Label-Free Identification of Exosomes using Raman Spectroscopy and Machine Learning.

Exosomes, nano-sized extracellular vesicles (EVs) secreted from cells, carry various cargo molecules reflecting their cells of origin. As EV content, structure, and size are highly heterogeneous, their classification via cargo molecules by determining their origin is challenging. Here, a method is presented combining surface-enhanced Raman spectroscopy (SERS) with machine learning algorithms to employ the classification of EVs derived from five different cell lines to reveal their cellular origins. Using an artificial neural network algorithm, it is shown that the label-free Raman spectroscopy method's prediction ratio correlates with the ratio of HT-1080 exosomes in the mixture. This machine learning-assisted SERS method enables a new direction through label-free investigation of EV preparations by differentiating cancer cell-derived exosomes from those of healthy. This approach will potentially open up new avenues of research for early detection and monitoring of various diseases, including cancer.

Quantifying the effects of antiangiogenic and chemotherapy drug combinations on drug delivery and treatment efficacy.

Tumor-induced angiogenesis leads to the development of leaky tumor vessels devoid of structural and morphological integrity. Due to angiogenesis, elevated interstitial fluid pressure (IFP) and low blood perfusion emerge as common properties of the tumor microenvironment that act as barriers for drug delivery. In order to overcome these barriers, normalization of vasculature is considered to be a viable option. However, insight is needed into the phenomenon of normalization and in which conditions it can realize its promise. In order to explore the effect of microenvironmental conditions and drug scheduling on normalization benefit, we build a mathematical model that incorporates tumor growth, angiogenesis and IFP. We administer various theoretical combinations of antiangiogenic agents and cytotoxic nanoparticles through heterogeneous vasculature that displays a similar morphology to tumor vasculature. We observe differences in drug extravasation that depend on the scheduling of combined therapy; for concurrent therapy, total drug extravasation is increased but in adjuvant therapy, drugs can penetrate into deeper regions of tumor.

Differentiation of tumor vasculature heterogeneity levels in small animals based on total hemoglobin concentration using magnetic resonance-guided diffuse optical tomography in vivo.

Insight into the vasculature of the tumor in small animals has the potential to impact many areas of cancer research. The heterogeneity of the vasculature of a tumor is directly related to tumor stage and disease progression. In this small scale animal study, we investigated the feasibility of differentiating tumors with different levels of vasculature heterogeneity in vivo using a previously developed hybrid magnetic resonance imaging (MRI) and diffuse optical tomography (DOT) system for small animal imaging. Cross-sectional total hemoglobin concentration maps of 10 Fisher rats bearing R3230 breast tumors are reconstructed using multi-wavelength DOT measurements both with and without magnetic resonance (MR) structural a priori information. Simultaneously acquired MR structural images are used to guide and constrain the DOT reconstruction, while dynamic contrast-enhanced MR functional images are used as the gold standard to classify the vasculature of the tumor into two types: high versus low heterogeneity. These preliminary results show that the stand-alone DOT is unable to differentiate tumors with low and high vascular heterogeneity without structural a priori information provided by a high resolution imaging modality. The mean total hemoglobin concentrations comparing the vasculature of the tumors with low and high heterogeneity are significant (p-value 0.02) only when MR structural a priori information is utilized.

Comprehensive analytical model for CW laser induced heat in turbid media.

In this work, we present a new analytical approach to model continuous wave laser induced temperature in highly homogeneous turbid media. First, the diffusion equation is used to model light transport and a comprehensive solution is derived analytically by obtaining a special Greens' function. Next, the time-dependent bio-heat equation is used to describe the induced heat increase and propagation within the medium. The bio-heat equation is solved analytically utilizing the separation of variables technique. Our theoretical model is successfully validated using numerical simulations and experimental studies with agarose phantoms and ex-vivo chicken breast samples. The encouraging results show that our method can be implemented as a simulation tool to determine important laser parameters that govern the magnitude of temperature rise within homogenous biological tissue or organs.

Examination of annulus fibrosus and nucleus pulposus in cervical and lumbar intervertebral disc herniation patients by scanning acoustic microscopy, scanning electron microscopy and energy dispersive spectroscopy.

Intervertebral disc herniation (IVDH) is observed in humans as a result of the alteration of annulus fibrous (AF) and nucleus pulposus (NP) tissue compositions in intervertebral discs. In this study, we studied the feasibility of scanning acoustic microscopy (SAM), scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS) in characterizing the herniated segments of AF and NP tissues from male and female patients. SAM determined the acoustic property variations in AF and NP tissues by calculating the acoustic impedance values of samples of 15 patients. SEM obtained higher resolution images and EDS made elemental analysis of the specimen. Consequently, we suggest that these techniques have the potential to be combined for the investigation and removal of the disrupted AF and NP tissues with micrometer resolution in clinics.

Label-free differentiation of functional zones in mature mouse placenta using micro-Raman imaging.

In histopathology, it is highly crucial to have chemical and structural information about tissues. Additionally, the segmentation of zones within a tissue plays a vital role in investigating the functions of these regions for better diagnosis and treatment. The placenta plays a vital role in embryonic and fetal development and in diagnosing some diseases associated with its dysfunction. This study provides a label-free approach to obtain the images of mature mouse placenta together with the chemical differences between the tissue compartments using Raman spectroscopy. To generate the Raman images, spectra of placental tissue were collected using a custom-built optical setup. The pre-processed spectra were analyzed using statistical and machine learning methods to acquire the Raman maps. We found that the placental regions called decidua and the labyrinth zone are biochemically distinct from the junctional zone. A histologist performed a comparison and evaluation of the Raman map with histological images of the placental tissue, and they were found to agree. The results of this study show that Raman spectroscopy offers the possibility of label-free monitoring of the placental tissue from mature mice while simultaneously revealing crucial structural information about the zones.

Technical note: Application of an optical hydrophone to ionoacoustic range detection in a tissue-mimicking agar phantom.

BACKGROUND: Ionoacoustics is a promising approach to reduce the range uncertainty in proton therapy. A miniature-sized optical hydrophone (OH) was used as a measuring device to detect weak ionoacoustic signals with a high signal-to-noise ratio in water. However, further development is necessary to prevent wave distortion because of nearby acoustic impedance discontinuities while detection is conducted on the patient's skin. PURPOSE: A prototype of the probe head attached to an OH was fabricated and the required dimensions were experimentally investigated using a 100-MeV proton beam from a fixed-field alternating gradient accelerator and k-Wave simulations. The beam range of the proton in a tissue-mimicking phantom was estimated by measuring γ-waves and spherical ionoacoustic waves with resonant frequency (SPIRE). METHODS: Four sizes of probe heads were fabricated from agar blocks for the OH. Using the prototype, the Î³-wave was detected at distal and lateral positions to the Bragg peak on the phantom surface for proton beams delivered at seven positions. For SPIRE, independent measurements were performed at distal on- and off-axis positions. The range positions were estimated by solving the linear equation using the sensitive matrix for the γ-wave and linear fitting of the correlation curve for SPIRE; they were compared with those measured using a film. RESULTS: The first peak of the γ-wave was undistorted with the 3 × 3 × 3-cm3 probe head used at the on-axis and 3-cm off-axis positions. The range positions estimated by the γ-wave agreed with the film-based range in the depth direction (the maximum deviation was 0.7 mm), although a 0.6-2.1 mm deviation was observed in the lateral direction. For SPIRE, the deviation was <1 mm for the two measurement positions. CONCLUSIONS: The attachment of a relatively small-sized probe head allowed the OH to measure the beam range on the phantom surface.

Virtual source method for diffuse optical imaging.

The Green's function for diffusive wave propagation can be obtained by utilizing the representation theorems of the convolution type and the correlation type. In this work, the Green's function is retrieved by making use of the Robin boundary condition and the representation theorems for diffusive media. The diffusive Green's function between two detectors for photon flux is calculated by combining detector readings due to point light sources and utilizing virtual light sources at the detector positions in optical tomography. Two dimensional simulations for a circular region with eight sources and eight detectors located on the boundary are performed using a finite element method to demonstrate the feasibility of virtual sources. The most important potential application would be the replacement of noisy measurements with synthetic measurements that are provided by the virtual sources. This becomes an important issue in small animal and human studies. In addition, the same method may also be used to reduce the imaging time.

Differentiation of advanced generation mutant wheat lines: Conventional techniques versus Raman spectroscopy.

This research aimed to assess the feasibility of utilizing Raman spectroscopy in plant breeding programs. For this purpose, the evaluation of the mutant populations set up the application of 4 mM NaN3 to the somatic embryos obtained from mature wheat (Triticum aestivum L. Adana-99 cv.) embryos. Advanced wheat mutant lines, which were brought up to the seventh generation with salt stress tolerance by following in vitro and in vivo environments constructed by mutated populations, were evaluated using conventional techniques [measurement of antioxidant enzyme activities (SOD, CAT, and POX), total chlorophyll, TBARS, and proline contents; measurement of the concentration of Na+ and K+ ions; and evaluation of gene expression by qPCR (TaHKT2;1, TaHKT1;5, TaSOS1, TaNa+/H+ vacuolar antiporter, TaV-PPase, TaV-ATPase, and TaP5CS)] and Raman spectroscopy. In this research, no significant difference was found in the increase of SOD, CAT, and POX antioxidant enzyme activities between the salt-treated and untreated experimental groups of the commercial cultivar, while there was a statistically significant increase in salt-treated advanced generation mutant lines as compared to control and the salt-treated commercial cultivar. Proline showed a statistically significant increase in all experimental groups compared to the untreated commercial cultivar. The degradation in the amount of chlorophyll was lower in the salt-treated advanced generation mutant lines than in the salt-treated commercial cultivar. According to gene expression studies, there were statistical differences at various levels in terms of Na+ and/or K+ uptake from soil to plant (TaHKT2;1, TaHKT1;5, and TaSOS1), and Na+ compartmentalizes into the cell vacuole (TaNa+/H+ vacuolar antiporter, Ta vacuolar pyrophosphatase, and Ta vacuolar H+-ATPase). The expression activity of TaP5CS, which is responsible for the transcription of proline, is similar to the content of proline in the current study. As a result of Raman spectroscopy, the differences in peaks represent the protein-related bands in mutant lines having a general decreasing trend in intensity when compared to the commercial cultivar. Amide-I (1,630 and 1,668 cm-1), Histidine, Lysine, Arginine, and Leucine bands (823, 849, 1,241, 1,443, and 1,582 cm-1) showed decreasing wavenumbers. Beta-carotene peaks at 1,153 and 1,519 cm-1 showed increasing trends when the normalized Raman intensities of the mutant lines were compared.

Comparison of the human's and camel's red blood cell deformability by optical tweezers and Raman spectroscopy.

Red blood cells of vertebrates have undergone evolutionary changes over time, leading to the diversification of morphological and mechanical properties of red blood cells (RBCs). Among the vertebrates, camelids have the most different RBC characteristics. As a result of adaptation to the desert environment, camelid RBCs can expand twice as much of their total volume in the case of rapid hydration yet are almost undeformable under mechanical stress. In this work, the mechanical and chemical differences in the RBC properties of the human and camelid species were examined using optical tweezers and Raman spectroscopy. We measured the deformability of camel and human RBCs at the single-cell level using optical tweezers. We found that the deformability index (DI) of the camel and the human RBCs were 0.024 ± 0.019 and 0.215 ± 0.061, respectively. To investigate the chemical properties of these cells, we measured the Raman spectra of the whole blood samples. The result of our study indicated that some of the Raman peaks observed on the camel's blood spectrum were absent in the human blood's spectrum, which further points to the difference in chemical contents of these two species' RBCs.

Application of scanning acoustic microscopy for evaluation of MMP activation in multiple cancer cell lines with a smart probe.

Background/aim: Matrix metalloproteinases (MMPs) play an important role in the evaluation of many cancer types; however, the detection usually presents a challenge. Further assays for a better understanding of the fundamental roles of MMPs in pathophysiology are still needed. We aimed to use an activatable probe in scanning acoustic microscopy (SAM) to evaluate acoustically if the probe can aid the visualization of the effects of in vitro MMP activity. Materials and methods: We applied scanning acoustic impedance microscopy to obtain acoustic impedance maps of the cell line models of HT1080, THP-1, and SK-MEL-28 with and without MMPSense 680 probe incubation. We visually validated our results using confocal laser scanning microscopy imaging. We further analyzed the effects of MMPSense 680 probe on cell viabilities to eliminate any artifacts. Results: This is the first study presenting the applicability of SAM in the acoustical evaluation of MMPSense 680 probe cleavage in a cellular medium through acoustic impedance measurements. We proposed that SAM measurement with the activatable probe can be used as an effective tool for studying the acoustical variations of MMP activities in cell lines. As a result, we detected MMPSense 680 probe cleavage in HT1080 human fibrosarcoma cell line. Conclusion: We showed that SAM with the smart probe can detect proteolytic activity using MMPSense 680 in in vitro HT1080 cell line by acoustic impedance measurements. SAM could be proposed as an alternative tool leading a novel way for a better understanding of the roles of MMPs in cancer progression before clinical settings.

Ionoacoustic application of an optical hydrophone to detect proton beam range in water.

BACKGROUND: Proton range uncertainty has been the main factor limiting the ability of proton therapy to concentrate doses to tumors to their full potential. Ionoacoustic (IA) range verification is an approach to reducing this uncertainty by detecting thermoacoustic waves emitted from an irradiated volume immediately following a pulsed proton beam delivery; however, the signal weakness has been an obstacle to its clinical application. To increase the signal-to-noise ratio (SNR) with the conventional piezoelectric hydrophone (PH), the detector-sensitive volume needs to be large, but it could narrow the range of available beam angles and disturb real-time images obtained during beam delivery. PURPOSE: To prevent this issue, we investigated a millimeter-sized optical hydrophone (OH) that exploits the laser interferometric principle. For two types of IA waves [γ-wave emitted from the Bragg peak (BP) and a spherical IA wave with resonant frequency (SPIRE) emitted from the gold fiducial marker (GM)], comparisons were made with PH in terms of waveforms, SNR, range detection accuracy, and signal intensity robustness against the small detector misalignment, particularly for SPIRE. METHODS: A 100-MeV proton beam with a 27 ns pulse width and 4 mm beam size was produced using a fixed-field alternating gradient accelerator and was irradiated to the water phantom. The GM was set on the beam's central axis. Acrylic plates of various thicknesses, up to 12 mm, were set in front of the phantoms to shift the proton range. OH was set distal and lateral to the beam, and the range was estimated using the time-of-flight method for γ-wave and by comparing with the calibration data (SPIRE intensity versus the distance between the GM and BP) derived from an IA wave transport simulation for SPIRE. The BP dose per pulse was 0.5-0.6 Gy. To measure the variation in SPIRE amplitude against the hydrophone misalignment, the hydrophone was shifted by ± 2 mm at a maximum in lateral directions. RESULTS: Despite its small size, OH could detect γ-wave with a higher SNR than the conventional PH (diameter, 29 mm), and a single measurement was sufficient to detect the beam range with a submillimeter accuracy in water. In the SPIRE measurement, OH was far more robust against the detector misalignment than the focused PH (FPH) used in our previous study [5%/mm (OH) versus 80%/mm (FPH)], and the correlation between the measured SPIRE intensity and the distance between the GM and BP agreed well with the simulation results. However, the OH sensitivity was lower than the FPH sensitivity, and about 5.6-Gy dose was required to decrease the intensity variation among measurements to less than 10%. CONCLUSION: The miniature OH was found to detect weak IA signals produced by proton beams with a BP dose used in hypofractionated regimens. The OH sensitivity improvement at the MHz regime is worth exploring as the next step.

Assessing the therapeutic response of tumors to hypoxia-targeted prodrugs with an in silico approach.

Tumor hypoxia is commonly recognized as a condition stimulating the progress of the aggressive phenotype of tumor cells. Hypoxic tumor cells inhibit the delivery of cytotoxic drugs, causing hypoxic areas to receive insufficient amounts of anticancer agents, which results in adverse treatment responses. Being such an obstruction to conventional therapies for cancer, hypoxia might be considered a target to facilitate the efficacy of treatments in the resistive environment of tumor sites. In this regard, benefiting from prodrugs that selectively target hypoxic regions remains an effective approach. Additionally, combining hypoxia-activated prodrugs (HAPs) with conventional chemotherapeutic drugs has been used as a promising strategy to eradicate hypoxic cells. However, determining the appropriate sequencing and scheduling of the combination therapy is also of great importance in obtaining favorable results in anticancer therapy. Here, benefiting from a modeling approach, we study the efficacy of HAPs in combination with chemotherapeutic drugs on tumor growth and the treatment response. Different treatment schedules have been investigated to see the importance of determining the optimal schedule in combination therapy. The effectiveness of HAPs in varying hypoxic conditions has also been explored in the study. The model provides qualitative conclusions about the treatment response, as the maximal benefit is obtained from combination therapy with greater cell death for highly hypoxic tumors. It has also been observed that the antitumor effects of HAPs show a hypoxia-dependent profile.

Chemotherapy response prediction with diffuser elapser network.

In solid tumors, elevated fluid pressure and inadequate blood perfusion resulting from unbalanced angiogenesis are the prominent reasons for the ineffective drug delivery inside tumors. To normalize the heterogeneous and tortuous tumor vessel structure, antiangiogenic treatment is an effective approach. Additionally, the combined therapy of antiangiogenic agents and chemotherapy drugs has shown promising effects on enhanced drug delivery. However, the need to find the appropriate scheduling and dosages of the combination therapy is one of the main problems in anticancer therapy. Our study aims to generate a realistic response to the treatment schedule, making it possible for future works to use these patient-specific responses to decide on the optimal starting time and dosages of cytotoxic drug treatment. Our dataset is based on our previous in-silico model with a framework for the tumor microenvironment, consisting of a tumor layer, vasculature network, interstitial fluid pressure, and drug diffusion maps. In this regard, the chemotherapy response prediction problem is discussed in the study, putting forth a proof of concept for deep learning models to capture the tumor growth and drug response behaviors simultaneously. The proposed model utilizes multiple convolutional neural network submodels to predict future tumor microenvironment maps considering the effects of ongoing treatment. Since the model has the task of predicting future tumor microenvironment maps, we use two image quality evaluation metrics, which are structural similarity and peak signal-to-noise ratio, to evaluate model performance. We track tumor cell density values of ground truth and predicted tumor microenvironments. The model predicts tumor microenvironment maps seven days ahead with the average structural similarity score of 0.973 and the average peak signal ratio of 35.41 in the test set. It also predicts tumor cell density at the end day of 7 with the mean absolute percentage error of [Formula: see text].

Quantification of salt stress in wheat leaves by Raman spectroscopy and machine learning.

The salinity level of the growing medium has diverse effects on the development of plants, including both physical and biochemical changes. To determine the salt stress level of a plant endures, one can measure these structural and chemical changes. Raman spectroscopy and biochemical analysis are some of the most common techniques in the literature. Here, we present a combination of machine learning and Raman spectroscopy with which we can both find out the biochemical change that occurs while the medium salt concentration changes and predict the level of salt stress a wheat sample experiences accurately using our trained regression models. In addition, by applying different machine learning algorithms, we compare the level of success for different algorithms and determine the best method to use in this application. Production units can take actions based on the quantitative information they get from the trained machine learning models related to salt stress, which can potentially increase efficiency and avoid the loss of crops.

Atrial fibrillation designation with micro-Raman spectroscopy and scanning acoustic microscope.

Atrial fibrillation (AF) is diagnosed with the electrocardiogram, which is the gold standard in clinics. However, sufficient arrhythmia monitoring takes a long time, and many of the tests are made in only a few seconds, which can lead arrhythmia to be missed. Here, we propose a combined method to detect the effects of AF on atrial tissue. We characterize tissues obtained from patients with or without AF by scanning acoustic microscopy (SAM) and by Raman spectroscopy (RS) to construct a mechano-chemical profile. We classify the Raman spectral measurements of the tissue samples with an unsupervised clustering method, k-means and compare their chemical properties. Besides, we utilize scanning acoustic microscopy to compare and determine differences in acoustic impedance maps of the groups. We compared the clinical outcomes with our findings using a neural network classification for Raman measurements and ANOVA for SAM measurements. Consequently, we show that the stiffness profiles of the tissues, corresponding to the patients with chronic AF, without AF or who experienced postoperative AF, are in agreement with the lipid-collagen profiles obtained by the Raman spectral characterization.

Acoustic impedance measurement of tissue mimicking materials by using scanning acoustic microscopy.

Tissue-mimicking materials (TMMs) play a key role in the quality assurance of ultrasound diagnostic equipment and should have acoustic properties similar to human tissues. We propose a method to quantify the acoustic properties of TMM samples through the use of an 80 MHz Scanning Acoustic Microscopy (SAM), which provides micrometer resolution and fast data recording. We produced breast TMM samples in varying compositions that resulted in acoustic impedance values in the range of 1.373 ± 0.031 and 1.707 ± 0.036 MRayl. Additionally, liver TMM and blood mimicking fluid (BMF) samples were prepared that had acoustic impedance values of 1.693 ± 0.085 MRayl and 1.624 ± 0.006 MRayl, respectively. The characterization of the TMMs by SAM may provide reproducible and uniform acoustic reference data for tissue substitutes in a single-run microscopy experiment.

Quantifying the influences of radiation therapy on deformability of human red blood cells by dual-beam optical tweezers.

Radiation therapy is widely used as a treatment tool for malignancies. However, radiation-related complications are still unavoidable risks for off-target cells. Little is known about radiation therapy's possible effects on mechanical features of the off-target cells such as human red blood cells (RBCs). RBCs are nucleus-free circulating cells that can deform without losing functionality in healthy conditions. Thus, to evaluate in vitro effects of radiation therapy on the healthy plasma membrane of cells, RBCs were selected as a primary test model. RBCs were exposed to clinically prescribed radiotherapy doses of 2 Gy, 12 Gy and, 25 Gy, and each radiotherapy dose group was compared to a non-irradiated group. Cells were characterized by stretching using dual-beam optical tweezers and compared using the resulting deformability index. The group receiving the highest radiation dose was found statistically distinguishable from the control group (DI0Gy = 0.33 ± 0.08), and revealed the highest deformability index (DI25Gy = 0.38 ± 0.11, p = 0.0068), while no significant differences were found for 2 Gy (DI2Gy = 0.33 ± 0.08, p = 0.9) and 12 Gy (DI12Gy = 0.31 ± 0.09, p = 0.2) dose groups. Based on these findings, we conclude that radiotherapy exposure may alter the deformability of red blood cells depending on the dose amount, and measurement of deformability index by dual-beam optical tweezers can serve as a sensitive biomarker to probe responses of cells to the radiotherapy.

Raman tweezers as an alternative diagnostic tool for paroxysmal nocturnal hemoglobinuria.

Paroxysmal nocturnal hemoglobinuria (PNH) is a rare disease characterized by hemolysis of red blood cells (RBC) and venous thrombosis. The gold standard method for the diagnosis of this disease is flow cytometry. Here, we propose a combined optical tweezers and Raman spectral (Raman tweezers) approach to analyze blood samples from volunteers with or without PNH conditions. Raman spectroscopy is a well-known method for investigating a material's chemical structure and is also used in molecular analysis of biological compounds. In this study, we trap individual RBCs found in whole blood samples drawn from PNH patients and the control group. Evaluation of the Raman spectra of these cells by band component analysis and machine learning shows a significant difference between the two groups. The specificity and the sensitivity of the training performed by support vector machine (SVM) analysis were found to be 81.8% and 78.3%, respectively. This study shows that an immediate and high accuracy test result is possible for PNH disease by employing Raman tweezers and machine learning.

Aortic aneurysm evaluation by scanning acoustic microscopy and Raman spectroscopy.

Aortic aneurysm is observed as a result of the extensive alteration in the elasticity of the aortic wall due to the breakdown of elastin and collagen. In this study, we studied the feasibility of scanning acoustic microscopy (SAM) and Raman spectroscopy (RS) in characterizing the dilated segments of the aorta from male and female patients with aortic aneurysm. SAM determined the acoustic property variation in the aorta by calculating the acoustic impedance values of aorta samples of 18 patients. RS determined the disease states by analyzing the chemical variation especially in the peaks related to elastin and collagen using the k-means classification method. Consequently, we assume that combining these two techniques in clinics will help to investigate the dilated segment of the aorta with micrometer resolution, which will reduce the possibility of new aneurysm formation due to a segment not excised during the surgery.