BioDMET: a physiologically based pharmacokinetic simulation tool for assessing proposed solutions to complex biological problems

We developed a detailed, whole-body physiologically based pharmacokinetic (PBPK) modeling tool for calculating the distribution of pharmaceutical agents in the various tissues and organs of a human or animal as a function of time. Ordinary differential equations (ODEs) represent the circulation of body fluids through organs and tissues at the macroscopic level, and the biological transport mechanisms and biotransformations within cells and their organelles at the molecular scale. Each major organ in the body is modeled as composed of one or more tissues. Tissues are made up of cells and fluid spaces. The model accounts for the circulation of arterial and venous blood as well as lymph. Since its development was fueled by the need to accurately predict the pharmacokinetic properties of imaging agents, BioDMET is more complex than most PBPK models. The anatomical details of the model are important for the imaging simulation endpoints. Model complexity has also been crucial for quickly adapting the tool to different problems without the need to generate a new model for every problem. When simpler models are preferred, the non-critical compartments can be dynamically collapsed to reduce unnecessary complexity. BioDMET has been used for imaging feasibility calculations in oncology, neurology, cardiology, and diabetes. For this purpose, the time concentration data generated by the model is inputted into a physics-based image simulator to establish imageability criteria. These are then used to define agent and physiology property ranges required for successful imaging. BioDMET has lately been adapted to aid the development of antimicrobial therapeutics. Given a range of built-in features and its inherent flexibility to customization, the model can be used to study a variety of pharmacokinetic and pharmacodynamic problems such as the effects of inter-individual differences and disease-states on drug pharmacokinetics and pharmacodynamics, dosing optimization, and inter-species scaling. While developing a tool to aid imaging agent and drug development, we aimed at accelerating the acceptance and broad use of PBPK modeling by providing a free mechanistic PBPK software that is user friendly, easy to adapt to a wide range of problems even by non-programmers, provided with ready-to-use parameterized models and benchmarking data collected from the peer-reviewed literature

A Linear Framework for Time-Scale Separation in Nonlinear Biochemical Systems

Cellular physiology is implemented by formidably complex biochemical systems with highly nonlinear dynamics, presenting a challenge for both experiment and theory. Time-scale separation has been one of the few theoretical methods for distilling general principles from such complexity. It has provided essential insights in areas such as enzyme kinetics, allosteric enzymes, G-protein coupled receptors, ion channels, gene regulation and post-translational modification. In each case, internal molecular complexity has been eliminated, leading to rational algebraic expressions among the remaining components. This has yielded familiar formulas such as those of Michaelis-Menten in enzyme kinetics, Monod-Wyman-Changeux in allostery and Ackers-Johnson-Shea in gene regulation. Here we show that these calculations are all instances of a single graph-theoretic framework. Despite the biochemical nonlinearity to which it is applied, this framework is entirely linear, yet requires no approximation. We show that elimination of internal complexity is feasible when the relevant graph is strongly connected. The framework provides a new methodology with the potential to subdue combinatorial explosion at the molecular level

Multi-angle TOF MR brain angiography of the common marmoset

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Lifespan cerebral grey matter changes in the marmoset monkey

International audienceLifespan cerebral grey matter changes in the marmoset monkeyF. Rémy, N. Vayssière, F. Bazzi, D. Mateo, A. Sadoun, P. Girard, M. Mescam, C. FontaIn the research field of nervous system aging, the common marmoset monkey Callithrix Jacchus may reveal a model of great interest. With its short lifespan (10 years on average), a life-long assessment of cerebral changes in an individual is made feasible in laboratory settings. Moreover, similar to humans, cognitive deficits spontaneously occur at old age and are highly variable between individuals (Sadoun et al 2019, Neurobiology of Aging 74:1-14). Here, we aimed at characterizing marmoset brain structural aging in a cross-sectional MRI study performed on 48 individuals of all ages (6 months to 14 years old, with 21 individuals above 8 years). High-resolution (0.35 × 0.35 × 0.35 mm3) T1-weighted anatomical scans were acquired on a 3T MRI system using a human wrist coil. Scans were processed in SPM12 using the voxel-based morphometry (VBM) pipeline. All images were co-registered to a home-made T1 template (average of 12 individual scans). The image segmentation used Tissue Probability Maps (TPMs) of grey matter (GM), white matter (WM), cerebrospinal fluid (CSF) and head/background, which were derived from the creation of a study-specific template using the SPM12 DARTEL procedure. GM images were then spatially normalized to the DARTEL template and smoothed. VBM of grey matter evidenced linear age-related decreases mainly in the prefrontal cortex, anterior cingulate region and hippocampus, in both hemispheres (figure). This is in line with age-related cortical changes observed in humans. Further analyses, using cortical regions-of-interest derived from the marmoset digital atlas developed in our group (Risser et al 2019, Brain Struct Funct 224(5):1957-1969) are currently underway and could be linked to behavioral performances of these animals in various tasks

665P Role of prior nephrectomy for synchronous metastatic renal cell carcinoma (mRCC) on efficacy in patients treated with avelumab + axitinib (A + Ax) or sunitinib (S): Results from JAVELIN Renal 101

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The scientist abroad: maximising research impact and effectiveness when working as a visiting scientist

Conservation science is crucial to global conservation efforts, and often involves projects where foreign scientists visit a host country to conduct research. Science can significantly contribute to conservation efforts in host countries. However, poorly conceived and implemented projects can lead to poor conservation outcomes, cause negative impacts on communities, and compromise future research. This paper presents guidance from scientists, managers, and conservation practitioners following the 10th Indo-Pacific Fish Conference, the region's largest ichthyology meeting where delegates presented many examples of collaborative research. The guidance provided focuses on issues regarding planning and preparation, collaboration and reciprocity, and conduct and protocol. The intent is to provide conservation scientists with practical advice from locally based and experienced conservation scientists and practitioners about how to maximise research effectiveness and conservation benefits when working abroad. A range of activities and approaches are suggested that visiting scientists can adopt and implement to build the relationships and trust needed for effective collaboration with local actors. Building effective collaborations between local actors and visiting scientists can maximise research effectiveness and impact by ensuring that projects address the most important issues and conservation concerns, involve the appropriate people, use suitable methods and approaches, and carefully consider local contexts and ethics. Such projects are more likely to provide lasting benefits to both parties, and enhance conservation outcomes. However, both visiting scientists and local actors need to communicate clearly, be accommodating, and commit to a genuine partnership to realise these benefits

Immunologic constant of rejection signature is prognostic in soft-tissue sarcoma and refines the CINSARC signature

Background Soft-tissue sarcomas (STSs) are heterogeneous and aggressive tumors, with high metastatic risk. The immunologic constant of rejection (ICR) 20-gene signature is a signature of cytotoxic immune response. We hypothesized that ICR might improve the prognostic assessment of early-stage STS. Methods We retrospectively applied ICR to 1455 non-metastatic STS and searched for correlations between ICR classes and clinicopathological and biological variables, including metastasis-free survival (MFS). Results Thirty-four per cent of tumors were classified as ICR1, 27% ICR2, 24% ICR3, and 15% ICR4. These classes were associated with patients' age, pathological type, and tumor depth, and an enrichment from ICR1 to ICR4 of quantitative/qualitative scores of immune response. ICR1 class was associated with a 59% increased risk of metastatic relapse when compared with ICR2-4 class. In multivariate analysis, ICR classification remained associated with MFS, as well as pathological type and Complexity Index in Sarcomas (CINSARC) classification, suggesting independent prognostic value. A prognostic clinicogenomic model, including the three variables, was built in a learning set (n=339) and validated in an independent set (n=339), showing greater prognostic precision than each variable alone or in doublet. Finally, connectivity mapping analysis identified drug classes potentially able to reverse the expression profile of poor-prognosis tumors, such as chemotherapy and targeted therapies. Conclusion ICR signature is independently associated with postoperative MFS in early-stage STS, independently from other prognostic features, including CINSARC. We built a robust prognostic clinicogenomic model integrating ICR, CINSARC, and pathological type, and suggested differential vulnerability of each prognostic group to different systemic therapies