Leishmaniasis is a protozoal vector-borne disease that affects both humans and animals. In the Mediterranean Basin, the primary reservoir hosts of Leishmania spp. are mainly rodents and canids. Lipidomic approaches have allowed scientists to establish Leishmania spp. lipid profiles for the identification of cell stage specific biomarkers, drug mechanisms of action, and host immune response. Using an in silico approach of global network interaction between genes involved in fatty acid (FA) synthesis followed by the GC-MS approach, we were able to characterize the fatty acid profiles of L. major derived from human and rodent hosts. Our results revealed that the lipid profile of L. major showed similarities and differences with those already reported for other Leishmania species. Phospholipids are the predominant lipid class. FA composition of rodent parasites was characterized by a lower abundance of the precursor C18:2(n-6). One of the rodent clones, which also expressed the lowest lipid abundance in PL and TAG, was the least sensitive clone to the miltefosine drug and has the lowest infection efficiency. Our findings suggest that the lipid composition variation may explain the response of the parasite toward treatment and their ability to infect their host.
This is the first study to analyze the spatial spillover effect of the internet on trade performance based on a vision of the public's sleep health. The internet's effect on trade performance has been enhanced in a new economy consisting of larger global markets. An overall improvement in health gradually impacts economic development. In this study, hierarchical modeling is applied to reveal the effect of the internet on trade performance at a fundamental level, and the effect of sleep health on trade performance at general level. The global network is structured by a spatial weight matrix based on the Mahalanobis distance of the internet and sleep health. Furthermore, spatial autoregressive modeling is applied to study the effect of the spatial weight matrix based on the Mahalanobis distance matrix of the internet and sleep health on trade performance. The spatial Durbin modeling is applied to further analyze the interaction effect of the spatial weight matrix and countries' factors on trade performance. It was found that the internet has a positive effect on trade performance, and good sleep health can be helpful to the spillover effect of the internet on trade performance. The interaction of the spatial weight matrix and gross domestic product (GDP) can further enhance the effect. This research can assist global managers to further understand the spatial spillover effect of the internet on trade performance based on a vision of the public's sleep health.
AbstractSearches for pseudo-magnetic spin couplings require implementation of techniques capable of sensitive detection of such interactions. While Spin-Exchange Relaxation Free (SERF) magnetometry is one of the most powerful approaches enabling the searches, it suffers from a strong magnetic coupling, deteriorating the pseudo-magnetic coupling sensitivity. To address this problem, here, we compare, via numerical simulations, the performance of SERF magnetometer and noble-gas-alkali-metal co-magnetometer, operating in a so-called self-compensating regime. We demonstrate that the co-magnetometer allows reduction of the sensitivity to low-frequency magnetic fields without loss of the sensitivity to nonmagnetic couplings. Based on that we investigate the responses of both systems to the oscillating and transient spin perturbations. Our simulations reveal about five orders of magnitude stronger response to the neutron pseudo-magnetic coupling and about three orders of magnitude stronger response to the proton pseudo-magnetic coupling of the co-magnetometer than those of the SERF magnetometer. Different frequency responses of the co-magnetometer to magnetic and nonmagnetic perturbations enables differentiation between these two types of interactions. This outlines the ability to implement the co-magnetometer as an advanced sensor for the Global Network of Optical Magnetometer for Exotic Physics searches (GNOME), aiming at detection of ultra-light bosons (e.g., axion-like particles).
Temporal lobe epilepsy (TLE) is commonly refractory. Epilepsy surgery is an effective treatment strategy for refractory epilepsy, but patients with a history of focal to bilateral tonic-clonic seizures (FBTCS) have poor outcomes. Previous network studies on epilepsy have found that TLE and idiopathic generalized epilepsy with generalized tonic-clonic seizures (IGE-GTCS) showed altered global and nodal topological properties. Alertness deficits also were found in TLE. However, FBTCS is a common type of seizure in TLE, and the implications for alertness as well as the topological rearrangements associated with this seizure type are not well understood.
We obtained rs-fMRI data and collected the neuropsychological assessment data from 21 TLE patients with FBTCS (TLE- FBTCS), 18 TLE patients without FBTCS (TLE-non- FBTCS) and 22 controls, and constructed their respective functional brain networks. The topological properties were analyzed using the graph theoretical approach and correlations between altered topological properties and alertness were analyzed.
We found that TLE-FBTCS patients showed more serious impairment in alertness effect, intrinsic alertness and phasic alertness than the patients with TLE-non-FBTCS. They also showed significantly higher small-worldness, normalized clustering coefficient (γ) and a trend of higher global network efficiency (gE) compared to TLE-non-FBTCS patients. The gE showed a significant negative correlation with intrinsic alertness for TLE-non-FBTCS patients.
Our findings show different impairments in brain network information integration, segregation and alertness between the patients with TLE-FBTCS and TLE-non-FBTCS, demonstrating that impairments of the brain network may underlie the disruptions in alertness functions.
Journalistic accounts of the opioid crisis often paint prescription opioids as the instrument of profit-minded pharmaceutical companies who enlisted pain specialists to overprescribe addictive drugs. Broadening beyond a focus on pharmaceutical power, this article offers a comparative-historical explanation, rooted in inter- and intra-professional dynamics, of the global increase in rates of opioid prescribing. Through archival analysis and in-depth interviews with pain specialists and public-health officials in the United States and France, I explain how and why opioids emerged as the “right tool for the job” of pain relief in the 1980s and 1990s, affecting how pain science is produced, pain management is administered, and a right to pain relief is promised in different national contexts. I argue that opioids, selected and destigmatized as the technology for pain relief, helped establish a global network of pain expertise, linking a fledgling field of pain specialists to the resources of global-health governance, public-health administration, humanitarian organizations, and pharmaceutical companies. I then compare how U.S. and French pain specialists leveraged opioids to strengthen the boundaries of their emergent fields. Pain specialists’ differing degrees of autonomy in each country’s network of pain expertise shaped the extent to which opioids could dominate pain management and lead to crisis. Tracing the relationship between opioids and pain expertise, I show how technologies can drive crises of expert credibility if and when they escape the control of the networked fields that selected them.
More and more evidence showed that long non-coding RNAs (lncRNAs) play important roles in the development and progression of human sophisticated diseases. Therefore, predicting human lncRNA-disease associations is a challenging and urgently task in bioinformatics to research of human sophisticated diseases.
In the work, a global network-based computational framework called as LRWRHLDA were proposed which is a universal network-based method. Firstly, four isomorphic networks include lncRNA similarity network, disease similarity network, gene similarity network and miRNA similarity network were constructed. And then, six heterogeneous networks include known lncRNA-disease, lncRNA-gene, lncRNA-miRNA, disease-gene, disease-miRNA, and gene-miRNA associations network were applied to design a multi-layer network. Finally, the Laplace normalized random walk with restart algorithm in this global network is suggested to predict the relationship between lncRNAs and diseases.
The ten-fold cross validation is used to evaluate the performance of LRWRHLDA. As a result, LRWRHLDA achieves an AUC of 0.98402, which is higher than other compared methods. Furthermore, LRWRHLDA can predict isolated disease-related lnRNA (isolated lnRNA related disease). The results for colorectal cancer, lung adenocarcinoma, stomach cancer and breast cancer have been verified by other researches. The case studies indicated that our method is effective.
Our subject is the legacy of Dada implicit to the Burning Man phenomenon. Animate in the provocative output of fin-de-siècle French Symbolist writer and puppeteer Alfred Jarry, and filtered through the antics of the San Francisco Cacophony Society, Dada is foundational to the cultural aesthetic of Burning Man, by which we mean the event in Nevada’s Black Rock Desert playa (Black Rock City) and a global network of “burn” events. We address the significance of the Cacophony Society expedition that inaugurated the desert phase of Burning Man in 1990, “Zone Trip # 4: Bad Day at Black Rock.” Integral to the surreal tourism ventured by Cacophonists prior to the inception of Burning Man, and pivotal to its desert phase, the Zone Trip kindled “Burner” culture on the Black Rock playa and abroad. Exploring the Dadaist impulse affecting Black Rock City and woven into a worldwide network, informed by interpretative and applied methods, the article addresses art projects (including those designed and implemented by Vitos) at three regional events—Israel’s Midburn and Germany’s Burning Bär and Kiez Burn—visited in 2018 and 2019 as part of a multisited ethnography of the Burning Man movement. As these projects illustrate, the ghost of Jarry haunts, as the spirit of Dada animates, the transnational “burnscape.”
AbstractAn experiment consisting of a network of sensors can endow several advantages over an experiment with a single sensor: improved sensitivity, error corrections, spatial resolution, etc. However, there is often a question of how to optimally set up the network to yield the best results. Here, we consider a network of devices that measure a vector field along a given axis; namely for magnetometers in the Global Network of Optical Magnetometers for Exotic physics searches (GNOME). We quantify how well the network is arranged, explore characteristics and examples of ideal networks, and characterize the optimal configuration for GNOME. We find that by re-orienting the sensitive axes of existing magnetometers, the sensitivity of the network can be improved relative to the past science runs.
Russian scientific, technical and innovation policy is aimed at R&D results mainly in the technological sphere, which have little chance of transforming into commercial products due to the incompleteness of the formation of the national innovation system. Its main drawback is the lack of attention to ensuring effective communication between all participants in innovation. The digitalization of the economy is, first of all, the digitalization of communications. The essence of this phenomenon lies in the acquisition by the communication processes and, accordingly, in giving any communication an optimal, unified and most adequate form for the current stage of scientific, technical and innovative development based on a standardset of signals (numbers). The growing communication revolution not only enhances the role of science and innovation as the main instruments of competition, but also contributes to the process of integrating country NIS into the global network structure. The observed restructuring of the global economic space is accompanied by the emergence of digital platforms that are changing the landscape of the global economy by working with big data, gaining control over the functioning of the information circuits of the global economy and ensuring the interaction of all innovative actors through effective communications.