Hubs with Network Motifs Organize Modularity Dynamically in the Protein-Protein Interaction Network of Yeast

BACKGROUND: It has been recognized that modular organization pervades biological complexity. Based on network analysis, 'party hubs' and 'date hubs' were proposed to understand the basic principle of module organization of biomolecular networks. However, recent study on hubs has suggested that there is no clear evidence for coexistence of 'party hubs' and 'date hubs'. Thus, an open question has been raised as to whether or not 'party hubs' and 'date hubs' truly exist in yeast interactome. METHODOLOGY: In contrast to previous studies focusing on the partners of a hub or the individual proteins around the hub, our work aims to study the network motifs of a hub or interactions among individual proteins including the hub and its neighbors. Depending on the relationship between a hub's network motifs and protein complexes, we define two new types of hubs, 'motif party hubs' and 'motif date hubs', which have the same characteristics as the original 'party hubs' and 'date hubs' respectively. The network motifs of these two types of hubs display significantly different features in spatial distribution (or cellular localizations), co-expression in microarray data, controlling topological structure of network, and organizing modularity. CONCLUSION: By virtue of network motifs, we basically solved the open question about 'party hubs' and 'date hubs' which was raised by previous studies. Specifically, at the level of network motifs instead of individual proteins, we found two types of hubs, motif party hubs (mPHs) and motif date hubs (mDHs), whose network motifs display distinct characteristics on biological functions. In addition, in this paper we studied network motifs from a different viewpoint. That is, we show that a network motif should not be merely considered as an interaction pattern but be considered as an essential function unit in organizing modules of networks

Facial image synthesis

With the ability to carry out challenging tasks such as photo generation, Generative Adversarial Networks have attracted increasing attention and achieved impressive progress in recent years [6]. Researchers are also exploring its possible applications for more complex tasks such as facial image synthesis. GAN has proven to have an outstanding performance in carrying out facial expression and attribute editing. A well-trained model could easily transform a facial image with one specific attribute/expression to another while preserving the identity information [7]. In this project, we will first discuss, in a very brief manner, the general problems that are faced by researchers in facial image synthesis. Subsequently, we will evaluate the common practices to solve those problems and their respective limitations. We will carry out an analysis on two advanced approaches, StarGan[2] and STGan[10], and discuss their respective ways to carry out facial image generation. . We will also explore the possibility of combining the best parts of these two models so that our designed facial expression GAN, CombineGAN, will be able to address both image feature transfer and quality issues. One possible way is to utilize STGan’s generator, built from a selective transfer perspective where Selective Transfer Units (STU) are built in the encoder-decoder generator architecture for it to adaptively choose and modify the encoder feature for an improved facial image synthesis. We will adopt evaluation metrics such as Inception Score (IS) and Frechet Inception Distance (FID) [18] to quantitively evaluate the model’s performance. We will also use qualitative method such as Amazon Mechanical Turk (AMT) [14] to evaluate the model performance from a human’s perspective. Lastly, our model will be applied to translate real life images for us to better understand its performance in a different context.Bachelor of Engineering (Computer Science

The effectiveness of influenza vaccine among elderly Chinese: A regression discontinuity design based on Yinzhou regional health information platform

In China, a free influenza vaccination policy is being implemented among individuals aged 70 years and over in Zhejiang province during the COVID-19 pandemic. The objective was to assess the effectiveness of influenza vaccine in reducing hospitalization and mortality in the elderly. We used data from the Regional Health Information Platform in Yinzhou located in Zhejiang province and applied a regression discontinuity design to estimate the intention-to-treat effect on admission and mortality rates by month of age in the population who was near the age of 70 years threshold. At age 70 years, the influenza vaccination rate increased by 29.1% (95% CI, 28.2% to 29.9%) compared to those under 70 in the study population. When turning age 70 years, the potential effectiveness of receiving influenza vaccine was 8.2% (95% CI, −36.8% to 51.3%) for total hospitalization and the evaluation of vaccine effectiveness was 13.1% (95% CI, −34.2 to 61.8) for the all-cause mortality. An increase in the influenza vaccination rate was associated with a weak decline in most outcomes, but no significance was found for all outcomes. Influenza vaccination had a limited effect on hospital admission and mortality for the free influenza vaccination program that can be related to the low vaccination rate among the Chinese elderly. Supplementation strategies and future studies may be needed to expand immunization coverage and validate this finding, and further provide a reference for other cities to promote the free influenza vaccination policy in China, especially under circumstances of the COVID-19 pandemic

Genotyping of Enterocytozoon bieneusi and Subtyping of Blastocystis in Cancer Patients: Relationship to Diarrhea and Assessment of Zoonotic Transmission

Enterocytozoon bieneusi (E. bieneusi) and Blastocystis are common pathogens responsible for diarrhea in humans, especially in immunocompromised individuals. The number of cancer patients has been increasing and diarrhea is a common clinical symptom in the treatment of cancers. To understand the prevalences and genotypes/subtypes of E. bieneusi and Blastocystis in cancer patients in China, to track the infection sources, and to explore the relationships between E. bieneusi and Blastocystis infections and diarrhea, 381 fecal specimens were collected from cancer patients. Each of them was analyzed for the presence of E. bieneusi and Blastocystis by PCR amplifying and sequencing the ITS region of the rRNA gene and the barcode region of the SSU rRNA gene, respectively. 1.3 and 7.1% of cancer patients were positive for E. bieneusi and Blastocystis, respectively. No statistical differences were observed in the infection rates between the groups by age, gender, and residence. E. bieneusi and Blastocystis were both significantly more common in cancer patients with diarrhea, and significant relationship of Blastocystis to diarrhea was found in chemotherapy group. Two E. bieneusi genotypes (D and a novel one named as HLJ-CP1) and two Blastocystis subtypes (ST1 and ST3) were identified with three novel ST1 sequences. This is the first report of occurrence and molecular characterizations of E. bieneusi and Blastocystis in cancer patients in China. E. bieneusi genotype D and Blastocystis ST1 and ST3 have been identified in humans and animals while one novel E. bieneusi genotype falling into zoonotic group 1, implying a potential of zoonotic transmission