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关键词： Pharmacology/Toxicology   Neurosciences  

关键词： Basal insulin   Glycemic control   Hypoglycemia   Weight gain   Type 1 diabetes   Network meta-analysis  

摘要： We aimed to assess the comparative efficacy and safety of second-generation basal insulins (glargine U300 and degludec U100) vs. neutral protamine Hagedorn (NPH) and first-generation basal insulins (glargine U100 and detemir) in type 1 diabetes (T1D) adults. PubMed, the Cochrane Library, ***, and Google Scholar (until January 2021) were systematically searched. Randomized controlled trials (RCTs) with >= 12 weeks of follow-up comparing efficacy (HbA(1c)) or safety (hypoglycemia and weight gain) between second-generation basal insulins vs. other basal insulins in T1D adults were included. Bayesian network meta-analyses were used to estimate risk ratio, hazard ratio, and mean difference. Grading of Recommendations, Assessment, Development and Evaluation (GRADE) was used to appraise evidence certainty. Eighteen RCTs (>= 24 weeks of follow-up) involving 7283 randomized participants were included for main analysis. Moderate to high certainty evidence suggested that second-generation basal insulins showed equivalent HbA(1c) reduction compared with NPH and first-generation basal insulins. Compared with second-generation basal insulins, low to high certainty evidence suggested that NPH was associated with a higher risk of patients experiencing severe hypoglycemia;NPH and first-generation basal insulins were associated with a higher rate of nocturnal confirmed hypoglycemic events. For the weight gain, glargine U300 was comparable to detemir (low certainty), but degludec U100 was greater than detemir (moderate certainty). In conclusion, second-generation basal insulins maintained equivalent efficacy of glycemic control (moderate to high certainty), with differences in safety (low to high certainty) compared with NPH and first-generation basal insulins during >= 24 weeks of follow-up in T1D adults.

关键词： hyperspectral image (HSI)   multilayer perceptrons (MLPs)   spectral-spatial classification  

摘要： Convolutional neural networks (CNNs) are the go-to model for hyperspectral image (HSI) classification because of the excellent locally contextual modeling ability that is beneficial to spatial and spectral feature extraction. However, CNNs with a limited receptive field pose challenges for modeling long-range dependencies. To solve this issue, we introduce a novel classification framework which regards the input HSI as a sequence data and is constructed exclusively with multilayer perceptrons (MLPs). Specifically, we propose a spectral-spatial MLP (SS-MLP) architecture, which uses matrix transposition and MLPs to achieve both spectral and spatial perception in global receptive field, capturing long-range dependencies and extracting more discriminative spectral-spatial features. Four benchmark HSI datasets are used to evaluate the classification performance of the proposed SS-MLP. Experimental results show that our pure MLP-based architecture outperforms other state-of-the-art convolution-based models in terms of both classification performance and computational time. When comparing with the SSSERN model, the average accuracy improvement of our approach is as high as 3.03%. We believe that our impressive experimental results will foster additional research on simple yet effective MLP-based architecture for HSI classification.

关键词： Oral cancer   squamous cell carcinoma   chemoradiotherapy   maxillofacial surgery   adjuvant  

摘要： Patients with locally advanced oral squamous cell cancer (LAOSCC) are treated with adjuvant radiotherapy (RT) or chemoradiotherapy (CRT) following surgical ablation. This depends on the pathological risk factors and aims to reduce the risk of local recurrence and improve survival. Delivery of these aggressive treatments is, however, challenging particularly following major surgery. To inform the adaptations necessary to deliver gold-standard therapy, we aimed to describe real-world delivery of multimodality treatment in LAOSCC, in a UK population with high levels of disease incidence and low socioeconomic status. Patients with LAOSCC (T1-4 N1-3/T3-4 N0) who were treated between October 2014 and October 2016 and had a minimum follow up of 24 months were included. They were identified using the Somerset Cancer Register and data were collected through retrospective case note review. Approval was obtained from the audit departments at the relevant NHS institutions, and data were analysed using IBM SPSS Statistics for Windows version 24 (IBM Corp). The analysis included 129 patients with 82% having an initial performance status (PS) of 0-1. The most frequent change in PS was a one point drop (46%). Twenty of the 93 eligible patients (22%) underwent adjuvant CRT. A total of 37 (40%) began adjuvant CRT/RT within 42 days, and 79 (85%) within 56 days. A delay in initiating adjuvant therapy was associated with higher rates of complications and a longer postoperative hospital stay. Concordance between imaging and pathological nodal staging was poor (cK 0.223). PS frequently declines after complex surgical procedures and long postoperative recovery periods, leading to difficulties providing adjuvant treatments within the national guidance of 42 days. Frequent deviation from planned adjuvant therapies highlights the need for improved treatment strategies. (c) 2020 The British Association of Oral and Maxillofacial Surgeons. Published by Elsevier Ltd. All rights reserved.

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关键词： biomass   browning degree   computer-aided vision technology   noninvasive quantitative method   Siraitia grosvenorii  

摘要： The rapid, accurate and noninvasive detection of biomass and plant cell browning can provide timely feedback on cell growth in plant cell culture. In this study, Siraitia grosvenorii suspension cells were taken as an example, a phenotype analysis platform was successfully developed to predict the biomass and the degree of cell browning based on the color changes of cells in computer-aided vision technology. First, a self-made laboratory system was established to obtain images. Then, matrices were prepared from digital images by a self-developed high-throughput image processing tool. Finally, classification models were used to judge different cell types, and then a semi-supervised classification to predict different degrees of cell browning. Meanwhile, regression models were developed to predict the plant cell mass. All models were verified with a good agreement by biological experiments. Therefore, this method can be applied for low-cost biomass estimation and browning degree quantification in plant cell culture.

关键词： High-frequency ultrasound   Basal cell carcinoma   Dermatology  

摘要： The purpose of the study was to evaluate the value of high-frequency ultrasound (HFUS) for differentiating invasive basal cell carcinomas (BCCs) from non-invasive BCCs. We established a prediction model based on ultrasound features and validated it further. One hundred patients in the pilot cohort and another 43 in the validation cohort were evaluated. All patients underwent HFUS examinations by the same radiologist, and then were divided on the basis of pathology into invasive and non-invasive types. With respect to growth pattern, 60.5% of invasive BCCs had an irregular pattern, whereas 89.5% of non-invasive BCCs had a nodular or crawling pattern (p < 0.001). As for the layers involved, the more invasive BCCs broke through the dermis compared with non-invasive BCCs (23.3% vs. 1.8%) (p < 0.001). With respect to intralesional hyperechoic spot distribution, invasive and non-invasive BCCs tended to be clustered and absent/scattered-like, respectively (55.8% vs. 91.2%) (p < 0.001). On the basis of the aforementioned features, a prediction model was established with accuracies of 84.0% and 76.7%, respectively, in the pilot and validation cohorts. HFUS holds promise for the differentiation of the invasiveness of BCCs and is helpful in its clinical management. (C) 2021 Published by Elsevier Inc. on behalf of World Federation for Ultrasound in Medicine & Biology.