Effects of a disease affecting a predator on the dynamics of a predator-prey system

We study the effects of a disease affecting a predator on the dynamics of a predator-prey system. We couple an SIRS model applied to the predator population, to a Lotka-Volterra model. The SIRS model describes the spread of the disease in a predator population subdivided into susceptible, infected and removed individuals. The Lotka-Volterra model describes the predator-prey interactions. We consider two time scales, a fast one for the disease and a comparatively slow one for predator-prey interactions and for predator mortality. We use the classical “aggregation method” in order to obtain a reduced equivalent model. We show that there are two possible asymptotic behaviors: either the predator population dies out and the prey tends to its carrying capacity, or the predator and prey coexist. In this latter case, the predator population tends either to a “disease-free” or to a “disease-endemic” state. Moreover, the total predator density in the disease-endemic state is greater than the predator density in the “disease-free” equilibrium (DFE).     

Delivery of substances and their target-specific topical activation

Goal in pharmaceutical research is achievement of necessary drug concentrations in the target organ, effective treatment with safe delivery of genetic agents, while sparing normal tissue and minimizing side effects. A new “BioShuttle”-delivery system harbouring a cathepsin B cutting site, a nuclear address sequence and a functional peptide was developed and tumor cells were treated. Transport and subcellular activation were determined by confocal laser scanning microscopy permitting the conclusion: BioShuttle-conjugates prove as efficient tools for genetic interventions by selective and topical activation of therapeutic peptide precursors by enzymatic cleavage. As shown here for glioma cells and the cathepsin B cleavable site, living cells can be treated with high specificity and selectivity for diagnostic and therapeutic purposes.     

Neurodegenerative disease-specific induced pluripotent stem cell research

Neurodegenerative disease-specific induced pluripotent stem cell (iPSC) research contributes to the following 3 areas; “Disease modeling”, “Disease material” and “Disease therapy”.“Disease modeling”, by recapitulating the disease phenotype in vitro, will reveal the pathomechanisms. Neurodegenerative disease-specific iPSC-derived non-neuronal cells harboring disease-causative protein(s), which play critical roles in neurodegeneration including motor neuron degeneration in amyotrophic lateral sclerosis, could be “Disease material”, the target cell(s) for drug screening. These differentiated cells also could be used for “Disease therapy”, an autologous cellular replacement/neuroprotection strategy, for patients with neurodegenerative disease.Further progress in these areas of research can be made for currently incurable neurodegenerative diseases.     

Coupling of metabolic, second messenger pathways and insulin granule dynamics in pancreatic beta-cells: a computational analysis

Insulin secretory responses to nutrient stimuli and hormonal modulators in pancreatic beta-cells are controlled by a variety of secondary messengers. We have analyzed numerous mechanisms responsible for regulated exocytosis in these cells and present an integrated mathematical model of cytosolic Ca²⁺, cAMP and granule dynamics. The insulin-containing granules in the beta-cell were divided into four classes: a large “reserve” granule pool, a smaller pool of the morphologically docked granules that is chemically ‘primed’ for release or the “readily releasable pool”, and a pool of “restless newcomer granules” that undergoes preferential exocytosis. The model incorporates glucose and other aspects of metabolism, the cAMP amplifying pathway, insulin granule dynamics and the exocyst concept for granule binding. The values of most of the model parameters were inferred from available experimental data. The model can generate both the fast first phase and slow biphasic insulin secretion found experimentally in response to a step increase of membrane potential or of glucose. The numerical simulations have also reproduced a variety of experimental conditions, such as periodic stimulation by high K⁺ and the potentiation induced in islets by pre-incubation with cAMP pathway activators. The explicit incorporation of Ca²⁺ channels, Ca²⁺ and cAMP dynamics allows the model to be further connected to current models for calcium and metabolic dynamics and provides an interpretation of the roles of the triggering and amplifying pathways of glucose-stimulated insulin secretion. The model may be important in the identification of pharmacological targets for improving insulin secretion in type 2 diabetes.     

Modeling the effect of information quality on risk behavior change and the transmission of infectious diseases

How the quality of information about the prevalence of an infectious disease affects individuals’ incentives to adopt self-protective actions to reduce the risk of infection is studied using an economic/game-theoretic model of epidemics. In the model, agents make inferences regarding the current prevalence of a disease by observing the health status of a subset of the population. Therefore, the higher the number of agents whose infection status can be observed, the better one’s information about the current prevalence is. In particular, it is assumed that an agent’s estimate of the current prevalence depends on observations of the current health status of other agents and on the agent’s estimate of past prevalence, and that the agent places more weight on the current observations in forming an estimate of the prevailing prevalence when the number of observations increases. It is shown that the likelihood of eradicating an infectious disease through behavioral changes depends critically on the amount of information that individuals have access to, which also determines whether prevalence will be relatively stable or will exhibit cyclical patterns over time. Increasing the amount of information that individuals possess may lower the likelihood of eradication.     

Metabolic setpoint control mechanisms in different physiological systems at rest and during exercise

Using a number of different homeostatic control mechanisms in the brain and peripheral physiological systems, metabolic activity is continuously regulated at rest and during exercise to prevent catastrophic system failure. Essential for the function of these regulatory processes are baseline “setpoint” levels of metabolic function, which can be used to calculate the level of response required for the maintenance of system homeostasis after system perturbation, and to which the perturbed metabolic activity levels are returned to at the end of the regulatory process. How these setpoint levels of all the different metabolic variables in the different peripheral physiological systems are created and maintained, and why they are similar in different individuals, has not been well explained. In this article, putative system regulators of metabolic setpoint levels are described. These include that: (i) innate setpoint values are stored in a certain region of the central nervous system, such as the hypothalamus; (ii) setpoint values are created and maintained as a response to continuous external perturbations, such as gravity or “zeitgebers”, (iii) setpoint values are created and maintained by complex system dynamical activity in the different peripheral systems, where setpoint levels are regulated by the ongoing feedback control activity between different peripheral variables; (iv) human anatomical and biomechanical constraints contribute to the creation and maintenance of metabolic setpoints values; or (v) a combination of all these four different mechanisms occurs. Exercise training and disease processes can affect these metabolic setpoint values, but the setpoint values are returned to pre-training or pre-disease levels if the training stimulus is removed or if the disease process is cured. Further work is required to determine what the ultimate system regulator of metabolic setpoint values is, why some setpoint values are more stringently protected by homeostatic regulatory mechanisms than others, and the role of conscious decision making processes in determining the regulation of metabolic setpoint values.     

Computational framework to understand the clinical stages of COVID-19 and visualization of time course for various treatment strategies

Coronavirus disease 2019 is known to be regulated by multiple factors such as delayed immune response, impaired T cell activation, and elevated levels of proinflammatory cytokines. Clinical management of the disease remains challenging due to interplay of various factors as drug candidates may elicit different responses depending on the staging of the disease. In this context, we propose a computational framework which provides insights into the interaction between viral infection and immune response in lung epithelial cells, with an aim of predicting optimal treatment strategies based on infection severity. First, we formulate the model for visualizing the nonlinear dynamics during the disease progression considering the role of T cells, macrophages and proinflammatory cytokines. Here, we show that the model is capable of emulating the dynamic and static data trends of viral load, T cell, macrophage levels, interleukin (IL)-6 and TNF-α levels. Second, we demonstrate the ability of the framework to capture the dynamics corresponding to mild, moderate, severe, and critical condition. Our result shows that, at late phase (>15 days), severity of disease is directly proportional to pro-inflammatory cytokine IL6 and tumor necrosis factor (TNF)-α levels and inversely proportional to the number of T cells. Finally, the simulation framework was used to assess the effect of drug administration time as well as efficacy of single or multiple drugs on patients. The major contribution of the proposed framework is to utilize the infection progression model for clinical management and administration of drugs inhibiting virus replication and cytokine levels as well as immunosuppressant drugs at various stages of the disease.     

A peptide biosensor for detecting intracellular Abl kinase activity using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry

Many cancers are characterized by changes in protein phosphorylation as a result of kinase dysregulation. Disruption of Abl kinase signaling through the Philadelphia chromosome (causing the Bcr-Abl mutation) in chronic myeloid leukemia (CML) has provided a paradigm for development of kinase inhibitor drugs such as the specific inhibitor imatinib (also known as STI571 or Gleevec). However, because patients are treated indefinitely with this drug to maintain remission, resistance is increasingly becoming an issue. Although there are many ways to detect kinase activity, most lack the ability to “multiplex” the analysis (i.e., to detect more than one substrate simultaneously). Here we report a novel biosensor for detecting Abl kinase activity and sensitivity to inhibitor in live intact cells overexpressing a CML model Abl kinase construct. This straightforward methodology could eventually provide a new tool for detecting kinase activity and inhibitor drug response in cancer cells that overexpress oncogenic kinases.     

Does predator interference cause alternative stable states in multispecies communities?

Whereas it is well known that simple ecological mechanisms may promote stability in simple species models, their consequences for stability and resilience in multispecies communities are largely unexplored. Here, we studied the effect of predator interference on the occurrence of alternative attractors and complex dynamics in randomly constructed multispecies predator-prey communities. We studied three types of interference: random interference (“asymmetric”), random interference but symmetrical between pairs of predators (“symmetric”), and interference among only the same species (“conspecific”). In all cases predator interference increased the average number of alternative attractors, whereas at the same time it reduced the emergence of oscillatory or chaotic dynamics. Our findings demonstrate a contrasting effect of predator interference on the stability of a community: on the one hand it reduces cycles and chaos in the dynamics, on the other hand predator interference increases the likelihood that communities may undergo critical transitions between multiple stable states.     

AMPK-sensed cellular energy state regulates the release of extracellular Fatty Acid Synthase

Fatty Acid Synthase (FASN), a 250-kDa cytosolic multi-enzyme catalyzing eukaryotic de novo FA biogenesis, unexpectedly localizes in cancer cell culture supernatants and in the blood of cancer patients. High levels of “extracellular FASN” have recently been found in supernatants from Hepatitis C Virus-infected liver cells. The ultimate mechanism regulating FASN release, however, remained completely undefined. When the AMPK-activating drug AICAR was used to simulate an elevated AMP/ATP ratio in breast cancer cells, ELISA-based analyses revealed that extracellular FASN dramatically augmented in a dose- and time-dependent manner. Immunoblotting procedures using a battery of anti-FASN antibodies further confirmed that, in response to AMPK activation, FASN protein is depleted from the cytosol to accumulate as different FASN isoforms in the extracellular milieu. siRNA-induced blockade of AMPK expression largely attenuated AICAR-promoted FASN release. FASN release might represent a previously unrecognized mechanism through which AMPK monitor and restores cellular energy state in response to increasing AMP/ATP ratios.     

Modelling the policy and economic context for detection- based monitoring tools: the costs and benefits of detecting last survivors and first re-colonisers

Establishing and maintaining the success of pest or weed eradication programmes requires interpretation of failures to detect survivors and first re-colonisers. Recent developments provide statistical frameworks that allow sequences of such failures to be interpreted in a probabilistic context. For example, application of these methods allow managers of eradication programmes to decide a priori an acceptable risk of programme failure, and to use this decision to design monitoring regimes that deliver this level of certainty, given the detection characteristics of the search techniques at their disposal. Similar methods could be use to design monitoring regimes to detect an incursion by a previously eradicated species (i.e. an eradication breakdown), which have an acceptable risk of failure. However, the availability of these methods begs questions about how “acceptable” risks of eradication failure or breakdown should be specified, and the consequent effort that should be expended to locate last survivors and first re- colonisers. We use a risk-based bioeconomic framework to model and analyse these decisions. The analysis demonstrates critical trade-offs between the cost and efficacy of the detection techniques available, the “value” of the eradication programme, and the perceived risk that a breakdown can occur. While our focus is on island pest eradication, we suggest how the bioeconomic framework used could be usefully applied to the detection of rare, at risk species, and the management of sporadically frequent diseases.     

Chemotherapy of vascularised tumours: Role of vessel density and the effect of vascular “pruning”

In this work we propose to model chemotherapy taking into account the mutual interaction between tumour growth and the development of tumour vasculature. By adopting a simple model for this interaction, and assuming that the efficacy of a drug can be modulated by the vessel density, we study the constant continuous therapy, the periodic bolus-based therapy, and combined therapy in which a chemotherapic drug is associated with an anti-angiogenic agent. The model allows to represent the vessel-disrupting activity of some standard chemotherapic drugs, and shows, in the case of constant continuous drug administration, the possibility of multiple stable equilibria. The multistability suggests an explanation for some sudden losses of control observed during therapy, and for the beneficial effect of vascular “pruning” exerted by anti-angiogenic agents in combined therapy. Moreover, in case of periodic therapies in which the drug amount administered per unit time is constant (“metronomic” delivery), the model predicts a response, as a function of the bolus frequency, significantly influenced by the extent of the anti-angiogenic activity of the chemotherapic drug and by the dependence of the drug efficacy on the vessel density.     

A mathematical model to study the effects of drugs administration on tumor growth dynamics

A mathematical model for describing the cancer growth dynamics in response to anticancer agents administration in xenograft models is discussed. The model consists of a system of ordinary differential equations involving five parameters (three for describing the untreated growth and two for describing the drug action). Tumor growth in untreated animals is modelled by an exponential growth followed by a linear growth. In treated animals, tumor growth rate is decreased by an additional factor proportional to both drug concentration and proliferating cells. The mathematical analysis conducted in this paper highlights several interesting properties of this tumor growth model. It suggests also effective strategies to design in vivo experiments in animals with potential saving of time and resources. For example, the drug concentration threshold for the tumor eradication, the delay between drug administration and tumor regression, and a time index that measures the efficacy of a treatment are derived and discussed. The model has already been employed in several drug discovery projects. Its application on a data set coming from one of these projects is discussed in this paper.     

Optimal control for pandemic influenza: The role of limited antiviral treatment and isolation

The implementation of optimal control strategies involving antiviral treatment and/or isolation measures can reduce significantly the number of clinical cases of influenza. Pandemic-level control measures must be carefully assessed specially in resource-limited situations. A model for the transmission dynamics of influenza is used to evaluate the impact of isolation and/or antiviral drug delivery measures during an influenza pandemic. Five pre-selected control strategies involving antiviral treatment and isolation are tested under the “unlimited” resource assumption followed by an exploration of the impact of these “optimal” policies when resources are limited in the context of a 1918-type influenza pandemic scenario. The implementation of antiviral treatment at the start of a pandemic tends to reduce the magnitude of epidemic peaks, spreading the maximal impact of an outbreak over an extended window in time. Hence, the controls’ timing and intensity can reduce the pressures placed on the health care infrastructure by a pandemic reducing the stress put on the system during epidemic peaks. The role of isolation strategies is highlighted in this study particularly when access to antiviral resources is limited.     

ErbBs in lung cancer

Lung cancer remains the leading cause of cancer deaths worldwide, and advanced stage disease is largely refractory to conventional chemotherapy. Thus, there is an important need for alternative treatment strategies, and the ErbB proteins have emerged as potentially important therapeutic drug targets in this setting, apparently reflecting a state of “oncogene addiction” in some lung tumors. In this review, we discuss the recent identification of mutations that promote activation of ErbB family proteins in a subset of lung cancers, and the development of selective inhibitors of these proteins that have demonstrated clinical efficacy. We also discuss the problem of drug resistance, which severely limits the clinical utility of such agents, and has prompted intense efforts to better understand molecular mechanisms underlying drug resistance as well as strategies to overcome or prevent such resistance.     

A “Krokodil” emerges from the murky waters of addiction. Abuse trends of an old drug

“Krokodil” is the street name for the semi-synthetic opioid derivative desomorphine. Although an old drug, it re-staged on “drug arena” during the last decade causing detrimental effects to its users. Despite the fact that Russia and other former Soviet Republics were the initial plagued countries, “krokodil” arrived in Europe and United States lately, as a substitute of the relative expensive, and in many cases unavailable, heroin. It can be easily manufactured in home-environment from codeine and causes significant health problems, even deaths worldwide. The aim of this review is to summarize the current knowledge about this drug, concerning its chemistry, synthesis, pharmacology and toxicology. Published or reported “krokodil” related cases, fatalities or intoxications, as well as self reports from drug users are reviewed. The existing analytical methodologies for the determination of desomorphine in biological samples as well as its legal status are also presented.     

Ampelozyziphus amazonicus Ducke (Rhamnaceae), a medicinal plant used to prevent malaria in the Amazon Region, hampers the development of Plasmodium berghei sporozoites

Most medicinal plants used against malaria in endemic areas aim to treat the acute symptoms of the disease such as high temperature fevers with periodicity and chills. In some endemic areas of the Brazilian Amazon region one medicinal plant seems to be an exception: Ampelozyziphus amazonicus, locally named “Indian beer” or “Saracura-mira”, used to prevent the disease when taken daily as a cold suspension of powdered dried roots. In previous work we found no activity of the plant extracts against malaria blood parasites in experimentally infected animals (mice and chickens) or in cultures of Plasmodium falciparum. However, in infections induced by sporozoites, chickens treated with plant extracts were partially protected against Plasmodium gallinaceum and showed reduced numbers of exoerythrocytic forms in the brain. We now present stronger evidence that the ethanolic extract of “Indian beer” roots hampers in vitro and in vivo development of Plasmodium berghei sporozoites, a rodent malaria parasite. Some mice treated with high doses of the plant extract did not become infected after sporozoite inoculation, whereas others had a delayed prepatent period and lower parasitemia. Our data validates the use of “Indian beer” as a remedy for malaria prophylaxis in the Amazon, where the plant exists and the disease represents an important problem which is difficult to control. Studies aiming to identify the active compounds responsible for the herein described causal prophylactic activity are needed and may lead to a new antimalarial prophylactic.     

The hidden variables of leadership

The dynamics of a collective move can be untangled into three components: initiation, following and cancellation. Varying the response function parameters attached to one individual can switch the collective phenomenology from an absence of well identified leader (“distributed leadership”) to the emergence of a “despotic regime”, i.e. this individual leading more often the collective moves. I show that not all parameters have the same impact but rather that only a large increase of the initiation rate can empower an obvious leader, up to the “despotic” regime. Being more readily followed, or cancelling less often can enhance the leader's prominence only up to a limited level. To overtake this limit would then further require to affect also the parameters attached to the others (e.g. to lower their eagerness to initiate group motion as well as their probability to be followed when they do).     

Immuno-PCR assays for immunogenicity testing

The administration of therapeutic proteins often induces immunogenic response and thus formation of anti-drug antibodies (ADA), which can neutralize the drug’s therapeutic effect and may even cause serious health problems. We here report on the employment of the ultra-sensitive immuno-PCR (IPCR) method to facilitate immunogenicity testing using two established assay formats. In a “bridging assay”, in which ADA forms a bridge to immobilize a signal-generating drug reporter probe, IPCR detection enabled an at least 1000-fold increase in sensitivity, as compared to the analogous ELISA, along with a high drug tolerance value. Moreover, we demonstrate that interfering effects of the biological matrix can be omitted by a simple dilution of analytical samples without loss in assay performance. In a cell-free “neutralizing assay”, in which a labeled drug reporter probe competes for binding to either surface-bound receptors or neutralizing ADA, the IPCR assay also revealed high sensitivity. These results suggest that IPCR has the potential to become a standard methodology in immunogenicity testing.     

Protons @ interfaces: Implications for biological energy conversion

The review focuses on the anisotropy of proton transfer at the surface of biological membranes. We consider (i) the data from “pulsed” experiments, where light-triggered enzymes capture or eject protons at the membrane surface, (ii) the electrostatic properties of water at charged interfaces, and (iii) the specific structural attributes of proton-translocating enzymes. The pulsed experiments revealed that proton exchange between the membrane surface and the bulk aqueous phase takes as much as about 1 ms, but could be accelerated by added mobile pH-buffers. Since the accelerating capacity of the latter decreased with the increase in their electric charge, it was concluded that the membrane surface is separated from the bulk aqueous phase by a barrier of electrostatic nature. The barrier could arise owing to the water polarization at the negatively charged membrane surface. The barrier height depends linearly on the charge of penetrating ions; for protons, it has been estimated as about 0.12 eV. While the proton exchange between the surface and the bulk aqueous phase is retarded by the interfacial barrier, the proton diffusion along the membrane, between neighboring enzymes, takes only microseconds. The proton spreading over the membrane is facilitated by the hydrogen-bonded networks at the surface. The membrane-buried layers of these networks can eventually serve as a storage/buffer for protons (proton sponges). As the proton equilibration between the surface and the bulk aqueous phase is slower than the lateral proton diffusion between the “sources” and “sinks”, the proton activity at the membrane surface, as sensed by the energy transducing enzymes at steady state, might deviate from that measured in the adjoining water phase. This trait should increase the driving force for ATP synthesis, especially in the case of alkaliphilic bacteria.