Host- and Helminth-Derived Endocannabinoids That Have Effects on Host Immunity Are Generated during Infection.

Helminths have coevolved with their hosts, resulting in the development of specialized host immune mechanisms and parasite-specific regulatory products. Identification of new pathways that regulate helminth infection could provide a better understanding of host-helminth interaction and may identify new therapeutic targets for helminth infection. Here we identify the endocannabinoid system as a new mechanism that influences host immunity to helminths. Endocannabinoids are lipid-derived signaling molecules that control important physiologic processes, such as feeding behavior and metabolism. Following murine infection with Nippostrongylus brasiliensis, an intestinal nematode with a life cycle similar to that of hookworms, we observed increased levels of endocannabinoids (2-arachidonoylglycerol [2-AG] or anandamide [AEA]) and the endocannabinoid-like molecule oleoylethanolamine (OEA) in infected lung and intestine. To investigate endocannabinoid function in helminth infection, we employed pharmacological inhibitors of cannabinoid subtype receptors 1 and 2 (CB1R and CB2R). Compared to findings for vehicle-treated mice, inhibition of CB1R but not CB2R resulted in increased N. brasiliensis worm burden and egg output, associated with significantly decreased expression of the T helper type 2 cytokine interleukin 5 (IL-5) in intestinal tissue and splenocyte cultures. Strikingly, bioinformatic analysis of genomic and transcriptome sequencing (RNA-seq) data sets identified putative genes encoding endocannabinoid biosynthetic and degradative enzymes in many parasitic nematodes. To test the novel hypothesis that helminth parasites produce their own endocannabinoids, we measured endocannabinoid levels in N. brasiliensis by mass spectrometry and quantitative PCR and found that N. brasiliensis parasites produced endocannabinoids, especially at the infectious larval stage. To our knowledge, this is the first report of helminth- and host-derived endocannabinoids that promote host immune responses and reduce parasite burden

Intelligent evacuation management systems: A review

Crowd and evacuation management have been active areas of research and study in the recent past. Various developments continue to take place in the process of efficient evacuation of crowds in mass gatherings. This article is intended to provide a review of intelligent evacuation management systems covering the aspects of crowd monitoring, crowd disaster prediction, evacuation modelling, and evacuation path guidelines. Soft computing approaches play a vital role in the design and deployment of intelligent evacuation applications pertaining to crowd control management. While the review deals with video and nonvideo based aspects of crowd monitoring and crowd disaster prediction, evacuation techniques are reviewed via the theme of soft computing, along with a brief review on the evacuation navigation path. We believe that this review will assist researchers in developing reliable automated evacuation systems that will help in ensuring the safety of the evacuees especially during emergency evacuation scenarios

A genome-scale integrated approach aids in genetic dissection of complex flowering time trait in chickpea

A combinatorial approach of candidate gene-based association analysis and genome-wide association study (GWAS) integrated with QTL mapping, differential gene expression profiling and molecular haplotyping was deployed in the present study for quantitative dissection of complex flowering time trait in chickpea. Candidate gene-based association mapping in a flowering time association panel (92 diverse desi and kabuli accessions) was performed by employing the genotyping information of 5724 SNPs discovered from 82 known flowering chickpea gene orthologs of Arabidopsis and legumes as well as 832 gene-encoding transcripts that are differentially expressed during flower development in chickpea. GWAS using both genome-wide GBS- and candidate gene-based genotyping data of 30,129 SNPs in a structured population of 92 sequenced accessions (with 200–250 kb LD decay) detected eight maximum effect genomic SNP loci (genes) associated (34 % combined PVE) with flowering time. Six flowering time-associated major genomic loci harbouring five robust QTLs mapped on a high-resolution intra-specific genetic linkage map were validated (11.6–27.3 % PVE at 5.4–11.7 LOD) further by traditional QTL mapping. The flower-specific expression, including differential up- and down-regulation (>three folds) of eight flowering time-associated genes (including six genes validated by QTL mapping) especially in early flowering than late flowering contrasting chickpea accessions/mapping individuals during flower development was evident. The gene haplotype-based LD mapping discovered diverse novel natural allelic variants and haplotypes in eight genes with high trait association potential (41 % combined PVE) for flowering time differentiation in cultivated and wild chickpea. Taken together, eight potential known/candidate flowering time-regulating genes [efl1 (early flowering 1), FLD (Flowering locus D), GI (GIGANTEA), Myb (Myeloblastosis), SFH3 (SEC14-like 3), bZIP (basic-leucine zipper), bHLH (basic helix-loop-helix) and SBP (SQUAMOSA promoter binding protein)], including novel markers, QTLs, alleles and haplotypes delineated by aforesaid genome-wide integrated approach have potential for marker-assisted genetic improvement and unravelling the domestication pattern of flowering time in chickpea