What can we learn about controlling a system solely from its underlying network structure? Here we adapt a recently developed framework for control of networks governed by a broad class of nonlinear dynamics that includes the major dynamic models of biological, technological, and social processes. This feedback-based framework provides realizable node overrides that steer a system toward any of its natural long-term dynamic behaviors, regardless of the specific functional forms and system parameters. We use this framework on several real networks, identify the topological characteristics that underlie the predicted node overrides, and compare its predictions to those of structural controllability in control theory. Finally, we demonstrate this framework's applicability in dynamic models of gene regulatory networks and identify nodes whose override is necessary for control in the general case but not in specific model instances.

https://www.pnas.org/content/pnas/114/28/7234.full.pdf

Structure-based control of complex networks with nonlinear dynamics

BACKGROUND: The global impact of the 2009 influenza A(H1N1) pandemic (H1N1pdm) is not well understood. OBJECTIVES: We estimate overall and age-specific prevalence of cross-reactive antibodies to H1N1pdm virus and rates of H1N1pdm infection during the first year of the pandemic using data from published and unpublished H1N1pdm seroepidemiological studies.
METHODS: Primary aggregate H1N1pdm serologic data from each study were stratified in standardized age groups and evaluated based on when sera were collected in relation to national or subnational peak H1N1pdm activity. Seropositivity was assessed using well-described and standardized hemagglutination inhibition (HI titers ≥ 32 or ≥ 40) and microneutralization (MN ≥ 40) laboratory assays. The prevalence of cross-reactive antibodies to the H1N1pdm virus was estimated for studies using sera collected prior to the start of the pandemic (between 2004 and April 2009); H1N1pdm cumulative incidence was estimated for studies in which collected both pre- and post-pandemic sera; and H1N1pdm seropositivity was calculated from studies with post-pandemic sera only (collected between December 2009-June 2010).
RESULTS: Data from 27 published/unpublished studies from 19 countries/administrative regions - Australia, Canada, China, Finland, France, Germany, Hong Kong SAR, India, Iran, Italy, Japan, Netherlands, New Zealand, Norway, Reunion Island, Singapore, United Kingdom, United States, and Vietnam - were eligible for inclusion. The overall age-standardized pre-pandemic prevalence of cross-reactive antibodies was 5% (95%CI 3-7%) and varied significantly by age with the highest rates among persons ≥ 65 years old (14% 95%CI 8-24%). Overall age-standardized H1N1pdm cumulative incidence was 24% (95%CI 20-27%) and varied significantly by age with the highest in children 5-19 (47% 95%CI 39-55%) and 0-4 years old (36% 95%CI 30-43%).
CONCLUSIONS: Our results offer unique insight into the global impact of the H1N1 pandemic and highlight the need for standardization of seroepidemiological studies and for their inclusion in pre-pandemic preparedness plans. Our results taken together with recent global pandemic respiratory-associated mortality estimates suggest that the case fatality ratio of the pandemic virus was approximately 0.02%.

https://www.who.int/influenza/surveillance_monitoring/EN_GIP_WHO_H1N1pdmSerologyManuscript_2013.pdf

Estimating age-specific cumulative incidence for the 2009 influenza pandemic: a meta-analysis of A(H1N1)pdm09 serological studies from 19 countries.

Background 
Pandemic influenza A(H1N1) 2009 virus was first detected in Japan in May 2009 and continued to circulate in the 2010–2011 season. This study aims to characterize human influenza viruses circulating in Japan in the pandemic and post-pandemic periods and to determine the prevalence of antiviral-resistant viruses.


Methods 
Respiratory specimens were collected from patients with influenza-like illness on their first visit at outpatient clinics during the 2009–2010 and 2010–2011 influenza seasons. Cycling probe real-time PCR assays were performed to screen for antiviral-resistant strains. Sequencing and phylogenetic analysis of the HA and NA genes were done to characterize circulating strains.


Results and Conclusion 
In the pandemic period (2009–2010), the pandemic influenza A(H1N1) 2009 virus was the only circulating strain isolated. None of the 601 A(H1N1)pdm09 virus isolates had the H275Y substitution in NA (oseltamivir resistance) while 599/601 isolates (99.7%) had the S31N substitution in M2 (amantadine resistance). In the post-pandemic period (2010–2011), cocirculation of different types and subtypes of influenza viruses was observed. Of the 1,278 samples analyzed, 414 (42.6%) were A(H1N1)pdm09, 525 (54.0%) were A(H3N2) and 33 (3.4%) were type-B viruses. Among A(H1N1)pdm09 isolates, 2 (0.5%) were oseltamivir-resistant and all were amantadine-resistant. Among A(H3N2) viruses, 520 (99.0%) were amantadine-resistant. Sequence and phylogenetic analyses of A(H1N1)pdm09 viruses from the post-pandemic period showed further evolution from the pandemic period viruses. For viruses that circulated in 2010–2011, strain predominance varied among prefectures. In Hokkaido, Niigata, Gunma and Nagasaki, A(H3N2) viruses (A/Perth/16/2009-like) were predominant whereas, in Kyoto, Hyogo and Osaka, A(H1N1)pdm09 viruses (A/New_York/10/2009-like) were predominant. Influenza B Victoria(HA)-Yamagata(NA) reassortant viruses (B/Brisbane/60/2008-like) were predominant while a small proportion was in Yamagata lineage. Genetic variants with mutations at antigenic sites were identified in A(H1N1)pdm09, A(H3N2) and type-B viruses in the 2010–2011 season but did not show a change in antigenicity when compared with respective vaccine strains.

/pdf/genetic-characterization-of-human-influenza-viruses-in-the-29alkkwzm0.pdf

Genetic Characterization of Human Influenza Viruses in the Pandemic (2009–2010) and Post-Pandemic (2010–2011) Periods in Japan

Self-organized collective coordinated behaviour is an impressive phenomenon, observed in a variety of natural and artificial systems, in which coherent global structures or dynamics emerge from local interactions between individual parts. If the degree of collective integration of a system does not depend on size, its level of robustness and adaptivity is typically increased and we refer to it as scale-invariant. In this review, we first identify three main types of self-organized scale-invariant systems: scale-invariant spatial structures, scale-invariant topologies and scale-invariant dynamics. We then provide examples of scale invariance from different domains in science, describe their origins and main features and discuss potential challenges and approaches for designing and engineering artificial systems with scale-invariant properties.

https://royalsocietypublishing.org/doi/pdf/10.1098/rsif.2017.0662

Scale invariance in natural and artificial collective systems : a review

Cellular stress responses require exquisite coordination between intracellular signaling molecules to integrate multiple stimuli and actuate specific cellular behaviors. Deciphering the web of complex interactions underlying stress responses is a key challenge in understanding robust biological systems and has the potential to lead to the discovery of targeted therapeutics for diseases triggered by dysregulation of stress response pathways. We constructed large-scale molecular interaction maps of six major stress response pathways in Saccharomyces cerevisiae (baker’s or budding yeast). Biological findings from over 900 publications were converted into standardized graphical formats and integrated into a common framework. The maps are posted at http://www.yeast-maps.org/yeast-stress-response/
 for browse and curation by the research community. On the basis of these maps, we undertook systematic analyses to unravel the underlying architecture of the networks. A series of network analyses revealed that yeast stress response pathways are organized in bow–tie structures, which have been proposed as universal sub-systems for robust biological regulation. Furthermore, we demonstrated a potential role for complexes in stabilizing the conserved core molecules of bow–tie structures. Specifically, complex-mediated reversible reactions, identified by network motif analyses, appeared to have an important role in buffering the concentration and activity of these core molecules. We propose complex-mediated reactions as a key mechanism mediating robust regulation of the yeast stress response. Thus, our comprehensive molecular interaction maps provide not only an integrated knowledge base, but also a platform for systematic network analyses to elucidate the underlying architecture in complex biological systems. Computer models assembled from curated experimental data offer insights into the mechanisms by which yeast cells respond to stressors. Every biological process is dependent on complex interactions between a host of different molecular factors, and modeling this interplay can pose a daunting challenge. A Japan-India team formed by Japan’s Systems Biology Institute and Persistent Systems Limited in India has now demonstrated how sophisticated biological networks can be reconstructed from a large-scale curation of publicly available articles and data. The researchers focused on the pathways that yeast use to adapt to stressors such as heat and nutrient deprivation, translating findings from more than 900 previously published studies into a machine-readable, visual format. Network analysis on this knowledge base revealed key factors that regulate the activity of stress-response networks and the mechanisms by which this regulation occurs.

/pdf/network-analyses-based-on-comprehensive-molecular-4hncdoztxk.pdf

Network analyses based on comprehensive molecular interaction maps reveal robust control structures in yeast stress response pathways

Since its emergence, the 2009 pandemic H1N1 virus has spread rapidly throughout the world. Previously, we reported that most individuals born after 1920 do not have cross-reactive virus-neutralizing antibodies against pandemic (H1N1) 2009 virus, indicating that they were immunologically naive to the pandemic virus prior to its emergence. This finding provided us with an excellent opportunity for a seroepidemiological investigation of the transmission mode of the pandemic virus in the community. To gain insight into its transmission within communities, we performed a serosurvey for pandemic virus infection with schoolchildren at an elementary school in Tokyo, Japan, and their parents. We observed a high prevalence of neutralizing antibodies to the pandemic virus in the children at this school, although the percentage of children positive for the neutralizing antibodies varied among classrooms. While a much lower prevalence was observed among parents, seropositivity of the parents correlated with that of their schoolchildren. Moreover, many adults appeared to have experienced asymptomatic infection with the pandemic virus. These data suggest that the pandemic virus was readily transmitted among schoolchildren in elementary schools and that it was also transmitted from schoolchildren to their parents.

https://cvi.asm.org/content/cdli/18/5/860.full.pdf

Seroprevalence of pandemic 2009 (H1N1) influenza A virus among schoolchildren and their parents in Tokyo, Japan.

Cultivation of cos lettuce using blue LED and quantum dot wavelength conversion sheets

http://manuscript.elsevier.com/S0006291X2200198X/pdf/S0006291X2200198X.pdf

Takashi Ishii

Papers

Network analyses based on comprehensive molecular interaction maps reveal robust control structures in yeast stress response pathways

Seroprevalence of pandemic 2009 (H1N1) influenza A virus among schoolchildren and their parents in Tokyo, Japan.

Cultivation of cos lettuce using blue LED and quantum dot wavelength conversion sheets

Involvement of Gtr1p in the oxidative stress response in yeast Saccharomyces cerevisiae.