Explore the vast range of titles available.

Exhaustion of cytotoxic effector natural killer (NK) and CD8 + T cells have important functions in the establishment of persistent viral infections, but how exhaustion is induced during chronic hepatitis C virus (HCV) infection remains poorly defined. Here we show, using the humanized C/O Tg mice permissive for persistent HCV infection, that NK and CD8 + T cells become sequentially exhausted shortly after their transient hepatic infiltration and activation in acute HCV infection. HCV infection upregulates Qa-1 expression in hepatocytes, which ligates NKG2A to induce NK cell exhaustion. Antibodies targeting NKG2A or Qa-1 prevents NK exhaustion and promotes NK-dependent HCV clearance. Moreover, reactivated NK cells provide sufficient IFN-γ that helps rejuvenate polyclonal HCV CD8 + T cell response and clearance of HCV. Our data thus show that NKG2A serves as a critical checkpoint for HCV-induced NK exhaustion, and that NKG2A blockade sequentially boosts interdependent NK and CD8 + T cell functions to prevent persistent HCV infection. Immune cells may become less responsive, or ‘exhausted’, upon chronic viral infection, but the underlying mechanism and crosstalk are still unclear. Here the authors show that, upon chronic hepatitis C virus (HCV) infection, natural killer cell exhaustion is induced by NKG2A signalling to instruct downstream exhaustion of CD8 + T cells and HCV persistence.

A promising new form-stable phase change material (PA/PB) was fabricated using pinecone biochar (PB) as the supporting material of palmitic acid (PA). The biochar of PB with large surface area was produced by forest residue of pinecone, and it was cheap, environment friendly and easy to prepare. The PB was firstly utilized as the supporter of PA and the characterizations of PA/PB were analyzed by the BET, SEM, XRD, DSC, TGA, FT-IR and thermal conductivity tester. The results demonstrated that the PA was physically absorbed by the PB and the crystal structure of the PA was not destroyed. The results of DSC showed that the fusing and crystallization points of the form-stable phase change material with the maximum content of PA (PA/PB-4) were 59.25 °C and 59.13 °C, and its fusing and freezing latent heat were 84.74 kJ/kg and 83.81 kJ/kg, respectively. The results of TGA suggested that the thermal stability of the PA/PB-4 composite was excellent, which could be used for the applications of thermal energy storage. Furthermore, the thermal conductivity of PA/PB-4 was 0.3926 W/(m∙K), which was increased by 43.76% compared with that of the pure PA. Thus, the study results indicated that the PA/PB-4 had great potential for thermal energy storage applications.

Computation offloading is one of the most important problems in edge computing. Devices can transmit computation tasks to servers to be executed through computation offloading. However, not all the computation tasks can be offloaded to servers with the limitation of network conditions. Therefore, it is very important to decide quickly how many tasks should be executed on servers and how many should be executed locally. Only computation tasks that are properly offloaded can improve the Quality of Service (QoS). Some existing methods only focus on a single objection, and of the others some have high computational complexity. There still have no method that could balance the targets and complexity for universal application. In this study, a Multi-Objective Whale Optimization Algorithm (MOWOA) based on time and energy consumption is proposed to solve the optimal offloading mechanism of computation offloading in mobile edge computing. It is the first time that MOWOA has been applied in this area. For improving the quality of the solution set, crowding degrees are introduced and all solutions are sorted by crowding degrees. Additionally, an improved MOWOA (MOWOA2) by using the gravity reference point method is proposed to obtain better diversity of the solution set. Compared with some typical approaches, such as the Grid-Based Evolutionary Algorithm (GrEA), Cluster-Gradient-based Artificial Immune System Algorithm (CGbAIS), Non-dominated Sorting Genetic Algorithm III (NSGA-III), etc., the MOWOA2 performs better in terms of the quality of the final solutions.

IntroductionGut microbiota is now considered to be a hidden organ that interacts bidirectionally with cellular responses in numerous organs belonged to the immune, bone, and nervous systems. Here, we aimed to investigate the relationships between gut microbiota and complex diseases by utilizing multiple publicly available genome-wide association.Materials and methodsWe applied a novel microbiota-related gene set enrichment analysis approach to detect the associations between gut microbiota and complex diseases by processing genome-wide association studies (GWASs) data sets of six autoimmune diseases (including celiac disease (CeD), inflammatory bowel diseases (IBD), multiple sclerosis (MS), primary biliary cirrhosis (PBC), type 1 diabetes (T1D) and primary sclerosing cholangitis (PSC)) and osteoporosis (OP).ResultsThe family Oxalobacteraceae and genus Candidatus_Soleaferrea were found to be correlated with all of the six autoimmune diseases (FDR adjusted P < 0.05). Moreover, we observed that the six autoimmune diseases except PBC shared 3 overlapping features (including family Peptostreptococcaceae, order Gastranaerophilales and genus Romboutsia). For all of the six autoimmune diseases and BMDs (LS-BMD and TB-BMD), an association signal was observed for genus Candidatus_Soleaferrea (FDR adjusted P < 0.05). Notably, FA / FN-BMD shared the maximum number of overlapping microbial features (e.g., genus Ruminococcaceae_UCG009, Erysipelatoclostridium and Ruminococcaceae_UCG013).ConclusionOur study found that part of the gut microbiota could be novel regulators of BMDs and autoimmune diseases via the effects of its metabolites and may lead to a better understanding of the role played by gut microbiota in the communication of the microbiota-skeletal/immune-gut axis.

Cytochrome P450 (CYP) 2D6 is one of the most investigated CYPs in relation to genetic polymorphism, but accounts for only a small percentage of all hepatic CYPs (∼2–4%). There is a large interindividual variation in the enzyme activity of CYP2D6. The enzyme is largely non-inducible and metabolizes ∼25% of current drugs. Typical substrates for CYP2D6 are largely lipophilic bases and include some antidepressants, antipsychotics, antiarrhythmics, antiemetics, β-adrenoceptor antagonists (β-blockers) and opioids. The CYP2D6 activity ranges considerably within a population and includes ultrarapid metabolizers (UMs), extensive metabolizers (EMs), intermediate metabolizers (IMs) and poor metabolizers (PMs). There is a considerable variability in the CYP2D6 allele distribution among different ethnic groups, resulting in variable percentages of PMs, IMs, EMs and UMs in a given population. To date, 74 allelic variants and a series of subvariants of the CYP2D6 gene have been reported and the number of alleles is still growing. Among these are fully functional alleles, alleles with reduced function and null (non-functional) alleles, which convey a wide range of enzyme activity, from no activity to ultrarapid metabolism of substrates. As a consequence, drug adverse effects or lack of drug effect may occur if standard doses are applied. The alleles *10, *17, *36 and *41 give rise to substrate-dependent decreased activity. Null alleles of CYP2D6 do not encode a functional protein and there is no detectable residual enzymatic activity. It is clear that alleles *3, *4, *5, *6, *7, *8, *11, *12, *13, *14, *15, *16, *18, *19, *20, *21, *38, *40, *42, *44, *56 and *62 have no enzyme activity. They are responsible for the PM phenotype when present in homozygous or compound heterozygous constellations. These alleles are of clinical significance as they often cause altered drug clearance and drug response. Among the most important variants are CYP2D6 *2, *3, *4, *5, *10, *17 and *41. On the other hand, the CYP2D6 gene is subject to copy number variations that are often associated with the UM phenotype. Marked decreases in drug concentrations have been observed in UMs with tramadol, venlafaxine, morphine, mirtazapine and metoprolol. The functional impact of CYP2D6 alleles may be substrate-dependent. For example, CYP2D6 *17 is generally considered as an allele with reduced function, but it displays remarkable variability in its activity towards substrates such as dextromethorphan, risperidone, codeine and haloperidol. The clinical consequence of the CYP2D6 polymorphism can be either occurrence of adverse drug reactions or altered drug response. Drugs that are most affected by CYP2D6 polymorphisms are commonly those in which CYP2D6 represents a substantial metabolic pathway either in the activation to form active metabolites or clearance of the agent. For example, encainide metabolites are more potent than the parent drug and thus QRS prolongation is more apparent in EMs than in PMs. In contrast, propafenone is a more potent b-blocker than its metabolites and the β-blocking activity during propafenone therapy is more prominent in PMs than EMs, as the parent drug accumulates in PMs. Since flecainide is mainly eliminated through renal excretion, and both R - and S -flecainide possess equivalent potency for sodium channel inhibition, the CYP2D6 phenotype has a minor impact on the response to flecainide. Since the contribution of CYP2D6 is greater for metoprolol than for carvedilol, propranolol and timolol, a stronger gene-dose effect is seen with this β-blocker, while such an effect is lesser or marginal in other β-blockers. Concordant genotype-phenotype correlation provides a basis for predicting the phenotype based on genetic testing, which has the potential to achieve optimal pharmacotherapy. However, genotype testing for CYP2D6 is not routinely performed in clinical practice and there is uncertainty regarding genotype-phenotype, gene-concentration and gene-dose relationships. Further prospective studies on the clinical impact of CYP2D6-dependent metabolism of drugs are warranted in large cohorts of subjects.

With tens of thousands of plant species on earth, we are endowed with an enormous wealth of medicinal remedies from Mother Nature. Natural products and their derivatives represent more than 50% of all the drugs in modern therapeutics. Because of the low success rate and huge capital investment need, the research and development of conventional drugs are very costly and difficult. Over the past few decades, researchers have focused on drug discovery from herbal medicines or botanical sources, an important group of complementary and alternative medicine (CAM) therapy. With a long history of herbal usage for the clinical management of a variety of diseases in indigenous cultures, the success rate of developing a new drug from herbal medicinal preparations should, in theory, be higher than that from chemical synthesis. While the endeavor for drug discovery from herbal medicines is “experience driven,” the search for a therapeutically useful synthetic drug, like “looking for a needle in a haystack,” is a daunting task. In this paper, we first illustrated various approaches of drug discovery from herbal medicines. Typical examples of successful drug discovery from botanical sources were given. In addition, problems in drug discovery from herbal medicines were described and possible solutions were proposed. The prospect of drug discovery from herbal medicines in the postgenomic era was made with the provision of future directions in this area of drug development.

Multimorbidity has become an important health challenge in the aging population. Accumulated evidence has shown that multimorbidity has complex association patterns, but the further mechanisms underlying the association patterns are largely unknown. Summary statistics of 14 conditions/diseases were available from the genome-wide association study (GWAS). Linkage disequilibrium score regression analysis (LDSC) was applied to estimate the genetic correlations. Pleiotropic SNPs between two genetically correlated traits were detected using pleiotropic analysis under the composite null hypothesis (PLACO). PLACO-identified SNPs were mapped to genes by Functional Mapping and Annotation of Genome-Wide Association Studies (FUMA), and gene set enrichment analysis and tissue differential expression were performed for the pleiotropic genes. Two-sample Mendelian randomization analyses assessed the bidirectional causality between conditions/diseases. LDSC analyses revealed the genetic correlations for 20 pairs based on different two-disease combinations of 14 conditions/diseases, and genetic correlations for 10 pairs were significant after Bonferroni adjustment (P<0.05/91 = 5.49E-04). Significant pleiotropic SNPs were detected for 11 pairs of correlated conditions/diseases. The corresponding pleiotropic genes were differentially expressed in the brain, nerves, heart, and blood vessels and enriched in gluconeogenesis and drug metabolism, biotransformation, and neurons. Comprehensive causal analyses showed strong causality between hypertension, stroke, and high cholesterol, which drive the development of multiple diseases. This study highlighted the complex mechanisms underlying the association patterns that include the shared genetic components and causal effects among the 14 conditions/diseases. These findings have important implications for guiding the early diagnosis, management, and treatment of comorbidities.

Part I of this article discussed the potential functional importance of genetic mutations and alleles of the human cytochrome P450 2D6 ( CYP2D6 ) gene. The impact of CYP2D6 polymorphisms on the clearance of and response to a series of cardiovascular drugs was addressed. Since CYP2D6 plays a major role in the metabolism of a large number of other drugs, Part II of the article highlights the impact of CYP2D6 polymorphisms on the response to other groups of clinically used drugs. Although clinical studies have observed a gene-dose effect for some tricyclic antidepressants, it is difficult to establish clear relationships of their pharmacokinetics and pharmacodynamic parameters to genetic variations of CYP2D6 ; therefore, dosage adjustment based on the CYP2D6 phenotype cannot be recommended at present. There is initial evidence for a gene-dose effect on commonly used selective serotonin reuptake inhibitors (SSRIs), but data on the effect of the CYP2D6 genotype/phenotype on the response to SSRIs and their adverse effects are scanty. Therefore, recommendations for dose adjustment of prescribed SSRIs based on the CYP2D6 genotype/phenotype may be premature. A number of clinical studies have indicated that there are significant relationships between the CYP2D6 genotype and steady-state concentrations of perphenazine, zuclopenthixol, risperidone and haloperidol. However, findings on the relationships between the CYP2D6 genotype and parkinsonism or tardive dyskinesia treatment with traditional antipsychotics are conflicting, probably because of small sample size, inclusion of antipsychotics with variable CYP2D6 metabolism, and co-medication. CYP2D6 phenotyping and genotyping appear to be useful in predicting steady-state concentrations of some classical antipsychotic drugs, but their usefulness in predicting clinical effects must be explored. Therapeutic drug monitoring has been strongly recommended for many antipsychotics, including haloperidol, chlorpromazine, fluphenazine, perphenazine, risperidone and thioridazine, which are all metabolized by CYP2D6. It is possible to merge therapeutic drug monitoring and pharmacogenetic testing for CYP2D6 into clinical practice. There is a clear gene-dose effect on the formation of O -demethylated metabolites from multiple opioids, but the clinical significance of this may be minimal, as the analgesic effect is not altered in poor metabolizers (PMs). Genetically caused inactivity of CYP2D6 renders codeine ineffective owing to lack of morphine formation, decreases the efficacy of tramadol owing to reduced formation of the active O -desmethyltramadol and reduces the clearance of methadone. Genetically precipitated drug interactions might render a standard opioid dose toxic. Because of the important role of CYP2D6 in tamoxifen metabolism and activation, PMs are likely to exhibit therapeutic failure, and ultrarapid metabolizers (UMs) are likely to experience adverse effects and toxicities. There is a clear gene-concentration effect for the formation of endoxifen and 4-OH-tamoxifen. Tamoxifen-treated cancer patients carrying CYP2D6 *4, *5, *10, or *41 associated with significantly decreased formation of antiestrogenic metabolites had significantly more recurrences of breast cancer and shorter relapse-free periods. Many studies have identified the genetic CYP2D6 status as an independent predictor of the outcome of tamoxifen treatment in women with breast cancer, but others have not observed this relationship. Thus, more favourable tamoxifen treatment seems to be feasible through a priori genetic assessment of CYP2D6, and proper dose adjustment may be needed when the CYP2D6 genotype is determined in a patient. Dolasetron, ondansetron and tropisetron, all in part metabolized by CYP2D6, are less effective in UMs than in other patients. Overall, there is a strong gene-concentration relationship only for tropisetron. CYP2D6 genotype screening prior to antiemetic treatment may allow for modification of antiemetic dosing. An alternative is to use a serotonin agent that is metabolized independently of CYP2D6, such as granisetron, which would obviate the need for genotyping and may lead to an improved drug response. To date, the functional impact of most CYP2D6 alleles has not been systematically assessed for most clinically important drugs that are mainly metabolized by CYP2D6, though some initial evidence has been identified for a very limited number of drugs. The majority of reported in vivo pharmacogenetic data on CYP2D6 are from single-dose and steady-state pharmacokinetic studies of a small number of drugs. Pharmacodynamic data on CYP2D6 polymorphisms are scanty for most drug studies. Given that genotype testing for CYP2D6 is not routinely performed in clinical practice and there is uncertainty regarding genotype-phenotype, gene-concentration and gene-dose relationships, further prospective studies on the clinical impact of CYP2D6-dependent metabolism of drugs are warranted in large cohorts.

Recent evidence has gradually recognized that the immune and skeletal systems are two closely correlated systems, but the specific immune factors on bone mineral density (BMD) are largely unknown. Based on the summary-level data of genome-wide association studies (GWASs), we performed a series of analyses including two-sample Mendelian randomization (MR) analysis to test potential causal links between 731 immune traits [including median fluorescence intensities (MFIs), absolute cell (AC) counts, relative cell (RC) counts, and morphological parameters (MP)] and BMD. After false discovery rate (FDR) correction, 9 MFI-BMD, 16 AC-BMD, 22 RC-BMD, and 5 MP-BMD pairs reached the level of significance (FDR-adjusted p < 0.05). For MFI traits, the T- and B-cell panels had the largest number of significant immune trait pairs than other panels. CD40, as a molecule expressed by four subsets of monocytes, was highlighted due to its consistently positive correlation with BMD at four sites. For both AC and RC traits, immune traits from the T-cell panel were also highlighted, with CD39-positive T-cell subsets being the most frequently observed feature. For MP traits, the most significant association immune trait with BMD was SSC-A on CD14 + monocyte. Sensitivity analyses suggested that the identified immune factors were robust to pleiotropy. Multivariable MR analysis confirmed the independent causal effect of several immune traits on BMD. Mediation analyses showed that CD40 on monocytes could mediate multiple immune traits, especially the suggestive associations of CD27 on several memory B cells with BMD mediated by CD40 on CD14 + CD16 − monocyte. Our study represents the first comprehensive evaluation of the causal effects of immune traits on the risk of osteoporosis. The findings highlighted the complex and important role of immune-derived factors in the pathogenesis of osteoporosis.