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Understanding the molecular mechanisms of differentiation is important for regenerative medicine and developmental biology. This study aims to characterise the role of the glycolysis/oxidative phosphorylation balance as a driver of mesenchymal stem cell (MSC) differentiation. Cells were maintained in normal conditions or stimulated towards the MSC trilineage cell types over 21 days. Multispectral imaging of cell autofluorescence was applied as a non-invasive methodology to continuously image cultures in situ. Spectral signals for collagen, NAD(P)H, and flavins were unmixed. MSCs cultured under chondrogenic conditions exhibited increased collagen levels relative to controls. Following osteogenic induction, MSCs showed increased collagen levels relative to controls during the earlier stages of culture; however, control cells increased their collagen levels as they became confluent. MSCs cultured under adipogenic conditions exhibited lower levels of collagen than controls. The redox ratio (RR; NAD(P)H/flavins) immediately decreased during chondrogenesis, with this early effect persisting throughout the culture compared to control cells, which appeared to increase their RR, similar to osteogenesis. Adipogenesis resulted in a small increase in RR on day 2 relative to control cells, followed by a persistent decrease. Chondrogenic and adipogenic differentiation favoured oxidative phosphorylation, whereas osteogenesis and MSC overgrowth resulted in a glycolytic metabolism. Following consideration of these findings, as well as the diverse reports in the literature, it is concluded that neither enhanced oxidative phosphorylation nor glycolysis are fundamental to the canonical modes of differentiation, and researchers should avoid interpreting shifts as indicating differentiation.

Islets prepared for transplantation into type 1 diabetes patients are exposed to compromising intrinsic and extrinsic factors that contribute to early graft failure, necessitating repeated islet infusions for clinical insulin independence. A lack of reliable pre-transplant measures to determine islet viability severely limits the success of islet transplantation and will limit future beta cell replacement strategies. We applied hyperspectral fluorescent microscopy to determine whether we could non-invasively detect islet damage induced by oxidative stress, hypoxia, cytokine injury, and warm ischaemia, and so predict transplant outcomes in a mouse model. In assessing islet spectral signals for NAD(P)H, flavins, collagen-I, and cytochrome-C in intact islets, we distinguished islets compromised by oxidative stress (ROS) (AUC = 1.00), hypoxia (AUC = 0.69), cytokine exposure (AUC = 0.94), and warm ischaemia (AUC = 0.94) compared to islets harvested from pristine anaesthetised heart-beating mouse donors. Significantly, with unsupervised assessment we defined an autofluorescent score for ischaemic islets that accurately predicted the restoration of glucose control in diabetic recipients following transplantation. Similar results were obtained for islet single cell suspensions, suggesting translational utility in the context of emerging beta cell replacement strategies. These data show that the pre-transplant hyperspectral imaging of islet autofluorescence has promise for predicting islet viability and transplant success.

Islets transplanted for type-1 diabetes have their viability reduced by warm ischemia, dimethyloxalylglycine (DMOG; hypoxia model), oxidative stress and cytokine injury. This results in frequent transplant failures and the major burden of patients having to undergo multiple rounds of treatment for insulin independence. Presently there is no reliable measure to assess islet preparation viability prior to clinical transplantation. We investigated deep morphological signatures (DMS) for detecting the exposure of islets to viability compromising insults from brightfield images. Accuracies ranged from 98 % to 68 % for; ROS damage, pro-inflammatory cytokines, warm ischemia and DMOG. When islets were disaggregated to single cells to enable higher throughput data collection, good accuracy was still obtained (83-71 %). Encapsulation of islets reduced accuracy for cytokine exposure, but it was still high (78 %). Unsupervised modelling of the DMS for islet preparations transplanted into a syngeneic mouse model was able to predict whether or not they would restore glucose control with 100 % accuracy. Our strategy for constructing DMS' is effective for the assessment of islet pre-transplant viability. If translated into the clinic, standard equipment could be used to prospectively identify non-functional islet preparations unable to contribute to the restoration of glucose control and reduce the burden of unsuccessful treatments., Competing Interests: No conflict of interest., (© 2023 The Authors.)

The purpose of this study is to develop a deep radiomic signature based on an artificial intelligence (AI) model. This radiomic signature identifies oocyte morphological changes corresponding to reproductive aging in bright field images captured by optical light microscopy. Oocytes were collected from three mice groups: young (4- to 5-week-old) C57BL/6J female mice, aged (12-month-old) mice, and aged mice treated with the NAD+ precursor nicotinamide mononucleotide (NMN), a treatment recently shown to rejuvenate aspects of fertility in aged mice. We applied deep learning, swarm intelligence, and discriminative analysis to images of mouse oocytes taken by bright field microscopy to identify a highly informative deep radiomic signature (DRS) of oocyte morphology. Predictive DRS accuracy was determined by evaluating sensitivity, specificity, and cross-validation, and was visualized using scatter plots of the data associated with three groups: Young, old and Old + NMN. DRS could successfully distinguish morphological changes in oocytes associated with maternal age with 92% accuracy (AUC~1), reflecting this decline in oocyte quality. We then employed the DRS to evaluate the impact of the treatment of reproductively aged mice with NMN. The DRS signature classified 60% of oocytes from NMN-treated aged mice as having a 'young' morphology. In conclusion, the DRS signature developed in this study was successfully able to detect aging-related oocyte morphological changes. The significance of our approach is that DRS applied to bright field oocyte images will allow us to distinguish and select oocytes originally affected by reproductive aging and whose quality has been successfully restored by the NMN therapy.

In this study, differentiation of pterygium vs. ocular surface squamous neoplasia based on multispectral autofluorescence imaging technique was investigated. Fifty (N = 50) patients with histopathological diagnosis of pterygium (PTG) and/or ocular surface squamous neoplasia (OSSN) were recruited. Fixed unstained biopsy specimens were imaged by multispectral microscopy. Tissue autofluorescence images were obtained with a custom-built fluorescent microscope with 59 spectral channels, each with specific excitation and emission wavelength ranges, suitable for the most abundant tissue fluorophores such as elastin, flavins, porphyrin, and lipofuscin. Images were analyzed using a new classification framework called fused-classification, designed to minimize interpatient variability, as an established support vector machine learning method. Normal, PTG, and OSSN regions were automatically detected and delineated, with accuracy evaluated against expert assessment by a specialist in OSSN pathology. Signals from spectral channels yielding signals from elastin, flavins, porphyrin, and lipofuscin were significantly different between regions classified as normal, PTG, and OSSN (p < 0.01). Differential diagnosis of PTG/OSSN and normal tissue had accuracy, sensitivity, and specificity of 88 ± 6%, 84 ± 10% and 91 ± 6%, respectively. Our automated diagnostic method generated maps of the reasonably well circumscribed normal/PTG and OSSN interface. PTG and OSSN margins identified by our automated analysis were in close agreement with the margins found in the H&E sections. Such a map can be rapidly generated on a real time basis and potentially used for intraoperative assessment.

Study Question: Can label-free, non-invasive optical imaging by hyperspectral autofluorescence microscopy discern between euploid and aneuploid cells within the inner cell mass (ICM) of the mouse preimplantation embryo?, Summary Answer: Hyperspectral autofluorescence microscopy enables discrimination between euploid and aneuploid ICM in mouse embryos., What Is Known Already: Euploid/aneuploid mosaicism affects up to 17.3% of human blastocyst embryos with trophectoderm biopsy or spent media currently utilized to diagnose aneuploidy and mosaicism in clinical in vitro fertilization. Based on their design, these approaches will fail to diagnose the presence or proportion of aneuploid cells within the foetal lineage ICM of some blastocyst embryos., Study Design, Size, Duration: The impact of aneuploidy on cellular autofluorescence and metabolism of primary human fibroblast cells and mouse embryos was assessed using a fluorescence microscope adapted for imaging with multiple spectral channels (hyperspectral imaging). Primary human fibroblast cells with known ploidy were subjected to hyperspectral imaging to record native cell fluorescence (4-6 independent replicates, euploid n = 467; aneuploid n = 969). For mouse embryos, blastomeres from the eight-cell stage (five independent replicates: control n = 39; reversine n = 44) and chimeric blastocysts (eight independent replicates: control n = 34; reversine n = 34; 1:1 (control:reversine) n = 30 and 1:3 (control:reversine) n = 37) were utilized for hyperspectral imaging. The ICM from control and reversine-treated embryos were mechanically dissected and their karyotype confirmed by whole genome sequencing (n = 13 euploid and n = 9 aneuploid)., Participants/materials, Setting, Methods: Two models were employed: (i) primary human fibroblasts with known karyotype and (ii) a mouse model of embryo aneuploidy where mouse embryos were treated with reversine, a reversible spindle assembly checkpoint inhibitor, during the four- to eight-cell division. Individual blastomeres were dissociated from control and reversine-treated eight-cell embryos and either imaged directly or used to generate chimeric blastocysts with differing ratios of control:reversine-treated cells. Individual blastomeres and embryos were interrogated by hyperspectral imaging. Changes in cellular metabolism were determined by quantification of metabolic co-factors (inferred from their autofluorescence signature): NAD(P)H and flavins with the subsequent calculation of the optical redox ratio (ORR: flavins/[NAD(P)H + flavins]). Autofluorescence signals obtained from hyperspectral imaging were examined mathematically to extract features from each cell/blastomere/ICM. This was used to discriminate between different cell populations., Main Results and the Role of Chance: An increase in the relative abundance of NAD(P)H and decrease in flavins led to a significant reduction in the ORR for aneuploid cells in primary human fibroblasts and reversine-treated mouse blastomeres (P < 0.05). Mathematical analysis of endogenous cell autofluorescence achieved separation between (i) euploid and aneuploid primary human fibroblast cells, (ii) control and reversine-treated mouse blastomeres cells, (iii) control and reversine-treated chimeric blastocysts, (iv) 1:1 and 1:3 chimeric blastocysts and (v) confirmed euploid and aneuploid ICM from mouse blastocysts. The accuracy of these separations was supported by receiver operating characteristic curves with areas under the curve of 0.97, 0.99, 0.87, 0.88 and 0.93, respectively. We believe that the role of chance is low as mathematical features separated euploid from aneuploid in both human fibroblasts and ICM of mouse blastocysts., Large Scale Data: N/A., Limitations, Reasons for Caution: Although we were able to discriminate between euploid and aneuploid ICM in mouse blastocysts, confirmation of this approach in human embryos is required. While we show this approach is safe in mouse, further validation is required in large animal species prior to implementation in a clinical setting., Wider Implications of the Findings: We have developed an original, accurate and non-invasive optical approach to assess aneuploidy within the ICM of mouse embryos in the absence of fluorescent tags. Hyperspectral autofluorescence imaging was able to discriminate between euploid and aneuploid human fibroblast and mouse blastocysts (ICM). This approach may potentially lead to a new diagnostic for embryo analysis., Study Funding/competing Interest(s): K.R.D. is supported by a Mid-Career Fellowship from the Hospital Research Foundation (C-MCF-58-2019). This study was funded by the Australian Research Council Centre of Excellence for Nanoscale Biophotonics (CE140100003) and the National Health and Medical Research Council (APP2003786). The authors declare that there is no conflict of interest., (© The Author(s) 2021. Published by Oxford University Press on behalf of European Society of Human Reproduction and Embryology. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

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., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

Acanthamoeba Keratitis (AK) can lead to substantial vision loss and morbidity among contact lens wearers. Misdiagnosis or delayed diagnosis is a major factor contributing to poor outcomes of AK. This study aimed to assess the effect of two antibiotics and one anaesthetic drug used in the diagnosis and nonspecific management of keratitis on the autofluorescence patterns of Acanthamoeba and two common bacteria that may also cause keratitis. Acanthamoeba castellanii ATCC 30868, Pseudomonas aeruginosa ATCC 9027, and Staphylococcus aureus ATCC 6538 were grown then diluted in either PBS (bacteria) or ¼ strength Ringer's solution ( Acanthamoeba ) to give final concentrations of 0.1 OD at 660 nm or 10 4 cells/mL. Cells were then treated with ciprofloxacin, tetracycline, tetracaine, or no treatment (naïve). Excitation-emission matrices (EEMs) were collected for each sample with excitation at 270-500 nm with increments in 5 nm steps and emission at 280-700 nm at 2 nm steps using a Fluoromax-4 spectrometer. The data were analysed using MATLAB software to produce smoothed color-coded images of the samples tested. Acanthamoeba exhibited a distinctive fluorescence pattern compared to bacteria. The addition of antibiotics and anaesthetic had variable effects on autofluorescence. Tetracaine altered the fluorescence of all three microorganisms, whereas tetracycline did not show any effect on the fluorescence. Ciprofloxacin produced changes to the fluorescence pattern for the bacteria, but not Acanthamoeba . Fluorescence spectroscopy was able to differentiate Acanthamoeba from P. aeruginosa and S. aureus in vitro. There is a need for further assessment of the fluorescence pattern for different strains of Acanthamoeba and bacteria. Additionally, analysis of the effects of anti-amoebic drugs on the fluorescence pattern of Acanthamoeba and bacteria would be prudent before in vivo testing of the fluorescence diagnostic approach in the animal models.

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.

Radiodynamic therapy (RDT) is an emerging non-invasive anti-cancer treatment based on the generation of the reactive oxygen species (ROS) at the lesion site following the interaction between X-rays and a photosensitizer drug (PS). The broader application of RDT is impeded by the tumor-associated hypoxia that results in low availability of oxygen for the generation of sufficient amounts of ROS. Herein, a novel nanoparticle drug formulation for RDT, which addresses the problem of low oxygen availability, is reported. It consists of poly (lactic-co-glycolic acid) (PLGA) nanoparticles (NPs) co-loaded with a PS drug verteporfin (VP), and the clinically approved oxygen-carrying molecule, perfluorooctylbromide (PFOB). When triggered by X-rays (4 Gy), under both normoxic and hypoxic conditions, PLGA-VP-PFOB nanoconstructs (NCs) induced a significant increase of the ROS production compared with matching PLGA-VP nanoparticles. The RDT with NCs effectively killed ~60% of human pancreatic cancer cells in monolayer cultures, and almost completely suppressed the outgrowth of tumor cells in 2-weeks clonogenic assay. In a 3D engineered model of pancreatic cancer metastasis to the liver, RDT with NCs destroyed ~35% of tumor cells, demonstrating an exceptional efficiency at a tissue level. These results show that PLGA-VP-PFOB is a promising agent for RDT of deep-seated hypoxic tumors.

Detecting reactive oxygen species (ROS) that play a critical role as redox modulators and signalling molecules in biological systems currently requires invasive methods such as ROS -specific indicators for imaging and quantification. We developed a non-invasive, real-time, label-free imaging technique for assessing the level of ROS in live cells and thawed cryopreserved tissues that is compatible with in-vivo imaging. The technique is based on autofluorescence multispectral imaging (AFMI) carried out in an adapted fluorescence microscope with an expanded number of spectral channels spanning specific excitation (365 nm-495 nm) and emission (420 nm-700 nm) wavelength ranges. We established a strong quantitative correlation between the spectral information obtained from AFMI and the level of ROS obtained from CellROX staining. The results were obtained in several cell types (HeLa, PANC1 and mesenchymal stem cells) and in live kidney tissue. Additioanly,two spectral regimes were considered: with and without UV excitation (wavelengths > 400 nm); the latter being suitable for UV-sensitive systems such as the eye. Data were analyzed by linear regression combined with an optimization method of swarm intelligence. This allowed the calibration of AFMI signals to the level of ROS with excellent correlation (R = 0.84, p = 0.00) in the entire spectral range and very good correlation (R = 0.78, p = 0.00) in the limited, UV-free spectral range. We also developed a strong classifier which allowed us to distinguish moderate and high levels of ROS in these two regimes (AUC = 0.91 in the entire spectral range and AUC = 0.78 for UV-free imaging). These results indicate that ROS in cells and tissues can be imaged non-invasively, which opens the way to future clinical applications in conditions where reactive oxygen species are known to contribute to progressive disease such as in ophthalmology, diabetes, kidney disease, cancer and neurodegenerative diseases., Competing Interests: Declaration of competing interest Authors declare no conflict of interest., (Copyright © 2020 The Authors. Published by Elsevier B.V. All rights reserved.)

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.

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.

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.

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.