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Additional file 7: Figure S6. Estimated and fitted relative reduction of weekly ILI counts by multivariate GAM model with combined NPI indicators in Beijing (a) and the Hong Kong SAR (b) in 2020–2021, based on non-COVID estimates using Eq. 7 and data in 2011–2019. ILI: Influenza-like illness; GAM: Generalized additive model; NPI: Non-pharmaceutical intervention; Hong Kong SAR: Hong Kong Special Administrative Region; COVID: Coronavirus disease 2019.

Additional file 3: Figure S2. Estimated and fitted relative reduction of weekly ILI counts by multivariate GAM model with combined NPI indicators in Beijing (a) and the Hong Kong SAR (b) in 2020–2021, based on non-COVID estimates using Eq. 6 and data in 2011–2019. ILI: Influenza-like illness; GAM: Generalized additive model; NPI: Non-pharmaceutical intervention; Hong Kong SAR: Hong Kong Special Administrative Region; COVID: Coronavirus disease 2019.

Additional file 2: Figure S1. Estimated and fitted relative reduction of weekly ILI counts by multivariate GAM model with individual NPI indicators in Beijing (a) and the Hong Kong SAR (b) in 2020–2021, based on non-COVID estimates using Eq. 6 and data in 2011–2019. ILI: Influenza-like illness; GAM: Generalized additive model; NPI: Non-pharmaceutical intervention; Hong Kong SAR: Hong Kong Special Administrative Region; COVID: Coronavirus disease 2019.

The intranasal spray COVID-19 vaccine was made available for the first time in China, it is necessary to understand receivers’ satisfaction and experience toward the vaccine to help optimize vaccination service. A self-administered multicenter cross-sectional questionnaire survey was conducted in Beijing, China, in December 2022. The vaccination experience was evaluated through three dimensions: immediate tolerance, smooth progress, and time-saving. Vaccine acceptability was measured by receivers’ preference for the intranasal spray over intramuscular injection after vaccination and their recommendation willingness. Stepwise multinomial and binary logistic regression models were applied to investigate factors associated with vaccine acceptability. Among 10,452 participants included in the analysis, 92.6% felt no discomfort during the inoculation, 99.8% thought the vaccination process went well, and 89.4% deemed it a time-saving option. For vaccine acceptability, 5566 (53.3%) participants were willing to recommend the vaccine to others, 534 (5.1%) refused, and 4352 (41.6%) had not decided yet; 6142 (58.8%) participants preferred the intranasal spray, 873 (8.4%) preferred the intramuscular injection, and 3437 (32.9%) had no preferences. The most concerned aspects of the intranasal spray vaccine were vaccine effectiveness and safety. Receivers who perceived higher vaccine effectiveness or safety were more likely to recommend it to others (OR, 95%CI: 4.41, 3.24–6.00; 6.11, 4.52–8.27) or prefer it over intramuscular injection after vaccination (OR, 95%CI: 5.94, 4.62–7.65; 8.50, 6.70–10.78). Receivers showed good acceptability and experience toward the intranasal spray COVID-19 vaccine. Vaccine effectiveness and safety were the most concerned aspects, and corresponding publicity and education efforts may help improve vaccine acceptability.

Additional file 5: Figure S4. Estimated and fitted relative reduction of weekly ILI counts by multivariate GAM model with combined NPI indicators in Beijing (a) and the Hong Kong SAR (b) in 2020–2021, based on non-COVID estimates using Eq. 6 and data in 2011–2017. ILI: Influenza-like illness; GAM: Generalized additive model; NPI: Non-pharmaceutical intervention; Hong Kong SAR: Hong Kong Special Administrative Region; COVID: Coronavirus disease 2019.

Additional file 2: Figure S1. Estimated and fitted relative reduction of weekly ILI counts by multivariate GAM model with individual NPI indicators in Beijing (a) and the Hong Kong SAR (b) in 2020–2021, based on non-COVID estimates using Eq. 6 and data in 2011–2019. ILI: Influenza-like illness; GAM: Generalized additive model; NPI: Non-pharmaceutical intervention; Hong Kong SAR: Hong Kong Special Administrative Region; COVID: Coronavirus disease 2019.

Additional file 6: Figure S5. Estimated and fitted relative reduction of weekly ILI counts by multivariate GAM model with individual NPI indicators in Beijing (a) and the Hong Kong SAR (b) in 2020–2021, based on non-COVID estimates using Eq. 7 and data in 2011–2019. ILI: Influenza-like illness; GAM: Generalized additive model; NPI: Non-pharmaceutical intervention; Hong Kong SAR: Hong Kong Special Administrative Region; COVID: Coronavirus disease 2019.

Additional file 4: Figure S3. Estimated and fitted relative reduction of weekly ILI counts by multivariate GAM model with individual NPI indicators in Beijing (a) and the Hong Kong SAR (b) in 2020–2021, based on non-COVID estimates using Eq. 6 and data in 2011–2017. ILI: Influenza-like illness; GAM: Generalized additive model; NPI: Non-pharmaceutical intervention; Hong Kong SAR: Hong Kong Special Administrative Region; COVID: Coronavirus disease 2019.

Additional file 6: Figure S5. Estimated and fitted relative reduction of weekly ILI counts by multivariate GAM model with individual NPI indicators in Beijing (a) and the Hong Kong SAR (b) in 2020–2021, based on non-COVID estimates using Eq. 7 and data in 2011–2019. ILI: Influenza-like illness; GAM: Generalized additive model; NPI: Non-pharmaceutical intervention; Hong Kong SAR: Hong Kong Special Administrative Region; COVID: Coronavirus disease 2019.

Additional file 5: Figure S4. Estimated and fitted relative reduction of weekly ILI counts by multivariate GAM model with combined NPI indicators in Beijing (a) and the Hong Kong SAR (b) in 2020–2021, based on non-COVID estimates using Eq. 6 and data in 2011–2017. ILI: Influenza-like illness; GAM: Generalized additive model; NPI: Non-pharmaceutical intervention; Hong Kong SAR: Hong Kong Special Administrative Region; COVID: Coronavirus disease 2019.

Additional file 7: Figure S6. Estimated and fitted relative reduction of weekly ILI counts by multivariate GAM model with combined NPI indicators in Beijing (a) and the Hong Kong SAR (b) in 2020–2021, based on non-COVID estimates using Eq. 7 and data in 2011–2019. ILI: Influenza-like illness; GAM: Generalized additive model; NPI: Non-pharmaceutical intervention; Hong Kong SAR: Hong Kong Special Administrative Region; COVID: Coronavirus disease 2019.

Additional file 1: Table S1. Individual COVID-19 NPI indicators, definition, and coding in Beijing and the Hong Kong SAR. Table S2. Combined COVID-19 NPI indicators, definition, and coding in Beijing and the Hong Kong SAR. Table S3. Collinearity analysis between meteorological factors in Beijing from 2011 to 2019 using the Pearson correlation method. Table S4. Collinearity analysis between meteorological factors in the Hong Kong SAR from 2011 to 2019 using the Pearson correlation method. Table S5. The goodness of fit of the predictive GAM models in Beijing with blocked cross-validation method. Table S6. The goodness of fit of the predictive GAM models in the Hong Kong SAR with blocked cross-validation method. Table S7. Collinearity analysis between relative change of meteorological factors in Beijing from 2020 to 2021 using the Pearson correlation method. Table S8. Collinearity analysis between relative change of meteorological factors in the Hong Kong SAR from 2020 to 2021 using the Pearson correlation method. Table S9. Collinearity analysis between 9 NPIs indicators in Beijing from 2020 to 2021 using the Pearson correlation method. Table S10. Collinearity analysis between 9 NPI indicators in the Hong Kong SAR from 2020 to 2021 using the Pearson correlation method. Table S11. Collinearity analysis between combined NPI indicators in Beijing from 2020 to 2021 using the Pearson correlation method. Table S12. Collinearity analysis between combined NPI indicators in the Hong Kong SAR from 2020 to 2021 using the Pearson correlation method. Table S13. The goodness of fit of the GAM models with blocked cross-validation method in Beijing and the Hong Kong SAR, 2020-2021. Table S14. The potential impact of each individual and combined NPI on weekly ILI counts in Beijing and the Hong Kong SAR, 2020-2021*. Table S15. Multivariable analysis for the potential impact of NPIs on weekly ILI counts in Beijing and the Hong Kong SAR, 2020-2021*. Table S16. The potential impact of each individual and combined NPI on weekly ILI counts in Beijing and the Hong Kong SAR, 2020-2021*. Table S17. Multivariable analysis for the potential impact of NPIs on weekly ILI counts in Beijing and the Hong Kong SAR, 2020-2021*.

Additional file 4: Figure S3. Estimated and fitted relative reduction of weekly ILI counts by multivariate GAM model with individual NPI indicators in Beijing (a) and the Hong Kong SAR (b) in 2020–2021, based on non-COVID estimates using Eq. 6 and data in 2011–2017. ILI: Influenza-like illness; GAM: Generalized additive model; NPI: Non-pharmaceutical intervention; Hong Kong SAR: Hong Kong Special Administrative Region; COVID: Coronavirus disease 2019.

IntroductionSeasonal influenza activity has declined globally since the widespread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission. There has been scarce information to understand the future dynamics of influenza — and under different hypothesis on relaxation of non-pharmaceutical interventions (NPIs) in particular — after the disruptions to seasonal patterns.MethodsWe collected data from public sources in China, the United Kingdom, and the United States, and forecasted the influenza dynamics in the incoming 2021–2022 season under different NPIs. We considered Northern China and Southern China separately, due to the sharp difference in the patterns of seasonal influenza. For the United Kingdom, data were collected for England only.ResultsCompared to the epidemics in 2017–2019, longer and blunter influenza outbreaks could occur should NPIs be fully lifted, with percent positivity varying from 10.5 to 18.6 in the studying regions. The rebounds would be smaller if the mask-wearing intervention continued or the international mobility stayed low, but sharper if the mask-wearing intervention was lifted in the middle of influenza season. Further, influenza activity could stay low under a much less stringent mask-wearing intervention coordinated with influenza vaccination.ConclusionsThe results added to our understandings of future influenza dynamics after the global decline during the coronavirus disease 2019 (COVID-19) pandemic. In light of the uncertainty on the incoming circulation strains and the relatively low negative impacts of mask wearing on society, our findings suggested that wearing mask could be considered as an accompanying mitigation measure in influenza prevention and control, especially for seasons after long periods of low-exposure to influenza viruses.

Governments worldwide have rapidly deployed non-pharmaceutical interventions (NPIs) to mitigate the COVID- 19 pandemic. However, the effect of these individual NPI measures across space and time has yet to be sufficiently assessed, especially with the increase of policy fatigue and the urge for NPI relaxation in the vaccination era. Using the decay ratio in the suppression of COVID-19 infections and multi-source big data, we investigated the changing performance of different NPIs across waves from global and regional levels (in 133 countries) to national and subnational (in the United States of America [USA]) scales before the implementation of mass vaccination. The synergistic effectiveness of all NPIs for reducing COVID-19 infections declined along waves, from 95.4% in the first wave to 56.0% in the third wave recently at the global level and similarly from 83.3% to 58.7% at the USA national level, while it had fluctuating performance across waves on regional and subnational scales. Regardless of geographical scale, gathering restrictions and facial coverings played significant roles in epidemic mitigation before the vaccine rollout. Our findings have important implications for continued tailoring and implementation of NPI strategies, together with vaccination, to mitigate future COVID-19 waves, caused by new variants, and other emerging respiratory infectious diseases. Published version

Additional file 1: Table S1. Top three reasons for willing to be vaccinated against herpes zoster for the elderly in China (n=9482). Table S2. Top three reasons for not willing to be vaccinated against herpes zoster for the elderly in China (n=9805). Table S3. Sensitivity analysis of intent to be vaccinated based on participant characteristics.

Additional file 1: Questionnaire

Additional file 2: Table S1. Characteristics of HCWs surveyed and in China Health Statistics Yearbook 2021.

Additional file 2: Table S1. Multivariate logistic regression to explore the risk factors that affect people to contract the SARS-CoV-2. Table S2. Multivariate logistic regression to explore the risk factors that affect people with underlying diseases to contract the SARS-CoV-2. Table S3. Demographics and positive rate of total antibodies of study subjects.

This paper summarizes the basic principles and models of early warning for infectious disease outbreaks, introduces the early warning systems for infectious disease based on different data sources and their applications, and discusses the application potential of big data and their analysing techniques, which have been studied and used in the prevention and control of COVID-19 pandemic, including internet inquiry, social media, mobile positioning, in the early warning of infectious diseases in order to provide reference for the establishment of an intelligent early warning mechanism and platform for infectious diseases based on multi-source big data.

Travel restrictions and physical distancing have been implemented across the world to mitigate the coronavirus disease 2019 (COVID-19) pandemic, but studies are needed to understand their effectiveness across regions and time. Based on the population mobility metrics derived from mobile phone geolocation data across 135 countries or territories during the first wave of the pandemic in 2020, we built a metapopulation epidemiological model to measure the effect of travel and contact restrictions on containing COVID-19 outbreaks across regions. We found that if these interventions had not been deployed, the cumulative number of cases could have shown a 97-fold (interquartile range 79-116) increase, as of May 31, 2020. However, their effectiveness depended upon the timing, duration, and intensity of the interventions, with variations in case severity seen across populations, regions, and seasons. Additionally, before effective vaccines are widely available and herd immunity is achieved, our results emphasize that a certain degree of physical distancing at the relaxation of the intervention stage will likely be needed to avoid rapid resurgences and subsequent lockdowns. (C) 2021 THE AUTHORS. Published by Elsevier LTD on behalf of Chinese Academy of Engineering and Higher Education Press Limited Company. Bill & Melinda Gates FoundationBill & Melinda Gates FoundationCGIAR [OPP1134076, INV-024911, OPP1106427, OPP1032350, OPP1094793, OPP1170969]; National Science FoundationNational Science Foundation (NSF) [1816075]; EU Horizon [MOOD 874850]; Clinton Health Access Initiative; UK Department for International Development (DFID); Well-come TrustWellcome TrustEuropean Commission [106866/Z/15/Z, 204613/Z/16/Z] Published version The authors would like to acknowledge Google and Baidu for sharing population movement data. This study was supported by the grants from the Bill & Melinda Gates Foundation (OPP1134076, INV-024911) . Nick W. Ruktanonchai is supported by funding from the Bill & Melinda Gates Foundation (OPP1170969) . Olivia Prosper is supported by the National Science Foundation (1816075) . Andrew J. Tatem is supported by funding from the Bill & Melinda Gates Foundation (OPP1106427, OPP1032350, OPP1134076, and OPP1094793) , the EU Horizon (MOOD 874850) , the Clinton Health Access Initiative, the UK Department for International Development (DFID) , and the Well-come Trust (106866/Z/15/Z and 204613/Z/16/Z) .

BACKGROUND: Previous studies have shown associations between local weather factors and dengue incidence in tropical and subtropical regions. However, spatial variability in those associations remains unclear and evidence is scarce regarding the effects of weather extremes. OBJECTIVES: We examined spatial variability in the effects of various weather conditions on the unprecedented dengue outbreak in Guangdong province of China in 2014 and explored how city characteristics modify weather-related risk. METHODS: A Bayesian spatial conditional autoregressive model was used to examine the overall and city-specific associations of dengue incidence with weather conditions including (1) average temperature, temperature variation, and average rainfall; and (2) weather extremes including numbers of days of extremely high temperature and high rainfall (both used 95th percentile as the cut-off). This model was run for cumulative dengue cases during five months from July to November (accounting for 99.8% of all dengue cases). A further analysis based on spatial variability was used to validate the modification effects by economic, demographic and environmental factors. RESULTS: We found a positive association of dengue incidence with average temperature in seven cities (relative risk (RR) range: 1.032 to 1.153), a positive association with average rainfall in seven cities (RR range: 1.237 to 1.974), and a negative association with temperature variation in four cities (RR range: 0.315 to 0.593). There was an overall positive association of dengue incidence with extremely high temperature (RR:1.054, 95% credible interval (CI): 1.016 to 1.094), without evidence of variation across cities, and an overall positive association of dengue with extremely high rainfall (RR:1.505, 95% CI: 1.096 to 2.080), with seven regions having stronger associations (RR range: 1.237 to 1.418). Greater effects of weather conditions appeared to occur in cities with higher economic level, lower green space coverage and lower elevation. CONCLUSIONS: Spatially varied effects of weather conditions on dengue outbreaks necessitate area-specific dengue prevention and control measures. Extremes of temperature and rainfall have strong and positive associations with dengue outbreaks.

BACKGROUND: The mosquitoes Aedes aegypti and Ae. albopictus are the primary vectors of dengue virus, and their geographic distributions are predicted to expand further with economic development, and in response to climate change. We aimed to estimate the impact of future climate change on dengue transmission through the development of a Suitable Conditions Index (SCI), based on climatic variables known to support vectorial capacity. We calculated the SCI based on various climate change scenarios for six countries in the Asia-Pacific region (Australia, China, Indonesia, The Philippines, Thailand and Vietnam). METHODS: Monthly raster climate data (temperature and precipitation) were collected for the period January 2005 to December 2018 along with projected climate estimates for the years 2030, 2050 and 2070 using Representative Concentration Pathway (RCP) 4·5, 6·0 and 8·5 emissions scenarios. We defined suitable temperature ranges for dengue transmission of between 17·05-34·61 °C for Ae. aegypti and 15·84-31·51 °C for Ae. albopictus and then developed a historical and predicted SCI based on weather variability to measure the expected geographic limits of dengue vectorial capacity. Historical and projected SCI values were compared through difference maps for the six countries. FINDINGS: Comparing different emission scenarios across all countries, we found that most South East Asian countries showed either a stable pattern of high suitability, or a potential decline in suitability for both vectors from 2030 to 2070, with a declining pattern particularly evident for Ae. albopictus. Temperate areas of both China and Australia showed a less stable pattern, with both moderate increases and decreases in suitability for each vector in different regions between 2030 and 2070. INTERPRETATION: The SCI will be a useful index for forecasting potential dengue risk distributions in response to climate change, and independently of the effects of human activity. When considered alongside additional correlates of infection such as human population density and socioeconomic development indicators, the SCI could be used to develop an early warning system for dengue transmission.

Travel and physical distancing interventions have been implemented across the World to mitigate the COVID-19 pandemic, but studies are needed to quantify the effectiveness of these measures across regions and time. Timely population mobility data were obtained to measure travel and contact reductions in 135 countries or territories. During the 10 weeks of March 22 - May 30, 2020, domestic travel in study regions has dramatically reduced to a median of 59% (interquartile range [IQR] 43% - 73%) of normal levels seen before the outbreak, with international travel down to 26% (IQR 12% - 35%). If these travel and physical distancing interventions had not been deployed across the World, the cumulative number of cases might have shown a 97-fold (IQR 79 - 116) increase, as of May 31, 2020. However, effectiveness differed by the duration and intensity of interventions and relaxation scenarios, with variations in case severity seen across populations, regions, and seasons.Competing Interest StatementThe authors have declared no competing interest.Funding StatementThis study was supported by the grants from the Bill & Melinda Gates Foundation (OPP1134076); the European Union Horizon 2020 (MOOD 874850). N.R. is supported by funding from the Bill & Melinda Gates Foundation (OPP1170969). O.P. is supported by the National Science Foundation (1816075). A.J.T. is supported by funding from the Bill & Melinda Gates Foundation (OPP1106427, OPP1032350, OPP1134076, OPP1094793), the Clinton Health Access Initiative, the UK Department for International Development (DFID) and the Wellcome Trust (106866/Z/15/Z, 204613/Z/16/Z). Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:Ethical clearance for collecting and using secondary population mobility data was granted by the institutional review board of the University of Southampton (No. 48002). All data were supplied and analyzed in an anonymous format, without access to personal identifying information.All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesCode for the model simulations is available at the following GitHub repository: https://github.com/wpgp/BEARmod. The data on COVID-19 cases and interventions reported by country are available from the data sources listed in Supplementary Materials. The parameters and population data for running simulations and estimating the severity are listed in Supplementary Data S1 to S2. The population movement data obtained from Baidu are available at: https://qianxi.baidu.com/. The Google COVID-19 Aggregated Mobility Research Dataset used for this study is available with permission of Google, LLC.

Backround:Pancreatic ductal adenocarcinoma (PDAC) is the most common and deadly cancer. Surgical resection is the only possible cure for pancreatic cancer but often has a poor prognosis, and the role of adjuvant therapy is urgently explored.Methods:MicroRNAs (miRNAs) play very important role in tumorigenesis by regulating the target genes. In this study, we identified miR-320b lower-expressed in human pancreatic cancer tissues but relatively higher-expressed in the adjacent nontumor tissues.Results:Consistently，the expression of miR-320b in different pancreatic cancer cell lines was significantly lower than the normal pancreatic cells. In order to identify the effects of miR-320b on cell growth, we overexpressed miR-320b in PANC-1 and FG pancreatic cancer cell lines, CCK8 and BrdU incorporation assay results showed that miR-320b inhibited cell proliferation.Discussion:We next predicted miR-20b targeted FOXM1（Forkhead box protein M1）and identified the negative relationship between miR-320b and FOXM1.We also demonstrated that elevated miR-320b expression inhibited tumor growth in vivo.Conclusion:All of these results showed that miR-320b suppressed pancreatic cancer cells proliferation by targeting FOXM1, which might provide a new diagnostic marker for pancreatic cancer.

BACKGROUND: A novel coronavirus (2019-nCoV) emerged in Wuhan City, China, at the end of 2019 and has caused an outbreak of human-to-human transmission with a Public Health Emergency of International Concern declared by the World Health Organization on January 30, 2020.AIM: We aimed to estimate the potential risk and geographic range of Wuhan novel coronavirus (2019-nCoV) spread within and beyond China from January through to April, 2020.METHODS: A series of domestic and international travel network-based connectivity and risk analyses were performed, by using de-identified and aggregated mobile phone data, air passenger itinerary data, and case reports.RESULTS: The cordon sanitaire of Wuhan is likely to have occurred during the latter stages of peak population numbers leaving the city before Lunar New Year (LNY), with travellers departing into neighbouring cities and other megacities in China. We estimated that 59,912 air passengers, of which 834 (95% UI: 478 - 1349) had 2019-nCoV infection, travelled from Wuhan to 382 cities outside of mainland China during the two weeks prior to the lockdown of Wuhan. The majority of these cities were in Asia, but major hubs in Europe, the US and Australia were also prominent, with strong correlation seen between predicted importation risks and reported cases. Because significant spread has already occurred, a large number of airline travellers (3.3 million under the scenario of 75% travel reduction from normal volumes) may be required to be screened at origin high-risk cities in China and destinations across the globe for the following three months of February to April, 2020 to effectively limit spread beyond its current extent.CONCLUSION: Further spread of 2019-nCoV within China and international exportation is likely to occur. All countries, especially vulnerable regions, should be prepared for efforts to contain the 2019-nCoV infection.

This chapter provides an overview of the basic theory of early warning for infectious diseases, including definitions of surveillance, early warning and prediction; the characteristics of early warning (surveillance, information for action, timeliness, insufficiency, and the uncertainty of information); a conceptual framework of an early warning system for infectious diseases (the target setting, data collection and analysis, disseminating early warning signals, response actions, and evaluation); classifying early warning based on the data sources (case-based, event-based, laboratory-based, or syndromic surveillance). The significance of early warning for infectious diseases, the status quo and research and application trends in the field are also highlighted.

This chapter introduces the history, design, technical elements, and functional framework of China Infectious Diseases Automated-alert and Response System (CIDARS). The targeted diseases, early warning methods, and response steps are also described. Based on the running data of the system from 2011 to 2013, the performance of CIDARS is analyzed and evaluated, and further direction of CIDARS is also discussed.

Surface temperature variation in a broiler&rsquo, s head can be used as an indicator of its health status. Surface temperatures in the existing thermograph based animal health assessment studies were mostly obtained manually. 2185 thermal images, each of which had an individual broiler, were captured from 20 broilers. Where 15 broilers served as the experimental group, they were injected with 0.1mL of pasteurella inoculum. The rest, 5 broilers, served as the control group. An algorithm was developed to extract head surface temperature automatically from the top-view broiler thermal image. Adaptive K-means clustering and ellipse fitting were applied to locate the broiler&rsquo, s head region. The maximum temperature inside the head region was extracted as the head surface temperature. The developed algorithm was tested in Matlab&reg, (R2016a) and the testing results indicated that the head region in 92.77% of the broiler thermal images could be located correctly. The maximum error of the extracted head surface temperatures was not greater than 0.1 &deg, C. Different trend features were observed in the smoothed head surface temperature time series of the broilers in experimental and control groups. Head surface temperature extracted by the presented algorithm lays a foundation for the development of an automatic system for febrile broiler identification.

This chapter introduces the history, design, technical elements, and functional framework of China Infectious Diseases Automated-alert and Response System (CIDARS). The targeted diseases, early warning methods, and response steps are also described. Based on the running data of the system from 2011 to 2013, the performance of CIDARS is analyzed and evaluated, and further direction of CIDARS is also discussed.

The present studies reveal that silver nanoparticles (AgNPs) can induce apoptosis and enhance radio-sensitivity on cancer cells. In this paper, we mainly investigated the effect of AgNPs on rat glioma C6 cells upon the combination treatment of hyperthermia treatment (HTT). AgNPs were synthesized by a polyol process and the mean size was 15 nm. The particles showed dose-dependent cytotoxicity on C6 cells from the experimental data. Besides, we found that heating cells could enhance the contents of cell uptake of AgNPs. From the survival curves, AgNPs showed the ability to enhance thermo-sensitivity on C6 cells. Our results revealed that AgNPs could have a potential application in enhancing effect on HTT induced killing of glioma cells.

To evaluate the clinical outcomes and operative techniques of microsurgical resection of lumbar intraspinal tumors through paraspinal approach by percutaneous tubular retractor system.A retrospective study was conducted to analyze 21 patients with lumbar intraspinal tumors between November 2011 and February 2014, including Schwannoma (n = 19) and meningioma (n = 2) without lumbar instability on preoperative images. The length of tumors was 0.6-2.0 cm. Tracheal intubation anesthesia was performed prior to microsurgery using percutaneous tubular retractor system through paraspinal approach. Operative duration, blood loss volume, postoperative wound pain duration and hospital stay were analyzed. Creatine phosphokinase (CPK-MM) level was recorded at 1 day preoperatively, 1 day, 3 days and 5 days postoperatively. The scores of Japanese Orthopedic Association (JOA) and visual analog scale (VAS) were analyzed at 1 day preoperatively, 1, 3, 5 days and 6 months postoperatively to evaluate the function status of spinal cord. Computed tomography ( CT) three-dimensional reconstruction of lumbar vertebrae was performed at 1 week postoperatively. Magnetic resonance imaging ( MRI) plain scan and enhanced scan of lumbar vertebrae were conducted preoperatively, 1 week and 6 months postoperatively.Complete removal of tumors was achieved in all patients without the injuries of spinal cord or nerve root. Postoperative scores of JOA and VAS improved versus preoperative ones (P0.05). Level of CPK-MM increased 1 day postoperatively and declined to preoperative level at 5 days postoperatively. And th difference was not statistically significant (P0.05). Neither residual tumor nor tumor recurrence was detected by MRI plain and enhanced scans. No postoperative spinal instability was identified by CT three-dimensional reconstruction. And no spinal deformity occurred during a follow-up period of 6-28 months.Microsurgical resection of lumbar intraspinal tumors using percutaneous tubular retractor system through paraspinal approach minimizes the injuries of paraspinal muscles, facet joint, spinous process and ligaments. This technique offers the advantages of mini-invasiveness, shorter hospital stay, rapid recovery and preserved postoperative spinal stability.

Background: A China Infectious Disease Automated-alert and Response System (CIDARS) has been increasingly utilized nationwide for early outbreak detection and rapid response for infectious diseases...

Performance evaluation of CIDARS on dengue fever outbreak detection, China Honglong Zhanga#, Zhongjie Lia#, Shengjie Laia, Archie Clementsb, Wenbiao Hub*, Weizhong Yanga* a Key Laboratory of Survei...

* Dan Zhao, Zhongjie Li and Yonghui Zhang contributed equally * Correspondence: Weizhong Yang: ywz126@vip.sina.com; Wenbiao Hu: w.hu@sph.uq.edu.au Background Dengue fever (DF) has been recognised a...

Objective: Intraoperative monitoring requires timely diagnosis of the reduction of cerebral blood flow and remnant of the aneurysm to prevent postoperative neurological deficits by impelling intraoperative decision making. The objective of this study is to evaluate the efficacy of the combined application[for full text, please go to the a.m. URL], 64. Jahrestagung der Deutschen Gesellschaft für Neurochirurgie (DGNC)

Background Streptococcus suis serotype 2 ( S. suis 2, SS2) is a major zoonotic pathogen that causes only sporadic cases of meningitis and sepsis in humans. Most if not all cases of Streptococcal toxic shock syndrome (STSS) that have been well-documented to date were associated with the non-SS2 group A streptococcus (GAS). However, a recent large-scale outbreak of SS2 in Sichuan Province, China, appeared to be caused by more invasive deep-tissue infection with STSS, characterized by acute high fever, vascular collapse, hypotension, shock, and multiple organ failure. Methods and Findings We investigated this outbreak of SS2 infections in both human and pigs, which took place from July to August, 2005, through clinical observation and laboratory experiments. Clinical and pathological characterization of the human patients revealed the hallmarks of typical STSS, which to date had only been associated with GAS infection. Retrospectively, we found that this outbreak was very similar to an earlier outbreak in Jiangsu Province, China, in 1998. We isolated and analyzed 37 bacterial strains from human specimens and eight from pig specimens of the recent outbreak, as well as three human isolates and two pig isolates from the 1998 outbreak we had kept in our laboratory. The bacterial isolates were examined using light microscopy observation, pig infection experiments, multiplex-PCR assay, as well as restriction fragment length polymorphisms (RFLP) and multiple sequence alignment analyses. Multiple lines of evidence confirmed that highly virulent strains of SS2 were the causative agents of both outbreaks. Conclusions We report, to our knowledge for the first time, two outbreaks of STSS caused by SS2, a non-GAS streptococcus. The 2005 outbreak was associated with 38 deaths out of 204 documented human cases; the 1998 outbreak with 14 deaths out of 25 reported human cases. Most of the fatal cases were characterized by STSS; some of them by meningitis or severe septicemia. The molecular mechanisms underlying these human STSS outbreaks in human beings remain unclear and an objective for further study., Clinical description of a 2005 S. suis outbreak in China that affected over 200 individuals and initial characterization of the pathogenic isolates from affected pigs and humans.

Input method (IM) is a sine qua non for text entry of many Asian languages, but its potential applications on other languages remain under-explored. This paper proposes a philosophy of input method design by seeing it as a nonintrusive plug-in text service framework. Such design allows new functionalities of text processing to be attached onto a running application without any tweaking of code. We also introduce OpenVanilla, a cross-platform framework that is designed with the above-mentioned model in mind. Frameworks like OpenVanilla have shown that an input method can be more than just a text entry tool: it offers a convenient way for developing various text service and language tools., Comment: 4 pages

The authors consider the main components of the error of measurement of the radio-brightness temperature of the Earth, including the background radiation of the Sun, and give an example of calculation for different reception frequencies.