Nitric oxide-induced lipophagic defects contribute to testosterone deficiency in rats with spinal cord injury

IntroductionMales with acute spinal cord injury (SCI) frequently exhibit testosterone deficiency and reproductive dysfunction. While such incidence rates are high in chronic patients, the underlying mechanisms remain elusive.Methods and resultsHerein, we generated a rat SCI model, which recapitulated complications in human males, including low testosterone levels and spermatogenic disorders. Proteomics analyses showed that the differentially expressed proteins were mostly enriched in lipid metabolism and steroid metabolism and biosynthesis. In SCI rats, we observed that testicular nitric oxide (NO) levels were elevated and lipid droplet-autophagosome co-localization in testicular interstitial cells was decreased. We hypothesized that NO impaired lipophagy in Leydig cells (LCs) to disrupt testosterone biosynthesis and spermatogenesis. As postulated, exogenous NO donor (S-nitroso-N-acetylpenicillamine (SNAP)) treatment markedly raised NO levels and disturbed lipophagy via the AMPK/mTOR/ULK1 pathway, and ultimately impaired testosterone production in mouse LCs. However, such alterations were not fully observed when cells were treated with an endogenous NO donor (L-arginine), suggesting that mouse LCs were devoid of an endogenous NO-production system. Alternatively, activated (M1) macrophages were predominant NO sources, as inducible NO synthase inhibition attenuated lipophagic defects and testosterone insufficiency in LCs in a macrophage-LC co-culture system. In scavenging NO (2-4-carboxyphenyl-4,4,5,5-tetramethylimidazoline-1-oxyl-3-oxide (CPTIO)) we effectively restored lipophagy and testosterone levels both in vitro and in vivo, and importantly, spermatogenesis in vivo. Autophagy activation by LYN-1604 also promoted lipid degradation and testosterone synthesis.DiscussionIn summary, we showed that NO-disrupted-lipophagy caused testosterone deficiency following SCI, and NO clearance or autophagy activation could be effective in preventing reproductive dysfunction in males with SCI

ATLAS Electron and Photon Trigger

ATLAS electron and photon triggers covering transverse energies from 5 GeV to several TeV are essential to record signals for a wide variety of physics: from Standard Model processes to searches for new phenomena. To cope with ever-increasing luminosity and more challenging pile-up conditions at a centre-of-mass energy of 13 TeV, the trigger selections need to be optimized to control the rates and keep efficiencies high. The ATLAS electron and photon performance during the Run 2 is presented, including new techniques developed to maintain their high performance even in high pile-up conditions

An Evolutionary Game with Reputation-based Imitation-Mutation Dynamics

Reputation plays a crucial role in social interactions by affecting the fitness of individuals during an evolutionary process. Previous works have extensively studied the result of imitation dynamics without focusing on potential irrational choices in strategy updates. We now fill this gap and explore the consequence of such kind of randomness, or one may interpret it as an autonomous thinking. In particular, we study how this extended dynamics alters the evolution of cooperation when individual reputation is directly linked to collected payoff, hence providing a general fitness function. For a broadly valid conclusion, our spatial populations cover different types of interaction topologies, including lattices, small-world and scale- free graphs. By means of intensive simulations we can detect substantial increase in cooperation level that shows a reasonable stability in the presence of a notable strategy mutation

Prisoner’s Dilemma Game with Cooperation-Defection Dominance Strategies on Correlational Multilayer Networks

As multilayer networks are widely applied in modern society, numerous studies have shown the impact of a multilayer network structure and the network nature on the proportion of cooperators in the network. In this paper, we use Barabási–Albert scale-free networks (BA) and Watts and Strogatz networks (WS) to build a multilayer network structure, and we propose a new strategy-updating rule called “cooperation-defection dominance”, which can be likened to dominant and recessive traits in biogenetics. With the newly constructed multilayer network structure and the strategy-updating rules, based on the simulation results, we find that in the BA-BA network, the cooperation dominance strategy can make the networks with different rs show a cooperative trend, while the defection dominance strategy only has an obvious effect on the network cooperation with a larger r. When the BA network is connected to the WS network, we find that the effect of strategy on the proportion of cooperators in the network decreases, and the main influencing factor is the structure of the network. In the three-layer network, the cooperation dominance strategy has a greater impact on the BA network, and the proportion of the cooperators is enhanced more than under the natural evolution strategy, but the promotion effect is still smaller than that of the two-layer BA network because of the WS network. Under the defection dominance strategy, the WS layer appears different from the first two strategies, and we conclude through simulation that when the payoff parameter is at the middle level, its cooperator proportion will be suppressed, and we deduce that the proportion of cooperators and defectors, as well as the payoff, play an important role

Coevolution of relationship and interaction in cooperative dynamical multiplex networks

Albeit actors in a population can interact with anyone else freely, but our standard relations largely boost our willingness whom to select. The consequence of such interactions, however, may also form the intensity of our relations. These dynamical processes are captured via a coevolutionary model where we introduce multiplex networks with two distinct layers. In a relationship layer the weights of edges among players may change in time as a consequence of games played in the interaction layer. As an reasonable assumption, bilateral cooperation confirms while mutual defection weakens these weight factors. Importantly, the fitness of a player, which basically determines the success of a strategy imitation, depends not only on the payoff collected from interactions, but also on the individual relationship index calculated from the mentioned weight factors of related edges. Within the framework of weak prisoner’s dilemma situation we explore the potential outcomes of the mentioned coevolutionary process where we assume different topologies for relationship layer. We find that higher average degree of the relationship graph is more beneficial to maintain cooperation, but the randomness of links could be a decisive factor in harsh situations. Surprisingly, a stronger coupling between relationship index and fitness discourage the evolution of cooperation by weakening the direct consequence of a strategy change. To complete our study we also monitor how the distribution of relationship index vary and detect a strong relation between its polarization and the general cooperation level

Communication-Efficient Federated Learning with Adaptive Consensus ADMM

This paper proposes utilizing federated learning (FL), a distributed learning paradigm, to process large, decentralized, and heterogeneous edge data in the context of Internet of Things (IoT) devices. However, heterogeneity and high communication costs are two primary challenges that hinder the efficacy of federated learning. To overcome these challenges, we have designed an algorithm, FedACADMM, which applies the adaptive consensus alternating direction method of multipliers (ACADMM) to federated learning clients (i.e., the edge mobile devices) to tackle the heterogeneity problem in federated networks. Importantly, the cost per round of communication for FedACADMM remains consistent with FedAvg and FedProx without adding any extra workload. Furthermore, our experimental results demonstrate that FedACADMM outperforms baseline methods with a realistic set of federated datasets, displaying enhanced convergence robustness. Notably, in highly heterogeneous scenarios, FedACADMM exhibits significant stability and rapid convergence, requiring at least 75% fewer communication rounds to achieve the target accuracy

Multi-Role Collaborative Behavior in the Construction Industry through Training Strategies

From a stakeholder perspective, the personal growth of industrial personnel is important for the promotion of the sustainable development of the construction industry. As an important part of knowledge management, training is a common way to improve the personal knowledge and skills of construction practitioners. Group role assignment with a training plan is thought to optimize group performance and the assignment of personnel with collaborative behaviors. However, existing mathematical models or approaches have mainly considered the loss of downtime caused by training while ignoring the different costs of training programs and personal capabilities, which affect the overall benefits. Hence, to solve the training-related role assignment problem, the intention of this study is to formulate a new model that integrates comprehensive training costs with various personal capabilities. After training, all roles need to be reassigned to maximize the overall benefit. Four experiments were conducted. The results show that training strategies can increase the total benefit, but also weaken it when the training costs are too high. Training strategies have a cumulative effect, i.e., training performance is positively related to the knowledge and skill levels of construction practitioners. Finally, training performance varies with the industrial role

Novel mechanism by which extracellular vesicles derived from Lactobacillus murinus alleviates deoxynivalenol-induced intestinal barrier disruption

Deoxynivalenol (DON) is a common environmental pollutant that poses a serious health risk to humans worldwide. This study was aim to explore whether gut microbiota is involved in DON-induced intestinal toxicity as well as to reveal effect of probiotics derived from gut microbiota in protecting intestinal barrier and to elucidate mechanism. We found that DON caused disturbed gut microbiota, particularly Lactobacillus murinus (L. murinus) deficiency. DON enhanced M1 macrophage polarization and decreased tight junction protein expression. Microbiota transplantation experiments showed that transfer of DON-disrupted microbiota to healthy mice resulted in delivery of DON-induced intestinal toxicity. Besides, DON lost its damaging effect on macrophage and intestinal barrier in antibiotic-treated mice. Further intervention experiments revealed that L. murinus induce macrophage conversion from M1 to M2 phenotype through secreted extracellular vesicles (EVs) to alleviate DON-induced intestinal barrier disruption. Mechanistically, EVs activate TLR2 to promote M2 macrophage polarization and release IL-10, which in turn enhances intestinal barrier function. Upon successful translation of its efficacy into clinical practice, EVs created from L. murinus could be a novel possible treatment strategy for DON-induced gut disease

Discovery of Acupoints and Combinations with Potential to Treat Vascular Dementia: A Data Mining Analysis

The prevalence of vascular dementia (VaD) is high among the elderly. Acupuncture, a popular therapeutic method in China, can improve memory, orientation, calculation, and self-managing ability in VaD patients. However, in clinical acupuncture and acupuncture research, the selection of acupoints to treat VaD remains challenging. This study aimed to discover acupoints and acupoint combinations with potential for VaD based on data mining. After database searching and screening for articles on clinical trials evaluating the effects of acupuncture on VaD, 238 acupuncture prescriptions were included for further analysis. Baihui (GV 20), Sishencong (EX-HN 1), Fengchi (GB 20), Shuigou (GV 26), and Shenting (GV 24) appeared most frequently in the modern literature and are potential acupoints for VaD. Combinations between Baihui (GV 20), Sishencong (EX-HN 1), Fengchi (GB 20), Shenting (GV 24), Shuigou (GV 26), and Zusanli (ST 36) were most frequent and represent potential combinations for VaD treatment. These results provide a reference for the selection and combination of acupoints to treat VaD in clinical acupuncture and acupuncture research