We systematically study how diverse physiologic systems in the human organism dynamically interact and collectively behave to produce distinct physiologic states and functions. This is a fundamental ...question in the new interdisciplinary field of Network Physiology, and has not been previously explored. Introducing the novel concept of Time Delay Stability (TDS), we develop a computational approach to identify and quantify networks of physiologic interactions from long-term continuous, multi-channel physiological recordings. We also develop a physiologically-motivated visualization framework to map networks of dynamical organ interactions to graphical objects encoded with information about the coupling strength of network links quantified using the TDS measure. Applying a system-wide integrative approach, we identify distinct patterns in the network structure of organ interactions, as well as the frequency bands through which these interactions are mediated. We establish first maps representing physiologic organ network interactions and discover basic rules underlying the complex hierarchical reorganization in physiologic networks with transitions across physiologic states. Our findings demonstrate a direct association between network topology and physiologic function, and provide new insights into understanding how health and distinct physiologic states emerge from networked interactions among nonlinear multi-component complex systems. The presented here investigations are initial steps in building a first atlas of dynamic interactions among organ systems.
Although numerous studies have investigated the association of ambient air pollution with hypertension and blood pressure (BP), the results were inconsistent. We performed a comprehensive systematic ...review and meta-analysis of these studies. Seven international and Chinese databases were searched for studies examining the associations of particulate (diameter<2.5 μm (PM2.5), 2.5–10 μm (PM2.5-10) or >10 μm (PM10)) and gaseous (sulfur dioxide (SO2), nitrogen dioxide (NO2), nitrogen oxides (NOx), ozone (O3), carbon monoxide (CO)) air pollutants with hypertension or BP. Odds ratios (OR), regression coefficients (β) and their 95% confidence intervals were calculated to evaluate the strength of the associations. Subgroup analysis, sensitivity analysis, and meta-regression analysis were also conducted. The overall meta-analysis showed significant associations of long-term exposures to PM2.5 with hypertension (OR = 1.05), and of PM10, PM2.5, and NO2 with DBP (β values: 0.47–0.86 mmHg). In addition, short-term exposures to four (PM10, PM2.5, SO2, NO2), two (PM2.5 and SO2), and four air pollutants (PM10, PM2.5, SO2, and NO2), were significantly associated with hypertension (ORs: 1.05–1.10), SBP (β values: 0.53–0.75 mmHg) and DBP (β values: 0.15–0.64 mmHg), respectively. Stratified analyses showed a generally stronger relationship among studies of men, Asians, North Americans, and areas with higher air pollutant levels. In conclusion, our study indicates a positive association between ambient air pollution and increased BP and hypertension. Geographical and socio-demographic factors may modify the pro-hypertensive effects of air pollutants.
Display omitted
•Evidence on ambient air pollution and blood pressure (BP) remains inconsistent.•A systematic review identified 100 studies involving ≈0.7 million participants.•Meta-analysis showed a positive association between air pollution and elevated BP.•Study-level geographical and socio-demographic factors modify the association.
Meta-analysis shows significant associations between ambient air pollution and hypertension.
Relation extraction is a key task for knowledge graph construction and natural language processing, which aims to extract meaningful relational information between entities from plain texts. With the ...development of deep learning, many neural relation extraction models were proposed recently. This paper introduces a survey on the task of neural relation extraction, including task description, widely used evaluation datasets, metrics, typical methods, challenges and recent research progresses. We mainly focus on four recent research problems: (1) how to learn the semantic representations from the given sentences for the target relation, (2) how to train a neural relation extraction model based on insufficient labeled instances, (3) how to extract relations across sentences or in a document and (4) how to jointly extract relations and corresponding entities? Finally, we give out our conclusion and future research issues.
Appropriate autophagy has protective effects on ischemic nerve tissue, while excessive autophagy may cause cell death. The inflammatory response plays an important role in the survival of nerve cells ...and the recovery of neural tissue after ischemia. Many studies have found an interaction between autophagy and inflammation in the pathogenesis of ischemic stroke. This study outlines recent advances regarding the role of autophagy in the post-stroke inflammatory response as follows. (1) Autophagy inhibits inflammatory responses caused by ischemic stimulation through mTOR, the AMPK pathway, and inhibition of inflammasome activation. (2) Activation of inflammation triggers the formation of autophagosomes, and the upregulation of autophagy levels is marked by a significant increase in the autophagy-forming markers LC3-II and Beclin-1. Lipopolysaccharide stimulates microglia and inhibits ULK1 activity by direct phosphorylation of p38 MAPK, reducing the flux and autophagy level, thereby inducing inflammatory activity. (3) By blocking the activation of autophagy, the activation of inflammasomes can alleviate cerebral ischemic injury. Autophagy can also regulate the phenotypic alternation of microglia through the nuclear factor-κB pathway, which is beneficial to the recovery of neural tissue after ischemia. Studies have shown that some drugs such as resveratrol can exert neuroprotective effects by regulating the autophagy-inflammatory pathway. These studies suggest that the autophagy-inflammatory pathway may provide a new direction for the treatment of ischemic stroke.
Detecting vehicles in aerial images provides important information for traffic management and urban planning. Detecting the cars in the images is challenging due to the relatively small size of the ...target objects and the complex background in man-made areas. It is particularly challenging if the goal is near-real-time detection, i.e., within few seconds, on large images without any additional information, e.g., road database and accurate target size. We present a method that can detect the vehicles on a 21-MPixel original frame image without accurate scale information within seconds on a laptop single threaded. In addition to the bounding box of the vehicles, we extract also orientation and type (car/truck) information. First, we apply a fast binary detector using integral channel features in a soft-cascade structure. In the next step, we apply a multiclass classifier on the output of the binary detector, which gives the orientation and type of the vehicles. We evaluate our method on a challenging data set of original aerial images over Munich and a data set captured from an unmanned aerial vehicle (UAV).
The incorporation of defects, such as vacancies, into functional materials could substantially tailor their intrinsic properties. Progress in vacancy chemistry has enabled advances in many ...technological applications, but creating new type of vacancies in existing material system remains a big challenge. We show here that ionized nitrogen plasma can break bonds of iron-carbon-nitrogen-nickel units in nickel-iron Prussian blue analogues, forming unconventional carbon-nitrogen vacancies. We study oxygen evolution reaction on the carbon-nitrogen vacancy-mediated Prussian blue analogues, which exhibit a low overpotential of 283 millivolts at 10 milliamperes per square centimeter in alkali, far exceeding that of original Prussian blue analogues and previously reported oxygen evolution catalysts with vacancies. We ascribe this enhancement to the in-situ generated nickel-iron oxy(hydroxide) active layer during oxygen evolution reaction, where the Fe leaching was significantly suppressed by the unconventional carbon-nitrogen vacancies. This work opens up opportunities for producing vacancy defects in nanomaterials for broad applications.
An improved equivalent-input-disturbance (EID) approach is devised to enhance the disturbance-rejection performance for a strictly proper plant with a state delay in a modified repetitive-control ...system. A gain factor is introduced to construct an improved EID estimator. This increases the flexibility of system design and enables the adjustment of the dynamical performance of disturbance rejection. Moreover, the commutative condition, which is widely used for the conventional EID estimator, is avoided. Thus, it reduces the conservativeness of design by removing the constraints imposed by the commutative condition. The system is divided into two subsystems, and the separation theorem is applied to simplify the design. For one subsystem, the delay information on both the modified repetitive controller and the plant is used to reduce the conservativeness of stability condition. The resulting linear matrix inequality ('MI) is used to find the gain of the state-feedback controller. Another 'MI is derived to design the gains of the state observer and the improved EID estimator for the other subsystem. A case study on a metal-cutting system validates the superiority of the developed method.
Despite the vast progress and achievements in systems biology and integrative physiology in the last decades, there is still a significant gap in understanding the mechanisms through which (i) ...genomic, proteomic and metabolic factors and signaling pathways impact vertical processes across cells, tissues and organs leading to the expression of different disease phenotypes and influence the functional and clinical associations between diseases, and (ii) how diverse physiological systems and organs coordinate their functions over a broad range of space and time scales and horizontally integrate to generate distinct physiologic states at the organism level. Two emerging fields, network medicine and network physiology, aim to address these fundamental questions. Novel concepts and approaches derived from recent advances in network theory, coupled dynamical systems, statistical and computational physics show promise to provide new insights into the complexity of physiological structure and function in health and disease, bridging the genetic and sub-cellular level with inter-cellular interactions and communications among integrated organ systems and sub-systems. These advances form first building blocks in the methodological formalism and theoretical framework necessary to address fundamental problems and challenges in physiology and medicine. This 'focus on' issue contains 26 articles representing state-of-the-art contributions covering diverse systems from the sub-cellular to the organism level where physicists have key role in laying the foundations of these new fields.
Precise control of solid-state elastic waves' mode content and coherence is of great use nowadays in reinforcing mechanical energy harvesting/storage, nondestructive material testing, wave-matter ...interaction, high sensitivity sensing, and information processing, etc. Its efficacy is highly dependent on having elastic transmission channels with lower loss and higher degree of freedom. Here, we demonstrate experimentally an elastic analog of the quantum spin Hall effects in a monolithically scalable configuration, which opens up a route in manipulating elastic waves represented by elastic pseudospins with spin-momentum locking. Their unique features including robustness and negligible propagation loss may enhance elastic planar-integrated circuit-level and system-level performance. Our approach promotes topological materials that can interact with solid-state phonons in both static and time-dependent regimes. It thus can be immediately applied to multifarious chip-scale topological phononic devices, such as path-arbitrary elastic wave-guiding, elastic splitters and elastic resonators with high-quality factors.
PDF
