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Programmed cell death 1 receptor (PD-1) and its ligands constitute an inhibitory pathway to mediate the mechanism of immune tolerance and provide immune homeostasis. Significantly, the binding partners of PD-1 and its associated ligands are diverse, which facilitates immunosuppression in cooperation with other immune checkpoint proteins. Accumulating evidence has demonstrated the important immunosuppressive role of the PD-1 axis in the tumor microenvironment and in autoimmune diseases. In addition, PD-1 blockades have been approved to treat various cancers, including solid tumors and hematological malignancies. Here, we provide a comprehensive review of the PD-1 pathway, focusing on the structure and expression of PD-1, programmed cell death 1 ligand 1 (PD-L1), and programmed cell death 1 ligand 2 (PD-L2); the diverse biological functions of PD-1 signaling in health and immune-related diseases (including tumor immunity, autoimmunity, infectious immunity, transplantation immunity, allergy and immune privilege); and immune-related adverse events related to PD-1 and PD-L1 inhibitors.

Exchange bias is a property of widespread technological utility, but its underlying mechanism remains elusive, in part because it is rooted in the interaction of coexisting order parameters in the presence of complex magnetic disorder. Here we show that a giant exchange bias housed within a spin-glass phase arises in a disordered antiferromagnet. The magnitude and robustness of the exchange bias emerges from a convolution of two energetic landscapes, namely the highly degenerate landscape of the spin glass biased by the sublattice spin configuration of the antiferromagnet. The former provides a source of uncompensated moment, whereas the latter provides a mechanism for its pinning, which leads to the exchange bias. Tuning the relative strengths of the spin-glass and antiferromagnetic order parameters reveals a principle for tailoring the exchange bias, with potential applications to spintronic technologies.Coexistence of a spin-glass phase with antiferromagnetism in an intercalated crystal produces a large exchange bias effect. This is due to the interplay of disorder and frustration.

This study aimed to assess the effects of restricting mobile phone use before bedtime on sleep, pre-sleep arousal, mood, and working memory. Thirty-eight participants were randomized to either an intervention group (n = 19), where members were instructed to avoid using their mobile phone 30 minutes before bedtime, or a control group (n = 19), where the participants were given no such instructions. Sleep habit, sleep quality, pre-sleep arousal and mood were measured using the sleep diary, the Pittsburgh sleep quality index, the Pre-sleep Arousal Scale and the Positive and Negative Affect Schedule respectively. Working memory was tested by using the 0-,1-,2-back task (n-back task). Restricting mobile phone use before bedtime for four weeks was effective in reducing sleep latency, increasing sleep duration, improving sleep quality, reducing pre-sleep arousal, and improving positive affect and working memory. Restricting mobile phone use close to bedtime reduced sleep latency and pre-sleep arousal and increased sleep duration and working memory. This simple change to moderate usage was recommended to individuals with sleep disturbances.

Drug-target interaction (DTI) is the basis of drug discovery. However, it is time-consuming and costly to determine DTIs experimentally. Over the past decade, various computational methods were proposed to predict potential DTIs with high efficiency and low costs. These methods can be roughly divided into several categories, such as molecular docking-based, pharmacophore-based, similarity-based, machine learning-based, and network-based methods. Among them, network-based methods, which do not rely on three-dimensional structures of targets and negative samples, have shown great advantages over the others. In this article, we focused on network-based methods for DTI prediction, in particular our network-based inference (NBI) methods that were derived from recommendation algorithms. We first introduced the methodologies and evaluation of network-based methods, and then the emphasis was put on their applications in a wide range of fields, including target prediction and elucidation of molecular mechanisms of therapeutic effects or safety problems. Finally, limitations and perspectives of network-based methods were discussed. In a word, network-based methods provide alternative tools for studies in drug repurposing, new drug discovery, systems pharmacology and systems toxicology.

Background As one of the deadliest diseases in the world, cancer is driven by a few somatic mutations that disrupt the normal growth of cells, and leads to abnormal proliferation and tumor development. The vast majority of somatic mutations did not affect the occurrence and development of cancer; thus, identifying the mutations responsible for tumor occurrence and development is one of the main targets of current cancer treatments. Results To effectively identify driver genes, we adopted a semi-local centrality measure and gene mutation effect function to assess the effect of gene mutations on changes in gene expression patterns. Firstly, we calculated the mutation score for each gene. Secondly, we identified differentially expressed genes (DEGs) in the cohort by comparing the expression profiles of tumor samples and normal samples, and then constructed a local network for each mutation gene using DEGs and mutant genes according to the protein–protein interaction network. Finally, we calculated the score of each mutant gene according to the objective function. The top-ranking mutant genes were selected as driver genes. We name the proposed method as mutations effect and network centrality. Conclusions Four types of cancer data in The Cancer Genome Atlas were tested. The experimental data proved that our method was superior to the existing network-centric method, as it was able to quickly and easily identify driver genes and rare driver factors.

Background Reactive oxygen species (ROS) levels largely determine pulmonary fibrosis. Antioxidants have been found to ameliorate lung fibrosis after long-term paraquat (PQ) exposure. The effects of antioxidants, however, on the signalling pathways involved in PQ-induced lung fibrosis have not yet been investigated sufficiently. Here, we examined the impacts of ligustrazin on lung fibrosis, in particular ROS-related autophagy and pro-fibrotic signalling pathways, using a murine model of PQ-induced lung fibrosis. Methods We explored the effects of microRNA-193 (miR-193a) on Hedgehog (Hh) and PI3K/Akt/mTOR signalling and oxidative stress in lung tissues. Levels of miR-193a, protein kinase B (Akt), phosphoinositide 3-Kinase (PI3K), ceclin1, mammalian target of rapamycin (mTOR), sonic hedgehog (SHH), myosin-like Bcl2 interacting protein (LC3), smoothened (Smo), and glioma-associated oncogene-1 (Gli-1) mRNAs were determined with quantitative real-time PCR. Protein levels of PI3K, p-mTOR, p-Akt, SHH, beclin1, gGli-1, LC3, smo, transforming growth factor-β1 (TGF-β1), mothers against DPP homologue-2 (Smad2), connective tissue growth factor (CTGF), collagen I, collagen III, α-smooth muscle actin (α-SMA) nuclear factor erythroid 2p45-related factor-2 (Nrf2), and p-Smad2 were detected by western blotting. In addition, α-SMA, malondialdehyde, ROS, superoxide dismutase (SOD), oxidised and reduced glutathione, hydroxyproline, and overall collagen levels were identified in lung tissues using immunohistochemistry. Results Long-term PQ exposure blocked miR-193a expression, reduced PI3K/Akt/mTOR signalling, increased oxidative stress, inhibited autophagy, increased Hh signalling, and facilitated the formation of pulmonary fibrosis. Ligustrazin blocked PI3K/Akt/mTOR and Hh signalling as well as reduced oxidative stress via increasing miR-193a expression and autophagy, all of which reduced pulmonary fibrosis. These effects of ligustrazin were accompanied by reduced TGF-β1, CTGF, and Collagen I and III expression. Conclusions Ligustrazin blocked PQ-induced PI3K/Akt/mTOR and Hh signalling by increasing miR-193a expression, thereby attenuating PQ-induced lung fibrosis.

Plant-derived nature products, known as herb formulas, have been commonly used in Traditional Chinese Medicine (TCM) for disease prevention and treatment. The herbs have been traditionally classified into different categories according to the TCM Organ systems known as Meridians. Despite the increasing knowledge on the active components of the herbs, the rationale of Meridian classification remains poorly understood. In this study, we took a machine learning approach to explore the classification of Meridian. We determined the molecule features for 646 herbs and their active components including structure-based fingerprints and ADME properties (absorption, distribution, metabolism and excretion), and found that the Meridian can be predicted by machine learning approaches with a top accuracy of 0.83. We also identified the top compound features that were important for the Meridian prediction. To the best of our knowledge, this is the first time that molecular properties of the herb compounds are associated with the TCM Meridians. Taken together, the machine learning approach may provide novel insights for the understanding of molecular evidence of Meridians in TCM.

Topological domain structures have drawn great attention as they have potential applications in future electronic devices. As an important concept linking the quantum and classical magnetism, a magnetic Bloch point, predicted in 1960s but not observed directly so far, is a singular point around which magnetization vectors orient to nearly all directions. Here we show polar Bloch points in tensile-strained ultrathin ferroelectric PbTiO 3 films, which are alternatively visualized by phase-field simulations and aberration-corrected scanning transmission electron microscopic imaging. The phase-field simulations indicate local steady-state negative capacitance around the Bloch points. The observation of polar Bloch points and their emergent properties consequently implies novel applications in future integrated circuits and low power electronic devices. Authors predict polar Bloch points with negative capacitance in tensile-strained ultrathin ferroelectric PbTiO 3 film by phase-field simulations, observing their polarization structures by scanning transmission electron microscopic imaging.

Happiness, defined as a state of well-being and contentment, is a central human goal. Despite advances in customer behavior research related to value co-creation, the link between customer happiness and these behaviors remains unclear. This study therefore examines customers' in-role participation behavior and extra-role citizenship behavior to determine their influence on customers' happiness. Customer participation and citizenship behaviors relate positively to customers' perceptions of both service performance and their contributions to others' welfare. In addition, collectivism moderates the relationship between perceived contributions to others' welfare and happiness; individualism instead moderates the relationship between perceived service performance and happiness. These findings provide both managerial implications and directions for business marketing ethics.

The period of polar domain ( d ) in ferroics was commonly believed to scale with corresponding film thicknesses ( h ), following the classical Kittel’s law of d ∝ h . Here, we have not only observed that this relationship fails in the case of polar skyrmions, where the period shrinks nearly to a constant value, or even experiences a slight increase, but also discovered that skyrmions have further persisted in [(PbTiO 3 ) 2 /(SrTiO 3 ) 2 ] 10 ultrathin superlattices. Both experimental and theoretical results indicate that the skyrmion periods ( d ) and PbTiO 3 layer thicknesses in superlattice ( h ) obey the hyperbolic function of d  = A h  +  B h other than previous believed, simple square root law. Phase-field analysis indicates that the relationship originates from the different energy competitions of the superlattices with PbTiO 3 layer thicknesses. This work exemplified the critical size problems faced by nanoscale ferroelectric device designing in the post-Moore era. Here, the authors find that ferroelectric skyrmions can be sustained in [(PbTiO 3 ) 2 /(SrTiO 3 ) 2 ] m ultrathin superlattices. The period-thickness relationship of skyrmions in the ultrathin PbTiO 3 layers breaks Kittel’s law.