1,564 research outputs found
Correction: assortative mating in fallow deer reduces the strength of sexual selection.
PMCID: PMC3182158
This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.This article corrects this one:
PLoS One. 2011; 6(4): e18533. doi:10.1371/journal.pone.0018533[This corrects the article on p. e18533 in vol. 6.]
Avalanche amplification of a single exciton in a semiconductor nanowire
Interfacing single photons and electrons is a crucial ingredient for sharing
quantum information between remote solid-state qubits. Semiconductor nanowires
offer the unique possibility to combine optical quantum dots with avalanche
photodiodes, thus enabling the conversion of an incoming single photon into a
macroscopic current for efficient electrical detection. Currently, millions of
excitation events are required to perform electrical read-out of an exciton
qubit state. Here we demonstrate multiplication of carriers from only a single
exciton generated in a quantum dot after tunneling into a nanowire avalanche
photodiode. Due to the large amplification of both electrons and holes (>
10^4), we reduce by four orders of magnitude the number of excitation events
required to electrically detect a single exciton generated in a quantum dot.
This work represents a significant step towards single-shot electrical read-out
and offers a new functionality for on-chip quantum information circuits
DEEP MOVEMENT: Deep learning of movie files for management of endovascular thrombectomy
Objectives: Treatment and outcomes of acute stroke have been revolutionised by mechanical thrombectomy. Deep learning has shown great promise in diagnostics but applications in video and interventional radiology lag behind. We aimed to develop a model that takes as input digital subtraction angiography (DSA) videos and classifies the video according to (1) the presence of large vessel occlusion (LVO), (2) the location of the occlusion, and (3) the efficacy of reperfusion. / Methods: All patients who underwent DSA for anterior circulation acute ischaemic stroke between 2012 and 2019 were included. Consecutive normal studies were included to balance classes. An external validation (EV) dataset was collected from another institution. The trained model was also used on DSA videos post mechanical thrombectomy to assess thrombectomy efficacy. / Results: In total, 1024 videos comprising 287 patients were included (44 for EV). Occlusion identification was achieved with 100% sensitivity and 91.67% specificity (EV 91.30% and 81.82%). Accuracy of location classification was 71% for ICA, 84% for M1, and 78% for M2 occlusions (EV 73, 25, and 50%). For post-thrombectomy DSA (n = 194), the model identified successful reperfusion with 100%, 88%, and 35% for ICA, M1, and M2 occlusion (EV 89, 88, and 60%). The model could also perform classification of post-intervention videos as mTICI < 3 with an AUC of 0.71. / Conclusions: Our model can successfully identify normal DSA studies from those with LVO and classify thrombectomy outcome and solve a clinical radiology problem with two temporal elements (dynamic video and pre and post intervention). / Key Points: • DEEP MOVEMENT represents a novel application of a model applied to acute stroke imaging to handle two types of temporal complexity, dynamic video and pre and post intervention. • The model takes as an input digital subtraction angiograms of the anterior cerebral circulation and classifies according to (1) the presence or absence of large vessel occlusion, (2) the location of the occlusion, and (3) the efficacy of thrombectomy. • Potential clinical utility lies in providing decision support via rapid interpretation (pre thrombectomy) and automated objective gradation of thrombectomy outcomes (post thrombectomy)
Can Antiviral Drugs Contain Pandemic Influenza Transmission?
Antiviral drugs dispensed during the 2009 influenza pandemic generally failed to
contain transmission. This poses the question of whether preparedness for a
future pandemic should include plans to use antiviral drugs to mitigate
transmission
A 'small-world-like' model for comparing interventions aimed at preventing and controlling influenza pandemics
BACKGROUND: With an influenza pandemic seemingly imminent, we constructed a model simulating the spread of influenza within the community, in order to test the impact of various interventions. METHODS: The model includes an individual level, in which the risk of influenza virus infection and the dynamics of viral shedding are simulated according to age, treatment, and vaccination status; and a community level, in which meetings between individuals are simulated on randomly generated graphs. We used data on real pandemics to calibrate some parameters of the model. The reference scenario assumes no vaccination, no use of antiviral drugs, and no preexisting herd immunity. We explored the impact of interventions such as vaccination, treatment/prophylaxis with neuraminidase inhibitors, quarantine, and closure of schools or workplaces. RESULTS: In the reference scenario, 57% of realizations lead to an explosive outbreak, lasting a mean of 82 days (standard deviation (SD) 12 days) and affecting 46.8% of the population on average. Interventions aimed at reducing the number of meetings, combined with measures reducing individual transmissibility, would be partly effective: coverage of 70% of affected households, with treatment of the index patient, prophylaxis of household contacts, and confinement to home of all household members, would reduce the probability of an outbreak by 52%, and the remaining outbreaks would be limited to 17% of the population (range 0.8%–25%). Reactive vaccination of 70% of the susceptible population would significantly reduce the frequency, size, and mean duration of outbreaks, but the benefit would depend markedly on the interval between identification of the first case and the beginning of mass vaccination. The epidemic would affect 4% of the population if vaccination started immediately, 17% if there was a 14-day delay, and 36% if there was a 28-day delay. Closing schools when the number of infections in the community exceeded 50 would be very effective, limiting the size of outbreaks to 10% of the population (range 0.9%–22%). CONCLUSION: This flexible tool can help to determine the interventions most likely to contain an influenza pandemic. These results support the stockpiling of antiviral drugs and accelerated vaccine development
Impact of Emerging Antiviral Drug Resistance on Influenza Containment and Spread: Influence of Subclinical Infection and Strategic Use of a Stockpile Containing One or Two Drugs
BACKGROUND: Wide-scale use of antiviral agents in the event of an influenza pandemic is likely to promote the emergence of drug resistance, with potentially deleterious effects for outbreak control. We explored factors promoting resistance within a dynamic infection model, and considered ways in which one or two drugs might be distributed to delay the spread of resistant strains or mitigate their impact. METHODS AND FINDINGS: We have previously developed a novel deterministic model of influenza transmission that simulates treatment and targeted contact prophylaxis, using a limited stockpile of antiviral agents. This model was extended to incorporate subclinical infections, and the emergence of resistant virus strains under the selective pressure imposed by various uses of one or two antiviral agents. For a fixed clinical attack rate, R(0) rises with the proportion of subclinical infections thus reducing the number of infections amenable to treatment or prophylaxis. In consequence, outbreak control is more difficult, but emergence of drug resistance is relatively uncommon. Where an epidemic may be constrained by use of a single antiviral agent, strategies that combine treatment and prophylaxis are most effective at controlling transmission, at the cost of facilitating the spread of resistant viruses. If two drugs are available, using one drug for treatment and the other for prophylaxis is more effective at preventing propagation of mutant strains than either random allocation or drug cycling strategies. Our model is relatively straightforward, and of necessity makes a number of simplifying assumptions. Our results are, however, consistent with the wider body of work in this area and are able to place related research in context while extending the analysis of resistance emergence and optimal drug use within the constraints of a finite drug stockpile. CONCLUSIONS: Combined treatment and prophylaxis represents optimal use of antiviral agents to control transmission, at the cost of drug resistance. Where two drugs are available, allocating different drugs to cases and contacts is likely to be most effective at constraining resistance emergence in a pandemic scenario
Post-exposure prophylaxis during pandemic outbreaks
<p>Abstract</p> <p>Background</p> <p>With the rise of the second pandemic wave of the novel influenza A (H1N1) virus in the current season in the Northern Hemisphere, pandemic plans are being carefully re-evaluated, particularly for the strategic use of antiviral drugs. The recent emergence of oseltamivir-resistant in treated H1N1 patients has raised concerns about the prudent use of neuraminidase inhibitors for both treatment of ill individuals and post-exposure prophylaxis of close contacts.</p> <p>Methods</p> <p>We extended an established population dynamical model of pandemic influenza with treatment to include post-exposure prophylaxis of close contacts. Using parameter estimates published in the literature, we simulated the model to evaluate the combined effect of treatment and prophylaxis in minimizing morbidity and mortality of pandemic infections in the context of transmissible drug resistance.</p> <p>Results</p> <p>We demonstrated that, when transmissible resistant strains are present, post-exposure prophylaxis can promote the spread of resistance, especially when combined with aggressive treatment. For a given treatment level, there is an optimal coverage of prophylaxis that minimizes the total number of infections (final size) and this coverage decreases as a higher proportion of infected individuals are treated. We found that, when treatment is maintained at intermediate levels, limited post-exposure prophylaxis provides an optimal strategy for reducing the final size of the pandemic while minimizing the total number of deaths. We tested our results by performing a sensitivity analysis over a range of key model parameters and observed that the incidence of infection depends strongly on the transmission fitness of resistant strains.</p> <p>Conclusion</p> <p>Our findings suggest that, in the presence of transmissible drug resistance, strategies that prioritize the treatment of only ill individuals, rather than the prophylaxis of those suspected of being exposed, are most effective in reducing the morbidity and mortality of the pandemic. The impact of post-exposure prophylaxis depends critically on the treatment level and the transmissibility of resistant strains and, therefore, enhanced surveillance and clinical monitoring for resistant mutants constitutes a key component of any comprehensive plan for antiviral drug use during an influenza pandemic.</p
Turnip yellow mosaic virus in Chinese cabbage in Spain: Commercial seed transmission and molecular characterization
[EN] Seed transmission of Turnip yellow mosaic virus (TYMV, genus Tymovirus) was evaluated in the whole seeds and seedlings that emerged from three commercial Chinese cabbage (Brassica pekinensis) seed batches. Seedlings in the cotyledon stage and adult plants were assayed for TYMV by DAS-ELISA and confirmed by RT-PCR. The proportion of whole seeds infected with TYMV was at least 0.15 %. The seeds of the three seed batches were grown in Petri dishes, and surveyed in the cotyledon stage in trays that contained a peat:sand mixture grown in greenhouses or growth chambers, which were analysed in the cotyledon and adult stages. The seed-to-seedling transmission rate ranged from 2.5 % to 2.9 % in two different seed batches (lot-08 and lot-09, respectively). Spanish isolates derived from turnip (Sp-03) and Chinese cabbage (Sp-09 and Sp-13), collected in 2003, 2009 and 2013 in two different Spanish regions, were molecularly characterised by analysing the partial nucleotide sequences of three TYMV genome regions: partial RNA-dependent RNA polymerase (RdRp), methyltransferase (MTR) and coat protein (CP) genes. Phylogenetic analyses showed that the CP gene represented two different groups: TYMV-1 and TYMV-2. The first was subdivided into three subclades: European, Australian and Japanese. Spanish isolate Sp-03 clustered together with European TYMV group, whereas Sp-09 and Sp-13 grouped with the Japanese TYMV group, and all differed from group TYMV-2. The sequences of the three different genomic regions examined clustered into the same groups. The results suggested that Spanish isolates grouped according to the original hosts from which they were isolated. The inoculation of the Spanish TYMV isolates to four crucifer plants species (turnip, broccoli, Brunswick cabbage and radish) revealed that all the isolates infected turnip with typical symptoms, although differences were observed in other hosts.Alfaro Fernández, AO.; Serrano, A.; Tornos, T.; Cebrian Mico, MC.; Córdoba-Sellés, MDC.; Jordá, C.; Font San Ambrosio, MI. (2016). Turnip yellow mosaic virus in Chinese cabbage in Spain: Commercial seed transmission and molecular characterization. EUROPEAN JOURNAL OF PLANT PATHOLOGY. 146(2):433-442. doi:10.1007/s10658-016-0929-3S4334421462Assis Filho, M., & Sherwood, J. L. (2000). Evaluation of seed transmission of Turnip yellow mosaic virus and Tobacco mosaic virus in Arabidopsis thaliana. Phytopathology, 90, 1233–1238.Benetti, M. P., & Kaswalder, F. (1983). Trasmisione per seme del virus del mosaico giallo rapa. Annali dell Istituto Sperimentale per la Patologia Vegetale, 8, 67–70.Blok, J., Mackenzie, A., Guy, P., & Gibbs, A. (1987). Nucleotide sequence comparisons of Turnip yellow mosaic virus isolates from Australia and Europe. Archives of Virology, 97, 283–295.Brunt, A., Crabtree, K., Dallwitz, M., Gibbs, A., Watson, L., & Zurcher, E.J. (1996). Plant Viruses Online: Descriptions and Lists from the VIDE Database. Version: 20th August 1996. URL http://biology.anu.edu.au/Groups/MES/vide/ .Campbell, R. N., Wipf-Scheibel, C., & Lecoq, H. (1996). Vector-assissted seed transmission of melon necrotic spot virus in melon. Phytopathology, 86, 1294–1298.Dreher, T. W., & Bransom, K. L. (1992). Genomic RNA sequence of Turnip yellow mosaic virus isolate TYMC, a cDNA-based clone with verified infectivity. Plant Molecular Biology, 18, 403–406.Fakhro, A., Von Bargen, S., Bandte, M., Büttner, C., Franken, P., & Schwarz, D. (2011). Susceptibility of different plant species and tomato cultivars to two isolates of Pepino mosaic virus. European Journal of Plant Pathology, 129, 579–590.Gibbs, A. J., & Gower, J. C. (1960). The use of a multiple-transfer method in plant virus transmission studies: some statistical points arising in the analysis of results. Annals of Applied Biology, 48, 75–83.Hayden, C. M., Mackenzie, A. M., & Gibbs, A. J. (1998a). Virion protein sequence variation among Australian isolates of turnip yellow mosaic tymovirus. Archives of Virology, 143, 191–201.Hayden, C. M., Mackenzie, A. M., Skotnicki, M. L., & Gibbs, A. (1998b). Turnip yellow mosaic virus isolates with experimentally produced recombinant virion proteins. Journal of General Virology, 79, 395–403.Hein, A. (1984). Transmission of Turnip yellow mosaic virus through seed of Camelina sativa gold of pleasure. Journal of Plant Diseases and Protection, 91, 549–551.Herrera-Vásquez, J. A., Córdoba-Sellés, M. C., Cebrián, M. C., Alfaro-Fernández, A., & Jordá, C. (2009). Seed transmission of Melon necrotic spot virus and efficacy of seed-disinfection treatments. Plant Pathology, 58, 436–452.Hull, R. (2002). Matthews’ plant virology (4a ed.1001 pp). San Diego: Academic Press.Johansen, E., Edwards, M. C., & Hampton, R. O. (1994). Seed transmission of viruses: current perspectives. Annual Review of Phytopathology, 32, 363–386.Kirino, N., Inoue, K., Tanina, K., Yamazaki, Y., & Ohki, S. T. (2008). Turnip yellow mosaic virus isolated from Chinese cabbage in Japan. Journal of General Plant Pathology, 74, 331–334.Markham, R., & Smith, K. S. (1949). Studies on the virus of turnip yellow mosaic. Parasitology, 39, 330–342.Mathews, R. E. F. (1980). Turnip yellow mosaic virus, CMI/AAB Descriptions of plant virus No. 230 (No. 2 revised). Kew: Commonwealth Mycology Institute/Association of Applied Biologists.Mitchell, E. J., & Bond, J. M. (2005). Variation in the coat protein sequence of British isolates of Turnip yellow mosaic virus and comparison with previously published isolates. Archives of Virology, 150, 2347–2355.Pagán, I., Fraile, A., Fernández-Fueyo, E., Montes, N., Alonso-Blanco, C., & García-Arenal, F. (2010). Arabidopsis thaliana as a model for the study of plant-virus co-evolution. Philosophical Transations of the Royal Society Biological Sciences, 365, 1983–1995.Paul, H. L., Gibbs, A., & Wittman-Liebold, B. (1980). The relationships of certain Tymoviruses assessed from the amino acid composition of their coat proteins. Intervirology, 13, 99–109.Pelikanova, J. (1990). Garlic mustard a spontaneous host of TYMV. Ochrana Rostlin, 26, 17–22.Procházková, Z. (1980). Host range and symptom differences between isolates of Turnip mosaic virus obtained from Sisymbrium loeselii. Biologia Plantarum, 22, 341–347.Rimmer, S. R., Shtattuck, V. I., & Buchwaldt, L. (2007). Compendium of brassica diseases (1ª Edición ed.p. 117). USA: APS press.Rot, M. E., & Jelkman, W. (2001). Characterization and detection of several filamentous viruses of cherry: Adaptation of an alternative cloning method (DOP-PCR), and modification of an RNA extraction protocol. European Journal of Plant Pathology, 107, 411–420.Sabanadzovic, S., Abou-Ghanem, N., Castellano, M. A., Digiaero, M., & Martelli, G. P. (2000). Grapevine fleck virus-like in Vitis. Archives of Virology, 145, 553–565.Špack, J., & Kubelková, D. (2000). Serological variability among European isolates of Radish mosaic virus. Plant Pathology, 49, 295–301.Špack, J., Kubelková, D., & Hnilicka, E. (1993). Seed transmission of Turnip yellow mosaic virus in winter turnip and winter oilseed rapes. Annals of Applied Biology, 123, 33–35.Stobbs, L. W., Cerkauskas, R. F., Lowery, T., & VanDriel, L. (1998). Occurrence of Turnip yellow mosaic virus on oriental cruciferours vegetables in Southern Ontario, Canada. Plant Disease, 82, 351.Tamura, 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, 2731–2739
Building for the future: essential infrastructure for rodent ageing studies
When planning ageing research using rodent models, the logistics of supply, long term housing and infrastructure provision are important factors to take into consideration. These issues need to be prioritised to ensure they meet the requirements of experiments which potentially will not be completed for several years. Although these issues are not unique to this discipline, the longevity of experiments and indeed the animals, requires a high level of consistency and sustainability to be maintained throughout lengthy periods of time. Moreover, the need to access aged stock or material for more immediate experiments poses many issues for the completion of pilot studies and/or short term intervention studies on older models. In this article, we highlight the increasing demand for ageing research, the resources and infrastructure involved, and the need for large-scale collaborative programmes to advance studies in both a timely and a cost-effective way
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