New Development in Understanding Drug-Polymer Interactions in Pharmaceutical Amorphous Solid Dispersions from Solid-State Nuclear Magnetic Resonance.

Pharmaceutical amorphous solid dispersions (ASDs) represent a widely used technology to increase the bioavailability of active pharmaceutical ingredients (APIs). ASDs are based on an amorphous API dispersed in a polymer, and their stability is driven by the presence of strong intermolecular interactions between these two species (e.g., hydrogen bond, electrostatic interactions, etc.). The understanding of these interactions at the atomic level is therefore crucial, and solid-state nuclear magnetic resonance (NMR) has demonstrated itself as a very powerful technique for probing API-polymer interactions. Other reviews have also reported exciting approaches to study the structures and dynamic properties of ASDs and largely focused on the study of API-polymer miscibility and on the identification of API-polymer interactions. Considering the increased use of NMR in the field, the aim of this Review is to specifically highlight recent experimental strategies used to identify API-polymer interactions and report promising recent examples using one-dimensional (1D) and two-dimensional (2D) experiments by exploiting the following emerging approaches of very-high magnetic field and ultrafast magic angle spinning (MAS). A range of different ASDs spanning APIs and polymers with varied structural motifs is targeted to illustrate new ways to understand the mechanism of stability of ASDs to enable the design of new dispersions.

Drug-Polymer Interactions in Acetaminophen/Hydroxypropylmethylcellulose Acetyl Succinate Amorphous Solid Dispersions Revealed by Multidimensional Multinuclear Solid-State NMR Spectroscopy.

The bioavailability of insoluble crystalline active pharmaceutical ingredients (APIs) can be enhanced by formulation as amorphous solid dispersions (ASDs). One of the key factors of ASD stabilization is the formation of drug-polymer interactions at the molecular level. Here, we used a range of multidimensional and multinuclear nuclear magnetic resonance (NMR) experiments to identify these interactions in amorphous acetaminophen (paracetamol)/hydroxypropylmethylcellulose acetyl succinate (HPMC-AS) ASDs at various drug loadings. At low drug loading (<20 wt %), we showed that 1H-13C through-space heteronuclear correlation experiments identify proximity between aromatic protons in acetaminophen with cellulose backbone protons in HPMC-AS. We also show that 14N-1H heteronuclear multiple quantum coherence (HMQC) experiments are a powerful approach in probing spatial interactions in amorphous materials and establish the presence of hydrogen bonds (H-bond) between the amide nitrogen of acetaminophen with the cellulose ring methyl protons in these ASDs. In contrast, at higher drug loading (40 wt %), no acetaminophen/HPMC-AS spatial proximity was identified and domains of recrystallization of amorphous acetaminophen into its crystalline form I, the most thermodynamically stable polymorph, and form II are identified. These results provide atomic scale understanding of the interactions in the acetaminophen/HPMC-AS ASD occurring via H-bond interactions.

Modeling the effect of immunotherapies on human castration-resistant prostate cancer.

In this paper we analyze the potential effect of immunotherapies on castration-resistant form of human Prostate Cancer (PCa). In particular, we examine the potential effect of the dendritic vaccine sipuleucel-T, the only currently available immunotherapy option for advanced PCa, and of ipilimumab, a drug targeting the Cytotoxic T-Lymphocyte Antigen 4 (CTLA4), exposed on the CTLs membrane, currently under Phase II clinical trial. The model, building on the one by Rutter and Kuang, includes different types of immune cells and interactions and is parameterized on available data. Our results show that the vaccine has only a very limited effect on PCa, while repeated treatments with ipilimumab appear potentially capable of controlling and even eradicating an androgen-independent prostate cancer. From a mathematical analysis of a simplified model, it seems likely that, under continuous administration of ipilimumab, the system lies in a bistable situation where both the no-tumor equilibrium and the high-tumor equilibrium are attractive. The schedule of periodic treatments could then determine the outcome, and mathematical models could help determine an optimal schedule.

Modelling Immune Memory Development.

The cellular adaptive immune response to influenza has been analyzed through several recent mathematical models. In particular, Zarnitsyna et al. (Front Immunol 7:1-9, 2016) show how central memory CD8+ T cells reach a plateau after repeated infections, and analyze their role in the immune response to further challenges. In this paper, we further investigate the theoretical features of that model by extracting from the infection dynamics a discrete map that describes the build-up of memory cells. Furthermore, we show how the model by Zarnitsyna et al. (Front Immunol 7:1-9, 2016) can be viewed as a fast-scale approximation of a model allowing for recruitment of target epithelial cells. Finally, we analyze which components of the model are essential to understand the progressive build-up of immune memory. This is performed through the analysis of simplified versions of the model that include some components only of immune response. The analysis performed may also provide a theoretical framework for understanding the conditions under which two-dose vaccination strategies can be helpful.

Evolutionary dynamics in an SI epidemic model with phenotype-structured susceptible compartment.

We present an SI epidemic model whereby a continuous structuring variable captures variability in proliferative potential and resistance to infection among susceptible individuals. The occurrence of heritable, spontaneous changes in these phenotypic characteristics and the presence of a fitness trade-off between resistance to infection and proliferative potential are explicitly incorporated into the model. The model comprises an ordinary differential equation for the number of infected individuals that is coupled with a partial integrodifferential equation for the population density function of susceptible individuals through an integral term. The expression for the basic reproduction number [Formula: see text] is derived, the disease-free equilibrium and endemic equilibrium of the model are characterised and a threshold theorem involving [Formula: see text] is proved. Analytical results are integrated with the results of numerical simulations of a calibrated version of the model based on the results of artificial selection experiments in a host-parasite system. The results of our mathematical study disentangle the impact of different evolutionary parameters on the spread of infectious diseases and the consequent phenotypic adaption of susceptible individuals. In particular, these results provide a theoretical basis for the observation that infectious diseases exerting stronger selective pressures on susceptible individuals and being characterised by higher infection rates are more likely to spread. Moreover, our results indicate that heritable, spontaneous phenotypic changes in proliferative potential and resistance to infection can either promote or prevent the spread of infectious diseases depending on the strength of selection acting on susceptible individuals prior to infection. Finally, we demonstrate that, when an endemic equilibrium is established, higher levels of resistance to infection and lower degrees of phenotypic heterogeneity among susceptible individuals are to be expected in the presence of infections which are characterised by lower rates of death and exert stronger selective pressures.

A geometric analysis of the SIRS epidemiological model on a homogeneous network.

We study a fast-slow version of an SIRS epidemiological model on homogeneous graphs, obtained through the application of the moment closure method. We use GSPT to study the model, taking into account that the infection period is much shorter than the average duration of immunity. We show that the dynamics occurs through a sequence of fast and slow flows, that can be described through 2-dimensional maps that, under some assumptions, can be approximated as 1-dimensional maps. Using this method, together with numerical bifurcation tools, we show that the model can give rise to periodic solutions, differently from the corresponding model based on homogeneous mixing.

Solid state nuclear magnetic resonance studies of hydroxypropylmethylcellulose acetyl succinate polymer, a useful carrier in pharmaceutical solid dispersions.

Hydroxypropylmethylcellulose (HPMC) acetyl succinate (HPMC-AS) is a key polymer used for the enablement of amorphous solid dispersions (ASDs) in oral solid dosage forms. Choice of the appropriate grade within the material is often made empirically by the manufacturer of small-scale formulations, followed by extensive real time stability. A key factor in understanding and predicting the performance of an ASD is related to the presence of hydrogen (or other) bonds between the polymer and active pharmaceutical ingredient (API), which will increase stability over the parameters captured by miscibility and predicted by the Gordon-Taylor equation. Solid state nuclear magnetic resonance (NMR) is particularly well equipped to probe spatial proximities, for example, between polymer and API; however, in the case of HPMC-AS, these interactions have been sometimes difficult to identity as the carbon-13 NMR spectra assignment is yet to be firmly established. Using feedstock, selectively substituted HPMC polymers, and NMR editing experiments, we propose here a comprehensive understanding of the chemical structure of HPMC-AS and a definitive spectral assignment of the 13 C NMR spectra of this polymer. The NMR data also capture the molar ratios of the acetate and succinate moieties present in HPMC-AS of various grades without the need for post treatment required by chromatography methods commonly use in pharmacopoeia. This knowledge will allow the prediction and measurement of interactions between polymers and APIs and therefore a rational choice of polymer grade to enhance the solid state stability of ASDs.

Spectral deconvolution in electrophoretic NMR to investigate the migration of neutral molecules in electrolytes.

Electrophoretic nuclear magnetic resonance (eNMR) is a powerful tool in studies of nonaqueous electrolytes, such as ionic liquids. It delivers electrophoretic mobilities of the ionic constituents and thus sheds light on ion correlations. In applications of liquid electrolytes, uncharged additives are often employed, detectable via 1 H NMR. Characterizing their mobility and coordination to charged entities is desirable; however, it is often hampered by small intensities and 1 H signals overlapping with major constituents of the electrolyte. In this work, we evaluate methods of phase analysis of overlapping resonances to yield electrophoretic mobilities even for minor constituents. We use phase-sensitive spectral deconvolution via a set of Lorentz distributions for the investigation of the migration behavior of additives in two different ionic liquid-based lithium salt electrolytes. For vinylene carbonate as an additive, no field-induced drift is observed; thus, its coordination to the Li+ ion does not induce a correlated drift with Li+ . On the other hand, in a solvate ionic liquid with tetraglyme (G4) as an additive, a correlated migration of tetraglyme with lithium as a complex solvate cation is directly proven by eNMR. The phase evaluation procedure of superimposed resonances thus broadens the applicability of eNMR to application-relevant complex electrolyte mixtures containing neutral additives with superimposed resonances.

A structured population model with diffusion in structure space.

A structured population model is described and analyzed, in which individual dynamics is stochastic. The model consists of a PDE of advection-diffusion type in the structure variable. The population may represent, for example, the density of infected individuals structured by pathogen density x, [Formula: see text]. The individuals with density [Formula: see text] are not infected, but rather susceptible or recovered. Their dynamics is described by an ODE with a source term that is the exact flux from the diffusion and advection as [Formula: see text]. Infection/reinfection is then modeled moving a fraction of these individuals into the infected class by distributing them in the structure variable through a probability density function. Existence of a global-in-time solution is proven, as well as a classical bifurcation result about equilibrium solutions: a net reproduction number [Formula: see text] is defined that separates the case of only the trivial equilibrium existing when [Formula: see text] from the existence of another-nontrivial-equilibrium when [Formula: see text]. Numerical simulation results are provided to show the stabilization towards the positive equilibrium when [Formula: see text] and towards the trivial one when [Formula: see text], result that is not proven analytically. Simulations are also provided to show the Allee effect that helps boost population sizes at low densities.

Multiple coexistence equilibria in a two parasitoid-one host model.

Briggs et al. (1993) introduced a host-parasitoid model for the dynamics of a system with two parasitoids that attack different juvenile stages of a common host. Their main result was that coexistence of the parasitoids is only possible when there is sufficient variability in the maturation delays of the host juvenile stages. Here, we analyze the phenomenon of coexistence in that model more deeply. We show that with some distribution families for the maturation delays, the coexistence equilibrium is unique, while with other distributions multiple coexistence equilibria can be found. In particular, we find that stable coexistence does not necessarily require mutual invasibility.

Exploring vector-borne infection ecology in multi-host communities: A case study of West Nile virus.

In this study, we develop a model to investigate how ecological factors might affect the dynamics of a vector-borne pathogen in a population composed by different hosts which interact with each other. Specifically, we consider the case when different host species compete with each other, as they share the same habitat, and the vector might have different feeding preference, which can also be time dependent. As a prototypical example, we apply our model to study the invasion and spread, during a typical season, of West Nile virus in an ecosystem composed of two competent avian host species and possibly of dead-end host species. We found that competition and vector feeding preferences can profoundly influence pathogen invasion, influencing its probability to start an epidemic, and influencing transmission rates. Finally, when considering time-dependent feeding preferences, as observed in the field, we noted that the virus circulation could be amplified and that the timing of epidemic peaks could be changed. Our work highlights that ecological interactions between hosts can have a profound influence on the dynamics of the pathogen and that, when modeling vector-borne infections, vector feeding behavior should, for this reason, be carefully evaluated.

Host coexistence in a model for two host-one parasitoid interactions.

Building from a continuous-time host-parasitoid model introduced by Murdoch et al. (Am Nat 129:263-282, 1987), we study the dynamics of a 2 host-parasitoid model assuming, for the sake of simplicity, that larval stages have a fixed duration. If each host is subjected to density-dependent mortality in its larval stage, we obtain explicit conditions for the existence of an equilibrium where the two host species coexist with the parasitoid. However, if host demography is density-independent, equilibrium coexistence is impossible. If at least one of the 1 host-parasitoid systems has an oscillatory dynamics (which happens under some parameter values), we found, through numerical bifurcation, that coexistence is favoured. Coexistence between the two hosts may occur along a periodic solution even without density-dependence. Models of this type may be relevant for the use of parasitoids as biocontrol agents of insect pests.

RiboAbacus: a model trained on polyribosome images predicts ribosome density and translational efficiency from mammalian transcriptomes.

Fluctuations in mRNA levels only partially contribute to determine variations in mRNA availability for translation, producing the well-known poor correlation between transcriptome and proteome data. Recent advances in microscopy now enable researchers to obtain high resolution images of ribosomes on transcripts, providing precious snapshots of translation in vivo. Here we propose RiboAbacus, a mathematical model that for the first time incorporates imaging data in a predictive model of transcript-specific ribosome densities and translational efficiencies. RiboAbacus uses a mechanistic model of ribosome dynamics, enabling the quantification of the relative importance of different features (such as codon usage and the 5' ramp effect) in determining the accuracy of predictions. The model has been optimized in the human Hek-293 cell line to fit thousands of images of human polysomes obtained by atomic force microscopy, from which we could get a reference distribution of the number of ribosomes per mRNA with unmatched resolution. After validation, we applied RiboAbacus to three case studies of known transcriptome-proteome datasets for estimating the translational efficiencies, resulting in an increased correlation with corresponding proteomes. RiboAbacus is an intuitive tool that allows an immediate estimation of crucial translation properties for entire transcriptomes, based on easily obtainable transcript expression levels.

One-Pot Multi-Enzymatic Synthesis of the Four Stereoisomers of 4-Methylheptan-3-ol.

The use of pheromones in the integrated pest management of insects is currently considered a sustainable and environmentally benign alternative to hazardous insecticides. 4-Methylheptan-3-ol is an interesting example of an insect pheromone, because its stereoisomers are active towards different species. All four possible stereoisomers of this compound were prepared from 4-methylhept-4-en-3-one by a one-pot procedure in which the two stereogenic centres were created during two sequential reductions catalysed by an ene-reductase (ER) and an alcohol dehydrogenase (ADH), respectively.

Perspectives on optimal control of varicella and herpes zoster by mass routine varicella vaccination.

Herpes zoster arises from reactivation of the varicella-zoster virus (VZV), causing varicella in children. As reactivation occurs when cell-mediated immunity (CMI) declines, and there is evidence that re-exposure to VZV boosts CMI, mass varicella immunization might increase the zoster burden, at least for some decades. Fear of this natural zoster boom is the main reason for the paralysis of varicella immunization in Europe. We apply optimal control to a realistically parametrized age-structured model for VZV transmission and reactivation to investigate whether feasible varicella immunization paths that are optimal in controlling both varicella and zoster exist. We analyse the optimality system numerically focusing on the role of the cost functional, of the relative zoster-varicella cost and of the planning horizon length. We show that optimal programmes will mostly be unfeasible for public health owing to their complex temporal profiles. This complexity is the consequence of the intrinsically antagonistic nature of varicella immunization programmes when aiming to control both varicella and zoster. However, we show that gradually increasing-hence feasible-vaccination schedules can perform better than routine programmes with constant vaccine uptake. Finally, we show the optimal profiles of feasible programmes targeting mitigation of the post-immunization natural zoster boom with priority.

Estimating transmission probability in schools for the 2009 H1N1 influenza pandemic in Italy.

BACKGROUND: Epidemic models are being extensively used to understand the main pathways of spread of infectious diseases, and thus to assess control methods. Schools are well known to represent hot spots for epidemic spread; hence, understanding typical patterns of infection transmission within schools is crucial for designing adequate control strategies. The attention that was given to the 2009 A/H1N1pdm09 flu pandemic has made it possible to collect detailed data on the occurrence of influenza-like illness (ILI) symptoms in two primary schools of Trento, Italy. RESULTS: The data collected in the two schools were used to calibrate a discrete-time SIR model, which was designed to estimate the probabilities of influenza transmission within the classes, grades and schools using Markov Chain Monte Carlo (MCMC) methods. We found that the virus was mainly transmitted within class, with lower levels of transmission between students in the same grade and even lower, though not significantly so, among different grades within the schools. We estimated median values of R 0 from the epidemic curves in the two schools of 1.16 and 1.40; on the other hand, we estimated the average number of students infected by the first school case to be 0.85 and 1.09 in the two schools. CONCLUSIONS: The discrepancy between the values of R 0 estimated from the epidemic curve or from the within-school transmission probabilities suggests that household and community transmission played an important role in sustaining the school epidemics. The high probability of infection between students in the same class confirms that targeting within-class transmission is key to controlling the spread of influenza in school settings and, as a consequence, in the general population.

Epidemic dynamics and host immune response: a nested approach.

This paper proposes an approach for building epidemiological models that incorporate the intra-host pathogen-immunity dynamics. The infected population is structured in terms of pathogen load and level of immunity, and the initial infection load may depend on the load of the individual from whom the infection is acquired. In particular, we focus on the case in which the initial inoculum is taken proportional to the load of the infectant. Possible reinfections are disregarded. Such an approach is applied to formulate an epidemic model with isolation in a closed population by introducing a specific intra-host dynamics. A numerical scheme for the solution of model equations is developed, and some numerical results illustrating the role of the initial inoculum, of the isolation threshold and of the pathogen dynamics on the epidemic evolution are presented. From the simulations the distributions of latency, infectivity, and isolation times can be also derived; however the predictions of the present models differ qualitatively from those of traditional SEIHR models with distributed latency, infectivity and isolation periods.

School closures during the 2009 influenza pandemic: national and local experiences.

BACKGROUND: School closure is a non-pharmaceutical intervention that was considered in many national pandemic plans developed prior to the start of the influenza A(H1N1)pdm09 pandemic, and received considerable attention during the event. Here, we retrospectively review and compare national and local experiences with school closures in several countries during the A(H1N1)pdm09 pandemic. Our intention is not to make a systematic review of country experiences; rather, it is to present the diversity of school closure experiences and provide examples from national and local perspectives. METHODS: Data were gathered during and following a meeting, organized by the European Centres for Disease Control, on school closures held in October 2010 in Stockholm, Sweden. A standard data collection form was developed and sent to all participants. The twelve participating countries and administrative regions (Bulgaria, China, France, Hong Kong Special Administrative Region (SAR), Italy, Japan, New Zealand, Serbia, South Africa, Thailand, United Kingdom, and United States) provided data. RESULTS: Our review highlights the very diverse national and local experiences on school closures during the A(H1N1)pdm09 pandemic. The processes including who was in charge of making recommendations and who was in charge of making the decision to close, the school-based control strategies, the extent of school closures, the public health tradition of responses and expectations on school closure varied greatly between countries. Our review also discusses the many challenges associated with the implementation of this intervention and makes recommendations for further practical work in this area. CONCLUSIONS: The single most important factor to explain differences observed between countries may have been the different public health practises and public expectations concerning school closures and influenza in the selected countries.

Declarative Logic-Based Pareto-Optimal Agent Decision Making.

There are many applications where an autonomous agent can perform many sets of actions. It must choose one set of actions based on some behavioral constraints on the agent. Past work has used deontic logic to declaratively express such constraints in logic, and developed the concept of a feasible status set (FSS), a set of actions that satisfy these constraints. However, multiple FSSs may exist and an agent needs to choose one in order to act. As there may be many different objective functions to evaluate status sets, we propose the novel concept of Pareto-optimal FSSs or . We show that checking if a status set is a is co-NP-hard. We develop an algorithm to find a and in special cases when the objective functions are monotonic (or anti-monotonic), we further develop more efficient algorithms. Finally, we conduct experiments to show the efficacy of our approach and we discuss possible ways to handle multiple Pareto-optimal Status Sets.

Estimating the potential risk of transmission of arboviruses in the Americas and Europe: a modelling study.

BACKGROUND: Estimates of the spatiotemporal distribution of different mosquito vector species and the associated risk of transmission of arboviruses are key to design adequate policies for preventing local outbreaks and reducing the number of human infections in endemic areas. In this study, we quantified the abundance of Aedes albopictus and Aedes aegypti and the local transmission potential for three arboviral infections at an unprecedented spatiotemporal resolution in areas where no entomological surveillance is available. METHODS: We developed a computational model to quantify the daily abundance of Aedes mosquitoes, leveraging temperature and precipitation records. The model was calibrated on mosquito surveillance data collected in 115 locations in Europe and the Americas between 2007 and 2018. Model estimates were used to quantify the reproduction number of dengue virus, Zika virus, and chikungunya in Europe and the Americas, at a high spatial resolution. FINDINGS: In areas colonised by both Aedes species, A aegypti was estimated to be the main vector for the transmission of dengue virus, Zika virus, and chikungunya, being associated with a higher estimate of R0 when compared with A albopictus. Our estimates highlighted that these arboviruses were endemic in tropical and subtropical countries, with the highest risks of transmission found in central America, Venezuela, Colombia, and central-east Brazil. A non-negligible potential risk of transmission was also estimated for Florida, Texas, and Arizona (USA). The broader ecological niche of A albopictus could contribute to the emergence of chikungunya outbreaks and clusters of dengue autochthonous cases in temperate areas of the Americas, as well as in mediterranean Europe (in particular, in Italy, southern France, and Spain). INTERPRETATION: Our results provide a comprehensive overview of the transmission potential of arboviral diseases in Europe and the Americas, highlighting areas where surveillance and mosquito control capacities should be prioritised. FUNDING: EU and Ministero dell'Università e della Ricerca, Italy (Piano Nazionale di Ripresa e Resilienza Extended Partnership initiative on Emerging Infectious Diseases); EU (Horizon 2020); Ministero dell'Università e della Ricerca, Italy (Progetti di ricerca di Rilevante Interesse Nazionale programme); Brazilian National Council of Science, Technology and Innovation; Ministry of Health, Brazil; and Foundation of Research for Minas Gerais, Brazil.