Advances in the ADAMTS Family in Cardiovascular Disease

Cardiovascular disease is a serious threat to human life and health. The number of people who die from cardiovascular disease is up to 15 million every year, ranking the first cause of all causes of death. ADAMTS family (A Disintegrin and Metalloproteinase With Thrombospondin Motifs, ADAMTSs) are matrix-associated zinc metallopeptidases with secretory function. It has diverse roles in tissue morphogenesis, pathophysiological remodeling, inflammation, and vascular biology. Controlling the structure and function of the Extracellular Matrix (ECM) is the central theme of the biology of ADAMTSs. ADAMTSs mainly play a biological role by regulating the structure and function of extracellular mechanisms, and the abnormal expression or dysfunction of some family members is associated with cardiovascular diseases. ADAMTS family plays an important role in the occurrence and development of various cardiovascular diseases. This paper aims to study the role of ADAMTS family in cardiovascular diseases

Digital Study of the Protestant Market: Taipei and Provincial Capital Cities in China's Southeast Coast as Case Studies

Addressing the digital and spatial study of the Protestant market in Taiwan and mainland China is pioneering attempt to enhance the Christian study in Asia. The article selects Taipei and China's five additional provincial capital cities in the southeast coast to calculate and map the supply-side and demand-side of the Protestant market in the early of 21st century. Utilizing the digital and spatial methods, the article provides a comparative perspective in measuring the Protestant density, accessibility and availability of Taipei and five capital cities in China's southeast coast. The article concludes that in light of a democratic society with a religious freedom policy, Taipei has enjoyed a healthy Protestant market demonstrated by its better Protestant density, accessibility and availability

The Spatial Study of Catholic Market in China

This article is designed to use geo-spatial, digital and statistical methods to visualize and measure the demand and supply of Catholic market in China. Selecting nine representative cities covering three regions of China, the article measures the density of Catholics through discussing the number of Catholic population and number of Catholic churches in an effort to calculate the average number of Catholics using each church. In addition, this article utilizes two spatial methods to visualize and gauge the distance and driving time between the Catholic residential area and the nearest church in an effort to measure the church availability and accessibility in the selected nine cities. After proposing three measurable criteria of evaluating the shortage of church, this article identifies five specific cities as the areas in which there is a Catholic church shortage in China

Mobile MIMO Channel Prediction with ODE-RNN: a Physics-Inspired Adaptive Approach

Obtaining accurate channel state information (CSI) is crucial and challenging for multiple-input multiple-output (MIMO) wireless communication systems. Conventional channel estimation method cannot guarantee the accuracy of mobile CSI while requires high signaling overhead. Through exploring the intrinsic correlation among a set of historical CSI instances randomly obtained in a certain communication environment, channel prediction can significantly increase CSI accuracy and save signaling overhead. In this paper, we propose a novel channel prediction method based on ordinary differential equation (ODE)-recurrent neural network (RNN) for accurate and flexible mobile MIMO channel prediction. Differing from existing works using sequential network structures for exploring the numerical correlation between observed data, our proposed method tries to represent the implicit physics process of path responses changing by specially designed continuous learning network with ODE structure. Due to the targeted design of learning network, our proposed method fits the mathematics feature of CSI data better and enjoy higher network interpretability. Experimental results show that the proposed learning approach outperforms existing methods, especially for long time interval of the CSI sequence and large channel measurement error.Comment: 7 pages, conferenc

Distributed Learning over Networks with Graph-Attention-Based Personalization

In conventional distributed learning over a network, multiple agents collaboratively build a common machine learning model. However, due to the underlying non-i.i.d. data distribution among agents, the unified learning model becomes inefficient for each agent to process its locally accessible data. To address this problem, we propose a graph-attention-based personalized training algorithm (GATTA) for distributed deep learning. The GATTA enables each agent to train its local personalized model while exploiting its correlation with neighboring nodes and utilizing their useful information for aggregation. In particular, the personalized model in each agent is composed of a global part and a node-specific part. By treating each agent as one node in a graph and the node-specific parameters as its features, the benefits of the graph attention mechanism can be inherited. Namely, instead of aggregation based on averaging, it learns the specific weights for different neighboring nodes without requiring prior knowledge about the graph structure or the neighboring nodes' data distribution. Furthermore, relying on the weight-learning procedure, we develop a communication-efficient GATTA by skipping the transmission of information with small aggregation weights. Additionally, we theoretically analyze the convergence properties of GATTA for non-convex loss functions. Numerical results validate the excellent performances of the proposed algorithms in terms of convergence and communication cost.Comment: Accepted for publication in IEEE TSP; with supplementary details for the derivation

Preparation and pre-clinical characterization of sustainedrelease ketoprofen implants for the management of pain and inflammation in osteoarthritis

Purpose: To prepare and evaluate sustained-release ketoprofen implants for prolonged drug release and activity.Methods: Ketoprofen implants were prepared with poly (lactic-co-glycolic acid) (PLGA) and chitosan in the form of tablets. The implants were analyzed for drug loading, thickness, hardness, swelling, in vitro drug release, as well as in vivo analgesic and anti-inflammatory activities.Results: The implants were round, smooth in appearance, uniform in thickness and showed no cracks or physical defects on the surface. Their friability was < 1 % while drug content ranged from 89.98 ± 2.06 to 92.95 ± 1.65 %. In vitro drug release ranged from 70.23 to 92.04 % at the end of 5 days. Implants containing higher amounts of PLGA produced the highest swelling (40.24 ± 1.08 %). Implant IKT3 showed maximum analgesic activity (7.75 ± 1.00 s) and shortest time of maximum analgesia (2.5 h) in hot plate method. Inhibition of rat paw edema for IKT1, IKT2 and IKT3 was 79.95, 69.98 and 82.24 %, respectively, after 24 h.Conclusion: Ketoprofen-loaded implant IKT3 (4:4:2 ratio of PLGA, chitosan and ketoprofen) provides relatively quick onset and prolonged duration of analgesic effect. Thus, ketoprofen implants have a potential for development into therapeutic products for prolonged management of pain and inflammation in osteoarthritis.Keywords: Osteoarthritis, Ketoprofen implant, Prolonged analgesia, Poly(lactic-co-glycolic acid), Chitosa

Preparation of UV-resistant PET fibres by direct melt spinning with on-line addition

In order to solve the uniform dispersion of inorganic particles and dispersion characterization, a batch of UV-resistant fibres has been manufactured by direct melt spinning with on-line addition. By combining image analysis software with OM images, the dispersion of TiO2 has been quantitatively analyzed. The formula of mass fraction of inorganic particles in fibre is deduced on the basis of crystallinity, and the calculated value is found consistent with theoretical value. Additionally, the comparative study of direct spinning and chip spinning shows that the former presents better dispersion of inorganic particles and superior performance. The tenacity of fibres from melt-direct spinning increases by 13.87%， the CV value decreases by 75.19% and Heywood diameter of TiO2 particles decreases by 13.97%. According to national standard (GB/T 18830-2009), UPF values of the fabric are found much greater than the standard [UPF>40, T(UVA)<5%]

Construing Ideational Meaning in Electronics Devicesadvertisements in Jawa Pos: a Systemic Functional Linguisticmultimodal Discourse Analysis

This research deals with multimodal discourse analysis. The data were collected from printed advertisements ofJawa Pos newspaper. Generic Structure Potential of printed advertisement (GSP) proposed by Cheong (2004)and Halliday\u27s (1994) transitivity were applied. Cheong\u27s framework is applied to reveal the elements of visualand linguistic elements, meanwhile Halliday\u27s transitivity is used to know the processes. Thereby, this researchdiscovers the relationship between image and text in one context. The result shows that visual elements in theprinted advertisements are Lead, Emblem, and Display. Lead consists of Locus of Attention (LoA) andComplements to the Locus of Attention (Comp. LoA). Meanwhile, the linguistic elements are Announcement,Emblem, Enhancer, Tag, and Call-and-Visit Information. Finally, it is found that there is interconnectednessbetween the visual and linguistic elements in the printed advertisement. It causes high ContextualizationPropensity (CP), narrow Interpretative Space (IS), and also small Semantic Effervescence (SE)

PARP inhibitor-related haemorrhages: What does the real-world study say?

BackgroundPARP inhibitors (PARPis) are novel molecular targeted therapeutics for inhibition of DNA repair in tumor cells, which are commonly used in ovarian cancer. Recent case reports have indicated that haemorrhages-related adverse events may be associated with PARPis. However, little is known about the characteristics and signal strength factors of this kind of adverse event.MethodsA pharmacovigilance study from January 2004 to March 2022 based on the FDA adverse event reporting system (FAERS) database was conducted by adopting the proportional imbalance method based on the four algorithms, including the reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian confidence propagation neural networks (BCPNN) and multi-item gamma Poisson shrinker (MGPS).Results725 cases of PARPi-haemorrhages-related adverse events were identified with a fatality rate of 4.72% (30/725) and a median age of 67 years. About 88% of the adverse events occurred within 6 months, and the median duration (IQR) was 68 days. Most adverse events (n=477, 75.11%) were related to the treatment of niraparib. Importantly, niraparib exposure was associated with a significant increase in haemorrhages-related adverse events (ROR (95% CI), 1.13(1.03,1.23), PRR (χ2), 1.12(7.32), IC (IC 025), 0.17(0.15). In addition, petechiae, gingival bleeding, bloody urine, as well as rectal haemorrhage should be monitored when using niraparib.ConclusionRecognition and management of PARPi-haemorrhages-related adverse events is of significance to clinical practice. In this study, we provided a safety signal that haemorrhage-related adverse events should be monitored for when using niraparib. However, larger and more robust post-market safety studies are needed to improve the quality of this evidence