The Hexosamine Biosynthetic Pathway Links Innate Inflammation With Epithelial-Mesenchymal Plasticity in Airway Remodeling

Disruption of the lower airway epithelial barrier plays a major role in the initiation and progression of chronic lung disease. Here, repetitive environmental insults produced by viral and allergens triggers metabolic adaptations, epithelial-mesenchymal plasticity (EMP) and airway remodeling. Epithelial plasticity disrupts epithelial barrier function, stimulates release of fibroblastic growth factors, and remodels the extracellular matrix (ECM). This review will focus on recent work demonstrating how the hexosamine biosynthetic pathway (HBP) links innate inflammation to airway remodeling. The HBP is a core metabolic pathway of the unfolded protein response (UPR) responsible for protein N-glycosylation, relief of proteotoxic stress and secretion of ECM modifiers. We will overview findings that the IκB kinase (IKK)-NFκB pathway directly activates expression of the SNAI-ZEB1 mesenchymal transcription factor module through regulation of the Bromodomain Containing Protein 4 (BRD4) chromatin modifier. BRD4 mediates transcriptional elongation of SNAI1-ZEB as well as enhancing chromatin accessibility and transcription of fibroblast growth factors, ECM and matrix metalloproteinases (MMPs). In addition, recent exciting findings that IKK cross-talks with the UPR by controlling phosphorylation and nuclear translocation of the autoregulatory XBP1s transcription factor are presented. HBP is required for N glycosylation and secretion of ECM components that play an important signaling role in airway remodeling. This interplay between innate inflammation, metabolic reprogramming and lower airway plasticity expands a population of subepithelial myofibroblasts by secreting fibroblastic growth factors, producing changes in ECM tensile strength, and fibroblast stimulation by MMP binding. Through these actions on myofibroblasts, EMP in lower airway cells produces expansion of the lamina reticularis and promotes airway remodeling. In this manner, metabolic reprogramming by the HBP mediates environmental insult-induced inflammation with remodeling in chronic airway diseases.

A study on the modeling for obesity

This study primarily aims to develop an Agent Based Model (ABM) that can simulate the obesity rates based on statistical analysis and to find out how obesity is affected by risk factors in a Canadian environment. As obesity can have many causes, it is assumed that various risk factors, not just a decisive one, have an influence on obesity and they interact with one another. Therefore, unlike most previous studies, I approached the obesity problem as a Complex -Adaptive System (CAS). The data used for this study was provided by Statistics Canada, and the Canadian Community Health Survey (CCHS). This survey is a cross-sectional survey that collects self-reported information related to health status, health care utilization, and health determinants for the Canadian population. To build the Obesity ABM, it is necessary to find out which risk factors are closely associated with obesity and to what extent they interact with one another. Twelve categories of factors that are expected to influence the obesity rate were chosen on the basis of the related works. Through the statistical data analysis carried out, the main factors and variables for obesity were identified and their respective mathematical relationships obtained. From this, two categories that have several sub-factors for the obesity model were chosen. I implemented statistical data analysis on the CCHS dataset to see the interrelationship among the factors. Also, I implemented a year-to-year analysis that can show how people change their obesity status each year. Based on the data analysis result, I defined rules for how each risk factor changes each year. These rules are applied to the obesity model using NetLogo. The architecture of obesity model implementation consists of three main parts: The population module, the risk factor module, and the results module. Performance evaluation was conducted to examine whether the obesity model can simulate the obesity rate. For this evaluation, the data of CCHS from 2009 to 2014 and the result of the obesity model which is generated by simulation are compared. Model calibration was executed to fit the actual data to the model test result. The result of the model test shows that the percentage error is less than 5%. This means that the obesity model has high validity in predicting obesity for each risk factor. The obesity ABM is a useful tool to find out the risk factors related to obesity and their relationships in the Canadian population. Thus, this model can potentially assist to improve obesity management at various levels. At the individual level, everyone can find what kinds of strategies are best fit to improve her/his physical condition. Also, at a government or community level, it could help develop policies for people to continue to implement these strategies well. This will lead to reducing the associated social costs and help to promote national health.

Advanced Fuzzy-Logic-Based Traffic Incident Detection Algorithm

This study demonstrates an incident detection algorithm that uses the meteorological and traffic parameters for improving the poor performance of the automatic incident detection (AID) algorithms under extreme weather conditions and for efficiently using the meteorological devices on advanced freeways. This algorithm comprises an incident detection module that is based on learning vector quantization (LVQ) and a meteorological influencing factor module. Field data are obtained from the Yuwu freeway in Chongqing, China, to verify the algorithm. Further, the performance of this algorithm is evaluated using commonly used criteria such as mean time to detection (MTTD), false alarm rate (FAR), and detection rate (DR). Initially, an experiment is conducted for selecting the algorithm architecture that yields the optimal detection performance. Additionally, a comparative experiment is performed using the California algorithm, exponential smoothing algorithm, standard normal deviation algorithm, and McMaster algorithm. The experimental results demonstrate that the algorithm proposed in this study is characterized by high DR, low FAR, and considerable suitability for applications in AID.

Pilot study determining the feasibility of implementing the Disadvantaged Populations eGFR Epidemiology Study (DEGREE) protocol, point-of-care field measurements and a new module on risk factors for chronic kidney disease of unknown origin in Hispanic outdoor workers

Background To field test the Disadvantaged Populations eGFR Epidemiology (DEGREE) protocol, outdoor point-of-care (POC) testing for serum creatinine, and a new risk factor module on chronic kidney disease of undetermined origin (CKDu) in U.S. outdoor Hispanic workers. Methods Fifty workers were interviewed in Houston (TX). DEGREE and CKDu questionnaires were completed indoors. Anthropometrics and paired blood samples for POC and laboratory assay were completed outdoors over two periods (November–December 2017, April–May 2018). Results Administration of DEGREE and CKDu questionnaires averaged 10 and 5 min, respectively, with all questions easily understood. We observed high correlations between POC and IDMS creatinine (r = 0.919) and BUN (r = 0.974). The POC device would disable testing when outdoor temperatures were above 85 °F or below 65 °F; this was adjustable. Conclusions Implementation of DEGREE and the new CKDu module was straightforward and well understood. The POC device performed well in the field, with some adjustment in methods when temperature readings were out of range.

Inter-sectoral CO2 flows implied in trade for Zhejiang Province, China

The transfer of carbon dioxide (CO2) implied in inter-sectoral trade is significantly affecting the process of reducing CO2 emissions in China. This phenomenon also affects Zhejiang Province, which has the top five GDP in China. In this study, a universal modeling system is developed to clarify CO2 emission reduction responsibilities and visualize relationships of each pair of transfers in Zhejiang Province. The system includes “three modules”, namely input-output module, CO2 emission factor module and ecological network module. The proposed modelling system is employed for sectors of Zhejiang province. Research results demonstrate that industry should assume more responsibility for emission reduction; the existing development models of various industries need to be further adjusted. Achievements of this research will provide a scientific reference and a strong basis for decision-makers to formulate reasonable emission reduction policies in Zhejiang Province.

AGTR: Adversarial Generation of Target Review for Rating Prediction

Recent years have witnessed a growing trend of utilizing reviews to improve the performance and interpretability of recommender systems. Almost all existing methods learn the latent representations from the user’s and the item’s historical reviews and then combine these two representations for rating prediction. The fatal limitation in these methods is that they are unable to utilize the most predictive review of the target user for the target item since such a review is not available at test time. In this paper, we propose a novel recommendation model, called AGTR, which can generate the unseen target review with adversarial training for rating prediction. To this end, we develop a unified framework to combine the rating tailored generative adversarial nets for synthetic review generation and the neural latent factor module using the generated target review along with historical reviews for rating prediction. Extensive experiments on four real-world datasets demonstrate that our model achieves the state-of-the-art performance in both rating prediction and review generation tasks.

Σ-Rickart modules

Hereditary rings have been extensively investigated in the literature after Kaplansky introduced them in the earliest 50’s. In this paper, we study the notion of a [Formula: see text]-Rickart module by utilizing the endomorphism ring of a module and using the recent notion of a Rickart module, as a module theoretic analogue of a right hereditary ring. A module [Formula: see text] is called [Formula: see text]-Rickart if every direct sum of copies of [Formula: see text] is Rickart. It is shown that any direct summand and any direct sum of copies of a [Formula: see text]-Rickart module are [Formula: see text]-Rickart modules. We also provide generalizations in a module theoretic setting of the most common results of hereditary rings: a ring [Formula: see text] is right hereditary if and only if every submodule of any projective right [Formula: see text]-module is projective if and only if every factor module of any injective right [Formula: see text]-module is injective. Also, we have a characterization of a finitely generated [Formula: see text]-Rickart module in terms of its endomorphism ring. Examples which delineate the concepts and results are provided.