In the context of autosomal dominant polycystic kidney disease (ADPKD), total kidney volume (TKV) plays a key role as biomarker of disease progression and response to therapy and has been recently recognized as enrichment biomarker and possible surrogate endpoint. Several imaging modalities and methods are available to calculate TKV, and the choice depends on the purpose of use. Technological advancements have made it possible to accurately assess cyst burden, that can be crucial to assess the disease state and help identifying rapid progressors. Moreover, the development of automated algorithms has increased the efficiency of total kidney and cyst volume measurements. Beyond total kidney and cyst volume, the quantification and characterization of non-cystic kidney tissue show potential to early stratify ADPKD patients, monitor disease progression, and possibly predict renal function loss. A broad spectrum of kid-ney MRI techniques are available to characterize kidney tissue, showing promise to non-invasively pick up early signs of ADPKD progression. Radiomics has been used to extract tex-tural features from ADPKD images, providing valuable information about the heterogeneity of the cystic and non-cystic components. This review provides an overview of ADPKD imaging bi-omarkers, focusing on quantification methods, potential, and necessary steps towards successful translation to clinical practice.

Mammography is the gold standard for breast cancer screening and diagnostic imaging; however, there is an unmet clinical need for complementary methods to detect lesions not characterized by mammography. Far-infrared 'thermogram' breast imaging can map the skin temperature, and signal inversion with components analysis can be used to identify the mechanisms of thermal image generation of the vasculature using dynamic thermal data. This work focuses on using dynamic infrared breast imaging to identify the thermal response of the stationary vascular system and the physiologic vascular response to a temperature stimulus affected by vasomodulation. The recorded data is analyzed by converting the diffusive heat propagation into a virtual wave and identifying the reflection using component analysis. Clear images of passive thermal reflection and thermal response to vasomodulation were obtained. Validation of this proposed paradigm through further clinical exploration may demonstrate clinical utility for the IR modality in diagnostic imaging, offering a potential solution to the current unmet clinical need.

The development of Imaging Atmospheric Cherenkov Telescopes (IACTs) unveiled the sky in the teraelectronvolt regime, initiating the so-called “TeV revolution” at the beginning of the new millennium. This revolution was also facilitated by the implementation and adaptation of statistical tools for analyzing the shower images collected by these telescopes and inferring the properties of the astrophysical sources that produce such events. The image reconstruction techniques, the background discrimination and the signal-detection analyses are just a few of the pioneering studies applied in the last decades in the analysis of IACTs data. This (succinct) review has the intent of summarizing the most common statistical tools that are used for analyzing data collected with IACTs, focusing on their application in the full analysis chain, giving references to the past literature for a deepened examination.

Uveal melanoma is the most common primary intraocular malignancy in adults characterized by insidious onset and poor prognosis strongly associated with tumor size and the presence of distant metastases, most commonly in the liver. Contrary to most tumor identification, biopsy followed by pathological exam is not recommended in ophthalmic oncology. Therefore, early and non-invasive diagnosis is essential to enhance patients’ chances for early treatment possibilities. We reviewed imaging modalities currently used in the diagnosis of uveal melanoma, i.e., fundus imaging, ultrasonography (US), optical coherence tomography (OCT), single-photon emission computed tomography (SPECT), positron emission tomography/computed tomography (PET/CT), magnetic resonance imaging (MRI), fundus fluorescein angiography (FFA), indocyanine green angiography (ICGA), fundus autofluorescence (FAF). The principle of imaging techniques was briefly explained, along with their role in the diagnostic process and a summary of their advantages and limitations. Further, the experimental data and the advancements in imaging modalities were searched. We described their innovations, showed current usage and research, and explained the possibilities of utilizing them to diagnose uveal melanoma and their potential application in personalized medicine such as theranostics.

Immunotherapy is an effective therapeutic option for several cancers. In the last years, the introduction of checkpoint inhibitors (ICIs) has shifted the therapeutic landscape in oncology and improved patient prognosis in a variety of neoplastic diseases. However, to date, the selection of the best patients eligible for these therapies, as well as the response assessment is still challenging. Patients are mainly stratified using immunohistochemical analysis of the expression of anti-gens on biopsy specimens, such as PD-L1 and PD-1, on tumor cells, on peritumoral immune cells, and/or in the tumor microenvironment (TME). Recently, the use and development of imaging biomarkers able to assess in-vivo cancer-related processes are becoming more important. Today, positron emission tomography (PET) with 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) is used routinely to evaluate tumor metabolism, and also to predict and monitor response to immunotherapy. Although highly sensitive, FDG-PET, in general, is rather unspecific. Novel radiopharmaceuticals (immuno-PET radiotracers) able to identify specific immune system targets are under investigation in pre-clinical and clinical settings. In this review, we will provide an overview of the main new immuno-PET radiotracers in development. We will also review the main players (immune cells, tumor cells, and molecular targets) involved in immunotherapy. Furthermore, we report current applications and the evidence of using [18F]FDG PET in immunotherapy, including the use of artificial intelligence (AI).

We present a MATLAB-based, open source reconstruction software for Hybrid Imaging problem arising from Current Density Impedance Imaging (CDII) and Acoustic-Electrical Impedance Tomography (AEIT), utilizing mixed finite element method solver of Darcy toolbox {\tt DarcyLite}~. For a formulation of hybrid inverse problems in impedance tomography the successive substitution iterative schemes are adapted and an reconstruction algorithm is developed. The problem formulation is a class of hybrid imaging modality which is current density impedance imaging or Acoustic-Electrical Impedance Tomography. The proposed algorithm is implemented numerically in two dimensions.

Three-dimensional (3D) imaging has attracted more and more interests because of its widespread applications, especially in information and life science. These techniques can be broadly divided into two types: ray-based and wavefront-based 3D imaging. Issues such as imaging quality and system complexity of these techniques limit the applications significantly, and therefore many investigations have focused on 3D imaging from depth measurements. This paper presents an overview of 3D imaging from depth measurements, and provides a summary of the connection between these the ray-based and wavefront-based 3D imaging techniques.

The social- and self-directed behaviours of two golden lion tamarins (Leontopithecus rosalia) was investigated while having residence in the tropical house of Aalborg Zoo, Denmark. The behaviour of the female had been distinct from the male since 2018. Despite several diagnostic examinations and medicinal treatments, the cause of the aberrant and apparently stereotypical behavioural patterns remained undetermined, which initiated this study. The pair were recorded throughout a predetermined observation period and these recordings were analysed to illuminate the behaviours of the individuals. The results showed that there were differences in the type, frequency, and durations of both social- and self-directed behaviours between the sick female and the healthy male. The female expressed both social- and self-directed behaviours more frequently and for longer durations, while the male were more socially reserved and did not engage in social behaviours as frequently. Furthermore, subsequent necropsy of the female revealed uro-genital disease.

Photoacoustic imaging (PAI) is a cutting-edge biomedical imaging modality, providing detailed anatomical and functional information about the area beneath the skin surface. Its light energy deposition is such that PAI typically provides clear images of the skin with high signal-to-noise ratios. Specifically, the rich optical contrast of PAI allows biological information related to lesion growth, malignancy, treatment response, and prognosis to be seen. Given its significant advantages and emerging role in imaging skin lesions, we summarize and comment on representative studies of skin PAI, such as the guidance of skin cancer biopsies and surgical excisions, and the accurate diagnosis of psoriasis. We conclude with our insights about the clinical significance of skin PAI, showing how its use to identify biological characteristics in lesion microenvironments allows early diagnosis and prognosis of disease.

Attempts to use computers to aid in the detection of breast malignancies date back more than 20 years. Despite significant interest and investment, this has historically led to minimal or no significant improvement in performance and outcomes with traditional computer aided detection. However, recent advances in artificial intelligence and machine learning are now starting to deliver on the promise of improved performance. There are at present more than 20 FDA approved AI applications for breast imaging, but adoption and utilization are widely variable and overall low. Breast imaging is unique and has aspects that create both opportunities and challenges for AI development and implementation. Breast cancer screening programs worldwide rely on screening mammography to reduce the morbidity and mortality of breast cancer and many of the most exciting research and available AI applications focus on cancer detection for mammography. There are however multiple additional potential applications for AI in breast imaging including decision support, risk assessment, breast density quantitation, workflow and triage, quality evaluation, response to neoadjuvant chemotherapy assessment, and image enhancement. In this review the current status, availability, and future directions of investigation of these applications are discussed, as well as the opportunities and barriers to more widespread utilization.

In this paper we explore extending the concept of common cross-study Common Data Element concepts beyond simple demographics to cover disease-specific concepts relevant to imaging. We test interactively linking the resulting database to the associated images in a federated manner. We examine the use of existing standards, not only for terminology, but for interchange of serialized data in forms familiar to imaging and clinical trials specialists and their dedicated systems. Our intent is to perform preliminary work to inform both the upcoming Imaging Data Commons specifically, as well as more general integration projects beyond imaging.

The cytokine-producing nucleotide-binding domain leucine-rich repeat and pyrin-containing receptor 3 (NLRP3) inflammasome is generally recognized to play a central role in the immune response to vaccination and NLRP3 activity is known to be increased by both aluminum adjuvants and by oxidative stress. Thus, the presence of oxidative stress may place individuals at higher risk for exaggerated or prolonged inflammatory responses and related side effects from vaccination. We here examine the relationship between oxidative stress and NLRP3 inflammasome activity, particularly in the context of aluminum-adjuvanted vaccines, and its implications for subpopulations of individuals with restricted antioxidant capacity.

The pandemic respiratory disease COVID-19, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), emerged in Wuhan in December 2019 and then spread throughout the world; Italy was the most affected European country. Despite the close pet-human contact, little is known about the predisposition of pets to SARS-CoV-2. Among these, felines are the most susceptible. In this study, a domestic cat with clear symptoms of pneumonia, confirmed by Rx imaging, was found to be infected by SARS-CoV-2 using quantitative RT–qPCR from a nasal swab. This is the first Italian study reporting on the request of the scientific community to focus attention on the possible role of pets as a SARS-CoV-2 reservoir. An important question remains unanswered: did the cat die from SARS-CoV-2 infection?

The AT-HOOK MOTIF NUCLEAR LOCALIZED PROTEIN (AHL) gene family encodes embryophyte-specific nuclear proteins with DNA binding activity. They modulate gene expression and affect various developmental processes in plants. We identify AHL18 (At3G60870) as a developmental modulator of root system architecture and growth. AHL18 regulates the length of the proliferation domain and number of dividing cells in the root apical meristem and thereby, cell production. Both primary root growth and lateral root development respond according to AHL18 transcription level. The ahl18 knock-out plants show reduced root systems due to a shorter primary root and a lower number of lateral roots. This change results from a higher number of arrested and non-developing lateral root primordia (LRP) rather than from decreased initiation. Overexpression of AHL18 results in a more extensive root system, longer primary roots, and increased density of lateral root initiation events. Formation of lateral roots is affected during the initiation of LRP and later development. AHL18 regulate root apical meristem activity, lateral root initiation and emergence, which is in accord with localization of its expression.

DEXTER (Detection of EXplosives and firearms to counter TERrorism) is a project funded by NATO’s Science for Peace and Security (SPS) program with the goal of developing an integrated system capable of remotely and accurately detecting explosives and firearms in public places without impeding the flow of pedestrians. The active microwave component of the DEXTER project is referred to as MIC (Microwave Imaging Curtain), supported by the French SGDSN (General Secretariat of Defense and National Security), and utilizes a radar system capable of generating 3D images in real time to address non-checkpoint detection of explosives and fire-arms. The project, led by the ONERA (France), is based on a radar imaging system developed by the Fraunhofer FHR institute, using a MIMO architecture with an Ultra Wide-Band waveform. Although high-resolution 3D microwave imaging is already being used in expensive body scanners to detect firearms concealed under clothing, MIC's innovative approach lies in utilizing a high-resolution 3D imaging device that can detect larger dangerous objects carried by moving individuals at a longer range, in addition to providing discrete detection in pedestrian flow. Automatic detection and classification of these dangerous objects is carried out on 3D radar im-ages using a deep-learning network. This paper will outline the project's objectives and constraints, as well as the design, architecture, and performance of the final system. Additionally, it will present real-time imaging results ob-tained during a live demonstration in a relevant environment.

Abstract: Mass spectrometry research laboratories reported multiple probes for ambient ionization in the last years. Combining them with a mechanical moving stage enables automated sampling and imaging applications. We developed a robotic platform, which is based on RepRap 3D-printer components, and therefore easy to reproduce and to adopt for custom prototypes. The minimal step width of the Open LabBot is 12.5 μm, and the sampling dimensions (x, y, z) are 18 × 15 × 20 cm. Adjustable rails in an aluminium frame construction facilitate the mounting of additional parts such as sensors, probes, or optical components. The Open LabBot uses industry-standard G-code for its control. The simple syntax facilitates the programming of the movement. We developed two programs: 1) LABI-Imaging, for direct control via a USB connection and the synchronization with MS data acquisition. 2) RmsiGUI, which integrates all steps of mass spectrometry imaging: The creation of G-code for robot control, the assembly of imzML files from raw data and the analysis of imzML files. We proved the functionality of the system by the automated sampling and classification of essential oils with a PlasmaChip probe. Further, we performed an ambient ionization mass spectrometry imaging (AIMSI) experiment of a lime slice with laser desorption low-temperature plasma (LD-LTP) ionization, demonstrating the integration of the complete workflow in RmsiGUI. The design of the Open LabBot and the software are released under open licenses to promote their use and adoption in the instrument developers’ community.

Traditional painting artefacts study and documentation face the limitations of well-known recording tools and methods, such as handwritten or digital descriptions, scaled 2D drawings in situ, measurements with calipers, rulers or tape measures, sketches, tracings, as well as conventional or technical photographs. This paper advocates Close-Range Photogrammetry (SfM-MVS) and Reflectance Transformation Imaging (RTI) for recording vital morphological and 2.5D geometric features of painted surfaces with high accuracy. These digital tools, widely accessible due to increased computing power, enhance art observation, material study and conservation assessment. Despite specialized alternatives like 3D laser scanners, the focus here is on the cost-effective SfM-MVS and RTI, which offer advanced pixel colour accuracy. The ability to reproduce photorealistic textures proves essential for accurate documentation of painted artefacts. The paper showcases promising results from applying these methods to a mural from the Palace of Tiryns, justifying their fundamental role in an integrated scientific art study methodology.

: Image guided superficial radiation therapy (IGSRT) combines superficial radiation therapy (SRT) with full dermal visualization (FDV) via high resolution dermal ultrasound (HRDUS) for the treatment of non-melanoma skin cancer (NMSC). The gold standard for IGSRT delivery includes a comprehensive cancer care model with support for the dermatologists by a multidisciplinary team. When delivered in this model, IGSRT can achieve cure rates of 99% for treatment of NMSC. This paper focuses on the benefits of IGSRT during therapy. Medical records from 7 dermatology clinics of 883 patients with 1,507 cases of NMSC treated with IGSRT be-tween 2017 and 2018 were retrospectively reviewed. 92% of the NMSC lesions showed daily depth fluctuations, 60.32% of lesions did not require changes during therapy, and nearly 40% of lesions required at least one compensatory change during therapy. 83% of NMSC lesions were labeled high-risk based on the 2024 NCCN guidelines. Increasing and decreasing tumor depth measurements during IGSRT inform dermatologists when adaptive changes in energy (kV), TDF and dose will result in more efficacy and less toxicity, respectively.

Microbiota-based strategies are a novel auxiliary therapeutic and preventative way of moderating chronic kidney disease. Lactobacillus mixture (Lm) was previously demonstrated to exert a renal-protective function in the CKD mice model. The efficacy of probiotics in pet foods is a relatively new area of study, and thus verifying the potential health benefits is necessary. This study evaluated the efficacy of Lm treats in feline CKD and elucidated the mechanisms underlying host-microbe interactions. CKD cats (2 and 3 stages) were administrated probiotic pet treats daily (10 g) for 8 weeks. The results demonstrated that during the eight weeks of Lm administration, creatinine was reduced or maintained in all cats with CKD. Similarly, gut-derived uremic toxins (GDUT), IS, and TMAO were significantly downregulated in the serum (confidence intervals = 90%). The life quality of the cats also improved. Feline gut microbiome data, KEGG pathway, and renal function indicator analyses revealed the possible mechanisms involved in modulating CKD feline microbial composition. Further regulation of the microbial functions in amino acid metabolism after Lm administration contributed to downregulating deleterious IS, PCS, and TMAO. The current study provides potential adjuvant therapeutic insights into probiotic pet foods or treats for pets with CKD.

Abstract: This study presents a methodological framework for AD and MCI diagnosis using radiomic analysis of 18FDG-PET imaging and conducts non-invasive predictions and in-depth analysis of AD and MCI and the associated small number of regions and features. Our methodology follows a structured process commencing with data preprocessing and labeling, facilitating segmentation through FastSurfer, a tool that efficiently segments the brain into 95 ROIs using the DKT-atlas. Subsequently, Feature extraction was carried out using PyRadiomics, calculating 120 features for each of the 95 ROIs (11,400 per image). These extracted features form the foundation of our radiomics analysis, primarily for early diagnostic purposes. In the feature selection phase, we explored a set of eight commonly employed techniques, including ANOVA, PCA, and LASSO, originating from the four main categories, namely filtered, embedded, wrapper, and hybrid methods, to identify a pertinent subset of features. Our evaluation assessed the performance of nine classification methods, such as GradientBoosting, RandomForest, and GaussianNB, in conjunction with eight feature selection techniques. The choice of feature selection method and classifiers was predicated on their ability to achieve the best area under the ROC curve with independent data. For all three predictions AD vs. CN, AD vs. MCI, and CN vs. MCI the Random Forest (RF) classifier with LASSO feature selection demonstrated the highest accuracy with an AUC of 0.976 for AD vs CN, AUC=0.917 for AD vs MCI, and AUC=0.877 for MCI vs CN. In conclusion, our RAB-PET platform enables efficient AD and MCI diagnosis from FDG-PET images using a radiomics pipeline. It also offers a general hardware and software tool for the investigation of other brain disorders.

Evaluation of the usefulness of [18F]FDG-PET/CT in the short-term follow-up of patients admitted for COVID-19 pneumonia and to explore the association of findings with clinical prognostic markers. Prospective study included 20 patients admitted to hospital with COVID-19 pneumonia between November 2020 and March 2021. Clinical and laboratory test findings were gathered at admission, 48-72h post-admission, and 2-3 months post-discharge. [18F]FDG-PET/CT and respiratory function tests were performed at 2-3 months post-discharge. Lung volumes (TLC), spirometry (FVC, FEV1), lung diffusion capacity for carbon monoxide (DLCO), and respiratory muscle strength were measured. PET/CT images were qualitatively and semi-quantitatively interpreted. Volumetric [18F]FDG-PET/CT results were correlated with laboratory test and respiratory parameters. Eleven [18F]FDG-PET/CT (55%) were positive. The main finding was hypermetabolic lymphade-nopathy in the mediastinum (90.9%). SUVpeak of the target mediastinum lesion was correlated with neutrophil and lymphocyte counts. Eleven (55%) patients had impaired respiratory function, most frequently a reduced DLCO (35%). SUVpeak was positively correlated with %predict-ed-DLCO values. Pulmonary TLG was negatively correlated with %predicted-DLCO and TLC values. In the short-term follow-up of patients hospitalized for COVID-19 pneumonia, [18F]FDG-PET/CT findings revealed significant detectable inflammation in lungs and mediastinal lymph nodes that correlated with pulmonary function impairment in more than half of the patients.

Positron emission tomography (PET) imaging of Colony Stimulating Factor 1 Receptor (CSF1R) is a new strategy for quantifying both neuroinflammation and inflammation in the periphery since CSF1R is expressed on microglia. AZ683 has high affinity for CSF1R (K_i = 8 nM; IC₅₀ = 6 nM) and >250-fold selectivity over 95 other kinases and, in this paper, we report the radiosynthesis of [¹¹C]AZ683 and initial evaluation of its use in CSF1R PET. [¹¹C]AZ683 was synthesized by ¹¹C-methylation of the desmethyl precursor with [¹¹C]MeOTf in 3.0% non-corrected activity yield (based upon [¹¹C]MeOTf), >99% radiochemical purity and high specific activity. Preliminary PET imaging with [¹¹C]AZ683 revealed no brain uptake in rodents and nonhuman primates suggesting that [¹¹C]AZ683 is a poor candidate for imaging neuroinflammation, but that it could still be useful for peripheral imaging of inflammation.

A new sustainable polypropylene terephthalate (PPT) coating was synthesized from recycled polyethylene terephthalate (PET) and applied on hydraulic concrete substrate to improve its durability. First step, PET bottles wastes were grinded and depolymerized by glycolysis using propylene glycol (PG), in a Vessel-type reactor (20–180 °C) to synthesize bis(2-hydroxypropyl)-terephthalate (BHPT), which was applied as coating to one-three layers on hydraulic concrete substrate, by brushing technique and polymerized (150 °C for 15 h) to obtain PPT. PET, BHPT and PPT were characterized by FT-IR, PET and PPT by TGA, and the PPT coatings by SEM (thickness), by ASTM-D3359-17 (adhesion) and by water contact angle (wettability). The durability of hydraulic concrete coated with PPT was studied by resist chloride ion penetration (ASTM-C1202-17), carbonation depth at 28 days (RILEM-CPC-18), and absorption water ratio (ASTM-C1585-20). The results demonstrated that the BHPT and PPT were synthetized (FT-IR), PPT had a similar thermal behaviour to PET (TGA); the PPT coatings had good adhesion to the substrate, with thicknesses of micrometric units; hydrophilic (similar to PET coatings), and the durability of hydraulic concrete coated with PPT (2-3 layers) improved (migration of chloride ions decreased, carbonation depth was negligible, and the absorption water ratio decreased).

in order to enhance the separation performance and to reduce the heat loss of the transmembrane for membrane distillation, the thermal efficiency and hydrophobicity of the membrane distillation should be simultaneously enhanced. In this work, a PVDF/PET hydrophobic/hydrophilic membrane is prepared by non-solvent phase inducing method. Nanosized silica aerogel (SiAG) with high porosity is added to the composite membranes. The modifying effects and operating conditions on permeate flux and thermal efficiency in direct contact membrane distillation (DCMD) are investigated. Furthermore, the latent heat of vaporization and the heat transfer across the membranes are compared for SiAG addition, which indicates that the composite PVDF@SiAG/PET membranes display a great potential for distillation-separation application with high heat efficiency.

Tumor immunotherapy represented by immune target blocking and chimeric antigen receptor cell therapy has developed rapidly. Among them, Natural Killer Cell (NK) is gradually becoming another preferred immunotherapy method after T cell immunotherapy because of its unique killing effect in innate immunity and adaptive immunity. Although NK cell therapy has achieved promising results in clinical trials, there are still some problems, such as low efficacy in solid tumors, insufficient penetration of NK cells and high cost of treatment. Nanomaterials are expected to be an excellent tool to improve the anti-tumor immune response of NK cells due to their advantages such as chemical specificity, biocompatibility and simple synthesis. Nanomaterials can enhance the cytotoxicity of NK cells, participate in the modification and noninvasive cell-tracking patterns of NK cells，and mediate their homing and infiltration, and thus significantly improve the efficiency of NK cell immunotherapy. In this review, we will briefly introduce the methods and mechanisms of tumor immunotherapy, emphasize the research progress of NK cell-based immunotherapy and imaging, and finally summarize the direction and research progress of nanomaterials in NK cell-based immunotherapy.

This research delves into the intricate challenges confronting the agricultural sector, with a specialized focus on mitigating infections in tomato crops, particularly powdery mildew induced by the Leveillula Taurica pathogen. Tomatoes, renowned for their nutritional richness, are vital to global food security. However, conventional methodologies for disease detection exhibit both laborious processes and limited accuracy. In response to these challenges, this study advocates for an innovative fusion of hyperspectral imaging and deep learning methodologies to detect crop disease and its severity. The systematic workflow commenced with the curation of a dataset, involving the acquisition of live images through OpenCV, followed by conversion to RGB format and subsequent feature extraction utilizing a pre-trained visual geometry group (VGG-16) model for enhanced analysis. Sequentially, RGB images were transformed into simulated hyperspectral images (SHSI) leveraging a Neural Network generator model, offering a distinctive viewpoint on spectral information. This novel approach transcends conventional constraints by delivering a three-dimensional perspective, seamlessly integrating spatial and spectral dimensions for holistic data acquisition. The SHSI is further transmuted into a 3D visualization cube comprehensive grasp of spatial and spectral aspects encompassing spectral, spatial, and Haralick features. The research concludes with severity detection, categorized as low, moderate, or high, employing a Gaussian Mixture Model (GMM) and K-means for visualization.

Particle-mediated elasticity/viscoelasticity imaging has potential to expand the elasticity imaging field, as it can provide accurate and local tissue elastic properties as well as density, Poisson’s ratio, and viscosity. Here, we investigated elasticity imaging based on the use of small particles located within the tissue and at the tissue interface exposed to a static and dynamic external load. First, we discuss elasticity/viscoelasticity imaging methods based on the use of particles (bubbles and rigid spheres) located within the tissue. Elasticity/viscoelasticity imaging techniques based on the use of particles (bubbles, rigid and soft spheres) located at the tissue interface are then presented. Based on new advances, we updated some of the models for the responses of the particles located within the tissue and at the tissue interface available in the literature. Finally, we compared the mathematical models for the particles located within the tissue and at the tissue interface and evaluated the elasticity/viscoelasticity imaging methods based on the use of small particles. Therefore, instead of the use of the term elasticity imaging, we suggest the use of the term viscoelasticity imaging.

In this paper, a relatively new hyper convolution spectra for characterization liquid, viscoelastic and solid samples is presented. Special attention is paid to the biophysical characterization of epithelial tissues and early detection of cancer of the skin, cervix, colon, and oral cavity. The method is based on the use of two types of white light, diffuse and polarized, from the same LED light sources. Based on the subtraction of the intensity values of these two lights and using the hyper convolution algorithm, the ratio of paired and unpaired electrons of tissue is obtained. This ratio correlates well with the state of the tissue: normal, irritating, precancerous, and cancerous. First, a proof-of-concept studies were performed, and later clinical studies on samples from one thousand two hundred fifteen people were performed. It showed that hyper Opto-Magnetic Imaging Spectroscopy (OMIS) can detect epithelial tissue cancers with an accuracy of 85-96%. Bearing in mind that the OMIS method also acquires the biophysical characteristics of the deeper skin layers (epidermis, basement membrane, dermis) by analysing convolution spectra of RGB channels of both diffuse and polarized white light, it is possible to apply this method in cosmetics (skin hydration, collagen, and elastin states, etc.). During OMIS applications, we noticed places where improvements could be made to increase method’s accuracy using advanced machine learning methodologies.

Breast cancer is the foremost common in women, and its early diagnosis will help treat and increase patients' survival. This review article aims to studies on recent findings of standard imaging techniques and their characteristics for breast cancer diagnosis and recent nanoparticles (NPs) which are used for breast cancer detection. Herein, The search was performed in the literature through scientific citation websites, including Google Scholar, PubMed, Scopus, and Web of Science until May 2023. A comprehensive study on different imaging modalities and NPs for breast cancer diagnosis is reviewed, and their successes, challenges, and limitations are discussed.

Coronavirus Disease 2019 (COVID-19) is the pandemic challenge of the last year. Cardiovascular involvement is one of the main characteristics of this disease. Due to endothelial damage, consequent phlogosis may increase a thrombosis risk. Cardiac injury may occur in different ways. However, an ischemic involvement of the cardiovascular system is rarely implied. In this regard, direct and indirect effects of COVID-19 are described. Nonetheless, the possible evaluation of the cardiovascular system may require different modalities. The cardiovascular evaluation may be different in emergency compared to critical care, requiring different tools for each setting. The aim of this review is to explore these modalities according to the different involvement of the cardiovascular system..

The aim of this research was to test recent developments in the use of Remotely Piloted Aircraft Systems or Unmanned Aerial Vehicles (UAV) to map pasture biomass yield and nutrient status, across a selected range of field sites throughout the rangelands of Queensland. Improved pasture management begins with an understanding of the state of the resource base, UAV based methods can potentially achieve this at improved spatial and temporal scales. This study developed predictive models of both pasture yield and pasture nutrient status. An automated pasture height surface modelling technique was developed, tested and used along with field site measurements of pasture yields, to predict further estimates across each field site. Both prior knowledge and automated predictive modelling techniques were employed to predict pasture yield and nutrition. Pasture height surface modelling was assessed against field measurements using a rising plate meter, results reported correlation coefficients (R2) ranging from 0.2 to 0.4 for both woodland and grassland field sites. Accuracy of the predictive modelling was determined from further field measurements of pasture yield and on average indicated an error of 0.8 t ha-1 in grasslands and 1.3 t ha-1 in mixed woodlands across both modelling approaches. Correlation analyses between measures of pasture quality, acid detergent fibre and crude protein (ADF, CP), and spectral reflectance data indicated the visible red (651 nm) and red-edge (759 nm) regions were highly correlated (ADF R2 = 0.9 and CP R2 = 0.5 mean values). These findings agreed with previous studies linking specific absorption features with grass chemical composition. These results conclude that the practical application of such techniques, to efficiently and accurately map pasture yield and quality, is possible at the field site scale, however further research is needed, in particular further field sampling of both yield and nutrient elements across such a diverse landscape, with the potential to scale up to a satellite platform for broader scale monitoring.

This review discusses a broad range of recent advances (2013-2017) of chemical imaging using electrochemical methods, with a particular focus on techniques that have been applied to study cellular processes, or techniques that show promise for use in this field in the future. Non-scanning techniques such as microelectrode arrays (MEAs) offer high time-resolution (< 10 ms) imaging, however at reduced spatial resolution. In contrast, scanning electrochemical probe microscopies (SEPMs) offer higher spatial resolution (as low as a few nm per pixel) imaging, with images collected typically over many minutes. Recent significant research efforts to improve the spatial resolution of SEPMs using nanoscale probes, and to improve the temporal resolution using fast scanning have resulted in movie (multiple frame) imaging with frame rates as low as a few seconds per image. Many SEPM techniques lack chemical specificity or have poor selectivity (defined by the choice of applied potential for redox-active species). This can be improved using multifunctional probes, ion-selective electrodes and tip-integrated biosensors, although additional effort may be required to preserve sensor performance after miniaturization of these probes. We discuss advances to the field of electrochemical imaging, and technological developments which are anticipated to extend the range of processes that can be studied. This includes imaging cellular processes with increased sensor selectivity and at much improved spatiotemporal resolution than has been previously customary.

Metandienone and methyltestosterone are orally active anabolic-androgenic steroids with a 17α-methyl structure that are prohibited in sports but are frequently detected in anti-doping analysis. After the previously reported detection of long-term metabolites with a 17ξ-hydroxymethyl-17ξ-methyl-18-nor-5ξ-androst-13-en-3ξ-ol structure in the chlorinated metandienone analog dehydrochloromethyltestosterone (“Oral Turinabol”), in this study we investigated the formation of similar metabolites of metandienone and 17α-methyltestosterone with a rearranged D-ring and a fully reduced A-ring. Using a semi-targeted approach including synthesis of reference compounds, two diastereomeric substances, viz. 17α-hydroxymethyl-17β-methyl-18-nor-5β-androst-13-en-3α-ol and its 5α-analog, were identified following an administration of methyltestosterone. In post-administration urines of metandienone, only the 5β-metabolite was detected. Additionally, 3α,5β-tetrahydro-epi-methyltestosterone was identified in the urines of both administrations besides the classical metabolites included in the screening procedures. Besides their applicability for anti-doping analysis, the results provide new insights on the metabolism of 17α-methyl steroids with respect to the order of reductions in the A-ring, the participation of different enzymes, and alterations of the D-ring.

Cell junction that is usually associated with dynamic cytoskeletons is essential for a wide range of cellular activities such as cell migration, cell communication, barrier function and signal transduction. Real-time observation of cell junction facilitates understanding of the mechanisms by which cell junction regulate relevant cellular activities. In this study, we examined the binding capacity of a modified tridecapeptide from Cx43 to cell junction protein ZO-1 and sought to create a fluorescent peptide that could be used to label cell junction. To introduce the fluorescent peptide into the cells, a cell-penetrating peptide was linked to the modified tridecapeptide and synthesized. The binding of the modified tridecapeptide was tested using pull down and immunoprecipitation assay. The ability of the peptide to label cell junction was assessed by adding it to fixed or cultured Caco-2 cells. Testing assay revealed that the Cx43-derived peptide can bind to ZO-1. Besides, the peptide was able to label cell junction of fixed cell, although no obvious cell junction labeling was observed clearly in living cells, probably due to the inadequate affinity. These results indicate that a peptide-based strategy for labeling cell junction may be feasible, and efforts to improve its affinity are warranted in the future.

The purpose of this study was to explore and develop high-resolution infrared thermal (HRIT) imaging for screening toddler’s fracture. A Toddler’s fracture is a common tibial fracture of children younger than 6 years old. Initial x-ray radiographs may not show the fracture and another x-ray during a follow-on visit is usually required. The study included 39 participants admitted to an emergency department with a suspected toddler’s fracture. X-ray confirmed 8 cases with a toddler’s fracture (20.5%). Infrared images of participants were recorded on their index visit, focusing on region-of-interests on the injured and the contralateral (uninjured) legs. The uninjured leg acted as a thermal reference. Nine statistical measures were extracted from the images: maximum, mini-mum, mean, standard deviation, median, mode, interquartile range, skewness, and kurtosis. Wilcoxon rank sum test indicated that maximum, mean, standard deviation, median, and inter quartile range temperature measures were significantly different (p<0.05) when comparing fractured and non-fractured legs. Principal component analysis of these measures highlighted distinct separation of toddler’s fracture and non-fracture cases. Similarly, plots of the statistical measures further confirmed clustering of toddler’s fracture cases. The study demonstrated that HRIT imaging can be a valuable tool for screening for toddler’s fracture.

Apurinic/apyrimidinic endonuclease 1 (APE1), also known as redox factor-1 (Ref-1), is a multifunctional protein which is widely existing in living organisms. It can specifically recognize and cleave the DNA in apurinic/apyrimidinic (AP) site in the base excision repair (BER) pathway, as well as regulate the expression of genes to activate some transcription factors. The abnormal ex-pression and disruptions in the biological functions of APE1 are linked to a number of diseases, including inflammation, immunodeficiency, and cancer. Hence, it is extremely desired to monitor the activity of APE1, acquiring a thorough understanding of the healing process of damaged DNA and making clinical diagnoses. Thanks to the advent of DNA nanotechnology, some nanodevices are used to image the activity of APE1 with great sensitivity and simplicity. In this review, we will summarize DNA nanotechnology-empowered fluorescence imaging in the past years for APE1 activity according to the types of DNA probe, which are classified into linear DNA probes, composite DNA nanomaterials and three-dimensional (3D) DNA nanostructures. We also highlight the future research directions in the field of APE1 activity imaging.

Among cross-sectional imaging modalities, computed tomography (CT) is more available and faster; however, magnetic resonance (MR) performs better in terms of sensitivity and specificity, due to its higher contrast resolution. The appearance of peritoneal deposits on CT and MR depends mainly on the primary tumour histology: in case of unknown primary tumour (3-5% of cases), their behaviour at imaging may provide insights on the tumour origin. The time-point of tumour evolution, previous or ongoing treatments and the peritoneal spaces where they occur, also play an important role in determining the appearance of peritoneal deposits. Thus, knowledge of peritoneal anatomy and fluid circulation is mandatory in detection and characterization of peritoneal deposits. Several benign and malignant conditions may show similar imaging features that overlap those of PC, making the differential diagnosis challenging. Clinical history, laboratory findings and previous imaging examinations must be considered to achieve the correct diagnosis.

This paper presents an overview of tomography and different tomographic imaging modalities. The goal of this paper is to provide an understanding of various imaging modalities; in particular, how the imaging is performed, working principles, and applications. It was not intended to provide the in-depth mathematical principles of these imaging modalities, rather this paper focuses on providing the knowledge in an easy-to-grasp manner for the readers' benefit. Imaging modalities are categorized based on the physics behind image generation. First, the paper explains the general tomography principle. Then explains Ultrasound Imaging, Electrical Impedance Tomography, Computed Tomography, Magnetic Resonance Imaging (MRI), Photoacoustic Tomography (PAT), and Positron Emission Tomography (PET). In the end, the paper provides the fundamentals and review of two relatively new imagining modalities, Diffuse Optical Tomography (DOT) and functional Near-infrared Spectroscopy (fNIRS).

Over recent years, the importance of patent literature has become more recognized in the academic setting. In the context of artificial intelligence, deep learning, and data sciences, patents are relevant to not only industry but also academe and other communities. In this article, we focus on deep tomographic imaging and perform a preliminary landscape analysis of the related patent literature. Our search tool is PatSeer . Our patent bibliometric data is summarized in various figures and tables. In particular, we qualitatively analyze key deep tomographic patent literature.

Quantitative differential phase contrast (qDPC) imaging has become an important method of optical measurement and life science research in microscopy because of its high reconstruction resolution and non-invasive, high-contrast and quantitative imaging of biological samples. Despite the continuous development of the principle and algorithm, the frame rate of the existing qDPC algorithm is still much lower than that of camera acquisition, so it is hardly applied to real-time image the fast-moving biological samples. In this paper, based on color-coded multiplexing strategy, a compact real-time quantitative phase imaging system is designed to realize multi-mode imaging. The system employs a programmable LED array to illuminate directly, and the phase reconstruction algorithm is deployed in the graphics processing unit (GPU) of the laptop to accelerate the calculation. The system can achieve high-speed quantitative phase imaging of non-stained biological samples, and the frame rate can reach 60fps. The device has the advantages of compact structure, low cost and portability. Thus, it is suitable for mobile medical applications.

Molecular imaging modalities are used for different type of cancers detection and diagnosis. In recent few years, there has been an increased focus on developing novel nanoparticles as new imaging contrast agents for early detection of cancer. The aim of this review article is to summarize molecular imaging technologies accompanying with using nanoparticles to improve potential imaging for cancer detection and hence valuable therapy in the future. Nanoprobes are rapidly becoming potentially transformative tools on cancer diagnostics for a wide range of imaging modalities such as CT, MRI, SPECT, PET, Ultrasound and Optical imaging. The study results seen in the recent literature are provided and discussed the diagnostic performance of imaging modalities for cancer diagnosis and their future directions. With knowledge of the correlation between the application of nanoparticles and molecular imaging modalities and with the development of targeted contrast agents or nanoprobes, they may provide better cancer diagnosis in the future.

In this paper, a new millimeter wave 3D imaging radar is proposed. The user just needs to move the radar along a circular track, a high resolution 3D imaging can be generated. The proposed radar uses the movement of itself to synthesize a large aperture in both the azimuth and elevation directions. It can utilize inverse Radon transform to resolve 3D imaging. To improve the sensing result, compressed sensing approach is further investigated. The simulation and experimental result further illustrated the design. Because a single transceiver circuit is needed, a light, affordable and high resolution 3D mmWave imaging radar is illustrated in the paper.

The landscape of medical education has witnessed significant transformations over the past decades, particularly with the advent of active teaching methodologies. However, despite these advancements, the traditional theoretical assessment methods have remained largely unchanged. This lack of evolution in assessment systems poses a challenge, as it is crucial for assessment methods to evolve in tandem with teaching approaches to ensure a comprehensive and effective learning process in medical education. This paper reviews the integration and effectiveness of open-book examinations (OBEs) in medical education, reflecting their growing significance. An integrative review of the literature was conducted, drawing from a range of relevant publications over the last decade, sourced from databases such as PubMed, Web of Science, Scopus, and ERIC. The inclusion criteria focused on full-text articles in English, with search terms including "medicine," "assessment," "open book examination," "open book exam," and "open book assessment," combined using Boolean operators. Thirteen publications were selected and critically appraised using The Critical Appraisal Skills Program checklist. The analysis identified three primary thematic categories: ' Teaching Strategy for Pandemic and Challenging Conditions,” Tool of Learning & Educational Impact” and “Operational Challenges & Future Directions”. These themes were explored to understand the role and impact of OBEs in medical education. The findings indicate that open-book examinations are a crucial component in the evolving landscape of medical education. While certain reservations remain, OBEs have shown significant potential in fostering critical thinking, argumentation skills, and lifelong learning among medical students. They reflect the ongoing evolution of knowledge in the medical field and contribute to the development of professionals’ adept at navigating and applying complex information. Further research is recommended to solidify these findings and to expand the understanding of OBEs in medical education.

Background and aim: To explore the discriminant accuracy of Cytokeratin 18 (CK18, including M65 and M30 forms) for an elevated fatty liver index (FLI) as a validated proxy of Non-Alcoholic Fatty Liver Disease (NAFLD), and cardiovascular disease (CVD) risk in the general population. Methods: Both serum CK18 forms were measured using a commercial immunoassay in randomly selected samples from 312 participants of the PREVEND general population cohort. FLI ≥60 was used to indicate NAFLD. Framingham Risk Score (FRS) and the SCORE2 were used to estimate the 10-year risk of CVD. Receiver Operating Characteristic (ROC) curve, linear/logistic regression models and Spearman's correlations were used. Results: Intricate associations were found between CK18, FLI and CVD risk scores. While M30 was the only independent predictor of FLI≥60, M65 discriminated best NAFLD individuals at very-high 10-years CVD risk according to SCORE2 (AUC:0.71; p=0.001). Values above the predefined manufacturer cut-off (400 U/l), were associated with an independent 5-fold increased risk (adjusted odds ratio: 5.44, p=0.01), with negative predictive value of 93%. Conclusions: Confirming that NAFLD is associated with an increased CVD risk, our results point to CK18 M65 as a candidate biomarker to identify NAFLD individuals at low CVD risk in European general population.

Several studies with kaempferol (KP) and linearolactone (LL) have shown antiparasitic activities. However, the toxicity of treat-ments with both active principles is unknown. Therefore, this study aimed to evaluate the toxicological effects of treatments with KP and LL on the amoebic liver abscess (ALA) model in M. auratus administered intraperitoneally (i.p.). For this, ALA in-duction was carried out in male hamsters with 1.5 x105 E. histolytica trophozoites inoculated in the left hepatic lobe. The lesion evolved for four days and the i.p. of the treatments with KP (5 mg/kg body weight/day) and LL (10 mg/kg body weight/day) was carried out for four consecutive days. For histopathological evaluation, NMR studies, paraclinical analysis, and necropsy were performed. The results revealed that the inhibition of ALA by KP and LL were similar to that metronidazole (MTZ). Biochemical parameters revealed hepatic and renal alterations in all treatment groups, mainly for KP (AST and BUN). The lesions found in the organs were those that are directly linked to the pathology. In conclusion, KP and LL decrease ALA development but have few toxicological effects. Both compounds combined with MTZ could be therapeutic alternatives for amoebiasis caused by E. histolytica.

The chiral optical Tamm state (COTS) is a special localized state at the interface of a handedness-preserving mirror and a structurally chiral medium such as a cholesteric liquid crystal or a chiral sculptured thin film. The spectral behavior of COTS, observed as reflection resonances, is described by the temporal coupled-mode theory. Mode coupling is different for two circular light polarizations because COTS has a helix structure replicating that of the cholesteric. The mode coupling for co-handed circularly polarized light exponentially attenuates with the cholesteric layer thickness since the COTS frequency falls into the stop band. Cross-handed circularly polarized light freely goes through the cholesteric layer and can excite COTS when reflected from the handedness-preserving mirror. The coupling in this case is proportional to anisotropy of the cholesteric and theoretically it is only anisotropy of magnetic permittivity that can ultimately cancel this coupling. These two couplings being equal results in a polarization crossover (the Kopp--Genack effect) for which a linear polarization is optimal to excite COTS. The corresponding cholesteric thickness and scattering matrix for COTS are generally described by simple expressions.

This work communicates the connection of measured shadowgraphs from optically induced air breakdown with emission spectroscopy in selected gas mixtures. Laser-induced optical breakdown is generated using 850 mJ and 170 mJ, 6-ns pulses at a wavelength of 1064 nm, the shadowgraphs are recorded using time-delayed 5-ns pulses at a wavelength of 532 nm and a digital camera, and emission spectra are recorded for typically a dozen of discrete time-delays from optical breakdown by employing an intensified charge-coupled device. The symmetry of the breakdown event can be viewed as close-to spherical symmetry for time-delays of several 100 ns. Spectroscopic analysis explores well-above hypersonic expansion dynamics using primarily the diatomic molecule cyanide and atomic hydrogen emission spectroscopy. Analysis of the air breakdown and selected gas breakdown events permits the use of Abel inversion for inference of the expanding species distribution. Typically, species are prevalent at higher density near the hypersonically expanding shockwave, measured by tracing cyanide and a specific carbon atomic line. Overall, recorded air breakdown shadowgraphs are indicative of laser-plasma expansion in selected gas mixtures, and optical spectroscopy delivers analytical insight into plasma expansion phenomena.

Introduction: An epidemic of Coronavirus Disease 2019 (COVID-19) begun in December 2019 in China, causing a Public Health Emergency of International Concern. Among raised questions, clinical, laboratory, and imaging features have been partially characterized in some observational studies. No systematic reviews have been published on this matter. Methods: We performed a systematic literature review with meta-analysis, using three databases to assess clinical, laboratory, imaging features, and outcomes of COVID-19 confirmed cases. Observational studies, and also case reports, were included and analyzed separately. We performed a random-effects model meta-analysis to calculate the pooled prevalence and 95% confidence interval (95%CI). Results: 660 articles were retrieved (1/1/2020-2/23/2020). After screening by abstract/title, 27 articles were selected for full-text assessment. Of them, 19 were finally included for qualitative and quantitative analyses. Additionally, 39 case report articles were included and analyzed separately. For 656 patients, fever (88.7%, 95%CI 84.5-92.9%), cough (57.6%, 40.8-74.4%) and dyspnea (45.6%, 10.9-80.4%) were the most prevalent manifestations. Among the patients, 20.3% (95%CI 10.0-30.6%) required intensive care unit (ICU), with 32.8% presenting acute respiratory distress syndrome (ARDS) (95%CI 13.7-51.8), 6.2% (95%CI 3.1-9.3) with shock and 13.9% (95%CI 6.2-21.5%) of hospitalized patients with fatal outcomes (case fatality rate, CFR).Conclusion: COVID-19 brings a huge burden to healthcare facilities, especially in patients with comorbidities. ICU was required for approximately 20% of polymorbid, COVID-19 infected patients and this group was associated with a CFR of over 13%. As this virus spreads globally, countries need to urgently prepare human resources, infrastructure, and facilities to treat severe COVID-19.

The agricultural industry relies on physical fences to manage livestock. However, physical fences present some practical, financial, and ecological problems, that partly may be solved by virtual fencing. However, it is necessary for the livestock to be adapted to virtual fencing. This study aims to identify if adaptation to virtual fence can be improved through social facilitation between experienced cattle and the remaining herd. Moreover, which of the two different learning processes, a gradual or instant introduction to virtual fence is the most effective in associating warnings with impulses. Three pastures containing Angus (Bos taurus) will be used to examine these investigations; A, B and C. All investigations are conducted on the Danish Island of Fanø. Three methods of learning process were used, one gradual and two instant introductions to the virtual fence. The investigations had varying amounts of experienced cattle. Impulses and warnings were recorded during a learning period and the following observation period. To quantify if the cattle adapt to the warnings, impulses per warning are used. There was no evidence of improvement with the presence of experienced cattle for any pastures, indicating no social facilitation. Gradual introduction was found to be more beneficial than instant introduction. More standardized tests are necessary to discover the full effect of experienced cattle.

Toxoplasmosis is a zoonosis of warm-blooded animals, affecting also humans, caused by Toxo-plasma gondii, an obligate intracellular parasite with a complex biological cycle. Toxoplasmosis is considered a re-emerging zoonosis and an important public health threat, also for the absence, up to now, of efficient vaccines and preventive measures. Sources of transmission to humans are environmental or food-borne, mainly through the consumption of raw and undercooked meat, predominantly of Sus scrofa, considered highly susceptible to T. gondii. Mainly in the last dec-ades, an effective strategy to counter animal infectious diseases was based on the discovery of resistance immuno-genetic markers, possibly to be used for association studies between geno-typic and phenotypic traits and consequently in Marker Assisted Selection. Until now, this gen-otyping approach has never been adopted for T. gondii infection, so this study aimed, for the first time, to fill this gap. In particular, pigs, reared in different farms of Central Italy, were serologically characterized by an ELISA assay performed on diaphragm meat juice. Out of 179 tested animals, 98 resulted seropositive (54.74%), 57 seronegative (31.84%) and 24 doubtful (10.6%), underlining a possible re-emerging diffusion of this protozoan in the investigated areas. Atten-tion was firstly focused on IL-18 gene, encoding for a pro-inflammatory cytokine that plays a key role starting from the upstream steps of the immunity pathway towards T. gondii. A RT-PCR assay followed by Sanger sequencing of IL-18 cDNA was de novo developed. For this interleukin, at this stage, genetic analysis has not highlighted significant polymorphic variations compared to the reference sequence, except for a seropositive animal. However, the outcomes of this pre-liminary innovative study will be investigated in depth analyzing other relevant genetic re-gions and other target genes.

This study introduces a compact Raman spectrometer with a 1064 nm excitation laser coupled with a fiber probe and an inexpensive motorized stage, offering a promising alternative to widely used Raman imaging instruments with 785 nm excitation lasers. The benefits of 1064 nm excitation for biomedical applications include further suppression of fluorescence background and deeper tissue penetration. The performance of the 1064 nm instrument in detecting cancer in human bladder resectates is demonstrated. Raman images with 1064 nm excitation were collected ex vivo from 10 human tumor and non-tumor bladder specimens and the results are compared to previously published Raman images with 785 nm excitation. K-Means cluster (KMC) analysis is used after pre-processing to identify Raman signatures of control, tumor, necrosis, and lipid-rich tissues. Hierarchical cluster analysis (HCA) groups the KMC centroids of all specimens as input. The tools for data processing and hyperspectral analysis were compiled in an open source Python library called SpectraMap (SpMap). In conclusion, the 1064 nm Raman system can differentiate between tumor and non-tumor bladder tissues in a similar way to 785 nm Raman spectroscopy. These findings hold promise for future clinical hyperspectral imaging.

Proper blood-brain barrier (BBB) function is essential to maintain homeostasis keeping the central nervous system healthy. Disruption of the BBB has been described in nearly all neurological disease and injury contexts. Given the various physical and metabolic roles of the BBB and gliovascular unit (GVU), dysfunction should be assessed across multiple levels to pinpoint the exact nature of the impairment. Here we describe imaging techniques for evaluating various aspects of BBB and GVU integrity and function, tailored for use in mouse models with protocols for quantitative image analysis. These imaging techniques complement classical dye tracer experiments and reveal underlying molecular causes of BBB dysfunction.

The review considers physics and some applications of a new approach that promises to be a breakthrough in efficiency and instrumentation of various methods for nondestructive testing (NDT) of composites. The approach is based on frequency-selective properties of defects which fall into resonance (Local Defect Resonance (LDR)) at certain frequencies. An activation of LDR enables to route the input acoustic energy directly to the defect that dramatically increases its vibration amplitude and thus facilitates defect-selective imaging, rises efficiencies of various derivative acoustic NDT methods (nonlinear, acousto-thermal) and enables to develop some new methodologies, like Resonant Air-Coupled Emission (RACE), machine and remote imaging.

Due to the adverse effect of prolonged drought stress on plants, accurate detection is essential for water use efficiency and maintaining productivity. Hyperspectral imaging is frequently used for non-invasive plant phenotyping, allowing for the long-term monitoring of crop health due to its sensitivity to subtle changes in leaf constituents. The broad spectrum of hyperspectral data enables the development of multiple vegetation indices (Vis) derived from the different spectral regions to estimate plant biophysical and biochemical traits. However, the known VIs often do not generalize well and perform poorly for multiple plant stresses. This study proposes new VIs combined with machine learning models to identify drought stress in wheat species under different nitrogen (N) levels. A wheat experiment was set up in the glasshouse with four treatments: well-watered high-N (WWHN), well-watered low-N (WWLN), drought-stress high N and drought-stress low-N. In addition to ensuring that plants were watered according to the experiment design, photosynthetic rate (Pn) and stomatal conductance (gs) were taken regularly, serving as the ground truth data for this study. Sensitive spectral features were selected using a custom-designed ensemble modelling technique. New drought VIs are proposed using different combinations of the selected features. Three classification models (support vector machines, random forest and deep neural network) were developed and trained using four sets of data: known VIs, proposed VIs, combined VIs (from the known and proposed VIs) and PCA-transformed features (over the whole spectral data). From the results, the proposed VIs outperformed the known VIs, yielding &gt; 0.94 accuracies for all three models, and the performance improved when they were trained with the combined VIs. The combined VIs were used to train three regression models to predict the stomatal conductances and photosynthetic rates of plants. The random forest regression model performed best, suggesting that it could be used as a stand-alone tool to forecast gs and Pn and track drought stress in wheat.

This study focuses on examining various approaches for Tensor Decompositions (TDs) and their potential applications in satellite imaging (SI) and deep learning (DL). The research highlights how these decompositions can contribute to the advancement of SI and DL, providing valuable insights for future utilization of TDs in research. It explores how these techniques contribute to the advancement of SI and DL methods, providing insights into their potential applications and suggesting future research directions. The study aims to enhance the use of TDs techniques to further advance research efforts in these fields. More importantly, the current investigation offers a thorough analysis of the potential advantages and reasons for employing TDs techniques in different domains, including satellite imaging and deep learning. The aim is to enhance research outcomes by utilizing TDs. The review also identifies unresolved issues and proposes future directions for further investigation in this field. Fundamentally, these proposed open problems will open new grounds to the research community to articulate, innovate, and provide more real-life applications to improve the current state of the art by delving into a wider vision for a higher-level performance of both satellite imaging (SI) and deep learning (DL). Looking at the bigger scenario, this also suggests that TDs could be potentially employed to revolutionize existing machine learning technologies as well as the current space AI industry.

The moisture content of maize seed is an important indicator for evaluating seed quality and a fundamental item in grain testing. The experiment used direct drying method to measure the moisture content of 80 different varieties of maize samples, and captured their images using a hyperspectral imaging (HSI) system in the spectral range of 1100~2498nm. By comparing seven spectral preprocessing methods, the PLSR model established after Normalize pretreatment had the best effect. The characteristic wavelengths were selected by Successive Projections Algorithm (SPA), Competitive Adaptive Reweighted Sampling (CARS) and Uninformative Variable Elimination (UVE). Twelve prediction models were established for full band spectra and characteristic wavelengths based on PLSR, PCR and SVM. By comparing the performance of the prediction models, it was found the Normalize-SPA-PLSR algorithm was optimized. The values of RC2 and RP2 in the model were higher, which were 0.9936 and 0.9933, respectively, while the values of RMSEP and RMSECV were lower, which were 0.0357 and 0.0380, respectively. The Normalize-SPA-PLSR model was used as a visual prediction model for moisture content of maize seed, the 20 maize varieties in the prediction set were visualized to obtain visualized color images of moisture content. The color differences between different moisture content images were significant. The result indicated that hyperspectral imaging could accurately, rapidly, and non-destructive predict moisture content of maize seed, which provided technical support for moisture content detection in the process of maize harvest, storage and processing.

Our aim was to compare the inter-rater agreement of Transvaginal ultrasonography (TVS) with Magnetic Resonance Imaging (MRI) regarding diagnosing adenomyosis and for various predefined imaging features of adenomyosis in the same set of women. MRIs were assessed by four experienced radiologists and 2D TVS videoclips and 3D ultrasound volumes were assessed by five experienced sonographers. Each rater subjectively evaluated the presence or absence of adenomyosis, assessed various imaging. Fleiss kappa (κ) was used to reflect inter-rater agreement for categorical data and the Intraclass correlation coefficient (ICC) to reflect the reliability of quantitative data. Agreement between raters for diagnosing adenomyosis was higher for TVS than for MRI (κ =0.42 vs.0.28). MRI had a higher inter-rater agreement in assessing wall asymmetry irregular Junctional Zone (JZ) presence of myometrial cysts, while TVU had a better agreement for globular shape. MRI showed a moderate-good reliability for measuring the JZ (ICC=0.57-0.82). For TVS, JZ was unmeasurable in &gt; 50% of cases and the remaining cases had a low reliability (ICC=-0.31-0.08). We found that Inter-rater agreement for diagnosing adenomyosis was higher for TVS than for MRI, despite that MRI showed a higher inter-rater agreement in most specific features. Measurements of JZ in the coronal plane with 3D TVS were unreliable and thus unlikely to be useful for diagnosing adenomyosis.

Functional Data Analysis (FDA) is a relatively new field of statistics dealing with data expressed in the form of functions. FDA methodologies can be easily extended to the study of imaging data, an application proposed in Wang et al. (2020), where the authors settle the mathematical groundwork and properties of the proposed estimators. This methodology allows for the estimation of mean functions and simultaneous confidence corridors (SCC), also known as simultaneous confidence bands, for imaging data and for the difference between two groups of images. This is especially relevant for the field of medical imaging, as one of the most extended research setups consists on the comparison between two groups of images, a pathological set against a control set. FDA applied to medical imaging presents at least two advantages compared to previous methodologies: it avoids loss of information in complex data structures and avoids the multiple comparison problem arising from traditional pixel-to-pixel comparisons. Nonetheless, computing times for this technique have only been explored in reduced and simulated setups (Arias-López et al., 2021). In the present article, we apply this procedure to a practical case with data extracted from open neuroimaging databases and then measure computing times for the construction of Delaunay triangulations, and for the computation of mean function and SCC for one-group and two-group approaches. The results suggest that previous researcher has been too conservative in its parameter selection and that computing times for this methodology are reasonable, confirming that this method should be further studied and applied to the field of medical imaging.

Model-based image reconstruction has brought improvements in terms of contrast and spatial resolution to imaging applications such as magnetic resonance imaging and emission computed tomography. However, their use for pulse-echo techniques like ultrasound imaging is limited by the fact that model-based algorithms assume a finite grid of possible locations of scatterers in a medium -- which does not reflect the continuous nature of real world objects and creates a problem known as off-grid deviation. To cope with this problem, we present a method of dictionary expansion and constrained reconstruction that approximates the continuous manifold of all possible scatterer locations within a region of interest. The expanded dictionary is created using a highly coherent sampling of the region of interest, followed by a rank reduction procedure based on a truncated singular value decomposition. We develop a greedy algorithm, based on the Orthogonal Matching Pursuit (OMP), that uses a correlation-based non-convex constraint set that allows for the division of the region of interest into cells of any size. To evaluate the performance of the method, we present results of 2-dimensional ultrasound image reconstructions with simulated data in a nondestructive testing application. Our method succeeds in the reconstructions of sparse images from noisy measurements, providing higher accuracy than previous approaches based on regular discrete models.

Age-related macular degeneration is one of the most common causes of blindness, and the incidence exhibits profound racial bias, occurring most frequently in Caucasians. A primary cell type affected in the disease is the retinal pigment epithelium, but the etiology is unclear. The end 10% of the photoreceptor outer segments are shed each day, and the underlying retinal pigment epithelium engulfs, digests, and recycles molecules back to the sensory retina. In previous work, we showed that GPR143 signaling in response to L-DOPA may be effective in the prevention or delay of age-related macular degeneration. In this study, we explore a novel potential effector of GPR143 signaling, that of outer segment uptake and digestion. Using isolated outer segments, labelled with a pH-sensitive marker to fluoresce in lysosomes, we show that GPR143 signaling does not impact outer segment uptake, but does have a significant effect on subsequent degradation. Interestingly, GPR143 signaling did not affect the digestive capacity of the cells, marked by total proteolytic capacity and cathepsin D activity. Rather, our data suggest GPR143 improved endosomal trafficking efficiency of the phagocytosed outer segments to the lysosome. This result is similar to the effect we previously reported for GPR143 on exosome release from the endosomal compartment. Our data illustrate that GPR143 is active in endosomal traffic A single paragraph of about 200 words maximum. For research articles, abstracts should give a pertinent overview of the work. We strongly encourage authors to use the following style of structured abstracts, but without headings: (1) Background: Place the question addressed in a broad context and highlight the purpose of the study; (2) Methods: briefly describe the main methods or treatments applied; (3) Results: summarize the article’s main findings; (4) Conclusions: indicate the main conclusions or interpretations. The abstract should be an objective representation of the article and it must not contain results that are not presented and substantiated in the main text and should not exaggerate the main conclusions.

Urinary tract infections (UTIs) are among the most common bacterial infections in community and hospital settings. Infections of the urinary system can range from pyelonephritis to urethritis. Acute renal infections encompass entities such as acute pyelonephritis, acute focal bacterial nephritis, renal and perinephric abscesses, emphysematous pyelonephritis, and pyonephrosis,while xanthogranulomatous pyelonephritis is a chronic granulomatous inflammatory condition that affects the kidneys. The diagnosis of UTIs predominantly relies on clinical assessment and confirmation through abnormal laboratory results. Therefore, routine medical imaging is typically reserved for complicated cases, aiming to identify contributing factors such as renal calculi, determine the type of infection, and evaluate the extent of the infection and its associated complications. Furthermore, imaging has become crucial for radiologists during interventional procedures in the treatment of pyonephrosis and renal abscesses. Traditional imaging tools, like abdominal X-rays, are vital for identifying renal calculi and gas shadows in emphysematous pyelonephritis, while ultrasonography emerges as an excellent modality for assessing urinary infections in emergency scenarios, pregnancy, and paediatric cases. Contrast-enhanced computed tomography (CECT) or non-contrast computed tomography (NCCT) is the imaging method of choice in the most complex situations, allowing for precise assessment of the disease burden. Current MRI sequences yield promising results in specific scenarios, such as pregnancy and paediatric subjects, where minimising radiation exposure is a concern. This article focuses on elucidating the essential radiological modalities and their distinctive features in the context of renal infections, offering valuable guidance to microbiologists and physicians.

In this work, we present a transceiver front-end in SiGe BiCMOS technology that can provide an ultra-wide bandwidth of 100 GHz at millimeter-wave frequencies. The front-end employs a novel configuration for low-loss distribution of broadband generated pulses as well as coherent spatial combining of received pulses. This leads to the realization of a fully integrated ultra-high-resolution imaging chip for biomedical applications. We realized an ultra-wide imaging bandwidth of 100 GHz by the integration of two adjacent, disjointed frequency sub-bands of 10–50 GHz and 50–110 GHz respectively. The transceiver front-end is capable of both transmit (TX) and receive (RX) operations. This is a key building-block for a scalable system in which a unit cell is repeated in the X and Y directions resulting in less power and area consumption. The imaging elements were designed and fabricated in Global Foundry 130-nm SiGe 8XP BiCMOS process technology.

Imaging-based biomarkers have developed as an effective tool in neurology, providing vital understandings of the structural, functional, and molecular changes associated with neurological disorders. Imaging techniques such as magnetic resonance imaging (MRI), positron emission tomography (PET), single-photon emission computed tomography (SPECT), and computed tomography (CT) have been widely employed to record disease-related alterations in the brain. These techniques provide a wide range of biomarkers, such as functional connectivity patterns, volumetric measurements, molecular imaging agents, and perfusion parameters, enabling the correct identification of neurological disorders. These biomarkers have proven useful in early diagnosis, disease progression tracking, therapy response prediction, and surgical planning. This review emphasizes the various obstacles and limitations that are associated with imaging-based biomarkers. Technical constraints, standardization obstacles, ethical concerns, regulatory challenges, and cost-effectiveness concerns all offer substantial barriers to wider use. It is vital to overcome these challenges if imaging biomarkers are to be successfully integrated into routine clinical practice. Imaging technology advancements like high-resolution imaging, multimodal imaging, and artificial intelligence-based analysis hold immense promise for imaging-based biomarkers in the future. While more study and standardization are needed, their ongoing development and integration into clinical practice have the potential to revolutionize the diagnosis, treatment, and management of neurological disorders, resulting in better patient care and outcomes.

The Compact Midwave Imaging System (CMIS) is a wide field of view, multi-angle, multi-spectral pushframe imager that relies on the forward motion of the satellite to create a two-dimensional (2D) image swath. An airborne demonstration of CMIS was successfully completed in January-February 2021 on the NASA Langley Research Center Gulfstream III. The primary objective of the four-flight campaign was to demonstrate the capability of this unique instrument to perform stereo observations of clouds and other particulates (e.g. smoke) in the atmosphere. It is shown that the midwave infrared (MWIR) spectral bands of CMIS provide a unique 24/7 capability with high resolution for accurate stereo sensing. The instrument relies on new focal plane array (FPA) technology, which provides excellent sensitivity at much warmer detector temperatures than traditional technologies. This capability enabled a compact, low-cost design that can provide atmospheric motion vectors and cloud heights to support requirements for atmospheric winds in the 2017-2027 Earth Science Decadal Survey. Applications include day/night observations of the planetary boundary layer, severe weather, and wildfires. A comparison with current space-based earth science instruments demonstrates that the SWIR/MWIR multi-spectral capability of CMIS is competitive with larger, more expensive instrumentation. Imagery obtained over a controlled burn and operating nuclear power plant demonstrated the sensitivity of the instrument to temperature variations. The system relies on a mature stereoscopic imaging technique applied to the same scene from two independent platforms to unambiguously retrieve atmospheric motion vectors (AMVs) with accurate height assignment. This capability has been successfully applied to geostationary and low-earth orbit satellites to achieve excellent accuracy. When applied to a ground-point validation case, the accuracy for the CMIS aircraft observations was 20 m and 0.3 m/s for cloud heights and motion vectors, respectively. This result was confirmed by a detailed error analysis with analytical and covariance models. The results for CMIS cases with underflights of Aeolus, CALIPSO and Aqua provided a good validation of expected accuracies. The paper also showed the feasibility of accommodating CMIS on CubeSats to enable multiple instruments to be flown in a leader-follower mode.

Background: global longitudinal strain (GLS) measures myocardial deformation and is a sensitive modality for detecting subclinical myocardial dysfunction and predicting cardiac outcomes. The accuracy of speckle-tracking echocardiography (STE) is dependent on temporal resolution. A novel software enables relatively high frame rate (Hi-FR) (~200 fps) echocardiographic images acquisition which empowers us to investigate the impact of Hi-FR imaging on GLS analysis. The goal of this pilot study was to demonstrate the feasibility of Hi-FR for STE. Methods: In this prospective study, we acquired echocardiographic images using clinical scanners on patients with normal left ventricular systolic function using Hi-FR and conventional frame rate (Reg-FR) (~50 FPS). GLS values were evaluated on apical 4-, 2- and 3-chamber images acquired in both Hi-FR and Reg-FR. Inter-observer and intra-observer variabilities were assessed in Hi-FR and Reg-FR. Results: There were 143 resting echocardiograms with normal LVEF included in this study. The frame rate of Hi-FR was 190 ± 25 and Reg-FR was 50 ± 3, and the heart rate was 71 ± 13. Strain values measured in Hi-FR were significantly higher than those measured in Reg-FR (all p < 0.001). Inter-observer and intra-observer correlations were strong in both Hi-FR and Reg-FR. Conclusions: We demonstrated that strain values were significantly higher using Hi-FR when compared with Reg-FR in patients with normal LVEF. It is plausible that higher temporal resolution enabled the measurement of myocardial strain at desired time point. The result of this study may inform clinical adoption of the novel technology. Further investigations are necessary to evaluate the value of Hi-FR to assess myocardial strain in stress echocardiography in the setting of tachycardia.

Magnetic Particle Imaging (MPI) is a new imaging modality that sensitively and specifically detects superparamagnetic iron oxide nanoparticles (SPIONs). Many labs have been developing cellular magnetic resonance imaging (MRI) tools using both SPIONs and fluorine-19 (19F)-based contrast agents for numerous important applications, including tracking of immune and stem cells used for cellular therapies. SPION-based MRI cell tracking has very high sensitivity, but low specificity. SPIONs produce negative contrast in MRI, or signal voids. SPIO is not directly detected by MRI, but indirectly through its relaxation effects on protons, therefore, it is not possible to reliably quantify the local tissue concentration of SPION particles and cell number cannot be determined. 19F based cell tracking uses perfluorocarbons (PFC) to label cells. The number of 19F atoms can be directly measured from 19F MR images and related to cell number. 19F MRI has high specificity, but low sensitivity. MPI cell tracking displays great potential for overcoming the challenges of MRI-based cell tracking allowing for both high cellular sensitivity and high specificity and quantification of SPIO labeled cell number. In this paper we describe nanoparticle and MPI system factors that influence MPI sensitivity and resolution, quantification methods and give our perspective on testing and applying MPI for cell tracking.

Imaging lidars are one of the hottest topics in the optronics industry. The need to sense the surroundings of every autonomous vehicle has pushed forward a career to decide the final solution to be implemented. The diversity of state-of-the art approaches to the solution brings, however, a large uncertainty towards such decision. This results often in contradictory claims from different manufacturers and developers. Within this paper we intend to provide an introductory overview of the technology linked to imaging lidars for autonomous vehicles. We start with the main single-point measurement principles, and then present the different imaging strategies implemented 8 in the different solutions. An overview of the main components most frequently used in practice is also presented. Finally, a brief section on pending issues for lidar development has been included, 10 in order to discuss some of the problems which still need to be solved before an efficient final implementation.Beyond this introduction, the reader is provided with a detailed bibliography containing both relevant books and state of the art papers.

A focal plane array (FPA) detector was used for hyperspectral imaging in the infrared (IR) spectral region using thermal and synchrotron light sources. FPA Fourier-transform IR (FTIR) imaging microspectroscopy will be able to monitor real time changes at specific absorption bands when combined with high brightness synchrotron source. In this study, several types of samples with unique structural motifs were selected and used for assessing the capability of the FPA-FTIR imaging technique. It was shown that the time required for polariscopy at IR wavelengths can be substantially reduced by the FPA-FTIR imaging approach. By using natural and laser fabricated polymers with sub-wavelength features, alignment of absorbing molecular dipoles was revealed as well as higher order patterns (laser fabricated structures). Micro-spectroscopy of absorber orientation reveals alignment patterns even when they are not spatially resolved.

We present a tutorial to realize a multidimensional fitting procedure capable of extracting all the relevant information contained in a sequence of charged particle images acquired as a function of time in femtosecond pump-probe experiments. The images are reproduced using a 3D fitting method, which provides the velocity (or center-of-mass kinetic energy) and angular distributions contained in the images and their time evolution. A detailed example of the method is shown through the analysis of the time-resolved predissociation dynamics of CH₃I on the B-band origin [Gitzinger et al., J. Chem. Phys. 133, 234313 (2010)]. We show that the multidimensional approach is essential for the analysis of complex images that contain several overlapping contributions where reduced dimensionality analyses cannot provide a reliable description of the features present in the image sequence. This methodology can be generalized to many types of multidimensional data analysis.

1) Background: Ultrasound-based strain imaging is now available in several ultrasound (US) scanners. Strain ratio (SR) can be used to quantify strain recorded simultaneously in two different user-selected areas, ideally exposed to the same amount of stress. The aim of this study was to evaluate SR variability when assessed in an in-vitro setup with a tissue-mimicking phantom, on resected tissue samples and in live tissue scanning with endoscopic applications. 2) Material and methods: Retrospective analysis of SR for quantification of elastic contrasts in a tissue-mimicking phantom containing four homogenous inclusions, in 38 resected bowel wall lesions and in 48 focal pancreatic lesions examined in vivo. Median SR and the inter-quartile range (IQR) was calculated on all external and endoscopic US-applications. The IQR/median provides a measure of the SR variability focusing on the two percentiles of the data closest to the median value. 3) Results: The overall variability of SR was lowest in a tissue-mimicking phantom (mean QR/median SR: 0.07). In resected bowel wall lesions representing adenomas, adenocarcinomas or Crohn lesions, the variability increased (mean IQR/Median: 0.62). During an endoscopic examination of focal pancreatic lesions in vivo, the variability increased further (mean IQR/Median: 2.04). 4) Conclusion: SR variability increased when assessed on different targets with growing heterogeneity and biological variability as one moved from homogeneous media to live tissues and endoscopic application. This may indicate a limitation for the accuracy SR evaluation in clinical applications.

The interest in virtual fencing, as opposed to traditional physical barriers, has increased since it makes it easier to move the boundaries of animal enclosures for agricultural and rewilding purposes. Despite this, the implementation of virtual fence systems, such as the Nofence© system, requires large financial investments. The necessity of individual collars also makes it more difficult to implement this system on a larger scale. If a herd of cattle tend to maintain cohesive social groups around dominant individuals, it might be possible to use fewer collars thereby making the system more cost efficient. This study investigates the pattern in spatial distribution in a herd of 17 Angus cows on Fanø in Denmark with GPS locations, using a Nofence© system. The aim of this paper is to determine how individuals position themselves in a herd, spatially, and identify a pattern in ranks. The method used in this study examines the distances between an individual to the rest of the herd mates using nearest neighbour and distribution plots. Contrary to the expectations, this study did not show a distinct pattern in herd distribution. While some tendencies in spatial distribution patterns were observed, only a low concordance could be found (W=0.15,p=3.02e−16). Therefore, interactions among individuals should be considered in future studies, rather than only investigating the herd as one unit. A cumulative curves of the ranks estimated over the entire periods allowed however a rough estimation of the hierarchy and allowed the identification of the highest ranked cows. Therefore it might be possible to use fewer collars if the high ranked cows are discovered, but the estimation of the hierarchy will require a period of observation overall several days as the hierarchical positions are fluctuating too much from days to days. Therefore the cumulative rank curves seems to be a valid solution.

Defectively manufactured and deliberately damaged composite laminates fabricated with different continuous reinforcing fibres (respectively, carbon and glass) and polymer matrices (respectively, thermoset and thermoplastic) were inspected in magnetic resonance imaging equipment. Two pulse sequences were evaluated during non-destructive examination conducted in saline solution-immersed samples to simulate load-bearing orthopaedic implants permanently in contact with biofluids. The orientation, positioning, shape, and especially the size of translaminar and delamination fractures were determined according to stringent structural assessment criteria. The spatial distribution, shape, and contours of water-filled voids were sufficiently delineated to infer the amount of absorbed water if thinner image slices than this study were used. The surface texture of composite specimens featuring roughness, waviness, indentation, crushing, and scratches was outlined, with fortuitous artefacts not impairing the image quality and interpretation. Low electromagnetic shielding glass fibres delivered the highest, while electrically conductive carbon fibres produced the poorest quality images, particularly when blended with thermoplastic polymer, though reliable image interpretation was still attainable.

Unmanned Aerial Vehicles (UAVs) equipped with hyperspectral imagers have emerged as an essential technology for the characterization of inland water bodies. The high spectral and spatial resolutions of these systems enable the retrieval of a plethora of optically-active water quality parameters via band ratio algorithms and machine learning methods. However, fitting and validating these models requires access to sufficient quantities of in situ reference data which are time-consuming and expensive to obtain. In this study, we demonstrate how the Generative Topographic Mapping (GTM), a Bayesian realization of the Self-organizing Map, can be used to visualize high-dimensional hyperspectral imagery and extract spectral signatures corresponding to unique endmembers present in the water. Using data collected across a North Texas pond, we first apply the GTM to visualize the distribution of captured reflectance spectra revealing small-scale spatial variability of water composition. Next, we demonstrate how the nodes of the fitted GTM can be interpreted as unique spectral endmembers. Using extracted endmembers together with the normalized spectral similarity score, we are able to efficiently map the abundance of near shore algae as well as the evolution of a rhodamine tracer dye used to simulate water contamination by a localized source.

Cardiomyopathies (CMPs) are a group of myocardial disorders that are characterized by structural and functional abnormalities of the heart muscle. These abnormalities occur in the absence of coronary artery disease (CAD), hypertension, valvular disease, and congenital heart disease. CMPs are an increasingly important topic in the field of cardiovascular diseases due to the complexity of their diagnosis and management. In 2023, the ESC guidelines on cardiomyopathies were first published, marking significant progress in the field. The growth of techniques such as cardiac magnetic resonance imaging (CMR) and genetics has been fueled by the development of multimodal imaging approaches. For the diagnosis of CMPs, a multimodal imaging approach, including CMR, is recommended. CMR has become the standard for non-invasive analysis of cardiac morphology and myocardial function. This document provides an overview of the role of CMR in CMPs, with a focus on tissue mapping. CMR enables the characterization of myocardial tissues and the assessment of cardiac functions. CMR sequences and techniques, such as late gadolinium enhancement (LGE) and parametric mapping, provide detailed information on tissue composition, fibrosis, edema, and myocardial perfusion. These techniques offer valuable insights for early diagnosis, prognostic evaluation, and therapeutic guidance of CMPs. The use of quantitative CMR markers enables personalized treatment plans, improving overall patient outcomes. This review aims to serve as a guide for the use of these new tools in clinical practice.

The pathology of idiopathic intracranial hypertension (IIH), a disease characterized by papillary edema and increased intracranial pressure (IICP), is not yet understood; this disease significantly affects quality of life due to symptoms, including vision loss, headache, and pulsatile tinnitus. By contrast, superficial siderosis (SS), a disorder in which hemosiderin is deposited on the surface of the cerebral cortex and cerebellum, potentially causes cerebellar ataxia or hearing loss. So far, no cases of IIH with infratentorial and supratentorial cortical SS have been reported. Herein, we report a case of a 31-year-old woman with obesity who developed this condition. The patient suddenly developed headache and dizziness, had difficulty walking, and subsequently became aware of diplopia. Fundus examination revealed bilateral optic nerve congestive papillae and right eye abducens disturbance. Head magnetic resonance imaging (MRI) showed prominent SS on the cerebellar surface and cerebral cortex. Lumbar puncture revealed IICP of 32 cmH2O, consistent with the diagnostic criteria for IIH, and treatment with oral acetazolamide was started; subsequently, the intracranial pressure decreased to 20 cmH2O. Her abduction disorder disappeared, and the swelling of the optic papilla improved. She was now able return to her life as a teacher without any sequelae. SS is caused by persistent slight hemorrhage into the subarachnoid space. In this case, both infratentorial and supratentorial cortical superficial SS was observed. Although cases of IIH complicated by SS are rare, it should be kept in mind that a causal relationship between IIH and SS was inferred from our case. Our findings also suggest that cerebrospinal fluid dynamic analysis using MRI is effective in diagnosing IIH and in determining the efficacy of treatment.

Purpose: We aimed to develop a nomogram able to predict treatment failure, skeletal events and overall survival (OS) in patients with castration-resistant prostate cancer with bone metastases (CRPC-BM) treated with Radium-223 dichloride (223Ra). Patients and Methods: Patients from Castilla-La Mancha Spanish region was prospectively included in ChoPET-Rad multicenter study, from January 2015 to December 2022. Patients underwent baseline, interim, and end-of-treatment bone scintigraphy (BS) and 18F-Fluorocholine PET/CT (FCH PET/CT) scans, obtaining multiple imaging radiomics as well as clinical and biochemical variables during follow-up and studying their association with the previously defined end-points. Survival analysis was performed using Kaplan-Meier method and Cox regression. Multivariate logistic and Cox regression models were calculated, and these models were depicted by means of nomograms. Results: Median progression-free survival (PFS) and OS for our population were 4 and 14 months (mo), respectively. The variables that showed the most robust independent significant association with therapeutic failure were baseline alkaline phosphatase (AP) levels (p=0.022) and the characteristics of BM on CT portion of PET/CT (p=0.017). In the case of OS, the significant variables were therapeutic failure (p=0.038), the number of lines received after 223Ra (p

Global use of single-use non-biodegradable plastics, like bottles made of polyethylene tereph-thalate (PET), have contributed to catastrophic levels of plastic pollution. Fortunately, microbi-al communities are adapting to assimilate plastic waste. Previously, our work showed a full consortium of five bacteria capable of synergistically degrading PET. Using omics approaches we identified key genes implicated in PET degradation within the consortium’s pangenome and transcriptome. This analysis led to the discovery of a novel PETase, EstB, discovered to hydrolyze oligomer BHET, and polymer PET. Besides genes implicated in PET degradation, many other biodegradation genes were discovered. Over 200 plastic and plasticizer degrada-tion related genes were discovered through the Plastic Microbial Biodegradation Database (PMBD). Diverse carbon source utilization was observed by a microbial community-based as-say, which paired with an abundant number of plastic and plasticizer degrading enzymes in-dicates a promising possibility for mixed plastic degradation. Using RNAseq differential analysis, several genes were predicted to be involved in PET degradation including aldehyde dehydrogenases and several classes of hydrolases. Active transcription of PET monomer me-tabolism was also observed, including the generation of polyhydroxyalkanoate (PHA) bi-opolymers. These results present an exciting opportunity for the bio-recycling of mixed plastic waste with upcycling potential.

Mitral valve disease is a common heart disease in dogs. The aim of this study was to describe the cases of dogs who underwent mitral valve repair using a v-clamp device and to provide their long-term follow-up data on cardiac function after mitral valve repair. Four dogs with mitral valve regurgitation who experienced coughing and dyspnea underwent surgical mitral valve repair between December 2023 and June 2024. The patients were evaluated by transthoracic and transesophageal echocardiography. Echocardiography revealed mitral valve leaflet regurgitation. Mitral valve repair was performed under general anesthesia using a v-clamp device introduced through an introducer wire guide. Echocardiography was conducted at baseline and the 6-month follow-up. Blood analysis results after surgical repair were normal. Follow-up echocardiography revealed no complications related to the procedure, with all dogs demonstrating improved respiratory signs and quality of life after repair. No adverse reactions were reported after surgery. A v-clamp device was used to repair mitral valve regurgitation in four dogs. Mitral valve repair using a v-clamp device is another treatment option for mitral valve disease in dogs.

Background/Aim: To evaluate the association between baseline [18F]FDG-PET/CT tumor burden parameters and disease progression rate after first-line target therapy or immunotherapy in advanced melanoma patients. Materials and Methods: 44 melanoma patients who underwent [18F]FDG-PET/CT before first-line target therapy (28/50) or immunotherapy (16/50) were retrospectively analyzed. Whole-body and per-district metabolic tumor volume (MTV) and total lesion glycolysis (TLG) were calculated. Therapy response was assessed according to RECIST 1.1 on CT scan at 3 (early) and 12 (late) months. PET parameters were compared with Mann-Whitney test. Optimal cut-offs for predicting progression were defined using the ROC curve. PFS and OS were studied using Kaplan-Meier analysis. Results: Median(IQR) MTVwb and TLGwb were 13.1 mL and 72.4 respectively. Non-responders patients were 38/44, 26/28 and 12/16 at early evaluation, and in 33/44, 21/28 and 12/16 at late evaluation in the whole-cohort, target and immunotherapy subgroup respectively. At late evaluation, MTVbone and TLGbone were higher in non-responders compared to responder patients (all p<0.037) in the whole-cohort and target subgroup and also MTVwb and TLGwb (all p<0.022) in target subgroup. No significant differences were found for immunotherapy subgroup. No metabolic parameters were able to predict PFS. Controversy, MTVlfn, TLGlfn, MTVsoft+lfn, TLG-soft+lfn, MTVwb and TLGwb were significantly associated (all p<0.05) with OS in both the whole-cohort and target therapy subgroup. Conclusion: Higher values of whole-body and bone metabolic parameters were correlated with poorer outcome, while higher values of whole-body, lymph node and soft tissue metabolic parameters were correlated with OS.

Accurate prostate volume estimation is crucial for effective prostate disease management. Ultrasound (US) imaging, particularly transrectal ultrasound, offers a cost-effective and rapid assessment. However, US images often suffer from artifacts and poor contrast, making prostate volume estimation challenging. This review explores recent advancements in deep learning (DL) techniques for automatic prostate segmentation in US images as a primary step for prostate volume estimation. We examine various DL architectures, including traditional U-Net modifications and innovative designs incorporating residual connections, multi-directional image data, and attention mechanisms. Additionally, we discuss pre-processing methods to enhance image quality, the integration of shape information, and strategies to improve the consistency and robustness of DL models. The effectiveness of these techniques is evaluated through metrics such as Dice Similarity Coefficient, Jaccard Index, and Hausdorff Distance. The review highlights the potential of DL in improving prostate volume estimation accuracy and reducing clinical workload, while also identifying areas for future research to enhance model performance and generalizability.

This study evaluated the hip joints of the giant anteater (Myrmecophaga tridactyla) through imaging and macroscopic analyses and proposed a surgical approach for arthrotomy procedures in this species. The study used four samples fixed in 10% formaldehyde and six thawed carcasses. Radiographic and ultrasound examinations and anatomical dissection allowed the proposal of a surgical approach for the hip joint. The radiographic evaluation occurred with frog-legged ventrodorsal and lateral projections, and the ultrasound enabled joint soft tissue assessment. The articular elements represented similar characteristics to other domestic species. Some anatomical particularities of muscle groups were the intermuscular septum between the tensor fasciae latae and superficial gluteus muscles at the level of the greater trochanter of the femur, which provides lateral access to the femoral head and neck more conservatively. In conclusion, the anatomical particularities of radiographic positioning, the clinical applications of joint ultrasound, and the arrangement of muscle groups must be considered when evaluating and surgically accessing the hip joint of the giant anteater.

This study presents a novel approach for automating the body condition scoring of dairy cows, leveraging advancements in 3D imaging technology and deep neural networks. The primary objective was to design and implement a system capable of accurately and efficiently assessing the body condition of dairy cows, a critical metric in livestock management for optimizing health and productivity. To achieve this, a 3D camera was employed to capture detailed point cloud data, reconstructing the three-dimensional morphology of individual cows. The obtained data were then fed into a deep neural network, specifically tailored for the task of ranking body condition. The neural network was trained on a diverse dataset of annotated body condition score representing varying degrees of body condition, ensuring robust performance across different physiological states. The results demonstrate the efficacy of the proposed system in automatically and objectively scoring the body condition of dairy cows. The automated process not only expedites the assessment but also reduces the subjectivity associated with manual scoring methods. This innovative approach holds promise for improving the efficiency of dairy farm management by providing timely and accurate body condition assessments. The integration of 3D imaging and deep learning techniques paves the way for future advancements in precision livestock farming, contributing to enhanced animal welfare, optimized production, and sustainable agriculture practices.

The relationship between epicardial adipose tissue (EAT) and atrial fibrillation (AF) has gained interest in recent years. Previous literature on the topic presents great heterogeneity, focusing especially on computed tomog-raphy imaging. Aim of the present study is to determine whether an increased volume of left atrial (LA) EAT evaluated at routine pre-procedural cardiac magnetic resonance imaging (MRI) relates to AF recurrences after catheter ablation. 50 patients undergoing AF cryoballoon ablation and pre-procedural cardiac MRI allowing quantification of LA EAT were enrolled. In one patient segmentation of LA EAT could not be achieved. After a median follow-up of 16.0 months, AF recurrences occurred in 17 patients (34%). Absolute volume of EAT was not different in patients with and without AF recurrences (10.35 ml vs. 10.29 ml; p-value=0.963), whereas volume of EAT indexed on the LA (EATi) was lower, albeit non statistically significant, in patients free from arrhythmias (12.77% vs. 14.06%; p-value=0.467). Receiver operating characteristic curve testing the ability of EATi to predict AF recurrence after catheter ablation showed sub-optimal performance (AUC: 0.588). The finest identified cut-off of EATi was 10.65%, achieving a sensitivity of 0.5, a specificity of 0.82, a positive predictive value of 0.59 and a negative predictive value of 0.76. Patients with values of EATi lower than 10.65% showed greater survival free from arrhythmias than patients with values above this cut-off (84% vs. 48%; p-value=0.04). In conclusion, indexed LA EAT volume evaluated at cardiac MRI independently relates to arrhythmia recurrence after AF cryoballoon ablation.

Foxtail millet, a traditional cereal crop, has gained increasing attention for its high nutritional value and potential health benefits. This study aimed to investigate the simultaneous and rapid detection of amylose and amylopectin content of foxtail millet flour under different sheep manure application rates by hyperspectral imaging combined with chemometrics. The spectral data preprocessing used multiplicative scatter correction (MSC), and the combined algorithm of competitive adaptive reweighted sampling (CARS), random frog (RF), iterated retaining informative variables (IRIV) were employed for key band extraction. The partial least squares regression (PLSR) was then used to establish the prediction model and the regression equation, that was used to visualize the two components. Results demonstrated the key band extraction combined algorithm effectively reduced data dimension without compromising the accuracy of the prediction model. The prediction model for amylose using MSC-RF-IRIV-PLSR exhibited good performance, with the correlation coefficient (R) and root mean square error (RMSE) predicted to be 0.73 and 1.23, respectively. Similarly, the prediction model for amylopectin using MSC-CARS-IRIV-PLSR also demonstrated good performance, with the R and RMSE predicted to be 0.59 and 7.34, respectively. Then, the visualization graph generated clearly shows under the condition of applying 6 m3 of sheep manure, the amount of amylopectin accumulation was highest, and the amount of amylose was lowest. The experimental results offer valuable insights for the rapid detection of nutritional components in foxtail millet, serving as a basis for further research.

The integration of artificial intelligence (AI) into medical imaging has guided in an era of transformation in healthcare. This literature review explores the latest innovations and applications of AI in the field, highlighting its profound impact on medical diagnosis and patient care. The innovation segment explores into cutting-edge developments in AI, such as deep learning algorithms, convolutional neural networks, and generative adversarial networks, which have significantly improved the accuracy and efficiency of medical image analysis. These innovations have enabled rapid and accurate detection of abnormalities, from identifying tumors during radiological examinations to detecting early signs of eye disease in retinal images. The article also highlights various applications of AI in medical imaging, including radiology, pathology, cardiology, and more. AI-based diagnostic tools not only speed up the interpretation of complex images but also improve early detection of disease, ultimately delivering better outcomes for patients. Additionally, AI-based image processing facilitates personalized treatment plans, thereby optimizing healthcare delivery. This literature review highlights the paradigm shift that AI has brought to medical imaging, highlighting its role in revolutionizing diagnosis and patient care. By combining cutting-edge AI techniques and their practical applications, it is clear that AI will continue shaping the future of healthcare in profound and positive ways.

Compton cameras detect scattered gamma rays and estimate the distribution of gamma-ray sources. Nonetheless, crafting a camera tailored to a specific application presents formidable challenges, often necessitating the implementation of diverse image reconstruction techniques. Delving into the factors influencing these cameras can pave the way for design optimization and performance enhancement. This study introduces an inventive detector design for Compton imaging systems, building upon the achievements of prior designs. The proposed system contains eight scatterer detectors and a semiconductor absorber detector, spaced at 1 mm and 30 mm intervals, respectively. The source-to-first-scatterer-detector distance is 5 mm, with scatterer and absorber detector plates measuring 70× 70× 2.125 mm³ and 70× 70× 10 mm³, respectively. Geant4 simulation toolkit models the Compton imaging system, and an analytical method reconstructs Compton camera images. Unlike more straightforward techniques, the analytical method directly reconstructs Compton camera images by solving the equation relating to the reflected image data. This approach is implemented in the C++ programming language. The study's findings reveal that the analytical method discerns optimal conditions and parameters that significantly influence efficiency, yielding a full width at half maximum (FWHM) of 3.7 mm with an angular uncertainty of approximately 2.7 degrees at an energy level of 0.662 MeV. Compared to another experimental design employing the analytical image reconstruction approach, the FWHM value decreased by 0.7 mm. This study presents an innovative detector design and an analytical reconstruction method for Compton imaging systems, showcasing improved efficiency and accuracy.

Gold nanoclusters (AuNCs) with fluorescence in the Near Infrared (NIR) by both one- and two-photon electronic excitation were incorporated in mesoporous silica nanoparticles (MSNs) using a novel one-pot synthesis procedure where the condensation polymerization of alkoxysilane monomers in the presence of the AuNCs and a surfactant produce hybrid MSNs of 49 nm diameter. This method was further developed to prepare 30 nm diameter nanocomposite particles with simultaneous NIR fluorescence and superparamagnetic properties, with a core composed of superparamagnetic manganese ferrite nanoparticles (MnFe2O4) coated with a thin silica layer, and a shell of mesoporous silica decorated with AuNCs. The nanocomposite particles feature NIR-photoluminescence with 0.6% quantum yield and large Stokes shift (290 nm), and superparamagnetic response at 300 K, with a saturation magnetization of 13.4 emu g-1. The conjugation of NIR photoluminescence and superparamagnetic properties in the biocompatible nanocomposite has high potential for application in multimodal bioimaging.

Dendritic Mesoporous Organosilica Nanoparticles (DMON) are a new class of biodegradable nanoparticles suitable for biomolecules delivery. In order to escape from the endosomes-lysosomes and to deliver biomolecules in the cytoplasm of cells, we studied photochemical internalization (PCI) and photodynamic therapy (PDT) of DMON. We added photosensitizers in the framework of DMON. DMON were also loaded with siRNA or FVIII factor protein. We made four formulations with four different photosensitizers, The photosensitizers allowed to perform imaging of DMON in cancer cells, but the presence of the tetrasulfide bond in the framework of DMON quenched the formation of singlet oxygen. Fortunately one formulation allowed to efficiently deliver proapoptotic siRNA in MCF-7 cancer cells leading to 31% of cancer cell death, without irradiation. For FVIII protein, it was loaded in two formulations with drug loading capacities (DLC) up to 25%. In conclusion DMON are versatile nanoparticles which allowed to load siRNA and to deliver it in cancer cells, and to load FVIII protein with good DLC. Due to the presence of tetrasulfide, it was not possible to perform PDT and PCI.

Hepatocellular carcinoma is the most common primary malignant hepatic tumor and occurs most often in the setting of chronic liver disease. Liver transplantation is a curative treatment option and is an ideal solution because it solves the chronic underlying liver disorder while removing the malignant lesion. Because of organ shortages this treatment can only be applied to carefully selected patients according to clinical guidelines to minimize risk of recurrence. Artificial intelligence is an emerging technology with multiple applications in medicine with a predilection for domains that work with medical imaging like radiology. With the help of these technologies laborious tasks like segmentation can be automated and workflow in radiology departments can be improved. Other roles include in depth pixel-wise analysis of lesions by radiomics or deep learning in order to find new imaging criteria that allow better prediction of treatment response or risk of recurrence. Liver transplant is an ideal treatment for patients with hepatocellular carcinoma in the setting of chronic liver disease and artificial intelligence could provide solutions for improving the management of liver transplant candidates to improve survival.

Intratumoral heterogeneity associates with more aggressive disease progression and worse patient outcomes. Understanding the reasons enabling the emergence of such heterogeneity remains incomplete, which restricts our ability to manage it from a therapeutic perspective. Technological advancements such as high-throughput molecular imaging, single-cell omics and spatial transcriptomics now allow recording the patterns of spatiotemporal heterogeneity in a longitudinal manner, thus offering insights into the multi-scale dynamics of its evolution. Here, we review latest technological trends and biological insights from molecular diagnostics as well as spatial transcriptomics, both of which have witnessed a burgeoning growth in recent past in terms of mapping heterogeneity within tumor cell types as well as stromal constitution. We also discuss ongoing challenges, indicating possible ways to integrate insights across these methods to have a systems-level spatiotemporal map of heterogeneity in each tumor, and a more systematic investigation of implications of heterogeneity for the patient outcomes.

At INFN-LNS, and in collaboration with the ATOMKI laboratories, an innovative multi-diagnostic system with advanced analytical methods has been designed and implemented. This is based on several detectors and techniques (Optical Emission Spectroscopy, RF systems, Interfero-polarimetry, X-ray detectors) and here we focus on high resolution spatially-resolved X-ray spectroscopy, performed by means of a X-ray pin-hole camera setup operating in the 0.5−20 keV energy domain. The diagnostic system was installed at a 14 GHz Electron Cyclotron Resonance (ECR) ion source (ATOMKI, Debrecen), enabling high precision X-ray spectrally-resolved imaging of ECR plasmas heated by hundreds of Watts. The achieved spatial and energy resolution were 0.5 mm and 300 eV at 8 keV, respectively. We here present the innovative analysis algorithm that we properly developed for obtaining Single Photon-Counted (SPhC) images providing the local plasma emitted spectrum in a High-Dynamic-Range (HDR) mode, by distinguishing fluorescence lines of the materials of the plasma chamber (Ti, Ta) from plasma (Ar). This method allows a quantitative characterization of warm electrons population in the plasma (and its 2D distribution) which are the most important for ionization, and also to estimate local plasma density and spectral temperatures. The developed post-processing analysis is also able to remove the readout noise, that is often observable at very low exposure times (msec). The setup is now under update including fast shutters and trigger systems in order to allow simultaneously space and time-resolved plasma spectroscopy during transients, stable and turbulent regimes.

pH value almost affects the function of cells and organisms in all aspects, so in biology, biochemical and many other research fields, it is necessary to apply simple, intuitive, sensitive, stable detection of pH and base characteristics inside and outside the cell. Therefore, many research groups have explored the design and application of pH probes based on surface enhanced Raman scattering（SERS）. In this review article, we discussed the basic theoretical background of explaining the working mechanism of pH SERS sensors, and also briefly described the significance of cell pH measurement, and simply classified and summarized the factors that affected the performance of pH SERS probes. Some applications of pH probes based on surface enhanced Raman scattering (SERS) in intracellular and extracellular pH imaging and the combination of other analytical detection techniques are described. And finally, the development prospect of this field is prospected.

Cells receive external stimuli to incur structural and functional damages. On scanning acoustic microscopy (SAM), speed-of-sound (SOS), attenuation-of-sound (AOS), and thickness values are plotted on the screen to create cellular images, which are related to stiffness, viscosity, and cell size, respectively. The obtained digital data compared using statistical analysis. We aimed to investigate the effects of anticancer drugs, acidic fluids, and heat effects on the cells by using SAM. Anticancer drug cisplatin induced cancer cell apoptosis/necrosis and regeneration in culture, causing elevated SOS, reduced AOS, and thickness. During a more prolonged incubation, the SAM values fluctuated differently between the cisplatin-treated and untreated cells. The tannic and acetic acid and microwave stimuli induced SOS and AOS elevations. These stimuli altered the cell size, number, differentiation, viscosity, and stiffness, which corresponded well to the fluctuation of the SOS and AOS values after incubation. Different anticancer drugs interacted with cancer cells to induce the characteristic alterations of the SAM values. These structural and mechanical alterations induced in cells was difficult to observe on light microscopy. Cellular damages were statistically compared between different stimuli and time-lapse cellular changes were observed using a SAM analysis. SAM is a useful modality to evaluate cellular damage.

Background: Lung CT provides an effective modality to evaluate patients with suspected COVID-19. However, overlapping imaging findings with cardiogenic pulmonary oedema have been reported. Reports comparing lung CT features of these diseases have not been elaborated. Thus, we aimed to investigate these gaps in the knowledge regarding low-dose lung CT features of patients with COVID-19 pneumonia with those with acute heart failure (HF). Methods: This retrospective analysis enrolled hospitalized patients with COVID-19 (n=10) and acute heart failure (n=9) that exclusively underwent low-dose lung CT scans within 24-hours of admission. Clinical and lung CT characteristics were collected and analysed. Results: Ground-glass-opacities (GGO) appearance has been recorded in all subjects in HF and COVID-19 group. There was no significant statistical difference between the two groups for rounded morphology, consolidation, crazy paving pattern, lesion distribution, parenchymal band (P> 0.05). However, diffuse lesions were more frequent in HF cases (55.6% vs. 0%) than in COVID-19 pneumonia, which had predominantly multifocal pattern. Notably, CT images in HF patients were more likely to have signs of interstitial tissue thickening such as the interlobular septums, fissures and peribronchovascular interstitium (55.6% vs 0%, 88.9% vs 20% and 44.4% vs 0%,respectively), as well as cardiomegaly (77.8% vs 0%), increased artery to bronchus ratio (55.6% vs 0%), and pleural effusions (77.8% vs 0%). Conclusions: Major overlaps of lung CT imaging features existed between COVID-19 pneumonia and acute HF cases. However, signs of fluid redistribution are clues that favour HF over COVID-19 pneumonia.

To elucidate dynamic developmental processes in plants, live tissues and organs have to be visualized frequently and for long time periods. The development of roots is studied in depth at a cellular resolution not only to comprehend the basic processes fundamental to maintenance and pattern formation but also study stress tolerance adaptation in plants. Despite technological advancements, maintaining continuous access to samples and simultaneously preserving their morphological structures and physiological conditions without causing damage presents hindrances in the measurement, visualization and analyses of growing organs including plant roots. We propose a preliminary system which integrates the optical real-time visualization through light microscopy with a liquid culture which enables us to image at the tissue and cellular level horizontally growing Brachypodium roots every few minutes and up to 24 hours. We describe a simple setup which can be used to track the growth of the root as it grows including the root tip growth and osmotic stress dynamics. We demonstrate the system’s capability to scale down the PEG-mediated osmotic stress analysis and collected data on gene expression under osmotic stress.

Imaging living cells by atomic force microscopy (AFM) promises not only high-resolution topographical data, but additionally, mechanical contrast, which are not obtainable with other microscopy techniques. Such imaging is however challenging, as cells need to be measured with low interaction forces to prevent either deformation or detachment from the surface. Off-resonance modes which periodically probe the surface have been shown to be advantageous, as they provide excellent force control combined with large amplitudes, which help reduce lateral force interactions. However, the low actuation frequency in traditional off-resonance techniques limits the imaging speed significantly. Using photothermal actuation, we probe the surface by directly actuating the cantilever. Due to the much smaller mass that needs to be actuated, the achievable measurement frequency is increased by two orders of magnitude. Additionally, photothermal off-resonance tapping retains the precise force control of conventional off-resonance modes and is therefore well suited to gentle imaging. Here we show how photothermal off-resonance tapping can be used to study live cells by AFM. As an example of imaging mammalian cells, the initial attachment, as well as long term detachment of a human thrombocytes are presented. The membrane disrupting effect of the antimicrobial peptide CM-15 is shown on the cell wall of E. coli. Finally, the dissolution of the cell wall of B. subtilis by lysozyme is shown. Taken together, these evolutionarily disparate forms of life exemplify the usefulness of PORT for live cell imaging in a multitude of biological disciplines.

The monitoring of sick newborns is a challenging task that health care providers in Neonatal Intensive Care Units (NICU) must contend with each day. Conventionally, newborns are monitored via probes that are affixed to their skin and attached to processing monitors (Fig.1). However, an alternative exists in contactless imaging to record such physiological signals (Physio-Markers), surface changes and internal structures which can be used independently of, or in conjunction with conventional monitors. Advantages of contactless monitoring methods include: i) quick data generation; ii) lack of contact with skin, which reduces skin breakdown and decreases risk of infection; and iii) minimizing the number of probes and monitors affixed to the skin, which allows greater body surface-area for other care. This paper is an attempt to build a foundation for and to provide a vision of the potential neonatal clinical applications of technologies that use non-contact modalities such as Visible Light Imaging (VLI), Near InfraRed Spectrum (NIRS), and Thermal Imaging (TI) using InfraRed Spectrum (IRS).

An automated discharge imaging system (ADIS), a non-intrusive and safe approach, was developed for measuring river flows during flash flood events. ADIS consists of dual cameras to capture complete surface images in the near and far fields. Surface velocities are accurately measured using the Large Scale Particle Image Velocimetry (LSPIV) technique. The stream discharges are then obtained from the depth-averaged velocity (based upon an empirical velocity-index relationship) and cross-section area. The ADIS was deployed at the Yu-Feng gauging station in Shimen Reservoir upper catchment, northern Taiwan. For a rigorous validation, surface velocity measurements were conducted using ADIS/LSPIV and other instruments. In terms of the averaged surface velocity, all measured results were in good agreement with small differences, i.e., 0.004 to 0.39 m/s and 0.023 to 0.345 m/s when compared to those from acoustic Doppler current profiler (ADCP) and surface velocity radar (SVR), respectively. The ADIS/LSPIV was further applied to measure surface velocities and discharges during typhoon events (i.e., Chan-Hom, Soudelor, Goni, and Dujuan) in 2015. The measured water level and surface velocity both showed rapid increases due to flash floods. The estimated discharges from ADIS/LSPIV and ADCP were compared, presenting good consistency with correlation coefficient R = 0.996 and normalized root mean square error NRMSE = 7.96%. The results of sensitivity analysis indicate that components till (τ) and roll (θ) of the camera are most sensitive parameter to affect the surface velocity using ADIS/LSPIV. Overall, the ADIS based upon LSPIV technique effectively measures surface velocities for reliable estimations of river discharges during typhoon events.

Manufactured nanoplastic particles (NPs) are indispensable for in vitro and in vivo testing and health risk assessment of this emerging environmental contaminant. High surface area and inherent hydrophobicity of plastic material, makes production of NPs devoid of any contaminants very challenging. In this study we produced nanoprecipitated polyethylene terephthalate (PET) NPs (300 nm hydrodynamic diameter) and characterized presence of ionic surfactant sodium dodecyl sulfate (SDS) by 1H NMR. Relative ratio of NP/surfactant was monitored on the basis of chemical shifts characteristic for PET and SDS. For a wide range of surfactant/NP ratio (1:17 to 1:1.2), measured zeta potential changed from -42.10 to -34.93 mV, but no clear differences were observed in cellular assays performed in protein-rich media on primary human cells. The remaining impurities contributed to the outcome of biological assays applied in protein-free buffers, such as human red blood cells hemolysis. As size, shape, zeta potential and contaminants of NPs may all be relevant parameters for biological effects of NPs, relative quantification of impurities exemplified in our work by application of 1H NMR for PET NPs and ionic surfactant SDS could be a valuable auxiliary method in quality control of manufactured NPs.

Dual-energy CT (DECT) imaging has broadened the potential of CT imaging by offering multiple postprocessing datasets with a single acquisition at more than one energy level. DECT shows profound capabilities to improve diagnosis based on its superior material differentiation and its quantitative value. However, the potential of dual energy imaging remains relatively untapped, possibly due to its intricate workflow and intrinsic technical limitations of DECT. Knowing the clinical advantages of dual-energy imaging and recognizing its limitations and pitfalls is neces-sary for an appropriate clinical use. The aims of this paper are to review physical and technical basis of DECT acquisition and analysis, to discuss advantages and limitations of DECT in dif-ferent clinical scenarios, to review technical constraints in material labeling and quantification, and to evaluate cutting-edge applications of DECT imaging, including artificial intelligence, qualitative and quantitative imaging biomarkers, and DECT-derived radiomics and radioge-nomics