Classification and sensitivity analysis of the transmission dynamic of hepatitis B

Background

Hepatitis B infection caused by the hepatitis B virus is one of the most serious viral infections and a global health problem. In the transmission of hepatitis B infection, three different phases, i.e. acute infected, chronically infected, and carrier individuals, play important roles. Carrier individuals are especially significant, because they do not exhibit any symptoms and are able to transmit the infection. Here we assessed the transmissibility associated with different infection stages of hepatitis B and generated an epidemic model.

Methods

To demonstrate the transmission dynamic of hepatitis B, we investigate an epidemic model by dividing the infectious class into three subclasses, namely acute infected, chronically infected, and carrier individuals with both horizontal and vertical transmission.

Results

Numerical results and sensitivity analysis of some important parameters are presented to show that the proportion of births without successful vaccination, perinatally infected individuals, and direct contact rate are highest risk factors for the spread of hepatitis B in the community.

Conclusion

Our work provides a coherent platform for studying the full dynamics of hepatitis B and an effective direction for theoretical work.

     

SOD1 protein aggregates stimulate macropinocytosis in neurons to facilitate their propagation

Background

Amyotrophic Lateral Sclerosis is characterized by a focal onset of symptoms followed by a progressive spread of pathology that has been likened to transmission of infectious prions. Cell-to-cell transmission of SOD1 protein aggregates is dependent on fluid-phase endocytosis pathways, although the precise molecular mechanisms remain to be elucidated.

Results

We demonstrate in this paper that SOD1 aggregates interact with the cell surface triggering activation of Rac1 and subsequent membrane ruffling permitting aggregate uptake via stimulated macropinocytosis. In addition, other protein aggregates, including those associated with neurodegenerative diseases (TDP-43, Htt_ex146Q, α-synuclein) also trigger membrane ruffling to gain entry into the cell. Aggregates are able to rupture unstructured macropinosomes to enter the cytosol allowing propagation of aggregation to proceed.

Conclusion

Thus, we conclude that in addition to basic proteostasis mechanisms, pathways involved in the activation of macropinocytosis are key determinants in the spread of pathology in these misfolding diseases.

     

Genetic mutations in influenza H3N2 viruses from a 2012 epidemic in Southern China

Background

An influenza H3N2 epidemic occurred throughout Southern China in 2012.

Methods

We analyzed the hemagglutinin (HA) and neuraminidase (NA) genes of influenza H3N2 strains isolated between 2011–2012 from Guangdong. Mutation sites, evolutionary selection, antigenic sites, and N-glycosylation within these strains were analyzed.

Results

The 2011–2012 Guangdong strains contained the HA-A214S, HA-V239I, HA-N328S, NA-L81P, and NA-D93G mutations, similar to those seen in the A/ Perth/16/2009 influenza strain. The HA-NSS_061–063 and NNS_160–162 glycosylation sites were prevalent among the 2011–2012 Guangdong strains but the NA-NRS_402–404 site was deleted. Antigenically, there was a four-fold difference between A/Perth/16/2009 -like strains and the 2011–2012 Guangdong strains.

Conclusion

Antigenic drift of the H3N2 subtype contributed to the occurrence of the Southern China influenza epidemic of 2012.

     

Psychosomatic complaints and sense of coherence among adolescents in a county in Sweden: a cross-sectional school survey

Background

Over the last five to ten years there has been an increase in psychosomatic complaints (PSC) in Swedish children. The objective of the study was to examine the relation between PSC and sense of coherence (SOC).

Methods

A cross-sectional school survey in the county of Västmanland, Sweden. All 16- and 19-year old adolescents present at school on the day of the survey were asked to complete a questionnaire in their classrooms during a one-lesson hour session under the supervision of their teachers. Totally 3,998 students in both private and public schools, studying in ninth grade elementary school or third grade secondary school participated.

Results

The results from our study show that there is a statistically significant relation between PSC and SOC among adolescents. It also shows that adolescents with a weak SOC score have more symptoms of PSC.

Conclusion

Our study indicates that SOC can help the adolescents to choose a coping strategy that is appropriate for the situation and thereby may prevent them from developing PSC. However, additional studies are needed to confirm our findings.

     

Medical students and physical education students as CPR instructors: an appropriate solution to the CPR-instructor shortage in secondary schools?

Background

Integrating cardiopulmonary resuscitation (CPR) training in secondary schools will increase the number of potential CPR providers. However, currently too few certified instructors are available for this purpose. Training medical students and physical education student teachers to become CPR instructors could decrease this shortage.

Aim

Examine whether medical students and physical education student teachers can provide CPR training for secondary school pupils as well as (i.?e., non-inferior to) registered nurses.

Methods

A total of 144 secondary school pupils were randomly assigned to CPR training by a registered nurse (n = 12), a  medical student (n = 17) or a physical education student teacher (n = 15). CPR performance was assessed after training and after eight weeks in a simulated cardiac arrest scenario on a resuscitation manikin, using manikin software and video recordings.

Results

No significant differences were found between the groups on the overall Cardiff Test scores and the correctness of the CPR techniques during the post-training and retention test. All pupils showed sufficient CPR competence, even after eight weeks.

Conclusion

Training by medical students or physical education student teachers is non-inferior to training by a registered nurse, suggesting that school teachers, student teachers and medical students can be recruited for CPR training in secondary schools.

     

An outbreak vector-host epidemic model with spatial structure: the 2015–2016 Zika outbreak in Rio De Janeiro

Background

A deterministic model is developed for the spatial spread of an epidemic disease in a geographical setting. The disease is borne by vectors tosusceptible hosts through criss-cross dynamics. The model is focused on an outbreak that arises from a small number of infected hosts imported into a subregion of the geographical setting. The goal is to understand how spatial heterogeneity of the vector and host populations influences the dynamics of the outbreak, in both the geographical spread and the final size of the epidemic.

Methods

Partial differential equations are formulated to describe the spatial interaction of the hosts and vectors. The partial differential equations have reaction-diffusion terms to describe the criss-cross interactions of hosts and vectors. The partial differential equations of the model are analyzed and proven to be well-posed. A local basic reproduction number for the epidemic is analyzed.

Results

The epidemic outcomes of the model are correlated to the spatially dependent parameters and initial conditions of the model. The partial differential equations of the model are adapted to seasonality of the vector population, and applied to the 2015–2016 Zika seasonal outbreak in Rio de Janeiro Municipality in Brazil.

Conclusions

The results for the model simulations of the 2015–2016 Zika seasonal outbreak in Rio de Janeiro Municipality indicate that the spatial distribution and final size of the epidemic at the end of the season are strongly dependent on the location and magnitude of local outbreaks at the beginning of the season. The application of the model to the Rio de Janeiro Municipality Zika 2015–2016 outbreak is limited by incompleteness of the epidemic data and by uncertainties in the parametric assumptions of the model.

     

Epidemic cycling in a multi-strain SIRS epidemic network model

Background

One common observation in infectious diseases caused by multi-strain pathogens is that both the incidence of all infections and the relative fraction of infection with each strain oscillate with time (i.e., so-called Epidemic cycling). Many different mechanisms have been proposed for the pervasive nature of epidemic cycling. Nevertheless, the two facts that people contact each other through a network rather than following a simple mass-action law and most infectious diseases involve multiple strains have not been considered together for their influence on the epidemic cycling.

Methods

To demonstrate how the structural contacts among people influences the dynamical patterns of multi-strain pathogens, we investigate a two strain epidemic model in a network where every individual randomly contacts with a fixed number of other individuals. The standard pair approximation is applied to describe the changing numbers of individuals in different infection states and contact pairs.

Results

We show that spatial correlation due to contact network and interactions between strains through both ecological interference and immune response interact to generate epidemic cycling. Compared to one strain epidemic model, the two strain model presented here can generate epidemic cycling within a much wider parameter range that covers many infectious diseases.

Conclusion

Our results suggest that co-circulation of multiple strains within a contact network provides an explanation for epidemic cycling.

     

Transmission dynamics of cholera in Yemen, 2017: a real time forecasting

Background

A large epidemic of cholera, caused by Vibrio cholerae, serotype Ogawa, has been ongoing in Yemen, 2017. To improve the situation awareness, the present study aimed to forecast the cholera epidemic, explicitly addressing the reporting delay and ascertainment bias.

Methods

Using weekly incidence of suspected cases, updated as a revised epidemic curve every week, the reporting delay was explicitly incorporated into the estimation model. Using the weekly case fatality risk as calculated by the World Health Organization, ascertainment bias was adjusted, enabling us to parameterize the family of logistic curves (i.e., logistic and generalized logistic models) for describing the unbiased incidence in 2017.

Results

The cumulative incidence at the end of the epidemic, was estimated at 790,778 (95% CI: 700,495, 914,442) cases and 767,029 (95% CI: 690,877, 871,671) cases, respectively, by using logistic and generalized logistic models. It was also estimated that we have just passed through the epidemic peak by week 26, 2017. From week 27 onwards, the weekly incidence was predicted to decrease.

Conclusions

Cholera epidemic in Yemen, 2017 was predicted to soon start to decrease. If the weekly incidence is reported in the up-to-the-minute manner and updated in later weeks, not a single data point but the entire epidemic curve must be precisely updated.

     

NMRProcFlow: a graphical and interactive tool dedicated to 1D spectra processing for NMR-based metabolomics

Introduction

Concerning NMR-based metabolomics, 1D spectra processing often requires an expert eye for disentangling the intertwined peaks.

Objectives

The objective of NMRProcFlow is to assist the expert in this task in the best way without requirement of programming skills.

Methods

NMRProcFlow was developed to be a graphical and interactive 1D NMR (¹H & ¹³C) spectra processing tool.

Results

NMRProcFlow (http://nmrprocflow.org), dedicated to metabolic fingerprinting and targeted metabolomics, covers all spectra processing steps including baseline correction, chemical shift calibration and alignment.

Conclusion

Biologists and NMR spectroscopists can easily interact and develop synergies by visualizing the NMR spectra along with their corresponding experimental-factor levels, thus setting a bridge between experimental design and subsequent statistical analyses.

     

Geographic and topographic determinants of local FMD transmission applied to the 2001 UK FMD epidemic

Background

Models of Foot and Mouth Disease (FMD) transmission have assumed a homogeneous landscape across which Euclidean distance is a suitable measure of the spatial dependency of transmission. This paper investigated features of the landscape and their impact on transmission during the period of predominantly local spread which followed the implementation of the national movement ban during the 2001 UK FMD epidemic. In this study 113 farms diagnosed with FMD which had a known source of infection within 3 km (cases) were matched to 188 control farms which were either uninfected or infected at a later timepoint. Cases were matched to controls by Euclidean distance to the source of infection and farm size. Intervening geographical features and connectivity between the source of infection and case and controls were compared.

Results

Road distance between holdings, access to holdings, presence of forest, elevation change between holdings and the presence of intervening roads had no impact on the risk of local FMD transmission (p > 0.2). However the presence of linear features in the form of rivers and railways acted as barriers to FMD transmission (odds ratio = 0.507, 95% CIs = 0.297,0.887, p = 0.018).

Conclusion

This paper demonstrated that although FMD spread can generally be modelled using Euclidean distance and numbers of animals on susceptible holdings, the presence of rivers and railways has an additional protective effect reducing the probability of transmission between holdings.

     

Effects of pathogen dependency in a multi-pathogen infectious disease system including population level heterogeneity – a simulation study

Background

Increased computational resources have made individual based models popular for modelling epidemics. They have the advantage of incorporating heterogeneous features, including realistic population structures (like e.g. households). Existing stochastic simulation studies of epidemics, however, have been developed mainly for incorporating single pathogen scenarios although the effect of different pathogens might directly or indirectly (e.g. via contact reductions) effect the spread of each pathogen. The goal of this work was to simulate a stochastic agent based system incorporating the effect of multiple pathogens, accounting for the household based transmission process and the dependency among pathogens.

Methods

With the help of simulations from such a system, we observed the behaviour of the epidemics in different scenarios. The scenarios included different household size distributions, dependency versus independency of pathogens, and also the degree of dependency expressed through household isolation during symptomatic phase of individuals. Generalized additive models were used to model the association between the epidemiological parameters of interest on the variation in the parameter values from the simulation data. All the simulations and statistical analyses were performed using R 3.4.0.

Results

We demonstrated the importance of considering pathogen dependency using two pathogens, and showing the difference when considered independent versus dependent. Additionally for the general scenario with more pathogens, the assumption of dependency among pathogens and the household size distribution in the population cohort was found to be effective in containing the epidemic process. Additionally, populations with larger household sizes reached the epidemic peak faster than societies with smaller household sizes but dependencies among pathogens did not affect this outcome significantly. Larger households had more infections in all population cohort examples considered in our simulations. Increase in household isolation coefficient for pathogen dependency also could control the epidemic process.

Conclusion

Presence of multiple pathogens and their interaction can impact the behaviour of an epidemic across cohorts with different household size distributions. Future household cohort studies identifying multiple pathogens will provide useful data to verify the interaction processes in such an infectious disease system.

     

A metabolomics approach to uncover effects of different exercise modalities in type 1 diabetes

Introduction

Exercise-associated metabolism in type 1 diabetes (T1D) remains under-studied due to the complex interplay between exogenous insulin, counter-regulatory hormones and insulin-sensitivity.

Objective

To identify the metabolic differences induced by two exercise modalities in T1D using ultra high-performance liquid chromatography coupled to high-resolution mass spectrometry (UHPLC–HRMS) based metabolomics.

Methods

Twelve T1D adults performed intermittent high-intensity (IHE) and continuous-moderate-intensity (CONT) exercise. Serum samples were analysed by UHPLC–HRMS.

Results

Metabolic profiling of IHE and CONT highlighted exercise-induced changes in purine and acylcarnitine metabolism.

Conclusion

IHE may increase beta-oxidation through higher ATP-turnover. UHPLC–HRMS based metabolomics as a data-driven approach without an a priori hypothesis may help uncover distinctive metabolic effects during exercise in T1D.Clinical trial registration number is www.clinicaltrials.gov: NCT02068638.

     

Optimization of fecal sample preparation for untargeted LC-HRMS based metabolomics

Introduction

Collecting feces is easy. It offers direct outcome to endogenous and microbial metabolites.

Objectives

In a context of lack of consensus about fecal sample preparation, especially in animal species, we developed a robust protocol allowing untargeted LC-HRMS fingerprinting.

Methods

The conditions of extraction (quantity, preparation, solvents, dilutions) were investigated in bovine feces.

Results

A rapid and simple protocol involving feces extraction with methanol (1/3, M/V) followed by centrifugation and a step filtration (10 kDa) was developed.

Conclusion

The workflow generated repeatable and informative fingerprints for robust metabolome characterization.

     

A lost opportunity for science: journals promote data sharing in metabolomics but do not enforce it

Introduction

Data sharing is being increasingly required by journals and has been heralded as a solution to the ‘replication crisis’.

Objectives

(i) Review data sharing policies of journals publishing the most metabolomics papers associated with open data and (ii) compare these journals’ policies to those that publish the most metabolomics papers.

Methods

A PubMed search was used to identify metabolomics papers. Metabolomics data repositories were manually searched for linked publications.

Results

Journals that support data sharing are not necessarily those with the most papers associated to open metabolomics data.

Conclusion

Further efforts are required to improve data sharing in metabolomics.

     

rDolphin: a GUI R package for proficient automatic profiling of 1D <Superscript>1</Superscript>H-NMR spectra of study datasets

Introduction

Adoption of automatic profiling tools for ¹H-NMR-based metabolomic studies still lags behind other approaches in the absence of the flexibility and interactivity necessary to adapt to the properties of study data sets of complex matrices.

Objectives

To provide an open source tool that fully integrates these needs and enables the reproducibility of the profiling process.

Methods

rDolphin incorporates novel techniques to optimize exploratory analysis, metabolite identification, and validation of profiling output quality.

Results

The information and quality achieved in two public datasets of complex matrices are maximized.

Conclusion

rDolphin is an open-source R package (http://github.com/danielcanueto/rDolphin) able to provide the best balance between accuracy, reproducibility and ease of use.

     

A mathematical model for Zika virus transmission dynamics with a time-dependent mosquito biting rate

Background

Mathematical modeling has become a tool used to address many emerging diseases. One of the most basic and popular modeling frameworks is the compartmental model. Unfortunately, most of the available compartmental models developed for Zika virus (ZIKV) transmission were designed to describe and reconstruct only past, short-time ZIKV outbreaks in which the effects of seasonal change to entomological parameters can be ignored. To make an accurate long-term prediction of ZIKV transmission, the inclusion of seasonal effects into an epidemic model is unavoidable.

Methods

We developed a vector-borne compartmental model to analyze the spread of the ZIKV during the 2015–2016 outbreaks in Bahia, Brazil and to investigate the impact of two vector control strategies, namely, reducing mosquito biting rates and reducing mosquito population size. The model considered the influences of seasonal change on the ZIKV transmission dynamics via the time-varying mosquito biting rate. The model was also validated by comparing the model prediction with reported data that were not used to calibrate the model.

Results

We found that the model can give a very good fit between the simulation results and the reported Zika cases in Bahia (R-square?=?0.9989). At the end of 2016, the total number of ZIKV infected people was predicted to be 1.2087 million. The model also predicted that there would not be a large outbreak from May 2016 to December 2016 due to the decrease of the susceptible pool. Implementing disease mitigation by reducing the mosquito biting rates was found to be more effective than reducing the mosquito population size. Finally, the correlation between the time series of estimated mosquito biting rates and the average temperature was also suggested.

Conclusions

The proposed ZIKV transmission model together with the estimated weekly biting rates can reconstruct the past long-time multi-peak ZIKV outbreaks in Bahia.

     

<Emphasis Type="Italic">Candida auris</Emphasis>: Antifungal Multi-Resistant Emerging Yeast

Purpose of Review

The purpose of this review is to contribute to the knowledge about the existence of Candida auris as an emerging pathogenic fungus, multi-resistant to antifungal, and causing health care-associated infections (HCAI).

Recent Findings

C. auris emerges as yeast with clonal transmission resistance to three families of commonly used antifungals, mainly azoles (fluconazole and voriconazole), diminishing therapeutic options for the treatment of fungal infections. In 2009, C. auris was isolated for the first time in Japan and by the time of this review, it has been reported in different countries in Africa, America, Asia, and Europe.

Summary

It is important to identify yeasts of the Candida genus up to species, to perform susceptibility tests and to implement surveillance, prevention, and control measures, to minimize the global spread of this fungus, due to its impact on public health.

     

Association between HMGB1 and asthma: a literature review

Background

Recently, some studies demonstrated that HMGB1, as proinflammatory mediator belonging to the alarmin family, has a key role in different acute and chronic immune disorders. Asthma is a complex disease characterised by recurrent and reversible airflow obstruction associated to airway hyper-responsiveness and airway inflammation.

Objective

This literature review aims to analyse advances on HMGB1 role, employment and potential diagnostic application in asthma.

Methods

We reviewed experimental studies that investigated the pathogenetic role of HMGB in bronchial airway hyper-responsiveness, inflammation and the correlation between HMGB1 level and asthma.

Results

A total of 19 studies assessing the association between HMGB1 and asthma were identified.

Conclusions

What emerged from this literature review was the confirmation of HMGB-1 involvement in diseases characterised by chronic inflammation, especially in pulmonary pathologies. Findings reported suggest a potential role of the alarmin in being a stadiation method and a marker of therapeutic efficacy; finally, inhibiting HMGB1 in humans in order to contrast inflammation should be the aim for future further studies.

     

Modeling the elevated risk of yellow fever among travelers visiting Brazil, 2018

Background

Unlike the epidemic of yellow fever from 2016 to 17 in Brazil mostly restricted to the States of Minas Gerais and Espirito Santo, the epidemic from 2017 to 18 mainly involved São Paulo and Rio de Janeiro and resulted in multiple international disseminations. To understand mechanisms behind this observation, the present study analyzed the distribution of imported cases from Brazil, 2018.

Methods

A statistical model was employed to capture the risk of importing yellow fever by returning international travelers from Brazil. We estimated the relative risk of importation among travelers by the extent of wealth measured by GDP per capita and the relative risk obtained by random assignment of travelers’ destination within Brazil by the relative population size.

Results

Upper-half wealthier countries had 2.1 to 3.4 times greater risk of importation than remainders. Even among countries with lower half of GDP per capita, the risk of importation was 2.5 to 2.8 times greater than assuming that the risk of travelers’ infection within Brazil is determined by the regional population size.

Conclusions

Travelers from wealthier countries were at elevated risk of yellow fever, allowing us to speculate that travelers’ local destination and behavior at high risk of infection are likely to act as a key determinant of the heterogeneous risk of importation. It is advised to inform travelers over the ongoing geographic foci of transmission, and if it appears unavoidable to visit tourist destination that has the history of producing imported cases, travelers must be strongly advised to receive vaccination in advance.

     

A methodology for elucidating regulatory mechanisms leading to changes in lipid profiles

Introduction

It is difficult to elucidate the metabolic and regulatory factors causing lipidome perturbations.

Objectives

This work simplifies this process.

Methods

A method has been developed to query an online holistic lipid metabolic network (of 7923 metabolites) to extract the pathways that connect the input list of lipids.

Results

The output enables pathway visualisation and the querying of other databases to identify potential regulators. When used to a study a plasma lipidome dataset of polycystic ovary syndrome, 14 enzymes were identified, of which 3 are linked to ELAVL1—an mRNA stabiliser.

Conclusion

This method provides a simplified approach to identifying potential regulators causing lipid-profile perturbations.