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Fulltext Homozygous deletion of six olfactory receptor genes in a subset of individuals with Beta-thalassemia

Van Ziffle J, Yang W, Chehab FF

PLoS One, 2011;6(2):e17327.
PMID: 21390308 DOI: 10.1371/journal.pone.0017327

Progress in the functional studies of human olfactory receptors has been largely hampered by the lack of a reliable experimental model system. Although transgenic approaches in mice could characterize the function of individual olfactory receptors, the presence of over 300 functional genes in the human genome becomes a daunting task. Thus, the characterization of individuals with a genetic susceptibility to altered olfaction coupled with the absence of particular olfactory receptor genes will allow phenotype/genotype correlations and vindicate the function of specific olfactory receptors with their cognate ligands. We characterized a 118 kb β-globin deletion and found that its 3' end breakpoint extends to the neighboring olfactory receptor region downstream of the β-globin gene cluster. This deletion encompasses six contiguous olfactory receptor genes (OR51V1, OR52Z1, OR51A1P, OR52A1, OR52A5, and OR52A4) all of which are expressed in the brain. Topology analysis of the encoded proteins from these olfactory receptor genes revealed that OR52Z1, OR52A1, OR52A5, and OR52A4 are predicted to be functional receptors as they display integral characteristics of G-proteins coupled receptors. Individuals homozygous for the 118 kb β-globin deletion are afflicted with β-thalassemia due to a homozygous deletion of the β-globin gene and have no alleles for the above mentioned olfactory receptors genes. This is the first example of a homozygous deletion of olfactory receptor genes in human. Although altered olfaction remains to be ascertained in these individuals, such a study can be carried out in β-thalassemia patients from Malaysia, Indonesia and the Philippines where this mutation is common. Furthermore, OR52A1 contains a γ-globin enhancer, which was previously shown to confer continuous expression of the fetal γ-globin genes. Thus, the hypothesis that β-thalassemia individuals, who are homozygous for the 118 kb deletion, may also have an exacerbation of their anemia due to the deletion of two copies of the γ-globin enhancer element is worthy of consideration.

Matched MeSH terms: Models, Biological
Fulltext In vitro and in vivo anti-inflammatory activity of 17-O-acetylacuminolide through the inhibition of cytokines, NF-κB translocation and IKKβ activity

Achoui M, Appleton D, Abdulla MA, Awang K, Mohd MA, Mustafa MR

PLoS One, 2010;5(12):e15105.
PMID: 21152019 DOI: 10.1371/journal.pone.0015105

17-O-acetylacuminolide (AA), a diterpenoid labdane, was isolated for the first time from the plant species Neouvaria foetida. The anti-inflammatory effects of this compound were studied both in vitro and in vivo.

Matched MeSH terms: Models, Biological
Fulltext Modelling the species distribution of flat-headed cats (Prionailurus planiceps), an endangered South-East Asian small felid

Wilting A, Cord A, Hearn AJ, Hesse D, Mohamed A, Traeholdt C, et al.

PLoS One, 2010;5(3):e9612.
PMID: 20305809 DOI: 10.1371/journal.pone.0009612

The flat-headed cat (Prionailurus planiceps) is one of the world's least known, highly threatened felids with a distribution restricted to tropical lowland rainforests in Peninsular Thailand/Malaysia, Borneo and Sumatra. Throughout its geographic range large-scale anthropogenic transformation processes, including the pollution of fresh-water river systems and landscape fragmentation, raise concerns regarding its conservation status. Despite an increasing number of camera-trapping field surveys for carnivores in South-East Asia during the past two decades, few of these studies recorded the flat-headed cat.

Matched MeSH terms: Models, Biological
Fulltext An evolutionary firefly algorithm for the estimation of nonlinear biological model parameters

Abdullah A, Deris S, Anwar S, Arjunan SN

PLoS One, 2013;8(3):e56310.
PMID: 23469172 DOI: 10.1371/journal.pone.0056310

The development of accurate computational models of biological processes is fundamental to computational systems biology. These models are usually represented by mathematical expressions that rely heavily on the system parameters. The measurement of these parameters is often difficult. Therefore, they are commonly estimated by fitting the predicted model to the experimental data using optimization methods. The complexity and nonlinearity of the biological processes pose a significant challenge, however, to the development of accurate and fast optimization methods. We introduce a new hybrid optimization method incorporating the Firefly Algorithm and the evolutionary operation of the Differential Evolution method. The proposed method improves solutions by neighbourhood search using evolutionary procedures. Testing our method on models for the arginine catabolism and the negative feedback loop of the p53 signalling pathway, we found that it estimated the parameters with high accuracy and within a reasonable computation time compared to well-known approaches, including Particle Swarm Optimization, Nelder-Mead, and Firefly Algorithm. We have also verified the reliability of the parameters estimated by the method using an a posteriori practical identifiability test.

Matched MeSH terms: Models, Biological*
Fulltext Projections of the current and future disease burden of hepatitis C virus infection in Malaysia

McDonald SA, Dahlui M, Mohamed R, Naning H, Shabaruddin FH, Kamarulzaman A

PLoS One, 2015;10(6):e0128091.
PMID: 26042425 DOI: 10.1371/journal.pone.0128091

BACKGROUND: The prevalence of hepatitis C virus (HCV) infection in Malaysia has been estimated at 2.5% of the adult population. Our objective, satisfying one of the directives of the WHO Framework for Global Action on Viral Hepatitis, was to forecast the HCV disease burden in Malaysia using modelling methods.
METHODS: An age-structured multi-state Markov model was developed to simulate the natural history of HCV infection. We tested three historical incidence scenarios that would give rise to the estimated prevalence in 2009, and calculated the incidence of cirrhosis, end-stage liver disease, and death, and disability-adjusted life-years (DALYs) under each scenario, to the year 2039. In the baseline scenario, current antiviral treatment levels were extended from 2014 to the end of the simulation period. To estimate the disease burden averted under current sustained virological response rates and treatment levels, the baseline scenario was compared to a counterfactual scenario in which no past or future treatment is assumed.
RESULTS: In the baseline scenario, the projected disease burden for the year 2039 is 94,900 DALYs/year (95% credible interval (CrI): 77,100 to 124,500), with 2,002 (95% CrI: 1340 to 3040) and 540 (95% CrI: 251 to 1,030) individuals predicted to develop decompensated cirrhosis and hepatocellular carcinoma, respectively, in that year. Although current treatment practice is estimated to avert a cumulative total of 2,200 deaths from DC or HCC, a cumulative total of 63,900 HCV-related deaths is projected by 2039.
CONCLUSIONS: The HCV-related disease burden is already high and is forecast to rise steeply over the coming decades under current levels of antiviral treatment. Increased governmental resources to improve HCV screening and treatment rates and to reduce transmission are essential to address the high projected HCV disease burden in Malaysia.

Matched MeSH terms: Models, Biological
Fulltext A newton cooperative genetic algorithm method for in silico optimization of metabolic pathway production

Ismail MA, Deris S, Mohamad MS, Abdullah A

PLoS One, 2015;10(5):e0126199.
PMID: 25961295 DOI: 10.1371/journal.pone.0126199

This paper presents an in silico optimization method of metabolic pathway production. The metabolic pathway can be represented by a mathematical model known as the generalized mass action model, which leads to a complex nonlinear equations system. The optimization process becomes difficult when steady state and the constraints of the components in the metabolic pathway are involved. To deal with this situation, this paper presents an in silico optimization method, namely the Newton Cooperative Genetic Algorithm (NCGA). The NCGA used Newton method in dealing with the metabolic pathway, and then integrated genetic algorithm and cooperative co-evolutionary algorithm. The proposed method was experimentally applied on the benchmark metabolic pathways, and the results showed that the NCGA achieved better results compared to the existing methods.

Matched MeSH terms: Models, Biological*
Fulltext Using bioconductor package BiGGR for metabolic flux estimation based on gene expression changes in brain

Gavai AK, Supandi F, Hettling H, Murrell P, Leunissen JA, van Beek JH

PLoS One, 2015;10(3):e0119016.
PMID: 25806817 DOI: 10.1371/journal.pone.0119016

Predicting the distribution of metabolic fluxes in biochemical networks is of major interest in systems biology. Several databases provide metabolic reconstructions for different organisms. Software to analyze flux distributions exists, among others for the proprietary MATLAB environment. Given the large user community for the R computing environment, a simple implementation of flux analysis in R appears desirable and will facilitate easy interaction with computational tools to handle gene expression data. We extended the R software package BiGGR, an implementation of metabolic flux analysis in R. BiGGR makes use of public metabolic reconstruction databases, and contains the BiGG database and the reconstruction of human metabolism Recon2 as Systems Biology Markup Language (SBML) objects. Models can be assembled by querying the databases for pathways, genes or reactions of interest. Fluxes can then be estimated by maximization or minimization of an objective function using linear inverse modeling algorithms. Furthermore, BiGGR provides functionality to quantify the uncertainty in flux estimates by sampling the constrained multidimensional flux space. As a result, ensembles of possible flux configurations are constructed that agree with measured data within precision limits. BiGGR also features automatic visualization of selected parts of metabolic networks using hypergraphs, with hyperedge widths proportional to estimated flux values. BiGGR supports import and export of models encoded in SBML and is therefore interoperable with different modeling and analysis tools. As an application example, we calculated the flux distribution in healthy human brain using a model of central carbon metabolism. We introduce a new algorithm termed Least-squares with equalities and inequalities Flux Balance Analysis (Lsei-FBA) to predict flux changes from gene expression changes, for instance during disease. Our estimates of brain metabolic flux pattern with Lsei-FBA for Alzheimer's disease agree with independent measurements of cerebral metabolism in patients. This second version of BiGGR is available from Bioconductor.

Matched MeSH terms: Models, Biological*
Fulltext Hybrid flower pollination algorithm strategies for t-way test suite generation

Nasser AB, Zamli KZ, Alsewari AA, Ahmed BS

PLoS One, 2018;13(5):e0195187.
PMID: 29718918 DOI: 10.1371/journal.pone.0195187

The application of meta-heuristic algorithms for t-way testing has recently become prevalent. Consequently, many useful meta-heuristic algorithms have been developed on the basis of the implementation of t-way strategies (where t indicates the interaction strength). Mixed results have been reported in the literature to highlight the fact that no single strategy appears to be superior compared with other configurations. The hybridization of two or more algorithms can enhance the overall search capabilities, that is, by compensating the limitation of one algorithm with the strength of others. Thus, hybrid variants of the flower pollination algorithm (FPA) are proposed in the current work. Four hybrid variants of FPA are considered by combining FPA with other algorithmic components. The experimental results demonstrate that FPA hybrids overcome the problems of slow convergence in the original FPA and offers statistically superior performance compared with existing t-way strategies in terms of test suite size.

Matched MeSH terms: Models, Biological*
Fulltext Exoskeleton robot control for synchronous walking assistance in repetitive manual handling works based on dual unscented Kalman filter

Sado F, Yap HJ, Ghazilla RAR, Ahmad N

PLoS One, 2018;13(7):e0200193.
PMID: 30001415 DOI: 10.1371/journal.pone.0200193

Prolong walking is a notable risk factor for work-related lower-limb disorders (WRLLD) in industries such as agriculture, construction, service profession, healthcare and retail works. It is one of the common causes of lower limb fatigue or muscular exhaustion leading to poor balance and fall. Exoskeleton technology is seen as a modern strategy to assist worker's in these professions to minimize or eliminate the risk of WRLLDs. Exoskeleton has potentials to benefit workers in prolong walking (amongst others) by augmenting their strength, increasing their endurance, and minimizing high muscular activation, resulting in overall work efficiency and productivity. Controlling exoskeleton to achieve this purpose for able-bodied personnel without impeding their natural movement is, however, challenging. In this study, we propose a control strategy that integrates a Dual Unscented Kalman Filter (DUKF) for trajectory generation/prediction of the spatio-temporal features of human walking (i.e. joint position, and velocity, and acceleration) and an impedance cum supervisory controller to enable the exoskeleton to follow this trajectory to synchronize with the human walking. Experiment is conducted with four subjects carrying a load and walking at their normal speed- a typical scenario in industries. EMG signals taken at two muscles: Right Vastus Intermedius (on the thigh) and Right Gastrocnemius (on the calf) indicated reduction in muscular activation during the experiment. The results also show the ability of the control system to predict spatio-temporal features of the pilots' walking and to enable the exoskeleton to move in concert with the pilot.

Matched MeSH terms: Models, Biological
Fulltext A short comparative study on modified Duckworth-Lewis methods

Asif M, Ahmadian A, Azeem M, Pansera BA

PLoS One, 2021;16(11):e0259423.
PMID: 34748588 DOI: 10.1371/journal.pone.0259423

In this paper, the Duckworth-Lewis-Stern (DLS) and Duckworth-Lewis-McHale-Asif (DLMA) methods of revising targets for a team batting in second innings in an interrupted Limited Overs International Cricket (LOI), are examined for fairness. The work discusses four significant points: flexibility, intuition, simplicity, and goodness-of-fit of the two mentioned methods. The research findings have shown that the DLMA method is better in every aspect than the DLS method. Further, the data of 1764 ODI matches played during 2004-2021 to investigate the compatibility of the DLMA for high run-scoring One-Day International matches. The results show that DLMA is compatible to the situation of the well-above run-scoring situation.

Matched MeSH terms: Models, Biological
Fulltext CFD study on NACA 4415 airfoil implementing spherical and sinusoidal Tubercle Leading Edge

Aftab SMA, Ahmad KA

PLoS One, 2017;12(8):e0183456.
PMID: 28850622 DOI: 10.1371/journal.pone.0183456

The Humpback whale tubercles have been studied for more than a decade. Tubercle Leading Edge (TLE) effectively reduces the separation bubble size and helps in delaying stall. They are very effective in case of low Reynolds number flows. The current Computational Fluid Dynamics (CFD) study is on NACA 4415 airfoil, at a Reynolds number 120,000. Two TLE shapes are tested on NACA 4415 airfoil. The tubercle designs implemented on the airfoil are sinusoidal and spherical. A parametric study is also carried out considering three amplitudes (0.025c, 0.05c and 0.075c), the wavelength (0.25c) is fixed. Structured mesh is utilized to generate grid and Transition SST turbulence model is used to capture the flow physics. Results clearly show spherical tubercles outperform sinusoidal tubercles. Furthermore experimental study considering spherical TLE is carried out at Reynolds number 200,000. The experimental results show that spherical TLE improve performance compared to clean airfoil.

Matched MeSH terms: Models, Biological*
Fulltext Factors determining dengue outbreak in Malaysia

Ahmad R, Suzilah I, Wan Najdah WMA, Topek O, Mustafakamal I, Lee HL

PLoS One, 2018;13(2):e0193326.
PMID: 29474401 DOI: 10.1371/journal.pone.0193326

A large scale study was conducted to elucidate the true relationship among entomological, epidemiological and environmental factors that contributed to dengue outbreak in Malaysia. Two large areas (Selayang and Bandar Baru Bangi) were selected in this study based on five consecutive years of high dengue cases. Entomological data were collected using ovitraps where the number of larvae was used to reflect Aedes mosquito population size; followed by RT-PCR screening to detect and serotype dengue virus in mosquitoes. Notified cases, date of disease onset, and number and type of the interventions were used as epidemiological endpoint, while rainfall, temperature, relative humidity and air pollution index (API) were indicators for environmental data. The field study was conducted during 81 weeks of data collection. Correlation and Autoregressive Distributed Lag Model were used to determine the relationship. The study showed that, notified cases were indirectly related with the environmental data, but shifted one week, i.e. last 3 weeks positive PCR; last 4 weeks rainfall; last 3 weeks maximum relative humidity; last 3 weeks minimum and maximum temperature; and last 4 weeks air pollution index (API), respectively. Notified cases were also related with next week intervention, while conventional intervention only happened 4 weeks after larvae were found, indicating ample time for dengue transmission. Based on a significant relationship among the three factors (epidemiological, entomological and environmental), estimated Autoregressive Distributed Lag (ADL) model for both locations produced high accuracy 84.9% for Selayang and 84.1% for Bandar Baru Bangi in predicting the actual notified cases. Hence, such model can be used in forestalling dengue outbreak and acts as an early warning system. The existence of relationships among the entomological, epidemiological and environmental factors can be used to build an early warning system for the prediction of dengue outbreak so that preventive interventions can be taken early to avert the outbreaks.

Matched MeSH terms: Models, Biological*
Fulltext Association of some Campylobacter jejuni with Pseudomonas aeruginosa biofilms increases attachment under conditions mimicking those in the environment

Teh AHT, Lee SM, Dykes GA

PLoS One, 2019;14(4):e0215275.
PMID: 30970009 DOI: 10.1371/journal.pone.0215275

Campylobacter jejuni is a microaerophilic bacterial species which is a major food-borne pathogen worldwide. Attachment and biofilm formation have been suggested to contribute to the survival of this fastidious bacteria in the environment. In this study the attachment of three C. jejuni strains (C. jejuni strains 2868 and 2871 isolated from poultry and ATCC 33291) to different abiotic surfaces (stainless steel, glass and polystyrene) alone or with Pseudomonas aeruginosa biofilms on them, in air at 25°C and under static or flow conditions, were investigated using a modified Robbins Device. Bacteria were enumerated and scanning electron microscopy was carried out. The results indicated that both C. jejuni strains isolated from poultry attached better to Pseudomonas aeruginosa biofilms on abiotic surfaces than to the surfaces alone under the different conditions tested. This suggests that biofilms of other bacterial species may passively protect C. jejuni against shear forces and potentially oxygen stress which then contribute to their persistence in environments which are detrimental to them. By contrast the C. jejuni ATCC 33291 strain did not attach differentially to P. aeruginosa biofilms, suggesting that different C. jejuni strains may have alternative strategies for persistence in the environment. This study supports the hypothesis that C. jejuni do not form biofilms per se under conditions they encounter in the environment but simply attach to surfaces or biofilms of other species.

Matched MeSH terms: Models, Biological
Fulltext Seagrass habitat suitability model for Redang Marine Park using multibeam echosounder data: Testing different spatial resolutions and analysis window sizes

Muhamad MAH, Che Hasan R, Md Said N, Ooi JL

PLoS One, 2021;16(9):e0257761.
PMID: 34555110 DOI: 10.1371/journal.pone.0257761

Integrating Multibeam Echosounder (MBES) data (bathymetry and backscatter) and underwater video technology allows scientists to study marine habitats. However, use of such data in modeling suitable seagrass habitats in Malaysian coastal waters is still limited. This study tested multiple spatial resolutions (1 and 50 m) and analysis window sizes (3 × 3, 9 × 9, and 21 × 21 cells) probably suitable for seagrass-habitat relationships in Redang Marine Park, Terengganu, Malaysia. A maximum entropy algorithm was applied, using 12 bathymetric and backscatter predictors to develop a total of 6 seagrass habitat suitability models. The results indicated that both fine and coarse spatial resolution datasets could produce models with high accuracy (>90%). However, the models derived from the coarser resolution dataset displayed inconsistent habitat suitability maps for different analysis window sizes. In contrast, habitat models derived from the fine resolution dataset exhibited similar habitat distribution patterns for three different analysis window sizes. Bathymetry was found to be the most influential predictor in all the models. The backscatter predictors, such as angular range analysis inversion parameters (characterization and grain size), gray-level co-occurrence texture predictors, and backscatter intensity levels, were more important for coarse resolution models. Areas of highest habitat suitability for seagrass were predicted to be in shallower (<20 m) waters and scattered between fringing reefs (east to south). Some fragmented, highly suitable habitats were also identified in the shallower (<20 m) areas in the northwest of the prediction models and scattered between fringing reefs. This study highlighted the importance of investigating the suitable spatial resolution and analysis window size of predictors from MBES for modeling suitable seagrass habitats. The findings provide important insight on the use of remote acoustic sonar data to study and map seagrass distribution in Malaysia coastal water.

Matched MeSH terms: Models, Biological
Fulltext A data driven change-point epidemic model for assessing the impact of large gathering and subsequent movement control order on COVID-19 spread in Malaysia

Dass SC, Kwok WM, Gibson GJ, Gill BS, Sundram BM, Singh S

PLoS One, 2021;16(5):e0252136.
PMID: 34043676 DOI: 10.1371/journal.pone.0252136

The second wave of COVID-19 in Malaysia is largely attributed to a four-day mass gathering held in Sri Petaling from February 27, 2020, which contributed to an exponential rise of COVID-19 cases in the country. Starting from March 18, 2020, the Malaysian government introduced four consecutive phases of a Movement Control Order (MCO) to stem the spread of COVID-19. The MCO was implemented through various non-pharmaceutical interventions (NPIs). The reported number of cases reached its peak by the first week of April and then started to reduce, hence proving the effectiveness of the MCO. To gain a quantitative understanding of the effect of MCO on the dynamics of COVID-19, this paper develops a class of mathematical models to capture the disease spread before and after MCO implementation in Malaysia. A heterogeneous variant of the Susceptible-Exposed-Infected-Recovered (SEIR) model is developed with additional compartments for asymptomatic transmission. Further, a change-point is incorporated to model disease dynamics before and after intervention which is inferred based on data. Related statistical analyses for inference are developed in a Bayesian framework and are able to provide quantitative assessments of (1) the impact of the Sri Petaling gathering, and (2) the extent of decreasing transmission during the MCO period. The analysis here also quantitatively demonstrates how quickly transmission rates fall under effective NPI implementation within a short time period. The models and methodology used provided important insights into the nature of local transmissions to decision makers in the Ministry of Health, Malaysia.

Matched MeSH terms: Models, Biological*
Fulltext An improved swarm optimization for parameter estimation and biological model selection

Abdullah A, Deris S, Mohamad MS, Anwar S

PLoS One, 2013;8(4):e61258.
PMID: 23593445 DOI: 10.1371/journal.pone.0061258

One of the key aspects of computational systems biology is the investigation on the dynamic biological processes within cells. Computational models are often required to elucidate the mechanisms and principles driving the processes because of the nonlinearity and complexity. The models usually incorporate a set of parameters that signify the physical properties of the actual biological systems. In most cases, these parameters are estimated by fitting the model outputs with the corresponding experimental data. However, this is a challenging task because the available experimental data are frequently noisy and incomplete. In this paper, a new hybrid optimization method is proposed to estimate these parameters from the noisy and incomplete experimental data. The proposed method, called Swarm-based Chemical Reaction Optimization, integrates the evolutionary searching strategy employed by the Chemical Reaction Optimization, into the neighbouring searching strategy of the Firefly Algorithm method. The effectiveness of the method was evaluated using a simulated nonlinear model and two biological models: synthetic transcriptional oscillators, and extracellular protease production models. The results showed that the accuracy and computational speed of the proposed method were better than the existing Differential Evolution, Firefly Algorithm and Chemical Reaction Optimization methods. The reliability of the estimated parameters was statistically validated, which suggests that the model outputs produced by these parameters were valid even when noisy and incomplete experimental data were used. Additionally, Akaike Information Criterion was employed to evaluate the model selection, which highlighted the capability of the proposed method in choosing a plausible model based on the experimental data. In conclusion, this paper presents the effectiveness of the proposed method for parameter estimation and model selection problems using noisy and incomplete experimental data. This study is hoped to provide a new insight in developing more accurate and reliable biological models based on limited and low quality experimental data.

Matched MeSH terms: Models, Biological*
Fulltext Reproductive number of coronavirus: A systematic review and meta-analysis based on global level evidence

Billah MA, Miah MM, Khan MN

PLoS One, 2020;15(11):e0242128.
PMID: 33175914 DOI: 10.1371/journal.pone.0242128

BACKGROUND: The coronavirus (SARS-COV-2) is now a global concern because of its higher transmission capacity and associated adverse consequences including death. The reproductive number of coronavirus provides an estimate of the possible extent of the transmission. This study aims to provide a summary reproductive number of coronavirus based on available global level evidence.
METHODS: A total of three databases were searched on September 15, 2020: PubMed, Web of Science, and Science Direct. The searches were conducted using a pre-specified search strategy to record studies reported the reproductive number of coronavirus from its inception in December 2019. It includes keywords of coronavirus and its reproductive number, which were combined using the Boolean operators (AND, OR). Based on the included studies, we estimated a summary reproductive number by using the meta-analysis. We used narrative synthesis to explain the results of the studies where the reproductive number was reported, however, were not possible to include in the meta-analysis because of the lack of data (mostly due to confidence interval was not reported).
RESULTS: Total of 42 studies included in this review whereas 29 of them were included in the meta-analysis. The estimated summary reproductive number was 2.87 (95% CI, 2.39-3.44). We found evidence of very high heterogeneity (99.5%) of the reproductive number reported in the included studies. Our sub-group analysis was found the significant variations of reproductive number across the country for which it was estimated, method and model that were used to estimate the reproductive number, number of case that was considered to estimate the reproductive number, and the type of reproductive number that was estimated. The highest reproductive number was reported for the Diamond Princess Cruise Ship in Japan (14.8). In the country-level, the higher reproductive number was reported for France (R, 6.32, 95% CI, 5.72-6.99) following Germany (R, 6.07, 95% CI, 5.51-6.69) and Spain (R, 3.56, 95% CI, 1.62-7.82). The higher reproductive number was reported if it was estimated by using the Markov Chain Monte Carlo method (MCMC) method and the Epidemic curve model. We also reported significant heterogeneity of the type of reproductive number- a high-value reported if it was the time-dependent reproductive number.
CONCLUSION: The estimated summary reproductive number indicates an exponential increase of coronavirus infection in the coming days. Comprehensive policies and programs are important to reduce new infections as well as the associated adverse consequences including death.

Matched MeSH terms: Models, Biological
Fulltext Agent Based Modeling of Human Gut Microbiome Interactions and Perturbations

Shashkova T, Popenko A, Tyakht A, Peskov K, Kosinsky Y, Bogolubsky L, et al.

PLoS One, 2016;11(2):e0148386.
PMID: 26894828 DOI: 10.1371/journal.pone.0148386

BACKGROUND: Intestinal microbiota plays an important role in the human health. It is involved in the digestion and protects the host against external pathogens. Examination of the intestinal microbiome interactions is required for understanding of the community influence on host health. Studies of the microbiome can provide insight on methods of improving health, including specific clinical procedures for individual microbial community composition modification and microbiota correction by colonizing with new bacterial species or dietary changes.
METHODOLOGY/PRINCIPAL FINDINGS: In this work we report an agent-based model of interactions between two bacterial species and between species and the gut. The model is based on reactions describing bacterial fermentation of polysaccharides to acetate and propionate and fermentation of acetate to butyrate. Antibiotic treatment was chosen as disturbance factor and used to investigate stability of the system. System recovery after antibiotic treatment was analyzed as dependence on quantity of feedback interactions inside the community, therapy duration and amount of antibiotics. Bacterial species are known to mutate and acquire resistance to the antibiotics. The ability to mutate was considered to be a stochastic process, under this suggestion ratio of sensitive to resistant bacteria was calculated during antibiotic therapy and recovery.
CONCLUSION/SIGNIFICANCE: The model confirms a hypothesis of feedbacks mechanisms necessity for providing functionality and stability of the system after disturbance. High fraction of bacterial community was shown to mutate during antibiotic treatment, though sensitive strains could become dominating after recovery. The recovery of sensitive strains is explained by fitness cost of the resistance. The model demonstrates not only quantitative dynamics of bacterial species, but also gives an ability to observe the emergent spatial structure and its alteration, depending on various feedback mechanisms. Visual version of the model shows that spatial structure is a key factor, which helps bacteria to survive and to adapt to changed environmental conditions.

Matched MeSH terms: Models, Biological*
Fulltext Effects of urbanization on host-pathogen interactions, using Yersinia in house sparrows as a model

Rouffaer LO, Strubbe D, Teyssier A, Salleh Hudin N, Van den Abeele AM, Cox I, et al.

PLoS One, 2017;12(12):e0189509.
PMID: 29281672 DOI: 10.1371/journal.pone.0189509

Urbanization strongly affects biodiversity, altering natural communities and often leading to a reduced species richness. Yet, despite its increasingly recognized importance, how urbanization impacts on the health of individual animals, wildlife populations and on disease ecology remains poorly understood. To test whether, and how, urbanization-driven ecosystem alterations influence pathogen dynamics and avian health, we use house sparrows (Passer domesticus) and Yersinia spp. (pathogenic for passerines) as a case study. Sparrows are granivorous urban exploiters, whose western European populations have declined over the past decades, especially in highly urbanized areas. We sampled 329 house sparrows originating from 36 populations along an urbanization gradient across Flanders (Belgium), and used isolation combined with 'matrix-assisted laser desorption ionization- time of flight mass spectrometry' (MALDI-TOF MS) and PCR methods for detecting the presence of different Yersinia species. Yersinia spp. were recovered from 57.43% of the sampled house sparrows, of which 4.06%, 53.30% and 69.54% were identified as Y. pseudotuberculosis, Y. enterocolitica and other Yersinia species, respectively. Presence of Yersinia was related to the degree of urbanization, average daily temperatures and the community of granivorous birds present at sparrow capture locations. Body condition of suburban house sparrows was found to be higher compared to urban and rural house sparrows, but no relationships between sparrows' body condition and presence of Yersinia spp. were found. We conclude that two determinants of pathogen infection dynamics, body condition and pathogen occurrence, vary along an urbanization gradient, potentially mediating the impact of urbanization on avian health.

Matched MeSH terms: Models, Biological*
Fulltext Allometry and Scaling of the Intraocular Pressure and Aqueous Humour Flow Rate in Vertebrate Eyes

Zouache MA, Eames I, Samsudin A

PLoS One, 2016;11(3):e0151490.
PMID: 26990431 DOI: 10.1371/journal.pone.0151490

In vertebrates, intraocular pressure (IOP) is required to maintain the eye into a shape allowing it to function as an optical instrument. It is sustained by the balance between the production of aqueous humour by the ciliary body and the resistance to its outflow from the eye. Dysregulation of the IOP is often pathological to vision. High IOP may lead to glaucoma, which is in man the second most prevalent cause of blindness. Here, we examine the importance of the IOP and rate of formation of aqueous humour in the development of vertebrate eyes by performing allometric and scaling analyses of the forces acting on the eye during head movement and the energy demands of the cornea, and testing the predictions of the models against a list of measurements in vertebrates collated through a systematic review. We show that the IOP has a weak dependence on body mass, and that in order to maintain the focal length of the eye, it needs to be an order of magnitude greater than the pressure drop across the eye resulting from gravity or head movement. This constitutes an evolutionary constraint that is common to all vertebrates. In animals with cornea-based optics, this constraint also represents a condition to maintain visual acuity. Estimated IOPs were found to increase with the evolution of terrestrial animals. The rate of formation of aqueous humour was found to be adjusted to the metabolic requirements of the cornea, scaling as Vac(0.67), where Vac is the volume of the anterior chamber. The present work highlights an interdependence between IOP and aqueous flow rate crucial to ocular function that must be considered to understand the evolution of the dioptric apparatus. It should also be taken into consideration in the prevention and treatment of glaucoma.

Matched MeSH terms: Models, Biological*

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