Spatial mapping of the collagen distribution in human and mouse tissues by force volume atomic force microscopy

Changes in the elastic properties of living tissues during normal development and in pathological processes are often due to modifications of the collagen component of the extracellular matrix at various length scales. Force volume AFM can precisely capture the mechanical properties of biological samples with force sensitivity and spatial resolution. The integration of AFM data with data of the molecular composition contributes to understanding the interplay between tissue biochemistry, organization and function. The detection of micrometer-size, heterogeneous domains at different elastic moduli in tissue sections by AFM has remained elusive so far, due to the lack of correlations with histological, optical and biochemical assessments. In this work, force volume AFM is used to identify collagen-enriched domains, naturally present in human and mouse tissues, by their elastic modulus. Collagen identification is obtained in a robust way and affordable timescales, through an optimal design of the sample preparation method and AFM parameters for faster scan with micrometer resolution. The choice of a separate reference sample stained for collagen allows correlating elastic modulus with collagen amount and position with high statistical significance. The proposed preparation method ensures safe handling of the tissue sections guarantees the preservation of their micromechanical characteristics over time and makes it much easier to perform correlation experiments with different biomarkers independently

TLR9 ligation in pancreatic stellate cells promotes tumorigenesis

Modulation of Toll-like receptor (TLR) signaling can have protective or protumorigenic effects on oncogenesis depending on the cancer subtype and on specific inflammatory elements within the tumor milieu. We found that TLR9 is widely expressed early during the course of pancreatic transformation and that TLR9 ligands are ubiquitous within the tumor microenvironment. TLR9 ligation markedly accelerates oncogenesis, whereas TLR9 deletion is protective. We show that TLR9 activation has distinct effects on the epithelial, inflammatory, and fibrogenic cellular subsets in pancreatic carcinoma and plays a central role in cross talk between these compartments. Specifically, TLR9 activation can induce proinflammatory signaling in transformed epithelial cells, but does not elicit oncogene expression or cancer cell proliferation. Conversely, TLR9 ligation induces pancreatic stellate cells (PSCs) to become fibrogenic and secrete chemokines that promote epithelial cell proliferation. TLR9-activated PSCs mediate their protumorigenic effects on the epithelial compartment via CCL11. Additionally, TLR9 has immune-suppressive effects in the tumor microenvironment (TME) via induction of regulatory T cell recruitment and myeloid-derived suppressor cell proliferation. Collectively, our work shows that TLR9 has protumorigenic effects in pancreatic carcinoma which are distinct from its influence in extrapancreatic malignancies and from the mechanistic effects of other TLRs on pancreatic oncogenesis

Disruption management in vehicle routing and scheduling

Traditionally, people in modern business environments have been focusing on planning: creating detailed and complete schemes for actions that will lead to gains of the highest value. There is no doubt that constructing a thorough plan before taking actions is extremely important and usually a prerequisite element of success. However, no matter how perfect or optimal a plan is, during the execution phase, several unanticipated events may disrupt the system and force the plan to deviate from its intended course, or even make it infeasible. How should we cope with disruptions in a timely manner? How can we reach the original goals and at the same time minimize the negative impact which was caused by the disruptions? These are amongst the essential topics examined by the field of Disruption Management. Disruption Management has been applied by researchers to optimization problems arising in a wide range of applications, including airline scheduling and production management. In our research we focus on disruption management in vehicle routing and scheduling for road freight distribution, after having recognized several gaps in research in this specific domain. In this thesis we present the following three problems: (1) the disrupted Vehicle Routing Problem with customer-specific orders and Vehicle Breakdown, (2) the Delayed Traveling Salesman Problem with Time Windows, and (3) the Single-Commodity Delayed Vehicle Routing Problem with Time Windows. The second and third problems have never been studied before, to the best of our knowledge. The first one has been studied before under different assumptions (i.e. with non customer-specific orders), which differentiates substantially the problem from the one proposed here. For each problem we present at least one exact mixed-integer linear programming formulation (single-objective or multi-objective), which can be implemented in an optimization solver (e.g. Cplex or AIMMS) and solve small instances to optimality. Due to the fact that the problems under study are computationally hard, for each problem we also propose at least one heuristic algorithm, which is capable of solving larger instances in short time. The heuristics described in this thesis are all based on Tabu Search. We present several variants of problems 2 and 3, which are solved using both single-objective and multi-objective optimization approaches: the Weighting Method, the Lexicographic Approach, and the Epsilon Constraint Method. For each one of the three problems under study, we have constructed a dataset of test instances, which we solved using different approaches. Comparisons of the results of the exact and heuristic methods are provided for each problem

Dynamics of hot random hyperbolic graphs

We derive the most basic dynamical properties of random hyperbolic graphs (the distributions of contact and intercontact durations) in the hot regime (network temperature $T > 1$). We show that for sufficiently large networks the contact distribution decays as a power law with exponent $2+T > 3$ for durations $t > T$, while for $t < T$ it exhibits exponential-like decays. This result holds irrespective of the expected degree distribution, as long as it has a finite $T^{\text{th}}$ moment. Otherwise, the contact distribution depends on the expected degree distribution and we show that if the latter is a power law with exponent $\gamma \in (2, T+1]$, then the former decays as a power law with exponent $\gamma+1 > 3$. On the other hand, the intercontact distribution exhibits power-law decays with exponent $2-T \in (0, 1)$ for $T \in (1,2)$, while for $T > 2$ it displays linear decays with a slope that depends on the observation interval. This result holds irrespective of the expected degree distribution as long as it has a finite $T^{\text{th}}$ moment if $T \in (1,2)$, or a finite second moment if $T > 2$. Otherwise, the intercontact distribution depends on the expected degree distribution and if the latter is a power law with exponent $\gamma \in (2, 3)$, then the former decays as a power law with exponent $3-\gamma \in (0,1)$. Thus, hot random hyperbolic graphs can give rise to contact and intercontact distributions that both decay as power laws. These power laws however are unrealistic for the case of the intercontact distribution, as their exponent is always less than one. These results mean that hot random hyperbolic graphs are not adequate for modeling real temporal networks, in stark contrast to cold random hyperbolic graphs ($T < 1$). Since the configuration model emerges at $T \to \infty$, these results also suggest that this is not an adequate null temporal network model

Dynamics of hot random hyperbolic graphs

We derive the most basic dynamical properties of random hyperbolic graphs (the distributions of contact and intercontact durations) in the hot regime (network temperature $T > 1$). We show that for sufficiently large networks the contact distribution decays as a power law with exponent $2+T > 3$ for durations $t > T$, while for $t < T$ it exhibits exponential-like decays. This result holds irrespective of the expected degree distribution, as long as it has a finite $T^{\text{th}}$ moment. Otherwise, the contact distribution depends on the expected degree distribution and we show that if the latter is a power law with exponent $\gamma \in (2, T+1]$, then the former decays as a power law with exponent $\gamma+1 > 3$. On the other hand, the intercontact distribution exhibits power-law decays with exponent $2-T \in (0, 1)$ for $T \in (1,2)$, while for $T > 2$ it displays linear decays with a slope that depends on the observation interval. This result holds irrespective of the expected degree distribution as long as it has a finite $T^{\text{th}}$ moment if $T \in (1,2)$, or a finite second moment if $T > 2$. Otherwise, the intercontact distribution depends on the expected degree distribution and if the latter is a power law with exponent $\gamma \in (2, 3)$, then the former decays as a power law with exponent $3-\gamma \in (0,1)$. Thus, hot random hyperbolic graphs can give rise to contact and intercontact distributions that both decay as power laws. These power laws however are unrealistic for the case of the intercontact distribution, as their exponent is always less than one. These results mean that hot random hyperbolic graphs are not adequate for modeling real temporal networks, in stark contrast to cold random hyperbolic graphs ($T < 1$). Since the configuration model emerges at $T \to \infty$, these results also suggest that this is not an adequate null temporal network model

Disruption management in vehicle routing and scheduling for road freight transport:a review

Disruption management is an approach to the rescheduling of operations following an unanticipated event occurring that has been applied in a wide range of applications, including airline scheduling and project management. This review focusses on the use of disruption management in vehicle routing and scheduling applied to road freight distribution. The paper discusses the key features of disruption management and examines the relevant objectives and types of disruption that may occur in this context. Different formulations and solution methods are described. A set of relevant papers are summarised and classified according to the type of disruption addressed, the relevant objectives and the solution approach