Theoretical and experimental study of attenuation in cancellous bone.

Significance: Photoacoustic (PA) technology shows great potential for bone assessment. However, the PA signals in cancellous bone are complex due to its complex composition and porous structure, making such signals challenging to apply directly in bone analysis. Aim: We introduce a photoacoustic differential attenuation spectrum (PA-DAS) method to separate the contribution of the acoustic propagation path to the PA signal from that of the source, and theoretically and experimentally investigate the propagation attenuation characteristics of cancellous bone. Approach: We modified Biot's theory by accounting for the high frequency and viscosity. In parallel with the rabbit osteoporosis model, we build an experimental PA-DAS system featuring an eccentric excitation differential detection mechanism. Moreover, we extract a PA-DAS quantization parameter-slope-to quantify the attenuation of high- and low-frequency components. Results: The results show that the porosity of cancellous bone can be evaluated by fast longitude wave attenuation at different frequencies and the PA-DAS slope of the osteoporotic group is significantly lower compared with the normal group (**p<0.01). Conclusions: Findings demonstrate that PA-DAS effectively differentiates osteoporotic bone from healthy bone, facilitating quantitative assessment of bone mineral density, and osteoporosis diagnosis.

Metal-organic frameworks as solid-phase microextraction adsorbents for the determination of triacetone triperoxide by gas chromatography-mass spectrometry.

Triacetone triperoxide (TATP) is a high-power explosive which is often used by criminals. The detection of TATP is of great significance for solving the explosion cases. However, the preconcentration and analysis of trace levels of TATP still pose challenges for analytical researchers. In this study, metal-organic frameworks (MOFs), including IRMOF-8, MOF-5, UIO-66, ZIF-8, and MIL-101(Cr), were immobilized on a stainless steel wire using a physical adhesive method as a solid-phase microextraction (SPME) fiber coating. The prepared fibers with a controllable thickness were used for the extraction of TATP followed by gas chromatography-mass spectrometry (GC-MS) analysis. Under the identical experimental conditions, the IRMOF-8-coated fiber exhibited higher extraction efficiency for TATP than the other fibers. The IRMOF-8-coated fiber was then characterized using scanning electron microscopy and thermogravimetric analysis. The results indicated that the IRMOF-8-coated fiber not only had good thermal and chemical stabilities but also afforded a high TATP extraction efficiency. Under the same extraction conditions, the extraction efficiency of the IRMOF-8-coated fiber was 2-8 times higher than those of commercial fibers. The limit of detection was 13 ng/mL, and linearity was observed in the range of 50-5000 ng/mL with a correlation coefficient greater than 0.998. The intraday repeatability (n = 6), interday repeatability (n = 3), and fiber-to-fiber reproducibility (n = 3), were 4.1 %, 4.8 %, and 8.0 %, respectively. The recoveries of TATP from the simulated tap water and soil samples were 87.32-90.57 % and 88.76-100.93 %, respectively, with relative standard deviations lower than 11.11 % (n = 3). The above method was successfully applied for the detection of TATP transferred from a finger to a paper surface, demonstrating its good application prospects in the analysis of trace TATP.

[Applications of functional materials-based solid phase microextraction technique in forensic science].

Sample extraction is a crucial step in forensic analysis, especially when dealing with trace and ultra-trace levels of target analytes present in various complex matrices (e. g., soil, biological samples, and fire debris). Conventional sample preparation techniques include Soxhlet extraction and liquid-liquid extraction. However, these techniques are tedious, time-consuming, labor-intensive and require large amounts of solvents, which poses a threat to the environment and health of researchers. Moreover, sample loss and secondary pollution can easily occur during the preparation procedure. Conversely, the solid phase microextraction (SPME) technique either requires a small amount of solvent or no solvent at all. Its small and portable size, simple and fast operation, easy-to-realize automation, and other characteristics thus make it a widely used sample pretreatment technique. More attention was given to the preparation of SPME coatings by using various functional materials, as commercialized SPME devices used in early studies were expensive, fragile, and lacked selectivity. Examples of those functional materials include metal-organic frameworks, covalent organic frameworks, carbon-based materials, molecularly imprinted polymers, ionic liquids, and conducting polymers, all widely used in environmental monitoring, food analysis, and drug detection. However, these SPME coating materials have relatively few applications in forensics. Given the high potential of SPME technology for the in situ and efficient extraction of samples from crime scenes, this study briefly introduces functional coating materials and summarizes the applications of SPME coating materials for the analysis of explosives, ignitable liquids, illicit drugs, poisons, paints, and human odors. Compared to commercial coatings, functional material-based SPME coatings exhibit higher selectivity, sensitivity, and stability. These advantages are mainly achieved through the following approaches: First, the selectivity can be improved by increasing the π-π, hydrogen bonds, and hydrophilic/hydrophobic interactions between the materials and analytes. Second, the sensitivity can be improved by using porous materials or by increasing their porosity. Third, thermal, chemical, and mechanical stability can be improved by using robust materials or fixing the chemical bonding between the coating and substrate. In addition, composite materials with multiple advantages are gradually replacing the single materials. In terms of the substrate, the silica support was gradually replaced by the metal support. This study also outlines the existing shortcomings in forensic science analysis of functional material-based SPME techniques. First, the application of functional material-based SPME techniques in forensic science remains limited. On one hand, the analytes are narrow in scope. As far as explosive analysis is concerned, functional material-based SPME coatings are mainly applied to nitrobenzene explosives, while other categories, such as nitroamine and peroxides, are rarely or never involved. Research and development of coatings is insufficient and the application of COFs in forensic science has not yet been reported. Second, functional material-based SPME coatings have not been commercialized as they don't yet have inter-laboratory validation tests or established official standard analytical methods. Therefore, some suggestions are proposed for the future development of forensic science analyses of functional material-based SPME coatings. First, research and development of functional material-based SPME coatings, especially fiber coatings with broad-spectrum applicability and high sensitivity, or outstanding selectivity for some compounds, is still an important direction for SPME future research. Second, a theoretical calculation of the binding energy between the analyte and coating was introduced to guide the design of functional coatings and improve the screening efficiency of new coatings. Third, we expand its application in forensic science by expanding the number of analytes. Fourth, we focused on the promotion of functional material-based SPME coatings in conventional laboratories and established performance evaluation protocols for the commercialization of functional material-based SPME coatings. This study is expected to serve as a reference for peers engaged in related research.

Nakagami statistics-based photoacoustic spectroscopy used for label-free assessment of bone tissue.

Quick identification of abnormal molecular metabolism of bone tissues is challenging. Photoacoustic (PA) spectroscopy techniques have great potential in molecular imaging. However, most of them are amplitude-dependent and easily affected by the light deposition, especially for bone tissues with high optical scattering. In this Letter, we propose a Nakagami statistics-based PA spectroscopy (NSPS) method for characterizing molecules in bone tissues. We indicate that the NSPS curve can intelligently identify changes in the content of molecules in bone tissues, with a high disturbance-resisting ability. The NSPS has remarkable potential for use in the early and rapid detection of bone diseases.

Photoacoustic characterization of bone physico-chemical information.

Osteoporosis usually alters the chemical composition and physical microstructure of bone. Currently, most clinical techniques for bone assessment are focused on the either bone microstructure or bone mineral density (BMD). In this study, a novel multi-wavelength photoacoustic time-frequency spectral analysis (MWPA-TFSA) method was introduced based on the optical absorption spectra and photoacoustic effects of biological macromolecules, which evaluates changes in bone chemical composition and microstructure. The results demonstrated that osteoporotic bones had decreased BMD, more lipids, and wider trabecular separation filled with larger marrow clusters, which were consistent with multiple gold-standard results, suggesting that the MWPA-TFSA method has the potential to provide a thorough bone physico-chemical information evaluation noninvasively and nonradiatively.

Deep Learning-Based Photoacoustic Imaging of Vascular Network Through Thick Porous Media.

Photoacoustic imaging is a promising approach used to realize in vivo transcranial cerebral vascular imaging. However, the strong attenuation and distortion of the photoacoustic wave caused by the thick porous skull greatly affect the imaging quality. In this study, we developed a convolutional neural network based on U-Net to extract the effective photoacoustic information hidden in the speckle patterns obtained from vascular network images datasets under porous media. Our simulation and experimental results show that the proposed neural network can learn the mapping relationship between the speckle pattern and the target, and extract the photoacoustic signals of the vessels submerged in noise to reconstruct high-quality images of the vessels with a sharp outline and a clean background. Compared with the traditional photoacoustic reconstruction methods, the proposed deep learning-based reconstruction algorithm has a better performance with a lower mean absolute error, higher structural similarity, and higher peak signal-to-noise ratio of reconstructed images. In conclusion, the proposed neural network can effectively extract valid information from highly blurred speckle patterns for the rapid reconstruction of target images, which offers promising applications in transcranial photoacoustic imaging.

Myocardial infarct border demarcation by dual-wavelength photoacoustic spectral analysis.

Myocardial infarction (MI) is a major cause of morbidity and mortality worldwide. Modern therapeutic strategies targeting the infarct border area have been shown to benefit overall cardiac function after MI. However, there is no non-invasive diagnostic technique to precisely demarcate the MI boundary till to now. In this study, the feasibility of demarcating the MI border using dual-wavelength photoacoustic spectral analysis (DWPASA) was investigated. To quantify specific molecular characteristics before and after MI, "the ratio of the areas of the power spectral densities (R APSD)" was computed from the DWPASA results. Compared to the normal tissue, MI tissue was shown to contain more collagen, resulting in higher R APSD values (p < 0.001). Cross-sectional MI lengths and the MI area border demarcated in two dimensions by DWPASA were in substantial agreement with Masson staining (ICC = 0.76, p < 0.001, IoU = 0.72). R APSD has been proved that can be used as an indicator of disease evolution to distinguish normal and pathological tissues. These findings indicate that the DWPASA method may offer a new diagnostic solution for determining MI borders.

Characterization of multi-biomarkers for bone health assessment based on photoacoustic physicochemical analysis method.

Photoacoustic (PA) techniques are potential alternatives to histopathology. The physicochemical spectrogram (PCS) generated by the PA measurement at multiple wavelengths can presents the morphology and chemical composition target at multi-biomarkers simultaneously. In this work, via multi-wavelength PA measurements performed on rabbit bone models, we investigated the feasibility of using PCSs for bone health assessment. A comprehensive analysis of the PCSs, termed PA physicochemical analysis (PAPCA), was conducted. The "slope" and "relative content" were used as the PAPCA-quantified parameters to characterize the changes in the physical and chemical properties of bone tissue, respectively. The findings are consistent well with the gold-standard imaging results. It demonstrated that the PAPCA can be used to characterize both the microstructure and content of multi-biomarkers which highly related with bone health. Considering the PA technique is noninvasive and radiation-free, it has great potential in the implementation and monitoring of bone diseases progression.

Detection of collagen by multi-wavelength photoacoustic analysis as a biomarker for bone health assessment.

Collagen is an important biomarker of osteoporosis progression. Noninvasive, multispectral, photoacoustic (PA) techniques use pulsed laser light to induce PA signals to facilitate the visualization of chemical components that are strongly related to tissue health. In this study, the feasibility of multi-wavelength PA (MWPA) measurement of the collagen in bone, using the wavelength range of 1300-1800 nm, was investigated. First, the feasibility of this approach for detecting the collagen content of bone was demonstrated by means of numerical simulation. Then, ex vivo experiments were conducted on both animal and human bone specimens with different bone densities using the MWPA method. The relative collagen content was extracted and compared with the results of micro-computed tomography (micro-CT) and histology. The results showed that the "relative collagen content" parameter obtained using the MWPA approach correlated well with the bone volume ratio obtained from micro-CT images and histological analysis results. This study highlights the potential of the proposed PA technique for determining the collagen content of bones as a biomarker for bone health assessment.

Wavelet transform-based photoacoustic time-frequency spectral analysis for bone assessment.

In this study, we investigated the feasibility of using photoacoustic time-frequency spectral analysis (PA-TFSA) for evaluating the bone mineral density (BMD) and bone structure. Simulations and ex vivo experiments on bone samples with different BMDs and mean trabecular thickness (MTT) were conducted. All photoacoustic signals were processed using the wavelet transform-based PA-TFSA. The power-weighted mean frequency (PWMF) was evaluated to obtain the main frequency component at different times. The y-intercept, midband-fit, and slope of the linearly fitted curve of the PWMF over time were also quantified. The results show that the osteoporotic bone samples with lower BMD and thinner MTT have higher frequency components and lower acoustic frequency attenuation over time, thus higher y-intercept, midband-fit, and slope. The midband-fit and slope were found to be sensitive to the BMD; therefore, both parameters could be used to distinguish between osteoporotic and normal bones (p < 0.05).

Photoacoustic power azimuth spectrum for microvascular evaluation.

The tubular structures and dendritic distributions of blood vessels emit anisotropic photoacoustic (PA) signals with different intensities and frequency components at different angles. Therefore, spectral analysis of PA signals from a single angle cannot accurately determine the physical characteristics of microvessels. This study investigated the feasibility of using the PA power azimuth spectrum (PA-PAS) method to evaluate microvessel structures. We mapped the acoustic power spectrum of the PA signals along the azimuth direction. Based on a frequency-domain analysis of the broadband PA signal, we calculated the spectral parameter power-weighted mean frequency (PWMF). The results demonstrate that the PA signal information of the microvessel is mainly concentrated in the direction of its width. In addition, the PWMF decreases linearly with the microvascular size. The experimental findings exhibit good agreement with the simulation results, thus demonstrating that this approach can effectively differentiate the sizes of microvessels.

Core-Shell Graphitic Carbon Nitride/Zinc Phytate as a Novel Efficient Flame Retardant for Fire Safety and Smoke Suppression in Epoxy Resin.

Novel core-shell graphitic carbon nitride/zinc phytate (g-C3N4/PAZn) flame retardant was simple synthetized using two-dimensional g-C3N4 and bio-based PAZn by self-assembly and incorporated into epoxy resin (EP) for improving the fire safety. The flame retardance and smoke suppression were investigated by cone calorimetry. The results indicated that g-C3N4/PAZn-EP displayed outstanding flame retardancy and smoke suppression, for example, the peak heat release rate and peak smoke production rate decreased by 71.38% and 25%, respectively. Furthermore, the flame retardancy mechanism was further explored by char residue and thermal stability analysis. It can be predicted that g-C3N4/PAZn will provide valuable reference about bio-based flame retardant.