In Vivo Molecular Imaging in Retinal Disease

There is an urgent need for early diagnosis in medicine, whereupon effective treatments could prevent irreversible tissue damage. The special structure of the eye provides a unique opportunity for noninvasive light-based imaging of ocular fundus vasculature. To detect endothelial injury at the early and reversible stage of adhesion molecule upregulation, some novel imaging agents that target retinal endothelial molecules were generated. In vivo molecular imaging has a great potential to impact medicine by detecting diseases or screening disease in early stages, identifying extent of disease, selecting disease and patient-specific therapeutic treatment, applying a directed or targeted therapy, and measuring molecular-specific effects of treatment. Current preclinical findings and advances in instrumentation such as endoscopes and microcatheters suggest that these molecular imaging modalities have numerous clinical applications and will be translated into clinical use in the near future

FAF: A novel multimodal emotion recognition approach integrating face, body and text

Multimodal emotion analysis performed better in emotion recognition depending on more comprehensive emotional clues and multimodal emotion dataset. In this paper, we developed a large multimodal emotion dataset, named "HED" dataset, to facilitate the emotion recognition task, and accordingly propose a multimodal emotion recognition method. To promote recognition accuracy, "Feature After Feature" framework was used to explore crucial emotional information from the aligned face, body and text samples. We employ various benchmarks to evaluate the "HED" dataset and compare the performance with our method. The results show that the five classification accuracy of the proposed multimodal fusion method is about 83.75%, and the performance is improved by 1.83%, 9.38%, and 21.62% respectively compared with that of individual modalities. The complementarity between each channel is effectively used to improve the performance of emotion recognition. We had also established a multimodal online emotion prediction platform, aiming to provide free emotion prediction to more users

Vascular Adhesion Protein 1 in the Eye

Semicarbazide-sensitive amine oxidase/vascular adhesion protein-1 (SSAO/VAP-1), a dual-function molecule with adhesive and enzymatic properties, is expressed on the surface of vascular endothelial cells of mammals. It also exists as a soluble form (sVAP-1), which is implicated in oxidative stress via its enzymatic activity and can be a prognostic biomarker. Recent evidence suggests that VAP-1 is an important therapeutic target for several inflammation-related ocular diseases, such as uveitis, agerelated macular degeneration (AMD), and diabetic retinopathy (DR), by involving in the recruitment of leukocytes at sites of inflammation. Furthermore, VAP-1 plays an important role in the pathogenesis of conjunctival inflammatory diseases such as pyogenic granulomas and the progression of conjunctival lymphoma. VAP-1 may be an alternative therapeutic target in ocular diseases. The in vivo imaging of inflammation using VAP-1 as a target molecule is a novel approach with a potential for early detection and characterization of inflammatory diseases. This paper reviews the critical roles of VAP-1 in ophthalmological diseases which may provide a novel research direction or a potent therapeutic strategy

Vascular Adhesion Protein 1 in the Eye

Semicarbazide-sensitive amine oxidase/vascular adhesion protein-1 (SSAO/VAP-1), a dual-function molecule with adhesive and enzymatic properties, is expressed on the surface of vascular endothelial cells of mammals. It also exists as a soluble form (sVAP-1), which is implicated in oxidative stress via its enzymatic activity and can be a prognostic biomarker. Recent evidence suggests that VAP-1 is an important therapeutic target for several inflammation-related ocular diseases, such as uveitis, age-related macular degeneration (AMD), and diabetic retinopathy (DR), by involving in the recruitment of leukocytes at sites of inflammation. Furthermore, VAP-1 plays an important role in the pathogenesis of conjunctival inflammatory diseases such as pyogenic granulomas and the progression of conjunctival lymphoma. VAP-1 may be an alternative therapeutic target in ocular diseases. The in vivo imaging of inflammation using VAP-1 as a target molecule is a novel approach with a potential for early detection and characterization of inflammatory diseases. This paper reviews the critical roles of VAP-1 in ophthalmological diseases which may provide a novel research direction or a potent therapeutic strategy

Insights into innate immune cell evasion by Chlamydia trachomatis

Chlamydia trachomatis, is a kind of obligate intracellular pathogen. The removal of C. trachomatis relies primarily on specific cellular immunity. It is currently considered that CD4+ Th1 cytokine responses are the major protective immunity against C. trachomatis infection and reinfection rather than CD8+ T cells. The non-specific immunity (innate immunity) also plays an important role in the infection process. To survive inside the cells, the first process that C. trachomatis faces is the innate immune response. As the “sentry” of the body, mast cells attempt to engulf and remove C. trachomatis. Dendritic cells present antigen of C. trachomatis to the “commanders” (T cells) through MHC-I and MHC-II. IFN-γ produced by activated T cells and natural killer cells (NK) further activates macrophages. They form the body’s “combat troops” and produce immunity against C. trachomatis in the tissues and blood. In addition, the role of eosinophils, basophils, innate lymphoid cells (ILCs), natural killer T (NKT) cells, γδT cells and B-1 cells should not be underestimated in the infection of C. trachomatis. The protective role of innate immunity is insufficient, and sexually transmitted diseases (STDs) caused by C. trachomatis infections tend to be insidious and recalcitrant. As a consequence, C. trachomatis has developed a unique evasion mechanism that triggers inflammatory immunopathology and acts as a bridge to protective to pathological adaptive immunity. This review focuses on the recent advances in how C. trachomatis evades various innate immune cells, which contributes to vaccine development and our understanding of the pathophysiologic consequences of C. trachomatis infection

The role of N6-methyladenosine (m6A) in kidney diseases

Chemical modifications are a specific and efficient way to regulate the function of biological macromolecules. Among them, RNA molecules exhibit a variety of modifications that play important regulatory roles in various biological processes. More than 170 modifications have been identified in RNA molecules, among which the most common internal modifications include N6-methyladenine (m6A), n1-methyladenosine (m1A), 5-methylcytosine (m5C), and 7-methylguanine nucleotide (m7G). The most widely affected RNA modification is m6A, whose writers, readers, and erasers all have regulatory effects on RNA localization, splicing, translation, and degradation. These functions, in turn, affect RNA functionality and disease development. RNA modifications, especially m6A, play a unique role in renal cell carcinoma disease. In this manuscript, we will focus on the biological roles of m6A in renal diseases such as acute kidney injury, chronic kidney disease, lupus nephritis, diabetic kidney disease, and renal cancer

A Random Forest Model for Daily PM2.5 Personal Exposure Assessment for a Chinese Cohort

Errors in air pollution exposure assessment are often considered as a major limitation in epidemiological studies. However, it is difficult to obtain accurate personal level exposure on cohort populations due to the often prohibitive expense. Personal exposure estimation models are used in lieu of direct personal exposure measures but still suffer from issues of availability and accuracy. We aim to establish a personal PM2.5 exposure assessment model for a cohort population and assess its performance by applying our model on cohort subjects. We analyzed data from representative sites selected from the subclinical outcomes of polluted air in China (SCOPA-China) cohort study and established a random forest model for estimating daily PM2.5 personal exposure. We also applied the model among subjects recruited in the project mentioned above within the same area and study period to estimate the reliability of the model. The established model showed a good fit with an R2 of 0.81. The model application results showed similar patterns with empirically measured data. Our pilot study provided a validated and feasible modeling approach for assessing daily personal PM2.5 exposure for large cohort populations. The promising model framework can improve PM2.5 exposure assessment accuracy for future environmental health studies of large populations