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An innovative amino acid-based metallo-supramolecular nanoassembly with POD- and GSHOx-like activities was designed for tumoricidal chemo-/photo-/catalytic combination therapy. [Display omitted] Nanozymes, as nanomaterials with natural enzyme activities, have been widely applied to deliver various therapeutic agents to synergistically combat the progression of malignant tumors. However, currently common inorganic nanozyme-based drug delivery systems still face challenges such as suboptimal biosafety, inadequate stability, and inferior tumor selectivity. Herein, a super-stable amino acid-based metallo-supramolecular nanoassembly (FPIC NPs) with peroxidase (POD)- and glutathione oxidase (GSHOx)-like activities was fabricated via Pt4+-driven coordination co-assembly of l -cysteine derivatives, the chemotherapeutic drug curcumin (Cur), and the photosensitizer indocyanine green (ICG). The superior POD- and GSHOx-like activities could not only catalyze the decomposition of endogenous hydrogen peroxide into massive hydroxyl radicals, but also deplete the overproduced glutathione (GSH) in cancer cells to weaken intracellular antioxidant defenses. Meanwhile, FPIC NPs would undergo degradation in response to GSH to specifically release Cur, causing efficient mitochondrial damage. In addition, FPIC NPs intrinsically enable fluorescence/photoacoustic imaging to visualize tumor accumulation of encapsulated ICG in real time, thereby determining an appropriate treatment time point for tumoricidal photothermal (PTT)/photodynamic therapy (PDT). In vitro and in vivo findings demonstrated the quadruple orchestration of catalytic therapy, chemotherapeutics, PTT, and PDT offers conspicuous antineoplastic effects with minimal side reactions. This work may provide novel ideas for designing supramolecular nanoassemblies with multiple enzymatic activities and therapeutic functions, allowing for wider applications of nanozymes and nanoassemblies in biomedicine. [ABSTRACT FROM AUTHOR]

Acidity-activated gold nanoparticles (AuNPs) with self-complementary zwitterionic peptide decoration are developed for photothermal eradication of drug-resistant biofilm infections. The self-complementary zwitterionic peptide with longer charge domains and a polyethylene glycol oligomer spacer endow AuNPs with greater photothermal antimicrobial and biofilm eradication. [Display omitted] Drug-resistant biofilm infection is an extremely serious clinical problem, that easily leads to failure of antibiotic treatment. Although gold nanoparticles (AuNPs) as photothermal agents have been widely used in biofilm eradication, there are still challenges to be addressed, such as insignificantly redshifted absorption and slow assembly process of aggregated AuNPs. Herein, we developed an acidity-activated dispersion-to-aggregation transition to enhance the accumulation of self-complementary zwitterionic peptide-decorated AuNPs for photothermal eradication of drug-resistant biofilm infections. AuNPs were decorated with self-complementary zwitterionic peptides (ZP1 and ZP2) coupled with pH-sensitive anhydride (DMA) and pH-insensitive anhydride (SA), respectively. ZP2-decorated AuNPs with DMA modification (AuNP@ZP2(DMA)) exhibited prolonged blood circulation and enhanced accumulation in acidic biofilm microenvironment. Moreover, the electrostatic attraction between self-complementary ligands drove AuNPs to form closely packed aggregates with strong near-infrared absorption, leading to in vivo photoacoustic imaging ability and photothermal effect against drug-resistant bacteria and fungus, as well as microbial biofilms. AuNP@ZP2(DMA) with longer charge domains and a polyethylene glycol oligomer spacer showed greater photothermal antimicrobial and biofilm resistance in vitro and in vivo. This study develops an innovative acidity-activated AuNP photothermal agent, which provides an effective approach for treatment of biofilm infections. [ABSTRACT FROM AUTHOR]

Tumor-associated macrophages (TAMs) are a key component of the immunosuppressive cell and cytokine network. They play a critical role in allowing tumors to evade the immune system. To successfully combat cancer through immunotherapy, it is essential to re-educate TAMs. This study introduces a TAM-targeting nanoreporter that can reshape the tumor immune microenvironment, enhancing cancer immunotherapy. Additionally, the nanoreporter allows for the monitoring of TAM immune activation through protease-responsive photoacoustic/fluorescent imaging. [Display omitted] • This paper described a non-invasive optical imaging technique for tracing the immune activation of tumor-associated macrophages. • This nanoreporter could target TAMs and achieve precise controlled release of TLR agonists. • This "all-in-one" nanoplatform shows promise in cancer diagnosis, treatment and prognosis assessment. Tumor-associated macrophages (TAMs) are vital in the tumor microenvironment, contributing to immunosuppression and therapy tolerance. Despite their importance, the precise re-education of TAMs in vivo continues to present a formidable challenge. Moreover, the lack of real-time and efficient methods to comprehend the spatiotemporal kinetics of TAMs repolarization remains a significant hurdle, severely hampering the accurate assessment of treatment efficacy and prognosis. Herein, we designed a metal–organic frameworks (MOFs) based Caspase-1 nanoreporter (MCNR) that can deliver a TLR7/8 agonist to the TAMs and track time-sensitive Caspase-1 activity as a direct method to monitor the initiation of immune reprogramming. This nanosystem exhibits excellent TAMs targeting ability, enhanced tumor accumulation, and stimuli-responsive behavior. By inducing the reprogramming of TAMs, they were able to enhance T -cell infiltration in tumor tissue, resulting in inhibited tumor growth and improved survival in mice model. Moreover, MCNR also serves as an activatable photoacoustic and fluorescent dual-mode imaging agent through Caspase-1-mediated specific enzyme digestion. This feature enables non-invasive and real-time antitumor immune activation monitoring. Overall, our findings indicate that MCNR has the potential to be a valuable tool for tumor immune microenvironment remodeling and noninvasive quantitative detection and real-time monitoring of TAMs repolarization to immunotherapy in the early stage. [ABSTRACT FROM AUTHOR]

We designed and constructed a nanoparticle LDNP@DMSN-Au@CaCO 3 (LDAC NPs) that integrates lanthanide-doped nanoparticles, Au NPs and CaCO 3 layer to achieve PAI/ NIR-II FI dual-mode imaging under 980 nm radiation. Under the excitation of 980 nm, LDNPs simultaneously implement the up/down-conversion, which not only can realize bright NIR-II FI, but also can provide the energy required for PAI of Au NPs through the fluorescence resonance energy transfer effect. In addition, the CaCO 3 layer can degrade under the tumor microenvironment and produce CO 2 microbubbles, which further enhance the PA signal through the bubble cavitation effect, thus improving the imaging effect. [Display omitted] As an important tumor diagnosis strategy in precision medicine, multimodal imaging has been widely studied. However, the weak imaging signal with low spatial resolution and the constant signal of lack of specific activation severely limit its disease diagnosis. Herein, a bubble-enhanced lanthanide-based up/down-conversion platform with tumor microenvironment response for dual-mode imaging, LDNP@DMSN-Au@CaCO 3 nanoparticles (named as LDAC NPs) were successfully developed. Combining the advantages of photoacoustic imaging (PAI) and the second near-infrared window (NIR-II) fluorescence imaging (FI), significantly improved the accuracy of diseases diagnosis. LDAC NPs with flower-like structure were synthesized through the encapsulation of uniform lanthanide-doped nanoparticles (NaYbF 4 :Ce,Er@NaYF 4 named LDNPs) with dendritic mesoporous silica (DMSN). The gold nanoparticles (Au NPs) were then in situ grown on the surface of DMSN and the surface were finally coated with a layer of calcium carbonate (CaCO 3). Under the excitation of the 980 nm laser, LDNPs showed strong emission of NIR-II at 1550 nm due to the doping of Ce and Er ions, showcasing excellent spatial resolution and deep tissue penetration characteristics, while the resulting visible light emission (540 nm) enables Au NPs to generate PAI signals with the aid of LDNPs via the fluorescence resonance energy transfer effect. In acidic tumoral environment, CaCO 3 layer could produce CO 2 microbubbles, and the PAI signals of LDAC NPs could be further enhanced with the generation of CO 2 bubbles due to the bubble cavitation effect. Simultaneously, the NIR-II FI of LDAC NPs was self-enhanced with the degradation of the CaCO 3. This intelligent nanoparticle with stimulus-activated dual-mode imaging capability holds great promise in future precision diagnostics. [ABSTRACT FROM AUTHOR]

[Display omitted] The development of intelligent nanodrug delivery systems that can visually guide the on-demand quantitative control of drug release has received extensive attention. Herein, two chemotherapeutic drugs, gallic acid and 5-fluorouracil, and Fe(III) were selected to prepare nanomedicine GF-Fe via polyphenol-metal self-assembly and infinite coordination of drug-metal. GF-Fe has good biocompatibility, photothermal properties and photoacoustic (PA) signals. When deferoxamine (DFO) was artificially applied and interacted with GF-Fe, GF-Fe began to disassemble, gallic acid and 5-fluorouracil were gradually released, while the PA signal of the nanomedicine decayed synchronously. Based on this, the relationship between the intensity of the PA signal and the drug release amount was established, so as to realize the precise quantitative control of the drug release in real-time under the guidance of PA imaging. Besides, the combined effect of the two therapeutic drugs in combination with photothermal therapy (PTT) can improve the therapeutic effect, resulting in significant superadditiveness. This nanoplatform constructed by facile synthesis provided good clinical translation potential for the implementation of precise multimodal combination therapy strategies for tumors. [ABSTRACT FROM AUTHOR]

NIR-driven Janus nanomotors for active photoacoustic imaging and synergistic photothermal/chemodynamic therapy. [Display omitted] Synthetic nanomotors have great application potential in deep tissue imaging and tumor treatment due to their active movement ability. Herein, a novel near infrared (NIR) light-driven Janus nanomotor is reported for active photoacoustic (PA) imaging and synergistic photothermal/chemodynamic therapy (PTT/CDT). Au nanoparticles (Au NPs) are sputtered on the half-sphere surface of copper-doped hollow cerium oxide nanoparticles after bovine serum albumin (BSA) modification. Such Janus nanomotors exhibit a rapid autonomous motion with a maximum speed of 110.6 ± 0.2 μm/s under 808 nm laser irradiation with a density of 3.0 W/cm2. With the assistance of light-powered motion, the Au/Cu-CeO 2 @BSA nanomotors (ACCB Janus NMs) can effectively adhere to and mechanically perforate tumor cells, thereby causing the higher cellular uptake and significantly enhancing the tumor tissue permeability in the tumor microenvironment (TME). ACCB Janus NMs also exhibit high nanozyme activity that can catalyze the production of reactive oxygen species (ROS) to reduce the TME oxidative stress response. Meanwhile, the potential PA imaging capability of ACCB Janus NMs offer promise for early diagnosis of tumors due to the photothermal conversion efficiency of Au NPs. Therefore, the nanotherapeutic platform provides a new tool for effectively imaging of deep tumors site in vivo to achieve synergistic PTT/CDT and accurate diagnosis. [ABSTRACT FROM AUTHOR]

The use of artificial intelligence (AI) to assist biomedical imaging have demonstrated its high accuracy and high efficiency in medical decision-making for individualized cancer medicine. In particular, optical imaging methods are able to visualize both the structural and functional information of tumors tissues with high contrast, low cost, and noninvasive property. However, no systematic work has been performed to inspect the recent advances on AI-aided optical imaging for cancer theranostics. In this review, we demonstrated how AI can guide optical imaging methods to improve the accuracy on tumor detection, automated analysis and prediction of its histopathological section, its monitoring during treatment, and its prognosis by using computer vision, deep learning and natural language processing. By contrast, the optical imaging techniques involved mainly consisted of various tomography and microscopy imaging methods such as optical endoscopy imaging, optical coherence tomography, photoacoustic imaging, diffuse optical tomography, optical microscopy imaging, Raman imaging, and fluorescent imaging. Meanwhile, existing problems, possible challenges and future prospects for AI-aided optical imaging protocol for cancer theranostics were also discussed. It is expected that the present work can open a new avenue for precision oncology by using AI and optical imaging tools. [ABSTRACT FROM AUTHOR]

A diagnosis of pancreatic cancer carries a 5-y survival rate of less than 10%. Furthermore, the detection of pancreatic cancer occurs most often in later stages of the disease due to its location in the retroperitoneum and lack of symptoms (in most cases) until tumors become more advanced. Once diagnosed, cross-sectional imaging techniques are heavily utilized to determine the tumor stage and the potential for surgical resection. However, a major determinant of resectability is the extent of local vascular involvement of the mesenteric vessels and critical tributaries; current imaging techniques have limited capacity to accurately determine vascular involvement. Surrounding inflammation and fibrosis can be difficult to discriminate from viable tumor, making determination of the degree of vascular involvement unreliable. New innovations in fluorescence and optoacoustic imaging techniques may overcome these limitations and make determination of resectability more accurate. These imaging modalities are able to more clearly discern between viable tumor tissue and non-neoplastic inflammation or desmoplasia, allowing clinicians to more reliably characterize vascular involvement and develop individualized treatment plans for patients. This review will discuss the current imaging techniques used to diagnose pancreatic cancer, the barriers that current techniques raise to accurate staging, and novel fluorescence and optoacoustic imaging techniques that may provide more accurate clinical staging of pancreatic cancer. [ABSTRACT FROM AUTHOR]

[Display omitted] In recent years, branched or star-shaped Au nanostructures composed of core and protruding arms have attracted much attention due to their unique optical properties and morphology. As the clinically adapted nanoagent, prussian blue (PB) has recently gained widespread attention in cancer theranostics with potential applications in magnetic resonance (MR) imaging. In this article, we propose a hybrid star gold nanostructure（Au-star@PB）as a novel theranostic agent for T1-weighted magnetic resonance imaging (MRI)/ photoacoustic imaging（PAI） and photothermal therapy (PTT) of tumors. Importantly, the Au-star@PB nanoparticles function as effective MRI/PA contrast agents in vivo by increasing T1-weighted MR/PAI signal intensity and as effective PTT agents in vivo by decreasing the tumor volume in MCF-7 tumor bearing BALB / c mouse model as well as in vitro by lessening tumor cells growth rate. Interestingly, we found the main photothermal effect of Au-star@PB is derived from Au-star, but not PB. In summary, the hybrid structure of Au-star@PB NPs with good biological safety, significant photostability, dual imaging capability, and high therapeutic efficiency, might offer a novel avenue for the future diagnosis and treatment of cancer. [ABSTRACT FROM AUTHOR]

In the past, attempts were made to determine the knives sharpness in agricultural harvesting processes online using various methods. One promising method is the recording and analysis of the structure-borne sound at the counter-blade of the chopper (Siebald, 2017; Siebald et al., 2017). First investigations show, further reference systems for monitoring the knife sharpness are needed to enable a calibration of the planned system. One such reference measurement that is readily available in practical operation is the assessment of the cut material, which has been used to date in the form of a qualitative visual inspection by the operator. In the present work, in addition to an analysis of acoustic data, the determination of the particles of the crop taken in parallel is carried out. This is done using computer image analysis, which is capable of reproducing the shape parameters of the chaff particles with high accuracy and complexity (Guth et al., 1995 ; Savoie et al., 2014). Computation of a predictive model for the cumulative throughput by means of projection of the manifest variables onto a subset of "latent factors" was performed with the software JMP using the NIPALS method. By projecting the mean values and standard deviations of the acoustic analysis parameters onto six latent variables, it was possible to generate predicted values for the cumulative chaff throughput whose correlation with the "actual" throughput values could be described by a regression fit with R 2 = 0.813. In the image analysis of the chaff data, even with only 2 variables, a R 2 = 0.912 was given. • Acoustic measurements, and taking chaff samples for image analysis. • Determination of chaff quality using computer image analysis of the harvested crop. • Investigation of the correlation of the chaff quality with the throughput. • Investigation of correlation between structure-borne sound and the total throughput. • Prediction of the throughput values based on acoustic and image analysis data. [ABSTRACT FROM AUTHOR]

We analyze the inversion of the photo-acoustic imaging modality using electromagnetic plasmonic nano-particles as contrast agents. We prove that the generated pressure, before and after injecting the plasmonic nano-particles, measured at a single point, located away from the targeted inhomogeneity to image, and at a given band of incident frequencies is enough to reconstruct the (eventually complex valued) permittivity. Indeed, from these measurements, we define an indicator function which depends on the used incident frequency and the time of measurement. This indicator function has differentiating behaviors in terms of both time and frequency. First, from the behavior in terms of time, we can estimate the arrival time of the pressure from which we can localize the injected nano-particle. Second, we show that this indicator function has maximum picks at incident frequencies close to the plasmonic resonances. This allows us to estimate these resonances from which we construct the permittivity. To justify these properties, we derive the dominant electric field created by the injected nano-particle when the incident frequency is close to plasmonic resonances. This is done for the full Maxwell system. To this end, we use a natural spectral decomposition of the vector space (L 2 (D)) 3 based on the spectra of the Newtonian and the Magnetization operators. As another key argument, we provide the singularity analysis of the Green's tensor of the Maxwell problem with varying permittivity. Such singularity is unusual if compared to the ones of the elliptic case (as the acoustic or elastic models). In addition, we show how the derived approximation of the electric fields propagates, as a source, in the induced pressure with the time. [ABSTRACT FROM AUTHOR]

[Display omitted] • A tumor-targeting dual-modal fluorescent probe (Cy-Bio-NO 2) is synthesized. • Cy-Bio-NO 2 exhibits remarkable sensitivity and selectivity to NTR. • The visualization of NTR activity in tumor cells has been achieved using Cy-Bio-NO 2. • Cy-Bio-NO 2 is applied for dual-modal imaging of NTR activity in tumor-bearing mice. • The incorporation of biotin enhances the tumor targeting ability of Cy-Bio-NO 2. Nitroreductase (NTR) overexpression often occurs in tumors, highlighting the significance of effective NTR detection. Despite the utilization of various optical methods for this purpose, the absence of an efficient tumor-targeting optical probe for NTR detection remains a challenge. In this research, a novel tumor-targeting probe (Cy-Bio-NO 2) is developed to perform dual-modal NTR detection using near-infrared fluorescence and photoacoustic techniques. This probe exhibits exceptional sensitivity and selectivity to NTR. Upon the reaction with NTR, Cy-Bio-NO 2 demonstrates a distinct fluorescence "off–on" response at 800 nm, with an impressive detection limit of 12 ng/mL. Furthermore, the probe shows on–off photoacoustic signal with NTR. Cy-Bio-NO 2 has been successfully employed for dual-modal NTR detection in living cells, specifically targeting biotin receptor-positive cancer cells for imaging purposes. Notably, this probe effectively detects tumor hypoxia through dual-modal imaging in tumor-bearing mice. The strategy of biotin incorporation markedly enhances the probe's tumor-targeting capability, facilitating its engagement in dual-modal imaging at tumor sites. This imaging capacity holds substantial promise as an accurate tool for cancer diagnosis. [ABSTRACT FROM AUTHOR]

Granulation is a common internal disease in citrus fruits, and it is difficult to distinguish fruits with granulation disease from their appearance. In this study, a novel acoustic vibration device based on a micro-LDV, a microphone and a resonance speaker was employed to collect acoustic vibration response signals of "Aiyuan 38" jelly orange. The one-dimensional acoustic vibration response signal was converted into acoustic vibration images, and a double-input Resnet-Transformer network (DresT) was constructed for extracting deep features in acoustic vibration images for identifying jelly-orange granulation disease. Firstly, train Drest and Resnet50 models using acoustic vibration images and compare the performance of Drest with that of Resnet50 (based on CNN). Then PLS-DA and SVM models are trained using acoustic vibration image texture features or acoustic vibration spectral features, and the performance is compared with the DresT model. The results showed that the DresT model trained using acoustic vibration images can accurately identify jelly orange granulation disease with a detection accuracy of 99.31 %. The F 1 of the model is 99.5 %, the accuracy is 99.01 %, and the recall is 100 %. • Construct a dual-input Resnet-Transformer network (DresT). • Detection of jelly orange granulation disease using a novel acoustic vibration device. • Converted acoustic vibration response signals to acoustic vibration images. • Compared performance of models based on different types of data. • Achieved precise identification of Jelly Orange granulation disease. [ABSTRACT FROM AUTHOR]

Deep Neural Network (DNN) models offer an attractive alternative to existing acoustic source imaging techniques, such as acoustic beamforming, due to their ever-growing potential with increasing computational power. Source resolution of acoustic beamforming methods is limited at lower frequencies and their source maps may possess sidelobes at higher frequencies. However, acoustic beamforming methods are typically robust over a wide range of simulation and experimental conditions, such as (i) the number of sources present, (ii) source frequency and (ii) extraneous noise sources. The performance of DNN models, when these conditions are varied from their specific design criteria, is yet to be investigated and much work is needed in this area before DNN models can be utilized in experiments, such as wind tunnel tests. Furthermore, few studies have been conducted on experimental validation of DNN models, predominately due to the difficulty of large sets of experimentally obtained data needed for DNN model training and the sensitivity of DNN model performance when any of the aforementioned experimental conditions are varied. In this paper, a series of studies on the robustness of DNN models based on numerical data and experimental data are presented. Numerical DNN (NDNN) models are trained using in-phase and random-phase pressure data generated from six sources over design frequencies from 500 Hz to 20,000 Hz. The robustness of the NDNN models is tested via (1) inclusion of extraneous Gaussian white noise, (2) inclusion of extraneous tonal noise near the design frequency, (3) using source frequencies that slightly differ from the design frequencies and (4) using a number of sources that differs from the design source number. DNN model performance metrics are introduced that present a promising framework for future DNN model studies and bridging the gap between NDNN and experimentally trained DNN models. A preliminary experimental validation was conducted using a single speaker that was systematically placed over a speaker grid to generate training data via acoustic superposition, from which an experimentally trained DNN (EDNN) model was produced. The EDNN model yields exceptional noise source localization capability of the DNN model, revealing a promising start for a more sophisticated EDNN model. • Robustness of a numerical DNN model is analyzed for conditions away from its design criteria. • Various conditions are tested, e.g., source number, source frequency, extraneous noise sources. • The numerical DNN model is trained using both in-phase and random phase sources. • Experimental validation is conducted through an experimentally trained DNN model. • The experimental DNN model yields exceptional noise source localization capability. [ABSTRACT FROM AUTHOR]

[Display omitted] The sythesis of composite nanosheets with multiple functions remains signifcantly challenging. In this study, we developed multifunctional H-TiO 2 /C-PEG nanosheets as theranostic agents combining sonodynamic therapy and a low-power-mild-photothermal-enhanced Fenton effect. The two-dimensional H-TiO 2 /C composite nanosheets were synthesized by reducing metal–organic frameworks (MOF)-derived from H-TiO 2 /C composite nanoparticles (NPs) by hydrogen. The resulting H-TiO 2 /C was introduced into polyethylene (PEG) to improve water solubility and increase the size of the particles to allow a higher level of H-TiO 2 /C accumulation at the tumor site through the enhanced permeability and retention effect. The H-TiO 2 /C nanosheets had excellent sonodynamic therapy (SDT) effects and could also achieve low-power mild photothermal therapy guided by photoacoustic imaging with high photothermal conversion efficiency (η = 56.2 %). Also, a strong photothermal effect accelerated the rate of the Fenton reaction to enhance the efficacy of chemodynamic therapy (CDT). Importantly, combination therapy can achieve signifcant antitumour efficacy whilst the strong biocompatibility of the particles minimising adverse effects in normal cells. This study provides a promising strategy for the development of novel two-dimensional composite materials that are safe and have multifunctional diagnostic and therapeutic properties. [ABSTRACT FROM AUTHOR]

Ultra-small carbon dots can promote anticancer efficiency by enhancing tumor penetration in breast cancer under near-infrared-II irradiation. [Display omitted] Because of the particular environment of the tumor microenvironment, improving the deep penetration of drugs in tumor sites is a critical problem to improve the therapeutic effect of the tumor. The ultra-small nanoparticles can achieve deep tumor tissue penetration without modification, which shows tremendous significance in tumor therapy. In this work, the ultra-small permeable carbon dots (PCD) have been developed with near-infrared-II (NIR-II) window photothermal irradiation and good biocompatibility. These PCD showed multi-color fluorescence under visible light and photoacoustic signals under an excitation of 808 nm, guiding fluorescence and photoacoustic imaging for location and distribution in vitro and vivo. The PCD could penetrate the deep tissue in tumor spheroids and tissues. Meanwhile, the irradiated depth of the NIR-II window can provide sufficient photothermal energy with the deep penetration of PCD in tumor tissue to cause tumor ablation. Therefore, this PCD can be used as a safe, fluorescent, and photoacoustic imaging agent for guided NIR-II photothermal tumor therapy, which provides a new direction for the use of ultra-small carbon dots in anticancer therapy in the future. [ABSTRACT FROM AUTHOR]

Nanoparticles have been widely used in biological imaging and treatments of various diseases, especially for studies of tumors, due to their high efficiency in drug delivery and many other functions. Metal-organic frameworks have been an important research area in recent years because of advantages such as large apertures, adjustable structural compositions, adjustable sizes, multifunctionality, high drug loading, good biocompatibility and so on, and they show promise as multifunctional drug carriers. In this study, a carbonized MOF with photothermal therapeutic potential and dual-mode imaging capability was prepared. The biophysical properties of MIL-100 and C-MIL nanoparticles were determined, such as particle size, zeta potential and saturation magnetization strength. CCK-8 cell assays and mouse HE sections confirmed that C-MIL nanoparticles have good in vitro and in vivo biocompatibility. The solution temperature of C-MIL nanoparticles reached 58.1 °C during sustained laser irradiation at 808 nm, which confirmed the photothermal potential of the nanoparticles. Moreover, in biological imaging, C-MIL nanoparticles showed the ability to support in vitro nuclear magnetic and photoacoustic dual-mode imaging. C-MIL nanoparticles provide new options for tumor therapy, drug delivery and biological imaging. • New biophysical characterization of Carbonized MOFs NPs is obtained after carbonization treatment. • The biocompatibility of Carbonized MOFs NPs in vitro and in vivo is evaluated. • Explore the possibility of carbonized MOFs in tumor therapy and dignosis from the aspects of therapy and bioimaging. • Carbonized MOFs NPs have good photothermal conversion, photoacoustic imaging and nuclear magnetic imaging capabilities. • Carbonized MOFs have been more comprehensively tested for biomedical applications. [ABSTRACT FROM AUTHOR]

[Display omitted] Photoacoustic imaging (PAI) has shown great clinical potential in diagnosing various diseases due to its noninvasive, cost-effective, and real-time imaging properties but is limited by the lack of contrast agents with high sensitivity for deep tissue imaging. Here, DNA-templated ultrasmall bismuth sulfide (Bi 2 S 3) nanoparticles (NPs) were reported as a photoacoustic (PA) probe for imaging myocardial infarction. We present a simple synthesis strategy of ultrasmall NPs via self-assembly of single-stranded DNA (ssDNA)/metal ion complexes. The in vivo imaging results showed a dramatically enhanced PA signal in the region of myocardial infarction after intravenous injection of DNA-Bi 2 S 3 NPs in the myocardial ischaemia/reperfusion (I/R) mouse model. Further near infrared fluorescence imaging indicated that Bi 2 S 3 NPs mainly accumulated in the infarcted area, leading to enhancement of PA signals. Moreover, such hybrid NPs possess a well-defined nanostructure, superior photobleaching resistance, excellent water dispersibility and negligible acute toxicity. These results not only demonstrate that ultrasmall DNA-Bi 2 S 3 NPs are a potent PA probe for imaging the infarcted region but also provide a new avenue for preparing ultrasmall-sized PA probes by using ssDNA as a template. [ABSTRACT FROM AUTHOR]

The presence of sound sources that rotate can cause interference with stationary acoustic imaging, especially if the intensity of the rotating sound source is strong. Vice versa, stationary sound sources can also interfere with rotational acoustic imaging. Current algorithms for separating and locating rotating and stationary sound sources have problems such as weak separation capabilities, complex calculations, and limited array layouts. To address these challenges more effectively, a frequency-domain hybrid deconvolution method based on modal composition beamforming is proposed to separate and localize rotating and stationary sound sources. This algorithm operates within the frequency domain and is not restricted by array layout or the tonal single-frequency nature of sound sources. First, the point spread function and cross-point spread function matrices of the array are derived based on the modal transfer function. Then, a system of linear equations is constructed to separate rotating and stationary sound sources. Finally, the sound source separation and localization problems are solved through Gaussian Seidel and sparse-constrained deconvolution, respectively. Compared with the virtual rotating array method combined with matrix completion, simulation and experimental results demonstrate that this method can accurately locate and separate rotating and stationary sound sources, even when there is a substantial difference in intensity between rotating and stationary sound sources. • Hybrid deconvolution way is proposed to separate rotating and stationary sources. • Gaussian-Seidel and sparsity constraints are used to solve deconvolution problem. • The method circumvents the limitations imposed by the array layout. • The cross-point spread function is solved based on the modal transfer function. [ABSTRACT FROM AUTHOR]

Recently, many forms of audio industrial applications, such as sound monitoring and source localization, have begun exploiting smart multi-modal devices equipped with a microphone array. Regrettably, model-based methods are often difficult to employ for such devices due to their high computational complexity, as well as the difficulty of appropriately selecting the user-determined parameters. As an alternative, one may use deep network-based methods, but these are often difficult to generalize, nor can they generate the desired beamforming map directly. In this paper, a computationally efficient acoustic beamforming algorithm is proposed, which may be unrolled to form a model-based deep learning network for real-time imaging, here termed the DAMAS-FISTA-Net. By exploiting the natural structure of an acoustic beamformer, the proposed network inherits the physical knowledge of the acoustic system, and thus learns the underlying physical properties of the propagation. As a result, all the network parameters may be learned end-to-end, guided by a model-based prior using back-propagation. Notably, the proposed network enables an excellent interpretability and the ability of being able to process the raw data directly. Extensive numerical experiments using both simulated and real-world data illustrate the preferable performance of the DAMAS-FISTA-Net as compared to alternative approaches. • We unroll an efficient algorithm to form a model-based network for real-time imaging. • This network exhibits an excellent interpretability and ability to be generalized. • This network can learn the physical knowledge and the underlying physical properties. • This network can process the raw data directly. • Extensive experiments illustrate that the proposed network's practical potential. [ABSTRACT FROM AUTHOR]

Plastic products' widespread applications and their non-biodegradable nature have resulted in the continuous accumulation of microplastic waste, emerging as a significant component of ecological environmental issues. In the field of microplastic detection, the intricate morphology poses challenges in achieving rapid visual characterization of microplastics. In this study, photoacoustic imaging technology is initially employed to capture high-resolution images of diverse microplastic samples. To address the limited dataset issue, an automated data processing pipeline is designed to obtain sample masks while effectively expanding the dataset size. Additionally, we propose Vqdp2, a generative deep learning model with multiple proxy tasks, for predicting six forms of microplastics data. By simultaneously constraining model parameters through two training modes, outstanding morphological category representations are achieved. The results demonstrate Vqdp2's excellent performance in classification accuracy and feature extraction by leveraging the advantages of multi-task training. This research is expected to be attractive for the detection classification and visual characterization of microplastics. [Display omitted] • Innovative microplastics detection using high resolution photoacoustic imaging method. • Automated SAM enhances detection efficiency and morphology characterization analysis. • Vqdp2 via multi-task parameter constraints to improve shape classification accuracy. [ABSTRACT FROM AUTHOR]

Three-dimensional acoustic imaging with microphone arrays is a challenging task due to the numerous degrees of freedom of the physical processes at stake. Instead of meshing a region of space to identify acoustic source distributions, the aim of this work is to propose a novel gridless method to reconstruct the sound field by an equivalent set of point sources with unrestricted coordinates, named "acoustic sonons". Their radiation is expected to reproduce the same acoustic properties as the measured acoustic field, such as its pressure level, directivity and spatial coherence by recovering phase information. It is found that the proposed concept of sonons, while being very flexible, effectively provides equivalent representations for a variety of source distributions. The simulation results show that the method can be adapted to diverse acoustic field situations, whether they are composed of elementary sources or intricate volumetric source densities. The problem is formulated within a probabilistic framework, through a hierarchical Bayesian model inferred by a dedicated Markov chain Monte Carlo algorithm. The performance of the method is evaluated on analytical radiation problems and its ability to reconstruct the directivity is tested for two far-field radiation cases. • Achieving gridless 3D imaging with unbounded acoustic particles. • Using Bayesian hierarchical model to achieve gridless via position posterior analysis. • Considering the source correlation prior to improved reconstruction results. • Employing the Hamiltonian Monte Carlo for high-dimensional posterior sampling. • Reconstructing original directivity by capturing phase and correlation information. [ABSTRACT FROM AUTHOR]

[Display omitted] • Co 2.19 S 4 nanodots were designed to efficiently catalyze H 2 O 2 in tumor to realize CDT. • The degraded S2− can capture the Cu2+ of tumor cells to achieve starvation therapy. • Enhanced PTT and CDT was achieved by starvation therapy. • Co 2.19 S 4 nanodots displayed excellent photothermal and photoacoustic imaging. Photodynamic therapy (PDT) mainly relies on reactive oxygen species generated by light- activated photosensitizers and oxygen to kill tumor cells. However, a critical limitation of the current PDT is that it is less effective in solid tumors where the microenvironment is hypoxic, and, therefore, repeated treatment is required. Here, non-stoichiometric Co 2.19 S 4 nanodots (NDs), which can be rapidly degraded to cobalt (Co2+) and sulfur (S2-) ions, were developed to enhance tumor photothermal therapy (PTT) and chemodynamic therapy (CDT) via the capture of copper (Cu2+) ions (starvation therapy) in the hypoxic tumor microenvironment under near-infrared irradiation. Co 2.19 S 4 NDs with excellent photothermal conversion efficiency (ɳ = 52%) can be used for PTT, and the Co2+ ions produced by their degradation can catalyze the endogenous hydrogen peroxide of tumor cells to produce highly toxic hydroxyl radicals to achieve tumor CDT. The mechanism of starvation therapy was explored using western blotting, and the results indicated that blocking the uptake of Cu2+ ions could restrain the growth and proliferation of tumors by inhibiting the BRAF/mitogen-activated extracellular signal regulated kinase (MEK)/extracellular regulated protein kinases (ERK) signaling pathway. Our work highlights the great potential of Co 2.19 S 4 NDs as a theranostic agent for implementing photoacoustic/photothermal imaging and starvation therapy-enhanced PTT/CDT. [ABSTRACT FROM AUTHOR]

Due to the non-conductive and non-magnetic properties, nonmetallic pipelines are difficult to be detected by traditional pipe location technologies. This paper presents a superimposed imaging method of acoustic wave reflections for pipe location, which operates on the propagation of elastic waves. The propagation and attenuation model of elastic waves in soil are constructed according to the geometric relationship between the acoustic source, geophone array and pipelines. The two-dimensional and three-dimensional acoustic field diagrams of underground pipeline are generated by superimposed imaging of the cross-correlation coefficients between the signals from the sound source and geophone array, with the attenuation caused by hysteretic damping and geometric dissipation considered in the imaging process. In order to suppress clutter interference on the imaging results, the strategy of 'multi-point transmit, multi-point receive and cross-correlation coefficient superposition' is adopted. In the simulation, comparison is made to demonstrate the influences of different excitation sources on the detection imaging results, including the single frequency signal, multi-frequency signal, Gaussian pulse signal and sweep signal. It is found that the excitation signals with rich frequency components are more conducive to improving the resolution of detection images. The effectiveness of the proposed imaging method is further verified in the experimental work, which may be beneficial for the visualization and determination of the location, depth and orientation of underground non-metallic pipelines. [ABSTRACT FROM AUTHOR]

• Graded nerve injury model influences the development of graded allodynia. • Graded nerve injury determines the extent of microglial density extent of microglial. • Graded nerve injury drives the microglial morphology. • Graded nerve injury influences the velocity of microglial process. The reactivity of microglia within the spinal cord in response to nerve injury, has been associated with the development and maintenance of neuropathic pain. However, the temporal changes in microglial reactivity following nerve injury remains to be defined. Importantly, the magnitude of behavioural allodynia displayed and the relationship to the phenotypic microglial changes is also unexplored. Using a heterozygous CX 3 CR 1 gfp+ transgenic mouse strain, we monitored microglial activity as measured by cell density, morphology, process movement and process length over 14 days following chronic constriction of the sciatic nerve via in vivo confocal microscopy. Uniquely this relationship was explored in groups of male mice which had graded nerve injury and associated graded behavioural mechanical nociceptive sensitivity. Significant mechanical allodynia was quantified from the ipsilateral hind paw and this interacted with the extent of nerve injury from day 5 to day 14 (p < 0.009). The extent of this ipsilateral allodynia was proportional to the nerve injury from day 5 to 14 (Spearman rho = −0.58 to −0.77; p < 0.002). This approach allowed for the assessment of the association of spinal microglial changes with the magnitude of the mechanical sensitivity quantified behaviourally. Additionally, the haemodynamic response in the somatosensory cortex was quantified as a surrogate measure of neuronal activity. We found that spinal dorsal horn microglia underwent changes unilateral to the injury in density (Spearman rho = 0.47; p = 0.01), velocity (Spearman rho = −0.68; p = 0.00009), and circularity (Spearman rho = 0.55; p = 0.01) proportional to the degree of the neuronal injury. Importantly, these data demonstrate for the first time that the mechanical allodynia behaviour is not a binary all or nothing state, and that microglial reactivity change proportional to this behavioural measurement. Increased total haemoglobin levels in the somatosensory cortex of higher-grade injured animals was observed when compared to sham controls suggesting increased neuronal activity in this brain region. The degree of phenotypic microglial changes quantified here, may explain how microglia can induce both rapid onset and sustained functional changes in the spinal cord dorsal horn, following peripheral injury. [ABSTRACT FROM AUTHOR]

Plasmonic particles have been proposed for a broad variety of optical and hybrid applications, including the photothermal ablation and photoacoustic imaging of cancer, or their integration in photonic sensors. Here, we address the effect of thermal resistance at the gold-water interface, or Kapitza resistance, on the performance of photoacoustic conversion of gold nanorods. Our findings point to possible strategies for the optimization of plasmonic particles as contrast agents for imaging, or even as transducers for biosensing. We perform numerical simulations that project a simultaneous increase of efficiency and stability of photoacoustic conversion with a decrease of Kapitza resistance. We suggest an effective approach to modulate Kapitza resistance by including underresolved features as roughness or the presence of adsorbates. Inspired by this idea, we synthesize a rough variant of gold nanorods by the deposition and galvanic replacement of a silver shell, where roughness provides higher photoacoustic signals by about 70% and damage thresholds by 120%. In addition, we coat our particles with a protein corona and find a decrease of photoacoustic signals with shell thickness, which may inspire new solutions for biosensors based on a mechanism of photoacoustic transduction. Both our findings are consistent with an effective modulation of Kapitza resistance, which decreases upon roughening, due to an underlying increase of specific surface area, and increases upon coating with a protein shell that may act as a thermal insulation. We discuss possible directions to gain more advantage of our concept for topical applications at the crossroads of plasmonics, biomedical optics and biosensing. [ABSTRACT FROM AUTHOR]

In this article, a general method is proposed to model layered acoustical systems with two-by-two transfer matrices, and further, to solve for their acoustic absorption, reflection, and transmission coefficients. Since the proposed method uses the matrix representation of various layers and interfaces, as in the Transfer Matrix Method (TMM), the equation system can be established efficiently. However, the traditional TMM can become unstable when there is a large disparity between the magnitudes of the waves traveling in opposite directions within the layers (i.e., at higher frequencies, for a thick layer, or for extreme parameter values). In such cases, the contribution of the most attenuated wave can be masked by numerical errors and can induce instability when solving the system. Therefore, in the proposed method, the accuracy of the wave attenuation terms is ensured by decomposing each layer's transfer matrix and reformulating the equation system. This method can be used to couple different layer types in a general way and is easy to assemble and implement with numerical code. The predicted acoustic properties of layered systems calculated using the proposed method have been validated by comparison with those predicted by previously-existing methods. • General transfer matrix technique for constructing acoustic model of layered systems. • System elements can be poro-elastic, elastic solid, fluid and thin panels. • Procedure can be used to calculate sound absorption coefficients and sound transmission loss. • Resulting system is stable for large layer depths and extreme parameter values. [ABSTRACT FROM AUTHOR]

A beamforming technique based on the genetic algorithm is proposed in this paper. This method reconstructs acoustic sources by exploiting the sparsity. To reduce the computational cost and speed up the implementation, a highly efficient algorithm is further developed by narrowing down the search domain for the genetic algorithm. The performance is numerically investigated through a quantitative analysis of the position and amplitude error of the recovered source, and experimentally demonstrated in acoustic imaging. For this newly established approach, the results indicate a higher resolution capability than the conventional beamforming, and better accuracy and robustness than the compressive sensing beamforming. Overall, the present work can enrich existing high-resolution beamforming methods and benefit relevant acoustic testing applications. [ABSTRACT FROM AUTHOR]

We introduce a direct, linear sampling approach to imaging in an acoustic waveguide with sound hard walls. The waveguide terminates at one end and has unknown geometry due to compactly supported wall deformations. The goal of imaging is to determine these deformations and to identify localized scatterers in the waveguide, using a remote array of sensors that emits time harmonic probing waves and records the echoes. We present a theoretical analysis of the imaging approach and illustrate its performance with numerical simulations. [ABSTRACT FROM AUTHOR]

Highlights • Synthetic Aperture Imaging of Acoustic Nonlinearity (SAIAN) is proposed. • Contact acoustic nonlinearity is visualized by synthetic aperture focusing technique. • A tone-burst wave is converted to a pulse-like contact acoustic nonlinearity signal. • The SAIAN visualizes closing cracks, which is difficult by linear ultrasonic imaging. • Probability of detection of a closing crack and accuracy in its sizing are increased. Abstract Contact acoustic nonlinearity (CAN) effect was visualized by synthetic aperture focusing technique (SAFT) via a signal-processing method for acoustic nonlinearity imaging. The proposed signal-processing technique, named Synthetic Aperture Imaging of Acoustic Nonlinearity (SAIAN), allows the SAFT to visualize CAN that is difficult to be visualized by linear ultrasonic imaging. Using the SAIAN algorithm, the fundamental and second-order harmonic frequency components are extracted from the tone-burst wave signal and then these component signals are transformed into pulse-like signals. From the pulse-like signals, the CAN parameter signals can be obtained in the form of pulses, which allows CAN to be visualized by SAFT. In order to verify the effectiveness of the SAIAN, the nonlinear ultrasonic measurements using tone-burst waves were conducted to visualize closing interfaces. As a result, CAN effect appeared at partially closed part of a contacting interface in the images of the CAN signals converted by the SAIAN; on the contrary, the CAN feature was not shown in linear ultrasonic images based on the fundamental frequency component. These results support that the SAIAN is a useful signal processing for acoustic nonlinearity visualization that improves the probability of detection of closing interfaces and the accuracy in crack sizing. [ABSTRACT FROM AUTHOR]

Abstract The issue of acoustic source identification has been widely explored in static or quasi-static source contexts, more recently for moving sources, in a wide range of applications. In the case of a passing-by vehicle, the beamforming method is a reference having well-known limitations that deconvolution methods try to overcome. Mostly developed in static source situations at the beginning, some recent deconvolution extensions to moving sources have been proposed in the transportation field, mainly in air transportation and underwater acoustics. In the present investigation, a new approach – called CLEANT for CLEAN-Time domain – is proposed and numerically tested with parameters fitted to the road vehicle context. Inspired by the CLEAN algorithm used to solve deconvolution problems, it is performed exclusively in the time domain and takes advantage of the source signal reconstruction available from the beamforming procedure. Its performance is assessed at several different speeds, source-to-array distances and with various additional noise levels, as well as its robustness regarding an uncertainty on some input parameters. The proposed approach is compared to a reference method using performance indicators. The simulations show better localization and quantification with CLEANT as compared to the other method tested in this road transportation context. Laboratory measurements in scaled pass-by conditions have been conducted and the results are presented and confirm the improvement brought by CLEANT. Highlights • CLEANT is a new time domain method adapted to short duration pass-by situations. • Simulations showed improvement in acoustic source localization and quantification. • Experimental results confirmed the improvement with two acoustic sources. • CLEANT performs well either for tone or white noise sources. [ABSTRACT FROM AUTHOR]

Graphical abstract Abstract Theranostics, integrating tumor treatment and diagnosis concurrently, has become an emerging and meaningful strategy in cancer therapy. In this work, an amphiphilic redox-sensitive near-infrared (NIR) BODIPY dye, which could be formed into nanoparticles (PEG-SS-BDP NPs) by self-assembly, was synthesized and possessed good capability of photothermal therapy (PTT), near-infrared fluorescence (NIRF) imaging, photoacoustic (PA) imaging and drug loading. The stable nanoparticles could be dissociated to turn on NIRF due to the rift of embedded disulfide bonds by glutathione (GSH). The enhanced fluorescence in vitro could be observed via confocal laser scanning microscopy (CLSM) after adding GSH, confirming the redox-sensitivity of disulfide bonds. NIRF and PA imaging demonstrated active accumulation in tumor and good imaging effect. At last, PEG-SS-BDP NPs could significantly suppress tumor growth in vivo upon irradiation. The amphiphilic redox-sensitive BODIPY nanoparticles provide a promising design strategy to formulate multifunctional stimuli-responsive theranostic nanoplatforms. [ABSTRACT FROM AUTHOR]

Abstract This study describes non-invasive photoacoustic imaging to detect and monitor the growth of conjunctival melanomas in vivo. Conjunctival melanomas were induced by injection of melanotic B16F10 cells into the subconjunctival space in syngeneic albino C57BL/6 mice. Non-invasive in vivo photoacoustic tomography was performed before, and after tumor induction up to 2 weeks. Spectral unmixing was performed to determine the location and to assess the distribution of melanin. The melanin photoacoustic signal intensity was quantified from the tumor-bearing and control eyes at all timepoints. For postmortem validation, total tumor and melanotic tumor volumes were measured using H&E stained tumor sections and were compared to in vivo photoacoustic imaging measurements. Photoacoustic imaging non-invasively detected eyes bearing conjunctival tumors of varying sizes. The melanin signal was detected as early as immediately following injection of melanotic tumor cells. Changes in tumor size over time were assessed with changes in the volume and intensity of the melanin signal. Four growing tumors and one regressing tumor were observed. Three tumors without significant change in signal intensity over time were observed, showing variable growth. Photoacoustic melanin signal on the last day of in vivo imaging correlated with postmortem total tumor volume (R2 = 0.81) and melanotic tumor volume (R2 = 0.80). The results of our study show that actively growing conjunctival melanomas can be quantified in a non-invasive manner using in vivo photoacoustic tomography. The photoacoustic melanin signal intensity correlated with total and melanotic tumor volume. This novel in vivo imaging platform may help to assess new treatment modalities to manage ocular tumors. Highlights • Non-invasive in vivo photoacoustic imaging was used to detect and monitor conjunctival melanomas. • Melanin content in tumors was quantified using photoacoustic tomography. • Melanin signal intensity correlated with histomorphometry. • In vivo quantification of melanin signal over time showed various patterns of tumors growth. [ABSTRACT FROM AUTHOR]

We study the acoustic imaging in low signal-to-noise ratio (SNR) environments with compressed sensing (CS) and microphone arrays. In this work, we propose an OMP-SVD method which combines the orthogonal matching pursuit (OMP) method of CS and the singular value decomposition (SVD). The performance of the proposed OMP-SVD method is compared with the CBF method, the OMP method and the l 1 -SVD method. In terms of the CPU time, the proposed method is highly efficient like the CBF method and the OMP method, and much more efficient than the l 1 -SVD method. In terms of the accuracy of the source maps, the OMP-SVD method can locate the sources exactly for the SNR as low as −10 dB and the frequency as low as 2000 Hz, while the other three different methods can only locate the sources when the SNR is greater than or equal to 5 dB. In addition, we find that the proposed method can obtain good performance when the target sparsity K T is overestimated and there is basis mismatch. Finally, a gas leakage experiment was conducted to verify the performance of the OMP-SVD method in practical application. The results show that the OMP-SVD method is robust in low SNR environments. [ABSTRACT FROM AUTHOR]

This paper presents the echoes-to-impedance transform, a nonlinear transform designed for acoustic imaging of layered media—for example, sedimentary geological formations, biological tissue such as skin, or laminated structures in the built environment. The transform converts time domain digital reflection data directly into impedance as a function of spatial location, using minimal prior information about the source wavelet and no prepreprocessing. It is simple, fast, and, according to numerical experiments, highly accurate. More than this, physical structure is superresolved at a finer scale than that of the source wavelet. The derivation of the echoes-to-impedance transform stems from a recently developed numerical method for wave propagation in one dimension in conjunction with the theory of orthogonal polynomials on the unit circle. [ABSTRACT FROM AUTHOR]

Understanding complex natural systems requires approaches with minimal statistical limitations and biases. Previously, however, the fields of behaviour, ecology and evolution generally have been restricted to evaluating differences between statistical distributions. This framework can be very powerful. Unfortunately, it has also created a bias in these, and many other, fields towards publications focusing only on phenomena for which there are statistically significant differences. However, there is a wide range of questions that would benefit from reversing the existing paradigm and testing, instead, for equivalence. We have adapted the two one-sided test (TOST), also known as equivalence testing, from pharmaceutical science to be applicable to behavioural and ecological studies. We created a repeated measures analysis that allows researchers to statistically examine similarities between distributions. We compared song structure in male and female eastern bluebirds, Sialia sialis , as a case study for this method. We failed to find significant differences between male and female songs via a more traditional test, repeated measures ANOVA. Therefore, no definitive conclusion could be drawn about the similarities or differences in song structure. However, our repeated measures equivalence test showed that, based on five standard measures of song variation, male and female eastern bluebirds sing statistically equivalent songs. Our study highlights the presence of complex female song in a temperate songbird species. Additionally, we provide a new statistical test useful for expanding the statistical toolbox to assess new behavioural and ecological questions, and to help counteract publication bias in our fields. Highlights • Although understudied, recent studies suggest that female birdsong is widespread. • We compared male and female song using a novel statistical equivalence test. • Both sexes had statistically equivalent songs based on five acoustic measures. • Our equivalence test will have wide applicability in behaviour, ecology and evolution. [ABSTRACT FROM AUTHOR]

Most sound source diagnosis systems based on acoustic images are spatially stationary and unable to combine information from multiple capture positions, resulting in unreliable and partial diagnostics. In this paper it is proposed, developed and validated a measurement method based on a mobile spherical microphone array that generates acoustic images using beamforming from multiple capture positions, called Acoustic Imaging Structure From Motion (AISFM). The tridimensional localization, magnitude and directivity of multiple sound sources may be recovered with or without knowledge of the capture positions. An automatic and unsupervised acoustic image processing algorithm is deployed to facilitate the measurement workflow. An acoustic image correspondence problem is solved in order to eliminate false-positives and false-negatives from the diagnostic and render the AISFM feasible. Sound sources localization uncertainties estimates related to the sources' magnitude, directivity and extension projected on the acoustic images are used in order to improve the diagnosis. The method and its effectiveness are experimentally validated with a measurement setup comprising five simultaneous sound sources on an anechoic environment. [Display omitted] • Computer vision algorithms for 3D reconstruction can be applied to acoustics. • These algorithms are integrated to a measurement method using a microphone array. • The microphone array generates a source map of the acoustic scene. • The method bundles information obtained from multiple source maps. • It outputs a 3D diagnostic of the acoustic scene. [ABSTRACT FROM AUTHOR]

Nanoprobes are small enough to circulate within the vasculature and can reach tumour tissues through the endothelial gap, providing a new strategy for accurate tumour monitoring and imaging-guided antitumour therapy at the molecular level. Both photoacoustic and ultrasonic imaging are noninvasive tools for cancer detection via the application of nanoprobes. In this study, a polymeric multifunctional nanoparticle probe loaded with gold nanorods (Au-NRs) and liquid perfluorocarbon (perfluorinated hexane/PFH) and conjugated to a monoclonal antibody (MAGE-1 antibody) to melanoma-associated antigens (MAGE) targeting melanoma was successfully prepared by the double emulsion and carbodiimide methods as a targeted photoacoustic/ultrasound dual-mode imaging contrast agent (MAGE-Au-PFH-NPs). Cell-targeting experiments in vitro showed large amounts of MAGE-Au-PFH-NPs surrounding B16 melanoma cells in the targeted group. The photoacoustic signal in the targeted group was significantly increased, and the duration was longer than that in the untargeted group in vivo . The photoacoustic signal of the nanoprobes was enhanced with increased Au-NR concentration in the photoacoustic experiment in vitro . The enhanced signal was observed by ultrasound after 808-nm laser irradiation. A cytotoxicity and biocompatibility test showed that MAGE-Au-PFH-NPs exhibited good biological safety. The MAGE-Au-PFH-NPs can be used as a photoacoustic/ultrasound dual-mode contrast agent to lay the foundation for a promising new approach for the noninvasive targeting, monitoring and treatment of tumours. [ABSTRACT FROM AUTHOR]

Phased array transducers are widely used for acoustic imaging and surround sensing applications. A major design challenge is the achievement of low mechanical cross-coupling between the single transducer elements. Cross-coupling induces a loss of imaging resolution. In this work, the mechanical cross-coupling between acoustic transducers is investigated for a generic model. The model contains a common backing with two bending elements bonded on top. The dimensions of the backing are small; thus, wave reflections on the backing edges have to be considered. This is different to other researches. The operating frequency in the generic model is set to a low kHz range. Low operating frequencies are typical for surround sensing applications. The influence of the backing on cross-coupling is investigated numerically. In order to reduce mechanical cross-coupling a stop band material is designed. It is shown numerically that a reduction in mechanical cross-coupling can be achieved by using stop band material as backing. The effect is validated with experimental testing. [ABSTRACT FROM AUTHOR]

We analyse the ill-posedness of the photoacoustic imaging problem in the case of an attenuating medium. To this end, we introduce an attenuated photoacoustic operator and determine the asymptotic behaviour of its singular values. Dividing the known attenuation models into strong and weak attenuation classes, we show that for strong attenuation, the singular values of the attenuated photoacoustic operator decay exponentially, and in the weak attenuation case the singular values of the attenuated photoacoustic operator decay with the same rate as the singular values of the non-attenuated photoacoustic operator. [ABSTRACT FROM AUTHOR]

The prediction and understanding of acetaminophen (APAP)-induced liver injury (APAP-ILI) and the response to therapeutic interventions is complex. This is due in part to sensitivity and specificity limitations of currently used assessment techniques. Here we sought to determine the utility of integrating translational non-invasive photoacoustic imaging of liver function with mechanistic circulating biomarkers of hepatotoxicity with histological assessment to facilitate the more accurate and precise characterization of APAP-ILI and the efficacy of therapeutic intervention. Perturbation of liver function and cellular viability was assessed in C57BL/6J male mice by Indocyanine green (ICG) clearance (Multispectral Optoacoustic Tomography (MSOT)) and by measurement of mechanistic (miR-122, HMGB1) and established (ALT, bilirubin) circulating biomarkers in response to the acetaminophen and its treatment with acetylcysteine (NAC) in vivo. We utilised a 60% partial hepatectomy model as a situation of defined hepatic functional mass loss to compared acetaminophen-induced changes to. Integration of these mechanistic markers correlated with histological features of APAP hepatotoxicity in a time-dependent manner. They accurately reflected the onset and recovery from hepatotoxicity compared to traditional biomarkers and also reported the efficacy of NAC with high sensitivity. ICG clearance kinetics correlated with histological scores for acute liver damage for APAP (i.e. 3 h timepoint; r = 0.90, P < 0.0001) and elevations in both of the mechanistic biomarkers, miR-122 (e.g. 6 h timepoint; r = 0.70, P = 0.005) and HMGB1 (e.g. 6 h timepoint; r = 0.56, P = 0.04). For the first time we report the utility of this non-invasive longitudinal imaging approach to provide direct visualisation of the liver function coupled with mechanistic biomarkers, in the same animal, allowing the investigation of the toxicological and pharmacological aspects of APAP-ILI and hepatic regeneration. [ABSTRACT FROM AUTHOR]

• A Taylor expansion-based two-dimensional off-grid CSB model is established for panoramic acoustic source identification with spherical microphone arrays. • OGSBI is adapted to solve this model to achieve DOA and strength estimation, thus forming OGSBI-CSB. • OGSBI-SBI not only can effectively alleviate basis mismatch problem and then improve identification accuracy for off-grid sources but also enjoys super-resolution and good resistance to noise interference. Compressive spherical beamforming (CSB) with spherical microphone arrays is a panoramic acoustic source identification technology with high spatial resolution and clear acoustic imaging, which has broad application prospects. Due to the discretization of the focus region and the assumption of on-grid sources, classical CSB suffers from the basis mismatch problem, i.e., it faces performance deterioration when identifying off-grid sources. To overcome the problem, this paper proposes off-grid sparse Bayesian inference-based CSB (OGSBI-CSB). OGSBI-CSB formulates the direction of arrival (DOA) as the sum of the DOA of grid point and DOA offset, constructs an off-grid model based on Taylor expansion, and adapts OGSBI to solve the model and obtains DOA and strength estimation. Simulations and experiments demonstrate that the proposed OGSBI-CSB not only can effectively alleviate the basis mismatch problem and then improve identification accuracy for off-grid sources, but also enjoys super-resolution and good resistance to noise interference. [ABSTRACT FROM AUTHOR]

Improving the resolution of ultrasound array imaging systems for multiple defects in a measured medium is a popular research topic in nondestructive testing technology. However, because of the diffraction of acoustic waves, the resolution of ultrasound array imaging systems must follow Rayleigh's criterion and hence is limited, and defects with a spacing smaller than the resolution limit cannot be identified using conventional ultrasound imaging methods. Ultrasonic Lamb waves have dispersion and mode conversion characteristics, and the scattering acoustic field after the interaction between Lamb waves and defects is usually complex, making it even more difficult to improve the imaging resolution. In this paper, ultrasonic Lamb wave imaging is investigated with the sign coherence factor-total focusing method (SCF-TFM) when the spacing of the detected defects is smaller than the resolution limit, and the imaging resolution limit of SCF-TFM is analyzed. Experiments on a single blind-hole defect show that the lateral resolution of the SCF-TFM imaging is nearly twice as high as that of the total focusing method (TFM), with a higher signal-to-noise ratio. For experiments on multiple blind-hole defects, the resolution of the SCF-TFM improves by 71.32%, which is higher than that of the TFM when the spacing of the detected defects is larger than the resolution limit. The SCF-TFM enables super-resolution imaging and achieves a higher resolution limit than time-domain topological energy when the spacing of the detected defects is smaller than the resolution limit. [ABSTRACT FROM AUTHOR]

An experimental comparison of four different methods of nearfield acoustic holography (NAH) for planar acoustic sources is presented in this study. The four NAH methods considered in this study are based on: (1) spatial Fourier transform, (2) equivalent sources model, (3) boundary element methods and (4) statistically optimized NAH. Two dimensional measurements were obtained at distances ranging from one-half to sixteen microphone spacings away from a sound source and the NAH methods were used to reconstruct the sound field at the source surface. Reconstructed particle velocity and acoustic pressure fields presented in this study showed that the equivalent sources model based algorithm along with Tikhonov regularization provided the best localization of the sources. Reconstruction errors were found to be smaller for the equivalent sources model based algorithm and the statistically optimized NAH algorithm. The effects of hologram distance on the performance of various algorithms are discussed in detail. The study also compares the computational time required by each algorithm to calculate the reconstruction. Four different regularization parameter choice methods were compared. The L-curve method provided more accurate reconstructions than the generalized cross validation and the Morozov discrepancy principle at larger measurement distances. The performance of fixed parameter regularization was comparable to that of the L-curve method. [ABSTRACT FROM AUTHOR]

There have been enormous technical advances in the use of imaging techniques in speech production research in terms of resolution and frame rates. However, a major bottleneck lies in the lack of appropriate data reduction and quantification methods which allow for a parsimonious representation of the high-dimensional image data. Particularly the rapid increase in frame rates seen in data acquisition makes traditional, error-prone methods of contour tracking unwieldy due to the high amount of manual intervention required. We discuss recent developments in methods that obviate contour tracking but instead process the entire image. Specifically, we focus on one such approach by demonstrating the application of Principal Component Analysis to ultrasound images. This method not only exploits the information present in the entire image, but it also straightforwardly allows for the representation of the temporal evolution of an utterance by reducing a series of images to a time-varying single-value representation. In an illustrative example, inspired by the seminal work of Öhman (1966), we show how characteristic patterns of coarticulation between vowels and consonants can be captured in this way. [ABSTRACT FROM AUTHOR]

Carbonaceous dots exhibit increasing applications in diagnosis and drug delivery due to excellent photostability and biocompatibility properties. However, relative short excitation and emission of melanin carbonaceous dots (MCDs) limit the applicability in fluorescence bioimaging. Furthermore, the generally poor spatial resolution of fluorescence imaging limits potential in vivo applications. Due to a variety of beneficial properties, in this study, MCDs were prepared exhibiting great potential in fluorescence and photoacoustic dual-mode bioimaging. The MCDs exhibited a long excitation peak at 615 nm and emission peak at 650 nm, further highlighting the applicability in fluorescence imaging, while the absorbance peak at 633 nm renders MCDs suitable for photoacoustic imaging. In vivo , the photoacoustic signal of MCDs was linearly correlated with the concentration of MCDs. Moreover, the MCDs were shown to be taken up into triple negative breast cancer cell line 4T1 in both a time- and concentration-dependent manner. In vivo fluorescence and photoacoustic imaging of subcutaneous 4T1 tumor demonstrated that MCDs could passively target triple negative breast cancer tissue by enhanced permeability and retention effects and may therefore be used for tumor dual-mode imaging. Furthermore, fluorescence distribution in tissue slices suggested that MCDs may distribute in 4T1 tumor with high efficacy. In conclusion, the MCDs studied offer potential application in fluorescence and photoacoustic dual-mode imaging. [ABSTRACT FROM AUTHOR]

This paper presents modeling and design of an active structural acoustic control (ASAC) system for controlling the low frequency sound field transmitted through an aircraft cabin window. The system uses stacked piezoelectric elements arranged in a manner to generate out-of-plane actuation point forces acting on the window panel boundaries. A theoretical vibro-acoustic model for an active quadruple-panel system is developed to characterize the dynamic behavior of the system and achieve a good understanding of the active control performance and the physical phenomena of the sound transmission loss (STL) characteristics. The quadruple-panel system represents the passenger window design used in some classes of modern aircraft with an exterior double pane of Plexiglas, an interior dust cover pane and a glazed dimmable pane, all separated by thin air cavities. The STL characteristics of identical pane window configurations with different piezoelectric actuator sets are analyzed. A parametric study describes the influence of important active parameters, such as the input voltage, number and location of the actuator elements, on the STL is investigated. In addition, a mathematical model for obtaining the optimal input voltage is developed to improve the acoustic attenuation capability of the control system. In general, the achieved results indicate that the proposed ASAC design offers a considerable improvement in the passive sound loss performance of cabin window design without significant effects, such as weight increase, on the original design. Also, the results show that the acoustic control of the active model with piezoelectric actuators bonded to the dust cover pane generates high structural vibrations in the radiating panel (dust cover) and an increase in sound power radiation. High active acoustic attenuation can be achieved by designing the ASAC system to apply active control forces on the inner Plexiglas panel or dimmable panel by installing the actuators on the boundaries of one of the two panels. In some cases, increasing the actuator numbers in the structure advances the active control performance by controlling more structural modes; however, this decreases the STL of the passive control system because of the increase in structure-borne sound transmission paths of the stiffer piezoelectric actuators. [ABSTRACT FROM AUTHOR]

Shallow water is a complicated sound propagation medium due to multiple reflections by water surface and bottom, imprecisely measured sound speed, noisy environment, etc. Therefore, in order to localize a shallow water sound source, classical signal processing techniques must be improved by taking these complexities into account. In this work, the multiple reflections and uncertain reflectivity of water bottom are explicitly modeled. In the proposed model, a measured signal is a mixture of the direct propagation from the source and the multiple reflections. Instead of solving the Helmholtz equation with boundary conditions of reflections, each signal is interpreted as a superposition of signals emitting from the physical source and its image sources in a free space, which results in a fast computation of sound propagation. Then, the source location, along with its amplitude, reflection paths and power loss of bottom reflection, is estimated via the iterative beamforming (IB) method, which alternatively estimates the source contributions and performs beamforming on these estimates until convergence. This approach does not need to compute the sound propagation for all the possible source locations in a large space, which thus leads to a low computational cost. Finally, numerical simulations are introduced to illustrate the advantage of the proposed model and the source estimation method. The sensitivity of the proposed method with respect to model parameter uncertainties is also investigated via a full uncertainty quantification analysis. The localization error of IB is proved to be acceptable in the given error range of sound speed and water depth. Besides, the IB source estimate is more sensitive to the sound speed while the matched-field processing methods have a stronger sensitivity to the water depth: this result can guide the choice of source localization method in different cases of model parameter uncertainties. [ABSTRACT FROM AUTHOR]

A long-standing challenge in optical neuroimaging has been the assessment of hemodynamics and oxygen metabolism in the awake rodent brain at the microscopic level. Here, we report first-of-a-kind head-restrained photoacoustic microscopy (PAM), which enables simultaneous imaging of the cerebrovascular anatomy, total concentration and oxygen saturation of hemoglobin, and blood flow in awake mice. Combining these hemodynamic measurements allows us to derive two key metabolic parameters—oxygen extraction fraction (OEF) and the cerebral metabolic rate of oxygen (CMRO 2 ). This enabling technology offers the first opportunity to comprehensively and quantitatively characterize the hemodynamic and oxygen-metabolic responses of the mouse brain to isoflurane, a general anesthetic widely used in preclinical research and clinical practice. Side-by-side comparison of the awake and anesthetized brains reveals that isoflurane induces diameter-dependent arterial dilation, elevated blood flow, and reduced OEF in a dose-dependent manner. As a result of the combined effects, CMRO 2 is significantly reduced in the anesthetized brain under both normoxia and hypoxia, which suggests a mechanism for anesthetic neuroprotection. The head-restrained functional and metabolic PAM opens a new avenue for basic and translational research on neurovascular coupling without the strong influence of anesthesia and on the neuroprotective effects of various interventions, including but not limited to volatile anesthetics, against cerebral hypoxia and ischemia. [ABSTRACT FROM AUTHOR]

Acoustic imaging methods are used to detect and quantify aerodynamic noise sources in aeroacoustic experiments. In wind tunnels with an open jet test section the sound wave propagating from an aeroacoustic source to a microphone array is distorted by the shear layer in the propagation path. The velocity fluctuations caused by the turbulence in the shear layer continuously alter the propagation time between source and observer causing reduction of the coherence between two microphone signals. The reduction in coherence is stochastic and dependents on the relative position between source and microphone. This leads to blurred acoustic source images with reduced peak Sound Pressure Level. This paper presents the Acoustic Lucky Imaging methodology, based on a methodology in astronomy to correct for image distortion due to turbulence present in Earth's atmosphere. Furthermore, a model for coherence loss is derived to explain the loss of acoustic image resolution and allow for a-priori estimates on acoustic image blurring. The methodology is applied to an acoustic data set obtained in the open jet of a large industrial wind tunnel. It is shown that the presented methodology can restore a loss of 6 dB peak Sound Pressure Level by 3 dB and increase the resolution of the acoustic image at 8 kHz, a wind tunnel speed of 34 m s−1, and a shear layer thickness of ∼ 1 m. [ABSTRACT FROM AUTHOR]