Oxytocin is implicated in social memory deficits induced by early sensory deprivation in mice

Acknowledgements We thank Miss Jia-Yin and Miss Yu-Ling Sun for their help in breading the mice. Funding This work was supported by grants from the National Natural Science Foundation of China (81200933 to N.-N. Song; 81200692 to L. Chen; 81101026 to Y. Huang; 31528011 to B. Lang; 81221001, 91232724 and 81571332 to Y-Q. Ding), Zhejiang Province Natural Science Foundation of China (LQ13C090004 to C. Zhang), China Postdoctoral Science Foundation (2016 M591714 to C.-C. Qi), and the Fundamental Research Funds for the Central Universities (2013KJ049).Peer reviewedPublisher PD

Weakly Supervised Anomaly Detection for Chest X-Ray Image

Chest X-Ray (CXR) examination is a common method for assessing thoracic diseases in clinical applications. While recent advances in deep learning have enhanced the significance of visual analysis for CXR anomaly detection, current methods often miss key cues in anomaly images crucial for identifying disease regions, as they predominantly rely on unsupervised training with normal images. This letter focuses on a more practical setup in which few-shot anomaly images with only image-level labels are available during training. For this purpose, we propose WSCXR, a weakly supervised anomaly detection framework for CXR. WSCXR firstly constructs sets of normal and anomaly image features respectively. It then refines the anomaly image features by eliminating normal region features through anomaly feature mining, thus fully leveraging the scarce yet crucial features of diseased areas. Additionally, WSCXR employs a linear mixing strategy to augment the anomaly features, facilitating the training of anomaly detector with few-shot anomaly images. Experiments on two CXR datasets demonstrate the effectiveness of our approach

Innovating Computational Biology and Intelligent Medicine: ICIBM 2019 Special Issue

The International Association for Intelligent Biology and Medicine (IAIBM) is a nonprofit organization that promotes intelligent biology and medical science. It hosts an annual International Conference on Intelligent Biology and Medicine (ICIBM), which was established in 2012. The ICIBM 2019 was held from 9 to 11 June 2019 in Columbus, Ohio, USA. Out of the 105 original research manuscripts submitted to the conference, 18 were selected for publication in a Special Issue in Genes. The topics of the selected manuscripts cover a wide range of current topics in biomedical research including cancer informatics, transcriptomic, computational algorithms, visualization and tools, deep learning, and microbiome research. In this editorial, we briefly introduce each of the manuscripts and discuss their contribution to the advance of science and technology

Inhibition of SARS Pseudovirus Cell Entry by Lactoferrin Binding to Heparan Sulfate Proteoglycans

It has been reported that lactoferrin (LF) participates in the host immune response against Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV) invasion by enhancing NK cell activity and stimulating neutrophil aggregation and adhesion. We further investigated the role of LF in the entry of SARS pseudovirus into HEK293E/ACE2-Myc cells. Our results reveal that LF inhibits SARS pseudovirus infection in a dose-dependent manner. Further analysis suggested that LF was able to block the binding of spike protein to host cells at 4°C, indicating that LF exerted its inhibitory function at the viral attachment stage. However, LF did not disrupt the interaction of spike protein with angiotensin-converting enzyme 2 (ACE2), the functional receptor of SARS-CoV. Previous studies have shown that LF colocalizes with the widely distributed cell-surface heparan sulfate proteoglycans (HSPGs). Our experiments have also confirmed this conclusion. Treatment of the cells with heparinase or exogenous heparin prevented binding of spike protein to host cells and inhibited SARS pseudovirus infection, demonstrating that HSPGs provide the binding sites for SARS-CoV invasion at the early attachment phase. Taken together, our results suggest that, in addition to ACE2, HSPGs are essential cell-surface molecules involved in SARS-CoV cell entry. LF may play a protective role in host defense against SARS-CoV infection through binding to HSPGs and blocking the preliminary interaction between SARS-CoV and host cells. Our findings may provide further understanding of SARS-CoV pathogenesis and aid in treatment of this deadly disease

The International Conference on Intelligent Biology and Medicine 2019 (ICIBM 2019): computational methods and applications in medical genomics

In this editorial, we briefly summarized the International Conference on Intelligent Biology and Medicine 2019 (ICIBM 2019) that was held on June 9-11, 2019 at Columbus, Ohio, USA. We further introduced the 19 research articles included in this supplement issue, covering four major areas, namely computational method development, genomics analysis, network-based analysis and biomarker prediction. The selected papers perform cutting edge computational research applied to a broad range of human diseases such as cancer, neural degenerative and chronic inflammatory disease. They also proposed solutions for fundamental medical genomics problems range from basic data processing and quality control to functional interpretation, biomarker and drug prediction, and database releasing