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Cells Jul 2023Cancer is the most common and fatal disease around the globe, with an estimated 19 million newly diagnosed patients and approximately 10 million deaths annually....
Cancer is the most common and fatal disease around the globe, with an estimated 19 million newly diagnosed patients and approximately 10 million deaths annually. Patients with cancer struggle daily due to difficult treatments, pain, and financial and social difficulties. Detecting the disease in its early stages is critical in increasing the likelihood of recovery and reducing the financial burden on the patient and society. Currently used methods for the diagnosis of cancer are time-consuming, producing discomfort and anxiety for patients and significant medical waste. The main goal of this study is to evaluate the potential of Raman spectroscopy-based machine learning for the identification and characterization of precancerous and cancerous cells. As a representative model, normal mouse primary fibroblast cells (NFC) as healthy cells; a mouse fibroblast cell line (NIH/3T3), as precancerous cells; and fully malignant mouse fibroblasts (MBM-T) as cancerous cells were used. Raman spectra were measured from three different sites of each of the 457 investigated cells and analyzed by principal component analysis (PCA) and linear discriminant analysis (LDA). Our results showed that it was possible to distinguish between the normal and abnormal (precancerous and cancerous) cells with a success rate of 93.1%; this value was 93.7% when distinguishing between normal and precancerous cells and 80.2% between precancerous and cancerous cells. Moreover, there was no influence of the measurement site on the differentiation between the different examined biological systems.
Topics: Animals; Mice; Spectrum Analysis, Raman; Early Detection of Cancer; Discriminant Analysis; Carcinoma, Squamous Cell; Precancerous Conditions
PubMed: 37508572
DOI: 10.3390/cells12141909 -
Biomacromolecules Feb 2024Even though the physical nature of shear and longitudinal moduli are different, empirical correlations between them have been reported in several biological systems....
Even though the physical nature of shear and longitudinal moduli are different, empirical correlations between them have been reported in several biological systems. This correlation is of fundamental interest and immense practical value in biomedicine due to the importance of the shear modulus and the possibility to map the longitudinal modulus at high-resolution with all-optical spectroscopy. We investigate the origin of such a correlation in hydrogels. We hypothesize that both moduli are influenced in the same direction by underlying physicochemical properties, which leads to the observed material-dependent correlation. Matching theoretical models with experimental data, we quantify the scenarios in which the correlation holds. For polymerized hydrogels, a correlation was found across different hydrogels through a common dependence on the effective polymer volume fraction. For hydrogels swollen to equilibrium, the correlation is valid only within a given hydrogel system, as the moduli are found to have different scalings on the swelling ratio. The observed correlation allows one to extract one modulus from another in relevant scenarios.
Topics: Hydrogels; Polymers; Spectrum Analysis; Models, Theoretical; Viscosity
PubMed: 38156622
DOI: 10.1021/acs.biomac.3c01073 -
Mikrochimica Acta Dec 2023Considering the need for a more time and cost-effective method for lamotrigine (LTG) detection in clinics we developed a fast and robust label-free assay based on...
Considering the need for a more time and cost-effective method for lamotrigine (LTG) detection in clinics we developed a fast and robust label-free assay based on surface-enhanced Raman scattering (SERS) for LTG quantification from human serum. The optimization and application of the developed assay is presented showing the: (i) exploration of different methods for LTG separation from human serum; (ii) implementation of a molecular adsorption step on an ordered Au nanopillar SERS substrate; (iii) adaptation of a fast scanning of the SERS substrate, performed with a custom-built compact Raman spectrometer; and (iv) development of LTG quantification methods with univariate and multivariate spectral data analysis. Our results showed, for the first time, the SERS-based characterization of LTG and its label-free identification in human serum. We found that combining a miniaturized solid phase extraction, as sample pre-treatment with the SERS assay, and using a multivariate model is an optimal strategy for LTG quantification in human serum in a linear range from 9.5 to 75 μM, with LoD and LoQ of 3.2 μM and 9.5 μM, respectively, covering the suggested clinical therapeutic window. We also showed that the developed assay allowed for quantifying LTG from human serum in the presence of other drugs, thereby demonstrating the robustness of label-free SERS. The sensing approach and instrumentation can be further automated and integrated in devices that can advance the drug monitoring in real clinical settings.
Topics: Humans; Lamotrigine; Anticonvulsants; Spectrum Analysis, Raman; Data Analysis
PubMed: 38036694
DOI: 10.1007/s00604-023-06085-3 -
Blood Advances Feb 2024
Topics: Spectrum Analysis, Raman; T-Lymphocytes
PubMed: 38349671
DOI: 10.1182/bloodadvances.2023012129 -
Scientific Reports Sep 2023Polarimetry is an optical characterization technique capable of analyzing the polarization state of light reflected by materials and biological samples. In this study,...
Polarimetry is an optical characterization technique capable of analyzing the polarization state of light reflected by materials and biological samples. In this study, we investigate the potential of Müller matrix polarimetry (MMP) to analyze fresh pancreatic tissue samples. Due to its highly heterogeneous appearance, pancreatic tissue type differentiation is a complex task. Furthermore, its challenging location in the body makes creating direct imaging difficult. However, accurate and reliable methods for diagnosing pancreatic diseases are critical for improving patient outcomes. To this end, we measured the Müller matrices of ex-vivo unfixed human pancreatic tissue and leverage the feature-learning capabilities of a machine-learning model to derive an optimized data representation that minimizes normal-abnormal classification error. We show experimentally that our approach accurately differentiates between normal and abnormal pancreatic tissue. This is, to our knowledge, the first study to use ex-vivo unfixed human pancreatic tissue combined with feature-learning from raw Müller matrix readings for this purpose.
Topics: Humans; Diagnostic Imaging; Spectrum Analysis
PubMed: 37775538
DOI: 10.1038/s41598-023-43195-7 -
PloS One 2023Photoacoustic and absorption spectroscopy imaging are safe and non-invasive molecular quantification techniques, which do not utilize ionizing radiation and allow for...
Photoacoustic and absorption spectroscopy imaging are safe and non-invasive molecular quantification techniques, which do not utilize ionizing radiation and allow for repeated probing of samples without them being contaminated or damaged. Here we assessed the potential of these techniques for measuring biochemical parameters. We investigated the statistical association between 31 time and frequency domain features derived from photoacoustic and absorption spectroscopy signals and 19 biochemical blood parameters. We found that photoacoustic and absorption spectroscopy imaging features are significantly correlated with 14 and 17 individual biochemical parameters, respectively. Moreover, some of the biochemical blood parameters can be accurately predicted based on photoacoustic and absorption spectroscopy imaging features by polynomial regression. In particular, the levels of uric acid and albumin can be accurately explained by a combination of photoacoustic and absorption spectroscopy imaging features (adjusted R-squared > 0.75), while creatinine levels can be accurately explained by the features of the photoacoustic system (adjusted R-squared > 0.80). We identified a number of imaging features that inform on the biochemical blood parameters and can be potentially useful in clinical diagnosis. We also demonstrated that linear and non-linear combinations of photoacoustic and absorption spectroscopy imaging features can accurately predict some of the biochemical blood parameters. These results demonstrate that photoacoustic and absorption spectroscopy imaging systems show promise for future applications in clinical practice.
Topics: Humans; Spectrum Analysis; Image Processing, Computer-Assisted; Diagnostic Imaging; Albumins; Photoacoustic Techniques
PubMed: 37540721
DOI: 10.1371/journal.pone.0289704 -
Tomography (Ann Arbor, Mich.) Aug 2023This study aimed to develop a time-efficient method of acquiring simultaneous, dual-slice MR spectroscopic imaging (MRSI) for the evaluation of brain metabolism.
BACKGROUND
This study aimed to develop a time-efficient method of acquiring simultaneous, dual-slice MR spectroscopic imaging (MRSI) for the evaluation of brain metabolism.
METHODS
Adaptive Hadamard-encoded pulses were developed and integrated with atlas-based automatic prescription. The excitation profiles were evaluated via simulation, phantom and volunteer experiments. The feasibility of γ-aminobutyric acid (GABA)-edited dual-slice MRSI was also assessed.
RESULTS
The signal between slices in the dual-band MRSI was less than 1% of the slice profiles. Data from a homemade phantom containing separate, interfacing compartments of creatine and acetate solutions demonstrated ~0.4% acetate signal contamination relative to the amplitude in the excited creatine compartment. The normalized signal-to-noise ratios from atlas-based acquisitions in volunteers were found to be comparable between dual-slice, Hadamard-encoded MRSI and 3D acquisitions. The mean and standard deviation of the coefficients of variation for NAA/Cho from the repeated volunteer scans were 8.2% ± 0.8% and 10.1% ± 3.7% in the top and bottom slices, respectively. GABA-edited, dual-slice MRSI demonstrated simultaneous detection of signals from GABA and coedited macromolecules (GABA+) from both superior grey and deep grey regions of volunteers.
CONCLUSION
This study demonstrated a fully automated dual-slice MRSI acquisition using atlas-based automatic prescription and adaptive Hadamard-encoded pulses.
Topics: Humans; Creatine; Spectrum Analysis; Magnetic Resonance Imaging; Phantoms, Imaging; gamma-Aminobutyric Acid
PubMed: 37736980
DOI: 10.3390/tomography9050127 -
Analytical Biochemistry Jul 2023Exosomes are potential biomarkers for disease diagnosis and treatment, as well as drug carriers. However, as their isolation and detection remain critical issues,...
Exosomes are potential biomarkers for disease diagnosis and treatment, as well as drug carriers. However, as their isolation and detection remain critical issues, convenient, rapid, low-cost, and effective methods are necessary. In this study, we present a rapid and simple method for directly capturing and analyzing exosomes from complex cell culture media using CaTiO:Eu@FeO multifunctional nanocomposites. The CaTiO:Eu@FeO nanocomposites were prepared by high-energy ball-milling and used to isolate exosomes by binding CaTiO:Eu@FeO nanocomposites and the hydrophilic phosphate head of the exosome phospholipids. Notably, the developed CaTiO:Eu@FeO multifunctional nanocomposites achieved results comparable with those of commercially available TiO and were separated using a magnet within 10 min. Moreover, we report a surface-enhanced Raman scattering (SERS)-based immunoassay for detecting the exosome biomarker CD81. Gold nanorods (Au NRs) were modified with detection antibodies, and antibody-conjugated Au NRs were labeled with 3, 3, diethylthiatricarbocyanine iodide (DTTC) as the SERS tags. A method combining magnetic separation and SERS was developed to detect exosomal biomarker CD81. The results of this study demonstrate the feasibility of this new technique as a useful tool for exosome isolation and detection.
Topics: Exosomes; Nanocomposites; Gold; Spectrum Analysis, Raman; Magnetics
PubMed: 37201773
DOI: 10.1016/j.ab.2023.115161 -
Environmental Research Aug 2023Rock particles from drilling and blasting during tunnel construction (DB particles) are released to the aquatic environment where they may cause negative toxicological...
Rock particles from drilling and blasting during tunnel construction (DB particles) are released to the aquatic environment where they may cause negative toxicological and ecological effects. However, there exists little research on the difference in morphology and structure of these particles. Despite this DB particles are assumed to be sharper and more angular than naturally eroded particles (NE particles), and in consequence cause greater mechanical abrasion to biota. Moreover, morphology of DB particles is assumed to depend on geology, thus depending on where construction takes place different morphologies may be emitted. The objectives in the current study were to investigate the morphological differences between DB and NE particles, and the influence of mineral and elemental content on DB particles. Particle geochemistry and morphology were characterized by inductively coupled plasma mass spectrometry, micro-X-ray fluorescence, X-ray diffraction, environmental scanning electron microscope interfaced with energy dispersive X-ray, stereo microscope, dynamic image analysis and coulter counter. DB particles (61-91% < 63 μm) collected from five different tunnel construction locations in Norway were 8-15% more elongated (lower aspect ratio) than NE particles from river water and sediments, although their angularity was similar (solidity; diff 0.3-0.8%). Despite distinct mineral and elemental characteristics between tunnel construction locations, DB morphology was not explained by geochemical content since only 2-2.1% of the variance was explained. This suggests that particle formation mechanisms during drilling and blasting are more influential of morphology than mineralogy, when working in granite-gneiss terrain. When tunnelling in granite-gneiss terrain, particles with greater elongation than natural particles may enter aquatic systems.
Topics: Particle Size; Silicon Dioxide; Spectrum Analysis; Environmental Monitoring
PubMed: 37268214
DOI: 10.1016/j.envres.2023.116250 -
Aging Clinical and Experimental Research Mar 2024Osteoporosis in males is largely under-diagnosed and under-treated, with most of the diagnosis confirmed only after an osteoporotic fracture. Therefore, there is an...
BACKGROUND
Osteoporosis in males is largely under-diagnosed and under-treated, with most of the diagnosis confirmed only after an osteoporotic fracture. Therefore, there is an urgent need for highly accurate and precise technologies capable of identifying osteoporosis earlier, thereby avoiding complications from fragility fractures.
AIMS
This study aimed to evaluate the diagnostic accuracy and precision of the non-ionizing technology Radiofrequency Echographic Multi Spectrometry (REMS) for the diagnosis of osteoporosis in a male population in comparison with conventional Dual-energy X-ray Absorptiometry (DXA).
METHODS
A cohort of 603 Caucasian males aged between 30 and 90 years were involved in the study. All the enrolled patients underwent lumbar and femoral scans with both DXA and REMS. The diagnostic agreement between REMS and DXA-measured BMD was expressed by Pearson correlation coefficient and Bland-Altman method. The accuracy of the diagnostic classification was evaluated by the assessment of sensitivity and specificity considering DXA as reference.
RESULTS
A significant correlation between REMS- and DXA-measured T-score values (r = 0.91, p < 0.0001) for lumbar spine and for femoral neck (r = 0.90, p < 0.0001) documented the substantial equivalence of the two measurement techniques. Bland-Altman outcomes showed that the average difference in T-score measurement is very close to zero (-0.06 ± 0.60 g/cm for lumbar spine and - 0.07 ± 0.44 g/cm for femoral neck) confirming the agreement between the two techniques. Furthermore, REMS resulted an effective technique to discriminate osteoporotic patients from the non-osteoporotic ones on both lumbar spine (sensitivity = 90.1%, specificity = 93.6%) and femoral neck (sensitivity = 90.9%, specificity = 94.6%). Precision yielded RMS-CV = 0.40% for spine and RMS-CV = 0.34% for femur.
CONCLUSION
REMS, is a reliable technology for the diagnosis of osteoporosis also in men. This evidence corroborates its high diagnostic performance already observed in previous studies involving female populations.
Topics: Humans; Male; Female; Aged; Aged, 80 and over; Bone Density; Osteoporosis; Osteoporotic Fractures; Femur Neck; Spectrum Analysis
PubMed: 38494464
DOI: 10.1007/s40520-024-02728-4