Coupling of transient near infrared photonic with magnetic nanoparticle for potential dissipation-free biomedical application in brain

Combined treatment strategies based on magnetic nanoparticles (MNPs) with near infrared ray (NIR) biophotonic possess tremendous potential for non-invasive therapeutic approach. Nonetheless, investigations in this direction have been limited to peripheral body region and little is known about the potential biomedical application of this approach for brain. Here we report that transient NIR exposure is dissipation-free and has no adverse effect on the viability and plasticity of major brain cells in the presence or absence superparamagnetic nanoparticles. The 808?nm NIR laser module with thermocouple was employed for functional studies upon NIR exposure to brain cells. Magnetic nanoparticles were characterized using transmission electron microscopy (TEM), X-ray diffraction (XRD), dynamic laser scattering (DLS), and vibrating sample magnetometer (VSM). Brain cells viability and plasticity were analyzed using electric cell-substrate impedance sensing system, cytotoxicity evaluation, and confocal microscopy. When efficacious non-invasive photobiomodulation and neuro-therapeutical targeting and monitoring to brain remain a formidable task, the discovery of this dissipation-free, transient NIR photonic approach for brain cells possesses remarkable potential to add new dimension

Wide Dynamic Range Neutron Flux Monitor Having Fast Time Response for the Large Helical Device

A fast time response, wide dynamic range neutron flux monitor has been developed toward the LHD deuterium operation by using leading-edge signal processing technologies providing maxi- mum counting rate up to ?5 × 109 counts/s. Because a maximum total neutron emission rate over 1 × 1016 n/s is predicted in neutral beam-heated LHD plasmas, fast response and wide dy- namic range capabilities of the system are essential. Preliminary tests have demonstrated success- ful performance as a wide dynamic range monitor along the design

Phylogeography and Molecular Evolution of Potato virus Y

Potato virus Y (PVY) is an important plant pathogen, whose host range includes economically important crops such as potato, tobacco, tomato, and pepper. PVY presents three main strains (PVYO, PVYN and PVYC) and several recombinant forms. PVY has a worldwide distribution, yet the mechanisms that promote and maintain its population structure and genetic diversity are still unclear. In this study, we used a pool of 77 complete PVY genomes from isolates collected worldwide. After removing the effect of recombination in our data set, we used Bayesian techniques to study the influence of geography and host species in both PVY population structure and dynamics. We have also performed selection and covariation analyses to identify evolutionarily relevant amino acid residues. Our results show that both geographic and host-driven adaptations explain PVY diversification. Furthermore, purifying selection is the main force driving PVY evolution, although some indications of positive selection accounted for the diversification of the different strains. Interestingly, the analysis of P3N-PIPO, a recently described gene in potyviruses, seems to show a variable length among the isolates analyzed, and this variability is explained, in part, by host-driven adaptation

NMDA Receptor Hypofunction Leads to Generalized and Persistent Aberrant γ Oscillations Independent of Hyperlocomotion and the State of Consciousness

International audienceNMDAr antagonists acutely produces, in the rodent CNS, generalized aberrant gamma oscillations, which are not dependent on hyperlocomotion-related brain state or conscious sensorimotor processing. These findings suggest that NMDAr hypofunction-related generalized gamma hypersynchronies represent an aberrant diffuse network noise, a potential electrophysiological correlate of a psychotic-like state. Such generalized noise might cause dysfunction of brain operations, including the impairments in cognition and sensorimotor integration seen in schizophrenia

Alexithymia may explain the relationship between autistic traits and eating disorder psychopathology

Background: Autistic people are disproportionately vulnerable to anorexia nervosa and other eating disorders (ED), and within the general population, autistic traits correlate with ED psychopathology. A putative mechanism which may underpin this heightened risk is alexithymia, a difficulty identifying and describing emotional states which is observed in both autism and ED. In two experiments with independent non-clinical samples, we explored whether alexithymia might mediate the heightened risk of eating psychopathology in individuals high in autistic traits. Methods: Our first experiment used the PROCESS macro for SPSS to examine relationships between alexithymia (measured by the Toronto Alexithymia Scale (TAS-20)), autistic traits (autism quotient (AQ)), and eating psychopathology (Eating Attitudes Test (EAT-26)) in 121 participants. Our second experiment (n = 300) replicated and furthered this analysis by examining moderating effects of sex and controlling for anxiety and depression as covariates. We also included an additional performance-based measure of alexithymia, the Levels of Emotional Awareness Scale (LEAS). Results: Study 1 suggested that TAS-20 scores mediated the relationship between heightened autistic traits and eating psychopathology. Replication and further scrutiny of this finding, in study 2, revealed that this mediation effect was partial and specific to the female participants in this sample. The mediation effect appeared to be carried by the difficulty identifying feelings subscale of the TAS-20, even when depression and anxiety were controlled for. LEAS scores, however, were not significantly related to autistic traits or eating psychopathology. Limitations: Cross-sectional data prevents any conclusions around the direction and causality of relationships between alexithymia, autistic traits, and eating psychopathology (alongside depression and anxiety), necessitating longitudinal research. Our non-clinical sample was predominantly Caucasian undergraduate students, so it remains to be seen if these results would extrapolate to clinical and/or autistic samples. Divergence between the TAS-20 and LEAS raises crucial questions regarding the construct validity of these measures. Conclusions: Our findings with respect to autistic traits suggest that alexithymia could partially explain the prevalence of ED in autistic people and may as such be an important consideration in the pathogenesis and treatment of ED in autistic and non-autistic people alike. Further research with clinical samples is critical to explore these ideas. Differences between men and women, furthermore, emphasize the importance of looking for sexspecific as well as generic risk factors in autistic and non-autistic men and women

2021 Taxonomic update of phylum Negarnaviricota (Riboviria: Orthornavirae), including the large orders Bunyavirales and Mononegavirales.

Correction to: 2021 Taxonomic update of phylum Negarnaviricota (Riboviria: Orthornavirae), including the large orders Bunyavirales and Mononegavirales. Archives of Virology (2021) 166:3567–3579. https://doi.org/10.1007/s00705-021-05266-wIn March 2021, following the annual International Committee on Taxonomy of Viruses (ICTV) ratification vote on newly proposed taxa, the phylum Negarnaviricota was amended and emended. The phylum was expanded by four families (Aliusviridae, Crepuscuviridae, Myriaviridae, and Natareviridae), three subfamilies (Alpharhabdovirinae, Betarhabdovirinae, and Gammarhabdovirinae), 42 genera, and 200 species. Thirty-nine species were renamed and/or moved and seven species were abolished. This article presents the updated taxonomy of Negarnaviricota as now accepted by the ICTV.This work was supported in part through Laulima Government Solutions, LLC prime contract with the US National Institute of Allergy and Infectious Diseases (NIAID) under Contract No. HHSN272201800013C. J.H.K. performed this work as an employee of Tunnell Government Services (TGS), a subcontractor of Laulima Government Solutions, LLC under Contract No. HHSN272201800013C. This work was also supported in part with federal funds from the National Cancer Institute (NCI), National Institutes of Health (NIH), under Contract No. 75N91019D00024, Task Order No. 75N91019F00130 to I.C., who was supported by the Clinical Monitoring Research Program Directorate, Frederick National Lab for Cancer Research. This work was also funded in part by Contract No. HSHQDC-15-C-00064 awarded by DHS S&T for the management and operation of The National Biodefense Analysis and Countermeasures Center, a federally funded research and development center operated by the Battelle National Biodefense Institute (V.W.); and NIH contract HHSN272201000040I/HHSN27200004/D04 and grant R24AI120942 (N.V., R.B.T.). S.S. acknowledges partial support from the Special Research Initiative of Mississippi Agricultural and Forestry Experiment Station (MAFES), Mississippi State University, and the National Institute of Food and Agriculture, US Department of Agriculture, Hatch Project 1021494. Part of this work was supported by the Francis Crick Institute which receives its core funding from Cancer Research UK (FC001030), the UK Medical Research Council (FC001030), and the Wellcome Trust (FC001030).S

Emergence and phylodynamics of Citrus tristeza virus in Sicily, Italy

[EN] Citrus tristeza virus (CTV) outbreaks were detected in Sicily island, Italy for the first time in 2002. To gain insight into the evolutionary forces driving the emergence and phylogeography of these CTV populations, we determined and analyzed the nucleotide sequences of the p20 gene from 108 CTV isolates collected from 2002 to 2009. Bayesian phylogenetic analysis revealed that mild and severe CTV isolates belonging to five different clades (lineages) were introduced in Sicily in 2002. Phylogeographic analysis showed that four lineages co-circulated in the main citrus growing area located in Eastern Sicily. However, only one lineage (composed of mild isolates) spread to distant areas of Sicily and was detected after 2007. No correlation was found between genetic variation and citrus host, indicating that citrus cultivars did not exert differential selective pressures on the virus. The genetic variation of CTV was not structured according to geographical location or sampling time, likely due to the multiple introduction events and a complex migration pattern with intense co- and recirculation of different lineages in the same area. The phylogenetic structure, statistical tests of neutrality and comparison of synonymous and nonsynonymous substitution rates suggest that weak negative selection and genetic drift following a rapid expansion may be the main causes of the CTV variability observed today in Sicily. Nonetheless, three adjacent amino acids at the p20 N-terminal region were found to be under positive selection, likely resulting from adaptation events.A.W. and S.F.E. were supported by grant BFU2012-30805 from the Spanish Secretaria de Estado de Investigacion, Desarrollo e Innovacion and by a grant 22371 from the John Templeton Foundation. The opinions expressed in this publication are those of the authors and do not necessarily reflect the views of the John Templeton Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Davino, S.; Willemsen, A.; Panno. Stefano; Davino, M.; Catara, A.; Elena Fito, SF.; Rubio, L. (2013). Emergence and phylodynamics of Citrus tristeza virus in Sicily, Italy. PLoS ONE. 8:66700-66700. doi:10.1371/journal.pone.0066700S66700667008Domingo, E., & Holland, J. J. (1997). RNA VIRUS MUTATIONS AND FITNESS FOR SURVIVAL. Annual Review of Microbiology, 51(1), 151-178. doi:10.1146/annurev.micro.51.1.151Grenfell, B. T. (2004). Unifying the Epidemiological and Evolutionary Dynamics of Pathogens. Science, 303(5656), 327-332. doi:10.1126/science.1090727Moya, A., Holmes, E. C., & González-Candelas, F. (2004). The population genetics and evolutionary epidemiology of RNA viruses. Nature Reviews Microbiology, 2(4), 279-288. doi:10.1038/nrmicro863Gray, R. R., Tatem, A. J., Lamers, S., Hou, W., Laeyendecker, O., Serwadda, D., … Salemi, M. (2009). Spatial phylodynamics of HIV-1 epidemic emergence in east Africa. AIDS, 23(14), F9-F17. doi:10.1097/qad.0b013e32832faf61Holmes, E. C. (2008). Evolutionary History and Phylogeography of Human Viruses. Annual Review of Microbiology, 62(1), 307-328. doi:10.1146/annurev.micro.62.081307.162912Pybus, O. G., Suchard, M. A., Lemey, P., Bernardin, F. J., Rambaut, A., Crawford, F. W., … Delwart, E. L. (2012). Unifying the spatial epidemiology and molecular evolution of emerging epidemics. Proceedings of the National Academy of Sciences, 109(37), 15066-15071. doi:10.1073/pnas.1206598109Talbi, C., Lemey, P., Suchard, M. A., Abdelatif, E., Elharrak, M., Jalal, N., … Bourhy, H. (2010). Phylodynamics and Human-Mediated Dispersal of a Zoonotic Virus. PLoS Pathogens, 6(10), e1001166. doi:10.1371/journal.ppat.1001166Vijaykrishna, D., Bahl, J., Riley, S., Duan, L., Zhang, J. X., Chen, H., … Guan, Y. (2008). Evolutionary Dynamics and Emergence of Panzootic H5N1 Influenza Viruses. PLoS Pathogens, 4(9), e1000161. doi:10.1371/journal.ppat.1000161Gómez, P., Sempere, R. N., Aranda, M. A., & Elena, S. F. (2012). Phylodynamics of Pepino mosaic virus in Spain. European Journal of Plant Pathology, 134(3), 445-449. doi:10.1007/s10658-012-0019-0Lefeuvre, P., Martin, D. P., Harkins, G., Lemey, P., Gray, A. J. A., Meredith, S., … Heydarnejad, J. (2010). The Spread of Tomato Yellow Leaf Curl Virus from the Middle East to the World. PLoS Pathogens, 6(10), e1001164. doi:10.1371/journal.ppat.1001164TOMITAKA, Y., & OHSHIMA, K. (2006). A phylogeographical study of the Turnip mosaic virus population in East Asia reveals an ‘emergent’ lineage in Japan. Molecular Ecology, 15(14), 4437-4457. doi:10.1111/j.1365-294x.2006.03094.xWu, B., Blanchard-Letort, A., Liu, Y., Zhou, G., Wang, X., & Elena, S. F. (2011). Dynamics of Molecular Evolution and Phylogeography of Barley yellow dwarf virus-PAV. PLoS ONE, 6(2), e16896. doi:10.1371/journal.pone.0016896MORENO, P., AMBRÓS, S., ALBIACH-MARTÍ, M. R., GUERRI, J., & PEÑA, L. (2008). Citrus tristeza virus: a pathogen that changed the course of the citrus industry. Molecular Plant Pathology, 9(2), 251-268. doi:10.1111/j.1364-3703.2007.00455.xTatineni, S., Robertson, C. J., Garnsey, S. M., & Dawson, W. O. (2011). A plant virus evolved by acquiring multiple nonconserved genes to extend its host range. Proceedings of the National Academy of Sciences, 108(42), 17366-17371. doi:10.1073/pnas.1113227108Folimonova, S. Y. (2012). Superinfection Exclusion Is an Active Virus-Controlled Function That Requires a Specific Viral Protein. Journal of Virology, 86(10), 5554-5561. doi:10.1128/jvi.00310-12Bar-Joseph, M., Marcus, R., & Lee, R. F. (1989). The Continuous Challenge of Citrus Tristeza Virus Control. Annual Review of Phytopathology, 27(1), 291-316. doi:10.1146/annurev.py.27.090189.001451Davino, S., Rubio, L., & Davino, M. (2005). Molecular analysis suggests that recent Citrus tristeza virus outbreaks in Italy were originated by at least two independent introductions. European Journal of Plant Pathology, 111(3), 289-293. doi:10.1007/s10658-003-2815-zAlbiach-Marti, M. R., Mawassi, M., Gowda, S., Satyanarayana, T., Hilf, M. E., Shanker, S., … Dawson, W. O. (2000). Sequences of Citrus Tristeza Virus Separated in Time and Space Are Essentially Identical. Journal of Virology, 74(15), 6856-6865. doi:10.1128/jvi.74.15.6856-6865.2000Rubio, L., Ayllon, M. A., Kong, P., Fernandez, A., Polek, M., Guerri, J., … Falk, B. W. (2001). Genetic Variation of Citrus Tristeza Virus Isolates from California and Spain: Evidence for Mixed Infections and Recombination. Journal of Virology, 75(17), 8054-8062. doi:10.1128/jvi.75.17.8054-8062.2001Silva, G., Marques, N., & Nolasco, G. (2011). The evolutionary rate of citrus tristeza virus ranks among the rates of the slowest RNA viruses. Journal of General Virology, 93(2), 419-429. doi:10.1099/vir.0.036574-0Mawassi, M., Mietkiewska, E., Gofman, R., Yang, G., & Bar-Joseph, M. (1996). Unusual Sequence Relationships Between Two Isolates of Citrus Tristeza Virus. Journal of General Virology, 77(9), 2359-2364. doi:10.1099/0022-1317-77-9-2359Vives, M. C., Dawson, W. O., Flores, R., L√≥pez, C., Albiach-Mart√≠, M. R., Rubio, L., … Moreno, P. (1999). The complete genome sequence of the major component of a mild citrus tristeza virus isolate. Journal of General Virology, 80(3), 811-816. doi:10.1099/0022-1317-80-3-811Martín, S., Elena, S. F., Guerri, J., Moreno, P., Sambade, A., Rubio, L., … Vives, M. C. (2009). Contribution of recombination and selection to molecular evolution of Citrus tristeza virus. Journal of General Virology, 90(6), 1527-1538. doi:10.1099/vir.0.008193-0Vives, M. C., Rubio, L., Sambade, A., Mirkov, T. E., Moreno, P., & Guerri, J. (2005). Evidence of multiple recombination events between two RNA sequence variants within a Citrus tristeza virus isolate. Virology, 331(2), 232-237. doi:10.1016/j.virol.2004.10.037D’Urso, F., Sambade, A., Moya, A., Guerri, J., & Moreno, P. (2003). Variation of haplotype distributions of two genomic regions of Citrus tristeza virus populations from eastern Spain. Molecular Ecology, 12(2), 517-526. doi:10.1046/j.1365-294x.2000.01747.xSambade, A., Rubio, L., Garnsey, S. M., Costa, N., Muller, G. W., Peyrou, M., … Moreno, P. (2002). Comparison of viral RNA populations of pathogenically distinct isolates of Citrus tristeza virus : application to monitoring cross-protection. Plant Pathology, 51(3), 257-265. doi:10.1046/j.1365-3059.2002.00720.xReed, J. C., Kasschau, K. D., Prokhnevsky, A. I., Gopinath, K., Pogue, G. P., Carrington, J. C., & Dolja, V. V. (2003). Suppressor of RNA silencing encoded by Beet yellows virus. Virology, 306(2), 203-209. doi:10.1016/s0042-6822(02)00051-xFolimonova, S. Y., Robertson, C. J., Shilts, T., Folimonov, A. S., Hilf, M. E., Garnsey, S. M., & Dawson, W. O. (2009). Infection with Strains of Citrus Tristeza Virus Does Not Exclude Superinfection by Other Strains of the Virus. Journal of Virology, 84(3), 1314-1325. doi:10.1128/jvi.02075-09Kong, P., Rubio, L., Polek, M., & Falk, B. W. (2000). Virus Genes, 21(3), 139-145. doi:10.1023/a:1008198311398Powell, C. A., Pelosi, R. R., Rundell, P. A., & Cohen, M. (2003). Breakdown of Cross-Protection of Grapefruit from Decline-Inducing Isolates of Citrus tristeza virus Following Introduction of the Brown Citrus Aphid. Plant Disease, 87(9), 1116-1118. doi:10.1094/pdis.2003.87.9.1116Roistacher C, Dodds J. (1993) Failure of 100 mild Citrus tristeza virus isolates from california to cross protect against a challenge by severe sweet orange stem pitting isolates. Proc 12th Conf IOCV: 100–107.Ayllón, M. A., Rubio, L., Sentandreu, V., Moya, A., Guerri, J., & Moreno, P. (2006). Variations in Two Gene Sequences of Citrus Tristeza Virus after Host Passage. Virus Genes, 32(2), 119-128. doi:10.1007/s11262-005-6866-4Ayllón, M. A., Rubio, L., Moya, A., Guerri, J., & Moreno, P. (1999). The Haplotype Distribution of Two Genes of Citrus Tristeza Virus Is Altered after Host Change or Aphid Transmission. Virology, 255(1), 32-39. doi:10.1006/viro.1998.9566Sentandreu, V., Castro, J. A., Ayllón, M. A., Rubio, L., Guerri, J., González-Candelas, F., … Moya, A. (2005). Evolutionary analysis of genetic variation observed in citrus tristeza virus (CTV) after host passage. Archives of Virology, 151(5), 875-894. doi:10.1007/s00705-005-0683-xMatos, L. A., Hilf, M. E., Cayetano, X. A., Feliz, A. O., Harper, S. J., & Folimonova, S. Y. (2013). Dramatic Change in Citrus tristeza virus Populations in the Dominican Republic. Plant Disease, 97(3), 339-345. doi:10.1094/pdis-05-12-0421-reDavino, S., Davino, M., Sambade, A., Guardo, M., & Caruso, A. (2003). The First Citrus tristeza virus Outbreak Found in a Relevant Citrus Producing Area of Sicily, Italy. Plant Disease, 87(3), 314-314. doi:10.1094/pdis.2003.87.3.314aRUBIO, L., AYLLONl, M. A., GUERRI, J., PAPPU, H., NIBLETT, C., & MORENO, P. (1996). Differentiation of citrus tristeza closterovirus (CTV) isolates by single-strand conformation polymorphism analysis of the coat protein gene. Annals of Applied Biology, 129(3), 479-489. doi:10.1111/j.1744-7348.1996.tb05770.xLarkin, M. A., Blackshields, G., Brown, N. P., Chenna, R., McGettigan, P. A., McWilliam, H., … Higgins, D. G. (2007). Clustal W and Clustal X version 2.0. Bioinformatics, 23(21), 2947-2948. doi:10.1093/bioinformatics/btm404Tamura, K., Peterson, D., Peterson, N., Stecher, G., Nei, M., & Kumar, S. (2011). MEGA5: Molecular Evolutionary Genetics Analysis Using Maximum Likelihood, Evolutionary Distance, and Maximum Parsimony Methods. Molecular Biology and Evolution, 28(10), 2731-2739. doi:10.1093/molbev/msr121Kosakovsky Pond, S. L., Posada, D., Gravenor, M. B., Woelk, C. H., & Frost, S. D. W. (2006). GARD: a genetic algorithm for recombination detection. Bioinformatics, 22(24), 3096-3098. doi:10.1093/bioinformatics/btl474Martin, D. P., Lemey, P., Lott, M., Moulton, V., Posada, D., & Lefeuvre, P. (2010). RDP3: a flexible and fast computer program for analyzing recombination. Bioinformatics, 26(19), 2462-2463. doi:10.1093/bioinformatics/btq467Librado, P., & Rozas, J. (2009). DnaSP v5: a software for comprehensive analysis of DNA polymorphism data. Bioinformatics, 25(11), 1451-1452. doi:10.1093/bioinformatics/btp187Kimura M. (1985) The neutral theory of molecular evolution. Cambridge Univ Pr.Weir, B. S., & Cockerham, C. C. (1984). Estimating F-Statistics for the Analysis of Population Structure. Evolution, 38(6), 1358. doi:10.2307/2408641Pond, S. L. K., & Frost, S. D. W. (2005). Datamonkey: rapid detection of selective pressure on individual sites of codon alignments. Bioinformatics, 21(10), 2531-2533. doi:10.1093/bioinformatics/bti320Drummond, A. J., & Rambaut, A. (2007). BEAST: Bayesian evolutionary analysis by sampling trees. BMC Evolutionary Biology, 7(1), 214. doi:10.1186/1471-2148-7-214Bielejec, F., Rambaut, A., Suchard, M. A., & Lemey, P. (2011). SPREAD: spatial phylogenetic reconstruction of evolutionary dynamics. Bioinformatics, 27(20), 2910-2912. doi:10.1093/bioinformatics/btr481Stamatakis, A. (2006). RAxML-VI-HPC: maximum likelihood-based phylogenetic analyses with thousands of taxa and mixed models. Bioinformatics, 22(21), 2688-2690. doi:10.1093/bioinformatics/btl446Ott M, Zola J, Stamatakis A, Aluru S. (2007) Large-scale maximum likelihood-based phylogenetic analysis on the IBM BlueGene/L. Proceedings of the 19th ACM/IEEE conference on Supercomputing. Article No. 4.Shimodaira, H., & Hasegawa, M. (1999). Multiple Comparisons of Log-Likelihoods with Applications to Phylogenetic Inference. Molecular Biology and Evolution, 16(8), 1114-1116. doi:10.1093/oxfordjournals.molbev.a026201Soria-Carrasco, V., Talavera, G., Igea, J., & Castresana, J. (2007). The K tree score: quantification of differences in the relative branch length and topology of phylogenetic trees. Bioinformatics, 23(21), 2954-2956. doi:10.1093/bioinformatics/btm466Puigbo, P., Garcia-Vallve, S., & McInerney, J. O. (2007). TOPD/FMTS: a new software to compare phylogenetic trees. Bioinformatics, 23(12), 1556-1558. doi:10.1093/bioinformatics/btm13