In this paper, we propose a novel face detection network with three novel contributions that address three key aspects of face detection, including better feature learning, progressive loss design and anchor assign based data augmentation, respectively. First, we propose a Feature Enhance Module (FEM) for enhancing the original feature maps to extend the single shot detector to dual shot detector. Second, we adopt Progressive Anchor Loss (PAL) computed by two different sets of anchors to effectively facilitate the features. Third, we use an Improved Anchor Matching (IAM) by integrating novel anchor assign strategy into data aug-

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The role of microbiota in health and diseases is being highlighted by numerous studies since its discovery. Depending on the localized regions, microbiota can be classified into gut, oral, respiratory, and skin microbiota. The microbial communities are in symbiosis with the host, contributing to homeostasis and regulating immune function. However, microbiota dysbiosis can lead to dysregulation of bodily functions and diseases including cardiovascular diseases (CVDs), cancers, respiratory diseases, etc. In this review, we discuss the current knowledge of how microbiota links to host health or pathogenesis. We first summarize the research of microbiota in healthy conditions, including the gut-brain axis, colonization resistance and immune modulation. Then, we highlight the pathogenesis of microbiota dysbiosis in disease development and progression, primarily associated with dysregulation of community composition, modulation of host immune response, and induction of chronic inflammation. Finally, we introduce the clinical approaches that utilize microbiota for disease treatment, such as microbiota modulation and fecal microbial transplantation.

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We conducted a joint (pooled) analysis of three genome-wide association studies (GWAS) 1-3 of esophageal squamous cell carcinoma (ESCC) in ethnic Chinese (5,337 ESCC cases and 5,787 controls) with 9,654 ESCC cases and 10,058 controls for follow-up. In a logistic regression model adjusted for age, sex, study, and two eigenvectors, two new loci achieved genome-wide significance, marked by rs7447927 at 5q31.2 (per-allele odds ratio (OR) = 0.85, 95% CI 0.82-0.88; P=7.72x10−20) and rs1642764 at 17p13.1 (per-allele OR= 0.88, 95% CI 0.85-0.91; P=3.10x10−13). rs7447927 is a synonymous single nucleotide polymorphism (SNP) in TMEM173 and rs1642764 is an intronic SNP in ATP1B2, near TP53. Furthermore, a locus in the HLA class II region at 6p21.32 (rs35597309) achieved genome-wide significance in the two populations at highest risk for ESSC (OR=1.33, 95% CI 1.22-1.46; P=1.99x10−10). Our joint analysis identified new ESCC susceptibility loci overall as well as a new locus unique to the ESCC high risk Taihang Mountain region.

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