DigestPath: A benchmark dataset with challenge review for the pathological detection and segmentation of digestive-system.

Examination of pathological images is the golden standard for diagnosing and screening many kinds of cancers. Multiple datasets, benchmarks, and challenges have been released in recent years, resulting in significant improvements in computer-aided diagnosis (CAD) of related diseases. However, few existing works focus on the digestive system. We released two well-annotated benchmark datasets and organized challenges for the digestive-system pathological cell detection and tissue segmentation, in conjunction with the International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI). This paper first introduces the two released datasets, i.e., signet ring cell detection and colonoscopy tissue segmentation, with the descriptions of data collection, annotation, and potential uses. We also report the set-up, evaluation metrics, and top-performing methods and results of two challenge tasks for cell detection and tissue segmentation. In particular, the challenge received 234 effective submissions from 32 participating teams, where top-performing teams developed advancing approaches and tools for the CAD of digestive pathology. To the best of our knowledge, these are the first released publicly available datasets with corresponding challenges for the digestive-system pathological detection and segmentation. The related datasets and results provide new opportunities for the research and application of digestive pathology.

Automated tumor proportion score analysis for PD-L1 (22C3) expression in lung squamous cell carcinoma.

Programmed cell death ligend-1 (PD-L1) expression by immunohistochemistry (IHC) assays is a predictive marker of anti-PD-1/PD-L1 therapy response. With the popularity of anti-PD-1/PD-L1 inhibitor drugs, quantitative assessment of PD-L1 expression becomes a new labor for pathologists. Manually counting the PD-L1 positive stained tumor cells is an obviously subjective and time-consuming process. In this paper, we developed a new computer aided Automated Tumor Proportion Scoring System (ATPSS) to determine the comparability of image analysis with pathologist scores. A three-stage process was performed using both image processing and deep learning techniques to mimic the actual diagnostic flow of the pathologists. We conducted a multi-reader multi-case study to evaluate the agreement between pathologists and ATPSS. Fifty-one surgically resected lung squamous cell carcinoma were prepared and stained using the Dako PD-L1 (22C3) assay, and six pathologists with different experience levels were involved in this study. The TPS predicted by the proposed model had high and statistically significant correlation with sub-specialty pathologists' scores with Mean Absolute Error (MAE) of 8.65 (95% confidence interval (CI): 6.42-10.90) and Pearson Correlation Coefficient (PCC) of 0.9436 ([Formula: see text]), and the performance on PD-L1 positive cases achieved by our method surpassed that of non-subspecialty and trainee pathologists. Those experimental results indicate that the proposed automated system can be a powerful tool to improve the PD-L1 TPS assessment of pathologists.

The Zinc Nutritional Immunity of Epinephelus coioides Contributes to the Importance of znuC During Pseudomonas plecoglossicida Infection.

Previously, the dual RNA-seq was carried out in a Pseudomonas plecoglossicida- Epinephelus coioides infection model to investigate the dynamics of pathogen-host interplay in vivo. ZnuC, a member of ZnuCBA Zn importer, was found transcriptionally up-regulated during infection. Thus, this study aimed to assess its role during the trade-off for Zn between host and P. plecoglossicida. ICP-MS analysis and fluorescent staining showed that Zn was withheld from serum and accumulated in the spleen, with increased Zn uptake in the Golgi apparatus of macrophages after infection. Additionally, growth assay, macrophage infection and animal infection after gene knockout / silencing revealed that znuC was necessary for growth in Zn-limiting conditions, colonization, intracellular viability, immune escape and virulence of P. plecoglossicida. Further analysis with dual RNA-seq revealed associations of host's Zn nutritional immunity genes with bacterial Zn assimilation genes. IL6 and ZIP4 played key roles in this network, and markedly affected znuB expression, intracellular viability and immune escape, as revealed by gene silencing. Moreover, EMSA and GFP reporter gene analysis showed that Fur sensed changes in Fe concentration to regulate znuCBA in P. plecoglossicida. Jointly, these findings suggest a trade-off for Zn between host and P. plecoglossicida, while ZnuC is important for P. plecoglossicida Zn acquisition.

Weakly Supervised Histopathology Image Segmentation With Sparse Point Annotations.

Digital histopathology image segmentation can facilitate computer-assisted cancer diagnostics. Given the difficulty of obtaining manual annotations, weak supervision is more suitable for the task than full supervision is. However, most weakly supervised models are not ideal for handling severe intra-class heterogeneity and inter-class homogeneity in histopathology images. Therefore, we propose a novel end-to-end weakly supervised learning framework named WESUP. With only sparse point annotations, it performs accurate segmentation and exhibits good generalizability. The training phase comprises two major parts, hierarchical feature representation and deep dynamic label propagation. The former uses superpixels to capture local details and global context from the convolutional feature maps obtained via transfer learning. The latter recognizes the manifold structure of the hierarchical features and identifies potential targets with the sparse annotations. Moreover, these two parts are trained jointly to improve the performance of the whole framework. To further boost test performance, pixel-wise inference is adopted for finer prediction. As demonstrated by experimental results, WESUP is able to largely resolve the confusion between histological foreground and background. It outperforms several state-of-the-art weakly supervised methods on a variety of histopathology datasets with minimal annotation efforts. Trained by very sparse point annotations, WESUP can even beat an advanced fully supervised segmentation network.

The immune response of a warm water fish orange-spotted grouper (Epinephelus coioides) infected with a typical cold water bacterial pathogen Aeromonas salmonicida is AhR dependent.

The present study reported the first pathogenic Aeromonas salmonicida (SRW-OG1) isolated from the warm water fish orange-spotted grouper (Epinephelus coioides), and investigated the function of Aryl hydrocarbon receptor (AhR), a ligand-dependent transcriptional factor which has been recently found to be closely associated with immune response in mammals and E. coioides. Our results showed that AhR was activated by an unknown ligand in the spleen, intestine and macrophages. Meanwhile, ahr1a and ahr1b were significantly increased in the spleen, intestine and macrophages, whereas ahr2 was only increased in the intestine, which indicated that the contribution of AhR2 to the immune response may be less than that of AhR1a and AhR1b. Some key genes involved in the macrophage inflammatory response, bacterial recognition, and intestinal immunity were significantly up-regulated in the SRW-OG1 infected E. coioides. Nevertheless, declining macrophage ROS production and down-regulation of related genes were also observed, suggesting that SRW-OG1 utilized its virulence mechanisms to prevent macrophage ROS production. Furthermore, AhR inhibitor 3', 4'-DMF and the silence of ahr1a or ahr1b significantly rescued the increased IL-1ß and IL-8 induced by SRW-OG1 infection, which proved that the induction of IL-1ß and IL-8 in E. coioides macrophages was mediated by AhR. However, BPI/LBP, ROS production and related genes were not affected by AhR. The survival rate and immune escape rate of SRW-OG1 in the ahr1a/ahr1b knocked-down and 3', 4'-DMF treated macrophages were significantly increased compared with those in wild type macrophages. Taken together, it was preliminarily confirmed that ahr1a and ahr1b played an important role in the immune response against A. salmonicida SRW-OG1.

Mechanisms underlying the virulence regulation of new Vibrio alginolyticus ncRNA Vvrr1 with a comparative proteomic analysis.

The incidence of Vibrio alginolyticus infections has increased in recent years due to the influence of climate change and rising sea temperature. Vibrio virulence regulatory RNA 1 (Vvrr1) is a newly found noncoding RNA (ncRNA) predicted to be closely related to the adhesion ability of V. alginolyticus based on the previous RNA-seq. In this study, the target genes of Vvrr1 were fully screened and verified by constructing Vvrr1-overexpressing strains and using the proteome sequencing technology. Pyruvate kinase I (pykF) gene was predicted to be a chief target gene of Vvrr1 involved in virulence regulation. The adhesion ability, biofilm formation and virulence were significantly reduced in the Vvrr1-overexpressing and the pykF-silenced strain compared with the wild strains. Similar to the overexpression of Vvrr1, the silencing of pykF also reduced the expression level of virulence genes, such as ndk, eno, sdhB, glpF, and cysH. Meanwhile, by constructing the "pykF-GFP" fusion expression plasmid and using the GFP reporter gene analysis in Escherichia coli, the fluorescence intensity of the strain containing Vvrr1 whole ncRNA sequence vector was found to be significantly weakened. These indicated that Vvrr1 participated in the virulence regulation mechanism of V. alginolyticus by interacting with the virulence gene pykF.

A metabolomic investigation into the temperature-dependent virulence of Pseudomonas plecoglossicida from large yellow croaker (Pseudosciaena crocea).

Pseudomonas plecoglossicida is associated with multiple fish diseases, and temperature is one of the most important environmental factors related to its outbreak. To elucidate the influence of temperature variation on the pathogen, the global metabolomics of P. plecoglossicida (NZBD9) were analysed at the virulent (18°C) and avirulent (12°C and 28°C) temperatures. The result showed that the levels of Phosphoric acid, Tyrosine, Spermidine and Sucrose were significantly reduced，while Itaconic acid, Glucaric acid and Isomaltose were increased in P. plecoglossicida at 18°C. These metabolic adjustments assist P. plecoglossicida to survive in adverse environments, proliferate in the host, colonize and resist host immune clearance during the initial steps of infection. The results suggested that L321_03626 and L321_18122 genes played a key role in the regulation of these metabolic adaptions and thus regulated P. plecoglossicida virulence at virulent temperature, which was proved by further gene silencing and artificial infection. The present study, for the first time, determines the P. plecoglossicida metabolomic responses to temperature variation, which is helpful to explore its pathogenic mechanism and provides reference for disease control.

Integration of Transcriptomic and Proteomic Approaches Reveals the Temperature-Dependent Virulence of Pseudomonas plecoglossicida.

Pseudomonas plecoglossicida is a facultative pathogen that is associated with diseases of multiple fish, mainly at 15-20°C. Although fish disease caused by P. plecoglossicida has led to significant economic losses, the mechanisms of the temperature-dependent virulence are unclear. Here, we identify potential pathogenicity mechanisms and demonstrate the direct regulation of several virulence factors by temperature with transcriptomic and proteomic analyses, quantitative real-time PCR (qRT-PCR), RNAi, pyoverdine (PVD) quantification, the chrome azurol S (CAS) assay, growth curve measurements, a biofilm assay, and artificial infection. The principal component analysis, the heat map generation and hierarchical clustering, together with the functional annotations of the differentially expressed genes (DEGs) demonstrated that, under different growth temperatures, the animation and focus of P. plecoglossicida are quite different, which may be the key to pathogenicity. Genes involved in PVD synthesis and in the type VI secretion system (T6SS) are specifically upregulated at the virulent temperature of 18°C. Silencing of the PVD-synthesis-related genes reduces the iron acquisition, growth, biofilm formation, distribution in host organs and virulence of the bacteria. Silencing of the T6SS genes also leads to the reduction of biofilm formation, distribution in host organs and virulence. These findings reveal that temperature regulates multiple virulence mechanisms in P. plecoglossicida, especially through iron acquisition and T6SS secretion. Meanwhile, integration of transcriptomic and proteomic data provide us with a new perspective into the pathogenesis of P. plecoglossicida, which would not have been easy to catch at either the protein or mRNA differential analyses alone, thus illustrating the power of multi-omics analyses in microbiology.