Statistical models for experimental model membranes.

Biological membranes are constituted from lipid bilayers and proteins. Investigation of protein-membrane interaction, essential for biological function of cells, must rest upon solid knowledge of lipid bilayer behavior. Thus, extensive studies of an experimental model for membranes, lipid bilayers in water solution, have been undertaken in the last decades. These systems present structural, thermal and electrical properties which depend on temperature, ionic strength or concentration. In this talk, we shall discuss statistical models for lipid bilayers, as well as the relation between their properties and results for properties of lipid dispersions investigated by the laboratories supervised by Teresa Lamy (IF-USP) and Amando Ito (FFCL-USP).

QSAR models for inhibitors of physiological impact of Escherichia coli that leads to diarrhea

Quantitative structure – activity relationships (QSARs) developed to evaluate percentage of inhibition of STa-stimulated (Escherichia coli) cGMP accumulation in T84 cells are calculated by the Monte Carlo method. This endpoint represents a measure of biological activity of a substance against diarrhea. Statistical quality of the developed models is quite good. The approach is tested using three random splits of data into the training and test sets. The statistical characteristics for three splits are the following: (1) n = 20, r2 = 0.7208, q2 = 0.6583, s = 16.9, F = 46 (training set); n = 11, r2 = 0.8986, s = 14.6 (test set); (2) n = 19, r2 = 0.6689, q2 = 0.5683, s = 17.6, F = 34 (training set); n = 12, r2 = 0.8998, s = 12.1 (test set); and (3) n = 20, r2 = 0.7141, q2 = 0.6525, s = 14.7, F = 45 (training set); n = 11, r2 = 0.8858, s = 19.5 (test set). Based on the proposed here models hypothetical compounds which can be useful agents against diarrhea are suggested.

Study of the thermal effects induced by magnetic resonance on endocardial leads: numerical models and experimental validation

Magnetic resonance imaging (MRI) is today precluded to patients bearing active implantable medical devices AIMDs). The great advantages related to this diagnostic modality, together with the increasing number of people benefiting from implantable devices, in particular pacemakers(PM)and carioverter/defibrillators (ICD), is prompting the scientific community the study the possibility to extend MRI also to implanted patients. The MRI induced specific absorption rate (SAR) and the consequent heating of biological tissues is one of the major concerns that makes patients bearing metallic structures contraindicated for MRI scans. To date, both in-vivo and in-vitro studies have demonstrated the potentially dangerous temperature increase caused by the radiofrequency (RF) field generated during MRI procedures in the tissues surrounding thin metallic implants. On the other side, the technical evolution of MRI scanners and of AIMDs together with published data on the lack of adverse events have reopened the interest in this field and suggest that, under given conditions, MRI can be safely performed also in implanted patients. With a better understanding of the hazards of performing MRI scans on implanted patients as well as the development of MRI safe devices, we may soon enter an era where the ability of this imaging modality may be more widely used to assist in the appropriate diagnosis of patients with devices. In this study both experimental measures and numerical analysis were performed. Aim of the study is to systematically investigate the effects of the MRI RF filed on implantable devices and to identify the elements that play a major role in the induced heating. Furthermore, we aimed at developing a realistic numerical model able to simulate the interactions between an RF coil for MRI and biological tissues implanted with a PM, and to predict the induced SAR as a function of the particular path of the PM lead. The methods developed and validated during the PhD program led to the design of an experimental framework for the accurate measure of PM lead heating induced by MRI systems. In addition, numerical models based on Finite-Differences Time-Domain (FDTD) simulations were validated to obtain a general tool for investigating the large number of parameters and factors involved in this complex phenomenon. The results obtained demonstrated that the MRI induced heating on metallic implants is a real risk that represents a contraindication in extending MRI scans also to patient bearing a PM, an ICD, or other thin metallic objects. On the other side, both experimental data and numerical results show that, under particular conditions, MRI procedures might be consider reasonably safe also for an implanted patient. The complexity and the large number of variables involved, make difficult to define a unique set of such conditions: when the benefits of a MRI investigation cannot be obtained using other imaging techniques, the possibility to perform the scan should not be immediately excluded, but some considerations are always needed.

Stochastic models and dynamic measures for the characterization of bistable circuits

During the last few years, a great deal of interest has risen concerning the applications of stochastic methods to several biochemical and biological phenomena. Phenomena like gene expression, cellular memory, bet-hedging strategy in bacterial growth and many others, cannot be described by continuous stochastic models due to their intrinsic discreteness and randomness. In this thesis I have used the Chemical Master Equation (CME) technique to modelize some feedback cycles and analyzing their properties, including experimental data. In the first part of this work, the effect of stochastic stability is discussed on a toy model of the genetic switch that triggers the cellular division, which malfunctioning is known to be one of the hallmarks of cancer. The second system I have worked on is the so-called futile cycle, a closed cycle of two enzymatic reactions that adds and removes a chemical compound, called phosphate group, to a specific substrate. I have thus investigated how adding noise to the enzyme (that is usually in the order of few hundred molecules) modifies the probability of observing a specific number of phosphorylated substrate molecules, and confirmed theoretical predictions with numerical simulations. In the third part the results of the study of a chain of multiple phosphorylation-dephosphorylation cycles will be presented. We will discuss an approximation method for the exact solution in the bidimensional case and the relationship that this method has with the thermodynamic properties of the system, which is an open system far from equilibrium.In the last section the agreement between the theoretical prediction of the total protein quantity in a mouse cells population and the observed quantity will be shown, measured via fluorescence microscopy.

Computational modelling of human stem cell-derived cardiomyocytes - Texture descriptors for biological image processing

This thesis investigates two distinct research topics. The main topic (Part I) is the computational modelling of cardiomyocytes derived from human stem cells, both embryonic (hESC-CM) and induced-pluripotent (hiPSC-CM). The aim of this research line lies in developing models of the electrophysiology of hESC-CM and hiPSC-CM in order to integrate the available experimental data and getting in-silico models to be used for studying/making new hypotheses/planning experiments on aspects not fully understood yet, such as the maturation process, the functionality of the Ca2+ hangling or why the hESC-CM/hiPSC-CM action potentials (APs) show some differences with respect to APs from adult cardiomyocytes. Chapter I.1 introduces the main concepts about hESC-CMs/hiPSC-CMs, the cardiac AP, and computational modelling. Chapter I.2 presents the hESC-CM AP model, able to simulate the maturation process through two developmental stages, Early and Late, based on experimental and literature data. Chapter I.3 describes the hiPSC-CM AP model, able to simulate the ventricular-like and atrial-like phenotypes. This model was used to assess which currents are responsible for the differences between the ventricular-like AP and the adult ventricular AP. The secondary topic (Part II) consists in the study of texture descriptors for biological image processing. Chapter II.1 provides an overview on important texture descriptors such as Local Binary Pattern or Local Phase Quantization. Moreover the non-binary coding and the multi-threshold approach are here introduced. Chapter II.2 shows that the non-binary coding and the multi-threshold approach improve the classification performance of cellular/sub-cellular part images, taken from six datasets. Chapter II.3 describes the case study of the classification of indirect immunofluorescence images of HEp2 cells, used for the antinuclear antibody clinical test. Finally the general conclusions are reported.

Nature and relevance of inherited blueprints on business models choices and innovation: an assessment

One important metaphor, referred to biological theories, used to investigate on organizational and business strategy issues is the metaphor about heredity; an area requiring further investigation is the extent to which the characteristics of blueprints inherited from the parent, helps in explaining subsequent development of the spawned ventures. In order to shed a light on the tension between inherited patterns and the new trajectory that may characterize spawned ventures’ development we propose a model aimed at investigating which blueprints elements might exert an effect on business model design choices and to which extent their persistence (or abandonment) determines subsequent business model innovation. Under the assumption that academic and corporate institutions transmit different genes to their spin-offs, we hence expect to have heterogeneity in elements that affect business model design choices and its subsequent evolution. This is the reason why we carry on a twofold analysis in the biotech (meta)industry: under a multiple-case research design, business model and especially its fundamental design elements and themes scholars individuated to decompose the construct, have been thoroughly analysed. Our purpose is to isolate the dimensions of business model that may have been the object of legacy and the ones along which an experimentation and learning process is more likely to happen, bearing in mind that differences between academic and corporate might not be that evident as expected, especially considering that business model innovation may occur.

Influence of Electromagnetic Fields On Biological Signalling: An Experimental and Theoretical Approach

The primary goals of this study were to develop a cell-free in vitro assay for the assessment of nonthermal electromagnetic (EMF) bioeffects and to develop theoretical models in accord with current experimental observations. Based upon the hypothesis that EMF effects operate by modulating Ca2+/CaM binding, an in vitro nitric oxide (NO) synthesis assay was developed to assess the effects of a pulsed radiofrequency (PRF) signal used for treatment of postoperative pain and edema. No effects of PRF on NO synthesis were observed. Effects of PRF on Ca2+/CaM binding were also assessed using a Ca2+-selective electrode, also yielding no EMF Ca2+/CaM binding. However, a PRF effect was observed on the interaction of hemoglobin (Hb) with tetrahydrobiopterin, leading to the development of an in vitro Hb deoxygenation assay, showing a reduction in the rate of Hb deoxygenation for exposures to both PRF and a static magnetic field (SMF). Structural studies using pyranine fluorescence, Gd3+ vibronic sideband luminescence and attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy were conducted in order to ascertain the mechanism of this EMF effect on Hb. Also, the effect of SMF on Hb oxygen saturation (SO2) was assessed under gas-controlled conditions. These studies showed no definitive changes in protein/solvation structure or SO2 under equilibrium conditions, suggesting the need for real-time instrumentation or other means of observing out-of-equilibrium Hb dynamics. Theoretical models were developed for EMF transduction, effects on ion binding, neuronal spike timing, and dynamics of Hb deoxygenation. The EMF sensitivity and simplicity of the Hb deoxygenation assay suggest a new tool to further establish basic biophysical EMF transduction mechanisms. If an EMF-induced increase in the rate of deoxygenation can be demonstrated in vivo, then enhancement of oxygen delivery may be a new therapeutic method by which clinically relevant EMF-mediated enhancement of growth and repair processes can occur.

Master Equation: Biological Applications and Thermodynamic Description

It is well known that many realistic mathematical models of biological systems, such as cell growth, cellular development and differentiation, gene expression, gene regulatory networks, enzyme cascades, synaptic plasticity, aging and population growth need to include stochasticity. These systems are not isolated, but rather subject to intrinsic and extrinsic fluctuations, which leads to a quasi equilibrium state (homeostasis). The natural framework is provided by Markov processes and the Master equation (ME) describes the temporal evolution of the probability of each state, specified by the number of units of each species. The ME is a relevant tool for modeling realistic biological systems and allow also to explore the behavior of open systems. These systems may exhibit not only the classical thermodynamic equilibrium states but also the nonequilibrium steady states (NESS). This thesis deals with biological problems that can be treat with the Master equation and also with its thermodynamic consequences. It is organized into six chapters with four new scientific works, which are grouped in two parts: (1) Biological applications of the Master equation: deals with the stochastic properties of a toggle switch, involving a protein compound and a miRNA cluster, known to control the eukaryotic cell cycle and possibly involved in oncogenesis and with the propose of a one parameter family of master equations for the evolution of a population having the logistic equation as mean field limit. (2) Nonequilibrium thermodynamics in terms of the Master equation: where we study the dynamical role of chemical fluxes that characterize the NESS of a chemical network and we propose a one parameter parametrization of BCM learning, that was originally proposed to describe plasticity processes, to study the differences between systems in DB and NESS.

Boron determination in biological samples - Intercomparison of three analytical methods to assist development of a treatment protocol for neoplastic diseases of the liver with Boron Neutron Capture Therapy

Die Bor-Neuroneneinfang-Therapie (engl.: Boron Neutron Capture Therapy, BNCT) ist eine indirekte Strahlentherapie, welche durch die gezielte Freisetzung von dicht ionisierender Strahlung Tumorzellen zerstört. Die freigesetzten Ionen sind Spaltfragmente einer Kernreaktion, bei welcher das Isotop 10B ein niederenergetisches (thermisches) Neutron einfängt. Das 10B wird durch ein spezielles Borpräparat in den Tumorzellen angereichert, welches selbst nicht radioaktiv ist. rnAn der Johannes Gutenberg-Universität Mainz wurde die Forschung für die Anwendung eines klinischen Behandlungsprotokolls durch zwei Heilversuche bei Patienten mit kolorektalen Lebermetastasen an der Universität Pavia, Italien, angeregt, bei denen die Leber außerhalb des Körpers in einem Forschungsreaktor bestrahlt wurde. Als erster Schritt wurde in Kooperation verschiedener universitärer Institute eine klinische Studie zur Bestimmung klinisch relevanter Parameter wie der Borverteilung in verschiedenen Geweben und dem pharmakokinetischen Aufnahmeverhalten des Borpräparates initiiert.rnDie Borkonzentration in den Gewebeproben wurde hinsichtlich ihrer räumlichen Verteilung in verschiedenen Zellarealen bestimmt, um mehr über das Aufnahmeverhalten der Zellen für das BPA im Hinblick auf ihre biologischen Charakteristika zu erfahren. Die Borbestimung wurde per Quantitative Neutron Capture Radiography, Prompt Gamma Activation Analysis und Inductively Coupled Plasma Mass Spectroscopy parallel zur histologischen Analyse des Gewebes durchgeführt. Es war möglich zu zeigen, dass in Proben aus Tumorgewebe und aus tumorfreiem Gewebe mit unterschiedlichen morphologischen Eigenschaften eine sehr heterogene Borverteilung vorliegt. Die Ergebnisse der Blutproben werden für die Erstellung eines pharmakokinetischen Modells verwendet und sind in Übereinstimmung mit existierenden pharmakokinetische Modellen. Zusätzlich wurden die Methoden zur Borbestimmung über speziell hergestellte Referenzstandards untereinander verglichen. Dabei wurde eine gute Übereinstimmung der Ergebnisse festgestellt, ferner wurde für alle biologischen Proben Standardanalyseprotokolle erstellt.rnDie bisher erhaltenen Ergebnisse der klinischen Studie sind vielversprechend, lassen aber noch keine endgültigen Schlussfolgerungen hinsichtlich der Wirksamkeit von BNCT für maligne Lebererkrankungen zu. rn

Semi-synthetic bile acids as novel drug candidate in liver diseases: physico-chemical characterization and HPLC-ES-MS/MS methods for their quali-quantitative analysis in different experimental animal models

The physico-chemical characterization, structure-pharmacokinetic and metabolism studies of new semi synthetic analogues of natural bile acids (BAs) drug candidates have been performed. Recent studies discovered a role of BAs as agonists of FXR and TGR5 receptor, thus opening new therapeutic target for the treatment of liver diseases or metabolic disorders. Up to twenty new semisynthetic analogues have been synthesized and studied in order to find promising novel drugs candidates. In order to define the BAs structure-activity relationship, their main physico-chemical properties (solubility, detergency, lipophilicity and affinity with serum albumin) have been measured with validated analytical methodologies. Their metabolism and biodistribution has been studied in “bile fistula rat”, model where each BA is acutely administered through duodenal and femoral infusion and bile collected at different time interval allowing to define the relationship between structure and intestinal absorption and hepatic uptake ,metabolism and systemic spill-over. One of the studied analogues, 6α-ethyl-3α7α-dihydroxy-5β-cholanic acid, analogue of CDCA (INT 747, Obeticholic Acid (OCA)), recently under approval for the treatment of cholestatic liver diseases, requires additional studies to ensure its safety and lack of toxicity when administered to patients with a strong liver impairment. For this purpose, CCl4 inhalation to rat causing hepatic decompensation (cirrhosis) animal model has been developed and used to define the difference of OCA biodistribution in respect to control animals trying to define whether peripheral tissues might be also exposed as a result of toxic plasma levels of OCA, evaluating also the endogenous BAs biodistribution. An accurate and sensitive HPLC-ES-MS/MS method is developed to identify and quantify all BAs in biological matrices (bile, plasma, urine, liver, kidney, intestinal content and tissue) for which a sample pretreatment have been optimized.

Visualization and validation of (Q)SAR models

Analyzing and modeling relationships between the structure of chemical compounds, their physico-chemical properties, and biological or toxic effects in chemical datasets is a challenging task for scientific researchers in the field of cheminformatics. Therefore, (Q)SAR model validation is essential to ensure future model predictivity on unseen compounds. Proper validation is also one of the requirements of regulatory authorities in order to approve its use in real-world scenarios as an alternative testing method. However, at the same time, the question of how to validate a (Q)SAR model is still under discussion. In this work, we empirically compare a k-fold cross-validation with external test set validation. The introduced workflow allows to apply the built and validated models to large amounts of unseen data, and to compare the performance of the different validation approaches. Our experimental results indicate that cross-validation produces (Q)SAR models with higher predictivity than external test set validation and reduces the variance of the results. Statistical validation is important to evaluate the performance of (Q)SAR models, but does not support the user in better understanding the properties of the model or the underlying correlations. We present the 3D molecular viewer CheS-Mapper (Chemical Space Mapper) that arranges compounds in 3D space, such that their spatial proximity reflects their similarity. The user can indirectly determine similarity, by selecting which features to employ in the process. The tool can use and calculate different kinds of features, like structural fragments as well as quantitative chemical descriptors. Comprehensive functionalities including clustering, alignment of compounds according to their 3D structure, and feature highlighting aid the chemist to better understand patterns and regularities and relate the observations to established scientific knowledge. Even though visualization tools for analyzing (Q)SAR information in small molecule datasets exist, integrated visualization methods that allows for the investigation of model validation results are still lacking. We propose visual validation, as an approach for the graphical inspection of (Q)SAR model validation results. New functionalities in CheS-Mapper 2.0 facilitate the analysis of (Q)SAR information and allow the visual validation of (Q)SAR models. The tool enables the comparison of model predictions to the actual activity in feature space. Our approach reveals if the endpoint is modeled too specific or too generic and highlights common properties of misclassified compounds. Moreover, the researcher can use CheS-Mapper to inspect how the (Q)SAR model predicts activity cliffs. The CheS-Mapper software is freely available at http://ches-mapper.org.

Dielectric relaxation in biological materials

The study of dielectric properties concerns storage and dissipation of electric and magnetic energy in materials. Dielectrics are important in order to explain various phenomena in Solid-State Physics and in Physics of Biological Materials. Indeed, during the last two centuries, many scientists have tried to explain and model the dielectric relaxation. Starting from the Kohlrausch model and passing through the ideal Debye one, they arrived at more com- plex models that try to explain the experimentally observed distributions of relaxation times, including the classical (Cole-Cole, Davidson-Cole and Havriliak-Negami) and the more recent ones (Hilfer, Jonscher, Weron, etc.). The purpose of this thesis is to discuss a variety of models carrying out the analysis both in the frequency and in the time domain. Particular attention is devoted to the three classical models, that are studied using a transcendental function known as Mittag-Leffler function. We highlight that one of the most important properties of this function, its complete monotonicity, is an essential property for the physical acceptability and realizability of the models. Lo studio delle proprietà dielettriche riguarda l’immagazzinamento e la dissipazione di energia elettrica e magnetica nei materiali. I dielettrici sono importanti al fine di spiegare vari fenomeni nell’ambito della Fisica dello Stato Solido e della Fisica dei Materiali Biologici. Infatti, durante i due secoli passati, molti scienziati hanno tentato di spiegare e modellizzare il rilassamento dielettrico. A partire dal modello di Kohlrausch e passando attraverso quello ideale di Debye, sono giunti a modelli più complessi che tentano di spiegare la distribuzione osservata sperimentalmente di tempi di rilassamento, tra i quali modelli abbiamo quelli classici (Cole-Cole, Davidson-Cole e Havriliak-Negami) e quelli più recenti (Hilfer, Jonscher, Weron, etc.). L’obiettivo di questa tesi è discutere vari modelli, conducendo l’analisi sia nel dominio delle frequenze sia in quello dei tempi. Particolare attenzione è rivolta ai tre modelli classici, i quali sono studiati utilizzando una funzione trascendente nota come funzione di Mittag-Leffler. Evidenziamo come una delle più importanti proprietà di questa funzione, la sua completa monotonia, è una proprietà essenziale per l’accettabilità fisica e la realizzabilità dei modelli.

Metabolomics reveals attenuation of the SLC6A20 kidney transporter in nonhuman primate and mouse models of type 2 diabetes mellitus

To enhance understanding of the metabolic indicators of type 2 diabetes mellitus (T2DM) disease pathogenesis and progression, the urinary metabolomes of well characterized rhesus macaques (normal or spontaneously and naturally diabetic) were examined. High-resolution ultra-performance liquid chromatography coupled with the accurate mass determination of time-of-flight mass spectrometry was used to analyze spot urine samples from normal (n = 10) and T2DM (n = 11) male monkeys. The machine-learning algorithm random forests classified urine samples as either from normal or T2DM monkeys. The metabolites important for developing the classifier were further examined for their biological significance. Random forests models had a misclassification error of less than 5%. Metabolites were identified based on accurate masses (<10 ppm) and confirmed by tandem mass spectrometry of authentic compounds. Urinary compounds significantly increased (p < 0.05) in the T2DM when compared with the normal group included glycine betaine (9-fold), citric acid (2.8-fold), kynurenic acid (1.8-fold), glucose (68-fold), and pipecolic acid (6.5-fold). When compared with the conventional definition of T2DM, the metabolites were also useful in defining the T2DM condition, and the urinary elevations in glycine betaine and pipecolic acid (as well as proline) indicated defective re-absorption in the kidney proximal tubules by SLC6A20, a Na(+)-dependent transporter. The mRNA levels of SLC6A20 were significantly reduced in the kidneys of monkeys with T2DM. These observations were validated in the db/db mouse model of T2DM. This study provides convincing evidence of the power of metabolomics for identifying functional changes at many levels in the omics pipeline.

[(99m)Tc]Demomedin C, a radioligand based on human gastrin releasing peptide(18-27): synthesis and preclinical evaluation in gastrin releasing peptide receptor-expressing models

The synthesis and preclinical evaluation of [(99m)Tc]Demomedin C in GRPR-expressing models are reported. Demomedin C resulted by coupling a Boc-protected N(4)-chelator to neuromedin C (human GRP(18-27)), which, after (99m)Tc-labeling, afforded [(99m)Tc]Demomedin C. Demomedin C showed high affinity and selectivity for the GRPR during receptor autoradiography on human cancer samples (IC(50) in nM: GRPR, 1.4 ± 0.2; NMBR, 106 ± 18; and BB(3)R, >1000). It triggered GRPR internalization in HEK-GRPR cells and Ca(2+) release in PC-3 cells (EC(50) = 1.3 nM). [(99m)Tc]Demomedin C rapidly and specifically internalized at 37 °C in PC-3 cells and was stable in mouse plasma. [(99m)Tc]Demomedin C efficiently and specifically localized in human PC-3 implants in mice (9.84 ± 0.81%ID/g at 1 h pi; 6.36 ± 0.85%ID/g at 4 h pi, and 0.41 ± 0.07%ID/g at 4 h pi block). Thus, human GRP-based radioligands, such as [(99m)Tc]Demomedin C, can successfully target GRPR-expressing human tumors in vivo while displaying attractive biological features--e.g. higher GRPR-selectivity--vs their frog-homologues.

Mechanical Properties of Plant Underground Storage Organs and Implications for Dietary Models of Early Hominins

The diet of early human ancestors has received renewed theoretical interest since the discovery of elevated d13C values in the enamel of Australopithecus africanus and Paranthropus robustus. As a result, the hominin diet is hypothesized to have included C4 grass or the tissues of animals which themselves consumed C4 grass. On mechanical grounds, such a diet is incompatible with the dental morphology and dental microwear of early hominins. Most inferences, particularly for Paranthropus, favor a diet of hard or mechanically resistant foods. This discrepancy has invigorated the longstanding hypothesis that hominins consumed plant underground storage organs (USOs). Plant USOs are attractive candidate foods because many bulbous grasses and cormous sedges use C4 photosynthesis. Yet mechanical data for USOs—or any putative hominin food—are scarcely known. To fill this empirical void we measured the mechanical properties of USOs from 98 plant species from across sub-Saharan Africa. We found that rhizomes were the most resistant to deformation and fracture, followed by tubers, corms, and bulbs. An important result of this study is that corms exhibited low toughness values (mean = 265.0 J m-2) and relatively high Young’s modulus values (mean = 4.9 MPa). This combination of properties fits many descriptions of the hominin diet as consisting of hard-brittle objects. When compared to corms, bulbs are tougher (mean = 325.0 J m-2) and less stiff (mean = 2.5 MPa). Again, this combination of traits resembles dietary inferences, especially for Australopithecus, which is predicted to have consumed soft-tough foods. Lastly, we observed the roasting behavior of Hadza hunter-gatherers and measured the effects of roasting on the toughness on undomesticated tubers. Our results support assumptions that roasting lessens the work of mastication, and, by inference, the cost of digestion. Together these findings provide the first mechanical basis for discussing the adaptive advantages of roasting tubers and the plausibility of USOs in the diet of early hominins.