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Autofluorescence
Autofluorescence
Autofluorescence
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Micrograph of paper autofluorescing under ultraviolet illumination. The individual fibres in this sample are around 10 μm in diameter.

Autofluorescence is the natural fluorescence of biological structures such as mitochondria and lysosomes, in contrast to fluorescence originating from artificially added fluorescent markers (fluorophores).[1]

The most commonly observed autofluorescencing molecules are NADPH and flavins; the extracellular matrix can also contribute to autofluorescence because of the intrinsic properties of collagen and elastin.[1]

Generally, proteins containing an increased amount of the amino acids tryptophan, tyrosine, and phenylalanine show some degree of autofluorescence.[2]

Autofluorescence also occurs in non-biological materials found in many papers and textiles. Autofluorescence from U.S. paper money has been demonstrated as a means for discerning counterfeit currency from authentic currency.[3]

Microscopy

[edit]
A multispectral image of tissue from a mouse intestine, showing how autofluoresce can obscure several fluorescence signals.

Autofluorescence can be problematic in fluorescence microscopy. Light-emitting stains (such as fluorescently labelled antibodies) are applied to samples to enable visualisation of specific structures.

Autofluorescence interferes with detection of specific fluorescent signals, especially when the signals of interest are very dim — it causes structures other than those of interest to become visible.

In some microscopes (mainly confocal microscopes), it is possible to make use of different lifetime of the excited states of the added fluorescent markers and the endogenous molecules to exclude most of the autofluorescence.

Autofluorescence super resolution microscopy/optical nanoscopy image of cellular structures that are invisible with confocal light microscopy

In a few cases, autofluorescence may actually illuminate the structures of interest, or serve as a useful diagnostic indicator.[1]

For example, cellular autofluorescence can be used as an indicator of cytotoxicity without the need to add fluorescent markers.[4]

The autofluorescence of human skin can be used to measure the level of advanced glycation end-products (AGEs), which are present in higher quantities during several human diseases.[5]

Autofluorescence in banana skin under different light conditions.

Optical imaging systems that utilize multispectral imaging can reduce signal degradation caused by autofluorescence while adding enhanced multiplexing capabilities.[6]

The super resolution microscopy SPDM revealed autofluorescent cellular objects which are not detectable under conventional fluorescence imaging conditions.[7]

Autofluorescent molecules

[edit]
Molecule Excitation
(nm) 		Fluorescence
(nm) Peak
Animals (Zoae)
Fungi
Plants
Reference
NAD(P)H 340 450 Z F P [8]
Chlorophyll 465–665 673–726 P
Collagen 270–370 305–450 Z [8]
Retinol 500 Z F P [9]
Riboflavin 550 Z F P [9]
Cholecalciferol 380–460 Z [9]
Folic acid 450 Z F P [9]
Pyridoxine 400 Z F P [9]
Tyrosine 270 305 Z F P [2]
Dityrosine 325 400 Z [2]
Excimer-like
aggregate
(collagen) 		270 360 Z [2]
Glycation adduct 370 450 Z [2]
Indolamine Z
Lipofuscin 410–470 500–695 Z F P [10]
Lignin
(a polyphenol) 		335–488 455–535 P [11]
Tryptophan 280 300–350 Z F P
Flavin 380–490 520–560 Z F P
Melanin 340–400 360–560 Z F P [12]
Substances luminous in animal tissue are, by taxonomic inclusion, also luminous in human tissue.

See also

[edit]

References

[edit]
Revisions and contributorsEdit on WikipediaRead on Wikipedia

Autofluorescence

View on Grokipedia
from Grokipedia
Autofluorescence is the natural emission of fluorescent light from endogenous molecules within biological tissues and cells when excited by light of a shorter , typically in the to , without the addition of external fluorescent probes. This phenomenon arises from intrinsic fluorophores such as aromatic , structural proteins, metabolic coenzymes, porphyrins, and , each contributing distinct excitation and emission spectra that reflect tissue composition and physiological state. In biological systems, autofluorescence serves as an intrinsic for monitoring metabolic activity, , and structural integrity across animals, , and microorganisms. For example, alterations in fluorescence signals can indicate metabolic shifts in pathological conditions or assess physiological processes like . Its non-invasive, label-free nature enables real-time visualization in techniques such as microscopy and . Autofluorescence has applications in biomedical research and clinical diagnostics, including early disease detection through optical imaging. Recent advances (as of 2025) include its use in fundus imaging for retinal diseases like age-related and in detecting bacterial infections in wounds. It also supports metabolic imaging in fields like and . While autofluorescence can introduce in fluorescence assays, advances in techniques and are improving its utility.

Basic Principles

Definition and Overview

Autofluorescence refers to the natural emission of light by biological tissues, cells, or molecules when excited by light of a shorter , occurring without the introduction of external fluorophores. This endogenous phenomenon arises from intrinsic fluorophores present in living organisms, distinguishing it from exogenous fluorescence, which requires the addition of synthetic dyes or genetically encoded proteins such as (GFP). The observation of autofluorescence dates back to the early , with the earliest microscopic reports attributed to Hans Stübel in 1911, who noted in biological samples using excitation at Jena University. Further advancements in the and , including work by Heimstädt on plant tissues, highlighted its potential in , while recognition in animal tissues expanded in the 1950s through studies by Britton Chance characterizing metabolic cofactors' emissions. Autofluorescence is ubiquitous across living organisms, contributing to background signals in and serving as a marker of cellular in (e.g., via ), animals (e.g., via ), and microbes (e.g., via flavins). At its core, the process involves electrons in fluorophores absorbing excitation energy to reach higher states, followed by relaxation that emits photons at longer wavelengths—a phenomenon known as the .

Mechanism of Autofluorescence

Autofluorescence arises from the absorption of photons by endogenous molecules, promoting from the ground (S₀) to an excited (S₁) through a quantum mechanical process governed by the Franck-Condon principle. Following excitation, rapid vibrational relaxation occurs within the S₁ state, typically on the timescale, before the electron returns to S₀, emitting a as . This emission is delayed relative to absorption due to non-radiative relaxation processes, resulting in a red-shifted . The energy transitions involved are illustrated by the , which depicts the electronic and vibrational energy levels of a . In this diagram, absorption promotes the molecule to higher vibrational levels of S₁, followed by to the lowest vibrational level of S₁. From there, emission returns the electron to S₀ vibrational levels; alternative pathways include to the (T₁), leading to delayed , though this is minor in biological autofluorescence due to the short lifetimes of endogenous s. A key feature of this process is the , defined as the difference between the emission (λ_em) and excitation (λ_ex): Δλ = λ_em - λ_ex. In biological autofluorescence, this shift typically ranges from 20 to 100 nm, arising from solvent reorganization and vibrational relaxation that lower the emission energy relative to absorption. The intensity of autofluorescence is modulated by several factors, including the (φ), defined as the ratio of emitted photons to absorbed photons, which varies; for example, ~0.13 for and ~0.02 for free NADH (increasing to ~0.05 when protein-bound). The lifetime (τ), the average time the molecule spends in the before emission, typically falls between 0.4 and 5 ns for these molecules. Environmental conditions further influence these parameters; for instance, variations can alter the protonation state of fluorophores like , affecting , while molecular oxygen quenches through collisional deactivation or . Photochemical reactions play a minor role in autofluorescence by contributing to quenching mechanisms, such as photooxidation where excited fluorophores react with oxygen to form non-fluorescent products, or through to nearby quenchers that dissipates excitation energy non-radiatively.

Endogenous Fluorophores

Common Autofluorescent Molecules

Autofluorescence in biological tissues primarily originates from endogenous molecules that are integral to cellular function but exhibit fluorescence as a secondary due to their aromatic or conjugated structures. These include metabolic cofactors, , structural proteins, and pigments, which vary in abundance and distribution across cell types and organisms. In animals, autofluorescence is prominent in tissues like , eyes, and , while show elevated levels due to photosynthetic pigments. Concentrations of these molecules influence the intensity of autofluorescent signals, with typical intracellular ranges spanning micromolar to millimolar levels depending on the metabolic state and tissue type. Reduced (NAD(P)H), encompassing both NADH and NADPH, and (FAD) are crucial metabolic cofactors that serve as indicators of cellular energy production and balance. NADH and NADPH, generated as byproducts of , the tricarboxylic acid cycle, and biosynthetic pathways, are predominantly located in mitochondria and the , where they act as donors; their typical intracellular free concentrations are approximately 1-10 μM, though total pools can reach 0.1-1 mM in active cells. FAD, a coenzyme in flavoproteins involved in oxidation-reduction reactions and transport, is similarly distributed in mitochondria and at concentrations of 10-100 μM, reflecting oxidative metabolic activity. These cofactors are ubiquitous in eukaryotic and prokaryotic cells, with signal strength varying by metabolic demand, such as higher NAD(P)H in glycolytic tissues. NAD(P)H exhibits autofluorescence with nearly identical spectral properties for NADH and NADPH, often analyzed together in imaging. Tryptophan, an and precursor to neurotransmitters like serotonin, contributes to autofluorescence via its ring within proteins. It is dispersed throughout the nucleus, , and extracellular proteins, with typical cellular concentrations of 50-500 μM tied to overall protein synthesis rates. This molecule's fluorescence arises incidentally from its structural role in enzymes and structural proteins, and its levels are consistent across organisms that utilize protein-based biology, though they fluctuate with dietary intake and . Collagen and elastin, as extracellular matrix components, are major autofluorescent contributors in connective tissues. provides structural support and tensile strength in , tendons, and , while elastin confers elasticity to dynamic structures like vessels, lungs, and ; both are synthesized by fibroblasts and accumulate extracellularly without specific intracellular concentrations, as they are not cytosolic. In humans and other vertebrates, these proteins drive strong autofluorescence in dermal and vascular tissues, with abundance varying by and age—higher in long-lived mammals. Lipofuscin, often termed the "age pigment," is a heterogeneous of and lysosomal degradation that accumulates in lysosomes of post-mitotic cells such as neurons, cardiomyocytes, and retinal pigment epithelial cells. It forms from undigested cellular residues and , serving no primary functional role but marking cellular aging and ; its levels increase progressively with age and in pathological conditions like neurodegeneration, where it contributes to tissue autofluorescence in the and eyes. Concentrations are variable and tissue-specific, starting low in but rising to detectable aggregates in older organisms across species. Porphyrins, including , are intermediates in heme biosynthesis essential for oxygen transport in and . They are primarily located in mitochondria and of erythroid and hepatic cells, with low baseline concentrations of 0.1-10 μM that can elevate in metabolic disorders; their is a incidental property of the porphyrin ring structure. These molecules are present in all oxygen-dependent organisms, from mammals to , though accumulation is more pronounced in disease states. In photosynthetic organisms like plants and algae, and dominate autofluorescence. is localized exclusively in chloroplasts where it captures light for at concentrations of 1-5 mM. This pigment's role is central to energy conversion, making plant tissues far more autofluorescent than animal counterparts, with emission influenced by environmental light and ; variations occur across plant species, highest in green leaves. , a complex polymer in s, provides structural rigidity and exhibits autofluorescence used to assess lignification and properties in plant tissues.

Spectral Properties

Autofluorescent molecules exhibit characteristic excitation and emission spectra primarily in the and visible ranges, enabling their detection but also complicating separation due to overlaps. For instance, is excited at approximately 280 nm and emits around 350 nm, while NADH shows excitation near 340 nm with emission peaking at 450-460 nm. FAD, in contrast, has excitation at about 450 nm and emission at 530-535 nm. These profiles span the UV-visible spectrum, with broad bands that often overlap, such as the emission tail of extending into NADH's excitation range and NADH's emission overlapping with FAD's in the green region. The emission spectra of these s typically have full widths at half maximum (FWHM) of 50-100 nm, contributing to significant spectral overlap in applications. NADH's emission band, for example, spans roughly 420-480 nm (FWHM ~60 nm), allowing partial bleed-through into adjacent detection channels. In multi-label , this overlap—exacerbated by autofluorescence from multiple endogenous sources—leads to , where signal from one contaminates another's channel, reducing specificity. Spectral properties are sensitive to environmental factors, including and quenchers. For NADH, emission peaks can blue-shift under acidic conditions (pH <5), with the spectrum shifting by up to 10-20 nm due to protonation effects, alongside reduced fluorescence lifetime. Quenching occurs via interactions with heavy metals, which generate reactive oxygen species that oxidize NADH, or directly by molecular oxygen through reactive quenching pathways, diminishing emission intensity. These shifts and quenching alter the effective quantum yield, linking back to the underlying relaxation mechanisms in autofluorescence. Two-photon excitation enhances autofluorescence imaging by using longer wavelengths (700-900 nm), reducing scattering and enabling deeper tissue penetration while exciting the same emission profiles as single-photon methods. For NADH, efficient two-photon excitation occurs at 710-780 nm, producing the characteristic blue emission without significant spectral alteration. This approach minimizes phototoxicity and autofluorescence from shallower layers.
FluorophoreExcitation Peak (nm)Emission Peak (nm)Quantum Yield (approximate, free form)
Tryptophan2803500.13
NADH340450-4600.02
FAD450530-5350.03

Applications in Biology and Medicine

Fluorescence Microscopy

Autofluorescence serves as both a valuable endogenous signal and a potential confound in fluorescence microscopy, enabling label-free visualization of cellular structures and metabolic states without the need for exogenous dyes. In live-cell imaging, it plays a key role in metabolic mapping by capturing fluorescence from intrinsic molecules like NADH and FAD, whose ratio reflects the cellular redox state. For instance, elevated NADH/FAD ratios indicate glycolytic shifts in cancer cells, allowing real-time assessment of metabolic alterations during processes such as tumor progression or drug response. This approach facilitates non-invasive monitoring of dynamic cellular events, such as oxidative stress or mitochondrial function, in living tissues. Techniques leveraging autofluorescence extend to advanced modalities, including autofluorescence-based cytometry and super-resolution methods. In flow cytometry, endogenous fluorescence from NADH and FAD enables label-free phenotyping of cell metabolism and viability, distinguishing subpopulations based on redox profiles without staining artifacts. Super-resolution approaches utilize autofluorescence to complement exogenous labels, providing high-resolution insights into subcellular distributions of endogenous fluorophores, such as in neural or metabolic studies where precise localization enhances understanding of protein interactions or organelle dynamics. These methods capitalize on the natural emission properties to achieve resolutions beyond the diffraction limit while minimizing sample perturbation. The primary advantages of autofluorescence in fluorescence microscopy include its label-free and non-invasive nature, which avoids phototoxicity associated with synthetic dyes and enables prolonged live imaging of sensitive biological samples. This is particularly beneficial for real-time tracking of cellular states, such as redox balance or structural integrity, in unperturbed environments. Instrumentation typically involves UV or visible excitation sources, like mercury arc lamps emitting at 340-450 nm to excite NADH, paired with emission filters such as 450/50 nm bandpass to selectively capture its blue fluorescence while reducing background. These setups, often integrated into confocal or multiphoton systems, ensure high signal specificity for endogenous probes. Practical examples highlight autofluorescence's utility in diverse tissues. In neural imaging, lipofuscin accumulation in aging or diseased neurons produces distinct yellow-orange autofluorescence, allowing quantification of lysosomal storage and neurodegeneration via standard widefield or confocal microscopy. Similarly, in plant biology, lignin's green-yellow autofluorescence delineates cell wall architecture, enabling label-free analysis of structural integrity in roots or stems during development or stress responses. These applications underscore autofluorescence's role in bridging basic research and applied imaging without spectral overlaps dominating other endogenous signals.

Clinical Diagnostics

Autofluorescence plays a pivotal role in non-invasive clinical diagnostics by leveraging endogenous fluorophores to identify pathological changes in tissues, enabling early disease detection without exogenous contrast agents. In various medical fields, alterations in autofluorescence patterns—such as intensity, spectral shifts, or ratios—serve as biomarkers for malignancy or degeneration, often integrated into endoscopic, dermatological, and ophthalmic imaging systems. This approach has been validated in clinical settings since the early 2000s, offering real-time visualization that complements traditional white-light examination. In endoscopic applications, autofluorescence bronchoscopy facilitates the detection of early lung cancer by exploiting altered signals in precancerous bronchial tissues. Under blue light excitation (around 405 nm), normal mucosa exhibits strong green autofluorescence (505–550 nm) from fluorophores like NADH and collagen, while precancerous or neoplastic lesions show reduced green emission and increased red fluorescence (>590 nm) due to accumulation. Clinical studies have demonstrated sensitivities of 71% and specificities of 74% for distinguishing malignant from normal bronchial mucosa using this technique. Dermatological diagnostics utilize autofluorescence to identify skin lesions, particularly (BCC), where reduced autofluorescence distinguishes malignant areas from healthy tissue. Excited by or blue light, in normal emits green fluorescence (around 520 nm), but BCC lesions display diminished intensity due to disrupted and increased cellular density. imaging with devices like smartphone-based RGB cameras has confirmed this pattern across multiple cases, aiding in precise demarcation for surgical excision. Ophthalmic imaging employs fundus autofluorescence (FAF) to diagnose retinal diseases, such as , using accumulation in the as a key . Short-wavelength FAF (488 nm excitation) reveals hyperautofluorescent spots from buildup in early and hypoautofluorescent areas indicating in advanced stages, with emission peaking around 600 nm. This non-invasive method maps disease progression and differentiates phenotypes, providing quantitative assessments like normalized AF intensity for clinical monitoring. In gastrointestinal , autofluorescence imaging aids in detecting precancerous and neoplastic lesions, such as in Barrett’s esophagus and , by highlighting changes in signals like and porphyrins. For example, endoscopic trimodal imaging achieves sensitivities of 77% for gastroesophageal reflux disease-related inflammation and 91.7% for colorectal neoplasia, improving detection over white-light alone. In endocrine surgery, near-infrared autofluorescence imaging enables real-time identification of parathyroid glands during thyroidectomy, reducing risks of inadvertent removal. This technique detects intrinsic fluorescence from parathyroid tissue with accuracies of 97–100%, allowing localization even before dissection in 37–67% of cases. Quantitative metrics, such as autofluorescence intensity ratios, enhance diagnostic precision by reflecting metabolic alterations like tumor hypoxia. The optical redox ratio, calculated as FAD/[NAD(P)H + FAD], decreases in hypoxic tumors due to elevated NADH from glycolytic shifts and reduced FAD from impaired oxidative phosphorylation, typically ranging from 0.45–0.5 in cancerous tissues versus 0.55–0.6 in normal ones. Clinical trials from the 2000s onward, including those using devices like VELscope for oral cancer screening, report sensitivities of 80–100% and specificities of 38–100% for detecting dysplastic or malignant lesions when combining autofluorescence with white-light examination. Emerging technologies like advance autofluorescence diagnostics by capturing full spectral profiles to differentiate diseased from healthy patterns. In , hyperspectral FAF with multiple excitations (e.g., 436–505 nm) identifies unique emission spectra from (peaking at 510–520 nm), absent in normal , enabling early lesion detection. This approach improves specificity in clinical settings by isolating contributions from multiple fluorophores, such as and sub-RPE deposits.

Challenges and Solutions

Sources of Interference

Autofluorescence serves as a of in fluorescence-based experiments by overlapping spectrally with signals from exogenous fluorophores, such as those used in labeling, thereby elevating the overall background and complicating the detection of specific signals. This overlap often occurs in the blue-green spectral range due to endogenous molecules like NAD(P)H and flavoproteins, which emit light that can bleed into the emission channels of common dyes like FITC or GFP. In typical fluorescence microscopy setups, this interference can substantially degrade the (SNR), where autofluorescence contributes to the background term in the SNR calculation, defined as SNR = (signal - background) / √background, limiting the sensitivity and of . For instance, in GFP-transfected cells, autofluorescence reduces image contrast and clarity, masking low-level GFP signals and thereby decreasing resolution of cellular structures. Tissue-specific factors exacerbate this issue, particularly in fixed samples where formalin fixation generates autofluorescent products that mimic lipofuscin-like signals and overlap with key endogenous fluorophores such as NAD(P)H and , increasing background intensity. In thick tissues, autofluorescence exhibits depth-dependent effects, with out-of-focus emission from superficial layers adding to the background in deeper regions, compounded by light scattering and absorption that attenuate the excitation and emission paths. Environmental and physiological contributors further modulate autofluorescence levels; for example, in animal models such as mice, dietary intake of from standard chow can induce autofluorescence in gastrointestinal tissues, interfering with in vivo imaging. Aging is associated with elevated accumulation, a granular that intensifies autofluorescence, particularly in post-mitotic cells like neurons and cardiac myocytes. In disease states, such as , autofluorescence is heightened due to increased metabolic activity and , leading to hyperautofluorescent patterns that correlate with disease severity in affected tissues. Non-biological sources in laboratory settings, including autofluorescence from plasticware like polystyrene plates and culture media components such as phenol red, can also introduce unintended background noise during cell-based fluorescence assays.

Methods to Reduce Autofluorescence

Several chemical quenching agents are employed to minimize autofluorescence by reacting with or blocking the reactive groups responsible for endogenous fluorescence signals. Sodium borohydride (NaBH₄) serves as a mild reducing agent that effectively dampens autofluorescence across various wavelengths in formalin-fixed tissues, including those from brain, kidney, and heart, by altering aldehyde groups formed during fixation. Glycine, often used at concentrations of 10-100 mM, quenches autofluorescence through similar blocking of reactive sites, particularly in fixed samples, and has been shown to reduce background in immunofluorescence assays without significantly affecting exogenous fluorophore signals. For protein-based autofluorescence, such as that from lipofuscin or heme-containing structures, copper sulfate (CuSO₄) incubation at low millimolar concentrations effectively suppresses signals, as demonstrated in immunohistochemical preparations of cortical tissue and decellularized scaffolds, where it reduced interference by at least 70% in relevant emission channels. Physical methods leverage differences in fluorescence decay kinetics between endogenous and exogenous probes. Time-gated detection exploits the typically shorter lifetimes of endogenous fluorophores (e.g., 0.3-2.5 ns for NADH and flavins) compared to many exogenous dyes (2-5 ns or longer), applying a gate delay of 1-5 ns to collect emission primarily from the longer-lived signals, thereby eliminating short-lived autofluorescence in live-cell and tissue imaging. This approach has been particularly useful in (FLIM) for distinguishing metabolic autofluorescence from targeted probes in biological samples, with recent GPU-accelerated high-speed FLIM (as of 2025) enabling real-time separation in various tissues. Optical strategies focus on selective excitation and emission filtering to bypass endogenous signals. Long-pass emission filters with cutoffs above 500 nm prevent detection of UV-excited autofluorescence from molecules like or NAD(P)H, which emit below this threshold, while allowing collection of signals from red-shifted exogenous dyes; this is commonly applied in confocal setups to enhance contrast in tissue sections. Multiphoton excitation, using near-infrared wavelengths (e.g., 700-1000 nm), confines excitation to the focal plane due to its nonlinear , reducing out-of-focus autofluorescence and in deep-tissue , such as in neuronal and gastrointestinal samples. Sample preparation techniques target specific autofluorescent components prior to . Sudan Black B (SBB), a lipophilic applied at 0.1-0.5% in ethanol, quenches lipid-associated autofluorescence from structures like or by binding and masking these sites, significantly lowering background in neural, renal, and pancreatic tissues without antibody-derived signals. Autofluorescence-free mounting media, such as ProLong Gold, provide a low-background matrix that preserves exogenous while minimizing contributions from the mounting agent itself, as utilized in high-resolution of fixed cells and sections to maintain over extended periods. Commercial quenching agents like TrueBlack® or TrueVIEW® offer further options for reducing background without significant signal loss in . Advanced computational approaches offer precise mitigation for complex samples. Software-based spectral unmixing algorithms, such as linear unmixing in systems, deconvolute overlapping emission spectra by estimating contributions from known endogenous and exogenous fluorophores, effectively subtracting autofluorescence in multispectral datasets from labeled tissues. Recent developments include deep learning-based methods for autofluorescence removal, improving accuracy in and imaging as of 2022 onward.

References

  1. https://pmc.ncbi.nlm.nih.gov/articles/PMC4289852/
  2. https://www.mdpi.com/1420-3049/25/9/2095
  3. https://pmc.ncbi.nlm.nih.gov/articles/PMC7288016/
  4. https://pmc.ncbi.nlm.nih.gov/articles/PMC12293359/
  5. https://pmc.ncbi.nlm.nih.gov/articles/PMC12117260/
  6. https://pmc.ncbi.nlm.nih.gov/articles/PMC10997463/
  7. https://www.sciencedirect.com/topics/medicine-and-dentistry/autofluorescence
  8. https://www.ejh.it/index.php/ejh/article/view/2461/2384
  9. https://www.sciencedirect.com/science/article/abs/pii/B9780124177604500082
  10. https://pmc.ncbi.nlm.nih.gov/articles/PMC6352511/
  11. https://www.sciencedirect.com/topics/immunology-and-microbiology/autofluorescence
  12. https://www.thermofisher.com/us/en/home/life-science/protein-biology/protein-biology-learning-center/protein-biology-resource-library/pierce-protein-methods/fluorescent-probes.html
  13. https://pmc.ncbi.nlm.nih.gov/articles/PMC2924670/
  14. https://pmc.ncbi.nlm.nih.gov/articles/PMC6959846/
  15. https://www.sciencedirect.com/science/article/pii/S1550413111003500
  16. https://www.nature.com/articles/ncomms4936
  17. https://pubmed.ncbi.nlm.nih.gov/35267784/
  18. https://omlc.org/spectra/PhotochemCAD/html/tryptophan.html
  19. https://pmc.ncbi.nlm.nih.gov/articles/PMC8367293/
  20. https://pmc.ncbi.nlm.nih.gov/articles/PMC2874879/
  21. https://zeiss-campus.magnet.fsu.edu/articles/spectralimaging/introduction.html
  22. https://www.microscopyu.com/techniques/confocal/spectral-imaging-and-linear-unmixing
  23. https://www.sciencedirect.com/science/article/pii/S1011134408002625
  24. https://www.sciencedirect.com/science/article/abs/pii/0005272881902085
  25. https://pmc.ncbi.nlm.nih.gov/articles/PMC3842212/
  26. https://pmc.ncbi.nlm.nih.gov/articles/PMC6951488/
  27. https://www.aatbio.com/resources/quantum-yield/tryptophan
  28. https://pmc.ncbi.nlm.nih.gov/articles/PMC5480559/
  29. https://www.researchgate.net/publication/360333134_Determination_of_quantum_yield_of_NADH_and_FAD_in_alcohol-water_solutions_the_analysis_of_radiative_and_nonradiative_relaxation_pathways
  30. https://www.pnas.org/doi/10.1073/pnas.0708425104
  31. https://onlinelibrary.wiley.com/doi/full/10.1002/cyto.a.23597
  32. https://pmc.ncbi.nlm.nih.gov/articles/PMC11118363/
  33. https://pmc.ncbi.nlm.nih.gov/articles/PMC10480099/
  34. https://elifesciences.org/articles/84375
  35. https://www.nature.com/articles/s41467-023-42809-y
  36. https://pmc.ncbi.nlm.nih.gov/articles/PMC8912355/
  37. https://academic.oup.com/aobpla/article/12/4/plaa032/5864598
  38. https://www.mdpi.com/2076-3417/7/1/32
  39. https://onlinelibrary.wiley.com/doi/10.1111/j.1759-7714.2012.00130.x
  40. https://www.spiedigitallibrary.org/journals/journal-of-biomedical-optics/volume-20/issue-12/120502/Autofluorescence-imaging-of-basal-cell-carcinoma-by-smartphone-RGB-camera/10.1117/1.JBO.20.12.120502.full
  41. https://pmc.ncbi.nlm.nih.gov/articles/PMC4358814/
  42. https://pmc.ncbi.nlm.nih.gov/articles/PMC3653312/
  43. https://pmc.ncbi.nlm.nih.gov/articles/PMC8009528/
  44. https://pmc.ncbi.nlm.nih.gov/articles/PMC5851340/
  45. https://pmc.ncbi.nlm.nih.gov/articles/PMC4711767/
  46. https://www.horiba.com/usa/scientific/technologies/fluorescence-spectroscopy/how-to-calculate-signal-to-noise-ratio/
  47. https://iccb.med.harvard.edu/file_url/385
  48. https://pmc.ncbi.nlm.nih.gov/articles/PMC10581792/
  49. https://pmc.ncbi.nlm.nih.gov/articles/PMC3324656/
  50. https://pmc.ncbi.nlm.nih.gov/articles/PMC3995316/
  51. https://www.leica-microsystems.com/science-lab/life-science/learn-how-to-remove-autofluorescence-from-your-confocal-images/
  52. https://pmc.ncbi.nlm.nih.gov/articles/PMC4174629/
  53. https://pubmed.ncbi.nlm.nih.gov/34217694/
  54. https://pubmed.ncbi.nlm.nih.gov/21978484/
  55. https://pmc.ncbi.nlm.nih.gov/articles/PMC9968082/
  56. https://pmc.ncbi.nlm.nih.gov/articles/PMC4814121/
  57. https://pmc.ncbi.nlm.nih.gov/articles/PMC7219965/
  58. https://www.nature.com/articles/s41598-025-89142-6
  59. https://pmc.ncbi.nlm.nih.gov/articles/PMC3537599/
  60. https://www.nature.com/articles/s42003-024-06057-0
  61. https://pmc.ncbi.nlm.nih.gov/articles/PMC4004770/
  62. https://pmc.ncbi.nlm.nih.gov/articles/PMC5657453/
  63. https://pubmed.ncbi.nlm.nih.gov/26802460/
  64. https://pmc.ncbi.nlm.nih.gov/articles/PMC8070804/
  65. https://pmc.ncbi.nlm.nih.gov/articles/PMC3415205/
  66. https://pmc.ncbi.nlm.nih.gov/articles/PMC7523684/
  67. https://nph.onlinelibrary.wiley.com/doi/10.1111/nph.18344
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