Regulatory interactions between daptomycin- and bacitracin-responsive pathways coordinate the cell envelope antibiotic resistance response of Enterococcus faecalis.

Enterococcal infections frequently show high levels of antibiotic resistance, including to cell envelope-acting antibiotics like daptomycin (DAP). While we have a good understanding of the resistance mechanisms, less is known about the control of such resistance genes in enterococci. Previous work unveiled a bacitracin resistance network, comprised of the sensory ABC transporter SapAB, the two-component system (TCS) SapRS and the resistance ABC transporter RapAB. Interestingly, components of this system have recently been implicated in DAP resistance, a role usually regulated by the TCS LiaFSR. To better understand the regulation of DAP resistance and how this relates to mutations observed in DAP-resistant clinical isolates of enterococci, we here explored the interplay between these two regulatory pathways. Our results show that SapR regulates an additional resistance operon, dltXABCD, a known DAP resistance determinant, and show that LiaFSR regulates the expression of sapRS. This regulatory structure places SapRS-target genes under dual control, where expression is directly controlled by SapRS, which itself is up-regulated through LiaFSR. The network structure described here shows how Enterococcus faecalis coordinates its response to cell envelope attack and can explain why clinical DAP resistance often emerges via mutations in regulatory components.

Aggregate fluctuations in adaptive production networks.

To counteract the adverse effects of shocks, such as the global pandemic, on the economy, governments have discussed policies to improve the resilience of supply chains by reducing dependence on foreign suppliers. In this paper, we develop and quantify an adaptive production network model to study network resilience and the consequences of reshoring of supply chains. In our model, firms exit due to exogenous shocks or the propagation of shocks through the network, while firms can replace suppliers they have lost due to exit subject to switching costs and search frictions. Applying our model to a large international firm-level production network dataset, we find that restricting buyer-supplier links via reshoring policies reduces output and increases volatility and that volatility can be amplified through network adaptivity.

Synchronized oscillations in growing cell populations are explained by demographic noise.

Understanding synchrony in growing populations is important for applications as diverse as epidemiology and cancer treatment. Recent experiments employing fluorescent reporters in melanoma cell lines have uncovered growing subpopulations exhibiting sustained oscillations, with nearby cells appearing to synchronize their cycles. In this study, we demonstrate that the behavior observed is consistent with long-lasting transient phenomenon initiated and amplified by the finite-sample effects and demographic noise. We present a novel mathematical analysis of a multistage model of cell growth, which accurately reproduces the synchronized oscillations. As part of the analysis, we elucidate the transient and asymptotic phases of the dynamics and derive an analytical formula to quantify the effect of demographic noise in the appearance of the oscillations. The implications of these findings are broad, such as providing insight into experimental protocols that are used to study the growth of asynchronous populations and, in particular, those investigations relating to anticancer drug discovery.

Predicting the Speed of Epidemics Spreading in Networks.

Global transport and communication networks enable information, ideas, and infectious diseases to now spread at speeds far beyond what has historically been possible. To effectively monitor, design, or intervene in such epidemic-like processes, there is a need to predict the speed of a particular contagion in a particular network, and to distinguish between nodes that are more likely to become infected sooner or later during an outbreak. Here, we study these quantities using a message-passing approach to derive simple and effective predictions that are validated against epidemic simulations on a variety of real-world networks with good agreement. In addition to individualized predictions for different nodes, we find an overall sudden transition from low density to almost full network saturation as the contagion progresses in time. Our theory is developed and explained in the setting of simple contagions on treelike networks, but we are also able to show how the method extends remarkably well to complex contagions and highly clustered networks.

Dual-specificity phosphatase 5 controls the localized inhibition, propagation, and transforming potential of ERK signaling.

Deregulated extracellular signal-regulated kinase (ERK) signaling drives cancer growth. Normally, ERK activity is self-limiting by the rapid inactivation of upstream kinases and delayed induction of dual-specificity MAP kinase phosphatases (MKPs/DUSPs). However, interactions between these feedback mechanisms are unclear. Here we show that, although the MKP DUSP5 both inactivates and anchors ERK in the nucleus, it paradoxically increases and prolongs cytoplasmic ERK activity. The latter effect is caused, at least in part, by the relief of ERK-mediated RAF inhibition. The importance of this spatiotemporal interaction between these distinct feedback mechanisms is illustrated by the fact that expression of oncogenic BRAFV600E, a feedback-insensitive mutant RAF kinase, reprograms DUSP5 into a cell-wide ERK inhibitor that facilitates cell proliferation and transformation. In contrast, DUSP5 deletion causes BRAFV600E-induced ERK hyperactivation and cellular senescence. Thus, feedback interactions within the ERK pathway can regulate cell proliferation and transformation, and suggest oncogene-specific roles for DUSP5 in controlling ERK signaling and cell fate.

The invasion speed of cell migration models with realistic cell cycle time distributions.

Cell proliferation is typically incorporated into stochastic mathematical models of cell migration by assuming that cell divisions occur after an exponentially distributed waiting time. Experimental observations, however, show that this assumption is often far from the real cell cycle time distribution (CCTD). Recent studies have suggested an alternative approach to modelling cell proliferation based on a multi-stage representation of the CCTD. In this paper we investigate the connection between the CCTD and the speed of the collective invasion. We first state a result for a general CCTD, which allows the computation of the invasion speed using the Laplace transform of the CCTD. We use this to deduce the range of speeds for the general case. We then focus on the more realistic case of multi-stage models, using both a stochastic agent-based model and a set of reaction-diffusion equations for the cells' average density. By studying the corresponding travelling wave solutions, we obtain an analytical expression for the speed of invasion for a general N-stage model with identical transition rates, in which case the resulting cell cycle times are Erlang distributed. We show that, for a general N-stage model, the Erlang distribution and the exponential distribution lead to the minimum and maximum invasion speed, respectively. This result allows us to determine the range of possible invasion speeds in terms of the average proliferation time for any multi-stage model.

Demographic noise can reverse the direction of deterministic selection.

Deterministic evolutionary theory robustly predicts that populations displaying altruistic behaviors will be driven to extinction by mutant cheats that absorb common benefits but do not themselves contribute. Here we show that when demographic stochasticity is accounted for, selection can in fact act in the reverse direction to that predicted deterministically, instead favoring cooperative behaviors that appreciably increase the carrying capacity of the population. Populations that exist in larger numbers experience a selective advantage by being more stochastically robust to invasions than smaller populations, and this advantage can persist even in the presence of reproductive costs. We investigate this general effect in the specific context of public goods production and find conditions for stochastic selection reversal leading to the success of public good producers. This insight, developed here analytically, is missed by the deterministic analysis as well as by standard game theoretic models that enforce a fixed population size. The effect is found to be amplified by space; in this scenario we find that selection reversal occurs within biologically reasonable parameter regimes for microbial populations. Beyond the public good problem, we formulate a general mathematical framework for models that may exhibit stochastic selection reversal. In this context, we describe a stochastic analog to [Formula: see text] theory, by which small populations can evolve to higher densities in the absence of disturbance.

Decentralizing the delivery of HIV pre-exposure prophylaxis (PrEP) through family physicians and sexual health clinic nurses: a dissemination and implementation study protocol.

BACKGROUND: Gay, bisexual and other men who have sex with men (gbMSM) in Canada continue to experience high rates of incident HIV. Pre-exposure prophylaxis (PrEP, the regular use of anti-HIV medication) reduces HIV acquisition and could reduce incidence. However, there are too few physicians with expertise in HIV care to meet the projected demand for PrEP. To meet demand and achieve greater public health impact, PrEP delivery could be 'decentralized' by incorporating it into front-line prevention services provided by family physicians (FPs) and sexual health clinic nurses. METHODS: This PrEP decentralization project will use two strategies. The first is an innovative knowledge dissemination approach called 'Patient-Initiated CME' (PICME), which aims to empower individuals to connect their family doctors with online, evidence-based, continuing medical education (CME) on PrEP. After learning about the project through community agencies or social/sexual networking applications, gbMSM interested in PrEP will use a uniquely coded card to access an online information module that includes coaching on how to discuss their HIV risk with their FP. They can provide their physician a link to the accredited CME module using the same card. The second strategy involves a pilot implementation program, in which gbMSM who do not have a FP may bring the card to designated sexual health clinics where trained nurses can deliver PrEP under a medical directive. These approaches will be evaluated through quantitative and qualitative methods, including: questionnaires administered to patients and physicians at baseline and at six months; focus groups with patients, FPs, and sexual health clinic staff; and review of sexual health clinic charts. The primary objective is to quantify the uptake of PrEP achieved using each decentralization strategy. Secondary objectives include a) characterizing barriers and facilitators to PrEP uptake for each strategy, b) assessing fidelity to core components of PrEP delivery within each strategy, c) measuring patient-reported outcomes including satisfaction with clinician-patient relationships, and d) conducting a preliminary costing analysis. DISCUSSION: This study will assess the feasibility of a novel strategy for disseminating knowledge about evidence-based clinical interventions, and inform future strategies for scale-up of an underutilized HIV prevention tool.

Demographic noise slows down cycles of dominance.

We study the phenomenon of cyclic dominance in the paradigmatic Rock-Paper-Scissors model, as occurring in both stochastic individual-based models of finite populations and in the deterministic replicator equations. The mean-field replicator equations are valid in the limit of large populations and, in the presence of mutation and unbalanced payoffs, they exhibit an attracting limit cycle. The period of this cycle depends on the rate of mutation; specifically, the period grows logarithmically as the mutation rate tends to zero. We find that this behaviour is not reproduced in stochastic simulations with a fixed finite population size. Instead, demographic noise present in the individual-based model dramatically slows down the progress of the limit cycle, with the typical period growing as the reciprocal of the mutation rate. Here we develop a theory that explains these scaling regimes and delineates them in terms of population size and mutation rate. We identify a further intermediate regime in which we construct a stochastic differential equation model describing the transition between stochastically-dominated and mean-field behaviour.

Network inoculation: Heteroclinics and phase transitions in an epidemic model.

In epidemiological modelling, dynamics on networks, and, in particular, adaptive and heterogeneous networks have recently received much interest. Here, we present a detailed analysis of a previously proposed model that combines heterogeneity in the individuals with adaptive rewiring of the network structure in response to a disease. We show that in this model, qualitative changes in the dynamics occur in two phase transitions. In a macroscopic description, one of these corresponds to a local bifurcation, whereas the other one corresponds to a non-local heteroclinic bifurcation. This model thus provides a rare example of a system where a phase transition is caused by a non-local bifurcation, while both micro- and macro-level dynamics are accessible to mathematical analysis. The bifurcation points mark the onset of a behaviour that we call network inoculation. In the respective parameter region, exposure of the system to a pathogen will lead to an outbreak that collapses but leaves the network in a configuration where the disease cannot reinvade, despite every agent returning to the susceptible class. We argue that this behaviour and the associated phase transitions can be expected to occur in a wide class of models of sufficient complexity.

Stochastic pattern formation and spontaneous polarisation: the linear noise approximation and beyond.

We review the mathematical formalism underlying the modelling of stochasticity in biological systems. Beginning with a description of the system in terms of its basic constituents, we derive the mesoscopic equations governing the dynamics which generalise the more familiar macroscopic equations. We apply this formalism to the analysis of two specific noise-induced phenomena observed in biologically inspired models. In the first example, we show how the stochastic amplification of a Turing instability gives rise to spatial and temporal patterns which may be understood within the linear noise approximation. The second example concerns the spontaneous emergence of cell polarity, where we make analytic progress by exploiting a separation of time-scales.

Collective synchronization through noise cancellation.

After decades of study, there are only two known mechanisms to induce global synchronization in a population of oscillators: Deterministic coupling and common forcing. The inclusion of independent noise in these models typically serves to drive disorder, increasing the stability of the incoherent state. Here we show that the reverse is also possible. We propose and analyze a simple general model of purely noise coupled oscillators. In the first explicit choice of noise coupling, we find the linear response around incoherence is identical to that of the paradigmatic Kuramoto model but exhibits binary phase locking instead of full coherence. We characterize the phase diagram, stationary states, and approximate low-dimensional dynamics for the model, revealing the curious behavior of this mechanism of synchronization. In the second minimal case we connect the final synchronized state to the initial conditions of the system.

Digital mental health and peer support: Building a Theory of Change informed by stakeholders' perspectives.

Digital Mental Health and Peer support has the potential to bridge gaps in support through its scalability and accessibility. Despite the increasing use of these platforms, there remains a lack of understanding of how they operate in real life, from initial engagement to longer-term impact. We aimed to explore the key inputs, processes, user interactions, assumptions, barriers, facilitators, outcomes, and impacts associated with the use of DMH and peer support platforms by developing a Theory of Change with stakeholders. Stakeholders (n = 77) contributed to the formulation of the Theory of Change through a series of online workshops, focus groups, interviews, and open-ended survey feedback. Workshops were structured to capture information related to aspects of the Theory of Change and to allow stakeholders to provide feedback to improve the diagram. A thematic framework approach was used to analyze transcripts to enable comparisons of factors reported by members, commissioners, and platform staff. Stakeholders identified a variety of factors contributing to initial inputs, processes, outcomes, and impact. Engagement emerged as the most significant barrier to the use of platforms. Motivations for use included filling in gaps in available support, connecting with others and upskilling. Different member types determined how users would interact with the platform which could influence the social response of others. Outcomes were largely positive including provision of a safe online space, improvement in wellbeing, and feeling connected to others. Stakeholders noted impact was harder to identify due to the preventative nature of these platforms but suggested this related to the knowledge of available support, reduction in waiting for support and in referrals, and increasing engagement and uptake of the platforms. Stakeholders identified assumptions regarding internet access as a significant barrier. The Theory of Change illustrated three distinct pathways in digital mental health and peer support. Further research is needed to improve engagement and factors influencing engagement, the member experience and how impact is measured.

Brachytherapy for rhabdomyosarcoma: Survey of international clinical practice and development of guidelines.

BACKGROUND AND PURPOSE: The purpose of this study was to address the lack of published data on the use of brachytherapy in pediatric rhabdomyosarcoma by describing current practice as starting point to develop consensus guidelines. MATERIALS AND METHODS: An international expert panel on the treatment of pediatric rhabdomyosarcoma comprising 24 (pediatric) radiation oncologists, brachytherapists and pediatric surgeons met for a Brachytherapy Workshop hosted by the European paediatric Soft tissue Sarcoma Study Group (EpSSG). The panel's clinical experience, the results of a previously distributed questionnaire, and a review of the literature were presented. RESULTS: The survey indicated the most common use of brachytherapy to be in combination with tumor resection, followed by brachytherapy as sole local therapy modality. HDR was increasingly deployed in pediatric practice, especially for genitourinary sites. Brachytherapy planning was mostly by 3D imaging based on CT. Recommendations for patient selection, treatment requirements, implant technique, delineation, dose prescription, dose reporting and clinical management were defined. CONCLUSIONS: Consensus guidelines for the use of brachytherapy in pediatric rhabdomyosarcoma have been developed through multicenter collaboration establishing the basis for future work. These have been adopted for the open EpSSG overarching study for children and adults with Frontline and Relapsed RhabdoMyoSarcoma (FaR-RMS).

Are there species smaller than 1 mm?

The rapid advance in genetic sequencing technologies has provided an unprecedented amount of data on the biodiversity of meiofauna. It was hoped that these data would allow the identification and counting of species, distinguished as tight clusters of similar genomes. Surprisingly, this appears not to be the case. Here, we begin a theoretical discussion of this phenomenon, drawing on an individual-based ecological model to inform our arguments. The determining factor in the emergence (or not) of distinguishable genetic clusters in the model is the product of population size with mutation rate-a measure of the adaptability of the population as a whole. This result suggests that indeed one should not expect to observe clearly distinguishable species groupings in data gathered from ultrasequencing of meiofauna.

Assisted percolation of slow-spreading mutants in heterogeneous environments.

Environmental heterogeneity can drive genetic heterogeneity in expanding populations; mutant strains may emerge that trade overall growth rate for an improved ability to survive in patches that are hostile to the wild type. This evolutionary dynamic is of practical importance when seeking to prevent the emergence of damaging traits. We show that a subcritical slow-spreading mutant can attain dominance even when the density of patches is below their percolation threshold and predict this transition using geometrical arguments. This work demonstrates a phenomenon of "assisted percolation", where one subcritical process assists another to achieve supercriticality.

The Role of Moderators in Facilitating and Encouraging Peer-to-Peer Support in an Online Mental Health Community: A Qualitative Exploratory Study.

Online peer support platforms have gained popularity as a potential way for people struggling with mental health problems to share information and provide support to each other. While these platforms can offer an open space to discuss emotionally difficult issues, unsafe or unmoderated communities can allow potential harm to users by spreading triggering content, misinformation or hostile interactions. The purpose of this study was to explore the role of moderators in these online communities, and how moderators can facilitate peer-to-peer support, while minimizing harms to users and amplifying potential benefits. Moderators of the Togetherall peer support platform were recruited to participate in qualitative interviews. The moderators, referred to as 'Wall Guides', were asked about their day-to-day responsibilities, positive and negative experiences they have witnessed on the platform and the strategies they employ when encountering problems such as lack of engagement or posting of inappropriate content. The data were then analyzed qualitatively using thematic content analysis and consensus codes were deduced and reviewed to reach final results and representative themes. In total, 20 moderators participated in this study, and described their experiences and efforts to follow a consistent and shared protocol for responding to common scenarios in the online community. Many reported the deep connections formed by the online community, the helpful and thoughtful responses that members give each other and the satisfaction of seeing progress in members' recovery. They also reported occasional aggressive, sensitive or inconsiderate comments and posts on the platform. They respond by removing or revising the hurtful post or reaching out to the affected member to maintain the 'house rules'. Lastly, many discussed strategies they elicit to promote engagement from members within the community and ensure each member is supported through their use of the platform. This study sheds light on the critical role of moderators of online peer support communities, and their ability to contribute to the potential benefits of digital peer support while minimizing risks to users. The findings reported here accentuate the importance of having well-trained moderators on online peer support platforms and can guide future efforts to effectively train and supervise prospective peer support moderators. Moderators can become an active 'shaping force' and bring a cohesive culture of expressed empathy, sensitivity and care. The delivery of a healthy and safe community contrasts starkly with non-moderated online forums, which can become unhealthy and unsafe as a result.

Lane nucleation in complex active flows.

Laning is a paradigmatic example of spontaneous organization in active two-component flows that has been observed in diverse contexts, including pedestrian traffic, driven colloids, complex plasmas, and molecular transport. We introduce a kinetic theory that elucidates the physical origins of laning and quantifies the propensity for lane nucleation in a given physical system. Our theory is valid in the low-density regime, and it makes different predictions about situations in which lanes may form that are not parallel with the direction of flow. We report on experiments with human crowds that verify two notable consequences of this phenomenon: tilting lanes under broken chiral symmetry and lane nucleation along elliptic, parabolic, and hyperbolic curves in the presence of sources or sinks.

Stochastic drift in discrete waves of nonlocally interacting particles.

In this paper, we investigate a generalized model of N particles undergoing second-order nonlocal interactions on a lattice. Our results have applications across many research areas, including the modeling of migration, information dynamics, and Muller's ratchet-the irreversible accumulation of deleterious mutations in an evolving population. Strikingly, numerical simulations of the model are observed to deviate significantly from its mean-field approximation even for large population sizes. We show that the disagreement between deterministic and stochastic solutions stems from finite-size effects that change the propagation speed and cause the position of the wave to fluctuate. These effects are shown to decay anomalously as (lnN)^{-2} and (lnN)^{-3}, respectively-much slower than the usual N^{-1/2} factor. Our results suggest that the accumulation of deleterious mutations in a Muller's ratchet and the loss of awareness in a population may occur much faster than predicted by the corresponding deterministic models. The general applicability of our model suggests that this unexpected scaling could be important in a wide range of real-world applications.

Spontaneous genetic clustering in populations of competing organisms.

We introduce and analyse an individual-based evolutionary model, in which a population of genetically diverse organisms compete with each other for limited resources. Through theoretical analysis and stochastic simulations, we show that the model exhibits a pattern-forming instability which is highly amplified by the effects of demographic noise, leading to the spontaneous formation of genotypic clusters. This mechanism supports the thesis that stochasticity has a central role in the formation and coherence of species.