Self-supervised vision-language pretraining for Medical visual question answering

Medical image visual question answering (VQA) is a task to answer clinical questions, given a radiographic image, which is a challenging problem that requires a model to integrate both vision and language information. To solve medical VQA problems with a limited number of training data, pretrain-finetune paradigm is widely used to improve the model generalization. In this paper, we propose a self-supervised method that applies Masked image modeling, Masked language modeling, Image text matching and Image text alignment via contrastive learning (M2I2) for pretraining on medical image caption dataset, and finetunes to downstream medical VQA tasks. The proposed method achieves state-of-the-art performance on all the three public medical VQA datasets. Our codes and models are available at https://github.com/pengfeiliHEU/M2I2.Comment: 5 pages, 3 figure

Gene and Pathway-Based Analysis: Second Wave of Genome-wide Association Studies

Despite great success of GWAS in identification of common genetic variants associated with complex diseases, the current GWAS have focused on single SNP analysis. However, single SNP analysis often identifies a number of the most significant SNPs that account for only a small proportion of the genetic variants and offers limited understanding of complex diseases. To overcome these limitations, we propose gene and pathway-based association analysis as a new paradigm for GWAS. As a proof of concept, we performed a comprehensive gene and pathway-based association analysis for thirteen published GWAS. Our results showed that the proposed new paradigm for GWAS not only identified the genes that include significant SNPs found by single SNP analysis, but also detected new genes in which each single SNP conferred small disease risk, but their joint actions were implicated in the development of diseases. The results also demonstrated that the new paradigm for GWAS was able to identify biologically meaningful pathways associated with the diseases which were confirmed by gene-set rich analysis using gene expression data

Direct single-molecule dynamic detection of chemical reactions.

Single-molecule detection can reveal time trajectories and reaction pathways of individual intermediates/transition states in chemical reactions and biological processes, which is of fundamental importance to elucidate their intrinsic mechanisms. We present a reliable, label-free single-molecule approach that allows us to directly explore the dynamic process of basic chemical reactions at the single-event level by using stable graphene-molecule single-molecule junctions. These junctions are constructed by covalently connecting a single molecule with a 9-fluorenone center to nanogapped graphene electrodes. For the first time, real-time single-molecule electrical measurements unambiguously show reproducible large-amplitude two-level fluctuations that are highly dependent on solvent environments in a nucleophilic addition reaction of hydroxylamine to a carbonyl group. Both theoretical simulations and ensemble experiments prove that this observation originates from the reversible transition between the reactant and a new intermediate state within a time scale of a few microseconds. These investigations open up a new route that is able to be immediately applied to probe fast single-molecule physics or biophysics with high time resolution, making an important contribution to broad fields beyond reaction chemistry

A New Race (X12) of Soybean Cyst Nematode in China

The soybean cyst nematode (SCN), Heterodera glycines, is a serious economic threat to soybean-producing regions worldwide. A new SCN population (called race X12) was detected in Shanxi province, China. Race X12 could reproduce on all the indicator lines of both race and Heterodera glycines (HG) type tests. The average number of females on Lee68 (susceptible control) was 171.40 with the lowest Female Index (FI) 61.31 on PI88788 and the highest FI 117.32 on Pickett in the race test. The average number of females on Lee68 was 323.17 with the lowest FI 44.18 on PI88788 and the highest FI 97.83 on PI548316 in the HG type test. ZDD2315 and ZDD24656 are elite resistant germplasms in China. ZDD2315 is highly resistant to race 4, the strongest infection race in the 16 races with FI 1.51 while being highly sensitive to race X12 with FI 64.32. ZDD24656, a variety derived from PI437654 and ZDD2315, is highly resistant to race 1 and race 2. ZDD24656 is highly sensitive to race X12 with FI 99.12. Morphological and molecular studies of J2 and cysts confirmed the population as the SCN H. glycines. This is a new SCN race with stronger virulence than that of race 4 and is a potential threat to soybean production in China