Role of ADAM and ADAMTS proteases in pathological tissue remodeling

Abstract Pathological tissue remodeling is closely associated with the occurrence and aggravation of various diseases. A Disintegrin And Metalloproteinases (ADAM), as well as A Disintegrin And Metalloproteinase with ThromboSpondin motifs (ADAMTS), belong to zinc-dependent metalloproteinase superfamily, are involved in a range of pathological states, including cancer metastasis, inflammatory disorders, respiratory diseases and cardiovascular diseases. Mounting studies suggest that ADAM and ADAMTS proteases contribute to the development of tissue remodeling in various diseases, mainly through the regulation of cell proliferation, apoptosis, migration and extracellular matrix remodeling. This review focuses on the roles of ADAM and ADAMTS proteinases in diseases with pathological tissue remodeling, with particular emphasis on the molecular mechanisms through which ADAM and ADAMTS proteins mediate tissue remodeling. Some of these reported proteinases have defined protective or contributing roles in indicated diseases, while their underlying regulation is obscure. Future studies are warranted to better understand the catalytic and non-catalytic functions of ADAM and ADAMTS proteins, as well as to evaluate the efficacy of targeting these proteases in pathological tissue remodeling

Effects of embedded distance measurements interacting with modeling approaches on empirical dynamical model predictions

Empirical Dynamic Modeling (EDM) has been a powerful tool for complex ecosystem prediction by providing an equation-free modelling framework. Theoretically, it allows future ecosystem behavior to be predicted by connecting current state to the similar, adjacent and future state on the attractor manifold which is reconstructed by single or multiple time series observed from natural systems. However, the Euclidean distance metric used in these algorithms could bias the true distance on the attractor manifold and consequently decrease the prediction performance. This could become worse if the dimension of the ecosystem is much higher and the system behavior is much complicated so that the reconstructed attractor manifold is more intricate. Therefore, manifold distance metric for both Simplex Projection and S-map was proposed. Our results clearly showed that the prediction accuracy of EDM had a general improvement after manifold distance metric was adopted. Experiments conducted on both synthetic and empirical data proved this advancement. Interestingly, these improvements were unequal for different implementations and the number of variables for embedding. Analysis demonstrated that S-map under multivariate embedding achieved the best prediction performance when manifold distance metric was applied. This suggested that the proposed manifold distance metric can work particularly well for predicting high dimensional ecosystem with complex behaviors. The main contribution of this research is that a new ecological indicator has been developed to more accurately estimate the similarity between ecological states in a reconstructed manifold and therefore provide higher prediction accuracy for EDM framework

Effects of climate change on vegetation dynamics of the Qinghai-Tibet Plateau, a causality analysis using empirical dynamic modeling

Given the vital role of the Qinghai-Tibet Plateau (QTP) as water tower in Asia and regulator for regional and even global climate, the relationship between climate change and vegetation dynamics on it has received considerable focused attention. Climate change may influence the vegetation growth on the plateau, but clear empirical evidence of such causal linkages is sparse. Herein, using datasets CRU-TS v4.04 and AVHHR NDVI from 1981 to 2019, we quantify causal effects of climate factors on vegetation dynamics with an empirical dynamical model (EDM) -- a nonlinear dynamical systems analysis approach based on state-space reconstruction rather than correlation. Results showed the following: (1) climate change promotes the growth of vegetation on the QTP, and specifically, this favorable influence of temperature is stronger than precipitation's; (2) the direction and strength of climate effects on vegetation varied over time, and the effects are seasonally different; (3) a significant increase in temperature and a slight increase in precipitation are beneficial to vegetation growth, specifically, NDVI will increase within 2% in the next 40 years with the climate trend of warming and humidity. Besides the above results, another interesting finding is that the two seasons in which precipitation strongly influence vegetation in the Three-River Source region (part of the QTP) are spring and winter. This study provides insights into the mechanisms by which climate change affects vegetation growth on the QTP, aiding in the modeling of vegetation dynamics in future scenarios

3D-Fingerprint Augment based on Super-Resolution for Indoor 3D WiFi Localization

Recently, 3D indoor positioning technology has attracted wide attention in smart medical treatment, intelligent robot and other application fields. Traditional 3D positioning technology requires to utilize the special-dedicated infrastructure for large-scale deployment but with high labor-cost. With advent of the high-density wireless networks deployment, WiFi fingerprint-based localization system reduces the high cost of large-scale device deployment and infrastructure, but is limited by heavy site survey in the offline phase. Meanwhile, most existing WiFi fingerprint-based localization systems are only aimed at 2D indoor scenes. Designing and implementing a high-precision and low-cost 3D indoor positioning system is still a challenging task. Inspired by our previous work in fingerprint augment method based on super-resolution (FASR), we design the super-resolution (3D-FASR) framework and develop a novel 3D fingerprint augment method in this paper. The 3D-fingerprint augment technology in the 3D indoor environment has achieved an attractive trade-off between positioning accuracy, equipment deployment costs and site survey labor costs, We first obtain 2D fingerprint data from the 3D fingerprint data by slicing operations and then adopt FASR twice to complete the conversion from sparse fingerprint to dense fingerprint, where we interspersed a subsampling operation between two super-resolution methods. The experimental results demonstrate the feasibility of our proposed solution in 3D indoor localization

Aberrant localization of FOXJ1 correlates with the disease severity and comorbidities in patients with nasal polyps

Abstract Background Upper airway inflammatory diseases are associated with abnormal expression of nasal epithelial forkhead-box J1 (FOXJ1) which regulates motile cilia formation. We sought to investigate whether aberrant FOXJ1 localizations correlate with the disease severity and the co-existence of allergic rhinitis (AR) or asthma in patients with nasal polyps (NPs). Methods We elucidated localization patterns of FOXJ1 by performing immunofluorescence assays in nasal specimens and cytospin samples from controls and patients with NPs. We also assayed mRNA expression levels of FOXJ1 by using quantitative real-time polymerase chain reaction. Four localization patterns [normal (N), intermediate (I), mislocalization (M), and absence (A)] were defined. A semi-quantitative scoring system was applied for demonstrating FOXJ1 localization in five areas per paraffin section, with individual sections being scored between 0 and 2. Results FOXJ1 localization score was significantly higher in samples from NPs than in controls (P < 0.001). Elevated FOXJ1 localization scores and down-regulation of FOXJ1 mRNA levels were observed in NPs with co-existing AR or asthma (all P < 0.05). Moreover, FOXJ1 localization scores positively correlated with Lund–Mackay score (r = 0.362, P = 0.007). Of primary cytospin samples, the mean percentage of patients with FOXJ1 localization patterns N, I, M and A was 15.0%, 3.3%, 53.3% and 28.3% in NPs, and 82.5%, 5.0%, 5.0% and 7.5% in controls, respectively (P < 0.001). Conclusions Aberrant localization of FOXJ1 correlates with the severity and co-existence of AR or asthma in patients with NPs, and might be a novel target for assessment and intervention in NPs