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Background: Bioinformatic analysis has revealed that OXR1 is significantly downregulated in muscle-invasive bladder cancer. Patients & methods: The expression of OXR1 in patients with urothelial carcinoma was evaluated by immunohistochemistry, including 340 cases with urothelial carcinoma in the upper urinary tract and 295 in the urinary bladder. Results: Low expression of OXR1 was significantly correlated with adverse pathological parameters including high primary tumor (pT) stage, high node stage, high histological grade, high mitotic activity and increased vascular or perineural invasion (all p

BackgroundEvans calcaneal lengthening osteotomy is used to treat symptomatic flexible flatfoot when conservative treatment fails. Grafts such as autologous iliac bone grafts, allografts, and xenografts are implanted at the osteotomy site to lengthen the lateral column of the hindfoot. This study aimed to present the outcomes of an autologous mid-fibula bone graft used for calcaneal lengthening in symptomatic pes valgus in adolescents.MethodsWe retrospectively examined 23 ft of 13 adolescents who underwent surgery between July 2014 and January 2018. The radiological and clinical outcomes (American Orthopaedic Foot and Ankle Society ankle-hindfoot scale scores) were assessed during a mean follow-up of 49.7 (range, 30.9–73.4) months. The mean distance of the lengthening site was measured to evaluate graft sinking or collapse. The Goldberg scoring system was used to determine the degree of union at the donor and recipient sites.ResultsThe calcaneal pitch and the anteroposterior and lateral talo-first metatarsal (Meary) angles showed significant correction, from 14.4 to 19.6 (p p p p = 0.203), suggesting no graft sinking or postoperative collapse. The lateral distal tibial angle showed no significant difference (p = 0.398), suggesting no postoperative ankle valgus changes. Healing of the recipient and donor sites occurred in 23 and 21 ft, respectively. The American Orthopaedic Foot and Ankle Society ankle-hindfoot scores improved significantly, from 68.0 to 98.5 (p ConclusionsEvans calcaneal lengthening using an ipsilateral mid-fibula bone autograft resulted in significant improvement in clinical and radiological outcomes without ankle valgus deformity. Hence, it could be a treatment option for lateral column calcaneal lengthening in adolescents.

Background Attention should be paid to delirium in coronavirus disease 2019 (COVID-19) patients, especially older people, since advanced age poses increased risk of both delirium and COVID-19-related death. Objective This study aims to summarise the evidence on prevalence, incidence and mortality of delirium in COVID-19 patients. Methods We conducted a comprehensive literature search on Pubmed and Embase from inception to 1 December 2020. Three independent reviewers evaluated study eligibility and data extraction, and assessed study quality. Outcomes were analysed as proportions with 95% confidence interval (CI). We also compared mortality differences in COVID-19 patients using odds ratio. Results In total, we identified 48 studies with 11,553 COVID-19 patients from 13 countries. Pooled prevalence, incidence and mortality rates for delirium in COVID-19 patients were 24.3% (95% CI: 19.4–29.6%), 32.4% (95% CI: 20.8–45.2%) and 44.5% (95% CI: 36.1–53.0%), respectively. For patients aged over 65 years, prevalence, incidence and mortality rates for delirium in COVID-19 patients were 28.2% (95% CI: 23.5–33.1%), 25.2% (95% CI: 16.0–35.6%) and 48.4% (95% CI: 40.6–56.1%), respectively. For patients under 65 years, prevalence, incidence and mortality rates for delirium in COVID-19 patients were 15.7% (95% CI: 9.2–23.6%), 71.4% (95% CI: 58.5–82.7%) and 21.2% (95% CI: 15.4–27.6%), respectively. Overall, COVID-19 patients with delirium suffered higher risk of mortality, compared with those without delirium (OR: 3.2, 95% CI: 2.1–4.8). Conclusion Delirium developed in almost 1 out of 3 COVID-19 patients, and was associated with 3-fold overall mortality. Our findings suggest that first-line healthcare providers should systematically assess delirium and monitor related symptoms among COVID-19 patients.

Cortical and hippocampal neuronal damages caused by traumatic brain injury (TBI) are associated with motor and cognitive impairments; however, only little attention paid to the striatal damage. It is known that the p53 tumor-suppressor transcription factor participated in TBI-induced secondary brain damage. We investigated how the p53 inactivator pifithrin (PFT)-α affected TBI-induced striatal neuronal damage at 24 h post-injury. Sprague-Dawley rats subjected to a controlled cortical impact were used as TBI models. We observed that p53 mRNA significantly increased, whereas p53 protein expression was distributed predominantly in neurons but not in glia cells in striatum after TBI. PFT-α improved motor deficit following TBI. PFT-α suppressed TBI-induced striatal glial activation and expression of proinflammatory cytokines. PFT-α alleviated TBI-induced oxidative damage TBI induced autophagy was evidenced by increased protein expression of Beclin-1 and shift of microtubule-associated light chain (LC)3-I to LC3-II, and decreased p62. These effects were reduced by PFT-α. Post-injury PFT-α treatment reduced the number of degenerating (FJC-positive) and apoptotic neurons. Our results suggest that PFT-α may provide neuroprotective effects via p53-dependent or -independent mechanisms depending on the cell type and timing after the TBI and can possibly be developed into a novel therapy to ameliorate TBI-induced neuronal damage.

In this paper, the neural network (NN)-based navigation satellite subset selection is presented. The approach is based on approximation or classification of the satellite geometry dilution of precision (GDOP) factors utilizing the NN approach. Without matrix inversion required, the NN-based approach is capable of evaluating all subsets of satellites and hence reduces the computational burden. This would enable the use of a high-integrity navigation solution without the delay required for many matrix inversions. For overcoming the problem of slow learning in the BPNN, three other NNs that feature very fast learning speed, including the optimal interpolative (OI) Net, probabilistic neural network (PNN) and general regression neural network (GRNN), are employed. The network performance and computational expense on NN-based GDOP approximation and classification are explored. All the networks are able to provide sufficiently good accuracy, given enough time (for BPNN) or enough training data (for the other three networks).

The neural networks (NN)-based geometry classification for good or acceptable navigation satellite subset selection is presented. The approach is based on classifying the values of satellite Geometry Dilution of Precision (GDOP) utilizing the classification-type NNs. Unlike some of the NNs that approximate the function, such as the back-propagation neural network (BPNN), the NNs here are employed as classifiers. Although BPNN can also be employed as a classifier, it takes a long training time. Two other methods that feature a fast learning speed will be implemented, including Optimal Interpolative (OI) Net and Probabilistic Neural Network (PNN). Simulation results from these three neural networks are presented. The classification performance and computational expense of neural network-based GDOP classification are explored.

Current capsule endoscope uses one camera to capture the surface image in the intestine. It can only observe the abnormal point, but cannot know the exact information of this abnormal point. Using two cameras can generate 3D images, but the visual plane changes while capsule endoscope rotates. It causes that two cameras can’t capture the images information completely. To solve this question, this research provides a new kind of capsule endoscope to capture 3D images, which is 'A 3D photographic capsule endoscope system'. The system uses three cameras to capture images in real time. The advantage is increasing the viewing range up to 2.99 times respect to the two camera system. The system can accompany 3D monitor provides the exact information of symptom points, helping doctors diagnose the disease.

This article mainly focuses on image processing of radial imaging capsule endoscope (RICE). First, it used the radial imaging capsule endoscope (RICE) to take the images, the experimental used a piggy to get the intestines and captured the images, but the images captured by RICE were blurred due to the RICE has aberration problems in the image center and lower light uniformity affect the image quality. To solve the problems, image processing can use to improve it. Therefore, the images captured by different time can use Person correlation coefficient algorithm to connect all the images, and using the color temperature mapping way to improve the discontinuous problem in the connection region.

The type of illumination systems and color filters used typically generate varying levels of color difference in capsule endoscopes, which influence medical diagnoses. In order to calibrate the color difference caused by the optical system, this study applied a radial imaging capsule endoscope (RICE) to photograph standard color charts, which were then employed to calculate the color gamut of RICE. Color gamut was also measured using a spectrometer in order to get a high-precision color information, and the results obtained using both methods were compared. Subsequently, color-correction methods, namely polynomial transform and conformal mapping, were used to improve the color difference. Before color calibration, the color difference value caused by the influences of optical systems in RICE was 21.45±1.09 . Through the proposed polynomial transformation, the color difference could be reduced effectively to 1.53±0.07 . Compared to another proposed conformal mapping, the color difference value was substantially reduced to 1.32±0.11 , and the color difference is imperceptible for human eye because it is . Then, real-time color correction was achieved using this algorithm combined with a field-programmable gate array, and the results of the color correction can be viewed from real-time images.

We investigate the switching characteristics of a silica nanoparticle-doped dual-mode liquid crystal (LC) display. In the multistable mode, aggregated silica networks impede the relaxation of LCs and increase the response time of the cell. A low-frequency AC pulse voltage rotates LCs and breaks aggregated silica networks. The breaking of silica networks accelerates the relaxation of LCs and hence decreases the response time of the cell. The low-frequency AC pulse voltage gives the cell a fast response time of ∼23 ms, which is ∼4% of our previous result.

We demonstrate a silica-nanoparticle-doped hybrid-aligned nematic device, which can be operated in the dynamic mode and the multistable mode. Under ac voltage excitation, the interfacial polarization effect between the homogeneously dispersed nanoparticles and the liquid crystal (LC) host reduces the dielectric relaxation time of the LC-silica dispersion, giving the LC cell a fast response time for the dynamic mode. Under dc voltage excitation, the silica nanoparticles accumulated on the planar side of the cell, creating agglomerates to stabilize the homeotropically aligned LCs, which is retained after switching off the voltage, giving the cell bistable/multistable switching characteristics.