High-Resolution Raman Imaging of >300 Patient-Derived Cells from Nine Different Leukemia Subtypes: A Global Clustering Approach.

Leukemia comprises a diverse group of bone marrow tumors marked by cell proliferation. Current diagnosis involves identifying leukemia subtypes through visual assessment of blood and bone marrow smears, a subjective and time-consuming method. Our study introduces the characterization of different leukemia subtypes using a global clustering approach of Raman hyperspectral maps of cells. We analyzed bone marrow samples from 19 patients, each presenting one of nine distinct leukemia subtypes, by conducting high spatial resolution Raman imaging on 319 cells, generating over 1.3 million spectra in total. An automated preprocessing pipeline followed by a single-step global clustering approach performed over the entire data set identified relevant cellular components (cytoplasm, nucleus, carotenoids, myeloperoxidase (MPO), and hemoglobin (HB)) enabling the unsupervised creation of high-quality pseudostained images at the single-cell level. Furthermore, this approach provided a semiquantitative analysis of cellular component distribution, and multivariate analysis of clustering results revealed the potential of Raman imaging in leukemia research, highlighting both advantages and challenges associated with global clustering.

Discovery of calcite as a new pro-inflammatory calcium-containing crystal in human osteoarthritic synovial fluid.

OBJECTIVE: We aimed to characterize calcium-containing crystals present in synovial fluid from patients with knee osteoarthritis (OA) using Raman spectroscopy, and specifically investigate the biological effects of calcite crystals. DESIGN: Thirty-two synovial fluid samples were collected pre-operatively from knee OA patients undergoing total joint arthroplasty. An integrated Raman polarized light microscope was used for identification of crystals in synovial fluid. Human peripheral blood mononuclear cells (PBMC's), human OA articular chondrocytes (HACs) and fibroblast-like synoviocytes (FLSs) were exposed to calcite crystals. Expression of relevant cytokines and inflammatory genes were measured using enzyme-linked immuno sorbent assay (ELISA) and real-time polymerase chain reaction (PCR). RESULTS: Various calcium-containing crystals were identified, including calcium pyrophosphate (37.5 %) and basic calcium phosphate (21.8 %), but they were never found simultaneously in the same OA synovial fluid sample. For the first time, we discovered the presence of calcite crystals in 93.8 % of the samples, while dolomite was detected in 25 % of the cases. Characterization of the cellular response to calcite crystal exposure revealed increased production of innate immune-derived cytokines by PBMC's, when co-stimulated with lipopolysaccharide (LPS). Additionally, calcite crystal stimulation of HACs and FLSs resulted in enhanced secretion of pro-inflammatory molecules and alterations in the expression of extracellular matrix remodeling enzymes. CONCLUSIONS: This study highlights the unique role of Raman spectroscopy in OA crystal research and identified calcite as a novel pro-inflammatory crystal type in OA synovial fluid. Understanding the role of specific crystal species in the OA joint may open new avenues for pharmacological interventions and personalized approaches to treating OA.

An objective diagnosis of gout and calcium pyrophosphate deposition disease with machine learning of Raman spectra acquired in a point-of-care setting.

OBJECTIVE: Raman spectroscopy is proposed as a next-generation method for the identification of monosodium urate (MSU) and calcium pyrophosphate (CPP) crystals in synovial fluid. As the interpretation of Raman spectra requires specific expertise, the method is not directly applicable for clinicians. We developed an approach to demonstrate that the identification process can be automated with the use of machine learning techniques. The developed system is tested in a point-of-care-setting at our outpatient rheumatology department. METHODS: We collected synovial fluid samples from 446 patients with various rheumatic diseases from three centra. We analyzed all samples with our Raman spectroscope and used 246 samples for training and 200 samples for validation. Trained observers classified every Raman spectrum as MSU, CPP or else. We designed two one-against-all classifiers, one for MSU and one for CPP. These classifiers consisted of a principal component analysis model followed by a support vector machine. RESULTS: The accuracy for classification of CPP using the 2023 ACR/EULAR CPPD classification criteria was 96.0% (95% CI 92.3-98.3), while the accuracy for classification of MSU with using the 2015 ACR/EULAR gout classification criteria was 92.5% (95% CI 87.9-95.7). Overall, the accuracy for classification of pathological crystals was 88.0% (95% CI 82.7-92.2). The model was able to discriminate between pathologic crystals, artifacts, and other particles such as microplastics. CONCLUSION: We here demonstrate that potentially complex Raman spectra from clinical patient samples can be successfully classified by a machine learning approach, resulting in an objective diagnosis independent of the opinion of the medical examiner.

Ultrasensitive Detection and In Situ Imaging of Analytes on Graphene Oxide Analogues Using Enhanced Raman Spectroscopy.

We demonstrate how algorithm-improved confocal Raman microscopy (ai-CRM), in combination with chemical enhancement by two-dimensional substrates, can be used as an ultrasensitive detection method for rhodamine (R6G) molecules adsorbed from aqueous solutions. After developing a protocol for laser-induced reduction of graphene oxide, followed by noninvasive Raman imaging, a limit of detection (LOD) of 5 × 10-10 M R6G was achieved using ai-CRM. An equivalent subnanomolar LOD was also achieved on another graphene oxide analogue -UV/ozone-oxidized graphene. These record-breaking detection capabilities also enabled us to study the adsorption kinetics and image the spatial distribution of the adsorbed R6G. These findings indicate a strong potential for algorithm-improved graphene-enhanced Raman spectroscopy as a facile method for detecting, imaging, and quantifying trace amounts of adsorbing molecules on a variety of 2D substrates.

PDMS Curing Inhibition on 3D-Printed Molds: Why? Also, How to Avoid It?

Three-dimensional (3D)-printing techniques such as stereolithography (SLA) are currently gaining momentum for the production of miniaturized analytical devices and molds for soft lithography. However, most commercially available SLA resins inhibit polydimethylsiloxane (PDMS) curing, impeding reliable replication of the 3D-printed structures in this elastomeric material. Here, we report a systematic study, using 16 commercial resins, to identify a fast and straightforward treatment of 3D-printed structures and to support accurate PDMS replication using UV and/or thermal post-curing. In-depth analysis using Raman spectroscopy, nuclear magnetic resonance, and high-resolution mass spectrometry revealed that phosphine oxide-based photo-initiators, leaching out of the 3D-printed structures, are poisoning the Pt-based PDMS catalyst. Yet, upon UV and/or thermal treatments, photo-initiators were both eliminated and recombined into high molecular weight species that were sequestered in the molds.

Synchronized Rayleigh and Raman scattering for the characterization of single optically trapped extracellular vesicles.

Extracellular Vesicles (EVs) can be used as biomarkers in diseases like cancer, as their lineage of origin and molecular composition depend on the presence of cancer cells. Recognition of tumor-derived EVs (tdEVs) from other particles and EVs in body fluids requires characterization of single EVs to exploit their biomarker potential. We present here a new method based on synchronized Rayleigh and Raman light scattering from a single laser beam, which optically traps single EVs. Rapidly measured sequences of the Rayleigh scattering amplitude show precisely when an individual EV is trapped and the synchronously acquired Raman spectrum labels every time interval with chemical information. Raman spectra of many single EVs can thus be acquired with great fidelity in an automated manner by blocking the laser beam at regular time intervals. This new method enables single EV characterization from fluids at the single particle level.

Label-Free Prostate Cancer Detection by Characterization of Extracellular Vesicles Using Raman Spectroscopy.

Mammalian cells release extracellular vesicles (EVs) into their microenvironment that travel the entire body along the stream of bodily fluids. EVs contain a wide range of biomolecules. The transported cargo varies depending on the EV origin. Knowledge of the origin and chemical composition of EVs can potentially be used as a biomarker to detect, stage, and monitor diseases. In this paper, we demonstrate the potential of EVs as a prostate cancer biomarker. A Raman optical tweezer was employed to obtain Raman signatures from four types of EV samples, which were red blood cell- and platelet-derived EVs of healthy donors and the prostate cancer cell lines- (PC3 and LNCaP) derived EVs. EVs' Raman spectra could be clearly separated/classified into distinct groups using principal component analysis (PCA) which permits the discrimination of the investigated EV subtypes. These findings may provide new methodology to detect and monitor early stage cancer.

Protein profiles in cortical and nuclear regions of aged human donor lenses: A confocal Raman microspectroscopic and imaging study.

A combination of Raman spectroscopy, imaging, hierarchical cluster analysis (HCA) and peak ratio analysis was used to analyze protein profiles in the superficial cortex (SC), deep cortex (DC) and nucleus of old human lenses with cortical, nuclear and mixed cataracts. No consistent differences were observed in protein spectra and after cluster analysis between the three locations irrespective of the presence or absence of cortical opacities and/or coloration. A sharp increase (∼15%-∼33%) in protein content from SC to DC, normal for human lenses, was found in 7 lenses. In 4 lenses, characterized by the absence of cortical opacities, the SC has a protein content of ∼35%. A significant increase in the disulfide-to-protein ratio is found only in the SC of the 7 cortical cataracts. No changes were found in sulfhydryl-to-protein ratio. The relative contents of α-helices and ß-sheets increase from SC to nucleus. ß-Sheets are more common in the SC of lenses with cortical cataract. The absence of significant and consistent changes in protein profiles between nucleus and cortex even in cases of severe coloration is not favoring the prevailing concept that ubiquitous protein oxidation is a key factor for age related nuclear (ARN) cataracts. The observations favor the idea that multilamellar bodies or protein aggregates at very low volume densities are responsible for the rise in Mie light scatter as a main cause of ARN cataracts leaving the short-range-order of the fiber cytoplasm largely intact. The absence of significant changes in the protein spectra of the deep cortical opacities, milky white as a result of the presence of vesicle-like features, indicate they are packed with relatively undisturbed crystallins.

Epi-detection of vibrational phase contrast coherent anti-Stokes Raman scattering.

We demonstrate a system for the phase-resolved epi-detection of coherent anti-Stokes Raman scattering (CARS) signals in highly scattering and/or thick samples. With this setup, we measure the complex vibrational responses of multiple components in a thick, highly-scattering pharmaceutical tablet in real time and verify that the epi- and forward-detected information are in very good agreement.

Absence of amyloid-beta in lenses of Alzheimer patients: a confocal Raman microspectroscopic study.

We have compared the protein profiles in plaques and tangles in the hippocampus of post-mortem Alzheimer brains and in opaque and clear regions in the deep cortex of eye lenses of the same donors. From the 7 Alzheimer donors studied, 1 had pronounced bilateral cortical lens opacities, 1 moderate and 5 only minor or no cortical opacities. We focused on beta-sheet levels, a hallmarking property of amyloid-beta, the major protein of plaques and tau protein, the major protein of tangles in Alzheimer brains. Confocal Raman microspectroscopy and imaging was used in combination with hierarchical cluster analysis. Plaques and tangles show high levels of beta-sheets with a beta-sheet to protein ratio of 1.67. This ratio is 1.12 in unaffected brain tissue surrounding the plaques and tangles. In the lenses this ratio is 1.17 independently of the presence or absence of opacities. This major difference in beta-sheet conformation between hippocampus and lens is supported by Congo red and immunostaining of amyloid-beta and tau which were positive for plaques and tangles in the hippocampus but fully negative for the lens irrespective of the presence or absence of opacities. In line with a previous study (Michael et al., 2013) we conclude that cortical lens opacities are not typical for Alzheimer patients and are not hallmarked by accumulation of amyloid-beta, and can thus not be considered as predictors or indicators of Alzheimer disease as claimed by Goldstein et al. (2003).

Diagnostic Accuracy of Raman Spectroscopy Integrated With Polarized Light Microscopy for Calcium Pyrophosphate-Associated Arthritis.

OBJECTIVE: We studied the performance of integrated Raman polarized light microscopy (iRPolM) for the identification of calcium pyrophosphate (CPP)-associated arthritis (CPPD). METHODS: This is a diagnostic accuracy study including 400 consecutive synovial fluid samples from a single hospital in the Netherlands. Accuracy measures were calculated against polarized light microscopy (PLM) and the 2023 American College of Rheumatology (ACR)/EULAR criteria set for CPPD. RESULTS: The interrater reliability between iRPolM and the 2023 ACR/EULAR criteria set for CPPD was strong (κ = 0.88). The diagnostic performance of iRPolM compared to the 2023 ACR/EULAR criteria set was sensitivity 86.0% (95% confidence interval [CI] 73.3-94.2), specificity 99.1% (95% CI 97.5-99.8), positive likelihood ratio 100.33 (95% CI 32.3-311.3), negative likelihood ratio 0.14 (95% CI 0.07-0.28), positive predictive value 93.5% (95% CI 82.2-97.8), negative predictive value 98.0% (95% CI 82.2-97.8), and accuracy 97.5% (95% CI 95.5-98.8). We allowed rheumatologists to rate the certainty of their microscopic identification of CPP and found a large correspondence between iRPolM and a certain identification (κ = 0.87), whereas only 10% of the uncertain CPP identifications could be confirmed with iRPolM. We identified several novel particle types in synovial fluid analysis, including calcium carbonate crystals, deposited carotenoids, microplastics, and three types of Maltese cross birefringent objects. CONCLUSION: iRPolM can easily identify CPP crystals with a strong diagnostic performance. PLM alone is not specific enough to reliably resolve complicated cases, and the implementation of Raman spectroscopy in rheumatology practice can be of benefit to patients with suspected CPPD.

Identification of extracellular vesicles from their Raman spectra via self-supervised learning.

Extracellular vesicles (EVs) released from cells attract interest for their possible role in health and diseases. The detection and characterization of EVs is challenging due to the lack of specialized methodologies. Raman spectroscopy, however, has been suggested as a novel approach for biochemical analysis of EVs. To extract information from the spectra, a novel deep learning architecture is explored as a versatile variant of autoencoders. The proposed architecture considers the frequency range separately from the intensity of the spectra. This enables the model to adapt to the frequency range, rather than requiring that all spectra be pre-processed to the same frequency range as it was trained on. It is demonstrated that the proposed architecture accepts Raman spectra of EVs and lipoproteins from 13 biological sources and from two laboratories. High reconstruction accuracy is maintained despite large variances in frequency range and noise level. It is also shown that the architecture is able to cluster the biological nanoparticles by their Raman spectra and differentiate them by their origin without pre-processing of the spectra or supervision during learning. The model performs label-free differentiation, including separating EVs from activated vs. non-activated blood platelets and EVs/lipoproteins from prostate cancer patients versus non-cancer controls. The differentiation is evaluated by creating a neural network classifier that observes the features extracted by the model to classify the spectra according to their sample origin. The classification reveals a test sensitivity of 92.2 % and selectivity of 92.3 % over 769 measurements from two labs that have different measurement configurations.

Effect of metal-liquid interface composition on the adsorption of a cyanine dye onto gold nanoparticles.

Synthesis of asymmetric nanoparticles, such as gold nanorods, with tunable optical properties providing metal structures with improved SERS performance is playing a critical role in expanding the use of SERS to imaging and sensing applications. However, the synthetic methods usually require surfactants or polymers as shape-directing agents. These chemicals normally remain firmly bound to the metal after the synthesis, preventing the direct adsorption of a large number of potential analytes and often hampering the chemical functionalization of the surface unless extended, and critical for the nanoparticle stability, postremoval steps were performed. For this reason, it is of great importance for the full exploitation of these nanostructures to gain a deeper insight into the dependence of the analyte-metal interaction to the metal-liquid interface composition. In this article, we investigated in detail the role played by each component of the gold nanorod (GNR) interface in the adsorption of indocyanine green (ICG) as a probe molecule. Citrate-reduced gold nanospheres were used as a model substrate since the negative citrate anions adsorbed onto the metal surface can be easily displaced by those chemicals usually involved in the GNR synthesis, allowing the GNR-like interface composition to be progressively rebuilt and modified at will on the citrate-capped nanoparticles. The obtained results provide a meticulous description of the role played by each individual component of the metal-liquid interface on the ICG interaction with the metal, illustrating how apparently minor experimental changes can dramatically modify the affinity and optical properties of the ICG probe adsorbed onto the nanoparticle.

Test characteristics of Raman spectroscopy integrated with polarized light microscopy for the diagnosis of acute gouty arthritis.

OBJECTIVES: We studied the performance of Raman spectroscopy integrated with polarized light microscopy (iRPolM) as a next-generation technique for synovial fluid analysis in gout. METHODS: This is a prospective study, including consecutive synovial fluid samples drawn from any peripheral swollen joint. Diagnostic accuracy was compared to the 2015 ACR/EULAR Gout classification criteria as a reference test and to polarized light microscopy (PLM) analysis by a rheumatologist. Synovial fluid was analysed with iRPolM after unblinding the PLM results. RESULTS: Two hundred unselected consecutive patient samples were included in this study. Validation against clinical criteria: 67 patients were classified as gout according to 2015 ACR/EULAR classification criteria. Compared to the 2015 ACR/EULAR gout classification criteria, iRPolM had a sensitivity of 77.6% (95% CI: 65.8-86.9), specificity of 97.7% (95% CI: 93.5-99.5), positive predictive value (PPV) of 94.5% (95% CI: 84.9-98.2), negative predictive value (NPV) of 89.7% (95% CI: 84.7-93.1), an accuracy of 91.0% (95% CI: 86.2-94.6), a positive likelihood ratio of 34.4 (95% CI: 11.16-106.10) and a negative likelihood ratio of 0.23 (95% CI: 0.15-0.36). Validation against PLM: 55 samples were positive for MSU according to PLM. The interrater agreement between PLM and iRPolM was near perfect (к=0.90). The sensitivity of iRPolM to identify MSU in PLM-positive samples was 91.2% (95% CI: 80.7-97.1), the specificity was 97.6% (95% CI: 93.0-99.5), the PPV was 94.6% (95% CI: 85.0-98.2), NPV was 96.0% (95% CI: 91.2-98.2) and the accuracy was 95.6% (95% CI: 91.4-98.2). The positive likelihood ratio was 37.4 (95% CI: 12.20-114.71), and the negative likelihood ratio was 0.09 (95% CI: 0.04-0.21). CONCLUSION: iRPolM is a promising next-generation diagnostic tool for rheumatology by diagnosing gout with high specificity, increased objectivity, and a sensitivity comparable to PLM.

Physical association of low density lipoprotein particles and extracellular vesicles unveiled by single particle analysis.

Extracellular vesicles (EVs) in blood plasma are recognized as potential biomarkers for disease. Although blood plasma is easily obtainable, analysis of EVs at the single particle level is still challenging due to the biological complexity of this body fluid. Besides EVs, plasma contains different types of lipoproteins particles (LPPs), that outnumber EVs by orders of magnitude and which partially overlap in biophysical properties such as size, density and molecular makeup. Consequently, during EV isolation LPPs are often co-isolated. Furthermore, physical EV-LPP complexes have been observed in purified EV preparations. Since co-isolation or association of LPPs can impact EV-based analysis and biomarker profiling, we investigated the presence and formation of EV-LPP complexes in biological samples by using label-free atomic force microscopy, cryo-electron tomography and synchronous Rayleigh and Raman scattering analysis of optically trapped particles and fluorescence-based high sensitivity single particle flow cytometry. Furthermore, we evaluated the impact on flow cytometric analysis in the presence of LPPs using in vitro spike-in experiments of purified tumour cell line-derived EVs in different classes of purified human LPPs. Based on orthogonal single-particle analysis techniques we demonstrate that EV-LPP complexes can form under physiological conditions. Furthermore, we show that in fluorescence-based flow cytometric EV analysis staining of LPPs, as well as EV-LPP associations, can influence quantitative and qualitative EV analysis. Lastly, we demonstrate that the colloidal matrix of the biofluid in which EVs reside impacts their buoyant density, size and/or refractive index (RI), which may have consequences for down-stream EV analysis and EV biomarker profiling.

Force spectroscopy and fluorescence microscopy of dsDNA-YOYO-1 complexes: implications for the structure of dsDNA in the overstretching region.

When individual dsDNA molecules are stretched beyond their B-form contour length, they reveal a structural transition in which the molecule extends 1.7 times its contour length. The nature of this transition is still a subject of debate. In the first model, the DNA helix unwinds and combined with the tilting of the base pairs (which remain intact), results in a stretched form of DNA (also known as S-DNA). In the second model the base pairs break resulting effectively in two single-strands, which is referred to as force-induced melting. Here a combination of optical tweezers force spectroscopy with fluorescence microscopy was used to study the structure of dsDNA in the overstretching regime. When dsDNA was stretched in the presence of 10 nM YOYO-1 an initial increase in total fluorescence intensity of the dye-DNA complex was observed and at an extension where the dsDNA started to overstretch the fluorescence intensity leveled off and ultimately decreased when stretched further into the overstretching region. Simultaneous force spectroscopy and fluorescence polarization microscopy revealed that the orientation of dye molecules did not change significantly in the overstretching region (78.0 degrees +/- 3.2 degrees). These results presented here clearly suggest that, the structure of overstretched dsDNA can be explained accurately by force induced melting.

Extracellular Vesicles: A New Source of Biomarkers in Pediatric Solid Tumors? A Systematic Review.

Virtually every cell in the body releases extracellular vesicles (EVs), the contents of which can provide a "fingerprint" of their cellular origin. EVs are present in all bodily fluids and can be obtained using minimally invasive techniques. Thus, EVs can provide a promising source of diagnostic, prognostic, and predictive biomarkers, particularly in the context of cancer. Despite advances using EVs as biomarkers in adult cancers, little is known regarding their use in pediatric cancers. In this review, we provide an overview of published clinical and in vitro studies in order to assess the potential of using EV-derived biomarkers in pediatric solid tumors. We performed a systematic literature search, which yielded studies regarding desmoplastic small round cell tumor, hepatoblastoma, neuroblastoma, osteosarcoma, and rhabdomyosarcoma. We then determined the extent to which the in vivo findings are supported by in vitro data, and vice versa. We also critically evaluated the clinical studies using the GRADE (Grading of Recommendations Assessment, Development, and Evaluation) system, and we evaluated the purification and characterization of EVs in both the in vivo and in vitro studies in accordance with MISEV guidelines, yielding EV-TRACK and PedEV scores. We found that several studies identified similar miRNAs in overlapping and distinct tumor entities, indicating the potential for EV-derived biomarkers. However, most studies regarding EV-based biomarkers in pediatric solid tumors lack a standardized system of reporting their EV purification and characterization methods, as well as validation in an independent cohort, which are needed in order to bring EV-based biomarkers to the clinic.

Membrane invagination in Rhodobacter sphaeroides is initiated at curved regions of the cytoplasmic membrane, then forms both budded and fully detached spherical vesicles.

The purple phototrophic bacteria synthesize an extensive system of intracytoplasmic membranes (ICM) in order to increase the surface area for absorbing and utilizing solar energy. Rhodobacter sphaeroides cells contain curved membrane invaginations. In order to study the biogenesis of ICM in this bacterium mature (ICM) and precursor (upper pigmented band - UPB) membranes were purified and compared at the single membrane level using electron, atomic force and fluorescence microscopy, revealing fundamental differences in their morphology, protein organization and function. Cryo-electron tomography demonstrates the complexity of the ICM of Rba. sphaeroides. Some ICM vesicles have no connection with other structures, others are found nearer to the cytoplasmic membrane (CM), often forming interconnected structures that retain a connection to the CM, and possibly having access to the periplasmic space. Near-spherical single invaginations are also observed, still attached to the CM by a 'neck'. Small indents of the CM are also seen, which are proposed to give rise to the UPB precursor membranes upon cell disruption. 'Free-living' ICM vesicles, which possess all the machinery for converting light energy into ATP, can be regarded as bacterial membrane organelles.

Strategies for patterning biomolecules with dip-pen nanolithography.

Dip-pen nanolithography (DPN) is an atomic force microscopy (AFM)-based lithography technique, which has the ability to fabricate patterns with a feature size down to approximately 15 nm using both top-down and bottom-up approaches. DPN utilizes the water meniscus formed between an AFM tip and a substrate to transfer ink molecules onto surfaces. A major application of this technique is the fabrication of micro- and nano-arrays of patterned biomolecules. To achieve this goal, a variety of chemical approaches has been used. This review concisely describes the development of DPN in the past decade and presents the related chemical strategies that have been reported to fabricate biomolecular patterns with DPN at micrometer and nanometer scale, classified into direct- and indirect DPN methodologies, discussing tip-functionalization strategies as well.