Applying the data fusion method to evaluation of the performance of two control signals in monitoring polarization mode dispersion effects in fiber optic links

With increasing distance and bit rate in fiber optic links the effects of polarization mode dispersion (PMD) have been highlighted. Since PMD has a statistical nature, using a control signal that can provide accurate information to dynamically tune a PMD compensator is of great importance. In this paper, we apply the data fusion method with the aim of introducing a method that can be used to evaluate more accurately the performance of control signals before applying them in a PMD compensation system. Firstly, the minimum and average degree of polarization (DOP_min and DOP_ave respectively) as control signals in monitoring differential group delay (DGD) for a system including all-order PMD are calculated. Then, features including the amounts of sensitivity and ambiguity in DGD monitoring are calculated for NRZ data format as DGD to bit time (DGD/T) varies. It is shown that each of the control signals mentioned has both positive and negative features for efficient DGD monitoring. Therefore, in order to evaluate features concurrently and increase reliability, we employ data fusion to fuse features of each control signal, which makes evaluating and predicting the performance of control signals possible, before applying them in a real PMD compensation system. Finally, the reliability of the results obtained from data fusion is tested in a typical PMD compensator

Clinical applications of non‐invasive multi and hyperspectral imaging of cell and tissue autofluorescence beyond oncology

Hyperspectral and multispectral imaging of cell and tissue autofluorescence employs fluorescence imaging, without exogenous fluorophores, across multiple excitation/ emission combinations (spectral channels). This produces an image stack where each pixel (matched by location) contains unique information about the sample's spectral properties. Analysis of this data enables access to a rich, molecularly specific data set from a broad range of cell-native fluorophores (autofluorophores) directly reflective of biochemical status, without use of fixation or stains. This non-invasive, non-destructive technology has great potential to spare the collection of biopsies from sensitive regions. As both staining and biopsy may be impossible, or undesirable, depending on the context, this technology great diagnostic potential for clinical decision making. The main research focus has been on the identification of neoplastic tissues. However, advances have been made in diverse applications—including ophthalmology, cardiovascular health, neurology, infection, assisted reproduction technology and organ transplantation.Jared M. Campbell, Saabah B. Mahbub, Abbas Habibalahi, Adnan Agha, Shannon Handley, Ayad G. Anwer, Ewa M. Goldy

Publisher Correction: Non-invasive assessment of exfoliated kidney cells extracted from urine using multispectral autofluorescence features (Scientific Reports, (2021), 11, 1, (10655), 10.1038/s41598-021-89758-4)

In the original version of this Article Saabah B. Mahbub and Long T. Nguyen were omitted as equally contributing authors. Additionally, Sonia Saad and Ewa M. Goldys were omitted as jointly supervised authors. This error has now been corrected in the PDF version of the Article; the HTML version was correct from the time of publication

Non-invasive, label-free optical analysis to detect aneuploidy within the inner cell mass of the preimplantation embryo

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.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

Emerging clinical applications in oncology for non‐invasive multi‐ and hyperspectral imaging of cell and tissue autofluorescence

OnlinePublHyperspectral and multispectral imaging of cell and tissue autofluorescence is an emerging technology in which fluorescence imaging is applied to biological materials across multiple spectral channels. This produces a stack of images where each matched pixel contains information about the sample's spectral properties at that location. This allows precise collection of molecularly specific data from a broad range of native fluorophores. Importantly, complex information, directly reflective of biological status, is collected without staining and tissues can be characterised in situ, without biopsy. For oncology, this can spare the collection of biopsies from sensitive regions and enable accurate tumour mapping. For in vivo tumour analysis, the greatest focus has been on oral cancer, whereas for ex vivo assessment head-and-neck cancers along with colon cancer have been the most studied, followed by oral and eye cancer. This review details the scope and progress of research undertaken towards clinical translation in oncology.Jared M. Campbell, Abbas Habibalahi, Shannon Handley, Adnan Agha, Saabah B. Mahbub, Ayad G. Anwer, Ewa M. Goldy

Automated pancreatic islet viability assessment for transplantation using bright-field deep morphological signature

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.Abbas Habibalahi, Jared M. Campbell, Stacey N. Walters, Saabah B. Mahbub, Ayad G. Anwer, Shane T. Grey, Ewa M. Goldy

Pancreatic Islet Viability Assessment Using Hyperspectral Imaging of Autofluorescence

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.Jared M. Campbell, Stacey N. Walters, Abbas Habibalahi, Saabah B. Mahbub, Ayad G. Anwer, Shannon Handley, Shane T. Grey, and Ewa M. Goldy

Non-destructive, label free identification of cell cycle phase in cancer cells by multispectral microscopy of autofluorescence

Background: Cell cycle analysis is important for cancer research. However, available methodologies have drawbacks including limited categorisation and reliance on fixation, staining or transformation. Multispectral analysis of endogenous cell autofluorescence has been shown to be sensitive to changes in cell status and could be applied to the discrimination of cell cycle without these steps. Methods: Cells from the MIA-PaCa-2, PANC-1, and HeLa cell lines were plated on gridded dishes and imaged using a multispectral fluorescence microscope. They were then stained for proliferating cell nuclear antigen (PCNA) and DNA intensity as a reference standard for their cell cycle position (G1, S, G2, M). The multispectral data was split into training and testing datasets and models were generated to discriminate between G1, S, and G2 + M phase cells. A standard decision tree classification approach was taken, and a two-step system was generated for each line. Results: Across cancer cell lines accuracy ranged from 68.3% (MIA-PaCa-2) to 73.3% (HeLa) for distinguishing G1 from S and G2 + M, and 69.0% (MIA-PaCa-2) to 78.0% (PANC1) for distinguishing S from G2 + M. Unmixing the multispectral data showed that the autofluorophores NADH, FAD, and PPIX had significant differences between phases. Similarly, the redox ratio and the ratio of protein bound to free NADH were significantly affected. Conclusions: These results demonstrate that multispectral microscopy could be used for the non-destructive, label free discrimination of cell cycle phase in cancer cells. They provide novel information on the mechanisms of cell-cycle progression and control, and have practical implications for oncology research.Jared M. Campbell, Abbas Habibalahi, Saabah Mahbub, Martin Gosnell, Ayad G. Anwer, Sharon Paton, Stan Gronthos and Ewa Goldy

Non-invasive real-time imaging of reactive oxygen species (ROS) using auto-fluorescence multispectral imaging technique: a novel tool for redox biology

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.Abbas Habibalahi, Mahdieh Dashtbani Moghari, Jared M. Campbell, Ayad G. Anwer, Saabah B. Mahbub, Martin Gosnell, Sonia Saad, Carol Pollock, Ewa M. Goldy

Unique Deep Radiomic Signature Shows NMN Treatment Reverses Morphology of Oocytes from Aged Mice

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-monthold) 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.Abbas Habibalahi, Jared M. Campbell, Michael J. Bertoldo, Saabah B. Mahbub, Dale M. Goss, William L. Ledger, Robert B. Gilchrist, Lindsay E. Wu, and Ewa M. Goldy