The Traditional Japanese Medicine Rikkunshito Promotes Gastric Emptying via the Antagonistic Action of the 5-HT3 Receptor Pathway in Rats

The traditional Japanese medicine rikkunshito ameliorates the nitric oxide-associated delay in gastric emptying. Whether rikkunshito affects gastric motility associated with 5-hydroxytryptamine (serotonin: 5-HT) receptors or dopamine receptors is unknown. We examined the effects of rikkunshito on the delay in gastric emptying induced by 5-HT or dopamine using the phenol red method in male Wistar rats. 5-HT (0.01–1.0 mg kg−1, i.p.) dose dependently delayed gastric emptying, similar to the effect of the 5-HT3 receptor agonist 1-(3-chlorophenyl) biguanide (0.01–1.0 mg kg−1, i.p.). Dopamine also dose dependently delayed gastric emptying. The 5-HT3 receptor antagonist ondansetron (0.04–4.0 mg kg−1) and rikkunshito (125–500 mg kg−1) significantly suppressed the delay in gastric emptying caused by 5-HT or 1-(3-chlorophenyl) biguanide. Hesperidin (the most active ingredient in rikkunshito) suppressed the 5-HT-induced delayed gastric emptying in a dose-dependent manner, the maximum effect of which was similar to that of ondansetron (0.4 mg kg−1). The improvement obtained by rikkunshito or ondansetron in delaying gastric emptying was completely blocked by pretreatment with atropine. Rikkunshito appears to improve delay in gastric emptying via the antagonistic action of the 5-HT3 receptor pathway

フィリピン都市河川における腸管系ウイルスの検出

Tohoku University押谷

Risk Factors of Household Transmission of Pandemic (H1N1) 2009 among Patients Treated with Antivirals: A Prospective Study at a Primary Clinic in Japan

Background: Household transmission of influenza can affect the daily lives of patients and their families and be a trigger for community transmission, thus it is necessary to take precautions to prevent household transmission. We aimed to determine the risks of household transmission of pandemic (H1N1) 2009 influenza virus from an index patient who visited a primary clinic and was treated with antiviral drugs. Methods: We followed up all the patients who were diagnosed with influenza A by rapid diagnostic test with a questionnaire or interview from July 2009 to April 2010. Secondary cases were defined as patients visiting the clinic or other clinics and being positive for influenza A by rapid diagnostic test within 7 days of onset of an index patient. Logistic regression analysis was used to explore the association between household transmission and the studied variables. Results: We recruited 591 index patients and 1629 household contacts. The crude secondary attack rate was 7.3 % [95% confidence interval (CI): 6.1–8.7]. Age of index patients (0–6 years old: odds ratio 2.56; 95 % CI: 1.31–4.01; 7–12 years old: 2.44, 1.31–3.72; 30–39 years old 3.88; 2.09–5.21; 40 years old or more 2.76; 1.17–4.53) and number of household members with five or more (3.09, 2.11–4.07), medication started 48 hours from the onset of fever (2.38, 1.17–3.87) were significantly associated with household transmission. Conclusions: Household transmission was associated with index patients aged #12 years old and adults 30 years wit

Health System Resource Gaps and Associated Mortality from Pandemic Influenza across Six Asian Territories

BACKGROUND: Southeast Asia has been the focus of considerable investment in pandemic influenza preparedness. Given the wide variation in socio-economic conditions, health system capacity across the region is likely to impact to varying degrees on pandemic mitigation operations. We aimed to estimate and compare the resource gaps, and potential mortalities associated with those gaps, for responding to pandemic influenza within and between six territories in Asia. METHODS AND FINDINGS: We collected health system resource data from Cambodia, Indonesia (Jakarta and Bali), Lao PDR, Taiwan, Thailand and Vietnam. We applied a mathematical transmission model to simulate a "mild-to-moderate" pandemic influenza scenario to estimate resource needs, gaps, and attributable mortalities at province level within each territory. The results show that wide variations exist in resource capacities between and within the six territories, with substantial mortalities predicted as a result of resource gaps (referred to here as "avoidable" mortalities), particularly in poorer areas. Severe nationwide shortages of mechanical ventilators were estimated to be a major cause of avoidable mortalities in all territories except Taiwan. Other resources (oseltamivir, hospital beds and human resources) are inequitably distributed within countries. Estimates of resource gaps and avoidable mortalities were highly sensitive to model parameters defining the transmissibility and clinical severity of the pandemic scenario. However, geographic patterns observed within and across territories remained similar for the range of parameter values explored. CONCLUSIONS: The findings have important implications for where (both geographically and in terms of which resource types) investment is most needed, and the potential impact of resource mobilization for mitigating the disease burden of an influenza pandemic. Effective mobilization of resources across administrative boundaries could go some way towards minimizing avoidable deaths

Field Effectiveness of Pandemic and 2009-2010 Seasonal Vaccines against 2009-2010 A(H1N1) Influenza: Estimations from Surveillance Data in France

BACKGROUND: In this study, we assess how effective pandemic and trivalent 2009-2010 seasonal vaccines were in preventing influenza-like illness (ILI) during the 2009 A(H1N1) pandemic in France. We also compare vaccine effectiveness against ILI versus laboratory-confirmed pandemic A(H1N1) influenza, and assess the possible bias caused by using non-specific endpoints and observational data. METHODOLOGY AND PRINCIPAL FINDINGS: We estimated vaccine effectiveness by using the following formula: VE  =  (PPV-PCV)/(PPV(1-PCV)) × 100%, where PPV is the proportion vaccinated in the population and PCV the proportion of vaccinated influenza cases. People were considered vaccinated three weeks after receiving a dose of vaccine. ILI and pandemic A(H1N1) laboratory-confirmed cases were obtained from two surveillance networks of general practitioners. During the epidemic, 99.7% of influenza isolates were pandemic A(H1N1). Pandemic and seasonal vaccine uptakes in the population were obtained from the National Health Insurance database and by telephonic surveys, respectively. Effectiveness estimates were adjusted by age and week. The presence of residual biases was explored by calculating vaccine effectiveness after the influenza period. The effectiveness of pandemic vaccines in preventing ILI was 52% (95% confidence interval: 30-69) during the pandemic and 33% (4-55) after. It was 86% (56-98) against confirmed influenza. The effectiveness of seasonal vaccines against ILI was 61% (56-66) during the pandemic and 19% (-10-41) after. It was 60% (41-74) against confirmed influenza. CONCLUSIONS: The effectiveness of pandemic vaccines in preventing confirmed pandemic A(H1N1) influenza on the field was high, consistently with published findings. It was significantly lower against ILI. This is unsurprising since not all ILI cases are caused by influenza. Trivalent 2009-2010 seasonal vaccines had a statistically significant effectiveness in preventing ILI and confirmed pandemic influenza, but were not better in preventing confirmed pandemic influenza than in preventing ILI. This lack of difference might be indicative of selection bias

Detection of Resistance Mutations to Antivirals Oseltamivir and Zanamivir in Avian Influenza A Viruses Isolated from Wild Birds

The neuraminidase (NA) inhibitors oseltamivir and zanamivir are the first-line of defense against potentially fatal variants of influenza A pandemic strains. However, if resistant virus strains start to arise easily or at a high frequency, a new anti-influenza strategy will be necessary. This study aimed to investigate if and to what extent NA inhibitor–resistant mutants exist in the wild population of influenza A viruses that inhabit wild birds. NA sequences of all NA subtypes available from 5490 avian, 379 swine and 122 environmental isolates were extracted from NCBI databases. In addition, a dataset containing 230 virus isolates from mallard collected at Ottenby Bird Observatory (Öland, Sweden) was analyzed. Isolated NA RNA fragments from Ottenby were transformed to cDNA by RT-PCR, which was followed by sequencing. The analysis of genotypic profiles for NAs from both data sets in regard to antiviral resistance mutations was performed using bioinformatics tools. All 6221 sequences were scanned for oseltamivir- (I117V, E119V, D198N, I222V, H274Y, R292K, N294S and I314V) and zanamivir-related mutations (V116A, R118K, E119G/A/D, Q136K, D151E, R152K, R224K, E276D, R292K and R371K). Of the sequences from the avian NCBI dataset, 132 (2.4%) carried at least one, or in two cases even two and three, NA inhibitor resistance mutations. Swine and environmental isolates from the same data set had 18 (4.75%) and one (0.82%) mutant, respectively, with at least one mutation. The Ottenby sequences carried at least one mutation in 15 cases (6.52%). Therefore, resistant strains were more frequently found in Ottenby samples than in NCBI data sets. However, it is still uncertain if these mutations are the result of natural variations in the viruses or if they are induced by the selective pressure of xenobiotics (e.g., oseltamivir, zanamivir)

Measles outbreaks in displaced populations: a review of transmission, morbidity and mortality associated factors

<p>Abstract</p> <p>Background</p> <p>Measles is a highly contagious infectious disease with a significant public health impact especially among displaced populations due to their characteristic mass population displacement, high population density in camps and low measles vaccination coverage among children. While the fatality rate in stable populations is generally around 2%, evidence shows that it is usually high among populations displaced by disasters. In recent years, refugees and internally displaced persons have been increasing. Our study aims to define the epidemiological characteristics and risk factors associated with measles outbreaks in displaced populations.</p> <p>Methods</p> <p>We reviewed literature in the PubMed database, and selected articles for our analysis that quantitatively described measles outbreaks.</p> <p>Results</p> <p>A total of nine articles describing 11 measles outbreak studies were selected. The outbreaks occurred between 1979 and 2005 in Asia and Africa, mostly during post-conflict situations. Seven of eight outbreaks were associated with poor vaccination status (vaccination coverage; 17-57%), while one was predominantly due to one-dose vaccine coverage. The age of cases ranged from 1 month to 39 years. Children aged 6 months to 5 years were the most common target group for vaccination; however, 1622 cases (51.0% of the total cases) were older than 5 years of age. Higher case-fatality rates (>5%) were reported for five outbreaks. Consistent factors associated with measles transmission, morbidity and mortality were vaccination status, living conditions, movements of refugees, nutritional status and effectiveness of control measures including vaccination campaigns, surveillance and security situations in affected zones. No fatalities were reported in two outbreaks during which a combination of active and passive surveillance was employed.</p> <p>Conclusion</p> <p>Measles patterns have varied over time among populations displaced by natural and man-made disasters. Appropriate risk assessment and surveillance strategies are essential approaches for reducing morbidity and mortality due to measles. Learning from past experiences of measles outbreaks in displaced populations is important for designing future strategies for measles control in such situations.</p

Mitigating effects of vaccination on influenza outbreaks given constraints in stockpile size and daily administration capacity

<p>Abstract</p> <p>Background</p> <p>Influenza viruses are a major cause of morbidity and mortality worldwide. Vaccination remains a powerful tool for preventing or mitigating influenza outbreaks. Yet, vaccine supplies and daily administration capacities are limited, even in developed countries. Understanding how such constraints can alter the mitigating effects of vaccination is a crucial part of influenza preparedness plans. Mathematical models provide tools for government and medical officials to assess the impact of different vaccination strategies and plan accordingly. However, many existing models of vaccination employ several questionable assumptions, including a rate of vaccination <it>proportional </it>to the population at each point in time.</p> <p>Methods</p> <p>We present a SIR-like model that explicitly takes into account vaccine supply and the <it>number </it>of vaccines administered per day and places data-informed limits on these parameters. We refer to this as the <it>non-proportional </it>model of vaccination and compare it to the proportional scheme typically found in the literature.</p> <p>Results</p> <p>The proportional and non-proportional models behave similarly for a few different vaccination scenarios. However, there are parameter regimes involving the vaccination campaign duration and daily supply limit for which the non-proportional model predicts smaller epidemics that peak later, but may last longer, than those of the proportional model. We also use the non-proportional model to predict the mitigating effects of variably timed vaccination campaigns for different levels of vaccination coverage, using specific constraints on daily administration capacity.</p> <p>Conclusions</p> <p>The non-proportional model of vaccination is a theoretical improvement that provides more accurate predictions of the mitigating effects of vaccination on influenza outbreaks than the proportional model. In addition, parameters such as vaccine supply and daily administration limit can be easily adjusted to simulate conditions in developed and developing nations with a wide variety of financial and medical resources. Finally, the model can be used by government and medical officials to create customized pandemic preparedness plans based on the supply and administration constraints of specific communities.</p