Autofluorescent imprint of chronic constriction nerve injury identified by deep learning.

Our understanding of chronic pain and the underlying molecular mechanisms remains limited due to a lack of tools to identify the complex phenomena responsible for exaggerated pain behaviours. Furthermore, currently there is no objective measure of pain with current assessment relying on patient self-scoring. Here, we applied a fully biologically unsupervised technique of hyperspectral autofluorescence imaging to identify a complex signature associated with chronic constriction nerve injury known to cause allodynia. The analysis was carried out using deep learning/artificial intelligence methods. The central element was a deep learning autoencoder we developed to condense the hyperspectral channel images into a four- colour image, such that spinal cord tissue based on nerve injury status could be differentiated from control tissue. This study provides the first validation of hyperspectral imaging as a tool to differentiate tissues from nerve injured vs non-injured mice. The auto-fluorescent signals associated with nerve injury were not diffuse throughout the tissue but formed specific microscopic size regions. Furthermore, we identified a unique fluorescent signal that could differentiate spinal cord tissue isolated from nerve injured male and female animals. The identification of a specific global autofluorescence fingerprint associated with nerve injury and resultant neuropathic pain opens up the exciting opportunity to develop a diagnostic tool for identifying novel contributors to pain in individuals.

Non-invasive assessment of exfoliated kidney cells extracted from urine using multispectral autofluorescence features.

Optimally preserved urinary exfoliated renal proximal tubule cells were assessed by multispectral imaging of cell autofluorescence. We demonstrated different multispectral autofluorescence signals in such cells extracted from the urine of patients with healthy or diseased kidneys. Using up to 10 features, we were able to differentiate cells from individuals with heathy kidneys and impaired renal function (indicated by estimated glomerular filtration rate (eGFR) values) with the receiver operating characteristic area under the curve (AUC) of 0.99. Using the same method, we were also able to discriminate such urine cells from patients with and without renal fibrosis on biopsy, where significant differences in multispectral autofluorescence signals (AUC = 0.90) were demonstrated between healthy and diseased patients (p < 0.05). These findings show that multispectral assessment of the cell autofluorescence in urine exfoliated proximal tubule kidney cells has the potential to be developed as a sensitive, non-invasive diagnostic method for CKD.

Non-Invasive Monitoring of Functional State of Articular Cartilage Tissue with Label-Free Unsupervised Hyperspectral Imaging.

Damage and degradation of articular cartilage leads to severe pain and loss of mobility. The development of new therapies for cartilage regeneration for monitoring their effect requires further study of cartilage, ideally at a molecular level and in a minimally invasive way. Hyperspectral microscopy is a novel technology which utilises endogenous fluorophores to non-invasively assess the molecular composition of cells and tissue. In this study, we applied hyperspectral microscopy to healthy bovine articular cartilage and osteoarthritic human articular cartilage to investigate its capacity to generate informative molecular data and characterise disease state and treatment effects. We successfully demonstrated label-free fluorescence identification of collagen type I and II - isolated in cartilage here for the first time and the co-enzymes free NADH and FAD which together give the optical redox ratio that is an important measure of metabolic activity. The intracellular composition of chondrocytes was also examined. Differences were observed in the molecular ratios within the superficial and transitional zones of the articular cartilage which appeared to be influenced by disease state and treatment. These findings show that hyperspectral microscopy could be useful for investigating the molecular underpinnings of articular cartilage degradation and repair. As it is non-invasive and non-destructive, samples can be repeatedly assessed over time, enabling true time-course experiments with in-depth molecular data. Additionally, there is potential for the hyperspectral approach to be adapted for patient examination to allow the investigation of cartilage state. This could be of advantage for assessment and diagnosis as well as treatment monitoring.

Computer-assisted cystoscopy diagnosis of bladder cancer.

OBJECTIVES: One of the most reliable methods for diagnosing bladder cancer is cystoscopy. Depending on the findings, this may be followed by a referral to a more experienced urologist or a biopsy and histological analysis of suspicious lesion. In this work, we explore whether computer-assisted triage of cystoscopy findings can identify low-risk lesions and reduce the number of referrals or biopsies, associated complications, and costs, although reducing subjectivity of the procedure and indicating when the risk of a lesion being malignant is minimal. MATERIALS AND METHODS: Cystoscopy images taken during routine clinical patient evaluation and supported by biopsy were interpreted by an expert clinician. They were further subjected to an automated image analysis developed to best capture cancer characteristics. The images were transformed and divided into segments, using a specialised color segmentation system. After the selection of a set of highly informative features, the segments were separated into 4 classes: healthy, veins, inflammation, and cancerous. The images were then classified as healthy and diseased, using a linear discriminant, the naïve Bayes, and the quadratic linear classifiers. Performance of the classifiers was measured by using receiver operation characteristic curves. RESULTS: The classification system developed here, with the quadratic classifier, yielded 50% false-positive rate and zero false-negative rate, which means, that no malignant lesions would be missed by this classifier. CONCLUSIONS: Based on criteria used for assessment of cystoscopy images by medical specialists and features that human visual system is less sensitive to, we developed a computer program that carries out automated analysis of cystoscopy images. Our program could be used as a triage to identify patients who do not require referral or further testing.

Statistically strong label-free quantitative identification of native fluorophores in a biological sample.

Bioimaging using endogenous cell fluorescence, without any external biomarkers makes it possible to explore cells and tissues in their original native state, also in vivo. In order to be informative, this label-free method requires careful multispectral or hyperspectral recording of autofluorescence images followed by unsupervised extraction (unmixing) of biochemical signatures. The unmixing is difficult due to the scarcity of biochemically pure regions in cells and also because autofluorescence is weak compared with signals from labelled cells, typically leading to low signal to noise ratio. Here, we solve the problem of unsupervised hyperspectral unmixing of cellular autofluorescence by introducing the Robust Dependent Component Analysis (RoDECA). This approach provides sophisticated and statistically robust quantitative biochemical analysis of cellular autofluorescence images. We validate our method on artificial images, where the addition of varying known level of noise has allowed us to quantify the accuracy of our RoDECA analysis in a way that can be applied to real biological datasets. The same unsupervised statistical minimisation is then applied to imaging of mouse retinal photoreceptor cells where we establish the identity of key endogenous fluorophores (free NADH, FAD and lipofuscin) and derive the corresponding molecular abundance maps. The pre-processing methodology of image datasets is also presented, which is essential for the spectral unmixing analysis, but mostly overlooked in the previous studies.

Fluorescence quenching of free and bound NADH in HeLa cells determined by hyperspectral imaging and unmixing of cell autofluorescence.

Carbonyl cyanide-p-trifluoro methoxyphenylhydrazone (FCCP) is a well-known mitochondrial uncoupling agent. We examined FCCP-induced fluorescence quenching of reduced nicotinamide adenine dinucleotide / nicotinamide adenine dinucleotide phosphate (NAD(P)H) in solution and in cultured HeLa cells in a wide range of FCCP concentrations from 50 to 1000µM. A non-invasive label-free method of hyperspectral imaging of cell autofluorescence combined with unsupervised unmixing was used to separately isolate the emissions of free and bound NAD(P)H from cell autofluorescence. Hyperspectral image analysis of FCCP-treated HeLa cells confirms that this agent selectively quenches fluorescence of free and bound NAD(P)H in a broad range of concentrations. This is confirmed by the measurements of average NAD/NADH and NADP/NADPH content in cells. FCCP quenching of free NAD(P)H in cells and in solution is found to be similar, but quenching of bound NAD(P)H in cells is attenuated compared to solution quenching possibly due to a contribution from the metabolic and/or antioxidant response in cells. Chemical quenching of NAD(P)H fluorescence by FCCP validates the results of unsupervised unmixing of cell autofluorescence.

Quantitative non-invasive cell characterisation and discrimination based on multispectral autofluorescence features.

Automated and unbiased methods of non-invasive cell monitoring able to deal with complex biological heterogeneity are fundamentally important for biology and medicine. Label-free cell imaging provides information about endogenous autofluorescent metabolites, enzymes and cofactors in cells. However extracting high content information from autofluorescence imaging has been hitherto impossible. Here, we quantitatively characterise cell populations in different tissue types, live or fixed, by using novel image processing and a simple multispectral upgrade of a wide-field fluorescence microscope. Our optimal discrimination approach enables statistical hypothesis testing and intuitive visualisations where previously undetectable differences become clearly apparent. Label-free classifications are validated by the analysis of Classification Determinant (CD) antigen expression. The versatility of our method is illustrated by detecting genetic mutations in cancer, non-invasive monitoring of CD90 expression, label-free tracking of stem cell differentiation, identifying stem cell subpopulations with varying functional characteristics, tissue diagnostics in diabetes, and assessing the condition of preimplantation embryos.

Functional hyperspectral imaging captures subtle details of cell metabolism in olfactory neurosphere cells, disease-specific models of neurodegenerative disorders.

Hyperspectral imaging uses spectral and spatial image information for target detection and classification. In this work hyperspectral autofluorescence imaging was applied to patient olfactory neurosphere-derived cells, a cell model of a human metabolic disease MELAS (mitochondrial myopathy, encephalomyopathy, lactic acidosis, stroke-like syndrome). By using an endogenous source of contrast subtle metabolic variations have been detected between living cells in their full morphological context which made it possible to distinguish healthy from diseased cells before and after therapy. Cellular maps of native fluorophores, flavins, bound and free NADH and retinoids unveiled subtle metabolic signatures and helped uncover significant cell subpopulations, in particular a subpopulation with compromised mitochondrial function. Taken together, our results demonstrate that multispectral spectral imaging provides a new non-invasive method to investigate neurodegenerative and other disease models, and it paves the way for novel cellular characterisation in health, disease and during treatment, with proper account of intrinsic cellular heterogeneity.

Oxidative stress, mitochondrial perturbations and fetal programming of renal disease induced by maternal smoking.

An adverse in-utero environment is increasingly recognized to predispose to chronic disease in adulthood. Maternal smoking remains the most common modifiable adverse in-utero exposure leading to low birth weight, which is strongly associated with chronic kidney disease (CKD) in later life. In order to investigate underlying mechanisms for such susceptibility, female Balb/c mice were sham or cigarette smoke-exposed (SE) for 6 weeks before mating, throughout gestation and lactation. Offspring kidneys were examined for oxidative stress, expression of mitochondrial proteins, mitochondrial structure as well as renal functional parameters on postnatal day 1, day 20 (weaning) and week 13 (adult age). From birth throughout adulthood, SE offspring had increased renal levels of mitochondrial-derived reactive oxygen species (ROS), which left a footprint on DNA with increased 8-hydroxydeoxyguanosin (8-OHdG) in kidney tubular cells. Mitochondrial structural abnormalities were seen in SE kidneys at day 1 and week 13 along with a reduction in oxidative phosphorylation (OXPHOS) proteins and activity of mitochondrial antioxidant Manganese superoxide dismutase (MnSOD). Smoke exposure also resulted in increased mitochondrial DNA copy number (day 1-week 13) and lysosome density (day 1 and week 13). The appearance of mitochondrial defects preceded the onset of albuminuria at week 13. Thus, mitochondrial damage caused by maternal smoking may play an important role in development of CKD at adult life.

L-Carnitine reverses maternal cigarette smoke exposure-induced renal oxidative stress and mitochondrial dysfunction in mouse offspring.

Maternal smoking is associated with metabolic disorders, renal underdevelopment, and a predisposition to chronic kidney disease in offspring, yet the underlying mechanisms are unclear. By exposing female Balb/c mice to cigarette smoke for 6 wk premating and during gestation and lactation, we showed that maternal smoke exposure induced glucose intolerance, renal underdevelopment, inflammation, and albuminuria in male offspring. This was associated with increased renal oxidative stress and mitochondrial dysfunction at birth and in adulthood. Importantly, we demonstrated that dietary supplementation of l-carnitine, an amino acid shown to increase antioxidant defenses and mitochondrial function in numerous diseases, in smoke-exposed mothers during pregnancy and lactation significantly reversed the detrimental maternal impacts on kidney pathology in these male offspring. It increased SOD2 and glutathione peroxidase 1, reduced ROS accumulation, and normalized levels of mitochondrial preprotein translocases of the outer membrane, and oxidative phosphorylation complexes I-V in the kidneys of mouse progeny after intrauterine cigarette smoke exposure. These findings support the hypothesis that oxidative stress and mitochondrial dysfunction are closely linked to the adverse effects of maternal smoking on male offspring renal pathology. The results of our study suggest that l-carnitine administration in cigarette smoke-exposed mothers mitigates these deleterious renal consequences.

Visible 532 nm laser irradiation of human adipose tissue-derived stem cells: effect on proliferation rates, mitochondria membrane potential and autofluorescence.

BACKGROUND AND OBJECTIVE: The photobiological effect of laser light on cells and tissues originates from light absorption by endogenous chromophores and hence it depends on the wavelength of light source and cell type. Earlier studies regarding the biostimulation effects of green laser light investigated a wide variety of cells but not adipose tissue-derived stem cells (ADSCS). In this study we reported the in vitro effect of 532-nm Nd:YAG laser on proliferation, mitochondrial activity of these mesenchymal stem cells (MSCs) on the autofluorescence emission at wavelengths associated with nicotinamide adenine dinucleotide (NADH) and flavoproteins. MATERIALS AND METHODS: ADSCS were exposed to 532 nm second harmonic generation laser light at moderate power density (0.153 W/cm(2)) for periods of 30, 45, 60, 180, and 300 seconds. Mitochondrial membrane potential was measured using JC1 stain and confocal laser scanning microscopy, cell proliferation rates, and cellular autofluorescence emission at 450 and 540 nm wavelengths were measured using micro plate spectrofluorometer 48 hours after irradiation. RESULTS: Shorter (30-60 seconds) exposure times led to significantly increased proliferation, attributed to increased mitochondrial activity (P < 0.05). At longer exposures we observed a significant decrease in proliferation and autofluorescence (P < 0.05). Strong correlation was observed between proliferation rates of cells and autofluorescence intensity. CONCLUSION: Our results show that autofluorescence of the respiratory chain components and key autofluorescent metabolites offers a non-invasive method to quantify cellular response to laser irradiation.