Biomedical Spectroscopy, Microscopy, and Imaging III

I will explore various facets of photonic quantum systems and their application in photonic quantum technologies. Firstly, I will focus into quantum foundations and by discuss quantum interference, a key element in photonic quantum technologies. I will highlight how the distinguishability and mixedness of quantum states influence the interference of multiple single photons – and demonstrate novel schemes for generating multipartite entangled quantum states. I will then address photonic quantum computing, specifically focusing on the building blocks of photonic quantum computers. This includes the generation of resource states essential for photonic quantum computing. I will then shift to photonic quantum networks, covering both their hardware aspects and showcasing quantum-network applications that extend beyond bi-partite quantum communication. Lastly, I will outline how photonic integration facilitates the scalability of these systems and discuss the associated challenges.

Joining the rich photophysics of organic light-emitting materials with the exquisite sensitivity of optical resonances to geometry and refractive index enables a plethora of devices with unusual and exciting properties. Examples from my team include biointegrated microlasers for real time sensing of cellular activity and long-term cell tracking, as well as the development of photonic implants with extreme form factors and wireless power supply that support thousands of individually addressable organic LEDs and thus allow optogenetic targeting of neurons deep in the brain with unprecedented spatial control. Very recently, by driving the interaction between excited states in organic materials and resonances in thin optical cavities into the strong coupling regime, we unlocked new tuning parameters which may play a crucial role in the next generation of TVs and computer displays to achieve even more saturated colour while retaining angle-independent emission characteristics.

We present our recent studies on on-the-fly Raman microscopy combined with multi-armed Bandits algorithm in reinforcement learning with spontaneous Raman measurements. This enables an several order acceleration of the measurements by designing and generating optimal illumination pattern “on the fly” during the measurements while keeping the accuracy of the discrimination. We will present the principle of the new microscopy and recent progress.

The current methodology used to diagnose drug-induced liver injury (DILI) is rather exhaustive and complex. Using non-destructive Raman spectroscopy for high-content liver cell screening may offer an improved system for early DILI detection. This study explores the potential of Raman spectroscopy in tracking the progression of drug-induced liver fibrosis by monitoring the hepatic stellate cell (HSC) activation. We observed that the loss of retinoid content during HSC activation is accompanied by Raman spectral changes, allowing for discrimination between quiescent and activated HSCs based on their Raman data. This suggests that Raman spectroscopy can be ideal in drug-induced liver fibrosis detection during the drug development process.

Our research investigates the potential of Raman spectroscopy combined with machine learning to enhance hemoglobinopathy screening. Hemoglobinopathies are common inherited diseases with serious health consequences. We use Raman spectroscopy to analyze hemoglobin fractions, enabling an accurate identification. By fine-tuning support vector machines (SVM) and fully connected neural networks (NN), we achieve test accuracies of 98.2% and 98.5%, respectively. Our research highlights the potential of Raman spectroscopy as an identification tool when combined with high-performance liquid chromatography. Furthermore, this detection approach can be easily miniaturized and integrated into microfluidics lab-on-chips.

Multiplex Coherent Anti-Stokes Raman Scattering (M-CARS) is an innovative nonlinear spectroscopic approach designed to characterize the vibrational modes of molecular structures. Coherent Raman scattering has been used for the characterization of biomedical targets for about 20 years and the multiplex aspect was introduced 10 years ago thanks to the use of a supercontinuum laser system. For each of these systems, the combination of a pump and a probe wave, driven by an external delay line, is however required to produce the vibrations. In the present work, we propose a new M-CARS system, free of the external delay line. A few-mode microstructured fiber enables merging both wave-packets (pump and supercontinuum) within a single waveguide. We showcase the capability of this system in generating hyperspectral images of biochemically active compounds. Curcumin I, the principal yellow compound isolated from Curcuma longa (Turmeric), is distinguishable by its multiple functional groups that display a nonlinear spectroscopic behavior.

Inappropriate management of plastic waste together with the large demand for plastic products endangered our environment with the problem of microplastic (MP) pollution. Microplastics may be released from blended polymers with complex structures making their analysis challenging. Here, we showcase the application of 3-D micro-Raman spectroscopy as a promising approach for the accurate study of blended microplastics (B-MPs). Moreover, the application of a line-shaped laser line focus is introduced to shorten the measurement time of 3-D Raman mapping from 56 to 2 hours, still acquiring valuable information about the morphology and concentration of polymers in B-MPs.

Raman spectroscopy is a powerful technique used across the life sciences to measure the molecular composition of a sample. There has been growing interest to miniaturize Raman imaging devices for endoscopic applications, however typically these probes are based on fiber bundles which increase the overall footprint of the probe. Recent works have shown that by applying a wavefront shaping technique, a single fiber may be transformed into a sub-cellular resolution Raman endoscope. However, a single probe both exciting and collecting the signal leads to an unavoidable large background signal from the fiber itself, masking large portions of the Raman signal from the sample. Here, we adopt a data-driven approach to de-convolve the background signal from the sample. In particular, we demonstrate that by applying PCA and machine learning techniques, sub-cellular resolution Raman images of pharmaceutical clusters can be made with supervision-free analysis.

We've established a nonlinear multimodal imaging system that incorporates stimulated Raman Scattering (SRS), multiphoton fluorescence (MPF), and second harmonic generation (SHG) to explore the connections between metabolic activities and the distribution of metabolites in cells and tissues. Furthermore, we've devised the Adam-based Pointillism Deconvolution (A-PoD) and Correlation Coefficient Mapping (CoCoMap) algorithms, enabling a deeper insight into the simultaneous recording and regulation of various metabolic processes within super-resolved images of nanoscale Regions of Interest (ROIs). In our pursuit of specifically identifying signals originating from distinct subcellular organelles, we've introduced a pioneering clustering algorithm known as Multi-SRS reference matching (Multi-SRM). This approach has the potential to improve early disease detection, prognosis, the evaluation of therapeutic effects, and our comprehension of the mechanisms underpinning aging and biomedicine.

Aging related biological mechanisms are often difficult to probe in situ without exogenous fluorophores. Here, we leverage label-free stimulated Raman scattering (SRS) microscopy to provide new insights into aging in C. elegans. We demonstrate multispectral SRS imaging of whole worms in vivo with quantitative chemical insights across different ages. We show that both lipid and protein synthesis and compartmentalization are associated with aging in worms. We additionally use SRS in combination with simultaneous two-photon fluorescence imaging to characterize the putatively aberrant protein accumulation. Moreover, we observe notable SRS image differences when worms are subjected to calorie restriction, suggesting a promising avenue towards understanding calorie-restriction’s enhancing effects on longevity when coupled to proteomic and metabolomic analysis.

In this study, we utilized holotomography to analyze prostate healthy (PNT2) and cancer (PC3) cells treated with glucose. After 48-hour incubation, distinct morphological differences were observed in cancer cells, including changes in lipid droplet volume, number, and refractive index. Raman spectroscopy confirmed the presence of these lipid droplets. Cancer cells exhibited larger and more numerous lipid droplets, with higher mean refractive-index, compared to healthy cells. The study achieved over 90% accuracy in discriminating between cell types, highlighting its potential in cancer diagnostics. The research contributes to biomedical spectroscopy, offering a valuable tool for understanding cancer cell morphology and enabling early and precise cancer diagnosis.

Implant associated infections can result in inflammatory conditions such as periimplantitis, that can ultimately lead to implant loss. This is caused by a large community of bacterial species. These bacteria form a multispecies biofilm on the tooth surface. Its composition can shift as it matures over time, the so-called pathogenic shift occurs once pathogens adhere to the biofilm. We developed a measurement protocol and analysis pipeline based on ATR-FTIR spectroscopy that is able to distinguish between different oral bacteria by detecting slight changes in protein expression. This can easily be done for single species samples with supervised learning algorithms like the k-nearest neighbour algorithm, with which we achieved a prediction accuracy of 99.8 %. Chemometric and deep learning approaches can streamline the process in distinguishing multispecies samples. This would be a step towards early detection of the pathogenic shift in oral biofilms and help avoiding diseases.

Osteoarthritis (OA), a degenerative joint disease presenting as loss of cartilage, is a leading cause of disability worldwide, increasingly with aging populations. Early detection is crucial for effective treatment since there is no definitive cure, yet, current assessment techniques fall short and rely on ionising radiation or invasive procedures. We report an application of multimodal “spectromics”, low-level abstraction data fusion of non-destructive NIR Raman and NIR-SWIR absorption spectroscopy, providing an enhanced, interpretable “fingerprint” for diagnosis of OA in human cartilage. Under multivariate statistical analyses and supervised machine learning, cartilage was classified with high precision and disease state predicted accurately. Discriminatory features within the spectromics fingerprint elucidated clinically relevant tissue components (OA biomarkers). Further, we have developed an automated goniometric 3D hyperspectral mapping setup, and characterised OA cartilage on whole human femoral heads post hip arthroplasty for spatially-resolved spectromics. These results lay foundation for minimally invasive, deeply penetrating, label-free, chemometric diagnosis of the hip.

Clinical evidence underscores the intricate interplay between the heart and kidneys, where dysfunction in one organ contributes to progressive failure of both. Using vibrational spectroscopy techniques, we demonstrated molecular changes in cardiac tissue post-uninephrectomy and ischemia-reperfusion in a rat cardiorenal syndrome (CS) model. It is now imperative to investigate whether structural changes in renal tissue following these two interventions are detectable. In response to the lack of renal-focused pharmacology for cardiorenal syndrome (CS), we also investigated the efficacy of the drug ProANP31-67, a peptide targeting cardiorenal complications that has already shown improvement in cardiac conditions following both pathologies. Micro-FTIR and micro-Raman spectroscopy were used to analyze kidney tissues, employing a dedicated R programming protocol to facilitate efficient analysis.

Probing volar side fingertip capillary beds with 830 nm light produces remission spectra containing Rayleigh and Raman scattered light and fluorescence, allowing continuous monitoring of intravascular plasma volume and hematocrit using the FRD-PVOH algorithm. During dialysis, Raman emission by polyatomic electrolytes i.e., phosphate tracks with fluid removal i.e., the change in intravascular plasma volume, measured in vivo with FRD-PVOH and in agreement with simultaneous hematocrit measurement of extracorporeal blood in the dialysis unit using the FDA approved CritLine. The variation of Raman features associated with urea in interstitial fluid and plasma suggests urea is involved in chemistry in the skin compartment i.e., in the extravascular space causing its clearance to lag the removal of electrolytes and water. Oral administration of Lasix removes more water than electrolytes relative to the proportions removed by dialysis leading to "solubility stress" reflected by Raman spectra. The various compartments in the human body do not drain at equal rates during dialysis. Real time spectroscopy-based monitoring could reduce the frequency of adverse events and thus improve outcomes.

Amid the SARS-CoV-2 pandemic, traditional virus detection methods like RT-qPCR face limitations in terms of infrastructure and processing time. This has spurred the development of agile diagnostic technologies, emphasizing non-invasive and rapid testing. Surface-Enhanced Raman Scattering (SERS) and Localized Surface Plasmon Resonance (LSPR) have emerged as promising alternatives. SERS, amplifying Raman signals through metal nanostructures, offers high sensitivity, high specificity, rapid response, qualitative and quantitative analysis enhanced by recent innovations like multiwell-array substrates. Integration with machine learning refines SERS's diagnostic capabilities, enabling rapid and accurate identification of SARS-CoV-2. LSPR, leveraging light-metal nanoparticle interactions, revolutionizes rapid viral detection, especially with the development of portable handheld devices. These devices enable real-time, on-site testing, proving crucial in managing infectious disease outbreaks. Their applications extend beyond SARS-CoV-2, holding potential for various pathogens.

Heart Failure with Preserved Ejection Fraction (HFpEF) is a severe medical condition. Concurrent pathologies linked with HFpEF create a complex scenario that contributes to structural and functional abnormalities in the heart and kidneys—the principal end organs affected by HFpEF. In this study, we assessed the effectiveness of a synergistic application of FTIR and Raman spectroscopy and multivariate/univariate statistical analyses to yield valuable pathophysiological insights in a rat model of heart failure. Peculiar biochemical differences were detected in the two organs demonstrating heightened sensitivity of these techniques towards the distinctive HFpEF phenotype.

Staphylococcus aureus (SA) is the most commonly isolated aetiological agent of osteomyelitis and periprosthetic joint infection (PJI), a major public health problem in western countries. Infections usually result from bacterial spread through fractures or implants and their treatment requires removal of infected tissue, thorough cleansing of the wound and administration of antibiotics directly to the site of infection. Despite a precise surgical procedure, removal and replacement of the medical device is often necessary when an infected prosthesis is involved. Here we discuss a methodology for investigating the impact of SA infection on the structure and chemical composition of bone tissue, based on the integration of Raman-Brillouin microspectroscopy (BRamS) and AFT-FTIR spectroscopy. Our aim is to improve the understanding of the effects of SA infection on bone tissue and to identify specific markers that can be used for the detection of damaged tissue.

Atopic dermatitis (AD) and psoriasis are the two most prevalent skin disorders, often assessed through subjective questionnaires or visual evaluations conducted by clinicians, which can be subject to interpersonal variations. This study aims to explore the distinctions between these skin conditions and healthy skin using a portable confocal Raman spectroscopy (CRS) system for objective assessment. Spectral measurements at 671 nm and 785 nm on 9 AD, 6 psoriasis, and 11 healthy subjects reveal lower water content in AD compared to psoriasis and healthy skin. Ceramide subclasses show disease-specific trends, distinguishing AD, and psoriasis. Cholesterol levels further differentiate these conditions, with lower concentrations in lesional AD and significantly higher concentrations in lesional psoriasis compared to healthy skin. These differences contribute to the objective differentiation of skin conditions aiding in thorough assessment and treatment monitoring. Furthermore, it offers valuable insights for developing targeted disease-specific topical treatments.

We present a compact and portable stimulated Raman scattering (SRS) imaging system capable of high speed, label-free imaging of cells and tissues. Our setup rapidly acquires multispectral datasets with high chemical specificity by scanning the spectral range of 700-3100 1/cm in just 100 ms, providing a tenfold increase in acquisition speed. It allowed to visualize cell nucleus and cytoplasm changes during drug induced cancer cell death. SRS offers distinct advantages, providing valuable insights into drug-cell interactions, cell morphology, and chemical changes without the interference of exogenous labels. The novel high-speed SRS systems allows rapid screening of drug effects on cancer cells.

Compressive Raman imaging has emerged as a promising technique to speed up chemical imaging by compressing the data during acquisition. Yet, current scanning imaging speed is fundamentally limited by the sensors pixel dwell times of at best 1µs. Here, we introduce a compressive Raman spectrometer layout equipped with a novel parallelized spatial acquisition using a single-photon avalanche detector array. We show imaging with pixel dwell times of <10µs using the otherwise weak spontaneous Raman effect, thereby unlocking video-rate imaging.

The problem of automated bacterial colony counting is a very relevant one, due to the high importance of bacteriological analysis. Moreover, this automated counting saves biologists time and improves the accuracy of their experiments. This paper has two aims: to investigate the challenges of automated bacterial colony counting, and to address the joint challenges of petri dish localization and bacterial colony reflections in such dishes. These reflections can seriously reduce the accuracy of automated bacterial colony counting. Therefore, the main aim of this paper is to show new methods for detecting and removing bacterial colony reflections in a petri dish by the use of computer vision. The experimental part of the paper contains the results, and descriptions of petri dish localization, and detecting and removing bacterial colony reflections. The proposed methods and the data obtained from these experiments significantly improve the accuracy of automated bacterial colony counting.

Total internal reflection fluorescence (TIRF) microscopy is a well-known technique allowing to confine the light close to the surface of a glass substrate. This axial confinement is based on the generation of evanescent waves. In TIRF microscopy however, there is no control of the light intensity in the transverse plane. Here, we propose a method to create evanescent patterns, which uses a fast-switching digital micro-mirror device to generate and scan an evanescent spot at multiple positions on the sample plane. In this way, patterns confined in the three dimensions of space can be produced in a fraction of second. This method would allow better spatial control in photo-activation or photo-conversion experiments in living cells, e.g. to target processes located at cell membranes.

Studying fiber architectures in tumor tissues is of great importance as the cancer cells interact with fiber structures in the Extracellular Matrix (ECM). Computational Scattered Light Imaging (ComSLI) represents an innovative, non-destructive approach to whole-slide imaging with micrometer resolution, uniquely capable of accurately unraveling the complex, intertwined fiber structures in biological tissues. So far, it has been mainly used to study highly interwoven nerve fiber architectures in brain tissues. In this study, we extend the application of ComSLI to visualize fibers in diverse tumor tissues, including oral squamous cell carcinoma (OSCC) and colorectal cancer.

Precision and stability in confocal microscopy are vital for maintaining image clarity and preventing misinterpretation of radiometric fluctuations as changes in fluorescence intensity within the sample. This study discusses a focus variation induced by an 810-nm continuous wave laser integrated into the optical path of an inverted confocal microscope with a 60x oil immersion objective. Activation or deactivation of the laser leads to a drift in the focus position towards lower or higher values of the vertical coordinate z, respectively. The maximum observed drift is 2.25 μm, occurring with a 40 mW laser power at the sample over a 600-second exposure time. The temporal behavior of the focus position follows exponential curves resembling temperature fluctuations associated with a heat source. Our analysis strongly indicates that the focus drift is attributable to the heating of the immersion oil.

Using machine learning techniques like deep neural networks for classifying plant diseases in images. Manual classification of plant diseases is time-consuming and requires trained professionals. Early detection of plant diseases is important for food security. Transfer learning with pre-trained neural networks is an effective approach for classifying plant diseases in images, with the potential to help scale up disease detection efforts.

We present a new architecture for frequency-modulation stimulated Raman Scattering (FM-SRS) that allows broadband background-free acquisitions. The system is based on a femtosecond laser oscillator (Stokes beam), used to pump a narrowband picosecond optical parametric oscillator (pump beam). Using an electro-optic modulator and polarizing beam splitter, we separate the broadband Stokes beam into two intensity-modulated Stokes beams that are spectrally filtered using a high-speed, narrowband acousto-optic tunable filter (AOTF) and a narrowband etalon. The two Stokes sub-beams and the pump beam are then recombined. By detecting the signal as the difference between in-Raman-resonance and off-Raman-resonance wavenumbers, we achieve background-free SRS measurements. Our scheme significantly simplifies and gives flexibility in selecting the pair of wavenumbers for FM-SRS, and allows background-free acquisitions from the fingerprint to the CH-stretch region of the Raman spectrum.

A promising alternative ultrasound detection scheme in photoacoustic imaging is the use of an optical camera to achieve massively parallelized data acquisition. For this purpose, the millions of pixels of common CMOS- or CCD-cameras are used to capture ultrasound-induced intensity modulations of a light field. Depending on the interaction mechanism in the propagation medium or at an interface, either projections or sectional images of the pressure field are recorded directly by means of free beam propagation or indirectly via optical fibers at certain times of wave propagation. Here we present the functionality of different experimental implementations and discusses their advantages and disadvantages in terms of achievable sensitivity, bandwidth, data structure, image acquisition rate, suitability for multimodal imaging, compactness of the implementation and gives an outlook on future new developments in this direction.

Conventional photoacoustic (PA) imaging suffers from visibility artefacts due to limitations in ultrasound transducer bandwidth, viewing angles, and the use of sparse arrays. PA fluctuation imaging (PAFI), exploiting the signal changes due to blood flow, compensates for these artefacts, at the cost of temporal resolution. Our study addresses this limitation employing a deep learning approach in which PAFI images serve as ground truths for training a 3D neural network to obtain real-time single-shot artefact-free images. Following a pre-training with simulated examples, a 3D-ResUnet network was trained with 90 PA chicken embryo vasculature volumes as input and corresponding PAFI as ground truths. Notably, inclusion of experimental data significantly improves predictions over simulation-only training, even accounting for transducer angular filtering. Furthermore, applying the same network exclusively trained in-ovo to predict the femoral artery in mice demonstrates the potential of this method for real-time, full-visibility multispectral PA imaging in vivo using sparse arrays.

Fabry-Perot tomographs have captured compelling photoacoustic images as they combine small element sizes with high acoustic sensitivity and a broad frequency response. A photoacoustic tomograph based on a sCMOS camera and a Fabry-Perot sensor with uniform optical thickness was developed. The influence of camera parameters on the e.g., spatial distribution of the acoustic sensitivity was evaluated. The imaging capabilities were demonstrated by capturing images of PA phantoms.

The development of photoacoustic contrast agents relies on the recovery of the photophysical properties from cuvette measurements. Photoacoustic signals are typically described using the Beer-Lambert law. In contrast agents with long excited state lifetimes, it is no longer valid. This is particularly noticeable at low concentrations and short cuvette pathlengths as acoustic propagation and detection effects become significant. A forward model is used to calculate time-resolved signals generated in a cuvette. The model is fitted to measured signals to recover absorption coefficients. The model will enable the characterization of new contrast agents by recovering the spatial distribution of thermalized energy.

Three-dimensional quantitative photoacoustic tomography (3D-QPAT) aims to recover tissue chromophore concentrations from multispectral images but is often hampered by the unknown light fluence and the transfer function of the scanner. Inversion schemes that use hybrid light transport and acoustic propagation models may be used to address this challenge. While model-based inversions have shown promising results in in silico and tissue phantom studies, limitations in accuracy arose from limited view artefacts. This study evaluated reconstruction methods such as time-reversal, maximum a posteriori, iterative least square and total variation to improve the accuracy of 3D-QPAT inversion techniques.

This work demonstrates the fabrication of high frequency ultrasound transducers, which is capable of sensing high frequency and broad bandwidth photoacoustic and ultrasound signals. For sensor film fabrication purposes, a piezoelectric composite polymer consisting of PVDF-TrFE (Polyvinylidene difluoride trifluoroethylene) and lab synthesized single crystal BSTO (Barium Strontium Titanate) nanofiller is developed. The piezoelectric efficiency after addition of BSTO is characterized using FTIR spectroscopy. The fabricated transducer is tested in the pulse echo mode and the central frequency is found to be 43 MHz with a bandwidth of 40 MHz (93% at -6dB). Photoacoustic signals of multiple frequencies are detected using the fabricated transducer. The high sensitivity and broad frequency spectrum of the transducer makes it a suitable candidate for high resolution photoacoustic and ultrasound imaging for biomedical imaging and nondestructive testing.

Optical cavities with nonlinear elements and delayed self-coupling are widely explored candidates for photonic reservoir computing (RC). For time series prediction applications that appear in many real-world problems, energy efficiency, robustness and performance are key indicators. With this contribution I want to clarify the role of internal dynamic coupling and timescales on the performance of a photonic RC system and discuss routes for optimization. By numerically comparing various delay-based RC systems e.g., quantum-dot lasers, spin-VCSEL (vertically emitting semiconductor lasers), and semiconductor amplifiers regarding their performance on different time series prediction tasks, to messages are emphasized: First, a concise understanding of the nonlinear dynamic response (bifurcation structure) of the chosen dynamical system is necessary in order to use its full potential for RC and prevent operation with unsuitable parameters. Second, the input scheme (optical injection, current modulation etc.) crucially changes the outcome as it changes the direction of the perturbation and therewith the nonlinearity. The input can be further utilized to externally add a memory timescale that is needed for the chosen task and thus offers an easy tunability of RC systems.

Programmable photonic circuits manipulate the flow of light on a chip by electrically controlling a set of tunable analog gates connected by optical waveguides. Light is distributed and spatially rerouted to implement various linear functions by interfering signals along different paths. A general-purpose photonic processor can be built by integrating this flexible hardware in a technology stack comprising an electronic monitoring and controlling layer and a software layer for resource control and programming. This processor can leverage the unique properties of photonics in terms of ultra-high bandwidth, high-speed operation, and low power consumption while operating in a complementary and synergistic way with electronic processors. This talk will review the recent advances in the field and it will also delve into the potential application fields for this technology including, communications, 6G systems, interconnections, switching for data centers and computing.

High-throughput screening Raman Spectroscopy (HTS-RS) is a breakthrough tool for clinical applications as it helps detect infection-associated cell activation. The technique captures the scattered light as a spectrum, presenting the sample's molecular signature. Machine learning methods are used to analyze the data confidently. Our study examined the influence of the interaction time between the virus and the cell on the spectral phenotype. HTS-RS has the potential to phenotype and identify cell activation associated with infections. This research could prove pivotal in developing effective strategies for diagnosing and treating the virus. Our findings provide a new information dimension of the cellular host response to virus infection.

In cancer research, accurate characterization of the tumor microenvironment (TME) is crucial for diagnosis and treatment. Desmoplasia, a cancer-specific fibrosis due to collagen overproduction, hinders treatment efficacy. This study introduces a fiber optic method utilizing adaptive focus light and fluorescence sensing to detect collagen in fresh cancer specimens. Conventional methods struggle with complex TME. Our approach, validated with diverse cancer samples, accurately identifies collagen. The method simplifies Atomic Force Microscopy, allowing multimodal characterization. This research revolutionizes cancer tissue analysis, providing a toolset for researchers and clinicians. Understanding collagen-cancer interplay opens avenues for targeted therapies, advancing cancer diagnostics and treatment.

Fluorescence lifetime imaging (FLI) has a major influence on our comprehension of biological systems, serving as a potent instrument for non-invasive exploration of biomolecular and cellular dynamics, both in vitro and in vivo. Its capacity to selectively target and multiplex diverse entities, coupled with heightened sensitivity and specificity, furnishes rapid and cost-effective insights. In this study, we conduct an extensive examination of the multiplexing capabilities of near-infrared (NIR) FLI within a scattering medium that emulates biological tissues. We introduce an efficient, novel Monte Carlo (MC) simulation approach that describe the scattering behavior of fluorescent photons within turbid media. Subsequent application of phasor analyses enabled multiplexing of distinct targets within a single image. Leveraging the cutting-edge single-photon avalanche diode (SPAD) time-gated camera, SPAD512S, to perform experimental wide-field FLI in the NIR regime, we present the multiplexing of dual targets within a single image to a depth of 1 cm within tissue-like phantoms.

We demonstrated the application of wavenumber-dependent DLS-OCT to measure both collective and self-diffusion coefficients in concentrated silica suspensions. Depending on the sample polydispersity, we successfully measured either long-time collective or long-time self-diffusion over a broad q-range using our custom-built OCT system. The measured collective diffusion coefficient shows excellent agreement with hard-sphere theory, providing further evidence for the dynamic scaling property. It also serves as an effective tool for accurately determining particle sizes in concentrated suspensions. We found the decoupling approximation to be highly effective in describing the first-order normalized autocovariance functions in both monodisperse and relatively polydisperse samples.

Optical elastography techniques utilise light to map the mechanical properties of tissue by measuring tissue deformation in response to an applied load. As is the case for most medical imaging techniques, the ongoing development of optical elastography is dependent on the parallel development of suitable tissue-mimicking phantoms. As optical elastography is still an emerging modality, existing phantoms are rudimentary and fail to capture the complex mechanical and structural heterogeneity of tissue. In this work, we present a methodology for the design of detailed tissue-mimicking phantoms that accurately represent the structures, surface profiles, and mechanical contrast of breast tissue specimens.

Genetically expressed fluorescent proteins are attractive contrast agents for molecular photoacoustic tomography. Pump-probe excitation, relying on the excitation of fluorescent proteins with a pump pulse and the subsequent stimulation of fluorescent emissions using a time-delayed probe pulse, is a simple experimental method that has been shown to provide fluorophore specific contrast. We developed a theoretical model to simulate photoacoustic pump probe signal generation in fluorophores. The results were validated experimentally in solutions of red fluorescent proteins and dyes using a photoacoustic spectrometer. The modeling results show good agreement with experimental data when scanning the pump wavelength across the absorption spectrum of fluorophores and when the pump probe time delay is varied. The results suggest that fluorescent proteins can be used as biosensors in PA imaging to measure biophysical parameters within tissue such as pH.

The capability of Raman spectroscopy for biological cell classification has been previously reported and is shown to be well suited for research purposes. The implementation in the clinical setting for such tasks as cell counting and pathology is prohibited by the required acquisition time due to the low scattering cross section present. In this work, we present a study on the capability of broadband coherent anti-Stokes Raman scattering (BCARS) using a fiber laser, for cell spectroscopy. The improvements in acquisition time afforded by the coherent process in BCARS could potentially allow for clinical implementation but there are known drawbacks in BCARS such as the quadratic concentration dependence and nonresonant background. We provide a comparison of the resulting spectra obtained from spontaneous Raman and BCARS of blood cells.

In this work, we present two approaches for Broadband coherent anti-stokes raman spectroscopy (BCARS) imaging for biomedical research applications. The first approach is optimized for fast microscopy. The setup combines a chirped pulse amplification laser with the generation of supercontinuum generation in YAG crystal and PCF fibers. The second approach uses a fiber-based optical parametric amplifier to enable fast-tuned narrow-band pulses for fast hyperspectral multi-modal image acquisition in endoscopy settings.

The high and unique demand for materials and their processing in nanophotonic technologies negatively impacts the environment. In this context, using biological systems as sources of photonic nanomaterial arose as an efficient alternative for light manipulation at the nanoscale, providing high-quality and sustainable materials for nanotechnological applications. Within the vast family of biomaterials suitable for photonic application, diatoms are one of the most attractive options due to their nanostructured biosilica exoskeleton – the frustule. Diatoms are a group of unicellular photosynthetic microalgae living in most aquatic and humid habitats. They naturally produce a species-dependant nano-porous pattern in their silicate-based frustule, which is easy to isolate and, therefore, easy to use as scaffolds for nanophotonic applications. In this paper, we introduce diatoms as a source of high-quality slab photonic crystals with incorporated micro-photoluminescence properties, which opens the doors for high-quality bio-produced emission devices.

We describe a new technique called widefield optical photothermal infrared (OPTIR) microscopy that selectively images chemical bonds in living biological and material samples. Our widefield OPTIR microscope captures images of a large specimen area in milliseconds at submicron spatial resolution. We use a pulsed visible (LED) light for high-throughput, widefield sensing of the transient photothermal effect induced by absorption of single mid-IR pulses of a pump laser. Our system can image a field of approximately 300×300 μm^2 at 10 ms frame rate using a 24.5 mega-pixel CMOS camera after two-fold binning. In our presentation, we will showcase the capabilities of our widefield OPTIR microscope by characterizing and imaging biological specimens and sub-micron polymer structures. Additionally, we will compare our results with those obtained using commercial infrared spectroscopy instruments. Furthermore, we will also demonstrate our latest development of our widefield OPTIR microscope for rapid multi-spectral imaging of biological samples.

Atopic dermatitis (AD), characterized by itchiness and inflammation, often results in increased skin thickness. Traditional treatments with topical corticosteroids may compound this effect. Addressing the need for accurate epidermal measurement and the slow acquisition times of previous methods, we developed a high-speed OCT system utilizing a 1.67 MHz FDML laser and a MEMS scanner, enabling 0.1-second scans that simplify patient compliance. The system has an axial resolution of 13-14 µm and a lateral resolution of 35 µm in air and a maximum field of view of 2.9 mm x 2.9 mm. An automatic segmentation algorithm was developed to delineate the skin surface and epidermal-dermal junction. Initial findings show the epidermal layer mostly ranges from 110 to 150 micrometers on dorsal hand skin, with a detailed epidermal thickness map for visualization of skin structure. A more efficient and patient-friendly approach is offered for evaluating AD severity and treatment response.

Astrocytes, integral glial cells within the CNS, have garnered increased attention for their pivotal roles in brain and spinal cord function, including information processing, neurotransmitter balance, and synaptic modulation. Their dysregulation has been implicated in various neurological disorders. Despite their acknowledged significance, our comprehension of astrocytes remains incomplete, particularly regarding their intricate morphology. Quantitative phase imaging (QPI) offers a novel approach, enabling label-free imaging of biological samples. In our study, we investigated the impact of silicon nanowire (SiNW) substrates on rat cortical astrocyte morphology, aiming to understand how this novel substrate influences astrocyte morphology compared to traditional glass substrates. The novelty lies in utilizing QPI to image astrocytes on nanostructured substrates such as SiNW substrates. Astrocytes cultured on SiNW substrates displayed a “star-like” morphology typically found in vivo. This leads to several opportunities for future studies such as quantification of morphological features of astrocytes on SiNW substrates.

Our previous studies have shown that laser speckle imaging with sensitive subpixel correlation analysis is able to detect bacterial growth activity and the pattern of colony growth. In the current study, we demonstrate the potential of this method to analyze fungal growth. We compare the characteristics of the signals obtained from bacteria and fungi. The obtained results will help to improve the parameters of the speckle image acquisition system and the signal processing algorithms useful for microorganism (both eukaryotic and prokaryotic) growth analyses and speeding up and facilitating microbiological diagnostics. Acknowledgments This research is funded by the Latvian Council of Science funded project “Dynamic laser speckle imaging for evaluation of fungal growth activity” (agreement No. lzp-2022/1-0247).

The study aimed to combine an X-ray micro-computed tomography (µCT), enhanced with convolutional neural network (CNN) assisted voxel classification and volume segmentation, with photoluminescence (PL) and micro-Raman spectroscopy (µ-RS) for tooth structural integrity assessment at the microcrack (MC) site, and verify this approach with extracted human teeth. The samples were first examined using an X-ray µCT and segmented with CNN to identify enamel, dentin, and cracks. Secondly, buccal and palatal teeth surfaces with MCs and sound areas were selected to obtain fluorescence spectra illuminated with laser exposure wavelengths: 325nm (CW) and 266nm (0.5 ns pulsed). Thirdly, chemical composition inside the crack and the difference from the good area were determined using µ-RS. The proposed approach revealed differences in the material along the crack line, with a variation in the hydroxyapatite crystals at the cracked versus sound area. This suggests a possible loss of tooth structural integrity at the MC site.

This work showcases an innovative approach to enhancing images acquired by a linear optical coherence tomography system. Multiple types of filtering combat image noise, while a sophisticated deconvolution algorithm based on maximum likelihood estimation compensates for degradation due to system blur. The results yield reduced noise, improved resolution and better structure visibility. Multiple examples of technical and biological samples demonstrate the significant increase in image quality.

This publication introduces a prototype of a fiber-based linear optical coherence tomography system (LOCT) that can be used for economical retinal screening in ophthalmology. The system uses standard off-the-shelf components to reduce production costs, complexity, and adjustment efforts while providing high-quality imaging of artificial retinal structures. We present the results of A- and B-scans of technical samples and an artificial eye model that was conducted to assess the system's performance regarding axial resolution, imaging depth, and dispersion compensation. The study's findings suggest that LOCT is a cost-effective solution for ophthalmology and shows great potential for monitoring the progression of retina-related diseases such as glaucoma or age-related macular degeneration.

The importance of bacteriological analysis is growing. The standard approach - disk-diffusion test allows estimating the susceptibility of bacteria to an antibiotic. It is possible to assess the susceptibility of bacteria by using the inhibition zone diameter. The bacteriologist usually measures the inhibition zone diameter manually. The proposed methods aim to perform automatic inhibition zone measurement that saves bacteriologists time and lowers patient treatment-related risks. The presented noncontact approach is based on computer vision technologies and addresses the challenges of image pre-processing, antibiotic disc localization, inhibition zones segmentation and measurement. The experimental part contains the results and comparisons of inhibition zones measurement methods. The experimental results show the advantages and disadvantages of existing methods. The existing approaches face the challenges of low contrast, overlapping zones, weak edges of a zone, non-circular inhibition shape and double inhibition zones. This work provides solutions to these problems.

We introduce a novel enhancement method for Optical Coherence Tomography (OCT) images, combining a "shifted steered mixture of experts" with an autoencoder for simultaneous denoising and super-resolution. This method uniquely avoids retraining for different scaling factors and allows on-the-fly adjustments for edge sharpening or defocusing. Tested on our in-house OCT dataset, it provides superior denoising and edge preservation without the computational burden of traditional deep learning approaches. Performance assessments demonstrate its advantage over current state-of-the-art methods in both subjective and objective (PSNR, perceptual metrics) evaluations.

Choroidal neovascularization (CNV) stands as the leading cause of vision loss in individuals afflicted with macular degeneration. Detecting CNV early and precisely determining its location accurately remains a formidable challenge with existing imaging methods. In this research, we introduce a multimodal triple imaging approach incorporating photoacoustic microscopy (PAM), optical coherence tomography (OCT), and fluorescence microscopy (FM) powered by gold nanoparticles to improve the precision of CNV diagnosis by harnessing the strengths of each modality. Nevertheless, conventional gold nanoparticle contrast agents have long-term safety concerns due to their accumulation in the liver and spleen. To overcome this issue, we have devised an innovative contrast agent founded on ultra-small gold nanospheres (GNS), which not only improves renal excretion but also enhances the contrast in PAM, OCT, and FM imaging. These ultra-small GNS were fabricated using pulsed laser ablation methods and subsequently surface-modified with CALNN peptides and cysteamine molecules, forming gold nanochains (GNC). Further surface conjugation with RGD peptides and indocyanine green (ICG) fluorescent dye

To investigate functionalized polymer-based nanoparticles (NPs) within cells and tissue, molecular selective microspectroscopic techniques are well suited. In our research we utilize confocal fluorescence microscopy and coherent anti-Stokes Raman scattering (CARS) microscopy to study the localization of NPs in cells and tissue. Raman spectroscopy in combination with two-dimensional correlation analysis (2DCOS) is utilized for the characterization of polymers, NPs, and drugs prior to its analysis in biological environments. Additionally, we utilize fluorescence lifetime microscopy (FLIM) to investigate the release of the encapsulated drug compounds of the functionalized NPs.

This approach offers continuous near-infrared fundus imaging while eliminating pupil contraction and minimizing reflections through polarized illumination. Utilizing a controllable screen to generate individual fixation stimuli allows for dynamic eye movements during imaging.The use of a high-pass filter improved the contrast perception of the fundus image and the direct tracking and storage of the relative eye position enables seamless data fusion with OCT measurements in the future. In addition, the system might detect visual field defects by identifying missing movements in the fundus image during recording.

The present study explores the capabilities that OCT has to serve for the study of biofilm deposition, eventually in conjunction with other investigation methods. The investigations were carried out on two directions: (i) to evaluate different methods for manufacturing dental prostheses, with the scope to identify a correlation between the design of the fixed partial prostheses pontic’s and the cytodiagnostic of the covering gingiva of the edentulous ridge and the gingival tissue around the abutments of the fix partial prostheses; (ii) to analyze the efficiency of different cleaning methods of dentistry equipment by assessing biofilm deposition in different types of tubes employed in such equipment (considering the inside of tubes of different diameters chosen for their long usage period in order to generate significant imaging results). In both studies an in-house developed Swept Source (SS) OCT system centered at 1300 nm, with an axial resolution of 15 µm was utilized. The results showed that OCT was capable to offer quantitative evaluations of the width of biofilm deposition, complementing for example (conventional) microbiology investigations.

This research focuses on enhancing the sensitivity of flow cytometry for the detection of extracellular vesicles (EVs), particularly those smaller than 100-200 nm. Extracellular vesicles play a crucial role in cellular waste disposal and intercellular communication, serving as disease biomarkers. Conventional flow cytometers often lack the required sensitivity for accurately detecting such small EVs. The study proposes the integration of Optical Coherence Tomography (OCT) with flow cytometry to improve sensitivity and reduce background signals. We first demonstrate the proof of concept with a commercial OCT system and conduct a comparative analysis alongside established commercial flow cytometers using a solution of polystyrene beads with known sizes. We determined the lower limit of detection (LOD) for the current OCT system to be a polystyrene bead of 600 nm diameter. Using this LOD, we describe potential hardware and software optical and fluidic modifications and calculate the potential LOD of an adapted OCT system to be the detection of an EV of 100 nm in diameter.

Since its inception in the 1980s, CARS microscopy has greatly advanced, offering label-free imaging of molecular distributions and incorporating ultra-short pulse lasers to facilitate modalities like SHG and TPEF. Translating these nonlinear imaging methods for endoscopic clinical diagnostics involves challenges such as reducing background noise, miniaturizing probes, optimizing light transmission, and advancing data processing. Addressing these, we introduce two nonlinear endoscopic systems: a multicore fiber-based probe with proximal remote scanning and a custom reconstruction algorithm that enhances image readability, and a double-core double clad fiber based endoscope that allows background-free laser delivery and sub cellular resolution imaging. These systems promise potential to meet clinical requirements by providing detailed imaging performance comparable to conventional nonlinear microscopy.

Diagnostic Raman spectroscopy offers a rapid approach for pathogen detection and phenotypic antimicrobial susceptibility testing. Following isolation, two common bloodstream infection bacteria, Escherichia coli and Staphylococcus aureus, were treated with appropriate antibiotic concentrations and analyzed using On-Chip Raman spectroscopy. Using photonic data analysis, the spectral signals are translated into antibiograms.

Two-photon excited fluorescence lifetime imaging microscopy (FLIM) is a powerful tool for visualizing minute changes in the chemical makeup of biological samples in a spatially resolved manner. Here, we present three applications of this concept from the field of biomedicine: (1) detection of tumor tissue in head and neck cancer samples, (2) sepsis characterization in mouse kidney tissue, and (3) characterization of the host response to influenza infection in lung tissue.

Identification of after-culture microbial species using a low-cost system would strongly benefit Low Income Countries, as traditional culture plate reading for species identification currently requires trained professionals and remains mostly manual, while more recent automated identification methods are costly. Our application is the label-free identification of uropathogens from bacterial colonies images directly on a non-chromogenic culture medium. With a frugal innovation mindset, we are developing a simple diagnostic system based on a filter wheel and a smartphone-driven camera. We are reporting performance of identification for true clinical samples and compare it to samples issued from a strain collection. Also, the capability to classify the five most-prevalent uropathogens (MPU) in presence of low-prevalent uropathogens (LPU) is evaluated. Two machine learning classification approaches are compared: classical or probabilistic support vector machine SVM (Platt method) using solely a 1-D vector of intensities without any morphological predictors at this stage. Some apparent shortcomings of the logistic regression approach are highlighted for the probabilistic SVM approach.

The evaluation of endogenous hyaluronic acid (HA) in the skin is important to understand the ageing process and analyze the effectiveness of dermocosmetics. Thus, this study evaluated the skin of 10 individuals between 51 and 65 years old, before and after the application of a dermocosmetic to stimulate HA, using the confocal Raman spectroscopy technique (Gen2 - Rivers Diagnostic). Six marker peaks for the presence of HA were observed: 1076, 1084, 1096, 1126, 1132 and 1208 cm-1, which allowed evidence of increases in their intensity after 30 and 60 days of use of the product, indicating an increase in the concentration of HA. Therefore, the in vivo assessment of cutaneous HA can facilitate the understanding of the role of dermocosmetics in skin aging, allowing for more effective treatments.

Pollen monitoring is helpful for medical purposes, weather or crop forecasting, and climate change analysis. Pollens are also important aeroallergens in veterinary medicine, causing atopic dermatitis in dogs and horses, and skin disease, seasonal rhinitis, and asthma in cats. In this study, we develop a lensless microscope and investigate its prospects for real-time detection and identification of six pollens relevant to veterinary medicine. By a systematic selection of a light source and imaging sensor, we present an optimal design for capturing digital holograms. Various light sources are studied based on parameters, including the source-object distance, temporal and spatial coherence, wavelength, and optical power for pulsed illumination. We propose an automated pollen detection and identification procedure based on a deep learning model for hologram classification. The proposed procedure is validated by an experienced pathologist using a conventional commercially available light microscope.

This study investigates an indirect measurement of the antibiotic susceptibility of Escherichia coli (E. coli) strain ATCC 25922 by analyzing sample background fluorescence at 455 nm excitation and 530 nm emission wavelengths. The study takes a practical approach by exposing the bacterial culture, suspended in Luria-Bertani (LB) broth medium, to various concentrations of ampicillin and analyzing the corresponding fluorescence intensities of the inhibitory and non-inhibitory ranges of antibiotic concentrations. The variations in fluorescence intensities indicate probable antibiotic sensitivity. The results are validated with gold standards such as the broth microdilution method.

Antimicrobial Resistant (AMR) fungal pathogens do not respond to conventional treatments, causing lethal infections, especially in immunocompromised people. The urgent need for fast, reliable, and highly specific diagnostic methods to control this silent pandemic is evident. Raman Spectroscopy methods have great potential for the detection and identification of microbial pathogens, either label- free or using specific Raman tags and probes. We are developing carbohydrate-based Raman probes aiming to achieve selective pathogen detection inspired by the first steps of infection, during which pathogens adhere to the surface of host cells via carbohydrate-protein interactions. Previously, our group identified an aromatic-core divalent galactoside, that mimics host cell carbohydrates and recognizes Candida albicans, a critical priority fungal pathogen. We have synthesized thiol-bearing derivatives of this compound, which are attached to the surface of gold nanoparticles to create novel Raman glycoprobes capable of binding C. albicans. These novel glycoprobes will be studied for the capture, detection and chemical imaging of fungal pathogens, such as C. albicans.

Hyperspectral imaging based on vibrational spectroscopy offers detailed, label-free chemical insights. Techniques like Near-Infrared (NIR), Fourier-Transform Infrared (FTIR), and Raman spectroscopy have bandwidth and speed constraints, particularly with water-based samples. Coherent Raman imaging, especially Stimulated Raman used with Second Harmonic Generation has recently been applied to produce virtual histology images without staining as well as segmenting cell features via spectral phasor analysis. Here we explore Broadband Coherent anti-Stokes Raman scattering (BCARS) as a method to produce high-quality virtually stained false-colour images of biological cells. BCARS enables fast, high-resolution (<10cm-1) and broad bandwidth (400-4000cm-1) bio-imaging but faces issues like low signal-to-noise ratio. This paper advances previous BCARS work, exploring new false-color image generation methods for diverse biological samples.

Optical Coherence Tomography (OCT) has become a ground-breaking method in medical imaging. This study covers all aspects of OCT, including its concepts, uses, and the considerable influence it has had on healthcare. OCT provides high-resolution, non-invasive imaging, making it a useful tool in ophthalmology, cardiology, dermatology, and other medical specialities. The underlying concepts underpinning OCT, such as its functioning principles, imaging modalities, and the most recent breakthroughs in the area were all looked at thoroughly. The study also goes through OCT's clinical uses, emphasizing its significance in the early identification, diagnosis, and monitoring of a variety of medical disorders. Furthermore, the potential future paths and advances in OCT technology that have the potential to improve diagnostic capabilities and widen clinical utility are also investigated. This thorough review seeks to offer a clearer knowledge of OCT's importance in modern medicine and to stimulate more study and development in this interesting topic.

Various biological surfaces are known to be covered by elaborated micro- and nano-structures, serving a number of functions (e.g. anti-reflective, structural coloration, anti-fouling, pro- or anti-adhesive, etc.) and inspiring numerous industrial applications. Recent years have witnessed a remarkable boost in research in this field. To a large extent, this boost owes to the increasing interdisciplinary of approaches being applied to the study of structured biosurfaces. Sciences as different as classical zoology and botany are inseminated with the advances in genetics and molecular biology; biologists collaborate more and more with nanotechnologists, materials scientists and engineers – all these contribute to the widening of the horizons of research on micro- and nano-structured biological surfaces, and to biomimetic and bioengineering applications of these surfaces in industry. We aim at ‘riding the wave’ of these developments with our proposal. In our talk I will present the main goal of the COST Action “Understanding interaction light – biological surfaces: possibility for new electronic materials and devices”.

Optoacoustic microscopy (OAM) is emerging as a promising biomedical imaging modality that integrates the advantages of optical and ultrasound imaging to visualize biological tissues with high sensitivity and spatial resolution. Our study demonstrated OAM with 3D Hessian filter segmentation to quantify microvasculatures within tumors in mice over 11 days. Analyzing diverse quantitative parameters such as vessel diameter, density, perfusion, and complexity yielded crucial insights into tumor growth dynamics and angiogenesis. Our result showed OAM and 3D Hessian filter segmentation's potential for rigorously quantifying tumor progression and guiding the development of precise cancer therapies.

The IR-ATR, IR transmittance and Raman spectroscopy techniques were used in monitoring the immobilization of newly synthesized compounds of (4-O-acetyl ferulato)triphenyltin(IV) and (fenoprofenato)tributyltin(IV), showing anticancer activity, on MCM-41 and SBA-15 mesoporous silica nanostructures. The IR analysis of the synthesized active compounds proved a monodentate binding of the carboxylate group to the Sn atom, using the splitting of the (COO) band in the IR spectrum. The IR-ATR spectra of the synthesized nanoparticles were used to check the porosity of the synthesized materials on the basis of the changes of the Si-OH(H2O) and Si-O stretching vibration band profile. The immobilized organotin(IV) compounds in both nanostructures were analyzed and the success of the immobilization was monitored and discussed through the changes in the IR and Raman spectra.

In this work, we present a method for analyzing the autofluorescence signal of an ex-vivo sample, obtained using a custom-made light-sheet microscope system capable of acquiring multispectral images thanks to a tunable filter. Once acquired, Principal Component Analysis (PCA) was employed for spectral unmixing of the captured images since no fluorescent markers are present in the sample.. This tool enables the determination of principal components (PCs) without prior knowledge of spectra. Thus, the extracted PCs can be associated with various specific tissues of the analyzed sample. This method represents a preliminary step toward establishing a non-invasive and label-free tissue characterization approach for both ex-vivo and in-vivo samples.

Fourier transform infrared microspectroscopy (FT-IR) is a nondestructive, information-rich, and label-free technique successfully applied for years in material science. The introduction of linear polarization enriches the technique with the possibility of studying the orientation of macromolecules. The extended four-polarization (4P) method, which enables the visualization of the macromolecule orientation regardless of the choice of the direction of polarization, was proposed by Hikima et al. for polymers [1]. The application of IR imaging with 4P on heterogeneous structure, human tissue microarrays, was presented for the first time by our team in 2020 [2], [3]. A deeper characterization of the sample structure is the next step. Simultaneous analysis of two bands of roughly perpendicular transition moment orientations was proposed by Lee in 2018 as a method of determining the orientation of the molecule in three-dimensional space [4]. The first application of “concurrent analysis” (4P-3D) to infrared spectromicroscopic data and obtaining orientation angles of a model polycaprolactone spherulite sample was presented by our team in 2022 [5]. The applicability of this method ranges from high-resolution, diffraction-limited FT-IR and Raman imaging to super-resolution O-PTIR imaging. The results obtained in these studies were very promising, we proved that this method can be easily applied not only to FT-IR but also to O-PTIR and Raman imaging. We now extend the applications to more complex biological systems and polymeric systems almost completely amorphic. Spatial, non-destructive orientation studies are expected to have a profound impact on materials and life sciences as a method of extracting previously unattainable information from complex systems. Grant No. 2018/31/D/ST4/01833; Project No. MRPO.05.01.00-12-013/15 [1] Y. Hikima, J. Morikawa, and T. Hashimoto, Macromolecules, vol. 44, no. 10, May 2011, doi: 10.1021/ma2003129. [2] K. Kosowska, P. Koziol, D. Liberda, and T. P. Wrobel, Clinical Spectroscopy, vol. 3, Dec. 2021, doi: 10.1016/j.clispe.2021.100013. [3] P. Koziol, D. Liberda, W. M. Kwiatek, and T. P. Wrobel, Analytical Chemistry, vol. 92, no. 19, Oct. 2020, doi: 10.1021/acs.analchem.0c02591. [4] Y. J. Lee, Optics Express, vol. 26, no. 19, p. 24577, Sep. 2018, doi: 10.1364/OE.26.024577. [5] P. Koziol, K. Kosowska, D. Liberda, F. Borondics, and T. P. Wrobel, JACS, 2022, doi 10.1021/jacs.2c05306.

Optical coherence elastography (OCE) is an imaging technique capable of mapping mechanical properties (such as elasticity) in 3-D and is emerging as a valuable tool in the study and potential intraoperative diagnosis of breast cancer due to mechanical contrast between healthy and malignant tissue. While the correlation between elevated elasticity in OCE and breast cancers has been well established, these studies have primarily focused on binary classifications of tissue as either malignant or benign, ignoring much of the heterogeneity present in breast tissue. In this work, we present a detailed assessment of the microstructures present in human breast tissue images acquired with OCE, identifying regions of interest that corresponded to invasive carcinomas, in situ carcinomas and benign tissue types. We also describe the unique morphological patterns present in each tissue type and provide a framework for the interpretation of breast cancer images acquired with OCE.

We quantify the precision and bias of dynamic light scattering optical coherence tomography (DLS-OCT) measurements of the diffusion coefficient and flow speed for first and second-order normalized autocovariance functions. For both diffusion and flow the measurement precision and accuracy are severely limited by correlations between the errors in the normalized autocovariance function. We demonstrate a method of mixing statistically independent normalized autocovariance functions at every time delay for removing these correlations. The mixing method reduces the uncertainty in the obtained parameters by a factor of two but has no effect on the standard error of the mean. We find that the precision in DLS-OCT is identical for different averaging techniques, but that the lowest bias is obtained by averaging the measured correlation functions before fitting the model parameters. With our correlation mixing method it is possible to quantify the precision in DLS-OCT and verify whether the Cramer-Rao bound is reached.

Atopic dermatitis (or eczema) is a common inflammatory skin condition treated mainly with steroid creams, which can lead to skin thinning. Although expensive, new drugs offer similar effectiveness with fewer side effects, necessitating a long-term skin impact assessment. Optical coherence tomography (OCT) offers non-invasive skin examination, but its popular 1300 nm wavelength limits imaging depth to about 1mm due to scattering. Shifting to 1600 nm can improve penetration depth due to reduced scattering. We aim to measure this improvement by building a dual band 1300 nm / 1600 nm OCT system, presenting initial skin imaging results with this system.

Atopic dermatitis (AD) often induces vasodilation, potentially impacting the velocity of blood flow within capillaries and vessels. This study aims to quantify these changes in blood flow velocities. We engineered a flow phantom infused with milk to simulate blood flow, utilizing a 1.67 MHz 1310 nm Fourier-domain mode-locked (FDML) OCT system for rapid acquisition and short-interscan imaging. Based on variable interscan time (VISTA) processing [1], we observed a correlation between the calculated decorrelation coefficients and the predetermined flow velocities, spanning a range from 0.16 mm/s to 30 mm/s. These findings enable us to explore our clinical hypotheses with in vivo tests. [1] Hwang, Yunchan, et al. "Retinal blood flow speed quantification at the capillary level using temporal autocorrelation fitting OCTA." Biomedical Optics Express 14.6 (2023): 2658-2677.

FFOCT (Full-field optical coherence tomography) is a high-resolution optical-sectioning imaging technique for biological tissues. Fractal analysis of the FFOCT image contrast is validated as a quantitative tool to measure the scattering properties of tissue. The defocus is one of the main factors that reduce FFOCT image contrast. This work applies the fractal analysis to model FFOCT image contrast. The contrast correction factor was proposed by considering tissue scattering and the system's defocused coherence transfer function. For each layer of the FFOCT image, the image is transformed to its original defocused amplitude and phase, then corrected with the proposed correction factor. The in-depth fractal dimension and EBCM (Edge-based contrast measurement) are introduced to validate the contrast enhancement quantitively. The result of the mouse organ demonstrated the correction effect quantitatively to a resolution limit, and it may guide a physics-informed interpretation of FFOCT and related augmented microscopy.

We present two neural networks: one capable of producing A-scans with only the second-order nonlinearities removed and another for creating A-scans with only the third-order nonlinearities removed. A spectrum free of nonlinearity (second or third order) can additionally be recovered using a third neural network, enabling the application of the nonlinearity-removing networks in a sequence. Our approach allows for either independent switching off of each order or the simultaneous removal of all orders, offering a tool for analysing the effects of each nonlinearity order individually or simply for performing all-depth, blind OCT data linearisation.

This study investigates the relationship between Pannexin 1 and refractive errors using a custom-made 1310nm OCT system, capable of imaging the whole eye. Prior research reported vision-related issues in Panx1 mutants but lacked insights into underlying mechanisms. Obtained OCT results establish a direct link between Pannexin1 (Pannexin 1a, Pannexin 1b, and Panx1DKO) and eye structure alterations, primarily manifesting as axial length elongation and negative RRE values, indicating myopia. Additionally, whole eye OCT imaging identifies several category of defects in the lens epithelium and aphakia. This research underscores Pannexin1's significance in visual system development and refractive errors, further emphasizing the diagnostic potential of optical coherence tomography in ophthalmology. Leveraging zebrafish as a model organism offers a unique opportunity to investigate genetic and cellular mechanisms influencing eye health, advancing our understanding of genetic factors and paving the way for further research and potential therapeutic interventions in the field of ophthalmology.

Optical diffraction tomography (ODT) is a powerful 3D imaging technique with immense potential in fields like cancer diagnosis and drug treatment. However, traditional ODT systems face limitations like the "missing cone" problem, affecting 3D resolution and cancer classification. To address this, fiber-optic dual-beam technology employs controlled laser beams for stable cell rotation, improving tomographic imaging. This improvement is further enhanced by a novel tomographic workflow that incorporates optical flow and deep learning, replacing manual interventions with automated processes. This novel method is validated by reconstructing 3D images of simulated cell phantoms, HL60 human cancer cells, and artificial cell phantoms. Its adaptability extends to diverse imaging techniques, promising advancements in cell biology, innovative therapeutics, and enhanced early-stage cancer diagnostics.

Feedback systems are crucial for a safe and accurate laser surgery. Optical coherence tomography (OCT) offers valuable feedback, including visual feedback and tissue differentiation. Detecting tissue type is important to avoid harming adjacent critical tissue, though water and blood in surgical settings may affect OCT’s precision. To address this, we integrated OCT and diffuse reflectance spectroscopy (DRS) for enhanced accuracy.This study employs a 1300 nm swept-source OCT with a 2x2 fiber coupler and double-clad fiber. DRS illumination is integrated, and data is collected using a double-clad fiber, analyzed by a spectrometer. The system’s performance is evaluated on various tissue types.

A multimodality visible to near-infrared multi-spectral optoacoustic microscopy (OAM) and optical coherence tomography (OCT) instrument is presented. The OAM channel was used for in-vivo imaging of five endogenous contrast agents in living tadpoles (Xenopus laevis), namely melanin, haemoglobin, collagen, glucose, and lipids. To accurately map absorbers, we developed a novel technique based on the assumption that each voxel in the 3D OAM image has only one chromophore contributing to the optoacoustic signal.

Sample handling is an important consideration when aiming for replicating in vivo conditions ex vivo for the sake of validating imaging protocols and identifying biomarkers of disease. We tested five different handling methods: Snap frozen in isopentane, directly frozen at -80 °C, slowly frozen in a cryobox with and without cryopreservation media, and formalin fixed. The samples were imaged using SD-OCT (1300nm) for qualitative and quantitative validation based on morphological and optical properties. All handling methods were compared in relation to representative histological image (HE staining), fresh tissue samples as well as each other. The results indicate a significant difference in the attenuation coefficient as well as morphological differences between the five different methods and support the hypothesis that proper sample handling is crucial for obtaining translatable results.

Atopic dermatitis is believed to be driven by abnormal skin barrier properties such as thickness and integrity of stratum corneum. As new generations of treatments for atopic dermatitis are under development, new optical imaging tools which enable to visualise the stratum corneum are thus in demand. Conventional optical coherence tomography (OCT) systems can readily image the epidermis and dermis but lacks the depth resolution to image stratum corneum, except at palmar skin sites. We report a Fourier domain visible light OCT system with a depth resolution of less than 1μm, and results on the stratum corneum thickness from imaging the hands of 12 healthy human subjects. We also investigated the effect of water on the stratum corneum properties.

Hyperspectral OCT imaging of retina within the visible-near-infrared (VIS-NIR) wavelengths could further improve the achievable axial resolution and harness the spectroscopic information as useful biomarker for retinal diseases. Previous efforts to develop OCT covering both visible and near-infrared wavelengths were hampered by the challenges in designing broadband spectrometer with adequate performance. Here, we described a design and implementation of a broadband spectrometer that could achieve spectral range of more than 450 nm with central wavelength around 680 nm. With it, we further demonstrate in vivo maging of mouse retina using a fiber-based OCT system.

In this work, the negative axicon probe is employed in an optical coherence phase microscopy (OCPM) system. The phase retrieval is done using conventional Hilbert transform for imaging and the Fresnel relation is used for refractive index measurement. In which, the reflected powers from air–glass and sample–glass interfaces are estimated using a fast-Fourier transform. Our OCPM system provides a phase sensitivity of ∼0.28 mrad and optical path length sensitivity of ∼23pm in air. This system is explored for phase imaging and refractive index measurement of the human male Leydig cells. A typical dimension of a Leydig cell from our system is ~19μm whereas the mean refractive index across a cell is found to be 1.3535. This system has potential to produce the phase imaging along with refractive index measurement of human male Leydig cell.

Designing Biomimetic Surfaces as Facilitator for a Cleaner Environment

Hyperspectral imaging (HSI) captures skin's spectral signatures, aiding noninvasive assessments. Efficient methods for estimating skin parameters like thickness and absorption are needed. Machine learning (ML) can reduce computational costs versus traditional methods like inverse Monte Carlo. This study explores using random Fourier features (RFF) with linear regression and neural networks (ANN) for parameter estimation from spectra. Compared to ANNs and 1D-CNNs using raw spectra, RFF-based models show similar accuracy with less time required. The RFF-ANN yielded the best performance, with a mean absolute error (MAE) of 0.0226, surpassing the 1D-CNN's MAE of 0.0284.

Forces inside cells play a fundamental role in cell behavior, for example in cancer cell migration. We focus on the vinculin protein which is involved in the stabilization of cell adhesion. Through fluorescence transfer (FRET), forces within vinculin can be measured with picoNewton sensitivity. We measure these internal forces while applying a calibrated external force with a laser-based optical tweezer via a microbead attached to the cell. Our most recent results using fibroblast cells show that the force applied with the optical tweezer induces the recruitment of vinculin and the formation of focal adhesions on the bead within a few minutes. Once the bead is attached to the cell, we record its trajectory and infer the force exerted by the cell. We correlate this force with the FRET efficiency of the force sensor.

In neuroscience, two photon scanning microscopy is commonly used to record brain activity in species that differ greatly in brain size and their properties and distributions of neurons. Accordingly, tailoring the properties of the imaging system to the experimental model in question is critical. These include adjustments in the size of the field-of-view, the shape and curvature of the scan-plane, or adjustment in excitation PSF sizes. Here, we report our progress to optimising these and other imaging parameters for high-signal-to-noise imaging of whole-brain neuronal activity in the large nervous system of Xenopus laevis tadpoles with comparable quality compared to what is currently possible in juvenile zebrafish.

We explore the application of structured vortex laser beams, or shaped light with orbital angular momentum (OAM), in the diagnosis of cell and cell cultures and the quantitative characterization of biological tissues. To examine the conservation of spin and orbital angular momenta during propagation, we constructed a Mach-Zehnder-like interferometer, equipped with a spatial light modulator (SLM), to generate Laguerre-Gaussian (LG) beams with varying momenta. As the LG beam traverses tissue samples, its interference with a reference plane wave is captured by a camera. Our findings reveal that the OAM of the LG beam is maintained through both normal and cancerous tissue samples, exhibiting a distinct phase shift – or twist of light – which is significantly more sensitive (up to ~1000 times) to changes in the tissue's refractive indices compared to conventional methods. We conclude that leveraging OAM in biomedical diagnosis presents exciting prospects for both groundbreaking biological research and enhanced clinical applications.

This study analyses the pH-dependent time resolved fluorescence of mCardinal and mNeptune, two red-shifted fluorescent proteins with applications in biomedical imaging. We utilized molecular dynamics (MD) simulations to illuminate the influence of water molecules on the proteins´ photophysical properties. In mCardinal, the average fluorescence lifetime markedly rises from 0.95 ns at pH 7.0 to 1.25 ns at pH 5.5. Conversely, mNeptune exhibits a constant fluorescence lifetime, showing no pH sensitivity. Through Decay-Associated Spectra and MD simulations, we correlated mCardinal’s pH-induced lifetime changes with its molecular properties. Despite both proteins being equally stabilized by hydrogen bonds, mCardinal’s chromophore formed more water contacts than mNeptune’s. Additionally, the chromophore’s interactions with specific amino acids varied between the two proteins, suggesting distinct differences in the excited state proton transfer as a crucial mechanism for pH sensitivity.

Spectroscopy is a key scientific technique to study the interaction of matter and electromagnetic radiation namely light. To make it possible, joint efforts are required where the integrated-circuit (IC) plays a major role. With today’s advances in CMOS technologies, increasing high-sensitivity and high-dynamic range becomes essential to cope with increasing demands of today’s applications. This paper proposes an InGaAs back-illuminated line-scan array of pixels adapted for new generations of spectroscopy imagers. It allows an effective 40-kHz frame-rate and 84dB dynamic range measured at low-gain for one frame and consumes only 16mA making it highly compatible with portable applications. The sensor proved a wide spectral range (0.9um to 2.1um) hence enabling application in the near infrared and short-wave domains.

Carbon nanoparticles (CNPs) are among the most extensively researched and utilized nanomaterials due to a combination of unique optical and electronic properties. This work proposes an inexpensive and time-efficient green synthesis method for synthesizing fluorescent CNPs from the leaf extracts of Murraya koenigii, following a microwave-assisted approach. This work highlights the successful synthesis of CNPs using a single organic solvent throughout the procedure, without the use of any hazardous chemicals. They offer great dispersibility with water, ranging from 20-30 nm in size, as confirmed by scanning electron microscopy (SEM), with the maximum height observed at 1.92 nm, as confirmed by atomic force microscopy (AFM). The derived CNPs exhibited bright red fluorescence emission at 663 nm, as investigated by optical characterization. The chemical functional groups were investigated and interpreted using Fourier transform infrared (FTIR) and X-ray diffraction (XRD) spectroscopy. Further, the antioxidant assay was performed on derived CNPs with different concentrations, which exhibited excellent free radical scavenging properties. Moreover, the anti-bacterial activity was performed

A wavelet-transform based denoising and random forest (RF) classification algorithm is utilized to analyze intrinsic fluorescence signals that can detect different grades (CIN-I, CIN-II and CIN-III) of cervical pre-cancer. Recorded fluorescence data are decomposed into corresponding wavelet components applying discrete wavelet transform that employs “coif3” mother wavelet function. The wavelet components are thresholded and the denoised data is reconstructed. A 3-fold cross-validation is used for the training of RF model. The calculated Receiver Operating Curves (ROC) of all grades exhibit lower false negatives and higher true positives and true negatives, which indicates good classification.

Infectious diseases are a major cause of human mortality and have also a huge impact on agriculture. Optimal methods to detect them would be non-invasive and without extensive sample-taking/processing. We developed a set of near infrared (NIR) fluorescent nanosensors and used them for remote fingerprinting of clinically important bacteria/viruses and to detect pathogen responses in plants [1,2,3]. The nanosensors are based on single-walled carbon nanotubes (SWCNTs) that fluoresce in the NIR optical tissue transparency window. To identify bacteria relevant for humans they were chemically tailored to detect released metabolites as well as specific virulence factors (lipopolysaccharides, siderophores, DNases, proteases) and integrated into functional hydrogel arrays with different sensors. These hydrogels are able to distinguish important bacteria (Staphylococcus aureus, Escherichia coli, …) by NIR imaging. Similar sensors allowed us to visualize the chemical defense of plants in response to pathogens and to detect the corona virus. In summary, such nanosensors in combination with NIR imaging concepts demonstrate huge potential for precise monitoring of pathogens.

Confocal microscopy is an essential tool in many academic disciplines due to its intrinsic sectioning capability. The combination with time-resolved single photon detectors and time-correlated single photon counting (TCSPC) devices has established it as the leading platform for time resolved investigation methods such as fluorescence lifetime imaging (FLIM). Recently, high-performance SPAD-arrays featuring few tens of pixels have become available. In this work we present the two central hardware building blocks: PicoQuant’s latest multi-channel TCSPC device and a cooled high-performance 23-pixel SPAD-array developed jointly with Pi Imaging Technologies. We discuss how these open up new possibilities in time-resolved confocal microscopy.

Miniaturized fluorescence microscope (Miniscope) emerges as a powerful tool for observing neural activities in unrestrained animals. However, its simplified optical design leads to optical distortions and uneven illumination, resulting in poor spatial resolution. Herein, we propose a Continuous Space-Varying Deconvolution (CSV-Deconv) algorithm for image enhancement. By calibrating the point spread function (PSF) through varying illumination and orientation, CSV-Deconv achieves a notable 3.2-fold increase in contrast-to-noise ratio. The algorithm exhibits robust generalizability across diverse Miniscope prototypes, showcasing its efficacy in rectifying spatial distortions. This innovation holds promise for advancing the precision and throughput of neural imaging in freely moving subjects.

Numerous biological surfaces exhibit intricate micro- and nano-structures, which fulfill various functions such as anti-reflective properties, structural coloration, anti-fouling capabilities, and pro- or anti-adhesive characteristics. These features have inspired a plethora of industrial applications. In recent years, there has been a significant surge in research in this domain, largely attributable to the growing interdisciplinary nature of the approaches applied to the investigation of structured biosurfaces. The convergence of classical zoology and botany with advances in genetics and molecular biology is noteworthy, as biologists increasingly collaborate with nanotechnologists, materials scientists, and engineers. This collaborative effort contributes significantly to expanding the horizons of research on micro- and nano-structured biological surfaces, fostering biomimetic and bioengineering applications in various industries (Fig.1). Our proposal seeks to capitalize on this momentum and align with the current developments in the field. The primary objective of the COST Action titled "Understanding interaction light – biological surfaces: possibility for new electronic materials and devices" is to unite scientists from diverse disciplines within this dynamic research realm. The emphasis of this collaborative effort is placed on exploring the photonic effects arising from the nano- and micro-structuring of biological surfaces, along with their potential bionic applications. Through our consortium, we aim to facilitate cross-inspiration among participants from distinct research fields, fostering an environment conducive to innovation in research and eventual industrial advancements. Our initiative seeks to ride the wave of these scientific developments, propelling forward the exploration of the intricate world of micro- and nano-structured biological surfaces.

We present a investigations of dental ceramics using in-house developed swept source (SS) optical coherence tomography (OCT) systems. The issue is related to the loss of calibration of ovens utilized for the fabrication of dental crowns. In the first study [http://dx.doi.org/10.3390/app7060552], metal-ceramics crowns were manufactured, in five study groups, with five maximum sintering temperatures: a normal one, two lower levels and two upper levels (up to +50ºC with regard to normal). OCT B- and C-scans were obtained, and qualitative rules-of-thumb were extracted to assess the oven temperature level by observing ceramic grains bellow the level of the tooth-shaped crowns. The second study [https://doi.org/10.3390/ma12060947] moved to a quantitative assessment of the calibration loss of the ovens. A second type of material (for all-ceramic crowns) was considered, and three levels of its specific temperature were tested. For both ceramics reflectivity curves were obtained from OCT C-scans. These analyses demonstrated that there is (only) one parameter consistent with the shift of the maximum temperature in the oven: the ratio of the maximum and minimum (filtered) reflectivity.

We discuss and present preliminary experimental evidence of three novel adds-on functionalities that can make Optical Feedback Imaging a truly small footprint and label free bioimaging technology. The first is single pixel compressed sensing. Here we demonstrate the proof of principle of scanless optical feedback imaging in free-space by spatially modulated illumination of the target. The second, is chemical sensitivity. Here we demonstrate identification of several pigments by selective spectral discrimination at three different wavelengths. The third functionality is the integration of OFI in silicon photonic chips. Here we identify the building blocks necessary to implement a scanless imaging system in an integrated photonic chip and show evidence of laser modulation through optical feedback provided by the emitted radiation after passing through a silicon passive integrated waveguide.

Design and synthesis of photosensitive 1D photonic system based on cholesteric liquid crystalline polymer will be presented. The photosensitivity and chirality is provided by a novel chiral hydrazone photochromic moiety covalently boud to the polymer backbone of a comb-shaped copolymer. Combination of the chirality and photosensitivity enabled reversible photomanipulation of the helical pitch of the supramolecular cholesteric structure resulting in material with a tunable selective reflection of circularly polarized light of the same helical sense as the chiral structure. In contrast to many other photochromic systems based on E-Z isomerization, the E and Z isomers of hydrazone photochromic group are kinetically stable that enable to achieve a pure photoinduced switch without any dark relaxation at any temperatures

Valproic acid (VPA), an epigenetic regulator used in the treatment of epilepsy and other neurological disorders in the past 50 years. The direct impact of VPA in cells of the immune system has only been explored recently. Immune cells have been relatively less studied in the context of photoacoustic tomography imaging which has been used in different biological systems with many different applications in biomedical investigations. Therefore, we aimed to perform a comparative analysis of photoacoustic imaging of immune cells in the context of VPA treatment. Four different doses of VPA (1 mM, 2.5 mM, 5 mM and 7.5 mM) were applied to in vitro models established with human EoL-1 eosinophilic cell line and human Jurkat T lymphocyte cell lines. Cell viability was assessed by trypan blue exclusion test. The changes in morphology caused by VPA were examined with a photoacoustic tomography system. Photoacoustic signals measured from the VPA in different immune cells showed the similar results obtained from light microscopy and cell viability. Photoacoustic imaging is promising for identifying and distinguishing different cell types and detecting changes at the cellular level.

In the biomedical field, the reemitted light intensity measured from the tissue depends on both scattering and absorption. In order to separate these variables, we use a physical phenomenon discovered in our lab, called the iso-path length (IPL) point. The IPL point is a specific angle around a cylindrical media, where the light intensity is not affected by the scattering and can serve for self-calibration. For a practical use of this concept, we designed an optic biosensor for measuring physiological parameters such as heart rate, oxygen saturation and respiratory rate, in both ordinary and extreme conditions in a hypoxic chamber.

3D laser nanoprinting based on multi-photon absorption (or multi-step absorption) has become an established commercially available and widespread technology. Here, we focus on recent progress concerning increasing print speed, improving the accessible spatial resolution beyond the diffraction limit, increasing the palette of available materials, and reducing instrument cost.

Biological discovery is a driving force of biomedical progress. With rapidly advancing technology to collect and analyze information from cells and tissues, we generate biomedical knowledge at rates never before attainable to science. Nevertheless, conversion of this knowledge to patient benefits remains a slow process. To accelerate the process of reaching solutions for healthcare, it would be important to complement this culture of discovery with a culture of problem-solving in healthcare. The talk focuses on recent progress with optical and optoacoustic technologies, as well as computational methods, which open new paths for solutions in biology and medicine. Particular attention is given on the use of these technologies for early detection and monitoring of disease evolution. The talk further shows new classes of imaging systems and sensors for assessing biochemical and pathophysiological parameters of systemic diseases, complement knowledge from –omic analytics and drive integrated solutions for improving healthcare.

In this paper, an innovative approach for detecting and analyzing speckle pattern signals is demonstrated, based on dynamic speckle analysis using a low-cost and low-framerate rolling shutter (RS) CMOS image sensor. The row scanning mechanism of a rolling shutter camera samples dynamic speckle patterns at a higher rate than typical Global Shutter (GS) cameras. In this research we demonstrate the detection and analysis of vibration signals that arise from an acoustic signal. We will illustrate the process of reconstructing a voice signal by analyzing a vibrating speckle pattern, with a primary focus on detecting and audibly capturing lung sounds.

Optimal laser energy delivery to target tissue is important to achieve an effective laser-induced hyperthermia (LH) with minimal damage to healthy tissue. However, this can be challenging because optical properties may vary depending on tissue type and environmental factors. Therefore, real-time measurement of temperature is as important as dosimetry for a successful and safe LH application. In this study, we developed a temperature-controlled 808 nm diode-laser system that eliminates the risk of thermal damage and contamination by performing non-contact, real-time temperature measurements of the irradiated surface. The system is composed of an 808 nm c-mount diode laser, an infrared (IR) array sensor for temperature measurement, a PC, and an electronic control unit (ECU). The system was tested on phantoms and ex vivo tissues. According to the results, the temperature-controlled 808 nm diode-laser system could maintain the surface temperature of samples at the target temperature value.

Bacterial biofilms are heterogeneous structures that are formed through a series of steps. It is essential to understand the stage of biofilm formation for several biomedical applications, such as assessing the coating efficacy for hard tissue implants, devising treatment strategies to inhibit biofilm formation in thin tissues, and building biocompatible diagnostic devices. The biofilm formation on polypropylene substrate is studied in this work. The formation of biofilm through different stages is evaluated through parameters extracted from Laser speckle imaging and validated through optical microscopy techniques. These parameters capture the concentration and orientation changes of bacteria through the different stages of biofilm.

Development of optical quality bioresorbable fibers is an emerging area of study where researchers are trying to advance the field by assessing the suitability of these fibers for various biomedical applications. These types of fiber implants dissolve in the human body over a clinically relevant time scale eliminating the need for extraction surgeries. We conducted both ex-vivo and in vivo diffuse correlation spectroscopic studies using our fibers to measure blood flow and a preliminary trial to integrate a biocompatible electrode material on the fiber for electrical signal measurements. The results demonstrated the potential of Calcium Phosphate glass-based fiber-optic devices in future physiological monitoring applications which can be implanted inside the body without the need of an explant procedure. Acknowledgement: This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 860185.

Liquid biopsy is an emerging and promising biomedical tool that aims to the early cancer diagnosis and the definition of personalized therapies in non-invasive and cost-effective way. Recently, tomographic phase imaging flow cytometry (TPIFC) has been developed as a technique for the reconstruction of the 3D volumetric distribution of the refractive indices (RIs) of single cells flowing along a microfluidic channel. Here we investigate the possibility of exploiting the 3D dataset of single cells recorded by TPIFC to feed a machine learning model, in order to recognize tumor cells with respect to a background of monocytes, which are the most similar cells among the WBCs in terms of morphology. Reported results aim to emulate a real scenario for the label-free liquid biopsy based on the machine learning-powered identification of circulating tumor cells within a blood sample imaged by the TPIFC system.

In this work, efficient light coupling into a microdisk capable of sustaining whispering gallery modes is thoroughly investigated, in order to understand the effect of polymer coating on the coupling efficiency. Light coupling within the microdisk from a tapered single mode optical fiber (SMF) is modelled and simulated, in presence and absence of a 100 nm thick polystyrene (PS) shell. The critical coupling parameters, such as the optical fiber distance to the microresonator (𝑑x) as well as the fiber optical properties such as cladding material (𝑛clad) are altered in order to achieve an efficient coupling and accordingly a high-quality factor 𝑄_F in the microresonator. Results show that the 𝑄_F of the resonators can exceed 10^4 only by tuning the geometrical parameter such as coupling distance 𝑑x where the ideal 𝑑x for uncoated and PS-coated microresonator is 0.55 μm and 0.40 μm respectively. Additionally, the sensitivity of the surrounding medium including the variation of the SMF cladding layer can be improved via using thin PS coatings on the surface of the microresonators.

We propose an analysis of the polarimetric attributes of biological tissue (dichroism, retardance and polarization). This analysis aims to characterize the intrinsic properties of the tissue and its polarimetric response when interacting with light. These polarimetric parameters are obtained through the experimental measurement of the Mueller matrix of the sample. We study the suitability of various sets of metrics for identification of biological tissues, by means of different pseudo-coloration techniques, highlighting some metrics such as depolarization. The results shown in an ex-vivo cow brain sample suggest the convenience of certain parameters which may be of interest in multiple biomedical applications.

Stem cell therapy holds tremendous potential for treating a wide range of currently incurable diseases, including retinal degenerations and geographic atrophy from macular degeneration. This study aimed to develop a non-invasive multimodality imaging system to track stem cells after transplantation in the subretinal space. Human-induced pluripotent stem cells differentiated to retinal pigment epithelium (hiPSC-RPE) cells were labeled with ultraminiaturized gold nanochains. The labeled hiPSC-RPE cells were then injected into 21 rabbits at 4 days after laser-induced photocoagulation damage to the RPE. Color fundus photography, photoacoustic microscopy, optical coherence tomography and fluorescent imaging were used to monitor the rabbit retina before and after the transplantation. The migration pattern and viability of the cells were monitored up to 6 months with a 37-fold increase in 650nm PAM signal. This approach allowed for the longitudinal evaluation of location of the transplanted stem cells, providing valuable insights for the advancement of stem cell therapies.

This paper introduces and validates a novel dual-comb functional Near-Infrared Spectroscopy (DC-fNIRS) technique, marking a significant advancement in the field of Near-Infrared Spectroscopy. DC-fNIRS distinguishes itself by its ability to accurately measure the diffuse time of flight (DTOF) within dispersive media in transmission and, for the first time, in backscattering configurations. The study demonstrates the technique's capability in spatially localizing perturbations within turbid media, showcasing its potential as a cost-effective alternative to traditional methods like functional Magnetic Resonance Imaging (fMRI). Employing a novel experimental setup involving dual Optical Frequency Combs generated from a single continuous wave laser source, the study captures intricate details of DTOF. This methodology allows for a comprehensive analysis of DTOF temporal evolution, enhancing our understanding of light propagation in complex media. The results obtained not only validate the effectiveness of the DC-fNIRS technique but also open new avenues for its application in non-invasive monitoring of brain activity and other critical biological processes.

Flow cytometry (FCM) quantifies sub-µm particles in body fluids as biomarkers. Typical FCM electronics detect particles based on a light scattering signal exceeding a threshold. When the sample dilution is reduced to enhance statistics, simultaneous illumination, and false detections occur. To enable measurements at higher concentrations, a signal processing algorithm was developed. The algorithm was evaluated by measuring dilution series of 150 nm and a mixture (150, 200, and 300 nm) of polystyrene beads. FCM electronics reliably measured up to 6.7×E+7 〖ml〗^(-1) for 150 nm beads and 1.3×E+8 〖ml〗^(-1) for the mixture, while the algorithm achieved concentrations up to 1.5×E+9 〖(ml〗^(-1)), enabling 10-fold faster concentration measurements.

Endoscopes are medical inspection devices made of optical fibers and an imaging lens at the tip. Miniaturizing the optical system is primordial to ensure agility and accessibility for clinical applications. Metalens-based fiber optics endoscopes offer a promising alternative to conventional devices to reduce the size while maintaining the image quality. In this work, we present a new multiscale metalens design solution for fiber optic endoscopes, utilizing full-wave electromagnetic simulations and ray-tracing techniques.

Tissue histopathology, reliant on costly and time-consuming hematoxylin and eosin (H&E) staining of thin tissue slices, faces limitations. Label-free non-linear optical microscopy in vivo presents a solution, allowing work on fresh samples. Implantable microstructures prove effective for systematic longitudinal in vivo studies of immunological responses to biomaterials using label-free non-linear optical microscopy. Employing two-photon laser polymerization, we implanted a matrix of 3D lattices in the chorioallantoic membrane of chicken embryos, establishing a 3D reference frame for cell counting. H&E analysis is compared to label-free in vivo non-linear excitation imaging for cell quantification and identifying granulocytes, collagen, and microvessels. Preliminary results in higher animal models demonstrate the transformative potential of this approach, offering an alternative to conventional histopathology for validating biomaterials in in vivo longitudinal studies.

Imaging a large number of samples is necessary to improve statistical robustness in biological assays. Using standard multiwell plates is not possible in usual light-sheet microscopes. One solution is to use an Oblique Plane Microscope (OPM), which is a special fluorescence light sheet microscope, with a single objective near to the sample. To avoid aberrations, OPM generally uses water or silicon immersion to match the refractive index of the sample. In this work we present an oil-immersed OPM and experimentally demonstrate the possibility of using a primary objective with a higher numerical aperture.

Cancer is one of the worldwide leading causes of death. They are diagnosed and graded histologically using biopsies, sliced at 2-5 μm, and stained with Haematoxylin and Eosin (H&E). Hyperspectral (HS) Imaging (HSI) has been arising to improve the spectral information given by RGB (Red-Green-Blue) cameras. This work aims to characterize the influence of tissue thickness on the spectral information. Captures were taken over breast tissue samples sectioned at 2 and 3 μm. They were pre-processed to reduce noise and normalize the data. Then, based on H&E absorption spectra peaks, HS images could be segmented into stroma (eosin-stained basic structures), nucleus (haematoxylin-stained acidic structures), and background (non-stained structures). Concluding, results show that 3 μm slides proportionate a bigger count of cells and a higher spectral contrast than 2 μm slides. However, further research is needed to study other thickness values, including more samples.

A Bayesian statistics-based image segmentation algorithm is applied on unstained tissue section images to distinguish normal and different grades (CIN-I, CIN-II, CIN-III) of cervical pre-cancer. This multi-level thresholding achieves an effective image quantization of the high cell density domain, most affected during the progression of the disease, which yields a precise visualization of the lesions in the epithelial cellular structures, revealing their spatial changes with the progression of the disease. The pixel count ratio of the quantized high cell density region drops below a statistically well-defined threshold, that quantitatively discriminates the different grades. The Receiver Operating Curve (ROC) exhibits good discrimination between normal and different pre-cancer grades.

Exploiting the best of both the worlds of light field and meta-optics to design and demonstrate a cost-effective and compact light field microscopy for high-speed volumetric imaging with high spatio-temporal resolution.

For multimode fiber imaging, deep learning's capability in handling complex data relationships is undeniable. However, it demands a substantial amount of high-quality data, and it takes 24 hours to measure speckle patterns for 60,000 MNIST digits. Therefore, we turn to conditional generative adversarial networks (CGANs) for data augmentation. Our CGAN model synthesizes data closely resembling experimental speckle patterns for MNIST digits, with an SSIM of 0.9840. With only 16,500 training samples, we generate an additional 38,500 speckle patterns in just 30 minutes. This research highlights the CGAN's potential in transcending data collection limitations for multimode fiber endoscopy and industrial inspection.

This study explored the relationship between the structure similarity coefficient extracted from time-lapse monitoring videos of embryos and the embryonic developmental process. It applied the K-means clustering method to analyze the clustering of structure similarity coefficients of different samples, and to investigate the correlation between the clusters with the ability of embryonic cells to develop into blastocysts. This study generated an effective predictive marker for morphological changes in embryonic cell development, contributing to the prediction of the developmental potential of embryonic cells.

Laser speckle contrast imaging (LSCI) is extensively used imaging technique in bio-medical engineering with optimization of laser sources and camera configurations. With an emphasis on type 2 diabetes, which affects 90% of patients globally, LSCI is useful in diagnosis of illness. Applications of LSCI, such as microvascular monitoring and wound healing assessment are examined in diabetes research. LSCI combines hardware design with useful healthcare applications, offering the opportunity for early diagnosis and tailored therapy in diabetes management. Researchers and medical practitioners looking to use LSCI technology to solve diabetes-related issues will find this evaluation to be a useful resource.