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BackgroundThe severe acute respiratory coronavirus 2 (SARS-CoV-2) pandemic calls for expanded opportunities for testing, including novel testing strategies such as home-collected specimens. ObjectiveWe aimed to understand whether oropharyngeal swab (OPS), saliva, and dried blood spot (DBS) specimens collected by participants at home and mailed to a laboratory were sufficient for use in diagnostic and serology tests of SARS-CoV-2. MethodsEligible participants consented online and were mailed a participant-collection kit to support collection of three specimens for SARS-CoV-2 testing: saliva, OPS, and DBS. Participants performed the specimen collection procedures during a telehealth video appointment while clinical observers watched and documented the suitability of the collection. The biological sufficiency of the specimens for detection of SARS-CoV-2 by reverse transcriptase–polymerase chain reaction and serology testing was assessed by laboratorians using visual inspection and quantification of the nucleic acid contents of the samples by ribonuclease P (RNase P) measurements. ResultsOf the enrolled participants,153/159 (96.2%) returned their kits, which were included in this analysis. All these participants attended their video appointments. Clinical observers assessed that of the samples collected, 147/153 (96.1%) of the saliva samples, 146/151 (96.7%) of the oropharyngeal samples, and 135/145 (93.1%) of the DBS samples were of sufficient quality for submission for laboratory testing; 100% of the OPS samples and 98% of the saliva samples had cycle threshold values for RNase P

Diabetic macular edema (DME) is a leading cause of vision impairment in diabetic patients, necessitating a timely and accurate diagnosis. This paper proposes a comprehensive system for DME grading using retinal fundus images. Our approach integrates multiple deep learning modules, each designed to address key aspects of the diagnostic process. The first module employs the ConvUNeXt model for segmenting hard exudates (HaEx), crucial indicators of DME. The second module uses RetinaNet for precise optic disc (OD) localization, which is essential for subsequent macula localization. The third module refines macula localization, leveraging preprocessing techniques to enhance image clarity. Finally, our system consolidates these results to provide interpretable DME grading. Experimental evaluations were conducted on the Messidor dataset, demonstrating the system's robust performance. The HaEx segmentation module achieved a mean IoU of 70.5% and a Dice coefficient of 0.64. The OD localization module showed perfect accuracy, recall, and precision at 1.0. For macula localization, our method satisfied the 1R criterion with 99.38% accuracy. The DME grading module achieved an overall accuracy of 91.12%, with an AUC of 0.9334. Our method offers a balanced performance across accuracy, sensitivity, and specificity compared to other non-interpretable and partially interpretable methods. [ABSTRACT FROM AUTHOR]

Uterine artery embolization (UAE) is a type of noninvasive treatment for symptomatic uterine fibroids. One of the complications of UAE is fibroid expulsion. Here, we report a case of a 45-year-old woman who underwent UAE for an intramural fibroid, which resulted in fibroid expulsion. To the best of our knowledge, there are only few reports of expulsion of intramural fibroids. The process of fibroid protrusion from the myometrium into the uterine cavity was depicted on magnetic resonance imaging (MRI) in this case. We discuss the risk factors and mechanisms of fibroid expulsion after UAE. [ABSTRACT FROM AUTHOR]

View large Download slide View large Download slide OBJECTIVES The through-and-through guidewire technique has been utilized for safe advancement of a high-profile stent graft delivery system through the tortuous aorta. A brachial-to-femoral configuration is most commonly established, but a few alternatives have been described. This study aimed to report our experience with the externalized transapical guidewire (ETAG) technique in patients who underwent thoracic endovascular aortic repair (TEVAR) and to explore its utility, feasibility and safety. METHODS Patients who underwent TEVAR between April 2015 and March 2017 were retrospectively reviewed, and 5 patients who underwent the procedure with the ETAG technique were found eligible for the study. Indications for the ETAG technique were the following challenging aortic anatomical configurations: (i) severely angulated aorta in 3; (ii) proximity of the proximal landing zone to the aortic valve in 2; (iii) a limited proximal landing zone in 1; and (iv) complex atheroma predominantly on the greater curvature of the aorta in 3 patients. RESULTS TEVAR was completed in all cases. The ETAG technique was utilized in all patients. The delivery system tip was navigated along the lesser curvature of the aortic arch as it was advanced. During deployment, conformability was increased by pushing both ends of the wire. Tip retrieval was also enhanced in 3 patients. Patients with complex aortic atheroma had no embolic complications. All patients survived TEVAR, but 1 patient with an aorto-oesophageal fistula did not survive the second-stage oesophagectomy. Postoperative complications included delayed cardiac tamponade requiring drainage in 2 patients. CONCLUSIONS The ETAG technique was useful in overcoming several anatomical challenges encountered during TEVAR. Contact of the delivery system with the greater curvature of the aortic arch could be avoided with this technique, potentially reducing embolization risk related to the complex aortic arch atheroma. [ABSTRACT FROM AUTHOR]

An imperceptible visible watermarking (IVW) algorithm is proposed to deliver auxiliary information about the visual contents, including ownership information. The proposed algorithm overcomes several inconveniences presented in previously reported IVW algorithms using the just noticeable difference (JND) criterion, invisible watermarking and binarisation function. The proposed algorithm consists of the visible watermark embedding and the exhibition stages. The JND criterion is used to embed visible watermark pattern in an imperceptible manner by the human visual system, while invisible watermarking based on the discrete cosine transform is used to share crucial parameters between both stages, which makes possible the watermark visualisation without any side information. In the watermark exhibition stage, the imperceptibly embedded visible watermark pattern is exhibited by the binarisation function. The proposed algorithm can be applied to any class of images with different characteristics and several visible watermark patterns can be embedded into an input image. Evaluation results show that performance of the proposed algorithm is better compared with previously reported algorithms from several practical points of view. [ABSTRACT FROM AUTHOR]

In this study, we demonstrate the one-step production of cadaverine (1,5-diaminopentane) from cellobiose using an Escherichia coli strain displaying β-glucosidase (BGL) on its cell surface. L-lysine decarboxylase (CadA) derived from E. coli and BGL from Thermobifida fusca YX (Tfu0937) fused to the anchor protein Blc from E. coli were co-expressed using E. coli as a host. The expression of CadA was confirmed by Western blotting and BGL activity on the cell surface was evaluated using pNPG as a substrate. Growth on cellobiose as the sole carbon source was also achieved. The OD600 value of the BGL and CadA co-expressing strain was 8.0 after 48 h cultivation, which is higher than that obtained by growth on glucose (5.4 after 48 h cultivation). The engineered strain produced cadaverine from cellobiose more effectively than from glucose: 6.1 mM after 48 h from 28 g/L of consumed cellobiose, vs. 3.3 mM from 20 g/L of consumed glucose. [ABSTRACT FROM AUTHOR]

The presence of smoke is the first symptom of fire; therefore to achieve early fire detection, accurate and quick estimation of the presence of smoke is very important. In this paper we propose an algorithm to detect the presence of smoke using video sequences captured by Internet Protocol (IP) cameras, in which important features of smoke, such as color, motion and growth properties are employed. For an efficient smoke detection in the IP camera platform, a detection algorithm must operate directly in the Discrete Cosine Transform (DCT) domain to reduce computational cost, avoiding a complete decoding process required for algorithms that operate in spatial domain. In the proposed algorithm the DCT Inter-transformation technique is used to increase the detection accuracy without inverse DCT operation. In the proposed scheme, firstly the candidate smoke regions are estimated using motion and color smoke properties; next using morphological operations the noise is reduced. Finally the growth properties of the candidate smoke regions are furthermore analyzed through time using the connected component labeling technique. Evaluation results show that a feasible smoke detection method with false negative and false positive error rates approximately equal to 4% and 2%, respectively, is obtained [ABSTRACT FROM AUTHOR]

This paper proposes a teleophthalmology support system in which we use algorithms of object detection and semantic segmentation, such as faster region-based CNN (FR-CNN) and SegNet, based on several CNN architectures such as: Vgg16, MobileNet, AlexNet, etc. These are used to segment and analyze the principal anatomical elements, such as optic disc (OD), region of interest (ROI) composed by the macular region, real retinal region, and vessels. Unlike the conventional retinal image quality assessment system, the proposed system provides some possible reasons about the low-quality image to support the operator of an ophthalmoscope and patient to acquire and transmit a better-quality image to central eye hospital for its diagnosis. The proposed system consists of four steps: OD detection, OD quality analysis, obstruction detection of the region of interest (ROI), and vessel segmentation. For the OD detection, artefacts and vessel segmentation, the FR-CNN and SegNet are used, while for the OD quality analysis, we use transfer learning. The proposed system provides accuracies of 0.93 for the OD detection, 0.86 for OD image quality, 1.0 for artefact detection, and 0.98 for vessel segmentation. As the global performance metric, the kappa-based agreement score between ophthalmologist and the proposed system is calculated, which is higher than the score between ophthalmologist and general practitioner. [ABSTRACT FROM AUTHOR]

The development of coding schemes with the capacity to simultaneously encrypt and compress audio signals is a subject of active research because of the increasing necessity for transmitting sensitive audio information over insecure communication channels. Thus, several schemes have been developed; firstly, some of them compress the digital information and subsequently encrypt the resulting information. These schemas efficiently compress and encrypt the information. However, they may compromise the information as it can be accessed before encryption. To overcome this problem, a compressing sensing-based system to simultaneously compress and encrypt audio signals is proposed in which the audio signal is segmented in frames of 1024 samples and transformed into a sparse frame using the discrete cosine transform (DCT). Each frame is then multiplied by a different sensing matrix generated using the chaotic mixing scheme. This fact allows that the proposed scheme satisfies the extended Wyner secrecy (EWS) criterion. The evaluation results obtained using several genres of audio signals show that the proposed system allows to simultaneously compress and encrypt audio signals, satisfying the EWS criterion. [ABSTRACT FROM AUTHOR]