ResearchPad - 87 Default RSS Feed en-us © 2020 Newgen KnowledgeWorks <![CDATA[Coexisting attractors in the context of cross-scale population dynamics: measles in London as a case study]]> Patterns of measles infection in large urban populations have long been considered the paradigm of synchronized nonlinear dynamics. Indeed, recurrent epidemics appear approximately mass-action despite underlying heterogeneity. However, using a subset of rich, newly digitized mortality data (1897–1906), we challenge that proposition. We find that sub-regions of London exhibited a mixture of simultaneous annual and biennial dynamics, while the aggregate city-level dynamics appears firmly annual. Using a simple stochastic epidemic model and maximum-likelihood inference methods, we show that we can capture this observed variation in periodicity. We identify agreement between theory and data, indicating that both changes in periodicity and epidemic coupling between regions can follow relatively simple rules; in particular we find local variation in seasonality drives periodicity. Our analysis underlines that multiple attractors can coexist in a strongly mixed population and follow theoretical predictions.

<![CDATA[Global shifts in mammalian population trends reveal key predictors of virus spillover risk]]> Emerging infectious diseases in humans are frequently caused by pathogens originating from animal hosts, and zoonotic disease outbreaks present a major challenge to global health. To investigate drivers of virus spillover, we evaluated the number of viruses mammalian species have shared with humans. We discovered that the number of zoonotic viruses detected in mammalian species scales positively with global species abundance, suggesting that virus transmission risk has been highest from animal species that have increased in abundance and even expanded their range by adapting to human-dominated landscapes. Domesticated species, primates and bats were identified as having more zoonotic viruses than other species. Among threatened wildlife species, those with population reductions owing to exploitation and loss of habitat shared more viruses with humans. Exploitation of wildlife through hunting and trade facilitates close contact between wildlife and humans, and our findings provide further evidence that exploitation, as well as anthropogenic activities that have caused losses in wildlife habitat quality, have increased opportunities for animal–human interactions and facilitated zoonotic disease transmission. Our study provides new evidence for assessing spillover risk from mammalian species and highlights convergent processes whereby the causes of wildlife population declines have facilitated the transmission of animal viruses to humans.

<![CDATA[Sexual frequency is associated with age of natural menopause: results from the Study of Women's Health Across the Nation]]>

It is often observed that married women have a later age of natural menopause (ANM) than unmarried women; however, the reason for this association is unknown. We test an original hypothesis that sexual frequency acts as a bio-behavioural mediator between marital status and ANM. We hypothesize that there is a trade-off between continued ovulation and menopause based on the woman's chances of becoming pregnant. If a woman is sexually inactive, then pregnancy is impossible, and continued investment in ovulation would not be adaptive. In addition, we test an existing hypothesis that the observed relationship is because of the exposure to male pheromones. Data from 2936 women were drawn from 11 waves of the Study of Women's Health Across the Nation, which is a longitudinal study conducted in the United States. Using time-varying Cox regression, we found no evidence for the pheromone hypothesis. However, we did observe that women who reported to have sex weekly during the study period were 28% less likely to experience menopause than women who had sex less than monthly. This is an indication that ANM may be somewhat facultative in response to the likelihood of pregnancy.

<![CDATA[Interplay between competitive and cooperative interactions in a three-player pathogen system]]>

In ecological systems, heterogeneous interactions between pathogens take place simultaneously. This occurs, for instance, when two pathogens cooperate, while at the same time, multiple strains of these pathogens co-circulate and compete. Notable examples include the cooperation of human immunodeficiency virus with antibiotic-resistant and susceptible strains of tuberculosis or some respiratory infections with Streptococcus pneumoniae strains. Models focusing on competition or cooperation separately fail to describe how these concurrent interactions shape the epidemiology of such diseases. We studied this problem considering two cooperating pathogens, where one pathogen is further structured in two strains. The spreading follows a susceptible-infected-susceptible process and the strains differ in transmissibility and extent of cooperation with the other pathogen. We combined a mean-field stability analysis with stochastic simulations on networks considering both well-mixed and structured populations. We observed the emergence of a complex phase diagram, where the conditions for the less transmissible, but more cooperative strain to dominate are non-trivial, e.g. non-monotonic boundaries and bistability. Coupled with community structure, the presence of the cooperative pathogen enables the coexistence between strains by breaking the spatial symmetry and dynamically creating different ecological niches. These results shed light on ecological mechanisms that may impact the epidemiology of diseases of public health concern.

<![CDATA[Onward transmission of viruses: how do viruses emerge to cause epidemics after spillover?]]>

The critical step in the emergence of a new epidemic or pandemic viral pathogen occurs after it infects the initial spillover host and then is successfully transmitted onwards, causing an outbreak chain of transmission within that new host population. Crossing these choke points sets a pathogen on the pathway to epidemic emergence. While many viruses spill over to infect new or alternative hosts, only a few accomplish this transition—and the reasons for the success of those pathogens are still unclear. Here, we consider this issue related to the emergence of animal viruses, where factors involved likely include the ability to efficiently infect the new animal host, the demographic features of the initial population that favour onward transmission, the level of shedding and degree of susceptibility of individuals of that population, along with pathogen evolution favouring increased replication and more efficient transmission among the new host individuals. A related form of emergence involves mutations that increased spread or virulence of an already-known virus within its usual host. In all of these cases, emergence may be due to altered viral properties, changes in the size or structure of the host populations, ease of transport, climate change or, in the case of arboviruses, to the expansion of the arthropod vectors. Here, we focus on three examples of viruses that have gained efficient onward transmission after spillover: influenza A viruses that are respiratory transmitted, HIV, a retrovirus, that is mostly blood or mucosal transmitted, and canine parvovirus that is faecal:oral transmitted. We describe our current understanding of the changes in the viruses that allowed them to overcome the barriers that prevented efficient replication and spread in their new hosts. We also briefly outline how we could gain a better understanding of the mechanisms and variability in order to better anticipate these events in the future.

This article is part of the theme issue ‘Dynamic and integrative approaches to understanding pathogen spillover’.

<![CDATA[Early warning signals of malaria resurgence in Kericho, Kenya]]>

Campaigns to eliminate infectious diseases could be greatly aided by methods for providing early warning signals of resurgence. Theory predicts that as a disease transmission system undergoes a transition from stability at the disease-free equilibrium to sustained transmission, it will exhibit characteristic behaviours known as critical slowing down, referring to the speed at which fluctuations in the number of cases are dampened, for instance the extinction of a local transmission chain after infection from an imported case. These phenomena include increases in several summary statistics, including lag-1 autocorrelation, variance and the first difference of variance. Here, we report the first empirical test of this prediction during the resurgence of malaria in Kericho, Kenya. For 10 summary statistics, we measured the approach to criticality in a rolling window to quantify the size of effect and directions. Nine of the statistics increased as predicted and variance, the first difference of variance, autocovariance, lag-1 autocorrelation and decay time returned early warning signals of critical slowing down based on permutation tests. These results show that time series of disease incidence collected through ordinary surveillance activities may exhibit characteristic signatures prior to an outbreak, a phenomenon that may be quite general among infectious disease systems.

<![CDATA[Improved susceptible–infectious–susceptible epidemic equations based on uncertainties and autocorrelation functions]]>

Compartmental equations are primary tools in the study of disease spreading processes. They provide accurate predictions for large populations but poor results whenever the integer nature of the number of agents is evident. In the latter instance, uncertainties are relevant factors for pathogen transmission. Starting from the agent-based approach, we investigate the role of uncertainties and autocorrelation functions in the susceptible–infectious–susceptible (SIS) epidemic model, including their relationship with epidemiological variables. We find new differential equations that take uncertainties into account. The findings provide improved equations, offering new insights on disease spreading processes.

<![CDATA[Migrating birds rapidly increase constitutive immune function during stopover]]>

Migratory flight is physiologically highly demanding and has been shown to negatively affect multiple parameters of constitutive immune function (CIF), an animal's first line of physiological defence against infections. In between migratory flights, most birds make stopovers, periods during which they accumulate fuel for the next flight(s). Stopovers are also commonly thought of as periods of rest and recovery, but what this encompasses is largely undefined. Here, we show that during stopover, northern wheatears Oenanthe oenanthe, a long-distance migratory bird, can rapidly increase constitutive innate immune function. We caught and temporarily caged birds under ad libitum food conditions at a stopover site in autumn. Within 2 days, most birds significantly increased complement activity and their ability to kill microbes. Changes in immune function were not related to the birds' food intake or extent of fuel accumulation. Our study suggests that stopovers may not only be important to refuel but also to restore immune function. Additionally, the increase in CIF could help migrating birds to deal with novel pathogens they may encounter at stopover sites.

<![CDATA[Transmural impedance detects graded changes of inflammation in experimental colitis]]>

Ulcerative colitis is a chronic disease in which the mucosa of the colon or rectum becomes inflamed. An objective biomarker of inflammation will provide quantitative measures to support qualitative assessment during an endoscopic examination. Previous studies show that transmural electrical impedance is a quantifiable biomarker of inflammation. Here, we hypothesize that impedance detects spatially restricted areas of inflammation, thereby allowing the distinction between regions that differ in their severity of inflammation. A platinum ball electrode was placed into minimally inflamed (i.e. normal) or 2,4,6-trinitrobenzene sulphonic acid (TNBS)-inflamed colonic regions of rats and impedance measurements obtained by passing current between the intraluminal and subcutaneous return electrode. Histology of the colon was correlated with impedance measurements. The impedance of minimally inflamed (normal) tissue was 1.5–1.9 kΩ. Following TNBS injection, impedance significantly decreased within the inflammatory penumbra (p < 0.05), and decreased more in the inflammatory epicentre (p = 0.02). Histological damage correlated with impedance values (p < 0.05). Thus, impedance values of 1.5–1.9, 1.3–1.4 and 0.9–1.1 kΩ corresponded to minimally inflamed, mildly inflamed and moderately inflamed tissue, respectively. In conclusion, transmural impedance is an objective, spatially localized biomarker of mucosal integrity, and distinguishes between severities of intestinal inflammation.

<![CDATA[Host density drives viral, but not trypanosome, transmission in a key pollinator]]>

Supplemental feeding of wildlife populations can locally increase the density of individuals, which may in turn impact disease dynamics. Flower strips are a widely used intervention in intensive agricultural systems to nutritionally support pollinators such as bees. Using a controlled experimental semi-field design, we asked how density impacts transmission of a virus and a trypanosome parasite in bumblebees. We manipulated bumblebee density by using different numbers of colonies within the same area of floral resource. In high-density compartments, slow bee paralysis virus was transmitted more quickly, resulting in higher prevalence and level of infection in bumblebee hosts. By contrast, there was no impact of density on the transmission of the trypanosome Crithidia bombi, which may reflect the ease with which this parasite is transmitted. These results suggest that agri-environment schemes such as flower strips, which are known to enhance the nutrition and survival of bumblebees, may also have negative impacts on pollinators through enhanced disease transmission. Future studies should assess how changing the design of these schemes could minimize disease transmission and thus maximise their health benefits to wild pollinators.

<![CDATA[Compound- and context-dependent effects of antibiotics on greenhouse gas emissions from livestock]]>

The use of antibiotics in livestock production may trigger ecosystem disservices, including increased emissions of greenhouse gases. To evaluate this, we conducted two separate animal experiments, administering two widely used antibiotic compounds (benzylpenicillin and tetracycline) to dairy cows over a 4- or 5-day period locally and/or systemically. We then recorded enteric methane production, total gas production from dung decomposing under aerobic versus anaerobic conditions, prokaryotic community composition in rumen and dung, and accompanying changes in nutrient intake, rumen fermentation, and digestibility resulting from antibiotic administration. The focal antibiotics had no detectable effect on gas emissions from enteric fermentation or dung in aerobic conditions, while they decreased total gas production from anaerobic dung. Microbiome-level effects of benzylpenicillin proved markedly different from those previously recorded for tetracycline in dung, and did not differ by the mode of administration (local or systemic). Antibiotic effects on gas production differed substantially between dung maintained under aerobic versus anaerobic conditions and between compounds. These findings demonstrate compound- and context-dependent impacts of antibiotics on methane emissions and underlying processes, and highlight the need for a global synthesis of data on agricultural antibiotic use before understanding their climatic impacts.

<![CDATA[Controlling for baseline telomere length biases estimates of the rate of telomere attrition]]>

Longitudinal studies have sought to establish whether environmental exposures such as smoking accelerate the attrition of individuals' telomeres over time. These studies typically control for baseline telomere length (TL) by including it as a covariate in statistical models. However, baseline TL also differs between smokers and non-smokers, and telomere attrition is spuriously linked to baseline TL via measurement error and regression to the mean. Using simulated datasets, we show that controlling for baseline TL overestimates the true effect of smoking on telomere attrition. This bias increases with increasing telomere measurement error and increasing difference in baseline TL between smokers and non-smokers. Using a meta-analysis of longitudinal datasets, we show that as predicted, the estimated difference in telomere attrition between smokers and non-smokers is greater when statistical models control for baseline TL than when they do not, and the size of the discrepancy is positively correlated with measurement error. The bias we describe is not specific to smoking and also applies to other exposures. We conclude that to avoid invalid inference, models of telomere attrition should not control for baseline TL by including it as a covariate. Many claims of accelerated telomere attrition in individuals exposed to adversity need to be re-assessed.

<![CDATA[Simulation analysis for tumor radiotherapy based on three‐component mathematical models]]>



To setup a three‐component tumor growth mathematical model and discuss its basic application in tumor fractional radiotherapy with computer simulation.


First, our three‐component tumor growth model extended from the classical Gompertz tumor model was formulated and applied to a fractional radiotherapy with a series of proper parameters. With the computer simulation of our model, the impact of some parameters such as fractional dose, amount of quiescent tumor cells, and α/β value to the effect of radiotherapy was also analyzed, respectively.


With several optimal technologies, the model could run stably and output a series of convergent results. The simulation results showed that the fractional radiotherapy dose could impact the effect of radiotherapy significantly, while the amount of quiescent tumor cells and α/β value did that to a certain extent.


Supported with some proper parameters, our model can simulate and analyze the tumor radiotherapy program as well as give some theoretical instruction to radiotherapy personalized optimization.

<![CDATA[Ancestral diet transgenerationally influences offspring in a parent-of-origin and sex-specific manner]]>

Parent-of-origin effects, whereby specific phenotypes are differentially inherited paternally or maternally, provide useful clues to better understand transgenerational effect transmission. Ancestral diet influences offspring phenotypes, including body composition and fitness. However, the specific role that mothers and fathers play in the transmission of altered phenotypes to male and female offspring remains unclear. We investigated the influence of the parent-of-origin's diet on adult progeny phenotypes and reproductive output for three generations in fruit flies (Drosophila melanogaster). Males and females reared on a control diet were exposed to the control diet or one of two altered (no- or high-) sugar treatment diets for a single generation. Flies from one of the two altered diet treatments were then mated to control flies in a full-factorial design to produce F1 offspring and kept on control media for each following generation. We found parent-of-origin (triglyceride) and non-parent-of-origin (sugar) body composition effects, which were transgenerational and sex-specific. Additionally, we observed a negative correlation between intergenerational maternal reproductive output and triglyceride levels, suggesting that ancestral diet may affect fitness. This work demonstrates that ancestral diet can transmit altered phenotypes in a parent-of-origin and sex-specific manner and highlights that mechanisms regulating such transmission have been greatly overlooked.

This article is part of the theme issue ‘The role of plasticity in phenotypic adaptation to rapid environmental change’.

<![CDATA[The behaviour of overweight dogs shows similarity with personality traits of overweight humans]]>

Excessive food intake and the resulting excess weight gain is a growing problem in human and canine populations. Dogs, due to their shared living environment with humans, may provide a beneficial model to study the causes and consequences of obesity. Here, we make use of two well-established research paradigms (two-way choice paradigm and cognitive bias test), previously applied with dogs, to investigate the role of obesity and obesity-prone breeds for food responsiveness. We found no evidence of breed differences in food responsiveness due to one breed being more prone to obesity than another. Breed differences found in this study, however, can be explained by working dog status, i.e. whether the dog works in cooperation with, or independently from, humans. Our results also confirm that overweight dogs, as opposed to normal weight dogs, tried to maximize food intake from the higher quality food and hesitated to do the task when the food reward was uncertain. These results are very similar to those expected from the parallel models that exist between certain personality traits and being overweight in humans, suggesting that dogs are indeed a promising model for experimentally investigating obesity in humans.

<![CDATA[Proteomic profiling of archaeological human bone]]>

Ancient protein analysis provides clues to human life and diseases from ancient times. Here, we performed shotgun proteomics of human archeological bones for the first time, using rib bones from the Hitotsubashi site (AD 1657–1683) in Tokyo, called Edo in ancient times. The output data obtained were analysed using Gene Ontology and label-free quantification. We detected leucocyte-derived proteins, possibly originating from the bone marrow of the rib. Particularly prevalent and relatively high expression of eosinophil peroxidase suggests the influence of infectious diseases. This scenario is plausible, considering the overcrowding and unhygienic living conditions of the Edo city described in the historical literature. We also observed age-dependent differences in proteome profiles, particularly for proteins involved in developmental processes. Among them, alpha-2-HS-glycoprotein demonstrated a strong negative correlation with age. These results suggest that analysis of ancient proteins could provide a useful indicator of stress, disease, starvation, obesity and other kinds of physiological and pathological information.

<![CDATA[Contact chains of cattle farms in Great Britain]]>

Network analyses can assist in predicting the course of epidemics. Time-directed paths or ‘contact chains' provide a measure of host-connectedness across specified timeframes, and so represent potential pathways for spread of infections with different epidemiological characteristics. We analysed networks and contact chains of cattle farms in Great Britain using Cattle Tracing System data from 2001 to 2015. We focused on the potential for between-farm transmission of bovine tuberculosis, a chronic infection with potential for hidden spread through the network. Networks were characterized by scale-free type properties, where individual farms were found to be influential ‘hubs' in the network. We found a markedly bimodal distribution of farms with either small or very large ingoing and outgoing contact chains (ICCs and OCCs). As a result of their cattle purchases within 12-month periods, 47% of British farms were connected by ICCs to more than 1000 other farms and 16% were connected to more than 10 000 other farms. As a result of their cattle sales within 12-month periods, 66% of farms had OCCs that reached more than 1000 other farms and 15% reached more than 10 000 other farms. Over 19 000 farms had both ICCs and OCCs reaching more than 10 000 farms for two or more years. While farms with more contacts in their ICCs or OCCs might play an important role in disease spread, farms with extensive ICCs and OCCs might be particularly important by being at higher risk of both acquiring and disseminating infections.

<![CDATA[Invasive mutualisms between a plant pathogen and insect vectors in the Middle East and Brazil]]>

Complex multi-trophic interactions in vectorborne diseases limit our understanding and ability to predict outbreaks. Arthropod-vectored pathogens are especially problematic, with the potential for novel interspecific interactions during invasions. Variations and novelties in plant–arthropod–pathogen triumvirates present significant threats to global food security. We examined aspects of a phytoplasma pathogen of citrus across two continents. ‘Candidatus Phytoplasma aurantifolia’ causes Witches' Broom Disease of Lime (WBDL) and has devastated citrus production in the Middle East. A variant of this phytoplasma currently displays asymptomatic or ‘silent’ infections in Brazil. We first studied vector capacity and fitness impacts of the pathogen on its vectors. The potential for co-occurring weed species to act as pathogen reservoirs was analysed and key transmission periods in the year were also studied. We demonstrate that two invasive hemipteran insects—Diaphorina citri and Hishimonus phycitis—can vector the phytoplasma. Feeding on phytoplasma-infected hosts greatly increased reproduction of its invasive vector D. citri both in Oman and Brazil; suggesting that increased fitness of invasive insect vectors thereby further increases the pathogen's capacity to spread. Based on our findings, this is a robust system for studying the effects of invasions on vectorborne diseases and highlights concerns about its spread to warmer, drier regions of Brazil.

<![CDATA[Phylogeny matters: revisiting ‘a comparison of bats and rodents as reservoirs of zoonotic viruses’]]>

Diseases emerging from wildlife have been the source of many major human outbreaks. Predicting key sources of these outbreaks requires an understanding of the factors that explain pathogen diversity in reservoir species. Comparative methods are powerful tools for understanding variation in pathogen diversity and rely on correcting for phylogenetic relatedness among reservoir species. We reanalysed a previously published dataset, examining the relative effects of species' traits on patterns of viral diversity in bats and rodents. We expanded on prior work by using more highly resolved phylogenies for bats and rodents and incorporating a phylogenetically controlled principal components analysis. For rodents, sympatry and torpor use were important predictors of viral richness and, as previously reported, phylogeny had minimal impact in models. For bats, in contrast to prior work, we find that phylogeny does have an effect in models. Patterns of viral diversity in bats were related to geographical distribution (i.e. latitude and range size) and life history (i.e. lifespan, body size and birthing frequency). However, the effects of these predictors were marginal relative to citation count, emphasizing that the ability to accurately assess reservoir status largely depends on sampling effort and highlighting the need for additional data in future comparative studies.

<![CDATA[Host species, pathogens and disease associated with divergent nasal microbial communities in tortoises]]>

Diverse bacterial communities are found on every surface of macro-organisms, and they play important roles in maintaining normal physiological functions in their hosts. While the study of microbiomes has expanded with the influx of data enabled by recent technological advances, microbiome research in reptiles lags behind other organisms. We sequenced the nasal microbiomes in a sample of four North American tortoise species, and we found differing community compositions among tortoise species and sampling sites, with higher richness and diversity in Texas and Sonoran desert tortoises. Using these data, we investigated the prevalence and operational taxonomic unit (OTU) diversity of the potential pathogen Pasteurella testudinis and found it to be common, abundant and highly diverse. However, the presence of this bacterium was not associated with differences in bacterial community composition within host species. We also found that the presence of nasal discharge from tortoises at the time of sampling was associated with a decline in diversity and a change in microbiome composition, which we posit is due to the harsh epithelial environment associated with immune responses. Repeated sampling across seasons, and at different points of pathogen colonization, should contribute to our understanding of the causes and consequences of different bacterial communities in these long-lived hosts.