Model-based design of experiments in the presence of structural model uncertainty: an extended information matrix approach

The identification of a parametric model, once a suitable model structure is proposed, requires the estimation of its non-measurable parameters. Model-based design of experiment (MBDoE) methods have been proposed in the literature for maximising the collection of information whenever there is a limited amount of resources available for conducting the experiments. Conventional MBDoE methods do not take into account the structural uncertainty on the model equations and this may lead to a substantial miscalculation of the information in the experimental design stage. In this work, an extended formulation of the Fisher information matrix is proposed as a metric of information accounting for model misspecification. The properties of the extended Fisher information matrix are presented and discussed with the support of two simulated case studies

Closed-Loop Model-Based Design of Experiments for Kinetic Model Discrimination and Parameter Estimation: Benzoic Acid Esterification on a Heterogeneous Catalyst

An autonomous reactor platform was developed to rapidly identify a kinetic model for the esterification of benzoic acid with ethanol with the heterogeneous Amberlyst-15 catalyst. A five-step methodology for kinetic studies was employed to systematically reduce the number of experiments required to identify a practical kinetic model. This included (i) initial screening using traditional factorial designed steady-state experiments, (ii) proposing and testing candidate kinetic models, (iii) performing an identifiability analysis to reject models whose model parameters cannot be estimated for a given experimental budget, (iv) performing online Model-Based Design of Experiments (MBDoE) for model discrimination to identify the best model from a list of candidates, and (v) performing online MBDoE for improving parameter precision for the chosen model. This methodology combined with the reactor platform, which conducted all kinetic experiments unattended, reduces the number of experiments and time required to identify kinetic models, significantly increasing lab productivity

IR ion spectroscopy in a combined approach with MS/MS and IM-MS to discriminate epimeric anthocyanin glycosides (cyanidin 3-O-glucoside and -galactoside)

Anthocyanins are widespread in plants and flowers, being responsible for their different colouring. Two representative members of this family have been selected, cyanidin 3-O-β-glucopyranoside and 3-O-β-galactopyranoside, and probed by mass spectrometry based methods, testing their performance in discriminating between the two epimers. The native anthocyanins, delivered into the gas phase by electrospray ionization, display a comparable drift time in ion mobility mass spectrometry (IM-MS) and a common fragment, corresponding to loss of the sugar moiety, in their collision induced dissociation (CID) pattern. However, the IR multiple photon dissociation (IRMPD) spectra in the fingerprint range show a feature particularly evident in the case of the glucoside. This signature is used to identify the presence of cyanidin 3-O-β-glucopyranoside in a natural extract of pomegranate. In an effort to increase any differentiation between the two epimers, aluminum complexes were prepared and sampled for elemental composition by FT-ICR-MS. CID experiments now display an extensive fragmentation pattern, showing few product ions peculiar to each species. More noteworthy is the IRMPD behavior in the OH stretching range showing significant differences in the spectra of the two epimers. DFT calculations allow to interpret the observed distinct bands due to a varied network of hydrogen bonding and relative conformer stability

Viral nervous necrosis outbreaks caused by the RGNNV/SJNNV reassortant betanodavirus in gilthead sea bream (Sparus aurata) and European sea bass (Dicentrarchus labrax)

Mediterranean marine aquaculture has suffered significant economic losses due to viral nervous necrosis (VNN) outbreaks mainly caused by different RGNNV betanodavirus strains. In recent years, the marine aquaculture sector has experienced the emergence of the RGNNV/SJNNV reassortant betanodavirus, harbouring the RNA1 segment of RGNNV genotype and the RNA2 segment of SJNNV genotype. So far, the reassortant strains caused massive mortality outbreaks in gilthead sea bream (Sparus aurata) larvae sparing the European sea bass (Dicentrarchus labrax). In this study, multiple mortality outbreaks occurred in one Italian marine hatchery involving both European sea bass and gilthead sea bream at different life stages were investigated through a complete microbiological and molecular analysis. Gilthead sea bream larvae and juveniles have recorded the highest mortality rates, however, both European sea bass and gilthead sea bream incurred a RGNNV/SJNNV reassortant betanodavirus persistent infection, able to act as asymptomatic carriers and viral source for susceptible fish. These new epidemiological data on nervous necrosis virus (NNV) reassortant infection provide precious advice on how to manage fish to reduce VNN spread in Mediterranean aquaculture. Evidence of interspecies transmission of RGNNV/SJNNV reassortant strains and the persistent infection in both European sea bass and gilthead sea bream, point out the importance to enforce a wide surveillance and a strict biosecurity programme addressing both RGNNV and reassortant RGNNV/SJNNV betanodaviruses in Mediterranean European sea bass and gilthead sea bream farms. Furthermore, the presence assessment of betanoviruses in all newly-introduced fish batches in the farm, regardless of the species and a strict segregation between European sea bass and gilthead sea bream batches within farms can significantly reduce the risk of NNV transmission. Finally, surviving fish can act as carrier fish, and thereby must be segregated from other batches and protected from stress conditions that could trigger a new clinical phase

A model-based data mining approach for determining the domain of validity of approximated models

Parametric models derived from simplifying modelling assumptions give an approximated description of the physical system under study. The value of an approximated model depends on the consciousness of its descriptive limits and on the precise estimation of its parameters. In this manuscript, a framework for identifying the model domain of validity for the simplifying model hypotheses is presented. A model-based data mining method for parameter estimation is proposed as central block to classify the observed experimental conditions as compatible or incompatible with the approximated model. A nonlinear support vector classifier is then trained on the classified (observed) experimental conditions to identify a decision function for quantifying the expected model reliability in unexplored regions of the experimental design space. The proposed approach is employed for determining the domain of reliability for a simplified kinetic model of methanol oxidation on silver catalyst

Online model-based redesign of experiments for improving parameter precision in continuous flow reactors

Online model-based redesign of experiments (OMBRE) techniques reduce the experimental effort substantially for achieving high model reliability along with the precise estimation of model parameters. In dynamic systems, OMBRE techniques allow redesigning an experiment while it is still running and information gathered from samples collected at multiple time points is used to update the experimental conditions before the completion of the experiment. For processes evolving through a sequence of steady state experiments, significant time delays may exist when collecting new information from each single run, because measurements can be available only after steady state conditions are reached. In this work an online model-based optimal redesign technique is employed in continuous flow reactors for improving the accuracy of estimation of kinetic parameters with great benefit in terms of time and analytical resources during the model identification task. The proposed approach is applied to a simulated case study and compared with the conventional sequential model-based design of experiments (MBDoE) techniques as well as the offline optimal redesign of experiments

Sempervirine inhibits RNA polymerase I transcription independently from p53 in tumor cells

In the search of small molecules that can target MDM2/p53 pathway in testicular germ cell tumors (TGCTs), we identified sempervirine (2,3,4,13-tetrahydro-1H-benz[g]indolo[2,3-a]quinolizin-6-ium), an alkaloid of Gelsemium sempervirens, that has been previously proposed as an inhibitor of MDM2 that targets p53-wildtype (wt) tumor cells. We found that sempervirine not only affects cell growth of p53-wt cancer cells, but it is also active in p53-mutated and p53-null cells by triggering p53-dependent and independent pathways without affecting non-transformed cells. To understand which mechanism/s could be activated both in p53-wt and -null cells, we found that sempervirine induced nucleolar remodeling and nucleolar stress by reducing protein stability of RPA194, the catalytic subunit of RNA polymerase I, that led to rRNA synthesis inhibition and to MDM2 block. As shown for other cancer cell models, MDM2 inhibition by nucleolar stress downregulated E2F1 protein levels both in p53-wt and p53-null TGCT cells with the concomitant upregulation of unphosphorylated pRb. Finally, we show that sempervirine is able to enter the nucleus and accumulates within the nucleolus where it binds rRNA without causing DNA damage. Our results identify semperivirine as a novel rRNA synthesis inhibitor and indicate this drug as a non-genotoxic anticancer small molecule

A smo/gli multitarget hedgehog pathway inhibitor impairs tumor growth

Pharmacological Hedgehog (Hh) pathway inhibition has emerged as a valuable anticancer strategy. A number of small molecules able to block the pathway at the upstream receptor Smoothened (Smo) or the downstream effector glioma-associated oncogene 1 (Gli1) has been designed and developed. In a recent study, we exploited the high versatility of the natural isoflavone scaffold for targeting the Hh signaling pathway at multiple levels showing that the simultaneous targeting of Smo and Gli1 provided synergistic Hh pathway inhibition stronger than single administration. This approach seems to effectively overcome the drug resistance, particularly at the level of Smo. Here, we combined the pharmacophores targeting Smo and Gli1 into a single and individual isoflavone, compound 22, which inhibits the Hh pathway at both upstream and downstream level. We demonstrate that this multitarget agent suppresses medulloblastoma growth in vitro and in vivo through antagonism of Smo and Gli1, which is a novel mechanism of action in Hh inhibition