Single cell, Label free Characterisation of Human Mesenchymal Stromal cell Stemness and Future Growth Potential by Autofluorescence Multispectral Imaging.

AIM: To use autofluorescence multispectral imaging (AFMI) to develop a non-invasive assay for the in-depth characterisation of human bone marrow derived mesenchymal stromal cells (hBM-MSCs). METHODS: hBM-MSCs were imaged by AFMI on gridded dishes, stained for endpoints of interest (STRO-1 positivity, alkaline phosphatase, beta galactosidase, DNA content) then relocated and results correlated. Intensity, texture and morphological features were used to characterise the colour distribution of regions of interest, and canonical discriminant analysis was used to separate groups. Additionally, hBM-MSC lines were cultured to arrest, with AFMI images taken after each passage to investigate whether an assay could be developed for growth potential. RESULTS: STRO-1 positivity could be predicted with a receiver operator characteristic area under the curve (AUC) of 0.67. For spontaneous differentiation this was 0.66, for entry to the cell-cycle it was 0.77 and for senescence it was 0.77. Growth potential (population doublings remaining) was estimated with an RMSPE = 2.296. The Mean Absolute Error of the final prediction model indicated that growth potential could be predicted with an error of ± 1.86 doublings remaining. CONCLUSIONS: This non-invasive methodology enabled the in-depth characterisation of hBM-MSCs from a single assay. This approach is advantageous for clinical applications as well as research and stands out for the characterisation of both present status as well as future behaviour. The use of data from five MSC lines with heterogenous AFMI profiles supports potential generalisability.

AutoMitoNetwork: Software for analyzing mitochondrial networks in autofluorescence images to enable label-free cell classification.

High-resolution mitochondria imaging in combination with image analysis tools have significantly advanced our understanding of cellular function in health and disease. However, most image analysis tools for mitochondrial studies have been designed to work with fluorescently labeled images only. Additionally, efforts to integrate features describing mitochondrial networks with machine learning techniques for the differentiation of cell types have been limited. Herein, we present AutoMitoNetwork software for image-based assessment of mitochondrial networks in label-free autofluorescence images using a range of interpretable morphological, intensity, and textural features. To demonstrate its utility, we characterized unstained mitochondrial networks in healthy retinal cells and in retinal cells exposed to two types of treatments: rotenone, which directly inhibited mitochondrial respiration and ATP production, and iodoacetic acid, which had a milder impact on mitochondrial networks via the inhibition of anaerobic glycolysis. For both cases, our multi-dimensional feature analysis combined with a support vector machine classifier distinguished between healthy cells and those treated with rotenone or iodoacetic acid. Subtle changes in morphological features were measured including increased fragmentation in the treated retinal cells, pointing to an association with metabolic mechanisms. AutoMitoNetwork opens new options for image-based machine learning in label-free imaging, diagnostics, and mitochondrial disease drug development.

Ageing and Polypharmacy in Mesenchymal Stromal Cells: Metabolic Impact Assessed by Hyperspectral Imaging of Autofluorescence.

The impact of age on mesenchymal stromal cell (MSC) characteristics has been well researched. However, increased age is concomitant with increased prevalence of polypharmacy. This adjustable factor may have further implications for the functionality of MSCs and the effectiveness of autologous MSC procedures. We applied hyperspectral microscopy of cell autofluorescence-a non-invasive imaging technique used to characterise cytometabolic heterogeneity-to identify changes in the autofluorescence signals of MSCs from (1) young mice, (2) old mice, (3) young mice randomised to receive polypharmacy (9-10 weeks of oral therapeutic doses of simvastatin, metoprolol, oxycodone, oxybutynin and citalopram), and (4) old mice randomised to receive polypharmacy. Principal Component Analysis and Logistic Regression Analysis were used to assess alterations in spectral and associated metabolic characteristics. Modelling demonstrated that cells from young mice receiving polypharmacy had less NAD(P)H and increased porphyrin relative to cells from old control mice, allowing for effective separation of the two groups (AUC of ROC curve > 0.94). Similarly, cells from old polypharmacy mice were accurately separated from those from young controls due to lower levels of NAD(P)H (p < 0.001) and higher porphyrin (p < 0.001), allowing for an extremely accurate logistic regression (AUC of ROC curve = 0.99). This polypharmacy regimen may have a more profound impact on MSCs than ageing, and can simultaneously reduce optical redox ratio (ORR) and increase porphyrin levels. This has implications for the use of autologous MSCs for older patients with chronic disease.

Label-Free Assessment of Key Biological Autofluorophores: Material Characteristics and Opportunities for Clinical Applications.

Autofluorophores are endogenous fluorescent compounds that naturally occur in the intra and extracellular spaces of all tissues and organs. Most have vital biological functions - like the metabolic cofactors NAD(P)H and FAD+, as well as the structural protein collagen. Others are considered to be waste products - like lipofuscin and advanced glycation end products - which accumulate with age and are associated with cellular dysfunction. Due to their natural fluorescence, these materials have great utility for enabling non-invasive, label-free assays with direct ties to biological function. Numerous technologies, with different advantages and drawbacks, are applied to their assessment, including fluorescence lifetime imaging microscopy, hyperspectral microscopy, and flow cytometry. Here, the applications of label-free autofluorophore assessment are reviewed for clinical and health-research applications, with specific attention to biomaterials, disease detection, surgical guidance, treatment monitoring, and tissue assessment - fields that greatly benefit from non-invasive methodologies capable of continuous, in vivo characterization.

Improved effectiveness of X-PDT against human triple-negative breast cancer cells through the use of liposomes co-loaded with protoporphyrin IX and perfluorooctyl bromide.

In this study, we utilized X-ray-induced photodynamic therapy (X-PDT) against triple-negative breast cancer (TNBC) cells. To achieve this, we developed a liposome delivery system that co-loaded protoporphyrin IX (PPIX) and perfluorooctyl bromide (PFOB) in a rational manner. Low-dose X-ray at 2 Gy was employed to activate PPIX for the generation of reactive oxygen species (ROS), and the co-loading of PFOB provided additional oxygen to enhance ROS production. The resulting highly toxic ROS effectively induced cell death in TNBC. In vitro X-PDT effects, including intracellular ROS generation, cell viability, and apoptosis/necrosis assays in TNBC cells, were thoroughly investigated. Our results indicate that the nanocarriers effectively induced X-PDT effects with very low-dose radiation, making it feasible to damage cancer cells. This suggests the potential for the effective utilization of X-PDT in treating hypoxic cancers, including TNBC, with only a fraction of conventional radiotherapy.

Topological barrier to Cas12a activation by circular DNA nanostructures facilitates autocatalysis and transforms DNA/RNA sensing.

Control of CRISPR/Cas12a trans-cleavage is crucial for biosensor development. Here, we show that small circular DNA nanostructures which partially match guide RNA sequences only minimally activate Cas12a ribonucleoproteins. However, linearizing these structures restores activation. Building on this finding, an Autocatalytic Cas12a Circular DNA Amplification Reaction (AutoCAR) system is established which allows a single nucleic acid target to activate multiple ribonucleoproteins, and greatly increases the achievable reporter cleavage rates per target. A rate-equation-based model explains the observed near-exponential rate trends. Autocatalysis is also sustained with DNA nanostructures modified with fluorophore-quencher pairs achieving 1 aM level (<1 copy/µL) DNA detection (106 times improvement), without additional amplification, within 15 min, at room temperature. The detection range is tuneable, spanning 3 to 11 orders of magnitude. We demonstrate 1 aM level detection of SNP mutations in circulating tumor DNA from blood plasma, genomic DNA (H. Pylori) and RNA (SARS-CoV-2) without reverse transcription as well as colorimetric lateral flow tests of cancer mutations with ~100 aM sensitivity.

Towards label-free non-invasive autofluorescence multispectral imaging for melanoma diagnosis.

This study focuses on the use of cellular autofluorescence which visualizes the cell metabolism by monitoring endogenous fluorophores including NAD(P)H and flavins. It explores the potential of multispectral imaging of native fluorophores in melanoma diagnostics using excitation wavelengths ranging from 340 nm to 510 nm and emission wavelengths above 391 nm. Cultured immortalized cells are utilized to compare the autofluorescent signatures of two melanoma cell lines to one fibroblast cell line. Feature analysis identifies the most significant and least correlated features for differentiating the cells. The investigation successfully applies this analysis to pre-processed, noise-removed images and original background-corrupted data. Furthermore, the applicability of distinguishing melanomas and healthy fibroblasts based on their autofluorescent characteristics is validated using the same evaluation technique on patient cells. Additionally, the study tentatively maps the detected features to underlying biological processes. This research demonstrates the potential of cellular autofluorescence as a promising tool for melanoma diagnostics.

Lipid-Based Nanoparticles for Drug/Gene Delivery: An Overview of the Production Techniques and Difficulties Encountered in Their Industrial Development.

Over the past decade, the therapeutic potential of nanomaterials as novel drug delivery systems complementing conventional pharmacology has been widely acknowledged. Among these nanomaterials, lipid-based nanoparticles (LNPs) have shown remarkable pharmacological performance and promising therapeutic outcomes, thus gaining substantial interest in preclinical and clinical research. In this review, we introduce the main types of LNPs used in drug formulations such as liposomes, nanoemulsions, solid lipid nanoparticles, nanostructured lipid carriers, and lipid polymer hybrid nanoparticles, focusing on their main physicochemical properties and therapeutic potential. We discuss computational studies and modeling techniques to enhance the understanding of how LNPs interact with therapeutic cargo and to predict the potential effectiveness of such interactions in therapeutic applications. We also analyze the benefits and drawbacks of various LNP production techniques such as nanoprecipitation, emulsification, evaporation, thin film hydration, microfluidic-based methods, and an impingement jet mixer. Additionally, we discuss the major challenges associated with industrial development, including stability and sterilization, storage, regulatory compliance, reproducibility, and quality control. Overcoming these challenges and facilitating regulatory compliance represent the key steps toward LNP's successful commercialization and translation into clinical settings.

Terahertz imaging: a diagnostic technology for prevention of grass seed infestation.

One of the most significant problems the Australian sheep and lamb industry faces today is grass seed infestation (GSI), which occurs when seeds accumulate in the sheep's fleece and penetrate the skin, causing infection. Meat & Livestock Australia estimates that the yearly losses caused due to GSI are around AUD$47.5 M (in Australia alone). Here, we demonstrate that terahertz spectroscopy and imaging can be utilized for early detection of GSI. This is possible because terahertz waves can penetrate through sheep wool and have the appropriate wavelength for identifying the seed. Moreover, terahertz waves have non-invasive and non-ionizing properties and are ideal for non-contact and standoff detection. This work demonstrates that terahertz waves can be utilized for the early detection of seeds in the animal fleece or on the pelt as a precursor tool for the prevention of GSI.

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.

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

Hyperspectral 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.

Diagnostic and prognostic biomarkers for tubulointerstitial fibrosis.

Renal fibrosis is the final common pathophysiological pathway in chronic kidney disease (CKD) regardless of the underlying cause of kidney injury. Tubulointerstitial fibrosis (TIF) is considered to be the key pathological predictor of CKD progression. Currently, the gold-standard tool to identify TIF is kidney biopsy, an invasive method that carries risks. Non-invasive diagnostics rely on an estimation of glomerular filtration rate and albuminuria to assess kidney function, but these fail to diagnose early CKD accurately or to predict progressive decline in kidney function. In this review, we summarize the current and emerging molecular biomarkers that have been studied in various clinical settings and in animal models of kidney disease and that are correlated with the degree of TIF. We examine the potential of these biomarkers to diagnose TIF non-invasively and to predict disease progression. We also examine the potential of new technologies and non-invasive diagnostic approaches in assessing TIF. Limitations of current and potential biomarkers are discussed and knowledge gaps identified.

Bi-functional antibody-CRISPR/Cas12a ribonucleoprotein conjugate for improved immunoassay performance.

Protein conjugates are commonly used in biochemistry, including diagnostic platforms such as antibody-based immunoassays. Antibodies can be bound to a variety of molecules creating conjugates with desirable functions, particularly for imaging and signal amplification. Cas12a is a recently discovered programable nuclease with the remarkable capability to amplify assay signals due to its trans-cleavage property. In this study, we directly conjugated antibody with Cas12a/gRNA ribonucleoprotein without the loss of function in either constituent. The conjugated antibody was suitable for immunoassays and the conjugated Cas12a was capable of amplifying the signal produced in an immunosensor without the need to change the original assay protocol. We applied the bi-functional antibody-Cas12a/gRNA conjugate to successfully detect two different types of targets, a whole pathogenic microorganism, Cryptosporidium, and a small protein, cytokine IFN-γ, with sensitivity reaching one single microorganism per sample and 10 fg/mL for IFN-γ, respectively. With simple substitution of the antibody conjugated with the Cas12a/gRNA RNP, this approach can potentially be applied to increase sensitivity of a variety of immunoassays for a broad range of different analytes.

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.

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.

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-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.

Exfoliated Kidney Cells from Urine for Early Diagnosis and Prognostication of CKD: The Way of the Future?

Chronic kidney disease (CKD) is a global health issue, affecting more than 10% of the worldwide population. The current approach for formal diagnosis and prognostication of CKD typically relies on non-invasive serum and urine biomarkers such as serum creatinine and albuminuria. However, histological evidence of tubulointerstitial fibrosis is the 'gold standard' marker of the likelihood of disease progression. The development of novel biomedical technologies to evaluate exfoliated kidney cells from urine for non-invasive diagnosis and prognostication of CKD presents opportunities to avoid kidney biopsy for the purpose of prognostication. Efforts to apply these technologies more widely in clinical practice are encouraged, given their potential as a cost-effective approach, and no risk of post-biopsy complications such as bleeding, pain and hospitalization. The identification of biomarkers in exfoliated kidney cells from urine via western blotting, enzyme-linked immunosorbent assay (ELISA), immunofluorescence techniques, measurement of cell and protein-specific messenger ribonucleic acid (mRNA)/micro-RNA and other techniques have been reported. Recent innovations such as multispectral autofluorescence imaging and single-cell RNA sequencing (scRNA-seq) have brought additional dimensions to the clinical application of exfoliated kidney cells from urine. In this review, we discuss the current evidence regarding the utility of exfoliated proximal tubule cells (PTC), podocytes, mesangial cells, extracellular vesicles and stem/progenitor cells as surrogate markers for the early diagnosis and prognostication of CKD. Future directions for development within this research area are also identified.

Gallium Nanodroplets are Anti-Inflammatory without Interfering with Iron Homeostasis.

Gallium (Ga) compounds, as the source of Ga ions (Ga3+), have been historically used as anti-inflammatories. Currently, the widely accepted mechanisms of the anti-inflammatory effects for Ga3+ are rationalized on the basis of their similarities to ferric ions (Fe3+), which permits Ga3+ to bind with Fe-binding proteins and subsequently disturbs the Fe homeostasis in the immune cells. Here in contrast to the classic views, our study presents the mechanisms of Ga as anti-inflammatory by delivering Ga nanodroplets (GNDs) into lipopolysaccharide-induced macrophages and exploring the processes. The GNDs show a selective inhibition of nitric oxide (NO) production without affecting the accumulation of pro-inflammatory mediators. This is explained by GNDs disrupting the synthesis of inducible NO synthase in the activated macrophages by upregulating the levels of eIF2α phosphorylation, without interfering with the Fe homeostasis. The Fe3+ transferrin receptor-independent endocytosis of GNDs by the cells prompts a fundamentally different mechanism as anti-inflammatories in comparison to that imparted by Ga3+. This study reveals the fundamental molecular basis of GND-macrophage interactions, which may provide additional avenues for the use of Ga for anti-inflammatory and future biomedical and pharmaceutical applications.

A simple and versatile CRISPR/Cas12a-based immunosensing platform: Towards attomolar level sensitivity for small protein diagnostics.

Recent advances in CRISPR/Cas biosensing have led to impressive performance in sensitivity, specificity, and speed for nucleic acid detection. However, the remarkable advantages (such as universality, ultralow, attomolar detection limits) of CRISPR/Cas biosensing systems are limited in testing non-nucleic acid targets. Herein, by synthesizing a functional hybrid conjugate of antibody and single strand DNA oligonucleotide, we had successfully demonstrated the capability to integrate CRISPR/Cas12a-based signal amplification into different types of immunoassay schemes without the need for any additional recognition molecule or molecular synthesis during the detection process, thus providing a simple but generally applicable approach to improve the conventional immunoassays with attomolar sensitivity for small protein detections, referred as the CRISPR-based Universal Immunoassay Signal Enhancer (CRUISE). CRUISE is capable of being integrated into various immunoassays either through the primary antibody or the secondary antibody, with sensitivity down to 1 fg mL-1 (∼50 aM) and 6 logs of linear range for detecting cytokines, such as IFN-γ and EGFR, under 3-4 h. It has a 103 times higher sensitivity compared to a commercial IFN-γ ELISA kit, but uses the same experimental scheme. The same 1 fg mL-1 sensitivity along with 6 logs of linear range was realized for IFN-γ detection in human plasma samples. We are expecting that our CRUISE provides an alternative but simple, user-friendly and effective strategy for those who rely on the use of immunoassays, while struggling with the limits of their sensitivity or detection ranges.

Pterygium and Ocular Surface Squamous Neoplasia: Optical Biopsy Using a Novel Autofluorescence Multispectral Imaging Technique.

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.