorescent protein (CFP), with excitation ~433 nm and emission ~475 nm, was developed by mutating Tyr66 to Trp (Y66W), while yellow fluorescent protein (YFP) (excitation ~514 nm, emission ~527 nm) incorporated the S65T mutation and additional substitutions like V68L and Q69M to stabilize the anionic chromophore form. Red fluorescent proteins (RFPs), such as mCherry (excitation ~587 nm, emission ~610 nm), were derived from far-red FPs like DsRed from Discosoma sp. through iterative mutagenesis to reduce oligomerization and enhance monomeric properties; mCherry, for instance, includes mutations like M1K and A69T for better solubility and folding. These variants form a color palette for multicolor imaging, with oligomeric tendencies (e.g., dimeric RFPs) addressed by engineering monomeric forms to minimize artifacts in protein fusions. In applications, FPs are fused to target proteins of interest via genetic encoding, allowing real-time tracking of dynamics in living cells without exogenous dyes; for example, GFP-histone fusions visualize chromatin movement during mitosis. Förster resonance energy transfer (FRET) pairs, such as CFP-YFP, enable detection of protein-protein interactions by monitoring energy transfer efficiency when donor-acceptor fusions are in close proximity (<10 nm), as demonstrated in early cameleon sensors for calcium signaling. Advances in protein engineering, particularly directed evolution, have yielded brighter and more photostable FPs by screening libraries for enhanced quantum yield and resistance to photobleaching; superfolder GFP (sfGFP), evolved from wild-type GFP, folds more efficiently at 37°C and exhibits 2.5-fold higher brightness. For super-resolution microscopy, reversibly switchable variants like rsEGFP were developed through mutagenesis of EGFP, enabling on-off photoswitching with 405 nm activation and 488 nm readout, facilitating techniques such as RESOLFT with resolutions below 50 nm in living cells.

Inorganic fluorophores

Inorganic fluorophores, particularly those based on nanoparticles, provide enhanced optical and physical properties for fluorescence imaging, including superior photostability and size-dependent tunability that surpass many organic alternatives.^[36] These materials, often semiconductor or lanthanide-doped nanocrystals, enable brighter and more persistent signals, making them ideal for long-term or high-intensity imaging applications where bleaching is a concern.^[37] Quantum dots (QDs), such as CdSe/ZnS core-shell semiconductor nanocrystals, represent a primary class of inorganic fluorophores, with particle sizes typically ranging from 2 to 10 nm that allow tunable emission wavelengths from visible to near-infrared through quantum confinement effects.^[38] This size-dependent property arises from the inverse relationship between nanocrystal diameter and bandgap energy, enabling precise control over emission color without changing the excitation source.^[39] Another key type is upconverting nanoparticles (UCNPs), exemplified by NaYF4 doped with Yb and Er ions, which convert near-infrared (NIR) excitation into higher-energy visible or NIR emissions via sequential photon absorption.^[40] These UCNPs facilitate deeper tissue penetration due to reduced autofluorescence and scattering in the NIR range.^[41] Key properties of inorganic fluorophores include high photostability, allowing sustained imaging under intense illumination without significant signal loss, broad absorption spectra for efficient excitation across wavelengths, and narrow emission bands (full width at half maximum ~20-40 nm) for high spectral resolution.^[42] Quantum yields can reach up to 90% in optimized core-shell QDs like CdSe/ZnS, enhancing signal-to-noise ratios in imaging.^[43] However, QDs often exhibit fluorescence blinking—intermittent on-off emission—due to charge trapping at surface defects, which can be mitigated through shell passivation, alloying, or post-synthetic treatments like ligand exchange to stabilize the excited state.^[44] UCNPs, in contrast, show minimal blinking and high resistance to photobleaching owing to their ladder-like energy levels.^[45] Synthesis of these fluorophores typically employs colloidal methods to achieve uniform size and shape control. For QDs, the hot-injection technique involves rapid injection of organometallic precursors (e.g., cadmium and selenium sources) into a heated solvent like octadecene with surfactants, promoting burst nucleation followed by controlled growth at temperatures around 200-300°C.^[46] UCNPs are similarly synthesized via thermal decomposition or co-precipitation of rare-earth salts in high-boiling solvents, often with oleic acid as a capping agent.^[47] To improve biocompatibility and reduce toxicity from heavy metals in QDs, surface passivation with inert shells (e.g., ZnS) or biocompatible ligands like polyethylene glycol (PEG) is essential, minimizing leaching and enabling aqueous dispersion for biological use.^[48] These modifications have supported the limited translation of certain QD probes into early-phase clinical trials for imaging applications, such as tumor detection, with a phase I trial initiated in 2019.^[49] In multiplexing scenarios, inorganic fluorophores like QDs complement organic dyes by providing non-overlapping emission spectra for simultaneous tracking of multiple targets.^[36]

Imaging Systems and Techniques

Conventional fluorescence microscopy

Conventional fluorescence microscopy, also known as widefield or epifluorescence microscopy, represents the foundational approach to visualizing fluorescently labeled specimens, originating with Albert Coons' development of immunofluorescence in 1941 to detect antigens in tissue sections.^[50] This technique illuminates the entire field of view with excitation light, capturing emitted fluorescence from the sample plane while much of the signal arises from out-of-focus regions above and below.^[51] The core setup includes a broadband light source such as mercury or xenon arc lamps, or more modern high-power LEDs, to provide excitation wavelengths matching the fluorophores used.^[52] Illumination passes through an excitation filter to select the appropriate wavelength band, reflects off a dichroic mirror to direct light onto the sample via the objective lens, and the resulting emission light passes through an emission filter to the detector, typically a camera.^[53] Objective lenses with high numerical aperture (NA > 1.0), often oil-immersion types reaching NA 1.4, are essential for maximizing light collection and resolution.^[1] Key techniques involve Köhler illumination to ensure even, artifact-free lighting by focusing the light source image into the condenser aperture plane, optimizing contrast and uniformity across the field.^[54] Sample preparation varies between fixed cells, preserved with agents like paraformaldehyde to maintain structure for static imaging, and live cells, which require vital dyes or fluorescent proteins compatible with physiological conditions to observe dynamics without phototoxicity.^[55] Multi-channel imaging enables simultaneous excitation and detection of multiple fluorophores, facilitating colocalization studies by overlaying signals from different wavelengths to identify spatial overlaps in molecular distributions.^[56] Resolution in conventional fluorescence microscopy is diffraction-limited, achieving approximately 200 nm laterally and 500 nm axially for typical visible wavelengths and high-NA objectives, though out-of-focus light from the specimen volume significantly degrades contrast and effective depth, limiting clear imaging to thin samples or surface layers.^[57] Fluorophore selection must consider excitation/emission spectra aligned with the filter sets to minimize crosstalk in multi-channel setups.^[13]

Advanced microscopy modalities

Confocal microscopy enhances fluorescence imaging by employing laser scanning to illuminate a single point on the sample at a time, with a pinhole aperture in the detection path rejecting out-of-focus light to achieve optical sectioning.^[51] This point-scanning approach, typically using galvanometer mirrors to direct the laser beam, enables the collection of high-contrast images from specific focal planes within thick specimens, minimizing the blur inherent in widefield techniques.^[51] By acquiring a series of optical sections at incremental depths—known as a z-stack—three-dimensional reconstructions can be generated, providing volumetric data for analysis.^[51] The axial resolution in confocal systems is approximately 0.5–0.6 μm, determined by factors such as wavelength, numerical aperture, and pinhole size, offering improved depth discrimination compared to conventional methods.^[51] Multiphoton excitation, particularly two-photon microscopy, extends these capabilities through nonlinear optical processes, where fluorophores are excited by the simultaneous absorption of two infrared photons from femtosecond-pulsed lasers.^[58] This quadratic intensity dependence confines excitation to the focal volume, inherently providing optical sectioning without a pinhole and reducing photodamage by limiting out-of-focus illumination and bleaching.^[58] The use of near-infrared light allows deeper tissue penetration, up to 1 mm, due to lower scattering and absorption in biological samples, making it ideal for in vivo imaging of living organisms.^[59] Variants of these techniques address specific needs, such as speed and scale. Spinning disk confocal microscopy employs a rotating Nipkow disk with thousands of pinholes to illuminate and detect multiple points simultaneously, enabling faster image acquisition suitable for dynamic processes like live-cell imaging.^[51] Light-sheet microscopy, on the other hand, illuminates the sample with a thin plane of light orthogonal to the detection axis, facilitating rapid volumetric imaging of large, cleared, or live specimens with minimal phototoxicity.^[60] Quantitative analysis in these modalities requires careful intensity calibration to account for variations in illumination, detector sensitivity, and sample properties, often using standardized fluorescent beads or dyes to convert pixel values to absolute units.^[61] Software tools, such as ImageJ plugins including the 3D ImageJ Suite, support z-stack processing, 3D rendering, and volume quantification, allowing researchers to visualize and measure fluorescence distributions in reconstructed datasets.^[62]

Specialized imaging methods

Specialized imaging methods in fluorescence microscopy extend beyond conventional diffraction-limited techniques to achieve higher resolutions, temporal insights, or applicability in challenging environments. These approaches leverage advanced optical principles to overcome limitations in spatial, temporal, or scale domains, enabling detailed visualization in biological and materials contexts. Super-resolution techniques break the diffraction barrier, typically around 200-250 nm for visible light, to image structures at the nanoscale. Stimulated emission depletion (STED) microscopy achieves this by using a doughnut-shaped depletion beam that suppresses fluorescence emission in the periphery of the excitation spot, confining emission to a central region smaller than the diffraction limit. This results in lateral resolutions below 50 nm, depending on depletion beam intensity and fluorophore properties.^[63]^[64] The method was pioneered by Stefan Hell and colleagues, with the foundational concept introduced in 1994.^[63] Another class of super-resolution methods, localization microscopy such as photoactivated localization microscopy (PALM) and stochastic optical reconstruction microscopy (STORM), relies on the precise localization of individual fluorophores that are stochastically activated and imaged in sparse subsets over multiple frames. These techniques use photoswitchable or blinking dyes to ensure only a small number of molecules emit at a time, allowing their positions to be fitted with sub-pixel accuracy and reconstructed into a high-resolution image. PALM and STORM routinely achieve resolutions around 20 nm by accumulating thousands of frames. Developed independently by Eric Betzig's group for PALM in 2006 and Xiaowei Zhuang's for STORM in the same year, these methods built on earlier single-molecule localization work by William Moerner. The groundbreaking contributions of Betzig, Hell, and Moerner to super-resolution fluorescence microscopy were recognized with the 2014 Nobel Prize in Chemistry. Time-domain methods, such as fluorescence lifetime imaging microscopy (FLIM), provide functional information by measuring the time delay between excitation and emission for each fluorophore, rather than intensity or wavelength alone. This lifetime, typically in the nanosecond range, is sensitive to the local microenvironment, including pH, ion concentration, and molecular interactions. FLIM is particularly valuable for Förster resonance energy transfer (FRET)-based sensing, where energy transfer between donor and acceptor fluorophores shortens the donor's lifetime, enabling quantification of protein-protein interactions or conformational changes at the molecular scale. Detection in FLIM employs either frequency-domain phase modulation, which analyzes phase shifts in modulated excitation light, or time-domain photon-counting techniques like time-correlated single-photon counting (TCSPC), which records arrival times of individual photons for exponential decay fitting.^[65]^[66] At the macro-scale, fluorescence imaging adapts to in vivo and endoscopic applications through miniaturized systems like fiber-optic probes, which deliver excitation light and collect emission signals from internal tissues or small animal models. These probes, often with diameters under 1 mm, enable real-time visualization in confined spaces such as the gastrointestinal tract or brain, supporting longitudinal studies in rodents without invasive surgery. For instance, fiber-optic bundles integrated with scanning mechanisms allow cellular-resolution imaging in deep tissues, facilitating the tracking of fluorescently labeled cells or probes in living subjects.^[67]^[68]

Applications

Biomedical imaging

Fluorescence imaging plays a pivotal role in cellular imaging, enabling the visualization and tracking of specific organelles and proteins within living cells. For instance, MitoTracker dyes are widely used to label and track mitochondria by accumulating in active organelles based on their membrane potential, allowing researchers to monitor mitochondrial dynamics, such as fission and fusion events, in real-time. This approach has been instrumental in studying mitochondrial function in cellular homeostasis and disease states, including neurodegeneration and cancer. Similarly, green fluorescent protein (GFP) fusions have revolutionized the observation of protein dynamics; by genetically fusing GFP to target proteins, scientists can track their localization, interactions, and movements in vivo without disrupting cellular processes. The seminal development of GFP as a fusion tag by Chalfie and colleagues in 1994 enabled non-invasive imaging of protein expression and trafficking, forming the basis for countless studies on cellular signaling and cytoskeletal rearrangements. In tissue and whole-organism imaging, fluorescence techniques facilitate intravital observations that reveal dynamic biological processes in their native context. In model organisms like zebrafish, which offer optical transparency, fluorescence imaging allows long-term tracking of cellular behaviors, such as metastasis in adult casper mutants, where fluorescently labeled tumor cells can be monitored non-invasively to study invasion and immune interactions. In mice, intravital fluorescence microscopy through imaging windows enables the visualization of tumor microenvironments, including vascularization and immune cell infiltration, providing insights into tumor progression and therapeutic responses. These methods extend to clinical settings for tumor margin detection during surgery, where fluorescence-guided resection highlights residual cancer cells, improving the precision of excisions and reducing recurrence risks. Clinical applications of fluorescence imaging span diagnostics and therapeutics, particularly in oncology and immunology. Endoscopic fluorescence using 5-aminolevulinic acid (5-ALA) induces protoporphyrin IX (PpIX) accumulation in cancer cells, enabling the detection of early lesions in the oral cavity and gastrointestinal tract with high specificity through red fluorescence emission under blue light excitation. This technique aids in identifying dysplastic tissues during endoscopy, guiding biopsies and minimizing unnecessary interventions. In flow cytometry, fluorescence-activated cell sorting (FACS) leverages multiple fluorescent markers to analyze and isolate cell populations based on surface or intracellular features, supporting applications like immunophenotyping and stem cell purification in clinical research. A notable advancement is the FDA approval of Gleolan (5-ALA hydrochloride) in 2017 as an optical imaging agent for fluorescence-guided surgery in high-grade gliomas, where it enhances intraoperative visualization of malignant tissue, leading to more complete resections and improved patient outcomes.

Materials and environmental science

In materials science, photoluminescence (PL) microscopy serves as a key tool for defect mapping in semiconductors, where spatial variations in emission intensity highlight crystal imperfections such as dislocations and impurities that affect electronic properties. High-resolution room-temperature PL mapping has revealed defect distributions like slip lines across entire silicon and silicon-germanium wafers, enabling non-destructive quality assessment during fabrication.^[69] Cathodoluminescence, a related electron-beam-induced technique, complements PL by providing nanoscale resolution for analyzing defects in advanced structures like microLEDs, identifying issues such as handling-induced damage in quantum well layers and electrical shorts with contrast ratios up to 7:1.^[70] Fluorescence microscopy facilitates the study of phase separation in polymer systems by labeling components with fluorophores to track morphological evolution in real time. In operando imaging during dicyclopentadiene polymerization, for example, has shown the formation of spherical polydicyclopentadiene aggregates that coalesce into dumbbell shapes through physical aggregation rather than continuous growth, with these early structures persisting in the final bulk material.^[71] Such visualizations aid in optimizing blend compositions for applications in coatings and adhesives. For nanoparticle-reinforced composites, cross-sectional fluorescence imaging quantifies distribution homogeneity, revealing surface-enriched loading of CdSe/ZnS quantum dots in polydimethylsiloxane matrices after swell encapsulation, with penetration depths reaching 163 μm and surface concentrations maximized after 48 hours of exposure.^[72] This approach informs the design of functional materials, such as antimicrobial polymers, by correlating nanoparticle placement with performance metrics. In environmental monitoring, fluorescence spectroscopy detects polycyclic aromatic hydrocarbon (PAH) pollutants in water, leveraging their native aromatic emissions for sensitive analysis without extensive preconcentration. Three-way excitation-emission fluorescence matrices combined with second-order calibration methods like unfolded partial least squares/residual bilinearization have quantified PAHs such as phenanthrene, pyrene, and anthracene at μg L⁻¹ levels in river and reservoir samples, achieving relative prediction errors below 6% for most analytes.^[73] Solar-induced chlorophyll fluorescence retrieved from satellite remote sensing tracks algal blooms by measuring red-wavelength emissions from phytoplankton, offering broad-scale, diurnal monitoring of bloom intensity and extent. Analysis of TROPOspheric Monitoring Instrument data has demonstrated this technique's efficacy in distinguishing harmful blooms, correlating fluorescence signals with chlorophyll-a concentrations to support early warning systems for coastal ecosystems.^[74] Hyperspectral fluorescence imaging adapts conventional systems for mineral identification in geological samples by resolving narrow emission bands unique to mineral compositions, enabling automated classification of ores like fluorite and scheelite under UV excitation. This method processes spatial-spectral data to differentiate minerals based on peak wavelengths and intensities, improving efficiency in mining exploration compared to reflectance-based hyperspectral approaches. Fiber-optic fluorescence sensors provide in-situ profiling of soil contaminants by transmitting UV excitation light through probes inserted into the subsurface and collecting emitted spectra from aromatic compounds. These systems, often integrated with cone penetrometers, achieve rapid screening of hydrocarbons at depths up to 50 m, with response times under 1 second for metals via fluorogenic indicators and real-time spectral resolution for organics.^[75] During the 2020s, Nile Red staining has advanced microplastic tracking by selectively binding to polymer surfaces, inducing bright fluorescence observable under epifluorescence microscopy. Optimized protocols using 25% (v/v) acetone/water as a carrier solvent have standardized staining across polymers like polyethylene and polystyrene, minimizing degradation.^[76]

Industrial and forensic uses

In industrial applications, fluorescence imaging plays a key role in leak detection for pipelines, particularly in subsea environments, where fluorescent dyes are introduced into the system and imaged under ultraviolet light to identify escape points with high sensitivity and spatial resolution.^[77] This method leverages the high visibility of fluorophores, such as those based on organic dyes, to enable rapid scanning via remotely operated vehicles (ROVs), minimizing downtime and environmental risks in oil and gas infrastructure.^[77] Fluorescence imaging also supports quality assurance in pharmaceutical manufacturing by assessing active pharmaceutical ingredient (API) uniformity in blends and tablets. Techniques like second-order nonlinear imaging of chiral crystals (SONICC) and multi-photon fluorescence selectively detect APIs amid excipients, providing non-destructive, high-throughput analysis to ensure content uniformity without sample preparation.^[78] In electronics production, high-throughput machine vision systems employ fluorescence to inspect defects, such as microcracks or contaminants on circuit boards, by exciting materials that fluoresce under specific wavelengths, enhancing contrast for automated detection and improving yield rates. In forensic investigations, fluorescence imaging enhances the visualization of latent fingerprints, where methods like ninhydrin treatment or cyanoacrylate fuming produce fluorescent residues that are captured under alternate light sources to reveal ridge details on non-porous surfaces.^[79] For bloodstain pattern analysis, fluorescence spectroscopy detects trace blood residues by exploiting the natural autofluorescence of hemoglobin or enhanced signals from dyes, aiding in reconstructing crime scenes through pattern distribution and age estimation.^[80]

Advantages and Limitations

Advantages

Fluorescence imaging achieves high specificity through the use of fluorophore conjugates that target specific biomolecules, such as antibodies or ligands bound to fluorescent dyes, enabling precise visualization of molecular structures and interactions within complex biological samples.^[81] This targeted labeling minimizes background noise from unlabeled regions, providing clear contrast that distinguishes the fluorophore signals from the surrounding environment.^[2] A key advantage is its capacity for multiplexed imaging, where multiple fluorophores with distinct excitation and emission spectra allow simultaneous labeling and detection of different targets in the same sample, supporting up to 4 or 5 colors in conventional setups and more with advanced spectral separation techniques.^[82] For instance, multichannel fluorescence microscopy leverages spectral separation to study co-localization of proteins or cellular compartments without cross-talk, enhancing the understanding of multifaceted biological processes.^[83] The technique excels in sensitivity, routinely achieving single-molecule detection levels, which permits the observation of rare events and low-concentration analytes that are undetectable by many other imaging modalities.^[84] This high sensitivity supports real-time imaging of dynamic processes, such as protein trafficking or cellular signaling, in live samples with minimal disruption to physiological conditions.^[85] Fluorescence imaging is highly versatile, offering non-invasive monitoring of live cells and tissues over extended periods, which preserves natural behaviors and functions during observation.^[85] It seamlessly integrates with genetic engineering approaches, including CRISPR/Cas9-mediated knock-in of fluorescent proteins like GFP for endogenous labeling of specific genes or proteins.^[86] Basic wide-field fluorescence setups are also relatively low-cost and straightforward to implement, broadening accessibility for research in diverse settings.^[2] In terms of quantitative potential, ratiometric fluorescence imaging provides robust measurement of analyte concentrations by calculating the ratio of dual-wavelength emissions from pH- or ion-sensitive probes, effectively correcting for artifacts like uneven illumination or dye variability.^[87] This approach enables accurate spatial mapping of physiological parameters, such as intracellular pH or calcium levels, with high reliability in live-cell contexts.^[88]

Limitations

One major limitation of fluorescence imaging is photobleaching, the irreversible photochemical destruction of fluorophores under excitation light, which progressively diminishes signal intensity and restricts observation times, particularly in live-cell applications. This process is primarily driven by the generation of reactive oxygen species (ROS) during repeated photon absorption, leading to covalent modifications or decomposition of the dye molecules. Phototoxicity, a related issue, occurs when these ROS cause oxidative damage to biological samples, including lipid peroxidation, protein denaturation, and DNA strand breaks, potentially inducing cell death or altering physiological processes. For instance, in super-resolution microscopy, high light doses exacerbate phototoxicity, limiting viable imaging durations to minutes in sensitive live samples. While antioxidants such as ascorbic acid can partially mitigate ROS-induced damage by scavenging free radicals, they do not fully eliminate the inherent trade-offs between imaging duration and sample integrity.^[89]^[90]^[91] Another key constraint is the limited penetration depth in scattering media like biological tissues, where visible light (typically 400–700 nm) is attenuated to less than 1 mm due to elastic scattering by cellular components and absorption by chromophores such as hemoglobin. This shallow depth confines high-resolution fluorescence imaging to superficial or thin samples, making it challenging to visualize structures in thicker tissues without additional clearing or sectioning. Autofluorescence from endogenous molecules, including flavins and porphyrins, compounds this issue by producing background signals that overlap with exogenous fluorophore emissions, reducing contrast and signal-to-noise ratios in deeper or heterogeneous samples.^[92]^[93]^[94] Spectral overlap poses significant challenges in multiplexed fluorescence imaging, where the broad emission spectra of commonly used fluorophores result in crosstalk, with signals from one channel bleeding into adjacent detection bands and complicating accurate separation of multiple targets. This overlap arises because most organic dyes and fluorescent proteins have full-width at half-maximum emission bandwidths exceeding 50 nm, limiting the number of resolvable colors to 4–5 in standard setups without advanced unmixing. Careful design of excitation and emission filters, along with computational spectral decomposition, is essential to minimize this interference, though it often introduces errors in low-abundance target quantification.^[81]^[95] Quantitative analysis in fluorescence imaging is hindered by non-uniform illumination across the imaging field, which creates intensity gradients that bias measurements of fluorophore concentration or binding events, often requiring post-acquisition corrections or specialized calibration standards like fluorescent beads. Variations in light distribution stem from optical system aberrations and sample-induced shading, leading to up to 20–50% intensity discrepancies in widefield setups without compensation. Furthermore, fluorophore quenching, environmental pH sensitivity, and incomplete labeling efficiency add variability, necessitating rigorous controls to ensure reproducibility, though these steps can increase experimental complexity and time.^[96]00102-4)^[97]

Advances and Future Directions

Recent technological developments

In the past decade, significant hardware innovations have enhanced fluorescence imaging by addressing optical aberrations and enabling minimally invasive deep-tissue access. Adaptive optics (AO) systems, initially developed for astronomical applications, have been integrated into fluorescence microscopy to correct wavefront distortions caused by biological tissues, thereby improving resolution and signal quality in deep imaging scenarios. For instance, sensorless AO techniques combined with confocal microscopy have achieved aberration correction in scattering tissues up to several millimeters deep, facilitating clearer visualization of subcellular structures in vivo.^[98] Complementing these, miniaturized endoscopes utilizing gradient-index (GRIN) lenses have revolutionized portable fluorescence imaging, allowing high-resolution observation in freely moving subjects such as rodents. GRIN-based microendoscopes, with diameters as small as 350 micrometers, support two-photon excitation for reduced phototoxicity and deeper penetration, enabling real-time imaging of neural activity in the brain without surgical disruption.^[99] Recent advancements in aberration-corrected GRIN endoscopes have further expanded field-of-view capabilities while maintaining sub-micron resolution, as demonstrated in studies of cortical circuits.^[100] Software developments, particularly those leveraging artificial intelligence (AI), have transformed post-acquisition processing in fluorescence imaging by mitigating noise and enhancing resolution without additional hardware. Deep learning algorithms for denoising have substantially improved signal-to-noise ratios in low-light conditions, with self-supervised methods achieving significant SNR enhancements, such as up to 17 dB, in live-cell fluorescence time-lapses.^[101] For super-resolution enhancement, single-frame deep learning methods, such as those employing edge-map guidance and multicomponent loss functions, have enabled isotropic resolutions below 100 nanometers from conventional diffraction-limited images, outperforming traditional deconvolution techniques in speed and artifact suppression.^[102] Automated analysis pipelines have also proliferated, streamlining workflows for high-content screening; for example, deep learning-based tools for cyclic immunofluorescence data processing automatically segment and quantify cellular features across thousands of images, reducing manual intervention by over 90% while preserving quantitative accuracy.^[103] Advancements in fluorophore chemistry have extended the spectral range and labeling efficiency of fluorescence probes, optimizing them for deeper tissue penetration and rapid bioorthogonal conjugation. Near-infrared II (NIR-II) dyes, emitting in the 1000-1700 nm window, exploit reduced tissue scattering and autofluorescence to achieve penetration depths of several centimeters, far surpassing visible or NIR-I fluorophores, with quantum yields exceeding 10% in aqueous environments.^[104] These dyes, often based on aggregation-induced emission scaffolds, have enabled high-contrast in vivo imaging of vascular dynamics and tumors. Clickable probes, utilizing bioorthogonal click chemistry such as strain-promoted azide-alkyne cycloaddition, facilitate superfast labeling of biomolecules in living systems, with second-order rate constants up to several M^{-1} s^{-1} for site-specific attachment of fluorophores to genetically encoded unnatural amino acids.^[105] A landmark technique in sample preparation, expansion microscopy introduced in 2015, physically enlarges fixed specimens by embedding them in swellable hydrogels, effectively boosting resolution by 4- to 10-fold on standard microscopes without optical modifications. This method anchors biomolecules to the gel matrix before isotropic expansion, transforming nanometer-scale features into micrometer separations for conventional fluorescence detection, and has been widely adopted for multicolor imaging of organelles and synapses.^[106]

Emerging trends and challenges

One prominent emerging trend in fluorescence imaging involves the development of CRISPR-fluorophore hybrids, which enable precise visualization of genome editing processes in live cells. These hybrids combine CRISPR-Cas systems with advanced fluorophores to track dynamic genomic events, such as single-nucleotide variations and nonrepetitive loci, offering higher resolution than traditional methods.^[107] Recent advancements have integrated novel CRISPR RNA designs and Cas protein variants with bright, photostable fluorophores, facilitating real-time monitoring of editing efficiency and off-target effects in mammalian cells.^[108] This approach holds potential for therapeutic applications, including in vivo gene therapy tracking, by providing multiplexed imaging without disrupting cellular processes. Another key trend is the rise of hybrid optoacoustic-fluorescence systems for multimodal imaging, which merge optical excitation with ultrasonic detection to overcome depth limitations in tissue penetration. These systems simultaneously capture fluorescence signals for molecular specificity and optoacoustic waves for structural and vascular details, achieving sub-millimeter resolution up to several centimeters deep in vivo.^[109] For instance, integrated platforms using near-infrared fluorophores have demonstrated concurrent imaging of calcium dynamics and blood flow in animal models, enhancing diagnostic accuracy in oncology and neurology.^[110] Such hybrids reduce artifacts from light scattering and autofluorescence, paving the way for clinical tools in real-time surgical guidance.^[111] Artificial intelligence (AI) integration is transforming fluorescence imaging through real-time 3D reconstruction and predictive modeling of photodynamics. AI algorithms, particularly deep learning networks, automate the segmentation and reconstruction of volumetric data from fluorescence microscopy stacks, enabling high-speed 3D visualization of cellular structures with reduced computational overhead.^[112] In clinical settings, AI-assisted fluorescence imaging has improved retinal pigment epithelial layer delineation, achieving sub-micron accuracy in live human eyes.^[113] For photodynamics, machine learning models predict fluorophore behavior, such as energy transfer and bleaching rates, by analyzing time-resolved fluorescence lifetime data to optimize probe selection and imaging protocols.^[114] These predictive tools simulate light-tissue interactions, minimizing experimental iterations in photodynamic therapy design.^[115] A notable 2024 breakthrough in bioluminescent probes has further advanced self-illuminating imaging by engineering de novo luciferases that eliminate the need for external excitation light, thereby reducing phototoxicity and background noise in deep-tissue applications. These probes, derived from synthetic biology, emit tunable bioluminescence across visible wavelengths, enabling multiplexed tracking of cellular events without optical interference.^[116] This innovation complements fluorescence techniques by hybridizing with existing fluorophores for enhanced signal stability in long-term studies.^[117] Despite these advances, significant challenges persist, particularly regarding the biocompatibility of new nanomaterials used in fluorescence probes. Quantum dots and carbon-based nanoparticles, while offering superior brightness and stability, often exhibit cytotoxicity due to heavy metal leaching or oxidative stress in vivo, limiting their safe deployment in human trials.^[118] Efforts to encapsulate these materials in biocompatible polymers have improved clearance rates, but long-term accumulation in organs remains a concern, necessitating rigorous toxicity assessments. Ethical issues in clinical translation of fluorescence imaging technologies also pose hurdles, including concerns over data privacy in AI-driven analyses and equitable access to advanced imaging in underserved regions. Algorithmic biases in training datasets can lead to disparities in diagnostic accuracy across demographics, raising questions about informed consent and regulatory oversight for AI-integrated devices.^[119] Moreover, the off-label use of experimental probes in precision surgery amplifies risks of unintended biodistribution, demanding robust ethical frameworks to balance innovation with patient safety.^[120] Standardization for reproducibility represents another critical challenge, as variations in excitation parameters, fluorophore calibration, and imaging hardware hinder cross-laboratory comparisons. Without unified protocols for fluorescence lifetime measurements or signal quantification, results from high-throughput screens often suffer from inconsistencies, impeding meta-analyses and clinical validation.^[121] Community-driven guidelines, such as those for reporting metadata in microscopy datasets, are emerging to address this, but adoption remains uneven due to proprietary equipment differences.^[122]

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Deep learning pipeline for automated cell profiling from cyclic imaging
Oct 9, 2024 · In this paper, we present CycloNET, a computational pipeline tailored for analyzing raw fluorescent images obtained through cyclic immunofluorescence.
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Recent Advances in Second Near-Infrared Region (NIR-II ... - Frontiers
The NIR-II fluorescence imaging significantly overcomes the strong tissue absorption, auto-fluorescence as well as photon scattering, and has deep tissue ...
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Site-specific protein labeling strategies for super-resolution ...
Bioorthogonal click reactions are crucial for conjugating fluorescent probes to UAAs [48]. These reactions are characterized by their fast kinetics and ...Missing: superfast | Show results with:superfast<|separator|>
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Expansion microscopy | Science
We discovered that by synthesizing a swellable polymer network within a specimen, it can be physically expanded, resulting in physical magnification.
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Live genome imaging by CRISPR engineering: progress ... - Nature
Jul 31, 2025 · Recent advancements in the design of CRISPR RNAs and Cas proteins, the development of novel fluorophores and the combination of CRISPR–Cas with ...
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Unveiling the invisible genomic dynamics - PMC - NIH
Jul 31, 2025 · Recent advances for CRISPR-based fixed-cell imaging have aimed to enhance genomic resolution, including the visualization of nonrepetitive ...
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https://www.sciencedirect.com/science/article/pii/S2213597924000880
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Multimodal fluorescence-optoacoustic in vivo imaging of the near ...
We finally demonstrate fully hybrid (concurrent) fluorescence and FONT in vivo imaging of NIR-GECO2G, setting the stage for further advances and applications of ...
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The need for optoacoustic microscopy | Rev. Mod. Phys.
Mar 4, 2025 · Hybrid optoacoustic implementations for multimodal interrogation that employ OptAM modes to deliver enhanced biological information to the ...
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Artificial intelligence assisted clinical fluorescence imaging achieves ...
Apr 23, 2025 · Advancements in biomedical optical imaging have enabled researchers to achieve cellular-level imaging in the living human body.
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Advances in the Application of Three‐Dimensional Reconstruction ...
Aug 29, 2025 · AI has facilitated the transition from labor‐intensive manual or semi‐automated segmentation methods to high‐precision, automated segmentation ...
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Application of fluorescence lifetime imaging-integrated deep ...
The integration of deep learning enhances FLIM's diagnostic potential by automating image analysis, identifying subtle metabolic changes, and improving ...
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Possible integration of artificial intelligence with photodynamic ...
AI algorithms provides highly accurate predictive models for optimising light delivery and light distribution patterns within tumour tissues [23]. Machine ...<|separator|>
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Creating coveted bioluminescence colors for simultaneous multi ...
Jan 22, 2025 · Bioluminescence, which does not require excitation light, is a potential alternative to circumvent the limitations of fluorescence imaging.Missing: breakthroughs | Show results with:breakthroughs
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De novo luciferases enable multiplexed bioluminescence imaging
Mar 13, 2025 · Bioluminescence technology offers highly sensitive and non-invasive imaging in living organisms without the need for external excitation.
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Recent advances in fluorescent nanomaterials designed for ...
The biocompatibility of fluorescent nanomaterials is critical for their in vivo application in biomarker detection.
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Challenges in clinical translation of artificial intelligence and real ...
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Artificial intelligence (AI) applications and their impact on thoracic ...
Aug 30, 2025 · The integration of AI into fluorescence imaging has been shown to enhance lesion recognition and improve biopsy targeting by reducing ...
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Application of fluorescence lifetime imaging-integrated deep ...
This review outlines advancements in FLIM instrumentation, computational models, and clinical relevance, emphasizing its promise for precision oncology and ...
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Best practices in plant fluorescence imaging and reporting: A primer
Jul 23, 2025 · We also present standards for methods reporting that will be valuable to all users and offer tools to improve reproducibility and data sharing.