Guldborgrefsgaard8578

So, a new method for calculating the half-inhibitory concentration was proposed. The result shows that the morphological and texture feature parameters can be used to evaluate the sensitivity of ovarian cancer cells to different drugs by fitting the half-inhibitory concentration numerically. And the result provides a new idea for drug potency assessment methods before chemotherapy for ovarian cancer.Retinopathy of prematurity (ROP) is a proliferative vascular disease, which is one of the most dangerous and severe ocular complications in premature infants. Automatic ROP detection system can assist ophthalmologists in the diagnosis of ROP, which is safe, objective, and cost-effective. Unfortunately, due to the large local redundancy and the complex global dependencies in medical image processing, it is challenging to learn the discriminative representation from ROP-related fundus images. To bridge this gap, a novel attention-awareness and deep supervision based network (ADS-Net) is proposed to detect the existence of ROP (Normal or ROP) and 3-level ROP grading (Mild, Moderate, or Severe). First, to balance the problems of large local redundancy and complex global dependencies in images, we design a multi-semantic feature aggregation (MsFA) module based on self-attention mechanism to take full advantage of convolution and self-attention, generating attention-aware expressive features. Then, to solve the challenge of difficult training of deep model and further improve ROP detection performance, we propose an optimization strategy with deeply supervised loss. Finally, the proposed ADS-Net is evaluated on ROP screening and grading tasks with per-image and per-examination strategies, respectively. In terms of per-image classification pattern, the proposed ADS-Net achieves 0.9552 and 0.9037 for Kappa index in ROP screening and grading, respectively. Experimental results demonstrate that the proposed ADS-Net generally outperforms other state-of-the-art classification networks, showing the effectiveness of the proposed method.The foveal cone mosaic can be directly visualized using adaptive optics scanning light ophthalmoscopy (AOSLO). Previous studies in individuals with normal vision report wide variability in the topography of the foveal cone mosaic, especially the value of peak cone density (PCD). While these studies often involve a human grader, there have been no studies examining intergrader reproducibility of foveal cone mosaic metrics. Here we re-analyzed published AOSLO foveal cone images from 44 individuals to assess the relationship between the cone density centroid (CDC) location and the location of PCD. Across 5 graders with variable experience, we found a measurement error of 11.7% in PCD estimates and higher intergrader reproducibility of CDC location compared to PCD location (p  less then  0.0001). These estimates of measurement error can be used in future studies of the foveal cone mosaic, and our results support use of the CDC location as a more reproducible anchor for cross-modality analyses.Circulating tumor DNA (ctDNA) has recently emerged as an ideal target for biomarker analytes. Thus, the development of rapid and ultrasensitive ctDNA detection methods is essential. In this study, a high-throughput surface-enhanced Raman scattering (SERS)-based lateral flow assay (LFA) strip is proposed. The aim of this method is to achieve accurate quantification of TP53 and PIK3CA E545K, two types of ctDNAs associated with head and neck squamous cell carcinoma (HNSCC), particularly for point-of-care testing (POCT). Raman reporters and hairpin DNAs are used to functionalize the Pd-Au core-shell nanorods (Pd-AuNRs), which serve as the SERS probes. During the detection process, the existence of targets could open the hairpins on the surface of Pd-AuNRs and trigger the first step of catalytic hairpin assembly (CHA) amplification. The next stage of CHA amplification is initiated by the hairpins prefixed on the test lines, generating numerous "hot spots" to enhance the SERS signal significantly. By the combination of high-performing SERS probes and a target-specific signal amplification strategy, TP53 and PIK3CA E545K are directly quantified in the range of 100 aM-1 nM, with the respective limits of detection (LOD) calculated as 33.1 aM and 20.0 aM in the PBS buffer and 37.8 aM and 23.1 aM in human serum, which are significantly lower than for traditional colorimetric LFA methods. The entire detection process is completed within 45 min, and the multichannel design realizes the parallel detection of multiple groups of samples. Moreover, the analytical performance is validated, including reproducibility, uniformity, and specificity. Finally, the SERS-LFA biosensor is employed to analyze the expression levels of TP53 and PIK3CA E545K in the serum of patients with HNSCC. The results are verified as consistent with those of qRT-PCR. Thus, the SERS-LFA biosensor can be considered as a noninvasive liquid biopsy assay for clinical cancer diagnosis.Quantifying the resolution of a super-resolution image is vital for biologists trying to apply super-resolution microscopy in various research fields. Among the reported image resolution estimation methods, the one that calculates the full width at half maximum (FWHM) of line profile, called FWHM resolution, continues the traditional resolution criteria and has been popularly used by many researchers. However, quantifying the FWHM resolution of a super-resolution image is a time-consuming, labor-intensive, and error-prone process because this method typically involves a manual and careful selection of one or several of the smallest structures. In this paper, we investigate the influencing factors in FWHM resolution quantification systematically and present an ImageJ plug-in called LuckyProfiler for biologists so that they can have an easy and effective way of quantifying the FWHM resolution of super-resolution images.Photoacoustic (PA) endoscopy has shown significant potential for clinical diagnosis and surgical guidance. Multimode fibres (MMFs) are becoming increasingly attractive for the development of miniature endoscopy probes owing to their ultrathin size, low cost and diffraction-limited spatial resolution enabled by wavefront shaping. However, current MMF-based PA endomicroscopy probes are either limited by a bulky ultrasound detector or a low imaging speed that hindered their usability. In this work, we report the development of a highly miniaturised and high-speed PA endomicroscopy probe that is integrated within the cannula of a 20 gauge medical needle. This probe comprises a MMF for delivering the PA excitation light and a single-mode optical fibre with a plano-concave microresonator for ultrasound detection. Wavefront shaping with a digital micromirror device enabled rapid raster-scanning of a focused light spot at the distal end of the MMF for tissue interrogation. High-resolution PA imaging of mouse red blood cells covering an area 100 µm in diameter was achieved with the needle probe at ∼3 frames per second. Mosaicing imaging was performed after fibre characterisation by translating the needle probe to enlarge the field-of-view in real-time. The developed ultrathin PA endomicroscopy probe is promising for guiding minimally invasive surgery by providing functional, molecular and microstructural information of tissue in real-time.Laser speckle contrast imaging (LSCI) has gained broad appeal as a technique to monitor tissue dynamics (broadly defined to include blood flow dynamics), in part because of its remarkable simplicity. When laser light is backscattered from a tissue, it produces speckle patterns that vary in time. A measure of the speckle field decorrelation time provides information about the tissue dynamics. In conventional LSCI, this measure requires numerical fitting to a specific theoretical model for the field decorrelation. However, this model may not be known a priori, or it may vary over the image field of view. We describe a method to reconstruct the speckle field decorrelation time that is completely model free, provided that the measured speckle dynamics are ergodic. We also extend our approach to allow for the possibility of non-ergodic measurements caused by the presence of a background static speckle field. In both ergodic and non-ergodic cases, our approach accurately retrieves the correlation time without any recourse to numerical fitting and is largely independent of camera exposure time. We apply our method to tissue phantom and in-vivo mouse brain imaging. Our aim is to facilitate and add robustness to LSCI processing methods for potential clinical or pre-clinical applications.We assessed the ability of the optical attenuation coefficient (AC) to detect early-stage glaucoma with two AC estimation algorithms retinal layer intensity ratio (LIR) and depth-resolved confocal (DRC). We also introduced new depth-dependent AC parameters for retinal nerve fiber layer assessment. Optical coherence tomography B-scans were collected from 44 eyes of age-similar participants with eye health ranging from healthy to severe glaucoma, including glaucoma suspect patients. Mean AC values estimated from the DRC method are comparable to ratio-extracted values (p > 0.5 for all study groups), and the depth-dependent ACDRC parameters enhance the utility of the AC for detection of early-stage glaucoma.Full-ring dual-modal ultrasound and photoacoustic imaging provide complementary contrasts, high spatial resolution, full view angle and are more desirable in pre-clinical and clinical applications. However, two long-standing challenges exist in achieving high-quality video-rate dual-modal imaging. One is the increased data processing burden from the dense acquisition. Another one is the object-dependent speed of sound variation, which may cause blurry, splitting artifacts, and low imaging contrast. Here, we develop a video-rate full-ring ultrasound and photoacoustic computed tomography (VF-USPACT) with real-time optimization of the speed of sound. We improve the imaging speed by selective and parallel image reconstruction. We determine the optimal sound speed via co-registered ultrasound imaging. Equipped with a 256-channel ultrasound array, the dual-modal system can optimize the sound speed and reconstruct dual-modal images at 10 Hz in real-time. The optimized sound speed can effectively enhance the imaging quality under various sample sizes, types, or physiological states. In animal and human imaging, the system shows co-registered dual contrasts, high spatial resolution (140 µm), single-pulse photoacoustic imaging ( 20 mm), full view, and adaptive sound speed correction. We believe VF-USPACT can advance many real-time biomedical imaging applications, such as vascular disease diagnosing, cancer screening, or neuroimaging.With the global spread of the COVID-19 pandemic, the water pollution caused by extensive production and application of COVID-19 related drugs has aroused growing attention. Herein, a novel biochar-supported red mud catalyst (RM-BC) containing abundant free hydroxyl groups was synthesized. The RM-BC activated persulfate process was firstly put forward to degrade COVID-19 related drugs, including arbidol (ARB), chloroquine phosphate, hydroxychloroquine sulfate, and acyclovir. Highly effective removal of these pharmaceuticals was achieved and even 100% of ARB was removed within 12 min at optimum conditions. Mechanism study indicated that SO4 •- and HO• were the predominant radicals, and these radicals were responsible for the formation of DMPOX in electron spin resonance experiments. Tubastatin A Fe species (Fe0 and Fe3O4) and oxygen-containing functional groups in RM-BC played crucial roles in the elimination of ARB. Effects of degradation conditions and several common water matrices were also investigated. Finally, the degradation products of ARB were identified by Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) and possible degradation pathways were proposed.