The optimal spatially-dependent control measures to effectively and economically eliminate emerging infectious diseases.

Non-pharmaceutical interventions (NPIs) are effective in mitigating infections during the early stages of an infectious disease outbreak. However, these measures incur significant economic and livelihood costs. To address this, we developed an optimal control framework aimed at identifying strategies that minimize such costs while ensuring full control of a cross-regional outbreak of emerging infectious diseases. Our approach uses a spatial SEIR model with interventions for the epidemic process, and incorporates population flow in a gravity model dependent on gross domestic product (GDP) and geographical distance. We applied this framework to identify an optimal control strategy for the COVID-19 outbreak caused by the Delta variant in Xi'an City, Shaanxi, China, between December 2021 and January 2022. The model was parameterized by fitting it to daily case data from each district of Xi'an City. Our findings indicate that an increase in the basic reproduction number, the latent period or the infectious period leads to a prolonged outbreak and a larger final size. This indicates that diseases with greater transmissibility are more challenging and costly to control, and so it is important for governments to quickly identify cases and implement control strategies. Indeed, the optimal control strategy we identified suggests that more costly control measures should be implemented as soon as they are deemed necessary. Our results demonstrate that optimal control regimes exhibit spatial, economic, and population heterogeneity. More populated and economically developed regions require a robust regular surveillance mechanism to ensure timely detection and control of imported infections. Regions with higher GDP tend to experience larger-scale epidemics and, consequently, require higher control costs. Notably, our proposed optimal strategy significantly reduced costs compared to the actual expenditures for the Xi'an outbreak.

Acceleration of plague outbreaks in the second pandemic.

Historical records reveal the temporal patterns of a sequence of plague epidemics in London, United Kingdom, from the 14th to 17th centuries. Analysis of these records shows that later epidemics spread significantly faster ("accelerated"). Between the Black Death of 1348 and the later epidemics that culminated with the Great Plague of 1665, we estimate that the epidemic growth rate increased fourfold. Currently available data do not provide enough information to infer the mode of plague transmission in any given epidemic; nevertheless, order-of-magnitude estimates of epidemic parameters suggest that the observed slow growth rates in the 14th century are inconsistent with direct (pneumonic) transmission. We discuss the potential roles of demographic and ecological factors, such as climate change or human or rat population density, in driving the observed acceleration.

Beneficial effects of endoscopic screening on gastric cancer and optimal screening interval: a population-based study.

BACKGROUND : The effectiveness of endoscopic screening on gastric cancer has not been widely investigated in China and the screening interval of repeated screening has not been determined. METHODS : In a population-based prospective study, we included 375,800 individuals, 14,670 of whom underwent endoscopic screening (2012-2018). We assessed the associations between endoscopic screening and risk of incident gastric cancer and gastric cancer-specific mortality, and examined changes in overall survival and disease-specific survival following screening. The optimal screening interval for repeated endoscopy for early detection of gastric cancer was explored. RESULTS : Ever receiving endoscopic screening significantly decreased the risk of invasive gastric cancer (age- and sex-adjusted relative risk [RR] 0.69, 95 % confidence interval [CI] 0.52-0.92) and gastric cancer-specific mortality (RR 0.33, 95 %CI 0.20-0.56), particularly for noncardia gastric cancer. Repeated screening strengthened the beneficial effect on invasive gastric cancer-specific mortality of one-time screening. Among invasive gastric cancers, screening-detected individuals had significantly better overall survival (RR 0.18, 95 %CI 0.13-0.25) and disease-specific survival (RR 0.18, 95 %CI 0.13-0.25) than unscreened individuals, particularly for those receiving repeated endoscopy. For individuals with intestinal metaplasia or low grade intraepithelial neoplasia, repeated endoscopy at an interval of < 2 years, particularly within 1 year, significantly enhanced the detection of early gastric cancer, compared with repeated screening after 2 years (P-trend = 0.02). CONCLUSION : Endoscopic screening prevented gastric cancer occurrence and death, and improved its prognosis in a population-based study. Repeated endoscopy enhanced the effectiveness. Screening interval should be based on gastric lesion severity.

Effect of the Coronary Arterial Diameter Derived From Coronary Computed Tomography Angiography on Fractional Flow Reserve.

BACKGROUND: Fractional flow reserve (FFR) is considered to be the criterion standard for the clinical diagnosis of functional myocardial ischemia. In this study, we explored the effect of the coronary arterial diameter derived from coronary computed tomography angiography on FFR. METHOD: We retrospectively reviewed the clinical information of 131 patients with moderate coronary artery stenosis. To compare the mean diameter of stenotic vessels, patients were divided into ischemic and nonischemic groups. According to the clinical statistics of the diameter of the ischemic group and the nonischemic group, we established 8 ideal models of coronary artery diameter of 4 mm (40%, 50%, 60%, and 70% stenosis) and diameter of 3 mm (40%, 50%, 60%, and 70% stenosis). Two sets of numerical simulation experiments were carried out: experiment 1 evaluated the variation rate of CT-based computation of non-invasive fractional flow reserve (FFRCT) with vessel diameters of 4 mm and 3 mm under different stenosis rates, and experiment 2 explored the variation of FFRCT with vessel diameters of 4 mm and 3 mm under different cardiac outputs. We simulated changes in the flow of narrow blood vessels by changes in cardiac output. RESULTS: According to clinical statistics, the mean ± SD diameter of stenotic vessels in the ischemic and nonischemic groups was 3.67 ± 0.77 mm and 3.31 ± 0.64 mm (P < 0.05 for difference), respectively. In experiment 1, the FFRCT of coronary with a diameter of 4 mm was 0.86, 0.80, 0.66, and 0.35, and that with a diameter of 3 mm was 0.90, 0.84, 0.71, and 0.50, respectively. In experiment 2, the FFRCT of the coronary vessel diameter of 4 mm was 0.84, 0.80, 0.76, and 0.72, respectively. The FFRCT coronary vessels with a diameter of 3 mm were 0.87, 0.84, 0.80, and 0.76, respectively. CONCLUSIONS: As the stenosis increases, compared with narrow blood vessel of small diameter, the narrow blood vessel with larger diameter is accompanied by faster flow rate changes and is more prone to ischemia.

Generating function approach to the effective degree SIR model.

The effective degree SIR model describes the dynamics of diseases with lifetime acquired immunity on a static random contact network. It is typically modeled as a system of ordinary differential equations describing the probability distribution of the infection status of neighbors of a susceptible node. Such a construct may not be used to study networks with an infinite degree distribution, such as an infinite scale-free network. We propose a new generating function approach to rewrite the effective degree SIR model as a nonlinear transport type partial differential equation. We show the existence and uniqueness of the solutions the are biologically relevant. In addition we show how this model may be reduced to the Volz model with the assumption that the infection statuses of the neighbors of an susceptible node are initially independent to each other. This paper paves the way to study the stability of the disease-free steady state and the disease threshold of the infinite dimensional effective degree SIR models.

Suppression of Helicobacter pylori infection by daily cranberry intake: A double-blind, randomized, placebo-controlled trial.

BACKGROUND AND AIM: Dietary strategies that contribute to reducing incidence of Helicobacter pylori infection without negative side effects are highly desirable owing to worldwide bacterial prevalence and carcinogenesis potential. The aim of this study was to determine dosage effect of daily cranberry consumption on H. pylori suppression over time in infected adults to assess the potential of this complementary management strategy in a region with high gastric cancer risk and high prevalence of H. pylori infection. METHODS: This double-blind, randomized, placebo-controlled trial on 522 H. pylori-positive adults evaluated dose-response effects of proanthocyanidin-standardized cranberry juice, cranberry powder, or their placebos on suppression of H. pylori at 2 and 8 weeks by 13 C-urea breath testing and eradication at 45 days post-intervention. RESULTS: H. pylori-negative rates in placebo, low-proanthocyanidin, medium-proanthocyanidin, and high-proanthocyanidin cranberry juice groups at week 2 were 13.24%, 7.58%, 1.49%, and 13.85% and at week 8 were 7.35%, 7.58%, 4.48%, and 20.00%, respectively. Consumption of high-proanthocyanidin juice twice daily (44 mg proanthocyanidin/240-mL serving) for 8 weeks resulted in decreased H. pylori infection rate by 20% as compared with other dosages and placebo (P < 0.05). Percentage of H. pylori-negative participants increased from 2 to 8 weeks in subjects who consumed 44 mg proanthocyanidin/day juice once or twice daily, showing a statistically significant positive trend over time. Encapsulated cranberry powder doses were not significantly effective at either time point. Overall trial compliance was 94.25%. Cranberry juice and powder were well-tolerated. CONCLUSIONS: Twice-daily consumption of proanthocyanidin-standardized cranberry juice may help potentiate suppression of H. pylori infection. TRIAL REGISTRATION: ChiCTR1800017522, per WHO ICTRP.

The Effect of Harvesting Adults on the Evolution of Reproduction Age Via Density-Dependent Juvenile Mortality.

In this paper, we used a generic two-stage population model to derive an adaptive dynamical system for the evolution of reproduction age and studied how this evolution is driven by the harvest of adults. We considered the tradeoffs between maturation rate and fecundity, juvenile mortality, and adult mortality. We analyzed the benefit and cost of faster maturation under each tradeoff that drives the evolution. We found that harvesting adults affects the evolution of maturation by affecting the benefit. For the tradeoff between maturation and juvenile mortality, harvesting adults does not affect the benefit and thus, does not affect optimal maturation strategy. For the other two tradeoffs, harvesting adults affects the benefit through the equilibrium adult/juvenile ratio, which is determined by the density dependence of juveniles. Harvesting adults causes a slower maturation only if it significantly reduces this ratio, which can only happen with very strong adult protection to juveniles. Otherwise, harvesting adults always causes a faster maturation.

Disease-Induced Hydra Effect with Overcompensatory Recruitment.

In ecological systems, the hydra effect is an increase in population size caused by an increase in mortality. This seemingly counterintuitive effect has been observed in several populations, including fish, blowflies, snails and plants, and has been modeled in both continuous and discrete time. A similar effect induced by disease has recently been observed empirically. Here we present theoretical and simulation results for an infectious disease-induced hydra effect, namely conditions under which the total population size, composed of those that are infectious as well as those that are susceptible, at an endemic equilibrium is greater than the population size at the disease-free equilibrium. (For an endemic k-cycle, this can be similarly defined using the average population.) We find this disease-induced hydra effect occurs when the intra-specific competition is strong and disease infection sufficiently inhibits the reproductive output of infected individuals. For our continuous time model, we give a necessary and sufficient condition for a disease-induced hydra effect. This condition requires overcompensatory recruitment. With a discrete time model, we show there is no disease-induced hydra effect without overcompensatory recruitment. We illustrate by simulations that a disease-induced hydra effect may occur with Ricker recruitment when the endemic system converges to either a fixed equilibrium or a 2-cycle.

Under-reporting of COVID-19 in the Northern Health Authority region of British Columbia.

Asymptomatic and pauci-symptomatic presentations of COVID-19 along with restrictive testing protocols result in undetected COVID-19 cases. Estimating undetected cases is crucial to understanding the true severity of the outbreak. We introduce a new hierarchical disease dynamics model based on the N-mixtures hidden population framework. The new models make use of three sets of disease count data per region: reported cases, recoveries and deaths. Treating the first two as under-counted through binomial thinning, we model the true population state at each time point by partitioning the diseased population into the active, recovered and died categories. Both domestic spread and imported cases are considered. These models are applied to estimate the level of under-reporting of COVID-19 in the Northern Health Authority region of British Columbia, Canada, during 30 weeks of the provincial recovery plan. Parameter covariates are easily implemented and used to improve model estimates. We compare two distinct methods of model-fitting for this case study: (1) maximum likelihood estimation, and (2) Bayesian Markov chain Monte Carlo. The two methods agreed exactly in their estimates of under-reporting rate. When accounting for changes in weekly testing volumes, we found under-reporting rates varying from 60.2% to 84.2%.

Le recours à des protocoles de tests restrictifs et l'existence de formes asymptomatiques et paucisymptomatiques de la COVID­19 contribuent à la non détection de cas COVID­19. Pour comprendre la véritable gravité de l'épidémie, il est primordial d'estimer correctement le nombre de cas non détectés. A cette fin, les auteurs de ce travail proposent un nouveau modèle hiérarchique des dynamiques de la maladie basé sur l'approche de N­mélanges de population cachée. Ces modèles utilisent trois types de données régionales, à savoir, les nombres de cas déclarés, guéris et décédés. En faisant appel à l'amincissement binomial (binomial thinning) et en traitant les nombres de cas déclarés et guéris comme étant sous­évalués, les auteurs proposent une modélisation de l'état réel de l'épidémie basée sur une partition de la population malade en trois catégories : cas actifs, cas guéris et cas décédés. Cette partition tient compte des cas de propagation intérieure et des cas importés. Les auteurs ont utilisé les données recueillies durant les trente semaines du plan de rétablissement provincial de la région de l'Autorité sanitaire du Nord de la Colombie­Britannique, Canada pour illustrer leur approche et estimer le niveau de sous­déclaration COVID­19 associé. Des covariables peuvent être facilement incorporées au modèle proposé et améliorer la qualité des estimations. Deux méthodes d'ajustement sont retenues: (1) l'estimation par maximum de vraisemblance, et (2) la méthode de Monte Carlo par chaînes de Markov. Les estimations du taux de sous­déclaration obtenues par ces deux méthodes concordent exactement et varient entre 60,2% et 84,2% après ajustement des variations des volumes de tests hebdomadaires.

Effect of Helicobacter pylori on gastrointestinal microbiota: a population-based study in Linqu, a high-risk area of gastric cancer.

OBJECTIVE: Gastrointestinal microbiota may be involved in Helicobacter pylori-associated gastric cancer development. The aim of this study was to explore the possible microbial mechanisms in gastric carcinogenesis and potential dysbiosis arising from H. pylori infection. DESIGN: Deep sequencing of the microbial 16S ribosomal RNA gene was used to investigate alterations in paired gastric biopsies and stool samples in 58 subjects with successful and 57 subjects with failed anti-H. pylori treatment, relative to 49 H. pylori negative subjects. RESULTS: In H. pylori positive subjects, richness and Shannon indexes increased significantly (both p<0.001) after successful eradication and showed no difference to those of negative subjects (p=0.493 for richness and p=0.420 for Shannon index). Differential taxa analysis identified 18 significantly altered gastric genera after eradication. The combination of these genera into a Microbial Dysbiosis Index revealed that the dysbiotic microbiota in H. pylori positive mucosa was associated with advanced gastric lesions (chronic atrophic gastritis and intestinal metaplasia/dysplasia) and could be reversed by eradication. Strong coexcluding interactions between Helicobacter and Fusobacterium, Neisseria, Prevotella, Veillonella, Rothia were found only in advanced gastric lesion patients, and were absent in normal/superficial gastritis group. Changes in faecal microbiota included increased Bifidobacterium after successful H. pylori eradication and more upregulated drug-resistant functional orthologs after failed treatment. CONCLUSION: H. pylori infection contributes significantly to gastric microbial dysbiosis that may be involved in carcinogenesis. Successful H. pylori eradication potentially restores gastric microbiota to a similar status as found in uninfected individuals, and shows beneficial effects on gut microbiota.

The influence of awareness on epidemic spreading on random networks.

During an outbreak, the perceived infection risk of an individual affects his/her behavior during an epidemic to lower the risk. We incorporate the awareness of infection risk into the Volz-Miller SIR epidemic model, to study the effect of awareness on disease dynamics. We consider two levels of awareness, the local one represented by the prevalence among the contacts of an individual, and the global one represented by the prevalence in the population. We also consider two possible effects of awareness: reducing infection rate or breaking infectious edges. We use the next generation matrix method to obtain the basic reproduction number of our models, and show that awareness acquired during an epidemic does not affect the basic reproduction number. However, awareness acquired from outbreaks in other regions before the start of the local epidemic reduces the basic reproduction number. Awareness always reduces the final size of an epidemic. Breaking infectious edges causes a larger reduction than reducing the infection rate. If awareness reduces the infection rate, the reduction increases with both local and global awareness. However, if it breaks infectious edges, the reduction may not be monotonic. For the same awareness, the reduction may reach a maximum on some intermediate infection rates. Whether local or global awareness has a larger effect on reducing the final size depends on the network degree distribution and the infection rate.

Visualising electrochemical reaction layers: mediated vs. direct oxidation.

Electrochemical treatments are widely used for 'clean up' in which toxic metals and organic compounds are removed using direct or mediated electrolysis. Herein we report novel studies offering proof of concept that spectrofluorometric electrochemistry can provide important mechanistic detail into these processes. A thin layer opto-electrochemical cell, with a carbon fibre (radius 3.5 µm) working electrode, is used to visualise the optical responses of the oxidative destruction of a fluorophore either directly, on an electrode, or via the indirect reaction of the analyte with an electrochemically formed species which 'mediates' the destruction. The optical responses of these two reaction mechanisms are first predicted by numerical simulation followed by experimental validation of each using two fluorescent probes, a redox inactive (in the electrochemical window) 1,3,6,8-pyrenetetrasulfonic acid and the redox-active derivative 8-hydroxypyrene-1,3,6-trisulfonic acid. In the vicinity of a carbon electrode held at different oxidative potentials, the contrast between indirect electro-destruction, chlorination, and direct oxidation is very obvious. Excellent agreement is seen between the numerically predicted fluorescence intensity profiles and experiment.

Patterns of seasonal and pandemic influenza-associated health care and mortality in Ontario, Canada.

BACKGROUND: Mathematical and statistical models are used to project the future time course of infectious disease epidemics and the expected future burden on health care systems and economies. Influenza is a particularly important disease in this context because it causes annual epidemics and occasional pandemics. In order to forecast health care utilization during epidemics-and the effects of hospitalizations and deaths on the contact network and, in turn, on transmission dynamics-modellers must make assumptions about the lengths of time between infection, visiting a physician, being admitted to hospital, leaving hospital, and death. More reliable forecasts could be be made if the distributions of times between these types of events ("delay distributions") were known. METHODS: We estimated delay distributions in the province of Ontario, Canada, between 2006 and 2010. To do so, we used encrypted health insurance numbers to link 1.34 billion health care billing records to 4.27 million hospital inpatient stays. Because the four year period we studied included three typical influenza seasons and the 2009 influenza pandemic, we were able to compare the delay distributions in non-pandemic and pandemic settings. We also estimated conditional probabilities such as the probability of hospitalization within the year if diagnosed with influenza. RESULTS: In non-pandemic [pandemic] years, delay distribution medians (inter-quartile ranges) were: Service to Admission 6.3 days (0.1-17.6 days) [2.4 days (-0.3-13.6 days)], Admission to Discharge 3 days (1.4-5.9 days) [2.6 days (1.2-5.1 days)], Admission to Death 5.3 days (2.1-11 days) [6 days (2.6-13.1 days)]. (Service date is defined as the date, within the year, of the first health care billing that included a diagnostic code for influenza-like-illness.) Among individuals diagnosed with either pneumonia or influenza in a given year, 19% [16%] were hospitalized within the year and 3% [2%] died in hospital. Among all individuals who were hospitalized, 10% [12%] were diagnosed with pneumonia or influenza during the year and 5% [5%] died in hospital. CONCLUSION: Our empirical delay distributions and conditional probabilities should help facilitate more accurate forecasts in the future, including improved predictions of hospital bed demands during influenza outbreaks, and the expected effects of hospitalizations on epidemic dynamics.

An edge-based SIR model for sexually transmitted diseases on the contact network.

Sexually transmitted diseases, which are infections through sexual contact, pose severe public health threat nowadays. In this paper, we develop a novel model for such diseases on a bipartite random contact network. Our model is precise with arbitrary initial conditions, which makes it suitable to study preventative vaccination strategies. We derive the reproduction number and show that R0=1 is the disease threshold. An implicit formula for the final epidemic size is also derived, and we show that the formula gives a unique positive final epidemic size when the reproduction number is larger than unity. We find that the final size in either sex is heavily influenced by the degree distribution of the opposite sex.

Edge-based epidemic spreading in degree-correlated complex networks.

Networks that grow through the addition of new nodes or edges may acquire degree-degree correlations. When one considers a short epidemic on a slowly growing network, such as the spread of a strain of influenza in a population for one season, it is reasonable to assume that the degree-correlated network is static during the course of an epidemic. In this case using only information about the network degree distribution is not enough to capture the exponential growth phase, the epidemic peak or the final epidemic size. Hence, in this paper we formulate an edge-based SIR epidemic model on degree-correlated networks, which includes the Miller model on configuration networks as a special case. The model is relatively low-dimensional; in particular, considering the fact that it captures degree correlations. Moreover, we derive rate equations to compute two node degree correlations in a growing network. Predictions of our model agree well with the corresponding stochastic SIR process on degree-correlated networks, such as the exponential growth phase, the epidemic peak and the final epidemic size. The basic reproduction number R0 and the final epidemic size are theoretically derived, which are equivalent to those based on the percolation theory. However, our model has the advantage that it can trace the dynamic spread of an epidemic on degree-correlated networks. This provides us with more accurate information to predict and control the spread of diseases in growing populations with biased-mixing. Finally, our model is tested on degree-correlated networks with clustering, and it is shown that our model is robust to degree-correlated networks with small clustering.

Estimation of Cross-Immunity Between Drifted Strains of Influenza A/H3N2.

To determine the cross-immunity between influenza strains, we design a novel statistical method, which uses a theoretical model and clinical data on attack rates and vaccine efficacy among school children for two seasons after the 1968 A/H3N2 influenza pandemic. This model incorporates the distribution of susceptibility and the dependence of cross-immunity on the antigenic distance of drifted strains. We find that the cross-immunity between an influenza strain and the mutant that causes the next epidemic is 88%. Our method also gives estimates of the vaccine protection against the vaccinating strain, and the basic reproduction number of the 1968 pandemic influenza.

The effect of sexual transmission on Zika virus dynamics.

Zika virus is a human disease that may lead to neurological disorders in affected individuals, and may be transmitted vectorially (by mosquitoes) or sexually. A mathematical model of Zika virus transmission is formulated, taking into account mosquitoes, sexually active males and females, inactive individuals, and considering both vector transmission and sexual transmission from infectious males to susceptible females. Basic reproduction numbers are computed, and disease control strategies are evaluated. The effect of the incidence function used to model sexual transmission from infectious males to susceptible females is investigated. It is proved that for such functions that are sublinear, if the basic reproduction [Formula: see text], then the disease dies out and [Formula: see text] is a sharp threshold. Moreover, under certain conditions on model parameters and assuming mass action incidence for sexual transmission, it is proved that if [Formula: see text], there exists a unique endemic equilibrium that is globally asymptotically stable. However, under nonlinear incidence, it is shown that for certain functions backward bifurcation and Hopf bifurcation may occur, giving rise to subthreshold equilibria and periodic solutions, respectively. Numerical simulations for various parameter values are displayed to illustrate these behaviours.

Host contact structure is important for the recurrence of Influenza A.

An important characteristic of influenza A is its ability to escape host immunity through antigenic drift. A novel influenza A strain that causes a pandemic confers full immunity to infected individuals. Yet when the pandemic strain drifts, these individuals will have decreased immunity to drifted strains in the following seasonal epidemics. We compute the required decrease in immunity so that a recurrence is possible. Models for influenza A must make assumptions on the contact structure on which the disease spreads. By considering local stability of the disease free equilibrium via computation of the reproduction number, we show that the classical random mixing assumption predicts an unrealistically large decrease of immunity before a recurrence is possible. We improve over the classical random mixing assumption by incorporating a contact network structure. A complication of contact networks is correlations induced by the initial pandemic. We provide a novel analytic derivation of such correlations and show that contact networks may require a dramatically smaller loss of immunity before recurrence. Hence, the key new insight in our paper is that on contact networks the establishment of a new strain is possible for much higher immunity levels of previously infected individuals than predicted by the commonly used random mixing assumption. This suggests that stable contacts like classmates, coworkers and family members are a crucial path for the spread of influenza in human populations.

Two Redundant Receptor-Like Cytoplasmic Kinases Function Downstream of Pattern Recognition Receptors to Regulate Activation of SA Biosynthesis.

Salicylic acid (SA) serves as a critical signaling molecule in plant defense. Two transcription factors, SARD1 and CBP60g, control SA biosynthesis through regulating pathogen-induced expression of Isochorismate Synthase1, which encodes a key enzyme for SA biosynthesis. Here, we report that Pattern-Triggered Immunity Compromised Receptor-like Cytoplasmic Kinase1 (PCRK1) and PCRK2 function as key regulators of SA biosynthesis. In the pcrk1 pcrk2 double mutant, pathogen-induced expression of SARD1, CBP60g, and ICS1 is greatly reduced. The pcrk1 pcrk2 double mutant, but neither of the single mutants, exhibits reduced accumulation of SA and enhanced disease susceptibility to bacterial pathogens. Both PCRK1 and PCRK2 interact with the pattern recognition receptor FLS2, and treatment with pathogen-associated molecular patterns leads to rapid phosphorylation of PCRK2. Our data suggest that PCRK1 and PCRK2 function downstream of pattern recognition receptor in a signal relay leading to the activation of SA biosynthesis.

Helicobacter pylori antibody responses in association with eradication outcome and recurrence: a population-based intervention trial with 7.3-year follow-up in China.

OBJECTIVE: To identify serum biomarkers that may predict the short or long term outcomes of anti-Helicobacter pylori (H. pylori) treatment, a follow-up study was performed based on an intervention trial in Linqu County, China. METHODS: A total of 529 subjects were selected randomly from 1,803 participants to evaluate total anti-H. pylori immunoglobulin G (IgG) and 10 specific antibody levels before and after treatment at 1-, 2- and 7.3-year. The outcomes of anti-H. pylori treatment were also parallelly assessed by13C-urea breath test at 45-d after treatment and 7.3-year at the end of follow-up. RESULTS: We found the medians of anti-H. pylori IgG titers were consistently below cut-off value through 7.3 years in eradicated group, however, the medians declined in recurrence group to 1.2 at 1-year after treatment and slightly increased to 2.0 at 7.3-year. While the medians were significantly higher (>3.0 at 2- and 7.3-year) among subjects who failed the eradication or received placebo. For specific antibody responses, baseline seropositivities of FliD and HpaA were reversely associated with eradication failure [for FliD, odds ratio (OR)=0.44, 95% confidence interval (95% CI): 0.27-0.73; for HpaA, OR=0.32, 95% CI: 0.17-0.60]. The subjects with multiple positive specific antibodies at baseline were more likely to be successfully eradicated in a linear fashion (Ptrend=0.006). CONCLUSIONS: Our study suggested that total anti-H. pylori IgG level may serve as a potential monitor of long-term impact on anti-H. pylori treatment, and priority forH. pylori treatment may be endowed to the subjects with multiple seropositive antibodies at baseline, especially for FliD and HapA.