Sun Yat-sen University

About: Sun Yat-sen University is a education organization based out in Guangzhou, Guangdong, China. It is known for research contribution in the topics: Population & Cancer. The organization has 115149 authors who have published 113763 publications receiving 2286465 citations. The organization is also known as: Zhongshan University & SYSU.

Diarrhoea may be underestimated: a missing link in 2019 novel coronavirus.

Abstract: A series of pneumonia cases caused by 2019 novel coronavirus (2019-nCoV, also named COVID-19) are being reported globally. Based on recent publications,1–3 the most common symptoms in patients infected by 2019-nCoV were fever and cough. However, the incidence of other clinical features differs in different reports. To address this issue, we collected the data from three reports1–3 and compared the incidence accordingly. We found that the incidence of leucopenia, fever and diarrhoea in the three studies showed a statistically significant difference (table 1). Among these symptoms, diarrhoea displayed the smallest p-value (p=0.016), suggesting that the criteria for diagnosing diarrhoea may differ in different hospitals. Due to the different criteria, clinicians may underestimate the value of this symptom in clinical practice, and it may affect the preliminary diagnostic accuracy. View this table: Table 1 Intergroup comparison between three recent publications Recent studies showed that the spike protein of 2019-nCoV shared the same cell entry receptor ACE2 as SARS-CoV.4 5 In terms of the pathological importance of ACE2 in modulating intestinal inflammation and diarrhoea,6 we examined the expression profiles of ACE2 in various human tissues and found that ACE2 was highly expressed in the human small intestine (online supplementary file 1). Intriguingly, the RNA level of ACE2 was quite low in lung tissues from healthy donors.### Supplementary data [gutjnl-2020-320832supp001.pdf] Given that the distribution of ACE2 may determine the route of 2019-nCoV infection, we next evaluated the expression of ACE2 in different cell …

Transferrable Prototypical Networks for Unsupervised Domain Adaptation

Abstract: In this paper, we introduce a new idea for unsupervised domain adaptation via a remold of Prototypical Networks, which learn an embedding space and perform classification via a remold of the distances to the prototype of each class. Specifically, we present Transferrable Prototypical Networks (TPN) for adaptation such that the prototypes for each class in source and target domains are close in the embedding space and the score distributions predicted by prototypes separately on source and target data are similar. Technically, TPN initially matches each target example to the nearest prototype in the source domain and assigns an example a ``pseudo" label. The prototype of each class could then be computed on source-only, target-only and source-target data, respectively. The optimization of TPN is end-to-end trained by jointly minimizing the distance across the prototypes on three types of data and KL-divergence of score distributions output by each pair of the prototypes. Extensive experiments are conducted on the transfers across MNIST, USPS and SVHN datasets, and superior results are reported when comparing to state-of-the-art approaches. More remarkably, we obtain an accuracy of 80.4% of single model on VisDA 2017 dataset.

Magnetic and highly recyclable macroporous carbon nanotubes for spilled oil sorption and separation.

Abstract: Development of sorbent materials with high selectivity and sorption capacity, easy collection and recyclability is demanding for spilled oil recovery. Although many sorption materials have been proposed, a systematic study on how they can be reused and possible performance degradation during regeneration remains absent. Here we report magnetic carbon nanotube sponges (Me-CNT sponge), which are porous structures consisting of interconnected CNTs with rich Fe encapsulation. The Me-CNT sponges show high mass sorption capacity for diesel oil reached 56 g/g, corresponding to a volume sorption capacity of 99%. The sponges are mechanically strong and oil can be squeezed out by compression. They can be recycled using through reclamation by magnetic force and desorption by simple heat treatment. The Me-CNT sponges maintain original structure, high capacity, and selectivity after 1000 sorption and reclamation cycles. Our results suggest that practical application of CNT macrostructures in the field of spilled oil r...

Astrocyte elevated gene-1 is a novel prognostic marker for breast cancer progression and overall patient survival.

Abstract: Purpose: The present study was aimed at clarifying the expression of astrocyte elevated gene-1 ( AEG-1 ), one of the target genes of oncogenic Ha-ras, in breast cancer and its correlation with clinicopathologic features, including the survival of patients with breast cancer. Experimental Design: The expression of AEG-1 in normal breast epithelial cells, breast cancer cell lines, and in four cases of paired primary breast tumor and normal breast tissue was examined using reverse transcription-PCR and Western blot. Real-time reverse transcription-PCR was applied to determine the mRNA level of AEG-1 in the four paired tissues, each from the same subject. Furthermore, AEG-1 protein expression was analyzed in 225 clinicopathologically characterized breast cancer cases using immunohistochemistry. Statistical analyses were applied to test for the prognostic and diagnostic associations. Results: Western blot and reverse transcription-PCR showed that the expression level of AEG-1 was markedly higher in breast cancer cell lines than that in the normal breast epithelial cells at both mRNA and protein levels. AEG-1 expression levels were significantly up-regulated by up to 35-fold in primary breast tumors in comparison to the paired normal breast tissue from the same patient. Immunohistochemical analysis revealed high expression of AEG-1 in 100 of 225 (44.4%) paraffin-embedded archival breast cancer biopsies. Statistical analysis showed a significant correlation of AEG-1 expression with the clinical staging of the patients with breast cancer ( P = 0.001), as well as with the tumor classification ( P = 0.004), node classification ( P = 0.026), and metastasis classification ( P = 0.001). Patients with higher AEG-1 expression had shorter overall survival time, whereas patients with lower AEG-1 expression had better survival. Multivariate analysis suggested that AEG-1 expression might be an independent prognostic indicator for the survival of patients with breast cancer. Conclusions: Our results suggest that AEG-1 protein is a valuable marker of breast cancer progression. High AEG-1 expression is associated with poor overall survival in patients with breast cancer.