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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.

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.

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.

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 interplay between metabolic pathways and the cellular survival programs that enable tumors to grow are poorly understood. Heat shock factor 1 (HSF1) coordinates an unexpectedly diverse transcriptional network involved in oncogenesis. Santagata et al. (p. 1238303 ; see the Perspective by Gandin and Topisirovic ) found that reduced translation may be used to sense a cell's metabolic status and regulate transcription, in particular by inactivating HSF1 with consequent affects on its targets. Small-molecule drugs that affected this link were able to inhibit the growth of transformed cells in culture and of an animal tumor model. Chemical and genetic screening links ribosome activity levels and a transcriptional regulator in malignant cells. [Also see Perspective by Gandin and Topisirovic ] The ribosome is centrally situated to sense metabolic states, but whether its activity, in turn, coherently rewires transcriptional responses is unknown. Here, through integrated chemical-genetic analyses, we found that a dominant transcriptional effect of blocking protein translation in cancer cells was inactivation of heat shock factor 1 (HSF1), a multifaceted transcriptional regulator of the heat-shock response and many other cellular processes essential for anabolic metabolism, cellular proliferation, and tumorigenesis. These analyses linked translational flux to the regulation of HSF1 transcriptional activity and to the modulation of energy metabolism. Targeting this link with translation initiation inhibitors such as rocaglates deprived cancer cells of their energy and chaperone armamentarium and selectively impaired the proliferation of both malignant and premalignant cells with early-stage oncogenic lesions.

Metal nanoparticles (NPs) with size comparable to their electron mean free path possess unusual properties and functionalities 1 , serving as model systems to explore quantum and classical coupling interactions as well as building blocks of practical applications 2 , 3 , 4 , 5 , 6 , 7 , 8 . Although advances in strategies for synthesizing metal NPs have enabled control of size, composition and shape 9 , 10 , 11 , 12 , 13 , the requirement that defects are simultaneously controlled, to ensure essential perfect nanocrystallinity for physics modelling as well as device optimization, is a potentially more significant issue, but has posed substantial technological challenges. Here we report that crystallinity of monodisperse silver NPs can be well controlled by judicious choice of functional groups of molecular precursors, thus facilitating investigation of their scope for versatile applications. We demonstrate how nanoscale chemical transformation, electron–phonon interactions and nanomechanical properties are modified by nanocrystallinity. Lastly, we find that performance of NP-based molecular sensing devices can be optimized with significant improvement of figure of merit if perfect single-crystalline NPs are applied. Our approach represents a versatile synthetic route for other metal nanomaterials with unprecedented control of their structure, creating a rational pathway for understanding and manipulating nanoscale chemical and physical processes as well as technological applications of metal NPs.

Uric acid (UA) is a risk factor for endothelial dysfunction, a process in which inflammation may play an important role. UA increases high mobility group box chromosomal protein 1 (HMGB1) expression and extracellular release in endothelial cells. HMGB1 is an inflammatory cytokine that interacts with the receptor for advanced glycation end products (RAGE), inducing an oxidative stress and inflammatory response, which leads to endothelial dysfunction. In this study, human umbilical vein endothelial cells (HUVECs) were incubated with a high concentration of UA (20 mg/dL) after which endothelial function and the expression of HMGB1, RAGE, nuclear factor kappa B (NF-κB), inflammatory cytokines, and adhesion molecules were evaluated. UA inhibited endothelial nitric oxide synthase (eNOS) expression and nitric oxide (NO) production in HUVECs, increased intracellular HMGB1 expression and extracellular HMGB1 secretion, and upregulated RAGE expression. UA also activated NF-κB and increased the level of inflammatory cytokines. Blocking RAGE significantly suppressed the upregulation of RAGE and HMGB1 and prevented the increase in DNA binding activity of NF-κB and the levels of inflammatory cytokines. It also blocked the decrease in eNOS expression and NO production induced by UA. Our results suggest that high concentrations of UA cause endothelial dysfunction via the HMGB1/RAGE signaling pathway.