Objectives This study sought to compare the diagnostic performance of a multidetector computed tomography (MDCT) integrated protocol (IP) including coronary angiography (CTA) and stress-rest ...perfusion (CTP) with cardiac magnetic resonance myocardial perfusion imaging (CMR-Perf) for detection of functionally significant coronary artery disease (CAD). Background MDCT stress-rest perfusion methods were recently described as adjunctive tools to improve CTA accuracy for detection of functionally significant CAD. However, only a few studies compared these MDCT-IP with other clinically validated perfusion techniques like CMR-Perf. Furthermore, CTP has never been validated against the invasive reference standard, fractional flow reserve (FFR), in patients with suspected CAD. Methods 101 symptomatic patients with suspected CAD (62 ± 8.0 years, 67% males) and intermediate/high pre-test probability underwent MDCT, CMR and invasive coronary angiography. Functionally significant CAD was defined by the presence of occlusive/subocclusive stenoses or FFR measurements ≤0.80 in vessels >2mm. Results On a patient-based model, the MDCT-IP had a sensitivity, specificity, positive and negative predictive values of 89%, 83%, 80% and 90%, respectively (global accuracy 85%). These results were closely related with those achieved by CMR-Perf: 89%, 88%, 85% and 91%, respectively (global accuracy 88%). When comparing test accuracies using noninferiority analysis, differences greater than 11% in favour of CMR-Perf can be confidently excluded. Conclusions MDCT protocols integrating CTA and stress-rest perfusion detect functionally significant CAD with similar accuracy as CMR-Perf. Both approaches yield a very good accuracy. Integration of CTP and CTA improves MDCT performance for the detection of relevant CAD in intermediate to high pre-test probability populations.
The intrinsic challenge of large molecules to cross the cell membrane and reach intracellular targets is a major obstacle for the development of new medicines. We report how rotation along a single ...C–C bond, between atropisomers of a drug in clinical trials, improves cell uptake and therapeutic efficacy. The atropisomers of redaporfin (a fluorinated sulfonamide bacteriochlorin photosensitizer of 1135 Da) are separable and display orders of magnitude differences in photodynamic efficacy that are directly related to their differential cellular uptake. We show that redaporfin atropisomer uptake is passive and only marginally affected by ATP depletion, plasma proteins, or formulation in micelles. The α4 atropisomer, where meso-phenyl sulfonamide substituents are on the same side of the tetrapyrrole macrocycle, exhibits the highest cellular uptake and phototoxicity. This is the most amphipathic atropisomer with a conformation that optimizes hydrogen bonding (H-bonding) with polar head groups of membrane phospholipids. Consequently, α4 binds to the phospholipids on the surface of the membrane, flips into the membrane to adopt the orientation of a surfactant, and eventually diffuses to the interior of the cell (bind-flip mechanism). We observed increased α4 internalization by cells of the tumor microenvironment in vivo and correlated this to the response of photodynamic therapy when tumor illumination was performed 24 h after α4 administration. These results show that properly orientated aryl sulfonamide groups can be incorporated into drug design as efficient cell-penetrating motifs in vivo and reveal the unexpected biological consequences of atropisomerism.
In the context of Shared Autonomous Vehicles, the need to monitor the environment inside the car will be crucial. This article focuses on the application of deep learning algorithms to present a ...fusion monitoring solution which was three different algorithms: a violent action detection system, which recognizes violent behaviors between passengers, a violent object detection system, and a lost items detection system. Public datasets were used for object detection algorithms (COCO and TAO) to train state-of-the-art algorithms such as YOLOv5. For violent action detection, the MoLa InCar dataset was used to train on state-of-the-art algorithms such as I3D, R(2+1)D, SlowFast, TSN, and TSM. Finally, an embedded automotive solution was used to demonstrate that both methods are running in real-time.
Point clouds are a very rich 3D visual representation model, which has become increasingly appealing for multimedia applications with immersion, interaction and realism requirements. Due to different ...acquisition and creation conditions as well as target applications, point clouds' characteristics may be very diverse, notably on their density. While geographical information systems or autonomous driving applications may use rather sparse point clouds, cultural heritage or virtual reality applications typically use denser point clouds to more accurately represent objects and people. Naturally, to offer immersion and realism, point clouds need a rather large number of points, thus asking for the development of efficient coding solutions. The use of deep learning models for coding purposes has recently gained relevance, with latest developments in image coding achieving state-of-the-art performance, thus making natural the adoption of this technology also for point cloud coding. This paper presents a novel deep learning-based solution for point cloud geometry coding which is able to efficiently adapt to the content's characteristics. The proposed coding solution divides the point cloud into 3D blocks and selects the most suitable available deep learning coding model to code each block, thus maximizing the compression performance. In comparison to the state-of-the-art MPEG G-PCC Trisoup standard, the proposed coding solution offers average quality gains up to 4.9 and 5.7 dB for PSNR D1 and PSNR D2, respectively.
The present work proposes a continuous electrocoagulation experimental setup for the removal of fluoride from water using aluminum electrodes. The experimental results showed that the proposed ...process can remove 97% of fluoride from 5 L of water with a concentration of 15 mg F–/L. Additionally, was verified that the applied voltage during the operation remains almost constant, indicating that this experimental setup overcomes the increase of the electrical resistance due to the electrode passivation. The statistical analysis of the results showed that for the fluoride removal all the operating variables have significant effects whereas for the applied voltage only the current intensity and electrodes configuration are significant. A quadratic model showed to be suitable to relate the responses with the operating variables. The experimental setup was tested for the treatment of 20 L of water. The results showed that for 20 L of water the total removal of fluoride could be achieved with an energy consumption of 506 kWh m–3.
This paper describes a highly efficient method for lossless compression of volumetric sets of medical images, such as CTs or MRIs. The proposed method, referred to as 3-D-MRP, is based on the ...principle of minimum rate predictors (MRPs), which is one of the state-of-the-art lossless compression technologies presented in the data compression literature. The main features of the proposed method include the use of 3-D predictors, 3-D-block octree partitioning and classification, volume-based optimization, and support for 16-b-depth images. Experimental results demonstrate the efficiency of the 3-D-MRP algorithm for the compression of volumetric sets of medical images, achieving gains above 15% and 12% for 8- and 16-bit-depth contents, respectively, when compared with JPEG-LS, JPEG2000, CALIC, and HEVC, as well as other proposals based on the MRP algorithm.
Deficits in decoding rewarding (and aversive) signals are present in several neuropsychiatric conditions such as depression and addiction, emphasising the importance of studying the underlying neural ...circuits in detail. One of the key regions of the reward circuit is the nucleus accumbens (NAc). The classical view on the field postulates that NAc dopamine receptor D1-expressing medium spiny neurons (D1-MSNs) convey reward signals, while dopamine receptor D2-expressing MSNs (D2-MSNs) encode aversion. Here, we show that both MSN subpopulations can drive reward and aversion, depending on their neuronal stimulation pattern. Brief D1- or D2-MSN optogenetic stimulation elicited positive reinforcement and enhanced cocaine conditioning. Conversely, prolonged activation induced aversion, and in the case of D2-MSNs, decreased cocaine conditioning. Brief stimulation was associated with increased ventral tegmenta area (VTA) dopaminergic tone either directly (for D1-MSNs) or indirectly via ventral pallidum (VP) (for D1- and D2-MSNs). Importantly, prolonged stimulation of either MSN subpopulation induced remarkably distinct electrophysiological effects in these target regions. We further show that blocking κ-opioid receptors in the VTA (but not in VP) abolishes the behavioral effects induced by D1-MSN prolonged stimulation. In turn, blocking δ-opioid receptors in the VP (but not in VTA) blocks the behavioral effects elicited by D2-MSN prolonged stimulation. Our findings demonstrate that D1- and D2-MSNs can bidirectionally control reward and aversion, explaining the existence of controversial studies in the field, and highlights that the proposed striatal functional opposition needs to be reconsidered.
Prostate cancer is one of the most common forms of cancer globally, affecting roughly one in every eight men according to the American Cancer Society. Although the survival rate for prostate cancer ...is significantly high given the very high incidence rate, there is an urgent need to improve and develop new clinical aid systems to help detect and treat prostate cancer in a timely manner. In this retrospective study, our contributions are twofold: First, we perform a comparative unified study of different commonly used segmentation models for prostate gland and zone (peripheral and transition) segmentation. Second, we present and evaluate an additional research question regarding the effectiveness of using an object detector as a pre-processing step to aid in the segmentation process. We perform a thorough evaluation of the deep learning models on two public datasets, where one is used for cross-validation and the other as an external test set. Overall, the results reveal that the choice of model is relatively inconsequential, as the majority produce non-significantly different scores, apart from nnU-Net which consistently outperforms others, and that the models trained on data cropped by the object detector often generalize better, despite performing worse during cross-validation.
Abstract
Bacterial AB toxins are secreted key virulence factors that are internalized by target cells through receptor-mediated endocytosis, translocating their enzymatic domain to the cytosol from ...endosomes (short-trip) or the endoplasmic reticulum (long-trip). To accomplish this, bacterial AB toxins evolved a multidomain structure organized into either a single polypeptide chain or non-covalently associated polypeptide chains. The prototypical short-trip single-chain toxin is characterized by a receptor-binding domain that confers cellular specificity and a translocation domain responsible for pore formation whereby the catalytic domain translocates to the cytosol in an endosomal acidification-dependent way. In this work, the determination of the three-dimensional structure of AIP56 shows that, instead of a two-domain organization suggested by previous studies, AIP56 has three-domains: a non-LEE encoded effector C (NleC)-like catalytic domain associated with a small middle domain that contains the linker-peptide, followed by the receptor-binding domain. In contrast to prototypical single-chain AB toxins, AIP56 does not comprise a typical structurally complex translocation domain; instead, the elements involved in translocation are scattered across its domains. Thus, the catalytic domain contains a helical hairpin that serves as a molecular switch for triggering the conformational changes necessary for membrane insertion only upon endosomal acidification, whereas the middle and receptor-binding domains are required for pore formation.
In this study, thin films composed of gold nanoparticles embedded in a copper oxide matrix (Au:CuO), manifesting Localized Surface Plasmon Resonance (LSPR) behavior, were produced by reactive DC ...magnetron sputtering and post-deposition in-air annealing. The effect of low-power Ar plasma etching on the surface properties of the plasmonic thin films was studied, envisaging its optimization as gas sensors. Thus, this work pretends to attain the maximum sensing response of the thin film system and to demonstrate its potential as a gas sensor. The results show that as Ar plasma treatment time increases, the host CuO matrix is etched while Au nanoparticles are uncovered, which leads to an enhancement of the sensitivity until a certain limit. Above such a time limit for plasma treatment, the CuO bonds are broken, and oxygen is removed from the film’s surface, resulting in a decrease in the gas sensing capabilities. Hence, the importance of the host matrix for the design of the LSPR sensor is also demonstrated. CuO not only provides stability and protection to the Au NPs but also promotes interactions between the thin film’s surface and the tested gases, thereby improving the nanocomposite film’s sensitivity. The optimized sensor sensitivity was estimated at 849 nm/RIU, which demonstrates that the Au-CuO thin films have the potential to be used as an LSPR platform for gas sensors.
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