Fibre-based fluorescence-lifetime imaging microscopy: a real-time biopsy guidance tool for suspected lung cancer.

Lung cancer is the most common cause of cancer-related deaths worldwide. Early detection improves outcomes, however, existing sampling techniques are associated with suboptimal diagnostic yield and procedure-related complications. Autofluorescence-based fluorescence-lifetime imaging microscopy (FLIM), a technique which measures endogenous fluorophore decay rates, may aid identification of optimal biopsy sites in suspected lung cancer. Our fibre-based fluorescence-lifetime imaging system, utilising 488 nm excitation, which is deliverable via existing diagnostic platforms, enables real-time visualisation and lifetime analysis of distal alveolar lung structure. We evaluated the diagnostic accuracy of the fibre-based fluorescence-lifetime imaging system to detect changes in fluorescence lifetime in freshly resected ex vivo lung cancer and adjacent healthy tissue as a first step towards future translation. The study compares paired non-small cell lung cancer (NSCLC) and non-cancerous tissues with gold standard diagnostic pathology to assess the performance of the technique. Paired NSCLC and non-cancerous lung tissues were obtained from thoracic resection patients (N=21). A clinically compatible 488 nm fluorescence-lifetime endomicroscopy platform was used to acquire simultaneous fluorescence intensity and lifetime images. Fluorescence lifetimes were calculated using a computationally-lightweight, rapid lifetime determination method. Fluorescence lifetime was significantly reduced in ex vivo lung cancer, compared with non-cancerous lung tissue [mean ± standard deviation (SD), 1.79±0.40 vs. 2.15±0.26 ns, P<0.0001], and fluorescence intensity images demonstrated distortion of alveolar elastin autofluorescence structure. Fibre-based fluorescence-lifetime imaging demonstrated good performance characteristics for distinguishing lung cancer, from adjacent non-cancerous tissue, with 81.0% sensitivity and 71.4% specificity. Our novel fibre-based fluorescence-lifetime imaging system, which enables label-free imaging and quantitative lifetime analysis, discriminates ex vivo lung cancer from adjacent healthy tissue. This minimally invasive technique has potential to be translated as a real-time biopsy guidance tool, capable of optimising diagnostic accuracy in lung cancer.

A Novel Fit-Flexible Fluorescence Soft Imager: Tri-Sensing of Intensity, Fall-Time, and Life Profile.

Time-resolved fluorescence imaging techniques, like confocal fluorescence lifetime imaging microscopy, are powerful photonic instrumentation tools of modern science with diverse applications, including: biology, medicine, and chemistry. However, complexities of the systems, both at specimen and device levels, cause difficulties in quantifying soft biomarkers. To address the problems, we first aim to understand and model the underlying photophysics of fluorescence decay curves. For this purpose, we provide a set of mathematical functions, called "life models", fittable with the real temporal recordings of histogram of photon counts. For each model, an equivalent electrical circuit, called a "life circuit", is derived for explaining the whole process. In confocal endomicroscopy, the components of excitation laser, specimen, and fluorescence-emission signal as the histogram of photon counts are modelled by a power source, network of resistor-inductor-capacitor circuitry, and multimetre, respectively. We then design a novel pixel-level temporal classification algorithm, called a "fit-flexible approach", where qualities of "intensity", "fall-time", and "life profile" are identified for each point. A model selection mechanism is used at each pixel to flexibly choose the best representative life model based on a proposed Misfit-percent metric. A two-dimensional arrangement of the quantified information detects some kind of structural information. This approach showed a potential of separating microbeads from lung tissue, distinguishing the tri-sensing from conventional methods. We alleviated by 7% the error of the Misfit-percent for recovering the histograms on real samples than the best state-of-the-art competitor. Codes are available online.

Bayesian Statistical Analysis for Bacterial Detection in Pulmonary Endomicroscopic Fluorescence Lifetime Imaging.

Pneumonia, a respiratory disease often caused by bacterial infection in the distal lung, requires rapid and accurate identification, especially in settings such as critical care. Initiating or de-escalating antimicrobials should ideally be guided by the quantification of pathogenic bacteria for effective treatment. Optical endomicroscopy is an emerging technology with the potential to expedite bacterial detection in the distal lung by enabling in vivo and in situ optical tissue characterisation. With advancements in detector technology, optical endomicroscopy can utilize fluorescence lifetime imaging (FLIM) to help detect events that were previously challenging or impossible to identify using fluorescence intensity imaging. In this paper, we propose an iterative Bayesian approach for bacterial detection in FLIM. We model the FLIM image as a linear combination of background intensity, Gaussian noise, and additive outliers (labelled bacteria). While previous bacteria detection methods model anomalous pixels as bacteria, here the FLIM outliers are modelled as circularly symmetric Gaussian-shaped objects, based on their discrete shape observed through visual analysis and the physical nature of the imaging modality. A Hierarchical Bayesian model is used to solve the bacterial detection problem where prior distributions are assigned to unknown parameters. A Metropolis-Hastings within Gibbs sampler draws samples from the posterior distribution. The proposed method's detection performance is initially measured using synthetic images, and shows significant improvement over existing approaches. Further analysis is conducted on real optical endomicroscopy FLIM images annotated by trained personnel. The experiments show the proposed approach outperforms existing methods by a margin of +16.85% ( F1 ) for detection accuracy.

Fibre-optic based exploration of lung cancer autofluorescence using spectral fluorescence lifetime.

Fibre-optic based time-resolved fluorescence spectroscopy (TRFS) is an advanced spectroscopy technique that generates sample-specific spectral-temporal signature, characterising variations in fluorescence in real-time. As such, it can be used to interrogate tissue autofluorescence. Recent advancements in TRFS technology, including the development of devices that simultaneously measure high-resolution spectral and temporal fluorescence, paired with novel analysis methods extracting information from these multidimensional measurements effectively, provide additional insight into the underlying autofluorescence features of a sample. This study demonstrates, using both simulated data and endogenous fluorophores measured bench-side, that the shape of the spectral fluorescence lifetime, or fluorescence lifetimes estimated over high-resolution spectral channels across a broad range, is influenced by the relative abundance of underlying fluorophores in mixed systems and their respective environment. This study, furthermore, explores the properties of the spectral fluorescence lifetime in paired lung tissue deemed either abnormal or normal by pathologists. We observe that, on average, the shape of the spectral fluorescence lifetime at multiple locations sampled on 14 abnormal lung tissue, compared to multiple locations sampled on the respective paired normal lung tissue, shows more variability; and, while not statistically significant, the average spectral fluorescence lifetime in abnormal tissue is consistently lower over every wavelength than the normal tissue.

Erratum to "Optical Detection of Distal Lung Enzyme Activity in Human Inflammatory Lung Disease".

[This corrects the article DOI: 10.34133/2021/9834163.].

Rapid Point-of-Care Identification of Aspergillus Species in Microbial Keratitis.

Importance: Microbial keratitis (MK) is a common cause of unilateral visual impairment, blindness, and eye loss in low-income and middle-income countries. There is an urgent need to develop and implement rapid and simple point-of-care diagnostics for MK to increase the likelihood of good outcomes. Objective: To evaluate the diagnostic performance of the Aspergillus-specific lateral-flow device (AspLFD) to identify Aspergillus species causing MK in corneal scrape and corneal swab samples of patients presenting with microbial keratitis. Design, Setting, and Participants: This diagnostic study was conducted between May 2022 and January 2023 at the corneal clinic of Aravind Eye Hospital in Madurai, Tamil Nadu, India. All study participants were recruited during their first presentation to the clinic. Patients aged 15 years or older met the eligibility criteria if they were attending their first appointment, had a corneal ulcer that was suggestive of a bacterial or fungal infection, and were about to undergo diagnostic scrape and culture. Main Outcomes and Measures: Sensitivity and specificity of the AspLFD with corneal samples collected from patients with MK. During routine diagnostic scraping, a minimally invasive corneal swab and an additional corneal scrape were collected and transferred to aliquots of sample buffer and analyzed by lateral-flow device (LFD) if the patient met the inclusion criteria. Photographs of devices were taken with a smartphone and analyzed using a ratiometric approach, which was developed for this study. The AspLFD results were compared with culture reports. Results: The 198 participants who met the inclusion criteria had a mean (range) age of 51 (15-85) years and included 126 males (63.6%). Overall, 35 of 198 participants with corneal scrape (17.7%) and 17 of 40 participants with swab samples (42.5%) had positive culture results for Aspergillus species. Ratiometric analysis results for the scrape samples found that the AspLFD achieved high sensitivity (0.89; 95% CI, 0.74-0.95), high negative predictive value (0.97; 95% CI, 0.94-0.99), low negative likelihood ratio (0.12; 95% CI, 0.05-0.30), and an accuracy of 0.94 (95% CI, 0.90-0.97). Ratiometric analysis results for the swab samples showed that the AspLFD had high sensitivity (0.94; 95% CI, 0.73-1.00), high negative predictive value (0.95; 95% CI, 0.76-1.00), low negative likelihood ratio (0.07; 95% CI, 0.01-0.48), and an accuracy of 0.88 (95% CI, 0.73-0.96). Conclusions and Relevance: Results of this diagnostic study suggest that AspLFD along with the ratiometric analysis of LFDs developed for this study has high diagnostic accuracy in identifying Aspergillus species from corneal scrapes and swabs. This technology is an important step toward the provision of point-of-care diagnostics for MK and could inform the clinical management strategy.

Evaluation of Nafamostat as Chemoprophylaxis for SARS-CoV-2 Infection in Hamsters.

The successful development of a chemoprophylaxis against SARS-CoV-2 could provide a tool for infection prevention that is implementable alongside vaccination programmes. Nafamostat is a serine protease inhibitor that inhibits SARS-CoV-2 entry in vitro, but it has not been characterised for chemoprophylaxis in animal models. Clinically, nafamostat is limited to intravenous delivery and has an extremely short plasma half-life. This study sought to determine whether intranasal dosing of nafamostat at 5 mg/kg twice daily was able to prevent the airborne transmission of SARS-CoV-2 from infected to uninfected Syrian Golden hamsters. SARS-CoV-2 RNA was detectable in the throat swabs of the water-treated control group 4 days after cohabitation with a SARS-CoV-2 inoculated hamster. However, throat swabs from the intranasal nafamostat-treated hamsters remained SARS-CoV-2 RNA negative for the full 4 days of cohabitation. Significantly lower SARS-CoV-2 RNA concentrations were seen in the nasal turbinates of the nafamostat-treated group compared to the control (p = 0.001). A plaque assay quantified a significantly lower concentration of infectious SARS-CoV-2 in the lungs of the nafamostat-treated group compared to the control (p = 0.035). When taken collectively with the pathological changes observed in the lungs and nasal mucosa, these data are strongly supportive of the utility of intranasally delivered nafamostat for the prevention of SARS-CoV-2 infection.

FluoroPi Device With SmartProbes: A Frugal Point-of-Care System for Fluorescent Detection of Bacteria From a Pre-Clinical Model of Microbial Keratitis.

Purpose: Rapid and accurate diagnosis of microbial keratitis (MK) could greatly improve patient outcomes. Here, we present the development of a rapid, accessible multicolour fluorescence imaging device (FluoroPi) and evaluate its performance in combination with fluorescent optical reporters (SmartProbes) to distinguish bacterial Gram status. Furthermore, we show feasibility by imaging samples obtained by corneal scrape and minimally invasive corneal impression membrane (CIM) from ex vivo porcine corneal MK models. Methods: FluoroPi was built using a Raspberry Pi single-board computer and camera, light-emitting-diodes (LEDs), and filters for white-light and fluorescent imaging, with excitation and detection of bacterial optical SmartProbes: Gram-negative, NBD-PMX (exmax 488 nm); Gram positive, Merocy-Van (exmax 590 nm). We evaluated FluoroPi with bacteria (Pseudomonas aeruginosa and Staphylococcus aureus) isolated from ex vivo porcine corneal models of MK by scrape (needle) and CIM with the SmartProbes. Results: FluoroPi provides <1 µm resolution and was able to readily distinguish bacteria isolated from ex vivo models of MK from tissue debris when combined with SmartProbes, retrieved by both scrape and CIM. Single bacteria could be resolved within the field of view, with limits of detection demonstrated as 103 to 104 CFU/mL. Sample preparation prior to imaging was minimal (wash-free), and imaging and postprocessing with FluoroPi were straightforward, confirming ease of use. Conclusions: FluoroPi coupled with SmartProbes provides effective, low-cost bacterial imaging, delineating Gram-negative and Gram-positive bacteria directly sampled from a preclinical model of MK. Translational Relevance: This study provides a crucial stepping stone toward clinical translation of a rapid, minimally invasive diagnostic approach for MK.

Quantitative proteomics identifies tumour matrisome signatures in patients with non-small cell lung cancer.

Introduction: The composition and remodelling of the extracellular matrix (ECM) are important factors in the development and progression of cancers, and the ECM is implicated in promoting tumour growth and restricting anti-tumour therapies through multiple mechanisms. The characterisation of differences in ECM composition between normal and diseased tissues may aid in identifying novel diagnostic markers, prognostic indicators and therapeutic targets for drug development. Methods: Using tissue from non-small cell lung cancer (NSCLC) patients undergoing curative intent surgery, we characterised quantitative tumour-specific ECM proteome signatures by mass spectrometry. Results: We identified 161 matrisome proteins differentially regulated between tumour tissue and nearby non-malignant lung tissue, and we defined a collagen hydroxylation functional protein network that is enriched in the lung tumour microenvironment. We validated two novel putative extracellular markers of NSCLC, the collagen cross-linking enzyme peroxidasin and a disintegrin and metalloproteinase with thrombospondin motifs 16 (ADAMTS16), for discrimination of malignant and non-malignant lung tissue. These proteins were up-regulated in lung tumour samples, and high PXDN and ADAMTS16 gene expression was associated with shorter survival of lung adenocarcinoma and squamous cell carcinoma patients, respectively. Discussion: These data chart extensive remodelling of the lung extracellular niche and reveal tumour matrisome signatures in human NSCLC.

Environmentally sensitive photosensitizers enable targeted photodynamic ablation of Gram-positive antibiotic resistant bacteria.

Bacterial infections remain among the biggest challenges to human health, leading to high antibiotic usage, morbidity, hospitalizations, and accounting for approximately 8 million deaths worldwide every year. The overuse of antibiotics and paucity of antimicrobial innovation has led to antimicrobial resistant pathogens that threaten to reverse key advances of modern medicine. Photodynamic therapeutics can kill bacteria but there are few agents that can ablate pathogens with minimal off-target effects. Methods: We describe nitrobenzoselenadiazoles as some of the first environmentally sensitive organic photosensitizers, and their adaptation to produce theranostics with optical detection and light-controlled antimicrobial activity. We combined nitrobenzoselenadiazoles with bacteria-targeting moieties (i.e., glucose-6-phosphate, amoxicillin, vancomycin) producing environmentally sensitive photodynamic agents. Results: The labelled vancomycin conjugate was able to both visualize and eradicate multidrug resistant Gram-positive ESKAPE pathogens at nanomolar concentrations, including clinical isolates and those that form biofilms. Conclusion: Nitrobenzoselenadiazole conjugates are easily synthesized and display strong environment dependent ROS production. Due to their small size and non-invasive character, they unobtrusively label antimicrobial targeting moieties. We envisage that the simplicity and modularity of this chemical strategy will accelerate the rational design of new antimicrobial therapies for refractory bacterial infections.

Phase 2 randomised placebo-controlled trial of spironolactone and dexamethasone versus dexamethasone in COVID-19 hospitalised patients in Delhi.

BACKGROUND: In this phase 2 randomised placebo-controlled clinical trial in patients with COVID-19, we hypothesised that blocking mineralocorticoid receptors using a combination of dexamethasone to suppress cortisol secretion and spironolactone is safe and may reduce illness severity. METHODS: Hospitalised patients with confirmed COVID-19 were randomly allocated to low dose oral spironolactone (50 mg day 1, then 25 mg once daily for 21 days) or standard of care in a 2:1 ratio. Both groups received dexamethasone 6 mg daily for 10 days. Group allocation was blinded to the patient and research team. Primary outcomes were time to recovery, defined as the number of days until patients achieved WHO Ordinal Scale (OS) category ≤ 3, and the effect of spironolactone on aldosterone, D-dimer, angiotensin II and Von Willebrand Factor (VWF). RESULTS: One hundred twenty patients with PCR confirmed COVID were recruited in Delhi from 01 February to 30 April 2021. 74 were randomly assigned to spironolactone and dexamethasone (SpiroDex), and 46 to dexamethasone alone (Dex). There was no significant difference in the time to recovery between SpiroDex and Dex groups (SpiroDex median 4.5 days, Dex median 5.5 days, p = 0.055). SpiroDex patients had significantly lower D-dimer levels on days 4 and 7 (day 7 mean D-dimer: SpiroDex 1.15 µg/mL, Dex 3.15 µg/mL, p = 0.0004) and aldosterone at day 7 (SpiroDex 6.8 ng/dL, Dex 14.52 ng/dL, p = 0.0075). There was no difference in VWF or angiotensin II levels between groups. For secondary outcomes, SpiroDex patients had a significantly greater number of oxygen free days and reached oxygen freedom sooner than the Dex group. Cough scores were no different during the acute illness, however the SpiroDex group had lower scores at day 28. There was no difference in corticosteroid levels between groups. There was no increase in adverse events in patients receiving SpiroDex. CONCLUSION: Low dose oral spironolactone in addition to dexamethasone was safe and reduced D-dimer and aldosterone. Time to recovery was not significantly reduced. Phase 3 randomised controlled trials with spironolactone and dexamethasone should be considered. TRIAL REGISTRATION: The trial was registered on the Clinical Trials Registry of India TRI: CTRI/2021/03/031721, reference: REF/2021/03/041472. Registered on 04/03/2021.

Simultaneous Spectral Temporal Modelling for a Time-Resolved Fluorescence Emission Spectrum.

Innovations in complementary metal-oxide semiconductor (CMOS) single-photon avalanche diode (SPAD) technology has featured in the development of next-generation instruments for point-based time-resolved fluorescence spectroscopy (TRFS). These instruments provide hundreds of spectral channels, allowing the collection of fluorescence intensity and fluorescence lifetime information over a broad spectral range at a high spectral and temporal resolution. We present Multichannel Fluorescence Lifetime Estimation, MuFLE, an efficient computational approach to exploit the unique multi-channel spectroscopy data with an emphasis on simultaneous estimation of the emission spectra, and the respective spectral fluorescence lifetimes. In addition, we show that this approach can estimate the individual spectral characteristics of fluorophores from a mixed sample.

Computational Fluorescence Suppression in Shifted Excitation Raman Spectroscopy.

Fiber-based Raman spectroscopy in the context of in vivo biomedical application suffers from the presence of background fluorescence from the surrounding tissue that might mask the crucial but inherently weak Raman signatures. One method that has shown potential for suppressing the background to reveal the Raman spectra is shifted excitation Raman spectroscopy (SER). SER collects multiple emission spectra by shifting the excitation by small amounts and uses these spectra to computationally suppress the fluorescence background based on the principle that Raman spectrum shifts with excitation while fluorescence spectrum does not. We introduce a method that utilizes the spectral characteristics of the Raman and fluorescence spectra to estimate them more effectively, and compare this approach against existing methods on real world datasets.

Specific in situ immuno-imaging of pulmonary-resident memory lymphocytes in human lungs.

Introduction: Pulmonary-resident memory T cells (TRM) and B cells (BRM) orchestrate protective immunity to reinfection with respiratory pathogens. Developing methods for the in situ detection of these populations would benefit both research and clinical settings. Methods: To address this need, we developed a novel in situ immunolabelling approach combined with clinic-ready fibre-based optical endomicroscopy (OEM) to detect canonical markers of lymphocyte tissue residency in situ in human lungs undergoing ex vivo lung ventilation (EVLV). Results: Initially, cells from human lung digests (confirmed to contain TRM/BRM populations using flow cytometry) were stained with CD69 and CD103/CD20 fluorescent antibodies and imaged in vitro using KronoScan, demonstrating it's ability to detect antibody labelled cells. We next instilled these pre-labelled cells into human lungs undergoing EVLV and confirmed they could still be visualised using both fluorescence intensity and lifetime imaging against background lung architecture. Finally, we instilled fluorescent CD69 and CD103/CD20 antibodies directly into the lung and were able to detect TRM/BRM following in situ labelling within seconds of direct intra-alveolar delivery of microdoses of fluorescently labelled antibodies. Discussion: In situ, no wash, immunolabelling with intra-alveolar OEM imaging is a novel methodology with the potential to expand the experimental utility of EVLV and pre-clinical models.

Tri-mode optical biopsy probe with fluorescence endomicroscopy, Raman spectroscopy, and time-resolved fluorescence spectroscopy.

We present an endoscopic probe that combines three distinct optical fibre technologies including: A high-resolution imaging fibre for optical endomicroscopy, a multimode fibre for time-resolved fluorescence spectroscopy, and a hollow-core fibre with multimode signal collection cores for Raman spectroscopy. The three fibers are all enclosed within a 1.2 mm diameter clinical grade catheter with a 1.4 mm end cap. To demonstrate the probe's flexibility we provide data acquired with it in loops of radii down to 2 cm. We then use the probe in an anatomically accurate model of adult human airways, showing that it can be navigated to any part of the distal lung using a commercial bronchoscope. Finally, we present data acquired from fresh ex vivo human lung tissue. Our experiments show that this minimally invasive probe can deliver real-time optical biopsies from within the distal lung - simultaneously acquiring co-located high-resolution endomicroscopy and biochemical spectra.

An Inhaled Galectin-3 Inhibitor in COVID-19 Pneumonitis: A Phase Ib/IIa Randomized Controlled Clinical Trial (DEFINE).

Rationale: High circulating galectin-3 is associated with poor outcomes in patients with coronavirus disease (COVID-19). We hypothesized that GB0139, a potent inhaled thiodigalactoside galectin-3 inhibitor with antiinflammatory and antifibrotic actions, would be safely and effectively delivered in COVID-19 pneumonitis. Objectives: Primary outcomes were safety and tolerability of inhaled GB0139 as an add-on therapy for patients hospitalized with COVID-19 pneumonitis. Methods: We present the findings of two arms of a phase Ib/IIa randomized controlled platform trial in hospitalized patients with confirmed COVID-19 pneumonitis. Patients received standard of care (SoC) or SoC plus 10 mg inhaled GB0139 twice daily for 48 hours, then once daily for up to 14 days or discharge. Measurements and Main Results: Data are reported from 41 patients, 20 of which were assigned randomly to receive GB0139. Primary outcomes: the GB0139 group experienced no treatment-related serious adverse events. Incidences of adverse events were similar between treatment arms (40 with GB0139 + SoC vs. 35 with SoC). Secondary outcomes: plasma GB0139 was measurable in all patients after inhaled exposure and demonstrated target engagement with decreased circulating galectin (overall treatment effect post-hoc analysis of covariance [ANCOVA] over days 2-7; P = 0.0099 vs. SoC). Plasma biomarkers associated with inflammation, fibrosis, coagulopathy, and major organ function were evaluated. Conclusions: In COVID-19 pneumonitis, inhaled GB0139 was well-tolerated and achieved clinically relevant plasma concentrations with target engagement. The data support larger clinical trials to determine clinical efficacy. Clinical trial registered with ClinicalTrials.gov (NCT04473053) and EudraCT (2020-002230-32).

Deep learning-assisted co-registration of full-spectral autofluorescence lifetime microscopic images with H&E-stained histology images.

Autofluorescence lifetime images reveal unique characteristics of endogenous fluorescence in biological samples. Comprehensive understanding and clinical diagnosis rely on co-registration with the gold standard, histology images, which is extremely challenging due to the difference of both images. Here, we show an unsupervised image-to-image translation network that significantly improves the success of the co-registration using a conventional optimisation-based regression network, applicable to autofluorescence lifetime images at different emission wavelengths. A preliminary blind comparison by experienced researchers shows the superiority of our method on co-registration. The results also indicate that the approach is applicable to various image formats, like fluorescence in-tensity images. With the registration, stitching outcomes illustrate the distinct differences of the spectral lifetime across an unstained tissue, enabling macro-level rapid visual identification of lung cancer and cellular-level characterisation of cell variants and common types. The approach could be effortlessly extended to lifetime images beyond this range and other staining technologies.

Phototherapeutic Induction of Immunogenic Cell Death and CD8+ T Cell-Granzyme B Mediated Cytolysis in Human Lung Cancer Cells and Organoids.

Augmenting T cell mediated tumor killing via immunogenic cancer cell death (ICD) is the cornerstone of emerging immunotherapeutic approaches. We investigated the potential of methylene blue photodynamic therapy (MB-PDT) to induce ICD in human lung cancer. Non-Small Cell Lung Cancer (NSCLC) cell lines and primary human lung cancer organoids were evaluated in co-culture killing assays with MB-PDT and light emitting diodes (LEDs). ICD was characterised using immunoblotting, immunofluorescence, flow cytometry and confocal microscopy. Phototherapy with MB treatment and low energy LEDs decreased the proliferation of NSCLC cell lines inducing early necrosis associated with reduced expression of the anti-apoptotic protein, Bcl2 and increased expression of ICD markers, calreticulin (CRT), intercellular cell-adhesion molecule-1 (ICAM-1) and major histocompatibility complex I (MHC-I) in NSCLC cells. MB-PDT also potentiated CD8+ T cell-mediated cytolysis of lung cancer via granzyme B in lung cancer cells and primary human lung cancer organoids.

Fast and Robust Single-Exponential Decay Recovery From Noisy Fluorescence Lifetime Imaging.

Fluorescence lifetime imaging is a valuable technique for probing characteristics of wide ranging samples and sensing of the molecular environment. However, the desire to measure faster and reduce effects such as photo bleaching in optical photon-count measurements for lifetime estimation lead to inevitable effects of convolution with the instrument response functions and noise, causing a degradation of the lifetime accuracy and precision. To tackle the problem, this paper presents a robust and computationally efficient framework for recovering fluorophore sample decay from the histogram of photon-count arrivals modelled as a decaying single-exponential function. In the proposed approach, the temporal histogram data is first decomposed into multiple bins via an adaptive multi-bin signal representation. Then, at each level of the multi-resolution temporal space, decay information including both the amplitude and the lifetime of a single-exponential function is rapidly decoded based on a novel statistical estimator. Ultimately, a game-theoretic model consisting of two players in an "amplitude-lifetime" game is constructed to be able to robustly recover optimal fluorescence decay signal from a set of fused multi-bin estimates. In addition to theoretical demonstrations, the efficiency of the proposed framework is experimentally shown on both synthesised and real data in different imaging circumstances. On a challenging low photon-count regime, our approach achieves about 28% improvement in bias than the best competing method. On real images, the proposed method processes data on average around 63 times faster than the gold standard least squares fit. Implementation codes are available to researchers.