Fusformer: A Transformer-based Fusion Approach for Hyperspectral Image Super-resolution

Hyperspectral image has become increasingly crucial due to its abundant spectral information. However, It has poor spatial resolution with the limitation of the current imaging mechanism. Nowadays, many convolutional neural networks have been proposed for the hyperspectral image super-resolution problem. However, convolutional neural network (CNN) based methods only consider the local information instead of the global one with the limited kernel size of receptive field in the convolution operation. In this paper, we design a network based on the transformer for fusing the low-resolution hyperspectral images and high-resolution multispectral images to obtain the high-resolution hyperspectral images. Thanks to the representing ability of the transformer, our approach is able to explore the intrinsic relationships of features globally. Furthermore, considering the LR-HSIs hold the main spectral structure, the network focuses on the spatial detail estimation releasing from the burden of reconstructing the whole data. It reduces the mapping space of the proposed network, which enhances the final performance. Various experiments and quality indexes show our approach's superiority compared with other state-of-the-art methods

Complexation between Antimony and o-Chlorophenylfluorone and its Application to Determination of Antimony in Wastewater

The formation of a chelate complex of antimony(III) with o-chlorophenylfluorone (CPF) was used for the spectrophotometric determination of antimony. The spectral correction technique was applied to characterize the complexation and the determination of SbIII. Results have shown that complex Sb(CPF)2H2O was formed and its stepwise stability constants were determined to be logK1 = 6.44 and logK2 = 5.81. The molar absorptivities of the complex at pH = 4.5 and at 540 nm were ε1 = 1.38×104 and ε2 = 3.46×104 dm3 mol–1 cm–1. The method is characterised by selectivity in the presence of the mixture of thiourea, triethanolamine and ethylenebis(oxyethylenenitrilo)-tetraacetic acid. The limit of detection is 0.03 µg cm–3 of SbIII. Analysis of wastewater samples was performed with satisfactory results. </p

Research progress on rapid determination of edible vegetable oil components

This paper summarizes the rapid detection methods of edible vegetable oil components from the aspects of analysis principle and application technology, such as simulation sensory analysis, spectral analysis, electromagnetic spectrum analysis and biochip technology. The application results of these techniques in the component mixing identification of edible vegetable were further analyzed. It was showed that the integrated online rapid detection technology of multi-channel, multi parameter and multi capacity will be the developing direction of component analysis of edible vegetable oil and will lay a technical foundation for further improving the quality supervision of edible vegetable oil and safeguarding the interests of consumers in China

Early Prediction of Gestational Diabetes Mellitus in the Chinese Population via Advanced Machine Learning

Acknowledgments We thank all those who helped to collect the data and the graduate students who took part in the statistical analysis. Financial Support: This work was supported by the National Key Research and Development Program of China (grant Nos.2018YFC1002804 and 2016YFC1000203), the National Natural Science Foundation of China (grant Nos. 81671412 and 81661128010), Program of Shanghai Academic Research Leader (grant No. 20XD1424100), the Outstanding Youth Medical Talents of Shanghai Rising Stars of Medical Talent Youth Development Program, Chinese Academy of Medical Sciences (CAMS) Innovation Fund for Medical Sciences (grant No. 2019-12M-5-064), the Foundation of Shanghai Municipal Commission of Health and Family Planning (grant No. 20144Y0110), the Natural Science Foundation of Shanghai (grant Nos. 20511101900 and 20ZR1427200), the Shanghai Shenkang Hospital Development Center, the Clinical Technology Innovation Project (grant Nos. SHDC12019107), and the Clinical Skills Improvement Foundation of Shanghai Jiaotong University School of Medicine (grant No. JQ201717).Peer reviewedPublisher PD

Licochalcone A exerts antitumor activity in bladder cancer cell lines and mice models

Purpose: To investigate the effect of licochalcone A (LA) on the inhibition of cell proliferation and ERK1/2 phosphorylation in bladder carcinoma cell lines.Methods: Cell viability was investigated using 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazoliumbromide (MTT) assay. Dye-binding method was used to examine the concentration of proteins. Lymphocytes were extracted from mice and after surface staining were subjected to BD fixation and permeabilization for intracellular staining. Flow cytometry was used to measure cellular fluorescence.Results: MTT results revealed a significant decrease in the proliferation of UM-UC-3, J82 and HT-1197 cell lines on treatment with LA. LA also induced reduction in phosphorylation of ERK1/2 in all three carcinoma cell lines. In the mouse model, licochalcone A treatment via intraperitoneal (ip) administration induced a significant decrease in the level of regulatory T cells (Tregs). Comparison of the mouse interferon-α (IFN-α)-treated and LA-treated groups revealed that LA treatment caused enhancement of cytotoxic T lymphocyte (CTL) activity similar to that of IFN-α. Administration of UM-UC-3 cells in C3H/HeN mice resulted in marked reduction in the counts for splenocytes and CD4+ CD25+ Foxp3+ T (regulatory T cells) cell proportion in LA-treated mice compared to untreated control group.Conclusion: Licochalcone A may be of therapeutic importance for the prevention of bladder carcinoma. However, studies are required to ascertain the compound’s usefulness in this regard.Keywords: Licochalcone A, Bladder carcinoma, Splenocytes, Phosphorylation, Cell proliferation, Interfero

Fate of Antibiotic Resistant Pseudomonas putida and Broad Host Range Plasmid in Natural Soil Microcosms

Plasmid conjugation is one of the dominant mechanisms of horizontal gene transfer, playing a noticeable role in the rapid spread of antibiotic resistance genes (ARGs). Broad host range plasmids are known to transfer to diverse bacteria in extracted soil bacterial communities when evaluated by filter mating incubation. However, the persistence and dissemination of broad range plasmid in natural soil has not been well studied. In this study, Pseudomonas putida with a conjugative antibiotic resistance plasmid RP4 was inoculated into a soil microcosm, the fate and persistence of P. putida and RP4 were monitored by quantitative PCR. The concentrations of P. putida and RP4 both rapidly decreased within 15-day incubation. P. putida then decayed at a significantly lower rate during subsequent incubation, however, no further decay of RP4 was observed, resulting in an elevated RP4/P. putida ratio (up to 10) after 75-day incubation, which implied potential transfer of RP4 to soil microbiota. We further sorted RP4 recipient bacteria from the soil microcosms by fluorescence-activated cell sorting. Spread of RP4 increased during 75-day microcosm operation and was estimated at around 10-4 transconjugants per recipient at the end of incubation. Analysis of 16S rRNA gene sequences of transconjugants showed that host bacteria of RP4 were affiliated to more than 15 phyla, with increased diversity and shift in the composition of host bacteria. Proteobacteria was the most dominant phylum in the transconjugant pools. Transient transfer of RP4 to some host bacteria was observed. These results emphasize the prolonged persistence of P. putida and RP4 in natural soil microcosms, and highlight the potential risks of increased spread potential of plasmid and broader range of host bacteria in disseminating ARGs in soil

Risk factors, clinical features, and outcomes of patients with hypertrophic cardiomyopathy complicated by ischemic stroke: A single-center retrospective study

ObjectiveThis study aimed to explore risk factors, clinical features, and prognosis of patients with hypertrophic cardiomyopathy (HCM) complicated by ischemic stroke (IS).MethodsWe conducted a retrospective analysis of all HCM patient data and a 1-year follow-up study.ResultsTotally, 506 patients with HCM, including 71 with IS, were enrolled. Older age (≥63 years) was associated with an increased risk of IS in HCM patients (OR = 1.045, 95% CI: 1.018–1.072, p = 0.001). Among 37 patients complicated by IS, 22 (59.5%, 22/37) manifested as cardioembolism (CE) subtype, and 13 (35.1%, 3/37) small artery occlusion (SAO) subtype, according to TOAST classification. In the acute phase, the IS patients presented with NIHSS 4 (interquartile range: 1, 10). Multi-infarction was more common than single infarction (72.7 vs. 27.3%), while cortical + subcortical infarction (CE group: 50%) or subcortical infarction (SAO group: 53.8%) constituted most IS cases. Additionally, the blood supply areas of anterior circulation (CE group: 45.5%; SAO group: 92.3%) or anterior + posterior circulation (CE group: 50%) were mainly involved. The 1-year survival rate of HCM patients with concomitant IS was 81.8%, and IS was associated with 1-year all-cause death in HCM patients (HR = 5.689, 95% CI: 1.784–18.144, p = 0.003).ConclusionOlder age is a risk factor for IS occurrence in HCM patients. Patients with HCM complicated by IS had mild or moderate neurologic deficits at disease onset. CE and SAO subtypes predominate in patients with concomitant IS, especially the former. Multiple cortical and subcortical infarctions are their neuroimaging characteristics, mainly involving the anterior circulation or anterior + posterior circulation. Is is a risk factor for all-cause death in HCM patients within 1 year

A New Variational Approach Based on Proximal Deep Injection and Gradient Intensity Similarity for Spatio-Spectral Image Fusion

Pansharpening is a very debated spatio-spectral fusion problem. It refers to the fusion of a high spatial resolution panchromatic image with a lower spatial but higher spectral resolution multispectral image in order to obtain an image with high resolution in both the domains. In this article, we propose a novel variational optimization-based (VO) approach to address this issue incorporating the outcome of a deep convolutional neural network (DCNN). This solution can take advantages of both the paradigms. On one hand, higher performance can be expected introducing machine learning (ML) methods based on the training by examples philosophy into VO approaches. On other hand, the combination of VO techniques with DCNNs can aid the generalization ability of these latter. In particular, we formulate a $\ell _2$ -based proximal deep injection term to evaluate the distance between the DCNN outcome, and the desired high spatial resolution multispectral image. This represents the regularization term for our VO model. Furthermore, a new data fitting term measuring the spatial fidelity is proposed. Finally, the proposed convex VO problem is efficiently solved by exploiting the framework of the alternating direction method of multipliers (ADMM), thus guaranteeing the convergence of the algorithm. Extensive experiments both on simulated, and real datasets demonstrate that the proposed approach can outperform state-of-the-art spatio-spectral fusion methods, even showing a significant generalization ability. Please find the project page at https://liangjiandeng.github.io/Projects_Res/DMPIF_2020jstars.html