Browsing by Author "Zhang, Qian"
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- Accuracy of epidemiological inferences based on publicly available information: retrospective comparative analysis of line lists of human cases infected with influenza A(H7N9) in ChinaLau, Eric H. Y.; Zheng, Jiandong; Tsang, Tim K.; Liao, Qiaohong; Lewis, Bryan L.; Brownstein, John S.; Sanders, Sharon; Wong, Jessica Y.; Mekaru, Sumiko R.; Rivers, Caitlin; Wu, Peng; Jiang, Hui; Li, Yu; Yu, Jianxing; Zhang, Qian; Chang, Zhaorui; Liu, Fengfeng; Peng, Zhibin; Leung, Gabriel M.; Feng, Luzhao; Cowling, Benjamin J.; Yu, Hongjie (2014-05-28)Background Appropriate public health responses to infectious disease threats should be based on best-available evidence, which requires timely reliable data for appropriate analysis. During the early stages of epidemics, analysis of ‘line lists’ with detailed information on laboratory-confirmed cases can provide important insights into the epidemiology of a specific disease. The objective of the present study was to investigate the extent to which reliable epidemiologic inferences could be made from publicly-available epidemiologic data of human infection with influenza A(H7N9) virus. Methods We collated and compared six different line lists of laboratory-confirmed human cases of influenza A(H7N9) virus infection in the 2013 outbreak in China, including the official line list constructed by the Chinese Center for Disease Control and Prevention plus five other line lists by HealthMap, Virginia Tech, Bloomberg News, the University of Hong Kong and FluTrackers, based on publicly-available information. We characterized clinical severity and transmissibility of the outbreak, using line lists available at specific dates to estimate epidemiologic parameters, to replicate real-time inferences on the hospitalization fatality risk, and the impact of live poultry market closure. Results Demographic information was mostly complete (less than 10% missing for all variables) in different line lists, but there were more missing data on dates of hospitalization, discharge and health status (more than 10% missing for each variable). The estimated onset to hospitalization distributions were similar (median ranged from 4.6 to 5.6 days) for all line lists. Hospital fatality risk was consistently around 20% in the early phase of the epidemic for all line lists and approached the final estimate of 35% afterwards for the official line list only. Most of the line lists estimated >90% reduction in incidence rates after live poultry market closures in Shanghai, Nanjing and Hangzhou. Conclusions We demonstrated that analysis of publicly-available data on H7N9 permitted reliable assessment of transmissibility and geographical dispersion, while assessment of clinical severity was less straightforward. Our results highlight the potential value in constructing a minimum dataset with standardized format and definition, and regular updates of patient status. Such an approach could be particularly useful for diseases that spread across multiple countries.
- Collaborative efforts to forecast seasonal influenza in the United States, 2015–2016McGowan, Craig J.; Biggerstaff, Matthew; Johansson, Michael; Apfeldorf, Karyn M.; Ben-Nun, Michal; Brooks, Logan; Convertino, Matteo; Erraguntla, Madhav; Farrow, David C.; Freeze, John; Ghosh, Saurav; Hyun, Sangwon; Kandula, Sasikiran; Lega, Joceline; Liu, Yang; Michaud, Nicholas; Morita, Haruka; Niemi, Jarad; Ramakrishnan, Naren; Ray, Evan L.; Reich, Nicholas G.; Riley, Pete; Shaman, Jeffrey; Tibshirani, Ryan; Vespignani, Alessandro; Zhang, Qian; Reed, Carrie; Rosenfeld, Roni; Ulloa, Nehemias; Will, Katie; Turtle, James; Bacon, David; Riley, Steven; Yang, Wan; The Influenza Forecasting Working Group (Nature Publishing Group, 2019-01-24)Since 2013, the Centers for Disease Control and Prevention (CDC) has hosted an annual influenza season forecasting challenge. The 2015–2016 challenge consisted of weekly probabilistic forecasts of multiple targets, including fourteen models submitted by eleven teams. Forecast skill was evaluated using a modified logarithmic score. We averaged submitted forecasts into a mean ensemble model and compared them against predictions based on historical trends. Forecast skill was highest for seasonal peak intensity and short-term forecasts, while forecast skill for timing of season onset and peak week was generally low. Higher forecast skill was associated with team participation in previous influenza forecasting challenges and utilization of ensemble forecasting techniques. The mean ensemble consistently performed well and outperformed historical trend predictions. CDC and contributing teams will continue to advance influenza forecasting and work to improve the accuracy and reliability of forecasts to facilitate increased incorporation into public health response efforts. © 2019, The Author(s).
- Combining Participatory Influenza Surveillance with Modeling and Forecasting: Three Alternative ApproachesBrownstein, John S.; Marathe, Achla (JMIR Publications, 2017)Background: Influenza outbreaks affect millions of people every year and its surveillance is usually carried out in developed countries through a network of sentinel doctors who report the weekly number of Influenza-like Illness cases observed among the visited patients. Monitoring and forecasting the evolution of these outbreaks supports decision makers in designing effective interventions and allocating resources to mitigate their impact. Objective: Describe the existing participatory surveillance approaches that have been used for modeling and forecasting of the seasonal influenza epidemic, and how they can help strengthen real-time epidemic science and provide a more rigorous understanding of epidemic conditions. Methods: We describe three different participatory surveillance systems, WISDM (Widely Internet Sourced Distributed Monitoring), Influenzanet and Flu Near You (FNY), and show how modeling and simulation can be or has been combined with participatory disease surveillance to: i) measure the non-response bias in a participatory surveillance sample using WISDM; and ii) nowcast and forecast influenza activity in different parts of the world (using Influenzanet and Flu Near You). Results: WISDM-based results measure the participatory and sample bias for three epidemic metrics i.e. attack rate, peak infection rate, and time-to-peak, and find the participatory bias to be the largest component of the total bias. The Influenzanet platform shows that digital participatory surveillance data combined with a realistic data-driven epidemiological model can provide both short-term and long-term forecasts of epidemic intensities, and the ground truth data lie within the 95 percent confidence intervals for most weeks. The statistical accuracy of the ensemble forecasts increase as the season progresses. The Flu Near You platform shows that participatory surveillance data provide accurate short-term flu activity forecasts and influenza activity predictions. The correlation of the HealthMap Flu Trends estimates with the observed CDC ILI rates is 0.99 for 2013-2015. Additional data sources lead to an error reduction of about 40% when compared to the estimates of the model that only incorporates CDC historical information. Conclusions: While the advantages of participatory surveillance, compared to traditional surveillance, include its timeliness, lower costs, and broader reach, it is limited by a lack of control over the characteristics of the population sample. Modeling and simulation can help overcome this limitation as well as provide real-time and long-term forecasting of influenza activity in data-poor parts of the world.
- Defining the mutation sites in chickpea nodulation mutants PM233 and PM405Frailey, Daniel C.; Zhang, Qian; Wood, David J.; Davis, Thomas M. (2022-02-09)Background Like most legumes, chickpeas form specialized organs called root nodules. These nodules allow for a symbiotic relationship with rhizobium bacteria. The rhizobia provide fixed atmospheric nitrogen to the plant in a usable form. It is of both basic and practical interest to understand the host plant genetics of legume root nodulation. Chickpea lines PM233 and PM405, which harbor the mutationally identified nodulation genes rn1 and rn4, respectively, both display nodulation-deficient phenotypes. Previous investigators identified the rn1 mutation with the chickpea homolog of Medicago truncatula nodulation gene NSP2, but were unable to define the mutant rn1 allele. We used Illumina and Nanopore sequencing reads to attempt to identify and characterize candidate mutation sites responsible for the PM233 and PM405 phenotypes. Results We aligned Illumina reads to the available desi chickpea reference genome, and did a de novo contig assembly of Nanopore reads. In mutant PM233, the Nanopore contigs allowed us to identify the breakpoints of a ~ 35 kb deleted region containing the CaNSP2 gene, the Medicago truncatula homolog of which is involved in nodulation. In mutant PM405, we performed variant calling in read alignments and identified 10 candidate mutations. Genotyping of a segregating progeny population narrowed that pool down to a single candidate gene which displayed homology to M. truncatula nodulation gene NIN. Conclusions We have characterized the nodulation mutation sites in chickpea mutants PM233 and PM405. In mutant PM233, the rn1 mutation was shown to be due to deletion of the entire CaNSP2 nodulation gene, while in mutant PM405 the rn4 mutation was due to a single base deletion resulting in a frameshift mutation between the predicted RWP-RK and PB1 domains of the NIN nodulation gene. Critical to characterization of the rn1 allele was the generation of Nanopore contigs for mutant PM233 and its wild type parent ICC 640, without which the deletional boundaries could not be defined. Our results suggest that efforts of prior investigators were hampered by genomic misassemblies in the CaNSP2 region of both the desi and kabuli reference genomes.
- Focused ultrasound extraction (FUSE) for the rapid extraction of DNA from tissue matricesHolmes, Hal R.; Haywood, Morgan; Hutchison, Ruby; Zhang, Qian; Edsall, Connor; Hall, Timothy L.; Baisch, David; Holliday, Jason A.; Vlaisavljevich, Eli (2020-10-09)Rapid DNA extraction is a critical barrier for routine and fieldable genetics tests for applications in conservation, such as illegal trafficking and fraudulent mislabelling. Here, we develop a non-thermal focused ultrasound extraction (FUSE) technique that creates a dense cloud of high-pressure acoustic cavitation bubbles to disintegrate targeted tissues into an acellular debris, resulting in the rapid release of entrapped DNA. In this work, we demonstrate the proof-of-concept of the FUSE technique by obtaining species identifiable sequences and shotgun sequencing reads from DNA extracted from Atlantic salmon Salmo salar tissues. Having mitigated the key risks for this technique, we hypothesize future developments with this technology can be applied to accelerate and simplify DNA extraction from exceedingly difficult samples with complex tissue matrices (i.e. fibrous tissue and timber samples) in both laboratory and field settings.
- A genome-guided strategy for climate resilience in American chestnut restoration populationsSandercock, Alexander M.; Westbrook, Jared W.; Zhang, Qian; Holliday, Jason A. (National Academy of Sciences, 2024-07-16)American chestnut (Castanea dentata) is a deciduous tree species of eastern North America that was decimated by the introduction of the chestnut blight fungus (Cryphonectria parasitica) in the early 20th century. Although millions of American chestnuts survive as root collar sprouts, these trees rarely reproduce. Thus, the species is considered functionally extinct. American chestnuts with improved blight resistance have been developed through interspecific hybridization followed by conspecific backcrossing, and by genetic engineering. Incorporating adaptive genomic diversity into these backcross families and transgenic lines is important for restoring the species across broad climatic gradients. To develop sampling recommendations for ex situ conservation of wild adaptive genetic variation, we coupled whole-genome resequencing of 384 stump sprouts with genotype–environment association analyses and found that the species range can be subdivided into three seed zones characterized by relatively homogeneous adaptive allele frequencies. We estimated that 21 to 29 trees per seed zone will need to be conserved to capture most extant adaptive diversity. We also resequenced the genomes of 269 backcross trees to understand the extent to which the breeding program has already captured wild adaptive diversity, and to estimate optimal reintroduction sites for specific families on the basis of their adaptive portfolio and future climate projections. Taken together, these results inform the development of an ex situ germplasm conservation and breeding plan to target blight-resistant breeding populations to specific environments and provides a blueprint for developing restoration plans for other imperiled tree species.
- A meta-analysis of 1,119 manipulative experiments on terrestrial carbon-cycling responses to global changeSong, Jian; Wan, Shiqiang; Piao, Shilong; Knapp, Alan K.; Classen, Aimee T.; Vicca, Sara; Ciais, Philippe; Hovenden, Mark J.; Leuzinger, Sebastian; Beier, Claus; Kardol, Paul; Xia, Jianyang; Liu, Qiang; Ru, Jingyi; Zhou, Zhenxing; Luo, Yiqi; Guo, Dali; Langley, J. Adam; Zscheischler, Jakob; Dukes, Jeffrey S.; Tang, Jianwu; Chen, Jiquan; Hofmockel, Kirsten S.; Kueppers, Lara M.; Rustad, Lindsey E.; Liu, Lingli; Smith, Melinda D.; Templer, Pamela H.; Thomas, R. Quinn; Norby, Richard J.; Phillips, Richard P.; Niu, Shuli; Fatichi, Simone; Wang, Yingping; Shao, Pengshuai; Han, Hongyan; Wang, Dandan; Lei, Lingjie; Wang, Jiali; Li, Xiaona; Zhang, Qian; Li, Xiaoming; Su, Fanglong; Liu, Bin; Yang, Fan; Ma, Gaigai; Li, Guoyong; Liu, Yanchun; Liu, Yinzhan; Yang, Zhongling; Zhang, Kesheng; Miao, Yuan; Hu, Mengjun; Yan, Chuang; Zhang, Ang; Zhong, Mingxing; Hui, Yan; Li, Ying; Zheng, Mengmei (2019-09)Direct quantification of terrestrial biosphere responses to global change is crucial for projections of future climate change in Earth system models. Here, we synthesized ecosystem carbon-cycling data from 1,119 experiments performed over the past four decades concerning changes in temperature, precipitation, CO2 and nitrogen across major terrestrial vegetation types of the world. Most experiments manipulated single rather than multiple global change drivers in temperate ecosystems of the USA, Europe and China. The magnitudes of warming and elevated CO2 treatments were consistent with the ranges of future projections, whereas those of precipitation changes and nitrogen inputs often exceeded the projected ranges. Increases in global change drivers consistently accelerated, but decreased precipitation slowed down carbon-cycle processes. Nonlinear (including synergistic and antagonistic) effects among global change drivers were rare. Belowground carbon allocation responded negatively to increased precipitation and nitrogen addition and positively to decreased precipitation and elevated CO2. The sensitivities of carbon variables to multiple global change drivers depended on the background climate and ecosystem condition, suggesting that Earth system models should be evaluated using site-specific conditions for best uses of this large dataset. Together, this synthesis underscores an urgent need to explore the interactions among multiple global change drivers in under-represented regions such as semi-arid ecosystems, forests in the tropics and subtropics, and Arctic tundra when forecasting future terrestrial carbon-climate feedback.
- Optimizing genomic selection for blight resistance in American chestnut backcross populations: A trade‐off with American chestnut ancestry implies resistance is polygenicWestbrook, Jared W.; Zhang, Qian; Mandal, Mihir Kumar; Jenkins, Eric V.; Barth, Laura E.; Jenkins, Jerry W.; Grimwood, Jane; Schmutz, Jeremy; Holliday, Jason A. (Wiley, 2019-10-02)American chestnut was once a foundation species of eastern North American forests, but was rendered functionally extinct in the early 20th century by an exotic fungal blight (Cryphonectria parasitica). Over the past 30 years, the American Chestnut Foundation (TACF) has pursued backcross breeding to generate hybrids that combine the timber‐type form of American chestnut with the blight resistance of Chinese chestnut based on a hypothesis of major gene resistance. To accelerate selection within two backcross populations that descended from two Chinese chestnuts, we developed genomic prediction models for five presence/absence blight phenotypes of 1,230 BC₃F₂ selection candidates and average canker severity of their BC₃F₃ progeny. We also genotyped pure Chinese and American chestnut reference panels to estimate the proportion of BC₃F₂ genomes inherited from parent species. We found that genomic prediction from a method that assumes an infinitesimal model of inheritance (HBLUP) has similar accuracy to a method that tends to perform well for traits controlled by major genes (Bayes C). Furthermore, the proportion of BC₃F₂ trees' genomes inherited from American chestnut was negatively correlated with the blight resistance of these trees and their progeny. On average, selected BC₃F₂ trees inherited 83% of their genome from American chestnut and have blight resistance that is intermediate between F₁ hybrids and American chestnut. Results suggest polygenic inheritance of blight resistance. The blight resistance of restoration populations will be enhanced through recurrent selection, by advancing additional sources of resistance through fewer backcross generations, and by potentially by breeding with transgenic blight‐tolerant trees.
- Synthesis and Characterization of Novel Magnetite Nanoparticle Block Copolymer ComplexesZhang, Qian (Virginia Tech, 2007-04-03)Superparamagnetic Magnetite (Fe3O4) nanoparticles were synthesized and complexed with carboxylate-functionalized block copolymers, and aqueous dispersions of the complexes were investigated as functions of their chemical and morphological structures. The block copolymer dispersants possessed either poly(ethylene oxide), poly(ethylene oxide-co-propylene oxide), or poly(ethylene oxide-b-propylene oxide) outer blocks, and all contained a polyurethane center block with pendant carboxylate functional groups. The complexes were formed through interactions of the carboxylates with the surfaces of the magnetite nanoparticles. Initial efforts utilized an aqueous coprecipitation method for the synthesis of magnetite nanoparticles, which yielded polydisperse magnetite nanoparticles. The nanoparticle complexes were characterized with a range of solution- and solid-state techniques including TGA, XPS, TEM, VSM, DLS and zeta potential measurements. DLVO calculation methods, which sum the contributions from van der Waals, steric, electrostatic and magnetic forces were utilized to examine the interparticle potentials in the presence and absence of external magnetic fields. Compositions were identified wherein a shallow, attractive interparticle potential minimum appears once the magnetic term is applied. This suggested the possibility of tuning the structures of superparamagnetic nanoparticle shells to allow discrete dispersions without a field, yet permit weak flocculation upon exposure to a field. This property has important implications for biomedical applications where movement of particles with an external magnetic field is desirable. In a second study, well-defined, narrow size dispersity magnetite nanoparticles were synthesized via the thermolysis of an iron (III) acetylacetonate (Fe(acac)3) precursor in the presence of benzyl alcohol. The magnetite nanoparticles were coated with triblock and pentablock copolymers possessing poly(ethylene oxide) and poly(propylene oxide-b-ethylene oxide) tailblocks and the carboxylate-functional anchor block. DLVO calculations were applied to the new magnetite particles and diagrams of potential energy versus interparticle distance indicated the predominant effect of steric and magnetic interactions on the particle stability. Exposure of the pentablock copolymer-magnetite complexes in phosphate buffered saline to a 1500 Oe magnetic field with concomitant DLS measurements indicated flocculation of the magnetic nanoparticles. DLS measurements showed increased hydrodynamic radii and scattering intensities with time.