Fluorescence lifetime imaging microscopy (FLIM) using endogenous fluorescence of NADH (reduced nicotinamide adenine dinucleotide) and its phosphorylated form NADPH represents a powerful tool for monitoring cellular metabolic states. For a more nuanced interpretation of the FLIM data, investigating NAD(P)H in different cell compartments is crucial. In this study, we demonstrate that a weak NAD(P)H fluorescence in cell nuclei, which is often ignored, can be reliably analyzed using a phasor plot approach and provides a sensitive readout of metabolic responses. Using colorectal cancer cells HCT116 treated with the metabolic inhibitors rotenone and 3-bromopyruvate, as well as the chemotherapeutic agent 5-fluorouracil (5-FU), we show that nuclear NAD(P)H fluorescence decay changes in response to treatment. In the case of 5-FU, the phasor analysis of nuclear NAD(P)H reveals heterogeneous cellular responses with two subpopulations differing in NAD(P)H fluorescence decay parameters, fluorescence intensity, and cytoplasm-to-nucleus intensity ratio. Notably, nuclear and cytoplasmic responses are strongly correlated, indicating tight coupling of their NAD(P)H pools. Overall, our results establish nuclear NAD(P)H fluorescence as a robust, label-free indicator of cellular metabolism and highlight its potential for metabolic monitoring in conditions where analysis of NAD(P)H fluorescence is limited by spectral overlap with exogenous fluorescent labels.

Accurate and rapid assessment of hemoglobin (Hb) concentration is essential for medical decision-making in preoperative evaluations, anemia screening, and blood loss monitoring. RGB imaging, which estimates Hb levels by analyzing tissue color in regions such as nail beds, has attracted growing interest due to its portability and compatibility with mobile devices. While promising, the reported prediction errors vary widely from 5.6[Formula: see text]g/L to 36[Formula: see text]g/L, raising concerns about clinical applicability. External physiological perturbations can significantly affect the reliability of RGB-based Hb estimation by altering tissue optical properties and introducing measurement bias. However, their systematic influence on signal quality and prediction accuracy remains insufficiently explored. In this study, we systematically evaluate the effects of ambient temperature, mechanical compression, and venous occlusion on RGB-based Hb estimation using a machine learning model trained on data from 298 patients with matched venous Hb values. Controlled experiments reveal that these external conditions introduce systematic biases ranging from 5[Formula: see text]g/L to 20[Formula: see text]g/L. To address intersubject variability, we propose a personalized intercalibration approach based on prior Hb measurements from the same individual, which we validate on 17 repeat blood donors. These findings provide a comprehensive quantification of how external and individual-specific factors affect non-invasive Hb prediction, and support the development of accurate, robust, and clinically viable RGB-based monitoring systems for both point-of-care and mobile healthcare applications.

The Siberian Arctic Shelf is experiencing rapid environmental change, driven by climate warming that is amplified in the Northern Hemisphere. A key consequence is mobilization of dissolved organic matter (DOM) from permafrost thaw and associated landscape degradation. In this study, we explore the molecular composition and optical properties of DOM across three Arctic Shelf regions: the Kara Sea (KS), Laptev Sea (LS), and East Siberian Sea (ESS). We developed a two-dimensional classification framework linking the optical properties of shelf water (absorbance and fluorescence) with DOM molecular composition (ultrahigh-resolution Fourier transform ion cyclotron resonance mass spectrometry [FT-ICR MS]) to trace DOM sources on the Arctic Shelf. A strong inverse correlation between SUVA254 (specific ultraviolet absorbance at 254 nm) and Asm280 (emission band asymmetry at 280 nm), i.e., R2 = 0.82, revealed a compositional continuum from highly aromatic DOM in KS and LS to more aliphatic, labile DOM in marine-influenced ESS waters. Molecular analysis confirmed this trend: DOM in KS and LS was enriched in hydrolyzable and condensed tannins, CARF (Core Arctic Riverine Fingerprint), and IOS (Island of Stability) formulae. In contrast, ESS and Arctic offshore DOM showed higher contributions of more saturated lignin-, terpenoid-, and carbohydrate-like compounds. The occupation densities of Van Krevelen diagrams attributed to the aromatics populated domain (D7), and the combined aliphatic/carbohydrate-like domain (D14 + D15) served as robust molecular predictors of DOM optical behavior. Their inverse relationship (R2 = 0.72) provided additional resolution for classifying DOM sources across regions. This integrated framework demonstrates the utility of combining optical and molecular techniques for tracking DOM composition and reactivity under changing Arctic hydroclimatic conditions.

Fluorescence lifetime imaging (FLIM) is a powerful tool for investigating the molecular microenvironment of fluorophores within living cells and tissues. One of its most prominent applications is in metabolic imaging, based on the autofluorescence of the dehydrogenase cofactors NAD(P)H and FAD. Our research is centered on tumor cell metabolism, key features of which include the Warburg effect, metabolic plasticity, and considerable intra- and intertumoral heterogeneity. The technique's label-free basis, quantitative output, and non-invasive image acquisition make metabolic FLIM highly suitable for clinical translation. Through investigations employing in vitro cell models, in vivo mouse tumors, and postoperative patient samples, we have assessed the diagnostic and prognostic potential of FLIM. Our results show that macroscopic FLIM can identify breast cancer metastases in sentinel lymph nodes and distinguish gliomas from the brain's white matter. Furthermore, we have demonstrated that FLIM can effectively visualize and quantify metabolic heterogeneity at the cellular level. Consistent with expectations, patient-derived tumors exhibited greater metabolic heterogeneity than standard cell lines or xenografts, an observation confirmed in colorectal and breast cancers. Overall, these results yield critical insights into the distinct metabolic features of tumors.

Blood serum fluorescence spectroscopy provides a rapid and facile method for assessing protein conformational states and metabolic shifts, rendering it highly valuable for the diagnostic investigation of pathologies. Here, we demonstrate the potential of blood serum fluorescence spectroscopy for prostate cancer diagnosis. Current diagnostic modalities for prostate cancer encompass blood tests for prostate-specific antigen level, digital rectal examination, ultrasound and MRI assay. Despite their widespread utilization, these established techniques exhibit limitations in specificity, resulting in an increased number of unnecessary biopsies. Based on the analysis of blood serum fluorescence emission spectra, we identified a novel potential marker - asymmetry of fluorescence spectra at 350 nm excitation, Asym350, for prostate cancer, which demonstrated statistically significant discriminatory power in identifying prostate cancer patients (p < 5×104). This fluorescence-derived marker was integrated into a classification model alongside PSA level and PI-RADS score. By using cross-validation to evaluate the performance of classification model across various feature sets, we achieved the highest F1 score of 0.91 when utilizing feature set of PI-RADS and Asym350. These findings underscore the capabilities of blood serum fluorescence spectroscopy for prostate cancer diagnostics and raise the crucial question of the feasibility of its translation into clinical application.

This study explored the mechanism of liquid nitrogen spray freezing and transglutaminase cross-linking in maintaining surimi gels' structure during storage. Results revealed that structure changes were, on the one hand, related to the growth and recrystallization of ice crystals during storage. Low cross-linking gels with air freezing exhibited minimum value after 20 days of storage, with hardness decreasing by 38.02 %, while -80 °C liquid nitrogen spray freezing combined with 62.99 % cross-linked effectively preserved structure by maintaining uniform ice crystal distribution and preventing microstructural fractures, limiting the hardness decrease to 18.32 %. On the other hand, structure changes were closely associated with protein variations. There were 766 differential proteins identified in the CKb vs. CKa comparison. The enhanced texture retention of 62.99 % cross-linked during storage, in contrast to low cross-linked gel, was probably associated with higher concentrations of structural proteins like A0A3N0XRS8 and A0A3N0YCS0 as well as calcium-related proteins like A0A3N0XCW2 and A0A3N0Y0G9.

The issue of variability introduced into blood plasma and serum analysis by preanalytical procedures is the major obstacle to obtaining accurate and reproducible results. While the question of how to overcome this issue has been discussed in biochemical detection of analytes and omics technologies, its relevance to the field of optical spectroscopy remains mostly unexplored. In this work, we evaluated the freeze-thaw cycle (FTC)-induced alternations in blood serum optical properties by means of autofluorescence and Raman spectroscopy, including surface-enhanced Raman spectroscopy (SERS). In the case of regular Raman spectroscopy, FTC-specific spectral variability was estimated to be <1%, being significantly smaller than patient-specific variability, while the t-distributed stochastic neighbor embedding clustering of principal components yielded spectral grouping by patient ID independent of sample freezing. For SERS, FTC-specific and patient-specific spectral variabilities were 15% and >90%, respectively. Finally, parallel factor analysis of autofluorescence excitation-emission matrices revealed that patient-specific variability in the visible spectral range was 13%, whereas FTC-specific variability was 4%. We further evaluated disease-specific variability for two datasets, namely, for colorectal cancer diagnostics with autofluorescence and for chronic kidney disease diagnostics using SERS. Disease-associated variabilities were determined to be 8% and 49%, significantly exceeding the possible FTC-induced variability. Hence, the obtained results suggest that FTC blood serum samples can be used for disease diagnostics by Raman spectroscopy and SERS, as well as through autofluorescence spectroscopy, although the difference in FTC-induced and disease-induced variabilities was lowest in the latter case.

Traumatic wounds are the prevalent scenarios encountered in battleground and emergency rooms. The rapid and effective hemostasis is imperative for life saving in these scenarios, for which the development of high-efficiency and biocompatible hemostatic materials is essential. Due to its excellent hemostatic property and biocompatibility, collagen has emerged as an ideal component of hemostatic materials. Furthermore, the properties of collagen-based hemostatic materials could be improved by the integration of other biomacromolecules, such as alginate, cellulose derivatives, and chitosan derivatives. Therefore, more and more novel hemostatic materials with exceptional hemostatic properties have been developed. This review aims to overview recent progress of collagen-based hemostatic materials. Firstly, the hemostatic mechanism of collagen was introduced. Secondly, various forms of collagen-based hemostatic materials, such as hydrogels, sponges, and powders, were highlighted. Thirdly, composite hemostatic materials of collagen and other biomacromolecules were overviewed. Finally, the outlook of collagen-based hemostatic materials was discussed.

Fluorogen-activating proteins are powerful molecular tools for microscopy, including functional imaging. These proteins serve as an alternative to GFP-like proteins, as they do not require oxygen for chromophore maturation. However, the restricted selectivity of proteins to chromophores, combined with the limited number of spectral channels of conventional fluorescent microscopes, hinders the development of multicolor synthetic dyes. Additionally, the poor cell and tissue permeability of synthetic chromophores further limits their utility. In this work, we address these challenges by combining time-resolved methods with the rational design of the UnaG protein, which utilizes bilirubin as a natural chromophore. To turn UnaG into a palette of probes for fluorescence lifetime imaging microscopy (FLIM), we solved two practical problems: first, we determined the limits of bilirubin lifetime variations in response to changes in the protein structure and, second, we determined what minimal structural changes can be reliably distinguished by lifetime analysis in cellula. Combining classical point mutagenesis and the translational introduction of noncanonical amino acids, we generated UnaG with fluorescence lifetimes ranging from hundreds of picoseconds to nanoseconds. We explored the potential for further modification of the UnaG protein matrix to optimize spectral and temporal characteristics of bilirubin fluorescence and its quantitative detection through time-resolved approaches.

Pathological processes are often accompanied by alterations of protein conformations in blood serum, making investigation of these structural rearrangements highly relevant for clinical diagnostics. Conformation of albumin, the predominant protein in blood serum, is known to be a sensor of pathologies in the human organism; however, label-free methods for its assessment directly in blood serum samples are lacking. In this work, we present a novel analytical methodology for evaluating albumin conformation using the fluorescence parameters of intrinsic blood serum fluorophores excited in the visible range. We first estimate the contribution of various endogenous fluorophores excited in the vicinity of 400 nm to both steady-state fluorescence and fluorescence decay across picosecond and nanosecond time scales, showing that one of the dominant fluorophores is bilirubin, an albumin ligand. In model experiments, we then demonstrate that the structural and photophysical features of bilirubin make its fluorescence decay at picosecond time scale sensitive to conformation of the protein-bilirubin complex. As a final step, it is demonstrated that changes in the ultrafast fluorescence decay parameters of the bilirubin are sensitive enough to detect biologically relevant differences in albumin conformation in serum across different patients. Specifically, we observed statistically significant differences in blood serum albumin's conformation for patients of different age groups (≤34 years and ≥65 years), suggesting that bilirubin may serve as a promising intrinsic sensor for assessing albumin conformational modifications in blood serum.

The most critical problem in clinical oncology is the metastasis of malignant neoplasms. The survival and growth of metastases in a new microenvironment fundamentally depend on adaptations in the energy metabolism of metastasizing cells. However, these adaptations are far less studied compared to primary tumors. A promising method for assessing the metabolic status of cells is fluorescence lifetime imaging microscopy (FLIM), based on recording the decay parameters of cellular autofluorescence emitted by pyridine and flavin cofactors. This work aims to identify differences in the fluorescence decay kinetics of NAD(P)H between metastatic breast cancer cells and the primary tumor, as well as between metastatic cells and lymph node tissue in a 4T1 mouse model experiment. The study revealed a decrease in the relative fraction of the free form of NAD(P)H (a1,

In this study, fluorescence recovery after photobleaching (FRAP) experiments were performed on RBC labeled by lipophilic fluorescent dye CM-DiI to evaluate the role of adenylyl cyclase cascade activation in changes of lateral diffusion of erythrocytes membrane lipids. Stimulation of adrenergic receptors with epinephrine (adrenaline) or metaproterenol led to the significant acceleration of the FRAP recovery, thus indicating an elevated membrane fluidity. The effect of the stimulation of protein kinase A with membrane-permeable analog of cAMP followed the same trend but was less significant. The observed effects are assumed to be driven by increased mobility of phospholipids resulting from the weakened interaction between the intermembrane proteins and RBC cytoskeleton due to activation of adenylyl cyclase signaling cascade.

The extracellular matrix (ECM), in which collagen is the most abundant protein, impacts many aspects of tumor physiology, including cellular metabolism and intracellular pH (pHi), as well as the efficacy of chemotherapy. Meanwhile, the role of collagen in differential cell responses to treatment within heterogeneous tumor environments remains poorly investigated. In the present study, we simultaneously monitored the changes in pHi and metabolism in living colorectal cancer cells in vitro upon treatment with a chemotherapeutic combination, FOLFOX (5-fluorouracil, oxaliplatin and leucovorin). The pHi was followed using the new pH-sensitive probe BC-Ga-Ir, working in the mode of phosphorescence lifetime imaging (PLIM), and metabolism was assessed from the autofluorescence of the metabolic cofactor NAD(P)H using fluorescence lifetime imaging (FLIM) with a two-photon laser scanning microscope. To model the ECM, 3D collagen-based hydrogels were used, and comparisons with conventional monolayer cells were made. It was found that FOLFOX treatment caused an early temporal intracellular acidification (reduction in pHi), followed by a shift to more alkaline values, and changed cellular metabolism to a more oxidative state. The presence of unstructured collagen markedly reduced the cytotoxic effects of FOLFOX, and delayed and diminished the pHi and metabolic responses. These results support the observation that collagen is a factor in the heterogeneous response of cancer cells to chemotherapy and a powerful regulator of their metabolic behavior.

Biomimetic hydrogels have garnered increased interest due to their considerable potential for use in various fields, such as tissue engineering, 3D cell cultivation, and drug delivery. The primary challenge for applying hydrogels in tissue engineering is accurately evaluating their mechanical characteristics. In this context, we propose a method using scanning ion conductance microscopy (SICM) to determine the rigidity of living human breast cancer cells MCF-7 cells grown on a soft, self-assembled Fmoc-FF peptide hydrogel. Moreover, it is demonstrated that the map of Young’s modulus distribution obtained by the SICM method allows for determining the core location. The Young’s modules for MCF-7 cells decrease with the substrate stiffening, with values of 1050 Pa, 835 Pa, and 600 Pa measured on a Petri dish, Fmoc-FF hydrogel, and Fmoc-FF/chitosan hydrogel, respectively. A comparative analysis of the SICM results and the data obtained by atomic force microscopy was in good agreement, allowing for the use of a composite cell–substrate model (CoCS) to evaluate the ‘soft substrate effect’. Using the CoCS model allowed us to conclude that the MCF-7 softening was due to the cells’ mechanical properties variations due to cytoskeletal changes. This research provides immediate insights into changes in cell mechanical properties resulting from different soft scaffold substrates.

Non-invasive assessment of haemoglobin (Hb) level in blood is a hot spot in the point-of-care biomedical diagnostics. Several optical methods are suggested as a solution, some of them being approved for clinical use. Still, there is no consensus on the accuracy of optical techniques, the quality of Hb assessment on different tissue sites, and on the ability of combined use of several optical techniques to improve the quality of Hb level prediction. In this work we examined the capabilities of two optical techniques-diffuse reflectance spectroscopy and RGB-imaging of the skin and fingernails areas-in detecting low blood Hb level. The test sample consisted of 240 adult volunteers with 70 volunteers exhibiting Hb level lower than 120 g/L. We show that using simple descriptors of the diffuse reflectance spectrum of the forearm skin and fingernails is applicable for predicting low blood Hb concentration (ROC-AUC = 0.84 +/- 0.08), while RGB-imaging shows similar performance when applied to the fingernail areas (ROC-AUC = 0.83 +/- 0.07), which can be considered perspective for clinical use and screening properties. We also report that while the joint use of predictions from two optical methods slightly improves the accuracy of non-invasive Hb level assessment (ROC-AUC = 0.86 +/- 0.07), the effect is not as high as one might expect from combining predictions of truly independent modalities, indicating the limit of the accuracy one can expect with multimodal optical approach. We review this case and propose possible solutions towards more sensitive non-invasive optical determination of hemoglobin.

The morphological diagnosis of thyroid gland neoplasms presents a dual challenge: it requires the expertise of highly trained specialists and considerable time, particularly when evaluating multiple whole slide images (WSIs) from a single patient. The integration of artificial intelligence (AI) techniques into the diagnostic workflow is a hot area of research. However, most studies rely on meticulously curated datasets, the preparation of which is both costly and fraught with complexities. This paper investigates the development of machine learning models using weakly-annotated “real-world” data, devoid of the selective preprocessing typical in common research datasets. Our study demonstrates that a Multiple-Instance Learning (MIL) model, trained on a weak patient-level annotations of 1102 patients encompassing 5104 WSIs, successfully discriminates between benign and malignant conditions at the patient level, achieving an average test set F1-Score of 0.85 with a standard deviation of 0.05. This study is, to our knowledge, the first to report findings from an AI model trained on patient-level data without prior labeling refinement. Additionally, we identify potential pitfalls in data quality that could induce model overfitting, such as the inadvertent inclusion of dye used to highlight resection margins, which correlates with the target variable. We also assessed the impact of detailed slide-level versus coarse patient-level annotations on classification accuracy using a smaller, more precisely annotated dataset of 36 laboratory cases (91 WSIs). The results indicate that detailed annotations substantially enhance classification performance in smaller datasets.

An urgent problem in biophotonics is the search and development of new methods for objective assessment of tissue parameters during surgical operations. This study examines two problems related to orthopedics and dentistry: assessing the condition of the tissues of the knee joint during arthroscopy, as well as assessing the distance to the dental pulp when removing infected dentin due to caries. An approach to solving these problems was studied using an optic fiber implementation of the diffuse reflectance spectroscopy method when measuring explants obtained during surgical interventions, as well as when measuring directly during operations. To optimize the measuring configuration, Monte Carlo simulation of light propagation in tissues was used; based on the experimental data obtained, methods for determining tissue parameters using machine learning methods were constructed. Further options for the improvement of these techniques are discussed.

Heterogeneity of tumor metabolism is an important, but still poorly understood aspect of tumor biology. Present work is focused on the visualization and quantification of cellular metabolic heterogeneity of colorectal cancer using fluorescence lifetime imaging (FLIM) of redox cofactor NAD(P)H. FLIM-microscopy of NAD(P)H was performed in vitro in four cancer cell lines (HT29, HCT116, CaCo2 and CT26), in vivo in the four types of colorectal tumors in mice and ex vivo in patients’ tumor samples. The dispersion and bimodality of the decay parameters were evaluated to quantify the intercellular metabolic heterogeneity. Our results demonstrate that patients’ colorectal tumors have significantly higher heterogeneity of energy metabolism compared with cultured cells and tumor xenografts, which was displayed as a wider and frequently bimodal distribution of a contribution of a free (glycolytic) fraction of NAD(P)H within a sample. Among patients’ tumors, the dispersion was larger in the high-grade and early stage ones, without, however, any association with bimodality. These results indicate that cell-level metabolic heterogeneity assessed from NAD(P)H FLIM has a potential to become a clinical prognostic factor.

ObjectivesThe aim of this work is to assess the performance of multimodal spectroscopic approach combined with single core optical fiber for detection of bladder cancer during surgery in vivo.MethodsMultimodal approach combines diffuse reflectance spectroscopy (DRS), fluorescence spectroscopy in the visible (405 nm excitation) and near-infrared (NIR) (690 nm excitation) ranges, and high-wavenumber Raman spectroscopy. All four spectroscopic methods were combined in a single setup. For 21 patients with suspected bladder cancer or during control cystoscopy optical spectra of bladder cancer, healthy bladder wall tissue and/or scars were measured. Classification of cancerous and healthy bladder tissue was performed using machine learning methods.ResultsStatistically significant differences in relative total haemoglobin content, oxygenation, scattering, and visible fluorescence intensity were found between tumor and normal tissues. The combination of DRS and visible fluorescence spectroscopy allowed detecting cancerous tissue with sensitivity and specificity of 78% and 91%, respectively. The addition of features extracted from NIR fluorescence and Raman spectra did not improve the quality of classification.ConclusionsThis study demonstrates that multimodal spectroscopic approach allows increasing sensitivity and specificity of bladder cancer detection in vivo. The developed approach does not require special probes and can be used with single-core optical fibers applied for laser surgery.