Activation Of α7 Nicotinic Acetylcholine Receptors Prevents Monosodium Iodoacetate-Induced Osteoarthritis In Rats

Background/Aims: Although some evidence suggests that the prevalence of osteoarthritis (OA) is lower in smokers compared to nonsmokers, the mechanisms of nicotine-induced protection remain unclear. Stimulation of the α7 nicotinic acetylcholine receptor (α7-nAChR) appears to be a critical mechanism underlying the anti-inflammatory potential of cholinergic agonists in immune cells. The inhibition of secreted inflammatory molecules and the subsequent inflammatory processes have been proposed as a novel strategy for the treatment of OA. The objective of the present study was to determine whether nicotine-induced protection in a monosodium iodoacetate (MIA) rat model of OA occurs via α7-nAChR-mediated inhibition of chondrocytes. Methods: Both in vivo (MIA) and in vitro (MIA; Interleukin-1β, IL-1β) models of OA were used to investigate the roles and the possible mechanisms whereby α7-nAChRs protect against knee joint degradation. Multiple experimental approaches, including macroscopic, histological analysis, chondrocyte cell cultures, confocal microscopy, and western blotting, were employed to elucidate the mechanisms of α7-nAChR-mediated protection. Results: Systemic administration of nicotine alleviated MIA-induced joint degradation. The protective effects of nicotine were abolished by administration of the α7-nAChR-selective antagonist methyllycaconitine (MLA). In primary cultured rat chondrocytes, pretreatment with nicotine suppressed both p38, extracellular regulated kinase (Erk) 1/2 and c-Jun-N-terminal kinase (JNK) mitogen-activated protein kinases (MAPK) phosphorylation and phosphorylated nuclear factor-kappa B (NF-κB) p65 activation induced by MIA- or IL-1β, and these effects were also reversed by MLA. Conclusion: Taken together, our results suggest that activation α7-nAChRs is an important mechanism underlying the protective effects of nicotine

Aboveground dry matter and grain yield of summer maize under different varieties and densities in North China Plain

To increase summer maize grain yield in North China Plain, we conducted field experiments with three densities (3, 6, and 9 plants m-2) on two plant types (a flat type, LD981, and a compact type, LD818) during 2010 and 2011 summer maize growing seasons to study leaf area index (LAI), above ground dry matter accumulation, grain filling rate, and grain yield. The results indicated that with the density increased, the LAI in the both varieties enhanced; however, plant density at the rate of 9 plants m-2 significantly (LSD, P < 0.05) increased LAI in LD818. Increasing densities enhanced the above ground dry matter of LD818, but not of LD981. With the density increased, the grain filling rate in the both varieties declined, but during the later growing season, the grain filling rate in LD818 was higher than that in LD919. Irrespective of plant density at the rate of from 3 to 6 or 6 to 9 plants m-2, the grain No. per ear, 1,000-kernel weight, and ears No. per m2 in LD981 were all lower than those in LD818; this was the main reason why with the increased density, the population yield in LD981 was lower than that in LD818. These results indicate that in North China Plain, increasing plant density could enhance the grain yield of compact type summer maize

Interkingdom multi-omics analysis reveals the effects of nitrogen application on growth and rhizosphere microbial community of Tartary buckwheat

Tartary buckwheat (Fagopyrum tataricum Gaertn.) is an important pseudocereal crop with excellent edible, nutritional and medicinal values. However, the yield of Tartary buckwheat (TB) is very low due to old-fashioned cultivation techniques, particularly unreasonable application of nitrogen fertilizer. To improve the understanding on the theories of nitrogen use in TB, the effects of nitrogen application on growth, as well as chemical properties and microbial community of rhizosphere soil were investigated in this study. Nitrogen application could promote the plant height, stem diameter, nitrogen accumulation and yield of TB. The relative abundance and diversity of bacteria and fungi in the rhizosphere soil of TB were improved by nitrogen fertilizer. Nitrogen application increased the abundance of beneficial bacteria such as Lysobacter and Sphingomonas in rhizosphere soil, and decreased the abundance of pathogenic fungi such as Fusarium and Plectosphaerella. The results indicated that nitrogen application changed the distribution of microbial communities in TB rhizosphere soil. Furthermore, the specific enriched or depleted microorganisms in the rhizosphere soil of four TB varieties were analyzed at OTU level. 87 specific nitrogen-responsive genes with sequence variation were identified in four varieties by integrating genomic re-sequencing and transcriptome analysis, and these genes may involve in the recruitment of specific rhizosphere microorganisms in different TB varieties. This study provided new insights into the effects of nitrogen application on TB growth and rhizosphere microbial community, and improved the understanding on the mechanisms of TB root–microbe interactions

DepthFormer: A High-Resolution Depth-Wise Transformer for Animal Pose Estimation

Animal pose estimation has important value in both theoretical research and practical applications, such as zoology and wildlife conservation. A simple but effective high-resolution Transformer model for animal pose estimation called DepthFormer is provided in this study to address the issue of large-scale models for multi-animal pose estimation being problematic with limited computing resources. We make good use of a multi-branch parallel design that can maintain high-resolution representations throughout the process. Along with two similarities, i.e., sparse connectivity and weight sharing between self-attention and depthwise convolution, we utilize the delicate structure of the Transformer and representative batch normalization to design a new basic block for reducing the number of parameters and the amount of computation required. In addition, four PoolFormer blocks are introduced after the parallel network to maintain good performance. Benchmark evaluation is performed on a public database named AP-10K, which contains 23 animal families and 54 species, and the results are compared with the other six state-of-the-art pose estimation networks. The results demonstrate that the performance of DepthFormer surpasses that of other popular lightweight networks (e.g., Lite-HRNet and HRFormer-Tiny) when performing this task. This work can provide effective technical support to accurately estimate animal poses with limited computing resources

Research on Critical Factors Influencing Organizational Resilience of Major Transportation Infrastructure Projects: A Hybrid Fuzzy DEMATEL-ISM-MICMAC Approach

To strengthen major transportation infrastructure projects’ (MTIPs’) organizational resilience and fortify their capacity for crisis management and project risk prevention. In this paper, based on the resilience theory development process, the connotation of organizational resilience of MTIPs is defined, and 20 influencing factors of organizational resilience of MTIPs are extracted from four categories of stability, redundancy, adaptability, and rapidity according to the literature analysis and case study method. The significance, causality, and multilevel recursive order structure of the influencing factors were investigated by the fuzzy DEMATEL-ISM approach, and their driving and dependent characteristics were analyzed through MICMAC. The results indicate that risk warning and prediction, human resources management, inter-organizational synergies, resource reserve situations, organizational leadership, and organizational learning are the crucial factors of organizational resilience in MTIPs. There are three levels and five ranks in the multilevel recursive rank structure of the factors affecting MTIPs’ organizational resilience. Among them, risk warning and prediction, equipment condition and performance, human resources management, and organizational leadership have the deepest impact on organizational resilience in MTIPs. The findings can clarify ideas for subsequent research on organizational resilience in this area and inform project decision-makers in developing strategies for optimizing organizational resilience

DepthFormer: A High-Resolution Depth-Wise Transformer for Animal Pose Estimation

Animal pose estimation has important value in both theoretical research and practical applications, such as zoology and wildlife conservation. A simple but effective high-resolution Transformer model for animal pose estimation called DepthFormer is provided in this study to address the issue of large-scale models for multi-animal pose estimation being problematic with limited computing resources. We make good use of a multi-branch parallel design that can maintain high-resolution representations throughout the process. Along with two similarities, i.e., sparse connectivity and weight sharing between self-attention and depthwise convolution, we utilize the delicate structure of the Transformer and representative batch normalization to design a new basic block for reducing the number of parameters and the amount of computation required. In addition, four PoolFormer blocks are introduced after the parallel network to maintain good performance. Benchmark evaluation is performed on a public database named AP-10K, which contains 23 animal families and 54 species, and the results are compared with the other six state-of-the-art pose estimation networks. The results demonstrate that the performance of DepthFormer surpasses that of other popular lightweight networks (e.g., Lite-HRNet and HRFormer-Tiny) when performing this task. This work can provide effective technical support to accurately estimate animal poses with limited computing resources

An Attention-Refined Light-Weight High-Resolution Network for Macaque Monkey Pose Estimation

Macaque monkey is a rare substitute which plays an important role for human beings in relation to psychological and spiritual science research. It is essential for these studies to accurately estimate the pose information of macaque monkeys. Many large-scale models have achieved state-of-the-art results in pose macaque estimation. However, it is difficult to deploy when computing resources are limited. Combining the structure of high-resolution network and the design principle of light-weight network, we propose the attention-refined light-weight high-resolution network for macaque monkey pose estimation (HR-MPE). The multi-branch parallel structure is adopted to maintain high-resolution representation throughout the process. Moreover, a novel basic block is designed by a powerful transformer structure and polarized self-attention, where there is a simple structure and fewer parameters. Two attention refined blocks are added at the end of the parallel structure, which are composed of light-weight asymmetric convolutions and a triplet attention with almost no parameter, obtaining richer representation information. An unbiased data processing method is also utilized to obtain an accurate flipping result. The experiment is conducted on a macaque dataset containing more than 13,000 pictures. Our network has reached a 77.0 AP score, surpassing HRFormer with fewer parameters by 1.8 AP

Complimentary return-freight insurance serves the dark side: An innovative online return policy in China

E-commerce is a typical form of retail digitalization that introduces online uncertainty and product returns. To decrease the negative influence of online uncertainty, the largest Chinese e-commerce company, the Alibaba Group, invited an insurance company to develop return-freight insurance (RFI), a new kind of insurance, to compensate for consumers' losses in the event of online product returns. Complimentary RFI can increase consumer confidence in the retailer and attract more demand. Retailers who offer complimentary RFI demonstrate to consumers that their products and services are too good to incur excessive product returns. However, some low-quality online retailers can mimic competitors’ behavior by offering complimentary RFI to consumers. This study aims to introduce an innovative online return policy based on RFI and to explore whether low-quality online retailers would use complimentary RFI as their return strategy to mislead consumers. Using signaling theory, we built a conceptual economic model that includes three exogenous pricing variables: RFI, insurance premium, and compensation. These variables play different roles in the model because consumers cannot observe the insurance premium, but the compensation can be. The main finding of this study is that innovative complimentary RFI could be abused by low-type retailers when the premium and compensation are appropriate. Interestingly, compensation plays different roles for retailers with different product values: low-type retailers use complimentary RFI as a noise tool. When the product works for the consumer and the insurance profit is not too high, the compensation for the low-quality product should be larger than that for the high-quality product, which is different from conventional wisdom. Although high-type online retailers may use complimentary RFI as a product quality signal, there is still a significant risk that nefarious elements will use it to create product quality noise

Decay of 1.643 h

The decay of 95Ru has been investigated by means of γ-ray spectroscopy. The 95Ru nuclei were produced by the reaction 92Mo( α, n) 95Ru at a beam energy of 17MeV. High-purity Ge detectors have been used singly and in coincidence to study γ-rays in the decay of 95Ru to 95Tc. 132 γ-rays are reported, among them, energies and intensities for 127 transitions have been determined. A decay scheme of 95Ru with 31 levels is proposed which accommodates 127 of these transitions. Spins and parities for three new levels are proposed from calculated log ft values, measured γ-ray branching ratios, and in-beam experiment results of the daughter nucleus 95Tc. Combining with the high-spin states observed by in-beam γ-ray spectroscopy of previous decay works, the structure of the excited states of 95Tc is discussed in the framework of the projected shell model

A Multi-Objective Optimisation Mathematical Model with Constraints Conducive to the Healthy Rhythm for Lighting Control Strategy

Studies have shown that illuminance and correlated colour temperature (CCT) are strongly correlated with body responses such as circadian rhythm, alertness, and mood. It is worth noting that these responses show a complex and variable coupling, which needs to be solved using accurate mathematical models for the regulation of indoor light parameters. Therefore, in this study, by weighing the evaluations of visual comfort, alertness, valence, and arousal of mood, a multi-objective optimisation mathematical model was developed with constraints conducive to the healthy rhythm. The problem was solved with the multi-objective evolutionary algorithm based on the decomposition differential evolution (MOEA/D-DE) algorithm. Taking educational space as the analysis goal, a dual-parameter setting strategy for illuminance and CCT covering four modes was proposed: focused learning, comfortable learning, soothing learning, and resting state, which could provide a scientific basis for the regulation of the lighting control system. The alertness during class time reached 3.01 compared to 2.34 during break time, showing a good light facilitation effect. The proposed mathematical model and analysis method also have the potential for application in the lighting design and control in other spaces to meet the era of intelligent, highly flexible, and sustainable buildings