Inorganic arsenic (iAs) is one of the most toxic metalloids which could accumulate in marine species, especially in clams, causing serious ecological risk. Marine clams accumulate high level of iAs in different tissues. Currently, Fluorescence Lifetime Microscopy (FLIM) technique has provided quantitative information in biochemical diagnosis. In this study, we applied FLIM method into analyzing Hematoxylin and eosin (H&E) stained sections of arsenic exposed Ruditapes philippinarum. The clams were exposed under different concentrations of As(Ⅲ) and As(V) for thirty days. Fluorescent images of the H&E stained hepatopancreas tissue were obtained with FLIM system, followed with data analysis for fluorescence lifetime values. The average fluorescence lifetime of sections in the control group was around 250 ps. The average lifetime value in the As(V) group was slightly increased to around 280-300 ps. The average lifetime value in the As(III) group achieved a significant increase to around 340 ps. These results suggested a higher extent of structural change in As(Ⅲ) exposed group than As(V) group. As a result, this work has provided quantitative evaluation standard for the toxicity of marine mollusk based on fluorescence lifetime imaging method.
Mitochondria functions as a major power source in diverse cell physiological processes. Mitochondria dysfunction is associated with many diseases, such as neurodegenerative diseases and various cancers. It is crucial to understand mitochondrial metabolism in live cells and related dysfunction in diseases. Currently, three-dimensional (3D) cultured tumor spheroids have been widely used in drug development in cancer therapy fields, due to their similarities with the animal model compared with 2D cultured cells. However, characterization methods to monitor metabolism status in tumor spheroids are limited by the lack of techniques to measure mitochondrial metabolic fluxes in a noninvasive and real-time way. Here, we proposed a Fluorescence Lifetime Imaging Microscopy (FLIM) based method to monitor the mitochondria status in 3D cultured cells. MCF-7 tumor spheroids or 2D cultured cells were labelled with a mitochondria specific dye Rhodamine123 (R123). Images of cultured cells were captured with a FLIM system and analyzed with software SPCImage, providing the size and shape of each tumor spheroid as well as the fluorescence lifetime values of mitochondria. In 2D cultured cells, the fluorescence lifetime values of each dye had little fluctuation, indicating similar physiological status. In tumor spheroids labelled with R123, the fluorescence lifetime values of the inner part of spheroids were uneven compared with those of the outer edge. The reason for this uneven lifetime span of mitochondria may be associated with the difference of status between the inner and outer layers of tumor spheroids. In conclusion, this FLIM based method has shown great advantages to characterize the mitochondria status in 3D cultured tumor spheroids, providing a powerful quantitative method in cellular physiology research fields.
Chlorella is a unicellular spherical green microalga with alternate colors from blue green to yellowish or red due to different components of innate pigments. Light and salinity are two important environmental factors in Chlorella culture. Light conditions directly affect the growth and biochemical composition of microalgae, while salinity change could influence the pigment composition of Chlorella. Therefore, it has crucial research significance to monitor the response of Chlorella to salinity stress under different light conditions. Recently, Fluorescence Lifetime Imaging Microscopy (FLIM) technology has been widely applied into biological fields, providing fluorescence lifetime values for quantitative analysis. Here, FLIM method was used to observe the autofluorescence of a freshwater microalga, Chlorella sp.. Chlorella cells were treated with a series of salinity concentrations (control sample in normal culture medium, 3S sample with an additional 3× salinity, 7S sample with an additional 7× salinity, respectively) under light (12 h/12 h light/dark cycles) or dark (0 h/24 h light/dark cycles) treatments. After one day, images of the microalgae cells from each group were obtained with FLIM system, followed by an analysis with SPCImage software. The results showed that 3× salinity condition had little effect on Chlorella in both light/dark conditions, suggesting the adaptive capacity of Chlorella to seawater salinity. By contrast, the mean fluorescence lifetime values in 7S samples under light conditions were significantly decreased compared to that of the control. Interestingly, similar lifetime values were observed in 7S samples and the control samples under dark conditions, which indicated a potential high salinity resistance induced by different light/dark conditions. In conclusion, FLIM could work as a fast evaluation method of the physiological status of living Chlorella sp. under different culture conditions in a quantitative way.
Esophageal carcinoma is a common clinical cancer and with sixth occurrence frequency in the world, has a low five-year survival rate. Among different types of esophageal carcinoma, esophageal squamous cell carcinoma (ESCC) has the highest incidence rate and has a poor prognosis after surgery. For clinical diagnosis, hematoxylin and eosin (H&E) stained sections of diseased tissues are considered as the “golden standard”. However, determination of the tumor regions is usually relied on professional experience, which is time consuming and has a high misdiagnosis rate. Currently, novel optical imaging tools such as multi-photon excitation imaging and fluorescence lifetime imaging microscopy (FLIM) have been applied in clinical diagnosis. FLIM contains advantages of accurate measurement and high sensitivity to microenvironment. In this work, we constructed mice orthotopic esophageal cancer model to investigate the characteristics of esophageal tumor cells. Then FLIM technique were used to investigate H&E stained sections from both healthy control mice and ESCC mice, providing difference between the fluorescence lifetime values of normal tissues and those of the pathological tissues. Results also revealed an alteration of the fluorescence lifetime values of esophageal stratum corneum, which might be generated through tumor extrusion. Furthermore, the fluorescence lifetime values of tumor cells are distinctly smaller than those of the surrounding stroma, indicating an accurate identification the lesion area. In conclusion, the fluorescence lifetime images obtained by FLIM could provide a quantitative method in future pathological identification.
As one of the most fatal cancers, pancreatic cancer generated nearly a half million of new cases world-widely in 2021. The cure rate of pancreatic cancer is extremely low, whose five-year survival rate after surgery is less than 5%, leading to a great demand of early diagnosis. Currently, the aspiration biopsy with hematoxylin-eosin (H&E) staining is considered as one golden standard for clinical cancer diagnosis. However, the accuracy of the identification of the biopsy is unsatisfied, which is highly affected by the experience of doctors. Here, we have used fluorescence lifetime imaging microscopy (FLIM) method to analyze H&E stained sections, providing quantitative data for further identification. Mice were randomly selected, divided into the experimental group injected with pancreatic cancer cells and the control group. Then the pancreatic tissues of both groups were obtained and stained with H&E dye solution. Next, the sections were imaged with FLIM system, providing fluorescence lifetime data for analysis. The results showed that the average fluorescence lifetime value of normal tissues was around 30.5% less than that of cancerous tissues. Moreover, phasor plot software was applied to distinguish certain regions (such as desmoplasia), which were not identified in either the bright-field-image mode nor the fluorescence lifetime mode. In conclusion, FLIM technique on H&E stained sections has generated quantitative information to identify cancerous tissues as well as desmoplasia, leading to an improved diagnostic accuracy. This FLIM-based method in analyzing H&E stained sections has a high potential in further quantitative diagnosis of different types of cancers.
As a kind of microalgae, Spirulina plays an important role in fish culture, food processing industry, medical treatment and bioenergetic development due to its reasonable nutritional composition and high hydrogenase activity. However, the purity of Spirulina , which could be significantly affected by virus infection and miscellaneous algal issues, has great impact on the quality of the product. Thus, periodic Spirulina detection is necessary for quality control of Spirulina culture. Currently, there are two main methods of Spirulina detection: the optical microscopic method and the fluorescence detection method. The former has higher accuracy and a lower speed while the latter has a higher speed in a sample destructing mode. Deep learning-based method has the ability to accelerate data processing. Meanwhile, it can achieve high accuracy by model training and validation. In this work, we have applied deep learning to Spirulina detection to achieve a higher accuracy rate. The process was divided into four main steps: Spirulina culture, image acquisition, image preprocessing and YOLO-v3 model training. The hyperparametric modulation was carried out to determine the appropriate training parameters, providing a trained model with mAP of 0.839 at a detection speed of 20.53 fps. It has great application potential in quantity detection and size detection of cultured Spirulina .
With the rapid development of modern industry, heavy metal pollution is becoming one of the most severe marine environmental problems among the world. Mussels are considered as suitable models to monitor heavy metal pollutions. The hematoxylin and eosin (H&E) sections of mussels could be observed with fluorescence lifetime imaging microscopy (FLIM) method, generating quantitative data of images for improved analysis with higher accuracy. In this study, we used FLIM method to investigate the fluorescence lifetime of digestive glands of adult mussels Mytilus galloprovincialis treated with two environmentally relevant concentrations (5 μg/L and 50 μg/L) of cadmium (Cd) for 14 days. After exposure, the H&E stained sections of the digestive glands were observed with FLIM system. The images were analyzed with SPCImage software, providing both the structural images with fluorescence intensity information and the pseudo-color images with fluorescence lifetime information. The fluorescence lifetime values were presented as total τ, which could be divided into τ1 (the shorter part) and τ2 (the longer part), respectively. Results showed that the τ2 values in 50 μg/L Cd treatments were significantly lower than those of the control group, suggesting that the high concentration of Cd treatment has a high impact on the digestive glands of M. galloprovincialis. The significance of the fluorescence lifetime data of mussel digestive glands induced by Cd at a high concentration has proved the sensitivity of FLIM method to distinguish the polluted mussels from the healthy individuals. In conclusion, FLIM has high potential in further applications of marine environment pollution monitoring.
Chlorella is a single-celled blue-green spherical microalga, whose color could change from green to red or yellowish due to the components of different types of innate pigments. Salinity change is one important environmental stressor that may influence the pigment composition of Chlorella. Therefore, it is necessary to monitor the salinity stress on Chlorella in a real-time mode. Recently, fluorescence lifetime imaging microscopy (FLIM) technology has been widely applied into biological fields, which could provide fluorescence lifetime values for quantitative analysis. Here, we used FLIM method to investigate a freshwater microalga, Chlorella sp. based on its autofluorescence. Chlorella cells were treated with a series of salinity concentrations (control sample in normal culture medium, 3S sample with an additional 3× salinity, 7S sample with an additional 7× salinity, respectively) for one day. Then images of the microalgae cells from each group were obtained with FLIM system and analyzed with SPCImage software, providing the fluorescence lifetime data. The results of fluorescence lifetime data showed that 3× salinity condition had little effect on Chlorella, which indicated that Chlorella had a strong adaptive capacity in environments close to seawater salinity. However, the significant left shift of lifetime distribution peak and decreased mean lifetime values were observed in 7S samples compared with the control. In conclusion, FLIM method has shown great potential as a fast identification method of living Chlorella sp. under high salinity conditions in a quantitative and non-invasive way.
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