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A gadofullerene primarily based liver-specific MRI comparison realtor on an early on carried out orthotopic hepatocellular carcinoma.
Diodon hystrix is a new and emerging aquaculture species in south China. However, due to the lack of understanding of reproductive regulation, the management of breeding and reproduction under captivity remains a barrier for the commercial aquaculture of D. hystrix. More genetic information is needed to identify genes critical for gonadal development. Here, the first gonadal transcriptomes of D. hystrix were analyzed and 151.89 million clean reads were generated. All reads were assembled into 57,077 unigenes, and 24,574 could be annotated. By comparing the gonad transcriptomes, 11,487 differentially expressed genes were obtained, of which 4599 were upregulated and 6888 were downregulated in the ovaries. Using enrichment analyses, many functional pathways were found to be associated with reproduction regulation. A set of sex-biased genes putatively involved in gonad development and gametogenesis were identified and their sexually dimorphic expression patterns were characterized. The detailed transcriptomic data provide a useful resource for further research on D. hystrix reproductive manipulation.We sought to systematically evaluate diagnostic performance of four-dimensional computed tomography (4D-CT) in the localization of hyperfunctioning parathyroid glands (HPGs) in patients with primary hyperparathyroidism (pHPT). We calculated the pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratios (DOR) of 4D-CT on a per-lesion level, as well as pooled sensitivity and positive predictive value (PPV) on a per-patient level with 95% confidence intervals (CIs). Additionally, we plotted summary receiver operating characteristic (SROC) curves and evaluated the areas under the curves (AUC). A total of 16 studies were included in the analysis. Their pooled sensitivity, specificity, PLR, NLR, and DOR of 4D-CT on per-lesion level were 75% (95%CI 66-82%), 85% (95%CI 50-97%), 4.9 (95%CI 1.1-21.3), 0.30 (95%CI 0.19-0.45), and 17 (95%CI 3-100), respectively, with an AUC of 81% (95%CI 77-84%). We also observed heterogeneity in sensitivity (I2 = 79%) and specificity (I2 = 94.7%), and obtained a pooled sensitivity of 81% (95%CI 70-90%) with heterogeneity of 81.9% (p less then 0.001) and PPV of 91% (95%CI 82-98%) with heterogeneity of 80.8% (p less then 0.001), based on a per-patient level. Overall, 4D-CT showed moderate sensitivity and specificity for preoperative localization of HPG(s) in patients with pHPT. The diagnostic performance may improve with 4D-CT's promotion to first-line use on a lesion-based level, further research is needed to confirm the results.Increased levels of light, moderate and vigorous physical activity (PA) are positively associated with health benefits. Therefore, sensor-based human activity recognition can identify different types and levels of PA. In this paper, we propose a two-layer locomotion recognition method using dynamic time warping applied to inertial sensor data. Based on a video-validated dataset (ADAPT), which included inertial sensor data recorded at the lower back (L5 position) during an unsupervised task-based free-living protocol, the recognition algorithm was developed, validated and tested. As a first step, we focused on the identification of locomotion activities walking, ascending and descending stairs. These activities are difficult to differentiate due to a high similarity. The results showed that walking could be recognized with a sensitivity of 88% and a specificity of 89%. Specificity for stair climbing was higher compared to walking, but sensitivity was noticeably decreased. In most cases of misclassification, stair climbing was falsely detected as walking, with only 0.2-5% not assigned to any of the chosen types of locomotion. Our results demonstrate a promising approach to recognize and differentiate human locomotion within a variety of daily activities.Pigeon haemoproteosis caused by Haemoproteus columbae (Apicomplexa Haemosporida Haemoproteidae) is globally prevalent in rock doves (Columba livia), although little is known regarding this disease in pigeons and doves in Indonesia. Blood samples of 35 farmed domestic pigeons (C. livia f. domestica) from four localities in Yogyakarta Special Region, Central Java, Indonesia, were collected from March to June, 2016, subjected to a hemogram, and analyzed for the presence of hemoprotozoan infections. Microscopic examination of blood smears revealed a prevalence of 62.5-100% of H. columbae at the four localities (n = 8-10 for each locality), and geometric means of 3.0-5.6% of erythrocytes were parasitized by young and mature gametocytes, suggesting that all infected pigeons were in the chronic phase of infection with repeated recurrences and/or reinfections. Nucleotide sequencing of mitochondrial cytochrome b gene (cytb) for haemosporidian species demonstrated the distribution of four major cytb lineages of H. columbae (mainly HAECOL1, accompanied by COLIV03, COQUI05, and CXNEA02 according to the MalAvi database). Hemogram analysis, involving the estimation of packed cell volume, erythrocyte counts, mean corpuscular volume, mean corpuscular hemoglobin concentration, and plasma protein and fibrinogen levels of 20 parasitized pigeons and five non-infected pigeons demonstrated significant macrocytic hypochromic anemia with hypoproteinemia and hyperfibrinogenemia in the infected pigeons. This study shows the profound impact of long-lasting subclinical pigeon haemoproteosis caused by H. columbae on the health of farmed domestic pigeons.Cataracts are the major cause of blindness worldwide, largely resulting from aging and diabetes mellitus. Advanced glycation end products (AGEs) have been identified as major contributors in cataract formation because they alter lens protein structure and stability and induce covalent cross-linking, aggregation, and insolubilization of lens crystallins. We investigated the potential of the deglycating enzyme fructosamine-3-kinase (FN3K) in the disruption of AGEs in cataractous lenses. Macroscopic changes of equine lenses were evaluated after ex vivo intravitreal FN3K injection. The mechanical properties of an equine lens pair were evaluated after treatment with saline and FN3K. AGE-type autofluorescence (AF) was measured to assess the time-dependent effects of FN3K on glycolaldehyde-induced AGE-modified porcine lens fragments and to evaluate its actions on intact lenses after in vivo intravitreal FN3K injection of murine eyes. A potential immune response after injection was evaluated by analysis of IL-2, TNFαune response in mice. AF kinetics of FN3K-treated cataractous human lens suspensions revealed dose- and time-dependent decreases. Incubation of cataractous human eye lenses with FN3K resulted in a macroscopic lighter color of the cortex and a decrease in AF values. At last, crossover topical treatment of intact human eyes revealed a decrease in AF values during FN3K treatment, while showing no notable changes with saline. Our study suggests, for the first time, a potential additional role of FN3K as an alternative treatment for AGE-related cataracts.Carbon-fiber aluminum honeycomb sandwich panels are vulnerable to low-velocity impacts, which can cause structural damage and failures that reduce the bearing performance and reliability of the structure. Therefore, a method for locating such impacts through a sensor network is very important for structural health monitoring. Unlike composite laminates, the stress wave generated by an impact is damped rapidly in a sandwich panel, meaning that the signal qualities measured by different sensors vary greatly, thereby making it difficult to locate the impact. This paper presents a method for locating impacts on carbon-fiber aluminum honeycomb sandwich panels utilizing fiber Bragg grating sensors. This method is based on a projective dictionary pair learning algorithm and uses structural sparse representation for impact localization. The measurement area is divided into several sub-areas, and a corresponding dictionary is trained separately for each sub-area. For each dictionary, the sensors are grouped into main sensors within the sub-area and auxiliary sensors outside the sub-area. selleck products A balancing weight factor is added to optimize the proportion of the two types of sensor in the recognition model, and the algorithm for determining the balancing weight factor is designed to suppress the negative effects on the positioning of the sensors with poor signal quality. The experimental results show that on a 300 mm × 300 mm × 15 mm sandwich panel, the impact positioning accuracy of this method is 96.7% and the average positioning error is 0.85 mm, which are both sufficient for structural health monitoring.Herein, the pyrolysis of low-density polyethylene (LDPE) scrap in the presence of a H-ZSM-11 zeolite was conducted as an effort to valorize plastic waste to fuel-range chemicals. The LDPE-derived pyrolytic gas was composed of low-molecular-weight aliphatic hydrocarbons (e.g., methane, ethane, propane, ethylene, and propylene) and hydrogen. An increase in pyrolysis temperature led to increasing the gaseous hydrocarbon yields for the pyrolysis of LDPE. Using the H-ZSM-11 catalyst in the pyrolysis of LDPE greatly enhanced the content of propylene in the pyrolytic gas because of promoted dehydrogenation of propane formed during the pyrolysis. Apart from the light aliphatic hydrocarbons, jet fuel-, diesel-, and motor oil-range hydrocarbons were found in the pyrolytic liquid for the non-catalytic and catalytic pyrolysis. The change in pyrolysis temperature for the catalytic pyrolysis affected the hydrocarbon compositions of the pyrolytic liquid more materially than for the non-catalytic pyrolysis. This study experimentally showed that H-ZSM-11 can be effective at producing fuel-range hydrocarbons from LDPE waste through pyrolysis. The results would contribute to the development of waste valorization process via plastic upcycling.Long Range Wide Area Network (LoRaWAN) has rapidly become one of the key enabling technologies for the development of Internet of Things (IoT) architectures. A wide range of different solutions relying on this communication technology can be found in the literature nevertheless, the most part of these architectures focus on single task systems. Conversely, the aim of this paper is to present the architecture of a LoRaWAN infrastructure gathering under the same network different typologies of services within one of the most significant sub-systems of the Smart City ecosystem (i.e., the Smart Waste Management). The proposed architecture exploits the whole range of different LoRaWAN classes, integrating nodes of growing complexity according to the different functions. The lowest level of this architecture is occupied by smart bins that simply collect data about their status. Moving on to upper levels, smart drop-off containers allow the interaction with users as well as the implementation of asynchronous downlink queries. At the top level, Video Surveillance Units (VSUs) are provided with machine learning capabilities for the detection of the presence of fire nearby bins or drop-off containers, thus fully implementing the Edge Computing paradigm. The proposed network infrastructure and its subsystems have been tested in a laboratory and in the field. This study has enhanced the readiness level of the proposed technology to Technology Readiness Level (TRL) 3.
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