Pathway Interaction Network Analysis Identifies Dysregulated Pathways in Human Monocytes Infected by Listeria monocytogenes

In our study, we aimed to extract dysregulated pathways in human monocytes infected by Listeria monocytogenes (LM) based on pathway interaction network (PIN) which presented the functional dependency between pathways. After genes were aligned to the pathways, principal component analysis (PCA) was used to calculate the pathway activity for each pathway, followed by detecting seed pathway. A PIN was constructed based on gene expression profile, protein-protein interactions (PPIs), and cellular pathways. Identifying dysregulated pathways from the PIN was performed relying on seed pathway and classification accuracy. To evaluate whether the PIN method was feasible or not, we compared the introduced method with standard network centrality measures. The pathway of RNA polymerase II pretranscription events was selected as the seed pathway. Taking this seed pathway as start, one pathway set (9 dysregulated pathways) with AUC score of 1.00 was identified. Among the 5 hub pathways obtained using standard network centrality measures, 4 pathways were the common ones between the two methods. RNA polymerase II transcription and DNA replication owned a higher number of pathway genes and DEGs. These dysregulated pathways work together to influence the progression of LM infection, and they will be available as biomarkers to diagnose LM infection

Towards Generalizable Diabetic Retinopathy Grading in Unseen Domains

Diabetic Retinopathy (DR) is a common complication of diabetes and a leading cause of blindness worldwide. Early and accurate grading of its severity is crucial for disease management. Although deep learning has shown great potential for automated DR grading, its real-world deployment is still challenging due to distribution shifts among source and target domains, known as the domain generalization problem. Existing works have mainly attributed the performance degradation to limited domain shifts caused by simple visual discrepancies, which cannot handle complex real-world scenarios. Instead, we present preliminary evidence suggesting the existence of three-fold generalization issues: visual and degradation style shifts, diagnostic pattern diversity, and data imbalance. To tackle these issues, we propose a novel unified framework named Generalizable Diabetic Retinopathy Grading Network (GDRNet). GDRNet consists of three vital components: fundus visual-artifact augmentation (FundusAug), dynamic hybrid-supervised loss (DahLoss), and domain-class-aware re-balancing (DCR). FundusAug generates realistic augmented images via visual transformation and image degradation, while DahLoss jointly leverages pixel-level consistency and image-level semantics to capture the diverse diagnostic patterns and build generalizable feature representations. Moreover, DCR mitigates the data imbalance from a domain-class view and avoids undesired over-emphasis on rare domain-class pairs. Finally, we design a publicly available benchmark for fair evaluations. Extensive comparison experiments against advanced methods and exhaustive ablation studies demonstrate the effectiveness and generalization ability of GDRNet.Comment: Earyly Accepted by MICCAI 2023, the 26th International Conference on Medical Image Computing and Computer Assisted Interventio

Proteomic analysis of glucohexaose induced resistance to downy mildew in Cucumis sativus

Glucohexaose, as one of synthetic oligosaccharides, induces the resistance response to protect plants from pathogen infection by inducing the systemic acquired resistance-like (SAR-like) response. To study the molecular mechanism of glucohexaose induced resistance, we investigate the physiological, biochemical and proteomic changes after glucohexaose treatment. The results shows cucumber plants had the highest protection level of 66.79% 48 h after the third times of 10 μg mLglucohexaose treatment. Significant increases in chlorophyll, photo synthetic rate, soluble sugar, leave dry weight and HO were observed after glucohexaose treatment. Eighteen up-regulated proteins were identified by MALDI-TOF/TOF in glucohexaose-treated plants, predicted to be involved in photosynthesis, photorespiration, oxidative burst, transcriptional regulation, signal transduction and pathogen defense processes. The identification of up-regulated proteins involved in photo synthetic processes is a significant finding which suggests that a boost in metabolites is required for repartition of resources towards defense mechanisms. The proteins which responded to glucohexaose also included those associated with oxidative burst response, such as APX and isocitrate dehydrogenase. More comprehensive studies about the link between the molecular mechanisms regulated by ROS mediated photosynthesis and cucumber induced resistance by glucohexaose, are necessary in the future to broaden our understanding of induced resistance in plants

Microwave electrometry with Rydberg atoms in a vapor cell using microwave amplitude modulation

We have theoretically and experimentally studied the dispersive signal of the Rydberg atomic electromagnetically induced transparency (EIT) - Autler-Townes (AT) splitting spectra obtained using amplitude modulation of the microwave (MW) field. In addition to the two zero-crossing points, the dispersion signal has two positive maxima with an interval defined as the shoulder interval of the dispersion signal $\Delta f_{\text{sho}}$. The relationship of MW field strength $E_{\text{MW}}$ and $\Delta f_{\text{sho}}$ are studied at the MW frequencies of 31.6 GHz, 22.1 GHz, and 9.2 GHz respectively. The results show that $\Delta f_{\text{sho}}$ can be used to character the much weaker $E_{\text{MW}}$ than the interval of two zero-crossing points $\Delta f_{\text{zeros}}$ and the traditional EIT-AT splitting interval $\Delta f_{\text{m}}$, the minimum $E_{\text{MW}}$ measured by $\Delta f_{\text{sho}}$ is about 30 times smaller than that by $\Delta f_{\text{m}}$. As an example, the minimum $E_{\text{MW}}$ at 9.2 GHz that can be characterized by $\Delta f_{\text{sho}}$ is 0.056 mV/cm, which is the minimum value characterized by frequency interval using vapour cell without adding any auxiliary fields. The proposed method can improve the weak limit and sensitivity of $E_{\text{MW}}$ measured by spectral frequency interval, which is important in the direct measurement of weak $E_{\text{MW}}$

Breakdown of effective-medium theory beyond the critical angle

Effective-medium theory pertains to the theoretical modelling of homogenization, which aims to replace an inhomogeneous structure of subwavelength-scale constituents with a homogeneous effective medium. The effective-medium theory is fundamental to various realms, including electromagnetics and material science, since it can largely decrease the complexity in the exploration of light-matter interactions by providing simple acceptable approximation. Generally, the effective-medium theory is thought to be applicable to any all-dielectric system with deep-subwavelength constituents, under the condition that the effective medium does not have a critical angle, at which the total internal reflection occurs. Here we reveal a fundamental breakdown of the effective-medium theory that can be applied in very general conditions: showing it for deep-subwavelength all-dielectric multilayers even without critical angle. Our finding relies on an exotic photonic spin Hall effect, which is shown to be ultra-sensitive to the stacking order of deep-subwavelength dielectric layers, since the spin-orbit interaction of light is dependent on slight phase accumulations during the wave propagation. Our results indicate that the photonic spin Hall effect could provide a promising and powerful tool for measuring structural defects for all-dielectric systems even in the extreme nanometer scale.Comment: 17 pages, 4 figure

Scalable high-precision trimming of photonic resonances by polymer exposure to energetic beams

Integrated photonic circuits (PICs) have seen an explosion in interest, through to commercialization in the past decade. Most PICs rely on sharp resonances to modulate, steer, and multiplex signals. However, the spectral characteristics of high-quality resonances are highly sensitive to small variations in fabrication and material constants, which limits their applicability. Active tuning mechanisms are commonly employed to account for such deviations, consuming energy and occupying valuable chip real estate. Readily employable, accurate, and highly scalable mechanisms to tailor the modal properties of photonic integrated circuits are urgently required. Here, we present an elegant and powerful solution to achieve this in a scalable manner during the semiconductor fabrication process using existing lithography tools: by exploiting the volume shrinkage exhibited by certain polymers to permanently modulate the waveguide’s effective index. This technique enables broadband and lossless tuning with immediate applicability in wide-ranging applications in optical computing, telecommunications, and free-space optics

Periodontal pathogens are a risk factor of oral cavity squamous cell carcinoma, independent of tobacco and alcohol and human papillomavirus

Over the past decade, there has been a change in the epidemiology of oral cavity squamous cell cancer (OC-SCC). Many new cases of OC-SCC lack the recognized risk factors of smoking, alcohol and human papilloma virus. The aim of this study was to determine if the oral microbiome may be associated with OC-SCC in nonsmoking HPV negative patients. We compared the oral microbiome of HPV-negative nonsmoker OC-SCC(n = 18), premalignant lesions(PML) (n = 8) and normal control patients (n = 12). Their oral microbiome was sampled by oral wash and defined by 16S rRNA gene sequencing. We report that the periodontal pathogens Fusobacterium, Prevotella, Alloprevotella were enriched while commensal Streptococcus depleted in OC-SCC. Based on the four genera plus a marker genus Veillonella for PML, we classified the oral microbiome into two types. Gene/pathway analysis revealed a progressive increase of genes encoding HSP90 and ligands for TLRs 1, 2 and 4 along the controls→PML → OC-SCC progression sequence. Our findings suggest an association between periodontal pathogens and OC-SCC in non smoking HPV negative patients

MSG-Fast: Metagenomic shotgun data fast annotation using microbial gene catalogs

Background: Current methods used for annotating metagenomics shotgun sequencing (MGS) data rely on a computationally intensive and low-stringency approach of mapping each read to a generic database of proteins or reference microbial genomes. Results: We developed MGS-Fast, an analysis approach for shotgun whole-genome metagenomic data utilizing Bowtie2 DNA-DNA alignment of reads that is an alternative to using the integrated catalog of reference genes database of well-annotated genes compiled from human microbiome data. This method is rapid and provides high-stringency matches (\u3e90% DNA sequence identity) of the metagenomics reads to genes with annotated functions. We demonstrate the use of this method with data from a study of liver disease and synthetic reads, and Human Microbiome Project shotgun data, to detect differentially abundant Kyoto Encyclopedia of Genes and Genomes gene functions in these experiments. This rapid annotation method is freely available as a Galaxy workflow within a Docker image. Conclusions: MGS-Fast can confidently transfer functional annotations from gene databases to metagenomic reads, with speed and accuracy