Deep-Learning–Based Characterization of Tumor-Infiltrating Lymphocytes in Breast Cancers From Histopathology Images and Multiomics Data

Purpose: Tumor-infiltrating lymphocytes (TILs) and their spatial characterizations on whole-slide images (WSIs) of histopathology sections have become crucial in diagnosis, prognosis, and treatment response prediction for different cancers. However, fully automatic assessment of TILs on WSIs currently remains a great challenge because of the heterogeneity and large size of WSIs. We present an automatic pipeline based on a cascade-training U-net to generate high-resolution TIL maps on WSIs. Methods: We present global cell-level TIL maps and 43 quantitative TIL spatial image features for 1,000 WSIs of The Cancer Genome Atlas patients with breast cancer. For more specific analysis, all the patients were divided into three subtypes, namely, estrogen receptor (ER)-positive, ER-negative, and triple-negative groups. The associations between TIL scores and gene expression and somatic mutation were examined separately in three breast cancer subtypes. Both univariate and multivariate survival analyses were performed on 43 TIL image features to examine the prognostic value of TIL spatial patterns in different breast cancer subtypes. Results: The TIL score was in strong association with immune response pathway and genes (eg, programmed death-1 and CLTA4). Different breast cancer subtypes showed TIL score in association with mutations from different genes suggesting that different genetic alterations may lead to similar phenotypes. Spatial TIL features that represent density and distribution of TIL clusters were important indicators of the patient outcomes. Conclusion: Our pipeline can facilitate computational pathology-based discovery in cancer immunology and research on immunotherapy. Our analysis results are available for the research community to generate new hypotheses and insights on breast cancer immunology and development

Analysis on contamination of Bacillus cereus in foodstuff in Jilin Province from 2011 to 2019

Objective To understand the contamination of Bacillus cereus in foodstuff of Jilin Province from 2011 to 2019, and to provide theoretical basis for food safety monitoring and prevention of foodborne diseases. Methods Totally 3 173 samples were collected from the catering service and circulation of nine prefecture (city) levels in Jilin Province from 2011 to 2019. Bacillus cereus in food was detected according to the method of GB 4789.14-2014 national food safety standard microbiological examination of food. The detection rate was analyzed by rate, composition ratio and χ2 test. Results Among 3 173 food samples from 2011 to 2019 in Jilin Province, the total detection rate of Bacillus cereus was 23.6% (750/3 173), the highest was in 2015 (38.5%, 62/161), and the lowest was in 2017 (11.8%, 20/170). Baishan City had the highest detection rate (35.8%, 139/388), followed by Yanbian Prefecture (31.4%, 97/309), and Siping City had the lowest detection rate (15.3%, 76/496). The detection rate of egg and egg products was the highest (60.0%, 3/5), followed by milk and dairy products (39.3%, 114/290) and infant food (31.1%, 185/595). Contamination of Bacillus cereus was the highest in department stores (32.4%, 22/68), followed by snack bars and beverage stores (30.9%, 43/139), and fast food stores (29.1%, 25/86). The median (interquartile interval) of the detection result of Bacillus cereus by colony forming units method was 5.8 (2.9, 8.7) CFU/g (mL), and the median (interquartile interval) of that by most probable number method was 6.4 (3.2, 9.6) MPN/g (mL). Conclusion There were different degrees of Bacillus cereus contamination in foodstuff in Jilin Province. Among the different cities, foodstuff samples collected from Baishan City was much more serious. Eggs and egg products, milk and dairy products were the main contaminated food. Safety monitoring and management of the snack bar, beverage shop and places in department store should be strengthen

Integrative analysis of histopathological images and chromatin accessibility data for estrogen receptor-positive breast cancer

Background: Existing studies have demonstrated that the integrative analysis of histopathological images and genomic data can be used to better understand the onset and progression of many diseases, as well as identify new diagnostic and prognostic biomarkers. However, since the development of pathological phenotypes are influenced by a variety of complex biological processes, complete understanding of the underlying gene regulatory mechanisms for the cell and tissue morphology is still a challenge. In this study, we explored the relationship between the chromatin accessibility changes and the epithelial tissue proportion in histopathological images of estrogen receptor (ER) positive breast cancer. Methods: An established whole slide image processing pipeline based on deep learning was used to perform global segmentation of epithelial and stromal tissues. We then used canonical correlation analysis to detect the epithelial tissue proportion-associated regulatory regions. By integrating ATAC-seq data with matched RNA-seq data, we found the potential target genes that associated with these regulatory regions. Then we used these genes to perform the following pathway and survival analysis. Results: Using canonical correlation analysis, we detected 436 potential regulatory regions that exhibited significant correlation between quantitative chromatin accessibility changes and the epithelial tissue proportion in tumors from 54 patients (FDR < 0.05). We then found that these 436 regulatory regions were associated with 74 potential target genes. After functional enrichment analysis, we observed that these potential target genes were enriched in cancer-associated pathways. We further demonstrated that using the gene expression signals and the epithelial tissue proportion extracted from this integration framework could stratify patient prognoses more accurately, outperforming predictions based on only omics or image features. Conclusion: This integrative analysis is a useful strategy for identifying potential regulatory regions in the human genome that are associated with tumor tissue quantification. This study will enable efficient prioritization of genomic regulatory regions identified by ATAC-seq data for further studies to validate their causal regulatory function. Ultimately, identifying epithelial tissue proportion-associated regulatory regions will further our understanding of the underlying molecular mechanisms of disease and inform the development of potential therapeutic targets

In utero Exposure to Atrazine Disrupts Rat Fetal Testis Development

Atrazine (ATR) is a commonly used agricultural herbicide and a potential endocrine disruptor that may cause testicular dysgenesis. The objective of the present study was to investigate the effects of atrazine on fetal testis development after in utero exposure. Female Sprague-Dawley rats were gavaged daily with vehicle (corn oil, control) or atrazine (25, 50, and 100 mg/kg body weight/day) from gestational day 12 to 21. Atrazine dose-dependently decreased serum testosterone levels of male pups, with a significant difference from the control recorded at a dose of 100 mg/kg. In addition, atrazine significantly increased fetal Leydig cell aggregation at a dose of 100 mg/kg. Atrazine increased fetal Leydig cell number but not Sertoli cell number. However, atrazine down-regulated Scarb1 and Cyp17a1 in the fetal Leydig cell per se and Hsd17b3 and Dhh in the Sertoli cell per se. These results demonstrated that in utero exposure to atrazine disrupted rat fetal testis development

Probing the fractional quantum Hall phases in valley-layer locked bilayer MoS2_{2}

Semiconducting transition-metal dichalcogenides (TMDs) exhibit high mobility, strong spin-orbit coupling, and large effective masses, which simultaneously leads to a rich wealth of Landau quantizations and inherently strong electronic interactions. However, in spite of their extensively explored Landau levels (LL) structure, probing electron correlations in the fractionally filled LL regime has not been possible due to the difficulty of reaching the quantum limit. Here, we report evidence for fractional quantum Hall (FQH) states at filling fractions 4/5 and 2/5 in the lowest LL of bilayer MoS$_{2}$, manifested in fractionally quantized transverse conductance plateaus accompanied by longitudinal resistance minima. We further show that the observed FQH states sensitively depend on the dielectric and gate screening of the Coulomb interactions. Our findings establish a new FQH experimental platform which are a scarce resource: an intrinsic semiconducting high mobility electron gas, whose electronic interactions in the FQH regime are in principle tunable by Coulomb-screening engineering, and as such, could be the missing link between atomically thin graphene and semiconducting quantum wells.Comment: 10 pages, 4 figure

Evaluation of the Observational Associations and Shared Genetics Between Glaucoma With Depression and Anxiety

PURPOSE: Glaucoma, a leading cause of blindness worldwide, is suspected to exhibit a notable association with psychological disturbances. This study aimed to investigate epidemiological associations and explore shared genetic architecture between glaucoma and mental traits, including depression and anxiety.METHODS: Multivariable logistic regression and Cox proportional hazards regression models were employed to investigate longitudinal associations based on UK Biobank. A stepwise approach was used to explore the shared genetic architecture. First, linkage disequilibrium score regression inferred global genetic correlations. Second, MiXeR analysis quantified the number of shared causal variants. Third, specific shared loci were detected through conditional/conjunctional false discovery rate (condFDR/conjFDR) analysis and characterized for biological insights. Finally, two-sample Mendelian randomization (MR) was conducted to investigate bidirectional causal associations.RESULTS: Glaucoma was significantly associated with elevated risks of hospitalized depression (hazard ratio [HR] = 1.54; 95% confidence interval [CI], 1.01-2.34) and anxiety (HR = 2.61; 95% CI, 1.70-4.01) compared to healthy controls. Despite the absence of global genetic correlations, MiXeR analysis revealed 300 variants shared between glaucoma and depression, and 500 variants shared between glaucoma and anxiety. Subsequent condFDR/conjFDR analysis discovered 906 single-nucleotide polymorphisms (SNPs) jointly associated with glaucoma and depression and two associated with glaucoma and anxiety. The MR analysis did not support robust causal associations but indicated the existence of pleiotropic genetic variants influencing both glaucoma and depression.CONCLUSIONS: Our study enhances the existing epidemiological evidence and underscores the polygenic overlap between glaucoma and mental traits. This observation suggests a correlation shaped by pleiotropic genetic variants rather than being indicative of direct causal relationships.</p