The M3 muscarinic receptor Is required for optimal adaptive immunity to Helminth and bacterial infection

Innate immunity is regulated by cholinergic signalling through nicotinic acetylcholine receptors. We show here that signalling through the M3 muscarinic acetylcholine receptor (M3R) plays an important role in adaptive immunity to both Nippostrongylus brasiliensis and Salmonella enterica serovar Typhimurium, as M3R-/- mice were impaired in their ability to resolve infection with either pathogen. CD4 T cell activation and cytokine production were reduced in M3R-/- mice. Immunity to secondary infection with N. brasiliensis was severely impaired, with reduced cytokine responses in M3R-/- mice accompanied by lower numbers of mucus-producing goblet cells and alternatively activated macrophages in the lungs. Ex vivo lymphocyte stimulation of cells from intact BALB/c mice infected with N. brasiliensis and S. typhimurium with muscarinic agonists resulted in enhanced production of IL-13 and IFN-γ respectively, which was blocked by an M3R-selective antagonist. Our data therefore indicate that cholinergic signalling via the M3R is essential for optimal Th1 and Th2 adaptive immunity to infection

Large-scale association analysis identifies new lung cancer susceptibility loci and heterogeneity in genetic susceptibility across histological subtypes.

Although several lung cancer susceptibility loci have been identified, much of the heritability for lung cancer remains unexplained. Here 14,803 cases and 12,262 controls of European descent were genotyped on the OncoArray and combined with existing data for an aggregated genome-wide association study (GWAS) analysis of lung cancer in 29,266 cases and 56,450 controls. We identified 18 susceptibility loci achieving genome-wide significance, including 10 new loci. The new loci highlight the striking heterogeneity in genetic susceptibility across the histological subtypes of lung cancer, with four loci associated with lung cancer overall and six loci associated with lung adenocarcinoma. Gene expression quantitative trait locus (eQTL) analysis in 1,425 normal lung tissue samples highlights RNASET2, SECISBP2L and NRG1 as candidate genes. Other loci include genes such as a cholinergic nicotinic receptor, CHRNA2, and the telomere-related genes OFBC1 and RTEL1. Further exploration of the target genes will continue to provide new insights into the etiology of lung cancer

Building a transdisciplinary expert consensus on the cognitive drivers of performance under pressure: An international multi-panel Delphi study

IntroductionThe ability to perform optimally under pressure is critical across many occupations, including the military, first responders, and competitive sport. Despite recognition that such performance depends on a range of cognitive factors, how common these factors are across performance domains remains unclear. The current study sought to integrate existing knowledge in the performance field in the form of a transdisciplinary expert consensus on the cognitive mechanisms that underlie performance under pressure.MethodsInternational experts were recruited from four performance domains [(i) Defense; (ii) Competitive Sport; (iii) Civilian High-stakes; and (iv) Performance Neuroscience]. Experts rated constructs from the Research Domain Criteria (RDoC) framework (and several expert-suggested constructs) across successive rounds, until all constructs reached consensus for inclusion or were eliminated. Finally, included constructs were ranked for their relative importance.ResultsSixty-eight experts completed the first Delphi round, with 94% of experts retained by the end of the Delphi process. The following 10 constructs reached consensus across all four panels (in order of overall ranking): (1) Attention; (2) Cognitive Control—Performance Monitoring; (3) Arousal and Regulatory Systems—Arousal; (4) Cognitive Control—Goal Selection, Updating, Representation, and Maintenance; (5) Cognitive Control—Response Selection and Inhibition/Suppression; (6) Working memory—Flexible Updating; (7) Working memory—Active Maintenance; (8) Perception and Understanding of Self—Self-knowledge; (9) Working memory—Interference Control, and (10) Expert-suggested—Shifting.DiscussionOur results identify a set of transdisciplinary neuroscience-informed constructs, validated through expert consensus. This expert consensus is critical to standardizing cognitive assessment and informing mechanism-targeted interventions in the broader field of human performance optimization